Update app.py

app.py

@@ -20,8 +20,9 @@ from langchain_community.vectorstores import FAISS
 
 from langchain.text_splitter import CharacterTextSplitter
 
-# from langchain.memory import ConversationBufferMemory
-# from langchain.chains import ConversationalRetrievalChain
+from langchain.memory import ConversationBufferMemory
+from langchain.chains import ConversationalRetrievalChain
+
 # from htmlTemplates import css, bot_template, user_template
 # from langchain.llms import HuggingFaceHub
 
@@ -74,20 +75,20 @@ def get_vectorstore(text_chunks):
 
     return vectorstore
 
-# def get_conversation_chain(vectorstore):
-#     # llm = ChatOpenAI()
-#     #  llm = HuggingFaceHub(repo_id="google/flan-t5-xxl", model_kwargs={"temperature":0.5, "max_length":512})
-#     #  google/bigbird-roberta-base     facebook/bart-large
-#     llm = HuggingFaceHub(repo_id="google/flan-t5-xxl", model_kwargs={"temperature": 0.5, "max_length": 512})
-
-#     memory = ConversationBufferMemory(
-#         memory_key='chat_history', return_messages=True)
-#     conversation_chain = ConversationalRetrievalChain.from_llm(
-#         llm=llm,
-#         retriever=vectorstore.as_retriever(),
-#         memory=memory,
-#     )
-#     return conversation_chain
+def get_conversation_chain(vectorstore):
+    # llm = ChatOpenAI()
+    #  llm = HuggingFaceHub(repo_id="google/flan-t5-xxl", model_kwargs={"temperature":0.5, "max_length":512})
+    #  google/bigbird-roberta-base     facebook/bart-large
+    llm = HuggingFaceHub(repo_id="google/flan-t5-xxl", model_kwargs={"temperature": 0.5, "max_length": 512})
+
+    memory = ConversationBufferMemory(
+        memory_key='chat_history', return_messages=True)
+    conversation_chain = ConversationalRetrievalChain.from_llm(
+        llm=llm,
+        retriever=vectorstore.as_retriever(),
+        memory=memory,
+    )
+    return conversation_chain
 
 # def handle_userinput(user_question):