Macscribe

Macscribe is a command-line tool for transcribing audio from YouTube videos, Apple Podcast episodes, and local audio/video files. It downloads audio from URLs or processes local files, transcribes them using a state-of-the-art ML model, and copies the transcription directly to your clipboard for easy use.

Features

• Multi-Platform Support: Accepts YouTube, Apple Podcast, and X URLs.
• Local File Support: Transcribes local audio files (MP3, WAV, FLAC, M4A, OGG, WMA) and video files (MP4, MOV, AVI, MKV, WEBM, M4V, WMV).
• Automated Audio Processing: Downloads high-quality audio from URLs or processes local files directly.
• State-of-the-Art Transcription: Utilizes mlx-whisper for accurate and fast transcription.
• Clipboard Integration: Automatically copies the transcript to your clipboard.
• Customizable Models: Option to specify a different Hugging Face model for transcription.
• Simple CLI Interface: Easy-to-use command-line interface built with Typer.

Installation

Macscribe can be installed using pip. Ensure you have Python 3.12 or later installed, then run:

pip install macscribe

This will install Macscribe along with its dependencies, including yt-dlp, mlx-whisper, and typer.

Usage

Once installed, you can run Macscribe directly from the command line. The basic usage is:

macscribe <INPUT> [--model MODEL]

Arguments:

• <INPUT>: Either a URL (YouTube, Apple Podcast, X) or path to a local audio/video file.
• --model MODEL: (Optional) The Hugging Face model to use for transcription.
  Defaults to "mlx-community/whisper-large-v3-mlx" if not specified.

Examples:

1. Transcribe a YouTube video using the default model:

   macscribe https://www.youtube.com/watch?v=dQw4w9WgXcQ
   

2. Transcribe an Apple Podcast episode with a specific model:

   macscribe https://podcasts.apple.com/us/podcast/example-episode-url --model some/alternative-model
   

3. Transcribe a local audio file:

   macscribe /path/to/your/audio.mp3
   

4. Transcribe a local video file:

   macscribe /path/to/your/video.mp4
   

After transcription, the resulting text is automatically copied to your clipboard.

Contributing

Contributions are welcome! If you'd like to contribute to Macscribe, please follow these steps:

1. Fork the repository on GitHub.
2. Clone your fork and create a new branch for your feature or bugfix.
3. Make your changes, ensuring code quality and consistency.
4. Test your changes thoroughly.
5. Submit a pull request describing your changes and why they should be merged.

License

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

This README provides an introduction, key features, installation instructions, usage examples, contribution guidelines, and licensing information, offering a comprehensive guide to using and contributing to Macscribe.