Update app.py

app.py

@@ -492,12 +492,44 @@ def perform_sustainability_analysis(state):
     except Exception as e:
         return f"❌ Error in sustainability analysis: {str(e)}", None, "Analysis failed"
 
-def predict_freight_cost(state, weight, line_item_value, cost_per_kg,
-                       shipment_mode, air_charter_weight=0, ocean_weight=0, truck_weight=0,
+def predict_freight_cost(state, weight=1000, line_item_value=10000, cost_per_kg=50,
+                       shipment_mode="Air", air_charter_weight=0, ocean_weight=0, truck_weight=0,
                        air_charter_value=0, ocean_value=0, truck_value=0):
     if state.freight_model is None:
         return "Error: Freight prediction model not loaded"
         
+    try:
+        # Set weights based on mode
+        if "Air" in shipment_mode:
+            air_charter_weight = weight
+            air_charter_value = line_item_value
+        elif "Ocean" in shipment_mode:
+            ocean_weight = weight
+            ocean_value = line_item_value
+        else:
+            truck_weight = weight
+            truck_value = line_item_value
+
+        features = {
+            'weight (kilograms)': weight,
+            'line item value': line_item_value,
+            'cost per kilogram': cost_per_kg,
+            'shipment mode_Air Charter_weight': air_charter_weight,
+            'shipment mode_Ocean_weight': ocean_weight,
+            'shipment mode_Truck_weight': truck_weight,
+            'shipment mode_Air Charter_line_item_value': air_charter_value,
+            'shipment mode_Ocean_line_item_value': ocean_value,
+            'shipment mode_Truck_line_item_value': truck_value
+        }
+        input_data = pd.DataFrame([features])
+        
+        prediction = state.freight_model.predict(input_data)
+        return round(float(prediction[0]), 2)
+    except Exception as e:
+        return f"Error making prediction: {str(e)}"
+    if state.freight_model is None:
+        return "Error: Freight prediction model not loaded"
+        
     try:
         features = {
             'weight (kilograms)': weight,
@@ -870,7 +902,13 @@ def create_interface():
         )
 
         predict_button.click(
-            fn=lambda *args: predict_and_store_freight(state, *args),
+            fn=lambda weight, value, mode: predict_and_store_freight(
+                state, 
+                weight=weight,
+                line_item_value=value,
+                cost_per_kg=50,  # Default value
+                shipment_mode=mode
+            ),
             inputs=[weight, line_item_value, shipment_mode],
             outputs=[freight_result]
         )