feat(lab): seal native risk review evidence
This commit is contained in:
DCCONSTRUCTIONS
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"""Seal native raw-fisheye M4.8Q risk review evidence as a terminal LAB phase."""
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from __future__ import annotations
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import hashlib
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import json
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import re
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import shutil
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import tempfile
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from dataclasses import dataclass
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from datetime import UTC, datetime
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from pathlib import Path
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from typing import Any, Final
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from k1link.perception.fixed_class_detector_tournament import (
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canonical_json,
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false_authority,
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sha256_path,
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)
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LAB_SCHEMA: Final = "missioncore.m48q-native-risk-quality-lab/v1"
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REPORT_SCHEMA: Final = "missioncore.m48q-native-risk-quality-report/v1"
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CATALOG_SCHEMA: Final = "missioncore.m48q-native-risk-review-catalog/v1"
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CASE_SCHEMA: Final = "missioncore.m48q-native-risk-review-case/v1"
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RESULT_PREFIX: Final = "m48q-native-risk-quality-lab-"
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PROFILE_RELATIVE_PATH: Final = Path("config/perception/m48q-native-risk-case-mining-v1.json")
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DETECTOR_PROFILE_RELATIVE_PATH: Final = Path(
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"config/perception/rf-detr-large-native-kb4-risk-shadow-v0.json"
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)
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WORKER_RELATIVE_ROOT: Final = Path(
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".runtime/worker-results/m48q-native-risk-case-mining/ravnoves00-native-raw-review-v3"
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)
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EXPECTED_PROFILE_SHA256: Final = "c455055e63578d505edc80b66d67e795916a3d0297cc18bfee5a6af7b032ceda"
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EXPECTED_DETECTOR_PROFILE_SHA256: Final = (
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"dbf4da5dbad6c3c22b1280b46ffcad81719bd183c81c263a4859847d829019b6"
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)
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EXPECTED_WORKER_RESULT_SHA256: Final = (
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"a8f98d6d68abd6fd627caa05aaa3f048d69279a989b07fc2552b508af909a623"
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)
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EXPECTED_CASES_SHA256: Final = "9cea2a4a4558d761bc76b0d70474673ff07210473f53bd32cf178e8e0c8e179c"
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EXPECTED_REPORT_IDENTITY_SHA256: Final = (
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"b744775c0e08d18d728f04021cd2acf9b1ed6fcacf1520352ee04e06a6d5d324"
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)
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CASE_ID: Final = re.compile(r"^[0-9]{6}$")
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class M48QNativeRiskQualityLabError(RuntimeError):
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"""Raised when native M4.8Q evidence cannot be sealed honestly."""
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@dataclass(frozen=True, slots=True)
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class M48QNativeRiskQualityLabResult:
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result_root: Path
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result_id: str
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manifest: dict[str, Any]
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def build_m48q_native_risk_quality_lab(
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*,
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repository_root: Path,
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output_root: Path,
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) -> M48QNativeRiskQualityLabResult:
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repository = repository_root.expanduser().resolve(strict=True)
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profile_path = repository / PROFILE_RELATIVE_PATH
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detector_profile_path = repository / DETECTOR_PROFILE_RELATIVE_PATH
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worker_root = repository / WORKER_RELATIVE_ROOT
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worker_result_path = worker_root / "result.json"
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cases_path = worker_root / "cases.jsonl"
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images_root = worker_root / "cases"
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for path in (
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profile_path,
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detector_profile_path,
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worker_result_path,
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cases_path,
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):
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if path.is_symlink() or not path.is_file():
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raise M48QNativeRiskQualityLabError(f"required M4.8Q evidence is missing: {path.name}")
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if images_root.is_symlink() or not images_root.is_dir():
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raise M48QNativeRiskQualityLabError("M4.8Q image evidence is missing")
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expected_hashes = {
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profile_path: EXPECTED_PROFILE_SHA256,
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detector_profile_path: EXPECTED_DETECTOR_PROFILE_SHA256,
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worker_result_path: EXPECTED_WORKER_RESULT_SHA256,
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cases_path: EXPECTED_CASES_SHA256,
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}
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if any(sha256_path(path) != expected for path, expected in expected_hashes.items()):
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raise M48QNativeRiskQualityLabError("M4.8Q source evidence identity changed")
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profile = _read_object(profile_path)
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detector_profile = _read_object(detector_profile_path)
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worker_result = _read_object(worker_result_path)
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cases = _read_cases(cases_path)
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_validate_inputs(
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profile=profile,
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detector_profile=detector_profile,
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worker_result=worker_result,
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cases=cases,
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images_root=images_root,
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)
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method = _method(profile, detector_profile, worker_result)
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identity = {
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"schema_version": LAB_SCHEMA,
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"profile": {
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"profile_id": profile["profile_id"],
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"sha256": EXPECTED_PROFILE_SHA256,
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},
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"detector_profile": {
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"profile_id": detector_profile["profile_id"],
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"sha256": EXPECTED_DETECTOR_PROFILE_SHA256,
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},
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"source": {
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"source_id": "RAVNOVES00",
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"video_sha256": profile["source"]["video_sha256"],
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"graph_result_sha256": worker_result["source"]["graph_result_sha256"],
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"graph_frames_sha256": worker_result["source"]["graph_frames_sha256"],
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"comparison_result_sha256": worker_result["source"]["comparison_result_sha256"],
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"comparison_frames_sha256": worker_result["source"]["comparison_frames_sha256"],
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"worker_result_sha256": EXPECTED_WORKER_RESULT_SHA256,
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"cases_sha256": EXPECTED_CASES_SHA256,
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},
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"method": method,
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"authority": false_authority(),
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}
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identity_sha256 = hashlib.sha256(canonical_json(identity)).hexdigest()
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result_id = RESULT_PREFIX + identity_sha256
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root = output_root.expanduser().absolute()
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root.mkdir(mode=0o700, parents=True, exist_ok=True)
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destination = root / result_id
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if destination.exists():
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manifest = _read_object(destination / "manifest.json")
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if (
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manifest.get("schema_version") != LAB_SCHEMA
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or manifest.get("identity_sha256") != identity_sha256
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or manifest.get("result_id") != result_id
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):
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raise M48QNativeRiskQualityLabError("existing M4.8Q LAB identity conflicts")
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return M48QNativeRiskQualityLabResult(destination, result_id, manifest)
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created_at_utc = datetime.now(UTC).isoformat(timespec="microseconds").replace("+00:00", "Z")
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temporary = Path(tempfile.mkdtemp(prefix=".m48q-native-risk-lab-", dir=root))
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try:
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(temporary / "cases").mkdir(mode=0o700)
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shutil.copyfile(profile_path, temporary / "profile.json")
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shutil.copyfile(detector_profile_path, temporary / "detector-profile.json")
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shutil.copyfile(worker_result_path, temporary / "worker-result.json")
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shutil.copyfile(cases_path, temporary / "cases.jsonl")
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catalog_cases: list[dict[str, object]] = []
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for case in cases:
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image = case["image"]
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source_image = worker_root / image["path"]
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destination_image = temporary / image["path"]
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shutil.copyfile(source_image, destination_image)
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catalog_cases.append(
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{
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"case_id": case["case_id"],
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"sequence": case["sequence"],
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"frame_id": case["frame_id"],
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"evidence_time_ns": case["evidence_time_ns"],
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"path": image["path"],
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"media_type": "image/jpeg",
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"width": 800,
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"height": 600,
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"byte_length": destination_image.stat().st_size,
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"sha256": sha256_path(destination_image),
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"geometric_resampling": False,
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"selection_buckets": case["selection_buckets"],
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"comparison": case["comparison"],
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"proposals": case["proposals"],
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}
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)
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catalog = {
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"schema_version": CATALOG_SCHEMA,
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"result_id": result_id,
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"case_count": len(catalog_cases),
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"source_raster": {"width": 800, "height": 600},
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"overlay": {
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"client_rendered": True,
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"toggleable": True,
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"box_coordinates": "source-pixel-xyxy",
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"class_names": True,
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"scores": True,
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},
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"ground_truth": False,
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"cases": catalog_cases,
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}
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catalog_path = temporary / "catalog.json"
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catalog_path.write_bytes(canonical_json(catalog) + b"\n")
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graph_qualification = detector_profile["qualification"][
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"full_ravnoves00_integrated_reference_graph"
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]
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decision = {
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"review_ready": True,
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"quality_evaluated": False,
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"ground_truth": False,
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"candidate_accepted": False,
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"production_accepted": False,
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"next_action": "operator-adjudication-in-existing-m48-review-instrument",
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}
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report = {
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"schema_version": REPORT_SCHEMA,
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"result_id": result_id,
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"source": {
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**profile["source"],
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"graph_result_sha256": worker_result["source"]["graph_result_sha256"],
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"graph_frames_sha256": worker_result["source"]["graph_frames_sha256"],
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"independent_route_truth_available": False,
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},
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"configuration": {
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"candidate": profile["candidate"],
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"selection": profile["selection"],
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},
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"method": method,
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"execution": {
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"worker": worker_result["worker"],
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"full_graph_frames": graph_qualification["frame_count"],
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"requested_source_rate_hz": graph_qualification["requested_source_rate_hz"],
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"effective_world_state_fps": graph_qualification["effective_world_state_fps"],
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"world_state_completion_p95_ms": graph_qualification[
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"world_state_completion_p95_ms"
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],
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"detector_total_p95_ms": graph_qualification["detector_total_p95_ms"],
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"gpu_utilization_p95_percent": graph_qualification["gpu_utilization_p95_percent"],
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"gpu_memory_used_maximum_mib": graph_qualification["gpu_memory_used_maximum_mib"],
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"additional_inference_passes": 0,
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},
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"metrics": {
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"selection": worker_result["selection"],
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"runtime": {
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"delivery_ratio": graph_qualification["delivery_ratio"],
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"integrated_runtime_gate_passed": graph_qualification[
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"integrated_runtime_gate_passed"
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],
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"operating_target_gate_passed": graph_qualification[
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"operating_target_gate_passed"
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],
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},
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"native_tensor_parity": detector_profile["qualification"][
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"native_pytorch_tensorrt_parity"
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],
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"native_vs_legacy_704": detector_profile["qualification"][
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"full_ravnoves00_native_vs_legacy_704"
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],
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},
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"acceptance": {
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"review_ready": True,
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"integrated_runtime_gate_passed": True,
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"independent_quality_evaluated": False,
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"semantic_candidate_accepted": False,
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},
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"decision": decision,
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"limitations": worker_result["limitations"],
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"authority": false_authority(),
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"visual_evidence": {
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"kind": "native-raw-fisheye-risk-case-review",
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"case_count": 24,
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"source_raster": "800x600",
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"geometric_resampling": False,
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"boxes_baked_into_images": False,
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"ground_truth": False,
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},
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}
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report_path = temporary / "report.json"
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report_path.write_bytes(canonical_json(report) + b"\n")
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artifacts = _artifact_manifest(temporary)
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manifest = {
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"schema_version": LAB_SCHEMA,
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"result_id": result_id,
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"identity_sha256": identity_sha256,
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"identity": identity,
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"created_at_utc": created_at_utc,
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"status": "complete-review-ready-quality-not-adjudicated",
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"completed": True,
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"bounded_question_accepted": True,
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"ground_truth": False,
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"method": method,
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"metrics": report["metrics"],
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"decision": decision,
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"limitations": worker_result["limitations"],
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"authority": false_authority(),
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"artifacts": artifacts,
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}
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(temporary / "manifest.json").write_bytes(canonical_json(manifest) + b"\n")
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temporary.replace(destination)
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except BaseException:
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shutil.rmtree(temporary, ignore_errors=True)
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raise
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return M48QNativeRiskQualityLabResult(destination, result_id, manifest)
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def _validate_inputs(
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*,
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profile: dict[str, Any],
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detector_profile: dict[str, Any],
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worker_result: dict[str, Any],
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cases: list[dict[str, Any]],
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images_root: Path,
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) -> None:
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if (
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profile.get("schema_version") != "missioncore.m48q-native-risk-case-mining-profile/v1"
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or profile.get("source", {}).get("geometric_resampling") is not False
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or profile.get("source", {}).get("raster_width") != 800
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or profile.get("source", {}).get("raster_height") != 600
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or profile.get("authority") != false_authority()
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or detector_profile.get("schema_version")
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!= "missioncore.rf-detr-native-risk-shadow-profile/v0"
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or detector_profile.get("preprocessing", {}).get("resize") is not False
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or detector_profile.get("preprocessing", {}).get("geometric_resampling") is not False
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or detector_profile.get("status", {}).get("integrated_world_state_gate_passed") is not True
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or worker_result.get("schema_version")
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!= "missioncore.m48q-native-risk-case-mining-result/v1"
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or worker_result.get("status") != "complete-review-ready-quality-not-adjudicated"
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or worker_result.get("completed") is not True
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or worker_result.get("report_identity_sha256") != EXPECTED_REPORT_IDENTITY_SHA256
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or worker_result.get("artifacts", {}).get("cases", {}).get("sha256")
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!= EXPECTED_CASES_SHA256
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or worker_result.get("selection", {}).get("case_count") != 24
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or worker_result.get("decision", {}).get("quality_evaluated") is not False
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or worker_result.get("authority") != false_authority()
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or len(cases) != 24
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or len({case.get("case_id") for case in cases}) != 24
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):
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raise M48QNativeRiskQualityLabError("M4.8Q evidence contract changed")
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for case in cases:
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image = case.get("image")
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proposals = case.get("proposals")
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if (
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case.get("schema_version") != CASE_SCHEMA
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or not isinstance(case.get("case_id"), str)
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or CASE_ID.fullmatch(case["case_id"]) is None
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or case.get("case_id") != f"{case.get('sequence'):06d}"
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or case.get("frame_id") != f"frame-{case.get('sequence'):06d}"
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or case.get("ground_truth") is not False
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or case.get("quality_evaluated") is not False
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or case.get("authority") != false_authority()
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or not isinstance(image, dict)
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or image.get("path") != f"cases/frame-{case['case_id']}.jpg"
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or image.get("width") != 800
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or image.get("height") != 600
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or image.get("geometric_resampling") is not False
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or not isinstance(proposals, list)
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or not proposals
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):
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raise M48QNativeRiskQualityLabError("M4.8Q review case contract changed")
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image_path = images_root.parent / image["path"]
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if (
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image_path.is_symlink()
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or not image_path.is_file()
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or image_path.stat().st_size != image.get("byte_length")
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or sha256_path(image_path) != image.get("sha256")
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):
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raise M48QNativeRiskQualityLabError("M4.8Q review image proof changed")
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def _method(
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profile: dict[str, Any],
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detector_profile: dict[str, Any],
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worker_result: dict[str, Any],
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) -> dict[str, object]:
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return {
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"schema_version": "missioncore.laboratory-method/v1",
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"completeness": "complete",
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"execution_class": "hybrid",
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"pipeline_id": "m48q-native-raw-fisheye-risk-case-review/v1",
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"components": [
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{
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"kind": "source",
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"name": "RAVNOVES00 raw KB4 video",
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"version": "800x600 immutable recording",
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"role": "unrectified review raster",
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"identity_sha256": profile["source"]["video_sha256"],
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},
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{
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"kind": "model",
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"name": "RF-DETR-L native KB4 TensorRT",
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"version": profile["candidate"]["model_id"],
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"role": "fixed-class behavior-risk shadow proposals",
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"identity_sha256": profile["candidate"]["engine_sha256"],
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},
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{
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"kind": "runtime",
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"name": "M4.7 native reference graph",
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"version": "full RAVNOVES00 at recorded 12 FPS",
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"role": "proposal and realtime evidence source",
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"identity_sha256": worker_result["source"]["graph_result_sha256"],
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},
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{
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"kind": "algorithm",
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"name": "bounded diagnostic case miner",
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"version": profile["profile_id"],
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"role": "deterministic risk-family and edge-case sampling",
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"identity_sha256": worker_result["identity"]["runner_sha256"],
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},
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{
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"kind": "tool",
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"name": "M4.8 existing image-case review instrument",
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"version": "client-rendered source-pixel overlay/v1",
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"role": "operator review without baked boxes",
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"identity_sha256": EXPECTED_CASES_SHA256,
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},
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],
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}
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def _artifact_manifest(root: Path) -> list[dict[str, object]]:
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artifacts: list[dict[str, object]] = []
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for path in sorted(item for item in root.rglob("*") if item.is_file()):
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relative = path.relative_to(root).as_posix()
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if relative == "manifest.json":
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continue
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media_type = "application/json"
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schema_version: str | None = None
|
||||
role = "supporting-evidence"
|
||||
if relative == "report.json":
|
||||
role = "laboratory-report"
|
||||
schema_version = REPORT_SCHEMA
|
||||
elif relative == "catalog.json":
|
||||
role = "visual-evidence-catalog"
|
||||
schema_version = CATALOG_SCHEMA
|
||||
elif relative == "profile.json":
|
||||
role = "predeclared-native-risk-review-profile"
|
||||
schema_version = "missioncore.m48q-native-risk-case-mining-profile/v1"
|
||||
elif relative == "detector-profile.json":
|
||||
role = "qualified-native-detector-profile"
|
||||
schema_version = "missioncore.rf-detr-native-risk-shadow-profile/v0"
|
||||
elif relative == "worker-result.json":
|
||||
role = "upstream-worker-case-mining-result"
|
||||
schema_version = "missioncore.m48q-native-risk-case-mining-result/v1"
|
||||
elif relative == "cases.jsonl":
|
||||
media_type = "application/x-ndjson"
|
||||
role = "native-risk-review-case-ledger"
|
||||
schema_version = CASE_SCHEMA
|
||||
elif relative.endswith(".jpg"):
|
||||
media_type = "image/jpeg"
|
||||
role = "visual-evidence-native-raw-fisheye-frame"
|
||||
artifacts.append(
|
||||
{
|
||||
"role": role,
|
||||
"path": relative,
|
||||
"byte_length": path.stat().st_size,
|
||||
"sha256": sha256_path(path),
|
||||
"media_type": media_type,
|
||||
"schema_version": schema_version,
|
||||
}
|
||||
)
|
||||
return artifacts
|
||||
|
||||
|
||||
def _read_object(path: Path) -> dict[str, Any]:
|
||||
try:
|
||||
value: object = json.loads(path.read_text("utf-8"))
|
||||
except (OSError, json.JSONDecodeError) as exc:
|
||||
raise M48QNativeRiskQualityLabError(f"invalid JSON evidence: {path.name}") from exc
|
||||
if not isinstance(value, dict):
|
||||
raise M48QNativeRiskQualityLabError(f"JSON evidence must be an object: {path.name}")
|
||||
return value
|
||||
|
||||
|
||||
def _read_cases(path: Path) -> list[dict[str, Any]]:
|
||||
cases: list[dict[str, Any]] = []
|
||||
try:
|
||||
with path.open("r", encoding="utf-8") as stream:
|
||||
for line in stream:
|
||||
value: object = json.loads(line)
|
||||
if not isinstance(value, dict):
|
||||
raise M48QNativeRiskQualityLabError("M4.8Q case ledger row is not an object")
|
||||
cases.append(value)
|
||||
except (OSError, json.JSONDecodeError) as exc:
|
||||
raise M48QNativeRiskQualityLabError("M4.8Q case ledger cannot be read") from exc
|
||||
return cases
|
||||
Reference in New Issue
Block a user