app14

app.py

@@ -104,14 +104,28 @@ qa_chain = ConversationalRetrievalChain.from_llm(
     get_chat_history = lambda h : h
 )
 
-def qa_response(user_message, chat_history, context):
-    response = qa_chain.predict(user_message, chat_history, context=context)
-    return response
 
-chatbot_gradio_app = gr.ChatInterface(fn=qa_response)
+def chat_interface(inputs):
+    question = inputs["question"]
+    chat_history = inputs["chat_history"]
+    # Assuming `chain` is your instance of ConversationalRetrievalChain
+    result = qa_chain.run({"question": question, "chat_history": chat_history})
+    return result["answer"]
+
+chatbot_gradio_app = gr.Interface(
+    fn=chat_interface, 
+    inputs=[
+        gr.inputs.Textbox(lines=1, label="Question"),
+        gr.inputs.Textbox(lines=5, label="Chat History"),
+    ], 
+    outputs="text"
+)
 
 # Combine both interfaces into a single app
-gr.TabbedInterface(
+app=gr.TabbedInterface(
     [image_gradio_app, chatbot_gradio_app],
     tab_names=["image","chatbot"]
-).launch()
+)
+
+app.queue()
+app.launch()