app.py

import streamlit as st
import pandas as pd
from db import insert_data_if_empty, get_mongo_client
from chatbot import chatbot_response

# Ensure that historical data is inserted if not already present.
insert_data_if_empty()

# Connect to MongoDB (optional: can be used for additional visualizations).
collection = get_mongo_client()

st.subheader("💬 Chatbot with Analysis for MongoDB Entries")
# Updated hint: ask for analysis of a specific data entry.
user_prompt = st.text_area("Ask me something (e.g., 'Provide analysis for the data entry 1 in the dataset'):")

if st.button("Get AI Response"):
    ai_response, sentiment_label, sentiment_confidence, topic_label, topic_confidence = chatbot_response(user_prompt)
    if ai_response:
        st.write("### Response:")
        st.write(ai_response)
        st.write("### Sentiment Analysis:")
        st.write(f"**Sentiment:** {sentiment_label} ({sentiment_confidence:.2f} confidence)")
        st.write("### Category Extraction:")
        st.write(f"**Detected Category:** {topic_label} ({topic_confidence:.2f} confidence)")
    else:
        st.warning("⚠️ Please enter a question or text for analysis.")