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app.py

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+import gradio as gr
+import pandas as pd
+import numpy as np 
+import joblib
+from deep_translator import GoogleTranslator
+
+model = joblib.load('nb.joblib')
+vectorizer = joblib.load('vectorizer.joblib')
+encoder = joblib.load('encoder.joblib')
+
+def pred(message):
+    message =  GoogleTranslator(source= 'fr', target= 'en').translate(message)
+    vecteur = vectorizer.transform([message])
+    prediction = model.predict(vecteur)[0]
+    
+    label = f"{'SPAM' if prediction == 1 else 'HAM'}"
+    return label
+
+
+interface = gr.Interface(
+    fn = pred,
+    inputs= gr.Textbox(lines= 3, placeholder= "Tape ton message"), 
+    outputs= gr.Textbox(label= "Resultat"),
+    title= "Detections des SPAM par IA",
+    description= "Entrez un message et l'application vous dira s'il s'agit de SPAM ou de HAM"
+)
+
+if __name__ == "__main__":
+    interface.launch()

encoder.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b44297fc24d57000e643dff5109674479501e7c15882812f9d6bbd6c64a1289c
+size 486

nb.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:98085f55ef2aa7d0071071d1e5aec7d9ce59110293680630bae4add3b6ce73e9
+size 160791

requirements.txt

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+pandas
+numpy
+joblib
+gradio
+scikit-learn
+deep-translator

vectorizer.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f0bd431c969880871c453035053619d61ee58f3d85f141e807601d2d91c891fa
+size 179834