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Source Code: examples/hardware_advisor_agent.py
The Hardware Advisor agent helps you figure out what size LLM your system can run by detecting your actual hardware capabilities.
Privacy-First: All hardware detection runs locally on your machine. No data leaves your system.

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Quick Start

This starts an interactive session where you can ask about your hardware and get language model recommendations.

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Example Interactions

Check your hardware:
Get recommendations:
Check specific models:

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How It Works

The agent uses three tools: The 70% Rule: Models should use less than 70% of available RAM to leave 30% overhead for inference operations (KV cache, context window, etc.).

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Requirements

  • GAIA installed: uv pip install amd-gaia
Hardware detection reads from the model server, but you don’t start that yourself — gaia daemon resolves, starts and supervises it.

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Troubleshooting

Error: Failed to get hardware information from Lemonade ServerYou shouldn’t have to start the model server yourself — gaia daemon resolves, starts and supervises it. So the question is why that didn’t happen.Start with the daemon, which reports the model server it supervises: gaia daemon statusIf no daemon is running, start it: gaia daemon startIf the daemon is up but the model server isn’t, the reason is in the daemon log: gaia daemon logs --lines 100The usual cause is that Lemonade isn’t installed at all. gaia init installs the server and pulls the model.
Possible causes:
  • Windows: PowerShell may be restricted. Run as administrator.
  • Linux: lspci not installed. Install with: sudo apt install pciutils
Note: The agent continues with CPU-only recommendations if GPU detection fails.
Requirements for NPU:
  • Ryzen AI processor (8000/9000 series)
  • NPU drivers installed
  • Lemonade Server configured for NPU
The agent works without NPU - it just won’t recommend NPU-accelerated models.

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Learn More

Build Your Own

Want to understand how this agent works or build something similar? Follow the step-by-step Hardware Advisor Playbook.