91 lines
5.1 KiB
Python
91 lines
5.1 KiB
Python
from __future__ import annotations
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from pathlib import Path
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from ..catalog import get_catalog
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from ..config import settings
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from ..coverage import get_coverage_report
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REQUIRED_TASKS = {
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"dataset.upload": "covered_by_api",
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"dataset.video_frames": "job",
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"dataset.yolo_txt_sort": "job",
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"segmodel.train": "job",
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"segmodel.predict": "job",
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"yolo.heatmap": "job",
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"yolo.video_visible": "job",
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"mmseg.flops_fps": "job",
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"analysis.all": "job",
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"visual.fps": "job",
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"system.check_graph_card": "job",
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}
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def evaluate_project() -> dict:
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"""Return product/implementation suggestions for the current web platform."""
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frontend = settings.project_root / "frontend" / "src" / "main.tsx"
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backend = settings.project_root / "backend" / "app" / "main.py"
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readme = settings.project_root / "README.md"
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catalog = get_catalog()
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coverage = get_coverage_report()
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checks = []
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suggestions = []
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frontend_text = frontend.read_text(encoding="utf-8") if frontend.exists() else ""
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backend_text = backend.read_text(encoding="utf-8") if 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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readme_text = readme.read_text(encoding="utf-8") if readme.exists() else ""
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expectations = {
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"left_nav_dataset": "数据集" in frontend_text and "#datasets" in frontend_text,
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"upload_ui": "uploadDatasetFiles" in frontend_text and "labels" in frontend_text and "masks" in frontend_text,
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"dataset_quality_ui": "DatasetQuality" in frontend_text and "generateSelectedYoloYaml" in frontend_text,
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"loss_result_ui": "loss" in frontend_text.lower() and "heatmap" in frontend_text.lower() and "CurvePanel" in frontend_text,
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"job_progress_ui": "JobProgressBar" in frontend_text and "progressTrack" in frontend_text,
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"runtime_readiness_ui": "runtimeReadiness" in frontend_text and "环境就绪" in frontend_text,
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"capability_matrix_ui": "capabilities" in frontend_text and "全功能矩阵" in frontend_text,
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"dataset_api": "/api/datasets" in backend_text and "api_upload_dataset_files" in backend_text,
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"dataset_quality_api": "/api/datasets/{dataset_name}/validate" in backend_text and "/api/datasets/{dataset_name}/yolo-yaml" in backend_text,
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"job_progress_api": "progress_from_log_path" in backend_text and '"progress"' in backend_text,
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"runtime_readiness_api": "/api/system/readiness" in backend_text,
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"capability_matrix_api": "/api/capabilities" in backend_text,
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"runtime_bootstrap_scripts": (settings.project_root / "scripts" / "bootstrap_conda_envs.sh").exists()
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and (settings.project_root / "scripts" / "verify_runtime_envs.py").exists(),
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"curve_api": "/api/results/curves" in backend_text,
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"deep_acceptance_api": "/api/acceptance/deep" in backend_text,
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"deep_acceptance_ui": "runDeepAcceptance" in frontend_text and "深度训练" in frontend_text,
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"deep_yolo_heatmap_validation": "yolo_tiny_heatmap_generation" in acceptance_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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"visual_tools": "visual.yolo11_heatmap_v2" in catalog["task_types"] and "visual.fps" in catalog["task_types"],
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"yolo_custom_train": "yolo.train_custom" in catalog["task_types"],
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"yolo_dataset_tools": "dataset.yolo_txt_sort" in catalog["task_types"] and "dataset.yolo_resize" in catalog["task_types"],
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"no_weight_to_gitea": "Do not push" in readme_text and "check_no_weight_git" in readme_text,
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"all_core_tasks": all(task in catalog["task_types"] for task in REQUIRED_TASKS if REQUIRED_TASKS[task] == "job"),
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"mapped_user_scripts": not coverage["unmapped_user_scripts"],
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}
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for name, passed in expectations.items():
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checks.append({"name": name, "passed": bool(passed)})
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if not passed:
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suggestions.append(f"Improve missing capability: {name}")
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if len(catalog["mmseg_algorithms"]) < 31:
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suggestions.append("MMSeg algorithm catalog should expose all 31 algorithm generators.")
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if len(catalog["segmodel_architectures"]) < 12:
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suggestions.append("SegModel catalog should expose all 12 supported architectures.")
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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 and synthetic deep training/heatmap acceptance; next focus is a user-supplied dataset end-to-end run.")
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score = sum(1 for item in checks if item["passed"]) / max(len(checks), 1)
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return {
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"agent": "evaluation_suggestion_agent",
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"score": round(score, 3),
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"checks": checks,
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"suggestions": suggestions,
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}
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