{"id":26772695,"url":"https://github.com/wearer-lab/transfer-learning","last_synced_at":"2025-10-28T16:47:57.477Z","repository":{"id":279807615,"uuid":"940045915","full_name":"Wearer-Lab/transfer-learning","owner":"Wearer-Lab","description":"A powerful CLI tool for processing videos and generating step-by-step guides using AI. 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This tool can handle both local video files and YouTube videos, extracting key frames and generating detailed guides using OpenAI's GPT-4 Vision API.\n\n## Features\n\n- Process local video files\n- Download and process YouTube videos\n- Extract frames at specified intervals\n- Generate step-by-step guides with AI analysis\n- Beautiful CLI interface with progress tracking\n- Support for both local and YouTube video sources\n- Built-in monitoring and metrics collection\n- Optimized performance with async processing\n\n## Installation\n\n1. Clone the repository:\n```bash\ngit clone https://github.com/Wearer-Lab/transfer-learning.git\ncd transfer-learning\n```\n\n2. Create a virtual environment and install dependencies using UV:\n```bash\npython -m venv .venv\nsource .venv/bin/activate  # On Windows, use `.venv\\Scripts\\activate`\npip install uv\nuv pip install -e .\n```\n\n3. Set up your OpenAI API key:\n```bash\necho \"OPENAI_API_KEY=your-api-key-here\" \u003e .env\n```\n\n## Usage\n\nThe CLI provides several commands for different operations:\n\n### Process a Local Video\n\nExtract frames from a local video file:\n\n```bash\ntransfer-learning process-video path/to/video.mp4 --output-dir output --batch-size 30\n```\n\n### Process a YouTube Video\n\nDownload and process a YouTube video:\n\n```bash\ntransfer-learning process-youtube \"https://youtube.com/watch?v=VIDEO_ID\" --output-dir output\n```\n\n### Generate a Guide\n\nGenerate a step-by-step guide from processed video frames:\n\n```bash\ntransfer-learning generate-guide output/processed_data --output-dir guides\n```\n\n### Complete YouTube Pipeline\n\nDownload a YouTube video and generate a guide in one command:\n\n```bash\ntransfer-learning youtube-guide \"https://youtube.com/watch?v=VIDEO_ID\" --output-dir output\n```\n\n### Transcribe Audio\n\nTranscribe audio from a video file:\n\n```bash\ntransfer-learning transcribe path/to/video.mp4 --output-dir transcripts\n```\n\n### Analyze Video Content\n\nAnalyze video content to extract key information:\n\n```bash\ntransfer-learning analyze path/to/video.mp4 --output-dir analysis\n```\n\n### Download Video\n\nDownload a video from YouTube or other supported platforms:\n\n```bash\ntransfer-learning download \"https://youtube.com/watch?v=VIDEO_ID\" --output-dir videos\n```\n\n## Command Options\n\nAll commands support various options. Use the `--help` flag to see available options for each command:\n\n```bash\ntransfer-learning process-video --help\n```\n\n## Monitoring and Metrics\n\nTransfer Learning includes built-in monitoring capabilities:\n\n- **Metrics Collection**: Performance metrics are collected during processing and saved to the `metrics` directory\n- **Logging**: Detailed logs are saved to the `logs` directory\n- **Progress Tracking**: Rich progress bars and status indicators in the terminal\n\nTo view collected metrics:\n\n```bash\ntransfer-learning config --show-metrics\n```\n\n## Output Format\n\nThe generated guide is saved as a JSON file with the following structure:\n\n```json\n{\n  \"title\": \"Process Title\",\n  \"description\": \"Overall process description\",\n  \"steps\": [\n    {\n      \"step_number\": 1,\n      \"title\": \"Step Title\",\n      \"description\": \"Step description\",\n      \"tools_used\": [\"tool1\", \"tool2\"],\n      \"duration\": 10.5,\n      \"key_points\": [\"point1\", \"point2\"],\n      \"timestamp\": 0.0\n    }\n  ],\n  \"principles\": [\n    {\n      \"name\": \"Principle Name\",\n      \"description\": \"Principle description\",\n      \"importance\": \"Why this principle matters\",\n      \"examples\": [\"example1\", \"example2\"]\n    }\n  ],\n  \"total_duration\": 120.5,\n  \"source_type\": \"local\",\n  \"source_path\": \"path/to/video.mp4\"\n}\n```\n\n## Development\n\nTo set up the development environment:\n\n1. Install development dependencies:\n```bash\nuv pip install -e \".[dev]\"\n```\n\n2. Run tests:\n```bash\npytest\n```\n\n3. Check code style:\n```bash\nruff check .\n```\n\n## Project Structure\n\n```\ntransfer-learning/\n├── data/               # Data storage directory\n├── docs/               # Documentation\n├── logs/               # Log files\n├── metrics/            # Metrics collection\n├── src/                # Source code\n│   └── transfer_learning/\n│       ├── core/       # Core processing modules\n│       ├── guide/      # Guide generation\n│       ├── models/     # AI model interfaces\n│       ├── monitoring/ # Monitoring and metrics\n│       ├── utils/      # Utility functions\n│       ├── cli.py      # CLI implementation\n│       └── config.py   # Configuration\n├── tests/              # Test suite\n├── .env                # Environment variables\n├── pyproject.toml      # Project configuration\n└── setup.py            # Package setup\n```\n\n## License\n\nThis project is licensed under the Eclipse Public License - v 2.0 - see the LICENSE file for details. 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