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A newer version of the Gradio SDK is available: 5.31.0

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metadata
title: Copyright Purpose Song Recommender
emoji: 🚀
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.24.0
app_file: app.py
pinned: false
short_description: AI-powered song recommendation engine for copyright purpose.

🎧 AI-Powered Song Recommender for Creative Projects

Welcome to the Copyrighted-Purpose Song Recommender — an intelligent assistant that helps you find the perfect song for your project using natural language.

Whether you're working on:

  • 🎬 a cinematic scene
  • 📱 a viral social media video
  • 📢 a brand campaign
  • 💔 an emotional film
  • etc etc

This app will analyze your needs and recommend songs using real music intelligence powered by:

  • Spotify audio features (valence, energy, tempo, danceability, etc.)
  • YouTube metadata (likes, comments, views)
  • LLM parsing (DeepSeek LLM for production, and still on research for compatible CPU model in HF demo.)

💡 How It Works

  1. Describe your project in natural language (e.g. "I want a sad, emotional breakup song for a scene for a K-drama").
  2. The system extracts structured intent like mood, tempo, genre, etc.
  3. Songs are recommended from our catalog based on matching features.
  4. ✅ You can give feedback (👍/👎) and export the results.
  5. As an overview of the outcome, go to notebook.ipynb -> 4.2 Temporary result alt text

✨ Features

  • 🎼 Valence + Danceability mood filtering
  • 🔁 Reference song similarity matching
  • 📊 YouTube popularity sorting
  • 🧠 LLM-powered input parsing
  • 💬 Feedback logging with export
  • 📁 Downloadable CSV for results & feedback

🚀 Try It Now

  1. Enter a description of your scene or campaign
  2. Click 🔍 Recommend Songs
  3. Optionally give feedback or export results

🛠️ Built With

  • Gradio – UI
  • Transformers – LLM model loading
  • LangChain – for prompt templates and parsing
  • Pandas – data filtering and exporting
  • DeepSeek LLM 7B Chat – for input parsing (production)
  • This space is using compatible model for CPU, yet still on research the best model.

📂 About the Dataset

  • The song catalog includes audio features from Spotify and engagement stats from YouTube.
  • You can modify or expand this dataset in your fork.

🙏 Credits

Developed by Shavira Z (personal project), for use in music publishing song user/clients.

📬 Feedback or Suggestions?

Feel free to reach out or leave an issue. We’re happy to collaborate or improve this experience!

Email: [email protected]

LinkedIn: https://linkedin.com/in/shavirazh

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference