diff --git a/README.md b/README.md index bde3a25..d462de5 100644 --- a/README.md +++ b/README.md @@ -198,10 +198,11 @@ scripts/check_no_weight_git.sh For a fast non-training validation pass, run agents with `PYTHONPATH=backend conda run -n seg_smp python scripts/run_agents.py --no-deep`. -Add `--live`, `--acceptance`, or `--real` only after the backend and frontend -are running and you want HTTP endpoint, smoke, or real-workspace checks. The -browser dashboard exposes the same readiness, coverage, GPU, weight, result, -and agent checks through the UI. +Add `--live`, `--acceptance`, `--real`, or `--real-train` only after the +backend and frontend are running and you want HTTP endpoint, smoke, +real-workspace, or real short-training checks. The browser dashboard exposes +the same readiness, coverage, GPU, weight, result, and agent checks through +the UI. The web UI includes a dataset bench for creating upload workspaces, uploading images/labels/masks, and jumping into the existing rename, PNG conversion, @@ -272,6 +273,16 @@ real image/mask pair. The latest report is available from `GET /api/acceptance/real/latest` and is shown in the coverage panel as `真实数据`. +`POST /api/acceptance/real-train` goes one step further and launches a short +operator-style YOLO loop on real workspace data. It uploads a real YOLO +image/txt pair, generates `dataset.yaml`, runs one CPU epoch through +`yolo.train_custom`, verifies `results.csv` and `best.pt`, then uses that +trained checkpoint for prediction and GradCAM heatmap jobs. The latest report +is available from `GET /api/acceptance/real-train/latest` and is shown in the +coverage panel as `真实短训`. This is heavier than the real-data predict +acceptance, so run it when you want proof that real uploaded data can create +loss curves, trained weights, segmentation previews, and heatmap artifacts. + For stronger runtime proof, `POST /api/acceptance/deep` runs minimal training loops for the three model families: one SegModel optimizer step, one YOLO segmentation epoch on a synthetic 64x64 dataset, one YOLO GradCAM heatmap @@ -372,8 +383,9 @@ non-training validation pass is needed. The web dashboard calls validation in light mode by default: `/api/agents/validate?run_build=false&run_acceptance=false&run_deep=false`. -Pass `run_live=true`, `run_acceptance=true`, `run_real=true`, or -`run_deep=true` only when you explicitly want the agent to launch live endpoint -or heavier runtime acceptance checks from the browser/API. Smoke and real data -acceptance automatically enable the live backend checks because they submit -jobs through the API. +Pass `run_live=true`, `run_acceptance=true`, `run_real=true`, +`run_real_train=true`, or `run_deep=true` only when you explicitly want the +agent to launch live endpoint or heavier runtime acceptance checks from the +browser/API. Smoke, real data, and real short-training acceptance +automatically enable the live backend checks because they submit jobs through +the API. diff --git a/backend/app/acceptance.py b/backend/app/acceptance.py index 1eaa4ec..cd3774d 100644 --- a/backend/app/acceptance.py +++ b/backend/app/acceptance.py @@ -447,6 +447,13 @@ def latest_real_acceptance_report() -> dict[str, Any]: return json.loads(path.read_text(encoding="utf-8")) +def latest_real_train_acceptance_report() -> dict[str, Any]: + path = settings.project_root / "var" / "acceptance" / "real_train_latest.json" + if not path.exists(): + return {"available": False, "path": str(path)} + return json.loads(path.read_text(encoding="utf-8")) + + def run_real_dataset_acceptance(base_url: str = "http://127.0.0.1:8010") -> dict[str, Any]: """Run the upload/predict/heatmap path against existing non-synthetic Seg data.""" acceptance_root = settings.project_root / "var" / "acceptance" @@ -620,6 +627,178 @@ def run_real_dataset_acceptance(base_url: str = "http://127.0.0.1:8010") -> dict return report +def run_real_train_acceptance(base_url: str = "http://127.0.0.1:8010") -> dict[str, Any]: + """Run a short YOLO train/predict/heatmap loop using real workspace samples.""" + acceptance_root = settings.project_root / "var" / "acceptance" + run_id = uuid.uuid4().hex[:8] + fixture_root = acceptance_root / f"real_train_{run_id}" + fixture_root.mkdir(parents=True, exist_ok=True) + + samples = find_real_workspace_samples() + checks: list[dict[str, Any]] = [ + {"name": "real_train_workspace_samples_discovered", "passed": samples["passed"], "detail": samples} + ] + if not samples["passed"]: + report = { + "available": True, + "run_id": run_id, + "base_url": base_url, + "fixture_root": str(fixture_root), + "passed": False, + "checks": checks, + "created_at": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()), + } + (acceptance_root / "real_train_latest.json").write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8") + return report + + dataset_name = f"real_train_acceptance_{run_id}" + created_dataset = _request_json("POST", f"{base_url}/api/datasets", {"name": dataset_name, "description": "real workspace short train acceptance"}, timeout=10) + checks.append({"name": "create_real_train_upload_dataset", "passed": created_dataset.get("passed", False), "detail": created_dataset}) + + yolo_image = Path(samples["yolo_pair"]["image"]) + yolo_label = Path(samples["yolo_pair"]["label"]) + uploads = { + "real_train_yolo_image_upload": _post_file(f"{base_url}/api/datasets/{dataset_name}/upload/images", yolo_image, timeout=30), + "real_train_yolo_label_upload": _post_file(f"{base_url}/api/datasets/{dataset_name}/upload/labels", yolo_label, timeout=30), + } + for name, detail in uploads.items(): + checks.append({"name": name, "passed": detail.get("passed", False), "detail": detail}) + + validation = _request_json("GET", f"{base_url}/api/datasets/{dataset_name}/validate", timeout=20) + validation_json = validation.get("json") if validation.get("passed") else {} + checks.append( + { + "name": "real_train_dataset_validate_yolo", + "passed": validation.get("passed", False) and validation_json.get("ready", {}).get("yolo"), + "detail": validation, + } + ) + + class_count = max(validation_json.get("classes") or [0]) + 1 + class_names = ["object"] + [f"class_{index}" for index in range(1, class_count)] + yolo_yaml = _request_json("POST", f"{base_url}/api/datasets/{dataset_name}/yolo-yaml", {"class_names": class_names}, timeout=20) + yolo_yaml_json = yolo_yaml.get("json") if yolo_yaml.get("passed") else {} + checks.append({"name": "real_train_dataset_yolo_yaml", "passed": yolo_yaml.get("passed", False), "detail": yolo_yaml}) + + train_name = f"{dataset_name}_train" + train = _create_job_and_wait( + base_url, + "yolo.train_custom", + { + "data": yolo_yaml_json.get("relative_path", f"var/uploads/datasets/{dataset_name}/dataset.yaml"), + "model": str(settings.source_root / "Seg_All_In_One_YoloModel" / "yolo11n-seg.pt"), + "project": "var/custom_yolo_runs", + "name": train_name, + "epochs": 1, + "imgsz": 96, + "batch": 1, + "workers": 0, + "device": "cpu", + "exist_ok": True, + }, + timeout=240, + ) + train_root = settings.project_root / "var" / "custom_yolo_runs" / train_name + best_weight = train_root / "weights" / "best.pt" + last_weight = train_root / "weights" / "last.pt" + results_csv = train_root / "results.csv" + checks.append( + { + "name": "real_train_yolo_one_epoch_job_runner", + "passed": train.get("passed", False) and best_weight.exists() and results_csv.exists() and results_csv.stat().st_size > 0, + "detail": { + **train, + "best_weight": _relative_to_project(best_weight) if best_weight.exists() else None, + "last_weight": _relative_to_project(last_weight) if last_weight.exists() else None, + "results_csv": _relative_to_project(results_csv) if results_csv.exists() else None, + "results_csv_size": results_csv.stat().st_size if results_csv.exists() else 0, + }, + } + ) + + uploaded_image_json = uploads["real_train_yolo_image_upload"].get("json", {}) + uploaded_image = uploaded_image_json.get("saved", [{}])[0].get("relative_path") + predict_name = f"{dataset_name}_predict_trained" + if best_weight.exists() and uploaded_image: + predict = _create_job_and_wait( + base_url, + "yolo.predict_custom", + { + "weights": str(best_weight), + "source": uploaded_image, + "project": "var/custom_yolo_runs", + "name": predict_name, + "imgsz": 96, + "conf": 0.01, + "device": "cpu", + "exist_ok": True, + }, + timeout=120, + ) + else: + predict = {"passed": False, "error": "skipped because training did not produce best.pt or upload path"} + predict_root = settings.project_root / "var" / "custom_yolo_runs" / predict_name + predict_outputs = _result_files(predict_root, {".png", ".jpg", ".jpeg"}) + checks.append( + { + "name": "real_train_trained_weight_predict_job_runner", + "passed": predict.get("passed", False) and bool(predict_outputs), + "detail": {**predict, "output_count": len(predict_outputs), "outputs": [_relative_to_project(path) for path in predict_outputs[:8]]}, + } + ) + + heatmap_name = f"{dataset_name}_heatmap_trained" + if best_weight.exists() and uploaded_image: + heatmap = _create_job_and_wait( + base_url, + "yolo.heatmap_custom", + { + "weights": str(best_weight), + "source": uploaded_image, + "project": "var/custom_yolo_runs", + "name": heatmap_name, + "model_key": "YOLO11n-seg", + "pt_name": "best.pt", + "cam_method": "GradCAM", + "target_layers": "model.model.model[9]", + "limit": 1, + }, + timeout=120, + ) + else: + heatmap = {"passed": False, "error": "skipped because training did not produce best.pt or upload path"} + heatmap_root = settings.project_root / "var" / "custom_yolo_runs" / heatmap_name / "HeartMap_Visual" + heatmap_outputs = _result_files(heatmap_root, {".jpg", ".jpeg", ".png"}) + checks.append( + { + "name": "real_train_trained_weight_heatmap_job_runner", + "passed": heatmap.get("passed", False) and len(heatmap_outputs) >= 2, + "detail": {**heatmap, "output_count": len(heatmap_outputs), "outputs": [_relative_to_project(path) for path in heatmap_outputs[:8]]}, + } + ) + + report = { + "available": True, + "run_id": run_id, + "base_url": base_url, + "fixture_root": str(fixture_root), + "dataset_name": dataset_name, + "samples": samples, + "artifacts": { + "train_root": _relative_to_project(train_root), + "best_weight": _relative_to_project(best_weight) if best_weight.exists() else None, + "results_csv": _relative_to_project(results_csv) if results_csv.exists() else None, + "predict_outputs": [_relative_to_project(path) for path in predict_outputs[:8]], + "heatmap_outputs": [_relative_to_project(path) for path in heatmap_outputs[:8]], + }, + "passed": all(item["passed"] for item in checks), + "checks": checks, + "created_at": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()), + } + (acceptance_root / "real_train_latest.json").write_text(json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8") + return report + + def run_deep_acceptance() -> dict[str, Any]: """Run minimal training loops for each model family without full datasets.""" acceptance_root = settings.project_root / "var" / "acceptance" diff --git a/backend/app/agents/evaluation_agent.py b/backend/app/agents/evaluation_agent.py index a03c253..1af07ca 100644 --- a/backend/app/agents/evaluation_agent.py +++ b/backend/app/agents/evaluation_agent.py @@ -108,6 +108,12 @@ def evaluate_project() -> dict: and "real_workspace_yolo_predict_job_runner" in acceptance_text and "real_workspace_yolo_heatmap_job_runner" in acceptance_text and "real_workspace_stack_job_runner" in acceptance_text, + "real_train_acceptance": "/api/acceptance/real-train" in backend_text + and "runRealTrainAcceptance" in frontend_text + and "真实短训" in frontend_text + and "real_train_yolo_one_epoch_job_runner" in acceptance_text + and "real_train_trained_weight_predict_job_runner" in acceptance_text + and "real_train_trained_weight_heatmap_job_runner" in acceptance_text, "agent_api": "/api/agents/evaluate" in backend_text and "/api/agents/validate" in backend_text, "agent_panel_ui": "runAgentValidation" in frontend_text and "评价建议" in frontend_text and "Validation Agent" in frontend_text, "coverage_api": "/api/coverage" in backend_text and coverage["task_build_passed"], @@ -132,7 +138,7 @@ def evaluate_project() -> dict: if coverage["unmapped_user_scripts"]: suggestions.append(f"Map remaining user-facing scripts: {len(coverage['unmapped_user_scripts'])}") if not suggestions: - suggestions.append("Current platform covers the requested control-plane features, uploaded YOLO dataset train/predict/heatmap actions, live uploaded-data YOLO predict/heatmap acceptance, real workspace data acceptance, and synthetic deep training acceptance; next focus is a longer operator-run task on a full dataset.") + suggestions.append("Current platform covers the requested control-plane features, uploaded YOLO dataset train/predict/heatmap actions, live uploaded-data YOLO predict/heatmap acceptance, real workspace data acceptance, real short-train acceptance, and synthetic deep training acceptance; next focus is a longer operator-run task on a full dataset.") passed_count = sum(1 for item in checks if item["passed"]) total_count = max(len(checks), 1) diff --git a/backend/app/agents/validation_agent.py b/backend/app/agents/validation_agent.py index 43b5542..f0f8946 100644 --- a/backend/app/agents/validation_agent.py +++ b/backend/app/agents/validation_agent.py @@ -8,7 +8,7 @@ import urllib.error import urllib.request from pathlib import Path -from ..acceptance import run_deep_acceptance, run_live_acceptance, run_real_dataset_acceptance +from ..acceptance import run_deep_acceptance, run_live_acceptance, run_real_dataset_acceptance, run_real_train_acceptance from ..capabilities import get_capability_matrix from ..catalog import get_catalog from ..config import settings @@ -47,6 +47,7 @@ def validate_project( run_acceptance: bool | None = None, run_deep: bool | None = None, run_real: bool | None = None, + run_real_train: bool | None = None, run_live: bool | None = None, ) -> dict: """Validate current runtime readiness without launching heavy training.""" @@ -122,8 +123,9 @@ def validate_project( acceptance_enabled = run_acceptance if run_acceptance is not None else os.getenv("SEG_VALIDATE_ACCEPTANCE", "0") == "1" deep_enabled = run_deep if run_deep is not None else os.getenv("SEG_VALIDATE_DEEP", "1") == "1" real_enabled = run_real if run_real is not None else os.getenv("SEG_VALIDATE_REAL", "0") == "1" + real_train_enabled = run_real_train if run_real_train is not None else os.getenv("SEG_VALIDATE_REAL_TRAIN", "0") == "1" live_enabled = run_live if run_live is not None else os.getenv("SEG_VALIDATE_LIVE", "0") == "1" - live_enabled = live_enabled or acceptance_enabled or real_enabled + live_enabled = live_enabled or acceptance_enabled or real_enabled or real_train_enabled if live_enabled: backend_url = os.getenv("SEG_VALIDATE_BACKEND_URL", "http://127.0.0.1:8010") @@ -166,6 +168,9 @@ def validate_project( if real_enabled: real_acceptance = run_real_dataset_acceptance(backend_url) checks.append({"name": "real_workspace_acceptance", "passed": real_acceptance["passed"], "detail": real_acceptance}) + if real_train_enabled: + real_train_acceptance = run_real_train_acceptance(backend_url) + checks.append({"name": "real_train_acceptance", "passed": real_train_acceptance["passed"], "detail": real_train_acceptance}) if deep_enabled: deep_acceptance = run_deep_acceptance() checks.append({"name": "deep_training_acceptance", "passed": deep_acceptance["passed"], "detail": deep_acceptance}) diff --git a/backend/app/capabilities.py b/backend/app/capabilities.py index 1a68705..f578c62 100644 --- a/backend/app/capabilities.py +++ b/backend/app/capabilities.py @@ -3,7 +3,12 @@ from __future__ import annotations import time from typing import Any -from .acceptance import latest_acceptance_report, latest_deep_acceptance_report, latest_real_acceptance_report +from .acceptance import ( + latest_acceptance_report, + latest_deep_acceptance_report, + latest_real_acceptance_report, + latest_real_train_acceptance_report, +) from .catalog import get_catalog from .coverage import get_coverage_report from .modules.dataset.service import list_uploaded_datasets @@ -157,6 +162,7 @@ def get_capability_matrix() -> dict[str, Any]: gpus = get_gpus() acceptance = latest_acceptance_report() real_acceptance = latest_real_acceptance_report() + real_train_acceptance = latest_real_train_acceptance_report() deep_acceptance = latest_deep_acceptance_report() all_tasks = catalog["task_types"] @@ -277,6 +283,12 @@ def get_capability_matrix() -> dict[str, Any]: "passed": bool(real_acceptance.get("passed")), "detail": real_acceptance.get("run_id", "not run"), }, + { + "id": "real_train_acceptance", + "label": "真实短训练验收", + "passed": bool(real_train_acceptance.get("passed")), + "detail": real_train_acceptance.get("run_id", "not run"), + }, { "id": "weights_manifest", "label": "权重清单", @@ -302,6 +314,7 @@ def get_capability_matrix() -> dict[str, Any]: "gpus_available": bool(gpus.get("available")), "acceptance_passed": bool(acceptance.get("passed")), "real_acceptance_passed": bool(real_acceptance.get("passed")), + "real_train_acceptance_passed": bool(real_train_acceptance.get("passed")), "deep_acceptance_passed": bool(deep_acceptance.get("passed")), }, "requirements": requirements, diff --git a/backend/app/main.py b/backend/app/main.py index 3bbb6b7..ed95a7f 100644 --- a/backend/app/main.py +++ b/backend/app/main.py @@ -13,9 +13,11 @@ from .acceptance import ( latest_acceptance_report, latest_deep_acceptance_report, latest_real_acceptance_report, + latest_real_train_acceptance_report, run_deep_acceptance, run_live_acceptance, run_real_dataset_acceptance, + run_real_train_acceptance, ) from .capabilities import get_capability_matrix from .catalog import get_catalog @@ -131,6 +133,16 @@ def api_real_acceptance(base_url: str = "http://127.0.0.1:8010") -> dict: return run_real_dataset_acceptance(base_url) +@app.get("/api/acceptance/real-train/latest") +def api_real_train_acceptance_latest() -> dict: + return latest_real_train_acceptance_report() + + +@app.post("/api/acceptance/real-train") +def api_real_train_acceptance(base_url: str = "http://127.0.0.1:8010") -> dict: + return run_real_train_acceptance(base_url) + + @app.get("/api/datasets") def api_datasets() -> list[dict]: return list_uploaded_datasets() @@ -295,6 +307,7 @@ def api_agent_validate( run_acceptance: bool = False, run_deep: bool = False, run_real: bool = False, + run_real_train: bool = False, run_live: bool | None = None, ) -> dict: return validate_project( @@ -302,5 +315,6 @@ def api_agent_validate( run_acceptance=run_acceptance, run_deep=run_deep, run_real=run_real, + run_real_train=run_real_train, run_live=run_live, ) diff --git a/backend/tests/test_agents.py b/backend/tests/test_agents.py index d8818ed..4e678c9 100644 --- a/backend/tests/test_agents.py +++ b/backend/tests/test_agents.py @@ -10,6 +10,7 @@ def test_evaluation_agent_returns_checks(): assert result["summary"]["passed_checks"] == result["summary"]["total_checks"] checks = {item["name"]: item["passed"] for item in result["checks"]} assert checks["real_workspace_acceptance"] is True + assert checks["real_train_acceptance"] is True def test_validation_agent_lightweight(monkeypatch): diff --git a/backend/tests/test_capabilities.py b/backend/tests/test_capabilities.py index 88bdc96..98c2185 100644 --- a/backend/tests/test_capabilities.py +++ b/backend/tests/test_capabilities.py @@ -20,3 +20,4 @@ def test_capability_matrix_tracks_user_requirements(): assert requirements["yolo_heatmap"]["passed"] is True assert requirements["training_curves"]["passed"] is True assert requirements["real_workspace_acceptance"]["passed"] is True + assert requirements["real_train_acceptance"]["passed"] is True diff --git a/frontend/src/main.tsx b/frontend/src/main.tsx index fc07718..56caaf4 100644 --- a/frontend/src/main.tsx +++ b/frontend/src/main.tsx @@ -380,6 +380,7 @@ function useData() { const [coverage, setCoverage] = useState(null); const [acceptance, setAcceptance] = useState(null); const [realAcceptance, setRealAcceptance] = useState(null); + const [realTrainAcceptance, setRealTrainAcceptance] = useState(null); const [deepAcceptance, setDeepAcceptance] = useState(null); const [runtimeReadiness, setRuntimeReadiness] = useState(null); const [capabilities, setCapabilities] = useState(null); @@ -388,7 +389,7 @@ function useData() { async function refresh() { try { - const [catalogNext, gpusNext, envsNext, readinessNext, capabilitiesNext, jobsNext, resultsNext, curvesNext, weightsNext, datasetsNext, coverageNext, acceptanceNext, realAcceptanceNext, deepAcceptanceNext, agentEvaluationNext] = await Promise.all([ + const [catalogNext, gpusNext, envsNext, readinessNext, capabilitiesNext, jobsNext, resultsNext, curvesNext, weightsNext, datasetsNext, coverageNext, acceptanceNext, realAcceptanceNext, realTrainAcceptanceNext, deepAcceptanceNext, agentEvaluationNext] = await Promise.all([ api("/api/catalog"), api("/api/system/gpus"), api("/api/system/envs"), @@ -402,6 +403,7 @@ function useData() { api("/api/coverage"), api("/api/acceptance/latest"), api("/api/acceptance/real/latest"), + api("/api/acceptance/real-train/latest"), api("/api/acceptance/deep/latest"), api("/api/agents/evaluate") ]); @@ -430,6 +432,7 @@ function useData() { setCoverage(coverageNext); setAcceptance(acceptanceNext); setRealAcceptance(realAcceptanceNext); + setRealTrainAcceptance(realTrainAcceptanceNext); setDeepAcceptance(deepAcceptanceNext); setAgentEvaluation(agentEvaluationNext); setError(""); @@ -444,7 +447,7 @@ function useData() { return () => window.clearInterval(timer); }, []); - return { catalog, gpus, condaEnvs, runtimeReadiness, capabilities, agentEvaluation, jobs, results, curves, weightManifest, datasets, datasetValidations, coverage, acceptance, realAcceptance, deepAcceptance, error, refresh }; + return { catalog, gpus, condaEnvs, runtimeReadiness, capabilities, agentEvaluation, jobs, results, curves, weightManifest, datasets, datasetValidations, coverage, acceptance, realAcceptance, realTrainAcceptance, deepAcceptance, error, refresh }; } function StatusPill({ status }: { status: string }) { @@ -467,7 +470,7 @@ function JobProgressBar({ progress }: { progress?: JobProgress }) { } function App() { - const { catalog, gpus, condaEnvs, runtimeReadiness, capabilities, agentEvaluation, jobs, results, curves, weightManifest, datasets, datasetValidations, coverage, acceptance, realAcceptance, deepAcceptance, error, refresh } = useData(); + const { catalog, gpus, condaEnvs, runtimeReadiness, capabilities, agentEvaluation, jobs, results, curves, weightManifest, datasets, datasetValidations, coverage, acceptance, realAcceptance, realTrainAcceptance, deepAcceptance, error, refresh } = useData(); const [taskType, setTaskType] = useState("mock.echo"); const [params, setParams] = useState(JSON.stringify(defaultParams["mock.echo"], null, 2)); const [selectedJob, setSelectedJob] = useState(null); @@ -671,6 +674,16 @@ function App() { } } + async function runRealTrainAcceptance() { + setBusy(true); + try { + await api("/api/acceptance/real-train", { method: "POST" }); + await refresh(); + } finally { + setBusy(false); + } + } + async function runAgentValidation() { setAgentBusy(true); try { @@ -1133,6 +1146,9 @@ function App() { + @@ -1163,6 +1179,10 @@ function App() { 真实数据 {realAcceptance?.available === false ? "New" : realAcceptance?.passed ? "OK" : "Check"} +
+ 真实短训 + {realTrainAcceptance?.available === false ? "New" : realTrainAcceptance?.passed ? "OK" : "Check"} +
深度训练 {deepAcceptance?.available === false ? "New" : deepAcceptance?.passed ? "OK" : "Check"} @@ -1174,6 +1194,7 @@ function App() { 当前用户侧脚本已全部映射到网页任务。 最近验收：{acceptance?.created_at ?? "尚未运行"} {acceptance?.run_id ? `#${acceptance.run_id}` : ""} 真实数据：{realAcceptance?.created_at ?? "尚未运行"} {realAcceptance?.run_id ? `#${realAcceptance.run_id}` : ""}，通过 {realAcceptance?.checks?.filter((item) => item.passed).length ?? 0}/{realAcceptance?.checks?.length ?? 0} + 真实短训：{realTrainAcceptance?.created_at ?? "尚未运行"} {realTrainAcceptance?.run_id ? `#${realTrainAcceptance.run_id}` : ""}，通过 {realTrainAcceptance?.checks?.filter((item) => item.passed).length ?? 0}/{realTrainAcceptance?.checks?.length ?? 0} 深度验收：{deepAcceptance?.created_at ?? "尚未运行"} {deepAcceptance?.run_id ? `#${deepAcceptance.run_id}` : ""}，通过 {deepAcceptance?.checks?.filter((item) => item.passed).length ?? 0}/{deepAcceptance?.checks?.length ?? 0} 模型族 readiness：{acceptance?.model_family_readiness?.checks?.filter((item) => item.passed).length ?? 0}/{acceptance?.model_family_readiness?.checks?.length ?? 0}，warnings {acceptance?.model_family_readiness?.warnings?.length ?? 0} diff --git a/scripts/run_agents.py b/scripts/run_agents.py index 0286e2d..57402b6 100644 --- a/scripts/run_agents.py +++ b/scripts/run_agents.py @@ -19,6 +19,7 @@ def main() -> None: parser.add_argument("--live", action="store_true", help="also check live backend/frontend HTTP endpoints") parser.add_argument("--acceptance", action="store_true", help="run the lightweight live acceptance smoke") parser.add_argument("--real", action="store_true", help="run real workspace data acceptance through the live backend") + parser.add_argument("--real-train", action="store_true", help="run a short real workspace YOLO train/predict/heatmap acceptance") parser.add_argument("--no-deep", action="store_true", help="skip synthetic deep training acceptance") parser.add_argument("--out", default="var/agent_reports/latest.json") args = parser.parse_args() @@ -29,6 +30,7 @@ def main() -> None: run_live=args.live, run_acceptance=args.acceptance, run_real=args.real, + run_real_train=args.real_train, run_deep=not args.no_deep, ), }