Refactor /api/generate：use llm_model_func directly

lightrag/api/lightrag_server.py

@@ -1272,23 +1272,17 @@ def create_app(args):
             # 计算输入token数量
             prompt_tokens = estimate_tokens(cleaned_query)
             
-            # 调用RAG进行查询
-            query_param = QueryParam(
-                mode=mode,
-                stream=request.stream,
-                only_need_context=False
-            )
-            
-            # 如果有 system prompt，更新 rag 的 llm_model_kwargs
+            # 直接使用 llm_model_func 进行查询
             if request.system:
                 rag.llm_model_kwargs["system_prompt"] = request.system
             
             if request.stream:
                 from fastapi.responses import StreamingResponse
                 
-                response = await rag.aquery(
-                    cleaned_query, 
-                    param=query_param
+                response = await rag.llm_model_func(
+                    cleaned_query,
+                    stream=True,
+                    **rag.llm_model_kwargs
                 )
                 
                 async def stream_generator():
@@ -1383,7 +1377,11 @@ def create_app(args):
                 )
             else:
                 first_chunk_time = time.time_ns()
-                response_text = await rag.aquery(cleaned_query, param=query_param)
+                response_text = await rag.llm_model_func(
+                    cleaned_query,
+                    stream=False,
+                    **rag.llm_model_kwargs
+                )
                 last_chunk_time = time.time_ns()
                 
                 if not response_text: