cua and Computer-Use-Agent
The open-source infrastructure providing sandboxes and SDKs for training computer-use agents (A) serves as the foundational platform that a specific agent implementation (B) would build upon or be evaluated against.
About cua
trycua/cua
Open-source infrastructure for Computer-Use Agents. Sandboxes, SDKs, and benchmarks to train and evaluate AI agents that can control full desktops (macOS, Linux, Windows).
Provides unified APIs for sandbox creation, UI automation (screenshots, mouse/keyboard/touch), and code execution across heterogeneous environments (containers, VMs, cloud, local QEMU) with platform-specific optimizations like H.265 streaming and native window integration. Includes cua-bench for standardized evaluation on OSWorld and ScreenSpot, plus Lume for high-performance macOS virtualization on Apple Silicon via Virtualization.Framework.
About Computer-Use-Agent
Codeeaner/Computer-Use-Agent
An AI Agent that is able to control your screen to complste any task
Implements a local, closed-loop automation system using Qwen3-VL vision-language model via Ollama to iteratively capture screenshots, analyze UI state, and execute mouse/keyboard actions on Windows 11. Built with `mss` for efficient screen capture and `pyautogui` for input control, it includes function calling for structured action planning and screenshot history for debugging automation workflows.
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