notice
This is documentation for Rasa Open Source Documentation v2.1.x, which is no longer actively maintained.
For up-to-date documentation, see the latest version (2.2.x).
Version: 2.1.x
rasa.nlu.utils.spacy_utils
SpacyNLP Objects
class SpacyNLP(Component)
load_model
| @staticmethod
| load_model(spacy_model_name: Text) -> "Language"
Try loading the model, catching the OSError if missing.
merge_content_lists
| @staticmethod
| merge_content_lists(indexed_training_samples: List[Tuple[int, Text]], doc_lists: List[Tuple[int, "Doc"]]) -> List[Tuple[int, "Doc"]]
Merge lists with processed Docs back into their original order.
filter_training_samples_by_content
| @staticmethod
| filter_training_samples_by_content(indexed_training_samples: List[Tuple[int, Text]]) -> Tuple[List[Tuple[int, Text]], List[Tuple[int, Text]]]
Separates empty training samples from content bearing ones.
process_content_bearing_samples
| process_content_bearing_samples(samples_to_pipe: List[Tuple[int, Text]]) -> List[Tuple[int, "Doc"]]
Sends content bearing training samples to spaCy's pipe.
process_non_content_bearing_samples
| process_non_content_bearing_samples(empty_samples: List[Tuple[int, Text]]) -> List[Tuple[int, "Doc"]]
Creates empty Doc-objects from zero-lengthed training samples strings.
ensure_proper_language_model
| @staticmethod
| ensure_proper_language_model(nlp: Optional["Language"]) -> None
Checks if the spacy language model is properly loaded.
Raises an exception if the model is invalid.