1. Environment Setup and Prerequisites

Before deployment, ensure the following system requirements are met:

System Requirements:

• Ubuntu 24.04 LTS (recommended latest stable version)

Dependency Installation:

sudo apt update && sudo apt install -y \
curl wget git nodejs npm build-essential

Node.js Version Management:
Use nvm for managing multiple Node.js versions (LTS recommended):

curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.5/install.sh | bash
source ~/.bashrc
nvm install --lts

2. AI Inference Framework Installation

2.1 Global Framework Installation

Configure npm for system-wide installation:

# Create dedicated directory and set permissions
sudo mkdir -p /opt/ai-framework
sudo chown -R $USER:$USER /opt/ai-framework
# Configure npm global path
npm config set prefix '/opt/ai-framework'
export PATH=$PATH:/opt/ai-framework/bin
# Install with permission handling
npm install -g openclaw@latest --unsafe-perm

2.2 Troubleshooting Common Issues

Directory Conflict Resolution:
For ENOTEMPTY errors:

pkill -f openclaw
rm -rf /opt/ai-framework/lib/node_modules/openclaw
rm -rf ~/.npm/_logs/*
npm cache clean --force

Dependency Conflict Handling:
For node-gyp compilation errors:

sudo apt install -y python3-distutils python3-dev
# Windows Subsystem only:
npm install --global windows-build-tools

2.3 Installation Verification

Validate the installation:

openclaw --version  # Expected output: e.g. 2026.3.2
openclaw doctor     # Checks Node.js compatibility, dependencies, and permissions

3. Large Model Service Integration

3.1 Interactive Configuration

Configure service parameters:

openclaw config

Configuration workflow:

1. Service Type: Add custom provider
2. Provider Naming: Use meaningful names (e.g., zhipu-glm)
3. API Endpoint Configuration:
   • Base URL: https://api.ai-service.example/v4 (example)
   • Version Path: /chat/completions
4. Authentication:
   • API Key format: sk-xxxxxxxxxxxxxxxxxxxxxxxx
   • Environment variable storage recommended:

     export AI_SERVICE_KEY='sk-xxxxxxxxxxxxxxxx'

3.2 Advanced Configuration

Performance Optimization (~/.openclaw/config.json):

{
  "concurrency": 4,
  "timeout": 60000,
  "retry": {
    "maxAttempts": 3,
    "backoffFactor": 1.5
  }
}

Security Recommendations:

1. API Key Rotation:
   • Rotate every 30 days
   • Implement automated rotation scripts
2. Network Isolation:
   • Restrict access via firewall rules
   • Consider private subnet deployment

4. Complete Workflow Example

4.1 Inference Testing

Create test-inference.js:

const { OpenClaw } = require('openclaw');
async function main() {
  const client = new OpenClaw({
    provider: 'zhipu-glm',
    apiKey: process.env.AI_SERVICE_KEY
  });
  const response = await client.chat({
    messages: [{
      role: 'user',
      content: 'Explain the basic principles of quantum computing'
    }]
  });
  console.log('Model response:', response.choices[0].message.content);
}
main().catch(console.error);

4.2 Test Execution

node test-inference.js
# Expected output:
# Model response: Quantum computing utilizes quantum mechanics principles...

5. Production Deployment Recommendations

5.1 Containerized Deployment

Dockerfile example:

FROM ubuntu:24.04
RUN apt update && apt install -y \
    nodejs npm && \
    npm install -g openclaw@latest --unsafe-perm
COPY config.json /root/.openclaw/
COPY entrypoint.sh /
CMD ["/entrypoint.sh"]

5.2 Monitoring Configuration

Recommended metrics:

1. API call success rate
2. Average response time
3. Error rate statistics
4. Concurrent request count

Prometheus configuration example:

scrape_configs:
  - job_name: 'openclaw'
    static_configs:
      - targets: ['localhost:9090']
    metrics_path: '/metrics'

6. Troubleshooting Guide

6.1 Connection Timeout Handling

1. Verify network connectivity:

   curl -v https://api.ai-service.example/v4/health

2. Check DNS resolution:

   nslookup api.ai-service.example

6.2 Authentication Failure Resolution

1. Verify API key validity
2. Check permission settings (ensure inference access)
3. Validate system clock synchronization (NTP service status)

6.3 Performance Bottleneck Analysis

1. Monitor system resources with htop
2. Generate performance profiles with node --prof
3. Check network bandwidth utilization

7. Upgrade and Maintenance Strategy

7.1 Version Upgrade Process

# Check for updates
npm outdated -g openclaw
# Perform upgrade (test first)
npm update -g openclaw@latest
# Verify upgrade
openclaw --version

7.2 Rollback Procedure

1. Backup current version:

   cp -r /opt/ai-framework/lib/node_modules/openclaw /backup/

2. Install specific version:

   npm install -g openclaw@2026.3.1

This comprehensive workflow enables developers to build stable large model inference environments on Ubuntu systems. For enterprise deployments, consider implementing high-availability architectures and disaster recovery plans after validating configurations in test environments.