🎤 Whisper Transcriber Web App

A modern web application for transcribing audio files using OpenAI's Whisper API

---

🎵 Convert your audio files to text with AI-powered transcription
🌐 Beautiful web interface accessible from any device
⚡ Fast, secure, and optimized for large files

---

A modern web application for transcribing audio files using OpenAI's Whisper API. This application provides a beautiful, responsive web interface that replaces the original tkinter GUI.

Features

• 🎤 Audio Transcription: Convert audio files to text using OpenAI's Whisper API
• 🌐 Web Interface: Modern, responsive web UI accessible from any browser
• 📁 Drag & Drop: Easy file upload with drag and drop support
• 📱 Mobile Friendly: Responsive design that works on all devices
• 💾 Download Transcripts: Save transcription results as text files
• 🔒 Secure: File validation and secure handling
• ⚡ Fast: Optimized for quick transcription processing
• ✂️ Audio Trimming: Option to trim audio to first 10 minutes to save API costs
• 🗜️ Smart Compression: Automatically compresses large files to meet Whisper's 25MB limit
• 📦 Intelligent Chunking: Splits very large files into manageable chunks for processing

Supported Audio Formats

• MP3
• WAV
• M4A
• FLAC
• OGG
• WEBM
• MP4

Prerequisites

• Python 3.7 or higher
• OpenAI API key

Installation

🪟 Windows Users (Recommended)

Quick Installation: Double-click install_windows.bat and follow the prompts!

For detailed Windows instructions, see README_WINDOWS.md or WINDOWS_INSTALL.md

🐧 Linux/macOS Users

1. Clone or download the project files

2. Install dependencies:

   pip install -r requirements.txt

3. Set up your OpenAI API key:

   export OPENAI_API_KEY="your-api-key-here"

   Or create a .env file in the project directory:

   OPENAI_API_KEY=your-api-key-here
   

Usage

1. Start the web server:

   python web_app.py

2. Open your browser and navigate to:

   http://localhost:5000
   

3. Upload an audio file:

   • Click the upload area to browse for files
   • Or drag and drop an audio file directly onto the upload area
   • File size limit: Up to 100MB (automatically optimized for Whisper's 25MB limit)

4. Transcribe:

   • Click the "Transcribe Audio" button
   • Wait for the transcription to complete
   • View the results in the transcript area

5. Audio Trimming (Optional):

   • Check "Trim to first 10 minutes" to save API costs
   • Useful for long audio files where you only need the beginning
   • Automatically converts trimmed audio to WAV format for optimal processing

6. File Optimization (Automatic):

   • Compression: Large files are automatically compressed to MP3 format
   • Chunking: Very large files are split into 10-minute chunks
   • Quality Optimization: Audio is optimized for Whisper (16kHz, mono)
   • Smart Processing: Only applies optimization when needed

7. Download:

   • Click "Download Transcript" to save the transcription as a text file
   • Use "Clear" to start over with a new file

File Structure

transcriber/
├── web_app.py          # Main Flask application
├── requirements.txt    # Python dependencies
├── templates/
│   └── index.html     # Web interface template
├── uploads/           # Temporary file storage (created automatically)
└── README.md          # This file

Configuration

The application can be configured by setting environment variables:

• OPENAI_API_KEY: Your OpenAI API key (required)
• SECRET_KEY: Flask secret key (optional, defaults to development key)
• MAX_CONTENT_LENGTH: Maximum file upload size (default: 50MB)

Security Features

• File type validation
• Secure filename handling
• Automatic cleanup of uploaded files
• Maximum file size limits
• Input sanitization

Troubleshooting

Common Issues

1. "OpenAI API key not configured"

   • Make sure you've set the OPENAI_API_KEY environment variable
   • Or create a .env file with your API key

2. "Invalid file type"

   • Ensure you're uploading a supported audio format
   • Check that the file extension is correct

3. "File too large"

   • The maximum file size is 100MB
   • Files are automatically compressed and chunked if needed
   • Consider using the trim option for very long files

4. "Transcription fails"

   • Check your internet connection
   • Verify your OpenAI API key is valid and has sufficient credits
   • Ensure the audio file is not corrupted
   • Large files may take longer to process due to compression/chunking

Getting Help

If you encounter issues:

1. Check the browser's developer console for error messages
2. Verify your OpenAI API key is working
3. Try with a smaller audio file first

Development

To run in development mode:

python web_app.py

The application will run on http://localhost:5000 with debug mode enabled.

Production Deployment

For production deployment:

1. Set a proper SECRET_KEY
2. Use a production WSGI server (e.g., Gunicorn)
3. Configure proper logging
4. Set up HTTPS
5. Consider using a reverse proxy (e.g., Nginx)

Example with Gunicorn:

pip install gunicorn
gunicorn -w 4 -b 0.0.0.0:5000 web_app:app

License

This project is open source and available under the MIT License.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.