app13

app.py

@@ -104,11 +104,18 @@ qa_chain = ConversationalRetrievalChain.from_llm(
     get_chat_history = lambda h : h
 )
 
-def qa_response(user_message,'chat_history'):
-    response = qa_chain.predict(user_message = question)
-    return response
+def qa_response(question, chat_history):
+    # Add user's question to chat history
+    chat_history.append(("User", question))
 
-chatbot_gradio_app = gr.ChatInterface(qa_response)
+    # 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", "I don't know.")
+    return assistant_answer + " thanks for asking!"
+
+chatbot_gradio_app = gr.ChatInterface(fn=qa_response, live=True)
 
 # Combine both interfaces into a single app
 gr.TabbedInterface(