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