Update app.py

app.py

@@ -86,12 +86,12 @@ retriever = PineconeHybridSearchRetriever(
 llm = ChatPerplexity(temperature=0, pplx_api_key=GROQ_API_KEY, model="llama-3.1-sonar-large-128k-chat", max_tokens=512, max_retries=2)
 
 # Initialize Reranker
-model = HuggingFaceCrossEncoder(model_name="BAAI/bge-reranker-base")
-compressor = CrossEncoderReranker(model=model, top_n=10)
+# model = HuggingFaceCrossEncoder(model_name="BAAI/bge-reranker-base")
+# compressor = CrossEncoderReranker(model=model, top_n=10)
 
-compression_retriever = ContextualCompressionRetriever(
-    base_compressor=compressor, base_retriever=retriever
-)
+# compression_retriever = ContextualCompressionRetriever(
+#     base_compressor=compressor, base_retriever=retriever
+# )
 
 # Contextualization prompt and retriever
 contextualize_q_system_prompt = """Given a chat history and the latest user question \
@@ -106,7 +106,7 @@ contextualize_q_prompt = ChatPromptTemplate.from_messages(
         ("human", "{input}")
     ]
 )
-history_aware_retriever = create_history_aware_retriever(llm, compression_retriever, contextualize_q_prompt)
+history_aware_retriever = create_history_aware_retriever(llm, retriever, contextualize_q_prompt)
 
 # QA system prompt and chain
 qa_system_prompt = """ You are a highly skilled information retrieval assistant. Use the following context to answer questions effectively. 
@@ -206,7 +206,7 @@ async def websocket_endpoint(websocket: WebSocket):
                 await stream_response()
             except Exception as e:
                 print(f"Error during message handling: {e}")
-                await websocket.send_json({'response': "Something went wrong, Please try again.."})
+                await websocket.send_json({'response': "Something went wrong, Please try again." + str(e)})
     except WebSocketDisconnect:
         print(f"Client disconnected: {websocket.client}")
         if session_id: