Sentiment Insight | Dual-Model Sentiment Analysis

A professional-grade sentiment analysis web application featuring a split-model architecture (Traditional ML vs. Transformer Deep Learning). This tool provides real-time analysis, word importance visualization, and a modern, adaptive UI.

✨ Features

• Dual-Approach Analysis: Compare results from TF-IDF + Logistic Regression (speed) and Fine-tuned BERT (accuracy) simultaneously.
• Dynamic Theme System: Seamless toggle between professional Light Mode and sleek Dark Mode.
• Neutral Sentiment Mapping: Advanced threshold logic (60% confidence) to correctly identify neutral text like greetings and facts.
• Explainable AI (XAI): Visualize exactly which words pushed the sentiment in a specific direction using dynamic bar charts.
• Real-World Training: Includes a script to train your localized model on the IMDB Movie Reviews dataset (10k samples).

🚀 Quick Start

1. Install Dependencies

pip install -r requirements.txt

2. Prepare the Models (Choose One)

• The Pro Way (Recommended): Train the TF-IDF model on 10,000 real movie reviews:

  python train_tfidf_real.py

• The Quick Way: Create tiny placeholder models for immediate UI testing:

  python create_dummy_models.py

3. Launch the Backend

python main.py

The API serves at http://localhost:8000.

4. Open the App

Open index.html in any modern web browser.

📁 Project Structure

• main.py: FastAPI backend handling inference and text cleaning.
• train_tfidf_real.py: Training script for commercial-grade accuracy.
• index.html / style.css / script.js: Clean, responsive frontend with theme management.
• models/: Storage for pickled models and BERT checkpoints.
• IMPLEMENTATION_DETAILS.md: Deep-dive technical documentation.

🛠️ Technology Stack

• FastAPI (Backend)
• Scikit-learn (Classical ML)
• Vanilla CSS3 & JS (ES6+) (Frontend)