Preset: OpenClaw AI Compute Gateway {#openclaw_basic}
Deploy OpenClaw AI messaging gateway, with optional local AI model powered by your device's GPU.
| Device | Purpose |
|---|
| reComputer Jetson | Runs OpenClaw gateway and local AI model with GPU acceleration |
What you'll get:
- AI chatbot gateway supporting 20+ messaging platforms
- Optional local AI model running on device GPU — no data leaves your network
- Web management interface for configuration
Requirements: Docker installed · Internet access (for first-time image download)
Step 1: Deploy OpenClaw {#deploy_openclaw type=docker_deploy required=true config=devices/local.yaml}
Deploy the OpenClaw AI gateway. If local AI model is enabled, it will be started and configured automatically.
Target: Local Deployment {#local type=local config=devices/local.yaml default=true}
Deploy on your reComputer Jetson device (running this software locally on the Jetson).
Wiring
- Ensure Docker is installed and running
- Optionally check Enable Local AI Model and select a model
- Click Deploy to start services
Deployment Complete
- Copy the Gateway Token shown in the deployment log
- Open http://localhost:18789 in your browser
- Go to the Overview page (left sidebar → Overview under "Control")
- In the Gateway Access section, paste the token into the Gateway Token field
- Click Connect to authenticate
- Connect your first messaging channel (WeChat, Telegram, Discord, etc.)
- If local AI model is enabled, it's already configured — select it when creating an agent
Troubleshooting
| Issue | Solution |
|---|
| Port 18789 already in use | Stop the service occupying port 18789, or check if OpenClaw is already running |
| Docker not found | Install Docker Desktop and ensure it is running |
| Model download slow | Large models take time; check your internet connection |
| OpenClaw container keeps restarting | Check logs: docker logs openclaw-gateway |
Target: Remote Deployment (Jetson) {#jetson_remote type=remote config=devices/jetson.yaml}
Deploy to a reComputer Jetson device over SSH, with GPU-accelerated local AI model.
Wiring
- Connect reComputer Jetson to the same network as your deployment machine
- Enter Jetson IP address, SSH username, and password
- Optionally check Enable Local AI Model and select a model
- Click Deploy to start services
Resource requirements: OpenClaw only needs 12GB disk + 4GB RAM; with Ollama needs 20GB disk + 8GB RAM.
Deployment Complete
- Copy the Gateway Token shown in the deployment log
- OpenClaw requires localhost access. Option A: Connect a display to the Jetson, open a browser, and visit
http://localhost:18789; Option B: On your computer, run ssh -L 18789:localhost:18789 <username>@<jetson-ip>, then open http://localhost:18789 in your local browser
- Go to the Overview page (left sidebar → Overview under "Control")
- In the Gateway Access section, paste the token into the Gateway Token field
- Click Connect to authenticate
- Connect your first messaging channel
- If local AI model is enabled, it's already configured with GPU acceleration — select it when creating an agent
Troubleshooting
| Issue | Solution |
|---|
| SSH connection failed | Verify Jetson IP, username, password, and that SSH service is running |
| NVIDIA runtime not detected | Ensure NVIDIA container runtime is installed: nvidia-smi should work |
| Docker Compose unavailable | Install it: sudo apt-get install -y docker-compose-plugin |
| Model download slow | First download gets the full model; subsequent runs use cache |
| Not enough disk space | OpenClaw only needs at least 12GB free disk; enabling Ollama raises that to 20GB. Check with df -h / |
| Not enough system memory | OpenClaw only needs at least 4GB RAM; enabling Ollama raises that to 8GB. Check with awk '/^MemTotal:/ {print int(($2 + 1048575) / 1048576) "GB"}' /proc/meminfo |
| Port 11434 already in use | The deployer prefers its own Docker-managed Ollama runtime. It will try to stop a native Ollama first; if the port is still occupied, stop the other Ollama service/process on the Jetson and retry |
Preset: OpenClaw Gateway {#openclaw_recomputer_r}
Deploy OpenClaw AI messaging gateway on reComputer R series. Lightweight deployment — gateway only, no local AI model needed.
| Device | Purpose |
|---|
| reComputer R1100 / R2000 | Runs OpenClaw gateway services |
What you'll get:
- Chat with AI across 20+ messaging platforms (WeChat, Telegram, Discord, etc.)
- Manage all channels from a single web interface
- Connect cloud AI providers (OpenAI, Claude, etc.) for conversations
Requirements: Docker installed · Internet access (for first-time image download)
Step 1: Deploy OpenClaw {#deploy_openclaw_r type=docker_deploy required=true config=devices/recomputer_r_local.yaml}
Deploy the OpenClaw AI gateway on your reComputer R.
Target: Local Deployment {#r_local type=local config=devices/recomputer_r_local.yaml default=true}
Deploy on the machine you're currently using.
Wiring
- Ensure Docker is installed and running
- Click Deploy to start services
Deployment Complete
- Copy the Gateway Token shown in the deployment log
- Open http://localhost:18789 in your browser
- Go to the Overview page (left sidebar → Overview under "Control")
- In the Gateway Access section, paste the token into the Gateway Token field
- Click Connect to authenticate
- Connect your first messaging channel (WeChat, Telegram, Discord, etc.)
Troubleshooting
| Issue | Solution |
|---|
| Port 18789 already in use | Stop the service occupying port 18789, or check if OpenClaw is already running |
| Docker not found | Install Docker Desktop and ensure it is running |
| OpenClaw container keeps restarting | Check logs: docker logs openclaw-gateway |
Target: Remote Deployment {#r_remote type=remote config=devices/recomputer_r_remote.yaml}
Deploy to a reComputer R device over SSH.
Wiring
- Connect reComputer R to the same network as your deployment machine
- Enter device IP address, SSH username, and password
- Click Deploy to start services
Deployment Complete
- Copy the Gateway Token shown in the deployment log
- OpenClaw requires localhost access. Option A: Connect a display to the device, open a browser, and visit
http://localhost:18789; Option B: On your computer, run ssh -L 18789:localhost:18789 <username>@<device-ip>, then open http://localhost:18789 in your local browser
- Go to the Overview page (left sidebar → Overview under "Control")
- In the Gateway Access section, paste the token into the Gateway Token field
- Click Connect to authenticate
- Connect your first messaging channel
Troubleshooting
| Issue | Solution |
|---|
| SSH connection failed | Verify device IP, username, password, and that SSH service is running |
| Docker Compose unavailable | Install it: sudo apt-get install -y docker-compose-plugin |
| Not enough disk space | Need at least 4GB free; check with df -h / |
| OpenClaw container keeps restarting | Check logs: docker logs openclaw-gateway |
Deployment Complete
OpenClaw AI gateway is deployed. Follow the "Deployment Complete" instructions in the step above to log in, then start using it.
Try a Conversation
- Click Chat in the left sidebar and send a message to verify AI is responding
- If local AI model is enabled, it's already configured — no extra setup needed
Connect Messaging Platforms
- Click Channels in the left sidebar to add your messaging platform (WeChat, Telegram, Discord, etc.)
- Follow the on-screen instructions to authorize the platform
- Send a test message through the connected platform
Next Steps
