Choose the best installation method for your platform and performance needs.
| Platform | Recommended Method | GPU Support | Performance |
|---|---|---|---|
| macOS | Native Setup | ✅ Metal GPU | Best |
| Linux | Native Setup | ✅ NVIDIA GPU | Best |
| NixOS | System Integration | ✅ NVIDIA GPU | Best |
| Any Platform | Docker Setup | Good |
Note: Docker on macOS does not support GPU acceleration. For best performance on Mac, use the native setup.
Best performance with Metal GPU acceleration
- Full GPU acceleration for Ollama
- Optimized for Apple Silicon
- Native macOS integrations
Best performance with NVIDIA GPU acceleration
- NVIDIA GPU support
- Full system integration
- Optimal resource usage
Declarative system configuration with GPU support
- System-level service integration
- Declarative configuration
- Automatic service management
Universal solution, some limitations
- Works on any platform
- Consistent environment
⚠️ No GPU acceleration on macOS⚠️ Limited GPU support on other platforms
All installation methods set up these services:
- 🧠 Ollama - LLM server (gemma3:4b model)
- 🎤 Wyoming Faster Whisper - Speech-to-text
- 🗣️ Wyoming Piper - Text-to-speech
- 👂 Wyoming OpenWakeWord - Wake word detection
All methods use the same ports:
- Ollama (LLM):
11434 - Whisper (ASR):
10300 - Piper (TTS):
10200 - OpenWakeWord:
10400
Once services are running, install the agent-cli package:
# Using uv (recommended)
uv tools install agent-cli
# Using pip
pip install agent-cliThen test with:
agent-cli autocorrect --help- Check the troubleshooting section in your chosen installation guide
- Open an issue on GitHub