cse151b-final-project/Gym-Wordle-main

Gym-Wordle

An OpenAI gym compatible environment for training agents to play Wordle.

User-input demo of the environment

Installation

My goal is for a minimalist package that lets you install quickly and get on with your research. Installation is just a simple call to pip:

$ pip install gym_wordle

Requirements

In keeping with my desire to have a minimalist package, there are only three major requirements:

• numpy
• gym
• sty, a lovely little package for stylizing text in terminals

Usage

The basic flow for training agents with the Wordle-v0 environment is the same as with gym environments generally:

import gym
import gym_wordle

eng = gym.make("Wordle-v0")

done = False
while not done:
    action = ...  # RL magic
    state, reward, done, info = env.step(action)

If you're like millions of other people, you're a Wordle-obsessive in your own right. I have good news for you! The Wordle-v0 environment currently has an implemented render method, which allows you to see a human-friendly version of the game. And it isn't so hard to set up the environment to play for yourself. Here's an example script:

from gym_wordle.utils import play

play()

Documentation

Coming soon!

Examples

Coming soon!

Citing

If you decide to use this project in your work, please consider a citation!

@misc{gym_wordle,
  author = {Kraemer, David},
  title = {An Environment for Reinforcement Learning with Wordle},
  year = {2022},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/DavidNKraemer/Gym-Wordle}},
}