From the source
Published on April 27, 2025 by Francesco Bonacci In our previous post , we built a basic Computer-Use Operator from scratch using OpenAI's computer-use-preview model and our cua-computer package.
While educational, implementing the control loop manually can be tedious and error-prone.
In this follow-up, we'll explore our cua-agent framework - a high-level abstraction that handles all the complexity of VM interaction, screenshot processing, model communication, and action execution automatically.
By the end of this tutorial, you'll be able to: Set up the cua-agent framework with various agent loop types and model providers Understand the different agent loop types and their capabilities Work with local models for cost-effective workflows Use a simple UI for your operator Prerequisites: Completed setup from Part 1 ( lume CLI installed , macOS Cua image already pulled) Python 3.10+.
We recommend using Conda (or Anaconda) to create an ad hoc Python environment.
API keys for OpenAI and/or Anthropic (optional for local models) Estimated Time: 30-45 minutes The cua-agent framework is designed to simplify building Computer-Use Agents.
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