Browser-Use Automation

AI-powered browser automation that executes web tasks from natural language descriptions using the browser-use Python library.

Quick Start

Browser-use enables browser automation through natural language task descriptions:

from browser_use import Agent, Browser, ChatBrowserUse
import asyncio

async def automate():
    browser = Browser()
    llm = ChatBrowserUse()

    agent = Agent(
        task="Go to github.com/browser-use/browser-use and find the star count",
        llm=llm,
        browser=browser,
    )

    result = await agent.run()
    await browser.close()
    return result

asyncio.run(automate())

Installation

Before using browser-use, ensure it's installed. Check and install automatically:

python scripts/check_install.py

Or install manually:

pip install browser-use

Core Workflow

1. Understand the Task

Identify what the user wants to accomplish:

• Data extraction: Scraping content, collecting information
• Form automation: Filling forms, submitting data
• Testing: Verifying functionality, checking elements
• Navigation: Multi-step processes, conditional flows

2. Write the Task Description

Translate the user's request into a clear, specific task description for the AI agent. Be explicit about:

• Target URL or starting point
• Specific actions to take
• Data to extract or input
• Expected outcome

Good example: "Go to example.com/products, filter by category 'Electronics', and extract the name and price of the first 10 products"

Avoid: "Get product data" (too vague)

3. Create the Automation Script

Use the basic pattern from scripts/basic_automation.py:

from browser_use import Agent, Browser, ChatBrowserUse
import asyncio

async def run_task(task_description: str):
    browser = Browser()
    llm = ChatBrowserUse()

    agent = Agent(
        task=task_description,
        llm=llm,
        browser=browser,
    )

    try:
        result = await agent.run()
        return result
    finally:
        await browser.close()

# Run it
result = asyncio.run(run_task("Your task here"))

4. Execute and Iterate

Run the script and adjust the task description if needed for better results.

Common Task Patterns

Web Scraping

Extract data from websites:

task = "Go to news.ycombinator.com and extract the titles of the top 10 stories"

Form Filling

Automate form submission:

task = """
Go to example.com/contact-us
Fill out the form with:
- Name: John Doe
- Email: john@example.com
- Message: I'm interested in your services
Then click Submit
"""

Multi-Step Navigation

Handle complex workflows:

task = """
1. Go to example.com
2. Click on 'Products' in the navigation
3. Filter by price range $50-$100
4. Sort by 'Most Popular'
5. Click on the first product and get its description
"""

Conditional Logic

Handle dynamic scenarios:

task = """
Go to example.com/dashboard
If prompted to log in, use username 'user@example.com' and password 'secure123'
Once logged in, navigate to Settings and export data
"""

Advanced Features

Headless Mode

Run browser without UI for faster execution:

browser = Browser(headless=True)

Stealth Mode

Avoid detection for sensitive scraping:

browser = Browser(stealth=True)

Custom Tools

Extend agent capabilities with custom functions:

from browser_use import Controller

@Controller.action("Save to file")
def save_data(content: str, filename: str):
    with open(filename, 'w') as f:
        f.write(content)
    return f"Saved to {filename}"

controller = Controller()
agent = Agent(task="...", llm=llm, browser=browser, controller=controller)

Cloud Browsers

Use cloud-hosted browsers:

browser = Browser(cloud=True, cloud_provider="browserbase")

Detailed Patterns

For comprehensive examples including data extraction patterns, form automation, navigation strategies, and error handling, see:

references/common_patterns.md

Load this file when you need detailed code examples or are implementing complex automation workflows.

Best Practices

1. Be specific in task descriptions - The more detailed, the better the AI performs
2. Use headless mode by default - Faster and more resource-efficient
3. Always close browsers - Use try/finally blocks to ensure cleanup
4. Handle errors gracefully - Wrap automation in try/except blocks
5. Test incrementally - Start with simple tasks and add complexity
6. Reuse browser instances - For multiple related tasks, keep browser open between operations

Troubleshooting

Task not completing correctly:

• Make task description more specific
• Break complex tasks into smaller steps
• Check if website requires authentication

Installation issues:

• Run scripts/check_install.py to verify installation
• Ensure Python 3.8+ is installed
• Check for dependency conflicts

Browser crashes or hangs:

• Use headless mode to reduce resource usage
• Ensure sufficient system memory
• Check for website anti-bot measures