with app.app_context():
PATH = "{}/{}".format(app.config["MODELS_DIR"],
app.config["INTENT_MODEL_NAME"])
sentence_classifier = IntentClassifier()
sentence_classifier.load(PATH)
print("Intent Model loaded.")
def update_model(app, message, **extra):
sentence_classifier.load(PATH)
print("Intent Model updated")
from app.nlu.tasks import model_updated_signal
model_updated_signal.connect(update_model, app)
from app.agents.models import Bot
def predict(sentence):
"""
Predict Intent using Intent classifier
:param sentence:
:return:
"""
bot = Bot.objects.get(name="default")
predicted = sentence_classifier.predict(sentence)
print(predicted)
if predicted["confidence"] < bot.config.get("confidence_threshold", .90):
return Intent.objects(
:param extra:
:return:
"""
global sentence_classifier
sentence_classifier = EmbeddingIntentClassifier.load(app.config["MODELS_DIR"])
synonyms = get_synonyms()
global entity_extraction
entity_extraction = EntityExtractor(synonyms)
app.logger.info("Intent Model updated")
with app.app_context():
update_model(app,"Modles updated")
from app.nlu.tasks import model_updated_signal
model_updated_signal.connect(update_model, app)
from app.agents.models import Bot
def predict(sentence):
"""
Predict Intent using Intent classifier
:param sentence:
:return:
"""
bot = Bot.objects.get(name="default")
predicted,intents = sentence_classifier.process(sentence)
app.logger.info("predicted intent %s", predicted)
if predicted["confidence"] < bot.config.get("confidence_threshold", .90):
return Intent.objects(intentId=app.config["DEFAULT_FALLBACK_INTENT_NAME"]).first().intentId, 1.0,[]
else:
return predicted["intent"], predicted["confidence"],intents[1:]
