diff --git a/requirements.txt b/requirements.txt
index b5cd996d..b8633d82 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -12,6 +12,7 @@ torch==2.1.0  ##on Windows system, install the cuda version manually from https:
 torchvision  #on Windows system, install the cuda version manually from https://pytorch.org/
 torchaudio  #on Windows system, install the cuda version manually from https://pytorch.org/
 fastapi>=0.104
+sse_starlette
 nltk>=3.8.1
 uvicorn>=0.24.0.post1
 starlette~=0.27.0
diff --git a/requirements_api.txt b/requirements_api.txt
index ec1005f9..e5d77b64 100644
--- a/requirements_api.txt
+++ b/requirements_api.txt
@@ -12,6 +12,7 @@ torch==2.1.0  ##on Windows system, install the cuda version manually from https:
 torchvision  #on Windows system, install the cuda version manually from https://pytorch.org/
 torchaudio  #on Windows system, install the cuda version manually from https://pytorch.org/
 fastapi>=0.104
+sse_starlette
 nltk>=3.8.1
 uvicorn>=0.24.0.post1
 starlette~=0.27.0
diff --git a/server/chat/knowledge_base_chat.py b/server/chat/knowledge_base_chat.py
index a3ab68b1..c37e030b 100644
--- a/server/chat/knowledge_base_chat.py
+++ b/server/chat/knowledge_base_chat.py
@@ -1,5 +1,5 @@
 from fastapi import Body, Request
-from fastapi.responses import StreamingResponse
+from sse_starlette.sse import EventSourceResponse
 from fastapi.concurrency import run_in_threadpool
 from configs import (LLM_MODELS, VECTOR_SEARCH_TOP_K, SCORE_THRESHOLD, TEMPERATURE)
 from server.utils import wrap_done, get_ChatOpenAI
@@ -119,9 +119,4 @@ async def knowledge_base_chat(query: str = Body(..., description="用户输入",
                              ensure_ascii=False)
         await task
 
-    return StreamingResponse(knowledge_base_chat_iterator(query=query,
-                                                          top_k=top_k,
-                                                          history=history,
-                                                          model_name=model_name,
-                                                          prompt_name=prompt_name),
-                             media_type="text/event-stream")
+    return EventSourceResponse(knowledge_base_chat_iterator(query, kb, top_k, history))