Speedofmastery's picture
Merge Landrun + Browser-Use + Chromium with AI agent support (without binary files)
d7b3d84
"""
Getting Started Example 3: Data Extraction
This example demonstrates how to:
- Navigate to a website with structured data
- Extract specific information from the page
- Process and organize the extracted data
- Return structured results
This builds on previous examples by showing how to get valuable data from websites.
Setup:
1. Get your API key from https://cloud.browser-use.com/new-api-key
2. Set environment variable: export BROWSER_USE_API_KEY="your-key"
"""
import asyncio
import os
import sys
# Add the parent directory to the path so we can import browser_use
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
from dotenv import load_dotenv
load_dotenv()
from browser_use import Agent, ChatBrowserUse
async def main():
# Initialize the model
llm = ChatBrowserUse()
# Define a data extraction task
task = """
Go to https://quotes.toscrape.com/ and extract the following information:
- The first 5 quotes on the page
- The author of each quote
- The tags associated with each quote
Present the information in a clear, structured format like:
Quote 1: "[quote text]" - Author: [author name] - Tags: [tag1, tag2, ...]
Quote 2: "[quote text]" - Author: [author name] - Tags: [tag1, tag2, ...]
etc.
"""
# Create and run the agent
agent = Agent(task=task, llm=llm)
await agent.run()
if __name__ == '__main__':
asyncio.run(main())