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app.py

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+import gradio as gr
+import joblib
+
+model = joblib.load('arabic_text_classifier.pkl')
+vectorizer = joblib.load('tfidf_vectorizer.pkl')
+label_encoder = joblib.load('label_encoder.pkl')
+
+def predict_category(text):
+    text_vector = vectorizer.transform([text])
+    probabilities = model.predict_proba(text_vector)[0]
+    max_prob = max(probabilities)
+    predicted_category = model.predict(text_vector)[0]
+
+    
+    if max_prob < 0.5:
+        return "Other"  
+
+    
+    predicted_label = label_encoder.inverse_transform([predicted_category])[0]
+    return predicted_label
+
+
+iface = gr.Interface(
+    fn=predict_category,
+    inputs=gr.Textbox(
+        lines=5, 
+        placeholder="Enter text in Arabic here...", 
+        label="Text"  
+    ),
+    outputs=gr.Label(label="Predicted Category"),  
+    title="Arabic Text Classification", 
+    description="Enter an Arabic text to get its classification based on the trained model.", 
+)
+
+
+iface.launch(share=True)

arabic_text_classifier.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0da3d2df4b2ae20905c1338418c6b259ba00d7e06e8972fe19c2fa5c6cb68e03
+size 38329167

label_encoder.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8fef4330d855f86185760e1a1a161644f270de3f0aec51fbd4a5cdb188b9ffbc
+size 614

tfidf_vectorizer.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:19e5cb9af2cdad61789ecc1c8971412086eec11cce9cb910158234daa68f951e
+size 19655535