Human Quickstart

To get started with Browser Use you need to install the package and create an .env file with your API key.

ChatBrowserUse is optimized for browser automation. See the model benchmarks and current pricing, then get your API key here.

1. Installing Browser-Use

create environment

pip install uv
uv venv --python 3.12

activate environment

source .venv/bin/activate
# On Windows use `.venv\Scripts\activate`

install browser-use & chromium

uv pip install browser-use
uvx browser-use install

2. Choose your favorite LLM

Create a .env file and add your API key.

We recommend starting with ChatBrowserUse, which is optimized for browser automation tasks. See the model benchmarks and current pricing. Get your API key here.

.env

touch .env

On Windows, use echo. > .env

Then add your API key to the file.

# add your key to .env file
BROWSER_USE_API_KEY=
# Get your API key at https://cloud.browser-use.com/new-api-key

# add your key to .env file
GOOGLE_API_KEY=
# Get your free Gemini API key from https://aistudio.google.com/app/u/1/apikey?pli=1.

# add your key to .env file
OPENAI_API_KEY=

# add your key to .env file
ANTHROPIC_API_KEY=

See Supported Models for more.

3. Run your first agent

from browser_use import Agent, ChatBrowserUse
from dotenv import load_dotenv
import asyncio

load_dotenv()

async def main():
    llm = ChatBrowserUse()
    task = "Find the number 1 post on Show HN"
    agent = Agent(task=task, llm=llm)
    await agent.run()

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

from browser_use import Agent, ChatGoogle
from dotenv import load_dotenv
import asyncio

load_dotenv()

async def main():
    llm = ChatGoogle(model="gemini-flash-latest")
    task = "Find the number 1 post on Show HN"
    agent = Agent(task=task, llm=llm)
    await agent.run()

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

from browser_use import Agent, ChatOpenAI
from dotenv import load_dotenv
import asyncio

load_dotenv()

async def main():
    llm = ChatOpenAI(model="gpt-4.1-mini")
    task = "Find the number 1 post on Show HN"
    agent = Agent(task=task, llm=llm)
    await agent.run()

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

from browser_use import Agent, ChatAnthropic
from dotenv import load_dotenv
import asyncio

load_dotenv()

async def main():
    llm = ChatAnthropic(model='claude-sonnet-4-0', temperature=0.0)
    task = "Find the number 1 post on Show HN"
    agent = Agent(task=task, llm=llm)
    await agent.run()

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

Custom browsers can be configured in one line. Check out browsers for more.

4. Going to Production

Sandboxes package agents, browsers, persistence, authentication, cookies, and LLMs into a managed runtime. To run in production with authentication, add @sandbox to your function:

import asyncio
from browser_use import Browser, sandbox, ChatBrowserUse
from browser_use.agent.service import Agent

@sandbox(cloud_profile_id='your-profile-id')
async def production_task(browser: Browser):
    agent = Agent(
        task="Your authenticated task",
        browser=browser,
        llm=ChatBrowserUse(),
    )
    await agent.run()

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

See Browser Use Cloud for how to sync your cookies to the cloud.

Get Started

Customize

Examples

Development

1. Installing Browser-Use

2. Choose your favorite LLM

3. Run your first agent

4. Going to Production

​1. Installing Browser-Use

​2. Choose your favorite LLM

​3. Run your first agent

​4. Going to Production

1. Installing Browser-Use

2. Choose your favorite LLM

3. Run your first agent

4. Going to Production