Windows-Use is an open-source automation agent designed to enable AI models to interact directly with the Windows graphical user interface (GUI). It bridges the gap between Large Language Models (LLMs) and the Windows operating system, allowing AI agents to perform tasks like opening applications, clicking buttons, typing text, and capturing UI state without relying solely on traditional computer vision. This empowers developers to integrate sophisticated automation capabilities into AI-driven applications running on Windows.

How It Works

The core approach involves the agent interacting directly with the Windows GUI layer. This method bypasses the need for complex computer vision pipelines typically used for UI automation, abstracting the OS interaction layer. This design allows any LLM to leverage the agent's capabilities for automation, promoting flexibility and reducing the dependency on specialized vision models for task execution.

Quick Start & Requirements

• Primary install command: uv pip install windows-use or pip install windows-use.
• Prerequisites: Python 3.12 or higher. Example usage requires langchain_google_genai and a compatible LLM (e.g., Gemini 2.0 Flash), along with the Chrome browser.
• Links: The primary source of information and code is the GitHub repository: https://github.com/CursorTouch/Windows-Use

Highlighted Details

• Direct GUI Interaction: Enables AI agents to perform low-level GUI operations such as clicking, typing, and executing shell commands directly within the Windows environment.
• LLM Agnostic Automation: Designed to abstract OS interactions, allowing diverse LLMs to control the Windows OS without requiring model-specific UI automation components.
• UI State Capture: Capable of capturing the current state of the user interface for context-aware decision-making by the AI agent.
• Demo Examples: Demonstrates practical use cases including writing notes and saving them, and switching system appearance modes (e.g., dark to light).

Maintenance & Community

• Developed by Jeomon George.
• Contribution guidelines are available in a CONTRIBUTING file within the repository. No other community channels (e.g., Discord, Slack) or roadmap details are specified in the README.

Licensing & Compatibility

• License: MIT License.
• Compatibility: The permissive MIT license generally allows for commercial use and integration within closed-source projects without significant restrictions.

Limitations & Caveats

• Direct OS Manipulation Risk: The agent directly manipulates the Windows GUI, which carries a risk of unintended system behavior or data modification if errors occur.
• Sandbox Recommendation: Due to the potential for instability and undesired system changes, running the agent within a sandboxed environment is strongly recommended.
• Vision Component: Although it aims to reduce reliance on traditional computer vision, the use_vision=True parameter in example code suggests that visual processing capabilities may still be utilized or configurable.