class_docstr: A class regrouping all the information to solve a problem on which we will evaluate agents.
  
  Args:
      task (`str` ou `list[str]`):
          One or several descriptions of the task to perform. If a list, it should contain variations on the
          phrasing, but for the same task.
      inputs (`list[str]` or `dict[str, str]`):
          The inputs that will be fed to the tools. For this testing environment, only strings are accepted as
          values. Pass along a dictionary when you want to specify the values of each inputs, or just the list of
          inputs expected (the value used will be `<<input_name>>` in this case).
      answer (`str` or `list[str`]):
          The theoretical answer (or list of possible valid answers) to the problem, as code.
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code: def __init__(self, task, inputs, answer):
      self.task = task
      self.inputs = inputs
      self.answer = answer
  
imports: from .agents import BASE_PYTHON_TOOLS, clean_code_for_chat, clean_code_for_run
  from .python_interpreter import InterpretorError, evaluate
label_desc: Use image node_id 1 to create a new Problem object  with example: obj = Problem(task, inputs, answer)