Installation Guide
Choose the best installation method for your platform and performance needs.
Quick Platform Guide
| 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 | ⚠️ Limited* | Good |
Warning
Docker on macOS does not support GPU acceleration. For best performance on Mac, use the native setup.
Installation Methods
🍎 macOS Native (Recommended)
Best performance with Metal GPU acceleration
- Full GPU acceleration for Ollama
- Optimized for Apple Silicon
- Native macOS integrations
🐧 Linux Native (Recommended)
Best performance with NVIDIA GPU acceleration
- NVIDIA GPU support
- Full system integration
- Optimal resource usage
❄️ NixOS System Integration
Declarative system configuration with GPU support
- System-level service integration
- Declarative configuration
- Automatic service management
🐳 Docker (Cross-platform)
Universal solution, some limitations
- Works on any platform
- Consistent environment
- ⚠️ No GPU acceleration on macOS
- ⚠️ Limited GPU support on other platforms
What Gets Installed
All installation methods set up these services:
- 🧠 Ollama - LLM server (gemma3:4b model)
- 🎤 Wyoming Whisper - Speech-to-text (faster-whisper on Linux/Intel, MLX Whisper on Apple Silicon)
- 🗣️ Wyoming Piper - Text-to-speech
- 👂 Wyoming OpenWakeWord - Wake word detection
Service Ports
All methods use the same ports:
- Ollama (LLM):
11434 - Whisper (ASR):
10300 - Piper (TTS):
10200 - OpenWakeWord:
10400
After Installation
Once services are running, install the agent-cli package:
Note
The -p 3.13 flag is required because some dependencies don't support Python 3.14 yet.
See uv issue #8206 for details.
Then test with:
Need Help?
- Check the troubleshooting section in your chosen installation guide
- Open an issue on GitHub