code: def get_human_eval() -> Dict[str, Dict]:
      """Get HumanEval from OpenAI's github repo and return as a list of parsed dicts.
  
      Returns:
          List[Dict[str, str]]: List of dicts with keys "prompt", "test", "entry_point"
  
      Notes:
          "task_id" is the identifier string for the task.
          "prompt" is the prompt to be used for the task (function signature with docstrings).
          "test" is test-cases wrapped in a `check` function.
          "entry_point" is the name of the function.
      """
      # Check if human eval file exists in CACHE_DIR
      human_eval_path = os.path.join(CACHE_DIR, "HumanEval.jsonl")
      make_cache(
          "https://github.com/openai/human-eval/raw/master/data/HumanEval.jsonl.gz",
          human_eval_path,
      )
  
      human_eval = open(human_eval_path, "r").read().split("\n")
      human_eval = [json.loads(line) for line in human_eval if line]
  
      # Handle 115_max_fill.py to make its docstring well-formed
      human_eval[115]["prompt"] = "import math\n" + human_eval[115][
          "prompt"
      ].replace("import math\n", "")
  
      return {task["task_id"]: task for task in human_eval}
  
file_path: evalplus/evalplus/data/humaneval.py
imports: import hashlib
  import json
  import os
  from typing import Dict
  from evalplus.data.utils import CACHE_DIR, completeness_check, get_dataset_metadata, make_cache, stream_jsonl
label_desc: Use image node_id 4 for calling a global function with example usage: get_human_eval() and returns: unknown