Quickstart

# Create a project directory
mkdir steel-browser-use-agent
cd steel-browser-use-agent

# Recommended: Create and activate a virtual environment
uv venv
source .venv/bin/activate  # On Windows, use: .venv\Scripts\activate

# Install required packages
pip install steel-sdk browser-use python-dotenv

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STEEL_API_KEY=your_steel_api_key_here
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OPENAI_API_KEY=your_openai_api_key_here
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TASK=Go to Wikipedia and search for machine learning

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import os
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from steel import Steel
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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STEEL_API_KEY = os.getenv("STEEL_API_KEY") or "your-steel-api-key-here"
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# Validate API key
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if STEEL_API_KEY == "your-steel-api-key-here":
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    print("⚠️  WARNING: Please replace with your actual Steel API key")
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    print("   Get your API key at: https://app.steel.dev/settings/api-keys")
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    return
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# Create a Steel browser session
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client = Steel(steel_api_key=STEEL_API_KEY)
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session = client.sessions.create()
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print("✅ Steel browser session started!")
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print(f"View live session at: {session.session_viewer_url}")

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from browser_use import Agent, BrowserSession
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# Connect browser-use to the Steel session
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cdp_url = f"wss://connect.steel.dev?apiKey={STEEL_API_KEY}&sessionId={session.id}"
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browser_session = BrowserSession(cdp_url=cdp_url)

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# After setting up the browser session
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from browser_use import Agent
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from browser_use.llm import ChatOpenAI
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# Create a ChatOpenAI model for agent reasoning
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model = ChatOpenAI(
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    model="gpt-4o",
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    temperature=0.3,
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    api_key=os.getenv('OPENAI_API_KEY')
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)
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# Define the task for the agent
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task = os.getenv("TASK") or "Go to Wikipedia and search for machine learning"
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# Create the agent with the task, model, and browser session
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agent = Agent(
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    task=task,
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    llm=model,
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    browser_session=browser_session,
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)

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import time
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# Define the main function with the agent execution
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async def main():
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    try:
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        start_time = time.time()
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        print(f"🎯 Executing task: {task}")
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        print("=" * 60)
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        # Run the agent
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        result = await agent.run()
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        duration = f"{(time.time() - start_time):.1f}"
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        print("\n" + "=" * 60)
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        print("🎉 TASK EXECUTION COMPLETED")
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        print("=" * 60)
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        print(f"⏱️  Duration: {duration} seconds")
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        print(f"🎯 Task: {task}")
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        if result:
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            print(f"📋 Result:\n{result}")
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        print("=" * 60)
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    except Exception as e:
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        print(f"❌ Task execution failed: {e}")
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    finally:
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        # Clean up resources
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        if session:
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            print("Releasing Steel session...")
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            client.sessions.release(session.id)
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            print(f"Session completed. View replay at {session.session_viewer_url}")
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        print("Done!")
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# Run the async main function
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if __name__ == '__main__':
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    asyncio.run(main())

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"""
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AI-powered browser automation using browser-use library with Steel browsers.
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https://github.com/steel-dev/steel-cookbook/tree/main/examples/steel-browser-use-starter
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"""
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import os
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import time
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import asyncio
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from dotenv import load_dotenv
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from steel import Steel
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from browser_use import Agent, BrowserSession
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from browser_use.llm import ChatOpenAI
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load_dotenv()
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# Replace with your own API keys
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STEEL_API_KEY = os.getenv("STEEL_API_KEY") or "your-steel-api-key-here"
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") or "your-openai-api-key-here"
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# Replace with your own task
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TASK = os.getenv("TASK") or "Go to Wikipedia and search for machine learning"
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async def main():
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    print("🚀 Steel + Browser Use Assistant")
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    print("=" * 60)
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    if STEEL_API_KEY == "your-steel-api-key-here":
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        print("⚠️  WARNING: Please replace 'your-steel-api-key-here' with your actual Steel API key")
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        print("   Get your API key at: https://app.steel.dev/settings/api-keys")
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        return
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    if OPENAI_API_KEY == "your-openai-api-key-here":
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        print("⚠️  WARNING: Please replace 'your-openai-api-key-here' with your actual OpenAI API key")
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        print("   Get your API key at: https://platform.openai.com/api-keys")
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        return
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    print("\nStarting Steel browser session...")
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    client = Steel(steel_api_key=STEEL_API_KEY)
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    try:
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        session = client.sessions.create()
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        print("✅ Steel browser session started!")
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        print(f"View live session at: {session.session_viewer_url}")
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        print(
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            f"\033[1;93mSteel Session created!\033[0m\n"
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            f"View session at \033[1;37m{session.session_viewer_url}\033[0m\n"
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        )
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        cdp_url = f"wss://connect.steel.dev?apiKey={STEEL_API_KEY}&sessionId={session.id}"
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        model = ChatOpenAI(model="gpt-4o", temperature=0.3, api_key=OPENAI_API_KEY)
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        agent = Agent(task=TASK, llm=model, browser_session=BrowserSession(cdp_url=cdp_url))
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        start_time = time.time()
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        print(f"🎯 Executing task: {TASK}")
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        print("=" * 60)
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        try:
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            result = await agent.run()
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            duration = f"{(time.time() - start_time):.1f}"
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            print("\n" + "=" * 60)
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            print("🎉 TASK EXECUTION COMPLETED")
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            print("=" * 60)
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            print(f"⏱️  Duration: {duration} seconds")
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            print(f"🎯 Task: {TASK}")
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            if result:
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                print(f"📋 Result:\n{result}")
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            print("=" * 60)
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        except Exception as e:
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            print(f"❌ Task execution failed: {e}")
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        finally:
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            if session:
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                print("Releasing Steel session...")
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                client.sessions.release(session.id)
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                print(f"Session completed. View replay at {session.session_viewer_url}")
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            print("Done!")
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    except Exception as e:
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        print(f"❌ Failed to start Steel browser: {e}")
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        print("Please check your STEEL_API_KEY and internet connection.")
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if __name__ == "__main__":
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    asyncio.run(main())

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# Search for weather information
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TASK = "Go to https://weather.com, search for 'San Francisco', and tell me today's forecast."
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# Research product information
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TASK = "Go to https://www.amazon.com, search for 'wireless headphones', and summarize the features of the first product."
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# Visit a documentation site
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TASK = "Go to https://docs.steel.dev, find information about the Steel API, and summarize the key features."