def get_prediction(texts):
if len(texts) < 1:
raise Exception("Wrong Data")
if not os.path.exists('my_model'):
EngModel._execute_teaching()
data = []
lang = detect(texts[0])
if lang == 'ru' or lang == 'uk' or lang == "bg":
for text in texts:
data.append(Translator._get_translate(text))
else:
data = texts
comments_list = EngModel._prepare_real_data(data)
new_model = models.load_model("my_model")
data = EngModel._vectorize(comments_list)
results = new_model.predict(data)
predictions = []
for result in results:
if result > 0.70:
predictions.append(1)
else:
predictions.append(0)
return predictions
