browser-use Agent工作流

Quickstart

.env

OPENAI_API_KEY=your-key

BROWSER_USE_API_KEY=your-key # Optional: BU2 model or cloud browser

For either optional Browser Use service, get a [Browser Use API key](https://cloud.browser-use.com/new-api-key).

**3. Save this as `agent.py`:**

from browser_use import Agent, Browser, ChatBrowserUse, ChatOpenAI from dotenv import load_dotenv

load_dotenv()

async def main(): llm = ChatOpenAI(model='gpt-5.6-luna', reasoning_effort='xhigh') # llm = ChatBrowserUse(model='bu-2-0') # Use BU2 instead; requires BROWSER_USE_API_KEY agent = Agent( task="Find the number of stars of the browser-use repo", llm=llm, # browser=Browser(use_cloud=True), # Use a cloud browser; requires BROWSER_USE_API_KEY ) history = await agent.run() print(history.final_result())

if name == "main": asyncio.run(main())

To use BU2, replace the `ChatOpenAI` line with the commented `ChatBrowserUse` line. The cloud-browser option works with either model.

**4. Run it:**

The agent opens a browser, looks up the repository, and prints its answer.

Python library docs ↗

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Integrations, hosting, custom tools, MCP, and more on our [Docs ↗](https://docs.browser-use.com)

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FAQ

<details> <summary><b>Should I use the fully hosted cloud, CLI, or Python library?</b></summary>

• Fully Hosted Cloud: Send tasks through the API and let Browser Use run the agent, browser, and infrastructure.
• CLI: Give an existing agent (Claude Code, Codex, Hermes, OpenClaw, Pi, Cursor, etc.) browser access. You can use it interactively or in scripts.
• Python Library: Run the open source agent in your own application, with custom tools, structured output, and your choice of model.

The CLI and Python library can each connect to a local or cloud browser. A cloud browser hosts the browser; the fully hosted API runs the agent as well. </details>

<details> <summary><b>What's the best model to use?</b></summary>

We recommend BU2, our model optimized for browser automation: ChatBrowserUse(model='bu-2-0'). It uses BROWSER_USE_API_KEY; ChatBrowserUse() currently selects the same model.

The best choice depends on your tasks, latency, and budget. See the BU2 model card, benchmark, and supported models and pricing to compare options. </details>

<details> <summary><b>Can I use Claude / GPT / Gemini through ChatBrowserUse?</b></summary>

Yes. ChatBrowserUse accepts provider-prefixed model IDs through the Browser Use gateway, using BROWSER_USE_API_KEY:

from browser_use import Agent, ChatBrowserUse

llm = ChatBrowserUse(model='anthropic/claude-sonnet-4-6')  # or 'google/gemini-3-pro'
agent = Agent(task='...', llm=llm)

You can also use providers directly through wrappers such as ChatOpenAI, ChatAnthropic, and ChatGoogle, with each provider's own API key. See supported models. </details>

<details> <summary><b>Do I need to provide a system prompt?</b></summary>

No. Agent(...) supplies the Browser Use system prompt automatically, including when you change models. Put your task in task=. Use extend_system_message to add instructions or override_system_message to replace the default prompt when you need custom behavior.

See the custom system prompt example. </details>

<details> <summary><b>Can I use custom tools with the agent?</b></summary>

Yes. Register a function with Tools and pass it to the agent. This example adds a tool for the current UTC time and uses BROWSER_USE_API_KEY from .env:

import asyncio
from datetime import datetime, timezone

from browser_use import ActionResult, Agent, ChatBrowserUse, Tools
from dotenv import load_dotenv

load_dotenv()
tools = Tools()

@tools.action(description='Get the current date and time in UTC.')
def get_current_time() -> ActionResult:
    return ActionResult(extracted_content=datetime.now(timezone.utc).isoformat())

async def main():
    agent = Agent(
        task="What is the current UTC time?",
        llm=ChatBrowserUse(model='bu-2-0'),
        tools=tools,
    )
    history = await agent.run()
    print(history.final_result())

if __name__ == "__main__":
    asyncio.run(main())

</details>

<details> <summary><b>Can I use this for free?</b></summary>

The Python library is free and MIT-licensed. Model inference and hosted browsers are separate: API providers, including ChatBrowserUse, and Browser Use Cloud charge for usage. You can also use a local browser and a local model through Ollama, subject to your hardware and model requirements. </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>

• Local browser: Use Browser.from_system_chrome() to reuse a Chrome profile. See the real-browser guide and example.
• Cloud browser: Follow the profile sync guide, then use Browser(use_cloud=True, cloud_profile_id='your-profile-id').

Profile sync transfers cookies, not local storage, IndexedDB, or extensions. Some sites may require you to sign in again. </details>

<details> <summary><b>How do I solve CAPTCHAs?</b></summary>

Browser Use Cloud provides stealth browsers and proxies designed to reduce bot detection and CAPTCHA challenges. With the Python library, enable a cloud browser with Browser(use_cloud=True) and set BROWSER_USE_API_KEY.

Results depend on the site and challenge; no browser configuration guarantees that every CAPTCHA can be avoided or solved. </details>

<details> <summary><b>How do I go into production?</b></summary>

Choose how much you want to manage:

• Keep your agent code: Connect the CLI or Python library to cloud browsers for managed browser infrastructure, stealth, profiles, and recordings.
• Have us run the agent too: Use the fully hosted Cloud API to submit tasks and retrieve results.

You can also host the Python library and browsers on your own infrastructure. </details>

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