fix: 1.新增think参数 2.移除enable_cot意外参数

app/api/routes.py

@@ -34,6 +34,7 @@ class QueryRequest(BaseModel):
     mode: str = "hybrid"  # 可选: naive, local, global, hybrid
     top_k: int = 5
     stream: bool = False
+    think: bool = False
 
 class IngestResponse(BaseModel):
     filename: str
@@ -111,6 +112,7 @@ async def query_knowledge_base(
                     request.query, 
                     system_prompt=sys_prompt, 
                     stream=True,
+                    think=request.think,
                     hashing_kv=rag.llm_response_cache
                 )
                 

app/core/rag.py

@@ -19,11 +19,13 @@ async def llm_func(prompt, system_prompt=None, history_messages=[], **kwargs) ->
     # 移除可能存在的 model 参数，避免冲突
     kwargs.pop('model', None)
     kwargs.pop('hashing_kv', None)
+    kwargs.pop('enable_cot', None)  # 移除不支持的参数
     keyword_extraction = kwargs.pop("keyword_extraction", False)
     if keyword_extraction:
         kwargs["format"] = "json"
     
     stream = kwargs.pop("stream", False)
+    think = kwargs.pop("think", False)
     # Debug: 检查流式参数
     if stream:
         logging.info("LLM called with stream=True")
@@ -40,7 +42,7 @@ async def llm_func(prompt, system_prompt=None, history_messages=[], **kwargs) ->
     if stream:
         async def inner():
             # 使用 **kwargs 透传参数，确保 format 等顶级参数生效
-            response = await client.chat(model=settings.LLM_MODEL, messages=messages, stream=True, **kwargs)
+            response = await client.chat(model=settings.LLM_MODEL, messages=messages, stream=True, think=think, **kwargs)
 
             async for chunk in response:
                 msg = chunk.get("message", {})