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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]]