Update app.py

app.py

@@ -76,14 +76,14 @@ embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-
 
 # Create a FAISS vector store and save embeddings
 db = FAISS.from_documents(data, embeddings)
-# db.save_local(DB_FAISS_PATH)
-
+db.save_local(DB_FAISS_PATH)
 
+db1 = db.load_local(DB_FAISS_PATH,embeddings)
 # Load the language model
 llm = load_llm()
 
 # Create a conversational chain
-chain = ConversationalRetrievalChain.from_llm(llm=llm, retriever=db.as_retriever())
+chain = ConversationalRetrievalChain.from_llm(llm=llm, retriever=db1.as_retriever())
 
 # Function for conversational chat
 def conversational_chat(query):