Update functions.py

functions.py

@@ -58,7 +58,7 @@ time_str = time.strftime("%d%m%Y-%H%M%S")
 HTML_WRAPPER = """<div style="overflow-x: auto; border: 1px solid #e6e9ef; border-radius: 0.25rem; padding: 1rem; 
 margin-bottom: 2.5rem">{}</div> """
 
-memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
+memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True, output_key='answer')
 
 #Stuff Chain Type Prompt template
 
@@ -230,15 +230,15 @@ def embed_text(query,embedding_model,_docsearch):
                           temperature=0
                          )
 
-    chain = RetrievalQA.from_chain_type(llm=chat_llm, chain_type="stuff", 
-                                 retriever=_docsearch.as_retriever(), 
-                                 return_source_documents=True)
+    # chain = RetrievalQA.from_chain_type(llm=chat_llm, chain_type="stuff", 
+    #                              retriever=_docsearch.as_retriever(), 
+    #                              return_source_documents=True)
     
-    # chain = ConversationalRetrievalChain.from_llm(chat_llm, 
-    #                                               retriever= _docsearch.as_retriever(),
-    #                                               # condense_question_prompt = load_prompt(),
-    #                                               memory = memory,
-    #                                               return_source_documents=True)
+    chain = ConversationalRetrievalChain.from_llm(chat_llm, 
+                                                  retriever= _docsearch.as_retriever(),
+                                                  qa_prompt = load_prompt(),
+                                                  memory = memory,
+                                                  return_source_documents=True)
     
     answer = chain({"query": query})