diff --git a/.gitignore b/.gitignore index 29e275b7..a5113296 100644 --- a/.gitignore +++ b/.gitignore @@ -46,10 +46,8 @@ neo4jWorkDir/ # Data & Storage inputs/ +output/ rag_storage/ -examples/input/ -examples/output/ -output*/ data/ # Miscellaneous @@ -59,18 +57,15 @@ ignore_this.txt *.ignore.* # Project-specific files -dickens*/ -book.txt -LightRAG.pdf +/dickens*/ +/book.txt download_models_hf.py -lightrag-dev/ -gui/ # Frontend build output (built during PyPI release) -lightrag/api/webui/ +/lightrag/api/webui/ # unit-test files test_* # Cline files -memory-bank/ +memory-bank diff --git a/Dockerfile b/Dockerfile index 67aa92b6..aaa3c84b 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,3 +1,5 @@ +# syntax=docker/dockerfile:1 + # Frontend build stage FROM oven/bun:1 AS frontend-builder @@ -7,7 +9,8 @@ WORKDIR /app COPY lightrag_webui/ ./lightrag_webui/ # Build frontend assets for inclusion in the API package -RUN cd lightrag_webui \ +RUN --mount=type=cache,target=/root/.bun/install/cache \ + cd lightrag_webui \ && bun install --frozen-lockfile \ && bun run build @@ -40,7 +43,8 @@ COPY setup.py . COPY uv.lock . # Install base, API, and offline extras without the project to improve caching -RUN uv sync --frozen --no-dev --extra api --extra offline --no-install-project --no-editable +RUN --mount=type=cache,target=/root/.local/share/uv \ + uv sync --frozen --no-dev --extra api --extra offline --no-install-project --no-editable # Copy project sources after dependency layer COPY lightrag/ ./lightrag/ @@ -49,7 +53,8 @@ COPY lightrag/ ./lightrag/ COPY --from=frontend-builder /app/lightrag/api/webui ./lightrag/api/webui # Sync project in non-editable mode and ensure pip is available for runtime installs -RUN uv sync --frozen --no-dev --extra api --extra offline --no-editable \ +RUN --mount=type=cache,target=/root/.local/share/uv \ + uv sync --frozen --no-dev --extra api --extra offline --no-editable \ && /app/.venv/bin/python -m ensurepip --upgrade # Prepare offline cache directory and pre-populate tiktoken data @@ -81,7 +86,8 @@ ENV PATH=/app/.venv/bin:/root/.local/bin:$PATH # Install dependencies with uv sync (uses locked versions from uv.lock) # And ensure pip is available for runtime installs -RUN uv sync --frozen --no-dev --extra api --extra offline --no-editable \ +RUN --mount=type=cache,target=/root/.local/share/uv \ + uv sync --frozen --no-dev --extra api --extra offline --no-editable \ && /app/.venv/bin/python -m ensurepip --upgrade # Create persistent data directories AFTER package installation diff --git a/Dockerfile.lite b/Dockerfile.lite index 25ec8fe5..3f488886 100644 --- a/Dockerfile.lite +++ b/Dockerfile.lite @@ -1,3 +1,5 @@ +# syntax=docker/dockerfile:1 + # Frontend build stage FROM oven/bun:1 AS frontend-builder @@ -7,7 +9,8 @@ WORKDIR /app COPY lightrag_webui/ ./lightrag_webui/ # Build frontend assets for inclusion in the API package -RUN cd lightrag_webui \ +RUN --mount=type=cache,target=/root/.bun/install/cache \ + cd lightrag_webui \ && bun install --frozen-lockfile \ && bun run build @@ -40,7 +43,8 @@ COPY setup.py . COPY uv.lock . # Install project dependencies (base + API extras) without the project to improve caching -RUN uv sync --frozen --no-dev --extra api --no-install-project --no-editable +RUN --mount=type=cache,target=/root/.local/share/uv \ + uv sync --frozen --no-dev --extra api --no-install-project --no-editable # Copy project sources after dependency layer COPY lightrag/ ./lightrag/ @@ -49,7 +53,8 @@ COPY lightrag/ ./lightrag/ COPY --from=frontend-builder /app/lightrag/api/webui ./lightrag/api/webui # Sync project in non-editable mode and ensure pip is available for runtime installs -RUN uv sync --frozen --no-dev --extra api --no-editable \ +RUN --mount=type=cache,target=/root/.local/share/uv \ + uv sync --frozen --no-dev --extra api --no-editable \ && /app/.venv/bin/python -m ensurepip --upgrade # Prepare tiktoken cache directory and pre-populate tokenizer data @@ -81,7 +86,8 @@ ENV PATH=/app/.venv/bin:/root/.local/bin:$PATH # Sync dependencies inside the final image using uv # And ensure pip is available for runtime installs -RUN uv sync --frozen --no-dev --extra api --no-editable \ +RUN --mount=type=cache,target=/root/.local/share/uv \ + uv sync --frozen --no-dev --extra api --no-editable \ && /app/.venv/bin/python -m ensurepip --upgrade # Create persistent data directories diff --git a/MANIFEST.in b/MANIFEST.in index 3c771107..cf12c1e9 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -1,3 +1,4 @@ include requirements.txt include lightrag/api/requirements.txt recursive-include lightrag/api/webui * +recursive-include lightrag/api/static * diff --git a/README-zh.md b/README-zh.md index 867478bd..552d566a 100644 --- a/README-zh.md +++ b/README-zh.md @@ -104,18 +104,26 @@ lightrag-server git clone https://github.com/HKUDS/LightRAG.git cd LightRAG # 如有必要，创建Python虚拟环境 -# 以可编辑模式安装并支持API +# 以可开发（编辑）模式安装LightRAG服务器 pip install -e ".[api]" -cp env.example .env + +cp env.example .env # 使用你的LLM和Embedding模型访问参数更新.env文件 + +# 构建前端代码 +cd lightrag_webui +bun install --frozen-lockfile +bun run build +cd .. + lightrag-server ``` * 使用 Docker Compose 启动 LightRAG 服务器 -``` +```bash git clone https://github.com/HKUDS/LightRAG.git cd LightRAG -cp env.example .env +cp env.example .env # 使用你的LLM和Embedding模型访问参数更新.env文件 # modify LLM and Embedding settings in .env docker compose up ``` diff --git a/README.md b/README.md index 9ba35c4b..b844a18d 100644 --- a/README.md +++ b/README.md @@ -103,19 +103,27 @@ lightrag-server ```bash git clone https://github.com/HKUDS/LightRAG.git cd LightRAG -# create a Python virtual enviroment if neccesary +# Create a Python virtual enviroment if neccesary # Install in editable mode with API support pip install -e ".[api]" -cp env.example .env + +cp env.example .env # Update the .env with your LLM and embedding configurations + +# Build front-end artifacts +cd lightrag_webui +bun install --frozen-lockfile +bun run build +cd .. + lightrag-server ``` * Launching the LightRAG Server with Docker Compose -``` +```bash git clone https://github.com/HKUDS/LightRAG.git cd LightRAG -cp env.example .env +cp env.example .env # Update the .env with your LLM and embedding configurations # modify LLM and Embedding settings in .env docker compose up ``` @@ -933,7 +941,8 @@ maxclients 500 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: - **For local file-based databases, data isolation is achieved through workspace subdirectories:** `JsonKVStorage`, `JsonDocStatusStorage`, `NetworkXStorage`, `NanoVectorDBStorage`, `FaissVectorDBStorage`. -- **For databases that store data in collections, it's done by adding a workspace prefix to the collection name:** `RedisKVStorage`, `RedisDocStatusStorage`, `MilvusVectorDBStorage`, `QdrantVectorDBStorage`, `MongoKVStorage`, `MongoDocStatusStorage`, `MongoVectorDBStorage`, `MongoGraphStorage`, `PGGraphStorage`. +- **For databases that store data in collections, it's done by adding a workspace prefix to the collection name:** `RedisKVStorage`, `RedisDocStatusStorage`, `MilvusVectorDBStorage`, `MongoKVStorage`, `MongoDocStatusStorage`, `MongoVectorDBStorage`, `MongoGraphStorage`, `PGGraphStorage`. +- **For Qdrant vector database, data isolation is achieved through payload-based partitioning (Qdrant's recommended multitenancy approach):** `QdrantVectorDBStorage` uses shared collections with payload filtering for unlimited workspace scalability. - **For relational databases, data isolation is achieved by adding a `workspace` field to the tables for logical data separation:** `PGKVStorage`, `PGVectorStorage`, `PGDocStatusStorage`. - **For the Neo4j graph database, logical data isolation is achieved through labels:** `Neo4JStorage` @@ -1538,7 +1547,7 @@ The dataset used in LightRAG can be downloaded from [TommyChien/UltraDomain](htt ### Generate Query -LightRAG uses the following prompt to generate high-level queries, with the corresponding code in `example/generate_query.py`. +LightRAG uses the following prompt to generate high-level queries, with the corresponding code in `examples/generate_query.py`.
Prompt diff --git a/docs/DockerDeployment.md b/docs/DockerDeployment.md index 968a8ec7..575359b4 100644 --- a/docs/DockerDeployment.md +++ b/docs/DockerDeployment.md @@ -59,10 +59,19 @@ LightRAG can be configured using environment variables in the `.env` file: Docker instructions work the same on all platforms with Docker Desktop installed. +### Build Optimization + +The Dockerfile uses BuildKit cache mounts to significantly improve build performance: + +- **Automatic cache management**: BuildKit is automatically enabled via `# syntax=docker/dockerfile:1` directive +- **Faster rebuilds**: Only downloads changed dependencies when `uv.lock` or `bun.lock` files are modified +- **Efficient package caching**: UV and Bun package downloads are cached across builds +- **No manual configuration needed**: Works out of the box in Docker Compose and GitHub Actions + ### Start LightRAG server: ```bash -docker-compose up -d +docker compose up -d ``` LightRAG Server uses the following paths for data storage: @@ -77,9 +86,9 @@ data/ To update the Docker container: ```bash -docker-compose pull -docker-compose down -docker-compose up +docker compose pull +docker compose down +docker compose up ``` ### Offline deployment @@ -91,10 +100,15 @@ Software packages requiring `transformers`, `torch`, or `cuda` will is not prein ### For local development and testing ```bash -# Build and run with docker-compose +# Build and run with Docker Compose (BuildKit automatically enabled) docker compose up --build + +# Or explicitly enable BuildKit if needed +DOCKER_BUILDKIT=1 docker compose up --build ``` +**Note**: BuildKit is automatically enabled by the `# syntax=docker/dockerfile:1` directive in the Dockerfile, ensuring optimal caching performance. + ### For production release **multi-architecture build and push**: diff --git a/env.example b/env.example index 3c5113ff..f60ba29d 100644 --- a/env.example +++ b/env.example @@ -119,6 +119,9 @@ ENABLE_LLM_CACHE_FOR_EXTRACT=true ### Document processing output language: English, Chinese, French, German ... SUMMARY_LANGUAGE=English +### PDF decryption password for protected PDF files +# PDF_DECRYPT_PASSWORD=your_pdf_password_here + ### Entity types that the LLM will attempt to recognize # ENTITY_TYPES='["Person", "Creature", "Organization", "Location", "Event", "Concept", "Method", "Content", "Data", "Artifact", "NaturalObject"]' @@ -163,10 +166,11 @@ MAX_PARALLEL_INSERT=2 ### Num of chunks send to Embedding in single request # EMBEDDING_BATCH_NUM=10 -########################################################### +########################################################################### ### LLM Configuration ### LLM_BINDING type: openai, ollama, lollms, azure_openai, aws_bedrock -########################################################### +### LLM_BINDING_HOST: host only for Ollama, endpoint for other LLM service +########################################################################### ### LLM request timeout setting for all llm (0 means no timeout for Ollma) # LLM_TIMEOUT=180 @@ -221,10 +225,11 @@ OLLAMA_LLM_NUM_CTX=32768 ### Bedrock Specific Parameters # BEDROCK_LLM_TEMPERATURE=1.0 -#################################################################################### +####################################################################################### ### Embedding Configuration (Should not be changed after the first file processed) ### EMBEDDING_BINDING: ollama, openai, azure_openai, jina, lollms, aws_bedrock -#################################################################################### +### EMBEDDING_BINDING_HOST: host only for Ollama, endpoint for other Embedding service +####################################################################################### # EMBEDDING_TIMEOUT=30 EMBEDDING_BINDING=ollama EMBEDDING_MODEL=bge-m3:latest diff --git a/examples/generate_query.py b/examples/generate_query.py new file mode 100644 index 00000000..705b23d3 --- /dev/null +++ b/examples/generate_query.py @@ -0,0 +1,55 @@ +from openai import OpenAI + +# os.environ["OPENAI_API_KEY"] = "" + + +def openai_complete_if_cache( + model="gpt-4o-mini", prompt=None, system_prompt=None, history_messages=[], **kwargs +) -> str: + openai_client = OpenAI() + + messages = [] + if system_prompt: + messages.append({"role": "system", "content": system_prompt}) + messages.extend(history_messages) + messages.append({"role": "user", "content": prompt}) + + response = openai_client.chat.completions.create( + model=model, messages=messages, **kwargs + ) + return response.choices[0].message.content + + +if __name__ == "__main__": + description = "" + prompt = f""" + Given the following description of a dataset: + + {description} + + Please identify 5 potential users who would engage with this dataset. For each user, list 5 tasks they would perform with this dataset. Then, for each (user, task) combination, generate 5 questions that require a high-level understanding of the entire dataset. + + Output the results in the following structure: + - User 1: [user description] + - Task 1: [task description] + - Question 1: + - Question 2: + - Question 3: + - Question 4: + - Question 5: + - Task 2: [task description] + ... + - Task 5: [task description] + - User 2: [user description] + ... + - User 5: [user description] + ... + """ + + result = openai_complete_if_cache(model="gpt-4o-mini", prompt=prompt) + + file_path = "./queries.txt" + with open(file_path, "w") as file: + file.write(result) + + print(f"Queries written to {file_path}") diff --git a/lightrag-api b/lightrag-api deleted file mode 100644 index 89c814fb..00000000 --- a/lightrag-api +++ /dev/null @@ -1,4 +0,0 @@ -#!/bin/bash - -source /home/netman/lightrag-xyj/venv/bin/activate -lightrag-server diff --git a/lightrag.service.example b/lightrag.service.example index 3c96e0b4..e99198d1 100644 --- a/lightrag.service.example +++ b/lightrag.service.example @@ -1,5 +1,5 @@ [Unit] -Description=LightRAG XYJ Ollama Service +Description=LightRAG XYJ Service After=network.target [Service] @@ -8,10 +8,23 @@ User=netman # Memory settings MemoryHigh=8G MemoryMax=12G -WorkingDirectory=/home/netman/lightrag-xyj -ExecStart=/home/netman/lightrag-xyj/lightrag-api + +# Set the LightRAG installation directory (change this to match your installation path) +Environment="LIGHTRAG_HOME=/home/netman/lightrag-xyj" + +# Set Environment to your Python virtual environment +Environment="PATH=${LIGHTRAG_HOME}/.venv/bin" +WorkingDirectory=${LIGHTRAG_HOME} +ExecStart=${LIGHTRAG_HOME}/.venv/bin/lightrag-server +# ExecStart=${LIGHTRAG_HOME}/.venv/bin/lightrag-gunicorn + +# Kill mode require ExecStart must be gunicorn or unvicorn main process +KillMode=process +ExecStop=/bin/kill -s TERM $MAINPID +TimeoutStopSec=60 + Restart=always -RestartSec=10 +RestartSec=30 [Install] WantedBy=multi-user.target diff --git a/lightrag/__init__.py b/lightrag/__init__.py index 1d044256..70a71899 100644 --- a/lightrag/__init__.py +++ b/lightrag/__init__.py @@ -1,5 +1,5 @@ from .lightrag import LightRAG as LightRAG, QueryParam as QueryParam -__version__ = "1.4.9.5" +__version__ = "1.4.9.8" __author__ = "Zirui Guo" __url__ = "https://github.com/HKUDS/LightRAG" diff --git a/lightrag/api/README-zh.md b/lightrag/api/README-zh.md index 692c589d..bd2bbd62 100644 --- a/lightrag/api/README-zh.md +++ b/lightrag/api/README-zh.md @@ -184,24 +184,16 @@ MAX_ASYNC=4 ### 将 Lightrag 安装为 Linux 服务 -从示例文件 `lightrag.service.example` 创建您的服务文件 `lightrag.service`。修改服务文件中的 WorkingDirectory 和 ExecStart： +从示例文件 `lightrag.service.example` 创建您的服务文件 `lightrag.service`。修改服务文件中的服务启动定义： ```text -Description=LightRAG Ollama Service -WorkingDirectory= -ExecStart=/lightrag/api/lightrag-api -``` - -修改您的服务启动脚本：`lightrag-api`。根据需要更改 python 虚拟环境激活命令： - -```shell -#!/bin/bash - -# 您的 python 虚拟环境激活命令 -source /home/netman/lightrag-xyj/venv/bin/activate -# 启动 lightrag api 服务器 -lightrag-server +# Set Enviroment to your Python virtual enviroment +Environment="PATH=/home/netman/lightrag-xyj/venv/bin" +WorkingDirectory=/home/netman/lightrag-xyj +# ExecStart=/home/netman/lightrag-xyj/venv/bin/lightrag-server +ExecStart=/home/netman/lightrag-xyj/venv/bin/lightrag-gunicorn ``` +> ExecStart命令必须是 lightrag-gunicorn 或 lightrag-server 中的一个，不能使用其它脚本包裹它们。因为停止服务必须要求主进程必须是这两个进程。 安装 LightRAG 服务。如果您的系统是 Ubuntu，以下命令将生效： diff --git a/lightrag/api/README.md b/lightrag/api/README.md index aa24576e..339500da 100644 --- a/lightrag/api/README.md +++ b/lightrag/api/README.md @@ -165,7 +165,8 @@ Configuring an independent working directory and a dedicated `.env` configuratio The command-line `workspace` argument and the `WORKSPACE` environment variable in the `.env` file can both be used to specify the workspace name for the current instance, with the command-line argument having higher priority. Here is how workspaces are implemented for different types of storage: - **For local file-based databases, data isolation is achieved through workspace subdirectories:** `JsonKVStorage`, `JsonDocStatusStorage`, `NetworkXStorage`, `NanoVectorDBStorage`, `FaissVectorDBStorage`. -- **For databases that store data in collections, it's done by adding a workspace prefix to the collection name:** `RedisKVStorage`, `RedisDocStatusStorage`, `MilvusVectorDBStorage`, `QdrantVectorDBStorage`, `MongoKVStorage`, `MongoDocStatusStorage`, `MongoVectorDBStorage`, `MongoGraphStorage`, `PGGraphStorage`. +- **For databases that store data in collections, it's done by adding a workspace prefix to the collection name:** `RedisKVStorage`, `RedisDocStatusStorage`, `MilvusVectorDBStorage`, `MongoKVStorage`, `MongoDocStatusStorage`, `MongoVectorDBStorage`, `MongoGraphStorage`, `PGGraphStorage`. +- **For Qdrant vector database, data isolation is achieved through payload-based partitioning (Qdrant's recommended multitenancy approach):** `QdrantVectorDBStorage` uses shared collections with payload filtering for unlimited workspace scalability. - **For relational databases, data isolation is achieved by adding a `workspace` field to the tables for logical data separation:** `PGKVStorage`, `PGVectorStorage`, `PGDocStatusStorage`. - **For graph databases, logical data isolation is achieved through labels:** `Neo4JStorage`, `MemgraphStorage` @@ -188,24 +189,18 @@ MAX_ASYNC=4 ### Install LightRAG as a Linux Service -Create your service file `lightrag.service` from the sample file: `lightrag.service.example`. Modify the `WorkingDirectory` and `ExecStart` in the service file: +Create your service file `lightrag.service` from the sample file: `lightrag.service.example`. Modify the start options the service file: ```text -Description=LightRAG Ollama Service -WorkingDirectory= -ExecStart=/lightrag/api/lightrag-api +# Set Enviroment to your Python virtual enviroment +Environment="PATH=/home/netman/lightrag-xyj/venv/bin" +WorkingDirectory=/home/netman/lightrag-xyj +# ExecStart=/home/netman/lightrag-xyj/venv/bin/lightrag-server +ExecStart=/home/netman/lightrag-xyj/venv/bin/lightrag-gunicorn + ``` -Modify your service startup script: `lightrag-api`. Change your Python virtual environment activation command as needed: - -```shell -#!/bin/bash - -# your python virtual environment activation -source /home/netman/lightrag-xyj/venv/bin/activate -# start lightrag api server -lightrag-server -``` +> The ExecStart command must be either `lightrag-gunicorn` or `lightrag-server`; no wrapper scripts are allowed. This is because service termination requires the main process to be one of these two executables. Install LightRAG service. If your system is Ubuntu, the following commands will work: diff --git a/lightrag/api/__init__.py b/lightrag/api/__init__.py index de364382..cd277b6e 100644 --- a/lightrag/api/__init__.py +++ b/lightrag/api/__init__.py @@ -1 +1 @@ -__api_version__ = "0245" +__api_version__ = "0250" diff --git a/lightrag/api/config.py b/lightrag/api/config.py index de569f47..de4fa00b 100644 --- a/lightrag/api/config.py +++ b/lightrag/api/config.py @@ -342,6 +342,9 @@ def parse_args() -> argparse.Namespace: # Select Document loading tool (DOCLING, DEFAULT) args.document_loading_engine = get_env_value("DOCUMENT_LOADING_ENGINE", "DEFAULT") + # PDF decryption password + args.pdf_decrypt_password = get_env_value("PDF_DECRYPT_PASSWORD", None) + # 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) diff --git a/lightrag/api/gunicorn_config.py b/lightrag/api/gunicorn_config.py index 7b25b5b9..4d2292d0 100644 --- a/lightrag/api/gunicorn_config.py +++ b/lightrag/api/gunicorn_config.py @@ -129,12 +129,10 @@ def on_exit(server): print("=" * 80) print("GUNICORN MASTER PROCESS: Shutting down") print(f"Process ID: {os.getpid()}") - print("=" * 80) - # Release shared resources + print("Finalizing shared storage...") finalize_share_data() - print("=" * 80) print("Gunicorn shutdown complete") print("=" * 80) diff --git a/lightrag/api/lightrag_server.py b/lightrag/api/lightrag_server.py index 19bc549a..fc1e0484 100644 --- a/lightrag/api/lightrag_server.py +++ b/lightrag/api/lightrag_server.py @@ -5,10 +5,13 @@ LightRAG FastAPI Server from fastapi import FastAPI, Depends, HTTPException, Request from fastapi.exceptions import RequestValidationError from fastapi.responses import JSONResponse +from fastapi.openapi.docs import ( + get_swagger_ui_html, + get_swagger_ui_oauth2_redirect_html, +) import os import logging import logging.config -import signal import sys import uvicorn import pipmaster as pm @@ -78,24 +81,6 @@ config.read("config.ini") auth_configured = bool(auth_handler.accounts) -def setup_signal_handlers(): - """Setup signal handlers for graceful shutdown""" - - def signal_handler(sig, frame): - print(f"\n\nReceived signal {sig}, shutting down gracefully...") - print(f"Process ID: {os.getpid()}") - - # Release shared resources - finalize_share_data() - - # Exit with success status - sys.exit(0) - - # Register signal handlers - signal.signal(signal.SIGINT, signal_handler) # Ctrl+C - signal.signal(signal.SIGTERM, signal_handler) # kill command - - class LLMConfigCache: """Smart LLM and Embedding configuration cache class""" @@ -146,7 +131,11 @@ class LLMConfigCache: def check_frontend_build(): - """Check if frontend is built and optionally check if source is up-to-date""" + """Check if frontend is built and optionally check if source is up-to-date + + Returns: + bool: True if frontend is outdated, False if up-to-date or production environment + """ webui_dir = Path(__file__).parent / "webui" index_html = webui_dir / "index.html" @@ -181,7 +170,7 @@ def check_frontend_build(): logger.debug( "Production environment detected, skipping source freshness check" ) - return + return False # Development environment, perform source code timestamp check logger.debug("Development environment detected, checking source freshness") @@ -212,7 +201,7 @@ def check_frontend_build(): source_dir / "bun.lock", source_dir / "vite.config.ts", source_dir / "tsconfig.json", - source_dir / "tailwind.config.js", + source_dir / "tailraid.config.js", source_dir / "index.html", ] @@ -256,17 +245,25 @@ def check_frontend_build(): ASCIIColors.cyan(" cd ..") ASCIIColors.yellow("\nThe server will continue with the current build.") ASCIIColors.yellow("=" * 80 + "\n") + return True # Frontend is outdated else: logger.info("Frontend build is up-to-date") + return False # Frontend is up-to-date except Exception as e: # If check fails, log warning but don't affect startup logger.warning(f"Failed to check frontend source freshness: {e}") + return False # Assume up-to-date on error def create_app(args): - # Check frontend build first - check_frontend_build() + # Check frontend build first and get outdated status + is_frontend_outdated = check_frontend_build() + + # Create unified API version display with warning symbol if frontend is outdated + api_version_display = ( + f"{__api_version__}⚠️" if is_frontend_outdated else __api_version__ + ) # Setup logging logger.setLevel(args.log_level) @@ -341,8 +338,15 @@ def create_app(args): # Clean up database connections await rag.finalize_storages() - # Clean up shared data - finalize_share_data() + if "LIGHTRAG_GUNICORN_MODE" not in os.environ: + # Only perform cleanup in Uvicorn single-process mode + logger.debug("Unvicorn Mode: finalizing shared storage...") + finalize_share_data() + else: + # In Gunicorn mode with preload_app=True, cleanup is handled by on_exit hooks + logger.debug( + "Gunicorn Mode: postpone shared storage finalization to master process" + ) # Initialize FastAPI base_description = ( @@ -358,7 +362,7 @@ def create_app(args): "description": swagger_description, "version": __api_version__, "openapi_url": "/openapi.json", # Explicitly set OpenAPI schema URL - "docs_url": "/docs", # Explicitly set docs URL + "docs_url": None, # Disable default docs, we'll create custom endpoint "redoc_url": "/redoc", # Explicitly set redoc URL "lifespan": lifespan, } @@ -769,6 +773,25 @@ def create_app(args): ollama_api = OllamaAPI(rag, top_k=args.top_k, api_key=api_key) app.include_router(ollama_api.router, prefix="/api") + # Custom Swagger UI endpoint for offline support + @app.get("/docs", include_in_schema=False) + async def custom_swagger_ui_html(): + """Custom Swagger UI HTML with local static files""" + return get_swagger_ui_html( + openapi_url=app.openapi_url, + title=app.title + " - Swagger UI", + oauth2_redirect_url="/docs/oauth2-redirect", + swagger_js_url="/static/swagger-ui/swagger-ui-bundle.js", + swagger_css_url="/static/swagger-ui/swagger-ui.css", + swagger_favicon_url="/static/swagger-ui/favicon-32x32.png", + swagger_ui_parameters=app.swagger_ui_parameters, + ) + + @app.get("/docs/oauth2-redirect", include_in_schema=False) + async def swagger_ui_redirect(): + """OAuth2 redirect for Swagger UI""" + return get_swagger_ui_oauth2_redirect_html() + @app.get("/") async def redirect_to_webui(): """Redirect root path to /webui""" @@ -790,7 +813,7 @@ def create_app(args): "auth_mode": "disabled", "message": "Authentication is disabled. Using guest access.", "core_version": core_version, - "api_version": __api_version__, + "api_version": api_version_display, "webui_title": webui_title, "webui_description": webui_description, } @@ -799,7 +822,7 @@ def create_app(args): "auth_configured": True, "auth_mode": "enabled", "core_version": core_version, - "api_version": __api_version__, + "api_version": api_version_display, "webui_title": webui_title, "webui_description": webui_description, } @@ -817,7 +840,7 @@ def create_app(args): "auth_mode": "disabled", "message": "Authentication is disabled. Using guest access.", "core_version": core_version, - "api_version": __api_version__, + "api_version": api_version_display, "webui_title": webui_title, "webui_description": webui_description, } @@ -834,7 +857,7 @@ def create_app(args): "token_type": "bearer", "auth_mode": "enabled", "core_version": core_version, - "api_version": __api_version__, + "api_version": api_version_display, "webui_title": webui_title, "webui_description": webui_description, } @@ -898,7 +921,7 @@ def create_app(args): "pipeline_busy": pipeline_status.get("busy", False), "keyed_locks": keyed_lock_info, "core_version": core_version, - "api_version": __api_version__, + "api_version": api_version_display, "webui_title": webui_title, "webui_description": webui_description, } @@ -935,6 +958,15 @@ def create_app(args): return response + # Mount Swagger UI static files for offline support + swagger_static_dir = Path(__file__).parent / "static" / "swagger-ui" + if swagger_static_dir.exists(): + app.mount( + "/static/swagger-ui", + StaticFiles(directory=swagger_static_dir), + name="swagger-ui-static", + ) + # Webui mount webui/index.html static_dir = Path(__file__).parent / "webui" static_dir.mkdir(exist_ok=True) @@ -1076,8 +1108,10 @@ def main(): update_uvicorn_mode_config() display_splash_screen(global_args) - # Setup signal handlers for graceful shutdown - setup_signal_handlers() + # Note: Signal handlers are NOT registered here because: + # - Uvicorn has built-in signal handling that properly calls lifespan shutdown + # - Custom signal handlers can interfere with uvicorn's graceful shutdown + # - Cleanup is handled by the lifespan context manager's finally block # Create application instance directly instead of using factory function app = create_app(global_args) diff --git a/lightrag/api/routers/document_routes.py b/lightrag/api/routers/document_routes.py index 54e6477d..3e479a53 100644 --- a/lightrag/api/routers/document_routes.py +++ b/lightrag/api/routers/document_routes.py @@ -1083,11 +1083,74 @@ async def pipeline_enqueue_file( else: if not pm.is_installed("pypdf2"): # type: ignore pm.install("pypdf2") + if not pm.is_installed("pycryptodome"): # type: ignore + pm.install("pycryptodome") from PyPDF2 import PdfReader # type: ignore from io import BytesIO pdf_file = BytesIO(file) reader = PdfReader(pdf_file) + + # Check if PDF is encrypted + if reader.is_encrypted: + pdf_password = global_args.pdf_decrypt_password + if not pdf_password: + # PDF is encrypted but no password provided + error_files = [ + { + "file_path": str(file_path.name), + "error_description": "[File Extraction]PDF is encrypted but no password provided", + "original_error": "Please set PDF_DECRYPT_PASSWORD environment variable to decrypt this PDF file", + "file_size": file_size, + } + ] + await rag.apipeline_enqueue_error_documents( + error_files, track_id + ) + logger.error( + f"[File Extraction]PDF is encrypted but no password provided: {file_path.name}" + ) + return False, track_id + + # Try to decrypt with password + try: + decrypt_result = reader.decrypt(pdf_password) + if decrypt_result == 0: + # Password is incorrect + error_files = [ + { + "file_path": str(file_path.name), + "error_description": "[File Extraction]Failed to decrypt PDF - incorrect password", + "original_error": "The provided PDF_DECRYPT_PASSWORD is incorrect for this file", + "file_size": file_size, + } + ] + await rag.apipeline_enqueue_error_documents( + error_files, track_id + ) + logger.error( + f"[File Extraction]Incorrect PDF password: {file_path.name}" + ) + return False, track_id + except Exception as decrypt_error: + # Decryption process error + error_files = [ + { + "file_path": str(file_path.name), + "error_description": "[File Extraction]PDF decryption failed", + "original_error": f"Error during PDF decryption: {str(decrypt_error)}", + "file_size": file_size, + } + ] + await rag.apipeline_enqueue_error_documents( + error_files, track_id + ) + logger.error( + f"[File Extraction]PDF decryption error for {file_path.name}: {str(decrypt_error)}" + ) + return False, track_id + + # Extract text from PDF (encrypted PDFs are now decrypted, unencrypted PDFs proceed directly) for page in reader.pages: content += page.extract_text() + "\n" except Exception as e: diff --git a/lightrag/api/routers/graph_routes.py b/lightrag/api/routers/graph_routes.py index f59a7c3d..e892ff01 100644 --- a/lightrag/api/routers/graph_routes.py +++ b/lightrag/api/routers/graph_routes.py @@ -17,6 +17,7 @@ class EntityUpdateRequest(BaseModel): entity_name: str updated_data: Dict[str, Any] allow_rename: bool = False + allow_merge: bool = False class RelationUpdateRequest(BaseModel): @@ -221,22 +222,178 @@ def create_graph_routes(rag, api_key: Optional[str] = None): """ Update an entity's properties in the knowledge graph + This endpoint allows updating entity properties, including renaming entities. + When renaming to an existing entity name, the behavior depends on allow_merge: + Args: - request (EntityUpdateRequest): Request containing entity name, updated data, and rename flag + request (EntityUpdateRequest): Request containing: + - entity_name (str): Name of the entity to update + - updated_data (Dict[str, Any]): Dictionary of properties to update + - allow_rename (bool): Whether to allow entity renaming (default: False) + - allow_merge (bool): Whether to merge into existing entity when renaming + causes name conflict (default: False) Returns: - Dict: Updated entity information + Dict with the following structure: + { + "status": "success", + "message": "Entity updated successfully" | "Entity merged successfully into 'target_name'", + "data": { + "entity_name": str, # Final entity name + "description": str, # Entity description + "entity_type": str, # Entity type + "source_id": str, # Source chunk IDs + ... # Other entity properties + }, + "operation_summary": { + "merged": bool, # Whether entity was merged into another + "merge_status": str, # "success" | "failed" | "not_attempted" + "merge_error": str | None, # Error message if merge failed + "operation_status": str, # "success" | "partial_success" | "failure" + "target_entity": str | None, # Target entity name if renaming/merging + "final_entity": str, # Final entity name after operation + "renamed": bool # Whether entity was renamed + } + } + + operation_status values explained: + - "success": All operations completed successfully + * For simple updates: entity properties updated + * For renames: entity renamed successfully + * For merges: non-name updates applied AND merge completed + + - "partial_success": Update succeeded but merge failed + * Non-name property updates were applied successfully + * Merge operation failed (entity not merged) + * Original entity still exists with updated properties + * Use merge_error for failure details + + - "failure": Operation failed completely + * If merge_status == "failed": Merge attempted but both update and merge failed + * If merge_status == "not_attempted": Regular update failed + * No changes were applied to the entity + + merge_status values explained: + - "success": Entity successfully merged into target entity + - "failed": Merge operation was attempted but failed + - "not_attempted": No merge was attempted (normal update/rename) + + Behavior when renaming to an existing entity: + - If allow_merge=False: Raises ValueError with 400 status (default behavior) + - If allow_merge=True: Automatically merges the source entity into the existing target entity, + preserving all relationships and applying non-name updates first + + Example Request (simple update): + POST /graph/entity/edit + { + "entity_name": "Tesla", + "updated_data": {"description": "Updated description"}, + "allow_rename": false, + "allow_merge": false + } + + Example Response (simple update success): + { + "status": "success", + "message": "Entity updated successfully", + "data": { ... }, + "operation_summary": { + "merged": false, + "merge_status": "not_attempted", + "merge_error": null, + "operation_status": "success", + "target_entity": null, + "final_entity": "Tesla", + "renamed": false + } + } + + Example Request (rename with auto-merge): + POST /graph/entity/edit + { + "entity_name": "Elon Msk", + "updated_data": { + "entity_name": "Elon Musk", + "description": "Corrected description" + }, + "allow_rename": true, + "allow_merge": true + } + + Example Response (merge success): + { + "status": "success", + "message": "Entity merged successfully into 'Elon Musk'", + "data": { ... }, + "operation_summary": { + "merged": true, + "merge_status": "success", + "merge_error": null, + "operation_status": "success", + "target_entity": "Elon Musk", + "final_entity": "Elon Musk", + "renamed": true + } + } + + Example Response (partial success - update succeeded but merge failed): + { + "status": "success", + "message": "Entity updated successfully", + "data": { ... }, # Data reflects updated "Elon Msk" entity + "operation_summary": { + "merged": false, + "merge_status": "failed", + "merge_error": "Target entity locked by another operation", + "operation_status": "partial_success", + "target_entity": "Elon Musk", + "final_entity": "Elon Msk", # Original entity still exists + "renamed": true + } + } """ try: result = await rag.aedit_entity( entity_name=request.entity_name, updated_data=request.updated_data, allow_rename=request.allow_rename, + allow_merge=request.allow_merge, + ) + + # Extract operation_summary from result, with fallback for backward compatibility + operation_summary = result.get( + "operation_summary", + { + "merged": False, + "merge_status": "not_attempted", + "merge_error": None, + "operation_status": "success", + "target_entity": None, + "final_entity": request.updated_data.get( + "entity_name", request.entity_name + ), + "renamed": request.updated_data.get( + "entity_name", request.entity_name + ) + != request.entity_name, + }, + ) + + # Separate entity data from operation_summary for clean response + entity_data = dict(result) + entity_data.pop("operation_summary", None) + + # Generate appropriate response message based on merge status + response_message = ( + f"Entity merged successfully into '{operation_summary['final_entity']}'" + if operation_summary.get("merged") + else "Entity updated successfully" ) return { "status": "success", - "message": "Entity updated successfully", - "data": result, + "message": response_message, + "data": entity_data, + "operation_summary": operation_summary, } except ValueError as ve: logger.error( diff --git a/lightrag/api/run_with_gunicorn.py b/lightrag/api/run_with_gunicorn.py index 929db019..f2d4d859 100644 --- a/lightrag/api/run_with_gunicorn.py +++ b/lightrag/api/run_with_gunicorn.py @@ -5,12 +5,11 @@ Start LightRAG server with Gunicorn import os import sys -import signal import pipmaster as pm from lightrag.api.utils_api import display_splash_screen, check_env_file from lightrag.api.config import global_args from lightrag.utils import get_env_value -from lightrag.kg.shared_storage import initialize_share_data, finalize_share_data +from lightrag.kg.shared_storage import initialize_share_data from lightrag.constants import ( DEFAULT_WOKERS, @@ -34,21 +33,10 @@ def check_and_install_dependencies(): print(f"{package} installed successfully") -# Signal handler for graceful shutdown -def signal_handler(sig, frame): - 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_?_.get(s+w,o,i,a):a},HashArrayMapNode.prototype.update=function(s,o,i,a,u,_,x){void 0===i&&(i=hash(a));var L=(0===o?i:i>>>o)&C,B=u===j,$=this.nodes,U=$[L];if(B&&!U)return this;var V=updateNode(U,s,o+w,i,a,u,_,x);if(V===U)return this;var z=this.count;if(U){if(!V&&--z0&&a=0&&s>>o&C;if(a>=this.array.length)return new VNode([],s);var u,_=0===a;if(o>0){var x=this.array[a];if((u=x&&x.removeBefore(s,o-w,i))===x&&_)return this}if(_&&!u)return this;var j=editableVNode(this,s);if(!_)for(var L=0;L>>o&C;if(u>=this.array.length)return this;if(o>0){var _=this.array[u];if((a=_&&_.removeAfter(s,o-w,i))===_&&u===this.array.length-1)return this}var x=editableVNode(this,s);return x.array.splice(u+1),a&&(x.array[u]=a),x};var Xe,Qe,et={};function iterateList(s,o){var i=s._origin,a=s._capacity,u=getTailOffset(a),_=s._tail;return iterateNodeOrLeaf(s._root,s._level,0);function iterateNodeOrLeaf(s,o,i){return 0===o?iterateLeaf(s,i):iterateNode(s,o,i)}function iterateLeaf(s,w){var C=w===u?_&&_.array:s&&s.array,j=w>i?0:i-w,L=a-w;return L>x&&(L=x),function(){if(j===L)return et;var s=o?--L:j++;return C&&C[s]}}function iterateNode(s,u,_){var C,j=s&&s.array,L=_>i?0:i-_>>u,B=1+(a-_>>u);return B>x&&(B=x),function(){for(;;){if(C){var s=C();if(s!==et)return s;C=null}if(L===B)return et;var i=o?--B:L++;C=iterateNodeOrLeaf(j&&j[i],u-w,_+(i<=s.size||o<0)return s.withMutations((function(s){o<0?setListBounds(s,o).set(0,i):setListBounds(s,0,o+1).set(o,i)}));o+=s._origin;var a=s._tail,u=s._root,_=MakeRef(B);return o>=getTailOffset(s._capacity)?a=updateVNode(a,s.__ownerID,0,o,i,_):u=updateVNode(u,s.__ownerID,s._level,o,i,_),_.value?s.__ownerID?(s._root=u,s._tail=a,s.__hash=void 0,s.__altered=!0,s):makeList(s._origin,s._capacity,s._level,u,a):s}function updateVNode(s,o,i,a,u,_){var x,j=a>>>i&C,L=s&&j0){var B=s&&s.array[j],$=updateVNode(B,o,i-w,a,u,_);return $===B?s:((x=editableVNode(s,o)).array[j]=$,x)}return L&&s.array[j]===u?s:(SetRef(_),x=editableVNode(s,o),void 0===u&&j===x.array.length-1?x.array.pop():x.array[j]=u,x)}function editableVNode(s,o){return o&&s&&o===s.ownerID?s:new VNode(s?s.array.slice():[],o)}function listNodeFor(s,o){if(o>=getTailOffset(s._capacity))return s._tail;if(o<1<0;)i=i.array[o>>>a&C],a-=w;return i}}function setListBounds(s,o,i){void 0!==o&&(o|=0),void 0!==i&&(i|=0);var a=s.__ownerID||new OwnerID,u=s._origin,_=s._capacity,x=u+o,j=void 0===i?_:i<0?_+i:u+i;if(x===u&&j===_)return s;if(x>=j)return s.clear();for(var L=s._level,B=s._root,$=0;x+$<0;)B=new VNode(B&&B.array.length?[void 0,B]:[],a),$+=1<<(L+=w);$&&(x+=$,u+=$,j+=$,_+=$);for(var U=getTailOffset(_),V=getTailOffset(j);V>=1<U?new VNode([],a):z;if(z&&V>U&&x<_&&z.array.length){for(var Z=B=editableVNode(B,a),ee=L;ee>w;ee-=w){var ie=U>>>ee&C;Z=Z.array[ie]=editableVNode(Z.array[ie],a)}Z.array[U>>>w&C]=z}if(j<_&&(Y=Y&&Y.removeAfter(a,0,j)),x>=V)x-=V,j-=V,L=w,B=null,Y=Y&&Y.removeBefore(a,0,x);else if(x>u||V>>L&C;if(ae!==V>>>L&C)break;ae&&($+=(1<u&&(B=B.removeBefore(a,L,x-$)),B&&Vu&&(u=x.size),isIterable(w)||(x=x.map((function(s){return fromJS(s)}))),a.push(x)}return u>s.size&&(s=s.setSize(u)),mergeIntoCollectionWith(s,o,a)}function getTailOffset(s){return s>>w<=x&&w.size>=2*_.size?(a=(u=w.filter((function(s,o){return void 0!==s&&C!==o}))).toKeyedSeq().map((function(s){return s[0]})).flip().toMap(),s.__ownerID&&(a.__ownerID=u.__ownerID=s.__ownerID)):(a=_.remove(o),u=C===w.size-1?w.pop():w.set(C,void 0))}else if(L){if(i===w.get(C)[1])return s;a=_,u=w.set(C,[o,i])}else a=_.set(o,w.size),u=w.set(w.size,[o,i]);return s.__ownerID?(s.size=a.size,s._map=a,s._list=u,s.__hash=void 0,s):makeOrderedMap(a,u)}function ToKeyedSequence(s,o){this._iter=s,this._useKeys=o,this.size=s.size}function ToIndexedSequence(s){this._iter=s,this.size=s.size}function ToSetSequence(s){this._iter=s,this.size=s.size}function FromEntriesSequence(s){this._iter=s,this.size=s.size}function flipFactory(s){var o=makeSequence(s);return o._iter=s,o.size=s.size,o.flip=function(){return s},o.reverse=function(){var o=s.reverse.apply(this);return o.flip=function(){return s.reverse()},o},o.has=function(o){return s.includes(o)},o.includes=function(o){return s.has(o)},o.cacheResult=cacheResultThrough,o.__iterateUncached=function(o,i){var a=this;return s.__iterate((function(s,i){return!1!==o(i,s,a)}),i)},o.__iteratorUncached=function(o,i){if(o===V){var a=s.__iterator(o,i);return new Iterator((function(){var s=a.next();if(!s.done){var o=s.value[0];s.value[0]=s.value[1],s.value[1]=o}return s}))}return s.__iterator(o===U?$:U,i)},o}function mapFactory(s,o,i){var a=makeSequence(s);return a.size=s.size,a.has=function(o){return s.has(o)},a.get=function(a,u){var _=s.get(a,j);return _===j?u:o.call(i,_,a,s)},a.__iterateUncached=function(a,u){var _=this;return s.__iterate((function(s,u,w){return!1!==a(o.call(i,s,u,w),u,_)}),u)},a.__iteratorUncached=function(a,u){var _=s.__iterator(V,u);return new Iterator((function(){var u=_.next();if(u.done)return u;var w=u.value,x=w[0];return iteratorValue(a,x,o.call(i,w[1],x,s),u)}))},a}function reverseFactory(s,o){var i=makeSequence(s);return i._iter=s,i.size=s.size,i.reverse=function(){return s},s.flip&&(i.flip=function(){var o=flipFactory(s);return o.reverse=function(){return s.flip()},o}),i.get=function(i,a){return s.get(o?i:-1-i,a)},i.has=function(i){return s.has(o?i:-1-i)},i.includes=function(o){return s.includes(o)},i.cacheResult=cacheResultThrough,i.__iterate=function(o,i){var a=this;return s.__iterate((function(s,i){return o(s,i,a)}),!i)},i.__iterator=function(o,i){return s.__iterator(o,!i)},i}function filterFactory(s,o,i,a){var u=makeSequence(s);return a&&(u.has=function(a){var u=s.get(a,j);return u!==j&&!!o.call(i,u,a,s)},u.get=function(a,u){var _=s.get(a,j);return _!==j&&o.call(i,_,a,s)?_:u}),u.__iterateUncached=function(u,_){var w=this,x=0;return s.__iterate((function(s,_,C){if(o.call(i,s,_,C))return x++,u(s,a?_:x-1,w)}),_),x},u.__iteratorUncached=function(u,_){var w=s.__iterator(V,_),x=0;return new Iterator((function(){for(;;){var _=w.next();if(_.done)return _;var C=_.value,j=C[0],L=C[1];if(o.call(i,L,j,s))return iteratorValue(u,a?j:x++,L,_)}}))},u}function countByFactory(s,o,i){var a=Map().asMutable();return s.__iterate((function(u,_){a.update(o.call(i,u,_,s),0,(function(s){return s+1}))})),a.asImmutable()}function groupByFactory(s,o,i){var a=isKeyed(s),u=(isOrdered(s)?OrderedMap():Map()).asMutable();s.__iterate((function(_,w){u.update(o.call(i,_,w,s),(function(s){return(s=s||[]).push(a?[w,_]:_),s}))}));var _=iterableClass(s);return u.map((function(o){return reify(s,_(o))}))}function sliceFactory(s,o,i,a){var u=s.size;if(void 0!==o&&(o|=0),void 0!==i&&(i===1/0?i=u:i|=0),wholeSlice(o,i,u))return s;var _=resolveBegin(o,u),w=resolveEnd(i,u);if(_!=_||w!=w)return sliceFactory(s.toSeq().cacheResult(),o,i,a);var x,C=w-_;C==C&&(x=C<0?0:C);var j=makeSequence(s);return j.size=0===x?x:s.size&&x||void 0,!a&&isSeq(s)&&x>=0&&(j.get=function(o,i){return(o=wrapIndex(this,o))>=0&&ox)return iteratorDone();var s=u.next();return a||o===U?s:iteratorValue(o,C-1,o===$?void 0:s.value[1],s)}))},j}function takeWhileFactory(s,o,i){var a=makeSequence(s);return a.__iterateUncached=function(a,u){var _=this;if(u)return this.cacheResult().__iterate(a,u);var w=0;return s.__iterate((function(s,u,x){return o.call(i,s,u,x)&&++w&&a(s,u,_)})),w},a.__iteratorUncached=function(a,u){var _=this;if(u)return this.cacheResult().__iterator(a,u);var w=s.__iterator(V,u),x=!0;return new Iterator((function(){if(!x)return iteratorDone();var s=w.next();if(s.done)return s;var u=s.value,C=u[0],j=u[1];return o.call(i,j,C,_)?a===V?s:iteratorValue(a,C,j,s):(x=!1,iteratorDone())}))},a}function skipWhileFactory(s,o,i,a){var u=makeSequence(s);return u.__iterateUncached=function(u,_){var w=this;if(_)return this.cacheResult().__iterate(u,_);var x=!0,C=0;return s.__iterate((function(s,_,j){if(!x||!(x=o.call(i,s,_,j)))return C++,u(s,a?_:C-1,w)})),C},u.__iteratorUncached=function(u,_){var w=this;if(_)return this.cacheResult().__iterator(u,_);var x=s.__iterator(V,_),C=!0,j=0;return new Iterator((function(){var s,_,L;do{if((s=x.next()).done)return a||u===U?s:iteratorValue(u,j++,u===$?void 0:s.value[1],s);var B=s.value;_=B[0],L=B[1],C&&(C=o.call(i,L,_,w))}while(C);return u===V?s:iteratorValue(u,_,L,s)}))},u}function concatFactory(s,o){var i=isKeyed(s),a=[s].concat(o).map((function(s){return isIterable(s)?i&&(s=KeyedIterable(s)):s=i?keyedSeqFromValue(s):indexedSeqFromValue(Array.isArray(s)?s:[s]),s})).filter((function(s){return 0!==s.size}));if(0===a.length)return s;if(1===a.length){var u=a[0];if(u===s||i&&isKeyed(u)||isIndexed(s)&&isIndexed(u))return u}var _=new ArraySeq(a);return i?_=_.toKeyedSeq():isIndexed(s)||(_=_.toSetSeq()),(_=_.flatten(!0)).size=a.reduce((function(s,o){if(void 0!==s){var i=o.size;if(void 0!==i)return s+i}}),0),_}function flattenFactory(s,o,i){var a=makeSequence(s);return a.__iterateUncached=function(a,u){var _=0,w=!1;function flatDeep(s,x){var C=this;s.__iterate((function(s,u){return(!o||x0}function zipWithFactory(s,o,i){var a=makeSequence(s);return a.size=new ArraySeq(i).map((function(s){return s.size})).min(),a.__iterate=function(s,o){for(var i,a=this.__iterator(U,o),u=0;!(i=a.next()).done&&!1!==s(i.value,u++,this););return u},a.__iteratorUncached=function(s,a){var u=i.map((function(s){return s=Iterable(s),getIterator(a?s.reverse():s)})),_=0,w=!1;return new Iterator((function(){var i;return w||(i=u.map((function(s){return s.next()})),w=i.some((function(s){return s.done}))),w?iteratorDone():iteratorValue(s,_++,o.apply(null,i.map((function(s){return s.value}))))}))},a}function reify(s,o){return isSeq(s)?o:s.constructor(o)}function validateEntry(s){if(s!==Object(s))throw new TypeError("Expected [K, V] tuple: "+s)}function resolveSize(s){return assertNotInfinite(s.size),ensureSize(s)}function iterableClass(s){return isKeyed(s)?KeyedIterable:isIndexed(s)?IndexedIterable:SetIterable}function makeSequence(s){return Object.create((isKeyed(s)?KeyedSeq:isIndexed(s)?IndexedSeq:SetSeq).prototype)}function cacheResultThrough(){return this._iter.cacheResult?(this._iter.cacheResult(),this.size=this._iter.size,this):Seq.prototype.cacheResult.call(this)}function defaultComparator(s,o){return s>o?1:s=0;i--)o={value:arguments[i],next:o};return this.__ownerID?(this.size=s,this._head=o,this.__hash=void 0,this.__altered=!0,this):makeStack(s,o)},Stack.prototype.pushAll=function(s){if(0===(s=IndexedIterable(s)).size)return this;assertNotInfinite(s.size);var o=this.size,i=this._head;return s.reverse().forEach((function(s){o++,i={value:s,next:i}})),this.__ownerID?(this.size=o,this._head=i,this.__hash=void 0,this.__altered=!0,this):makeStack(o,i)},Stack.prototype.pop=function(){return this.slice(1)},Stack.prototype.unshift=function(){return this.push.apply(this,arguments)},Stack.prototype.unshiftAll=function(s){return this.pushAll(s)},Stack.prototype.shift=function(){return this.pop.apply(this,arguments)},Stack.prototype.clear=function(){return 0===this.size?this:this.__ownerID?(this.size=0,this._head=void 0,this.__hash=void 0,this.__altered=!0,this):emptyStack()},Stack.prototype.slice=function(s,o){if(wholeSlice(s,o,this.size))return this;var i=resolveBegin(s,this.size);if(resolveEnd(o,this.size)!==this.size)return IndexedCollection.prototype.slice.call(this,s,o);for(var a=this.size-i,u=this._head;i--;)u=u.next;return this.__ownerID?(this.size=a,this._head=u,this.__hash=void 0,this.__altered=!0,this):makeStack(a,u)},Stack.prototype.__ensureOwner=function(s){return s===this.__ownerID?this:s?makeStack(this.size,this._head,s,this.__hash):(this.__ownerID=s,this.__altered=!1,this)},Stack.prototype.__iterate=function(s,o){if(o)return this.reverse().__iterate(s);for(var i=0,a=this._head;a&&!1!==s(a.value,i++,this);)a=a.next;return i},Stack.prototype.__iterator=function(s,o){if(o)return this.reverse().__iterator(s);var i=0,a=this._head;return new Iterator((function(){if(a){var o=a.value;return a=a.next,iteratorValue(s,i++,o)}return iteratorDone()}))},Stack.isStack=isStack;var at,ct="@@__IMMUTABLE_STACK__@@",lt=Stack.prototype;function makeStack(s,o,i,a){var u=Object.create(lt);return u.size=s,u._head=o,u.__ownerID=i,u.__hash=a,u.__altered=!1,u}function emptyStack(){return at||(at=makeStack(0))}function mixin(s,o){var keyCopier=function(i){s.prototype[i]=o[i]};return Object.keys(o).forEach(keyCopier),Object.getOwnPropertySymbols&&Object.getOwnPropertySymbols(o).forEach(keyCopier),s}lt[ct]=!0,lt.withMutations=$e.withMutations,lt.asMutable=$e.asMutable,lt.asImmutable=$e.asImmutable,lt.wasAltered=$e.wasAltered,Iterable.Iterator=Iterator,mixin(Iterable,{toArray:function(){assertNotInfinite(this.size);var s=new Array(this.size||0);return this.valueSeq().__iterate((function(o,i){s[i]=o})),s},toIndexedSeq:function(){return new ToIndexedSequence(this)},toJS:function(){return this.toSeq().map((function(s){return s&&"function"==typeof s.toJS?s.toJS():s})).__toJS()},toJSON:function(){return this.toSeq().map((function(s){return s&&"function"==typeof s.toJSON?s.toJSON():s})).__toJS()},toKeyedSeq:function(){return new ToKeyedSequence(this,!0)},toMap:function(){return Map(this.toKeyedSeq())},toObject:function(){assertNotInfinite(this.size);var s={};return this.__iterate((function(o,i){s[i]=o})),s},toOrderedMap:function(){return OrderedMap(this.toKeyedSeq())},toOrderedSet:function(){return OrderedSet(isKeyed(this)?this.valueSeq():this)},toSet:function(){return Set(isKeyed(this)?this.valueSeq():this)},toSetSeq:function(){return new ToSetSequence(this)},toSeq:function(){return isIndexed(this)?this.toIndexedSeq():isKeyed(this)?this.toKeyedSeq():this.toSetSeq()},toStack:function(){return Stack(isKeyed(this)?this.valueSeq():this)},toList:function(){return List(isKeyed(this)?this.valueSeq():this)},toString:function(){return"[Iterable]"},__toString:function(s,o){return 0===this.size?s+o:s+" "+this.toSeq().map(this.__toStringMapper).join(", ")+" "+o},concat:function(){return reify(this,concatFactory(this,s.call(arguments,0)))},includes:function(s){return this.some((function(o){return is(o,s)}))},entries:function(){return this.__iterator(V)},every:function(s,o){assertNotInfinite(this.size);var i=!0;return this.__iterate((function(a,u,_){if(!s.call(o,a,u,_))return i=!1,!1})),i},filter:function(s,o){return reify(this,filterFactory(this,s,o,!0))},find:function(s,o,i){var a=this.findEntry(s,o);return a?a[1]:i},forEach:function(s,o){return assertNotInfinite(this.size),this.__iterate(o?s.bind(o):s)},join:function(s){assertNotInfinite(this.size),s=void 0!==s?""+s:",";var o="",i=!0;return 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