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