Update app.py

app.py

@@ -19,23 +19,20 @@ for i, out in enumerate(output_info):
 if PROB_INDEX is None:
     raise RuntimeError("Probability output not found in ONNX model")
 
-print(f" Using output index {PROB_INDEX} as probability tensor")
+print(f"✅ Using output index {PROB_INDEX} as probability tensor")
 
 
 def predict(amount, user_txn, driver_txn, pair_count, hour, day):
-    # -------- feature engineering (inference-time) --------
-    pair_ratio_user = pair_count / user_txn if user_txn > 0 else 0.0
-    pair_ratio_driver = pair_count / driver_txn if driver_txn > 0 else 0.0
+    # IMPORTANT: feature order MUST match training
+    # Training features:
+    # [amount, user_txn_count, driver_txn_count, user_driver_pair_count, hour, day_of_week]
 
-    # -------- final feature vector (ORDER MUST MATCH TRAINING) --------
     X = np.array(
         [[
             amount,
             user_txn,
             driver_txn,
             pair_count,
-            pair_ratio_user,
-            pair_ratio_driver,
             hour,
             day
         ]],