old_contents: import argparse
  
  from rasa.cli.arguments.default_arguments import (
      add_nlu_data_param,
      add_out_param,
      add_data_param,
      add_domain_param,
  )
  
  
  def set_convert_arguments(parser: argparse.ArgumentParser):
      add_data_param(parser, required=True, default=None, data_type="Rasa NLU ")
  
      add_out_param(
          parser,
          required=True,
          default=None,
          help_text="File where to save training data in Rasa format.",
      )
  
      parser.add_argument("-l", "--language", default="en", help="Language of data.")
  
      parser.add_argument(
          "-f",
          "--format",
          required=True,
          choices=["json", "md"],
          help="Output format the training data should be converted into.",
      )
  
  
  def set_split_arguments(parser: argparse.ArgumentParser):
      add_nlu_data_param(parser, help_text="File or folder containing your NLU data.")
  
      parser.add_argument(
          "--training-fraction",
          type=float,
          default=0.8,
          help="Percentage of the data which should be in the training data.",
      )
  
      add_out_param(
          parser,
          default="train_test_split",
          help_text="Directory where the split files should be stored.",
      )
  
  
  def set_validator_arguments(parser: argparse.ArgumentParser):
      parser.add_argument(
          "--fail-on-warnings",
          default=False,
          action="store_true",
          help="Fail validation on warnings and errors. "
          "If omitted only errors will result in a non zero exit code.",
      )
      add_domain_param(parser)
      add_data_param(parser)
  
new_contents: import argparse
  
  from rasa.cli.arguments.default_arguments import (
      add_nlu_data_param,
      add_out_param,
      add_data_param,
      add_domain_param,
  )
  
  
  def set_convert_arguments(parser: argparse.ArgumentParser):
      add_data_param(parser, required=True, default=None, data_type="Rasa NLU ")
  
      add_out_param(
          parser,
          required=True,
          default=None,
          help_text="File where to save training data in Rasa format.",
      )
  
      parser.add_argument("-l", "--language", default="en", help="Language of data.")
  
      parser.add_argument(
          "-f",
          "--format",
          required=True,
          choices=["json", "md"],
          help="Output format the training data should be converted into.",
      )
  
  
  def set_split_arguments(parser: argparse.ArgumentParser):
      add_nlu_data_param(parser, help_text="File or folder containing your NLU data.")
  
      parser.add_argument(
          "--training-fraction",
          type=float,
          default=0.8,
          help="Percentage of the data which should be in the training data.",
      )
  
      parser.add_argument(
          "--random-seed",
          type=int,
          default=None,
          help="Seed to generate the same train/test split.",
      )
  
      add_out_param(
          parser,
          default="train_test_split",
          help_text="Directory where the split files should be stored.",
      )
  
  
  def set_validator_arguments(parser: argparse.ArgumentParser):
      parser.add_argument(
          "--fail-on-warnings",
          default=False,
          action="store_true",
          help="Fail validation on warnings and errors. "
          "If omitted only errors will result in a non zero exit code.",
      )
      add_domain_param(parser)
      add_data_param(parser)
  
subject: Add --random-seed argument in rasa split command