Update app.py

app.py

@@ -7,6 +7,15 @@ import tensorflow as tf
 # Load the trained model
 model = tf.keras.models.load_model("saaara/real_estate_price_prediction/mon_modele.bin")
 
+import os
+
+file_path = "saaara/real_estate_price_prediction/mon_modele.bin"
+if os.path.exists(file_path):
+    model = tf.keras.models.load_model(file_path)
+else:
+    print(f"Error: File '{file_path}' not found.")
+
+    
 # Load the original dataset to get unique categories for 'secteur' and 'city'
 original_df = pd.read_excel("saaara/real_estate_price_prediction/Moroccan Real Estate Price Clean Dataset .xlsx")  # Replace with your dataset path