Update app.py

app.py

@@ -92,14 +92,35 @@ def predict_price(model, brand, model_name, year):
         'paint_color': 'White'  # Default color
     }
     
-    # Calculate age
+    # Calculate age and other required fields
     current_year = datetime.now().year
     input_data['age'] = current_year - year
     input_data['age_squared'] = input_data['age'] ** 2
+    input_data['mileage_per_year'] = 12000  # Assuming average annual mileage
     
     # Prepare the input for the model
     input_df = pd.DataFrame([input_data])
     
+    # Rename columns to match what the model expects
+    input_df = input_df.rename(columns={
+        'make': 'Make',
+        'model': 'Model',
+        'year': 'Year',
+        'trim': 'Trim',
+        'condition': 'Condition',
+        'fuel': 'Fuel',
+        'odometer': 'Odometer',
+        'title_status': 'Title_status',
+        'transmission': 'Transmission',
+        'drive': 'Drive',
+        'size': 'Size',
+        'type': 'Type',
+        'paint_color': 'Paint_color',
+        'age': 'Age',
+        'age_squared': 'Age_squared',
+        'mileage_per_year': 'Mileage_per_year'
+    })
+    
     # Make sure to only include columns that the model expects
     model_columns = model.feature_names_in_
     input_df = input_df[model_columns]