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)
