content: from rasa.core.cli import arguments
  
  
  def add_evaluation_arguments(parser):
      parser.add_argument(
          '-m', '--max_stories',
          type=int,
          help="maximum number of stories to test on")
      parser.add_argument(
          '-u', '--nlu',
          type=str,
          help="nlu model to run with the server. None for regex interpreter")
      parser.add_argument(
          '-o', '--output',
          type=str,
          default="results",
          help="output path for the any files created from the evaluation")
      parser.add_argument(
          '--e2e', '--end-to-end',
          action='store_true',
          help="Run an end-to-end evaluation for combined action and "
               "intent prediction. Requires a story file in end-to-end "
               "format.")
      parser.add_argument(
          '--endpoints',
          default=None,
          help="Configuration file for the connectors as a yml file")
      parser.add_argument(
          '--fail_on_prediction_errors',
          action='store_true',
          help="If a prediction error is encountered, an exception "
               "is thrown. This can be used to validate stories during "
               "tests, e.g. on travis.")
  
      arguments.add_core_model_arg(parser)
  