def set_test_core_arguments(parser: argparse.ArgumentParser): core_arguments = parser.add_argument_group("Core Test arguments") add_test_core_arguments(core_arguments) add_stories_param(core_arguments, "test") add_url_param(core_arguments) add_test_core_model_param(parser)
def add_test_core_argument_group(parser: Union[argparse.ArgumentParser, argparse._ActionsContainer]): add_stories_param(parser, "test") parser.add_argument("--max-stories", type=int, help="Maximum number of stories to test on.") parser.add_argument( "--output", type=str, default="results", help="Output path for any files created during 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.", ) add_endpoint_param(parser) 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.", ) parser.add_argument( "--url", type=str, help="If supplied, downloads a story file from a URL and " "trains on it. Fetches the data by sending a GET request " "to the supplied URL.", )
def set_interactive_core_arguments(parser: argparse.ArgumentParser) -> None: add_model_param(parser, model_name="Rasa Core", default=None) add_stories_param(parser) _add_common_params(parser) _add_training_arguments(parser) add_port_argument(parser)
def set_test_arguments(parser): add_model_param(parser, add_positional_arg=False) core_arguments = parser.add_argument_group("Core Test arguments") add_test_core_arguments(core_arguments) add_stories_param(core_arguments, "test") add_url_param(core_arguments) nlu_arguments = parser.add_argument_group("NLU Test arguments") add_test_nlu_arguments(nlu_arguments)
def add_test_core_argument_group( parser: Union[argparse.ArgumentParser, argparse._ActionsContainer], include_e2e_argument: bool = False, ) -> None: add_stories_param(parser, "test") parser.add_argument( "--max-stories", type=int, help="Maximum number of stories to test on." ) add_out_param( parser, default=DEFAULT_RESULTS_PATH, help_text="Output path for any files created during the evaluation.", ) if include_e2e_argument: 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.", ) add_endpoint_param( parser, help_text="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.", ) parser.add_argument( "--url", type=str, help="If supplied, downloads a story file from a URL and " "trains on it. Fetches the data by sending a GET request " "to the supplied URL.", ) parser.add_argument( "--evaluate-model-directory", default=False, action="store_true", help="Should be set to evaluate models trained via " "'rasa train core --config <config-1> <config-2>'. " "All models in the provided directory are evaluated " "and compared against each other.", ) add_no_plot_param(parser) add_errors_success_params(parser)
def _add_core_arguments(parser: Union[argparse.ArgumentParser, argparse._ActionsContainer]): from rasa.cli.arguments.test import add_evaluation_arguments add_evaluation_arguments(parser) add_stories_param(parser, "test") parser.add_argument( "--url", type=str, help="If supplied, downloads a story file from a URL and " "trains on it. Fetches the data by sending a GET request " "to the supplied URL.", )
def set_interactive_core_arguments(parser: argparse.ArgumentParser): add_model_param(parser) add_config_param(parser) add_domain_param(parser) add_stories_param(parser) add_out_param(parser) add_augmentation_param(parser) add_debug_plots_param(parser) add_dump_stories_param(parser) add_skip_visualization_param(parser) add_server_arguments(parser)
def set_train_core_arguments(parser: argparse.ArgumentParser): add_stories_param(parser) add_domain_param(parser) add_core_config_param(parser) add_out_param(parser, help_text="Directory where your models should be stored.") add_augmentation_param(parser) add_debug_plots_param(parser) add_dump_stories_param(parser) add_force_param(parser) add_model_name_param(parser) compare_arguments = parser.add_argument_group("Comparison Arguments") add_compare_params(compare_arguments)
def set_train_core_arguments(parser: argparse.ArgumentParser): add_stories_param(parser) add_domain_param(parser) add_core_config_param(parser) add_out_param(parser) add_augmentation_param(parser) add_debug_plots_param(parser) add_dump_stories_param(parser) add_force_param(parser) add_model_name_param(parser) add_compress_param(parser) compare_arguments = parser.add_argument_group("Comparison Arguments") add_compare_params(compare_arguments)
def set_train_core_arguments(parser: argparse.ArgumentParser) -> None: """Specifies CLI arguments for `rasa train core`.""" add_stories_param(parser) add_domain_param(parser) _add_core_config_param(parser) add_out_param(parser, help_text="Directory where your models should be stored.") add_augmentation_param(parser) add_debug_plots_param(parser) add_force_param(parser) _add_model_name_param(parser) compare_arguments = parser.add_argument_group("Comparison Arguments") _add_compare_params(compare_arguments) add_finetune_params(parser)
def set_interactive_core_arguments(parser: argparse.ArgumentParser): add_model_param(parser, model_name="Rasa Core", default=None) add_stories_param(parser) add_skip_visualization_param(parser) add_endpoint_param( parser, help_text= "Configuration file for the model server and the connectors as a yml file.", ) train_arguments = parser.add_argument_group("Train Arguments") add_config_param(train_arguments) add_domain_param(train_arguments) add_out_param(train_arguments) add_augmentation_param(train_arguments) add_debug_plots_param(train_arguments) add_dump_stories_param(train_arguments)
def set_visualize_stories_arguments(parser: argparse.ArgumentParser): add_domain_param(parser) add_stories_param(parser) add_config_param(parser) add_out_param( parser, default="graph.html", help_text="Filename of the output path, e.g. 'graph.html'.", ) parser.add_argument( "--max-history", default=2, type=int, help="Max history to consider when merging paths in the output graph.", ) add_nlu_data_param( parser, default=None, help_text="File or folder containing your NLU data, " "used to insert example messages into the graph.", )
def add_subparser(subparsers: argparse._SubParsersAction, parents: List[argparse.ArgumentParser]): import rasa.cli.arguments.train as core_cli train_parser = subparsers.add_parser("train", help="Train the Rasa bot") train_subparsers = train_parser.add_subparsers() train_core_parser = train_subparsers.add_parser( "core", conflict_handler="resolve", formatter_class=argparse.ArgumentDefaultsHelpFormatter, help="Train Rasa Core", ) train_core_parser.set_defaults(func=train_core) train_nlu_parser = train_subparsers.add_parser( "nlu", parents=parents, formatter_class=argparse.ArgumentDefaultsHelpFormatter, help="Train Rasa NLU", ) train_nlu_parser.set_defaults(func=train_nlu) for p in [train_parser, train_core_parser, train_nlu_parser]: add_general_arguments(p) for p in [train_core_parser, train_parser]: add_domain_param(p) core_cli.add_general_args(p) add_stories_param(train_core_parser) _add_core_compare_arguments(train_core_parser) add_nlu_data_param(train_nlu_parser) add_joint_parser_arguments(train_parser) train_parser.set_defaults(func=train)
def set_show_stories_arguments(parser: argparse.ArgumentParser): add_domain_param(parser) add_stories_param(parser) add_config_param(parser) add_visualization_arguments(parser)
def add_core_visualization_params(parser: argparse.ArgumentParser): from rasa.cli.arguments.visualization import add_visualization_arguments add_visualization_arguments(parser) add_domain_param(parser) add_stories_param(parser)