> ## Documentation Index
> Fetch the complete documentation index at: https://docs.anchorbrowser.io/llms.txt
> Use this file to discover all available pages before exploring further.
# Browser-use
This guide is dedicated to running your own browser-use agent while connecting to an Anchor browser. To use the embedded browser use capability, refer to [AI task completion](/agentic-browser-control/ai-task-completion)
```python python theme={null}
from anchorbrowser import Anchorbrowser
import os
anchor_client = Anchorbrowser(
api_key=os.getenv("ANCHOR_API_KEY")
)
session = anchor_client.sessions.create()
cdp_url = session.data.cdp_url
print("Session's CDP_URL for later use\n", cdp_url)
```
```python python theme={null}
from browser_use import Agent, Controller
from browser_use.browser import BrowserProfile, BrowserSession
from browser_use.llm import ChatOpenAI
import os
# Configure your LLM (example with OpenAI)
llm = ChatOpenAI(
model='gpt-4o',
api_key=os.getenv('OPENAI_API_KEY'),
)
# Initialize browser session with Anchor
profile = BrowserProfile(keep_alive=True)
browser_session = BrowserSession(
headless=False,
cdp_url=cdp_url,
browser_profile=profile
)
# Create controller and agent
controller = Controller()
agent = Agent(
task="Your task description here",
llm=llm,
enable_memory=False,
use_vision=False,
controller=controller,
browser_session=browser_session,
)
# Run the agent
result = await agent.run(max_steps=40)
```
Use the `live_view_url` returned on the first step to view the browser session in real-time, or to embed it as a UI component
```html theme={null}
```