chore: import upstream snapshot with attribution

examples/getting_started/04_multi_step_task.py

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+"""
+Getting Started Example 4: Multi-Step Task
+
+This example demonstrates how to:
+- Perform a complex workflow with multiple steps
+- Navigate between different pages
+- Combine search, form filling, and data extraction
+- Handle a realistic end-to-end scenario
+
+This is the most advanced getting started example, combining all previous concepts.
+
+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(model='bu-2-0')
+
+	# Define a multi-step task
+	task = """
+    I want you to research Python web scraping libraries. Here's what I need:
+    
+    1. First, search Google for "best Python web scraping libraries 2024"
+    2. Find a reputable article or blog post about this topic
+    3. From that article, extract the top 3 recommended libraries
+    4. For each library, visit its official website or GitHub page
+    5. Extract key information about each library:
+       - Name
+       - Brief description
+       - Main features or advantages
+       - GitHub stars (if available)
+    
+    Present your findings in a summary format comparing the three libraries.
+    """
+
+	# Create and run the agent
+	agent = Agent(task=task, llm=llm)
+	await agent.run()
+
+
+if __name__ == '__main__':
+	asyncio.run(main())