Merge 4d2d781246 into 1f8751225d
This commit is contained in:
Chen Zhidong
GitHub
commit
b1a948e5cf
7 changed files with 410 additions and 301 deletions
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@ -2,67 +2,60 @@
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LightRAG FastAPI Server
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"""
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from fastapi import FastAPI, Depends, HTTPException, Request
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import configparser
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import logging
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import logging.config
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import os
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import sys
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from contextlib import asynccontextmanager
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from pathlib import Path
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import pipmaster as pm
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import uvicorn
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from ascii_colors import ASCIIColors
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from dotenv import load_dotenv
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from fastapi import Depends, FastAPI, HTTPException, Request
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from fastapi.exceptions import RequestValidationError
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from fastapi.responses import JSONResponse
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.openapi.docs import (
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get_swagger_ui_html,
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get_swagger_ui_oauth2_redirect_html,
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)
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import os
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import logging
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import logging.config
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import sys
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import uvicorn
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import pipmaster as pm
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from fastapi.responses import JSONResponse, RedirectResponse
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from fastapi.security import OAuth2PasswordRequestForm
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from fastapi.staticfiles import StaticFiles
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from fastapi.responses import RedirectResponse
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from pathlib import Path
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import configparser
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from ascii_colors import ASCIIColors
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from fastapi.middleware.cors import CORSMiddleware
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from contextlib import asynccontextmanager
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from dotenv import load_dotenv
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from lightrag.api.utils_api import (
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get_combined_auth_dependency,
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display_splash_screen,
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check_env_file,
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)
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from .config import (
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global_args,
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update_uvicorn_mode_config,
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get_default_host,
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)
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from lightrag.utils import get_env_value
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from lightrag import LightRAG, __version__ as core_version
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from lightrag import LightRAG
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from lightrag import __version__ as core_version
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from lightrag.api import __api_version__
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from lightrag.types import GPTKeywordExtractionFormat
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from lightrag.utils import EmbeddingFunc
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from lightrag.constants import (
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DEFAULT_LOG_MAX_BYTES,
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DEFAULT_LOG_BACKUP_COUNT,
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DEFAULT_LOG_FILENAME,
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DEFAULT_LLM_TIMEOUT,
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DEFAULT_EMBEDDING_TIMEOUT,
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)
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from lightrag.api.routers.document_routes import (
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DocumentManager,
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create_document_routes,
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)
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from lightrag.api.routers.query_routes import create_query_routes
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from lightrag.api.auth import auth_handler
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from lightrag.api.routers.document_routes import DocumentManager, create_document_routes
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from lightrag.api.routers.graph_routes import create_graph_routes
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from lightrag.api.routers.ollama_api import OllamaAPI
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from lightrag.utils import logger, set_verbose_debug
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from lightrag.api.routers.query_routes import create_query_routes
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from lightrag.api.utils_api import (
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check_env_file,
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display_splash_screen,
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get_combined_auth_dependency,
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)
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from lightrag.constants import (
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DEFAULT_EMBEDDING_TIMEOUT,
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DEFAULT_LLM_TIMEOUT,
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DEFAULT_LOG_BACKUP_COUNT,
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DEFAULT_LOG_FILENAME,
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DEFAULT_LOG_MAX_BYTES,
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)
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from lightrag.kg.shared_storage import (
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get_namespace_data,
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get_default_workspace,
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# set_default_workspace,
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cleanup_keyed_lock,
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finalize_share_data,
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get_default_workspace,
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get_namespace_data,
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set_default_workspace,
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)
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from fastapi.security import OAuth2PasswordRequestForm
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from lightrag.api.auth import auth_handler
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from lightrag.types import GPTKeywordExtractionFormat
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from lightrag.utils import EmbeddingFunc, get_env_value, logger, set_verbose_debug
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from .config import get_default_host, global_args, update_uvicorn_mode_config
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# use the .env that is inside the current folder
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# allows to use different .env file for each lightrag instance
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@ -343,8 +336,85 @@ def create_app(args):
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# Check if API key is provided either through env var or args
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api_key = os.getenv("LIGHTRAG_API_KEY") or args.key
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# Initialize document manager with workspace support for data isolation
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doc_manager = DocumentManager(args.input_dir, workspace=args.workspace)
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doc_manager_cache = {}
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def create_doc_manager(request: Request | None) -> DocumentManager:
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"""Create or retrieve DocumentManager for the current workspace"""
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workspace = args.workspace
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if request is not None:
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workspace = get_workspace_from_request(request, args.workspace)
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logger.debug(f"Using DocumentManager for workspace: '{workspace}'")
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if workspace in doc_manager_cache:
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return doc_manager_cache[workspace]
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doc_manager = DocumentManager(args.input_dir, workspace=workspace)
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doc_manager_cache[workspace] = doc_manager
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return doc_manager_cache[workspace]
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rag_cache = {}
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async def create_rag(request: Request | None) -> LightRAG:
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"""Create or retrieve LightRAG instance for the current workspace"""
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workspace = args.workspace
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if request is not None:
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workspace = get_workspace_from_request(request, args.workspace)
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logger.debug(f"Using LightRAG instance for workspace: '{workspace}'")
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if workspace in rag_cache:
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return rag_cache[workspace]
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# Create ollama_server_infos from command line arguments
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from lightrag.api.config import OllamaServerInfos
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ollama_server_infos = OllamaServerInfos(name=args.simulated_model_name, tag=args.simulated_model_tag)
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# Initialize RAG with unified configuration
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try:
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rag = LightRAG(
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working_dir=args.working_dir,
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workspace=workspace,
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llm_model_func=create_llm_model_func(args.llm_binding),
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llm_model_name=args.llm_model,
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llm_model_max_async=args.max_async,
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summary_max_tokens=args.summary_max_tokens,
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summary_context_size=args.summary_context_size,
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chunk_token_size=int(args.chunk_size),
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chunk_overlap_token_size=int(args.chunk_overlap_size),
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llm_model_kwargs=create_llm_model_kwargs(args.llm_binding, args, llm_timeout),
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embedding_func=embedding_func,
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default_llm_timeout=llm_timeout,
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default_embedding_timeout=embedding_timeout,
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kv_storage=args.kv_storage,
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graph_storage=args.graph_storage,
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vector_storage=args.vector_storage,
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doc_status_storage=args.doc_status_storage,
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vector_db_storage_cls_kwargs={"cosine_better_than_threshold": args.cosine_threshold},
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enable_llm_cache_for_entity_extract=args.enable_llm_cache_for_extract,
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enable_llm_cache=args.enable_llm_cache,
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rerank_model_func=rerank_model_func,
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max_parallel_insert=args.max_parallel_insert,
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max_graph_nodes=args.max_graph_nodes,
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addon_params={
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"language": args.summary_language,
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"entity_types": args.entity_types,
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},
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ollama_server_infos=ollama_server_infos,
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)
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# Initialize database connections
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# Note: initialize_storages() now auto-initializes pipeline_status for rag.workspace
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await rag.initialize_storages()
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# Data migration regardless of storage implementation
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await rag.check_and_migrate_data()
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rag_cache[workspace] = rag
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return rag
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except Exception as e:
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logger.error(f"Failed to initialize LightRAG: {e}")
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raise
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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@ -353,12 +423,8 @@ def create_app(args):
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app.state.background_tasks = set()
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try:
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# Initialize database connections
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# Note: initialize_storages() now auto-initializes pipeline_status for rag.workspace
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await rag.initialize_storages()
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# Data migration regardless of storage implementation
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await rag.check_and_migrate_data()
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create_doc_manager(None) # Pre-create default DocumentManager
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await create_rag(None) # Pre-create default LightRAG
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ASCIIColors.green("\nServer is ready to accept connections! 🚀\n")
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@ -366,7 +432,8 @@ def create_app(args):
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finally:
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# Clean up database connections
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await rag.finalize_storages()
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for rag in rag_cache.values():
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await rag.finalize_storages()
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if "LIGHTRAG_GUNICORN_MODE" not in os.environ:
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# Only perform cleanup in Uvicorn single-process mode
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@ -404,6 +471,7 @@ def create_app(args):
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"tryItOutEnabled": True,
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}
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set_default_workspace(args.workspace)
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app = FastAPI(**app_kwargs)
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# Add custom validation error handler for /query/data endpoint
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@ -456,7 +524,7 @@ def create_app(args):
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# Create combined auth dependency for all endpoints
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combined_auth = get_combined_auth_dependency(api_key)
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def get_workspace_from_request(request: Request) -> str | None:
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def get_workspace_from_request(request: Request, default: str) -> str:
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"""
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Extract workspace from HTTP request header or use default.
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@ -474,7 +542,7 @@ def create_app(args):
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workspace = request.headers.get("LIGHTRAG-WORKSPACE", "").strip()
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if not workspace:
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workspace = None
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workspace = default
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return workspace
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@ -1022,66 +1090,19 @@ def create_app(args):
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else:
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logger.info("Reranking is disabled")
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# Create ollama_server_infos from command line arguments
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from lightrag.api.config import OllamaServerInfos
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ollama_server_infos = OllamaServerInfos(
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name=args.simulated_model_name, tag=args.simulated_model_tag
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)
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# Initialize RAG with unified configuration
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try:
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rag = LightRAG(
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working_dir=args.working_dir,
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workspace=args.workspace,
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llm_model_func=create_llm_model_func(args.llm_binding),
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llm_model_name=args.llm_model,
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llm_model_max_async=args.max_async,
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summary_max_tokens=args.summary_max_tokens,
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summary_context_size=args.summary_context_size,
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chunk_token_size=int(args.chunk_size),
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chunk_overlap_token_size=int(args.chunk_overlap_size),
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llm_model_kwargs=create_llm_model_kwargs(
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args.llm_binding, args, llm_timeout
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),
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embedding_func=embedding_func,
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default_llm_timeout=llm_timeout,
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default_embedding_timeout=embedding_timeout,
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kv_storage=args.kv_storage,
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graph_storage=args.graph_storage,
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vector_storage=args.vector_storage,
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doc_status_storage=args.doc_status_storage,
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vector_db_storage_cls_kwargs={
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"cosine_better_than_threshold": args.cosine_threshold
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},
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enable_llm_cache_for_entity_extract=args.enable_llm_cache_for_extract,
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enable_llm_cache=args.enable_llm_cache,
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rerank_model_func=rerank_model_func,
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max_parallel_insert=args.max_parallel_insert,
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max_graph_nodes=args.max_graph_nodes,
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addon_params={
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"language": args.summary_language,
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"entity_types": args.entity_types,
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},
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ollama_server_infos=ollama_server_infos,
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)
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except Exception as e:
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logger.error(f"Failed to initialize LightRAG: {e}")
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raise
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# Add routes
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app.include_router(
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create_document_routes(
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rag,
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doc_manager,
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create_rag,
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create_doc_manager,
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api_key,
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)
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)
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app.include_router(create_query_routes(rag, api_key, args.top_k))
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app.include_router(create_graph_routes(rag, api_key))
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app.include_router(create_query_routes(create_rag, api_key, args.top_k))
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app.include_router(create_graph_routes(create_rag, api_key))
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# Add Ollama API routes
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ollama_api = OllamaAPI(rag, top_k=args.top_k, api_key=api_key)
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ollama_api = OllamaAPI(create_rag, top_k=args.top_k, api_key=api_key)
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app.include_router(ollama_api.router, prefix="/api")
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# Custom Swagger UI endpoint for offline support
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@ -1212,10 +1233,7 @@ def create_app(args):
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async def get_status(request: Request):
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"""Get current system status including WebUI availability"""
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try:
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workspace = get_workspace_from_request(request)
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default_workspace = get_default_workspace()
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if workspace is None:
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workspace = default_workspace
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workspace = get_workspace_from_request(request, get_default_workspace())
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pipeline_status = await get_namespace_data(
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"pipeline_status", workspace=workspace
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)
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@ -1250,7 +1268,7 @@ def create_app(args):
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"vector_storage": args.vector_storage,
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"enable_llm_cache_for_extract": args.enable_llm_cache_for_extract,
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"enable_llm_cache": args.enable_llm_cache,
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"workspace": default_workspace,
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"workspace": workspace,
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"max_graph_nodes": args.max_graph_nodes,
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# Rerank configuration
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"enable_rerank": rerank_model_func is not None,
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|
|
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@ -3,29 +3,31 @@ This module contains all document-related routes for the LightRAG API.
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"""
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import asyncio
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from functools import lru_cache
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from lightrag.utils import logger, get_pinyin_sort_key
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import aiofiles
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import shutil
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import traceback
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Dict, List, Optional, Any, Literal
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from functools import lru_cache
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from io import BytesIO
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from pathlib import Path
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from typing import Any, Dict, List, Literal, Optional
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|
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import aiofiles
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from fastapi import (
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APIRouter,
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BackgroundTasks,
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Depends,
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File,
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HTTPException,
|
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Request,
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UploadFile,
|
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)
|
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from pydantic import BaseModel, Field, field_validator
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|
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from lightrag import LightRAG
|
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from lightrag.base import DeletionResult, DocProcessingStatus, DocStatus
|
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from lightrag.utils import generate_track_id
|
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from lightrag.api.utils_api import get_combined_auth_dependency
|
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from lightrag.base import DeletionResult, DocProcessingStatus, DocStatus
|
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from lightrag.utils import generate_track_id, get_pinyin_sort_key, logger
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|
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from ..config import global_args
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||||
|
|
@ -2029,16 +2031,12 @@ async def background_delete_documents(
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logger.error(f"Error processing pending documents after deletion: {e}")
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def create_document_routes(
|
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rag: LightRAG, doc_manager: DocumentManager, api_key: Optional[str] = None
|
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):
|
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def create_document_routes(create_rag, create_doc_manager, api_key: Optional[str] = None):
|
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# Create combined auth dependency for document routes
|
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combined_auth = get_combined_auth_dependency(api_key)
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|
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@router.post(
|
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"/scan", response_model=ScanResponse, dependencies=[Depends(combined_auth)]
|
||||
)
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async def scan_for_new_documents(background_tasks: BackgroundTasks):
|
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@router.post("/scan", response_model=ScanResponse, dependencies=[Depends(combined_auth)])
|
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async def scan_for_new_documents(raw_request: Request, background_tasks: BackgroundTasks):
|
||||
"""
|
||||
Trigger the scanning process for new documents.
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||||
|
||||
|
|
@ -2049,6 +2047,9 @@ def create_document_routes(
|
|||
Returns:
|
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ScanResponse: A response object containing the scanning status and track_id
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"""
|
||||
rag = await create_rag(raw_request)
|
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doc_manager = create_doc_manager(raw_request)
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||||
|
||||
# Generate track_id with "scan" prefix for scanning operation
|
||||
track_id = generate_track_id("scan")
|
||||
|
||||
|
|
@ -2060,11 +2061,9 @@ def create_document_routes(
|
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track_id=track_id,
|
||||
)
|
||||
|
||||
@router.post(
|
||||
"/upload", response_model=InsertResponse, dependencies=[Depends(combined_auth)]
|
||||
)
|
||||
@router.post("/upload", response_model=InsertResponse, dependencies=[Depends(combined_auth)])
|
||||
async def upload_to_input_dir(
|
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background_tasks: BackgroundTasks, file: UploadFile = File(...)
|
||||
raw_request: Request, background_tasks: BackgroundTasks, file: UploadFile = File(...)
|
||||
):
|
||||
"""
|
||||
Upload a file to the input directory and index it.
|
||||
|
|
@ -2085,6 +2084,9 @@ def create_document_routes(
|
|||
HTTPException: If the file type is not supported (400) or other errors occur (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
doc_manager = create_doc_manager(raw_request)
|
||||
|
||||
# Sanitize filename to prevent Path Traversal attacks
|
||||
safe_filename = sanitize_filename(file.filename, doc_manager.input_dir)
|
||||
|
||||
|
|
@ -2133,12 +2135,8 @@ def create_document_routes(
|
|||
logger.error(traceback.format_exc())
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@router.post(
|
||||
"/text", response_model=InsertResponse, dependencies=[Depends(combined_auth)]
|
||||
)
|
||||
async def insert_text(
|
||||
request: InsertTextRequest, background_tasks: BackgroundTasks
|
||||
):
|
||||
@router.post("/text", response_model=InsertResponse, dependencies=[Depends(combined_auth)])
|
||||
async def insert_text(raw_request: Request, request: InsertTextRequest, background_tasks: BackgroundTasks):
|
||||
"""
|
||||
Insert text into the RAG system.
|
||||
|
||||
|
|
@ -2156,6 +2154,8 @@ def create_document_routes(
|
|||
HTTPException: If an error occurs during text processing (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
# Check if file_source already exists in doc_status storage
|
||||
if (
|
||||
request.file_source
|
||||
|
|
@ -2200,9 +2200,7 @@ def create_document_routes(
|
|||
response_model=InsertResponse,
|
||||
dependencies=[Depends(combined_auth)],
|
||||
)
|
||||
async def insert_texts(
|
||||
request: InsertTextsRequest, background_tasks: BackgroundTasks
|
||||
):
|
||||
async def insert_texts(raw_request: Request, request: InsertTextsRequest, background_tasks: BackgroundTasks):
|
||||
"""
|
||||
Insert multiple texts into the RAG system.
|
||||
|
||||
|
|
@ -2220,6 +2218,8 @@ def create_document_routes(
|
|||
HTTPException: If an error occurs during text processing (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
# Check if any file_sources already exist in doc_status storage
|
||||
if request.file_sources:
|
||||
for file_source in request.file_sources:
|
||||
|
|
@ -2261,10 +2261,8 @@ def create_document_routes(
|
|||
logger.error(traceback.format_exc())
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@router.delete(
|
||||
"", response_model=ClearDocumentsResponse, dependencies=[Depends(combined_auth)]
|
||||
)
|
||||
async def clear_documents():
|
||||
@router.delete("", response_model=ClearDocumentsResponse, dependencies=[Depends(combined_auth)])
|
||||
async def clear_documents(raw_request: Request):
|
||||
"""
|
||||
Clear all documents from the RAG system.
|
||||
|
||||
|
|
@ -2285,46 +2283,49 @@ def create_document_routes(
|
|||
HTTPException: Raised when a serious error occurs during the clearing process,
|
||||
with status code 500 and error details in the detail field.
|
||||
"""
|
||||
from lightrag.kg.shared_storage import (
|
||||
get_namespace_data,
|
||||
get_namespace_lock,
|
||||
)
|
||||
|
||||
# Get pipeline status and lock
|
||||
pipeline_status = await get_namespace_data(
|
||||
"pipeline_status", workspace=rag.workspace
|
||||
)
|
||||
pipeline_status_lock = get_namespace_lock(
|
||||
"pipeline_status", workspace=rag.workspace
|
||||
)
|
||||
|
||||
# Check and set status with lock
|
||||
async with pipeline_status_lock:
|
||||
if pipeline_status.get("busy", False):
|
||||
return ClearDocumentsResponse(
|
||||
status="busy",
|
||||
message="Cannot clear documents while pipeline is busy",
|
||||
)
|
||||
# Set busy to true
|
||||
pipeline_status.update(
|
||||
{
|
||||
"busy": True,
|
||||
"job_name": "Clearing Documents",
|
||||
"job_start": datetime.now().isoformat(),
|
||||
"docs": 0,
|
||||
"batchs": 0,
|
||||
"cur_batch": 0,
|
||||
"request_pending": False, # Clear any previous request
|
||||
"latest_message": "Starting document clearing process",
|
||||
}
|
||||
)
|
||||
# Cleaning history_messages without breaking it as a shared list object
|
||||
del pipeline_status["history_messages"][:]
|
||||
pipeline_status["history_messages"].append(
|
||||
"Starting document clearing process"
|
||||
)
|
||||
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
doc_manager = create_doc_manager(raw_request)
|
||||
|
||||
from lightrag.kg.shared_storage import (
|
||||
get_namespace_data,
|
||||
get_namespace_lock,
|
||||
)
|
||||
|
||||
# Get pipeline status and lock
|
||||
pipeline_status = await get_namespace_data(
|
||||
"pipeline_status", workspace=rag.workspace
|
||||
)
|
||||
pipeline_status_lock = get_namespace_lock(
|
||||
"pipeline_status", workspace=rag.workspace
|
||||
)
|
||||
|
||||
# Check and set status with lock
|
||||
async with pipeline_status_lock:
|
||||
if pipeline_status.get("busy", False):
|
||||
return ClearDocumentsResponse(
|
||||
status="busy",
|
||||
message="Cannot clear documents while pipeline is busy",
|
||||
)
|
||||
# Set busy to true
|
||||
pipeline_status.update(
|
||||
{
|
||||
"busy": True,
|
||||
"job_name": "Clearing Documents",
|
||||
"job_start": datetime.now().isoformat(),
|
||||
"docs": 0,
|
||||
"batchs": 0,
|
||||
"cur_batch": 0,
|
||||
"request_pending": False, # Clear any previous request
|
||||
"latest_message": "Starting document clearing process",
|
||||
}
|
||||
)
|
||||
# Cleaning history_messages without breaking it as a shared list object
|
||||
del pipeline_status["history_messages"][:]
|
||||
pipeline_status["history_messages"].append(
|
||||
"Starting document clearing process"
|
||||
)
|
||||
|
||||
# Use drop method to clear all data
|
||||
drop_tasks = []
|
||||
storages = [
|
||||
|
|
@ -2460,7 +2461,7 @@ def create_document_routes(
|
|||
dependencies=[Depends(combined_auth)],
|
||||
response_model=PipelineStatusResponse,
|
||||
)
|
||||
async def get_pipeline_status() -> PipelineStatusResponse:
|
||||
async def get_pipeline_status(raw_request: Request) -> PipelineStatusResponse:
|
||||
"""
|
||||
Get the current status of the document indexing pipeline.
|
||||
|
||||
|
|
@ -2485,10 +2486,12 @@ def create_document_routes(
|
|||
HTTPException: If an error occurs while retrieving pipeline status (500)
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
from lightrag.kg.shared_storage import (
|
||||
get_all_update_flags_status,
|
||||
get_namespace_data,
|
||||
get_namespace_lock,
|
||||
get_all_update_flags_status,
|
||||
)
|
||||
|
||||
pipeline_status = await get_namespace_data(
|
||||
|
|
@ -2556,10 +2559,8 @@ def create_document_routes(
|
|||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
# TODO: Deprecated, use /documents/paginated instead
|
||||
@router.get(
|
||||
"", response_model=DocsStatusesResponse, dependencies=[Depends(combined_auth)]
|
||||
)
|
||||
async def documents() -> DocsStatusesResponse:
|
||||
@router.get("", response_model=DocsStatusesResponse, dependencies=[Depends(combined_auth)])
|
||||
async def documents(raw_request: Request) -> DocsStatusesResponse:
|
||||
"""
|
||||
Get the status of all documents in the system. This endpoint is deprecated; use /documents/paginated instead.
|
||||
To prevent excessive resource consumption, a maximum of 1,000 records is returned.
|
||||
|
|
@ -2578,6 +2579,8 @@ def create_document_routes(
|
|||
HTTPException: If an error occurs while retrieving document statuses (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
statuses = (
|
||||
DocStatus.PENDING,
|
||||
DocStatus.PROCESSING,
|
||||
|
|
@ -2673,6 +2676,7 @@ def create_document_routes(
|
|||
summary="Delete a document and all its associated data by its ID.",
|
||||
)
|
||||
async def delete_document(
|
||||
raw_request: Request,
|
||||
delete_request: DeleteDocRequest,
|
||||
background_tasks: BackgroundTasks,
|
||||
) -> DeleteDocByIdResponse:
|
||||
|
|
@ -2699,9 +2703,12 @@ def create_document_routes(
|
|||
HTTPException:
|
||||
- 500: If an unexpected internal error occurs during initialization.
|
||||
"""
|
||||
doc_ids = delete_request.doc_ids
|
||||
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
doc_manager = create_doc_manager(raw_request)
|
||||
|
||||
doc_ids = delete_request.doc_ids
|
||||
|
||||
from lightrag.kg.shared_storage import (
|
||||
get_namespace_data,
|
||||
get_namespace_lock,
|
||||
|
|
@ -2750,7 +2757,7 @@ def create_document_routes(
|
|||
response_model=ClearCacheResponse,
|
||||
dependencies=[Depends(combined_auth)],
|
||||
)
|
||||
async def clear_cache(request: ClearCacheRequest):
|
||||
async def clear_cache(raw_request: Request, request: ClearCacheRequest):
|
||||
"""
|
||||
Clear all cache data from the LLM response cache storage.
|
||||
|
||||
|
|
@ -2767,6 +2774,7 @@ def create_document_routes(
|
|||
HTTPException: If an error occurs during cache clearing (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
# Call the aclear_cache method (no modes parameter)
|
||||
await rag.aclear_cache()
|
||||
|
||||
|
|
@ -2784,7 +2792,7 @@ def create_document_routes(
|
|||
response_model=DeletionResult,
|
||||
dependencies=[Depends(combined_auth)],
|
||||
)
|
||||
async def delete_entity(request: DeleteEntityRequest):
|
||||
async def delete_entity(raw_request: Request, request: DeleteEntityRequest):
|
||||
"""
|
||||
Delete an entity and all its relationships from the knowledge graph.
|
||||
|
||||
|
|
@ -2798,6 +2806,8 @@ def create_document_routes(
|
|||
HTTPException: If the entity is not found (404) or an error occurs (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
result = await rag.adelete_by_entity(entity_name=request.entity_name)
|
||||
if result.status == "not_found":
|
||||
raise HTTPException(status_code=404, detail=result.message)
|
||||
|
|
@ -2819,7 +2829,7 @@ def create_document_routes(
|
|||
response_model=DeletionResult,
|
||||
dependencies=[Depends(combined_auth)],
|
||||
)
|
||||
async def delete_relation(request: DeleteRelationRequest):
|
||||
async def delete_relation(raw_request: Request, request: DeleteRelationRequest):
|
||||
"""
|
||||
Delete a relationship between two entities from the knowledge graph.
|
||||
|
||||
|
|
@ -2833,6 +2843,8 @@ def create_document_routes(
|
|||
HTTPException: If the relation is not found (404) or an error occurs (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
result = await rag.adelete_by_relation(
|
||||
source_entity=request.source_entity,
|
||||
target_entity=request.target_entity,
|
||||
|
|
@ -2857,7 +2869,7 @@ def create_document_routes(
|
|||
response_model=TrackStatusResponse,
|
||||
dependencies=[Depends(combined_auth)],
|
||||
)
|
||||
async def get_track_status(track_id: str) -> TrackStatusResponse:
|
||||
async def get_track_status(raw_request: Request, track_id: str) -> TrackStatusResponse:
|
||||
"""
|
||||
Get the processing status of documents by tracking ID.
|
||||
|
||||
|
|
@ -2877,6 +2889,8 @@ def create_document_routes(
|
|||
HTTPException: If track_id is invalid (400) or an error occurs (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
# Validate track_id
|
||||
if not track_id or not track_id.strip():
|
||||
raise HTTPException(status_code=400, detail="Track ID cannot be empty")
|
||||
|
|
@ -2932,6 +2946,7 @@ def create_document_routes(
|
|||
dependencies=[Depends(combined_auth)],
|
||||
)
|
||||
async def get_documents_paginated(
|
||||
raw_request: Request,
|
||||
request: DocumentsRequest,
|
||||
) -> PaginatedDocsResponse:
|
||||
"""
|
||||
|
|
@ -2954,6 +2969,8 @@ def create_document_routes(
|
|||
HTTPException: If an error occurs while retrieving documents (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
# Get paginated documents and status counts in parallel
|
||||
docs_task = rag.doc_status.get_docs_paginated(
|
||||
status_filter=request.status_filter,
|
||||
|
|
@ -3018,7 +3035,7 @@ def create_document_routes(
|
|||
response_model=StatusCountsResponse,
|
||||
dependencies=[Depends(combined_auth)],
|
||||
)
|
||||
async def get_document_status_counts() -> StatusCountsResponse:
|
||||
async def get_document_status_counts(raw_request: Request) -> StatusCountsResponse:
|
||||
"""
|
||||
Get counts of documents by status.
|
||||
|
||||
|
|
@ -3032,6 +3049,8 @@ def create_document_routes(
|
|||
HTTPException: If an error occurs while retrieving status counts (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
status_counts = await rag.doc_status.get_all_status_counts()
|
||||
return StatusCountsResponse(status_counts=status_counts)
|
||||
|
||||
|
|
@ -3045,7 +3064,7 @@ def create_document_routes(
|
|||
response_model=ReprocessResponse,
|
||||
dependencies=[Depends(combined_auth)],
|
||||
)
|
||||
async def reprocess_failed_documents(background_tasks: BackgroundTasks):
|
||||
async def reprocess_failed_documents(raw_request: Request, background_tasks: BackgroundTasks):
|
||||
"""
|
||||
Reprocess failed and pending documents.
|
||||
|
||||
|
|
@ -3068,6 +3087,8 @@ def create_document_routes(
|
|||
HTTPException: If an error occurs while initiating reprocessing (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
# Generate track_id with "retry" prefix for retry operation
|
||||
track_id = generate_track_id("retry")
|
||||
|
||||
|
|
@ -3093,7 +3114,7 @@ def create_document_routes(
|
|||
response_model=CancelPipelineResponse,
|
||||
dependencies=[Depends(combined_auth)],
|
||||
)
|
||||
async def cancel_pipeline():
|
||||
async def cancel_pipeline(raw_request: Request):
|
||||
"""
|
||||
Request cancellation of the currently running pipeline.
|
||||
|
||||
|
|
@ -3115,6 +3136,8 @@ def create_document_routes(
|
|||
HTTPException: If an error occurs while setting cancellation flag (500).
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
from lightrag.kg.shared_storage import (
|
||||
get_namespace_data,
|
||||
get_namespace_lock,
|
||||
|
|
|
|||
|
|
@ -2,12 +2,14 @@
|
|||
This module contains all graph-related routes for the LightRAG API.
|
||||
"""
|
||||
|
||||
from typing import Optional, Dict, Any
|
||||
import traceback
|
||||
from fastapi import APIRouter, Depends, Query, HTTPException
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Query, Request
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from lightrag.utils import logger
|
||||
|
||||
from ..utils_api import get_combined_auth_dependency
|
||||
|
||||
router = APIRouter(tags=["graph"])
|
||||
|
|
@ -86,11 +88,11 @@ class RelationCreateRequest(BaseModel):
|
|||
)
|
||||
|
||||
|
||||
def create_graph_routes(rag, api_key: Optional[str] = None):
|
||||
def create_graph_routes(create_rag, api_key: Optional[str] = None):
|
||||
combined_auth = get_combined_auth_dependency(api_key)
|
||||
|
||||
@router.get("/graph/label/list", dependencies=[Depends(combined_auth)])
|
||||
async def get_graph_labels():
|
||||
async def get_graph_labels(raw_request: Request):
|
||||
"""
|
||||
Get all graph labels
|
||||
|
||||
|
|
@ -98,6 +100,8 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
List[str]: List of graph labels
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
return await rag.get_graph_labels()
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting graph labels: {str(e)}")
|
||||
|
|
@ -108,9 +112,8 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
|
||||
@router.get("/graph/label/popular", dependencies=[Depends(combined_auth)])
|
||||
async def get_popular_labels(
|
||||
limit: int = Query(
|
||||
300, description="Maximum number of popular labels to return", ge=1, le=1000
|
||||
),
|
||||
raw_request: Request,
|
||||
limit: int = Query(300, description="Maximum number of popular labels to return", ge=1, le=1000),
|
||||
):
|
||||
"""
|
||||
Get popular labels by node degree (most connected entities)
|
||||
|
|
@ -122,6 +125,8 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
List[str]: List of popular labels sorted by degree (highest first)
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
return await rag.chunk_entity_relation_graph.get_popular_labels(limit)
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting popular labels: {str(e)}")
|
||||
|
|
@ -132,6 +137,7 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
|
||||
@router.get("/graph/label/search", dependencies=[Depends(combined_auth)])
|
||||
async def search_labels(
|
||||
raw_request: Request,
|
||||
q: str = Query(..., description="Search query string"),
|
||||
limit: int = Query(
|
||||
50, description="Maximum number of search results to return", ge=1, le=100
|
||||
|
|
@ -148,6 +154,8 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
List[str]: List of matching labels sorted by relevance
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
return await rag.chunk_entity_relation_graph.search_labels(q, limit)
|
||||
except Exception as e:
|
||||
logger.error(f"Error searching labels with query '{q}': {str(e)}")
|
||||
|
|
@ -158,6 +166,7 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
|
||||
@router.get("/graphs", dependencies=[Depends(combined_auth)])
|
||||
async def get_knowledge_graph(
|
||||
raw_request: Request,
|
||||
label: str = Query(..., description="Label to get knowledge graph for"),
|
||||
max_depth: int = Query(3, description="Maximum depth of graph", ge=1),
|
||||
max_nodes: int = Query(1000, description="Maximum nodes to return", ge=1),
|
||||
|
|
@ -177,6 +186,8 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
Dict[str, List[str]]: Knowledge graph for label
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
# 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)})"
|
||||
|
|
@ -196,6 +207,7 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
|
||||
@router.get("/graph/entity/exists", dependencies=[Depends(combined_auth)])
|
||||
async def check_entity_exists(
|
||||
raw_request: Request,
|
||||
name: str = Query(..., description="Entity name to check"),
|
||||
):
|
||||
"""
|
||||
|
|
@ -208,6 +220,8 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
Dict[str, bool]: Dictionary with 'exists' key indicating if entity exists
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
exists = await rag.chunk_entity_relation_graph.has_node(name)
|
||||
return {"exists": exists}
|
||||
except Exception as e:
|
||||
|
|
@ -218,7 +232,7 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
)
|
||||
|
||||
@router.post("/graph/entity/edit", dependencies=[Depends(combined_auth)])
|
||||
async def update_entity(request: EntityUpdateRequest):
|
||||
async def update_entity(raw_request: Request, request: EntityUpdateRequest):
|
||||
"""
|
||||
Update an entity's properties in the knowledge graph
|
||||
|
||||
|
|
@ -353,6 +367,8 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
}
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
result = await rag.aedit_entity(
|
||||
entity_name=request.entity_name,
|
||||
updated_data=request.updated_data,
|
||||
|
|
@ -408,7 +424,7 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
)
|
||||
|
||||
@router.post("/graph/relation/edit", dependencies=[Depends(combined_auth)])
|
||||
async def update_relation(request: RelationUpdateRequest):
|
||||
async def update_relation(raw_request: Request, request: RelationUpdateRequest):
|
||||
"""Update a relation's properties in the knowledge graph
|
||||
|
||||
Args:
|
||||
|
|
@ -418,6 +434,8 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
Dict: Updated relation information
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
result = await rag.aedit_relation(
|
||||
source_entity=request.source_id,
|
||||
target_entity=request.target_id,
|
||||
|
|
@ -443,7 +461,7 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
)
|
||||
|
||||
@router.post("/graph/entity/create", dependencies=[Depends(combined_auth)])
|
||||
async def create_entity(request: EntityCreateRequest):
|
||||
async def create_entity(raw_request: Request, request: EntityCreateRequest):
|
||||
"""
|
||||
Create a new entity in the knowledge graph
|
||||
|
||||
|
|
@ -488,6 +506,8 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
}
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
# Use the proper acreate_entity method which handles:
|
||||
# - Graph lock for concurrency
|
||||
# - Vector embedding creation in entities_vdb
|
||||
|
|
@ -516,7 +536,7 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
)
|
||||
|
||||
@router.post("/graph/relation/create", dependencies=[Depends(combined_auth)])
|
||||
async def create_relation(request: RelationCreateRequest):
|
||||
async def create_relation(raw_request: Request, request: RelationCreateRequest):
|
||||
"""
|
||||
Create a new relationship between two entities in the knowledge graph
|
||||
|
||||
|
|
@ -573,6 +593,8 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
}
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
# Use the proper acreate_relation method which handles:
|
||||
# - Graph lock for concurrency
|
||||
# - Entity existence validation
|
||||
|
|
@ -605,7 +627,7 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
)
|
||||
|
||||
@router.post("/graph/entities/merge", dependencies=[Depends(combined_auth)])
|
||||
async def merge_entities(request: EntityMergeRequest):
|
||||
async def merge_entities(raw_request: Request, request: EntityMergeRequest):
|
||||
"""
|
||||
Merge multiple entities into a single entity, preserving all relationships
|
||||
|
||||
|
|
@ -662,6 +684,8 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
|
|||
- This operation cannot be undone, so verify entity names before merging
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
result = await rag.amerge_entities(
|
||||
source_entities=request.entities_to_change,
|
||||
target_entity=request.entity_to_change_into,
|
||||
|
|
|
|||
|
|
@ -1,17 +1,17 @@
|
|||
from fastapi import APIRouter, HTTPException, Request
|
||||
from pydantic import BaseModel
|
||||
from typing import List, Dict, Any, Optional, Type
|
||||
from lightrag.utils import logger
|
||||
import time
|
||||
import asyncio
|
||||
import json
|
||||
import re
|
||||
import time
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, List, Optional, Type
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Request
|
||||
from fastapi.responses import StreamingResponse
|
||||
import asyncio
|
||||
from pydantic import BaseModel
|
||||
|
||||
from lightrag import LightRAG, QueryParam
|
||||
from lightrag.utils import TiktokenTokenizer
|
||||
from lightrag.api.utils_api import get_combined_auth_dependency
|
||||
from fastapi import Depends
|
||||
from lightrag.utils import TiktokenTokenizer, logger
|
||||
|
||||
|
||||
# query mode according to query prefix (bypass is not LightRAG quer mode)
|
||||
|
|
@ -117,9 +117,7 @@ class OllamaPsResponse(BaseModel):
|
|||
models: List[OllamaRunningModel]
|
||||
|
||||
|
||||
async def parse_request_body(
|
||||
request: Request, model_class: Type[BaseModel]
|
||||
) -> BaseModel:
|
||||
async def parse_request_body(request: Request, model_class: Type[BaseModel]) -> BaseModel:
|
||||
"""
|
||||
Parse request body based on Content-Type header.
|
||||
Supports both application/json and application/octet-stream.
|
||||
|
|
@ -151,9 +149,7 @@ async def parse_request_body(
|
|||
except json.JSONDecodeError:
|
||||
raise HTTPException(status_code=400, detail="Invalid JSON in request body")
|
||||
except Exception as e:
|
||||
raise HTTPException(
|
||||
status_code=400, detail=f"Error parsing request body: {str(e)}"
|
||||
)
|
||||
raise HTTPException(status_code=400, detail=f"Error parsing request body: {str(e)}")
|
||||
|
||||
|
||||
def estimate_tokens(text: str) -> int:
|
||||
|
|
@ -218,9 +214,8 @@ def parse_query_mode(query: str) -> tuple[str, SearchMode, bool, Optional[str]]:
|
|||
|
||||
|
||||
class OllamaAPI:
|
||||
def __init__(self, rag: LightRAG, top_k: int = 60, api_key: Optional[str] = None):
|
||||
self.rag = rag
|
||||
self.ollama_server_infos = rag.ollama_server_infos
|
||||
def __init__(self, create_rag, top_k: int = 60, api_key: Optional[str] = None):
|
||||
self.create_rag = create_rag
|
||||
self.top_k = top_k
|
||||
self.api_key = api_key
|
||||
self.router = APIRouter(tags=["ollama"])
|
||||
|
|
@ -236,21 +231,24 @@ class OllamaAPI:
|
|||
return OllamaVersionResponse(version="0.9.3")
|
||||
|
||||
@self.router.get("/tags", dependencies=[Depends(combined_auth)])
|
||||
async def get_tags():
|
||||
async def get_tags(raw_request: Request):
|
||||
"""Return available models acting as an Ollama server"""
|
||||
rag = await self.create_rag(raw_request)
|
||||
ollama_server_infos = rag.ollama_server_infos
|
||||
|
||||
return OllamaTagResponse(
|
||||
models=[
|
||||
{
|
||||
"name": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"modified_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"size": self.ollama_server_infos.LIGHTRAG_SIZE,
|
||||
"digest": self.ollama_server_infos.LIGHTRAG_DIGEST,
|
||||
"name": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"modified_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"size": ollama_server_infos.LIGHTRAG_SIZE,
|
||||
"digest": ollama_server_infos.LIGHTRAG_DIGEST,
|
||||
"details": {
|
||||
"parent_model": "",
|
||||
"format": "gguf",
|
||||
"family": self.ollama_server_infos.LIGHTRAG_NAME,
|
||||
"families": [self.ollama_server_infos.LIGHTRAG_NAME],
|
||||
"family": ollama_server_infos.LIGHTRAG_NAME,
|
||||
"families": [ollama_server_infos.LIGHTRAG_NAME],
|
||||
"parameter_size": "13B",
|
||||
"quantization_level": "Q4_0",
|
||||
},
|
||||
|
|
@ -259,15 +257,18 @@ class OllamaAPI:
|
|||
)
|
||||
|
||||
@self.router.get("/ps", dependencies=[Depends(combined_auth)])
|
||||
async def get_running_models():
|
||||
async def get_running_models(raw_request: Request):
|
||||
"""List Running Models - returns currently running models"""
|
||||
rag = await self.create_rag(raw_request)
|
||||
ollama_server_infos = rag.ollama_server_infos
|
||||
|
||||
return OllamaPsResponse(
|
||||
models=[
|
||||
{
|
||||
"name": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"size": self.ollama_server_infos.LIGHTRAG_SIZE,
|
||||
"digest": self.ollama_server_infos.LIGHTRAG_DIGEST,
|
||||
"name": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"size": ollama_server_infos.LIGHTRAG_SIZE,
|
||||
"digest": ollama_server_infos.LIGHTRAG_DIGEST,
|
||||
"details": {
|
||||
"parent_model": "",
|
||||
"format": "gguf",
|
||||
|
|
@ -277,14 +278,12 @@ class OllamaAPI:
|
|||
"quantization_level": "Q4_0",
|
||||
},
|
||||
"expires_at": "2050-12-31T14:38:31.83753-07:00",
|
||||
"size_vram": self.ollama_server_infos.LIGHTRAG_SIZE,
|
||||
"size_vram": ollama_server_infos.LIGHTRAG_SIZE,
|
||||
}
|
||||
]
|
||||
)
|
||||
|
||||
@self.router.post(
|
||||
"/generate", dependencies=[Depends(combined_auth)], include_in_schema=True
|
||||
)
|
||||
@self.router.post("/generate", dependencies=[Depends(combined_auth)], include_in_schema=True)
|
||||
async def generate(raw_request: Request):
|
||||
"""Handle generate completion requests acting as an Ollama model
|
||||
For compatibility purpose, the request is not processed by LightRAG,
|
||||
|
|
@ -292,6 +291,9 @@ class OllamaAPI:
|
|||
Supports both application/json and application/octet-stream Content-Types.
|
||||
"""
|
||||
try:
|
||||
rag = await self.create_rag(raw_request)
|
||||
ollama_server_infos = rag.ollama_server_infos
|
||||
|
||||
# Parse the request body manually
|
||||
request = await parse_request_body(raw_request, OllamaGenerateRequest)
|
||||
|
||||
|
|
@ -300,12 +302,10 @@ class OllamaAPI:
|
|||
prompt_tokens = estimate_tokens(query)
|
||||
|
||||
if request.system:
|
||||
self.rag.llm_model_kwargs["system_prompt"] = request.system
|
||||
rag.llm_model_kwargs["system_prompt"] = request.system
|
||||
|
||||
if request.stream:
|
||||
response = await self.rag.llm_model_func(
|
||||
query, stream=True, **self.rag.llm_model_kwargs
|
||||
)
|
||||
response = await rag.llm_model_func(query, stream=True, **rag.llm_model_kwargs)
|
||||
|
||||
async def stream_generator():
|
||||
first_chunk_time = None
|
||||
|
|
@ -320,8 +320,8 @@ class OllamaAPI:
|
|||
total_response = response
|
||||
|
||||
data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"response": response,
|
||||
"done": False,
|
||||
}
|
||||
|
|
@ -333,8 +333,8 @@ class OllamaAPI:
|
|||
eval_time = last_chunk_time - first_chunk_time
|
||||
|
||||
data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"response": "",
|
||||
"done": True,
|
||||
"done_reason": "stop",
|
||||
|
|
@ -358,8 +358,8 @@ class OllamaAPI:
|
|||
|
||||
total_response += chunk
|
||||
data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"response": chunk,
|
||||
"done": False,
|
||||
}
|
||||
|
|
@ -375,8 +375,8 @@ class OllamaAPI:
|
|||
|
||||
# Send error message to client
|
||||
error_data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"response": f"\n\nError: {error_msg}",
|
||||
"error": f"\n\nError: {error_msg}",
|
||||
"done": False,
|
||||
|
|
@ -385,8 +385,8 @@ class OllamaAPI:
|
|||
|
||||
# Send final message to close the stream
|
||||
final_data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"response": "",
|
||||
"done": True,
|
||||
}
|
||||
|
|
@ -400,8 +400,8 @@ class OllamaAPI:
|
|||
eval_time = last_chunk_time - first_chunk_time
|
||||
|
||||
data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"response": "",
|
||||
"done": True,
|
||||
"done_reason": "stop",
|
||||
|
|
@ -428,9 +428,7 @@ class OllamaAPI:
|
|||
)
|
||||
else:
|
||||
first_chunk_time = time.time_ns()
|
||||
response_text = await self.rag.llm_model_func(
|
||||
query, stream=False, **self.rag.llm_model_kwargs
|
||||
)
|
||||
response_text = await rag.llm_model_func(query, stream=False, **rag.llm_model_kwargs)
|
||||
last_chunk_time = time.time_ns()
|
||||
|
||||
if not response_text:
|
||||
|
|
@ -442,8 +440,8 @@ class OllamaAPI:
|
|||
eval_time = last_chunk_time - first_chunk_time
|
||||
|
||||
return {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"response": str(response_text),
|
||||
"done": True,
|
||||
"done_reason": "stop",
|
||||
|
|
@ -468,7 +466,11 @@ class OllamaAPI:
|
|||
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.
|
||||
"""
|
||||
|
||||
try:
|
||||
rag = await self.create_rag(raw_request)
|
||||
ollama_server_infos = rag.ollama_server_infos
|
||||
|
||||
# Parse the request body manually
|
||||
request = await parse_request_body(raw_request, OllamaChatRequest)
|
||||
|
||||
|
|
@ -516,15 +518,15 @@ class OllamaAPI:
|
|||
# Determine if the request is prefix with "/bypass"
|
||||
if mode == SearchMode.bypass:
|
||||
if request.system:
|
||||
self.rag.llm_model_kwargs["system_prompt"] = request.system
|
||||
response = await self.rag.llm_model_func(
|
||||
rag.llm_model_kwargs["system_prompt"] = request.system
|
||||
response = await rag.llm_model_func(
|
||||
cleaned_query,
|
||||
stream=True,
|
||||
history_messages=conversation_history,
|
||||
**self.rag.llm_model_kwargs,
|
||||
**rag.llm_model_kwargs,
|
||||
)
|
||||
else:
|
||||
response = await self.rag.aquery(
|
||||
response = await rag.aquery(
|
||||
cleaned_query, param=query_param
|
||||
)
|
||||
|
||||
|
|
@ -541,8 +543,8 @@ class OllamaAPI:
|
|||
total_response = response
|
||||
|
||||
data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": response,
|
||||
|
|
@ -558,8 +560,8 @@ class OllamaAPI:
|
|||
eval_time = last_chunk_time - first_chunk_time
|
||||
|
||||
data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": "",
|
||||
|
|
@ -586,8 +588,8 @@ class OllamaAPI:
|
|||
|
||||
total_response += chunk
|
||||
data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": chunk,
|
||||
|
|
@ -607,8 +609,8 @@ class OllamaAPI:
|
|||
|
||||
# Send error message to client
|
||||
error_data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": f"\n\nError: {error_msg}",
|
||||
|
|
@ -621,8 +623,8 @@ class OllamaAPI:
|
|||
|
||||
# Send final message to close the stream
|
||||
final_data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": "",
|
||||
|
|
@ -641,8 +643,8 @@ class OllamaAPI:
|
|||
eval_time = last_chunk_time - first_chunk_time
|
||||
|
||||
data = {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": "",
|
||||
|
|
@ -678,18 +680,16 @@ class OllamaAPI:
|
|||
)
|
||||
if match_result or mode == SearchMode.bypass:
|
||||
if request.system:
|
||||
self.rag.llm_model_kwargs["system_prompt"] = request.system
|
||||
rag.llm_model_kwargs["system_prompt"] = request.system
|
||||
|
||||
response_text = await self.rag.llm_model_func(
|
||||
response_text = await rag.llm_model_func(
|
||||
cleaned_query,
|
||||
stream=False,
|
||||
history_messages=conversation_history,
|
||||
**self.rag.llm_model_kwargs,
|
||||
**rag.llm_model_kwargs,
|
||||
)
|
||||
else:
|
||||
response_text = await self.rag.aquery(
|
||||
cleaned_query, param=query_param
|
||||
)
|
||||
response_text = await rag.aquery(cleaned_query, param=query_param)
|
||||
|
||||
last_chunk_time = time.time_ns()
|
||||
|
||||
|
|
@ -702,8 +702,8 @@ class OllamaAPI:
|
|||
eval_time = last_chunk_time - first_chunk_time
|
||||
|
||||
return {
|
||||
"model": self.ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": self.ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"model": ollama_server_infos.LIGHTRAG_MODEL,
|
||||
"created_at": ollama_server_infos.LIGHTRAG_CREATED_AT,
|
||||
"message": {
|
||||
"role": "assistant",
|
||||
"content": str(response_text),
|
||||
|
|
|
|||
|
|
@ -4,12 +4,14 @@ This module contains all query-related routes for the LightRAG API.
|
|||
|
||||
import json
|
||||
from typing import Any, Dict, List, Literal, Optional
|
||||
from fastapi import APIRouter, Depends, HTTPException
|
||||
from lightrag.base import QueryParam
|
||||
from lightrag.api.utils_api import get_combined_auth_dependency
|
||||
from lightrag.utils import logger
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Request
|
||||
from pydantic import BaseModel, Field, field_validator
|
||||
|
||||
from lightrag.api.utils_api import get_combined_auth_dependency
|
||||
from lightrag.base import QueryParam
|
||||
from lightrag.utils import logger
|
||||
|
||||
router = APIRouter(tags=["query"])
|
||||
|
||||
|
||||
|
|
@ -190,7 +192,7 @@ class StreamChunkResponse(BaseModel):
|
|||
)
|
||||
|
||||
|
||||
def create_query_routes(rag, api_key: Optional[str] = None, top_k: int = 60):
|
||||
def create_query_routes(create_rag, api_key: Optional[str] = None, top_k: int = 60):
|
||||
combined_auth = get_combined_auth_dependency(api_key)
|
||||
|
||||
@router.post(
|
||||
|
|
@ -322,7 +324,7 @@ def create_query_routes(rag, api_key: Optional[str] = None, top_k: int = 60):
|
|||
},
|
||||
},
|
||||
)
|
||||
async def query_text(request: QueryRequest):
|
||||
async def query_text(raw_request: Request, request: QueryRequest):
|
||||
"""
|
||||
Comprehensive RAG query endpoint with non-streaming response. Parameter "stream" is ignored.
|
||||
|
||||
|
|
@ -402,6 +404,8 @@ def create_query_routes(rag, api_key: Optional[str] = None, top_k: int = 60):
|
|||
- 500: Internal processing error (e.g., LLM service unavailable)
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
param = request.to_query_params(
|
||||
False
|
||||
) # Ensure stream=False for non-streaming endpoint
|
||||
|
|
@ -532,7 +536,7 @@ def create_query_routes(rag, api_key: Optional[str] = None, top_k: int = 60):
|
|||
},
|
||||
},
|
||||
)
|
||||
async def query_text_stream(request: QueryRequest):
|
||||
async def query_text_stream(raw_request: Request, request: QueryRequest):
|
||||
"""
|
||||
Advanced RAG query endpoint with flexible streaming response.
|
||||
|
||||
|
|
@ -660,6 +664,8 @@ def create_query_routes(rag, api_key: Optional[str] = None, top_k: int = 60):
|
|||
Use streaming mode for real-time interfaces and non-streaming for batch processing.
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
# Use the stream parameter from the request, defaulting to True if not specified
|
||||
stream_mode = request.stream if request.stream is not None else True
|
||||
param = request.to_query_params(stream_mode)
|
||||
|
|
@ -1035,7 +1041,7 @@ def create_query_routes(rag, api_key: Optional[str] = None, top_k: int = 60):
|
|||
},
|
||||
},
|
||||
)
|
||||
async def query_data(request: QueryRequest):
|
||||
async def query_data(raw_request: Request, request: QueryRequest):
|
||||
"""
|
||||
Advanced data retrieval endpoint for structured RAG analysis.
|
||||
|
||||
|
|
@ -1139,6 +1145,8 @@ def create_query_routes(rag, api_key: Optional[str] = None, top_k: int = 60):
|
|||
as structured data analysis typically requires source attribution.
|
||||
"""
|
||||
try:
|
||||
rag = await create_rag(raw_request)
|
||||
|
||||
param = request.to_query_params(False) # No streaming for data endpoint
|
||||
response = await rag.aquery_data(request.query, param=param)
|
||||
|
||||
|
|
@ -1151,6 +1159,7 @@ def create_query_routes(rag, api_key: Optional[str] = None, top_k: int = 60):
|
|||
status="failure",
|
||||
message="Invalid response type",
|
||||
data={},
|
||||
metadata={},
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"Error processing data query: {str(e)}", exc_info=True)
|
||||
|
|
|
|||
|
|
@ -289,6 +289,7 @@ const axiosInstance = axios.create({
|
|||
axiosInstance.interceptors.request.use((config) => {
|
||||
const apiKey = useSettingsStore.getState().apiKey
|
||||
const token = localStorage.getItem('LIGHTRAG-API-TOKEN');
|
||||
const workspace = localStorage.getItem('LIGHTRAG-WORKSPACE');
|
||||
|
||||
// Always include token if it exists, regardless of path
|
||||
if (token) {
|
||||
|
|
@ -297,6 +298,9 @@ axiosInstance.interceptors.request.use((config) => {
|
|||
if (apiKey) {
|
||||
config.headers['X-API-Key'] = apiKey
|
||||
}
|
||||
if (workspace) {
|
||||
config.headers['LIGHTRAG-WORKSPACE'] = workspace
|
||||
}
|
||||
return config
|
||||
})
|
||||
|
||||
|
|
@ -397,6 +401,7 @@ export const queryTextStream = async (
|
|||
) => {
|
||||
const apiKey = useSettingsStore.getState().apiKey;
|
||||
const token = localStorage.getItem('LIGHTRAG-API-TOKEN');
|
||||
const workspace = localStorage.getItem('LIGHTRAG-WORKSPACE');
|
||||
const headers: HeadersInit = {
|
||||
'Content-Type': 'application/json',
|
||||
'Accept': 'application/x-ndjson',
|
||||
|
|
@ -407,6 +412,9 @@ export const queryTextStream = async (
|
|||
if (apiKey) {
|
||||
headers['X-API-Key'] = apiKey;
|
||||
}
|
||||
if (workspace) {
|
||||
headers['LIGHTRAG-WORKSPACE'] = workspace;
|
||||
}
|
||||
|
||||
try {
|
||||
const response = await fetch(`${backendBaseUrl}/query/stream`, {
|
||||
|
|
|
|||
|
|
@ -7,8 +7,10 @@ import { useAuthStore } from '@/stores/state'
|
|||
import { cn } from '@/lib/utils'
|
||||
import { useTranslation } from 'react-i18next'
|
||||
import { navigationService } from '@/services/navigation'
|
||||
import { ZapIcon, GithubIcon, LogOutIcon } from 'lucide-react'
|
||||
import { ZapIcon, GithubIcon, LogOutIcon, CheckIcon } from 'lucide-react'
|
||||
import { Tooltip, TooltipContent, TooltipProvider, TooltipTrigger } from '@/components/ui/Tooltip'
|
||||
import {useState, useEffect} from "react";
|
||||
import {toast} from 'sonner';
|
||||
|
||||
interface NavigationTabProps {
|
||||
value: string
|
||||
|
|
@ -57,6 +59,7 @@ function TabsNavigation() {
|
|||
export default function SiteHeader() {
|
||||
const { t } = useTranslation()
|
||||
const { isGuestMode, coreVersion, apiVersion, username, webuiTitle, webuiDescription } = useAuthStore()
|
||||
const [workspace, setWorkspace] = useState('');
|
||||
|
||||
const versionDisplay = (coreVersion && apiVersion)
|
||||
? `${coreVersion}/${apiVersion}`
|
||||
|
|
@ -72,6 +75,26 @@ export default function SiteHeader() {
|
|||
navigationService.navigateToLogin();
|
||||
}
|
||||
|
||||
useEffect(() => {
|
||||
const ws = localStorage.getItem('LIGHTRAG-WORKSPACE') || '';
|
||||
setWorkspace(ws);
|
||||
}, []);
|
||||
|
||||
const handleWorkspaceUpdate = () => {
|
||||
const trimed = workspace.trim();
|
||||
if (trimed) {
|
||||
localStorage.setItem('LIGHTRAG-WORKSPACE', trimed);
|
||||
toast.success(t('Workspace set. Reloading page...'));
|
||||
} else {
|
||||
localStorage.removeItem('LIGHTRAG-WORKSPACE');
|
||||
toast.success(t('Workspace cleared. Reloading page...'));
|
||||
}
|
||||
|
||||
setTimeout(() => {
|
||||
window.location.reload();
|
||||
}, 500);
|
||||
}
|
||||
|
||||
return (
|
||||
<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">
|
||||
<div className="min-w-[200px] w-auto flex items-center">
|
||||
|
|
@ -111,6 +134,10 @@ export default function SiteHeader() {
|
|||
|
||||
<nav className="w-[200px] flex items-center justify-end">
|
||||
<div className="flex items-center gap-2">
|
||||
<div className="flex items-center gap-1">
|
||||
<input type="text" value={workspace} onChange={(e) => setWorkspace(e.target.value)} placeholder="workspace" className="h-6 w-20 px-1 text-xs border rounded bg-background text-foreground"/>
|
||||
<Button variant="ghost" size="icon" className="h-6 w-6" side="bottom" tooltip={t('header.updateWorkspace', 'Update Workspace')} onClick={handleWorkspaceUpdate}><CheckIcon className="size-3" aria-hidden="true" /></Button>
|
||||
</div>
|
||||
{versionDisplay && (
|
||||
<TooltipProvider>
|
||||
<Tooltip>
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue