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app.py

@@ -30,13 +30,22 @@ def predict_sales():
 # Predict for a batch (CSV upload)
 @sales_forecast_api.post('/v1/predict_batch')
 def predict_sales_batch():
+    # Read uploaded CSV file
     file = request.files['file']
     input_data = pd.read_csv(file)
 
+    # Check for optional Product_Id column
+    if "Product_Id" in input_data.columns:
+        ids = input_data["Product_Id"].astype(str)
+        input_data = input_data.drop(columns=["Product_Id"])
+    else:
+        ids = input_data.index.astype(str)  # fallback to row indices
+
+    # Make predictions
     preds = model.predict(input_data).tolist()
 
-    # Map row index → prediction
-    results = {i: pred for i, pred in enumerate(preds)}
+    # Map Product_Id (or row index) → prediction
+    results = dict(zip(ids, preds))
 
     return jsonify(results)