Open-computer-use is a framework designed to connect vision-capable language models to isolated cloud-based desktop environments. It functions as an agentic interface that enables autonomous systems to interact with graphical user interfaces by simulating mouse movements, keyboard keystrokes, and shell commands. By bridging language models with remote workspaces, the platform facilitates the execution of complex, long-running tasks within secure, sandboxed environments.
e2b-dev/open-computer-use 的主要功能包括：Computer Use, Desktop Automation, Desktop AI Agents, Cloud-Hosted Agent Sandboxes, AI Model Integrations, Vision-Language-Action Mappings, AI Observability and Evaluation, Keyboard and Mouse Input Simulations。
e2b-dev/open-computer-use 的开源替代品包括： e2b-dev/code-interpreter — This project is an infrastructure platform designed to provide secure, isolated, and ephemeral cloud-based Linux… bytebot-ai/bytebot — Bytebot is an LLM desktop automation framework and virtual Linux desktop environment. It enables AI agents to plan and… suitedaces/computer-agent — This project is an autonomous desktop automation agent that interprets natural language instructions to control… openinterpreter/open-interpreter — Open Interpreter is an autonomous agent runtime that translates natural language instructions into executable code to… dockur/macos — This project provides a containerized environment for running a full macOS desktop operating system. It utilizes a… rivet-dev/sandbox-agent — Sandbox Agent is a platform designed to manage, secure, and orchestrate autonomous coding assistants. It provides a…
This project is an infrastructure platform designed to provide secure, isolated, and ephemeral cloud-based Linux environments for AI agents and automated code execution. It functions as an orchestrator that provisions on-demand virtual machines, allowing developers to run arbitrary code generated by large language models within hardware-level security boundaries. The platform distinguishes itself through its ability to manage stateful, long-lived sessions that persist across multiple execution calls, enabling complex, multi-step workflows. It supports high-concurrency scaling, allowing for th
Bytebot is an LLM desktop automation framework and virtual Linux desktop environment. It enables AI agents to plan and execute mouse and keyboard actions on a virtual computer using natural language, allowing for autonomous desktop automation and the integration of legacy systems that lack native APIs. The system operates as an LLM API gateway and a Model Context Protocol server, routing requests across multiple language model providers with integrated load balancing and rate limiting. It provides isolated, containerized environments where agents use visual reasoning to interpret screenshots
This project is an autonomous desktop automation agent that interprets natural language instructions to control applications, browser interfaces, and system terminals. It functions as a cross-platform utility designed to manage complex workflows by integrating visual screen analysis with system-level input simulation. The agent distinguishes itself through its ability to perform tasks asynchronously, ensuring that web and terminal operations run in the background without interrupting the active user session or desktop focus. By combining computer vision to map interface elements with event-dr
Open Interpreter is an autonomous agent runtime that translates natural language instructions into executable code to interact with local software and operating systems. It functions as an orchestration framework that connects language models to a secure execution environment, enabling the development of agents capable of managing system resources and performing complex tasks. To ensure safety, the system mandates explicit user verification before executing any generated code and provides robust isolation through containerized sandboxing. The project distinguishes itself through its deep inte