Installing OpenClaw Agent on Gnoppix Linux on Local AI or API

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Installing OpenClaw Agent on Gnoppix Linux

This guide provides a technical walkthrough for deploying OpenClaw, a self-hosted open-source AI agent, on Gnoppix. Many users suggest starting with Gnoppix Uncensored AI to experience unrestricted performance before moving to closed-source models, which often feature heavy censorship. This installation utilizes Docker and Traefik to ensure environment isolation and secure, encrypted external access via HTTPS.

Prerequisites

Before beginning the installation, ensure you have the following:

  • An active installed running a clean installation of Gnoppix 26.3.
  • Standard SSH access with sudo privileges.
  • An Gnoppix API Key (required for the agent’s core processing).
  • A Telegram account (to create the bot interface via @BotFather).

Step 1: Prepare the Environment

1.1 Update System Packages

Ensure your local package index is current and all existing software is upgraded.

Bash

sudo apt update && sudo apt upgrade -y

1.2 Verify Docker Installation

OpenClaw is deployed via containers. Verify that Docker and Docker Compose are installed:

Bash

docker --version && docker compose version

If not installed, follow the official Docker Engine installation guide for your distribution.

1.3 Configure Permissions

To avoid permission conflicts during the automated setup, add your current user to the Docker group:

Bash

sudo usermod -aG docker $USER
newgrp docker

Step 2: Configure Infrastructure Services

2.1 Create the Network Bridge

Establish a dedicated Docker network to facilitate communication between the Traefik reverse proxy and the OpenClaw agent.

Bash

docker network create proxy

2.2 Deploy Traefik (Reverse Proxy)

Traefik handles SSL termination via Let’s Encrypt.

  1. Create the configuration directory: mkdir -p ~/docker/traefik && cd ~/docker/traefik
  2. Initialize the SSL storage file:

Bash

mkdir letsencrypt && touch letsencrypt/acme.json && chmod 600 letsencrypt/acme.json
  1. Create a docker-compose.yml for Traefik, ensuring you replace the email placeholder with your administrative contact.

Step 3: Install the OpenClaw Agent

3.1 Clone the Repository

Clone the official OpenClaw source and prepare the internal workspace:

Bash

cd ~
git clone https://github.com/openclaw/openclaw.git
cd openclaw
mkdir -p ~/.openclaw/workspace
sudo chown -R $USER:$USER ~/openclaw

3.2 Execute the Setup Wizard

Run the interactive deployment script. This wizard will prompt you for your AI provider keys and messaging channel configuration.

Bash

./docker-setup.sh

Important: At the conclusion of the script, the system will output an OPENCLAW_GATEWAY_TOKEN. Secure this value immediately; it is required for agent authentication.

Step 4: Finalize External Access

4.1 Domain Configuration

Edit the OpenClaw docker-compose.yml generated by the setup script. Update the labels to match your domain name so Traefik can correctly route traffic.

4.2 Initialize Containers

Launch the agent in detached mode:

Bash

docker compose up -d

Verification and Next Steps

Once the containers are healthy, you can verify the deployment:

  1. Check Logs: Use docker compose logs -f to monitor the initial handshake with your API Account.
  2. Connect to Telegram: Open your bot in Telegram and send a message. If correctly configured, the agent will respond using the Anthropic model specified during setup.
  3. Security Audit: Ensure port 18789 is not exposed globally in your Computer firewall; all traffic should flow through the Traefik proxy on ports 80 and 443.

For troubleshooting specific API connection issues or advanced “Skill” configurations, refer to the official OpenClaw documentation.

To support a local Ollama installation—whether through a native Gnoppix/Debian package or a Docker container—you need to ensure OpenClaw can “see” the Ollama API across the network boundaries.

Here is the complete setup for both environments.

5. Gnoppix Ollama Installation

Since you installed Ollama via the .deb package or the install script, it likely runs as a systemd service. By default, it only listens on 127.0.0.1, which is fine if OpenClaw is on the same machine.

The Configuration Fix:

Open your OpenClaw config: nano ~/.openclaw/openclaw.json

Update the providers section to point to your local service:

JSON

"models": {
  "providers": {
    "ollama": {
      "baseUrl": "http://127.0.0.1:11434",
      "apiKey": "ollama-local", 
      "api": "ollama"
    }
  }
}

Note: Using "api": "ollama" (native) instead of "api": "openai" is critical to prevent the 400 error you saw earlier.

6. Docker Container Installation

If you are running Ollama in one container and OpenClaw in another (or OpenClaw on the host), they cannot reach each other via localhost.

A. If Ollama is in Docker and OpenClaw is on the Host:

You must ensure Ollama is bound to 0.0.0.0. In your Docker run command or Compose file, add:

  • ENVIRONMENT OLLAMA_HOST=0.0.0.0
  • In OpenClaw, use http://localhost:11434 or your LAN IP.

B. If both are in Docker (Recommended):

Use a shared network. In your docker-compose.yml:

YAML

services:
  ollama:
    image: ollama/ollama
    networks:
      - openclaw-net
  openclaw:
    image: openclaw/gateway
    networks:
      - openclaw-net
    environment:
      - OLLAMA_BASE_URL=http://ollama:11434

The Configuration Fix:

In openclaw.json, the baseUrl must change from 127.0.0.1 to the service name:

"baseUrl": "http://ollama:11434"

7. Applying the “Thinking” Fix for 2026

To avoid the 400 think value "low" error in this local setup, manually define your model in the openclaw.json file to override the framework’s default behavior:

JSON

"models": [
  {
    "id": "qwen3:4b",
    "name": "Local Qwen Agent",
    "reasoning": true,
    "think": true,
    "contextWindow": 64000
  }
]

Quick Verification

After setting this up, run the “doctor” command to ensure the connection is live:

Bash

openclaw doctor --provider ollama

If it returns a green checkmark next to your local models, the bridge is successful.

Would you like me to provide a Docker Compose template that links both services with GPU passthrough enabled for your Gnoppix system?