create_your_environment.md

How to create your custom environments

As an example to demonstrate how to develop your own environment, we develop a language game based on The Chameleon. The example code is available here.

Here are the detailed steps to develop a custom environment class

1. Define the class: Start by defining the class and inherit from a suitable base class (e.g., Environment). In this case, the custom class Chameleon inherits from the Environment base class.

class Chameleon(Environment):
    type_name = "chameleon"

The type_name is required and it is used by the ENV_REGISTRY to identify the class when loading the class from a config file.

Make sure you add the class to ALL_ENVIRONMENTS in environments/__init__.py so that it can be detected.

2. Initialize the class: Define the __init__ method to initialize the class attributes, such as player names, game state, and any other necessary variables.

def __init__(self, player_names: List[str], topic_codes: Dict[str, List[str]] = None, **kwargs):
    super().__init__(player_names=player_names, ..., **kwargs)
    ...

    # The "state" of the environment is maintained by the message pool
    self.message_pool = MessagePool()
    ...

3. Implement game mechanics: Write methods that define the game mechanics, such as giving clues, voting, and guessing the secret word. In the Chameleon class, these mechanics are implemented in the step method.

def step(self, player_name: str, action: str) -> TimeStep:
    ...

4. Handle game states and rewards: Implement methods to manage game states, such as resetting the environment, getting observations, checking if the game has reached a terminal state, and giving rewards to players.

def reset(self):
    ...


def get_observation(self, player_name=None) -> List[Message]:
    ...


def is_terminal(self) -> bool:
    ...


def get_rewards(self, ...) -> Dict[str, float]:
    ...

5. Develop your role description prompts for the players: Now that you have defined the game mechanics, you can develop the role description prompts for the players. These prompts are used to guide the LLM-powered players to play the game correctly. You can use the CLI for this purpose. For example, you can run the following code to launch the CLI:

alice = Player(name="Alice", backend=OpenAIChat(), role_desc="Write your prompt here")
bob = Player(name="Bob", backend=OpenAIChat(), role_desc="Write your prompt here")
env = Chameleon(player_names=["Alice", "Bob"], topic_codes=...)
arena = Arena(players=[alice, bob], environment=env).launch_cli()

Once you are happy with you prompts, you can save them to a config file for future use or sharing.

arena.save_config(path=...)

Another option is using the Web UI. You can run the following code to launch the Web UI:

gradio app.py

and select your custom environment from the dropdown menu.