​
Anchor Browser + Groq: Blazing, Accurate Fast Browser Agents

Groq is the fast inference paltform, providing llm APIs with low time-to-first-token and time-to-response

​
Python Quickstart (2 minutes to hello world)

​
Prerequisites

  • Python 3.8 or higher installed.

​
Setup

  1. Get your API keys:
  2. Install dependencies: Install the Anchor Browser Python SDK. (Typescript SDK is also available). 
pip install anchorbrowser pydantic

​
Quick Example: Extract Latest AI News

python
import os
from anchorbrowser import Anchorbrowser

# Initialize the Anchor Browser Client
client = Anchorbrowser(api_key=os.getenv("ANCHOR_API_KEY"))

# Collect the newest from AI News website
task_result = client.agent.task(
    "Extract the latest news title from this AI News website",
    task_options={
        "url": "https://www.artificialintelligence-news.com/",
        "provider": "groq",
        "model": "openai/gpt-oss-120b",
    }
)

print("Latest news title:", task_result)

​
Advanced Session Configuration

Create a session using advanced configuration (see Anchor API reference).
python
import os
from anchorbrowser import Anchorbrowser

# configuration example, can be ommited for default values.
session_config = {
    "session": {
        "recording": False,  # Disable session recording
        "proxy": {
            "active": True,
            "type": "anchor_residential",
            "country_code": "us"
        },
        "max_duration": 5,  # 5 minutes
        "idle_timeout": 1    # 1 minute
    }
}

client = Anchorbrowser(api_key=os.getenv("ANCHOR_API_KEY"))
configured_session = client.sessions.create(browser=session_config)

# Get the session_id to run automation workflows to the same running session.
session_id = configured_session.data.id

# Get the live view url to browse the browser in action (it's interactive!).
live_view_url = configured_session.data.live_view_url

print('session_id:', session_id, '\nlive_view_url:', live_view_url)

​
Next Steps