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| import streamlit as st | |
| import pandas as pd | |
| from db import insert_data_if_empty, get_mongo_client | |
| from chatbot import chatbot_response # Import chatbot functionality | |
| # 1. Ensure the sentiment140 dataset is inserted into MongoDB | |
| insert_data_if_empty() | |
| # 2. MongoDB Connection | |
| collection = get_mongo_client() | |
| st.subheader("💬 Chatbot with Sentiment & Topic Analysis") | |
| # User input for chatbot | |
| user_prompt = st.text_area("Ask me something:") | |
| if st.button("Get AI Response"): | |
| # Generate real-time AI response, sentiment, and topic extraction | |
| 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)") | |
| # 3. Historical Insight: Compare with historical data from sentiment140.csv | |
| historical_data = list(collection.find({}, {"_id": 0})) | |
| if historical_data: | |
| df = pd.DataFrame(historical_data) | |
| # Assume the CSV has a 'sentiment' column with numeric labels: | |
| # 0: Negative, 2: Neutral, 4: Positive. | |
| if 'sentiment' in df.columns: | |
| sentiment_map = {0: "Negative", 2: "Neutral", 4: "Positive"} | |
| # Ensure the sentiment column is numeric and map it to readable labels | |
| df['sentiment_label'] = df['sentiment'].astype(int).map(sentiment_map) | |
| matching_count = df[df['sentiment_label'] == sentiment_label].shape[0] | |
| st.write("### Historical Insights:") | |
| st.info(f"There are {matching_count} tweets in our dataset with a {sentiment_label} sentiment.") | |
| else: | |
| st.warning("Historical data does not contain a sentiment field.") | |
| else: | |
| st.warning("No historical data available.") | |
| else: | |
| st.warning("⚠️ Please enter a question or text for analysis.") | |