Gate real train curve evidence
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@@ -30,6 +30,7 @@ def evaluate_project() -> dict:
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backend = settings.project_root / "backend" / "app" / "main.py"
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jobs_backend = settings.project_root / "backend" / "app" / "jobs.py"
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readme = settings.project_root / "README.md"
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results_service = settings.project_root / "backend" / "app" / "modules" / "results" / "service.py"
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catalog = get_catalog()
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coverage = get_coverage_report()
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checks = []
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@@ -39,6 +40,7 @@ def evaluate_project() -> dict:
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backend_text = backend.read_text(encoding="utf-8") if backend.exists() else ""
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jobs_text = jobs_backend.read_text(encoding="utf-8") if jobs_backend.exists() else ""
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acceptance_text = (settings.project_root / "backend" / "app" / "acceptance.py").read_text(encoding="utf-8")
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results_service_text = results_service.read_text(encoding="utf-8") if results_service.exists() else ""
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readme_text = readme.read_text(encoding="utf-8") if readme.exists() else ""
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expectations = {
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@@ -119,6 +121,9 @@ def evaluate_project() -> dict:
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and "best_weight" in frontend_text
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and "results_csv" in frontend_text
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and "heatmap_outputs" in frontend_text,
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"single_epoch_curve_support": "if points:" in results_service_text
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and "scaled.length === 1" in frontend_text
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and "<circle" in frontend_text,
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"agent_api": "/api/agents/evaluate" in backend_text and "/api/agents/validate" in backend_text,
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"agent_panel_ui": "runAgentValidation" in frontend_text and "评价建议" in frontend_text and "Validation Agent" in frontend_text,
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"coverage_api": "/api/coverage" in backend_text and coverage["task_build_passed"],
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@@ -143,7 +148,7 @@ def evaluate_project() -> dict:
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if coverage["unmapped_user_scripts"]:
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suggestions.append(f"Map remaining user-facing scripts: {len(coverage['unmapped_user_scripts'])}")
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if not suggestions:
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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 with artifact links, and synthetic deep training acceptance; next focus is a longer operator-run task on a full dataset.")
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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 with artifact links and single-epoch curves, and synthetic deep training acceptance; next focus is a longer operator-run task on a full dataset.")
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passed_count = sum(1 for item in checks if item["passed"])
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total_count = max(len(checks), 1)
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@@ -168,6 +168,7 @@ def get_capability_matrix() -> dict[str, Any]:
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all_tasks = catalog["task_types"]
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buildable_tasks = _coverage_build_task_set(coverage)
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runtime_by_role = _runtime_map(readiness)
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real_train_curves = [item for item in curves if "real_train_acceptance" in item.get("relative_path", "")]
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domains = []
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for group in CAPABILITY_GROUPS:
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@@ -271,6 +272,12 @@ def get_capability_matrix() -> dict[str, Any]:
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"passed": len(curves) >= 1,
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"detail": f"{len(curves)} curve file(s)",
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},
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{
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"id": "real_train_curve",
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"label": "真实短训 loss 曲线",
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"passed": len(real_train_curves) >= 1,
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"detail": f"{len(real_train_curves)} real train curve file(s)",
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},
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{
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"id": "deep_acceptance",
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"label": "深度训练验收",
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@@ -310,6 +317,7 @@ def get_capability_matrix() -> dict[str, Any]:
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"uploaded_datasets": len(datasets),
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"artifacts": len(results),
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"curves": len(curves),
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"real_train_curves": len(real_train_curves),
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"weights": manifest.get("count", 0),
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"gpus_available": bool(gpus.get("available")),
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"acceptance_passed": bool(acceptance.get("passed")),
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