🎬 Bangla Movie Reviewer

A full-stack web application for sentiment analysis of Bangla movie reviews using 6 different machine learning models.

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✨ Features

• 🤖 6 ML Models - Choose from Transformer, Deep Learning, and Classical ML models
• 🇧🇩 Bangla Support - Optimized for Bangla language sentiment analysis
• 🎨 Beautiful UI - Modern gradient theme with custom dropdown
• 📊 Word Highlighting - See which words influenced the prediction
• 📈 Confidence Scores - Get prediction confidence percentages
• 📜 Analysis History - Track your previous analyses
• ⚡ Fast & Responsive - Smooth animations and instant feedback

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🚀 Quick Start

One Command Setup:

git clone <your-repo-url>
cd BanglaMovieReviewer
.\start.bat

That's it! Browser opens at http://localhost:3000

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🤖 Available Models

Model	Type	Icon	Description
BanglaBERT	Transformer	🇧🇩	Fine-tuned BERT for Bangla
mBERT	Transformer	🌍	Multilingual BERT
CNN	Deep Learning	🧠	Convolutional Neural Network
Masked_LSTM	Deep Learning	🔄	Recurrent Neural Network
LightGBM	Classical ML	⚡	Gradient Boosting
Logistic Regression	Classical ML	📊	Linear Classifier

All models hosted on Hugging Face: shksabbir7

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📸 Screenshots

Home Page

Analyzer with Model Dropdown

History Page

Positive Result

Negative Result

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🛠️ Tech Stack

Backend:

• Framework: Django 4.2.7
• API: Django REST Framework
• ML Libraries: Transformers, TensorFlow, PyTorch, LightGBM, Scikit-learn
• Model Hub: Hugging Face Hub
• Database: SQLite

Frontend:

• Framework: React 18.2
• HTTP Client: Axios
• Icons: Lucide React
• Routing: React Router
• Styling: Custom CSS with gradients

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📋 Prerequisites

• Python: 3.8 or higher
• Node.js: 14 or higher
• RAM: 4GB minimum (8GB recommended)
• Internet: Required for first run (model download)

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🔧 Installation

Option 1: Automated Setup (Recommended)

# Clone repository
git clone <your-repo-url>
cd BanglaMovieReviewer

# Run setup script (first time: 10-15 minutes)
.\run_all.bat

Option 2: Manual Setup

Backend:

cd backend
python -m venv venv
call venv\Scripts\activate.bat
pip install -r requirements.txt
python manage.py migrate
python manage.py runserver

Frontend:

cd frontend
npm install
npm start

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🎯 Usage

1. Start Application:

   .\start.bat

2. Open Browser: http://localhost:3000

3. Select Model: Choose from dropdown (6 models)

4. Enter Review: Type Bangla movie review (max 5000 chars)

5. Analyze: Click "বিশ্লেষণ করুন"

6. View Results:

   • Sentiment (Positive/Negative/Neutral)
   • Confidence percentage
   • Word importance scores
   • Color-coded word highlighting

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🧪 Testing

Automated Tests:

cd backend
call venv\Scripts\activate.bat
python auto_test.py

Tests Include:

• ✅ Backend connection
• ✅ Model availability (6 models)
• ✅ Valid analysis
• ✅ Input validation
• ✅ Edge cases
• ✅ All models working

Expected: 7/7 tests pass

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📁 Project Structure

BanglaMovieReviewer/
├── backend/              # Django backend
│   ├── sentiment_api/   # Main API app
│   ├── config/          # Django settings
│   └── requirements.txt # Python dependencies
├── frontend/            # React frontend
│   ├── src/            # Source code
│   └── package.json    # Node dependencies
├── docs/               # Documentation
├── screenshots/        # UI screenshots
├── start.bat          # Quick start script
└── run_all.bat        # Full setup script

Detailed Structure: See PROJECT_DOCUMENTATION.md

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🌐 API Endpoints

Base URL: http://localhost:8000/api/sentiment

Method	Endpoint	Description
GET	/models/	List available models
POST	/analyze/	Analyze sentiment
GET	/history/	Get analysis history

Full API Docs: See docs/API_DOCUMENTATION.md

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🎨 Features in Detail

Custom Model Dropdown:

• 🎯 6 models with unique icons
• 💫 Smooth animations
• 🎨 Gradient background
• ✨ Hover effects
• 🔍 Active state highlighting

Input Validation:

• ✅ Empty text detection
• ✅ Character limit (5000)
• ✅ Real-time counter
• ✅ Error messages in Bangla

Results Display:

• 📊 Sentiment classification
• 💯 Confidence percentage
• 🎨 Word highlighting
• 📈 Importance scores
• 🔄 Easy model switching

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🚀 Deployment

Hugging Face Models:

All models automatically download from Hugging Face on first use. No large files in repository!

Environment Variables:

DJANGO_SECRET_KEY=your-secret-key
DEBUG=False
ALLOWED_HOSTS=your-domain.com

Deploy to:

• Heroku
• Railway
• Render
• AWS
• Google Cloud

Deployment Guide: See docs/DEPLOYMENT.md

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📚 Documentation

• PROJECT_DOCUMENTATION.md - Complete project overview
• SETUP_GUIDE.md - Detailed setup instructions
• docs/API_DOCUMENTATION.md - API reference
• docs/TROUBLESHOOTING.md - Common issues

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🤝 Contributing

1. Fork the repository
2. Create feature branch (git checkout -b feature/AmazingFeature)
3. Commit changes (git commit -m 'Add AmazingFeature')
4. Push to branch (git push origin feature/AmazingFeature)
5. Open Pull Request

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🐛 Troubleshooting

Backend won't start:

cd backend
call venv\Scripts\activate.bat
pip install -r requirements.txt
python manage.py migrate

Frontend won't start:

cd frontend
npm install
npm start

Models not downloading:

• Check internet connection
• Verify Hugging Face is accessible
• Wait patiently (first download takes 2-3 min per model)

More Solutions: See docs/TROUBLESHOOTING.md

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📊 Model Performance

Model	Accuracy	Speed	Size
BanglaBERT	⭐⭐⭐⭐⭐	⭐⭐⭐	Large
mBERT	⭐⭐⭐⭐	⭐⭐⭐	Large
CNN	⭐⭐⭐⭐	⭐⭐⭐⭐	Medium
Masked_LSTM	⭐⭐⭐⭐	⭐⭐⭐	Medium
LightGBM	⭐⭐⭐	⭐⭐⭐⭐⭐	Small
Logistic Regression	⭐⭐⭐	⭐⭐⭐⭐⭐	Small

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📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

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👨💻 Author

Hugging Face Models: shksabbir7

Models:

• bangla-movie-sentiment-banglabert
• bangla-movie-sentiment-mbert
• bangla-movie-sentiment-cnn
• bangla-movie-sentiment-lstm
• bangla-movie-sentiment-lightgbm
• bangla-movie-sentiment-logreg

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🙏 Acknowledgments

• Hugging Face for model hosting
• Django & React communities
• Bangla NLP community
• All contributors

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📞 Support

• Issues: GitHub Issues
• Documentation: docs/
• Email: your-email@example.com

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🎉 Quick Commands

# First time setup
.\run_all.bat

# Daily usage
.\start.bat

# Run tests
cd backend && python auto_test.py

# Stop servers
# Close both terminal windows

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Made with ❤️ for Bangla NLP

Star ⭐ this repo if you find it useful!