code: def _make_input_for_apps(
      question: str, starter_code: str, answer_type: str
  ) -> str:
      """Format the prompt as in the original training pipeline."""
      # Different from the original paper: We add the phrase 'in Python' to make models only generate Python code;
      #   otherwise models can generate C++ and code in other languages. The evaluation engine, mostly copied from the
      #   original APPS codebase, runs PyExt and has no way to execute C++ code.
      # The extra phrase isn't needed when there's in-context examples of Python code.
      return (
          "\nQUESTION:\n"
          + question
          + "\n"
          + starter_code
          + "\n"
          + answer_type
          + "\nANSWER in Python code:\n"
      )
  
imports: import io
  import json
  import os
  from typing import List, Dict, Iterable, Optional, cast
  from helm.common.general import ensure_file_downloaded
  from helm.common.hierarchical_logger import hlog
  from .code_scenario_helper import run
  from .code_scenario_apps_pinned_file_order import apps_listdir_with_pinned_order
  from .scenario import Scenario, Instance, Reference, TRAIN_SPLIT, VALID_SPLIT, TEST_SPLIT, CORRECT_TAG, Input, Output
label_desc: Use image node_id 6 for calling a global function with example usage: _make_input_for_apps(question, starter_code, answer_type) and returns: unknown