text: simulated environment and agentâ€‹env = gym.make("Blackjack-v1")agent = GymnasiumAgent(model=ChatOpenAI(temperature=0.2), env=env)Main loopâ€‹observation, info = env.reset()agent.reset()obs_message = agent.observe(observation)print(obs_message)while True:    action = agent.act()    observation, reward, termination, truncation, info = env.step(action)    obs_message = agent.observe(observation, reward, termination, truncation, info)    print(f"Action: {action}")    print(obs_message)    if termination or truncation:        print("break", termination, truncation)        breakenv.close()        Observation: (15, 4, 0)    Reward: 0    Termination: False    Truncation: False    Return: 0                Action: 1        Observation: (25, 4, 0)    Reward: -1.0    Termination: True    Truncation: False    Return: -1.0                break True FalsePreviousGenerative Agents in LangChainNextMulti-Player Dungeons & DragonsDefine the agentInitialize the simulated environment and agentMain loopCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.