import json
from desktop_env.envs.desktop_env import DesktopEnv


def human_agent():
    """
    Runs the Gym environment with human input.
    """

    with open("evaluation_examples/examples/f9584479-3d0d-4c79-affa-9ad7afdd8850.json", "r") as f:
        example = json.load(f)

    env = DesktopEnv( path_to_vm=r"C:\Users\tianbaox\Documents\Virtual Machines\Ubuntu\Ubuntu.vmx"
                    , action_space="computer_13"
                    , snapshot_path="base_setup"
                    , instruction=example["instruction"]
                    , config=example["config"]
                    , evaluator=example["evaluator"]
                    )

    # reset the environment to certain snapshot
    observation = env.reset()
    done = False

    trajectory = [
        {
            "action_type": "MOVE_TO",
            "parameters": {
                "x": 754,
                "y": 1057
            }
        },
        {"action_type": "CLICK", "parameters": {"button": "right", "num_clicks": 1}}
    ]

    for i in range(len(trajectory)):
        # action = get_human_action()

        # action = {
        #     "action_type": 0,
        #     "click_type": 3,
        # }
        print(trajectory[i])

        observation, reward, done, info = env.step(trajectory[i], pause=5)
        print("Observation:", observation)
        print("Reward:", reward)
        print("Info:", info)

        print("================================\n")

        if done:
            print("The episode is done.")
            break

    result = env.evaluate()
    print("Result:", result)

    env.close()
    print("Environment closed.")


if __name__ == "__main__":
    human_agent()