Source repos: shadcn/ui, vercel-labs/agent-skills, coreyhaines31/marketingskills, supabase/agent-skills, vercel-labs/next-skills, kepano/obsidian-skills, pbakaus/impeccable, browser-use/browser-use Categories: - shadcn (1): shadcn UI component system - vercel (7): react-best-practices, composition-patterns, deploy-to-vercel, etc. - marketing (35): seo-audit, copywriting, marketing-psychology, pricing-strategy, etc. - supabase (2): postgres-best-practices, supabase - next.js (3): next-best-practices, next-cache-components, next-upgrade - obsidian (5): obsidian-markdown, obsidian-cli, obsidian-bases, json-canvas, defuddle - impeccable (21): polish, animate, critique, colorize, audit, harden, etc. - browser-use (4): browser automation and testing Location: personas/_shared/community-skills/ Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Quickstart & Production Deployment
Table of Contents
Installation
pip install uv
uv venv --python 3.12
source .venv/bin/activate # Windows: .venv\Scripts\activate
uv pip install browser-use
uvx browser-use install # Downloads Chromium
Environment Variables
# Browser Use (recommended) — https://cloud.browser-use.com/new-api-key
BROWSER_USE_API_KEY=
# Google — https://aistudio.google.com/app/u/1/apikey
GOOGLE_API_KEY=
# OpenAI
OPENAI_API_KEY=
# Anthropic
ANTHROPIC_API_KEY=
First Agent
ChatBrowserUse (Recommended — fastest, cheapest, highest accuracy)
from browser_use import Agent, ChatBrowserUse
from dotenv import load_dotenv
import asyncio
load_dotenv()
async def main():
llm = ChatBrowserUse()
agent = Agent(task="Find the number 1 post on Show HN", llm=llm)
await agent.run()
if __name__ == "__main__":
asyncio.run(main())
Google Gemini
from browser_use import Agent, ChatGoogle
from dotenv import load_dotenv
import asyncio
load_dotenv()
async def main():
llm = ChatGoogle(model="gemini-flash-latest")
agent = Agent(task="Find the number 1 post on Show HN", llm=llm)
await agent.run()
if __name__ == "__main__":
asyncio.run(main())
OpenAI
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")
agent = Agent(task="Find the number 1 post on Show HN", llm=llm)
await agent.run()
if __name__ == "__main__":
asyncio.run(main())
Anthropic
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)
agent = Agent(task="Find the number 1 post on Show HN", llm=llm)
await agent.run()
if __name__ == "__main__":
asyncio.run(main())
See references/open-source/models.md for all 15+ providers.
Production with @sandbox
The @sandbox decorator is the easiest way to deploy to production. The agent runs next to the browser on cloud infrastructure with minimal latency.
Basic Deployment
from browser_use import Browser, sandbox, ChatBrowserUse
from browser_use.agent.service import Agent
import asyncio
@sandbox()
async def my_task(browser: Browser):
agent = Agent(task="Find the top HN post", browser=browser, llm=ChatBrowserUse())
await agent.run()
asyncio.run(my_task())
With Proxies
@sandbox(cloud_proxy_country_code='us')
async def stealth_task(browser: Browser):
agent = Agent(task="Your task", browser=browser, llm=ChatBrowserUse())
await agent.run()
With Authentication (Profile Sync)
- Sync local cookies:
export BROWSER_USE_API_KEY=your_key && curl -fsSL https://browser-use.com/profile.sh | sh
- Use the returned profile_id:
@sandbox(cloud_profile_id='your-profile-id')
async def authenticated_task(browser: Browser):
agent = Agent(task="Your authenticated task", browser=browser, llm=ChatBrowserUse())
await agent.run()
Sandbox Parameters
| Parameter | Type | Description | Default |
|---|---|---|---|
BROWSER_USE_API_KEY |
str | API key (env var) | Required |
cloud_profile_id |
str | Browser profile UUID | None |
cloud_proxy_country_code |
str | us, uk, fr, it, jp, au, de, fi, ca, in | None |
cloud_timeout |
int | Minutes (max: 15 free, 240 paid) | None |
on_browser_created |
Callable | Receives data.live_url |
None |
on_log |
Callable | Receives log.level, log.message |
None |
on_result |
Callable | Success callback | None |
on_error |
Callable | Receives error.error |
None |
Event Callbacks
from browser_use.sandbox import BrowserCreatedData, LogData, ResultData, ErrorData
@sandbox(
cloud_profile_id='your-profile-id',
cloud_proxy_country_code='us',
on_browser_created=lambda data: print(f'Live: {data.live_url}'),
on_log=lambda log: print(f'{log.level}: {log.message}'),
on_result=lambda result: print('Done!'),
on_error=lambda error: print(f'Error: {error.error}'),
)
async def task(browser: Browser):
agent = Agent(task="your task", browser=browser, llm=ChatBrowserUse())
await agent.run()
All callbacks can be sync or async.
Local Development
git clone https://github.com/browser-use/browser-use
cd browser-use
uv sync --all-extras --dev
# Helper scripts
./bin/setup.sh # Complete setup
./bin/lint.sh # Formatting, linting, type checking
./bin/test.sh # CI test suite
# Run examples
uv run examples/simple.py
Telemetry
Opt out with ANONYMIZED_TELEMETRY=false env var. Zero performance impact.