Load full artifact scan in dashboard

backend/tests/test_results_service.py

@@ -1,5 +1,9 @@
 from pathlib import Path
 
+from fastapi.testclient import TestClient
+
+from app import main
+from app.main import app
 from app.modules.results.service import parse_training_curve
 
 
@@ -25,3 +29,31 @@ def test_parse_yolo_results_curve(tmp_path: Path):
     assert "train/seg_loss" in names
     assert "metrics/mAP50(M)" in names
     assert all("lr/" not in name for name in names)
+
+
+def test_results_api_honors_limit(monkeypatch):
+    calls = {}
+
+    def fake_scan_results(limit: int = 1000):
+        calls["limit"] = limit
+        return [{"name": "a.png", "relative_path": "var/a.png"}]
+
+    monkeypatch.setattr(main, "scan_results", fake_scan_results)
+    response = TestClient(app).get("/api/results?limit=123")
+
+    assert response.status_code == 200
+    assert calls["limit"] == 123
+
+
+def test_results_curve_api_honors_limit(monkeypatch):
+    calls = {}
+
+    def fake_scan_training_curves(limit: int = 100):
+        calls["limit"] = limit
+        return [{"name": "results", "relative_path": "var/results.csv"}]
+
+    monkeypatch.setattr(main, "scan_training_curves", fake_scan_training_curves)
+    response = TestClient(app).get("/api/results/curves?limit=77")
+
+    assert response.status_code == 200
+    assert calls["limit"] == 77