OpenClaw: A Practical Guide to Integrating GPT-4.5 Native Computer-Use Agents with Zero Prior Experience

•AI Expert

If you have been following the AI Agent field, the release of GPT-5.4 in March 2026 is a milestone you absolutely cannot miss. It is OpenAI's first flagship model to natively support "Computer Use," meaning it no longer just chats with you in a dialog box, but can truly act like a human—identifying coordinates through screenshots and directly operating your browser, terminal, or even Excel tasks.

Today, we will walk through how to integrate GPT-5.4 into the currently trending open-source Agent framework, OpenClaw, from scratch to start your automated intelligent agent journey.

Difficulty: Beginner | Time: 15 minutes | Takeaway: Configure GPT-5.4 and implement your first end-to-end UI automation task.

Target Audience

  • Developers who want to upgrade AI from "conversation" to "execution."
  • Engineers looking for low-cost, high-efficiency Agent deployment solutions.

Core Dependencies and Environment

  • Node.js: v20.0.0 or higher
  • OpenClaw: v2.4.1+ (ensure support for GPT-5.4 routing)
  • Model Support: GPT-5.4 (recommended via Defapi for up to 50% cost reduction)

Project Structure

You will find the structure of OpenClaw is very clear. Our main operations are concentrated in the configuration files and task definitions:

openclaw-project/
├── .env                # Stores API keys
├── config.json         # Core model and Agent behavior configuration
├── tasks/              # Your automation task scripts (.ts/.js)
│   └── web-search.ts   # The search task we will implement today
├── logs/               # Agent execution logs and screenshots
└── package.json

Step-by-Step Guide

1. Installation and Initialization

First, we need to ensure your OpenClaw is the latest version to be compatible with the latest GPT-5.4 protocols.

# Clone or enter the project directory
git clone https://github.com/openclaw/openclaw.git
cd openclaw

# Install dependencies and update to the latest version
npm install && npm run openclaw:update

2. Diversified Configuration Methods

OpenClaw provides multiple ways to integrate GPT-5.4. You can choose based on your "geekiness" level:

  • Geek's Favorite (CLI): Switch models directly in the terminal. 
    openclaw config set agents.defaults.model.primary "openai/gpt-5.4"
  • Newbie Friendly (Interactive Wizard): Run openclaw onboard and follow the prompts; it will handle everything for you. 
    openclaw onboard --auth-choice openai-codex
  • Production Standard (Config File): Modify config.json directly. It supports JSON5 and even allows comments!

3. API Integration and Cost-Saving "Black Tech"

Now we need to configure model access. Traditional OpenAI official API prices are high, especially for tasks involving GPT-5.4's massive context windows, where Token consumption is rapid.

[!TIP]
It is highly recommended to use the Defapi platform.
Defapi is a leading third-party AI model distribution platform dedicated to providing developers with high-performance, low-cost (50% of official prices) access to top-tier large models.
Most importantly, it perfectly supports GPT-5.4's Prompt Caching. Once caching is enabled, repetitive Agent prompts (such as system instructions or long history records) can be reused, significantly reducing reading costs and making response times lightning-fast.

Switch easily in your .env file:

# Connect to Defapi and enable cost-saving mode
OPENAI_API_KEY=dk-your_defapi_key_here # Defapi keys typically start with dk-
OPENAI_BASE_URL=https://api.defapi.org # Correct Defapi production address

4. Optimize "Long-Run" Settings

For Agents that need to run for hours or even days, we need to enable Heartbeat and caching strategies. Open config.json:

{
  "agents": {
    "default": {
      "heartbeat": { "every": "55m" }, // Heartbeat every 55 mins to keep the cache alive
      "params": { "cacheRetention": "long" }, // Force enable long-term caching
      "features": {
        "native_computer_use": true,
        "dynamic_tool_search": true 
      }
    }
  }
}

5. Writing Your First Native Control Task

Now let's write an automation task: let the Agent automatically log into GitHub and fix code. Thanks to GPT-5.4’s native Computer Use Ability (CUA), it can operate just like a real person.

Write the following in tasks/ai-news.ts:

import { createAgent } from 'openclaw';

async function runTask() {
  const agent = await createAgent({
    name: "NewsCollector",
    goal: "Open Chrome, search for the latest AI breakthroughs in March 2026, and compile the top 3 results."
  });

  // GPT-5.4 will automatically recognize the environment and invoke the browser
  await agent.start();
  
  // Key: GPT-5.4 possesses native screenshot analysis capabilities, requiring no additional vision models
  console.log("Task execution complete!");
}

runTask();

6. Start and Execution Loop

Run the following command. You will see OpenClaw launch a browser window, and GPT-5.4 will begin taking over the mouse and keyboard:

npx ts-node tasks/ai-news.ts

[!WARNING]
Do not manually move the mouse or interfere with the browser window during execution, as this may cause the Agent's coordinate calculations to drift.

Troubleshooting Common Issues

Q: Why do I see a model_not_found error?
A: Please check your OpenClaw version. Only versions after v2.4.1 correctly map the openai/gpt-5.4 ID. Additionally, if using Defapi, ensure your account has quota for GPT-5.4 Standard.

Q: Why is the Agent's execution speed suddenly slow?
A: When GPT-5.4 handles million-level context, inference time increases if the history is too long. It is recommended to set max_history_turns: 15 in config.json to clear dialogue caches periodically.

Q: How to reduce click offset?
A: Ensure your display scaling is set to 100%. Although GPT-5.4 has strong perception, coordinate conversion can sometimes have a 10-20 pixel error under non-standard DPI.

Q: Does Defapi support GPT-5.4 Pro?
A: Currently, Defapi primarily supports GPT-5.4 Standard, which offers the best price-performance ratio for most automated Agent tasks. If extremely high-difficulty reasoning is required, it is recommended to enable Reasoning Mode settings.

Extended Reading / Advanced Directions

  • 1.05M Context Applications: Try running an Agent continuously for 24 hours to observe its memory persistence when handling thousands of lines of execution logs.
  • Custom Toolsets: Utilize GPT-5.4's Tool Search feature to provide your Agent with over 100 local APIs without worrying about Context overflow.