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| import pickle | |
| import re | |
| from pathlib import Path | |
| __version__ = "0.1.0" | |
| BASE_DIR = Path(__file__).resolve(strict=True).parent | |
| with open(f"{BASE_DIR}/trained_pipeline-{__version__}.pkl", "rb") as f: | |
| model = pickle.load(f) | |
| classes = [ | |
| "Arabic", | |
| "Danish", | |
| "Dutch", | |
| "English", | |
| "French", | |
| "German", | |
| "Greek", | |
| "Hindi", | |
| "Italian", | |
| "Kannada", | |
| "Malayalam", | |
| "Portugeese", | |
| "Russian", | |
| "Spanish", | |
| "Sweedish", | |
| "Tamil", | |
| "Turkish", | |
| ] | |
| def predict_pipeline(text): | |
| text = re.sub(r'[!@#$(),\n"%^*?\:;~`0-9]', " ", text) | |
| text = re.sub(r"[[]]", " ", text) | |
| text = text.lower() | |
| pred = model.predict([text]) | |
| return classes[pred[0]] | |