lmnr-index 0.0.1

Index - SOTA browser AI agent for autonomous task execution on the web

Index

Index is a state-of-the-art browser agent that uses VLMs (vision-language models) to autonomously execute complex tasks on the web. Available as a Python package and as a hosted API.

Index API

Index API is available on Laminar. Index API manages remote browser sessions and agent infrastructure. Index API is the best way to run AI browser automation in production. To get started, sign up and create project API key.

Install Laminar

pip install lmnr

Use Index API

from lmnr import Laminar, AsyncLaminarClient
# you can also set LMNR_PROJECT_API_KEY environment variable

# Initialize tracing
Laminar.initialize(project_api_key="your_api_key")

# Initialize the client
client = AsyncLaminarClient(api_key="your_api_key")

async def main():

    # Run a task
    response = await client.agent.run(
        prompt="Navigate to news.ycombinator.com, find a post about AI, and summarize it"
    )

    # Print the result
    print(response.result)
    
if __name__ == "__main__":
    asyncio.run(main())

Local Quick Start

Install dependencies

pip install lmnr-index

# Install playwright
playwright install chromium

Run the agent

import asyncio
from lmnr_index import Agent, AnthropicProvider

async def main():
    # Initialize the LLM provider
    llm = AnthropicProvider(
            model="claude-3-7-sonnet-20250219",
            enable_thinking=True, 
            thinking_token_budget=2048)
    
    # Create an agent with the LLM
    agent = Agent(llm=llm)
    
    # Run the agent with a task
    output = await agent.run(
        "Navigate to news.ycombinator.com, find a post about AI, and summarize it"
    )
    
    # Print the result
    print(output.result)
    
if __name__ == "__main__":
    asyncio.run(main())

Stream the agent's output

from lmnr_index import Agent, AnthropicProvider

agent = Agent(llm=AnthropicProvider(model="claude-3-7-sonnet-20250219"))    

# Stream the agent's output
async for chunk in agent.run_stream(
    prompt="Navigate to news.ycombinator.com, find a post about AI, and summarize it"):
    print(chunk)

Run with remote CDP url

import asyncio
from lmnr_index import Agent, AnthropicProvider, Browser, BrowserConfig

async def main():
    # Configure browser to connect to an existing Chrome DevTools Protocol endpoint
    browser_config = BrowserConfig(
        cdp_url="ws://localhost:9222/devtools/browser/[session-id]"
    )
    
    # Create browser with the config
    browser = Browser(config=browser_config)
    
    # Initialize the LLM provider
    llm = AnthropicProvider(model="claude-3-7-sonnet-20250219")
    
    # Create an agent with the LLM and browser
    agent = Agent(llm=llm, browser=browser)
    
    # Run the agent with a task
    output = await agent.run(
        "Navigate to news.ycombinator.com and find the top story"
    )
    
    # Print the result
    print(output.result)
    
if __name__ == "__main__":
    asyncio.run(main())

Customize browser window size

import asyncio
from lmnr_index import Agent, AnthropicProvider, Browser, BrowserConfig

async def main():
    # Configure browser with custom viewport size
    browser_config = BrowserConfig(
        viewport_size={"width": 1920, "height": 1080}  # Full HD resolution
    )
    
    # Create browser with the config
    browser = Browser(config=browser_config)
    
    # Initialize the LLM provider
    llm = AnthropicProvider(model="claude-3-7-sonnet-20250219")
    
    # Create an agent with the LLM and browser
    agent = Agent(llm=llm, browser=browser)
    
    # Run the agent with a task
    output = await agent.run(
        "Navigate to a responsive website and capture how it looks in full HD resolution"
    )
    
    # Print the result
    print(output.result)
    
if __name__ == "__main__":
    asyncio.run(main())

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Made with ❤️ by the Laminar team