Upload app.py

app.py

@@ -613,20 +613,20 @@ elif page == "💸 Price Prediction":
 
         # Prepare input data as JSON
         input_data = pd.DataFrame({
-            "model_key": car_model,
-            "mileage": mileage,
-            "engine_power": engine_power,
-            "fuel": fuel,
-            "paint_color": paint_color,
-            "car_type": car_type,
-            "private_parking_available": private_parking_available,
-            "has_gps": has_gps,
-            "has_air_conditioning": has_air_conditioning,
-            "automatic_car": automatic_car,
-            "has_getaround_connect": has_getaround_connect,
-            "has_speed_regulator": has_speed_regulator,
-            "winter_tires": winter_tires
-        })
+                    "model_key": [car_model],  # Wrap scalars in lists
+                    "mileage": [mileage],
+                    "engine_power": [engine_power],
+                    "fuel": [fuel],
+                    "paint_color": [paint_color],
+                    "car_type": [car_type],
+                    "private_parking_available": [private_parking_available],
+                    "has_gps": [has_gps],
+                    "has_air_conditioning": [has_air_conditioning],
+                    "automatic_car": [automatic_car],
+                    "has_getaround_connect": [has_getaround_connect],
+                    "has_speed_regulator": [has_speed_regulator],
+                    "winter_tires": [winter_tires]
+                })
 
         # Load the preprocessor
         with open('preprocessor.pkl', 'rb') as file: