def set_visualize_stories_arguments(parser: argparse.ArgumentParser): add_domain_param(parser) add_stories_param(parser) add_config_param(parser) parser.add_argument( "--output", default="graph.html", type=str, help="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.", ) parser.add_argument( "-nlu", "--nlu-data", default=None, type=str, help="Path of the Rasa NLU training data, " "used to insert example messages into the graph.", )
def set_migrate_arguments(parser: argparse.ArgumentParser) -> None: """Sets migrate command arguments.""" add_domain_param(parser) add_out_param( parser, default=DEFAULT_DOMAIN_PATH, help_text="Path (for `yaml`) where to save migrated domain in Rasa 3.0 format.", )
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 _add_training_arguments( parser: argparse.ArgumentParser) -> argparse._ArgumentGroup: train_arguments = parser.add_argument_group("Train Arguments") add_config_param(train_arguments) add_domain_param(train_arguments) add_out_param(train_arguments, help_text="Directory where your models should be stored.") add_augmentation_param(train_arguments) add_debug_plots_param(train_arguments) return train_arguments
def set_train_arguments(parser: argparse.ArgumentParser): add_data_param(parser) add_config_param(parser) add_domain_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_model_name_param(parser) add_force_param(parser)
def set_interactive_arguments(parser: argparse.ArgumentParser): add_model_param(parser) add_config_param(parser) add_domain_param(parser) add_data_param(parser) add_out_param(parser) add_force_param(parser) add_skip_visualization_param(parser) add_server_arguments(parser)
def set_migrate_arguments(parser: argparse.ArgumentParser) -> None: """Sets migrate command arguments.""" add_domain_param(parser) add_out_param( parser, default=None, help_text= "Path (for `yaml`) where to save migrated domain in Rasa 3.0 format." "If none is specified, either a `new_domain.yml` file or `new_domain` folder " "will be created in the folder that contains the given domain.", )
def set_train_arguments(parser: argparse.ArgumentParser): add_data_param(parser) add_config_param(parser) add_domain_param(parser) add_out_param(parser) add_augmentation_param(parser) add_debug_plots_param(parser) add_dump_stories_param(parser) add_model_name_param(parser) add_force_param(parser) add_compress_param(parser)
def set_train_nlu_arguments(parser: argparse.ArgumentParser): add_config_param(parser) add_domain_param(parser, default=None) add_out_param(parser, help_text="Directory where your models should be stored.") add_nlu_data_param(parser, help_text="File or folder containing your NLU data.") add_num_threads_param(parser) add_model_name_param(parser) add_persist_nlu_data_param(parser)
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_nlu_arguments(parser: argparse.ArgumentParser) -> None: """Specifies CLI arguments for `rasa train nlu`.""" add_config_param(parser) add_domain_param(parser, default=None) add_out_param(parser, help_text="Directory where your models should be stored.") add_nlu_data_param(parser, help_text="File or folder containing your NLU data.") _add_num_threads_param(parser) _add_model_name_param(parser) add_persist_nlu_data_param(parser) add_finetune_params(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_markers_arguments(parser: argparse.ArgumentParser) -> None: """Specifies arguments for `rasa evaluate markers`.""" parser.add_argument( "output_filename", type=Path, help="The filename to write the extracted markers to (CSV format).", ) parser.add_argument( "--config", default="markers.yml", type=Path, help="The marker configuration file(s) containing marker definitions. " "This can be a single YAML file, or a directory that contains several " "files with marker definitions in it. The content of these files will " "be read and merged together.", ) stats = parser.add_mutually_exclusive_group() stats.add_argument( "--no-stats", action="store_false", dest="stats", help="Do not compute summary statistics.", ) stats.add_argument( "--stats-file-prefix", default="stats", nargs="?", type=Path, help= "The common file prefix of the files where we write out the compute " "statistics. More precisely, the file prefix must consist of a common " "path plus a common file prefix, to which suffixes `-overall.csv` and " "`-per-session.csv` will be added automatically.", ) add_endpoint_param( parser, help_text="Configuration file for the tracker store as a yml file.", ) add_domain_param(parser)
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_train_arguments(parser: argparse.ArgumentParser) -> None: """Specifies CLI arguments for `rasa train`.""" add_data_param(parser) add_config_param(parser) add_domain_param(parser) add_out_param(parser, help_text="Directory where your models should be stored.") add_dry_run_param(parser) add_augmentation_param(parser) add_debug_plots_param(parser) _add_num_threads_param(parser) _add_model_name_param(parser) add_persist_nlu_data_param(parser) add_force_param(parser) 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_interactive_arguments(parser: argparse.ArgumentParser): add_model_param(parser, default=None) add_data_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, help_text="Directory where your models should be stored.") add_augmentation_param(train_arguments) add_debug_plots_param(train_arguments) add_dump_stories_param(train_arguments) add_force_param(train_arguments)
def set_x_arguments(parser: argparse.ArgumentParser): default_arguments.add_model_param(parser, add_positional_arg=False) default_arguments.add_data_param(parser, default=DEFAULT_DATA_PATH, data_type="stories and Rasa NLU ") default_arguments.add_config_param(parser) default_arguments.add_domain_param(parser) 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_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 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)
def _add_data_convert_parsers(data_subparsers, parents: List[argparse.ArgumentParser]) -> None: convert_parser = data_subparsers.add_parser( "convert", formatter_class=argparse.ArgumentDefaultsHelpFormatter, parents=parents, help="Converts Rasa data between different formats.", ) convert_parser.set_defaults(func=lambda _: convert_parser.print_help(None)) convert_subparsers = convert_parser.add_subparsers() convert_nlu_parser = convert_subparsers.add_parser( "nlu", formatter_class=argparse.ArgumentDefaultsHelpFormatter, parents=parents, help="Converts NLU data between formats.", ) convert_nlu_parser.set_defaults(func=_convert_nlu_data) arguments.set_convert_arguments(convert_nlu_parser, data_type="Rasa NLU") convert_nlg_parser = convert_subparsers.add_parser( "nlg", formatter_class=argparse.ArgumentDefaultsHelpFormatter, parents=parents, help= ("Converts NLG data between formats. If you're migrating from 1.x, " "please run `rasa data convert responses` to adapt the training data " "to the new response selector format."), ) convert_nlg_parser.set_defaults(func=_convert_nlg_data) arguments.set_convert_arguments(convert_nlg_parser, data_type="Rasa NLG") convert_core_parser = convert_subparsers.add_parser( "core", formatter_class=argparse.ArgumentDefaultsHelpFormatter, parents=parents, help="Converts Core data between formats.", ) convert_core_parser.set_defaults(func=_convert_core_data) arguments.set_convert_arguments(convert_core_parser, data_type="Rasa Core") migrate_config_parser = convert_subparsers.add_parser( "config", formatter_class=argparse.ArgumentDefaultsHelpFormatter, parents=parents, help="Migrate model configuration between Rasa Open Source versions.", ) migrate_config_parser.set_defaults(func=_migrate_model_config) default_arguments.add_config_param(migrate_config_parser) default_arguments.add_domain_param(migrate_config_parser) default_arguments.add_out_param( migrate_config_parser, default=os.path.join(DEFAULT_DATA_PATH, "rules.yml"), help_text= "Path to the file which should contain any rules which are created " "as part of the migration. If the file doesn't exist, it will be created.", ) convert_responses_parser = convert_subparsers.add_parser( "responses", formatter_class=argparse.ArgumentDefaultsHelpFormatter, parents=parents, help= ("Convert retrieval intent responses between Rasa Open Source versions. " "Please also run `rasa data convert nlg` to convert training data files " "to the right format."), ) convert_responses_parser.set_defaults(func=_migrate_responses) arguments.set_convert_arguments(convert_responses_parser, data_type="Rasa stories") default_arguments.add_domain_param(convert_responses_parser)
def set_validator_arguments(parser: argparse.ArgumentParser): add_domain_param(parser) add_data_param(parser)
def set_show_stories_arguments(parser: argparse.ArgumentParser): add_domain_param(parser) add_stories_param(parser) add_config_param(parser) add_visualization_arguments(parser)