open-computer-use

e2b-devApache-2.0活跃维护

用开源大模型驱动 AI 操作电脑桌面,配合 E2B 桌面沙箱安全执行点击、输入等操作,可替代 Claude 的闭源 computer-use 方案。

AI computer use powered by open source LLMs and E2B Desktop Sandbox

暂无版本2,409star +3 / 7 天269fork同步于 2026-11-10 05:43 UTC

怎么上手

由 README 提炼,执行前请确认
brew install poetry ffmpeg
poetry install
poetry run start
硬件要求按 README 说明

README 未说明本地硬件要求;计算跑在 E2B 云端 Linux 沙箱上,本地只需能运行 Python 客户端并接收画面串流。

下载:源码 zip·GitHub Releases(安装包)本站不镜像安装包

项目说明

由 README 自动翻译提炼

用开源 LLM 驱动 E2B 云端 Linux 桌面沙箱,让 AI 自己操作电脑

用开源大模型驱动 AI 操作电脑桌面,配合 E2B 桌面沙箱安全执行点击、输入等操作,可替代 Claude 的闭源 computer-use 方案。

核心能力

  • 通过键盘、鼠标和 shell 命令操作云端桌面
  • 支持 10+ LLM,可自由替换 grounding/vision/action 模型
  • 实时把沙箱画面串流到本地客户端
  • 用户可随时暂停并追加提示词
  • 基于 E2B Desktop Sandbox 提供隔离的 Ubuntu 环境

容易踩的坑

需要 E2B API key 和所选 LLM 提供商的 API key,Hugging Face Spaces 还需 HF_TOKEN 绕过 Gradio 限流;模型在 config.py 中指定,换模型要改配置并配好对应 key;README 的安装命令用 brew,非 macOS 需自行装 poetry 和 ffmpeg。

内容由模型根据 README 生成,可能不完整或不准确,以官方文档为准。看原文 README

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    README 原文

    未翻译

    Open Computer Use

    A secure cloud Linux computer powered by E2B Desktop Sandbox and controlled by open-source LLMs.

    https://github.com/user-attachments/assets/3837c4f6-45cb-43f2-9d51-a45f742424d4

    Features

    • Uses E2B for secure Desktop Sandbox
    • Operates the computer via the keyboard, mouse, and shell commands
    • Supports 10+ LLMs, OS-Atlas/ShowUI and any other models you want to integrate!
    • Live streams the display of the sandbox on the client computer
    • User can pause and prompt the agent at any time
    • Uses Ubuntu, but designed to work with any operating system

    Design

    Open Computer Use Architecture Open Computer Use Architecture

    The details of the design are laid out in this article: How I taught an AI to use a computer

    LLM support

    Open Computer Use is designed to make it easy to swap in and out new LLMs. The LLMs used by the agent are specified in config.py like this:

    grounding_model = providers.OSAtlasProvider()
    vision_model = providers.GroqProvider("llama3.2")
    action_model = providers.GroqProvider("llama3.3")
    

    The providers are imported from providers.py and include:

    • Fireworks, OpenRouter, Llama API:
      • Llama 3.2 (vision only), Llama 3.3 (action only)
    • Groq:
      • Llama 3.2 (vision + action), Llama 3.3 (action only)
    • DeepSeek:
      • DeepSeek (action only)
    • Google:
      • Gemini 2.0 Flash (vision + action)
    • OpenAI:
      • GPT-4o and GPT-4o mini (vision + action)
    • Anthropic:
      • Claude (vision + action)
    • HuggingFace Spaces:
      • OS-Atlas (grounding)
      • ShowUI (grounding)
    • Moonshot
    • Mistral AI (Pixtral for vision, Mistral Large for actions)

    If you add a new model or provider, please make a PR to this repository with the updated providers.py!

    Get started

    Prerequisites

    • Python 3.10 or later
    • git
    • E2B API key
    • API key for an LLM provider (see above)

    1. Install the prerequisites

    In your terminal:

    brew install poetry ffmpeg
    

    2. Clone the repository

    In your terminal:

    git clone https://github.com/e2b-dev/open-computer-use/
    

    3. Set the environment variables

    Enter the project directory:

    cd open-computer-use
    

    Create a .env file in open-computer-use and set the following:

    # Get your API key here: https://e2b.dev/?utm_source=github&utm_medium=referral&utm_campaign=readme&utm_content=open-computer-use
    E2B_API_KEY="your-e2b-api-key"
    

    Additionally, add API key(s) for any LLM providers you're using:

    # You only need the API key for the provider(s) selected in config.py:
    # Hugging Face Spaces do not require an API key.
    FIREWORKS_API_KEY=...
    OPENROUTER_API_KEY=...
    LLAMA_API_KEY=...
    GROQ_API_KEY=...
    GEMINI_API_KEY=...
    OPENAI_API_KEY=...
    ANTHROPIC_API_KEY=...
    MOONSHOT_API_KEY=...
    # Required: Provide your Hugging Face token to bypass Gradio rate limits.
    HF_TOKEN=...
    

    4. Start the web interface

    Run the following command to start the agent:

    poetry install
    
    poetry run start
    

    The agent will open and prompt you for its first instruction.

    To start the agent with a specified prompt, run:

    poetry run start --prompt "use the web browser to get the current weather in sf"
    

    The display stream should be visible a few seconds after the Python program starts.