Load full artifact scan in dashboard

README.md

@@ -57,9 +57,9 @@ written under `var/custom_yolo_runs` and are scanned by the results dashboard.
 When a dataset is selected, the dataset panel shows its custom YOLO `best.pt`,
 prediction previews, heatmap previews, and inline training curve previews.
 Segmentation previews, YOLO heatmaps, and loss/metric artifacts are grouped on
-the results dashboard. The artifact browser can filter by model family and
+the results dashboard. The artifact browser loads the full result scan, can
-artifact role, and YOLO-style `results.csv` files are parsed into lightweight
+filter by model family and artifact role, and YOLO-style `results.csv` files
-training curves.
+are parsed into lightweight training curves.
 Job APIs and the SSE log stream also expose structured progress parsed from
 YOLO, MMSeg/MMEngine, SegModel-style epoch logs, and generic tqdm percentages,
 so the queue and live log panel can show stage, epoch/iteration, and percent
@@ -163,8 +163,10 @@ Use `GET /api/coverage` to inspect script-to-task coverage and task
 buildability.
 Use `GET /api/capabilities` to inspect the grouped full-function readiness
 matrix used by the web dashboard and agents.
-Use `GET /api/results/curves` to inspect parsed training curves discovered
+Use `GET /api/results?limit=1000` to inspect browsable artifacts and
-from YOLO, SegModel, MMSeg, visual-tool, and analysis output directories.
+`GET /api/results/curves?limit=100` to inspect parsed training curves
+discovered from YOLO, SegModel, MMSeg, visual-tool, and analysis output
+directories.
 Use `GET /api/agents/evaluate` and `GET /api/agents/validate` to surface the
 same evaluation and validation feedback shown in the web dashboard Agent panel.
 

backend/app/agents/evaluation_agent.py

@@ -54,7 +54,10 @@ def evaluate_project() -> dict:
         and "resultFamilyFilter" in frontend_text
         and "resultRoleFilter" in frontend_text
         and "familyOptions" in frontend_text
-        and "roleOptions" in frontend_text,
+        and "roleOptions" in frontend_text
+        and "/api/results?limit=1000" in frontend_text
+        and "setResults(resultsNext)" in frontend_text
+        and "slice(0, 240)" not in frontend_text,
         "job_progress_ui": "JobProgressBar" in frontend_text and "progressTrack" in frontend_text,
         "runtime_readiness_ui": "runtimeReadiness" in frontend_text and "环境就绪" in frontend_text,
         "capability_matrix_ui": "capabilities" in frontend_text and "全功能矩阵" in frontend_text,

backend/app/main.py

@@ -4,7 +4,7 @@ import asyncio
 import json
 from pathlib import Path
 
-from fastapi import FastAPI, File, HTTPException, UploadFile
+from fastapi import FastAPI, File, HTTPException, Query, UploadFile
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import FileResponse, StreamingResponse
 
@@ -211,12 +211,12 @@ async def api_job_events(job_id: str):
 
 
 @app.get("/api/results")
-def api_results() -> list[dict]:
+def api_results(limit: int = Query(1000, ge=1, le=5000)) -> list[dict]:
-    return scan_results()
+    return scan_results(limit=limit)
 
 
 @app.get("/api/results/curves")
-def api_result_curves(limit: int = 100) -> list[dict]:
+def api_result_curves(limit: int = Query(100, ge=1, le=500)) -> list[dict]:
     return scan_training_curves(limit=limit)
 
 

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

frontend/src/main.tsx

@@ -347,8 +347,8 @@ function useData() {
         api<RuntimeReadinessPayload>("/api/system/readiness"),
         api<CapabilityPayload>("/api/capabilities"),
         api<Job[]>("/api/jobs"),
-        api<ResultItem[]>("/api/results"),
+        api<ResultItem[]>("/api/results?limit=1000"),
-        api<TrainingCurve[]>("/api/results/curves"),
+        api<TrainingCurve[]>("/api/results/curves?limit=100"),
         api<UploadedDataset[]>("/api/datasets"),
         api<CoveragePayload>("/api/coverage"),
         api<AcceptancePayload>("/api/acceptance/latest"),
@@ -360,8 +360,8 @@ function useData() {
       setRuntimeReadiness(readinessNext);
       setCapabilities(capabilitiesNext);
       setJobs(jobsNext);
-      setResults(resultsNext.slice(0, 240));
+      setResults(resultsNext);
-      setCurves(curvesNext.slice(0, 12));
+      setCurves(curvesNext);
       setDatasets(datasetsNext);
       const validationEntries: Array<[string, DatasetValidation]> = [];
       await Promise.all(
@@ -1319,12 +1319,16 @@ function ResultBrowser({
         <span>/ {total} artifacts</span>
       </div>
       <div className="resultList">
-        {results.map((item) => (
+        {results.length ? (
+          results.map((item) => (
             <a key={item.path} href={`${API_BASE}/api/artifacts/${item.relative_path}`} target="_blank" rel="noreferrer">
               <span>{item.name}</span>
               <small>{item.family ?? "artifact"} · {item.role ?? "artifact"} · {formatBytes(item.size)}</small>
             </a>
-        ))}
+          ))
+        ) : (
+          <p className="muted">没有匹配产物</p>
+        )}
       </div>
     </div>
   );