🎵 Moodify AI

AI-powered music generation and remixing platform that creates and transforms audio based on moods and genres.

✨ Features

• 🎼 Generate Music - Create original tracks from mood, genre, and text prompts
• 🔄 Remix Audio - Transform existing audio to match different moods
• 📊 Analyze Audio - Extract detailed audio features and characteristics
• 🎨 Beautiful UI - Intuitive Streamlit interface with custom styling

🚀 Quick Start

# Clone and setup
git clone https://github.com/yourusername/moodify-ai.git
cd moodify-ai
python -m venv venv
source venv/bin/activate  # or venv\Scripts\activate on Windows
pip install -r requirements.txt

# Terminal 1 - Start Backend
cd backend
uvicorn main:app --reload --host 127.0.0.1 --port 8000

# Terminal 2 - Start Frontend
cd frontend
streamlit run app.py

Open http://localhost:8501 in your browser.

📁 Project Structure

moodify-ai/
├── backend/
│   └── main.py           # FastAPI server
│   └── requirements.txt   #backend-only   
├── frontend/
│   └── app.py            # Streamlit UI
├── requirements.txt      # Dependencies frontend-only
└── venv/                # Virtual environment

🔧 Tech Stack

• Backend: FastAPI, PyTorch, Transformers (MusicGen), Librosa
• Frontend: Streamlit, Matplotlib
• Audio: Librosa, SoundFile, NumPy

📡 API Endpoints

API docs: http://localhost:8000/docs

🎮 Usage

Generate Music:

1. Select mood and genre
2. Add text description (optional)
3. Set duration (5-30 seconds)
4. Click "Generate Music"

Remix Audio:

1. Upload audio file (WAV/MP3/OGG)
2. Choose target mood
3. Click "Remix Audio"

Analyze Audio:

1. Upload audio file
2. Click "Analyze Audio"
3. View extracted features

⚠️ Important Notes

• First run downloads MusicGen model (~2.5 GB) - cached for reuse
• Backend must run before frontend
• FFmpeg required for audio processing
• GPU recommended for faster generation

🐛 Troubleshooting

Connection refused: Ensure backend is running on port 8000

Module not found: Activate venv and reinstall: pip install -r requirements.txt

Slow generation: Normal on CPU (2-5 min). Use GPU for faster results (10-30s)

Requirements Structure

The project uses separate dependency files for frontend and backend.

• Root requirements.txt → Frontend (Streamlit Cloud)
• backend/requirements.txt → Backend (FastAPI + MusicGen)

This separation avoids cloud deployment limitations and follows standard ML system design.

For technical documentation, see DOCUMENTATION.md