Music Recommendation System 🎵

A personalized music recommendation MVP using Python and the Last.FM API, featuring a clean web UI, real-time API integration, user feedback, and engagement metrics. Includes a demo mode that boosts metrics for Taylor Swift for the username suketh11.

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🚀 Features

• Last.FM API Integration: Fetches user listening data and similar artists/tracks
• Personalized Recommendations: Based on your Last.FM history
• Modern Web UI: Responsive, Bootstrap-powered interface
• User Feedback: Like/dislike recommendations, tracked in real time
• Engagement Metrics: See your likes, dislikes, and engagement rate
• Demo Boost: For username suketh11, Taylor Swift and her songs are pre-liked for demo purposes

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🗂️ Project Structure

music-recommender/
├── app.py               # Main Flask app
├── recommender.py       # Recommendation logic & feedback
├── lastfm_client.py     # Last.FM API wrapper
├── templates/
│   └── index.html       # Main UI template
├── requirements.txt     # Dependencies
├── .env                 # Your API keys (not in repo)
└── README.md            # This file

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🛠️ Setup Instructions

1. Clone the repository

   git clone <repository-url>
   cd music-recommender

2. Create a virtual environment & activate it

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

   pip install -r requirements.txt

4. Create a .env file in the project root:

   LASTFM_API_KEY=your_api_key_here
   LASTFM_API_SECRET=your_api_secret_here
   FLASK_SECRET_KEY=your_secret_key_here
   

   • Get your Last.FM API credentials at: https://www.last.fm/api/account/create
   • Generate a Flask secret key: python -c "import secrets; print(secrets.token_hex(16))"

5. Run the app

   python app.py

   • Visit http://localhost:5000 in your browser

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🧑‍💻 Usage

1. Enter your Last.FM username and click Get Recommendations
2. Like or dislike the recommended artists/tracks
3. Watch your metrics update in real time
4. Demo: Enter suketh11 to see Taylor Swift and her songs pre-liked, boosting metrics for demo purposes

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🏆 Demo Mode (Boosted Metrics)

• For the username suketh11, the app pre-populates likes for Taylor Swift and her top tracks.
• This is useful for demos, presentations, or testing the feedback/metrics features.
• To customize, edit the recommender.py file in the MusicRecommender.__init__ method.

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📝 Customization

• Change demo user or artist: Edit the user_feedback initialization in recommender.py
• Add more demo tracks: Add more entries to the likes set
• Remove demo mode: Remove or comment out the demo code in recommender.py

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📦 Dependencies

• Flask
• requests
• pandas
• python-dotenv
• plotly
• numpy
• scikit-learn
• pylast

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🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to your branch
5. Open a Pull Request

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📄 License

MIT License

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🙏 Acknowledgments

• Last.FM API
• Flask
• Bootstrap