def read_from_json(self, js, **kwargs): """Loads training data stored in the rasa NLU data format.""" validate_rasa_nlu_data(js) data = js['rasa_nlu_data'] common_examples = data.get("common_examples", []) intent_examples = data.get("intent_examples", []) entity_examples = data.get("entity_examples", []) entity_synonyms = data.get("entity_synonyms", []) regex_features = data.get("regex_features", []) entity_synonyms = transform_entity_synonyms(entity_synonyms) if intent_examples or entity_examples: logger.warn("DEPRECATION warning: your rasa data " "contains 'intent_examples' " "or 'entity_examples' which will be " "removed in the future. Consider " "putting all your examples " "into the 'common_examples' section.") all_examples = common_examples + intent_examples + entity_examples training_examples = [] for ex in all_examples: msg = Message.build(ex['text'], ex.get("intent"), ex.get("entities")) training_examples.append(msg) return TrainingData(training_examples, entity_synonyms, regex_features)
def read_from_json(self, js, **kwargs): """Loads training data stored in the rasa NLU data format.""" validate_rasa_nlu_data(js) data = js['rasa_nlu_data'] common_examples = data.get("common_examples", []) intent_examples = data.get("intent_examples", []) entity_examples = data.get("entity_examples", []) entity_synonyms = data.get("entity_synonyms", []) regex_features = data.get("regex_features", []) lookup_tables = data.get("lookup_tables", []) entity_synonyms = transform_entity_synonyms(entity_synonyms) if intent_examples or entity_examples: logger.warning("DEPRECATION warning: your rasa data " "contains 'intent_examples' " "or 'entity_examples' which will be " "removed in the future. Consider " "putting all your examples " "into the 'common_examples' section.") all_examples = common_examples + intent_examples + entity_examples training_examples = [] for ex in all_examples: msg = Message.build(ex['text'], ex.get("intent"), ex.get("entities")) training_examples.append(msg) return TrainingData(training_examples, entity_synonyms, regex_features, lookup_tables)
def _read_entities(entity_js, examples_js): from rasa_nlu.training_data import TrainingData entity_synonyms = transform_entity_synonyms(examples_js) name = entity_js.get("name") lookup_tables = DialogflowReader._extract_lookup_tables( name, examples_js) return TrainingData([], entity_synonyms, [], lookup_tables)
def _read_entities(entity_js, examples_js): from rasa_nlu.training_data import TrainingData entity_synonyms = transform_entity_synonyms(examples_js) name = entity_js.get("name") lookup_tables = DialogflowReader._extract_lookup_tables(name, examples_js) return TrainingData([], entity_synonyms, [], lookup_tables)
def _read_entities(examples_js): from rasa_nlu.training_data import TrainingData entity_synonyms = transform_entity_synonyms(examples_js) return TrainingData([], entity_synonyms)
def _read_entities(self, examples_js): entity_synonyms = transform_entity_synonyms(examples_js) return TrainingData([], entity_synonyms)