Update app.py

app.py

@@ -233,18 +233,9 @@ model, vectorizer, label_encoder = load_model()
 # ✅ Prediction Function
 def predict_category(text):
     processed_text = [pre_process(text)]
-
-    # Vectorize the input
-    text_vectorized = vectorizer(processed_text).np.tolist()
-
-    # Pad the sequence
-    text_vectorized = pad_sequences(text_vectorized, padding='pre', maxlen=128)
-
-    # Model prediction
+    text_vectorized = pad_sequences(vectorizer(processed_text).numpy().tolist(), padding='pre', maxlen=128)
     prediction = model.predict(text_vectorized)
     category_idx = np.argmax(prediction, axis=1)[0]
-
-    # Return the category label
     return label_encoder.inverse_transform([category_idx])[0]