Update app.py

app.py

@@ -48,9 +48,9 @@ vectorstore = Chroma.from_documents(documents=splits, embedding=embedding)
 def format_docs(docs):
     return "\n\n".join(doc.page_content for doc in docs)
 
-#search_kwargs={"score_threshold": 0.3}
-#search_type="similarity_score_threshold"
-retriever = vectorstore.as_retriever(k = 4)
+search_kwargs={"score_threshold": 0.3}
+search_type="similarity_score_threshold"
+retriever = vectorstore.as_retriever(k = 4, )
 
 prompt = hub.pull("rlm/rag-prompt")
 llm = HuggingFaceEndpoint(repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1", stop_sequences=["Human:"])
@@ -97,7 +97,7 @@ Make your answer at least three sentences and very comprehensive.
 Make your message in markdown with lots lines in between sentences.
 
 Please use only the documents/text provided below to answer the question.
-If the documents/text provided cannot answer the question, please say that the answer might not be present in the available database of information
+If the documents/text provided cannot answer the question, please say that the answer might not be present in the available database of information.
 """
 qa_prompt = ChatPromptTemplate.from_messages(
     [
@@ -157,13 +157,13 @@ async def echo(websocket):
             while response.startswith("\n"):
                 response = response[1:]
             await websocket.send(json.dumps({"response": response}))
-    except ConnectionClosedError:
+    except Exception:
         pass
 
 async def main():
     try:
         async with serve(echo, "0.0.0.0", 7860):
             await asyncio.Future()
-    except ConnectionClosedError:
+    except Exception:
         pass
 asyncio.run(main())