Update app.py

app.py

@@ -153,39 +153,56 @@ def explain(batch: Optional[BatchInputData] = None, limit: int = 100):
 # =====================================================
 
 @app.post("/metrics")
-def metrics(batch: Optional[BatchInputData] = None, y: Optional[List[int]] = None, limit: int = 100):
+def metrics(batch: Optional[BatchInputData] = None, y_true: Optional[List[int]] = None, limit: int = 100):
     """Compute ROC AUC and threshold analysis, using input or NoCoDB test data."""
     try:
         # Use provided data or fallback to test data from NoCoDB
         if batch:
             X = pd.DataFrame([item.dict() for item in batch.data])
+            source = "client batch"
         else:
             X = fetch_test_data(limit=limit)
+            source = f"NoCoDB (limit={limit})"
+
+        print(f"[DEBUG] Metrics called using {source} | shape={X.shape}")
+
+        # Identify and separate target variable
+        possible_targets = ["y", "target", "label"]
+        target_col = next((c for c in possible_targets if c in X.columns), None)
+
+        if target_col is not None:
+            y_true = X[target_col].astype(int).tolist()
+            X = X.drop(columns=[target_col])
+        elif y_true is None:
+            return {"error": "No target (y_true) provided or found in dataset."}
 
-        if y is None:
-            # Look for 'y' column in NoCoDB data
-            if "y" in X.columns:
-                y = X["y"].astype(int).tolist()
-                X = X.drop(columns=["y"])
-            else:
-                return {"error": "ye values not provided or found in dataset"}
+        # Drop ID if exists
+        if "Id" in X.columns:
+            X = X.drop(columns=["Id"])
 
+        # Predict probabilities
         y_prob = model.predict_proba(X)[:, 1]
-        roc_auc = roc_auc_score(y, y_prob)
-        precision, recall, thresholds = precision_recall_curve(y, y_prob)
+
+        roc_auc = roc_auc_score(y_true, y_prob)
+        precision, recall, thresholds = precision_recall_curve(y_true, y_prob)
         pr_auc = auc(recall, precision)
 
+        print(f"[DEBUG] ROC AUC={roc_auc:.3f} | PR AUC={pr_auc:.3f}")
+
         return {
             "roc_auc": roc_auc,
             "pr_auc": pr_auc,
-            "thresholds": thresholds.tolist()[:20],  # limit output size
+            "thresholds": thresholds.tolist()[:20],
             "precision": precision.tolist()[:20],
             "recall": recall.tolist()[:20]
         }
 
     except Exception as e:
         import traceback
+        print("[ERROR] Metrics failed:", e)
+        print(traceback.format_exc())
         return {"error": str(e), "trace": traceback.format_exc()}
+
     
 @app.get("/coefficients")
 def coefficients():