A lightweight macOS menu bar app for quick audio transcription using OpenAI Whisper, Google Gemini, Local WhisperKit, or Nvidia Parakeet. Press a hotkey, record your thoughts, and get instant text that's automatically copied to your clipboard.

• 🎯 Quick Access: Global hotkey (⌘⇧Space) to start recording from anywhere
• 🎙️ Menu Bar App: Lives quietly in your menu bar, no dock icon
• 🚀 Instant Transcription: Powered by OpenAI Whisper, Google Gemini, Local WhisperKit with CoreML, or Parakeet-MLX
• 📋 Smart Paste: Transcribed text is automatically copied and can be pasted
• 🔈 Visual and Sound Feedback: Real-time audio level indicator while recording, chime when finished transcription
• ⌨️ Keyboard Shortcuts: Space to start/stop recording, ESC to cancel
• 💬 User Guidance: Clear on-screen instructions for all actions
• 🌓 Dark Mode: Beautiful native macOS design that adapts to your system
• 🔐 Secure: API keys stored in macOS Keychain
• 🔒 Privacy-First: Local transcription option keeps audio on your device
• ⚡ Lightweight: Minimal resource usage, starts with your Mac

• macOS 14.0 (Sonoma) or later
• OpenAI API key, Google Gemini API key, Local Whisper (no API key required), or Parakeet with Python
• Swift 5.9+ (for building from source)

1. Download the latest release from Releases
2. Drag AudioWhisper.app to your Applications folder
3. Launch and configure your API key through the settings

# Clone the repository
git clone https://github.com/mazdak/AudioWhisper.git
cd AudioWhisper

# Build the app
./build.sh

# Copy to Applications
cp -r AudioWhisper.app /Applications/

Local WhisperKit (Privacy-First)

• No API key required
• Audio never leaves your device
• CoreML hardware acceleration with Neural Engine support
• Choose from 6 different model sizes (39MB to 2.9GB)
• Models download automatically on first use

Local Parakeet (VERY Fast, English only, Privacy-First)

• No API key required
• Audio never leaves your device
• MLX hardware acceleration
• ADVANCED: Make sure you have a Python installation on your machine: Parakeet MLX Instructions.
• Pick Parakeet (Advanced) and enter the full path to your Python binary

OpenAI (Recommended for Cloud)

1. Visit https://platform.openai.com/api-keys
2. Create a new API key
3. Copy the key starting with sk-

Google Gemini

1. Visit https://makersuite.google.com/app/apikey
2. Create a new API key
3. Copy the key starting with AIza

Parakeet (Advanced)

• Local transcription using MLX framework for Apple Silicon optimization
• Requires Python with parakeet-mlx installed
• First use downloads ~600MB model from Hugging Face
• Setup instructions:

  # Install parakeet-mlx 
  uv add parakeet-mlx -U
  # or
  pip install parakeet-mlx

• Configure Python path in settings (usually /usr/bin/python3)

1. Launch AudioWhisper from Applications

2. The app will detect no API keys and show a welcome dialog

3. Click OK to open Settings

4. Choose your preferred provider:

   • Local WhisperKit: Select model size (downloads automatically, no API key needed)
   • OpenAI or Gemini: Paste your API key and click "Save"
   • Advanced: Parakeet 🦜: You need a working Python 3 installation with parakeet-mlx installed.

5. Toggle "Start at Login" if you want the app to launch automatically

1. Quick Recording: Press ⌘⇧Space anywhere to open the recording window
2. Start Recording: Click the blue microphone button or press Space
3. Stop Recording: Click the button again or press Space
4. Cancel: Press ESC at any time to dismiss the window
5. Auto-Paste: After transcription, text is automatically copied and pasted to the previous app

The app lives in your menu bar - click the microphone icon for quick access to recording or settings.

The recording window shows helpful instructions at the bottom:

• Ready: "Press Space to record • Escape to close"
• Recording: "Press Space to stop • Escape to cancel"
• Processing: "Processing audio..."
• Success: "Text copied to clipboard"

• Xcode 15.0 or later
• Swift 5.9 or later

# Clone the repository
git clone https://github.com/mazdak/AudioWhisper.git
cd AudioWhisper

# Run in development mode
swift run

# Build for release
swift build -c release

# Create full app bundle with icon
./build.sh

• Local Transcription: Choose Local WhisperKit to keep audio completely on your device
• Third Party Processing: OpenAI/Google options transmit audio for transcription
• Keychain Storage: API keys are securely stored in macOS Keychain
• No Tracking: We don't collect any usage data or analytics
• Microphone Permission: You'll be prompted once on first use
• Open Source: Audit the code yourself for peace of mind

"Unidentified Developer" Warning

• Right-click the app and select "Open" instead of double-clicking
• Click "Open" in the security dialog

Microphone Permission

• Go to System Settings → Privacy & Security → Microphone
• Ensure AudioWhisper is enabled

API Key Issues

• Verify your API key is correct in Settings
• Check your API quota/credits
• Try switching between OpenAI and Gemini

Recording Window Issues

• The window floats above all apps
• Click outside or press ESC to dismiss
• Use ⌘⇧Space to toggle visibility

Parakeet Setup Issues

• Ensure Python and parakeet-mlx are installed: python3 -c "import parakeet_mlx; print('OK')"
• Use "Test" button in settings to validate setup
• Check Python path is correct (usually /usr/bin/python3)
• For custom Python installations, specify full path to python executable

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

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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

• Alamofire - MIT License
• HotKey - MIT License
• WhisperKit - MIT License

• Built with SwiftUI and AppKit
• Uses OpenAI Whisper API for cloud transcription
• Supports Google Gemini as an alternative
• Local transcription powered by WhisperKit with CoreML acceleration
• Parakeet-MLX library for providing an easy accelerated Python interface

Made with ❤️ for the macOS community. If you find this useful, please consider starring the repository!