Metadata-Version: 2.4
Name: ai_music_remixer
Version: 3.0.0
Summary: AI-powered intelligent music remixer with optional neural transitions
Author: YourName
Author-email: you@example.com
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: pydub
Requires-Dist: librosa
Requires-Dist: soundfile
Requires-Dist: spleeter
Requires-Dist: numpy
Requires-Dist: scipy

# AI Music Remixer

AI-powered intelligent music remixer with optional neural transitions.

## Features

- Intelligent audio remixing using Spleeter for stem separation
- Optional PyTorch-based neural transition model for smoother transitions
- Beat-synchronized remixing with automatic tempo detection
- Command-line interface for easy usage
- Safe fallback to deterministic smoothing if neural model is unavailable

## Installation

```bash
pip install ai_music_remixer
```

For GPU support (optional):
```bash
pip install ai_music_remixer[gpu]
```

## Usage

### Command Line

Basic remix:
```bash
ai-remix input.mp3 -o output.wav
```

Beat-synchronized remix:
```bash
ai-remix input.mp3 --beats -o output.wav
```

With custom BPM:
```bash
ai-remix input.mp3 --beats --bpm 120 -o output.wav
```

### Python API

```python
from ai_music_remixer import ai_remix, ai_remix_beatsync

# Basic remix
ai_remix("input.mp3", "output.wav")

# Beat-synchronized remix
ai_remix_beatsync("input.mp3", "output.wav", beats_per_minute=120)
```

## Neural Transition Model

The package includes an optional PyTorch-based neural transition model. If you place a trained checkpoint file at `models/transition_ckpt.pt`, the remixer will automatically use it for smoother transitions. Without a checkpoint, the package falls back to deterministic Gaussian smoothing.

To train a model (requires PyTorch):
```bash
python -m ai_music_remixer.neural.train_transition
```

## Requirements

- Python >= 3.8
- pydub
- librosa
- soundfile
- spleeter
- numpy
- scipy

Optional:
- torch (for neural transitions)

## License

MIT

