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)
