def set_convert_arguments(parser: argparse.ArgumentParser, data_type: Text) -> None: parser.add_argument( "-f", "--format", default="yaml", choices=["json", "md", "yaml"], help="Output format the training data should be converted into. " "Note: currently training data can be converted to 'yaml' format " "only from 'md' format", ) add_data_param(parser, required=True, data_type=data_type) add_out_param( parser, default=DEFAULT_CONVERTED_DATA_PATH, help_text="File (for `json` and `md`) or existing path (for `yaml`) " "where to save training data in Rasa format.", ) parser.add_argument("-l", "--language", default="en", help="Language of data.")
def set_x_arguments(parser: argparse.ArgumentParser): add_model_param(parser, add_positional_arg=False) add_data_param(parser, default=DEFAULT_DATA_PATH, data_type="stories and Rasa NLU ") parser.add_argument( "--no-prompt", action="store_true", help="Automatic yes or default options to prompts and oppressed warnings.", ) parser.add_argument( "--production", action="store_true", help="Run Rasa X in a production environment.", ) parser.add_argument( "--rasa-x-port", default=DEFAULT_RASA_X_PORT, type=int, help="Port to run the Rasa X server at.", ) parser.add_argument( "--config-endpoint", type=str, help="Rasa X endpoint URL from which to pull the runtime config. This URL " "typically contains the Rasa X token for authentication. Example: " "https://example.com/api/config?token=my_rasa_x_token", ) add_server_arguments(parser)
def set_x_arguments(parser: argparse.ArgumentParser): add_model_param(parser, add_positional_arg=False) add_data_param(parser, default=DEFAULT_DATA_PATH, data_type="stories and Rasa NLU ") parser.add_argument( "--no-prompt", action="store_true", help= "Automatic yes or default options to prompts and oppressed warnings.", ) parser.add_argument( "--production", action="store_true", help="Run Rasa X in a production environment.", ) parser.add_argument( "--rasa-x-port", default=DEFAULT_RASA_X_PORT, type=int, help="Port to run the Rasa X server at.", ) add_server_arguments(parser)
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)
def set_x_arguments(parser: argparse.ArgumentParser): add_model_param(parser, add_positional_arg=False) parser.add_argument( "--no-prompt", action="store_true", help= "Automatic yes or default options to prompts and oppressed warnings.", ) parser.add_argument( "--production", action="store_true", help="Run Rasa X in a production environment.", ) parser.add_argument( "--nlg", type=str, default="http://localhost:5002/api/nlg", help="Rasa NLG endpoint.", ) parser.add_argument( "--model-endpoint-url", type=str, default= "http://localhost:5002/api/projects/default/models/tags/production", help="Rasa model endpoint URL.", ) parser.add_argument( "--project-path", type=str, default=".", help="Path to the Rasa project directory.", ) add_data_param(parser, default=DEFAULT_DATA_PATH, data_type="stories and Rasa NLU ") add_server_arguments(parser)
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_convert_arguments(parser: argparse.ArgumentParser, data_type: Text): add_data_param(parser, required=True, default=None, data_type=data_type) 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", "yaml"], help="Output format the training data should be converted into. " "Note: currently training data can be converted to 'yaml' format " "only from 'md' format", )
def set_validator_arguments(parser: argparse.ArgumentParser): add_domain_param(parser) add_data_param(parser)