Update app.py

app.py

@@ -1,3 +1,4 @@
+%%writefile backend_files/app.py
 # Backend_files/app.y
 import joblib
 import pandas as pd
@@ -79,15 +80,18 @@ def predict_batch():
             'Store_Size', 'Store_Location_City_Type', 'Store_Type'
         ]
 
-        # Check each record
+        # Check each record for required fields
         for i, record in enumerate(batch_data):
-            missing = [f for f in required_fields if f not in record]
-            if missing:
-                return jsonify({"error": f"Missing fields in record {i}: {missing}"}), 400
+          missing = [f for f in required_fields if f not in record]          
+          if missing:
+            return jsonify({"error": f"Missing fields in record {i}: {missing}"}), 400
 
         # Convert list of dicts to DataFrame
         df = pd.DataFrame(batch_data)
 
+        # Remove Product_Id and target column if present
+        columns_to_remove = ['Product_Id', 'Product_Store_Sales_Total']
+        df = df.drop(columns=[col for col in columns_to_remove if col in df.columns])
         # Predict
         predictions = Random_Forest_Loaded_Model.predict(df)
 
@@ -99,4 +103,4 @@ def predict_batch():
 
 # Run flask in debug mode
 if __name__ == '__main__':
-    Superkart_Sales_Predictor_API.run(debug=False, host='0.0.0.0', port=7860)
+    Superkart_Sales_Predictor_API.run(debug=False, host='0.0.0.0', port=7860)