94 lines
2.2 KiB
Markdown
94 lines
2.2 KiB
Markdown
# YouTube Transcription with Whisper
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A web application that allows you to transcribe YouTube videos with OpenAI's Whisper speech-to-text model.
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## Features
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- Paste a YouTube URL and get a full transcription
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- Support for individual videos and playlists
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- Queue management with video thumbnails
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- Real-time progress updates
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- Download transcriptions in TXT and SRT formats
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- Clean, responsive user interface
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## Installation
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### Prerequisites
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- Python 3.7 or higher
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- FFmpeg (required for audio processing)
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- Git (optional, for cloning the repository)
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### Install FFmpeg
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#### macOS:
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```
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brew install ffmpeg
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```
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#### Ubuntu/Debian:
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```
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sudo apt update
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sudo apt install ffmpeg
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```
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#### Windows:
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Download from [FFmpeg's official website](https://ffmpeg.org/download.html) or install via Chocolatey:
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```
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choco install ffmpeg
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```
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### Setup Steps
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1. Clone the repository:
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```
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git clone https://github.com/yourusername/youtube-whisper-app.git
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cd youtube-whisper-app
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```
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2. Create a virtual environment:
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```
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python -m venv venv
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```
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3. Activate the virtual environment:
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- Windows: `venv\Scripts\activate`
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- macOS/Linux: `source venv/bin/activate`
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4. Install dependencies:
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```
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pip install -r requirements.txt
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```
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5. Run the application:
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```
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python app.py
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```
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6. Open your browser and navigate to http://127.0.0.1:5000
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## Usage
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1. Paste a YouTube URL into the input field (supports individual videos or playlists).
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2. Click "Transcribe" to start the process.
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3. Watch the progress in real-time with the queue display.
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4. Click on any queued video to see detailed status.
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5. Once completed, preview the transcription and download in your preferred format.
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## Note on YouTube Restrictions
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YouTube employs anti-bot measures that may block automated downloads. For best results:
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- Run the application locally on your personal computer
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- Use your browser's cookies with the `--cookies-from-browser` option
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- Access from a residential IP address
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## Technical Details
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- Backend: Flask with Flask-SocketIO for real-time updates
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- Audio download: yt-dlp for efficient YouTube download
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- Transcription: OpenAI's Whisper speech recognition model
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- Frontend: Vanilla JavaScript, CSS, and HTML
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## License
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MIT |