app.py

from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.chat_models import ChatOpenAI
from langchain.chains import ConversationalRetrievalChain
from langchain.document_loaders.csv_loader import CSVLoader
from langchain.vectorstores import FAISS
import tempfile 
from streamlit_chat import message
import streamlit as st

import os 
import sys
import pandas as pd

user_api_key = st.sidebar.text_input(
    label="#### Your OpenAI API key 👇",
    placeholder="Paste your openAI API key, sk-",
    type="password")

file_path='./personality_less.csv'


loader = CSVLoader(file_path=file_path, encoding="utf-8", csv_args={
                'delimiter': ','})

data = loader.load()

embeddings = OpenAIEmbeddings()
vectorstore = FAISS.from_documents(data, embeddings)

chain = ConversationalRetrievalChain.from_llm(
llm = ChatOpenAI(temperature=0.0,model_name='gpt-3.5-turbo'),
retriever=vectorstore.as_retriever())

def conversational_chat(query):    
    result = chain({"question": query, 
    "chat_history": st.session_state['history']})
    st.session_state['history'].append((query, result["answer"]))

    return result["answer"]

if 'history' not in st.session_state:
    st.session_state['history'] = []

    if 'generated' not in st.session_state:
        st.session_state['generated'] = ["Hello ! Ask me anything about " + " 🤗"]

    if 'past' not in st.session_state:
        st.session_state['past'] = ["Hey ! 👋"]
        
    #container for the chat history
    response_container = st.container()
    #container for the user's text input
    container = st.container()

with container:
    with st.form(key='my_form', clear_on_submit=True):
        
        user_input = st.text_input("Query:", placeholder="Talk about your csv data here (:", key='input')
        submit_button = st.form_submit_button(label='Send')
        
    if submit_button and user_input:
        output = conversational_chat(user_input)
        
        st.session_state['past'].append(user_input)
        st.session_state['generated'].append(output)

if st.session_state['generated']:
        with response_container:
            for i in range(len(st.session_state['generated'])):
                message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="big-smile")
                message(st.session_state["generated"][i], key=str(i), avatar_style="thumbs")