Computer Using Agent Sample App

Get started building a Computer Using Agent (CUA) with the OpenAI API.

Caution

Computer use is in preview. Because the model is still in preview and may be susceptible to exploits and inadvertent mistakes, we discourage trusting it in authenticated environments or for high-stakes tasks.

Set Up & Run

Set up python env and install dependencies.

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Run CLI to let CUA use a local browser window, using playwright. (Stop with CTRL+C)

python cli.py --computer local-playwright

Note

The first time you run this, if you haven't used Playwright before, you will be prompted to install dependencies. Execute the command suggested, which will depend on your OS.

Other included sample computer environments:

• Docker (containerized desktop)
• Browserbase (remote browser, requires account)
• Scrapybara (remote browser or computer, requires account)
• ...or implement your own Computer!

Overview

The computer use tool and model are available via the Responses API. At a high level, CUA will look at a screenshot of the computer interface and recommend actions. Specifically, it sends computer_call(s) with actions like click(x,y) or type(text) that you have to execute on your environment, and then expects screenshots of the outcomes.

You can learn more about this tool in the Computer use guide.

Abstractions

This repository defines two lightweight abstractions to make interacting with CUA agents more ergonomic. Everything works without them, but they provide a convenient separation of concerns.

Abstraction	File	Description
Computer	computers/computer.py	Defines a Computer interface for various environments (local desktop, remote browser, etc.). An implementation of Computer is responsible for executing any computer_action sent by CUA (clicks, etc).
Agent	agent/agent.py	Simple, familiar agent loop – implements run_full_turn(), which just keeps calling the model until all computer actions and function calls are handled.

CLI Usage

The CLI (cli.py) is the easiest way to get started with CUA. It accepts the following arguments:

• --computer: The computer environment to use. See the Computer Environments section below for options. By default, the CLI will use the local-playwright environment.
• --input: The initial input to the agent (optional: the CLI will prompt you for input if not provided)
• --debug: Enable debug mode.
• --show: Show images (screenshots) during the execution.
• --start-url: Start the browsing session with a specific URL (only for browser environments). By default, the CLI will start the browsing session with https://bing.com.

Run examples (optional)

The examples folder contains more examples of how to use CUA.

python -m examples.weather_example

For reference, the file simple_cua_loop.py implements the basics of the CUA loop.

You can run it with:

python simple_cua_loop.py

Computer Environments

CUA can work with any Computer environment that can handle the CUA actions:

Action	Example
click(x, y, button="left")	click(24, 150)
double_click(x, y)	double_click(24, 150)
scroll(x, y, scroll_x, scroll_y)	scroll(24, 150, 0, -100)
type(text)	type("Hello, World!")
wait(ms=1000)	wait(2000)
move(x, y)	move(24, 150)
keypress(keys)	keypress(["CTRL", "C"])
drag(path)	drag([[24, 150], [100, 200]])

This sample app provides a set of implemented Computer examples, but feel free to add your own!

Computer	Option	Type	Description	Requirements
LocalPlaywright	local-playwright	browser	Local browser window	Playwright SDK
Docker	docker	linux	Docker container environment	Docker running
Browserbase	browserbase	browser	Remote browser environment	Browserbase API key in .env
ScrapybaraBrowser	scrapybara-browser	browser	Remote browser environment	Scrapybara API key in .env
ScrapybaraUbuntu	scrapybara-ubuntu	linux	Remote Ubuntu desktop environment	Scrapybara API key in .env

Using the CLI, you can run the sample app with different computer environments using the options listed above:

python cli.py --show --computer <computer-option>

For example, to run the sample app with the Docker computer environment, you can run:

python cli.py --show --computer docker

Docker Setup

If you want to run the sample app with the Docker computer environment, you need to build and run a local Docker container.

Open a new shell to build and run the Docker image. The first time you do this, it may take a few minutes, but subsequent runs should be much faster. Once the logs stop, proceed to the next setup step. To stop the container, press CTRL+C on the terminal where you ran the command below.

docker build -t cua-sample-app .
docker run --rm -it --name cua-sample-app -p 5900:5900 --dns=1.1.1.3 -e DISPLAY=:99 cua-sample-app

Note

We use --dns=1.1.1.3 to restrict accessible websites to a smaller, safer set. We highly recommend you take similar safety precautions.

Warning

If you get the below error, then you need to kill that container.

docker: Error response from daemon: Conflict. The container name "/cua-sample-app" is already in use by container "e72fcb962b548e06a9dcdf6a99bc4b49642df2265440da7544330eb420b51d87"

Kill that container and try again.

docker rm -f cua-sample-app

Hosted environment setup

This repository contains example implementations of third-party hosted environments. To use these, you will need to set up an account with the service by following the links aboveand add your API key to the .env file.

Function Calling

The Agent class accepts regular function schemas in tools – it will return a hard-coded value for any invocations.

However, if you pass in any tools that are also defined in your Computer methods, in addition to the required Computer methods, they will be routed to your Computer to be handled when called. This is useful for cases where screenshots often don't capture the search bar or back arrow, so CUA may get stuck. So instead, you can provide a back() or goto(url) functions. See examples/playwright_with_custom_functions.py for an example.

Risks & Safety considerations

This repository provides example implementations with basic safety measures in place.

We recommend reviewing the best practices outlined in our guide, and making sure you understand the risks involved with using this tool.