lmnr-index 0.1.0

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

Index

Index is a state-of-the-art open-source browser agent that autonomously executes complex tasks on the web.

• It is powered by Claude 3.7 Sonnet with extented thinking. More models will be supported in the future.
• Index is also available as a hosted API.
• Supports advanced browser agent observability powered by Laminar.

prompt: go to ycombinator.com. summarize first 3 companies in the W25 batch and make new spreadsheet in google sheets.

https://github.com/user-attachments/assets/2b46ee20-81b6-4188-92fb-4d97fe0b3d6a

Index API

Index API is available as hosted api on the Laminar platform. 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 via 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())

When you call Index via API, you automatically get full browser agent observability on Laminar platform. Learn more about Index browser observability.

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(
        prompt="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)

Enable browser agent observability

To trace Index agent's actions and record browser session you simply need to initialize Laminar tracing before running the agent.

from lmnr import Laminar

Laminar.initialize(project_api_key="your_api_key")

Then you will get full observability on the agent's actions synced with the browser session in the Laminar platform.

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="<cdp_url>"
    )
    
    # 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 and browser
    agent = Agent(llm=llm, browser_config=browser_config)
    
    # Run the agent with a task
    output = await agent.run(
        prompt="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": 1200, "height": 900}
    )
    
    # 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_config=browser_config)
    
    # 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