diff --git a/app/controller/add_knowledge_route.py b/app/controller/add_knowledge_route.py
index 02a4da3..6745362 100644
--- a/app/controller/add_knowledge_route.py
+++ b/app/controller/add_knowledge_route.py
@@ -1,14 +1,15 @@
 import asyncio
 import json
-from http.client import HTTPException
 from typing import List
 
-from fastapi import UploadFile, File, Form
+from fastapi import UploadFile, File, Form, HTTPException
 from langchain_core.messages import HumanMessage, SystemMessage
 from langchain_core.output_parsers import StrOutputParser
+from starlette import status
 from starlette.requests import Request
-from starlette.responses import StreamingResponse
+from starlette.responses import StreamingResponse, JSONResponse
 
+from app.general.perform_general_operation import perform_general_operation
 from app.utils.db_utils import AsyncSessionDep
 from app.utils.knowledge_utils import knowledge_service
 from app.utils.llm_utils import create_llm
@@ -45,6 +46,77 @@ def add_knowledge_route(app):
 
     return StreamingResponse(generator_function(), media_type="text/event-stream")
 
+  @app.post("/knowledge/qa/stream")
+  async def knowledge_search(body: dict, session: AsyncSessionDep, request: Request):
+
+    # 机器人的id，用来一会查询知识库编码以及判断机器人是否已经禁用
+    qaId = body.get('input').get('qaId')
+    # 聊天历史
+    messages = body.get('input').get('messages')
+    # 用户问题
+    question = body.get('input').get('question')
+
+    # 查询qa_bot信息
+    perform_result = await perform_general_operation(
+      session=session,
+      module='knowledge_qa_bot',
+      data={"id": qaId},
+      debug_data=[],
+      user=request.state.user,
+      type='item'
+    )
+    if 'error' in perform_result:
+      return JSONResponse(content={"message": perform_result.get('error')}, status_code=status.HTTP_500_INTERNAL_SERVER_ERROR)
+
+    qa_record_bot = perform_result.get('result', None)
+
+    # 找不到机器人
+    if not qa_record_bot:
+      return JSONResponse(content={"message": f"""无法找到对应问答机器人的编号:{qaId}"""}, status_code=status.HTTP_500_INTERNAL_SERVER_ERROR)
+
+    # 机器人已经被禁用
+    if qa_record_bot.get('disable') == 'Y':
+      return JSONResponse(content={"message": "该问答机器人已经禁用"}, status_code=status.HTTP_500_INTERNAL_SERVER_ERROR)
+
+    # 查询rel_qa_kb信息
+    perform_result = await perform_general_operation(
+      session=session,
+      module='rel_qa_base',
+      data={"all": True, "filters": [{"id": "01", "field": "qaId", "operator": "=", "value": qaId}]},
+      debug_data=[],
+      user=request.state.user,
+      type='list'
+    )
+
+    if 'error' in perform_result:
+      return JSONResponse(content={"message": perform_result.get('error')}, status_code=status.HTTP_500_INTERNAL_SERVER_ERROR)
+
+    rel_qa_kb_list = perform_result.get('list', [])
+
+    kb_codes = [item.get('kbCode') for item in rel_qa_kb_list]
+
+    async def generator_function():
+
+      param = KnowledgeQueryParam(kb_code=kb_codes, question=question)
+      search_response = await milvus_service.async_search(param)
+
+      chain = create_llm() | StrOutputParser()
+
+      # 先把检索结果返回前端
+      yield f'data: {json.dumps({"type": "retrieve", "data": json.dumps(search_response.model_dump())}, ensure_ascii=False)}\n\n'
+
+      external_prompt = qa_record_bot.get('prompt', '')
+
+      print("external_prompt", external_prompt, qa_record_bot)
+
+      async for chunk in chain.astream([
+        SystemMessage(content=f"""你需要根据如下内容来回答用户的问题：{search_response.answer}，如果内容为'在提供的资料中未找到相关信息'，你需要根据你自己的知识来回答用户问题。""" + external_prompt),
+        *messages,
+      ]):
+        yield f'data: {json.dumps({"type": "messages", "data": chunk}, ensure_ascii=False)}\n\n'
+
+    return StreamingResponse(generator_function(), media_type="text/event-stream")
+
   # @app.post("/knowledge/embed_text")
   # async def knowledge_embed_text(text_list: List[str]):
   #   id_list = await next_id(len(text_list))