BrowserGym

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

• Setup
• Usage
• Demo

Setup

To install browsergym, you can either install one of the browsergym-miniwob, browsergym-webarena 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

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

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

Usage

Open-ended task example

Boilerplate code to run an agent on an interactive, openended task:

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

env = gym.make(
    "browsergym/openended", start_url="https://www.google.com/", wait_for_user_message=True
)
obs, info = env.reset()
done = False
while not done:
    action = ...  # implement your agent here
    obs, reward, terminated, truncated, info = env.step(action)

MiniWoB++ task example

Boilerplate code to run an agent on a miniwob task:

import gymnasium as gym
import browsergym.miniwob  # register miniwob tasks as gym environments

env = gym.make("browsergym/miniwob.choose-list")
obs, info = env.reset()
done = False
while not done:
    action = ...  # implement your agent here
    obs, reward, terminated, truncated, info = env.step(action)

List of all the available MiniWoB++ environments

env_ids = [id for id in gym.envs.registry.keys() if id.startswith("browsergym/miniwob")]
print("\n".join(env_ids))

WebArena task example

Boilerplate code to run an agent on a webarena task:

import gymnasium as gym
import browsergym.webarena  # register webarena tasks as gym environments

env = gym.make("browsergym/webarena.310")
obs, info = env.reset()
done = False
while not done:
    action = ...  # implement your agent here
    obs, reward, terminated, truncated, info = env.step(action)

List of all the available WebArena environments

env_ids = [id for id in gym.envs.registry.keys() if id.startswith("browsergym/webarena")]
print("\n".join(env_ids))

WorkArena task example

Boilerplate code to run an agent on a workarena task:

import gymnasium as gym
import browsergym.workarena  # register workarena tasks as gym environments

env = gym.make("browsergym/workarena.servicenow.order-ipad-pro")
obs, info = env.reset()
done = False
while not done:
    action = ...  # implement your agent here
    obs, reward, terminated, truncated, info = env.step(action)

List of all the available WorkArena environments

env_ids = [id for id in gym.envs.registry.keys() if id.startswith("browsergym/workarena")]
print("\n".join(env_ids))

Demo

If you want to experiment with an agent in BrowserGym, follow these steps:

cd ui_assist
conda env create -f environment.yml; conda activate ui-assist
# or simply use `pip install -r requirements.txt`
playwright install

Optional: Set your OPENAI_API_KEY if you want to use a GPT agent.

Launch the demo on the open web:

python run_demo.py --task_name openended --start_url www.google.com

You can customize your experience by changing the model_name to your preferred LLM, toggling Chain-of-thought with use_thinking, adding screenshots for your VLMs with use_screenshot, and much more!

multiple agent demos on the open web, WorkArena and WebArena

https://github.com/ServiceNow/BrowserGym/assets/26232819/e0bfc788-cc8e-44f1-b8c3-0d1114108b85