A Raycast extension that uses OpenAI's Whisper model for speech-to-text transcription, powered by whisper.cpp by Georgi Gerganov.
- Start/stop audio recording with customizable hotkeys (default: Cmd+T)
- High-performance speech recognition using whisper.cpp
- Optimized for Apple Silicon
- Supports various audio formats via FFmpeg
-
Clone this repository:
git clone https://github.com/yourusername/raycast-whisper-transcription.git -
Install FFmpeg:
brew install ffmpeg -
Set up whisper.cpp:
git clone https://github.com/ggerganov/whisper.cpp.git cd whisper.cpp make bash ./models/download-ggml-model.sh base.en -
Add the extension to Raycast:
- Open Raycast
- Go to Extensions > Script Commands
- Click the "+" button and select "Add Script Directory"
- Choose the directory containing this extension
-
Set up the hotkey:
- In Raycast, go to Extensions > Script Commands
- Find the Whisper Transcription command
- Click on it and assign your desired hotkey (e.g., Cmd+T)
After installation, you need to set up the environment variables. Copy the .env.example file to a new file named .env and fill in the following variables:
-
Copy the example file:
cp .env.example .env -
Edit the
.envfile and set the following variables:RAYCAST_SCRIPT_DIR=/path/to/your/raycast/extension/directory WHISPER_DIR=/path/to/whisper.cpp/main WHISPER_MODEL=/path/to/whisper.cpp/models/ggml-base.en.binReplace the paths with the actual locations on your system:
RAYCAST_SCRIPT_DIR: The directory where this Raycast extension is locatedWHISPER_DIR: The directory containing the whisper.cppmainexecutable (typically/path/to/whisper.cpp/main)WHISPER_MODEL: The full path to the Whisper model file (typically/path/to/whisper.cpp/models/ggml-base.en.bin)
Ensure that these paths are correct for your system setup. The extension will use these variables to locate the necessary files and directories.
- Press Cmd+T (or your custom hotkey) to start recording audio
- Press Cmd+T again to stop recording and start transcription
- The transcribed text will appear in Raycast
This extension leverages the high-performance C/C++ implementation of OpenAI's Whisper model provided by whisper.cpp. Key features include:
- Plain C/C++ implementation without dependencies
- Optimized for Apple Silicon via ARM NEON, Accelerate framework, Metal, and Core ML
- Mixed F16 / F32 precision
- 4-bit and 5-bit integer quantization support
- Zero memory allocations at runtime
- CPU and GPU inference support
MIT