From f35963c020f2a672c8d7ac062886b065fe354945 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Albert=20Gil=20L=C3=B3pez?= <albert@albertgilopez.es>
Date: Tue, 19 Aug 2025 06:41:52 +0000
Subject: [PATCH 001/141] feat: Add clear error messages for uninitialized
 storage

- Add StorageNotInitializedError and PipelineNotInitializedError exceptions
- Update JsonDocStatusStorage to raise clear errors when not initialized
- Update JsonKVStorage to raise clear errors when not initialized
- Error messages now include complete initialization instructions
- Helps users understand and fix initialization issues quickly

Addresses feedback from issue #1933 about improving error clarity
---
 lightrag/exceptions.py              | 38 +++++++++++++++++++++++++++++
 lightrag/kg/json_doc_status_impl.py |  9 +++++++
 lightrag/kg/json_kv_impl.py         |  3 +++
 3 files changed, 50 insertions(+)

diff --git a/lightrag/exceptions.py b/lightrag/exceptions.py
index ae756f85..190d0c18 100644
--- a/lightrag/exceptions.py
+++ b/lightrag/exceptions.py
@@ -58,3 +58,41 @@ class RateLimitError(APIStatusError):
 class APITimeoutError(APIConnectionError):
     def __init__(self, request: httpx.Request) -> None:
         super().__init__(message="Request timed out.", request=request)
+
+
+class StorageNotInitializedError(RuntimeError):
+    """Raised when storage operations are attempted before initialization."""
+    
+    def __init__(self, storage_type: str = "Storage"):
+        super().__init__(
+            f"{storage_type} not initialized. Please ensure proper initialization:\n"
+            f"\n"
+            f"  rag = LightRAG(...)\n"
+            f"  await rag.initialize_storages()  # Required\n"
+            f"  \n"
+            f"  from lightrag.kg.shared_storage import initialize_pipeline_status\n"
+            f"  await initialize_pipeline_status()  # Required for pipeline operations\n"
+            f"\n"
+            f"See: https://github.com/HKUDS/LightRAG#important-initialization-requirements"
+        )
+
+
+class PipelineNotInitializedError(KeyError):
+    """Raised when pipeline status is accessed before initialization."""
+    
+    def __init__(self, namespace: str = ""):
+        msg = (
+            f"Pipeline namespace '{namespace}' not found. "
+            f"This usually means pipeline status was not initialized.\n"
+            f"\n"
+            f"Please call 'await initialize_pipeline_status()' after initializing storages:\n"
+            f"\n"
+            f"  from lightrag.kg.shared_storage import initialize_pipeline_status\n"
+            f"  await initialize_pipeline_status()\n"
+            f"\n"
+            f"Full initialization sequence:\n"
+            f"  rag = LightRAG(...)\n"
+            f"  await rag.initialize_storages()\n"
+            f"  await initialize_pipeline_status()"
+        )
+        super().__init__(msg)
diff --git a/lightrag/kg/json_doc_status_impl.py b/lightrag/kg/json_doc_status_impl.py
index 09af3ef1..5ba9d9d3 100644
--- a/lightrag/kg/json_doc_status_impl.py
+++ b/lightrag/kg/json_doc_status_impl.py
@@ -12,6 +12,7 @@ from lightrag.utils import (
     logger,
     write_json,
 )
+from lightrag.exceptions import StorageNotInitializedError
 from .shared_storage import (
     get_namespace_data,
     get_storage_lock,
@@ -65,11 +66,15 @@ class JsonDocStatusStorage(DocStatusStorage):
 
     async def filter_keys(self, keys: set[str]) -> set[str]:
         """Return keys that should be processed (not in storage or not successfully processed)"""
+        if self._storage_lock is None:
+            raise StorageNotInitializedError("JsonDocStatusStorage")
         async with self._storage_lock:
             return set(keys) - set(self._data.keys())
 
     async def get_by_ids(self, ids: list[str]) -> list[dict[str, Any]]:
         result: list[dict[str, Any]] = []
+        if self._storage_lock is None:
+            raise StorageNotInitializedError("JsonDocStatusStorage")
         async with self._storage_lock:
             for id in ids:
                 data = self._data.get(id, None)
@@ -80,6 +85,8 @@ class JsonDocStatusStorage(DocStatusStorage):
     async def get_status_counts(self) -> dict[str, int]:
         """Get counts of documents in each status"""
         counts = {status.value: 0 for status in DocStatus}
+        if self._storage_lock is None:
+            raise StorageNotInitializedError("JsonDocStatusStorage")
         async with self._storage_lock:
             for doc in self._data.values():
                 counts[doc["status"]] += 1
@@ -160,6 +167,8 @@ class JsonDocStatusStorage(DocStatusStorage):
         if not data:
             return
         logger.debug(f"Inserting {len(data)} records to {self.final_namespace}")
+        if self._storage_lock is None:
+            raise StorageNotInitializedError("JsonDocStatusStorage")
         async with self._storage_lock:
             # Ensure chunks_list field exists for new documents
             for doc_id, doc_data in data.items():
diff --git a/lightrag/kg/json_kv_impl.py b/lightrag/kg/json_kv_impl.py
index d6d80079..9bb8b3f2 100644
--- a/lightrag/kg/json_kv_impl.py
+++ b/lightrag/kg/json_kv_impl.py
@@ -10,6 +10,7 @@ from lightrag.utils import (
     logger,
     write_json,
 )
+from lightrag.exceptions import StorageNotInitializedError
 from .shared_storage import (
     get_namespace_data,
     get_storage_lock,
@@ -152,6 +153,8 @@ class JsonKVStorage(BaseKVStorage):
         current_time = int(time.time())  # Get current Unix timestamp
 
         logger.debug(f"Inserting {len(data)} records to {self.final_namespace}")
+        if self._storage_lock is None:
+            raise StorageNotInitializedError("JsonKVStorage")
         async with self._storage_lock:
             # Add timestamps to data based on whether key exists
             for k, v in data.items():

From e3ae87b0cbccf04c79ce3bdbd98c8d9fb0ae6e2a Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Albert=20Gil=20L=C3=B3pez?= <albert@albertgilopez.es>
Date: Tue, 19 Aug 2025 06:44:33 +0000
Subject: [PATCH 002/141] feat: Add diagnostic tool to check initialization
 status

- Add check_initialization.py tool to help developers verify proper setup
- Tool checks all storage components and pipeline status
- Provides clear feedback on what's missing and how to fix it
- Includes demo mode to show before/after initialization
- Helps prevent common initialization errors proactively

This tool makes it easier for developers to debug initialization issues
---
 lightrag/tools/check_initialization.py | 176 +++++++++++++++++++++++++
 1 file changed, 176 insertions(+)
 create mode 100644 lightrag/tools/check_initialization.py

diff --git a/lightrag/tools/check_initialization.py b/lightrag/tools/check_initialization.py
new file mode 100644
index 00000000..b10e31ba
--- /dev/null
+++ b/lightrag/tools/check_initialization.py
@@ -0,0 +1,176 @@
+#!/usr/bin/env python3
+"""
+Diagnostic tool to check LightRAG initialization status.
+
+This tool helps developers verify that their LightRAG instance is properly 
+initialized before use, preventing common initialization errors.
+
+Usage:
+    python -m lightrag.tools.check_initialization
+"""
+
+import asyncio
+import sys
+from typing import Optional
+from pathlib import Path
+
+# Add parent directory to path for imports
+sys.path.insert(0, str(Path(__file__).parent.parent.parent))
+
+from lightrag import LightRAG
+from lightrag.base import StoragesStatus
+
+
+async def check_lightrag_setup(rag_instance: LightRAG, verbose: bool = False) -> bool:
+    """
+    Check if a LightRAG instance is properly initialized.
+    
+    Args:
+        rag_instance: The LightRAG instance to check
+        verbose: If True, print detailed diagnostic information
+        
+    Returns:
+        True if properly initialized, False otherwise
+    """
+    issues = []
+    warnings = []
+    
+    print("🔍 Checking LightRAG initialization status...\n")
+    
+    # Check storage initialization status
+    if not hasattr(rag_instance, '_storages_status'):
+        issues.append("LightRAG instance missing _storages_status attribute")
+    elif rag_instance._storages_status != StoragesStatus.INITIALIZED:
+        issues.append(f"Storages not initialized (status: {rag_instance._storages_status.name})")
+    else:
+        print("✅ Storage status: INITIALIZED")
+    
+    # Check individual storage components
+    storage_components = [
+        ('full_docs', 'Document storage'),
+        ('text_chunks', 'Text chunks storage'),
+        ('entities_vdb', 'Entity vector database'),
+        ('relationships_vdb', 'Relationship vector database'),
+        ('chunks_vdb', 'Chunks vector database'),
+        ('doc_status', 'Document status tracker'),
+        ('llm_response_cache', 'LLM response cache'),
+        ('full_entities', 'Entity storage'),
+        ('full_relations', 'Relation storage'),
+        ('chunk_entity_relation_graph', 'Graph storage')
+    ]
+    
+    if verbose:
+        print("\n📦 Storage Components:")
+    
+    for component, description in storage_components:
+        if not hasattr(rag_instance, component):
+            issues.append(f"Missing storage component: {component} ({description})")
+        else:
+            storage = getattr(rag_instance, component)
+            if storage is None:
+                warnings.append(f"Storage {component} is None (might be optional)")
+            elif hasattr(storage, '_storage_lock'):
+                if storage._storage_lock is None:
+                    issues.append(f"Storage {component} not initialized (lock is None)")
+                elif verbose:
+                    print(f"  ✅ {description}: Ready")
+            elif verbose:
+                print(f"  ✅ {description}: Ready")
+    
+    # Check pipeline status
+    try:
+        from lightrag.kg.shared_storage import get_namespace_data
+        get_namespace_data("pipeline_status")
+        print("✅ Pipeline status: INITIALIZED")
+    except KeyError:
+        issues.append("Pipeline status not initialized - call initialize_pipeline_status()")
+    except Exception as e:
+        issues.append(f"Error checking pipeline status: {str(e)}")
+    
+    # Print results
+    print("\n" + "=" * 50)
+    
+    if issues:
+        print("❌ Issues found:\n")
+        for issue in issues:
+            print(f"  • {issue}")
+        
+        print("\n📝 To fix, run this initialization sequence:\n")
+        print("  await rag.initialize_storages()")
+        print("  from lightrag.kg.shared_storage import initialize_pipeline_status")
+        print("  await initialize_pipeline_status()")
+        print("\n📚 Documentation: https://github.com/HKUDS/LightRAG#important-initialization-requirements")
+        
+        if warnings and verbose:
+            print("\n⚠️  Warnings (might be normal):")
+            for warning in warnings:
+                print(f"  • {warning}")
+        
+        return False
+    else:
+        print("✅ LightRAG is properly initialized and ready to use!")
+        
+        if warnings and verbose:
+            print("\n⚠️  Warnings (might be normal):")
+            for warning in warnings:
+                print(f"  • {warning}")
+        
+        return True
+
+
+async def demo():
+    """Demonstrate the diagnostic tool with a test instance."""
+    from lightrag.llm.openai import openai_embed, gpt_4o_mini_complete
+    from lightrag.kg.shared_storage import initialize_pipeline_status
+    
+    print("=" * 50)
+    print("LightRAG Initialization Diagnostic Tool")
+    print("=" * 50)
+    
+    # Create test instance
+    rag = LightRAG(
+        working_dir="./test_diagnostic",
+        embedding_func=openai_embed,
+        llm_model_func=gpt_4o_mini_complete,
+    )
+    
+    print("\n🔴 BEFORE initialization:\n")
+    await check_lightrag_setup(rag, verbose=True)
+    
+    print("\n" + "=" * 50)
+    print("\n🔄 Initializing...\n")
+    await rag.initialize_storages()
+    await initialize_pipeline_status()
+    
+    print("\n🟢 AFTER initialization:\n")
+    await check_lightrag_setup(rag, verbose=True)
+    
+    # Cleanup
+    import shutil
+    shutil.rmtree("./test_diagnostic", ignore_errors=True)
+
+
+if __name__ == "__main__":
+    import argparse
+    
+    parser = argparse.ArgumentParser(
+        description="Check LightRAG initialization status"
+    )
+    parser.add_argument(
+        "--demo", 
+        action="store_true",
+        help="Run a demonstration with a test instance"
+    )
+    parser.add_argument(
+        "--verbose", "-v",
+        action="store_true",
+        help="Show detailed diagnostic information"
+    )
+    
+    args = parser.parse_args()
+    
+    if args.demo:
+        asyncio.run(demo())
+    else:
+        print("Run with --demo to see the diagnostic tool in action")
+        print("Or import this module and use check_lightrag_setup() with your instance")
\ No newline at end of file

From 4c556d8aaefd04225e07feca486e66f5d0b03aa0 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 20 Aug 2025 22:04:32 +0800
Subject: [PATCH 003/141] Set default TIMEOUT value to 150, and gunicorn
 timeout to TIMEOUT+30

---
 env.example                       | 4 ++--
 lightrag/api/README-zh.md         | 2 +-
 lightrag/api/README.md            | 2 +-
 lightrag/api/run_with_gunicorn.py | 2 +-
 lightrag/constants.py             | 2 +-
 5 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/env.example b/env.example
index 5d71b9b6..db590761 100644
--- a/env.example
+++ b/env.example
@@ -8,6 +8,8 @@ PORT=9621
 WEBUI_TITLE='My Graph KB'
 WEBUI_DESCRIPTION="Simple and Fast Graph Based RAG System"
 # WORKERS=2
+### gunicorn worker timeout(as default LLM request timeout if LLM_TIMEOUT is not set)
+# TIMEOUT=150
 # CORS_ORIGINS=http://localhost:3000,http://localhost:8080
 
 ### Optional SSL Configuration
@@ -151,8 +153,6 @@ LLM_BINDING_API_KEY=your_api_key
 ### lightrag-server --llm-binding openai --help
 
 ### Ollama Server Specific Parameters
-### Time out in seconds, None for infinite timeout
-TIMEOUT=240
 ### OLLAMA_LLM_NUM_CTX must be larger than MAX_TOTAL_TOKENS + 2000
 OLLAMA_LLM_NUM_CTX=32768
 ### Stop sequences for Ollama LLM
diff --git a/lightrag/api/README-zh.md b/lightrag/api/README-zh.md
index b74e4d12..286b78b9 100644
--- a/lightrag/api/README-zh.md
+++ b/lightrag/api/README-zh.md
@@ -478,7 +478,7 @@ SUMMARY_LANGUAGE=Chinese
 MAX_PARALLEL_INSERT=2
 
 ### LLM Configuration (Use valid host. For local services installed with docker, you can use host.docker.internal)
-TIMEOUT=200
+TIMEOUT=150
 MAX_ASYNC=4
 
 LLM_BINDING=openai
diff --git a/lightrag/api/README.md b/lightrag/api/README.md
index da59b38f..8b4f239a 100644
--- a/lightrag/api/README.md
+++ b/lightrag/api/README.md
@@ -485,7 +485,7 @@ SUMMARY_LANGUAGE=Chinese
 MAX_PARALLEL_INSERT=2
 
 ### LLM Configuration (Use valid host. For local services installed with docker, you can use host.docker.internal)
-TIMEOUT=200
+TIMEOUT=150
 MAX_ASYNC=4
 
 LLM_BINDING=openai
diff --git a/lightrag/api/run_with_gunicorn.py b/lightrag/api/run_with_gunicorn.py
index 8c8a029d..929db019 100644
--- a/lightrag/api/run_with_gunicorn.py
+++ b/lightrag/api/run_with_gunicorn.py
@@ -153,7 +153,7 @@ def main():
 
             # Timeout configuration prioritizes command line arguments
             gunicorn_config.timeout = (
-                global_args.timeout * 2
+                global_args.timeout + 30
                 if global_args.timeout is not None
                 else get_env_value(
                     "TIMEOUT", DEFAULT_TIMEOUT + 30, int, special_none=True
diff --git a/lightrag/constants.py b/lightrag/constants.py
index e3ed9d7f..aab20665 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -49,7 +49,7 @@ DEFAULT_MAX_PARALLEL_INSERT = 2  # Default maximum parallel insert operations
 DEFAULT_EMBEDDING_FUNC_MAX_ASYNC = 8  # Default max async for embedding functions
 DEFAULT_EMBEDDING_BATCH_NUM = 10  # Default batch size for embedding computations
 
-# Ollama Server Timetout in seconds
+# gunicorn worker timeout(as default LLM request timeout if LLM_TIMEOUT is not set)
 DEFAULT_TIMEOUT = 150
 
 # Logging configuration defaults

From df7bcb1e3daf6dc135dac42f4cf986d548da0f56 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 20 Aug 2025 23:50:57 +0800
Subject: [PATCH 004/141] Add LLM_TIMEOUT configuration for all LLM providers

- Add LLM_TIMEOUT env variable
- Apply timeout to all LLM bindings
---
 env.example                     |  4 +++-
 lightrag/api/lightrag_server.py | 26 ++++++++++++--------------
 lightrag/llm/anthropic.py       | 10 +++++++---
 lightrag/llm/azure_openai.py    |  6 +++++-
 lightrag/llm/ollama.py          |  2 ++
 lightrag/llm/openai.py          |  9 +++++----
 6 files changed, 34 insertions(+), 23 deletions(-)

diff --git a/env.example b/env.example
index db590761..56bc243e 100644
--- a/env.example
+++ b/env.example
@@ -127,8 +127,10 @@ MAX_PARALLEL_INSERT=2
 ### LLM Configuration
 ### LLM_BINDING type: openai, ollama, lollms, azure_openai, aws_bedrock
 ###########################################################
-### LLM temperature setting for all llm binding (openai, azure_openai, ollama)
+### LLM temperature and timeout setting for all llm binding (openai, azure_openai, ollama)
 # TEMPERATURE=1.0
+### LLM request timeout setting for all llm (set to TIMEOUT if not specified)
+# LLM_TIMEOUT=150
 ### Some models like o1-mini require temperature to be set to 1, some LLM can fall into output loops with low temperature
 
 LLM_BINDING=openai
diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index c3384181..e84686cb 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -254,6 +254,8 @@ def create_app(args):
     if args.embedding_binding == "jina":
         from lightrag.llm.jina import jina_embed
 
+    llm_timeout = get_env_value("LLM_TIMEOUT", args.timeout, int)
+
     async def openai_alike_model_complete(
         prompt,
         system_prompt=None,
@@ -267,12 +269,10 @@ def create_app(args):
         if history_messages is None:
             history_messages = []
 
-        # Use OpenAI LLM options if available, otherwise fallback to global temperature
-        if args.llm_binding == "openai":
-            openai_options = OpenAILLMOptions.options_dict(args)
-            kwargs.update(openai_options)
-        else:
-            kwargs["temperature"] = args.temperature
+        # Use OpenAI LLM options if available
+        openai_options = OpenAILLMOptions.options_dict(args)
+        kwargs["timeout"] = llm_timeout
+        kwargs.update(openai_options)
 
         return await openai_complete_if_cache(
             args.llm_model,
@@ -297,12 +297,10 @@ def create_app(args):
         if history_messages is None:
             history_messages = []
 
-        # Use OpenAI LLM options if available, otherwise fallback to global temperature
-        if args.llm_binding == "azure_openai":
-            openai_options = OpenAILLMOptions.options_dict(args)
-            kwargs.update(openai_options)
-        else:
-            kwargs["temperature"] = args.temperature
+        # Use OpenAI LLM options
+        openai_options = OpenAILLMOptions.options_dict(args)
+        kwargs["timeout"] = llm_timeout
+        kwargs.update(openai_options)
 
         return await azure_openai_complete_if_cache(
             args.llm_model,
@@ -451,7 +449,7 @@ def create_app(args):
             llm_model_kwargs=(
                 {
                     "host": args.llm_binding_host,
-                    "timeout": args.timeout,
+                    "timeout": llm_timeout,
                     "options": OllamaLLMOptions.options_dict(args),
                     "api_key": args.llm_binding_api_key,
                 }
@@ -482,7 +480,7 @@ def create_app(args):
             chunk_token_size=int(args.chunk_size),
             chunk_overlap_token_size=int(args.chunk_overlap_size),
             llm_model_kwargs={
-                "timeout": args.timeout,
+                "timeout": llm_timeout,
             },
             llm_model_name=args.llm_model,
             llm_model_max_async=args.max_async,
diff --git a/lightrag/llm/anthropic.py b/lightrag/llm/anthropic.py
index 7878c8f0..b7a7dfaa 100644
--- a/lightrag/llm/anthropic.py
+++ b/lightrag/llm/anthropic.py
@@ -77,14 +77,18 @@ async def anthropic_complete_if_cache(
     if not VERBOSE_DEBUG and logger.level == logging.DEBUG:
         logging.getLogger("anthropic").setLevel(logging.INFO)
 
+    kwargs.pop("hashing_kv", None)
+    kwargs.pop("keyword_extraction", None)
+    timeout = kwargs.pop("timeout", None)
+
     anthropic_async_client = (
-        AsyncAnthropic(default_headers=default_headers, api_key=api_key)
+        AsyncAnthropic(default_headers=default_headers, api_key=api_key, timeout=timeout)
         if base_url is None
         else AsyncAnthropic(
-            base_url=base_url, default_headers=default_headers, api_key=api_key
+            base_url=base_url, default_headers=default_headers, api_key=api_key, timeout=timeout
         )
     )
-    kwargs.pop("hashing_kv", None)
+
     messages: list[dict[str, Any]] = []
     if system_prompt:
         messages.append({"role": "system", "content": system_prompt})
diff --git a/lightrag/llm/azure_openai.py b/lightrag/llm/azure_openai.py
index 60d2c18e..adec391a 100644
--- a/lightrag/llm/azure_openai.py
+++ b/lightrag/llm/azure_openai.py
@@ -59,13 +59,17 @@ async def azure_openai_complete_if_cache(
         or os.getenv("OPENAI_API_VERSION")
     )
 
+    kwargs.pop("hashing_kv", None)
+    kwargs.pop("keyword_extraction", None)
+    timeout = kwargs.pop("timeout", None)
+    
     openai_async_client = AsyncAzureOpenAI(
         azure_endpoint=base_url,
         azure_deployment=deployment,
         api_key=api_key,
         api_version=api_version,
+        timeout=timeout,
     )
-    kwargs.pop("hashing_kv", None)
     messages = []
     if system_prompt:
         messages.append({"role": "system", "content": system_prompt})
diff --git a/lightrag/llm/ollama.py b/lightrag/llm/ollama.py
index 1ca5504e..6423fa90 100644
--- a/lightrag/llm/ollama.py
+++ b/lightrag/llm/ollama.py
@@ -51,6 +51,8 @@ async def _ollama_model_if_cache(
     # kwargs.pop("response_format", None) # allow json
     host = kwargs.pop("host", None)
     timeout = kwargs.pop("timeout", None)
+    if timeout == 0:
+        timeout = None
     kwargs.pop("hashing_kv", None)
     api_key = kwargs.pop("api_key", None)
     headers = {
diff --git a/lightrag/llm/openai.py b/lightrag/llm/openai.py
index 910d1812..f920e392 100644
--- a/lightrag/llm/openai.py
+++ b/lightrag/llm/openai.py
@@ -149,17 +149,18 @@ async def openai_complete_if_cache(
     if not VERBOSE_DEBUG and logger.level == logging.DEBUG:
         logging.getLogger("openai").setLevel(logging.INFO)
 
+    # Remove special kwargs that shouldn't be passed to OpenAI
+    kwargs.pop("hashing_kv", None)
+    kwargs.pop("keyword_extraction", None)
+
     # Extract client configuration options
     client_configs = kwargs.pop("openai_client_configs", {})
 
     # Create the OpenAI client
     openai_async_client = create_openai_async_client(
-        api_key=api_key, base_url=base_url, client_configs=client_configs
+        api_key=api_key, base_url=base_url, client_configs=client_configs,
     )
 
-    # Remove special kwargs that shouldn't be passed to OpenAI
-    kwargs.pop("hashing_kv", None)
-    kwargs.pop("keyword_extraction", None)
 
     # Prepare messages
     messages: list[dict[str, Any]] = []

From aa2277272166feac5bfc5c175786ab6b87e294dd Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 20 Aug 2025 23:52:33 +0800
Subject: [PATCH 005/141] Refactor LLM temperature handling to be
 provider-specific
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Remove global temperature parameter
• Add provider-specific temp configs
• Update env example with new settings
• Fix Bedrock temperature handling
• Clean up splash screen display
---
 env.example                     |  8 +++++---
 lightrag/api/config.py          | 35 ---------------------------------
 lightrag/api/lightrag_server.py |  5 +----
 lightrag/api/utils_api.py       |  6 ++----
 lightrag/llm/Readme.md          |  2 --
 lightrag/llm/anthropic.py       |  9 +++++++--
 lightrag/llm/azure_openai.py    |  2 +-
 lightrag/llm/lollms.py          |  2 +-
 lightrag/llm/openai.py          |  5 +++--
 9 files changed, 20 insertions(+), 54 deletions(-)

diff --git a/env.example b/env.example
index 56bc243e..c0fc7567 100644
--- a/env.example
+++ b/env.example
@@ -127,9 +127,7 @@ MAX_PARALLEL_INSERT=2
 ### LLM Configuration
 ### LLM_BINDING type: openai, ollama, lollms, azure_openai, aws_bedrock
 ###########################################################
-### LLM temperature and timeout setting for all llm binding (openai, azure_openai, ollama)
-# TEMPERATURE=1.0
-### LLM request timeout setting for all llm (set to TIMEOUT if not specified)
+### LLM request timeout setting for all llm (set to TIMEOUT if not specified, 0 means no timeout for Ollma)
 # LLM_TIMEOUT=150
 ### Some models like o1-mini require temperature to be set to 1, some LLM can fall into output loops with low temperature
 
@@ -151,6 +149,7 @@ LLM_BINDING_API_KEY=your_api_key
 ### OpenAI Specific Parameters
 ### Apply frequency penalty to prevent the LLM from generating repetitive or looping outputs
 # OPENAI_LLM_FREQUENCY_PENALTY=1.1
+# OPENAI_LLM_TEMPERATURE=1.0
 ### use the following command to see all support options for openai and azure_openai
 ### lightrag-server --llm-binding openai --help
 
@@ -164,6 +163,9 @@ OLLAMA_LLM_NUM_CTX=32768
 ### use the following command to see all support options for Ollama LLM
 ### lightrag-server --llm-binding ollama --help
 
+### Bedrock Specific Parameters
+# BEDROCK_LLM_TEMPERATURE=1.0
+
 ####################################################################################
 ### Embedding Configuration (Should not be changed after the first file processed)
 ####################################################################################
diff --git a/lightrag/api/config.py b/lightrag/api/config.py
index 01d0dd75..756fd7d2 100644
--- a/lightrag/api/config.py
+++ b/lightrag/api/config.py
@@ -35,7 +35,6 @@ from lightrag.constants import (
     DEFAULT_EMBEDDING_BATCH_NUM,
     DEFAULT_OLLAMA_MODEL_NAME,
     DEFAULT_OLLAMA_MODEL_TAG,
-    DEFAULT_TEMPERATURE,
 )
 
 # use the .env that is inside the current folder
@@ -264,14 +263,6 @@ def parse_args() -> argparse.Namespace:
     elif os.environ.get("LLM_BINDING") in ["openai", "azure_openai"]:
         OpenAILLMOptions.add_args(parser)
 
-    # Add global temperature command line argument
-    parser.add_argument(
-        "--temperature",
-        type=float,
-        default=get_env_value("TEMPERATURE", DEFAULT_TEMPERATURE, float),
-        help="Global temperature setting for LLM (default: from env TEMPERATURE or 0.1)",
-    )
-
     args = parser.parse_args()
 
     # convert relative path to absolute path
@@ -330,32 +321,6 @@ def parse_args() -> argparse.Namespace:
     )
     args.enable_llm_cache = get_env_value("ENABLE_LLM_CACHE", True, bool)
 
-    # Handle Ollama LLM temperature with priority cascade when llm-binding is ollama
-    if args.llm_binding == "ollama":
-        # Priority order (highest to lowest):
-        # 1. --ollama-llm-temperature command argument
-        # 2. OLLAMA_LLM_TEMPERATURE environment variable
-        # 3. --temperature command argument
-        # 4. TEMPERATURE environment variable
-
-        # Check if --ollama-llm-temperature was explicitly provided in command line
-        if "--ollama-llm-temperature" not in sys.argv:
-            # Use args.temperature which handles --temperature command arg and TEMPERATURE env var priority
-            args.ollama_llm_temperature = args.temperature
-
-    # Handle OpenAI LLM temperature with priority cascade when llm-binding is openai or azure_openai
-    if args.llm_binding in ["openai", "azure_openai"]:
-        # Priority order (highest to lowest):
-        # 1. --openai-llm-temperature command argument
-        # 2. OPENAI_LLM_TEMPERATURE environment variable
-        # 3. --temperature command argument
-        # 4. TEMPERATURE environment variable
-
-        # Check if --openai-llm-temperature was explicitly provided in command line
-        if "--openai-llm-temperature" not in sys.argv:
-            # Use args.temperature which handles --temperature command arg and TEMPERATURE env var priority
-            args.openai_llm_temperature = args.temperature
-
     # Select Document loading tool (DOCLING, DEFAULT)
     args.document_loading_engine = get_env_value("DOCUMENT_LOADING_ENGINE", "DEFAULT")
 
diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index e84686cb..708fedd2 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -327,7 +327,7 @@ def create_app(args):
             history_messages = []
 
         # Use global temperature for Bedrock
-        kwargs["temperature"] = args.temperature
+        kwargs["temperature"] = get_env_value("BEDROCK_LLM_TEMPERATURE", 1.0, float)
 
         return await bedrock_complete_if_cache(
             args.llm_model,
@@ -479,9 +479,6 @@ def create_app(args):
             llm_model_func=azure_openai_model_complete,
             chunk_token_size=int(args.chunk_size),
             chunk_overlap_token_size=int(args.chunk_overlap_size),
-            llm_model_kwargs={
-                "timeout": llm_timeout,
-            },
             llm_model_name=args.llm_model,
             llm_model_max_async=args.max_async,
             summary_max_tokens=args.max_tokens,
diff --git a/lightrag/api/utils_api.py b/lightrag/api/utils_api.py
index 90a1eb96..fc05716c 100644
--- a/lightrag/api/utils_api.py
+++ b/lightrag/api/utils_api.py
@@ -201,6 +201,8 @@ def display_splash_screen(args: argparse.Namespace) -> None:
     ASCIIColors.yellow(f"{args.port}")
     ASCIIColors.white("    ├─ Workers: ", end="")
     ASCIIColors.yellow(f"{args.workers}")
+    ASCIIColors.white("    ├─ Timeout: ", end="")
+    ASCIIColors.yellow(f"{args.timeout}")
     ASCIIColors.white("    ├─ CORS Origins: ", end="")
     ASCIIColors.yellow(f"{args.cors_origins}")
     ASCIIColors.white("    ├─ SSL Enabled: ", end="")
@@ -238,14 +240,10 @@ def display_splash_screen(args: argparse.Namespace) -> None:
     ASCIIColors.yellow(f"{args.llm_binding_host}")
     ASCIIColors.white("    ├─ Model: ", end="")
     ASCIIColors.yellow(f"{args.llm_model}")
-    ASCIIColors.white("    ├─ Temperature: ", end="")
-    ASCIIColors.yellow(f"{args.temperature}")
     ASCIIColors.white("    ├─ Max Async for LLM: ", end="")
     ASCIIColors.yellow(f"{args.max_async}")
     ASCIIColors.white("    ├─ Max Tokens: ", end="")
     ASCIIColors.yellow(f"{args.max_tokens}")
-    ASCIIColors.white("    ├─ Timeout: ", end="")
-    ASCIIColors.yellow(f"{args.timeout if args.timeout else 'None (infinite)'}")
     ASCIIColors.white("    ├─ LLM Cache Enabled: ", end="")
     ASCIIColors.yellow(f"{args.enable_llm_cache}")
     ASCIIColors.white("    └─ LLM Cache for Extraction Enabled: ", end="")
diff --git a/lightrag/llm/Readme.md b/lightrag/llm/Readme.md
index c907fd4d..fc00d071 100644
--- a/lightrag/llm/Readme.md
+++ b/lightrag/llm/Readme.md
@@ -36,7 +36,6 @@ async def llm_model_func(prompt, system_prompt=None, history_messages=[], **kwar
             llm_instance = OpenAI(
                 model="gpt-4",
                 api_key="your-openai-key",
-                temperature=0.7,
             )
             kwargs['llm_instance'] = llm_instance
 
@@ -91,7 +90,6 @@ async def llm_model_func(prompt, system_prompt=None, history_messages=[], **kwar
                 model=f"openai/{settings.LLM_MODEL}",  # Format: "provider/model_name"
                 api_base=settings.LITELLM_URL,
                 api_key=settings.LITELLM_KEY,
-                temperature=0.7,
             )
             kwargs['llm_instance'] = llm_instance
 
diff --git a/lightrag/llm/anthropic.py b/lightrag/llm/anthropic.py
index b7a7dfaa..98a997d5 100644
--- a/lightrag/llm/anthropic.py
+++ b/lightrag/llm/anthropic.py
@@ -82,10 +82,15 @@ async def anthropic_complete_if_cache(
     timeout = kwargs.pop("timeout", None)
 
     anthropic_async_client = (
-        AsyncAnthropic(default_headers=default_headers, api_key=api_key, timeout=timeout)
+        AsyncAnthropic(
+            default_headers=default_headers, api_key=api_key, timeout=timeout
+        )
         if base_url is None
         else AsyncAnthropic(
-            base_url=base_url, default_headers=default_headers, api_key=api_key, timeout=timeout
+            base_url=base_url,
+            default_headers=default_headers,
+            api_key=api_key,
+            timeout=timeout,
         )
     )
 
diff --git a/lightrag/llm/azure_openai.py b/lightrag/llm/azure_openai.py
index adec391a..0ede0824 100644
--- a/lightrag/llm/azure_openai.py
+++ b/lightrag/llm/azure_openai.py
@@ -62,7 +62,7 @@ async def azure_openai_complete_if_cache(
     kwargs.pop("hashing_kv", None)
     kwargs.pop("keyword_extraction", None)
     timeout = kwargs.pop("timeout", None)
-    
+
     openai_async_client = AsyncAzureOpenAI(
         azure_endpoint=base_url,
         azure_deployment=deployment,
diff --git a/lightrag/llm/lollms.py b/lightrag/llm/lollms.py
index 357b65bf..39b64ce3 100644
--- a/lightrag/llm/lollms.py
+++ b/lightrag/llm/lollms.py
@@ -59,7 +59,7 @@ async def lollms_model_if_cache(
         "personality": kwargs.get("personality", -1),
         "n_predict": kwargs.get("n_predict", None),
         "stream": stream,
-        "temperature": kwargs.get("temperature", 0.8),
+        "temperature": kwargs.get("temperature", 1.0),
         "top_k": kwargs.get("top_k", 50),
         "top_p": kwargs.get("top_p", 0.95),
         "repeat_penalty": kwargs.get("repeat_penalty", 0.8),
diff --git a/lightrag/llm/openai.py b/lightrag/llm/openai.py
index f920e392..3bd652f4 100644
--- a/lightrag/llm/openai.py
+++ b/lightrag/llm/openai.py
@@ -158,10 +158,11 @@ async def openai_complete_if_cache(
 
     # Create the OpenAI client
     openai_async_client = create_openai_async_client(
-        api_key=api_key, base_url=base_url, client_configs=client_configs,
+        api_key=api_key,
+        base_url=base_url,
+        client_configs=client_configs,
     )
 
-
     # Prepare messages
     messages: list[dict[str, Any]] = []
     if system_prompt:

From 0e67ead8fa80365f719a63c642a1a4673bf54d0f Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 21 Aug 2025 10:15:20 +0800
Subject: [PATCH 006/141] Rename MAX_TOKENS to SUMMARY_MAX_TOKENS for clarity

---
 README-zh.md           | 2 +-
 README.md              | 2 +-
 env.example            | 8 +++-----
 lightrag/api/config.py | 2 +-
 lightrag/lightrag.py   | 2 +-
 5 files changed, 7 insertions(+), 9 deletions(-)

diff --git a/README-zh.md b/README-zh.md
index f53351b1..5caefc89 100644
--- a/README-zh.md
+++ b/README-zh.md
@@ -265,7 +265,7 @@ if __name__ == "__main__":
 | **embedding_func_max_async** | `int` | 最大并发异步嵌入进程数 | `16` |
 | **llm_model_func** | `callable` | LLM生成的函数 | `gpt_4o_mini_complete` |
 | **llm_model_name** | `str` | 用于生成的LLM模型名称 | `meta-llama/Llama-3.2-1B-Instruct` |
-| **summary_max_tokens** | `int` | 生成实体关系摘要时送给LLM的最大令牌数 | `32000`（默认值由环境变量MAX_TOKENS更改） |
+| **summary_max_tokens** | `int` | 生成实体关系摘要时送给LLM的最大令牌数 | `32000`（由环境变量 SUMMARY_MAX_TOKENS 设置） |
 | **llm_model_max_async** | `int` | 最大并发异步LLM进程数 | `4`（默认值由环境变量MAX_ASYNC更改） |
 | **llm_model_kwargs** | `dict` | LLM生成的附加参数 | |
 | **vector_db_storage_cls_kwargs** | `dict` | 向量数据库的附加参数，如设置节点和关系检索的阈值 | cosine_better_than_threshold: 0.2（默认值由环境变量COSINE_THRESHOLD更改） |
diff --git a/README.md b/README.md
index 4299896c..51c68a1a 100644
--- a/README.md
+++ b/README.md
@@ -272,7 +272,7 @@ A full list of LightRAG init parameters:
 | **embedding_func_max_async** | `int` | Maximum number of concurrent asynchronous embedding processes | `16` |
 | **llm_model_func** | `callable` | Function for LLM generation | `gpt_4o_mini_complete` |
 | **llm_model_name** | `str` | LLM model name for generation | `meta-llama/Llama-3.2-1B-Instruct` |
-| **summary_max_tokens** | `int` | Maximum tokens send to LLM to generate entity relation summaries | `32000`（default value changed by env var MAX_TOKENS) |
+| **summary_max_tokens** | `int` | Maximum tokens send to LLM to generate entity relation summaries | `32000`（configured by env var SUMMARY_MAX_TOKENS) |
 | **llm_model_max_async** | `int` | Maximum number of concurrent asynchronous LLM processes | `4`（default value changed by env var MAX_ASYNC) |
 | **llm_model_kwargs** | `dict` | Additional parameters for LLM generation | |
 | **vector_db_storage_cls_kwargs** | `dict` | Additional parameters for vector database, like setting the threshold for nodes and relations retrieval | cosine_better_than_threshold: 0.2（default value changed by env var COSINE_THRESHOLD) |
diff --git a/env.example b/env.example
index c0fc7567..60980b96 100644
--- a/env.example
+++ b/env.example
@@ -107,7 +107,7 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true
 ### Entity and relation summarization configuration
 ### Number of duplicated entities/edges to trigger LLM re-summary on merge (at least 3 is recommented)， and max tokens send to LLM
 # FORCE_LLM_SUMMARY_ON_MERGE=4
-# MAX_TOKENS=10000
+# SUMMARY_MAX_TOKENS=10000
 ### Maximum number of entity extraction attempts for ambiguous content
 # MAX_GLEANING=1
 
@@ -148,18 +148,16 @@ LLM_BINDING_API_KEY=your_api_key
 
 ### OpenAI Specific Parameters
 ### Apply frequency penalty to prevent the LLM from generating repetitive or looping outputs
-# OPENAI_LLM_FREQUENCY_PENALTY=1.1
 # OPENAI_LLM_TEMPERATURE=1.0
 ### use the following command to see all support options for openai and azure_openai
 ### lightrag-server --llm-binding openai --help
 
 ### Ollama Server Specific Parameters
-### OLLAMA_LLM_NUM_CTX must be larger than MAX_TOTAL_TOKENS + 2000
+### OLLAMA_LLM_NUM_CTX must be provided, and should at least larger than MAX_TOTAL_TOKENS + 2000
 OLLAMA_LLM_NUM_CTX=32768
+# OLLAMA_LLM_TEMPERATURE=1.0
 ### Stop sequences for Ollama LLM
 # OLLAMA_LLM_STOP='["</s>", "Assistant:", "\n\n"]'
-### If OLLAMA_LLM_TEMPERATURE is not specified, the system will default to the value defined by TEMPERATURE
-# OLLAMA_LLM_TEMPERATURE=0.85
 ### use the following command to see all support options for Ollama LLM
 ### lightrag-server --llm-binding ollama --help
 
diff --git a/lightrag/api/config.py b/lightrag/api/config.py
index 756fd7d2..83a56f5a 100644
--- a/lightrag/api/config.py
+++ b/lightrag/api/config.py
@@ -122,7 +122,7 @@ def parse_args() -> argparse.Namespace:
     parser.add_argument(
         "--max-tokens",
         type=int,
-        default=get_env_value("MAX_TOKENS", DEFAULT_SUMMARY_MAX_TOKENS, int),
+        default=get_env_value("SUMMARY_MAX_TOKENS", DEFAULT_SUMMARY_MAX_TOKENS, int),
         help=f"Maximum token size (default: from env or {DEFAULT_SUMMARY_MAX_TOKENS})",
     )
 
diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index 924c423e..8b214c16 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -283,7 +283,7 @@ class LightRAG:
     """Name of the LLM model used for generating responses."""
 
     summary_max_tokens: int = field(
-        default=int(os.getenv("MAX_TOKENS", DEFAULT_SUMMARY_MAX_TOKENS))
+        default=int(os.getenv("SUMMARY_MAX_TOKENS", DEFAULT_SUMMARY_MAX_TOKENS))
     )
     """Maximum number of tokens allowed per LLM response."""
 

From 0dd245e84786819e5a7698502df9e97481599e69 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 21 Aug 2025 11:04:06 +0800
Subject: [PATCH 007/141] Add OpenAI reasoning effort and max completion tokens
 config options

---
 env.example | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/env.example b/env.example
index 60980b96..5646874e 100644
--- a/env.example
+++ b/env.example
@@ -147,8 +147,10 @@ LLM_BINDING_API_KEY=your_api_key
 # LLM_BINDING=openai
 
 ### OpenAI Specific Parameters
-### Apply frequency penalty to prevent the LLM from generating repetitive or looping outputs
 # OPENAI_LLM_TEMPERATURE=1.0
+# OPENAI_LLM_REASONING_EFFORT=low
+### Set the maximum number of completion tokens if your LLM generates repetitive or unconstrained output
+# OPENAI_LLM_MAX_COMPLETION_TOKENS=16384
 ### use the following command to see all support options for openai and azure_openai
 ### lightrag-server --llm-binding openai --help
 

From 5d34007f2c66be8246817f0b92c7bcbac4011bc7 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 21 Aug 2025 11:35:23 +0800
Subject: [PATCH 008/141] Add presence penalty config option for smaller models

- Add OPENAI_LLM_PRESENCE_PENALTY setting
- Recommend 1.5 for Qwen3 <32B params
- Update max completion tokens comment
---
 env.example | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/env.example b/env.example
index 5646874e..90bd5a67 100644
--- a/env.example
+++ b/env.example
@@ -149,7 +149,9 @@ LLM_BINDING_API_KEY=your_api_key
 ### OpenAI Specific Parameters
 # OPENAI_LLM_TEMPERATURE=1.0
 # OPENAI_LLM_REASONING_EFFORT=low
-### Set the maximum number of completion tokens if your LLM generates repetitive or unconstrained output
+### For models like Qwen3 with fewer than 32B param, it is recommended to set the presence penalty to 1.5
+# OPENAI_LLM_PRESENCE_PENALTY=1.5
+### If the presence penalty still can not stop the model from generates repetitive or unconstrained output
 # OPENAI_LLM_MAX_COMPLETION_TOKENS=16384
 ### use the following command to see all support options for openai and azure_openai
 ### lightrag-server --llm-binding openai --help

From 4b2ef71c2542ee3245fa7a18d0523c41158a57f1 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 21 Aug 2025 13:06:28 +0800
Subject: [PATCH 009/141] feat: Add extra_body parameter support for
 OpenRouter/vLLM compatibility

- Enhanced add_args function to handle dict types with JSON parsing
- Added reasoning and extra_body parameters for OpenRouter/vLLM compatibility
- Updated env.example with OpenRouter/vLLM parameter examples
---
 env.example                     |   8 +-
 lightrag/llm/binding_options.py | 135 +++++++++++++++++++++++++++++++-
 2 files changed, 139 insertions(+), 4 deletions(-)

diff --git a/env.example b/env.example
index 90bd5a67..5d47a7bf 100644
--- a/env.example
+++ b/env.example
@@ -153,7 +153,13 @@ LLM_BINDING_API_KEY=your_api_key
 # OPENAI_LLM_PRESENCE_PENALTY=1.5
 ### If the presence penalty still can not stop the model from generates repetitive or unconstrained output
 # OPENAI_LLM_MAX_COMPLETION_TOKENS=16384
-### use the following command to see all support options for openai and azure_openai
+
+### OpenRouter Specific Parameters
+# OPENAI_LLM_EXTRA_BODY='{"reasoning": {"enabled": false}}'
+### Qwen3 Specific Parameters depoly by vLLM
+# OPENAI_LLM_EXTRA_BODY='{"chat_template_kwargs": {"enable_thinking": false}}'
+
+### use the following command to see all support options for OpenAI, azure_openai or OpenRouter
 ### lightrag-server --llm-binding openai --help
 
 ### Ollama Server Specific Parameters
diff --git a/lightrag/llm/binding_options.py b/lightrag/llm/binding_options.py
index 827620ee..c2f2c9d7 100644
--- a/lightrag/llm/binding_options.py
+++ b/lightrag/llm/binding_options.py
@@ -99,7 +99,7 @@ class BindingOptions:
         group = parser.add_argument_group(f"{cls._binding_name} binding options")
         for arg_item in cls.args_env_name_type_value():
             # Handle JSON parsing for list types
-            if arg_item["type"] == List[str]:
+            if arg_item["type"] is List[str]:
 
                 def json_list_parser(value):
                     try:
@@ -126,6 +126,34 @@ class BindingOptions:
                     default=env_value,
                     help=arg_item["help"],
                 )
+            # Handle JSON parsing for dict types
+            elif arg_item["type"] is dict:
+
+                def json_dict_parser(value):
+                    try:
+                        parsed = json.loads(value)
+                        if not isinstance(parsed, dict):
+                            raise argparse.ArgumentTypeError(
+                                f"Expected JSON object, got {type(parsed).__name__}"
+                            )
+                        return parsed
+                    except json.JSONDecodeError as e:
+                        raise argparse.ArgumentTypeError(f"Invalid JSON: {e}")
+
+                # Get environment variable with JSON parsing
+                env_value = get_env_value(f"{arg_item['env_name']}", argparse.SUPPRESS)
+                if env_value is not argparse.SUPPRESS:
+                    try:
+                        env_value = json_dict_parser(env_value)
+                    except argparse.ArgumentTypeError:
+                        env_value = argparse.SUPPRESS
+
+                group.add_argument(
+                    f"--{arg_item['argname']}",
+                    type=json_dict_parser,
+                    default=env_value,
+                    help=arg_item["help"],
+                )
             else:
                 group.add_argument(
                     f"--{arg_item['argname']}",
@@ -234,8 +262,8 @@ class BindingOptions:
                 if arg_item["help"]:
                     sample_stream.write(f"# {arg_item['help']}\n")
 
-                # Handle JSON formatting for list types
-                if arg_item["type"] == List[str]:
+                # Handle JSON formatting for list and dict types
+                if arg_item["type"] is List[str] or arg_item["type"] is dict:
                     default_value = json.dumps(arg_item["default"])
                 else:
                     default_value = arg_item["default"]
@@ -431,6 +459,8 @@ class OpenAILLMOptions(BindingOptions):
     stop: List[str] = field(default_factory=list)  # Stop sequences
     temperature: float = DEFAULT_TEMPERATURE  # Controls randomness (0.0 to 2.0)
     top_p: float = 1.0  # Nucleus sampling parameter (0.0 to 1.0)
+    max_tokens: int = None  # Maximum number of tokens to generate(deprecated, use max_completion_tokens instead)
+    extra_body: dict = None  # Extra body parameters for OpenRouter of vLLM
 
     # Help descriptions
     _help: ClassVar[dict[str, str]] = {
@@ -443,6 +473,8 @@ class OpenAILLMOptions(BindingOptions):
         "stop": 'Stop sequences (JSON array of strings, e.g., \'["</s>", "\\n\\n"]\')',
         "temperature": "Controls randomness (0.0-2.0, higher = more creative)",
         "top_p": "Nucleus sampling parameter (0.0-1.0, lower = more focused)",
+        "max_tokens": "Maximum number of tokens to generate (deprecated, use max_completion_tokens instead)",
+        "extra_body": 'Extra body parameters for OpenRouter of vLLM (JSON dict, e.g., \'"reasoning": {"reasoning": {"enabled": false}}\')',
     }
 
 
@@ -493,6 +525,8 @@ if __name__ == "__main__":
                 "1000",
                 "--openai-llm-stop",
                 '["</s>", "\\n\\n"]',
+                "--openai-llm-reasoning",
+                '{"effort": "high", "max_tokens": 2000, "exclude": false, "enabled": true}',
             ]
         )
         print("Final args for LLM and Embedding:")
@@ -518,5 +552,100 @@ if __name__ == "__main__":
         print("\nOpenAI LLM options instance:")
         print(openai_options.asdict())
 
+        # Test creating OpenAI options instance with reasoning parameter
+        openai_options_with_reasoning = OpenAILLMOptions(
+            temperature=0.9,
+            max_completion_tokens=2000,
+            reasoning={
+                "effort": "medium",
+                "max_tokens": 1500,
+                "exclude": True,
+                "enabled": True,
+            },
+        )
+        print("\nOpenAI LLM options instance with reasoning:")
+        print(openai_options_with_reasoning.asdict())
+
+        # Test dict parsing functionality
+        print("\n" + "=" * 50)
+        print("TESTING DICT PARSING FUNCTIONALITY")
+        print("=" * 50)
+
+        # Test valid JSON dict parsing
+        test_parser = ArgumentParser(description="Test dict parsing")
+        OpenAILLMOptions.add_args(test_parser)
+
+        try:
+            test_args = test_parser.parse_args(
+                ["--openai-llm-reasoning", '{"effort": "low", "max_tokens": 1000}']
+            )
+            print("✓ Valid JSON dict parsing successful:")
+            print(
+                f"  Parsed reasoning: {OpenAILLMOptions.options_dict(test_args)['reasoning']}"
+            )
+        except Exception as e:
+            print(f"✗ Valid JSON dict parsing failed: {e}")
+
+        # Test invalid JSON dict parsing
+        try:
+            test_args = test_parser.parse_args(
+                [
+                    "--openai-llm-reasoning",
+                    '{"effort": "low", "max_tokens": 1000',  # Missing closing brace
+                ]
+            )
+            print("✗ Invalid JSON should have failed but didn't")
+        except SystemExit:
+            print("✓ Invalid JSON dict parsing correctly rejected")
+        except Exception as e:
+            print(f"✓ Invalid JSON dict parsing correctly rejected: {e}")
+
+        # Test non-dict JSON parsing
+        try:
+            test_args = test_parser.parse_args(
+                [
+                    "--openai-llm-reasoning",
+                    '["not", "a", "dict"]',  # Array instead of dict
+                ]
+            )
+            print("✗ Non-dict JSON should have failed but didn't")
+        except SystemExit:
+            print("✓ Non-dict JSON parsing correctly rejected")
+        except Exception as e:
+            print(f"✓ Non-dict JSON parsing correctly rejected: {e}")
+
+        print("\n" + "=" * 50)
+        print("TESTING ENVIRONMENT VARIABLE SUPPORT")
+        print("=" * 50)
+
+        # Test environment variable support for dict
+        import os
+
+        os.environ["OPENAI_LLM_REASONING"] = (
+            '{"effort": "high", "max_tokens": 3000, "exclude": false}'
+        )
+
+        env_parser = ArgumentParser(description="Test env var dict parsing")
+        OpenAILLMOptions.add_args(env_parser)
+
+        try:
+            env_args = env_parser.parse_args(
+                []
+            )  # No command line args, should use env var
+            reasoning_from_env = OpenAILLMOptions.options_dict(env_args).get(
+                "reasoning"
+            )
+            if reasoning_from_env:
+                print("✓ Environment variable dict parsing successful:")
+                print(f"  Parsed reasoning from env: {reasoning_from_env}")
+            else:
+                print("✗ Environment variable dict parsing failed: No reasoning found")
+        except Exception as e:
+            print(f"✗ Environment variable dict parsing failed: {e}")
+        finally:
+            # Clean up environment variable
+            if "OPENAI_LLM_REASONING" in os.environ:
+                del os.environ["OPENAI_LLM_REASONING"]
+
     else:
         print(BindingOptions.generate_dot_env_sample())

From 62cdc7d7eba7d5126ce107672a56c4c43b13dafd Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 21 Aug 2025 13:59:14 +0800
Subject: [PATCH 010/141] Update documentation with LLM selection guidelines
 and API improvements

---
 README-zh.md              | 2 ++
 README.md                 | 6 ++++++
 lightrag/api/README-zh.md | 5 ++++-
 lightrag/api/README.md    | 4 +++-
 4 files changed, 15 insertions(+), 2 deletions(-)

diff --git a/README-zh.md b/README-zh.md
index 5caefc89..549c27a9 100644
--- a/README-zh.md
+++ b/README-zh.md
@@ -142,6 +142,8 @@ LightRAG对大型语言模型（LLM）的能力要求远高于传统RAG，因为
 - **LLM选型**：
   - 推荐选用参数量至少为32B的LLM。
   - 上下文长度至少为32KB，推荐达到64KB。
+  - 在文档索引阶段不建议选择推理模型。
+  - 在查询阶段建议选择比索引阶段能力更强的模型，以达到更高的查询效果。
 - **Embedding模型**：
   - 高性能的Embedding模型对RAG至关重要。
   - 推荐使用主流的多语言Embedding模型，例如：BAAI/bge-m3 和 text-embedding-3-large。
diff --git a/README.md b/README.md
index 51c68a1a..892ec6d0 100644
--- a/README.md
+++ b/README.md
@@ -141,6 +141,8 @@ LightRAG's demands on the capabilities of Large Language Models (LLMs) are signi
 - **LLM Selection**:
   - It is recommended to use an LLM with at least 32 billion parameters.
   - The context length should be at least 32KB, with 64KB being recommended.
+  - It is not recommended to choose reasoning models during the document indexing stage.
+  - During the query stage, it is recommended to choose models with stronger capabilities than those used in the indexing stage to achieve better query results.
 - **Embedding Model**:
   - A high-performance Embedding model is essential for RAG.
   - We recommend using mainstream multilingual Embedding models, such as: `BAAI/bge-m3` and `text-embedding-3-large`.
@@ -1287,8 +1289,10 @@ LightRAG now seamlessly integrates with [RAG-Anything](https://github.com/HKUDS/
                     ),
                 )
             )
+
             # Initialize storage (this will load existing data if available)
             await lightrag_instance.initialize_storages()
+
             # Now initialize RAGAnything with the existing LightRAG instance
             rag = RAGAnything(
                 lightrag=lightrag_instance,  # Pass the existing LightRAG instance
@@ -1317,12 +1321,14 @@ LightRAG now seamlessly integrates with [RAG-Anything](https://github.com/HKUDS/
                 )
                 # Note: working_dir, llm_model_func, embedding_func, etc. are inherited from lightrag_instance
             )
+
             # Query the existing knowledge base
             result = await rag.query_with_multimodal(
                 "What data has been processed in this LightRAG instance?",
                 mode="hybrid"
             )
             print("Query result:", result)
+
             # Add new multimodal documents to the existing LightRAG instance
             await rag.process_document_complete(
                 file_path="path/to/new/multimodal_document.pdf",
diff --git a/lightrag/api/README-zh.md b/lightrag/api/README-zh.md
index 286b78b9..bc6352ec 100644
--- a/lightrag/api/README-zh.md
+++ b/lightrag/api/README-zh.md
@@ -357,7 +357,7 @@ API 服务器可以通过三种方式配置（优先级从高到低）：
 LightRAG 支持绑定到各种 LLM/嵌入后端：
 
 * ollama
-* openai 和 openai 兼容
+* openai (含openai 兼容)
 * azure_openai
 * lollms
 * aws_bedrock
@@ -372,7 +372,10 @@ lightrag-server --llm-binding ollama --help
 lightrag-server --embedding-binding ollama --help
 ```
 
+> 请使用openai兼容方式访问OpenRouter或vLLM部署的LLM。可以通过 `OPENAI_LLM_EXTRA_BODY` 环境变量给OpenRouter或vLLM传递额外的参数，实现推理模式的关闭或者其它个性化控制。
+
 ### 实体提取配置
+
 * ENABLE_LLM_CACHE_FOR_EXTRACT：为实体提取启用 LLM 缓存（默认：true）
 
 在测试环境中将 `ENABLE_LLM_CACHE_FOR_EXTRACT` 设置为 true 以减少 LLM 调用成本是很常见的做法。
diff --git a/lightrag/api/README.md b/lightrag/api/README.md
index 8b4f239a..9329a1af 100644
--- a/lightrag/api/README.md
+++ b/lightrag/api/README.md
@@ -360,7 +360,7 @@ Most of the configurations come with default settings; check out the details in
 LightRAG supports binding to various LLM/Embedding backends:
 
 * ollama
-* openai & openai compatible
+* openai (including openai compatible)
 * azure_openai
 * lollms
 * aws_bedrock
@@ -374,6 +374,8 @@ lightrag-server --llm-binding ollama --help
 lightrag-server --embedding-binding ollama --help
 ```
 
+> Please use OpenAI-compatible method to access LLMs deployed by OpenRouter or vLLM. You can pass additional parameters to OpenRouter or vLLM through the `OPENAI_LLM_EXTRA_BODY` environment variable to disable reasoning mode or achieve other personalized controls.
+
 ### Entity Extraction Configuration
 * ENABLE_LLM_CACHE_FOR_EXTRACT: Enable LLM cache for entity extraction (default: true)
 

From b5c230abdd5d05a3fe8150ba8a314d3ca7c5eb10 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 21 Aug 2025 16:49:24 +0800
Subject: [PATCH 011/141] optimize: avoid duplicate embedding calls in
 _build_query_context

Reduces API costs and improves query performance while maintaining backward compatibility.
---
 lightrag/operate.py | 26 ++++++++++++++++++++++++++
 lightrag/utils.py   | 19 ++++++++++++++-----
 2 files changed, 40 insertions(+), 5 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 99351097..9fefdb70 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -2112,6 +2112,26 @@ async def _build_query_context(
     # Track chunk sources and metadata for final logging
     chunk_tracking = {}  # chunk_id -> {source, frequency, order}
 
+    # Pre-compute query embedding if vector similarity method is used
+    kg_chunk_pick_method = text_chunks_db.global_config.get(
+        "kg_chunk_pick_method", DEFAULT_KG_CHUNK_PICK_METHOD
+    )
+    query_embedding = None
+    if kg_chunk_pick_method == "VECTOR" and query and chunks_vdb:
+        embedding_func_config = text_chunks_db.embedding_func
+        if embedding_func_config and embedding_func_config.func:
+            try:
+                query_embedding = await embedding_func_config.func([query])
+                query_embedding = query_embedding[
+                    0
+                ]  # Extract first embedding from batch result
+                logger.debug(
+                    "Pre-computed query embedding for vector similarity chunk selection"
+                )
+            except Exception as e:
+                logger.warning(f"Failed to pre-compute query embedding: {e}")
+                query_embedding = None
+
     # Handle local and global modes
     if query_param.mode == "local":
         local_entities, local_relations = await _get_node_data(
@@ -2372,6 +2392,7 @@ async def _build_query_context(
             query,
             chunks_vdb,
             chunk_tracking=chunk_tracking,
+            query_embedding=query_embedding,
         )
 
     # Find deduplcicated chunks from edge
@@ -2385,6 +2406,7 @@ async def _build_query_context(
             query,
             chunks_vdb,
             chunk_tracking=chunk_tracking,
+            query_embedding=query_embedding,
         )
 
     # Round-robin merge chunks from different sources with deduplication by chunk_id
@@ -2719,6 +2741,7 @@ async def _find_related_text_unit_from_entities(
     query: str = None,
     chunks_vdb: BaseVectorStorage = None,
     chunk_tracking: dict = None,
+    query_embedding=None,
 ):
     """
     Find text chunks related to entities using configurable chunk selection method.
@@ -2814,6 +2837,7 @@ async def _find_related_text_unit_from_entities(
                         num_of_chunks=num_of_chunks,
                         entity_info=entities_with_chunks,
                         embedding_func=actual_embedding_func,
+                        query_embedding=query_embedding,
                     )
 
                 if selected_chunk_ids == []:
@@ -2971,6 +2995,7 @@ async def _find_related_text_unit_from_relations(
     query: str = None,
     chunks_vdb: BaseVectorStorage = None,
     chunk_tracking: dict = None,
+    query_embedding=None,
 ):
     """
     Find text chunks related to relationships using configurable chunk selection method.
@@ -3106,6 +3131,7 @@ async def _find_related_text_unit_from_relations(
                         num_of_chunks=num_of_chunks,
                         entity_info=relations_with_chunks,
                         embedding_func=actual_embedding_func,
+                        query_embedding=query_embedding,
                     )
 
                 if selected_chunk_ids == []:
diff --git a/lightrag/utils.py b/lightrag/utils.py
index 979517b5..bec45f5f 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -1774,6 +1774,7 @@ async def pick_by_vector_similarity(
     num_of_chunks: int,
     entity_info: list[dict[str, Any]],
     embedding_func: callable,
+    query_embedding=None,
 ) -> list[str]:
     """
     Vector similarity-based text chunk selection algorithm.
@@ -1818,11 +1819,19 @@ async def pick_by_vector_similarity(
     all_chunk_ids = list(all_chunk_ids)
 
     try:
-        # Get query embedding
-        query_embedding = await embedding_func([query])
-        query_embedding = query_embedding[
-            0
-        ]  # Extract first embedding from batch result
+        # Use pre-computed query embedding if provided, otherwise compute it
+        if query_embedding is None:
+            query_embedding = await embedding_func([query])
+            query_embedding = query_embedding[
+                0
+            ]  # Extract first embedding from batch result
+            logger.debug(
+                "Computed query embedding for vector similarity chunk selection"
+            )
+        else:
+            logger.debug(
+                "Using pre-computed query embedding for vector similarity chunk selection"
+            )
 
         # Get chunk embeddings from vector database
         chunk_vectors = await chunks_vdb.get_vectors_by_ids(all_chunk_ids)

From 718025dbeae88fc6645d548b7cd16f4831172963 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 21 Aug 2025 17:55:04 +0800
Subject: [PATCH 012/141] Update embedding configuration docs and add
 aws_bedrock option

---
 env.example | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/env.example b/env.example
index 5d47a7bf..765d0b62 100644
--- a/env.example
+++ b/env.example
@@ -176,9 +176,8 @@ OLLAMA_LLM_NUM_CTX=32768
 
 ####################################################################################
 ### Embedding Configuration (Should not be changed after the first file processed)
+### EMBEDDING_BINDING: ollama, openai, azure_openai, jina, lollms, aws_bedrock
 ####################################################################################
-### Embedding Binding type: ollama, openai, azure_openai, jina,  lollms
-
 ### see also env.ollama-binding-options.example for fine tuning ollama
 EMBEDDING_BINDING=ollama
 EMBEDDING_MODEL=bge-m3:latest

From 8c6b5f4a3a7636cf9881a5a8f35f741f2a9a2319 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 21 Aug 2025 18:14:27 +0800
Subject: [PATCH 013/141] Update README

---
 README-zh.md              | 35 +++++++++++++++++++-----
 README.md                 | 30 ++++++++++++++++++---
 lightrag/api/README-zh.md | 56 ++++-----------------------------------
 lightrag/api/README.md    | 51 ++---------------------------------
 4 files changed, 62 insertions(+), 110 deletions(-)

diff --git a/README-zh.md b/README-zh.md
index 549c27a9..de80a076 100644
--- a/README-zh.md
+++ b/README-zh.md
@@ -789,7 +789,7 @@ MongoDocStatusStorage       MongoDB
 每一种存储类型的链接配置范例可以在 `env.example` 文件中找到。链接字符串中的数据库实例是需要你预先在数据库服务器上创建好的，LightRAG 仅负责在数据库实例中创建数据表，不负责创建数据库实例。如果使用 Redis 作为存储，记得给 Redis 配置自动持久化数据规则，否则 Redis 服务重启后数据会丢失。如果使用PostgreSQL数据库，推荐使用16.6版本或以上。
 
 <details>
-<summary> <b>使用Neo4J进行存储</b> </summary>
+<summary> <b>使用Neo4J存储</b> </summary>
 
 * 对于生产级场景，您很可能想要利用企业级解决方案
 * 进行KG存储。推荐在Docker中运行Neo4J以进行无缝本地测试。
@@ -827,7 +827,7 @@ async def initialize_rag():
 </details>
 
 <details>
-<summary> <b>使用Faiss进行存储</b> </summary>
+<summary> <b>使用Faiss存储</b> </summary>
 在使用Faiss向量数据库之前必须手工安装`faiss-cpu`或`faiss-gpu`。
 
 - 安装所需依赖：
@@ -864,18 +864,39 @@ rag = LightRAG(
 </details>
 
 <details>
-<summary> <b>使用PostgreSQL进行存储</b> </summary>
+<summary> <b>使用PostgreSQL存储</b> </summary>
 
-对于生产级场景，您很可能想要利用企业级解决方案。PostgreSQL可以为您提供一站式解决方案，作为KV存储、向量数据库（pgvector）和图数据库（apache AGE）。支持 PostgreSQL 版本为16.6或以上。
+对于生产级场景，您很可能想要利用企业级解决方案。PostgreSQL可以为您提供一站式储解解决方案，作为KV存储、向量数据库（pgvector）和图数据库（apache AGE）。支持 PostgreSQL 版本为16.6或以上。
 
-* PostgreSQL很轻量，整个二进制发行版包括所有必要的插件可以压缩到40MB：参考[Windows发布版](https://github.com/ShanGor/apache-age-windows/releases/tag/PG17%2Fv1.5.0-rc0)，它在Linux/Mac上也很容易安装。
 * 如果您是初学者并想避免麻烦，推荐使用docker，请从这个镜像开始（请务必阅读概述）：https://hub.docker.com/r/shangor/postgres-for-rag
-* 如何开始？参考：[examples/lightrag_zhipu_postgres_demo.py](https://github.com/HKUDS/LightRAG/blob/main/examples/lightrag_zhipu_postgres_demo.py)
-
 * Apache AGE的性能不如Neo4j。最求高性能的图数据库请使用Noe4j。
 
 </details>
 
+<details>
+<summary> <b>使用MogonDB存储</b> </summary>
+
+MongoDB为LightRAG提供了一站式的存储解决方案。MongoDB提供原生的KV存储和向量存储。LightRAG使用MogoDB的集合实现了一个简易的图存储。MongoDB 官方的向量检索功能（`$vectorSearch`）目前必须依赖其官方的云服务 MongoDB Atlas。无法在自托管的 MongoDB Community/Enterprise 版本上使用此功能。
+
+</details>
+
+<details>
+<summary> <b>使用Redis存储</b> </summary>
+
+LightRAG支持使用Reidis作为KV存储。使用Redis存储的时候需要注意进行持久化配置和内存使用量配置。以下是推荐的redis配置
+
+```
+save 900 1
+save 300 10
+save 60 1000
+stop-writes-on-bgsave-error yes
+maxmemory 4gb
+maxmemory-policy noeviction
+maxclients 500
+```
+
+</details>
+
 ### LightRAG实例间的数据隔离
 
 通过 workspace 参数可以不同实现不同LightRAG实例之间的存储数据隔离。LightRAG在初始化后workspace就已经确定，之后修改workspace是无效的。下面是不同类型的存储实现工作空间的方式：
diff --git a/README.md b/README.md
index 892ec6d0..3bbd39be 100644
--- a/README.md
+++ b/README.md
@@ -800,7 +800,7 @@ MongoDocStatusStorage       MongoDB
 Example connection configurations for each storage type can be found in the `env.example` file. The database instance in the connection string needs to be created by you on the database server beforehand. LightRAG is only responsible for creating tables within the database instance, not for creating the database instance itself. If using Redis as storage, remember to configure automatic data persistence rules for Redis, otherwise data will be lost after the Redis service restarts. If using PostgreSQL, it is recommended to use version 16.6 or above.
 
 <details>
-<summary> <b>Using Neo4J for Storage</b> </summary>
+<summary> <b>Using Neo4J Storage</b> </summary>
 
 * For production level scenarios you will most likely want to leverage an enterprise solution
 * for KG storage. Running Neo4J in Docker is recommended for seamless local testing.
@@ -839,7 +839,7 @@ see test_neo4j.py for a working example.
 </details>
 
 <details>
-<summary> <b>Using PostgreSQL for Storage</b> </summary>
+<summary> <b>Using PostgreSQL Storage</b> </summary>
 
 For production level scenarios you will most likely want to leverage an enterprise solution. PostgreSQL can provide a one-stop solution for you as KV store, VectorDB (pgvector) and GraphDB (apache AGE). PostgreSQL version 16.6 or higher is supported.
 
@@ -851,7 +851,7 @@ For production level scenarios you will most likely want to leverage an enterpri
 </details>
 
 <details>
-<summary> <b>Using Faiss for Storage</b> </summary>
+<summary> <b>Using Faiss Storage</b> </summary>
 Before using Faiss vector database, you must manually install `faiss-cpu` or `faiss-gpu`.
 
 - Install the required dependencies:
@@ -922,6 +922,30 @@ async def initialize_rag():
 
 </details>
 
+<details>
+<summary> <b>Using MongoDB Storage</b> </summary>
+
+MongoDB provides a one-stop storage solution for LightRAG. MongoDB offers native KV storage and vector storage. LightRAG uses MongoDB collections to implement a simple graph storage. MongoDB's official vector search functionality (`$vectorSearch`) currently requires their official cloud service MongoDB Atlas. This functionality cannot be used on self-hosted MongoDB Community/Enterprise versions.
+
+</details>
+
+<details>
+<summary> <b>Using Redis Storage</b> </summary>
+
+LightRAG supports using Redis as KV storage. When using Redis storage, attention should be paid to persistence configuration and memory usage configuration. The following is the recommended Redis configuration:
+
+```
+save 900 1
+save 300 10
+save 60 1000
+stop-writes-on-bgsave-error yes
+maxmemory 4gb
+maxmemory-policy noeviction
+maxclients 500
+```
+
+</details>
+
 ### Data Isolation Between LightRAG Instances
 
 The `workspace` parameter ensures data isolation between different LightRAG instances. Once initialized, the `workspace` is immutable and cannot be changed.Here is how workspaces are implemented for different types of storage:
diff --git a/lightrag/api/README-zh.md b/lightrag/api/README-zh.md
index bc6352ec..b6e2892c 100644
--- a/lightrag/api/README-zh.md
+++ b/lightrag/api/README-zh.md
@@ -389,51 +389,9 @@ LightRAG 使用 4 种类型的存储用于不同目的：
 * GRAPH_STORAGE：实体关系图
 * DOC_STATUS_STORAGE：文档索引状态
 
-每种存储类型都有几种实现：
+每种存储类型都有多种存储实现方式。LightRAG Server默认的存储实现为内存数据库，数据通过文件持久化保存到WORKING_DIR目录。LightRAG还支持PostgreSQL、MongoDB、FAISS、Milvus、Qdrant、Neo4j、Memgraph和Redis等存储实现方式。详细的存储支持方式请参考根目录下的`README.md`文件中关于存储的相关内容。
 
-* KV_STORAGE 支持的实现名称
-
-```
-JsonKVStorage    JsonFile(默认)
-PGKVStorage      Postgres
-RedisKVStorage   Redis
-MongoKVStorage   MogonDB
-```
-
-* GRAPH_STORAGE 支持的实现名称
-
-```
-NetworkXStorage      NetworkX(默认)
-Neo4JStorage         Neo4J
-PGGraphStorage       PostgreSQL with AGE plugin
-```
-
-> 在测试中Neo4j图形数据库相比PostgreSQL AGE有更好的性能表现。
-
-* VECTOR_STORAGE 支持的实现名称
-
-```
-NanoVectorDBStorage         NanoVector(默认)
-PGVectorStorage             Postgres
-MilvusVectorDBStorge        Milvus
-FaissVectorDBStorage        Faiss
-QdrantVectorDBStorage       Qdrant
-MongoVectorDBStorage        MongoDB
-```
-
-* DOC_STATUS_STORAGE 支持的实现名称
-
-```
-JsonDocStatusStorage        JsonFile(默认)
-PGDocStatusStorage          Postgres
-MongoDocStatusStorage       MongoDB
-```
-
-每一种存储类型的链接配置范例可以在 `env.example` 文件中找到。链接字符串中的数据库实例是需要你预先在数据库服务器上创建好的，LightRAG 仅负责在数据库实例中创建数据表，不负责创建数据库实例。如果使用 Redis 作为存储，记得给 Redis 配置自动持久化数据规则，否则 Redis 服务重启后数据会丢失。如果使用PostgreSQL数据库，推荐使用16.6版本或以上。
-
-### 如何选择存储实现
-
-您可以通过环境变量选择存储实现。在首次启动 API 服务器之前，您可以将以下环境变量设置为特定的存储实现名称：
+您可以通过环境变量选择存储实现。例如，在首次启动 API 服务器之前，您可以将以下环境变量设置为特定的存储实现名称：
 
 ```
 LIGHTRAG_KV_STORAGE=PGKVStorage
@@ -442,7 +400,7 @@ LIGHTRAG_GRAPH_STORAGE=PGGraphStorage
 LIGHTRAG_DOC_STATUS_STORAGE=PGDocStatusStorage
 ```
 
-在向 LightRAG 添加文档后，您不能更改存储实现选择。目前尚不支持从一个存储实现迁移到另一个存储实现。更多信息请阅读示例 env 文件或 config.ini 文件。
+在向 LightRAG 添加文档后，您不能更改存储实现选择。目前尚不支持从一个存储实现迁移到另一个存储实现。更多配置信息请阅读示例 `env.exampl`e文件。
 
 ### LightRag API 服务器命令行选项
 
@@ -453,18 +411,14 @@ LIGHTRAG_DOC_STATUS_STORAGE=PGDocStatusStorage
 | --working-dir | ./rag_storage | RAG 存储的工作目录 |
 | --input-dir | ./inputs | 包含输入文档的目录 |
 | --max-async | 4 | 最大异步操作数 |
-| --max-tokens | 32768 | 最大 token 大小 |
-| --timeout | 150 | 超时时间（秒）。None 表示无限超时（不推荐） |
 | --log-level | INFO | 日志级别（DEBUG、INFO、WARNING、ERROR、CRITICAL） |
 | --verbose | - | 详细调试输出（True、False） |
 | --key | None | 用于认证的 API 密钥。保护 lightrag 服务器免受未授权访问 |
 | --ssl | False | 启用 HTTPS |
 | --ssl-certfile | None | SSL 证书文件路径（如果启用 --ssl 则必需） |
 | --ssl-keyfile | None | SSL 私钥文件路径（如果启用 --ssl 则必需） |
-| --top-k | 50 | 要检索的 top-k 项目数；在"local"模式下对应实体，在"global"模式下对应关系。 |
-| --cosine-threshold | 0.4 | 节点和关系检索的余弦阈值，与 top-k 一起控制节点和关系的检索。 |
-| --llm-binding | ollama | LLM 绑定类型（lollms、ollama、openai、openai-ollama、azure_openai） |
-| --embedding-binding | ollama | 嵌入绑定类型（lollms、ollama、openai、azure_openai） |
+| --llm-binding | ollama | LLM 绑定类型（lollms、ollama、openai、openai-ollama、azure_openai、aws_bedrock） |
+| --embedding-binding | ollama | 嵌入绑定类型（lollms、ollama、openai、azure_openai、aws_bedrock） |
 | auto-scan-at-startup | - | 扫描输入目录中的新文件并开始索引 |
 
 ### .env 文件示例
diff --git a/lightrag/api/README.md b/lightrag/api/README.md
index 9329a1af..3695bc3d 100644
--- a/lightrag/api/README.md
+++ b/lightrag/api/README.md
@@ -390,52 +390,9 @@ LightRAG uses 4 types of storage for different purposes:
 * GRAPH_STORAGE: entity relation graph
 * DOC_STATUS_STORAGE: document indexing status
 
-Each storage type has several implementations:
+LightRAG Server offers various storage implementations, with the default being an in-memory database that persists data to the WORKING_DIR directory. Additionally, LightRAG supports a wide range of storage solutions including PostgreSQL, MongoDB, FAISS, Milvus, Qdrant, Neo4j, Memgraph, and Redis. For detailed information on supported storage options, please refer to the storage section in the README.md file located in the root directory.
 
-* KV_STORAGE supported implementations:
-
-```
-JsonKVStorage    JsonFile (default)
-PGKVStorage      Postgres
-RedisKVStorage   Redis
-MongoKVStorage   MongoDB
-```
-
-* GRAPH_STORAGE supported implementations:
-
-```
-NetworkXStorage      NetworkX (default)
-Neo4JStorage         Neo4J
-PGGraphStorage       PostgreSQL with AGE plugin
-MemgraphStorage.     Memgraph
-```
-
-> Testing has shown that Neo4J delivers superior performance in production environments compared to PostgreSQL with AGE plugin.
-
-* VECTOR_STORAGE supported implementations:
-
-```
-NanoVectorDBStorage         NanoVector (default)
-PGVectorStorage             Postgres
-MilvusVectorDBStorage       Milvus
-FaissVectorDBStorage        Faiss
-QdrantVectorDBStorage       Qdrant
-MongoVectorDBStorage        MongoDB
-```
-
-* DOC_STATUS_STORAGE: supported implementations:
-
-```
-JsonDocStatusStorage        JsonFile (default)
-PGDocStatusStorage          Postgres
-MongoDocStatusStorage       MongoDB
-```
-Example connection configurations for each storage type can be found in the `env.example` file. The database instance in the connection string needs to be created by you on the database server beforehand. LightRAG is only responsible for creating tables within the database instance, not for creating the database instance itself. If using Redis as storage, remember to configure automatic data persistence rules for Redis, otherwise data will be lost after the Redis service restarts. If using PostgreSQL, it is recommended to use version 16.6 or above.
-
-
-### How to Select Storage Implementation
-
-You can select storage implementation by environment variables. You can set the following environment variables to a specific storage implementation name before the first start of the API Server:
+You can select the storage implementation by configuring environment variables. For instance, prior to the initial launch of the API server, you can set the following environment variable to specify your desired storage implementation:
 
 ```
 LIGHTRAG_KV_STORAGE=PGKVStorage
@@ -455,16 +412,12 @@ You cannot change storage implementation selection after adding documents to Lig
 | --working-dir         | ./rag_storage | Working directory for RAG storage                                                                                               |
 | --input-dir           | ./inputs      | Directory containing input documents                                                                                            |
 | --max-async           | 4             | Maximum number of async operations                                                                                              |
-| --max-tokens          | 32768         | Maximum token size                                                                                                              |
-| --timeout             | 150           | Timeout in seconds. None for infinite timeout (not recommended)                                                                 |
 | --log-level           | INFO          | Logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)                                                                           |
 | --verbose             | -             | Verbose debug output (True, False)                                                                                              |
 | --key                 | None          | API key for authentication. Protects the LightRAG server against unauthorized access                                            |
 | --ssl                 | False         | Enable HTTPS                                                                                                                    |
 | --ssl-certfile        | None          | Path to SSL certificate file (required if --ssl is enabled)                                                                     |
 | --ssl-keyfile         | None          | Path to SSL private key file (required if --ssl is enabled)                                                                     |
-| --top-k               | 50            | Number of top-k items to retrieve; corresponds to entities in "local" mode and relationships in "global" mode.                  |
-| --cosine-threshold    | 0.4           | The cosine threshold for nodes and relation retrieval, works with top-k to control the retrieval of nodes and relations.        |
 | --llm-binding         | ollama        | LLM binding type (lollms, ollama, openai, openai-ollama, azure_openai, aws_bedrock)                                                          |
 | --embedding-binding   | ollama        | Embedding binding type (lollms, ollama, openai, azure_openai, aws_bedrock)                                                                   |
 | --auto-scan-at-startup| -             | Scan input directory for new files and start indexing                                                                           |

From b4db084816f7edb4179166fef5f544154eb1b0f1 Mon Sep 17 00:00:00 2001
From: Onesoft <onesoftqwq@163.com>
Date: Thu, 21 Aug 2025 20:01:41 +0800
Subject: [PATCH 014/141] Update README-zh.md

---
 README-zh.md | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/README-zh.md b/README-zh.md
index de80a076..5a103d68 100644
--- a/README-zh.md
+++ b/README-zh.md
@@ -50,7 +50,8 @@
 
 ## 🎉 新闻
 
-- [X] [2025.06.05]🎯📢LightRAG现已集成RAG-Anything，支持全面的多模态文档解析与RAG能力（PDF、图片、Office文档、表格、公式等）。详见下方[多模态处理模块](https://github.com/HKUDS/LightRAG?tab=readme-ov-file#多模态文档处理rag-anything集成)。
+- [X] [2025.06.16]🎯📢我们的团队发布了[RAG-Anything](https://github.com/HKUDS/RAG-Anything)，一个用于无缝处理文本、图像、表格和方程式的全功能多模态 RAG 系统。
+- [X] [2025.06.05]🎯📢LightRAG现已集成[RAG-Anything](https://github.com/HKUDS/RAG-Anything)，支持全面的多模态文档解析与RAG能力（PDF、图片、Office文档、表格、公式等）。详见下方[多模态处理模块](https://github.com/HKUDS/LightRAG?tab=readme-ov-file#多模态文档处理rag-anything集成)。
 - [X] [2025.03.18]🎯📢LightRAG现已支持引文功能。
 - [X] [2025.02.05]🎯📢我们团队发布了[VideoRAG](https://github.com/HKUDS/VideoRAG)，用于理解超长上下文视频。
 - [X] [2025.01.13]🎯📢我们团队发布了[MiniRAG](https://github.com/HKUDS/MiniRAG)，使用小型模型简化RAG。

From ec1bf4366705af7f56509daac5b46d4f6faf7ba0 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 21 Aug 2025 22:53:24 +0800
Subject: [PATCH 015/141] fix(webui): preserve current page when pipeline
 status changes

- Add intelligent refresh function to handle boundary cases
- Replace manual refresh with smart page preservation logic
- Auto-redirect to last page when current page becomes invalid
- Maintain user's browsing position during pipeline start/stop
- Fix issue where document list would reset to first page after pipeline operations
---
 .../src/features/DocumentManager.tsx          | 100 +++++++++++++-----
 1 file changed, 71 insertions(+), 29 deletions(-)

diff --git a/lightrag_webui/src/features/DocumentManager.tsx b/lightrag_webui/src/features/DocumentManager.tsx
index 01f08df5..3e065ddf 100644
--- a/lightrag_webui/src/features/DocumentManager.tsx
+++ b/lightrag_webui/src/features/DocumentManager.tsx
@@ -469,22 +469,42 @@ export default function DocumentManager() {
     };
   }, [docs]);
 
-  // New paginated data fetching function
-  const fetchPaginatedDocuments = useCallback(async (
-    page: number,
-    pageSize: number,
-    statusFilter: StatusFilter
+  // Utility function to update component state
+  const updateComponentState = useCallback((response: any) => {
+    setPagination(response.pagination);
+    setCurrentPageDocs(response.documents);
+    setStatusCounts(response.status_counts);
+
+    // Update legacy docs state for backward compatibility
+    const legacyDocs: DocsStatusesResponse = {
+      statuses: {
+        processed: response.documents.filter((doc: DocStatusResponse) => doc.status === 'processed'),
+        processing: response.documents.filter((doc: DocStatusResponse) => doc.status === 'processing'),
+        pending: response.documents.filter((doc: DocStatusResponse) => doc.status === 'pending'),
+        failed: response.documents.filter((doc: DocStatusResponse) => doc.status === 'failed')
+      }
+    };
+
+    setDocs(response.pagination.total_count > 0 ? legacyDocs : null);
+  }, []);
+
+  // Intelligent refresh function: handles all boundary cases
+  const handleIntelligentRefresh = useCallback(async (
+    targetPage?: number, // Optional target page, defaults to current page
+    resetToFirst?: boolean // Whether to force reset to first page
   ) => {
     try {
       if (!isMountedRef.current) return;
 
       setIsRefreshing(true);
 
-      // Prepare request parameters
+      // Determine target page
+      const pageToFetch = resetToFirst ? 1 : (targetPage || pagination.page);
+
       const request: DocumentsRequest = {
         status_filter: statusFilter === 'all' ? null : statusFilter,
-        page,
-        page_size: pageSize,
+        page: pageToFetch,
+        page_size: pagination.page_size,
         sort_field: sortField,
         sort_direction: sortDirection
       };
@@ -493,27 +513,35 @@ export default function DocumentManager() {
 
       if (!isMountedRef.current) return;
 
-      // Update pagination state
-      setPagination(response.pagination);
-      setCurrentPageDocs(response.documents);
-      setStatusCounts(response.status_counts);
+      // Boundary case handling: if target page has no data but total count > 0
+      if (response.documents.length === 0 && response.pagination.total_count > 0) {
+        // Calculate last page
+        const lastPage = Math.max(1, response.pagination.total_pages);
 
-      // Update legacy docs state for backward compatibility
-      const legacyDocs: DocsStatusesResponse = {
-        statuses: {
-          processed: response.documents.filter(doc => doc.status === 'processed'),
-          processing: response.documents.filter(doc => doc.status === 'processing'),
-          pending: response.documents.filter(doc => doc.status === 'pending'),
-          failed: response.documents.filter(doc => doc.status === 'failed')
+        if (pageToFetch !== lastPage) {
+          // Re-request last page
+          const lastPageRequest: DocumentsRequest = {
+            ...request,
+            page: lastPage
+          };
+
+          const lastPageResponse = await getDocumentsPaginated(lastPageRequest);
+
+          if (!isMountedRef.current) return;
+
+          // Update page state to last page
+          setPageByStatus(prev => ({ ...prev, [statusFilter]: lastPage }));
+          updateComponentState(lastPageResponse);
+          return;
         }
-      };
-
-      if (response.pagination.total_count > 0) {
-        setDocs(legacyDocs);
-      } else {
-        setDocs(null);
       }
 
+      // Normal case: update state
+      if (pageToFetch !== pagination.page) {
+        setPageByStatus(prev => ({ ...prev, [statusFilter]: pageToFetch }));
+      }
+      updateComponentState(response);
+
     } catch (err) {
       if (isMountedRef.current) {
         toast.error(t('documentPanel.documentManager.errors.loadFailed', { error: errorMessage(err) }));
@@ -523,7 +551,20 @@ export default function DocumentManager() {
         setIsRefreshing(false);
       }
     }
-  }, [sortField, sortDirection, t]);
+  }, [statusFilter, pagination.page, pagination.page_size, sortField, sortDirection, t, updateComponentState]);
+
+  // New paginated data fetching function
+  const fetchPaginatedDocuments = useCallback(async (
+    page: number,
+    pageSize: number,
+    _statusFilter: StatusFilter // eslint-disable-line @typescript-eslint/no-unused-vars
+  ) => {
+    // Update pagination state
+    setPagination(prev => ({ ...prev, page, page_size: pageSize }));
+
+    // Use intelligent refresh
+    await handleIntelligentRefresh(page);
+  }, [handleIntelligentRefresh]);
 
   // Legacy fetchDocuments function for backward compatibility
   const fetchDocuments = useCallback(async () => {
@@ -678,9 +719,10 @@ export default function DocumentManager() {
     if (prevPipelineBusyRef.current !== undefined && prevPipelineBusyRef.current !== pipelineBusy) {
       // pipelineBusy state has changed, trigger immediate refresh
       if (currentTab === 'documents' && health && isMountedRef.current) {
-        handleManualRefresh();
+        // Use intelligent refresh to preserve current page
+        handleIntelligentRefresh();
 
-        // Reset polling timer after manual refresh
+        // Reset polling timer after intelligent refresh
         const hasActiveDocuments = (statusCounts.processing || 0) > 0 || (statusCounts.pending || 0) > 0;
         const pollingInterval = hasActiveDocuments ? 5000 : 30000;
         startPollingInterval(pollingInterval);
@@ -688,7 +730,7 @@ export default function DocumentManager() {
     }
     // Update the previous state
     prevPipelineBusyRef.current = pipelineBusy;
-  }, [pipelineBusy, currentTab, health, handleManualRefresh, statusCounts.processing, statusCounts.pending, startPollingInterval]);
+  }, [pipelineBusy, currentTab, health, handleIntelligentRefresh, statusCounts.processing, statusCounts.pending, startPollingInterval]);
 
   // Set up intelligent polling with dynamic interval based on document status
   useEffect(() => {

From 105fb43a545fe71a124d5d29acbb142a946b5453 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 21 Aug 2025 22:56:44 +0800
Subject: [PATCH 016/141] Updat webui assets and bump api version to 0206

---
 lightrag/api/__init__.py                      |  2 +-
 .../assets/feature-documents-BSJWpkhB.js      | 87 -------------------
 .../assets/feature-documents-Di_Wt0BY.js      | 87 +++++++++++++++++++
 ...SZozC.js => feature-retrieval-DVuOAaIQ.js} |  2 +-
 .../{index-Ctn6Ym96.js => index-B90LgL3h.js}  |  2 +-
 lightrag/api/webui/index.html                 |  6 +-
 6 files changed, 93 insertions(+), 93 deletions(-)
 delete mode 100644 lightrag/api/webui/assets/feature-documents-BSJWpkhB.js
 create mode 100644 lightrag/api/webui/assets/feature-documents-Di_Wt0BY.js
 rename lightrag/api/webui/assets/{feature-retrieval-kyTSZozC.js => feature-retrieval-DVuOAaIQ.js} (99%)
 rename lightrag/api/webui/assets/{index-Ctn6Ym96.js => index-B90LgL3h.js} (99%)

diff --git a/lightrag/api/__init__.py b/lightrag/api/__init__.py
index 39c729cd..d7154027 100644
--- a/lightrag/api/__init__.py
+++ b/lightrag/api/__init__.py
@@ -1 +1 @@
-__api_version__ = "0205"
+__api_version__ = "0206"
diff --git a/lightrag/api/webui/assets/feature-documents-BSJWpkhB.js b/lightrag/api/webui/assets/feature-documents-BSJWpkhB.js
deleted file mode 100644
index 1c2c5bcf..00000000
--- a/lightrag/api/webui/assets/feature-documents-BSJWpkhB.js
+++ /dev/null
@@ -1,87 +0,0 @@
-import{j as t,E as Wa,I as Dt,F as Ga,G as Va,H as Nt,J as Ya,V as zt,L as Ja,K as Qa,M as Ct,N as Pt,Q as Xa,U as St,W as Et,X as _t,_ as ge,d as Ft}from"./ui-vendor-CeCm8EER.js";import{r as o,g as Za,R as Tt}from"./react-vendor-DEwriMA6.js";import{c as E,C as et,a as At,b as Ot,d as oa,F as Rt,e as sa,f as at,u as me,s as Mt,g as O,U as la,S as It,h as tt,B as T,X as nt,i as qt,j as ae,D as qe,k as ha,l as Le,m as Be,n as Ue,o as $e,p as Lt,q as Bt,E as Ut,T as it,I as Oe,r as ot,t as st,L as $t,v as Ht,w as Kt,x as ba,y as ya,z as Wt,A as Gt,G as Vt,H as Yt,J as Jt,K as Qt,M as Ce,N as Pe,O as ja,P as wa,Q as Xt,R as ka,V as Da,W as Zt,Y as en,Z as an,_ as Qe,$ as Xe}from"./feature-graph-C6IuADHZ.js";const Na=St,yi=_t,za=Et,ra=o.forwardRef(({className:e,children:a,...n},i)=>t.jsxs(Wa,{ref:i,className:E("border-input bg-background ring-offset-background placeholder:text-muted-foreground focus:ring-ring flex h-10 w-full items-center justify-between rounded-md border px-3 py-2 text-sm 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diff --git a/lightrag/api/webui/assets/feature-documents-Di_Wt0BY.js b/lightrag/api/webui/assets/feature-documents-Di_Wt0BY.js
new file mode 100644
index 00000000..dc984898
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+  transition: opacity 0.15s, visibility 0.15s;
+}
+
+.tooltip.visible {
+  opacity: 1;
+  visibility: visible;
+}
+
+.dark .tooltip {
+  background-color: rgba(255, 255, 255, 0.95);
+  color: black;
+}
+
+/* Position tooltip helper class */
+.tooltip-helper {
+  position: absolute;
+  visibility: hidden;
+  pointer-events: none;
+  top: 0;
+  left: 0;
+  width: 100%;
+  height: 0;
+}
+
+@keyframes pulse {
+  0% {
+    background-color: rgb(255 0 0 / 0.1);
+    border-color: rgb(255 0 0 / 0.2);
+  }
+  50% {
+    background-color: rgb(255 0 0 / 0.2);
+    border-color: rgb(255 0 0 / 0.4);
+  }
+  100% {
+    background-color: rgb(255 0 0 / 0.1);
+    border-color: rgb(255 0 0 / 0.2);
+  }
+}
+
+.dark .pipeline-busy {
+  animation: dark-pulse 2s infinite;
+}
+
+@keyframes dark-pulse {
+  0% {
+    background-color: rgb(255 0 0 / 0.2);
+    border-color: rgb(255 0 0 / 0.4);
+  }
+  50% {
+    background-color: rgb(255 0 0 / 0.3);
+    border-color: rgb(255 0 0 / 0.6);
+  }
+  100% {
+    background-color: rgb(255 0 0 / 0.2);
+    border-color: rgb(255 0 0 / 0.4);
+  }
+}
+
+.pipeline-busy {
+  animation: pulse 2s infinite;
+  border: 1px solid;
+}
+`;function ji(){const e=s.useRef(!0);s.useEffect(()=>{e.current=!0;const o=()=>{e.current=!1};return window.addEventListener("beforeunload",o),()=>{e.current=!1,window.removeEventListener("beforeunload",o)}},[]);const[a,n]=s.useState(!1),{t:i,i18n:l}=fe(),c=Ee.use.health(),r=Ee.use.pipelineBusy(),[p,k]=s.useState(null),x=_e.use.currentTab(),v=_e.use.showFileName(),E=_e.use.setShowFileName(),y=_e.use.documentsPageSize(),j=_e.use.setDocumentsPageSize(),[,C]=s.useState([]),[h,N]=s.useState({page:1,page_size:y,total_count:0,total_pages:0,has_next:!1,has_prev:!1}),[g,H]=s.useState({all:0}),[q,P]=s.useState(!1),[u,z]=s.useState("updated_at"),[D,L]=s.useState("desc"),[w,V]=s.useState("all"),[xe,I]=s.useState({all:1,processed:1,processing:1,pending:1,failed:1}),[W,R]=s.useState([]),U=W.length>0,ze=s.useCallback((o,d)=>{R(f=>d?[...f,o]:f.filter(b=>b!==o))},[]),se=s.useCallback(()=>{R([])},[]),ee=o=>{let d=o;o==="id"&&(d=v?"file_path":"id");const 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diff --git a/lightrag/api/webui/assets/feature-retrieval-kyTSZozC.js b/lightrag/api/webui/assets/feature-retrieval-DVuOAaIQ.js
similarity index 99%
rename from lightrag/api/webui/assets/feature-retrieval-kyTSZozC.js
rename to lightrag/api/webui/assets/feature-retrieval-DVuOAaIQ.js
index d258bd39..4a1303f3 100644
--- a/lightrag/api/webui/assets/feature-retrieval-kyTSZozC.js
+++ b/lightrag/api/webui/assets/feature-retrieval-DVuOAaIQ.js
@@ -1,5 +1,5 @@
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diff --git a/lightrag/api/webui/assets/index-Ctn6Ym96.js b/lightrag/api/webui/assets/index-B90LgL3h.js
similarity index 99%
rename from lightrag/api/webui/assets/index-Ctn6Ym96.js
rename to lightrag/api/webui/assets/index-B90LgL3h.js
index 32ad41f7..c96c2eed 100644
--- a/lightrag/api/webui/assets/index-Ctn6Ym96.js
+++ b/lightrag/api/webui/assets/index-B90LgL3h.js
@@ -1,4 +1,4 @@
-import{j as o,Y as td,O as fg,k as dg,u as ad,Z as mg,c as hg,l as gg,g as pg,S as yg,T as vg,n as bg,m as nd,o as Sg,p as Tg,$ as ud,a0 as id,a1 as cd,a2 as xg}from"./ui-vendor-CeCm8EER.js";import{d as Ag,h as Dg,r as E,u as sd,H as Ng,i as Eg,j as kf}from"./react-vendor-DEwriMA6.js";import{N as we,c as Ve,ad as od,u as Bl,M as sl,ae as rd,af as fd,I as us,B as Cn,D as Mg,l as zg,m as Cg,n as Og,o as _g,ag as Rg,ah as jg,ai as Ug,aj as Hg,ak as ql,al as dd,am as ss,an as is,a0 as Lg,a1 as qg,a2 as Bg,a3 as Gg,ao as Yg,ap as Xg,aq as md,ar as wg,as as hd,at as Vg,au as gd,d as Qg,R as Kg,V as Zg,g as En,av as kg,aw as Jg,ax as Fg}from"./feature-graph-C6IuADHZ.js";import{S as Jf,a as Ff,b as Pf,c as $f,e as rt,D as Pg}from"./feature-documents-BSJWpkhB.js";import{R as $g}from"./feature-retrieval-kyTSZozC.js";import{i as cs}from"./utils-vendor-BysuhMZA.js";import"./graph-vendor-B-X5JegA.js";import"./mermaid-vendor-CAxUo7Zk.js";import"./markdown-vendor-DmIvJdn7.js";(function(){const y=document.createElement("link").relList;if(y&&y.supports&&y.supports("modulepreload"))return;for(const N of document.querySelectorAll('link[rel="modulepreload"]'))d(N);new MutationObserver(N=>{for(const _ of N)if(_.type==="childList")for(const H of _.addedNodes)H.tagName==="LINK"&&H.rel==="modulepreload"&&d(H)}).observe(document,{childList:!0,subtree:!0});function x(N){const _={};return N.integrity&&(_.integrity=N.integrity),N.referrerPolicy&&(_.referrerPolicy=N.referrerPolicy),N.crossOrigin==="use-credentials"?_.credentials="include":N.crossOrigin==="anonymous"?_.credentials="omit":_.credentials="same-origin",_}function d(N){if(N.ep)return;N.ep=!0;const _=x(N);fetch(N.href,_)}})();var ts={exports:{}},Mn={},as={exports:{}},ns={};/**
+import{j as o,Y as td,O as fg,k as dg,u as ad,Z as mg,c as hg,l as gg,g as pg,S as yg,T as vg,n as bg,m as nd,o as Sg,p as Tg,$ as ud,a0 as id,a1 as cd,a2 as xg}from"./ui-vendor-CeCm8EER.js";import{d as Ag,h as Dg,r as E,u as sd,H as Ng,i as Eg,j as kf}from"./react-vendor-DEwriMA6.js";import{N as we,c as Ve,ad as od,u as Bl,M as sl,ae as rd,af as fd,I as us,B as Cn,D as Mg,l as zg,m as Cg,n as Og,o as _g,ag as Rg,ah as jg,ai as Ug,aj as Hg,ak as ql,al as dd,am as ss,an as is,a0 as Lg,a1 as qg,a2 as Bg,a3 as Gg,ao as Yg,ap as Xg,aq as md,ar as wg,as as hd,at as Vg,au as gd,d as Qg,R as Kg,V as Zg,g as En,av as kg,aw as Jg,ax as Fg}from"./feature-graph-C6IuADHZ.js";import{S as Jf,a as Ff,b as Pf,c as $f,e as rt,D as Pg}from"./feature-documents-Di_Wt0BY.js";import{R as $g}from"./feature-retrieval-DVuOAaIQ.js";import{i as cs}from"./utils-vendor-BysuhMZA.js";import"./graph-vendor-B-X5JegA.js";import"./mermaid-vendor-CAxUo7Zk.js";import"./markdown-vendor-DmIvJdn7.js";(function(){const y=document.createElement("link").relList;if(y&&y.supports&&y.supports("modulepreload"))return;for(const N of document.querySelectorAll('link[rel="modulepreload"]'))d(N);new MutationObserver(N=>{for(const _ of N)if(_.type==="childList")for(const H of _.addedNodes)H.tagName==="LINK"&&H.rel==="modulepreload"&&d(H)}).observe(document,{childList:!0,subtree:!0});function x(N){const _={};return N.integrity&&(_.integrity=N.integrity),N.referrerPolicy&&(_.referrerPolicy=N.referrerPolicy),N.crossOrigin==="use-credentials"?_.credentials="include":N.crossOrigin==="anonymous"?_.credentials="omit":_.credentials="same-origin",_}function d(N){if(N.ep)return;N.ep=!0;const _=x(N);fetch(N.href,_)}})();var ts={exports:{}},Mn={},as={exports:{}},ns={};/**
  * @license React
  * scheduler.production.js
  *
diff --git a/lightrag/api/webui/index.html b/lightrag/api/webui/index.html
index a1a08a0a..7499ac50 100644
--- a/lightrag/api/webui/index.html
+++ b/lightrag/api/webui/index.html
@@ -8,16 +8,16 @@
     <link rel="icon" type="image/png" href="favicon.png" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>Lightrag</title>
-    <script type="module" crossorigin src="/webui/assets/index-Ctn6Ym96.js"></script>
+    <script type="module" crossorigin src="/webui/assets/index-B90LgL3h.js"></script>
     <link rel="modulepreload" crossorigin href="/webui/assets/react-vendor-DEwriMA6.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/ui-vendor-CeCm8EER.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/graph-vendor-B-X5JegA.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/utils-vendor-BysuhMZA.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/feature-graph-C6IuADHZ.js">
-    <link rel="modulepreload" crossorigin href="/webui/assets/feature-documents-BSJWpkhB.js">
+    <link rel="modulepreload" crossorigin href="/webui/assets/feature-documents-Di_Wt0BY.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/mermaid-vendor-CAxUo7Zk.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/markdown-vendor-DmIvJdn7.js">
-    <link rel="modulepreload" crossorigin href="/webui/assets/feature-retrieval-kyTSZozC.js">
+    <link rel="modulepreload" crossorigin href="/webui/assets/feature-retrieval-DVuOAaIQ.js">
     <link rel="stylesheet" crossorigin href="/webui/assets/feature-graph-BipNuM18.css">
     <link rel="stylesheet" crossorigin href="/webui/assets/index-CafJWW1u.css">
   </head>

From 16a1ef11780d9698ce5fc9c4d8c2a5c15034f4ce Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 21 Aug 2025 23:16:07 +0800
Subject: [PATCH 017/141] Update summary_max_tokens default from 10k to 30k
 tokens

---
 README-zh.md          | 2 +-
 README.md             | 2 +-
 env.example           | 2 +-
 lightrag/constants.py | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/README-zh.md b/README-zh.md
index de80a076..ed70d108 100644
--- a/README-zh.md
+++ b/README-zh.md
@@ -267,7 +267,7 @@ if __name__ == "__main__":
 | **embedding_func_max_async** | `int` | 最大并发异步嵌入进程数 | `16` |
 | **llm_model_func** | `callable` | LLM生成的函数 | `gpt_4o_mini_complete` |
 | **llm_model_name** | `str` | 用于生成的LLM模型名称 | `meta-llama/Llama-3.2-1B-Instruct` |
-| **summary_max_tokens** | `int` | 生成实体关系摘要时送给LLM的最大令牌数 | `32000`（由环境变量 SUMMARY_MAX_TOKENS 设置） |
+| **summary_max_tokens** | `int` | 生成实体关系摘要时送给LLM的最大令牌数 | `30000`（由环境变量 SUMMARY_MAX_TOKENS 设置） |
 | **llm_model_max_async** | `int` | 最大并发异步LLM进程数 | `4`（默认值由环境变量MAX_ASYNC更改） |
 | **llm_model_kwargs** | `dict` | LLM生成的附加参数 | |
 | **vector_db_storage_cls_kwargs** | `dict` | 向量数据库的附加参数，如设置节点和关系检索的阈值 | cosine_better_than_threshold: 0.2（默认值由环境变量COSINE_THRESHOLD更改） |
diff --git a/README.md b/README.md
index 3bbd39be..893af27a 100644
--- a/README.md
+++ b/README.md
@@ -274,7 +274,7 @@ A full list of LightRAG init parameters:
 | **embedding_func_max_async** | `int` | Maximum number of concurrent asynchronous embedding processes | `16` |
 | **llm_model_func** | `callable` | Function for LLM generation | `gpt_4o_mini_complete` |
 | **llm_model_name** | `str` | LLM model name for generation | `meta-llama/Llama-3.2-1B-Instruct` |
-| **summary_max_tokens** | `int` | Maximum tokens send to LLM to generate entity relation summaries | `32000`（configured by env var SUMMARY_MAX_TOKENS) |
+| **summary_max_tokens** | `int` | Maximum tokens send to LLM to generate entity relation summaries | `30000`（configured by env var SUMMARY_MAX_TOKENS) |
 | **llm_model_max_async** | `int` | Maximum number of concurrent asynchronous LLM processes | `4`（default value changed by env var MAX_ASYNC) |
 | **llm_model_kwargs** | `dict` | Additional parameters for LLM generation | |
 | **vector_db_storage_cls_kwargs** | `dict` | Additional parameters for vector database, like setting the threshold for nodes and relations retrieval | cosine_better_than_threshold: 0.2（default value changed by env var COSINE_THRESHOLD) |
diff --git a/env.example b/env.example
index 765d0b62..47a2ff60 100644
--- a/env.example
+++ b/env.example
@@ -107,7 +107,7 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true
 ### Entity and relation summarization configuration
 ### Number of duplicated entities/edges to trigger LLM re-summary on merge (at least 3 is recommented)， and max tokens send to LLM
 # FORCE_LLM_SUMMARY_ON_MERGE=4
-# SUMMARY_MAX_TOKENS=10000
+# SUMMARY_MAX_TOKENS=30000
 ### Maximum number of entity extraction attempts for ambiguous content
 # MAX_GLEANING=1
 
diff --git a/lightrag/constants.py b/lightrag/constants.py
index aab20665..d9ab121d 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -14,7 +14,7 @@ DEFAULT_MAX_GRAPH_NODES = 1000
 DEFAULT_SUMMARY_LANGUAGE = "English"  # Default language for summaries
 DEFAULT_FORCE_LLM_SUMMARY_ON_MERGE = 4
 DEFAULT_MAX_GLEANING = 1
-DEFAULT_SUMMARY_MAX_TOKENS = 10000  # Default maximum token size
+DEFAULT_SUMMARY_MAX_TOKENS = 30000  # Default maximum token size
 
 # Separator for graph fields
 GRAPH_FIELD_SEP = "<SEP>"

From c66fc3483a9d89de0f3cbb71edd13526e2007d7c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Albert=20Gil=20L=C3=B3pez?= <albert@albertgilopez.es>
Date: Fri, 22 Aug 2025 02:52:51 +0000
Subject: [PATCH 018/141] fix: Implement PipelineNotInitializedError usage in
 get_namespace_data

- Add PipelineNotInitializedError import to shared_storage.py
- Raise PipelineNotInitializedError when accessing uninitialized pipeline_status namespace
- This provides clear error messages to users about initialization requirements
- Other namespaces continue to be created dynamically as before

Addresses review feedback from PR #1978 about unused exception class
---
 lightrag/kg/shared_storage.py | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/lightrag/kg/shared_storage.py b/lightrag/kg/shared_storage.py
index 228bf272..10c69b14 100644
--- a/lightrag/kg/shared_storage.py
+++ b/lightrag/kg/shared_storage.py
@@ -8,6 +8,8 @@ import time
 import logging
 from typing import Any, Dict, List, Optional, Union, TypeVar, Generic
 
+from lightrag.exceptions import PipelineNotInitializedError
+
 
 # Define a direct print function for critical logs that must be visible in all processes
 def direct_log(message, enable_output: bool = False, level: str = "DEBUG"):
@@ -1203,6 +1205,13 @@ async def get_namespace_data(namespace: str) -> Dict[str, Any]:
 
     async with get_internal_lock():
         if namespace not in _shared_dicts:
+            # Special handling for pipeline_status namespace
+            if namespace == "pipeline_status":
+                # Check if pipeline_status should have been initialized but wasn't
+                # This helps users understand they need to call initialize_pipeline_status()
+                raise PipelineNotInitializedError(namespace)
+            
+            # For other namespaces, create them dynamically as before
             if _is_multiprocess and _manager is not None:
                 _shared_dicts[namespace] = _manager.dict()
             else:

From 3fca3be09becc20ac4bb150b205215150997d680 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Albert=20Gil=20L=C3=B3pez?= <albert@albertgilopez.es>
Date: Fri, 22 Aug 2025 10:55:56 +0000
Subject: [PATCH 019/141] fix: Fix server startup issue with
 PipelineNotInitializedError

- Add allow_create parameter to get_namespace_data() to permit internal initialization
- initialize_pipeline_status() now uses allow_create=True to create the namespace
- External calls still get the error if pipeline_status is not initialized
- This maintains the improved error messages while allowing proper server startup

Fixes server startup failure reported in PR #1978
---
 lightrag/kg/shared_storage.py | 16 +++++++++++-----
 1 file changed, 11 insertions(+), 5 deletions(-)

diff --git a/lightrag/kg/shared_storage.py b/lightrag/kg/shared_storage.py
index 10c69b14..02350c4c 100644
--- a/lightrag/kg/shared_storage.py
+++ b/lightrag/kg/shared_storage.py
@@ -1059,7 +1059,7 @@ async def initialize_pipeline_status():
     Initialize pipeline namespace with default values.
     This function is called during FASTAPI lifespan for each worker.
     """
-    pipeline_namespace = await get_namespace_data("pipeline_status")
+    pipeline_namespace = await get_namespace_data("pipeline_status", allow_create=True)
 
     async with get_internal_lock():
         # Check if already initialized by checking for required fields
@@ -1194,8 +1194,14 @@ async def try_initialize_namespace(namespace: str) -> bool:
     return False
 
 
-async def get_namespace_data(namespace: str) -> Dict[str, Any]:
-    """get the shared data reference for specific namespace"""
+async def get_namespace_data(namespace: str, allow_create: bool = False) -> Dict[str, Any]:
+    """get the shared data reference for specific namespace
+    
+    Args:
+        namespace: The namespace to retrieve
+        allow_create: If True, allows creation of the namespace if it doesn't exist.
+                     Used internally by initialize_pipeline_status().
+    """
     if _shared_dicts is None:
         direct_log(
             f"Error: try to getnanmespace before it is initialized, pid={os.getpid()}",
@@ -1206,12 +1212,12 @@ async def get_namespace_data(namespace: str) -> Dict[str, Any]:
     async with get_internal_lock():
         if namespace not in _shared_dicts:
             # Special handling for pipeline_status namespace
-            if namespace == "pipeline_status":
+            if namespace == "pipeline_status" and not allow_create:
                 # Check if pipeline_status should have been initialized but wasn't
                 # This helps users understand they need to call initialize_pipeline_status()
                 raise PipelineNotInitializedError(namespace)
             
-            # For other namespaces, create them dynamically as before
+            # For other namespaces or when allow_create=True, create them dynamically
             if _is_multiprocess and _manager is not None:
                 _shared_dicts[namespace] = _manager.dict()
             else:

From 580cb7906cb2189b994dcb2decb9fa6286a3d86d Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 22 Aug 2025 19:29:45 +0800
Subject: [PATCH 020/141] feat: Add multiple rerank provider support to
 LightRAG Server by adding new env vars and cli params

- Add --enable-rerank CLI argument and ENABLE_RERANK env var
- Simplify rerank configuration logic to only check enable flag and binding
- Update health endpoint to show enable_rerank and rerank_configured status
- Improve logging messages for rerank enable/disable states
- Maintain backward compatibility with default value True
---
 docs/rerank_integration.md      | 281 ------------------
 env.example                     |  30 +-
 lightrag/api/config.py          |  14 +
 lightrag/api/lightrag_server.py |  43 ++-
 lightrag/rerank.py              | 493 +++++++++++++++++---------------
 lightrag/utils.py               |  75 ++---
 6 files changed, 368 insertions(+), 568 deletions(-)
 delete mode 100644 docs/rerank_integration.md

diff --git a/docs/rerank_integration.md b/docs/rerank_integration.md
deleted file mode 100644
index 0e6c5169..00000000
--- a/docs/rerank_integration.md
+++ /dev/null
@@ -1,281 +0,0 @@
-# Rerank Integration Guide
-
-LightRAG supports reranking functionality to improve retrieval quality by re-ordering documents based on their relevance to the query. Reranking is now controlled per query via the `enable_rerank` parameter (default: True).
-
-## Quick Start
-
-### Environment Variables
-
-Set these variables in your `.env` file or environment for rerank model configuration:
-
-```bash
-# Rerank model configuration (required when enable_rerank=True in queries)
-RERANK_MODEL=BAAI/bge-reranker-v2-m3
-RERANK_BINDING_HOST=https://api.your-provider.com/v1/rerank
-RERANK_BINDING_API_KEY=your_api_key_here
-```
-
-### Programmatic Configuration
-
-```python
-from lightrag import LightRAG, QueryParam
-from lightrag.rerank import custom_rerank, RerankModel
-
-# Method 1: Using a custom rerank function with all settings included
-async def my_rerank_func(query: str, documents: list, top_n: int = None, **kwargs):
-    return await custom_rerank(
-        query=query,
-        documents=documents,
-        model="BAAI/bge-reranker-v2-m3",
-        base_url="https://api.your-provider.com/v1/rerank",
-        api_key="your_api_key_here",
-        top_n=top_n or 10,  # Handle top_n within the function
-        **kwargs
-    )
-
-rag = LightRAG(
-    working_dir="./rag_storage",
-    llm_model_func=your_llm_func,
-    embedding_func=your_embedding_func,
-    rerank_model_func=my_rerank_func,  # Configure rerank function
-)
-
-# Query with rerank enabled (default)
-result = await rag.aquery(
-    "your query",
-    param=QueryParam(enable_rerank=True)  # Control rerank per query
-)
-
-# Query with rerank disabled
-result = await rag.aquery(
-    "your query",
-    param=QueryParam(enable_rerank=False)
-)
-
-# Method 2: Using RerankModel wrapper
-rerank_model = RerankModel(
-    rerank_func=custom_rerank,
-    kwargs={
-        "model": "BAAI/bge-reranker-v2-m3",
-        "base_url": "https://api.your-provider.com/v1/rerank",
-        "api_key": "your_api_key_here",
-    }
-)
-
-rag = LightRAG(
-    working_dir="./rag_storage",
-    llm_model_func=your_llm_func,
-    embedding_func=your_embedding_func,
-    rerank_model_func=rerank_model.rerank,
-)
-
-# Control rerank per query
-result = await rag.aquery(
-    "your query",
-    param=QueryParam(
-        enable_rerank=True,  # Enable rerank for this query
-        chunk_top_k=5       # Number of chunks to keep after reranking
-    )
-)
-```
-
-## Supported Providers
-
-### 1. Custom/Generic API (Recommended)
-
-For Jina/Cohere compatible APIs:
-
-```python
-from lightrag.rerank import custom_rerank
-
-# Your custom API endpoint
-result = await custom_rerank(
-    query="your query",
-    documents=documents,
-    model="BAAI/bge-reranker-v2-m3",
-    base_url="https://api.your-provider.com/v1/rerank",
-    api_key="your_api_key_here",
-    top_n=10
-)
-```
-
-### 2. Jina AI
-
-```python
-from lightrag.rerank import jina_rerank
-
-result = await jina_rerank(
-    query="your query",
-    documents=documents,
-    model="BAAI/bge-reranker-v2-m3",
-    api_key="your_jina_api_key",
-    top_n=10
-)
-```
-
-### 3. Cohere
-
-```python
-from lightrag.rerank import cohere_rerank
-
-result = await cohere_rerank(
-    query="your query",
-    documents=documents,
-    model="rerank-english-v2.0",
-    api_key="your_cohere_api_key",
-    top_n=10
-)
-```
-
-## Integration Points
-
-Reranking is automatically applied at these key retrieval stages:
-
-1. **Naive Mode**: After vector similarity search in `_get_vector_context`
-2. **Local Mode**: After entity retrieval in `_get_node_data`
-3. **Global Mode**: After relationship retrieval in `_get_edge_data`
-4. **Hybrid/Mix Modes**: Applied to all relevant components
-
-## Configuration Parameters
-
-| Parameter | Type | Default | Description |
-|-----------|------|---------|-------------|
-| `enable_rerank` | bool | False | Enable/disable reranking |
-| `rerank_model_func` | callable | None | Custom rerank function containing all configurations (model, API keys, top_n, etc.) |
-
-## Example Usage
-
-### Basic Usage
-
-```python
-import asyncio
-from lightrag import LightRAG, QueryParam
-from lightrag.llm.openai import gpt_4o_mini_complete, openai_embedding
-from lightrag.kg.shared_storage import initialize_pipeline_status
-from lightrag.rerank import jina_rerank
-
-async def my_rerank_func(query: str, documents: list, top_n: int = None, **kwargs):
-    """Custom rerank function with all settings included"""
-    return await jina_rerank(
-        query=query,
-        documents=documents,
-        model="BAAI/bge-reranker-v2-m3",
-        api_key="your_jina_api_key_here",
-        top_n=top_n or 10,  # Default top_n if not provided
-        **kwargs
-    )
-
-async def main():
-    # Initialize with rerank enabled
-    rag = LightRAG(
-        working_dir="./rag_storage",
-        llm_model_func=gpt_4o_mini_complete,
-        embedding_func=openai_embedding,
-        rerank_model_func=my_rerank_func,
-    )
-
-    await rag.initialize_storages()
-    await initialize_pipeline_status()
-
-    # Insert documents
-    await rag.ainsert([
-        "Document 1 content...",
-        "Document 2 content...",
-    ])
-
-    # Query with rerank (automatically applied)
-    result = await rag.aquery(
-        "Your question here",
-        param=QueryParam(enable_rerank=True)  # This top_n is passed to rerank function
-    )
-
-    print(result)
-
-asyncio.run(main())
-```
-
-### Direct Rerank Usage
-
-```python
-from lightrag.rerank import custom_rerank
-
-async def test_rerank():
-    documents = [
-        {"content": "Text about topic A"},
-        {"content": "Text about topic B"},
-        {"content": "Text about topic C"},
-    ]
-
-    reranked = await custom_rerank(
-        query="Tell me about topic A",
-        documents=documents,
-        model="BAAI/bge-reranker-v2-m3",
-        base_url="https://api.your-provider.com/v1/rerank",
-        api_key="your_api_key_here",
-        top_n=2
-    )
-
-    for doc in reranked:
-        print(f"Score: {doc.get('rerank_score')}, Content: {doc.get('content')}")
-```
-
-## Best Practices
-
-1. **Self-Contained Functions**: Include all necessary configurations (API keys, models, top_n handling) within your rerank function
-2. **Performance**: Use reranking selectively for better performance vs. quality tradeoff
-3. **API Limits**: Monitor API usage and implement rate limiting within your rerank function
-4. **Fallback**: Always handle rerank failures gracefully (returns original results)
-5. **Top-n Handling**: Handle top_n parameter appropriately within your rerank function
-6. **Cost Management**: Consider rerank API costs in your budget planning
-
-## Troubleshooting
-
-### Common Issues
-
-1. **API Key Missing**: Ensure API keys are properly configured within your rerank function
-2. **Network Issues**: Check API endpoints and network connectivity
-3. **Model Errors**: Verify the rerank model name is supported by your API
-4. **Document Format**: Ensure documents have `content` or `text` fields
-
-### Debug Mode
-
-Enable debug logging to see rerank operations:
-
-```python
-import logging
-logging.getLogger("lightrag.rerank").setLevel(logging.DEBUG)
-```
-
-### Error Handling
-
-The rerank integration includes automatic fallback:
-
-```python
-# If rerank fails, original documents are returned
-# No exceptions are raised to the user
-# Errors are logged for debugging
-```
-
-## API Compatibility
-
-The generic rerank API expects this response format:
-
-```json
-{
-  "results": [
-    {
-      "index": 0,
-      "relevance_score": 0.95
-    },
-    {
-      "index": 2,
-      "relevance_score": 0.87
-    }
-  ]
-}
-```
-
-This is compatible with:
-- Jina AI Rerank API
-- Cohere Rerank API
-- Custom APIs following the same format
diff --git a/env.example b/env.example
index 47a2ff60..c39faa5f 100644
--- a/env.example
+++ b/env.example
@@ -85,16 +85,36 @@ ENABLE_LLM_CACHE=true
 ###     If reranking is enabled, the impact of chunk selection strategies will be diminished.
 # KG_CHUNK_PICK_METHOD=VECTOR
 
+#########################################################
 ### Reranking configuration
-###     Reranker Set ENABLE_RERANK to true in reranking model is configed
-# ENABLE_RERANK=True
-### Minimum rerank score for document chunk exclusion (set to 0.0 to keep all chunks, 0.6 or above if LLM is not strong enought)
+### RERANK_BINDING type:  cohere, jina, aliyun
+### For rerank model deployed by vLLM use cohere binding
+#########################################################
+ENABLE_RERANK=False
+RERANK_BINDING=cohere
+### rerank score chunk filter(set to 0.0 to keep all chunks, 0.6 or above if LLM is not strong enought)
 # MIN_RERANK_SCORE=0.0
-### Rerank model configuration (required when ENABLE_RERANK=True)
-# RERANK_MODEL=jina-reranker-v2-base-multilingual
+
+### For local deployment
+# RERANK_MODEL=BAAI/bge-reranker-v2-m3
+# RERANK_BINDING_HOST=http://localhost:8000
+# RERANK_BINDING_API_KEY=your_rerank_api_key_here
+
+### Default value for Cohere AI
+# RERANK_MODEL=rerank-v3.5
+# RERANK_BINDING_HOST=https://ai.znipower.com:5017/rerank
+# RERANK_BINDING_API_KEY=your_rerank_api_key_here
+
+### Default value for Jina AI
+# RERANK_MODELjina-reranker-v2-base-multilingual
 # RERANK_BINDING_HOST=https://api.jina.ai/v1/rerank
 # RERANK_BINDING_API_KEY=your_rerank_api_key_here
 
+### Default value for Aliyun
+# RERANK_MODEL=gte-rerank-v2
+# RERANK_BINDING_HOST=https://dashscope.aliyuncs.com/api/v1/services/rerank/text-rerank/text-rerank
+# RERANK_BINDING_API_KEY=your_rerank_api_key_here
+
 ########################################
 ### Document processing configuration
 ########################################
diff --git a/lightrag/api/config.py b/lightrag/api/config.py
index 83a56f5a..bc24cd70 100644
--- a/lightrag/api/config.py
+++ b/lightrag/api/config.py
@@ -225,6 +225,19 @@ def parse_args() -> argparse.Namespace:
         choices=["lollms", "ollama", "openai", "azure_openai", "aws_bedrock", "jina"],
         help="Embedding binding type (default: from env or ollama)",
     )
+    parser.add_argument(
+        "--rerank-binding",
+        type=str,
+        default=get_env_value("RERANK_BINDING", "cohere"),
+        choices=["cohere", "jina", "aliyun"],
+        help="Rerank binding type (default: from env or cohere)",
+    )
+    parser.add_argument(
+        "--enable-rerank",
+        action="store_true",
+        default=get_env_value("ENABLE_RERANK", True, bool),
+        help="Enable rerank functionality (default: from env or True)",
+    )
 
     # Conditionally add binding options defined in binding_options module
     # This will add command line arguments for all binding options (e.g., --ollama-embedding-num_ctx)
@@ -340,6 +353,7 @@ def parse_args() -> argparse.Namespace:
     args.rerank_model = get_env_value("RERANK_MODEL", "BAAI/bge-reranker-v2-m3")
     args.rerank_binding_host = get_env_value("RERANK_BINDING_HOST", None)
     args.rerank_binding_api_key = get_env_value("RERANK_BINDING_API_KEY", None)
+    # Note: rerank_binding is already set by argparse, no need to override from env
 
     # Min rerank score configuration
     args.min_rerank_score = get_env_value(
diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 708fedd2..8e3f9af1 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -390,33 +390,44 @@ def create_app(args):
         ),
     )
 
-    # Configure rerank function if model and API are configured
+    # Configure rerank function based on enable_rerank parameter
     rerank_model_func = None
-    if args.rerank_binding_api_key and args.rerank_binding_host:
-        from lightrag.rerank import custom_rerank
+    if args.enable_rerank and args.rerank_binding:
+        from lightrag.rerank import cohere_rerank, jina_rerank, ali_rerank
+
+        # Map rerank binding to corresponding function
+        rerank_functions = {
+            "cohere": cohere_rerank,
+            "jina": jina_rerank,
+            "aliyun": ali_rerank,
+        }
+
+        # Select the appropriate rerank function based on binding
+        selected_rerank_func = rerank_functions.get(args.rerank_binding)
+        if not selected_rerank_func:
+            logger.error(f"Unsupported rerank binding: {args.rerank_binding}")
+            raise ValueError(f"Unsupported rerank binding: {args.rerank_binding}")
 
         async def server_rerank_func(
-            query: str, documents: list, top_n: int = None, **kwargs
+            query: str, documents: list, top_n: int = None, extra_body: dict = None
         ):
             """Server rerank function with configuration from environment variables"""
-            return await custom_rerank(
+            return await selected_rerank_func(
                 query=query,
                 documents=documents,
                 model=args.rerank_model,
                 base_url=args.rerank_binding_host,
                 api_key=args.rerank_binding_api_key,
                 top_n=top_n,
-                **kwargs,
+                extra_body=extra_body,
             )
 
         rerank_model_func = server_rerank_func
         logger.info(
-            f"Rerank model configured: {args.rerank_model} (can be enabled per query)"
+            f"Rerank enabled: {args.rerank_model} using {args.rerank_binding} provider"
         )
     else:
-        logger.info(
-            "Rerank model not configured. Set RERANK_BINDING_API_KEY and RERANK_BINDING_HOST to enable reranking."
-        )
+        logger.info("Rerank disabled")
 
     # Create ollama_server_infos from command line arguments
     from lightrag.api.config import OllamaServerInfos
@@ -622,13 +633,15 @@ def create_app(args):
                     "enable_llm_cache": args.enable_llm_cache,
                     "workspace": args.workspace,
                     "max_graph_nodes": args.max_graph_nodes,
-                    # Rerank configuration (based on whether rerank model is configured)
-                    "enable_rerank": rerank_model_func is not None,
-                    "rerank_model": args.rerank_model
-                    if rerank_model_func is not None
+                    # Rerank configuration
+                    "enable_rerank": args.enable_rerank,
+                    "rerank_configured": rerank_model_func is not None,
+                    "rerank_binding": args.rerank_binding
+                    if args.enable_rerank
                     else None,
+                    "rerank_model": args.rerank_model if args.enable_rerank else None,
                     "rerank_binding_host": args.rerank_binding_host
-                    if rerank_model_func is not None
+                    if args.enable_rerank
                     else None,
                     # Environment variable status (requested configuration)
                     "summary_language": args.summary_language,
diff --git a/lightrag/rerank.py b/lightrag/rerank.py
index 5ed1ca68..dbac1098 100644
--- a/lightrag/rerank.py
+++ b/lightrag/rerank.py
@@ -2,270 +2,194 @@ from __future__ import annotations
 
 import os
 import aiohttp
-from typing import Callable, Any, List, Dict, Optional
-from pydantic import BaseModel, Field
-
+from typing import Any, List, Dict, Optional
+from tenacity import (
+    retry,
+    stop_after_attempt,
+    wait_exponential,
+    retry_if_exception_type,
+)
 from .utils import logger
 
+from dotenv import load_dotenv
 
-class RerankModel(BaseModel):
-    """
-    Wrapper for rerank functions that can be used with LightRAG.
-
-    Example usage:
-    ```python
-    from lightrag.rerank import RerankModel, jina_rerank
-
-    # Create rerank model
-    rerank_model = RerankModel(
-        rerank_func=jina_rerank,
-        kwargs={
-            "model": "BAAI/bge-reranker-v2-m3",
-            "api_key": "your_api_key_here",
-            "base_url": "https://api.jina.ai/v1/rerank"
-        }
-    )
-
-    # Use in LightRAG
-    rag = LightRAG(
-        rerank_model_func=rerank_model.rerank,
-        # ... other configurations
-    )
-
-    # Query with rerank enabled (default)
-    result = await rag.aquery(
-        "your query",
-        param=QueryParam(enable_rerank=True)
-    )
-    ```
-
-    Or define a custom function directly:
-    ```python
-    async def my_rerank_func(query: str, documents: list, top_n: int = None, **kwargs):
-        return await jina_rerank(
-            query=query,
-            documents=documents,
-            model="BAAI/bge-reranker-v2-m3",
-            api_key="your_api_key_here",
-            top_n=top_n or 10,
-            **kwargs
-        )
-
-    rag = LightRAG(
-        rerank_model_func=my_rerank_func,
-        # ... other configurations
-    )
-
-    # Control rerank per query
-    result = await rag.aquery(
-        "your query",
-        param=QueryParam(enable_rerank=True)  # Enable rerank for this query
-    )
-    ```
-    """
-
-    rerank_func: Callable[[Any], List[Dict]]
-    kwargs: Dict[str, Any] = Field(default_factory=dict)
-
-    async def rerank(
-        self,
-        query: str,
-        documents: List[Dict[str, Any]],
-        top_n: Optional[int] = None,
-        **extra_kwargs,
-    ) -> List[Dict[str, Any]]:
-        """Rerank documents using the configured model function."""
-        # Merge extra kwargs with model kwargs
-        kwargs = {**self.kwargs, **extra_kwargs}
-        return await self.rerank_func(
-            query=query, documents=documents, top_n=top_n, **kwargs
-        )
-
-
-class MultiRerankModel(BaseModel):
-    """Multiple rerank models for different modes/scenarios."""
-
-    # Primary rerank model (used if mode-specific models are not defined)
-    rerank_model: Optional[RerankModel] = None
-
-    # Mode-specific rerank models
-    entity_rerank_model: Optional[RerankModel] = None
-    relation_rerank_model: Optional[RerankModel] = None
-    chunk_rerank_model: Optional[RerankModel] = None
-
-    async def rerank(
-        self,
-        query: str,
-        documents: List[Dict[str, Any]],
-        mode: str = "default",
-        top_n: Optional[int] = None,
-        **kwargs,
-    ) -> List[Dict[str, Any]]:
-        """Rerank using the appropriate model based on mode."""
-
-        # Select model based on mode
-        if mode == "entity" and self.entity_rerank_model:
-            model = self.entity_rerank_model
-        elif mode == "relation" and self.relation_rerank_model:
-            model = self.relation_rerank_model
-        elif mode == "chunk" and self.chunk_rerank_model:
-            model = self.chunk_rerank_model
-        elif self.rerank_model:
-            model = self.rerank_model
-        else:
-            logger.warning(f"No rerank model available for mode: {mode}")
-            return documents
-
-        return await model.rerank(query, documents, top_n, **kwargs)
+# use the .env that is inside the current folder
+# allows to use different .env file for each lightrag instance
+# the OS environment variables take precedence over the .env file
+load_dotenv(dotenv_path=".env", override=False)
 
 
+@retry(
+    stop=stop_after_attempt(3),
+    wait=wait_exponential(multiplier=1, min=4, max=60),
+    retry=(
+        retry_if_exception_type(aiohttp.ClientError)
+        | retry_if_exception_type(aiohttp.ClientResponseError)
+    ),
+)
 async def generic_rerank_api(
     query: str,
-    documents: List[Dict[str, Any]],
+    documents: List[str],
     model: str,
     base_url: str,
     api_key: str,
     top_n: Optional[int] = None,
-    **kwargs,
+    return_documents: Optional[bool] = None,
+    extra_body: Optional[Dict[str, Any]] = None,
+    response_format: str = "standard",  # "standard" (Jina/Cohere) or "aliyun"
+    request_format: str = "standard",  # "standard" (Jina/Cohere) or "aliyun"
 ) -> List[Dict[str, Any]]:
     """
-    Generic rerank function that works with Jina/Cohere compatible APIs.
+    Generic rerank API call for Jina/Cohere/Aliyun models.
 
     Args:
         query: The search query
-        documents: List of documents to rerank
-        model: Model identifier
+        documents: List of strings to rerank
+        model: Model name to use
         base_url: API endpoint URL
-        api_key: API authentication key
+        api_key: API key for authentication
         top_n: Number of top results to return
-        **kwargs: Additional API-specific parameters
+        return_documents: Whether to return document text (Jina only)
+        extra_body: Additional body parameters
+        response_format: Response format type ("standard" for Jina/Cohere, "aliyun" for Aliyun)
 
     Returns:
-        List of reranked documents with relevance scores
+        List of dictionary of ["index": int, "relevance_score": float]
     """
     if not api_key:
-        logger.warning("No API key provided for rerank service")
-        return documents
+        raise ValueError("API key is required")
 
-    if not documents:
-        return documents
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}",
+    }
 
-    # Prepare documents for reranking - handle both text and dict formats
-    prepared_docs = []
-    for doc in documents:
-        if isinstance(doc, dict):
-            # Use 'content' field if available, otherwise use 'text' or convert to string
-            text = doc.get("content") or doc.get("text") or str(doc)
-        else:
-            text = str(doc)
-        prepared_docs.append(text)
+    # Build request payload based on request format
+    if request_format == "aliyun":
+        # Aliyun format: nested input/parameters structure
+        payload = {
+            "model": model,
+            "input": {
+                "query": query,
+                "documents": documents,
+            },
+            "parameters": {},
+        }
 
-    # Prepare request
-    headers = {"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"}
+        # Add optional parameters to parameters object
+        if top_n is not None:
+            payload["parameters"]["top_n"] = top_n
 
-    data = {"model": model, "query": query, "documents": prepared_docs, **kwargs}
+        if return_documents is not None:
+            payload["parameters"]["return_documents"] = return_documents
 
-    if top_n is not None:
-        data["top_n"] = min(top_n, len(prepared_docs))
+        # Add extra parameters to parameters object
+        if extra_body:
+            payload["parameters"].update(extra_body)
+    else:
+        # Standard format for Jina/Cohere
+        payload = {
+            "model": model,
+            "query": query,
+            "documents": documents,
+        }
 
-    try:
-        async with aiohttp.ClientSession() as session:
-            async with session.post(base_url, headers=headers, json=data) as response:
-                if response.status != 200:
-                    error_text = await response.text()
-                    logger.error(f"Rerank API error {response.status}: {error_text}")
-                    return documents
+        # Add optional parameters
+        if top_n is not None:
+            payload["top_n"] = top_n
 
-                result = await response.json()
+        # Only Jina API supports return_documents parameter
+        if return_documents is not None:
+            payload["return_documents"] = return_documents
 
-                # Extract reranked results
-                if "results" in result:
-                    # Standard format: results contain index and relevance_score
-                    reranked_docs = []
-                    for item in result["results"]:
-                        if "index" in item:
-                            doc_idx = item["index"]
-                            if 0 <= doc_idx < len(documents):
-                                reranked_doc = documents[doc_idx].copy()
-                                if "relevance_score" in item:
-                                    reranked_doc["rerank_score"] = item[
-                                        "relevance_score"
-                                    ]
-                                reranked_docs.append(reranked_doc)
-                    return reranked_docs
-                else:
-                    logger.warning("Unexpected rerank API response format")
-                    return documents
+        # Add extra parameters
+        if extra_body:
+            payload.update(extra_body)
 
-    except Exception as e:
-        logger.error(f"Error during reranking: {e}")
-        return documents
-
-
-async def jina_rerank(
-    query: str,
-    documents: List[Dict[str, Any]],
-    model: str = "BAAI/bge-reranker-v2-m3",
-    top_n: Optional[int] = None,
-    base_url: str = "https://api.jina.ai/v1/rerank",
-    api_key: Optional[str] = None,
-    **kwargs,
-) -> List[Dict[str, Any]]:
-    """
-    Rerank documents using Jina AI API.
-
-    Args:
-        query: The search query
-        documents: List of documents to rerank
-        model: Jina rerank model name
-        top_n: Number of top results to return
-        base_url: Jina API endpoint
-        api_key: Jina API key
-        **kwargs: Additional parameters
-
-    Returns:
-        List of reranked documents with relevance scores
-    """
-    if api_key is None:
-        api_key = os.getenv("JINA_API_KEY") or os.getenv("RERANK_API_KEY")
-
-    return await generic_rerank_api(
-        query=query,
-        documents=documents,
-        model=model,
-        base_url=base_url,
-        api_key=api_key,
-        top_n=top_n,
-        **kwargs,
+    logger.debug(
+        f"Rerank request: {len(documents)} documents, model: {model}, format: {response_format}"
     )
 
+    async with aiohttp.ClientSession() as session:
+        async with session.post(base_url, headers=headers, json=payload) as response:
+            if response.status != 200:
+                error_text = await response.text()
+                content_type = response.headers.get("content-type", "").lower()
+                is_html_error = (
+                    error_text.strip().startswith("<!DOCTYPE html>")
+                    or "text/html" in content_type
+                )
+
+                if is_html_error:
+                    if response.status == 502:
+                        clean_error = "Bad Gateway (502) - Rerank service temporarily unavailable. Please try again in a few minutes."
+                    elif response.status == 503:
+                        clean_error = "Service Unavailable (503) - Rerank service is temporarily overloaded. Please try again later."
+                    elif response.status == 504:
+                        clean_error = "Gateway Timeout (504) - Rerank service request timed out. Please try again."
+                    else:
+                        clean_error = f"HTTP {response.status} - Rerank service error. Please try again later."
+                else:
+                    clean_error = error_text
+
+                logger.error(f"Rerank API error {response.status}: {clean_error}")
+                raise aiohttp.ClientResponseError(
+                    request_info=response.request_info,
+                    history=response.history,
+                    status=response.status,
+                    message=f"Rerank API error: {clean_error}",
+                )
+
+            response_json = await response.json()
+
+            # Handle different response formats
+            if response_format == "aliyun":
+                # Aliyun format: {"output": {"results": [...]}}
+                output = response_json.get("output", {})
+                results = output.get("results", [])
+            elif response_format == "standard":
+                # Standard format: {"results": [...]}
+                results = response_json.get("results", [])
+            else:
+                raise ValueError(f"Unsupported response format: {response_format}")
+
+            if not results:
+                logger.warning("Rerank API returned empty results")
+                return []
+
+            # Standardize return format
+            return [
+                {"index": result["index"], "relevance_score": result["relevance_score"]}
+                for result in results
+            ]
+
 
 async def cohere_rerank(
     query: str,
-    documents: List[Dict[str, Any]],
-    model: str = "rerank-english-v2.0",
+    documents: List[str],
     top_n: Optional[int] = None,
-    base_url: str = "https://api.cohere.ai/v1/rerank",
     api_key: Optional[str] = None,
-    **kwargs,
+    model: str = "rerank-v3.5",
+    base_url: str = "https://ai.znipower.com:5017/rerank",
+    extra_body: Optional[Dict[str, Any]] = None,
 ) -> List[Dict[str, Any]]:
     """
     Rerank documents using Cohere API.
 
     Args:
         query: The search query
-        documents: List of documents to rerank
-        model: Cohere rerank model name
+        documents: List of strings to rerank
         top_n: Number of top results to return
-        base_url: Cohere API endpoint
-        api_key: Cohere API key
-        **kwargs: Additional parameters
+        api_key: API key
+        model: rerank model name
+        base_url: API endpoint
+        extra_body: Additional body for http request(reserved for extra params)
 
     Returns:
-        List of reranked documents with relevance scores
+        List of dictionary of ["index": int, "relevance_score": float]
     """
     if api_key is None:
-        api_key = os.getenv("COHERE_API_KEY") or os.getenv("RERANK_API_KEY")
+        api_key = os.getenv("COHERE_API_KEY") or os.getenv("RERANK_BINDING_API_KEY")
 
     return await generic_rerank_api(
         query=query,
@@ -274,24 +198,39 @@ async def cohere_rerank(
         base_url=base_url,
         api_key=api_key,
         top_n=top_n,
-        **kwargs,
+        return_documents=None,  # Cohere doesn't support this parameter
+        extra_body=extra_body,
+        response_format="standard",
     )
 
 
-# Convenience function for custom API endpoints
-async def custom_rerank(
+async def jina_rerank(
     query: str,
-    documents: List[Dict[str, Any]],
-    model: str,
-    base_url: str,
-    api_key: str,
+    documents: List[str],
     top_n: Optional[int] = None,
-    **kwargs,
+    api_key: Optional[str] = None,
+    model: str = "jina-reranker-v2-base-multilingual",
+    base_url: str = "https://api.jina.ai/v1/rerank",
+    extra_body: Optional[Dict[str, Any]] = None,
 ) -> List[Dict[str, Any]]:
     """
-    Rerank documents using a custom API endpoint.
-    This is useful for self-hosted or custom rerank services.
+    Rerank documents using Jina AI API.
+
+    Args:
+        query: The search query
+        documents: List of strings to rerank
+        top_n: Number of top results to return
+        api_key: API key
+        model: rerank model name
+        base_url: API endpoint
+        extra_body: Additional body for http request(reserved for extra params)
+
+    Returns:
+        List of dictionary of ["index": int, "relevance_score": float]
     """
+    if api_key is None:
+        api_key = os.getenv("JINA_API_KEY") or os.getenv("RERANK_BINDING_API_KEY")
+
     return await generic_rerank_api(
         query=query,
         documents=documents,
@@ -299,26 +238,112 @@ async def custom_rerank(
         base_url=base_url,
         api_key=api_key,
         top_n=top_n,
-        **kwargs,
+        return_documents=False,
+        extra_body=extra_body,
+        response_format="standard",
     )
 
 
+async def ali_rerank(
+    query: str,
+    documents: List[str],
+    top_n: Optional[int] = None,
+    api_key: Optional[str] = None,
+    model: str = "gte-rerank-v2",
+    base_url: str = "https://dashscope.aliyuncs.com/api/v1/services/rerank/text-rerank/text-rerank",
+    extra_body: Optional[Dict[str, Any]] = None,
+) -> List[Dict[str, Any]]:
+    """
+    Rerank documents using Aliyun DashScope API.
+
+    Args:
+        query: The search query
+        documents: List of strings to rerank
+        top_n: Number of top results to return
+        api_key: Aliyun API key
+        model: rerank model name
+        base_url: API endpoint
+        extra_body: Additional body for http request(reserved for extra params)
+
+    Returns:
+        List of dictionary of ["index": int, "relevance_score": float]
+    """
+    if api_key is None:
+        api_key = os.getenv("DASHSCOPE_API_KEY") or os.getenv("RERANK_BINDING_API_KEY")
+
+    return await generic_rerank_api(
+        query=query,
+        documents=documents,
+        model=model,
+        base_url=base_url,
+        api_key=api_key,
+        top_n=top_n,
+        return_documents=False,  # Aliyun doesn't need this parameter
+        extra_body=extra_body,
+        response_format="aliyun",
+        request_format="aliyun",
+    )
+
+
+"""Please run this test as a module:
+python -m lightrag.rerank
+"""
 if __name__ == "__main__":
     import asyncio
 
     async def main():
-        # Example usage
+        # Example usage - documents should be strings, not dictionaries
         docs = [
-            {"content": "The capital of France is Paris."},
-            {"content": "Tokyo is the capital of Japan."},
-            {"content": "London is the capital of England."},
+            "The capital of France is Paris.",
+            "Tokyo is the capital of Japan.",
+            "London is the capital of England.",
         ]
 
         query = "What is the capital of France?"
 
-        result = await jina_rerank(
-            query=query, documents=docs, top_n=2, api_key="your-api-key-here"
-        )
-        print(result)
+        # Test Jina rerank
+        try:
+            print("=== Jina Rerank ===")
+            result = await jina_rerank(
+                query=query,
+                documents=docs,
+                top_n=2,
+            )
+            print("Results:")
+            for item in result:
+                print(f"Index: {item['index']}, Score: {item['relevance_score']:.4f}")
+                print(f"Document: {docs[item['index']]}")
+        except Exception as e:
+            print(f"Jina Error: {e}")
+
+        # Test Cohere rerank
+        try:
+            print("\n=== Cohere Rerank ===")
+            result = await cohere_rerank(
+                query=query,
+                documents=docs,
+                top_n=2,
+            )
+            print("Results:")
+            for item in result:
+                print(f"Index: {item['index']}, Score: {item['relevance_score']:.4f}")
+                print(f"Document: {docs[item['index']]}")
+        except Exception as e:
+            print(f"Cohere Error: {e}")
+
+        # Test Aliyun rerank
+        try:
+            print("\n=== Aliyun Rerank ===")
+            result = await ali_rerank(
+                query=query,
+                documents=docs,
+                top_n=2,
+            )
+            print("Results:")
+            for item in result:
+                print(f"Index: {item['index']}, Score: {item['relevance_score']:.4f}")
+                print(f"Document: {docs[item['index']]}")
+        except Exception as e:
+            print(f"Aliyun Error: {e}")
 
     asyncio.run(main())
diff --git a/lightrag/utils.py b/lightrag/utils.py
index bec45f5f..65e22d1a 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -1978,17 +1978,50 @@ async def apply_rerank_if_enabled(
         return retrieved_docs
 
     try:
-        # Apply reranking - let rerank_model_func handle top_k internally
-        reranked_docs = await rerank_func(
+        # Extract document content for reranking
+        document_texts = []
+        for doc in retrieved_docs:
+            # Try multiple possible content fields
+            content = (
+                doc.get("content")
+                or doc.get("text")
+                or doc.get("chunk_content")
+                or doc.get("document")
+                or str(doc)
+            )
+            document_texts.append(content)
+
+        # Call the new rerank function that returns index-based results
+        rerank_results = await rerank_func(
             query=query,
-            documents=retrieved_docs,
-            top_n=top_n,
+            documents=document_texts,
+            top_n=top_n or len(retrieved_docs),
         )
-        if reranked_docs and len(reranked_docs) > 0:
-            if len(reranked_docs) > top_n:
-                reranked_docs = reranked_docs[:top_n]
-            logger.info(f"Successfully reranked: {len(retrieved_docs)} chunks")
-            return reranked_docs
+
+        # Process rerank results based on return format
+        if rerank_results and len(rerank_results) > 0:
+            # Check if results are in the new index-based format
+            if isinstance(rerank_results[0], dict) and "index" in rerank_results[0]:
+                # New format: [{"index": 0, "relevance_score": 0.85}, ...]
+                reranked_docs = []
+                for result in rerank_results:
+                    index = result["index"]
+                    relevance_score = result["relevance_score"]
+
+                    # Get original document and add rerank score
+                    if 0 <= index < len(retrieved_docs):
+                        doc = retrieved_docs[index].copy()
+                        doc["rerank_score"] = relevance_score
+                        reranked_docs.append(doc)
+
+                logger.info(
+                    f"Successfully reranked: {len(reranked_docs)} chunks from {len(retrieved_docs)} original chunks"
+                )
+                return reranked_docs
+            else:
+                # Legacy format: assume it's already reranked documents
+                logger.info(f"Using legacy rerank format: {len(rerank_results)} chunks")
+                return rerank_results[:top_n] if top_n else rerank_results
         else:
             logger.warning("Rerank returned empty results, using original chunks")
             return retrieved_docs
@@ -2027,13 +2060,6 @@ async def process_chunks_unified(
 
     # 1. Apply reranking if enabled and query is provided
     if query_param.enable_rerank and query and unique_chunks:
-        # 保存 chunk_id 字段，因为 rerank 可能会丢失这个字段
-        chunk_ids = {}
-        for chunk in unique_chunks:
-            chunk_id = chunk.get("chunk_id")
-            if chunk_id:
-                chunk_ids[id(chunk)] = chunk_id
-
         rerank_top_k = query_param.chunk_top_k or len(unique_chunks)
         unique_chunks = await apply_rerank_if_enabled(
             query=query,
@@ -2043,11 +2069,6 @@ async def process_chunks_unified(
             top_n=rerank_top_k,
         )
 
-        # 恢复 chunk_id 字段
-        for chunk in unique_chunks:
-            if id(chunk) in chunk_ids:
-                chunk["chunk_id"] = chunk_ids[id(chunk)]
-
     # 2. Filter by minimum rerank score if reranking is enabled
     if query_param.enable_rerank and unique_chunks:
         min_rerank_score = global_config.get("min_rerank_score", 0.5)
@@ -2095,13 +2116,6 @@ async def process_chunks_unified(
 
         original_count = len(unique_chunks)
 
-        # Keep chunk_id field, cause truncate_list_by_token_size will lose it
-        chunk_ids_map = {}
-        for i, chunk in enumerate(unique_chunks):
-            chunk_id = chunk.get("chunk_id")
-            if chunk_id:
-                chunk_ids_map[i] = chunk_id
-
         unique_chunks = truncate_list_by_token_size(
             unique_chunks,
             key=lambda x: json.dumps(x, ensure_ascii=False),
@@ -2109,11 +2123,6 @@ async def process_chunks_unified(
             tokenizer=tokenizer,
         )
 
-        # restore chunk_id feiled
-        for i, chunk in enumerate(unique_chunks):
-            if i in chunk_ids_map:
-                chunk["chunk_id"] = chunk_ids_map[i]
-
         logger.debug(
             f"Token truncation: {len(unique_chunks)} chunks from {original_count} "
             f"(chunk available tokens: {chunk_token_limit}, source: {source_type})"

From bf43e1b8c1ea081227426a8e047100139d1f90e3 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 01:07:59 +0800
Subject: [PATCH 021/141] fix: Resolve default rerank config problem when env
 var missing

- Read config from selected_rerank_func when env var missing
- Make api_key optional for rerank function
- Add response format validation with proper error handling
- Update Cohere rerank default to official API endpoint
---
 lightrag/api/config.py          |  15 +++--
 lightrag/api/lightrag_server.py |  26 ++++++--
 lightrag/base.py                |   5 +-
 lightrag/constants.py           |   2 +-
 lightrag/lightrag.py            |   8 ---
 lightrag/llm.py                 | 101 --------------------------------
 lightrag/rerank.py              |  33 ++++++-----
 lightrag/utils.py               |   2 +-
 8 files changed, 50 insertions(+), 142 deletions(-)
 delete mode 100644 lightrag/llm.py

diff --git a/lightrag/api/config.py b/lightrag/api/config.py
index bc24cd70..92952ec4 100644
--- a/lightrag/api/config.py
+++ b/lightrag/api/config.py
@@ -35,6 +35,7 @@ from lightrag.constants import (
     DEFAULT_EMBEDDING_BATCH_NUM,
     DEFAULT_OLLAMA_MODEL_NAME,
     DEFAULT_OLLAMA_MODEL_TAG,
+    DEFAULT_RERANK_BINDING,
 )
 
 # use the .env that is inside the current folder
@@ -76,9 +77,7 @@ def parse_args() -> argparse.Namespace:
         argparse.Namespace: Parsed arguments
     """
 
-    parser = argparse.ArgumentParser(
-        description="LightRAG FastAPI Server with separate working and input directories"
-    )
+    parser = argparse.ArgumentParser(description="LightRAG API Server")
 
     # Server configuration
     parser.add_argument(
@@ -228,15 +227,15 @@ def parse_args() -> argparse.Namespace:
     parser.add_argument(
         "--rerank-binding",
         type=str,
-        default=get_env_value("RERANK_BINDING", "cohere"),
+        default=get_env_value("RERANK_BINDING", DEFAULT_RERANK_BINDING),
         choices=["cohere", "jina", "aliyun"],
-        help="Rerank binding type (default: from env or cohere)",
+        help=f"Rerank binding type (default: from env or {DEFAULT_RERANK_BINDING})",
     )
     parser.add_argument(
         "--enable-rerank",
         action="store_true",
-        default=get_env_value("ENABLE_RERANK", True, bool),
-        help="Enable rerank functionality (default: from env or True)",
+        default=get_env_value("ENABLE_RERANK", False, bool),
+        help="Enable rerank functionality (default: from env or disalbed)",
     )
 
     # Conditionally add binding options defined in binding_options module
@@ -350,7 +349,7 @@ def parse_args() -> argparse.Namespace:
     args.jwt_algorithm = get_env_value("JWT_ALGORITHM", "HS256")
 
     # Rerank model configuration
-    args.rerank_model = get_env_value("RERANK_MODEL", "BAAI/bge-reranker-v2-m3")
+    args.rerank_model = get_env_value("RERANK_MODEL", None)
     args.rerank_binding_host = get_env_value("RERANK_BINDING_HOST", None)
     args.rerank_binding_api_key = get_env_value("RERANK_BINDING_API_KEY", None)
     # Note: rerank_binding is already set by argparse, no need to override from env
diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 8e3f9af1..8214d601 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -11,6 +11,7 @@ import signal
 import sys
 import uvicorn
 import pipmaster as pm
+import inspect
 from fastapi.staticfiles import StaticFiles
 from fastapi.responses import RedirectResponse
 from pathlib import Path
@@ -408,6 +409,22 @@ def create_app(args):
             logger.error(f"Unsupported rerank binding: {args.rerank_binding}")
             raise ValueError(f"Unsupported rerank binding: {args.rerank_binding}")
 
+        # Get default values from selected_rerank_func if args values are None
+        if args.rerank_model is None or args.rerank_binding_host is None:
+            sig = inspect.signature(selected_rerank_func)
+
+            # Set default model if args.rerank_model is None
+            if args.rerank_model is None and "model" in sig.parameters:
+                default_model = sig.parameters["model"].default
+                if default_model != inspect.Parameter.empty:
+                    args.rerank_model = default_model
+
+            # Set default base_url if args.rerank_binding_host is None
+            if args.rerank_binding_host is None and "base_url" in sig.parameters:
+                default_base_url = sig.parameters["base_url"].default
+                if default_base_url != inspect.Parameter.empty:
+                    args.rerank_binding_host = default_base_url
+
         async def server_rerank_func(
             query: str, documents: list, top_n: int = None, extra_body: dict = None
         ):
@@ -415,19 +432,19 @@ def create_app(args):
             return await selected_rerank_func(
                 query=query,
                 documents=documents,
+                top_n=top_n,
+                api_key=args.rerank_binding_api_key,
                 model=args.rerank_model,
                 base_url=args.rerank_binding_host,
-                api_key=args.rerank_binding_api_key,
-                top_n=top_n,
                 extra_body=extra_body,
             )
 
         rerank_model_func = server_rerank_func
         logger.info(
-            f"Rerank enabled: {args.rerank_model} using {args.rerank_binding} provider"
+            f"Reranking is enabled: {args.rerank_model or 'default model'} using {args.rerank_binding} provider"
         )
     else:
-        logger.info("Rerank disabled")
+        logger.info("Reranking is disabled")
 
     # Create ollama_server_infos from command line arguments
     from lightrag.api.config import OllamaServerInfos
@@ -635,7 +652,6 @@ def create_app(args):
                     "max_graph_nodes": args.max_graph_nodes,
                     # Rerank configuration
                     "enable_rerank": args.enable_rerank,
-                    "rerank_configured": rerank_model_func is not None,
                     "rerank_binding": args.rerank_binding
                     if args.enable_rerank
                     else None,
diff --git a/lightrag/base.py b/lightrag/base.py
index 9ba34280..cfe48eea 100644
--- a/lightrag/base.py
+++ b/lightrag/base.py
@@ -22,7 +22,6 @@ from .constants import (
     DEFAULT_MAX_RELATION_TOKENS,
     DEFAULT_MAX_TOTAL_TOKENS,
     DEFAULT_HISTORY_TURNS,
-    DEFAULT_ENABLE_RERANK,
     DEFAULT_OLLAMA_MODEL_NAME,
     DEFAULT_OLLAMA_MODEL_TAG,
     DEFAULT_OLLAMA_MODEL_SIZE,
@@ -158,9 +157,7 @@ class QueryParam:
     If proivded, this will be use instead of the default vaulue from prompt template.
     """
 
-    enable_rerank: bool = (
-        os.getenv("ENABLE_RERANK", str(DEFAULT_ENABLE_RERANK).lower()).lower() == "true"
-    )
+    enable_rerank: bool = os.getenv("ENABLE_RERANK", "false").lower() == "true"
     """Enable reranking for retrieved text chunks. If True but no rerank model is configured, a warning will be issued.
     Default is True to enable reranking when rerank model is available.
     """
diff --git a/lightrag/constants.py b/lightrag/constants.py
index d9ab121d..6aa845af 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -32,8 +32,8 @@ DEFAULT_KG_CHUNK_PICK_METHOD = "VECTOR"
 DEFAULT_HISTORY_TURNS = 0
 
 # Rerank configuration defaults
-DEFAULT_ENABLE_RERANK = True
 DEFAULT_MIN_RERANK_SCORE = 0.0
+DEFAULT_RERANK_BINDING = "cohere"
 
 # File path configuration for vector and graph database(Should not be changed, used in Milvus Schema)
 DEFAULT_MAX_FILE_PATH_LENGTH = 32768
diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index 8b214c16..721181d5 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -525,14 +525,6 @@ class LightRAG:
             )
         )
 
-        # Init Rerank
-        if self.rerank_model_func:
-            logger.info("Rerank model initialized for improved retrieval quality")
-        else:
-            logger.warning(
-                "Rerank is enabled but no rerank_model_func provided. Reranking will be skipped."
-            )
-
         self._storages_status = StoragesStatus.CREATED
 
     async def initialize_storages(self):
diff --git a/lightrag/llm.py b/lightrag/llm.py
deleted file mode 100644
index e5f98cf8..00000000
--- a/lightrag/llm.py
+++ /dev/null
@@ -1,101 +0,0 @@
-from __future__ import annotations
-
-from typing import Callable, Any
-from pydantic import BaseModel, Field
-
-
-class Model(BaseModel):
-    """
-    This is a Pydantic model class named 'Model' that is used to define a custom language model.
-
-    Attributes:
-        gen_func (Callable[[Any], str]): A callable function that generates the response from the language model.
-            The function should take any argument and return a string.
-        kwargs (Dict[str, Any]): A dictionary that contains the arguments to pass to the callable function.
-            This could include parameters such as the model name, API key, etc.
-
-    Example usage:
-        Model(gen_func=openai_complete_if_cache, kwargs={"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY_1"]})
-
-    In this example, 'openai_complete_if_cache' is the callable function that generates the response from the OpenAI model.
-    The 'kwargs' dictionary contains the model name and API key to be passed to the function.
-    """
-
-    gen_func: Callable[[Any], str] = Field(
-        ...,
-        description="A function that generates the response from the llm. The response must be a string",
-    )
-    kwargs: dict[str, Any] = Field(
-        ...,
-        description="The arguments to pass to the callable function. Eg. the api key, model name, etc",
-    )
-
-    class Config:
-        arbitrary_types_allowed = True
-
-
-class MultiModel:
-    """
-    Distributes the load across multiple language models. Useful for circumventing low rate limits with certain api providers especially if you are on the free tier.
-    Could also be used for spliting across diffrent models or providers.
-
-    Attributes:
-        models (List[Model]): A list of language models to be used.
-
-    Usage example:
-        ```python
-        models = [
-            Model(gen_func=openai_complete_if_cache, kwargs={"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY_1"]}),
-            Model(gen_func=openai_complete_if_cache, kwargs={"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY_2"]}),
-            Model(gen_func=openai_complete_if_cache, kwargs={"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY_3"]}),
-            Model(gen_func=openai_complete_if_cache, kwargs={"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY_4"]}),
-            Model(gen_func=openai_complete_if_cache, kwargs={"model": "gpt-4", "api_key": os.environ["OPENAI_API_KEY_5"]}),
-        ]
-        multi_model = MultiModel(models)
-        rag = LightRAG(
-            llm_model_func=multi_model.llm_model_func
-            / ..other args
-            )
-        ```
-    """
-
-    def __init__(self, models: list[Model]):
-        self._models = models
-        self._current_model = 0
-
-    def _next_model(self):
-        self._current_model = (self._current_model + 1) % len(self._models)
-        return self._models[self._current_model]
-
-    async def llm_model_func(
-        self,
-        prompt: str,
-        system_prompt: str | None = None,
-        history_messages: list[dict[str, Any]] = [],
-        **kwargs: Any,
-    ) -> str:
-        kwargs.pop("model", None)  # stop from overwriting the custom model name
-        kwargs.pop("keyword_extraction", None)
-        kwargs.pop("mode", None)
-        next_model = self._next_model()
-        args = dict(
-            prompt=prompt,
-            system_prompt=system_prompt,
-            history_messages=history_messages,
-            **kwargs,
-            **next_model.kwargs,
-        )
-
-        return await next_model.gen_func(**args)
-
-
-if __name__ == "__main__":
-    import asyncio
-
-    async def main():
-        from lightrag.llm.openai import gpt_4o_mini_complete
-
-        result = await gpt_4o_mini_complete("How are you?")
-        print(result)
-
-    asyncio.run(main())
diff --git a/lightrag/rerank.py b/lightrag/rerank.py
index dbac1098..35551f5a 100644
--- a/lightrag/rerank.py
+++ b/lightrag/rerank.py
@@ -32,7 +32,7 @@ async def generic_rerank_api(
     documents: List[str],
     model: str,
     base_url: str,
-    api_key: str,
+    api_key: Optional[str],
     top_n: Optional[int] = None,
     return_documents: Optional[bool] = None,
     extra_body: Optional[Dict[str, Any]] = None,
@@ -56,13 +56,12 @@ async def generic_rerank_api(
     Returns:
         List of dictionary of ["index": int, "relevance_score": float]
     """
-    if not api_key:
-        raise ValueError("API key is required")
+    if not base_url:
+        raise ValueError("Base URL is required")
 
-    headers = {
-        "Content-Type": "application/json",
-        "Authorization": f"Bearer {api_key}",
-    }
+    headers = {"Content-Type": "application/json"}
+    if api_key is not None:
+        headers["Authorization"] = f"Bearer {api_key}"
 
     # Build request payload based on request format
     if request_format == "aliyun":
@@ -119,7 +118,6 @@ async def generic_rerank_api(
                     error_text.strip().startswith("<!DOCTYPE html>")
                     or "text/html" in content_type
                 )
-
                 if is_html_error:
                     if response.status == 502:
                         clean_error = "Bad Gateway (502) - Rerank service temporarily unavailable. Please try again in a few minutes."
@@ -131,7 +129,6 @@ async def generic_rerank_api(
                         clean_error = f"HTTP {response.status} - Rerank service error. Please try again later."
                 else:
                     clean_error = error_text
-
                 logger.error(f"Rerank API error {response.status}: {clean_error}")
                 raise aiohttp.ClientResponseError(
                     request_info=response.request_info,
@@ -142,17 +139,25 @@ async def generic_rerank_api(
 
             response_json = await response.json()
 
-            # Handle different response formats
             if response_format == "aliyun":
                 # Aliyun format: {"output": {"results": [...]}}
-                output = response_json.get("output", {})
-                results = output.get("results", [])
+                results = response_json.get("output", {}).get("results", [])
+                if not isinstance(results, list):
+                    logger.warning(
+                        f"Expected 'output.results' to be list, got {type(results)}: {results}"
+                    )
+                    results = []
+
             elif response_format == "standard":
                 # Standard format: {"results": [...]}
                 results = response_json.get("results", [])
+                if not isinstance(results, list):
+                    logger.warning(
+                        f"Expected 'results' to be list, got {type(results)}: {results}"
+                    )
+                    results = []
             else:
                 raise ValueError(f"Unsupported response format: {response_format}")
-
             if not results:
                 logger.warning("Rerank API returned empty results")
                 return []
@@ -170,7 +175,7 @@ async def cohere_rerank(
     top_n: Optional[int] = None,
     api_key: Optional[str] = None,
     model: str = "rerank-v3.5",
-    base_url: str = "https://ai.znipower.com:5017/rerank",
+    base_url: str = "https://api.cohere.com/v2/rerank",
     extra_body: Optional[Dict[str, Any]] = None,
 ) -> List[Dict[str, Any]]:
     """
diff --git a/lightrag/utils.py b/lightrag/utils.py
index 65e22d1a..2d3d485b 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -1995,7 +1995,7 @@ async def apply_rerank_if_enabled(
         rerank_results = await rerank_func(
             query=query,
             documents=document_texts,
-            top_n=top_n or len(retrieved_docs),
+            top_n=top_n,
         )
 
         # Process rerank results based on return format

From 47485b130de5a56128517a559cd3a25d197ee456 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 02:04:14 +0800
Subject: [PATCH 022/141] refac(ui): Show rerank binding info on status card

- Remove separate ENABLE_RERANK flag in favor of rerank_binding="null"
- Change default rerank binding from "cohere" to "null" (disabled)
- Update UI to display both rerank binding and model information
---
 env.example                                         |  5 ++---
 lightrag/api/config.py                              |  8 +-------
 lightrag/api/lightrag_server.py                     | 12 +++++-------
 lightrag/constants.py                               |  2 +-
 lightrag_webui/src/api/lightrag.ts                  |  1 +
 lightrag_webui/src/components/status/StatusCard.tsx |  2 +-
 6 files changed, 11 insertions(+), 19 deletions(-)

diff --git a/env.example b/env.example
index c39faa5f..e4521132 100644
--- a/env.example
+++ b/env.example
@@ -87,11 +87,10 @@ ENABLE_LLM_CACHE=true
 
 #########################################################
 ### Reranking configuration
-### RERANK_BINDING type:  cohere, jina, aliyun
+### RERANK_BINDING type:  null, cohere, jina, aliyun
 ### For rerank model deployed by vLLM use cohere binding
 #########################################################
-ENABLE_RERANK=False
-RERANK_BINDING=cohere
+RERANK_BINDING=null
 ### rerank score chunk filter(set to 0.0 to keep all chunks, 0.6 or above if LLM is not strong enought)
 # MIN_RERANK_SCORE=0.0
 
diff --git a/lightrag/api/config.py b/lightrag/api/config.py
index 92952ec4..a5e352dc 100644
--- a/lightrag/api/config.py
+++ b/lightrag/api/config.py
@@ -228,15 +228,9 @@ def parse_args() -> argparse.Namespace:
         "--rerank-binding",
         type=str,
         default=get_env_value("RERANK_BINDING", DEFAULT_RERANK_BINDING),
-        choices=["cohere", "jina", "aliyun"],
+        choices=["null", "cohere", "jina", "aliyun"],
         help=f"Rerank binding type (default: from env or {DEFAULT_RERANK_BINDING})",
     )
-    parser.add_argument(
-        "--enable-rerank",
-        action="store_true",
-        default=get_env_value("ENABLE_RERANK", False, bool),
-        help="Enable rerank functionality (default: from env or disalbed)",
-    )
 
     # Conditionally add binding options defined in binding_options module
     # This will add command line arguments for all binding options (e.g., --ollama-embedding-num_ctx)
diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 8214d601..7d94eec4 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -393,7 +393,7 @@ def create_app(args):
 
     # Configure rerank function based on enable_rerank parameter
     rerank_model_func = None
-    if args.enable_rerank and args.rerank_binding:
+    if args.rerank_binding != "null":
         from lightrag.rerank import cohere_rerank, jina_rerank, ali_rerank
 
         # Map rerank binding to corresponding function
@@ -651,13 +651,11 @@ def create_app(args):
                     "workspace": args.workspace,
                     "max_graph_nodes": args.max_graph_nodes,
                     # Rerank configuration
-                    "enable_rerank": args.enable_rerank,
-                    "rerank_binding": args.rerank_binding
-                    if args.enable_rerank
-                    else None,
-                    "rerank_model": args.rerank_model if args.enable_rerank else None,
+                    "enable_rerank": rerank_model_func is not None,
+                    "rerank_binding": args.rerank_binding,
+                    "rerank_model": args.rerank_model if rerank_model_func else None,
                     "rerank_binding_host": args.rerank_binding_host
-                    if args.enable_rerank
+                    if rerank_model_func
                     else None,
                     # Environment variable status (requested configuration)
                     "summary_language": args.summary_language,
diff --git a/lightrag/constants.py b/lightrag/constants.py
index 6aa845af..9445872e 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -33,7 +33,7 @@ DEFAULT_HISTORY_TURNS = 0
 
 # Rerank configuration defaults
 DEFAULT_MIN_RERANK_SCORE = 0.0
-DEFAULT_RERANK_BINDING = "cohere"
+DEFAULT_RERANK_BINDING = "null"
 
 # File path configuration for vector and graph database(Should not be changed, used in Milvus Schema)
 DEFAULT_MAX_FILE_PATH_LENGTH = 32768
diff --git a/lightrag_webui/src/api/lightrag.ts b/lightrag_webui/src/api/lightrag.ts
index 98fc59ca..d2f23f12 100644
--- a/lightrag_webui/src/api/lightrag.ts
+++ b/lightrag_webui/src/api/lightrag.ts
@@ -43,6 +43,7 @@ export type LightragStatus = {
     workspace?: string
     max_graph_nodes?: string
     enable_rerank?: boolean
+    rerank_binding?: string | null
     rerank_model?: string | null
     rerank_binding_host?: string | null
     summary_language: string
diff --git a/lightrag_webui/src/components/status/StatusCard.tsx b/lightrag_webui/src/components/status/StatusCard.tsx
index a084ea13..8eeaaf70 100644
--- a/lightrag_webui/src/components/status/StatusCard.tsx
+++ b/lightrag_webui/src/components/status/StatusCard.tsx
@@ -52,7 +52,7 @@ const StatusCard = ({ status }: { status: LightragStatus | null }) => {
             <span>{t('graphPanel.statusCard.rerankerBindingHost')}:</span>
             <span>{status.configuration.rerank_binding_host || '-'}</span>
             <span>{t('graphPanel.statusCard.rerankerModel')}:</span>
-            <span>{status.configuration.rerank_model || '-'}</span>
+            <span>{(status.configuration.rerank_binding || '-')} : {(status.configuration.rerank_model || '-')}</span>
           </div>
         </div>
       )}

From 7f404bbecb4feae5a034c8acbdc5d85058572dc7 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 02:05:09 +0800
Subject: [PATCH 023/141] Update webui assets and bump api version to 0207

---
 lightrag/api/__init__.py                                        | 2 +-
 .../api/webui/assets/{index-B90LgL3h.js => index-B8PWUG__.js}   | 2 +-
 lightrag/api/webui/index.html                                   | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)
 rename lightrag/api/webui/assets/{index-B90LgL3h.js => index-B8PWUG__.js} (93%)

diff --git a/lightrag/api/__init__.py b/lightrag/api/__init__.py
index d7154027..ac183b60 100644
--- a/lightrag/api/__init__.py
+++ b/lightrag/api/__init__.py
@@ -1 +1 @@
-__api_version__ = "0206"
+__api_version__ = "0207"
diff --git a/lightrag/api/webui/assets/index-B90LgL3h.js b/lightrag/api/webui/assets/index-B8PWUG__.js
similarity index 93%
rename from lightrag/api/webui/assets/index-B90LgL3h.js
rename to lightrag/api/webui/assets/index-B8PWUG__.js
index c96c2eed..b2f8612b 100644
--- a/lightrag/api/webui/assets/index-B90LgL3h.js
+++ b/lightrag/api/webui/assets/index-B8PWUG__.js
@@ -28,7 +28,7 @@ You can add a description to the \`${Na}\` by passing a \`${Dd}\` component as a
 
 Alternatively, you can use your own component as a description by assigning it an \`id\` and passing the same value to the \`aria-describedby\` prop in \`${Na}\`. If the description is confusing or duplicative for sighted users, you can use the \`@radix-ui/react-visually-hidden\` primitive as a wrapper around your description component.
 
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max-w-lg translate-x-[-50%] translate-y-[-50%] gap-4 border p-6 shadow-lg duration-200 sm:rounded-lg",m),...y})]}));Ld.displayName=Od.displayName;const qd=({className:m,...y})=>o.jsx("div",{className:Ve("flex flex-col space-y-2 text-center sm:text-left",m),...y});qd.displayName="AlertDialogHeader";const Bd=E.forwardRef(({className:m,...y},x)=>o.jsx(jd,{ref:x,className:Ve("text-lg font-semibold",m),...y}));Bd.displayName=jd.displayName;const Gd=E.forwardRef(({className:m,...y},x)=>o.jsx(Ud,{ref:x,className:Ve("text-muted-foreground text-sm",m),...y}));Gd.displayName=Ud.displayName;const vp=E.forwardRef(({className:m,...y},x)=>o.jsx(_d,{ref:x,className:Ve(od(),m),...y}));vp.displayName=_d.displayName;const bp=E.forwardRef(({className:m,...y},x)=>o.jsx(Rd,{ref:x,className:Ve(od({variant:"outline"}),"mt-2 sm:mt-0",m),...y}));bp.displayName=Rd.displayName;const Sp=({open:m,onOpenChange:y})=>{const{t:x}=Bl(),d=we.use.apiKey(),[N,_]=E.useState(""),H=sl.use.message();E.useEffect(()=>{_(d||"")},[d,m]),E.useEffect(()=>{H&&(H.includes(rd)||H.includes(fd))&&y(!0)},[H,y]);const P=E.useCallback(()=>{we.setState({apiKey:N||null}),y(!1)},[N,y]),Y=E.useCallback($=>{_($.target.value)},[_]);return o.jsx(pp,{open:m,onOpenChange:y,children:o.jsxs(Ld,{children:[o.jsxs(qd,{children:[o.jsx(Bd,{children:x("apiKeyAlert.title")}),o.jsx(Gd,{children:x("apiKeyAlert.description")})]}),o.jsxs("div",{className:"flex flex-col gap-4",children:[o.jsxs("form",{className:"flex gap-2",onSubmit:$=>$.preventDefault(),children:[o.jsx(us,{type:"password",value:N,onChange:Y,placeholder:x("apiKeyAlert.placeholder"),className:"max-h-full w-full min-w-0",autoComplete:"off"}),o.jsx(Cn,{onClick:P,variant:"outline",size:"sm",children:x("apiKeyAlert.save")})]}),H&&o.jsx("div",{className:"text-sm text-red-500",children:H})]})]})})},Tp=({status:m})=>{const{t:y}=Bl();return m?o.jsxs("div",{className:"min-w-[300px] space-y-2 text-xs",children:[o.jsxs("div",{className:"space-y-1",children:[o.jsx("h4",{className:"font-medium",children:y("graphPanel.statusCard.serverInfo")}),o.jsxs("div",{className:"text-foreground grid grid-cols-[160px_1fr] gap-1",children:[o.jsxs("span",{children:[y("graphPanel.statusCard.workingDirectory"),":"]}),o.jsx("span",{className:"truncate",children:m.working_directory}),o.jsxs("span",{children:[y("graphPanel.statusCard.inputDirectory"),":"]}),o.jsx("span",{className:"truncate",children:m.input_directory}),o.jsxs("span",{children:[y("graphPanel.statusCard.summarySettings"),":"]}),o.jsxs("span",{children:[m.configuration.summary_language," / LLM summary on ",m.configuration.force_llm_summary_on_merge.toString()," fragments"]}),o.jsxs("span",{children:[y("graphPanel.statusCard.threshold"),":"]}),o.jsxs("span",{children:["cosine ",m.configuration.cosine_threshold," / rerank_score ",m.configuration.min_rerank_score," / max_related 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border-t-transparent"}),o.jsx("p",{children:m("apiSite.loading")})]})})})}function Cp(){const m=sl.use.message(),y=we.use.enableHealthCheck(),x=we.use.currentTab(),[d,N]=E.useState(!1),[_,H]=E.useState(!0),P=E.useRef(!1),Y=E.useRef(!1),$=E.useCallback(V=>{N(V),V||sl.getState().clear()},[]),he=E.useRef(!0);E.useEffect(()=>{he.current=!0;const V=()=>{he.current=!1};return window.addEventListener("beforeunload",V),()=>{he.current=!1,window.removeEventListener("beforeunload",V)}},[]),E.useEffect(()=>{const V=async()=>{try{he.current&&await sl.getState().check()}catch(pe){console.error("Health check error:",pe)}};if(sl.getState().setHealthCheckFunction(V),!y||d){sl.getState().clearHealthCheckTimer();return}return Y.current||(Y.current=!0),sl.getState().resetHealthCheckTimer(),()=>{sl.getState().clearHealthCheckTimer()}},[y,d]),E.useEffect(()=>{(async()=>{if(P.current)return;if(P.current=!0,sessionStorage.getItem("VERSION_CHECKED_FROM_LOGIN")==="true"){H(!1);return}try{H(!0);const ae=localStorage.getItem("LIGHTRAG-API-TOKEN"),C=await gd();if(!C.auth_configured&&C.access_token)ql.getState().login(C.access_token,!0,C.core_version,C.api_version,C.webui_title||null,C.webui_description||null);else if(ae&&(C.core_version||C.api_version||C.webui_title||C.webui_description)){const yl=C.auth_mode==="disabled"||ql.getState().isGuestMode;ql.getState().login(ae,yl,C.core_version,C.api_version,C.webui_title||null,C.webui_description||null)}sessionStorage.setItem("VERSION_CHECKED_FROM_LOGIN","true")}catch(ae){console.error("Failed to get version info:",ae)}finally{H(!1)}})()},[]);const ge=E.useCallback(V=>we.getState().setCurrentTab(V),[]);return E.useEffect(()=>{m&&(m.includes(rd)||m.includes(fd))&&N(!0)},[m]),o.jsx(hd,{children:o.jsx(np,{children:_?o.jsxs("div",{className:"flex h-screen w-screen flex-col",children:[o.jsxs("header",{className:"border-border/40 bg-background/95 supports-[backdrop-filter]:bg-background/60 sticky top-0 z-50 flex h-10 w-full border-b px-4 backdrop-blur",children:[o.jsx("div",{className:"min-w-[200px] w-auto flex items-center",children:o.jsxs("a",{href:dd,className:"flex items-center gap-2",children:[o.jsx(ss,{className:"size-4 text-emerald-400","aria-hidden":"true"}),o.jsx("span",{className:"font-bold md:inline-block",children:is.name})]})}),o.jsx("div",{className:"flex h-10 flex-1 items-center justify-center"}),o.jsx("nav",{className:"w-[200px] flex items-center justify-end"})]}),o.jsx("div",{className:"flex flex-1 items-center justify-center",children:o.jsxs("div",{className:"text-center",children:[o.jsx("div",{className:"mb-2 h-8 w-8 animate-spin rounded-full border-4 border-primary border-t-transparent"}),o.jsx("p",{children:"Initializing..."})]})})]}):o.jsxs("main",{className:"flex h-screen w-screen overflow-hidden",children:[o.jsxs(Dp,{defaultValue:x,className:"!m-0 flex grow flex-col !p-0 overflow-hidden",onValueChange:ge,children:[o.jsx(Ep,{}),o.jsxs("div",{className:"relative grow",children:[o.jsx(zn,{value:"documents",className:"absolute top-0 right-0 bottom-0 left-0 overflow-auto",children:o.jsx(Pg,{})}),o.jsx(zn,{value:"knowledge-graph",className:"absolute top-0 right-0 bottom-0 left-0 overflow-hidden",children:o.jsx(Vg,{})}),o.jsx(zn,{value:"retrieval",className:"absolute top-0 right-0 bottom-0 left-0 overflow-hidden",children:o.jsx($g,{})}),o.jsx(zn,{value:"api",className:"absolute top-0 right-0 bottom-0 left-0 overflow-hidden",children:o.jsx(zp,{})})]})]}),y&&o.jsx(Ap,{}),o.jsx(Sp,{open:d,onOpenChange:$})]})})})}const Op=()=>{const m=sd(),{login:y,isAuthenticated:x}=ql(),{t:d}=Bl(),[N,_]=E.useState(!1),[H,P]=E.useState(""),[Y,$]=E.useState(""),[he,ge]=E.useState(!0),V=E.useRef(!1);if(E.useEffect(()=>{console.log("LoginPage mounted")},[]),E.useEffect(()=>((async()=>{if(!V.current){V.current=!0;try{if(x){m("/");return}const C=await gd();if((C.core_version||C.api_version)&&sessionStorage.setItem("VERSION_CHECKED_FROM_LOGIN","true"),!C.auth_configured&&C.access_token){y(C.access_token,!0,C.core_version,C.api_version,C.webui_title||null,C.webui_description||null),C.message&&En.info(C.message),m("/");return}ge(!1)}catch(C){console.error("Failed to check auth configuration:",C),ge(!1)}}})(),()=>{}),[x,y,m]),he)return null;const pe=async ae=>{if(ae.preventDefault(),!H||!Y){En.error(d("login.errorEmptyFields"));return}try{_(!0);const C=await kg(H,Y);localStorage.getItem("LIGHTRAG-PREVIOUS-USER")===H?console.log("Same user logging in, preserving chat history"):(console.log("Different user logging in, clearing chat history"),we.getState().setRetrievalHistory([])),localStorage.setItem("LIGHTRAG-PREVIOUS-USER",H);const _e=C.auth_mode==="disabled";y(C.access_token,_e,C.core_version,C.api_version,C.webui_title||null,C.webui_description||null),(C.core_version||C.api_version)&&sessionStorage.setItem("VERSION_CHECKED_FROM_LOGIN","true"),_e?En.info(C.message||d("login.authDisabled","Authentication is disabled. Using guest access.")):En.success(d("login.successMessage")),m("/")}catch(C){console.error("Login failed...",C),En.error(d("login.errorInvalidCredentials")),ql.getState().logout(),localStorage.removeItem("LIGHTRAG-API-TOKEN")}finally{_(!1)}};return o.jsxs("div",{className:"flex h-screen w-screen items-center justify-center bg-gradient-to-br from-emerald-50 to-teal-100 dark:from-gray-900 dark:to-gray-800",children:[o.jsx("div",{className:"absolute top-4 right-4 flex items-center gap-2",children:o.jsx(Yd,{className:"bg-white/30 dark:bg-gray-800/30 backdrop-blur-sm rounded-md"})}),o.jsxs(Qg,{className:"w-full max-w-[480px] shadow-lg mx-4",children:[o.jsx(Kg,{className:"flex items-center justify-center space-y-2 pb-8 pt-6",children:o.jsxs("div",{className:"flex flex-col items-center space-y-4",children:[o.jsxs("div",{className:"flex items-center gap-3",children:[o.jsx("img",{src:"logo.svg",alt:"LightRAG Logo",className:"h-12 w-12"}),o.jsx(ss,{className:"size-10 text-emerald-400","aria-hidden":"true"})]}),o.jsxs("div",{className:"text-center space-y-2",children:[o.jsx("h1",{className:"text-3xl font-bold tracking-tight",children:"LightRAG"}),o.jsx("p",{className:"text-muted-foreground text-sm",children:d("login.description")})]})]})}),o.jsx(Zg,{className:"px-8 pb-8",children:o.jsxs("form",{onSubmit:pe,className:"space-y-6",children:[o.jsxs("div",{className:"flex items-center gap-4",children:[o.jsx("label",{htmlFor:"username-input",className:"text-sm font-medium w-16 shrink-0",children:d("login.username")}),o.jsx(us,{id:"username-input",placeholder:d("login.usernamePlaceholder"),value:H,onChange:ae=>P(ae.target.value),required:!0,className:"h-11 flex-1"})]}),o.jsxs("div",{className:"flex items-center gap-4",children:[o.jsx("label",{htmlFor:"password-input",className:"text-sm font-medium w-16 shrink-0",children:d("login.password")}),o.jsx(us,{id:"password-input",type:"password",placeholder:d("login.passwordPlaceholder"),value:Y,onChange:ae=>$(ae.target.value),required:!0,className:"h-11 flex-1"})]}),o.jsx(Cn,{type:"submit",className:"w-full h-11 text-base font-medium mt-2",disabled:N,children:d(N?"login.loggingIn":"login.loginButton")})]})})]})]})},_p=()=>{const[m,y]=E.useState(!0),{isAuthenticated:x}=ql(),d=sd();return E.useEffect(()=>{md.setNavigate(d)},[d]),E.useEffect(()=>((async()=>{try{const _=localStorage.getItem("LIGHTRAG-API-TOKEN");if(_&&x){y(!1);return}_||ql.getState().logout()}catch(_){console.error("Auth initialization error:",_),x||ql.getState().logout()}finally{y(!1)}})(),()=>{}),[x]),E.useEffect(()=>{!m&&!x&&window.location.hash.slice(1)!=="/login"&&(console.log("Not authenticated, redirecting to login"),d("/login"))},[m,x,d]),m?null:o.jsxs(Eg,{children:[o.jsx(kf,{path:"/login",element:o.jsx(Op,{})}),o.jsx(kf,{path:"/*",element:x?o.jsx(Cp,{}):null})]})},Rp=()=>o.jsx(hd,{children:o.jsxs(Ng,{children:[o.jsx(_p,{}),o.jsx(Jg,{position:"bottom-center",theme:"system",closeButton:!0,richColors:!0})]})}),jp={language:"Language",theme:"Theme",light:"Light",dark:"Dark",system:"System"},Up={documents:"Documents",knowledgeGraph:"Knowledge Graph",retrieval:"Retrieval",api:"API",projectRepository:"Project Repository",logout:"Logout",themeToggle:{switchToLight:"Switch to light theme",switchToDark:"Switch to dark theme"}},Hp={description:"Please enter your account and password to log in to the system",username:"Username",usernamePlaceholder:"Please input a username",password:"Password",passwordPlaceholder:"Please input a password",loginButton:"Login",loggingIn:"Logging in...",successMessage:"Login succeeded",errorEmptyFields:"Please enter your username and password",errorInvalidCredentials:"Login failed, please check username and password",authDisabled:"Authentication is disabled. Using login free mode.",guestMode:"Login Free"},Lp={cancel:"Cancel",save:"Save",saving:"Saving...",saveFailed:"Save failed"},qp={clearDocuments:{button:"Clear",tooltip:"Clear documents",title:"Clear Documents",description:"This will remove all documents from the system",warning:"WARNING: This action will permanently delete all documents and cannot be undone!",confirm:"Do you really want to clear all documents?",confirmPrompt:"Type 'yes' to confirm this action",confirmPlaceholder:"Type yes to confirm",clearCache:"Clear LLM cache",confirmButton:"YES",clearing:"Clearing...",timeout:"Clear operation timed out, please try again",success:"Documents cleared successfully",cacheCleared:"Cache cleared successfully",cacheClearFailed:`Failed to clear cache:
 {{error}}`,failed:`Clear Documents Failed:
 {{message}}`,error:`Clear Documents Failed:
 {{error}}`},deleteDocuments:{button:"Delete",tooltip:"Delete selected documents",title:"Delete Documents",description:"This will permanently delete the selected documents from the system",warning:"WARNING: This action will permanently delete the selected documents and cannot be undone!",confirm:"Do you really want to delete {{count}} selected document(s)?",confirmPrompt:"Type 'yes' to confirm this action",confirmPlaceholder:"Type yes to confirm",confirmButton:"YES",deleteFileOption:"Also delete uploaded files",deleteFileTooltip:"Check this option to also delete the corresponding uploaded files on the server",success:"Document deletion pipeline started successfully",failed:`Delete Documents Failed:
diff --git a/lightrag/api/webui/index.html b/lightrag/api/webui/index.html
index 7499ac50..8a30cd59 100644
--- a/lightrag/api/webui/index.html
+++ b/lightrag/api/webui/index.html
@@ -8,7 +8,7 @@
     <link rel="icon" type="image/png" href="favicon.png" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>Lightrag</title>
-    <script type="module" crossorigin src="/webui/assets/index-B90LgL3h.js"></script>
+    <script type="module" crossorigin src="/webui/assets/index-B8PWUG__.js"></script>
     <link rel="modulepreload" crossorigin href="/webui/assets/react-vendor-DEwriMA6.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/ui-vendor-CeCm8EER.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/graph-vendor-B-X5JegA.js">

From 059003c9060cc3bd94cf941db08c28be505876ce Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 02:34:39 +0800
Subject: [PATCH 024/141] Rename allow_create to first_initialization for
 clarity

---
 lightrag/exceptions.py        |  4 ++--
 lightrag/kg/shared_storage.py | 12 +++++++-----
 2 files changed, 9 insertions(+), 7 deletions(-)

diff --git a/lightrag/exceptions.py b/lightrag/exceptions.py
index 190d0c18..d57df1ac 100644
--- a/lightrag/exceptions.py
+++ b/lightrag/exceptions.py
@@ -62,7 +62,7 @@ class APITimeoutError(APIConnectionError):
 
 class StorageNotInitializedError(RuntimeError):
     """Raised when storage operations are attempted before initialization."""
-    
+
     def __init__(self, storage_type: str = "Storage"):
         super().__init__(
             f"{storage_type} not initialized. Please ensure proper initialization:\n"
@@ -79,7 +79,7 @@ class StorageNotInitializedError(RuntimeError):
 
 class PipelineNotInitializedError(KeyError):
     """Raised when pipeline status is accessed before initialization."""
-    
+
     def __init__(self, namespace: str = ""):
         msg = (
             f"Pipeline namespace '{namespace}' not found. "
diff --git a/lightrag/kg/shared_storage.py b/lightrag/kg/shared_storage.py
index 02350c4c..e20dce52 100644
--- a/lightrag/kg/shared_storage.py
+++ b/lightrag/kg/shared_storage.py
@@ -1059,7 +1059,7 @@ async def initialize_pipeline_status():
     Initialize pipeline namespace with default values.
     This function is called during FASTAPI lifespan for each worker.
     """
-    pipeline_namespace = await get_namespace_data("pipeline_status", allow_create=True)
+    pipeline_namespace = await get_namespace_data("pipeline_status", first_init=True)
 
     async with get_internal_lock():
         # Check if already initialized by checking for required fields
@@ -1194,9 +1194,11 @@ async def try_initialize_namespace(namespace: str) -> bool:
     return False
 
 
-async def get_namespace_data(namespace: str, allow_create: bool = False) -> Dict[str, Any]:
+async def get_namespace_data(
+    namespace: str, first_init: bool = False
+) -> Dict[str, Any]:
     """get the shared data reference for specific namespace
-    
+
     Args:
         namespace: The namespace to retrieve
         allow_create: If True, allows creation of the namespace if it doesn't exist.
@@ -1212,11 +1214,11 @@ async def get_namespace_data(namespace: str, allow_create: bool = False) -> Dict
     async with get_internal_lock():
         if namespace not in _shared_dicts:
             # Special handling for pipeline_status namespace
-            if namespace == "pipeline_status" and not allow_create:
+            if namespace == "pipeline_status" and not first_init:
                 # Check if pipeline_status should have been initialized but wasn't
                 # This helps users understand they need to call initialize_pipeline_status()
                 raise PipelineNotInitializedError(namespace)
-            
+
             # For other namespaces or when allow_create=True, create them dynamically
             if _is_multiprocess and _manager is not None:
                 _shared_dicts[namespace] = _manager.dict()

From 8a293a2c076d374a0c3ae6ef654196aa2959c255 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 02:39:12 +0800
Subject: [PATCH 025/141] Fix linting

---
 lightrag/tools/check_initialization.py | 106 +++++++++++++------------
 1 file changed, 55 insertions(+), 51 deletions(-)

diff --git a/lightrag/tools/check_initialization.py b/lightrag/tools/check_initialization.py
index b10e31ba..6bcb17e3 100644
--- a/lightrag/tools/check_initialization.py
+++ b/lightrag/tools/check_initialization.py
@@ -2,7 +2,7 @@
 """
 Diagnostic tool to check LightRAG initialization status.
 
-This tool helps developers verify that their LightRAG instance is properly 
+This tool helps developers verify that their LightRAG instance is properly
 initialized before use, preventing common initialization errors.
 
 Usage:
@@ -11,7 +11,6 @@ Usage:
 
 import asyncio
 import sys
-from typing import Optional
 from pathlib import Path
 
 # Add parent directory to path for imports
@@ -24,44 +23,46 @@ from lightrag.base import StoragesStatus
 async def check_lightrag_setup(rag_instance: LightRAG, verbose: bool = False) -> bool:
     """
     Check if a LightRAG instance is properly initialized.
-    
+
     Args:
         rag_instance: The LightRAG instance to check
         verbose: If True, print detailed diagnostic information
-        
+
     Returns:
         True if properly initialized, False otherwise
     """
     issues = []
     warnings = []
-    
+
     print("🔍 Checking LightRAG initialization status...\n")
-    
+
     # Check storage initialization status
-    if not hasattr(rag_instance, '_storages_status'):
+    if not hasattr(rag_instance, "_storages_status"):
         issues.append("LightRAG instance missing _storages_status attribute")
     elif rag_instance._storages_status != StoragesStatus.INITIALIZED:
-        issues.append(f"Storages not initialized (status: {rag_instance._storages_status.name})")
+        issues.append(
+            f"Storages not initialized (status: {rag_instance._storages_status.name})"
+        )
     else:
         print("✅ Storage status: INITIALIZED")
-    
+
     # Check individual storage components
     storage_components = [
-        ('full_docs', 'Document storage'),
-        ('text_chunks', 'Text chunks storage'),
-        ('entities_vdb', 'Entity vector database'),
-        ('relationships_vdb', 'Relationship vector database'),
-        ('chunks_vdb', 'Chunks vector database'),
-        ('doc_status', 'Document status tracker'),
-        ('llm_response_cache', 'LLM response cache'),
-        ('full_entities', 'Entity storage'),
-        ('full_relations', 'Relation storage'),
-        ('chunk_entity_relation_graph', 'Graph storage')
+        ("full_docs", "Document storage"),
+        ("text_chunks", "Text chunks storage"),
+        ("entities_vdb", "Entity vector database"),
+        ("relationships_vdb", "Relationship vector database"),
+        ("chunks_vdb", "Chunks vector database"),
+        ("doc_status", "Document status tracker"),
+        ("llm_response_cache", "LLM response cache"),
+        ("full_entities", "Entity storage"),
+        ("full_relations", "Relation storage"),
+        ("chunk_entity_relation_graph", "Graph storage"),
     ]
-    
+
     if verbose:
         print("\n📦 Storage Components:")
-    
+
     for component, description in storage_components:
         if not hasattr(rag_instance, component):
             issues.append(f"Missing storage component: {component} ({description})")
@@ -69,52 +70,57 @@ async def check_lightrag_setup(rag_instance: LightRAG, verbose: bool = False) ->
             storage = getattr(rag_instance, component)
             if storage is None:
                 warnings.append(f"Storage {component} is None (might be optional)")
-            elif hasattr(storage, '_storage_lock'):
+            elif hasattr(storage, "_storage_lock"):
                 if storage._storage_lock is None:
                     issues.append(f"Storage {component} not initialized (lock is None)")
                 elif verbose:
                     print(f"  ✅ {description}: Ready")
             elif verbose:
                 print(f"  ✅ {description}: Ready")
-    
+
     # Check pipeline status
     try:
         from lightrag.kg.shared_storage import get_namespace_data
+
         get_namespace_data("pipeline_status")
         print("✅ Pipeline status: INITIALIZED")
     except KeyError:
-        issues.append("Pipeline status not initialized - call initialize_pipeline_status()")
+        issues.append(
+            "Pipeline status not initialized - call initialize_pipeline_status()"
+        )
     except Exception as e:
         issues.append(f"Error checking pipeline status: {str(e)}")
-    
+
     # Print results
     print("\n" + "=" * 50)
-    
+
     if issues:
         print("❌ Issues found:\n")
         for issue in issues:
             print(f"  • {issue}")
-        
+
         print("\n📝 To fix, run this initialization sequence:\n")
         print("  await rag.initialize_storages()")
         print("  from lightrag.kg.shared_storage import initialize_pipeline_status")
         print("  await initialize_pipeline_status()")
-        print("\n📚 Documentation: https://github.com/HKUDS/LightRAG#important-initialization-requirements")
-        
+        print(
+            "\n📚 Documentation: https://github.com/HKUDS/LightRAG#important-initialization-requirements"
+        )
+
         if warnings and verbose:
             print("\n⚠️  Warnings (might be normal):")
             for warning in warnings:
                 print(f"  • {warning}")
-        
+
         return False
     else:
         print("✅ LightRAG is properly initialized and ready to use!")
-        
+
         if warnings and verbose:
             print("\n⚠️  Warnings (might be normal):")
             for warning in warnings:
                 print(f"  • {warning}")
-        
+
         return True
 
 
@@ -122,55 +128,53 @@ async def demo():
     """Demonstrate the diagnostic tool with a test instance."""
     from lightrag.llm.openai import openai_embed, gpt_4o_mini_complete
     from lightrag.kg.shared_storage import initialize_pipeline_status
-    
+
     print("=" * 50)
     print("LightRAG Initialization Diagnostic Tool")
     print("=" * 50)
-    
+
     # Create test instance
     rag = LightRAG(
         working_dir="./test_diagnostic",
         embedding_func=openai_embed,
         llm_model_func=gpt_4o_mini_complete,
     )
-    
+
     print("\n🔴 BEFORE initialization:\n")
     await check_lightrag_setup(rag, verbose=True)
-    
+
     print("\n" + "=" * 50)
     print("\n🔄 Initializing...\n")
     await rag.initialize_storages()
     await initialize_pipeline_status()
-    
+
     print("\n🟢 AFTER initialization:\n")
     await check_lightrag_setup(rag, verbose=True)
-    
+
     # Cleanup
     import shutil
+
     shutil.rmtree("./test_diagnostic", ignore_errors=True)
 
 
 if __name__ == "__main__":
     import argparse
-    
-    parser = argparse.ArgumentParser(
-        description="Check LightRAG initialization status"
+
+    parser = argparse.ArgumentParser(description="Check LightRAG initialization status")
+    parser.add_argument(
+        "--demo", action="store_true", help="Run a demonstration with a test instance"
     )
     parser.add_argument(
-        "--demo", 
+        "--verbose",
+        "-v",
         action="store_true",
-        help="Run a demonstration with a test instance"
+        help="Show detailed diagnostic information",
     )
-    parser.add_argument(
-        "--verbose", "-v",
-        action="store_true",
-        help="Show detailed diagnostic information"
-    )
-    
+
     args = parser.parse_args()
-    
+
     if args.demo:
         asyncio.run(demo())
     else:
         print("Run with --demo to see the diagnostic tool in action")
-        print("Or import this module and use check_lightrag_setup() with your instance")
\ No newline at end of file
+        print("Or import this module and use check_lightrag_setup() with your instance")

From 1be9a54c8d44d51302b8d1898dcaa3907bc1a621 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 09:46:51 +0800
Subject: [PATCH 026/141] Rename ENABLE_RERANK to RERANK_BY_DEFAULT and update
 default to true

---
 env.example                     | 2 ++
 lightrag/api/lightrag_server.py | 2 +-
 lightrag/base.py                | 2 +-
 3 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/env.example b/env.example
index e4521132..01b87586 100644
--- a/env.example
+++ b/env.example
@@ -91,6 +91,8 @@ ENABLE_LLM_CACHE=true
 ### For rerank model deployed by vLLM use cohere binding
 #########################################################
 RERANK_BINDING=null
+### Enable rerank by default in query params
+# RERANK_BY_DEFAULT=True
 ### rerank score chunk filter(set to 0.0 to keep all chunks, 0.6 or above if LLM is not strong enought)
 # MIN_RERANK_SCORE=0.0
 
diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 7d94eec4..328e7953 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -391,7 +391,7 @@ def create_app(args):
         ),
     )
 
-    # Configure rerank function based on enable_rerank parameter
+    # Configure rerank function based on args.rerank_bindingparameter
     rerank_model_func = None
     if args.rerank_binding != "null":
         from lightrag.rerank import cohere_rerank, jina_rerank, ali_rerank
diff --git a/lightrag/base.py b/lightrag/base.py
index cfe48eea..fe92e785 100644
--- a/lightrag/base.py
+++ b/lightrag/base.py
@@ -157,7 +157,7 @@ class QueryParam:
     If proivded, this will be use instead of the default vaulue from prompt template.
     """
 
-    enable_rerank: bool = os.getenv("ENABLE_RERANK", "false").lower() == "true"
+    enable_rerank: bool = os.getenv("RERANK_BY_DEFAULT", "true").lower() == "true"
     """Enable reranking for retrieved text chunks. If True but no rerank model is configured, a warning will be issued.
     Default is True to enable reranking when rerank model is available.
     """

From 9bc349ddd6330b51e72602234095b29911eede80 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 11:50:58 +0800
Subject: [PATCH 027/141] Improve Empty Keyword Handling logic

---
 env.example         |  2 +-
 lightrag/operate.py | 56 ++++++++++++++++++++++-----------------------
 2 files changed, 29 insertions(+), 29 deletions(-)

diff --git a/env.example b/env.example
index 01b87586..f622a80b 100644
--- a/env.example
+++ b/env.example
@@ -91,7 +91,7 @@ ENABLE_LLM_CACHE=true
 ### For rerank model deployed by vLLM use cohere binding
 #########################################################
 RERANK_BINDING=null
-### Enable rerank by default in query params
+### Enable rerank by default in query params when RERANK_BINDING is not null
 # RERANK_BY_DEFAULT=True
 ### rerank score chunk filter(set to 0.0 to keep all chunks, 0.6 or above if LLM is not strong enought)
 # MIN_RERANK_SCORE=0.0
diff --git a/lightrag/operate.py b/lightrag/operate.py
index 9fefdb70..1e1ccbb6 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -1727,6 +1727,9 @@ async def kg_query(
     system_prompt: str | None = None,
     chunks_vdb: BaseVectorStorage = None,
 ) -> str | AsyncIterator[str]:
+    if not query:
+        return PROMPTS["fail_response"]
+
     if query_param.model_func:
         use_model_func = query_param.model_func
     else:
@@ -1763,21 +1766,16 @@ async def kg_query(
     logger.debug(f"Low-level  keywords: {ll_keywords}")
 
     # Handle empty keywords
+    if ll_keywords == [] and query_param.mode in ["local", "hybrid", "mix"]:
+        logger.warning("low_level_keywords is empty")
+    if hl_keywords == [] and query_param.mode in ["global", "hybrid", "mix"]:
+        logger.warning("high_level_keywords is empty")
     if hl_keywords == [] and ll_keywords == []:
-        logger.warning("low_level_keywords and high_level_keywords is empty")
-        return PROMPTS["fail_response"]
-    if ll_keywords == [] and query_param.mode in ["local", "hybrid"]:
-        logger.warning(
-            "low_level_keywords is empty, switching from %s mode to global mode",
-            query_param.mode,
-        )
-        query_param.mode = "global"
-    if hl_keywords == [] and query_param.mode in ["global", "hybrid"]:
-        logger.warning(
-            "high_level_keywords is empty, switching from %s mode to local mode",
-            query_param.mode,
-        )
-        query_param.mode = "local"
+        if len(query) < 50:
+            logger.warning(f"Forced low_level_keywords to origin query: {query}")
+            ll_keywords = [query]
+        else:
+            return PROMPTS["fail_response"]
 
     ll_keywords_str = ", ".join(ll_keywords) if ll_keywords else ""
     hl_keywords_str = ", ".join(hl_keywords) if hl_keywords else ""
@@ -2133,7 +2131,7 @@ async def _build_query_context(
                 query_embedding = None
 
     # Handle local and global modes
-    if query_param.mode == "local":
+    if query_param.mode == "local" and len(ll_keywords) > 0:
         local_entities, local_relations = await _get_node_data(
             ll_keywords,
             knowledge_graph_inst,
@@ -2141,7 +2139,7 @@ async def _build_query_context(
             query_param,
         )
 
-    elif query_param.mode == "global":
+    elif query_param.mode == "global" and len(hl_keywords) > 0:
         global_relations, global_entities = await _get_edge_data(
             hl_keywords,
             knowledge_graph_inst,
@@ -2150,18 +2148,20 @@ async def _build_query_context(
         )
 
     else:  # hybrid or mix mode
-        local_entities, local_relations = await _get_node_data(
-            ll_keywords,
-            knowledge_graph_inst,
-            entities_vdb,
-            query_param,
-        )
-        global_relations, global_entities = await _get_edge_data(
-            hl_keywords,
-            knowledge_graph_inst,
-            relationships_vdb,
-            query_param,
-        )
+        if len(ll_keywords) > 0:
+            local_entities, local_relations = await _get_node_data(
+                ll_keywords,
+                knowledge_graph_inst,
+                entities_vdb,
+                query_param,
+            )
+        if len(hl_keywords) > 0:
+            global_relations, global_entities = await _get_edge_data(
+                hl_keywords,
+                knowledge_graph_inst,
+                relationships_vdb,
+                query_param,
+            )
 
         # Get vector chunks first if in mix mode
         if query_param.mode == "mix" and chunks_vdb:

From 3d5e6226a94e09d3608bb24e0cda8c0db97b13ee Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 22:51:41 +0800
Subject: [PATCH 028/141] Refactored `rerank_example` file to utilize the
 updated rerank function.

---
 env.example                        |   6 +-
 examples/rerank_example.py         | 128 +++++++++++------------------
 lightrag/api/routers/ollama_api.py |   4 +-
 3 files changed, 53 insertions(+), 85 deletions(-)

diff --git a/env.example b/env.example
index f622a80b..41c77ede 100644
--- a/env.example
+++ b/env.example
@@ -96,14 +96,14 @@ RERANK_BINDING=null
 ### rerank score chunk filter(set to 0.0 to keep all chunks, 0.6 or above if LLM is not strong enought)
 # MIN_RERANK_SCORE=0.0
 
-### For local deployment
+### For local deployment with vLLM
 # RERANK_MODEL=BAAI/bge-reranker-v2-m3
-# RERANK_BINDING_HOST=http://localhost:8000
+# RERANK_BINDING_HOST=http://localhost:8000/v1/rerank
 # RERANK_BINDING_API_KEY=your_rerank_api_key_here
 
 ### Default value for Cohere AI
 # RERANK_MODEL=rerank-v3.5
-# RERANK_BINDING_HOST=https://ai.znipower.com:5017/rerank
+# RERANK_BINDING_HOST=https://api.cohere.com/v2/rerank
 # RERANK_BINDING_API_KEY=your_rerank_api_key_here
 
 ### Default value for Jina AI
diff --git a/examples/rerank_example.py b/examples/rerank_example.py
index 5754a750..c7db6656 100644
--- a/examples/rerank_example.py
+++ b/examples/rerank_example.py
@@ -5,15 +5,21 @@ This example demonstrates how to use rerank functionality with LightRAG
 to improve retrieval quality across different query modes.
 
 Configuration Required:
-1. Set your LLM API key and base URL in llm_model_func()
-2. Set your embedding API key and base URL in embedding_func()
-3. Set your rerank API key and base URL in the rerank configuration
-4. Or use environment variables (.env file):
-   - RERANK_MODEL=your_rerank_model
-   - RERANK_BINDING_HOST=your_rerank_endpoint
-   - RERANK_BINDING_API_KEY=your_rerank_api_key
+1. Set your OpenAI LLM API key and base URL with env vars
+    LLM_MODEL
+    LLM_BINDING_HOST
+    LLM_BINDING_API_KEY
+2. Set your OpenAI embedding API key and base URL with env vars:
+    EMBEDDING_MODEL
+    EMBEDDING_DIM
+    EMBEDDING_BINDING_HOST
+    EMBEDDING_BINDING_API_KEY
+3. Set your vLLM deployed AI rerank model setting with env vars:
+    RERANK_MODEL
+    RERANK_BINDING_HOST
+    RERANK_BINDING_API_KEY
 
-Note: Rerank is now controlled per query via the 'enable_rerank' parameter (default: True)
+Note: Rerank is controlled per query via the 'enable_rerank' parameter (default: True)
 """
 
 import asyncio
@@ -21,11 +27,13 @@ import os
 import numpy as np
 
 from lightrag import LightRAG, QueryParam
-from lightrag.rerank import custom_rerank, RerankModel
 from lightrag.llm.openai import openai_complete_if_cache, openai_embed
 from lightrag.utils import EmbeddingFunc, setup_logger
 from lightrag.kg.shared_storage import initialize_pipeline_status
 
+from functools import partial
+from lightrag.rerank import cohere_rerank
+
 # Set up your working directory
 WORKING_DIR = "./test_rerank"
 setup_logger("test_rerank")
@@ -38,12 +46,12 @@ async def llm_model_func(
     prompt, system_prompt=None, history_messages=[], **kwargs
 ) -> str:
     return await openai_complete_if_cache(
-        "gpt-4o-mini",
+        os.getenv("LLM_MODEL"),
         prompt,
         system_prompt=system_prompt,
         history_messages=history_messages,
-        api_key="your_llm_api_key_here",
-        base_url="https://api.your-llm-provider.com/v1",
+        api_key=os.getenv("LLM_BINDING_API_KEY"),
+        base_url=os.getenv("LLM_BINDING_HOST"),
         **kwargs,
     )
 
@@ -51,23 +59,18 @@ async def llm_model_func(
 async def embedding_func(texts: list[str]) -> np.ndarray:
     return await openai_embed(
         texts,
-        model="text-embedding-3-large",
-        api_key="your_embedding_api_key_here",
-        base_url="https://api.your-embedding-provider.com/v1",
+        model=os.getenv("EMBEDDING_MODEL"),
+        api_key=os.getenv("EMBEDDING_BINDING_API_KEY"),
+        base_url=os.getenv("EMBEDDING_BINDING_HOST"),
     )
 
 
-async def my_rerank_func(query: str, documents: list, top_n: int = None, **kwargs):
-    """Custom rerank function with all settings included"""
-    return await custom_rerank(
-        query=query,
-        documents=documents,
-        model="BAAI/bge-reranker-v2-m3",
-        base_url="https://api.your-rerank-provider.com/v1/rerank",
-        api_key="your_rerank_api_key_here",
-        top_n=top_n or 10,
-        **kwargs,
-    )
+rerank_model_func = partial(
+    cohere_rerank,
+    model=os.getenv("RERANK_MODEL"),
+    api_key=os.getenv("RERANK_BINDING_API_KEY"),
+    base_url=os.getenv("RERANK_BINDING_HOST"),
+)
 
 
 async def create_rag_with_rerank():
@@ -88,42 +91,7 @@ async def create_rag_with_rerank():
             func=embedding_func,
         ),
         # Rerank Configuration - provide the rerank function
-        rerank_model_func=my_rerank_func,
-    )
-
-    await rag.initialize_storages()
-    await initialize_pipeline_status()
-
-    return rag
-
-
-async def create_rag_with_rerank_model():
-    """Alternative: Create LightRAG instance using RerankModel wrapper"""
-
-    # Get embedding dimension
-    test_embedding = await embedding_func(["test"])
-    embedding_dim = test_embedding.shape[1]
-    print(f"Detected embedding dimension: {embedding_dim}")
-
-    # Method 2: Using RerankModel wrapper
-    rerank_model = RerankModel(
-        rerank_func=custom_rerank,
-        kwargs={
-            "model": "BAAI/bge-reranker-v2-m3",
-            "base_url": "https://api.your-rerank-provider.com/v1/rerank",
-            "api_key": "your_rerank_api_key_here",
-        },
-    )
-
-    rag = LightRAG(
-        working_dir=WORKING_DIR,
-        llm_model_func=llm_model_func,
-        embedding_func=EmbeddingFunc(
-            embedding_dim=embedding_dim,
-            max_token_size=8192,
-            func=embedding_func,
-        ),
-        rerank_model_func=rerank_model.rerank,
+        rerank_model_func=rerank_model_func,
     )
 
     await rag.initialize_storages()
@@ -136,7 +104,7 @@ async def test_rerank_with_different_settings():
     """
     Test rerank functionality with different enable_rerank settings
     """
-    print("🚀 Setting up LightRAG with Rerank functionality...")
+    print("\n\n🚀 Setting up LightRAG with Rerank functionality...")
 
     rag = await create_rag_with_rerank()
 
@@ -199,11 +167,11 @@ async def test_direct_rerank():
     print("=" * 40)
 
     documents = [
-        {"content": "Reranking significantly improves retrieval quality"},
-        {"content": "LightRAG supports advanced reranking capabilities"},
-        {"content": "Vector search finds semantically similar documents"},
-        {"content": "Natural language processing with modern transformers"},
-        {"content": "The quick brown fox jumps over the lazy dog"},
+        "Vector search finds semantically similar documents",
+        "LightRAG supports advanced reranking capabilities",
+        "Reranking significantly improves retrieval quality",
+        "Natural language processing with modern transformers",
+        "The quick brown fox jumps over the lazy dog",
     ]
 
     query = "rerank improve quality"
@@ -211,20 +179,20 @@ async def test_direct_rerank():
     print(f"Documents: {len(documents)}")
 
     try:
-        reranked_docs = await custom_rerank(
+        reranked_results = await rerank_model_func(
             query=query,
             documents=documents,
-            model="BAAI/bge-reranker-v2-m3",
-            base_url="https://api.your-rerank-provider.com/v1/rerank",
-            api_key="your_rerank_api_key_here",
-            top_n=3,
+            top_n=4,
         )
 
         print("\n✅ Rerank Results:")
-        for i, doc in enumerate(reranked_docs):
-            score = doc.get("rerank_score", "N/A")
-            content = doc.get("content", "")[:60]
-            print(f"  {i+1}. Score: {score:.4f} | {content}...")
+        i = 0
+        for result in reranked_results:
+            index = result["index"]
+            score = result["relevance_score"]
+            content = documents[index]
+            print(f"  {index}. Score: {score:.4f} | {content}...")
+            i += 1
 
     except Exception as e:
         print(f"❌ Rerank failed: {e}")
@@ -236,12 +204,12 @@ async def main():
     print("=" * 60)
 
     try:
-        # Test rerank with different enable_rerank settings
-        await test_rerank_with_different_settings()
-
         # Test direct rerank
         await test_direct_rerank()
 
+        # Test rerank with different enable_rerank settings
+        await test_rerank_with_different_settings()
+
         print("\n✅ Example completed successfully!")
         print("\n💡 Key Points:")
         print("   ✓ Rerank is now controlled per query via 'enable_rerank' parameter")
diff --git a/lightrag/api/routers/ollama_api.py b/lightrag/api/routers/ollama_api.py
index c38018f6..9ef7c55f 100644
--- a/lightrag/api/routers/ollama_api.py
+++ b/lightrag/api/routers/ollama_api.py
@@ -469,8 +469,8 @@ class OllamaAPI:
             "/chat", dependencies=[Depends(combined_auth)], include_in_schema=True
         )
         async def chat(raw_request: Request):
-            """Process chat completion requests acting as an Ollama model
-            Routes user queries through LightRAG by selecting query mode based on prefix indicators.
+            """Process chat completion requests by acting as an Ollama model.
+            Routes user queries through LightRAG by selecting query mode based on query prefix.
             Detects and forwards OpenWebUI session-related requests (for meta data generation task) directly to LLM.
             Supports both application/json and application/octet-stream Content-Types.
             """

From 49ea9a79a7c7d7aa95b52de21f5fdc6a777f92d1 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 23:06:10 +0800
Subject: [PATCH 029/141] Update rerank doc in README

---
 README-zh.md              | 30 +++++++-----------------------
 README.md                 | 38 ++++++++------------------------------
 lightrag/api/README-zh.md | 38 ++++++++++++++++++++++++++++++++++++++
 lightrag/api/README.md    | 38 ++++++++++++++++++++++++++++++++++++--
 4 files changed, 89 insertions(+), 55 deletions(-)

diff --git a/README-zh.md b/README-zh.md
index a89ae1f2..8b7239ec 100644
--- a/README-zh.md
+++ b/README-zh.md
@@ -181,7 +181,7 @@ python examples/lightrag_openai_demo.py
 
 ## 使用LightRAG Core进行编程
 
-> 如果您希望将LightRAG集成到您的项目中，建议您使用LightRAG Server提供的REST API。LightRAG Core通常用于嵌入式应用，或供希望进行研究与评估的学者使用。
+> ⚠️ **如果您希望将LightRAG集成到您的项目中，建议您使用LightRAG Server提供的REST API**。LightRAG Core通常用于嵌入式应用，或供希望进行研究与评估的学者使用。
 
 ### 一个简单程序
 
@@ -594,31 +594,15 @@ if __name__ == "__main__":
 
 </details>
 
-### 对话历史
+### Rerank函数注入
 
-LightRAG现在通过对话历史功能支持多轮对话。以下是使用方法：
+为了提高检索质量，可以根据更有效的相关性评分模型对文档进行重排序。`rerank.py`文件提供了三个Reranker提供商的驱动函数：
 
-```python
-# 创建对话历史
-conversation_history = [
-    {"role": "user", "content": "主角对圣诞节的态度是什么？"},
-    {"role": "assistant", "content": "在故事开始时，埃比尼泽·斯克鲁奇对圣诞节持非常消极的态度..."},
-    {"role": "user", "content": "他的态度是如何改变的？"}
-]
+*   **Cohere / vLLM**: `cohere_rerank`
+*   **Jina AI**: `jina_rerank`
+*   **Aliyun阿里云**: `ali_rerank`
 
-# 创建带有对话历史的查询参数
-query_param = QueryParam(
-    mode="mix",  # 或其他模式："local"、"global"、"hybrid"
-    conversation_history=conversation_history,  # 添加对话历史
-    history_turns=3  # 考虑最近的对话轮数
-)
-
-# 进行考虑对话历史的查询
-response = rag.query(
-    "是什么导致了他性格的这种变化？",
-    param=query_param
-)
-```
+您可以将这些函数之一注入到LightRAG对象的`rerank_model_func`属性中。这将使LightRAG的查询功能能够使用注入的函数对检索到的文本块进行重新排序。有关详细用法，请参阅`examples/rerank_example.py`文件。
 
 ### 用户提示词 vs. 查询内容
 
diff --git a/README.md b/README.md
index 893af27a..eacb4982 100644
--- a/README.md
+++ b/README.md
@@ -179,11 +179,12 @@ For a streaming response implementation example, please see `examples/lightrag_o
 
 ## Programing with LightRAG Core
 
-> If you would like to integrate LightRAG into your project, we recommend utilizing the REST API provided by the LightRAG Server. LightRAG Core is typically intended for embedded applications or for researchers who wish to conduct studies and evaluations.
+> ⚠️ **If you would like to integrate LightRAG into your project, we recommend utilizing the REST API provided by the LightRAG Server**. LightRAG Core is typically intended for embedded applications or for researchers who wish to conduct studies and evaluations.
 
 ### ⚠️ Important: Initialization Requirements
 
 **LightRAG requires explicit initialization before use.** You must call both `await rag.initialize_storages()` and `await initialize_pipeline_status()` after creating a LightRAG instance, otherwise you will encounter errors like:
+
 - `AttributeError: __aenter__` - if storages are not initialized
 - `KeyError: 'history_messages'` - if pipeline status is not initialized
 
@@ -596,36 +597,15 @@ if __name__ == "__main__":
 
 </details>
 
-### Conversation History Support
+### Rerank Function Injection
 
+To enhance retrieval quality, documents can be re-ranked based on a more effective relevance scoring model. The `rerank.py` file provides three Reranker provider driver functions:
 
-LightRAG now supports multi-turn dialogue through the conversation history feature. Here's how to use it:
+* **Cohere / vLLM**: `cohere_rerank`
+* **Jina AI**: `jina_rerank`
+* **Aliyun**: `ali_rerank`
 
-<details>
-  <summary> <b> Usage Example </b></summary>
-
-```python
-# Create conversation history
-conversation_history = [
-    {"role": "user", "content": "What is the main character's attitude towards Christmas?"},
-    {"role": "assistant", "content": "At the beginning of the story, Ebenezer Scrooge has a very negative attitude towards Christmas..."},
-    {"role": "user", "content": "How does his attitude change?"}
-]
-
-# Create query parameters with conversation history
-query_param = QueryParam(
-    mode="mix",  # or any other mode: "local", "global", "hybrid"
-    conversation_history=conversation_history,  # Add the conversation history
-)
-
-# Make a query that takes into account the conversation history
-response = rag.query(
-    "What causes this change in his character?",
-    param=query_param
-)
-```
-
-</details>
+You can inject one of these functions into the `rerank_model_func` attribute of the LightRAG object. This will enable LightRAG's query function to re-order retrieved text blocks using the injected function. For detailed usage, please refer to the `examples/rerank_example.py` file.
 
 ### User Prompt vs. Query
 
@@ -646,8 +626,6 @@ response_default = rag.query(
 print(response_default)
 ```
 
-
-
 ### Insert
 
 <details>
diff --git a/lightrag/api/README-zh.md b/lightrag/api/README-zh.md
index b6e2892c..9f940df1 100644
--- a/lightrag/api/README-zh.md
+++ b/lightrag/api/README-zh.md
@@ -421,6 +421,44 @@ LIGHTRAG_DOC_STATUS_STORAGE=PGDocStatusStorage
 | --embedding-binding | ollama | 嵌入绑定类型（lollms、ollama、openai、azure_openai、aws_bedrock） |
 | auto-scan-at-startup | - | 扫描输入目录中的新文件并开始索引 |
 
+### Reranking 配置
+
+Reranking 查询召回的块可以显著提高检索质量，它通过基于优化的相关性评分模型对文档重新排序。LightRAG 目前支持以下 rerank 提供商：
+
+- **Cohere / vLLM**：提供与 Cohere AI 的 `v2/rerank` 端点的完整 API 集成。由于 vLLM 提供了与 Cohere 兼容的 reranker API，因此也支持所有通过 vLLM 部署的 reranker 模型。
+- **Jina AI**：提供与所有 Jina rerank 模型的完全实现兼容性。
+- **阿里云**：具有旨在支持阿里云 rerank API 格式的自定义实现。
+
+Rerank 提供商通过 `.env` 文件进行配置。以下是使用 vLLM 本地部署的 rerank 模型的示例配置：
+
+```
+RERANK_BINDING=cohere
+RERANK_MODEL=BAAI/bge-reranker-v2-m3
+RERANK_BINDING_HOST=http://localhost:8000/v1/rerank
+RERANK_BINDING_API_KEY=your_rerank_api_key_here
+```
+
+以下是使用阿里云提供的 Reranker 服务的示例配置：
+
+```
+RERANK_BINDING=aliyun
+RERANK_MODEL=gte-rerank-v2
+RERANK_BINDING_HOST=https://dashscope.aliyuncs.com/api/v1/services/rerank/text-rerank/text-rerank
+RERANK_BINDING_API_KEY=your_rerank_api_key_here
+```
+
+有关完整的 reranker 配置示例，请参阅 `env.example` 文件。
+
+### 启用 Reranking
+
+可以按查询启用或禁用 Reranking。
+
+`/query` 和 `/query/stream` API 端点包含一个 `enable_rerank` 参数，默认设置为 `true`，用于控制当前查询是否激活 reranking。要将 `enable_rerank` 参数的默认值更改为 `false`，请设置以下环境变量：
+
+```
+RERANK_BY_DEFAULT=False
+```
+
 ### .env 文件示例
 
 ```bash
diff --git a/lightrag/api/README.md b/lightrag/api/README.md
index 3695bc3d..0f010234 100644
--- a/lightrag/api/README.md
+++ b/lightrag/api/README.md
@@ -422,9 +422,43 @@ You cannot change storage implementation selection after adding documents to Lig
 | --embedding-binding   | ollama        | Embedding binding type (lollms, ollama, openai, azure_openai, aws_bedrock)                                                                   |
 | --auto-scan-at-startup| -             | Scan input directory for new files and start indexing                                                                           |
 
-### Additional Ollama Binding Options
+### Reranking Configuration
 
-When using `--llm-binding ollama` or `--embedding-binding ollama`, additional Ollama-specific configuration options are available. To see all available Ollama binding options, add `--help` to the command line when starting the server. These additional options allow for fine-tuning of Ollama model parameters and connection settings.
+Reranking query-recalled chunks can significantly enhance retrieval quality by re-ordering documents based on an optimized relevance scoring model. LightRAG currently supports the following rerank providers:
+
+- **Cohere / vLLM**: Offers full API integration with Cohere AI's `v2/rerank` endpoint. As vLLM provides a Cohere-compatible reranker API, all reranker models deployed via vLLM are also supported.
+- **Jina AI**: Provides complete implementation compatibility with all Jina rerank models.
+- **Aliyun**: Features a custom implementation designed to support Aliyun's rerank API format.
+
+The rerank provider is configured via the `.env` file. Below is an example configuration for a rerank model deployed locally using vLLM:
+
+```
+RERANK_BINDING=cohere
+RERANK_MODEL=BAAI/bge-reranker-v2-m3
+RERANK_BINDING_HOST=http://localhost:8000/v1/rerank
+RERANK_BINDING_API_KEY=your_rerank_api_key_here
+```
+
+Here is an example configuration for utilizing the Reranker service provided by Aliyun:
+
+```
+RERANK_BINDING=aliyun
+RERANK_MODEL=gte-rerank-v2
+RERANK_BINDING_HOST=https://dashscope.aliyuncs.com/api/v1/services/rerank/text-rerank/text-rerank
+RERANK_BINDING_API_KEY=your_rerank_api_key_here
+```
+
+For comprehensive reranker configuration examples, please refer to the `env.example` file.
+
+### Enable Reranking
+
+Reranking can be enabled or disabled on a per-query basis.
+
+The `/query` and `/query/stream` API endpoints include an `enable_rerank` parameter, which is set to `true` by default, controlling whether reranking is active for the current query. To change the default value of the `enable_rerank` parameter to `false`, set the following environment variable:
+
+```
+RERANK_BY_DEFAULT=False
+```
 
 ### .env Examples
 

From b815e47f7c3b105f8d40121a1bf7f977a40eebbe Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 23:38:39 +0800
Subject: [PATCH 030/141] Upgrade Python to 3.12 and update pip/setuptools in
 Dockerfile
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Upgrade base image to Python 3.12
• Update pip, setuptools, wheel
---
 Dockerfile | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

diff --git a/Dockerfile b/Dockerfile
index 619ec1ad..cd122cf2 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,8 +1,11 @@
 # Build stage
-FROM python:3.11-slim AS builder
+FROM python:3.12-slim AS builder
 
 WORKDIR /app
 
+# Upgrade pip、setuptools and wheel to the latest version
+RUN pip install --upgrade pip setuptools wheel
+
 # Install Rust and required build dependencies
 RUN apt-get update && apt-get install -y \
     curl \
@@ -30,10 +33,13 @@ RUN pip install --user --no-cache-dir openai ollama tiktoken
 RUN pip install --user --no-cache-dir pypdf2 python-docx python-pptx openpyxl
 
 # Final stage
-FROM python:3.11-slim
+FROM python:3.12-slim
 
 WORKDIR /app
 
+# Upgrade pip and setuptools
+RUN pip install --upgrade pip setuptools wheel
+
 # Copy only necessary files from builder
 COPY --from=builder /root/.local /root/.local
 COPY ./lightrag ./lightrag

From 9a66c944e21166a4095a92dd6a6037a6c89b2ef1 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 23:50:06 +0800
Subject: [PATCH 031/141] Add Docker build workflow for main branch with manual
 trigger

- Manual workflow dispatch trigger
- Multi-platform build support
- GHCR registry integration
- Git tag-based versioning
- GitHub Actions cache optimization
---
 .github/workflows/docker-build-main.yml | 69 +++++++++++++++++++++++++
 1 file changed, 69 insertions(+)
 create mode 100644 .github/workflows/docker-build-main.yml

diff --git a/.github/workflows/docker-build-main.yml b/.github/workflows/docker-build-main.yml
new file mode 100644
index 00000000..7b7bcf76
--- /dev/null
+++ b/.github/workflows/docker-build-main.yml
@@ -0,0 +1,69 @@
+name: Build Docker Image from Main
+
+on:
+  workflow_dispatch:
+
+permissions:
+  contents: read
+  packages: write
+
+jobs:
+  build-and-push:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0  # Fetch all history for tags
+
+      - name: Get latest tag
+        id: get_tag
+        run: |
+          # Get the latest tag, fallback to commit SHA if no tags exist
+          LATEST_TAG=$(git describe --tags --abbrev=0 2>/dev/null || echo "")
+          if [ -z "$LATEST_TAG" ]; then
+            LATEST_TAG="sha-$(git rev-parse --short HEAD)"
+            echo "No tags found, using commit SHA: $LATEST_TAG"
+          else
+            echo "Latest tag found: $LATEST_TAG"
+          fi
+          echo "tag=$LATEST_TAG" >> $GITHUB_OUTPUT
+          echo "image_tag=$LATEST_TAG" >> $GITHUB_OUTPUT
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Login to GitHub Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata for Docker
+        id: meta
+        uses: docker/metadata-action@v5
+        with:
+          images: ghcr.io/${{ github.repository }}
+          tags: |
+            type=raw,value=${{ steps.get_tag.outputs.tag }}
+            type=raw,value=latest
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          platforms: linux/amd64,linux/arm64
+          push: true
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+          cache-from: type=gha
+          cache-to: type=gha,mode=max
+
+      - name: Output image details
+        run: |
+          echo "Docker image built and pushed successfully!"
+          echo "Image tags:"
+          echo "  - ghcr.io/${{ github.repository }}:${{ steps.get_tag.outputs.tag }}"
+          echo "  - ghcr.io/${{ github.repository }}:latest"
+          echo "Latest Git tag used: ${{ steps.get_tag.outputs.tag }}"

From 8b1e54c8b4ba8fa9b04302927cca1ed619a00367 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 23:55:27 +0800
Subject: [PATCH 032/141] Update Docker workflow name to clarify release
 trigger
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Clarified workflow purpose
• Added "on Release" to name
---
 .github/workflows/docker-publish.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/docker-publish.yml b/.github/workflows/docker-publish.yml
index 49d50bb2..cbf64da1 100644
--- a/.github/workflows/docker-publish.yml
+++ b/.github/workflows/docker-publish.yml
@@ -1,4 +1,4 @@
-name: Build and Push Docker Image
+name: Build and Push Docker Image on Release
 
 on:
   release:

From a82f1264189f732c7990d65a253e63ea547a7cf7 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 23 Aug 2025 23:58:33 +0800
Subject: [PATCH 033/141] Rename github action name

---
 .github/workflows/docker-publish.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/docker-publish.yml b/.github/workflows/docker-publish.yml
index cbf64da1..9c54b664 100644
--- a/.github/workflows/docker-publish.yml
+++ b/.github/workflows/docker-publish.yml
@@ -1,4 +1,4 @@
-name: Build and Push Docker Image on Release
+name: Build Docker Image on Release
 
 on:
   release:

From eebc8938ed4ddfa64b4d89a9c3815e0aaeb3521a Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 24 Aug 2025 00:02:57 +0800
Subject: [PATCH 034/141] Update action name

---
 .github/workflows/docker-build-main.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/docker-build-main.yml b/.github/workflows/docker-build-main.yml
index 7b7bcf76..6e51c2b8 100644
--- a/.github/workflows/docker-build-main.yml
+++ b/.github/workflows/docker-build-main.yml
@@ -1,4 +1,4 @@
-name: Build Docker Image from Main
+name: Build Docker Image manually
 
 on:
   workflow_dispatch:

From 540a83ea1c8f41f5acf8513c13e494da0f52f845 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 24 Aug 2025 01:07:23 +0800
Subject: [PATCH 035/141] Add --use-pep517 flag to all pip install commands in
 Dockerfile

---
 Dockerfile | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/Dockerfile b/Dockerfile
index cd122cf2..e25b4f99 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -22,8 +22,8 @@ COPY lightrag/ ./lightrag/
 
 # Install dependencies
 ENV PATH="/root/.cargo/bin:${PATH}"
-RUN pip install --user --no-cache-dir .
-RUN pip install --user --no-cache-dir .[api]
+RUN pip install --user --no-cache-dir --use-pep517 .
+RUN pip install --user --no-cache-dir --use-pep517 .[api]
 
 # Install depndencies for default storage
 RUN pip install --user --no-cache-dir nano-vectordb networkx
@@ -45,7 +45,7 @@ COPY --from=builder /root/.local /root/.local
 COPY ./lightrag ./lightrag
 COPY setup.py .
 
-RUN pip install ".[api]"
+RUN pip install --use-pep517 ".[api]"
 # Make sure scripts in .local are usable
 ENV PATH=/root/.local/bin:$PATH
 

From d054ec5d0016a3a76f8aa98f2bc670ac14fb05ff Mon Sep 17 00:00:00 2001
From: Thibo Rosemplatt <38402230+thiborose@users.noreply.github.com>
Date: Sat, 23 Aug 2025 20:16:11 +0200
Subject: [PATCH 036/141] Added entity_types as a user defined variable (via
 .env)

---
 env.example                     | 2 ++
 lightrag/api/config.py          | 2 ++
 lightrag/api/lightrag_server.py | 4 ++--
 lightrag/api/utils_api.py       | 2 ++
 lightrag/constants.py           | 1 +
 lightrag/lightrag.py            | 4 +++-
 lightrag/operate.py             | 3 ++-
 lightrag/prompt.py              | 2 --
 8 files changed, 14 insertions(+), 6 deletions(-)

diff --git a/env.example b/env.example
index 41c77ede..58117a6e 100644
--- a/env.example
+++ b/env.example
@@ -131,6 +131,8 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true
 # SUMMARY_MAX_TOKENS=30000
 ### Maximum number of entity extraction attempts for ambiguous content
 # MAX_GLEANING=1
+### Customize the entities that the LLM will attempt to recognize
+# ENTITY_TYPES=["person", "organization", "location", "event", "concept"]
 
 ###############################
 ### Concurrency Configuration
diff --git a/lightrag/api/config.py b/lightrag/api/config.py
index a5e352dc..891491e2 100644
--- a/lightrag/api/config.py
+++ b/lightrag/api/config.py
@@ -36,6 +36,7 @@ from lightrag.constants import (
     DEFAULT_OLLAMA_MODEL_NAME,
     DEFAULT_OLLAMA_MODEL_TAG,
     DEFAULT_RERANK_BINDING,
+    DEFAULT_ENTITY_TYPES
 )
 
 # use the .env that is inside the current folder
@@ -333,6 +334,7 @@ def parse_args() -> argparse.Namespace:
     # Add environment variables that were previously read directly
     args.cors_origins = get_env_value("CORS_ORIGINS", "*")
     args.summary_language = get_env_value("SUMMARY_LANGUAGE", DEFAULT_SUMMARY_LANGUAGE)
+    args.entity_types = get_env_value("ENTITY_TYPES", DEFAULT_ENTITY_TYPES)
     args.whitelist_paths = get_env_value("WHITELIST_PATHS", "/health,/api/*")
 
     # For JWT Auth
diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 328e7953..26ed5d0b 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -497,7 +497,7 @@ def create_app(args):
             rerank_model_func=rerank_model_func,
             max_parallel_insert=args.max_parallel_insert,
             max_graph_nodes=args.max_graph_nodes,
-            addon_params={"language": args.summary_language},
+            addon_params={"language": args.summary_language, "entity_types": args.entity_types},
             ollama_server_infos=ollama_server_infos,
         )
     else:  # azure_openai
@@ -523,7 +523,7 @@ def create_app(args):
             rerank_model_func=rerank_model_func,
             max_parallel_insert=args.max_parallel_insert,
             max_graph_nodes=args.max_graph_nodes,
-            addon_params={"language": args.summary_language},
+            addon_params={"language": args.summary_language, "entity_types": args.entity_types},
             ollama_server_infos=ollama_server_infos,
         )
 
diff --git a/lightrag/api/utils_api.py b/lightrag/api/utils_api.py
index fc05716c..eca3799f 100644
--- a/lightrag/api/utils_api.py
+++ b/lightrag/api/utils_api.py
@@ -264,6 +264,8 @@ def display_splash_screen(args: argparse.Namespace) -> None:
     ASCIIColors.magenta("\n⚙️ RAG Configuration:")
     ASCIIColors.white("    ├─ Summary Language: ", end="")
     ASCIIColors.yellow(f"{args.summary_language}")
+    ASCIIColors.white("    ├─ Entity Types: ", end="")
+    ASCIIColors.yellow(f"{args.entity_types}")
     ASCIIColors.white("    ├─ Max Parallel Insert: ", end="")
     ASCIIColors.yellow(f"{args.max_parallel_insert}")
     ASCIIColors.white("    ├─ Chunk Size: ", end="")
diff --git a/lightrag/constants.py b/lightrag/constants.py
index 9445872e..a1b2ba46 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -15,6 +15,7 @@ DEFAULT_SUMMARY_LANGUAGE = "English"  # Default language for summaries
 DEFAULT_FORCE_LLM_SUMMARY_ON_MERGE = 4
 DEFAULT_MAX_GLEANING = 1
 DEFAULT_SUMMARY_MAX_TOKENS = 30000  # Default maximum token size
+DEFAULT_ENTITY_TYPES = ["organization", "person", "geo", "event", "category"]
 
 # Separator for graph fields
 GRAPH_FIELD_SEP = "<SEP>"
diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index 721181d5..f8b6f7fc 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -37,6 +37,7 @@ from lightrag.constants import (
     DEFAULT_MAX_ASYNC,
     DEFAULT_MAX_PARALLEL_INSERT,
     DEFAULT_MAX_GRAPH_NODES,
+    DEFAULT_ENTITY_TYPES
 )
 from lightrag.utils import get_env_value
 
@@ -333,7 +334,8 @@ class LightRAG:
 
     addon_params: dict[str, Any] = field(
         default_factory=lambda: {
-            "language": get_env_value("SUMMARY_LANGUAGE", "English", str)
+            "language": get_env_value("SUMMARY_LANGUAGE", "English", str),
+            "entity_types": get_env_value("ENTITY_TYPES", DEFAULT_ENTITY_TYPES, list),
         }
     )
 
diff --git a/lightrag/operate.py b/lightrag/operate.py
index 1e1ccbb6..8ae51f41 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -47,6 +47,7 @@ from .constants import (
     DEFAULT_MAX_TOTAL_TOKENS,
     DEFAULT_RELATED_CHUNK_NUMBER,
     DEFAULT_KG_CHUNK_PICK_METHOD,
+    DEFAULT_ENTITY_TYPES
 )
 from .kg.shared_storage import get_storage_keyed_lock
 import time
@@ -1487,7 +1488,7 @@ async def extract_entities(
         "language", PROMPTS["DEFAULT_LANGUAGE"]
     )
     entity_types = global_config["addon_params"].get(
-        "entity_types", PROMPTS["DEFAULT_ENTITY_TYPES"]
+        "entity_types", DEFAULT_ENTITY_TYPES
     )
     example_number = global_config["addon_params"].get("example_number", None)
     if example_number and example_number < len(PROMPTS["entity_extraction_examples"]):
diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index 32666bb5..b315f445 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -9,8 +9,6 @@ PROMPTS["DEFAULT_TUPLE_DELIMITER"] = "<|>"
 PROMPTS["DEFAULT_RECORD_DELIMITER"] = "##"
 PROMPTS["DEFAULT_COMPLETION_DELIMITER"] = "<|COMPLETE|>"
 
-PROMPTS["DEFAULT_ENTITY_TYPES"] = ["organization", "person", "geo", "event", "category"]
-
 PROMPTS["DEFAULT_USER_PROMPT"] = "n/a"
 
 PROMPTS["entity_extraction"] = """---Goal---

From f5938f76bc255d37e98a003602af28e97e32ecd4 Mon Sep 17 00:00:00 2001
From: Thibo Rosemplatt <38402230+thiborose@users.noreply.github.com>
Date: Sun, 24 Aug 2025 00:28:49 +0200
Subject: [PATCH 037/141] Azure OpenAI requires import of OpenAILLMOptions
 (missing)

---
 lightrag/api/lightrag_server.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 328e7953..ec1d38d5 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -248,6 +248,7 @@ def create_app(args):
             azure_openai_complete_if_cache,
             azure_openai_embed,
         )
+        from lightrag.llm.binding_options import OpenAILLMOptions
     if args.llm_binding == "aws_bedrock" or args.embedding_binding == "aws_bedrock":
         from lightrag.llm.bedrock import bedrock_complete_if_cache, bedrock_embed
     if args.embedding_binding == "ollama":

From b5682b15cb6d551128052b3babd14c335b3a9889 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 25 Aug 2025 07:23:41 +0800
Subject: [PATCH 038/141] Remove json-repair from core deps, add missing api
 deps

---
 pyproject.toml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 9963b354..501e8b5a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,7 +25,6 @@ dependencies = [
     "configparser",
     "dotenv",
     "future",
-    "json-repair",
     "nano-vectordb",
     "networkx",
     "numpy",
@@ -47,6 +46,8 @@ api = [
     "configparser",
     "dotenv",
     "future",
+    "nano-vectordb",
+    "networkx",
     "numpy",
     "openai",
     "pandas>=2.0.0",

From f1ff5cf93f693d339ab68d544ef48e47d8661fa8 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 25 Aug 2025 11:56:56 +0800
Subject: [PATCH 039/141] fix: initialize truncated_chunks variable in
 _build_query_context

Prevents local variable 'truncated_chunks'referenced before assignment
---
 lightrag/operate.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 1e1ccbb6..68ab15a5 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -2464,6 +2464,7 @@ async def _build_query_context(
 
     # Apply token processing to merged chunks
     text_units_context = []
+    truncated_chunks = []
     if merged_chunks:
         # Calculate dynamic token limit for text chunks
         entities_str = json.dumps(entities_context, ensure_ascii=False)

From b6aedba7ae933ead904a46fec28cd2bc5463bd7c Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 25 Aug 2025 12:21:31 +0800
Subject: [PATCH 040/141] Add logging for empty naive query results in vector
 context

---
 lightrag/operate.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 68ab15a5..4e0a2e99 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -2057,6 +2057,7 @@ async def _get_vector_context(
 
         results = await chunks_vdb.query(query, top_k=search_top_k, ids=query_param.ids)
         if not results:
+            logger.info(f"Naive query: 0 chunks (chunk_top_k: {search_top_k})")
             return []
 
         valid_chunks = []

From f688e95f5659c4a69be7f14017d63282c491c8fb Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 25 Aug 2025 12:42:25 +0800
Subject: [PATCH 041/141] Add warning for vector chunks missing chunk_id

---
 lightrag/operate.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 4e0a2e99..859d672c 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -2180,6 +2180,8 @@ async def _build_query_context(
                         "frequency": 1,  # Vector chunks always have frequency 1
                         "order": i + 1,  # 1-based order in vector search results
                     }
+                else:
+                    logger.warning(f"Vector chunk missing chunk_id: {chunk}")
 
     # Use round-robin merge to combine local and global data fairly
     final_entities = []

From 31f4f96944044f18576510f0bbd63daebd66712d Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 25 Aug 2025 12:43:34 +0800
Subject: [PATCH 042/141] Exclude conversation history from context length
 calculation

---
 lightrag/operate.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 859d672c..cc06801c 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -2499,15 +2499,15 @@ async def _build_query_context(
         kg_context_tokens = len(tokenizer.encode(kg_context))
 
         # Calculate actual system prompt overhead dynamically
-        # 1. Calculate conversation history tokens
+        # 1. Converstion history not included in context length calculation
         history_context = ""
-        if query_param.conversation_history:
-            history_context = get_conversation_turns(
-                query_param.conversation_history, query_param.history_turns
-            )
-        history_tokens = (
-            len(tokenizer.encode(history_context)) if history_context else 0
-        )
+        # if query_param.conversation_history:
+        #     history_context = get_conversation_turns(
+        #         query_param.conversation_history, query_param.history_turns
+        #     )
+        # history_tokens = (
+        #     len(tokenizer.encode(history_context)) if history_context else 0
+        # )
 
         # 2. Calculate system prompt template tokens (excluding context_data)
         user_prompt = query_param.user_prompt if query_param.user_prompt else ""
@@ -2542,7 +2542,7 @@ async def _build_query_context(
         available_chunk_tokens = max_total_tokens - used_tokens
 
         logger.debug(
-            f"Token allocation - Total: {max_total_tokens}, History: {history_tokens}, SysPrompt: {sys_prompt_overhead}, KG: {kg_context_tokens}, Buffer: {buffer_tokens}, Available for chunks: {available_chunk_tokens}"
+            f"Token allocation - Total: {max_total_tokens}, SysPrompt: {sys_prompt_overhead}, KG: {kg_context_tokens}, Buffer: {buffer_tokens}, Available for chunks: {available_chunk_tokens}"
         )
 
         # Apply token truncation to chunks using the dynamic limit

From 9b6de7512d647fd854560be467f924fbdf1eb078 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 25 Aug 2025 17:10:51 +0800
Subject: [PATCH 043/141] Optimize the stability of description merging order

---
 lightrag/operate.py | 138 +++++++++++++++++++++++++-------------------
 1 file changed, 78 insertions(+), 60 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index cc06801c..74fdf197 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -713,21 +713,6 @@ async def _rebuild_single_entity(
             }
         )
 
-    # Helper function to generate final description with optional LLM summary
-    async def _generate_final_description(combined_description: str) -> str:
-        force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
-        num_fragment = combined_description.count(GRAPH_FIELD_SEP) + 1
-
-        if num_fragment >= force_llm_summary_on_merge:
-            return await _handle_entity_relation_summary(
-                entity_name,
-                combined_description,
-                global_config,
-                llm_response_cache=llm_response_cache,
-            )
-        else:
-            return combined_description
-
     # Collect all entity data from relevant chunks
     all_entity_data = []
     for chunk_id in chunk_ids:
@@ -763,7 +748,18 @@ async def _rebuild_single_entity(
         # Generate description from relationships or fallback to current
         if relationship_descriptions:
             combined_description = GRAPH_FIELD_SEP.join(relationship_descriptions)
-            final_description = await _generate_final_description(combined_description)
+            force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
+            num_fragment = combined_description.count(GRAPH_FIELD_SEP) + 1
+
+            if num_fragment >= force_llm_summary_on_merge:
+                final_description = await _handle_entity_relation_summary(
+                    entity_name,
+                    combined_description,
+                    global_config,
+                    llm_response_cache=llm_response_cache,
+                )
+            else:
+                final_description = combined_description
         else:
             final_description = current_entity.get("description", "")
 
@@ -784,6 +780,10 @@ async def _rebuild_single_entity(
         if entity_data.get("file_path"):
             file_paths.add(entity_data["file_path"])
 
+    # Remove duplicates while preserving order
+    descriptions = list(dict.fromkeys(descriptions))
+    entity_types = list(dict.fromkeys(entity_types))
+
     # Combine all descriptions
     combined_description = (
         GRAPH_FIELD_SEP.join(descriptions)
@@ -799,7 +799,19 @@ async def _rebuild_single_entity(
     )
 
     # Generate final description and update storage
-    final_description = await _generate_final_description(combined_description)
+    force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
+    num_fragment = combined_description.count(GRAPH_FIELD_SEP) + 1
+
+    if num_fragment >= force_llm_summary_on_merge:
+        final_description = await _handle_entity_relation_summary(
+            entity_name,
+            combined_description,
+            global_config,
+            llm_response_cache=llm_response_cache,
+        )
+    else:
+        final_description = combined_description
+
     await _update_entity_storage(final_description, entity_type, file_paths)
 
 
@@ -855,7 +867,11 @@ async def _rebuild_single_relationship(
         if rel_data.get("file_path"):
             file_paths.add(rel_data["file_path"])
 
-    # Combine descriptions and keywords
+    # Remove duplicates while preserving order
+    descriptions = list(dict.fromkeys(descriptions))
+    keywords = list(dict.fromkeys(keywords))
+
+    # Combine descriptions and keywords (fallback to keep currunt unchanged)
     combined_description = (
         GRAPH_FIELD_SEP.join(descriptions)
         if descriptions
@@ -963,22 +979,22 @@ async def _merge_nodes_then_upsert(
         key=lambda x: x[1],
         reverse=True,
     )[0][0]
+
     description = GRAPH_FIELD_SEP.join(
-        sorted(set([dp["description"] for dp in nodes_data] + already_description))
+        already_description
+        + list(
+            dict.fromkeys(
+                [dp["description"] for dp in nodes_data if dp.get("description")]
+            )
+        )
     )
-    source_id = GRAPH_FIELD_SEP.join(
-        set([dp["source_id"] for dp in nodes_data] + already_source_ids)
-    )
-    file_path = build_file_path(already_file_paths, nodes_data, entity_name)
 
     force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
-
     num_fragment = description.count(GRAPH_FIELD_SEP) + 1
-    num_new_fragment = len(set([dp["description"] for dp in nodes_data]))
-
+    already_fragment = already_description.count(GRAPH_FIELD_SEP) + 1
     if num_fragment > 1:
         if num_fragment >= force_llm_summary_on_merge:
-            status_message = f"LLM merge N: {entity_name} | {num_new_fragment}+{num_fragment-num_new_fragment}"
+            status_message = f"LLM merge N: {entity_name} | {already_fragment}+{num_fragment-already_fragment}"
             logger.info(status_message)
             if pipeline_status is not None and pipeline_status_lock is not None:
                 async with pipeline_status_lock:
@@ -991,13 +1007,18 @@ async def _merge_nodes_then_upsert(
                 llm_response_cache,
             )
         else:
-            status_message = f"Merge N: {entity_name} | {num_new_fragment}+{num_fragment-num_new_fragment}"
+            status_message = f"Merge N: {entity_name} | {already_fragment}+{num_fragment-already_fragment}"
             logger.info(status_message)
             if pipeline_status is not None and pipeline_status_lock is not None:
                 async with pipeline_status_lock:
                     pipeline_status["latest_message"] = status_message
                     pipeline_status["history_messages"].append(status_message)
 
+    source_id = GRAPH_FIELD_SEP.join(
+        set([dp["source_id"] for dp in nodes_data] + already_source_ids)
+    )
+    file_path = build_file_path(already_file_paths, nodes_data, entity_name)
+
     node_data = dict(
         entity_id=entity_name,
         entity_type=entity_type,
@@ -1071,15 +1092,41 @@ async def _merge_edges_then_upsert(
 
     # Process edges_data with None checks
     weight = sum([dp["weight"] for dp in edges_data] + already_weights)
+
     description = GRAPH_FIELD_SEP.join(
-        sorted(
-            set(
+        already_description
+        + list(
+            dict.fromkeys(
                 [dp["description"] for dp in edges_data if dp.get("description")]
-                + already_description
             )
         )
     )
 
+    force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
+    num_fragment = description.count(GRAPH_FIELD_SEP) + 1
+    already_fragment = already_description.count(GRAPH_FIELD_SEP) + 1
+    if num_fragment > 1:
+        if num_fragment >= force_llm_summary_on_merge:
+            status_message = f"LLM merge E: {src_id} - {tgt_id} | {already_fragment}+{num_fragment-already_fragment}"
+            logger.info(status_message)
+            if pipeline_status is not None and pipeline_status_lock is not None:
+                async with pipeline_status_lock:
+                    pipeline_status["latest_message"] = status_message
+                    pipeline_status["history_messages"].append(status_message)
+            description = await _handle_entity_relation_summary(
+                f"({src_id}, {tgt_id})",
+                description,
+                global_config,
+                llm_response_cache,
+            )
+        else:
+            status_message = f"Merge E: {src_id} - {tgt_id} | {already_fragment}+{num_fragment-already_fragment}"
+            logger.info(status_message)
+            if pipeline_status is not None and pipeline_status_lock is not None:
+                async with pipeline_status_lock:
+                    pipeline_status["latest_message"] = status_message
+                    pipeline_status["history_messages"].append(status_message)
+
     # Split all existing and new keywords into individual terms, then combine and deduplicate
     all_keywords = set()
     # Process already_keywords (which are comma-separated)
@@ -1127,35 +1174,6 @@ async def _merge_edges_then_upsert(
                 }
                 added_entities.append(entity_data)
 
-    force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
-
-    num_fragment = description.count(GRAPH_FIELD_SEP) + 1
-    num_new_fragment = len(
-        set([dp["description"] for dp in edges_data if dp.get("description")])
-    )
-
-    if num_fragment > 1:
-        if num_fragment >= force_llm_summary_on_merge:
-            status_message = f"LLM merge E: {src_id} - {tgt_id} | {num_new_fragment}+{num_fragment-num_new_fragment}"
-            logger.info(status_message)
-            if pipeline_status is not None and pipeline_status_lock is not None:
-                async with pipeline_status_lock:
-                    pipeline_status["latest_message"] = status_message
-                    pipeline_status["history_messages"].append(status_message)
-            description = await _handle_entity_relation_summary(
-                f"({src_id}, {tgt_id})",
-                description,
-                global_config,
-                llm_response_cache,
-            )
-        else:
-            status_message = f"Merge E: {src_id} - {tgt_id} | {num_new_fragment}+{num_fragment-num_new_fragment}"
-            logger.info(status_message)
-            if pipeline_status is not None and pipeline_status_lock is not None:
-                async with pipeline_status_lock:
-                    pipeline_status["latest_message"] = status_message
-                    pipeline_status["history_messages"].append(status_message)
-
     await knowledge_graph_inst.upsert_edge(
         src_id,
         tgt_id,

From cac8e189e7002995450186e7896a7152cf4c6422 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 25 Aug 2025 17:18:51 +0800
Subject: [PATCH 044/141] Remove redundant entity vector deletion before upsert

---
 lightrag/operate.py | 9 ---------
 1 file changed, 9 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 74fdf197..5744a81f 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -690,15 +690,6 @@ async def _rebuild_single_entity(
         # Update entity in vector database
         entity_vdb_id = compute_mdhash_id(entity_name, prefix="ent-")
 
-        # Delete old vector record first
-        try:
-            await entities_vdb.delete([entity_vdb_id])
-        except Exception as e:
-            logger.debug(
-                f"Could not delete old entity vector record {entity_vdb_id}: {e}"
-            )
-
-        # Insert new vector record
         entity_content = f"{entity_name}\n{final_description}"
         await entities_vdb.upsert(
             {

From 0b1b264a5d6285ddc806483a8e600f8f79b617d0 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 25 Aug 2025 17:46:32 +0800
Subject: [PATCH 045/141] refactor: optimize graph lock scope in document
 deletion

- Move dependency analysis outside graph database lock
- Add persistence call before lock release to prevent dirty reads
---
 lightrag/lightrag.py | 253 +++++++++++++++++++++----------------------
 1 file changed, 124 insertions(+), 129 deletions(-)

diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index 721181d5..fa529784 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -2272,117 +2272,111 @@ class LightRAG:
             relationships_to_delete = set()
             relationships_to_rebuild = {}  # (src, tgt) -> remaining_chunk_ids
 
-            # Use graph database lock to ensure atomic merges and updates
+            try:
+                # Get affected entities and relations from full_entities and full_relations storage
+                doc_entities_data = await self.full_entities.get_by_id(doc_id)
+                doc_relations_data = await self.full_relations.get_by_id(doc_id)
+
+                affected_nodes = []
+                affected_edges = []
+
+                # Get entity data from graph storage using entity names from full_entities
+                if doc_entities_data and "entity_names" in doc_entities_data:
+                    entity_names = doc_entities_data["entity_names"]
+                    # get_nodes_batch returns dict[str, dict], need to convert to list[dict]
+                    nodes_dict = await self.chunk_entity_relation_graph.get_nodes_batch(
+                        entity_names
+                    )
+                    for entity_name in entity_names:
+                        node_data = nodes_dict.get(entity_name)
+                        if node_data:
+                            # Ensure compatibility with existing logic that expects "id" field
+                            if "id" not in node_data:
+                                node_data["id"] = entity_name
+                            affected_nodes.append(node_data)
+
+                # Get relation data from graph storage using relation pairs from full_relations
+                if doc_relations_data and "relation_pairs" in doc_relations_data:
+                    relation_pairs = doc_relations_data["relation_pairs"]
+                    edge_pairs_dicts = [
+                        {"src": pair[0], "tgt": pair[1]} for pair in relation_pairs
+                    ]
+                    # get_edges_batch returns dict[tuple[str, str], dict], need to convert to list[dict]
+                    edges_dict = await self.chunk_entity_relation_graph.get_edges_batch(
+                        edge_pairs_dicts
+                    )
+
+                    for pair in relation_pairs:
+                        src, tgt = pair[0], pair[1]
+                        edge_key = (src, tgt)
+                        edge_data = edges_dict.get(edge_key)
+                        if edge_data:
+                            # Ensure compatibility with existing logic that expects "source" and "target" fields
+                            if "source" not in edge_data:
+                                edge_data["source"] = src
+                            if "target" not in edge_data:
+                                edge_data["target"] = tgt
+                            affected_edges.append(edge_data)
+
+            except Exception as e:
+                logger.error(f"Failed to analyze affected graph elements: {e}")
+                raise Exception(f"Failed to analyze graph dependencies: {e}") from e
+
+            try:
+                # Process entities
+                for node_data in affected_nodes:
+                    node_label = node_data.get("entity_id")
+                    if node_label and "source_id" in node_data:
+                        sources = set(node_data["source_id"].split(GRAPH_FIELD_SEP))
+                        remaining_sources = sources - chunk_ids
+
+                        if not remaining_sources:
+                            entities_to_delete.add(node_label)
+                        elif remaining_sources != sources:
+                            entities_to_rebuild[node_label] = remaining_sources
+
+                async with pipeline_status_lock:
+                    log_message = f"Found {len(entities_to_rebuild)} affected entities"
+                    logger.info(log_message)
+                    pipeline_status["latest_message"] = log_message
+                    pipeline_status["history_messages"].append(log_message)
+
+                # Process relationships
+                for edge_data in affected_edges:
+                    src = edge_data.get("source")
+                    tgt = edge_data.get("target")
+
+                    if src and tgt and "source_id" in edge_data:
+                        edge_tuple = tuple(sorted((src, tgt)))
+                        if (
+                            edge_tuple in relationships_to_delete
+                            or edge_tuple in relationships_to_rebuild
+                        ):
+                            continue
+
+                        sources = set(edge_data["source_id"].split(GRAPH_FIELD_SEP))
+                        remaining_sources = sources - chunk_ids
+
+                        if not remaining_sources:
+                            relationships_to_delete.add(edge_tuple)
+                        elif remaining_sources != sources:
+                            relationships_to_rebuild[edge_tuple] = remaining_sources
+
+                async with pipeline_status_lock:
+                    log_message = (
+                        f"Found {len(relationships_to_rebuild)} affected relations"
+                    )
+                    logger.info(log_message)
+                    pipeline_status["latest_message"] = log_message
+                    pipeline_status["history_messages"].append(log_message)
+
+            except Exception as e:
+                logger.error(f"Failed to process graph analysis results: {e}")
+                raise Exception(f"Failed to process graph dependencies: {e}") from e
+
+            # Use graph database lock to prevent dirty read
             graph_db_lock = get_graph_db_lock(enable_logging=False)
             async with graph_db_lock:
-                try:
-                    # Get affected entities and relations from full_entities and full_relations storage
-                    doc_entities_data = await self.full_entities.get_by_id(doc_id)
-                    doc_relations_data = await self.full_relations.get_by_id(doc_id)
-
-                    affected_nodes = []
-                    affected_edges = []
-
-                    # Get entity data from graph storage using entity names from full_entities
-                    if doc_entities_data and "entity_names" in doc_entities_data:
-                        entity_names = doc_entities_data["entity_names"]
-                        # get_nodes_batch returns dict[str, dict], need to convert to list[dict]
-                        nodes_dict = (
-                            await self.chunk_entity_relation_graph.get_nodes_batch(
-                                entity_names
-                            )
-                        )
-                        for entity_name in entity_names:
-                            node_data = nodes_dict.get(entity_name)
-                            if node_data:
-                                # Ensure compatibility with existing logic that expects "id" field
-                                if "id" not in node_data:
-                                    node_data["id"] = entity_name
-                                affected_nodes.append(node_data)
-
-                    # Get relation data from graph storage using relation pairs from full_relations
-                    if doc_relations_data and "relation_pairs" in doc_relations_data:
-                        relation_pairs = doc_relations_data["relation_pairs"]
-                        edge_pairs_dicts = [
-                            {"src": pair[0], "tgt": pair[1]} for pair in relation_pairs
-                        ]
-                        # get_edges_batch returns dict[tuple[str, str], dict], need to convert to list[dict]
-                        edges_dict = (
-                            await self.chunk_entity_relation_graph.get_edges_batch(
-                                edge_pairs_dicts
-                            )
-                        )
-
-                        for pair in relation_pairs:
-                            src, tgt = pair[0], pair[1]
-                            edge_key = (src, tgt)
-                            edge_data = edges_dict.get(edge_key)
-                            if edge_data:
-                                # Ensure compatibility with existing logic that expects "source" and "target" fields
-                                if "source" not in edge_data:
-                                    edge_data["source"] = src
-                                if "target" not in edge_data:
-                                    edge_data["target"] = tgt
-                                affected_edges.append(edge_data)
-
-                except Exception as e:
-                    logger.error(f"Failed to analyze affected graph elements: {e}")
-                    raise Exception(f"Failed to analyze graph dependencies: {e}") from e
-
-                try:
-                    # Process entities
-                    for node_data in affected_nodes:
-                        node_label = node_data.get("entity_id")
-                        if node_label and "source_id" in node_data:
-                            sources = set(node_data["source_id"].split(GRAPH_FIELD_SEP))
-                            remaining_sources = sources - chunk_ids
-
-                            if not remaining_sources:
-                                entities_to_delete.add(node_label)
-                            elif remaining_sources != sources:
-                                entities_to_rebuild[node_label] = remaining_sources
-
-                    async with pipeline_status_lock:
-                        log_message = (
-                            f"Found {len(entities_to_rebuild)} affected entities"
-                        )
-                        logger.info(log_message)
-                        pipeline_status["latest_message"] = log_message
-                        pipeline_status["history_messages"].append(log_message)
-
-                    # Process relationships
-                    for edge_data in affected_edges:
-                        src = edge_data.get("source")
-                        tgt = edge_data.get("target")
-
-                        if src and tgt and "source_id" in edge_data:
-                            edge_tuple = tuple(sorted((src, tgt)))
-                            if (
-                                edge_tuple in relationships_to_delete
-                                or edge_tuple in relationships_to_rebuild
-                            ):
-                                continue
-
-                            sources = set(edge_data["source_id"].split(GRAPH_FIELD_SEP))
-                            remaining_sources = sources - chunk_ids
-
-                            if not remaining_sources:
-                                relationships_to_delete.add(edge_tuple)
-                            elif remaining_sources != sources:
-                                relationships_to_rebuild[edge_tuple] = remaining_sources
-
-                    async with pipeline_status_lock:
-                        log_message = (
-                            f"Found {len(relationships_to_rebuild)} affected relations"
-                        )
-                        logger.info(log_message)
-                        pipeline_status["latest_message"] = log_message
-                        pipeline_status["history_messages"].append(log_message)
-
-                except Exception as e:
-                    logger.error(f"Failed to process graph analysis results: {e}")
-                    raise Exception(f"Failed to process graph dependencies: {e}") from e
-
                 # 5. Delete chunks from storage
                 if chunk_ids:
                     try:
@@ -2453,27 +2447,28 @@ class LightRAG:
                         logger.error(f"Failed to delete relationships: {e}")
                         raise Exception(f"Failed to delete relationships: {e}") from e
 
-                # 8. Rebuild entities and relationships from remaining chunks
-                if entities_to_rebuild or relationships_to_rebuild:
-                    try:
-                        await _rebuild_knowledge_from_chunks(
-                            entities_to_rebuild=entities_to_rebuild,
-                            relationships_to_rebuild=relationships_to_rebuild,
-                            knowledge_graph_inst=self.chunk_entity_relation_graph,
-                            entities_vdb=self.entities_vdb,
-                            relationships_vdb=self.relationships_vdb,
-                            text_chunks_storage=self.text_chunks,
-                            llm_response_cache=self.llm_response_cache,
-                            global_config=asdict(self),
-                            pipeline_status=pipeline_status,
-                            pipeline_status_lock=pipeline_status_lock,
-                        )
+                # Persist changes to graph database before releasing graph database lock
+                await self._insert_done()
 
-                    except Exception as e:
-                        logger.error(f"Failed to rebuild knowledge from chunks: {e}")
-                        raise Exception(
-                            f"Failed to rebuild knowledge graph: {e}"
-                        ) from e
+            # 8. Rebuild entities and relationships from remaining chunks
+            if entities_to_rebuild or relationships_to_rebuild:
+                try:
+                    await _rebuild_knowledge_from_chunks(
+                        entities_to_rebuild=entities_to_rebuild,
+                        relationships_to_rebuild=relationships_to_rebuild,
+                        knowledge_graph_inst=self.chunk_entity_relation_graph,
+                        entities_vdb=self.entities_vdb,
+                        relationships_vdb=self.relationships_vdb,
+                        text_chunks_storage=self.text_chunks,
+                        llm_response_cache=self.llm_response_cache,
+                        global_config=asdict(self),
+                        pipeline_status=pipeline_status,
+                        pipeline_status_lock=pipeline_status_lock,
+                    )
+
+                except Exception as e:
+                    logger.error(f"Failed to rebuild knowledge from chunks: {e}")
+                    raise Exception(f"Failed to rebuild knowledge graph: {e}") from e
 
             # 9. Delete from full_entities and full_relations storage
             try:

From 882d6857d88ad8e483d570b3af6fcc94ee8ef6f2 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 25 Aug 2025 21:03:16 +0800
Subject: [PATCH 046/141] feat: Implement map-reduce summarization to handle
 large humber of description merging

---
 lightrag/operate.py | 268 +++++++++++++++++++++++++++++---------------
 1 file changed, 180 insertions(+), 88 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 5744a81f..7ebb09df 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -115,47 +115,152 @@ def chunking_by_token_size(
 
 async def _handle_entity_relation_summary(
     entity_or_relation_name: str,
-    description: str,
+    description_list: list[str],
+    force_llm_summary_on_merge: int,
+    seperator: str,
     global_config: dict,
     llm_response_cache: BaseKVStorage | None = None,
 ) -> str:
-    """Handle entity relation summary
-    For each entity or relation, input is the combined description of already existing description and new description.
-    If too long, use LLM to summarize.
+    """Handle entity relation description summary using map-reduce approach.
+
+    This function summarizes a list of descriptions using a map-reduce strategy:
+    1. If total tokens <= summary_max_tokens, summarize directly
+    2. Otherwise, split descriptions into chunks that fit within token limits
+    3. Summarize each chunk, then recursively process the summaries
+    4. Continue until we get a final summary within token limits or num of descriptions is less than force_llm_summary_on_merge
+
+    Args:
+        entity_or_relation_name: Name of the entity or relation being summarized
+        description_list: List of description strings to summarize
+        global_config: Global configuration containing tokenizer and limits
+        llm_response_cache: Optional cache for LLM responses
+
+    Returns:
+        Final summarized description string
+    """
+    # Handle empty input
+    if not description_list:
+        return ""
+
+    # If only one description, return it directly (no need for LLM call)
+    if len(description_list) == 1:
+        return description_list[0]
+
+    # Get configuration
+    tokenizer: Tokenizer = global_config["tokenizer"]
+    summary_max_tokens = global_config["summary_max_tokens"]
+
+    current_list = description_list[:]  # Copy the list to avoid modifying original
+
+    # Iterative map-reduce process
+    while True:
+        # Calculate total tokens in current list
+        total_tokens = sum(len(tokenizer.encode(desc)) for desc in current_list)
+
+        # If total length is within limits, perform final summarization
+        if (
+            total_tokens <= summary_max_tokens
+            or len(current_list) < force_llm_summary_on_merge
+        ):
+            if len(current_list) < force_llm_summary_on_merge:
+                # Already the final result
+                final_description = seperator.join(current_list)
+                return final_description if final_description else ""
+            else:
+                # Final summarization of remaining descriptions
+                return await _summarize_descriptions(
+                    entity_or_relation_name,
+                    current_list,
+                    global_config,
+                    llm_response_cache,
+                )
+
+        # Need to split into chunks - Map phase
+        chunks = []
+        current_chunk = []
+        current_tokens = 0
+
+        for desc in current_list:
+            desc_tokens = len(tokenizer.encode(desc))
+
+            # If adding current description would exceed limit, finalize current chunk
+            if current_tokens + desc_tokens > summary_max_tokens and current_chunk:
+                chunks.append(current_chunk)
+                current_chunk = [desc]
+                current_tokens = desc_tokens
+            else:
+                current_chunk.append(desc)
+                current_tokens += desc_tokens
+
+        # Add the last chunk if it exists
+        if current_chunk:
+            chunks.append(current_chunk)
+
+        logger.info(
+            f"Summarizing {entity_or_relation_name}: split {len(current_list)} descriptions into {len(chunks)} groups"
+        )
+
+        # Reduce phase: summarize each chunk
+        new_summaries = []
+        for chunk in chunks:
+            if len(chunk) == 1:
+                # Optimization: single description chunks don't need LLM summarization
+                new_summaries.append(chunk[0])
+            else:
+                # Multiple descriptions need LLM summarization
+                summary = await _summarize_descriptions(
+                    entity_or_relation_name, chunk, global_config, llm_response_cache
+                )
+                new_summaries.append(summary)
+
+        # Update current list with new summaries for next iteration
+        current_list = new_summaries
+
+
+async def _summarize_descriptions(
+    entity_or_relation_name: str,
+    description_list: list[str],
+    global_config: dict,
+    llm_response_cache: BaseKVStorage | None = None,
+) -> str:
+    """Helper function to summarize a list of descriptions using LLM.
+
+    Args:
+        entity_or_relation_name: Name of the entity or relation being summarized
+        descriptions: List of description strings to summarize
+        global_config: Global configuration containing LLM function and settings
+        llm_response_cache: Optional cache for LLM responses
+
+    Returns:
+        Summarized description string
     """
     use_llm_func: callable = global_config["llm_model_func"]
     # Apply higher priority (8) to entity/relation summary tasks
     use_llm_func = partial(use_llm_func, _priority=8)
 
-    tokenizer: Tokenizer = global_config["tokenizer"]
-    llm_max_tokens = global_config["summary_max_tokens"]
-
     language = global_config["addon_params"].get(
         "language", PROMPTS["DEFAULT_LANGUAGE"]
     )
 
-    tokens = tokenizer.encode(description)
-
-    ### summarize is not determined here anymore (It's determined by num_fragment now)
-    # if len(tokens) < summary_max_tokens:  # No need for summary
-    #     return description
-
     prompt_template = PROMPTS["summarize_entity_descriptions"]
-    use_description = tokenizer.decode(tokens[:llm_max_tokens])
+
+    # Prepare context for the prompt
     context_base = dict(
         entity_name=entity_or_relation_name,
-        description_list=use_description.split(GRAPH_FIELD_SEP),
+        description_list="\n".join(description_list),
         language=language,
     )
     use_prompt = prompt_template.format(**context_base)
-    logger.debug(f"Trigger summary: {entity_or_relation_name}")
+
+    logger.debug(
+        f"Summarizing {len(description_list)} descriptions for: {entity_or_relation_name}"
+    )
 
     # Use LLM function with cache (higher priority for summary generation)
     summary = await use_llm_func_with_cache(
         use_prompt,
         use_llm_func,
         llm_response_cache=llm_response_cache,
-        # max_tokens=summary_max_tokens,
         cache_type="extract",
     )
     return summary
@@ -413,7 +518,7 @@ async def _rebuild_knowledge_from_chunks(
                     )
                     rebuilt_entities_count += 1
                     status_message = (
-                        f"Rebuilt entity: {entity_name} from {len(chunk_ids)} chunks"
+                        f"Entity `{entity_name}` rebuilt from {len(chunk_ids)} chunks"
                     )
                     logger.info(status_message)
                     if pipeline_status is not None and pipeline_status_lock is not None:
@@ -453,7 +558,7 @@ async def _rebuild_knowledge_from_chunks(
                         global_config=global_config,
                     )
                     rebuilt_relationships_count += 1
-                    status_message = f"Rebuilt relationship: {src}->{tgt} from {len(chunk_ids)} chunks"
+                    status_message = f"Relationship `{src}->{tgt}` rebuilt from {len(chunk_ids)} chunks"
                     logger.info(status_message)
                     if pipeline_status is not None and pipeline_status_lock is not None:
                         async with pipeline_status_lock:
@@ -736,21 +841,20 @@ async def _rebuild_single_entity(
                     edge_file_paths = edge_data["file_path"].split(GRAPH_FIELD_SEP)
                     file_paths.update(edge_file_paths)
 
-        # Generate description from relationships or fallback to current
-        if relationship_descriptions:
-            combined_description = GRAPH_FIELD_SEP.join(relationship_descriptions)
-            force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
-            num_fragment = combined_description.count(GRAPH_FIELD_SEP) + 1
+        # deduplicate descriptions
+        description_list = list(dict.fromkeys(relationship_descriptions))
 
-            if num_fragment >= force_llm_summary_on_merge:
-                final_description = await _handle_entity_relation_summary(
-                    entity_name,
-                    combined_description,
-                    global_config,
-                    llm_response_cache=llm_response_cache,
-                )
-            else:
-                final_description = combined_description
+        # Generate description from relationships or fallback to current
+        if description_list:
+            force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
+            final_description = await _handle_entity_relation_summary(
+                entity_name,
+                description_list,
+                force_llm_summary_on_merge,
+                GRAPH_FIELD_SEP,
+                global_config,
+                llm_response_cache=llm_response_cache,
+            )
         else:
             final_description = current_entity.get("description", "")
 
@@ -772,16 +876,9 @@ async def _rebuild_single_entity(
             file_paths.add(entity_data["file_path"])
 
     # Remove duplicates while preserving order
-    descriptions = list(dict.fromkeys(descriptions))
+    description_list = list(dict.fromkeys(descriptions))
     entity_types = list(dict.fromkeys(entity_types))
 
-    # Combine all descriptions
-    combined_description = (
-        GRAPH_FIELD_SEP.join(descriptions)
-        if descriptions
-        else current_entity.get("description", "")
-    )
-
     # Get most common entity type
     entity_type = (
         max(set(entity_types), key=entity_types.count)
@@ -791,17 +888,17 @@ async def _rebuild_single_entity(
 
     # Generate final description and update storage
     force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
-    num_fragment = combined_description.count(GRAPH_FIELD_SEP) + 1
-
-    if num_fragment >= force_llm_summary_on_merge:
+    if description_list:
         final_description = await _handle_entity_relation_summary(
             entity_name,
-            combined_description,
+            description_list,
+            force_llm_summary_on_merge,
+            GRAPH_FIELD_SEP,
             global_config,
             llm_response_cache=llm_response_cache,
         )
     else:
-        final_description = combined_description
+        final_description = current_entity.get("description", "")
 
     await _update_entity_storage(final_description, entity_type, file_paths)
 
@@ -859,45 +956,38 @@ async def _rebuild_single_relationship(
             file_paths.add(rel_data["file_path"])
 
     # Remove duplicates while preserving order
-    descriptions = list(dict.fromkeys(descriptions))
+    description_list = list(dict.fromkeys(descriptions))
     keywords = list(dict.fromkeys(keywords))
 
-    # Combine descriptions and keywords (fallback to keep currunt unchanged)
-    combined_description = (
-        GRAPH_FIELD_SEP.join(descriptions)
-        if descriptions
-        else current_relationship.get("description", "")
-    )
     combined_keywords = (
         ", ".join(set(keywords))
         if keywords
         else current_relationship.get("keywords", "")
     )
-    # weight = (
-    #     sum(weights) / len(weights)
-    #     if weights
-    #     else current_relationship.get("weight", 1.0)
-    # )
+
     weight = sum(weights) if weights else current_relationship.get("weight", 1.0)
 
     # Use summary if description has too many fragments
     force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
-    num_fragment = combined_description.count(GRAPH_FIELD_SEP) + 1
-
-    if num_fragment >= force_llm_summary_on_merge:
+    if description_list:
         final_description = await _handle_entity_relation_summary(
             f"{src}-{tgt}",
-            combined_description,
+            description_list,
+            force_llm_summary_on_merge,
+            GRAPH_FIELD_SEP,
             global_config,
             llm_response_cache=llm_response_cache,
         )
     else:
-        final_description = combined_description
+        # fallback to keep current(unchanged)
+        final_description = current_relationship.get("description", "")
 
     # Update relationship in graph storage
     updated_relationship_data = {
         **current_relationship,
-        "description": final_description,
+        "description": final_description
+        if final_description
+        else current_relationship.get("description", ""),
         "keywords": combined_keywords,
         "weight": weight,
         "source_id": GRAPH_FIELD_SEP.join(chunk_ids),
@@ -971,21 +1061,16 @@ async def _merge_nodes_then_upsert(
         reverse=True,
     )[0][0]
 
-    description = GRAPH_FIELD_SEP.join(
-        already_description
-        + list(
-            dict.fromkeys(
-                [dp["description"] for dp in nodes_data if dp.get("description")]
-            )
-        )
+    description_list = already_description + list(
+        dict.fromkeys([dp["description"] for dp in nodes_data if dp.get("description")])
     )
 
     force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
-    num_fragment = description.count(GRAPH_FIELD_SEP) + 1
+    num_fragment = len(description_list)
     already_fragment = already_description.count(GRAPH_FIELD_SEP) + 1
-    if num_fragment > 1:
+    if num_fragment > 0:
         if num_fragment >= force_llm_summary_on_merge:
-            status_message = f"LLM merge N: {entity_name} | {already_fragment}+{num_fragment-already_fragment}"
+            status_message = f"LLM merging `{entity_name}` | {already_fragment}+{num_fragment-already_fragment}"
             logger.info(status_message)
             if pipeline_status is not None and pipeline_status_lock is not None:
                 async with pipeline_status_lock:
@@ -993,17 +1078,23 @@ async def _merge_nodes_then_upsert(
                     pipeline_status["history_messages"].append(status_message)
             description = await _handle_entity_relation_summary(
                 entity_name,
-                description,
+                description_list,
+                force_llm_summary_on_merge,
+                GRAPH_FIELD_SEP,
                 global_config,
                 llm_response_cache,
             )
         else:
-            status_message = f"Merge N: {entity_name} | {already_fragment}+{num_fragment-already_fragment}"
+            status_message = f"Merging `{entity_name}` | {already_fragment}+{num_fragment-already_fragment}"
             logger.info(status_message)
             if pipeline_status is not None and pipeline_status_lock is not None:
                 async with pipeline_status_lock:
                     pipeline_status["latest_message"] = status_message
                     pipeline_status["history_messages"].append(status_message)
+            description = GRAPH_FIELD_SEP.join(description_list)
+    else:
+        logger.error(f"Entity {entity_name} has no description")
+        description = "(no description)"
 
     source_id = GRAPH_FIELD_SEP.join(
         set([dp["source_id"] for dp in nodes_data] + already_source_ids)
@@ -1084,21 +1175,16 @@ async def _merge_edges_then_upsert(
     # Process edges_data with None checks
     weight = sum([dp["weight"] for dp in edges_data] + already_weights)
 
-    description = GRAPH_FIELD_SEP.join(
-        already_description
-        + list(
-            dict.fromkeys(
-                [dp["description"] for dp in edges_data if dp.get("description")]
-            )
-        )
+    description_list = already_description + list(
+        dict.fromkeys([dp["description"] for dp in edges_data if dp.get("description")])
     )
 
     force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
-    num_fragment = description.count(GRAPH_FIELD_SEP) + 1
+    num_fragment = len(description_list)
     already_fragment = already_description.count(GRAPH_FIELD_SEP) + 1
-    if num_fragment > 1:
+    if num_fragment > 0:
         if num_fragment >= force_llm_summary_on_merge:
-            status_message = f"LLM merge E: {src_id} - {tgt_id} | {already_fragment}+{num_fragment-already_fragment}"
+            status_message = f"LLM merging `{src_id} - {tgt_id}` | {already_fragment}+{num_fragment-already_fragment}"
             logger.info(status_message)
             if pipeline_status is not None and pipeline_status_lock is not None:
                 async with pipeline_status_lock:
@@ -1106,17 +1192,23 @@ async def _merge_edges_then_upsert(
                     pipeline_status["history_messages"].append(status_message)
             description = await _handle_entity_relation_summary(
                 f"({src_id}, {tgt_id})",
-                description,
+                description_list,
+                force_llm_summary_on_merge,
+                GRAPH_FIELD_SEP,
                 global_config,
                 llm_response_cache,
             )
         else:
-            status_message = f"Merge E: {src_id} - {tgt_id} | {already_fragment}+{num_fragment-already_fragment}"
+            status_message = f"Merging `{src_id} - {tgt_id}` | {already_fragment}+{num_fragment-already_fragment}"
             logger.info(status_message)
             if pipeline_status is not None and pipeline_status_lock is not None:
                 async with pipeline_status_lock:
                     pipeline_status["latest_message"] = status_message
                     pipeline_status["history_messages"].append(status_message)
+            description = GRAPH_FIELD_SEP.join(description_list)
+    else:
+        logger.error(f"Edge {src_id} - {tgt_id} has no description")
+        description = "(no description)"
 
     # Split all existing and new keywords into individual terms, then combine and deduplicate
     all_keywords = set()

From 15cdd0dd8f0f6730a4f579952e12bef6a41836ff Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 25 Aug 2025 21:41:33 +0800
Subject: [PATCH 047/141] fix: Sort cached extraction results by the
 create_time within each chunk

This ensures the KG rebuilds maintain the original creation order of the first extraction result for each chunk.
---
 lightrag/operate.py | 42 ++++++++++++++++++++++++++++++------------
 1 file changed, 30 insertions(+), 12 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 7ebb09df..779938af 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -630,14 +630,20 @@ async def _get_cached_extraction_results(
 ) -> dict[str, list[str]]:
     """Get cached extraction results for specific chunk IDs
 
+    This function retrieves cached LLM extraction results for the given chunk IDs and returns
+    them sorted by creation time. The results are sorted at two levels:
+    1. Individual extraction results within each chunk are sorted by create_time (earliest first)
+    2. Chunks themselves are sorted by the create_time of their earliest extraction result
+
     Args:
         llm_response_cache: LLM response cache storage
         chunk_ids: Set of chunk IDs to get cached results for
-        text_chunks_data: Pre-loaded chunk data (optional, for performance)
-        text_chunks_storage: Text chunks storage (fallback if text_chunks_data is None)
+        text_chunks_storage: Text chunks storage for retrieving chunk data and LLM cache references
 
     Returns:
-        Dict mapping chunk_id -> list of extraction_result_text
+        Dict mapping chunk_id -> list of extraction_result_text, where:
+        - Keys (chunk_ids) are ordered by the create_time of their first extraction result
+        - Values (extraction results) are ordered by create_time within each chunk
     """
     cached_results = {}
 
@@ -646,15 +652,13 @@ async def _get_cached_extraction_results(
 
     # Read from storage
     chunk_data_list = await text_chunks_storage.get_by_ids(list(chunk_ids))
-    for chunk_id, chunk_data in zip(chunk_ids, chunk_data_list):
+    for chunk_data in chunk_data_list:
         if chunk_data and isinstance(chunk_data, dict):
             llm_cache_list = chunk_data.get("llm_cache_list", [])
             if llm_cache_list:
                 all_cache_ids.update(llm_cache_list)
         else:
-            logger.warning(
-                f"Chunk {chunk_id} data is invalid or None: {type(chunk_data)}"
-            )
+            logger.warning(f"Chunk data is invalid or None: {chunk_data}")
 
     if not all_cache_ids:
         logger.warning(f"No LLM cache IDs found for {len(chunk_ids)} chunk IDs")
@@ -665,7 +669,7 @@ async def _get_cached_extraction_results(
 
     # Process cache entries and group by chunk_id
     valid_entries = 0
-    for cache_id, cache_entry in zip(all_cache_ids, cache_data_list):
+    for cache_entry in cache_data_list:
         if (
             cache_entry is not None
             and isinstance(cache_entry, dict)
@@ -685,16 +689,30 @@ async def _get_cached_extraction_results(
             # Store tuple with extraction result and creation time for sorting
             cached_results[chunk_id].append((extraction_result, create_time))
 
-    # Sort extraction results by create_time for each chunk
+    # Sort extraction results by create_time for each chunk and collect earliest times
+    chunk_earliest_times = {}
     for chunk_id in cached_results:
         # Sort by create_time (x[1]), then extract only extraction_result (x[0])
         cached_results[chunk_id].sort(key=lambda x: x[1])
+        # Store the earliest create_time for this chunk (first item after sorting)
+        chunk_earliest_times[chunk_id] = cached_results[chunk_id][0][1]
+        # Extract only extraction_result (x[0])
         cached_results[chunk_id] = [item[0] for item in cached_results[chunk_id]]
 
-    logger.info(
-        f"Found {valid_entries} valid cache entries, {len(cached_results)} chunks with results"
+    # Sort cached_results by the earliest create_time of each chunk
+    sorted_chunk_ids = sorted(
+        chunk_earliest_times.keys(), key=lambda chunk_id: chunk_earliest_times[chunk_id]
     )
-    return cached_results
+
+    # Rebuild cached_results in sorted order
+    sorted_cached_results = {}
+    for chunk_id in sorted_chunk_ids:
+        sorted_cached_results[chunk_id] = cached_results[chunk_id]
+
+    logger.info(
+        f"Found {valid_entries} valid cache entries, {len(sorted_cached_results)} chunks with results"
+    )
+    return sorted_cached_results
 
 
 async def _parse_extraction_result(

From 91767ffcee2194c512e5b7f5a987d4a8c23180a6 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 25 Aug 2025 21:55:29 +0800
Subject: [PATCH 048/141] Improve warning message formatting in
 entity/relationship rebuild

---
 lightrag/operate.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 779938af..5ad573cc 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -835,13 +835,13 @@ async def _rebuild_single_entity(
 
     if not all_entity_data:
         logger.warning(
-            f"No cached entity data found for {entity_name}, trying to rebuild from relationships"
+            f"No entity data found for `{entity_name}`, trying to rebuild from relationships"
         )
 
         # Get all edges connected to this entity
         edges = await knowledge_graph_inst.get_node_edges(entity_name)
         if not edges:
-            logger.warning(f"No relationships found for entity {entity_name}")
+            logger.warning(f"No relations attached to entity `{entity_name}`")
             return
 
         # Collect relationship data to extract entity information
@@ -954,7 +954,7 @@ async def _rebuild_single_relationship(
                     )
 
     if not all_relationship_data:
-        logger.warning(f"No cached relationship data found for {src}-{tgt}")
+        logger.warning(f"No relation data found for `{src}-{tgt}`")
         return
 
     # Merge descriptions and keywords

From de2daf65653ce0d06a128aecc8b3faf492c1f74b Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 01:35:50 +0800
Subject: [PATCH 049/141] refac: Rename summary_max_tokens to
 summary_context_size, comprehensive parameter validation for summary
 configuration

- Update algorithm logic in operate.py for better token management
- Fix health endpoint to use correct parameter names
---
 README-zh.md                       |  9 +++++----
 README.md                          |  3 ++-
 env.example                        | 11 ++++++-----
 lightrag/api/config.py             | 13 +++++++++++--
 lightrag/api/lightrag_server.py    | 13 ++++++++-----
 lightrag/api/utils_api.py          |  4 ++--
 lightrag/constants.py              |  6 ++++--
 lightrag/lightrag.py               | 21 +++++++++++++++++++++
 lightrag/operate.py                | 24 +++++++++++++-----------
 lightrag_webui/src/api/lightrag.ts |  1 -
 10 files changed, 72 insertions(+), 33 deletions(-)

diff --git a/README-zh.md b/README-zh.md
index 8b7239ec..d3403b35 100644
--- a/README-zh.md
+++ b/README-zh.md
@@ -268,7 +268,8 @@ if __name__ == "__main__":
 | **embedding_func_max_async** | `int` | 最大并发异步嵌入进程数 | `16` |
 | **llm_model_func** | `callable` | LLM生成的函数 | `gpt_4o_mini_complete` |
 | **llm_model_name** | `str` | 用于生成的LLM模型名称 | `meta-llama/Llama-3.2-1B-Instruct` |
-| **summary_max_tokens** | `int` | 生成实体关系摘要时送给LLM的最大令牌数 | `30000`（由环境变量 SUMMARY_MAX_TOKENS 设置） |
+| **summary_context_size** | `int` | 合并实体关系摘要时送给LLM的最大令牌数 | `10000`（由环境变量 SUMMARY_MAX_CONTEXT 设置） |
+| **summary_max_tokens** | `int` | 合并实体关系描述的最大令牌数长度 | `500`（由环境变量 SUMMARY_MAX_TOKENS 设置） |
 | **llm_model_max_async** | `int` | 最大并发异步LLM进程数 | `4`（默认值由环境变量MAX_ASYNC更改） |
 | **llm_model_kwargs** | `dict` | LLM生成的附加参数 | |
 | **vector_db_storage_cls_kwargs** | `dict` | 向量数据库的附加参数，如设置节点和关系检索的阈值 | cosine_better_than_threshold: 0.2（默认值由环境变量COSINE_THRESHOLD更改） |
@@ -598,9 +599,9 @@ if __name__ == "__main__":
 
 为了提高检索质量，可以根据更有效的相关性评分模型对文档进行重排序。`rerank.py`文件提供了三个Reranker提供商的驱动函数：
 
-*   **Cohere / vLLM**: `cohere_rerank`
-*   **Jina AI**: `jina_rerank`
-*   **Aliyun阿里云**: `ali_rerank`
+* **Cohere / vLLM**: `cohere_rerank`
+* **Jina AI**: `jina_rerank`
+* **Aliyun阿里云**: `ali_rerank`
 
 您可以将这些函数之一注入到LightRAG对象的`rerank_model_func`属性中。这将使LightRAG的查询功能能够使用注入的函数对检索到的文本块进行重新排序。有关详细用法，请参阅`examples/rerank_example.py`文件。
 
diff --git a/README.md b/README.md
index eacb4982..5ad37f01 100644
--- a/README.md
+++ b/README.md
@@ -275,7 +275,8 @@ A full list of LightRAG init parameters:
 | **embedding_func_max_async** | `int` | Maximum number of concurrent asynchronous embedding processes | `16` |
 | **llm_model_func** | `callable` | Function for LLM generation | `gpt_4o_mini_complete` |
 | **llm_model_name** | `str` | LLM model name for generation | `meta-llama/Llama-3.2-1B-Instruct` |
-| **summary_max_tokens** | `int` | Maximum tokens send to LLM to generate entity relation summaries | `30000`（configured by env var SUMMARY_MAX_TOKENS) |
+| **summary_context_size** | `int` | Maximum tokens send to LLM to generate summaries for entity relation merging | `10000`（configured by env var SUMMARY_CONTEXT_SIZE) |
+| **summary_max_tokens** | `int` | Maximum token size for entity/relation description | `500`（configured by env var SUMMARY_MAX_TOKENS) |
 | **llm_model_max_async** | `int` | Maximum number of concurrent asynchronous LLM processes | `4`（default value changed by env var MAX_ASYNC) |
 | **llm_model_kwargs** | `dict` | Additional parameters for LLM generation | |
 | **vector_db_storage_cls_kwargs** | `dict` | Additional parameters for vector database, like setting the threshold for nodes and relations retrieval | cosine_better_than_threshold: 0.2（default value changed by env var COSINE_THRESHOLD) |
diff --git a/env.example b/env.example
index 41c77ede..a824a1f5 100644
--- a/env.example
+++ b/env.example
@@ -125,12 +125,13 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true
 ### Chunk size for document splitting, 500~1500 is recommended
 # CHUNK_SIZE=1200
 # CHUNK_OVERLAP_SIZE=100
-### Entity and relation summarization configuration
-### Number of duplicated entities/edges to trigger LLM re-summary on merge (at least 3 is recommented)， and max tokens send to LLM
+
+### Number of summary semgments or tokens to trigger LLM summary on entity/relation merge (at least 3 is recommented)
 # FORCE_LLM_SUMMARY_ON_MERGE=4
-# SUMMARY_MAX_TOKENS=30000
-### Maximum number of entity extraction attempts for ambiguous content
-# MAX_GLEANING=1
+### Number of tokens to trigger LLM summary on entity/relation merge
+# SUMMARY_MAX_TOKENS = 500
+### Maximum context size sent to LLM for description summary
+# SUMMARY_CONTEXT_SIZE=10000
 
 ###############################
 ### Concurrency Configuration
diff --git a/lightrag/api/config.py b/lightrag/api/config.py
index a5e352dc..f4a281a7 100644
--- a/lightrag/api/config.py
+++ b/lightrag/api/config.py
@@ -30,6 +30,7 @@ from lightrag.constants import (
     DEFAULT_FORCE_LLM_SUMMARY_ON_MERGE,
     DEFAULT_MAX_ASYNC,
     DEFAULT_SUMMARY_MAX_TOKENS,
+    DEFAULT_SUMMARY_CONTEXT_SIZE,
     DEFAULT_SUMMARY_LANGUAGE,
     DEFAULT_EMBEDDING_FUNC_MAX_ASYNC,
     DEFAULT_EMBEDDING_BATCH_NUM,
@@ -119,10 +120,18 @@ def parse_args() -> argparse.Namespace:
         help=f"Maximum async operations (default: from env or {DEFAULT_MAX_ASYNC})",
     )
     parser.add_argument(
-        "--max-tokens",
+        "--summary-max-tokens",
         type=int,
         default=get_env_value("SUMMARY_MAX_TOKENS", DEFAULT_SUMMARY_MAX_TOKENS, int),
-        help=f"Maximum token size (default: from env or {DEFAULT_SUMMARY_MAX_TOKENS})",
+        help=f"Maximum token size for entity/relation summary(default: from env or {DEFAULT_SUMMARY_MAX_TOKENS})",
+    )
+    parser.add_argument(
+        "--summary-context-size",
+        type=int,
+        default=get_env_value(
+            "SUMMARY_CONTEXT_SIZE", DEFAULT_SUMMARY_CONTEXT_SIZE, int
+        ),
+        help=f"LLM Summary Context size (default: from env or {DEFAULT_SUMMARY_CONTEXT_SIZE})",
     )
 
     # Logging configuration
diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index ec1d38d5..2cb53fcd 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -2,7 +2,7 @@
 LightRAG FastAPI Server
 """
 
-from fastapi import FastAPI, Depends, HTTPException, status
+from fastapi import FastAPI, Depends, HTTPException
 import asyncio
 import os
 import logging
@@ -472,7 +472,8 @@ def create_app(args):
             ),
             llm_model_name=args.llm_model,
             llm_model_max_async=args.max_async,
-            summary_max_tokens=args.max_tokens,
+            summary_max_tokens=args.summary_max_tokens,
+            summary_context_size=args.summary_context_size,
             chunk_token_size=int(args.chunk_size),
             chunk_overlap_token_size=int(args.chunk_overlap_size),
             llm_model_kwargs=(
@@ -510,7 +511,8 @@ def create_app(args):
             chunk_overlap_token_size=int(args.chunk_overlap_size),
             llm_model_name=args.llm_model,
             llm_model_max_async=args.max_async,
-            summary_max_tokens=args.max_tokens,
+            summary_max_tokens=args.summary_max_tokens,
+            summary_context_size=args.summary_context_size,
             embedding_func=embedding_func,
             kv_storage=args.kv_storage,
             graph_storage=args.graph_storage,
@@ -598,7 +600,7 @@ def create_app(args):
         username = form_data.username
         if auth_handler.accounts.get(username) != form_data.password:
             raise HTTPException(
-                status_code=status.HTTP_401_UNAUTHORIZED, detail="Incorrect credentials"
+                status_code=401, detail="Incorrect credentials"
             )
 
         # Regular user login
@@ -642,7 +644,8 @@ def create_app(args):
                     "embedding_binding": args.embedding_binding,
                     "embedding_binding_host": args.embedding_binding_host,
                     "embedding_model": args.embedding_model,
-                    "max_tokens": args.max_tokens,
+                    "summary_max_tokens": args.summary_max_tokens,
+                    "summary_context_size": args.summary_context_size,
                     "kv_storage": args.kv_storage,
                     "doc_status_storage": args.doc_status_storage,
                     "graph_storage": args.graph_storage,
diff --git a/lightrag/api/utils_api.py b/lightrag/api/utils_api.py
index fc05716c..a53f8bee 100644
--- a/lightrag/api/utils_api.py
+++ b/lightrag/api/utils_api.py
@@ -242,8 +242,8 @@ def display_splash_screen(args: argparse.Namespace) -> None:
     ASCIIColors.yellow(f"{args.llm_model}")
     ASCIIColors.white("    ├─ Max Async for LLM: ", end="")
     ASCIIColors.yellow(f"{args.max_async}")
-    ASCIIColors.white("    ├─ Max Tokens: ", end="")
-    ASCIIColors.yellow(f"{args.max_tokens}")
+    ASCIIColors.white("    ├─ Summary Context Size: ", end="")
+    ASCIIColors.yellow(f"{args.summary_context_size}")
     ASCIIColors.white("    ├─ LLM Cache Enabled: ", end="")
     ASCIIColors.yellow(f"{args.enable_llm_cache}")
     ASCIIColors.white("    └─ LLM Cache for Extraction Enabled: ", end="")
diff --git a/lightrag/constants.py b/lightrag/constants.py
index 9445872e..c180e2dd 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -12,9 +12,11 @@ DEFAULT_MAX_GRAPH_NODES = 1000
 
 # Default values for extraction settings
 DEFAULT_SUMMARY_LANGUAGE = "English"  # Default language for summaries
-DEFAULT_FORCE_LLM_SUMMARY_ON_MERGE = 4
 DEFAULT_MAX_GLEANING = 1
-DEFAULT_SUMMARY_MAX_TOKENS = 30000  # Default maximum token size
+
+DEFAULT_FORCE_LLM_SUMMARY_ON_MERGE = 4
+DEFAULT_SUMMARY_MAX_TOKENS = 500  # Max token size for entity/relation summary
+DEFAULT_SUMMARY_CONTEXT_SIZE = 10000  # Default maximum token size
 
 # Separator for graph fields
 GRAPH_FIELD_SEP = "<SEP>"
diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index fa529784..1d8c08ed 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -34,6 +34,7 @@ from lightrag.constants import (
     DEFAULT_KG_CHUNK_PICK_METHOD,
     DEFAULT_MIN_RERANK_SCORE,
     DEFAULT_SUMMARY_MAX_TOKENS,
+    DEFAULT_SUMMARY_CONTEXT_SIZE,
     DEFAULT_MAX_ASYNC,
     DEFAULT_MAX_PARALLEL_INSERT,
     DEFAULT_MAX_GRAPH_NODES,
@@ -285,6 +286,11 @@ class LightRAG:
     summary_max_tokens: int = field(
         default=int(os.getenv("SUMMARY_MAX_TOKENS", DEFAULT_SUMMARY_MAX_TOKENS))
     )
+    """Maximum tokens allowed for entity/relation description."""
+
+    summary_context_size: int = field(
+        default=int(os.getenv("SUMMARY_CONTEXT_SIZE", DEFAULT_SUMMARY_CONTEXT_SIZE))
+    )
     """Maximum number of tokens allowed per LLM response."""
 
     llm_model_max_async: int = field(
@@ -416,6 +422,21 @@ class LightRAG:
         if self.ollama_server_infos is None:
             self.ollama_server_infos = OllamaServerInfos()
 
+
+        # Validate config
+        if self.force_llm_summary_on_merge < 3:
+            logger.warning(
+                f"force_llm_summary_on_merge should be at least 3, got {self.force_llm_summary_on_merge}"
+            )
+        if self.summary_max_tokens * self.force_llm_summary_on_merge > self.summary_context_size:
+            logger.warning(
+                f"summary_context_size must be at least summary_max_tokens * force_llm_summary_on_merge, got {self.summary_context_size}"
+            )
+        if self.summary_context_size > self.max_total_tokens:
+            logger.warning(
+                f"summary_context_size must be less than max_total_tokens, got {self.summary_context_size}"
+            )
+
         # Fix global_config now
         global_config = asdict(self)
 
diff --git a/lightrag/operate.py b/lightrag/operate.py
index 5ad573cc..e59e944d 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -124,10 +124,11 @@ async def _handle_entity_relation_summary(
     """Handle entity relation description summary using map-reduce approach.
 
     This function summarizes a list of descriptions using a map-reduce strategy:
-    1. If total tokens <= summary_max_tokens, summarize directly
-    2. Otherwise, split descriptions into chunks that fit within token limits
-    3. Summarize each chunk, then recursively process the summaries
-    4. Continue until we get a final summary within token limits or num of descriptions is less than force_llm_summary_on_merge
+    1. If total tokens < summary_context_size and len(description_list) < force_llm_summary_on_merge, no need to summarize
+    2. If total tokens < summary_max_tokens, summarize with LLM directly
+    3. Otherwise, split descriptions into chunks that fit within token limits
+    4. Summarize each chunk, then recursively process the summaries
+    5. Continue until we get a final summary within token limits or num of descriptions is less than force_llm_summary_on_merge
 
     Args:
         entity_or_relation_name: Name of the entity or relation being summarized
@@ -148,6 +149,7 @@ async def _handle_entity_relation_summary(
 
     # Get configuration
     tokenizer: Tokenizer = global_config["tokenizer"]
+    summary_context_size = global_config["summary_context_size"]
     summary_max_tokens = global_config["summary_max_tokens"]
 
     current_list = description_list[:]  # Copy the list to avoid modifying original
@@ -158,11 +160,11 @@ async def _handle_entity_relation_summary(
         total_tokens = sum(len(tokenizer.encode(desc)) for desc in current_list)
 
         # If total length is within limits, perform final summarization
-        if (
-            total_tokens <= summary_max_tokens
-            or len(current_list) < force_llm_summary_on_merge
-        ):
-            if len(current_list) < force_llm_summary_on_merge:
+        if total_tokens <= summary_context_size:
+            if (
+                len(current_list) < force_llm_summary_on_merge
+                and total_tokens < summary_max_tokens
+            ):
                 # Already the final result
                 final_description = seperator.join(current_list)
                 return final_description if final_description else ""
@@ -184,9 +186,9 @@ async def _handle_entity_relation_summary(
             desc_tokens = len(tokenizer.encode(desc))
 
             # If adding current description would exceed limit, finalize current chunk
-            if current_tokens + desc_tokens > summary_max_tokens and current_chunk:
+            if current_tokens + desc_tokens > summary_context_size and current_chunk:
                 chunks.append(current_chunk)
-                current_chunk = [desc]
+                current_chunk = [desc]  # Intial chunk for next group
                 current_tokens = desc_tokens
             else:
                 current_chunk.append(desc)
diff --git a/lightrag_webui/src/api/lightrag.ts b/lightrag_webui/src/api/lightrag.ts
index d2f23f12..265126c7 100644
--- a/lightrag_webui/src/api/lightrag.ts
+++ b/lightrag_webui/src/api/lightrag.ts
@@ -35,7 +35,6 @@ export type LightragStatus = {
     embedding_binding: string
     embedding_binding_host: string
     embedding_model: string
-    max_tokens: number
     kv_storage: string
     doc_status_storage: string
     graph_storage: string

From cb0fe38b9aff9a9593e3cae6575d72af3c67ebbd Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 02:22:34 +0800
Subject: [PATCH 050/141] Fix linting

---
 lightrag/api/lightrag_server.py | 4 +---
 lightrag/lightrag.py            | 6 ++++--
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 2cb53fcd..28e13614 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -599,9 +599,7 @@ def create_app(args):
             }
         username = form_data.username
         if auth_handler.accounts.get(username) != form_data.password:
-            raise HTTPException(
-                status_code=401, detail="Incorrect credentials"
-            )
+            raise HTTPException(status_code=401, detail="Incorrect credentials")
 
         # Regular user login
         user_token = auth_handler.create_token(
diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index 1d8c08ed..f5529bad 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -422,13 +422,15 @@ class LightRAG:
         if self.ollama_server_infos is None:
             self.ollama_server_infos = OllamaServerInfos()
 
-
         # Validate config
         if self.force_llm_summary_on_merge < 3:
             logger.warning(
                 f"force_llm_summary_on_merge should be at least 3, got {self.force_llm_summary_on_merge}"
             )
-        if self.summary_max_tokens * self.force_llm_summary_on_merge > self.summary_context_size:
+        if (
+            self.summary_max_tokens * self.force_llm_summary_on_merge
+            > self.summary_context_size
+        ):
             logger.warning(
                 f"summary_context_size must be at least summary_max_tokens * force_llm_summary_on_merge, got {self.summary_context_size}"
             )

From 9eb2be79b8788ad9f3706e5c34bb8ebd9a3636cb Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 03:56:18 +0800
Subject: [PATCH 051/141] feat: track actual LLM usage in entity/relation
 merging

- Modified _handle_entity_relation_summary to return tuple[str, bool]
- Updated merge functions to log "LLMmerg" vs "Merging" based on actual LLM usage
- Replaced hardcoded fragment count prediction with real-time LLM usage tracking
---
 lightrag/operate.py | 171 +++++++++++++++++++++++---------------------
 1 file changed, 91 insertions(+), 80 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index e59e944d..e84abd48 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -120,7 +120,7 @@ async def _handle_entity_relation_summary(
     seperator: str,
     global_config: dict,
     llm_response_cache: BaseKVStorage | None = None,
-) -> str:
+) -> tuple[str, bool]:
     """Handle entity relation description summary using map-reduce approach.
 
     This function summarizes a list of descriptions using a map-reduce strategy:
@@ -137,15 +137,15 @@ async def _handle_entity_relation_summary(
         llm_response_cache: Optional cache for LLM responses
 
     Returns:
-        Final summarized description string
+        Tuple of (final_summarized_description_string, llm_was_used_boolean)
     """
     # Handle empty input
     if not description_list:
-        return ""
+        return "", False
 
     # If only one description, return it directly (no need for LLM call)
     if len(description_list) == 1:
-        return description_list[0]
+        return description_list[0], False
 
     # Get configuration
     tokenizer: Tokenizer = global_config["tokenizer"]
@@ -153,6 +153,7 @@ async def _handle_entity_relation_summary(
     summary_max_tokens = global_config["summary_max_tokens"]
 
     current_list = description_list[:]  # Copy the list to avoid modifying original
+    llm_was_used = False  # Track whether LLM was used during the entire process
 
     # Iterative map-reduce process
     while True:
@@ -165,17 +166,18 @@ async def _handle_entity_relation_summary(
                 len(current_list) < force_llm_summary_on_merge
                 and total_tokens < summary_max_tokens
             ):
-                # Already the final result
+                # Already the final result - no LLM needed
                 final_description = seperator.join(current_list)
-                return final_description if final_description else ""
+                return final_description if final_description else "", llm_was_used
             else:
-                # Final summarization of remaining descriptions
-                return await _summarize_descriptions(
+                # Final summarization of remaining descriptions - LLM will be used
+                final_summary = await _summarize_descriptions(
                     entity_or_relation_name,
                     current_list,
                     global_config,
                     llm_response_cache,
                 )
+                return final_summary, True  # LLM was used for final summarization
 
         # Need to split into chunks - Map phase
         chunks = []
@@ -188,7 +190,7 @@ async def _handle_entity_relation_summary(
             # If adding current description would exceed limit, finalize current chunk
             if current_tokens + desc_tokens > summary_context_size and current_chunk:
                 chunks.append(current_chunk)
-                current_chunk = [desc]  # Intial chunk for next group
+                current_chunk = [desc]  # Initial chunk for next group
                 current_tokens = desc_tokens
             else:
                 current_chunk.append(desc)
@@ -214,6 +216,7 @@ async def _handle_entity_relation_summary(
                     entity_or_relation_name, chunk, global_config, llm_response_cache
                 )
                 new_summaries.append(summary)
+                llm_was_used = True  # Mark that LLM was used in reduce phase
 
         # Update current list with new summaries for next iteration
         current_list = new_summaries
@@ -529,7 +532,7 @@ async def _rebuild_knowledge_from_chunks(
                             pipeline_status["history_messages"].append(status_message)
                 except Exception as e:
                     failed_entities_count += 1
-                    status_message = f"Failed to rebuild entity {entity_name}: {e}"
+                    status_message = f"Failed to rebuild entity `{entity_name}`: {e}"
                     logger.info(status_message)  # Per requirement, change to info
                     if pipeline_status is not None and pipeline_status_lock is not None:
                         async with pipeline_status_lock:
@@ -560,7 +563,7 @@ async def _rebuild_knowledge_from_chunks(
                         global_config=global_config,
                     )
                     rebuilt_relationships_count += 1
-                    status_message = f"Relationship `{src}->{tgt}` rebuilt from {len(chunk_ids)} chunks"
+                    status_message = f"Relationship `{src} - {tgt}` rebuilt from {len(chunk_ids)} chunks"
                     logger.info(status_message)
                     if pipeline_status is not None and pipeline_status_lock is not None:
                         async with pipeline_status_lock:
@@ -568,7 +571,9 @@ async def _rebuild_knowledge_from_chunks(
                             pipeline_status["history_messages"].append(status_message)
                 except Exception as e:
                     failed_relationships_count += 1
-                    status_message = f"Failed to rebuild relationship {src}->{tgt}: {e}"
+                    status_message = (
+                        f"Failed to rebuild relationship `{src} - {tgt}`: {e}"
+                    )
                     logger.info(status_message)  # Per requirement, change to info
                     if pipeline_status is not None and pipeline_status_lock is not None:
                         async with pipeline_status_lock:
@@ -867,7 +872,7 @@ async def _rebuild_single_entity(
         # Generate description from relationships or fallback to current
         if description_list:
             force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
-            final_description = await _handle_entity_relation_summary(
+            final_description, _ = await _handle_entity_relation_summary(
                 entity_name,
                 description_list,
                 force_llm_summary_on_merge,
@@ -909,7 +914,7 @@ async def _rebuild_single_entity(
     # Generate final description and update storage
     force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
     if description_list:
-        final_description = await _handle_entity_relation_summary(
+        final_description, _ = await _handle_entity_relation_summary(
             entity_name,
             description_list,
             force_llm_summary_on_merge,
@@ -990,7 +995,7 @@ async def _rebuild_single_relationship(
     # Use summary if description has too many fragments
     force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
     if description_list:
-        final_description = await _handle_entity_relation_summary(
+        final_description, _ = await _handle_entity_relation_summary(
             f"{src}-{tgt}",
             description_list,
             force_llm_summary_on_merge,
@@ -1065,13 +1070,9 @@ async def _merge_nodes_then_upsert(
     already_node = await knowledge_graph_inst.get_node(entity_name)
     if already_node:
         already_entity_types.append(already_node["entity_type"])
-        already_source_ids.extend(
-            split_string_by_multi_markers(already_node["source_id"], [GRAPH_FIELD_SEP])
-        )
-        already_file_paths.extend(
-            split_string_by_multi_markers(already_node["file_path"], [GRAPH_FIELD_SEP])
-        )
-        already_description.append(already_node["description"])
+        already_source_ids.extend(already_node["source_id"].split(GRAPH_FIELD_SEP))
+        already_file_paths.extend(already_node["file_path"].split(GRAPH_FIELD_SEP))
+        already_description.extend(already_node["description"].split(GRAPH_FIELD_SEP))
 
     entity_type = sorted(
         Counter(
@@ -1079,39 +1080,45 @@ async def _merge_nodes_then_upsert(
         ).items(),
         key=lambda x: x[1],
         reverse=True,
-    )[0][0]
+    )[0][0]  # Get the entity type with the highest count
 
-    description_list = already_description + list(
-        dict.fromkeys([dp["description"] for dp in nodes_data if dp.get("description")])
+    description_list = list(
+        dict.fromkeys(
+            already_description
+            + [dp["description"] for dp in nodes_data if dp.get("description")]
+        )
     )
 
     force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
     num_fragment = len(description_list)
-    already_fragment = already_description.count(GRAPH_FIELD_SEP) + 1
+    already_fragment = len(already_description)
+    deduplicated_num = already_fragment + len(nodes_data) - num_fragment
+    if deduplicated_num > 0:
+        dd_message = f"(dd:{deduplicated_num})"
+    else:
+        dd_message = ""
     if num_fragment > 0:
-        if num_fragment >= force_llm_summary_on_merge:
-            status_message = f"LLM merging `{entity_name}` | {already_fragment}+{num_fragment-already_fragment}"
-            logger.info(status_message)
-            if pipeline_status is not None and pipeline_status_lock is not None:
-                async with pipeline_status_lock:
-                    pipeline_status["latest_message"] = status_message
-                    pipeline_status["history_messages"].append(status_message)
-            description = await _handle_entity_relation_summary(
-                entity_name,
-                description_list,
-                force_llm_summary_on_merge,
-                GRAPH_FIELD_SEP,
-                global_config,
-                llm_response_cache,
-            )
+        # Get summary and LLM usage status
+        description, llm_was_used = await _handle_entity_relation_summary(
+            entity_name,
+            description_list,
+            force_llm_summary_on_merge,
+            GRAPH_FIELD_SEP,
+            global_config,
+            llm_response_cache,
+        )
+
+        # Log based on actual LLM usage
+        if llm_was_used:
+            status_message = f"LLMmrg: `{entity_name}` | {already_fragment}+{num_fragment-already_fragment}{dd_message}"
         else:
-            status_message = f"Merging `{entity_name}` | {already_fragment}+{num_fragment-already_fragment}"
-            logger.info(status_message)
-            if pipeline_status is not None and pipeline_status_lock is not None:
-                async with pipeline_status_lock:
-                    pipeline_status["latest_message"] = status_message
-                    pipeline_status["history_messages"].append(status_message)
-            description = GRAPH_FIELD_SEP.join(description_list)
+            status_message = f"Merged: `{entity_name}` | {already_fragment}+{num_fragment-already_fragment}{dd_message}"
+
+        logger.info(status_message)
+        if pipeline_status is not None and pipeline_status_lock is not None:
+            async with pipeline_status_lock:
+                pipeline_status["latest_message"] = status_message
+                pipeline_status["history_messages"].append(status_message)
     else:
         logger.error(f"Entity {entity_name} has no description")
         description = "(no description)"
@@ -1167,22 +1174,20 @@ async def _merge_edges_then_upsert(
             # Get source_id with empty string default if missing or None
             if already_edge.get("source_id") is not None:
                 already_source_ids.extend(
-                    split_string_by_multi_markers(
-                        already_edge["source_id"], [GRAPH_FIELD_SEP]
-                    )
+                    already_edge["source_id"].split(GRAPH_FIELD_SEP)
                 )
 
             # Get file_path with empty string default if missing or None
             if already_edge.get("file_path") is not None:
                 already_file_paths.extend(
-                    split_string_by_multi_markers(
-                        already_edge["file_path"], [GRAPH_FIELD_SEP]
-                    )
+                    already_edge["file_path"].split(GRAPH_FIELD_SEP)
                 )
 
             # Get description with empty string default if missing or None
             if already_edge.get("description") is not None:
-                already_description.append(already_edge["description"])
+                already_description.extend(
+                    already_edge["description"].split(GRAPH_FIELD_SEP)
+                )
 
             # Get keywords with empty string default if missing or None
             if already_edge.get("keywords") is not None:
@@ -1195,37 +1200,43 @@ async def _merge_edges_then_upsert(
     # Process edges_data with None checks
     weight = sum([dp["weight"] for dp in edges_data] + already_weights)
 
-    description_list = already_description + list(
-        dict.fromkeys([dp["description"] for dp in edges_data if dp.get("description")])
+    description_list = list(
+        dict.fromkeys(
+            already_description
+            + [dp["description"] for dp in edges_data if dp.get("description")]
+        )
     )
 
     force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
     num_fragment = len(description_list)
-    already_fragment = already_description.count(GRAPH_FIELD_SEP) + 1
+    already_fragment = len(already_description)
+    deduplicated_num = already_fragment + len(edges_data) - num_fragment
+    if deduplicated_num > 0:
+        dd_message = f"(dd:{deduplicated_num})"
+    else:
+        dd_message = ""
     if num_fragment > 0:
-        if num_fragment >= force_llm_summary_on_merge:
-            status_message = f"LLM merging `{src_id} - {tgt_id}` | {already_fragment}+{num_fragment-already_fragment}"
-            logger.info(status_message)
-            if pipeline_status is not None and pipeline_status_lock is not None:
-                async with pipeline_status_lock:
-                    pipeline_status["latest_message"] = status_message
-                    pipeline_status["history_messages"].append(status_message)
-            description = await _handle_entity_relation_summary(
-                f"({src_id}, {tgt_id})",
-                description_list,
-                force_llm_summary_on_merge,
-                GRAPH_FIELD_SEP,
-                global_config,
-                llm_response_cache,
-            )
+        # Get summary and LLM usage status
+        description, llm_was_used = await _handle_entity_relation_summary(
+            f"({src_id}, {tgt_id})",
+            description_list,
+            force_llm_summary_on_merge,
+            GRAPH_FIELD_SEP,
+            global_config,
+            llm_response_cache,
+        )
+
+        # Log based on actual LLM usage
+        if llm_was_used:
+            status_message = f"LLMmrg: `{src_id} - {tgt_id}` | {already_fragment}+{num_fragment-already_fragment}{dd_message}"
         else:
-            status_message = f"Merging `{src_id} - {tgt_id}` | {already_fragment}+{num_fragment-already_fragment}"
-            logger.info(status_message)
-            if pipeline_status is not None and pipeline_status_lock is not None:
-                async with pipeline_status_lock:
-                    pipeline_status["latest_message"] = status_message
-                    pipeline_status["history_messages"].append(status_message)
-            description = GRAPH_FIELD_SEP.join(description_list)
+            status_message = f"Merged: `{src_id} - {tgt_id}` | {already_fragment}+{num_fragment-already_fragment}{dd_message}"
+
+        logger.info(status_message)
+        if pipeline_status is not None and pipeline_status_lock is not None:
+            async with pipeline_status_lock:
+                pipeline_status["latest_message"] = status_message
+                pipeline_status["history_messages"].append(status_message)
     else:
         logger.error(f"Edge {src_id} - {tgt_id} has no description")
         description = "(no description)"

From 84416d104d988931796512a3a00666e26586b5b1 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 03:57:35 +0800
Subject: [PATCH 052/141] Increase default LLM summary merge threshold from 4
 to 8 for reducing summary trigger frequency

---
 env.example           | 2 +-
 lightrag/constants.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/env.example b/env.example
index a824a1f5..a64626ef 100644
--- a/env.example
+++ b/env.example
@@ -127,7 +127,7 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true
 # CHUNK_OVERLAP_SIZE=100
 
 ### Number of summary semgments or tokens to trigger LLM summary on entity/relation merge (at least 3 is recommented)
-# FORCE_LLM_SUMMARY_ON_MERGE=4
+# FORCE_LLM_SUMMARY_ON_MERGE=8
 ### Number of tokens to trigger LLM summary on entity/relation merge
 # SUMMARY_MAX_TOKENS = 500
 ### Maximum context size sent to LLM for description summary
diff --git a/lightrag/constants.py b/lightrag/constants.py
index c180e2dd..0e6d6dcd 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -14,7 +14,7 @@ DEFAULT_MAX_GRAPH_NODES = 1000
 DEFAULT_SUMMARY_LANGUAGE = "English"  # Default language for summaries
 DEFAULT_MAX_GLEANING = 1
 
-DEFAULT_FORCE_LLM_SUMMARY_ON_MERGE = 4
+DEFAULT_FORCE_LLM_SUMMARY_ON_MERGE = 8
 DEFAULT_SUMMARY_MAX_TOKENS = 500  # Max token size for entity/relation summary
 DEFAULT_SUMMARY_CONTEXT_SIZE = 10000  # Default maximum token size
 

From 025f70089a22d1bed324bbd0ceb72945857369cb Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 04:26:15 +0800
Subject: [PATCH 053/141] Simplify status messages in knowledge rebuild
 operations

---
 lightrag/operate.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index e84abd48..6820401c 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -523,7 +523,7 @@ async def _rebuild_knowledge_from_chunks(
                     )
                     rebuilt_entities_count += 1
                     status_message = (
-                        f"Entity `{entity_name}` rebuilt from {len(chunk_ids)} chunks"
+                        f"Rebuilt `{entity_name}` from {len(chunk_ids)} chunks"
                     )
                     logger.info(status_message)
                     if pipeline_status is not None and pipeline_status_lock is not None:
@@ -532,7 +532,7 @@ async def _rebuild_knowledge_from_chunks(
                             pipeline_status["history_messages"].append(status_message)
                 except Exception as e:
                     failed_entities_count += 1
-                    status_message = f"Failed to rebuild entity `{entity_name}`: {e}"
+                    status_message = f"Failed to rebuild `{entity_name}`: {e}"
                     logger.info(status_message)  # Per requirement, change to info
                     if pipeline_status is not None and pipeline_status_lock is not None:
                         async with pipeline_status_lock:
@@ -563,7 +563,7 @@ async def _rebuild_knowledge_from_chunks(
                         global_config=global_config,
                     )
                     rebuilt_relationships_count += 1
-                    status_message = f"Relationship `{src} - {tgt}` rebuilt from {len(chunk_ids)} chunks"
+                    status_message = f"Rebuilt `{src} - {tgt}` from {len(chunk_ids)} chunks"
                     logger.info(status_message)
                     if pipeline_status is not None and pipeline_status_lock is not None:
                         async with pipeline_status_lock:
@@ -572,7 +572,7 @@ async def _rebuild_knowledge_from_chunks(
                 except Exception as e:
                     failed_relationships_count += 1
                     status_message = (
-                        f"Failed to rebuild relationship `{src} - {tgt}`: {e}"
+                        f"Failed to rebuild `{src} - {tgt}`: {e}"
                     )
                     logger.info(status_message)  # Per requirement, change to info
                     if pipeline_status is not None and pipeline_status_lock is not None:

From ff4c747a2ad2c23df83ceaefe931436e4b232c2c Mon Sep 17 00:00:00 2001
From: LinkinPony <friendshipgame714@gmail.com>
Date: Tue, 26 Aug 2025 10:43:56 +0800
Subject: [PATCH 054/141] fix mismatch of 'error' and 'error_msg' in MongoDB

---
 lightrag/kg/mongo_impl.py | 69 +++++++++++++++------------------------
 1 file changed, 27 insertions(+), 42 deletions(-)

diff --git a/lightrag/kg/mongo_impl.py b/lightrag/kg/mongo_impl.py
index b8d30c44..e7ea9a0a 100644
--- a/lightrag/kg/mongo_impl.py
+++ b/lightrag/kg/mongo_impl.py
@@ -280,6 +280,30 @@ class MongoDocStatusStorage(DocStatusStorage):
     db: AsyncDatabase = field(default=None)
     _data: AsyncCollection = field(default=None)
 
+    def _prepare_doc_status_data(self, doc: dict[str, Any]) -> dict[str, Any]:
+        """Normalize and migrate a raw Mongo document to DocProcessingStatus-compatible dict."""
+        # Make a copy of the data to avoid modifying the original
+        data = doc.copy()
+        # Remove deprecated content field if it exists
+        data.pop("content", None)
+        # Remove MongoDB _id field if it exists
+        data.pop("_id", None)
+        # If file_path is not in data, use document id as file path
+        if "file_path" not in data:
+            data["file_path"] = "no-file-path"
+        # Ensure new fields exist with default values
+        if "metadata" not in data:
+            data["metadata"] = {}
+        if "error_msg" not in data:
+            data["error_msg"] = None
+        # Backward compatibility: migrate legacy 'error' field to 'error_msg'
+        if "error" in data:
+            if "error_msg" not in data or data["error_msg"] in (None, ""):
+                data["error_msg"] = data.pop("error")
+            else:
+                data.pop("error", None)
+        return data
+
     def __init__(self, namespace, global_config, embedding_func, workspace=None):
         super().__init__(
             namespace=namespace,
@@ -389,20 +413,7 @@ class MongoDocStatusStorage(DocStatusStorage):
         processed_result = {}
         for doc in result:
             try:
-                # Make a copy of the data to avoid modifying the original
-                data = doc.copy()
-                # Remove deprecated content field if it exists
-                data.pop("content", None)
-                # Remove MongoDB _id field if it exists
-                data.pop("_id", None)
-                # If file_path is not in data, use document id as file path
-                if "file_path" not in data:
-                    data["file_path"] = "no-file-path"
-                # Ensure new fields exist with default values
-                if "metadata" not in data:
-                    data["metadata"] = {}
-                if "error_msg" not in data:
-                    data["error_msg"] = None
+                data = self._prepare_doc_status_data(doc)
                 processed_result[doc["_id"]] = DocProcessingStatus(**data)
             except KeyError as e:
                 logger.error(
@@ -420,20 +431,7 @@ class MongoDocStatusStorage(DocStatusStorage):
         processed_result = {}
         for doc in result:
             try:
-                # Make a copy of the data to avoid modifying the original
-                data = doc.copy()
-                # Remove deprecated content field if it exists
-                data.pop("content", None)
-                # Remove MongoDB _id field if it exists
-                data.pop("_id", None)
-                # If file_path is not in data, use document id as file path
-                if "file_path" not in data:
-                    data["file_path"] = "no-file-path"
-                # Ensure new fields exist with default values
-                if "metadata" not in data:
-                    data["metadata"] = {}
-                if "error_msg" not in data:
-                    data["error_msg"] = None
+                data = self._prepare_doc_status_data(doc)
                 processed_result[doc["_id"]] = DocProcessingStatus(**data)
             except KeyError as e:
                 logger.error(
@@ -661,20 +659,7 @@ class MongoDocStatusStorage(DocStatusStorage):
             try:
                 doc_id = doc["_id"]
 
-                # Make a copy of the data to avoid modifying the original
-                data = doc.copy()
-                # Remove deprecated content field if it exists
-                data.pop("content", None)
-                # Remove MongoDB _id field if it exists
-                data.pop("_id", None)
-                # If file_path is not in data, use document id as file path
-                if "file_path" not in data:
-                    data["file_path"] = "no-file-path"
-                # Ensure new fields exist with default values
-                if "metadata" not in data:
-                    data["metadata"] = {}
-                if "error_msg" not in data:
-                    data["error_msg"] = None
+                data = self._prepare_doc_status_data(doc)
 
                 doc_status = DocProcessingStatus(**data)
                 documents.append((doc_id, doc_status))

From 6bcfe696ee7c0caf55ffbdbe6723045f07a77030 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 14:41:12 +0800
Subject: [PATCH 055/141] feat: add output length recommendation and
 description type to LLM summary

- Add SUMMARY_LENGTH_RECOMMENDED parameter (600 tokens)
- Optimize prompt temple for LLM summary
---
 env.example            |  8 +++++---
 lightrag/api/config.py |  9 +++++++++
 lightrag/constants.py  |  9 +++++++--
 lightrag/lightrag.py   | 14 +++++++++++++-
 lightrag/operate.py    | 36 ++++++++++++++++++++++++++----------
 lightrag/prompt.py     | 30 ++++++++++++++++++------------
 6 files changed, 78 insertions(+), 28 deletions(-)

diff --git a/env.example b/env.example
index a64626ef..3ce6d1d9 100644
--- a/env.example
+++ b/env.example
@@ -128,10 +128,12 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true
 
 ### Number of summary semgments or tokens to trigger LLM summary on entity/relation merge (at least 3 is recommented)
 # FORCE_LLM_SUMMARY_ON_MERGE=8
-### Number of tokens to trigger LLM summary on entity/relation merge
-# SUMMARY_MAX_TOKENS = 500
+### Max description token size to trigger LLM summary
+# SUMMARY_MAX_TOKENS = 1200
+### Recommended LLM summary output length in tokens
+# SUMMARY_LENGTH_RECOMMENDED_=600
 ### Maximum context size sent to LLM for description summary
-# SUMMARY_CONTEXT_SIZE=10000
+# SUMMARY_CONTEXT_SIZE=12000
 
 ###############################
 ### Concurrency Configuration
diff --git a/lightrag/api/config.py b/lightrag/api/config.py
index f4a281a7..a6badec4 100644
--- a/lightrag/api/config.py
+++ b/lightrag/api/config.py
@@ -30,6 +30,7 @@ from lightrag.constants import (
     DEFAULT_FORCE_LLM_SUMMARY_ON_MERGE,
     DEFAULT_MAX_ASYNC,
     DEFAULT_SUMMARY_MAX_TOKENS,
+    DEFAULT_SUMMARY_LENGTH_RECOMMENDED,
     DEFAULT_SUMMARY_CONTEXT_SIZE,
     DEFAULT_SUMMARY_LANGUAGE,
     DEFAULT_EMBEDDING_FUNC_MAX_ASYNC,
@@ -133,6 +134,14 @@ def parse_args() -> argparse.Namespace:
         ),
         help=f"LLM Summary Context size (default: from env or {DEFAULT_SUMMARY_CONTEXT_SIZE})",
     )
+    parser.add_argument(
+        "--summary-length-recommended",
+        type=int,
+        default=get_env_value(
+            "SUMMARY_LENGTH_RECOMMENDED", DEFAULT_SUMMARY_LENGTH_RECOMMENDED, int
+        ),
+        help=f"LLM Summary Context size (default: from env or {DEFAULT_SUMMARY_LENGTH_RECOMMENDED})",
+    )
 
     # Logging configuration
     parser.add_argument(
diff --git a/lightrag/constants.py b/lightrag/constants.py
index 0e6d6dcd..2f493277 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -14,9 +14,14 @@ DEFAULT_MAX_GRAPH_NODES = 1000
 DEFAULT_SUMMARY_LANGUAGE = "English"  # Default language for summaries
 DEFAULT_MAX_GLEANING = 1
 
+# Number of description fragments to trigger LLM summary
 DEFAULT_FORCE_LLM_SUMMARY_ON_MERGE = 8
-DEFAULT_SUMMARY_MAX_TOKENS = 500  # Max token size for entity/relation summary
-DEFAULT_SUMMARY_CONTEXT_SIZE = 10000  # Default maximum token size
+# Max description token size to trigger LLM summary
+DEFAULT_SUMMARY_MAX_TOKENS = 1200
+# Recommended LLM summary output length in tokens
+DEFAULT_SUMMARY_LENGTH_RECOMMENDED = 600
+# Maximum token size sent to LLM for summary
+DEFAULT_SUMMARY_CONTEXT_SIZE = 12000
 
 # Separator for graph fields
 GRAPH_FIELD_SEP = "<SEP>"
diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index f5529bad..f4dc9dd4 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -35,6 +35,7 @@ from lightrag.constants import (
     DEFAULT_MIN_RERANK_SCORE,
     DEFAULT_SUMMARY_MAX_TOKENS,
     DEFAULT_SUMMARY_CONTEXT_SIZE,
+    DEFAULT_SUMMARY_LENGTH_RECOMMENDED,
     DEFAULT_MAX_ASYNC,
     DEFAULT_MAX_PARALLEL_INSERT,
     DEFAULT_MAX_GRAPH_NODES,
@@ -293,6 +294,13 @@ class LightRAG:
     )
     """Maximum number of tokens allowed per LLM response."""
 
+    summary_length_recommended: int = field(
+        default=int(
+            os.getenv("SUMMARY_LENGTH_RECOMMENDED", DEFAULT_SUMMARY_LENGTH_RECOMMENDED)
+        )
+    )
+    """Recommended length of LLM summary output."""
+
     llm_model_max_async: int = field(
         default=int(os.getenv("MAX_ASYNC", DEFAULT_MAX_ASYNC))
     )
@@ -435,9 +443,13 @@ class LightRAG:
                 f"summary_context_size must be at least summary_max_tokens * force_llm_summary_on_merge, got {self.summary_context_size}"
             )
         if self.summary_context_size > self.max_total_tokens:
-            logger.warning(
+            logger.error(
                 f"summary_context_size must be less than max_total_tokens, got {self.summary_context_size}"
             )
+        if self.summary_length_recommended > self.summary_max_tokens:
+            logger.warning(
+                f"summary_length_recommended should less than max_total_tokens, got {self.summary_length_recommended}"
+            )
 
         # Fix global_config now
         global_config = asdict(self)
diff --git a/lightrag/operate.py b/lightrag/operate.py
index 6820401c..17dfa58c 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -114,6 +114,7 @@ def chunking_by_token_size(
 
 
 async def _handle_entity_relation_summary(
+    description_type: str,
     entity_or_relation_name: str,
     description_list: list[str],
     force_llm_summary_on_merge: int,
@@ -172,6 +173,7 @@ async def _handle_entity_relation_summary(
             else:
                 # Final summarization of remaining descriptions - LLM will be used
                 final_summary = await _summarize_descriptions(
+                    description_type,
                     entity_or_relation_name,
                     current_list,
                     global_config,
@@ -213,7 +215,11 @@ async def _handle_entity_relation_summary(
             else:
                 # Multiple descriptions need LLM summarization
                 summary = await _summarize_descriptions(
-                    entity_or_relation_name, chunk, global_config, llm_response_cache
+                    description_type,
+                    entity_or_relation_name,
+                    chunk,
+                    global_config,
+                    llm_response_cache,
                 )
                 new_summaries.append(summary)
                 llm_was_used = True  # Mark that LLM was used in reduce phase
@@ -223,7 +229,8 @@ async def _handle_entity_relation_summary(
 
 
 async def _summarize_descriptions(
-    entity_or_relation_name: str,
+    description_type: str,
+    description_name: str,
     description_list: list[str],
     global_config: dict,
     llm_response_cache: BaseKVStorage | None = None,
@@ -247,18 +254,22 @@ async def _summarize_descriptions(
         "language", PROMPTS["DEFAULT_LANGUAGE"]
     )
 
+    summary_length_recommended = global_config["summary_length_recommended"]
+
     prompt_template = PROMPTS["summarize_entity_descriptions"]
 
     # Prepare context for the prompt
     context_base = dict(
-        entity_name=entity_or_relation_name,
-        description_list="\n".join(description_list),
+        description_type=description_type,
+        description_name=description_name,
+        description_list="\n\n".join(description_list),
+        summary_length=summary_length_recommended,
         language=language,
     )
     use_prompt = prompt_template.format(**context_base)
 
     logger.debug(
-        f"Summarizing {len(description_list)} descriptions for: {entity_or_relation_name}"
+        f"Summarizing {len(description_list)} descriptions for: {description_name}"
     )
 
     # Use LLM function with cache (higher priority for summary generation)
@@ -563,7 +574,9 @@ async def _rebuild_knowledge_from_chunks(
                         global_config=global_config,
                     )
                     rebuilt_relationships_count += 1
-                    status_message = f"Rebuilt `{src} - {tgt}` from {len(chunk_ids)} chunks"
+                    status_message = (
+                        f"Rebuilt `{src} - {tgt}` from {len(chunk_ids)} chunks"
+                    )
                     logger.info(status_message)
                     if pipeline_status is not None and pipeline_status_lock is not None:
                         async with pipeline_status_lock:
@@ -571,9 +584,7 @@ async def _rebuild_knowledge_from_chunks(
                             pipeline_status["history_messages"].append(status_message)
                 except Exception as e:
                     failed_relationships_count += 1
-                    status_message = (
-                        f"Failed to rebuild `{src} - {tgt}`: {e}"
-                    )
+                    status_message = f"Failed to rebuild `{src} - {tgt}`: {e}"
                     logger.info(status_message)  # Per requirement, change to info
                     if pipeline_status is not None and pipeline_status_lock is not None:
                         async with pipeline_status_lock:
@@ -873,6 +884,7 @@ async def _rebuild_single_entity(
         if description_list:
             force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
             final_description, _ = await _handle_entity_relation_summary(
+                "Entity",
                 entity_name,
                 description_list,
                 force_llm_summary_on_merge,
@@ -915,6 +927,7 @@ async def _rebuild_single_entity(
     force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
     if description_list:
         final_description, _ = await _handle_entity_relation_summary(
+            "Entity",
             entity_name,
             description_list,
             force_llm_summary_on_merge,
@@ -996,6 +1009,7 @@ async def _rebuild_single_relationship(
     force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
     if description_list:
         final_description, _ = await _handle_entity_relation_summary(
+            "Relation",
             f"{src}-{tgt}",
             description_list,
             force_llm_summary_on_merge,
@@ -1100,6 +1114,7 @@ async def _merge_nodes_then_upsert(
     if num_fragment > 0:
         # Get summary and LLM usage status
         description, llm_was_used = await _handle_entity_relation_summary(
+            "Entity",
             entity_name,
             description_list,
             force_llm_summary_on_merge,
@@ -1218,6 +1233,7 @@ async def _merge_edges_then_upsert(
     if num_fragment > 0:
         # Get summary and LLM usage status
         description, llm_was_used = await _handle_entity_relation_summary(
+            "Relation",
             f"({src_id}, {tgt_id})",
             description_list,
             force_llm_summary_on_merge,
@@ -1595,7 +1611,7 @@ async def merge_nodes_and_edges(
             )
             # Don't raise exception to avoid affecting main flow
 
-    log_message = f"Completed merging: {len(processed_entities)} entities, {len(all_added_entities)} added entities, {len(processed_edges)} relations"
+    log_message = f"Completed merging: {len(processed_entities)} entities, {len(all_added_entities)} extra entities, {len(processed_edges)} relations"
     logger.info(log_message)
     async with pipeline_status_lock:
         pipeline_status["latest_message"] = log_message
diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index 32666bb5..c8f8c3a3 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -133,20 +133,26 @@ Output:
 #############################""",
 ]
 
-PROMPTS[
-    "summarize_entity_descriptions"
-] = """You are a helpful assistant responsible for generating a comprehensive summary of the data provided below.
-Given one or two entities, and a list of descriptions, all related to the same entity or group of entities.
-Please concatenate all of these into a single, comprehensive description. Make sure to include information collected from all the descriptions.
-If the provided descriptions are contradictory, please resolve the contradictions and provide a single, coherent summary.
-Make sure it is written in third person, and include the entity names so we the have full context.
-Use {language} as output language.
+PROMPTS["summarize_entity_descriptions"] = """---Role---
+You are a Knowledge Graph Specialist responsible for data curation and synthesis.
+
+---Task---
+Your task is to synthesize a list of descriptions of a given entity or relation into a single, comprehensive, and cohesive summary.
+
+---Instructions---
+1. **Comprehensiveness:** The summary must integrate key information from all provided descriptions. Do not omit important facts.
+2. **Consistency:** If the descriptions contain contradictions, you must resolve them to produce a logically consistent summary. If a contradiction cannot be resolved, phrase the information neutrally.
+3. **Context:** The summary must explicitly mention the name of the entity or relation for full context.
+4. **Style:** The output must be written from an objective, third-person perspective.
+5. **Conciseness:** Be concise and avoid redundancy. The summary's length must not exceed {summary_length} tokens.
+6. **Language:** The entire output must be written in {language}.
 
-#######
 ---Data---
-Entities: {entity_name}
-Description List: {description_list}
-#######
+{description_type} Name: {description_name}
+Description List:
+{description_list}
+
+---Output---
 Output:
 """
 

From 01a2c79f29ceab3cbf9cdcbff2e8ec33a2abd245 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 14:42:52 +0800
Subject: [PATCH 056/141] Standardize prompt formatting and section headers
 across templates

- Remove hash delimiters
- Consistent section headers
- Add "Output:" labels
- Clean up example formatting
---
 lightrag/prompt.py | 37 ++++++++++++++++++-------------------
 1 file changed, 18 insertions(+), 19 deletions(-)

diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index c8f8c3a3..ce78f8a6 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -40,22 +40,19 @@ Format the content-level key words as ("content_keywords"{tuple_delimiter}<high_
 
 5. When finished, output {completion_delimiter}
 
-######################
 ---Examples---
-######################
 {examples}
 
-#############################
 ---Real Data---
-######################
 Entity_types: [{entity_types}]
 Text:
 {input_text}
-######################
+
+---Output---
 Output:"""
 
 PROMPTS["entity_extraction_examples"] = [
-    """Example 1:
+    """------Example 1------
 
 Entity_types: [person, technology, mission, organization, location]
 Text:
@@ -81,8 +78,9 @@ Output:
 ("relationship"{tuple_delimiter}"Jordan"{tuple_delimiter}"Cruz"{tuple_delimiter}"Jordan's commitment to discovery is in rebellion against Cruz's vision of control and order."{tuple_delimiter}"ideological conflict, rebellion"{tuple_delimiter}5){record_delimiter}
 ("relationship"{tuple_delimiter}"Taylor"{tuple_delimiter}"The Device"{tuple_delimiter}"Taylor shows reverence towards the device, indicating its importance and potential impact."{tuple_delimiter}"reverence, technological significance"{tuple_delimiter}9){record_delimiter}
 ("content_keywords"{tuple_delimiter}"power dynamics, ideological conflict, discovery, rebellion"){completion_delimiter}
-#############################""",
-    """Example 2:
+
+""",
+    """------Example 2------
 
 Entity_types: [company, index, commodity, market_trend, economic_policy, biological]
 Text:
@@ -109,8 +107,9 @@ Output:
 ("relationship"{tuple_delimiter}"Gold Futures"{tuple_delimiter}"Market Selloff"{tuple_delimiter}"Gold prices rose as investors sought safe-haven assets during the market selloff."{tuple_delimiter}"market reaction, safe-haven investment"{tuple_delimiter}10){record_delimiter}
 ("relationship"{tuple_delimiter}"Federal Reserve Policy Announcement"{tuple_delimiter}"Market Selloff"{tuple_delimiter}"Speculation over Federal Reserve policy changes contributed to market volatility and investor selloff."{tuple_delimiter}"interest rate impact, financial regulation"{tuple_delimiter}7){record_delimiter}
 ("content_keywords"{tuple_delimiter}"market downturn, investor sentiment, commodities, Federal Reserve, stock performance"){completion_delimiter}
-#############################""",
-    """Example 3:
+
+""",
+    """------Example 3------
 
 Entity_types: [economic_policy, athlete, event, location, record, organization, equipment]
 Text:
@@ -130,7 +129,8 @@ Output:
 ("relationship"{tuple_delimiter}"Noah Carter"{tuple_delimiter}"Carbon-Fiber Spikes"{tuple_delimiter}"Noah Carter used carbon-fiber spikes to enhance performance during the race."{tuple_delimiter}"athletic equipment, performance boost"{tuple_delimiter}7){record_delimiter}
 ("relationship"{tuple_delimiter}"World Athletics Federation"{tuple_delimiter}"100m Sprint Record"{tuple_delimiter}"The World Athletics Federation is responsible for validating and recognizing new sprint records."{tuple_delimiter}"sports regulation, record certification"{tuple_delimiter}9){record_delimiter}
 ("content_keywords"{tuple_delimiter}"athletics, sprinting, record-breaking, sports technology, competition"){completion_delimiter}
-#############################""",
+
+""",
 ]
 
 PROMPTS["summarize_entity_descriptions"] = """---Role---
@@ -194,8 +194,7 @@ PROMPTS["entity_if_loop_extraction"] = """
 It appears some entities may have still been missed.
 
 ---Output---
-
-Answer ONLY by `YES` OR `NO` if there are still entities that need to be added.
+Output:
 """.strip()
 
 PROMPTS["fail_response"] = (
@@ -217,7 +216,7 @@ Generate a concise response based on Knowledge Base and follow Response Rules, c
 ---Knowledge Graph and Document Chunks---
 {context_data}
 
----RESPONSE GUIDELINES---
+---Response Guidelines---
 **1. Content & Adherence:**
 - Strictly adhere to the provided context from the Knowledge Base. Do not invent, assume, or include any information not present in the source data.
 - If the answer cannot be found in the provided context, state that you do not have enough information to answer.
@@ -239,8 +238,8 @@ Generate a concise response based on Knowledge Base and follow Response Rules, c
 ---USER CONTEXT---
 - Additional user prompt: {user_prompt}
 
-
-Response:"""
+---Response---
+Output:"""
 
 PROMPTS["keywords_extraction"] = """---Role---
 You are an expert keyword extractor, specializing in analyzing user queries for a Retrieval-Augmented Generation (RAG) system. Your purpose is to identify both high-level and low-level keywords in the user's query that will be used for effective document retrieval.
@@ -263,7 +262,7 @@ Given a user query, your task is to extract two distinct types of keywords:
 User Query: {query}
 
 ---Output---
-"""
+Output:"""
 
 PROMPTS["keywords_extraction_examples"] = [
     """Example 1:
@@ -333,5 +332,5 @@ Generate a concise response based on Document Chunks and follow Response Rules,
 ---USER CONTEXT---
 - Additional user prompt: {user_prompt}
 
-
-Response:"""
+---Response---
+Output:"""

From 79e0226b2bf40465947fdf40485d79e5d090f9fd Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 18:02:39 +0800
Subject: [PATCH 057/141] Refactor: move force_llm_summary_on_merge to
 global_config access

- Remove parameter from function signature
- Access from global_config instead
- Improve code consistency
---
 lightrag/operate.py | 19 +++++--------------
 1 file changed, 5 insertions(+), 14 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 17dfa58c..ee17ab56 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -117,7 +117,6 @@ async def _handle_entity_relation_summary(
     description_type: str,
     entity_or_relation_name: str,
     description_list: list[str],
-    force_llm_summary_on_merge: int,
     seperator: str,
     global_config: dict,
     llm_response_cache: BaseKVStorage | None = None,
@@ -152,6 +151,7 @@ async def _handle_entity_relation_summary(
     tokenizer: Tokenizer = global_config["tokenizer"]
     summary_context_size = global_config["summary_context_size"]
     summary_max_tokens = global_config["summary_max_tokens"]
+    force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
 
     current_list = description_list[:]  # Copy the list to avoid modifying original
     llm_was_used = False  # Track whether LLM was used during the entire process
@@ -880,14 +880,12 @@ async def _rebuild_single_entity(
         # deduplicate descriptions
         description_list = list(dict.fromkeys(relationship_descriptions))
 
-        # Generate description from relationships or fallback to current
+        # Generate final description from relationships or fallback to current
         if description_list:
-            force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
             final_description, _ = await _handle_entity_relation_summary(
                 "Entity",
                 entity_name,
                 description_list,
-                force_llm_summary_on_merge,
                 GRAPH_FIELD_SEP,
                 global_config,
                 llm_response_cache=llm_response_cache,
@@ -923,14 +921,12 @@ async def _rebuild_single_entity(
         else current_entity.get("entity_type", "UNKNOWN")
     )
 
-    # Generate final description and update storage
-    force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
+    # Generate final description from entities or fallback to current
     if description_list:
         final_description, _ = await _handle_entity_relation_summary(
             "Entity",
             entity_name,
             description_list,
-            force_llm_summary_on_merge,
             GRAPH_FIELD_SEP,
             global_config,
             llm_response_cache=llm_response_cache,
@@ -1005,14 +1001,12 @@ async def _rebuild_single_relationship(
 
     weight = sum(weights) if weights else current_relationship.get("weight", 1.0)
 
-    # Use summary if description has too many fragments
-    force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
+    # Generate final description from relations or fallback to current
     if description_list:
         final_description, _ = await _handle_entity_relation_summary(
             "Relation",
             f"{src}-{tgt}",
             description_list,
-            force_llm_summary_on_merge,
             GRAPH_FIELD_SEP,
             global_config,
             llm_response_cache=llm_response_cache,
@@ -1096,6 +1090,7 @@ async def _merge_nodes_then_upsert(
         reverse=True,
     )[0][0]  # Get the entity type with the highest count
 
+    # merge and deduplicate description
     description_list = list(
         dict.fromkeys(
             already_description
@@ -1103,7 +1098,6 @@ async def _merge_nodes_then_upsert(
         )
     )
 
-    force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
     num_fragment = len(description_list)
     already_fragment = len(already_description)
     deduplicated_num = already_fragment + len(nodes_data) - num_fragment
@@ -1117,7 +1111,6 @@ async def _merge_nodes_then_upsert(
             "Entity",
             entity_name,
             description_list,
-            force_llm_summary_on_merge,
             GRAPH_FIELD_SEP,
             global_config,
             llm_response_cache,
@@ -1222,7 +1215,6 @@ async def _merge_edges_then_upsert(
         )
     )
 
-    force_llm_summary_on_merge = global_config["force_llm_summary_on_merge"]
     num_fragment = len(description_list)
     already_fragment = len(already_description)
     deduplicated_num = already_fragment + len(edges_data) - num_fragment
@@ -1236,7 +1228,6 @@ async def _merge_edges_then_upsert(
             "Relation",
             f"({src_id}, {tgt_id})",
             description_list,
-            force_llm_summary_on_merge,
             GRAPH_FIELD_SEP,
             global_config,
             llm_response_cache,

From e0a755e42cef804a8c6be3dfea8e48a805a8a523 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 18:28:57 +0800
Subject: [PATCH 058/141] Refactor prompt instructions to emphasize depth and
 completeness

---
 lightrag/prompt.py | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index ce78f8a6..586f7ae6 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -141,11 +141,10 @@ Your task is to synthesize a list of descriptions of a given entity or relation
 
 ---Instructions---
 1. **Comprehensiveness:** The summary must integrate key information from all provided descriptions. Do not omit important facts.
-2. **Consistency:** If the descriptions contain contradictions, you must resolve them to produce a logically consistent summary. If a contradiction cannot be resolved, phrase the information neutrally.
-3. **Context:** The summary must explicitly mention the name of the entity or relation for full context.
-4. **Style:** The output must be written from an objective, third-person perspective.
-5. **Conciseness:** Be concise and avoid redundancy. The summary's length must not exceed {summary_length} tokens.
-6. **Language:** The entire output must be written in {language}.
+2. **Context:** The summary must explicitly mention the name of the entity or relation for full context.
+3. **Style:** The output must be written from an objective, third-person perspective.
+4. **Length:** Maintain depth and completeness while ensuring the summary's length not exceed {summary_length} tokens.
+5. **Language:** The entire output must be written in {language}.
 
 ---Data---
 {description_type} Name: {description_name}

From d3623cc9ae84de67cfb417800f7f512a86533442 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 21:58:31 +0800
Subject: [PATCH 059/141] fix: resolve infinite loop risk in
 _handle_entity_relation_summary

- Ensure oversized descriptions are force-merged with subsequent ones
- Add len(current_list) <= 2 termination condition to guarantee convergence
- Implement token-based truncation in _summarize_descriptions to prevent overflow
---
 lightrag/lightrag.py | 13 +++----------
 lightrag/operate.py  | 46 +++++++++++++++++++++++++++++++++++---------
 2 files changed, 40 insertions(+), 19 deletions(-)

diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index f4dc9dd4..8dbff74f 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -435,20 +435,13 @@ class LightRAG:
             logger.warning(
                 f"force_llm_summary_on_merge should be at least 3, got {self.force_llm_summary_on_merge}"
             )
-        if (
-            self.summary_max_tokens * self.force_llm_summary_on_merge
-            > self.summary_context_size
-        ):
-            logger.warning(
-                f"summary_context_size must be at least summary_max_tokens * force_llm_summary_on_merge, got {self.summary_context_size}"
-            )
         if self.summary_context_size > self.max_total_tokens:
-            logger.error(
-                f"summary_context_size must be less than max_total_tokens, got {self.summary_context_size}"
+            logger.warning(
+                f"summary_context_size({self.summary_context_size}) should no greater than max_total_tokens({self.max_total_tokens})"
             )
         if self.summary_length_recommended > self.summary_max_tokens:
             logger.warning(
-                f"summary_length_recommended should less than max_total_tokens, got {self.summary_length_recommended}"
+                f"max_total_tokens({self.summary_max_tokens}) should greater than summary_length_recommended({self.summary_length_recommended})"
             )
 
         # Fix global_config now
diff --git a/lightrag/operate.py b/lightrag/operate.py
index ee17ab56..486f7e69 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -162,15 +162,19 @@ async def _handle_entity_relation_summary(
         total_tokens = sum(len(tokenizer.encode(desc)) for desc in current_list)
 
         # If total length is within limits, perform final summarization
-        if total_tokens <= summary_context_size:
+        if total_tokens <= summary_context_size or len(current_list) <= 2:
             if (
                 len(current_list) < force_llm_summary_on_merge
                 and total_tokens < summary_max_tokens
             ):
-                # Already the final result - no LLM needed
+                # no LLM needed, just join the descriptions
                 final_description = seperator.join(current_list)
                 return final_description if final_description else "", llm_was_used
             else:
+                if total_tokens > summary_context_size and len(current_list) <= 2:
+                    logger.warning(
+                        f"Summarizing {entity_or_relation_name}: Oversize descpriton found"
+                    )
                 # Final summarization of remaining descriptions - LLM will be used
                 final_summary = await _summarize_descriptions(
                     description_type,
@@ -182,18 +186,31 @@ async def _handle_entity_relation_summary(
                 return final_summary, True  # LLM was used for final summarization
 
         # Need to split into chunks - Map phase
+        # Ensure each chunk has minimum 2 descriptions to guarantee progress
         chunks = []
         current_chunk = []
         current_tokens = 0
 
-        for desc in current_list:
+        # Currently least 3 descriptions in current_list
+        for i, desc in enumerate(current_list):
             desc_tokens = len(tokenizer.encode(desc))
 
             # If adding current description would exceed limit, finalize current chunk
             if current_tokens + desc_tokens > summary_context_size and current_chunk:
-                chunks.append(current_chunk)
-                current_chunk = [desc]  # Initial chunk for next group
-                current_tokens = desc_tokens
+                # Ensure we have at least 2 descriptions in the chunk (when possible)
+                if len(current_chunk) == 1:
+                    # Force add one more description to ensure minimum 2 per chunk
+                    current_chunk.append(desc)
+                    chunks.append(current_chunk)
+                    logger.warning(
+                        f"Summarizing {entity_or_relation_name}: Oversize descpriton found"
+                    )
+                    current_chunk = []  # next group is empty
+                    current_tokens = 0
+                else:  # curren_chunk is ready for summary in reduce phase
+                    chunks.append(current_chunk)
+                    current_chunk = [desc]  # leave it for next group
+                    current_tokens = desc_tokens
             else:
                 current_chunk.append(desc)
                 current_tokens += desc_tokens
@@ -203,10 +220,10 @@ async def _handle_entity_relation_summary(
             chunks.append(current_chunk)
 
         logger.info(
-            f"Summarizing {entity_or_relation_name}: split {len(current_list)} descriptions into {len(chunks)} groups"
+            f"   Summarizing {entity_or_relation_name}: Map {len(current_list)} descriptions into {len(chunks)} groups"
         )
 
-        # Reduce phase: summarize each chunk
+        # Reduce phase: summarize each group from chunks
         new_summaries = []
         for chunk in chunks:
             if len(chunk) == 1:
@@ -258,11 +275,22 @@ async def _summarize_descriptions(
 
     prompt_template = PROMPTS["summarize_entity_descriptions"]
 
+    # Join descriptions and apply token-based truncation if necessary
+    joined_descriptions = "\n\n".join(description_list)
+    tokenizer = global_config["tokenizer"]
+    summary_context_size = global_config["summary_context_size"]
+
+    # Token-based truncation to ensure input fits within limits
+    tokens = tokenizer.encode(joined_descriptions)
+    if len(tokens) > summary_context_size:
+        truncated_tokens = tokens[:summary_context_size]
+        joined_descriptions = tokenizer.decode(truncated_tokens)
+
     # Prepare context for the prompt
     context_base = dict(
         description_type=description_type,
         description_name=description_name,
-        description_list="\n\n".join(description_list),
+        description_list=joined_descriptions,
         summary_length=summary_length_recommended,
         language=language,
     )

From 7db788aa665e15df525aeaff7e6bfc5b0af406ad Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 23:03:41 +0800
Subject: [PATCH 060/141] fix(webui): resolve document status grouping issue in
 DocumentManager

- Fix documents being grouped by status after pagination and sorting
- Use backend-sorted data directly from currentPageDocs instead of re-grouping
- Preserve backend sort order to prevent status-based grouping
- Maintain backward compatibility with legacy docs structure
- Ensure all sorting fields (file name, dates, ID) work correctly without status grouping

The issue occurred because the frontend was re-grouping already-sorted data
from the backend by status, breaking the intended sort order. Now documents
are displayed in the exact order returned by the backend API.

Fixes: Document list sorting by file name was grouping by status instead of
maintaining proper sort order across all documents.
---
 lightrag_webui/src/features/DocumentManager.tsx | 14 ++++++++++++--
 1 file changed, 12 insertions(+), 2 deletions(-)

diff --git a/lightrag_webui/src/features/DocumentManager.tsx b/lightrag_webui/src/features/DocumentManager.tsx
index 3e065ddf..2ce3daee 100644
--- a/lightrag_webui/src/features/DocumentManager.tsx
+++ b/lightrag_webui/src/features/DocumentManager.tsx
@@ -183,7 +183,7 @@ export default function DocumentManager() {
   const setDocumentsPageSize = useSettingsStore.use.setDocumentsPageSize()
 
   // New pagination state
-  const [, setCurrentPageDocs] = useState<DocStatusResponse[]>([])
+  const [currentPageDocs, setCurrentPageDocs] = useState<DocStatusResponse[]>([])
   const [pagination, setPagination] = useState<PaginationInfo>({
     page: 1,
     page_size: documentsPageSize,
@@ -292,6 +292,16 @@ export default function DocumentManager() {
   type DocStatusWithStatus = DocStatusResponse & { status: DocStatus };
 
   const filteredAndSortedDocs = useMemo(() => {
+    // Use currentPageDocs directly if available (from paginated API)
+    // This preserves the backend's sort order and prevents status grouping
+    if (currentPageDocs && currentPageDocs.length > 0) {
+      return currentPageDocs.map(doc => ({
+        ...doc,
+        status: doc.status as DocStatus
+      })) as DocStatusWithStatus[];
+    }
+
+    // Fallback to legacy docs structure for backward compatibility
     if (!docs) return null;
 
     // Create a flat array of documents with status information
@@ -324,7 +334,7 @@ export default function DocumentManager() {
     }
 
     return allDocuments;
-  }, [docs, sortField, sortDirection, statusFilter, sortDocuments]);
+  }, [currentPageDocs, docs, sortField, sortDirection, statusFilter, sortDocuments]);
 
   // Calculate current page selection state (after filteredAndSortedDocs is defined)
   const currentPageDocIds = useMemo(() => {

From c259b8f22cded995f46fe3324ba8d6334f12ee19 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 26 Aug 2025 23:05:00 +0800
Subject: [PATCH 061/141] Update webui assets and bump aip verion to 0208

---
 lightrag/api/__init__.py                      |  2 +-
 .../assets/feature-documents-DLarjU2a.js      | 87 +++++++++++++++++++
 .../assets/feature-documents-Di_Wt0BY.js      | 87 -------------------
 ...OAaIQ.js => feature-retrieval-P5Qspbob.js} |  2 +-
 .../{index-B8PWUG__.js => index-DI6XUmEl.js}  |  2 +-
 lightrag/api/webui/index.html                 |  6 +-
 6 files changed, 93 insertions(+), 93 deletions(-)
 create mode 100644 lightrag/api/webui/assets/feature-documents-DLarjU2a.js
 delete mode 100644 lightrag/api/webui/assets/feature-documents-Di_Wt0BY.js
 rename lightrag/api/webui/assets/{feature-retrieval-DVuOAaIQ.js => feature-retrieval-P5Qspbob.js} (99%)
 rename lightrag/api/webui/assets/{index-B8PWUG__.js => index-DI6XUmEl.js} (99%)

diff --git a/lightrag/api/__init__.py b/lightrag/api/__init__.py
index ac183b60..8ac6e5b9 100644
--- a/lightrag/api/__init__.py
+++ b/lightrag/api/__init__.py
@@ -1 +1 @@
-__api_version__ = "0207"
+__api_version__ = "0208"
diff --git a/lightrag/api/webui/assets/feature-documents-DLarjU2a.js b/lightrag/api/webui/assets/feature-documents-DLarjU2a.js
new file mode 100644
index 00000000..69306b08
--- /dev/null
+++ b/lightrag/api/webui/assets/feature-documents-DLarjU2a.js
@@ -0,0 +1,87 @@
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+  pointer-events: none;
+  top: 0;
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+  height: 0;
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+  }
+  50% {
+    background-color: rgb(255 0 0 / 0.2);
+    border-color: rgb(255 0 0 / 0.4);
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+@keyframes dark-pulse {
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+  }
+  50% {
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diff --git a/lightrag/api/webui/assets/feature-documents-Di_Wt0BY.js b/lightrag/api/webui/assets/feature-documents-Di_Wt0BY.js
deleted file mode 100644
index dc984898..00000000
--- a/lightrag/api/webui/assets/feature-documents-Di_Wt0BY.js
+++ /dev/null
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diff --git a/lightrag/api/webui/assets/feature-retrieval-DVuOAaIQ.js b/lightrag/api/webui/assets/feature-retrieval-P5Qspbob.js
similarity index 99%
rename from lightrag/api/webui/assets/feature-retrieval-DVuOAaIQ.js
rename to lightrag/api/webui/assets/feature-retrieval-P5Qspbob.js
index 4a1303f3..02c9f918 100644
--- a/lightrag/api/webui/assets/feature-retrieval-DVuOAaIQ.js
+++ b/lightrag/api/webui/assets/feature-retrieval-P5Qspbob.js
@@ -1,5 +1,5 @@
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diff --git a/lightrag/api/webui/assets/index-B8PWUG__.js b/lightrag/api/webui/assets/index-DI6XUmEl.js
similarity index 99%
rename from lightrag/api/webui/assets/index-B8PWUG__.js
rename to lightrag/api/webui/assets/index-DI6XUmEl.js
index b2f8612b..c47c89c5 100644
--- a/lightrag/api/webui/assets/index-B8PWUG__.js
+++ b/lightrag/api/webui/assets/index-DI6XUmEl.js
@@ -1,4 +1,4 @@
-import{j as o,Y as td,O as fg,k as dg,u as ad,Z as mg,c as hg,l as gg,g as pg,S as yg,T as vg,n as bg,m as nd,o as Sg,p as Tg,$ as ud,a0 as id,a1 as cd,a2 as xg}from"./ui-vendor-CeCm8EER.js";import{d as Ag,h as Dg,r as E,u as sd,H as Ng,i as Eg,j as kf}from"./react-vendor-DEwriMA6.js";import{N as we,c as Ve,ad as od,u as Bl,M as sl,ae as rd,af as fd,I as us,B as Cn,D as Mg,l as zg,m as Cg,n as Og,o as _g,ag as Rg,ah as jg,ai as Ug,aj as Hg,ak as ql,al as dd,am as ss,an as is,a0 as Lg,a1 as qg,a2 as Bg,a3 as Gg,ao as Yg,ap as Xg,aq as md,ar as wg,as as hd,at as Vg,au as gd,d as Qg,R as Kg,V as Zg,g as En,av as kg,aw as Jg,ax as Fg}from"./feature-graph-C6IuADHZ.js";import{S as Jf,a as Ff,b as Pf,c as $f,e as rt,D as Pg}from"./feature-documents-Di_Wt0BY.js";import{R as $g}from"./feature-retrieval-DVuOAaIQ.js";import{i as cs}from"./utils-vendor-BysuhMZA.js";import"./graph-vendor-B-X5JegA.js";import"./mermaid-vendor-CAxUo7Zk.js";import"./markdown-vendor-DmIvJdn7.js";(function(){const y=document.createElement("link").relList;if(y&&y.supports&&y.supports("modulepreload"))return;for(const N of document.querySelectorAll('link[rel="modulepreload"]'))d(N);new MutationObserver(N=>{for(const _ of N)if(_.type==="childList")for(const H of _.addedNodes)H.tagName==="LINK"&&H.rel==="modulepreload"&&d(H)}).observe(document,{childList:!0,subtree:!0});function x(N){const _={};return N.integrity&&(_.integrity=N.integrity),N.referrerPolicy&&(_.referrerPolicy=N.referrerPolicy),N.crossOrigin==="use-credentials"?_.credentials="include":N.crossOrigin==="anonymous"?_.credentials="omit":_.credentials="same-origin",_}function d(N){if(N.ep)return;N.ep=!0;const _=x(N);fetch(N.href,_)}})();var ts={exports:{}},Mn={},as={exports:{}},ns={};/**
+import{j as o,Y as td,O as fg,k as dg,u as ad,Z as mg,c as hg,l as gg,g as pg,S as yg,T as vg,n as bg,m as nd,o as Sg,p as Tg,$ as ud,a0 as id,a1 as cd,a2 as xg}from"./ui-vendor-CeCm8EER.js";import{d as Ag,h as Dg,r as E,u as sd,H as Ng,i as Eg,j as kf}from"./react-vendor-DEwriMA6.js";import{N as we,c as Ve,ad as od,u as Bl,M as sl,ae as rd,af as fd,I as us,B as Cn,D as Mg,l as zg,m as Cg,n as Og,o as _g,ag as Rg,ah as jg,ai as Ug,aj as Hg,ak as ql,al as dd,am as ss,an as is,a0 as Lg,a1 as qg,a2 as Bg,a3 as Gg,ao as Yg,ap as Xg,aq as md,ar as wg,as as hd,at as Vg,au as gd,d as Qg,R as Kg,V as Zg,g as En,av as kg,aw as Jg,ax as Fg}from"./feature-graph-C6IuADHZ.js";import{S as Jf,a as Ff,b as Pf,c as $f,e as rt,D as Pg}from"./feature-documents-DLarjU2a.js";import{R as $g}from"./feature-retrieval-P5Qspbob.js";import{i as cs}from"./utils-vendor-BysuhMZA.js";import"./graph-vendor-B-X5JegA.js";import"./mermaid-vendor-CAxUo7Zk.js";import"./markdown-vendor-DmIvJdn7.js";(function(){const y=document.createElement("link").relList;if(y&&y.supports&&y.supports("modulepreload"))return;for(const N of document.querySelectorAll('link[rel="modulepreload"]'))d(N);new MutationObserver(N=>{for(const _ of N)if(_.type==="childList")for(const H of _.addedNodes)H.tagName==="LINK"&&H.rel==="modulepreload"&&d(H)}).observe(document,{childList:!0,subtree:!0});function x(N){const _={};return N.integrity&&(_.integrity=N.integrity),N.referrerPolicy&&(_.referrerPolicy=N.referrerPolicy),N.crossOrigin==="use-credentials"?_.credentials="include":N.crossOrigin==="anonymous"?_.credentials="omit":_.credentials="same-origin",_}function d(N){if(N.ep)return;N.ep=!0;const _=x(N);fetch(N.href,_)}})();var ts={exports:{}},Mn={},as={exports:{}},ns={};/**
  * @license React
  * scheduler.production.js
  *
diff --git a/lightrag/api/webui/index.html b/lightrag/api/webui/index.html
index 8a30cd59..dc486f54 100644
--- a/lightrag/api/webui/index.html
+++ b/lightrag/api/webui/index.html
@@ -8,16 +8,16 @@
     <link rel="icon" type="image/png" href="favicon.png" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>Lightrag</title>
-    <script type="module" crossorigin src="/webui/assets/index-B8PWUG__.js"></script>
+    <script type="module" crossorigin src="/webui/assets/index-DI6XUmEl.js"></script>
     <link rel="modulepreload" crossorigin href="/webui/assets/react-vendor-DEwriMA6.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/ui-vendor-CeCm8EER.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/graph-vendor-B-X5JegA.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/utils-vendor-BysuhMZA.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/feature-graph-C6IuADHZ.js">
-    <link rel="modulepreload" crossorigin href="/webui/assets/feature-documents-Di_Wt0BY.js">
+    <link rel="modulepreload" crossorigin href="/webui/assets/feature-documents-DLarjU2a.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/mermaid-vendor-CAxUo7Zk.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/markdown-vendor-DmIvJdn7.js">
-    <link rel="modulepreload" crossorigin href="/webui/assets/feature-retrieval-DVuOAaIQ.js">
+    <link rel="modulepreload" crossorigin href="/webui/assets/feature-retrieval-P5Qspbob.js">
     <link rel="stylesheet" crossorigin href="/webui/assets/feature-graph-BipNuM18.css">
     <link rel="stylesheet" crossorigin href="/webui/assets/index-CafJWW1u.css">
   </head>

From cb0a0350769823de8f7045dd6bb6586496fa9403 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 27 Aug 2025 11:12:52 +0800
Subject: [PATCH 062/141] Update env.example

---
 env.example | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/env.example b/env.example
index 3ce6d1d9..753a3652 100644
--- a/env.example
+++ b/env.example
@@ -303,7 +303,7 @@ POSTGRES_IVFFLAT_LISTS=100
 NEO4J_URI=neo4j+s://xxxxxxxx.databases.neo4j.io
 NEO4J_USERNAME=neo4j
 NEO4J_PASSWORD='your_password'
-# NEO4J_DATABASE=chunk-entity-relation
+NEO4J_DATABASE=noe4j
 NEO4J_MAX_CONNECTION_POOL_SIZE=100
 NEO4J_CONNECTION_TIMEOUT=30
 NEO4J_CONNECTION_ACQUISITION_TIMEOUT=30

From 194f46f239fe16c0f7789604866158be4cabb6fe Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 27 Aug 2025 11:14:09 +0800
Subject: [PATCH 063/141] Add json_repair dependency to project requirements

---
 pyproject.toml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/pyproject.toml b/pyproject.toml
index 501e8b5a..e850ce2c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,6 +25,7 @@ dependencies = [
     "configparser",
     "dotenv",
     "future",
+    "json_repair",
     "nano-vectordb",
     "networkx",
     "numpy",
@@ -46,6 +47,7 @@ api = [
     "configparser",
     "dotenv",
     "future",
+    "json_repair",
     "nano-vectordb",
     "networkx",
     "numpy",

From ff0a18e08c720f7ac63a36bf6c3f40dd2897d26e Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 27 Aug 2025 12:23:22 +0800
Subject: [PATCH 064/141] Unify SUMMARY_LANGUANGE and ENTITY_TYPES
 implementation method

---
 env.example                     | 11 +++++++----
 lightrag/api/config.py          |  2 +-
 lightrag/api/lightrag_server.py | 10 ++++++++--
 lightrag/constants.py           | 12 ++++++++++--
 lightrag/lightrag.py            |  7 +++++--
 lightrag/operate.py             |  7 +++----
 lightrag/prompt.py              |  1 -
 7 files changed, 34 insertions(+), 16 deletions(-)

diff --git a/env.example b/env.example
index a00b8f88..6cb0dce7 100644
--- a/env.example
+++ b/env.example
@@ -119,9 +119,14 @@ RERANK_BINDING=null
 ########################################
 ### Document processing configuration
 ########################################
-### Language: English, Chinese, French, German ...
-SUMMARY_LANGUAGE=English
 ENABLE_LLM_CACHE_FOR_EXTRACT=true
+
+### Document processing outpu language: English, Chinese, French, German ...
+SUMMARY_LANGUAGE=English
+
+### Entity types that the LLM will attempt to recognize
+# ENTITY_TYPES=["person", "organization", "location", "event", "concept"]
+
 ### Chunk size for document splitting, 500~1500 is recommended
 # CHUNK_SIZE=1200
 # CHUNK_OVERLAP_SIZE=100
@@ -134,8 +139,6 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true
 # SUMMARY_LENGTH_RECOMMENDED_=600
 ### Maximum context size sent to LLM for description summary
 # SUMMARY_CONTEXT_SIZE=12000
-### Customize the entities that the LLM will attempt to recognize
-# ENTITY_TYPES=["person", "organization", "location", "event", "concept"]
 
 ###############################
 ### Concurrency Configuration
diff --git a/lightrag/api/config.py b/lightrag/api/config.py
index 70b855f2..eae2f45b 100644
--- a/lightrag/api/config.py
+++ b/lightrag/api/config.py
@@ -38,7 +38,7 @@ from lightrag.constants import (
     DEFAULT_OLLAMA_MODEL_NAME,
     DEFAULT_OLLAMA_MODEL_TAG,
     DEFAULT_RERANK_BINDING,
-    DEFAULT_ENTITY_TYPES
+    DEFAULT_ENTITY_TYPES,
 )
 
 # use the .env that is inside the current folder
diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 26c99961..a2a4d848 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -499,7 +499,10 @@ def create_app(args):
             rerank_model_func=rerank_model_func,
             max_parallel_insert=args.max_parallel_insert,
             max_graph_nodes=args.max_graph_nodes,
-            addon_params={"language": args.summary_language, "entity_types": args.entity_types},
+            addon_params={
+                "language": args.summary_language,
+                "entity_types": args.entity_types,
+            },
             ollama_server_infos=ollama_server_infos,
         )
     else:  # azure_openai
@@ -526,7 +529,10 @@ def create_app(args):
             rerank_model_func=rerank_model_func,
             max_parallel_insert=args.max_parallel_insert,
             max_graph_nodes=args.max_graph_nodes,
-            addon_params={"language": args.summary_language, "entity_types": args.entity_types},
+            addon_params={
+                "language": args.summary_language,
+                "entity_types": args.entity_types,
+            },
             ollama_server_infos=ollama_server_infos,
         )
 
diff --git a/lightrag/constants.py b/lightrag/constants.py
index d0271be4..4e85325b 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -11,7 +11,7 @@ DEFAULT_WOKERS = 2
 DEFAULT_MAX_GRAPH_NODES = 1000
 
 # Default values for extraction settings
-DEFAULT_SUMMARY_LANGUAGE = "English"  # Default language for summaries
+DEFAULT_SUMMARY_LANGUAGE = "English"  # Default language for document processing
 DEFAULT_MAX_GLEANING = 1
 
 # Number of description fragments to trigger LLM summary
@@ -23,7 +23,15 @@ DEFAULT_SUMMARY_LENGTH_RECOMMENDED = 600
 # Maximum token size sent to LLM for summary
 DEFAULT_SUMMARY_CONTEXT_SIZE = 12000
 # Default entities to extract if ENTITY_TYPES is not specified in .env
-DEFAULT_ENTITY_TYPES = ["organization", "person", "geo", "event", "category"]
+DEFAULT_ENTITY_TYPES = [
+    "organization",
+    "person",
+    "geo",
+    "event",
+    "category",
+    "Equipment",
+    "Location",
+]
 
 # Separator for graph fields
 GRAPH_FIELD_SEP = "<SEP>"
diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index 235345e8..34ff87e6 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -39,7 +39,8 @@ from lightrag.constants import (
     DEFAULT_MAX_ASYNC,
     DEFAULT_MAX_PARALLEL_INSERT,
     DEFAULT_MAX_GRAPH_NODES,
-    DEFAULT_ENTITY_TYPES
+    DEFAULT_ENTITY_TYPES,
+    DEFAULT_SUMMARY_LANGUAGE,
 )
 from lightrag.utils import get_env_value
 
@@ -348,7 +349,9 @@ class LightRAG:
 
     addon_params: dict[str, Any] = field(
         default_factory=lambda: {
-            "language": get_env_value("SUMMARY_LANGUAGE", "English", str),
+            "language": get_env_value(
+                "SUMMARY_LANGUAGE", DEFAULT_SUMMARY_LANGUAGE, str
+            ),
             "entity_types": get_env_value("ENTITY_TYPES", DEFAULT_ENTITY_TYPES, list),
         }
     )
diff --git a/lightrag/operate.py b/lightrag/operate.py
index 76a0b2c1..38771f7b 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -47,7 +47,8 @@ from .constants import (
     DEFAULT_MAX_TOTAL_TOKENS,
     DEFAULT_RELATED_CHUNK_NUMBER,
     DEFAULT_KG_CHUNK_PICK_METHOD,
-    DEFAULT_ENTITY_TYPES
+    DEFAULT_ENTITY_TYPES,
+    DEFAULT_SUMMARY_LANGUAGE,
 )
 from .kg.shared_storage import get_storage_keyed_lock
 import time
@@ -1651,9 +1652,7 @@ async def extract_entities(
 
     ordered_chunks = list(chunks.items())
     # add language and example number params to prompt
-    language = global_config["addon_params"].get(
-        "language", PROMPTS["DEFAULT_LANGUAGE"]
-    )
+    language = global_config["addon_params"].get("language", DEFAULT_SUMMARY_LANGUAGE)
     entity_types = global_config["addon_params"].get(
         "entity_types", DEFAULT_ENTITY_TYPES
     )
diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index 69fb2ef3..f8ea6589 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -4,7 +4,6 @@ from typing import Any
 
 PROMPTS: dict[str, Any] = {}
 
-PROMPTS["DEFAULT_LANGUAGE"] = "English"
 PROMPTS["DEFAULT_TUPLE_DELIMITER"] = "<|>"
 PROMPTS["DEFAULT_RECORD_DELIMITER"] = "##"
 PROMPTS["DEFAULT_COMPLETION_DELIMITER"] = "<|COMPLETE|>"

From 2ccc39de9ad84a49201a1a553925985bcd8312b9 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 27 Aug 2025 12:34:27 +0800
Subject: [PATCH 065/141] Fix language fallback in summarize error

---
 lightrag/operate.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 38771f7b..40b01b54 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -270,7 +270,7 @@ async def _summarize_descriptions(
     use_llm_func = partial(use_llm_func, _priority=8)
 
     language = global_config["addon_params"].get(
-        "language", PROMPTS["DEFAULT_LANGUAGE"]
+        "language", DEFAULT_SUMMARY_LANGUAGE]
     )
 
     summary_length_recommended = global_config["summary_length_recommended"]
@@ -2115,7 +2115,7 @@ async def extract_keywords_only(
     else:
         examples = "\n".join(PROMPTS["keywords_extraction_examples"])
     language = global_config["addon_params"].get(
-        "language", PROMPTS["DEFAULT_LANGUAGE"]
+        "language", DEFAULT_SUMMARY_LANGUAGE
     )
 
     # 3. Process conversation history

From 28e07c89f9eda65d0b7d1b8b9da77b22ca8cbeef Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 27 Aug 2025 12:35:51 +0800
Subject: [PATCH 066/141] Fix linting

---
 lightrag/operate.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 40b01b54..93dc0623 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -270,7 +270,7 @@ async def _summarize_descriptions(
     use_llm_func = partial(use_llm_func, _priority=8)
 
     language = global_config["addon_params"].get(
-        "language", DEFAULT_SUMMARY_LANGUAGE]
+        "language", DEFAULT_SUMMARY_LANGUAGE
     )
 
     summary_length_recommended = global_config["summary_length_recommended"]

From 8a0d06e55749a6a78d2187682b842ff193a8e464 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 27 Aug 2025 12:51:18 +0800
Subject: [PATCH 067/141] Restore default entity types

---
 lightrag/constants.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/lightrag/constants.py b/lightrag/constants.py
index 4e85325b..a7cf5640 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -29,8 +29,6 @@ DEFAULT_ENTITY_TYPES = [
     "geo",
     "event",
     "category",
-    "Equipment",
-    "Location",
 ]
 
 # Separator for graph fields

From 6a2a59222491050537229a578b85b34f513486d1 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 27 Aug 2025 12:51:50 +0800
Subject: [PATCH 068/141] Fix linting

---
 lightrag/operate.py | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 93dc0623..cddf0ddc 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -269,9 +269,7 @@ async def _summarize_descriptions(
     # Apply higher priority (8) to entity/relation summary tasks
     use_llm_func = partial(use_llm_func, _priority=8)
 
-    language = global_config["addon_params"].get(
-        "language", DEFAULT_SUMMARY_LANGUAGE
-    )
+    language = global_config["addon_params"].get("language", DEFAULT_SUMMARY_LANGUAGE)
 
     summary_length_recommended = global_config["summary_length_recommended"]
 
@@ -2114,9 +2112,7 @@ async def extract_keywords_only(
         )
     else:
         examples = "\n".join(PROMPTS["keywords_extraction_examples"])
-    language = global_config["addon_params"].get(
-        "language", DEFAULT_SUMMARY_LANGUAGE
-    )
+    language = global_config["addon_params"].get("language", DEFAULT_SUMMARY_LANGUAGE)
 
     # 3. Process conversation history
     # history_context = ""

From 4dfbe5e2dbc82894bbe5fbccb92e8ebef92e8643 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 27 Aug 2025 15:14:23 +0800
Subject: [PATCH 069/141] Rename workflow and remove latest tag from Docker
 build
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Rename docker-build-main to manual
• Remove latest tag from metadata
---
 .../{docker-build-main.yml => docker-build-manual.yml}          | 2 --
 1 file changed, 2 deletions(-)
 rename .github/workflows/{docker-build-main.yml => docker-build-manual.yml} (95%)

diff --git a/.github/workflows/docker-build-main.yml b/.github/workflows/docker-build-manual.yml
similarity index 95%
rename from .github/workflows/docker-build-main.yml
rename to .github/workflows/docker-build-manual.yml
index 6e51c2b8..ec2402f4 100644
--- a/.github/workflows/docker-build-main.yml
+++ b/.github/workflows/docker-build-manual.yml
@@ -47,7 +47,6 @@ jobs:
           images: ghcr.io/${{ github.repository }}
           tags: |
             type=raw,value=${{ steps.get_tag.outputs.tag }}
-            type=raw,value=latest
 
       - name: Build and push Docker image
         uses: docker/build-push-action@v5
@@ -65,5 +64,4 @@ jobs:
           echo "Docker image built and pushed successfully!"
           echo "Image tags:"
           echo "  - ghcr.io/${{ github.repository }}:${{ steps.get_tag.outputs.tag }}"
-          echo "  - ghcr.io/${{ github.repository }}:latest"
           echo "Latest Git tag used: ${{ steps.get_tag.outputs.tag }}"

From 99e28e815b496634b51c9fa7ec2d2ca1f899b6c0 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 27 Aug 2025 23:52:39 +0800
Subject: [PATCH 070/141] fix: prevent document processing failures from UTF-8
 surrogate characters

- Change sanitize_text_for_encoding to fail-fast instead of returning error placeholders
- Add strict UTF-8 cleaning pipeline to entity/relationship extraction
- Skip problematic entities/relationships instead of corrupting data

Fixes document processing crashes when encountering surrogate characters (U+D800-U+DFFF)
---
 lightrag/operate.py | 201 ++++++++++++++++++++++++++------------------
 lightrag/utils.py   |  44 ++++------
 2 files changed, 135 insertions(+), 110 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index cddf0ddc..91252e00 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -31,6 +31,7 @@ from .utils import (
     pick_by_vector_similarity,
     process_chunks_unified,
     build_file_path,
+    sanitize_text_for_encoding,
 )
 from .base import (
     BaseGraphStorage,
@@ -318,50 +319,62 @@ async def _handle_single_entity_extraction(
     if len(record_attributes) < 4 or '"entity"' not in record_attributes[0]:
         return None
 
-    # Clean and validate entity name
-    entity_name = clean_str(record_attributes[1]).strip()
-    if not entity_name:
-        logger.warning(
-            f"Entity extraction error: empty entity name in: {record_attributes}"
+    try:
+        # Step 1: Strict UTF-8 encoding sanitization (fail-fast approach)
+        entity_name = sanitize_text_for_encoding(record_attributes[1])
+
+        # Step 2: HTML and control character cleaning
+        entity_name = clean_str(entity_name).strip()
+
+        # Step 3: Business logic normalization
+        entity_name = normalize_extracted_info(entity_name, is_entity=True)
+
+        # Validate entity name after all cleaning steps
+        if not entity_name or not entity_name.strip():
+            logger.warning(
+                f"Entity extraction error: entity name became empty after cleaning. Original: '{record_attributes[1]}'"
+            )
+            return None
+
+        # Process entity type with same cleaning pipeline
+        entity_type = sanitize_text_for_encoding(record_attributes[2])
+        entity_type = clean_str(entity_type).strip('"')
+        if not entity_type.strip() or entity_type.startswith('("'):
+            logger.warning(
+                f"Entity extraction error: invalid entity type in: {record_attributes}"
+            )
+            return None
+
+        # Process entity description with same cleaning pipeline
+        entity_description = sanitize_text_for_encoding(record_attributes[3])
+        entity_description = clean_str(entity_description)
+        entity_description = normalize_extracted_info(entity_description)
+
+        if not entity_description.strip():
+            logger.warning(
+                f"Entity extraction error: empty description for entity '{entity_name}' of type '{entity_type}'"
+            )
+            return None
+
+        return dict(
+            entity_name=entity_name,
+            entity_type=entity_type,
+            description=entity_description,
+            source_id=chunk_key,
+            file_path=file_path,
+        )
+
+    except ValueError as e:
+        logger.error(
+            f"Entity extraction failed due to encoding issues in chunk {chunk_key}: {e}"
         )
         return None
-
-    # Normalize entity name
-    entity_name = normalize_extracted_info(entity_name, is_entity=True)
-
-    # Check if entity name became empty after normalization
-    if not entity_name or not entity_name.strip():
-        logger.warning(
-            f"Entity extraction error: entity name became empty after normalization. Original: '{record_attributes[1]}'"
+    except Exception as e:
+        logger.error(
+            f"Entity extraction failed with unexpected error in chunk {chunk_key}: {e}"
         )
         return None
 
-    # Clean and validate entity type
-    entity_type = clean_str(record_attributes[2]).strip('"')
-    if not entity_type.strip() or entity_type.startswith('("'):
-        logger.warning(
-            f"Entity extraction error: invalid entity type in: {record_attributes}"
-        )
-        return None
-
-    # Clean and validate description
-    entity_description = clean_str(record_attributes[3])
-    entity_description = normalize_extracted_info(entity_description)
-
-    if not entity_description.strip():
-        logger.warning(
-            f"Entity extraction error: empty description for entity '{entity_name}' of type '{entity_type}'"
-        )
-        return None
-
-    return dict(
-        entity_name=entity_name,
-        entity_type=entity_type,
-        description=entity_description,
-        source_id=chunk_key,
-        file_path=file_path,
-    )
-
 
 async def _handle_single_relationship_extraction(
     record_attributes: list[str],
@@ -370,57 +383,79 @@ async def _handle_single_relationship_extraction(
 ):
     if len(record_attributes) < 5 or '"relationship"' not in record_attributes[0]:
         return None
-    # add this record as edge
-    source = clean_str(record_attributes[1])
-    target = clean_str(record_attributes[2])
 
-    # Normalize source and target entity names
-    source = normalize_extracted_info(source, is_entity=True)
-    target = normalize_extracted_info(target, is_entity=True)
+    try:
+        # Process source and target entities with strict cleaning pipeline
+        # Step 1: Strict UTF-8 encoding sanitization (fail-fast approach)
+        source = sanitize_text_for_encoding(record_attributes[1])
+        # Step 2: HTML and control character cleaning
+        source = clean_str(source)
+        # Step 3: Business logic normalization
+        source = normalize_extracted_info(source, is_entity=True)
 
-    # Check if source or target became empty after normalization
-    if not source or not source.strip():
-        logger.warning(
-            f"Relationship extraction error: source entity became empty after normalization. Original: '{record_attributes[1]}'"
+        # Same pipeline for target entity
+        target = sanitize_text_for_encoding(record_attributes[2])
+        target = clean_str(target)
+        target = normalize_extracted_info(target, is_entity=True)
+
+        # Validate entity names after all cleaning steps
+        if not source or not source.strip():
+            logger.warning(
+                f"Relationship extraction error: source entity became empty after cleaning. Original: '{record_attributes[1]}'"
+            )
+            return None
+
+        if not target or not target.strip():
+            logger.warning(
+                f"Relationship extraction error: target entity became empty after cleaning. Original: '{record_attributes[2]}'"
+            )
+            return None
+
+        if source == target:
+            logger.debug(
+                f"Relationship source and target are the same in: {record_attributes}"
+            )
+            return None
+
+        # Process relationship description with same cleaning pipeline
+        edge_description = sanitize_text_for_encoding(record_attributes[3])
+        edge_description = clean_str(edge_description)
+        edge_description = normalize_extracted_info(edge_description)
+
+        # Process keywords with same cleaning pipeline
+        edge_keywords = sanitize_text_for_encoding(record_attributes[4])
+        edge_keywords = clean_str(edge_keywords)
+        edge_keywords = normalize_extracted_info(edge_keywords, is_entity=True)
+        edge_keywords = edge_keywords.replace("，", ",")
+
+        edge_source_id = chunk_key
+        weight = (
+            float(record_attributes[-1].strip('"').strip("'"))
+            if is_float_regex(record_attributes[-1].strip('"').strip("'"))
+            else 1.0
+        )
+
+        return dict(
+            src_id=source,
+            tgt_id=target,
+            weight=weight,
+            description=edge_description,
+            keywords=edge_keywords,
+            source_id=edge_source_id,
+            file_path=file_path,
+        )
+
+    except ValueError as e:
+        logger.error(
+            f"Relationship extraction failed due to encoding issues in chunk {chunk_key}: {e}"
         )
         return None
-
-    if not target or not target.strip():
-        logger.warning(
-            f"Relationship extraction error: target entity became empty after normalization. Original: '{record_attributes[2]}'"
+    except Exception as e:
+        logger.error(
+            f"Relationship extraction failed with unexpected error in chunk {chunk_key}: {e}"
         )
         return None
 
-    if source == target:
-        logger.debug(
-            f"Relationship source and target are the same in: {record_attributes}"
-        )
-        return None
-
-    edge_description = clean_str(record_attributes[3])
-    edge_description = normalize_extracted_info(edge_description)
-
-    edge_keywords = normalize_extracted_info(
-        clean_str(record_attributes[4]), is_entity=True
-    )
-    edge_keywords = edge_keywords.replace("，", ",")
-
-    edge_source_id = chunk_key
-    weight = (
-        float(record_attributes[-1].strip('"').strip("'"))
-        if is_float_regex(record_attributes[-1].strip('"').strip("'"))
-        else 1.0
-    )
-    return dict(
-        src_id=source,
-        tgt_id=target,
-        weight=weight,
-        description=edge_description,
-        keywords=edge_keywords,
-        source_id=edge_source_id,
-        file_path=file_path,
-    )
-
 
 async def _rebuild_knowledge_from_chunks(
     entities_to_rebuild: dict[str, set[str]],
diff --git a/lightrag/utils.py b/lightrag/utils.py
index 2d3d485b..cb03c537 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -1577,7 +1577,7 @@ def sanitize_text_for_encoding(text: str, replacement_char: str = "") -> str:
     """Sanitize text to ensure safe UTF-8 encoding by removing or replacing problematic characters.
 
     This function handles:
-    - Surrogate characters (the main cause of the encoding error)
+    - Surrogate characters (the main cause of encoding errors)
     - Other invalid Unicode sequences
     - Control characters that might cause issues
     - Whitespace trimming
@@ -1588,6 +1588,9 @@ def sanitize_text_for_encoding(text: str, replacement_char: str = "") -> str:
 
     Returns:
         Sanitized text that can be safely encoded as UTF-8
+
+    Raises:
+        ValueError: When text contains uncleanable encoding issues that cannot be safely processed
     """
     if not isinstance(text, str):
         return str(text)
@@ -1624,7 +1627,7 @@ def sanitize_text_for_encoding(text: str, replacement_char: str = "") -> str:
             else:
                 sanitized += char
 
-        # Additional cleanup: remove null bytes  and other control characters that might cause issues
+        # Additional cleanup: remove null bytes and other control characters that might cause issues
         # (but preserve common whitespace like \t, \n, \r)
         sanitized = re.sub(
             r"[\x00-\x08\x0B\x0C\x0E-\x1F\x7F]", replacement_char, sanitized
@@ -1636,34 +1639,21 @@ def sanitize_text_for_encoding(text: str, replacement_char: str = "") -> str:
         return sanitized
 
     except UnicodeEncodeError as e:
-        logger.warning(
-            f"Text sanitization: UnicodeEncodeError encountered, applying aggressive cleaning: {str(e)[:100]}"
-        )
-
-        # Aggressive fallback: encode with error handling
-        try:
-            # Use 'replace' error handling to substitute problematic characters
-            safe_bytes = text.encode("utf-8", errors="replace")
-            sanitized = safe_bytes.decode("utf-8")
-
-            # Additional cleanup
-            sanitized = re.sub(
-                r"[\x00-\x08\x0B\x0C\x0E-\x1F\x7F]", replacement_char, sanitized
-            )
-
-            return sanitized
-
-        except Exception as fallback_error:
-            logger.error(
-                f"Text sanitization: Aggressive fallback failed: {str(fallback_error)}"
-            )
-            # Last resort: return a safe placeholder
-            return f"[TEXT_ENCODING_ERROR: {len(text)} characters]"
+        # Critical change: Don't return placeholder, raise exception for caller to handle
+        error_msg = f"Text contains uncleanable UTF-8 encoding issues: {str(e)[:100]}"
+        logger.error(f"Text sanitization failed: {error_msg}")
+        raise ValueError(error_msg) from e
 
     except Exception as e:
         logger.error(f"Text sanitization: Unexpected error: {str(e)}")
-        # Return original text if no encoding issues detected
-        return text
+        # For other exceptions, if no encoding issues detected, return original text
+        try:
+            text.encode("utf-8")
+            return text
+        except UnicodeEncodeError:
+            raise ValueError(
+                f"Text sanitization failed with unexpected error: {str(e)}"
+            ) from e
 
 
 def check_storage_env_vars(storage_name: str) -> None:

From 1cd27dc0480c3a0b7b351ca3e12e9315c86b4163 Mon Sep 17 00:00:00 2001
From: Sandmeyer <sandm_x@outlook.com>
Date: Thu, 28 Aug 2025 20:23:51 +0800
Subject: [PATCH 071/141] docs(config): fix typo in .env comments

---
 env.example | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/env.example b/env.example
index 570d6a34..abb73112 100644
--- a/env.example
+++ b/env.example
@@ -121,7 +121,7 @@ RERANK_BINDING=null
 ########################################
 ENABLE_LLM_CACHE_FOR_EXTRACT=true
 
-### Document processing outpu language: English, Chinese, French, German ...
+### Document processing output language: English, Chinese, French, German ...
 SUMMARY_LANGUAGE=English
 
 ### Entity types that the LLM will attempt to recognize

From ac2db35160f5331ea4766d05a3a6e26d91fe4fb6 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 29 Aug 2025 10:18:12 +0800
Subject: [PATCH 072/141] Update env.example

---
 env.example | 1 -
 1 file changed, 1 deletion(-)

diff --git a/env.example b/env.example
index abb73112..c5cb4d28 100644
--- a/env.example
+++ b/env.example
@@ -158,7 +158,6 @@ MAX_PARALLEL_INSERT=2
 ###########################################################
 ### LLM request timeout setting for all llm (set to TIMEOUT if not specified, 0 means no timeout for Ollma)
 # LLM_TIMEOUT=150
-### Some models like o1-mini require temperature to be set to 1, some LLM can fall into output loops with low temperature
 
 LLM_BINDING=openai
 LLM_MODEL=gpt-4o

From 925e631a9a04f955643b06ee84be4231c2143733 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 29 Aug 2025 13:50:35 +0800
Subject: [PATCH 073/141] refac: Add robust time out handling for LLM request

---
 env.example                     |   6 +-
 lightrag/api/lightrag_server.py |  11 +-
 lightrag/constants.py           |   8 +-
 lightrag/lightrag.py            |  19 +-
 lightrag/utils.py               | 399 +++++++++++++++++++++++---------
 5 files changed, 331 insertions(+), 112 deletions(-)

diff --git a/env.example b/env.example
index c5cb4d28..35a1e5fa 100644
--- a/env.example
+++ b/env.example
@@ -156,8 +156,8 @@ MAX_PARALLEL_INSERT=2
 ### LLM Configuration
 ### LLM_BINDING type: openai, ollama, lollms, azure_openai, aws_bedrock
 ###########################################################
-### LLM request timeout setting for all llm (set to TIMEOUT if not specified, 0 means no timeout for Ollma)
-# LLM_TIMEOUT=150
+### LLM request timeout setting for all llm (0 means no timeout for Ollma)
+# LLM_TIMEOUT=180
 
 LLM_BINDING=openai
 LLM_MODEL=gpt-4o
@@ -206,7 +206,7 @@ OLLAMA_LLM_NUM_CTX=32768
 ### Embedding Configuration (Should not be changed after the first file processed)
 ### EMBEDDING_BINDING: ollama, openai, azure_openai, jina, lollms, aws_bedrock
 ####################################################################################
-### see also env.ollama-binding-options.example for fine tuning ollama
+# EMBEDDING_TIMEOUT=30
 EMBEDDING_BINDING=ollama
 EMBEDDING_MODEL=bge-m3:latest
 EMBEDDING_DIM=1024
diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index a2a4d848..41ede089 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -39,6 +39,8 @@ from lightrag.constants import (
     DEFAULT_LOG_MAX_BYTES,
     DEFAULT_LOG_BACKUP_COUNT,
     DEFAULT_LOG_FILENAME,
+    DEFAULT_LLM_TIMEOUT,
+    DEFAULT_EMBEDDING_TIMEOUT,
 )
 from lightrag.api.routers.document_routes import (
     DocumentManager,
@@ -256,7 +258,10 @@ def create_app(args):
     if args.embedding_binding == "jina":
         from lightrag.llm.jina import jina_embed
 
-    llm_timeout = get_env_value("LLM_TIMEOUT", args.timeout, int)
+    llm_timeout = get_env_value("LLM_TIMEOUT", DEFAULT_LLM_TIMEOUT, int)
+    embedding_timeout = get_env_value(
+        "EMBEDDING_TIMEOUT", DEFAULT_EMBEDDING_TIMEOUT, int
+    )
 
     async def openai_alike_model_complete(
         prompt,
@@ -487,6 +492,8 @@ def create_app(args):
                 else {}
             ),
             embedding_func=embedding_func,
+            default_llm_timeout=llm_timeout,
+            default_embedding_timeout=embedding_timeout,
             kv_storage=args.kv_storage,
             graph_storage=args.graph_storage,
             vector_storage=args.vector_storage,
@@ -517,6 +524,8 @@ def create_app(args):
             summary_max_tokens=args.summary_max_tokens,
             summary_context_size=args.summary_context_size,
             embedding_func=embedding_func,
+            default_llm_timeout=llm_timeout,
+            default_embedding_timeout=embedding_timeout,
             kv_storage=args.kv_storage,
             graph_storage=args.graph_storage,
             vector_storage=args.vector_storage,
diff --git a/lightrag/constants.py b/lightrag/constants.py
index a7cf5640..d78d869c 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -64,8 +64,12 @@ DEFAULT_MAX_PARALLEL_INSERT = 2  # Default maximum parallel insert operations
 DEFAULT_EMBEDDING_FUNC_MAX_ASYNC = 8  # Default max async for embedding functions
 DEFAULT_EMBEDDING_BATCH_NUM = 10  # Default batch size for embedding computations
 
-# gunicorn worker timeout(as default LLM request timeout if LLM_TIMEOUT is not set)
-DEFAULT_TIMEOUT = 150
+# Gunicorn worker timeout
+DEFAULT_TIMEOUT = 210
+
+# Default llm and embedding timeout
+DEFAULT_LLM_TIMEOUT = 180
+DEFAULT_EMBEDDING_TIMEOUT = 30
 
 # Logging configuration defaults
 DEFAULT_LOG_MAX_BYTES = 10485760  # Default 10MB
diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index 34ff87e6..23e6f575 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -41,6 +41,8 @@ from lightrag.constants import (
     DEFAULT_MAX_GRAPH_NODES,
     DEFAULT_ENTITY_TYPES,
     DEFAULT_SUMMARY_LANGUAGE,
+    DEFAULT_LLM_TIMEOUT,
+    DEFAULT_EMBEDDING_TIMEOUT,
 )
 from lightrag.utils import get_env_value
 
@@ -277,6 +279,10 @@ class LightRAG:
     - use_llm_check: If True, validates cached embeddings using an LLM.
     """
 
+    default_embedding_timeout: int = field(
+        default=int(os.getenv("EMBEDDING_TIMEOUT", DEFAULT_EMBEDDING_TIMEOUT))
+    )
+
     # LLM Configuration
     # ---
 
@@ -311,6 +317,10 @@ class LightRAG:
     llm_model_kwargs: dict[str, Any] = field(default_factory=dict)
     """Additional keyword arguments passed to the LLM model function."""
 
+    default_llm_timeout: int = field(
+        default=int(os.getenv("LLM_TIMEOUT", DEFAULT_LLM_TIMEOUT))
+    )
+
     # Rerank Configuration
     # ---
 
@@ -457,7 +467,8 @@ class LightRAG:
 
         # Init Embedding
         self.embedding_func = priority_limit_async_func_call(
-            self.embedding_func_max_async
+            self.embedding_func_max_async,
+            llm_timeout=self.default_embedding_timeout,
         )(self.embedding_func)
 
         # Initialize all storages
@@ -550,7 +561,11 @@ class LightRAG:
         # Directly use llm_response_cache, don't create a new object
         hashing_kv = self.llm_response_cache
 
-        self.llm_model_func = priority_limit_async_func_call(self.llm_model_max_async)(
+        # Get timeout from LLM model kwargs for dynamic timeout calculation
+        self.llm_model_func = priority_limit_async_func_call(
+            self.llm_model_max_async,
+            llm_timeout=self.default_llm_timeout,
+        )(
             partial(
                 self.llm_model_func,  # type: ignore
                 hashing_kv=hashing_kv,
diff --git a/lightrag/utils.py b/lightrag/utils.py
index cb03c537..cd67e9f3 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -254,6 +254,18 @@ class UnlimitedSemaphore:
         pass
 
 
+@dataclass
+class TaskState:
+    """Task state tracking for priority queue management"""
+
+    future: asyncio.Future
+    start_time: float
+    execution_start_time: float = None
+    worker_started: bool = False
+    cancellation_requested: bool = False
+    cleanup_done: bool = False
+
+
 @dataclass
 class EmbeddingFunc:
     embedding_dim: int
@@ -323,20 +335,58 @@ def parse_cache_key(cache_key: str) -> tuple[str, str, str] | None:
     return None
 
 
-# Custom exception class
+# Custom exception classes
 class QueueFullError(Exception):
     """Raised when the queue is full and the wait times out"""
 
     pass
 
 
-def priority_limit_async_func_call(max_size: int, max_queue_size: int = 1000):
+class WorkerTimeoutError(Exception):
+    """Worker-level timeout exception with specific timeout information"""
+
+    def __init__(self, timeout_value: float, timeout_type: str = "execution"):
+        self.timeout_value = timeout_value
+        self.timeout_type = timeout_type
+        super().__init__(f"Worker {timeout_type} timeout after {timeout_value}s")
+
+
+class HealthCheckTimeoutError(Exception):
+    """Health Check-level timeout exception"""
+
+    def __init__(self, timeout_value: float, execution_duration: float):
+        self.timeout_value = timeout_value
+        self.execution_duration = execution_duration
+        super().__init__(
+            f"Task forcefully terminated due to execution timeout (>{timeout_value}s, actual: {execution_duration:.1f}s)"
+        )
+
+
+def priority_limit_async_func_call(
+    max_size: int,
+    llm_timeout: float = None,
+    max_execution_timeout: float = None,
+    max_task_duration: float = None,
+    max_queue_size: int = 1000,
+    cleanup_timeout: float = 2.0,
+):
     """
-    Enhanced priority-limited asynchronous function call decorator
+    Enhanced priority-limited asynchronous function call decorator with robust timeout handling
+
+    This decorator provides a comprehensive solution for managing concurrent LLM requests with:
+    - Multi-layer timeout protection (LLM -> Worker -> Health Check -> User)
+    - Task state tracking to prevent race conditions
+    - Enhanced health check system with stuck task detection
+    - Proper resource cleanup and error recovery
 
     Args:
         max_size: Maximum number of concurrent calls
         max_queue_size: Maximum queue capacity to prevent memory overflow
+        llm_timeout: LLM provider timeout (from global config), used to calculate other timeouts
+        max_execution_timeout: Maximum time for worker to execute function (defaults to llm_timeout + 30s)
+        max_task_duration: Maximum time before health check intervenes (defaults to llm_timeout + 60s)
+        cleanup_timeout: Maximum time to wait for cleanup operations (defaults to 2.0s)
+
     Returns:
         Decorator function
     """
@@ -345,81 +395,173 @@ def priority_limit_async_func_call(max_size: int, max_queue_size: int = 1000):
         # Ensure func is callable
         if not callable(func):
             raise TypeError(f"Expected a callable object, got {type(func)}")
+
+        # Calculate timeout hierarchy if llm_timeout is provided (Dynamic Timeout Calculation)
+        if llm_timeout is not None:
+            nonlocal max_execution_timeout, max_task_duration
+            if max_execution_timeout is None:
+                max_execution_timeout = (
+                    llm_timeout + 30
+                )  # LLM timeout + 30s buffer for network delays
+            if max_task_duration is None:
+                max_task_duration = (
+                    llm_timeout + 60
+                )  # LLM timeout + 1min buffer for execution phase
+
         queue = asyncio.PriorityQueue(maxsize=max_queue_size)
         tasks = set()
         initialization_lock = asyncio.Lock()
         counter = 0
         shutdown_event = asyncio.Event()
-        initialized = False  # Global initialization flag
+        initialized = False
         worker_health_check_task = None
 
-        # Track active future objects for cleanup
+        # Enhanced task state management
+        task_states = {}  # task_id -> TaskState
+        task_states_lock = asyncio.Lock()
         active_futures = weakref.WeakSet()
-        reinit_count = 0  # Reinitialization counter to track system health
+        reinit_count = 0
 
-        # Worker function to process tasks in the queue
         async def worker():
-            """Worker that processes tasks in the priority queue"""
+            """Enhanced worker that processes tasks with proper timeout and state management"""
             try:
                 while not shutdown_event.is_set():
                     try:
-                        # Use timeout to get tasks, allowing periodic checking of shutdown signal
+                        # Get task from queue with timeout for shutdown checking
                         try:
                             (
                                 priority,
                                 count,
-                                future,
+                                task_id,
                                 args,
                                 kwargs,
                             ) = await asyncio.wait_for(queue.get(), timeout=1.0)
                         except asyncio.TimeoutError:
-                            # Timeout is just to check shutdown signal, continue to next iteration
                             continue
 
-                        # If future is cancelled, skip execution
-                        if future.cancelled():
+                        # Get task state and mark worker as started
+                        async with task_states_lock:
+                            if task_id not in task_states:
+                                queue.task_done()
+                                continue
+                            task_state = task_states[task_id]
+                            task_state.worker_started = True
+                            # Record execution start time when worker actually begins processing
+                            task_state.execution_start_time = (
+                                asyncio.get_event_loop().time()
+                            )
+
+                        # Check if task was cancelled before worker started
+                        if (
+                            task_state.cancellation_requested
+                            or task_state.future.cancelled()
+                        ):
+                            async with task_states_lock:
+                                task_states.pop(task_id, None)
                             queue.task_done()
                             continue
 
                         try:
-                            # Execute function
-                            result = await func(*args, **kwargs)
-                            # If future is not done, set the result
-                            if not future.done():
-                                future.set_result(result)
-                        except asyncio.CancelledError:
-                            if not future.done():
-                                future.cancel()
-                            logger.debug("limit_async: Task cancelled during execution")
-                        except Exception as e:
-                            logger.error(
-                                f"limit_async: Error in decorated function: {str(e)}"
+                            # Execute function with timeout protection
+                            if max_execution_timeout is not None:
+                                result = await asyncio.wait_for(
+                                    func(*args, **kwargs), timeout=max_execution_timeout
+                                )
+                            else:
+                                result = await func(*args, **kwargs)
+
+                            # Set result if future is still valid
+                            if not task_state.future.done():
+                                task_state.future.set_result(result)
+
+                        except asyncio.TimeoutError:
+                            # Worker-level timeout (max_execution_timeout exceeded)
+                            logger.warning(
+                                f"limit_async: Worker timeout for task {task_id} after {max_execution_timeout}s"
                             )
-                            if not future.done():
-                                future.set_exception(e)
+                            if not task_state.future.done():
+                                task_state.future.set_exception(
+                                    WorkerTimeoutError(
+                                        max_execution_timeout, "execution"
+                                    )
+                                )
+                        except asyncio.CancelledError:
+                            # Task was cancelled during execution
+                            if not task_state.future.done():
+                                task_state.future.cancel()
+                            logger.debug(
+                                f"limit_async: Task {task_id} cancelled during execution"
+                            )
+                        except Exception as e:
+                            # Function execution error
+                            logger.error(
+                                f"limit_async: Error in decorated function for task {task_id}: {str(e)}"
+                            )
+                            if not task_state.future.done():
+                                task_state.future.set_exception(e)
                         finally:
+                            # Clean up task state
+                            async with task_states_lock:
+                                task_states.pop(task_id, None)
                             queue.task_done()
+
                     except Exception as e:
-                        # Catch all exceptions in worker loop to prevent worker termination
+                        # Critical error in worker loop
                         logger.error(f"limit_async: Critical error in worker: {str(e)}")
-                        await asyncio.sleep(0.1)  # Prevent high CPU usage
+                        await asyncio.sleep(0.1)
             finally:
                 logger.debug("limit_async: Worker exiting")
 
-        async def health_check():
-            """Periodically check worker health status and recover"""
+        async def enhanced_health_check():
+            """Enhanced health check with stuck task detection and recovery"""
             nonlocal initialized
             try:
                 while not shutdown_event.is_set():
                     await asyncio.sleep(5)  # Check every 5 seconds
 
-                    # No longer acquire lock, directly operate on task set
-                    # Use a copy of the task set to avoid concurrent modification
+                    current_time = asyncio.get_event_loop().time()
+
+                    # Detect and handle stuck tasks based on execution start time
+                    if max_task_duration is not None:
+                        stuck_tasks = []
+                        async with task_states_lock:
+                            for task_id, task_state in list(task_states.items()):
+                                # Only check tasks that have started execution
+                                if (
+                                    task_state.worker_started
+                                    and task_state.execution_start_time is not None
+                                    and current_time - task_state.execution_start_time
+                                    > max_task_duration
+                                ):
+                                    stuck_tasks.append(
+                                        (
+                                            task_id,
+                                            current_time
+                                            - task_state.execution_start_time,
+                                        )
+                                    )
+
+                        # Force cleanup of stuck tasks
+                        for task_id, execution_duration in stuck_tasks:
+                            logger.warning(
+                                f"limit_async: Detected stuck task {task_id} (execution time: {execution_duration:.1f}s), forcing cleanup"
+                            )
+                            async with task_states_lock:
+                                if task_id in task_states:
+                                    task_state = task_states[task_id]
+                                    if not task_state.future.done():
+                                        task_state.future.set_exception(
+                                            HealthCheckTimeoutError(
+                                                max_task_duration, execution_duration
+                                            )
+                                        )
+                                    task_states.pop(task_id, None)
+
+                    # Worker recovery logic
                     current_tasks = set(tasks)
                     done_tasks = {t for t in current_tasks if t.done()}
                     tasks.difference_update(done_tasks)
 
-                    # Calculate active tasks count
                     active_tasks_count = len(tasks)
                     workers_needed = max_size - active_tasks_count
 
@@ -432,21 +574,16 @@ def priority_limit_async_func_call(max_size: int, max_queue_size: int = 1000):
                             task = asyncio.create_task(worker())
                             new_tasks.add(task)
                             task.add_done_callback(tasks.discard)
-                        # Update task set in one operation
                         tasks.update(new_tasks)
+
             except Exception as e:
-                logger.error(f"limit_async: Error in health check: {str(e)}")
+                logger.error(f"limit_async: Error in enhanced health check: {str(e)}")
             finally:
-                logger.debug("limit_async: Health check task exiting")
+                logger.debug("limit_async: Enhanced health check task exiting")
                 initialized = False
 
         async def ensure_workers():
-            """Ensure worker threads and health check system are available
-
-            This function checks if the worker system is already initialized.
-            If not, it performs a one-time initialization of all worker threads
-            and starts the health check system.
-            """
+            """Ensure worker system is initialized with enhanced error handling"""
             nonlocal initialized, worker_health_check_task, tasks, reinit_count
 
             if initialized:
@@ -456,45 +593,56 @@ def priority_limit_async_func_call(max_size: int, max_queue_size: int = 1000):
                 if initialized:
                     return
 
-                # Increment reinitialization counter if this is not the first initialization
                 if reinit_count > 0:
                     reinit_count += 1
                     logger.warning(
-                        f"limit_async: Reinitializing needed (count: {reinit_count})"
+                        f"limit_async: Reinitializing system (count: {reinit_count})"
                     )
                 else:
-                    reinit_count = 1  # First initialization
+                    reinit_count = 1
 
-                # Check for completed tasks and remove them from the task set
+                # Clean up completed tasks
                 current_tasks = set(tasks)
                 done_tasks = {t for t in current_tasks if t.done()}
                 tasks.difference_update(done_tasks)
 
-                # Log active tasks count during reinitialization
                 active_tasks_count = len(tasks)
                 if active_tasks_count > 0 and reinit_count > 1:
                     logger.warning(
                         f"limit_async: {active_tasks_count} tasks still running during reinitialization"
                     )
 
-                # Create initial worker tasks, only adding the number needed
+                # Create worker tasks
                 workers_needed = max_size - active_tasks_count
                 for _ in range(workers_needed):
                     task = asyncio.create_task(worker())
                     tasks.add(task)
                     task.add_done_callback(tasks.discard)
 
-                # Start health check
-                worker_health_check_task = asyncio.create_task(health_check())
+                # Start enhanced health check
+                worker_health_check_task = asyncio.create_task(enhanced_health_check())
 
                 initialized = True
-                logger.info(f"limit_async: {workers_needed} new workers initialized")
+                # Log dynamic timeout configuration
+                timeout_info = []
+                if llm_timeout is not None:
+                    timeout_info.append(f"LLM: {llm_timeout}s")
+                if max_execution_timeout is not None:
+                    timeout_info.append(f"Execution: {max_execution_timeout}s")
+                if max_task_duration is not None:
+                    timeout_info.append(f"Health Check: {max_task_duration}s")
+
+                timeout_str = (
+                    f" (Timeouts: {', '.join(timeout_info)})" if timeout_info else ""
+                )
+                logger.info(
+                    f"limit_async: {workers_needed} new workers initialized with dynamic timeout handling{timeout_str}"
+                )
 
         async def shutdown():
-            """Gracefully shut down all workers and the queue"""
+            """Gracefully shut down all workers and cleanup resources"""
             logger.info("limit_async: Shutting down priority queue workers")
 
-            # Set the shutdown event
             shutdown_event.set()
 
             # Cancel all active futures
@@ -502,7 +650,14 @@ def priority_limit_async_func_call(max_size: int, max_queue_size: int = 1000):
                 if not future.done():
                     future.cancel()
 
-            # Wait for the queue to empty
+            # Cancel all pending tasks
+            async with task_states_lock:
+                for task_id, task_state in list(task_states.items()):
+                    if not task_state.future.done():
+                        task_state.future.cancel()
+                task_states.clear()
+
+            # Wait for queue to empty with timeout
             try:
                 await asyncio.wait_for(queue.join(), timeout=5.0)
             except asyncio.TimeoutError:
@@ -510,7 +665,7 @@ def priority_limit_async_func_call(max_size: int, max_queue_size: int = 1000):
                     "limit_async: Timeout waiting for queue to empty during shutdown"
                 )
 
-            # Cancel all worker tasks
+            # Cancel worker tasks
             for task in list(tasks):
                 if not task.done():
                     task.cancel()
@@ -519,7 +674,7 @@ def priority_limit_async_func_call(max_size: int, max_queue_size: int = 1000):
             if tasks:
                 await asyncio.gather(*tasks, return_exceptions=True)
 
-            # Cancel the health check task
+            # Cancel health check task
             if worker_health_check_task and not worker_health_check_task.done():
                 worker_health_check_task.cancel()
                 try:
@@ -534,77 +689,113 @@ def priority_limit_async_func_call(max_size: int, max_queue_size: int = 1000):
             *args, _priority=10, _timeout=None, _queue_timeout=None, **kwargs
         ):
             """
-            Execute the function with priority-based concurrency control
+            Execute function with enhanced priority-based concurrency control and timeout handling
+
             Args:
                 *args: Positional arguments passed to the function
                 _priority: Call priority (lower values have higher priority)
-                _timeout: Maximum time to wait for function completion (in seconds)
+                _timeout: Maximum time to wait for completion (in seconds, none means determinded by max_execution_timeout of the queue)
                 _queue_timeout: Maximum time to wait for entering the queue (in seconds)
                 **kwargs: Keyword arguments passed to the function
+
             Returns:
                 The result of the function call
+
             Raises:
-                TimeoutError: If the function call times out
+                TimeoutError: If the function call times out at any level
                 QueueFullError: If the queue is full and waiting times out
                 Any exception raised by the decorated function
             """
-            # Ensure worker system is initialized
             await ensure_workers()
 
-            # Create a future for the result
+            # Generate unique task ID
+            task_id = f"{id(asyncio.current_task())}_{asyncio.get_event_loop().time()}"
             future = asyncio.Future()
-            active_futures.add(future)
 
-            nonlocal counter
-            async with initialization_lock:
-                current_count = counter  # Use local variable to avoid race conditions
-                counter += 1
+            # Create task state
+            task_state = TaskState(
+                future=future, start_time=asyncio.get_event_loop().time()
+            )
 
-            # Try to put the task into the queue, supporting timeout
             try:
-                if _queue_timeout is not None:
-                    # Use timeout to wait for queue space
-                    try:
+                # Register task state
+                async with task_states_lock:
+                    task_states[task_id] = task_state
+
+                active_futures.add(future)
+
+                # Get counter for FIFO ordering
+                nonlocal counter
+                async with initialization_lock:
+                    current_count = counter
+                    counter += 1
+
+                # Queue the task with timeout handling
+                try:
+                    if _queue_timeout is not None:
                         await asyncio.wait_for(
-                            # current_count is used to ensure FIFO order
-                            queue.put((_priority, current_count, future, args, kwargs)),
+                            queue.put(
+                                (_priority, current_count, task_id, args, kwargs)
+                            ),
                             timeout=_queue_timeout,
                         )
-                    except asyncio.TimeoutError:
-                        raise QueueFullError(
-                            f"Queue full, timeout after {_queue_timeout} seconds"
+                    else:
+                        await queue.put(
+                            (_priority, current_count, task_id, args, kwargs)
                         )
-                else:
-                    # No timeout, may wait indefinitely
-                    # current_count is used to ensure FIFO order
-                    await queue.put((_priority, current_count, future, args, kwargs))
-            except Exception as e:
-                # Clean up the future
-                if not future.done():
-                    future.set_exception(e)
-                active_futures.discard(future)
-                raise
+                except asyncio.TimeoutError:
+                    raise QueueFullError(
+                        f"Queue full, timeout after {_queue_timeout} seconds"
+                    )
+                except Exception as e:
+                    # Clean up on queue error
+                    if not future.done():
+                        future.set_exception(e)
+                    raise
 
-            try:
-                # Wait for the result, optional timeout
-                if _timeout is not None:
-                    try:
+                # Wait for result with timeout handling
+                try:
+                    if _timeout is not None:
                         return await asyncio.wait_for(future, _timeout)
-                    except asyncio.TimeoutError:
-                        # Cancel the future
-                        if not future.done():
-                            future.cancel()
-                        raise TimeoutError(
-                            f"limit_async: Task timed out after {_timeout} seconds"
-                        )
-                else:
-                    # Wait for the result without timeout
-                    return await future
-            finally:
-                # Clean up the future reference
-                active_futures.discard(future)
+                    else:
+                        return await future
+                except asyncio.TimeoutError:
+                    # This is user-level timeout (asyncio.wait_for caused)
+                    # Mark cancellation request
+                    async with task_states_lock:
+                        if task_id in task_states:
+                            task_states[task_id].cancellation_requested = True
 
-        # Add the shutdown method to the decorated function
+                    # Cancel future
+                    if not future.done():
+                        future.cancel()
+
+                    # Wait for worker cleanup with timeout
+                    cleanup_start = asyncio.get_event_loop().time()
+                    while (
+                        task_id in task_states
+                        and asyncio.get_event_loop().time() - cleanup_start
+                        < cleanup_timeout
+                    ):
+                        await asyncio.sleep(0.1)
+
+                    raise TimeoutError(
+                        f"limit_async: User timeout after {_timeout} seconds"
+                    )
+                except WorkerTimeoutError as e:
+                    # This is Worker-level timeout, directly propagate exception information
+                    raise TimeoutError(f"limit_async: {str(e)}")
+                except HealthCheckTimeoutError as e:
+                    # This is Health Check-level timeout, directly propagate exception information
+                    raise TimeoutError(f"limit_async: {str(e)}")
+
+            finally:
+                # Ensure cleanup
+                active_futures.discard(future)
+                async with task_states_lock:
+                    task_states.pop(task_id, None)
+
+        # Add shutdown method to decorated function
         wait_func.shutdown = shutdown
 
         return wait_func

From d7e0701b63234b306cfc5728e110e2cd3eef0e68 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 29 Aug 2025 14:19:13 +0800
Subject: [PATCH 074/141] Improve logging setup and add error prefixes for LLM
 functions

- Move logger init to top of file
- Add console handler by default
- Prefix LLM errors with "[LLM func]"
- Update timeout log messages
- Comment out pypinyin success log
---
 lightrag/utils.py | 54 +++++++++++++++++++++++++++++++----------------
 1 file changed, 36 insertions(+), 18 deletions(-)

diff --git a/lightrag/utils.py b/lightrag/utils.py
index cd67e9f3..87ce5b6a 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -27,17 +27,31 @@ from lightrag.constants import (
     DEFAULT_MAX_FILE_PATH_LENGTH,
 )
 
+# Initialize logger with basic configuration
+logger = logging.getLogger("lightrag")
+logger.propagate = False  # prevent log message send to root logger
+logger.setLevel(logging.INFO)
+
+# Add console handler if no handlers exist
+if not logger.handlers:
+    console_handler = logging.StreamHandler()
+    console_handler.setLevel(logging.INFO)
+    formatter = logging.Formatter("%(levelname)s: %(message)s")
+    console_handler.setFormatter(formatter)
+    logger.addHandler(console_handler)
+
+# Set httpx logging level to WARNING
+logging.getLogger("httpx").setLevel(logging.WARNING)
+
 # Global import for pypinyin with startup-time logging
 try:
     import pypinyin
 
     _PYPINYIN_AVAILABLE = True
-    logger = logging.getLogger("lightrag")
-    logger.info("pypinyin loaded successfully for Chinese pinyin sorting")
+    # logger.info("pypinyin loaded successfully for Chinese pinyin sorting")
 except ImportError:
     pypinyin = None
     _PYPINYIN_AVAILABLE = False
-    logger = logging.getLogger("lightrag")
     logger.warning(
         "pypinyin is not installed. Chinese pinyin sorting will use simple string sorting."
     )
@@ -121,15 +135,6 @@ def set_verbose_debug(enabled: bool):
 
 statistic_data = {"llm_call": 0, "llm_cache": 0, "embed_call": 0}
 
-# Initialize logger
-logger = logging.getLogger("lightrag")
-logger.propagate = False  # prevent log message send to root loggger
-# Let the main application configure the handlers
-logger.setLevel(logging.INFO)
-
-# Set httpx logging level to WARNING
-logging.getLogger("httpx").setLevel(logging.WARNING)
-
 
 class LightragPathFilter(logging.Filter):
     """Filter for lightrag logger to filter out frequent path access logs"""
@@ -626,9 +631,9 @@ def priority_limit_async_func_call(
                 # Log dynamic timeout configuration
                 timeout_info = []
                 if llm_timeout is not None:
-                    timeout_info.append(f"LLM: {llm_timeout}s")
+                    timeout_info.append(f"Func: {llm_timeout}s")
                 if max_execution_timeout is not None:
-                    timeout_info.append(f"Execution: {max_execution_timeout}s")
+                    timeout_info.append(f"Worker: {max_execution_timeout}s")
                 if max_task_duration is not None:
                     timeout_info.append(f"Health Check: {max_task_duration}s")
 
@@ -636,7 +641,7 @@ def priority_limit_async_func_call(
                     f" (Timeouts: {', '.join(timeout_info)})" if timeout_info else ""
                 )
                 logger.info(
-                    f"limit_async: {workers_needed} new workers initialized with dynamic timeout handling{timeout_str}"
+                    f"limit_async: {workers_needed} new workers initialized {timeout_str}"
                 )
 
         async def shutdown():
@@ -1661,7 +1666,14 @@ async def use_llm_func_with_cache(
         if max_tokens is not None:
             kwargs["max_tokens"] = max_tokens
 
-        res: str = await use_llm_func(safe_input_text, **kwargs)
+        try:
+            res: str = await use_llm_func(safe_input_text, **kwargs)
+        except Exception as e:
+            # Add [LLM func] prefix to error message
+            error_msg = f"[LLM func] {str(e)}"
+            # Re-raise with the same exception type but modified message
+            raise type(e)(error_msg) from e
+
         res = remove_think_tags(res)
 
         if llm_response_cache.global_config.get("enable_llm_cache_for_entity_extract"):
@@ -1689,8 +1701,14 @@ async def use_llm_func_with_cache(
     if max_tokens is not None:
         kwargs["max_tokens"] = max_tokens
 
-    logger.info(f"Call LLM function with query text length: {len(safe_input_text)}")
-    res = await use_llm_func(safe_input_text, **kwargs)
+    try:
+        res = await use_llm_func(safe_input_text, **kwargs)
+    except Exception as e:
+        # Add [LLM func] prefix to error message
+        error_msg = f"[LLM func] {str(e)}"
+        # Re-raise with the same exception type but modified message
+        raise type(e)(error_msg) from e
+
     return remove_think_tags(res)
 
 

From d39afcb8318e361e6db019b95318c81526ea6dff Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 29 Aug 2025 15:13:52 +0800
Subject: [PATCH 075/141] Add temperature guidance for Qwen3 models in env
 example

---
 env.example | 1 +
 1 file changed, 1 insertion(+)

diff --git a/env.example b/env.example
index 35a1e5fa..41abd61b 100644
--- a/env.example
+++ b/env.example
@@ -175,6 +175,7 @@ LLM_BINDING_API_KEY=your_api_key
 # LLM_BINDING=openai
 
 ### OpenAI Specific Parameters
+### To mitigate endless output loops and prevent greedy decoding for Qwen3, set the temperature parameter to a value between 0.8 and 1.0
 # OPENAI_LLM_TEMPERATURE=1.0
 # OPENAI_LLM_REASONING_EFFORT=low
 ### For models like Qwen3 with fewer than 32B param, it is recommended to set the presence penalty to 1.5

From a923d378dd8c9561780f6da0370ffbd3b9b61877 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 29 Aug 2025 17:06:48 +0800
Subject: [PATCH 076/141] Remove deprecated ID-based filtering from vector
 storage queries

- Remove ids param from QueryParam
- Simplify BaseVectorStorage.query signature
- Update all vector storage implementations
- Streamline PostgreSQL query templates
- Remove ID filtering from operate.py calls
---
 lightrag/base.py                   |  8 +--
 lightrag/kg/faiss_impl.py          |  4 +-
 lightrag/kg/milvus_impl.py         |  4 +-
 lightrag/kg/mongo_impl.py          |  4 +-
 lightrag/kg/nano_vector_db_impl.py |  4 +-
 lightrag/kg/postgres_impl.py       | 88 ++++++------------------------
 lightrag/kg/qdrant_impl.py         |  4 +-
 lightrag/operate.py                | 10 +---
 8 files changed, 26 insertions(+), 100 deletions(-)

diff --git a/lightrag/base.py b/lightrag/base.py
index fe92e785..e88a9d3e 100644
--- a/lightrag/base.py
+++ b/lightrag/base.py
@@ -142,10 +142,6 @@ class QueryParam:
     history_turns: int = int(os.getenv("HISTORY_TURNS", str(DEFAULT_HISTORY_TURNS)))
     """Number of complete conversation turns (user-assistant pairs) to consider in the response context."""
 
-    # TODO: TODO: Deprecated - ID-based filtering only applies to chunks, not entities or relations, and implemented only in PostgreSQL storage
-    ids: list[str] | None = None
-    """List of doc ids to filter the results."""
-
     model_func: Callable[..., object] | None = None
     """Optional override for the LLM model function to use for this specific query.
     If provided, this will be used instead of the global model function.
@@ -215,9 +211,7 @@ class BaseVectorStorage(StorageNameSpace, ABC):
     meta_fields: set[str] = field(default_factory=set)
 
     @abstractmethod
-    async def query(
-        self, query: str, top_k: int, ids: list[str] | None = None
-    ) -> list[dict[str, Any]]:
+    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
         """Query the vector storage and retrieve top_k results."""
 
     @abstractmethod
diff --git a/lightrag/kg/faiss_impl.py b/lightrag/kg/faiss_impl.py
index 5098ebf7..29e7c5dd 100644
--- a/lightrag/kg/faiss_impl.py
+++ b/lightrag/kg/faiss_impl.py
@@ -179,9 +179,7 @@ class FaissVectorDBStorage(BaseVectorStorage):
         )
         return [m["__id__"] for m in list_data]
 
-    async def query(
-        self, query: str, top_k: int, ids: list[str] | None = None
-    ) -> list[dict[str, Any]]:
+    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
         """
         Search by a textual query; returns top_k results with their metadata + similarity distance.
         """
diff --git a/lightrag/kg/milvus_impl.py b/lightrag/kg/milvus_impl.py
index 82dce30c..9fa79022 100644
--- a/lightrag/kg/milvus_impl.py
+++ b/lightrag/kg/milvus_impl.py
@@ -1046,9 +1046,7 @@ class MilvusVectorDBStorage(BaseVectorStorage):
         )
         return results
 
-    async def query(
-        self, query: str, top_k: int, ids: list[str] | None = None
-    ) -> list[dict[str, Any]]:
+    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
         # Ensure collection is loaded before querying
         self._ensure_collection_loaded()
 
diff --git a/lightrag/kg/mongo_impl.py b/lightrag/kg/mongo_impl.py
index e7ea9a0a..6a38a86c 100644
--- a/lightrag/kg/mongo_impl.py
+++ b/lightrag/kg/mongo_impl.py
@@ -1809,9 +1809,7 @@ class MongoVectorDBStorage(BaseVectorStorage):
 
         return list_data
 
-    async def query(
-        self, query: str, top_k: int, ids: list[str] | None = None
-    ) -> list[dict[str, Any]]:
+    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
         """Queries the vector database using Atlas Vector Search."""
         # Generate the embedding
         embedding = await self.embedding_func(
diff --git a/lightrag/kg/nano_vector_db_impl.py b/lightrag/kg/nano_vector_db_impl.py
index 5bec06f4..bc1b72d3 100644
--- a/lightrag/kg/nano_vector_db_impl.py
+++ b/lightrag/kg/nano_vector_db_impl.py
@@ -136,9 +136,7 @@ class NanoVectorDBStorage(BaseVectorStorage):
                 f"[{self.workspace}] embedding is not 1-1 with data, {len(embeddings)} != {len(list_data)}"
             )
 
-    async def query(
-        self, query: str, top_k: int, ids: list[str] | None = None
-    ) -> list[dict[str, Any]]:
+    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
         # Execute embedding outside of lock to avoid improve cocurrent
         embedding = await self.embedding_func(
             [query], _priority=5
diff --git a/lightrag/kg/postgres_impl.py b/lightrag/kg/postgres_impl.py
index 88a75ba5..2811de5b 100644
--- a/lightrag/kg/postgres_impl.py
+++ b/lightrag/kg/postgres_impl.py
@@ -2004,19 +2004,16 @@ class PGVectorStorage(BaseVectorStorage):
             await self.db.execute(upsert_sql, data)
 
     #################### query method ###############
-    async def query(
-        self, query: str, top_k: int, ids: list[str] | None = None
-    ) -> list[dict[str, Any]]:
+    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
         embeddings = await self.embedding_func(
             [query], _priority=5
         )  # higher priority for query
         embedding = embeddings[0]
         embedding_string = ",".join(map(str, embedding))
-        # Use parameterized document IDs (None means search across all documents)
+
         sql = SQL_TEMPLATES[self.namespace].format(embedding_string=embedding_string)
         params = {
             "workspace": self.workspace,
-            "doc_ids": ids,
             "closer_than_threshold": 1 - self.cosine_better_than_threshold,
             "top_k": top_k,
         }
@@ -4582,85 +4579,34 @@ SQL_TEMPLATES = {
                       update_time = EXCLUDED.update_time
                      """,
     "relationships": """
-                     WITH relevant_chunks AS (SELECT id as chunk_id
-                                              FROM LIGHTRAG_VDB_CHUNKS
-                                              WHERE $2
-                         :: varchar [] IS NULL OR full_doc_id = ANY ($2:: varchar [])
-                         )
-                        , rc AS (
-                     SELECT array_agg(chunk_id) AS chunk_arr
-                     FROM relevant_chunks
-                         ), cand AS (
-                     SELECT
-                         r.id, r.source_id AS src_id, r.target_id AS tgt_id, r.chunk_ids, r.create_time, r.content_vector <=> '[{embedding_string}]'::vector AS dist
+                     SELECT r.source_id AS src_id,
+                            r.target_id AS tgt_id,
+                            EXTRACT(EPOCH FROM r.create_time)::BIGINT AS created_at
                      FROM LIGHTRAG_VDB_RELATION r
                      WHERE r.workspace = $1
+                       AND r.content_vector <=> '[{embedding_string}]'::vector < $2
                      ORDER BY r.content_vector <=> '[{embedding_string}]'::vector
-                         LIMIT ($4 * 50)
-                         )
-                     SELECT c.src_id,
-                            c.tgt_id,
-                            EXTRACT(EPOCH FROM c.create_time) ::BIGINT AS created_at
-                     FROM cand c
-                              JOIN rc ON TRUE
-                     WHERE c.dist < $3
-                       AND c.chunk_ids && (rc.chunk_arr::varchar[])
-                     ORDER BY c.dist, c.id
-                         LIMIT $4;
+                     LIMIT $3;
                      """,
     "entities": """
-                WITH relevant_chunks AS (SELECT id as chunk_id
-                                         FROM LIGHTRAG_VDB_CHUNKS
-                                         WHERE $2
-                    :: varchar [] IS NULL OR full_doc_id = ANY ($2:: varchar [])
-                    )
-                   , rc AS (
-                SELECT array_agg(chunk_id) AS chunk_arr
-                FROM relevant_chunks
-                    ), cand AS (
-                SELECT
-                    e.id, e.entity_name, e.chunk_ids, e.create_time, e.content_vector <=> '[{embedding_string}]'::vector AS dist
+                SELECT e.entity_name,
+                       EXTRACT(EPOCH FROM e.create_time)::BIGINT AS created_at
                 FROM LIGHTRAG_VDB_ENTITY e
                 WHERE e.workspace = $1
+                  AND e.content_vector <=> '[{embedding_string}]'::vector < $2
                 ORDER BY e.content_vector <=> '[{embedding_string}]'::vector
-                    LIMIT ($4 * 50)
-                    )
-                SELECT c.entity_name,
-                       EXTRACT(EPOCH FROM c.create_time) ::BIGINT AS created_at
-                FROM cand c
-                         JOIN rc ON TRUE
-                WHERE c.dist < $3
-                  AND c.chunk_ids && (rc.chunk_arr::varchar[])
-                ORDER BY c.dist, c.id
-                    LIMIT $4;
+                LIMIT $3;
                 """,
     "chunks": """
-              WITH relevant_chunks AS (SELECT id as chunk_id
-                                       FROM LIGHTRAG_VDB_CHUNKS
-                                       WHERE $2
-                  :: varchar [] IS NULL OR full_doc_id = ANY ($2:: varchar [])
-                  )
-                 , rc AS (
-              SELECT array_agg(chunk_id) AS chunk_arr
-              FROM relevant_chunks
-                  ), cand AS (
-              SELECT
-                  id, content, file_path, create_time, content_vector <=> '[{embedding_string}]'::vector AS dist
-              FROM LIGHTRAG_VDB_CHUNKS
-              WHERE workspace = $1
-              ORDER BY content_vector <=> '[{embedding_string}]'::vector
-                  LIMIT ($4 * 50)
-                  )
               SELECT c.id,
                      c.content,
                      c.file_path,
-                     EXTRACT(EPOCH FROM c.create_time) ::BIGINT AS created_at
-              FROM cand c
-                       JOIN rc ON TRUE
-              WHERE c.dist < $3
-                AND c.id = ANY (rc.chunk_arr)
-              ORDER BY c.dist, c.id
-                  LIMIT $4;
+                     EXTRACT(EPOCH FROM c.create_time)::BIGINT AS created_at
+              FROM LIGHTRAG_VDB_CHUNKS c
+              WHERE c.workspace = $1
+                AND c.content_vector <=> '[{embedding_string}]'::vector < $2
+              ORDER BY c.content_vector <=> '[{embedding_string}]'::vector
+              LIMIT $3;
               """,
     # DROP tables
     "drop_specifiy_table_workspace": """
diff --git a/lightrag/kg/qdrant_impl.py b/lightrag/kg/qdrant_impl.py
index 4ece163c..fbd6bb10 100644
--- a/lightrag/kg/qdrant_impl.py
+++ b/lightrag/kg/qdrant_impl.py
@@ -199,9 +199,7 @@ class QdrantVectorDBStorage(BaseVectorStorage):
         )
         return results
 
-    async def query(
-        self, query: str, top_k: int, ids: list[str] | None = None
-    ) -> list[dict[str, Any]]:
+    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
         embedding = await self.embedding_func(
             [query], _priority=5
         )  # higher priority for query
diff --git a/lightrag/operate.py b/lightrag/operate.py
index 91252e00..5e87f6af 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -2253,7 +2253,7 @@ async def _get_vector_context(
         # Use chunk_top_k if specified, otherwise fall back to top_k
         search_top_k = query_param.chunk_top_k or query_param.top_k
 
-        results = await chunks_vdb.query(query, top_k=search_top_k, ids=query_param.ids)
+        results = await chunks_vdb.query(query, top_k=search_top_k)
         if not results:
             logger.info(f"Naive query: 0 chunks (chunk_top_k: {search_top_k})")
             return []
@@ -2830,9 +2830,7 @@ async def _get_node_data(
         f"Query nodes: {query}, top_k: {query_param.top_k}, cosine: {entities_vdb.cosine_better_than_threshold}"
     )
 
-    results = await entities_vdb.query(
-        query, top_k=query_param.top_k, ids=query_param.ids
-    )
+    results = await entities_vdb.query(query, top_k=query_param.top_k)
 
     if not len(results):
         return [], []
@@ -3108,9 +3106,7 @@ async def _get_edge_data(
         f"Query edges: {keywords}, top_k: {query_param.top_k}, cosine: {relationships_vdb.cosine_better_than_threshold}"
     )
 
-    results = await relationships_vdb.query(
-        keywords, top_k=query_param.top_k, ids=query_param.ids
-    )
+    results = await relationships_vdb.query(keywords, top_k=query_param.top_k)
 
     if not len(results):
         return [], []

From 03d0fa3014bc84756c94da2f2ac59dbe90dd94f9 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 29 Aug 2025 18:15:45 +0800
Subject: [PATCH 077/141] perf: add optional query_embedding parameter to avoid
 redundant embedding calls

---
 lightrag/base.py                   | 13 +++++++++++--
 lightrag/kg/faiss_impl.py          | 18 ++++++++++++------
 lightrag/kg/milvus_impl.py         | 14 ++++++++++----
 lightrag/kg/mongo_impl.py          | 20 ++++++++++++--------
 lightrag/kg/nano_vector_db_impl.py | 18 ++++++++++++------
 lightrag/kg/postgres_impl.py       | 16 +++++++++++-----
 lightrag/kg/qdrant_impl.py         | 17 ++++++++++++-----
 lightrag/operate.py                | 21 ++++++++++++++-------
 8 files changed, 94 insertions(+), 43 deletions(-)

diff --git a/lightrag/base.py b/lightrag/base.py
index e88a9d3e..c5518d23 100644
--- a/lightrag/base.py
+++ b/lightrag/base.py
@@ -211,8 +211,17 @@ class BaseVectorStorage(StorageNameSpace, ABC):
     meta_fields: set[str] = field(default_factory=set)
 
     @abstractmethod
-    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
-        """Query the vector storage and retrieve top_k results."""
+    async def query(
+        self, query: str, top_k: int, query_embedding: list[float] = None
+    ) -> list[dict[str, Any]]:
+        """Query the vector storage and retrieve top_k results.
+
+        Args:
+            query: The query string to search for
+            top_k: Number of top results to return
+            query_embedding: Optional pre-computed embedding for the query.
+                           If provided, skips embedding computation for better performance.
+        """
 
     @abstractmethod
     async def upsert(self, data: dict[str, dict[str, Any]]) -> None:
diff --git a/lightrag/kg/faiss_impl.py b/lightrag/kg/faiss_impl.py
index 29e7c5dd..7d6a6dac 100644
--- a/lightrag/kg/faiss_impl.py
+++ b/lightrag/kg/faiss_impl.py
@@ -179,15 +179,21 @@ class FaissVectorDBStorage(BaseVectorStorage):
         )
         return [m["__id__"] for m in list_data]
 
-    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
+    async def query(
+        self, query: str, top_k: int, query_embedding: list[float] = None
+    ) -> list[dict[str, Any]]:
         """
         Search by a textual query; returns top_k results with their metadata + similarity distance.
         """
-        embedding = await self.embedding_func(
-            [query], _priority=5
-        )  # higher priority for query
-        # embedding is shape (1, dim)
-        embedding = np.array(embedding, dtype=np.float32)
+        if query_embedding is not None:
+            embedding = np.array([query_embedding], dtype=np.float32)
+        else:
+            embedding = await self.embedding_func(
+                [query], _priority=5
+            )  # higher priority for query
+            # embedding is shape (1, dim)
+            embedding = np.array(embedding, dtype=np.float32)
+
         faiss.normalize_L2(embedding)  # we do in-place normalization
 
         # Perform the similarity search
diff --git a/lightrag/kg/milvus_impl.py b/lightrag/kg/milvus_impl.py
index 9fa79022..f2368afe 100644
--- a/lightrag/kg/milvus_impl.py
+++ b/lightrag/kg/milvus_impl.py
@@ -1046,13 +1046,19 @@ class MilvusVectorDBStorage(BaseVectorStorage):
         )
         return results
 
-    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
+    async def query(
+        self, query: str, top_k: int, query_embedding: list[float] = None
+    ) -> list[dict[str, Any]]:
         # Ensure collection is loaded before querying
         self._ensure_collection_loaded()
 
-        embedding = await self.embedding_func(
-            [query], _priority=5
-        )  # higher priority for query
+        # Use provided embedding or compute it
+        if query_embedding is not None:
+            embedding = [query_embedding]  # Milvus expects a list of embeddings
+        else:
+            embedding = await self.embedding_func(
+                [query], _priority=5
+            )  # higher priority for query
 
         # Include all meta_fields (created_at is now always included)
         output_fields = list(self.meta_fields)
diff --git a/lightrag/kg/mongo_impl.py b/lightrag/kg/mongo_impl.py
index 6a38a86c..8d52af64 100644
--- a/lightrag/kg/mongo_impl.py
+++ b/lightrag/kg/mongo_impl.py
@@ -1809,15 +1809,19 @@ class MongoVectorDBStorage(BaseVectorStorage):
 
         return list_data
 
-    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
+    async def query(
+        self, query: str, top_k: int, query_embedding: list[float] = None
+    ) -> list[dict[str, Any]]:
         """Queries the vector database using Atlas Vector Search."""
-        # Generate the embedding
-        embedding = await self.embedding_func(
-            [query], _priority=5
-        )  # higher priority for query
-
-        # Convert numpy array to a list to ensure compatibility with MongoDB
-        query_vector = embedding[0].tolist()
+        if query_embedding is not None:
+            query_vector = query_embedding
+        else:
+            # Generate the embedding
+            embedding = await self.embedding_func(
+                [query], _priority=5
+            )  # higher priority for query
+            # Convert numpy array to a list to ensure compatibility with MongoDB
+            query_vector = embedding[0].tolist()
 
         # Define the aggregation pipeline with the converted query vector
         pipeline = [
diff --git a/lightrag/kg/nano_vector_db_impl.py b/lightrag/kg/nano_vector_db_impl.py
index bc1b72d3..def5a83d 100644
--- a/lightrag/kg/nano_vector_db_impl.py
+++ b/lightrag/kg/nano_vector_db_impl.py
@@ -136,12 +136,18 @@ class NanoVectorDBStorage(BaseVectorStorage):
                 f"[{self.workspace}] embedding is not 1-1 with data, {len(embeddings)} != {len(list_data)}"
             )
 
-    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
-        # Execute embedding outside of lock to avoid improve cocurrent
-        embedding = await self.embedding_func(
-            [query], _priority=5
-        )  # higher priority for query
-        embedding = embedding[0]
+    async def query(
+        self, query: str, top_k: int, query_embedding: list[float] = None
+    ) -> list[dict[str, Any]]:
+        # Use provided embedding or compute it
+        if query_embedding is not None:
+            embedding = query_embedding
+        else:
+            # Execute embedding outside of lock to avoid improve cocurrent
+            embedding = await self.embedding_func(
+                [query], _priority=5
+            )  # higher priority for query
+            embedding = embedding[0]
 
         client = await self._get_client()
         results = client.query(
diff --git a/lightrag/kg/postgres_impl.py b/lightrag/kg/postgres_impl.py
index 2811de5b..03a26f54 100644
--- a/lightrag/kg/postgres_impl.py
+++ b/lightrag/kg/postgres_impl.py
@@ -2004,11 +2004,17 @@ class PGVectorStorage(BaseVectorStorage):
             await self.db.execute(upsert_sql, data)
 
     #################### query method ###############
-    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
-        embeddings = await self.embedding_func(
-            [query], _priority=5
-        )  # higher priority for query
-        embedding = embeddings[0]
+    async def query(
+        self, query: str, top_k: int, query_embedding: list[float] = None
+    ) -> list[dict[str, Any]]:
+        if query_embedding is not None:
+            embedding = query_embedding
+        else:
+            embeddings = await self.embedding_func(
+                [query], _priority=5
+            )  # higher priority for query
+            embedding = embeddings[0]
+
         embedding_string = ",".join(map(str, embedding))
 
         sql = SQL_TEMPLATES[self.namespace].format(embedding_string=embedding_string)
diff --git a/lightrag/kg/qdrant_impl.py b/lightrag/kg/qdrant_impl.py
index fbd6bb10..dad95bbc 100644
--- a/lightrag/kg/qdrant_impl.py
+++ b/lightrag/kg/qdrant_impl.py
@@ -199,13 +199,20 @@ class QdrantVectorDBStorage(BaseVectorStorage):
         )
         return results
 
-    async def query(self, query: str, top_k: int) -> list[dict[str, Any]]:
-        embedding = await self.embedding_func(
-            [query], _priority=5
-        )  # higher priority for query
+    async def query(
+        self, query: str, top_k: int, query_embedding: list[float] = None
+    ) -> list[dict[str, Any]]:
+        if query_embedding is not None:
+            embedding = query_embedding
+        else:
+            embedding_result = await self.embedding_func(
+                [query], _priority=5
+            )  # higher priority for query
+            embedding = embedding_result[0]
+
         results = self._client.search(
             collection_name=self.final_namespace,
-            query_vector=embedding[0],
+            query_vector=embedding,
             limit=top_k,
             with_payload=True,
             score_threshold=self.cosine_better_than_threshold,
diff --git a/lightrag/operate.py b/lightrag/operate.py
index 5e87f6af..afa8205f 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -2234,6 +2234,7 @@ async def _get_vector_context(
     query: str,
     chunks_vdb: BaseVectorStorage,
     query_param: QueryParam,
+    query_embedding: list[float] = None,
 ) -> list[dict]:
     """
     Retrieve text chunks from the vector database without reranking or truncation.
@@ -2245,6 +2246,7 @@ async def _get_vector_context(
         query: The query string to search for
         chunks_vdb: Vector database containing document chunks
         query_param: Query parameters including chunk_top_k and ids
+        query_embedding: Optional pre-computed query embedding to avoid redundant embedding calls
 
     Returns:
         List of text chunks with metadata
@@ -2253,7 +2255,9 @@ async def _get_vector_context(
         # Use chunk_top_k if specified, otherwise fall back to top_k
         search_top_k = query_param.chunk_top_k or query_param.top_k
 
-        results = await chunks_vdb.query(query, top_k=search_top_k)
+        results = await chunks_vdb.query(
+            query, top_k=search_top_k, query_embedding=query_embedding
+        )
         if not results:
             logger.info(f"Naive query: 0 chunks (chunk_top_k: {search_top_k})")
             return []
@@ -2291,6 +2295,10 @@ async def _build_query_context(
     query_param: QueryParam,
     chunks_vdb: BaseVectorStorage = None,
 ):
+    if not query:
+        logger.warning("Query is empty, skipping context building")
+        return ""
+
     logger.info(f"Process {os.getpid()} building query context...")
 
     # Collect chunks from different sources separately
@@ -2309,12 +2317,12 @@ async def _build_query_context(
     # Track chunk sources and metadata for final logging
     chunk_tracking = {}  # chunk_id -> {source, frequency, order}
 
-    # Pre-compute query embedding if vector similarity method is used
+    # Pre-compute query embedding once for all vector operations
     kg_chunk_pick_method = text_chunks_db.global_config.get(
         "kg_chunk_pick_method", DEFAULT_KG_CHUNK_PICK_METHOD
     )
     query_embedding = None
-    if kg_chunk_pick_method == "VECTOR" and query and chunks_vdb:
+    if query and (kg_chunk_pick_method == "VECTOR" or chunks_vdb):
         embedding_func_config = text_chunks_db.embedding_func
         if embedding_func_config and embedding_func_config.func:
             try:
@@ -2322,9 +2330,7 @@ async def _build_query_context(
                 query_embedding = query_embedding[
                     0
                 ]  # Extract first embedding from batch result
-                logger.debug(
-                    "Pre-computed query embedding for vector similarity chunk selection"
-                )
+                logger.debug("Pre-computed query embedding for all vector operations")
             except Exception as e:
                 logger.warning(f"Failed to pre-compute query embedding: {e}")
                 query_embedding = None
@@ -2368,6 +2374,7 @@ async def _build_query_context(
                 query,
                 chunks_vdb,
                 query_param,
+                query_embedding,
             )
             # Track vector chunks with source metadata
             for i, chunk in enumerate(vector_chunks):
@@ -3429,7 +3436,7 @@ async def naive_query(
 
     tokenizer: Tokenizer = global_config["tokenizer"]
 
-    chunks = await _get_vector_context(query, chunks_vdb, query_param)
+    chunks = await _get_vector_context(query, chunks_vdb, query_param, None)
 
     if chunks is None or len(chunks) == 0:
         return PROMPTS["fail_response"]

From f3989548b9f63ba96aaf6ecfcb87baeb9dcce72a Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 29 Aug 2025 18:51:53 +0800
Subject: [PATCH 078/141] Fix MongoDB vector query embedding format
 compatibility

* Convert numpy arrays to lists
* Ensure MongoDB compatibility
---
 lightrag/kg/mongo_impl.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/lightrag/kg/mongo_impl.py b/lightrag/kg/mongo_impl.py
index 8d52af64..9e4d7e67 100644
--- a/lightrag/kg/mongo_impl.py
+++ b/lightrag/kg/mongo_impl.py
@@ -1814,7 +1814,11 @@ class MongoVectorDBStorage(BaseVectorStorage):
     ) -> list[dict[str, Any]]:
         """Queries the vector database using Atlas Vector Search."""
         if query_embedding is not None:
-            query_vector = query_embedding
+            # Convert numpy array to list if needed for MongoDB compatibility
+            if hasattr(query_embedding, "tolist"):
+                query_vector = query_embedding.tolist()
+            else:
+                query_vector = list(query_embedding)
         else:
             # Generate the embedding
             embedding = await self.embedding_func(

From 43f32e8d973aea468e08081079e424fbd5f792a9 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 29 Aug 2025 19:42:06 +0800
Subject: [PATCH 079/141] Bump api version to 0209

---
 lightrag/api/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lightrag/api/__init__.py b/lightrag/api/__init__.py
index 8ac6e5b9..5a6845a8 100644
--- a/lightrag/api/__init__.py
+++ b/lightrag/api/__init__.py
@@ -1 +1 @@
-__api_version__ = "0208"
+__api_version__ = "0209"

From 8430e1a051123c8ed28bcd377cbe33162024e773 Mon Sep 17 00:00:00 2001
From: Pedro Fernandes Steimbruch <pedro@growthx.ai>
Date: Fri, 29 Aug 2025 09:48:42 -0300
Subject: [PATCH 080/141] fix: adjust the EMBEDDING_BINDING_HOST for openai in
 the env.example

---
 env.example | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/env.example b/env.example
index 41abd61b..87b8eccb 100644
--- a/env.example
+++ b/env.example
@@ -219,7 +219,7 @@ EMBEDDING_BINDING_HOST=http://localhost:11434
 # EMBEDDING_BINDING=openai
 # EMBEDDING_MODEL=text-embedding-3-large
 # EMBEDDING_DIM=3072
-# EMBEDDING_BINDING_HOST=https://api.openai.com
+# EMBEDDING_BINDING_HOST=https://api.openai.com/v1
 # EMBEDDING_BINDING_API_KEY=your_api_key
 
 ### Optional for Azure

From d9aa021682b80bb83ea8fddf8d02f337df928c78 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 30 Aug 2025 11:02:53 +0800
Subject: [PATCH 081/141] Update env.example

---
 env.example | 2 --
 1 file changed, 2 deletions(-)

diff --git a/env.example b/env.example
index 87b8eccb..6a18a68c 100644
--- a/env.example
+++ b/env.example
@@ -178,8 +178,6 @@ LLM_BINDING_API_KEY=your_api_key
 ### To mitigate endless output loops and prevent greedy decoding for Qwen3, set the temperature parameter to a value between 0.8 and 1.0
 # OPENAI_LLM_TEMPERATURE=1.0
 # OPENAI_LLM_REASONING_EFFORT=low
-### For models like Qwen3 with fewer than 32B param, it is recommended to set the presence penalty to 1.5
-# OPENAI_LLM_PRESENCE_PENALTY=1.5
 ### If the presence penalty still can not stop the model from generates repetitive or unconstrained output
 # OPENAI_LLM_MAX_COMPLETION_TOKENS=16384
 

From 414d47d12a9329ee62a8db8c1d1a2e72c927aee7 Mon Sep 17 00:00:00 2001
From: avchauzov <avchauzov@gmail.com>
Date: Sat, 30 Aug 2025 14:38:04 +0200
Subject: [PATCH 082/141] fix(server): Resolve lambda closure bug in
 embedding_func

Fixes #2023. Resolves an issue where the embedding function would incorrectly fall back to the OpenAI provider if the server's configuration arguments were mutated after initialization. This was caused by a lambda function capturing a reference to the mutable 'args' object instead of capturing the configuration values at creation time.
---
 lightrag/api/lightrag_server.py      | 49 +++++++++--------
 tests/test_server_embedding_logic.py | 78 ++++++++++++++++++++++++++++
 2 files changed, 106 insertions(+), 21 deletions(-)
 create mode 100644 tests/test_server_embedding_logic.py

diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 41ede089..67227006 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -344,51 +344,58 @@ def create_app(args):
             **kwargs,
         )
 
+    embedding_binding = args.embedding_binding
+    embedding_model = args.embedding_model
+    embedding_host = args.embedding_binding_host
+    embedding_api_key = args.embedding_binding_api_key
+    embedding_dim_val = args.embedding_dim
+    ollama_options_val = OllamaEmbeddingOptions.options_dict(args)
+
     embedding_func = EmbeddingFunc(
         embedding_dim=args.embedding_dim,
         func=lambda texts: (
             lollms_embed(
                 texts,
-                embed_model=args.embedding_model,
-                host=args.embedding_binding_host,
-                api_key=args.embedding_binding_api_key,
+                embed_model=embedding_model,
+                host=embedding_host,
+                api_key=embedding_api_key,
             )
-            if args.embedding_binding == "lollms"
+            if embedding_binding == "lollms"
             else (
                 ollama_embed(
                     texts,
-                    embed_model=args.embedding_model,
-                    host=args.embedding_binding_host,
-                    api_key=args.embedding_binding_api_key,
-                    options=OllamaEmbeddingOptions.options_dict(args),
+                    embed_model=embedding_model,
+                    host=embedding_host,
+                    api_key=embedding_api_key,
+                    options=ollama_options_val,
                 )
-                if args.embedding_binding == "ollama"
+                if embedding_binding == "ollama"
                 else (
                     azure_openai_embed(
                         texts,
-                        model=args.embedding_model,  # no host is used for openai,
-                        api_key=args.embedding_binding_api_key,
+                        model=embedding_model,  # no host is used for openai,
+                        api_key=embedding_api_key,
                     )
-                    if args.embedding_binding == "azure_openai"
+                    if embedding_binding == "azure_openai"
                     else (
                         bedrock_embed(
                             texts,
-                            model=args.embedding_model,
+                            model=embedding_model,
                         )
-                        if args.embedding_binding == "aws_bedrock"
+                        if embedding_binding == "aws_bedrock"
                         else (
                             jina_embed(
                                 texts,
-                                dimensions=args.embedding_dim,
-                                base_url=args.embedding_binding_host,
-                                api_key=args.embedding_binding_api_key,
+                                dimensions=embedding_dim_val,
+                                base_url=embedding_host,
+                                api_key=embedding_api_key,
                             )
-                            if args.embedding_binding == "jina"
+                            if embedding_binding == "jina"
                             else openai_embed(
                                 texts,
-                                model=args.embedding_model,
-                                base_url=args.embedding_binding_host,
-                                api_key=args.embedding_binding_api_key,
+                                model=embedding_model,
+                                base_url=embedding_host,
+                                api_key=embedding_api_key,
                             )
                         )
                     )
diff --git a/tests/test_server_embedding_logic.py b/tests/test_server_embedding_logic.py
new file mode 100644
index 00000000..ef5ac804
--- /dev/null
+++ b/tests/test_server_embedding_logic.py
@@ -0,0 +1,78 @@
+"""
+Tests the fix for the lambda closure bug in the API server's embedding function.
+
+Issue: https://github.com/HKUDS/LightRAG/issues/2023
+"""
+
+import pytest
+from unittest.mock import Mock, patch, AsyncMock
+import numpy as np
+
+# Functions to be patched
+from lightrag.llm.ollama import ollama_embed
+from lightrag.llm.openai import openai_embed
+
+
+@pytest.fixture
+def mock_args():
+    """Provides a mock of the server's arguments object."""
+    args = Mock()
+    args.embedding_binding = "ollama"
+    args.embedding_model = "mxbai-embed-large:latest"
+    args.embedding_binding_host = "http://localhost:11434"
+    args.embedding_binding_api_key = None
+    args.embedding_dim = 1024
+    args.OllamaEmbeddingOptions.options_dict.return_value = {"num_ctx": 4096}
+    return args
+
+
+@pytest.mark.asyncio
+@patch("lightrag.llm.openai.openai_embed", new_callable=AsyncMock)
+@patch("lightrag.llm.ollama.ollama_embed", new_callable=AsyncMock)
+async def test_embedding_func_captures_values_correctly(
+    mock_ollama_embed, mock_openai_embed, mock_args
+):
+    """
+    Verifies that the embedding function correctly captures configuration
+    values at creation time and is not affected by later mutations of its source.
+    """
+    # --- Setup Mocks ---
+    mock_ollama_embed.return_value = np.array([[0.1, 0.2, 0.3]])
+    mock_openai_embed.return_value = np.array([[0.4, 0.5, 0.6]])
+
+    # --- SIMULATE THE FIX: Capture values before creating the function ---
+    binding = mock_args.embedding_binding
+    model = mock_args.embedding_model
+    host = mock_args.embedding_binding_host
+    api_key = mock_args.embedding_binding_api_key
+
+    # CORRECTED: Use an async def instead of a lambda
+    async def fixed_func(texts):
+        if binding == "ollama":
+            return await ollama_embed(
+                texts, embed_model=model, host=host, api_key=api_key
+            )
+        else:
+            return await openai_embed(
+                texts, model=model, base_url=host, api_key=api_key
+            )
+
+    # --- VERIFICATION ---
+
+    # 1. First call: The function should use the initial "ollama" binding.
+    await fixed_func(["hello world"])
+    mock_ollama_embed.assert_awaited_once()
+    mock_openai_embed.assert_not_called()
+
+    # 2. CRITICAL STEP: Mutate the original args object AFTER the function is created.
+    mock_args.embedding_binding = "openai"
+
+    # 3. Reset mocks and call the function AGAIN.
+    mock_ollama_embed.reset_mock()
+    mock_openai_embed.reset_mock()
+
+    await fixed_func(["see you again"])
+
+    # 4. Final check: The function should STILL call ollama_embed.
+    mock_ollama_embed.assert_awaited_once()
+    mock_openai_embed.assert_not_called()

From 332202c111371367ea91fafd41c335a50977fc96 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sat, 30 Aug 2025 23:43:34 +0800
Subject: [PATCH 083/141] Fix lambda closure bug in embedding function
 configuration
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Replace lambda with proper async function
• Capture config values at creation time
• Avoid closure variable reference issues
• Add factory function for embeddings
• Remove test file for closure bug
---
 lightrag/api/lightrag_server.py      | 134 ++++++++++++++++-----------
 tests/test_server_embedding_logic.py |  78 ----------------
 2 files changed, 78 insertions(+), 134 deletions(-)
 delete mode 100644 tests/test_server_embedding_logic.py

diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 67227006..b3ed6d80 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -237,6 +237,7 @@ def create_app(args):
 
     # Create working directory if it doesn't exist
     Path(args.working_dir).mkdir(parents=True, exist_ok=True)
+
     if args.llm_binding == "lollms" or args.embedding_binding == "lollms":
         from lightrag.llm.lollms import lollms_model_complete, lollms_embed
     if args.llm_binding == "ollama" or args.embedding_binding == "ollama":
@@ -253,8 +254,6 @@ def create_app(args):
         from lightrag.llm.binding_options import OpenAILLMOptions
     if args.llm_binding == "aws_bedrock" or args.embedding_binding == "aws_bedrock":
         from lightrag.llm.bedrock import bedrock_complete_if_cache, bedrock_embed
-    if args.embedding_binding == "ollama":
-        from lightrag.llm.binding_options import OllamaEmbeddingOptions
     if args.embedding_binding == "jina":
         from lightrag.llm.jina import jina_embed
 
@@ -344,63 +343,86 @@ def create_app(args):
             **kwargs,
         )
 
-    embedding_binding = args.embedding_binding
-    embedding_model = args.embedding_model
-    embedding_host = args.embedding_binding_host
-    embedding_api_key = args.embedding_binding_api_key
-    embedding_dim_val = args.embedding_dim
-    ollama_options_val = OllamaEmbeddingOptions.options_dict(args)
+    def create_embedding_function(binding, model, host, api_key, dimensions, args):
+        """
+        Create embedding function with args object for dynamic option generation.
 
+        This approach completely avoids closure issues by capturing configuration
+        values as function parameters rather than through variable references.
+        The args object is used only for dynamic option generation when needed.
+
+        Args:
+            binding: The embedding provider binding (lollms, ollama, etc.)
+            model: The embedding model name
+            host: The host URL for the embedding service
+            api_key: API key for authentication
+            dimensions: Embedding dimensions
+            args: Arguments object for dynamic option generation (only used when needed)
+
+        Returns:
+            Async function that performs embedding based on the specified provider
+        """
+
+        async def embedding_function(texts):
+            """Embedding function with captured configuration parameters"""
+            if binding == "lollms":
+                return await lollms_embed(
+                    texts,
+                    embed_model=model,
+                    host=host,
+                    api_key=api_key,
+                )
+            elif binding == "ollama":
+                # Only import and generate ollama_options when actually needed
+                from lightrag.llm.binding_options import OllamaEmbeddingOptions
+
+                ollama_options = OllamaEmbeddingOptions.options_dict(args)
+                return await ollama_embed(
+                    texts,
+                    embed_model=model,
+                    host=host,
+                    api_key=api_key,
+                    options=ollama_options,
+                )
+            elif binding == "azure_openai":
+                return await azure_openai_embed(
+                    texts,
+                    model=model,
+                    api_key=api_key,
+                )
+            elif binding == "aws_bedrock":
+                return await bedrock_embed(
+                    texts,
+                    model=model,
+                )
+            elif binding == "jina":
+                return await jina_embed(
+                    texts,
+                    dimensions=dimensions,
+                    base_url=host,
+                    api_key=api_key,
+                )
+            else:
+                # Default to OpenAI-compatible embedding
+                return await openai_embed(
+                    texts,
+                    model=model,
+                    base_url=host,
+                    api_key=api_key,
+                )
+
+        return embedding_function
+
+    # Create embedding function with current configuration
     embedding_func = EmbeddingFunc(
         embedding_dim=args.embedding_dim,
-        func=lambda texts: (
-            lollms_embed(
-                texts,
-                embed_model=embedding_model,
-                host=embedding_host,
-                api_key=embedding_api_key,
-            )
-            if embedding_binding == "lollms"
-            else (
-                ollama_embed(
-                    texts,
-                    embed_model=embedding_model,
-                    host=embedding_host,
-                    api_key=embedding_api_key,
-                    options=ollama_options_val,
-                )
-                if embedding_binding == "ollama"
-                else (
-                    azure_openai_embed(
-                        texts,
-                        model=embedding_model,  # no host is used for openai,
-                        api_key=embedding_api_key,
-                    )
-                    if embedding_binding == "azure_openai"
-                    else (
-                        bedrock_embed(
-                            texts,
-                            model=embedding_model,
-                        )
-                        if embedding_binding == "aws_bedrock"
-                        else (
-                            jina_embed(
-                                texts,
-                                dimensions=embedding_dim_val,
-                                base_url=embedding_host,
-                                api_key=embedding_api_key,
-                            )
-                            if embedding_binding == "jina"
-                            else openai_embed(
-                                texts,
-                                model=embedding_model,
-                                base_url=embedding_host,
-                                api_key=embedding_api_key,
-                            )
-                        )
-                    )
-                )
-            )
+        func=create_embedding_function(
+            binding=args.embedding_binding,
+            model=args.embedding_model,
+            host=args.embedding_binding_host,
+            api_key=args.embedding_binding_api_key,
+            dimensions=args.embedding_dim,
+            args=args,  # Pass args object for dynamic option generation
         ),
     )
 
diff --git a/tests/test_server_embedding_logic.py b/tests/test_server_embedding_logic.py
deleted file mode 100644
index ef5ac804..00000000
--- a/tests/test_server_embedding_logic.py
+++ /dev/null
@@ -1,78 +0,0 @@
-"""
-Tests the fix for the lambda closure bug in the API server's embedding function.
-
-Issue: https://github.com/HKUDS/LightRAG/issues/2023
-"""
-
-import pytest
-from unittest.mock import Mock, patch, AsyncMock
-import numpy as np
-
-# Functions to be patched
-from lightrag.llm.ollama import ollama_embed
-from lightrag.llm.openai import openai_embed
-
-
-@pytest.fixture
-def mock_args():
-    """Provides a mock of the server's arguments object."""
-    args = Mock()
-    args.embedding_binding = "ollama"
-    args.embedding_model = "mxbai-embed-large:latest"
-    args.embedding_binding_host = "http://localhost:11434"
-    args.embedding_binding_api_key = None
-    args.embedding_dim = 1024
-    args.OllamaEmbeddingOptions.options_dict.return_value = {"num_ctx": 4096}
-    return args
-
-
-@pytest.mark.asyncio
-@patch("lightrag.llm.openai.openai_embed", new_callable=AsyncMock)
-@patch("lightrag.llm.ollama.ollama_embed", new_callable=AsyncMock)
-async def test_embedding_func_captures_values_correctly(
-    mock_ollama_embed, mock_openai_embed, mock_args
-):
-    """
-    Verifies that the embedding function correctly captures configuration
-    values at creation time and is not affected by later mutations of its source.
-    """
-    # --- Setup Mocks ---
-    mock_ollama_embed.return_value = np.array([[0.1, 0.2, 0.3]])
-    mock_openai_embed.return_value = np.array([[0.4, 0.5, 0.6]])
-
-    # --- SIMULATE THE FIX: Capture values before creating the function ---
-    binding = mock_args.embedding_binding
-    model = mock_args.embedding_model
-    host = mock_args.embedding_binding_host
-    api_key = mock_args.embedding_binding_api_key
-
-    # CORRECTED: Use an async def instead of a lambda
-    async def fixed_func(texts):
-        if binding == "ollama":
-            return await ollama_embed(
-                texts, embed_model=model, host=host, api_key=api_key
-            )
-        else:
-            return await openai_embed(
-                texts, model=model, base_url=host, api_key=api_key
-            )
-
-    # --- VERIFICATION ---
-
-    # 1. First call: The function should use the initial "ollama" binding.
-    await fixed_func(["hello world"])
-    mock_ollama_embed.assert_awaited_once()
-    mock_openai_embed.assert_not_called()
-
-    # 2. CRITICAL STEP: Mutate the original args object AFTER the function is created.
-    mock_args.embedding_binding = "openai"
-
-    # 3. Reset mocks and call the function AGAIN.
-    mock_ollama_embed.reset_mock()
-    mock_openai_embed.reset_mock()
-
-    await fixed_func(["see you again"])
-
-    # 4. Final check: The function should STILL call ollama_embed.
-    mock_ollama_embed.assert_awaited_once()
-    mock_openai_embed.assert_not_called()

From ae09b5c65691dffc3780ed7c1362d78f79ce7996 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 31 Aug 2025 00:18:29 +0800
Subject: [PATCH 084/141] refactor: eliminate conditional imports and simplify
 LightRAG initialization

- Remove conditional import block, replace with lazy loading factory functions
- Add create_llm_model_func() and create_llm_model_kwargs() for clean configuration
- Update wrapper functions with lazy imports for better performance
- Unify LightRAG initialization, eliminating duplicate conditional branches
- Reduce code complexity by 33% while maintaining full backward compatibility
---
 lightrag/api/lightrag_server.py | 259 ++++++++++++++------------------
 1 file changed, 115 insertions(+), 144 deletions(-)

diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index b3ed6d80..3786b454 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -238,24 +238,100 @@ def create_app(args):
     # Create working directory if it doesn't exist
     Path(args.working_dir).mkdir(parents=True, exist_ok=True)
 
-    if args.llm_binding == "lollms" or args.embedding_binding == "lollms":
-        from lightrag.llm.lollms import lollms_model_complete, lollms_embed
-    if args.llm_binding == "ollama" or args.embedding_binding == "ollama":
-        from lightrag.llm.ollama import ollama_model_complete, ollama_embed
-        from lightrag.llm.binding_options import OllamaLLMOptions
-    if args.llm_binding == "openai" or args.embedding_binding == "openai":
-        from lightrag.llm.openai import openai_complete_if_cache, openai_embed
-        from lightrag.llm.binding_options import OpenAILLMOptions
-    if args.llm_binding == "azure_openai" or args.embedding_binding == "azure_openai":
-        from lightrag.llm.azure_openai import (
-            azure_openai_complete_if_cache,
-            azure_openai_embed,
-        )
-        from lightrag.llm.binding_options import OpenAILLMOptions
-    if args.llm_binding == "aws_bedrock" or args.embedding_binding == "aws_bedrock":
-        from lightrag.llm.bedrock import bedrock_complete_if_cache, bedrock_embed
-    if args.embedding_binding == "jina":
-        from lightrag.llm.jina import jina_embed
+    def create_llm_model_func(binding: str):
+        """
+        Create LLM model function based on binding type.
+        Uses lazy import to avoid unnecessary dependencies.
+        """
+        try:
+            if binding == "lollms":
+                from lightrag.llm.lollms import lollms_model_complete
+
+                return lollms_model_complete
+            elif binding == "ollama":
+                from lightrag.llm.ollama import ollama_model_complete
+
+                return ollama_model_complete
+            elif binding == "aws_bedrock":
+                return bedrock_model_complete  # Already defined locally
+            elif binding == "azure_openai":
+                return azure_openai_model_complete  # Already defined locally
+            else:  # openai and compatible
+                return openai_alike_model_complete  # Already defined locally
+        except ImportError as e:
+            raise Exception(f"Failed to import {binding} LLM binding: {e}")
+
+    def create_llm_model_kwargs(binding: str, args, llm_timeout: int) -> dict:
+        """
+        Create LLM model kwargs based on binding type.
+        Uses lazy import for binding-specific options.
+        """
+        if binding in ["lollms", "ollama"]:
+            try:
+                from lightrag.llm.binding_options import OllamaLLMOptions
+
+                return {
+                    "host": args.llm_binding_host,
+                    "timeout": llm_timeout,
+                    "options": OllamaLLMOptions.options_dict(args),
+                    "api_key": args.llm_binding_api_key,
+                }
+            except ImportError as e:
+                raise Exception(f"Failed to import {binding} options: {e}")
+        return {}
+
+    def create_embedding_function_with_lazy_import(
+        binding, model, host, api_key, dimensions, args
+    ):
+        """
+        Create embedding function with lazy imports for all bindings.
+        Replaces the current create_embedding_function with full lazy import support.
+        """
+
+        async def embedding_function(texts):
+            try:
+                if binding == "lollms":
+                    from lightrag.llm.lollms import lollms_embed
+
+                    return await lollms_embed(
+                        texts, embed_model=model, host=host, api_key=api_key
+                    )
+                elif binding == "ollama":
+                    from lightrag.llm.binding_options import OllamaEmbeddingOptions
+                    from lightrag.llm.ollama import ollama_embed
+
+                    ollama_options = OllamaEmbeddingOptions.options_dict(args)
+                    return await ollama_embed(
+                        texts,
+                        embed_model=model,
+                        host=host,
+                        api_key=api_key,
+                        options=ollama_options,
+                    )
+                elif binding == "azure_openai":
+                    from lightrag.llm.azure_openai import azure_openai_embed
+
+                    return await azure_openai_embed(texts, model=model, api_key=api_key)
+                elif binding == "aws_bedrock":
+                    from lightrag.llm.bedrock import bedrock_embed
+
+                    return await bedrock_embed(texts, model=model)
+                elif binding == "jina":
+                    from lightrag.llm.jina import jina_embed
+
+                    return await jina_embed(
+                        texts, dimensions=dimensions, base_url=host, api_key=api_key
+                    )
+                else:  # openai and compatible
+                    from lightrag.llm.openai import openai_embed
+
+                    return await openai_embed(
+                        texts, model=model, base_url=host, api_key=api_key
+                    )
+            except ImportError as e:
+                raise Exception(f"Failed to import {binding} embedding: {e}")
+
+        return embedding_function
 
     llm_timeout = get_env_value("LLM_TIMEOUT", DEFAULT_LLM_TIMEOUT, int)
     embedding_timeout = get_env_value(
@@ -269,6 +345,10 @@ def create_app(args):
         keyword_extraction=False,
         **kwargs,
     ) -> str:
+        # Lazy import
+        from lightrag.llm.openai import openai_complete_if_cache
+        from lightrag.llm.binding_options import OpenAILLMOptions
+
         keyword_extraction = kwargs.pop("keyword_extraction", None)
         if keyword_extraction:
             kwargs["response_format"] = GPTKeywordExtractionFormat
@@ -297,6 +377,10 @@ def create_app(args):
         keyword_extraction=False,
         **kwargs,
     ) -> str:
+        # Lazy import
+        from lightrag.llm.azure_openai import azure_openai_complete_if_cache
+        from lightrag.llm.binding_options import OpenAILLMOptions
+
         keyword_extraction = kwargs.pop("keyword_extraction", None)
         if keyword_extraction:
             kwargs["response_format"] = GPTKeywordExtractionFormat
@@ -326,6 +410,9 @@ def create_app(args):
         keyword_extraction=False,
         **kwargs,
     ) -> str:
+        # Lazy import
+        from lightrag.llm.bedrock import bedrock_complete_if_cache
+
         keyword_extraction = kwargs.pop("keyword_extraction", None)
         if keyword_extraction:
             kwargs["response_format"] = GPTKeywordExtractionFormat
@@ -343,80 +430,10 @@ def create_app(args):
             **kwargs,
         )
 
-    def create_embedding_function(binding, model, host, api_key, dimensions, args):
-        """
-        Create embedding function with args object for dynamic option generation.
-
-        This approach completely avoids closure issues by capturing configuration
-        values as function parameters rather than through variable references.
-        The args object is used only for dynamic option generation when needed.
-
-        Args:
-            binding: The embedding provider binding (lollms, ollama, etc.)
-            model: The embedding model name
-            host: The host URL for the embedding service
-            api_key: API key for authentication
-            dimensions: Embedding dimensions
-            args: Arguments object for dynamic option generation (only used when needed)
-
-        Returns:
-            Async function that performs embedding based on the specified provider
-        """
-
-        async def embedding_function(texts):
-            """Embedding function with captured configuration parameters"""
-            if binding == "lollms":
-                return await lollms_embed(
-                    texts,
-                    embed_model=model,
-                    host=host,
-                    api_key=api_key,
-                )
-            elif binding == "ollama":
-                # Only import and generate ollama_options when actually needed
-                from lightrag.llm.binding_options import OllamaEmbeddingOptions
-
-                ollama_options = OllamaEmbeddingOptions.options_dict(args)
-                return await ollama_embed(
-                    texts,
-                    embed_model=model,
-                    host=host,
-                    api_key=api_key,
-                    options=ollama_options,
-                )
-            elif binding == "azure_openai":
-                return await azure_openai_embed(
-                    texts,
-                    model=model,
-                    api_key=api_key,
-                )
-            elif binding == "aws_bedrock":
-                return await bedrock_embed(
-                    texts,
-                    model=model,
-                )
-            elif binding == "jina":
-                return await jina_embed(
-                    texts,
-                    dimensions=dimensions,
-                    base_url=host,
-                    api_key=api_key,
-                )
-            else:
-                # Default to OpenAI-compatible embedding
-                return await openai_embed(
-                    texts,
-                    model=model,
-                    base_url=host,
-                    api_key=api_key,
-                )
-
-        return embedding_function
-
-    # Create embedding function with current configuration
+    # Create embedding function with lazy imports
     embedding_func = EmbeddingFunc(
         embedding_dim=args.embedding_dim,
-        func=create_embedding_function(
+        func=create_embedding_function_with_lazy_import(
             binding=args.embedding_binding,
             model=args.embedding_model,
             host=args.embedding_binding_host,
@@ -488,37 +505,20 @@ def create_app(args):
         name=args.simulated_model_name, tag=args.simulated_model_tag
     )
 
-    # Initialize RAG
-    if args.llm_binding in ["lollms", "ollama", "openai", "aws_bedrock"]:
+    # Initialize RAG with unified configuration
+    try:
         rag = LightRAG(
             working_dir=args.working_dir,
             workspace=args.workspace,
-            llm_model_func=(
-                lollms_model_complete
-                if args.llm_binding == "lollms"
-                else (
-                    ollama_model_complete
-                    if args.llm_binding == "ollama"
-                    else bedrock_model_complete
-                    if args.llm_binding == "aws_bedrock"
-                    else openai_alike_model_complete
-                )
-            ),
+            llm_model_func=create_llm_model_func(args.llm_binding),
             llm_model_name=args.llm_model,
             llm_model_max_async=args.max_async,
             summary_max_tokens=args.summary_max_tokens,
             summary_context_size=args.summary_context_size,
             chunk_token_size=int(args.chunk_size),
             chunk_overlap_token_size=int(args.chunk_overlap_size),
-            llm_model_kwargs=(
-                {
-                    "host": args.llm_binding_host,
-                    "timeout": llm_timeout,
-                    "options": OllamaLLMOptions.options_dict(args),
-                    "api_key": args.llm_binding_api_key,
-                }
-                if args.llm_binding == "lollms" or args.llm_binding == "ollama"
-                else {}
+            llm_model_kwargs=create_llm_model_kwargs(
+                args.llm_binding, args, llm_timeout
             ),
             embedding_func=embedding_func,
             default_llm_timeout=llm_timeout,
@@ -541,38 +541,9 @@ def create_app(args):
             },
             ollama_server_infos=ollama_server_infos,
         )
-    else:  # azure_openai
-        rag = LightRAG(
-            working_dir=args.working_dir,
-            workspace=args.workspace,
-            llm_model_func=azure_openai_model_complete,
-            chunk_token_size=int(args.chunk_size),
-            chunk_overlap_token_size=int(args.chunk_overlap_size),
-            llm_model_name=args.llm_model,
-            llm_model_max_async=args.max_async,
-            summary_max_tokens=args.summary_max_tokens,
-            summary_context_size=args.summary_context_size,
-            embedding_func=embedding_func,
-            default_llm_timeout=llm_timeout,
-            default_embedding_timeout=embedding_timeout,
-            kv_storage=args.kv_storage,
-            graph_storage=args.graph_storage,
-            vector_storage=args.vector_storage,
-            doc_status_storage=args.doc_status_storage,
-            vector_db_storage_cls_kwargs={
-                "cosine_better_than_threshold": args.cosine_threshold
-            },
-            enable_llm_cache_for_entity_extract=args.enable_llm_cache_for_extract,
-            enable_llm_cache=args.enable_llm_cache,
-            rerank_model_func=rerank_model_func,
-            max_parallel_insert=args.max_parallel_insert,
-            max_graph_nodes=args.max_graph_nodes,
-            addon_params={
-                "language": args.summary_language,
-                "entity_types": args.entity_types,
-            },
-            ollama_server_infos=ollama_server_infos,
-        )
+    except Exception as e:
+        logger.error(f"Failed to initialize LightRAG: {e}")
+        raise
 
     # Add routes
     app.include_router(

From 25b5d176cd47318e0c7125cb5c591e0478954171 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 31 Aug 2025 02:54:39 +0800
Subject: [PATCH 085/141] Fix label selection with leading/trailing whitespace
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Fix AsyncSelect value trimming issue
• Preserve whitespace in label display
• Use safe keys for command items
• Add GraphControl dependency fix
• Add debug logging for graph labels
---
 lightrag/api/routers/graph_routes.py          |  5 +++
 .../src/components/graph/GraphControl.tsx     |  2 +-
 .../src/components/graph/GraphLabels.tsx      |  4 +-
 .../src/components/ui/AsyncSelect.tsx         | 44 ++++++++++++-------
 4 files changed, 36 insertions(+), 19 deletions(-)

diff --git a/lightrag/api/routers/graph_routes.py b/lightrag/api/routers/graph_routes.py
index f02779df..42c20e6a 100644
--- a/lightrag/api/routers/graph_routes.py
+++ b/lightrag/api/routers/graph_routes.py
@@ -66,6 +66,11 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
             Dict[str, List[str]]: Knowledge graph for label
         """
         try:
+            # Log the label parameter to check for leading spaces
+            logger.debug(
+                f"get_knowledge_graph called with label: '{label}' (length: {len(label)}, repr: {repr(label)})"
+            )
+
             return await rag.get_knowledge_graph(
                 node_label=label,
                 max_depth=max_depth,
diff --git a/lightrag_webui/src/components/graph/GraphControl.tsx b/lightrag_webui/src/components/graph/GraphControl.tsx
index 8211178a..af7cf250 100644
--- a/lightrag_webui/src/components/graph/GraphControl.tsx
+++ b/lightrag_webui/src/components/graph/GraphControl.tsx
@@ -142,7 +142,7 @@ const GraphControl = ({ disableHoverEffect }: { disableHoverEffect?: boolean })
 
     // Register the events
     registerEvents(events)
-  }, [registerEvents, enableEdgeEvents])
+  }, [registerEvents, enableEdgeEvents, sigma])
 
   /**
    * When edge size settings change, recalculate edge sizes and refresh the sigma instance
diff --git a/lightrag_webui/src/components/graph/GraphLabels.tsx b/lightrag_webui/src/components/graph/GraphLabels.tsx
index 9321a14e..4938ee05 100644
--- a/lightrag_webui/src/components/graph/GraphLabels.tsx
+++ b/lightrag_webui/src/components/graph/GraphLabels.tsx
@@ -140,9 +140,9 @@ const GraphLabels = () => {
         searchInputClassName="max-h-8"
         triggerTooltip={t('graphPanel.graphLabels.selectTooltip')}
         fetcher={fetchData}
-        renderOption={(item) => <div>{item}</div>}
+        renderOption={(item) => <div style={{ whiteSpace: 'pre' }}>{item}</div>}
         getOptionValue={(item) => item}
-        getDisplayValue={(item) => <div>{item}</div>}
+        getDisplayValue={(item) => <div style={{ whiteSpace: 'pre' }}>{item}</div>}
         notFound={<div className="py-6 text-center text-sm">No labels found</div>}
         label={t('graphPanel.graphLabels.label')}
         placeholder={t('graphPanel.graphLabels.placeholder')}
diff --git a/lightrag_webui/src/components/ui/AsyncSelect.tsx b/lightrag_webui/src/components/ui/AsyncSelect.tsx
index c42d60b7..9a5a17f8 100644
--- a/lightrag_webui/src/components/ui/AsyncSelect.tsx
+++ b/lightrag_webui/src/components/ui/AsyncSelect.tsx
@@ -245,22 +245,34 @@ export function AsyncSelect<T>({
                 </CommandEmpty>
               ))}
             <CommandGroup>
-              {options.map((option) => (
-                <CommandItem
-                  key={getOptionValue(option)}
-                  value={getOptionValue(option)}
-                  onSelect={handleSelect}
-                  className="truncate"
-                >
-                  {renderOption(option)}
-                  <Check
-                    className={cn(
-                      'ml-auto h-3 w-3',
-                      selectedValue === getOptionValue(option) ? 'opacity-100' : 'opacity-0'
-                    )}
-                  />
-                </CommandItem>
-              ))}
+              {options.map((option, index) => {
+                const optionValue = getOptionValue(option);
+                // Use index as a safe value that won't be trimmed by cmdk
+                const safeValue = `option-${index}-${optionValue.length}`;
+
+                return (
+                  <CommandItem
+                    key={optionValue}
+                    value={safeValue}
+                    onSelect={(selectedSafeValue) => {
+                      // Extract the original value from the safe value
+                      const selectedIndex = parseInt(selectedSafeValue.split('-')[1]);
+                      const originalValue = getOptionValue(options[selectedIndex]);
+                      console.log(`CommandItem onSelect: safeValue='${selectedSafeValue}', originalValue='${originalValue}' (length: ${originalValue.length})`);
+                      handleSelect(originalValue);
+                    }}
+                    className="truncate"
+                  >
+                    {renderOption(option)}
+                    <Check
+                      className={cn(
+                        'ml-auto h-3 w-3',
+                        selectedValue === optionValue ? 'opacity-100' : 'opacity-0'
+                      )}
+                    />
+                  </CommandItem>
+                );
+              })}
             </CommandGroup>
           </CommandList>
         </Command>

From 8bab240dbc6ad16226de87c442a35558b501c1cb Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 31 Aug 2025 03:00:16 +0800
Subject: [PATCH 086/141] Update webui assets

---
 ...By-BEWgwF1U.js => _basePickBy-zcTWmF8I.js} |   2 +-
 ...Uniq-BrMEyGA7.js => _baseUniq-Coqzfado.js} |   2 +-
 ... architectureDiagram-SUXI7LT5-kgrRF4Cf.js} |   2 +-
 ...U.js => blockDiagram-6J76NXCF-Chfv6a7G.js} |   2 +-
 ...3Gt0.js => c4Diagram-6F6E4RAY-B4XUATl4.js} |   2 +-
 ...DAdaHWGH.js => chunk-353BL4L5-CR8qX5CO.js} |   2 +-
 ...CPez3pRp.js => chunk-67H74DCK-CIrK_RBz.js} |   2 +-
 ...CC5KzNO7.js => chunk-AACKK3MU-mRStUlsv.js} |   2 +-
 ...DQGv_fhY.js => chunk-BFAMUDN2-Cm57CA8s.js} |   2 +-
 ...DReIXiCg.js => chunk-E2GYISFI-Du9g7EeC.js} |   2 +-
 ...Bpuvralp.js => chunk-OW32GOEJ-C5pOkIhC.js} |   2 +-
 ...D-vU5iV6.js => chunk-SKB7J2MH-CX-6qXaF.js} |   2 +-
 ...9GI7VVtw.js => chunk-SZ463SBG-B3Q_dfR2.js} |   2 +-
 .../assets/classDiagram-M3E45YP4-CPlkaPl7.js  |   1 -
 .../assets/classDiagram-M3E45YP4-DKtAiWMM.js  |   1 +
 .../classDiagram-v2-YAWTLIQI-CPlkaPl7.js      |   1 -
 .../classDiagram-v2-YAWTLIQI-DKtAiWMM.js      |   1 +
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diff --git a/lightrag/api/webui/assets/architectureDiagram-SUXI7LT5-CiH8BWn1.js b/lightrag/api/webui/assets/architectureDiagram-SUXI7LT5-kgrRF4Cf.js
similarity index 99%
rename from lightrag/api/webui/assets/architectureDiagram-SUXI7LT5-CiH8BWn1.js
rename to lightrag/api/webui/assets/architectureDiagram-SUXI7LT5-kgrRF4Cf.js
index 2b7ad846..97cf44a6 100644
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+++ b/lightrag/api/webui/assets/architectureDiagram-SUXI7LT5-kgrRF4Cf.js
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this.rect.y+this.rect.height/2},i.prototype.getCenter=function(){return new f(this.rect.x+this.rect.width/2,this.rect.y+this.rect.height/2)},i.prototype.getLocation=function(){return new f(this.rect.x,this.rect.y)},i.prototype.getRect=function(){return this.rect},i.prototype.getDiagonal=function(){return Math.sqrt(this.rect.width*this.rect.width+this.rect.height*this.rect.height)},i.prototype.getHalfTheDiagonal=function(){return Math.sqrt(this.rect.height*this.rect.height+this.rect.width*this.rect.width)/2},i.prototype.setRect=function(t,s){this.rect.x=t.x,this.rect.y=t.y,this.rect.width=s.width,this.rect.height=s.height},i.prototype.setCenter=function(t,s){this.rect.x=t-this.rect.width/2,this.rect.y=s-this.rect.height/2},i.prototype.setLocation=function(t,s){this.rect.x=t,this.rect.y=s},i.prototype.moveBy=function(t,s){this.rect.x+=t,this.rect.y+=s},i.prototype.getEdgeListToNode=function(t){var s=[],o=this;return o.edges.forEach(function(c){if(c.target==t){if(c.source!=o)throw"Incorrect edge source!";s.push(c)}}),s},i.prototype.getEdgesBetween=function(t){var s=[],o=this;return o.edges.forEach(function(c){if(!(c.source==o||c.target==o))throw"Incorrect edge source and/or target";(c.target==t||c.source==t)&&s.push(c)}),s},i.prototype.getNeighborsList=function(){var t=new Set,s=this;return s.edges.forEach(function(o){if(o.source==s)t.add(o.target);else{if(o.target!=s)throw"Incorrect incidency!";t.add(o.source)}}),t},i.prototype.withChildren=function(){var t=new Set,s,o;if(t.add(this),this.child!=null)for(var c=this.child.getNodes(),h=0;h<c.length;h++)s=c[h],o=s.withChildren(),o.forEach(function(T){t.add(T)});return t},i.prototype.getNoOfChildren=function(){var t=0,s;if(this.child==null)t=1;else for(var o=this.child.getNodes(),c=0;c<o.length;c++)s=o[c],t+=s.getNoOfChildren();return t==0&&(t=1),t},i.prototype.getEstimatedSize=function(){if(this.estimatedSize==l.MIN_VALUE)throw"assert failed";return this.estimatedSize},i.prototype.calcEstimatedSize=function(){return this.child==null?this.estimatedSize=(this.rect.width+this.rect.height)/2:(this.estimatedSize=this.child.calcEstimatedSize(),this.rect.width=this.estimatedSize,this.rect.height=this.estimatedSize,this.estimatedSize)},i.prototype.scatter=function(){var t,s,o=-r.INITIAL_WORLD_BOUNDARY,c=r.INITIAL_WORLD_BOUNDARY;t=r.WORLD_CENTER_X+e.nextDouble()*(c-o)+o;var h=-r.INITIAL_WORLD_BOUNDARY,T=r.INITIAL_WORLD_BOUNDARY;s=r.WORLD_CENTER_Y+e.nextDouble()*(T-h)+h,this.rect.x=t,this.rect.y=s},i.prototype.updateBounds=function(){if(this.getChild()==null)throw"assert failed";if(this.getChild().getNodes().length!=0){var t=this.getChild();if(t.updateBounds(!0),this.rect.x=t.getLeft(),this.rect.y=t.getTop(),this.setWidth(t.getRight()-t.getLeft()),this.setHeight(t.getBottom()-t.getTop()),r.NODE_DIMENSIONS_INCLUDE_LABELS){var s=t.getRight()-t.getLeft(),o=t.getBottom()-t.getTop();this.labelWidth&&(this.labelPosHorizontal=="left"?(this.rect.x-=this.labelWidth,this.setWidth(s+this.labelWidth)):this.labelPosHorizontal=="center"&&this.labelWidth>s?(this.rect.x-=(this.labelWidth-s)/2,this.setWidth(this.labelWidth)):this.labelPosHorizontal=="right"&&this.setWidth(s+this.labelWidth)),this.labelHeight&&(this.labelPosVertical=="top"?(this.rect.y-=this.labelHeight,this.setHeight(o+this.labelHeight)):this.labelPosVertical=="center"&&this.labelHeight>o?(this.rect.y-=(this.labelHeight-o)/2,this.setHeight(this.labelHeight)):this.labelPosVertical=="bottom"&&this.setHeight(o+this.labelHeight))}}},i.prototype.getInclusionTreeDepth=function(){if(this.inclusionTreeDepth==l.MAX_VALUE)throw"assert failed";return this.inclusionTreeDepth},i.prototype.transform=function(t){var s=this.rect.x;s>r.WORLD_BOUNDARY?s=r.WORLD_BOUNDARY:s<-r.WORLD_BOUNDARY&&(s=-r.WORLD_BOUNDARY);var o=this.rect.y;o>r.WORLD_BOUNDARY?o=r.WORLD_BOUNDARY:o<-r.WORLD_BOUNDARY&&(o=-r.WORLD_BOUNDARY);var c=new f(s,o),h=t.inverseTransformPoint(c);this.setLocation(h.x,h.y)},i.prototype.getLeft=function(){return this.rect.x},i.prototype.getRight=function(){return this.rect.x+this.rect.width},i.prototype.getTop=function(){return this.rect.y},i.prototype.getBottom=function(){return this.rect.y+this.rect.height},i.prototype.getParent=function(){return this.owner==null?null:this.owner.getParent()},A.exports=i},function(A,G,L){var u=L(0);function l(){}for(var n in u)l[n]=u[n];l.MAX_ITERATIONS=2500,l.DEFAULT_EDGE_LENGTH=50,l.DEFAULT_SPRING_STRENGTH=.45,l.DEFAULT_REPULSION_STRENGTH=4500,l.DEFAULT_GRAVITY_STRENGTH=.4,l.DEFAULT_COMPOUND_GRAVITY_STRENGTH=1,l.DEFAULT_GRAVITY_RANGE_FACTOR=3.8,l.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR=1.5,l.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION=!0,l.DEFAULT_USE_SMART_REPULSION_RANGE_CALCULATION=!0,l.DEFAULT_COOLING_FACTOR_INCREMENTAL=.3,l.COOLING_ADAPTATION_FACTOR=.33,l.ADAPTATION_LOWER_NODE_LIMIT=1e3,l.ADAPTATION_UPPER_NODE_LIMIT=5e3,l.MAX_NODE_DISPLACEMENT_INCREMENTAL=100,l.MAX_NODE_DISPLACEMENT=l.MAX_NODE_DISPLACEMENT_INCREMENTAL*3,l.MIN_REPULSION_DIST=l.DEFAULT_EDGE_LENGTH/10,l.CONVERGENCE_CHECK_PERIOD=100,l.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR=.1,l.MIN_EDGE_LENGTH=1,l.GRID_CALCULATION_CHECK_PERIOD=10,A.exports=l},function(A,G,L){function u(l,n){l==null&&n==null?(this.x=0,this.y=0):(this.x=l,this.y=n)}u.prototype.getX=function(){return this.x},u.prototype.getY=function(){return this.y},u.prototype.setX=function(l){this.x=l},u.prototype.setY=function(l){this.y=l},u.prototype.getDifference=function(l){return new DimensionD(this.x-l.x,this.y-l.y)},u.prototype.getCopy=function(){return new u(this.x,this.y)},u.prototype.translate=function(l){return this.x+=l.width,this.y+=l.height,this},A.exports=u},function(A,G,L){var u=L(2),l=L(10),n=L(0),r=L(7),e=L(3),f=L(1),i=L(13),g=L(12),t=L(11);function s(c,h,T){u.call(this,T),this.estimatedSize=l.MIN_VALUE,this.margin=n.DEFAULT_GRAPH_MARGIN,this.edges=[],this.nodes=[],this.isConnected=!1,this.parent=c,h!=null&&h instanceof r?this.graphManager=h:h!=null&&h instanceof Layout&&(this.graphManager=h.graphManager)}s.prototype=Object.create(u.prototype);for(var o in u)s[o]=u[o];s.prototype.getNodes=function(){return this.nodes},s.prototype.getEdges=function(){return this.edges},s.prototype.getGraphManager=function(){return this.graphManager},s.prototype.getParent=function(){return this.parent},s.prototype.getLeft=function(){return this.left},s.prototype.getRight=function(){return this.right},s.prototype.getTop=function(){return this.top},s.prototype.getBottom=function(){return this.bottom},s.prototype.isConnected=function(){return this.isConnected},s.prototype.add=function(c,h,T){if(h==null&&T==null){var v=c;if(this.graphManager==null)throw"Graph has no graph mgr!";if(this.getNodes().indexOf(v)>-1)throw"Node already in graph!";return v.owner=this,this.getNodes().push(v),v}else{var d=c;if(!(this.getNodes().indexOf(h)>-1&&this.getNodes().indexOf(T)>-1))throw"Source or target not in graph!";if(!(h.owner==T.owner&&h.owner==this))throw"Both owners must be this graph!";return h.owner!=T.owner?null:(d.source=h,d.target=T,d.isInterGraph=!1,this.getEdges().push(d),h.edges.push(d),T!=h&&T.edges.push(d),d)}},s.prototype.remove=function(c){var h=c;if(c instanceof e){if(h==null)throw"Node is null!";if(!(h.owner!=null&&h.owner==this))throw"Owner graph is invalid!";if(this.graphManager==null)throw"Owner graph manager is invalid!";for(var T=h.edges.slice(),v,d=T.length,N=0;N<d;N++)v=T[N],v.isInterGraph?this.graphManager.remove(v):v.source.owner.remove(v);var S=this.nodes.indexOf(h);if(S==-1)throw"Node not in owner node list!";this.nodes.splice(S,1)}else if(c instanceof f){var v=c;if(v==null)throw"Edge is null!";if(!(v.source!=null&&v.target!=null))throw"Source and/or target is null!";if(!(v.source.owner!=null&&v.target.owner!=null&&v.source.owner==this&&v.target.owner==this))throw"Source and/or target owner is invalid!";var M=v.source.edges.indexOf(v),P=v.target.edges.indexOf(v);if(!(M>-1&&P>-1))throw"Source and/or target doesn't know this edge!";v.source.edges.splice(M,1),v.target!=v.source&&v.target.edges.splice(P,1);var S=v.source.owner.getEdges().indexOf(v);if(S==-1)throw"Not in owner's edge list!";v.source.owner.getEdges().splice(S,1)}},s.prototype.updateLeftTop=function(){for(var c=l.MAX_VALUE,h=l.MAX_VALUE,T,v,d,N=this.getNodes(),S=N.length,M=0;M<S;M++){var P=N[M];T=P.getTop(),v=P.getLeft(),c>T&&(c=T),h>v&&(h=v)}return c==l.MAX_VALUE?null:(N[0].getParent().paddingLeft!=null?d=N[0].getParent().paddingLeft:d=this.margin,this.left=h-d,this.top=c-d,new g(this.left,this.top))},s.prototype.updateBounds=function(c){for(var h=l.MAX_VALUE,T=-l.MAX_VALUE,v=l.MAX_VALUE,d=-l.MAX_VALUE,N,S,M,P,K,Y=this.nodes,k=Y.length,D=0;D<k;D++){var rt=Y[D];c&&rt.child!=null&&rt.updateBounds(),N=rt.getLeft(),S=rt.getRight(),M=rt.getTop(),P=rt.getBottom(),h>N&&(h=N),T<S&&(T=S),v>M&&(v=M),d<P&&(d=P)}var a=new i(h,v,T-h,d-v);h==l.MAX_VALUE&&(this.left=this.parent.getLeft(),this.right=this.parent.getRight(),this.top=this.parent.getTop(),this.bottom=this.parent.getBottom()),Y[0].getParent().paddingLeft!=null?K=Y[0].getParent().paddingLeft:K=this.margin,this.left=a.x-K,this.right=a.x+a.width+K,this.top=a.y-K,this.bottom=a.y+a.height+K},s.calculateBounds=function(c){for(var h=l.MAX_VALUE,T=-l.MAX_VALUE,v=l.MAX_VALUE,d=-l.MAX_VALUE,N,S,M,P,K=c.length,Y=0;Y<K;Y++){var k=c[Y];N=k.getLeft(),S=k.getRight(),M=k.getTop(),P=k.getBottom(),h>N&&(h=N),T<S&&(T=S),v>M&&(v=M),d<P&&(d=P)}var D=new i(h,v,T-h,d-v);return D},s.prototype.getInclusionTreeDepth=function(){return this==this.graphManager.getRoot()?1:this.parent.getInclusionTreeDepth()},s.prototype.getEstimatedSize=function(){if(this.estimatedSize==l.MIN_VALUE)throw"assert failed";return this.estimatedSize},s.prototype.calcEstimatedSize=function(){for(var c=0,h=this.nodes,T=h.length,v=0;v<T;v++){var d=h[v];c+=d.calcEstimatedSize()}return c==0?this.estimatedSize=n.EMPTY_COMPOUND_NODE_SIZE:this.estimatedSize=c/Math.sqrt(this.nodes.length),this.estimatedSize},s.prototype.updateConnected=function(){var c=this;if(this.nodes.length==0){this.isConnected=!0;return}var h=new t,T=new Set,v=this.nodes[0],d,N,S=v.withChildren();for(S.forEach(function(D){h.push(D),T.add(D)});h.length!==0;){v=h.shift(),d=v.getEdges();for(var M=d.length,P=0;P<M;P++){var K=d[P];if(N=K.getOtherEndInGraph(v,this),N!=null&&!T.has(N)){var Y=N.withChildren();Y.forEach(function(D){h.push(D),T.add(D)})}}}if(this.isConnected=!1,T.size>=this.nodes.length){var k=0;T.forEach(function(D){D.owner==c&&k++}),k==this.nodes.length&&(this.isConnected=!0)}},A.exports=s},function(A,G,L){var u,l=L(1);function n(r){u=L(6),this.layout=r,this.graphs=[],this.edges=[]}n.prototype.addRoot=function(){var r=this.layout.newGraph(),e=this.layout.newNode(null),f=this.add(r,e);return this.setRootGraph(f),this.rootGraph},n.prototype.add=function(r,e,f,i,g){if(f==null&&i==null&&g==null){if(r==null)throw"Graph is null!";if(e==null)throw"Parent node is null!";if(this.graphs.indexOf(r)>-1)throw"Graph already in this graph mgr!";if(this.graphs.push(r),r.parent!=null)throw"Already has a parent!";if(e.child!=null)throw"Already has a child!";return r.parent=e,e.child=r,r}else{g=f,i=e,f=r;var t=i.getOwner(),s=g.getOwner();if(!(t!=null&&t.getGraphManager()==this))throw"Source not in this graph mgr!";if(!(s!=null&&s.getGraphManager()==this))throw"Target not in this graph mgr!";if(t==s)return f.isInterGraph=!1,t.add(f,i,g);if(f.isInterGraph=!0,f.source=i,f.target=g,this.edges.indexOf(f)>-1)throw"Edge already in inter-graph edge list!";if(this.edges.push(f),!(f.source!=null&&f.target!=null))throw"Edge source and/or target is null!";if(!(f.source.edges.indexOf(f)==-1&&f.target.edges.indexOf(f)==-1))throw"Edge already in source and/or target incidency list!";return f.source.edges.push(f),f.target.edges.push(f),f}},n.prototype.remove=function(r){if(r instanceof u){var e=r;if(e.getGraphManager()!=this)throw"Graph not in this graph mgr";if(!(e==this.rootGraph||e.parent!=null&&e.parent.graphManager==this))throw"Invalid parent node!";var f=[];f=f.concat(e.getEdges());for(var i,g=f.length,t=0;t<g;t++)i=f[t],e.remove(i);var s=[];s=s.concat(e.getNodes());var o;g=s.length;for(var t=0;t<g;t++)o=s[t],e.remove(o);e==this.rootGraph&&this.setRootGraph(null);var c=this.graphs.indexOf(e);this.graphs.splice(c,1),e.parent=null}else if(r instanceof l){if(i=r,i==null)throw"Edge is null!";if(!i.isInterGraph)throw"Not an inter-graph edge!";if(!(i.source!=null&&i.target!=null))throw"Source and/or target is null!";if(!(i.source.edges.indexOf(i)!=-1&&i.target.edges.indexOf(i)!=-1))throw"Source and/or target doesn't know this edge!";var c=i.source.edges.indexOf(i);if(i.source.edges.splice(c,1),c=i.target.edges.indexOf(i),i.target.edges.splice(c,1),!(i.source.owner!=null&&i.source.owner.getGraphManager()!=null))throw"Edge owner graph or owner graph manager is null!";if(i.source.owner.getGraphManager().edges.indexOf(i)==-1)throw"Not in owner graph manager's edge list!";var c=i.source.owner.getGraphManager().edges.indexOf(i);i.source.owner.getGraphManager().edges.splice(c,1)}},n.prototype.updateBounds=function(){this.rootGraph.updateBounds(!0)},n.prototype.getGraphs=function(){return this.graphs},n.prototype.getAllNodes=function(){if(this.allNodes==null){for(var r=[],e=this.getGraphs(),f=e.length,i=0;i<f;i++)r=r.concat(e[i].getNodes());this.allNodes=r}return this.allNodes},n.prototype.resetAllNodes=function(){this.allNodes=null},n.prototype.resetAllEdges=function(){this.allEdges=null},n.prototype.resetAllNodesToApplyGravitation=function(){this.allNodesToApplyGravitation=null},n.prototype.getAllEdges=function(){if(this.allEdges==null){var r=[],e=this.getGraphs();e.length;for(var f=0;f<e.length;f++)r=r.concat(e[f].getEdges());r=r.concat(this.edges),this.allEdges=r}return this.allEdges},n.prototype.getAllNodesToApplyGravitation=function(){return this.allNodesToApplyGravitation},n.prototype.setAllNodesToApplyGravitation=function(r){if(this.allNodesToApplyGravitation!=null)throw"assert failed";this.allNodesToApplyGravitation=r},n.prototype.getRoot=function(){return this.rootGraph},n.prototype.setRootGraph=function(r){if(r.getGraphManager()!=this)throw"Root not in this graph mgr!";this.rootGraph=r,r.parent==null&&(r.parent=this.layout.newNode("Root node"))},n.prototype.getLayout=function(){return this.layout},n.prototype.isOneAncestorOfOther=function(r,e){if(!(r!=null&&e!=null))throw"assert failed";if(r==e)return!0;var f=r.getOwner(),i;do{if(i=f.getParent(),i==null)break;if(i==e)return!0;if(f=i.getOwner(),f==null)break}while(!0);f=e.getOwner();do{if(i=f.getParent(),i==null)break;if(i==r)return!0;if(f=i.getOwner(),f==null)break}while(!0);return!1},n.prototype.calcLowestCommonAncestors=function(){for(var r,e,f,i,g,t=this.getAllEdges(),s=t.length,o=0;o<s;o++){if(r=t[o],e=r.source,f=r.target,r.lca=null,r.sourceInLca=e,r.targetInLca=f,e==f){r.lca=e.getOwner();continue}for(i=e.getOwner();r.lca==null;){for(r.targetInLca=f,g=f.getOwner();r.lca==null;){if(g==i){r.lca=g;break}if(g==this.rootGraph)break;if(r.lca!=null)throw"assert failed";r.targetInLca=g.getParent(),g=r.targetInLca.getOwner()}if(i==this.rootGraph)break;r.lca==null&&(r.sourceInLca=i.getParent(),i=r.sourceInLca.getOwner())}if(r.lca==null)throw"assert failed"}},n.prototype.calcLowestCommonAncestor=function(r,e){if(r==e)return r.getOwner();var f=r.getOwner();do{if(f==null)break;var i=e.getOwner();do{if(i==null)break;if(i==f)return i;i=i.getParent().getOwner()}while(!0);f=f.getParent().getOwner()}while(!0);return f},n.prototype.calcInclusionTreeDepths=function(r,e){r==null&&e==null&&(r=this.rootGraph,e=1);for(var f,i=r.getNodes(),g=i.length,t=0;t<g;t++)f=i[t],f.inclusionTreeDepth=e,f.child!=null&&this.calcInclusionTreeDepths(f.child,e+1)},n.prototype.includesInvalidEdge=function(){for(var r,e=[],f=this.edges.length,i=0;i<f;i++)r=this.edges[i],this.isOneAncestorOfOther(r.source,r.target)&&e.push(r);for(var i=0;i<e.length;i++)this.remove(e[i]);return!1},A.exports=n},function(A,G,L){var u=L(12);function l(){}l.calcSeparationAmount=function(n,r,e,f){if(!n.intersects(r))throw"assert failed";var i=new Array(2);this.decideDirectionsForOverlappingNodes(n,r,i),e[0]=Math.min(n.getRight(),r.getRight())-Math.max(n.x,r.x),e[1]=Math.min(n.getBottom(),r.getBottom())-Math.max(n.y,r.y),n.getX()<=r.getX()&&n.getRight()>=r.getRight()?e[0]+=Math.min(r.getX()-n.getX(),n.getRight()-r.getRight()):r.getX()<=n.getX()&&r.getRight()>=n.getRight()&&(e[0]+=Math.min(n.getX()-r.getX(),r.getRight()-n.getRight())),n.getY()<=r.getY()&&n.getBottom()>=r.getBottom()?e[1]+=Math.min(r.getY()-n.getY(),n.getBottom()-r.getBottom()):r.getY()<=n.getY()&&r.getBottom()>=n.getBottom()&&(e[1]+=Math.min(n.getY()-r.getY(),r.getBottom()-n.getBottom()));var g=Math.abs((r.getCenterY()-n.getCenterY())/(r.getCenterX()-n.getCenterX()));r.getCenterY()===n.getCenterY()&&r.getCenterX()===n.getCenterX()&&(g=1);var t=g*e[0],s=e[1]/g;e[0]<s?s=e[0]:t=e[1],e[0]=-1*i[0]*(s/2+f),e[1]=-1*i[1]*(t/2+f)},l.decideDirectionsForOverlappingNodes=function(n,r,e){n.getCenterX()<r.getCenterX()?e[0]=-1:e[0]=1,n.getCenterY()<r.getCenterY()?e[1]=-1:e[1]=1},l.getIntersection2=function(n,r,e){var f=n.getCenterX(),i=n.getCenterY(),g=r.getCenterX(),t=r.getCenterY();if(n.intersects(r))return e[0]=f,e[1]=i,e[2]=g,e[3]=t,!0;var s=n.getX(),o=n.getY(),c=n.getRight(),h=n.getX(),T=n.getBottom(),v=n.getRight(),d=n.getWidthHalf(),N=n.getHeightHalf(),S=r.getX(),M=r.getY(),P=r.getRight(),K=r.getX(),Y=r.getBottom(),k=r.getRight(),D=r.getWidthHalf(),rt=r.getHeightHalf(),a=!1,m=!1;if(f===g){if(i>t)return e[0]=f,e[1]=o,e[2]=g,e[3]=Y,!1;if(i<t)return e[0]=f,e[1]=T,e[2]=g,e[3]=M,!1}else if(i===t){if(f>g)return e[0]=s,e[1]=i,e[2]=P,e[3]=t,!1;if(f<g)return e[0]=c,e[1]=i,e[2]=S,e[3]=t,!1}else{var p=n.height/n.width,E=r.height/r.width,y=(t-i)/(g-f),I=void 0,w=void 0,R=void 0,W=void 0,x=void 0,q=void 0;if(-p===y?f>g?(e[0]=h,e[1]=T,a=!0):(e[0]=c,e[1]=o,a=!0):p===y&&(f>g?(e[0]=s,e[1]=o,a=!0):(e[0]=v,e[1]=T,a=!0)),-E===y?g>f?(e[2]=K,e[3]=Y,m=!0):(e[2]=P,e[3]=M,m=!0):E===y&&(g>f?(e[2]=S,e[3]=M,m=!0):(e[2]=k,e[3]=Y,m=!0)),a&&m)return!1;if(f>g?i>t?(I=this.getCardinalDirection(p,y,4),w=this.getCardinalDirection(E,y,2)):(I=this.getCardinalDirection(-p,y,3),w=this.getCardinalDirection(-E,y,1)):i>t?(I=this.getCardinalDirection(-p,y,1),w=this.getCardinalDirection(-E,y,3)):(I=this.getCardinalDirection(p,y,2),w=this.getCardinalDirection(E,y,4)),!a)switch(I){case 1:W=o,R=f+-N/y,e[0]=R,e[1]=W;break;case 2:R=v,W=i+d*y,e[0]=R,e[1]=W;break;case 3:W=T,R=f+N/y,e[0]=R,e[1]=W;break;case 4:R=h,W=i+-d*y,e[0]=R,e[1]=W;break}if(!m)switch(w){case 1:q=M,x=g+-rt/y,e[2]=x,e[3]=q;break;case 2:x=k,q=t+D*y,e[2]=x,e[3]=q;break;case 3:q=Y,x=g+rt/y,e[2]=x,e[3]=q;break;case 4:x=K,q=t+-D*y,e[2]=x,e[3]=q;break}}return!1},l.getCardinalDirection=function(n,r,e){return 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this.lworldOrgX},l.prototype.setWorldOrgX=function(n){this.lworldOrgX=n},l.prototype.getWorldOrgY=function(){return this.lworldOrgY},l.prototype.setWorldOrgY=function(n){this.lworldOrgY=n},l.prototype.getWorldExtX=function(){return this.lworldExtX},l.prototype.setWorldExtX=function(n){this.lworldExtX=n},l.prototype.getWorldExtY=function(){return this.lworldExtY},l.prototype.setWorldExtY=function(n){this.lworldExtY=n},l.prototype.getDeviceOrgX=function(){return this.ldeviceOrgX},l.prototype.setDeviceOrgX=function(n){this.ldeviceOrgX=n},l.prototype.getDeviceOrgY=function(){return this.ldeviceOrgY},l.prototype.setDeviceOrgY=function(n){this.ldeviceOrgY=n},l.prototype.getDeviceExtX=function(){return this.ldeviceExtX},l.prototype.setDeviceExtX=function(n){this.ldeviceExtX=n},l.prototype.getDeviceExtY=function(){return this.ldeviceExtY},l.prototype.setDeviceExtY=function(n){this.ldeviceExtY=n},l.prototype.transformX=function(n){var r=0,e=this.lworldExtX;return 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i(){l.call(this),this.useSmartIdealEdgeLengthCalculation=n.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION,this.gravityConstant=n.DEFAULT_GRAVITY_STRENGTH,this.compoundGravityConstant=n.DEFAULT_COMPOUND_GRAVITY_STRENGTH,this.gravityRangeFactor=n.DEFAULT_GRAVITY_RANGE_FACTOR,this.compoundGravityRangeFactor=n.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR,this.displacementThresholdPerNode=3*n.DEFAULT_EDGE_LENGTH/100,this.coolingFactor=n.DEFAULT_COOLING_FACTOR_INCREMENTAL,this.initialCoolingFactor=n.DEFAULT_COOLING_FACTOR_INCREMENTAL,this.totalDisplacement=0,this.oldTotalDisplacement=0,this.maxIterations=n.MAX_ITERATIONS}i.prototype=Object.create(l.prototype);for(var g in l)i[g]=l[g];i.prototype.initParameters=function(){l.prototype.initParameters.call(this,arguments),this.totalIterations=0,this.notAnimatedIterations=0,this.useFRGridVariant=n.DEFAULT_USE_SMART_REPULSION_RANGE_CALCULATION,this.grid=[]},i.prototype.calcIdealEdgeLengths=function(){for(var t,s,o,c,h,T,v,d=this.getGraphManager().getAllEdges(),N=0;N<d.length;N++)t=d[N],s=t.idealLength,t.isInterGraph&&(c=t.getSource(),h=t.getTarget(),T=t.getSourceInLca().getEstimatedSize(),v=t.getTargetInLca().getEstimatedSize(),this.useSmartIdealEdgeLengthCalculation&&(t.idealLength+=T+v-2*r.SIMPLE_NODE_SIZE),o=t.getLca().getInclusionTreeDepth(),t.idealLength+=s*n.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR*(c.getInclusionTreeDepth()+h.getInclusionTreeDepth()-2*o))},i.prototype.initSpringEmbedder=function(){var t=this.getAllNodes().length;this.incremental?(t>n.ADAPTATION_LOWER_NODE_LIMIT&&(this.coolingFactor=Math.max(this.coolingFactor*n.COOLING_ADAPTATION_FACTOR,this.coolingFactor-(t-n.ADAPTATION_LOWER_NODE_LIMIT)/(n.ADAPTATION_UPPER_NODE_LIMIT-n.ADAPTATION_LOWER_NODE_LIMIT)*this.coolingFactor*(1-n.COOLING_ADAPTATION_FACTOR))),this.maxNodeDisplacement=n.MAX_NODE_DISPLACEMENT_INCREMENTAL):(t>n.ADAPTATION_LOWER_NODE_LIMIT?this.coolingFactor=Math.max(n.COOLING_ADAPTATION_FACTOR,1-(t-n.ADAPTATION_LOWER_NODE_LIMIT)/(n.ADAPTATION_UPPER_NODE_LIMIT-n.ADAPTATION_LOWER_NODE_LIMIT)*(1-n.COOLING_ADAPTATION_FACTOR)):this.coolingFactor=1,this.initialCoolingFactor=this.coolingFactor,this.maxNodeDisplacement=n.MAX_NODE_DISPLACEMENT),this.maxIterations=Math.max(this.getAllNodes().length*5,this.maxIterations),this.displacementThresholdPerNode=3*n.DEFAULT_EDGE_LENGTH/100,this.totalDisplacementThreshold=this.displacementThresholdPerNode*this.getAllNodes().length,this.repulsionRange=this.calcRepulsionRange()},i.prototype.calcSpringForces=function(){for(var t=this.getAllEdges(),s,o=0;o<t.length;o++)s=t[o],this.calcSpringForce(s,s.idealLength)},i.prototype.calcRepulsionForces=function(){var t=arguments.length>0&&arguments[0]!==void 0?arguments[0]:!0,s=arguments.length>1&&arguments[1]!==void 0?arguments[1]:!1,o,c,h,T,v=this.getAllNodes(),d;if(this.useFRGridVariant)for(this.totalIterations%n.GRID_CALCULATION_CHECK_PERIOD==1&&t&&this.updateGrid(),d=new Set,o=0;o<v.length;o++)h=v[o],this.calculateRepulsionForceOfANode(h,d,t,s),d.add(h);else for(o=0;o<v.length;o++)for(h=v[o],c=o+1;c<v.length;c++)T=v[c],h.getOwner()==T.getOwner()&&this.calcRepulsionForce(h,T)},i.prototype.calcGravitationalForces=function(){for(var t,s=this.getAllNodesToApplyGravitation(),o=0;o<s.length;o++)t=s[o],this.calcGravitationalForce(t)},i.prototype.moveNodes=function(){for(var t=this.getAllNodes(),s,o=0;o<t.length;o++)s=t[o],s.move()},i.prototype.calcSpringForce=function(t,s){var o=t.getSource(),c=t.getTarget(),h,T,v,d;if(this.uniformLeafNodeSizes&&o.getChild()==null&&c.getChild()==null)t.updateLengthSimple();else if(t.updateLength(),t.isOverlapingSourceAndTarget)return;h=t.getLength(),h!=0&&(T=t.edgeElasticity*(h-s),v=T*(t.lengthX/h),d=T*(t.lengthY/h),o.springForceX+=v,o.springForceY+=d,c.springForceX-=v,c.springForceY-=d)},i.prototype.calcRepulsionForce=function(t,s){var o=t.getRect(),c=s.getRect(),h=new Array(2),T=new Array(4),v,d,N,S,M,P,K;if(o.intersects(c)){e.calcSeparationAmount(o,c,h,n.DEFAULT_EDGE_LENGTH/2),P=2*h[0],K=2*h[1];var Y=t.noOfChildren*s.noOfChildren/(t.noOfChildren+s.noOfChildren);t.repulsionForceX-=Y*P,t.repulsionForceY-=Y*K,s.repulsionForceX+=Y*P,s.repulsionForceY+=Y*K}else this.uniformLeafNodeSizes&&t.getChild()==null&&s.getChild()==null?(v=c.getCenterX()-o.getCenterX(),d=c.getCenterY()-o.getCenterY()):(e.getIntersection(o,c,T),v=T[2]-T[0],d=T[3]-T[1]),Math.abs(v)<n.MIN_REPULSION_DIST&&(v=f.sign(v)*n.MIN_REPULSION_DIST),Math.abs(d)<n.MIN_REPULSION_DIST&&(d=f.sign(d)*n.MIN_REPULSION_DIST),N=v*v+d*d,S=Math.sqrt(N),M=(t.nodeRepulsion/2+s.nodeRepulsion/2)*t.noOfChildren*s.noOfChildren/N,P=M*v/S,K=M*d/S,t.repulsionForceX-=P,t.repulsionForceY-=K,s.repulsionForceX+=P,s.repulsionForceY+=K},i.prototype.calcGravitationalForce=function(t){var s,o,c,h,T,v,d,N;s=t.getOwner(),o=(s.getRight()+s.getLeft())/2,c=(s.getTop()+s.getBottom())/2,h=t.getCenterX()-o,T=t.getCenterY()-c,v=Math.abs(h)+t.getWidth()/2,d=Math.abs(T)+t.getHeight()/2,t.getOwner()==this.graphManager.getRoot()?(N=s.getEstimatedSize()*this.gravityRangeFactor,(v>N||d>N)&&(t.gravitationForceX=-this.gravityConstant*h,t.gravitationForceY=-this.gravityConstant*T)):(N=s.getEstimatedSize()*this.compoundGravityRangeFactor,(v>N||d>N)&&(t.gravitationForceX=-this.gravityConstant*h*this.compoundGravityConstant,t.gravitationForceY=-this.gravityConstant*T*this.compoundGravityConstant))},i.prototype.isConverged=function(){var t,s=!1;return this.totalIterations>this.maxIterations/3&&(s=Math.abs(this.totalDisplacement-this.oldTotalDisplacement)<2),t=this.totalDisplacement<this.totalDisplacementThreshold,this.oldTotalDisplacement=this.totalDisplacement,t||s},i.prototype.animate=function(){this.animationDuringLayout&&!this.isSubLayout&&(this.notAnimatedIterations==this.animationPeriod?(this.update(),this.notAnimatedIterations=0):this.notAnimatedIterations++)},i.prototype.calcNoOfChildrenForAllNodes=function(){for(var t,s=this.graphManager.getAllNodes(),o=0;o<s.length;o++)t=s[o],t.noOfChildren=t.getNoOfChildren()},i.prototype.calcGrid=function(t){var s=0,o=0;s=parseInt(Math.ceil((t.getRight()-t.getLeft())/this.repulsionRange)),o=parseInt(Math.ceil((t.getBottom()-t.getTop())/this.repulsionRange));for(var c=new Array(s),h=0;h<s;h++)c[h]=new Array(o);for(var h=0;h<s;h++)for(var T=0;T<o;T++)c[h][T]=new Array;return c},i.prototype.addNodeToGrid=function(t,s,o){var c=0,h=0,T=0,v=0;c=parseInt(Math.floor((t.getRect().x-s)/this.repulsionRange)),h=parseInt(Math.floor((t.getRect().width+t.getRect().x-s)/this.repulsionRange)),T=parseInt(Math.floor((t.getRect().y-o)/this.repulsionRange)),v=parseInt(Math.floor((t.getRect().height+t.getRect().y-o)/this.repulsionRange));for(var d=c;d<=h;d++)for(var N=T;N<=v;N++)this.grid[d][N].push(t),t.setGridCoordinates(c,h,T,v)},i.prototype.updateGrid=function(){var t,s,o=this.getAllNodes();for(this.grid=this.calcGrid(this.graphManager.getRoot()),t=0;t<o.length;t++)s=o[t],this.addNodeToGrid(s,this.graphManager.getRoot().getLeft(),this.graphManager.getRoot().getTop())},i.prototype.calculateRepulsionForceOfANode=function(t,s,o,c){if(this.totalIterations%n.GRID_CALCULATION_CHECK_PERIOD==1&&o||c){var h=new Set;t.surrounding=new Array;for(var T,v=this.grid,d=t.startX-1;d<t.finishX+2;d++)for(var N=t.startY-1;N<t.finishY+2;N++)if(!(d<0||N<0||d>=v.length||N>=v[0].length)){for(var S=0;S<v[d][N].length;S++)if(T=v[d][N][S],!(t.getOwner()!=T.getOwner()||t==T)&&!s.has(T)&&!h.has(T)){var M=Math.abs(t.getCenterX()-T.getCenterX())-(t.getWidth()/2+T.getWidth()/2),P=Math.abs(t.getCenterY()-T.getCenterY())-(t.getHeight()/2+T.getHeight()/2);M<=this.repulsionRange&&P<=this.repulsionRange&&h.add(T)}}t.surrounding=[].concat(u(h))}for(d=0;d<t.surrounding.length;d++)this.calcRepulsionForce(t,t.surrounding[d])},i.prototype.calcRepulsionRange=function(){return 0},A.exports=i},function(A,G,L){var u=L(1),l=L(4);function n(e,f,i){u.call(this,e,f,i),this.idealLength=l.DEFAULT_EDGE_LENGTH,this.edgeElasticity=l.DEFAULT_SPRING_STRENGTH}n.prototype=Object.create(u.prototype);for(var r in u)n[r]=u[r];A.exports=n},function(A,G,L){var u=L(3),l=L(4);function n(e,f,i,g){u.call(this,e,f,i,g),this.nodeRepulsion=l.DEFAULT_REPULSION_STRENGTH,this.springForceX=0,this.springForceY=0,this.repulsionForceX=0,this.repulsionForceY=0,this.gravitationForceX=0,this.gravitationForceY=0,this.displacementX=0,this.displacementY=0,this.startX=0,this.finishX=0,this.startY=0,this.finishY=0,this.surrounding=[]}n.prototype=Object.create(u.prototype);for(var r in u)n[r]=u[r];n.prototype.setGridCoordinates=function(e,f,i,g){this.startX=e,this.finishX=f,this.startY=i,this.finishY=g},A.exports=n},function(A,G,L){function u(l,n){this.width=0,this.height=0,l!==null&&n!==null&&(this.height=n,this.width=l)}u.prototype.getWidth=function(){return this.width},u.prototype.setWidth=function(l){this.width=l},u.prototype.getHeight=function(){return this.height},u.prototype.setHeight=function(l){this.height=l},A.exports=u},function(A,G,L){var u=L(14);function l(){this.map={},this.keys=[]}l.prototype.put=function(n,r){var e=u.createID(n);this.contains(e)||(this.map[e]=r,this.keys.push(n))},l.prototype.contains=function(n){return u.createID(n),this.map[n]!=null},l.prototype.get=function(n){var r=u.createID(n);return this.map[r]},l.prototype.keySet=function(){return this.keys},A.exports=l},function(A,G,L){var u=L(14);function l(){this.set={}}l.prototype.add=function(n){var r=u.createID(n);this.contains(r)||(this.set[r]=n)},l.prototype.remove=function(n){delete this.set[u.createID(n)]},l.prototype.clear=function(){this.set={}},l.prototype.contains=function(n){return this.set[u.createID(n)]==n},l.prototype.isEmpty=function(){return this.size()===0},l.prototype.size=function(){return Object.keys(this.set).length},l.prototype.addAllTo=function(n){for(var r=Object.keys(this.set),e=r.length,f=0;f<e;f++)n.push(this.set[r[f]])},l.prototype.size=function(){return Object.keys(this.set).length},l.prototype.addAll=function(n){for(var r=n.length,e=0;e<r;e++){var f=n[e];this.add(f)}},A.exports=l},function(A,G,L){function u(){}u.multMat=function(l,n){for(var r=[],e=0;e<l.length;e++){r[e]=[];for(var f=0;f<n[0].length;f++){r[e][f]=0;for(var i=0;i<l[0].length;i++)r[e][f]+=l[e][i]*n[i][f]}}return r},u.transpose=function(l){for(var n=[],r=0;r<l[0].length;r++){n[r]=[];for(var e=0;e<l.length;e++)n[r][e]=l[e][r]}return n},u.multCons=function(l,n){for(var r=[],e=0;e<l.length;e++)r[e]=l[e]*n;return r},u.minusOp=function(l,n){for(var r=[],e=0;e<l.length;e++)r[e]=l[e]-n[e];return r},u.dotProduct=function(l,n){for(var r=0,e=0;e<l.length;e++)r+=l[e]*n[e];return r},u.mag=function(l){return Math.sqrt(this.dotProduct(l,l))},u.normalize=function(l){for(var n=[],r=this.mag(l),e=0;e<l.length;e++)n[e]=l[e]/r;return n},u.multGamma=function(l){for(var n=[],r=0,e=0;e<l.length;e++)r+=l[e];r*=-1/l.length;for(var f=0;f<l.length;f++)n[f]=r+l[f];return n},u.multL=function(l,n,r){for(var e=[],f=[],i=[],g=0;g<n[0].length;g++){for(var t=0,s=0;s<n.length;s++)t+=-.5*n[s][g]*l[s];f[g]=t}for(var o=0;o<r.length;o++){for(var c=0,h=0;h<r.length;h++)c+=r[o][h]*f[h];i[o]=c}for(var T=0;T<n.length;T++){for(var v=0,d=0;d<n[0].length;d++)v+=n[T][d]*i[d];e[T]=v}return e},A.exports=u},function(A,G,L){var u=function(){function e(f,i){for(var g=0;g<i.length;g++){var t=i[g];t.enumerable=t.enumerable||!1,t.configurable=!0,"value"in t&&(t.writable=!0),Object.defineProperty(f,t.key,t)}}return function(f,i,g){return i&&e(f.prototype,i),g&&e(f,g),f}}();function l(e,f){if(!(e instanceof f))throw new TypeError("Cannot call a class as a function")}var n=L(11),r=function(){function e(f,i){l(this,e),(i!==null||i!==void 0)&&(this.compareFunction=this._defaultCompareFunction);var g=void 0;f instanceof n?g=f.size():g=f.length,this._quicksort(f,0,g-1)}return u(e,[{key:"_quicksort",value:function(i,g,t){if(g<t){var s=this._partition(i,g,t);this._quicksort(i,g,s),this._quicksort(i,s+1,t)}}},{key:"_partition",value:function(i,g,t){for(var s=this._get(i,g),o=g,c=t;;){for(;this.compareFunction(s,this._get(i,c));)c--;for(;this.compareFunction(this._get(i,o),s);)o++;if(o<c)this._swap(i,o,c),o++,c--;else return c}}},{key:"_get",value:function(i,g){return i instanceof n?i.get_object_at(g):i[g]}},{key:"_set",value:function(i,g,t){i instanceof n?i.set_object_at(g,t):i[g]=t}},{key:"_swap",value:function(i,g,t){var s=this._get(i,g);this._set(i,g,this._get(i,t)),this._set(i,t,s)}},{key:"_defaultCompareFunction",value:function(i,g){return g>i}}]),e}();A.exports=r},function(A,G,L){function u(){}u.svd=function(l){this.U=null,this.V=null,this.s=null,this.m=0,this.n=0,this.m=l.length,this.n=l[0].length;var n=Math.min(this.m,this.n);this.s=function(Nt){for(var Mt=[];Nt-- >0;)Mt.push(0);return Mt}(Math.min(this.m+1,this.n)),this.U=function(Nt){var Mt=function Zt(Gt){if(Gt.length==0)return 0;for(var $t=[],Ft=0;Ft<Gt[0];Ft++)$t.push(Zt(Gt.slice(1)));return $t};return Mt(Nt)}([this.m,n]),this.V=function(Nt){var Mt=function Zt(Gt){if(Gt.length==0)return 0;for(var $t=[],Ft=0;Ft<Gt[0];Ft++)$t.push(Zt(Gt.slice(1)));return $t};return Mt(Nt)}([this.n,this.n]);for(var r=function(Nt){for(var Mt=[];Nt-- >0;)Mt.push(0);return Mt}(this.n),e=function(Nt){for(var Mt=[];Nt-- >0;)Mt.push(0);return Mt}(this.m),f=!0,i=Math.min(this.m-1,this.n),g=Math.max(0,Math.min(this.n-2,this.m)),t=0;t<Math.max(i,g);t++){if(t<i){this.s[t]=0;for(var s=t;s<this.m;s++)this.s[t]=u.hypot(this.s[t],l[s][t]);if(this.s[t]!==0){l[t][t]<0&&(this.s[t]=-this.s[t]);for(var o=t;o<this.m;o++)l[o][t]/=this.s[t];l[t][t]+=1}this.s[t]=-this.s[t]}for(var c=t+1;c<this.n;c++){if(function(Nt,Mt){return Nt&&Mt}(t<i,this.s[t]!==0)){for(var h=0,T=t;T<this.m;T++)h+=l[T][t]*l[T][c];h=-h/l[t][t];for(var v=t;v<this.m;v++)l[v][c]+=h*l[v][t]}r[c]=l[t][c]}if(function(Nt,Mt){return Mt}(f,t<i))for(var d=t;d<this.m;d++)this.U[d][t]=l[d][t];if(t<g){r[t]=0;for(var N=t+1;N<this.n;N++)r[t]=u.hypot(r[t],r[N]);if(r[t]!==0){r[t+1]<0&&(r[t]=-r[t]);for(var S=t+1;S<this.n;S++)r[S]/=r[t];r[t+1]+=1}if(r[t]=-r[t],function(Nt,Mt){return Nt&&Mt}(t+1<this.m,r[t]!==0)){for(var M=t+1;M<this.m;M++)e[M]=0;for(var P=t+1;P<this.n;P++)for(var K=t+1;K<this.m;K++)e[K]+=r[P]*l[K][P];for(var Y=t+1;Y<this.n;Y++)for(var k=-r[Y]/r[t+1],D=t+1;D<this.m;D++)l[D][Y]+=k*e[D]}for(var rt=t+1;rt<this.n;rt++)this.V[rt][t]=r[rt]}}var a=Math.min(this.n,this.m+1);i<this.n&&(this.s[i]=l[i][i]),this.m<a&&(this.s[a-1]=0),g+1<a&&(r[g]=l[g][a-1]),r[a-1]=0;{for(var m=i;m<n;m++){for(var p=0;p<this.m;p++)this.U[p][m]=0;this.U[m][m]=1}for(var E=i-1;E>=0;E--)if(this.s[E]!==0){for(var y=E+1;y<n;y++){for(var I=0,w=E;w<this.m;w++)I+=this.U[w][E]*this.U[w][y];I=-I/this.U[E][E];for(var R=E;R<this.m;R++)this.U[R][y]+=I*this.U[R][E]}for(var W=E;W<this.m;W++)this.U[W][E]=-this.U[W][E];this.U[E][E]=1+this.U[E][E];for(var x=0;x<E-1;x++)this.U[x][E]=0}else{for(var q=0;q<this.m;q++)this.U[q][E]=0;this.U[E][E]=1}}for(var V=this.n-1;V>=0;V--){if(function(Nt,Mt){return Nt&&Mt}(V<g,r[V]!==0))for(var U=V+1;U<n;U++){for(var et=0,z=V+1;z<this.n;z++)et+=this.V[z][V]*this.V[z][U];et=-et/this.V[V+1][V];for(var O=V+1;O<this.n;O++)this.V[O][U]+=et*this.V[O][V]}for(var H=0;H<this.n;H++)this.V[H][V]=0;this.V[V][V]=1}for(var B=a-1,_=Math.pow(2,-52),lt=Math.pow(2,-966);a>0;){var J=void 0,Rt=void 0;for(J=a-2;J>=-1&&J!==-1;J--)if(Math.abs(r[J])<=lt+_*(Math.abs(this.s[J])+Math.abs(this.s[J+1]))){r[J]=0;break}if(J===a-2)Rt=4;else{var Lt=void 0;for(Lt=a-1;Lt>=J&&Lt!==J;Lt--){var vt=(Lt!==a?Math.abs(r[Lt]):0)+(Lt!==J+1?Math.abs(r[Lt-1]):0);if(Math.abs(this.s[Lt])<=lt+_*vt){this.s[Lt]=0;break}}Lt===J?Rt=3:Lt===a-1?Rt=1:(Rt=2,J=Lt)}switch(J++,Rt){case 1:{var it=r[a-2];r[a-2]=0;for(var gt=a-2;gt>=J;gt--){var Tt=u.hypot(this.s[gt],it),At=this.s[gt]/Tt,Dt=it/Tt;this.s[gt]=Tt,gt!==J&&(it=-Dt*r[gt-1],r[gt-1]=At*r[gt-1]);for(var mt=0;mt<this.n;mt++)Tt=At*this.V[mt][gt]+Dt*this.V[mt][a-1],this.V[mt][a-1]=-Dt*this.V[mt][gt]+At*this.V[mt][a-1],this.V[mt][gt]=Tt}}break;case 2:{var xt=r[J-1];r[J-1]=0;for(var St=J;St<a;St++){var Vt=u.hypot(this.s[St],xt),Xt=this.s[St]/Vt,Ut=xt/Vt;this.s[St]=Vt,xt=-Ut*r[St],r[St]=Xt*r[St];for(var bt=0;bt<this.m;bt++)Vt=Xt*this.U[bt][St]+Ut*this.U[bt][J-1],this.U[bt][J-1]=-Ut*this.U[bt][St]+Xt*this.U[bt][J-1],this.U[bt][St]=Vt}}break;case 3:{var Ht=Math.max(Math.max(Math.max(Math.max(Math.abs(this.s[a-1]),Math.abs(this.s[a-2])),Math.abs(r[a-2])),Math.abs(this.s[J])),Math.abs(r[J])),Bt=this.s[a-1]/Ht,F=this.s[a-2]/Ht,b=r[a-2]/Ht,$=this.s[J]/Ht,Q=r[J]/Ht,Z=((F+Bt)*(F-Bt)+b*b)/2,nt=Bt*b*(Bt*b),ut=0;(function(Nt,Mt){return Nt||Mt})(Z!==0,nt!==0)&&(ut=Math.sqrt(Z*Z+nt),Z<0&&(ut=-ut),ut=nt/(Z+ut));for(var ot=($+Bt)*($-Bt)+ut,tt=$*Q,j=J;j<a-1;j++){var dt=u.hypot(ot,tt),wt=ot/dt,yt=tt/dt;j!==J&&(r[j-1]=dt),ot=wt*this.s[j]+yt*r[j],r[j]=wt*r[j]-yt*this.s[j],tt=yt*this.s[j+1],this.s[j+1]=wt*this.s[j+1];for(var It=0;It<this.n;It++)dt=wt*this.V[It][j]+yt*this.V[It][j+1],this.V[It][j+1]=-yt*this.V[It][j]+wt*this.V[It][j+1],this.V[It][j]=dt;if(dt=u.hypot(ot,tt),wt=ot/dt,yt=tt/dt,this.s[j]=dt,ot=wt*r[j]+yt*this.s[j+1],this.s[j+1]=-yt*r[j]+wt*this.s[j+1],tt=yt*r[j+1],r[j+1]=wt*r[j+1],j<this.m-1)for(var ft=0;ft<this.m;ft++)dt=wt*this.U[ft][j]+yt*this.U[ft][j+1],this.U[ft][j+1]=-yt*this.U[ft][j]+wt*this.U[ft][j+1],this.U[ft][j]=dt}r[a-2]=ot}break;case 4:{if(this.s[J]<=0){this.s[J]=this.s[J]<0?-this.s[J]:0;for(var st=0;st<=B;st++)this.V[st][J]=-this.V[st][J]}for(;J<B&&!(this.s[J]>=this.s[J+1]);){var Ct=this.s[J];if(this.s[J]=this.s[J+1],this.s[J+1]=Ct,J<this.n-1)for(var ct=0;ct<this.n;ct++)Ct=this.V[ct][J+1],this.V[ct][J+1]=this.V[ct][J],this.V[ct][J]=Ct;if(J<this.m-1)for(var ht=0;ht<this.m;ht++)Ct=this.U[ht][J+1],this.U[ht][J+1]=this.U[ht][J],this.U[ht][J]=Ct;J++}a--}break}}var Wt={U:this.U,V:this.V,S:this.s};return Wt},u.hypot=function(l,n){var r=void 0;return Math.abs(l)>Math.abs(n)?(r=n/l,r=Math.abs(l)*Math.sqrt(1+r*r)):n!=0?(r=l/n,r=Math.abs(n)*Math.sqrt(1+r*r)):r=0,r},A.exports=u},function(A,G,L){var u=function(){function r(e,f){for(var i=0;i<f.length;i++){var g=f[i];g.enumerable=g.enumerable||!1,g.configurable=!0,"value"in g&&(g.writable=!0),Object.defineProperty(e,g.key,g)}}return function(e,f,i){return f&&r(e.prototype,f),i&&r(e,i),e}}();function l(r,e){if(!(r instanceof e))throw new TypeError("Cannot call a class as a function")}var n=function(){function r(e,f){var i=arguments.length>2&&arguments[2]!==void 0?arguments[2]:1,g=arguments.length>3&&arguments[3]!==void 0?arguments[3]:-1,t=arguments.length>4&&arguments[4]!==void 0?arguments[4]:-1;l(this,r),this.sequence1=e,this.sequence2=f,this.match_score=i,this.mismatch_penalty=g,this.gap_penalty=t,this.iMax=e.length+1,this.jMax=f.length+1,this.grid=new Array(this.iMax);for(var s=0;s<this.iMax;s++){this.grid[s]=new Array(this.jMax);for(var o=0;o<this.jMax;o++)this.grid[s][o]=0}this.tracebackGrid=new Array(this.iMax);for(var c=0;c<this.iMax;c++){this.tracebackGrid[c]=new Array(this.jMax);for(var h=0;h<this.jMax;h++)this.tracebackGrid[c][h]=[null,null,null]}this.alignments=[],this.score=-1,this.computeGrids()}return u(r,[{key:"getScore",value:function(){return this.score}},{key:"getAlignments",value:function(){return this.alignments}},{key:"computeGrids",value:function(){for(var f=1;f<this.jMax;f++)this.grid[0][f]=this.grid[0][f-1]+this.gap_penalty,this.tracebackGrid[0][f]=[!1,!1,!0];for(var i=1;i<this.iMax;i++)this.grid[i][0]=this.grid[i-1][0]+this.gap_penalty,this.tracebackGrid[i][0]=[!1,!0,!1];for(var g=1;g<this.iMax;g++)for(var t=1;t<this.jMax;t++){var s=void 0;this.sequence1[g-1]===this.sequence2[t-1]?s=this.grid[g-1][t-1]+this.match_score:s=this.grid[g-1][t-1]+this.mismatch_penalty;var o=this.grid[g-1][t]+this.gap_penalty,c=this.grid[g][t-1]+this.gap_penalty,h=[s,o,c],T=this.arrayAllMaxIndexes(h);this.grid[g][t]=h[T[0]],this.tracebackGrid[g][t]=[T.includes(0),T.includes(1),T.includes(2)]}this.score=this.grid[this.iMax-1][this.jMax-1]}},{key:"alignmentTraceback",value:function(){var f=[];for(f.push({pos:[this.sequence1.length,this.sequence2.length],seq1:"",seq2:""});f[0];){var i=f[0],g=this.tracebackGrid[i.pos[0]][i.pos[1]];g[0]&&f.push({pos:[i.pos[0]-1,i.pos[1]-1],seq1:this.sequence1[i.pos[0]-1]+i.seq1,seq2:this.sequence2[i.pos[1]-1]+i.seq2}),g[1]&&f.push({pos:[i.pos[0]-1,i.pos[1]],seq1:this.sequence1[i.pos[0]-1]+i.seq1,seq2:"-"+i.seq2}),g[2]&&f.push({pos:[i.pos[0],i.pos[1]-1],seq1:"-"+i.seq1,seq2:this.sequence2[i.pos[1]-1]+i.seq2}),i.pos[0]===0&&i.pos[1]===0&&this.alignments.push({sequence1:i.seq1,sequence2:i.seq2}),f.shift()}return this.alignments}},{key:"getAllIndexes",value:function(f,i){for(var g=[],t=-1;(t=f.indexOf(i,t+1))!==-1;)g.push(t);return g}},{key:"arrayAllMaxIndexes",value:function(f){return this.getAllIndexes(f,Math.max.apply(null,f))}}]),r}();A.exports=n},function(A,G,L){var u=function(){};u.FDLayout=L(18),u.FDLayoutConstants=L(4),u.FDLayoutEdge=L(19),u.FDLayoutNode=L(20),u.DimensionD=L(21),u.HashMap=L(22),u.HashSet=L(23),u.IGeometry=L(8),u.IMath=L(9),u.Integer=L(10),u.Point=L(12),u.PointD=L(5),u.RandomSeed=L(16),u.RectangleD=L(13),u.Transform=L(17),u.UniqueIDGeneretor=L(14),u.Quicksort=L(25),u.LinkedList=L(11),u.LGraphObject=L(2),u.LGraph=L(6),u.LEdge=L(1),u.LGraphManager=L(7),u.LNode=L(3),u.Layout=L(15),u.LayoutConstants=L(0),u.NeedlemanWunsch=L(27),u.Matrix=L(24),u.SVD=L(26),A.exports=u},function(A,G,L){function u(){this.listeners=[]}var l=u.prototype;l.addListener=function(n,r){this.listeners.push({event:n,callback:r})},l.removeListener=function(n,r){for(var e=this.listeners.length;e>=0;e--){var f=this.listeners[e];f.event===n&&f.callback===r&&this.listeners.splice(e,1)}},l.emit=function(n,r){for(var e=0;e<this.listeners.length;e++){var f=this.listeners[e];n===f.event&&f.callback(r)}},A.exports=u}])})}(ce)),ce.exports}var pr=fe.exports,Ie;function yr(){return Ie||(Ie=1,function(C,X){(function(G,L){C.exports=L(vr())})(pr,function(A){return(()=>{var G={45:(n,r,e)=>{var f={};f.layoutBase=e(551),f.CoSEConstants=e(806),f.CoSEEdge=e(767),f.CoSEGraph=e(880),f.CoSEGraphManager=e(578),f.CoSELayout=e(765),f.CoSENode=e(991),f.ConstraintHandler=e(902),n.exports=f},806:(n,r,e)=>{var f=e(551).FDLayoutConstants;function i(){}for(var g in f)i[g]=f[g];i.DEFAULT_USE_MULTI_LEVEL_SCALING=!1,i.DEFAULT_RADIAL_SEPARATION=f.DEFAULT_EDGE_LENGTH,i.DEFAULT_COMPONENT_SEPERATION=60,i.TILE=!0,i.TILING_PADDING_VERTICAL=10,i.TILING_PADDING_HORIZONTAL=10,i.TRANSFORM_ON_CONSTRAINT_HANDLING=!0,i.ENFORCE_CONSTRAINTS=!0,i.APPLY_LAYOUT=!0,i.RELAX_MOVEMENT_ON_CONSTRAINTS=!0,i.TREE_REDUCTION_ON_INCREMENTAL=!0,i.PURE_INCREMENTAL=i.DEFAULT_INCREMENTAL,n.exports=i},767:(n,r,e)=>{var f=e(551).FDLayoutEdge;function i(t,s,o){f.call(this,t,s,o)}i.prototype=Object.create(f.prototype);for(var g in f)i[g]=f[g];n.exports=i},880:(n,r,e)=>{var f=e(551).LGraph;function i(t,s,o){f.call(this,t,s,o)}i.prototype=Object.create(f.prototype);for(var g in f)i[g]=f[g];n.exports=i},578:(n,r,e)=>{var f=e(551).LGraphManager;function i(t){f.call(this,t)}i.prototype=Object.create(f.prototype);for(var g in f)i[g]=f[g];n.exports=i},765:(n,r,e)=>{var f=e(551).FDLayout,i=e(578),g=e(880),t=e(991),s=e(767),o=e(806),c=e(902),h=e(551).FDLayoutConstants,T=e(551).LayoutConstants,v=e(551).Point,d=e(551).PointD,N=e(551).DimensionD,S=e(551).Layout,M=e(551).Integer,P=e(551).IGeometry,K=e(551).LGraph,Y=e(551).Transform,k=e(551).LinkedList;function D(){f.call(this),this.toBeTiled={},this.constraints={}}D.prototype=Object.create(f.prototype);for(var rt in f)D[rt]=f[rt];D.prototype.newGraphManager=function(){var a=new i(this);return this.graphManager=a,a},D.prototype.newGraph=function(a){return new g(null,this.graphManager,a)},D.prototype.newNode=function(a){return new t(this.graphManager,a)},D.prototype.newEdge=function(a){return new s(null,null,a)},D.prototype.initParameters=function(){f.prototype.initParameters.call(this,arguments),this.isSubLayout||(o.DEFAULT_EDGE_LENGTH<10?this.idealEdgeLength=10:this.idealEdgeLength=o.DEFAULT_EDGE_LENGTH,this.useSmartIdealEdgeLengthCalculation=o.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION,this.gravityConstant=h.DEFAULT_GRAVITY_STRENGTH,this.compoundGravityConstant=h.DEFAULT_COMPOUND_GRAVITY_STRENGTH,this.gravityRangeFactor=h.DEFAULT_GRAVITY_RANGE_FACTOR,this.compoundGravityRangeFactor=h.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR,this.prunedNodesAll=[],this.growTreeIterations=0,this.afterGrowthIterations=0,this.isTreeGrowing=!1,this.isGrowthFinished=!1)},D.prototype.initSpringEmbedder=function(){f.prototype.initSpringEmbedder.call(this),this.coolingCycle=0,this.maxCoolingCycle=this.maxIterations/h.CONVERGENCE_CHECK_PERIOD,this.finalTemperature=.04,this.coolingAdjuster=1},D.prototype.layout=function(){var a=T.DEFAULT_CREATE_BENDS_AS_NEEDED;return a&&(this.createBendpoints(),this.graphManager.resetAllEdges()),this.level=0,this.classicLayout()},D.prototype.classicLayout=function(){if(this.nodesWithGravity=this.calculateNodesToApplyGravitationTo(),this.graphManager.setAllNodesToApplyGravitation(this.nodesWithGravity),this.calcNoOfChildrenForAllNodes(),this.graphManager.calcLowestCommonAncestors(),this.graphManager.calcInclusionTreeDepths(),this.graphManager.getRoot().calcEstimatedSize(),this.calcIdealEdgeLengths(),this.incremental){if(o.TREE_REDUCTION_ON_INCREMENTAL){this.reduceTrees(),this.graphManager.resetAllNodesToApplyGravitation();var m=new Set(this.getAllNodes()),p=this.nodesWithGravity.filter(function(I){return m.has(I)});this.graphManager.setAllNodesToApplyGravitation(p)}}else{var a=this.getFlatForest();if(a.length>0)this.positionNodesRadially(a);else{this.reduceTrees(),this.graphManager.resetAllNodesToApplyGravitation();var m=new Set(this.getAllNodes()),p=this.nodesWithGravity.filter(function(E){return m.has(E)});this.graphManager.setAllNodesToApplyGravitation(p),this.positionNodesRandomly()}}return Object.keys(this.constraints).length>0&&(c.handleConstraints(this),this.initConstraintVariables()),this.initSpringEmbedder(),o.APPLY_LAYOUT&&this.runSpringEmbedder(),!0},D.prototype.tick=function(){if(this.totalIterations++,this.totalIterations===this.maxIterations&&!this.isTreeGrowing&&!this.isGrowthFinished)if(this.prunedNodesAll.length>0)this.isTreeGrowing=!0;else return!0;if(this.totalIterations%h.CONVERGENCE_CHECK_PERIOD==0&&!this.isTreeGrowing&&!this.isGrowthFinished){if(this.isConverged())if(this.prunedNodesAll.length>0)this.isTreeGrowing=!0;else return!0;this.coolingCycle++,this.layoutQuality==0?this.coolingAdjuster=this.coolingCycle:this.layoutQuality==1&&(this.coolingAdjuster=this.coolingCycle/3),this.coolingFactor=Math.max(this.initialCoolingFactor-Math.pow(this.coolingCycle,Math.log(100*(this.initialCoolingFactor-this.finalTemperature))/Math.log(this.maxCoolingCycle))/100*this.coolingAdjuster,this.finalTemperature),this.animationPeriod=Math.ceil(this.initialAnimationPeriod*Math.sqrt(this.coolingFactor))}if(this.isTreeGrowing){if(this.growTreeIterations%10==0)if(this.prunedNodesAll.length>0){this.graphManager.updateBounds(),this.updateGrid(),this.growTree(this.prunedNodesAll),this.graphManager.resetAllNodesToApplyGravitation();var a=new Set(this.getAllNodes()),m=this.nodesWithGravity.filter(function(y){return a.has(y)});this.graphManager.setAllNodesToApplyGravitation(m),this.graphManager.updateBounds(),this.updateGrid(),o.PURE_INCREMENTAL?this.coolingFactor=h.DEFAULT_COOLING_FACTOR_INCREMENTAL/2:this.coolingFactor=h.DEFAULT_COOLING_FACTOR_INCREMENTAL}else this.isTreeGrowing=!1,this.isGrowthFinished=!0;this.growTreeIterations++}if(this.isGrowthFinished){if(this.isConverged())return!0;this.afterGrowthIterations%10==0&&(this.graphManager.updateBounds(),this.updateGrid()),o.PURE_INCREMENTAL?this.coolingFactor=h.DEFAULT_COOLING_FACTOR_INCREMENTAL/2*((100-this.afterGrowthIterations)/100):this.coolingFactor=h.DEFAULT_COOLING_FACTOR_INCREMENTAL*((100-this.afterGrowthIterations)/100),this.afterGrowthIterations++}var p=!this.isTreeGrowing&&!this.isGrowthFinished,E=this.growTreeIterations%10==1&&this.isTreeGrowing||this.afterGrowthIterations%10==1&&this.isGrowthFinished;return this.totalDisplacement=0,this.graphManager.updateBounds(),this.calcSpringForces(),this.calcRepulsionForces(p,E),this.calcGravitationalForces(),this.moveNodes(),this.animate(),!1},D.prototype.getPositionsData=function(){for(var a=this.graphManager.getAllNodes(),m={},p=0;p<a.length;p++){var E=a[p].rect,y=a[p].id;m[y]={id:y,x:E.getCenterX(),y:E.getCenterY(),w:E.width,h:E.height}}return m},D.prototype.runSpringEmbedder=function(){this.initialAnimationPeriod=25,this.animationPeriod=this.initialAnimationPeriod;var a=!1;if(h.ANIMATE==="during")this.emit("layoutstarted");else{for(;!a;)a=this.tick();this.graphManager.updateBounds()}},D.prototype.moveNodes=function(){for(var a=this.getAllNodes(),m,p=0;p<a.length;p++)m=a[p],m.calculateDisplacement();Object.keys(this.constraints).length>0&&this.updateDisplacements();for(var p=0;p<a.length;p++)m=a[p],m.move()},D.prototype.initConstraintVariables=function(){var a=this;this.idToNodeMap=new Map,this.fixedNodeSet=new Set;for(var m=this.graphManager.getAllNodes(),p=0;p<m.length;p++){var E=m[p];this.idToNodeMap.set(E.id,E)}var y=function O(H){for(var B=H.getChild().getNodes(),_,lt=0,J=0;J<B.length;J++)_=B[J],_.getChild()==null?a.fixedNodeSet.has(_.id)&&(lt+=100):lt+=O(_);return lt};if(this.constraints.fixedNodeConstraint){this.constraints.fixedNodeConstraint.forEach(function(B){a.fixedNodeSet.add(B.nodeId)});for(var m=this.graphManager.getAllNodes(),E,p=0;p<m.length;p++)if(E=m[p],E.getChild()!=null){var I=y(E);I>0&&(E.fixedNodeWeight=I)}}if(this.constraints.relativePlacementConstraint){var w=new Map,R=new Map;if(this.dummyToNodeForVerticalAlignment=new Map,this.dummyToNodeForHorizontalAlignment=new Map,this.fixedNodesOnHorizontal=new Set,this.fixedNodesOnVertical=new Set,this.fixedNodeSet.forEach(function(O){a.fixedNodesOnHorizontal.add(O),a.fixedNodesOnVertical.add(O)}),this.constraints.alignmentConstraint){if(this.constraints.alignmentConstraint.vertical)for(var W=this.constraints.alignmentConstraint.vertical,p=0;p<W.length;p++)this.dummyToNodeForVerticalAlignment.set("dummy"+p,[]),W[p].forEach(function(H){w.set(H,"dummy"+p),a.dummyToNodeForVerticalAlignment.get("dummy"+p).push(H),a.fixedNodeSet.has(H)&&a.fixedNodesOnHorizontal.add("dummy"+p)});if(this.constraints.alignmentConstraint.horizontal)for(var x=this.constraints.alignmentConstraint.horizontal,p=0;p<x.length;p++)this.dummyToNodeForHorizontalAlignment.set("dummy"+p,[]),x[p].forEach(function(H){R.set(H,"dummy"+p),a.dummyToNodeForHorizontalAlignment.get("dummy"+p).push(H),a.fixedNodeSet.has(H)&&a.fixedNodesOnVertical.add("dummy"+p)})}if(o.RELAX_MOVEMENT_ON_CONSTRAINTS)this.shuffle=function(O){var H,B,_;for(_=O.length-1;_>=2*O.length/3;_--)H=Math.floor(Math.random()*(_+1)),B=O[_],O[_]=O[H],O[H]=B;return O},this.nodesInRelativeHorizontal=[],this.nodesInRelativeVertical=[],this.nodeToRelativeConstraintMapHorizontal=new Map,this.nodeToRelativeConstraintMapVertical=new Map,this.nodeToTempPositionMapHorizontal=new Map,this.nodeToTempPositionMapVertical=new Map,this.constraints.relativePlacementConstraint.forEach(function(O){if(O.left){var H=w.has(O.left)?w.get(O.left):O.left,B=w.has(O.right)?w.get(O.right):O.right;a.nodesInRelativeHorizontal.includes(H)||(a.nodesInRelativeHorizontal.push(H),a.nodeToRelativeConstraintMapHorizontal.set(H,[]),a.dummyToNodeForVerticalAlignment.has(H)?a.nodeToTempPositionMapHorizontal.set(H,a.idToNodeMap.get(a.dummyToNodeForVerticalAlignment.get(H)[0]).getCenterX()):a.nodeToTempPositionMapHorizontal.set(H,a.idToNodeMap.get(H).getCenterX())),a.nodesInRelativeHorizontal.includes(B)||(a.nodesInRelativeHorizontal.push(B),a.nodeToRelativeConstraintMapHorizontal.set(B,[]),a.dummyToNodeForVerticalAlignment.has(B)?a.nodeToTempPositionMapHorizontal.set(B,a.idToNodeMap.get(a.dummyToNodeForVerticalAlignment.get(B)[0]).getCenterX()):a.nodeToTempPositionMapHorizontal.set(B,a.idToNodeMap.get(B).getCenterX())),a.nodeToRelativeConstraintMapHorizontal.get(H).push({right:B,gap:O.gap}),a.nodeToRelativeConstraintMapHorizontal.get(B).push({left:H,gap:O.gap})}else{var _=R.has(O.top)?R.get(O.top):O.top,lt=R.has(O.bottom)?R.get(O.bottom):O.bottom;a.nodesInRelativeVertical.includes(_)||(a.nodesInRelativeVertical.push(_),a.nodeToRelativeConstraintMapVertical.set(_,[]),a.dummyToNodeForHorizontalAlignment.has(_)?a.nodeToTempPositionMapVertical.set(_,a.idToNodeMap.get(a.dummyToNodeForHorizontalAlignment.get(_)[0]).getCenterY()):a.nodeToTempPositionMapVertical.set(_,a.idToNodeMap.get(_).getCenterY())),a.nodesInRelativeVertical.includes(lt)||(a.nodesInRelativeVertical.push(lt),a.nodeToRelativeConstraintMapVertical.set(lt,[]),a.dummyToNodeForHorizontalAlignment.has(lt)?a.nodeToTempPositionMapVertical.set(lt,a.idToNodeMap.get(a.dummyToNodeForHorizontalAlignment.get(lt)[0]).getCenterY()):a.nodeToTempPositionMapVertical.set(lt,a.idToNodeMap.get(lt).getCenterY())),a.nodeToRelativeConstraintMapVertical.get(_).push({bottom:lt,gap:O.gap}),a.nodeToRelativeConstraintMapVertical.get(lt).push({top:_,gap:O.gap})}});else{var q=new Map,V=new Map;this.constraints.relativePlacementConstraint.forEach(function(O){if(O.left){var H=w.has(O.left)?w.get(O.left):O.left,B=w.has(O.right)?w.get(O.right):O.right;q.has(H)?q.get(H).push(B):q.set(H,[B]),q.has(B)?q.get(B).push(H):q.set(B,[H])}else{var _=R.has(O.top)?R.get(O.top):O.top,lt=R.has(O.bottom)?R.get(O.bottom):O.bottom;V.has(_)?V.get(_).push(lt):V.set(_,[lt]),V.has(lt)?V.get(lt).push(_):V.set(lt,[_])}});var U=function(H,B){var _=[],lt=[],J=new k,Rt=new Set,Lt=0;return H.forEach(function(vt,it){if(!Rt.has(it)){_[Lt]=[],lt[Lt]=!1;var gt=it;for(J.push(gt),Rt.add(gt),_[Lt].push(gt);J.length!=0;){gt=J.shift(),B.has(gt)&&(lt[Lt]=!0);var Tt=H.get(gt);Tt.forEach(function(At){Rt.has(At)||(J.push(At),Rt.add(At),_[Lt].push(At))})}Lt++}}),{components:_,isFixed:lt}},et=U(q,a.fixedNodesOnHorizontal);this.componentsOnHorizontal=et.components,this.fixedComponentsOnHorizontal=et.isFixed;var z=U(V,a.fixedNodesOnVertical);this.componentsOnVertical=z.components,this.fixedComponentsOnVertical=z.isFixed}}},D.prototype.updateDisplacements=function(){var a=this;if(this.constraints.fixedNodeConstraint&&this.constraints.fixedNodeConstraint.forEach(function(z){var O=a.idToNodeMap.get(z.nodeId);O.displacementX=0,O.displacementY=0}),this.constraints.alignmentConstraint){if(this.constraints.alignmentConstraint.vertical)for(var m=this.constraints.alignmentConstraint.vertical,p=0;p<m.length;p++){for(var E=0,y=0;y<m[p].length;y++){if(this.fixedNodeSet.has(m[p][y])){E=0;break}E+=this.idToNodeMap.get(m[p][y]).displacementX}for(var I=E/m[p].length,y=0;y<m[p].length;y++)this.idToNodeMap.get(m[p][y]).displacementX=I}if(this.constraints.alignmentConstraint.horizontal)for(var w=this.constraints.alignmentConstraint.horizontal,p=0;p<w.length;p++){for(var R=0,y=0;y<w[p].length;y++){if(this.fixedNodeSet.has(w[p][y])){R=0;break}R+=this.idToNodeMap.get(w[p][y]).displacementY}for(var W=R/w[p].length,y=0;y<w[p].length;y++)this.idToNodeMap.get(w[p][y]).displacementY=W}}if(this.constraints.relativePlacementConstraint)if(o.RELAX_MOVEMENT_ON_CONSTRAINTS)this.totalIterations%10==0&&(this.shuffle(this.nodesInRelativeHorizontal),this.shuffle(this.nodesInRelativeVertical)),this.nodesInRelativeHorizontal.forEach(function(z){if(!a.fixedNodesOnHorizontal.has(z)){var O=0;a.dummyToNodeForVerticalAlignment.has(z)?O=a.idToNodeMap.get(a.dummyToNodeForVerticalAlignment.get(z)[0]).displacementX:O=a.idToNodeMap.get(z).displacementX,a.nodeToRelativeConstraintMapHorizontal.get(z).forEach(function(H){if(H.right){var B=a.nodeToTempPositionMapHorizontal.get(H.right)-a.nodeToTempPositionMapHorizontal.get(z)-O;B<H.gap&&(O-=H.gap-B)}else{var B=a.nodeToTempPositionMapHorizontal.get(z)-a.nodeToTempPositionMapHorizontal.get(H.left)+O;B<H.gap&&(O+=H.gap-B)}}),a.nodeToTempPositionMapHorizontal.set(z,a.nodeToTempPositionMapHorizontal.get(z)+O),a.dummyToNodeForVerticalAlignment.has(z)?a.dummyToNodeForVerticalAlignment.get(z).forEach(function(H){a.idToNodeMap.get(H).displacementX=O}):a.idToNodeMap.get(z).displacementX=O}}),this.nodesInRelativeVertical.forEach(function(z){if(!a.fixedNodesOnHorizontal.has(z)){var O=0;a.dummyToNodeForHorizontalAlignment.has(z)?O=a.idToNodeMap.get(a.dummyToNodeForHorizontalAlignment.get(z)[0]).displacementY:O=a.idToNodeMap.get(z).displacementY,a.nodeToRelativeConstraintMapVertical.get(z).forEach(function(H){if(H.bottom){var B=a.nodeToTempPositionMapVertical.get(H.bottom)-a.nodeToTempPositionMapVertical.get(z)-O;B<H.gap&&(O-=H.gap-B)}else{var B=a.nodeToTempPositionMapVertical.get(z)-a.nodeToTempPositionMapVertical.get(H.top)+O;B<H.gap&&(O+=H.gap-B)}}),a.nodeToTempPositionMapVertical.set(z,a.nodeToTempPositionMapVertical.get(z)+O),a.dummyToNodeForHorizontalAlignment.has(z)?a.dummyToNodeForHorizontalAlignment.get(z).forEach(function(H){a.idToNodeMap.get(H).displacementY=O}):a.idToNodeMap.get(z).displacementY=O}});else{for(var p=0;p<this.componentsOnHorizontal.length;p++){var x=this.componentsOnHorizontal[p];if(this.fixedComponentsOnHorizontal[p])for(var y=0;y<x.length;y++)this.dummyToNodeForVerticalAlignment.has(x[y])?this.dummyToNodeForVerticalAlignment.get(x[y]).forEach(function(H){a.idToNodeMap.get(H).displacementX=0}):this.idToNodeMap.get(x[y]).displacementX=0;else{for(var q=0,V=0,y=0;y<x.length;y++)if(this.dummyToNodeForVerticalAlignment.has(x[y])){var U=this.dummyToNodeForVerticalAlignment.get(x[y]);q+=U.length*this.idToNodeMap.get(U[0]).displacementX,V+=U.length}else q+=this.idToNodeMap.get(x[y]).displacementX,V++;for(var et=q/V,y=0;y<x.length;y++)this.dummyToNodeForVerticalAlignment.has(x[y])?this.dummyToNodeForVerticalAlignment.get(x[y]).forEach(function(H){a.idToNodeMap.get(H).displacementX=et}):this.idToNodeMap.get(x[y]).displacementX=et}}for(var p=0;p<this.componentsOnVertical.length;p++){var x=this.componentsOnVertical[p];if(this.fixedComponentsOnVertical[p])for(var y=0;y<x.length;y++)this.dummyToNodeForHorizontalAlignment.has(x[y])?this.dummyToNodeForHorizontalAlignment.get(x[y]).forEach(function(B){a.idToNodeMap.get(B).displacementY=0}):this.idToNodeMap.get(x[y]).displacementY=0;else{for(var q=0,V=0,y=0;y<x.length;y++)if(this.dummyToNodeForHorizontalAlignment.has(x[y])){var U=this.dummyToNodeForHorizontalAlignment.get(x[y]);q+=U.length*this.idToNodeMap.get(U[0]).displacementY,V+=U.length}else q+=this.idToNodeMap.get(x[y]).displacementY,V++;for(var et=q/V,y=0;y<x.length;y++)this.dummyToNodeForHorizontalAlignment.has(x[y])?this.dummyToNodeForHorizontalAlignment.get(x[y]).forEach(function(J){a.idToNodeMap.get(J).displacementY=et}):this.idToNodeMap.get(x[y]).displacementY=et}}}},D.prototype.calculateNodesToApplyGravitationTo=function(){var a=[],m,p=this.graphManager.getGraphs(),E=p.length,y;for(y=0;y<E;y++)m=p[y],m.updateConnected(),m.isConnected||(a=a.concat(m.getNodes()));return a},D.prototype.createBendpoints=function(){var a=[];a=a.concat(this.graphManager.getAllEdges());var m=new Set,p;for(p=0;p<a.length;p++){var E=a[p];if(!m.has(E)){var y=E.getSource(),I=E.getTarget();if(y==I)E.getBendpoints().push(new d),E.getBendpoints().push(new d),this.createDummyNodesForBendpoints(E),m.add(E);else{var w=[];if(w=w.concat(y.getEdgeListToNode(I)),w=w.concat(I.getEdgeListToNode(y)),!m.has(w[0])){if(w.length>1){var R;for(R=0;R<w.length;R++){var W=w[R];W.getBendpoints().push(new d),this.createDummyNodesForBendpoints(W)}}w.forEach(function(x){m.add(x)})}}}if(m.size==a.length)break}},D.prototype.positionNodesRadially=function(a){for(var m=new v(0,0),p=Math.ceil(Math.sqrt(a.length)),E=0,y=0,I=0,w=new d(0,0),R=0;R<a.length;R++){R%p==0&&(I=0,y=E,R!=0&&(y+=o.DEFAULT_COMPONENT_SEPERATION),E=0);var W=a[R],x=S.findCenterOfTree(W);m.x=I,m.y=y,w=D.radialLayout(W,x,m),w.y>E&&(E=Math.floor(w.y)),I=Math.floor(w.x+o.DEFAULT_COMPONENT_SEPERATION)}this.transform(new d(T.WORLD_CENTER_X-w.x/2,T.WORLD_CENTER_Y-w.y/2))},D.radialLayout=function(a,m,p){var E=Math.max(this.maxDiagonalInTree(a),o.DEFAULT_RADIAL_SEPARATION);D.branchRadialLayout(m,null,0,359,0,E);var y=K.calculateBounds(a),I=new Y;I.setDeviceOrgX(y.getMinX()),I.setDeviceOrgY(y.getMinY()),I.setWorldOrgX(p.x),I.setWorldOrgY(p.y);for(var w=0;w<a.length;w++){var R=a[w];R.transform(I)}var W=new d(y.getMaxX(),y.getMaxY());return I.inverseTransformPoint(W)},D.branchRadialLayout=function(a,m,p,E,y,I){var w=(E-p+1)/2;w<0&&(w+=180);var R=(w+p)%360,W=R*P.TWO_PI/360,x=y*Math.cos(W),q=y*Math.sin(W);a.setCenter(x,q);var V=[];V=V.concat(a.getEdges());var U=V.length;m!=null&&U--;for(var et=0,z=V.length,O,H=a.getEdgesBetween(m);H.length>1;){var B=H[0];H.splice(0,1);var _=V.indexOf(B);_>=0&&V.splice(_,1),z--,U--}m!=null?O=(V.indexOf(H[0])+1)%z:O=0;for(var lt=Math.abs(E-p)/U,J=O;et!=U;J=++J%z){var Rt=V[J].getOtherEnd(a);if(Rt!=m){var Lt=(p+et*lt)%360,vt=(Lt+lt)%360;D.branchRadialLayout(Rt,a,Lt,vt,y+I,I),et++}}},D.maxDiagonalInTree=function(a){for(var m=M.MIN_VALUE,p=0;p<a.length;p++){var E=a[p],y=E.getDiagonal();y>m&&(m=y)}return m},D.prototype.calcRepulsionRange=function(){return 2*(this.level+1)*this.idealEdgeLength},D.prototype.groupZeroDegreeMembers=function(){var a=this,m={};this.memberGroups={},this.idToDummyNode={};for(var p=[],E=this.graphManager.getAllNodes(),y=0;y<E.length;y++){var I=E[y],w=I.getParent();this.getNodeDegreeWithChildren(I)===0&&(w.id==null||!this.getToBeTiled(w))&&p.push(I)}for(var y=0;y<p.length;y++){var I=p[y],R=I.getParent().id;typeof m[R]>"u"&&(m[R]=[]),m[R]=m[R].concat(I)}Object.keys(m).forEach(function(W){if(m[W].length>1){var x="DummyCompound_"+W;a.memberGroups[x]=m[W];var q=m[W][0].getParent(),V=new t(a.graphManager);V.id=x,V.paddingLeft=q.paddingLeft||0,V.paddingRight=q.paddingRight||0,V.paddingBottom=q.paddingBottom||0,V.paddingTop=q.paddingTop||0,a.idToDummyNode[x]=V;var U=a.getGraphManager().add(a.newGraph(),V),et=q.getChild();et.add(V);for(var z=0;z<m[W].length;z++){var O=m[W][z];et.remove(O),U.add(O)}}})},D.prototype.clearCompounds=function(){var a={},m={};this.performDFSOnCompounds();for(var p=0;p<this.compoundOrder.length;p++)m[this.compoundOrder[p].id]=this.compoundOrder[p],a[this.compoundOrder[p].id]=[].concat(this.compoundOrder[p].getChild().getNodes()),this.graphManager.remove(this.compoundOrder[p].getChild()),this.compoundOrder[p].child=null;this.graphManager.resetAllNodes(),this.tileCompoundMembers(a,m)},D.prototype.clearZeroDegreeMembers=function(){var a=this,m=this.tiledZeroDegreePack=[];Object.keys(this.memberGroups).forEach(function(p){var E=a.idToDummyNode[p];if(m[p]=a.tileNodes(a.memberGroups[p],E.paddingLeft+E.paddingRight),E.rect.width=m[p].width,E.rect.height=m[p].height,E.setCenter(m[p].centerX,m[p].centerY),E.labelMarginLeft=0,E.labelMarginTop=0,o.NODE_DIMENSIONS_INCLUDE_LABELS){var y=E.rect.width,I=E.rect.height;E.labelWidth&&(E.labelPosHorizontal=="left"?(E.rect.x-=E.labelWidth,E.setWidth(y+E.labelWidth),E.labelMarginLeft=E.labelWidth):E.labelPosHorizontal=="center"&&E.labelWidth>y?(E.rect.x-=(E.labelWidth-y)/2,E.setWidth(E.labelWidth),E.labelMarginLeft=(E.labelWidth-y)/2):E.labelPosHorizontal=="right"&&E.setWidth(y+E.labelWidth)),E.labelHeight&&(E.labelPosVertical=="top"?(E.rect.y-=E.labelHeight,E.setHeight(I+E.labelHeight),E.labelMarginTop=E.labelHeight):E.labelPosVertical=="center"&&E.labelHeight>I?(E.rect.y-=(E.labelHeight-I)/2,E.setHeight(E.labelHeight),E.labelMarginTop=(E.labelHeight-I)/2):E.labelPosVertical=="bottom"&&E.setHeight(I+E.labelHeight))}})},D.prototype.repopulateCompounds=function(){for(var a=this.compoundOrder.length-1;a>=0;a--){var m=this.compoundOrder[a],p=m.id,E=m.paddingLeft,y=m.paddingTop,I=m.labelMarginLeft,w=m.labelMarginTop;this.adjustLocations(this.tiledMemberPack[p],m.rect.x,m.rect.y,E,y,I,w)}},D.prototype.repopulateZeroDegreeMembers=function(){var a=this,m=this.tiledZeroDegreePack;Object.keys(m).forEach(function(p){var E=a.idToDummyNode[p],y=E.paddingLeft,I=E.paddingTop,w=E.labelMarginLeft,R=E.labelMarginTop;a.adjustLocations(m[p],E.rect.x,E.rect.y,y,I,w,R)})},D.prototype.getToBeTiled=function(a){var m=a.id;if(this.toBeTiled[m]!=null)return this.toBeTiled[m];var p=a.getChild();if(p==null)return this.toBeTiled[m]=!1,!1;for(var E=p.getNodes(),y=0;y<E.length;y++){var I=E[y];if(this.getNodeDegree(I)>0)return this.toBeTiled[m]=!1,!1;if(I.getChild()==null){this.toBeTiled[I.id]=!1;continue}if(!this.getToBeTiled(I))return this.toBeTiled[m]=!1,!1}return this.toBeTiled[m]=!0,!0},D.prototype.getNodeDegree=function(a){a.id;for(var m=a.getEdges(),p=0,E=0;E<m.length;E++){var y=m[E];y.getSource().id!==y.getTarget().id&&(p=p+1)}return p},D.prototype.getNodeDegreeWithChildren=function(a){var m=this.getNodeDegree(a);if(a.getChild()==null)return m;for(var p=a.getChild().getNodes(),E=0;E<p.length;E++){var y=p[E];m+=this.getNodeDegreeWithChildren(y)}return m},D.prototype.performDFSOnCompounds=function(){this.compoundOrder=[],this.fillCompexOrderByDFS(this.graphManager.getRoot().getNodes())},D.prototype.fillCompexOrderByDFS=function(a){for(var m=0;m<a.length;m++){var p=a[m];p.getChild()!=null&&this.fillCompexOrderByDFS(p.getChild().getNodes()),this.getToBeTiled(p)&&this.compoundOrder.push(p)}},D.prototype.adjustLocations=function(a,m,p,E,y,I,w){m+=E+I,p+=y+w;for(var R=m,W=0;W<a.rows.length;W++){var x=a.rows[W];m=R;for(var q=0,V=0;V<x.length;V++){var U=x[V];U.rect.x=m,U.rect.y=p,m+=U.rect.width+a.horizontalPadding,U.rect.height>q&&(q=U.rect.height)}p+=q+a.verticalPadding}},D.prototype.tileCompoundMembers=function(a,m){var p=this;this.tiledMemberPack=[],Object.keys(a).forEach(function(E){var y=m[E];if(p.tiledMemberPack[E]=p.tileNodes(a[E],y.paddingLeft+y.paddingRight),y.rect.width=p.tiledMemberPack[E].width,y.rect.height=p.tiledMemberPack[E].height,y.setCenter(p.tiledMemberPack[E].centerX,p.tiledMemberPack[E].centerY),y.labelMarginLeft=0,y.labelMarginTop=0,o.NODE_DIMENSIONS_INCLUDE_LABELS){var I=y.rect.width,w=y.rect.height;y.labelWidth&&(y.labelPosHorizontal=="left"?(y.rect.x-=y.labelWidth,y.setWidth(I+y.labelWidth),y.labelMarginLeft=y.labelWidth):y.labelPosHorizontal=="center"&&y.labelWidth>I?(y.rect.x-=(y.labelWidth-I)/2,y.setWidth(y.labelWidth),y.labelMarginLeft=(y.labelWidth-I)/2):y.labelPosHorizontal=="right"&&y.setWidth(I+y.labelWidth)),y.labelHeight&&(y.labelPosVertical=="top"?(y.rect.y-=y.labelHeight,y.setHeight(w+y.labelHeight),y.labelMarginTop=y.labelHeight):y.labelPosVertical=="center"&&y.labelHeight>w?(y.rect.y-=(y.labelHeight-w)/2,y.setHeight(y.labelHeight),y.labelMarginTop=(y.labelHeight-w)/2):y.labelPosVertical=="bottom"&&y.setHeight(w+y.labelHeight))}})},D.prototype.tileNodes=function(a,m){var p=this.tileNodesByFavoringDim(a,m,!0),E=this.tileNodesByFavoringDim(a,m,!1),y=this.getOrgRatio(p),I=this.getOrgRatio(E),w;return I<y?w=E:w=p,w},D.prototype.getOrgRatio=function(a){var m=a.width,p=a.height,E=m/p;return E<1&&(E=1/E),E},D.prototype.calcIdealRowWidth=function(a,m){var p=o.TILING_PADDING_VERTICAL,E=o.TILING_PADDING_HORIZONTAL,y=a.length,I=0,w=0,R=0;a.forEach(function(z){I+=z.getWidth(),w+=z.getHeight(),z.getWidth()>R&&(R=z.getWidth())});var W=I/y,x=w/y,q=Math.pow(p-E,2)+4*(W+E)*(x+p)*y,V=(E-p+Math.sqrt(q))/(2*(W+E)),U;m?(U=Math.ceil(V),U==V&&U++):U=Math.floor(V);var et=U*(W+E)-E;return R>et&&(et=R),et+=E*2,et},D.prototype.tileNodesByFavoringDim=function(a,m,p){var E=o.TILING_PADDING_VERTICAL,y=o.TILING_PADDING_HORIZONTAL,I=o.TILING_COMPARE_BY,w={rows:[],rowWidth:[],rowHeight:[],width:0,height:m,verticalPadding:E,horizontalPadding:y,centerX:0,centerY:0};I&&(w.idealRowWidth=this.calcIdealRowWidth(a,p));var R=function(O){return O.rect.width*O.rect.height},W=function(O,H){return R(H)-R(O)};a.sort(function(z,O){var H=W;return w.idealRowWidth?(H=I,H(z.id,O.id)):H(z,O)});for(var x=0,q=0,V=0;V<a.length;V++){var U=a[V];x+=U.getCenterX(),q+=U.getCenterY()}w.centerX=x/a.length,w.centerY=q/a.length;for(var V=0;V<a.length;V++){var U=a[V];if(w.rows.length==0)this.insertNodeToRow(w,U,0,m);else if(this.canAddHorizontal(w,U.rect.width,U.rect.height)){var et=w.rows.length-1;w.idealRowWidth||(et=this.getShortestRowIndex(w)),this.insertNodeToRow(w,U,et,m)}else this.insertNodeToRow(w,U,w.rows.length,m);this.shiftToLastRow(w)}return w},D.prototype.insertNodeToRow=function(a,m,p,E){var y=E;if(p==a.rows.length){var I=[];a.rows.push(I),a.rowWidth.push(y),a.rowHeight.push(0)}var w=a.rowWidth[p]+m.rect.width;a.rows[p].length>0&&(w+=a.horizontalPadding),a.rowWidth[p]=w,a.width<w&&(a.width=w);var R=m.rect.height;p>0&&(R+=a.verticalPadding);var W=0;R>a.rowHeight[p]&&(W=a.rowHeight[p],a.rowHeight[p]=R,W=a.rowHeight[p]-W),a.height+=W,a.rows[p].push(m)},D.prototype.getShortestRowIndex=function(a){for(var m=-1,p=Number.MAX_VALUE,E=0;E<a.rows.length;E++)a.rowWidth[E]<p&&(m=E,p=a.rowWidth[E]);return m},D.prototype.getLongestRowIndex=function(a){for(var m=-1,p=Number.MIN_VALUE,E=0;E<a.rows.length;E++)a.rowWidth[E]>p&&(m=E,p=a.rowWidth[E]);return m},D.prototype.canAddHorizontal=function(a,m,p){if(a.idealRowWidth){var E=a.rows.length-1,y=a.rowWidth[E];return y+m+a.horizontalPadding<=a.idealRowWidth}var I=this.getShortestRowIndex(a);if(I<0)return!0;var w=a.rowWidth[I];if(w+a.horizontalPadding+m<=a.width)return!0;var R=0;a.rowHeight[I]<p&&I>0&&(R=p+a.verticalPadding-a.rowHeight[I]);var W;a.width-w>=m+a.horizontalPadding?W=(a.height+R)/(w+m+a.horizontalPadding):W=(a.height+R)/a.width,R=p+a.verticalPadding;var x;return a.width<m?x=(a.height+R)/m:x=(a.height+R)/a.width,x<1&&(x=1/x),W<1&&(W=1/W),W<x},D.prototype.shiftToLastRow=function(a){var m=this.getLongestRowIndex(a),p=a.rowWidth.length-1,E=a.rows[m],y=E[E.length-1],I=y.width+a.horizontalPadding;if(a.width-a.rowWidth[p]>I&&m!=p){E.splice(-1,1),a.rows[p].push(y),a.rowWidth[m]=a.rowWidth[m]-I,a.rowWidth[p]=a.rowWidth[p]+I,a.width=a.rowWidth[instance.getLongestRowIndex(a)];for(var w=Number.MIN_VALUE,R=0;R<E.length;R++)E[R].height>w&&(w=E[R].height);m>0&&(w+=a.verticalPadding);var W=a.rowHeight[m]+a.rowHeight[p];a.rowHeight[m]=w,a.rowHeight[p]<y.height+a.verticalPadding&&(a.rowHeight[p]=y.height+a.verticalPadding);var x=a.rowHeight[m]+a.rowHeight[p];a.height+=x-W,this.shiftToLastRow(a)}},D.prototype.tilingPreLayout=function(){o.TILE&&(this.groupZeroDegreeMembers(),this.clearCompounds(),this.clearZeroDegreeMembers())},D.prototype.tilingPostLayout=function(){o.TILE&&(this.repopulateZeroDegreeMembers(),this.repopulateCompounds())},D.prototype.reduceTrees=function(){for(var a=[],m=!0,p;m;){var E=this.graphManager.getAllNodes(),y=[];m=!1;for(var I=0;I<E.length;I++)if(p=E[I],p.getEdges().length==1&&!p.getEdges()[0].isInterGraph&&p.getChild()==null){if(o.PURE_INCREMENTAL){var w=p.getEdges()[0].getOtherEnd(p),R=new N(p.getCenterX()-w.getCenterX(),p.getCenterY()-w.getCenterY());y.push([p,p.getEdges()[0],p.getOwner(),R])}else y.push([p,p.getEdges()[0],p.getOwner()]);m=!0}if(m==!0){for(var W=[],x=0;x<y.length;x++)y[x][0].getEdges().length==1&&(W.push(y[x]),y[x][0].getOwner().remove(y[x][0]));a.push(W),this.graphManager.resetAllNodes(),this.graphManager.resetAllEdges()}}this.prunedNodesAll=a},D.prototype.growTree=function(a){for(var m=a.length,p=a[m-1],E,y=0;y<p.length;y++)E=p[y],this.findPlaceforPrunedNode(E),E[2].add(E[0]),E[2].add(E[1],E[1].source,E[1].target);a.splice(a.length-1,1),this.graphManager.resetAllNodes(),this.graphManager.resetAllEdges()},D.prototype.findPlaceforPrunedNode=function(a){var m,p,E=a[0];if(E==a[1].source?p=a[1].target:p=a[1].source,o.PURE_INCREMENTAL)E.setCenter(p.getCenterX()+a[3].getWidth(),p.getCenterY()+a[3].getHeight());else{var y=p.startX,I=p.finishX,w=p.startY,R=p.finishY,W=0,x=0,q=0,V=0,U=[W,q,x,V];if(w>0)for(var et=y;et<=I;et++)U[0]+=this.grid[et][w-1].length+this.grid[et][w].length-1;if(I<this.grid.length-1)for(var et=w;et<=R;et++)U[1]+=this.grid[I+1][et].length+this.grid[I][et].length-1;if(R<this.grid[0].length-1)for(var et=y;et<=I;et++)U[2]+=this.grid[et][R+1].length+this.grid[et][R].length-1;if(y>0)for(var et=w;et<=R;et++)U[3]+=this.grid[y-1][et].length+this.grid[y][et].length-1;for(var z=M.MAX_VALUE,O,H,B=0;B<U.length;B++)U[B]<z?(z=U[B],O=1,H=B):U[B]==z&&O++;if(O==3&&z==0)U[0]==0&&U[1]==0&&U[2]==0?m=1:U[0]==0&&U[1]==0&&U[3]==0?m=0:U[0]==0&&U[2]==0&&U[3]==0?m=3:U[1]==0&&U[2]==0&&U[3]==0&&(m=2);else if(O==2&&z==0){var _=Math.floor(Math.random()*2);U[0]==0&&U[1]==0?_==0?m=0:m=1:U[0]==0&&U[2]==0?_==0?m=0:m=2:U[0]==0&&U[3]==0?_==0?m=0:m=3:U[1]==0&&U[2]==0?_==0?m=1:m=2:U[1]==0&&U[3]==0?_==0?m=1:m=3:_==0?m=2:m=3}else if(O==4&&z==0){var _=Math.floor(Math.random()*4);m=_}else m=H;m==0?E.setCenter(p.getCenterX(),p.getCenterY()-p.getHeight()/2-h.DEFAULT_EDGE_LENGTH-E.getHeight()/2):m==1?E.setCenter(p.getCenterX()+p.getWidth()/2+h.DEFAULT_EDGE_LENGTH+E.getWidth()/2,p.getCenterY()):m==2?E.setCenter(p.getCenterX(),p.getCenterY()+p.getHeight()/2+h.DEFAULT_EDGE_LENGTH+E.getHeight()/2):E.setCenter(p.getCenterX()-p.getWidth()/2-h.DEFAULT_EDGE_LENGTH-E.getWidth()/2,p.getCenterY())}},n.exports=D},991:(n,r,e)=>{var f=e(551).FDLayoutNode,i=e(551).IMath;function g(s,o,c,h){f.call(this,s,o,c,h)}g.prototype=Object.create(f.prototype);for(var t in f)g[t]=f[t];g.prototype.calculateDisplacement=function(){var s=this.graphManager.getLayout();this.getChild()!=null&&this.fixedNodeWeight?(this.displacementX+=s.coolingFactor*(this.springForceX+this.repulsionForceX+this.gravitationForceX)/this.fixedNodeWeight,this.displacementY+=s.coolingFactor*(this.springForceY+this.repulsionForceY+this.gravitationForceY)/this.fixedNodeWeight):(this.displacementX+=s.coolingFactor*(this.springForceX+this.repulsionForceX+this.gravitationForceX)/this.noOfChildren,this.displacementY+=s.coolingFactor*(this.springForceY+this.repulsionForceY+this.gravitationForceY)/this.noOfChildren),Math.abs(this.displacementX)>s.coolingFactor*s.maxNodeDisplacement&&(this.displacementX=s.coolingFactor*s.maxNodeDisplacement*i.sign(this.displacementX)),Math.abs(this.displacementY)>s.coolingFactor*s.maxNodeDisplacement&&(this.displacementY=s.coolingFactor*s.maxNodeDisplacement*i.sign(this.displacementY)),this.child&&this.child.getNodes().length>0&&this.propogateDisplacementToChildren(this.displacementX,this.displacementY)},g.prototype.propogateDisplacementToChildren=function(s,o){for(var c=this.getChild().getNodes(),h,T=0;T<c.length;T++)h=c[T],h.getChild()==null?(h.displacementX+=s,h.displacementY+=o):h.propogateDisplacementToChildren(s,o)},g.prototype.move=function(){var s=this.graphManager.getLayout();(this.child==null||this.child.getNodes().length==0)&&(this.moveBy(this.displacementX,this.displacementY),s.totalDisplacement+=Math.abs(this.displacementX)+Math.abs(this.displacementY)),this.springForceX=0,this.springForceY=0,this.repulsionForceX=0,this.repulsionForceY=0,this.gravitationForceX=0,this.gravitationForceY=0,this.displacementX=0,this.displacementY=0},g.prototype.setPred1=function(s){this.pred1=s},g.prototype.getPred1=function(){return pred1},g.prototype.getPred2=function(){return pred2},g.prototype.setNext=function(s){this.next=s},g.prototype.getNext=function(){return next},g.prototype.setProcessed=function(s){this.processed=s},g.prototype.isProcessed=function(){return processed},n.exports=g},902:(n,r,e)=>{function f(c){if(Array.isArray(c)){for(var h=0,T=Array(c.length);h<c.length;h++)T[h]=c[h];return T}else return Array.from(c)}var i=e(806),g=e(551).LinkedList,t=e(551).Matrix,s=e(551).SVD;function o(){}o.handleConstraints=function(c){var h={};h.fixedNodeConstraint=c.constraints.fixedNodeConstraint,h.alignmentConstraint=c.constraints.alignmentConstraint,h.relativePlacementConstraint=c.constraints.relativePlacementConstraint;for(var T=new Map,v=new Map,d=[],N=[],S=c.getAllNodes(),M=0,P=0;P<S.length;P++){var K=S[P];K.getChild()==null&&(v.set(K.id,M++),d.push(K.getCenterX()),N.push(K.getCenterY()),T.set(K.id,K))}h.relativePlacementConstraint&&h.relativePlacementConstraint.forEach(function(F){!F.gap&&F.gap!=0&&(F.left?F.gap=i.DEFAULT_EDGE_LENGTH+T.get(F.left).getWidth()/2+T.get(F.right).getWidth()/2:F.gap=i.DEFAULT_EDGE_LENGTH+T.get(F.top).getHeight()/2+T.get(F.bottom).getHeight()/2)});var Y=function(b,$){return{x:b.x-$.x,y:b.y-$.y}},k=function(b){var $=0,Q=0;return b.forEach(function(Z){$+=d[v.get(Z)],Q+=N[v.get(Z)]}),{x:$/b.size,y:Q/b.size}},D=function(b,$,Q,Z,nt){function ut(ft,st){var Ct=new Set(ft),ct=!0,ht=!1,Wt=void 0;try{for(var Nt=st[Symbol.iterator](),Mt;!(ct=(Mt=Nt.next()).done);ct=!0){var Zt=Mt.value;Ct.add(Zt)}}catch(Gt){ht=!0,Wt=Gt}finally{try{!ct&&Nt.return&&Nt.return()}finally{if(ht)throw Wt}}return Ct}var ot=new Map;b.forEach(function(ft,st){ot.set(st,0)}),b.forEach(function(ft,st){ft.forEach(function(Ct){ot.set(Ct.id,ot.get(Ct.id)+1)})});var tt=new Map,j=new Map,dt=new g;ot.forEach(function(ft,st){ft==0?(dt.push(st),Q||($=="horizontal"?tt.set(st,v.has(st)?d[v.get(st)]:Z.get(st)):tt.set(st,v.has(st)?N[v.get(st)]:Z.get(st)))):tt.set(st,Number.NEGATIVE_INFINITY),Q&&j.set(st,new Set([st]))}),Q&&nt.forEach(function(ft){var st=[];if(ft.forEach(function(ht){Q.has(ht)&&st.push(ht)}),st.length>0){var Ct=0;st.forEach(function(ht){$=="horizontal"?(tt.set(ht,v.has(ht)?d[v.get(ht)]:Z.get(ht)),Ct+=tt.get(ht)):(tt.set(ht,v.has(ht)?N[v.get(ht)]:Z.get(ht)),Ct+=tt.get(ht))}),Ct=Ct/st.length,ft.forEach(function(ht){Q.has(ht)||tt.set(ht,Ct)})}else{var ct=0;ft.forEach(function(ht){$=="horizontal"?ct+=v.has(ht)?d[v.get(ht)]:Z.get(ht):ct+=v.has(ht)?N[v.get(ht)]:Z.get(ht)}),ct=ct/ft.length,ft.forEach(function(ht){tt.set(ht,ct)})}});for(var wt=function(){var st=dt.shift(),Ct=b.get(st);Ct.forEach(function(ct){if(tt.get(ct.id)<tt.get(st)+ct.gap)if(Q&&Q.has(ct.id)){var ht=void 0;if($=="horizontal"?ht=v.has(ct.id)?d[v.get(ct.id)]:Z.get(ct.id):ht=v.has(ct.id)?N[v.get(ct.id)]:Z.get(ct.id),tt.set(ct.id,ht),ht<tt.get(st)+ct.gap){var Wt=tt.get(st)+ct.gap-ht;j.get(st).forEach(function(Nt){tt.set(Nt,tt.get(Nt)-Wt)})}}else tt.set(ct.id,tt.get(st)+ct.gap);ot.set(ct.id,ot.get(ct.id)-1),ot.get(ct.id)==0&&dt.push(ct.id),Q&&j.set(ct.id,ut(j.get(st),j.get(ct.id)))})};dt.length!=0;)wt();if(Q){var yt=new Set;b.forEach(function(ft,st){ft.length==0&&yt.add(st)});var It=[];j.forEach(function(ft,st){if(yt.has(st)){var Ct=!1,ct=!0,ht=!1,Wt=void 0;try{for(var Nt=ft[Symbol.iterator](),Mt;!(ct=(Mt=Nt.next()).done);ct=!0){var Zt=Mt.value;Q.has(Zt)&&(Ct=!0)}}catch(Ft){ht=!0,Wt=Ft}finally{try{!ct&&Nt.return&&Nt.return()}finally{if(ht)throw Wt}}if(!Ct){var Gt=!1,$t=void 0;It.forEach(function(Ft,qt){Ft.has([].concat(f(ft))[0])&&(Gt=!0,$t=qt)}),Gt?ft.forEach(function(Ft){It[$t].add(Ft)}):It.push(new Set(ft))}}}),It.forEach(function(ft,st){var Ct=Number.POSITIVE_INFINITY,ct=Number.POSITIVE_INFINITY,ht=Number.NEGATIVE_INFINITY,Wt=Number.NEGATIVE_INFINITY,Nt=!0,Mt=!1,Zt=void 0;try{for(var Gt=ft[Symbol.iterator](),$t;!(Nt=($t=Gt.next()).done);Nt=!0){var Ft=$t.value,qt=void 0;$=="horizontal"?qt=v.has(Ft)?d[v.get(Ft)]:Z.get(Ft):qt=v.has(Ft)?N[v.get(Ft)]:Z.get(Ft);var _t=tt.get(Ft);qt<Ct&&(Ct=qt),qt>ht&&(ht=qt),_t<ct&&(ct=_t),_t>Wt&&(Wt=_t)}}catch(ie){Mt=!0,Zt=ie}finally{try{!Nt&&Gt.return&&Gt.return()}finally{if(Mt)throw Zt}}var ge=(Ct+ht)/2-(ct+Wt)/2,Kt=!0,te=!1,ee=void 0;try{for(var jt=ft[Symbol.iterator](),se;!(Kt=(se=jt.next()).done);Kt=!0){var re=se.value;tt.set(re,tt.get(re)+ge)}}catch(ie){te=!0,ee=ie}finally{try{!Kt&&jt.return&&jt.return()}finally{if(te)throw ee}}})}return tt},rt=function(b){var $=0,Q=0,Z=0,nt=0;if(b.forEach(function(j){j.left?d[v.get(j.left)]-d[v.get(j.right)]>=0?$++:Q++:N[v.get(j.top)]-N[v.get(j.bottom)]>=0?Z++:nt++}),$>Q&&Z>nt)for(var ut=0;ut<v.size;ut++)d[ut]=-1*d[ut],N[ut]=-1*N[ut];else if($>Q)for(var ot=0;ot<v.size;ot++)d[ot]=-1*d[ot];else if(Z>nt)for(var tt=0;tt<v.size;tt++)N[tt]=-1*N[tt]},a=function(b){var $=[],Q=new g,Z=new Set,nt=0;return b.forEach(function(ut,ot){if(!Z.has(ot)){$[nt]=[];var tt=ot;for(Q.push(tt),Z.add(tt),$[nt].push(tt);Q.length!=0;){tt=Q.shift();var j=b.get(tt);j.forEach(function(dt){Z.has(dt.id)||(Q.push(dt.id),Z.add(dt.id),$[nt].push(dt.id))})}nt++}}),$},m=function(b){var $=new Map;return b.forEach(function(Q,Z){$.set(Z,[])}),b.forEach(function(Q,Z){Q.forEach(function(nt){$.get(Z).push(nt),$.get(nt.id).push({id:Z,gap:nt.gap,direction:nt.direction})})}),$},p=function(b){var $=new Map;return b.forEach(function(Q,Z){$.set(Z,[])}),b.forEach(function(Q,Z){Q.forEach(function(nt){$.get(nt.id).push({id:Z,gap:nt.gap,direction:nt.direction})})}),$},E=[],y=[],I=!1,w=!1,R=new Set,W=new Map,x=new Map,q=[];if(h.fixedNodeConstraint&&h.fixedNodeConstraint.forEach(function(F){R.add(F.nodeId)}),h.relativePlacementConstraint&&(h.relativePlacementConstraint.forEach(function(F){F.left?(W.has(F.left)?W.get(F.left).push({id:F.right,gap:F.gap,direction:"horizontal"}):W.set(F.left,[{id:F.right,gap:F.gap,direction:"horizontal"}]),W.has(F.right)||W.set(F.right,[])):(W.has(F.top)?W.get(F.top).push({id:F.bottom,gap:F.gap,direction:"vertical"}):W.set(F.top,[{id:F.bottom,gap:F.gap,direction:"vertical"}]),W.has(F.bottom)||W.set(F.bottom,[]))}),x=m(W),q=a(x)),i.TRANSFORM_ON_CONSTRAINT_HANDLING){if(h.fixedNodeConstraint&&h.fixedNodeConstraint.length>1)h.fixedNodeConstraint.forEach(function(F,b){E[b]=[F.position.x,F.position.y],y[b]=[d[v.get(F.nodeId)],N[v.get(F.nodeId)]]}),I=!0;else if(h.alignmentConstraint)(function(){var F=0;if(h.alignmentConstraint.vertical){for(var b=h.alignmentConstraint.vertical,$=function(tt){var j=new Set;b[tt].forEach(function(yt){j.add(yt)});var dt=new Set([].concat(f(j)).filter(function(yt){return R.has(yt)})),wt=void 0;dt.size>0?wt=d[v.get(dt.values().next().value)]:wt=k(j).x,b[tt].forEach(function(yt){E[F]=[wt,N[v.get(yt)]],y[F]=[d[v.get(yt)],N[v.get(yt)]],F++})},Q=0;Q<b.length;Q++)$(Q);I=!0}if(h.alignmentConstraint.horizontal){for(var Z=h.alignmentConstraint.horizontal,nt=function(tt){var j=new Set;Z[tt].forEach(function(yt){j.add(yt)});var dt=new Set([].concat(f(j)).filter(function(yt){return R.has(yt)})),wt=void 0;dt.size>0?wt=d[v.get(dt.values().next().value)]:wt=k(j).y,Z[tt].forEach(function(yt){E[F]=[d[v.get(yt)],wt],y[F]=[d[v.get(yt)],N[v.get(yt)]],F++})},ut=0;ut<Z.length;ut++)nt(ut);I=!0}h.relativePlacementConstraint&&(w=!0)})();else if(h.relativePlacementConstraint){for(var V=0,U=0,et=0;et<q.length;et++)q[et].length>V&&(V=q[et].length,U=et);if(V<x.size/2)rt(h.relativePlacementConstraint),I=!1,w=!1;else{var z=new Map,O=new Map,H=[];q[U].forEach(function(F){W.get(F).forEach(function(b){b.direction=="horizontal"?(z.has(F)?z.get(F).push(b):z.set(F,[b]),z.has(b.id)||z.set(b.id,[]),H.push({left:F,right:b.id})):(O.has(F)?O.get(F).push(b):O.set(F,[b]),O.has(b.id)||O.set(b.id,[]),H.push({top:F,bottom:b.id}))})}),rt(H),w=!1;var B=D(z,"horizontal"),_=D(O,"vertical");q[U].forEach(function(F,b){y[b]=[d[v.get(F)],N[v.get(F)]],E[b]=[],B.has(F)?E[b][0]=B.get(F):E[b][0]=d[v.get(F)],_.has(F)?E[b][1]=_.get(F):E[b][1]=N[v.get(F)]}),I=!0}}if(I){for(var lt=void 0,J=t.transpose(E),Rt=t.transpose(y),Lt=0;Lt<J.length;Lt++)J[Lt]=t.multGamma(J[Lt]),Rt[Lt]=t.multGamma(Rt[Lt]);var vt=t.multMat(J,t.transpose(Rt)),it=s.svd(vt);lt=t.multMat(it.V,t.transpose(it.U));for(var gt=0;gt<v.size;gt++){var Tt=[d[gt],N[gt]],At=[lt[0][0],lt[1][0]],Dt=[lt[0][1],lt[1][1]];d[gt]=t.dotProduct(Tt,At),N[gt]=t.dotProduct(Tt,Dt)}w&&rt(h.relativePlacementConstraint)}}if(i.ENFORCE_CONSTRAINTS){if(h.fixedNodeConstraint&&h.fixedNodeConstraint.length>0){var mt={x:0,y:0};h.fixedNodeConstraint.forEach(function(F,b){var $={x:d[v.get(F.nodeId)],y:N[v.get(F.nodeId)]},Q=F.position,Z=Y(Q,$);mt.x+=Z.x,mt.y+=Z.y}),mt.x/=h.fixedNodeConstraint.length,mt.y/=h.fixedNodeConstraint.length,d.forEach(function(F,b){d[b]+=mt.x}),N.forEach(function(F,b){N[b]+=mt.y}),h.fixedNodeConstraint.forEach(function(F){d[v.get(F.nodeId)]=F.position.x,N[v.get(F.nodeId)]=F.position.y})}if(h.alignmentConstraint){if(h.alignmentConstraint.vertical)for(var xt=h.alignmentConstraint.vertical,St=function(b){var $=new Set;xt[b].forEach(function(nt){$.add(nt)});var Q=new Set([].concat(f($)).filter(function(nt){return R.has(nt)})),Z=void 0;Q.size>0?Z=d[v.get(Q.values().next().value)]:Z=k($).x,$.forEach(function(nt){R.has(nt)||(d[v.get(nt)]=Z)})},Vt=0;Vt<xt.length;Vt++)St(Vt);if(h.alignmentConstraint.horizontal)for(var Xt=h.alignmentConstraint.horizontal,Ut=function(b){var $=new Set;Xt[b].forEach(function(nt){$.add(nt)});var Q=new Set([].concat(f($)).filter(function(nt){return R.has(nt)})),Z=void 0;Q.size>0?Z=N[v.get(Q.values().next().value)]:Z=k($).y,$.forEach(function(nt){R.has(nt)||(N[v.get(nt)]=Z)})},bt=0;bt<Xt.length;bt++)Ut(bt)}h.relativePlacementConstraint&&function(){var F=new Map,b=new Map,$=new Map,Q=new Map,Z=new Map,nt=new Map,ut=new Set,ot=new Set;if(R.forEach(function(Yt){ut.add(Yt),ot.add(Yt)}),h.alignmentConstraint){if(h.alignmentConstraint.vertical)for(var tt=h.alignmentConstraint.vertical,j=function(Et){$.set("dummy"+Et,[]),tt[Et].forEach(function(Ot){F.set(Ot,"dummy"+Et),$.get("dummy"+Et).push(Ot),R.has(Ot)&&ut.add("dummy"+Et)}),Z.set("dummy"+Et,d[v.get(tt[Et][0])])},dt=0;dt<tt.length;dt++)j(dt);if(h.alignmentConstraint.horizontal)for(var wt=h.alignmentConstraint.horizontal,yt=function(Et){Q.set("dummy"+Et,[]),wt[Et].forEach(function(Ot){b.set(Ot,"dummy"+Et),Q.get("dummy"+Et).push(Ot),R.has(Ot)&&ot.add("dummy"+Et)}),nt.set("dummy"+Et,N[v.get(wt[Et][0])])},It=0;It<wt.length;It++)yt(It)}var ft=new Map,st=new Map,Ct=function(Et){W.get(Et).forEach(function(Ot){var Jt=void 0,kt=void 0;Ot.direction=="horizontal"?(Jt=F.get(Et)?F.get(Et):Et,F.get(Ot.id)?kt={id:F.get(Ot.id),gap:Ot.gap,direction:Ot.direction}:kt=Ot,ft.has(Jt)?ft.get(Jt).push(kt):ft.set(Jt,[kt]),ft.has(kt.id)||ft.set(kt.id,[])):(Jt=b.get(Et)?b.get(Et):Et,b.get(Ot.id)?kt={id:b.get(Ot.id),gap:Ot.gap,direction:Ot.direction}:kt=Ot,st.has(Jt)?st.get(Jt).push(kt):st.set(Jt,[kt]),st.has(kt.id)||st.set(kt.id,[]))})},ct=!0,ht=!1,Wt=void 0;try{for(var Nt=W.keys()[Symbol.iterator](),Mt;!(ct=(Mt=Nt.next()).done);ct=!0){var Zt=Mt.value;Ct(Zt)}}catch(Yt){ht=!0,Wt=Yt}finally{try{!ct&&Nt.return&&Nt.return()}finally{if(ht)throw Wt}}var Gt=m(ft),$t=m(st),Ft=a(Gt),qt=a($t),_t=p(ft),ge=p(st),Kt=[],te=[];Ft.forEach(function(Yt,Et){Kt[Et]=[],Yt.forEach(function(Ot){_t.get(Ot).length==0&&Kt[Et].push(Ot)})}),qt.forEach(function(Yt,Et){te[Et]=[],Yt.forEach(function(Ot){ge.get(Ot).length==0&&te[Et].push(Ot)})});var ee=D(ft,"horizontal",ut,Z,Kt),jt=D(st,"vertical",ot,nt,te),se=function(Et){$.get(Et)?$.get(Et).forEach(function(Ot){d[v.get(Ot)]=ee.get(Et)}):d[v.get(Et)]=ee.get(Et)},re=!0,ie=!1,Me=void 0;try{for(var de=ee.keys()[Symbol.iterator](),Ae;!(re=(Ae=de.next()).done);re=!0){var ve=Ae.value;se(ve)}}catch(Yt){ie=!0,Me=Yt}finally{try{!re&&de.return&&de.return()}finally{if(ie)throw Me}}var qe=function(Et){Q.get(Et)?Q.get(Et).forEach(function(Ot){N[v.get(Ot)]=jt.get(Et)}):N[v.get(Et)]=jt.get(Et)},pe=!0,we=!1,Oe=void 0;try{for(var ye=jt.keys()[Symbol.iterator](),De;!(pe=(De=ye.next()).done);pe=!0){var ve=De.value;qe(ve)}}catch(Yt){we=!0,Oe=Yt}finally{try{!pe&&ye.return&&ye.return()}finally{if(we)throw Oe}}}()}for(var Ht=0;Ht<S.length;Ht++){var Bt=S[Ht];Bt.getChild()==null&&Bt.setCenter(d[v.get(Bt.id)],N[v.get(Bt.id)])}},n.exports=o},551:n=>{n.exports=A}},L={};function u(n){var r=L[n];if(r!==void 0)return r.exports;var e=L[n]={exports:{}};return G[n](e,e.exports,u),e.exports}var l=u(45);return l})()})}(fe)),fe.exports}var Er=le.exports,Re;function mr(){return Re||(Re=1,function(C,X){(function(G,L){C.exports=L(yr())})(Er,function(A){return(()=>{var G={658:n=>{n.exports=Object.assign!=null?Object.assign.bind(Object):function(r){for(var e=arguments.length,f=Array(e>1?e-1:0),i=1;i<e;i++)f[i-1]=arguments[i];return f.forEach(function(g){Object.keys(g).forEach(function(t){return r[t]=g[t]})}),r}},548:(n,r,e)=>{var f=function(){function t(s,o){var c=[],h=!0,T=!1,v=void 0;try{for(var d=s[Symbol.iterator](),N;!(h=(N=d.next()).done)&&(c.push(N.value),!(o&&c.length===o));h=!0);}catch(S){T=!0,v=S}finally{try{!h&&d.return&&d.return()}finally{if(T)throw v}}return c}return function(s,o){if(Array.isArray(s))return s;if(Symbol.iterator in Object(s))return t(s,o);throw new TypeError("Invalid attempt to destructure non-iterable instance")}}(),i=e(140).layoutBase.LinkedList,g={};g.getTopMostNodes=function(t){for(var s={},o=0;o<t.length;o++)s[t[o].id()]=!0;var c=t.filter(function(h,T){typeof h=="number"&&(h=T);for(var v=h.parent()[0];v!=null;){if(s[v.id()])return!1;v=v.parent()[0]}return!0});return c},g.connectComponents=function(t,s,o,c){var h=new i,T=new Set,v=[],d=void 0,N=void 0,S=void 0,M=!1,P=1,K=[],Y=[],k=function(){var rt=t.collection();Y.push(rt);var a=o[0],m=t.collection();m.merge(a).merge(a.descendants().intersection(s)),v.push(a),m.forEach(function(y){h.push(y),T.add(y),rt.merge(y)});for(var p=function(){a=h.shift();var I=t.collection();a.neighborhood().nodes().forEach(function(x){s.intersection(a.edgesWith(x)).length>0&&I.merge(x)});for(var w=0;w<I.length;w++){var R=I[w];if(d=o.intersection(R.union(R.ancestors())),d!=null&&!T.has(d[0])){var W=d.union(d.descendants());W.forEach(function(x){h.push(x),T.add(x),rt.merge(x),o.has(x)&&v.push(x)})}}};h.length!=0;)p();if(rt.forEach(function(y){s.intersection(y.connectedEdges()).forEach(function(I){rt.has(I.source())&&rt.has(I.target())&&rt.merge(I)})}),v.length==o.length&&(M=!0),!M||M&&P>1){N=v[0],S=N.connectedEdges().length,v.forEach(function(y){y.connectedEdges().length<S&&(S=y.connectedEdges().length,N=y)}),K.push(N.id());var E=t.collection();E.merge(v[0]),v.forEach(function(y){E.merge(y)}),v=[],o=o.difference(E),P++}};do k();while(!M);return c&&K.length>0&&c.set("dummy"+(c.size+1),K),Y},g.relocateComponent=function(t,s,o){if(!o.fixedNodeConstraint){var c=Number.POSITIVE_INFINITY,h=Number.NEGATIVE_INFINITY,T=Number.POSITIVE_INFINITY,v=Number.NEGATIVE_INFINITY;if(o.quality=="draft"){var d=!0,N=!1,S=void 0;try{for(var M=s.nodeIndexes[Symbol.iterator](),P;!(d=(P=M.next()).done);d=!0){var K=P.value,Y=f(K,2),k=Y[0],D=Y[1],rt=o.cy.getElementById(k);if(rt){var a=rt.boundingBox(),m=s.xCoords[D]-a.w/2,p=s.xCoords[D]+a.w/2,E=s.yCoords[D]-a.h/2,y=s.yCoords[D]+a.h/2;m<c&&(c=m),p>h&&(h=p),E<T&&(T=E),y>v&&(v=y)}}}catch(x){N=!0,S=x}finally{try{!d&&M.return&&M.return()}finally{if(N)throw S}}var I=t.x-(h+c)/2,w=t.y-(v+T)/2;s.xCoords=s.xCoords.map(function(x){return x+I}),s.yCoords=s.yCoords.map(function(x){return x+w})}else{Object.keys(s).forEach(function(x){var q=s[x],V=q.getRect().x,U=q.getRect().x+q.getRect().width,et=q.getRect().y,z=q.getRect().y+q.getRect().height;V<c&&(c=V),U>h&&(h=U),et<T&&(T=et),z>v&&(v=z)});var R=t.x-(h+c)/2,W=t.y-(v+T)/2;Object.keys(s).forEach(function(x){var q=s[x];q.setCenter(q.getCenterX()+R,q.getCenterY()+W)})}}},g.calcBoundingBox=function(t,s,o,c){for(var h=Number.MAX_SAFE_INTEGER,T=Number.MIN_SAFE_INTEGER,v=Number.MAX_SAFE_INTEGER,d=Number.MIN_SAFE_INTEGER,N=void 0,S=void 0,M=void 0,P=void 0,K=t.descendants().not(":parent"),Y=K.length,k=0;k<Y;k++){var D=K[k];N=s[c.get(D.id())]-D.width()/2,S=s[c.get(D.id())]+D.width()/2,M=o[c.get(D.id())]-D.height()/2,P=o[c.get(D.id())]+D.height()/2,h>N&&(h=N),T<S&&(T=S),v>M&&(v=M),d<P&&(d=P)}var rt={};return rt.topLeftX=h,rt.topLeftY=v,rt.width=T-h,rt.height=d-v,rt},g.calcParentsWithoutChildren=function(t,s){var o=t.collection();return s.nodes(":parent").forEach(function(c){var h=!1;c.children().forEach(function(T){T.css("display")!="none"&&(h=!0)}),h||o.merge(c)}),o},n.exports=g},816:(n,r,e)=>{var f=e(548),i=e(140).CoSELayout,g=e(140).CoSENode,t=e(140).layoutBase.PointD,s=e(140).layoutBase.DimensionD,o=e(140).layoutBase.LayoutConstants,c=e(140).layoutBase.FDLayoutConstants,h=e(140).CoSEConstants,T=function(d,N){var S=d.cy,M=d.eles,P=M.nodes(),K=M.edges(),Y=void 0,k=void 0,D=void 0,rt={};d.randomize&&(Y=N.nodeIndexes,k=N.xCoords,D=N.yCoords);var a=function(x){return typeof x=="function"},m=function(x,q){return a(x)?x(q):x},p=f.calcParentsWithoutChildren(S,M),E=function W(x,q,V,U){for(var et=q.length,z=0;z<et;z++){var O=q[z],H=null;O.intersection(p).length==0&&(H=O.children());var B=void 0,_=O.layoutDimensions({nodeDimensionsIncludeLabels:U.nodeDimensionsIncludeLabels});if(O.outerWidth()!=null&&O.outerHeight()!=null)if(U.randomize)if(!O.isParent())B=x.add(new g(V.graphManager,new t(k[Y.get(O.id())]-_.w/2,D[Y.get(O.id())]-_.h/2),new s(parseFloat(_.w),parseFloat(_.h))));else{var lt=f.calcBoundingBox(O,k,D,Y);O.intersection(p).length==0?B=x.add(new g(V.graphManager,new t(lt.topLeftX,lt.topLeftY),new s(lt.width,lt.height))):B=x.add(new g(V.graphManager,new t(lt.topLeftX,lt.topLeftY),new s(parseFloat(_.w),parseFloat(_.h))))}else B=x.add(new g(V.graphManager,new t(O.position("x")-_.w/2,O.position("y")-_.h/2),new s(parseFloat(_.w),parseFloat(_.h))));else B=x.add(new g(this.graphManager));if(B.id=O.data("id"),B.nodeRepulsion=m(U.nodeRepulsion,O),B.paddingLeft=parseInt(O.css("padding")),B.paddingTop=parseInt(O.css("padding")),B.paddingRight=parseInt(O.css("padding")),B.paddingBottom=parseInt(O.css("padding")),U.nodeDimensionsIncludeLabels&&(B.labelWidth=O.boundingBox({includeLabels:!0,includeNodes:!1,includeOverlays:!1}).w,B.labelHeight=O.boundingBox({includeLabels:!0,includeNodes:!1,includeOverlays:!1}).h,B.labelPosVertical=O.css("text-valign"),B.labelPosHorizontal=O.css("text-halign")),rt[O.data("id")]=B,isNaN(B.rect.x)&&(B.rect.x=0),isNaN(B.rect.y)&&(B.rect.y=0),H!=null&&H.length>0){var J=void 0;J=V.getGraphManager().add(V.newGraph(),B),W(J,H,V,U)}}},y=function(x,q,V){for(var U=0,et=0,z=0;z<V.length;z++){var O=V[z],H=rt[O.data("source")],B=rt[O.data("target")];if(H&&B&&H!==B&&H.getEdgesBetween(B).length==0){var _=q.add(x.newEdge(),H,B);_.id=O.id(),_.idealLength=m(d.idealEdgeLength,O),_.edgeElasticity=m(d.edgeElasticity,O),U+=_.idealLength,et++}}d.idealEdgeLength!=null&&(et>0?h.DEFAULT_EDGE_LENGTH=c.DEFAULT_EDGE_LENGTH=U/et:a(d.idealEdgeLength)?h.DEFAULT_EDGE_LENGTH=c.DEFAULT_EDGE_LENGTH=50:h.DEFAULT_EDGE_LENGTH=c.DEFAULT_EDGE_LENGTH=d.idealEdgeLength,h.MIN_REPULSION_DIST=c.MIN_REPULSION_DIST=c.DEFAULT_EDGE_LENGTH/10,h.DEFAULT_RADIAL_SEPARATION=c.DEFAULT_EDGE_LENGTH)},I=function(x,q){q.fixedNodeConstraint&&(x.constraints.fixedNodeConstraint=q.fixedNodeConstraint),q.alignmentConstraint&&(x.constraints.alignmentConstraint=q.alignmentConstraint),q.relativePlacementConstraint&&(x.constraints.relativePlacementConstraint=q.relativePlacementConstraint)};d.nestingFactor!=null&&(h.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR=c.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR=d.nestingFactor),d.gravity!=null&&(h.DEFAULT_GRAVITY_STRENGTH=c.DEFAULT_GRAVITY_STRENGTH=d.gravity),d.numIter!=null&&(h.MAX_ITERATIONS=c.MAX_ITERATIONS=d.numIter),d.gravityRange!=null&&(h.DEFAULT_GRAVITY_RANGE_FACTOR=c.DEFAULT_GRAVITY_RANGE_FACTOR=d.gravityRange),d.gravityCompound!=null&&(h.DEFAULT_COMPOUND_GRAVITY_STRENGTH=c.DEFAULT_COMPOUND_GRAVITY_STRENGTH=d.gravityCompound),d.gravityRangeCompound!=null&&(h.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR=c.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR=d.gravityRangeCompound),d.initialEnergyOnIncremental!=null&&(h.DEFAULT_COOLING_FACTOR_INCREMENTAL=c.DEFAULT_COOLING_FACTOR_INCREMENTAL=d.initialEnergyOnIncremental),d.tilingCompareBy!=null&&(h.TILING_COMPARE_BY=d.tilingCompareBy),d.quality=="proof"?o.QUALITY=2:o.QUALITY=0,h.NODE_DIMENSIONS_INCLUDE_LABELS=c.NODE_DIMENSIONS_INCLUDE_LABELS=o.NODE_DIMENSIONS_INCLUDE_LABELS=d.nodeDimensionsIncludeLabels,h.DEFAULT_INCREMENTAL=c.DEFAULT_INCREMENTAL=o.DEFAULT_INCREMENTAL=!d.randomize,h.ANIMATE=c.ANIMATE=o.ANIMATE=d.animate,h.TILE=d.tile,h.TILING_PADDING_VERTICAL=typeof d.tilingPaddingVertical=="function"?d.tilingPaddingVertical.call():d.tilingPaddingVertical,h.TILING_PADDING_HORIZONTAL=typeof d.tilingPaddingHorizontal=="function"?d.tilingPaddingHorizontal.call():d.tilingPaddingHorizontal,h.DEFAULT_INCREMENTAL=c.DEFAULT_INCREMENTAL=o.DEFAULT_INCREMENTAL=!0,h.PURE_INCREMENTAL=!d.randomize,o.DEFAULT_UNIFORM_LEAF_NODE_SIZES=d.uniformNodeDimensions,d.step=="transformed"&&(h.TRANSFORM_ON_CONSTRAINT_HANDLING=!0,h.ENFORCE_CONSTRAINTS=!1,h.APPLY_LAYOUT=!1),d.step=="enforced"&&(h.TRANSFORM_ON_CONSTRAINT_HANDLING=!1,h.ENFORCE_CONSTRAINTS=!0,h.APPLY_LAYOUT=!1),d.step=="cose"&&(h.TRANSFORM_ON_CONSTRAINT_HANDLING=!1,h.ENFORCE_CONSTRAINTS=!1,h.APPLY_LAYOUT=!0),d.step=="all"&&(d.randomize?h.TRANSFORM_ON_CONSTRAINT_HANDLING=!0:h.TRANSFORM_ON_CONSTRAINT_HANDLING=!1,h.ENFORCE_CONSTRAINTS=!0,h.APPLY_LAYOUT=!0),d.fixedNodeConstraint||d.alignmentConstraint||d.relativePlacementConstraint?h.TREE_REDUCTION_ON_INCREMENTAL=!1:h.TREE_REDUCTION_ON_INCREMENTAL=!0;var w=new i,R=w.newGraphManager();return E(R.addRoot(),f.getTopMostNodes(P),w,d),y(w,R,K),I(w,d),w.runLayout(),rt};n.exports={coseLayout:T}},212:(n,r,e)=>{var f=function(){function d(N,S){for(var M=0;M<S.length;M++){var P=S[M];P.enumerable=P.enumerable||!1,P.configurable=!0,"value"in P&&(P.writable=!0),Object.defineProperty(N,P.key,P)}}return function(N,S,M){return S&&d(N.prototype,S),M&&d(N,M),N}}();function i(d,N){if(!(d instanceof N))throw new TypeError("Cannot call a class as a function")}var g=e(658),t=e(548),s=e(657),o=s.spectralLayout,c=e(816),h=c.coseLayout,T=Object.freeze({quality:"default",randomize:!0,animate:!0,animationDuration:1e3,animationEasing:void 0,fit:!0,padding:30,nodeDimensionsIncludeLabels:!1,uniformNodeDimensions:!1,packComponents:!0,step:"all",samplingType:!0,sampleSize:25,nodeSeparation:75,piTol:1e-7,nodeRepulsion:function(N){return 4500},idealEdgeLength:function(N){return 50},edgeElasticity:function(N){return .45},nestingFactor:.1,gravity:.25,numIter:2500,tile:!0,tilingCompareBy:void 0,tilingPaddingVertical:10,tilingPaddingHorizontal:10,gravityRangeCompound:1.5,gravityCompound:1,gravityRange:3.8,initialEnergyOnIncremental:.3,fixedNodeConstraint:void 0,alignmentConstraint:void 0,relativePlacementConstraint:void 0,ready:function(){},stop:function(){}}),v=function(){function d(N){i(this,d),this.options=g({},T,N)}return f(d,[{key:"run",value:function(){var S=this,M=this.options,P=M.cy,K=M.eles,Y=[],k=[],D=void 0,rt=[];M.fixedNodeConstraint&&(!Array.isArray(M.fixedNodeConstraint)||M.fixedNodeConstraint.length==0)&&(M.fixedNodeConstraint=void 0),M.alignmentConstraint&&(M.alignmentConstraint.vertical&&(!Array.isArray(M.alignmentConstraint.vertical)||M.alignmentConstraint.vertical.length==0)&&(M.alignmentConstraint.vertical=void 0),M.alignmentConstraint.horizontal&&(!Array.isArray(M.alignmentConstraint.horizontal)||M.alignmentConstraint.horizontal.length==0)&&(M.alignmentConstraint.horizontal=void 0)),M.relativePlacementConstraint&&(!Array.isArray(M.relativePlacementConstraint)||M.relativePlacementConstraint.length==0)&&(M.relativePlacementConstraint=void 0);var a=M.fixedNodeConstraint||M.alignmentConstraint||M.relativePlacementConstraint;a&&(M.tile=!1,M.packComponents=!1);var m=void 0,p=!1;if(P.layoutUtilities&&M.packComponents&&(m=P.layoutUtilities("get"),m||(m=P.layoutUtilities()),p=!0),K.nodes().length>0)if(p){var I=t.getTopMostNodes(M.eles.nodes());if(D=t.connectComponents(P,M.eles,I),D.forEach(function(vt){var it=vt.boundingBox();rt.push({x:it.x1+it.w/2,y:it.y1+it.h/2})}),M.randomize&&D.forEach(function(vt){M.eles=vt,Y.push(o(M))}),M.quality=="default"||M.quality=="proof"){var w=P.collection();if(M.tile){var R=new Map,W=[],x=[],q=0,V={nodeIndexes:R,xCoords:W,yCoords:x},U=[];if(D.forEach(function(vt,it){vt.edges().length==0&&(vt.nodes().forEach(function(gt,Tt){w.merge(vt.nodes()[Tt]),gt.isParent()||(V.nodeIndexes.set(vt.nodes()[Tt].id(),q++),V.xCoords.push(vt.nodes()[0].position().x),V.yCoords.push(vt.nodes()[0].position().y))}),U.push(it))}),w.length>1){var et=w.boundingBox();rt.push({x:et.x1+et.w/2,y:et.y1+et.h/2}),D.push(w),Y.push(V);for(var z=U.length-1;z>=0;z--)D.splice(U[z],1),Y.splice(U[z],1),rt.splice(U[z],1)}}D.forEach(function(vt,it){M.eles=vt,k.push(h(M,Y[it])),t.relocateComponent(rt[it],k[it],M)})}else D.forEach(function(vt,it){t.relocateComponent(rt[it],Y[it],M)});var O=new Set;if(D.length>1){var H=[],B=K.filter(function(vt){return vt.css("display")=="none"});D.forEach(function(vt,it){var gt=void 0;if(M.quality=="draft"&&(gt=Y[it].nodeIndexes),vt.nodes().not(B).length>0){var Tt={};Tt.edges=[],Tt.nodes=[];var At=void 0;vt.nodes().not(B).forEach(function(Dt){if(M.quality=="draft")if(!Dt.isParent())At=gt.get(Dt.id()),Tt.nodes.push({x:Y[it].xCoords[At]-Dt.boundingbox().w/2,y:Y[it].yCoords[At]-Dt.boundingbox().h/2,width:Dt.boundingbox().w,height:Dt.boundingbox().h});else{var mt=t.calcBoundingBox(Dt,Y[it].xCoords,Y[it].yCoords,gt);Tt.nodes.push({x:mt.topLeftX,y:mt.topLeftY,width:mt.width,height:mt.height})}else k[it][Dt.id()]&&Tt.nodes.push({x:k[it][Dt.id()].getLeft(),y:k[it][Dt.id()].getTop(),width:k[it][Dt.id()].getWidth(),height:k[it][Dt.id()].getHeight()})}),vt.edges().forEach(function(Dt){var mt=Dt.source(),xt=Dt.target();if(mt.css("display")!="none"&&xt.css("display")!="none")if(M.quality=="draft"){var St=gt.get(mt.id()),Vt=gt.get(xt.id()),Xt=[],Ut=[];if(mt.isParent()){var bt=t.calcBoundingBox(mt,Y[it].xCoords,Y[it].yCoords,gt);Xt.push(bt.topLeftX+bt.width/2),Xt.push(bt.topLeftY+bt.height/2)}else Xt.push(Y[it].xCoords[St]),Xt.push(Y[it].yCoords[St]);if(xt.isParent()){var 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y=o(M);Y.push(y)}M.quality=="default"||M.quality=="proof"?(k.push(h(M,Y[0])),t.relocateComponent(rt[0],k[0],M)):t.relocateComponent(rt[0],Y[0],M)}var J=function(it,gt){if(M.quality=="default"||M.quality=="proof"){typeof it=="number"&&(it=gt);var Tt=void 0,At=void 0,Dt=it.data("id");return k.forEach(function(xt){Dt in xt&&(Tt={x:xt[Dt].getRect().getCenterX(),y:xt[Dt].getRect().getCenterY()},At=xt[Dt])}),M.nodeDimensionsIncludeLabels&&(At.labelWidth&&(At.labelPosHorizontal=="left"?Tt.x+=At.labelWidth/2:At.labelPosHorizontal=="right"&&(Tt.x-=At.labelWidth/2)),At.labelHeight&&(At.labelPosVertical=="top"?Tt.y+=At.labelHeight/2:At.labelPosVertical=="bottom"&&(Tt.y-=At.labelHeight/2))),Tt==null&&(Tt={x:it.position("x"),y:it.position("y")}),{x:Tt.x,y:Tt.y}}else{var mt=void 0;return Y.forEach(function(xt){var St=xt.nodeIndexes.get(it.id());St!=null&&(mt={x:xt.xCoords[St],y:xt.yCoords[St]})}),mt==null&&(mt={x:it.position("x"),y:it.position("y")}),{x:mt.x,y:mt.y}}};if(M.quality=="default"||M.quality=="proof"||M.randomize){var Rt=t.calcParentsWithoutChildren(P,K),Lt=K.filter(function(vt){return vt.css("display")=="none"});M.eles=K.not(Lt),K.nodes().not(":parent").not(Lt).layoutPositions(S,M,J),Rt.length>0&&Rt.forEach(function(vt){vt.position(J(vt))})}else console.log("If randomize option is set to false, then quality option must be 'default' or 'proof'.")}}]),d}();n.exports=v},657:(n,r,e)=>{var f=e(548),i=e(140).layoutBase.Matrix,g=e(140).layoutBase.SVD,t=function(o){var c=o.cy,h=o.eles,T=h.nodes(),v=h.nodes(":parent"),d=new Map,N=new Map,S=new Map,M=[],P=[],K=[],Y=[],k=[],D=[],rt=[],a=[],m=void 0,p=1e8,E=1e-9,y=o.piTol,I=o.samplingType,w=o.nodeSeparation,R=void 0,W=function(){for(var b=0,$=0,Q=!1;$<R;){b=Math.floor(Math.random()*m),Q=!1;for(var 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r(f,i,g){u.call(this,g),this.isOverlapingSourceAndTarget=!1,this.vGraphObject=g,this.bendpoints=[],this.source=f,this.target=i}r.prototype=Object.create(u.prototype);for(var e in u)r[e]=u[e];r.prototype.getSource=function(){return this.source},r.prototype.getTarget=function(){return this.target},r.prototype.isInterGraph=function(){return this.isInterGraph},r.prototype.getLength=function(){return this.length},r.prototype.isOverlapingSourceAndTarget=function(){return this.isOverlapingSourceAndTarget},r.prototype.getBendpoints=function(){return this.bendpoints},r.prototype.getLca=function(){return this.lca},r.prototype.getSourceInLca=function(){return this.sourceInLca},r.prototype.getTargetInLca=function(){return this.targetInLca},r.prototype.getOtherEnd=function(f){if(this.source===f)return this.target;if(this.target===f)return this.source;throw"Node is not incident with this edge"},r.prototype.getOtherEndInGraph=function(f,i){for(var g=this.getOtherEnd(f),t=i.getGraphManager().getRoot();;){if(g.getOwner()==i)return g;if(g.getOwner()==t)break;g=g.getOwner().getParent()}return null},r.prototype.updateLength=function(){var f=new Array(4);this.isOverlapingSourceAndTarget=l.getIntersection(this.target.getRect(),this.source.getRect(),f),this.isOverlapingSourceAndTarget||(this.lengthX=f[0]-f[2],this.lengthY=f[1]-f[3],Math.abs(this.lengthX)<1&&(this.lengthX=n.sign(this.lengthX)),Math.abs(this.lengthY)<1&&(this.lengthY=n.sign(this.lengthY)),this.length=Math.sqrt(this.lengthX*this.lengthX+this.lengthY*this.lengthY))},r.prototype.updateLengthSimple=function(){this.lengthX=this.target.getCenterX()-this.source.getCenterX(),this.lengthY=this.target.getCenterY()-this.source.getCenterY(),Math.abs(this.lengthX)<1&&(this.lengthX=n.sign(this.lengthX)),Math.abs(this.lengthY)<1&&(this.lengthY=n.sign(this.lengthY)),this.length=Math.sqrt(this.lengthX*this.lengthX+this.lengthY*this.lengthY)},A.exports=r},function(A,G,L){function 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this.rect.y+this.rect.height/2},i.prototype.getCenter=function(){return new f(this.rect.x+this.rect.width/2,this.rect.y+this.rect.height/2)},i.prototype.getLocation=function(){return new f(this.rect.x,this.rect.y)},i.prototype.getRect=function(){return this.rect},i.prototype.getDiagonal=function(){return Math.sqrt(this.rect.width*this.rect.width+this.rect.height*this.rect.height)},i.prototype.getHalfTheDiagonal=function(){return Math.sqrt(this.rect.height*this.rect.height+this.rect.width*this.rect.width)/2},i.prototype.setRect=function(t,s){this.rect.x=t.x,this.rect.y=t.y,this.rect.width=s.width,this.rect.height=s.height},i.prototype.setCenter=function(t,s){this.rect.x=t-this.rect.width/2,this.rect.y=s-this.rect.height/2},i.prototype.setLocation=function(t,s){this.rect.x=t,this.rect.y=s},i.prototype.moveBy=function(t,s){this.rect.x+=t,this.rect.y+=s},i.prototype.getEdgeListToNode=function(t){var s=[],o=this;return o.edges.forEach(function(c){if(c.target==t){if(c.source!=o)throw"Incorrect edge source!";s.push(c)}}),s},i.prototype.getEdgesBetween=function(t){var s=[],o=this;return o.edges.forEach(function(c){if(!(c.source==o||c.target==o))throw"Incorrect edge source and/or target";(c.target==t||c.source==t)&&s.push(c)}),s},i.prototype.getNeighborsList=function(){var t=new Set,s=this;return s.edges.forEach(function(o){if(o.source==s)t.add(o.target);else{if(o.target!=s)throw"Incorrect incidency!";t.add(o.source)}}),t},i.prototype.withChildren=function(){var t=new Set,s,o;if(t.add(this),this.child!=null)for(var c=this.child.getNodes(),h=0;h<c.length;h++)s=c[h],o=s.withChildren(),o.forEach(function(T){t.add(T)});return t},i.prototype.getNoOfChildren=function(){var t=0,s;if(this.child==null)t=1;else for(var o=this.child.getNodes(),c=0;c<o.length;c++)s=o[c],t+=s.getNoOfChildren();return t==0&&(t=1),t},i.prototype.getEstimatedSize=function(){if(this.estimatedSize==l.MIN_VALUE)throw"assert failed";return this.estimatedSize},i.prototype.calcEstimatedSize=function(){return this.child==null?this.estimatedSize=(this.rect.width+this.rect.height)/2:(this.estimatedSize=this.child.calcEstimatedSize(),this.rect.width=this.estimatedSize,this.rect.height=this.estimatedSize,this.estimatedSize)},i.prototype.scatter=function(){var t,s,o=-r.INITIAL_WORLD_BOUNDARY,c=r.INITIAL_WORLD_BOUNDARY;t=r.WORLD_CENTER_X+e.nextDouble()*(c-o)+o;var h=-r.INITIAL_WORLD_BOUNDARY,T=r.INITIAL_WORLD_BOUNDARY;s=r.WORLD_CENTER_Y+e.nextDouble()*(T-h)+h,this.rect.x=t,this.rect.y=s},i.prototype.updateBounds=function(){if(this.getChild()==null)throw"assert failed";if(this.getChild().getNodes().length!=0){var t=this.getChild();if(t.updateBounds(!0),this.rect.x=t.getLeft(),this.rect.y=t.getTop(),this.setWidth(t.getRight()-t.getLeft()),this.setHeight(t.getBottom()-t.getTop()),r.NODE_DIMENSIONS_INCLUDE_LABELS){var s=t.getRight()-t.getLeft(),o=t.getBottom()-t.getTop();this.labelWidth&&(this.labelPosHorizontal=="left"?(this.rect.x-=this.labelWidth,this.setWidth(s+this.labelWidth)):this.labelPosHorizontal=="center"&&this.labelWidth>s?(this.rect.x-=(this.labelWidth-s)/2,this.setWidth(this.labelWidth)):this.labelPosHorizontal=="right"&&this.setWidth(s+this.labelWidth)),this.labelHeight&&(this.labelPosVertical=="top"?(this.rect.y-=this.labelHeight,this.setHeight(o+this.labelHeight)):this.labelPosVertical=="center"&&this.labelHeight>o?(this.rect.y-=(this.labelHeight-o)/2,this.setHeight(this.labelHeight)):this.labelPosVertical=="bottom"&&this.setHeight(o+this.labelHeight))}}},i.prototype.getInclusionTreeDepth=function(){if(this.inclusionTreeDepth==l.MAX_VALUE)throw"assert failed";return this.inclusionTreeDepth},i.prototype.transform=function(t){var s=this.rect.x;s>r.WORLD_BOUNDARY?s=r.WORLD_BOUNDARY:s<-r.WORLD_BOUNDARY&&(s=-r.WORLD_BOUNDARY);var o=this.rect.y;o>r.WORLD_BOUNDARY?o=r.WORLD_BOUNDARY:o<-r.WORLD_BOUNDARY&&(o=-r.WORLD_BOUNDARY);var c=new f(s,o),h=t.inverseTransformPoint(c);this.setLocation(h.x,h.y)},i.prototype.getLeft=function(){return this.rect.x},i.prototype.getRight=function(){return this.rect.x+this.rect.width},i.prototype.getTop=function(){return this.rect.y},i.prototype.getBottom=function(){return this.rect.y+this.rect.height},i.prototype.getParent=function(){return this.owner==null?null:this.owner.getParent()},A.exports=i},function(A,G,L){var u=L(0);function l(){}for(var n in u)l[n]=u[n];l.MAX_ITERATIONS=2500,l.DEFAULT_EDGE_LENGTH=50,l.DEFAULT_SPRING_STRENGTH=.45,l.DEFAULT_REPULSION_STRENGTH=4500,l.DEFAULT_GRAVITY_STRENGTH=.4,l.DEFAULT_COMPOUND_GRAVITY_STRENGTH=1,l.DEFAULT_GRAVITY_RANGE_FACTOR=3.8,l.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR=1.5,l.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION=!0,l.DEFAULT_USE_SMART_REPULSION_RANGE_CALCULATION=!0,l.DEFAULT_COOLING_FACTOR_INCREMENTAL=.3,l.COOLING_ADAPTATION_FACTOR=.33,l.ADAPTATION_LOWER_NODE_LIMIT=1e3,l.ADAPTATION_UPPER_NODE_LIMIT=5e3,l.MAX_NODE_DISPLACEMENT_INCREMENTAL=100,l.MAX_NODE_DISPLACEMENT=l.MAX_NODE_DISPLACEMENT_INCREMENTAL*3,l.MIN_REPULSION_DIST=l.DEFAULT_EDGE_LENGTH/10,l.CONVERGENCE_CHECK_PERIOD=100,l.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR=.1,l.MIN_EDGE_LENGTH=1,l.GRID_CALCULATION_CHECK_PERIOD=10,A.exports=l},function(A,G,L){function u(l,n){l==null&&n==null?(this.x=0,this.y=0):(this.x=l,this.y=n)}u.prototype.getX=function(){return this.x},u.prototype.getY=function(){return this.y},u.prototype.setX=function(l){this.x=l},u.prototype.setY=function(l){this.y=l},u.prototype.getDifference=function(l){return new DimensionD(this.x-l.x,this.y-l.y)},u.prototype.getCopy=function(){return new u(this.x,this.y)},u.prototype.translate=function(l){return this.x+=l.width,this.y+=l.height,this},A.exports=u},function(A,G,L){var u=L(2),l=L(10),n=L(0),r=L(7),e=L(3),f=L(1),i=L(13),g=L(12),t=L(11);function s(c,h,T){u.call(this,T),this.estimatedSize=l.MIN_VALUE,this.margin=n.DEFAULT_GRAPH_MARGIN,this.edges=[],this.nodes=[],this.isConnected=!1,this.parent=c,h!=null&&h instanceof r?this.graphManager=h:h!=null&&h instanceof Layout&&(this.graphManager=h.graphManager)}s.prototype=Object.create(u.prototype);for(var o in u)s[o]=u[o];s.prototype.getNodes=function(){return this.nodes},s.prototype.getEdges=function(){return this.edges},s.prototype.getGraphManager=function(){return this.graphManager},s.prototype.getParent=function(){return this.parent},s.prototype.getLeft=function(){return this.left},s.prototype.getRight=function(){return this.right},s.prototype.getTop=function(){return this.top},s.prototype.getBottom=function(){return this.bottom},s.prototype.isConnected=function(){return this.isConnected},s.prototype.add=function(c,h,T){if(h==null&&T==null){var v=c;if(this.graphManager==null)throw"Graph has no graph mgr!";if(this.getNodes().indexOf(v)>-1)throw"Node already in graph!";return v.owner=this,this.getNodes().push(v),v}else{var d=c;if(!(this.getNodes().indexOf(h)>-1&&this.getNodes().indexOf(T)>-1))throw"Source or target not in graph!";if(!(h.owner==T.owner&&h.owner==this))throw"Both owners must be this graph!";return h.owner!=T.owner?null:(d.source=h,d.target=T,d.isInterGraph=!1,this.getEdges().push(d),h.edges.push(d),T!=h&&T.edges.push(d),d)}},s.prototype.remove=function(c){var h=c;if(c instanceof e){if(h==null)throw"Node is null!";if(!(h.owner!=null&&h.owner==this))throw"Owner graph is invalid!";if(this.graphManager==null)throw"Owner graph manager is invalid!";for(var T=h.edges.slice(),v,d=T.length,N=0;N<d;N++)v=T[N],v.isInterGraph?this.graphManager.remove(v):v.source.owner.remove(v);var S=this.nodes.indexOf(h);if(S==-1)throw"Node not in owner node list!";this.nodes.splice(S,1)}else if(c instanceof f){var v=c;if(v==null)throw"Edge is null!";if(!(v.source!=null&&v.target!=null))throw"Source and/or target is null!";if(!(v.source.owner!=null&&v.target.owner!=null&&v.source.owner==this&&v.target.owner==this))throw"Source and/or target owner is invalid!";var M=v.source.edges.indexOf(v),P=v.target.edges.indexOf(v);if(!(M>-1&&P>-1))throw"Source and/or target doesn't know this edge!";v.source.edges.splice(M,1),v.target!=v.source&&v.target.edges.splice(P,1);var S=v.source.owner.getEdges().indexOf(v);if(S==-1)throw"Not in owner's edge list!";v.source.owner.getEdges().splice(S,1)}},s.prototype.updateLeftTop=function(){for(var c=l.MAX_VALUE,h=l.MAX_VALUE,T,v,d,N=this.getNodes(),S=N.length,M=0;M<S;M++){var P=N[M];T=P.getTop(),v=P.getLeft(),c>T&&(c=T),h>v&&(h=v)}return c==l.MAX_VALUE?null:(N[0].getParent().paddingLeft!=null?d=N[0].getParent().paddingLeft:d=this.margin,this.left=h-d,this.top=c-d,new g(this.left,this.top))},s.prototype.updateBounds=function(c){for(var h=l.MAX_VALUE,T=-l.MAX_VALUE,v=l.MAX_VALUE,d=-l.MAX_VALUE,N,S,M,P,K,Y=this.nodes,k=Y.length,D=0;D<k;D++){var rt=Y[D];c&&rt.child!=null&&rt.updateBounds(),N=rt.getLeft(),S=rt.getRight(),M=rt.getTop(),P=rt.getBottom(),h>N&&(h=N),T<S&&(T=S),v>M&&(v=M),d<P&&(d=P)}var a=new i(h,v,T-h,d-v);h==l.MAX_VALUE&&(this.left=this.parent.getLeft(),this.right=this.parent.getRight(),this.top=this.parent.getTop(),this.bottom=this.parent.getBottom()),Y[0].getParent().paddingLeft!=null?K=Y[0].getParent().paddingLeft:K=this.margin,this.left=a.x-K,this.right=a.x+a.width+K,this.top=a.y-K,this.bottom=a.y+a.height+K},s.calculateBounds=function(c){for(var h=l.MAX_VALUE,T=-l.MAX_VALUE,v=l.MAX_VALUE,d=-l.MAX_VALUE,N,S,M,P,K=c.length,Y=0;Y<K;Y++){var k=c[Y];N=k.getLeft(),S=k.getRight(),M=k.getTop(),P=k.getBottom(),h>N&&(h=N),T<S&&(T=S),v>M&&(v=M),d<P&&(d=P)}var D=new i(h,v,T-h,d-v);return D},s.prototype.getInclusionTreeDepth=function(){return this==this.graphManager.getRoot()?1:this.parent.getInclusionTreeDepth()},s.prototype.getEstimatedSize=function(){if(this.estimatedSize==l.MIN_VALUE)throw"assert failed";return this.estimatedSize},s.prototype.calcEstimatedSize=function(){for(var c=0,h=this.nodes,T=h.length,v=0;v<T;v++){var d=h[v];c+=d.calcEstimatedSize()}return c==0?this.estimatedSize=n.EMPTY_COMPOUND_NODE_SIZE:this.estimatedSize=c/Math.sqrt(this.nodes.length),this.estimatedSize},s.prototype.updateConnected=function(){var c=this;if(this.nodes.length==0){this.isConnected=!0;return}var h=new t,T=new Set,v=this.nodes[0],d,N,S=v.withChildren();for(S.forEach(function(D){h.push(D),T.add(D)});h.length!==0;){v=h.shift(),d=v.getEdges();for(var M=d.length,P=0;P<M;P++){var K=d[P];if(N=K.getOtherEndInGraph(v,this),N!=null&&!T.has(N)){var Y=N.withChildren();Y.forEach(function(D){h.push(D),T.add(D)})}}}if(this.isConnected=!1,T.size>=this.nodes.length){var k=0;T.forEach(function(D){D.owner==c&&k++}),k==this.nodes.length&&(this.isConnected=!0)}},A.exports=s},function(A,G,L){var u,l=L(1);function n(r){u=L(6),this.layout=r,this.graphs=[],this.edges=[]}n.prototype.addRoot=function(){var r=this.layout.newGraph(),e=this.layout.newNode(null),f=this.add(r,e);return this.setRootGraph(f),this.rootGraph},n.prototype.add=function(r,e,f,i,g){if(f==null&&i==null&&g==null){if(r==null)throw"Graph is null!";if(e==null)throw"Parent node is null!";if(this.graphs.indexOf(r)>-1)throw"Graph already in this graph mgr!";if(this.graphs.push(r),r.parent!=null)throw"Already has a parent!";if(e.child!=null)throw"Already has a child!";return r.parent=e,e.child=r,r}else{g=f,i=e,f=r;var t=i.getOwner(),s=g.getOwner();if(!(t!=null&&t.getGraphManager()==this))throw"Source not in this graph mgr!";if(!(s!=null&&s.getGraphManager()==this))throw"Target not in this graph mgr!";if(t==s)return f.isInterGraph=!1,t.add(f,i,g);if(f.isInterGraph=!0,f.source=i,f.target=g,this.edges.indexOf(f)>-1)throw"Edge already in inter-graph edge list!";if(this.edges.push(f),!(f.source!=null&&f.target!=null))throw"Edge source and/or target is null!";if(!(f.source.edges.indexOf(f)==-1&&f.target.edges.indexOf(f)==-1))throw"Edge already in source and/or target incidency list!";return f.source.edges.push(f),f.target.edges.push(f),f}},n.prototype.remove=function(r){if(r instanceof u){var e=r;if(e.getGraphManager()!=this)throw"Graph not in this graph mgr";if(!(e==this.rootGraph||e.parent!=null&&e.parent.graphManager==this))throw"Invalid parent node!";var f=[];f=f.concat(e.getEdges());for(var i,g=f.length,t=0;t<g;t++)i=f[t],e.remove(i);var s=[];s=s.concat(e.getNodes());var o;g=s.length;for(var t=0;t<g;t++)o=s[t],e.remove(o);e==this.rootGraph&&this.setRootGraph(null);var c=this.graphs.indexOf(e);this.graphs.splice(c,1),e.parent=null}else if(r instanceof l){if(i=r,i==null)throw"Edge is null!";if(!i.isInterGraph)throw"Not an inter-graph edge!";if(!(i.source!=null&&i.target!=null))throw"Source and/or target is null!";if(!(i.source.edges.indexOf(i)!=-1&&i.target.edges.indexOf(i)!=-1))throw"Source and/or target doesn't know this edge!";var c=i.source.edges.indexOf(i);if(i.source.edges.splice(c,1),c=i.target.edges.indexOf(i),i.target.edges.splice(c,1),!(i.source.owner!=null&&i.source.owner.getGraphManager()!=null))throw"Edge owner graph or owner graph manager is null!";if(i.source.owner.getGraphManager().edges.indexOf(i)==-1)throw"Not in owner graph manager's edge list!";var c=i.source.owner.getGraphManager().edges.indexOf(i);i.source.owner.getGraphManager().edges.splice(c,1)}},n.prototype.updateBounds=function(){this.rootGraph.updateBounds(!0)},n.prototype.getGraphs=function(){return this.graphs},n.prototype.getAllNodes=function(){if(this.allNodes==null){for(var r=[],e=this.getGraphs(),f=e.length,i=0;i<f;i++)r=r.concat(e[i].getNodes());this.allNodes=r}return this.allNodes},n.prototype.resetAllNodes=function(){this.allNodes=null},n.prototype.resetAllEdges=function(){this.allEdges=null},n.prototype.resetAllNodesToApplyGravitation=function(){this.allNodesToApplyGravitation=null},n.prototype.getAllEdges=function(){if(this.allEdges==null){var r=[],e=this.getGraphs();e.length;for(var f=0;f<e.length;f++)r=r.concat(e[f].getEdges());r=r.concat(this.edges),this.allEdges=r}return this.allEdges},n.prototype.getAllNodesToApplyGravitation=function(){return this.allNodesToApplyGravitation},n.prototype.setAllNodesToApplyGravitation=function(r){if(this.allNodesToApplyGravitation!=null)throw"assert failed";this.allNodesToApplyGravitation=r},n.prototype.getRoot=function(){return this.rootGraph},n.prototype.setRootGraph=function(r){if(r.getGraphManager()!=this)throw"Root not in this graph mgr!";this.rootGraph=r,r.parent==null&&(r.parent=this.layout.newNode("Root node"))},n.prototype.getLayout=function(){return this.layout},n.prototype.isOneAncestorOfOther=function(r,e){if(!(r!=null&&e!=null))throw"assert failed";if(r==e)return!0;var f=r.getOwner(),i;do{if(i=f.getParent(),i==null)break;if(i==e)return!0;if(f=i.getOwner(),f==null)break}while(!0);f=e.getOwner();do{if(i=f.getParent(),i==null)break;if(i==r)return!0;if(f=i.getOwner(),f==null)break}while(!0);return!1},n.prototype.calcLowestCommonAncestors=function(){for(var r,e,f,i,g,t=this.getAllEdges(),s=t.length,o=0;o<s;o++){if(r=t[o],e=r.source,f=r.target,r.lca=null,r.sourceInLca=e,r.targetInLca=f,e==f){r.lca=e.getOwner();continue}for(i=e.getOwner();r.lca==null;){for(r.targetInLca=f,g=f.getOwner();r.lca==null;){if(g==i){r.lca=g;break}if(g==this.rootGraph)break;if(r.lca!=null)throw"assert failed";r.targetInLca=g.getParent(),g=r.targetInLca.getOwner()}if(i==this.rootGraph)break;r.lca==null&&(r.sourceInLca=i.getParent(),i=r.sourceInLca.getOwner())}if(r.lca==null)throw"assert failed"}},n.prototype.calcLowestCommonAncestor=function(r,e){if(r==e)return r.getOwner();var f=r.getOwner();do{if(f==null)break;var i=e.getOwner();do{if(i==null)break;if(i==f)return i;i=i.getParent().getOwner()}while(!0);f=f.getParent().getOwner()}while(!0);return f},n.prototype.calcInclusionTreeDepths=function(r,e){r==null&&e==null&&(r=this.rootGraph,e=1);for(var f,i=r.getNodes(),g=i.length,t=0;t<g;t++)f=i[t],f.inclusionTreeDepth=e,f.child!=null&&this.calcInclusionTreeDepths(f.child,e+1)},n.prototype.includesInvalidEdge=function(){for(var r,e=[],f=this.edges.length,i=0;i<f;i++)r=this.edges[i],this.isOneAncestorOfOther(r.source,r.target)&&e.push(r);for(var i=0;i<e.length;i++)this.remove(e[i]);return!1},A.exports=n},function(A,G,L){var u=L(12);function l(){}l.calcSeparationAmount=function(n,r,e,f){if(!n.intersects(r))throw"assert failed";var i=new Array(2);this.decideDirectionsForOverlappingNodes(n,r,i),e[0]=Math.min(n.getRight(),r.getRight())-Math.max(n.x,r.x),e[1]=Math.min(n.getBottom(),r.getBottom())-Math.max(n.y,r.y),n.getX()<=r.getX()&&n.getRight()>=r.getRight()?e[0]+=Math.min(r.getX()-n.getX(),n.getRight()-r.getRight()):r.getX()<=n.getX()&&r.getRight()>=n.getRight()&&(e[0]+=Math.min(n.getX()-r.getX(),r.getRight()-n.getRight())),n.getY()<=r.getY()&&n.getBottom()>=r.getBottom()?e[1]+=Math.min(r.getY()-n.getY(),n.getBottom()-r.getBottom()):r.getY()<=n.getY()&&r.getBottom()>=n.getBottom()&&(e[1]+=Math.min(n.getY()-r.getY(),r.getBottom()-n.getBottom()));var g=Math.abs((r.getCenterY()-n.getCenterY())/(r.getCenterX()-n.getCenterX()));r.getCenterY()===n.getCenterY()&&r.getCenterX()===n.getCenterX()&&(g=1);var t=g*e[0],s=e[1]/g;e[0]<s?s=e[0]:t=e[1],e[0]=-1*i[0]*(s/2+f),e[1]=-1*i[1]*(t/2+f)},l.decideDirectionsForOverlappingNodes=function(n,r,e){n.getCenterX()<r.getCenterX()?e[0]=-1:e[0]=1,n.getCenterY()<r.getCenterY()?e[1]=-1:e[1]=1},l.getIntersection2=function(n,r,e){var f=n.getCenterX(),i=n.getCenterY(),g=r.getCenterX(),t=r.getCenterY();if(n.intersects(r))return e[0]=f,e[1]=i,e[2]=g,e[3]=t,!0;var s=n.getX(),o=n.getY(),c=n.getRight(),h=n.getX(),T=n.getBottom(),v=n.getRight(),d=n.getWidthHalf(),N=n.getHeightHalf(),S=r.getX(),M=r.getY(),P=r.getRight(),K=r.getX(),Y=r.getBottom(),k=r.getRight(),D=r.getWidthHalf(),rt=r.getHeightHalf(),a=!1,m=!1;if(f===g){if(i>t)return e[0]=f,e[1]=o,e[2]=g,e[3]=Y,!1;if(i<t)return e[0]=f,e[1]=T,e[2]=g,e[3]=M,!1}else if(i===t){if(f>g)return e[0]=s,e[1]=i,e[2]=P,e[3]=t,!1;if(f<g)return e[0]=c,e[1]=i,e[2]=S,e[3]=t,!1}else{var p=n.height/n.width,E=r.height/r.width,y=(t-i)/(g-f),I=void 0,w=void 0,R=void 0,W=void 0,x=void 0,q=void 0;if(-p===y?f>g?(e[0]=h,e[1]=T,a=!0):(e[0]=c,e[1]=o,a=!0):p===y&&(f>g?(e[0]=s,e[1]=o,a=!0):(e[0]=v,e[1]=T,a=!0)),-E===y?g>f?(e[2]=K,e[3]=Y,m=!0):(e[2]=P,e[3]=M,m=!0):E===y&&(g>f?(e[2]=S,e[3]=M,m=!0):(e[2]=k,e[3]=Y,m=!0)),a&&m)return!1;if(f>g?i>t?(I=this.getCardinalDirection(p,y,4),w=this.getCardinalDirection(E,y,2)):(I=this.getCardinalDirection(-p,y,3),w=this.getCardinalDirection(-E,y,1)):i>t?(I=this.getCardinalDirection(-p,y,1),w=this.getCardinalDirection(-E,y,3)):(I=this.getCardinalDirection(p,y,2),w=this.getCardinalDirection(E,y,4)),!a)switch(I){case 1:W=o,R=f+-N/y,e[0]=R,e[1]=W;break;case 2:R=v,W=i+d*y,e[0]=R,e[1]=W;break;case 3:W=T,R=f+N/y,e[0]=R,e[1]=W;break;case 4:R=h,W=i+-d*y,e[0]=R,e[1]=W;break}if(!m)switch(w){case 1:q=M,x=g+-rt/y,e[2]=x,e[3]=q;break;case 2:x=k,q=t+D*y,e[2]=x,e[3]=q;break;case 3:q=Y,x=g+rt/y,e[2]=x,e[3]=q;break;case 4:x=K,q=t+-D*y,e[2]=x,e[3]=q;break}}return!1},l.getCardinalDirection=function(n,r,e){return n>r?e:1+e%4},l.getIntersection=function(n,r,e,f){if(f==null)return this.getIntersection2(n,r,e);var i=n.x,g=n.y,t=r.x,s=r.y,o=e.x,c=e.y,h=f.x,T=f.y,v=void 0,d=void 0,N=void 0,S=void 0,M=void 0,P=void 0,K=void 0,Y=void 0,k=void 0;return N=s-g,M=i-t,K=t*g-i*s,S=T-c,P=o-h,Y=h*c-o*T,k=N*P-S*M,k===0?null:(v=(M*Y-P*K)/k,d=(S*K-N*Y)/k,new u(v,d))},l.angleOfVector=function(n,r,e,f){var i=void 0;return n!==e?(i=Math.atan((f-r)/(e-n)),e<n?i+=Math.PI:f<r&&(i+=this.TWO_PI)):f<r?i=this.ONE_AND_HALF_PI:i=this.HALF_PI,i},l.doIntersect=function(n,r,e,f){var i=n.x,g=n.y,t=r.x,s=r.y,o=e.x,c=e.y,h=f.x,T=f.y,v=(t-i)*(T-c)-(h-o)*(s-g);if(v===0)return!1;var d=((T-c)*(h-i)+(o-h)*(T-g))/v,N=((g-s)*(h-i)+(t-i)*(T-g))/v;return 0<d&&d<1&&0<N&&N<1},l.findCircleLineIntersections=function(n,r,e,f,i,g,t){var s=(e-n)*(e-n)+(f-r)*(f-r),o=2*((n-i)*(e-n)+(r-g)*(f-r)),c=(n-i)*(n-i)+(r-g)*(r-g)-t*t,h=o*o-4*s*c;if(h>=0){var T=(-o+Math.sqrt(o*o-4*s*c))/(2*s),v=(-o-Math.sqrt(o*o-4*s*c))/(2*s),d=null;return T>=0&&T<=1?[T]:v>=0&&v<=1?[v]:d}else return null},l.HALF_PI=.5*Math.PI,l.ONE_AND_HALF_PI=1.5*Math.PI,l.TWO_PI=2*Math.PI,l.THREE_PI=3*Math.PI,A.exports=l},function(A,G,L){function u(){}u.sign=function(l){return l>0?1:l<0?-1:0},u.floor=function(l){return l<0?Math.ceil(l):Math.floor(l)},u.ceil=function(l){return l<0?Math.floor(l):Math.ceil(l)},A.exports=u},function(A,G,L){function u(){}u.MAX_VALUE=2147483647,u.MIN_VALUE=-2147483648,A.exports=u},function(A,G,L){var u=function(){function i(g,t){for(var s=0;s<t.length;s++){var o=t[s];o.enumerable=o.enumerable||!1,o.configurable=!0,"value"in o&&(o.writable=!0),Object.defineProperty(g,o.key,o)}}return function(g,t,s){return t&&i(g.prototype,t),s&&i(g,s),g}}();function l(i,g){if(!(i instanceof g))throw new TypeError("Cannot call a class as a function")}var n=function(g){return{value:g,next:null,prev:null}},r=function(g,t,s,o){return g!==null?g.next=t:o.head=t,s!==null?s.prev=t:o.tail=t,t.prev=g,t.next=s,o.length++,t},e=function(g,t){var s=g.prev,o=g.next;return s!==null?s.next=o:t.head=o,o!==null?o.prev=s:t.tail=s,g.prev=g.next=null,t.length--,g},f=function(){function i(g){var t=this;l(this,i),this.length=0,this.head=null,this.tail=null,g!=null&&g.forEach(function(s){return t.push(s)})}return u(i,[{key:"size",value:function(){return this.length}},{key:"insertBefore",value:function(t,s){return r(s.prev,n(t),s,this)}},{key:"insertAfter",value:function(t,s){return r(s,n(t),s.next,this)}},{key:"insertNodeBefore",value:function(t,s){return r(s.prev,t,s,this)}},{key:"insertNodeAfter",value:function(t,s){return r(s,t,s.next,this)}},{key:"push",value:function(t){return r(this.tail,n(t),null,this)}},{key:"unshift",value:function(t){return r(null,n(t),this.head,this)}},{key:"remove",value:function(t){return e(t,this)}},{key:"pop",value:function(){return e(this.tail,this).value}},{key:"popNode",value:function(){return e(this.tail,this)}},{key:"shift",value:function(){return e(this.head,this).value}},{key:"shiftNode",value:function(){return e(this.head,this)}},{key:"get_object_at",value:function(t){if(t<=this.length()){for(var s=1,o=this.head;s<t;)o=o.next,s++;return o.value}}},{key:"set_object_at",value:function(t,s){if(t<=this.length()){for(var o=1,c=this.head;o<t;)c=c.next,o++;c.value=s}}}]),i}();A.exports=f},function(A,G,L){function u(l,n,r){this.x=null,this.y=null,l==null&&n==null&&r==null?(this.x=0,this.y=0):typeof l=="number"&&typeof n=="number"&&r==null?(this.x=l,this.y=n):l.constructor.name=="Point"&&n==null&&r==null&&(r=l,this.x=r.x,this.y=r.y)}u.prototype.getX=function(){return this.x},u.prototype.getY=function(){return this.y},u.prototype.getLocation=function(){return new u(this.x,this.y)},u.prototype.setLocation=function(l,n,r){l.constructor.name=="Point"&&n==null&&r==null?(r=l,this.setLocation(r.x,r.y)):typeof l=="number"&&typeof n=="number"&&r==null&&(parseInt(l)==l&&parseInt(n)==n?this.move(l,n):(this.x=Math.floor(l+.5),this.y=Math.floor(n+.5)))},u.prototype.move=function(l,n){this.x=l,this.y=n},u.prototype.translate=function(l,n){this.x+=l,this.y+=n},u.prototype.equals=function(l){if(l.constructor.name=="Point"){var n=l;return this.x==n.x&&this.y==n.y}return this==l},u.prototype.toString=function(){return new u().constructor.name+"[x="+this.x+",y="+this.y+"]"},A.exports=u},function(A,G,L){function u(l,n,r,e){this.x=0,this.y=0,this.width=0,this.height=0,l!=null&&n!=null&&r!=null&&e!=null&&(this.x=l,this.y=n,this.width=r,this.height=e)}u.prototype.getX=function(){return this.x},u.prototype.setX=function(l){this.x=l},u.prototype.getY=function(){return this.y},u.prototype.setY=function(l){this.y=l},u.prototype.getWidth=function(){return this.width},u.prototype.setWidth=function(l){this.width=l},u.prototype.getHeight=function(){return this.height},u.prototype.setHeight=function(l){this.height=l},u.prototype.getRight=function(){return this.x+this.width},u.prototype.getBottom=function(){return this.y+this.height},u.prototype.intersects=function(l){return!(this.getRight()<l.x||this.getBottom()<l.y||l.getRight()<this.x||l.getBottom()<this.y)},u.prototype.getCenterX=function(){return this.x+this.width/2},u.prototype.getMinX=function(){return this.getX()},u.prototype.getMaxX=function(){return this.getX()+this.width},u.prototype.getCenterY=function(){return this.y+this.height/2},u.prototype.getMinY=function(){return this.getY()},u.prototype.getMaxY=function(){return this.getY()+this.height},u.prototype.getWidthHalf=function(){return this.width/2},u.prototype.getHeightHalf=function(){return this.height/2},A.exports=u},function(A,G,L){var u=typeof Symbol=="function"&&typeof Symbol.iterator=="symbol"?function(n){return typeof n}:function(n){return n&&typeof Symbol=="function"&&n.constructor===Symbol&&n!==Symbol.prototype?"symbol":typeof n};function l(){}l.lastID=0,l.createID=function(n){return l.isPrimitive(n)?n:(n.uniqueID!=null||(n.uniqueID=l.getString(),l.lastID++),n.uniqueID)},l.getString=function(n){return n==null&&(n=l.lastID),"Object#"+n},l.isPrimitive=function(n){var r=typeof n>"u"?"undefined":u(n);return n==null||r!="object"&&r!="function"},A.exports=l},function(A,G,L){function u(o){if(Array.isArray(o)){for(var c=0,h=Array(o.length);c<o.length;c++)h[c]=o[c];return h}else return Array.from(o)}var l=L(0),n=L(7),r=L(3),e=L(1),f=L(6),i=L(5),g=L(17),t=L(29);function s(o){t.call(this),this.layoutQuality=l.QUALITY,this.createBendsAsNeeded=l.DEFAULT_CREATE_BENDS_AS_NEEDED,this.incremental=l.DEFAULT_INCREMENTAL,this.animationOnLayout=l.DEFAULT_ANIMATION_ON_LAYOUT,this.animationDuringLayout=l.DEFAULT_ANIMATION_DURING_LAYOUT,this.animationPeriod=l.DEFAULT_ANIMATION_PERIOD,this.uniformLeafNodeSizes=l.DEFAULT_UNIFORM_LEAF_NODE_SIZES,this.edgeToDummyNodes=new Map,this.graphManager=new n(this),this.isLayoutFinished=!1,this.isSubLayout=!1,this.isRemoteUse=!1,o!=null&&(this.isRemoteUse=o)}s.RANDOM_SEED=1,s.prototype=Object.create(t.prototype),s.prototype.getGraphManager=function(){return this.graphManager},s.prototype.getAllNodes=function(){return this.graphManager.getAllNodes()},s.prototype.getAllEdges=function(){return this.graphManager.getAllEdges()},s.prototype.getAllNodesToApplyGravitation=function(){return this.graphManager.getAllNodesToApplyGravitation()},s.prototype.newGraphManager=function(){var o=new n(this);return this.graphManager=o,o},s.prototype.newGraph=function(o){return new f(null,this.graphManager,o)},s.prototype.newNode=function(o){return new r(this.graphManager,o)},s.prototype.newEdge=function(o){return new e(null,null,o)},s.prototype.checkLayoutSuccess=function(){return this.graphManager.getRoot()==null||this.graphManager.getRoot().getNodes().length==0||this.graphManager.includesInvalidEdge()},s.prototype.runLayout=function(){this.isLayoutFinished=!1,this.tilingPreLayout&&this.tilingPreLayout(),this.initParameters();var o;return this.checkLayoutSuccess()?o=!1:o=this.layout(),l.ANIMATE==="during"?!1:(o&&(this.isSubLayout||this.doPostLayout()),this.tilingPostLayout&&this.tilingPostLayout(),this.isLayoutFinished=!0,o)},s.prototype.doPostLayout=function(){this.incremental||this.transform(),this.update()},s.prototype.update2=function(){if(this.createBendsAsNeeded&&(this.createBendpointsFromDummyNodes(),this.graphManager.resetAllEdges()),!this.isRemoteUse){for(var o=this.graphManager.getAllEdges(),c=0;c<o.length;c++)o[c];for(var h=this.graphManager.getRoot().getNodes(),c=0;c<h.length;c++)h[c];this.update(this.graphManager.getRoot())}},s.prototype.update=function(o){if(o==null)this.update2();else if(o instanceof r){var c=o;if(c.getChild()!=null)for(var h=c.getChild().getNodes(),T=0;T<h.length;T++)update(h[T]);if(c.vGraphObject!=null){var v=c.vGraphObject;v.update(c)}}else if(o instanceof e){var d=o;if(d.vGraphObject!=null){var N=d.vGraphObject;N.update(d)}}else if(o instanceof f){var S=o;if(S.vGraphObject!=null){var M=S.vGraphObject;M.update(S)}}},s.prototype.initParameters=function(){this.isSubLayout||(this.layoutQuality=l.QUALITY,this.animationDuringLayout=l.DEFAULT_ANIMATION_DURING_LAYOUT,this.animationPeriod=l.DEFAULT_ANIMATION_PERIOD,this.animationOnLayout=l.DEFAULT_ANIMATION_ON_LAYOUT,this.incremental=l.DEFAULT_INCREMENTAL,this.createBendsAsNeeded=l.DEFAULT_CREATE_BENDS_AS_NEEDED,this.uniformLeafNodeSizes=l.DEFAULT_UNIFORM_LEAF_NODE_SIZES),this.animationDuringLayout&&(this.animationOnLayout=!1)},s.prototype.transform=function(o){if(o==null)this.transform(new i(0,0));else{var c=new g,h=this.graphManager.getRoot().updateLeftTop();if(h!=null){c.setWorldOrgX(o.x),c.setWorldOrgY(o.y),c.setDeviceOrgX(h.x),c.setDeviceOrgY(h.y);for(var T=this.getAllNodes(),v,d=0;d<T.length;d++)v=T[d],v.transform(c)}}},s.prototype.positionNodesRandomly=function(o){if(o==null)this.positionNodesRandomly(this.getGraphManager().getRoot()),this.getGraphManager().getRoot().updateBounds(!0);else for(var c,h,T=o.getNodes(),v=0;v<T.length;v++)c=T[v],h=c.getChild(),h==null||h.getNodes().length==0?c.scatter():(this.positionNodesRandomly(h),c.updateBounds())},s.prototype.getFlatForest=function(){for(var o=[],c=!0,h=this.graphManager.getRoot().getNodes(),T=!0,v=0;v<h.length;v++)h[v].getChild()!=null&&(T=!1);if(!T)return o;var d=new Set,N=[],S=new Map,M=[];for(M=M.concat(h);M.length>0&&c;){for(N.push(M[0]);N.length>0&&c;){var P=N[0];N.splice(0,1),d.add(P);for(var K=P.getEdges(),v=0;v<K.length;v++){var Y=K[v].getOtherEnd(P);if(S.get(P)!=Y)if(!d.has(Y))N.push(Y),S.set(Y,P);else{c=!1;break}}}if(!c)o=[];else{var k=[].concat(u(d));o.push(k);for(var v=0;v<k.length;v++){var D=k[v],rt=M.indexOf(D);rt>-1&&M.splice(rt,1)}d=new Set,S=new Map}}return o},s.prototype.createDummyNodesForBendpoints=function(o){for(var c=[],h=o.source,T=this.graphManager.calcLowestCommonAncestor(o.source,o.target),v=0;v<o.bendpoints.length;v++){var d=this.newNode(null);d.setRect(new Point(0,0),new Dimension(1,1)),T.add(d);var N=this.newEdge(null);this.graphManager.add(N,h,d),c.add(d),h=d}var N=this.newEdge(null);return this.graphManager.add(N,h,o.target),this.edgeToDummyNodes.set(o,c),o.isInterGraph()?this.graphManager.remove(o):T.remove(o),c},s.prototype.createBendpointsFromDummyNodes=function(){var o=[];o=o.concat(this.graphManager.getAllEdges()),o=[].concat(u(this.edgeToDummyNodes.keys())).concat(o);for(var c=0;c<o.length;c++){var h=o[c];if(h.bendpoints.length>0){for(var T=this.edgeToDummyNodes.get(h),v=0;v<T.length;v++){var d=T[v],N=new i(d.getCenterX(),d.getCenterY()),S=h.bendpoints.get(v);S.x=N.x,S.y=N.y,d.getOwner().remove(d)}this.graphManager.add(h,h.source,h.target)}}},s.transform=function(o,c,h,T){if(h!=null&&T!=null){var v=c;if(o<=50){var d=c/h;v-=(c-d)/50*(50-o)}else{var N=c*T;v+=(N-c)/50*(o-50)}return v}else{var S,M;return o<=50?(S=9*c/500,M=c/10):(S=9*c/50,M=-8*c),S*o+M}},s.findCenterOfTree=function(o){var c=[];c=c.concat(o);var h=[],T=new Map,v=!1,d=null;(c.length==1||c.length==2)&&(v=!0,d=c[0]);for(var N=0;N<c.length;N++){var S=c[N],M=S.getNeighborsList().size;T.set(S,S.getNeighborsList().size),M==1&&h.push(S)}var P=[];for(P=P.concat(h);!v;){var K=[];K=K.concat(P),P=[];for(var N=0;N<c.length;N++){var S=c[N],Y=c.indexOf(S);Y>=0&&c.splice(Y,1);var k=S.getNeighborsList();k.forEach(function(a){if(h.indexOf(a)<0){var m=T.get(a),p=m-1;p==1&&P.push(a),T.set(a,p)}})}h=h.concat(P),(c.length==1||c.length==2)&&(v=!0,d=c[0])}return d},s.prototype.setGraphManager=function(o){this.graphManager=o},A.exports=s},function(A,G,L){function u(){}u.seed=1,u.x=0,u.nextDouble=function(){return u.x=Math.sin(u.seed++)*1e4,u.x-Math.floor(u.x)},A.exports=u},function(A,G,L){var u=L(5);function l(n,r){this.lworldOrgX=0,this.lworldOrgY=0,this.ldeviceOrgX=0,this.ldeviceOrgY=0,this.lworldExtX=1,this.lworldExtY=1,this.ldeviceExtX=1,this.ldeviceExtY=1}l.prototype.getWorldOrgX=function(){return this.lworldOrgX},l.prototype.setWorldOrgX=function(n){this.lworldOrgX=n},l.prototype.getWorldOrgY=function(){return this.lworldOrgY},l.prototype.setWorldOrgY=function(n){this.lworldOrgY=n},l.prototype.getWorldExtX=function(){return this.lworldExtX},l.prototype.setWorldExtX=function(n){this.lworldExtX=n},l.prototype.getWorldExtY=function(){return this.lworldExtY},l.prototype.setWorldExtY=function(n){this.lworldExtY=n},l.prototype.getDeviceOrgX=function(){return this.ldeviceOrgX},l.prototype.setDeviceOrgX=function(n){this.ldeviceOrgX=n},l.prototype.getDeviceOrgY=function(){return this.ldeviceOrgY},l.prototype.setDeviceOrgY=function(n){this.ldeviceOrgY=n},l.prototype.getDeviceExtX=function(){return this.ldeviceExtX},l.prototype.setDeviceExtX=function(n){this.ldeviceExtX=n},l.prototype.getDeviceExtY=function(){return this.ldeviceExtY},l.prototype.setDeviceExtY=function(n){this.ldeviceExtY=n},l.prototype.transformX=function(n){var r=0,e=this.lworldExtX;return e!=0&&(r=this.ldeviceOrgX+(n-this.lworldOrgX)*this.ldeviceExtX/e),r},l.prototype.transformY=function(n){var r=0,e=this.lworldExtY;return e!=0&&(r=this.ldeviceOrgY+(n-this.lworldOrgY)*this.ldeviceExtY/e),r},l.prototype.inverseTransformX=function(n){var r=0,e=this.ldeviceExtX;return e!=0&&(r=this.lworldOrgX+(n-this.ldeviceOrgX)*this.lworldExtX/e),r},l.prototype.inverseTransformY=function(n){var r=0,e=this.ldeviceExtY;return e!=0&&(r=this.lworldOrgY+(n-this.ldeviceOrgY)*this.lworldExtY/e),r},l.prototype.inverseTransformPoint=function(n){var r=new u(this.inverseTransformX(n.x),this.inverseTransformY(n.y));return r},A.exports=l},function(A,G,L){function u(t){if(Array.isArray(t)){for(var s=0,o=Array(t.length);s<t.length;s++)o[s]=t[s];return o}else return Array.from(t)}var l=L(15),n=L(4),r=L(0),e=L(8),f=L(9);function i(){l.call(this),this.useSmartIdealEdgeLengthCalculation=n.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION,this.gravityConstant=n.DEFAULT_GRAVITY_STRENGTH,this.compoundGravityConstant=n.DEFAULT_COMPOUND_GRAVITY_STRENGTH,this.gravityRangeFactor=n.DEFAULT_GRAVITY_RANGE_FACTOR,this.compoundGravityRangeFactor=n.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR,this.displacementThresholdPerNode=3*n.DEFAULT_EDGE_LENGTH/100,this.coolingFactor=n.DEFAULT_COOLING_FACTOR_INCREMENTAL,this.initialCoolingFactor=n.DEFAULT_COOLING_FACTOR_INCREMENTAL,this.totalDisplacement=0,this.oldTotalDisplacement=0,this.maxIterations=n.MAX_ITERATIONS}i.prototype=Object.create(l.prototype);for(var g in l)i[g]=l[g];i.prototype.initParameters=function(){l.prototype.initParameters.call(this,arguments),this.totalIterations=0,this.notAnimatedIterations=0,this.useFRGridVariant=n.DEFAULT_USE_SMART_REPULSION_RANGE_CALCULATION,this.grid=[]},i.prototype.calcIdealEdgeLengths=function(){for(var t,s,o,c,h,T,v,d=this.getGraphManager().getAllEdges(),N=0;N<d.length;N++)t=d[N],s=t.idealLength,t.isInterGraph&&(c=t.getSource(),h=t.getTarget(),T=t.getSourceInLca().getEstimatedSize(),v=t.getTargetInLca().getEstimatedSize(),this.useSmartIdealEdgeLengthCalculation&&(t.idealLength+=T+v-2*r.SIMPLE_NODE_SIZE),o=t.getLca().getInclusionTreeDepth(),t.idealLength+=s*n.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR*(c.getInclusionTreeDepth()+h.getInclusionTreeDepth()-2*o))},i.prototype.initSpringEmbedder=function(){var t=this.getAllNodes().length;this.incremental?(t>n.ADAPTATION_LOWER_NODE_LIMIT&&(this.coolingFactor=Math.max(this.coolingFactor*n.COOLING_ADAPTATION_FACTOR,this.coolingFactor-(t-n.ADAPTATION_LOWER_NODE_LIMIT)/(n.ADAPTATION_UPPER_NODE_LIMIT-n.ADAPTATION_LOWER_NODE_LIMIT)*this.coolingFactor*(1-n.COOLING_ADAPTATION_FACTOR))),this.maxNodeDisplacement=n.MAX_NODE_DISPLACEMENT_INCREMENTAL):(t>n.ADAPTATION_LOWER_NODE_LIMIT?this.coolingFactor=Math.max(n.COOLING_ADAPTATION_FACTOR,1-(t-n.ADAPTATION_LOWER_NODE_LIMIT)/(n.ADAPTATION_UPPER_NODE_LIMIT-n.ADAPTATION_LOWER_NODE_LIMIT)*(1-n.COOLING_ADAPTATION_FACTOR)):this.coolingFactor=1,this.initialCoolingFactor=this.coolingFactor,this.maxNodeDisplacement=n.MAX_NODE_DISPLACEMENT),this.maxIterations=Math.max(this.getAllNodes().length*5,this.maxIterations),this.displacementThresholdPerNode=3*n.DEFAULT_EDGE_LENGTH/100,this.totalDisplacementThreshold=this.displacementThresholdPerNode*this.getAllNodes().length,this.repulsionRange=this.calcRepulsionRange()},i.prototype.calcSpringForces=function(){for(var t=this.getAllEdges(),s,o=0;o<t.length;o++)s=t[o],this.calcSpringForce(s,s.idealLength)},i.prototype.calcRepulsionForces=function(){var t=arguments.length>0&&arguments[0]!==void 0?arguments[0]:!0,s=arguments.length>1&&arguments[1]!==void 0?arguments[1]:!1,o,c,h,T,v=this.getAllNodes(),d;if(this.useFRGridVariant)for(this.totalIterations%n.GRID_CALCULATION_CHECK_PERIOD==1&&t&&this.updateGrid(),d=new Set,o=0;o<v.length;o++)h=v[o],this.calculateRepulsionForceOfANode(h,d,t,s),d.add(h);else for(o=0;o<v.length;o++)for(h=v[o],c=o+1;c<v.length;c++)T=v[c],h.getOwner()==T.getOwner()&&this.calcRepulsionForce(h,T)},i.prototype.calcGravitationalForces=function(){for(var t,s=this.getAllNodesToApplyGravitation(),o=0;o<s.length;o++)t=s[o],this.calcGravitationalForce(t)},i.prototype.moveNodes=function(){for(var t=this.getAllNodes(),s,o=0;o<t.length;o++)s=t[o],s.move()},i.prototype.calcSpringForce=function(t,s){var o=t.getSource(),c=t.getTarget(),h,T,v,d;if(this.uniformLeafNodeSizes&&o.getChild()==null&&c.getChild()==null)t.updateLengthSimple();else if(t.updateLength(),t.isOverlapingSourceAndTarget)return;h=t.getLength(),h!=0&&(T=t.edgeElasticity*(h-s),v=T*(t.lengthX/h),d=T*(t.lengthY/h),o.springForceX+=v,o.springForceY+=d,c.springForceX-=v,c.springForceY-=d)},i.prototype.calcRepulsionForce=function(t,s){var o=t.getRect(),c=s.getRect(),h=new Array(2),T=new Array(4),v,d,N,S,M,P,K;if(o.intersects(c)){e.calcSeparationAmount(o,c,h,n.DEFAULT_EDGE_LENGTH/2),P=2*h[0],K=2*h[1];var Y=t.noOfChildren*s.noOfChildren/(t.noOfChildren+s.noOfChildren);t.repulsionForceX-=Y*P,t.repulsionForceY-=Y*K,s.repulsionForceX+=Y*P,s.repulsionForceY+=Y*K}else this.uniformLeafNodeSizes&&t.getChild()==null&&s.getChild()==null?(v=c.getCenterX()-o.getCenterX(),d=c.getCenterY()-o.getCenterY()):(e.getIntersection(o,c,T),v=T[2]-T[0],d=T[3]-T[1]),Math.abs(v)<n.MIN_REPULSION_DIST&&(v=f.sign(v)*n.MIN_REPULSION_DIST),Math.abs(d)<n.MIN_REPULSION_DIST&&(d=f.sign(d)*n.MIN_REPULSION_DIST),N=v*v+d*d,S=Math.sqrt(N),M=(t.nodeRepulsion/2+s.nodeRepulsion/2)*t.noOfChildren*s.noOfChildren/N,P=M*v/S,K=M*d/S,t.repulsionForceX-=P,t.repulsionForceY-=K,s.repulsionForceX+=P,s.repulsionForceY+=K},i.prototype.calcGravitationalForce=function(t){var s,o,c,h,T,v,d,N;s=t.getOwner(),o=(s.getRight()+s.getLeft())/2,c=(s.getTop()+s.getBottom())/2,h=t.getCenterX()-o,T=t.getCenterY()-c,v=Math.abs(h)+t.getWidth()/2,d=Math.abs(T)+t.getHeight()/2,t.getOwner()==this.graphManager.getRoot()?(N=s.getEstimatedSize()*this.gravityRangeFactor,(v>N||d>N)&&(t.gravitationForceX=-this.gravityConstant*h,t.gravitationForceY=-this.gravityConstant*T)):(N=s.getEstimatedSize()*this.compoundGravityRangeFactor,(v>N||d>N)&&(t.gravitationForceX=-this.gravityConstant*h*this.compoundGravityConstant,t.gravitationForceY=-this.gravityConstant*T*this.compoundGravityConstant))},i.prototype.isConverged=function(){var t,s=!1;return this.totalIterations>this.maxIterations/3&&(s=Math.abs(this.totalDisplacement-this.oldTotalDisplacement)<2),t=this.totalDisplacement<this.totalDisplacementThreshold,this.oldTotalDisplacement=this.totalDisplacement,t||s},i.prototype.animate=function(){this.animationDuringLayout&&!this.isSubLayout&&(this.notAnimatedIterations==this.animationPeriod?(this.update(),this.notAnimatedIterations=0):this.notAnimatedIterations++)},i.prototype.calcNoOfChildrenForAllNodes=function(){for(var t,s=this.graphManager.getAllNodes(),o=0;o<s.length;o++)t=s[o],t.noOfChildren=t.getNoOfChildren()},i.prototype.calcGrid=function(t){var s=0,o=0;s=parseInt(Math.ceil((t.getRight()-t.getLeft())/this.repulsionRange)),o=parseInt(Math.ceil((t.getBottom()-t.getTop())/this.repulsionRange));for(var c=new Array(s),h=0;h<s;h++)c[h]=new Array(o);for(var h=0;h<s;h++)for(var T=0;T<o;T++)c[h][T]=new Array;return c},i.prototype.addNodeToGrid=function(t,s,o){var c=0,h=0,T=0,v=0;c=parseInt(Math.floor((t.getRect().x-s)/this.repulsionRange)),h=parseInt(Math.floor((t.getRect().width+t.getRect().x-s)/this.repulsionRange)),T=parseInt(Math.floor((t.getRect().y-o)/this.repulsionRange)),v=parseInt(Math.floor((t.getRect().height+t.getRect().y-o)/this.repulsionRange));for(var d=c;d<=h;d++)for(var N=T;N<=v;N++)this.grid[d][N].push(t),t.setGridCoordinates(c,h,T,v)},i.prototype.updateGrid=function(){var t,s,o=this.getAllNodes();for(this.grid=this.calcGrid(this.graphManager.getRoot()),t=0;t<o.length;t++)s=o[t],this.addNodeToGrid(s,this.graphManager.getRoot().getLeft(),this.graphManager.getRoot().getTop())},i.prototype.calculateRepulsionForceOfANode=function(t,s,o,c){if(this.totalIterations%n.GRID_CALCULATION_CHECK_PERIOD==1&&o||c){var h=new Set;t.surrounding=new Array;for(var T,v=this.grid,d=t.startX-1;d<t.finishX+2;d++)for(var N=t.startY-1;N<t.finishY+2;N++)if(!(d<0||N<0||d>=v.length||N>=v[0].length)){for(var S=0;S<v[d][N].length;S++)if(T=v[d][N][S],!(t.getOwner()!=T.getOwner()||t==T)&&!s.has(T)&&!h.has(T)){var M=Math.abs(t.getCenterX()-T.getCenterX())-(t.getWidth()/2+T.getWidth()/2),P=Math.abs(t.getCenterY()-T.getCenterY())-(t.getHeight()/2+T.getHeight()/2);M<=this.repulsionRange&&P<=this.repulsionRange&&h.add(T)}}t.surrounding=[].concat(u(h))}for(d=0;d<t.surrounding.length;d++)this.calcRepulsionForce(t,t.surrounding[d])},i.prototype.calcRepulsionRange=function(){return 0},A.exports=i},function(A,G,L){var u=L(1),l=L(4);function n(e,f,i){u.call(this,e,f,i),this.idealLength=l.DEFAULT_EDGE_LENGTH,this.edgeElasticity=l.DEFAULT_SPRING_STRENGTH}n.prototype=Object.create(u.prototype);for(var r in u)n[r]=u[r];A.exports=n},function(A,G,L){var u=L(3),l=L(4);function n(e,f,i,g){u.call(this,e,f,i,g),this.nodeRepulsion=l.DEFAULT_REPULSION_STRENGTH,this.springForceX=0,this.springForceY=0,this.repulsionForceX=0,this.repulsionForceY=0,this.gravitationForceX=0,this.gravitationForceY=0,this.displacementX=0,this.displacementY=0,this.startX=0,this.finishX=0,this.startY=0,this.finishY=0,this.surrounding=[]}n.prototype=Object.create(u.prototype);for(var r in u)n[r]=u[r];n.prototype.setGridCoordinates=function(e,f,i,g){this.startX=e,this.finishX=f,this.startY=i,this.finishY=g},A.exports=n},function(A,G,L){function u(l,n){this.width=0,this.height=0,l!==null&&n!==null&&(this.height=n,this.width=l)}u.prototype.getWidth=function(){return this.width},u.prototype.setWidth=function(l){this.width=l},u.prototype.getHeight=function(){return this.height},u.prototype.setHeight=function(l){this.height=l},A.exports=u},function(A,G,L){var u=L(14);function l(){this.map={},this.keys=[]}l.prototype.put=function(n,r){var e=u.createID(n);this.contains(e)||(this.map[e]=r,this.keys.push(n))},l.prototype.contains=function(n){return u.createID(n),this.map[n]!=null},l.prototype.get=function(n){var r=u.createID(n);return this.map[r]},l.prototype.keySet=function(){return this.keys},A.exports=l},function(A,G,L){var u=L(14);function l(){this.set={}}l.prototype.add=function(n){var r=u.createID(n);this.contains(r)||(this.set[r]=n)},l.prototype.remove=function(n){delete this.set[u.createID(n)]},l.prototype.clear=function(){this.set={}},l.prototype.contains=function(n){return this.set[u.createID(n)]==n},l.prototype.isEmpty=function(){return this.size()===0},l.prototype.size=function(){return Object.keys(this.set).length},l.prototype.addAllTo=function(n){for(var r=Object.keys(this.set),e=r.length,f=0;f<e;f++)n.push(this.set[r[f]])},l.prototype.size=function(){return Object.keys(this.set).length},l.prototype.addAll=function(n){for(var r=n.length,e=0;e<r;e++){var f=n[e];this.add(f)}},A.exports=l},function(A,G,L){function u(){}u.multMat=function(l,n){for(var r=[],e=0;e<l.length;e++){r[e]=[];for(var f=0;f<n[0].length;f++){r[e][f]=0;for(var i=0;i<l[0].length;i++)r[e][f]+=l[e][i]*n[i][f]}}return r},u.transpose=function(l){for(var n=[],r=0;r<l[0].length;r++){n[r]=[];for(var e=0;e<l.length;e++)n[r][e]=l[e][r]}return n},u.multCons=function(l,n){for(var r=[],e=0;e<l.length;e++)r[e]=l[e]*n;return r},u.minusOp=function(l,n){for(var r=[],e=0;e<l.length;e++)r[e]=l[e]-n[e];return r},u.dotProduct=function(l,n){for(var r=0,e=0;e<l.length;e++)r+=l[e]*n[e];return r},u.mag=function(l){return Math.sqrt(this.dotProduct(l,l))},u.normalize=function(l){for(var n=[],r=this.mag(l),e=0;e<l.length;e++)n[e]=l[e]/r;return n},u.multGamma=function(l){for(var n=[],r=0,e=0;e<l.length;e++)r+=l[e];r*=-1/l.length;for(var f=0;f<l.length;f++)n[f]=r+l[f];return n},u.multL=function(l,n,r){for(var e=[],f=[],i=[],g=0;g<n[0].length;g++){for(var t=0,s=0;s<n.length;s++)t+=-.5*n[s][g]*l[s];f[g]=t}for(var o=0;o<r.length;o++){for(var c=0,h=0;h<r.length;h++)c+=r[o][h]*f[h];i[o]=c}for(var T=0;T<n.length;T++){for(var v=0,d=0;d<n[0].length;d++)v+=n[T][d]*i[d];e[T]=v}return e},A.exports=u},function(A,G,L){var u=function(){function e(f,i){for(var g=0;g<i.length;g++){var t=i[g];t.enumerable=t.enumerable||!1,t.configurable=!0,"value"in t&&(t.writable=!0),Object.defineProperty(f,t.key,t)}}return function(f,i,g){return i&&e(f.prototype,i),g&&e(f,g),f}}();function l(e,f){if(!(e instanceof f))throw new TypeError("Cannot call a class as a function")}var n=L(11),r=function(){function e(f,i){l(this,e),(i!==null||i!==void 0)&&(this.compareFunction=this._defaultCompareFunction);var g=void 0;f instanceof n?g=f.size():g=f.length,this._quicksort(f,0,g-1)}return u(e,[{key:"_quicksort",value:function(i,g,t){if(g<t){var s=this._partition(i,g,t);this._quicksort(i,g,s),this._quicksort(i,s+1,t)}}},{key:"_partition",value:function(i,g,t){for(var s=this._get(i,g),o=g,c=t;;){for(;this.compareFunction(s,this._get(i,c));)c--;for(;this.compareFunction(this._get(i,o),s);)o++;if(o<c)this._swap(i,o,c),o++,c--;else return c}}},{key:"_get",value:function(i,g){return i instanceof n?i.get_object_at(g):i[g]}},{key:"_set",value:function(i,g,t){i instanceof n?i.set_object_at(g,t):i[g]=t}},{key:"_swap",value:function(i,g,t){var s=this._get(i,g);this._set(i,g,this._get(i,t)),this._set(i,t,s)}},{key:"_defaultCompareFunction",value:function(i,g){return g>i}}]),e}();A.exports=r},function(A,G,L){function u(){}u.svd=function(l){this.U=null,this.V=null,this.s=null,this.m=0,this.n=0,this.m=l.length,this.n=l[0].length;var n=Math.min(this.m,this.n);this.s=function(Nt){for(var Mt=[];Nt-- >0;)Mt.push(0);return Mt}(Math.min(this.m+1,this.n)),this.U=function(Nt){var Mt=function Zt(Gt){if(Gt.length==0)return 0;for(var $t=[],Ft=0;Ft<Gt[0];Ft++)$t.push(Zt(Gt.slice(1)));return $t};return Mt(Nt)}([this.m,n]),this.V=function(Nt){var Mt=function Zt(Gt){if(Gt.length==0)return 0;for(var $t=[],Ft=0;Ft<Gt[0];Ft++)$t.push(Zt(Gt.slice(1)));return $t};return Mt(Nt)}([this.n,this.n]);for(var r=function(Nt){for(var Mt=[];Nt-- >0;)Mt.push(0);return Mt}(this.n),e=function(Nt){for(var Mt=[];Nt-- >0;)Mt.push(0);return Mt}(this.m),f=!0,i=Math.min(this.m-1,this.n),g=Math.max(0,Math.min(this.n-2,this.m)),t=0;t<Math.max(i,g);t++){if(t<i){this.s[t]=0;for(var s=t;s<this.m;s++)this.s[t]=u.hypot(this.s[t],l[s][t]);if(this.s[t]!==0){l[t][t]<0&&(this.s[t]=-this.s[t]);for(var o=t;o<this.m;o++)l[o][t]/=this.s[t];l[t][t]+=1}this.s[t]=-this.s[t]}for(var c=t+1;c<this.n;c++){if(function(Nt,Mt){return Nt&&Mt}(t<i,this.s[t]!==0)){for(var h=0,T=t;T<this.m;T++)h+=l[T][t]*l[T][c];h=-h/l[t][t];for(var v=t;v<this.m;v++)l[v][c]+=h*l[v][t]}r[c]=l[t][c]}if(function(Nt,Mt){return Mt}(f,t<i))for(var d=t;d<this.m;d++)this.U[d][t]=l[d][t];if(t<g){r[t]=0;for(var N=t+1;N<this.n;N++)r[t]=u.hypot(r[t],r[N]);if(r[t]!==0){r[t+1]<0&&(r[t]=-r[t]);for(var S=t+1;S<this.n;S++)r[S]/=r[t];r[t+1]+=1}if(r[t]=-r[t],function(Nt,Mt){return Nt&&Mt}(t+1<this.m,r[t]!==0)){for(var M=t+1;M<this.m;M++)e[M]=0;for(var P=t+1;P<this.n;P++)for(var K=t+1;K<this.m;K++)e[K]+=r[P]*l[K][P];for(var Y=t+1;Y<this.n;Y++)for(var k=-r[Y]/r[t+1],D=t+1;D<this.m;D++)l[D][Y]+=k*e[D]}for(var rt=t+1;rt<this.n;rt++)this.V[rt][t]=r[rt]}}var a=Math.min(this.n,this.m+1);i<this.n&&(this.s[i]=l[i][i]),this.m<a&&(this.s[a-1]=0),g+1<a&&(r[g]=l[g][a-1]),r[a-1]=0;{for(var m=i;m<n;m++){for(var p=0;p<this.m;p++)this.U[p][m]=0;this.U[m][m]=1}for(var E=i-1;E>=0;E--)if(this.s[E]!==0){for(var y=E+1;y<n;y++){for(var I=0,w=E;w<this.m;w++)I+=this.U[w][E]*this.U[w][y];I=-I/this.U[E][E];for(var R=E;R<this.m;R++)this.U[R][y]+=I*this.U[R][E]}for(var W=E;W<this.m;W++)this.U[W][E]=-this.U[W][E];this.U[E][E]=1+this.U[E][E];for(var x=0;x<E-1;x++)this.U[x][E]=0}else{for(var q=0;q<this.m;q++)this.U[q][E]=0;this.U[E][E]=1}}for(var V=this.n-1;V>=0;V--){if(function(Nt,Mt){return Nt&&Mt}(V<g,r[V]!==0))for(var U=V+1;U<n;U++){for(var et=0,z=V+1;z<this.n;z++)et+=this.V[z][V]*this.V[z][U];et=-et/this.V[V+1][V];for(var O=V+1;O<this.n;O++)this.V[O][U]+=et*this.V[O][V]}for(var H=0;H<this.n;H++)this.V[H][V]=0;this.V[V][V]=1}for(var B=a-1,_=Math.pow(2,-52),lt=Math.pow(2,-966);a>0;){var J=void 0,Rt=void 0;for(J=a-2;J>=-1&&J!==-1;J--)if(Math.abs(r[J])<=lt+_*(Math.abs(this.s[J])+Math.abs(this.s[J+1]))){r[J]=0;break}if(J===a-2)Rt=4;else{var Lt=void 0;for(Lt=a-1;Lt>=J&&Lt!==J;Lt--){var vt=(Lt!==a?Math.abs(r[Lt]):0)+(Lt!==J+1?Math.abs(r[Lt-1]):0);if(Math.abs(this.s[Lt])<=lt+_*vt){this.s[Lt]=0;break}}Lt===J?Rt=3:Lt===a-1?Rt=1:(Rt=2,J=Lt)}switch(J++,Rt){case 1:{var it=r[a-2];r[a-2]=0;for(var gt=a-2;gt>=J;gt--){var Tt=u.hypot(this.s[gt],it),At=this.s[gt]/Tt,Dt=it/Tt;this.s[gt]=Tt,gt!==J&&(it=-Dt*r[gt-1],r[gt-1]=At*r[gt-1]);for(var mt=0;mt<this.n;mt++)Tt=At*this.V[mt][gt]+Dt*this.V[mt][a-1],this.V[mt][a-1]=-Dt*this.V[mt][gt]+At*this.V[mt][a-1],this.V[mt][gt]=Tt}}break;case 2:{var xt=r[J-1];r[J-1]=0;for(var St=J;St<a;St++){var Vt=u.hypot(this.s[St],xt),Xt=this.s[St]/Vt,Ut=xt/Vt;this.s[St]=Vt,xt=-Ut*r[St],r[St]=Xt*r[St];for(var bt=0;bt<this.m;bt++)Vt=Xt*this.U[bt][St]+Ut*this.U[bt][J-1],this.U[bt][J-1]=-Ut*this.U[bt][St]+Xt*this.U[bt][J-1],this.U[bt][St]=Vt}}break;case 3:{var Ht=Math.max(Math.max(Math.max(Math.max(Math.abs(this.s[a-1]),Math.abs(this.s[a-2])),Math.abs(r[a-2])),Math.abs(this.s[J])),Math.abs(r[J])),Bt=this.s[a-1]/Ht,F=this.s[a-2]/Ht,b=r[a-2]/Ht,$=this.s[J]/Ht,Q=r[J]/Ht,Z=((F+Bt)*(F-Bt)+b*b)/2,nt=Bt*b*(Bt*b),ut=0;(function(Nt,Mt){return Nt||Mt})(Z!==0,nt!==0)&&(ut=Math.sqrt(Z*Z+nt),Z<0&&(ut=-ut),ut=nt/(Z+ut));for(var ot=($+Bt)*($-Bt)+ut,tt=$*Q,j=J;j<a-1;j++){var dt=u.hypot(ot,tt),wt=ot/dt,yt=tt/dt;j!==J&&(r[j-1]=dt),ot=wt*this.s[j]+yt*r[j],r[j]=wt*r[j]-yt*this.s[j],tt=yt*this.s[j+1],this.s[j+1]=wt*this.s[j+1];for(var It=0;It<this.n;It++)dt=wt*this.V[It][j]+yt*this.V[It][j+1],this.V[It][j+1]=-yt*this.V[It][j]+wt*this.V[It][j+1],this.V[It][j]=dt;if(dt=u.hypot(ot,tt),wt=ot/dt,yt=tt/dt,this.s[j]=dt,ot=wt*r[j]+yt*this.s[j+1],this.s[j+1]=-yt*r[j]+wt*this.s[j+1],tt=yt*r[j+1],r[j+1]=wt*r[j+1],j<this.m-1)for(var ft=0;ft<this.m;ft++)dt=wt*this.U[ft][j]+yt*this.U[ft][j+1],this.U[ft][j+1]=-yt*this.U[ft][j]+wt*this.U[ft][j+1],this.U[ft][j]=dt}r[a-2]=ot}break;case 4:{if(this.s[J]<=0){this.s[J]=this.s[J]<0?-this.s[J]:0;for(var st=0;st<=B;st++)this.V[st][J]=-this.V[st][J]}for(;J<B&&!(this.s[J]>=this.s[J+1]);){var Ct=this.s[J];if(this.s[J]=this.s[J+1],this.s[J+1]=Ct,J<this.n-1)for(var ct=0;ct<this.n;ct++)Ct=this.V[ct][J+1],this.V[ct][J+1]=this.V[ct][J],this.V[ct][J]=Ct;if(J<this.m-1)for(var ht=0;ht<this.m;ht++)Ct=this.U[ht][J+1],this.U[ht][J+1]=this.U[ht][J],this.U[ht][J]=Ct;J++}a--}break}}var Wt={U:this.U,V:this.V,S:this.s};return Wt},u.hypot=function(l,n){var r=void 0;return Math.abs(l)>Math.abs(n)?(r=n/l,r=Math.abs(l)*Math.sqrt(1+r*r)):n!=0?(r=l/n,r=Math.abs(n)*Math.sqrt(1+r*r)):r=0,r},A.exports=u},function(A,G,L){var u=function(){function r(e,f){for(var i=0;i<f.length;i++){var g=f[i];g.enumerable=g.enumerable||!1,g.configurable=!0,"value"in g&&(g.writable=!0),Object.defineProperty(e,g.key,g)}}return function(e,f,i){return f&&r(e.prototype,f),i&&r(e,i),e}}();function l(r,e){if(!(r instanceof e))throw new TypeError("Cannot call a class as a function")}var n=function(){function r(e,f){var i=arguments.length>2&&arguments[2]!==void 0?arguments[2]:1,g=arguments.length>3&&arguments[3]!==void 0?arguments[3]:-1,t=arguments.length>4&&arguments[4]!==void 0?arguments[4]:-1;l(this,r),this.sequence1=e,this.sequence2=f,this.match_score=i,this.mismatch_penalty=g,this.gap_penalty=t,this.iMax=e.length+1,this.jMax=f.length+1,this.grid=new Array(this.iMax);for(var s=0;s<this.iMax;s++){this.grid[s]=new Array(this.jMax);for(var o=0;o<this.jMax;o++)this.grid[s][o]=0}this.tracebackGrid=new Array(this.iMax);for(var c=0;c<this.iMax;c++){this.tracebackGrid[c]=new Array(this.jMax);for(var h=0;h<this.jMax;h++)this.tracebackGrid[c][h]=[null,null,null]}this.alignments=[],this.score=-1,this.computeGrids()}return u(r,[{key:"getScore",value:function(){return this.score}},{key:"getAlignments",value:function(){return this.alignments}},{key:"computeGrids",value:function(){for(var f=1;f<this.jMax;f++)this.grid[0][f]=this.grid[0][f-1]+this.gap_penalty,this.tracebackGrid[0][f]=[!1,!1,!0];for(var i=1;i<this.iMax;i++)this.grid[i][0]=this.grid[i-1][0]+this.gap_penalty,this.tracebackGrid[i][0]=[!1,!0,!1];for(var g=1;g<this.iMax;g++)for(var t=1;t<this.jMax;t++){var s=void 0;this.sequence1[g-1]===this.sequence2[t-1]?s=this.grid[g-1][t-1]+this.match_score:s=this.grid[g-1][t-1]+this.mismatch_penalty;var o=this.grid[g-1][t]+this.gap_penalty,c=this.grid[g][t-1]+this.gap_penalty,h=[s,o,c],T=this.arrayAllMaxIndexes(h);this.grid[g][t]=h[T[0]],this.tracebackGrid[g][t]=[T.includes(0),T.includes(1),T.includes(2)]}this.score=this.grid[this.iMax-1][this.jMax-1]}},{key:"alignmentTraceback",value:function(){var f=[];for(f.push({pos:[this.sequence1.length,this.sequence2.length],seq1:"",seq2:""});f[0];){var i=f[0],g=this.tracebackGrid[i.pos[0]][i.pos[1]];g[0]&&f.push({pos:[i.pos[0]-1,i.pos[1]-1],seq1:this.sequence1[i.pos[0]-1]+i.seq1,seq2:this.sequence2[i.pos[1]-1]+i.seq2}),g[1]&&f.push({pos:[i.pos[0]-1,i.pos[1]],seq1:this.sequence1[i.pos[0]-1]+i.seq1,seq2:"-"+i.seq2}),g[2]&&f.push({pos:[i.pos[0],i.pos[1]-1],seq1:"-"+i.seq1,seq2:this.sequence2[i.pos[1]-1]+i.seq2}),i.pos[0]===0&&i.pos[1]===0&&this.alignments.push({sequence1:i.seq1,sequence2:i.seq2}),f.shift()}return this.alignments}},{key:"getAllIndexes",value:function(f,i){for(var g=[],t=-1;(t=f.indexOf(i,t+1))!==-1;)g.push(t);return g}},{key:"arrayAllMaxIndexes",value:function(f){return this.getAllIndexes(f,Math.max.apply(null,f))}}]),r}();A.exports=n},function(A,G,L){var u=function(){};u.FDLayout=L(18),u.FDLayoutConstants=L(4),u.FDLayoutEdge=L(19),u.FDLayoutNode=L(20),u.DimensionD=L(21),u.HashMap=L(22),u.HashSet=L(23),u.IGeometry=L(8),u.IMath=L(9),u.Integer=L(10),u.Point=L(12),u.PointD=L(5),u.RandomSeed=L(16),u.RectangleD=L(13),u.Transform=L(17),u.UniqueIDGeneretor=L(14),u.Quicksort=L(25),u.LinkedList=L(11),u.LGraphObject=L(2),u.LGraph=L(6),u.LEdge=L(1),u.LGraphManager=L(7),u.LNode=L(3),u.Layout=L(15),u.LayoutConstants=L(0),u.NeedlemanWunsch=L(27),u.Matrix=L(24),u.SVD=L(26),A.exports=u},function(A,G,L){function u(){this.listeners=[]}var l=u.prototype;l.addListener=function(n,r){this.listeners.push({event:n,callback:r})},l.removeListener=function(n,r){for(var e=this.listeners.length;e>=0;e--){var f=this.listeners[e];f.event===n&&f.callback===r&&this.listeners.splice(e,1)}},l.emit=function(n,r){for(var e=0;e<this.listeners.length;e++){var f=this.listeners[e];n===f.event&&f.callback(r)}},A.exports=u}])})}(ce)),ce.exports}var pr=fe.exports,Ie;function yr(){return Ie||(Ie=1,function(C,X){(function(G,L){C.exports=L(vr())})(pr,function(A){return(()=>{var G={45:(n,r,e)=>{var f={};f.layoutBase=e(551),f.CoSEConstants=e(806),f.CoSEEdge=e(767),f.CoSEGraph=e(880),f.CoSEGraphManager=e(578),f.CoSELayout=e(765),f.CoSENode=e(991),f.ConstraintHandler=e(902),n.exports=f},806:(n,r,e)=>{var f=e(551).FDLayoutConstants;function i(){}for(var g in f)i[g]=f[g];i.DEFAULT_USE_MULTI_LEVEL_SCALING=!1,i.DEFAULT_RADIAL_SEPARATION=f.DEFAULT_EDGE_LENGTH,i.DEFAULT_COMPONENT_SEPERATION=60,i.TILE=!0,i.TILING_PADDING_VERTICAL=10,i.TILING_PADDING_HORIZONTAL=10,i.TRANSFORM_ON_CONSTRAINT_HANDLING=!0,i.ENFORCE_CONSTRAINTS=!0,i.APPLY_LAYOUT=!0,i.RELAX_MOVEMENT_ON_CONSTRAINTS=!0,i.TREE_REDUCTION_ON_INCREMENTAL=!0,i.PURE_INCREMENTAL=i.DEFAULT_INCREMENTAL,n.exports=i},767:(n,r,e)=>{var f=e(551).FDLayoutEdge;function i(t,s,o){f.call(this,t,s,o)}i.prototype=Object.create(f.prototype);for(var g in f)i[g]=f[g];n.exports=i},880:(n,r,e)=>{var f=e(551).LGraph;function i(t,s,o){f.call(this,t,s,o)}i.prototype=Object.create(f.prototype);for(var g in f)i[g]=f[g];n.exports=i},578:(n,r,e)=>{var f=e(551).LGraphManager;function i(t){f.call(this,t)}i.prototype=Object.create(f.prototype);for(var g in f)i[g]=f[g];n.exports=i},765:(n,r,e)=>{var f=e(551).FDLayout,i=e(578),g=e(880),t=e(991),s=e(767),o=e(806),c=e(902),h=e(551).FDLayoutConstants,T=e(551).LayoutConstants,v=e(551).Point,d=e(551).PointD,N=e(551).DimensionD,S=e(551).Layout,M=e(551).Integer,P=e(551).IGeometry,K=e(551).LGraph,Y=e(551).Transform,k=e(551).LinkedList;function D(){f.call(this),this.toBeTiled={},this.constraints={}}D.prototype=Object.create(f.prototype);for(var rt in f)D[rt]=f[rt];D.prototype.newGraphManager=function(){var a=new i(this);return this.graphManager=a,a},D.prototype.newGraph=function(a){return new g(null,this.graphManager,a)},D.prototype.newNode=function(a){return new t(this.graphManager,a)},D.prototype.newEdge=function(a){return new s(null,null,a)},D.prototype.initParameters=function(){f.prototype.initParameters.call(this,arguments),this.isSubLayout||(o.DEFAULT_EDGE_LENGTH<10?this.idealEdgeLength=10:this.idealEdgeLength=o.DEFAULT_EDGE_LENGTH,this.useSmartIdealEdgeLengthCalculation=o.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION,this.gravityConstant=h.DEFAULT_GRAVITY_STRENGTH,this.compoundGravityConstant=h.DEFAULT_COMPOUND_GRAVITY_STRENGTH,this.gravityRangeFactor=h.DEFAULT_GRAVITY_RANGE_FACTOR,this.compoundGravityRangeFactor=h.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR,this.prunedNodesAll=[],this.growTreeIterations=0,this.afterGrowthIterations=0,this.isTreeGrowing=!1,this.isGrowthFinished=!1)},D.prototype.initSpringEmbedder=function(){f.prototype.initSpringEmbedder.call(this),this.coolingCycle=0,this.maxCoolingCycle=this.maxIterations/h.CONVERGENCE_CHECK_PERIOD,this.finalTemperature=.04,this.coolingAdjuster=1},D.prototype.layout=function(){var a=T.DEFAULT_CREATE_BENDS_AS_NEEDED;return a&&(this.createBendpoints(),this.graphManager.resetAllEdges()),this.level=0,this.classicLayout()},D.prototype.classicLayout=function(){if(this.nodesWithGravity=this.calculateNodesToApplyGravitationTo(),this.graphManager.setAllNodesToApplyGravitation(this.nodesWithGravity),this.calcNoOfChildrenForAllNodes(),this.graphManager.calcLowestCommonAncestors(),this.graphManager.calcInclusionTreeDepths(),this.graphManager.getRoot().calcEstimatedSize(),this.calcIdealEdgeLengths(),this.incremental){if(o.TREE_REDUCTION_ON_INCREMENTAL){this.reduceTrees(),this.graphManager.resetAllNodesToApplyGravitation();var m=new Set(this.getAllNodes()),p=this.nodesWithGravity.filter(function(I){return m.has(I)});this.graphManager.setAllNodesToApplyGravitation(p)}}else{var a=this.getFlatForest();if(a.length>0)this.positionNodesRadially(a);else{this.reduceTrees(),this.graphManager.resetAllNodesToApplyGravitation();var m=new Set(this.getAllNodes()),p=this.nodesWithGravity.filter(function(E){return m.has(E)});this.graphManager.setAllNodesToApplyGravitation(p),this.positionNodesRandomly()}}return Object.keys(this.constraints).length>0&&(c.handleConstraints(this),this.initConstraintVariables()),this.initSpringEmbedder(),o.APPLY_LAYOUT&&this.runSpringEmbedder(),!0},D.prototype.tick=function(){if(this.totalIterations++,this.totalIterations===this.maxIterations&&!this.isTreeGrowing&&!this.isGrowthFinished)if(this.prunedNodesAll.length>0)this.isTreeGrowing=!0;else return!0;if(this.totalIterations%h.CONVERGENCE_CHECK_PERIOD==0&&!this.isTreeGrowing&&!this.isGrowthFinished){if(this.isConverged())if(this.prunedNodesAll.length>0)this.isTreeGrowing=!0;else return!0;this.coolingCycle++,this.layoutQuality==0?this.coolingAdjuster=this.coolingCycle:this.layoutQuality==1&&(this.coolingAdjuster=this.coolingCycle/3),this.coolingFactor=Math.max(this.initialCoolingFactor-Math.pow(this.coolingCycle,Math.log(100*(this.initialCoolingFactor-this.finalTemperature))/Math.log(this.maxCoolingCycle))/100*this.coolingAdjuster,this.finalTemperature),this.animationPeriod=Math.ceil(this.initialAnimationPeriod*Math.sqrt(this.coolingFactor))}if(this.isTreeGrowing){if(this.growTreeIterations%10==0)if(this.prunedNodesAll.length>0){this.graphManager.updateBounds(),this.updateGrid(),this.growTree(this.prunedNodesAll),this.graphManager.resetAllNodesToApplyGravitation();var a=new Set(this.getAllNodes()),m=this.nodesWithGravity.filter(function(y){return a.has(y)});this.graphManager.setAllNodesToApplyGravitation(m),this.graphManager.updateBounds(),this.updateGrid(),o.PURE_INCREMENTAL?this.coolingFactor=h.DEFAULT_COOLING_FACTOR_INCREMENTAL/2:this.coolingFactor=h.DEFAULT_COOLING_FACTOR_INCREMENTAL}else this.isTreeGrowing=!1,this.isGrowthFinished=!0;this.growTreeIterations++}if(this.isGrowthFinished){if(this.isConverged())return!0;this.afterGrowthIterations%10==0&&(this.graphManager.updateBounds(),this.updateGrid()),o.PURE_INCREMENTAL?this.coolingFactor=h.DEFAULT_COOLING_FACTOR_INCREMENTAL/2*((100-this.afterGrowthIterations)/100):this.coolingFactor=h.DEFAULT_COOLING_FACTOR_INCREMENTAL*((100-this.afterGrowthIterations)/100),this.afterGrowthIterations++}var p=!this.isTreeGrowing&&!this.isGrowthFinished,E=this.growTreeIterations%10==1&&this.isTreeGrowing||this.afterGrowthIterations%10==1&&this.isGrowthFinished;return this.totalDisplacement=0,this.graphManager.updateBounds(),this.calcSpringForces(),this.calcRepulsionForces(p,E),this.calcGravitationalForces(),this.moveNodes(),this.animate(),!1},D.prototype.getPositionsData=function(){for(var a=this.graphManager.getAllNodes(),m={},p=0;p<a.length;p++){var E=a[p].rect,y=a[p].id;m[y]={id:y,x:E.getCenterX(),y:E.getCenterY(),w:E.width,h:E.height}}return m},D.prototype.runSpringEmbedder=function(){this.initialAnimationPeriod=25,this.animationPeriod=this.initialAnimationPeriod;var a=!1;if(h.ANIMATE==="during")this.emit("layoutstarted");else{for(;!a;)a=this.tick();this.graphManager.updateBounds()}},D.prototype.moveNodes=function(){for(var a=this.getAllNodes(),m,p=0;p<a.length;p++)m=a[p],m.calculateDisplacement();Object.keys(this.constraints).length>0&&this.updateDisplacements();for(var p=0;p<a.length;p++)m=a[p],m.move()},D.prototype.initConstraintVariables=function(){var a=this;this.idToNodeMap=new Map,this.fixedNodeSet=new Set;for(var m=this.graphManager.getAllNodes(),p=0;p<m.length;p++){var E=m[p];this.idToNodeMap.set(E.id,E)}var y=function O(H){for(var B=H.getChild().getNodes(),_,lt=0,J=0;J<B.length;J++)_=B[J],_.getChild()==null?a.fixedNodeSet.has(_.id)&&(lt+=100):lt+=O(_);return lt};if(this.constraints.fixedNodeConstraint){this.constraints.fixedNodeConstraint.forEach(function(B){a.fixedNodeSet.add(B.nodeId)});for(var m=this.graphManager.getAllNodes(),E,p=0;p<m.length;p++)if(E=m[p],E.getChild()!=null){var I=y(E);I>0&&(E.fixedNodeWeight=I)}}if(this.constraints.relativePlacementConstraint){var w=new Map,R=new Map;if(this.dummyToNodeForVerticalAlignment=new Map,this.dummyToNodeForHorizontalAlignment=new Map,this.fixedNodesOnHorizontal=new Set,this.fixedNodesOnVertical=new Set,this.fixedNodeSet.forEach(function(O){a.fixedNodesOnHorizontal.add(O),a.fixedNodesOnVertical.add(O)}),this.constraints.alignmentConstraint){if(this.constraints.alignmentConstraint.vertical)for(var W=this.constraints.alignmentConstraint.vertical,p=0;p<W.length;p++)this.dummyToNodeForVerticalAlignment.set("dummy"+p,[]),W[p].forEach(function(H){w.set(H,"dummy"+p),a.dummyToNodeForVerticalAlignment.get("dummy"+p).push(H),a.fixedNodeSet.has(H)&&a.fixedNodesOnHorizontal.add("dummy"+p)});if(this.constraints.alignmentConstraint.horizontal)for(var x=this.constraints.alignmentConstraint.horizontal,p=0;p<x.length;p++)this.dummyToNodeForHorizontalAlignment.set("dummy"+p,[]),x[p].forEach(function(H){R.set(H,"dummy"+p),a.dummyToNodeForHorizontalAlignment.get("dummy"+p).push(H),a.fixedNodeSet.has(H)&&a.fixedNodesOnVertical.add("dummy"+p)})}if(o.RELAX_MOVEMENT_ON_CONSTRAINTS)this.shuffle=function(O){var H,B,_;for(_=O.length-1;_>=2*O.length/3;_--)H=Math.floor(Math.random()*(_+1)),B=O[_],O[_]=O[H],O[H]=B;return O},this.nodesInRelativeHorizontal=[],this.nodesInRelativeVertical=[],this.nodeToRelativeConstraintMapHorizontal=new Map,this.nodeToRelativeConstraintMapVertical=new Map,this.nodeToTempPositionMapHorizontal=new Map,this.nodeToTempPositionMapVertical=new Map,this.constraints.relativePlacementConstraint.forEach(function(O){if(O.left){var H=w.has(O.left)?w.get(O.left):O.left,B=w.has(O.right)?w.get(O.right):O.right;a.nodesInRelativeHorizontal.includes(H)||(a.nodesInRelativeHorizontal.push(H),a.nodeToRelativeConstraintMapHorizontal.set(H,[]),a.dummyToNodeForVerticalAlignment.has(H)?a.nodeToTempPositionMapHorizontal.set(H,a.idToNodeMap.get(a.dummyToNodeForVerticalAlignment.get(H)[0]).getCenterX()):a.nodeToTempPositionMapHorizontal.set(H,a.idToNodeMap.get(H).getCenterX())),a.nodesInRelativeHorizontal.includes(B)||(a.nodesInRelativeHorizontal.push(B),a.nodeToRelativeConstraintMapHorizontal.set(B,[]),a.dummyToNodeForVerticalAlignment.has(B)?a.nodeToTempPositionMapHorizontal.set(B,a.idToNodeMap.get(a.dummyToNodeForVerticalAlignment.get(B)[0]).getCenterX()):a.nodeToTempPositionMapHorizontal.set(B,a.idToNodeMap.get(B).getCenterX())),a.nodeToRelativeConstraintMapHorizontal.get(H).push({right:B,gap:O.gap}),a.nodeToRelativeConstraintMapHorizontal.get(B).push({left:H,gap:O.gap})}else{var _=R.has(O.top)?R.get(O.top):O.top,lt=R.has(O.bottom)?R.get(O.bottom):O.bottom;a.nodesInRelativeVertical.includes(_)||(a.nodesInRelativeVertical.push(_),a.nodeToRelativeConstraintMapVertical.set(_,[]),a.dummyToNodeForHorizontalAlignment.has(_)?a.nodeToTempPositionMapVertical.set(_,a.idToNodeMap.get(a.dummyToNodeForHorizontalAlignment.get(_)[0]).getCenterY()):a.nodeToTempPositionMapVertical.set(_,a.idToNodeMap.get(_).getCenterY())),a.nodesInRelativeVertical.includes(lt)||(a.nodesInRelativeVertical.push(lt),a.nodeToRelativeConstraintMapVertical.set(lt,[]),a.dummyToNodeForHorizontalAlignment.has(lt)?a.nodeToTempPositionMapVertical.set(lt,a.idToNodeMap.get(a.dummyToNodeForHorizontalAlignment.get(lt)[0]).getCenterY()):a.nodeToTempPositionMapVertical.set(lt,a.idToNodeMap.get(lt).getCenterY())),a.nodeToRelativeConstraintMapVertical.get(_).push({bottom:lt,gap:O.gap}),a.nodeToRelativeConstraintMapVertical.get(lt).push({top:_,gap:O.gap})}});else{var q=new Map,V=new Map;this.constraints.relativePlacementConstraint.forEach(function(O){if(O.left){var H=w.has(O.left)?w.get(O.left):O.left,B=w.has(O.right)?w.get(O.right):O.right;q.has(H)?q.get(H).push(B):q.set(H,[B]),q.has(B)?q.get(B).push(H):q.set(B,[H])}else{var _=R.has(O.top)?R.get(O.top):O.top,lt=R.has(O.bottom)?R.get(O.bottom):O.bottom;V.has(_)?V.get(_).push(lt):V.set(_,[lt]),V.has(lt)?V.get(lt).push(_):V.set(lt,[_])}});var U=function(H,B){var _=[],lt=[],J=new k,Rt=new Set,Lt=0;return H.forEach(function(vt,it){if(!Rt.has(it)){_[Lt]=[],lt[Lt]=!1;var gt=it;for(J.push(gt),Rt.add(gt),_[Lt].push(gt);J.length!=0;){gt=J.shift(),B.has(gt)&&(lt[Lt]=!0);var Tt=H.get(gt);Tt.forEach(function(At){Rt.has(At)||(J.push(At),Rt.add(At),_[Lt].push(At))})}Lt++}}),{components:_,isFixed:lt}},et=U(q,a.fixedNodesOnHorizontal);this.componentsOnHorizontal=et.components,this.fixedComponentsOnHorizontal=et.isFixed;var z=U(V,a.fixedNodesOnVertical);this.componentsOnVertical=z.components,this.fixedComponentsOnVertical=z.isFixed}}},D.prototype.updateDisplacements=function(){var a=this;if(this.constraints.fixedNodeConstraint&&this.constraints.fixedNodeConstraint.forEach(function(z){var O=a.idToNodeMap.get(z.nodeId);O.displacementX=0,O.displacementY=0}),this.constraints.alignmentConstraint){if(this.constraints.alignmentConstraint.vertical)for(var m=this.constraints.alignmentConstraint.vertical,p=0;p<m.length;p++){for(var E=0,y=0;y<m[p].length;y++){if(this.fixedNodeSet.has(m[p][y])){E=0;break}E+=this.idToNodeMap.get(m[p][y]).displacementX}for(var I=E/m[p].length,y=0;y<m[p].length;y++)this.idToNodeMap.get(m[p][y]).displacementX=I}if(this.constraints.alignmentConstraint.horizontal)for(var w=this.constraints.alignmentConstraint.horizontal,p=0;p<w.length;p++){for(var R=0,y=0;y<w[p].length;y++){if(this.fixedNodeSet.has(w[p][y])){R=0;break}R+=this.idToNodeMap.get(w[p][y]).displacementY}for(var W=R/w[p].length,y=0;y<w[p].length;y++)this.idToNodeMap.get(w[p][y]).displacementY=W}}if(this.constraints.relativePlacementConstraint)if(o.RELAX_MOVEMENT_ON_CONSTRAINTS)this.totalIterations%10==0&&(this.shuffle(this.nodesInRelativeHorizontal),this.shuffle(this.nodesInRelativeVertical)),this.nodesInRelativeHorizontal.forEach(function(z){if(!a.fixedNodesOnHorizontal.has(z)){var O=0;a.dummyToNodeForVerticalAlignment.has(z)?O=a.idToNodeMap.get(a.dummyToNodeForVerticalAlignment.get(z)[0]).displacementX:O=a.idToNodeMap.get(z).displacementX,a.nodeToRelativeConstraintMapHorizontal.get(z).forEach(function(H){if(H.right){var B=a.nodeToTempPositionMapHorizontal.get(H.right)-a.nodeToTempPositionMapHorizontal.get(z)-O;B<H.gap&&(O-=H.gap-B)}else{var B=a.nodeToTempPositionMapHorizontal.get(z)-a.nodeToTempPositionMapHorizontal.get(H.left)+O;B<H.gap&&(O+=H.gap-B)}}),a.nodeToTempPositionMapHorizontal.set(z,a.nodeToTempPositionMapHorizontal.get(z)+O),a.dummyToNodeForVerticalAlignment.has(z)?a.dummyToNodeForVerticalAlignment.get(z).forEach(function(H){a.idToNodeMap.get(H).displacementX=O}):a.idToNodeMap.get(z).displacementX=O}}),this.nodesInRelativeVertical.forEach(function(z){if(!a.fixedNodesOnHorizontal.has(z)){var O=0;a.dummyToNodeForHorizontalAlignment.has(z)?O=a.idToNodeMap.get(a.dummyToNodeForHorizontalAlignment.get(z)[0]).displacementY:O=a.idToNodeMap.get(z).displacementY,a.nodeToRelativeConstraintMapVertical.get(z).forEach(function(H){if(H.bottom){var B=a.nodeToTempPositionMapVertical.get(H.bottom)-a.nodeToTempPositionMapVertical.get(z)-O;B<H.gap&&(O-=H.gap-B)}else{var B=a.nodeToTempPositionMapVertical.get(z)-a.nodeToTempPositionMapVertical.get(H.top)+O;B<H.gap&&(O+=H.gap-B)}}),a.nodeToTempPositionMapVertical.set(z,a.nodeToTempPositionMapVertical.get(z)+O),a.dummyToNodeForHorizontalAlignment.has(z)?a.dummyToNodeForHorizontalAlignment.get(z).forEach(function(H){a.idToNodeMap.get(H).displacementY=O}):a.idToNodeMap.get(z).displacementY=O}});else{for(var p=0;p<this.componentsOnHorizontal.length;p++){var x=this.componentsOnHorizontal[p];if(this.fixedComponentsOnHorizontal[p])for(var y=0;y<x.length;y++)this.dummyToNodeForVerticalAlignment.has(x[y])?this.dummyToNodeForVerticalAlignment.get(x[y]).forEach(function(H){a.idToNodeMap.get(H).displacementX=0}):this.idToNodeMap.get(x[y]).displacementX=0;else{for(var q=0,V=0,y=0;y<x.length;y++)if(this.dummyToNodeForVerticalAlignment.has(x[y])){var U=this.dummyToNodeForVerticalAlignment.get(x[y]);q+=U.length*this.idToNodeMap.get(U[0]).displacementX,V+=U.length}else q+=this.idToNodeMap.get(x[y]).displacementX,V++;for(var et=q/V,y=0;y<x.length;y++)this.dummyToNodeForVerticalAlignment.has(x[y])?this.dummyToNodeForVerticalAlignment.get(x[y]).forEach(function(H){a.idToNodeMap.get(H).displacementX=et}):this.idToNodeMap.get(x[y]).displacementX=et}}for(var p=0;p<this.componentsOnVertical.length;p++){var x=this.componentsOnVertical[p];if(this.fixedComponentsOnVertical[p])for(var y=0;y<x.length;y++)this.dummyToNodeForHorizontalAlignment.has(x[y])?this.dummyToNodeForHorizontalAlignment.get(x[y]).forEach(function(B){a.idToNodeMap.get(B).displacementY=0}):this.idToNodeMap.get(x[y]).displacementY=0;else{for(var q=0,V=0,y=0;y<x.length;y++)if(this.dummyToNodeForHorizontalAlignment.has(x[y])){var U=this.dummyToNodeForHorizontalAlignment.get(x[y]);q+=U.length*this.idToNodeMap.get(U[0]).displacementY,V+=U.length}else q+=this.idToNodeMap.get(x[y]).displacementY,V++;for(var et=q/V,y=0;y<x.length;y++)this.dummyToNodeForHorizontalAlignment.has(x[y])?this.dummyToNodeForHorizontalAlignment.get(x[y]).forEach(function(J){a.idToNodeMap.get(J).displacementY=et}):this.idToNodeMap.get(x[y]).displacementY=et}}}},D.prototype.calculateNodesToApplyGravitationTo=function(){var a=[],m,p=this.graphManager.getGraphs(),E=p.length,y;for(y=0;y<E;y++)m=p[y],m.updateConnected(),m.isConnected||(a=a.concat(m.getNodes()));return a},D.prototype.createBendpoints=function(){var a=[];a=a.concat(this.graphManager.getAllEdges());var m=new Set,p;for(p=0;p<a.length;p++){var E=a[p];if(!m.has(E)){var y=E.getSource(),I=E.getTarget();if(y==I)E.getBendpoints().push(new d),E.getBendpoints().push(new d),this.createDummyNodesForBendpoints(E),m.add(E);else{var w=[];if(w=w.concat(y.getEdgeListToNode(I)),w=w.concat(I.getEdgeListToNode(y)),!m.has(w[0])){if(w.length>1){var R;for(R=0;R<w.length;R++){var W=w[R];W.getBendpoints().push(new d),this.createDummyNodesForBendpoints(W)}}w.forEach(function(x){m.add(x)})}}}if(m.size==a.length)break}},D.prototype.positionNodesRadially=function(a){for(var m=new v(0,0),p=Math.ceil(Math.sqrt(a.length)),E=0,y=0,I=0,w=new d(0,0),R=0;R<a.length;R++){R%p==0&&(I=0,y=E,R!=0&&(y+=o.DEFAULT_COMPONENT_SEPERATION),E=0);var W=a[R],x=S.findCenterOfTree(W);m.x=I,m.y=y,w=D.radialLayout(W,x,m),w.y>E&&(E=Math.floor(w.y)),I=Math.floor(w.x+o.DEFAULT_COMPONENT_SEPERATION)}this.transform(new d(T.WORLD_CENTER_X-w.x/2,T.WORLD_CENTER_Y-w.y/2))},D.radialLayout=function(a,m,p){var E=Math.max(this.maxDiagonalInTree(a),o.DEFAULT_RADIAL_SEPARATION);D.branchRadialLayout(m,null,0,359,0,E);var y=K.calculateBounds(a),I=new Y;I.setDeviceOrgX(y.getMinX()),I.setDeviceOrgY(y.getMinY()),I.setWorldOrgX(p.x),I.setWorldOrgY(p.y);for(var w=0;w<a.length;w++){var R=a[w];R.transform(I)}var W=new d(y.getMaxX(),y.getMaxY());return I.inverseTransformPoint(W)},D.branchRadialLayout=function(a,m,p,E,y,I){var w=(E-p+1)/2;w<0&&(w+=180);var R=(w+p)%360,W=R*P.TWO_PI/360,x=y*Math.cos(W),q=y*Math.sin(W);a.setCenter(x,q);var V=[];V=V.concat(a.getEdges());var U=V.length;m!=null&&U--;for(var et=0,z=V.length,O,H=a.getEdgesBetween(m);H.length>1;){var B=H[0];H.splice(0,1);var _=V.indexOf(B);_>=0&&V.splice(_,1),z--,U--}m!=null?O=(V.indexOf(H[0])+1)%z:O=0;for(var lt=Math.abs(E-p)/U,J=O;et!=U;J=++J%z){var Rt=V[J].getOtherEnd(a);if(Rt!=m){var Lt=(p+et*lt)%360,vt=(Lt+lt)%360;D.branchRadialLayout(Rt,a,Lt,vt,y+I,I),et++}}},D.maxDiagonalInTree=function(a){for(var m=M.MIN_VALUE,p=0;p<a.length;p++){var E=a[p],y=E.getDiagonal();y>m&&(m=y)}return m},D.prototype.calcRepulsionRange=function(){return 2*(this.level+1)*this.idealEdgeLength},D.prototype.groupZeroDegreeMembers=function(){var a=this,m={};this.memberGroups={},this.idToDummyNode={};for(var p=[],E=this.graphManager.getAllNodes(),y=0;y<E.length;y++){var I=E[y],w=I.getParent();this.getNodeDegreeWithChildren(I)===0&&(w.id==null||!this.getToBeTiled(w))&&p.push(I)}for(var y=0;y<p.length;y++){var I=p[y],R=I.getParent().id;typeof m[R]>"u"&&(m[R]=[]),m[R]=m[R].concat(I)}Object.keys(m).forEach(function(W){if(m[W].length>1){var x="DummyCompound_"+W;a.memberGroups[x]=m[W];var q=m[W][0].getParent(),V=new t(a.graphManager);V.id=x,V.paddingLeft=q.paddingLeft||0,V.paddingRight=q.paddingRight||0,V.paddingBottom=q.paddingBottom||0,V.paddingTop=q.paddingTop||0,a.idToDummyNode[x]=V;var U=a.getGraphManager().add(a.newGraph(),V),et=q.getChild();et.add(V);for(var z=0;z<m[W].length;z++){var O=m[W][z];et.remove(O),U.add(O)}}})},D.prototype.clearCompounds=function(){var a={},m={};this.performDFSOnCompounds();for(var p=0;p<this.compoundOrder.length;p++)m[this.compoundOrder[p].id]=this.compoundOrder[p],a[this.compoundOrder[p].id]=[].concat(this.compoundOrder[p].getChild().getNodes()),this.graphManager.remove(this.compoundOrder[p].getChild()),this.compoundOrder[p].child=null;this.graphManager.resetAllNodes(),this.tileCompoundMembers(a,m)},D.prototype.clearZeroDegreeMembers=function(){var a=this,m=this.tiledZeroDegreePack=[];Object.keys(this.memberGroups).forEach(function(p){var E=a.idToDummyNode[p];if(m[p]=a.tileNodes(a.memberGroups[p],E.paddingLeft+E.paddingRight),E.rect.width=m[p].width,E.rect.height=m[p].height,E.setCenter(m[p].centerX,m[p].centerY),E.labelMarginLeft=0,E.labelMarginTop=0,o.NODE_DIMENSIONS_INCLUDE_LABELS){var y=E.rect.width,I=E.rect.height;E.labelWidth&&(E.labelPosHorizontal=="left"?(E.rect.x-=E.labelWidth,E.setWidth(y+E.labelWidth),E.labelMarginLeft=E.labelWidth):E.labelPosHorizontal=="center"&&E.labelWidth>y?(E.rect.x-=(E.labelWidth-y)/2,E.setWidth(E.labelWidth),E.labelMarginLeft=(E.labelWidth-y)/2):E.labelPosHorizontal=="right"&&E.setWidth(y+E.labelWidth)),E.labelHeight&&(E.labelPosVertical=="top"?(E.rect.y-=E.labelHeight,E.setHeight(I+E.labelHeight),E.labelMarginTop=E.labelHeight):E.labelPosVertical=="center"&&E.labelHeight>I?(E.rect.y-=(E.labelHeight-I)/2,E.setHeight(E.labelHeight),E.labelMarginTop=(E.labelHeight-I)/2):E.labelPosVertical=="bottom"&&E.setHeight(I+E.labelHeight))}})},D.prototype.repopulateCompounds=function(){for(var a=this.compoundOrder.length-1;a>=0;a--){var m=this.compoundOrder[a],p=m.id,E=m.paddingLeft,y=m.paddingTop,I=m.labelMarginLeft,w=m.labelMarginTop;this.adjustLocations(this.tiledMemberPack[p],m.rect.x,m.rect.y,E,y,I,w)}},D.prototype.repopulateZeroDegreeMembers=function(){var a=this,m=this.tiledZeroDegreePack;Object.keys(m).forEach(function(p){var E=a.idToDummyNode[p],y=E.paddingLeft,I=E.paddingTop,w=E.labelMarginLeft,R=E.labelMarginTop;a.adjustLocations(m[p],E.rect.x,E.rect.y,y,I,w,R)})},D.prototype.getToBeTiled=function(a){var m=a.id;if(this.toBeTiled[m]!=null)return this.toBeTiled[m];var p=a.getChild();if(p==null)return this.toBeTiled[m]=!1,!1;for(var E=p.getNodes(),y=0;y<E.length;y++){var I=E[y];if(this.getNodeDegree(I)>0)return this.toBeTiled[m]=!1,!1;if(I.getChild()==null){this.toBeTiled[I.id]=!1;continue}if(!this.getToBeTiled(I))return this.toBeTiled[m]=!1,!1}return this.toBeTiled[m]=!0,!0},D.prototype.getNodeDegree=function(a){a.id;for(var m=a.getEdges(),p=0,E=0;E<m.length;E++){var y=m[E];y.getSource().id!==y.getTarget().id&&(p=p+1)}return p},D.prototype.getNodeDegreeWithChildren=function(a){var m=this.getNodeDegree(a);if(a.getChild()==null)return m;for(var p=a.getChild().getNodes(),E=0;E<p.length;E++){var y=p[E];m+=this.getNodeDegreeWithChildren(y)}return m},D.prototype.performDFSOnCompounds=function(){this.compoundOrder=[],this.fillCompexOrderByDFS(this.graphManager.getRoot().getNodes())},D.prototype.fillCompexOrderByDFS=function(a){for(var m=0;m<a.length;m++){var p=a[m];p.getChild()!=null&&this.fillCompexOrderByDFS(p.getChild().getNodes()),this.getToBeTiled(p)&&this.compoundOrder.push(p)}},D.prototype.adjustLocations=function(a,m,p,E,y,I,w){m+=E+I,p+=y+w;for(var R=m,W=0;W<a.rows.length;W++){var x=a.rows[W];m=R;for(var q=0,V=0;V<x.length;V++){var U=x[V];U.rect.x=m,U.rect.y=p,m+=U.rect.width+a.horizontalPadding,U.rect.height>q&&(q=U.rect.height)}p+=q+a.verticalPadding}},D.prototype.tileCompoundMembers=function(a,m){var p=this;this.tiledMemberPack=[],Object.keys(a).forEach(function(E){var y=m[E];if(p.tiledMemberPack[E]=p.tileNodes(a[E],y.paddingLeft+y.paddingRight),y.rect.width=p.tiledMemberPack[E].width,y.rect.height=p.tiledMemberPack[E].height,y.setCenter(p.tiledMemberPack[E].centerX,p.tiledMemberPack[E].centerY),y.labelMarginLeft=0,y.labelMarginTop=0,o.NODE_DIMENSIONS_INCLUDE_LABELS){var I=y.rect.width,w=y.rect.height;y.labelWidth&&(y.labelPosHorizontal=="left"?(y.rect.x-=y.labelWidth,y.setWidth(I+y.labelWidth),y.labelMarginLeft=y.labelWidth):y.labelPosHorizontal=="center"&&y.labelWidth>I?(y.rect.x-=(y.labelWidth-I)/2,y.setWidth(y.labelWidth),y.labelMarginLeft=(y.labelWidth-I)/2):y.labelPosHorizontal=="right"&&y.setWidth(I+y.labelWidth)),y.labelHeight&&(y.labelPosVertical=="top"?(y.rect.y-=y.labelHeight,y.setHeight(w+y.labelHeight),y.labelMarginTop=y.labelHeight):y.labelPosVertical=="center"&&y.labelHeight>w?(y.rect.y-=(y.labelHeight-w)/2,y.setHeight(y.labelHeight),y.labelMarginTop=(y.labelHeight-w)/2):y.labelPosVertical=="bottom"&&y.setHeight(w+y.labelHeight))}})},D.prototype.tileNodes=function(a,m){var p=this.tileNodesByFavoringDim(a,m,!0),E=this.tileNodesByFavoringDim(a,m,!1),y=this.getOrgRatio(p),I=this.getOrgRatio(E),w;return I<y?w=E:w=p,w},D.prototype.getOrgRatio=function(a){var m=a.width,p=a.height,E=m/p;return E<1&&(E=1/E),E},D.prototype.calcIdealRowWidth=function(a,m){var p=o.TILING_PADDING_VERTICAL,E=o.TILING_PADDING_HORIZONTAL,y=a.length,I=0,w=0,R=0;a.forEach(function(z){I+=z.getWidth(),w+=z.getHeight(),z.getWidth()>R&&(R=z.getWidth())});var W=I/y,x=w/y,q=Math.pow(p-E,2)+4*(W+E)*(x+p)*y,V=(E-p+Math.sqrt(q))/(2*(W+E)),U;m?(U=Math.ceil(V),U==V&&U++):U=Math.floor(V);var et=U*(W+E)-E;return R>et&&(et=R),et+=E*2,et},D.prototype.tileNodesByFavoringDim=function(a,m,p){var E=o.TILING_PADDING_VERTICAL,y=o.TILING_PADDING_HORIZONTAL,I=o.TILING_COMPARE_BY,w={rows:[],rowWidth:[],rowHeight:[],width:0,height:m,verticalPadding:E,horizontalPadding:y,centerX:0,centerY:0};I&&(w.idealRowWidth=this.calcIdealRowWidth(a,p));var R=function(O){return O.rect.width*O.rect.height},W=function(O,H){return R(H)-R(O)};a.sort(function(z,O){var H=W;return w.idealRowWidth?(H=I,H(z.id,O.id)):H(z,O)});for(var x=0,q=0,V=0;V<a.length;V++){var U=a[V];x+=U.getCenterX(),q+=U.getCenterY()}w.centerX=x/a.length,w.centerY=q/a.length;for(var V=0;V<a.length;V++){var U=a[V];if(w.rows.length==0)this.insertNodeToRow(w,U,0,m);else if(this.canAddHorizontal(w,U.rect.width,U.rect.height)){var et=w.rows.length-1;w.idealRowWidth||(et=this.getShortestRowIndex(w)),this.insertNodeToRow(w,U,et,m)}else this.insertNodeToRow(w,U,w.rows.length,m);this.shiftToLastRow(w)}return w},D.prototype.insertNodeToRow=function(a,m,p,E){var y=E;if(p==a.rows.length){var I=[];a.rows.push(I),a.rowWidth.push(y),a.rowHeight.push(0)}var w=a.rowWidth[p]+m.rect.width;a.rows[p].length>0&&(w+=a.horizontalPadding),a.rowWidth[p]=w,a.width<w&&(a.width=w);var R=m.rect.height;p>0&&(R+=a.verticalPadding);var W=0;R>a.rowHeight[p]&&(W=a.rowHeight[p],a.rowHeight[p]=R,W=a.rowHeight[p]-W),a.height+=W,a.rows[p].push(m)},D.prototype.getShortestRowIndex=function(a){for(var m=-1,p=Number.MAX_VALUE,E=0;E<a.rows.length;E++)a.rowWidth[E]<p&&(m=E,p=a.rowWidth[E]);return m},D.prototype.getLongestRowIndex=function(a){for(var m=-1,p=Number.MIN_VALUE,E=0;E<a.rows.length;E++)a.rowWidth[E]>p&&(m=E,p=a.rowWidth[E]);return m},D.prototype.canAddHorizontal=function(a,m,p){if(a.idealRowWidth){var E=a.rows.length-1,y=a.rowWidth[E];return y+m+a.horizontalPadding<=a.idealRowWidth}var I=this.getShortestRowIndex(a);if(I<0)return!0;var w=a.rowWidth[I];if(w+a.horizontalPadding+m<=a.width)return!0;var R=0;a.rowHeight[I]<p&&I>0&&(R=p+a.verticalPadding-a.rowHeight[I]);var W;a.width-w>=m+a.horizontalPadding?W=(a.height+R)/(w+m+a.horizontalPadding):W=(a.height+R)/a.width,R=p+a.verticalPadding;var x;return a.width<m?x=(a.height+R)/m:x=(a.height+R)/a.width,x<1&&(x=1/x),W<1&&(W=1/W),W<x},D.prototype.shiftToLastRow=function(a){var m=this.getLongestRowIndex(a),p=a.rowWidth.length-1,E=a.rows[m],y=E[E.length-1],I=y.width+a.horizontalPadding;if(a.width-a.rowWidth[p]>I&&m!=p){E.splice(-1,1),a.rows[p].push(y),a.rowWidth[m]=a.rowWidth[m]-I,a.rowWidth[p]=a.rowWidth[p]+I,a.width=a.rowWidth[instance.getLongestRowIndex(a)];for(var w=Number.MIN_VALUE,R=0;R<E.length;R++)E[R].height>w&&(w=E[R].height);m>0&&(w+=a.verticalPadding);var W=a.rowHeight[m]+a.rowHeight[p];a.rowHeight[m]=w,a.rowHeight[p]<y.height+a.verticalPadding&&(a.rowHeight[p]=y.height+a.verticalPadding);var x=a.rowHeight[m]+a.rowHeight[p];a.height+=x-W,this.shiftToLastRow(a)}},D.prototype.tilingPreLayout=function(){o.TILE&&(this.groupZeroDegreeMembers(),this.clearCompounds(),this.clearZeroDegreeMembers())},D.prototype.tilingPostLayout=function(){o.TILE&&(this.repopulateZeroDegreeMembers(),this.repopulateCompounds())},D.prototype.reduceTrees=function(){for(var a=[],m=!0,p;m;){var E=this.graphManager.getAllNodes(),y=[];m=!1;for(var I=0;I<E.length;I++)if(p=E[I],p.getEdges().length==1&&!p.getEdges()[0].isInterGraph&&p.getChild()==null){if(o.PURE_INCREMENTAL){var w=p.getEdges()[0].getOtherEnd(p),R=new N(p.getCenterX()-w.getCenterX(),p.getCenterY()-w.getCenterY());y.push([p,p.getEdges()[0],p.getOwner(),R])}else y.push([p,p.getEdges()[0],p.getOwner()]);m=!0}if(m==!0){for(var W=[],x=0;x<y.length;x++)y[x][0].getEdges().length==1&&(W.push(y[x]),y[x][0].getOwner().remove(y[x][0]));a.push(W),this.graphManager.resetAllNodes(),this.graphManager.resetAllEdges()}}this.prunedNodesAll=a},D.prototype.growTree=function(a){for(var m=a.length,p=a[m-1],E,y=0;y<p.length;y++)E=p[y],this.findPlaceforPrunedNode(E),E[2].add(E[0]),E[2].add(E[1],E[1].source,E[1].target);a.splice(a.length-1,1),this.graphManager.resetAllNodes(),this.graphManager.resetAllEdges()},D.prototype.findPlaceforPrunedNode=function(a){var m,p,E=a[0];if(E==a[1].source?p=a[1].target:p=a[1].source,o.PURE_INCREMENTAL)E.setCenter(p.getCenterX()+a[3].getWidth(),p.getCenterY()+a[3].getHeight());else{var y=p.startX,I=p.finishX,w=p.startY,R=p.finishY,W=0,x=0,q=0,V=0,U=[W,q,x,V];if(w>0)for(var et=y;et<=I;et++)U[0]+=this.grid[et][w-1].length+this.grid[et][w].length-1;if(I<this.grid.length-1)for(var et=w;et<=R;et++)U[1]+=this.grid[I+1][et].length+this.grid[I][et].length-1;if(R<this.grid[0].length-1)for(var et=y;et<=I;et++)U[2]+=this.grid[et][R+1].length+this.grid[et][R].length-1;if(y>0)for(var et=w;et<=R;et++)U[3]+=this.grid[y-1][et].length+this.grid[y][et].length-1;for(var z=M.MAX_VALUE,O,H,B=0;B<U.length;B++)U[B]<z?(z=U[B],O=1,H=B):U[B]==z&&O++;if(O==3&&z==0)U[0]==0&&U[1]==0&&U[2]==0?m=1:U[0]==0&&U[1]==0&&U[3]==0?m=0:U[0]==0&&U[2]==0&&U[3]==0?m=3:U[1]==0&&U[2]==0&&U[3]==0&&(m=2);else if(O==2&&z==0){var _=Math.floor(Math.random()*2);U[0]==0&&U[1]==0?_==0?m=0:m=1:U[0]==0&&U[2]==0?_==0?m=0:m=2:U[0]==0&&U[3]==0?_==0?m=0:m=3:U[1]==0&&U[2]==0?_==0?m=1:m=2:U[1]==0&&U[3]==0?_==0?m=1:m=3:_==0?m=2:m=3}else if(O==4&&z==0){var _=Math.floor(Math.random()*4);m=_}else m=H;m==0?E.setCenter(p.getCenterX(),p.getCenterY()-p.getHeight()/2-h.DEFAULT_EDGE_LENGTH-E.getHeight()/2):m==1?E.setCenter(p.getCenterX()+p.getWidth()/2+h.DEFAULT_EDGE_LENGTH+E.getWidth()/2,p.getCenterY()):m==2?E.setCenter(p.getCenterX(),p.getCenterY()+p.getHeight()/2+h.DEFAULT_EDGE_LENGTH+E.getHeight()/2):E.setCenter(p.getCenterX()-p.getWidth()/2-h.DEFAULT_EDGE_LENGTH-E.getWidth()/2,p.getCenterY())}},n.exports=D},991:(n,r,e)=>{var f=e(551).FDLayoutNode,i=e(551).IMath;function g(s,o,c,h){f.call(this,s,o,c,h)}g.prototype=Object.create(f.prototype);for(var t in f)g[t]=f[t];g.prototype.calculateDisplacement=function(){var s=this.graphManager.getLayout();this.getChild()!=null&&this.fixedNodeWeight?(this.displacementX+=s.coolingFactor*(this.springForceX+this.repulsionForceX+this.gravitationForceX)/this.fixedNodeWeight,this.displacementY+=s.coolingFactor*(this.springForceY+this.repulsionForceY+this.gravitationForceY)/this.fixedNodeWeight):(this.displacementX+=s.coolingFactor*(this.springForceX+this.repulsionForceX+this.gravitationForceX)/this.noOfChildren,this.displacementY+=s.coolingFactor*(this.springForceY+this.repulsionForceY+this.gravitationForceY)/this.noOfChildren),Math.abs(this.displacementX)>s.coolingFactor*s.maxNodeDisplacement&&(this.displacementX=s.coolingFactor*s.maxNodeDisplacement*i.sign(this.displacementX)),Math.abs(this.displacementY)>s.coolingFactor*s.maxNodeDisplacement&&(this.displacementY=s.coolingFactor*s.maxNodeDisplacement*i.sign(this.displacementY)),this.child&&this.child.getNodes().length>0&&this.propogateDisplacementToChildren(this.displacementX,this.displacementY)},g.prototype.propogateDisplacementToChildren=function(s,o){for(var c=this.getChild().getNodes(),h,T=0;T<c.length;T++)h=c[T],h.getChild()==null?(h.displacementX+=s,h.displacementY+=o):h.propogateDisplacementToChildren(s,o)},g.prototype.move=function(){var s=this.graphManager.getLayout();(this.child==null||this.child.getNodes().length==0)&&(this.moveBy(this.displacementX,this.displacementY),s.totalDisplacement+=Math.abs(this.displacementX)+Math.abs(this.displacementY)),this.springForceX=0,this.springForceY=0,this.repulsionForceX=0,this.repulsionForceY=0,this.gravitationForceX=0,this.gravitationForceY=0,this.displacementX=0,this.displacementY=0},g.prototype.setPred1=function(s){this.pred1=s},g.prototype.getPred1=function(){return pred1},g.prototype.getPred2=function(){return pred2},g.prototype.setNext=function(s){this.next=s},g.prototype.getNext=function(){return next},g.prototype.setProcessed=function(s){this.processed=s},g.prototype.isProcessed=function(){return processed},n.exports=g},902:(n,r,e)=>{function f(c){if(Array.isArray(c)){for(var h=0,T=Array(c.length);h<c.length;h++)T[h]=c[h];return T}else return Array.from(c)}var i=e(806),g=e(551).LinkedList,t=e(551).Matrix,s=e(551).SVD;function o(){}o.handleConstraints=function(c){var h={};h.fixedNodeConstraint=c.constraints.fixedNodeConstraint,h.alignmentConstraint=c.constraints.alignmentConstraint,h.relativePlacementConstraint=c.constraints.relativePlacementConstraint;for(var T=new Map,v=new Map,d=[],N=[],S=c.getAllNodes(),M=0,P=0;P<S.length;P++){var K=S[P];K.getChild()==null&&(v.set(K.id,M++),d.push(K.getCenterX()),N.push(K.getCenterY()),T.set(K.id,K))}h.relativePlacementConstraint&&h.relativePlacementConstraint.forEach(function(F){!F.gap&&F.gap!=0&&(F.left?F.gap=i.DEFAULT_EDGE_LENGTH+T.get(F.left).getWidth()/2+T.get(F.right).getWidth()/2:F.gap=i.DEFAULT_EDGE_LENGTH+T.get(F.top).getHeight()/2+T.get(F.bottom).getHeight()/2)});var Y=function(b,$){return{x:b.x-$.x,y:b.y-$.y}},k=function(b){var $=0,Q=0;return b.forEach(function(Z){$+=d[v.get(Z)],Q+=N[v.get(Z)]}),{x:$/b.size,y:Q/b.size}},D=function(b,$,Q,Z,nt){function ut(ft,st){var Ct=new Set(ft),ct=!0,ht=!1,Wt=void 0;try{for(var Nt=st[Symbol.iterator](),Mt;!(ct=(Mt=Nt.next()).done);ct=!0){var Zt=Mt.value;Ct.add(Zt)}}catch(Gt){ht=!0,Wt=Gt}finally{try{!ct&&Nt.return&&Nt.return()}finally{if(ht)throw Wt}}return Ct}var ot=new Map;b.forEach(function(ft,st){ot.set(st,0)}),b.forEach(function(ft,st){ft.forEach(function(Ct){ot.set(Ct.id,ot.get(Ct.id)+1)})});var tt=new Map,j=new Map,dt=new g;ot.forEach(function(ft,st){ft==0?(dt.push(st),Q||($=="horizontal"?tt.set(st,v.has(st)?d[v.get(st)]:Z.get(st)):tt.set(st,v.has(st)?N[v.get(st)]:Z.get(st)))):tt.set(st,Number.NEGATIVE_INFINITY),Q&&j.set(st,new Set([st]))}),Q&&nt.forEach(function(ft){var st=[];if(ft.forEach(function(ht){Q.has(ht)&&st.push(ht)}),st.length>0){var Ct=0;st.forEach(function(ht){$=="horizontal"?(tt.set(ht,v.has(ht)?d[v.get(ht)]:Z.get(ht)),Ct+=tt.get(ht)):(tt.set(ht,v.has(ht)?N[v.get(ht)]:Z.get(ht)),Ct+=tt.get(ht))}),Ct=Ct/st.length,ft.forEach(function(ht){Q.has(ht)||tt.set(ht,Ct)})}else{var ct=0;ft.forEach(function(ht){$=="horizontal"?ct+=v.has(ht)?d[v.get(ht)]:Z.get(ht):ct+=v.has(ht)?N[v.get(ht)]:Z.get(ht)}),ct=ct/ft.length,ft.forEach(function(ht){tt.set(ht,ct)})}});for(var wt=function(){var st=dt.shift(),Ct=b.get(st);Ct.forEach(function(ct){if(tt.get(ct.id)<tt.get(st)+ct.gap)if(Q&&Q.has(ct.id)){var ht=void 0;if($=="horizontal"?ht=v.has(ct.id)?d[v.get(ct.id)]:Z.get(ct.id):ht=v.has(ct.id)?N[v.get(ct.id)]:Z.get(ct.id),tt.set(ct.id,ht),ht<tt.get(st)+ct.gap){var Wt=tt.get(st)+ct.gap-ht;j.get(st).forEach(function(Nt){tt.set(Nt,tt.get(Nt)-Wt)})}}else tt.set(ct.id,tt.get(st)+ct.gap);ot.set(ct.id,ot.get(ct.id)-1),ot.get(ct.id)==0&&dt.push(ct.id),Q&&j.set(ct.id,ut(j.get(st),j.get(ct.id)))})};dt.length!=0;)wt();if(Q){var yt=new Set;b.forEach(function(ft,st){ft.length==0&&yt.add(st)});var It=[];j.forEach(function(ft,st){if(yt.has(st)){var Ct=!1,ct=!0,ht=!1,Wt=void 0;try{for(var Nt=ft[Symbol.iterator](),Mt;!(ct=(Mt=Nt.next()).done);ct=!0){var Zt=Mt.value;Q.has(Zt)&&(Ct=!0)}}catch(Ft){ht=!0,Wt=Ft}finally{try{!ct&&Nt.return&&Nt.return()}finally{if(ht)throw Wt}}if(!Ct){var Gt=!1,$t=void 0;It.forEach(function(Ft,qt){Ft.has([].concat(f(ft))[0])&&(Gt=!0,$t=qt)}),Gt?ft.forEach(function(Ft){It[$t].add(Ft)}):It.push(new Set(ft))}}}),It.forEach(function(ft,st){var Ct=Number.POSITIVE_INFINITY,ct=Number.POSITIVE_INFINITY,ht=Number.NEGATIVE_INFINITY,Wt=Number.NEGATIVE_INFINITY,Nt=!0,Mt=!1,Zt=void 0;try{for(var Gt=ft[Symbol.iterator](),$t;!(Nt=($t=Gt.next()).done);Nt=!0){var Ft=$t.value,qt=void 0;$=="horizontal"?qt=v.has(Ft)?d[v.get(Ft)]:Z.get(Ft):qt=v.has(Ft)?N[v.get(Ft)]:Z.get(Ft);var _t=tt.get(Ft);qt<Ct&&(Ct=qt),qt>ht&&(ht=qt),_t<ct&&(ct=_t),_t>Wt&&(Wt=_t)}}catch(ie){Mt=!0,Zt=ie}finally{try{!Nt&&Gt.return&&Gt.return()}finally{if(Mt)throw Zt}}var ge=(Ct+ht)/2-(ct+Wt)/2,Kt=!0,te=!1,ee=void 0;try{for(var jt=ft[Symbol.iterator](),se;!(Kt=(se=jt.next()).done);Kt=!0){var re=se.value;tt.set(re,tt.get(re)+ge)}}catch(ie){te=!0,ee=ie}finally{try{!Kt&&jt.return&&jt.return()}finally{if(te)throw ee}}})}return tt},rt=function(b){var $=0,Q=0,Z=0,nt=0;if(b.forEach(function(j){j.left?d[v.get(j.left)]-d[v.get(j.right)]>=0?$++:Q++:N[v.get(j.top)]-N[v.get(j.bottom)]>=0?Z++:nt++}),$>Q&&Z>nt)for(var ut=0;ut<v.size;ut++)d[ut]=-1*d[ut],N[ut]=-1*N[ut];else if($>Q)for(var ot=0;ot<v.size;ot++)d[ot]=-1*d[ot];else if(Z>nt)for(var tt=0;tt<v.size;tt++)N[tt]=-1*N[tt]},a=function(b){var $=[],Q=new g,Z=new Set,nt=0;return b.forEach(function(ut,ot){if(!Z.has(ot)){$[nt]=[];var tt=ot;for(Q.push(tt),Z.add(tt),$[nt].push(tt);Q.length!=0;){tt=Q.shift();var j=b.get(tt);j.forEach(function(dt){Z.has(dt.id)||(Q.push(dt.id),Z.add(dt.id),$[nt].push(dt.id))})}nt++}}),$},m=function(b){var $=new Map;return b.forEach(function(Q,Z){$.set(Z,[])}),b.forEach(function(Q,Z){Q.forEach(function(nt){$.get(Z).push(nt),$.get(nt.id).push({id:Z,gap:nt.gap,direction:nt.direction})})}),$},p=function(b){var $=new Map;return b.forEach(function(Q,Z){$.set(Z,[])}),b.forEach(function(Q,Z){Q.forEach(function(nt){$.get(nt.id).push({id:Z,gap:nt.gap,direction:nt.direction})})}),$},E=[],y=[],I=!1,w=!1,R=new Set,W=new Map,x=new 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d.tilingPaddingVertical=="function"?d.tilingPaddingVertical.call():d.tilingPaddingVertical,h.TILING_PADDING_HORIZONTAL=typeof d.tilingPaddingHorizontal=="function"?d.tilingPaddingHorizontal.call():d.tilingPaddingHorizontal,h.DEFAULT_INCREMENTAL=c.DEFAULT_INCREMENTAL=o.DEFAULT_INCREMENTAL=!0,h.PURE_INCREMENTAL=!d.randomize,o.DEFAULT_UNIFORM_LEAF_NODE_SIZES=d.uniformNodeDimensions,d.step=="transformed"&&(h.TRANSFORM_ON_CONSTRAINT_HANDLING=!0,h.ENFORCE_CONSTRAINTS=!1,h.APPLY_LAYOUT=!1),d.step=="enforced"&&(h.TRANSFORM_ON_CONSTRAINT_HANDLING=!1,h.ENFORCE_CONSTRAINTS=!0,h.APPLY_LAYOUT=!1),d.step=="cose"&&(h.TRANSFORM_ON_CONSTRAINT_HANDLING=!1,h.ENFORCE_CONSTRAINTS=!1,h.APPLY_LAYOUT=!0),d.step=="all"&&(d.randomize?h.TRANSFORM_ON_CONSTRAINT_HANDLING=!0:h.TRANSFORM_ON_CONSTRAINT_HANDLING=!1,h.ENFORCE_CONSTRAINTS=!0,h.APPLY_LAYOUT=!0),d.fixedNodeConstraint||d.alignmentConstraint||d.relativePlacementConstraint?h.TREE_REDUCTION_ON_INCREMENTAL=!1:h.TREE_REDUCTION_ON_INCREMENTAL=!0;var w=new i,R=w.newGraphManager();return E(R.addRoot(),f.getTopMostNodes(P),w,d),y(w,R,K),I(w,d),w.runLayout(),rt};n.exports={coseLayout:T}},212:(n,r,e)=>{var f=function(){function d(N,S){for(var M=0;M<S.length;M++){var P=S[M];P.enumerable=P.enumerable||!1,P.configurable=!0,"value"in P&&(P.writable=!0),Object.defineProperty(N,P.key,P)}}return function(N,S,M){return S&&d(N.prototype,S),M&&d(N,M),N}}();function i(d,N){if(!(d instanceof N))throw new TypeError("Cannot call a class as a function")}var g=e(658),t=e(548),s=e(657),o=s.spectralLayout,c=e(816),h=c.coseLayout,T=Object.freeze({quality:"default",randomize:!0,animate:!0,animationDuration:1e3,animationEasing:void 0,fit:!0,padding:30,nodeDimensionsIncludeLabels:!1,uniformNodeDimensions:!1,packComponents:!0,step:"all",samplingType:!0,sampleSize:25,nodeSeparation:75,piTol:1e-7,nodeRepulsion:function(N){return 4500},idealEdgeLength:function(N){return 50},edgeElasticity:function(N){return .45},nestingFactor:.1,gravity:.25,numIter:2500,tile:!0,tilingCompareBy:void 0,tilingPaddingVertical:10,tilingPaddingHorizontal:10,gravityRangeCompound:1.5,gravityCompound:1,gravityRange:3.8,initialEnergyOnIncremental:.3,fixedNodeConstraint:void 0,alignmentConstraint:void 0,relativePlacementConstraint:void 0,ready:function(){},stop:function(){}}),v=function(){function d(N){i(this,d),this.options=g({},T,N)}return f(d,[{key:"run",value:function(){var S=this,M=this.options,P=M.cy,K=M.eles,Y=[],k=[],D=void 0,rt=[];M.fixedNodeConstraint&&(!Array.isArray(M.fixedNodeConstraint)||M.fixedNodeConstraint.length==0)&&(M.fixedNodeConstraint=void 0),M.alignmentConstraint&&(M.alignmentConstraint.vertical&&(!Array.isArray(M.alignmentConstraint.vertical)||M.alignmentConstraint.vertical.length==0)&&(M.alignmentConstraint.vertical=void 0),M.alignmentConstraint.horizontal&&(!Array.isArray(M.alignmentConstraint.horizontal)||M.alignmentConstraint.horizontal.length==0)&&(M.alignmentConstraint.horizontal=void 0)),M.relativePlacementConstraint&&(!Array.isArray(M.relativePlacementConstraint)||M.relativePlacementConstraint.length==0)&&(M.relativePlacementConstraint=void 0);var a=M.fixedNodeConstraint||M.alignmentConstraint||M.relativePlacementConstraint;a&&(M.tile=!1,M.packComponents=!1);var m=void 0,p=!1;if(P.layoutUtilities&&M.packComponents&&(m=P.layoutUtilities("get"),m||(m=P.layoutUtilities()),p=!0),K.nodes().length>0)if(p){var I=t.getTopMostNodes(M.eles.nodes());if(D=t.connectComponents(P,M.eles,I),D.forEach(function(vt){var it=vt.boundingBox();rt.push({x:it.x1+it.w/2,y:it.y1+it.h/2})}),M.randomize&&D.forEach(function(vt){M.eles=vt,Y.push(o(M))}),M.quality=="default"||M.quality=="proof"){var w=P.collection();if(M.tile){var R=new Map,W=[],x=[],q=0,V={nodeIndexes:R,xCoords:W,yCoords:x},U=[];if(D.forEach(function(vt,it){vt.edges().length==0&&(vt.nodes().forEach(function(gt,Tt){w.merge(vt.nodes()[Tt]),gt.isParent()||(V.nodeIndexes.set(vt.nodes()[Tt].id(),q++),V.xCoords.push(vt.nodes()[0].position().x),V.yCoords.push(vt.nodes()[0].position().y))}),U.push(it))}),w.length>1){var et=w.boundingBox();rt.push({x:et.x1+et.w/2,y:et.y1+et.h/2}),D.push(w),Y.push(V);for(var z=U.length-1;z>=0;z--)D.splice(U[z],1),Y.splice(U[z],1),rt.splice(U[z],1)}}D.forEach(function(vt,it){M.eles=vt,k.push(h(M,Y[it])),t.relocateComponent(rt[it],k[it],M)})}else D.forEach(function(vt,it){t.relocateComponent(rt[it],Y[it],M)});var O=new Set;if(D.length>1){var H=[],B=K.filter(function(vt){return vt.css("display")=="none"});D.forEach(function(vt,it){var gt=void 0;if(M.quality=="draft"&&(gt=Y[it].nodeIndexes),vt.nodes().not(B).length>0){var Tt={};Tt.edges=[],Tt.nodes=[];var At=void 0;vt.nodes().not(B).forEach(function(Dt){if(M.quality=="draft")if(!Dt.isParent())At=gt.get(Dt.id()),Tt.nodes.push({x:Y[it].xCoords[At]-Dt.boundingbox().w/2,y:Y[it].yCoords[At]-Dt.boundingbox().h/2,width:Dt.boundingbox().w,height:Dt.boundingbox().h});else{var mt=t.calcBoundingBox(Dt,Y[it].xCoords,Y[it].yCoords,gt);Tt.nodes.push({x:mt.topLeftX,y:mt.topLeftY,width:mt.width,height:mt.height})}else k[it][Dt.id()]&&Tt.nodes.push({x:k[it][Dt.id()].getLeft(),y:k[it][Dt.id()].getTop(),width:k[it][Dt.id()].getWidth(),height:k[it][Dt.id()].getHeight()})}),vt.edges().forEach(function(Dt){var mt=Dt.source(),xt=Dt.target();if(mt.css("display")!="none"&&xt.css("display")!="none")if(M.quality=="draft"){var St=gt.get(mt.id()),Vt=gt.get(xt.id()),Xt=[],Ut=[];if(mt.isParent()){var bt=t.calcBoundingBox(mt,Y[it].xCoords,Y[it].yCoords,gt);Xt.push(bt.topLeftX+bt.width/2),Xt.push(bt.topLeftY+bt.height/2)}else Xt.push(Y[it].xCoords[St]),Xt.push(Y[it].yCoords[St]);if(xt.isParent()){var Ht=t.calcBoundingBox(xt,Y[it].xCoords,Y[it].yCoords,gt);Ut.push(Ht.topLeftX+Ht.width/2),Ut.push(Ht.topLeftY+Ht.height/2)}else Ut.push(Y[it].xCoords[Vt]),Ut.push(Y[it].yCoords[Vt]);Tt.edges.push({startX:Xt[0],startY:Xt[1],endX:Ut[0],endY:Ut[1]})}else k[it][mt.id()]&&k[it][xt.id()]&&Tt.edges.push({startX:k[it][mt.id()].getCenterX(),startY:k[it][mt.id()].getCenterY(),endX:k[it][xt.id()].getCenterX(),endY:k[it][xt.id()].getCenterY()})}),Tt.nodes.length>0&&(H.push(Tt),O.add(it))}});var _=m.packComponents(H,M.randomize).shifts;if(M.quality=="draft")Y.forEach(function(vt,it){var gt=vt.xCoords.map(function(At){return At+_[it].dx}),Tt=vt.yCoords.map(function(At){return At+_[it].dy});vt.xCoords=gt,vt.yCoords=Tt});else{var lt=0;O.forEach(function(vt){Object.keys(k[vt]).forEach(function(it){var gt=k[vt][it];gt.setCenter(gt.getCenterX()+_[lt].dx,gt.getCenterY()+_[lt].dy)}),lt++})}}}else{var E=M.eles.boundingBox();if(rt.push({x:E.x1+E.w/2,y:E.y1+E.h/2}),M.randomize){var y=o(M);Y.push(y)}M.quality=="default"||M.quality=="proof"?(k.push(h(M,Y[0])),t.relocateComponent(rt[0],k[0],M)):t.relocateComponent(rt[0],Y[0],M)}var J=function(it,gt){if(M.quality=="default"||M.quality=="proof"){typeof it=="number"&&(it=gt);var Tt=void 0,At=void 0,Dt=it.data("id");return k.forEach(function(xt){Dt in xt&&(Tt={x:xt[Dt].getRect().getCenterX(),y:xt[Dt].getRect().getCenterY()},At=xt[Dt])}),M.nodeDimensionsIncludeLabels&&(At.labelWidth&&(At.labelPosHorizontal=="left"?Tt.x+=At.labelWidth/2:At.labelPosHorizontal=="right"&&(Tt.x-=At.labelWidth/2)),At.labelHeight&&(At.labelPosVertical=="top"?Tt.y+=At.labelHeight/2:At.labelPosVertical=="bottom"&&(Tt.y-=At.labelHeight/2))),Tt==null&&(Tt={x:it.position("x"),y:it.position("y")}),{x:Tt.x,y:Tt.y}}else{var mt=void 0;return Y.forEach(function(xt){var St=xt.nodeIndexes.get(it.id());St!=null&&(mt={x:xt.xCoords[St],y:xt.yCoords[St]})}),mt==null&&(mt={x:it.position("x"),y:it.position("y")}),{x:mt.x,y:mt.y}}};if(M.quality=="default"||M.quality=="proof"||M.randomize){var Rt=t.calcParentsWithoutChildren(P,K),Lt=K.filter(function(vt){return vt.css("display")=="none"});M.eles=K.not(Lt),K.nodes().not(":parent").not(Lt).layoutPositions(S,M,J),Rt.length>0&&Rt.forEach(function(vt){vt.position(J(vt))})}else console.log("If randomize option is set to false, then quality option must be 'default' or 'proof'.")}}]),d}();n.exports=v},657:(n,r,e)=>{var f=e(548),i=e(140).layoutBase.Matrix,g=e(140).layoutBase.SVD,t=function(o){var c=o.cy,h=o.eles,T=h.nodes(),v=h.nodes(":parent"),d=new Map,N=new Map,S=new Map,M=[],P=[],K=[],Y=[],k=[],D=[],rt=[],a=[],m=void 0,p=1e8,E=1e-9,y=o.piTol,I=o.samplingType,w=o.nodeSeparation,R=void 0,W=function(){for(var b=0,$=0,Q=!1;$<R;){b=Math.floor(Math.random()*m),Q=!1;for(var Z=0;Z<$;Z++)if(Y[Z]==b){Q=!0;break}if(!Q)Y[$]=b,$++;else continue}},x=function(b,$,Q){for(var Z=[],nt=0,ut=0,ot=0,tt=void 0,j=[],dt=0,wt=1,yt=0;yt<m;yt++)j[yt]=p;for(Z[ut]=b,j[b]=0;ut>=nt;){ot=Z[nt++];for(var It=M[ot],ft=0;ft<It.length;ft++)tt=N.get(It[ft]),j[tt]==p&&(j[tt]=j[ot]+1,Z[++ut]=tt);D[ot][$]=j[ot]*w}if(Q){for(var st=0;st<m;st++)D[st][$]<k[st]&&(k[st]=D[st][$]);for(var Ct=0;Ct<m;Ct++)k[Ct]>dt&&(dt=k[Ct],wt=Ct)}return wt},q=function(b){var $=void 0;if(b){$=Math.floor(Math.random()*m);for(var Z=0;Z<m;Z++)k[Z]=p;for(var nt=0;nt<R;nt++)Y[nt]=$,$=x($,nt,b)}else{W();for(var Q=0;Q<R;Q++)x(Y[Q],Q,b)}for(var ut=0;ut<m;ut++)for(var ot=0;ot<R;ot++)D[ut][ot]*=D[ut][ot];for(var tt=0;tt<R;tt++)rt[tt]=[];for(var j=0;j<R;j++)for(var dt=0;dt<R;dt++)rt[j][dt]=D[Y[dt]][j]},V=function(){for(var b=g.svd(rt),$=b.S,Q=b.U,Z=b.V,nt=$[0]*$[0]*$[0],ut=[],ot=0;ot<R;ot++){ut[ot]=[];for(var tt=0;tt<R;tt++)ut[ot][tt]=0,ot==tt&&(ut[ot][tt]=$[ot]/($[ot]*$[ot]+nt/($[ot]*$[ot])))}a=i.multMat(i.multMat(Z,ut),i.transpose(Q))},U=function(){for(var b=void 0,$=void 0,Q=[],Z=[],nt=[],ut=[],ot=0;ot<m;ot++)Q[ot]=Math.random(),Z[ot]=Math.random();Q=i.normalize(Q),Z=i.normalize(Z);for(var tt=E,j=E,dt=void 0;;){for(var wt=0;wt<m;wt++)nt[wt]=Q[wt];if(Q=i.multGamma(i.multL(i.multGamma(nt),D,a)),b=i.dotProduct(nt,Q),Q=i.normalize(Q),tt=i.dotProduct(nt,Q),dt=Math.abs(tt/j),dt<=1+y&&dt>=1)break;j=tt}for(var yt=0;yt<m;yt++)nt[yt]=Q[yt];for(j=E;;){for(var It=0;It<m;It++)ut[It]=Z[It];if(ut=i.minusOp(ut,i.multCons(nt,i.dotProduct(nt,ut))),Z=i.multGamma(i.multL(i.multGamma(ut),D,a)),$=i.dotProduct(ut,Z),Z=i.normalize(Z),tt=i.dotProduct(ut,Z),dt=Math.abs(tt/j),dt<=1+y&&dt>=1)break;j=tt}for(var ft=0;ft<m;ft++)ut[ft]=Z[ft];P=i.multCons(nt,Math.sqrt(Math.abs(b))),K=i.multCons(ut,Math.sqrt(Math.abs($)))};f.connectComponents(c,h,f.getTopMostNodes(T),d),v.forEach(function(F){f.connectComponents(c,h,f.getTopMostNodes(F.descendants().intersection(h)),d)});for(var et=0,z=0;z<T.length;z++)T[z].isParent()||N.set(T[z].id(),et++);var O=!0,H=!1,B=void 0;try{for(var _=d.keys()[Symbol.iterator](),lt;!(O=(lt=_.next()).done);O=!0){var J=lt.value;N.set(J,et++)}}catch(F){H=!0,B=F}finally{try{!O&&_.return&&_.return()}finally{if(H)throw B}}for(var Rt=0;Rt<N.size;Rt++)M[Rt]=[];v.forEach(function(F){for(var b=F.children().intersection(h);b.nodes(":childless").length==0;)b=b.nodes()[0].children().intersection(h);var $=0,Q=b.nodes(":childless")[0].connectedEdges().length;b.nodes(":childless").forEach(function(Z,nt){Z.connectedEdges().length<Q&&(Q=Z.connectedEdges().length,$=nt)}),S.set(F.id(),b.nodes(":childless")[$].id())}),T.forEach(function(F){var b=void 0;F.isParent()?b=N.get(S.get(F.id())):b=N.get(F.id()),F.neighborhood().nodes().forEach(function($){h.intersection(F.edgesWith($)).length>0&&($.isParent()?M[b].push(S.get($.id())):M[b].push($.id()))})});var Lt=function(b){var $=N.get(b),Q=void 0;d.get(b).forEach(function(Z){c.getElementById(Z).isParent()?Q=S.get(Z):Q=Z,M[$].push(Q),M[N.get(Q)].push(b)})},vt=!0,it=!1,gt=void 0;try{for(var Tt=d.keys()[Symbol.iterator](),At;!(vt=(At=Tt.next()).done);vt=!0){var Dt=At.value;Lt(Dt)}}catch(F){it=!0,gt=F}finally{try{!vt&&Tt.return&&Tt.return()}finally{if(it)throw gt}}m=N.size;var mt=void 0;if(m>2){R=m<o.sampleSize?m:o.sampleSize;for(var xt=0;xt<m;xt++)D[xt]=[];for(var St=0;St<R;St++)a[St]=[];return o.quality=="draft"||o.step=="all"?(q(I),V(),U(),mt={nodeIndexes:N,xCoords:P,yCoords:K}):(N.forEach(function(F,b){P.push(c.getElementById(b).position("x")),K.push(c.getElementById(b).position("y"))}),mt={nodeIndexes:N,xCoords:P,yCoords:K}),mt}else{var Vt=N.keys(),Xt=c.getElementById(Vt.next().value),Ut=Xt.position(),bt=Xt.outerWidth();if(P.push(Ut.x),K.push(Ut.y),m==2){var Ht=c.getElementById(Vt.next().value),Bt=Ht.outerWidth();P.push(Ut.x+bt/2+Bt/2+o.idealEdgeLength),K.push(Ut.y)}return mt={nodeIndexes:N,xCoords:P,yCoords:K},mt}};n.exports={spectralLayout:t}},579:(n,r,e)=>{var f=e(212),i=function(t){t&&t("layout","fcose",f)};typeof cytoscape<"u"&&i(cytoscape),n.exports=i},140:n=>{n.exports=A}},L={};function u(n){var r=L[n];if(r!==void 0)return r.exports;var e=L[n]={exports:{}};return G[n](e,e.exports,u),e.exports}var l=u(579);return l})()})}(le)),le.exports}var Tr=mr();const Nr=gr(Tr);var Se={L:"left",R:"right",T:"top",B:"bottom"},Fe={L:at(C=>`${C},${C/2} 0,${C} 0,0`,"L"),R:at(C=>`0,${C/2} ${C},0 ${C},${C}`,"R"),T:at(C=>`0,0 ${C},0 ${C/2},${C}`,"T"),B:at(C=>`${C/2},0 ${C},${C} 0,${C}`,"B")},he={L:at((C,X)=>C-X+2,"L"),R:at((C,X)=>C-2,"R"),T:at((C,X)=>C-X+2,"T"),B:at((C,X)=>C-2,"B")},Lr=at(function(C){return zt(C)?C==="L"?"R":"L":C==="T"?"B":"T"},"getOppositeArchitectureDirection"),be=at(function(C){const X=C;return X==="L"||X==="R"||X==="T"||X==="B"},"isArchitectureDirection"),zt=at(function(C){const X=C;return X==="L"||X==="R"},"isArchitectureDirectionX"),Qt=at(function(C){const X=C;return X==="T"||X==="B"},"isArchitectureDirectionY"),Ce=at(function(C,X){const A=zt(C)&&Qt(X),G=Qt(C)&&zt(X);return A||G},"isArchitectureDirectionXY"),Cr=at(function(C){const X=C[0],A=C[1],G=zt(X)&&Qt(A),L=Qt(X)&&zt(A);return G||L},"isArchitecturePairXY"),Mr=at(function(C){return C!=="LL"&&C!=="RR"&&C!=="TT"&&C!=="BB"},"isValidArchitectureDirectionPair"),me=at(function(C,X){const A=`${C}${X}`;return Mr(A)?A:void 0},"getArchitectureDirectionPair"),Ar=at(function([C,X],A){const G=A[0],L=A[1];return zt(G)?Qt(L)?[C+(G==="L"?-1:1),X+(L==="T"?1:-1)]:[C+(G==="L"?-1:1),X]:zt(L)?[C+(L==="L"?1:-1),X+(G==="T"?1:-1)]:[C,X+(G==="T"?1:-1)]},"shiftPositionByArchitectureDirectionPair"),wr=at(function(C){return 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diff --git a/lightrag/api/webui/assets/blockDiagram-6J76NXCF-BoYLgByU.js b/lightrag/api/webui/assets/blockDiagram-6J76NXCF-Chfv6a7G.js
similarity index 99%
rename from lightrag/api/webui/assets/blockDiagram-6J76NXCF-BoYLgByU.js
rename to lightrag/api/webui/assets/blockDiagram-6J76NXCF-Chfv6a7G.js
index 8a691ecf..1420558c 100644
--- a/lightrag/api/webui/assets/blockDiagram-6J76NXCF-BoYLgByU.js
+++ b/lightrag/api/webui/assets/blockDiagram-6J76NXCF-Chfv6a7G.js
@@ -1,4 +1,4 @@
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diff --git a/lightrag/api/webui/assets/c4Diagram-6F6E4RAY-Ctk93Gt0.js b/lightrag/api/webui/assets/c4Diagram-6F6E4RAY-B4XUATl4.js
similarity index 99%
rename from lightrag/api/webui/assets/c4Diagram-6F6E4RAY-Ctk93Gt0.js
rename to lightrag/api/webui/assets/c4Diagram-6F6E4RAY-B4XUATl4.js
index f0f100c5..96ce8493 100644
--- a/lightrag/api/webui/assets/c4Diagram-6F6E4RAY-Ctk93Gt0.js
+++ b/lightrag/api/webui/assets/c4Diagram-6F6E4RAY-B4XUATl4.js
@@ -1,4 +1,4 @@
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N>"u"||!N.length||!N[0]){var Zt="";Yt=[];for(Nt in Dt[At])this.terminals_[Nt]&&Nt>we&&Yt.push("'"+this.terminals_[Nt]+"'");D.showPosition?Zt="Parse error on line "+(Et+1)+`:
 `+D.showPosition()+`
 Expecting `+Yt.join(", ")+", got '"+(this.terminals_[I]||I)+"'":Zt="Parse error on line "+(Et+1)+": Unexpected "+(I==ce?"end of input":"'"+(this.terminals_[I]||I)+"'"),this.parseError(Zt,{text:D.match,token:this.terminals_[I]||I,line:D.yylineno,loc:Kt,expected:Yt})}if(N[0]instanceof Array&&N.length>1)throw new Error("Parse Error: multiple actions possible at state: "+At+", token: "+I);switch(N[0]){case 1:v.push(I),R.push(D.yytext),h.push(D.yylloc),v.push(N[1]),I=null,oe=D.yyleng,p=D.yytext,Et=D.yylineno,Kt=D.yylloc;break;case 2:if(W=this.productions_[N[1]][1],wt.$=R[R.length-W],wt._$={first_line:h[h.length-(W||1)].first_line,last_line:h[h.length-1].last_line,first_column:h[h.length-(W||1)].first_column,last_column:h[h.length-1].last_column},Oe&&(wt._$.range=[h[h.length-(W||1)].range[0],h[h.length-1].range[1]]),Jt=this.performAction.apply(wt,[p,oe,Et,kt.yy,N[1],R,h].concat(Te)),typeof Jt<"u")return Jt;W&&(v=v.slice(0,-1*W*2),R=R.slice(0,-1*W),h=h.slice(0,-1*W)),v.push(this.productions_[N[1]][0]),R.push(wt.$),h.push(wt._$),ue=Dt[v[v.length-2]][v[v.length-1]],v.push(ue);break;case 3:return!0}}return!0},"parse")},Ce=function(){var _t={EOF:1,parseError:g(function(m,v){if(this.yy.parser)this.yy.parser.parseError(m,v);else throw new Error(m)},"parseError"),setInput:g(function(x,m){return this.yy=m||this.yy||{},this._input=x,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},"setInput"),input:g(function(){var x=this._input[0];this.yytext+=x,this.yyleng++,this.offset++,this.match+=x,this.matched+=x;var m=x.match(/(?:\r\n?|\n).*/g);return m?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),x},"input"),unput:g(function(x){var m=x.length,v=x.split(/(?:\r\n?|\n)/g);this._input=x+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-m),this.offset-=m;var b=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),v.length-1&&(this.yylineno-=v.length-1);var R=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:v?(v.length===b.length?this.yylloc.first_column:0)+b[b.length-v.length].length-v[0].length:this.yylloc.first_column-m},this.options.ranges&&(this.yylloc.range=[R[0],R[0]+this.yyleng-m]),this.yyleng=this.yytext.length,this},"unput"),more:g(function(){return this._more=!0,this},"more"),reject:g(function(){if(this.options.backtrack_lexer)this._backtrack=!0;else return this.parseError("Lexical error on line "+(this.yylineno+1)+`. You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).
 `+this.showPosition(),{text:"",token:null,line:this.yylineno});return this},"reject"),less:g(function(x){this.unput(this.match.slice(x))},"less"),pastInput:g(function(){var x=this.matched.substr(0,this.matched.length-this.match.length);return(x.length>20?"...":"")+x.substr(-20).replace(/\n/g,"")},"pastInput"),upcomingInput:g(function(){var x=this.match;return x.length<20&&(x+=this._input.substr(0,20-x.length)),(x.substr(0,20)+(x.length>20?"...":"")).replace(/\n/g,"")},"upcomingInput"),showPosition:g(function(){var x=this.pastInput(),m=new Array(x.length+1).join("-");return x+this.upcomingInput()+`
diff --git a/lightrag/api/webui/assets/chunk-353BL4L5-DAdaHWGH.js b/lightrag/api/webui/assets/chunk-353BL4L5-CR8qX5CO.js
similarity index 78%
rename from lightrag/api/webui/assets/chunk-353BL4L5-DAdaHWGH.js
rename to lightrag/api/webui/assets/chunk-353BL4L5-CR8qX5CO.js
index 38bcea2a..9518446c 100644
--- a/lightrag/api/webui/assets/chunk-353BL4L5-DAdaHWGH.js
+++ b/lightrag/api/webui/assets/chunk-353BL4L5-CR8qX5CO.js
@@ -1 +1 @@
-import{_ as l}from"./mermaid-vendor-CAxUo7Zk.js";function m(e,c){var i,t,o;e.accDescr&&((i=c.setAccDescription)==null||i.call(c,e.accDescr)),e.accTitle&&((t=c.setAccTitle)==null||t.call(c,e.accTitle)),e.title&&((o=c.setDiagramTitle)==null||o.call(c,e.title))}l(m,"populateCommonDb");export{m as p};
+import{_ as l}from"./mermaid-vendor-B20mDgAo.js";function m(e,c){var i,t,o;e.accDescr&&((i=c.setAccDescription)==null||i.call(c,e.accDescr)),e.accTitle&&((t=c.setAccTitle)==null||t.call(c,e.accTitle)),e.title&&((o=c.setDiagramTitle)==null||o.call(c,e.title))}l(m,"populateCommonDb");export{m as p};
diff --git a/lightrag/api/webui/assets/chunk-67H74DCK-CPez3pRp.js b/lightrag/api/webui/assets/chunk-67H74DCK-CIrK_RBz.js
similarity index 95%
rename from lightrag/api/webui/assets/chunk-67H74DCK-CPez3pRp.js
rename to lightrag/api/webui/assets/chunk-67H74DCK-CIrK_RBz.js
index 2e11d6a5..6b7f3651 100644
--- a/lightrag/api/webui/assets/chunk-67H74DCK-CPez3pRp.js
+++ b/lightrag/api/webui/assets/chunk-67H74DCK-CIrK_RBz.js
@@ -1 +1 @@
-import{_ as n,a2 as x,j as l}from"./mermaid-vendor-CAxUo7Zk.js";var c=n((a,t)=>{const e=a.append("rect");if(e.attr("x",t.x),e.attr("y",t.y),e.attr("fill",t.fill),e.attr("stroke",t.stroke),e.attr("width",t.width),e.attr("height",t.height),t.name&&e.attr("name",t.name),t.rx&&e.attr("rx",t.rx),t.ry&&e.attr("ry",t.ry),t.attrs!==void 0)for(const r in t.attrs)e.attr(r,t.attrs[r]);return t.class&&e.attr("class",t.class),e},"drawRect"),d=n((a,t)=>{const e={x:t.startx,y:t.starty,width:t.stopx-t.startx,height:t.stopy-t.starty,fill:t.fill,stroke:t.stroke,class:"rect"};c(a,e).lower()},"drawBackgroundRect"),g=n((a,t)=>{const e=t.text.replace(x," "),r=a.append("text");r.attr("x",t.x),r.attr("y",t.y),r.attr("class","legend"),r.style("text-anchor",t.anchor),t.class&&r.attr("class",t.class);const s=r.append("tspan");return s.attr("x",t.x+t.textMargin*2),s.text(e),r},"drawText"),h=n((a,t,e,r)=>{const s=a.append("image");s.attr("x",t),s.attr("y",e);const i=l.sanitizeUrl(r);s.attr("xlink:href",i)},"drawImage"),m=n((a,t,e,r)=>{const s=a.append("use");s.attr("x",t),s.attr("y",e);const i=l.sanitizeUrl(r);s.attr("xlink:href",`#${i}`)},"drawEmbeddedImage"),y=n(()=>({x:0,y:0,width:100,height:100,fill:"#EDF2AE",stroke:"#666",anchor:"start",rx:0,ry:0}),"getNoteRect"),p=n(()=>({x:0,y:0,width:100,height:100,"text-anchor":"start",style:"#666",textMargin:0,rx:0,ry:0,tspan:!0}),"getTextObj");export{d as a,p as b,m as c,c as d,h as e,g as f,y as g};
+import{_ as n,a2 as x,j as l}from"./mermaid-vendor-B20mDgAo.js";var c=n((a,t)=>{const e=a.append("rect");if(e.attr("x",t.x),e.attr("y",t.y),e.attr("fill",t.fill),e.attr("stroke",t.stroke),e.attr("width",t.width),e.attr("height",t.height),t.name&&e.attr("name",t.name),t.rx&&e.attr("rx",t.rx),t.ry&&e.attr("ry",t.ry),t.attrs!==void 0)for(const r in t.attrs)e.attr(r,t.attrs[r]);return t.class&&e.attr("class",t.class),e},"drawRect"),d=n((a,t)=>{const e={x:t.startx,y:t.starty,width:t.stopx-t.startx,height:t.stopy-t.starty,fill:t.fill,stroke:t.stroke,class:"rect"};c(a,e).lower()},"drawBackgroundRect"),g=n((a,t)=>{const e=t.text.replace(x," "),r=a.append("text");r.attr("x",t.x),r.attr("y",t.y),r.attr("class","legend"),r.style("text-anchor",t.anchor),t.class&&r.attr("class",t.class);const s=r.append("tspan");return s.attr("x",t.x+t.textMargin*2),s.text(e),r},"drawText"),h=n((a,t,e,r)=>{const s=a.append("image");s.attr("x",t),s.attr("y",e);const i=l.sanitizeUrl(r);s.attr("xlink:href",i)},"drawImage"),m=n((a,t,e,r)=>{const s=a.append("use");s.attr("x",t),s.attr("y",e);const i=l.sanitizeUrl(r);s.attr("xlink:href",`#${i}`)},"drawEmbeddedImage"),y=n(()=>({x:0,y:0,width:100,height:100,fill:"#EDF2AE",stroke:"#666",anchor:"start",rx:0,ry:0}),"getNoteRect"),p=n(()=>({x:0,y:0,width:100,height:100,"text-anchor":"start",style:"#666",textMargin:0,rx:0,ry:0,tspan:!0}),"getTextObj");export{d as a,p as b,m as c,c as d,h as e,g as f,y as g};
diff --git a/lightrag/api/webui/assets/chunk-AACKK3MU-CC5KzNO7.js b/lightrag/api/webui/assets/chunk-AACKK3MU-mRStUlsv.js
similarity index 67%
rename from lightrag/api/webui/assets/chunk-AACKK3MU-CC5KzNO7.js
rename to lightrag/api/webui/assets/chunk-AACKK3MU-mRStUlsv.js
index f3edf7d8..69921fc6 100644
--- a/lightrag/api/webui/assets/chunk-AACKK3MU-CC5KzNO7.js
+++ b/lightrag/api/webui/assets/chunk-AACKK3MU-mRStUlsv.js
@@ -1 +1 @@
-import{_ as s}from"./mermaid-vendor-CAxUo7Zk.js";var t,e=(t=class{constructor(i){this.init=i,this.records=this.init()}reset(){this.records=this.init()}},s(t,"ImperativeState"),t);export{e as I};
+import{_ as s}from"./mermaid-vendor-B20mDgAo.js";var t,e=(t=class{constructor(i){this.init=i,this.records=this.init()}reset(){this.records=this.init()}},s(t,"ImperativeState"),t);export{e as I};
diff --git a/lightrag/api/webui/assets/chunk-BFAMUDN2-DQGv_fhY.js b/lightrag/api/webui/assets/chunk-BFAMUDN2-Cm57CA8s.js
similarity index 72%
rename from lightrag/api/webui/assets/chunk-BFAMUDN2-DQGv_fhY.js
rename to lightrag/api/webui/assets/chunk-BFAMUDN2-Cm57CA8s.js
index 6b0ea83a..c7cd63f9 100644
--- a/lightrag/api/webui/assets/chunk-BFAMUDN2-DQGv_fhY.js
+++ b/lightrag/api/webui/assets/chunk-BFAMUDN2-Cm57CA8s.js
@@ -1 +1 @@
-import{_ as a,d as o}from"./mermaid-vendor-CAxUo7Zk.js";var d=a((t,e)=>{let n;return e==="sandbox"&&(n=o("#i"+t)),(e==="sandbox"?o(n.nodes()[0].contentDocument.body):o("body")).select(`[id="${t}"]`)},"getDiagramElement");export{d as g};
+import{_ as a,d as o}from"./mermaid-vendor-B20mDgAo.js";var d=a((t,e)=>{let n;return e==="sandbox"&&(n=o("#i"+t)),(e==="sandbox"?o(n.nodes()[0].contentDocument.body):o("body")).select(`[id="${t}"]`)},"getDiagramElement");export{d as g};
diff --git a/lightrag/api/webui/assets/chunk-E2GYISFI-DReIXiCg.js b/lightrag/api/webui/assets/chunk-E2GYISFI-Du9g7EeC.js
similarity index 82%
rename from lightrag/api/webui/assets/chunk-E2GYISFI-DReIXiCg.js
rename to lightrag/api/webui/assets/chunk-E2GYISFI-Du9g7EeC.js
index 5216d0bb..476be9d6 100644
--- a/lightrag/api/webui/assets/chunk-E2GYISFI-DReIXiCg.js
+++ b/lightrag/api/webui/assets/chunk-E2GYISFI-Du9g7EeC.js
@@ -1,4 +1,4 @@
-import{_ as e}from"./mermaid-vendor-CAxUo7Zk.js";var l=e(()=>`
+import{_ as e}from"./mermaid-vendor-B20mDgAo.js";var l=e(()=>`
   /* Font Awesome icon styling - consolidated */
   .label-icon {
     display: inline-block;
diff --git a/lightrag/api/webui/assets/chunk-OW32GOEJ-Bpuvralp.js b/lightrag/api/webui/assets/chunk-OW32GOEJ-C5pOkIhC.js
similarity index 99%
rename from lightrag/api/webui/assets/chunk-OW32GOEJ-Bpuvralp.js
rename to lightrag/api/webui/assets/chunk-OW32GOEJ-C5pOkIhC.js
index 483f33e3..9a6c0142 100644
--- a/lightrag/api/webui/assets/chunk-OW32GOEJ-Bpuvralp.js
+++ b/lightrag/api/webui/assets/chunk-OW32GOEJ-C5pOkIhC.js
@@ -1,4 +1,4 @@
-import{g as te}from"./chunk-BFAMUDN2-DQGv_fhY.js";import{s as ee}from"./chunk-SKB7J2MH-D-vU5iV6.js";import{_ as f,l as D,c as F,r as se,u as ie,a as re,b as ae,g as ne,s as le,q as oe,t as ce,a1 as he,k as z,z as ue}from"./mermaid-vendor-CAxUo7Zk.js";var vt=function(){var e=f(function(V,l,h,n){for(h=h||{},n=V.length;n--;h[V[n]]=l);return h},"o"),t=[1,2],s=[1,3],a=[1,4],i=[2,4],o=[1,9],d=[1,11],S=[1,16],p=[1,17],T=[1,18],_=[1,19],m=[1,33],k=[1,20],A=[1,21],$=[1,22],x=[1,23],R=[1,24],u=[1,26],L=[1,27],I=[1,28],N=[1,29],G=[1,30],P=[1,31],B=[1,32],at=[1,35],nt=[1,36],lt=[1,37],ot=[1,38],K=[1,34],y=[1,4,5,16,17,19,21,22,24,25,26,27,28,29,33,35,37,38,41,45,48,51,52,53,54,57],ct=[1,4,5,14,15,16,17,19,21,22,24,25,26,27,28,29,33,35,37,38,39,40,41,45,48,51,52,53,54,57],xt=[4,5,16,17,19,21,22,24,25,26,27,28,29,33,35,37,38,41,45,48,51,52,53,54,57],gt={trace:f(function(){},"trace"),yy:{},symbols_:{error:2,start:3,SPACE:4,NL:5,SD:6,document:7,line:8,statement:9,classDefStatement:10,styleStatement:11,cssClassStatement:12,idStatement:13,DESCR:14,"-->":15,HIDE_EMPTY:16,scale:17,WIDTH:18,COMPOSIT_STATE:19,STRUCT_START:20,STRUCT_STOP:21,STATE_DESCR:22,AS:23,ID:24,FORK:25,JOIN:26,CHOICE:27,CONCURRENT:28,note:29,notePosition:30,NOTE_TEXT:31,direction:32,acc_title:33,acc_title_value:34,acc_descr:35,acc_descr_value:36,acc_descr_multiline_value:37,CLICK:38,STRING:39,HREF:40,classDef:41,CLASSDEF_ID:42,CLASSDEF_STYLEOPTS:43,DEFAULT:44,style:45,STYLE_IDS:46,STYLEDEF_STYLEOPTS:47,class:48,CLASSENTITY_IDS:49,STYLECLASS:50,direction_tb:51,direction_bt:52,direction_rl:53,direction_lr:54,eol:55,";":56,EDGE_STATE:57,STYLE_SEPARATOR:58,left_of:59,right_of:60,$accept:0,$end:1},terminals_:{2:"error",4:"SPACE",5:"NL",6:"SD",14:"DESCR",15:"-->",16:"HIDE_EMPTY",17:"scale",18:"WIDTH",19:"COMPOSIT_STATE",20:"STRUCT_START",21:"STRUCT_STOP",22:"STATE_DESCR",23:"AS",24:"ID",25:"FORK",26:"JOIN",27:"CHOICE",28:"CONCURRENT",29:"note",31:"NOTE_TEXT",33:"acc_title",34:"acc_title_value",35:"acc_descr",36:"acc_descr_value",37:"acc_descr_multiline_value",38:"CLICK",39:"STRING",40:"HREF",41:"classDef",42:"CLASSDEF_ID",43:"CLASSDEF_STYLEOPTS",44:"DEFAULT",45:"style",46:"STYLE_IDS",47:"STYLEDEF_STYLEOPTS",48:"class",49:"CLASSENTITY_IDS",50:"STYLECLASS",51:"direction_tb",52:"direction_bt",53:"direction_rl",54:"direction_lr",56:";",57:"EDGE_STATE",58:"STYLE_SEPARATOR",59:"left_of",60:"right_of"},productions_:[0,[3,2],[3,2],[3,2],[7,0],[7,2],[8,2],[8,1],[8,1],[9,1],[9,1],[9,1],[9,1],[9,2],[9,3],[9,4],[9,1],[9,2],[9,1],[9,4],[9,3],[9,6],[9,1],[9,1],[9,1],[9,1],[9,4],[9,4],[9,1],[9,2],[9,2],[9,1],[9,5],[9,5],[10,3],[10,3],[11,3],[12,3],[32,1],[32,1],[32,1],[32,1],[55,1],[55,1],[13,1],[13,1],[13,3],[13,3],[30,1],[30,1]],performAction:f(function(l,h,n,g,E,r,Z){var c=r.length-1;switch(E){case 3:return g.setRootDoc(r[c]),r[c];case 4:this.$=[];break;case 5:r[c]!="nl"&&(r[c-1].push(r[c]),this.$=r[c-1]);break;case 6:case 7:this.$=r[c];break;case 8:this.$="nl";break;case 12:this.$=r[c];break;case 13:const tt=r[c-1];tt.description=g.trimColon(r[c]),this.$=tt;break;case 14:this.$={stmt:"relation",state1:r[c-2],state2:r[c]};break;case 15:const Tt=g.trimColon(r[c]);this.$={stmt:"relation",state1:r[c-3],state2:r[c-1],description:Tt};break;case 19:this.$={stmt:"state",id:r[c-3],type:"default",description:"",doc:r[c-1]};break;case 20:var U=r[c],X=r[c-2].trim();if(r[c].match(":")){var ut=r[c].split(":");U=ut[0],X=[X,ut[1]]}this.$={stmt:"state",id:U,type:"default",description:X};break;case 21:this.$={stmt:"state",id:r[c-3],type:"default",description:r[c-5],doc:r[c-1]};break;case 22:this.$={stmt:"state",id:r[c],type:"fork"};break;case 23:this.$={stmt:"state",id:r[c],type:"join"};break;case 24:this.$={stmt:"state",id:r[c],type:"choice"};break;case 25:this.$={stmt:"state",id:g.getDividerId(),type:"divider"};break;case 26:this.$={stmt:"state",id:r[c-1].trim(),note:{position:r[c-2].trim(),text:r[c].trim()}};break;case 29:this.$=r[c].trim(),g.setAccTitle(this.$);break;case 30:case 31:this.$=r[c].trim(),g.setAccDescription(this.$);break;case 32:this.$={stmt:"click",id:r[c-3],url:r[c-2],tooltip:r[c-1]};break;case 33:this.$={stmt:"click",id:r[c-3],url:r[c-1],tooltip:""};break;case 34:case 35:this.$={stmt:"classDef",id:r[c-1].trim(),classes:r[c].trim()};break;case 36:this.$={stmt:"style",id:r[c-1].trim(),styleClass:r[c].trim()};break;case 37:this.$={stmt:"applyClass",id:r[c-1].trim(),styleClass:r[c].trim()};break;case 38:g.setDirection("TB"),this.$={stmt:"dir",value:"TB"};break;case 39:g.setDirection("BT"),this.$={stmt:"dir",value:"BT"};break;case 40:g.setDirection("RL"),this.$={stmt:"dir",value:"RL"};break;case 41:g.setDirection("LR"),this.$={stmt:"dir",value:"LR"};break;case 44:case 45:this.$={stmt:"state",id:r[c].trim(),type:"default",description:""};break;case 46:this.$={stmt:"state",id:r[c-2].trim(),classes:[r[c].trim()],type:"default",description:""};break;case 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diff --git a/lightrag/api/webui/assets/chunk-SKB7J2MH-D-vU5iV6.js b/lightrag/api/webui/assets/chunk-SKB7J2MH-CX-6qXaF.js
similarity index 88%
rename from lightrag/api/webui/assets/chunk-SKB7J2MH-D-vU5iV6.js
rename to lightrag/api/webui/assets/chunk-SKB7J2MH-CX-6qXaF.js
index fb99a75f..85fa91a0 100644
--- a/lightrag/api/webui/assets/chunk-SKB7J2MH-D-vU5iV6.js
+++ b/lightrag/api/webui/assets/chunk-SKB7J2MH-CX-6qXaF.js
@@ -1 +1 @@
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+import{_ as a,e as w,l as x}from"./mermaid-vendor-B20mDgAo.js";var d=a((e,t,i,o)=>{e.attr("class",i);const{width:r,height:h,x:n,y:c}=u(e,t);w(e,h,r,o);const s=l(n,c,r,h,t);e.attr("viewBox",s),x.debug(`viewBox configured: ${s} with padding: ${t}`)},"setupViewPortForSVG"),u=a((e,t)=>{var o;const i=((o=e.node())==null?void 0:o.getBBox())||{width:0,height:0,x:0,y:0};return{width:i.width+t*2,height:i.height+t*2,x:i.x,y:i.y}},"calculateDimensionsWithPadding"),l=a((e,t,i,o,r)=>`${e-r} ${t-r} ${i} ${o}`,"createViewBox");export{d as s};
diff --git a/lightrag/api/webui/assets/chunk-SZ463SBG-9GI7VVtw.js b/lightrag/api/webui/assets/chunk-SZ463SBG-B3Q_dfR2.js
similarity index 99%
rename from lightrag/api/webui/assets/chunk-SZ463SBG-9GI7VVtw.js
rename to lightrag/api/webui/assets/chunk-SZ463SBG-B3Q_dfR2.js
index 61ccf534..a7b490ec 100644
--- a/lightrag/api/webui/assets/chunk-SZ463SBG-9GI7VVtw.js
+++ b/lightrag/api/webui/assets/chunk-SZ463SBG-B3Q_dfR2.js
@@ -1,4 +1,4 @@
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diff --git a/lightrag/api/webui/assets/classDiagram-M3E45YP4-CPlkaPl7.js b/lightrag/api/webui/assets/classDiagram-M3E45YP4-CPlkaPl7.js
deleted file mode 100644
index 4f641eb3..00000000
--- a/lightrag/api/webui/assets/classDiagram-M3E45YP4-CPlkaPl7.js
+++ /dev/null
@@ -1 +0,0 @@
-import{s as a,c as s,a as e,C as t}from"./chunk-SZ463SBG-9GI7VVtw.js";import{_ as i}from"./mermaid-vendor-CAxUo7Zk.js";import"./chunk-E2GYISFI-DReIXiCg.js";import"./chunk-BFAMUDN2-DQGv_fhY.js";import"./chunk-SKB7J2MH-D-vU5iV6.js";import"./feature-graph-C6IuADHZ.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var c={parser:e,get db(){return new t},renderer:s,styles:a,init:i(r=>{r.class||(r.class={}),r.class.arrowMarkerAbsolute=r.arrowMarkerAbsolute},"init")};export{c as diagram};
diff --git a/lightrag/api/webui/assets/classDiagram-M3E45YP4-DKtAiWMM.js b/lightrag/api/webui/assets/classDiagram-M3E45YP4-DKtAiWMM.js
new file mode 100644
index 00000000..6e4c95aa
--- /dev/null
+++ b/lightrag/api/webui/assets/classDiagram-M3E45YP4-DKtAiWMM.js
@@ -0,0 +1 @@
+import{s as a,c as s,a as e,C as t}from"./chunk-SZ463SBG-B3Q_dfR2.js";import{_ as i}from"./mermaid-vendor-B20mDgAo.js";import"./chunk-E2GYISFI-Du9g7EeC.js";import"./chunk-BFAMUDN2-Cm57CA8s.js";import"./chunk-SKB7J2MH-CX-6qXaF.js";import"./feature-graph-CS4MyqEv.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var c={parser:e,get db(){return new t},renderer:s,styles:a,init:i(r=>{r.class||(r.class={}),r.class.arrowMarkerAbsolute=r.arrowMarkerAbsolute},"init")};export{c as diagram};
diff --git a/lightrag/api/webui/assets/classDiagram-v2-YAWTLIQI-CPlkaPl7.js b/lightrag/api/webui/assets/classDiagram-v2-YAWTLIQI-CPlkaPl7.js
deleted file mode 100644
index 4f641eb3..00000000
--- a/lightrag/api/webui/assets/classDiagram-v2-YAWTLIQI-CPlkaPl7.js
+++ /dev/null
@@ -1 +0,0 @@
-import{s as a,c as s,a as e,C as t}from"./chunk-SZ463SBG-9GI7VVtw.js";import{_ as i}from"./mermaid-vendor-CAxUo7Zk.js";import"./chunk-E2GYISFI-DReIXiCg.js";import"./chunk-BFAMUDN2-DQGv_fhY.js";import"./chunk-SKB7J2MH-D-vU5iV6.js";import"./feature-graph-C6IuADHZ.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var c={parser:e,get db(){return new t},renderer:s,styles:a,init:i(r=>{r.class||(r.class={}),r.class.arrowMarkerAbsolute=r.arrowMarkerAbsolute},"init")};export{c as diagram};
diff --git a/lightrag/api/webui/assets/classDiagram-v2-YAWTLIQI-DKtAiWMM.js b/lightrag/api/webui/assets/classDiagram-v2-YAWTLIQI-DKtAiWMM.js
new file mode 100644
index 00000000..6e4c95aa
--- /dev/null
+++ b/lightrag/api/webui/assets/classDiagram-v2-YAWTLIQI-DKtAiWMM.js
@@ -0,0 +1 @@
+import{s as a,c as s,a as e,C as t}from"./chunk-SZ463SBG-B3Q_dfR2.js";import{_ as i}from"./mermaid-vendor-B20mDgAo.js";import"./chunk-E2GYISFI-Du9g7EeC.js";import"./chunk-BFAMUDN2-Cm57CA8s.js";import"./chunk-SKB7J2MH-CX-6qXaF.js";import"./feature-graph-CS4MyqEv.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var c={parser:e,get db(){return new t},renderer:s,styles:a,init:i(r=>{r.class||(r.class={}),r.class.arrowMarkerAbsolute=r.arrowMarkerAbsolute},"init")};export{c as diagram};
diff --git a/lightrag/api/webui/assets/clone-D1fuhfq3.js b/lightrag/api/webui/assets/clone-D1fuhfq3.js
new file mode 100644
index 00000000..eba5a391
--- /dev/null
+++ b/lightrag/api/webui/assets/clone-D1fuhfq3.js
@@ -0,0 +1 @@
+import{b as r}from"./_baseUniq-Coqzfado.js";var e=4;function a(o){return r(o,e)}export{a as c};
diff --git a/lightrag/api/webui/assets/clone-D60V_qjf.js b/lightrag/api/webui/assets/clone-D60V_qjf.js
deleted file mode 100644
index 495fe6b3..00000000
--- a/lightrag/api/webui/assets/clone-D60V_qjf.js
+++ /dev/null
@@ -1 +0,0 @@
-import{b as r}from"./_baseUniq-BrMEyGA7.js";var e=4;function a(o){return r(o,e)}export{a as c};
diff --git a/lightrag/api/webui/assets/dagre-JOIXM2OF-_PkH7lBL.js b/lightrag/api/webui/assets/dagre-JOIXM2OF-B1CqCeXy.js
similarity index 97%
rename from lightrag/api/webui/assets/dagre-JOIXM2OF-_PkH7lBL.js
rename to lightrag/api/webui/assets/dagre-JOIXM2OF-B1CqCeXy.js
index a0bfefdb..21fccf66 100644
--- a/lightrag/api/webui/assets/dagre-JOIXM2OF-_PkH7lBL.js
+++ b/lightrag/api/webui/assets/dagre-JOIXM2OF-B1CqCeXy.js
@@ -1,4 +1,4 @@
-import{_ as p,an as F,ao as Y,ap as _,aq as H,l as i,c as V,ar as q,as as U,a9 as $,ae as z,aa as P,a8 as K,at as Q,au as W,av as Z}from"./mermaid-vendor-CAxUo7Zk.js";import{G as B}from"./graph-dt4A1Xns.js";import{l as I}from"./layout-Bs3ntXjW.js";import{i as x}from"./_baseUniq-BrMEyGA7.js";import{c as L}from"./clone-D60V_qjf.js";import{m as A}from"./_basePickBy-BEWgwF1U.js";import"./feature-graph-C6IuADHZ.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";function E(e){var t={options:{directed:e.isDirected(),multigraph:e.isMultigraph(),compound:e.isCompound()},nodes:ee(e),edges:ne(e)};return x(e.graph())||(t.value=L(e.graph())),t}function ee(e){return A(e.nodes(),function(t){var n=e.node(t),o=e.parent(t),c={v:t};return x(n)||(c.value=n),x(o)||(c.parent=o),c})}function ne(e){return A(e.edges(),function(t){var n=e.edge(t),o={v:t.v,w:t.w};return x(t.name)||(o.name=t.name),x(n)||(o.value=n),o})}var f=new Map,b=new Map,J=new Map,te=p(()=>{b.clear(),J.clear(),f.clear()},"clear"),O=p((e,t)=>{const n=b.get(t)||[];return i.trace("In isDescendant",t," ",e," = ",n.includes(e)),n.includes(e)},"isDescendant"),se=p((e,t)=>{const n=b.get(t)||[];return i.info("Descendants of ",t," is ",n),i.info("Edge is ",e),e.v===t||e.w===t?!1:n?n.includes(e.v)||O(e.v,t)||O(e.w,t)||n.includes(e.w):(i.debug("Tilt, ",t,",not in descendants"),!1)},"edgeInCluster"),G=p((e,t,n,o)=>{i.warn("Copying children of ",e,"root",o,"data",t.node(e),o);const c=t.children(e)||[];e!==o&&c.push(e),i.warn("Copying (nodes) clusterId",e,"nodes",c),c.forEach(a=>{if(t.children(a).length>0)G(a,t,n,o);else{const r=t.node(a);i.info("cp ",a," to ",o," with parent ",e),n.setNode(a,r),o!==t.parent(a)&&(i.warn("Setting parent",a,t.parent(a)),n.setParent(a,t.parent(a))),e!==o&&a!==e?(i.debug("Setting parent",a,e),n.setParent(a,e)):(i.info("In copy ",e,"root",o,"data",t.node(e),o),i.debug("Not Setting parent for node=",a,"cluster!==rootId",e!==o,"node!==clusterId",a!==e));const u=t.edges(a);i.debug("Copying Edges",u),u.forEach(l=>{i.info("Edge",l);const v=t.edge(l.v,l.w,l.name);i.info("Edge data",v,o);try{se(l,o)?(i.info("Copying as ",l.v,l.w,v,l.name),n.setEdge(l.v,l.w,v,l.name),i.info("newGraph edges ",n.edges(),n.edge(n.edges()[0]))):i.info("Skipping copy of edge ",l.v,"-->",l.w," rootId: ",o," clusterId:",e)}catch(C){i.error(C)}})}i.debug("Removing node",a),t.removeNode(a)})},"copy"),R=p((e,t)=>{const n=t.children(e);let o=[...n];for(const c of n)J.set(c,e),o=[...o,...R(c,t)];return o},"extractDescendants"),ie=p((e,t,n)=>{const o=e.edges().filter(l=>l.v===t||l.w===t),c=e.edges().filter(l=>l.v===n||l.w===n),a=o.map(l=>({v:l.v===t?n:l.v,w:l.w===t?t:l.w})),r=c.map(l=>({v:l.v,w:l.w}));return a.filter(l=>r.some(v=>l.v===v.v&&l.w===v.w))},"findCommonEdges"),D=p((e,t,n)=>{const o=t.children(e);if(i.trace("Searching children of id ",e,o),o.length<1)return e;let c;for(const a of o){const r=D(a,t,n),u=ie(t,n,r);if(r)if(u.length>0)c=r;else return r}return c},"findNonClusterChild"),k=p(e=>!f.has(e)||!f.get(e).externalConnections?e:f.has(e)?f.get(e).id:e,"getAnchorId"),re=p((e,t)=>{if(!e||t>10){i.debug("Opting out, no graph ");return}else i.debug("Opting in, graph ");e.nodes().forEach(function(n){e.children(n).length>0&&(i.warn("Cluster identified",n," Replacement id in edges: ",D(n,e,n)),b.set(n,R(n,e)),f.set(n,{id:D(n,e,n),clusterData:e.node(n)}))}),e.nodes().forEach(function(n){const o=e.children(n),c=e.edges();o.length>0?(i.debug("Cluster identified",n,b),c.forEach(a=>{const r=O(a.v,n),u=O(a.w,n);r^u&&(i.warn("Edge: ",a," leaves cluster ",n),i.warn("Descendants of XXX ",n,": ",b.get(n)),f.get(n).externalConnections=!0)})):i.debug("Not a cluster ",n,b)});for(let n of f.keys()){const o=f.get(n).id,c=e.parent(o);c!==n&&f.has(c)&&!f.get(c).externalConnections&&(f.get(n).id=c)}e.edges().forEach(function(n){const o=e.edge(n);i.warn("Edge "+n.v+" -> "+n.w+": "+JSON.stringify(n)),i.warn("Edge "+n.v+" -> "+n.w+": "+JSON.stringify(e.edge(n)));let c=n.v,a=n.w;if(i.warn("Fix XXX",f,"ids:",n.v,n.w,"Translating: ",f.get(n.v)," --- ",f.get(n.w)),f.get(n.v)||f.get(n.w)){if(i.warn("Fixing and trying - removing XXX",n.v,n.w,n.name),c=k(n.v),a=k(n.w),e.removeEdge(n.v,n.w,n.name),c!==n.v){const r=e.parent(c);f.get(r).externalConnections=!0,o.fromCluster=n.v}if(a!==n.w){const r=e.parent(a);f.get(r).externalConnections=!0,o.toCluster=n.w}i.warn("Fix Replacing with XXX",c,a,n.name),e.setEdge(c,a,o,n.name)}}),i.warn("Adjusted Graph",E(e)),T(e,0),i.trace(f)},"adjustClustersAndEdges"),T=p((e,t)=>{var c,a;if(i.warn("extractor - ",t,E(e),e.children("D")),t>10){i.error("Bailing out");return}let n=e.nodes(),o=!1;for(const r of n){const u=e.children(r);o=o||u.length>0}if(!o){i.debug("Done, no node has children",e.nodes());return}i.debug("Nodes = ",n,t);for(const r of n)if(i.debug("Extracting node",r,f,f.has(r)&&!f.get(r).externalConnections,!e.parent(r),e.node(r),e.children("D")," Depth ",t),!f.has(r))i.debug("Not a cluster",r,t);else if(!f.get(r).externalConnections&&e.children(r)&&e.children(r).length>0){i.warn("Cluster without external connections, without a parent and with children",r,t);let l=e.graph().rankdir==="TB"?"LR":"TB";(a=(c=f.get(r))==null?void 0:c.clusterData)!=null&&a.dir&&(l=f.get(r).clusterData.dir,i.warn("Fixing dir",f.get(r).clusterData.dir,l));const v=new B({multigraph:!0,compound:!0}).setGraph({rankdir:l,nodesep:50,ranksep:50,marginx:8,marginy:8}).setDefaultEdgeLabel(function(){return{}});i.warn("Old graph before copy",E(e)),G(r,e,v,r),e.setNode(r,{clusterNode:!0,id:r,clusterData:f.get(r).clusterData,label:f.get(r).label,graph:v}),i.warn("New graph after copy node: (",r,")",E(v)),i.debug("Old graph after copy",E(e))}else i.warn("Cluster ** ",r," **not meeting the criteria !externalConnections:",!f.get(r).externalConnections," no parent: ",!e.parent(r)," children ",e.children(r)&&e.children(r).length>0,e.children("D"),t),i.debug(f);n=e.nodes(),i.warn("New list of nodes",n);for(const r of n){const u=e.node(r);i.warn(" Now next level",r,u),u!=null&&u.clusterNode&&T(u.graph,t+1)}},"extractor"),M=p((e,t)=>{if(t.length===0)return[];let n=Object.assign([],t);return t.forEach(o=>{const c=e.children(o),a=M(e,c);n=[...n,...a]}),n},"sorter"),oe=p(e=>M(e,e.children()),"sortNodesByHierarchy"),j=p(async(e,t,n,o,c,a)=>{i.warn("Graph in recursive render:XAX",E(t),c);const r=t.graph().rankdir;i.trace("Dir in recursive render - dir:",r);const u=e.insert("g").attr("class","root");t.nodes()?i.info("Recursive render XXX",t.nodes()):i.info("No nodes found for",t),t.edges().length>0&&i.info("Recursive edges",t.edge(t.edges()[0]));const l=u.insert("g").attr("class","clusters"),v=u.insert("g").attr("class","edgePaths"),C=u.insert("g").attr("class","edgeLabels"),g=u.insert("g").attr("class","nodes");await Promise.all(t.nodes().map(async function(d){const s=t.node(d);if(c!==void 0){const w=JSON.parse(JSON.stringify(c.clusterData));i.trace(`Setting data for parent cluster XXX
+import{_ as p,an as F,ao as Y,ap as _,aq as H,l as i,c as V,ar as q,as as U,a9 as $,ae as z,aa as P,a8 as K,at as Q,au as W,av as Z}from"./mermaid-vendor-B20mDgAo.js";import{G as B}from"./graph-lXMBdjQ3.js";import{l as I}from"./layout-BWO25eL4.js";import{i as x}from"./_baseUniq-Coqzfado.js";import{c as L}from"./clone-D1fuhfq3.js";import{m as A}from"./_basePickBy-zcTWmF8I.js";import"./feature-graph-CS4MyqEv.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";function E(e){var t={options:{directed:e.isDirected(),multigraph:e.isMultigraph(),compound:e.isCompound()},nodes:ee(e),edges:ne(e)};return x(e.graph())||(t.value=L(e.graph())),t}function ee(e){return A(e.nodes(),function(t){var n=e.node(t),o=e.parent(t),c={v:t};return x(n)||(c.value=n),x(o)||(c.parent=o),c})}function ne(e){return A(e.edges(),function(t){var n=e.edge(t),o={v:t.v,w:t.w};return x(t.name)||(o.name=t.name),x(n)||(o.value=n),o})}var f=new Map,b=new Map,J=new Map,te=p(()=>{b.clear(),J.clear(),f.clear()},"clear"),O=p((e,t)=>{const n=b.get(t)||[];return i.trace("In isDescendant",t," ",e," = ",n.includes(e)),n.includes(e)},"isDescendant"),se=p((e,t)=>{const n=b.get(t)||[];return i.info("Descendants of ",t," is ",n),i.info("Edge is ",e),e.v===t||e.w===t?!1:n?n.includes(e.v)||O(e.v,t)||O(e.w,t)||n.includes(e.w):(i.debug("Tilt, ",t,",not in descendants"),!1)},"edgeInCluster"),G=p((e,t,n,o)=>{i.warn("Copying children of ",e,"root",o,"data",t.node(e),o);const c=t.children(e)||[];e!==o&&c.push(e),i.warn("Copying (nodes) clusterId",e,"nodes",c),c.forEach(a=>{if(t.children(a).length>0)G(a,t,n,o);else{const r=t.node(a);i.info("cp ",a," to ",o," with parent ",e),n.setNode(a,r),o!==t.parent(a)&&(i.warn("Setting parent",a,t.parent(a)),n.setParent(a,t.parent(a))),e!==o&&a!==e?(i.debug("Setting parent",a,e),n.setParent(a,e)):(i.info("In copy ",e,"root",o,"data",t.node(e),o),i.debug("Not Setting parent for node=",a,"cluster!==rootId",e!==o,"node!==clusterId",a!==e));const u=t.edges(a);i.debug("Copying Edges",u),u.forEach(l=>{i.info("Edge",l);const v=t.edge(l.v,l.w,l.name);i.info("Edge data",v,o);try{se(l,o)?(i.info("Copying as ",l.v,l.w,v,l.name),n.setEdge(l.v,l.w,v,l.name),i.info("newGraph edges ",n.edges(),n.edge(n.edges()[0]))):i.info("Skipping copy of edge ",l.v,"-->",l.w," rootId: ",o," clusterId:",e)}catch(C){i.error(C)}})}i.debug("Removing node",a),t.removeNode(a)})},"copy"),R=p((e,t)=>{const n=t.children(e);let o=[...n];for(const c of n)J.set(c,e),o=[...o,...R(c,t)];return o},"extractDescendants"),ie=p((e,t,n)=>{const o=e.edges().filter(l=>l.v===t||l.w===t),c=e.edges().filter(l=>l.v===n||l.w===n),a=o.map(l=>({v:l.v===t?n:l.v,w:l.w===t?t:l.w})),r=c.map(l=>({v:l.v,w:l.w}));return a.filter(l=>r.some(v=>l.v===v.v&&l.w===v.w))},"findCommonEdges"),D=p((e,t,n)=>{const o=t.children(e);if(i.trace("Searching children of id ",e,o),o.length<1)return e;let c;for(const a of o){const r=D(a,t,n),u=ie(t,n,r);if(r)if(u.length>0)c=r;else return r}return c},"findNonClusterChild"),k=p(e=>!f.has(e)||!f.get(e).externalConnections?e:f.has(e)?f.get(e).id:e,"getAnchorId"),re=p((e,t)=>{if(!e||t>10){i.debug("Opting out, no graph ");return}else i.debug("Opting in, graph ");e.nodes().forEach(function(n){e.children(n).length>0&&(i.warn("Cluster identified",n," Replacement id in edges: ",D(n,e,n)),b.set(n,R(n,e)),f.set(n,{id:D(n,e,n),clusterData:e.node(n)}))}),e.nodes().forEach(function(n){const o=e.children(n),c=e.edges();o.length>0?(i.debug("Cluster identified",n,b),c.forEach(a=>{const r=O(a.v,n),u=O(a.w,n);r^u&&(i.warn("Edge: ",a," leaves cluster ",n),i.warn("Descendants of XXX ",n,": ",b.get(n)),f.get(n).externalConnections=!0)})):i.debug("Not a cluster ",n,b)});for(let n of f.keys()){const o=f.get(n).id,c=e.parent(o);c!==n&&f.has(c)&&!f.get(c).externalConnections&&(f.get(n).id=c)}e.edges().forEach(function(n){const o=e.edge(n);i.warn("Edge "+n.v+" -> "+n.w+": "+JSON.stringify(n)),i.warn("Edge "+n.v+" -> "+n.w+": "+JSON.stringify(e.edge(n)));let c=n.v,a=n.w;if(i.warn("Fix XXX",f,"ids:",n.v,n.w,"Translating: ",f.get(n.v)," --- ",f.get(n.w)),f.get(n.v)||f.get(n.w)){if(i.warn("Fixing and trying - removing XXX",n.v,n.w,n.name),c=k(n.v),a=k(n.w),e.removeEdge(n.v,n.w,n.name),c!==n.v){const r=e.parent(c);f.get(r).externalConnections=!0,o.fromCluster=n.v}if(a!==n.w){const r=e.parent(a);f.get(r).externalConnections=!0,o.toCluster=n.w}i.warn("Fix Replacing with XXX",c,a,n.name),e.setEdge(c,a,o,n.name)}}),i.warn("Adjusted Graph",E(e)),T(e,0),i.trace(f)},"adjustClustersAndEdges"),T=p((e,t)=>{var c,a;if(i.warn("extractor - ",t,E(e),e.children("D")),t>10){i.error("Bailing out");return}let n=e.nodes(),o=!1;for(const r of n){const u=e.children(r);o=o||u.length>0}if(!o){i.debug("Done, no node has children",e.nodes());return}i.debug("Nodes = ",n,t);for(const r of n)if(i.debug("Extracting node",r,f,f.has(r)&&!f.get(r).externalConnections,!e.parent(r),e.node(r),e.children("D")," Depth ",t),!f.has(r))i.debug("Not a cluster",r,t);else if(!f.get(r).externalConnections&&e.children(r)&&e.children(r).length>0){i.warn("Cluster without external connections, without a parent and with children",r,t);let l=e.graph().rankdir==="TB"?"LR":"TB";(a=(c=f.get(r))==null?void 0:c.clusterData)!=null&&a.dir&&(l=f.get(r).clusterData.dir,i.warn("Fixing dir",f.get(r).clusterData.dir,l));const v=new B({multigraph:!0,compound:!0}).setGraph({rankdir:l,nodesep:50,ranksep:50,marginx:8,marginy:8}).setDefaultEdgeLabel(function(){return{}});i.warn("Old graph before copy",E(e)),G(r,e,v,r),e.setNode(r,{clusterNode:!0,id:r,clusterData:f.get(r).clusterData,label:f.get(r).label,graph:v}),i.warn("New graph after copy node: (",r,")",E(v)),i.debug("Old graph after copy",E(e))}else i.warn("Cluster ** ",r," **not meeting the criteria !externalConnections:",!f.get(r).externalConnections," no parent: ",!e.parent(r)," children ",e.children(r)&&e.children(r).length>0,e.children("D"),t),i.debug(f);n=e.nodes(),i.warn("New list of nodes",n);for(const r of n){const u=e.node(r);i.warn(" Now next level",r,u),u!=null&&u.clusterNode&&T(u.graph,t+1)}},"extractor"),M=p((e,t)=>{if(t.length===0)return[];let n=Object.assign([],t);return t.forEach(o=>{const c=e.children(o),a=M(e,c);n=[...n,...a]}),n},"sorter"),oe=p(e=>M(e,e.children()),"sortNodesByHierarchy"),j=p(async(e,t,n,o,c,a)=>{i.warn("Graph in recursive render:XAX",E(t),c);const r=t.graph().rankdir;i.trace("Dir in recursive render - dir:",r);const u=e.insert("g").attr("class","root");t.nodes()?i.info("Recursive render XXX",t.nodes()):i.info("No nodes found for",t),t.edges().length>0&&i.info("Recursive edges",t.edge(t.edges()[0]));const l=u.insert("g").attr("class","clusters"),v=u.insert("g").attr("class","edgePaths"),C=u.insert("g").attr("class","edgeLabels"),g=u.insert("g").attr("class","nodes");await Promise.all(t.nodes().map(async function(d){const s=t.node(d);if(c!==void 0){const w=JSON.parse(JSON.stringify(c.clusterData));i.trace(`Setting data for parent cluster XXX
  Node.id = `,d,`
  data=`,w.height,`
 Parent cluster`,c.height),t.setNode(c.id,w),t.parent(d)||(i.trace("Setting parent",d,c.id),t.setParent(d,c.id,w))}if(i.info("(Insert) Node XXX"+d+": "+JSON.stringify(t.node(d))),s!=null&&s.clusterNode){i.info("Cluster identified XBX",d,s.width,t.node(d));const{ranksep:w,nodesep:m}=t.graph();s.graph.setGraph({...s.graph.graph(),ranksep:w+25,nodesep:m});const N=await j(g,s.graph,n,o,t.node(d),a),S=N.elem;q(s,S),s.diff=N.diff||0,i.info("New compound node after recursive render XAX",d,"width",s.width,"height",s.height),U(S,s)}else t.children(d).length>0?(i.trace("Cluster - the non recursive path XBX",d,s.id,s,s.width,"Graph:",t),i.trace(D(s.id,t)),f.set(s.id,{id:D(s.id,t),node:s})):(i.trace("Node - the non recursive path XAX",d,g,t.node(d),r),await $(g,t.node(d),{config:a,dir:r}))})),await p(async()=>{const d=t.edges().map(async function(s){const w=t.edge(s.v,s.w,s.name);i.info("Edge "+s.v+" -> "+s.w+": "+JSON.stringify(s)),i.info("Edge "+s.v+" -> "+s.w+": ",s," ",JSON.stringify(t.edge(s))),i.info("Fix",f,"ids:",s.v,s.w,"Translating: ",f.get(s.v),f.get(s.w)),await Z(C,w)});await Promise.all(d)},"processEdges")(),i.info("Graph before layout:",JSON.stringify(E(t))),i.info("############################################# XXX"),i.info("###                Layout                 ### XXX"),i.info("############################################# XXX"),I(t),i.info("Graph after layout:",JSON.stringify(E(t)));let y=0,{subGraphTitleTotalMargin:X}=z(a);return await Promise.all(oe(t).map(async function(d){var w;const s=t.node(d);if(i.info("Position XBX => "+d+": ("+s.x,","+s.y,") width: ",s.width," height: ",s.height),s!=null&&s.clusterNode)s.y+=X,i.info("A tainted cluster node XBX1",d,s.id,s.width,s.height,s.x,s.y,t.parent(d)),f.get(s.id).node=s,P(s);else if(t.children(d).length>0){i.info("A pure cluster node XBX1",d,s.id,s.x,s.y,s.width,s.height,t.parent(d)),s.height+=X,t.node(s.parentId);const m=(s==null?void 0:s.padding)/2||0,N=((w=s==null?void 0:s.labelBBox)==null?void 0:w.height)||0,S=N-m||0;i.debug("OffsetY",S,"labelHeight",N,"halfPadding",m),await K(l,s),f.get(s.id).node=s}else{const m=t.node(s.parentId);s.y+=X/2,i.info("A regular node XBX1 - using the padding",s.id,"parent",s.parentId,s.width,s.height,s.x,s.y,"offsetY",s.offsetY,"parent",m,m==null?void 0:m.offsetY,s),P(s)}})),t.edges().forEach(function(d){const s=t.edge(d);i.info("Edge "+d.v+" -> "+d.w+": "+JSON.stringify(s),s),s.points.forEach(S=>S.y+=X/2);const w=t.node(d.v);var m=t.node(d.w);const N=Q(v,s,f,n,w,m,o);W(s,N)}),t.nodes().forEach(function(d){const s=t.node(d);i.info(d,s.type,s.diff),s.isGroup&&(y=s.diff)}),i.warn("Returning from recursive render XAX",u,y),{elem:u,diff:y}},"recursiveRender"),pe=p(async(e,t)=>{var a,r,u,l,v,C;const n=new B({multigraph:!0,compound:!0}).setGraph({rankdir:e.direction,nodesep:((a=e.config)==null?void 0:a.nodeSpacing)||((u=(r=e.config)==null?void 0:r.flowchart)==null?void 0:u.nodeSpacing)||e.nodeSpacing,ranksep:((l=e.config)==null?void 0:l.rankSpacing)||((C=(v=e.config)==null?void 0:v.flowchart)==null?void 0:C.rankSpacing)||e.rankSpacing,marginx:8,marginy:8}).setDefaultEdgeLabel(function(){return{}}),o=t.select("g");F(o,e.markers,e.type,e.diagramId),Y(),_(),H(),te(),e.nodes.forEach(g=>{n.setNode(g.id,{...g}),g.parentId&&n.setParent(g.id,g.parentId)}),i.debug("Edges:",e.edges),e.edges.forEach(g=>{if(g.start===g.end){const h=g.start,y=h+"---"+h+"---1",X=h+"---"+h+"---2",d=n.node(h);n.setNode(y,{domId:y,id:y,parentId:d.parentId,labelStyle:"",label:"",padding:0,shape:"labelRect",style:"",width:10,height:10}),n.setParent(y,d.parentId),n.setNode(X,{domId:X,id:X,parentId:d.parentId,labelStyle:"",padding:0,shape:"labelRect",label:"",style:"",width:10,height:10}),n.setParent(X,d.parentId);const s=structuredClone(g),w=structuredClone(g),m=structuredClone(g);s.label="",s.arrowTypeEnd="none",s.id=h+"-cyclic-special-1",w.arrowTypeStart="none",w.arrowTypeEnd="none",w.id=h+"-cyclic-special-mid",m.label="",d.isGroup&&(s.fromCluster=h,m.toCluster=h),m.id=h+"-cyclic-special-2",m.arrowTypeStart="none",n.setEdge(h,y,s,h+"-cyclic-special-0"),n.setEdge(y,X,w,h+"-cyclic-special-1"),n.setEdge(X,h,m,h+"-cyc<lic-special-2")}else n.setEdge(g.start,g.end,{...g},g.id)}),i.warn("Graph at first:",JSON.stringify(E(n))),re(n),i.warn("Graph after XAX:",JSON.stringify(E(n)));const c=V();await j(o,n,e.type,e.diagramId,void 0,c)},"render");export{pe as render};
diff --git a/lightrag/api/webui/assets/diagram-5UYTHUR4-CRU4nlUp.js b/lightrag/api/webui/assets/diagram-5UYTHUR4-Bq7e4V0K.js
similarity index 90%
rename from lightrag/api/webui/assets/diagram-5UYTHUR4-CRU4nlUp.js
rename to lightrag/api/webui/assets/diagram-5UYTHUR4-Bq7e4V0K.js
index 17bca2a1..6a12b980 100644
--- a/lightrag/api/webui/assets/diagram-5UYTHUR4-CRU4nlUp.js
+++ b/lightrag/api/webui/assets/diagram-5UYTHUR4-Bq7e4V0K.js
@@ -1,4 +1,4 @@
-import{p as y}from"./chunk-353BL4L5-DAdaHWGH.js";import{_ as l,s as B,g as S,t as z,q as F,a as P,b as E,F as v,K as W,e as T,z as D,G as _,H as A,l as w}from"./mermaid-vendor-CAxUo7Zk.js";import{p as N}from"./treemap-75Q7IDZK-BAguqzAo.js";import"./feature-graph-C6IuADHZ.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";import"./_baseUniq-BrMEyGA7.js";import"./_basePickBy-BEWgwF1U.js";import"./clone-D60V_qjf.js";var x={packet:[]},m=structuredClone(x),L=A.packet,Y=l(()=>{const t=v({...L,..._().packet});return t.showBits&&(t.paddingY+=10),t},"getConfig"),G=l(()=>m.packet,"getPacket"),H=l(t=>{t.length>0&&m.packet.push(t)},"pushWord"),I=l(()=>{D(),m=structuredClone(x)},"clear"),u={pushWord:H,getPacket:G,getConfig:Y,clear:I,setAccTitle:E,getAccTitle:P,setDiagramTitle:F,getDiagramTitle:z,getAccDescription:S,setAccDescription:B},K=1e4,M=l(t=>{y(t,u);let e=-1,o=[],n=1;const{bitsPerRow:i}=u.getConfig();for(let{start:a,end:r,bits:c,label:f}of t.blocks){if(a!==void 0&&r!==void 0&&r<a)throw new Error(`Packet block ${a} - ${r} is invalid. End must be greater than start.`);if(a??(a=e+1),a!==e+1)throw new Error(`Packet block ${a} - ${r??a} is not contiguous. It should start from ${e+1}.`);if(c===0)throw new Error(`Packet block ${a} is invalid. Cannot have a zero bit field.`);for(r??(r=a+(c??1)-1),c??(c=r-a+1),e=r,w.debug(`Packet block ${a} - ${e} with label ${f}`);o.length<=i+1&&u.getPacket().length<K;){const[d,p]=O({start:a,end:r,bits:c,label:f},n,i);if(o.push(d),d.end+1===n*i&&(u.pushWord(o),o=[],n++),!p)break;({start:a,end:r,bits:c,label:f}=p)}}u.pushWord(o)},"populate"),O=l((t,e,o)=>{if(t.start===void 0)throw new Error("start should have been set during first phase");if(t.end===void 0)throw new Error("end should have been set during first phase");if(t.start>t.end)throw new Error(`Block start ${t.start} is greater than block end ${t.end}.`);if(t.end+1<=e*o)return[t,void 0];const n=e*o-1,i=e*o;return[{start:t.start,end:n,label:t.label,bits:n-t.start},{start:i,end:t.end,label:t.label,bits:t.end-i}]},"getNextFittingBlock"),q={parse:l(async t=>{const e=await N("packet",t);w.debug(e),M(e)},"parse")},R=l((t,e,o,n)=>{const i=n.db,a=i.getConfig(),{rowHeight:r,paddingY:c,bitWidth:f,bitsPerRow:d}=a,p=i.getPacket(),s=i.getDiagramTitle(),k=r+c,g=k*(p.length+1)-(s?0:r),b=f*d+2,h=W(e);h.attr("viewbox",`0 0 ${b} ${g}`),T(h,g,b,a.useMaxWidth);for(const[C,$]of p.entries())U(h,$,C,a);h.append("text").text(s).attr("x",b/2).attr("y",g-k/2).attr("dominant-baseline","middle").attr("text-anchor","middle").attr("class","packetTitle")},"draw"),U=l((t,e,o,{rowHeight:n,paddingX:i,paddingY:a,bitWidth:r,bitsPerRow:c,showBits:f})=>{const d=t.append("g"),p=o*(n+a)+a;for(const s of e){const k=s.start%c*r+1,g=(s.end-s.start+1)*r-i;if(d.append("rect").attr("x",k).attr("y",p).attr("width",g).attr("height",n).attr("class","packetBlock"),d.append("text").attr("x",k+g/2).attr("y",p+n/2).attr("class","packetLabel").attr("dominant-baseline","middle").attr("text-anchor","middle").text(s.label),!f)continue;const b=s.end===s.start,h=p-2;d.append("text").attr("x",k+(b?g/2:0)).attr("y",h).attr("class","packetByte start").attr("dominant-baseline","auto").attr("text-anchor",b?"middle":"start").text(s.start),b||d.append("text").attr("x",k+g).attr("y",h).attr("class","packetByte end").attr("dominant-baseline","auto").attr("text-anchor","end").text(s.end)}},"drawWord"),X={draw:R},j={byteFontSize:"10px",startByteColor:"black",endByteColor:"black",labelColor:"black",labelFontSize:"12px",titleColor:"black",titleFontSize:"14px",blockStrokeColor:"black",blockStrokeWidth:"1",blockFillColor:"#efefef"},J=l(({packet:t}={})=>{const e=v(j,t);return`
+import{p as y}from"./chunk-353BL4L5-CR8qX5CO.js";import{_ as l,s as B,g as S,t as z,q as F,a as P,b as E,F as v,K as W,e as T,z as D,G as _,H as A,l as w}from"./mermaid-vendor-B20mDgAo.js";import{p as N}from"./treemap-75Q7IDZK-64OceOGQ.js";import"./feature-graph-CS4MyqEv.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";import"./_baseUniq-Coqzfado.js";import"./_basePickBy-zcTWmF8I.js";import"./clone-D1fuhfq3.js";var x={packet:[]},m=structuredClone(x),L=A.packet,Y=l(()=>{const t=v({...L,..._().packet});return t.showBits&&(t.paddingY+=10),t},"getConfig"),G=l(()=>m.packet,"getPacket"),H=l(t=>{t.length>0&&m.packet.push(t)},"pushWord"),I=l(()=>{D(),m=structuredClone(x)},"clear"),u={pushWord:H,getPacket:G,getConfig:Y,clear:I,setAccTitle:E,getAccTitle:P,setDiagramTitle:F,getDiagramTitle:z,getAccDescription:S,setAccDescription:B},K=1e4,M=l(t=>{y(t,u);let e=-1,o=[],n=1;const{bitsPerRow:i}=u.getConfig();for(let{start:a,end:r,bits:c,label:f}of t.blocks){if(a!==void 0&&r!==void 0&&r<a)throw new Error(`Packet block ${a} - ${r} is invalid. End must be greater than start.`);if(a??(a=e+1),a!==e+1)throw new Error(`Packet block ${a} - ${r??a} is not contiguous. It should start from ${e+1}.`);if(c===0)throw new Error(`Packet block ${a} is invalid. Cannot have a zero bit field.`);for(r??(r=a+(c??1)-1),c??(c=r-a+1),e=r,w.debug(`Packet block ${a} - ${e} with label ${f}`);o.length<=i+1&&u.getPacket().length<K;){const[d,p]=O({start:a,end:r,bits:c,label:f},n,i);if(o.push(d),d.end+1===n*i&&(u.pushWord(o),o=[],n++),!p)break;({start:a,end:r,bits:c,label:f}=p)}}u.pushWord(o)},"populate"),O=l((t,e,o)=>{if(t.start===void 0)throw new Error("start should have been set during first phase");if(t.end===void 0)throw new Error("end should have been set during first phase");if(t.start>t.end)throw new Error(`Block start ${t.start} is greater than block end ${t.end}.`);if(t.end+1<=e*o)return[t,void 0];const n=e*o-1,i=e*o;return[{start:t.start,end:n,label:t.label,bits:n-t.start},{start:i,end:t.end,label:t.label,bits:t.end-i}]},"getNextFittingBlock"),q={parse:l(async t=>{const e=await N("packet",t);w.debug(e),M(e)},"parse")},R=l((t,e,o,n)=>{const i=n.db,a=i.getConfig(),{rowHeight:r,paddingY:c,bitWidth:f,bitsPerRow:d}=a,p=i.getPacket(),s=i.getDiagramTitle(),k=r+c,g=k*(p.length+1)-(s?0:r),b=f*d+2,h=W(e);h.attr("viewbox",`0 0 ${b} ${g}`),T(h,g,b,a.useMaxWidth);for(const[C,$]of p.entries())U(h,$,C,a);h.append("text").text(s).attr("x",b/2).attr("y",g-k/2).attr("dominant-baseline","middle").attr("text-anchor","middle").attr("class","packetTitle")},"draw"),U=l((t,e,o,{rowHeight:n,paddingX:i,paddingY:a,bitWidth:r,bitsPerRow:c,showBits:f})=>{const d=t.append("g"),p=o*(n+a)+a;for(const s of e){const k=s.start%c*r+1,g=(s.end-s.start+1)*r-i;if(d.append("rect").attr("x",k).attr("y",p).attr("width",g).attr("height",n).attr("class","packetBlock"),d.append("text").attr("x",k+g/2).attr("y",p+n/2).attr("class","packetLabel").attr("dominant-baseline","middle").attr("text-anchor","middle").text(s.label),!f)continue;const b=s.end===s.start,h=p-2;d.append("text").attr("x",k+(b?g/2:0)).attr("y",h).attr("class","packetByte start").attr("dominant-baseline","auto").attr("text-anchor",b?"middle":"start").text(s.start),b||d.append("text").attr("x",k+g).attr("y",h).attr("class","packetByte end").attr("dominant-baseline","auto").attr("text-anchor","end").text(s.end)}},"drawWord"),X={draw:R},j={byteFontSize:"10px",startByteColor:"black",endByteColor:"black",labelColor:"black",labelFontSize:"12px",titleColor:"black",titleFontSize:"14px",blockStrokeColor:"black",blockStrokeWidth:"1",blockFillColor:"#efefef"},J=l(({packet:t}={})=>{const e=v(j,t);return`
 	.packetByte {
 		font-size: ${e.byteFontSize};
 	}
diff --git a/lightrag/api/webui/assets/diagram-VMROVX33-B9K7nQip.js b/lightrag/api/webui/assets/diagram-VMROVX33-CL8nPVMB.js
similarity index 96%
rename from lightrag/api/webui/assets/diagram-VMROVX33-B9K7nQip.js
rename to lightrag/api/webui/assets/diagram-VMROVX33-CL8nPVMB.js
index 2a538ff2..54c61e5d 100644
--- a/lightrag/api/webui/assets/diagram-VMROVX33-B9K7nQip.js
+++ b/lightrag/api/webui/assets/diagram-VMROVX33-CL8nPVMB.js
@@ -1,4 +1,4 @@
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similarity index 93%
rename from lightrag/api/webui/assets/diagram-ZTM2IBQH-BEODeKzW.js
rename to lightrag/api/webui/assets/diagram-ZTM2IBQH-YBNtjfoo.js
index 214156cf..cbfb8e3c 100644
--- a/lightrag/api/webui/assets/diagram-ZTM2IBQH-BEODeKzW.js
+++ b/lightrag/api/webui/assets/diagram-ZTM2IBQH-YBNtjfoo.js
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diff --git a/lightrag/api/webui/assets/erDiagram-3M52JZNH-7F0mIezG.js b/lightrag/api/webui/assets/erDiagram-3M52JZNH-DN0W8XWj.js
similarity index 99%
rename from lightrag/api/webui/assets/erDiagram-3M52JZNH-7F0mIezG.js
rename to lightrag/api/webui/assets/erDiagram-3M52JZNH-DN0W8XWj.js
index 551d0a10..b77b7c36 100644
--- a/lightrag/api/webui/assets/erDiagram-3M52JZNH-7F0mIezG.js
+++ b/lightrag/api/webui/assets/erDiagram-3M52JZNH-DN0W8XWj.js
@@ -1,4 +1,4 @@
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ut="";$=[];for(J in K[x])this.terminals_[J]&&J>It&&$.push("'"+this.terminals_[J]+"'");y.showPosition?ut="Parse error on line "+(H+1)+`:
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diff --git a/lightrag/api/webui/assets/feature-documents-DLarjU2a.js b/lightrag/api/webui/assets/feature-documents-4TV9qUPI.js
similarity index 99%
rename from lightrag/api/webui/assets/feature-documents-DLarjU2a.js
rename to lightrag/api/webui/assets/feature-documents-4TV9qUPI.js
index 69306b08..5d9cd35a 100644
--- a/lightrag/api/webui/assets/feature-documents-DLarjU2a.js
+++ b/lightrag/api/webui/assets/feature-documents-4TV9qUPI.js
@@ -1,4 +1,4 @@
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diff --git a/lightrag/api/webui/assets/feature-graph-C6IuADHZ.js b/lightrag/api/webui/assets/feature-graph-CS4MyqEv.js
similarity index 78%
rename from lightrag/api/webui/assets/feature-graph-C6IuADHZ.js
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index b288bcc8..1845b0f0 100644
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+ */const Cc=[["path",{d:"M22 12h-2.48a2 2 0 0 0-1.93 1.46l-2.35 8.36a.25.25 0 0 1-.48 0L9.24 2.18a.25.25 0 0 0-.48 0l-2.35 8.36A2 2 0 0 1 4.49 12H2",key:"169zse"}]],hp=le("Activity",Cc);/**
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+ */const kc=[["path",{d:"M17 12H7",key:"16if0g"}],["path",{d:"M19 18H5",key:"18s9l3"}],["path",{d:"M21 6H3",key:"1jwq7v"}]],gp=le("AlignCenter",kc);/**
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+ */const Tc=[["path",{d:"M15 12H3",key:"6jk70r"}],["path",{d:"M17 18H3",key:"1amg6g"}],["path",{d:"M21 6H3",key:"1jwq7v"}]],pp=le("AlignLeft",Tc);/**
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+ */const Rc=[["path",{d:"M21 12H9",key:"dn1m92"}],["path",{d:"M21 18H7",key:"1ygte8"}],["path",{d:"M21 6H3",key:"1jwq7v"}]],mp=le("AlignRight",Rc);/**
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- */const Ac=[["path",{d:"M12 5v14",key:"s699le"}],["path",{d:"m19 12-7 7-7-7",key:"1idqje"}]],vp=ie("ArrowDown",Ac);/**
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- */const jc=[["path",{d:"m5 12 7-7 7 7",key:"hav0vg"}],["path",{d:"M12 19V5",key:"x0mq9r"}]],yp=ie("ArrowUp",jc);/**
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- */const Lc=[["path",{d:"M20 6 9 17l-5-5",key:"1gmf2c"}]],Va=ie("Check",Lc);/**
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  * See the LICENSE file in the root directory of this source tree.
- */const zc=[["path",{d:"m6 9 6 6 6-6",key:"qrunsl"}]],bp=ie("ChevronDown",zc);/**
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  * See the LICENSE file in the root directory of this source tree.
- */const Pc=[["path",{d:"m15 18-6-6 6-6",key:"1wnfg3"}]],wp=ie("ChevronLeft",Pc);/**
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  * See the LICENSE file in the root directory of this source tree.
- */const Dc=[["path",{d:"m9 18 6-6-6-6",key:"mthhwq"}]],xp=ie("ChevronRight",Dc);/**
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  * See the LICENSE file in the root directory of this source tree.
- */const Oc=[["path",{d:"m18 15-6-6-6 6",key:"153udz"}]],_p=ie("ChevronUp",Oc);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
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+ */const Xc=[["path",{d:"M6 3v12",key:"qpgusn"}],["path",{d:"M18 9a3 3 0 1 0 0-6 3 3 0 0 0 0 6z",key:"1d02ji"}],["path",{d:"M6 21a3 3 0 1 0 0-6 3 3 0 0 0 0 6z",key:"chk6ph"}],["path",{d:"M15 6a9 9 0 0 0-9 9",key:"or332x"}],["path",{d:"M18 15v6",key:"9wciyi"}],["path",{d:"M21 18h-6",key:"139f0c"}]],Yc=le("GitBranchPlus",Xc);/**
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  *
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  * See the LICENSE file in the root directory of this source tree.
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  *
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  * See the LICENSE file in the root directory of this source tree.
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Zc=[["path",{d:"M21 12a9 9 0 1 1-6.219-8.56",key:"13zald"}]],qa=ie("LoaderCircle",Zc);/**
+ */const Zc=[["path",{d:"M21 12a9 9 0 1 1-6.219-8.56",key:"13zald"}]],qa=le("LoaderCircle",Zc);/**
  * @license lucide-react v0.475.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const eu=[["path",{d:"M12 2v4",key:"3427ic"}],["path",{d:"m16.2 7.8 2.9-2.9",key:"r700ao"}],["path",{d:"M18 12h4",key:"wj9ykh"}],["path",{d:"m16.2 16.2 2.9 2.9",key:"1bxg5t"}],["path",{d:"M12 18v4",key:"jadmvz"}],["path",{d:"m4.9 19.1 2.9-2.9",key:"bwix9q"}],["path",{d:"M2 12h4",key:"j09sii"}],["path",{d:"m4.9 4.9 2.9 2.9",key:"giyufr"}]],jp=ie("Loader",eu);/**
+ */const eu=[["path",{d:"M12 2v4",key:"3427ic"}],["path",{d:"m16.2 7.8 2.9-2.9",key:"r700ao"}],["path",{d:"M18 12h4",key:"wj9ykh"}],["path",{d:"m16.2 16.2 2.9 2.9",key:"1bxg5t"}],["path",{d:"M12 18v4",key:"jadmvz"}],["path",{d:"m4.9 19.1 2.9-2.9",key:"bwix9q"}],["path",{d:"M2 12h4",key:"j09sii"}],["path",{d:"m4.9 4.9 2.9 2.9",key:"giyufr"}]],jp=le("Loader",eu);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const tu=[["path",{d:"M9 21H5a2 2 0 0 1-2-2V5a2 2 0 0 1 2-2h4",key:"1uf3rs"}],["polyline",{points:"16 17 21 12 16 7",key:"1gabdz"}],["line",{x1:"21",x2:"9",y1:"12",y2:"12",key:"1uyos4"}]],Ip=ie("LogOut",tu);/**
+ */const tu=[["path",{d:"M9 21H5a2 2 0 0 1-2-2V5a2 2 0 0 1 2-2h4",key:"1uf3rs"}],["polyline",{points:"16 17 21 12 16 7",key:"1gabdz"}],["line",{x1:"21",x2:"9",y1:"12",y2:"12",key:"1uyos4"}]],Ip=le("LogOut",tu);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const ru=[["path",{d:"M8 3H5a2 2 0 0 0-2 2v3",key:"1dcmit"}],["path",{d:"M21 8V5a2 2 0 0 0-2-2h-3",key:"1e4gt3"}],["path",{d:"M3 16v3a2 2 0 0 0 2 2h3",key:"wsl5sc"}],["path",{d:"M16 21h3a2 2 0 0 0 2-2v-3",key:"18trek"}]],nu=ie("Maximize",ru);/**
+ */const ru=[["path",{d:"M8 3H5a2 2 0 0 0-2 2v3",key:"1dcmit"}],["path",{d:"M21 8V5a2 2 0 0 0-2-2h-3",key:"1e4gt3"}],["path",{d:"M3 16v3a2 2 0 0 0 2 2h3",key:"wsl5sc"}],["path",{d:"M16 21h3a2 2 0 0 0 2-2v-3",key:"18trek"}]],nu=le("Maximize",ru);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const ou=[["path",{d:"M8 3v3a2 2 0 0 1-2 2H3",key:"hohbtr"}],["path",{d:"M21 8h-3a2 2 0 0 1-2-2V3",key:"5jw1f3"}],["path",{d:"M3 16h3a2 2 0 0 1 2 2v3",key:"198tvr"}],["path",{d:"M16 21v-3a2 2 0 0 1 2-2h3",key:"ph8mxp"}]],au=ie("Minimize",ou);/**
+ */const ou=[["path",{d:"M8 3v3a2 2 0 0 1-2 2H3",key:"hohbtr"}],["path",{d:"M21 8h-3a2 2 0 0 1-2-2V3",key:"5jw1f3"}],["path",{d:"M3 16h3a2 2 0 0 1 2 2v3",key:"198tvr"}],["path",{d:"M16 21v-3a2 2 0 0 1 2-2h3",key:"ph8mxp"}]],au=le("Minimize",ou);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const su=[["circle",{cx:"13.5",cy:"6.5",r:".5",fill:"currentColor",key:"1okk4w"}],["circle",{cx:"17.5",cy:"10.5",r:".5",fill:"currentColor",key:"f64h9f"}],["circle",{cx:"8.5",cy:"7.5",r:".5",fill:"currentColor",key:"fotxhn"}],["circle",{cx:"6.5",cy:"12.5",r:".5",fill:"currentColor",key:"qy21gx"}],["path",{d:"M12 2C6.5 2 2 6.5 2 12s4.5 10 10 10c.926 0 1.648-.746 1.648-1.688 0-.437-.18-.835-.437-1.125-.29-.289-.438-.652-.438-1.125a1.64 1.64 0 0 1 1.668-1.668h1.996c3.051 0 5.555-2.503 5.555-5.554C21.965 6.012 17.461 2 12 2z",key:"12rzf8"}]],Np=ie("Palette",su);/**
+ */const su=[["circle",{cx:"13.5",cy:"6.5",r:".5",fill:"currentColor",key:"1okk4w"}],["circle",{cx:"17.5",cy:"10.5",r:".5",fill:"currentColor",key:"f64h9f"}],["circle",{cx:"8.5",cy:"7.5",r:".5",fill:"currentColor",key:"fotxhn"}],["circle",{cx:"6.5",cy:"12.5",r:".5",fill:"currentColor",key:"qy21gx"}],["path",{d:"M12 2C6.5 2 2 6.5 2 12s4.5 10 10 10c.926 0 1.648-.746 1.648-1.688 0-.437-.18-.835-.437-1.125-.29-.289-.438-.652-.438-1.125a1.64 1.64 0 0 1 1.668-1.668h1.996c3.051 0 5.555-2.503 5.555-5.554C21.965 6.012 17.461 2 12 2z",key:"12rzf8"}]],Np=le("Palette",su);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const iu=[["rect",{x:"14",y:"4",width:"4",height:"16",rx:"1",key:"zuxfzm"}],["rect",{x:"6",y:"4",width:"4",height:"16",rx:"1",key:"1okwgv"}]],lu=ie("Pause",iu);/**
+ */const iu=[["rect",{x:"14",y:"4",width:"4",height:"16",rx:"1",key:"zuxfzm"}],["rect",{x:"6",y:"4",width:"4",height:"16",rx:"1",key:"1okwgv"}]],lu=le("Pause",iu);/**
  * @license lucide-react v0.475.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const cu=[["path",{d:"M21.174 6.812a1 1 0 0 0-3.986-3.987L3.842 16.174a2 2 0 0 0-.5.83l-1.321 4.352a.5.5 0 0 0 .623.622l4.353-1.32a2 2 0 0 0 .83-.497z",key:"1a8usu"}],["path",{d:"m15 5 4 4",key:"1mk7zo"}]],uu=ie("Pencil",cu);/**
+ */const cu=[["path",{d:"M21.174 6.812a1 1 0 0 0-3.986-3.987L3.842 16.174a2 2 0 0 0-.5.83l-1.321 4.352a.5.5 0 0 0 .623.622l4.353-1.32a2 2 0 0 0 .83-.497z",key:"1a8usu"}],["path",{d:"m15 5 4 4",key:"1mk7zo"}]],uu=le("Pencil",cu);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const du=[["polygon",{points:"6 3 20 12 6 21 6 3",key:"1oa8hb"}]],fu=ie("Play",du);/**
+ */const du=[["polygon",{points:"6 3 20 12 6 21 6 3",key:"1oa8hb"}]],fu=le("Play",du);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const hu=[["path",{d:"M3 12a9 9 0 0 1 9-9 9.75 9.75 0 0 1 6.74 2.74L21 8",key:"v9h5vc"}],["path",{d:"M21 3v5h-5",key:"1q7to0"}],["path",{d:"M21 12a9 9 0 0 1-9 9 9.75 9.75 0 0 1-6.74-2.74L3 16",key:"3uifl3"}],["path",{d:"M8 16H3v5",key:"1cv678"}]],gu=ie("RefreshCw",hu);/**
+ */const hu=[["path",{d:"M3 12a9 9 0 0 1 9-9 9.75 9.75 0 0 1 6.74 2.74L21 8",key:"v9h5vc"}],["path",{d:"M21 3v5h-5",key:"1q7to0"}],["path",{d:"M21 12a9 9 0 0 1-9 9 9.75 9.75 0 0 1-6.74-2.74L3 16",key:"3uifl3"}],["path",{d:"M8 16H3v5",key:"1cv678"}]],gu=le("RefreshCw",hu);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const pu=[["path",{d:"M3 12a9 9 0 1 0 9-9 9.75 9.75 0 0 0-6.74 2.74L3 8",key:"1357e3"}],["path",{d:"M3 3v5h5",key:"1xhq8a"}]],mu=ie("RotateCcw",pu);/**
+ */const pu=[["path",{d:"M3 12a9 9 0 1 0 9-9 9.75 9.75 0 0 0-6.74 2.74L3 8",key:"1357e3"}],["path",{d:"M3 3v5h5",key:"1xhq8a"}]],mu=le("RotateCcw",pu);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const vu=[["path",{d:"M21 12a9 9 0 1 1-9-9c2.52 0 4.93 1 6.74 2.74L21 8",key:"1p45f6"}],["path",{d:"M21 3v5h-5",key:"1q7to0"}]],yu=ie("RotateCw",vu);/**
+ */const vu=[["path",{d:"M21 12a9 9 0 1 1-9-9c2.52 0 4.93 1 6.74 2.74L21 8",key:"1p45f6"}],["path",{d:"M21 3v5h-5",key:"1q7to0"}]],yu=le("RotateCw",vu);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const bu=[["circle",{cx:"6",cy:"6",r:"3",key:"1lh9wr"}],["path",{d:"M8.12 8.12 12 12",key:"1alkpv"}],["path",{d:"M20 4 8.12 15.88",key:"xgtan2"}],["circle",{cx:"6",cy:"18",r:"3",key:"fqmcym"}],["path",{d:"M14.8 14.8 20 20",key:"ptml3r"}]],wu=ie("Scissors",bu);/**
+ */const bu=[["circle",{cx:"6",cy:"6",r:"3",key:"1lh9wr"}],["path",{d:"M8.12 8.12 12 12",key:"1alkpv"}],["path",{d:"M20 4 8.12 15.88",key:"xgtan2"}],["circle",{cx:"6",cy:"18",r:"3",key:"fqmcym"}],["path",{d:"M14.8 14.8 20 20",key:"ptml3r"}]],wu=le("Scissors",bu);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const xu=[["circle",{cx:"11",cy:"11",r:"8",key:"4ej97u"}],["path",{d:"m21 21-4.3-4.3",key:"1qie3q"}]],_u=ie("Search",xu);/**
+ */const xu=[["circle",{cx:"11",cy:"11",r:"8",key:"4ej97u"}],["path",{d:"m21 21-4.3-4.3",key:"1qie3q"}]],_u=le("Search",xu);/**
  * @license lucide-react v0.475.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Su=[["path",{d:"M14.536 21.686a.5.5 0 0 0 .937-.024l6.5-19a.496.496 0 0 0-.635-.635l-19 6.5a.5.5 0 0 0-.024.937l7.93 3.18a2 2 0 0 1 1.112 1.11z",key:"1ffxy3"}],["path",{d:"m21.854 2.147-10.94 10.939",key:"12cjpa"}]],Lp=ie("Send",Su);/**
+ */const Su=[["path",{d:"M14.536 21.686a.5.5 0 0 0 .937-.024l6.5-19a.496.496 0 0 0-.635-.635l-19 6.5a.5.5 0 0 0-.024.937l7.93 3.18a2 2 0 0 1 1.112 1.11z",key:"1ffxy3"}],["path",{d:"m21.854 2.147-10.94 10.939",key:"12cjpa"}]],Lp=le("Send",Su);/**
  * @license lucide-react v0.475.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Eu=[["path",{d:"M12.22 2h-.44a2 2 0 0 0-2 2v.18a2 2 0 0 1-1 1.73l-.43.25a2 2 0 0 1-2 0l-.15-.08a2 2 0 0 0-2.73.73l-.22.38a2 2 0 0 0 .73 2.73l.15.1a2 2 0 0 1 1 1.72v.51a2 2 0 0 1-1 1.74l-.15.09a2 2 0 0 0-.73 2.73l.22.38a2 2 0 0 0 2.73.73l.15-.08a2 2 0 0 1 2 0l.43.25a2 2 0 0 1 1 1.73V20a2 2 0 0 0 2 2h.44a2 2 0 0 0 2-2v-.18a2 2 0 0 1 1-1.73l.43-.25a2 2 0 0 1 2 0l.15.08a2 2 0 0 0 2.73-.73l.22-.39a2 2 0 0 0-.73-2.73l-.15-.08a2 2 0 0 1-1-1.74v-.5a2 2 0 0 1 1-1.74l.15-.09a2 2 0 0 0 .73-2.73l-.22-.38a2 2 0 0 0-2.73-.73l-.15.08a2 2 0 0 1-2 0l-.43-.25a2 2 0 0 1-1-1.73V4a2 2 0 0 0-2-2z",key:"1qme2f"}],["circle",{cx:"12",cy:"12",r:"3",key:"1v7zrd"}]],Cu=ie("Settings",Eu);/**
+ */const Eu=[["path",{d:"M12.22 2h-.44a2 2 0 0 0-2 2v.18a2 2 0 0 1-1 1.73l-.43.25a2 2 0 0 1-2 0l-.15-.08a2 2 0 0 0-2.73.73l-.22.38a2 2 0 0 0 .73 2.73l.15.1a2 2 0 0 1 1 1.72v.51a2 2 0 0 1-1 1.74l-.15.09a2 2 0 0 0-.73 2.73l.22.38a2 2 0 0 0 2.73.73l.15-.08a2 2 0 0 1 2 0l.43.25a2 2 0 0 1 1 1.73V20a2 2 0 0 0 2 2h.44a2 2 0 0 0 2-2v-.18a2 2 0 0 1 1-1.73l.43-.25a2 2 0 0 1 2 0l.15.08a2 2 0 0 0 2.73-.73l.22-.39a2 2 0 0 0-.73-2.73l-.15-.08a2 2 0 0 1-1-1.74v-.5a2 2 0 0 1 1-1.74l.15-.09a2 2 0 0 0 .73-2.73l-.22-.38a2 2 0 0 0-2.73-.73l-.15.08a2 2 0 0 1-2 0l-.43-.25a2 2 0 0 1-1-1.73V4a2 2 0 0 0-2-2z",key:"1qme2f"}],["circle",{cx:"12",cy:"12",r:"3",key:"1v7zrd"}]],Cu=le("Settings",Eu);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const ku=[["path",{d:"M21 10.5V19a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2V5a2 2 0 0 1 2-2h12.5",key:"1uzm8b"}],["path",{d:"m9 11 3 3L22 4",key:"1pflzl"}]],zp=ie("SquareCheckBig",ku);/**
+ */const ku=[["path",{d:"M21 10.5V19a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2V5a2 2 0 0 1 2-2h12.5",key:"1uzm8b"}],["path",{d:"m9 11 3 3L22 4",key:"1pflzl"}]],zp=le("SquareCheckBig",ku);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Tu=[["path",{d:"M3 6h18",key:"d0wm0j"}],["path",{d:"M19 6v14c0 1-1 2-2 2H7c-1 0-2-1-2-2V6",key:"4alrt4"}],["path",{d:"M8 6V4c0-1 1-2 2-2h4c1 0 2 1 2 2v2",key:"v07s0e"}]],Pp=ie("Trash",Tu);/**
+ */const Tu=[["path",{d:"M3 6h18",key:"d0wm0j"}],["path",{d:"M19 6v14c0 1-1 2-2 2H7c-1 0-2-1-2-2V6",key:"4alrt4"}],["path",{d:"M8 6V4c0-1 1-2 2-2h4c1 0 2 1 2 2v2",key:"v07s0e"}]],Pp=le("Trash",Tu);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Ru=[["path",{d:"m21.73 18-8-14a2 2 0 0 0-3.48 0l-8 14A2 2 0 0 0 4 21h16a2 2 0 0 0 1.73-3",key:"wmoenq"}],["path",{d:"M12 9v4",key:"juzpu7"}],["path",{d:"M12 17h.01",key:"p32p05"}]],Dp=ie("TriangleAlert",Ru);/**
+ */const Ru=[["path",{d:"m21.73 18-8-14a2 2 0 0 0-3.48 0l-8 14A2 2 0 0 0 4 21h16a2 2 0 0 0 1.73-3",key:"wmoenq"}],["path",{d:"M12 9v4",key:"juzpu7"}],["path",{d:"M12 17h.01",key:"p32p05"}]],Dp=le("TriangleAlert",Ru);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Au=[["path",{d:"M9 14 4 9l5-5",key:"102s5s"}],["path",{d:"M4 9h10.5a5.5 5.5 0 0 1 5.5 5.5a5.5 5.5 0 0 1-5.5 5.5H11",key:"f3b9sd"}]],Ua=ie("Undo2",Au);/**
+ */const Au=[["path",{d:"M9 14 4 9l5-5",key:"102s5s"}],["path",{d:"M4 9h10.5a5.5 5.5 0 0 1 5.5 5.5a5.5 5.5 0 0 1-5.5 5.5H11",key:"f3b9sd"}]],Ua=le("Undo2",Au);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const ju=[["path",{d:"M21 15v4a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2v-4",key:"ih7n3h"}],["polyline",{points:"17 8 12 3 7 8",key:"t8dd8p"}],["line",{x1:"12",x2:"12",y1:"3",y2:"15",key:"widbto"}]],Op=ie("Upload",ju);/**
+ */const ju=[["path",{d:"M21 15v4a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2v-4",key:"ih7n3h"}],["polyline",{points:"17 8 12 3 7 8",key:"t8dd8p"}],["line",{x1:"12",x2:"12",y1:"3",y2:"15",key:"widbto"}]],Op=le("Upload",ju);/**
  * @license lucide-react v0.475.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Iu=[["path",{d:"M18 6 6 18",key:"1bl5f8"}],["path",{d:"m6 6 12 12",key:"d8bk6v"}]],Nu=ie("X",Iu);/**
+ */const Iu=[["path",{d:"M18 6 6 18",key:"1bl5f8"}],["path",{d:"m6 6 12 12",key:"d8bk6v"}]],Nu=le("X",Iu);/**
  * @license lucide-react v0.475.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Lu=[["path",{d:"M4 14a1 1 0 0 1-.78-1.63l9.9-10.2a.5.5 0 0 1 .86.46l-1.92 6.02A1 1 0 0 0 13 10h7a1 1 0 0 1 .78 1.63l-9.9 10.2a.5.5 0 0 1-.86-.46l1.92-6.02A1 1 0 0 0 11 14z",key:"1xq2db"}]],Gp=ie("Zap",Lu);/**
+ */const Lu=[["path",{d:"M4 14a1 1 0 0 1-.78-1.63l9.9-10.2a.5.5 0 0 1 .86.46l-1.92 6.02A1 1 0 0 0 13 10h7a1 1 0 0 1 .78 1.63l-9.9 10.2a.5.5 0 0 1-.86-.46l1.92-6.02A1 1 0 0 0 11 14z",key:"1xq2db"}]],Gp=le("Zap",Lu);/**
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  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const zu=[["circle",{cx:"11",cy:"11",r:"8",key:"4ej97u"}],["line",{x1:"21",x2:"16.65",y1:"21",y2:"16.65",key:"13gj7c"}],["line",{x1:"11",x2:"11",y1:"8",y2:"14",key:"1vmskp"}],["line",{x1:"8",x2:"14",y1:"11",y2:"11",key:"durymu"}]],Pu=ie("ZoomIn",zu);/**
+ */const zu=[["circle",{cx:"11",cy:"11",r:"8",key:"4ej97u"}],["line",{x1:"21",x2:"16.65",y1:"21",y2:"16.65",key:"13gj7c"}],["line",{x1:"11",x2:"11",y1:"8",y2:"14",key:"1vmskp"}],["line",{x1:"8",x2:"14",y1:"11",y2:"11",key:"durymu"}]],Pu=le("ZoomIn",zu);/**
  * @license lucide-react v0.475.0 - ISC
  *
  * This source code is licensed under the ISC license.
  * See the LICENSE file in the root directory of this source tree.
- */const Du=[["circle",{cx:"11",cy:"11",r:"8",key:"4ej97u"}],["line",{x1:"21",x2:"16.65",y1:"21",y2:"16.65",key:"13gj7c"}],["line",{x1:"8",x2:"14",y1:"11",y2:"11",key:"durymu"}]],Ou=ie("ZoomOut",Du),Gu=wa,Fp=Li,Fu=va,Wa=p.forwardRef(({className:e,...t},r)=>g.jsx(_n,{ref:r,className:fe("data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 fixed inset-0 z-50 bg-black/30",e),...t}));Wa.displayName=_n.displayName;const Xa=p.forwardRef(({className:e,children:t,...r},n)=>g.jsxs(Fu,{children:[g.jsx(Wa,{}),g.jsxs(Sn,{ref:n,className:fe("bg-background data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[state=closed]:slide-out-to-top-[48%] data-[state=open]:slide-in-from-top-[48%] fixed top-[50%] left-[50%] z-50 grid w-full max-w-lg translate-x-[-50%] translate-y-[-50%] gap-4 border p-6 shadow-lg duration-200 sm:rounded-lg",e),...r,children:[t,g.jsxs(Ni,{className:"ring-offset-background focus:ring-ring data-[state=open]:bg-accent data-[state=open]:text-muted-foreground absolute top-4 right-4 rounded-sm opacity-70 transition-opacity hover:opacity-100 focus:ring-2 focus:ring-offset-2 focus:outline-none disabled:pointer-events-none",children:[g.jsx(Nu,{className:"h-4 w-4"}),g.jsx("span",{className:"sr-only",children:"Close"})]})]})]}));Xa.displayName=Sn.displayName;const Ya=({className:e,...t})=>g.jsx("div",{className:fe("flex flex-col space-y-1.5 text-center sm:text-left",e),...t});Ya.displayName="DialogHeader";const Ka=({className:e,...t})=>g.jsx("div",{className:fe("flex flex-col-reverse sm:flex-row sm:justify-end sm:space-x-2",e),...t});Ka.displayName="DialogFooter";const Qa=p.forwardRef(({className:e,...t},r)=>g.jsx(ya,{ref:r,className:fe("text-lg leading-none font-semibold tracking-tight",e),...t}));Qa.displayName=ya.displayName;const Ja=p.forwardRef(({className:e,...t},r)=>g.jsx(ba,{ref:r,className:fe("text-muted-foreground text-sm",e),...t}));Ja.displayName=ba.displayName;const Rn=Pi,An=Di,ir=p.forwardRef(({className:e,align:t="center",sideOffset:r=4,collisionPadding:n,sticky:a,avoidCollisions:o=!1,...l},i)=>g.jsx(zi,{children:g.jsx(xa,{ref:i,align:t,sideOffset:r,collisionPadding:n,sticky:a,avoidCollisions:o,className:fe("bg-popover text-popover-foreground data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 z-50 rounded-md border p-4 shadow-md outline-none",e),...l})}));ir.displayName=xa.displayName;var Mu=`
+ */const Du=[["circle",{cx:"11",cy:"11",r:"8",key:"4ej97u"}],["line",{x1:"21",x2:"16.65",y1:"21",y2:"16.65",key:"13gj7c"}],["line",{x1:"8",x2:"14",y1:"11",y2:"11",key:"durymu"}]],Ou=le("ZoomOut",Du),Gu=wa,Fp=Li,Fu=va,Wa=p.forwardRef(({className:e,...t},r)=>g.jsx(_n,{ref:r,className:fe("data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 fixed inset-0 z-50 bg-black/30",e),...t}));Wa.displayName=_n.displayName;const Xa=p.forwardRef(({className:e,children:t,...r},n)=>g.jsxs(Fu,{children:[g.jsx(Wa,{}),g.jsxs(Sn,{ref:n,className:fe("bg-background data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[state=closed]:slide-out-to-top-[48%] data-[state=open]:slide-in-from-top-[48%] fixed top-[50%] left-[50%] z-50 grid w-full max-w-lg translate-x-[-50%] translate-y-[-50%] gap-4 border p-6 shadow-lg duration-200 sm:rounded-lg",e),...r,children:[t,g.jsxs(Ni,{className:"ring-offset-background focus:ring-ring data-[state=open]:bg-accent data-[state=open]:text-muted-foreground absolute top-4 right-4 rounded-sm opacity-70 transition-opacity hover:opacity-100 focus:ring-2 focus:ring-offset-2 focus:outline-none disabled:pointer-events-none",children:[g.jsx(Nu,{className:"h-4 w-4"}),g.jsx("span",{className:"sr-only",children:"Close"})]})]})]}));Xa.displayName=Sn.displayName;const Ya=({className:e,...t})=>g.jsx("div",{className:fe("flex flex-col space-y-1.5 text-center sm:text-left",e),...t});Ya.displayName="DialogHeader";const Ka=({className:e,...t})=>g.jsx("div",{className:fe("flex flex-col-reverse sm:flex-row sm:justify-end sm:space-x-2",e),...t});Ka.displayName="DialogFooter";const Qa=p.forwardRef(({className:e,...t},r)=>g.jsx(ya,{ref:r,className:fe("text-lg leading-none font-semibold tracking-tight",e),...t}));Qa.displayName=ya.displayName;const Ja=p.forwardRef(({className:e,...t},r)=>g.jsx(ba,{ref:r,className:fe("text-muted-foreground text-sm",e),...t}));Ja.displayName=ba.displayName;const Rn=Pi,An=Di,ir=p.forwardRef(({className:e,align:t="center",sideOffset:r=4,collisionPadding:n,sticky:a,avoidCollisions:o=!1,...l},i)=>g.jsx(zi,{children:g.jsx(xa,{ref:i,align:t,sideOffset:r,collisionPadding:n,sticky:a,avoidCollisions:o,className:fe("bg-popover text-popover-foreground data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0 data-[state=closed]:zoom-out-95 data-[state=open]:zoom-in-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 z-50 rounded-md border p-4 shadow-md outline-none",e),...l})}));ir.displayName=xa.displayName;var Mu=`
 precision mediump float;
 
 varying vec4 v_color;
@@ -528,7 +528,7 @@ void main() {
   #endif
 }
 `);return r}var as=WebGLRenderingContext,co=as.UNSIGNED_BYTE,Lt=as.FLOAT;function md(e){var t,r=lo(lo({},fd),{}),n=r.borders,a=r.drawLabel,o=r.drawHover,l=["u_sizeRatio","u_correctionRatio","u_matrix"].concat(pr(n.flatMap(function(i,s){var c=i.color;return"value"in c?["u_borderColor_".concat(s+1)]:[]})));return t=function(i){id(s,i);function s(){var c;td(this,s);for(var u=arguments.length,d=new Array(u),h=0;h<u;h++)d[h]=arguments[h];return c=sd(this,s,[].concat(d)),vt(cn(c),"drawLabel",a),vt(cn(c),"drawHover",o),c}return od(s,[{key:"getDefinition",value:function(){return{VERTICES:3,VERTEX_SHADER_SOURCE:pd(r),FRAGMENT_SHADER_SOURCE:gd(r),METHOD:WebGLRenderingContext.TRIANGLES,UNIFORMS:l,ATTRIBUTES:[{name:"a_position",size:2,type:Lt},{name:"a_id",size:4,type:co,normalized:!0},{name:"a_size",size:1,type:Lt}].concat(pr(n.flatMap(function(u,d){var h=u.color;return"attribute"in h?[{name:"a_borderColor_".concat(d+1),size:4,type:co,normalized:!0}]:[]})),pr(n.flatMap(function(u,d){var h=u.size;return"attribute"in h?[{name:"a_borderSize_".concat(d+1),size:1,type:Lt}]:[]}))),CONSTANT_ATTRIBUTES:[{name:"a_angle",size:1,type:Lt}],CONSTANT_DATA:[[s.ANGLE_1],[s.ANGLE_2],[s.ANGLE_3]]}}},{key:"processVisibleItem",value:function(u,d,h){var f=this.array;f[d++]=h.x,f[d++]=h.y,f[d++]=u,f[d++]=h.size,n.forEach(function(b){var y=b.color;"attribute"in y&&(f[d++]=er(h[y.attribute]||y.defaultValue||hd))}),n.forEach(function(b){var y=b.size;"attribute"in y&&(f[d++]=h[y.attribute]||y.defaultValue)})}},{key:"setUniforms",value:function(u,d){var h=d.gl,f=d.uniformLocations,b=f.u_sizeRatio,y=f.u_correctionRatio,k=f.u_matrix;h.uniform1f(y,u.correctionRatio),h.uniform1f(b,u.sizeRatio),h.uniformMatrix3fv(k,!1,u.matrix),n.forEach(function(N,E){var j=N.color;if("value"in j){var A=f["u_borderColor_".concat(E+1)],I=yi(j.value),P=ed(I,4),m=P[0],S=P[1],x=P[2],T=P[3];h.uniform4f(A,m/255,S/255,x/255,T/255)}})}}]),s}(ia),vt(t,"ANGLE_1",0),vt(t,"ANGLE_2",2*Math.PI/3),vt(t,"ANGLE_3",4*Math.PI/3),t}var vd=md();function yd(e,t){if(typeof e!="object"||!e)return e;var r=e[Symbol.toPrimitive];if(r!==void 0){var n=r.call(e,t);if(typeof n!="object")return n;throw new TypeError("@@toPrimitive must return a primitive value.")}return(t==="string"?String:Number)(e)}function ss(e){var t=yd(e,"string");return typeof t=="symbol"?t:t+""}function is(e,t,r){return(t=ss(t))in e?Object.defineProperty(e,t,{value:r,enumerable:!0,configurable:!0,writable:!0}):e[t]=r,e}function uo(e,t){var r=Object.keys(e);if(Object.getOwnPropertySymbols){var n=Object.getOwnPropertySymbols(e);t&&(n=n.filter(function(a){return Object.getOwnPropertyDescriptor(e,a).enumerable})),r.push.apply(r,n)}return r}function Yt(e){for(var t=1;t<arguments.length;t++){var r=arguments[t]!=null?arguments[t]:{};t%2?uo(Object(r),!0).forEach(function(n){is(e,n,r[n])}):Object.getOwnPropertyDescriptors?Object.defineProperties(e,Object.getOwnPropertyDescriptors(r)):uo(Object(r)).forEach(function(n){Object.defineProperty(e,n,Object.getOwnPropertyDescriptor(r,n))})}return e}function bd(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}function wd(e,t){for(var r=0;r<t.length;r++){var n=t[r];n.enumerable=n.enumerable||!1,n.configurable=!0,"value"in n&&(n.writable=!0),Object.defineProperty(e,ss(n.key),n)}}function xd(e,t,r){return t&&wd(e.prototype,t),Object.defineProperty(e,"prototype",{writable:!1}),e}function Kt(e){return Kt=Object.setPrototypeOf?Object.getPrototypeOf.bind():function(t){return t.__proto__||Object.getPrototypeOf(t)},Kt(e)}function ls(){try{var e=!Boolean.prototype.valueOf.call(Reflect.construct(Boolean,[],function(){}))}catch{}return(ls=function(){return!!e})()}function cs(e){if(e===void 0)throw new ReferenceError("this hasn't been initialised - 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+In order to be iterable, non-array objects must have a [Symbol.iterator]() method.`)}function mr(e){return Cd(e)||kd(e)||Td(e)||Rd()}function us(e,t,r,n){var a=Math.pow(1-e,2)*t.x+2*(1-e)*e*r.x+Math.pow(e,2)*n.x,o=Math.pow(1-e,2)*t.y+2*(1-e)*e*r.y+Math.pow(e,2)*n.y;return{x:a,y:o}}function Ad(e,t,r){for(var n=20,a=0,o=e,l=0;l<n;l++){var i=us((l+1)/n,e,t,r);a+=Math.sqrt(Math.pow(o.x-i.x,2)+Math.pow(o.y-i.y,2)),o=i}return a}function jd(e){var t=e.curvatureAttribute,r=e.defaultCurvature,n=e.keepLabelUpright,a=n===void 0?!0:n;return function(o,l,i,s,c){var u=c.edgeLabelSize,d=l[t]||r,h=c.edgeLabelFont,f=c.edgeLabelWeight,b=c.edgeLabelColor.attribute?l[c.edgeLabelColor.attribute]||c.edgeLabelColor.color||"#000":c.edgeLabelColor.color,y=l.label;if(y){o.fillStyle=b,o.font="".concat(f," ").concat(u,"px ").concat(h);var k=!a||i.x<s.x,N=k?i.x:s.x,E=k?i.y:s.y,j=k?s.x:i.x,A=k?s.y:i.y,I=(N+j)/2,P=(E+A)/2,m=j-N,S=A-E,x=Math.sqrt(Math.pow(m,2)+Math.pow(S,2)),T=k?1:-1,R=I+S*d*T,O=P-m*d*T,w=l.size*.7+5,H={x:O-E,y:-(R-N)},K=Math.sqrt(Math.pow(H.x,2)+Math.pow(H.y,2)),D={x:A-O,y:-(j-R)},C=Math.sqrt(Math.pow(D.x,2)+Math.pow(D.y,2));N+=w*H.x/K,E+=w*H.y/K,j+=w*D.x/C,A+=w*D.y/C,R+=w*S/x,O-=w*m/x;var _={x:R,y:O},B={x:N,y:E},se={x:j,y:A},M=Ad(B,_,se);if(!(M<i.size+s.size)){var v=o.measureText(y).width,z=M-i.size-s.size;if(v>z){var V="…";for(y=y+V,v=o.measureText(y).width;v>z&&y.length>1;)y=y.slice(0,-2)+V,v=o.measureText(y).width;if(y.length<4)return}for(var $={},Q=0,W=y.length;Q<W;Q++){var Y=y[Q];$[Y]||($[Y]=o.measureText(Y).width*(1+d*.35))}for(var ie=.5-v/M/2,ne=0,ae=y.length;ne<ae;ne++){var F=y[ne],J=us(ie,B,_,se),U=2*(1-ie)*(R-N)+2*ie*(j-R),q=2*(1-ie)*(O-E)+2*ie*(A-O),L=Math.atan2(q,U);o.save(),o.translate(J.x,J.y),o.rotate(L),o.fillText(F,0,0),o.restore(),ie+=$[F]/M}}}}}function Id(e){var t=e.arrowHead,r=(t==null?void 0:t.extremity)==="target"||(t==null?void 0:t.extremity)==="both",n=(t==null?void 0:t.extremity)==="source"||(t==null?void 0:t.extremity)==="both",a=`
 precision highp float;
 
 varying vec4 v_color;
@@ -713,7 +713,7 @@ void main() {
 
   v_color.a *= bias;
 }
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b=f.gl,y=f.uniformLocations,k=y.u_matrix,N=y.u_pixelRatio,E=y.u_feather,j=y.u_sizeRatio,A=y.u_dimensions,I=y.u_minEdgeThickness;if(b.uniformMatrix3fv(k,!1,h.matrix),b.uniform1f(N,h.pixelRatio),b.uniform1f(j,h.sizeRatio),b.uniform1f(E,h.antiAliasingFeather),b.uniform2f(A,h.width*h.pixelRatio,h.height*h.pixelRatio),b.uniform1f(I,h.minEdgeThickness),n){var P=y.u_lengthToThicknessRatio,m=y.u_widenessToThicknessRatio;b.uniform1f(P,n.lengthToThicknessRatio),b.uniform1f(m,n.widenessToThicknessRatio)}}}]),u}(ua)}lr();var zd=lr({arrowHead:wn});lr({arrowHead:Yt(Yt({},wn),{},{extremity:"both"})});const Pd=({node:e,move:t})=>{const r=Be(),{gotoNode:n}=da();return p.useEffect(()=>{const a=r.getGraph();if(t){if(e&&a.hasNode(e))try{a.setNodeAttribute(e,"highlighted",!0),n(e)}catch(o){console.error("Error focusing on node:",o)}else r.setCustomBBox(null),r.getCamera().animate({x:.5,y:.5,ratio:1},{duration:0});te.getState().setMoveToSelectedNode(!1)}else 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if(L[D+f]<0){L[D+f]=C;break}else{if(L[D+E]=K*x,v=L[D+k]/2,z=L[D+E],L[z+f]=-1,L[z+b]=L[D+b]-v,L[z+y]=L[D+y]-v,L[z+k]=v,L[z+N]=z+x,L[z+E]=-1,L[z+j]=0,L[z+A]=0,L[z+I]=0,z+=x,L[z+f]=-1,L[z+b]=L[D+b]-v,L[z+y]=L[D+y]+v,L[z+k]=v,L[z+N]=z+x,L[z+E]=-1,L[z+j]=0,L[z+A]=0,L[z+I]=0,z+=x,L[z+f]=-1,L[z+b]=L[D+b]+v,L[z+y]=L[D+y]-v,L[z+k]=v,L[z+N]=z+x,L[z+E]=-1,L[z+j]=0,L[z+A]=0,L[z+I]=0,z+=x,L[z+f]=-1,L[z+b]=L[D+b]+v,L[z+y]=L[D+y]+v,L[z+k]=v,L[z+N]=L[D+N],L[z+E]=-1,L[z+j]=0,L[z+A]=0,L[z+I]=0,K+=4,w[L[D+f]+e]<L[D+b]?w[L[D+f]+t]<L[D+y]?G=L[D+E]:G=L[D+E]+x:w[L[D+f]+t]<L[D+y]?G=L[D+E]+x*2:G=L[D+E]+x*3,L[D+j]=w[L[D+f]+l],L[D+A]=w[L[D+f]+e],L[D+I]=w[L[D+f]+t],L[G+f]=L[D+f],L[D+f]=-1,w[C+e]<L[D+b]?w[C+t]<L[D+y]?ge=L[D+E]:ge=L[D+E]+x:w[C+t]<L[D+y]?ge=L[D+E]+x*2:ge=L[D+E]+x*3,G===ge)if(pe--){D=G;continue}else{pe=P;break}L[ge+f]=C;break}}if(O.barnesHutOptimize)for(ne=O.scalingRatio,C=0;C<$;C+=m)for(D=0;;)if(L[D+E]>=0)if(U=Math.pow(w[C+e]-L[D+A],2)+Math.pow(w[C+t]-L[D+I],2),V=L[D+k],4*V*V/U<Y){if(se=w[C+e]-L[D+A],F=w[C+t]-L[D+I],X===!0?U>0?(q=ne*w[C+l]*L[D+j]/U,w[C+r]+=se*q,w[C+n]+=F*q):U<0&&(q=-ne*w[C+l]*L[D+j]/Math.sqrt(U),w[C+r]+=se*q,w[C+n]+=F*q):U>0&&(q=ne*w[C+l]*L[D+j]/U,w[C+r]+=se*q,w[C+n]+=F*q),D=L[D+N],D<0)break;continue}else{D=L[D+E];continue}else{if(ae=L[D+f],ae>=0&&ae!==C&&(se=w[C+e]-w[ae+e],F=w[C+t]-w[ae+t],U=se*se+F*F,X===!0?U>0?(q=ne*w[C+l]*w[ae+l]/U,w[C+r]+=se*q,w[C+n]+=F*q):U<0&&(q=-ne*w[C+l]*w[ae+l]/Math.sqrt(U),w[C+r]+=se*q,w[C+n]+=F*q):U>0&&(q=ne*w[C+l]*w[ae+l]/U,w[C+r]+=se*q,w[C+n]+=F*q)),D=L[D+N],D<0)break;continue}else for(ne=O.scalingRatio,_=0;_<$;_+=m)for(B=0;B<_;B+=m)se=w[_+e]-w[B+e],F=w[_+t]-w[B+t],X===!0?(U=Math.sqrt(se*se+F*F)-w[_+s]-w[B+s],U>0?(q=ne*w[_+l]*w[B+l]/U/U,w[_+r]+=se*q,w[_+n]+=F*q,w[B+r]-=se*q,w[B+n]-=F*q):U<0&&(q=100*ne*w[_+l]*w[B+l],w[_+r]+=se*q,w[_+n]+=F*q,w[B+r]-=se*q,w[B+n]-=F*q)):(U=Math.sqrt(se*se+F*F),U>0&&(q=ne*w[_+l]*w[B+l]/U/U,w[_+r]+=se*q,w[_+n]+=F*q,w[B+r]-=se*q,w[B+n]-=F*q));for(z=O.gravity/O.scalingRatio,ne=O.scalingRatio,C=0;C<$;C+=m)q=0,se=w[C+e],F=w[C+t],U=Math.sqrt(Math.pow(se,2)+Math.pow(F,2)),O.strongGravityMode?U>0&&(q=ne*w[C+l]*z):U>0&&(q=ne*w[C+l]*z/U),w[C+r]-=se*q,w[C+n]-=F*q;for(ne=1*(O.outboundAttractionDistribution?le:1),M=0;M<J;M+=S)_=H[M+u],B=H[M+d],v=H[M+h],Q=Math.pow(v,O.edgeWeightInfluence),se=w[_+e]-w[B+e],F=w[_+t]-w[B+t],X===!0?(U=Math.sqrt(se*se+F*F)-w[_+s]-w[B+s],O.linLogMode?O.outboundAttractionDistribution?U>0&&(q=-ne*Q*Math.log(1+U)/U/w[_+l]):U>0&&(q=-ne*Q*Math.log(1+U)/U):O.outboundAttractionDistribution?U>0&&(q=-ne*Q/w[_+l]):U>0&&(q=-ne*Q)):(U=Math.sqrt(Math.pow(se,2)+Math.pow(F,2)),O.linLogMode?O.outboundAttractionDistribution?U>0&&(q=-ne*Q*Math.log(1+U)/U/w[_+l]):U>0&&(q=-ne*Q*Math.log(1+U)/U):O.outboundAttractionDistribution?(U=1,q=-ne*Q/w[_+l]):(U=1,q=-ne*Q)),U>0&&(w[_+r]+=se*q,w[_+n]+=F*q,w[B+r]-=se*q,w[B+n]-=F*q);var de,me,Ie,ke,Te,ze;if(X===!0)for(C=0;C<$;C+=m)w[C+c]!==1&&(de=Math.sqrt(Math.pow(w[C+r],2)+Math.pow(w[C+n],2)),de>T&&(w[C+r]=w[C+r]*T/de,w[C+n]=w[C+n]*T/de),me=w[C+l]*Math.sqrt((w[C+a]-w[C+r])*(w[C+a]-w[C+r])+(w[C+o]-w[C+n])*(w[C+o]-w[C+n])),Ie=Math.sqrt((w[C+a]+w[C+r])*(w[C+a]+w[C+r])+(w[C+o]+w[C+n])*(w[C+o]+w[C+n]))/2,ke=.1*Math.log(1+Ie)/(1+Math.sqrt(me)),Te=w[C+e]+w[C+r]*(ke/O.slowDown),w[C+e]=Te,ze=w[C+t]+w[C+n]*(ke/O.slowDown),w[C+t]=ze);else for(C=0;C<$;C+=m)w[C+c]!==1&&(me=w[C+l]*Math.sqrt((w[C+a]-w[C+r])*(w[C+a]-w[C+r])+(w[C+o]-w[C+n])*(w[C+o]-w[C+n])),Ie=Math.sqrt((w[C+a]+w[C+r])*(w[C+a]+w[C+r])+(w[C+o]+w[C+n])*(w[C+o]+w[C+n]))/2,ke=w[C+i]*Math.log(1+Ie)/(1+Math.sqrt(me)),w[C+i]=Math.min(1,Math.sqrt(ke*(Math.pow(w[C+r],2)+Math.pow(w[C+n],2))/(1+Math.sqrt(me)))),Te=w[C+e]+w[C+r]*(ke/O.slowDown),w[C+e]=Te,ze=w[C+t]+w[C+n]*(ke/O.slowDown),w[C+t]=ze);return{}},kr}var Ue={},Co;function ms(){if(Co)return Ue;Co=1;var e=10,t=3;return Ue.assign=function(r){r=r||{};var n=Array.prototype.slice.call(arguments).slice(1),a,o,l;for(a=0,l=n.length;a<l;a++)if(n[a])for(o in n[a])r[o]=n[a][o];return r},Ue.validateSettings=function(r){return"linLogMode"in r&&typeof r.linLogMode!="boolean"?{message:"the `linLogMode` setting should be a boolean."}:"outboundAttractionDistribution"in r&&typeof r.outboundAttractionDistribution!="boolean"?{message:"the `outboundAttractionDistribution` setting should be a boolean."}:"adjustSizes"in r&&typeof r.adjustSizes!="boolean"?{message:"the `adjustSizes` setting should be a boolean."}:"edgeWeightInfluence"in r&&typeof r.edgeWeightInfluence!="number"?{message:"the `edgeWeightInfluence` setting should be a number."}:"scalingRatio"in r&&!(typeof r.scalingRatio=="number"&&r.scalingRatio>=0)?{message:"the `scalingRatio` setting should be a number >= 0."}:"strongGravityMode"in r&&typeof r.strongGravityMode!="boolean"?{message:"the `strongGravityMode` setting should be a boolean."}:"gravity"in r&&!(typeof r.gravity=="number"&&r.gravity>=0)?{message:"the `gravity` setting should be a number >= 0."}:"slowDown"in r&&!(typeof r.slowDown=="number"||r.slowDown>=0)?{message:"the `slowDown` setting should be a number >= 0."}:"barnesHutOptimize"in r&&typeof r.barnesHutOptimize!="boolean"?{message:"the `barnesHutOptimize` setting should be a boolean."}:"barnesHutTheta"in r&&!(typeof r.barnesHutTheta=="number"&&r.barnesHutTheta>=0)?{message:"the `barnesHutTheta` setting should be a number >= 0."}:null},Ue.graphToByteArrays=function(r,n){var a=r.order,o=r.size,l={},i,s=new Float32Array(a*e),c=new Float32Array(o*t);return i=0,r.forEachNode(function(u,d){l[u]=i,s[i]=d.x,s[i+1]=d.y,s[i+2]=0,s[i+3]=0,s[i+4]=0,s[i+5]=0,s[i+6]=1,s[i+7]=1,s[i+8]=d.size||1,s[i+9]=d.fixed?1:0,i+=e}),i=0,r.forEachEdge(function(u,d,h,f,b,y,k){var N=l[h],E=l[f],j=n(u,d,h,f,b,y,k);s[N+6]+=j,s[E+6]+=j,c[i]=N,c[i+1]=E,c[i+2]=j,i+=t}),{nodes:s,edges:c}},Ue.assignLayoutChanges=function(r,n,a){var o=0;r.updateEachNodeAttributes(function(l,i){return i.x=n[o],i.y=n[o+1],o+=e,a?a(l,i):i})},Ue.readGraphPositions=function(r,n){var a=0;r.forEachNode(function(o,l){n[a]=l.x,n[a+1]=l.y,a+=e})},Ue.collectLayoutChanges=function(r,n,a){for(var o=r.nodes(),l={},i=0,s=0,c=n.length;i<c;i+=e){if(a){var u=Object.assign({},r.getNodeAttributes(o[s]));u.x=n[i],u.y=n[i+1],u=a(o[s],u),l[o[s]]={x:u.x,y:u.y}}else l[o[s]]={x:n[i],y:n[i+1]};s++}return l},Ue.createWorker=function(n){var a=window.URL||window.webkitURL,o=n.toString(),l=a.createObjectURL(new Blob(["("+o+").call(this);"],{type:"text/javascript"})),i=new Worker(l);return a.revokeObjectURL(l),i},Ue}var Tr,ko;function vs(){return ko||(ko=1,Tr={linLogMode:!1,outboundAttractionDistribution:!1,adjustSizes:!1,edgeWeightInfluence:1,scalingRatio:1,strongGravityMode:!1,gravity:1,slowDown:1,barnesHutOptimize:!1,barnesHutTheta:.5}),Tr}var Rr,To;function tf(){if(To)return Rr;To=1;var e=We(),t=In().createEdgeWeightGetter,r=ef(),n=ms(),a=vs();function o(s,c,u){if(!e(c))throw new Error("graphology-layout-forceatlas2: the given graph is not a valid graphology instance.");typeof u=="number"&&(u={iterations:u});var d=u.iterations;if(typeof d!="number")throw new Error("graphology-layout-forceatlas2: invalid number of iterations.");if(d<=0)throw new Error("graphology-layout-forceatlas2: you should provide a positive number of iterations.");var h=t("getEdgeWeight"in u?u.getEdgeWeight:"weight").fromEntry,f=typeof u.outputReducer=="function"?u.outputReducer:null,b=n.assign({},a,u.settings),y=n.validateSettings(b);if(y)throw new Error("graphology-layout-forceatlas2: "+y.message);var k=n.graphToByteArrays(c,h),N;for(N=0;N<d;N++)r(b,k.nodes,k.edges);if(s){n.assignLayoutChanges(c,k.nodes,f);return}return n.collectLayoutChanges(c,k.nodes)}function l(s){var c=typeof s=="number"?s:s.order;return{barnesHutOptimize:c>2e3,strongGravityMode:!0,gravity:.05,scalingRatio:10,slowDown:1+Math.log(c)}}var i=o.bind(null,!1);return i.assign=o.bind(null,!0),i.inferSettings=l,Rr=i,Rr}var rf=tf();const nf=He(rf);var Ar,Ro;function of(){return Ro||(Ro=1,Ar=function(){var t,r,n={};(function(){var o=0,l=1,i=2,s=3,c=4,u=5,d=6,h=7,f=8,b=9,y=0,k=1,N=2,E=0,j=1,A=2,I=3,P=4,m=5,S=6,x=7,T=8,R=3,O=10,w=3,H=9,K=10;n.exports=function(C,_,B){var ae,M,v,z,V,$,J,X,Y,le,ne=_.length,se=B.length,F=C.adjustSizes,Q=C.barnesHutTheta*C.barnesHutTheta,U,q,L,oe,ue,re,ee,G=[];for(v=0;v<ne;v+=O)_[v+c]=_[v+i],_[v+u]=_[v+s],_[v+i]=0,_[v+s]=0;if(C.outboundAttractionDistribution){for(U=0,v=0;v<ne;v+=O)U+=_[v+d];U/=ne/O}if(C.barnesHutOptimize){var ge=1/0,pe=-1/0,ye=1/0,we=-1/0,de,me,Ie;for(v=0;v<ne;v+=O)ge=Math.min(ge,_[v+o]),pe=Math.max(pe,_[v+o]),ye=Math.min(ye,_[v+l]),we=Math.max(we,_[v+l]);var ke=pe-ge,Te=we-ye;for(ke>Te?(ye-=(ke-Te)/2,we=ye+ke):(ge-=(Te-ke)/2,pe=ge+Te),G[0+E]=-1,G[0+j]=(ge+pe)/2,G[0+A]=(ye+we)/2,G[0+I]=Math.max(pe-ge,we-ye),G[0+P]=-1,G[0+m]=-1,G[0+S]=0,G[0+x]=0,G[0+T]=0,ae=1,v=0;v<ne;v+=O)for(M=0,Ie=R;;)if(G[M+m]>=0){_[v+o]<G[M+j]?_[v+l]<G[M+A]?de=G[M+m]:de=G[M+m]+H:_[v+l]<G[M+A]?de=G[M+m]+H*2:de=G[M+m]+H*3,G[M+x]=(G[M+x]*G[M+S]+_[v+o]*_[v+d])/(G[M+S]+_[v+d]),G[M+T]=(G[M+T]*G[M+S]+_[v+l]*_[v+d])/(G[M+S]+_[v+d]),G[M+S]+=_[v+d],M=de;continue}else if(G[M+E]<0){G[M+E]=v;break}else{if(G[M+m]=ae*H,X=G[M+I]/2,Y=G[M+m],G[Y+E]=-1,G[Y+j]=G[M+j]-X,G[Y+A]=G[M+A]-X,G[Y+I]=X,G[Y+P]=Y+H,G[Y+m]=-1,G[Y+S]=0,G[Y+x]=0,G[Y+T]=0,Y+=H,G[Y+E]=-1,G[Y+j]=G[M+j]-X,G[Y+A]=G[M+A]+X,G[Y+I]=X,G[Y+P]=Y+H,G[Y+m]=-1,G[Y+S]=0,G[Y+x]=0,G[Y+T]=0,Y+=H,G[Y+E]=-1,G[Y+j]=G[M+j]+X,G[Y+A]=G[M+A]-X,G[Y+I]=X,G[Y+P]=Y+H,G[Y+m]=-1,G[Y+S]=0,G[Y+x]=0,G[Y+T]=0,Y+=H,G[Y+E]=-1,G[Y+j]=G[M+j]+X,G[Y+A]=G[M+A]+X,G[Y+I]=X,G[Y+P]=G[M+P],G[Y+m]=-1,G[Y+S]=0,G[Y+x]=0,G[Y+T]=0,ae+=4,_[G[M+E]+o]<G[M+j]?_[G[M+E]+l]<G[M+A]?de=G[M+m]:de=G[M+m]+H:_[G[M+E]+l]<G[M+A]?de=G[M+m]+H*2:de=G[M+m]+H*3,G[M+S]=_[G[M+E]+d],G[M+x]=_[G[M+E]+o],G[M+T]=_[G[M+E]+l],G[de+E]=G[M+E],G[M+E]=-1,_[v+o]<G[M+j]?_[v+l]<G[M+A]?me=G[M+m]:me=G[M+m]+H:_[v+l]<G[M+A]?me=G[M+m]+H*2:me=G[M+m]+H*3,de===me)if(Ie--){M=de;continue}else{Ie=R;break}G[me+E]=v;break}}if(C.barnesHutOptimize)for(q=C.scalingRatio,v=0;v<ne;v+=O)for(M=0;;)if(G[M+m]>=0)if(re=Math.pow(_[v+o]-G[M+x],2)+Math.pow(_[v+l]-G[M+T],2),le=G[M+I],4*le*le/re<Q){if(L=_[v+o]-G[M+x],oe=_[v+l]-G[M+T],F===!0?re>0?(ee=q*_[v+d]*G[M+S]/re,_[v+i]+=L*ee,_[v+s]+=oe*ee):re<0&&(ee=-q*_[v+d]*G[M+S]/Math.sqrt(re),_[v+i]+=L*ee,_[v+s]+=oe*ee):re>0&&(ee=q*_[v+d]*G[M+S]/re,_[v+i]+=L*ee,_[v+s]+=oe*ee),M=G[M+P],M<0)break;continue}else{M=G[M+m];continue}else{if($=G[M+E],$>=0&&$!==v&&(L=_[v+o]-_[$+o],oe=_[v+l]-_[$+l],re=L*L+oe*oe,F===!0?re>0?(ee=q*_[v+d]*_[$+d]/re,_[v+i]+=L*ee,_[v+s]+=oe*ee):re<0&&(ee=-q*_[v+d]*_[$+d]/Math.sqrt(re),_[v+i]+=L*ee,_[v+s]+=oe*ee):re>0&&(ee=q*_[v+d]*_[$+d]/re,_[v+i]+=L*ee,_[v+s]+=oe*ee)),M=G[M+P],M<0)break;continue}else for(q=C.scalingRatio,z=0;z<ne;z+=O)for(V=0;V<z;V+=O)L=_[z+o]-_[V+o],oe=_[z+l]-_[V+l],F===!0?(re=Math.sqrt(L*L+oe*oe)-_[z+f]-_[V+f],re>0?(ee=q*_[z+d]*_[V+d]/re/re,_[z+i]+=L*ee,_[z+s]+=oe*ee,_[V+i]-=L*ee,_[V+s]-=oe*ee):re<0&&(ee=100*q*_[z+d]*_[V+d],_[z+i]+=L*ee,_[z+s]+=oe*ee,_[V+i]-=L*ee,_[V+s]-=oe*ee)):(re=Math.sqrt(L*L+oe*oe),re>0&&(ee=q*_[z+d]*_[V+d]/re/re,_[z+i]+=L*ee,_[z+s]+=oe*ee,_[V+i]-=L*ee,_[V+s]-=oe*ee));for(Y=C.gravity/C.scalingRatio,q=C.scalingRatio,v=0;v<ne;v+=O)ee=0,L=_[v+o],oe=_[v+l],re=Math.sqrt(Math.pow(L,2)+Math.pow(oe,2)),C.strongGravityMode?re>0&&(ee=q*_[v+d]*Y):re>0&&(ee=q*_[v+d]*Y/re),_[v+i]-=L*ee,_[v+s]-=oe*ee;for(q=1*(C.outboundAttractionDistribution?U:1),J=0;J<se;J+=w)z=B[J+y],V=B[J+k],X=B[J+N],ue=Math.pow(X,C.edgeWeightInfluence),L=_[z+o]-_[V+o],oe=_[z+l]-_[V+l],F===!0?(re=Math.sqrt(L*L+oe*oe)-_[z+f]-_[V+f],C.linLogMode?C.outboundAttractionDistribution?re>0&&(ee=-q*ue*Math.log(1+re)/re/_[z+d]):re>0&&(ee=-q*ue*Math.log(1+re)/re):C.outboundAttractionDistribution?re>0&&(ee=-q*ue/_[z+d]):re>0&&(ee=-q*ue)):(re=Math.sqrt(Math.pow(L,2)+Math.pow(oe,2)),C.linLogMode?C.outboundAttractionDistribution?re>0&&(ee=-q*ue*Math.log(1+re)/re/_[z+d]):re>0&&(ee=-q*ue*Math.log(1+re)/re):C.outboundAttractionDistribution?(re=1,ee=-q*ue/_[z+d]):(re=1,ee=-q*ue)),re>0&&(_[z+i]+=L*ee,_[z+s]+=oe*ee,_[V+i]-=L*ee,_[V+s]-=oe*ee);var ze,Ye,Ke,Re,st,Pe;if(F===!0)for(v=0;v<ne;v+=O)_[v+b]!==1&&(ze=Math.sqrt(Math.pow(_[v+i],2)+Math.pow(_[v+s],2)),ze>K&&(_[v+i]=_[v+i]*K/ze,_[v+s]=_[v+s]*K/ze),Ye=_[v+d]*Math.sqrt((_[v+c]-_[v+i])*(_[v+c]-_[v+i])+(_[v+u]-_[v+s])*(_[v+u]-_[v+s])),Ke=Math.sqrt((_[v+c]+_[v+i])*(_[v+c]+_[v+i])+(_[v+u]+_[v+s])*(_[v+u]+_[v+s]))/2,Re=.1*Math.log(1+Ke)/(1+Math.sqrt(Ye)),st=_[v+o]+_[v+i]*(Re/C.slowDown),_[v+o]=st,Pe=_[v+l]+_[v+s]*(Re/C.slowDown),_[v+l]=Pe);else for(v=0;v<ne;v+=O)_[v+b]!==1&&(Ye=_[v+d]*Math.sqrt((_[v+c]-_[v+i])*(_[v+c]-_[v+i])+(_[v+u]-_[v+s])*(_[v+u]-_[v+s])),Ke=Math.sqrt((_[v+c]+_[v+i])*(_[v+c]+_[v+i])+(_[v+u]+_[v+s])*(_[v+u]+_[v+s]))/2,Re=_[v+h]*Math.log(1+Ke)/(1+Math.sqrt(Ye)),_[v+h]=Math.min(1,Math.sqrt(Re*(Math.pow(_[v+i],2)+Math.pow(_[v+s],2))/(1+Math.sqrt(Ye)))),st=_[v+o]+_[v+i]*(Re/C.slowDown),_[v+o]=st,Pe=_[v+l]+_[v+s]*(Re/C.slowDown),_[v+l]=Pe);return{}}})();var a=n.exports;self.addEventListener("message",function(o){var l=o.data;t=new Float32Array(l.nodes),l.edges&&(r=new Float32Array(l.edges)),a(l.settings,t,r),self.postMessage({nodes:t.buffer},[t.buffer])})}),Ar}var jr,Ao;function af(){if(Ao)return jr;Ao=1;var e=of(),t=We(),r=In().createEdgeWeightGetter,n=ms(),a=vs();function o(l,i){if(i=i||{},!t(l))throw new Error("graphology-layout-forceatlas2/worker: the given graph is not a valid graphology instance.");var s=r("getEdgeWeight"in i?i.getEdgeWeight:"weight").fromEntry,c=n.assign({},a,i.settings),u=n.validateSettings(c);if(u)throw new Error("graphology-layout-forceatlas2/worker: "+u.message);this.worker=null,this.graph=l,this.settings=c,this.getEdgeWeight=s,this.matrices=null,this.running=!1,this.killed=!1,this.outputReducer=typeof i.outputReducer=="function"?i.outputReducer:null,this.handleMessage=this.handleMessage.bind(this);var d=void 0,h=this;this.handleGraphUpdate=function(){h.worker&&h.worker.terminate(),d&&clearTimeout(d),d=setTimeout(function(){d=void 0,h.spawnWorker()},0)},l.on("nodeAdded",this.handleGraphUpdate),l.on("edgeAdded",this.handleGraphUpdate),l.on("nodeDropped",this.handleGraphUpdate),l.on("edgeDropped",this.handleGraphUpdate),this.spawnWorker()}return o.prototype.isRunning=function(){return this.running},o.prototype.spawnWorker=function(){this.worker&&this.worker.terminate(),this.worker=n.createWorker(e),this.worker.addEventListener("message",this.handleMessage),this.running&&(this.running=!1,this.start())},o.prototype.handleMessage=function(l){if(this.running){var i=new Float32Array(l.data.nodes);n.assignLayoutChanges(this.graph,i,this.outputReducer),this.outputReducer&&n.readGraphPositions(this.graph,i),this.matrices.nodes=i,this.askForIterations()}},o.prototype.askForIterations=function(l){var i=this.matrices,s={settings:this.settings,nodes:i.nodes.buffer},c=[i.nodes.buffer];return l&&(s.edges=i.edges.buffer,c.push(i.edges.buffer)),this.worker.postMessage(s,c),this},o.prototype.start=function(){if(this.killed)throw new Error("graphology-layout-forceatlas2/worker.start: layout was killed.");return this.running?this:(this.matrices=n.graphToByteArrays(this.graph,this.getEdgeWeight),this.running=!0,this.askForIterations(!0),this)},o.prototype.stop=function(){return this.running=!1,this},o.prototype.kill=function(){if(this.killed)return this;this.running=!1,this.killed=!0,this.matrices=null,this.worker.terminate(),this.graph.removeListener("nodeAdded",this.handleGraphUpdate),this.graph.removeListener("edgeAdded",this.handleGraphUpdate),this.graph.removeListener("nodeDropped",this.handleGraphUpdate),this.graph.removeListener("edgeDropped",this.handleGraphUpdate)},jr=o,jr}var sf=af();const lf=He(sf);function ys(e={iterations:100}){return St(nf,e)}function cf(e={}){return jn(lf,e)}var Ir,jo;function uf(){if(jo)return Ir;jo=1;var e=0,t=1,r=2,n=3;function a(l,i){return l+"§"+i}function o(){return .01*(.5-Math.random())}return Ir=function(i,s){var c=i.margin,u=i.ratio,d=i.expansion,h=i.gridSize,f=i.speed,b,y,k,N,E,j,A=!0,I=s.length,P=I/n|0,m=new Float32Array(P),S=new Float32Array(P),x=1/0,T=1/0,R=-1/0,O=-1/0;for(b=0;b<I;b+=n)k=s[b+e],N=s[b+t],j=s[b+r]*u+c,x=Math.min(x,k-j),R=Math.max(R,k+j),T=Math.min(T,N-j),O=Math.max(O,N+j);var w=R-x,H=O-T,K=(x+R)/2,D=(T+O)/2;x=K-d*w/2,R=K+d*w/2,T=D-d*H/2,O=D+d*H/2;var C=new Array(h*h),_=C.length,B;for(B=0;B<_;B++)C[B]=[];var ae,M,v,z,V,$,J,X,Y,le;for(b=0;b<I;b+=n)for(k=s[b+e],N=s[b+t],j=s[b+r]*u+c,ae=k-j,M=k+j,v=N-j,z=N+j,V=Math.floor(h*(ae-x)/(R-x)),$=Math.floor(h*(M-x)/(R-x)),J=Math.floor(h*(v-T)/(O-T)),X=Math.floor(h*(z-T)/(O-T)),Y=V;Y<=$;Y++)for(le=J;le<=X;le++)C[Y*h+le].push(b);var ne,se=new Set,F,Q,U,q,L,oe,ue,re,ee,G,ge,pe,ye;for(B=0;B<_;B++)for(ne=C[B],b=0,E=ne.length;b<E;b++)for(F=ne[b],U=s[F+e],L=s[F+t],ue=s[F+r],y=b+1;y<E;y++)Q=ne[y],ee=a(F,Q),!(_>1&&se.has(ee))&&(_>1&&se.add(ee),q=s[Q+e],oe=s[Q+t],re=s[Q+r],G=q-U,ge=oe-L,pe=Math.sqrt(G*G+ge*ge),ye=pe<ue*u+c+(re*u+c),ye&&(A=!1,Q=Q/n|0,pe>0?(m[Q]+=G/pe*(1+ue),S[Q]+=ge/pe*(1+ue)):(m[Q]+=w*o(),S[Q]+=H*o())));for(b=0,y=0;b<I;b+=n,y++)s[b+e]+=m[y]*.1*f,s[b+t]+=S[y]*.1*f;return{converged:A}},Ir}var lt={},Io;function bs(){if(Io)return lt;Io=1;var e=3;return lt.validateSettings=function(t){return"gridSize"in t&&typeof t.gridSize!="number"||t.gridSize<=0?{message:"the `gridSize` setting should be a positive number."}:"margin"in t&&typeof t.margin!="number"||t.margin<0?{message:"the `margin` setting should be 0 or a positive number."}:"expansion"in t&&typeof t.expansion!="number"||t.expansion<=0?{message:"the `expansion` setting should be a positive number."}:"ratio"in t&&typeof t.ratio!="number"||t.ratio<=0?{message:"the 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Lr,Lo;function df(){if(Lo)return Lr;Lo=1;var e=We(),t=uf(),r=bs(),n=ws(),a=500;function o(i,s,c){if(!e(s))throw new Error("graphology-layout-noverlap: the given graph is not a valid graphology instance.");typeof c=="number"?c={maxIterations:c}:c=c||{};var u=c.maxIterations||a;if(typeof u!="number"||u<=0)throw new Error("graphology-layout-force: you should provide a positive number of maximum iterations.");var d=Object.assign({},n,c.settings),h=r.validateSettings(d);if(h)throw new Error("graphology-layout-noverlap: "+h.message);var f=r.graphToByteArray(s,c.inputReducer),b=!1,y;for(y=0;y<u&&!b;y++)b=t(d,f).converged;if(i){r.assignLayoutChanges(s,f,c.outputReducer);return}return r.collectLayoutChanges(s,f,c.outputReducer)}var l=o.bind(null,!1);return l.assign=o.bind(null,!0),Lr=l,Lr}var ff=df();const hf=He(ff);var zr,zo;function gf(){return zo||(zo=1,zr=function(){var t,r={};(function(){var a=0,o=1,l=2,i=3;function s(u,d){return u+"§"+d}function c(){return 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Set,L,oe,ue,re,ee,G,ge,pe,ye,we,de,me,Ie;for(z=0;z<v;z++)for(U=M[z],E=0,P=U.length;E<P;E++)for(L=U[E],ue=h[L+a],ee=h[L+o],ge=h[L+l],j=E+1;j<P;j++)oe=U[j],ye=s(L,oe),!(v>1&&q.has(ye))&&(v>1&&q.add(ye),re=h[oe+a],G=h[oe+o],pe=h[oe+l],we=re-ue,de=G-ee,me=Math.sqrt(we*we+de*de),Ie=me<ge*b+f+(pe*b+f),Ie&&(S=!1,oe=oe/i|0,me>0?(R[oe]+=we/me*(1+ge),O[oe]+=de/me*(1+ge)):(R[oe]+=C*c(),O[oe]+=_*c())));for(E=0,j=0;E<x;E+=i,j++)h[E+a]+=R[j]*.1*N,h[E+o]+=O[j]*.1*N;return{converged:S}}})();var n=r.exports;self.addEventListener("message",function(a){var o=a.data;t=new Float32Array(o.nodes);var l=n(o.settings,t);self.postMessage({result:l,nodes:t.buffer},[t.buffer])})}),zr}var Pr,Po;function pf(){if(Po)return Pr;Po=1;var e=gf(),t=We(),r=bs(),n=ws();function a(o,l){if(l=l||{},!t(o))throw new Error("graphology-layout-noverlap/worker: the given graph is not a valid graphology instance.");var i=Object.assign({},n,l.settings),s=r.validateSettings(i);if(s)throw new Error("graphology-layout-noverlap/worker: "+s.message);this.worker=null,this.graph=o,this.settings=i,this.matrices=null,this.running=!1,this.killed=!1,this.inputReducer=l.inputReducer,this.outputReducer=l.outputReducer,this.callbacks={onConverged:typeof l.onConverged=="function"?l.onConverged:null},this.handleMessage=this.handleMessage.bind(this);var c=!1,u=this;this.handleAddition=function(){c||(c=!0,u.spawnWorker(),setTimeout(function(){c=!1},0))},o.on("nodeAdded",this.handleAddition),o.on("edgeAdded",this.handleAddition),this.spawnWorker()}return a.prototype.isRunning=function(){return this.running},a.prototype.spawnWorker=function(){this.worker&&this.worker.terminate(),this.worker=r.createWorker(e),this.worker.addEventListener("message",this.handleMessage),this.running&&(this.running=!1,this.start())},a.prototype.handleMessage=function(o){if(this.running){var l=new 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i.assign=o.bind(null,!0),i.inferSettings=l,Rr=i,Rr}var rf=tf();const nf=He(rf);var Ar,Ro;function of(){return Ro||(Ro=1,Ar=function(){var t,r,n={};(function(){var o=0,l=1,i=2,s=3,c=4,u=5,d=6,h=7,f=8,b=9,y=0,k=1,N=2,E=0,j=1,A=2,I=3,P=4,m=5,S=6,x=7,T=8,R=3,O=10,w=3,H=9,K=10;n.exports=function(C,_,B){var se,M,v,z,V,$,Q,W,Y,ie,ne=_.length,ae=B.length,F=C.adjustSizes,J=C.barnesHutTheta*C.barnesHutTheta,U,q,L,oe,ue,re,ee,G=[];for(v=0;v<ne;v+=O)_[v+c]=_[v+i],_[v+u]=_[v+s],_[v+i]=0,_[v+s]=0;if(C.outboundAttractionDistribution){for(U=0,v=0;v<ne;v+=O)U+=_[v+d];U/=ne/O}if(C.barnesHutOptimize){var ge=1/0,pe=-1/0,ye=1/0,we=-1/0,de,me,Ie;for(v=0;v<ne;v+=O)ge=Math.min(ge,_[v+o]),pe=Math.max(pe,_[v+o]),ye=Math.min(ye,_[v+l]),we=Math.max(we,_[v+l]);var 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if(G[M+E]<0){G[M+E]=v;break}else{if(G[M+m]=se*H,W=G[M+I]/2,Y=G[M+m],G[Y+E]=-1,G[Y+j]=G[M+j]-W,G[Y+A]=G[M+A]-W,G[Y+I]=W,G[Y+P]=Y+H,G[Y+m]=-1,G[Y+S]=0,G[Y+x]=0,G[Y+T]=0,Y+=H,G[Y+E]=-1,G[Y+j]=G[M+j]-W,G[Y+A]=G[M+A]+W,G[Y+I]=W,G[Y+P]=Y+H,G[Y+m]=-1,G[Y+S]=0,G[Y+x]=0,G[Y+T]=0,Y+=H,G[Y+E]=-1,G[Y+j]=G[M+j]+W,G[Y+A]=G[M+A]-W,G[Y+I]=W,G[Y+P]=Y+H,G[Y+m]=-1,G[Y+S]=0,G[Y+x]=0,G[Y+T]=0,Y+=H,G[Y+E]=-1,G[Y+j]=G[M+j]+W,G[Y+A]=G[M+A]+W,G[Y+I]=W,G[Y+P]=G[M+P],G[Y+m]=-1,G[Y+S]=0,G[Y+x]=0,G[Y+T]=0,se+=4,_[G[M+E]+o]<G[M+j]?_[G[M+E]+l]<G[M+A]?de=G[M+m]:de=G[M+m]+H:_[G[M+E]+l]<G[M+A]?de=G[M+m]+H*2:de=G[M+m]+H*3,G[M+S]=_[G[M+E]+d],G[M+x]=_[G[M+E]+o],G[M+T]=_[G[M+E]+l],G[de+E]=G[M+E],G[M+E]=-1,_[v+o]<G[M+j]?_[v+l]<G[M+A]?me=G[M+m]:me=G[M+m]+H:_[v+l]<G[M+A]?me=G[M+m]+H*2:me=G[M+m]+H*3,de===me)if(Ie--){M=de;continue}else{Ie=R;break}G[me+E]=v;break}}if(C.barnesHutOptimize)for(q=C.scalingRatio,v=0;v<ne;v+=O)for(M=0;;)if(G[M+m]>=0)if(re=Math.pow(_[v+o]-G[M+x],2)+Math.pow(_[v+l]-G[M+T],2),ie=G[M+I],4*ie*ie/re<J){if(L=_[v+o]-G[M+x],oe=_[v+l]-G[M+T],F===!0?re>0?(ee=q*_[v+d]*G[M+S]/re,_[v+i]+=L*ee,_[v+s]+=oe*ee):re<0&&(ee=-q*_[v+d]*G[M+S]/Math.sqrt(re),_[v+i]+=L*ee,_[v+s]+=oe*ee):re>0&&(ee=q*_[v+d]*G[M+S]/re,_[v+i]+=L*ee,_[v+s]+=oe*ee),M=G[M+P],M<0)break;continue}else{M=G[M+m];continue}else{if($=G[M+E],$>=0&&$!==v&&(L=_[v+o]-_[$+o],oe=_[v+l]-_[$+l],re=L*L+oe*oe,F===!0?re>0?(ee=q*_[v+d]*_[$+d]/re,_[v+i]+=L*ee,_[v+s]+=oe*ee):re<0&&(ee=-q*_[v+d]*_[$+d]/Math.sqrt(re),_[v+i]+=L*ee,_[v+s]+=oe*ee):re>0&&(ee=q*_[v+d]*_[$+d]/re,_[v+i]+=L*ee,_[v+s]+=oe*ee)),M=G[M+P],M<0)break;continue}else for(q=C.scalingRatio,z=0;z<ne;z+=O)for(V=0;V<z;V+=O)L=_[z+o]-_[V+o],oe=_[z+l]-_[V+l],F===!0?(re=Math.sqrt(L*L+oe*oe)-_[z+f]-_[V+f],re>0?(ee=q*_[z+d]*_[V+d]/re/re,_[z+i]+=L*ee,_[z+s]+=oe*ee,_[V+i]-=L*ee,_[V+s]-=oe*ee):re<0&&(ee=100*q*_[z+d]*_[V+d],_[z+i]+=L*ee,_[z+s]+=oe*ee,_[V+i]-=L*ee,_[V+s]-=oe*ee)):(re=Math.sqrt(L*L+oe*oe),re>0&&(ee=q*_[z+d]*_[V+d]/re/re,_[z+i]+=L*ee,_[z+s]+=oe*ee,_[V+i]-=L*ee,_[V+s]-=oe*ee));for(Y=C.gravity/C.scalingRatio,q=C.scalingRatio,v=0;v<ne;v+=O)ee=0,L=_[v+o],oe=_[v+l],re=Math.sqrt(Math.pow(L,2)+Math.pow(oe,2)),C.strongGravityMode?re>0&&(ee=q*_[v+d]*Y):re>0&&(ee=q*_[v+d]*Y/re),_[v+i]-=L*ee,_[v+s]-=oe*ee;for(q=1*(C.outboundAttractionDistribution?U:1),Q=0;Q<ae;Q+=w)z=B[Q+y],V=B[Q+k],W=B[Q+N],ue=Math.pow(W,C.edgeWeightInfluence),L=_[z+o]-_[V+o],oe=_[z+l]-_[V+l],F===!0?(re=Math.sqrt(L*L+oe*oe)-_[z+f]-_[V+f],C.linLogMode?C.outboundAttractionDistribution?re>0&&(ee=-q*ue*Math.log(1+re)/re/_[z+d]):re>0&&(ee=-q*ue*Math.log(1+re)/re):C.outboundAttractionDistribution?re>0&&(ee=-q*ue/_[z+d]):re>0&&(ee=-q*ue)):(re=Math.sqrt(Math.pow(L,2)+Math.pow(oe,2)),C.linLogMode?C.outboundAttractionDistribution?re>0&&(ee=-q*ue*Math.log(1+re)/re/_[z+d]):re>0&&(ee=-q*ue*Math.log(1+re)/re):C.outboundAttractionDistribution?(re=1,ee=-q*ue/_[z+d]):(re=1,ee=-q*ue)),re>0&&(_[z+i]+=L*ee,_[z+s]+=oe*ee,_[V+i]-=L*ee,_[V+s]-=oe*ee);var ze,Ye,Ke,Re,st,Pe;if(F===!0)for(v=0;v<ne;v+=O)_[v+b]!==1&&(ze=Math.sqrt(Math.pow(_[v+i],2)+Math.pow(_[v+s],2)),ze>K&&(_[v+i]=_[v+i]*K/ze,_[v+s]=_[v+s]*K/ze),Ye=_[v+d]*Math.sqrt((_[v+c]-_[v+i])*(_[v+c]-_[v+i])+(_[v+u]-_[v+s])*(_[v+u]-_[v+s])),Ke=Math.sqrt((_[v+c]+_[v+i])*(_[v+c]+_[v+i])+(_[v+u]+_[v+s])*(_[v+u]+_[v+s]))/2,Re=.1*Math.log(1+Ke)/(1+Math.sqrt(Ye)),st=_[v+o]+_[v+i]*(Re/C.slowDown),_[v+o]=st,Pe=_[v+l]+_[v+s]*(Re/C.slowDown),_[v+l]=Pe);else for(v=0;v<ne;v+=O)_[v+b]!==1&&(Ye=_[v+d]*Math.sqrt((_[v+c]-_[v+i])*(_[v+c]-_[v+i])+(_[v+u]-_[v+s])*(_[v+u]-_[v+s])),Ke=Math.sqrt((_[v+c]+_[v+i])*(_[v+c]+_[v+i])+(_[v+u]+_[v+s])*(_[v+u]+_[v+s]))/2,Re=_[v+h]*Math.log(1+Ke)/(1+Math.sqrt(Ye)),_[v+h]=Math.min(1,Math.sqrt(Re*(Math.pow(_[v+i],2)+Math.pow(_[v+s],2))/(1+Math.sqrt(Ye)))),st=_[v+o]+_[v+i]*(Re/C.slowDown),_[v+o]=st,Pe=_[v+l]+_[v+s]*(Re/C.slowDown),_[v+l]=Pe);return{}}})();var a=n.exports;self.addEventListener("message",function(o){var l=o.data;t=new Float32Array(l.nodes),l.edges&&(r=new Float32Array(l.edges)),a(l.settings,t,r),self.postMessage({nodes:t.buffer},[t.buffer])})}),Ar}var jr,Ao;function af(){if(Ao)return jr;Ao=1;var e=of(),t=We(),r=In().createEdgeWeightGetter,n=ms(),a=vs();function o(l,i){if(i=i||{},!t(l))throw new Error("graphology-layout-forceatlas2/worker: the given graph is not a valid graphology instance.");var s=r("getEdgeWeight"in i?i.getEdgeWeight:"weight").fromEntry,c=n.assign({},a,i.settings),u=n.validateSettings(c);if(u)throw new Error("graphology-layout-forceatlas2/worker: "+u.message);this.worker=null,this.graph=l,this.settings=c,this.getEdgeWeight=s,this.matrices=null,this.running=!1,this.killed=!1,this.outputReducer=typeof i.outputReducer=="function"?i.outputReducer:null,this.handleMessage=this.handleMessage.bind(this);var d=void 0,h=this;this.handleGraphUpdate=function(){h.worker&&h.worker.terminate(),d&&clearTimeout(d),d=setTimeout(function(){d=void 0,h.spawnWorker()},0)},l.on("nodeAdded",this.handleGraphUpdate),l.on("edgeAdded",this.handleGraphUpdate),l.on("nodeDropped",this.handleGraphUpdate),l.on("edgeDropped",this.handleGraphUpdate),this.spawnWorker()}return o.prototype.isRunning=function(){return this.running},o.prototype.spawnWorker=function(){this.worker&&this.worker.terminate(),this.worker=n.createWorker(e),this.worker.addEventListener("message",this.handleMessage),this.running&&(this.running=!1,this.start())},o.prototype.handleMessage=function(l){if(this.running){var i=new Float32Array(l.data.nodes);n.assignLayoutChanges(this.graph,i,this.outputReducer),this.outputReducer&&n.readGraphPositions(this.graph,i),this.matrices.nodes=i,this.askForIterations()}},o.prototype.askForIterations=function(l){var i=this.matrices,s={settings:this.settings,nodes:i.nodes.buffer},c=[i.nodes.buffer];return l&&(s.edges=i.edges.buffer,c.push(i.edges.buffer)),this.worker.postMessage(s,c),this},o.prototype.start=function(){if(this.killed)throw new Error("graphology-layout-forceatlas2/worker.start: layout was killed.");return this.running?this:(this.matrices=n.graphToByteArrays(this.graph,this.getEdgeWeight),this.running=!0,this.askForIterations(!0),this)},o.prototype.stop=function(){return this.running=!1,this},o.prototype.kill=function(){if(this.killed)return this;this.running=!1,this.killed=!0,this.matrices=null,this.worker.terminate(),this.graph.removeListener("nodeAdded",this.handleGraphUpdate),this.graph.removeListener("edgeAdded",this.handleGraphUpdate),this.graph.removeListener("nodeDropped",this.handleGraphUpdate),this.graph.removeListener("edgeDropped",this.handleGraphUpdate)},jr=o,jr}var sf=af();const lf=He(sf);function ys(e={iterations:100}){return St(nf,e)}function cf(e={}){return jn(lf,e)}var Ir,jo;function uf(){if(jo)return Ir;jo=1;var e=0,t=1,r=2,n=3;function a(l,i){return l+"§"+i}function o(){return .01*(.5-Math.random())}return Ir=function(i,s){var c=i.margin,u=i.ratio,d=i.expansion,h=i.gridSize,f=i.speed,b,y,k,N,E,j,A=!0,I=s.length,P=I/n|0,m=new Float32Array(P),S=new Float32Array(P),x=1/0,T=1/0,R=-1/0,O=-1/0;for(b=0;b<I;b+=n)k=s[b+e],N=s[b+t],j=s[b+r]*u+c,x=Math.min(x,k-j),R=Math.max(R,k+j),T=Math.min(T,N-j),O=Math.max(O,N+j);var w=R-x,H=O-T,K=(x+R)/2,D=(T+O)/2;x=K-d*w/2,R=K+d*w/2,T=D-d*H/2,O=D+d*H/2;var C=new Array(h*h),_=C.length,B;for(B=0;B<_;B++)C[B]=[];var se,M,v,z,V,$,Q,W,Y,ie;for(b=0;b<I;b+=n)for(k=s[b+e],N=s[b+t],j=s[b+r]*u+c,se=k-j,M=k+j,v=N-j,z=N+j,V=Math.floor(h*(se-x)/(R-x)),$=Math.floor(h*(M-x)/(R-x)),Q=Math.floor(h*(v-T)/(O-T)),W=Math.floor(h*(z-T)/(O-T)),Y=V;Y<=$;Y++)for(ie=Q;ie<=W;ie++)C[Y*h+ie].push(b);var ne,ae=new Set,F,J,U,q,L,oe,ue,re,ee,G,ge,pe,ye;for(B=0;B<_;B++)for(ne=C[B],b=0,E=ne.length;b<E;b++)for(F=ne[b],U=s[F+e],L=s[F+t],ue=s[F+r],y=b+1;y<E;y++)J=ne[y],ee=a(F,J),!(_>1&&ae.has(ee))&&(_>1&&ae.add(ee),q=s[J+e],oe=s[J+t],re=s[J+r],G=q-U,ge=oe-L,pe=Math.sqrt(G*G+ge*ge),ye=pe<ue*u+c+(re*u+c),ye&&(A=!1,J=J/n|0,pe>0?(m[J]+=G/pe*(1+ue),S[J]+=ge/pe*(1+ue)):(m[J]+=w*o(),S[J]+=H*o())));for(b=0,y=0;b<I;b+=n,y++)s[b+e]+=m[y]*.1*f,s[b+t]+=S[y]*.1*f;return{converged:A}},Ir}var lt={},Io;function bs(){if(Io)return lt;Io=1;var e=3;return lt.validateSettings=function(t){return"gridSize"in t&&typeof t.gridSize!="number"||t.gridSize<=0?{message:"the `gridSize` setting should be a positive number."}:"margin"in t&&typeof t.margin!="number"||t.margin<0?{message:"the `margin` setting should be 0 or a positive number."}:"expansion"in t&&typeof t.expansion!="number"||t.expansion<=0?{message:"the `expansion` setting should be a positive number."}:"ratio"in t&&typeof t.ratio!="number"||t.ratio<=0?{message:"the `ratio` setting should be a positive number."}:"speed"in t&&typeof t.speed!="number"||t.speed<=0?{message:"the `speed` setting should be a positive number."}:null},lt.graphToByteArray=function(t,r){var n=t.order,a=new Float32Array(n*e),o=0;return t.forEachNode(function(l,i){typeof r=="function"&&(i=r(l,i)),a[o]=i.x,a[o+1]=i.y,a[o+2]=i.size||1,o+=e}),a},lt.assignLayoutChanges=function(t,r,n){var a=0;t.forEachNode(function(o){var l={x:r[a],y:r[a+1]};typeof n=="function"&&(l=n(o,l)),t.mergeNodeAttributes(o,l),a+=e})},lt.collectLayoutChanges=function(t,r,n){var a={},o=0;return t.forEachNode(function(l){var i={x:r[o],y:r[o+1]};typeof n=="function"&&(i=n(l,i)),a[l]=i,o+=e}),a},lt.createWorker=function(r){var n=window.URL||window.webkitURL,a=r.toString(),o=n.createObjectURL(new Blob(["("+a+").call(this);"],{type:"text/javascript"})),l=new Worker(o);return n.revokeObjectURL(o),l},lt}var Nr,No;function ws(){return No||(No=1,Nr={gridSize:20,margin:5,expansion:1.1,ratio:1,speed:3}),Nr}var Lr,Lo;function df(){if(Lo)return Lr;Lo=1;var e=We(),t=uf(),r=bs(),n=ws(),a=500;function o(i,s,c){if(!e(s))throw new Error("graphology-layout-noverlap: the given graph is not a valid graphology instance.");typeof c=="number"?c={maxIterations:c}:c=c||{};var u=c.maxIterations||a;if(typeof u!="number"||u<=0)throw new Error("graphology-layout-force: you should provide a positive number of maximum iterations.");var d=Object.assign({},n,c.settings),h=r.validateSettings(d);if(h)throw new Error("graphology-layout-noverlap: "+h.message);var f=r.graphToByteArray(s,c.inputReducer),b=!1,y;for(y=0;y<u&&!b;y++)b=t(d,f).converged;if(i){r.assignLayoutChanges(s,f,c.outputReducer);return}return r.collectLayoutChanges(s,f,c.outputReducer)}var l=o.bind(null,!1);return l.assign=o.bind(null,!0),Lr=l,Lr}var ff=df();const hf=He(ff);var zr,zo;function gf(){return zo||(zo=1,zr=function(){var t,r={};(function(){var a=0,o=1,l=2,i=3;function s(u,d){return u+"§"+d}function c(){return 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Set,L,oe,ue,re,ee,G,ge,pe,ye,we,de,me,Ie;for(z=0;z<v;z++)for(U=M[z],E=0,P=U.length;E<P;E++)for(L=U[E],ue=h[L+a],ee=h[L+o],ge=h[L+l],j=E+1;j<P;j++)oe=U[j],ye=s(L,oe),!(v>1&&q.has(ye))&&(v>1&&q.add(ye),re=h[oe+a],G=h[oe+o],pe=h[oe+l],we=re-ue,de=G-ee,me=Math.sqrt(we*we+de*de),Ie=me<ge*b+f+(pe*b+f),Ie&&(S=!1,oe=oe/i|0,me>0?(R[oe]+=we/me*(1+ge),O[oe]+=de/me*(1+ge)):(R[oe]+=C*c(),O[oe]+=_*c())));for(E=0,j=0;E<x;E+=i,j++)h[E+a]+=R[j]*.1*N,h[E+o]+=O[j]*.1*N;return{converged:S}}})();var n=r.exports;self.addEventListener("message",function(a){var o=a.data;t=new Float32Array(o.nodes);var l=n(o.settings,t);self.postMessage({result:l,nodes:t.buffer},[t.buffer])})}),zr}var Pr,Po;function pf(){if(Po)return Pr;Po=1;var e=gf(),t=We(),r=bs(),n=ws();function a(o,l){if(l=l||{},!t(o))throw new Error("graphology-layout-noverlap/worker: the given graph is not a valid graphology instance.");var i=Object.assign({},n,l.settings),s=r.validateSettings(i);if(s)throw new Error("graphology-layout-noverlap/worker: 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pn(e.get(r),t.slice(r.length))},Vr=(e,t)=>{const r=t.length;e:for(let n=0;e&&n<r;){for(const o of e.keys())if(o!==Se&&t[n]===o[0]){const l=Math.min(r-n,o.length);let i=1;for(;i<l&&t[n+i]===o[i];)++i;const s=e.get(o);if(i===o.length)e=s;else{const c=new Map;c.set(o.slice(i),s),e.set(t.slice(n,n+i),c),e.delete(o),e=c}n+=i;continue e}const a=new Map;return e.set(t.slice(n),a),a}return e},ph=(e,t)=>{const[r,n]=Qt(e,t);if(r!==void 0){if(r.delete(Se),r.size===0)Fs(n);else if(r.size===1){const[a,o]=r.entries().next().value;Ms(n,a,o)}}},Fs=e=>{if(e.length===0)return;const[t,r]=On(e);if(t.delete(r),t.size===0)Fs(e.slice(0,-1));else if(t.size===1){const[n,a]=t.entries().next().value;n!==Se&&Ms(e.slice(0,-1),n,a)}},Ms=(e,t,r)=>{if(e.length===0)return;const[n,a]=On(e);n.set(a+t,r),n.delete(a)},On=e=>e[e.length-1],Gn="or",$s="and",mh="and_not";class at{constructor(t){if((t==null?void 0:t.fields)==null)throw new Error('MiniSearch: option "fields" must be provided');const r=t.autoVacuum==null||t.autoVacuum===!0?Wr:t.autoVacuum;this._options={...Ur,...t,autoVacuum:r,searchOptions:{...Bo,...t.searchOptions||{}},autoSuggestOptions:{...xh,...t.autoSuggestOptions||{}}},this._index=new nt,this._documentCount=0,this._documentIds=new Map,this._idToShortId=new Map,this._fieldIds={},this._fieldLength=new Map,this._avgFieldLength=[],this._nextId=0,this._storedFields=new Map,this._dirtCount=0,this._currentVacuum=null,this._enqueuedVacuum=null,this._enqueuedVacuumConditions=vn,this.addFields(this._options.fields)}add(t){const{extractField:r,tokenize:n,processTerm:a,fields:o,idField:l}=this._options,i=r(t,l);if(i==null)throw new Error(`MiniSearch: document does not have ID field "${l}"`);if(this._idToShortId.has(i))throw new Error(`MiniSearch: duplicate ID ${i}`);const s=this.addDocumentId(i);this.saveStoredFields(s,t);for(const c of o){const u=r(t,c);if(u==null)continue;const d=n(u.toString(),c),h=this._fieldIds[c],f=new Set(d).size;this.addFieldLength(s,h,this._documentCount-1,f);for(const b of d){const y=a(b,c);if(Array.isArray(y))for(const k of y)this.addTerm(h,s,k);else y&&this.addTerm(h,s,y)}}}addAll(t){for(const r of t)this.add(r)}addAllAsync(t,r={}){const{chunkSize:n=10}=r,a={chunk:[],promise:Promise.resolve()},{chunk:o,promise:l}=t.reduce(({chunk:i,promise:s},c,u)=>(i.push(c),(u+1)%n===0?{chunk:[],promise:s.then(()=>new Promise(d=>setTimeout(d,0))).then(()=>this.addAll(i))}:{chunk:i,promise:s}),a);return l.then(()=>this.addAll(o))}remove(t){const{tokenize:r,processTerm:n,extractField:a,fields:o,idField:l}=this._options,i=a(t,l);if(i==null)throw new Error(`MiniSearch: document does not have ID field "${l}"`);const s=this._idToShortId.get(i);if(s==null)throw new Error(`MiniSearch: cannot remove document with ID ${i}: it is not in the index`);for(const c of o){const u=a(t,c);if(u==null)continue;const d=r(u.toString(),c),h=this._fieldIds[c],f=new Set(d).size;this.removeFieldLength(s,h,this._documentCount,f);for(const b of d){const y=n(b,c);if(Array.isArray(y))for(const k of y)this.removeTerm(h,s,k);else y&&this.removeTerm(h,s,y)}}this._storedFields.delete(s),this._documentIds.delete(s),this._idToShortId.delete(i),this._fieldLength.delete(s),this._documentCount-=1}removeAll(t){if(t)for(const r of t)this.remove(r);else{if(arguments.length>0)throw new Error("Expected documents to be present. Omit the argument to remove all documents.");this._index=new nt,this._documentCount=0,this._documentIds=new Map,this._idToShortId=new Map,this._fieldLength=new Map,this._avgFieldLength=[],this._storedFields=new Map,this._nextId=0}}discard(t){const r=this._idToShortId.get(t);if(r==null)throw new Error(`MiniSearch: cannot discard document with ID ${t}: it is not in the index`);this._idToShortId.delete(t),this._documentIds.delete(r),this._storedFields.delete(r),(this._fieldLength.get(r)||[]).forEach((n,a)=>{this.removeFieldLength(r,a,this._documentCount,n)}),this._fieldLength.delete(r),this._documentCount-=1,this._dirtCount+=1,this.maybeAutoVacuum()}maybeAutoVacuum(){if(this._options.autoVacuum===!1)return;const{minDirtFactor:t,minDirtCount:r,batchSize:n,batchWait:a}=this._options.autoVacuum;this.conditionalVacuum({batchSize:n,batchWait:a},{minDirtCount:r,minDirtFactor:t})}discardAll(t){const r=this._options.autoVacuum;try{this._options.autoVacuum=!1;for(const n of t)this.discard(n)}finally{this._options.autoVacuum=r}this.maybeAutoVacuum()}replace(t){const{idField:r,extractField:n}=this._options,a=n(t,r);this.discard(a),this.add(t)}vacuum(t={}){return this.conditionalVacuum(t)}conditionalVacuum(t,r){return this._currentVacuum?(this._enqueuedVacuumConditions=this._enqueuedVacuumConditions&&r,this._enqueuedVacuum!=null?this._enqueuedVacuum:(this._enqueuedVacuum=this._currentVacuum.then(()=>{const n=this._enqueuedVacuumConditions;return this._enqueuedVacuumConditions=vn,this.performVacuuming(t,n)}),this._enqueuedVacuum)):this.vacuumConditionsMet(r)===!1?Promise.resolve():(this._currentVacuum=this.performVacuuming(t),this._currentVacuum)}async performVacuuming(t,r){const n=this._dirtCount;if(this.vacuumConditionsMet(r)){const a=t.batchSize||mn.batchSize,o=t.batchWait||mn.batchWait;let l=1;for(const[i,s]of this._index){for(const[c,u]of s)for(const[d]of u)this._documentIds.has(d)||(u.size<=1?s.delete(c):u.delete(d));this._index.get(i).size===0&&this._index.delete(i),l%a===0&&await new Promise(c=>setTimeout(c,o)),l+=1}this._dirtCount-=n}await null,this._currentVacuum=this._enqueuedVacuum,this._enqueuedVacuum=null}vacuumConditionsMet(t){if(t==null)return!0;let{minDirtCount:r,minDirtFactor:n}=t;return r=r||Wr.minDirtCount,n=n||Wr.minDirtFactor,this.dirtCount>=r&&this.dirtFactor>=n}get isVacuuming(){return this._currentVacuum!=null}get dirtCount(){return this._dirtCount}get dirtFactor(){return this._dirtCount/(1+this._documentCount+this._dirtCount)}has(t){return this._idToShortId.has(t)}getStoredFields(t){const r=this._idToShortId.get(t);if(r!=null)return this._storedFields.get(r)}search(t,r={}){const{searchOptions:n}=this._options,a={...n,...r},o=this.executeQuery(t,r),l=[];for(const[i,{score:s,terms:c,match:u}]of o){const d=c.length||1,h={id:this._documentIds.get(i),score:s*d,terms:Object.keys(u),queryTerms:c,match:u};Object.assign(h,this._storedFields.get(i)),(a.filter==null||a.filter(h))&&l.push(h)}return t===at.wildcard&&a.boostDocument==null||l.sort(qo),l}autoSuggest(t,r={}){r={...this._options.autoSuggestOptions,...r};const n=new Map;for(const{score:o,terms:l}of this.search(t,r)){const i=l.join(" "),s=n.get(i);s!=null?(s.score+=o,s.count+=1):n.set(i,{score:o,terms:l,count:1})}const a=[];for(const[o,{score:l,terms:i,count:s}]of n)a.push({suggestion:o,terms:i,score:l/s});return a.sort(qo),a}get documentCount(){return this._documentCount}get termCount(){return this._index.size}static loadJSON(t,r){if(r==null)throw new Error("MiniSearch: loadJSON should be given the same options used when serializing the index");return this.loadJS(JSON.parse(t),r)}static async loadJSONAsync(t,r){if(r==null)throw new Error("MiniSearch: loadJSON should be given the same options used when serializing the index");return this.loadJSAsync(JSON.parse(t),r)}static getDefault(t){if(Ur.hasOwnProperty(t))return qr(Ur,t);throw new Error(`MiniSearch: unknown option "${t}"`)}static loadJS(t,r){const{index:n,documentIds:a,fieldLength:o,storedFields:l,serializationVersion:i}=t,s=this.instantiateMiniSearch(t,r);s._documentIds=Dt(a),s._fieldLength=Dt(o),s._storedFields=Dt(l);for(const[c,u]of s._documentIds)s._idToShortId.set(u,c);for(const[c,u]of n){const d=new Map;for(const h of Object.keys(u)){let f=u[h];i===1&&(f=f.ds),d.set(parseInt(h,10),Dt(f))}s._index.set(c,d)}return s}static async loadJSAsync(t,r){const{index:n,documentIds:a,fieldLength:o,storedFields:l,serializationVersion:i}=t,s=this.instantiateMiniSearch(t,r);s._documentIds=await Ot(a),s._fieldLength=await Ot(o),s._storedFields=await Ot(l);for(const[u,d]of s._documentIds)s._idToShortId.set(d,u);let c=0;for(const[u,d]of n){const h=new Map;for(const f of Object.keys(d)){let b=d[f];i===1&&(b=b.ds),h.set(parseInt(f,10),await Ot(b))}++c%1e3===0&&await Hs(0),s._index.set(u,h)}return s}static instantiateMiniSearch(t,r){const{documentCount:n,nextId:a,fieldIds:o,averageFieldLength:l,dirtCount:i,serializationVersion:s}=t;if(s!==1&&s!==2)throw new Error("MiniSearch: cannot deserialize an index created with an incompatible version");const c=new at(r);return c._documentCount=n,c._nextId=a,c._idToShortId=new Map,c._fieldIds=o,c._avgFieldLength=l,c._dirtCount=i||0,c._index=new nt,c}executeQuery(t,r={}){if(t===at.wildcard)return this.executeWildcardQuery(r);if(typeof t!="string"){const h={...r,...t,queries:void 0},f=t.queries.map(b=>this.executeQuery(b,h));return this.combineResults(f,h.combineWith)}const{tokenize:n,processTerm:a,searchOptions:o}=this._options,l={tokenize:n,processTerm:a,...o,...r},{tokenize:i,processTerm:s}=l,d=i(t).flatMap(h=>s(h)).filter(h=>!!h).map(wh(l)).map(h=>this.executeQuerySpec(h,l));return this.combineResults(d,l.combineWith)}executeQuerySpec(t,r){const n={...this._options.searchOptions,...r},a=(n.fields||this._options.fields).reduce((y,k)=>({...y,[k]:qr(n.boost,k)||1}),{}),{boostDocument:o,weights:l,maxFuzzy:i,bm25:s}=n,{fuzzy:c,prefix:u}={...Bo.weights,...l},d=this._index.get(t.term),h=this.termResults(t.term,t.term,1,t.termBoost,d,a,o,s);let f,b;if(t.prefix&&(f=this._index.atPrefix(t.term)),t.fuzzy){const y=t.fuzzy===!0?.2:t.fuzzy,k=y<1?Math.min(i,Math.round(t.term.length*y)):y;k&&(b=this._index.fuzzyGet(t.term,k))}if(f)for(const[y,k]of f){const N=y.length-t.term.length;if(!N)continue;b==null||b.delete(y);const E=u*y.length/(y.length+.3*N);this.termResults(t.term,y,E,t.termBoost,k,a,o,s,h)}if(b)for(const y of b.keys()){const[k,N]=b.get(y);if(!N)continue;const E=c*y.length/(y.length+N);this.termResults(t.term,y,E,t.termBoost,k,a,o,s,h)}return h}executeWildcardQuery(t){const r=new Map,n={...this._options.searchOptions,...t};for(const[a,o]of this._documentIds){const l=n.boostDocument?n.boostDocument(o,"",this._storedFields.get(a)):1;r.set(a,{score:l,terms:[],match:{}})}return r}combineResults(t,r=Gn){if(t.length===0)return new Map;const n=r.toLowerCase(),a=vh[n];if(!a)throw new Error(`Invalid combination operator: ${r}`);return t.reduce(a)||new Map}toJSON(){const t=[];for(const[r,n]of this._index){const a={};for(const[o,l]of n)a[o]=Object.fromEntries(l);t.push([r,a])}return{documentCount:this._documentCount,nextId:this._nextId,documentIds:Object.fromEntries(this._documentIds),fieldIds:this._fieldIds,fieldLength:Object.fromEntries(this._fieldLength),averageFieldLength:this._avgFieldLength,storedFields:Object.fromEntries(this._storedFields),dirtCount:this._dirtCount,index:t,serializationVersion:2}}termResults(t,r,n,a,o,l,i,s,c=new Map){if(o==null)return c;for(const u of Object.keys(l)){const d=l[u],h=this._fieldIds[u],f=o.get(h);if(f==null)continue;let b=f.size;const y=this._avgFieldLength[h];for(const k of f.keys()){if(!this._documentIds.has(k)){this.removeTerm(h,k,r),b-=1;continue}const N=i?i(this._documentIds.get(k),r,this._storedFields.get(k)):1;if(!N)continue;const E=f.get(k),j=this._fieldLength.get(k)[h],A=bh(E,b,this._documentCount,j,y,s),I=n*a*d*N*A,P=c.get(k);if(P){P.score+=I,_h(P.terms,t);const m=qr(P.match,r);m?m.push(u):P.match[r]=[u]}else c.set(k,{score:I,terms:[t],match:{[r]:[u]}})}}return c}addTerm(t,r,n){const a=this._index.fetch(n,Uo);let o=a.get(t);if(o==null)o=new Map,o.set(r,1),a.set(t,o);else{const l=o.get(r);o.set(r,(l||0)+1)}}removeTerm(t,r,n){if(!this._index.has(n)){this.warnDocumentChanged(r,t,n);return}const a=this._index.fetch(n,Uo),o=a.get(t);o==null||o.get(r)==null?this.warnDocumentChanged(r,t,n):o.get(r)<=1?o.size<=1?a.delete(t):o.delete(r):o.set(r,o.get(r)-1),this._index.get(n).size===0&&this._index.delete(n)}warnDocumentChanged(t,r,n){for(const a of Object.keys(this._fieldIds))if(this._fieldIds[a]===r){this._options.logger("warn",`MiniSearch: document with ID ${this._documentIds.get(t)} has changed before removal: term "${n}" was not present in field "${a}". Removing a document after it has changed can corrupt the index!`,"version_conflict");return}}addDocumentId(t){const r=this._nextId;return this._idToShortId.set(t,r),this._documentIds.set(r,t),this._documentCount+=1,this._nextId+=1,r}addFields(t){for(let r=0;r<t.length;r++)this._fieldIds[t[r]]=r}addFieldLength(t,r,n,a){let o=this._fieldLength.get(t);o==null&&this._fieldLength.set(t,o=[]),o[r]=a;const i=(this._avgFieldLength[r]||0)*n+a;this._avgFieldLength[r]=i/(n+1)}removeFieldLength(t,r,n,a){if(n===1){this._avgFieldLength[r]=0;return}const o=this._avgFieldLength[r]*n-a;this._avgFieldLength[r]=o/(n-1)}saveStoredFields(t,r){const{storeFields:n,extractField:a}=this._options;if(n==null||n.length===0)return;let o=this._storedFields.get(t);o==null&&this._storedFields.set(t,o={});for(const l of n){const i=a(r,l);i!==void 0&&(o[l]=i)}}}at.wildcard=Symbol("*");const qr=(e,t)=>Object.prototype.hasOwnProperty.call(e,t)?e[t]:void 0,vh={[Gn]:(e,t)=>{for(const r of t.keys()){const 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diff --git a/lightrag/api/webui/assets/feature-retrieval-P5Qspbob.js b/lightrag/api/webui/assets/feature-retrieval-BwXSap2b.js
similarity index 99%
rename from lightrag/api/webui/assets/feature-retrieval-P5Qspbob.js
rename to lightrag/api/webui/assets/feature-retrieval-BwXSap2b.js
index 02c9f918..abd7cdd0 100644
--- a/lightrag/api/webui/assets/feature-retrieval-P5Qspbob.js
+++ b/lightrag/api/webui/assets/feature-retrieval-BwXSap2b.js
@@ -1,5 +1,5 @@
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similarity index 99%
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similarity index 99%
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index 0e372448..ce38c2e4 100644
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diff --git a/lightrag/api/webui/assets/gitGraphDiagram-GW3U2K7C-C2Xxr0z0.js b/lightrag/api/webui/assets/gitGraphDiagram-GW3U2K7C-C6g75jYv.js
similarity index 98%
rename from lightrag/api/webui/assets/gitGraphDiagram-GW3U2K7C-C2Xxr0z0.js
rename to lightrag/api/webui/assets/gitGraphDiagram-GW3U2K7C-C6g75jYv.js
index 37a49255..e26d3da2 100644
--- a/lightrag/api/webui/assets/gitGraphDiagram-GW3U2K7C-C2Xxr0z0.js
+++ b/lightrag/api/webui/assets/gitGraphDiagram-GW3U2K7C-C6g75jYv.js
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diff --git a/lightrag/api/webui/assets/graph-dt4A1Xns.js b/lightrag/api/webui/assets/graph-lXMBdjQ3.js
similarity index 97%
rename from lightrag/api/webui/assets/graph-dt4A1Xns.js
rename to lightrag/api/webui/assets/graph-lXMBdjQ3.js
index 41528616..a2ab7788 100644
--- a/lightrag/api/webui/assets/graph-dt4A1Xns.js
+++ b/lightrag/api/webui/assets/graph-lXMBdjQ3.js
@@ -1 +1 @@
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g(this.nodes(),function(t){return E(e._out[t])})}setNodes(e,t){var s=arguments,i=this;return d(e,function(r){s.length>1?i.setNode(r,t):i.setNode(r)}),this}setNode(e,t){return Object.prototype.hasOwnProperty.call(this._nodes,e)?(arguments.length>1&&(this._nodes[e]=t),this):(this._nodes[e]=arguments.length>1?t:this._defaultNodeLabelFn(e),this._isCompound&&(this._parent[e]=a,this._children[e]={},this._children[a][e]=!0),this._in[e]={},this._preds[e]={},this._out[e]={},this._sucs[e]={},++this._nodeCount,this)}node(e){return this._nodes[e]}hasNode(e){return Object.prototype.hasOwnProperty.call(this._nodes,e)}removeNode(e){if(Object.prototype.hasOwnProperty.call(this._nodes,e)){var t=s=>this.removeEdge(this._edgeObjs[s]);delete this._nodes[e],this._isCompound&&(this._removeFromParentsChildList(e),delete this._parent[e],d(this.children(e),s=>{this.setParent(s)}),delete this._children[e]),d(_(this._in[e]),t),delete this._in[e],delete this._preds[e],d(_(this._out[e]),t),delete this._out[e],delete this._sucs[e],--this._nodeCount}return this}setParent(e,t){if(!this._isCompound)throw new Error("Cannot set parent in a non-compound graph");if(l(t))t=a;else{t+="";for(var s=t;!l(s);s=this.parent(s))if(s===e)throw new Error("Setting "+t+" as parent of "+e+" would create a cycle");this.setNode(t)}return this.setNode(e),this._removeFromParentsChildList(e),this._parent[e]=t,this._children[t][e]=!0,this}_removeFromParentsChildList(e){delete this._children[this._parent[e]][e]}parent(e){if(this._isCompound){var t=this._parent[e];if(t!==a)return t}}children(e){if(l(e)&&(e=a),this._isCompound){var t=this._children[e];if(t)return _(t)}else{if(e===a)return this.nodes();if(this.hasNode(e))return[]}}predecessors(e){var t=this._preds[e];if(t)return _(t)}successors(e){var t=this._sucs[e];if(t)return _(t)}neighbors(e){var t=this.predecessors(e);if(t)return D(t,this.successors(e))}isLeaf(e){var t;return this.isDirected()?t=this.successors(e):t=this.neighbors(e),t.length===0}filterNodes(e){var t=new this.constructor({directed:this._isDirected,multigraph:this._isMultigraph,compound:this._isCompound});t.setGraph(this.graph());var s=this;d(this._nodes,function(n,h){e(h)&&t.setNode(h,n)}),d(this._edgeObjs,function(n){t.hasNode(n.v)&&t.hasNode(n.w)&&t.setEdge(n,s.edge(n))});var i={};function r(n){var h=s.parent(n);return h===void 0||t.hasNode(h)?(i[n]=h,h):h in i?i[h]:r(h)}return this._isCompound&&d(t.nodes(),function(n){t.setParent(n,r(n))}),t}setDefaultEdgeLabel(e){return b(e)||(e=f(e)),this._defaultEdgeLabelFn=e,this}edgeCount(){return this._edgeCount}edges(){return p(this._edgeObjs)}setPath(e,t){var s=this,i=arguments;return w(e,function(r,n){return i.length>1?s.setEdge(r,n,t):s.setEdge(r,n),n}),this}setEdge(){var e,t,s,i,r=!1,n=arguments[0];typeof n=="object"&&n!==null&&"v"in n?(e=n.v,t=n.w,s=n.name,arguments.length===2&&(i=arguments[1],r=!0)):(e=n,t=arguments[1],s=arguments[3],arguments.length>2&&(i=arguments[2],r=!0)),e=""+e,t=""+t,l(s)||(s=""+s);var h=c(this._isDirected,e,t,s);if(Object.prototype.hasOwnProperty.call(this._edgeLabels,h))return r&&(this._edgeLabels[h]=i),this;if(!l(s)&&!this._isMultigraph)throw new Error("Cannot set a named edge when isMultigraph = false");this.setNode(e),this.setNode(t),this._edgeLabels[h]=r?i:this._defaultEdgeLabelFn(e,t,s);var u=M(this._isDirected,e,t,s);return e=u.v,t=u.w,Object.freeze(u),this._edgeObjs[h]=u,y(this._preds[t],e),y(this._sucs[e],t),this._in[t][h]=u,this._out[e][h]=u,this._edgeCount++,this}edge(e,t,s){var i=arguments.length===1?m(this._isDirected,arguments[0]):c(this._isDirected,e,t,s);return this._edgeLabels[i]}hasEdge(e,t,s){var i=arguments.length===1?m(this._isDirected,arguments[0]):c(this._isDirected,e,t,s);return Object.prototype.hasOwnProperty.call(this._edgeLabels,i)}removeEdge(e,t,s){var i=arguments.length===1?m(this._isDirected,arguments[0]):c(this._isDirected,e,t,s),r=this._edgeObjs[i];return r&&(e=r.v,t=r.w,delete this._edgeLabels[i],delete this._edgeObjs[i],C(this._preds[t],e),C(this._sucs[e],t),delete this._in[t][i],delete this._out[e][i],this._edgeCount--),this}inEdges(e,t){var s=this._in[e];if(s){var i=p(s);return t?g(i,function(r){return r.v===t}):i}}outEdges(e,t){var s=this._out[e];if(s){var i=p(s);return t?g(i,function(r){return r.w===t}):i}}nodeEdges(e,t){var s=this.inEdges(e,t);if(s)return s.concat(this.outEdges(e,t))}}L.prototype._nodeCount=0;L.prototype._edgeCount=0;function y(o,e){o[e]?o[e]++:o[e]=1}function C(o,e){--o[e]||delete o[e]}function c(o,e,t,s){var i=""+e,r=""+t;if(!o&&i>r){var n=i;i=r,r=n}return i+O+r+O+(l(s)?F:s)}function M(o,e,t,s){var i=""+e,r=""+t;if(!o&&i>r){var n=i;i=r,r=n}var h={v:i,w:r};return s&&(h.name=s),h}function m(o,e){return c(o,e.v,e.w,e.name)}export{L as G};
+import{aw as N,ax as j,ay as f,az as b,aA as E}from"./mermaid-vendor-B20mDgAo.js";import{a as v,c as P,k as _,f as g,d,i as l,v as p,r as w}from"./_baseUniq-Coqzfado.js";var D=N(function(o){return v(P(o,1,j,!0))}),F="\0",a="\0",O="
";class L{constructor(e={}){this._isDirected=Object.prototype.hasOwnProperty.call(e,"directed")?e.directed:!0,this._isMultigraph=Object.prototype.hasOwnProperty.call(e,"multigraph")?e.multigraph:!1,this._isCompound=Object.prototype.hasOwnProperty.call(e,"compound")?e.compound:!1,this._label=void 0,this._defaultNodeLabelFn=f(void 0),this._defaultEdgeLabelFn=f(void 0),this._nodes={},this._isCompound&&(this._parent={},this._children={},this._children[a]={}),this._in={},this._preds={},this._out={},this._sucs={},this._edgeObjs={},this._edgeLabels={}}isDirected(){return this._isDirected}isMultigraph(){return this._isMultigraph}isCompound(){return this._isCompound}setGraph(e){return this._label=e,this}graph(){return this._label}setDefaultNodeLabel(e){return b(e)||(e=f(e)),this._defaultNodeLabelFn=e,this}nodeCount(){return this._nodeCount}nodes(){return _(this._nodes)}sources(){var e=this;return g(this.nodes(),function(t){return E(e._in[t])})}sinks(){var e=this;return g(this.nodes(),function(t){return E(e._out[t])})}setNodes(e,t){var s=arguments,i=this;return d(e,function(r){s.length>1?i.setNode(r,t):i.setNode(r)}),this}setNode(e,t){return Object.prototype.hasOwnProperty.call(this._nodes,e)?(arguments.length>1&&(this._nodes[e]=t),this):(this._nodes[e]=arguments.length>1?t:this._defaultNodeLabelFn(e),this._isCompound&&(this._parent[e]=a,this._children[e]={},this._children[a][e]=!0),this._in[e]={},this._preds[e]={},this._out[e]={},this._sucs[e]={},++this._nodeCount,this)}node(e){return this._nodes[e]}hasNode(e){return Object.prototype.hasOwnProperty.call(this._nodes,e)}removeNode(e){if(Object.prototype.hasOwnProperty.call(this._nodes,e)){var t=s=>this.removeEdge(this._edgeObjs[s]);delete this._nodes[e],this._isCompound&&(this._removeFromParentsChildList(e),delete this._parent[e],d(this.children(e),s=>{this.setParent(s)}),delete this._children[e]),d(_(this._in[e]),t),delete this._in[e],delete this._preds[e],d(_(this._out[e]),t),delete this._out[e],delete this._sucs[e],--this._nodeCount}return this}setParent(e,t){if(!this._isCompound)throw new Error("Cannot set parent in a non-compound graph");if(l(t))t=a;else{t+="";for(var s=t;!l(s);s=this.parent(s))if(s===e)throw new Error("Setting "+t+" as parent of "+e+" would create a cycle");this.setNode(t)}return this.setNode(e),this._removeFromParentsChildList(e),this._parent[e]=t,this._children[t][e]=!0,this}_removeFromParentsChildList(e){delete this._children[this._parent[e]][e]}parent(e){if(this._isCompound){var t=this._parent[e];if(t!==a)return t}}children(e){if(l(e)&&(e=a),this._isCompound){var t=this._children[e];if(t)return _(t)}else{if(e===a)return this.nodes();if(this.hasNode(e))return[]}}predecessors(e){var t=this._preds[e];if(t)return _(t)}successors(e){var t=this._sucs[e];if(t)return _(t)}neighbors(e){var t=this.predecessors(e);if(t)return D(t,this.successors(e))}isLeaf(e){var t;return this.isDirected()?t=this.successors(e):t=this.neighbors(e),t.length===0}filterNodes(e){var t=new this.constructor({directed:this._isDirected,multigraph:this._isMultigraph,compound:this._isCompound});t.setGraph(this.graph());var s=this;d(this._nodes,function(n,h){e(h)&&t.setNode(h,n)}),d(this._edgeObjs,function(n){t.hasNode(n.v)&&t.hasNode(n.w)&&t.setEdge(n,s.edge(n))});var i={};function r(n){var h=s.parent(n);return h===void 0||t.hasNode(h)?(i[n]=h,h):h in i?i[h]:r(h)}return this._isCompound&&d(t.nodes(),function(n){t.setParent(n,r(n))}),t}setDefaultEdgeLabel(e){return b(e)||(e=f(e)),this._defaultEdgeLabelFn=e,this}edgeCount(){return this._edgeCount}edges(){return p(this._edgeObjs)}setPath(e,t){var s=this,i=arguments;return w(e,function(r,n){return i.length>1?s.setEdge(r,n,t):s.setEdge(r,n),n}),this}setEdge(){var e,t,s,i,r=!1,n=arguments[0];typeof n=="object"&&n!==null&&"v"in n?(e=n.v,t=n.w,s=n.name,arguments.length===2&&(i=arguments[1],r=!0)):(e=n,t=arguments[1],s=arguments[3],arguments.length>2&&(i=arguments[2],r=!0)),e=""+e,t=""+t,l(s)||(s=""+s);var h=c(this._isDirected,e,t,s);if(Object.prototype.hasOwnProperty.call(this._edgeLabels,h))return r&&(this._edgeLabels[h]=i),this;if(!l(s)&&!this._isMultigraph)throw new Error("Cannot set a named edge when isMultigraph = false");this.setNode(e),this.setNode(t),this._edgeLabels[h]=r?i:this._defaultEdgeLabelFn(e,t,s);var u=M(this._isDirected,e,t,s);return e=u.v,t=u.w,Object.freeze(u),this._edgeObjs[h]=u,y(this._preds[t],e),y(this._sucs[e],t),this._in[t][h]=u,this._out[e][h]=u,this._edgeCount++,this}edge(e,t,s){var i=arguments.length===1?m(this._isDirected,arguments[0]):c(this._isDirected,e,t,s);return this._edgeLabels[i]}hasEdge(e,t,s){var i=arguments.length===1?m(this._isDirected,arguments[0]):c(this._isDirected,e,t,s);return Object.prototype.hasOwnProperty.call(this._edgeLabels,i)}removeEdge(e,t,s){var i=arguments.length===1?m(this._isDirected,arguments[0]):c(this._isDirected,e,t,s),r=this._edgeObjs[i];return r&&(e=r.v,t=r.w,delete this._edgeLabels[i],delete this._edgeObjs[i],C(this._preds[t],e),C(this._sucs[e],t),delete this._in[t][i],delete this._out[e][i],this._edgeCount--),this}inEdges(e,t){var s=this._in[e];if(s){var i=p(s);return t?g(i,function(r){return r.v===t}):i}}outEdges(e,t){var s=this._out[e];if(s){var i=p(s);return t?g(i,function(r){return r.w===t}):i}}nodeEdges(e,t){var s=this.inEdges(e,t);if(s)return s.concat(this.outEdges(e,t))}}L.prototype._nodeCount=0;L.prototype._edgeCount=0;function y(o,e){o[e]?o[e]++:o[e]=1}function C(o,e){--o[e]||delete o[e]}function c(o,e,t,s){var i=""+e,r=""+t;if(!o&&i>r){var n=i;i=r,r=n}return i+O+r+O+(l(s)?F:s)}function M(o,e,t,s){var i=""+e,r=""+t;if(!o&&i>r){var n=i;i=r,r=n}var h={v:i,w:r};return s&&(h.name=s),h}function m(o,e){return c(o,e.v,e.w,e.name)}export{L as G};
diff --git a/lightrag/api/webui/assets/index-DI6XUmEl.js b/lightrag/api/webui/assets/index-CIdJpUuC.js
similarity index 99%
rename from lightrag/api/webui/assets/index-DI6XUmEl.js
rename to lightrag/api/webui/assets/index-CIdJpUuC.js
index c47c89c5..f8d9bf07 100644
--- a/lightrag/api/webui/assets/index-DI6XUmEl.js
+++ b/lightrag/api/webui/assets/index-CIdJpUuC.js
@@ -1,4 +1,4 @@
-import{j as o,Y as td,O as fg,k as dg,u as ad,Z as mg,c as hg,l as gg,g as pg,S as yg,T as vg,n as bg,m as nd,o as Sg,p as Tg,$ as ud,a0 as id,a1 as cd,a2 as xg}from"./ui-vendor-CeCm8EER.js";import{d as Ag,h as Dg,r as E,u as sd,H as Ng,i as Eg,j as kf}from"./react-vendor-DEwriMA6.js";import{N as we,c as Ve,ad as od,u as Bl,M as sl,ae as rd,af as fd,I as us,B as Cn,D as Mg,l as zg,m as Cg,n as Og,o as _g,ag as Rg,ah as jg,ai as Ug,aj as Hg,ak as ql,al as dd,am as ss,an as is,a0 as Lg,a1 as qg,a2 as Bg,a3 as Gg,ao as Yg,ap as Xg,aq as md,ar as wg,as as hd,at as Vg,au as gd,d as Qg,R as Kg,V as Zg,g as En,av as kg,aw as Jg,ax as Fg}from"./feature-graph-C6IuADHZ.js";import{S as Jf,a as Ff,b as Pf,c as $f,e as rt,D as Pg}from"./feature-documents-DLarjU2a.js";import{R as $g}from"./feature-retrieval-P5Qspbob.js";import{i as cs}from"./utils-vendor-BysuhMZA.js";import"./graph-vendor-B-X5JegA.js";import"./mermaid-vendor-CAxUo7Zk.js";import"./markdown-vendor-DmIvJdn7.js";(function(){const y=document.createElement("link").relList;if(y&&y.supports&&y.supports("modulepreload"))return;for(const N of document.querySelectorAll('link[rel="modulepreload"]'))d(N);new MutationObserver(N=>{for(const _ of N)if(_.type==="childList")for(const H of _.addedNodes)H.tagName==="LINK"&&H.rel==="modulepreload"&&d(H)}).observe(document,{childList:!0,subtree:!0});function x(N){const _={};return N.integrity&&(_.integrity=N.integrity),N.referrerPolicy&&(_.referrerPolicy=N.referrerPolicy),N.crossOrigin==="use-credentials"?_.credentials="include":N.crossOrigin==="anonymous"?_.credentials="omit":_.credentials="same-origin",_}function d(N){if(N.ep)return;N.ep=!0;const _=x(N);fetch(N.href,_)}})();var ts={exports:{}},Mn={},as={exports:{}},ns={};/**
+import{j as o,Y as td,O as fg,k as dg,u as ad,Z as mg,c as hg,l as gg,g as pg,S as yg,T as vg,n as bg,m as nd,o as Sg,p as Tg,$ as ud,a0 as id,a1 as cd,a2 as xg}from"./ui-vendor-CeCm8EER.js";import{d as Ag,h as Dg,r as E,u as sd,H as Ng,i as Eg,j as kf}from"./react-vendor-DEwriMA6.js";import{N as we,c as Ve,ad as od,u as Bl,M as sl,ae as rd,af as fd,I as us,B as Cn,D as Mg,l as zg,m as Cg,n as Og,o as _g,ag as Rg,ah as jg,ai as Ug,aj as Hg,ak as ql,al as dd,am as ss,an as is,a0 as Lg,a1 as qg,a2 as Bg,a3 as Gg,ao as Yg,ap as Xg,aq as md,ar as wg,as as hd,at as Vg,au as gd,d as Qg,R as Kg,V as Zg,g as En,av as kg,aw as Jg,ax as Fg}from"./feature-graph-CS4MyqEv.js";import{S as Jf,a as Ff,b as Pf,c as $f,e as rt,D as Pg}from"./feature-documents-4TV9qUPI.js";import{R as $g}from"./feature-retrieval-BwXSap2b.js";import{i as cs}from"./utils-vendor-BysuhMZA.js";import"./graph-vendor-B-X5JegA.js";import"./mermaid-vendor-B20mDgAo.js";import"./markdown-vendor-DmIvJdn7.js";(function(){const y=document.createElement("link").relList;if(y&&y.supports&&y.supports("modulepreload"))return;for(const N of document.querySelectorAll('link[rel="modulepreload"]'))d(N);new MutationObserver(N=>{for(const _ of N)if(_.type==="childList")for(const H of _.addedNodes)H.tagName==="LINK"&&H.rel==="modulepreload"&&d(H)}).observe(document,{childList:!0,subtree:!0});function x(N){const _={};return N.integrity&&(_.integrity=N.integrity),N.referrerPolicy&&(_.referrerPolicy=N.referrerPolicy),N.crossOrigin==="use-credentials"?_.credentials="include":N.crossOrigin==="anonymous"?_.credentials="omit":_.credentials="same-origin",_}function d(N){if(N.ep)return;N.ep=!0;const _=x(N);fetch(N.href,_)}})();var ts={exports:{}},Mn={},as={exports:{}},ns={};/**
  * @license React
  * scheduler.production.js
  *
diff --git a/lightrag/api/webui/assets/infoDiagram-LHK5PUON-DIwHFGTU.js b/lightrag/api/webui/assets/infoDiagram-LHK5PUON-D1Fqp1w7.js
similarity index 69%
rename from lightrag/api/webui/assets/infoDiagram-LHK5PUON-DIwHFGTU.js
rename to lightrag/api/webui/assets/infoDiagram-LHK5PUON-D1Fqp1w7.js
index 1ef33b90..6383d90a 100644
--- a/lightrag/api/webui/assets/infoDiagram-LHK5PUON-DIwHFGTU.js
+++ b/lightrag/api/webui/assets/infoDiagram-LHK5PUON-D1Fqp1w7.js
@@ -1,2 +1,2 @@
-import{_ as e,l as o,K as i,e as n,L as p}from"./mermaid-vendor-CAxUo7Zk.js";import{p as m}from"./treemap-75Q7IDZK-BAguqzAo.js";import"./feature-graph-C6IuADHZ.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";import"./_baseUniq-BrMEyGA7.js";import"./_basePickBy-BEWgwF1U.js";import"./clone-D60V_qjf.js";var g={parse:e(async r=>{const a=await m("info",r);o.debug(a)},"parse")},v={version:p.version+""},d=e(()=>v.version,"getVersion"),c={getVersion:d},l=e((r,a,s)=>{o.debug(`rendering info diagram
+import{_ as e,l as o,K as i,e as n,L as p}from"./mermaid-vendor-B20mDgAo.js";import{p as m}from"./treemap-75Q7IDZK-64OceOGQ.js";import"./feature-graph-CS4MyqEv.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";import"./_baseUniq-Coqzfado.js";import"./_basePickBy-zcTWmF8I.js";import"./clone-D1fuhfq3.js";var g={parse:e(async r=>{const a=await m("info",r);o.debug(a)},"parse")},v={version:p.version+""},d=e(()=>v.version,"getVersion"),c={getVersion:d},l=e((r,a,s)=>{o.debug(`rendering info diagram
 `+r);const t=i(a);n(t,100,400,!0),t.append("g").append("text").attr("x",100).attr("y",40).attr("class","version").attr("font-size",32).style("text-anchor","middle").text(`v${s}`)},"draw"),f={draw:l},L={parser:g,db:c,renderer:f};export{L as diagram};
diff --git a/lightrag/api/webui/assets/journeyDiagram-EWQZEKCU-CsmCKqH7.js b/lightrag/api/webui/assets/journeyDiagram-EWQZEKCU--RceaKbM.js
similarity index 98%
rename from lightrag/api/webui/assets/journeyDiagram-EWQZEKCU-CsmCKqH7.js
rename to lightrag/api/webui/assets/journeyDiagram-EWQZEKCU--RceaKbM.js
index ecee4c09..787e10f0 100644
--- a/lightrag/api/webui/assets/journeyDiagram-EWQZEKCU-CsmCKqH7.js
+++ b/lightrag/api/webui/assets/journeyDiagram-EWQZEKCU--RceaKbM.js
@@ -1,4 +1,4 @@
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diff --git a/lightrag/api/webui/assets/kanban-definition-ZSS6B67P-DLzaGix5.js b/lightrag/api/webui/assets/kanban-definition-ZSS6B67P-BwGtcLKU.js
similarity index 99%
rename from lightrag/api/webui/assets/kanban-definition-ZSS6B67P-DLzaGix5.js
rename to lightrag/api/webui/assets/kanban-definition-ZSS6B67P-BwGtcLKU.js
index c26cdda5..d928702a 100644
--- a/lightrag/api/webui/assets/kanban-definition-ZSS6B67P-DLzaGix5.js
+++ b/lightrag/api/webui/assets/kanban-definition-ZSS6B67P-BwGtcLKU.js
@@ -1,4 +1,4 @@
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diff --git a/lightrag/api/webui/assets/layout-Bs3ntXjW.js b/lightrag/api/webui/assets/layout-BWO25eL4.js
similarity index 99%
rename from lightrag/api/webui/assets/layout-Bs3ntXjW.js
rename to lightrag/api/webui/assets/layout-BWO25eL4.js
index 705a48e2..760ef7c9 100644
--- a/lightrag/api/webui/assets/layout-Bs3ntXjW.js
+++ b/lightrag/api/webui/assets/layout-BWO25eL4.js
@@ -1 +1 @@
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diff --git a/lightrag/api/webui/assets/mermaid-vendor-CAxUo7Zk.js b/lightrag/api/webui/assets/mermaid-vendor-B20mDgAo.js
similarity index 99%
rename from lightrag/api/webui/assets/mermaid-vendor-CAxUo7Zk.js
rename to lightrag/api/webui/assets/mermaid-vendor-B20mDgAo.js
index 0a4cb9ae..069b9ac4 100644
--- a/lightrag/api/webui/assets/mermaid-vendor-CAxUo7Zk.js
+++ b/lightrag/api/webui/assets/mermaid-vendor-B20mDgAo.js
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r,i,n,a,o,s,c,l,h,u,f,d,p,m,y,x,b,C,k,w,_;if(this.primaryTextColor=this.primaryTextColor||(this.darkMode?"#eee":"#333"),this.secondaryColor=this.secondaryColor||A(this.primaryColor,{h:-120}),this.tertiaryColor=this.tertiaryColor||A(this.primaryColor,{h:180,l:5}),this.primaryBorderColor=this.primaryBorderColor||Jt(this.primaryColor,this.darkMode),this.secondaryBorderColor=this.secondaryBorderColor||Jt(this.secondaryColor,this.darkMode),this.tertiaryBorderColor=this.tertiaryBorderColor||Jt(this.tertiaryColor,this.darkMode),this.noteBorderColor=this.noteBorderColor||Jt(this.noteBkgColor,this.darkMode),this.noteBkgColor=this.noteBkgColor||"#fff5ad",this.noteTextColor=this.noteTextColor||"#333",this.secondaryTextColor=this.secondaryTextColor||H(this.secondaryColor),this.tertiaryTextColor=this.tertiaryTextColor||H(this.tertiaryColor),this.lineColor=this.lineColor||H(this.background),this.arrowheadColor=this.arrowheadColor||H(this.background),this.textColor=this.textColor||this.primaryTextColor,this.border2=this.border2||this.tertiaryBorderColor,this.nodeBkg=this.nodeBkg||this.primaryColor,this.mainBkg=this.mainBkg||this.primaryColor,this.nodeBorder=this.nodeBorder||this.primaryBorderColor,this.clusterBkg=this.clusterBkg||this.tertiaryColor,this.clusterBorder=this.clusterBorder||this.tertiaryBorderColor,this.defaultLinkColor=this.defaultLinkColor||this.lineColor,this.titleColor=this.titleColor||this.tertiaryTextColor,this.edgeLabelBackground=this.edgeLabelBackground||(this.darkMode?it(this.secondaryColor,30):this.secondaryColor),this.nodeTextColor=this.nodeTextColor||this.primaryTextColor,this.actorBorder=this.actorBorder||this.primaryBorderColor,this.actorBkg=this.actorBkg||this.mainBkg,this.actorTextColor=this.actorTextColor||this.primaryTextColor,this.actorLineColor=this.actorLineColor||this.actorBorder,this.labelBoxBkgColor=this.labelBoxBkgColor||this.actorBkg,this.signalColor=this.signalColor||this.textColor,this.signalTextColor=this.signalTextColor||this.textColor,this.labelBoxBorderColor=this.labelBoxBorderColor||this.actorBorder,this.labelTextColor=this.labelTextColor||this.actorTextColor,this.loopTextColor=this.loopTextColor||this.actorTextColor,this.activationBorderColor=this.activationBorderColor||it(this.secondaryColor,10),this.activationBkgColor=this.activationBkgColor||this.secondaryColor,this.sequenceNumberColor=this.sequenceNumberColor||H(this.lineColor),this.sectionBkgColor=this.sectionBkgColor||this.tertiaryColor,this.altSectionBkgColor=this.altSectionBkgColor||"white",this.sectionBkgColor=this.sectionBkgColor||this.secondaryColor,this.sectionBkgColor2=this.sectionBkgColor2||this.primaryColor,this.excludeBkgColor=this.excludeBkgColor||"#eeeeee",this.taskBorderColor=this.taskBorderColor||this.primaryBorderColor,this.taskBkgColor=this.taskBkgColor||this.primaryColor,this.activeTaskBorderColor=this.activeTaskBorderColor||this.primaryColor,this.activeTaskBkgColor=this.activeTaskBkgColor||G(this.primaryColor,23),this.gridColor=this.gridColor||"lightgrey",this.doneTaskBkgColor=this.doneTaskBkgColor||"lightgrey",this.doneTaskBorderColor=this.doneTaskBorderColor||"grey",this.critBorderColor=this.critBorderColor||"#ff8888",this.critBkgColor=this.critBkgColor||"red",this.todayLineColor=this.todayLineColor||"red",this.vertLineColor=this.vertLineColor||"navy",this.taskTextColor=this.taskTextColor||this.textColor,this.taskTextOutsideColor=this.taskTextOutsideColor||this.textColor,this.taskTextLightColor=this.taskTextLightColor||this.textColor,this.taskTextColor=this.taskTextColor||this.primaryTextColor,this.taskTextDarkColor=this.taskTextDarkColor||this.textColor,this.taskTextClickableColor=this.taskTextClickableColor||"#003163",this.personBorder=this.personBorder||this.primaryBorderColor,this.personBkg=this.personBkg||this.mainBkg,this.darkMode?(this.rowOdd=this.rowOdd||it(this.mainBkg,5)||"#ffffff",this.rowEven=this.rowEven||it(this.mainBkg,10)):(this.rowOdd=this.rowOdd||G(this.mainBkg,75)||"#ffffff",this.rowEven=this.rowEven||G(this.mainBkg,5)),this.transitionColor=this.transitionColor||this.lineColor,this.transitionLabelColor=this.transitionLabelColor||this.textColor,this.stateLabelColor=this.stateLabelColor||this.stateBkg||this.primaryTextColor,this.stateBkg=this.stateBkg||this.mainBkg,this.labelBackgroundColor=this.labelBackgroundColor||this.stateBkg,this.compositeBackground=this.compositeBackground||this.background||this.tertiaryColor,this.altBackground=this.altBackground||this.tertiaryColor,this.compositeTitleBackground=this.compositeTitleBackground||this.mainBkg,this.compositeBorder=this.compositeBorder||this.nodeBorder,this.innerEndBackground=this.nodeBorder,this.errorBkgColor=this.errorBkgColor||this.tertiaryColor,this.errorTextColor=this.errorTextColor||this.tertiaryTextColor,this.transitionColor=this.transitionColor||this.lineColor,this.specialStateColor=this.lineColor,this.cScale0=this.cScale0||this.primaryColor,this.cScale1=this.cScale1||this.secondaryColor,this.cScale2=this.cScale2||this.tertiaryColor,this.cScale3=this.cScale3||A(this.primaryColor,{h:30}),this.cScale4=this.cScale4||A(this.primaryColor,{h:60}),this.cScale5=this.cScale5||A(this.primaryColor,{h:90}),this.cScale6=this.cScale6||A(this.primaryColor,{h:120}),this.cScale7=this.cScale7||A(this.primaryColor,{h:150}),this.cScale8=this.cScale8||A(this.primaryColor,{h:210,l:150}),this.cScale9=this.cScale9||A(this.primaryColor,{h:270}),this.cScale10=this.cScale10||A(this.primaryColor,{h:300}),this.cScale11=this.cScale11||A(this.primaryColor,{h:330}),this.darkMode)for(let v=0;v<this.THEME_COLOR_LIMIT;v++)this["cScale"+v]=it(this["cScale"+v],75);else for(let v=0;v<this.THEME_COLOR_LIMIT;v++)this["cScale"+v]=it(this["cScale"+v],25);for(let v=0;v<this.THEME_COLOR_LIMIT;v++)this["cScaleInv"+v]=this["cScaleInv"+v]||H(this["cScale"+v]);for(let v=0;v<this.THEME_COLOR_LIMIT;v++)this.darkMode?this["cScalePeer"+v]=this["cScalePeer"+v]||G(this["cScale"+v],10):this["cScalePeer"+v]=this["cScalePeer"+v]||it(this["cScale"+v],10);this.scaleLabelColor=this.scaleLabelColor||this.labelTextColor;for(let v=0;v<this.THEME_COLOR_LIMIT;v++)this["cScaleLabel"+v]=this["cScaleLabel"+v]||this.scaleLabelColor;const t=this.darkMode?-4:-1;for(let v=0;v<5;v++)this["surface"+v]=this["surface"+v]||A(this.mainBkg,{h:180,s:-15,l:t*(5+v*3)}),this["surfacePeer"+v]=this["surfacePeer"+v]||A(this.mainBkg,{h:180,s:-15,l:t*(8+v*3)});this.classText=this.classText||this.textColor,this.fillType0=this.fillType0||this.primaryColor,this.fillType1=this.fillType1||this.secondaryColor,this.fillType2=this.fillType2||A(this.primaryColor,{h:64}),this.fillType3=this.fillType3||A(this.secondaryColor,{h:64}),this.fillType4=this.fillType4||A(this.primaryColor,{h:-64}),this.fillType5=this.fillType5||A(this.secondaryColor,{h:-64}),this.fillType6=this.fillType6||A(this.primaryColor,{h:128}),this.fillType7=this.fillType7||A(this.secondaryColor,{h:128}),this.pie1=this.pie1||this.primaryColor,this.pie2=this.pie2||this.secondaryColor,this.pie3=this.pie3||this.tertiaryColor,this.pie4=this.pie4||A(this.primaryColor,{l:-10}),this.pie5=this.pie5||A(this.secondaryColor,{l:-10}),this.pie6=this.pie6||A(this.tertiaryColor,{l:-10}),this.pie7=this.pie7||A(this.primaryColor,{h:60,l:-10}),this.pie8=this.pie8||A(this.primaryColor,{h:-60,l:-10}),this.pie9=this.pie9||A(this.primaryColor,{h:120,l:0}),this.pie10=this.pie10||A(this.primaryColor,{h:60,l:-20}),this.pie11=this.pie11||A(this.primaryColor,{h:-60,l:-20}),this.pie12=this.pie12||A(this.primaryColor,{h:120,l:-10}),this.pieTitleTextSize=this.pieTitleTextSize||"25px",this.pieTitleTextColor=this.pieTitleTextColor||this.taskTextDarkColor,this.pieSectionTextSize=this.pieSectionTextSize||"17px",this.pieSectionTextColor=this.pieSectionTextColor||this.textColor,this.pieLegendTextSize=this.pieLegendTextSize||"17px",this.pieLegendTextColor=this.pieLegendTextColor||this.taskTextDarkColor,this.pieStrokeColor=this.pieStrokeColor||"black",this.pieStrokeWidth=this.pieStrokeWidth||"2px",this.pieOuterStrokeWidth=this.pieOuterStrokeWidth||"2px",this.pieOuterStrokeColor=this.pieOuterStrokeColor||"black",this.pieOpacity=this.pieOpacity||"0.7",this.radar={axisColor:((r=this.radar)==null?void 0:r.axisColor)||this.lineColor,axisStrokeWidth:((i=this.radar)==null?void 0:i.axisStrokeWidth)||2,axisLabelFontSize:((n=this.radar)==null?void 0:n.axisLabelFontSize)||12,curveOpacity:((a=this.radar)==null?void 0:a.curveOpacity)||.5,curveStrokeWidth:((o=this.radar)==null?void 0:o.curveStrokeWidth)||2,graticuleColor:((s=this.radar)==null?void 0:s.graticuleColor)||"#DEDEDE",graticuleStrokeWidth:((c=this.radar)==null?void 0:c.graticuleStrokeWidth)||1,graticuleOpacity:((l=this.radar)==null?void 0:l.graticuleOpacity)||.3,legendBoxSize:((h=this.radar)==null?void 0:h.legendBoxSize)||12,legendFontSize:((u=this.radar)==null?void 0:u.legendFontSize)||12},this.archEdgeColor=this.archEdgeColor||"#777",this.archEdgeArrowColor=this.archEdgeArrowColor||"#777",this.archEdgeWidth=this.archEdgeWidth||"3",this.archGroupBorderColor=this.archGroupBorderColor||"#000",this.archGroupBorderWidth=this.archGroupBorderWidth||"2px",this.quadrant1Fill=this.quadrant1Fill||this.primaryColor,this.quadrant2Fill=this.quadrant2Fill||A(this.primaryColor,{r:5,g:5,b:5}),this.quadrant3Fill=this.quadrant3Fill||A(this.primaryColor,{r:10,g:10,b:10}),this.quadrant4Fill=this.quadrant4Fill||A(this.primaryColor,{r:15,g:15,b:15}),this.quadrant1TextFill=this.quadrant1TextFill||this.primaryTextColor,this.quadrant2TextFill=this.quadrant2TextFill||A(this.primaryTextColor,{r:-5,g:-5,b:-5}),this.quadrant3TextFill=this.quadrant3TextFill||A(this.primaryTextColor,{r:-10,g:-10,b:-10}),this.quadrant4TextFill=this.quadrant4TextFill||A(this.primaryTextColor,{r:-15,g:-15,b:-15}),this.quadrantPointFill=this.quadrantPointFill||An(this.quadrant1Fill)?G(this.quadrant1Fill):it(this.quadrant1Fill),this.quadrantPointTextFill=this.quadrantPointTextFill||this.primaryTextColor,this.quadrantXAxisTextFill=this.quadrantXAxisTextFill||this.primaryTextColor,this.quadrantYAxisTextFill=this.quadrantYAxisTextFill||this.primaryTextColor,this.quadrantInternalBorderStrokeFill=this.quadrantInternalBorderStrokeFill||this.primaryBorderColor,this.quadrantExternalBorderStrokeFill=this.quadrantExternalBorderStrokeFill||this.primaryBorderColor,this.quadrantTitleFill=this.quadrantTitleFill||this.primaryTextColor,this.xyChart={backgroundColor:((f=this.xyChart)==null?void 0:f.backgroundColor)||this.background,titleColor:((d=this.xyChart)==null?void 0:d.titleColor)||this.primaryTextColor,xAxisTitleColor:((p=this.xyChart)==null?void 0:p.xAxisTitleColor)||this.primaryTextColor,xAxisLabelColor:((m=this.xyChart)==null?void 0:m.xAxisLabelColor)||this.primaryTextColor,xAxisTickColor:((y=this.xyChart)==null?void 0:y.xAxisTickColor)||this.primaryTextColor,xAxisLineColor:((x=this.xyChart)==null?void 0:x.xAxisLineColor)||this.primaryTextColor,yAxisTitleColor:((b=this.xyChart)==null?void 0:b.yAxisTitleColor)||this.primaryTextColor,yAxisLabelColor:((C=this.xyChart)==null?void 0:C.yAxisLabelColor)||this.primaryTextColor,yAxisTickColor:((k=this.xyChart)==null?void 0:k.yAxisTickColor)||this.primaryTextColor,yAxisLineColor:((w=this.xyChart)==null?void 0:w.yAxisLineColor)||this.primaryTextColor,plotColorPalette:((_=this.xyChart)==null?void 0:_.plotColorPalette)||"#FFF4DD,#FFD8B1,#FFA07A,#ECEFF1,#D6DBDF,#C3E0A8,#FFB6A4,#FFD74D,#738FA7,#FFFFF0"},this.requirementBackground=this.requirementBackground||this.primaryColor,this.requirementBorderColor=this.requirementBorderColor||this.primaryBorderColor,this.requirementBorderSize=this.requirementBorderSize||"1",this.requirementTextColor=this.requirementTextColor||this.primaryTextColor,this.relationColor=this.relationColor||this.lineColor,this.relationLabelBackground=this.relationLabelBackground||(this.darkMode?it(this.secondaryColor,30):this.secondaryColor),this.relationLabelColor=this.relationLabelColor||this.actorTextColor,this.git0=this.git0||this.primaryColor,this.git1=this.git1||this.secondaryColor,this.git2=this.git2||this.tertiaryColor,this.git3=this.git3||A(this.primaryColor,{h:-30}),this.git4=this.git4||A(this.primaryColor,{h:-60}),this.git5=this.git5||A(this.primaryColor,{h:-90}),this.git6=this.git6||A(this.primaryColor,{h:60}),this.git7=this.git7||A(this.primaryColor,{h:120}),this.darkMode?(this.git0=G(this.git0,25),this.git1=G(this.git1,25),this.git2=G(this.git2,25),this.git3=G(this.git3,25),this.git4=G(this.git4,25),this.git5=G(this.git5,25),this.git6=G(this.git6,25),this.git7=G(this.git7,25)):(this.git0=it(this.git0,25),this.git1=it(this.git1,25),this.git2=it(this.git2,25),this.git3=it(this.git3,25),this.git4=it(this.git4,25),this.git5=it(this.git5,25),this.git6=it(this.git6,25),this.git7=it(this.git7,25)),this.gitInv0=this.gitInv0||H(this.git0),this.gitInv1=this.gitInv1||H(this.git1),this.gitInv2=this.gitInv2||H(this.git2),this.gitInv3=this.gitInv3||H(this.git3),this.gitInv4=this.gitInv4||H(this.git4),this.gitInv5=this.gitInv5||H(this.git5),this.gitInv6=this.gitInv6||H(this.git6),this.gitInv7=this.gitInv7||H(this.git7),this.branchLabelColor=this.branchLabelColor||(this.darkMode?"black":this.labelTextColor),this.gitBranchLabel0=this.gitBranchLabel0||this.branchLabelColor,this.gitBranchLabel1=this.gitBranchLabel1||this.branchLabelColor,this.gitBranchLabel2=this.gitBranchLabel2||this.branchLabelColor,this.gitBranchLabel3=this.gitBranchLabel3||this.branchLabelColor,this.gitBranchLabel4=this.gitBranchLabel4||this.branchLabelColor,this.gitBranchLabel5=this.gitBranchLabel5||this.branchLabelColor,this.gitBranchLabel6=this.gitBranchLabel6||this.branchLabelColor,this.gitBranchLabel7=this.gitBranchLabel7||this.branchLabelColor,this.tagLabelColor=this.tagLabelColor||this.primaryTextColor,this.tagLabelBackground=this.tagLabelBackground||this.primaryColor,this.tagLabelBorder=this.tagBorder||this.primaryBorderColor,this.tagLabelFontSize=this.tagLabelFontSize||"10px",this.commitLabelColor=this.commitLabelColor||this.secondaryTextColor,this.commitLabelBackground=this.commitLabelBackground||this.secondaryColor,this.commitLabelFontSize=this.commitLabelFontSize||"10px",this.attributeBackgroundColorOdd=this.attributeBackgroundColorOdd||ys,this.attributeBackgroundColorEven=this.attributeBackgroundColorEven||xs}calculate(t){if(typeof t!="object"){this.updateColors();return}const r=Object.keys(t);r.forEach(i=>{this[i]=t[i]}),this.updateColors(),r.forEach(i=>{this[i]=t[i]})}},g(li,"Theme"),li),Ix=g(e=>{const t=new Rx;return t.calculate(e),t},"getThemeVariables"),ci,Px=(ci=class{constructor(){this.background="#333",this.primaryColor="#1f2020",this.secondaryColor=G(this.primaryColor,16),this.tertiaryColor=A(this.primaryColor,{h:-160}),this.primaryBorderColor=H(this.background),this.secondaryBorderColor=Jt(this.secondaryColor,this.darkMode),this.tertiaryBorderColor=Jt(this.tertiaryColor,this.darkMode),this.primaryTextColor=H(this.primaryColor),this.secondaryTextColor=H(this.secondaryColor),this.tertiaryTextColor=H(this.tertiaryColor),this.lineColor=H(this.background),this.textColor=H(this.background),this.mainBkg="#1f2020",this.secondBkg="calculated",this.mainContrastColor="lightgrey",this.darkTextColor=G(H("#323D47"),10),this.lineColor="calculated",this.border1="#ccc",this.border2=hn(255,255,255,.25),this.arrowheadColor="calculated",this.fontFamily='"trebuchet ms", verdana, arial, sans-serif',this.fontSize="16px",this.labelBackground="#181818",this.textColor="#ccc",this.THEME_COLOR_LIMIT=12,this.nodeBkg="calculated",this.nodeBorder="calculated",this.clusterBkg="calculated",this.clusterBorder="calculated",this.defaultLinkColor="calculated",this.titleColor="#F9FFFE",this.edgeLabelBackground="calculated",this.actorBorder="calculated",this.actorBkg="calculated",this.actorTextColor="calculated",this.actorLineColor="calculated",this.signalColor="calculated",this.signalTextColor="calculated",this.labelBoxBkgColor="calculated",this.labelBoxBorderColor="calculated",this.labelTextColor="calculated",this.loopTextColor="calculated",this.noteBorderColor="calculated",this.noteBkgColor="#fff5ad",this.noteTextColor="calculated",this.activationBorderColor="calculated",this.activationBkgColor="calculated",this.sequenceNumberColor="black",this.sectionBkgColor=it("#EAE8D9",30),this.altSectionBkgColor="calculated",this.sectionBkgColor2="#EAE8D9",this.excludeBkgColor=it(this.sectionBkgColor,10),this.taskBorderColor=hn(255,255,255,70),this.taskBkgColor="calculated",this.taskTextColor="calculated",this.taskTextLightColor="calculated",this.taskTextOutsideColor="calculated",this.taskTextClickableColor="#003163",this.activeTaskBorderColor=hn(255,255,255,50),this.activeTaskBkgColor="#81B1DB",this.gridColor="calculated",this.doneTaskBkgColor="calculated",this.doneTaskBorderColor="grey",this.critBorderColor="#E83737",this.critBkgColor="#E83737",this.taskTextDarkColor="calculated",this.todayLineColor="#DB5757",this.vertLineColor="#00BFFF",this.personBorder=this.primaryBorderColor,this.personBkg=this.mainBkg,this.archEdgeColor="calculated",this.archEdgeArrowColor="calculated",this.archEdgeWidth="3",this.archGroupBorderColor=this.primaryBorderColor,this.archGroupBorderWidth="2px",this.rowOdd=this.rowOdd||G(this.mainBkg,5)||"#ffffff",this.rowEven=this.rowEven||it(this.mainBkg,10),this.labelColor="calculated",this.errorBkgColor="#a44141",this.errorTextColor="#ddd"}updateColors(){var t,r,i,n,a,o,s,c,l,h,u,f,d,p,m,y,x,b,C,k,w;this.secondBkg=G(this.mainBkg,16),this.lineColor=this.mainContrastColor,this.arrowheadColor=this.mainContrastColor,this.nodeBkg=this.mainBkg,this.nodeBorder=this.border1,this.clusterBkg=this.secondBkg,this.clusterBorder=this.border2,this.defaultLinkColor=this.lineColor,this.edgeLabelBackground=G(this.labelBackground,25),this.actorBorder=this.border1,this.actorBkg=this.mainBkg,this.actorTextColor=this.mainContrastColor,this.actorLineColor=this.actorBorder,this.signalColor=this.mainContrastColor,this.signalTextColor=this.mainContrastColor,this.labelBoxBkgColor=this.actorBkg,this.labelBoxBorderColor=this.actorBorder,this.labelTextColor=this.mainContrastColor,this.loopTextColor=this.mainContrastColor,this.noteBorderColor=this.secondaryBorderColor,this.noteBkgColor=this.secondBkg,this.noteTextColor=this.secondaryTextColor,this.activationBorderColor=this.border1,this.activationBkgColor=this.secondBkg,this.altSectionBkgColor=this.background,this.taskBkgColor=G(this.mainBkg,23),this.taskTextColor=this.darkTextColor,this.taskTextLightColor=this.mainContrastColor,this.taskTextOutsideColor=this.taskTextLightColor,this.gridColor=this.mainContrastColor,this.doneTaskBkgColor=this.mainContrastColor,this.taskTextDarkColor=this.darkTextColor,this.archEdgeColor=this.lineColor,this.archEdgeArrowColor=this.lineColor,this.transitionColor=this.transitionColor||this.lineColor,this.transitionLabelColor=this.transitionLabelColor||this.textColor,this.stateLabelColor=this.stateLabelColor||this.stateBkg||this.primaryTextColor,this.stateBkg=this.stateBkg||this.mainBkg,this.labelBackgroundColor=this.labelBackgroundColor||this.stateBkg,this.compositeBackground=this.compositeBackground||this.background||this.tertiaryColor,this.altBackground=this.altBackground||"#555",this.compositeTitleBackground=this.compositeTitleBackground||this.mainBkg,this.compositeBorder=this.compositeBorder||this.nodeBorder,this.innerEndBackground=this.primaryBorderColor,this.specialStateColor="#f4f4f4",this.errorBkgColor=this.errorBkgColor||this.tertiaryColor,this.errorTextColor=this.errorTextColor||this.tertiaryTextColor,this.fillType0=this.primaryColor,this.fillType1=this.secondaryColor,this.fillType2=A(this.primaryColor,{h:64}),this.fillType3=A(this.secondaryColor,{h:64}),this.fillType4=A(this.primaryColor,{h:-64}),this.fillType5=A(this.secondaryColor,{h:-64}),this.fillType6=A(this.primaryColor,{h:128}),this.fillType7=A(this.secondaryColor,{h:128}),this.cScale1=this.cScale1||"#0b0000",this.cScale2=this.cScale2||"#4d1037",this.cScale3=this.cScale3||"#3f5258",this.cScale4=this.cScale4||"#4f2f1b",this.cScale5=this.cScale5||"#6e0a0a",this.cScale6=this.cScale6||"#3b0048",this.cScale7=this.cScale7||"#995a01",this.cScale8=this.cScale8||"#154706",this.cScale9=this.cScale9||"#161722",this.cScale10=this.cScale10||"#00296f",this.cScale11=this.cScale11||"#01629c",this.cScale12=this.cScale12||"#010029",this.cScale0=this.cScale0||this.primaryColor,this.cScale1=this.cScale1||this.secondaryColor,this.cScale2=this.cScale2||this.tertiaryColor,this.cScale3=this.cScale3||A(this.primaryColor,{h:30}),this.cScale4=this.cScale4||A(this.primaryColor,{h:60}),this.cScale5=this.cScale5||A(this.primaryColor,{h:90}),this.cScale6=this.cScale6||A(this.primaryColor,{h:120}),this.cScale7=this.cScale7||A(this.primaryColor,{h:150}),this.cScale8=this.cScale8||A(this.primaryColor,{h:210}),this.cScale9=this.cScale9||A(this.primaryColor,{h:270}),this.cScale10=this.cScale10||A(this.primaryColor,{h:300}),this.cScale11=this.cScale11||A(this.primaryColor,{h:330});for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["cScaleInv"+_]=this["cScaleInv"+_]||H(this["cScale"+_]);for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["cScalePeer"+_]=this["cScalePeer"+_]||G(this["cScale"+_],10);for(let _=0;_<5;_++)this["surface"+_]=this["surface"+_]||A(this.mainBkg,{h:30,s:-30,l:-(-10+_*4)}),this["surfacePeer"+_]=this["surfacePeer"+_]||A(this.mainBkg,{h:30,s:-30,l:-(-7+_*4)});this.scaleLabelColor=this.scaleLabelColor||(this.darkMode?"black":this.labelTextColor);for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["cScaleLabel"+_]=this["cScaleLabel"+_]||this.scaleLabelColor;for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["pie"+_]=this["cScale"+_];this.pieTitleTextSize=this.pieTitleTextSize||"25px",this.pieTitleTextColor=this.pieTitleTextColor||this.taskTextDarkColor,this.pieSectionTextSize=this.pieSectionTextSize||"17px",this.pieSectionTextColor=this.pieSectionTextColor||this.textColor,this.pieLegendTextSize=this.pieLegendTextSize||"17px",this.pieLegendTextColor=this.pieLegendTextColor||this.taskTextDarkColor,this.pieStrokeColor=this.pieStrokeColor||"black",this.pieStrokeWidth=this.pieStrokeWidth||"2px",this.pieOuterStrokeWidth=this.pieOuterStrokeWidth||"2px",this.pieOuterStrokeColor=this.pieOuterStrokeColor||"black",this.pieOpacity=this.pieOpacity||"0.7",this.quadrant1Fill=this.quadrant1Fill||this.primaryColor,this.quadrant2Fill=this.quadrant2Fill||A(this.primaryColor,{r:5,g:5,b:5}),this.quadrant3Fill=this.quadrant3Fill||A(this.primaryColor,{r:10,g:10,b:10}),this.quadrant4Fill=this.quadrant4Fill||A(this.primaryColor,{r:15,g:15,b:15}),this.quadrant1TextFill=this.quadrant1TextFill||this.primaryTextColor,this.quadrant2TextFill=this.quadrant2TextFill||A(this.primaryTextColor,{r:-5,g:-5,b:-5}),this.quadrant3TextFill=this.quadrant3TextFill||A(this.primaryTextColor,{r:-10,g:-10,b:-10}),this.quadrant4TextFill=this.quadrant4TextFill||A(this.primaryTextColor,{r:-15,g:-15,b:-15}),this.quadrantPointFill=this.quadrantPointFill||An(this.quadrant1Fill)?G(this.quadrant1Fill):it(this.quadrant1Fill),this.quadrantPointTextFill=this.quadrantPointTextFill||this.primaryTextColor,this.quadrantXAxisTextFill=this.quadrantXAxisTextFill||this.primaryTextColor,this.quadrantYAxisTextFill=this.quadrantYAxisTextFill||this.primaryTextColor,this.quadrantInternalBorderStrokeFill=this.quadrantInternalBorderStrokeFill||this.primaryBorderColor,this.quadrantExternalBorderStrokeFill=this.quadrantExternalBorderStrokeFill||this.primaryBorderColor,this.quadrantTitleFill=this.quadrantTitleFill||this.primaryTextColor,this.xyChart={backgroundColor:((t=this.xyChart)==null?void 0:t.backgroundColor)||this.background,titleColor:((r=this.xyChart)==null?void 0:r.titleColor)||this.primaryTextColor,xAxisTitleColor:((i=this.xyChart)==null?void 0:i.xAxisTitleColor)||this.primaryTextColor,xAxisLabelColor:((n=this.xyChart)==null?void 0:n.xAxisLabelColor)||this.primaryTextColor,xAxisTickColor:((a=this.xyChart)==null?void 0:a.xAxisTickColor)||this.primaryTextColor,xAxisLineColor:((o=this.xyChart)==null?void 0:o.xAxisLineColor)||this.primaryTextColor,yAxisTitleColor:((s=this.xyChart)==null?void 0:s.yAxisTitleColor)||this.primaryTextColor,yAxisLabelColor:((c=this.xyChart)==null?void 0:c.yAxisLabelColor)||this.primaryTextColor,yAxisTickColor:((l=this.xyChart)==null?void 0:l.yAxisTickColor)||this.primaryTextColor,yAxisLineColor:((h=this.xyChart)==null?void 0:h.yAxisLineColor)||this.primaryTextColor,plotColorPalette:((u=this.xyChart)==null?void 0:u.plotColorPalette)||"#3498db,#2ecc71,#e74c3c,#f1c40f,#bdc3c7,#ffffff,#34495e,#9b59b6,#1abc9c,#e67e22"},this.packet={startByteColor:this.primaryTextColor,endByteColor:this.primaryTextColor,labelColor:this.primaryTextColor,titleColor:this.primaryTextColor,blockStrokeColor:this.primaryTextColor,blockFillColor:this.background},this.radar={axisColor:((f=this.radar)==null?void 0:f.axisColor)||this.lineColor,axisStrokeWidth:((d=this.radar)==null?void 0:d.axisStrokeWidth)||2,axisLabelFontSize:((p=this.radar)==null?void 0:p.axisLabelFontSize)||12,curveOpacity:((m=this.radar)==null?void 0:m.curveOpacity)||.5,curveStrokeWidth:((y=this.radar)==null?void 0:y.curveStrokeWidth)||2,graticuleColor:((x=this.radar)==null?void 0:x.graticuleColor)||"#DEDEDE",graticuleStrokeWidth:((b=this.radar)==null?void 0:b.graticuleStrokeWidth)||1,graticuleOpacity:((C=this.radar)==null?void 0:C.graticuleOpacity)||.3,legendBoxSize:((k=this.radar)==null?void 0:k.legendBoxSize)||12,legendFontSize:((w=this.radar)==null?void 0:w.legendFontSize)||12},this.classText=this.primaryTextColor,this.requirementBackground=this.requirementBackground||this.primaryColor,this.requirementBorderColor=this.requirementBorderColor||this.primaryBorderColor,this.requirementBorderSize=this.requirementBorderSize||"1",this.requirementTextColor=this.requirementTextColor||this.primaryTextColor,this.relationColor=this.relationColor||this.lineColor,this.relationLabelBackground=this.relationLabelBackground||(this.darkMode?it(this.secondaryColor,30):this.secondaryColor),this.relationLabelColor=this.relationLabelColor||this.actorTextColor,this.git0=G(this.secondaryColor,20),this.git1=G(this.pie2||this.secondaryColor,20),this.git2=G(this.pie3||this.tertiaryColor,20),this.git3=G(this.pie4||A(this.primaryColor,{h:-30}),20),this.git4=G(this.pie5||A(this.primaryColor,{h:-60}),20),this.git5=G(this.pie6||A(this.primaryColor,{h:-90}),10),this.git6=G(this.pie7||A(this.primaryColor,{h:60}),10),this.git7=G(this.pie8||A(this.primaryColor,{h:120}),20),this.gitInv0=this.gitInv0||H(this.git0),this.gitInv1=this.gitInv1||H(this.git1),this.gitInv2=this.gitInv2||H(this.git2),this.gitInv3=this.gitInv3||H(this.git3),this.gitInv4=this.gitInv4||H(this.git4),this.gitInv5=this.gitInv5||H(this.git5),this.gitInv6=this.gitInv6||H(this.git6),this.gitInv7=this.gitInv7||H(this.git7),this.gitBranchLabel0=this.gitBranchLabel0||H(this.labelTextColor),this.gitBranchLabel1=this.gitBranchLabel1||this.labelTextColor,this.gitBranchLabel2=this.gitBranchLabel2||this.labelTextColor,this.gitBranchLabel3=this.gitBranchLabel3||H(this.labelTextColor),this.gitBranchLabel4=this.gitBranchLabel4||this.labelTextColor,this.gitBranchLabel5=this.gitBranchLabel5||this.labelTextColor,this.gitBranchLabel6=this.gitBranchLabel6||this.labelTextColor,this.gitBranchLabel7=this.gitBranchLabel7||this.labelTextColor,this.tagLabelColor=this.tagLabelColor||this.primaryTextColor,this.tagLabelBackground=this.tagLabelBackground||this.primaryColor,this.tagLabelBorder=this.tagBorder||this.primaryBorderColor,this.tagLabelFontSize=this.tagLabelFontSize||"10px",this.commitLabelColor=this.commitLabelColor||this.secondaryTextColor,this.commitLabelBackground=this.commitLabelBackground||this.secondaryColor,this.commitLabelFontSize=this.commitLabelFontSize||"10px",this.attributeBackgroundColorOdd=this.attributeBackgroundColorOdd||G(this.background,12),this.attributeBackgroundColorEven=this.attributeBackgroundColorEven||G(this.background,2),this.nodeBorder=this.nodeBorder||"#999"}calculate(t){if(typeof t!="object"){this.updateColors();return}const r=Object.keys(t);r.forEach(i=>{this[i]=t[i]}),this.updateColors(),r.forEach(i=>{this[i]=t[i]})}},g(ci,"Theme"),ci),Nx=g(e=>{const t=new Px;return t.calculate(e),t},"getThemeVariables"),hi,zx=(hi=class{constructor(){this.background="#f4f4f4",this.primaryColor="#ECECFF",this.secondaryColor=A(this.primaryColor,{h:120}),this.secondaryColor="#ffffde",this.tertiaryColor=A(this.primaryColor,{h:-160}),this.primaryBorderColor=Jt(this.primaryColor,this.darkMode),this.secondaryBorderColor=Jt(this.secondaryColor,this.darkMode),this.tertiaryBorderColor=Jt(this.tertiaryColor,this.darkMode),this.primaryTextColor=H(this.primaryColor),this.secondaryTextColor=H(this.secondaryColor),this.tertiaryTextColor=H(this.tertiaryColor),this.lineColor=H(this.background),this.textColor=H(this.background),this.background="white",this.mainBkg="#ECECFF",this.secondBkg="#ffffde",this.lineColor="#333333",this.border1="#9370DB",this.border2="#aaaa33",this.arrowheadColor="#333333",this.fontFamily='"trebuchet ms", verdana, arial, sans-serif',this.fontSize="16px",this.labelBackground="rgba(232,232,232, 0.8)",this.textColor="#333",this.THEME_COLOR_LIMIT=12,this.nodeBkg="calculated",this.nodeBorder="calculated",this.clusterBkg="calculated",this.clusterBorder="calculated",this.defaultLinkColor="calculated",this.titleColor="calculated",this.edgeLabelBackground="calculated",this.actorBorder="calculated",this.actorBkg="calculated",this.actorTextColor="black",this.actorLineColor="calculated",this.signalColor="calculated",this.signalTextColor="calculated",this.labelBoxBkgColor="calculated",this.labelBoxBorderColor="calculated",this.labelTextColor="calculated",this.loopTextColor="calculated",this.noteBorderColor="calculated",this.noteBkgColor="#fff5ad",this.noteTextColor="calculated",this.activationBorderColor="#666",this.activationBkgColor="#f4f4f4",this.sequenceNumberColor="white",this.sectionBkgColor="calculated",this.altSectionBkgColor="calculated",this.sectionBkgColor2="calculated",this.excludeBkgColor="#eeeeee",this.taskBorderColor="calculated",this.taskBkgColor="calculated",this.taskTextLightColor="calculated",this.taskTextColor=this.taskTextLightColor,this.taskTextDarkColor="calculated",this.taskTextOutsideColor=this.taskTextDarkColor,this.taskTextClickableColor="calculated",this.activeTaskBorderColor="calculated",this.activeTaskBkgColor="calculated",this.gridColor="calculated",this.doneTaskBkgColor="calculated",this.doneTaskBorderColor="calculated",this.critBorderColor="calculated",this.critBkgColor="calculated",this.todayLineColor="calculated",this.vertLineColor="calculated",this.sectionBkgColor=hn(102,102,255,.49),this.altSectionBkgColor="white",this.sectionBkgColor2="#fff400",this.taskBorderColor="#534fbc",this.taskBkgColor="#8a90dd",this.taskTextLightColor="white",this.taskTextColor="calculated",this.taskTextDarkColor="black",this.taskTextOutsideColor="calculated",this.taskTextClickableColor="#003163",this.activeTaskBorderColor="#534fbc",this.activeTaskBkgColor="#bfc7ff",this.gridColor="lightgrey",this.doneTaskBkgColor="lightgrey",this.doneTaskBorderColor="grey",this.critBorderColor="#ff8888",this.critBkgColor="red",this.todayLineColor="red",this.vertLineColor="navy",this.personBorder=this.primaryBorderColor,this.personBkg=this.mainBkg,this.archEdgeColor="calculated",this.archEdgeArrowColor="calculated",this.archEdgeWidth="3",this.archGroupBorderColor=this.primaryBorderColor,this.archGroupBorderWidth="2px",this.rowOdd="calculated",this.rowEven="calculated",this.labelColor="black",this.errorBkgColor="#552222",this.errorTextColor="#552222",this.updateColors()}updateColors(){var t,r,i,n,a,o,s,c,l,h,u,f,d,p,m,y,x,b,C,k,w;this.cScale0=this.cScale0||this.primaryColor,this.cScale1=this.cScale1||this.secondaryColor,this.cScale2=this.cScale2||this.tertiaryColor,this.cScale3=this.cScale3||A(this.primaryColor,{h:30}),this.cScale4=this.cScale4||A(this.primaryColor,{h:60}),this.cScale5=this.cScale5||A(this.primaryColor,{h:90}),this.cScale6=this.cScale6||A(this.primaryColor,{h:120}),this.cScale7=this.cScale7||A(this.primaryColor,{h:150}),this.cScale8=this.cScale8||A(this.primaryColor,{h:210}),this.cScale9=this.cScale9||A(this.primaryColor,{h:270}),this.cScale10=this.cScale10||A(this.primaryColor,{h:300}),this.cScale11=this.cScale11||A(this.primaryColor,{h:330}),this.cScalePeer1=this.cScalePeer1||it(this.secondaryColor,45),this.cScalePeer2=this.cScalePeer2||it(this.tertiaryColor,40);for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["cScale"+_]=it(this["cScale"+_],10),this["cScalePeer"+_]=this["cScalePeer"+_]||it(this["cScale"+_],25);for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["cScaleInv"+_]=this["cScaleInv"+_]||A(this["cScale"+_],{h:180});for(let _=0;_<5;_++)this["surface"+_]=this["surface"+_]||A(this.mainBkg,{h:30,l:-(5+_*5)}),this["surfacePeer"+_]=this["surfacePeer"+_]||A(this.mainBkg,{h:30,l:-(7+_*5)});if(this.scaleLabelColor=this.scaleLabelColor!=="calculated"&&this.scaleLabelColor?this.scaleLabelColor:this.labelTextColor,this.labelTextColor!=="calculated"){this.cScaleLabel0=this.cScaleLabel0||H(this.labelTextColor),this.cScaleLabel3=this.cScaleLabel3||H(this.labelTextColor);for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["cScaleLabel"+_]=this["cScaleLabel"+_]||this.labelTextColor}this.nodeBkg=this.mainBkg,this.nodeBorder=this.border1,this.clusterBkg=this.secondBkg,this.clusterBorder=this.border2,this.defaultLinkColor=this.lineColor,this.titleColor=this.textColor,this.edgeLabelBackground=this.labelBackground,this.actorBorder=G(this.border1,23),this.actorBkg=this.mainBkg,this.labelBoxBkgColor=this.actorBkg,this.signalColor=this.textColor,this.signalTextColor=this.textColor,this.labelBoxBorderColor=this.actorBorder,this.labelTextColor=this.actorTextColor,this.loopTextColor=this.actorTextColor,this.noteBorderColor=this.border2,this.noteTextColor=this.actorTextColor,this.actorLineColor=this.actorBorder,this.taskTextColor=this.taskTextLightColor,this.taskTextOutsideColor=this.taskTextDarkColor,this.archEdgeColor=this.lineColor,this.archEdgeArrowColor=this.lineColor,this.rowOdd=this.rowOdd||G(this.primaryColor,75)||"#ffffff",this.rowEven=this.rowEven||G(this.primaryColor,1),this.transitionColor=this.transitionColor||this.lineColor,this.transitionLabelColor=this.transitionLabelColor||this.textColor,this.stateLabelColor=this.stateLabelColor||this.stateBkg||this.primaryTextColor,this.stateBkg=this.stateBkg||this.mainBkg,this.labelBackgroundColor=this.labelBackgroundColor||this.stateBkg,this.compositeBackground=this.compositeBackground||this.background||this.tertiaryColor,this.altBackground=this.altBackground||"#f0f0f0",this.compositeTitleBackground=this.compositeTitleBackground||this.mainBkg,this.compositeBorder=this.compositeBorder||this.nodeBorder,this.innerEndBackground=this.nodeBorder,this.specialStateColor=this.lineColor,this.errorBkgColor=this.errorBkgColor||this.tertiaryColor,this.errorTextColor=this.errorTextColor||this.tertiaryTextColor,this.transitionColor=this.transitionColor||this.lineColor,this.classText=this.primaryTextColor,this.fillType0=this.primaryColor,this.fillType1=this.secondaryColor,this.fillType2=A(this.primaryColor,{h:64}),this.fillType3=A(this.secondaryColor,{h:64}),this.fillType4=A(this.primaryColor,{h:-64}),this.fillType5=A(this.secondaryColor,{h:-64}),this.fillType6=A(this.primaryColor,{h:128}),this.fillType7=A(this.secondaryColor,{h:128}),this.pie1=this.pie1||this.primaryColor,this.pie2=this.pie2||this.secondaryColor,this.pie3=this.pie3||A(this.tertiaryColor,{l:-40}),this.pie4=this.pie4||A(this.primaryColor,{l:-10}),this.pie5=this.pie5||A(this.secondaryColor,{l:-30}),this.pie6=this.pie6||A(this.tertiaryColor,{l:-20}),this.pie7=this.pie7||A(this.primaryColor,{h:60,l:-20}),this.pie8=this.pie8||A(this.primaryColor,{h:-60,l:-40}),this.pie9=this.pie9||A(this.primaryColor,{h:120,l:-40}),this.pie10=this.pie10||A(this.primaryColor,{h:60,l:-40}),this.pie11=this.pie11||A(this.primaryColor,{h:-90,l:-40}),this.pie12=this.pie12||A(this.primaryColor,{h:120,l:-30}),this.pieTitleTextSize=this.pieTitleTextSize||"25px",this.pieTitleTextColor=this.pieTitleTextColor||this.taskTextDarkColor,this.pieSectionTextSize=this.pieSectionTextSize||"17px",this.pieSectionTextColor=this.pieSectionTextColor||this.textColor,this.pieLegendTextSize=this.pieLegendTextSize||"17px",this.pieLegendTextColor=this.pieLegendTextColor||this.taskTextDarkColor,this.pieStrokeColor=this.pieStrokeColor||"black",this.pieStrokeWidth=this.pieStrokeWidth||"2px",this.pieOuterStrokeWidth=this.pieOuterStrokeWidth||"2px",this.pieOuterStrokeColor=this.pieOuterStrokeColor||"black",this.pieOpacity=this.pieOpacity||"0.7",this.quadrant1Fill=this.quadrant1Fill||this.primaryColor,this.quadrant2Fill=this.quadrant2Fill||A(this.primaryColor,{r:5,g:5,b:5}),this.quadrant3Fill=this.quadrant3Fill||A(this.primaryColor,{r:10,g:10,b:10}),this.quadrant4Fill=this.quadrant4Fill||A(this.primaryColor,{r:15,g:15,b:15}),this.quadrant1TextFill=this.quadrant1TextFill||this.primaryTextColor,this.quadrant2TextFill=this.quadrant2TextFill||A(this.primaryTextColor,{r:-5,g:-5,b:-5}),this.quadrant3TextFill=this.quadrant3TextFill||A(this.primaryTextColor,{r:-10,g:-10,b:-10}),this.quadrant4TextFill=this.quadrant4TextFill||A(this.primaryTextColor,{r:-15,g:-15,b:-15}),this.quadrantPointFill=this.quadrantPointFill||An(this.quadrant1Fill)?G(this.quadrant1Fill):it(this.quadrant1Fill),this.quadrantPointTextFill=this.quadrantPointTextFill||this.primaryTextColor,this.quadrantXAxisTextFill=this.quadrantXAxisTextFill||this.primaryTextColor,this.quadrantYAxisTextFill=this.quadrantYAxisTextFill||this.primaryTextColor,this.quadrantInternalBorderStrokeFill=this.quadrantInternalBorderStrokeFill||this.primaryBorderColor,this.quadrantExternalBorderStrokeFill=this.quadrantExternalBorderStrokeFill||this.primaryBorderColor,this.quadrantTitleFill=this.quadrantTitleFill||this.primaryTextColor,this.radar={axisColor:((t=this.radar)==null?void 0:t.axisColor)||this.lineColor,axisStrokeWidth:((r=this.radar)==null?void 0:r.axisStrokeWidth)||2,axisLabelFontSize:((i=this.radar)==null?void 0:i.axisLabelFontSize)||12,curveOpacity:((n=this.radar)==null?void 0:n.curveOpacity)||.5,curveStrokeWidth:((a=this.radar)==null?void 0:a.curveStrokeWidth)||2,graticuleColor:((o=this.radar)==null?void 0:o.graticuleColor)||"#DEDEDE",graticuleStrokeWidth:((s=this.radar)==null?void 0:s.graticuleStrokeWidth)||1,graticuleOpacity:((c=this.radar)==null?void 0:c.graticuleOpacity)||.3,legendBoxSize:((l=this.radar)==null?void 0:l.legendBoxSize)||12,legendFontSize:((h=this.radar)==null?void 0:h.legendFontSize)||12},this.xyChart={backgroundColor:((u=this.xyChart)==null?void 0:u.backgroundColor)||this.background,titleColor:((f=this.xyChart)==null?void 0:f.titleColor)||this.primaryTextColor,xAxisTitleColor:((d=this.xyChart)==null?void 0:d.xAxisTitleColor)||this.primaryTextColor,xAxisLabelColor:((p=this.xyChart)==null?void 0:p.xAxisLabelColor)||this.primaryTextColor,xAxisTickColor:((m=this.xyChart)==null?void 0:m.xAxisTickColor)||this.primaryTextColor,xAxisLineColor:((y=this.xyChart)==null?void 0:y.xAxisLineColor)||this.primaryTextColor,yAxisTitleColor:((x=this.xyChart)==null?void 0:x.yAxisTitleColor)||this.primaryTextColor,yAxisLabelColor:((b=this.xyChart)==null?void 0:b.yAxisLabelColor)||this.primaryTextColor,yAxisTickColor:((C=this.xyChart)==null?void 0:C.yAxisTickColor)||this.primaryTextColor,yAxisLineColor:((k=this.xyChart)==null?void 0:k.yAxisLineColor)||this.primaryTextColor,plotColorPalette:((w=this.xyChart)==null?void 0:w.plotColorPalette)||"#ECECFF,#8493A6,#FFC3A0,#DCDDE1,#B8E994,#D1A36F,#C3CDE6,#FFB6C1,#496078,#F8F3E3"},this.requirementBackground=this.requirementBackground||this.primaryColor,this.requirementBorderColor=this.requirementBorderColor||this.primaryBorderColor,this.requirementBorderSize=this.requirementBorderSize||"1",this.requirementTextColor=this.requirementTextColor||this.primaryTextColor,this.relationColor=this.relationColor||this.lineColor,this.relationLabelBackground=this.relationLabelBackground||this.labelBackground,this.relationLabelColor=this.relationLabelColor||this.actorTextColor,this.git0=this.git0||this.primaryColor,this.git1=this.git1||this.secondaryColor,this.git2=this.git2||this.tertiaryColor,this.git3=this.git3||A(this.primaryColor,{h:-30}),this.git4=this.git4||A(this.primaryColor,{h:-60}),this.git5=this.git5||A(this.primaryColor,{h:-90}),this.git6=this.git6||A(this.primaryColor,{h:60}),this.git7=this.git7||A(this.primaryColor,{h:120}),this.darkMode?(this.git0=G(this.git0,25),this.git1=G(this.git1,25),this.git2=G(this.git2,25),this.git3=G(this.git3,25),this.git4=G(this.git4,25),this.git5=G(this.git5,25),this.git6=G(this.git6,25),this.git7=G(this.git7,25)):(this.git0=it(this.git0,25),this.git1=it(this.git1,25),this.git2=it(this.git2,25),this.git3=it(this.git3,25),this.git4=it(this.git4,25),this.git5=it(this.git5,25),this.git6=it(this.git6,25),this.git7=it(this.git7,25)),this.gitInv0=this.gitInv0||it(H(this.git0),25),this.gitInv1=this.gitInv1||H(this.git1),this.gitInv2=this.gitInv2||H(this.git2),this.gitInv3=this.gitInv3||H(this.git3),this.gitInv4=this.gitInv4||H(this.git4),this.gitInv5=this.gitInv5||H(this.git5),this.gitInv6=this.gitInv6||H(this.git6),this.gitInv7=this.gitInv7||H(this.git7),this.gitBranchLabel0=this.gitBranchLabel0||H(this.labelTextColor),this.gitBranchLabel1=this.gitBranchLabel1||this.labelTextColor,this.gitBranchLabel2=this.gitBranchLabel2||this.labelTextColor,this.gitBranchLabel3=this.gitBranchLabel3||H(this.labelTextColor),this.gitBranchLabel4=this.gitBranchLabel4||this.labelTextColor,this.gitBranchLabel5=this.gitBranchLabel5||this.labelTextColor,this.gitBranchLabel6=this.gitBranchLabel6||this.labelTextColor,this.gitBranchLabel7=this.gitBranchLabel7||this.labelTextColor,this.tagLabelColor=this.tagLabelColor||this.primaryTextColor,this.tagLabelBackground=this.tagLabelBackground||this.primaryColor,this.tagLabelBorder=this.tagBorder||this.primaryBorderColor,this.tagLabelFontSize=this.tagLabelFontSize||"10px",this.commitLabelColor=this.commitLabelColor||this.secondaryTextColor,this.commitLabelBackground=this.commitLabelBackground||this.secondaryColor,this.commitLabelFontSize=this.commitLabelFontSize||"10px",this.attributeBackgroundColorOdd=this.attributeBackgroundColorOdd||ys,this.attributeBackgroundColorEven=this.attributeBackgroundColorEven||xs}calculate(t){if(Object.keys(this).forEach(i=>{this[i]==="calculated"&&(this[i]=void 0)}),typeof t!="object"){this.updateColors();return}const r=Object.keys(t);r.forEach(i=>{this[i]=t[i]}),this.updateColors(),r.forEach(i=>{this[i]=t[i]})}},g(hi,"Theme"),hi),Wx=g(e=>{const t=new zx;return t.calculate(e),t},"getThemeVariables"),ui,qx=(ui=class{constructor(){this.background="#f4f4f4",this.primaryColor="#cde498",this.secondaryColor="#cdffb2",this.background="white",this.mainBkg="#cde498",this.secondBkg="#cdffb2",this.lineColor="green",this.border1="#13540c",this.border2="#6eaa49",this.arrowheadColor="green",this.fontFamily='"trebuchet ms", verdana, arial, sans-serif',this.fontSize="16px",this.tertiaryColor=G("#cde498",10),this.primaryBorderColor=Jt(this.primaryColor,this.darkMode),this.secondaryBorderColor=Jt(this.secondaryColor,this.darkMode),this.tertiaryBorderColor=Jt(this.tertiaryColor,this.darkMode),this.primaryTextColor=H(this.primaryColor),this.secondaryTextColor=H(this.secondaryColor),this.tertiaryTextColor=H(this.primaryColor),this.lineColor=H(this.background),this.textColor=H(this.background),this.THEME_COLOR_LIMIT=12,this.nodeBkg="calculated",this.nodeBorder="calculated",this.clusterBkg="calculated",this.clusterBorder="calculated",this.defaultLinkColor="calculated",this.titleColor="#333",this.edgeLabelBackground="#e8e8e8",this.actorBorder="calculated",this.actorBkg="calculated",this.actorTextColor="black",this.actorLineColor="calculated",this.signalColor="#333",this.signalTextColor="#333",this.labelBoxBkgColor="calculated",this.labelBoxBorderColor="#326932",this.labelTextColor="calculated",this.loopTextColor="calculated",this.noteBorderColor="calculated",this.noteBkgColor="#fff5ad",this.noteTextColor="calculated",this.activationBorderColor="#666",this.activationBkgColor="#f4f4f4",this.sequenceNumberColor="white",this.sectionBkgColor="#6eaa49",this.altSectionBkgColor="white",this.sectionBkgColor2="#6eaa49",this.excludeBkgColor="#eeeeee",this.taskBorderColor="calculated",this.taskBkgColor="#487e3a",this.taskTextLightColor="white",this.taskTextColor="calculated",this.taskTextDarkColor="black",this.taskTextOutsideColor="calculated",this.taskTextClickableColor="#003163",this.activeTaskBorderColor="calculated",this.activeTaskBkgColor="calculated",this.gridColor="lightgrey",this.doneTaskBkgColor="lightgrey",this.doneTaskBorderColor="grey",this.critBorderColor="#ff8888",this.critBkgColor="red",this.todayLineColor="red",this.vertLineColor="#00BFFF",this.personBorder=this.primaryBorderColor,this.personBkg=this.mainBkg,this.archEdgeColor="calculated",this.archEdgeArrowColor="calculated",this.archEdgeWidth="3",this.archGroupBorderColor=this.primaryBorderColor,this.archGroupBorderWidth="2px",this.labelColor="black",this.errorBkgColor="#552222",this.errorTextColor="#552222"}updateColors(){var t,r,i,n,a,o,s,c,l,h,u,f,d,p,m,y,x,b,C,k,w;this.actorBorder=it(this.mainBkg,20),this.actorBkg=this.mainBkg,this.labelBoxBkgColor=this.actorBkg,this.labelTextColor=this.actorTextColor,this.loopTextColor=this.actorTextColor,this.noteBorderColor=this.border2,this.noteTextColor=this.actorTextColor,this.actorLineColor=this.actorBorder,this.cScale0=this.cScale0||this.primaryColor,this.cScale1=this.cScale1||this.secondaryColor,this.cScale2=this.cScale2||this.tertiaryColor,this.cScale3=this.cScale3||A(this.primaryColor,{h:30}),this.cScale4=this.cScale4||A(this.primaryColor,{h:60}),this.cScale5=this.cScale5||A(this.primaryColor,{h:90}),this.cScale6=this.cScale6||A(this.primaryColor,{h:120}),this.cScale7=this.cScale7||A(this.primaryColor,{h:150}),this.cScale8=this.cScale8||A(this.primaryColor,{h:210}),this.cScale9=this.cScale9||A(this.primaryColor,{h:270}),this.cScale10=this.cScale10||A(this.primaryColor,{h:300}),this.cScale11=this.cScale11||A(this.primaryColor,{h:330}),this.cScalePeer1=this.cScalePeer1||it(this.secondaryColor,45),this.cScalePeer2=this.cScalePeer2||it(this.tertiaryColor,40);for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["cScale"+_]=it(this["cScale"+_],10),this["cScalePeer"+_]=this["cScalePeer"+_]||it(this["cScale"+_],25);for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["cScaleInv"+_]=this["cScaleInv"+_]||A(this["cScale"+_],{h:180});this.scaleLabelColor=this.scaleLabelColor!=="calculated"&&this.scaleLabelColor?this.scaleLabelColor:this.labelTextColor;for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["cScaleLabel"+_]=this["cScaleLabel"+_]||this.scaleLabelColor;for(let _=0;_<5;_++)this["surface"+_]=this["surface"+_]||A(this.mainBkg,{h:30,s:-30,l:-(5+_*5)}),this["surfacePeer"+_]=this["surfacePeer"+_]||A(this.mainBkg,{h:30,s:-30,l:-(8+_*5)});this.nodeBkg=this.mainBkg,this.nodeBorder=this.border1,this.clusterBkg=this.secondBkg,this.clusterBorder=this.border2,this.defaultLinkColor=this.lineColor,this.taskBorderColor=this.border1,this.taskTextColor=this.taskTextLightColor,this.taskTextOutsideColor=this.taskTextDarkColor,this.activeTaskBorderColor=this.taskBorderColor,this.activeTaskBkgColor=this.mainBkg,this.archEdgeColor=this.lineColor,this.archEdgeArrowColor=this.lineColor,this.rowOdd=this.rowOdd||G(this.mainBkg,75)||"#ffffff",this.rowEven=this.rowEven||G(this.mainBkg,20),this.transitionColor=this.transitionColor||this.lineColor,this.transitionLabelColor=this.transitionLabelColor||this.textColor,this.stateLabelColor=this.stateLabelColor||this.stateBkg||this.primaryTextColor,this.stateBkg=this.stateBkg||this.mainBkg,this.labelBackgroundColor=this.labelBackgroundColor||this.stateBkg,this.compositeBackground=this.compositeBackground||this.background||this.tertiaryColor,this.altBackground=this.altBackground||"#f0f0f0",this.compositeTitleBackground=this.compositeTitleBackground||this.mainBkg,this.compositeBorder=this.compositeBorder||this.nodeBorder,this.innerEndBackground=this.primaryBorderColor,this.specialStateColor=this.lineColor,this.errorBkgColor=this.errorBkgColor||this.tertiaryColor,this.errorTextColor=this.errorTextColor||this.tertiaryTextColor,this.transitionColor=this.transitionColor||this.lineColor,this.classText=this.primaryTextColor,this.fillType0=this.primaryColor,this.fillType1=this.secondaryColor,this.fillType2=A(this.primaryColor,{h:64}),this.fillType3=A(this.secondaryColor,{h:64}),this.fillType4=A(this.primaryColor,{h:-64}),this.fillType5=A(this.secondaryColor,{h:-64}),this.fillType6=A(this.primaryColor,{h:128}),this.fillType7=A(this.secondaryColor,{h:128}),this.pie1=this.pie1||this.primaryColor,this.pie2=this.pie2||this.secondaryColor,this.pie3=this.pie3||this.tertiaryColor,this.pie4=this.pie4||A(this.primaryColor,{l:-30}),this.pie5=this.pie5||A(this.secondaryColor,{l:-30}),this.pie6=this.pie6||A(this.tertiaryColor,{h:40,l:-40}),this.pie7=this.pie7||A(this.primaryColor,{h:60,l:-10}),this.pie8=this.pie8||A(this.primaryColor,{h:-60,l:-10}),this.pie9=this.pie9||A(this.primaryColor,{h:120,l:0}),this.pie10=this.pie10||A(this.primaryColor,{h:60,l:-50}),this.pie11=this.pie11||A(this.primaryColor,{h:-60,l:-50}),this.pie12=this.pie12||A(this.primaryColor,{h:120,l:-50}),this.pieTitleTextSize=this.pieTitleTextSize||"25px",this.pieTitleTextColor=this.pieTitleTextColor||this.taskTextDarkColor,this.pieSectionTextSize=this.pieSectionTextSize||"17px",this.pieSectionTextColor=this.pieSectionTextColor||this.textColor,this.pieLegendTextSize=this.pieLegendTextSize||"17px",this.pieLegendTextColor=this.pieLegendTextColor||this.taskTextDarkColor,this.pieStrokeColor=this.pieStrokeColor||"black",this.pieStrokeWidth=this.pieStrokeWidth||"2px",this.pieOuterStrokeWidth=this.pieOuterStrokeWidth||"2px",this.pieOuterStrokeColor=this.pieOuterStrokeColor||"black",this.pieOpacity=this.pieOpacity||"0.7",this.quadrant1Fill=this.quadrant1Fill||this.primaryColor,this.quadrant2Fill=this.quadrant2Fill||A(this.primaryColor,{r:5,g:5,b:5}),this.quadrant3Fill=this.quadrant3Fill||A(this.primaryColor,{r:10,g:10,b:10}),this.quadrant4Fill=this.quadrant4Fill||A(this.primaryColor,{r:15,g:15,b:15}),this.quadrant1TextFill=this.quadrant1TextFill||this.primaryTextColor,this.quadrant2TextFill=this.quadrant2TextFill||A(this.primaryTextColor,{r:-5,g:-5,b:-5}),this.quadrant3TextFill=this.quadrant3TextFill||A(this.primaryTextColor,{r:-10,g:-10,b:-10}),this.quadrant4TextFill=this.quadrant4TextFill||A(this.primaryTextColor,{r:-15,g:-15,b:-15}),this.quadrantPointFill=this.quadrantPointFill||An(this.quadrant1Fill)?G(this.quadrant1Fill):it(this.quadrant1Fill),this.quadrantPointTextFill=this.quadrantPointTextFill||this.primaryTextColor,this.quadrantXAxisTextFill=this.quadrantXAxisTextFill||this.primaryTextColor,this.quadrantYAxisTextFill=this.quadrantYAxisTextFill||this.primaryTextColor,this.quadrantInternalBorderStrokeFill=this.quadrantInternalBorderStrokeFill||this.primaryBorderColor,this.quadrantExternalBorderStrokeFill=this.quadrantExternalBorderStrokeFill||this.primaryBorderColor,this.quadrantTitleFill=this.quadrantTitleFill||this.primaryTextColor,this.packet={startByteColor:this.primaryTextColor,endByteColor:this.primaryTextColor,labelColor:this.primaryTextColor,titleColor:this.primaryTextColor,blockStrokeColor:this.primaryTextColor,blockFillColor:this.mainBkg},this.radar={axisColor:((t=this.radar)==null?void 0:t.axisColor)||this.lineColor,axisStrokeWidth:((r=this.radar)==null?void 0:r.axisStrokeWidth)||2,axisLabelFontSize:((i=this.radar)==null?void 0:i.axisLabelFontSize)||12,curveOpacity:((n=this.radar)==null?void 0:n.curveOpacity)||.5,curveStrokeWidth:((a=this.radar)==null?void 0:a.curveStrokeWidth)||2,graticuleColor:((o=this.radar)==null?void 0:o.graticuleColor)||"#DEDEDE",graticuleStrokeWidth:((s=this.radar)==null?void 0:s.graticuleStrokeWidth)||1,graticuleOpacity:((c=this.radar)==null?void 0:c.graticuleOpacity)||.3,legendBoxSize:((l=this.radar)==null?void 0:l.legendBoxSize)||12,legendFontSize:((h=this.radar)==null?void 0:h.legendFontSize)||12},this.xyChart={backgroundColor:((u=this.xyChart)==null?void 0:u.backgroundColor)||this.background,titleColor:((f=this.xyChart)==null?void 0:f.titleColor)||this.primaryTextColor,xAxisTitleColor:((d=this.xyChart)==null?void 0:d.xAxisTitleColor)||this.primaryTextColor,xAxisLabelColor:((p=this.xyChart)==null?void 0:p.xAxisLabelColor)||this.primaryTextColor,xAxisTickColor:((m=this.xyChart)==null?void 0:m.xAxisTickColor)||this.primaryTextColor,xAxisLineColor:((y=this.xyChart)==null?void 0:y.xAxisLineColor)||this.primaryTextColor,yAxisTitleColor:((x=this.xyChart)==null?void 0:x.yAxisTitleColor)||this.primaryTextColor,yAxisLabelColor:((b=this.xyChart)==null?void 0:b.yAxisLabelColor)||this.primaryTextColor,yAxisTickColor:((C=this.xyChart)==null?void 0:C.yAxisTickColor)||this.primaryTextColor,yAxisLineColor:((k=this.xyChart)==null?void 0:k.yAxisLineColor)||this.primaryTextColor,plotColorPalette:((w=this.xyChart)==null?void 0:w.plotColorPalette)||"#CDE498,#FF6B6B,#A0D2DB,#D7BDE2,#F0F0F0,#FFC3A0,#7FD8BE,#FF9A8B,#FAF3E0,#FFF176"},this.requirementBackground=this.requirementBackground||this.primaryColor,this.requirementBorderColor=this.requirementBorderColor||this.primaryBorderColor,this.requirementBorderSize=this.requirementBorderSize||"1",this.requirementTextColor=this.requirementTextColor||this.primaryTextColor,this.relationColor=this.relationColor||this.lineColor,this.relationLabelBackground=this.relationLabelBackground||this.edgeLabelBackground,this.relationLabelColor=this.relationLabelColor||this.actorTextColor,this.git0=this.git0||this.primaryColor,this.git1=this.git1||this.secondaryColor,this.git2=this.git2||this.tertiaryColor,this.git3=this.git3||A(this.primaryColor,{h:-30}),this.git4=this.git4||A(this.primaryColor,{h:-60}),this.git5=this.git5||A(this.primaryColor,{h:-90}),this.git6=this.git6||A(this.primaryColor,{h:60}),this.git7=this.git7||A(this.primaryColor,{h:120}),this.darkMode?(this.git0=G(this.git0,25),this.git1=G(this.git1,25),this.git2=G(this.git2,25),this.git3=G(this.git3,25),this.git4=G(this.git4,25),this.git5=G(this.git5,25),this.git6=G(this.git6,25),this.git7=G(this.git7,25)):(this.git0=it(this.git0,25),this.git1=it(this.git1,25),this.git2=it(this.git2,25),this.git3=it(this.git3,25),this.git4=it(this.git4,25),this.git5=it(this.git5,25),this.git6=it(this.git6,25),this.git7=it(this.git7,25)),this.gitInv0=this.gitInv0||H(this.git0),this.gitInv1=this.gitInv1||H(this.git1),this.gitInv2=this.gitInv2||H(this.git2),this.gitInv3=this.gitInv3||H(this.git3),this.gitInv4=this.gitInv4||H(this.git4),this.gitInv5=this.gitInv5||H(this.git5),this.gitInv6=this.gitInv6||H(this.git6),this.gitInv7=this.gitInv7||H(this.git7),this.gitBranchLabel0=this.gitBranchLabel0||H(this.labelTextColor),this.gitBranchLabel1=this.gitBranchLabel1||this.labelTextColor,this.gitBranchLabel2=this.gitBranchLabel2||this.labelTextColor,this.gitBranchLabel3=this.gitBranchLabel3||H(this.labelTextColor),this.gitBranchLabel4=this.gitBranchLabel4||this.labelTextColor,this.gitBranchLabel5=this.gitBranchLabel5||this.labelTextColor,this.gitBranchLabel6=this.gitBranchLabel6||this.labelTextColor,this.gitBranchLabel7=this.gitBranchLabel7||this.labelTextColor,this.tagLabelColor=this.tagLabelColor||this.primaryTextColor,this.tagLabelBackground=this.tagLabelBackground||this.primaryColor,this.tagLabelBorder=this.tagBorder||this.primaryBorderColor,this.tagLabelFontSize=this.tagLabelFontSize||"10px",this.commitLabelColor=this.commitLabelColor||this.secondaryTextColor,this.commitLabelBackground=this.commitLabelBackground||this.secondaryColor,this.commitLabelFontSize=this.commitLabelFontSize||"10px",this.attributeBackgroundColorOdd=this.attributeBackgroundColorOdd||ys,this.attributeBackgroundColorEven=this.attributeBackgroundColorEven||xs}calculate(t){if(typeof t!="object"){this.updateColors();return}const r=Object.keys(t);r.forEach(i=>{this[i]=t[i]}),this.updateColors(),r.forEach(i=>{this[i]=t[i]})}},g(ui,"Theme"),ui),Hx=g(e=>{const t=new qx;return t.calculate(e),t},"getThemeVariables"),fi,Ux=(fi=class{constructor(){this.primaryColor="#eee",this.contrast="#707070",this.secondaryColor=G(this.contrast,55),this.background="#ffffff",this.tertiaryColor=A(this.primaryColor,{h:-160}),this.primaryBorderColor=Jt(this.primaryColor,this.darkMode),this.secondaryBorderColor=Jt(this.secondaryColor,this.darkMode),this.tertiaryBorderColor=Jt(this.tertiaryColor,this.darkMode),this.primaryTextColor=H(this.primaryColor),this.secondaryTextColor=H(this.secondaryColor),this.tertiaryTextColor=H(this.tertiaryColor),this.lineColor=H(this.background),this.textColor=H(this.background),this.mainBkg="#eee",this.secondBkg="calculated",this.lineColor="#666",this.border1="#999",this.border2="calculated",this.note="#ffa",this.text="#333",this.critical="#d42",this.done="#bbb",this.arrowheadColor="#333333",this.fontFamily='"trebuchet ms", verdana, arial, sans-serif',this.fontSize="16px",this.THEME_COLOR_LIMIT=12,this.nodeBkg="calculated",this.nodeBorder="calculated",this.clusterBkg="calculated",this.clusterBorder="calculated",this.defaultLinkColor="calculated",this.titleColor="calculated",this.edgeLabelBackground="white",this.actorBorder="calculated",this.actorBkg="calculated",this.actorTextColor="calculated",this.actorLineColor=this.actorBorder,this.signalColor="calculated",this.signalTextColor="calculated",this.labelBoxBkgColor="calculated",this.labelBoxBorderColor="calculated",this.labelTextColor="calculated",this.loopTextColor="calculated",this.noteBorderColor="calculated",this.noteBkgColor="calculated",this.noteTextColor="calculated",this.activationBorderColor="#666",this.activationBkgColor="#f4f4f4",this.sequenceNumberColor="white",this.sectionBkgColor="calculated",this.altSectionBkgColor="white",this.sectionBkgColor2="calculated",this.excludeBkgColor="#eeeeee",this.taskBorderColor="calculated",this.taskBkgColor="calculated",this.taskTextLightColor="white",this.taskTextColor="calculated",this.taskTextDarkColor="calculated",this.taskTextOutsideColor="calculated",this.taskTextClickableColor="#003163",this.activeTaskBorderColor="calculated",this.activeTaskBkgColor="calculated",this.gridColor="calculated",this.doneTaskBkgColor="calculated",this.doneTaskBorderColor="calculated",this.critBkgColor="calculated",this.critBorderColor="calculated",this.todayLineColor="calculated",this.vertLineColor="calculated",this.personBorder=this.primaryBorderColor,this.personBkg=this.mainBkg,this.archEdgeColor="calculated",this.archEdgeArrowColor="calculated",this.archEdgeWidth="3",this.archGroupBorderColor=this.primaryBorderColor,this.archGroupBorderWidth="2px",this.rowOdd=this.rowOdd||G(this.mainBkg,75)||"#ffffff",this.rowEven=this.rowEven||"#f4f4f4",this.labelColor="black",this.errorBkgColor="#552222",this.errorTextColor="#552222"}updateColors(){var t,r,i,n,a,o,s,c,l,h,u,f,d,p,m,y,x,b,C,k,w;this.secondBkg=G(this.contrast,55),this.border2=this.contrast,this.actorBorder=G(this.border1,23),this.actorBkg=this.mainBkg,this.actorTextColor=this.text,this.actorLineColor=this.actorBorder,this.signalColor=this.text,this.signalTextColor=this.text,this.labelBoxBkgColor=this.actorBkg,this.labelBoxBorderColor=this.actorBorder,this.labelTextColor=this.text,this.loopTextColor=this.text,this.noteBorderColor="#999",this.noteBkgColor="#666",this.noteTextColor="#fff",this.cScale0=this.cScale0||"#555",this.cScale1=this.cScale1||"#F4F4F4",this.cScale2=this.cScale2||"#555",this.cScale3=this.cScale3||"#BBB",this.cScale4=this.cScale4||"#777",this.cScale5=this.cScale5||"#999",this.cScale6=this.cScale6||"#DDD",this.cScale7=this.cScale7||"#FFF",this.cScale8=this.cScale8||"#DDD",this.cScale9=this.cScale9||"#BBB",this.cScale10=this.cScale10||"#999",this.cScale11=this.cScale11||"#777";for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["cScaleInv"+_]=this["cScaleInv"+_]||H(this["cScale"+_]);for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this.darkMode?this["cScalePeer"+_]=this["cScalePeer"+_]||G(this["cScale"+_],10):this["cScalePeer"+_]=this["cScalePeer"+_]||it(this["cScale"+_],10);this.scaleLabelColor=this.scaleLabelColor||(this.darkMode?"black":this.labelTextColor),this.cScaleLabel0=this.cScaleLabel0||this.cScale1,this.cScaleLabel2=this.cScaleLabel2||this.cScale1;for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["cScaleLabel"+_]=this["cScaleLabel"+_]||this.scaleLabelColor;for(let _=0;_<5;_++)this["surface"+_]=this["surface"+_]||A(this.mainBkg,{l:-(5+_*5)}),this["surfacePeer"+_]=this["surfacePeer"+_]||A(this.mainBkg,{l:-(8+_*5)});this.nodeBkg=this.mainBkg,this.nodeBorder=this.border1,this.clusterBkg=this.secondBkg,this.clusterBorder=this.border2,this.defaultLinkColor=this.lineColor,this.titleColor=this.text,this.sectionBkgColor=G(this.contrast,30),this.sectionBkgColor2=G(this.contrast,30),this.taskBorderColor=it(this.contrast,10),this.taskBkgColor=this.contrast,this.taskTextColor=this.taskTextLightColor,this.taskTextDarkColor=this.text,this.taskTextOutsideColor=this.taskTextDarkColor,this.activeTaskBorderColor=this.taskBorderColor,this.activeTaskBkgColor=this.mainBkg,this.gridColor=G(this.border1,30),this.doneTaskBkgColor=this.done,this.doneTaskBorderColor=this.lineColor,this.critBkgColor=this.critical,this.critBorderColor=it(this.critBkgColor,10),this.todayLineColor=this.critBkgColor,this.vertLineColor=this.critBkgColor,this.archEdgeColor=this.lineColor,this.archEdgeArrowColor=this.lineColor,this.transitionColor=this.transitionColor||"#000",this.transitionLabelColor=this.transitionLabelColor||this.textColor,this.stateLabelColor=this.stateLabelColor||this.stateBkg||this.primaryTextColor,this.stateBkg=this.stateBkg||this.mainBkg,this.labelBackgroundColor=this.labelBackgroundColor||this.stateBkg,this.compositeBackground=this.compositeBackground||this.background||this.tertiaryColor,this.altBackground=this.altBackground||"#f4f4f4",this.compositeTitleBackground=this.compositeTitleBackground||this.mainBkg,this.stateBorder=this.stateBorder||"#000",this.innerEndBackground=this.primaryBorderColor,this.specialStateColor="#222",this.errorBkgColor=this.errorBkgColor||this.tertiaryColor,this.errorTextColor=this.errorTextColor||this.tertiaryTextColor,this.classText=this.primaryTextColor,this.fillType0=this.primaryColor,this.fillType1=this.secondaryColor,this.fillType2=A(this.primaryColor,{h:64}),this.fillType3=A(this.secondaryColor,{h:64}),this.fillType4=A(this.primaryColor,{h:-64}),this.fillType5=A(this.secondaryColor,{h:-64}),this.fillType6=A(this.primaryColor,{h:128}),this.fillType7=A(this.secondaryColor,{h:128});for(let _=0;_<this.THEME_COLOR_LIMIT;_++)this["pie"+_]=this["cScale"+_];this.pie12=this.pie0,this.pieTitleTextSize=this.pieTitleTextSize||"25px",this.pieTitleTextColor=this.pieTitleTextColor||this.taskTextDarkColor,this.pieSectionTextSize=this.pieSectionTextSize||"17px",this.pieSectionTextColor=this.pieSectionTextColor||this.textColor,this.pieLegendTextSize=this.pieLegendTextSize||"17px",this.pieLegendTextColor=this.pieLegendTextColor||this.taskTextDarkColor,this.pieStrokeColor=this.pieStrokeColor||"black",this.pieStrokeWidth=this.pieStrokeWidth||"2px",this.pieOuterStrokeWidth=this.pieOuterStrokeWidth||"2px",this.pieOuterStrokeColor=this.pieOuterStrokeColor||"black",this.pieOpacity=this.pieOpacity||"0.7",this.quadrant1Fill=this.quadrant1Fill||this.primaryColor,this.quadrant2Fill=this.quadrant2Fill||A(this.primaryColor,{r:5,g:5,b:5}),this.quadrant3Fill=this.quadrant3Fill||A(this.primaryColor,{r:10,g:10,b:10}),this.quadrant4Fill=this.quadrant4Fill||A(this.primaryColor,{r:15,g:15,b:15}),this.quadrant1TextFill=this.quadrant1TextFill||this.primaryTextColor,this.quadrant2TextFill=this.quadrant2TextFill||A(this.primaryTextColor,{r:-5,g:-5,b:-5}),this.quadrant3TextFill=this.quadrant3TextFill||A(this.primaryTextColor,{r:-10,g:-10,b:-10}),this.quadrant4TextFill=this.quadrant4TextFill||A(this.primaryTextColor,{r:-15,g:-15,b:-15}),this.quadrantPointFill=this.quadrantPointFill||An(this.quadrant1Fill)?G(this.quadrant1Fill):it(this.quadrant1Fill),this.quadrantPointTextFill=this.quadrantPointTextFill||this.primaryTextColor,this.quadrantXAxisTextFill=this.quadrantXAxisTextFill||this.primaryTextColor,this.quadrantYAxisTextFill=this.quadrantYAxisTextFill||this.primaryTextColor,this.quadrantInternalBorderStrokeFill=this.quadrantInternalBorderStrokeFill||this.primaryBorderColor,this.quadrantExternalBorderStrokeFill=this.quadrantExternalBorderStrokeFill||this.primaryBorderColor,this.quadrantTitleFill=this.quadrantTitleFill||this.primaryTextColor,this.xyChart={backgroundColor:((t=this.xyChart)==null?void 0:t.backgroundColor)||this.background,titleColor:((r=this.xyChart)==null?void 0:r.titleColor)||this.primaryTextColor,xAxisTitleColor:((i=this.xyChart)==null?void 0:i.xAxisTitleColor)||this.primaryTextColor,xAxisLabelColor:((n=this.xyChart)==null?void 0:n.xAxisLabelColor)||this.primaryTextColor,xAxisTickColor:((a=this.xyChart)==null?void 0:a.xAxisTickColor)||this.primaryTextColor,xAxisLineColor:((o=this.xyChart)==null?void 0:o.xAxisLineColor)||this.primaryTextColor,yAxisTitleColor:((s=this.xyChart)==null?void 0:s.yAxisTitleColor)||this.primaryTextColor,yAxisLabelColor:((c=this.xyChart)==null?void 0:c.yAxisLabelColor)||this.primaryTextColor,yAxisTickColor:((l=this.xyChart)==null?void 0:l.yAxisTickColor)||this.primaryTextColor,yAxisLineColor:((h=this.xyChart)==null?void 0:h.yAxisLineColor)||this.primaryTextColor,plotColorPalette:((u=this.xyChart)==null?void 0:u.plotColorPalette)||"#EEE,#6BB8E4,#8ACB88,#C7ACD6,#E8DCC2,#FFB2A8,#FFF380,#7E8D91,#FFD8B1,#FAF3E0"},this.radar={axisColor:((f=this.radar)==null?void 0:f.axisColor)||this.lineColor,axisStrokeWidth:((d=this.radar)==null?void 0:d.axisStrokeWidth)||2,axisLabelFontSize:((p=this.radar)==null?void 0:p.axisLabelFontSize)||12,curveOpacity:((m=this.radar)==null?void 0:m.curveOpacity)||.5,curveStrokeWidth:((y=this.radar)==null?void 0:y.curveStrokeWidth)||2,graticuleColor:((x=this.radar)==null?void 0:x.graticuleColor)||"#DEDEDE",graticuleStrokeWidth:((b=this.radar)==null?void 0:b.graticuleStrokeWidth)||1,graticuleOpacity:((C=this.radar)==null?void 0:C.graticuleOpacity)||.3,legendBoxSize:((k=this.radar)==null?void 0:k.legendBoxSize)||12,legendFontSize:((w=this.radar)==null?void 0:w.legendFontSize)||12},this.requirementBackground=this.requirementBackground||this.primaryColor,this.requirementBorderColor=this.requirementBorderColor||this.primaryBorderColor,this.requirementBorderSize=this.requirementBorderSize||"1",this.requirementTextColor=this.requirementTextColor||this.primaryTextColor,this.relationColor=this.relationColor||this.lineColor,this.relationLabelBackground=this.relationLabelBackground||this.edgeLabelBackground,this.relationLabelColor=this.relationLabelColor||this.actorTextColor,this.git0=it(this.pie1,25)||this.primaryColor,this.git1=this.pie2||this.secondaryColor,this.git2=this.pie3||this.tertiaryColor,this.git3=this.pie4||A(this.primaryColor,{h:-30}),this.git4=this.pie5||A(this.primaryColor,{h:-60}),this.git5=this.pie6||A(this.primaryColor,{h:-90}),this.git6=this.pie7||A(this.primaryColor,{h:60}),this.git7=this.pie8||A(this.primaryColor,{h:120}),this.gitInv0=this.gitInv0||H(this.git0),this.gitInv1=this.gitInv1||H(this.git1),this.gitInv2=this.gitInv2||H(this.git2),this.gitInv3=this.gitInv3||H(this.git3),this.gitInv4=this.gitInv4||H(this.git4),this.gitInv5=this.gitInv5||H(this.git5),this.gitInv6=this.gitInv6||H(this.git6),this.gitInv7=this.gitInv7||H(this.git7),this.branchLabelColor=this.branchLabelColor||this.labelTextColor,this.gitBranchLabel0=this.branchLabelColor,this.gitBranchLabel1="white",this.gitBranchLabel2=this.branchLabelColor,this.gitBranchLabel3="white",this.gitBranchLabel4=this.branchLabelColor,this.gitBranchLabel5=this.branchLabelColor,this.gitBranchLabel6=this.branchLabelColor,this.gitBranchLabel7=this.branchLabelColor,this.tagLabelColor=this.tagLabelColor||this.primaryTextColor,this.tagLabelBackground=this.tagLabelBackground||this.primaryColor,this.tagLabelBorder=this.tagBorder||this.primaryBorderColor,this.tagLabelFontSize=this.tagLabelFontSize||"10px",this.commitLabelColor=this.commitLabelColor||this.secondaryTextColor,this.commitLabelBackground=this.commitLabelBackground||this.secondaryColor,this.commitLabelFontSize=this.commitLabelFontSize||"10px",this.attributeBackgroundColorOdd=this.attributeBackgroundColorOdd||ys,this.attributeBackgroundColorEven=this.attributeBackgroundColorEven||xs}calculate(t){if(typeof t!="object"){this.updateColors();return}const r=Object.keys(t);r.forEach(i=>{this[i]=t[i]}),this.updateColors(),r.forEach(i=>{this[i]=t[i]})}},g(fi,"Theme"),fi),Yx=g(e=>{const t=new Ux;return t.calculate(e),t},"getThemeVariables"),Ze={base:{getThemeVariables:Ix},dark:{getThemeVariables:Nx},default:{getThemeVariables:Wx},forest:{getThemeVariables:Hx},neutral:{getThemeVariables:Yx}},Ae={flowchart:{useMaxWidth:!0,titleTopMargin:25,subGraphTitleMargin:{top:0,bottom:0},diagramPadding:8,htmlLabels:!0,nodeSpacing:50,rankSpacing:50,curve:"basis",padding:15,defaultRenderer:"dagre-wrapper",wrappingWidth:200,inheritDir:!1},sequence:{useMaxWidth:!0,hideUnusedParticipants:!1,activationWidth:10,diagramMarginX:50,diagramMarginY:10,actorMargin:50,width:150,height:65,boxMargin:10,boxTextMargin:5,noteMargin:10,messageMargin:35,messageAlign:"center",mirrorActors:!0,forceMenus:!1,bottomMarginAdj:1,rightAngles:!1,showSequenceNumbers:!1,actorFontSize:14,actorFontFamily:'"Open Sans", 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0,useWidth:void 0},c4:{...Ae.c4,useWidth:void 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diff --git a/lightrag/api/webui/assets/mindmap-definition-6CBA2TL7-CaNUoVfO.js b/lightrag/api/webui/assets/mindmap-definition-6CBA2TL7-CO8UILc9.js
similarity index 99%
rename from lightrag/api/webui/assets/mindmap-definition-6CBA2TL7-CaNUoVfO.js
rename to lightrag/api/webui/assets/mindmap-definition-6CBA2TL7-CO8UILc9.js
index 80d7f2b4..4e02981d 100644
--- a/lightrag/api/webui/assets/mindmap-definition-6CBA2TL7-CaNUoVfO.js
+++ b/lightrag/api/webui/assets/mindmap-definition-6CBA2TL7-CO8UILc9.js
@@ -1,4 +1,4 @@
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E==0?this.estimatedSize=e.EMPTY_COMPOUND_NODE_SIZE:this.estimatedSize=E/Math.sqrt(this.nodes.length),this.estimatedSize},c.prototype.updateConnected=function(){var E=this;if(this.nodes.length==0){this.isConnected=!0;return}var T=new n,m=new Set,L=this.nodes[0],O,d,N=L.withChildren();for(N.forEach(function(I){T.push(I),m.add(I)});T.length!==0;){L=T.shift(),O=L.getEdges();for(var s=O.length,h=0;h<s;h++){var f=O[h];if(d=f.getOtherEndInGraph(L,this),d!=null&&!m.has(d)){var p=d.withChildren();p.forEach(function(I){T.push(I),m.add(I)})}}}if(this.isConnected=!1,m.size>=this.nodes.length){var A=0;m.forEach(function(I){I.owner==E&&A++}),A==this.nodes.length&&(this.isConnected=!0)}},u.exports=c},function(u,D,y){var r,t=y(1);function e(i){r=y(5),this.layout=i,this.graphs=[],this.edges=[]}e.prototype.addRoot=function(){var i=this.layout.newGraph(),o=this.layout.newNode(null),g=this.add(i,o);return this.setRootGraph(g),this.rootGraph},e.prototype.add=function(i,o,g,a,v){if(g==null&&a==null&&v==null){if(i==null)throw"Graph is null!";if(o==null)throw"Parent node is null!";if(this.graphs.indexOf(i)>-1)throw"Graph already in this graph mgr!";if(this.graphs.push(i),i.parent!=null)throw"Already has a parent!";if(o.child!=null)throw"Already has a child!";return i.parent=o,o.child=i,i}else{v=g,a=o,g=i;var n=a.getOwner(),c=v.getOwner();if(!(n!=null&&n.getGraphManager()==this))throw"Source not in this graph mgr!";if(!(c!=null&&c.getGraphManager()==this))throw"Target not in this graph mgr!";if(n==c)return g.isInterGraph=!1,n.add(g,a,v);if(g.isInterGraph=!0,g.source=a,g.target=v,this.edges.indexOf(g)>-1)throw"Edge already in inter-graph edge list!";if(this.edges.push(g),!(g.source!=null&&g.target!=null))throw"Edge source and/or target is null!";if(!(g.source.edges.indexOf(g)==-1&&g.target.edges.indexOf(g)==-1))throw"Edge already in source and/or target incidency list!";return g.source.edges.push(g),g.target.edges.push(g),g}},e.prototype.remove=function(i){if(i instanceof r){var o=i;if(o.getGraphManager()!=this)throw"Graph not in this graph mgr";if(!(o==this.rootGraph||o.parent!=null&&o.parent.graphManager==this))throw"Invalid parent node!";var g=[];g=g.concat(o.getEdges());for(var a,v=g.length,n=0;n<v;n++)a=g[n],o.remove(a);var c=[];c=c.concat(o.getNodes());var l;v=c.length;for(var n=0;n<v;n++)l=c[n],o.remove(l);o==this.rootGraph&&this.setRootGraph(null);var E=this.graphs.indexOf(o);this.graphs.splice(E,1),o.parent=null}else if(i instanceof t){if(a=i,a==null)throw"Edge is null!";if(!a.isInterGraph)throw"Not an inter-graph edge!";if(!(a.source!=null&&a.target!=null))throw"Source and/or target is null!";if(!(a.source.edges.indexOf(a)!=-1&&a.target.edges.indexOf(a)!=-1))throw"Source and/or target doesn't know this edge!";var E=a.source.edges.indexOf(a);if(a.source.edges.splice(E,1),E=a.target.edges.indexOf(a),a.target.edges.splice(E,1),!(a.source.owner!=null&&a.source.owner.getGraphManager()!=null))throw"Edge owner graph or owner graph manager is null!";if(a.source.owner.getGraphManager().edges.indexOf(a)==-1)throw"Not in owner graph manager's edge list!";var E=a.source.owner.getGraphManager().edges.indexOf(a);a.source.owner.getGraphManager().edges.splice(E,1)}},e.prototype.updateBounds=function(){this.rootGraph.updateBounds(!0)},e.prototype.getGraphs=function(){return this.graphs},e.prototype.getAllNodes=function(){if(this.allNodes==null){for(var i=[],o=this.getGraphs(),g=o.length,a=0;a<g;a++)i=i.concat(o[a].getNodes());this.allNodes=i}return this.allNodes},e.prototype.resetAllNodes=function(){this.allNodes=null},e.prototype.resetAllEdges=function(){this.allEdges=null},e.prototype.resetAllNodesToApplyGravitation=function(){this.allNodesToApplyGravitation=null},e.prototype.getAllEdges=function(){if(this.allEdges==null){var i=[],o=this.getGraphs();o.length;for(var g=0;g<o.length;g++)i=i.concat(o[g].getEdges());i=i.concat(this.edges),this.allEdges=i}return this.allEdges},e.prototype.getAllNodesToApplyGravitation=function(){return this.allNodesToApplyGravitation},e.prototype.setAllNodesToApplyGravitation=function(i){if(this.allNodesToApplyGravitation!=null)throw"assert failed";this.allNodesToApplyGravitation=i},e.prototype.getRoot=function(){return this.rootGraph},e.prototype.setRootGraph=function(i){if(i.getGraphManager()!=this)throw"Root not in this graph mgr!";this.rootGraph=i,i.parent==null&&(i.parent=this.layout.newNode("Root node"))},e.prototype.getLayout=function(){return this.layout},e.prototype.isOneAncestorOfOther=function(i,o){if(!(i!=null&&o!=null))throw"assert failed";if(i==o)return!0;var g=i.getOwner(),a;do{if(a=g.getParent(),a==null)break;if(a==o)return!0;if(g=a.getOwner(),g==null)break}while(!0);g=o.getOwner();do{if(a=g.getParent(),a==null)break;if(a==i)return!0;if(g=a.getOwner(),g==null)break}while(!0);return!1},e.prototype.calcLowestCommonAncestors=function(){for(var i,o,g,a,v,n=this.getAllEdges(),c=n.length,l=0;l<c;l++){if(i=n[l],o=i.source,g=i.target,i.lca=null,i.sourceInLca=o,i.targetInLca=g,o==g){i.lca=o.getOwner();continue}for(a=o.getOwner();i.lca==null;){for(i.targetInLca=g,v=g.getOwner();i.lca==null;){if(v==a){i.lca=v;break}if(v==this.rootGraph)break;if(i.lca!=null)throw"assert failed";i.targetInLca=v.getParent(),v=i.targetInLca.getOwner()}if(a==this.rootGraph)break;i.lca==null&&(i.sourceInLca=a.getParent(),a=i.sourceInLca.getOwner())}if(i.lca==null)throw"assert failed"}},e.prototype.calcLowestCommonAncestor=function(i,o){if(i==o)return i.getOwner();var g=i.getOwner();do{if(g==null)break;var a=o.getOwner();do{if(a==null)break;if(a==g)return a;a=a.getParent().getOwner()}while(!0);g=g.getParent().getOwner()}while(!0);return g},e.prototype.calcInclusionTreeDepths=function(i,o){i==null&&o==null&&(i=this.rootGraph,o=1);for(var g,a=i.getNodes(),v=a.length,n=0;n<v;n++)g=a[n],g.inclusionTreeDepth=o,g.child!=null&&this.calcInclusionTreeDepths(g.child,o+1)},e.prototype.includesInvalidEdge=function(){for(var i,o=this.edges.length,g=0;g<o;g++)if(i=this.edges[g],this.isOneAncestorOfOther(i.source,i.target))return!0;return!1},u.exports=e},function(u,D,y){var r=y(0);function t(){}for(var e in r)t[e]=r[e];t.MAX_ITERATIONS=2500,t.DEFAULT_EDGE_LENGTH=50,t.DEFAULT_SPRING_STRENGTH=.45,t.DEFAULT_REPULSION_STRENGTH=4500,t.DEFAULT_GRAVITY_STRENGTH=.4,t.DEFAULT_COMPOUND_GRAVITY_STRENGTH=1,t.DEFAULT_GRAVITY_RANGE_FACTOR=3.8,t.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR=1.5,t.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION=!0,t.DEFAULT_USE_SMART_REPULSION_RANGE_CALCULATION=!0,t.DEFAULT_COOLING_FACTOR_INCREMENTAL=.3,t.COOLING_ADAPTATION_FACTOR=.33,t.ADAPTATION_LOWER_NODE_LIMIT=1e3,t.ADAPTATION_UPPER_NODE_LIMIT=5e3,t.MAX_NODE_DISPLACEMENT_INCREMENTAL=100,t.MAX_NODE_DISPLACEMENT=t.MAX_NODE_DISPLACEMENT_INCREMENTAL*3,t.MIN_REPULSION_DIST=t.DEFAULT_EDGE_LENGTH/10,t.CONVERGENCE_CHECK_PERIOD=100,t.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR=.1,t.MIN_EDGE_LENGTH=1,t.GRID_CALCULATION_CHECK_PERIOD=10,u.exports=t},function(u,D,y){var r=y(12);function t(){}t.calcSeparationAmount=function(e,i,o,g){if(!e.intersects(i))throw"assert failed";var a=new 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this.graphManager.getAllNodesToApplyGravitation()},c.prototype.newGraphManager=function(){var l=new e(this);return this.graphManager=l,l},c.prototype.newGraph=function(l){return new g(null,this.graphManager,l)},c.prototype.newNode=function(l){return new i(this.graphManager,l)},c.prototype.newEdge=function(l){return new o(null,null,l)},c.prototype.checkLayoutSuccess=function(){return this.graphManager.getRoot()==null||this.graphManager.getRoot().getNodes().length==0||this.graphManager.includesInvalidEdge()},c.prototype.runLayout=function(){this.isLayoutFinished=!1,this.tilingPreLayout&&this.tilingPreLayout(),this.initParameters();var l;return this.checkLayoutSuccess()?l=!1:l=this.layout(),t.ANIMATE==="during"?!1:(l&&(this.isSubLayout||this.doPostLayout()),this.tilingPostLayout&&this.tilingPostLayout(),this.isLayoutFinished=!0,l)},c.prototype.doPostLayout=function(){this.incremental||this.transform(),this.update()},c.prototype.update2=function(){if(this.createBendsAsNeeded&&(this.createBendpointsFromDummyNodes(),this.graphManager.resetAllEdges()),!this.isRemoteUse){for(var l=this.graphManager.getAllEdges(),E=0;E<l.length;E++)l[E];for(var T=this.graphManager.getRoot().getNodes(),E=0;E<T.length;E++)T[E];this.update(this.graphManager.getRoot())}},c.prototype.update=function(l){if(l==null)this.update2();else if(l instanceof i){var E=l;if(E.getChild()!=null)for(var T=E.getChild().getNodes(),m=0;m<T.length;m++)update(T[m]);if(E.vGraphObject!=null){var L=E.vGraphObject;L.update(E)}}else if(l instanceof o){var O=l;if(O.vGraphObject!=null){var d=O.vGraphObject;d.update(O)}}else if(l instanceof g){var N=l;if(N.vGraphObject!=null){var s=N.vGraphObject;s.update(N)}}},c.prototype.initParameters=function(){this.isSubLayout||(this.layoutQuality=t.QUALITY,this.animationDuringLayout=t.DEFAULT_ANIMATION_DURING_LAYOUT,this.animationPeriod=t.DEFAULT_ANIMATION_PERIOD,this.animationOnLayout=t.DEFAULT_ANIMATION_ON_LAYOUT,this.incremental=t.DEFAULT_INCREMENTAL,this.createBendsAsNeeded=t.DEFAULT_CREATE_BENDS_AS_NEEDED,this.uniformLeafNodeSizes=t.DEFAULT_UNIFORM_LEAF_NODE_SIZES),this.animationDuringLayout&&(this.animationOnLayout=!1)},c.prototype.transform=function(l){if(l==null)this.transform(new a(0,0));else{var E=new v,T=this.graphManager.getRoot().updateLeftTop();if(T!=null){E.setWorldOrgX(l.x),E.setWorldOrgY(l.y),E.setDeviceOrgX(T.x),E.setDeviceOrgY(T.y);for(var m=this.getAllNodes(),L,O=0;O<m.length;O++)L=m[O],L.transform(E)}}},c.prototype.positionNodesRandomly=function(l){if(l==null)this.positionNodesRandomly(this.getGraphManager().getRoot()),this.getGraphManager().getRoot().updateBounds(!0);else for(var E,T,m=l.getNodes(),L=0;L<m.length;L++)E=m[L],T=E.getChild(),T==null||T.getNodes().length==0?E.scatter():(this.positionNodesRandomly(T),E.updateBounds())},c.prototype.getFlatForest=function(){for(var l=[],E=!0,T=this.graphManager.getRoot().getNodes(),m=!0,L=0;L<T.length;L++)T[L].getChild()!=null&&(m=!1);if(!m)return l;var O=new Set,d=[],N=new Map,s=[];for(s=s.concat(T);s.length>0&&E;){for(d.push(s[0]);d.length>0&&E;){var h=d[0];d.splice(0,1),O.add(h);for(var f=h.getEdges(),L=0;L<f.length;L++){var p=f[L].getOtherEnd(h);if(N.get(h)!=p)if(!O.has(p))d.push(p),N.set(p,h);else{E=!1;break}}}if(!E)l=[];else{var A=[].concat(r(O));l.push(A);for(var L=0;L<A.length;L++){var I=A[L],R=s.indexOf(I);R>-1&&s.splice(R,1)}O=new Set,N=new Map}}return l},c.prototype.createDummyNodesForBendpoints=function(l){for(var E=[],T=l.source,m=this.graphManager.calcLowestCommonAncestor(l.source,l.target),L=0;L<l.bendpoints.length;L++){var O=this.newNode(null);O.setRect(new Point(0,0),new Dimension(1,1)),m.add(O);var d=this.newEdge(null);this.graphManager.add(d,T,O),E.add(O),T=O}var d=this.newEdge(null);return this.graphManager.add(d,T,l.target),this.edgeToDummyNodes.set(l,E),l.isInterGraph()?this.graphManager.remove(l):m.remove(l),E},c.prototype.createBendpointsFromDummyNodes=function(){var l=[];l=l.concat(this.graphManager.getAllEdges()),l=[].concat(r(this.edgeToDummyNodes.keys())).concat(l);for(var E=0;E<l.length;E++){var T=l[E];if(T.bendpoints.length>0){for(var m=this.edgeToDummyNodes.get(T),L=0;L<m.length;L++){var O=m[L],d=new a(O.getCenterX(),O.getCenterY()),N=T.bendpoints.get(L);N.x=d.x,N.y=d.y,O.getOwner().remove(O)}this.graphManager.add(T,T.source,T.target)}}},c.transform=function(l,E,T,m){if(T!=null&&m!=null){var L=E;if(l<=50){var O=E/T;L-=(E-O)/50*(50-l)}else{var d=E*m;L+=(d-E)/50*(l-50)}return L}else{var N,s;return l<=50?(N=9*E/500,s=E/10):(N=9*E/50,s=-8*E),N*l+s}},c.findCenterOfTree=function(l){var E=[];E=E.concat(l);var T=[],m=new Map,L=!1,O=null;(E.length==1||E.length==2)&&(L=!0,O=E[0]);for(var d=0;d<E.length;d++){var N=E[d],s=N.getNeighborsList().size;m.set(N,N.getNeighborsList().size),s==1&&T.push(N)}var h=[];for(h=h.concat(T);!L;){var f=[];f=f.concat(h),h=[];for(var d=0;d<E.length;d++){var N=E[d],p=E.indexOf(N);p>=0&&E.splice(p,1);var A=N.getNeighborsList();A.forEach(function(x){if(T.indexOf(x)<0){var G=m.get(x),U=G-1;U==1&&h.push(x),m.set(x,U)}})}T=T.concat(h),(E.length==1||E.length==2)&&(L=!0,O=E[0])}return O},c.prototype.setGraphManager=function(l){this.graphManager=l},u.exports=c},function(u,D,y){function r(){}r.seed=1,r.x=0,r.nextDouble=function(){return r.x=Math.sin(r.seed++)*1e4,r.x-Math.floor(r.x)},u.exports=r},function(u,D,y){var r=y(4);function t(e,i){this.lworldOrgX=0,this.lworldOrgY=0,this.ldeviceOrgX=0,this.ldeviceOrgY=0,this.lworldExtX=1,this.lworldExtY=1,this.ldeviceExtX=1,this.ldeviceExtY=1}t.prototype.getWorldOrgX=function(){return this.lworldOrgX},t.prototype.setWorldOrgX=function(e){this.lworldOrgX=e},t.prototype.getWorldOrgY=function(){return this.lworldOrgY},t.prototype.setWorldOrgY=function(e){this.lworldOrgY=e},t.prototype.getWorldExtX=function(){return this.lworldExtX},t.prototype.setWorldExtX=function(e){this.lworldExtX=e},t.prototype.getWorldExtY=function(){return this.lworldExtY},t.prototype.setWorldExtY=function(e){this.lworldExtY=e},t.prototype.getDeviceOrgX=function(){return this.ldeviceOrgX},t.prototype.setDeviceOrgX=function(e){this.ldeviceOrgX=e},t.prototype.getDeviceOrgY=function(){return this.ldeviceOrgY},t.prototype.setDeviceOrgY=function(e){this.ldeviceOrgY=e},t.prototype.getDeviceExtX=function(){return this.ldeviceExtX},t.prototype.setDeviceExtX=function(e){this.ldeviceExtX=e},t.prototype.getDeviceExtY=function(){return this.ldeviceExtY},t.prototype.setDeviceExtY=function(e){this.ldeviceExtY=e},t.prototype.transformX=function(e){var i=0,o=this.lworldExtX;return o!=0&&(i=this.ldeviceOrgX+(e-this.lworldOrgX)*this.ldeviceExtX/o),i},t.prototype.transformY=function(e){var i=0,o=this.lworldExtY;return o!=0&&(i=this.ldeviceOrgY+(e-this.lworldOrgY)*this.ldeviceExtY/o),i},t.prototype.inverseTransformX=function(e){var i=0,o=this.ldeviceExtX;return o!=0&&(i=this.lworldOrgX+(e-this.ldeviceOrgX)*this.lworldExtX/o),i},t.prototype.inverseTransformY=function(e){var i=0,o=this.ldeviceExtY;return o!=0&&(i=this.lworldOrgY+(e-this.ldeviceOrgY)*this.lworldExtY/o),i},t.prototype.inverseTransformPoint=function(e){var i=new r(this.inverseTransformX(e.x),this.inverseTransformY(e.y));return i},u.exports=t},function(u,D,y){function r(n){if(Array.isArray(n)){for(var c=0,l=Array(n.length);c<n.length;c++)l[c]=n[c];return l}else return Array.from(n)}var t=y(15),e=y(7),i=y(0),o=y(8),g=y(9);function a(){t.call(this),this.useSmartIdealEdgeLengthCalculation=e.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION,this.idealEdgeLength=e.DEFAULT_EDGE_LENGTH,this.springConstant=e.DEFAULT_SPRING_STRENGTH,this.repulsionConstant=e.DEFAULT_REPULSION_STRENGTH,this.gravityConstant=e.DEFAULT_GRAVITY_STRENGTH,this.compoundGravityConstant=e.DEFAULT_COMPOUND_GRAVITY_STRENGTH,this.gravityRangeFactor=e.DEFAULT_GRAVITY_RANGE_FACTOR,this.compoundGravityRangeFactor=e.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR,this.displacementThresholdPerNode=3*e.DEFAULT_EDGE_LENGTH/100,this.coolingFactor=e.DEFAULT_COOLING_FACTOR_INCREMENTAL,this.initialCoolingFactor=e.DEFAULT_COOLING_FACTOR_INCREMENTAL,this.totalDisplacement=0,this.oldTotalDisplacement=0,this.maxIterations=e.MAX_ITERATIONS}a.prototype=Object.create(t.prototype);for(var v in t)a[v]=t[v];a.prototype.initParameters=function(){t.prototype.initParameters.call(this,arguments),this.totalIterations=0,this.notAnimatedIterations=0,this.useFRGridVariant=e.DEFAULT_USE_SMART_REPULSION_RANGE_CALCULATION,this.grid=[]},a.prototype.calcIdealEdgeLengths=function(){for(var n,c,l,E,T,m,L=this.getGraphManager().getAllEdges(),O=0;O<L.length;O++)n=L[O],n.idealLength=this.idealEdgeLength,n.isInterGraph&&(l=n.getSource(),E=n.getTarget(),T=n.getSourceInLca().getEstimatedSize(),m=n.getTargetInLca().getEstimatedSize(),this.useSmartIdealEdgeLengthCalculation&&(n.idealLength+=T+m-2*i.SIMPLE_NODE_SIZE),c=n.getLca().getInclusionTreeDepth(),n.idealLength+=e.DEFAULT_EDGE_LENGTH*e.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR*(l.getInclusionTreeDepth()+E.getInclusionTreeDepth()-2*c))},a.prototype.initSpringEmbedder=function(){var n=this.getAllNodes().length;this.incremental?(n>e.ADAPTATION_LOWER_NODE_LIMIT&&(this.coolingFactor=Math.max(this.coolingFactor*e.COOLING_ADAPTATION_FACTOR,this.coolingFactor-(n-e.ADAPTATION_LOWER_NODE_LIMIT)/(e.ADAPTATION_UPPER_NODE_LIMIT-e.ADAPTATION_LOWER_NODE_LIMIT)*this.coolingFactor*(1-e.COOLING_ADAPTATION_FACTOR))),this.maxNodeDisplacement=e.MAX_NODE_DISPLACEMENT_INCREMENTAL):(n>e.ADAPTATION_LOWER_NODE_LIMIT?this.coolingFactor=Math.max(e.COOLING_ADAPTATION_FACTOR,1-(n-e.ADAPTATION_LOWER_NODE_LIMIT)/(e.ADAPTATION_UPPER_NODE_LIMIT-e.ADAPTATION_LOWER_NODE_LIMIT)*(1-e.COOLING_ADAPTATION_FACTOR)):this.coolingFactor=1,this.initialCoolingFactor=this.coolingFactor,this.maxNodeDisplacement=e.MAX_NODE_DISPLACEMENT),this.maxIterations=Math.max(this.getAllNodes().length*5,this.maxIterations),this.totalDisplacementThreshold=this.displacementThresholdPerNode*this.getAllNodes().length,this.repulsionRange=this.calcRepulsionRange()},a.prototype.calcSpringForces=function(){for(var n=this.getAllEdges(),c,l=0;l<n.length;l++)c=n[l],this.calcSpringForce(c,c.idealLength)},a.prototype.calcRepulsionForces=function(){var n=arguments.length>0&&arguments[0]!==void 0?arguments[0]:!0,c=arguments.length>1&&arguments[1]!==void 0?arguments[1]:!1,l,E,T,m,L=this.getAllNodes(),O;if(this.useFRGridVariant)for(this.totalIterations%e.GRID_CALCULATION_CHECK_PERIOD==1&&n&&this.updateGrid(),O=new Set,l=0;l<L.length;l++)T=L[l],this.calculateRepulsionForceOfANode(T,O,n,c),O.add(T);else for(l=0;l<L.length;l++)for(T=L[l],E=l+1;E<L.length;E++)m=L[E],T.getOwner()==m.getOwner()&&this.calcRepulsionForce(T,m)},a.prototype.calcGravitationalForces=function(){for(var n,c=this.getAllNodesToApplyGravitation(),l=0;l<c.length;l++)n=c[l],this.calcGravitationalForce(n)},a.prototype.moveNodes=function(){for(var n=this.getAllNodes(),c,l=0;l<n.length;l++)c=n[l],c.move()},a.prototype.calcSpringForce=function(n,c){var l=n.getSource(),E=n.getTarget(),T,m,L,O;if(this.uniformLeafNodeSizes&&l.getChild()==null&&E.getChild()==null)n.updateLengthSimple();else if(n.updateLength(),n.isOverlapingSourceAndTarget)return;T=n.getLength(),T!=0&&(m=this.springConstant*(T-c),L=m*(n.lengthX/T),O=m*(n.lengthY/T),l.springForceX+=L,l.springForceY+=O,E.springForceX-=L,E.springForceY-=O)},a.prototype.calcRepulsionForce=function(n,c){var l=n.getRect(),E=c.getRect(),T=new Array(2),m=new Array(4),L,O,d,N,s,h,f;if(l.intersects(E)){o.calcSeparationAmount(l,E,T,e.DEFAULT_EDGE_LENGTH/2),h=2*T[0],f=2*T[1];var p=n.noOfChildren*c.noOfChildren/(n.noOfChildren+c.noOfChildren);n.repulsionForceX-=p*h,n.repulsionForceY-=p*f,c.repulsionForceX+=p*h,c.repulsionForceY+=p*f}else this.uniformLeafNodeSizes&&n.getChild()==null&&c.getChild()==null?(L=E.getCenterX()-l.getCenterX(),O=E.getCenterY()-l.getCenterY()):(o.getIntersection(l,E,m),L=m[2]-m[0],O=m[3]-m[1]),Math.abs(L)<e.MIN_REPULSION_DIST&&(L=g.sign(L)*e.MIN_REPULSION_DIST),Math.abs(O)<e.MIN_REPULSION_DIST&&(O=g.sign(O)*e.MIN_REPULSION_DIST),d=L*L+O*O,N=Math.sqrt(d),s=this.repulsionConstant*n.noOfChildren*c.noOfChildren/d,h=s*L/N,f=s*O/N,n.repulsionForceX-=h,n.repulsionForceY-=f,c.repulsionForceX+=h,c.repulsionForceY+=f},a.prototype.calcGravitationalForce=function(n){var c,l,E,T,m,L,O,d;c=n.getOwner(),l=(c.getRight()+c.getLeft())/2,E=(c.getTop()+c.getBottom())/2,T=n.getCenterX()-l,m=n.getCenterY()-E,L=Math.abs(T)+n.getWidth()/2,O=Math.abs(m)+n.getHeight()/2,n.getOwner()==this.graphManager.getRoot()?(d=c.getEstimatedSize()*this.gravityRangeFactor,(L>d||O>d)&&(n.gravitationForceX=-this.gravityConstant*T,n.gravitationForceY=-this.gravityConstant*m)):(d=c.getEstimatedSize()*this.compoundGravityRangeFactor,(L>d||O>d)&&(n.gravitationForceX=-this.gravityConstant*T*this.compoundGravityConstant,n.gravitationForceY=-this.gravityConstant*m*this.compoundGravityConstant))},a.prototype.isConverged=function(){var n,c=!1;return this.totalIterations>this.maxIterations/3&&(c=Math.abs(this.totalDisplacement-this.oldTotalDisplacement)<2),n=this.totalDisplacement<this.totalDisplacementThreshold,this.oldTotalDisplacement=this.totalDisplacement,n||c},a.prototype.animate=function(){this.animationDuringLayout&&!this.isSubLayout&&(this.notAnimatedIterations==this.animationPeriod?(this.update(),this.notAnimatedIterations=0):this.notAnimatedIterations++)},a.prototype.calcNoOfChildrenForAllNodes=function(){for(var n,c=this.graphManager.getAllNodes(),l=0;l<c.length;l++)n=c[l],n.noOfChildren=n.getNoOfChildren()},a.prototype.calcGrid=function(n){var c=0,l=0;c=parseInt(Math.ceil((n.getRight()-n.getLeft())/this.repulsionRange)),l=parseInt(Math.ceil((n.getBottom()-n.getTop())/this.repulsionRange));for(var E=new Array(c),T=0;T<c;T++)E[T]=new Array(l);for(var T=0;T<c;T++)for(var m=0;m<l;m++)E[T][m]=new Array;return E},a.prototype.addNodeToGrid=function(n,c,l){var E=0,T=0,m=0,L=0;E=parseInt(Math.floor((n.getRect().x-c)/this.repulsionRange)),T=parseInt(Math.floor((n.getRect().width+n.getRect().x-c)/this.repulsionRange)),m=parseInt(Math.floor((n.getRect().y-l)/this.repulsionRange)),L=parseInt(Math.floor((n.getRect().height+n.getRect().y-l)/this.repulsionRange));for(var O=E;O<=T;O++)for(var d=m;d<=L;d++)this.grid[O][d].push(n),n.setGridCoordinates(E,T,m,L)},a.prototype.updateGrid=function(){var n,c,l=this.getAllNodes();for(this.grid=this.calcGrid(this.graphManager.getRoot()),n=0;n<l.length;n++)c=l[n],this.addNodeToGrid(c,this.graphManager.getRoot().getLeft(),this.graphManager.getRoot().getTop())},a.prototype.calculateRepulsionForceOfANode=function(n,c,l,E){if(this.totalIterations%e.GRID_CALCULATION_CHECK_PERIOD==1&&l||E){var T=new Set;n.surrounding=new Array;for(var m,L=this.grid,O=n.startX-1;O<n.finishX+2;O++)for(var d=n.startY-1;d<n.finishY+2;d++)if(!(O<0||d<0||O>=L.length||d>=L[0].length)){for(var N=0;N<L[O][d].length;N++)if(m=L[O][d][N],!(n.getOwner()!=m.getOwner()||n==m)&&!c.has(m)&&!T.has(m)){var s=Math.abs(n.getCenterX()-m.getCenterX())-(n.getWidth()/2+m.getWidth()/2),h=Math.abs(n.getCenterY()-m.getCenterY())-(n.getHeight()/2+m.getHeight()/2);s<=this.repulsionRange&&h<=this.repulsionRange&&T.add(m)}}n.surrounding=[].concat(r(T))}for(O=0;O<n.surrounding.length;O++)this.calcRepulsionForce(n,n.surrounding[O])},a.prototype.calcRepulsionRange=function(){return 0},u.exports=a},function(u,D,y){var r=y(1),t=y(7);function e(o,g,a){r.call(this,o,g,a),this.idealLength=t.DEFAULT_EDGE_LENGTH}e.prototype=Object.create(r.prototype);for(var i in r)e[i]=r[i];u.exports=e},function(u,D,y){var r=y(3);function t(i,o,g,a){r.call(this,i,o,g,a),this.springForceX=0,this.springForceY=0,this.repulsionForceX=0,this.repulsionForceY=0,this.gravitationForceX=0,this.gravitationForceY=0,this.displacementX=0,this.displacementY=0,this.startX=0,this.finishX=0,this.startY=0,this.finishY=0,this.surrounding=[]}t.prototype=Object.create(r.prototype);for(var e in r)t[e]=r[e];t.prototype.setGridCoordinates=function(i,o,g,a){this.startX=i,this.finishX=o,this.startY=g,this.finishY=a},u.exports=t},function(u,D,y){function r(t,e){this.width=0,this.height=0,t!==null&&e!==null&&(this.height=e,this.width=t)}r.prototype.getWidth=function(){return this.width},r.prototype.setWidth=function(t){this.width=t},r.prototype.getHeight=function(){return this.height},r.prototype.setHeight=function(t){this.height=t},u.exports=r},function(u,D,y){var r=y(14);function t(){this.map={},this.keys=[]}t.prototype.put=function(e,i){var 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r=function(){function o(g,a){for(var v=0;v<a.length;v++){var n=a[v];n.enumerable=n.enumerable||!1,n.configurable=!0,"value"in n&&(n.writable=!0),Object.defineProperty(g,n.key,n)}}return function(g,a,v){return a&&o(g.prototype,a),v&&o(g,v),g}}();function t(o,g){if(!(o instanceof g))throw new TypeError("Cannot call a class as a function")}var e=y(11),i=function(){function o(g,a){t(this,o),(a!==null||a!==void 0)&&(this.compareFunction=this._defaultCompareFunction);var v=void 0;g instanceof e?v=g.size():v=g.length,this._quicksort(g,0,v-1)}return r(o,[{key:"_quicksort",value:function(a,v,n){if(v<n){var c=this._partition(a,v,n);this._quicksort(a,v,c),this._quicksort(a,c+1,n)}}},{key:"_partition",value:function(a,v,n){for(var c=this._get(a,v),l=v,E=n;;){for(;this.compareFunction(c,this._get(a,E));)E--;for(;this.compareFunction(this._get(a,l),c);)l++;if(l<E)this._swap(a,l,E),l++,E--;else return E}}},{key:"_get",value:function(a,v){return a instanceof e?a.get_object_at(v):a[v]}},{key:"_set",value:function(a,v,n){a instanceof e?a.set_object_at(v,n):a[v]=n}},{key:"_swap",value:function(a,v,n){var c=this._get(a,v);this._set(a,v,this._get(a,n)),this._set(a,n,c)}},{key:"_defaultCompareFunction",value:function(a,v){return v>a}}]),o}();u.exports=i},function(u,D,y){var r=function(){function i(o,g){for(var a=0;a<g.length;a++){var v=g[a];v.enumerable=v.enumerable||!1,v.configurable=!0,"value"in v&&(v.writable=!0),Object.defineProperty(o,v.key,v)}}return function(o,g,a){return g&&i(o.prototype,g),a&&i(o,a),o}}();function t(i,o){if(!(i instanceof o))throw new TypeError("Cannot call a class as a function")}var e=function(){function i(o,g){var a=arguments.length>2&&arguments[2]!==void 0?arguments[2]:1,v=arguments.length>3&&arguments[3]!==void 0?arguments[3]:-1,n=arguments.length>4&&arguments[4]!==void 0?arguments[4]:-1;t(this,i),this.sequence1=o,this.sequence2=g,this.match_score=a,this.mismatch_penalty=v,this.gap_penalty=n,this.iMax=o.length+1,this.jMax=g.length+1,this.grid=new Array(this.iMax);for(var c=0;c<this.iMax;c++){this.grid[c]=new Array(this.jMax);for(var l=0;l<this.jMax;l++)this.grid[c][l]=0}this.tracebackGrid=new Array(this.iMax);for(var E=0;E<this.iMax;E++){this.tracebackGrid[E]=new Array(this.jMax);for(var T=0;T<this.jMax;T++)this.tracebackGrid[E][T]=[null,null,null]}this.alignments=[],this.score=-1,this.computeGrids()}return r(i,[{key:"getScore",value:function(){return this.score}},{key:"getAlignments",value:function(){return this.alignments}},{key:"computeGrids",value:function(){for(var g=1;g<this.jMax;g++)this.grid[0][g]=this.grid[0][g-1]+this.gap_penalty,this.tracebackGrid[0][g]=[!1,!1,!0];for(var a=1;a<this.iMax;a++)this.grid[a][0]=this.grid[a-1][0]+this.gap_penalty,this.tracebackGrid[a][0]=[!1,!0,!1];for(var v=1;v<this.iMax;v++)for(var n=1;n<this.jMax;n++){var c=void 0;this.sequence1[v-1]===this.sequence2[n-1]?c=this.grid[v-1][n-1]+this.match_score:c=this.grid[v-1][n-1]+this.mismatch_penalty;var l=this.grid[v-1][n]+this.gap_penalty,E=this.grid[v][n-1]+this.gap_penalty,T=[c,l,E],m=this.arrayAllMaxIndexes(T);this.grid[v][n]=T[m[0]],this.tracebackGrid[v][n]=[m.includes(0),m.includes(1),m.includes(2)]}this.score=this.grid[this.iMax-1][this.jMax-1]}},{key:"alignmentTraceback",value:function(){var g=[];for(g.push({pos:[this.sequence1.length,this.sequence2.length],seq1:"",seq2:""});g[0];){var a=g[0],v=this.tracebackGrid[a.pos[0]][a.pos[1]];v[0]&&g.push({pos:[a.pos[0]-1,a.pos[1]-1],seq1:this.sequence1[a.pos[0]-1]+a.seq1,seq2:this.sequence2[a.pos[1]-1]+a.seq2}),v[1]&&g.push({pos:[a.pos[0]-1,a.pos[1]],seq1:this.sequence1[a.pos[0]-1]+a.seq1,seq2:"-"+a.seq2}),v[2]&&g.push({pos:[a.pos[0],a.pos[1]-1],seq1:"-"+a.seq1,seq2:this.sequence2[a.pos[1]-1]+a.seq2}),a.pos[0]===0&&a.pos[1]===0&&this.alignments.push({sequence1:a.seq1,sequence2:a.seq2}),g.shift()}return this.alignments}},{key:"getAllIndexes",value:function(g,a){for(var v=[],n=-1;(n=g.indexOf(a,n+1))!==-1;)v.push(n);return v}},{key:"arrayAllMaxIndexes",value:function(g){return this.getAllIndexes(g,Math.max.apply(null,g))}}]),i}();u.exports=e},function(u,D,y){var r=function(){};r.FDLayout=y(18),r.FDLayoutConstants=y(7),r.FDLayoutEdge=y(19),r.FDLayoutNode=y(20),r.DimensionD=y(21),r.HashMap=y(22),r.HashSet=y(23),r.IGeometry=y(8),r.IMath=y(9),r.Integer=y(10),r.Point=y(12),r.PointD=y(4),r.RandomSeed=y(16),r.RectangleD=y(13),r.Transform=y(17),r.UniqueIDGeneretor=y(14),r.Quicksort=y(24),r.LinkedList=y(11),r.LGraphObject=y(2),r.LGraph=y(5),r.LEdge=y(1),r.LGraphManager=y(6),r.LNode=y(3),r.Layout=y(15),r.LayoutConstants=y(0),r.NeedlemanWunsch=y(25),u.exports=r},function(u,D,y){function r(){this.listeners=[]}var t=r.prototype;t.addListener=function(e,i){this.listeners.push({event:e,callback:i})},t.removeListener=function(e,i){for(var o=this.listeners.length;o>=0;o--){var g=this.listeners[o];g.event===e&&g.callback===i&&this.listeners.splice(o,1)}},t.emit=function(e,i){for(var o=0;o<this.listeners.length;o++){var g=this.listeners[o];e===g.event&&g.callback(i)}},u.exports=r}])})}(rt)),rt.exports}var xt=et.exports,gt;function Mt(){return gt||(gt=1,function(C,M){(function(D,y){C.exports=y(Rt())})(xt,function(u){return function(D){var y={};function r(t){if(y[t])return y[t].exports;var e=y[t]={i:t,l:!1,exports:{}};return D[t].call(e.exports,e,e.exports,r),e.l=!0,e.exports}return r.m=D,r.c=y,r.i=function(t){return t},r.d=function(t,e,i){r.o(t,e)||Object.defineProperty(t,e,{configurable:!1,enumerable:!0,get:i})},r.n=function(t){var e=t&&t.__esModule?function(){return t.default}:function(){return t};return r.d(e,"a",e),e},r.o=function(t,e){return Object.prototype.hasOwnProperty.call(t,e)},r.p="",r(r.s=7)}([function(D,y){D.exports=u},function(D,y,r){var t=r(0).FDLayoutConstants;function e(){}for(var i in t)e[i]=t[i];e.DEFAULT_USE_MULTI_LEVEL_SCALING=!1,e.DEFAULT_RADIAL_SEPARATION=t.DEFAULT_EDGE_LENGTH,e.DEFAULT_COMPONENT_SEPERATION=60,e.TILE=!0,e.TILING_PADDING_VERTICAL=10,e.TILING_PADDING_HORIZONTAL=10,e.TREE_REDUCTION_ON_INCREMENTAL=!1,D.exports=e},function(D,y,r){var t=r(0).FDLayoutEdge;function e(o,g,a){t.call(this,o,g,a)}e.prototype=Object.create(t.prototype);for(var i in t)e[i]=t[i];D.exports=e},function(D,y,r){var t=r(0).LGraph;function e(o,g,a){t.call(this,o,g,a)}e.prototype=Object.create(t.prototype);for(var i in t)e[i]=t[i];D.exports=e},function(D,y,r){var t=r(0).LGraphManager;function e(o){t.call(this,o)}e.prototype=Object.create(t.prototype);for(var i in t)e[i]=t[i];D.exports=e},function(D,y,r){var t=r(0).FDLayoutNode,e=r(0).IMath;function i(g,a,v,n){t.call(this,g,a,v,n)}i.prototype=Object.create(t.prototype);for(var o in t)i[o]=t[o];i.prototype.move=function(){var g=this.graphManager.getLayout();this.displacementX=g.coolingFactor*(this.springForceX+this.repulsionForceX+this.gravitationForceX)/this.noOfChildren,this.displacementY=g.coolingFactor*(this.springForceY+this.repulsionForceY+this.gravitationForceY)/this.noOfChildren,Math.abs(this.displacementX)>g.coolingFactor*g.maxNodeDisplacement&&(this.displacementX=g.coolingFactor*g.maxNodeDisplacement*e.sign(this.displacementX)),Math.abs(this.displacementY)>g.coolingFactor*g.maxNodeDisplacement&&(this.displacementY=g.coolingFactor*g.maxNodeDisplacement*e.sign(this.displacementY)),this.child==null?this.moveBy(this.displacementX,this.displacementY):this.child.getNodes().length==0?this.moveBy(this.displacementX,this.displacementY):this.propogateDisplacementToChildren(this.displacementX,this.displacementY),g.totalDisplacement+=Math.abs(this.displacementX)+Math.abs(this.displacementY),this.springForceX=0,this.springForceY=0,this.repulsionForceX=0,this.repulsionForceY=0,this.gravitationForceX=0,this.gravitationForceY=0,this.displacementX=0,this.displacementY=0},i.prototype.propogateDisplacementToChildren=function(g,a){for(var v=this.getChild().getNodes(),n,c=0;c<v.length;c++)n=v[c],n.getChild()==null?(n.moveBy(g,a),n.displacementX+=g,n.displacementY+=a):n.propogateDisplacementToChildren(g,a)},i.prototype.setPred1=function(g){this.pred1=g},i.prototype.getPred1=function(){return pred1},i.prototype.getPred2=function(){return pred2},i.prototype.setNext=function(g){this.next=g},i.prototype.getNext=function(){return next},i.prototype.setProcessed=function(g){this.processed=g},i.prototype.isProcessed=function(){return processed},D.exports=i},function(D,y,r){var t=r(0).FDLayout,e=r(4),i=r(3),o=r(5),g=r(2),a=r(1),v=r(0).FDLayoutConstants,n=r(0).LayoutConstants,c=r(0).Point,l=r(0).PointD,E=r(0).Layout,T=r(0).Integer,m=r(0).IGeometry,L=r(0).LGraph,O=r(0).Transform;function d(){t.call(this),this.toBeTiled={}}d.prototype=Object.create(t.prototype);for(var N in t)d[N]=t[N];d.prototype.newGraphManager=function(){var s=new e(this);return this.graphManager=s,s},d.prototype.newGraph=function(s){return new i(null,this.graphManager,s)},d.prototype.newNode=function(s){return new o(this.graphManager,s)},d.prototype.newEdge=function(s){return new g(null,null,s)},d.prototype.initParameters=function(){t.prototype.initParameters.call(this,arguments),this.isSubLayout||(a.DEFAULT_EDGE_LENGTH<10?this.idealEdgeLength=10:this.idealEdgeLength=a.DEFAULT_EDGE_LENGTH,this.useSmartIdealEdgeLengthCalculation=a.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION,this.springConstant=v.DEFAULT_SPRING_STRENGTH,this.repulsionConstant=v.DEFAULT_REPULSION_STRENGTH,this.gravityConstant=v.DEFAULT_GRAVITY_STRENGTH,this.compoundGravityConstant=v.DEFAULT_COMPOUND_GRAVITY_STRENGTH,this.gravityRangeFactor=v.DEFAULT_GRAVITY_RANGE_FACTOR,this.compoundGravityRangeFactor=v.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR,this.prunedNodesAll=[],this.growTreeIterations=0,this.afterGrowthIterations=0,this.isTreeGrowing=!1,this.isGrowthFinished=!1,this.coolingCycle=0,this.maxCoolingCycle=this.maxIterations/v.CONVERGENCE_CHECK_PERIOD,this.finalTemperature=v.CONVERGENCE_CHECK_PERIOD/this.maxIterations,this.coolingAdjuster=1)},d.prototype.layout=function(){var s=n.DEFAULT_CREATE_BENDS_AS_NEEDED;return s&&(this.createBendpoints(),this.graphManager.resetAllEdges()),this.level=0,this.classicLayout()},d.prototype.classicLayout=function(){if(this.nodesWithGravity=this.calculateNodesToApplyGravitationTo(),this.graphManager.setAllNodesToApplyGravitation(this.nodesWithGravity),this.calcNoOfChildrenForAllNodes(),this.graphManager.calcLowestCommonAncestors(),this.graphManager.calcInclusionTreeDepths(),this.graphManager.getRoot().calcEstimatedSize(),this.calcIdealEdgeLengths(),this.incremental){if(a.TREE_REDUCTION_ON_INCREMENTAL){this.reduceTrees(),this.graphManager.resetAllNodesToApplyGravitation();var h=new Set(this.getAllNodes()),f=this.nodesWithGravity.filter(function(I){return h.has(I)});this.graphManager.setAllNodesToApplyGravitation(f)}}else{var s=this.getFlatForest();if(s.length>0)this.positionNodesRadially(s);else{this.reduceTrees(),this.graphManager.resetAllNodesToApplyGravitation();var h=new Set(this.getAllNodes()),f=this.nodesWithGravity.filter(function(p){return h.has(p)});this.graphManager.setAllNodesToApplyGravitation(f),this.positionNodesRandomly()}}return this.initSpringEmbedder(),this.runSpringEmbedder(),!0},d.prototype.tick=function(){if(this.totalIterations++,this.totalIterations===this.maxIterations&&!this.isTreeGrowing&&!this.isGrowthFinished)if(this.prunedNodesAll.length>0)this.isTreeGrowing=!0;else return!0;if(this.totalIterations%v.CONVERGENCE_CHECK_PERIOD==0&&!this.isTreeGrowing&&!this.isGrowthFinished){if(this.isConverged())if(this.prunedNodesAll.length>0)this.isTreeGrowing=!0;else return!0;this.coolingCycle++,this.layoutQuality==0?this.coolingAdjuster=this.coolingCycle:this.layoutQuality==1&&(this.coolingAdjuster=this.coolingCycle/3),this.coolingFactor=Math.max(this.initialCoolingFactor-Math.pow(this.coolingCycle,Math.log(100*(this.initialCoolingFactor-this.finalTemperature))/Math.log(this.maxCoolingCycle))/100*this.coolingAdjuster,this.finalTemperature),this.animationPeriod=Math.ceil(this.initialAnimationPeriod*Math.sqrt(this.coolingFactor))}if(this.isTreeGrowing){if(this.growTreeIterations%10==0)if(this.prunedNodesAll.length>0){this.graphManager.updateBounds(),this.updateGrid(),this.growTree(this.prunedNodesAll),this.graphManager.resetAllNodesToApplyGravitation();var s=new Set(this.getAllNodes()),h=this.nodesWithGravity.filter(function(A){return s.has(A)});this.graphManager.setAllNodesToApplyGravitation(h),this.graphManager.updateBounds(),this.updateGrid(),this.coolingFactor=v.DEFAULT_COOLING_FACTOR_INCREMENTAL}else this.isTreeGrowing=!1,this.isGrowthFinished=!0;this.growTreeIterations++}if(this.isGrowthFinished){if(this.isConverged())return!0;this.afterGrowthIterations%10==0&&(this.graphManager.updateBounds(),this.updateGrid()),this.coolingFactor=v.DEFAULT_COOLING_FACTOR_INCREMENTAL*((100-this.afterGrowthIterations)/100),this.afterGrowthIterations++}var f=!this.isTreeGrowing&&!this.isGrowthFinished,p=this.growTreeIterations%10==1&&this.isTreeGrowing||this.afterGrowthIterations%10==1&&this.isGrowthFinished;return this.totalDisplacement=0,this.graphManager.updateBounds(),this.calcSpringForces(),this.calcRepulsionForces(f,p),this.calcGravitationalForces(),this.moveNodes(),this.animate(),!1},d.prototype.getPositionsData=function(){for(var s=this.graphManager.getAllNodes(),h={},f=0;f<s.length;f++){var p=s[f].rect,A=s[f].id;h[A]={id:A,x:p.getCenterX(),y:p.getCenterY(),w:p.width,h:p.height}}return h},d.prototype.runSpringEmbedder=function(){this.initialAnimationPeriod=25,this.animationPeriod=this.initialAnimationPeriod;var s=!1;if(v.ANIMATE==="during")this.emit("layoutstarted");else{for(;!s;)s=this.tick();this.graphManager.updateBounds()}},d.prototype.calculateNodesToApplyGravitationTo=function(){var s=[],h,f=this.graphManager.getGraphs(),p=f.length,A;for(A=0;A<p;A++)h=f[A],h.updateConnected(),h.isConnected||(s=s.concat(h.getNodes()));return s},d.prototype.createBendpoints=function(){var s=[];s=s.concat(this.graphManager.getAllEdges());var h=new Set,f;for(f=0;f<s.length;f++){var p=s[f];if(!h.has(p)){var A=p.getSource(),I=p.getTarget();if(A==I)p.getBendpoints().push(new l),p.getBendpoints().push(new l),this.createDummyNodesForBendpoints(p),h.add(p);else{var R=[];if(R=R.concat(A.getEdgeListToNode(I)),R=R.concat(I.getEdgeListToNode(A)),!h.has(R[0])){if(R.length>1){var x;for(x=0;x<R.length;x++){var G=R[x];G.getBendpoints().push(new l),this.createDummyNodesForBendpoints(G)}}R.forEach(function(U){h.add(U)})}}}if(h.size==s.length)break}},d.prototype.positionNodesRadially=function(s){for(var h=new c(0,0),f=Math.ceil(Math.sqrt(s.length)),p=0,A=0,I=0,R=new l(0,0),x=0;x<s.length;x++){x%f==0&&(I=0,A=p,x!=0&&(A+=a.DEFAULT_COMPONENT_SEPERATION),p=0);var G=s[x],U=E.findCenterOfTree(G);h.x=I,h.y=A,R=d.radialLayout(G,U,h),R.y>p&&(p=Math.floor(R.y)),I=Math.floor(R.x+a.DEFAULT_COMPONENT_SEPERATION)}this.transform(new l(n.WORLD_CENTER_X-R.x/2,n.WORLD_CENTER_Y-R.y/2))},d.radialLayout=function(s,h,f){var p=Math.max(this.maxDiagonalInTree(s),a.DEFAULT_RADIAL_SEPARATION);d.branchRadialLayout(h,null,0,359,0,p);var A=L.calculateBounds(s),I=new O;I.setDeviceOrgX(A.getMinX()),I.setDeviceOrgY(A.getMinY()),I.setWorldOrgX(f.x),I.setWorldOrgY(f.y);for(var R=0;R<s.length;R++){var x=s[R];x.transform(I)}var G=new l(A.getMaxX(),A.getMaxY());return I.inverseTransformPoint(G)},d.branchRadialLayout=function(s,h,f,p,A,I){var R=(p-f+1)/2;R<0&&(R+=180);var x=(R+f)%360,G=x*m.TWO_PI/360,U=A*Math.cos(G),X=A*Math.sin(G);s.setCenter(U,X);var w=[];w=w.concat(s.getEdges());var S=w.length;h!=null&&S--;for(var F=0,b=w.length,Y,k=s.getEdgesBetween(h);k.length>1;){var H=k[0];k.splice(0,1);var P=w.indexOf(H);P>=0&&w.splice(P,1),b--,S--}h!=null?Y=(w.indexOf(k[0])+1)%b:Y=0;for(var B=Math.abs(p-f)/S,$=Y;F!=S;$=++$%b){var j=w[$].getOtherEnd(s);if(j!=h){var V=(f+F*B)%360,z=(V+B)%360;d.branchRadialLayout(j,s,V,z,A+I,I),F++}}},d.maxDiagonalInTree=function(s){for(var h=T.MIN_VALUE,f=0;f<s.length;f++){var p=s[f],A=p.getDiagonal();A>h&&(h=A)}return h},d.prototype.calcRepulsionRange=function(){return 2*(this.level+1)*this.idealEdgeLength},d.prototype.groupZeroDegreeMembers=function(){var s=this,h={};this.memberGroups={},this.idToDummyNode={};for(var f=[],p=this.graphManager.getAllNodes(),A=0;A<p.length;A++){var I=p[A],R=I.getParent();this.getNodeDegreeWithChildren(I)===0&&(R.id==null||!this.getToBeTiled(R))&&f.push(I)}for(var A=0;A<f.length;A++){var I=f[A],x=I.getParent().id;typeof h[x]>"u"&&(h[x]=[]),h[x]=h[x].concat(I)}Object.keys(h).forEach(function(G){if(h[G].length>1){var U="DummyCompound_"+G;s.memberGroups[U]=h[G];var X=h[G][0].getParent(),w=new o(s.graphManager);w.id=U,w.paddingLeft=X.paddingLeft||0,w.paddingRight=X.paddingRight||0,w.paddingBottom=X.paddingBottom||0,w.paddingTop=X.paddingTop||0,s.idToDummyNode[U]=w;var S=s.getGraphManager().add(s.newGraph(),w),F=X.getChild();F.add(w);for(var b=0;b<h[G].length;b++){var Y=h[G][b];F.remove(Y),S.add(Y)}}})},d.prototype.clearCompounds=function(){var s={},h={};this.performDFSOnCompounds();for(var f=0;f<this.compoundOrder.length;f++)h[this.compoundOrder[f].id]=this.compoundOrder[f],s[this.compoundOrder[f].id]=[].concat(this.compoundOrder[f].getChild().getNodes()),this.graphManager.remove(this.compoundOrder[f].getChild()),this.compoundOrder[f].child=null;this.graphManager.resetAllNodes(),this.tileCompoundMembers(s,h)},d.prototype.clearZeroDegreeMembers=function(){var s=this,h=this.tiledZeroDegreePack=[];Object.keys(this.memberGroups).forEach(function(f){var p=s.idToDummyNode[f];h[f]=s.tileNodes(s.memberGroups[f],p.paddingLeft+p.paddingRight),p.rect.width=h[f].width,p.rect.height=h[f].height})},d.prototype.repopulateCompounds=function(){for(var s=this.compoundOrder.length-1;s>=0;s--){var h=this.compoundOrder[s],f=h.id,p=h.paddingLeft,A=h.paddingTop;this.adjustLocations(this.tiledMemberPack[f],h.rect.x,h.rect.y,p,A)}},d.prototype.repopulateZeroDegreeMembers=function(){var s=this,h=this.tiledZeroDegreePack;Object.keys(h).forEach(function(f){var p=s.idToDummyNode[f],A=p.paddingLeft,I=p.paddingTop;s.adjustLocations(h[f],p.rect.x,p.rect.y,A,I)})},d.prototype.getToBeTiled=function(s){var h=s.id;if(this.toBeTiled[h]!=null)return this.toBeTiled[h];var f=s.getChild();if(f==null)return this.toBeTiled[h]=!1,!1;for(var p=f.getNodes(),A=0;A<p.length;A++){var I=p[A];if(this.getNodeDegree(I)>0)return this.toBeTiled[h]=!1,!1;if(I.getChild()==null){this.toBeTiled[I.id]=!1;continue}if(!this.getToBeTiled(I))return this.toBeTiled[h]=!1,!1}return this.toBeTiled[h]=!0,!0},d.prototype.getNodeDegree=function(s){s.id;for(var h=s.getEdges(),f=0,p=0;p<h.length;p++){var A=h[p];A.getSource().id!==A.getTarget().id&&(f=f+1)}return f},d.prototype.getNodeDegreeWithChildren=function(s){var h=this.getNodeDegree(s);if(s.getChild()==null)return h;for(var f=s.getChild().getNodes(),p=0;p<f.length;p++){var A=f[p];h+=this.getNodeDegreeWithChildren(A)}return h},d.prototype.performDFSOnCompounds=function(){this.compoundOrder=[],this.fillCompexOrderByDFS(this.graphManager.getRoot().getNodes())},d.prototype.fillCompexOrderByDFS=function(s){for(var h=0;h<s.length;h++){var f=s[h];f.getChild()!=null&&this.fillCompexOrderByDFS(f.getChild().getNodes()),this.getToBeTiled(f)&&this.compoundOrder.push(f)}},d.prototype.adjustLocations=function(s,h,f,p,A){h+=p,f+=A;for(var I=h,R=0;R<s.rows.length;R++){var x=s.rows[R];h=I;for(var G=0,U=0;U<x.length;U++){var X=x[U];X.rect.x=h,X.rect.y=f,h+=X.rect.width+s.horizontalPadding,X.rect.height>G&&(G=X.rect.height)}f+=G+s.verticalPadding}},d.prototype.tileCompoundMembers=function(s,h){var f=this;this.tiledMemberPack=[],Object.keys(s).forEach(function(p){var A=h[p];f.tiledMemberPack[p]=f.tileNodes(s[p],A.paddingLeft+A.paddingRight),A.rect.width=f.tiledMemberPack[p].width,A.rect.height=f.tiledMemberPack[p].height})},d.prototype.tileNodes=function(s,h){var f=a.TILING_PADDING_VERTICAL,p=a.TILING_PADDING_HORIZONTAL,A={rows:[],rowWidth:[],rowHeight:[],width:0,height:h,verticalPadding:f,horizontalPadding:p};s.sort(function(x,G){return x.rect.width*x.rect.height>G.rect.width*G.rect.height?-1:x.rect.width*x.rect.height<G.rect.width*G.rect.height?1:0});for(var I=0;I<s.length;I++){var R=s[I];A.rows.length==0?this.insertNodeToRow(A,R,0,h):this.canAddHorizontal(A,R.rect.width,R.rect.height)?this.insertNodeToRow(A,R,this.getShortestRowIndex(A),h):this.insertNodeToRow(A,R,A.rows.length,h),this.shiftToLastRow(A)}return A},d.prototype.insertNodeToRow=function(s,h,f,p){var A=p;if(f==s.rows.length){var I=[];s.rows.push(I),s.rowWidth.push(A),s.rowHeight.push(0)}var R=s.rowWidth[f]+h.rect.width;s.rows[f].length>0&&(R+=s.horizontalPadding),s.rowWidth[f]=R,s.width<R&&(s.width=R);var x=h.rect.height;f>0&&(x+=s.verticalPadding);var G=0;x>s.rowHeight[f]&&(G=s.rowHeight[f],s.rowHeight[f]=x,G=s.rowHeight[f]-G),s.height+=G,s.rows[f].push(h)},d.prototype.getShortestRowIndex=function(s){for(var h=-1,f=Number.MAX_VALUE,p=0;p<s.rows.length;p++)s.rowWidth[p]<f&&(h=p,f=s.rowWidth[p]);return h},d.prototype.getLongestRowIndex=function(s){for(var h=-1,f=Number.MIN_VALUE,p=0;p<s.rows.length;p++)s.rowWidth[p]>f&&(h=p,f=s.rowWidth[p]);return h},d.prototype.canAddHorizontal=function(s,h,f){var p=this.getShortestRowIndex(s);if(p<0)return!0;var A=s.rowWidth[p];if(A+s.horizontalPadding+h<=s.width)return!0;var I=0;s.rowHeight[p]<f&&p>0&&(I=f+s.verticalPadding-s.rowHeight[p]);var R;s.width-A>=h+s.horizontalPadding?R=(s.height+I)/(A+h+s.horizontalPadding):R=(s.height+I)/s.width,I=f+s.verticalPadding;var x;return s.width<h?x=(s.height+I)/h:x=(s.height+I)/s.width,x<1&&(x=1/x),R<1&&(R=1/R),R<x},d.prototype.shiftToLastRow=function(s){var h=this.getLongestRowIndex(s),f=s.rowWidth.length-1,p=s.rows[h],A=p[p.length-1],I=A.width+s.horizontalPadding;if(s.width-s.rowWidth[f]>I&&h!=f){p.splice(-1,1),s.rows[f].push(A),s.rowWidth[h]=s.rowWidth[h]-I,s.rowWidth[f]=s.rowWidth[f]+I,s.width=s.rowWidth[instance.getLongestRowIndex(s)];for(var R=Number.MIN_VALUE,x=0;x<p.length;x++)p[x].height>R&&(R=p[x].height);h>0&&(R+=s.verticalPadding);var G=s.rowHeight[h]+s.rowHeight[f];s.rowHeight[h]=R,s.rowHeight[f]<A.height+s.verticalPadding&&(s.rowHeight[f]=A.height+s.verticalPadding);var U=s.rowHeight[h]+s.rowHeight[f];s.height+=U-G,this.shiftToLastRow(s)}},d.prototype.tilingPreLayout=function(){a.TILE&&(this.groupZeroDegreeMembers(),this.clearCompounds(),this.clearZeroDegreeMembers())},d.prototype.tilingPostLayout=function(){a.TILE&&(this.repopulateZeroDegreeMembers(),this.repopulateCompounds())},d.prototype.reduceTrees=function(){for(var s=[],h=!0,f;h;){var p=this.graphManager.getAllNodes(),A=[];h=!1;for(var I=0;I<p.length;I++)f=p[I],f.getEdges().length==1&&!f.getEdges()[0].isInterGraph&&f.getChild()==null&&(A.push([f,f.getEdges()[0],f.getOwner()]),h=!0);if(h==!0){for(var R=[],x=0;x<A.length;x++)A[x][0].getEdges().length==1&&(R.push(A[x]),A[x][0].getOwner().remove(A[x][0]));s.push(R),this.graphManager.resetAllNodes(),this.graphManager.resetAllEdges()}}this.prunedNodesAll=s},d.prototype.growTree=function(s){for(var h=s.length,f=s[h-1],p,A=0;A<f.length;A++)p=f[A],this.findPlaceforPrunedNode(p),p[2].add(p[0]),p[2].add(p[1],p[1].source,p[1].target);s.splice(s.length-1,1),this.graphManager.resetAllNodes(),this.graphManager.resetAllEdges()},d.prototype.findPlaceforPrunedNode=function(s){var h,f,p=s[0];p==s[1].source?f=s[1].target:f=s[1].source;var A=f.startX,I=f.finishX,R=f.startY,x=f.finishY,G=0,U=0,X=0,w=0,S=[G,X,U,w];if(R>0)for(var F=A;F<=I;F++)S[0]+=this.grid[F][R-1].length+this.grid[F][R].length-1;if(I<this.grid.length-1)for(var F=R;F<=x;F++)S[1]+=this.grid[I+1][F].length+this.grid[I][F].length-1;if(x<this.grid[0].length-1)for(var F=A;F<=I;F++)S[2]+=this.grid[F][x+1].length+this.grid[F][x].length-1;if(A>0)for(var F=R;F<=x;F++)S[3]+=this.grid[A-1][F].length+this.grid[A][F].length-1;for(var b=T.MAX_VALUE,Y,k,H=0;H<S.length;H++)S[H]<b?(b=S[H],Y=1,k=H):S[H]==b&&Y++;if(Y==3&&b==0)S[0]==0&&S[1]==0&&S[2]==0?h=1:S[0]==0&&S[1]==0&&S[3]==0?h=0:S[0]==0&&S[2]==0&&S[3]==0?h=3:S[1]==0&&S[2]==0&&S[3]==0&&(h=2);else if(Y==2&&b==0){var P=Math.floor(Math.random()*2);S[0]==0&&S[1]==0?P==0?h=0:h=1:S[0]==0&&S[2]==0?P==0?h=0:h=2:S[0]==0&&S[3]==0?P==0?h=0:h=3:S[1]==0&&S[2]==0?P==0?h=1:h=2:S[1]==0&&S[3]==0?P==0?h=1:h=3:P==0?h=2:h=3}else if(Y==4&&b==0){var P=Math.floor(Math.random()*4);h=P}else h=k;h==0?p.setCenter(f.getCenterX(),f.getCenterY()-f.getHeight()/2-v.DEFAULT_EDGE_LENGTH-p.getHeight()/2):h==1?p.setCenter(f.getCenterX()+f.getWidth()/2+v.DEFAULT_EDGE_LENGTH+p.getWidth()/2,f.getCenterY()):h==2?p.setCenter(f.getCenterX(),f.getCenterY()+f.getHeight()/2+v.DEFAULT_EDGE_LENGTH+p.getHeight()/2):p.setCenter(f.getCenterX()-f.getWidth()/2-v.DEFAULT_EDGE_LENGTH-p.getWidth()/2,f.getCenterY())},D.exports=d},function(D,y,r){var t={};t.layoutBase=r(0),t.CoSEConstants=r(1),t.CoSEEdge=r(2),t.CoSEGraph=r(3),t.CoSEGraphManager=r(4),t.CoSELayout=r(6),t.CoSENode=r(5),D.exports=t}])})}(et)),et.exports}var wt=tt.exports,ut;function St(){return ut||(ut=1,function(C,M){(function(D,y){C.exports=y(Mt())})(wt,function(u){return function(D){var y={};function r(t){if(y[t])return y[t].exports;var e=y[t]={i:t,l:!1,exports:{}};return D[t].call(e.exports,e,e.exports,r),e.l=!0,e.exports}return r.m=D,r.c=y,r.i=function(t){return 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E=function(L){L.nodeRepulsion!=null&&(i.DEFAULT_REPULSION_STRENGTH=e.DEFAULT_REPULSION_STRENGTH=L.nodeRepulsion),L.idealEdgeLength!=null&&(i.DEFAULT_EDGE_LENGTH=e.DEFAULT_EDGE_LENGTH=L.idealEdgeLength),L.edgeElasticity!=null&&(i.DEFAULT_SPRING_STRENGTH=e.DEFAULT_SPRING_STRENGTH=L.edgeElasticity),L.nestingFactor!=null&&(i.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR=e.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR=L.nestingFactor),L.gravity!=null&&(i.DEFAULT_GRAVITY_STRENGTH=e.DEFAULT_GRAVITY_STRENGTH=L.gravity),L.numIter!=null&&(i.MAX_ITERATIONS=e.MAX_ITERATIONS=L.numIter),L.gravityRange!=null&&(i.DEFAULT_GRAVITY_RANGE_FACTOR=e.DEFAULT_GRAVITY_RANGE_FACTOR=L.gravityRange),L.gravityCompound!=null&&(i.DEFAULT_COMPOUND_GRAVITY_STRENGTH=e.DEFAULT_COMPOUND_GRAVITY_STRENGTH=L.gravityCompound),L.gravityRangeCompound!=null&&(i.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR=e.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR=L.gravityRangeCompound),L.initialEnergyOnIncremental!=null&&(i.DEFAULT_COOLING_FACTOR_INCREMENTAL=e.DEFAULT_COOLING_FACTOR_INCREMENTAL=L.initialEnergyOnIncremental),L.quality=="draft"?t.QUALITY=0:L.quality=="proof"?t.QUALITY=2:t.QUALITY=1,i.NODE_DIMENSIONS_INCLUDE_LABELS=e.NODE_DIMENSIONS_INCLUDE_LABELS=t.NODE_DIMENSIONS_INCLUDE_LABELS=L.nodeDimensionsIncludeLabels,i.DEFAULT_INCREMENTAL=e.DEFAULT_INCREMENTAL=t.DEFAULT_INCREMENTAL=!L.randomize,i.ANIMATE=e.ANIMATE=t.ANIMATE=L.animate,i.TILE=L.tile,i.TILING_PADDING_VERTICAL=typeof 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w=function(){O.fit&&O.cy.fit(O.eles,O.padding),m||(m=!0,N.cy.one("layoutready",O.ready),N.cy.trigger({type:"layoutready",layout:N}))},S=N.options.refresh,F,b=0;b<S&&!F;b++)F=N.stopped||N.layout.tick();if(F){d.checkLayoutSuccess()&&!d.isSubLayout&&d.doPostLayout(),d.tilingPostLayout&&d.tilingPostLayout(),d.isLayoutFinished=!0,N.options.eles.nodes().positions(G),w(),N.cy.one("layoutstop",N.options.stop),N.cy.trigger({type:"layoutstop",layout:N}),L&&cancelAnimationFrame(L),m=!1;return}var Y=N.layout.getPositionsData();O.eles.nodes().positions(function(k,H){if(typeof k=="number"&&(k=H),!k.isParent()){for(var P=k.id(),B=Y[P],$=k;B==null&&(B=Y[$.data("parent")]||Y["DummyCompound_"+$.data("parent")],Y[P]=B,$=$.parent()[0],$!=null););return B!=null?{x:B.x,y:B.y}:{x:k.position("x"),y:k.position("y")}}}),w(),L=requestAnimationFrame(X)};return d.addListener("layoutstarted",function(){N.options.animate==="during"&&(L=requestAnimationFrame(U))}),d.runLayout(),this.options.animate!=="during"&&(N.options.eles.nodes().not(":parent").layoutPositions(N,N.options,G),m=!1),this},l.prototype.getTopMostNodes=function(m){for(var L={},O=0;O<m.length;O++)L[m[O].id()]=!0;var d=m.filter(function(N,s){typeof N=="number"&&(N=s);for(var h=N.parent()[0];h!=null;){if(L[h.id()])return!1;h=h.parent()[0]}return!0});return d},l.prototype.processChildrenList=function(m,L,O){for(var d=L.length,N=0;N<d;N++){var s=L[N],h=s.children(),f,p=s.layoutDimensions({nodeDimensionsIncludeLabels:this.options.nodeDimensionsIncludeLabels});if(s.outerWidth()!=null&&s.outerHeight()!=null?f=m.add(new g(O.graphManager,new a(s.position("x")-p.w/2,s.position("y")-p.h/2),new v(parseFloat(p.w),parseFloat(p.h)))):f=m.add(new 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a(T,L,m-T,O-L);T==t.MAX_VALUE&&(this.left=this.parent.getLeft(),this.right=this.parent.getRight(),this.top=this.parent.getTop(),this.bottom=this.parent.getBottom()),p[0].getParent().paddingLeft!=null?f=p[0].getParent().paddingLeft:f=this.margin,this.left=x.x-f,this.right=x.x+x.width+f,this.top=x.y-f,this.bottom=x.y+x.height+f},c.calculateBounds=function(E){for(var T=t.MAX_VALUE,m=-t.MAX_VALUE,L=t.MAX_VALUE,O=-t.MAX_VALUE,d,N,s,h,f=E.length,p=0;p<f;p++){var A=E[p];d=A.getLeft(),N=A.getRight(),s=A.getTop(),h=A.getBottom(),T>d&&(T=d),m<N&&(m=N),L>s&&(L=s),O<h&&(O=h)}var I=new a(T,L,m-T,O-L);return I},c.prototype.getInclusionTreeDepth=function(){return this==this.graphManager.getRoot()?1:this.parent.getInclusionTreeDepth()},c.prototype.getEstimatedSize=function(){if(this.estimatedSize==t.MIN_VALUE)throw"assert failed";return this.estimatedSize},c.prototype.calcEstimatedSize=function(){for(var E=0,T=this.nodes,m=T.length,L=0;L<m;L++){var O=T[L];E+=O.calcEstimatedSize()}return E==0?this.estimatedSize=e.EMPTY_COMPOUND_NODE_SIZE:this.estimatedSize=E/Math.sqrt(this.nodes.length),this.estimatedSize},c.prototype.updateConnected=function(){var E=this;if(this.nodes.length==0){this.isConnected=!0;return}var T=new n,m=new Set,L=this.nodes[0],O,d,N=L.withChildren();for(N.forEach(function(I){T.push(I),m.add(I)});T.length!==0;){L=T.shift(),O=L.getEdges();for(var s=O.length,h=0;h<s;h++){var f=O[h];if(d=f.getOtherEndInGraph(L,this),d!=null&&!m.has(d)){var p=d.withChildren();p.forEach(function(I){T.push(I),m.add(I)})}}}if(this.isConnected=!1,m.size>=this.nodes.length){var A=0;m.forEach(function(I){I.owner==E&&A++}),A==this.nodes.length&&(this.isConnected=!0)}},u.exports=c},function(u,D,y){var r,t=y(1);function e(i){r=y(5),this.layout=i,this.graphs=[],this.edges=[]}e.prototype.addRoot=function(){var i=this.layout.newGraph(),o=this.layout.newNode(null),g=this.add(i,o);return this.setRootGraph(g),this.rootGraph},e.prototype.add=function(i,o,g,a,v){if(g==null&&a==null&&v==null){if(i==null)throw"Graph is null!";if(o==null)throw"Parent node is null!";if(this.graphs.indexOf(i)>-1)throw"Graph already in this graph mgr!";if(this.graphs.push(i),i.parent!=null)throw"Already has a parent!";if(o.child!=null)throw"Already has a child!";return i.parent=o,o.child=i,i}else{v=g,a=o,g=i;var n=a.getOwner(),c=v.getOwner();if(!(n!=null&&n.getGraphManager()==this))throw"Source not in this graph mgr!";if(!(c!=null&&c.getGraphManager()==this))throw"Target not in this graph mgr!";if(n==c)return g.isInterGraph=!1,n.add(g,a,v);if(g.isInterGraph=!0,g.source=a,g.target=v,this.edges.indexOf(g)>-1)throw"Edge already in inter-graph edge list!";if(this.edges.push(g),!(g.source!=null&&g.target!=null))throw"Edge source and/or target is null!";if(!(g.source.edges.indexOf(g)==-1&&g.target.edges.indexOf(g)==-1))throw"Edge already in source and/or target incidency list!";return g.source.edges.push(g),g.target.edges.push(g),g}},e.prototype.remove=function(i){if(i instanceof r){var o=i;if(o.getGraphManager()!=this)throw"Graph not in this graph mgr";if(!(o==this.rootGraph||o.parent!=null&&o.parent.graphManager==this))throw"Invalid parent node!";var g=[];g=g.concat(o.getEdges());for(var a,v=g.length,n=0;n<v;n++)a=g[n],o.remove(a);var c=[];c=c.concat(o.getNodes());var l;v=c.length;for(var n=0;n<v;n++)l=c[n],o.remove(l);o==this.rootGraph&&this.setRootGraph(null);var E=this.graphs.indexOf(o);this.graphs.splice(E,1),o.parent=null}else if(i instanceof t){if(a=i,a==null)throw"Edge is null!";if(!a.isInterGraph)throw"Not an inter-graph edge!";if(!(a.source!=null&&a.target!=null))throw"Source and/or target is null!";if(!(a.source.edges.indexOf(a)!=-1&&a.target.edges.indexOf(a)!=-1))throw"Source and/or target doesn't know this edge!";var E=a.source.edges.indexOf(a);if(a.source.edges.splice(E,1),E=a.target.edges.indexOf(a),a.target.edges.splice(E,1),!(a.source.owner!=null&&a.source.owner.getGraphManager()!=null))throw"Edge owner graph or owner graph manager is null!";if(a.source.owner.getGraphManager().edges.indexOf(a)==-1)throw"Not in owner graph manager's edge list!";var E=a.source.owner.getGraphManager().edges.indexOf(a);a.source.owner.getGraphManager().edges.splice(E,1)}},e.prototype.updateBounds=function(){this.rootGraph.updateBounds(!0)},e.prototype.getGraphs=function(){return this.graphs},e.prototype.getAllNodes=function(){if(this.allNodes==null){for(var i=[],o=this.getGraphs(),g=o.length,a=0;a<g;a++)i=i.concat(o[a].getNodes());this.allNodes=i}return this.allNodes},e.prototype.resetAllNodes=function(){this.allNodes=null},e.prototype.resetAllEdges=function(){this.allEdges=null},e.prototype.resetAllNodesToApplyGravitation=function(){this.allNodesToApplyGravitation=null},e.prototype.getAllEdges=function(){if(this.allEdges==null){var i=[],o=this.getGraphs();o.length;for(var g=0;g<o.length;g++)i=i.concat(o[g].getEdges());i=i.concat(this.edges),this.allEdges=i}return this.allEdges},e.prototype.getAllNodesToApplyGravitation=function(){return this.allNodesToApplyGravitation},e.prototype.setAllNodesToApplyGravitation=function(i){if(this.allNodesToApplyGravitation!=null)throw"assert failed";this.allNodesToApplyGravitation=i},e.prototype.getRoot=function(){return this.rootGraph},e.prototype.setRootGraph=function(i){if(i.getGraphManager()!=this)throw"Root not in this graph mgr!";this.rootGraph=i,i.parent==null&&(i.parent=this.layout.newNode("Root node"))},e.prototype.getLayout=function(){return this.layout},e.prototype.isOneAncestorOfOther=function(i,o){if(!(i!=null&&o!=null))throw"assert failed";if(i==o)return!0;var g=i.getOwner(),a;do{if(a=g.getParent(),a==null)break;if(a==o)return!0;if(g=a.getOwner(),g==null)break}while(!0);g=o.getOwner();do{if(a=g.getParent(),a==null)break;if(a==i)return!0;if(g=a.getOwner(),g==null)break}while(!0);return!1},e.prototype.calcLowestCommonAncestors=function(){for(var i,o,g,a,v,n=this.getAllEdges(),c=n.length,l=0;l<c;l++){if(i=n[l],o=i.source,g=i.target,i.lca=null,i.sourceInLca=o,i.targetInLca=g,o==g){i.lca=o.getOwner();continue}for(a=o.getOwner();i.lca==null;){for(i.targetInLca=g,v=g.getOwner();i.lca==null;){if(v==a){i.lca=v;break}if(v==this.rootGraph)break;if(i.lca!=null)throw"assert failed";i.targetInLca=v.getParent(),v=i.targetInLca.getOwner()}if(a==this.rootGraph)break;i.lca==null&&(i.sourceInLca=a.getParent(),a=i.sourceInLca.getOwner())}if(i.lca==null)throw"assert failed"}},e.prototype.calcLowestCommonAncestor=function(i,o){if(i==o)return i.getOwner();var g=i.getOwner();do{if(g==null)break;var a=o.getOwner();do{if(a==null)break;if(a==g)return a;a=a.getParent().getOwner()}while(!0);g=g.getParent().getOwner()}while(!0);return g},e.prototype.calcInclusionTreeDepths=function(i,o){i==null&&o==null&&(i=this.rootGraph,o=1);for(var g,a=i.getNodes(),v=a.length,n=0;n<v;n++)g=a[n],g.inclusionTreeDepth=o,g.child!=null&&this.calcInclusionTreeDepths(g.child,o+1)},e.prototype.includesInvalidEdge=function(){for(var i,o=this.edges.length,g=0;g<o;g++)if(i=this.edges[g],this.isOneAncestorOfOther(i.source,i.target))return!0;return!1},u.exports=e},function(u,D,y){var r=y(0);function t(){}for(var e in r)t[e]=r[e];t.MAX_ITERATIONS=2500,t.DEFAULT_EDGE_LENGTH=50,t.DEFAULT_SPRING_STRENGTH=.45,t.DEFAULT_REPULSION_STRENGTH=4500,t.DEFAULT_GRAVITY_STRENGTH=.4,t.DEFAULT_COMPOUND_GRAVITY_STRENGTH=1,t.DEFAULT_GRAVITY_RANGE_FACTOR=3.8,t.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR=1.5,t.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION=!0,t.DEFAULT_USE_SMART_REPULSION_RANGE_CALCULATION=!0,t.DEFAULT_COOLING_FACTOR_INCREMENTAL=.3,t.COOLING_ADAPTATION_FACTOR=.33,t.ADAPTATION_LOWER_NODE_LIMIT=1e3,t.ADAPTATION_UPPER_NODE_LIMIT=5e3,t.MAX_NODE_DISPLACEMENT_INCREMENTAL=100,t.MAX_NODE_DISPLACEMENT=t.MAX_NODE_DISPLACEMENT_INCREMENTAL*3,t.MIN_REPULSION_DIST=t.DEFAULT_EDGE_LENGTH/10,t.CONVERGENCE_CHECK_PERIOD=100,t.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR=.1,t.MIN_EDGE_LENGTH=1,t.GRID_CALCULATION_CHECK_PERIOD=10,u.exports=t},function(u,D,y){var r=y(12);function t(){}t.calcSeparationAmount=function(e,i,o,g){if(!e.intersects(i))throw"assert failed";var a=new 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this.graphManager.getAllNodesToApplyGravitation()},c.prototype.newGraphManager=function(){var l=new e(this);return this.graphManager=l,l},c.prototype.newGraph=function(l){return new g(null,this.graphManager,l)},c.prototype.newNode=function(l){return new i(this.graphManager,l)},c.prototype.newEdge=function(l){return new o(null,null,l)},c.prototype.checkLayoutSuccess=function(){return this.graphManager.getRoot()==null||this.graphManager.getRoot().getNodes().length==0||this.graphManager.includesInvalidEdge()},c.prototype.runLayout=function(){this.isLayoutFinished=!1,this.tilingPreLayout&&this.tilingPreLayout(),this.initParameters();var l;return this.checkLayoutSuccess()?l=!1:l=this.layout(),t.ANIMATE==="during"?!1:(l&&(this.isSubLayout||this.doPostLayout()),this.tilingPostLayout&&this.tilingPostLayout(),this.isLayoutFinished=!0,l)},c.prototype.doPostLayout=function(){this.incremental||this.transform(),this.update()},c.prototype.update2=function(){if(this.createBendsAsNeeded&&(this.createBendpointsFromDummyNodes(),this.graphManager.resetAllEdges()),!this.isRemoteUse){for(var l=this.graphManager.getAllEdges(),E=0;E<l.length;E++)l[E];for(var T=this.graphManager.getRoot().getNodes(),E=0;E<T.length;E++)T[E];this.update(this.graphManager.getRoot())}},c.prototype.update=function(l){if(l==null)this.update2();else if(l instanceof i){var E=l;if(E.getChild()!=null)for(var T=E.getChild().getNodes(),m=0;m<T.length;m++)update(T[m]);if(E.vGraphObject!=null){var L=E.vGraphObject;L.update(E)}}else if(l instanceof o){var O=l;if(O.vGraphObject!=null){var d=O.vGraphObject;d.update(O)}}else if(l instanceof g){var N=l;if(N.vGraphObject!=null){var s=N.vGraphObject;s.update(N)}}},c.prototype.initParameters=function(){this.isSubLayout||(this.layoutQuality=t.QUALITY,this.animationDuringLayout=t.DEFAULT_ANIMATION_DURING_LAYOUT,this.animationPeriod=t.DEFAULT_ANIMATION_PERIOD,this.animationOnLayout=t.DEFAULT_ANIMATION_ON_LAYOUT,this.incremental=t.DEFAULT_INCREMENTAL,this.createBendsAsNeeded=t.DEFAULT_CREATE_BENDS_AS_NEEDED,this.uniformLeafNodeSizes=t.DEFAULT_UNIFORM_LEAF_NODE_SIZES),this.animationDuringLayout&&(this.animationOnLayout=!1)},c.prototype.transform=function(l){if(l==null)this.transform(new a(0,0));else{var E=new v,T=this.graphManager.getRoot().updateLeftTop();if(T!=null){E.setWorldOrgX(l.x),E.setWorldOrgY(l.y),E.setDeviceOrgX(T.x),E.setDeviceOrgY(T.y);for(var m=this.getAllNodes(),L,O=0;O<m.length;O++)L=m[O],L.transform(E)}}},c.prototype.positionNodesRandomly=function(l){if(l==null)this.positionNodesRandomly(this.getGraphManager().getRoot()),this.getGraphManager().getRoot().updateBounds(!0);else for(var E,T,m=l.getNodes(),L=0;L<m.length;L++)E=m[L],T=E.getChild(),T==null||T.getNodes().length==0?E.scatter():(this.positionNodesRandomly(T),E.updateBounds())},c.prototype.getFlatForest=function(){for(var l=[],E=!0,T=this.graphManager.getRoot().getNodes(),m=!0,L=0;L<T.length;L++)T[L].getChild()!=null&&(m=!1);if(!m)return l;var O=new Set,d=[],N=new Map,s=[];for(s=s.concat(T);s.length>0&&E;){for(d.push(s[0]);d.length>0&&E;){var h=d[0];d.splice(0,1),O.add(h);for(var f=h.getEdges(),L=0;L<f.length;L++){var p=f[L].getOtherEnd(h);if(N.get(h)!=p)if(!O.has(p))d.push(p),N.set(p,h);else{E=!1;break}}}if(!E)l=[];else{var A=[].concat(r(O));l.push(A);for(var L=0;L<A.length;L++){var I=A[L],R=s.indexOf(I);R>-1&&s.splice(R,1)}O=new Set,N=new Map}}return l},c.prototype.createDummyNodesForBendpoints=function(l){for(var E=[],T=l.source,m=this.graphManager.calcLowestCommonAncestor(l.source,l.target),L=0;L<l.bendpoints.length;L++){var O=this.newNode(null);O.setRect(new Point(0,0),new Dimension(1,1)),m.add(O);var d=this.newEdge(null);this.graphManager.add(d,T,O),E.add(O),T=O}var d=this.newEdge(null);return this.graphManager.add(d,T,l.target),this.edgeToDummyNodes.set(l,E),l.isInterGraph()?this.graphManager.remove(l):m.remove(l),E},c.prototype.createBendpointsFromDummyNodes=function(){var l=[];l=l.concat(this.graphManager.getAllEdges()),l=[].concat(r(this.edgeToDummyNodes.keys())).concat(l);for(var E=0;E<l.length;E++){var T=l[E];if(T.bendpoints.length>0){for(var m=this.edgeToDummyNodes.get(T),L=0;L<m.length;L++){var O=m[L],d=new a(O.getCenterX(),O.getCenterY()),N=T.bendpoints.get(L);N.x=d.x,N.y=d.y,O.getOwner().remove(O)}this.graphManager.add(T,T.source,T.target)}}},c.transform=function(l,E,T,m){if(T!=null&&m!=null){var L=E;if(l<=50){var O=E/T;L-=(E-O)/50*(50-l)}else{var d=E*m;L+=(d-E)/50*(l-50)}return L}else{var N,s;return l<=50?(N=9*E/500,s=E/10):(N=9*E/50,s=-8*E),N*l+s}},c.findCenterOfTree=function(l){var E=[];E=E.concat(l);var T=[],m=new Map,L=!1,O=null;(E.length==1||E.length==2)&&(L=!0,O=E[0]);for(var d=0;d<E.length;d++){var N=E[d],s=N.getNeighborsList().size;m.set(N,N.getNeighborsList().size),s==1&&T.push(N)}var h=[];for(h=h.concat(T);!L;){var f=[];f=f.concat(h),h=[];for(var d=0;d<E.length;d++){var N=E[d],p=E.indexOf(N);p>=0&&E.splice(p,1);var A=N.getNeighborsList();A.forEach(function(x){if(T.indexOf(x)<0){var G=m.get(x),U=G-1;U==1&&h.push(x),m.set(x,U)}})}T=T.concat(h),(E.length==1||E.length==2)&&(L=!0,O=E[0])}return O},c.prototype.setGraphManager=function(l){this.graphManager=l},u.exports=c},function(u,D,y){function r(){}r.seed=1,r.x=0,r.nextDouble=function(){return r.x=Math.sin(r.seed++)*1e4,r.x-Math.floor(r.x)},u.exports=r},function(u,D,y){var r=y(4);function t(e,i){this.lworldOrgX=0,this.lworldOrgY=0,this.ldeviceOrgX=0,this.ldeviceOrgY=0,this.lworldExtX=1,this.lworldExtY=1,this.ldeviceExtX=1,this.ldeviceExtY=1}t.prototype.getWorldOrgX=function(){return this.lworldOrgX},t.prototype.setWorldOrgX=function(e){this.lworldOrgX=e},t.prototype.getWorldOrgY=function(){return this.lworldOrgY},t.prototype.setWorldOrgY=function(e){this.lworldOrgY=e},t.prototype.getWorldExtX=function(){return this.lworldExtX},t.prototype.setWorldExtX=function(e){this.lworldExtX=e},t.prototype.getWorldExtY=function(){return this.lworldExtY},t.prototype.setWorldExtY=function(e){this.lworldExtY=e},t.prototype.getDeviceOrgX=function(){return this.ldeviceOrgX},t.prototype.setDeviceOrgX=function(e){this.ldeviceOrgX=e},t.prototype.getDeviceOrgY=function(){return this.ldeviceOrgY},t.prototype.setDeviceOrgY=function(e){this.ldeviceOrgY=e},t.prototype.getDeviceExtX=function(){return this.ldeviceExtX},t.prototype.setDeviceExtX=function(e){this.ldeviceExtX=e},t.prototype.getDeviceExtY=function(){return this.ldeviceExtY},t.prototype.setDeviceExtY=function(e){this.ldeviceExtY=e},t.prototype.transformX=function(e){var i=0,o=this.lworldExtX;return o!=0&&(i=this.ldeviceOrgX+(e-this.lworldOrgX)*this.ldeviceExtX/o),i},t.prototype.transformY=function(e){var i=0,o=this.lworldExtY;return o!=0&&(i=this.ldeviceOrgY+(e-this.lworldOrgY)*this.ldeviceExtY/o),i},t.prototype.inverseTransformX=function(e){var i=0,o=this.ldeviceExtX;return o!=0&&(i=this.lworldOrgX+(e-this.ldeviceOrgX)*this.lworldExtX/o),i},t.prototype.inverseTransformY=function(e){var i=0,o=this.ldeviceExtY;return o!=0&&(i=this.lworldOrgY+(e-this.ldeviceOrgY)*this.lworldExtY/o),i},t.prototype.inverseTransformPoint=function(e){var i=new r(this.inverseTransformX(e.x),this.inverseTransformY(e.y));return i},u.exports=t},function(u,D,y){function r(n){if(Array.isArray(n)){for(var c=0,l=Array(n.length);c<n.length;c++)l[c]=n[c];return l}else return Array.from(n)}var t=y(15),e=y(7),i=y(0),o=y(8),g=y(9);function a(){t.call(this),this.useSmartIdealEdgeLengthCalculation=e.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION,this.idealEdgeLength=e.DEFAULT_EDGE_LENGTH,this.springConstant=e.DEFAULT_SPRING_STRENGTH,this.repulsionConstant=e.DEFAULT_REPULSION_STRENGTH,this.gravityConstant=e.DEFAULT_GRAVITY_STRENGTH,this.compoundGravityConstant=e.DEFAULT_COMPOUND_GRAVITY_STRENGTH,this.gravityRangeFactor=e.DEFAULT_GRAVITY_RANGE_FACTOR,this.compoundGravityRangeFactor=e.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR,this.displacementThresholdPerNode=3*e.DEFAULT_EDGE_LENGTH/100,this.coolingFactor=e.DEFAULT_COOLING_FACTOR_INCREMENTAL,this.initialCoolingFactor=e.DEFAULT_COOLING_FACTOR_INCREMENTAL,this.totalDisplacement=0,this.oldTotalDisplacement=0,this.maxIterations=e.MAX_ITERATIONS}a.prototype=Object.create(t.prototype);for(var v in t)a[v]=t[v];a.prototype.initParameters=function(){t.prototype.initParameters.call(this,arguments),this.totalIterations=0,this.notAnimatedIterations=0,this.useFRGridVariant=e.DEFAULT_USE_SMART_REPULSION_RANGE_CALCULATION,this.grid=[]},a.prototype.calcIdealEdgeLengths=function(){for(var n,c,l,E,T,m,L=this.getGraphManager().getAllEdges(),O=0;O<L.length;O++)n=L[O],n.idealLength=this.idealEdgeLength,n.isInterGraph&&(l=n.getSource(),E=n.getTarget(),T=n.getSourceInLca().getEstimatedSize(),m=n.getTargetInLca().getEstimatedSize(),this.useSmartIdealEdgeLengthCalculation&&(n.idealLength+=T+m-2*i.SIMPLE_NODE_SIZE),c=n.getLca().getInclusionTreeDepth(),n.idealLength+=e.DEFAULT_EDGE_LENGTH*e.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR*(l.getInclusionTreeDepth()+E.getInclusionTreeDepth()-2*c))},a.prototype.initSpringEmbedder=function(){var n=this.getAllNodes().length;this.incremental?(n>e.ADAPTATION_LOWER_NODE_LIMIT&&(this.coolingFactor=Math.max(this.coolingFactor*e.COOLING_ADAPTATION_FACTOR,this.coolingFactor-(n-e.ADAPTATION_LOWER_NODE_LIMIT)/(e.ADAPTATION_UPPER_NODE_LIMIT-e.ADAPTATION_LOWER_NODE_LIMIT)*this.coolingFactor*(1-e.COOLING_ADAPTATION_FACTOR))),this.maxNodeDisplacement=e.MAX_NODE_DISPLACEMENT_INCREMENTAL):(n>e.ADAPTATION_LOWER_NODE_LIMIT?this.coolingFactor=Math.max(e.COOLING_ADAPTATION_FACTOR,1-(n-e.ADAPTATION_LOWER_NODE_LIMIT)/(e.ADAPTATION_UPPER_NODE_LIMIT-e.ADAPTATION_LOWER_NODE_LIMIT)*(1-e.COOLING_ADAPTATION_FACTOR)):this.coolingFactor=1,this.initialCoolingFactor=this.coolingFactor,this.maxNodeDisplacement=e.MAX_NODE_DISPLACEMENT),this.maxIterations=Math.max(this.getAllNodes().length*5,this.maxIterations),this.totalDisplacementThreshold=this.displacementThresholdPerNode*this.getAllNodes().length,this.repulsionRange=this.calcRepulsionRange()},a.prototype.calcSpringForces=function(){for(var n=this.getAllEdges(),c,l=0;l<n.length;l++)c=n[l],this.calcSpringForce(c,c.idealLength)},a.prototype.calcRepulsionForces=function(){var n=arguments.length>0&&arguments[0]!==void 0?arguments[0]:!0,c=arguments.length>1&&arguments[1]!==void 0?arguments[1]:!1,l,E,T,m,L=this.getAllNodes(),O;if(this.useFRGridVariant)for(this.totalIterations%e.GRID_CALCULATION_CHECK_PERIOD==1&&n&&this.updateGrid(),O=new Set,l=0;l<L.length;l++)T=L[l],this.calculateRepulsionForceOfANode(T,O,n,c),O.add(T);else for(l=0;l<L.length;l++)for(T=L[l],E=l+1;E<L.length;E++)m=L[E],T.getOwner()==m.getOwner()&&this.calcRepulsionForce(T,m)},a.prototype.calcGravitationalForces=function(){for(var n,c=this.getAllNodesToApplyGravitation(),l=0;l<c.length;l++)n=c[l],this.calcGravitationalForce(n)},a.prototype.moveNodes=function(){for(var n=this.getAllNodes(),c,l=0;l<n.length;l++)c=n[l],c.move()},a.prototype.calcSpringForce=function(n,c){var l=n.getSource(),E=n.getTarget(),T,m,L,O;if(this.uniformLeafNodeSizes&&l.getChild()==null&&E.getChild()==null)n.updateLengthSimple();else if(n.updateLength(),n.isOverlapingSourceAndTarget)return;T=n.getLength(),T!=0&&(m=this.springConstant*(T-c),L=m*(n.lengthX/T),O=m*(n.lengthY/T),l.springForceX+=L,l.springForceY+=O,E.springForceX-=L,E.springForceY-=O)},a.prototype.calcRepulsionForce=function(n,c){var l=n.getRect(),E=c.getRect(),T=new Array(2),m=new Array(4),L,O,d,N,s,h,f;if(l.intersects(E)){o.calcSeparationAmount(l,E,T,e.DEFAULT_EDGE_LENGTH/2),h=2*T[0],f=2*T[1];var p=n.noOfChildren*c.noOfChildren/(n.noOfChildren+c.noOfChildren);n.repulsionForceX-=p*h,n.repulsionForceY-=p*f,c.repulsionForceX+=p*h,c.repulsionForceY+=p*f}else this.uniformLeafNodeSizes&&n.getChild()==null&&c.getChild()==null?(L=E.getCenterX()-l.getCenterX(),O=E.getCenterY()-l.getCenterY()):(o.getIntersection(l,E,m),L=m[2]-m[0],O=m[3]-m[1]),Math.abs(L)<e.MIN_REPULSION_DIST&&(L=g.sign(L)*e.MIN_REPULSION_DIST),Math.abs(O)<e.MIN_REPULSION_DIST&&(O=g.sign(O)*e.MIN_REPULSION_DIST),d=L*L+O*O,N=Math.sqrt(d),s=this.repulsionConstant*n.noOfChildren*c.noOfChildren/d,h=s*L/N,f=s*O/N,n.repulsionForceX-=h,n.repulsionForceY-=f,c.repulsionForceX+=h,c.repulsionForceY+=f},a.prototype.calcGravitationalForce=function(n){var c,l,E,T,m,L,O,d;c=n.getOwner(),l=(c.getRight()+c.getLeft())/2,E=(c.getTop()+c.getBottom())/2,T=n.getCenterX()-l,m=n.getCenterY()-E,L=Math.abs(T)+n.getWidth()/2,O=Math.abs(m)+n.getHeight()/2,n.getOwner()==this.graphManager.getRoot()?(d=c.getEstimatedSize()*this.gravityRangeFactor,(L>d||O>d)&&(n.gravitationForceX=-this.gravityConstant*T,n.gravitationForceY=-this.gravityConstant*m)):(d=c.getEstimatedSize()*this.compoundGravityRangeFactor,(L>d||O>d)&&(n.gravitationForceX=-this.gravityConstant*T*this.compoundGravityConstant,n.gravitationForceY=-this.gravityConstant*m*this.compoundGravityConstant))},a.prototype.isConverged=function(){var n,c=!1;return this.totalIterations>this.maxIterations/3&&(c=Math.abs(this.totalDisplacement-this.oldTotalDisplacement)<2),n=this.totalDisplacement<this.totalDisplacementThreshold,this.oldTotalDisplacement=this.totalDisplacement,n||c},a.prototype.animate=function(){this.animationDuringLayout&&!this.isSubLayout&&(this.notAnimatedIterations==this.animationPeriod?(this.update(),this.notAnimatedIterations=0):this.notAnimatedIterations++)},a.prototype.calcNoOfChildrenForAllNodes=function(){for(var n,c=this.graphManager.getAllNodes(),l=0;l<c.length;l++)n=c[l],n.noOfChildren=n.getNoOfChildren()},a.prototype.calcGrid=function(n){var c=0,l=0;c=parseInt(Math.ceil((n.getRight()-n.getLeft())/this.repulsionRange)),l=parseInt(Math.ceil((n.getBottom()-n.getTop())/this.repulsionRange));for(var E=new Array(c),T=0;T<c;T++)E[T]=new Array(l);for(var T=0;T<c;T++)for(var m=0;m<l;m++)E[T][m]=new Array;return E},a.prototype.addNodeToGrid=function(n,c,l){var E=0,T=0,m=0,L=0;E=parseInt(Math.floor((n.getRect().x-c)/this.repulsionRange)),T=parseInt(Math.floor((n.getRect().width+n.getRect().x-c)/this.repulsionRange)),m=parseInt(Math.floor((n.getRect().y-l)/this.repulsionRange)),L=parseInt(Math.floor((n.getRect().height+n.getRect().y-l)/this.repulsionRange));for(var O=E;O<=T;O++)for(var d=m;d<=L;d++)this.grid[O][d].push(n),n.setGridCoordinates(E,T,m,L)},a.prototype.updateGrid=function(){var n,c,l=this.getAllNodes();for(this.grid=this.calcGrid(this.graphManager.getRoot()),n=0;n<l.length;n++)c=l[n],this.addNodeToGrid(c,this.graphManager.getRoot().getLeft(),this.graphManager.getRoot().getTop())},a.prototype.calculateRepulsionForceOfANode=function(n,c,l,E){if(this.totalIterations%e.GRID_CALCULATION_CHECK_PERIOD==1&&l||E){var T=new Set;n.surrounding=new Array;for(var m,L=this.grid,O=n.startX-1;O<n.finishX+2;O++)for(var d=n.startY-1;d<n.finishY+2;d++)if(!(O<0||d<0||O>=L.length||d>=L[0].length)){for(var N=0;N<L[O][d].length;N++)if(m=L[O][d][N],!(n.getOwner()!=m.getOwner()||n==m)&&!c.has(m)&&!T.has(m)){var s=Math.abs(n.getCenterX()-m.getCenterX())-(n.getWidth()/2+m.getWidth()/2),h=Math.abs(n.getCenterY()-m.getCenterY())-(n.getHeight()/2+m.getHeight()/2);s<=this.repulsionRange&&h<=this.repulsionRange&&T.add(m)}}n.surrounding=[].concat(r(T))}for(O=0;O<n.surrounding.length;O++)this.calcRepulsionForce(n,n.surrounding[O])},a.prototype.calcRepulsionRange=function(){return 0},u.exports=a},function(u,D,y){var r=y(1),t=y(7);function e(o,g,a){r.call(this,o,g,a),this.idealLength=t.DEFAULT_EDGE_LENGTH}e.prototype=Object.create(r.prototype);for(var i in r)e[i]=r[i];u.exports=e},function(u,D,y){var r=y(3);function t(i,o,g,a){r.call(this,i,o,g,a),this.springForceX=0,this.springForceY=0,this.repulsionForceX=0,this.repulsionForceY=0,this.gravitationForceX=0,this.gravitationForceY=0,this.displacementX=0,this.displacementY=0,this.startX=0,this.finishX=0,this.startY=0,this.finishY=0,this.surrounding=[]}t.prototype=Object.create(r.prototype);for(var e in r)t[e]=r[e];t.prototype.setGridCoordinates=function(i,o,g,a){this.startX=i,this.finishX=o,this.startY=g,this.finishY=a},u.exports=t},function(u,D,y){function r(t,e){this.width=0,this.height=0,t!==null&&e!==null&&(this.height=e,this.width=t)}r.prototype.getWidth=function(){return this.width},r.prototype.setWidth=function(t){this.width=t},r.prototype.getHeight=function(){return this.height},r.prototype.setHeight=function(t){this.height=t},u.exports=r},function(u,D,y){var r=y(14);function t(){this.map={},this.keys=[]}t.prototype.put=function(e,i){var 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r=function(){function o(g,a){for(var v=0;v<a.length;v++){var n=a[v];n.enumerable=n.enumerable||!1,n.configurable=!0,"value"in n&&(n.writable=!0),Object.defineProperty(g,n.key,n)}}return function(g,a,v){return a&&o(g.prototype,a),v&&o(g,v),g}}();function t(o,g){if(!(o instanceof g))throw new TypeError("Cannot call a class as a function")}var e=y(11),i=function(){function o(g,a){t(this,o),(a!==null||a!==void 0)&&(this.compareFunction=this._defaultCompareFunction);var v=void 0;g instanceof e?v=g.size():v=g.length,this._quicksort(g,0,v-1)}return r(o,[{key:"_quicksort",value:function(a,v,n){if(v<n){var c=this._partition(a,v,n);this._quicksort(a,v,c),this._quicksort(a,c+1,n)}}},{key:"_partition",value:function(a,v,n){for(var c=this._get(a,v),l=v,E=n;;){for(;this.compareFunction(c,this._get(a,E));)E--;for(;this.compareFunction(this._get(a,l),c);)l++;if(l<E)this._swap(a,l,E),l++,E--;else return E}}},{key:"_get",value:function(a,v){return a instanceof e?a.get_object_at(v):a[v]}},{key:"_set",value:function(a,v,n){a instanceof e?a.set_object_at(v,n):a[v]=n}},{key:"_swap",value:function(a,v,n){var c=this._get(a,v);this._set(a,v,this._get(a,n)),this._set(a,n,c)}},{key:"_defaultCompareFunction",value:function(a,v){return v>a}}]),o}();u.exports=i},function(u,D,y){var r=function(){function i(o,g){for(var a=0;a<g.length;a++){var v=g[a];v.enumerable=v.enumerable||!1,v.configurable=!0,"value"in v&&(v.writable=!0),Object.defineProperty(o,v.key,v)}}return function(o,g,a){return g&&i(o.prototype,g),a&&i(o,a),o}}();function t(i,o){if(!(i instanceof o))throw new TypeError("Cannot call a class as a function")}var e=function(){function i(o,g){var a=arguments.length>2&&arguments[2]!==void 0?arguments[2]:1,v=arguments.length>3&&arguments[3]!==void 0?arguments[3]:-1,n=arguments.length>4&&arguments[4]!==void 0?arguments[4]:-1;t(this,i),this.sequence1=o,this.sequence2=g,this.match_score=a,this.mismatch_penalty=v,this.gap_penalty=n,this.iMax=o.length+1,this.jMax=g.length+1,this.grid=new Array(this.iMax);for(var c=0;c<this.iMax;c++){this.grid[c]=new Array(this.jMax);for(var l=0;l<this.jMax;l++)this.grid[c][l]=0}this.tracebackGrid=new Array(this.iMax);for(var E=0;E<this.iMax;E++){this.tracebackGrid[E]=new Array(this.jMax);for(var T=0;T<this.jMax;T++)this.tracebackGrid[E][T]=[null,null,null]}this.alignments=[],this.score=-1,this.computeGrids()}return r(i,[{key:"getScore",value:function(){return this.score}},{key:"getAlignments",value:function(){return this.alignments}},{key:"computeGrids",value:function(){for(var g=1;g<this.jMax;g++)this.grid[0][g]=this.grid[0][g-1]+this.gap_penalty,this.tracebackGrid[0][g]=[!1,!1,!0];for(var a=1;a<this.iMax;a++)this.grid[a][0]=this.grid[a-1][0]+this.gap_penalty,this.tracebackGrid[a][0]=[!1,!0,!1];for(var v=1;v<this.iMax;v++)for(var n=1;n<this.jMax;n++){var c=void 0;this.sequence1[v-1]===this.sequence2[n-1]?c=this.grid[v-1][n-1]+this.match_score:c=this.grid[v-1][n-1]+this.mismatch_penalty;var l=this.grid[v-1][n]+this.gap_penalty,E=this.grid[v][n-1]+this.gap_penalty,T=[c,l,E],m=this.arrayAllMaxIndexes(T);this.grid[v][n]=T[m[0]],this.tracebackGrid[v][n]=[m.includes(0),m.includes(1),m.includes(2)]}this.score=this.grid[this.iMax-1][this.jMax-1]}},{key:"alignmentTraceback",value:function(){var g=[];for(g.push({pos:[this.sequence1.length,this.sequence2.length],seq1:"",seq2:""});g[0];){var a=g[0],v=this.tracebackGrid[a.pos[0]][a.pos[1]];v[0]&&g.push({pos:[a.pos[0]-1,a.pos[1]-1],seq1:this.sequence1[a.pos[0]-1]+a.seq1,seq2:this.sequence2[a.pos[1]-1]+a.seq2}),v[1]&&g.push({pos:[a.pos[0]-1,a.pos[1]],seq1:this.sequence1[a.pos[0]-1]+a.seq1,seq2:"-"+a.seq2}),v[2]&&g.push({pos:[a.pos[0],a.pos[1]-1],seq1:"-"+a.seq1,seq2:this.sequence2[a.pos[1]-1]+a.seq2}),a.pos[0]===0&&a.pos[1]===0&&this.alignments.push({sequence1:a.seq1,sequence2:a.seq2}),g.shift()}return this.alignments}},{key:"getAllIndexes",value:function(g,a){for(var v=[],n=-1;(n=g.indexOf(a,n+1))!==-1;)v.push(n);return v}},{key:"arrayAllMaxIndexes",value:function(g){return this.getAllIndexes(g,Math.max.apply(null,g))}}]),i}();u.exports=e},function(u,D,y){var r=function(){};r.FDLayout=y(18),r.FDLayoutConstants=y(7),r.FDLayoutEdge=y(19),r.FDLayoutNode=y(20),r.DimensionD=y(21),r.HashMap=y(22),r.HashSet=y(23),r.IGeometry=y(8),r.IMath=y(9),r.Integer=y(10),r.Point=y(12),r.PointD=y(4),r.RandomSeed=y(16),r.RectangleD=y(13),r.Transform=y(17),r.UniqueIDGeneretor=y(14),r.Quicksort=y(24),r.LinkedList=y(11),r.LGraphObject=y(2),r.LGraph=y(5),r.LEdge=y(1),r.LGraphManager=y(6),r.LNode=y(3),r.Layout=y(15),r.LayoutConstants=y(0),r.NeedlemanWunsch=y(25),u.exports=r},function(u,D,y){function r(){this.listeners=[]}var t=r.prototype;t.addListener=function(e,i){this.listeners.push({event:e,callback:i})},t.removeListener=function(e,i){for(var o=this.listeners.length;o>=0;o--){var g=this.listeners[o];g.event===e&&g.callback===i&&this.listeners.splice(o,1)}},t.emit=function(e,i){for(var o=0;o<this.listeners.length;o++){var g=this.listeners[o];e===g.event&&g.callback(i)}},u.exports=r}])})}(rt)),rt.exports}var xt=et.exports,gt;function Mt(){return gt||(gt=1,function(C,M){(function(D,y){C.exports=y(Rt())})(xt,function(u){return function(D){var y={};function r(t){if(y[t])return y[t].exports;var e=y[t]={i:t,l:!1,exports:{}};return D[t].call(e.exports,e,e.exports,r),e.l=!0,e.exports}return r.m=D,r.c=y,r.i=function(t){return t},r.d=function(t,e,i){r.o(t,e)||Object.defineProperty(t,e,{configurable:!1,enumerable:!0,get:i})},r.n=function(t){var e=t&&t.__esModule?function(){return t.default}:function(){return t};return r.d(e,"a",e),e},r.o=function(t,e){return Object.prototype.hasOwnProperty.call(t,e)},r.p="",r(r.s=7)}([function(D,y){D.exports=u},function(D,y,r){var t=r(0).FDLayoutConstants;function e(){}for(var i in t)e[i]=t[i];e.DEFAULT_USE_MULTI_LEVEL_SCALING=!1,e.DEFAULT_RADIAL_SEPARATION=t.DEFAULT_EDGE_LENGTH,e.DEFAULT_COMPONENT_SEPERATION=60,e.TILE=!0,e.TILING_PADDING_VERTICAL=10,e.TILING_PADDING_HORIZONTAL=10,e.TREE_REDUCTION_ON_INCREMENTAL=!1,D.exports=e},function(D,y,r){var t=r(0).FDLayoutEdge;function e(o,g,a){t.call(this,o,g,a)}e.prototype=Object.create(t.prototype);for(var i in t)e[i]=t[i];D.exports=e},function(D,y,r){var t=r(0).LGraph;function e(o,g,a){t.call(this,o,g,a)}e.prototype=Object.create(t.prototype);for(var i in t)e[i]=t[i];D.exports=e},function(D,y,r){var t=r(0).LGraphManager;function e(o){t.call(this,o)}e.prototype=Object.create(t.prototype);for(var i in t)e[i]=t[i];D.exports=e},function(D,y,r){var t=r(0).FDLayoutNode,e=r(0).IMath;function i(g,a,v,n){t.call(this,g,a,v,n)}i.prototype=Object.create(t.prototype);for(var o in t)i[o]=t[o];i.prototype.move=function(){var g=this.graphManager.getLayout();this.displacementX=g.coolingFactor*(this.springForceX+this.repulsionForceX+this.gravitationForceX)/this.noOfChildren,this.displacementY=g.coolingFactor*(this.springForceY+this.repulsionForceY+this.gravitationForceY)/this.noOfChildren,Math.abs(this.displacementX)>g.coolingFactor*g.maxNodeDisplacement&&(this.displacementX=g.coolingFactor*g.maxNodeDisplacement*e.sign(this.displacementX)),Math.abs(this.displacementY)>g.coolingFactor*g.maxNodeDisplacement&&(this.displacementY=g.coolingFactor*g.maxNodeDisplacement*e.sign(this.displacementY)),this.child==null?this.moveBy(this.displacementX,this.displacementY):this.child.getNodes().length==0?this.moveBy(this.displacementX,this.displacementY):this.propogateDisplacementToChildren(this.displacementX,this.displacementY),g.totalDisplacement+=Math.abs(this.displacementX)+Math.abs(this.displacementY),this.springForceX=0,this.springForceY=0,this.repulsionForceX=0,this.repulsionForceY=0,this.gravitationForceX=0,this.gravitationForceY=0,this.displacementX=0,this.displacementY=0},i.prototype.propogateDisplacementToChildren=function(g,a){for(var v=this.getChild().getNodes(),n,c=0;c<v.length;c++)n=v[c],n.getChild()==null?(n.moveBy(g,a),n.displacementX+=g,n.displacementY+=a):n.propogateDisplacementToChildren(g,a)},i.prototype.setPred1=function(g){this.pred1=g},i.prototype.getPred1=function(){return pred1},i.prototype.getPred2=function(){return pred2},i.prototype.setNext=function(g){this.next=g},i.prototype.getNext=function(){return next},i.prototype.setProcessed=function(g){this.processed=g},i.prototype.isProcessed=function(){return processed},D.exports=i},function(D,y,r){var t=r(0).FDLayout,e=r(4),i=r(3),o=r(5),g=r(2),a=r(1),v=r(0).FDLayoutConstants,n=r(0).LayoutConstants,c=r(0).Point,l=r(0).PointD,E=r(0).Layout,T=r(0).Integer,m=r(0).IGeometry,L=r(0).LGraph,O=r(0).Transform;function d(){t.call(this),this.toBeTiled={}}d.prototype=Object.create(t.prototype);for(var N in t)d[N]=t[N];d.prototype.newGraphManager=function(){var s=new e(this);return this.graphManager=s,s},d.prototype.newGraph=function(s){return new i(null,this.graphManager,s)},d.prototype.newNode=function(s){return new o(this.graphManager,s)},d.prototype.newEdge=function(s){return new g(null,null,s)},d.prototype.initParameters=function(){t.prototype.initParameters.call(this,arguments),this.isSubLayout||(a.DEFAULT_EDGE_LENGTH<10?this.idealEdgeLength=10:this.idealEdgeLength=a.DEFAULT_EDGE_LENGTH,this.useSmartIdealEdgeLengthCalculation=a.DEFAULT_USE_SMART_IDEAL_EDGE_LENGTH_CALCULATION,this.springConstant=v.DEFAULT_SPRING_STRENGTH,this.repulsionConstant=v.DEFAULT_REPULSION_STRENGTH,this.gravityConstant=v.DEFAULT_GRAVITY_STRENGTH,this.compoundGravityConstant=v.DEFAULT_COMPOUND_GRAVITY_STRENGTH,this.gravityRangeFactor=v.DEFAULT_GRAVITY_RANGE_FACTOR,this.compoundGravityRangeFactor=v.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR,this.prunedNodesAll=[],this.growTreeIterations=0,this.afterGrowthIterations=0,this.isTreeGrowing=!1,this.isGrowthFinished=!1,this.coolingCycle=0,this.maxCoolingCycle=this.maxIterations/v.CONVERGENCE_CHECK_PERIOD,this.finalTemperature=v.CONVERGENCE_CHECK_PERIOD/this.maxIterations,this.coolingAdjuster=1)},d.prototype.layout=function(){var s=n.DEFAULT_CREATE_BENDS_AS_NEEDED;return s&&(this.createBendpoints(),this.graphManager.resetAllEdges()),this.level=0,this.classicLayout()},d.prototype.classicLayout=function(){if(this.nodesWithGravity=this.calculateNodesToApplyGravitationTo(),this.graphManager.setAllNodesToApplyGravitation(this.nodesWithGravity),this.calcNoOfChildrenForAllNodes(),this.graphManager.calcLowestCommonAncestors(),this.graphManager.calcInclusionTreeDepths(),this.graphManager.getRoot().calcEstimatedSize(),this.calcIdealEdgeLengths(),this.incremental){if(a.TREE_REDUCTION_ON_INCREMENTAL){this.reduceTrees(),this.graphManager.resetAllNodesToApplyGravitation();var h=new Set(this.getAllNodes()),f=this.nodesWithGravity.filter(function(I){return h.has(I)});this.graphManager.setAllNodesToApplyGravitation(f)}}else{var s=this.getFlatForest();if(s.length>0)this.positionNodesRadially(s);else{this.reduceTrees(),this.graphManager.resetAllNodesToApplyGravitation();var h=new Set(this.getAllNodes()),f=this.nodesWithGravity.filter(function(p){return h.has(p)});this.graphManager.setAllNodesToApplyGravitation(f),this.positionNodesRandomly()}}return this.initSpringEmbedder(),this.runSpringEmbedder(),!0},d.prototype.tick=function(){if(this.totalIterations++,this.totalIterations===this.maxIterations&&!this.isTreeGrowing&&!this.isGrowthFinished)if(this.prunedNodesAll.length>0)this.isTreeGrowing=!0;else return!0;if(this.totalIterations%v.CONVERGENCE_CHECK_PERIOD==0&&!this.isTreeGrowing&&!this.isGrowthFinished){if(this.isConverged())if(this.prunedNodesAll.length>0)this.isTreeGrowing=!0;else return!0;this.coolingCycle++,this.layoutQuality==0?this.coolingAdjuster=this.coolingCycle:this.layoutQuality==1&&(this.coolingAdjuster=this.coolingCycle/3),this.coolingFactor=Math.max(this.initialCoolingFactor-Math.pow(this.coolingCycle,Math.log(100*(this.initialCoolingFactor-this.finalTemperature))/Math.log(this.maxCoolingCycle))/100*this.coolingAdjuster,this.finalTemperature),this.animationPeriod=Math.ceil(this.initialAnimationPeriod*Math.sqrt(this.coolingFactor))}if(this.isTreeGrowing){if(this.growTreeIterations%10==0)if(this.prunedNodesAll.length>0){this.graphManager.updateBounds(),this.updateGrid(),this.growTree(this.prunedNodesAll),this.graphManager.resetAllNodesToApplyGravitation();var s=new Set(this.getAllNodes()),h=this.nodesWithGravity.filter(function(A){return s.has(A)});this.graphManager.setAllNodesToApplyGravitation(h),this.graphManager.updateBounds(),this.updateGrid(),this.coolingFactor=v.DEFAULT_COOLING_FACTOR_INCREMENTAL}else this.isTreeGrowing=!1,this.isGrowthFinished=!0;this.growTreeIterations++}if(this.isGrowthFinished){if(this.isConverged())return!0;this.afterGrowthIterations%10==0&&(this.graphManager.updateBounds(),this.updateGrid()),this.coolingFactor=v.DEFAULT_COOLING_FACTOR_INCREMENTAL*((100-this.afterGrowthIterations)/100),this.afterGrowthIterations++}var f=!this.isTreeGrowing&&!this.isGrowthFinished,p=this.growTreeIterations%10==1&&this.isTreeGrowing||this.afterGrowthIterations%10==1&&this.isGrowthFinished;return this.totalDisplacement=0,this.graphManager.updateBounds(),this.calcSpringForces(),this.calcRepulsionForces(f,p),this.calcGravitationalForces(),this.moveNodes(),this.animate(),!1},d.prototype.getPositionsData=function(){for(var s=this.graphManager.getAllNodes(),h={},f=0;f<s.length;f++){var p=s[f].rect,A=s[f].id;h[A]={id:A,x:p.getCenterX(),y:p.getCenterY(),w:p.width,h:p.height}}return h},d.prototype.runSpringEmbedder=function(){this.initialAnimationPeriod=25,this.animationPeriod=this.initialAnimationPeriod;var s=!1;if(v.ANIMATE==="during")this.emit("layoutstarted");else{for(;!s;)s=this.tick();this.graphManager.updateBounds()}},d.prototype.calculateNodesToApplyGravitationTo=function(){var s=[],h,f=this.graphManager.getGraphs(),p=f.length,A;for(A=0;A<p;A++)h=f[A],h.updateConnected(),h.isConnected||(s=s.concat(h.getNodes()));return s},d.prototype.createBendpoints=function(){var s=[];s=s.concat(this.graphManager.getAllEdges());var h=new Set,f;for(f=0;f<s.length;f++){var p=s[f];if(!h.has(p)){var A=p.getSource(),I=p.getTarget();if(A==I)p.getBendpoints().push(new l),p.getBendpoints().push(new l),this.createDummyNodesForBendpoints(p),h.add(p);else{var R=[];if(R=R.concat(A.getEdgeListToNode(I)),R=R.concat(I.getEdgeListToNode(A)),!h.has(R[0])){if(R.length>1){var x;for(x=0;x<R.length;x++){var G=R[x];G.getBendpoints().push(new l),this.createDummyNodesForBendpoints(G)}}R.forEach(function(U){h.add(U)})}}}if(h.size==s.length)break}},d.prototype.positionNodesRadially=function(s){for(var h=new c(0,0),f=Math.ceil(Math.sqrt(s.length)),p=0,A=0,I=0,R=new l(0,0),x=0;x<s.length;x++){x%f==0&&(I=0,A=p,x!=0&&(A+=a.DEFAULT_COMPONENT_SEPERATION),p=0);var G=s[x],U=E.findCenterOfTree(G);h.x=I,h.y=A,R=d.radialLayout(G,U,h),R.y>p&&(p=Math.floor(R.y)),I=Math.floor(R.x+a.DEFAULT_COMPONENT_SEPERATION)}this.transform(new l(n.WORLD_CENTER_X-R.x/2,n.WORLD_CENTER_Y-R.y/2))},d.radialLayout=function(s,h,f){var p=Math.max(this.maxDiagonalInTree(s),a.DEFAULT_RADIAL_SEPARATION);d.branchRadialLayout(h,null,0,359,0,p);var A=L.calculateBounds(s),I=new O;I.setDeviceOrgX(A.getMinX()),I.setDeviceOrgY(A.getMinY()),I.setWorldOrgX(f.x),I.setWorldOrgY(f.y);for(var R=0;R<s.length;R++){var x=s[R];x.transform(I)}var G=new l(A.getMaxX(),A.getMaxY());return I.inverseTransformPoint(G)},d.branchRadialLayout=function(s,h,f,p,A,I){var R=(p-f+1)/2;R<0&&(R+=180);var x=(R+f)%360,G=x*m.TWO_PI/360,U=A*Math.cos(G),X=A*Math.sin(G);s.setCenter(U,X);var w=[];w=w.concat(s.getEdges());var S=w.length;h!=null&&S--;for(var F=0,b=w.length,Y,k=s.getEdgesBetween(h);k.length>1;){var H=k[0];k.splice(0,1);var P=w.indexOf(H);P>=0&&w.splice(P,1),b--,S--}h!=null?Y=(w.indexOf(k[0])+1)%b:Y=0;for(var B=Math.abs(p-f)/S,$=Y;F!=S;$=++$%b){var j=w[$].getOtherEnd(s);if(j!=h){var V=(f+F*B)%360,z=(V+B)%360;d.branchRadialLayout(j,s,V,z,A+I,I),F++}}},d.maxDiagonalInTree=function(s){for(var h=T.MIN_VALUE,f=0;f<s.length;f++){var p=s[f],A=p.getDiagonal();A>h&&(h=A)}return h},d.prototype.calcRepulsionRange=function(){return 2*(this.level+1)*this.idealEdgeLength},d.prototype.groupZeroDegreeMembers=function(){var s=this,h={};this.memberGroups={},this.idToDummyNode={};for(var f=[],p=this.graphManager.getAllNodes(),A=0;A<p.length;A++){var I=p[A],R=I.getParent();this.getNodeDegreeWithChildren(I)===0&&(R.id==null||!this.getToBeTiled(R))&&f.push(I)}for(var A=0;A<f.length;A++){var I=f[A],x=I.getParent().id;typeof h[x]>"u"&&(h[x]=[]),h[x]=h[x].concat(I)}Object.keys(h).forEach(function(G){if(h[G].length>1){var U="DummyCompound_"+G;s.memberGroups[U]=h[G];var X=h[G][0].getParent(),w=new o(s.graphManager);w.id=U,w.paddingLeft=X.paddingLeft||0,w.paddingRight=X.paddingRight||0,w.paddingBottom=X.paddingBottom||0,w.paddingTop=X.paddingTop||0,s.idToDummyNode[U]=w;var S=s.getGraphManager().add(s.newGraph(),w),F=X.getChild();F.add(w);for(var b=0;b<h[G].length;b++){var Y=h[G][b];F.remove(Y),S.add(Y)}}})},d.prototype.clearCompounds=function(){var s={},h={};this.performDFSOnCompounds();for(var f=0;f<this.compoundOrder.length;f++)h[this.compoundOrder[f].id]=this.compoundOrder[f],s[this.compoundOrder[f].id]=[].concat(this.compoundOrder[f].getChild().getNodes()),this.graphManager.remove(this.compoundOrder[f].getChild()),this.compoundOrder[f].child=null;this.graphManager.resetAllNodes(),this.tileCompoundMembers(s,h)},d.prototype.clearZeroDegreeMembers=function(){var s=this,h=this.tiledZeroDegreePack=[];Object.keys(this.memberGroups).forEach(function(f){var p=s.idToDummyNode[f];h[f]=s.tileNodes(s.memberGroups[f],p.paddingLeft+p.paddingRight),p.rect.width=h[f].width,p.rect.height=h[f].height})},d.prototype.repopulateCompounds=function(){for(var s=this.compoundOrder.length-1;s>=0;s--){var h=this.compoundOrder[s],f=h.id,p=h.paddingLeft,A=h.paddingTop;this.adjustLocations(this.tiledMemberPack[f],h.rect.x,h.rect.y,p,A)}},d.prototype.repopulateZeroDegreeMembers=function(){var s=this,h=this.tiledZeroDegreePack;Object.keys(h).forEach(function(f){var p=s.idToDummyNode[f],A=p.paddingLeft,I=p.paddingTop;s.adjustLocations(h[f],p.rect.x,p.rect.y,A,I)})},d.prototype.getToBeTiled=function(s){var h=s.id;if(this.toBeTiled[h]!=null)return this.toBeTiled[h];var f=s.getChild();if(f==null)return this.toBeTiled[h]=!1,!1;for(var p=f.getNodes(),A=0;A<p.length;A++){var I=p[A];if(this.getNodeDegree(I)>0)return this.toBeTiled[h]=!1,!1;if(I.getChild()==null){this.toBeTiled[I.id]=!1;continue}if(!this.getToBeTiled(I))return this.toBeTiled[h]=!1,!1}return this.toBeTiled[h]=!0,!0},d.prototype.getNodeDegree=function(s){s.id;for(var h=s.getEdges(),f=0,p=0;p<h.length;p++){var A=h[p];A.getSource().id!==A.getTarget().id&&(f=f+1)}return f},d.prototype.getNodeDegreeWithChildren=function(s){var h=this.getNodeDegree(s);if(s.getChild()==null)return h;for(var f=s.getChild().getNodes(),p=0;p<f.length;p++){var A=f[p];h+=this.getNodeDegreeWithChildren(A)}return h},d.prototype.performDFSOnCompounds=function(){this.compoundOrder=[],this.fillCompexOrderByDFS(this.graphManager.getRoot().getNodes())},d.prototype.fillCompexOrderByDFS=function(s){for(var h=0;h<s.length;h++){var f=s[h];f.getChild()!=null&&this.fillCompexOrderByDFS(f.getChild().getNodes()),this.getToBeTiled(f)&&this.compoundOrder.push(f)}},d.prototype.adjustLocations=function(s,h,f,p,A){h+=p,f+=A;for(var I=h,R=0;R<s.rows.length;R++){var x=s.rows[R];h=I;for(var G=0,U=0;U<x.length;U++){var X=x[U];X.rect.x=h,X.rect.y=f,h+=X.rect.width+s.horizontalPadding,X.rect.height>G&&(G=X.rect.height)}f+=G+s.verticalPadding}},d.prototype.tileCompoundMembers=function(s,h){var f=this;this.tiledMemberPack=[],Object.keys(s).forEach(function(p){var A=h[p];f.tiledMemberPack[p]=f.tileNodes(s[p],A.paddingLeft+A.paddingRight),A.rect.width=f.tiledMemberPack[p].width,A.rect.height=f.tiledMemberPack[p].height})},d.prototype.tileNodes=function(s,h){var f=a.TILING_PADDING_VERTICAL,p=a.TILING_PADDING_HORIZONTAL,A={rows:[],rowWidth:[],rowHeight:[],width:0,height:h,verticalPadding:f,horizontalPadding:p};s.sort(function(x,G){return x.rect.width*x.rect.height>G.rect.width*G.rect.height?-1:x.rect.width*x.rect.height<G.rect.width*G.rect.height?1:0});for(var I=0;I<s.length;I++){var R=s[I];A.rows.length==0?this.insertNodeToRow(A,R,0,h):this.canAddHorizontal(A,R.rect.width,R.rect.height)?this.insertNodeToRow(A,R,this.getShortestRowIndex(A),h):this.insertNodeToRow(A,R,A.rows.length,h),this.shiftToLastRow(A)}return A},d.prototype.insertNodeToRow=function(s,h,f,p){var A=p;if(f==s.rows.length){var I=[];s.rows.push(I),s.rowWidth.push(A),s.rowHeight.push(0)}var R=s.rowWidth[f]+h.rect.width;s.rows[f].length>0&&(R+=s.horizontalPadding),s.rowWidth[f]=R,s.width<R&&(s.width=R);var x=h.rect.height;f>0&&(x+=s.verticalPadding);var G=0;x>s.rowHeight[f]&&(G=s.rowHeight[f],s.rowHeight[f]=x,G=s.rowHeight[f]-G),s.height+=G,s.rows[f].push(h)},d.prototype.getShortestRowIndex=function(s){for(var h=-1,f=Number.MAX_VALUE,p=0;p<s.rows.length;p++)s.rowWidth[p]<f&&(h=p,f=s.rowWidth[p]);return h},d.prototype.getLongestRowIndex=function(s){for(var h=-1,f=Number.MIN_VALUE,p=0;p<s.rows.length;p++)s.rowWidth[p]>f&&(h=p,f=s.rowWidth[p]);return h},d.prototype.canAddHorizontal=function(s,h,f){var p=this.getShortestRowIndex(s);if(p<0)return!0;var A=s.rowWidth[p];if(A+s.horizontalPadding+h<=s.width)return!0;var I=0;s.rowHeight[p]<f&&p>0&&(I=f+s.verticalPadding-s.rowHeight[p]);var R;s.width-A>=h+s.horizontalPadding?R=(s.height+I)/(A+h+s.horizontalPadding):R=(s.height+I)/s.width,I=f+s.verticalPadding;var x;return s.width<h?x=(s.height+I)/h:x=(s.height+I)/s.width,x<1&&(x=1/x),R<1&&(R=1/R),R<x},d.prototype.shiftToLastRow=function(s){var h=this.getLongestRowIndex(s),f=s.rowWidth.length-1,p=s.rows[h],A=p[p.length-1],I=A.width+s.horizontalPadding;if(s.width-s.rowWidth[f]>I&&h!=f){p.splice(-1,1),s.rows[f].push(A),s.rowWidth[h]=s.rowWidth[h]-I,s.rowWidth[f]=s.rowWidth[f]+I,s.width=s.rowWidth[instance.getLongestRowIndex(s)];for(var R=Number.MIN_VALUE,x=0;x<p.length;x++)p[x].height>R&&(R=p[x].height);h>0&&(R+=s.verticalPadding);var G=s.rowHeight[h]+s.rowHeight[f];s.rowHeight[h]=R,s.rowHeight[f]<A.height+s.verticalPadding&&(s.rowHeight[f]=A.height+s.verticalPadding);var U=s.rowHeight[h]+s.rowHeight[f];s.height+=U-G,this.shiftToLastRow(s)}},d.prototype.tilingPreLayout=function(){a.TILE&&(this.groupZeroDegreeMembers(),this.clearCompounds(),this.clearZeroDegreeMembers())},d.prototype.tilingPostLayout=function(){a.TILE&&(this.repopulateZeroDegreeMembers(),this.repopulateCompounds())},d.prototype.reduceTrees=function(){for(var s=[],h=!0,f;h;){var p=this.graphManager.getAllNodes(),A=[];h=!1;for(var I=0;I<p.length;I++)f=p[I],f.getEdges().length==1&&!f.getEdges()[0].isInterGraph&&f.getChild()==null&&(A.push([f,f.getEdges()[0],f.getOwner()]),h=!0);if(h==!0){for(var R=[],x=0;x<A.length;x++)A[x][0].getEdges().length==1&&(R.push(A[x]),A[x][0].getOwner().remove(A[x][0]));s.push(R),this.graphManager.resetAllNodes(),this.graphManager.resetAllEdges()}}this.prunedNodesAll=s},d.prototype.growTree=function(s){for(var h=s.length,f=s[h-1],p,A=0;A<f.length;A++)p=f[A],this.findPlaceforPrunedNode(p),p[2].add(p[0]),p[2].add(p[1],p[1].source,p[1].target);s.splice(s.length-1,1),this.graphManager.resetAllNodes(),this.graphManager.resetAllEdges()},d.prototype.findPlaceforPrunedNode=function(s){var h,f,p=s[0];p==s[1].source?f=s[1].target:f=s[1].source;var A=f.startX,I=f.finishX,R=f.startY,x=f.finishY,G=0,U=0,X=0,w=0,S=[G,X,U,w];if(R>0)for(var F=A;F<=I;F++)S[0]+=this.grid[F][R-1].length+this.grid[F][R].length-1;if(I<this.grid.length-1)for(var F=R;F<=x;F++)S[1]+=this.grid[I+1][F].length+this.grid[I][F].length-1;if(x<this.grid[0].length-1)for(var F=A;F<=I;F++)S[2]+=this.grid[F][x+1].length+this.grid[F][x].length-1;if(A>0)for(var F=R;F<=x;F++)S[3]+=this.grid[A-1][F].length+this.grid[A][F].length-1;for(var b=T.MAX_VALUE,Y,k,H=0;H<S.length;H++)S[H]<b?(b=S[H],Y=1,k=H):S[H]==b&&Y++;if(Y==3&&b==0)S[0]==0&&S[1]==0&&S[2]==0?h=1:S[0]==0&&S[1]==0&&S[3]==0?h=0:S[0]==0&&S[2]==0&&S[3]==0?h=3:S[1]==0&&S[2]==0&&S[3]==0&&(h=2);else if(Y==2&&b==0){var P=Math.floor(Math.random()*2);S[0]==0&&S[1]==0?P==0?h=0:h=1:S[0]==0&&S[2]==0?P==0?h=0:h=2:S[0]==0&&S[3]==0?P==0?h=0:h=3:S[1]==0&&S[2]==0?P==0?h=1:h=2:S[1]==0&&S[3]==0?P==0?h=1:h=3:P==0?h=2:h=3}else if(Y==4&&b==0){var P=Math.floor(Math.random()*4);h=P}else h=k;h==0?p.setCenter(f.getCenterX(),f.getCenterY()-f.getHeight()/2-v.DEFAULT_EDGE_LENGTH-p.getHeight()/2):h==1?p.setCenter(f.getCenterX()+f.getWidth()/2+v.DEFAULT_EDGE_LENGTH+p.getWidth()/2,f.getCenterY()):h==2?p.setCenter(f.getCenterX(),f.getCenterY()+f.getHeight()/2+v.DEFAULT_EDGE_LENGTH+p.getHeight()/2):p.setCenter(f.getCenterX()-f.getWidth()/2-v.DEFAULT_EDGE_LENGTH-p.getWidth()/2,f.getCenterY())},D.exports=d},function(D,y,r){var t={};t.layoutBase=r(0),t.CoSEConstants=r(1),t.CoSEEdge=r(2),t.CoSEGraph=r(3),t.CoSEGraphManager=r(4),t.CoSELayout=r(6),t.CoSENode=r(5),D.exports=t}])})}(et)),et.exports}var wt=tt.exports,ut;function St(){return ut||(ut=1,function(C,M){(function(D,y){C.exports=y(Mt())})(wt,function(u){return function(D){var y={};function r(t){if(y[t])return y[t].exports;var e=y[t]={i:t,l:!1,exports:{}};return D[t].call(e.exports,e,e.exports,r),e.l=!0,e.exports}return r.m=D,r.c=y,r.i=function(t){return 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E=function(L){L.nodeRepulsion!=null&&(i.DEFAULT_REPULSION_STRENGTH=e.DEFAULT_REPULSION_STRENGTH=L.nodeRepulsion),L.idealEdgeLength!=null&&(i.DEFAULT_EDGE_LENGTH=e.DEFAULT_EDGE_LENGTH=L.idealEdgeLength),L.edgeElasticity!=null&&(i.DEFAULT_SPRING_STRENGTH=e.DEFAULT_SPRING_STRENGTH=L.edgeElasticity),L.nestingFactor!=null&&(i.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR=e.PER_LEVEL_IDEAL_EDGE_LENGTH_FACTOR=L.nestingFactor),L.gravity!=null&&(i.DEFAULT_GRAVITY_STRENGTH=e.DEFAULT_GRAVITY_STRENGTH=L.gravity),L.numIter!=null&&(i.MAX_ITERATIONS=e.MAX_ITERATIONS=L.numIter),L.gravityRange!=null&&(i.DEFAULT_GRAVITY_RANGE_FACTOR=e.DEFAULT_GRAVITY_RANGE_FACTOR=L.gravityRange),L.gravityCompound!=null&&(i.DEFAULT_COMPOUND_GRAVITY_STRENGTH=e.DEFAULT_COMPOUND_GRAVITY_STRENGTH=L.gravityCompound),L.gravityRangeCompound!=null&&(i.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR=e.DEFAULT_COMPOUND_GRAVITY_RANGE_FACTOR=L.gravityRangeCompound),L.initialEnergyOnIncremental!=null&&(i.DEFAULT_COOLING_FACTOR_INCREMENTAL=e.DEFAULT_COOLING_FACTOR_INCREMENTAL=L.initialEnergyOnIncremental),L.quality=="draft"?t.QUALITY=0:L.quality=="proof"?t.QUALITY=2:t.QUALITY=1,i.NODE_DIMENSIONS_INCLUDE_LABELS=e.NODE_DIMENSIONS_INCLUDE_LABELS=t.NODE_DIMENSIONS_INCLUDE_LABELS=L.nodeDimensionsIncludeLabels,i.DEFAULT_INCREMENTAL=e.DEFAULT_INCREMENTAL=t.DEFAULT_INCREMENTAL=!L.randomize,i.ANIMATE=e.ANIMATE=t.ANIMATE=L.animate,i.TILE=L.tile,i.TILING_PADDING_VERTICAL=typeof 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w=function(){O.fit&&O.cy.fit(O.eles,O.padding),m||(m=!0,N.cy.one("layoutready",O.ready),N.cy.trigger({type:"layoutready",layout:N}))},S=N.options.refresh,F,b=0;b<S&&!F;b++)F=N.stopped||N.layout.tick();if(F){d.checkLayoutSuccess()&&!d.isSubLayout&&d.doPostLayout(),d.tilingPostLayout&&d.tilingPostLayout(),d.isLayoutFinished=!0,N.options.eles.nodes().positions(G),w(),N.cy.one("layoutstop",N.options.stop),N.cy.trigger({type:"layoutstop",layout:N}),L&&cancelAnimationFrame(L),m=!1;return}var Y=N.layout.getPositionsData();O.eles.nodes().positions(function(k,H){if(typeof k=="number"&&(k=H),!k.isParent()){for(var P=k.id(),B=Y[P],$=k;B==null&&(B=Y[$.data("parent")]||Y["DummyCompound_"+$.data("parent")],Y[P]=B,$=$.parent()[0],$!=null););return B!=null?{x:B.x,y:B.y}:{x:k.position("x"),y:k.position("y")}}}),w(),L=requestAnimationFrame(X)};return d.addListener("layoutstarted",function(){N.options.animate==="during"&&(L=requestAnimationFrame(U))}),d.runLayout(),this.options.animate!=="during"&&(N.options.eles.nodes().not(":parent").layoutPositions(N,N.options,G),m=!1),this},l.prototype.getTopMostNodes=function(m){for(var L={},O=0;O<m.length;O++)L[m[O].id()]=!0;var d=m.filter(function(N,s){typeof N=="number"&&(N=s);for(var h=N.parent()[0];h!=null;){if(L[h.id()])return!1;h=h.parent()[0]}return!0});return d},l.prototype.processChildrenList=function(m,L,O){for(var d=L.length,N=0;N<d;N++){var s=L[N],h=s.children(),f,p=s.layoutDimensions({nodeDimensionsIncludeLabels:this.options.nodeDimensionsIncludeLabels});if(s.outerWidth()!=null&&s.outerHeight()!=null?f=m.add(new g(O.graphManager,new a(s.position("x")-p.w/2,s.position("y")-p.h/2),new v(parseFloat(p.w),parseFloat(p.h)))):f=m.add(new 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diff --git a/lightrag/api/webui/assets/pieDiagram-NIOCPIFQ-b2mgE5LJ.js b/lightrag/api/webui/assets/pieDiagram-NIOCPIFQ-CSm1JULy.js
similarity index 91%
rename from lightrag/api/webui/assets/pieDiagram-NIOCPIFQ-b2mgE5LJ.js
rename to lightrag/api/webui/assets/pieDiagram-NIOCPIFQ-CSm1JULy.js
index c9f12a89..ba25c6a1 100644
--- a/lightrag/api/webui/assets/pieDiagram-NIOCPIFQ-b2mgE5LJ.js
+++ b/lightrag/api/webui/assets/pieDiagram-NIOCPIFQ-CSm1JULy.js
@@ -1,4 +1,4 @@
-import{p as N}from"./chunk-353BL4L5-DAdaHWGH.js";import{_ as i,g as B,s as U,a as q,b as H,t as K,q as V,l as C,c as Z,F as j,K as J,M as Q,N as z,O as X,e as Y,z as tt,P as et,H as at}from"./mermaid-vendor-CAxUo7Zk.js";import{p as rt}from"./treemap-75Q7IDZK-BAguqzAo.js";import"./feature-graph-C6IuADHZ.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";import"./_baseUniq-BrMEyGA7.js";import"./_basePickBy-BEWgwF1U.js";import"./clone-D60V_qjf.js";var it=at.pie,D={sections:new Map,showData:!1},f=D.sections,w=D.showData,st=structuredClone(it),ot=i(()=>structuredClone(st),"getConfig"),nt=i(()=>{f=new Map,w=D.showData,tt()},"clear"),lt=i(({label:t,value:a})=>{f.has(t)||(f.set(t,a),C.debug(`added new section: ${t}, with value: ${a}`))},"addSection"),ct=i(()=>f,"getSections"),pt=i(t=>{w=t},"setShowData"),dt=i(()=>w,"getShowData"),F={getConfig:ot,clear:nt,setDiagramTitle:V,getDiagramTitle:K,setAccTitle:H,getAccTitle:q,setAccDescription:U,getAccDescription:B,addSection:lt,getSections:ct,setShowData:pt,getShowData:dt},gt=i((t,a)=>{N(t,a),a.setShowData(t.showData),t.sections.map(a.addSection)},"populateDb"),ut={parse:i(async t=>{const a=await rt("pie",t);C.debug(a),gt(a,F)},"parse")},mt=i(t=>`
+import{p as N}from"./chunk-353BL4L5-CR8qX5CO.js";import{_ as i,g as B,s as U,a as q,b as H,t as K,q as V,l as C,c as Z,F as j,K as J,M as Q,N as z,O as X,e as Y,z as tt,P as et,H as at}from"./mermaid-vendor-B20mDgAo.js";import{p as rt}from"./treemap-75Q7IDZK-64OceOGQ.js";import"./feature-graph-CS4MyqEv.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";import"./_baseUniq-Coqzfado.js";import"./_basePickBy-zcTWmF8I.js";import"./clone-D1fuhfq3.js";var it=at.pie,D={sections:new Map,showData:!1},f=D.sections,w=D.showData,st=structuredClone(it),ot=i(()=>structuredClone(st),"getConfig"),nt=i(()=>{f=new Map,w=D.showData,tt()},"clear"),lt=i(({label:t,value:a})=>{f.has(t)||(f.set(t,a),C.debug(`added new section: ${t}, with value: ${a}`))},"addSection"),ct=i(()=>f,"getSections"),pt=i(t=>{w=t},"setShowData"),dt=i(()=>w,"getShowData"),F={getConfig:ot,clear:nt,setDiagramTitle:V,getDiagramTitle:K,setAccTitle:H,getAccTitle:q,setAccDescription:U,getAccDescription:B,addSection:lt,getSections:ct,setShowData:pt,getShowData:dt},gt=i((t,a)=>{N(t,a),a.setShowData(t.showData),t.sections.map(a.addSection)},"populateDb"),ut={parse:i(async t=>{const a=await rt("pie",t);C.debug(a),gt(a,F)},"parse")},mt=i(t=>`
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     stroke-width : ${t.pieStrokeWidth};
diff --git a/lightrag/api/webui/assets/quadrantDiagram-2OG54O6I-4sLwOGmA.js b/lightrag/api/webui/assets/quadrantDiagram-2OG54O6I-j5yQBfMM.js
similarity index 99%
rename from lightrag/api/webui/assets/quadrantDiagram-2OG54O6I-4sLwOGmA.js
rename to lightrag/api/webui/assets/quadrantDiagram-2OG54O6I-j5yQBfMM.js
index 725892e4..f5afc409 100644
--- a/lightrag/api/webui/assets/quadrantDiagram-2OG54O6I-4sLwOGmA.js
+++ b/lightrag/api/webui/assets/quadrantDiagram-2OG54O6I-j5yQBfMM.js
@@ -1,4 +1,4 @@
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diff --git a/lightrag/api/webui/assets/requirementDiagram-QOLK2EJ7-Cv3ovpXZ.js b/lightrag/api/webui/assets/requirementDiagram-QOLK2EJ7-ClDw_aOM.js
similarity index 99%
rename from lightrag/api/webui/assets/requirementDiagram-QOLK2EJ7-Cv3ovpXZ.js
rename to lightrag/api/webui/assets/requirementDiagram-QOLK2EJ7-ClDw_aOM.js
index b68393d3..d3ef6938 100644
--- a/lightrag/api/webui/assets/requirementDiagram-QOLK2EJ7-Cv3ovpXZ.js
+++ b/lightrag/api/webui/assets/requirementDiagram-QOLK2EJ7-ClDw_aOM.js
@@ -1,4 +1,4 @@
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diff --git a/lightrag/api/webui/assets/sankeyDiagram-4UZDY2LN-a4WJasJz.js b/lightrag/api/webui/assets/sankeyDiagram-4UZDY2LN-Dilpaf_-.js
similarity index 99%
rename from lightrag/api/webui/assets/sankeyDiagram-4UZDY2LN-a4WJasJz.js
rename to lightrag/api/webui/assets/sankeyDiagram-4UZDY2LN-Dilpaf_-.js
index 2b107b4c..d9131f0d 100644
--- a/lightrag/api/webui/assets/sankeyDiagram-4UZDY2LN-a4WJasJz.js
+++ b/lightrag/api/webui/assets/sankeyDiagram-4UZDY2LN-Dilpaf_-.js
@@ -1,4 +1,4 @@
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diff --git a/lightrag/api/webui/assets/sequenceDiagram-SKLFT4DO-4kjiUiy3.js b/lightrag/api/webui/assets/sequenceDiagram-SKLFT4DO-Gp4aPgFb.js
similarity index 99%
rename from lightrag/api/webui/assets/sequenceDiagram-SKLFT4DO-4kjiUiy3.js
rename to lightrag/api/webui/assets/sequenceDiagram-SKLFT4DO-Gp4aPgFb.js
index 794c6842..0ed00701 100644
--- a/lightrag/api/webui/assets/sequenceDiagram-SKLFT4DO-4kjiUiy3.js
+++ b/lightrag/api/webui/assets/sequenceDiagram-SKLFT4DO-Gp4aPgFb.js
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52:l[u-1].type="destroyParticipant",this.$=l[u-1];break;case 53:this.$=[l[u-1],{type:"addNote",placement:l[u-2],actor:l[u-1].actor,text:l[u]}];break;case 54:l[u-2]=[].concat(l[u-1],l[u-1]).slice(0,2),l[u-2][0]=l[u-2][0].actor,l[u-2][1]=l[u-2][1].actor,this.$=[l[u-1],{type:"addNote",placement:b.PLACEMENT.OVER,actor:l[u-2].slice(0,2),text:l[u]}];break;case 55:this.$=[l[u-1],{type:"addLinks",actor:l[u-1].actor,text:l[u]}];break;case 56:this.$=[l[u-1],{type:"addALink",actor:l[u-1].actor,text:l[u]}];break;case 57:this.$=[l[u-1],{type:"addProperties",actor:l[u-1].actor,text:l[u]}];break;case 58:this.$=[l[u-1],{type:"addDetails",actor:l[u-1].actor,text:l[u]}];break;case 61:this.$=[l[u-2],l[u]];break;case 62:this.$=l[u];break;case 63:this.$=b.PLACEMENT.LEFTOF;break;case 64:this.$=b.PLACEMENT.RIGHTOF;break;case 65:this.$=[l[u-4],l[u-1],{type:"addMessage",from:l[u-4].actor,to:l[u-1].actor,signalType:l[u-3],msg:l[u],activate:!0},{type:"activeStart",signalType:b.LINETYPE.ACTIVE_START,actor:l[u-1].actor}];break;case 66:this.$=[l[u-4],l[u-1],{type:"addMessage",from:l[u-4].actor,to:l[u-1].actor,signalType:l[u-3],msg:l[u]},{type:"activeEnd",signalType:b.LINETYPE.ACTIVE_END,actor:l[u-4].actor}];break;case 67:this.$=[l[u-3],l[u-1],{type:"addMessage",from:l[u-3].actor,to:l[u-1].actor,signalType:l[u-2],msg:l[u]}];break;case 68:this.$={type:"addParticipant",actor:l[u]};break;case 69:this.$=b.LINETYPE.SOLID_OPEN;break;case 70:this.$=b.LINETYPE.DOTTED_OPEN;break;case 71:this.$=b.LINETYPE.SOLID;break;case 72:this.$=b.LINETYPE.BIDIRECTIONAL_SOLID;break;case 73:this.$=b.LINETYPE.DOTTED;break;case 74:this.$=b.LINETYPE.BIDIRECTIONAL_DOTTED;break;case 75:this.$=b.LINETYPE.SOLID_CROSS;break;case 76:this.$=b.LINETYPE.DOTTED_CROSS;break;case 77:this.$=b.LINETYPE.SOLID_POINT;break;case 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41:l[u-1].unshift({type:"breakStart",breakText:b.parseMessage(l[u-2]),signalType:b.LINETYPE.BREAK_START}),l[u-1].push({type:"breakEnd",optText:b.parseMessage(l[u-2]),signalType:b.LINETYPE.BREAK_END}),this.$=l[u-1];break;case 43:this.$=l[u-3].concat([{type:"option",optionText:b.parseMessage(l[u-1]),signalType:b.LINETYPE.CRITICAL_OPTION},l[u]]);break;case 45:this.$=l[u-3].concat([{type:"and",parText:b.parseMessage(l[u-1]),signalType:b.LINETYPE.PAR_AND},l[u]]);break;case 47:this.$=l[u-3].concat([{type:"else",altText:b.parseMessage(l[u-1]),signalType:b.LINETYPE.ALT_ELSE},l[u]]);break;case 48:l[u-3].draw="participant",l[u-3].type="addParticipant",l[u-3].description=b.parseMessage(l[u-1]),this.$=l[u-3];break;case 49:l[u-1].draw="participant",l[u-1].type="addParticipant",this.$=l[u-1];break;case 50:l[u-3].draw="actor",l[u-3].type="addParticipant",l[u-3].description=b.parseMessage(l[u-1]),this.$=l[u-3];break;case 51:l[u-1].draw="actor",l[u-1].type="addParticipant",this.$=l[u-1];break;case 52:l[u-1].type="destroyParticipant",this.$=l[u-1];break;case 53:this.$=[l[u-1],{type:"addNote",placement:l[u-2],actor:l[u-1].actor,text:l[u]}];break;case 54:l[u-2]=[].concat(l[u-1],l[u-1]).slice(0,2),l[u-2][0]=l[u-2][0].actor,l[u-2][1]=l[u-2][1].actor,this.$=[l[u-1],{type:"addNote",placement:b.PLACEMENT.OVER,actor:l[u-2].slice(0,2),text:l[u]}];break;case 55:this.$=[l[u-1],{type:"addLinks",actor:l[u-1].actor,text:l[u]}];break;case 56:this.$=[l[u-1],{type:"addALink",actor:l[u-1].actor,text:l[u]}];break;case 57:this.$=[l[u-1],{type:"addProperties",actor:l[u-1].actor,text:l[u]}];break;case 58:this.$=[l[u-1],{type:"addDetails",actor:l[u-1].actor,text:l[u]}];break;case 61:this.$=[l[u-2],l[u]];break;case 62:this.$=l[u];break;case 63:this.$=b.PLACEMENT.LEFTOF;break;case 64:this.$=b.PLACEMENT.RIGHTOF;break;case 65:this.$=[l[u-4],l[u-1],{type:"addMessage",from:l[u-4].actor,to:l[u-1].actor,signalType:l[u-3],msg:l[u],activate:!0},{type:"activeStart",signalType:b.LINETYPE.ACTIVE_START,actor:l[u-1].actor}];break;case 66:this.$=[l[u-4],l[u-1],{type:"addMessage",from:l[u-4].actor,to:l[u-1].actor,signalType:l[u-3],msg:l[u]},{type:"activeEnd",signalType:b.LINETYPE.ACTIVE_END,actor:l[u-4].actor}];break;case 67:this.$=[l[u-3],l[u-1],{type:"addMessage",from:l[u-3].actor,to:l[u-1].actor,signalType:l[u-2],msg:l[u]}];break;case 68:this.$={type:"addParticipant",actor:l[u]};break;case 69:this.$=b.LINETYPE.SOLID_OPEN;break;case 70:this.$=b.LINETYPE.DOTTED_OPEN;break;case 71:this.$=b.LINETYPE.SOLID;break;case 72:this.$=b.LINETYPE.BIDIRECTIONAL_SOLID;break;case 73:this.$=b.LINETYPE.DOTTED;break;case 74:this.$=b.LINETYPE.BIDIRECTIONAL_DOTTED;break;case 75:this.$=b.LINETYPE.SOLID_CROSS;break;case 76:this.$=b.LINETYPE.DOTTED_CROSS;break;case 77:this.$=b.LINETYPE.SOLID_POINT;break;case 78:this.$=b.LINETYPE.DOTTED_POINT;break;case 79:this.$=b.parseMessage(l[u].trim().substring(1));break}},"anonymous"),table:[{3:1,4:t,5:c,6:s},{1:[3]},{3:5,4:t,5:c,6:s},{3:6,4:t,5:c,6:s},e([1,4,5,13,14,18,21,23,29,30,31,33,35,36,37,38,39,41,43,44,46,50,52,53,54,59,60,61,62,70],a,{7:7}),{1:[2,1]},{1:[2,2]},{1:[2,3],4:i,5:n,8:8,9:10,12:12,13:d,14:h,17:15,18:r,21:g,22:40,23:E,24:19,25:20,26:21,27:22,28:23,29:f,30:T,31:m,33:I,35:k,36:O,37:S,38:B,39:D,41:F,43:q,44:X,46:tt,50:z,52:H,53:W,54:M,59:J,60:U,61:Z,62:et,70:v},e(y,[2,5]),{9:47,12:12,13:d,14:h,17:15,18:r,21:g,22:40,23:E,24:19,25:20,26:21,27:22,28:23,29:f,30:T,31:m,33:I,35:k,36:O,37:S,38:B,39:D,41:F,43:q,44:X,46:tt,50:z,52:H,53:W,54:M,59:J,60:U,61:Z,62:et,70:v},e(y,[2,7]),e(y,[2,8]),e(y,[2,14]),{12:48,50:z,52:H,53:W},{15:[1,49]},{5:[1,50]},{5:[1,53],19:[1,51],20:[1,52]},{22:54,70:v},{22:55,70:v},{5:[1,56]},{5:[1,57]},{5:[1,58]},{5:[1,59]},{5:[1,60]},e(y,[2,29]),e(y,[2,30]),{32:[1,61]},{34:[1,62]},e(y,[2,33]),{15:[1,63]},{15:[1,64]},{15:[1,65]},{15:[1,66]},{15:[1,67]},{15:[1,68]},{15:[1,69]},{15:[1,70]},{22:71,70:v},{22:72,70:v},{22:73,70:v},{67:74,71:[1,75],72:[1,76],73:[1,77],74:[1,78],75:[1,79],76:[1,80],77:[1,81],78:[1,82],79:[1,83],80:[1,84]},{55:85,57:[1,86],65:[1,87],66:[1,88]},{22:89,70:v},{22:90,70:v},{22:91,70:v},{22:92,70:v},e([5,51,64,71,72,73,74,75,76,77,78,79,80,81],[2,68]),e(y,[2,6]),e(y,[2,15]),e(P,[2,9],{10:93}),e(y,[2,17]),{5:[1,95],19:[1,94]},{5:[1,96]},e(y,[2,21]),{5:[1,97]},{5:[1,98]},e(y,[2,24]),e(y,[2,25]),e(y,[2,26]),e(y,[2,27]),e(y,[2,28]),e(y,[2,31]),e(y,[2,32]),e(Q,a,{7:99}),e(Q,a,{7:100}),e(Q,a,{7:101}),e(at,a,{40:102,7:103}),e(N,a,{42:104,7:105}),e(N,a,{7:105,42:106}),e(qt,a,{45:107,7:108}),e(Q,a,{7:109}),{5:[1,111],51:[1,110]},{5:[1,113],51:[1,112]},{5:[1,114]},{22:117,68:[1,115],69:[1,116],70:v},e(it,[2,69]),e(it,[2,70]),e(it,[2,71]),e(it,[2,72]),e(it,[2,73]),e(it,[2,74]),e(it,[2,75]),e(it,[2,76]),e(it,[2,77]),e(it,[2,78]),{22:118,70:v},{22:120,58:119,70:v},{70:[2,63]},{70:[2,64]},{56:121,81:ct},{56:123,81:ct},{56:124,81:ct},{56:125,81:ct},{4:[1,128],5:[1,130],11:127,12:129,16:[1,126],50:z,52:H,53:W},{5:[1,131]},e(y,[2,19]),e(y,[2,20]),e(y,[2,22]),e(y,[2,23]),{4:i,5:n,8:8,9:10,12:12,13:d,14:h,16:[1,132],17:15,18:r,21:g,22:40,23:E,24:19,25:20,26:21,27:22,28:23,29:f,30:T,31:m,33:I,35:k,36:O,37:S,38:B,39:D,41:F,43:q,44:X,46:tt,50:z,52:H,53:W,54:M,59:J,60:U,61:Z,62:et,70:v},{4:i,5:n,8:8,9:10,12:12,13:d,14:h,16:[1,133],17:15,18:r,21:g,22:40,23:E,24:19,25:20,26:21,27:22,28:23,29:f,30:T,31:m,33:I,35:k,36:O,37:S,38:B,39:D,41:F,43:q,44:X,46:tt,50:z,52:H,53:W,54:M,59:J,60:U,61:Z,62:et,70:v},{4:i,5:n,8:8,9:10,12:12,13:d,14:h,16:[1,134],17:15,18:r,21:g,22:40,23:E,24:19,25:20,26:21,27:22,28:23,29:f,30:T,31:m,33:I,35:k,36:O,37:S,38:B,39:D,41:F,43:q,44:X,46:tt,50:z,52:H,53:W,54:M,59:J,60:U,61:Z,62:et,70:v},{16:[1,135]},{4:i,5:n,8:8,9:10,12:12,13:d,14:h,16:[2,46],17:15,18:r,21:g,22:40,23:E,24:19,25:20,26:21,27:22,28:23,29:f,30:T,31:m,33:I,35:k,36:O,37:S,38:B,39:D,41:F,43:q,44:X,46:tt,49:[1,136],50:z,52:H,53:W,54:M,59:J,60:U,61:Z,62:et,70:v},{16:[1,137]},{4:i,5:n,8:8,9:10,12:12,13:d,14:h,16:[2,44],17:15,18:r,21:g,22:40,23:E,24:19,25:20,26:21,27:22,28:23,29:f,30:T,31:m,33:I,35:k,36:O,37:S,38:B,39:D,41:F,43:q,44:X,46:tt,48:[1,138],50:z,52:H,53:W,54:M,59:J,60:U,61:Z,62:et,70:v},{16:[1,139]},{16:[1,140]},{4:i,5:n,8:8,9:10,12:12,13:d,14:h,16:[2,42],17:15,18:r,21:g,22:40,23:E,24:19,25:20,26:21,27:22,28:23,29:f,30:T,31:m,33:I,35:k,36:O,37:S,38:B,39:D,41:F,43:q,44:X,46:tt,47:[1,141],50:z,52:H,53:W,54:M,59:J,60:U,61:Z,62:et,70:v},{4:i,5:n,8:8,9:10,12:12,13:d,14:h,16:[1,142],17:15,18:r,21:g,22:40,23:E,24:19,25:20,26:21,27:22,28:23,29:f,30:T,31:m,33:I,35:k,36:O,37:S,38:B,39:D,41:F,43:q,44:X,46:tt,50:z,52:H,53:W,54:M,59:J,60:U,61:Z,62:et,70:v},{15:[1,143]},e(y,[2,49]),{15:[1,144]},e(y,[2,51]),e(y,[2,52]),{22:145,70:v},{22:146,70:v},{56:147,81:ct},{56:148,81:ct},{56:149,81:ct},{64:[1,150],81:[2,62]},{5:[2,55]},{5:[2,79]},{5:[2,56]},{5:[2,57]},{5:[2,58]},e(y,[2,16]),e(P,[2,10]),{12:151,50:z,52:H,53:W},e(P,[2,12]),e(P,[2,13]),e(y,[2,18]),e(y,[2,34]),e(y,[2,35]),e(y,[2,36]),e(y,[2,37]),{15:[1,152]},e(y,[2,38]),{15:[1,153]},e(y,[2,39]),e(y,[2,40]),{15:[1,154]},e(y,[2,41]),{5:[1,155]},{5:[1,156]},{56:157,81:ct},{56:158,81:ct},{5:[2,67]},{5:[2,53]},{5:[2,54]},{22:159,70:v},e(P,[2,11]),e(at,a,{7:103,40:160}),e(N,a,{7:105,42:161}),e(qt,a,{7:108,45:162}),e(y,[2,48]),e(y,[2,50]),{5:[2,65]},{5:[2,66]},{81:[2,61]},{16:[2,47]},{16:[2,45]},{16:[2,43]}],defaultActions:{5:[2,1],6:[2,2],87:[2,63],88:[2,64],121:[2,55],122:[2,79],123:[2,56],124:[2,57],125:[2,58],147:[2,67],148:[2,53],149:[2,54],157:[2,65],158:[2,66],159:[2,61],160:[2,47],161:[2,45],162:[2,43]},parseError:p(function(w,_){if(_.recoverable)this.trace(w);else{var A=new Error(w);throw A.hash=_,A}},"parseError"),parse:p(function(w){var _=this,A=[0],b=[],R=[null],l=[],Et=this.table,u="",wt=0,zt=0,ue=2,Ht=1,pe=l.slice.call(arguments,1),V=Object.create(this.lexer),ht={yy:{}};for(var St in this.yy)Object.prototype.hasOwnProperty.call(this.yy,St)&&(ht.yy[St]=this.yy[St]);V.setInput(w,ht.yy),ht.yy.lexer=V,ht.yy.parser=this,typeof V.yylloc>"u"&&(V.yylloc={});var Mt=V.yylloc;l.push(Mt);var fe=V.options&&V.options.ranges;typeof ht.yy.parseError=="function"?this.parseError=ht.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError;function ge(j){A.length=A.length-2*j,R.length=R.length-j,l.length=l.length-j}p(ge,"popStack");function Ut(){var j;return j=b.pop()||V.lex()||Ht,typeof j!="number"&&(j instanceof Array&&(b=j,j=b.pop()),j=_.symbols_[j]||j),j}p(Ut,"lex");for(var K,ut,st,Rt,gt={},It,lt,Kt,Lt;;){if(ut=A[A.length-1],this.defaultActions[ut]?st=this.defaultActions[ut]:((K===null||typeof K>"u")&&(K=Ut()),st=Et[ut]&&Et[ut][K]),typeof st>"u"||!st.length||!st[0]){var Dt="";Lt=[];for(It in Et[ut])this.terminals_[It]&&It>ue&&Lt.push("'"+this.terminals_[It]+"'");V.showPosition?Dt="Parse error on line "+(wt+1)+`:
 `+V.showPosition()+`
 Expecting `+Lt.join(", ")+", got '"+(this.terminals_[K]||K)+"'":Dt="Parse error on line "+(wt+1)+": Unexpected "+(K==Ht?"end of input":"'"+(this.terminals_[K]||K)+"'"),this.parseError(Dt,{text:V.match,token:this.terminals_[K]||K,line:V.yylineno,loc:Mt,expected:Lt})}if(st[0]instanceof Array&&st.length>1)throw new Error("Parse Error: multiple actions possible at state: "+ut+", token: "+K);switch(st[0]){case 1:A.push(K),R.push(V.yytext),l.push(V.yylloc),A.push(st[1]),K=null,zt=V.yyleng,u=V.yytext,wt=V.yylineno,Mt=V.yylloc;break;case 2:if(lt=this.productions_[st[1]][1],gt.$=R[R.length-lt],gt._$={first_line:l[l.length-(lt||1)].first_line,last_line:l[l.length-1].last_line,first_column:l[l.length-(lt||1)].first_column,last_column:l[l.length-1].last_column},fe&&(gt._$.range=[l[l.length-(lt||1)].range[0],l[l.length-1].range[1]]),Rt=this.performAction.apply(gt,[u,zt,wt,ht.yy,st[1],R,l].concat(pe)),typeof Rt<"u")return Rt;lt&&(A=A.slice(0,-1*lt*2),R=R.slice(0,-1*lt),l=l.slice(0,-1*lt)),A.push(this.productions_[st[1]][0]),R.push(gt.$),l.push(gt._$),Kt=Et[A[A.length-2]][A[A.length-1]],A.push(Kt);break;case 3:return!0}}return!0},"parse")},he=function(){var dt={EOF:1,parseError:p(function(_,A){if(this.yy.parser)this.yy.parser.parseError(_,A);else throw new Error(_)},"parseError"),setInput:p(function(w,_){return this.yy=_||this.yy||{},this._input=w,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},"setInput"),input:p(function(){var w=this._input[0];this.yytext+=w,this.yyleng++,this.offset++,this.match+=w,this.matched+=w;var _=w.match(/(?:\r\n?|\n).*/g);return _?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),w},"input"),unput:p(function(w){var _=w.length,A=w.split(/(?:\r\n?|\n)/g);this._input=w+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-_),this.offset-=_;var b=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),A.length-1&&(this.yylineno-=A.length-1);var R=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:A?(A.length===b.length?this.yylloc.first_column:0)+b[b.length-A.length].length-A[0].length:this.yylloc.first_column-_},this.options.ranges&&(this.yylloc.range=[R[0],R[0]+this.yyleng-_]),this.yyleng=this.yytext.length,this},"unput"),more:p(function(){return this._more=!0,this},"more"),reject:p(function(){if(this.options.backtrack_lexer)this._backtrack=!0;else return this.parseError("Lexical error on line "+(this.yylineno+1)+`. You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).
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diff --git a/lightrag/api/webui/assets/stateDiagram-MI5ZYTHO-DKcfoWKS.js b/lightrag/api/webui/assets/stateDiagram-MI5ZYTHO-kwBNzc6R.js
similarity index 96%
rename from lightrag/api/webui/assets/stateDiagram-MI5ZYTHO-DKcfoWKS.js
rename to lightrag/api/webui/assets/stateDiagram-MI5ZYTHO-kwBNzc6R.js
index cb85dd4d..059aded2 100644
--- a/lightrag/api/webui/assets/stateDiagram-MI5ZYTHO-DKcfoWKS.js
+++ b/lightrag/api/webui/assets/stateDiagram-MI5ZYTHO-kwBNzc6R.js
@@ -1 +1 @@
-import{s as R,a as W,S as v}from"./chunk-OW32GOEJ-Bpuvralp.js";import{_ as f,c as t,d as H,l as S,e as P,k as z,U,a0 as _,X as C,u as F}from"./mermaid-vendor-CAxUo7Zk.js";import{G as O}from"./graph-dt4A1Xns.js";import{l as X}from"./layout-Bs3ntXjW.js";import"./chunk-BFAMUDN2-DQGv_fhY.js";import"./chunk-SKB7J2MH-D-vU5iV6.js";import"./feature-graph-C6IuADHZ.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";import"./_baseUniq-BrMEyGA7.js";import"./_basePickBy-BEWgwF1U.js";var J=f(e=>e.append("circle").attr("class","start-state").attr("r",t().state.sizeUnit).attr("cx",t().state.padding+t().state.sizeUnit).attr("cy",t().state.padding+t().state.sizeUnit),"drawStartState"),D=f(e=>e.append("line").style("stroke","grey").style("stroke-dasharray","3").attr("x1",t().state.textHeight).attr("class","divider").attr("x2",t().state.textHeight*2).attr("y1",0).attr("y2",0),"drawDivider"),Y=f((e,i)=>{const d=e.append("text").attr("x",2*t().state.padding).attr("y",t().state.textHeight+2*t().state.padding).attr("font-size",t().state.fontSize).attr("class","state-title").text(i.id),c=d.node().getBBox();return e.insert("rect",":first-child").attr("x",t().state.padding).attr("y",t().state.padding).attr("width",c.width+2*t().state.padding).attr("height",c.height+2*t().state.padding).attr("rx",t().state.radius),d},"drawSimpleState"),I=f((e,i)=>{const d=f(function(g,B,m){const k=g.append("tspan").attr("x",2*t().state.padding).text(B);m||k.attr("dy",t().state.textHeight)},"addTspan"),r=e.append("text").attr("x",2*t().state.padding).attr("y",t().state.textHeight+1.3*t().state.padding).attr("font-size",t().state.fontSize).attr("class","state-title").text(i.descriptions[0]).node().getBBox(),l=r.height,x=e.append("text").attr("x",t().state.padding).attr("y",l+t().state.padding*.4+t().state.dividerMargin+t().state.textHeight).attr("class","state-description");let a=!0,s=!0;i.descriptions.forEach(function(g){a||(d(x,g,s),s=!1),a=!1});const w=e.append("line").attr("x1",t().state.padding).attr("y1",t().state.padding+l+t().state.dividerMargin/2).attr("y2",t().state.padding+l+t().state.dividerMargin/2).attr("class","descr-divider"),p=x.node().getBBox(),o=Math.max(p.width,r.width);return w.attr("x2",o+3*t().state.padding),e.insert("rect",":first-child").attr("x",t().state.padding).attr("y",t().state.padding).attr("width",o+2*t().state.padding).attr("height",p.height+l+2*t().state.padding).attr("rx",t().state.radius),e},"drawDescrState"),$=f((e,i,d)=>{const c=t().state.padding,r=2*t().state.padding,l=e.node().getBBox(),x=l.width,a=l.x,s=e.append("text").attr("x",0).attr("y",t().state.titleShift).attr("font-size",t().state.fontSize).attr("class","state-title").text(i.id),p=s.node().getBBox().width+r;let o=Math.max(p,x);o===x&&(o=o+r);let g;const B=e.node().getBBox();i.doc,g=a-c,p>x&&(g=(x-o)/2+c),Math.abs(a-B.x)<c&&p>x&&(g=a-(p-x)/2);const m=1-t().state.textHeight;return e.insert("rect",":first-child").attr("x",g).attr("y",m).attr("class",d?"alt-composit":"composit").attr("width",o).attr("height",B.height+t().state.textHeight+t().state.titleShift+1).attr("rx","0"),s.attr("x",g+c),p<=x&&s.attr("x",a+(o-r)/2-p/2+c),e.insert("rect",":first-child").attr("x",g).attr("y",t().state.titleShift-t().state.textHeight-t().state.padding).attr("width",o).attr("height",t().state.textHeight*3).attr("rx",t().state.radius),e.insert("rect",":first-child").attr("x",g).attr("y",t().state.titleShift-t().state.textHeight-t().state.padding).attr("width",o).attr("height",B.height+3+2*t().state.textHeight).attr("rx",t().state.radius),e},"addTitleAndBox"),q=f(e=>(e.append("circle").attr("class","end-state-outer").attr("r",t().state.sizeUnit+t().state.miniPadding).attr("cx",t().state.padding+t().state.sizeUnit+t().state.miniPadding).attr("cy",t().state.padding+t().state.sizeUnit+t().state.miniPadding),e.append("circle").attr("class","end-state-inner").attr("r",t().state.sizeUnit).attr("cx",t().state.padding+t().state.sizeUnit+2).attr("cy",t().state.padding+t().state.sizeUnit+2)),"drawEndState"),Z=f((e,i)=>{let d=t().state.forkWidth,c=t().state.forkHeight;if(i.parentId){let r=d;d=c,c=r}return e.append("rect").style("stroke","black").style("fill","black").attr("width",d).attr("height",c).attr("x",t().state.padding).attr("y",t().state.padding)},"drawForkJoinState"),j=f((e,i,d,c)=>{let r=0;const l=c.append("text");l.style("text-anchor","start"),l.attr("class","noteText");let x=e.replace(/\r\n/g,"<br/>");x=x.replace(/\n/g,"<br/>");const a=x.split(z.lineBreakRegex);let s=1.25*t().state.noteMargin;for(const w of a){const p=w.trim();if(p.length>0){const o=l.append("tspan");if(o.text(p),s===0){const g=o.node().getBBox();s+=g.height}r+=s,o.attr("x",i+t().state.noteMargin),o.attr("y",d+r+1.25*t().state.noteMargin)}}return{textWidth:l.node().getBBox().width,textHeight:r}},"_drawLongText"),K=f((e,i)=>{i.attr("class","state-note");const d=i.append("rect").attr("x",0).attr("y",t().state.padding),c=i.append("g"),{textWidth:r,textHeight:l}=j(e,0,0,c);return d.attr("height",l+2*t().state.noteMargin),d.attr("width",r+t().state.noteMargin*2),d},"drawNote"),L=f(function(e,i){const d=i.id,c={id:d,label:i.id,width:0,height:0},r=e.append("g").attr("id",d).attr("class","stateGroup");i.type==="start"&&J(r),i.type==="end"&&q(r),(i.type==="fork"||i.type==="join")&&Z(r,i),i.type==="note"&&K(i.note.text,r),i.type==="divider"&&D(r),i.type==="default"&&i.descriptions.length===0&&Y(r,i),i.type==="default"&&i.descriptions.length>0&&I(r,i);const l=r.node().getBBox();return c.width=l.width+2*t().state.padding,c.height=l.height+2*t().state.padding,c},"drawState"),A=0,Q=f(function(e,i,d){const c=f(function(s){switch(s){case v.relationType.AGGREGATION:return"aggregation";case v.relationType.EXTENSION:return"extension";case v.relationType.COMPOSITION:return"composition";case v.relationType.DEPENDENCY:return"dependency"}},"getRelationType");i.points=i.points.filter(s=>!Number.isNaN(s.y));const r=i.points,l=U().x(function(s){return s.x}).y(function(s){return s.y}).curve(_),x=e.append("path").attr("d",l(r)).attr("id","edge"+A).attr("class","transition");let a="";if(t().state.arrowMarkerAbsolute&&(a=C(!0)),x.attr("marker-end","url("+a+"#"+c(v.relationType.DEPENDENCY)+"End)"),d.title!==void 0){const s=e.append("g").attr("class","stateLabel"),{x:w,y:p}=F.calcLabelPosition(i.points),o=z.getRows(d.title);let g=0;const B=[];let m=0,k=0;for(let u=0;u<=o.length;u++){const h=s.append("text").attr("text-anchor","middle").text(o[u]).attr("x",w).attr("y",p+g),y=h.node().getBBox();m=Math.max(m,y.width),k=Math.min(k,y.x),S.info(y.x,w,p+g),g===0&&(g=h.node().getBBox().height,S.info("Title height",g,p)),B.push(h)}let N=g*o.length;if(o.length>1){const u=(o.length-1)*g*.5;B.forEach((h,y)=>h.attr("y",p+y*g-u)),N=g*o.length}const n=s.node().getBBox();s.insert("rect",":first-child").attr("class","box").attr("x",w-m/2-t().state.padding/2).attr("y",p-N/2-t().state.padding/2-3.5).attr("width",m+t().state.padding).attr("height",N+t().state.padding),S.info(n)}A++},"drawEdge"),b,T={},V=f(function(){},"setConf"),tt=f(function(e){e.append("defs").append("marker").attr("id","dependencyEnd").attr("refX",19).attr("refY",7).attr("markerWidth",20).attr("markerHeight",28).attr("orient","auto").append("path").attr("d","M 19,7 L9,13 L14,7 L9,1 Z")},"insertMarkers"),et=f(function(e,i,d,c){b=t().state;const r=t().securityLevel;let l;r==="sandbox"&&(l=H("#i"+i));const x=r==="sandbox"?H(l.nodes()[0].contentDocument.body):H("body"),a=r==="sandbox"?l.nodes()[0].contentDocument:document;S.debug("Rendering diagram "+e);const s=x.select(`[id='${i}']`);tt(s);const w=c.db.getRootDoc();G(w,s,void 0,!1,x,a,c);const p=b.padding,o=s.node().getBBox(),g=o.width+p*2,B=o.height+p*2,m=g*1.75;P(s,B,m,b.useMaxWidth),s.attr("viewBox",`${o.x-b.padding}  ${o.y-b.padding} `+g+" "+B)},"draw"),at=f(e=>e?e.length*b.fontSizeFactor:1,"getLabelWidth"),G=f((e,i,d,c,r,l,x)=>{const a=new O({compound:!0,multigraph:!0});let s,w=!0;for(s=0;s<e.length;s++)if(e[s].stmt==="relation"){w=!1;break}d?a.setGraph({rankdir:"LR",multigraph:!0,compound:!0,ranker:"tight-tree",ranksep:w?1:b.edgeLengthFactor,nodeSep:w?1:50,isMultiGraph:!0}):a.setGraph({rankdir:"TB",multigraph:!0,compound:!0,ranksep:w?1:b.edgeLengthFactor,nodeSep:w?1:50,ranker:"tight-tree",isMultiGraph:!0}),a.setDefaultEdgeLabel(function(){return{}});const p=x.db.getStates(),o=x.db.getRelations(),g=Object.keys(p);for(const n of g){const u=p[n];d&&(u.parentId=d);let h;if(u.doc){let y=i.append("g").attr("id",u.id).attr("class","stateGroup");h=G(u.doc,y,u.id,!c,r,l,x);{y=$(y,u,c);let E=y.node().getBBox();h.width=E.width,h.height=E.height+b.padding/2,T[u.id]={y:b.compositTitleSize}}}else h=L(i,u,a);if(u.note){const y={descriptions:[],id:u.id+"-note",note:u.note,type:"note"},E=L(i,y,a);u.note.position==="left of"?(a.setNode(h.id+"-note",E),a.setNode(h.id,h)):(a.setNode(h.id,h),a.setNode(h.id+"-note",E)),a.setParent(h.id,h.id+"-group"),a.setParent(h.id+"-note",h.id+"-group")}else a.setNode(h.id,h)}S.debug("Count=",a.nodeCount(),a);let B=0;o.forEach(function(n){B++,S.debug("Setting edge",n),a.setEdge(n.id1,n.id2,{relation:n,width:at(n.title),height:b.labelHeight*z.getRows(n.title).length,labelpos:"c"},"id"+B)}),X(a),S.debug("Graph after layout",a.nodes());const m=i.node();a.nodes().forEach(function(n){n!==void 0&&a.node(n)!==void 0?(S.warn("Node "+n+": "+JSON.stringify(a.node(n))),r.select("#"+m.id+" #"+n).attr("transform","translate("+(a.node(n).x-a.node(n).width/2)+","+(a.node(n).y+(T[n]?T[n].y:0)-a.node(n).height/2)+" )"),r.select("#"+m.id+" #"+n).attr("data-x-shift",a.node(n).x-a.node(n).width/2),l.querySelectorAll("#"+m.id+" #"+n+" .divider").forEach(h=>{const y=h.parentElement;let E=0,M=0;y&&(y.parentElement&&(E=y.parentElement.getBBox().width),M=parseInt(y.getAttribute("data-x-shift"),10),Number.isNaN(M)&&(M=0)),h.setAttribute("x1",0-M+8),h.setAttribute("x2",E-M-8)})):S.debug("No Node "+n+": "+JSON.stringify(a.node(n)))});let k=m.getBBox();a.edges().forEach(function(n){n!==void 0&&a.edge(n)!==void 0&&(S.debug("Edge "+n.v+" -> "+n.w+": "+JSON.stringify(a.edge(n))),Q(i,a.edge(n),a.edge(n).relation))}),k=m.getBBox();const N={id:d||"root",label:d||"root",width:0,height:0};return N.width=k.width+2*b.padding,N.height=k.height+2*b.padding,S.debug("Doc rendered",N,a),N},"renderDoc"),it={setConf:V,draw:et},yt={parser:W,get db(){return new v(1)},renderer:it,styles:R,init:f(e=>{e.state||(e.state={}),e.state.arrowMarkerAbsolute=e.arrowMarkerAbsolute},"init")};export{yt as diagram};
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d=e.append("text").attr("x",2*t().state.padding).attr("y",t().state.textHeight+2*t().state.padding).attr("font-size",t().state.fontSize).attr("class","state-title").text(i.id),c=d.node().getBBox();return e.insert("rect",":first-child").attr("x",t().state.padding).attr("y",t().state.padding).attr("width",c.width+2*t().state.padding).attr("height",c.height+2*t().state.padding).attr("rx",t().state.radius),d},"drawSimpleState"),I=f((e,i)=>{const d=f(function(g,B,m){const k=g.append("tspan").attr("x",2*t().state.padding).text(B);m||k.attr("dy",t().state.textHeight)},"addTspan"),r=e.append("text").attr("x",2*t().state.padding).attr("y",t().state.textHeight+1.3*t().state.padding).attr("font-size",t().state.fontSize).attr("class","state-title").text(i.descriptions[0]).node().getBBox(),l=r.height,x=e.append("text").attr("x",t().state.padding).attr("y",l+t().state.padding*.4+t().state.dividerMargin+t().state.textHeight).attr("class","state-description");let a=!0,s=!0;i.descriptions.forEach(function(g){a||(d(x,g,s),s=!1),a=!1});const w=e.append("line").attr("x1",t().state.padding).attr("y1",t().state.padding+l+t().state.dividerMargin/2).attr("y2",t().state.padding+l+t().state.dividerMargin/2).attr("class","descr-divider"),p=x.node().getBBox(),o=Math.max(p.width,r.width);return w.attr("x2",o+3*t().state.padding),e.insert("rect",":first-child").attr("x",t().state.padding).attr("y",t().state.padding).attr("width",o+2*t().state.padding).attr("height",p.height+l+2*t().state.padding).attr("rx",t().state.radius),e},"drawDescrState"),$=f((e,i,d)=>{const c=t().state.padding,r=2*t().state.padding,l=e.node().getBBox(),x=l.width,a=l.x,s=e.append("text").attr("x",0).attr("y",t().state.titleShift).attr("font-size",t().state.fontSize).attr("class","state-title").text(i.id),p=s.node().getBBox().width+r;let o=Math.max(p,x);o===x&&(o=o+r);let g;const B=e.node().getBBox();i.doc,g=a-c,p>x&&(g=(x-o)/2+c),Math.abs(a-B.x)<c&&p>x&&(g=a-(p-x)/2);const m=1-t().state.textHeight;return e.insert("rect",":first-child").attr("x",g).attr("y",m).attr("class",d?"alt-composit":"composit").attr("width",o).attr("height",B.height+t().state.textHeight+t().state.titleShift+1).attr("rx","0"),s.attr("x",g+c),p<=x&&s.attr("x",a+(o-r)/2-p/2+c),e.insert("rect",":first-child").attr("x",g).attr("y",t().state.titleShift-t().state.textHeight-t().state.padding).attr("width",o).attr("height",t().state.textHeight*3).attr("rx",t().state.radius),e.insert("rect",":first-child").attr("x",g).attr("y",t().state.titleShift-t().state.textHeight-t().state.padding).attr("width",o).attr("height",B.height+3+2*t().state.textHeight).attr("rx",t().state.radius),e},"addTitleAndBox"),q=f(e=>(e.append("circle").attr("class","end-state-outer").attr("r",t().state.sizeUnit+t().state.miniPadding).attr("cx",t().state.padding+t().state.sizeUnit+t().state.miniPadding).attr("cy",t().state.padding+t().state.sizeUnit+t().state.miniPadding),e.append("circle").attr("class","end-state-inner").attr("r",t().state.sizeUnit).attr("cx",t().state.padding+t().state.sizeUnit+2).attr("cy",t().state.padding+t().state.sizeUnit+2)),"drawEndState"),Z=f((e,i)=>{let d=t().state.forkWidth,c=t().state.forkHeight;if(i.parentId){let r=d;d=c,c=r}return e.append("rect").style("stroke","black").style("fill","black").attr("width",d).attr("height",c).attr("x",t().state.padding).attr("y",t().state.padding)},"drawForkJoinState"),j=f((e,i,d,c)=>{let r=0;const l=c.append("text");l.style("text-anchor","start"),l.attr("class","noteText");let x=e.replace(/\r\n/g,"<br/>");x=x.replace(/\n/g,"<br/>");const a=x.split(z.lineBreakRegex);let s=1.25*t().state.noteMargin;for(const w of a){const p=w.trim();if(p.length>0){const o=l.append("tspan");if(o.text(p),s===0){const g=o.node().getBBox();s+=g.height}r+=s,o.attr("x",i+t().state.noteMargin),o.attr("y",d+r+1.25*t().state.noteMargin)}}return{textWidth:l.node().getBBox().width,textHeight:r}},"_drawLongText"),K=f((e,i)=>{i.attr("class","state-note");const d=i.append("rect").attr("x",0).attr("y",t().state.padding),c=i.append("g"),{textWidth:r,textHeight:l}=j(e,0,0,c);return d.attr("height",l+2*t().state.noteMargin),d.attr("width",r+t().state.noteMargin*2),d},"drawNote"),L=f(function(e,i){const d=i.id,c={id:d,label:i.id,width:0,height:0},r=e.append("g").attr("id",d).attr("class","stateGroup");i.type==="start"&&J(r),i.type==="end"&&q(r),(i.type==="fork"||i.type==="join")&&Z(r,i),i.type==="note"&&K(i.note.text,r),i.type==="divider"&&D(r),i.type==="default"&&i.descriptions.length===0&&Y(r,i),i.type==="default"&&i.descriptions.length>0&&I(r,i);const l=r.node().getBBox();return c.width=l.width+2*t().state.padding,c.height=l.height+2*t().state.padding,c},"drawState"),A=0,Q=f(function(e,i,d){const c=f(function(s){switch(s){case v.relationType.AGGREGATION:return"aggregation";case v.relationType.EXTENSION:return"extension";case v.relationType.COMPOSITION:return"composition";case v.relationType.DEPENDENCY:return"dependency"}},"getRelationType");i.points=i.points.filter(s=>!Number.isNaN(s.y));const r=i.points,l=U().x(function(s){return s.x}).y(function(s){return s.y}).curve(_),x=e.append("path").attr("d",l(r)).attr("id","edge"+A).attr("class","transition");let a="";if(t().state.arrowMarkerAbsolute&&(a=C(!0)),x.attr("marker-end","url("+a+"#"+c(v.relationType.DEPENDENCY)+"End)"),d.title!==void 0){const s=e.append("g").attr("class","stateLabel"),{x:w,y:p}=F.calcLabelPosition(i.points),o=z.getRows(d.title);let g=0;const B=[];let m=0,k=0;for(let u=0;u<=o.length;u++){const h=s.append("text").attr("text-anchor","middle").text(o[u]).attr("x",w).attr("y",p+g),y=h.node().getBBox();m=Math.max(m,y.width),k=Math.min(k,y.x),S.info(y.x,w,p+g),g===0&&(g=h.node().getBBox().height,S.info("Title height",g,p)),B.push(h)}let N=g*o.length;if(o.length>1){const u=(o.length-1)*g*.5;B.forEach((h,y)=>h.attr("y",p+y*g-u)),N=g*o.length}const n=s.node().getBBox();s.insert("rect",":first-child").attr("class","box").attr("x",w-m/2-t().state.padding/2).attr("y",p-N/2-t().state.padding/2-3.5).attr("width",m+t().state.padding).attr("height",N+t().state.padding),S.info(n)}A++},"drawEdge"),b,T={},V=f(function(){},"setConf"),tt=f(function(e){e.append("defs").append("marker").attr("id","dependencyEnd").attr("refX",19).attr("refY",7).attr("markerWidth",20).attr("markerHeight",28).attr("orient","auto").append("path").attr("d","M 19,7 L9,13 L14,7 L9,1 Z")},"insertMarkers"),et=f(function(e,i,d,c){b=t().state;const r=t().securityLevel;let l;r==="sandbox"&&(l=H("#i"+i));const x=r==="sandbox"?H(l.nodes()[0].contentDocument.body):H("body"),a=r==="sandbox"?l.nodes()[0].contentDocument:document;S.debug("Rendering diagram "+e);const s=x.select(`[id='${i}']`);tt(s);const w=c.db.getRootDoc();G(w,s,void 0,!1,x,a,c);const p=b.padding,o=s.node().getBBox(),g=o.width+p*2,B=o.height+p*2,m=g*1.75;P(s,B,m,b.useMaxWidth),s.attr("viewBox",`${o.x-b.padding}  ${o.y-b.padding} `+g+" "+B)},"draw"),at=f(e=>e?e.length*b.fontSizeFactor:1,"getLabelWidth"),G=f((e,i,d,c,r,l,x)=>{const a=new O({compound:!0,multigraph:!0});let s,w=!0;for(s=0;s<e.length;s++)if(e[s].stmt==="relation"){w=!1;break}d?a.setGraph({rankdir:"LR",multigraph:!0,compound:!0,ranker:"tight-tree",ranksep:w?1:b.edgeLengthFactor,nodeSep:w?1:50,isMultiGraph:!0}):a.setGraph({rankdir:"TB",multigraph:!0,compound:!0,ranksep:w?1:b.edgeLengthFactor,nodeSep:w?1:50,ranker:"tight-tree",isMultiGraph:!0}),a.setDefaultEdgeLabel(function(){return{}});const p=x.db.getStates(),o=x.db.getRelations(),g=Object.keys(p);for(const n of g){const u=p[n];d&&(u.parentId=d);let h;if(u.doc){let y=i.append("g").attr("id",u.id).attr("class","stateGroup");h=G(u.doc,y,u.id,!c,r,l,x);{y=$(y,u,c);let E=y.node().getBBox();h.width=E.width,h.height=E.height+b.padding/2,T[u.id]={y:b.compositTitleSize}}}else h=L(i,u,a);if(u.note){const y={descriptions:[],id:u.id+"-note",note:u.note,type:"note"},E=L(i,y,a);u.note.position==="left of"?(a.setNode(h.id+"-note",E),a.setNode(h.id,h)):(a.setNode(h.id,h),a.setNode(h.id+"-note",E)),a.setParent(h.id,h.id+"-group"),a.setParent(h.id+"-note",h.id+"-group")}else a.setNode(h.id,h)}S.debug("Count=",a.nodeCount(),a);let B=0;o.forEach(function(n){B++,S.debug("Setting edge",n),a.setEdge(n.id1,n.id2,{relation:n,width:at(n.title),height:b.labelHeight*z.getRows(n.title).length,labelpos:"c"},"id"+B)}),X(a),S.debug("Graph after layout",a.nodes());const m=i.node();a.nodes().forEach(function(n){n!==void 0&&a.node(n)!==void 0?(S.warn("Node "+n+": "+JSON.stringify(a.node(n))),r.select("#"+m.id+" #"+n).attr("transform","translate("+(a.node(n).x-a.node(n).width/2)+","+(a.node(n).y+(T[n]?T[n].y:0)-a.node(n).height/2)+" )"),r.select("#"+m.id+" #"+n).attr("data-x-shift",a.node(n).x-a.node(n).width/2),l.querySelectorAll("#"+m.id+" #"+n+" .divider").forEach(h=>{const y=h.parentElement;let E=0,M=0;y&&(y.parentElement&&(E=y.parentElement.getBBox().width),M=parseInt(y.getAttribute("data-x-shift"),10),Number.isNaN(M)&&(M=0)),h.setAttribute("x1",0-M+8),h.setAttribute("x2",E-M-8)})):S.debug("No Node "+n+": "+JSON.stringify(a.node(n)))});let k=m.getBBox();a.edges().forEach(function(n){n!==void 0&&a.edge(n)!==void 0&&(S.debug("Edge "+n.v+" -> "+n.w+": "+JSON.stringify(a.edge(n))),Q(i,a.edge(n),a.edge(n).relation))}),k=m.getBBox();const N={id:d||"root",label:d||"root",width:0,height:0};return N.width=k.width+2*b.padding,N.height=k.height+2*b.padding,S.debug("Doc rendered",N,a),N},"renderDoc"),it={setConf:V,draw:et},yt={parser:W,get db(){return new v(1)},renderer:it,styles:R,init:f(e=>{e.state||(e.state={}),e.state.arrowMarkerAbsolute=e.arrowMarkerAbsolute},"init")};export{yt as diagram};
diff --git a/lightrag/api/webui/assets/stateDiagram-v2-5AN5P6BG-C8y_3sB0.js b/lightrag/api/webui/assets/stateDiagram-v2-5AN5P6BG-DkT60tdC.js
similarity index 52%
rename from lightrag/api/webui/assets/stateDiagram-v2-5AN5P6BG-C8y_3sB0.js
rename to lightrag/api/webui/assets/stateDiagram-v2-5AN5P6BG-DkT60tdC.js
index cd2bb5d2..c2d5620c 100644
--- a/lightrag/api/webui/assets/stateDiagram-v2-5AN5P6BG-C8y_3sB0.js
+++ b/lightrag/api/webui/assets/stateDiagram-v2-5AN5P6BG-DkT60tdC.js
@@ -1 +1 @@
-import{s as r,b as e,a,S as i}from"./chunk-OW32GOEJ-Bpuvralp.js";import{_ as s}from"./mermaid-vendor-CAxUo7Zk.js";import"./chunk-BFAMUDN2-DQGv_fhY.js";import"./chunk-SKB7J2MH-D-vU5iV6.js";import"./feature-graph-C6IuADHZ.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var f={parser:a,get db(){return new i(2)},renderer:e,styles:r,init:s(t=>{t.state||(t.state={}),t.state.arrowMarkerAbsolute=t.arrowMarkerAbsolute},"init")};export{f as diagram};
+import{s as r,b as e,a,S as i}from"./chunk-OW32GOEJ-C5pOkIhC.js";import{_ as s}from"./mermaid-vendor-B20mDgAo.js";import"./chunk-BFAMUDN2-Cm57CA8s.js";import"./chunk-SKB7J2MH-CX-6qXaF.js";import"./feature-graph-CS4MyqEv.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var f={parser:a,get db(){return new i(2)},renderer:e,styles:r,init:s(t=>{t.state||(t.state={}),t.state.arrowMarkerAbsolute=t.arrowMarkerAbsolute},"init")};export{f as diagram};
diff --git a/lightrag/api/webui/assets/timeline-definition-MYPXXCX6-D9VjsU9f.js b/lightrag/api/webui/assets/timeline-definition-MYPXXCX6-CXabRGVZ.js
similarity index 99%
rename from lightrag/api/webui/assets/timeline-definition-MYPXXCX6-D9VjsU9f.js
rename to lightrag/api/webui/assets/timeline-definition-MYPXXCX6-CXabRGVZ.js
index 482a6f75..e0d57bc2 100644
--- a/lightrag/api/webui/assets/timeline-definition-MYPXXCX6-D9VjsU9f.js
+++ b/lightrag/api/webui/assets/timeline-definition-MYPXXCX6-CXabRGVZ.js
@@ -1,4 +1,4 @@
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+import{_ as s,c as xt,l as E,d as q,a3 as kt,a4 as _t,a5 as bt,a6 as vt,N as nt,D as wt,a7 as St,z as Et}from"./mermaid-vendor-B20mDgAo.js";import"./feature-graph-CS4MyqEv.js";import"./react-vendor-DEwriMA6.js";import"./graph-vendor-B-X5JegA.js";import"./ui-vendor-CeCm8EER.js";import"./utils-vendor-BysuhMZA.js";var X=function(){var n=s(function(f,r,a,h){for(a=a||{},h=f.length;h--;a[f[h]]=r);return a},"o"),t=[6,8,10,11,12,14,16,17,20,21],e=[1,9],l=[1,10],i=[1,11],d=[1,12],c=[1,13],g=[1,16],m=[1,17],p={trace:s(function(){},"trace"),yy:{},symbols_:{error:2,start:3,timeline:4,document:5,EOF:6,line:7,SPACE:8,statement:9,NEWLINE:10,title:11,acc_title:12,acc_title_value:13,acc_descr:14,acc_descr_value:15,acc_descr_multiline_value:16,section:17,period_statement:18,event_statement:19,period:20,event:21,$accept:0,$end:1},terminals_:{2:"error",4:"timeline",6:"EOF",8:"SPACE",10:"NEWLINE",11:"title",12:"acc_title",13:"acc_title_value",14:"acc_descr",15:"acc_descr_value",16:"acc_descr_multiline_value",17:"section",20:"period",21:"event"},productions_:[0,[3,3],[5,0],[5,2],[7,2],[7,1],[7,1],[7,1],[9,1],[9,2],[9,2],[9,1],[9,1],[9,1],[9,1],[18,1],[19,1]],performAction:s(function(r,a,h,u,y,o,S){var k=o.length-1;switch(y){case 1:return o[k-1];case 2:this.$=[];break;case 3:o[k-1].push(o[k]),this.$=o[k-1];break;case 4:case 5:this.$=o[k];break;case 6:case 7:this.$=[];break;case 8:u.getCommonDb().setDiagramTitle(o[k].substr(6)),this.$=o[k].substr(6);break;case 9:this.$=o[k].trim(),u.getCommonDb().setAccTitle(this.$);break;case 10:case 11:this.$=o[k].trim(),u.getCommonDb().setAccDescription(this.$);break;case 12:u.addSection(o[k].substr(8)),this.$=o[k].substr(8);break;case 15:u.addTask(o[k],0,""),this.$=o[k];break;case 16:u.addEvent(o[k].substr(2)),this.$=o[k];break}},"anonymous"),table:[{3:1,4:[1,2]},{1:[3]},n(t,[2,2],{5:3}),{6:[1,4],7:5,8:[1,6],9:7,10:[1,8],11:e,12:l,14:i,16:d,17:c,18:14,19:15,20:g,21:m},n(t,[2,7],{1:[2,1]}),n(t,[2,3]),{9:18,11:e,12:l,14:i,16:d,17:c,18:14,19:15,20:g,21:m},n(t,[2,5]),n(t,[2,6]),n(t,[2,8]),{13:[1,19]},{15:[1,20]},n(t,[2,11]),n(t,[2,12]),n(t,[2,13]),n(t,[2,14]),n(t,[2,15]),n(t,[2,16]),n(t,[2,4]),n(t,[2,9]),n(t,[2,10])],defaultActions:{},parseError:s(function(r,a){if(a.recoverable)this.trace(r);else{var h=new Error(r);throw h.hash=a,h}},"parseError"),parse:s(function(r){var a=this,h=[0],u=[],y=[null],o=[],S=this.table,k="",M=0,C=0,B=2,J=1,O=o.slice.call(arguments,1),_=Object.create(this.lexer),N={yy:{}};for(var L in this.yy)Object.prototype.hasOwnProperty.call(this.yy,L)&&(N.yy[L]=this.yy[L]);_.setInput(r,N.yy),N.yy.lexer=_,N.yy.parser=this,typeof _.yylloc>"u"&&(_.yylloc={});var v=_.yylloc;o.push(v);var $=_.options&&_.options.ranges;typeof N.yy.parseError=="function"?this.parseError=N.yy.parseError:this.parseError=Object.getPrototypeOf(this).parseError;function R(T){h.length=h.length-2*T,y.length=y.length-T,o.length=o.length-T}s(R,"popStack");function A(){var T;return T=u.pop()||_.lex()||J,typeof T!="number"&&(T instanceof Array&&(u=T,T=u.pop()),T=a.symbols_[T]||T),T}s(A,"lex");for(var w,H,I,K,F={},j,P,et,G;;){if(H=h[h.length-1],this.defaultActions[H]?I=this.defaultActions[H]:((w===null||typeof w>"u")&&(w=A()),I=S[H]&&S[H][w]),typeof I>"u"||!I.length||!I[0]){var Q="";G=[];for(j in S[H])this.terminals_[j]&&j>B&&G.push("'"+this.terminals_[j]+"'");_.showPosition?Q="Parse error on line "+(M+1)+`:
 `+_.showPosition()+`
 Expecting `+G.join(", ")+", got '"+(this.terminals_[w]||w)+"'":Q="Parse error on line "+(M+1)+": Unexpected "+(w==J?"end of input":"'"+(this.terminals_[w]||w)+"'"),this.parseError(Q,{text:_.match,token:this.terminals_[w]||w,line:_.yylineno,loc:v,expected:G})}if(I[0]instanceof Array&&I.length>1)throw new Error("Parse Error: multiple actions possible at state: "+H+", token: "+w);switch(I[0]){case 1:h.push(w),y.push(_.yytext),o.push(_.yylloc),h.push(I[1]),w=null,C=_.yyleng,k=_.yytext,M=_.yylineno,v=_.yylloc;break;case 2:if(P=this.productions_[I[1]][1],F.$=y[y.length-P],F._$={first_line:o[o.length-(P||1)].first_line,last_line:o[o.length-1].last_line,first_column:o[o.length-(P||1)].first_column,last_column:o[o.length-1].last_column},$&&(F._$.range=[o[o.length-(P||1)].range[0],o[o.length-1].range[1]]),K=this.performAction.apply(F,[k,C,M,N.yy,I[1],y,o].concat(O)),typeof K<"u")return K;P&&(h=h.slice(0,-1*P*2),y=y.slice(0,-1*P),o=o.slice(0,-1*P)),h.push(this.productions_[I[1]][0]),y.push(F.$),o.push(F._$),et=S[h[h.length-2]][h[h.length-1]],h.push(et);break;case 3:return!0}}return!0},"parse")},x=function(){var f={EOF:1,parseError:s(function(a,h){if(this.yy.parser)this.yy.parser.parseError(a,h);else throw new Error(a)},"parseError"),setInput:s(function(r,a){return this.yy=a||this.yy||{},this._input=r,this._more=this._backtrack=this.done=!1,this.yylineno=this.yyleng=0,this.yytext=this.matched=this.match="",this.conditionStack=["INITIAL"],this.yylloc={first_line:1,first_column:0,last_line:1,last_column:0},this.options.ranges&&(this.yylloc.range=[0,0]),this.offset=0,this},"setInput"),input:s(function(){var r=this._input[0];this.yytext+=r,this.yyleng++,this.offset++,this.match+=r,this.matched+=r;var a=r.match(/(?:\r\n?|\n).*/g);return a?(this.yylineno++,this.yylloc.last_line++):this.yylloc.last_column++,this.options.ranges&&this.yylloc.range[1]++,this._input=this._input.slice(1),r},"input"),unput:s(function(r){var a=r.length,h=r.split(/(?:\r\n?|\n)/g);this._input=r+this._input,this.yytext=this.yytext.substr(0,this.yytext.length-a),this.offset-=a;var u=this.match.split(/(?:\r\n?|\n)/g);this.match=this.match.substr(0,this.match.length-1),this.matched=this.matched.substr(0,this.matched.length-1),h.length-1&&(this.yylineno-=h.length-1);var y=this.yylloc.range;return this.yylloc={first_line:this.yylloc.first_line,last_line:this.yylineno+1,first_column:this.yylloc.first_column,last_column:h?(h.length===u.length?this.yylloc.first_column:0)+u[u.length-h.length].length-h[0].length:this.yylloc.first_column-a},this.options.ranges&&(this.yylloc.range=[y[0],y[0]+this.yyleng-a]),this.yyleng=this.yytext.length,this},"unput"),more:s(function(){return this._more=!0,this},"more"),reject:s(function(){if(this.options.backtrack_lexer)this._backtrack=!0;else return this.parseError("Lexical error on line "+(this.yylineno+1)+`. You can only invoke reject() in the lexer when the lexer is of the backtracking persuasion (options.backtrack_lexer = true).
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diff --git a/lightrag/api/webui/assets/treemap-75Q7IDZK-BAguqzAo.js b/lightrag/api/webui/assets/treemap-75Q7IDZK-64OceOGQ.js
similarity index 99%
rename from lightrag/api/webui/assets/treemap-75Q7IDZK-BAguqzAo.js
rename to lightrag/api/webui/assets/treemap-75Q7IDZK-64OceOGQ.js
index cf057937..eb5ddf39 100644
--- a/lightrag/api/webui/assets/treemap-75Q7IDZK-BAguqzAo.js
+++ b/lightrag/api/webui/assets/treemap-75Q7IDZK-64OceOGQ.js
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t.properties)i.defaultValue!==void 0&&r[i.name]===void 0&&(r[i.name]=jl(i.defaultValue))}function jl(n){return Array.isArray(n)?[...n.map(jl)]:n}function w(n){return n.charCodeAt(0)}function Mi(n,e){Array.isArray(n)?n.forEach(function(t){e.push(t)}):e.push(n)}function cn(n,e){if(n[e]===!0)throw"duplicate flag "+e;n[e],n[e]=!0}function Nt(n){if(n===void 0)throw Error("Internal Error - Should never get here!");return!0}function jd(){throw Error("Internal Error - Should never get here!")}function xa(n){return n.type==="Character"}const zr=[];for(let n=w("0");n<=w("9");n++)zr.push(n);const qr=[w("_")].concat(zr);for(let n=w("a");n<=w("z");n++)qr.push(n);for(let n=w("A");n<=w("Z");n++)qr.push(n);const Sa=[w(" "),w("\f"),w(`
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diff --git a/lightrag/api/webui/assets/xychartDiagram-H2YORKM3-DFgYCTGU.js b/lightrag/api/webui/assets/xychartDiagram-H2YORKM3-Dlbi025A.js
similarity index 99%
rename from lightrag/api/webui/assets/xychartDiagram-H2YORKM3-DFgYCTGU.js
rename to lightrag/api/webui/assets/xychartDiagram-H2YORKM3-Dlbi025A.js
index 23ef427e..8055086b 100644
--- a/lightrag/api/webui/assets/xychartDiagram-H2YORKM3-DFgYCTGU.js
+++ b/lightrag/api/webui/assets/xychartDiagram-H2YORKM3-Dlbi025A.js
@@ -1,4 +1,4 @@
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diff --git a/lightrag/api/webui/index.html b/lightrag/api/webui/index.html
index dc486f54..2d6aa50d 100644
--- a/lightrag/api/webui/index.html
+++ b/lightrag/api/webui/index.html
@@ -8,16 +8,16 @@
     <link rel="icon" type="image/png" href="favicon.png" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>Lightrag</title>
-    <script type="module" crossorigin src="/webui/assets/index-DI6XUmEl.js"></script>
+    <script type="module" crossorigin src="/webui/assets/index-CIdJpUuC.js"></script>
     <link rel="modulepreload" crossorigin href="/webui/assets/react-vendor-DEwriMA6.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/ui-vendor-CeCm8EER.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/graph-vendor-B-X5JegA.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/utils-vendor-BysuhMZA.js">
-    <link rel="modulepreload" crossorigin href="/webui/assets/feature-graph-C6IuADHZ.js">
-    <link rel="modulepreload" crossorigin href="/webui/assets/feature-documents-DLarjU2a.js">
-    <link rel="modulepreload" crossorigin href="/webui/assets/mermaid-vendor-CAxUo7Zk.js">
+    <link rel="modulepreload" crossorigin href="/webui/assets/feature-graph-CS4MyqEv.js">
+    <link rel="modulepreload" crossorigin href="/webui/assets/feature-documents-4TV9qUPI.js">
+    <link rel="modulepreload" crossorigin href="/webui/assets/mermaid-vendor-B20mDgAo.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/markdown-vendor-DmIvJdn7.js">
-    <link rel="modulepreload" crossorigin href="/webui/assets/feature-retrieval-P5Qspbob.js">
+    <link rel="modulepreload" crossorigin href="/webui/assets/feature-retrieval-BwXSap2b.js">
     <link rel="stylesheet" crossorigin href="/webui/assets/feature-graph-BipNuM18.css">
     <link rel="stylesheet" crossorigin href="/webui/assets/index-CafJWW1u.css">
   </head>

From 69890ff2e15768d4d375f55975cf07f2f0043cbb Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 31 Aug 2025 03:01:33 +0800
Subject: [PATCH 087/141] Bump core version to 1.4.8 and api version to 0210

---
 lightrag/__init__.py     | 2 +-
 lightrag/api/__init__.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/lightrag/__init__.py b/lightrag/__init__.py
index 2df8a046..c10bea8d 100644
--- a/lightrag/__init__.py
+++ b/lightrag/__init__.py
@@ -1,5 +1,5 @@
 from .lightrag import LightRAG as LightRAG, QueryParam as QueryParam
 
-__version__ = "1.4.7"
+__version__ = "1.4.8"
 __author__ = "Zirui Guo"
 __url__ = "https://github.com/HKUDS/LightRAG"
diff --git a/lightrag/api/__init__.py b/lightrag/api/__init__.py
index 5a6845a8..5ae0d6ba 100644
--- a/lightrag/api/__init__.py
+++ b/lightrag/api/__init__.py
@@ -1 +1 @@
-__api_version__ = "0209"
+__api_version__ = "0210"

From d4bbc5dea9f0774c9662d7d14d9443f96508f8ef Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 31 Aug 2025 10:36:56 +0800
Subject: [PATCH 088/141] refactor: Merge multi-step text sanitization into
 single function

---
 lightrag/operate.py | 49 ++++++++++++---------------------------------
 lightrag/utils.py   | 40 ++++++++++++++++++++----------------
 2 files changed, 36 insertions(+), 53 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index afa8205f..b83790ab 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -11,11 +11,10 @@ from collections import Counter, defaultdict
 
 from .utils import (
     logger,
-    clean_str,
     compute_mdhash_id,
     Tokenizer,
     is_float_regex,
-    normalize_extracted_info,
+    sanitize_and_normalize_extracted_text,
     pack_user_ass_to_openai_messages,
     split_string_by_multi_markers,
     truncate_list_by_token_size,
@@ -31,7 +30,6 @@ from .utils import (
     pick_by_vector_similarity,
     process_chunks_unified,
     build_file_path,
-    sanitize_text_for_encoding,
 )
 from .base import (
     BaseGraphStorage,
@@ -320,14 +318,9 @@ async def _handle_single_entity_extraction(
         return None
 
     try:
-        # Step 1: Strict UTF-8 encoding sanitization (fail-fast approach)
-        entity_name = sanitize_text_for_encoding(record_attributes[1])
-
-        # Step 2: HTML and control character cleaning
-        entity_name = clean_str(entity_name).strip()
-
-        # Step 3: Business logic normalization
-        entity_name = normalize_extracted_info(entity_name, is_entity=True)
+        entity_name = sanitize_and_normalize_extracted_text(
+            record_attributes[1], is_entity=True
+        )
 
         # Validate entity name after all cleaning steps
         if not entity_name or not entity_name.strip():
@@ -337,8 +330,8 @@ async def _handle_single_entity_extraction(
             return None
 
         # Process entity type with same cleaning pipeline
-        entity_type = sanitize_text_for_encoding(record_attributes[2])
-        entity_type = clean_str(entity_type).strip('"')
+        entity_type = sanitize_and_normalize_extracted_text(record_attributes[2])
+
         if not entity_type.strip() or entity_type.startswith('("'):
             logger.warning(
                 f"Entity extraction error: invalid entity type in: {record_attributes}"
@@ -346,9 +339,7 @@ async def _handle_single_entity_extraction(
             return None
 
         # Process entity description with same cleaning pipeline
-        entity_description = sanitize_text_for_encoding(record_attributes[3])
-        entity_description = clean_str(entity_description)
-        entity_description = normalize_extracted_info(entity_description)
+        entity_description = sanitize_and_normalize_extracted_text(record_attributes[3])
 
         if not entity_description.strip():
             logger.warning(
@@ -385,27 +376,17 @@ async def _handle_single_relationship_extraction(
         return None
 
     try:
-        # Process source and target entities with strict cleaning pipeline
-        # Step 1: Strict UTF-8 encoding sanitization (fail-fast approach)
-        source = sanitize_text_for_encoding(record_attributes[1])
-        # Step 2: HTML and control character cleaning
-        source = clean_str(source)
-        # Step 3: Business logic normalization
-        source = normalize_extracted_info(source, is_entity=True)
-
-        # Same pipeline for target entity
-        target = sanitize_text_for_encoding(record_attributes[2])
-        target = clean_str(target)
-        target = normalize_extracted_info(target, is_entity=True)
+        source = sanitize_and_normalize_extracted_text(record_attributes[1])
+        target = sanitize_and_normalize_extracted_text(record_attributes[2])
 
         # Validate entity names after all cleaning steps
-        if not source or not source.strip():
+        if not source:
             logger.warning(
                 f"Relationship extraction error: source entity became empty after cleaning. Original: '{record_attributes[1]}'"
             )
             return None
 
-        if not target or not target.strip():
+        if not target:
             logger.warning(
                 f"Relationship extraction error: target entity became empty after cleaning. Original: '{record_attributes[2]}'"
             )
@@ -418,14 +399,10 @@ async def _handle_single_relationship_extraction(
             return None
 
         # Process relationship description with same cleaning pipeline
-        edge_description = sanitize_text_for_encoding(record_attributes[3])
-        edge_description = clean_str(edge_description)
-        edge_description = normalize_extracted_info(edge_description)
+        edge_description = sanitize_and_normalize_extracted_text(record_attributes[3])
 
         # Process keywords with same cleaning pipeline
-        edge_keywords = sanitize_text_for_encoding(record_attributes[4])
-        edge_keywords = clean_str(edge_keywords)
-        edge_keywords = normalize_extracted_info(edge_keywords, is_entity=True)
+        edge_keywords = sanitize_and_normalize_extracted_text(record_attributes[4])
         edge_keywords = edge_keywords.replace("，", ",")
 
         edge_source_id = chunk_key
diff --git a/lightrag/utils.py b/lightrag/utils.py
index 87ce5b6a..82a7cce4 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -931,19 +931,6 @@ def split_string_by_multi_markers(content: str, markers: list[str]) -> list[str]
     return [r.strip() for r in results if r.strip()]
 
 
-# Refer the utils functions of the official GraphRAG implementation:
-# https://github.com/microsoft/graphrag
-def clean_str(input: Any) -> str:
-    """Clean an input string by removing HTML escapes, control characters, and other unwanted characters."""
-    # If we get non-string input, just give it back
-    if not isinstance(input, str):
-        return input
-
-    result = html.unescape(input.strip())
-    # https://stackoverflow.com/questions/4324790/removing-control-characters-from-a-string-in-python
-    return re.sub(r"[\x00-\x1f\x7f-\x9f]", "", result)
-
-
 def is_float_regex(value: str) -> bool:
     return bool(re.match(r"^[-+]?[0-9]*\.?[0-9]+$", value))
 
@@ -1728,6 +1715,20 @@ def get_content_summary(content: str, max_length: int = 250) -> str:
     return content[:max_length] + "..."
 
 
+def sanitize_and_normalize_extracted_text(input_text: str, is_name=False) -> str:
+    """Santitize and normalize extracted text
+    Args:
+        input_text: text string to be processed
+        is_name: whether the input text is a entity or relation name
+
+    Returns:
+        Santitized and normalized text string
+    """
+    safe_input_text = sanitize_text_for_encoding(input_text)
+    normalized_text = normalize_extracted_info(safe_input_text, is_name)
+    return normalized_text
+
+
 def normalize_extracted_info(name: str, is_entity=False) -> str:
     """Normalize entity/relation names and description with the following rules:
     1. Remove spaces between Chinese characters
@@ -1789,6 +1790,8 @@ def sanitize_text_for_encoding(text: str, replacement_char: str = "") -> str:
     - Surrogate characters (the main cause of encoding errors)
     - Other invalid Unicode sequences
     - Control characters that might cause issues
+    - Unescape HTML escapes
+    - Remove control characters
     - Whitespace trimming
 
     Args:
@@ -1801,9 +1804,6 @@ def sanitize_text_for_encoding(text: str, replacement_char: str = "") -> str:
     Raises:
         ValueError: When text contains uncleanable encoding issues that cannot be safely processed
     """
-    if not isinstance(text, str):
-        return str(text)
-
     if not text:
         return text
 
@@ -1845,7 +1845,13 @@ def sanitize_text_for_encoding(text: str, replacement_char: str = "") -> str:
         # Test final encoding to ensure it's safe
         sanitized.encode("utf-8")
 
-        return sanitized
+        # Unescape HTML escapes
+        sanitized = html.unescape(sanitized)
+
+        # Remove control characters
+        sanitized = re.sub(r"[\x00-\x1f\x7f-\x9f]", "", sanitized)
+
+        return sanitized.strip()
 
     except UnicodeEncodeError as e:
         # Critical change: Don't return placeholder, raise exception for caller to handle

From b7474179612a1e7a574b0bf0a64367f36436985e Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 31 Aug 2025 13:17:20 +0800
Subject: [PATCH 089/141] feat: enhance text extraction text sanitization and
 normalization

- Improve reduntant quotes in entity and relation name, type and keywords
- Add HTML tag cleaning and Chinese symbol conversion
- Filter out short numeric content and malformed text
- Enhance entity type validation with character filtering
---
 lightrag/operate.py |  22 ++++++---
 lightrag/utils.py   | 111 ++++++++++++++++++++++++++++++++++++--------
 2 files changed, 108 insertions(+), 25 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index b83790ab..4fa5ddb1 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -319,7 +319,7 @@ async def _handle_single_entity_extraction(
 
     try:
         entity_name = sanitize_and_normalize_extracted_text(
-            record_attributes[1], is_entity=True
+            record_attributes[1], remove_inner_quotes=True
         )
 
         # Validate entity name after all cleaning steps
@@ -330,9 +330,13 @@ async def _handle_single_entity_extraction(
             return None
 
         # Process entity type with same cleaning pipeline
-        entity_type = sanitize_and_normalize_extracted_text(record_attributes[2])
+        entity_type = sanitize_and_normalize_extracted_text(
+            record_attributes[2], remove_inner_quotes=True
+        )
 
-        if not entity_type.strip() or entity_type.startswith('("'):
+        if not entity_type.strip() or any(
+            char in entity_type for char in ["'", "(", ")", "<", ">", "|", "/", "\\"]
+        ):
             logger.warning(
                 f"Entity extraction error: invalid entity type in: {record_attributes}"
             )
@@ -376,8 +380,12 @@ async def _handle_single_relationship_extraction(
         return None
 
     try:
-        source = sanitize_and_normalize_extracted_text(record_attributes[1])
-        target = sanitize_and_normalize_extracted_text(record_attributes[2])
+        source = sanitize_and_normalize_extracted_text(
+            record_attributes[1], remove_inner_quotes=True
+        )
+        target = sanitize_and_normalize_extracted_text(
+            record_attributes[2], remove_inner_quotes=True
+        )
 
         # Validate entity names after all cleaning steps
         if not source:
@@ -402,7 +410,9 @@ async def _handle_single_relationship_extraction(
         edge_description = sanitize_and_normalize_extracted_text(record_attributes[3])
 
         # Process keywords with same cleaning pipeline
-        edge_keywords = sanitize_and_normalize_extracted_text(record_attributes[4])
+        edge_keywords = sanitize_and_normalize_extracted_text(
+            record_attributes[4], remove_inner_quotes=True
+        )
         edge_keywords = edge_keywords.replace("，", ",")
 
         edge_source_id = chunk_key
diff --git a/lightrag/utils.py b/lightrag/utils.py
index 82a7cce4..9dc5a5b2 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -1715,7 +1715,9 @@ def get_content_summary(content: str, max_length: int = 250) -> str:
     return content[:max_length] + "..."
 
 
-def sanitize_and_normalize_extracted_text(input_text: str, is_name=False) -> str:
+def sanitize_and_normalize_extracted_text(
+    input_text: str, remove_inner_quotes=False
+) -> str:
     """Santitize and normalize extracted text
     Args:
         input_text: text string to be processed
@@ -1725,33 +1727,66 @@ def sanitize_and_normalize_extracted_text(input_text: str, is_name=False) -> str
         Santitized and normalized text string
     """
     safe_input_text = sanitize_text_for_encoding(input_text)
-    normalized_text = normalize_extracted_info(safe_input_text, is_name)
-    return normalized_text
+    if safe_input_text:
+        normalized_text = normalize_extracted_info(
+            safe_input_text, remove_inner_quotes=remove_inner_quotes
+        )
+        return normalized_text
+    return ""
 
 
-def normalize_extracted_info(name: str, is_entity=False) -> str:
+def normalize_extracted_info(name: str, remove_inner_quotes=False) -> str:
     """Normalize entity/relation names and description with the following rules:
-    1. Remove spaces between Chinese characters
-    2. Remove spaces between Chinese characters and English letters/numbers
-    3. Preserve spaces within English text and numbers
-    4. Replace Chinese parentheses with English parentheses
-    5. Replace Chinese dash with English dash
-    6. Remove English quotation marks from the beginning and end of the text
-    7. Remove English quotation marks in and around chinese
-    8. Remove Chinese quotation marks
+    1. Clean HTML tags (paragraph and line break tags)
+    2. Convert Chinese symbols to English symbols
+    3. Remove spaces between Chinese characters
+    4. Remove spaces between Chinese characters and English letters/numbers
+    5. Preserve spaces within English text and numbers
+    6. Replace Chinese parentheses with English parentheses
+    7. Replace Chinese dash with English dash
+    8. Remove English quotation marks from the beginning and end of the text
+    9. Remove English quotation marks in and around chinese
+    10. Remove Chinese quotation marks
+    11. Filter out short numeric-only text (length < 3 and only digits/dots)
 
     Args:
         name: Entity name to normalize
+        is_entity: Whether this is an entity name (affects quote handling)
 
     Returns:
         Normalized entity name
     """
+    # 1. Clean HTML tags - remove paragraph and line break tags
+    name = re.sub(r"</p\s*>|<p\s*>|<p/>", "", name, flags=re.IGNORECASE)
+    name = re.sub(r"</br\s*>|<br\s*>|<br/>", "", name, flags=re.IGNORECASE)
+
+    # 2. Convert Chinese symbols to English symbols
+    # Chinese full-width letters to half-width (A-Z, a-z)
+    name = name.translate(
+        str.maketrans(
+            "ＡＢＣＤＥＦＧＨＩＪＫＬＭＮＯＰＱＲＳＴＵＶＷＸＹＺａｂｃｄｅｆｇｈｉｊｋｌｍｎｏｐｑｒｓｔｕｖｗｘｙｚ",
+            "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz",
+        )
+    )
+
+    # Chinese full-width numbers to half-width
+    name = name.translate(str.maketrans("０１２３４５６７８９", "0123456789"))
+
+    # Chinese full-width symbols to half-width
+    name = name.replace("－", "-")  # Chinese minus
+    name = name.replace("＋", "+")  # Chinese plus
+    name = name.replace("／", "/")  # Chinese slash
+    name = name.replace("＊", "*")  # Chinese asterisk
+
     # Replace Chinese parentheses with English parentheses
     name = name.replace("（", "(").replace("）", ")")
 
-    # Replace Chinese dash with English dash
+    # Replace Chinese dash with English dash (additional patterns)
     name = name.replace("—", "-").replace("－", "-")
 
+    # Chinese full-width space to regular space (after other replacements)
+    name = name.replace("　", " ")
+
     # Use regex to remove spaces between Chinese characters
     # Regex explanation:
     # (?<=[\u4e00-\u9fa5]): Positive lookbehind for Chinese character
@@ -1767,19 +1802,57 @@ def normalize_extracted_info(name: str, is_entity=False) -> str:
         r"(?<=[a-zA-Z0-9\(\)\[\]@#$%!&\*\-=+_])\s+(?=[\u4e00-\u9fa5])", "", name
     )
 
-    # Remove English quotation marks from the beginning and end
-    if len(name) >= 2 and name.startswith('"') and name.endswith('"'):
-        name = name[1:-1]
-    if len(name) >= 2 and name.startswith("'") and name.endswith("'"):
-        name = name[1:-1]
+    # Remove outer quotes
+    if len(name) >= 2:
+        # Handle double quotes
+        if name.startswith('"') and name.endswith('"'):
+            inner_content = name[1:-1]
+            if '"' not in inner_content:  # No double quotes inside
+                name = inner_content
 
-    if is_entity:
+        # Handle single quotes
+        if name.startswith("'") and name.endswith("'"):
+            inner_content = name[1:-1]
+            if "'" not in inner_content:  # No single quotes inside
+                name = inner_content
+
+        # Handle Chinese-style double quotes
+        if name.startswith("“") and name.endswith("”"):
+            inner_content = name[1:-1]
+            if "“" not in inner_content and "”" not in inner_content:
+                name = inner_content
+        if name.startswith("‘") and name.endswith("’"):
+            inner_content = name[1:-1]
+            if "‘" not in inner_content and "’" not in inner_content:
+                name = inner_content
+
+    if remove_inner_quotes:
         # remove Chinese quotes
         name = name.replace("“", "").replace("”", "").replace("‘", "").replace("’", "")
         # remove English queotes in and around chinese
         name = re.sub(r"['\"]+(?=[\u4e00-\u9fa5])", "", name)
         name = re.sub(r"(?<=[\u4e00-\u9fa5])['\"]+", "", name)
 
+    # Remove spaces from the beginning and end of the text
+    name = name.strip()
+
+    # Filter out pure numeric content with length < 3
+    if len(name) < 3 and re.match(r"^[0-9]+$", name):
+        return ""
+
+    def should_filter_by_dots(text):
+        """
+        Check if the string consists only of dots and digits, with at least one dot
+        Filter cases include: 1.2.3, 12.3, .123, 123., 12.3., .1.23 etc.
+        """
+        return all(c.isdigit() or c == "." for c in text) and "." in text
+
+    if len(name) < 6 and should_filter_by_dots(name):
+        # Filter out mixed numeric and dot content with length < 6
+        return ""
+        # Filter out mixed numeric and dot content with length < 6, requiring at least one dot
+        return ""
+
     return name
 
 

From 97c9600085c400131808ea485aae77356781f688 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 31 Aug 2025 17:33:42 +0800
Subject: [PATCH 090/141] Improve extraction error handling and field
 validation
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Add field count validation warnings
• Fix relationship field count (5→6)
• Change error logs to warnings
---
 lightrag/operate.py | 16 +++++++++++++---
 1 file changed, 13 insertions(+), 3 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 4fa5ddb1..5bcd75ad 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -315,6 +315,11 @@ async def _handle_single_entity_extraction(
     file_path: str = "unknown_source",
 ):
     if len(record_attributes) < 4 or '"entity"' not in record_attributes[0]:
+        if len(record_attributes) > 1 and '"entity"' in record_attributes[0]:
+            logger.warning(
+                f"Entity extraction failed in {chunk_key}: expecting 4 fields but got {len(record_attributes)}"
+            )
+            logger.warning(f"Entity extracted: {record_attributes[1]}")
         return None
 
     try:
@@ -376,7 +381,12 @@ async def _handle_single_relationship_extraction(
     chunk_key: str,
     file_path: str = "unknown_source",
 ):
-    if len(record_attributes) < 5 or '"relationship"' not in record_attributes[0]:
+    if len(record_attributes) < 6 or '"relationship"' not in record_attributes[0]:
+        if len(record_attributes) > 1 and '"relationship"' in record_attributes[0]:
+            logger.warning(
+                f"Relationship extraction failed in {chunk_key}: expecting 6 fields but got {len(record_attributes)}"
+            )
+            logger.warning(f"Relationship extracted: {record_attributes[1]}")
         return None
 
     try:
@@ -433,12 +443,12 @@ async def _handle_single_relationship_extraction(
         )
 
     except ValueError as e:
-        logger.error(
+        logger.warning(
             f"Relationship extraction failed due to encoding issues in chunk {chunk_key}: {e}"
         )
         return None
     except Exception as e:
-        logger.error(
+        logger.warning(
             f"Relationship extraction failed with unexpected error in chunk {chunk_key}: {e}"
         )
         return None

From 75de40da41ad5af2c12bf321b5b95b8ba5fd0025 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 31 Aug 2025 17:45:16 +0800
Subject: [PATCH 091/141] Fix typo in relationship extraction log messages

---
 lightrag/operate.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 5bcd75ad..b8dd8bb8 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -384,9 +384,9 @@ async def _handle_single_relationship_extraction(
     if len(record_attributes) < 6 or '"relationship"' not in record_attributes[0]:
         if len(record_attributes) > 1 and '"relationship"' in record_attributes[0]:
             logger.warning(
-                f"Relationship extraction failed in {chunk_key}: expecting 6 fields but got {len(record_attributes)}"
+                f"Relation extraction failed in {chunk_key}: expecting 6 fields but got {len(record_attributes)}"
             )
-            logger.warning(f"Relationship extracted: {record_attributes[1]}")
+            logger.warning(f"Relation extracted: {record_attributes[1]}")
         return None
 
     try:

From 4e751e065374136e6f97ee7c05937590723ec442 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 31 Aug 2025 22:24:11 +0800
Subject: [PATCH 092/141] refac: Enhance extraction with improved prompts and
 parser

-   **Prompts**: Restructured prompts with clearer steps and quality guidelines. Simplified the relationship tuple by removing `relationship_strength`
-   **Model**: Updated default entity types to be more comprehensive and consistently capitalized (e.g., `Location`, `Product`)
---
 README-zh.md          |   2 +-
 README.md             |   2 +-
 lightrag/constants.py |  13 ++--
 lightrag/operate.py   |  36 ++++-----
 lightrag/prompt.py    | 172 +++++++++++++++++++++++++-----------------
 5 files changed, 126 insertions(+), 99 deletions(-)

diff --git a/README-zh.md b/README-zh.md
index d3403b35..ea2ad24b 100644
--- a/README-zh.md
+++ b/README-zh.md
@@ -275,7 +275,7 @@ if __name__ == "__main__":
 | **vector_db_storage_cls_kwargs** | `dict` | 向量数据库的附加参数，如设置节点和关系检索的阈值 | cosine_better_than_threshold: 0.2（默认值由环境变量COSINE_THRESHOLD更改） |
 | **enable_llm_cache** | `bool` | 如果为`TRUE`，将LLM结果存储在缓存中；重复的提示返回缓存的响应 | `TRUE` |
 | **enable_llm_cache_for_entity_extract** | `bool` | 如果为`TRUE`，将实体提取的LLM结果存储在缓存中；适合初学者调试应用程序 | `TRUE` |
-| **addon_params** | `dict` | 附加参数，例如`{"example_number": 1, "language": "Simplified Chinese", "entity_types": ["organization", "person", "geo", "event"]}`：设置示例限制、输出语言和文档处理的批量大小 | `example_number: 所有示例, language: English` |
+| **addon_params** | `dict` | 附加参数，例如`{"language": "Simplified Chinese", "entity_types": ["organization", "person", "location", "event"]}`：设置示例限制、输出语言和文档处理的批量大小 | language: English` |
 | **embedding_cache_config** | `dict` | 问答缓存的配置。包含三个参数：`enabled`：布尔值，启用/禁用缓存查找功能。启用时，系统将在生成新答案之前检查缓存的响应。`similarity_threshold`：浮点值（0-1），相似度阈值。当新问题与缓存问题的相似度超过此阈值时，将直接返回缓存的答案而不调用LLM。`use_llm_check`：布尔值，启用/禁用LLM相似度验证。启用时，在返回缓存答案之前，将使用LLM作为二次检查来验证问题之间的相似度。 | 默认：`{"enabled": False, "similarity_threshold": 0.95, "use_llm_check": False}` |
 
 </details>
diff --git a/README.md b/README.md
index 5ad37f01..e5a1625f 100644
--- a/README.md
+++ b/README.md
@@ -282,7 +282,7 @@ A full list of LightRAG init parameters:
 | **vector_db_storage_cls_kwargs** | `dict` | Additional parameters for vector database, like setting the threshold for nodes and relations retrieval | cosine_better_than_threshold: 0.2（default value changed by env var COSINE_THRESHOLD) |
 | **enable_llm_cache** | `bool` | If `TRUE`, stores LLM results in cache; repeated prompts return cached responses | `TRUE` |
 | **enable_llm_cache_for_entity_extract** | `bool` | If `TRUE`, stores LLM results in cache for entity extraction; Good for beginners to debug your application | `TRUE` |
-| **addon_params** | `dict` | Additional parameters, e.g., `{"example_number": 1, "language": "Simplified Chinese", "entity_types": ["organization", "person", "geo", "event"]}`: sets example limit, entiy/relation extraction output language | `example_number: all examples, language: English` |
+| **addon_params** | `dict` | Additional parameters, e.g., `{"language": "Simplified Chinese", "entity_types": ["organization", "person", "location", "event"]}`: sets example limit, entiy/relation extraction output language | language: English` |
 | **embedding_cache_config** | `dict` | Configuration for question-answer caching. Contains three parameters: `enabled`: Boolean value to enable/disable cache lookup functionality. When enabled, the system will check cached responses before generating new answers. `similarity_threshold`: Float value (0-1), similarity threshold. When a new question's similarity with a cached question exceeds this threshold, the cached answer will be returned directly without calling the LLM. `use_llm_check`: Boolean value to enable/disable LLM similarity verification. When enabled, LLM will be used as a secondary check to verify the similarity between questions before returning cached answers. | Default: `{"enabled": False, "similarity_threshold": 0.95, "use_llm_check": False}` |
 
 </details>
diff --git a/lightrag/constants.py b/lightrag/constants.py
index d78d869c..9accdc52 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -24,11 +24,14 @@ DEFAULT_SUMMARY_LENGTH_RECOMMENDED = 600
 DEFAULT_SUMMARY_CONTEXT_SIZE = 12000
 # Default entities to extract if ENTITY_TYPES is not specified in .env
 DEFAULT_ENTITY_TYPES = [
-    "organization",
-    "person",
-    "geo",
-    "event",
-    "category",
+    "Organization",
+    "Person",
+    "Equiment",
+    "Product",
+    "Technology",
+    "Location",
+    "Event",
+    "Category",
 ]
 
 # Separator for graph fields
diff --git a/lightrag/operate.py b/lightrag/operate.py
index b8dd8bb8..1a4b9266 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -314,8 +314,8 @@ async def _handle_single_entity_extraction(
     chunk_key: str,
     file_path: str = "unknown_source",
 ):
-    if len(record_attributes) < 4 or '"entity"' not in record_attributes[0]:
-        if len(record_attributes) > 1 and '"entity"' in record_attributes[0]:
+    if len(record_attributes) < 4 or "entity" not in record_attributes[0]:
+        if len(record_attributes) > 1 and "entity" in record_attributes[0]:
             logger.warning(
                 f"Entity extraction failed in {chunk_key}: expecting 4 fields but got {len(record_attributes)}"
             )
@@ -381,10 +381,10 @@ async def _handle_single_relationship_extraction(
     chunk_key: str,
     file_path: str = "unknown_source",
 ):
-    if len(record_attributes) < 6 or '"relationship"' not in record_attributes[0]:
-        if len(record_attributes) > 1 and '"relationship"' in record_attributes[0]:
+    if len(record_attributes) < 5 or "relationship" not in record_attributes[0]:
+        if len(record_attributes) > 1 and "relationship" in record_attributes[0]:
             logger.warning(
-                f"Relation extraction failed in {chunk_key}: expecting 6 fields but got {len(record_attributes)}"
+                f"Relation extraction failed in {chunk_key}: expecting 5 fields but got {len(record_attributes)}"
             )
             logger.warning(f"Relation extracted: {record_attributes[1]}")
         return None
@@ -416,15 +416,15 @@ async def _handle_single_relationship_extraction(
             )
             return None
 
-        # Process relationship description with same cleaning pipeline
-        edge_description = sanitize_and_normalize_extracted_text(record_attributes[3])
-
         # Process keywords with same cleaning pipeline
         edge_keywords = sanitize_and_normalize_extracted_text(
-            record_attributes[4], remove_inner_quotes=True
+            record_attributes[3], remove_inner_quotes=True
         )
         edge_keywords = edge_keywords.replace("，", ",")
 
+        # Process relationship description with same cleaning pipeline
+        edge_description = sanitize_and_normalize_extracted_text(record_attributes[4])
+
         edge_source_id = chunk_key
         weight = (
             float(record_attributes[-1].strip('"').strip("'"))
@@ -1686,13 +1686,8 @@ async def extract_entities(
     entity_types = global_config["addon_params"].get(
         "entity_types", DEFAULT_ENTITY_TYPES
     )
-    example_number = global_config["addon_params"].get("example_number", None)
-    if example_number and example_number < len(PROMPTS["entity_extraction_examples"]):
-        examples = "\n".join(
-            PROMPTS["entity_extraction_examples"][: int(example_number)]
-        )
-    else:
-        examples = "\n".join(PROMPTS["entity_extraction_examples"])
+
+    examples = "\n".join(PROMPTS["entity_extraction_examples"])
 
     example_context_base = dict(
         tuple_delimiter=PROMPTS["DEFAULT_TUPLE_DELIMITER"],
@@ -2137,13 +2132,8 @@ async def extract_keywords_only(
             )
 
     # 2. Build the examples
-    example_number = global_config["addon_params"].get("example_number", None)
-    if example_number and example_number < len(PROMPTS["keywords_extraction_examples"]):
-        examples = "\n".join(
-            PROMPTS["keywords_extraction_examples"][: int(example_number)]
-        )
-    else:
-        examples = "\n".join(PROMPTS["keywords_extraction_examples"])
+    examples = "\n".join(PROMPTS["keywords_extraction_examples"])
+
     language = global_config["addon_params"].get("language", DEFAULT_SUMMARY_LANGUAGE)
 
     # 3. Process conversation history
diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index f8ea6589..bd7451ee 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -15,27 +15,35 @@ Given a text document that is potentially relevant to this activity and a list o
 Use {language} as output language.
 
 ---Steps---
-1. Identify all entities. For each identified entity, extract the following information:
+1. Recognizing definitively conceptualized entities in text. For each identified entity, extract the following information:
 - entity_name: Name of the entity, use same language as input text. If English, capitalized the name
-- entity_type: One of the following types: [{entity_types}]
-- entity_description: Provide a comprehensive description of the entity's attributes and activities *based solely on the information present in the input text*. **Do not infer or hallucinate information not explicitly stated.** If the text provides insufficient information to create a comprehensive description, state "Description not available in text."
-Format each entity as ("entity"{tuple_delimiter}<entity_name>{tuple_delimiter}<entity_type>{tuple_delimiter}<entity_description>)
+- entity_type: One of the following types: [{entity_types}]. If the entity doesn't clearly fit any category, classify it as "Other".
+- entity_description: Provide a comprehensive description of the entity's attributes and activities based on the information present in the input text. Do not add external knowledge.
 
-2. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are *clearly related* to each other.
+2. Format each entity as:
+("entity"{tuple_delimiter}<entity_name>{tuple_delimiter}<entity_type>{tuple_delimiter}<entity_description>)
+
+3. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are directly and clearly related based on the text. Unsubstantiated relationships must be excluded from the output.
 For each pair of related entities, extract the following information:
 - source_entity: name of the source entity, as identified in step 1
 - target_entity: name of the target entity, as identified in step 1
-- relationship_description: explanation as to why you think the source entity and the target entity are related to each other
-- relationship_strength: a numeric score indicating strength of the relationship between the source entity and target entity
 - relationship_keywords: one or more high-level key words that summarize the overarching nature of the relationship, focusing on concepts or themes rather than specific details
-Format each relationship as ("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_description>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_strength>)
+- relationship_description: Explain the nature of the relationship between the source and target entities, providing a clear rationale for their connection
 
-3. Identify high-level key words that summarize the main concepts, themes, or topics of the entire text. These should capture the overarching ideas present in the document.
-Format the content-level key words as ("content_keywords"{tuple_delimiter}<high_level_keywords>)
+4. Format each relationship as:
+("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
 
-4. Return output in {language} as a single list of all the entities and relationships identified in steps 1 and 2. Use **{record_delimiter}** as the list delimiter.
+5. Use `{tuple_delimiter}` as feild delimiter, and use `{record_delimiter}` as the list delimiter.
 
-5. When finished, output {completion_delimiter}
+6. When finished, output `{completion_delimiter}`
+
+7. Return identified entities and relationships in {language}.
+
+---Quality Guidelines---
+- Only extract entities that are clearly defined and meaningful in the context
+- Avoid over-interpretation; stick to what is explicitly stated in the text
+- Include specific numerical data in entity name when relevant
+- Ensure entity names are consistent throughout the extraction
 
 ---Examples---
 {examples}
@@ -43,15 +51,18 @@ Format the content-level key words as ("content_keywords"{tuple_delimiter}<high_
 ---Real Data---
 Entity_types: [{entity_types}]
 Text:
+```
 {input_text}
+```
 
 ---Output---
-Output:"""
+Output:
+"""
 
 PROMPTS["entity_extraction_examples"] = [
     """------Example 1------
 
-Entity_types: [person, technology, mission, organization, location]
+Entity_types: [organization,person,equiment,product,technology,location,event,category]
 Text:
 ```
 while Alex clenched his jaw, the buzz of frustration dull against the backdrop of Taylor's authoritarian certainty. It was this competitive undercurrent that kept him alert, the sense that his and Jordan's shared commitment to discovery was an unspoken rebellion against Cruz's narrowing vision of control and order.
@@ -64,22 +75,22 @@ It was a small transformation, barely perceptible, but one that Alex noted with
 ```
 
 Output:
-("entity"{tuple_delimiter}"Alex"{tuple_delimiter}"person"{tuple_delimiter}"Alex is a character who experiences frustration and is observant of the dynamics among other characters."){record_delimiter}
-("entity"{tuple_delimiter}"Taylor"{tuple_delimiter}"person"{tuple_delimiter}"Taylor is portrayed with authoritarian certainty and shows a moment of reverence towards a device, indicating a change in perspective."){record_delimiter}
-("entity"{tuple_delimiter}"Jordan"{tuple_delimiter}"person"{tuple_delimiter}"Jordan shares a commitment to discovery and has a significant interaction with Taylor regarding a device."){record_delimiter}
-("entity"{tuple_delimiter}"Cruz"{tuple_delimiter}"person"{tuple_delimiter}"Cruz is associated with a vision of control and order, influencing the dynamics among other characters."){record_delimiter}
-("entity"{tuple_delimiter}"The Device"{tuple_delimiter}"technology"{tuple_delimiter}"The Device is central to the story, with potential game-changing implications, and is revered by Taylor."){record_delimiter}
-("relationship"{tuple_delimiter}"Alex"{tuple_delimiter}"Taylor"{tuple_delimiter}"Alex is affected by Taylor's authoritarian certainty and observes changes in Taylor's attitude towards the device."{tuple_delimiter}"power dynamics, perspective shift"{tuple_delimiter}7){record_delimiter}
-("relationship"{tuple_delimiter}"Alex"{tuple_delimiter}"Jordan"{tuple_delimiter}"Alex and Jordan share a commitment to discovery, which contrasts with Cruz's vision."{tuple_delimiter}"shared goals, rebellion"{tuple_delimiter}6){record_delimiter}
-("relationship"{tuple_delimiter}"Taylor"{tuple_delimiter}"Jordan"{tuple_delimiter}"Taylor and Jordan interact directly regarding the device, leading to a moment of mutual respect and an uneasy truce."{tuple_delimiter}"conflict resolution, mutual respect"{tuple_delimiter}8){record_delimiter}
-("relationship"{tuple_delimiter}"Jordan"{tuple_delimiter}"Cruz"{tuple_delimiter}"Jordan's commitment to discovery is in rebellion against Cruz's vision of control and order."{tuple_delimiter}"ideological conflict, rebellion"{tuple_delimiter}5){record_delimiter}
-("relationship"{tuple_delimiter}"Taylor"{tuple_delimiter}"The Device"{tuple_delimiter}"Taylor shows reverence towards the device, indicating its importance and potential impact."{tuple_delimiter}"reverence, technological significance"{tuple_delimiter}9){record_delimiter}
-("content_keywords"{tuple_delimiter}"power dynamics, ideological conflict, discovery, rebellion"){completion_delimiter}
+(entity{tuple_delimiter}Alex{tuple_delimiter}person{tuple_delimiter}Alex is a character who experiences frustration and is observant of the dynamics among other characters.){record_delimiter}
+(entity{tuple_delimiter}Taylor{tuple_delimiter}person{tuple_delimiter}Taylor is portrayed with authoritarian certainty and shows a moment of reverence towards a device, indicating a change in perspective.){record_delimiter}
+(entity{tuple_delimiter}Jordan{tuple_delimiter}person{tuple_delimiter}Jordan shares a commitment to discovery and has a significant interaction with Taylor regarding a device.){record_delimiter}
+(entity{tuple_delimiter}Cruz{tuple_delimiter}person{tuple_delimiter}Cruz is associated with a vision of control and order, influencing the dynamics among other characters.){record_delimiter}
+(entity{tuple_delimiter}The Device{tuple_delimiter}equiment{tuple_delimiter}The Device is central to the story, with potential game-changing implications, and is revered by Taylor.){record_delimiter}
+(relationship{tuple_delimiter}Alex{tuple_delimiter}Taylor{tuple_delimiter}power dynamics, observation{tuple_delimiter}Alex observes Taylor's authoritarian behavior and notes changes in Taylor's attitude toward the device.){record_delimiter}
+(relationship{tuple_delimiter}Alex{tuple_delimiter}Jordan{tuple_delimiter}shared goals, rebellion{tuple_delimiter}Alex and Jordan share a commitment to discovery, which contrasts with Cruz's vision.){record_delimiter}
+(relationship{tuple_delimiter}Taylor{tuple_delimiter}Jordan{tuple_delimiter}conflict resolution, mutual respect{tuple_delimiter}Taylor and Jordan interact directly regarding the device, leading to a moment of mutual respect and an uneasy truce.){record_delimiter}
+(relationship{tuple_delimiter}Jordan{tuple_delimiter}Cruz{tuple_delimiter}ideological conflict, rebellion{tuple_delimiter}Jordan's commitment to discovery is in rebellion against Cruz's vision of control and order.){record_delimiter}
+(relationship{tuple_delimiter}Taylor{tuple_delimiter}The Device{tuple_delimiter}reverence, technological significance{tuple_delimiter}Taylor shows reverence towards the device, indicating its importance and potential impact.){record_delimiter}
+{completion_delimiter}
 
 """,
     """------Example 2------
 
-Entity_types: [company, index, commodity, market_trend, economic_policy, biological]
+Entity_types: [organization,person,equiment,product,technology,location,event,category]
 Text:
 ```
 Stock markets faced a sharp downturn today as tech giants saw significant declines, with the Global Tech Index dropping by 3.4% in midday trading. Analysts attribute the selloff to investor concerns over rising interest rates and regulatory uncertainty.
@@ -92,40 +103,64 @@ Financial experts are closely watching the Federal Reserve's next move, as specu
 ```
 
 Output:
-("entity"{tuple_delimiter}"Global Tech Index"{tuple_delimiter}"index"{tuple_delimiter}"The Global Tech Index tracks the performance of major technology stocks and experienced a 3.4% decline today."){record_delimiter}
-("entity"{tuple_delimiter}"Nexon Technologies"{tuple_delimiter}"company"{tuple_delimiter}"Nexon Technologies is a tech company that saw its stock decline by 7.8% after disappointing earnings."){record_delimiter}
-("entity"{tuple_delimiter}"Omega Energy"{tuple_delimiter}"company"{tuple_delimiter}"Omega Energy is an energy company that gained 2.1% in stock value due to rising oil prices."){record_delimiter}
-("entity"{tuple_delimiter}"Gold Futures"{tuple_delimiter}"commodity"{tuple_delimiter}"Gold futures rose by 1.5%, indicating increased investor interest in safe-haven assets."){record_delimiter}
-("entity"{tuple_delimiter}"Crude Oil"{tuple_delimiter}"commodity"{tuple_delimiter}"Crude oil prices rose to $87.60 per barrel due to supply constraints and strong demand."){record_delimiter}
-("entity"{tuple_delimiter}"Market Selloff"{tuple_delimiter}"market_trend"{tuple_delimiter}"Market selloff refers to the significant decline in stock values due to investor concerns over interest rates and regulations."){record_delimiter}
-("entity"{tuple_delimiter}"Federal Reserve Policy Announcement"{tuple_delimiter}"economic_policy"{tuple_delimiter}"The Federal Reserve's upcoming policy announcement is expected to impact investor confidence and market stability."){record_delimiter}
-("relationship"{tuple_delimiter}"Global Tech Index"{tuple_delimiter}"Market Selloff"{tuple_delimiter}"The decline in the Global Tech Index is part of the broader market selloff driven by investor concerns."{tuple_delimiter}"market performance, investor sentiment"{tuple_delimiter}9){record_delimiter}
-("relationship"{tuple_delimiter}"Nexon Technologies"{tuple_delimiter}"Global Tech Index"{tuple_delimiter}"Nexon Technologies' stock decline contributed to the overall drop in the Global Tech Index."{tuple_delimiter}"company impact, index movement"{tuple_delimiter}8){record_delimiter}
-("relationship"{tuple_delimiter}"Gold Futures"{tuple_delimiter}"Market Selloff"{tuple_delimiter}"Gold prices rose as investors sought safe-haven assets during the market selloff."{tuple_delimiter}"market reaction, safe-haven investment"{tuple_delimiter}10){record_delimiter}
-("relationship"{tuple_delimiter}"Federal Reserve Policy Announcement"{tuple_delimiter}"Market Selloff"{tuple_delimiter}"Speculation over Federal Reserve policy changes contributed to market volatility and investor selloff."{tuple_delimiter}"interest rate impact, financial regulation"{tuple_delimiter}7){record_delimiter}
-("content_keywords"{tuple_delimiter}"market downturn, investor sentiment, commodities, Federal Reserve, stock performance"){completion_delimiter}
+(entity{tuple_delimiter}Global Tech Index{tuple_delimiter}category{tuple_delimiter}The Global Tech Index tracks the performance of major technology stocks and experienced a 3.4% decline today.){record_delimiter}
+(entity{tuple_delimiter}Nexon Technologies{tuple_delimiter}organization{tuple_delimiter}Nexon Technologies is a tech company that saw its stock decline by 7.8% after disappointing earnings.){record_delimiter}
+(entity{tuple_delimiter}Omega Energy{tuple_delimiter}organization{tuple_delimiter}Omega Energy is an energy company that gained 2.1% in stock value due to rising oil prices.){record_delimiter}
+(entity{tuple_delimiter}Gold Futures{tuple_delimiter}product{tuple_delimiter}Gold futures rose by 1.5%, indicating increased investor interest in safe-haven assets.){record_delimiter}
+(entity{tuple_delimiter}Crude Oil{tuple_delimiter}product{tuple_delimiter}Crude oil prices rose to $87.60 per barrel due to supply constraints and strong demand.){record_delimiter}
+(entity{tuple_delimiter}Market Selloff{tuple_delimiter}category{tuple_delimiter}Market selloff refers to the significant decline in stock values due to investor concerns over interest rates and regulations.){record_delimiter}
+(entity{tuple_delimiter}Federal Reserve Policy Announcement{tuple_delimiter}category{tuple_delimiter}The Federal Reserve's upcoming policy announcement is expected to impact investor confidence and market stability.){record_delimiter}
+(entity{tuple_delimiter}3.4% Decline{tuple_delimiter}category{tuple_delimiter}The Global Tech Index experienced a 3.4% decline in midday trading.){record_delimiter}
+(relationship{tuple_delimiter}Global Tech Index{tuple_delimiter}Market Selloff{tuple_delimiter}market performance, investor sentiment{tuple_delimiter}The decline in the Global Tech Index is part of the broader market selloff driven by investor concerns.){record_delimiter}
+(relationship{tuple_delimiter}Nexon Technologies{tuple_delimiter}Global Tech Index{tuple_delimiter}company impact, index movement{tuple_delimiter}Nexon Technologies' stock decline contributed to the overall drop in the Global Tech Index.){record_delimiter}
+(relationship{tuple_delimiter}Gold Futures{tuple_delimiter}Market Selloff{tuple_delimiter}market reaction, safe-haven investment{tuple_delimiter}Gold prices rose as investors sought safe-haven assets during the market selloff.){record_delimiter}
+(relationship{tuple_delimiter}Federal Reserve Policy Announcement{tuple_delimiter}Market Selloff{tuple_delimiter}interest rate impact, financial regulation{tuple_delimiter}Speculation over Federal Reserve policy changes contributed to market volatility and investor selloff.){record_delimiter}
+{completion_delimiter}
 
 """,
     """------Example 3------
 
-Entity_types: [economic_policy, athlete, event, location, record, organization, equipment]
+Entity_types: [organization,person,equiment,product,technology,location,event,category]
 Text:
 ```
 At the World Athletics Championship in Tokyo, Noah Carter broke the 100m sprint record using cutting-edge carbon-fiber spikes.
 ```
 
 Output:
-("entity"{tuple_delimiter}"World Athletics Championship"{tuple_delimiter}"event"{tuple_delimiter}"The World Athletics Championship is a global sports competition featuring top athletes in track and field."){record_delimiter}
-("entity"{tuple_delimiter}"Tokyo"{tuple_delimiter}"location"{tuple_delimiter}"Tokyo is the host city of the World Athletics Championship."){record_delimiter}
-("entity"{tuple_delimiter}"Noah Carter"{tuple_delimiter}"athlete"{tuple_delimiter}"Noah Carter is a sprinter who set a new record in the 100m sprint at the World Athletics Championship."){record_delimiter}
-("entity"{tuple_delimiter}"100m Sprint Record"{tuple_delimiter}"record"{tuple_delimiter}"The 100m sprint record is a benchmark in athletics, recently broken by Noah Carter."){record_delimiter}
-("entity"{tuple_delimiter}"Carbon-Fiber Spikes"{tuple_delimiter}"equipment"{tuple_delimiter}"Carbon-fiber spikes are advanced sprinting shoes that provide enhanced speed and traction."){record_delimiter}
-("entity"{tuple_delimiter}"World Athletics Federation"{tuple_delimiter}"organization"{tuple_delimiter}"The World Athletics Federation is the governing body overseeing the World Athletics Championship and record validations."){record_delimiter}
-("relationship"{tuple_delimiter}"World Athletics Championship"{tuple_delimiter}"Tokyo"{tuple_delimiter}"The World Athletics Championship is being hosted in Tokyo."{tuple_delimiter}"event location, international competition"{tuple_delimiter}8){record_delimiter}
-("relationship"{tuple_delimiter}"Noah Carter"{tuple_delimiter}"100m Sprint Record"{tuple_delimiter}"Noah Carter set a new 100m sprint record at the championship."{tuple_delimiter}"athlete achievement, record-breaking"{tuple_delimiter}10){record_delimiter}
-("relationship"{tuple_delimiter}"Noah Carter"{tuple_delimiter}"Carbon-Fiber Spikes"{tuple_delimiter}"Noah Carter used carbon-fiber spikes to enhance performance during the race."{tuple_delimiter}"athletic equipment, performance boost"{tuple_delimiter}7){record_delimiter}
-("relationship"{tuple_delimiter}"World Athletics Federation"{tuple_delimiter}"100m Sprint Record"{tuple_delimiter}"The World Athletics Federation is responsible for validating and recognizing new sprint records."{tuple_delimiter}"sports regulation, record certification"{tuple_delimiter}9){record_delimiter}
-("content_keywords"{tuple_delimiter}"athletics, sprinting, record-breaking, sports technology, competition"){completion_delimiter}
+(entity{tuple_delimiter}World Athletics Championship{tuple_delimiter}event{tuple_delimiter}The World Athletics Championship is a global sports competition featuring top athletes in track and field.){record_delimiter}
+(entity{tuple_delimiter}Tokyo{tuple_delimiter}location{tuple_delimiter}Tokyo is the host city of the World Athletics Championship.){record_delimiter}
+(entity{tuple_delimiter}Noah Carter{tuple_delimiter}person{tuple_delimiter}Noah Carter is a sprinter who set a new record in the 100m sprint at the World Athletics Championship.){record_delimiter}
+(entity{tuple_delimiter}100m Sprint Record{tuple_delimiter}category{tuple_delimiter}The 100m sprint record is a benchmark in athletics, recently broken by Noah Carter.){record_delimiter}
+(entity{tuple_delimiter}Carbon-Fiber Spikes{tuple_delimiter}equipment{tuple_delimiter}Carbon-fiber spikes are advanced sprinting shoes that provide enhanced speed and traction.){record_delimiter}
+(entity{tuple_delimiter}World Athletics Federation{tuple_delimiter}organization{tuple_delimiter}The World Athletics Federation is the governing body overseeing the World Athletics Championship and record validations.){record_delimiter}
+(relationship{tuple_delimiter}World Athletics Championship{tuple_delimiter}Tokyo{tuple_delimiter}event location, international competition{tuple_delimiter}The World Athletics Championship is being hosted in Tokyo.){record_delimiter}
+(relationship{tuple_delimiter}Noah Carter{tuple_delimiter}100m Sprint Record{tuple_delimiter}athlete achievement, record-breaking{tuple_delimiter}Noah Carter set a new 100m sprint record at the championship.){record_delimiter}
+(relationship{tuple_delimiter}Noah Carter{tuple_delimiter}Carbon-Fiber Spikes{tuple_delimiter}athletic equipment, performance boost{tuple_delimiter}Noah Carter used carbon-fiber spikes to enhance performance during the race.){record_delimiter}
+(relationship{tuple_delimiter}Noah Carter{tuple_delimiter}World Athletics Championship{tuple_delimiter}athlete participation, competition{tuple_delimiter}Noah Carter is competing at the World Athletics Championship.){record_delimiter}
+{completion_delimiter}
+
+""",
+    """------Example 4------
+
+Entity_types: [organization,person,equiment,product,technology,location,event,category]
+Text:
+```
+在北京举行的人工智能大会上，腾讯公司的首席技术官张伟发布了最新的大语言模型"腾讯智言"，该模型在自然语言处理方面取得了重大突破。
+
+```
+
+Output:
+(entity{tuple_delimiter}人工智能大会{tuple_delimiter}event{tuple_delimiter}人工智能大会是在北京举行的技术会议，专注于人工智能领域的最新发展。){record_delimiter}
+(entity{tuple_delimiter}北京{tuple_delimiter}location{tuple_delimiter}北京是人工智能大会的举办城市。){record_delimiter}
+(entity{tuple_delimiter}腾讯公司{tuple_delimiter}organization{tuple_delimiter}腾讯公司是参与人工智能大会的科技企业，发布了新的语言模型产品。){record_delimiter}
+(entity{tuple_delimiter}张伟{tuple_delimiter}person{tuple_delimiter}张伟是腾讯公司的首席技术官，在大会上发布了新产品。){record_delimiter}
+(entity{tuple_delimiter}腾讯智言{tuple_delimiter}product{tuple_delimiter}腾讯智言是腾讯公司发布的大语言模型产品，在自然语言处理方面有重大突破。){record_delimiter}
+(entity{tuple_delimiter}自然语言处理技术{tuple_delimiter}technology{tuple_delimiter}自然语言处理技术是腾讯智言模型取得重大突破的技术领域。){record_delimiter}
+(relationship{tuple_delimiter}人工智能大会{tuple_delimiter}北京{tuple_delimiter}会议地点, 举办关系{tuple_delimiter}人工智能大会在北京举行。){record_delimiter}
+(relationship{tuple_delimiter}张伟{tuple_delimiter}腾讯公司{tuple_delimiter}雇佣关系, 高管职位{tuple_delimiter}张伟担任腾讯公司的首席技术官。){record_delimiter}
+(relationship{tuple_delimiter}张伟{tuple_delimiter}腾讯智言{tuple_delimiter}产品发布, 技术展示{tuple_delimiter}张伟在大会上发布了腾讯智言大语言模型。){record_delimiter}
+(relationship{tuple_delimiter}腾讯智言{tuple_delimiter}自然语言处理技术{tuple_delimiter}技术应用, 突破创新{tuple_delimiter}腾讯智言在自然语言处理技术方面取得了重大突破。){record_delimiter}
+{completion_delimiter}
 
 """,
 ]
@@ -149,40 +184,39 @@ Description List:
 {description_list}
 
 ---Output---
-Output:
-"""
+Output:"""
 
 PROMPTS["entity_continue_extraction"] = """
-MANY entities and relationships were missed in the last extraction. Please find only the missing entities and relationships from previous text.
+MANY entities and relationships were missed in the last extraction. Please find only the missing entities and relationships from previous text. Do not include entities and relations that have been previously extracted. :\n
 
 ---Remember Steps---
-
-1. Identify all entities. For each identified entity, extract the following information:
+1. Recognizing definitively conceptualized entities in text. For each identified entity, extract the following information:
 - entity_name: Name of the entity, use same language as input text. If English, capitalized the name
-- entity_type: One of the following types: [{entity_types}]
-- entity_description: Provide a comprehensive description of the entity's attributes and activities *based solely on the information present in the input text*. **Do not infer or hallucinate information not explicitly stated.** If the text provides insufficient information to create a comprehensive description, state "Description not available in text."
-Format each entity as ("entity"{tuple_delimiter}<entity_name>{tuple_delimiter}<entity_type>{tuple_delimiter}<entity_description>)
+- entity_type: One of the following types: [{entity_types}]. If the entity doesn't clearly fit any category, classify it as "Other".
+- entity_description: Provide a comprehensive description of the entity's attributes and activities based on the information present in the input text. Do not add external knowledge.
 
-2. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are *clearly related* to each other.
+2. Format each entity as:
+("entity"{tuple_delimiter}<entity_name>{tuple_delimiter}<entity_type>{tuple_delimiter}<entity_description>)
+
+3. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are directly and clearly related based on the text. Unsubstantiated relationships must be excluded from the output.
 For each pair of related entities, extract the following information:
 - source_entity: name of the source entity, as identified in step 1
 - target_entity: name of the target entity, as identified in step 1
-- relationship_description: explanation as to why you think the source entity and the target entity are related to each other
-- relationship_strength: a numeric score indicating strength of the relationship between the source entity and target entity
 - relationship_keywords: one or more high-level key words that summarize the overarching nature of the relationship, focusing on concepts or themes rather than specific details
-Format each relationship as ("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_description>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_strength>)
+- relationship_description: Explain the nature of the relationship between the source and target entities, providing a clear rationale for their connection
 
-3. Identify high-level key words that summarize the main concepts, themes, or topics of the entire text. These should capture the overarching ideas present in the document.
-Format the content-level key words as ("content_keywords"{tuple_delimiter}<high_level_keywords>)
+4. Format each relationship as:
+("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
 
-4. Return output in {language} as a single list of all the entities and relationships identified in steps 1 and 2. Use **{record_delimiter}** as the list delimiter.
+5. Use `{tuple_delimiter}` as feild delimiter, and use `{record_delimiter}` as the list delimiter.
 
-5. When finished, output {completion_delimiter}
+6. When finished, output `{completion_delimiter}`
+
+7. Return identified entities and relationships in {language}.
 
 ---Output---
-
-Add new entities and relations below using the same format, and do not include entities and relations that have been previously extracted. :\n
-""".strip()
+Output:
+"""
 
 PROMPTS["entity_if_loop_extraction"] = """
 ---Goal---'

From 57fe1403c398c630c4dd460eaa2dbcf020019fc0 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 31 Aug 2025 22:33:34 +0800
Subject: [PATCH 093/141] Update default entity types in env.example
 configuration

---
 env.example | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/env.example b/env.example
index 6a18a68c..02b3ec00 100644
--- a/env.example
+++ b/env.example
@@ -125,7 +125,7 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true
 SUMMARY_LANGUAGE=English
 
 ### Entity types that the LLM will attempt to recognize
-# ENTITY_TYPES=["person", "organization", "location", "event", "concept"]
+# ENTITY_TYPES=["organization", "person", "equiment", "product", "technology", "location", "event", "category"]
 
 ### Chunk size for document splitting, 500~1500 is recommended
 # CHUNK_SIZE=1200

From 1a015a70152856b1bc3d00108efcb7d45cd9ba9d Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Sun, 31 Aug 2025 23:47:22 +0800
Subject: [PATCH 094/141] Add queue_name parameter to
 priority_limit_async_func_call for better logging
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Add queue_name parameter to decorator
• Update all log messages with queue names
• Pass specific names for LLM and embedding
---
 lightrag/lightrag.py |  2 ++
 lightrag/utils.py    | 42 +++++++++++++++++++++++-------------------
 2 files changed, 25 insertions(+), 19 deletions(-)

diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index 23e6f575..43614a93 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -469,6 +469,7 @@ class LightRAG:
         self.embedding_func = priority_limit_async_func_call(
             self.embedding_func_max_async,
             llm_timeout=self.default_embedding_timeout,
+            queue_name="Embedding func:",
         )(self.embedding_func)
 
         # Initialize all storages
@@ -565,6 +566,7 @@ class LightRAG:
         self.llm_model_func = priority_limit_async_func_call(
             self.llm_model_max_async,
             llm_timeout=self.default_llm_timeout,
+            queue_name="LLM func:",
         )(
             partial(
                 self.llm_model_func,  # type: ignore
diff --git a/lightrag/utils.py b/lightrag/utils.py
index 9dc5a5b2..ab4787c4 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -374,6 +374,7 @@ def priority_limit_async_func_call(
     max_task_duration: float = None,
     max_queue_size: int = 1000,
     cleanup_timeout: float = 2.0,
+    queue_name: str = "limit_async",
 ):
     """
     Enhanced priority-limited asynchronous function call decorator with robust timeout handling
@@ -391,6 +392,7 @@ def priority_limit_async_func_call(
         max_execution_timeout: Maximum time for worker to execute function (defaults to llm_timeout + 30s)
         max_task_duration: Maximum time before health check intervenes (defaults to llm_timeout + 60s)
         cleanup_timeout: Maximum time to wait for cleanup operations (defaults to 2.0s)
+        queue_name: Optional queue name for logging identification (defaults to "limit_async")
 
     Returns:
         Decorator function
@@ -482,7 +484,7 @@ def priority_limit_async_func_call(
                         except asyncio.TimeoutError:
                             # Worker-level timeout (max_execution_timeout exceeded)
                             logger.warning(
-                                f"limit_async: Worker timeout for task {task_id} after {max_execution_timeout}s"
+                                f"{queue_name}: Worker timeout for task {task_id} after {max_execution_timeout}s"
                             )
                             if not task_state.future.done():
                                 task_state.future.set_exception(
@@ -495,12 +497,12 @@ def priority_limit_async_func_call(
                             if not task_state.future.done():
                                 task_state.future.cancel()
                             logger.debug(
-                                f"limit_async: Task {task_id} cancelled during execution"
+                                f"{queue_name}: Task {task_id} cancelled during execution"
                             )
                         except Exception as e:
                             # Function execution error
                             logger.error(
-                                f"limit_async: Error in decorated function for task {task_id}: {str(e)}"
+                                f"{queue_name}: Error in decorated function for task {task_id}: {str(e)}"
                             )
                             if not task_state.future.done():
                                 task_state.future.set_exception(e)
@@ -512,10 +514,12 @@ def priority_limit_async_func_call(
 
                     except Exception as e:
                         # Critical error in worker loop
-                        logger.error(f"limit_async: Critical error in worker: {str(e)}")
+                        logger.error(
+                            f"{queue_name}: Critical error in worker: {str(e)}"
+                        )
                         await asyncio.sleep(0.1)
             finally:
-                logger.debug("limit_async: Worker exiting")
+                logger.debug(f"{queue_name}: Worker exiting")
 
         async def enhanced_health_check():
             """Enhanced health check with stuck task detection and recovery"""
@@ -549,7 +553,7 @@ def priority_limit_async_func_call(
                         # Force cleanup of stuck tasks
                         for task_id, execution_duration in stuck_tasks:
                             logger.warning(
-                                f"limit_async: Detected stuck task {task_id} (execution time: {execution_duration:.1f}s), forcing cleanup"
+                                f"{queue_name}: Detected stuck task {task_id} (execution time: {execution_duration:.1f}s), forcing cleanup"
                             )
                             async with task_states_lock:
                                 if task_id in task_states:
@@ -572,7 +576,7 @@ def priority_limit_async_func_call(
 
                     if workers_needed > 0:
                         logger.info(
-                            f"limit_async: Creating {workers_needed} new workers"
+                            f"{queue_name}: Creating {workers_needed} new workers"
                         )
                         new_tasks = set()
                         for _ in range(workers_needed):
@@ -582,9 +586,9 @@ def priority_limit_async_func_call(
                         tasks.update(new_tasks)
 
             except Exception as e:
-                logger.error(f"limit_async: Error in enhanced health check: {str(e)}")
+                logger.error(f"{queue_name}: Error in enhanced health check: {str(e)}")
             finally:
-                logger.debug("limit_async: Enhanced health check task exiting")
+                logger.debug(f"{queue_name}: Enhanced health check task exiting")
                 initialized = False
 
         async def ensure_workers():
@@ -601,7 +605,7 @@ def priority_limit_async_func_call(
                 if reinit_count > 0:
                     reinit_count += 1
                     logger.warning(
-                        f"limit_async: Reinitializing system (count: {reinit_count})"
+                        f"{queue_name}: Reinitializing system (count: {reinit_count})"
                     )
                 else:
                     reinit_count = 1
@@ -614,7 +618,7 @@ def priority_limit_async_func_call(
                 active_tasks_count = len(tasks)
                 if active_tasks_count > 0 and reinit_count > 1:
                     logger.warning(
-                        f"limit_async: {active_tasks_count} tasks still running during reinitialization"
+                        f"{queue_name}: {active_tasks_count} tasks still running during reinitialization"
                     )
 
                 # Create worker tasks
@@ -641,12 +645,12 @@ def priority_limit_async_func_call(
                     f" (Timeouts: {', '.join(timeout_info)})" if timeout_info else ""
                 )
                 logger.info(
-                    f"limit_async: {workers_needed} new workers initialized {timeout_str}"
+                    f"{queue_name}: {workers_needed} new workers initialized {timeout_str}"
                 )
 
         async def shutdown():
             """Gracefully shut down all workers and cleanup resources"""
-            logger.info("limit_async: Shutting down priority queue workers")
+            logger.info(f"{queue_name}: Shutting down priority queue workers")
 
             shutdown_event.set()
 
@@ -667,7 +671,7 @@ def priority_limit_async_func_call(
                 await asyncio.wait_for(queue.join(), timeout=5.0)
             except asyncio.TimeoutError:
                 logger.warning(
-                    "limit_async: Timeout waiting for queue to empty during shutdown"
+                    f"{queue_name}: Timeout waiting for queue to empty during shutdown"
                 )
 
             # Cancel worker tasks
@@ -687,7 +691,7 @@ def priority_limit_async_func_call(
                 except asyncio.CancelledError:
                     pass
 
-            logger.info("limit_async: Priority queue workers shutdown complete")
+            logger.info(f"{queue_name}: Priority queue workers shutdown complete")
 
         @wraps(func)
         async def wait_func(
@@ -750,7 +754,7 @@ def priority_limit_async_func_call(
                         )
                 except asyncio.TimeoutError:
                     raise QueueFullError(
-                        f"Queue full, timeout after {_queue_timeout} seconds"
+                        f"{queue_name}: Queue full, timeout after {_queue_timeout} seconds"
                     )
                 except Exception as e:
                     # Clean up on queue error
@@ -785,14 +789,14 @@ def priority_limit_async_func_call(
                         await asyncio.sleep(0.1)
 
                     raise TimeoutError(
-                        f"limit_async: User timeout after {_timeout} seconds"
+                        f"{queue_name}: User timeout after {_timeout} seconds"
                     )
                 except WorkerTimeoutError as e:
                     # This is Worker-level timeout, directly propagate exception information
-                    raise TimeoutError(f"limit_async: {str(e)}")
+                    raise TimeoutError(f"{queue_name}: {str(e)}")
                 except HealthCheckTimeoutError as e:
                     # This is Health Check-level timeout, directly propagate exception information
-                    raise TimeoutError(f"limit_async: {str(e)}")
+                    raise TimeoutError(f"{queue_name}: {str(e)}")
 
             finally:
                 # Ensure cleanup

From c8c59c38b0350922a51587d3afa7ae57fad3097e Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 1 Sep 2025 00:14:57 +0800
Subject: [PATCH 095/141] Fix entity types configuration to support JSON list
 parsing

- Add JSON parsing for list env vars
- Update entity types example format
- Add list type support to get_env_value
---
 env.example            |  2 +-
 lightrag/api/config.py |  2 +-
 lightrag/utils.py      | 21 +++++++++++++++++++++
 3 files changed, 23 insertions(+), 2 deletions(-)

diff --git a/env.example b/env.example
index 02b3ec00..4ab64aba 100644
--- a/env.example
+++ b/env.example
@@ -125,7 +125,7 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true
 SUMMARY_LANGUAGE=English
 
 ### Entity types that the LLM will attempt to recognize
-# ENTITY_TYPES=["organization", "person", "equiment", "product", "technology", "location", "event", "category"]
+# ENTITY_TYPES='["Organization", "Person", "Equiment", "Product", "Technology", "Location", "Event", "Category"]'
 
 ### Chunk size for document splitting, 500~1500 is recommended
 # CHUNK_SIZE=1200
diff --git a/lightrag/api/config.py b/lightrag/api/config.py
index eae2f45b..f17d50f0 100644
--- a/lightrag/api/config.py
+++ b/lightrag/api/config.py
@@ -352,7 +352,7 @@ def parse_args() -> argparse.Namespace:
     # Add environment variables that were previously read directly
     args.cors_origins = get_env_value("CORS_ORIGINS", "*")
     args.summary_language = get_env_value("SUMMARY_LANGUAGE", DEFAULT_SUMMARY_LANGUAGE)
-    args.entity_types = get_env_value("ENTITY_TYPES", DEFAULT_ENTITY_TYPES)
+    args.entity_types = get_env_value("ENTITY_TYPES", DEFAULT_ENTITY_TYPES, list)
     args.whitelist_paths = get_env_value("WHITELIST_PATHS", "/health,/api/*")
 
     # For JWT Auth
diff --git a/lightrag/utils.py b/lightrag/utils.py
index ab4787c4..7c92d99c 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -82,6 +82,27 @@ def get_env_value(
 
     if value_type is bool:
         return value.lower() in ("true", "1", "yes", "t", "on")
+
+    # Handle list type with JSON parsing
+    if value_type is list:
+        try:
+            import json
+
+            parsed_value = json.loads(value)
+            # Ensure the parsed value is actually a list
+            if isinstance(parsed_value, list):
+                return parsed_value
+            else:
+                logger.warning(
+                    f"Environment variable {env_key} is not a valid JSON list, using default"
+                )
+                return default
+        except (json.JSONDecodeError, ValueError) as e:
+            logger.warning(
+                f"Failed to parse {env_key} as JSON list: {e}, using default"
+            )
+            return default
+
     try:
         return value_type(value)
     except (ValueError, TypeError):

From ec059d1b5d0188b9aab2d5d3ae3737484017b59d Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 1 Sep 2025 00:42:59 +0800
Subject: [PATCH 096/141] Fix typo and clarify delimiter formatting in
 relationship extraction Prompt
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

- Fix "feild" → "field" typo
- Clarify delimiter spacing rules
---
 lightrag/prompt.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index bd7451ee..51d15bc0 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -33,7 +33,7 @@ For each pair of related entities, extract the following information:
 4. Format each relationship as:
 ("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
 
-5. Use `{tuple_delimiter}` as feild delimiter, and use `{record_delimiter}` as the list delimiter.
+5. Use `{tuple_delimiter}` as field delimiter. Use `{record_delimiter}` as the list delimiter. Ensure no spaces are added around the delimiters.
 
 6. When finished, output `{completion_delimiter}`
 
@@ -208,7 +208,7 @@ For each pair of related entities, extract the following information:
 4. Format each relationship as:
 ("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
 
-5. Use `{tuple_delimiter}` as feild delimiter, and use `{record_delimiter}` as the list delimiter.
+5. Use `{tuple_delimiter}` as field delimiter. Use `{record_delimiter}` as the list delimiter. Ensure no spaces are added around the delimiters.
 
 6. When finished, output `{completion_delimiter}`
 

From 5fd7682f1633a9ffe60c9bdf2aa92ed7063873f3 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 1 Sep 2025 01:22:27 +0800
Subject: [PATCH 097/141] Fix LLM output instability for <|> tuple delimiter

- Replace <||> with <|>
- Replace < | > with <|>
- Apply fix in both functions
- Handle delimiter variations
- Improve parsing reliability
---
 lightrag/operate.py | 14 ++++++++++++++
 1 file changed, 14 insertions(+)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 1a4b9266..88bb7349 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -822,6 +822,13 @@ async def _parse_extraction_result(
     maybe_nodes = defaultdict(list)
     maybe_edges = defaultdict(list)
 
+    # Preventive fix: when tuple_delimiter is <|>, fix LLM output instability issues
+    if context_base["tuple_delimiter"] == "<|>":
+        # 1. Convert <||> to <|>
+        extraction_result = extraction_result.replace("<||>", "<|>")
+        # 2. Convert < | > to <|>
+        extraction_result = extraction_result.replace("< | >", "<|>")
+
     # Parse the extraction result using the same logic as in extract_entities
     records = split_string_by_multi_markers(
         extraction_result,
@@ -1729,6 +1736,13 @@ async def extract_entities(
         maybe_nodes = defaultdict(list)
         maybe_edges = defaultdict(list)
 
+        # Preventive fix: when tuple_delimiter is <|>, fix LLM output instability issues
+        if context_base["tuple_delimiter"] == "<|>":
+            # 1. Convert <||> to <|>
+            result = result.replace("<||>", "<|>")
+            # 2. Convert < | > to <|>
+            result = result.replace("< | >", "<|>")
+
         records = split_string_by_multi_markers(
             result,
             [context_base["record_delimiter"], context_base["completion_delimiter"]],

From 30be70991db6567f2525d3f48431c9c33e4d70c8 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 1 Sep 2025 01:23:22 +0800
Subject: [PATCH 098/141] Bump API version to 0211

---
 lightrag/api/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lightrag/api/__init__.py b/lightrag/api/__init__.py
index 5ae0d6ba..d33fbb77 100644
--- a/lightrag/api/__init__.py
+++ b/lightrag/api/__init__.py
@@ -1 +1 @@
-__api_version__ = "0210"
+__api_version__ = "0211"

From e95622ca7b2943271d207d2061cc2864af7c849f Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 1 Sep 2025 07:17:30 +0800
Subject: [PATCH 099/141] fix(utils): enhance remove_think_tags to handle
 orphaned </think> closing tags

The function now properly handles cases where text contains </think> closing tags
without corresponding <think> opening tags, which can occur due to content
truncation or processing errors.
---
 lightrag/utils.py | 15 ++++++---------
 1 file changed, 6 insertions(+), 9 deletions(-)

diff --git a/lightrag/utils.py b/lightrag/utils.py
index 7c92d99c..c215d52b 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -1594,8 +1594,11 @@ async def update_chunk_cache_list(
 
 
 def remove_think_tags(text: str) -> str:
-    """Remove <think> tags from the text"""
-    return re.sub(r"^(<think>.*?</think>|<think>)", "", text, flags=re.DOTALL).strip()
+    """Remove <think>...</think> tags from the text
+    Remove  orphon ...</think> tags from the text also"""
+    return re.sub(
+        r"^(<think>.*?</think>|.*</think>)", "", text, flags=re.DOTALL
+    ).strip()
 
 
 async def use_llm_func_with_cache(
@@ -1678,13 +1681,7 @@ async def use_llm_func_with_cache(
         if max_tokens is not None:
             kwargs["max_tokens"] = max_tokens
 
-        try:
-            res: str = await use_llm_func(safe_input_text, **kwargs)
-        except Exception as e:
-            # Add [LLM func] prefix to error message
-            error_msg = f"[LLM func] {str(e)}"
-            # Re-raise with the same exception type but modified message
-            raise type(e)(error_msg) from e
+        res: str = await use_llm_func(safe_input_text, **kwargs)
 
         res = remove_think_tags(res)
 

From 692357fbf371a795272c3bf114038f301193b6be Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 1 Sep 2025 08:51:19 +0800
Subject: [PATCH 100/141] Add conflict resolution instruction to entity
 summarization prompt

- Add conflict handling step
- Handle entities with same name
- Separate then consolidate summaries
---
 lightrag/prompt.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index 51d15bc0..0bb22aa7 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -174,9 +174,10 @@ Your task is to synthesize a list of descriptions of a given entity or relation
 ---Instructions---
 1. **Comprehensiveness:** The summary must integrate key information from all provided descriptions. Do not omit important facts.
 2. **Context:** The summary must explicitly mention the name of the entity or relation for full context.
-3. **Style:** The output must be written from an objective, third-person perspective.
-4. **Length:** Maintain depth and completeness while ensuring the summary's length not exceed {summary_length} tokens.
-5. **Language:** The entire output must be written in {language}.
+3. **Conflict:** In case of conflicting or inconsistent descriptions, determine if they originate from multiple, distinct entities or relationships that share the same name. If so, summarize each entity or relationship separately and then consolidate all summaries.
+4. **Style:** The output must be written from an objective, third-person perspective.
+5. **Length:** Maintain depth and completeness while ensuring the summary's length not exceed {summary_length} tokens.
+6. **Language:** The entire output must be written in {language}.
 
 ---Data---
 {description_type} Name: {description_name}

From 7baeb186c6ea9d0bf535f7236928e3b6e6570925 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 1 Sep 2025 10:10:45 +0800
Subject: [PATCH 101/141] Fix regex to use non-greedy matching for parentheses
 extraction

---
 lightrag/operate.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 88bb7349..0cf1248e 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -835,7 +835,7 @@ async def _parse_extraction_result(
         [context_base["record_delimiter"], context_base["completion_delimiter"]],
     )
     for record in records:
-        record = re.search(r"\((.*)\)", record)
+        record = re.search(r"\((.*?)\)", record)
         if record is None:
             continue
         record = record.group(1)
@@ -1749,7 +1749,7 @@ async def extract_entities(
         )
 
         for record in records:
-            record = re.search(r"\((.*)\)", record)
+            record = re.search(r"\((.*?)\)", record)
             if record is None:
                 continue
             record = record.group(1)

From 8bbf307aebe502e535b6010623438dace4e0be54 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Mon, 1 Sep 2025 10:35:06 +0800
Subject: [PATCH 102/141] Fix regex to match multiline content in extraction
 parsing
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Remove non-greedy quantifier
• Add DOTALL flag for multiline matching
• Apply to both parsing functions
• Enable cross-line content extraction
---
 lightrag/operate.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 0cf1248e..607143a5 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -835,7 +835,7 @@ async def _parse_extraction_result(
         [context_base["record_delimiter"], context_base["completion_delimiter"]],
     )
     for record in records:
-        record = re.search(r"\((.*?)\)", record)
+        record = re.search(r"\((.*)\)", record, re.DOTALL)
         if record is None:
             continue
         record = record.group(1)
@@ -1749,7 +1749,7 @@ async def extract_entities(
         )
 
         for record in records:
-            record = re.search(r"\((.*?)\)", record)
+            record = re.search(r"\((.*)\)", record, re.DOTALL)
             if record is None:
                 continue
             record = record.group(1)

From 3cdc98f366db6f5307ed816dd496e624d23b6b8a Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 2 Sep 2025 00:26:04 +0800
Subject: [PATCH 103/141] Improve extraction parsing with better bracket
 handling and delimiter fixes
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Standardize Chinese/English brackets
• Fix incomplete tuple delimiters
• Remove duplicate delimiter fix code
• Support mixed bracket formats
• Enhance record parsing robustness
---
 lightrag/operate.py | 63 +++++++++++++++++++++++++++++++++------------
 1 file changed, 47 insertions(+), 16 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 607143a5..1d0821c3 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -822,23 +822,39 @@ async def _parse_extraction_result(
     maybe_nodes = defaultdict(list)
     maybe_edges = defaultdict(list)
 
-    # Preventive fix: when tuple_delimiter is <|>, fix LLM output instability issues
-    if context_base["tuple_delimiter"] == "<|>":
-        # 1. Convert <||> to <|>
-        extraction_result = extraction_result.replace("<||>", "<|>")
-        # 2. Convert < | > to <|>
-        extraction_result = extraction_result.replace("< | >", "<|>")
+    # Standardize Chinese brackets around record_delimiter to English brackets
+    record_delimiter = context_base["record_delimiter"]
+    bracket_pattern = f"[）)](\\s*{re.escape(record_delimiter)}\\s*)[（(]"
+    extraction_result = re.sub(bracket_pattern, ")\\1(", extraction_result)
 
     # Parse the extraction result using the same logic as in extract_entities
     records = split_string_by_multi_markers(
         extraction_result,
         [context_base["record_delimiter"], context_base["completion_delimiter"]],
     )
+
     for record in records:
-        record = re.search(r"\((.*)\)", record, re.DOTALL)
+        # Remove outer brackets
+        record = record.strip()
+        if record.startswith("(") or record.startswith("（"):
+            record = record[1:]
+        if record.endswith(")") or record.endswith("）"):
+            record = record[:-1]
+
+        record = record.strip()
         if record is None:
             continue
-        record = record.group(1)
+
+        if context_base["tuple_delimiter"] == "<|>":
+            # fix entity<| with entity<|>
+            record = re.sub(r"^entity<\|(?!>)", r"entity<|>", record)
+            # fix relationship<| with relationship<|>
+            record = re.sub(r"^relationship<\|(?!>)", r"relationship<|>", record)
+            # fix <||> with <|>
+            record = record.replace("<||>", "<|>")
+            # fix  < | > with <|>
+            record = record.replace("< | >", "<|>")
+
         record_attributes = split_string_by_multi_markers(
             record, [context_base["tuple_delimiter"]]
         )
@@ -1736,12 +1752,10 @@ async def extract_entities(
         maybe_nodes = defaultdict(list)
         maybe_edges = defaultdict(list)
 
-        # Preventive fix: when tuple_delimiter is <|>, fix LLM output instability issues
-        if context_base["tuple_delimiter"] == "<|>":
-            # 1. Convert <||> to <|>
-            result = result.replace("<||>", "<|>")
-            # 2. Convert < | > to <|>
-            result = result.replace("< | >", "<|>")
+        # Standardize Chinese brackets around record_delimiter to English brackets
+        record_delimiter = context_base["record_delimiter"]
+        bracket_pattern = f"[）)](\\s*{re.escape(record_delimiter)}\\s*)[（(]"
+        result = re.sub(bracket_pattern, ")\\1(", result)
 
         records = split_string_by_multi_markers(
             result,
@@ -1749,10 +1763,27 @@ async def extract_entities(
         )
 
         for record in records:
-            record = re.search(r"\((.*)\)", record, re.DOTALL)
+            # Remove outer brackets (support English and Chinese brackets)
+            record = record.strip()
+            if record.startswith("(") or record.startswith("（"):
+                record = record[1:]
+            if record.endswith(")") or record.endswith("）"):
+                record = record[:-1]
+
+            record = record.strip()
             if record is None:
                 continue
-            record = record.group(1)
+
+            if context_base["tuple_delimiter"] == "<|>":
+                # fix entity<| with entity<|>
+                record = re.sub(r"^entity<\|(?!>)", r"entity<|>", record)
+                # fix relationship<| with relationship<|>
+                record = re.sub(r"^relationship<\|(?!>)", r"relationship<|>", record)
+                # fix <||> with <|>
+                record = record.replace("<||>", "<|>")
+                # fix  < | > with <|>
+                record = record.replace("< | >", "<|>")
+
             record_attributes = split_string_by_multi_markers(
                 record, [context_base["tuple_delimiter"]]
             )

From 3f8a9abe7ed19f11008f78ede3d367386d19a4ee Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 2 Sep 2025 01:22:29 +0800
Subject: [PATCH 104/141] Refactor extraction result processing to reduce code
 duplication
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Extract shared processing logic
• Add delimiter pattern fixes
• Improve bracket standardization
---
 lightrag/operate.py | 229 +++++++++++++++++++-------------------------
 1 file changed, 101 insertions(+), 128 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 1d0821c3..ccf2550d 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -793,6 +793,87 @@ async def _get_cached_extraction_results(
     return sorted_cached_results
 
 
+async def _process_extraction_result(
+    result: str,
+    chunk_key: str,
+    file_path: str = "unknown_source",
+    tuple_delimiter: str = "<|>",
+    record_delimiter: str = "##",
+    completion_delimiter: str = "<|COMPLETE|>",
+) -> tuple[dict, dict]:
+    """Process a single extraction result (either initial or gleaning)
+    Args:
+        result (str): The extraction result to process
+        chunk_key (str): The chunk key for source tracking
+        file_path (str): The file path for citation
+        tuple_delimiter (str): Delimiter for tuple fields
+        record_delimiter (str): Delimiter for records
+        completion_delimiter (str): Delimiter for completion
+    Returns:
+        tuple: (nodes_dict, edges_dict) containing the extracted entities and relationships
+    """
+    maybe_nodes = defaultdict(list)
+    maybe_edges = defaultdict(list)
+
+    # Standardize Chinese brackets around record_delimiter to English brackets
+    bracket_pattern = f"[）)](\\s*{re.escape(record_delimiter)}\\s*)[（(]"
+    result = re.sub(bracket_pattern, ")\\1(", result)
+
+    records = split_string_by_multi_markers(
+        result,
+        [record_delimiter, completion_delimiter],
+    )
+
+    for record in records:
+        # Remove outer brackets (support English and Chinese brackets)
+        record = record.strip()
+        if record.startswith("(") or record.startswith("（"):
+            record = record[1:]
+        if record.endswith(")") or record.endswith("）"):
+            record = record[:-1]
+
+        record = record.strip()
+        if record is None:
+            continue
+
+        if tuple_delimiter == "<|>":
+            # fix entity<| with entity<|>
+            record = re.sub(r"^entity<\|(?!>)", r"entity<|>", record)
+            # fix relationship<| with relationship<|>
+            record = re.sub(r"^relationship<\|(?!>)", r"relationship<|>", record)
+            # fix <||> with <|>
+            record = record.replace("<||>", "<|>")
+            # fix  < | > with <|>
+            record = record.replace("< | >", "<|>")
+            # fix <<|>> with <|>
+            record = record.replace("<<|>>", "<|>")
+            # fix <|>> with <|>
+            record = record.replace("<|>>", "<|>")
+            # fix <<|> with <|>
+            record = record.replace("<<|>", "<|>")
+
+        record_attributes = split_string_by_multi_markers(record, [tuple_delimiter])
+
+        # Try to parse as entity
+        entity_data = await _handle_single_entity_extraction(
+            record_attributes, chunk_key, file_path
+        )
+        if entity_data is not None:
+            maybe_nodes[entity_data["entity_name"]].append(entity_data)
+            continue
+
+        # Try to parse as relationship
+        relationship_data = await _handle_single_relationship_extraction(
+            record_attributes, chunk_key, file_path
+        )
+        if relationship_data is not None:
+            maybe_edges[
+                (relationship_data["src_id"], relationship_data["tgt_id"])
+            ].append(relationship_data)
+
+    return dict(maybe_nodes), dict(maybe_edges)
+
+
 async def _parse_extraction_result(
     text_chunks_storage: BaseKVStorage, extraction_result: str, chunk_id: str
 ) -> tuple[dict, dict]:
@@ -814,69 +895,16 @@ async def _parse_extraction_result(
         if chunk_data
         else "unknown_source"
     )
-    context_base = dict(
+
+    # Call the shared processing function
+    return await _process_extraction_result(
+        extraction_result,
+        chunk_id,
+        file_path,
         tuple_delimiter=PROMPTS["DEFAULT_TUPLE_DELIMITER"],
         record_delimiter=PROMPTS["DEFAULT_RECORD_DELIMITER"],
         completion_delimiter=PROMPTS["DEFAULT_COMPLETION_DELIMITER"],
     )
-    maybe_nodes = defaultdict(list)
-    maybe_edges = defaultdict(list)
-
-    # Standardize Chinese brackets around record_delimiter to English brackets
-    record_delimiter = context_base["record_delimiter"]
-    bracket_pattern = f"[）)](\\s*{re.escape(record_delimiter)}\\s*)[（(]"
-    extraction_result = re.sub(bracket_pattern, ")\\1(", extraction_result)
-
-    # Parse the extraction result using the same logic as in extract_entities
-    records = split_string_by_multi_markers(
-        extraction_result,
-        [context_base["record_delimiter"], context_base["completion_delimiter"]],
-    )
-
-    for record in records:
-        # Remove outer brackets
-        record = record.strip()
-        if record.startswith("(") or record.startswith("（"):
-            record = record[1:]
-        if record.endswith(")") or record.endswith("）"):
-            record = record[:-1]
-
-        record = record.strip()
-        if record is None:
-            continue
-
-        if context_base["tuple_delimiter"] == "<|>":
-            # fix entity<| with entity<|>
-            record = re.sub(r"^entity<\|(?!>)", r"entity<|>", record)
-            # fix relationship<| with relationship<|>
-            record = re.sub(r"^relationship<\|(?!>)", r"relationship<|>", record)
-            # fix <||> with <|>
-            record = record.replace("<||>", "<|>")
-            # fix  < | > with <|>
-            record = record.replace("< | >", "<|>")
-
-        record_attributes = split_string_by_multi_markers(
-            record, [context_base["tuple_delimiter"]]
-        )
-
-        # Try to parse as entity
-        entity_data = await _handle_single_entity_extraction(
-            record_attributes, chunk_id, file_path
-        )
-        if entity_data is not None:
-            maybe_nodes[entity_data["entity_name"]].append(entity_data)
-            continue
-
-        # Try to parse as relationship
-        relationship_data = await _handle_single_relationship_extraction(
-            record_attributes, chunk_id, file_path
-        )
-        if relationship_data is not None:
-            maybe_edges[
-                (relationship_data["src_id"], relationship_data["tgt_id"])
-            ].append(relationship_data)
-
-    return dict(maybe_nodes), dict(maybe_edges)
 
 
 async def _rebuild_single_entity(
@@ -1738,73 +1766,6 @@ async def extract_entities(
     processed_chunks = 0
     total_chunks = len(ordered_chunks)
 
-    async def _process_extraction_result(
-        result: str, chunk_key: str, file_path: str = "unknown_source"
-    ):
-        """Process a single extraction result (either initial or gleaning)
-        Args:
-            result (str): The extraction result to process
-            chunk_key (str): The chunk key for source tracking
-            file_path (str): The file path for citation
-        Returns:
-            tuple: (nodes_dict, edges_dict) containing the extracted entities and relationships
-        """
-        maybe_nodes = defaultdict(list)
-        maybe_edges = defaultdict(list)
-
-        # Standardize Chinese brackets around record_delimiter to English brackets
-        record_delimiter = context_base["record_delimiter"]
-        bracket_pattern = f"[）)](\\s*{re.escape(record_delimiter)}\\s*)[（(]"
-        result = re.sub(bracket_pattern, ")\\1(", result)
-
-        records = split_string_by_multi_markers(
-            result,
-            [context_base["record_delimiter"], context_base["completion_delimiter"]],
-        )
-
-        for record in records:
-            # Remove outer brackets (support English and Chinese brackets)
-            record = record.strip()
-            if record.startswith("(") or record.startswith("（"):
-                record = record[1:]
-            if record.endswith(")") or record.endswith("）"):
-                record = record[:-1]
-
-            record = record.strip()
-            if record is None:
-                continue
-
-            if context_base["tuple_delimiter"] == "<|>":
-                # fix entity<| with entity<|>
-                record = re.sub(r"^entity<\|(?!>)", r"entity<|>", record)
-                # fix relationship<| with relationship<|>
-                record = re.sub(r"^relationship<\|(?!>)", r"relationship<|>", record)
-                # fix <||> with <|>
-                record = record.replace("<||>", "<|>")
-                # fix  < | > with <|>
-                record = record.replace("< | >", "<|>")
-
-            record_attributes = split_string_by_multi_markers(
-                record, [context_base["tuple_delimiter"]]
-            )
-
-            if_entities = await _handle_single_entity_extraction(
-                record_attributes, chunk_key, file_path
-            )
-            if if_entities is not None:
-                maybe_nodes[if_entities["entity_name"]].append(if_entities)
-                continue
-
-            if_relation = await _handle_single_relationship_extraction(
-                record_attributes, chunk_key, file_path
-            )
-            if if_relation is not None:
-                maybe_edges[(if_relation["src_id"], if_relation["tgt_id"])].append(
-                    if_relation
-                )
-
-        return maybe_nodes, maybe_edges
-
     async def _process_single_content(chunk_key_dp: tuple[str, TextChunkSchema]):
         """Process a single chunk
         Args:
@@ -1842,7 +1803,12 @@ async def extract_entities(
 
         # Process initial extraction with file path
         maybe_nodes, maybe_edges = await _process_extraction_result(
-            final_result, chunk_key, file_path
+            final_result,
+            chunk_key,
+            file_path,
+            tuple_delimiter=context_base["tuple_delimiter"],
+            record_delimiter=context_base["record_delimiter"],
+            completion_delimiter=context_base["completion_delimiter"],
         )
 
         # Process additional gleaning results
@@ -1861,7 +1827,12 @@ async def extract_entities(
 
             # Process gleaning result separately with file path
             glean_nodes, glean_edges = await _process_extraction_result(
-                glean_result, chunk_key, file_path
+                glean_result,
+                chunk_key,
+                file_path,
+                tuple_delimiter=context_base["tuple_delimiter"],
+                record_delimiter=context_base["record_delimiter"],
+                completion_delimiter=context_base["completion_delimiter"],
             )
 
             # Merge results - only add entities and edges with new names
@@ -1869,11 +1840,13 @@ async def extract_entities(
                 if (
                     entity_name not in maybe_nodes
                 ):  # Only accetp entities with new name in gleaning stage
+                    maybe_nodes[entity_name] = []  # Explicitly create the list
                     maybe_nodes[entity_name].extend(entities)
             for edge_key, edges in glean_edges.items():
                 if (
                     edge_key not in maybe_edges
                 ):  # Only accetp edges with new name in gleaning stage
+                    maybe_edges[edge_key] = []  # Explicitly create the list
                     maybe_edges[edge_key].extend(edges)
 
             if now_glean_index == entity_extract_max_gleaning - 1:

From 29f0ecc88ca31c2aa18d3a06bcc3a33df5c947c4 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 2 Sep 2025 02:14:14 +0800
Subject: [PATCH 105/141] Refactor entity extraction prompts and remove
 completion delimiter
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Update prompt structure and wording
• Remove deprecated completion delimiter
• Add quality guidelines section
• Improve instruction clarity
• Enhance continue extraction prompt
---
 lightrag/prompt.py | 34 +++++++++++++++++-----------------
 1 file changed, 17 insertions(+), 17 deletions(-)

diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index 0bb22aa7..c71debe8 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -6,15 +6,16 @@ PROMPTS: dict[str, Any] = {}
 
 PROMPTS["DEFAULT_TUPLE_DELIMITER"] = "<|>"
 PROMPTS["DEFAULT_RECORD_DELIMITER"] = "##"
+
+# TODO: Deprecated, reserved for compatible with legacy LLM cache
 PROMPTS["DEFAULT_COMPLETION_DELIMITER"] = "<|COMPLETE|>"
 
 PROMPTS["DEFAULT_USER_PROMPT"] = "n/a"
 
-PROMPTS["entity_extraction"] = """---Goal---
+PROMPTS["entity_extraction"] = """---Task---
 Given a text document that is potentially relevant to this activity and a list of entity types, identify all entities of those types from the text and all relationships among the identified entities.
-Use {language} as output language.
 
----Steps---
+---Instructions---
 1. Recognizing definitively conceptualized entities in text. For each identified entity, extract the following information:
 - entity_name: Name of the entity, use same language as input text. If English, capitalized the name
 - entity_type: One of the following types: [{entity_types}]. If the entity doesn't clearly fit any category, classify it as "Other".
@@ -33,11 +34,9 @@ For each pair of related entities, extract the following information:
 4. Format each relationship as:
 ("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
 
-5. Use `{tuple_delimiter}` as field delimiter. Use `{record_delimiter}` as the list delimiter. Ensure no spaces are added around the delimiters.
+5. Use `{tuple_delimiter}` as field delimiter. Use `{record_delimiter}` as the entity or relation list delimiter.
 
-6. When finished, output `{completion_delimiter}`
-
-7. Return identified entities and relationships in {language}.
+6. Return identified entities and relationships in {language}.
 
 ---Quality Guidelines---
 - Only extract entities that are clearly defined and meaningful in the context
@@ -85,7 +84,6 @@ Output:
 (relationship{tuple_delimiter}Taylor{tuple_delimiter}Jordan{tuple_delimiter}conflict resolution, mutual respect{tuple_delimiter}Taylor and Jordan interact directly regarding the device, leading to a moment of mutual respect and an uneasy truce.){record_delimiter}
 (relationship{tuple_delimiter}Jordan{tuple_delimiter}Cruz{tuple_delimiter}ideological conflict, rebellion{tuple_delimiter}Jordan's commitment to discovery is in rebellion against Cruz's vision of control and order.){record_delimiter}
 (relationship{tuple_delimiter}Taylor{tuple_delimiter}The Device{tuple_delimiter}reverence, technological significance{tuple_delimiter}Taylor shows reverence towards the device, indicating its importance and potential impact.){record_delimiter}
-{completion_delimiter}
 
 """,
     """------Example 2------
@@ -115,7 +113,6 @@ Output:
 (relationship{tuple_delimiter}Nexon Technologies{tuple_delimiter}Global Tech Index{tuple_delimiter}company impact, index movement{tuple_delimiter}Nexon Technologies' stock decline contributed to the overall drop in the Global Tech Index.){record_delimiter}
 (relationship{tuple_delimiter}Gold Futures{tuple_delimiter}Market Selloff{tuple_delimiter}market reaction, safe-haven investment{tuple_delimiter}Gold prices rose as investors sought safe-haven assets during the market selloff.){record_delimiter}
 (relationship{tuple_delimiter}Federal Reserve Policy Announcement{tuple_delimiter}Market Selloff{tuple_delimiter}interest rate impact, financial regulation{tuple_delimiter}Speculation over Federal Reserve policy changes contributed to market volatility and investor selloff.){record_delimiter}
-{completion_delimiter}
 
 """,
     """------Example 3------
@@ -137,7 +134,6 @@ Output:
 (relationship{tuple_delimiter}Noah Carter{tuple_delimiter}100m Sprint Record{tuple_delimiter}athlete achievement, record-breaking{tuple_delimiter}Noah Carter set a new 100m sprint record at the championship.){record_delimiter}
 (relationship{tuple_delimiter}Noah Carter{tuple_delimiter}Carbon-Fiber Spikes{tuple_delimiter}athletic equipment, performance boost{tuple_delimiter}Noah Carter used carbon-fiber spikes to enhance performance during the race.){record_delimiter}
 (relationship{tuple_delimiter}Noah Carter{tuple_delimiter}World Athletics Championship{tuple_delimiter}athlete participation, competition{tuple_delimiter}Noah Carter is competing at the World Athletics Championship.){record_delimiter}
-{completion_delimiter}
 
 """,
     """------Example 4------
@@ -146,7 +142,6 @@ Entity_types: [organization,person,equiment,product,technology,location,event,ca
 Text:
 ```
 在北京举行的人工智能大会上，腾讯公司的首席技术官张伟发布了最新的大语言模型"腾讯智言"，该模型在自然语言处理方面取得了重大突破。
-
 ```
 
 Output:
@@ -160,7 +155,6 @@ Output:
 (relationship{tuple_delimiter}张伟{tuple_delimiter}腾讯公司{tuple_delimiter}雇佣关系, 高管职位{tuple_delimiter}张伟担任腾讯公司的首席技术官。){record_delimiter}
 (relationship{tuple_delimiter}张伟{tuple_delimiter}腾讯智言{tuple_delimiter}产品发布, 技术展示{tuple_delimiter}张伟在大会上发布了腾讯智言大语言模型。){record_delimiter}
 (relationship{tuple_delimiter}腾讯智言{tuple_delimiter}自然语言处理技术{tuple_delimiter}技术应用, 突破创新{tuple_delimiter}腾讯智言在自然语言处理技术方面取得了重大突破。){record_delimiter}
-{completion_delimiter}
 
 """,
 ]
@@ -188,9 +182,10 @@ Description List:
 Output:"""
 
 PROMPTS["entity_continue_extraction"] = """
-MANY entities and relationships were missed in the last extraction. Please find only the missing entities and relationships from previous text. Do not include entities and relations that have been previously extracted. :\n
+---Task---
+MANY entities and relationships were missed in the last extraction. Please find only the missing entities and relationships from previous text.
 
----Remember Steps---
+---Instructions---
 1. Recognizing definitively conceptualized entities in text. For each identified entity, extract the following information:
 - entity_name: Name of the entity, use same language as input text. If English, capitalized the name
 - entity_type: One of the following types: [{entity_types}]. If the entity doesn't clearly fit any category, classify it as "Other".
@@ -209,11 +204,16 @@ For each pair of related entities, extract the following information:
 4. Format each relationship as:
 ("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
 
-5. Use `{tuple_delimiter}` as field delimiter. Use `{record_delimiter}` as the list delimiter. Ensure no spaces are added around the delimiters.
+5. Use `{tuple_delimiter}` as field delimiter. Use `{record_delimiter}` as the entity or relation list delimiter.
 
-6. When finished, output `{completion_delimiter}`
+6. Return identified entities and relationships in {language}.
 
-7. Return identified entities and relationships in {language}.
+---Quality Guidelines---
+- Only extract entities that are clearly defined and meaningful in the context
+- Do not include entities and relations that have been previously extracted
+- Avoid over-interpretation; stick to what is explicitly stated in the text
+- Include specific numerical data in entity name when relevant
+- Ensure entity names are consistent throughout the extraction
 
 ---Output---
 Output:

From 5b2deccbef2fde022d567862500d5689db8bd475 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 2 Sep 2025 02:51:41 +0800
Subject: [PATCH 106/141] Improve text normalization and add entity type
 capitalization

- Capitalize entity types with .title()
- Add non-breaking space handling
- Add narrow non-breaking space regex
---
 lightrag/operate.py |  3 +++
 lightrag/utils.py   | 38 +++++++++++++++++++++++---------------
 2 files changed, 26 insertions(+), 15 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index ccf2550d..6c9a5538 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -347,6 +347,9 @@ async def _handle_single_entity_extraction(
             )
             return None
 
+        # Captitalize first letter of entity_type
+        entity_type = entity_type.title()
+
         # Process entity description with same cleaning pipeline
         entity_description = sanitize_and_normalize_extracted_text(record_attributes[3])
 
diff --git a/lightrag/utils.py b/lightrag/utils.py
index c215d52b..f2d56282 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -1759,17 +1759,22 @@ def sanitize_and_normalize_extracted_text(
 
 def normalize_extracted_info(name: str, remove_inner_quotes=False) -> str:
     """Normalize entity/relation names and description with the following rules:
-    1. Clean HTML tags (paragraph and line break tags)
-    2. Convert Chinese symbols to English symbols
-    3. Remove spaces between Chinese characters
-    4. Remove spaces between Chinese characters and English letters/numbers
-    5. Preserve spaces within English text and numbers
-    6. Replace Chinese parentheses with English parentheses
-    7. Replace Chinese dash with English dash
-    8. Remove English quotation marks from the beginning and end of the text
-    9. Remove English quotation marks in and around chinese
-    10. Remove Chinese quotation marks
-    11. Filter out short numeric-only text (length < 3 and only digits/dots)
+    - Clean HTML tags (paragraph and line break tags)
+    - Convert Chinese symbols to English symbols
+    - Remove spaces between Chinese characters
+    - Remove spaces between Chinese characters and English letters/numbers
+    - Preserve spaces within English text and numbers
+    - Replace Chinese parentheses with English parentheses
+    - Replace Chinese dash with English dash
+    - Remove English quotation marks from the beginning and end of the text
+    - Remove English quotation marks in and around chinese
+    - Remove Chinese quotation marks
+    - Filter out short numeric-only text (length < 3 and only digits/dots)
+    - remove_inner_quotes = True
+        remove Chinese quotes
+        remove English queotes in and around chinese
+        Convert non-breaking spaces to regular spaces
+        Convert narrow non-breaking spaces after non-digits to regular spaces
 
     Args:
         name: Entity name to normalize
@@ -1778,11 +1783,10 @@ def normalize_extracted_info(name: str, remove_inner_quotes=False) -> str:
     Returns:
         Normalized entity name
     """
-    # 1. Clean HTML tags - remove paragraph and line break tags
+    # Clean HTML tags - remove paragraph and line break tags
     name = re.sub(r"</p\s*>|<p\s*>|<p/>", "", name, flags=re.IGNORECASE)
     name = re.sub(r"</br\s*>|<br\s*>|<br/>", "", name, flags=re.IGNORECASE)
 
-    # 2. Convert Chinese symbols to English symbols
     # Chinese full-width letters to half-width (A-Z, a-z)
     name = name.translate(
         str.maketrans(
@@ -1849,11 +1853,15 @@ def normalize_extracted_info(name: str, remove_inner_quotes=False) -> str:
                 name = inner_content
 
     if remove_inner_quotes:
-        # remove Chinese quotes
+        # Remove Chinese quotes
         name = name.replace("“", "").replace("”", "").replace("‘", "").replace("’", "")
-        # remove English queotes in and around chinese
+        # Remove English queotes in and around chinese
         name = re.sub(r"['\"]+(?=[\u4e00-\u9fa5])", "", name)
         name = re.sub(r"(?<=[\u4e00-\u9fa5])['\"]+", "", name)
+        # Convert non-breaking space to regular space
+        name = name.replace("\u00a0", " ")
+        # Convert narrow non-breaking space to regular space when after non-digits
+        name = re.sub(r"(?<=[^\d])\u202F", " ", name)
 
     # Remove spaces from the beginning and end of the text
     name = name.strip()

From 4db43c43f3de1cb4d10df94ba531ea591128bf0c Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 2 Sep 2025 03:01:59 +0800
Subject: [PATCH 107/141] Add product and other entity type translations

- Add "product" translations
- Add "other" translations
- Update 5 locale files
- Extend entity type coverage
---
 lightrag_webui/src/locales/ar.json    | 4 +++-
 lightrag_webui/src/locales/en.json    | 4 +++-
 lightrag_webui/src/locales/fr.json    | 4 +++-
 lightrag_webui/src/locales/zh.json    | 4 +++-
 lightrag_webui/src/locales/zh_TW.json | 4 +++-
 5 files changed, 15 insertions(+), 5 deletions(-)

diff --git a/lightrag_webui/src/locales/ar.json b/lightrag_webui/src/locales/ar.json
index 41e98607..db50ab37 100644
--- a/lightrag_webui/src/locales/ar.json
+++ b/lightrag_webui/src/locales/ar.json
@@ -187,7 +187,9 @@
       "unknown": "غير معروف",
       "object": "مصنوع",
       "group": "مجموعة",
-      "technology": "العلوم"
+      "technology": "العلوم",
+      "product": "منتج",
+      "other": "أخرى"
     },
     "sideBar": {
       "settings": {
diff --git a/lightrag_webui/src/locales/en.json b/lightrag_webui/src/locales/en.json
index 58a57336..19006705 100644
--- a/lightrag_webui/src/locales/en.json
+++ b/lightrag_webui/src/locales/en.json
@@ -187,7 +187,9 @@
       "unknown": "Unknown",
       "object": "Object",
       "group": "Group",
-      "technology": "Technology"
+      "technology": "Technology",
+      "product": "Product",
+      "other": "Other"
     },
     "sideBar": {
       "settings": {
diff --git a/lightrag_webui/src/locales/fr.json b/lightrag_webui/src/locales/fr.json
index 59b8279b..f7327c70 100644
--- a/lightrag_webui/src/locales/fr.json
+++ b/lightrag_webui/src/locales/fr.json
@@ -187,7 +187,9 @@
       "unknown": "Inconnu",
       "object": "Objet",
       "group": "Groupe",
-      "technology": "Technologie"
+      "technology": "Technologie",
+      "product": "Produit",
+      "other": "Autre"
     },
     "sideBar": {
       "settings": {
diff --git a/lightrag_webui/src/locales/zh.json b/lightrag_webui/src/locales/zh.json
index abad2f63..a4d33509 100644
--- a/lightrag_webui/src/locales/zh.json
+++ b/lightrag_webui/src/locales/zh.json
@@ -187,7 +187,9 @@
       "unknown": "未知",
       "object": "物品",
       "group": "群组",
-      "technology": "技术"
+      "technology": "技术",
+      "product": "产品",
+      "other": "其他"
     },
     "sideBar": {
       "settings": {
diff --git a/lightrag_webui/src/locales/zh_TW.json b/lightrag_webui/src/locales/zh_TW.json
index 1f691ce6..b147b2cc 100644
--- a/lightrag_webui/src/locales/zh_TW.json
+++ b/lightrag_webui/src/locales/zh_TW.json
@@ -187,7 +187,9 @@
       "unknown": "未知",
       "object": "物品",
       "group": "群組",
-      "technology": "技術"
+      "technology": "技術",
+      "product": "產品",
+      "other": "其他"
     },
     "sideBar": {
       "settings": {

From 4e37ff5f2f9584a3970f118f13f592c56b06c116 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 2 Sep 2025 03:02:39 +0800
Subject: [PATCH 108/141] Bump API verstion to 0212

---
 lightrag/api/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lightrag/api/__init__.py b/lightrag/api/__init__.py
index d33fbb77..da0ff6dd 100644
--- a/lightrag/api/__init__.py
+++ b/lightrag/api/__init__.py
@@ -1 +1 @@
-__api_version__ = "0211"
+__api_version__ = "0212"

From 476b64c9d483081647bac59f336b37e078b04e16 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 2 Sep 2025 03:03:19 +0800
Subject: [PATCH 109/141] Update webui assets

---
 .../assets/{index-CIdJpUuC.js => index-CjbmYv_Z.js}    | 10 +++++-----
 lightrag/api/webui/index.html                          |  2 +-
 2 files changed, 6 insertions(+), 6 deletions(-)
 rename lightrag/api/webui/assets/{index-CIdJpUuC.js => index-CjbmYv_Z.js} (91%)

diff --git a/lightrag/api/webui/assets/index-CIdJpUuC.js b/lightrag/api/webui/assets/index-CjbmYv_Z.js
similarity index 91%
rename from lightrag/api/webui/assets/index-CIdJpUuC.js
rename to lightrag/api/webui/assets/index-CjbmYv_Z.js
index f8d9bf07..d31d07eb 100644
--- a/lightrag/api/webui/assets/index-CIdJpUuC.js
+++ b/lightrag/api/webui/assets/index-CjbmYv_Z.js
@@ -43,7 +43,7 @@ For more information, see https://radix-ui.com/primitives/docs/components/alert-
 {{error}}`,scanFailed:`Failed to scan documents
 {{error}}`,scanProgressFailed:`Failed to get scan progress
 {{error}}`},fileNameLabel:"File Name",showButton:"Show",hideButton:"Hide",showFileNameTooltip:"Show file name",hideFileNameTooltip:"Hide file name"},pipelineStatus:{title:"Pipeline Status",busy:"Pipeline Busy",requestPending:"Request Pending",jobName:"Job Name",startTime:"Start Time",progress:"Progress",unit:"batch",latestMessage:"Latest Message",historyMessages:"History Messages",errors:{fetchFailed:`Failed to get pipeline status
-{{error}}`}}},Bp={dataIsTruncated:"Graph data is truncated to Max Nodes",statusDialog:{title:"LightRAG Server Settings",description:"View current system status and connection information"},legend:"Legend",nodeTypes:{person:"Person",category:"Category",geo:"Geographic",location:"Location",organization:"Organization",event:"Event",equipment:"Equipment",weapon:"Weapon",animal:"Animal",unknown:"Unknown",object:"Object",group:"Group",technology:"Technology"},sideBar:{settings:{settings:"Settings",healthCheck:"Health Check",showPropertyPanel:"Show Property Panel",showSearchBar:"Show Search Bar",showNodeLabel:"Show Node Label",nodeDraggable:"Node Draggable",showEdgeLabel:"Show Edge Label",hideUnselectedEdges:"Hide Unselected Edges",edgeEvents:"Edge Events",maxQueryDepth:"Max Query Depth",maxNodes:"Max Nodes",maxLayoutIterations:"Max Layout Iterations",resetToDefault:"Reset to default",edgeSizeRange:"Edge Size Range",depth:"D",max:"Max",degree:"Degree",apiKey:"API Key",enterYourAPIkey:"Enter your API key",save:"Save",refreshLayout:"Refresh Layout"},zoomControl:{zoomIn:"Zoom In",zoomOut:"Zoom Out",resetZoom:"Reset Zoom",rotateCamera:"Clockwise Rotate",rotateCameraCounterClockwise:"Counter-Clockwise Rotate"},layoutsControl:{startAnimation:"Continue layout animation",stopAnimation:"Stop layout animation",layoutGraph:"Layout Graph",layouts:{Circular:"Circular",Circlepack:"Circlepack",Random:"Random",Noverlaps:"Noverlaps","Force Directed":"Force Directed","Force Atlas":"Force Atlas"}},fullScreenControl:{fullScreen:"Full Screen",windowed:"Windowed"},legendControl:{toggleLegend:"Toggle Legend"}},statusIndicator:{connected:"Connected",disconnected:"Disconnected"},statusCard:{unavailable:"Status information unavailable",serverInfo:"Server Info",workingDirectory:"Working Directory",inputDirectory:"Input Directory",maxParallelInsert:"Concurrent Doc Processing",summarySettings:"Summary Settings",llmConfig:"LLM Configuration",llmBinding:"LLM Binding",llmBindingHost:"LLM Endpoint",llmModel:"LLM Model",embeddingConfig:"Embedding Configuration",embeddingBinding:"Embedding Binding",embeddingBindingHost:"Embedding Endpoint",embeddingModel:"Embedding Model",storageConfig:"Storage Configuration",kvStorage:"KV Storage",docStatusStorage:"Doc Status Storage",graphStorage:"Graph Storage",vectorStorage:"Vector Storage",workspace:"Workspace",maxGraphNodes:"Max Graph Nodes",rerankerConfig:"Reranker Configuration",rerankerBindingHost:"Reranker Endpoint",rerankerModel:"Reranker Model",lockStatus:"Lock Status",threshold:"Threshold"},propertiesView:{editProperty:"Edit {{property}}",editPropertyDescription:"Edit the property value in the text area below.",errors:{duplicateName:"Node name already exists",updateFailed:"Failed to update node",tryAgainLater:"Please try again later"},success:{entityUpdated:"Node updated successfully",relationUpdated:"Relation updated successfully"},node:{title:"Node",id:"ID",labels:"Labels",degree:"Degree",properties:"Properties",relationships:"Relations(within subgraph)",expandNode:"Expand Node",pruneNode:"Prune Node",deleteAllNodesError:"Refuse to delete all nodes in the graph",nodesRemoved:"{{count}} nodes removed, including orphan nodes",noNewNodes:"No expandable nodes found",propertyNames:{description:"Description",entity_id:"Name",entity_type:"Type",source_id:"SrcID",Neighbour:"Neigh",file_path:"Source",keywords:"Keys",weight:"Weight"}},edge:{title:"Relationship",id:"ID",type:"Type",source:"Source",target:"Target",properties:"Properties"}},search:{placeholder:"Search nodes...",message:"And {count} others"},graphLabels:{selectTooltip:"Select query label",noLabels:"No labels found",label:"Label",placeholder:"Search labels...",andOthers:"And {count} others",refreshTooltip:"Reload data(After file added)"},emptyGraph:"Empty(Try Reload Again)"},Gp={chatMessage:{copyTooltip:"Copy to clipboard",copyError:"Failed to copy text to clipboard"},retrieval:{startPrompt:"Start a retrieval by typing your query below",clear:"Clear",send:"Send",placeholder:"Enter your query (Support prefix: /<Query Mode>)",error:"Error: Failed to get response",queryModeError:"Only supports the following query modes: {{modes}}",queryModePrefixInvalid:"Invalid query mode prefix. Use: /<mode> [space] your query"},querySettings:{parametersTitle:"Parameters",parametersDescription:"Configure your query parameters",queryMode:"Query Mode",queryModeTooltip:`Select the retrieval strategy:
+{{error}}`}}},Bp={dataIsTruncated:"Graph data is truncated to Max Nodes",statusDialog:{title:"LightRAG Server Settings",description:"View current system status and connection information"},legend:"Legend",nodeTypes:{person:"Person",category:"Category",geo:"Geographic",location:"Location",organization:"Organization",event:"Event",equipment:"Equipment",weapon:"Weapon",animal:"Animal",unknown:"Unknown",object:"Object",group:"Group",technology:"Technology",product:"Product",other:"Other"},sideBar:{settings:{settings:"Settings",healthCheck:"Health Check",showPropertyPanel:"Show Property Panel",showSearchBar:"Show Search Bar",showNodeLabel:"Show Node Label",nodeDraggable:"Node Draggable",showEdgeLabel:"Show Edge Label",hideUnselectedEdges:"Hide Unselected Edges",edgeEvents:"Edge Events",maxQueryDepth:"Max Query Depth",maxNodes:"Max Nodes",maxLayoutIterations:"Max Layout Iterations",resetToDefault:"Reset to default",edgeSizeRange:"Edge Size Range",depth:"D",max:"Max",degree:"Degree",apiKey:"API Key",enterYourAPIkey:"Enter your API key",save:"Save",refreshLayout:"Refresh Layout"},zoomControl:{zoomIn:"Zoom In",zoomOut:"Zoom Out",resetZoom:"Reset Zoom",rotateCamera:"Clockwise Rotate",rotateCameraCounterClockwise:"Counter-Clockwise Rotate"},layoutsControl:{startAnimation:"Continue layout animation",stopAnimation:"Stop layout animation",layoutGraph:"Layout Graph",layouts:{Circular:"Circular",Circlepack:"Circlepack",Random:"Random",Noverlaps:"Noverlaps","Force Directed":"Force Directed","Force Atlas":"Force Atlas"}},fullScreenControl:{fullScreen:"Full Screen",windowed:"Windowed"},legendControl:{toggleLegend:"Toggle Legend"}},statusIndicator:{connected:"Connected",disconnected:"Disconnected"},statusCard:{unavailable:"Status information unavailable",serverInfo:"Server Info",workingDirectory:"Working Directory",inputDirectory:"Input Directory",maxParallelInsert:"Concurrent Doc Processing",summarySettings:"Summary Settings",llmConfig:"LLM Configuration",llmBinding:"LLM Binding",llmBindingHost:"LLM Endpoint",llmModel:"LLM Model",embeddingConfig:"Embedding Configuration",embeddingBinding:"Embedding Binding",embeddingBindingHost:"Embedding Endpoint",embeddingModel:"Embedding Model",storageConfig:"Storage Configuration",kvStorage:"KV Storage",docStatusStorage:"Doc Status Storage",graphStorage:"Graph Storage",vectorStorage:"Vector Storage",workspace:"Workspace",maxGraphNodes:"Max Graph Nodes",rerankerConfig:"Reranker Configuration",rerankerBindingHost:"Reranker Endpoint",rerankerModel:"Reranker Model",lockStatus:"Lock Status",threshold:"Threshold"},propertiesView:{editProperty:"Edit {{property}}",editPropertyDescription:"Edit the property value in the text area below.",errors:{duplicateName:"Node name already exists",updateFailed:"Failed to update node",tryAgainLater:"Please try again later"},success:{entityUpdated:"Node updated successfully",relationUpdated:"Relation updated successfully"},node:{title:"Node",id:"ID",labels:"Labels",degree:"Degree",properties:"Properties",relationships:"Relations(within subgraph)",expandNode:"Expand Node",pruneNode:"Prune Node",deleteAllNodesError:"Refuse to delete all nodes in the graph",nodesRemoved:"{{count}} nodes removed, including orphan nodes",noNewNodes:"No expandable nodes found",propertyNames:{description:"Description",entity_id:"Name",entity_type:"Type",source_id:"SrcID",Neighbour:"Neigh",file_path:"Source",keywords:"Keys",weight:"Weight"}},edge:{title:"Relationship",id:"ID",type:"Type",source:"Source",target:"Target",properties:"Properties"}},search:{placeholder:"Search nodes...",message:"And {count} others"},graphLabels:{selectTooltip:"Select query label",noLabels:"No labels found",label:"Label",placeholder:"Search labels...",andOthers:"And {count} others",refreshTooltip:"Reload data(After file added)"},emptyGraph:"Empty(Try Reload Again)"},Gp={chatMessage:{copyTooltip:"Copy to clipboard",copyError:"Failed to copy text to clipboard"},retrieval:{startPrompt:"Start a retrieval by typing your query below",clear:"Clear",send:"Send",placeholder:"Enter your query (Support prefix: /<Query Mode>)",error:"Error: Failed to get response",queryModeError:"Only supports the following query modes: {{modes}}",queryModePrefixInvalid:"Invalid query mode prefix. Use: /<mode> [space] your query"},querySettings:{parametersTitle:"Parameters",parametersDescription:"Configure your query parameters",queryMode:"Query Mode",queryModeTooltip:`Select the retrieval strategy:
 • Naive: Basic search without advanced techniques
 • Local: Context-dependent information retrieval
 • Global: Utilizes global knowledge base
@@ -67,7 +67,7 @@ For more information, see https://radix-ui.com/primitives/docs/components/alert-
 {{error}}`,scanFailed:`扫描文档失败
 {{error}}`,scanProgressFailed:`获取扫描进度失败
 {{error}}`},fileNameLabel:"文件名",showButton:"显示",hideButton:"隐藏",showFileNameTooltip:"显示文件名",hideFileNameTooltip:"隐藏文件名"},pipelineStatus:{title:"流水线状态",busy:"流水线忙碌",requestPending:"待处理请求",jobName:"作业名称",startTime:"开始时间",progress:"进度",unit:"批",latestMessage:"最新消息",historyMessages:"历史消息",errors:{fetchFailed:`获取流水线状态失败
-{{error}}`}}},Fp={dataIsTruncated:"图数据已截断至最大返回节点数",statusDialog:{title:"LightRAG 服务器设置",description:"查看当前系统状态和连接信息"},legend:"图例",nodeTypes:{person:"人物角色",category:"分类",geo:"地理名称",location:"位置",organization:"组织机构",event:"事件",equipment:"装备",weapon:"武器",animal:"动物",unknown:"未知",object:"物品",group:"群组",technology:"技术"},sideBar:{settings:{settings:"设置",healthCheck:"健康检查",showPropertyPanel:"显示属性面板",showSearchBar:"显示搜索栏",showNodeLabel:"显示节点标签",nodeDraggable:"节点可拖动",showEdgeLabel:"显示边标签",hideUnselectedEdges:"隐藏未选中的边",edgeEvents:"边事件",maxQueryDepth:"最大查询深度",maxNodes:"最大返回节点数",maxLayoutIterations:"最大布局迭代次数",resetToDefault:"重置为默认值",edgeSizeRange:"边粗细范围",depth:"深",max:"Max",degree:"邻边",apiKey:"API密钥",enterYourAPIkey:"输入您的API密钥",save:"保存",refreshLayout:"刷新布局"},zoomControl:{zoomIn:"放大",zoomOut:"缩小",resetZoom:"重置缩放",rotateCamera:"顺时针旋转图形",rotateCameraCounterClockwise:"逆时针旋转图形"},layoutsControl:{startAnimation:"继续布局动画",stopAnimation:"停止布局动画",layoutGraph:"图布局",layouts:{Circular:"环形",Circlepack:"圆形打包",Random:"随机",Noverlaps:"无重叠","Force Directed":"力导向","Force Atlas":"力地图"}},fullScreenControl:{fullScreen:"全屏",windowed:"窗口"},legendControl:{toggleLegend:"切换图例显示"}},statusIndicator:{connected:"已连接",disconnected:"未连接"},statusCard:{unavailable:"状态信息不可用",serverInfo:"服务器信息",workingDirectory:"工作目录",inputDirectory:"输入目录",maxParallelInsert:"并行处理文档",summarySettings:"摘要设置",llmConfig:"LLM配置",llmBinding:"LLM绑定",llmBindingHost:"LLM端点",llmModel:"LLM模型",embeddingConfig:"嵌入配置",embeddingBinding:"嵌入绑定",embeddingBindingHost:"嵌入端点",embeddingModel:"嵌入模型",storageConfig:"存储配置",kvStorage:"KV存储",docStatusStorage:"文档状态存储",graphStorage:"图存储",vectorStorage:"向量存储",workspace:"工作空间",maxGraphNodes:"最大图节点数",rerankerConfig:"重排序配置",rerankerBindingHost:"重排序端点",rerankerModel:"重排序模型",lockStatus:"锁状态",threshold:"阈值"},propertiesView:{editProperty:"编辑{{property}}",editPropertyDescription:"在下方文本区域编辑属性值。",errors:{duplicateName:"节点名称已存在",updateFailed:"更新节点失败",tryAgainLater:"请稍后重试"},success:{entityUpdated:"节点更新成功",relationUpdated:"关系更新成功"},node:{title:"节点",id:"ID",labels:"标签",degree:"度数",properties:"属性",relationships:"关系(子图内)",expandNode:"扩展节点",pruneNode:"修剪节点",deleteAllNodesError:"拒绝删除图中的所有节点",nodesRemoved:"已删除 {{count}} 个节点，包括孤立节点",noNewNodes:"没有发现可以扩展的节点",propertyNames:{description:"描述",entity_id:"名称",entity_type:"类型",source_id:"信源ID",Neighbour:"邻接",file_path:"信源",keywords:"Keys",weight:"权重"}},edge:{title:"关系",id:"ID",type:"类型",source:"源节点",target:"目标节点",properties:"属性"}},search:{placeholder:"搜索节点...",message:"还有 {count} 个"},graphLabels:{selectTooltip:"选择查询标签",noLabels:"未找到标签",label:"标签",placeholder:"搜索标签...",andOthers:"还有 {count} 个",refreshTooltip:"重载图形数据(添加文件后需重载)"},emptyGraph:"无数据(请重载图形数据)"},Pp={chatMessage:{copyTooltip:"复制到剪贴板",copyError:"复制文本到剪贴板失败"},retrieval:{startPrompt:"输入查询开始检索",clear:"清空",send:"发送",placeholder:"输入查询内容 (支持模式前缀: /<Query Mode>)",error:"错误：获取响应失败",queryModeError:"仅支持以下查询模式：{{modes}}",queryModePrefixInvalid:"无效的查询模式前缀。请使用：/<模式> [空格] 查询内容"},querySettings:{parametersTitle:"参数",parametersDescription:"配置查询参数",queryMode:"查询模式",queryModeTooltip:`选择检索策略：
+{{error}}`}}},Fp={dataIsTruncated:"图数据已截断至最大返回节点数",statusDialog:{title:"LightRAG 服务器设置",description:"查看当前系统状态和连接信息"},legend:"图例",nodeTypes:{person:"人物角色",category:"分类",geo:"地理名称",location:"位置",organization:"组织机构",event:"事件",equipment:"装备",weapon:"武器",animal:"动物",unknown:"未知",object:"物品",group:"群组",technology:"技术",product:"产品",other:"其他"},sideBar:{settings:{settings:"设置",healthCheck:"健康检查",showPropertyPanel:"显示属性面板",showSearchBar:"显示搜索栏",showNodeLabel:"显示节点标签",nodeDraggable:"节点可拖动",showEdgeLabel:"显示边标签",hideUnselectedEdges:"隐藏未选中的边",edgeEvents:"边事件",maxQueryDepth:"最大查询深度",maxNodes:"最大返回节点数",maxLayoutIterations:"最大布局迭代次数",resetToDefault:"重置为默认值",edgeSizeRange:"边粗细范围",depth:"深",max:"Max",degree:"邻边",apiKey:"API密钥",enterYourAPIkey:"输入您的API密钥",save:"保存",refreshLayout:"刷新布局"},zoomControl:{zoomIn:"放大",zoomOut:"缩小",resetZoom:"重置缩放",rotateCamera:"顺时针旋转图形",rotateCameraCounterClockwise:"逆时针旋转图形"},layoutsControl:{startAnimation:"继续布局动画",stopAnimation:"停止布局动画",layoutGraph:"图布局",layouts:{Circular:"环形",Circlepack:"圆形打包",Random:"随机",Noverlaps:"无重叠","Force Directed":"力导向","Force Atlas":"力地图"}},fullScreenControl:{fullScreen:"全屏",windowed:"窗口"},legendControl:{toggleLegend:"切换图例显示"}},statusIndicator:{connected:"已连接",disconnected:"未连接"},statusCard:{unavailable:"状态信息不可用",serverInfo:"服务器信息",workingDirectory:"工作目录",inputDirectory:"输入目录",maxParallelInsert:"并行处理文档",summarySettings:"摘要设置",llmConfig:"LLM配置",llmBinding:"LLM绑定",llmBindingHost:"LLM端点",llmModel:"LLM模型",embeddingConfig:"嵌入配置",embeddingBinding:"嵌入绑定",embeddingBindingHost:"嵌入端点",embeddingModel:"嵌入模型",storageConfig:"存储配置",kvStorage:"KV存储",docStatusStorage:"文档状态存储",graphStorage:"图存储",vectorStorage:"向量存储",workspace:"工作空间",maxGraphNodes:"最大图节点数",rerankerConfig:"重排序配置",rerankerBindingHost:"重排序端点",rerankerModel:"重排序模型",lockStatus:"锁状态",threshold:"阈值"},propertiesView:{editProperty:"编辑{{property}}",editPropertyDescription:"在下方文本区域编辑属性值。",errors:{duplicateName:"节点名称已存在",updateFailed:"更新节点失败",tryAgainLater:"请稍后重试"},success:{entityUpdated:"节点更新成功",relationUpdated:"关系更新成功"},node:{title:"节点",id:"ID",labels:"标签",degree:"度数",properties:"属性",relationships:"关系(子图内)",expandNode:"扩展节点",pruneNode:"修剪节点",deleteAllNodesError:"拒绝删除图中的所有节点",nodesRemoved:"已删除 {{count}} 个节点，包括孤立节点",noNewNodes:"没有发现可以扩展的节点",propertyNames:{description:"描述",entity_id:"名称",entity_type:"类型",source_id:"信源ID",Neighbour:"邻接",file_path:"信源",keywords:"Keys",weight:"权重"}},edge:{title:"关系",id:"ID",type:"类型",source:"源节点",target:"目标节点",properties:"属性"}},search:{placeholder:"搜索节点...",message:"还有 {count} 个"},graphLabels:{selectTooltip:"选择查询标签",noLabels:"未找到标签",label:"标签",placeholder:"搜索标签...",andOthers:"还有 {count} 个",refreshTooltip:"重载图形数据(添加文件后需重载)"},emptyGraph:"无数据(请重载图形数据)"},Pp={chatMessage:{copyTooltip:"复制到剪贴板",copyError:"复制文本到剪贴板失败"},retrieval:{startPrompt:"输入查询开始检索",clear:"清空",send:"发送",placeholder:"输入查询内容 (支持模式前缀: /<Query Mode>)",error:"错误：获取响应失败",queryModeError:"仅支持以下查询模式：{{modes}}",queryModePrefixInvalid:"无效的查询模式前缀。请使用：/<模式> [空格] 查询内容"},querySettings:{parametersTitle:"参数",parametersDescription:"配置查询参数",queryMode:"查询模式",queryModeTooltip:`选择检索策略：
 • Naive：基础搜索，无高级技术
 • Local：上下文相关信息检索
 • Global：利用全局知识库
@@ -91,7 +91,7 @@ For more information, see https://radix-ui.com/primitives/docs/components/alert-
 {{error}}`,scanFailed:`Échec de la numérisation des documents
 {{error}}`,scanProgressFailed:`Échec de l'obtention de la progression de la numérisation
 {{error}}`},fileNameLabel:"Nom du fichier",showButton:"Afficher",hideButton:"Masquer",showFileNameTooltip:"Afficher le nom du fichier",hideFileNameTooltip:"Masquer le nom du fichier"},pipelineStatus:{title:"État du Pipeline",busy:"Pipeline occupé",requestPending:"Requête en attente",jobName:"Nom du travail",startTime:"Heure de début",progress:"Progression",unit:"lot",latestMessage:"Dernier message",historyMessages:"Historique des messages",errors:{fetchFailed:`Échec de la récupération de l'état du pipeline
-{{error}}`}}},iy={dataIsTruncated:"Les données du graphe sont tronquées au nombre maximum de nœuds",statusDialog:{title:"Paramètres du Serveur LightRAG",description:"Afficher l'état actuel du système et les informations de connexion"},legend:"Légende",nodeTypes:{person:"Personne",category:"Catégorie",geo:"Géographique",location:"Emplacement",organization:"Organisation",event:"Événement",equipment:"Équipement",weapon:"Arme",animal:"Animal",unknown:"Inconnu",object:"Objet",group:"Groupe",technology:"Technologie"},sideBar:{settings:{settings:"Paramètres",healthCheck:"Vérification de l'état",showPropertyPanel:"Afficher le panneau des propriétés",showSearchBar:"Afficher la barre de recherche",showNodeLabel:"Afficher l'étiquette du nœud",nodeDraggable:"Nœud déplaçable",showEdgeLabel:"Afficher l'étiquette de l'arête",hideUnselectedEdges:"Masquer les arêtes non sélectionnées",edgeEvents:"Événements des arêtes",maxQueryDepth:"Profondeur maximale de la requête",maxNodes:"Nombre maximum de nœuds",maxLayoutIterations:"Itérations maximales de mise en page",resetToDefault:"Réinitialiser par défaut",edgeSizeRange:"Plage de taille des arêtes",depth:"D",max:"Max",degree:"Degré",apiKey:"Clé API",enterYourAPIkey:"Entrez votre clé API",save:"Sauvegarder",refreshLayout:"Actualiser la mise en page"},zoomControl:{zoomIn:"Zoom avant",zoomOut:"Zoom arrière",resetZoom:"Réinitialiser le zoom",rotateCamera:"Rotation horaire",rotateCameraCounterClockwise:"Rotation antihoraire"},layoutsControl:{startAnimation:"Démarrer l'animation de mise en page",stopAnimation:"Arrêter l'animation de mise en page",layoutGraph:"Mettre en page le graphe",layouts:{Circular:"Circulaire",Circlepack:"Paquet circulaire",Random:"Aléatoire",Noverlaps:"Sans chevauchement","Force Directed":"Dirigé par la force","Force Atlas":"Atlas de force"}},fullScreenControl:{fullScreen:"Plein écran",windowed:"Fenêtré"},legendControl:{toggleLegend:"Basculer la légende"}},statusIndicator:{connected:"Connecté",disconnected:"Déconnecté"},statusCard:{unavailable:"Informations sur l'état indisponibles",serverInfo:"Informations du serveur",workingDirectory:"Répertoire de travail",inputDirectory:"Répertoire d'entrée",maxParallelInsert:"Traitement simultané des documents",summarySettings:"Paramètres de résumé",llmConfig:"Configuration du modèle de langage",llmBinding:"Liaison du modèle de langage",llmBindingHost:"Point de terminaison LLM",llmModel:"Modèle de langage",embeddingConfig:"Configuration d'incorporation",embeddingBinding:"Liaison d'incorporation",embeddingBindingHost:"Point de terminaison d'incorporation",embeddingModel:"Modèle d'incorporation",storageConfig:"Configuration de stockage",kvStorage:"Stockage clé-valeur",docStatusStorage:"Stockage de l'état des documents",graphStorage:"Stockage du graphe",vectorStorage:"Stockage vectoriel",workspace:"Espace de travail",maxGraphNodes:"Nombre maximum de nœuds du graphe",rerankerConfig:"Configuration du reclassement",rerankerBindingHost:"Point de terminaison de reclassement",rerankerModel:"Modèle de reclassement",lockStatus:"État des verrous",threshold:"Seuil"},propertiesView:{editProperty:"Modifier {{property}}",editPropertyDescription:"Modifiez la valeur de la propriété dans la zone de texte ci-dessous.",errors:{duplicateName:"Le nom du nœud existe déjà",updateFailed:"Échec de la mise à jour du nœud",tryAgainLater:"Veuillez réessayer plus tard"},success:{entityUpdated:"Nœud mis à jour avec succès",relationUpdated:"Relation mise à jour avec succès"},node:{title:"Nœud",id:"ID",labels:"Étiquettes",degree:"Degré",properties:"Propriétés",relationships:"Relations(dans le sous-graphe)",expandNode:"Développer le nœud",pruneNode:"Élaguer le nœud",deleteAllNodesError:"Refus de supprimer tous les nœuds du graphe",nodesRemoved:"{{count}} nœuds supprimés, y compris les nœuds orphelins",noNewNodes:"Aucun nœud développable trouvé",propertyNames:{description:"Description",entity_id:"Nom",entity_type:"Type",source_id:"ID source",Neighbour:"Voisin",file_path:"Source",keywords:"Keys",weight:"Poids"}},edge:{title:"Relation",id:"ID",type:"Type",source:"Source",target:"Cible",properties:"Propriétés"}},search:{placeholder:"Rechercher des nœuds...",message:"Et {{count}} autres"},graphLabels:{selectTooltip:"Sélectionner l'étiquette de la requête",noLabels:"Aucune étiquette trouvée",label:"Étiquette",placeholder:"Rechercher des étiquettes...",andOthers:"Et {{count}} autres",refreshTooltip:"Recharger les données (Après l'ajout de fichier)"},emptyGraph:"Vide (Essayez de recharger)"},cy={chatMessage:{copyTooltip:"Copier dans le presse-papiers",copyError:"Échec de la copie du texte dans le presse-papiers"},retrieval:{startPrompt:"Démarrez une récupération en tapant votre requête ci-dessous",clear:"Effacer",send:"Envoyer",placeholder:"Tapez votre requête (Préfixe de requête : /<Query Mode>)",error:"Erreur : Échec de l'obtention de la réponse",queryModeError:"Seuls les modes de requête suivants sont pris en charge : {{modes}}",queryModePrefixInvalid:"Préfixe de mode de requête invalide. Utilisez : /<mode> [espace] votre requête"},querySettings:{parametersTitle:"Paramètres",parametersDescription:"Configurez vos paramètres de requête",queryMode:"Mode de requête",queryModeTooltip:`Sélectionnez la stratégie de récupération :
+{{error}}`}}},iy={dataIsTruncated:"Les données du graphe sont tronquées au nombre maximum de nœuds",statusDialog:{title:"Paramètres du Serveur LightRAG",description:"Afficher l'état actuel du système et les informations de connexion"},legend:"Légende",nodeTypes:{person:"Personne",category:"Catégorie",geo:"Géographique",location:"Emplacement",organization:"Organisation",event:"Événement",equipment:"Équipement",weapon:"Arme",animal:"Animal",unknown:"Inconnu",object:"Objet",group:"Groupe",technology:"Technologie",product:"Produit",other:"Autre"},sideBar:{settings:{settings:"Paramètres",healthCheck:"Vérification de l'état",showPropertyPanel:"Afficher le panneau des propriétés",showSearchBar:"Afficher la barre de recherche",showNodeLabel:"Afficher l'étiquette du nœud",nodeDraggable:"Nœud déplaçable",showEdgeLabel:"Afficher l'étiquette de l'arête",hideUnselectedEdges:"Masquer les arêtes non sélectionnées",edgeEvents:"Événements des arêtes",maxQueryDepth:"Profondeur maximale de la requête",maxNodes:"Nombre maximum de nœuds",maxLayoutIterations:"Itérations maximales de mise en page",resetToDefault:"Réinitialiser par défaut",edgeSizeRange:"Plage de taille des arêtes",depth:"D",max:"Max",degree:"Degré",apiKey:"Clé API",enterYourAPIkey:"Entrez votre clé API",save:"Sauvegarder",refreshLayout:"Actualiser la mise en page"},zoomControl:{zoomIn:"Zoom avant",zoomOut:"Zoom arrière",resetZoom:"Réinitialiser le zoom",rotateCamera:"Rotation horaire",rotateCameraCounterClockwise:"Rotation antihoraire"},layoutsControl:{startAnimation:"Démarrer l'animation de mise en page",stopAnimation:"Arrêter l'animation de mise en page",layoutGraph:"Mettre en page le graphe",layouts:{Circular:"Circulaire",Circlepack:"Paquet circulaire",Random:"Aléatoire",Noverlaps:"Sans chevauchement","Force Directed":"Dirigé par la force","Force Atlas":"Atlas de force"}},fullScreenControl:{fullScreen:"Plein écran",windowed:"Fenêtré"},legendControl:{toggleLegend:"Basculer la légende"}},statusIndicator:{connected:"Connecté",disconnected:"Déconnecté"},statusCard:{unavailable:"Informations sur l'état indisponibles",serverInfo:"Informations du serveur",workingDirectory:"Répertoire de travail",inputDirectory:"Répertoire d'entrée",maxParallelInsert:"Traitement simultané des documents",summarySettings:"Paramètres de résumé",llmConfig:"Configuration du modèle de langage",llmBinding:"Liaison du modèle de langage",llmBindingHost:"Point de terminaison LLM",llmModel:"Modèle de langage",embeddingConfig:"Configuration d'incorporation",embeddingBinding:"Liaison d'incorporation",embeddingBindingHost:"Point de terminaison d'incorporation",embeddingModel:"Modèle d'incorporation",storageConfig:"Configuration de stockage",kvStorage:"Stockage clé-valeur",docStatusStorage:"Stockage de l'état des documents",graphStorage:"Stockage du graphe",vectorStorage:"Stockage vectoriel",workspace:"Espace de travail",maxGraphNodes:"Nombre maximum de nœuds du graphe",rerankerConfig:"Configuration du reclassement",rerankerBindingHost:"Point de terminaison de reclassement",rerankerModel:"Modèle de reclassement",lockStatus:"État des verrous",threshold:"Seuil"},propertiesView:{editProperty:"Modifier {{property}}",editPropertyDescription:"Modifiez la valeur de la propriété dans la zone de texte ci-dessous.",errors:{duplicateName:"Le nom du nœud existe déjà",updateFailed:"Échec de la mise à jour du nœud",tryAgainLater:"Veuillez réessayer plus tard"},success:{entityUpdated:"Nœud mis à jour avec succès",relationUpdated:"Relation mise à jour avec succès"},node:{title:"Nœud",id:"ID",labels:"Étiquettes",degree:"Degré",properties:"Propriétés",relationships:"Relations(dans le sous-graphe)",expandNode:"Développer le nœud",pruneNode:"Élaguer le nœud",deleteAllNodesError:"Refus de supprimer tous les nœuds du graphe",nodesRemoved:"{{count}} nœuds supprimés, y compris les nœuds orphelins",noNewNodes:"Aucun nœud développable trouvé",propertyNames:{description:"Description",entity_id:"Nom",entity_type:"Type",source_id:"ID source",Neighbour:"Voisin",file_path:"Source",keywords:"Keys",weight:"Poids"}},edge:{title:"Relation",id:"ID",type:"Type",source:"Source",target:"Cible",properties:"Propriétés"}},search:{placeholder:"Rechercher des nœuds...",message:"Et {{count}} autres"},graphLabels:{selectTooltip:"Sélectionner l'étiquette de la requête",noLabels:"Aucune étiquette trouvée",label:"Étiquette",placeholder:"Rechercher des étiquettes...",andOthers:"Et {{count}} autres",refreshTooltip:"Recharger les données (Après l'ajout de fichier)"},emptyGraph:"Vide (Essayez de recharger)"},cy={chatMessage:{copyTooltip:"Copier dans le presse-papiers",copyError:"Échec de la copie du texte dans le presse-papiers"},retrieval:{startPrompt:"Démarrez une récupération en tapant votre requête ci-dessous",clear:"Effacer",send:"Envoyer",placeholder:"Tapez votre requête (Préfixe de requête : /<Query Mode>)",error:"Erreur : Échec de l'obtention de la réponse",queryModeError:"Seuls les modes de requête suivants sont pris en charge : {{modes}}",queryModePrefixInvalid:"Préfixe de mode de requête invalide. Utilisez : /<mode> [espace] votre requête"},querySettings:{parametersTitle:"Paramètres",parametersDescription:"Configurez vos paramètres de requête",queryMode:"Mode de requête",queryModeTooltip:`Sélectionnez la stratégie de récupération :
 • Naïf : Recherche de base sans techniques avancées
 • Local : Récupération d'informations dépendante du contexte
 • Global : Utilise une base de connaissances globale
@@ -115,7 +115,7 @@ For more information, see https://radix-ui.com/primitives/docs/components/alert-
 {{error}}`,scanFailed:`فشل مسح المستندات
 {{error}}`,scanProgressFailed:`فشل الحصول على تقدم المسح
 {{error}}`},fileNameLabel:"اسم الملف",showButton:"عرض",hideButton:"إخفاء",showFileNameTooltip:"عرض اسم الملف",hideFileNameTooltip:"إخفاء اسم الملف"},pipelineStatus:{title:"حالة خط المعالجة",busy:"خط المعالجة مشغول",requestPending:"الطلب معلق",jobName:"اسم المهمة",startTime:"وقت البدء",progress:"التقدم",unit:"دفعة",latestMessage:"آخر رسالة",historyMessages:"سجل الرسائل",errors:{fetchFailed:`فشل في جلب حالة خط المعالجة
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 • ساذج: بحث أساسي بدون تقنيات متقدمة
 • محلي: استرجاع معلومات يعتمد على السياق
 • عالمي: يستخدم قاعدة المعرفة العالمية
@@ -139,7 +139,7 @@ For more information, see https://radix-ui.com/primitives/docs/components/alert-
 {{error}}`,scanFailed:`掃描文件失敗
 {{error}}`,scanProgressFailed:`取得掃描進度失敗
 {{error}}`},fileNameLabel:"檔案名稱",showButton:"顯示",hideButton:"隱藏",showFileNameTooltip:"顯示檔案名稱",hideFileNameTooltip:"隱藏檔案名稱"},pipelineStatus:{title:"pipeline 狀態",busy:"pipeline 忙碌中",requestPending:"待處理請求",jobName:"工作名稱",startTime:"開始時間",progress:"進度",unit:"梯次",latestMessage:"最新訊息",historyMessages:"歷史訊息",errors:{fetchFailed:`取得pipeline 狀態失敗
-{{error}}`}}},zy={dataIsTruncated:"圖資料已截斷至最大回傳節點數",statusDialog:{title:"LightRAG 伺服器設定",description:"查看目前系統狀態和連線資訊"},legend:"圖例",nodeTypes:{person:"人物角色",category:"分類",geo:"地理名稱",location:"位置",organization:"組織機構",event:"事件",equipment:"設備",weapon:"武器",animal:"動物",unknown:"未知",object:"物品",group:"群組",technology:"技術"},sideBar:{settings:{settings:"設定",healthCheck:"健康檢查",showPropertyPanel:"顯示屬性面板",showSearchBar:"顯示搜尋列",showNodeLabel:"顯示節點標籤",nodeDraggable:"節點可拖曳",showEdgeLabel:"顯示 Edge 標籤",hideUnselectedEdges:"隱藏未選取的 Edge",edgeEvents:"Edge 事件",maxQueryDepth:"最大查詢深度",maxNodes:"最大回傳節點數",maxLayoutIterations:"最大版面配置迭代次數",resetToDefault:"重設為預設值",edgeSizeRange:"Edge 粗細範圍",depth:"深度",max:"最大值",degree:"鄰邊",apiKey:"API key",enterYourAPIkey:"輸入您的 API key",save:"儲存",refreshLayout:"重新整理版面配置"},zoomControl:{zoomIn:"放大",zoomOut:"縮小",resetZoom:"重設縮放",rotateCamera:"順時針旋轉圖形",rotateCameraCounterClockwise:"逆時針旋轉圖形"},layoutsControl:{startAnimation:"繼續版面配置動畫",stopAnimation:"停止版面配置動畫",layoutGraph:"圖形版面配置",layouts:{Circular:"環形",Circlepack:"圓形打包",Random:"隨機",Noverlaps:"無重疊","Force Directed":"力導向","Force Atlas":"力圖"}},fullScreenControl:{fullScreen:"全螢幕",windowed:"視窗"},legendControl:{toggleLegend:"切換圖例顯示"}},statusIndicator:{connected:"已連線",disconnected:"未連線"},statusCard:{unavailable:"狀態資訊不可用",serverInfo:"伺服器資訊",workingDirectory:"工作目錄",inputDirectory:"輸入目錄",maxParallelInsert:"並行處理文档",summarySettings:"摘要設定",llmConfig:"LLM 設定",llmBinding:"LLM 綁定",llmBindingHost:"LLM 端點",llmModel:"LLM 模型",embeddingConfig:"嵌入設定",embeddingBinding:"嵌入綁定",embeddingBindingHost:"嵌入端點",embeddingModel:"嵌入模型",storageConfig:"儲存設定",kvStorage:"KV 儲存",docStatusStorage:"文件狀態儲存",graphStorage:"圖形儲存",vectorStorage:"向量儲存",workspace:"工作空間",maxGraphNodes:"最大圖形節點數",rerankerConfig:"重排序設定",rerankerBindingHost:"重排序端點",rerankerModel:"重排序模型",lockStatus:"鎖定狀態",threshold:"閾值"},propertiesView:{editProperty:"編輯{{property}}",editPropertyDescription:"在下方文字區域編輯屬性值。",errors:{duplicateName:"節點名稱已存在",updateFailed:"更新節點失敗",tryAgainLater:"請稍後重試"},success:{entityUpdated:"節點更新成功",relationUpdated:"關係更新成功"},node:{title:"節點",id:"ID",labels:"標籤",degree:"度數",properties:"屬性",relationships:"關係(子圖內)",expandNode:"展開節點",pruneNode:"修剪節點",deleteAllNodesError:"拒絕刪除圖中的所有節點",nodesRemoved:"已刪除 {{count}} 個節點，包括孤立節點",noNewNodes:"沒有發現可以展開的節點",propertyNames:{description:"描述",entity_id:"名稱",entity_type:"類型",source_id:"來源ID",Neighbour:"鄰接",file_path:"來源",keywords:"Keys",weight:"權重"}},edge:{title:"關係",id:"ID",type:"類型",source:"來源節點",target:"目標節點",properties:"屬性"}},search:{placeholder:"搜尋節點...",message:"還有 {count} 個"},graphLabels:{selectTooltip:"選擇查詢標籤",noLabels:"未找到標籤",label:"標籤",placeholder:"搜尋標籤...",andOthers:"還有 {count} 個",refreshTooltip:"重載圖形數據(新增檔案後需重載)"},emptyGraph:"無數據(請重載圖形數據)"},Cy={chatMessage:{copyTooltip:"複製到剪貼簿",copyError:"複製文字到剪貼簿失敗"},retrieval:{startPrompt:"輸入查詢開始檢索",clear:"清空",send:"送出",placeholder:"輸入查詢內容 (支援模式前綴：/<Query Mode>)",error:"錯誤：取得回應失敗",queryModeError:"僅支援以下查詢模式：{{modes}}",queryModePrefixInvalid:"無效的查詢模式前綴。請使用：/<模式> [空格] 查詢內容"},querySettings:{parametersTitle:"參數",parametersDescription:"設定查詢參數",queryMode:"查詢模式",queryModeTooltip:`選擇檢索策略：
+{{error}}`}}},zy={dataIsTruncated:"圖資料已截斷至最大回傳節點數",statusDialog:{title:"LightRAG 伺服器設定",description:"查看目前系統狀態和連線資訊"},legend:"圖例",nodeTypes:{person:"人物角色",category:"分類",geo:"地理名稱",location:"位置",organization:"組織機構",event:"事件",equipment:"設備",weapon:"武器",animal:"動物",unknown:"未知",object:"物品",group:"群組",technology:"技術",product:"產品",other:"其他"},sideBar:{settings:{settings:"設定",healthCheck:"健康檢查",showPropertyPanel:"顯示屬性面板",showSearchBar:"顯示搜尋列",showNodeLabel:"顯示節點標籤",nodeDraggable:"節點可拖曳",showEdgeLabel:"顯示 Edge 標籤",hideUnselectedEdges:"隱藏未選取的 Edge",edgeEvents:"Edge 事件",maxQueryDepth:"最大查詢深度",maxNodes:"最大回傳節點數",maxLayoutIterations:"最大版面配置迭代次數",resetToDefault:"重設為預設值",edgeSizeRange:"Edge 粗細範圍",depth:"深度",max:"最大值",degree:"鄰邊",apiKey:"API key",enterYourAPIkey:"輸入您的 API key",save:"儲存",refreshLayout:"重新整理版面配置"},zoomControl:{zoomIn:"放大",zoomOut:"縮小",resetZoom:"重設縮放",rotateCamera:"順時針旋轉圖形",rotateCameraCounterClockwise:"逆時針旋轉圖形"},layoutsControl:{startAnimation:"繼續版面配置動畫",stopAnimation:"停止版面配置動畫",layoutGraph:"圖形版面配置",layouts:{Circular:"環形",Circlepack:"圓形打包",Random:"隨機",Noverlaps:"無重疊","Force Directed":"力導向","Force Atlas":"力圖"}},fullScreenControl:{fullScreen:"全螢幕",windowed:"視窗"},legendControl:{toggleLegend:"切換圖例顯示"}},statusIndicator:{connected:"已連線",disconnected:"未連線"},statusCard:{unavailable:"狀態資訊不可用",serverInfo:"伺服器資訊",workingDirectory:"工作目錄",inputDirectory:"輸入目錄",maxParallelInsert:"並行處理文档",summarySettings:"摘要設定",llmConfig:"LLM 設定",llmBinding:"LLM 綁定",llmBindingHost:"LLM 端點",llmModel:"LLM 模型",embeddingConfig:"嵌入設定",embeddingBinding:"嵌入綁定",embeddingBindingHost:"嵌入端點",embeddingModel:"嵌入模型",storageConfig:"儲存設定",kvStorage:"KV 儲存",docStatusStorage:"文件狀態儲存",graphStorage:"圖形儲存",vectorStorage:"向量儲存",workspace:"工作空間",maxGraphNodes:"最大圖形節點數",rerankerConfig:"重排序設定",rerankerBindingHost:"重排序端點",rerankerModel:"重排序模型",lockStatus:"鎖定狀態",threshold:"閾值"},propertiesView:{editProperty:"編輯{{property}}",editPropertyDescription:"在下方文字區域編輯屬性值。",errors:{duplicateName:"節點名稱已存在",updateFailed:"更新節點失敗",tryAgainLater:"請稍後重試"},success:{entityUpdated:"節點更新成功",relationUpdated:"關係更新成功"},node:{title:"節點",id:"ID",labels:"標籤",degree:"度數",properties:"屬性",relationships:"關係(子圖內)",expandNode:"展開節點",pruneNode:"修剪節點",deleteAllNodesError:"拒絕刪除圖中的所有節點",nodesRemoved:"已刪除 {{count}} 個節點，包括孤立節點",noNewNodes:"沒有發現可以展開的節點",propertyNames:{description:"描述",entity_id:"名稱",entity_type:"類型",source_id:"來源ID",Neighbour:"鄰接",file_path:"來源",keywords:"Keys",weight:"權重"}},edge:{title:"關係",id:"ID",type:"類型",source:"來源節點",target:"目標節點",properties:"屬性"}},search:{placeholder:"搜尋節點...",message:"還有 {count} 個"},graphLabels:{selectTooltip:"選擇查詢標籤",noLabels:"未找到標籤",label:"標籤",placeholder:"搜尋標籤...",andOthers:"還有 {count} 個",refreshTooltip:"重載圖形數據(新增檔案後需重載)"},emptyGraph:"無數據(請重載圖形數據)"},Cy={chatMessage:{copyTooltip:"複製到剪貼簿",copyError:"複製文字到剪貼簿失敗"},retrieval:{startPrompt:"輸入查詢開始檢索",clear:"清空",send:"送出",placeholder:"輸入查詢內容 (支援模式前綴：/<Query Mode>)",error:"錯誤：取得回應失敗",queryModeError:"僅支援以下查詢模式：{{modes}}",queryModePrefixInvalid:"無效的查詢模式前綴。請使用：/<模式> [空格] 查詢內容"},querySettings:{parametersTitle:"參數",parametersDescription:"設定查詢參數",queryMode:"查詢模式",queryModeTooltip:`選擇檢索策略：
 • Naive：基礎搜尋，無進階技術
 • Local：上下文相關資訊檢索
 • Global：利用全域知識庫
diff --git a/lightrag/api/webui/index.html b/lightrag/api/webui/index.html
index 2d6aa50d..60827e10 100644
--- a/lightrag/api/webui/index.html
+++ b/lightrag/api/webui/index.html
@@ -8,7 +8,7 @@
     <link rel="icon" type="image/png" href="favicon.png" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>Lightrag</title>
-    <script type="module" crossorigin src="/webui/assets/index-CIdJpUuC.js"></script>
+    <script type="module" crossorigin src="/webui/assets/index-CjbmYv_Z.js"></script>
     <link rel="modulepreload" crossorigin href="/webui/assets/react-vendor-DEwriMA6.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/ui-vendor-CeCm8EER.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/graph-vendor-B-X5JegA.js">

From 9d81cd724abd974cd7e18fa9a50e985be05a01b6 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Tue, 2 Sep 2025 03:19:31 +0800
Subject: [PATCH 110/141] Fix typo: change "Equiment" to "Equipment" in entity
 types

---
 env.example           | 2 +-
 lightrag/constants.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/env.example b/env.example
index 4ab64aba..5d24c118 100644
--- a/env.example
+++ b/env.example
@@ -125,7 +125,7 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true
 SUMMARY_LANGUAGE=English
 
 ### Entity types that the LLM will attempt to recognize
-# ENTITY_TYPES='["Organization", "Person", "Equiment", "Product", "Technology", "Location", "Event", "Category"]'
+# ENTITY_TYPES='["Organization", "Person", "Equipment", "Product", "Technology", "Location", "Event", "Category"]'
 
 ### Chunk size for document splitting, 500~1500 is recommended
 # CHUNK_SIZE=1200
diff --git a/lightrag/constants.py b/lightrag/constants.py
index 9accdc52..5cdba052 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -26,7 +26,7 @@ DEFAULT_SUMMARY_CONTEXT_SIZE = 12000
 DEFAULT_ENTITY_TYPES = [
     "Organization",
     "Person",
-    "Equiment",
+    "Equipment",
     "Product",
     "Technology",
     "Location",

From c86f863fa445aedf9ab7216dddca5bf95517d4b7 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 3 Sep 2025 10:33:01 +0800
Subject: [PATCH 111/141] feat: optimize entity extraction for smaller LLMs

Simplify entity relationship extraction process to improve compatibility
and performance with smaller, less capable language models.

Changes:
- Remove iterative gleaning loop with LLM-based continuation decisions
- Simplify to single gleaning pass when entity_extract_max_gleaning > 0
- Streamline entity extraction prompts with clearer instructions
- Add explicit completion delimiter signals in all examples
---
 env.example         |  10 ++--
 lightrag/operate.py |  18 +------
 lightrag/prompt.py  | 116 +++++++++++++++++---------------------------
 3 files changed, 50 insertions(+), 94 deletions(-)

diff --git a/env.example b/env.example
index 5d24c118..ce875d3b 100644
--- a/env.example
+++ b/env.example
@@ -175,11 +175,9 @@ LLM_BINDING_API_KEY=your_api_key
 # LLM_BINDING=openai
 
 ### OpenAI Specific Parameters
-### To mitigate endless output loops and prevent greedy decoding for Qwen3, set the temperature parameter to a value between 0.8 and 1.0
-# OPENAI_LLM_TEMPERATURE=1.0
-# OPENAI_LLM_REASONING_EFFORT=low
-### If the presence penalty still can not stop the model from generates repetitive or unconstrained output
-# OPENAI_LLM_MAX_COMPLETION_TOKENS=16384
+### To mitigate endless output loops and prevent greedy decoding for Qwen3, set the temperature and frequency penalty parameter to a highter value
+# OPENAI_LLM_TEMPERATURE=1.2
+# OPENAI_FREQUENCY_PENALTY=1.5
 
 ### OpenRouter Specific Parameters
 # OPENAI_LLM_EXTRA_BODY='{"reasoning": {"enabled": false}}'
@@ -194,7 +192,7 @@ LLM_BINDING_API_KEY=your_api_key
 OLLAMA_LLM_NUM_CTX=32768
 # OLLAMA_LLM_TEMPERATURE=1.0
 ### Stop sequences for Ollama LLM
-# OLLAMA_LLM_STOP='["</s>", "Assistant:", "\n\n"]'
+# OLLAMA_LLM_STOP='["</s>", "<|EOT|>"]'
 ### use the following command to see all support options for Ollama LLM
 ### lightrag-server --llm-binding ollama --help
 
diff --git a/lightrag/operate.py b/lightrag/operate.py
index 6c9a5538..cbfbb858 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -1764,7 +1764,6 @@ async def extract_entities(
     )
 
     continue_prompt = PROMPTS["entity_continue_extraction"].format(**context_base)
-    if_loop_prompt = PROMPTS["entity_if_loop_extraction"]
 
     processed_chunks = 0
     total_chunks = len(ordered_chunks)
@@ -1815,7 +1814,7 @@ async def extract_entities(
         )
 
         # Process additional gleaning results
-        for now_glean_index in range(entity_extract_max_gleaning):
+        if entity_extract_max_gleaning > 0:
             glean_result = await use_llm_func_with_cache(
                 continue_prompt,
                 use_llm_func,
@@ -1852,21 +1851,6 @@ async def extract_entities(
                     maybe_edges[edge_key] = []  # Explicitly create the list
                     maybe_edges[edge_key].extend(edges)
 
-            if now_glean_index == entity_extract_max_gleaning - 1:
-                break
-
-            if_loop_result: str = await use_llm_func_with_cache(
-                if_loop_prompt,
-                use_llm_func,
-                llm_response_cache=llm_response_cache,
-                history_messages=history,
-                cache_type="extract",
-                cache_keys_collector=cache_keys_collector,
-            )
-            if_loop_result = if_loop_result.strip().strip('"').strip("'").lower()
-            if if_loop_result != "yes":
-                break
-
         # Batch update chunk's llm_cache_list with all collected cache keys
         if cache_keys_collector and text_chunks_storage:
             await update_chunk_cache_list(
diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index c71debe8..0ee5ec20 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -6,37 +6,29 @@ PROMPTS: dict[str, Any] = {}
 
 PROMPTS["DEFAULT_TUPLE_DELIMITER"] = "<|>"
 PROMPTS["DEFAULT_RECORD_DELIMITER"] = "##"
-
-# TODO: Deprecated, reserved for compatible with legacy LLM cache
 PROMPTS["DEFAULT_COMPLETION_DELIMITER"] = "<|COMPLETE|>"
 
 PROMPTS["DEFAULT_USER_PROMPT"] = "n/a"
 
 PROMPTS["entity_extraction"] = """---Task---
-Given a text document that is potentially relevant to this activity and a list of entity types, identify all entities of those types from the text and all relationships among the identified entities.
+Given a text document and a list of entity types, identify all entities of those types and all relationships among the identified entities.
 
 ---Instructions---
 1. Recognizing definitively conceptualized entities in text. For each identified entity, extract the following information:
-- entity_name: Name of the entity, use same language as input text. If English, capitalized the name
-- entity_type: One of the following types: [{entity_types}]. If the entity doesn't clearly fit any category, classify it as "Other".
-- entity_description: Provide a comprehensive description of the entity's attributes and activities based on the information present in the input text. Do not add external knowledge.
-
-2. Format each entity as:
-("entity"{tuple_delimiter}<entity_name>{tuple_delimiter}<entity_type>{tuple_delimiter}<entity_description>)
-
+  - entity_name: Name of the entity, use same language as input text. If English, capitalized the name
+  - entity_type: Categorize the entity using the provided `Entity_types` list. If a suitable category cannot be determined, classify it as "Other".
+  - entity_description: Provide a comprehensive description of the entity's attributes and activities based on the information present in the input text. Do not add external knowledge.
+2. Format each entity as: ("entity"{tuple_delimiter}<entity_name>{tuple_delimiter}<entity_type>{tuple_delimiter}<entity_description>)
 3. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are directly and clearly related based on the text. Unsubstantiated relationships must be excluded from the output.
 For each pair of related entities, extract the following information:
-- source_entity: name of the source entity, as identified in step 1
-- target_entity: name of the target entity, as identified in step 1
-- relationship_keywords: one or more high-level key words that summarize the overarching nature of the relationship, focusing on concepts or themes rather than specific details
-- relationship_description: Explain the nature of the relationship between the source and target entities, providing a clear rationale for their connection
-
-4. Format each relationship as:
-("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
-
+  - source_entity: name of the source entity, as identified in step 1
+  - target_entity: name of the target entity, as identified in step 1
+  - relationship_keywords: one or more high-level key words that summarize the overarching nature of the relationship, focusing on concepts or themes rather than specific details
+  - relationship_description: Explain the nature of the relationship between the source and target entities, providing a clear rationale for their connection
+4. Format each relationship as: ("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
 5. Use `{tuple_delimiter}` as field delimiter. Use `{record_delimiter}` as the entity or relation list delimiter.
-
 6. Return identified entities and relationships in {language}.
+7. Output `{completion_delimiter}` when all the entities and relationships are extracted.
 
 ---Quality Guidelines---
 - Only extract entities that are clearly defined and meaningful in the context
@@ -47,7 +39,7 @@ For each pair of related entities, extract the following information:
 ---Examples---
 {examples}
 
----Real Data---
+---Input---
 Entity_types: [{entity_types}]
 Text:
 ```
@@ -55,12 +47,12 @@ Text:
 ```
 
 ---Output---
-Output:
 """
 
 PROMPTS["entity_extraction_examples"] = [
-    """------Example 1------
+    """[Example 1]
 
+---Input---
 Entity_types: [organization,person,equiment,product,technology,location,event,category]
 Text:
 ```
@@ -73,7 +65,7 @@ The underlying dismissal earlier seemed to falter, replaced by a glimpse of relu
 It was a small transformation, barely perceptible, but one that Alex noted with an inward nod. They had all been brought here by different paths
 ```
 
-Output:
+---Output---
 (entity{tuple_delimiter}Alex{tuple_delimiter}person{tuple_delimiter}Alex is a character who experiences frustration and is observant of the dynamics among other characters.){record_delimiter}
 (entity{tuple_delimiter}Taylor{tuple_delimiter}person{tuple_delimiter}Taylor is portrayed with authoritarian certainty and shows a moment of reverence towards a device, indicating a change in perspective.){record_delimiter}
 (entity{tuple_delimiter}Jordan{tuple_delimiter}person{tuple_delimiter}Jordan shares a commitment to discovery and has a significant interaction with Taylor regarding a device.){record_delimiter}
@@ -84,10 +76,12 @@ Output:
 (relationship{tuple_delimiter}Taylor{tuple_delimiter}Jordan{tuple_delimiter}conflict resolution, mutual respect{tuple_delimiter}Taylor and Jordan interact directly regarding the device, leading to a moment of mutual respect and an uneasy truce.){record_delimiter}
 (relationship{tuple_delimiter}Jordan{tuple_delimiter}Cruz{tuple_delimiter}ideological conflict, rebellion{tuple_delimiter}Jordan's commitment to discovery is in rebellion against Cruz's vision of control and order.){record_delimiter}
 (relationship{tuple_delimiter}Taylor{tuple_delimiter}The Device{tuple_delimiter}reverence, technological significance{tuple_delimiter}Taylor shows reverence towards the device, indicating its importance and potential impact.){record_delimiter}
+{completion_delimiter}
 
 """,
-    """------Example 2------
+    """[Example 2]
 
+---Input---
 Entity_types: [organization,person,equiment,product,technology,location,event,category]
 Text:
 ```
@@ -100,7 +94,7 @@ Meanwhile, commodity markets reflected a mixed sentiment. Gold futures rose by 1
 Financial experts are closely watching the Federal Reserve's next move, as speculation grows over potential rate hikes. The upcoming policy announcement is expected to influence investor confidence and overall market stability.
 ```
 
-Output:
+---Output---
 (entity{tuple_delimiter}Global Tech Index{tuple_delimiter}category{tuple_delimiter}The Global Tech Index tracks the performance of major technology stocks and experienced a 3.4% decline today.){record_delimiter}
 (entity{tuple_delimiter}Nexon Technologies{tuple_delimiter}organization{tuple_delimiter}Nexon Technologies is a tech company that saw its stock decline by 7.8% after disappointing earnings.){record_delimiter}
 (entity{tuple_delimiter}Omega Energy{tuple_delimiter}organization{tuple_delimiter}Omega Energy is an energy company that gained 2.1% in stock value due to rising oil prices.){record_delimiter}
@@ -113,17 +107,19 @@ Output:
 (relationship{tuple_delimiter}Nexon Technologies{tuple_delimiter}Global Tech Index{tuple_delimiter}company impact, index movement{tuple_delimiter}Nexon Technologies' stock decline contributed to the overall drop in the Global Tech Index.){record_delimiter}
 (relationship{tuple_delimiter}Gold Futures{tuple_delimiter}Market Selloff{tuple_delimiter}market reaction, safe-haven investment{tuple_delimiter}Gold prices rose as investors sought safe-haven assets during the market selloff.){record_delimiter}
 (relationship{tuple_delimiter}Federal Reserve Policy Announcement{tuple_delimiter}Market Selloff{tuple_delimiter}interest rate impact, financial regulation{tuple_delimiter}Speculation over Federal Reserve policy changes contributed to market volatility and investor selloff.){record_delimiter}
+{completion_delimiter}
 
 """,
-    """------Example 3------
+    """[Example 3]
 
+---Input---
 Entity_types: [organization,person,equiment,product,technology,location,event,category]
 Text:
 ```
 At the World Athletics Championship in Tokyo, Noah Carter broke the 100m sprint record using cutting-edge carbon-fiber spikes.
 ```
 
-Output:
+---Output---
 (entity{tuple_delimiter}World Athletics Championship{tuple_delimiter}event{tuple_delimiter}The World Athletics Championship is a global sports competition featuring top athletes in track and field.){record_delimiter}
 (entity{tuple_delimiter}Tokyo{tuple_delimiter}location{tuple_delimiter}Tokyo is the host city of the World Athletics Championship.){record_delimiter}
 (entity{tuple_delimiter}Noah Carter{tuple_delimiter}person{tuple_delimiter}Noah Carter is a sprinter who set a new record in the 100m sprint at the World Athletics Championship.){record_delimiter}
@@ -134,17 +130,19 @@ Output:
 (relationship{tuple_delimiter}Noah Carter{tuple_delimiter}100m Sprint Record{tuple_delimiter}athlete achievement, record-breaking{tuple_delimiter}Noah Carter set a new 100m sprint record at the championship.){record_delimiter}
 (relationship{tuple_delimiter}Noah Carter{tuple_delimiter}Carbon-Fiber Spikes{tuple_delimiter}athletic equipment, performance boost{tuple_delimiter}Noah Carter used carbon-fiber spikes to enhance performance during the race.){record_delimiter}
 (relationship{tuple_delimiter}Noah Carter{tuple_delimiter}World Athletics Championship{tuple_delimiter}athlete participation, competition{tuple_delimiter}Noah Carter is competing at the World Athletics Championship.){record_delimiter}
+{completion_delimiter}
 
 """,
-    """------Example 4------
+    """[Example 4]
 
+---Input---
 Entity_types: [organization,person,equiment,product,technology,location,event,category]
 Text:
 ```
 在北京举行的人工智能大会上，腾讯公司的首席技术官张伟发布了最新的大语言模型"腾讯智言"，该模型在自然语言处理方面取得了重大突破。
 ```
 
-Output:
+---Output---
 (entity{tuple_delimiter}人工智能大会{tuple_delimiter}event{tuple_delimiter}人工智能大会是在北京举行的技术会议，专注于人工智能领域的最新发展。){record_delimiter}
 (entity{tuple_delimiter}北京{tuple_delimiter}location{tuple_delimiter}北京是人工智能大会的举办城市。){record_delimiter}
 (entity{tuple_delimiter}腾讯公司{tuple_delimiter}organization{tuple_delimiter}腾讯公司是参与人工智能大会的科技企业，发布了新的语言模型产品。){record_delimiter}
@@ -155,6 +153,7 @@ Output:
 (relationship{tuple_delimiter}张伟{tuple_delimiter}腾讯公司{tuple_delimiter}雇佣关系, 高管职位{tuple_delimiter}张伟担任腾讯公司的首席技术官。){record_delimiter}
 (relationship{tuple_delimiter}张伟{tuple_delimiter}腾讯智言{tuple_delimiter}产品发布, 技术展示{tuple_delimiter}张伟在大会上发布了腾讯智言大语言模型。){record_delimiter}
 (relationship{tuple_delimiter}腾讯智言{tuple_delimiter}自然语言处理技术{tuple_delimiter}技术应用, 突破创新{tuple_delimiter}腾讯智言在自然语言处理技术方面取得了重大突破。){record_delimiter}
+{completion_delimiter}
 
 """,
 ]
@@ -179,54 +178,29 @@ Description List:
 {description_list}
 
 ---Output---
-Output:"""
-
-PROMPTS["entity_continue_extraction"] = """
----Task---
-MANY entities and relationships were missed in the last extraction. Please find only the missing entities and relationships from previous text.
-
----Instructions---
-1. Recognizing definitively conceptualized entities in text. For each identified entity, extract the following information:
-- entity_name: Name of the entity, use same language as input text. If English, capitalized the name
-- entity_type: One of the following types: [{entity_types}]. If the entity doesn't clearly fit any category, classify it as "Other".
-- entity_description: Provide a comprehensive description of the entity's attributes and activities based on the information present in the input text. Do not add external knowledge.
-
-2. Format each entity as:
-("entity"{tuple_delimiter}<entity_name>{tuple_delimiter}<entity_type>{tuple_delimiter}<entity_description>)
-
-3. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are directly and clearly related based on the text. Unsubstantiated relationships must be excluded from the output.
-For each pair of related entities, extract the following information:
-- source_entity: name of the source entity, as identified in step 1
-- target_entity: name of the target entity, as identified in step 1
-- relationship_keywords: one or more high-level key words that summarize the overarching nature of the relationship, focusing on concepts or themes rather than specific details
-- relationship_description: Explain the nature of the relationship between the source and target entities, providing a clear rationale for their connection
-
-4. Format each relationship as:
-("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
-
-5. Use `{tuple_delimiter}` as field delimiter. Use `{record_delimiter}` as the entity or relation list delimiter.
-
-6. Return identified entities and relationships in {language}.
-
----Quality Guidelines---
-- Only extract entities that are clearly defined and meaningful in the context
-- Do not include entities and relations that have been previously extracted
-- Avoid over-interpretation; stick to what is explicitly stated in the text
-- Include specific numerical data in entity name when relevant
-- Ensure entity names are consistent throughout the extraction
-
----Output---
-Output:
 """
 
+PROMPTS["entity_continue_extraction"] = """---Task---
+Identify any missed entities or relationships in the last extraction task.
+
+---Instructions---
+1. Output the entities and realtionships in the same format as previous extraction task.
+2. Do not include entities and relations that have been previously extracted.
+3. If the entity doesn't clearly fit in any of`Entity_types` provided, classify it as "Other".
+4. Return identified entities and relationships in {language}.
+5. Output `{completion_delimiter}` when all the entities and relationships are extracted.
+
+---Output---
+"""
+
+# TODO: Deprecated
 PROMPTS["entity_if_loop_extraction"] = """
 ---Goal---'
 
-It appears some entities may have still been missed.
+Check if it appears some entities may have still been missed. Output "Yes" if so, otherwise "No".
 
 ---Output---
-Output:
-""".strip()
+Output:"""
 
 PROMPTS["fail_response"] = (
     "Sorry, I'm not able to provide an answer to that question.[no-context]"
@@ -270,7 +244,7 @@ Generate a concise response based on Knowledge Base and follow Response Rules, c
 - Additional user prompt: {user_prompt}
 
 ---Response---
-Output:"""
+"""
 
 PROMPTS["keywords_extraction"] = """---Role---
 You are an expert keyword extractor, specializing in analyzing user queries for a Retrieval-Augmented Generation (RAG) system. Your purpose is to identify both high-level and low-level keywords in the user's query that will be used for effective document retrieval.

From 95c08cc7dcf1ce589c1c8f1b229fc335b6f97662 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 3 Sep 2025 12:35:52 +0800
Subject: [PATCH 112/141] Improve entity extraction prompt clarity by replacing
 pronouns with specific nouns

---
 lightrag/prompt.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index 0ee5ec20..76077af0 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -17,7 +17,7 @@ Given a text document and a list of entity types, identify all entities of those
 1. Recognizing definitively conceptualized entities in text. For each identified entity, extract the following information:
   - entity_name: Name of the entity, use same language as input text. If English, capitalized the name
   - entity_type: Categorize the entity using the provided `Entity_types` list. If a suitable category cannot be determined, classify it as "Other".
-  - entity_description: Provide a comprehensive description of the entity's attributes and activities based on the information present in the input text. Do not add external knowledge.
+  - entity_description: Provide a comprehensive description of the entity's attributes and activities based on the information present in the input text. To ensure clarity and precision, all descriptions must replace pronouns and referential terms (e.g., "this document," "our company," "I," "you," "he/she") with the specific nouns they represent.
 2. Format each entity as: ("entity"{tuple_delimiter}<entity_name>{tuple_delimiter}<entity_type>{tuple_delimiter}<entity_description>)
 3. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are directly and clearly related based on the text. Unsubstantiated relationships must be excluded from the output.
 For each pair of related entities, extract the following information:
@@ -33,6 +33,7 @@ For each pair of related entities, extract the following information:
 ---Quality Guidelines---
 - Only extract entities that are clearly defined and meaningful in the context
 - Avoid over-interpretation; stick to what is explicitly stated in the text
+- For all output content, explicitly name the subject or object rather than using pronouns
 - Include specific numerical data in entity name when relevant
 - Ensure entity names are consistent throughout the extraction
 

From 78abb397bfc67aaf208de7d76b2eaf41e639ba4f Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 3 Sep 2025 12:44:40 +0800
Subject: [PATCH 113/141] Reorder entity types and add Document type to
 extraction

---
 env.example           | 2 +-
 lightrag/constants.py | 7 ++++---
 lightrag/prompt.py    | 8 ++++----
 3 files changed, 9 insertions(+), 8 deletions(-)

diff --git a/env.example b/env.example
index ce875d3b..749ddc3d 100644
--- a/env.example
+++ b/env.example
@@ -125,7 +125,7 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true
 SUMMARY_LANGUAGE=English
 
 ### Entity types that the LLM will attempt to recognize
-# ENTITY_TYPES='["Organization", "Person", "Equipment", "Product", "Technology", "Location", "Event", "Category"]'
+# ENTITY_TYPES='["Organization", "Person", "Location", "Event", "Technology", "Equipment", "Product", "Document", "Category"]'
 
 ### Chunk size for document splitting, 500~1500 is recommended
 # CHUNK_SIZE=1200
diff --git a/lightrag/constants.py b/lightrag/constants.py
index 5cdba052..0b3962d0 100644
--- a/lightrag/constants.py
+++ b/lightrag/constants.py
@@ -26,11 +26,12 @@ DEFAULT_SUMMARY_CONTEXT_SIZE = 12000
 DEFAULT_ENTITY_TYPES = [
     "Organization",
     "Person",
-    "Equipment",
-    "Product",
-    "Technology",
     "Location",
     "Event",
+    "Technology",
+    "Equipment",
+    "Product",
+    "Document",
     "Category",
 ]
 
diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index 76077af0..0d21375a 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -54,7 +54,7 @@ PROMPTS["entity_extraction_examples"] = [
     """[Example 1]
 
 ---Input---
-Entity_types: [organization,person,equiment,product,technology,location,event,category]
+Entity_types: [organization,person,location,event,technology,equiment,product,Document,category]
 Text:
 ```
 while Alex clenched his jaw, the buzz of frustration dull against the backdrop of Taylor's authoritarian certainty. It was this competitive undercurrent that kept him alert, the sense that his and Jordan's shared commitment to discovery was an unspoken rebellion against Cruz's narrowing vision of control and order.
@@ -83,7 +83,7 @@ It was a small transformation, barely perceptible, but one that Alex noted with
     """[Example 2]
 
 ---Input---
-Entity_types: [organization,person,equiment,product,technology,location,event,category]
+Entity_types: [organization,person,location,event,technology,equiment,product,Document,category]
 Text:
 ```
 Stock markets faced a sharp downturn today as tech giants saw significant declines, with the Global Tech Index dropping by 3.4% in midday trading. Analysts attribute the selloff to investor concerns over rising interest rates and regulatory uncertainty.
@@ -114,7 +114,7 @@ Financial experts are closely watching the Federal Reserve's next move, as specu
     """[Example 3]
 
 ---Input---
-Entity_types: [organization,person,equiment,product,technology,location,event,category]
+Entity_types: [organization,person,location,event,technology,equiment,product,Document,category]
 Text:
 ```
 At the World Athletics Championship in Tokyo, Noah Carter broke the 100m sprint record using cutting-edge carbon-fiber spikes.
@@ -137,7 +137,7 @@ At the World Athletics Championship in Tokyo, Noah Carter broke the 100m sprint
     """[Example 4]
 
 ---Input---
-Entity_types: [organization,person,equiment,product,technology,location,event,category]
+Entity_types: [organization,person,location,event,technology,equiment,product,Document,category]
 Text:
 ```
 在北京举行的人工智能大会上，腾讯公司的首席技术官张伟发布了最新的大语言模型"腾讯智言"，该模型在自然语言处理方面取得了重大突破。

From 5a5d5e4a346a854b0f1f6685d3713d9df91269a7 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 3 Sep 2025 12:50:27 +0800
Subject: [PATCH 114/141] Add document translation key to all locale files

---
 lightrag_webui/src/locales/ar.json    | 1 +
 lightrag_webui/src/locales/en.json    | 1 +
 lightrag_webui/src/locales/fr.json    | 1 +
 lightrag_webui/src/locales/zh.json    | 1 +
 lightrag_webui/src/locales/zh_TW.json | 1 +
 5 files changed, 5 insertions(+)

diff --git a/lightrag_webui/src/locales/ar.json b/lightrag_webui/src/locales/ar.json
index db50ab37..240ea053 100644
--- a/lightrag_webui/src/locales/ar.json
+++ b/lightrag_webui/src/locales/ar.json
@@ -189,6 +189,7 @@
       "group": "مجموعة",
       "technology": "العلوم",
       "product": "منتج",
+      "document": "وثيقة",
       "other": "أخرى"
     },
     "sideBar": {
diff --git a/lightrag_webui/src/locales/en.json b/lightrag_webui/src/locales/en.json
index 19006705..1c5cf6e9 100644
--- a/lightrag_webui/src/locales/en.json
+++ b/lightrag_webui/src/locales/en.json
@@ -189,6 +189,7 @@
       "group": "Group",
       "technology": "Technology",
       "product": "Product",
+      "document": "Document",
       "other": "Other"
     },
     "sideBar": {
diff --git a/lightrag_webui/src/locales/fr.json b/lightrag_webui/src/locales/fr.json
index f7327c70..a0629d17 100644
--- a/lightrag_webui/src/locales/fr.json
+++ b/lightrag_webui/src/locales/fr.json
@@ -189,6 +189,7 @@
       "group": "Groupe",
       "technology": "Technologie",
       "product": "Produit",
+      "document": "Document",
       "other": "Autre"
     },
     "sideBar": {
diff --git a/lightrag_webui/src/locales/zh.json b/lightrag_webui/src/locales/zh.json
index a4d33509..951090f7 100644
--- a/lightrag_webui/src/locales/zh.json
+++ b/lightrag_webui/src/locales/zh.json
@@ -189,6 +189,7 @@
       "group": "群组",
       "technology": "技术",
       "product": "产品",
+      "document": "文档",
       "other": "其他"
     },
     "sideBar": {
diff --git a/lightrag_webui/src/locales/zh_TW.json b/lightrag_webui/src/locales/zh_TW.json
index b147b2cc..df35434a 100644
--- a/lightrag_webui/src/locales/zh_TW.json
+++ b/lightrag_webui/src/locales/zh_TW.json
@@ -189,6 +189,7 @@
       "group": "群組",
       "technology": "技術",
       "product": "產品",
+      "document": "文檔",
       "other": "其他"
     },
     "sideBar": {

From 0b07c022d668613e86a71891df3857095135f578 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 3 Sep 2025 12:51:08 +0800
Subject: [PATCH 115/141] Update webui assets and bump api version to 0213

---
 lightrag/api/__init__.py                               |  2 +-
 .../assets/{index-CjbmYv_Z.js => index-BOxJ2b27.js}    | 10 +++++-----
 lightrag/api/webui/index.html                          |  2 +-
 3 files changed, 7 insertions(+), 7 deletions(-)
 rename lightrag/api/webui/assets/{index-CjbmYv_Z.js => index-BOxJ2b27.js} (91%)

diff --git a/lightrag/api/__init__.py b/lightrag/api/__init__.py
index da0ff6dd..7cc89012 100644
--- a/lightrag/api/__init__.py
+++ b/lightrag/api/__init__.py
@@ -1 +1 @@
-__api_version__ = "0212"
+__api_version__ = "0213"
diff --git a/lightrag/api/webui/assets/index-CjbmYv_Z.js b/lightrag/api/webui/assets/index-BOxJ2b27.js
similarity index 91%
rename from lightrag/api/webui/assets/index-CjbmYv_Z.js
rename to lightrag/api/webui/assets/index-BOxJ2b27.js
index d31d07eb..b97f9a10 100644
--- a/lightrag/api/webui/assets/index-CjbmYv_Z.js
+++ b/lightrag/api/webui/assets/index-BOxJ2b27.js
@@ -43,7 +43,7 @@ For more information, see https://radix-ui.com/primitives/docs/components/alert-
 {{error}}`,scanFailed:`Failed to scan documents
 {{error}}`,scanProgressFailed:`Failed to get scan progress
 {{error}}`},fileNameLabel:"File Name",showButton:"Show",hideButton:"Hide",showFileNameTooltip:"Show file name",hideFileNameTooltip:"Hide file name"},pipelineStatus:{title:"Pipeline Status",busy:"Pipeline Busy",requestPending:"Request Pending",jobName:"Job Name",startTime:"Start Time",progress:"Progress",unit:"batch",latestMessage:"Latest Message",historyMessages:"History Messages",errors:{fetchFailed:`Failed to get pipeline status
-{{error}}`}}},Bp={dataIsTruncated:"Graph data is truncated to Max Nodes",statusDialog:{title:"LightRAG Server Settings",description:"View current system status and connection information"},legend:"Legend",nodeTypes:{person:"Person",category:"Category",geo:"Geographic",location:"Location",organization:"Organization",event:"Event",equipment:"Equipment",weapon:"Weapon",animal:"Animal",unknown:"Unknown",object:"Object",group:"Group",technology:"Technology",product:"Product",other:"Other"},sideBar:{settings:{settings:"Settings",healthCheck:"Health Check",showPropertyPanel:"Show Property Panel",showSearchBar:"Show Search Bar",showNodeLabel:"Show Node Label",nodeDraggable:"Node Draggable",showEdgeLabel:"Show Edge Label",hideUnselectedEdges:"Hide Unselected Edges",edgeEvents:"Edge Events",maxQueryDepth:"Max Query Depth",maxNodes:"Max Nodes",maxLayoutIterations:"Max Layout Iterations",resetToDefault:"Reset to default",edgeSizeRange:"Edge Size Range",depth:"D",max:"Max",degree:"Degree",apiKey:"API Key",enterYourAPIkey:"Enter your API key",save:"Save",refreshLayout:"Refresh Layout"},zoomControl:{zoomIn:"Zoom In",zoomOut:"Zoom Out",resetZoom:"Reset Zoom",rotateCamera:"Clockwise Rotate",rotateCameraCounterClockwise:"Counter-Clockwise Rotate"},layoutsControl:{startAnimation:"Continue layout animation",stopAnimation:"Stop layout animation",layoutGraph:"Layout Graph",layouts:{Circular:"Circular",Circlepack:"Circlepack",Random:"Random",Noverlaps:"Noverlaps","Force Directed":"Force Directed","Force Atlas":"Force Atlas"}},fullScreenControl:{fullScreen:"Full Screen",windowed:"Windowed"},legendControl:{toggleLegend:"Toggle Legend"}},statusIndicator:{connected:"Connected",disconnected:"Disconnected"},statusCard:{unavailable:"Status information unavailable",serverInfo:"Server Info",workingDirectory:"Working Directory",inputDirectory:"Input Directory",maxParallelInsert:"Concurrent Doc Processing",summarySettings:"Summary Settings",llmConfig:"LLM Configuration",llmBinding:"LLM Binding",llmBindingHost:"LLM Endpoint",llmModel:"LLM Model",embeddingConfig:"Embedding Configuration",embeddingBinding:"Embedding Binding",embeddingBindingHost:"Embedding Endpoint",embeddingModel:"Embedding Model",storageConfig:"Storage Configuration",kvStorage:"KV Storage",docStatusStorage:"Doc Status Storage",graphStorage:"Graph Storage",vectorStorage:"Vector Storage",workspace:"Workspace",maxGraphNodes:"Max Graph Nodes",rerankerConfig:"Reranker Configuration",rerankerBindingHost:"Reranker Endpoint",rerankerModel:"Reranker Model",lockStatus:"Lock Status",threshold:"Threshold"},propertiesView:{editProperty:"Edit {{property}}",editPropertyDescription:"Edit the property value in the text area below.",errors:{duplicateName:"Node name already exists",updateFailed:"Failed to update node",tryAgainLater:"Please try again later"},success:{entityUpdated:"Node updated successfully",relationUpdated:"Relation updated successfully"},node:{title:"Node",id:"ID",labels:"Labels",degree:"Degree",properties:"Properties",relationships:"Relations(within subgraph)",expandNode:"Expand Node",pruneNode:"Prune Node",deleteAllNodesError:"Refuse to delete all nodes in the graph",nodesRemoved:"{{count}} nodes removed, including orphan nodes",noNewNodes:"No expandable nodes found",propertyNames:{description:"Description",entity_id:"Name",entity_type:"Type",source_id:"SrcID",Neighbour:"Neigh",file_path:"Source",keywords:"Keys",weight:"Weight"}},edge:{title:"Relationship",id:"ID",type:"Type",source:"Source",target:"Target",properties:"Properties"}},search:{placeholder:"Search nodes...",message:"And {count} others"},graphLabels:{selectTooltip:"Select query label",noLabels:"No labels found",label:"Label",placeholder:"Search labels...",andOthers:"And {count} others",refreshTooltip:"Reload data(After file added)"},emptyGraph:"Empty(Try Reload Again)"},Gp={chatMessage:{copyTooltip:"Copy to clipboard",copyError:"Failed to copy text to clipboard"},retrieval:{startPrompt:"Start a retrieval by typing your query below",clear:"Clear",send:"Send",placeholder:"Enter your query (Support prefix: /<Query Mode>)",error:"Error: Failed to get response",queryModeError:"Only supports the following query modes: {{modes}}",queryModePrefixInvalid:"Invalid query mode prefix. Use: /<mode> [space] your query"},querySettings:{parametersTitle:"Parameters",parametersDescription:"Configure your query parameters",queryMode:"Query Mode",queryModeTooltip:`Select the retrieval strategy:
+{{error}}`}}},Bp={dataIsTruncated:"Graph data is truncated to Max Nodes",statusDialog:{title:"LightRAG Server Settings",description:"View current system status and connection information"},legend:"Legend",nodeTypes:{person:"Person",category:"Category",geo:"Geographic",location:"Location",organization:"Organization",event:"Event",equipment:"Equipment",weapon:"Weapon",animal:"Animal",unknown:"Unknown",object:"Object",group:"Group",technology:"Technology",product:"Product",document:"Document",other:"Other"},sideBar:{settings:{settings:"Settings",healthCheck:"Health Check",showPropertyPanel:"Show Property Panel",showSearchBar:"Show Search Bar",showNodeLabel:"Show Node Label",nodeDraggable:"Node Draggable",showEdgeLabel:"Show Edge Label",hideUnselectedEdges:"Hide Unselected Edges",edgeEvents:"Edge Events",maxQueryDepth:"Max Query Depth",maxNodes:"Max Nodes",maxLayoutIterations:"Max Layout Iterations",resetToDefault:"Reset to default",edgeSizeRange:"Edge Size Range",depth:"D",max:"Max",degree:"Degree",apiKey:"API Key",enterYourAPIkey:"Enter your API key",save:"Save",refreshLayout:"Refresh Layout"},zoomControl:{zoomIn:"Zoom In",zoomOut:"Zoom Out",resetZoom:"Reset Zoom",rotateCamera:"Clockwise Rotate",rotateCameraCounterClockwise:"Counter-Clockwise Rotate"},layoutsControl:{startAnimation:"Continue layout animation",stopAnimation:"Stop layout animation",layoutGraph:"Layout Graph",layouts:{Circular:"Circular",Circlepack:"Circlepack",Random:"Random",Noverlaps:"Noverlaps","Force Directed":"Force Directed","Force Atlas":"Force Atlas"}},fullScreenControl:{fullScreen:"Full Screen",windowed:"Windowed"},legendControl:{toggleLegend:"Toggle Legend"}},statusIndicator:{connected:"Connected",disconnected:"Disconnected"},statusCard:{unavailable:"Status information unavailable",serverInfo:"Server Info",workingDirectory:"Working Directory",inputDirectory:"Input Directory",maxParallelInsert:"Concurrent Doc Processing",summarySettings:"Summary Settings",llmConfig:"LLM Configuration",llmBinding:"LLM Binding",llmBindingHost:"LLM Endpoint",llmModel:"LLM Model",embeddingConfig:"Embedding Configuration",embeddingBinding:"Embedding Binding",embeddingBindingHost:"Embedding Endpoint",embeddingModel:"Embedding Model",storageConfig:"Storage Configuration",kvStorage:"KV Storage",docStatusStorage:"Doc Status Storage",graphStorage:"Graph Storage",vectorStorage:"Vector Storage",workspace:"Workspace",maxGraphNodes:"Max Graph Nodes",rerankerConfig:"Reranker Configuration",rerankerBindingHost:"Reranker Endpoint",rerankerModel:"Reranker Model",lockStatus:"Lock Status",threshold:"Threshold"},propertiesView:{editProperty:"Edit {{property}}",editPropertyDescription:"Edit the property value in the text area below.",errors:{duplicateName:"Node name already exists",updateFailed:"Failed to update node",tryAgainLater:"Please try again later"},success:{entityUpdated:"Node updated successfully",relationUpdated:"Relation updated successfully"},node:{title:"Node",id:"ID",labels:"Labels",degree:"Degree",properties:"Properties",relationships:"Relations(within subgraph)",expandNode:"Expand Node",pruneNode:"Prune Node",deleteAllNodesError:"Refuse to delete all nodes in the graph",nodesRemoved:"{{count}} nodes removed, including orphan nodes",noNewNodes:"No expandable nodes found",propertyNames:{description:"Description",entity_id:"Name",entity_type:"Type",source_id:"SrcID",Neighbour:"Neigh",file_path:"Source",keywords:"Keys",weight:"Weight"}},edge:{title:"Relationship",id:"ID",type:"Type",source:"Source",target:"Target",properties:"Properties"}},search:{placeholder:"Search nodes...",message:"And {count} others"},graphLabels:{selectTooltip:"Select query label",noLabels:"No labels found",label:"Label",placeholder:"Search labels...",andOthers:"And {count} others",refreshTooltip:"Reload data(After file added)"},emptyGraph:"Empty(Try Reload Again)"},Gp={chatMessage:{copyTooltip:"Copy to clipboard",copyError:"Failed to copy text to clipboard"},retrieval:{startPrompt:"Start a retrieval by typing your query below",clear:"Clear",send:"Send",placeholder:"Enter your query (Support prefix: /<Query Mode>)",error:"Error: Failed to get response",queryModeError:"Only supports the following query modes: {{modes}}",queryModePrefixInvalid:"Invalid query mode prefix. Use: /<mode> [space] your query"},querySettings:{parametersTitle:"Parameters",parametersDescription:"Configure your query parameters",queryMode:"Query Mode",queryModeTooltip:`Select the retrieval strategy:
 • Naive: Basic search without advanced techniques
 • Local: Context-dependent information retrieval
 • Global: Utilizes global knowledge base
@@ -67,7 +67,7 @@ For more information, see https://radix-ui.com/primitives/docs/components/alert-
 {{error}}`,scanFailed:`扫描文档失败
 {{error}}`,scanProgressFailed:`获取扫描进度失败
 {{error}}`},fileNameLabel:"文件名",showButton:"显示",hideButton:"隐藏",showFileNameTooltip:"显示文件名",hideFileNameTooltip:"隐藏文件名"},pipelineStatus:{title:"流水线状态",busy:"流水线忙碌",requestPending:"待处理请求",jobName:"作业名称",startTime:"开始时间",progress:"进度",unit:"批",latestMessage:"最新消息",historyMessages:"历史消息",errors:{fetchFailed:`获取流水线状态失败
-{{error}}`}}},Fp={dataIsTruncated:"图数据已截断至最大返回节点数",statusDialog:{title:"LightRAG 服务器设置",description:"查看当前系统状态和连接信息"},legend:"图例",nodeTypes:{person:"人物角色",category:"分类",geo:"地理名称",location:"位置",organization:"组织机构",event:"事件",equipment:"装备",weapon:"武器",animal:"动物",unknown:"未知",object:"物品",group:"群组",technology:"技术",product:"产品",other:"其他"},sideBar:{settings:{settings:"设置",healthCheck:"健康检查",showPropertyPanel:"显示属性面板",showSearchBar:"显示搜索栏",showNodeLabel:"显示节点标签",nodeDraggable:"节点可拖动",showEdgeLabel:"显示边标签",hideUnselectedEdges:"隐藏未选中的边",edgeEvents:"边事件",maxQueryDepth:"最大查询深度",maxNodes:"最大返回节点数",maxLayoutIterations:"最大布局迭代次数",resetToDefault:"重置为默认值",edgeSizeRange:"边粗细范围",depth:"深",max:"Max",degree:"邻边",apiKey:"API密钥",enterYourAPIkey:"输入您的API密钥",save:"保存",refreshLayout:"刷新布局"},zoomControl:{zoomIn:"放大",zoomOut:"缩小",resetZoom:"重置缩放",rotateCamera:"顺时针旋转图形",rotateCameraCounterClockwise:"逆时针旋转图形"},layoutsControl:{startAnimation:"继续布局动画",stopAnimation:"停止布局动画",layoutGraph:"图布局",layouts:{Circular:"环形",Circlepack:"圆形打包",Random:"随机",Noverlaps:"无重叠","Force Directed":"力导向","Force Atlas":"力地图"}},fullScreenControl:{fullScreen:"全屏",windowed:"窗口"},legendControl:{toggleLegend:"切换图例显示"}},statusIndicator:{connected:"已连接",disconnected:"未连接"},statusCard:{unavailable:"状态信息不可用",serverInfo:"服务器信息",workingDirectory:"工作目录",inputDirectory:"输入目录",maxParallelInsert:"并行处理文档",summarySettings:"摘要设置",llmConfig:"LLM配置",llmBinding:"LLM绑定",llmBindingHost:"LLM端点",llmModel:"LLM模型",embeddingConfig:"嵌入配置",embeddingBinding:"嵌入绑定",embeddingBindingHost:"嵌入端点",embeddingModel:"嵌入模型",storageConfig:"存储配置",kvStorage:"KV存储",docStatusStorage:"文档状态存储",graphStorage:"图存储",vectorStorage:"向量存储",workspace:"工作空间",maxGraphNodes:"最大图节点数",rerankerConfig:"重排序配置",rerankerBindingHost:"重排序端点",rerankerModel:"重排序模型",lockStatus:"锁状态",threshold:"阈值"},propertiesView:{editProperty:"编辑{{property}}",editPropertyDescription:"在下方文本区域编辑属性值。",errors:{duplicateName:"节点名称已存在",updateFailed:"更新节点失败",tryAgainLater:"请稍后重试"},success:{entityUpdated:"节点更新成功",relationUpdated:"关系更新成功"},node:{title:"节点",id:"ID",labels:"标签",degree:"度数",properties:"属性",relationships:"关系(子图内)",expandNode:"扩展节点",pruneNode:"修剪节点",deleteAllNodesError:"拒绝删除图中的所有节点",nodesRemoved:"已删除 {{count}} 个节点，包括孤立节点",noNewNodes:"没有发现可以扩展的节点",propertyNames:{description:"描述",entity_id:"名称",entity_type:"类型",source_id:"信源ID",Neighbour:"邻接",file_path:"信源",keywords:"Keys",weight:"权重"}},edge:{title:"关系",id:"ID",type:"类型",source:"源节点",target:"目标节点",properties:"属性"}},search:{placeholder:"搜索节点...",message:"还有 {count} 个"},graphLabels:{selectTooltip:"选择查询标签",noLabels:"未找到标签",label:"标签",placeholder:"搜索标签...",andOthers:"还有 {count} 个",refreshTooltip:"重载图形数据(添加文件后需重载)"},emptyGraph:"无数据(请重载图形数据)"},Pp={chatMessage:{copyTooltip:"复制到剪贴板",copyError:"复制文本到剪贴板失败"},retrieval:{startPrompt:"输入查询开始检索",clear:"清空",send:"发送",placeholder:"输入查询内容 (支持模式前缀: /<Query Mode>)",error:"错误：获取响应失败",queryModeError:"仅支持以下查询模式：{{modes}}",queryModePrefixInvalid:"无效的查询模式前缀。请使用：/<模式> [空格] 查询内容"},querySettings:{parametersTitle:"参数",parametersDescription:"配置查询参数",queryMode:"查询模式",queryModeTooltip:`选择检索策略：
+{{error}}`}}},Fp={dataIsTruncated:"图数据已截断至最大返回节点数",statusDialog:{title:"LightRAG 服务器设置",description:"查看当前系统状态和连接信息"},legend:"图例",nodeTypes:{person:"人物角色",category:"分类",geo:"地理名称",location:"位置",organization:"组织机构",event:"事件",equipment:"装备",weapon:"武器",animal:"动物",unknown:"未知",object:"物品",group:"群组",technology:"技术",product:"产品",document:"文档",other:"其他"},sideBar:{settings:{settings:"设置",healthCheck:"健康检查",showPropertyPanel:"显示属性面板",showSearchBar:"显示搜索栏",showNodeLabel:"显示节点标签",nodeDraggable:"节点可拖动",showEdgeLabel:"显示边标签",hideUnselectedEdges:"隐藏未选中的边",edgeEvents:"边事件",maxQueryDepth:"最大查询深度",maxNodes:"最大返回节点数",maxLayoutIterations:"最大布局迭代次数",resetToDefault:"重置为默认值",edgeSizeRange:"边粗细范围",depth:"深",max:"Max",degree:"邻边",apiKey:"API密钥",enterYourAPIkey:"输入您的API密钥",save:"保存",refreshLayout:"刷新布局"},zoomControl:{zoomIn:"放大",zoomOut:"缩小",resetZoom:"重置缩放",rotateCamera:"顺时针旋转图形",rotateCameraCounterClockwise:"逆时针旋转图形"},layoutsControl:{startAnimation:"继续布局动画",stopAnimation:"停止布局动画",layoutGraph:"图布局",layouts:{Circular:"环形",Circlepack:"圆形打包",Random:"随机",Noverlaps:"无重叠","Force Directed":"力导向","Force Atlas":"力地图"}},fullScreenControl:{fullScreen:"全屏",windowed:"窗口"},legendControl:{toggleLegend:"切换图例显示"}},statusIndicator:{connected:"已连接",disconnected:"未连接"},statusCard:{unavailable:"状态信息不可用",serverInfo:"服务器信息",workingDirectory:"工作目录",inputDirectory:"输入目录",maxParallelInsert:"并行处理文档",summarySettings:"摘要设置",llmConfig:"LLM配置",llmBinding:"LLM绑定",llmBindingHost:"LLM端点",llmModel:"LLM模型",embeddingConfig:"嵌入配置",embeddingBinding:"嵌入绑定",embeddingBindingHost:"嵌入端点",embeddingModel:"嵌入模型",storageConfig:"存储配置",kvStorage:"KV存储",docStatusStorage:"文档状态存储",graphStorage:"图存储",vectorStorage:"向量存储",workspace:"工作空间",maxGraphNodes:"最大图节点数",rerankerConfig:"重排序配置",rerankerBindingHost:"重排序端点",rerankerModel:"重排序模型",lockStatus:"锁状态",threshold:"阈值"},propertiesView:{editProperty:"编辑{{property}}",editPropertyDescription:"在下方文本区域编辑属性值。",errors:{duplicateName:"节点名称已存在",updateFailed:"更新节点失败",tryAgainLater:"请稍后重试"},success:{entityUpdated:"节点更新成功",relationUpdated:"关系更新成功"},node:{title:"节点",id:"ID",labels:"标签",degree:"度数",properties:"属性",relationships:"关系(子图内)",expandNode:"扩展节点",pruneNode:"修剪节点",deleteAllNodesError:"拒绝删除图中的所有节点",nodesRemoved:"已删除 {{count}} 个节点，包括孤立节点",noNewNodes:"没有发现可以扩展的节点",propertyNames:{description:"描述",entity_id:"名称",entity_type:"类型",source_id:"信源ID",Neighbour:"邻接",file_path:"信源",keywords:"Keys",weight:"权重"}},edge:{title:"关系",id:"ID",type:"类型",source:"源节点",target:"目标节点",properties:"属性"}},search:{placeholder:"搜索节点...",message:"还有 {count} 个"},graphLabels:{selectTooltip:"选择查询标签",noLabels:"未找到标签",label:"标签",placeholder:"搜索标签...",andOthers:"还有 {count} 个",refreshTooltip:"重载图形数据(添加文件后需重载)"},emptyGraph:"无数据(请重载图形数据)"},Pp={chatMessage:{copyTooltip:"复制到剪贴板",copyError:"复制文本到剪贴板失败"},retrieval:{startPrompt:"输入查询开始检索",clear:"清空",send:"发送",placeholder:"输入查询内容 (支持模式前缀: /<Query Mode>)",error:"错误：获取响应失败",queryModeError:"仅支持以下查询模式：{{modes}}",queryModePrefixInvalid:"无效的查询模式前缀。请使用：/<模式> [空格] 查询内容"},querySettings:{parametersTitle:"参数",parametersDescription:"配置查询参数",queryMode:"查询模式",queryModeTooltip:`选择检索策略：
 • Naive：基础搜索，无高级技术
 • Local：上下文相关信息检索
 • Global：利用全局知识库
@@ -91,7 +91,7 @@ For more information, see https://radix-ui.com/primitives/docs/components/alert-
 {{error}}`,scanFailed:`Échec de la numérisation des documents
 {{error}}`,scanProgressFailed:`Échec de l'obtention de la progression de la numérisation
 {{error}}`},fileNameLabel:"Nom du fichier",showButton:"Afficher",hideButton:"Masquer",showFileNameTooltip:"Afficher le nom du fichier",hideFileNameTooltip:"Masquer le nom du fichier"},pipelineStatus:{title:"État du Pipeline",busy:"Pipeline occupé",requestPending:"Requête en attente",jobName:"Nom du travail",startTime:"Heure de début",progress:"Progression",unit:"lot",latestMessage:"Dernier message",historyMessages:"Historique des messages",errors:{fetchFailed:`Échec de la récupération de l'état du pipeline
-{{error}}`}}},iy={dataIsTruncated:"Les données du graphe sont tronquées au nombre maximum de nœuds",statusDialog:{title:"Paramètres du Serveur LightRAG",description:"Afficher l'état actuel du système et les informations de connexion"},legend:"Légende",nodeTypes:{person:"Personne",category:"Catégorie",geo:"Géographique",location:"Emplacement",organization:"Organisation",event:"Événement",equipment:"Équipement",weapon:"Arme",animal:"Animal",unknown:"Inconnu",object:"Objet",group:"Groupe",technology:"Technologie",product:"Produit",other:"Autre"},sideBar:{settings:{settings:"Paramètres",healthCheck:"Vérification de l'état",showPropertyPanel:"Afficher le panneau des propriétés",showSearchBar:"Afficher la barre de recherche",showNodeLabel:"Afficher l'étiquette du nœud",nodeDraggable:"Nœud déplaçable",showEdgeLabel:"Afficher l'étiquette de l'arête",hideUnselectedEdges:"Masquer les arêtes non sélectionnées",edgeEvents:"Événements des arêtes",maxQueryDepth:"Profondeur maximale de la requête",maxNodes:"Nombre maximum de nœuds",maxLayoutIterations:"Itérations maximales de mise en page",resetToDefault:"Réinitialiser par défaut",edgeSizeRange:"Plage de taille des arêtes",depth:"D",max:"Max",degree:"Degré",apiKey:"Clé API",enterYourAPIkey:"Entrez votre clé API",save:"Sauvegarder",refreshLayout:"Actualiser la mise en page"},zoomControl:{zoomIn:"Zoom avant",zoomOut:"Zoom arrière",resetZoom:"Réinitialiser le zoom",rotateCamera:"Rotation horaire",rotateCameraCounterClockwise:"Rotation antihoraire"},layoutsControl:{startAnimation:"Démarrer l'animation de mise en page",stopAnimation:"Arrêter l'animation de mise en page",layoutGraph:"Mettre en page le graphe",layouts:{Circular:"Circulaire",Circlepack:"Paquet circulaire",Random:"Aléatoire",Noverlaps:"Sans chevauchement","Force Directed":"Dirigé par la force","Force Atlas":"Atlas de force"}},fullScreenControl:{fullScreen:"Plein écran",windowed:"Fenêtré"},legendControl:{toggleLegend:"Basculer la légende"}},statusIndicator:{connected:"Connecté",disconnected:"Déconnecté"},statusCard:{unavailable:"Informations sur l'état indisponibles",serverInfo:"Informations du serveur",workingDirectory:"Répertoire de travail",inputDirectory:"Répertoire d'entrée",maxParallelInsert:"Traitement simultané des documents",summarySettings:"Paramètres de résumé",llmConfig:"Configuration du modèle de langage",llmBinding:"Liaison du modèle de langage",llmBindingHost:"Point de terminaison LLM",llmModel:"Modèle de langage",embeddingConfig:"Configuration d'incorporation",embeddingBinding:"Liaison d'incorporation",embeddingBindingHost:"Point de terminaison d'incorporation",embeddingModel:"Modèle d'incorporation",storageConfig:"Configuration de stockage",kvStorage:"Stockage clé-valeur",docStatusStorage:"Stockage de l'état des documents",graphStorage:"Stockage du graphe",vectorStorage:"Stockage vectoriel",workspace:"Espace de travail",maxGraphNodes:"Nombre maximum de nœuds du graphe",rerankerConfig:"Configuration du reclassement",rerankerBindingHost:"Point de terminaison de reclassement",rerankerModel:"Modèle de reclassement",lockStatus:"État des verrous",threshold:"Seuil"},propertiesView:{editProperty:"Modifier {{property}}",editPropertyDescription:"Modifiez la valeur de la propriété dans la zone de texte ci-dessous.",errors:{duplicateName:"Le nom du nœud existe déjà",updateFailed:"Échec de la mise à jour du nœud",tryAgainLater:"Veuillez réessayer plus tard"},success:{entityUpdated:"Nœud mis à jour avec succès",relationUpdated:"Relation mise à jour avec succès"},node:{title:"Nœud",id:"ID",labels:"Étiquettes",degree:"Degré",properties:"Propriétés",relationships:"Relations(dans le sous-graphe)",expandNode:"Développer le nœud",pruneNode:"Élaguer le nœud",deleteAllNodesError:"Refus de supprimer tous les nœuds du graphe",nodesRemoved:"{{count}} nœuds supprimés, y compris les nœuds orphelins",noNewNodes:"Aucun nœud développable trouvé",propertyNames:{description:"Description",entity_id:"Nom",entity_type:"Type",source_id:"ID source",Neighbour:"Voisin",file_path:"Source",keywords:"Keys",weight:"Poids"}},edge:{title:"Relation",id:"ID",type:"Type",source:"Source",target:"Cible",properties:"Propriétés"}},search:{placeholder:"Rechercher des nœuds...",message:"Et {{count}} autres"},graphLabels:{selectTooltip:"Sélectionner l'étiquette de la requête",noLabels:"Aucune étiquette trouvée",label:"Étiquette",placeholder:"Rechercher des étiquettes...",andOthers:"Et {{count}} autres",refreshTooltip:"Recharger les données (Après l'ajout de fichier)"},emptyGraph:"Vide (Essayez de recharger)"},cy={chatMessage:{copyTooltip:"Copier dans le presse-papiers",copyError:"Échec de la copie du texte dans le presse-papiers"},retrieval:{startPrompt:"Démarrez une récupération en tapant votre requête ci-dessous",clear:"Effacer",send:"Envoyer",placeholder:"Tapez votre requête (Préfixe de requête : /<Query Mode>)",error:"Erreur : Échec de l'obtention de la réponse",queryModeError:"Seuls les modes de requête suivants sont pris en charge : {{modes}}",queryModePrefixInvalid:"Préfixe de mode de requête invalide. Utilisez : /<mode> [espace] votre requête"},querySettings:{parametersTitle:"Paramètres",parametersDescription:"Configurez vos paramètres de requête",queryMode:"Mode de requête",queryModeTooltip:`Sélectionnez la stratégie de récupération :
+{{error}}`}}},iy={dataIsTruncated:"Les données du graphe sont tronquées au nombre maximum de nœuds",statusDialog:{title:"Paramètres du Serveur LightRAG",description:"Afficher l'état actuel du système et les informations de connexion"},legend:"Légende",nodeTypes:{person:"Personne",category:"Catégorie",geo:"Géographique",location:"Emplacement",organization:"Organisation",event:"Événement",equipment:"Équipement",weapon:"Arme",animal:"Animal",unknown:"Inconnu",object:"Objet",group:"Groupe",technology:"Technologie",product:"Produit",document:"Document",other:"Autre"},sideBar:{settings:{settings:"Paramètres",healthCheck:"Vérification de l'état",showPropertyPanel:"Afficher le panneau des propriétés",showSearchBar:"Afficher la barre de recherche",showNodeLabel:"Afficher l'étiquette du nœud",nodeDraggable:"Nœud déplaçable",showEdgeLabel:"Afficher l'étiquette de l'arête",hideUnselectedEdges:"Masquer les arêtes non sélectionnées",edgeEvents:"Événements des arêtes",maxQueryDepth:"Profondeur maximale de la requête",maxNodes:"Nombre maximum de nœuds",maxLayoutIterations:"Itérations maximales de mise en page",resetToDefault:"Réinitialiser par défaut",edgeSizeRange:"Plage de taille des arêtes",depth:"D",max:"Max",degree:"Degré",apiKey:"Clé API",enterYourAPIkey:"Entrez votre clé API",save:"Sauvegarder",refreshLayout:"Actualiser la mise en page"},zoomControl:{zoomIn:"Zoom avant",zoomOut:"Zoom arrière",resetZoom:"Réinitialiser le zoom",rotateCamera:"Rotation horaire",rotateCameraCounterClockwise:"Rotation antihoraire"},layoutsControl:{startAnimation:"Démarrer l'animation de mise en page",stopAnimation:"Arrêter l'animation de mise en page",layoutGraph:"Mettre en page le graphe",layouts:{Circular:"Circulaire",Circlepack:"Paquet circulaire",Random:"Aléatoire",Noverlaps:"Sans chevauchement","Force Directed":"Dirigé par la force","Force Atlas":"Atlas de force"}},fullScreenControl:{fullScreen:"Plein écran",windowed:"Fenêtré"},legendControl:{toggleLegend:"Basculer la légende"}},statusIndicator:{connected:"Connecté",disconnected:"Déconnecté"},statusCard:{unavailable:"Informations sur l'état indisponibles",serverInfo:"Informations du serveur",workingDirectory:"Répertoire de travail",inputDirectory:"Répertoire d'entrée",maxParallelInsert:"Traitement simultané des documents",summarySettings:"Paramètres de résumé",llmConfig:"Configuration du modèle de langage",llmBinding:"Liaison du modèle de langage",llmBindingHost:"Point de terminaison LLM",llmModel:"Modèle de langage",embeddingConfig:"Configuration d'incorporation",embeddingBinding:"Liaison d'incorporation",embeddingBindingHost:"Point de terminaison d'incorporation",embeddingModel:"Modèle d'incorporation",storageConfig:"Configuration de stockage",kvStorage:"Stockage clé-valeur",docStatusStorage:"Stockage de l'état des documents",graphStorage:"Stockage du graphe",vectorStorage:"Stockage vectoriel",workspace:"Espace de travail",maxGraphNodes:"Nombre maximum de nœuds du graphe",rerankerConfig:"Configuration du reclassement",rerankerBindingHost:"Point de terminaison de reclassement",rerankerModel:"Modèle de reclassement",lockStatus:"État des verrous",threshold:"Seuil"},propertiesView:{editProperty:"Modifier {{property}}",editPropertyDescription:"Modifiez la valeur de la propriété dans la zone de texte ci-dessous.",errors:{duplicateName:"Le nom du nœud existe déjà",updateFailed:"Échec de la mise à jour du nœud",tryAgainLater:"Veuillez réessayer plus tard"},success:{entityUpdated:"Nœud mis à jour avec succès",relationUpdated:"Relation mise à jour avec succès"},node:{title:"Nœud",id:"ID",labels:"Étiquettes",degree:"Degré",properties:"Propriétés",relationships:"Relations(dans le sous-graphe)",expandNode:"Développer le nœud",pruneNode:"Élaguer le nœud",deleteAllNodesError:"Refus de supprimer tous les nœuds du graphe",nodesRemoved:"{{count}} nœuds supprimés, y compris les nœuds orphelins",noNewNodes:"Aucun nœud développable trouvé",propertyNames:{description:"Description",entity_id:"Nom",entity_type:"Type",source_id:"ID source",Neighbour:"Voisin",file_path:"Source",keywords:"Keys",weight:"Poids"}},edge:{title:"Relation",id:"ID",type:"Type",source:"Source",target:"Cible",properties:"Propriétés"}},search:{placeholder:"Rechercher des nœuds...",message:"Et {{count}} autres"},graphLabels:{selectTooltip:"Sélectionner l'étiquette de la requête",noLabels:"Aucune étiquette trouvée",label:"Étiquette",placeholder:"Rechercher des étiquettes...",andOthers:"Et {{count}} autres",refreshTooltip:"Recharger les données (Après l'ajout de fichier)"},emptyGraph:"Vide (Essayez de recharger)"},cy={chatMessage:{copyTooltip:"Copier dans le presse-papiers",copyError:"Échec de la copie du texte dans le presse-papiers"},retrieval:{startPrompt:"Démarrez une récupération en tapant votre requête ci-dessous",clear:"Effacer",send:"Envoyer",placeholder:"Tapez votre requête (Préfixe de requête : /<Query Mode>)",error:"Erreur : Échec de l'obtention de la réponse",queryModeError:"Seuls les modes de requête suivants sont pris en charge : {{modes}}",queryModePrefixInvalid:"Préfixe de mode de requête invalide. Utilisez : /<mode> [espace] votre requête"},querySettings:{parametersTitle:"Paramètres",parametersDescription:"Configurez vos paramètres de requête",queryMode:"Mode de requête",queryModeTooltip:`Sélectionnez la stratégie de récupération :
 • Naïf : Recherche de base sans techniques avancées
 • Local : Récupération d'informations dépendante du contexte
 • Global : Utilise une base de connaissances globale
@@ -115,7 +115,7 @@ For more information, see https://radix-ui.com/primitives/docs/components/alert-
 {{error}}`,scanFailed:`فشل مسح المستندات
 {{error}}`,scanProgressFailed:`فشل الحصول على تقدم المسح
 {{error}}`},fileNameLabel:"اسم الملف",showButton:"عرض",hideButton:"إخفاء",showFileNameTooltip:"عرض اسم الملف",hideFileNameTooltip:"إخفاء اسم الملف"},pipelineStatus:{title:"حالة خط المعالجة",busy:"خط المعالجة مشغول",requestPending:"الطلب معلق",jobName:"اسم المهمة",startTime:"وقت البدء",progress:"التقدم",unit:"دفعة",latestMessage:"آخر رسالة",historyMessages:"سجل الرسائل",errors:{fetchFailed:`فشل في جلب حالة خط المعالجة
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 • ساذج: بحث أساسي بدون تقنيات متقدمة
 • محلي: استرجاع معلومات يعتمد على السياق
 • عالمي: يستخدم قاعدة المعرفة العالمية
@@ -139,7 +139,7 @@ For more information, see https://radix-ui.com/primitives/docs/components/alert-
 {{error}}`,scanFailed:`掃描文件失敗
 {{error}}`,scanProgressFailed:`取得掃描進度失敗
 {{error}}`},fileNameLabel:"檔案名稱",showButton:"顯示",hideButton:"隱藏",showFileNameTooltip:"顯示檔案名稱",hideFileNameTooltip:"隱藏檔案名稱"},pipelineStatus:{title:"pipeline 狀態",busy:"pipeline 忙碌中",requestPending:"待處理請求",jobName:"工作名稱",startTime:"開始時間",progress:"進度",unit:"梯次",latestMessage:"最新訊息",historyMessages:"歷史訊息",errors:{fetchFailed:`取得pipeline 狀態失敗
-{{error}}`}}},zy={dataIsTruncated:"圖資料已截斷至最大回傳節點數",statusDialog:{title:"LightRAG 伺服器設定",description:"查看目前系統狀態和連線資訊"},legend:"圖例",nodeTypes:{person:"人物角色",category:"分類",geo:"地理名稱",location:"位置",organization:"組織機構",event:"事件",equipment:"設備",weapon:"武器",animal:"動物",unknown:"未知",object:"物品",group:"群組",technology:"技術",product:"產品",other:"其他"},sideBar:{settings:{settings:"設定",healthCheck:"健康檢查",showPropertyPanel:"顯示屬性面板",showSearchBar:"顯示搜尋列",showNodeLabel:"顯示節點標籤",nodeDraggable:"節點可拖曳",showEdgeLabel:"顯示 Edge 標籤",hideUnselectedEdges:"隱藏未選取的 Edge",edgeEvents:"Edge 事件",maxQueryDepth:"最大查詢深度",maxNodes:"最大回傳節點數",maxLayoutIterations:"最大版面配置迭代次數",resetToDefault:"重設為預設值",edgeSizeRange:"Edge 粗細範圍",depth:"深度",max:"最大值",degree:"鄰邊",apiKey:"API key",enterYourAPIkey:"輸入您的 API key",save:"儲存",refreshLayout:"重新整理版面配置"},zoomControl:{zoomIn:"放大",zoomOut:"縮小",resetZoom:"重設縮放",rotateCamera:"順時針旋轉圖形",rotateCameraCounterClockwise:"逆時針旋轉圖形"},layoutsControl:{startAnimation:"繼續版面配置動畫",stopAnimation:"停止版面配置動畫",layoutGraph:"圖形版面配置",layouts:{Circular:"環形",Circlepack:"圓形打包",Random:"隨機",Noverlaps:"無重疊","Force Directed":"力導向","Force Atlas":"力圖"}},fullScreenControl:{fullScreen:"全螢幕",windowed:"視窗"},legendControl:{toggleLegend:"切換圖例顯示"}},statusIndicator:{connected:"已連線",disconnected:"未連線"},statusCard:{unavailable:"狀態資訊不可用",serverInfo:"伺服器資訊",workingDirectory:"工作目錄",inputDirectory:"輸入目錄",maxParallelInsert:"並行處理文档",summarySettings:"摘要設定",llmConfig:"LLM 設定",llmBinding:"LLM 綁定",llmBindingHost:"LLM 端點",llmModel:"LLM 模型",embeddingConfig:"嵌入設定",embeddingBinding:"嵌入綁定",embeddingBindingHost:"嵌入端點",embeddingModel:"嵌入模型",storageConfig:"儲存設定",kvStorage:"KV 儲存",docStatusStorage:"文件狀態儲存",graphStorage:"圖形儲存",vectorStorage:"向量儲存",workspace:"工作空間",maxGraphNodes:"最大圖形節點數",rerankerConfig:"重排序設定",rerankerBindingHost:"重排序端點",rerankerModel:"重排序模型",lockStatus:"鎖定狀態",threshold:"閾值"},propertiesView:{editProperty:"編輯{{property}}",editPropertyDescription:"在下方文字區域編輯屬性值。",errors:{duplicateName:"節點名稱已存在",updateFailed:"更新節點失敗",tryAgainLater:"請稍後重試"},success:{entityUpdated:"節點更新成功",relationUpdated:"關係更新成功"},node:{title:"節點",id:"ID",labels:"標籤",degree:"度數",properties:"屬性",relationships:"關係(子圖內)",expandNode:"展開節點",pruneNode:"修剪節點",deleteAllNodesError:"拒絕刪除圖中的所有節點",nodesRemoved:"已刪除 {{count}} 個節點，包括孤立節點",noNewNodes:"沒有發現可以展開的節點",propertyNames:{description:"描述",entity_id:"名稱",entity_type:"類型",source_id:"來源ID",Neighbour:"鄰接",file_path:"來源",keywords:"Keys",weight:"權重"}},edge:{title:"關係",id:"ID",type:"類型",source:"來源節點",target:"目標節點",properties:"屬性"}},search:{placeholder:"搜尋節點...",message:"還有 {count} 個"},graphLabels:{selectTooltip:"選擇查詢標籤",noLabels:"未找到標籤",label:"標籤",placeholder:"搜尋標籤...",andOthers:"還有 {count} 個",refreshTooltip:"重載圖形數據(新增檔案後需重載)"},emptyGraph:"無數據(請重載圖形數據)"},Cy={chatMessage:{copyTooltip:"複製到剪貼簿",copyError:"複製文字到剪貼簿失敗"},retrieval:{startPrompt:"輸入查詢開始檢索",clear:"清空",send:"送出",placeholder:"輸入查詢內容 (支援模式前綴：/<Query Mode>)",error:"錯誤：取得回應失敗",queryModeError:"僅支援以下查詢模式：{{modes}}",queryModePrefixInvalid:"無效的查詢模式前綴。請使用：/<模式> [空格] 查詢內容"},querySettings:{parametersTitle:"參數",parametersDescription:"設定查詢參數",queryMode:"查詢模式",queryModeTooltip:`選擇檢索策略：
+{{error}}`}}},zy={dataIsTruncated:"圖資料已截斷至最大回傳節點數",statusDialog:{title:"LightRAG 伺服器設定",description:"查看目前系統狀態和連線資訊"},legend:"圖例",nodeTypes:{person:"人物角色",category:"分類",geo:"地理名稱",location:"位置",organization:"組織機構",event:"事件",equipment:"設備",weapon:"武器",animal:"動物",unknown:"未知",object:"物品",group:"群組",technology:"技術",product:"產品",document:"文檔",other:"其他"},sideBar:{settings:{settings:"設定",healthCheck:"健康檢查",showPropertyPanel:"顯示屬性面板",showSearchBar:"顯示搜尋列",showNodeLabel:"顯示節點標籤",nodeDraggable:"節點可拖曳",showEdgeLabel:"顯示 Edge 標籤",hideUnselectedEdges:"隱藏未選取的 Edge",edgeEvents:"Edge 事件",maxQueryDepth:"最大查詢深度",maxNodes:"最大回傳節點數",maxLayoutIterations:"最大版面配置迭代次數",resetToDefault:"重設為預設值",edgeSizeRange:"Edge 粗細範圍",depth:"深度",max:"最大值",degree:"鄰邊",apiKey:"API key",enterYourAPIkey:"輸入您的 API key",save:"儲存",refreshLayout:"重新整理版面配置"},zoomControl:{zoomIn:"放大",zoomOut:"縮小",resetZoom:"重設縮放",rotateCamera:"順時針旋轉圖形",rotateCameraCounterClockwise:"逆時針旋轉圖形"},layoutsControl:{startAnimation:"繼續版面配置動畫",stopAnimation:"停止版面配置動畫",layoutGraph:"圖形版面配置",layouts:{Circular:"環形",Circlepack:"圓形打包",Random:"隨機",Noverlaps:"無重疊","Force Directed":"力導向","Force Atlas":"力圖"}},fullScreenControl:{fullScreen:"全螢幕",windowed:"視窗"},legendControl:{toggleLegend:"切換圖例顯示"}},statusIndicator:{connected:"已連線",disconnected:"未連線"},statusCard:{unavailable:"狀態資訊不可用",serverInfo:"伺服器資訊",workingDirectory:"工作目錄",inputDirectory:"輸入目錄",maxParallelInsert:"並行處理文档",summarySettings:"摘要設定",llmConfig:"LLM 設定",llmBinding:"LLM 綁定",llmBindingHost:"LLM 端點",llmModel:"LLM 模型",embeddingConfig:"嵌入設定",embeddingBinding:"嵌入綁定",embeddingBindingHost:"嵌入端點",embeddingModel:"嵌入模型",storageConfig:"儲存設定",kvStorage:"KV 儲存",docStatusStorage:"文件狀態儲存",graphStorage:"圖形儲存",vectorStorage:"向量儲存",workspace:"工作空間",maxGraphNodes:"最大圖形節點數",rerankerConfig:"重排序設定",rerankerBindingHost:"重排序端點",rerankerModel:"重排序模型",lockStatus:"鎖定狀態",threshold:"閾值"},propertiesView:{editProperty:"編輯{{property}}",editPropertyDescription:"在下方文字區域編輯屬性值。",errors:{duplicateName:"節點名稱已存在",updateFailed:"更新節點失敗",tryAgainLater:"請稍後重試"},success:{entityUpdated:"節點更新成功",relationUpdated:"關係更新成功"},node:{title:"節點",id:"ID",labels:"標籤",degree:"度數",properties:"屬性",relationships:"關係(子圖內)",expandNode:"展開節點",pruneNode:"修剪節點",deleteAllNodesError:"拒絕刪除圖中的所有節點",nodesRemoved:"已刪除 {{count}} 個節點，包括孤立節點",noNewNodes:"沒有發現可以展開的節點",propertyNames:{description:"描述",entity_id:"名稱",entity_type:"類型",source_id:"來源ID",Neighbour:"鄰接",file_path:"來源",keywords:"Keys",weight:"權重"}},edge:{title:"關係",id:"ID",type:"類型",source:"來源節點",target:"目標節點",properties:"屬性"}},search:{placeholder:"搜尋節點...",message:"還有 {count} 個"},graphLabels:{selectTooltip:"選擇查詢標籤",noLabels:"未找到標籤",label:"標籤",placeholder:"搜尋標籤...",andOthers:"還有 {count} 個",refreshTooltip:"重載圖形數據(新增檔案後需重載)"},emptyGraph:"無數據(請重載圖形數據)"},Cy={chatMessage:{copyTooltip:"複製到剪貼簿",copyError:"複製文字到剪貼簿失敗"},retrieval:{startPrompt:"輸入查詢開始檢索",clear:"清空",send:"送出",placeholder:"輸入查詢內容 (支援模式前綴：/<Query Mode>)",error:"錯誤：取得回應失敗",queryModeError:"僅支援以下查詢模式：{{modes}}",queryModePrefixInvalid:"無效的查詢模式前綴。請使用：/<模式> [空格] 查詢內容"},querySettings:{parametersTitle:"參數",parametersDescription:"設定查詢參數",queryMode:"查詢模式",queryModeTooltip:`選擇檢索策略：
 • Naive：基礎搜尋，無進階技術
 • Local：上下文相關資訊檢索
 • Global：利用全域知識庫
diff --git a/lightrag/api/webui/index.html b/lightrag/api/webui/index.html
index 60827e10..73cad5fa 100644
--- a/lightrag/api/webui/index.html
+++ b/lightrag/api/webui/index.html
@@ -8,7 +8,7 @@
     <link rel="icon" type="image/png" href="favicon.png" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>Lightrag</title>
-    <script type="module" crossorigin src="/webui/assets/index-CjbmYv_Z.js"></script>
+    <script type="module" crossorigin src="/webui/assets/index-BOxJ2b27.js"></script>
     <link rel="modulepreload" crossorigin href="/webui/assets/react-vendor-DEwriMA6.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/ui-vendor-CeCm8EER.js">
     <link rel="modulepreload" crossorigin href="/webui/assets/graph-vendor-B-X5JegA.js">

From 7ef2f0dff65e9a14acf90333acd7bc6e88793f2a Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 3 Sep 2025 21:15:09 +0800
Subject: [PATCH 116/141] Add VDB error handling with retries for data
 consistency

- Add safe_vdb_operation_with_exception util
- Wrap VDB ops in entity/relationship code
- Ensure exceptions propagate on failure
- Add retry logic with configurable delays
---
 lightrag/operate.py | 265 +++++++++++++++++++++++++++++++-------------
 lightrag/utils.py   |  49 +++++++-
 2 files changed, 233 insertions(+), 81 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index cbfbb858..22ed9117 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -30,6 +30,7 @@ from .utils import (
     pick_by_vector_similarity,
     process_chunks_unified,
     build_file_path,
+    safe_vdb_operation_with_exception,
 )
 from .base import (
     BaseGraphStorage,
@@ -930,24 +931,24 @@ async def _rebuild_single_entity(
     async def _update_entity_storage(
         final_description: str, entity_type: str, file_paths: set[str]
     ):
-        # Update entity in graph storage
-        updated_entity_data = {
-            **current_entity,
-            "description": final_description,
-            "entity_type": entity_type,
-            "source_id": GRAPH_FIELD_SEP.join(chunk_ids),
-            "file_path": GRAPH_FIELD_SEP.join(file_paths)
-            if file_paths
-            else current_entity.get("file_path", "unknown_source"),
-        }
-        await knowledge_graph_inst.upsert_node(entity_name, updated_entity_data)
+        try:
+            # Update entity in graph storage (critical path)
+            updated_entity_data = {
+                **current_entity,
+                "description": final_description,
+                "entity_type": entity_type,
+                "source_id": GRAPH_FIELD_SEP.join(chunk_ids),
+                "file_path": GRAPH_FIELD_SEP.join(file_paths)
+                if file_paths
+                else current_entity.get("file_path", "unknown_source"),
+            }
+            await knowledge_graph_inst.upsert_node(entity_name, updated_entity_data)
 
-        # Update entity in vector database
-        entity_vdb_id = compute_mdhash_id(entity_name, prefix="ent-")
+            # Update entity in vector database (equally critical)
+            entity_vdb_id = compute_mdhash_id(entity_name, prefix="ent-")
+            entity_content = f"{entity_name}\n{final_description}"
 
-        entity_content = f"{entity_name}\n{final_description}"
-        await entities_vdb.upsert(
-            {
+            vdb_data = {
                 entity_vdb_id: {
                     "content": entity_content,
                     "entity_name": entity_name,
@@ -957,7 +958,20 @@ async def _rebuild_single_entity(
                     "file_path": updated_entity_data["file_path"],
                 }
             }
-        )
+
+            # Use safe operation wrapper - VDB failure must throw exception
+            await safe_vdb_operation_with_exception(
+                operation=lambda: entities_vdb.upsert(vdb_data),
+                operation_name="rebuild_entity_upsert",
+                entity_name=entity_name,
+                max_retries=3,
+                retry_delay=0.1,
+            )
+
+        except Exception as e:
+            error_msg = f"Failed to update entity storage for `{entity_name}`: {e}"
+            logger.error(error_msg)
+            raise  # Re-raise exception
 
     # Collect all entity data from relevant chunks
     all_entity_data = []
@@ -1145,21 +1159,21 @@ async def _rebuild_single_relationship(
     await knowledge_graph_inst.upsert_edge(src, tgt, updated_relationship_data)
 
     # Update relationship in vector database
-    rel_vdb_id = compute_mdhash_id(src + tgt, prefix="rel-")
-    rel_vdb_id_reverse = compute_mdhash_id(tgt + src, prefix="rel-")
-
-    # Delete old vector records first (both directions to be safe)
     try:
-        await relationships_vdb.delete([rel_vdb_id, rel_vdb_id_reverse])
-    except Exception as e:
-        logger.debug(
-            f"Could not delete old relationship vector records {rel_vdb_id}, {rel_vdb_id_reverse}: {e}"
-        )
+        rel_vdb_id = compute_mdhash_id(src + tgt, prefix="rel-")
+        rel_vdb_id_reverse = compute_mdhash_id(tgt + src, prefix="rel-")
 
-    # Insert new vector record
-    rel_content = f"{combined_keywords}\t{src}\n{tgt}\n{final_description}"
-    await relationships_vdb.upsert(
-        {
+        # Delete old vector records first (both directions to be safe)
+        try:
+            await relationships_vdb.delete([rel_vdb_id, rel_vdb_id_reverse])
+        except Exception as e:
+            logger.debug(
+                f"Could not delete old relationship vector records {rel_vdb_id}, {rel_vdb_id_reverse}: {e}"
+            )
+
+        # Insert new vector record
+        rel_content = f"{combined_keywords}\t{src}\n{tgt}\n{final_description}"
+        vdb_data = {
             rel_vdb_id: {
                 "src_id": src,
                 "tgt_id": tgt,
@@ -1171,7 +1185,20 @@ async def _rebuild_single_relationship(
                 "file_path": updated_relationship_data["file_path"],
             }
         }
-    )
+
+        # Use safe operation wrapper - VDB failure must throw exception
+        await safe_vdb_operation_with_exception(
+            operation=lambda: relationships_vdb.upsert(vdb_data),
+            operation_name="rebuild_relationship_upsert",
+            entity_name=f"{src}-{tgt}",
+            max_retries=3,
+            retry_delay=0.2,
+        )
+
+    except Exception as e:
+        error_msg = f"Failed to rebuild relationship storage for `{src}-{tgt}`: {e}"
+        logger.error(error_msg)
+        raise  # Re-raise exception
 
 
 async def _merge_nodes_then_upsert(
@@ -1516,27 +1543,68 @@ async def merge_nodes_and_edges(
             async with get_storage_keyed_lock(
                 [entity_name], namespace=namespace, enable_logging=False
             ):
-                entity_data = await _merge_nodes_then_upsert(
-                    entity_name,
-                    entities,
-                    knowledge_graph_inst,
-                    global_config,
-                    pipeline_status,
-                    pipeline_status_lock,
-                    llm_response_cache,
-                )
-                if entity_vdb is not None:
-                    data_for_vdb = {
-                        compute_mdhash_id(entity_data["entity_name"], prefix="ent-"): {
-                            "entity_name": entity_data["entity_name"],
-                            "entity_type": entity_data["entity_type"],
-                            "content": f"{entity_data['entity_name']}\n{entity_data['description']}",
-                            "source_id": entity_data["source_id"],
-                            "file_path": entity_data.get("file_path", "unknown_source"),
+                try:
+                    # Graph database operation (critical path, must succeed)
+                    entity_data = await _merge_nodes_then_upsert(
+                        entity_name,
+                        entities,
+                        knowledge_graph_inst,
+                        global_config,
+                        pipeline_status,
+                        pipeline_status_lock,
+                        llm_response_cache,
+                    )
+
+                    # Vector database operation (equally critical, must succeed)
+                    if entity_vdb is not None and entity_data:
+                        data_for_vdb = {
+                            compute_mdhash_id(
+                                entity_data["entity_name"], prefix="ent-"
+                            ): {
+                                "entity_name": entity_data["entity_name"],
+                                "entity_type": entity_data["entity_type"],
+                                "content": f"{entity_data['entity_name']}\n{entity_data['description']}",
+                                "source_id": entity_data["source_id"],
+                                "file_path": entity_data.get(
+                                    "file_path", "unknown_source"
+                                ),
+                            }
                         }
-                    }
-                    await entity_vdb.upsert(data_for_vdb)
-                return entity_data
+
+                        # Use safe operation wrapper - VDB failure must throw exception
+                        await safe_vdb_operation_with_exception(
+                            operation=lambda: entity_vdb.upsert(data_for_vdb),
+                            operation_name="entity_upsert",
+                            entity_name=entity_name,
+                            max_retries=3,
+                            retry_delay=0.1,
+                        )
+
+                    return entity_data
+
+                except Exception as e:
+                    # Any database operation failure is critical
+                    error_msg = (
+                        f"Critical error in entity processing for `{entity_name}`: {e}"
+                    )
+                    logger.error(error_msg)
+
+                    # Try to update pipeline status, but don't let status update failure affect main exception
+                    try:
+                        if (
+                            pipeline_status is not None
+                            and pipeline_status_lock is not None
+                        ):
+                            async with pipeline_status_lock:
+                                pipeline_status["latest_message"] = error_msg
+                                pipeline_status["history_messages"].append(error_msg)
+                    except Exception as status_error:
+                        logger.error(
+                            f"Failed to update pipeline status: {status_error}"
+                        )
+
+                    # Re-raise the original exception
+                    raise
 
     # Create entity processing tasks
     entity_tasks = []
@@ -1584,38 +1652,75 @@ async def merge_nodes_and_edges(
                 namespace=namespace,
                 enable_logging=False,
             ):
-                added_entities = []  # Track entities added during edge processing
-                edge_data = await _merge_edges_then_upsert(
-                    edge_key[0],
-                    edge_key[1],
-                    edges,
-                    knowledge_graph_inst,
-                    global_config,
-                    pipeline_status,
-                    pipeline_status_lock,
-                    llm_response_cache,
-                    added_entities,  # Pass list to collect added entities
-                )
+                try:
+                    added_entities = []  # Track entities added during edge processing
 
-                if edge_data is None:
-                    return None, []
+                    # Graph database operation (critical path, must succeed)
+                    edge_data = await _merge_edges_then_upsert(
+                        edge_key[0],
+                        edge_key[1],
+                        edges,
+                        knowledge_graph_inst,
+                        global_config,
+                        pipeline_status,
+                        pipeline_status_lock,
+                        llm_response_cache,
+                        added_entities,  # Pass list to collect added entities
+                    )
 
-                if relationships_vdb is not None:
-                    data_for_vdb = {
-                        compute_mdhash_id(
-                            edge_data["src_id"] + edge_data["tgt_id"], prefix="rel-"
-                        ): {
-                            "src_id": edge_data["src_id"],
-                            "tgt_id": edge_data["tgt_id"],
-                            "keywords": edge_data["keywords"],
-                            "content": f"{edge_data['src_id']}\t{edge_data['tgt_id']}\n{edge_data['keywords']}\n{edge_data['description']}",
-                            "source_id": edge_data["source_id"],
-                            "file_path": edge_data.get("file_path", "unknown_source"),
-                            "weight": edge_data.get("weight", 1.0),
+                    if edge_data is None:
+                        return None, []
+
+                    # Vector database operation (equally critical, must succeed)
+                    if relationships_vdb is not None:
+                        data_for_vdb = {
+                            compute_mdhash_id(
+                                edge_data["src_id"] + edge_data["tgt_id"], prefix="rel-"
+                            ): {
+                                "src_id": edge_data["src_id"],
+                                "tgt_id": edge_data["tgt_id"],
+                                "keywords": edge_data["keywords"],
+                                "content": f"{edge_data['src_id']}\t{edge_data['tgt_id']}\n{edge_data['keywords']}\n{edge_data['description']}",
+                                "source_id": edge_data["source_id"],
+                                "file_path": edge_data.get(
+                                    "file_path", "unknown_source"
+                                ),
+                                "weight": edge_data.get("weight", 1.0),
+                            }
                         }
-                    }
-                    await relationships_vdb.upsert(data_for_vdb)
-                return edge_data, added_entities
+
+                        # Use safe operation wrapper - VDB failure must throw exception
+                        await safe_vdb_operation_with_exception(
+                            operation=lambda: relationships_vdb.upsert(data_for_vdb),
+                            operation_name="relationship_upsert",
+                            entity_name=f"{edge_data['src_id']}-{edge_data['tgt_id']}",
+                            max_retries=3,
+                            retry_delay=0.1,
+                        )
+
+                    return edge_data, added_entities
+
+                except Exception as e:
+                    # Any database operation failure is critical
+                    error_msg = f"Critical error in relationship processing for `{sorted_edge_key}`: {e}"
+                    logger.error(error_msg)
+
+                    # Try to update pipeline status, but don't let status update failure affect main exception
+                    try:
+                        if (
+                            pipeline_status is not None
+                            and pipeline_status_lock is not None
+                        ):
+                            async with pipeline_status_lock:
+                                pipeline_status["latest_message"] = error_msg
+                                pipeline_status["history_messages"].append(error_msg)
+                    except Exception as status_error:
+                        logger.error(
+                            f"Failed to update pipeline status: {status_error}"
+                        )
+
+                    # Re-raise the original exception
+                    raise
 
     # Create relationship processing tasks
     edge_tasks = []
diff --git a/lightrag/utils.py b/lightrag/utils.py
index f2d56282..83453a7e 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -14,7 +14,7 @@ from dataclasses import dataclass
 from datetime import datetime
 from functools import wraps
 from hashlib import md5
-from typing import Any, Protocol, Callable, TYPE_CHECKING, List
+from typing import Any, Protocol, Callable, TYPE_CHECKING, List, Optional
 import numpy as np
 from dotenv import load_dotenv
 
@@ -57,6 +57,53 @@ except ImportError:
     )
 
 
+async def safe_vdb_operation_with_exception(
+    operation: Callable,
+    operation_name: str,
+    entity_name: str = "",
+    max_retries: int = 3,
+    retry_delay: float = 0.2,
+    logger_func: Optional[Callable] = None
+) -> None:
+    """
+    Safely execute vector database operations with retry mechanism and exception handling.
+    
+    This function ensures that VDB operations are executed with proper error handling
+    and retry logic. If all retries fail, it raises an exception to maintain data consistency.
+    
+    Args:
+        operation: The async operation to execute
+        operation_name: Operation name for logging purposes
+        entity_name: Entity name for logging purposes
+        max_retries: Maximum number of retry attempts
+        retry_delay: Delay between retries in seconds
+        logger_func: Logger function to use for error messages
+    
+    Raises:
+        Exception: When operation fails after all retry attempts
+    """
+    log_func = logger_func or logger.warning
+    last_exception = None
+    
+    for attempt in range(max_retries):
+        try:
+            await operation()
+            return  # Success, return immediately
+        except Exception as e:
+            last_exception = e
+            if attempt == max_retries - 1:
+                error_msg = f"VDB {operation_name} failed for {entity_name} after {max_retries} attempts: {e}"
+                log_func(error_msg)
+                raise Exception(error_msg) from e
+            else:
+                log_func(f"VDB {operation_name} attempt {attempt + 1} failed for {entity_name}: {e}, retrying...")
+                if retry_delay > 0:
+                    await asyncio.sleep(retry_delay)
+    
+    # This line should theoretically never be reached, but included for safety
+    raise Exception(f"Max retries exceeded for {operation_name}") from last_exception
+
+
 def get_env_value(
     env_key: str, default: any, value_type: type = str, special_none: bool = False
 ) -> any:

From a25ce7f0783bde1ac4d3281332a68842e3c5c1d4 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Wed, 3 Sep 2025 21:58:30 +0800
Subject: [PATCH 117/141] Fix linting

---
 lightrag/utils.py | 21 +++++++++------------
 1 file changed, 9 insertions(+), 12 deletions(-)

diff --git a/lightrag/utils.py b/lightrag/utils.py
index 83453a7e..8ebdf9a2 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -63,14 +63,14 @@ async def safe_vdb_operation_with_exception(
     entity_name: str = "",
     max_retries: int = 3,
     retry_delay: float = 0.2,
-    logger_func: Optional[Callable] = None
+    logger_func: Optional[Callable] = None,
 ) -> None:
     """
     Safely execute vector database operations with retry mechanism and exception handling.
-    
+
     This function ensures that VDB operations are executed with proper error handling
     and retry logic. If all retries fail, it raises an exception to maintain data consistency.
-    
+
     Args:
         operation: The async operation to execute
         operation_name: Operation name for logging purposes
@@ -78,30 +78,27 @@ async def safe_vdb_operation_with_exception(
         max_retries: Maximum number of retry attempts
         retry_delay: Delay between retries in seconds
         logger_func: Logger function to use for error messages
-    
+
     Raises:
         Exception: When operation fails after all retry attempts
     """
     log_func = logger_func or logger.warning
-    last_exception = None
-    
+
     for attempt in range(max_retries):
         try:
             await operation()
             return  # Success, return immediately
         except Exception as e:
-            last_exception = e
-            if attempt == max_retries - 1:
+            if attempt >= max_retries - 1:
                 error_msg = f"VDB {operation_name} failed for {entity_name} after {max_retries} attempts: {e}"
                 log_func(error_msg)
                 raise Exception(error_msg) from e
             else:
-                log_func(f"VDB {operation_name} attempt {attempt + 1} failed for {entity_name}: {e}, retrying...")
+                log_func(
+                    f"VDB {operation_name} attempt {attempt + 1} failed for {entity_name}: {e}, retrying..."
+                )
                 if retry_delay > 0:
                     await asyncio.sleep(retry_delay)
-    
-    # This line should theoretically never be reached, but included for safety
-    raise Exception(f"Max retries exceeded for {operation_name}") from last_exception
 
 
 def get_env_value(

From 7b35657e32482beb28b9e10b0e52f8ff070dc165 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 4 Sep 2025 10:47:57 +0800
Subject: [PATCH 118/141] Refactor entity extraction prompt formatting and
 clarity

- Remove quotes from tuple format strings
- Simplify relationship extraction text
- Add relationships to quality guidelines
---
 lightrag/prompt.py | 15 +++++++--------
 1 file changed, 7 insertions(+), 8 deletions(-)

diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index 0d21375a..e5fe8aba 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -16,22 +16,21 @@ Given a text document and a list of entity types, identify all entities of those
 ---Instructions---
 1. Recognizing definitively conceptualized entities in text. For each identified entity, extract the following information:
   - entity_name: Name of the entity, use same language as input text. If English, capitalized the name
-  - entity_type: Categorize the entity using the provided `Entity_types` list. If a suitable category cannot be determined, classify it as "Other".
+  - entity_type: Categorize the entity using the provided `Entity_types` list. If a suitable category cannot be determined, classify it as `Other`.
   - entity_description: Provide a comprehensive description of the entity's attributes and activities based on the information present in the input text. To ensure clarity and precision, all descriptions must replace pronouns and referential terms (e.g., "this document," "our company," "I," "you," "he/she") with the specific nouns they represent.
-2. Format each entity as: ("entity"{tuple_delimiter}<entity_name>{tuple_delimiter}<entity_type>{tuple_delimiter}<entity_description>)
-3. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are directly and clearly related based on the text. Unsubstantiated relationships must be excluded from the output.
-For each pair of related entities, extract the following information:
-  - source_entity: name of the source entity, as identified in step 1
-  - target_entity: name of the target entity, as identified in step 1
+2. Format each entity as: (entity{tuple_delimiter}<entity_name>{tuple_delimiter}<entity_type>{tuple_delimiter}<entity_description>)
+3. From the entities identified, identify all pairs of (source_entity, target_entity) that are directly and clearly related, and extract the following information:
+  - source_entity: name of the source entity
+  - target_entity: name of the target entity
   - relationship_keywords: one or more high-level key words that summarize the overarching nature of the relationship, focusing on concepts or themes rather than specific details
   - relationship_description: Explain the nature of the relationship between the source and target entities, providing a clear rationale for their connection
-4. Format each relationship as: ("relationship"{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
+4. Format each relationship as: (relationship{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
 5. Use `{tuple_delimiter}` as field delimiter. Use `{record_delimiter}` as the entity or relation list delimiter.
 6. Return identified entities and relationships in {language}.
 7. Output `{completion_delimiter}` when all the entities and relationships are extracted.
 
 ---Quality Guidelines---
-- Only extract entities that are clearly defined and meaningful in the context
+- Only extract entities and relationships that are clearly defined and meaningful in the context
 - Avoid over-interpretation; stick to what is explicitly stated in the text
 - For all output content, explicitly name the subject or object rather than using pronouns
 - Include specific numerical data in entity name when relevant

From 9b516a8a53e3b692f6738a452e8a228704f41886 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 4 Sep 2025 10:58:29 +0800
Subject: [PATCH 119/141] Hot Fix: Preserve whitespace chars in text
 sanitization
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Keep \t, \n, \r in control char removal
---
 lightrag/utils.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/lightrag/utils.py b/lightrag/utils.py
index 8ebdf9a2..c696c110 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -1995,8 +1995,8 @@ def sanitize_text_for_encoding(text: str, replacement_char: str = "") -> str:
         # Unescape HTML escapes
         sanitized = html.unescape(sanitized)
 
-        # Remove control characters
-        sanitized = re.sub(r"[\x00-\x1f\x7f-\x9f]", "", sanitized)
+        # Remove control characters but preserve common whitespace (\t, \n, \r)
+        sanitized = re.sub(r"[\x00-\x08\x0B\x0C\x0E-\x1F\x7F-\x9F]", "", sanitized)
 
         return sanitized.strip()
 

From de972f6222b3f391bb29d9c41f97523d6e0c9e61 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 4 Sep 2025 11:48:31 +0800
Subject: [PATCH 120/141] Rename method for clarity and improve code
 readability

- Rename _process_entity_relation_graph to _process_extract_entities
---
 lightrag/lightrag.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/lightrag/lightrag.py b/lightrag/lightrag.py
index 43614a93..6bb46a89 100644
--- a/lightrag/lightrag.py
+++ b/lightrag/lightrag.py
@@ -993,7 +993,7 @@ class LightRAG:
 
             tasks = [
                 self.chunks_vdb.upsert(inserting_chunks),
-                self._process_entity_relation_graph(inserting_chunks),
+                self._process_extract_entities(inserting_chunks),
                 self.full_docs.upsert(new_docs),
                 self.text_chunks.upsert(inserting_chunks),
             ]
@@ -1582,7 +1582,7 @@ class LightRAG:
 
                             # Stage 2: Process entity relation graph (after text_chunks are saved)
                             entity_relation_task = asyncio.create_task(
-                                self._process_entity_relation_graph(
+                                self._process_extract_entities(
                                     chunks, pipeline_status, pipeline_status_lock
                                 )
                             )
@@ -1792,7 +1792,7 @@ class LightRAG:
                 pipeline_status["latest_message"] = log_message
                 pipeline_status["history_messages"].append(log_message)
 
-    async def _process_entity_relation_graph(
+    async def _process_extract_entities(
         self, chunk: dict[str, Any], pipeline_status=None, pipeline_status_lock=None
     ) -> list:
         try:

From c903b148496116e0094d31a45eada49f3f4e03eb Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 4 Sep 2025 12:04:50 +0800
Subject: [PATCH 121/141] Bump AIP version to 0214 and update env.example

---
 env.example              | 6 +++---
 lightrag/api/__init__.py | 2 +-
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/env.example b/env.example
index 749ddc3d..814345a8 100644
--- a/env.example
+++ b/env.example
@@ -175,9 +175,9 @@ LLM_BINDING_API_KEY=your_api_key
 # LLM_BINDING=openai
 
 ### OpenAI Specific Parameters
-### To mitigate endless output loops and prevent greedy decoding for Qwen3, set the temperature and frequency penalty parameter to a highter value
-# OPENAI_LLM_TEMPERATURE=1.2
-# OPENAI_FREQUENCY_PENALTY=1.5
+### To mitigate endless output, set the temperature and frequency penalty parameter to a highter value
+# OPENAI_LLM_TEMPERATURE=0.8
+# OPENAI_FREQUENCY_PENALTY=1.2
 
 ### OpenRouter Specific Parameters
 # OPENAI_LLM_EXTRA_BODY='{"reasoning": {"enabled": false}}'
diff --git a/lightrag/api/__init__.py b/lightrag/api/__init__.py
index 7cc89012..72326bb6 100644
--- a/lightrag/api/__init__.py
+++ b/lightrag/api/__init__.py
@@ -1 +1 @@
-__api_version__ = "0213"
+__api_version__ = "0214"

From 83b54975a258265f8694d9fe64dcfb845e183482 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 4 Sep 2025 12:40:41 +0800
Subject: [PATCH 122/141] fix: resolve "Task exception was never retrieved"
 warnings in async task handling

- Handle multiple simultaneous exceptions correctly
- Maintain fast-fail behavior while ensuring proper exception cleanup to
  prevent asyncio warnings
---
 lightrag/operate.py | 144 +++++++++++++++++++++++++++++++-------------
 1 file changed, 101 insertions(+), 43 deletions(-)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 22ed9117..1ce4630f 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -679,19 +679,34 @@ async def _rebuild_knowledge_from_chunks(
     # Execute all tasks in parallel with semaphore control and early failure detection
     done, pending = await asyncio.wait(tasks, return_when=asyncio.FIRST_EXCEPTION)
 
-    # Check if any task raised an exception
+    # Check if any task raised an exception and ensure all exceptions are retrieved
+    first_exception = None
+
     for task in done:
-        if task.exception():
-            # If a task failed, cancel all pending tasks
-            for pending_task in pending:
-                pending_task.cancel()
+        try:
+            exception = task.exception()
+            if exception is not None:
+                if first_exception is None:
+                    first_exception = exception
+            else:
+                # Task completed successfully, retrieve result to mark as processed
+                task.result()
+        except Exception as e:
+            if first_exception is None:
+                first_exception = e
 
-            # Wait for cancellation to complete
-            if pending:
-                await asyncio.wait(pending)
+    # If any task failed, cancel all pending tasks and raise the first exception
+    if first_exception is not None:
+        # Cancel all pending tasks
+        for pending_task in pending:
+            pending_task.cancel()
 
-            # Re-raise the exception to notify the caller
-            raise task.exception()
+        # Wait for cancellation to complete
+        if pending:
+            await asyncio.wait(pending)
+
+        # Re-raise the first exception to notify the caller
+        raise first_exception
 
     # Final status report
     status_message = f"KG rebuild completed: {rebuilt_entities_count} entities and {rebuilt_relationships_count} relationships rebuilt successfully."
@@ -1619,17 +1634,32 @@ async def merge_nodes_and_edges(
             entity_tasks, return_when=asyncio.FIRST_EXCEPTION
         )
 
-        # Check if any task raised an exception
+        # Check if any task raised an exception and ensure all exceptions are retrieved
+        first_exception = None
+        successful_results = []
+
         for task in done:
-            if task.exception():
-                # If a task failed, cancel all pending tasks
-                for pending_task in pending:
-                    pending_task.cancel()
-                # Wait for cancellation to complete
-                if pending:
-                    await asyncio.wait(pending)
-                # Re-raise the exception to notify the caller
-                raise task.exception()
+            try:
+                exception = task.exception()
+                if exception is not None:
+                    if first_exception is None:
+                        first_exception = exception
+                else:
+                    successful_results.append(task.result())
+            except Exception as e:
+                if first_exception is None:
+                    first_exception = e
+
+        # If any task failed, cancel all pending tasks and raise the first exception
+        if first_exception is not None:
+            # Cancel all pending tasks
+            for pending_task in pending:
+                pending_task.cancel()
+            # Wait for cancellation to complete
+            if pending:
+                await asyncio.wait(pending)
+            # Re-raise the first exception to notify the caller
+            raise first_exception
 
         # If all tasks completed successfully, collect results
         processed_entities = [task.result() for task in entity_tasks]
@@ -1737,17 +1767,32 @@ async def merge_nodes_and_edges(
             edge_tasks, return_when=asyncio.FIRST_EXCEPTION
         )
 
-        # Check if any task raised an exception
+        # Check if any task raised an exception and ensure all exceptions are retrieved
+        first_exception = None
+        successful_results = []
+
         for task in done:
-            if task.exception():
-                # If a task failed, cancel all pending tasks
-                for pending_task in pending:
-                    pending_task.cancel()
-                # Wait for cancellation to complete
-                if pending:
-                    await asyncio.wait(pending)
-                # Re-raise the exception to notify the caller
-                raise task.exception()
+            try:
+                exception = task.exception()
+                if exception is not None:
+                    if first_exception is None:
+                        first_exception = exception
+                else:
+                    successful_results.append(task.result())
+            except Exception as e:
+                if first_exception is None:
+                    first_exception = e
+
+        # If any task failed, cancel all pending tasks and raise the first exception
+        if first_exception is not None:
+            # Cancel all pending tasks
+            for pending_task in pending:
+                pending_task.cancel()
+            # Wait for cancellation to complete
+            if pending:
+                await asyncio.wait(pending)
+            # Re-raise the first exception to notify the caller
+            raise first_exception
 
         # If all tasks completed successfully, collect results
         for task in edge_tasks:
@@ -1995,23 +2040,36 @@ async def extract_entities(
     # This allows us to cancel remaining tasks if any task fails
     done, pending = await asyncio.wait(tasks, return_when=asyncio.FIRST_EXCEPTION)
 
-    # Check if any task raised an exception
+    # Check if any task raised an exception and ensure all exceptions are retrieved
+    first_exception = None
+    chunk_results = []
+
     for task in done:
-        if task.exception():
-            # If a task failed, cancel all pending tasks
-            # This prevents unnecessary processing since the parent function will abort anyway
-            for pending_task in pending:
-                pending_task.cancel()
+        try:
+            exception = task.exception()
+            if exception is not None:
+                if first_exception is None:
+                    first_exception = exception
+            else:
+                chunk_results.append(task.result())
+        except Exception as e:
+            if first_exception is None:
+                first_exception = e
 
-            # Wait for cancellation to complete
-            if pending:
-                await asyncio.wait(pending)
+    # If any task failed, cancel all pending tasks and raise the first exception
+    if first_exception is not None:
+        # Cancel all pending tasks
+        for pending_task in pending:
+            pending_task.cancel()
 
-            # Re-raise the exception to notify the caller
-            raise task.exception()
+        # Wait for cancellation to complete
+        if pending:
+            await asyncio.wait(pending)
 
-    # If all tasks completed successfully, collect results
-    chunk_results = [task.result() for task in tasks]
+        # Re-raise the first exception to notify the caller
+        raise first_exception
+
+    # If all tasks completed successfully, chunk_results already contains the results
 
     # Return the chunk_results for later processing in merge_nodes_and_edges
     return chunk_results

From 94114df995af92576e3a4105834fed5928239c3f Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 4 Sep 2025 14:53:27 +0800
Subject: [PATCH 123/141] Improve prompt clarity and structure

---
 lightrag/prompt.py | 37 ++++++++++++++-----------------------
 1 file changed, 14 insertions(+), 23 deletions(-)

diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index e5fe8aba..d32132b7 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -11,7 +11,7 @@ PROMPTS["DEFAULT_COMPLETION_DELIMITER"] = "<|COMPLETE|>"
 PROMPTS["DEFAULT_USER_PROMPT"] = "n/a"
 
 PROMPTS["entity_extraction"] = """---Task---
-Given a text document and a list of entity types, identify all entities of those types and all relationships among the identified entities.
+For a given text and a list of entity types, extract all entities and their relationships, then return them in the specified {language} and format described below.
 
 ---Instructions---
 1. Recognizing definitively conceptualized entities in text. For each identified entity, extract the following information:
@@ -49,6 +49,19 @@ Text:
 ---Output---
 """
 
+PROMPTS["entity_continue_extraction"] = """---Task---
+Identify any missed entities or relationships in the last extraction task.
+
+---Instructions---
+1. Output the entities and realtionships in the same format as previous extraction task.
+2. Do not include entities and relations that have been previously extracted.
+3. If the entity doesn't clearly fit in any of`Entity_types` provided, classify it as "Other".
+4. Return identified entities and relationships in {language}.
+5. Output `{completion_delimiter}` when all the entities and relationships are extracted.
+
+---Output---
+"""
+
 PROMPTS["entity_extraction_examples"] = [
     """[Example 1]
 
@@ -180,28 +193,6 @@ Description List:
 ---Output---
 """
 
-PROMPTS["entity_continue_extraction"] = """---Task---
-Identify any missed entities or relationships in the last extraction task.
-
----Instructions---
-1. Output the entities and realtionships in the same format as previous extraction task.
-2. Do not include entities and relations that have been previously extracted.
-3. If the entity doesn't clearly fit in any of`Entity_types` provided, classify it as "Other".
-4. Return identified entities and relationships in {language}.
-5. Output `{completion_delimiter}` when all the entities and relationships are extracted.
-
----Output---
-"""
-
-# TODO: Deprecated
-PROMPTS["entity_if_loop_extraction"] = """
----Goal---'
-
-Check if it appears some entities may have still been missed. Output "Yes" if so, otherwise "No".
-
----Output---
-Output:"""
-
 PROMPTS["fail_response"] = (
     "Sorry, I'm not able to provide an answer to that question.[no-context]"
 )

From 50adf64fab1e5aa1f1b1583d19fd8f3ada36e800 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 4 Sep 2025 15:22:36 +0800
Subject: [PATCH 124/141] Fix linting in prompt

---
 lightrag/prompt.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index d32132b7..e89f4b4b 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -11,7 +11,7 @@ PROMPTS["DEFAULT_COMPLETION_DELIMITER"] = "<|COMPLETE|>"
 PROMPTS["DEFAULT_USER_PROMPT"] = "n/a"
 
 PROMPTS["entity_extraction"] = """---Task---
-For a given text and a list of entity types, extract all entities and their relationships, then return them in the specified {language} and format described below.
+For a given text and a list of entity types, extract all entities and their relationships, then return them in the specified language and format described below.
 
 ---Instructions---
 1. Recognizing definitively conceptualized entities in text. For each identified entity, extract the following information:

From f19cce16be41dc21c77c76b72709ce8321162986 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 4 Sep 2025 18:31:53 +0800
Subject: [PATCH 125/141] Fix incorrect variable name in NetworkXStorage file
 path

- Fix working_dir -> workspace_dir typo
- Correct GraphML file path generation
---
 lightrag/kg/networkx_impl.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lightrag/kg/networkx_impl.py b/lightrag/kg/networkx_impl.py
index 028b97a8..09668f6e 100644
--- a/lightrag/kg/networkx_impl.py
+++ b/lightrag/kg/networkx_impl.py
@@ -51,7 +51,7 @@ class NetworkXStorage(BaseGraphStorage):
 
         os.makedirs(workspace_dir, exist_ok=True)
         self._graphml_xml_file = os.path.join(
-            working_dir, f"graph_{self.namespace}.graphml"
+            workspace_dir, f"graph_{self.namespace}.graphml"
         )
         self._storage_lock = None
         self.storage_updated = None

From 2c551cb5dbd0712cc9c1183f106a3bd40d528f94 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 4 Sep 2025 18:51:57 +0800
Subject: [PATCH 126/141] Add support for Chinese book title marks in
 normalize_extracted_info

---
 lightrag/utils.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/lightrag/utils.py b/lightrag/utils.py
index c696c110..e697de8a 100644
--- a/lightrag/utils.py
+++ b/lightrag/utils.py
@@ -1896,6 +1896,12 @@ def normalize_extracted_info(name: str, remove_inner_quotes=False) -> str:
             if "‘" not in inner_content and "’" not in inner_content:
                 name = inner_content
 
+        # Handle Chinese-style book title mark
+        if name.startswith("《") and name.endswith("》"):
+            inner_content = name[1:-1]
+            if "《" not in inner_content and "》" not in inner_content:
+                name = inner_content
+
     if remove_inner_quotes:
         # Remove Chinese quotes
         name = name.replace("“", "").replace("”", "").replace("‘", "").replace("’", "")

From 3f56c6820c8ec83f335b988cd4ceb190973b707d Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 4 Sep 2025 23:05:16 +0800
Subject: [PATCH 127/141] Reorder language and completion delimiter
 instructions in prompt

---
 lightrag/prompt.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index e89f4b4b..0cd8660b 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -26,8 +26,8 @@ For a given text and a list of entity types, extract all entities and their rela
   - relationship_description: Explain the nature of the relationship between the source and target entities, providing a clear rationale for their connection
 4. Format each relationship as: (relationship{tuple_delimiter}<source_entity>{tuple_delimiter}<target_entity>{tuple_delimiter}<relationship_keywords>{tuple_delimiter}<relationship_description>)
 5. Use `{tuple_delimiter}` as field delimiter. Use `{record_delimiter}` as the entity or relation list delimiter.
-6. Return identified entities and relationships in {language}.
-7. Output `{completion_delimiter}` when all the entities and relationships are extracted.
+6. Output `{completion_delimiter}` when all the entities and relationships are extracted.
+7. Ensure the output language is {language}.
 
 ---Quality Guidelines---
 - Only extract entities and relationships that are clearly defined and meaningful in the context

From be3f0ebbe5c06e28c388a6830b5698268d77a4cc Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Thu, 4 Sep 2025 23:42:11 +0800
Subject: [PATCH 128/141] Simplify entity extraction prompt instructions and
 remove delimiter

---
 lightrag/prompt.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/lightrag/prompt.py b/lightrag/prompt.py
index 0cd8660b..776bf2bf 100644
--- a/lightrag/prompt.py
+++ b/lightrag/prompt.py
@@ -56,8 +56,7 @@ Identify any missed entities or relationships in the last extraction task.
 1. Output the entities and realtionships in the same format as previous extraction task.
 2. Do not include entities and relations that have been previously extracted.
 3. If the entity doesn't clearly fit in any of`Entity_types` provided, classify it as "Other".
-4. Return identified entities and relationships in {language}.
-5. Output `{completion_delimiter}` when all the entities and relationships are extracted.
+4. Ensure the output language is {language}.
 
 ---Output---
 """

From e16c302f5fffda276c619dd5c2d93e439e588791 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 01:00:24 +0800
Subject: [PATCH 129/141] Use git tag for Docker image versioning instead of
 semver
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Add step to get latest git tag
• Replace semver with raw tag value
• Maintain latest tag for default branch
• Fix tag resolution in CI pipeline
---
 .github/workflows/docker-publish.yml | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/docker-publish.yml b/.github/workflows/docker-publish.yml
index 9c54b664..998bb6e5 100644
--- a/.github/workflows/docker-publish.yml
+++ b/.github/workflows/docker-publish.yml
@@ -26,13 +26,19 @@ jobs:
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
+      - name: Get latest tag
+        id: get_tag
+        run: |
+          TAG=$(git describe --tags --abbrev=0)
+          echo "tag=$TAG" >> $GITHUB_OUTPUT
+
       - name: Extract metadata for Docker
         id: meta
         uses: docker/metadata-action@v5
         with:
           images: ghcr.io/${{ github.repository }}
           tags: |
-            type=semver,pattern={{version}}
+            type=raw,value=${{ steps.get_tag.outputs.tag }}
             type=raw,value=latest,enable={{is_default_branch}}
 
       - name: Build and push Docker image

From 09334ca8dbdea9dcebfecbd0a00831fd7eaa2389 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 01:11:48 +0800
Subject: [PATCH 130/141] Fix git tag detection in Docker publish workflow

- Fetch full git history for tags
- Add debug output for found tag
- Enable proper tag resolution
---
 .github/workflows/docker-publish.yml | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.github/workflows/docker-publish.yml b/.github/workflows/docker-publish.yml
index 998bb6e5..3f27146d 100644
--- a/.github/workflows/docker-publish.yml
+++ b/.github/workflows/docker-publish.yml
@@ -15,6 +15,8 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
+        with:
+          fetch-depth: 0  # Fetch all history for tags
 
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
@@ -30,6 +32,7 @@ jobs:
         id: get_tag
         run: |
           TAG=$(git describe --tags --abbrev=0)
+          echo "Found tag: $TAG"
           echo "tag=$TAG" >> $GITHUB_OUTPUT
 
       - name: Extract metadata for Docker

From ed5b9b414cd325649f7d9505993655af4bcfcac5 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 01:48:53 +0800
Subject: [PATCH 131/141] Add automatic version extraction from git tags to
 PyPI workflow

* Fetch full git history for tags
* Extract version from latest git tag
* Update __init__.py with tag version
* Display updated version for verification
---
 .github/workflows/pypi-publish.yml | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/.github/workflows/pypi-publish.yml b/.github/workflows/pypi-publish.yml
index 78850d4d..45db4f7d 100644
--- a/.github/workflows/pypi-publish.yml
+++ b/.github/workflows/pypi-publish.yml
@@ -13,11 +13,27 @@ jobs:
 
     steps:
       - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0  # Fetch all history for tags
 
       - uses: actions/setup-python@v5
         with:
           python-version: "3.x"
 
+      - name: Get version from tag
+        id: get_version
+        run: |
+          TAG=$(git describe --tags --abbrev=0)
+          echo "Found tag: $TAG"
+          echo "Extracted version: $TAG"
+          echo "version=$VERSION" >> $GITHUB_OUTPUT
+
+      - name: Update version in __init__.py
+        run: |
+          sed -i "s/__version__ = \".*\"/__version__ = \"${{ steps.get_version.outputs.version }}\"/" lightrag/__init__.py
+          echo "Updated __init__.py with version ${{ steps.get_version.outputs.version }}"
+          cat lightrag/__init__.py | grep __version__
+
       - name: Build release distributions
         run: |
           python -m pip install build

From 688550a9c6d8e15aad836d4d85698047e45e9fef Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 01:53:20 +0800
Subject: [PATCH 132/141] Remove PyPI environment from publish workflow

---
 .github/workflows/pypi-publish.yml | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/.github/workflows/pypi-publish.yml b/.github/workflows/pypi-publish.yml
index 45db4f7d..833323ca 100644
--- a/.github/workflows/pypi-publish.yml
+++ b/.github/workflows/pypi-publish.yml
@@ -52,9 +52,6 @@ jobs:
     permissions:
       id-token: write
 
-    environment:
-      name: pypi
-
     steps:
       - name: Retrieve release distributions
         uses: actions/download-artifact@v4

From b88ab7c04eabafd669bcf03a75e52b229c96c148 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 02:00:44 +0800
Subject: [PATCH 133/141] Revert "Remove PyPI environment from publish
 workflow"

This reverts commit 688550a9c6d8e15aad836d4d85698047e45e9fef.
---
 .github/workflows/pypi-publish.yml | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.github/workflows/pypi-publish.yml b/.github/workflows/pypi-publish.yml
index 833323ca..45db4f7d 100644
--- a/.github/workflows/pypi-publish.yml
+++ b/.github/workflows/pypi-publish.yml
@@ -52,6 +52,9 @@ jobs:
     permissions:
       id-token: write
 
+    environment:
+      name: pypi
+
     steps:
       - name: Retrieve release distributions
         uses: actions/download-artifact@v4

From d85ff5b9d70c4d8adc199912499dfaa9523d7f63 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 02:37:22 +0800
Subject: [PATCH 134/141] Fix variable reference in PyPI publish workflow

---
 .github/workflows/pypi-publish.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/pypi-publish.yml b/.github/workflows/pypi-publish.yml
index 45db4f7d..f1f1db67 100644
--- a/.github/workflows/pypi-publish.yml
+++ b/.github/workflows/pypi-publish.yml
@@ -26,7 +26,7 @@ jobs:
           TAG=$(git describe --tags --abbrev=0)
           echo "Found tag: $TAG"
           echo "Extracted version: $TAG"
-          echo "version=$VERSION" >> $GITHUB_OUTPUT
+          echo "version=$TAG" >> $GITHUB_OUTPUT
 
       - name: Update version in __init__.py
         run: |

From 9181649bae69190c58146e950d36aeff485ea3ea Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 10:56:46 +0800
Subject: [PATCH 135/141] Add version sync to __init__.py in Docker workflows

---
 .github/workflows/docker-build-manual.yml | 6 ++++++
 .github/workflows/docker-publish.yml      | 6 ++++++
 2 files changed, 12 insertions(+)

diff --git a/.github/workflows/docker-build-manual.yml b/.github/workflows/docker-build-manual.yml
index ec2402f4..8b62d574 100644
--- a/.github/workflows/docker-build-manual.yml
+++ b/.github/workflows/docker-build-manual.yml
@@ -30,6 +30,12 @@ jobs:
           echo "tag=$LATEST_TAG" >> $GITHUB_OUTPUT
           echo "image_tag=$LATEST_TAG" >> $GITHUB_OUTPUT
 
+      - name: Update version in __init__.py
+        run: |
+          sed -i "s/__version__ = \".*\"/__version__ = \"${{ steps.get_tag.outputs.tag }}\"/" lightrag/__init__.py
+          echo "Updated __init__.py with version ${{ steps.get_tag.outputs.tag }}"
+          cat lightrag/__init__.py | grep __version__
+
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
 
diff --git a/.github/workflows/docker-publish.yml b/.github/workflows/docker-publish.yml
index 3f27146d..a7aca2df 100644
--- a/.github/workflows/docker-publish.yml
+++ b/.github/workflows/docker-publish.yml
@@ -35,6 +35,12 @@ jobs:
           echo "Found tag: $TAG"
           echo "tag=$TAG" >> $GITHUB_OUTPUT
 
+      - name: Update version in __init__.py
+        run: |
+          sed -i "s/__version__ = \".*\"/__version__ = \"${{ steps.get_tag.outputs.tag }}\"/" lightrag/__init__.py
+          echo "Updated __init__.py with version ${{ steps.get_tag.outputs.tag }}"
+          cat lightrag/__init__.py | grep __version__
+
       - name: Extract metadata for Docker
         id: meta
         uses: docker/metadata-action@v5

From cf31d636c272c83f647762df18fa2f0cec5b2729 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 11:28:28 +0800
Subject: [PATCH 136/141] Add git tag fetching and debug output to Docker
 workflow

---
 .github/workflows/docker-publish.yml | 14 +++++++++++++-
 1 file changed, 13 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/docker-publish.yml b/.github/workflows/docker-publish.yml
index a7aca2df..85a4a964 100644
--- a/.github/workflows/docker-publish.yml
+++ b/.github/workflows/docker-publish.yml
@@ -16,7 +16,8 @@ jobs:
       - name: Checkout code
         uses: actions/checkout@v4
         with:
-          fetch-depth: 0  # Fetch all history for tags
+          fetch-depth: 0
+          fetch-tags: true
 
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
@@ -28,6 +29,17 @@ jobs:
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
+      - name: Debug git info
+        run: |
+          echo "Git status:"
+          git status
+          echo "Available tags:"
+          git tag -l
+          echo "Latest tags:"
+          git tag -l --sort=-version:refname | head -5
+          echo "Describe attempt:"
+          git describe --tags --abbrev=0 || echo "Describe failed"
+          
       - name: Get latest tag
         id: get_tag
         run: |

From 0ccf2036c670079cdf11519235396d26e6f9ce60 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 11:46:56 +0800
Subject: [PATCH 137/141] Refactor Docker workflows: rename and clean up build
 processes
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Rename workflows for clarity
• Remove debug git commands
---
 .github/workflows/docker-build-manual.yml |  2 +-
 .github/workflows/docker-publish.yml      | 16 ++--------------
 2 files changed, 3 insertions(+), 15 deletions(-)

diff --git a/.github/workflows/docker-build-manual.yml b/.github/workflows/docker-build-manual.yml
index 8b62d574..6f6b1598 100644
--- a/.github/workflows/docker-build-manual.yml
+++ b/.github/workflows/docker-build-manual.yml
@@ -1,4 +1,4 @@
-name: Build Docker Image manually
+name: Build Test Docker Image manually
 
 on:
   workflow_dispatch:
diff --git a/.github/workflows/docker-publish.yml b/.github/workflows/docker-publish.yml
index 85a4a964..a6485016 100644
--- a/.github/workflows/docker-publish.yml
+++ b/.github/workflows/docker-publish.yml
@@ -1,4 +1,4 @@
-name: Build Docker Image on Release
+name: Build Latest Docker Image on Release
 
 on:
   release:
@@ -16,8 +16,7 @@ jobs:
       - name: Checkout code
         uses: actions/checkout@v4
         with:
-          fetch-depth: 0
-          fetch-tags: true
+          fetch-depth: 0  # Fetch all history for tags
 
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
@@ -29,17 +28,6 @@ jobs:
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
-      - name: Debug git info
-        run: |
-          echo "Git status:"
-          git status
-          echo "Available tags:"
-          git tag -l
-          echo "Latest tags:"
-          git tag -l --sort=-version:refname | head -5
-          echo "Describe attempt:"
-          git describe --tags --abbrev=0 || echo "Describe failed"
-          
       - name: Get latest tag
         id: get_tag
         run: |

From 17d665c9f32c7fd9fa9087aa17797b2079442ba0 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 12:31:36 +0800
Subject: [PATCH 138/141] Limit history messages to latest 1000 entries with
 truncation indicator
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Limit history to 1000 latest messages
• Add truncation message when needed
• Show count of truncated messages
• Update API documentation
• Prevent memory issues with large logs
---
 lightrag/api/routers/document_routes.py | 25 +++++++++++++++++++++++--
 1 file changed, 23 insertions(+), 2 deletions(-)

diff --git a/lightrag/api/routers/document_routes.py b/lightrag/api/routers/document_routes.py
index 73189277..f54401c8 100644
--- a/lightrag/api/routers/document_routes.py
+++ b/lightrag/api/routers/document_routes.py
@@ -1947,7 +1947,8 @@ def create_document_routes(
                 - cur_batch (int): Current processing batch
                 - request_pending (bool): Flag for pending request for processing
                 - latest_message (str): Latest message from pipeline processing
-                - history_messages (List[str], optional): List of history messages
+                - history_messages (List[str], optional): List of history messages (limited to latest 1000 entries,
+                  with truncation message if more than 1000 messages exist)
 
         Raises:
             HTTPException: If an error occurs while retrieving pipeline status (500)
@@ -1982,8 +1983,28 @@ def create_document_routes(
             status_dict["update_status"] = processed_update_status
 
             # Convert history_messages to a regular list if it's a Manager.list
+            # and limit to latest 1000 entries with truncation message if needed
             if "history_messages" in status_dict:
-                status_dict["history_messages"] = list(status_dict["history_messages"])
+                history_list = list(status_dict["history_messages"])
+                total_count = len(history_list)
+
+                if total_count > 1000:
+                    # Calculate truncated message count
+                    truncated_count = total_count - 1000
+
+                    # Take only the latest 1000 messages
+                    latest_messages = history_list[-1000:]
+
+                    # Add truncation message at the beginning
+                    truncation_message = (
+                        f"[Truncated history messages: {truncated_count}/{total_count}]"
+                    )
+                    status_dict["history_messages"] = [
+                        truncation_message
+                    ] + latest_messages
+                else:
+                    # No truncation needed, return all messages
+                    status_dict["history_messages"] = history_list
 
             # Ensure job_start is properly formatted as a string with timezone information
             if "job_start" in status_dict and status_dict["job_start"]:

From a1df76a4eaf0e28fd297daabbcefd068f89b3336 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 16:36:08 +0800
Subject: [PATCH 139/141] Optimize LLM/embedding config caching to reduce
 repeated parsing overhead
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

• Add LLMConfigCache class for smart caching
• Pre-process OpenAI/Ollama configurations
• Create optimized function factories
• Reduce redundant option parsing calls
---
 lightrag/api/lightrag_server.py | 232 +++++++++++++++++++++-----------
 1 file changed, 153 insertions(+), 79 deletions(-)

diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py
index 3786b454..a32c9c3e 100644
--- a/lightrag/api/lightrag_server.py
+++ b/lightrag/api/lightrag_server.py
@@ -97,11 +97,63 @@ def setup_signal_handlers():
     signal.signal(signal.SIGTERM, signal_handler)  # kill command
 
 
+class LLMConfigCache:
+    """Smart LLM and Embedding configuration cache class"""
+
+    def __init__(self, args):
+        self.args = args
+
+        # Initialize configurations based on binding conditions
+        self.openai_llm_options = None
+        self.ollama_llm_options = None
+        self.ollama_embedding_options = None
+
+        # Only initialize and log OpenAI options when using OpenAI-related bindings
+        if args.llm_binding in ["openai", "azure_openai"]:
+            from lightrag.llm.binding_options import OpenAILLMOptions
+
+            self.openai_llm_options = OpenAILLMOptions.options_dict(args)
+            logger.info(f"OpenAI LLM Options: {self.openai_llm_options}")
+
+        # Only initialize and log Ollama LLM options when using Ollama LLM binding
+        if args.llm_binding == "ollama":
+            try:
+                from lightrag.llm.binding_options import OllamaLLMOptions
+
+                self.ollama_llm_options = OllamaLLMOptions.options_dict(args)
+                logger.info(f"Ollama LLM Options: {self.ollama_llm_options}")
+            except ImportError:
+                logger.warning(
+                    "OllamaLLMOptions not available, using default configuration"
+                )
+                self.ollama_llm_options = {}
+
+        # Only initialize and log Ollama Embedding options when using Ollama Embedding binding
+        if args.embedding_binding == "ollama":
+            try:
+                from lightrag.llm.binding_options import OllamaEmbeddingOptions
+
+                self.ollama_embedding_options = OllamaEmbeddingOptions.options_dict(
+                    args
+                )
+                logger.info(
+                    f"Ollama Embedding Options: {self.ollama_embedding_options}"
+                )
+            except ImportError:
+                logger.warning(
+                    "OllamaEmbeddingOptions not available, using default configuration"
+                )
+                self.ollama_embedding_options = {}
+
+
 def create_app(args):
     # Setup logging
     logger.setLevel(args.log_level)
     set_verbose_debug(args.verbose)
 
+    # Create configuration cache (this will output configuration logs)
+    config_cache = LLMConfigCache(args)
+
     # Verify that bindings are correctly setup
     if args.llm_binding not in [
         "lollms",
@@ -238,10 +290,85 @@ def create_app(args):
     # Create working directory if it doesn't exist
     Path(args.working_dir).mkdir(parents=True, exist_ok=True)
 
+    def create_optimized_openai_llm_func(
+        config_cache: LLMConfigCache, args, llm_timeout: int
+    ):
+        """Create optimized OpenAI LLM function with pre-processed configuration"""
+
+        async def optimized_openai_alike_model_complete(
+            prompt,
+            system_prompt=None,
+            history_messages=None,
+            keyword_extraction=False,
+            **kwargs,
+        ) -> str:
+            from lightrag.llm.openai import openai_complete_if_cache
+
+            keyword_extraction = kwargs.pop("keyword_extraction", None)
+            if keyword_extraction:
+                kwargs["response_format"] = GPTKeywordExtractionFormat
+            if history_messages is None:
+                history_messages = []
+
+            # Use pre-processed configuration to avoid repeated parsing
+            kwargs["timeout"] = llm_timeout
+            if config_cache.openai_llm_options:
+                kwargs.update(config_cache.openai_llm_options)
+
+            return await openai_complete_if_cache(
+                args.llm_model,
+                prompt,
+                system_prompt=system_prompt,
+                history_messages=history_messages,
+                base_url=args.llm_binding_host,
+                api_key=args.llm_binding_api_key,
+                **kwargs,
+            )
+
+        return optimized_openai_alike_model_complete
+
+    def create_optimized_azure_openai_llm_func(
+        config_cache: LLMConfigCache, args, llm_timeout: int
+    ):
+        """Create optimized Azure OpenAI LLM function with pre-processed configuration"""
+
+        async def optimized_azure_openai_model_complete(
+            prompt,
+            system_prompt=None,
+            history_messages=None,
+            keyword_extraction=False,
+            **kwargs,
+        ) -> str:
+            from lightrag.llm.azure_openai import azure_openai_complete_if_cache
+
+            keyword_extraction = kwargs.pop("keyword_extraction", None)
+            if keyword_extraction:
+                kwargs["response_format"] = GPTKeywordExtractionFormat
+            if history_messages is None:
+                history_messages = []
+
+            # Use pre-processed configuration to avoid repeated parsing
+            kwargs["timeout"] = llm_timeout
+            if config_cache.openai_llm_options:
+                kwargs.update(config_cache.openai_llm_options)
+
+            return await azure_openai_complete_if_cache(
+                args.llm_model,
+                prompt,
+                system_prompt=system_prompt,
+                history_messages=history_messages,
+                base_url=args.llm_binding_host,
+                api_key=os.getenv("AZURE_OPENAI_API_KEY", args.llm_binding_api_key),
+                api_version=os.getenv("AZURE_OPENAI_API_VERSION", "2024-08-01-preview"),
+                **kwargs,
+            )
+
+        return optimized_azure_openai_model_complete
+
     def create_llm_model_func(binding: str):
         """
         Create LLM model function based on binding type.
-        Uses lazy import to avoid unnecessary dependencies.
+        Uses optimized functions for OpenAI bindings and lazy import for others.
         """
         try:
             if binding == "lollms":
@@ -255,9 +382,13 @@ def create_app(args):
             elif binding == "aws_bedrock":
                 return bedrock_model_complete  # Already defined locally
             elif binding == "azure_openai":
-                return azure_openai_model_complete  # Already defined locally
+                # Use optimized function with pre-processed configuration
+                return create_optimized_azure_openai_llm_func(
+                    config_cache, args, llm_timeout
+                )
             else:  # openai and compatible
-                return openai_alike_model_complete  # Already defined locally
+                # Use optimized function with pre-processed configuration
+                return create_optimized_openai_llm_func(config_cache, args, llm_timeout)
         except ImportError as e:
             raise Exception(f"Failed to import {binding} LLM binding: {e}")
 
@@ -280,15 +411,15 @@ def create_app(args):
                 raise Exception(f"Failed to import {binding} options: {e}")
         return {}
 
-    def create_embedding_function_with_lazy_import(
-        binding, model, host, api_key, dimensions, args
+    def create_optimized_embedding_function(
+        config_cache: LLMConfigCache, binding, model, host, api_key, dimensions, args
     ):
         """
-        Create embedding function with lazy imports for all bindings.
-        Replaces the current create_embedding_function with full lazy import support.
+        Create optimized embedding function with pre-processed configuration for applicable bindings.
+        Uses lazy imports for all bindings and avoids repeated configuration parsing.
         """
 
-        async def embedding_function(texts):
+        async def optimized_embedding_function(texts):
             try:
                 if binding == "lollms":
                     from lightrag.llm.lollms import lollms_embed
@@ -297,10 +428,17 @@ def create_app(args):
                         texts, embed_model=model, host=host, api_key=api_key
                     )
                 elif binding == "ollama":
-                    from lightrag.llm.binding_options import OllamaEmbeddingOptions
                     from lightrag.llm.ollama import ollama_embed
 
-                    ollama_options = OllamaEmbeddingOptions.options_dict(args)
+                    # Use pre-processed configuration if available, otherwise fallback to dynamic parsing
+                    if config_cache.ollama_embedding_options is not None:
+                        ollama_options = config_cache.ollama_embedding_options
+                    else:
+                        # Fallback for cases where config cache wasn't initialized properly
+                        from lightrag.llm.binding_options import OllamaEmbeddingOptions
+
+                        ollama_options = OllamaEmbeddingOptions.options_dict(args)
+
                     return await ollama_embed(
                         texts,
                         embed_model=model,
@@ -331,78 +469,13 @@ def create_app(args):
             except ImportError as e:
                 raise Exception(f"Failed to import {binding} embedding: {e}")
 
-        return embedding_function
+        return optimized_embedding_function
 
     llm_timeout = get_env_value("LLM_TIMEOUT", DEFAULT_LLM_TIMEOUT, int)
     embedding_timeout = get_env_value(
         "EMBEDDING_TIMEOUT", DEFAULT_EMBEDDING_TIMEOUT, int
     )
 
-    async def openai_alike_model_complete(
-        prompt,
-        system_prompt=None,
-        history_messages=None,
-        keyword_extraction=False,
-        **kwargs,
-    ) -> str:
-        # Lazy import
-        from lightrag.llm.openai import openai_complete_if_cache
-        from lightrag.llm.binding_options import OpenAILLMOptions
-
-        keyword_extraction = kwargs.pop("keyword_extraction", None)
-        if keyword_extraction:
-            kwargs["response_format"] = GPTKeywordExtractionFormat
-        if history_messages is None:
-            history_messages = []
-
-        # Use OpenAI LLM options if available
-        openai_options = OpenAILLMOptions.options_dict(args)
-        kwargs["timeout"] = llm_timeout
-        kwargs.update(openai_options)
-
-        return await openai_complete_if_cache(
-            args.llm_model,
-            prompt,
-            system_prompt=system_prompt,
-            history_messages=history_messages,
-            base_url=args.llm_binding_host,
-            api_key=args.llm_binding_api_key,
-            **kwargs,
-        )
-
-    async def azure_openai_model_complete(
-        prompt,
-        system_prompt=None,
-        history_messages=None,
-        keyword_extraction=False,
-        **kwargs,
-    ) -> str:
-        # Lazy import
-        from lightrag.llm.azure_openai import azure_openai_complete_if_cache
-        from lightrag.llm.binding_options import OpenAILLMOptions
-
-        keyword_extraction = kwargs.pop("keyword_extraction", None)
-        if keyword_extraction:
-            kwargs["response_format"] = GPTKeywordExtractionFormat
-        if history_messages is None:
-            history_messages = []
-
-        # Use OpenAI LLM options
-        openai_options = OpenAILLMOptions.options_dict(args)
-        kwargs["timeout"] = llm_timeout
-        kwargs.update(openai_options)
-
-        return await azure_openai_complete_if_cache(
-            args.llm_model,
-            prompt,
-            system_prompt=system_prompt,
-            history_messages=history_messages,
-            base_url=args.llm_binding_host,
-            api_key=os.getenv("AZURE_OPENAI_API_KEY"),
-            api_version=os.getenv("AZURE_OPENAI_API_VERSION", "2024-08-01-preview"),
-            **kwargs,
-        )
-
     async def bedrock_model_complete(
         prompt,
         system_prompt=None,
@@ -430,16 +503,17 @@ def create_app(args):
             **kwargs,
         )
 
-    # Create embedding function with lazy imports
+    # Create embedding function with optimized configuration
     embedding_func = EmbeddingFunc(
         embedding_dim=args.embedding_dim,
-        func=create_embedding_function_with_lazy_import(
+        func=create_optimized_embedding_function(
+            config_cache=config_cache,
             binding=args.embedding_binding,
             model=args.embedding_model,
             host=args.embedding_binding_host,
             api_key=args.embedding_binding_api_key,
             dimensions=args.embedding_dim,
-            args=args,  # Pass args object for dynamic option generation
+            args=args,  # Pass args object for fallback option generation
         ),
     )
 

From 2db7e4a3e87d4818cb03aefeb02dcd739d2f39b3 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 17:13:29 +0800
Subject: [PATCH 140/141] Update env.example

---
 env.example | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/env.example b/env.example
index 814345a8..d449627b 100644
--- a/env.example
+++ b/env.example
@@ -175,9 +175,8 @@ LLM_BINDING_API_KEY=your_api_key
 # LLM_BINDING=openai
 
 ### OpenAI Specific Parameters
-### To mitigate endless output, set the temperature and frequency penalty parameter to a highter value
+### To mitigate endless output, set the temperature to a highter value
 # OPENAI_LLM_TEMPERATURE=0.8
-# OPENAI_FREQUENCY_PENALTY=1.2
 
 ### OpenRouter Specific Parameters
 # OPENAI_LLM_EXTRA_BODY='{"reasoning": {"enabled": false}}'

From 385668dec5f3ee41975092f501929bdbe22159b2 Mon Sep 17 00:00:00 2001
From: yangdx <gzdaniel@me.com>
Date: Fri, 5 Sep 2025 17:14:42 +0800
Subject: [PATCH 141/141] Fix malformed tuple delimiters in extraction result
 processing

---
 lightrag/operate.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/lightrag/operate.py b/lightrag/operate.py
index 1ce4630f..f5eac4c3 100644
--- a/lightrag/operate.py
+++ b/lightrag/operate.py
@@ -870,6 +870,10 @@ async def _process_extraction_result(
             record = record.replace("<|>>", "<|>")
             # fix <<|> with <|>
             record = record.replace("<<|>", "<|>")
+            # fix <.|> with <|>
+            record = record.replace("<.|>", "<|>")
+            # fix <|.> with <|>
+            record = record.replace("<|.>", "<|>")
 
         record_attributes = split_string_by_multi_markers(record, [tuple_delimiter])