app13

app.py

@@ -104,16 +104,9 @@ qa_chain = ConversationalRetrievalChain.from_llm(
     get_chat_history = lambda h : h
 )
 
-def qa_response(question, chat_history):
-    # Add user's question to chat history
-    chat_history.append(("User", question))
-
-    # Get response from the conversational retrieval chain
-    response = qa_chain.invoke(chat_history)
-
-    # Extract and return the assistant's answer from the response
-    assistant_answer = response.get("answer")
-    return assistant_answer
+def qa_response(user_message,chat_history):
+    response = llm_chain.predict(user_message = user_message)
+    return response
 
 chatbot_gradio_app = gr.ChatInterface(fn=qa_response)