Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import joblib
 import pandas as pd
 
-# Load trained model
+# Load model
 model = joblib.load("model.pkl")
 
 def predict(
@@ -15,10 +15,10 @@ def predict(
     Store_Size,
     Store_Location_City_Type,
     Store_Type,
-    Product_Id_char
+    Product_Id_char,
+    Product_Type_Category
 ):
 
-    # Create DataFrame with correct column names
     input_data = pd.DataFrame([{
         "Product_Weight": Product_Weight,
         "Product_Sugar_Content": Product_Sugar_Content,
@@ -29,15 +29,14 @@ def predict(
         "Store_Size": Store_Size,
         "Store_Location_City_Type": Store_Location_City_Type,
         "Store_Type": Store_Type,
-        "Product_Id_char": Product_Id_char
+        "Product_Id_char": Product_Id_char,
+        "Product_Type_Category": Product_Type_Category
     }])
 
-    # Make prediction
     prediction = model.predict(input_data)
     return round(float(prediction[0]), 2)
 
 
-# Gradio Interface
 interface = gr.Interface(
     fn=predict,
     inputs=[
@@ -53,12 +52,11 @@ interface = gr.Interface(
             ["Grocery Store", "Supermarket Type1", "Supermarket Type2", "Supermarket Type3"],
             label="Store Type"
         ),
-        gr.Textbox(label="Product ID Char")  #  Final missing feature
+        gr.Textbox(label="Product ID Char"),
+        gr.Textbox(label="Product Type Category")  #  NEW FINAL ONE
     ],
     outputs=gr.Number(label="Predicted Sales"),
-    title="🛒 SuperKart Sales Prediction",
-    description="Enter product and store details to predict sales"
+    title="🛒 SuperKart Sales Prediction"
 )
 
-# Launch app
 interface.launch()