feat: add governed nationwide AOI orchestration and CUDA enforcement

backend/app/services/detection_service.py

@@ -15,7 +15,7 @@ from sqlalchemy import func
 from app.core.config import Settings, get_settings
 from app.core.errors import AppError
 from app.core.request_context import get_request_id
-from app.models import AnalysisRun, Dataset, Detection, Job, Project, VectorFeature
+from app.models import AnalysisRun, Area, Dataset, Detection, Job, Project, VectorFeature
 from app.schemas.detection import DetectionListResponse, DetectionRead, DetectionRunListResponse, DetectionRunRead, DetectionRunResponse
 from app.services.detection_georeferencing import pixel_bbox_to_epsg4326_polygon
 from app.services.detection_qa_service import DetectionQaService
@@ -90,6 +90,12 @@ class DetectionService:
                 message="Configured YOLO inference requires an existing raster tile manifest path",
                 status_code=400,
             )
+        requested_classes = {DetectionService._canonical_class_name(value) for value in (class_filter or [])}
+        unsupported_classes = sorted(requested_classes - set(model.supported_classes))
+        if unsupported_classes:
+            raise AppError(code="DETECTION_CLASS_NOT_VALIDATED", message="The selected model is not validated for one or more requested classes", details={"unsupported_classes": unsupported_classes, "supported_classes": model.supported_classes}, status_code=422)
+        if model.model_id == resolved_settings.yolo_model_id and resolved_settings.yolo_enforce_validation_scope:
+            DetectionService._validate_model_area_scope(db, dataset, resolved_settings)
 
         run_parameters = {
             "model_id": model.model_id,
@@ -214,6 +220,18 @@ class DetectionService:
         raise AppError(code="DETECTION_MODEL_UNAVAILABLE", message="Detection model is unavailable", status_code=503)
 
     @staticmethod
+    def _validate_model_area_scope(db, dataset: Dataset, settings: Settings) -> None:
+        allowed_names = [value.strip().casefold() for value in settings.yolo_validated_area_names.split(",") if value.strip()]
+        area = db.get(Area, dataset.area_id) if dataset.area_id else None
+        area_name = area.name.strip() if area is not None else ""
+        if not area_name or not any(token in area_name.casefold() for token in allowed_names):
+            raise AppError(
+                code="DETECTION_VALIDATION_SCOPE_UNAVAILABLE",
+                message="Configured YOLO inference is not validated for this Dataset area.",
+                details={"dataset_id": str(dataset.id), "dataset_area": area_name or None, "validated_area_names": allowed_names},
+                status_code=422,
+            )
+    @staticmethod
     def _fail_run_after_exception(db, analysis_run: AnalysisRun, job: Job, exc: Exception, fallback_code: str) -> None:
         try:
             db.rollback()