Apache License 2.0

项目介绍

magnitudedev/browser-agent 是一个托管在 GitHub 上的开源项目,主要使用 TypeScript 编写,采用 Apache License 2.0 许可证,目前获得 4.1k 个 Star、247 次 Fork。

仓库全名
magnitudedev/browser-agent
开源许可证
Apache License 2.0
Star 数
4.1k
Fork 数
247
未关闭 Issue
33

README 摘要

🚀 New: Magnitude is state-of-the-art, scoring 94% on WebVoyager! Magnitude uses vision AI to enable you to control your browser with natural language. 🧭 Navigate - Sees and understands any interface to plan out actions 🖱️ Interact - Executes precise actions using mouse and keyboard 🔍 Extract - Intelligently extracts useful structured data ✅ Verify - Built-in test runner with powerful visual assertions You can…

完整内容见 GitHub 原始 README 或本页 。

常见问题

browser-agent 用什么语言开发?

主要使用 TypeScript 编写,采用 Apache License 2.0 许可证,目前有 4.1k 个 Star。

browser-agent 可以免费商用吗?

仓库采用 Apache License 2.0 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 browser-agent 的源码?

可以直接克隆仓库:git clone https://github.com/magnitudedev/browser-agent.git;安装与运行步骤见仓库 README。

browser-agent 最近还在维护吗?

仓库最近一次更新为 2月9日,当前有 33 个未关闭 Issue;Star 数为 4.1k,可作为社区活跃度的参考。

关于

GitHub 原始描述(英文)

Open-source, vision-first browser agent

描述取自 GitHub 官方 API,保持仓库作者书写的原文。

简要分析

热度分
4659
价值分
2558
活跃状态
活跃

语言占比

HTML
JavaScript
Python
Shell
TypeScript

README

Magnitude Text Logo

Documentation License Discord Follow Tom Follow Anders

🚀 New: Magnitude is state-of-the-art, scoring 94% on WebVoyager!

Magnitude uses vision AI to enable you to control your browser with natural language.

  • 🧭 Navigate - Sees and understands any interface to plan out actions
  • 🖱️ Interact - Executes precise actions using mouse and keyboard
  • 🔍 Extract - Intelligently extracts useful structured data
  • ✅ Verify - Built-in test runner with powerful visual assertions

You can use it to automate tasks on the web, integrate between apps without APIs, extract data, test your web apps, or as a building block for your own browser agents.

Video showing Magnitude tests running in a terminal and agent taking actions in the browser

↕️ Magnitude in action! ↕️

// Magnitude can handle high-level tasks
await agent.act('Create a task', {
    // Optionally pass data that the agent will use where appropriate
    data: {
        title: 'Use Magnitude',
        description: 'Run "npx create-magnitude-app" and follow the instructions',
    },
});

// It can also handle low-level actions
await agent.act('Drag "Use Magnitude" to the top of the in progress column');

// Intelligently extract data based on the DOM content matching a provided zod schema
const tasks = await agent.extract(
    'List in progress tasks',
    z.array(z.object({
        title: z.string(),
        description: z.string(),
        // Agent can extract existing data or new insights
        difficulty: z.number().describe('Rate the difficulty between 1-5')
    })),
);

Get started

Running your first browser automation

npx create-magnitude-app

This will create a new project and walk you through the steps for setting up Magnitude. It will also create an example script that you can run right away!

Using the test runner

To install the test runner for use in an existing web app, please run:

npm i --save-dev magnitude-test && npx magnitude init

This will create a basic tests directory tests/magnitude with:

  • magnitude.config.ts: Magnitude test configuration file
  • example.mag.ts: An example test file

For information on how to run tests and integrate into CI/CD see here.

Note 注意

Magnitude requires a large visually grounded model. We recommend Claude Sonnet 4 for the best performance, but are also compatible with Qwen-2.5VL 72B. See docs for more information.

Why Magnitude?

❌ Problem #1: Most browser agents draw numbered boxes around page elements - doesn’t generalize well due to complex modern sites

✅ Solution: Vision-first architecture

  • Visually grounded LLM specifies pixel coordinates
  • True generalization independent of DOM structure
  • Future-proof architecture for desktop apps, VMs, etc.

❌ Problem #2: Most browser agents follow “high-level prompt + tools = work until done” - works for demos, not production

✅ Solution: Controllable & repeatable automation

  • Flexible abstraction levels (granular actions vs. flows)
  • Custom actions + prompts at agent and action level
  • Deterministic runs via native caching system (in progress)

Additional info

Please see our docs for more information on how to best build Magnitude automations and test cases.

Contact

If you are an enterprise and want more features or support, feel free to reach out to us at [email protected] or schedule a call here to discuss your needs.

You can also join our Discord community for help or any suggestions!

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