This is unreleased documentation for Rasa Documentation Main/Unreleased version.
For the latest released documentation, see the latest version (3.x).

Version: Main/Unreleased



def run(model: "Text",
endpoints: "Text",
connector: "Optional[Text]" = None,
credentials: "Optional[Text]" = None,
**kwargs: "Dict[Text, Any]") -> None

Runs a Rasa model.


  • model - Path to model archive.
  • endpoints - Path to endpoints file.
  • connector - Connector which should be use (overwrites credentials field).
  • credentials - Path to channel credentials file.
  • **kwargs - Additional arguments which are passed to


def train(domain: "Text",
config: "Text",
training_files: "Union[Text, List[Text]]",
output: "Text" = rasa.shared.constants.DEFAULT_MODELS_PATH,
dry_run: bool = False,
force_training: bool = False,
fixed_model_name: "Optional[Text]" = None,
persist_nlu_training_data: bool = False,
core_additional_arguments: "Optional[Dict]" = None,
nlu_additional_arguments: "Optional[Dict]" = None,
model_to_finetune: "Optional[Text]" = None,
finetuning_epoch_fraction: float = 1.0) -> "TrainingResult"

Runs Rasa Core and NLU training in async loop.


  • domain - Path to the domain file.
  • config - Path to the config for Core and NLU.
  • training_files - Paths to the training data for Core and NLU.
  • output - Output path.
  • dry_run - If True then no training will be done, and the information about whether the training needs to be done will be printed.
  • force_training - If True retrain model even if data has not changed.
  • fixed_model_name - Name of model to be stored.
  • domain0 - True if the NLU training data should be persisted with the model.
  • domain2 - Additional training parameters for core training.
  • domain3 - Additional training parameters forwarded to training method of each NLU component.
  • domain4 - Optional path to a model which should be finetuned or a directory in case the latest trained model should be used.
  • domain5 - The fraction currently specified training epochs in the model configuration which should be used for finetuning.


An instance of domain6.


def test(model: "Text",
stories: "Text",
nlu_data: "Text",
output: "Text" = rasa.shared.constants.DEFAULT_RESULTS_PATH,
additional_arguments: "Optional[Dict]" = None) -> None

Test a Rasa model against a set of test data.


  • model - model to test
  • stories - path to the dialogue test data
  • nlu_data - path to the NLU test data
  • output - path to folder where all output will be stored
  • additional_arguments - additional arguments for the test call