notice
This is documentation for Rasa & Rasa Pro Documentation v2.x, which is no longer actively maintained.
For up-to-date documentation, see the latest version (3.x).
Version: 2.x
rasa.api
run
run(model: "Text", endpoints: "Text", connector: "Text" = None, credentials: "Text" = None, **kwargs: "Dict[Text, Any]", ,) -> "NoReturn"
Runs a Rasa model.
Arguments:
model
- Path to model archive.endpoints
- Path to endpoints file.connector
- Connector which should be use (overwritescredentials
field).credentials
- Path to channel credentials file.**kwargs
- Additional arguments which are passed torasa.core.run.serve_application
.
train
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, loop: "Optional[asyncio.AbstractEventLoop]" = None, model_to_finetune: "Optional[Text]" = None, finetuning_epoch_fraction: float = 1.0) -> "TrainingResult"
Runs Rasa Core and NLU training in async
loop.
Arguments:
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
- IfTrue
then no training will be done, and the information about whether the training needs to be done will be printed.force_training
- IfTrue
retrain model even if data has not changed.fixed_model_name
- Name of model to be stored.persist_nlu_training_data
-True
if the NLU training data should be persisted with the model.core_additional_arguments
- Additional training parameters for core training.nlu_additional_arguments
- Additional training parameters forwarded to training method of each NLU component.loop
- Optional EventLoop for running coroutines.model_to_finetune
- Optional path to a model which should be finetuned or a directory in case the latest trained model should be used.finetuning_epoch_fraction
- The fraction currently specified training epochs in the model configuration which should be used for finetuning.
Returns:
An instance of TrainingResult
.
test
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.
Arguments:
model
- model to teststories
- path to the dialogue test datanlu_data
- path to the NLU test dataoutput
- path to folder where all output will be storedadditional_arguments
- additional arguments for the test call