code: def interactive_optimize_with_client(
      ax_client: AxClient,
      num_trials: int,
      candidate_queue_maxsize: int,
      elicitation_function: Callable[
          [Tuple[TParameterization, int]], TEvaluationOutcome
      ],
  ) -> bool:
      """
      Implementation of `interactive_loop` using the AxClient. Extract results of the
      experiment from the AxClient passed in.
  
      The basic structure is as follows: One thread tries for a lock on the AxClient,
      generates a candidate, and enqueues it to a candidate queue. Another thread tries
      for the same lock, takes all the trial outcomes in the outcome queue, and attaches
      them to the AxClient. The main thread pops a candidate off the candidate queue,
      elicits response from the user, and puts the response onto the outcome queue.
      """
  
      # Construct a lock to ensure only one thread my access the AxClient at any moment
      ax_client_lock = Lock()
  
      return interactive_optimize(
          num_trials=num_trials,
          candidate_queue_maxsize=candidate_queue_maxsize,
          candidate_generator_function=ax_client_candidate_generator,
          candidate_generator_kwargs={
              "ax_client": ax_client,
              "lock": ax_client_lock,
          },
          data_attacher_function=ax_client_data_attacher,
          data_attacher_kwargs={
              "ax_client": ax_client,
              "lock": ax_client_lock,
          },
          elicitation_function=elicitation_function,
      )
  
file_path: Ax/ax/service/interactive_loop.py
imports: import time
  from logging import Logger
  from queue import Queue
  from threading import Event, Lock, Thread
  from typing import Any, Callable, Dict, Optional, Tuple
  from ax.core.types import TEvaluationOutcome, TParameterization
  from ax.exceptions.core import DataRequiredError
  from ax.exceptions.generation_strategy import MaxParallelismReachedException
  from ax.service.ax_client import AxClient
  from ax.utils.common.logger import get_logger
label_desc: Use image node_id 2 for calling a global function with example usage: interactive_optimize_with_client(ax_client, num_trials, candidate_queue_maxsize, elicitation_function) and returns: interactive_optimize