Update app.py

app.py

@@ -56,14 +56,23 @@ retriever = vectordb.as_retriever(
     search_type="similarity", search_kwargs={"k": 2}
 )
 
-from langchain.chains import RetrievalQA
-
+#from langchain.chains import RetrievalQA
 
+from langchain.chains import create_retrieval_chain
+from langchain.chains.combine_documents import create_stuff_documents_chain
+from langchain import hub
 
 READER_MODEL="HuggingFaceH4/zephyr-7b-beta"
 #HuggingFaceH4/zephyr-7b-beta
 #qa = ConversationalRetrievalChain.from_llm(llm=READER_MODEL,retriever=retriever,memory=memory)
-qa = RetrievalQA.from_chain_type(llm=READER_MODEL,chain_type="map_reduce",retriever=retriever,verbose=True)
+#qa = RetrievalQA.from_chain_type(llm=READER_MODEL,chain_type="map_reduce",retriever=retriever,verbose=True)
+
+retrieval_qa_chat_prompt = hub.pull("langchain-ai/retrieval-qa-chat")
+combine_docs_chain = create_stuff_documents_chain(
+    READER_MODEL, retrieval_qa_chat_prompt
+)
+qa = create_retrieval_chain(retriever, combine_docs_chain)
+
 result = qa(question)
 import gradio as gr
 gr.load("READER_MODEL").launch()