[Setup] [Usage] [Demo] [Citation]

This package provides browsergym, a gym environment for web task automation in the Chromium browser.

Example of a GPT4-V agent executing openended tasks (top row, chat interactive), as well as WebArena and WorkArena tasks (bottom row)

BrowserGym includes the following benchmarks by default:

• MiniWob++
• WebArena
• VisualWebArena
• WorkArena

Designing new web benchmarks with BrowserGym is easy, and simply requires to inherit the AbstractBrowserTask class.

To install browsergym, you can either install one of the browsergym-miniwob, browsergym-webarena, browsergym-visualwebarena and browsergym-workarena packages, or you can simply install browsergym which includes all of these by default.

pip install browsergym

Then, a required step is to setup playwright by running

playwright install chromium

Finally, each benchmark comes with its own specific setup that requires to follow additional steps.

• for miniwob, see miniwob/README.md
• for webarena, see webarena/README.md
• for visualwebarena, see visualwebarena/README.md
• for workarena, see WorkArena

To install browsergym locally for development, use the following commands:

git clone https://github.com/ServiceNow/BrowserGym.git
cd BrowserGym
make install

Boilerplate code to run an agent on an interactive, open-ended task:

import gymnasium as gym
import browsergym.core  # register the openended task as a gym environment

env = gym.make(
    "browsergym/openended",
    task_kwargs={"start_url": "https://www.google.com/"},  # starting URL
    wait_for_user_message=True,  # wait for a user message after each agent message sent to the chat
)
obs, info = env.reset()
done =