Fix: top_k param handling error, unify top_k and cosine default value.

.env.example

@@ -32,8 +32,8 @@ MAX_EMBED_TOKENS=8192
 #HISTORY_TURNS=3
 #CHUNK_SIZE=1200
 #CHUNK_OVERLAP_SIZE=100
-#COSINE_THRESHOLD=0.4   # 0.2 while not running API server
+#COSINE_THRESHOLD=0.2
-#TOP_K=50               # 60  while not running API server
+#TOP_K=60
 
 ### LLM Configuration (Use valid host. For local services, you can use host.docker.internal)
 ### Ollama example

lightrag/api/README.md

@@ -103,7 +103,7 @@ After starting the lightrag-server, you can add an Ollama-type connection in the
 
 LightRAG can be configured using either command-line arguments or environment variables. When both are provided, command-line arguments take precedence over environment variables.
 
-For better performance, the API server's default values for TOP_K and COSINE_THRESHOLD are set to 50 and 0.4 respectively. If COSINE_THRESHOLD remains at its default value of 0.2 in LightRAG, many irrelevant entities and relations would be retrieved and sent to the LLM.
+Default `TOP_K` is set to `60`. Default `COSINE_THRESHOLD` are set to `0.2`.
 
 ### Environment Variables
 

lightrag/api/lightrag_server.py

@@ -530,13 +530,13 @@ def parse_args() -> argparse.Namespace:
     parser.add_argument(
         "--top-k",
         type=int,
-        default=get_env_value("TOP_K", 50, int),
+        default=get_env_value("TOP_K", 60, int),
-        help="Number of most similar results to return (default: from env or 50)",
+        help="Number of most similar results to return (default: from env or 60)",
     )
     parser.add_argument(
         "--cosine-threshold",
         type=float,
-        default=get_env_value("COSINE_THRESHOLD", 0.4, float),
+        default=get_env_value("COSINE_THRESHOLD", 0.2, float),
         help="Cosine similarity threshold (default: from env or 0.4)",
     )
 
@@ -669,7 +669,13 @@ def get_api_key_dependency(api_key: Optional[str]):
     return api_key_auth
 
 
+# Global configuration
+global_top_k = 60  # default value
+
 def create_app(args):
+    global global_top_k
+    global_top_k = args.top_k  # save top_k from args
+    
     # Verify that bindings are correctly setup
     if args.llm_binding not in [
         "lollms",
@@ -1279,7 +1285,7 @@ def create_app(args):
                     mode=request.mode,
                     stream=request.stream,
                     only_need_context=request.only_need_context,
-                    top_k=args.top_k,
+                    top_k=global_top_k,
                 ),
             )
 
@@ -1321,7 +1327,7 @@ def create_app(args):
                     mode=request.mode,
                     stream=True,
                     only_need_context=request.only_need_context,
-                    top_k=args.top_k,
+                    top_k=global_top_k,
                 ),
             )
 
@@ -1611,7 +1617,7 @@ def create_app(args):
         return await rag.get_graps(nodel_label=label, max_depth=100)
 
     # Add Ollama API routes
-    ollama_api = OllamaAPI(rag)
+    ollama_api = OllamaAPI(rag, top_k=args.top_k)
     app.include_router(ollama_api.router, prefix="/api")
 
     @app.get("/documents", dependencies=[Depends(optional_api_key)])

lightrag/api/ollama_api.py

@@ -148,9 +148,10 @@ def parse_query_mode(query: str) -> tuple[str, SearchMode]:
 
 
 class OllamaAPI:
-    def __init__(self, rag: LightRAG):
+    def __init__(self, rag: LightRAG, top_k: int = 60):
         self.rag = rag
         self.ollama_server_infos = ollama_server_infos
+        self.top_k = top_k
         self.router = APIRouter()
         self.setup_routes()
 
@@ -381,7 +382,7 @@ class OllamaAPI:
                     "stream": request.stream,
                     "only_need_context": False,
                     "conversation_history": conversation_history,
-                    "top_k": self.rag.args.top_k if hasattr(self.rag, "args") else 50,
+                    "top_k": self.top_k,
                 }
 
                 if (