import opensim as osim

from osim.http.client import Client

import numpy as np

# Settings

remote_base = "http://osim-rl-grader.aicrowd.com/"

aicrowd_token = "a66245c8324e2d37b92f098a57ef3f99" # use your aicrowd token

# your aicrowd token (API KEY) can be found at your prorfile page at https://www.aicrowd.com

client = Client(remote_base)

# Create environment

observation = client.env_create(aicrowd_token, env_id='L2M2019Env')

# IMPLEMENTATION OF YOUR CONTROLLER

# my_controller = ... (for example the one trained in keras_rl)

while True:

    #action = my_controller.update(observation)

    action = [.5]*22

    [observation, reward, done, info] = client.env_step(action)

    print(observation)

    if done:

        observation = client.env_reset()

        if not observation:

            break

client.submit()