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app/api/routes.py

@@ -345,6 +345,22 @@ async def db_status_endpoint():
     return await repo.db_status()
 
 
+# ---- ML advisory diagnostics ----------------------------------------
+@router.get("/ml/status", tags=["System"])
+async def ml_status():
+    """Operability of the advisory DistilBERT layer (flag / repo / load state)."""
+    from ..config import settings
+    from ..ml.runtime import get_model
+
+    model = get_model()
+    return {
+        "enabled": settings.ml_disposable_enabled,
+        "repo": settings.ml_model_repo,
+        "loaded": bool(model is not None and model.loaded),
+        "last_error": getattr(model, "last_error", None) if model else None,
+    }
+
+
 # ---- History --------------------------------------------------------
 @router.get("/history", tags=["Validation"])
 async def get_history(limit: int = Query(default=50, ge=1, le=500)):

app/ml/runtime.py

@@ -58,6 +58,7 @@ class EmailRiskModel:
         self._factory = pipeline_factory or default_pipeline_factory
         self._pipeline = None
         self._loaded = False
+        self.last_error: Optional[str] = None
         self._lock = threading.Lock()
 
     @property
@@ -75,9 +76,10 @@ class EmailRiskModel:
                 )
                 self._loaded = True
                 return True
-            except Exception:
+            except Exception as exc:
                 self._pipeline = None
                 self._loaded = False
+                self.last_error = f"{type(exc).__name__}: {exc}"
                 return False
 
     def predict(self, texts: list[str]) -> Optional[list[tuple[str, float]]]: