app.py

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

# Ensure the historical data is inserted into MongoDB if not already present.
insert_data_if_empty()

# (Optional) Connect to MongoDB for further visualization if needed.
collection = get_mongo_client()

st.subheader("💬 Chatbot with Analysis for Specific MongoDB Entries")
st.write("Ask me something (e.g., 'Provide analysis for the data entry 1 in the dataset'): ")
user_prompt = st.text_area("Your Query:")

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("### AI 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 valid query for analysis.")