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)
