This project is a computer control framework that uses multimodal vision models to simulate mouse and keyboard inputs for automating desktop tasks. It functions as an autonomous agent and vision-based orchestrator that interprets screen visuals to interact with user interfaces.
The system employs vision language models and object detection to locate and click interface elements. It utilizes visual grounding to overlay numerical markers on UI components and uses optical character recognition to map on-screen text to precise pixel coordinates.
The framework supports voice-controlled computing by translating spoken commands into text-based objectives. It manages a full automation loop encompassing state observation through screenshots, action planning via cloud or local APIs, and the execution of synthetic inputs.