Merge branch 'HKUDS:main' into main

lightrag/api/lightrag_server.py

@@ -13,18 +13,6 @@ from fastapi import (
 from typing import Dict
 import threading
 
-# Global progress tracker
-scan_progress: Dict = {
-    "is_scanning": False,
-    "current_file": "",
-    "indexed_count": 0,
-    "total_files": 0,
-    "progress": 0,
-}
-
-# Lock for thread-safe operations
-progress_lock = threading.Lock()
-
 import json
 import os
 
@@ -34,7 +22,7 @@ import logging
 import argparse
 import time
 import re
-from typing import List, Dict, Any, Optional, Union
+from typing import List, Any, Optional, Union
 from lightrag import LightRAG, QueryParam
 from lightrag.api import __api_version__
 
@@ -57,8 +45,21 @@ import pipmaster as pm
 
 from dotenv import load_dotenv
 
+# Load environment variables
 load_dotenv()
 
+# Global progress tracker
+scan_progress: Dict = {
+    "is_scanning": False,
+    "current_file": "",
+    "indexed_count": 0,
+    "total_files": 0,
+    "progress": 0,
+}
+
+# Lock for thread-safe operations
+progress_lock = threading.Lock()
+
 
 def estimate_tokens(text: str) -> int:
     """Estimate the number of tokens in text
@@ -918,6 +919,12 @@ def create_app(args):
             vector_db_storage_cls_kwargs={
                 "cosine_better_than_threshold": args.cosine_threshold
             },
+            enable_llm_cache_for_entity_extract=False,  # set to True for debuging to reduce llm fee
+            embedding_cache_config={
+                "enabled": True,
+                "similarity_threshold": 0.95,
+                "use_llm_check": False,
+            },
         )
     else:
         rag = LightRAG(
@@ -941,6 +948,12 @@ def create_app(args):
             vector_db_storage_cls_kwargs={
                 "cosine_better_than_threshold": args.cosine_threshold
             },
+            enable_llm_cache_for_entity_extract=False,  # set to True for debuging to reduce llm fee
+            embedding_cache_config={
+                "enabled": True,
+                "similarity_threshold": 0.95,
+                "use_llm_check": False,
+            },
         )
 
     async def index_file(file_path: Union[str, Path]) -> None: