Cua Agent Template
https://github.com/trycua/agent-template- Category
- AI Agents
- Rank
- No. 2135Tools index
Previous survey · No. 2094 ·
- Pricing
- Open Source
- Type
- AGENT
- Builder
- trycua
- GitHub
- 9 stars
- Date
About
Sample use of the Cua Python SDK for running an agent on a cloud sandbox.
What it does
A runnable Python starting point for computer-control automation. It connects an OpenAI computer-use model to a remote Linux machine, then carries conversation history across tasks while the agent operates websites, downloads a document, and completes a form from that document.
Why it's ranked here
The template makes a complex interaction loop unusually concrete: credentials are checked, actions and model messages are printed, screenshots are handled, and task context persists between steps. Its narrow example is useful for learning, but it remains starter code rather than a complete automation system.
What's good
The example teaches several practical patterns at once. It validates required credentials before starting, preserves context between sequential tasks, streams structured agent output, logs computer actions, stores trajectories, enables prompt caching, limits retained screenshots, and handles interruption cleanly.
Tradeoffs
Running it requires a Cua account, an active sandbox, and an OpenAI key with computer-use access. The task list and model are fixed in code. Error handling mainly prints tracebacks, and the supplied text shows no tests, deployment setup, user interface, or production controls.
How to use it well
Use it when learning computer-use agents or prototyping a browser workflow that spans documents and forms. Replace the sample tasks, inspect recorded trajectories, and keep experiments bounded. It does not cover production orchestration, testing, monitoring, permissions design, or a general end-user interface.
Technical notes+
main.py creates Computer with VMProviderType.CLOUD, Linux as the operating system, and credentials from the environment. It constructs ComputerAgent with openai/computer-use-preview, retains three recent images, enables prompt caching, writes to trajectories, and passes accumulated message history through two tasks. utils.py manually loads .env.local before .env and installs a SIGINT handler. pyproject.toml requires Python 3.10 or newer, declares Hatchling packaging, and includes main.py plus utils.py in the wheel. requirements.txt duplicates the three runtime dependencies.
Observed
- Primary language
- Python
- Runtime requirement
- Python 3.10 or newer
- Packaging
- Hatchling build backend, with uv and pip installation surfaces documented
- Interface
- Runnable command-line Python example using the Cua agent and computer libraries
- Runtime dependencies
- cua-agent, cua-computer, and python-dotenv
- Platform support
- The example targets a cloud Linux virtual machine; the README also points to local macOS testing
- Credentials
- Requires Cua API key, Cua sandbox name, and OpenAI API key
- License
- No license is specified in the supplied repository text
Read from README.md, pyproject.toml, requirements.txt, main.py, utils.py, .env.example.
What it can do
Run Python-based AI agent in cloud environment
Agent configuration and code → Agent execution results
Execute agent workflows in isolated sandbox
Workflow definitions and parameters → Workflow execution logs and outputs
Integrate with Cua Python SDK services
SDK method calls and configurations → Service responses and data
Deploy agent template to cloud infrastructure
Template files and deployment settings → Deployed agent instance
Monitor agent performance and status
Agent instance identifiers → Performance metrics and status reports
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