code: def test_create_from_recsim_interest_exploration(self):
      env = RecSim(
          num_candidates=20,
          slate_size=3,
          resample_documents=False,
          is_interest_exploration=True,
      )
      replay_buffer = ReplayBuffer(replay_capacity=100, batch_size=10)
      obs = env.reset()
      observation = obs["user"]
      action = env.action_space.sample()
      log_prob = -1.0
      quality = np.stack(
          [v["quality"] for v in obs["doc"].values()], axis=0
      )
      cluster_id = np.array(
          [v["cluster_id"] for v in obs["doc"].values()]
      )
  
      next_obs, reward, terminal, _env = env.step(action)
  
      response = next_obs["response"]
      click = np.array([r["click"] for r in response])
      response_quality = np.stack(
          [r["quality"] for r in response], axis=0
      )
      repsonse_cluster_id = np.array(
          [r["cluster_id"] for r in response]
      )
      replay_buffer.add(
          observation=observation,
          action=action,
          reward=reward,
          terminal=terminal,
          mdp_id=0,
          sequence_number=0,
          doc_quality=quality,
          doc_cluster_id=cluster_id,
          response_click=click,
          response_cluster_id=repsonse_cluster_id,
          response_quality=response_quality,
          log_prob=log_prob,
      )
  
file_path: ReAgent/reagent/test/replay_memory/create_from_env_test.py
imports: import logging
  import unittest
  import numpy
  from reagent.replay_memory.circular_replay_buffer import ReplayBuffer
label_desc: Use image node_id 1 for calling the CreateFromEnvTest obj's underlying member method code with example usage: obj.test_create_from_recsim_interest_exploration() without return types