OmniParser AutoGUI

Windows Desktop Control

Empower artificial intelligence systems to manage desktop applications on Windows using a combination of UIAutomation and PyAutoGUI. This allows for program initiation, command execution, and mouse/keyboard operations while utilizing tree-like structures to identify UI elements.

Computer Control

Enhance desktop functionality by utilizing mouse manipulation, keyboard commands, screen capturing, optical character recognition (OCR), and efficient window handling to directly engage with graphical user interfaces.

SwiftAutoGUI

Enhance your macOS control using mouse actions with SwiftAutoGUI. This tool enables seamless interaction with the macOS interface for streamlined automation tasks and graphical user interface testing.

Windows Desktop Automation

Facilitate seamless Windows desktop automation using TypeScript-wrapped AutoIt functions that allow for effortless control of mouse actions, keyboard commands, window handling, and user interface elements based on intuitive natural language commands.

OmniParser

Enhance your UI automation with a powerful framework utilizing cutting-edge computer vision technology for accurate detection, interaction, and validation across diverse interfaces.

macOS GUI Control

Empower AI virtual assistants to effectively manage macOS software by capturing screen images, recognizing interface components, and automating mouse and keyboard functions using the macOS accessibility system.

PyAutoGUI

Facilitates automated testing and management of graphical user interfaces (GUI) on various platforms by utilizing PyAutoGUI for tasks such as mouse manipulation, keyboard commands, screen capturing, and image identification.

Screen Capture

Capture and share screen images efficiently with PyAutoGUI, enabling quick analysis of on-screen content through compressed screenshot sharing.

AutoGen

Facilitates seamless integration between Microsoft's AutoGen framework and external tools, empowering autonomous agents to run code, conduct investigations, and engage in collaborative multi-agent dialogues to tackle intricate problem-solving assignments.