Human Quickstart - Browser Use

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

ChatBrowserUse offers the fastest and most cost-effective models, completing tasks 3-5x faster. New users get 5 free tasks. 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 using ChatBrowserUse which is optimized for browser automation tasks (highest accuracy + fastest speed + lowest token cost). Get your API key here — new users get 5 free tasks.

.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 - new users get 5 free tasks

# 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 are the easiest way to run Browser-Use in production. We handle agents, browsers, persistence, auth, cookies, and LLMs. It is also the fastest way to deploy - the agent runs right next to the browser, so latency is minimal. 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.

​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