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# How to Deploy a Long-Running AI Agent Gateway with nanobot
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The nanobot gateway is the long-running process behind WebUI sessions, chat app
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messages, automations, local triggers, and WebSocket delivery.
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## What you will build
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- a configured nanobot instance
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- a gateway process that survives terminal exits
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- a service or container deployment path
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## When to use this
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Deploy the gateway when nanobot must keep receiving messages or running
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automations after a one-off CLI command ends.
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## Install
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```bash
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python -m pip install nanobot-ai
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nanobot onboard --wizard
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nanobot agent -m "Hello!"
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```
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## Minimal working example
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Start the gateway in the foreground:
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```bash
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nanobot gateway
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```
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For browser usage, the WebUI launcher can manage the gateway:
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```bash
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nanobot webui --background
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```
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For server usage, configure Docker, systemd, or macOS LaunchAgent from the
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deployment reference.
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## Production notes
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- Keep config and workspace paths explicit in services.
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- Persist `~/.nanobot/config.json`, the workspace, sessions, and memory files.
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- Use one process per config/workspace pair.
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- Expose only the ports required by the surfaces you use.
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## Security notes
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- Bind local-only surfaces to `127.0.0.1`.
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- Add an API key before exposing `nanobot serve` beyond localhost.
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- Restrict chat app access and workspace tools before putting the gateway on a
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shared server.
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## Troubleshooting
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- Use `nanobot status` with the same config/workspace as the service.
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- Check service logs for provider, port, channel, and permission errors.
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- If WebUI works locally but not remotely, verify host binding, token settings,
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and firewall rules.
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## Related nanobot docs
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- [Deploy nanobot gateway](./deploy-nanobot-gateway.md)
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- [Deployment](../deployment.md)
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- [Multiple Instances](../multiple-instances.md)
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- [WebUI](../webui.md)
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