code: def lts_user_model_creator(env_ctx):
      return lts.LTSUserModel(
          env_ctx["slate_size"],
          user_state_ctor=lts.LTSUserState,
          response_model_ctor=lts.LTSResponse,
      )
  
file_path: ray/rllib_contrib/slate_q/src/rllib_slate_q/env/recommender_system_envs_with_recsim.py
imports: from recsim import choice_model
  from recsim.environments import interest_evolution
  from recsim.environments import interest_exploration
  from recsim.environments import long_term_satisfaction
  from ray.rllib.env.wrappers.recsim import make_recsim_env
  from ray.tune import register_env
label_desc: Use image node_id 1 for calling a global function with example usage: lts_user_model_creator(env_ctx) and returns: lts