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)
def _read_entities(self, examples_js):
entity_synonyms = transform_entity_synonyms(examples_js)
return TrainingData([], entity_synonyms)
