Update app.py

app.py

@@ -11,7 +11,7 @@ from langchain.document_loaders import TextLoader
 from langchain.chains.combine_documents import create_stuff_documents_chain
 from langchain_community.chat_message_histories.streamlit import StreamlitChatMessageHistory
 from langchain.prompts import PromptTemplate
-from langchain.chains.question_answering import load_qa_chain
+from langchain.chains import create_history_aware_retriever, create_retrieval_chain
 from langchain.vectorstores import Chroma
 from utills import load_txt_documents , split_docs,  load_uploaded_documents,retriever_from_chroma
 
@@ -72,11 +72,7 @@ which maybe reference context in the chat history, formulate a standalone questi
 which can be understood without the chat history. Do NOT answer the question,
 just reformulate it if needed and otherwise return it as is."""
 
-@st.cache_resource
-def create_history_aware_retriever():
-    return history_aware_retriever(llm, retriever, contextualize_q_system_prompt)
-
-ha_retriever = create_history_aware_retriever()
+ha_retriever = history_aware_retriever(llm, retriever, contextualize_q_system_prompt)
 
 qa_system_prompt = """You are an assistant for question-answering tasks. Use the following pieces of retrieved context to answer the question. If you don't know the answer, just say that you don't know. Be as informative as possible, be polite and formal.\n{context}"""
 
@@ -88,17 +84,10 @@ qa_prompt = ChatPromptTemplate.from_messages(
     ]
 )
 
-@st.cache_resource
-def create_question_answer_chain():
-    return create_stuff_documents_chain(llm, qa_prompt)
+question_answer_chain = create_stuff_documents_chain(llm, qa_prompt)
 
-question_answer_chain = create_question_answer_chain()
-
-@st.cache_resource
-def create_rag_chain():
-    return create_retrieval_chain(ha_retriever, question_answer_chain)
 
-rag_chain = create_rag_chain()
+rag_chain = create_retrieval_chain(ha_retriever, question_answer_chain)
 msgs = StreamlitChatMessageHistory(key="special_app_key")
 
 @st.cache_resource