Initial public release

backend/tests/test_model_asset_catalog.py

@@ -0,0 +1,355 @@
+from __future__ import annotations
+
+from hashlib import sha256
+import json
+from pathlib import Path
+from uuid import uuid4
+
+import pytest
+from fastapi.testclient import TestClient
+
+from app.core.config import Settings
+from app.core.errors import AppError
+from app.main import app
+from app.models import (
+    AnalysisRun,
+    Dataset,
+    DatasetVersion,
+    Detection,
+    Job,
+    Project,
+    SourceRegistry,
+    SourceSnapshot,
+)
+from app.services.detection_service import DetectionService
+from app.services.model_asset_catalog_service import ModelAssetCatalogService
+from app.services.runtime_model_provenance_service import RuntimeModelProvenanceService
+from app.services.tile_manifest_service import TileManifestService
+
+
+class FakeSession:
+    def __init__(self, objects=None) -> None:
+        self.objects = objects or {}
+        self.added = []
+        self.commits = 0
+        self.refreshes = []
+
+    def get(self, model, item_id):
+        return self.objects.get((model, item_id))
+
+    def add(self, item) -> None:
+        self.added.append(item)
+        if getattr(item, "id", None) is not None:
+            self.objects[(item.__class__, item.id)] = item
+
+    def commit(self) -> None:
+        self.commits += 1
+
+    def refresh(self, item) -> None:
+        self.refreshes.append(item)
+
+
+class MockYoloAdapter:
+    def __init__(self, settings: Settings) -> None:
+        self.settings = settings
+
+    @staticmethod
+    def dependencies_available() -> bool:
+        return True
+
+    def load_model(self, model_path: Path):
+        return {"model_path": str(model_path)}
+
+    def predict_tiles(self, model, tile_paths, confidence_threshold: float) -> list[list[dict]]:
+        # The service batches tiles; this double still answers per tile.
+        return [self.predict_tile(model, tile_path, confidence_threshold) for tile_path in tile_paths]
+
+    def predict_tile(self, model, tile_path: Path, confidence_threshold: float) -> list[dict]:
+        assert model["model_path"].endswith("building-detector.pt")
+        return [
+            {
+                "class_name": "building",
+                "confidence": 0.9,
+                "bbox": [10.0, 20.0, 30.0, 40.0],
+                "properties": {"adapter": "mock"},
+            }
+        ]
+
+
+def _project_and_raster_dataset():
+    project_id = uuid4()
+    dataset_id = uuid4()
+    source_registry_id = uuid4()
+    source_snapshot_id = uuid4()
+    checksum = "a" * 64
+    project = Project(id=project_id, name="Geel")
+    source_registry = SourceRegistry(
+        id=source_registry_id,
+        source_key="test-derived-raster",
+        display_name="Governed test-derived raster",
+        classification="derived",
+        authority_name="GeoIntel test fixture",
+        usage_policy_json={"ground_truth_allowed": False},
+    )
+    source_snapshot = SourceSnapshot(
+        id=source_snapshot_id,
+        source_registry_id=source_registry_id,
+        snapshot_key="test-derived-raster-v1",
+        checksum_sha256=checksum,
+        freshness_status="current",
+        ingest_status="ingested",
+    )
+    dataset = Dataset(
+        id=dataset_id,
+        project_id=project_id,
+        name="source.tif",
+        dataset_type="raster",
+        source="test-derived-raster",
+        source_name="test-derived-raster",
+        storage_path="storage/uploads/source.tif",
+        checksum_sha256=checksum,
+        crs="EPSG:4326",
+        bounds_json={"min_x": 4.0, "min_y": 51.0, "max_x": 5.0, "max_y": 52.0},
+        source_registry_id=source_registry_id,
+        source_snapshot_id=source_snapshot_id,
+        data_contract_key="geointel.raster.geotiff",
+        data_contract_version="1.0.0",
+        validation_status="passed",
+        provenance_status="complete",
+        lineage_status="not_applicable",
+        quarantine_status="not_quarantined",
+        status="ready",
+    )
+    dataset.source_registry = source_registry
+    dataset.source_snapshot = source_snapshot
+    dataset.versions.append(
+        DatasetVersion(id=uuid4(), dataset_id=dataset_id, version=1, checksum_sha256=checksum)
+    )
+    db = FakeSession(objects={(Project, project_id): project, (Dataset, dataset_id): dataset})
+    return db, project_id, dataset_id
+
+
+def _manifest(tmp_path: Path, db: FakeSession, dataset: Dataset) -> Path:
+    tile_path = tmp_path / "tile_0000.tif"
+    tile_path.write_bytes(b"tile")
+    binding = TileManifestService.dataset_binding(db, dataset)
+    manifest_path = tmp_path / "manifest.json"
+    manifest_path.write_text(
+        json.dumps(
+            {
+                **binding,
+                "tile_set_id": "tiles-fixture",
+                "count": 1,
+                "crs": "EPSG:4326",
+                "bounds": [4.0, 51.0, 5.0, 52.0],
+                "tiles": [
+                    {
+                        "path": str(tile_path),
+                        "pixel_window": [0, 0, 100, 100],
+                        "bounds": [4.0, 51.0, 5.0, 52.0],
+                        "transform": [4.0, 0.01, 0.0, 52.0, 0.0, -0.01],
+                        "crs": "EPSG:4326",
+                        "index": 0,
+                        **TileManifestService.tile_integrity(tile_path),
+                    }
+                ],
+            }
+        ),
+        encoding="utf-8",
+    )
+    return manifest_path
+
+
+def _write_model_sidecar(
+    model_path: Path,
+    settings: Settings,
+    *,
+    db: FakeSession | None = None,
+) -> None:
+    model_sha256 = sha256(model_path.read_bytes()).hexdigest()
+    source_registry_id = uuid4()
+    source_snapshot_id = uuid4()
+    source_version = settings.yolo_model_version or "test-v1"
+    if db is not None:
+        source_registry = SourceRegistry(
+            id=source_registry_id,
+            source_key="model",
+            display_name="Governed test model artifact",
+            classification="experimental",
+            authority_name="GeoIntel test fixture",
+            freshness_status="current",
+            ingest_status="configured",
+        )
+        source_snapshot = SourceSnapshot(
+            id=source_snapshot_id,
+            source_registry_id=source_registry_id,
+            snapshot_key=f"model-{source_version}",
+            source_version=source_version,
+            checksum_sha256=model_sha256,
+            freshness_status="current",
+            ingest_status="ingested",
+        )
+        db.objects[(SourceRegistry, source_registry_id)] = source_registry
+        db.objects[(SourceSnapshot, source_snapshot_id)] = source_snapshot
+    payload = {
+        "schema_version": RuntimeModelProvenanceService.MANIFEST_SCHEMA_VERSION,
+        "data_contract": {"key": "geointel.model.pytorch", "version": "1.0.0"},
+        "model": {
+            "model_id": settings.yolo_model_id,
+            "task_type": "object_detection",
+            "sha256": model_sha256,
+            "model_format": "pytorch",
+            "framework": "ultralytics/pytorch",
+            "class_mapping": {"0": "building"},
+            "source_version": source_version,
+        },
+        "source": {
+            "source_registry_id": str(source_registry_id),
+            "source_snapshot_id": str(source_snapshot_id),
+            "source_registry_key": "model",
+            "source_snapshot_checksum_sha256": model_sha256,
+        },
+        "lineage": {
+            "upstream_asset_ids": ["test-training-corpus"],
+            "upstream_checksums_sha256": ["a" * 64],
+            "transformations": [
+                {"name": "test-training", "version": "1.0.0", "checksum_sha256": "b" * 64}
+            ],
+        },
+        "metadata": {"training_manifest_sha256": "c" * 64},
+        "imported_at": "2026-08-01T10:00:00+00:00",
+    }
+    payload["metadata"]["runtime_manifest_sha256"] = RuntimeModelProvenanceService.manifest_self_checksum(payload)
+    RuntimeModelProvenanceService.manifest_path_for_model(model_path).write_text(
+        json.dumps(payload, sort_keys=True),
+        encoding="utf-8",
+    )
+
+
+def test_model_asset_catalog_lists_supported_local_model_files(tmp_path: Path) -> None:
+    model_file = tmp_path / "building-detector.pt"
+    model_file.write_bytes(b"local model")
+    ignored_file = tmp_path / "notes.txt"
+    ignored_file.write_text("ignore me", encoding="utf-8")
+    settings = Settings(yolo_models_dir=str(tmp_path), yolo_model_path=str(model_file), yolo_enabled=True)
+
+    response = ModelAssetCatalogService.list_assets(settings=settings)
+
+    assert response.total == 1
+    asset = response.items[0]
+    assert asset.model_asset_id == "building-detector-pt"
+    assert asset.filename == "building-detector.pt"
+    assert asset.display_name == "building-detector"
+    assert asset.model_path == str(model_file)
+    assert asset.size_bytes == len(b"local model")
+    assert len(asset.sha256) == 64
+    assert asset.active is True
+    assert asset.runtime_available is True
+    assert asset.runtime_status == "active"
+    assert asset.governed_validation_status == "not_verified_by_catalog"
+    assert asset.promotion_status == "not_verified_by_catalog"
+    assert asset.status == "runtime_active"
+    assert asset.will_download_models is False
+
+
+def test_model_asset_catalog_resolves_known_asset(tmp_path: Path) -> None:
+    model_file = tmp_path / "building-detector.pt"
+    model_file.write_bytes(b"local model")
+    settings = Settings(yolo_models_dir=str(tmp_path), yolo_enabled=True)
+
+    asset = ModelAssetCatalogService.resolve_asset("building-detector-pt", settings=settings)
+
+    assert asset.filename == "building-detector.pt"
+    assert asset.model_path == str(model_file)
+
+
+def test_model_asset_catalog_only_exposes_explicit_active_asset_in_runtime(tmp_path: Path) -> None:
+    active_file = tmp_path / "approved-building-detector.pt"
+    active_file.write_bytes(b"approved")
+    (tmp_path / "training-smoke.pt").write_bytes(b"experiment")
+    (tmp_path / "partial-checkpoint.pt").write_bytes(b"partial")
+    settings = Settings(
+        yolo_models_dir=str(tmp_path),
+        yolo_model_path=str(active_file),
+        yolo_enabled=True,
+    )
+
+    response = ModelAssetCatalogService.list_assets(settings=settings)
+
+    assert response.total == 1
+    assert response.items[0].filename == active_file.name
+    assert response.items[0].active is True
+    assert response.items[0].runtime_status == "active"
+    assert response.items[0].governed_validation_status == "not_verified_by_catalog"
+    assert response.items[0].promotion_status == "not_verified_by_catalog"
+    assert response.items[0].status == "runtime_active"
+
+
+def test_model_asset_catalog_rejects_unknown_asset(tmp_path: Path) -> None:
+    settings = Settings(yolo_models_dir=str(tmp_path), yolo_enabled=True)
+
+    with pytest.raises(AppError) as exc_info:
+        ModelAssetCatalogService.resolve_asset("missing-model", settings=settings)
+
+    assert exc_info.value.code == "DETECTION_MODEL_ASSET_NOT_FOUND"
+    assert exc_info.value.status_code == 404
+
+
+def test_model_assets_api_returns_canonical_envelope(monkeypatch, tmp_path: Path) -> None:
+    model_file = tmp_path / "building-detector.pt"
+    model_file.write_bytes(b"local model")
+    monkeypatch.setenv("YOLO_MODELS_DIR", str(tmp_path))
+    monkeypatch.setenv("YOLO_MODEL_PATH", str(model_file))
+
+    response = TestClient(app).get("/api/v1/detection/model-assets")
+
+    assert response.status_code == 200
+    payload = response.json()
+    assert set(payload) == {"data"}
+    assert payload["data"]["total"] == 1
+    assert payload["data"]["items"][0]["model_asset_id"] == "building-detector-pt"
+    assert payload["data"]["items"][0]["active"] is True
+    assert payload["data"]["items"][0]["runtime_status"] == "active"
+    assert payload["data"]["items"][0]["governed_validation_status"] == "not_verified_by_catalog"
+    assert payload["data"]["items"][0]["promotion_status"] == "not_verified_by_catalog"
+    assert payload["data"]["items"][0]["will_download_models"] is False
+
+
+def test_detection_run_persists_selected_model_asset_parameters(tmp_path, monkeypatch: Path) -> None:
+    # A manifest written into tmp_path is only a governed artifact if
+    # tmp_path is the storage root.
+    monkeypatch.setenv("STORAGE_ROOT", str(tmp_path))
+    model_file = tmp_path / "building-detector.pt"
+    model_file.write_bytes(b"local model")
+    db, project_id, dataset_id = _project_and_raster_dataset()
+    settings = Settings(
+        yolo_enabled=True,
+        yolo_model_path=str(tmp_path / "default.pt"),
+        yolo_models_dir=str(tmp_path),
+        yolo_max_tiles=4,
+    )
+    _write_model_sidecar(model_file, settings, db=db)
+
+    result = DetectionService.run_detection(
+        db=db,
+        project_id=project_id,
+        dataset_id=dataset_id,
+        model_id="yolo-configured",
+        model_asset_id="building-detector-pt",
+        confidence_threshold=0.5,
+        tile_manifest_path=str(_manifest(tmp_path, db, db.get(Dataset, dataset_id))),
+        settings=settings,
+        yolo_adapter_class=MockYoloAdapter,
+    )
+
+    jobs = [item for item in db.added if isinstance(item, Job)]
+    runs = [item for item in db.added if isinstance(item, AnalysisRun)]
+    detections = [item for item in db.added if isinstance(item, Detection)]
+
+    assert result.status == "success"
+    assert result.detection_count == 1
+    assert jobs[0].parameters_json["model_asset_id"] == "building-detector-pt"
+    assert jobs[0].parameters_json["model_asset_path"] == str(model_file)
+    assert len(jobs[0].parameters_json["model_asset_sha256"]) == 64
+    assert runs[0].parameters_json["model_asset_id"] == "building-detector-pt"
+    assert detections[0].model_name == "yolo-configured"