Update app.py

app.py

@@ -4,9 +4,9 @@ import langchain
 
 from langchain_community.llms import HuggingFaceEndpoint
 from langchain_community.vectorstores import Chroma # Light-weight and in memory
-#from langchain.chains import RetrievalQA
-from langchain.chains import ConversationalRetrievalChain
-from langchain.memory import ConversationBufferMemory
+from langchain.chains import RetrievalQA
+#from langchain.chains import ConversationalRetrievalChain
+#from langchain.memory import ConversationBufferMemory
 
 
 # Authentication for Huggingface API
@@ -56,23 +56,17 @@ vectordb = Chroma(
 
 # Adding memory
 
-memory = ConversationBufferMemory(
-    memory_key="chat_history",
-    return_messages=True
-)
+#memory = ConversationBufferMemory(memory_key="chat_history",return_messages=True)
 
 
 title = "Q&A  on enterprise data"
 description = "Implementation of Open Source RAG on Private Document"
 
 def quena(question):
-  #qa_chain = RetrievalQA.from_chain_type(llm, retriever=vectordb.as_retriever(), return_source_documents=True)
-  qa_chain =  ConversationalRetrievalChain.from_llm(llm,
-                                                    retriever=vectordb.as_retriever(search_type="mmr",search_kwargs={"k": 10, "fetch_k":15} ), # "k":2, "fetch_k":3
-                                                    memory=memory
-                                                   )  
-  result = qa_chain.invoke({"question": question})
-  return result['answer']
+  qa_chain = RetrievalQA.from_chain_type(llm, retriever=vectordb.as_retriever(search_type="mmr",search_kwargs={"k": 8, "fetch_k":12}), return_source_documents=True)
+  #qa_chain =  ConversationalRetrievalChain.from_llm(llm,retriever=vectordb.as_retriever(search_type="mmr",search_kwargs={"k": 10, "fetch_k":15} ),memory=memory)  
+  result = qa_chain.invoke({"query": question}) # qa_chain.invoke({"question": question})
+  return result["result"] # result['answer']
     
 demo=gr.Interface(fn=quena,
                   inputs=gr.Textbox(lines=10,placeholder='''Write your question inside double quotation..Type the Sample Question:\n