from flair.models import SequenceTagger from utils.nlu_utils import predict_single, predict_multiple, predict_and_annotate # Exploratory tests frame_model = SequenceTagger.load('frame-model-prod/best-model.pt') tests = [ 'chciałbym zamówić pizzę', 'na godzinę 12', 'prosiłbym o pizzę z pieczarkami', 'to wszystko, jaka cena?', 'ile kosztuje pizza', 'do widzenia', 'tak', 'nie dziękuję', 'dodatkowy ser', 'pizzę barcelona bez cebuli', ] print("=== Exploratory tests - frame model ===") for test in tests: print(f"Sentence: {test}") print(f"Single prediction: {predict_single(frame_model, test.split(), 'frame')}") print(f"Multiple predictions: {predict_multiple(frame_model, test.split(), 'frame')}") print(f"Annotated sentence: {predict_and_annotate(frame_model, test.split(), 'frame')}") print("=== Exploratory tests - slot model ===") slot_model = SequenceTagger.load('slot-model-prod/best-model.pt') for test in tests: print(f"Sentence: {test}") print(f"Prediction: {predict_and_annotate(slot_model, test.split(), 'slot')}")