AI Skill Hub 强烈推荐:browser-use Agent工作流 是一款优质的Agent工作流。在 GitHub 上收获超过 93.6k 颗 Star,AI 综合评分 8.8 分,在同类工具中表现稳健。如果你正在寻找可靠的Agent工作流解决方案,这是一个值得深入了解的选择。
browser-use Agent工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
browser-use Agent工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一:pip 安装(推荐)
pip install browser-use
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install browser-use
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/browser-use/browser-use
cd browser-use
pip install -e .
# 验证安装
python -c "import browser_use; print('安装成功')"
# 命令行使用
browser-use --help
# 基本用法
browser-use input_file -o output_file
# Python 代码中调用
import browser_use
# 示例
result = browser_use.process("input")
print(result)
# browser-use 配置文件示例(config.yml) app: name: "browser-use" debug: false log_level: "INFO" # 运行时指定配置文件 browser-use --config config.yml # 或通过环境变量配置 export BROWSER_USE_API_KEY="your-key" export BROWSER_USE_OUTPUT_DIR="./output"
<picture> <source media="(prefers-color-scheme: light)" srcset="https://github.com/user-attachments/assets/2ccdb752-22fb-41c7-8948-857fc1ad7e24"> <source media="(prefers-color-scheme: dark)" srcset="https://github.com/user-attachments/assets/774a46d5-27a0-490c-b7d0-e65fcbbfa358"> <img alt="Shows a black Browser Use Logo in light color mode and a white one in dark color mode." src="https://github.com/user-attachments/assets/2ccdb752-22fb-41c7-8948-857fc1ad7e24" width="full"> </picture>
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**2. Add your LLM API key to `.env`**. Get one from [Browser Use Cloud](https://cloud.browser-use.com/new-api-key?utm_source=github&utm_medium=readme-quickstart-api-key), or bring your own provider key:
bash
If you want to use Browser Use in your agent (Claude Code, Codex, Cursor, Hermes, OpenClaw, etc.), paste this prompt, and it sets everything up itself:
Install or upgrade browser-use to the latest stable version with uv using Python 3.12, run `browser-use skill install` to register the skill, and connect it to my browser. If setup or connection fails, follow https://github.com/browser-use/browser-harness/blob/main/install.md.
Then tell your agent what you want done.
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BROWSER_USE_API_KEY=your-key
**3. Run your first agent:**
python import asyncio
from browser_use import Agent, ChatBrowserUse
async def main(): agent = Agent( task="Find the number of stars of the browser-use repo", llm=ChatBrowserUse(model='openai/gpt-5.5'), # llm=ChatBrowserUse(model='bu-2-0-mini-preview'), # Browser Use's optimized model # llm=ChatOpenAI(model='gpt-5.5'), # llm=ChatAnthropic(model='claude-opus-4-8'), # Sonnet also works well ) history = await agent.run()
if name == "main": asyncio.run(main()) ```
Check out the library docs and the cloud docs for more!
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<picture> <source media="(prefers-color-scheme: light)" srcset="static/accuracy_by_model_light.png"> <source media="(prefers-color-scheme: dark)" srcset="static/accuracy_by_model_dark.png"> <img alt="BU Bench V1 - LLM Success Rates" src="static/accuracy_by_model_light.png" width="100%"> </picture>
We benchmark Browser Use across 100 real-world browser tasks. Full benchmark is open source: browser-use/benchmark.
Browser Use is also #1 on the Odysseys leaderboard with an 87.4% average, ahead of computer-use agents from OpenAI, Anthropic, Google, and Microsoft. Odysseys measures the agent's performance on 200 long-horizon web tasks.
Use the Open-Source Agent - Free, and runs on your own machine - Deep code-level integration and control: pick your LLM, customize the agent's behavior - We recommend pairing it with our cloud browsers for leading stealth, proxy rotation, and scaling
Use the Fully-Hosted Cloud Agent (recommended) - Much more powerful agent for complex tasks (see plot above) - Easiest way to start and scale - Best stealth with proxy rotation and captcha solving - 1000+ integrations (Gmail, Slack, Notion, and more) - Persistent filesystem and memory - Rerunnable scripts fetch live data, even when sites change (guide)
curl -X POST https://api.browser-use.com/api/v4/runs \
-H "X-Browser-Use-API-Key: $BROWSER_USE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"task": "Your task"}'
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<details> <summary><b>Should I use the CLI vs. the Python library?</b></summary>
Use the CLI if you already have an agent (Claude Code, Codex, Cursor, Hermes, OpenClaw, etc.) that you want to complete browser tasks for you. The agent installs the skill once (see Quickstart) and can then control the browser. Examples: - "Upload this video to YouTube" - "Compare these three laptops and give me a table with prices" - "Fill in this job application with my resume"
Use the Python library when you are building software that automates the web. Examples: - Run many tasks on a schedule or in parallel (scraping, monitoring, QA) - Embed a browser agent into your own product - Custom tools, custom system prompts, structured output, fine-grained browser control
Rule of thumb: one-off tasks through an agent → CLI. Repeatable automation in code → Python library. </details>
<details> <summary><b>What's the best model to use?</b></summary>
We optimized ChatBrowserUse() specifically for browser automation tasks. On avg it completes tasks 3-5x faster than other models with SOTA accuracy.
For pricing and other LLM providers, see our supported models documentation. </details>
<details> <summary><b>Can I use Claude / GPT / Gemini through ChatBrowserUse?</b></summary>
Yes. ChatBrowserUse accepts provider-prefixed model ids, so a single BROWSER_USE_API_KEY reaches all of them — no separate OpenAI/Anthropic/Google keys required:
from browser_use import Agent, ChatBrowserUse
llm = ChatBrowserUse(model='anthropic/claude-sonnet-4-6') # or 'openai/gpt-5.5', 'google/gemini-3-pro'
agent = Agent(task='...', llm=llm)
For the best speed and cost we still recommend the default bu-* models. </details>
<details> <summary><b>Should I use the Browser Use system prompt with the open-source preview model?</b></summary>
Yes. If you use ChatBrowserUse(model='browser-use/bu-30b-a3b-preview') with a normal Agent(...), Browser Use still sends its default agent system prompt for you.
You do not need to add a separate custom "Browser Use system message" just because you switched to the open-source preview model. Only use extend_system_message or override_system_message when you intentionally want to customize the default behavior for your task.
If you want the best default speed/accuracy, we still recommend the newer hosted bu-* models. If you want the open-source preview model, the setup stays the same apart from the model= value. </details>
<details> <summary><b>Can I use custom tools with the agent?</b></summary>
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,
)
</details>
<details> <summary><b>Can I use this for free?</b></summary>
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). </details>
<details> <summary><b>Terms of Service</b></summary>
This open-source library is licensed under the MIT License. For Browser Use services & data policy, see our Terms of Service and Privacy Policy. </details>
<details> <summary><b>How do I handle authentication?</b></summary>
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 a remote browser, install profile-use for your platform from the official releases, then follow the profile sync guide.
These examples show how to maintain sessions and handle authentication seamlessly. </details>
<details> <summary><b>How do I solve CAPTCHAs?</b></summary>
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. </details>
<details> <summary><b>How do I go into production?</b></summary>
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 </details>
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本项目是一个简介,介绍了项目的基本信息。
如果您没有 Chromium,使用以下命令安装:uvx browser-use install。您还可以获取 Browser Use Cloud 的 API 密钥。
使用 LLM Quickstart,直接将您的编码代理(如 Cursor、Claude Code 等)指向 Agents.md。或者,您可以使用 Human Quickstart,创建环境并安装 Browser-Use,使用 uv (Python>=3.11)。
配置文件中包含了 BROWSER_USE_API_KEY 等关键参数。您可以在 .env 文件中设置这些参数。
API 文档中包含了 Google API 密钥、Anthropic API 密钥等信息。您需要在配置文件中设置这些参数。
工作流 / 模块说明中介绍了项目的整体架构,包括 Integrations、hosting、custom tools、MCP 等功能。
FAQ 中回答了常见问题,包括最佳模型选择、定价信息等。
工程化完善的AI自动化框架,9.3万Stars体现高热度。核心创新在将LLM与浏览器交互深度融合,降低Web自动化门槛。代码质量优秀,文档完整,生产环境友好。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
总体来看,browser-use Agent工作流 是一款质量优秀的Agent工作流,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | browser-use |
| 原始描述 | 开源AI工作流:🌐 Make websites accessible for AI agents. Automate tasks online with ease.。⭐93.6k · Python |
| Topics | 浏览器自动化AI智能体工作流网页自动化LLM应用 |
| GitHub | https://github.com/browser-use/browser-use |
| License | MIT |
| 语言 | Python |
收录时间:2026-05-13 · 更新时间:2026-05-16 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
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