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 nltk
from nltk.sentiment import SentimentIntensityAnalyzer

def get_sentiment(text):
    sid = SentimentIntensityAnalyzer()
    sentiment_scores = sid.polarity_scores(text)
    compound_score = sentiment_scores['compound']
    if compound_score >= 0.05:
        return 'positive'
    elif compound_score <= -0.05:
        return 'negative'
    else:
        return 'neutral'

def add_sentiment_emoji(text, sentiment):
    emoji_mapping = {
        'positive': '😄',
        'negative': '😞',
        'neutral': '😐'
    }
    emoji = emoji_mapping.get(sentiment, '')
    return f"{text} {emoji}"

import os 
import sys
import pandas as pd


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"]


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

if user_api_key is not None and user_api_key.strip() != "":
    os.environ["OPENAI_API_KEY"] =user_api_key
    
    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())


    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")

else:
    st.text("Please enter your OpenAI API key above.")