Update app.py

app.py

@@ -97,43 +97,3 @@ if uploaded_file:
 # Maintain and display the chat history
                 message(st.session_state["generated"][i], key=str(i), avatar_style="thumbs")
             
-# Split the text into Chunks
-text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=20)
-text_chunks = text_splitter.split_documents(data)
-
-
-# COnverting the text Chunks into embeddings and saving the embeddings into FAISS Knowledge Base
-docsearch = FAISS.from_documents(text_chunks, embeddings)
-
-docsearch.save_local(DB_FAISS_PATH)
-
-
-#query = "What is the value of GDP per capita of Finland provided in the data?"
-
-#docs = docsearch.similarity_search(query, k=3)
-
-#print("Result", docs)
-
-
-
-qa = ConversationalRetrievalChain.from_llm(llm, retriever=docsearch.as_retriever())
-
-# Insert a chat message container.
-with st.chat_message("user"):
-   st.write("Hello 👋")
-   st.line_chart(np.random.randn(30, 3))
-
-# Display a chat input widget.
-st.chat_input("Say something")
-
-while True:
-    chat_history = []
-    #query = "What is the value of  GDP per capita of Finland provided in the data?"
-    query = input(f"Input Prompt: ")
-    if query == 'exit':
-        print('Exiting')
-        sys.exit()
-    if query == '':
-        continue
-    result = qa({"question":query, "chat_history":chat_history})
-    print("Response: ", result['answer'])