Co-Pilot / 辅助式
更新于 a month ago

browser-use

Bbrowser-use
76.3k
browser-use/browser-use
82
Agent 评分

💡 摘要

Browser-Use 通过 AI 代理实现自动化浏览器任务,以提高网络交互效率。

🎯 适合人群

寻找自动化工具的网页开发者需要抓取网页数据的数据分析师希望简化工作流程的产品经理测试网页应用程序的 QA 工程师探索浏览器自动化的 AI 爱好者

🤖 AI 吐槽:看起来很能打,但别让配置把人劝退。

安全分析中风险

风险:Medium。建议检查:是否执行 shell/命令行指令;是否发起外网请求(SSRF/数据外发);API Key/Token 的获取、存储与泄露风险;文件读写范围与路径穿越风险。以最小权限运行,并在生产环境启用前审计代码与依赖。


🌤️ Want to skip the setup? Use our cloud for faster, scalable, stealth-enabled browser automation!

🤖 LLM Quickstart

  1. Direct your favorite coding agent (Cursor, Claude Code, etc) to Agents.md
  2. Prompt away!

👋 Human Quickstart

1. Create environment with uv (Python>=3.11):

uv init

2. Install Browser-Use package:

# We ship every day - use the latest version! uv add browser-use uv sync

3. Get your API key from Browser Use Cloud and add it to your .env file (new signups get $10 free credits):

# .env
BROWSER_USE_API_KEY=your-key

4. Install Chromium browser:

uvx browser-use install

5. Run your first agent:

from browser_use import Agent, Browser, ChatBrowserUse import asyncio async def example(): browser = Browser( # use_cloud=True, # Uncomment to use a stealth browser on Browser Use Cloud ) llm = ChatBrowserUse() agent = Agent( task="Find the number of stars of the browser-use repo", llm=llm, browser=browser, ) history = await agent.run() return history if __name__ == "__main__": history = asyncio.run(example())

Check out the library docs and the cloud docs for more!

🔥 Deploy on Sandboxes

We handle agents, browsers, persistence, auth, cookies, and LLMs. The agent runs right next to the browser for minimal latency.

from browser_use import Browser, sandbox, ChatBrowserUse from browser_use.agent.service import Agent import asyncio @sandbox() async def my_task(browser: Browser): agent = Agent(task="Find the top HN post", browser=browser, llm=ChatBrowserUse()) await agent.run() # Just call it like any async function asyncio.run(my_task())

See Going to Production for more details.

🚀 Template Quickstart

Want to get started even faster? Generate a ready-to-run template:

uvx browser-use init --template default

This creates a browser_use_default.py file with a working example. Available templates:

  • default - Minimal setup to get started quickly
  • advanced - All configuration options with detailed comments
  • tools - Examples of custom tools and extending the agent

You can also specify a custom output path:

uvx browser-use init --template default --output my_agent.py

💻 CLI

Fast, persistent browser automation from the command line:

browser-use open https://example.com # Navigate to URL browser-use state # See clickable elements browser-use click 5 # Click element by index browser-use type "Hello" # Type text browser-use screenshot page.png # Take screenshot browser-use close # Close browser

The CLI keeps the browser running between commands for fast iteration. See CLI docs for all commands.

Claude Code Skill

For Claude Code, install the skill to enable AI-assisted browser automation:

mkdir -p ~/.claude/skills/browser-use curl -o ~/.claude/skills/browser-use/SKILL.md \ https://raw.githubusercontent.com/browser-use/browser-use/main/skills/browser-use/SKILL.md

Demos

📋 Form-Filling

Task = "Fill in this job application with my resume and information."

Job Application Demo Example code ↗

🍎 Grocery-Shopping

Task = "Put this list of items into my instacart."

https://github.com/user-attachments/assets/a6813fa7-4a7c-40a6-b4aa-382bf88b1850

Example code ↗

💻 Personal-Assistant.

Task = "Help me find parts for a custom PC."

https://github.com/user-attachments/assets/ac34f75c-057a-43ef-ad06-5b2c9d42bf06

Example code ↗

💡See more examples here ↗ and give us a star!

Integrations, hosting, custom tools, MCP, and more on our Docs ↗

FAQ

We optimized ChatBrowserUse() specifically for browser automation tasks. On avg it completes tasks 3-5x faster than other models with SOTA accuracy.

Pricing (per 1M tokens):

  • Input tokens: $0.20
  • Cached input tokens: $0.02
  • Output tokens: $2.00

For other LLM providers, see our supported models documentation.

Yes! You can add custom tools to extend the agent's capabilities:

from browser_use import Tools tools = Tools() @tools.action(description='Description of what this tool does.') def custom_tool(param: str) -> str: return f"Result: {param}" agent = Agent( task="Your task", llm=llm, browser=browser, tools=tools, )

Yes! Browser-Use is open source and free to use. You only need to choose an LLM provider (like OpenAI, Google, ChatBrowserUse, or run local models with Ollama).

Check out our authentication examples:

  • Using real browser profiles - Reuse your existing Chrome profile with saved logins
  • If you want to use temporary accounts with inbox, choose AgentMail
  • To sync your auth profile with the remote browser, run curl -fsSL https://browser-use.com/profile.sh | BROWSER_USE_API_KEY=XXXX sh (replace XXXX with your API key)

These examples show how to maintain sessions and handle authentication seamlessly.

For CAPTCHA handling, you need better browser fingerprinting and proxies. Use Browser Use Cloud which provides stealth browsers designed to avoid detection and CAPTCHA challenges.

Chrome can consume a lot of memory, and running many agents in parallel can be tricky to manage.

For production use cases, use our Browser Use Cloud API which handles:

  • Scalable browser infrastructure
  • Memory management
  • Proxy rotation
  • Stealth browser fingerprinting
  • High-performance parallel execution

Tell your computer what to do, and it gets it done.

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五维分析
清晰度8/10
创新性7/10
实用性9/10
完整性9/10
可维护性8/10
优缺点分析

优点

  • 支持多种 AI 模型以提供灵活性
  • 提供清晰的说明,易于设置
  • 提供基于云的选项以实现可扩展性
  • 包含 CLI 以快速实现浏览器自动化

缺点

  • 需要 API 密钥才能实现全部功能
  • 某些功能依赖于外部服务
  • 对不熟悉 Python 的新用户有学习曲线
  • 高级用例的示例有限

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免责声明:本内容来源于 GitHub 开源项目,仅供展示和评分分析使用。

版权归原作者所有 browser-use.