refactor: extract enrichment internals into StoreEnrichmentMixin
Move provider-state sync, local face evidence/crop sync + retention purge, internal/Google re-analysis, face-crop web detection, and the auto Google/Naver search drivers into a mixin; CopyrighterStore inherits it. Drop now-unused imports. Tests now also patch HeuristicFacePersonDetector on store_enrichment (face detection moved there). sqlite_store.py 2358 -> 1598 lines (-70% overall).
This commit is contained in:
유창욱
parent
8e0a8c307d
commit
3bc07d94c3
4 changed files with 802 additions and 760 deletions
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@ -15,9 +15,7 @@ from urllib.parse import urlparse
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from rights_filter.analysis.face_person_detection import HeuristicFacePersonDetector
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from rights_filter.analysis.fingerprints import FingerprintService
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from rights_filter.analysis.internal_analyzer import InternalAnalyzer
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from rights_filter.analysis.preprocessing import build_external_derivative, build_face_crop_derivatives
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from rights_filter.analysis.risk_scoring import RiskScorer
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from rights_filter.analysis.search_query_generation import SearchQueryGenerator
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from rights_filter.analysis.search_result_promoter import SearchResultPromoter
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from rights_filter.domain.records import (
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Evidence,
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@ -50,6 +48,7 @@ from rights_filter.server.store_remote_fetch import (
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_fetch_stylesheet_url_bytes,
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_fetch_url_bytes,
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)
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from rights_filter.server.store_enrichment import StoreEnrichmentMixin
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from rights_filter.server.store_persistence import StorePersistenceMixin
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from rights_filter.server.store_search_candidates import StoreSearchCandidatesMixin
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from rights_filter.server.store_schema import (
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@ -64,23 +63,10 @@ from rights_filter.server.store_serialization import (
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_evidence_id,
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_evidence_matches_provider,
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_evidence_payload,
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_existing_google_custom_query_signatures,
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_existing_naver_query_signatures,
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_external_provider_ids,
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_external_provider_state_for_submission,
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_face_crop_web_evidence,
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_google_custom_image_query_signature,
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_google_custom_web_query_signature,
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_google_weak_label_title,
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_is_google_weak_label_payload,
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_knowledge_type_value,
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_naver_blog_query_signature,
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_naver_query_signature,
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_naver_web_query_signature,
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_now_label,
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_provider_item_failed,
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_provider_item_has_result,
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_query_history_status,
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_stable_id,
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_submission_payload,
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_submission_search_hint_evidence,
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@ -90,7 +76,7 @@ from rights_filter.server.store_serialization import (
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from rights_filter.server.store_text import _text_list, _unique_texts
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class CopyrighterStore(StorePersistenceMixin, StoreSearchCandidatesMixin):
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class CopyrighterStore(StorePersistenceMixin, StoreSearchCandidatesMixin, StoreEnrichmentMixin):
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def __init__(
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self,
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db_path: Path | str,
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@ -1610,747 +1596,3 @@ class CopyrighterStore(StorePersistenceMixin, StoreSearchCandidatesMixin):
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),
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)
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def _sync_provider_payloads(self) -> None:
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existing = {provider["id"]: provider for provider in self._all("providers")}
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for provider_id, payload in self.provider_runtime.provider_payloads.items():
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merged = {
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**payload,
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"usage": existing.get(provider_id, {}).get("usage", payload["usage"]),
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}
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self._put("providers", provider_id, merged)
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self._sync_submission_provider_state()
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def _sync_submission_provider_state(self, queue_id: str | None = None) -> None:
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provider_payloads = {provider["id"]: provider for provider in self._all("providers")}
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evidence_by_submission = self._evidence_by_submission(queue_id=queue_id)
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for submission in self._all("submissions", queue_id=queue_id):
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provider_state = submission.get("providerState", {})
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evidence = evidence_by_submission.get(str(submission["id"]), [])
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provider_state["internal"] = "ok"
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for provider_id in _external_provider_ids(provider_payloads):
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provider_state[provider_id] = _external_provider_state_for_submission(
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provider_payloads,
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provider_id,
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submission,
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evidence,
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)
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submission["providerState"] = provider_state
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self._put("submissions", submission["id"], submission)
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def _normalize_saved_google_weak_labels_and_rescore(self, queue_id: str | None = None) -> None:
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changed_submissions: set[str] = set()
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with self._connect() as conn:
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rows = conn.execute(
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"""
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select id, submission_id, payload
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from evidence
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""".strip() + (
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" where submission_id in (select id from submissions where queue_id = ?)"
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if queue_id is not None
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else ""
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),
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(queue_id,) if queue_id is not None else (),
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).fetchall()
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for row in rows:
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payload = json.loads(row["payload"])
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if _is_google_weak_label_payload(payload):
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payload["title"] = _google_weak_label_title(str(payload.get("title", "")))
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payload["confidence"] = 0.0
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payload["contributed"] = False
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payload["status"] = "weak"
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self._put("evidence", row["id"], payload)
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changed_submissions.add(str(row["submission_id"]))
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for submission_id in changed_submissions:
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self._rescore_submission(submission_id)
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def _refresh_existing_local_face_evidence(
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self,
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image_store: LocalSubmissionImageStore,
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*,
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queue_id: str,
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) -> None:
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existing_submission_ids = {submission["id"] for submission in self._all("submissions", queue_id=queue_id)}
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if not existing_submission_ids:
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return
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evidence_by_submission = self._evidence_by_submission(queue_id=queue_id)
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detector = HeuristicFacePersonDetector()
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for record in image_store.submission_records():
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submission_id = str(record["id"])
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if submission_id not in existing_submission_ids:
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continue
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if any(
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item.get("source") == "face"
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for item in evidence_by_submission.get(submission_id, [])
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):
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continue
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signal = detector.detect(image_store.image_payload(submission_id))
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if not signal.present:
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continue
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evidence = Evidence(
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source=EvidenceSource.FACE_PERSON,
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reason="Face/person detected",
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confidence=0.8,
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data={
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"face_count": signal.face_count,
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"person_count": signal.person_count,
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},
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)
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self._put(
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"evidence",
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_evidence_id(submission_id, evidence),
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_evidence_payload(submission_id, evidence),
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)
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self._rescore_submission(submission_id)
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def _sync_face_crops(
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self,
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submission_id: str,
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image_store: LocalSubmissionImageStore | None,
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) -> None:
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if image_store is None:
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return
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try:
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original = image_store.image_payload(submission_id)
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except Exception:
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return
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signal = HeuristicFacePersonDetector().detect(original)
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crop_dir = self.face_crop_image_dir / submission_id
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if crop_dir.exists():
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for stale in crop_dir.glob("crop-*.jpg"):
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try:
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stale.unlink()
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except OSError:
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continue
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face_crops: list[dict[str, Any]] = []
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for index, box in enumerate(signal.face_boxes[:3], start=1):
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crops = build_face_crop_derivatives(original, [box])
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if not crops:
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continue
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try:
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crop_dir.mkdir(parents=True, exist_ok=True)
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crop_path = crop_dir / f"crop-{index}.jpg"
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crop_path.write_bytes(crops[0].content)
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except OSError:
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continue
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face_crops.append(
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{
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"index": index,
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"url": f"{self.face_crop_public_prefix}/{submission_id}/crop-{index}.jpg",
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"box": [int(value) for value in box],
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}
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)
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submission = self._get("submissions", submission_id)
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submission["faceCrops"] = face_crops
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self._put("submissions", submission_id, submission)
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def purge_expired_face_crops(self, *, now_epoch: float | None = None) -> int:
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# Delete biometric face-crop files older than the retention window and
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# drop their references from the owning submission, with an audit trail.
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retention_days = int(self.face_crop_retention_days)
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if retention_days <= 0 or not self.face_crop_image_dir.exists():
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return 0
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now = now_epoch if now_epoch is not None else datetime.now().timestamp()
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cutoff = now - retention_days * 86400
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purged = 0
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with self._write_lock:
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for crop_dir in sorted(p for p in self.face_crop_image_dir.iterdir() if p.is_dir()):
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submission_id = crop_dir.name
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removed: list[str] = []
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for crop_file in crop_dir.glob("crop-*.jpg"):
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try:
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if crop_file.stat().st_mtime >= cutoff:
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continue
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crop_file.unlink()
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except OSError:
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continue
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removed.append(crop_file.name)
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purged += 1
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if not removed:
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continue
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change = f"retention {retention_days}d: removed {len(removed)} biometric crop(s)"
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try:
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submission = self._get("submissions", submission_id)
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except KeyError:
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self.add_audit_event("system", "Face crop purged", submission_id, change)
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continue
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remaining = [
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crop
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for crop in submission.get("faceCrops", [])
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if f"crop-{crop.get('index')}.jpg" not in removed
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]
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with self._transaction() as conn:
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submission["faceCrops"] = remaining
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self._put("submissions", submission_id, submission, conn=conn)
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self.add_audit_event("system", "Face crop purged", submission_id, change, conn=conn)
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return purged
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def _refresh_existing_submission_file_facts(
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self,
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image_store: LocalSubmissionImageStore,
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*,
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queue_id: str,
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) -> None:
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existing_submission_ids = {submission["id"] for submission in self._all("submissions", queue_id=queue_id)}
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for record in image_store.submission_records():
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submission_id = str(record["id"])
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if submission_id not in existing_submission_ids:
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continue
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submission = self._get("submissions", submission_id)
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submission["asset"] = record["asset"]
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submission["fileFacts"] = {
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**submission.get("fileFacts", {}),
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"size": f"{record.get('width', 1)} x {record.get('height', 1)}",
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"format": record.get("format", "FILE"),
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}
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self._put("submissions", submission_id, submission)
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def _rerun_internal_analysis(
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self,
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submission_id: str,
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image_store: LocalSubmissionImageStore,
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) -> list[Evidence]:
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repository = self._knowledge_repository()
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analyzer = InternalAnalyzer(
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repository,
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FingerprintService(),
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HeuristicFacePersonDetector(),
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)
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domain_evidence = analyzer.analyze(
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submission_id,
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image_store.image_payload(submission_id),
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)
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for item in domain_evidence:
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payload = _evidence_payload(submission_id, item)
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payload["status"] = "rerun"
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self._put("evidence", payload["id"], payload)
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self._sync_similar_reference_images(submission_id, domain_evidence)
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self._increment_knowledge_contribution_counts(submission_id, domain_evidence)
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self._rescore_submission(submission_id)
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self._sync_face_crops(submission_id, image_store)
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return domain_evidence
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def _rerun_google_image_search(
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self,
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submission_id: str,
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image_store: LocalSubmissionImageStore,
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) -> list[Evidence]:
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if self.provider_runtime.google_adapter is None:
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return []
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original_image = image_store.image_payload(submission_id)
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derivative = build_external_derivative(original_image)
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domain_evidence = self.provider_runtime.google_adapter.detect(
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submission_id,
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derivative,
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self.provider_runtime.external_policy,
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)
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call_count = 1
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face_crop_evidence, face_crop_calls = self._google_face_crop_web_detection(
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submission_id,
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original_image,
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)
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call_count += face_crop_calls
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domain_evidence.extend(face_crop_evidence)
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for item in domain_evidence:
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payload = _evidence_payload(submission_id, item)
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payload["status"] = "rerun" if payload["status"] == "active" else payload["status"]
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self._put("evidence", payload["id"], payload)
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self._sync_search_result_image_similarity(
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submission_id,
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domain_evidence,
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image_store,
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status="rerun",
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)
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google_provider = self._get("providers", "google")
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if any(
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item.source in {EvidenceSource.FAILURE, EvidenceSource.EXTERNAL_SKIPPED}
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for item in domain_evidence
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):
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google_provider["lastFailure"] = domain_evidence[0].reason if domain_evidence else "Google image search failed"
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else:
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google_provider["lastSuccess"] = _now_label()
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google_provider["lastFailure"] = "없음"
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self._apply_provider_usage_delta("google", call_count, google_provider)
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self.add_audit_event(
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"rights.ops",
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"Provider called",
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f"google / {submission_id}",
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"image web detection rerun",
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)
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self._rescore_submission(submission_id)
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return domain_evidence
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def _google_face_crop_web_detection(
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self,
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submission_id: str,
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original_image: Any,
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) -> tuple[list[Evidence], int]:
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if self.provider_runtime.google_adapter is None:
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return [], 0
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if not self.provider_runtime.face_crop_web_detection_enabled:
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return [], 0
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submission = self._get("submissions", submission_id)
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stored_crops = submission.get("faceCrops")
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if stored_crops is None:
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signal = HeuristicFacePersonDetector().detect(original_image)
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indexed_boxes = [
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(index, box)
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for index, box in enumerate(signal.face_boxes[:3], start=1)
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]
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else:
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# 저장된 faceCrops의 index를 그대로 사용해 증거의 crop_index가
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# 워크벤치 썸네일 번호와 항상 일치하게 한다(중간 박스 크롭 실패 시
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# 재열거하면 번호가 어긋난다).
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indexed_boxes = [
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(int(item.get("index", 0)), tuple(int(value) for value in item.get("box", [])))
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for item in stored_crops
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if len(item.get("box", [])) == 4
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]
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if not indexed_boxes:
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return [], 0
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evidence: list[Evidence] = []
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call_count = 0
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for crop_index, box in indexed_boxes:
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crops = build_face_crop_derivatives(original_image, [box])
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if not crops:
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continue
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crop = crops[0]
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call_count += 1
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crop_evidence = self.provider_runtime.google_adapter.detect(
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f"{submission_id}:face-crop-{crop_index}",
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crop,
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self.provider_runtime.external_policy,
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)
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for item in crop_evidence:
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face_web_evidence = _face_crop_web_evidence(submission_id, crop_index, item)
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evidence.append(face_web_evidence)
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crop_matches = self._face_crop_search_result_similarity_evidence(
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submission_id,
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crop_index,
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crop,
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face_web_evidence,
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)
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if crop_matches:
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evidence.extend(crop_matches)
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if call_count:
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# Governance: personal (biometric) images left the system to a
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# third-party API. The external call itself is permitted, but the
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# transmission must be auditable.
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self.add_audit_event(
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"system",
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"Personal image sent to external provider",
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submission_id,
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f"{call_count} face crop(s) -> Google Vision web detection",
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)
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return evidence, call_count
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def _auto_google_custom_search(
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self,
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submission_id: str,
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source_evidence: list[Evidence],
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image_store: LocalSubmissionImageStore | None = None,
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) -> None:
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if self.provider_runtime.google_custom_search_adapter is None:
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return
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if self.provider_runtime.auto_google_custom_query_limit <= 0:
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return
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query_plan = SearchQueryGenerator().plan(
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source_evidence,
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[],
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max_queries=self.provider_runtime.auto_google_custom_query_limit,
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)
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if not query_plan:
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return
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existing_signatures = _existing_google_custom_query_signatures(
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self._evidence_by_submission().get(submission_id, [])
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)
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can_compare_search_images = self._can_compare_search_result_images(
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submission_id,
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image_store,
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)
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all_domain_evidence: list[Evidence] = []
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history_entries: list[dict[str, Any]] = []
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external_call_count = 0
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for planned in query_plan:
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query = planned.query
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image_signature = _google_custom_image_query_signature(query)
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if image_signature in existing_signatures:
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continue
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existing_signatures.add(image_signature)
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image_evidence = self.provider_runtime.google_custom_search_adapter.search_images(
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submission_id,
|
||||
query,
|
||||
self.provider_runtime.google_custom_search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in image_evidence):
|
||||
external_call_count += 1
|
||||
image_evidence = [
|
||||
replace(
|
||||
item,
|
||||
data={
|
||||
**item.data,
|
||||
"query_strategy": planned.strategy,
|
||||
"query_source": planned.source,
|
||||
"query_priority": planned.priority,
|
||||
},
|
||||
)
|
||||
for item in image_evidence
|
||||
]
|
||||
all_domain_evidence.extend(image_evidence)
|
||||
for item in image_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "auto" if payload["status"] == "active" else payload["status"]
|
||||
self._put("evidence", payload["id"], payload)
|
||||
|
||||
similarity_evidence: list[Evidence] = []
|
||||
remaining_matches = self._search_result_similarity_remaining_budget(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
if can_compare_search_images and remaining_matches > 0:
|
||||
similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
image_evidence,
|
||||
image_store,
|
||||
status="auto",
|
||||
max_matches=remaining_matches,
|
||||
)
|
||||
all_domain_evidence.extend(similarity_evidence)
|
||||
|
||||
history_entries.append(
|
||||
{
|
||||
"provider": "google_search",
|
||||
"query": query,
|
||||
"status": _query_history_status(image_evidence),
|
||||
"strategy": planned.strategy,
|
||||
"source": planned.source,
|
||||
"timestamp": _now_label(),
|
||||
"count": len(image_evidence),
|
||||
}
|
||||
)
|
||||
|
||||
web_signature = _google_custom_web_query_signature(query)
|
||||
if web_signature in existing_signatures:
|
||||
continue
|
||||
existing_signatures.add(web_signature)
|
||||
|
||||
web_evidence = self.provider_runtime.google_custom_search_adapter.search_web_pages(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.google_custom_search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in web_evidence):
|
||||
external_call_count += 1
|
||||
web_evidence = [
|
||||
replace(
|
||||
item,
|
||||
data={
|
||||
**item.data,
|
||||
"query_strategy": planned.strategy,
|
||||
"query_source": planned.source,
|
||||
"query_priority": planned.priority,
|
||||
},
|
||||
)
|
||||
for item in web_evidence
|
||||
]
|
||||
all_domain_evidence.extend(web_evidence)
|
||||
for item in web_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "auto" if payload["status"] == "active" else payload["status"]
|
||||
self._put("evidence", payload["id"], payload)
|
||||
all_domain_evidence.extend(
|
||||
self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
web_evidence,
|
||||
image_store,
|
||||
status="auto",
|
||||
max_matches=self._search_result_similarity_remaining_budget(
|
||||
submission_id,
|
||||
image_store,
|
||||
),
|
||||
)
|
||||
)
|
||||
history_entries.append(
|
||||
{
|
||||
"provider": "google_search",
|
||||
"query": query,
|
||||
"status": _query_history_status(web_evidence),
|
||||
"strategy": planned.strategy,
|
||||
"source": planned.source,
|
||||
"timestamp": _now_label(),
|
||||
"count": len(web_evidence),
|
||||
}
|
||||
)
|
||||
|
||||
if not history_entries:
|
||||
return
|
||||
|
||||
submission = self._get("submissions", submission_id)
|
||||
submission["queryHistory"] = [*history_entries, *submission.get("queryHistory", [])]
|
||||
self._put("submissions", submission_id, submission)
|
||||
|
||||
google_search_provider = self._get("providers", "google_search")
|
||||
if any(
|
||||
item.source in {EvidenceSource.SEARCH_SKIPPED, EvidenceSource.ENRICHMENT_FAILURE}
|
||||
for item in all_domain_evidence
|
||||
):
|
||||
google_search_provider["lastFailure"] = all_domain_evidence[0].reason if all_domain_evidence else "Google custom search failed"
|
||||
else:
|
||||
google_search_provider["lastSuccess"] = _now_label()
|
||||
google_search_provider["lastFailure"] = "없음"
|
||||
self._apply_provider_usage_delta("google_search", external_call_count, google_search_provider)
|
||||
self.add_audit_event(
|
||||
"system",
|
||||
"Provider called",
|
||||
f"google_search / {submission_id}",
|
||||
f"auto custom search query batch: {', '.join(item['query'] for item in history_entries)}",
|
||||
)
|
||||
|
||||
def _auto_naver_search(
|
||||
self,
|
||||
submission_id: str,
|
||||
source_evidence: list[Evidence],
|
||||
image_store: LocalSubmissionImageStore | None = None,
|
||||
) -> None:
|
||||
if self.provider_runtime.naver_adapter is None:
|
||||
return
|
||||
if self.provider_runtime.auto_naver_query_limit <= 0:
|
||||
return
|
||||
|
||||
query_plan = SearchQueryGenerator().plan(
|
||||
source_evidence,
|
||||
[],
|
||||
max_queries=self.provider_runtime.auto_naver_query_limit,
|
||||
)
|
||||
if not query_plan:
|
||||
return
|
||||
|
||||
existing_signatures = _existing_naver_query_signatures(
|
||||
self._evidence_by_submission().get(submission_id, [])
|
||||
)
|
||||
can_compare_search_images = self._can_compare_search_result_images(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
all_domain_evidence: list[Evidence] = []
|
||||
history_entries: list[dict[str, Any]] = []
|
||||
external_call_count = 0
|
||||
blog_query_count = 0
|
||||
web_query_count = 0
|
||||
promoter = SearchResultPromoter()
|
||||
|
||||
for planned in query_plan:
|
||||
query = planned.query
|
||||
signature = _naver_query_signature(query)
|
||||
if signature in existing_signatures:
|
||||
continue
|
||||
existing_signatures.add(signature)
|
||||
|
||||
domain_evidence = self.provider_runtime.naver_adapter.search(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in domain_evidence):
|
||||
external_call_count += 1
|
||||
domain_evidence = [
|
||||
replace(
|
||||
item,
|
||||
data={
|
||||
**item.data,
|
||||
"query_strategy": planned.strategy,
|
||||
"query_source": planned.source,
|
||||
"query_priority": planned.priority,
|
||||
},
|
||||
)
|
||||
for item in domain_evidence
|
||||
]
|
||||
domain_evidence = promoter.promote(domain_evidence)
|
||||
all_domain_evidence.extend(domain_evidence)
|
||||
for item in domain_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "auto" if payload["status"] == "active" else payload["status"]
|
||||
self._put("evidence", payload["id"], payload)
|
||||
similarity_evidence: list[Evidence] = []
|
||||
remaining_matches = self._search_result_similarity_remaining_budget(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
if can_compare_search_images and remaining_matches > 0:
|
||||
similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
domain_evidence,
|
||||
image_store,
|
||||
status="auto",
|
||||
max_matches=remaining_matches,
|
||||
)
|
||||
all_domain_evidence.extend(similarity_evidence)
|
||||
|
||||
history_entries.append(
|
||||
{
|
||||
"provider": "naver",
|
||||
"query": query,
|
||||
"status": _query_history_status(domain_evidence),
|
||||
"strategy": planned.strategy,
|
||||
"source": planned.source,
|
||||
"timestamp": _now_label(),
|
||||
"count": len(domain_evidence),
|
||||
}
|
||||
)
|
||||
|
||||
page_similarity_evidence: list[Evidence] = []
|
||||
remaining_matches = self._search_result_similarity_remaining_budget(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
if blog_query_count < self.provider_runtime.auto_naver_blog_query_limit:
|
||||
blog_signature = _naver_blog_query_signature(query)
|
||||
if blog_signature in existing_signatures:
|
||||
continue
|
||||
existing_signatures.add(blog_signature)
|
||||
blog_query_count += 1
|
||||
|
||||
page_evidence = self.provider_runtime.naver_adapter.search_pages(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in page_evidence):
|
||||
external_call_count += 1
|
||||
page_evidence = [
|
||||
replace(
|
||||
item,
|
||||
data={
|
||||
**item.data,
|
||||
"query_strategy": planned.strategy,
|
||||
"query_source": planned.source,
|
||||
"query_priority": planned.priority,
|
||||
},
|
||||
)
|
||||
for item in page_evidence
|
||||
]
|
||||
page_evidence = promoter.promote(page_evidence)
|
||||
all_domain_evidence.extend(page_evidence)
|
||||
for item in page_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "auto" if payload["status"] == "active" else payload["status"]
|
||||
self._put("evidence", payload["id"], payload)
|
||||
page_similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
page_evidence,
|
||||
image_store,
|
||||
status="auto",
|
||||
max_matches=remaining_matches if can_compare_search_images else 0,
|
||||
)
|
||||
all_domain_evidence.extend(page_similarity_evidence)
|
||||
history_entries.append(
|
||||
{
|
||||
"provider": "naver_blog",
|
||||
"query": query,
|
||||
"status": _query_history_status(page_evidence),
|
||||
"strategy": planned.strategy,
|
||||
"source": planned.source,
|
||||
"timestamp": _now_label(),
|
||||
"count": len(page_evidence),
|
||||
}
|
||||
)
|
||||
|
||||
if web_query_count < self.provider_runtime.auto_naver_web_query_limit:
|
||||
web_signature = _naver_web_query_signature(query)
|
||||
if web_signature in existing_signatures:
|
||||
continue
|
||||
existing_signatures.add(web_signature)
|
||||
web_query_count += 1
|
||||
|
||||
web_evidence = self.provider_runtime.naver_adapter.search_web_pages(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in web_evidence):
|
||||
external_call_count += 1
|
||||
web_evidence = [
|
||||
replace(
|
||||
item,
|
||||
data={
|
||||
**item.data,
|
||||
"query_strategy": planned.strategy,
|
||||
"query_source": planned.source,
|
||||
"query_priority": planned.priority,
|
||||
},
|
||||
)
|
||||
for item in web_evidence
|
||||
]
|
||||
web_evidence = promoter.promote(web_evidence)
|
||||
all_domain_evidence.extend(web_evidence)
|
||||
for item in web_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "auto" if payload["status"] == "active" else payload["status"]
|
||||
self._put("evidence", payload["id"], payload)
|
||||
all_domain_evidence.extend(
|
||||
self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
web_evidence,
|
||||
image_store,
|
||||
status="auto",
|
||||
max_matches=(
|
||||
self._search_result_similarity_remaining_budget(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
if can_compare_search_images
|
||||
else 0
|
||||
),
|
||||
)
|
||||
)
|
||||
history_entries.append(
|
||||
{
|
||||
"provider": "naver_web",
|
||||
"query": query,
|
||||
"status": _query_history_status(web_evidence),
|
||||
"strategy": planned.strategy,
|
||||
"source": planned.source,
|
||||
"timestamp": _now_label(),
|
||||
"count": len(web_evidence),
|
||||
}
|
||||
)
|
||||
|
||||
if not history_entries:
|
||||
return
|
||||
|
||||
submission = self._get("submissions", submission_id)
|
||||
submission["queryHistory"] = [*history_entries, *submission.get("queryHistory", [])]
|
||||
self._put("submissions", submission_id, submission)
|
||||
|
||||
naver_provider = self._get("providers", "naver")
|
||||
if any(
|
||||
item.source in {EvidenceSource.SEARCH_SKIPPED, EvidenceSource.ENRICHMENT_FAILURE}
|
||||
for item in all_domain_evidence
|
||||
):
|
||||
naver_provider["lastFailure"] = all_domain_evidence[0].reason if all_domain_evidence else "Naver search failed"
|
||||
else:
|
||||
naver_provider["lastSuccess"] = _now_label()
|
||||
naver_provider["lastFailure"] = "없음"
|
||||
self._apply_provider_usage_delta("naver", external_call_count, naver_provider)
|
||||
self.add_audit_event(
|
||||
"system",
|
||||
"Provider called",
|
||||
f"naver / {submission_id}",
|
||||
f"auto text query batch: {', '.join(item['query'] for item in history_entries)}",
|
||||
)
|
||||
|
||||
|
|
|
|||
789
src/rights_filter/server/store_enrichment.py
Normal file
789
src/rights_filter/server/store_enrichment.py
Normal file
|
|
@ -0,0 +1,789 @@
|
|||
"""Enrichment internals for CopyrighterStore, as a mixin.
|
||||
|
||||
Provider-state sync, local face evidence/crop sync + retention, internal/Google
|
||||
re-analysis, face-crop web detection, and the auto Google/Naver search drivers.
|
||||
Mixed into CopyrighterStore; relies on persistence methods, self.* attributes
|
||||
(provider_runtime, image dirs, fetchers, _write_lock), and self.add_audit_event /
|
||||
rescoring provided by the host class. Behavior unchanged.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from dataclasses import replace
|
||||
from datetime import datetime
|
||||
from typing import Any
|
||||
|
||||
from rights_filter.analysis.face_person_detection import HeuristicFacePersonDetector
|
||||
from rights_filter.analysis.fingerprints import FingerprintService
|
||||
from rights_filter.analysis.internal_analyzer import InternalAnalyzer
|
||||
from rights_filter.analysis.preprocessing import build_external_derivative, build_face_crop_derivatives
|
||||
from rights_filter.analysis.search_query_generation import SearchQueryGenerator
|
||||
from rights_filter.analysis.search_result_promoter import SearchResultPromoter
|
||||
from rights_filter.domain.records import Evidence, EvidenceSource
|
||||
from rights_filter.server.image_store import LocalSubmissionImageStore
|
||||
from rights_filter.server.store_serialization import (
|
||||
_evidence_id,
|
||||
_evidence_payload,
|
||||
_existing_google_custom_query_signatures,
|
||||
_existing_naver_query_signatures,
|
||||
_external_provider_ids,
|
||||
_external_provider_state_for_submission,
|
||||
_face_crop_web_evidence,
|
||||
_google_custom_image_query_signature,
|
||||
_google_custom_web_query_signature,
|
||||
_google_weak_label_title,
|
||||
_is_google_weak_label_payload,
|
||||
_naver_blog_query_signature,
|
||||
_naver_query_signature,
|
||||
_naver_web_query_signature,
|
||||
_now_label,
|
||||
_query_history_status,
|
||||
)
|
||||
|
||||
|
||||
class StoreEnrichmentMixin:
|
||||
def _sync_provider_payloads(self) -> None:
|
||||
existing = {provider["id"]: provider for provider in self._all("providers")}
|
||||
for provider_id, payload in self.provider_runtime.provider_payloads.items():
|
||||
merged = {
|
||||
**payload,
|
||||
"usage": existing.get(provider_id, {}).get("usage", payload["usage"]),
|
||||
}
|
||||
self._put("providers", provider_id, merged)
|
||||
self._sync_submission_provider_state()
|
||||
|
||||
def _sync_submission_provider_state(self, queue_id: str | None = None) -> None:
|
||||
provider_payloads = {provider["id"]: provider for provider in self._all("providers")}
|
||||
evidence_by_submission = self._evidence_by_submission(queue_id=queue_id)
|
||||
for submission in self._all("submissions", queue_id=queue_id):
|
||||
provider_state = submission.get("providerState", {})
|
||||
evidence = evidence_by_submission.get(str(submission["id"]), [])
|
||||
provider_state["internal"] = "ok"
|
||||
for provider_id in _external_provider_ids(provider_payloads):
|
||||
provider_state[provider_id] = _external_provider_state_for_submission(
|
||||
provider_payloads,
|
||||
provider_id,
|
||||
submission,
|
||||
evidence,
|
||||
)
|
||||
submission["providerState"] = provider_state
|
||||
self._put("submissions", submission["id"], submission)
|
||||
|
||||
def _normalize_saved_google_weak_labels_and_rescore(self, queue_id: str | None = None) -> None:
|
||||
changed_submissions: set[str] = set()
|
||||
with self._connect() as conn:
|
||||
rows = conn.execute(
|
||||
"""
|
||||
select id, submission_id, payload
|
||||
from evidence
|
||||
""".strip() + (
|
||||
" where submission_id in (select id from submissions where queue_id = ?)"
|
||||
if queue_id is not None
|
||||
else ""
|
||||
),
|
||||
(queue_id,) if queue_id is not None else (),
|
||||
).fetchall()
|
||||
|
||||
for row in rows:
|
||||
payload = json.loads(row["payload"])
|
||||
if _is_google_weak_label_payload(payload):
|
||||
payload["title"] = _google_weak_label_title(str(payload.get("title", "")))
|
||||
payload["confidence"] = 0.0
|
||||
payload["contributed"] = False
|
||||
payload["status"] = "weak"
|
||||
self._put("evidence", row["id"], payload)
|
||||
changed_submissions.add(str(row["submission_id"]))
|
||||
|
||||
for submission_id in changed_submissions:
|
||||
self._rescore_submission(submission_id)
|
||||
|
||||
def _refresh_existing_local_face_evidence(
|
||||
self,
|
||||
image_store: LocalSubmissionImageStore,
|
||||
*,
|
||||
queue_id: str,
|
||||
) -> None:
|
||||
existing_submission_ids = {submission["id"] for submission in self._all("submissions", queue_id=queue_id)}
|
||||
if not existing_submission_ids:
|
||||
return
|
||||
|
||||
evidence_by_submission = self._evidence_by_submission(queue_id=queue_id)
|
||||
detector = HeuristicFacePersonDetector()
|
||||
for record in image_store.submission_records():
|
||||
submission_id = str(record["id"])
|
||||
if submission_id not in existing_submission_ids:
|
||||
continue
|
||||
if any(
|
||||
item.get("source") == "face"
|
||||
for item in evidence_by_submission.get(submission_id, [])
|
||||
):
|
||||
continue
|
||||
|
||||
signal = detector.detect(image_store.image_payload(submission_id))
|
||||
if not signal.present:
|
||||
continue
|
||||
|
||||
evidence = Evidence(
|
||||
source=EvidenceSource.FACE_PERSON,
|
||||
reason="Face/person detected",
|
||||
confidence=0.8,
|
||||
data={
|
||||
"face_count": signal.face_count,
|
||||
"person_count": signal.person_count,
|
||||
},
|
||||
)
|
||||
self._put(
|
||||
"evidence",
|
||||
_evidence_id(submission_id, evidence),
|
||||
_evidence_payload(submission_id, evidence),
|
||||
)
|
||||
self._rescore_submission(submission_id)
|
||||
|
||||
def _sync_face_crops(
|
||||
self,
|
||||
submission_id: str,
|
||||
image_store: LocalSubmissionImageStore | None,
|
||||
) -> None:
|
||||
if image_store is None:
|
||||
return
|
||||
try:
|
||||
original = image_store.image_payload(submission_id)
|
||||
except Exception:
|
||||
return
|
||||
|
||||
signal = HeuristicFacePersonDetector().detect(original)
|
||||
crop_dir = self.face_crop_image_dir / submission_id
|
||||
if crop_dir.exists():
|
||||
for stale in crop_dir.glob("crop-*.jpg"):
|
||||
try:
|
||||
stale.unlink()
|
||||
except OSError:
|
||||
continue
|
||||
|
||||
face_crops: list[dict[str, Any]] = []
|
||||
for index, box in enumerate(signal.face_boxes[:3], start=1):
|
||||
crops = build_face_crop_derivatives(original, [box])
|
||||
if not crops:
|
||||
continue
|
||||
try:
|
||||
crop_dir.mkdir(parents=True, exist_ok=True)
|
||||
crop_path = crop_dir / f"crop-{index}.jpg"
|
||||
crop_path.write_bytes(crops[0].content)
|
||||
except OSError:
|
||||
continue
|
||||
face_crops.append(
|
||||
{
|
||||
"index": index,
|
||||
"url": f"{self.face_crop_public_prefix}/{submission_id}/crop-{index}.jpg",
|
||||
"box": [int(value) for value in box],
|
||||
}
|
||||
)
|
||||
|
||||
submission = self._get("submissions", submission_id)
|
||||
submission["faceCrops"] = face_crops
|
||||
self._put("submissions", submission_id, submission)
|
||||
|
||||
def purge_expired_face_crops(self, *, now_epoch: float | None = None) -> int:
|
||||
# Delete biometric face-crop files older than the retention window and
|
||||
# drop their references from the owning submission, with an audit trail.
|
||||
retention_days = int(self.face_crop_retention_days)
|
||||
if retention_days <= 0 or not self.face_crop_image_dir.exists():
|
||||
return 0
|
||||
now = now_epoch if now_epoch is not None else datetime.now().timestamp()
|
||||
cutoff = now - retention_days * 86400
|
||||
purged = 0
|
||||
with self._write_lock:
|
||||
for crop_dir in sorted(p for p in self.face_crop_image_dir.iterdir() if p.is_dir()):
|
||||
submission_id = crop_dir.name
|
||||
removed: list[str] = []
|
||||
for crop_file in crop_dir.glob("crop-*.jpg"):
|
||||
try:
|
||||
if crop_file.stat().st_mtime >= cutoff:
|
||||
continue
|
||||
crop_file.unlink()
|
||||
except OSError:
|
||||
continue
|
||||
removed.append(crop_file.name)
|
||||
purged += 1
|
||||
if not removed:
|
||||
continue
|
||||
change = f"retention {retention_days}d: removed {len(removed)} biometric crop(s)"
|
||||
try:
|
||||
submission = self._get("submissions", submission_id)
|
||||
except KeyError:
|
||||
self.add_audit_event("system", "Face crop purged", submission_id, change)
|
||||
continue
|
||||
remaining = [
|
||||
crop
|
||||
for crop in submission.get("faceCrops", [])
|
||||
if f"crop-{crop.get('index')}.jpg" not in removed
|
||||
]
|
||||
with self._transaction() as conn:
|
||||
submission["faceCrops"] = remaining
|
||||
self._put("submissions", submission_id, submission, conn=conn)
|
||||
self.add_audit_event("system", "Face crop purged", submission_id, change, conn=conn)
|
||||
return purged
|
||||
|
||||
def _refresh_existing_submission_file_facts(
|
||||
self,
|
||||
image_store: LocalSubmissionImageStore,
|
||||
*,
|
||||
queue_id: str,
|
||||
) -> None:
|
||||
existing_submission_ids = {submission["id"] for submission in self._all("submissions", queue_id=queue_id)}
|
||||
for record in image_store.submission_records():
|
||||
submission_id = str(record["id"])
|
||||
if submission_id not in existing_submission_ids:
|
||||
continue
|
||||
submission = self._get("submissions", submission_id)
|
||||
submission["asset"] = record["asset"]
|
||||
submission["fileFacts"] = {
|
||||
**submission.get("fileFacts", {}),
|
||||
"size": f"{record.get('width', 1)} x {record.get('height', 1)}",
|
||||
"format": record.get("format", "FILE"),
|
||||
}
|
||||
self._put("submissions", submission_id, submission)
|
||||
|
||||
def _rerun_internal_analysis(
|
||||
self,
|
||||
submission_id: str,
|
||||
image_store: LocalSubmissionImageStore,
|
||||
) -> list[Evidence]:
|
||||
repository = self._knowledge_repository()
|
||||
analyzer = InternalAnalyzer(
|
||||
repository,
|
||||
FingerprintService(),
|
||||
HeuristicFacePersonDetector(),
|
||||
)
|
||||
domain_evidence = analyzer.analyze(
|
||||
submission_id,
|
||||
image_store.image_payload(submission_id),
|
||||
)
|
||||
for item in domain_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "rerun"
|
||||
self._put("evidence", payload["id"], payload)
|
||||
self._sync_similar_reference_images(submission_id, domain_evidence)
|
||||
self._increment_knowledge_contribution_counts(submission_id, domain_evidence)
|
||||
self._rescore_submission(submission_id)
|
||||
self._sync_face_crops(submission_id, image_store)
|
||||
return domain_evidence
|
||||
|
||||
def _rerun_google_image_search(
|
||||
self,
|
||||
submission_id: str,
|
||||
image_store: LocalSubmissionImageStore,
|
||||
) -> list[Evidence]:
|
||||
if self.provider_runtime.google_adapter is None:
|
||||
return []
|
||||
|
||||
original_image = image_store.image_payload(submission_id)
|
||||
derivative = build_external_derivative(original_image)
|
||||
domain_evidence = self.provider_runtime.google_adapter.detect(
|
||||
submission_id,
|
||||
derivative,
|
||||
self.provider_runtime.external_policy,
|
||||
)
|
||||
call_count = 1
|
||||
face_crop_evidence, face_crop_calls = self._google_face_crop_web_detection(
|
||||
submission_id,
|
||||
original_image,
|
||||
)
|
||||
call_count += face_crop_calls
|
||||
domain_evidence.extend(face_crop_evidence)
|
||||
for item in domain_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "rerun" if payload["status"] == "active" else payload["status"]
|
||||
self._put("evidence", payload["id"], payload)
|
||||
self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
domain_evidence,
|
||||
image_store,
|
||||
status="rerun",
|
||||
)
|
||||
|
||||
google_provider = self._get("providers", "google")
|
||||
if any(
|
||||
item.source in {EvidenceSource.FAILURE, EvidenceSource.EXTERNAL_SKIPPED}
|
||||
for item in domain_evidence
|
||||
):
|
||||
google_provider["lastFailure"] = domain_evidence[0].reason if domain_evidence else "Google image search failed"
|
||||
else:
|
||||
google_provider["lastSuccess"] = _now_label()
|
||||
google_provider["lastFailure"] = "없음"
|
||||
self._apply_provider_usage_delta("google", call_count, google_provider)
|
||||
self.add_audit_event(
|
||||
"rights.ops",
|
||||
"Provider called",
|
||||
f"google / {submission_id}",
|
||||
"image web detection rerun",
|
||||
)
|
||||
self._rescore_submission(submission_id)
|
||||
return domain_evidence
|
||||
|
||||
def _google_face_crop_web_detection(
|
||||
self,
|
||||
submission_id: str,
|
||||
original_image: Any,
|
||||
) -> tuple[list[Evidence], int]:
|
||||
if self.provider_runtime.google_adapter is None:
|
||||
return [], 0
|
||||
if not self.provider_runtime.face_crop_web_detection_enabled:
|
||||
return [], 0
|
||||
|
||||
submission = self._get("submissions", submission_id)
|
||||
stored_crops = submission.get("faceCrops")
|
||||
if stored_crops is None:
|
||||
signal = HeuristicFacePersonDetector().detect(original_image)
|
||||
indexed_boxes = [
|
||||
(index, box)
|
||||
for index, box in enumerate(signal.face_boxes[:3], start=1)
|
||||
]
|
||||
else:
|
||||
# 저장된 faceCrops의 index를 그대로 사용해 증거의 crop_index가
|
||||
# 워크벤치 썸네일 번호와 항상 일치하게 한다(중간 박스 크롭 실패 시
|
||||
# 재열거하면 번호가 어긋난다).
|
||||
indexed_boxes = [
|
||||
(int(item.get("index", 0)), tuple(int(value) for value in item.get("box", [])))
|
||||
for item in stored_crops
|
||||
if len(item.get("box", [])) == 4
|
||||
]
|
||||
if not indexed_boxes:
|
||||
return [], 0
|
||||
|
||||
evidence: list[Evidence] = []
|
||||
call_count = 0
|
||||
for crop_index, box in indexed_boxes:
|
||||
crops = build_face_crop_derivatives(original_image, [box])
|
||||
if not crops:
|
||||
continue
|
||||
crop = crops[0]
|
||||
call_count += 1
|
||||
crop_evidence = self.provider_runtime.google_adapter.detect(
|
||||
f"{submission_id}:face-crop-{crop_index}",
|
||||
crop,
|
||||
self.provider_runtime.external_policy,
|
||||
)
|
||||
for item in crop_evidence:
|
||||
face_web_evidence = _face_crop_web_evidence(submission_id, crop_index, item)
|
||||
evidence.append(face_web_evidence)
|
||||
crop_matches = self._face_crop_search_result_similarity_evidence(
|
||||
submission_id,
|
||||
crop_index,
|
||||
crop,
|
||||
face_web_evidence,
|
||||
)
|
||||
if crop_matches:
|
||||
evidence.extend(crop_matches)
|
||||
if call_count:
|
||||
# Governance: personal (biometric) images left the system to a
|
||||
# third-party API. The external call itself is permitted, but the
|
||||
# transmission must be auditable.
|
||||
self.add_audit_event(
|
||||
"system",
|
||||
"Personal image sent to external provider",
|
||||
submission_id,
|
||||
f"{call_count} face crop(s) -> Google Vision web detection",
|
||||
)
|
||||
return evidence, call_count
|
||||
|
||||
def _auto_google_custom_search(
|
||||
self,
|
||||
submission_id: str,
|
||||
source_evidence: list[Evidence],
|
||||
image_store: LocalSubmissionImageStore | None = None,
|
||||
) -> None:
|
||||
if self.provider_runtime.google_custom_search_adapter is None:
|
||||
return
|
||||
if self.provider_runtime.auto_google_custom_query_limit <= 0:
|
||||
return
|
||||
|
||||
query_plan = SearchQueryGenerator().plan(
|
||||
source_evidence,
|
||||
[],
|
||||
max_queries=self.provider_runtime.auto_google_custom_query_limit,
|
||||
)
|
||||
if not query_plan:
|
||||
return
|
||||
|
||||
existing_signatures = _existing_google_custom_query_signatures(
|
||||
self._evidence_by_submission().get(submission_id, [])
|
||||
)
|
||||
can_compare_search_images = self._can_compare_search_result_images(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
all_domain_evidence: list[Evidence] = []
|
||||
history_entries: list[dict[str, Any]] = []
|
||||
external_call_count = 0
|
||||
|
||||
for planned in query_plan:
|
||||
query = planned.query
|
||||
image_signature = _google_custom_image_query_signature(query)
|
||||
if image_signature in existing_signatures:
|
||||
continue
|
||||
existing_signatures.add(image_signature)
|
||||
|
||||
image_evidence = self.provider_runtime.google_custom_search_adapter.search_images(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.google_custom_search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in image_evidence):
|
||||
external_call_count += 1
|
||||
image_evidence = [
|
||||
replace(
|
||||
item,
|
||||
data={
|
||||
**item.data,
|
||||
"query_strategy": planned.strategy,
|
||||
"query_source": planned.source,
|
||||
"query_priority": planned.priority,
|
||||
},
|
||||
)
|
||||
for item in image_evidence
|
||||
]
|
||||
all_domain_evidence.extend(image_evidence)
|
||||
for item in image_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "auto" if payload["status"] == "active" else payload["status"]
|
||||
self._put("evidence", payload["id"], payload)
|
||||
|
||||
similarity_evidence: list[Evidence] = []
|
||||
remaining_matches = self._search_result_similarity_remaining_budget(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
if can_compare_search_images and remaining_matches > 0:
|
||||
similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
image_evidence,
|
||||
image_store,
|
||||
status="auto",
|
||||
max_matches=remaining_matches,
|
||||
)
|
||||
all_domain_evidence.extend(similarity_evidence)
|
||||
|
||||
history_entries.append(
|
||||
{
|
||||
"provider": "google_search",
|
||||
"query": query,
|
||||
"status": _query_history_status(image_evidence),
|
||||
"strategy": planned.strategy,
|
||||
"source": planned.source,
|
||||
"timestamp": _now_label(),
|
||||
"count": len(image_evidence),
|
||||
}
|
||||
)
|
||||
|
||||
web_signature = _google_custom_web_query_signature(query)
|
||||
if web_signature in existing_signatures:
|
||||
continue
|
||||
existing_signatures.add(web_signature)
|
||||
|
||||
web_evidence = self.provider_runtime.google_custom_search_adapter.search_web_pages(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.google_custom_search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in web_evidence):
|
||||
external_call_count += 1
|
||||
web_evidence = [
|
||||
replace(
|
||||
item,
|
||||
data={
|
||||
**item.data,
|
||||
"query_strategy": planned.strategy,
|
||||
"query_source": planned.source,
|
||||
"query_priority": planned.priority,
|
||||
},
|
||||
)
|
||||
for item in web_evidence
|
||||
]
|
||||
all_domain_evidence.extend(web_evidence)
|
||||
for item in web_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "auto" if payload["status"] == "active" else payload["status"]
|
||||
self._put("evidence", payload["id"], payload)
|
||||
all_domain_evidence.extend(
|
||||
self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
web_evidence,
|
||||
image_store,
|
||||
status="auto",
|
||||
max_matches=self._search_result_similarity_remaining_budget(
|
||||
submission_id,
|
||||
image_store,
|
||||
),
|
||||
)
|
||||
)
|
||||
history_entries.append(
|
||||
{
|
||||
"provider": "google_search",
|
||||
"query": query,
|
||||
"status": _query_history_status(web_evidence),
|
||||
"strategy": planned.strategy,
|
||||
"source": planned.source,
|
||||
"timestamp": _now_label(),
|
||||
"count": len(web_evidence),
|
||||
}
|
||||
)
|
||||
|
||||
if not history_entries:
|
||||
return
|
||||
|
||||
submission = self._get("submissions", submission_id)
|
||||
submission["queryHistory"] = [*history_entries, *submission.get("queryHistory", [])]
|
||||
self._put("submissions", submission_id, submission)
|
||||
|
||||
google_search_provider = self._get("providers", "google_search")
|
||||
if any(
|
||||
item.source in {EvidenceSource.SEARCH_SKIPPED, EvidenceSource.ENRICHMENT_FAILURE}
|
||||
for item in all_domain_evidence
|
||||
):
|
||||
google_search_provider["lastFailure"] = all_domain_evidence[0].reason if all_domain_evidence else "Google custom search failed"
|
||||
else:
|
||||
google_search_provider["lastSuccess"] = _now_label()
|
||||
google_search_provider["lastFailure"] = "없음"
|
||||
self._apply_provider_usage_delta("google_search", external_call_count, google_search_provider)
|
||||
self.add_audit_event(
|
||||
"system",
|
||||
"Provider called",
|
||||
f"google_search / {submission_id}",
|
||||
f"auto custom search query batch: {', '.join(item['query'] for item in history_entries)}",
|
||||
)
|
||||
|
||||
def _auto_naver_search(
|
||||
self,
|
||||
submission_id: str,
|
||||
source_evidence: list[Evidence],
|
||||
image_store: LocalSubmissionImageStore | None = None,
|
||||
) -> None:
|
||||
if self.provider_runtime.naver_adapter is None:
|
||||
return
|
||||
if self.provider_runtime.auto_naver_query_limit <= 0:
|
||||
return
|
||||
|
||||
query_plan = SearchQueryGenerator().plan(
|
||||
source_evidence,
|
||||
[],
|
||||
max_queries=self.provider_runtime.auto_naver_query_limit,
|
||||
)
|
||||
if not query_plan:
|
||||
return
|
||||
|
||||
existing_signatures = _existing_naver_query_signatures(
|
||||
self._evidence_by_submission().get(submission_id, [])
|
||||
)
|
||||
can_compare_search_images = self._can_compare_search_result_images(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
all_domain_evidence: list[Evidence] = []
|
||||
history_entries: list[dict[str, Any]] = []
|
||||
external_call_count = 0
|
||||
blog_query_count = 0
|
||||
web_query_count = 0
|
||||
promoter = SearchResultPromoter()
|
||||
|
||||
for planned in query_plan:
|
||||
query = planned.query
|
||||
signature = _naver_query_signature(query)
|
||||
if signature in existing_signatures:
|
||||
continue
|
||||
existing_signatures.add(signature)
|
||||
|
||||
domain_evidence = self.provider_runtime.naver_adapter.search(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in domain_evidence):
|
||||
external_call_count += 1
|
||||
domain_evidence = [
|
||||
replace(
|
||||
item,
|
||||
data={
|
||||
**item.data,
|
||||
"query_strategy": planned.strategy,
|
||||
"query_source": planned.source,
|
||||
"query_priority": planned.priority,
|
||||
},
|
||||
)
|
||||
for item in domain_evidence
|
||||
]
|
||||
domain_evidence = promoter.promote(domain_evidence)
|
||||
all_domain_evidence.extend(domain_evidence)
|
||||
for item in domain_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "auto" if payload["status"] == "active" else payload["status"]
|
||||
self._put("evidence", payload["id"], payload)
|
||||
similarity_evidence: list[Evidence] = []
|
||||
remaining_matches = self._search_result_similarity_remaining_budget(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
if can_compare_search_images and remaining_matches > 0:
|
||||
similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
domain_evidence,
|
||||
image_store,
|
||||
status="auto",
|
||||
max_matches=remaining_matches,
|
||||
)
|
||||
all_domain_evidence.extend(similarity_evidence)
|
||||
|
||||
history_entries.append(
|
||||
{
|
||||
"provider": "naver",
|
||||
"query": query,
|
||||
"status": _query_history_status(domain_evidence),
|
||||
"strategy": planned.strategy,
|
||||
"source": planned.source,
|
||||
"timestamp": _now_label(),
|
||||
"count": len(domain_evidence),
|
||||
}
|
||||
)
|
||||
|
||||
page_similarity_evidence: list[Evidence] = []
|
||||
remaining_matches = self._search_result_similarity_remaining_budget(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
if blog_query_count < self.provider_runtime.auto_naver_blog_query_limit:
|
||||
blog_signature = _naver_blog_query_signature(query)
|
||||
if blog_signature in existing_signatures:
|
||||
continue
|
||||
existing_signatures.add(blog_signature)
|
||||
blog_query_count += 1
|
||||
|
||||
page_evidence = self.provider_runtime.naver_adapter.search_pages(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in page_evidence):
|
||||
external_call_count += 1
|
||||
page_evidence = [
|
||||
replace(
|
||||
item,
|
||||
data={
|
||||
**item.data,
|
||||
"query_strategy": planned.strategy,
|
||||
"query_source": planned.source,
|
||||
"query_priority": planned.priority,
|
||||
},
|
||||
)
|
||||
for item in page_evidence
|
||||
]
|
||||
page_evidence = promoter.promote(page_evidence)
|
||||
all_domain_evidence.extend(page_evidence)
|
||||
for item in page_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "auto" if payload["status"] == "active" else payload["status"]
|
||||
self._put("evidence", payload["id"], payload)
|
||||
page_similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
page_evidence,
|
||||
image_store,
|
||||
status="auto",
|
||||
max_matches=remaining_matches if can_compare_search_images else 0,
|
||||
)
|
||||
all_domain_evidence.extend(page_similarity_evidence)
|
||||
history_entries.append(
|
||||
{
|
||||
"provider": "naver_blog",
|
||||
"query": query,
|
||||
"status": _query_history_status(page_evidence),
|
||||
"strategy": planned.strategy,
|
||||
"source": planned.source,
|
||||
"timestamp": _now_label(),
|
||||
"count": len(page_evidence),
|
||||
}
|
||||
)
|
||||
|
||||
if web_query_count < self.provider_runtime.auto_naver_web_query_limit:
|
||||
web_signature = _naver_web_query_signature(query)
|
||||
if web_signature in existing_signatures:
|
||||
continue
|
||||
existing_signatures.add(web_signature)
|
||||
web_query_count += 1
|
||||
|
||||
web_evidence = self.provider_runtime.naver_adapter.search_web_pages(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in web_evidence):
|
||||
external_call_count += 1
|
||||
web_evidence = [
|
||||
replace(
|
||||
item,
|
||||
data={
|
||||
**item.data,
|
||||
"query_strategy": planned.strategy,
|
||||
"query_source": planned.source,
|
||||
"query_priority": planned.priority,
|
||||
},
|
||||
)
|
||||
for item in web_evidence
|
||||
]
|
||||
web_evidence = promoter.promote(web_evidence)
|
||||
all_domain_evidence.extend(web_evidence)
|
||||
for item in web_evidence:
|
||||
payload = _evidence_payload(submission_id, item)
|
||||
payload["status"] = "auto" if payload["status"] == "active" else payload["status"]
|
||||
self._put("evidence", payload["id"], payload)
|
||||
all_domain_evidence.extend(
|
||||
self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
web_evidence,
|
||||
image_store,
|
||||
status="auto",
|
||||
max_matches=(
|
||||
self._search_result_similarity_remaining_budget(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
if can_compare_search_images
|
||||
else 0
|
||||
),
|
||||
)
|
||||
)
|
||||
history_entries.append(
|
||||
{
|
||||
"provider": "naver_web",
|
||||
"query": query,
|
||||
"status": _query_history_status(web_evidence),
|
||||
"strategy": planned.strategy,
|
||||
"source": planned.source,
|
||||
"timestamp": _now_label(),
|
||||
"count": len(web_evidence),
|
||||
}
|
||||
)
|
||||
|
||||
if not history_entries:
|
||||
return
|
||||
|
||||
submission = self._get("submissions", submission_id)
|
||||
submission["queryHistory"] = [*history_entries, *submission.get("queryHistory", [])]
|
||||
self._put("submissions", submission_id, submission)
|
||||
|
||||
naver_provider = self._get("providers", "naver")
|
||||
if any(
|
||||
item.source in {EvidenceSource.SEARCH_SKIPPED, EvidenceSource.ENRICHMENT_FAILURE}
|
||||
for item in all_domain_evidence
|
||||
):
|
||||
naver_provider["lastFailure"] = all_domain_evidence[0].reason if all_domain_evidence else "Naver search failed"
|
||||
else:
|
||||
naver_provider["lastSuccess"] = _now_label()
|
||||
naver_provider["lastFailure"] = "없음"
|
||||
self._apply_provider_usage_delta("naver", external_call_count, naver_provider)
|
||||
self.add_audit_event(
|
||||
"system",
|
||||
"Provider called",
|
||||
f"naver / {submission_id}",
|
||||
f"auto text query batch: {', '.join(item['query'] for item in history_entries)}",
|
||||
)
|
||||
|
||||
|
|
@ -13,6 +13,7 @@ from rights_filter.analysis.face_person_detection import FacePersonSignal
|
|||
from rights_filter.server.http_app import build_server
|
||||
from rights_filter.server.image_store import LocalSubmissionImageStore
|
||||
from rights_filter.server import sqlite_store as sqlite_store_module
|
||||
from rights_filter.server import store_enrichment as store_enrichment_module
|
||||
from rights_filter.server.sqlite_store import CopyrighterStore
|
||||
from rights_filter.integrations.env_clients import build_provider_runtime
|
||||
|
||||
|
|
@ -75,6 +76,7 @@ class OneFaceDetector:
|
|||
@pytest.fixture(autouse=True)
|
||||
def use_explicit_test_face_detector(monkeypatch):
|
||||
monkeypatch.setattr(sqlite_store_module, "HeuristicFacePersonDetector", lambda: OneFaceDetector())
|
||||
monkeypatch.setattr(store_enrichment_module, "HeuristicFacePersonDetector", lambda: OneFaceDetector())
|
||||
|
||||
|
||||
def _fixtures(tmp_path: Path):
|
||||
|
|
@ -1233,6 +1235,7 @@ class OneFaceBoxDetector:
|
|||
|
||||
def test_face_crops_are_persisted_served_and_listed_in_review(tmp_path: Path, monkeypatch):
|
||||
monkeypatch.setattr(sqlite_store_module, "HeuristicFacePersonDetector", lambda: OneFaceBoxDetector())
|
||||
monkeypatch.setattr(store_enrichment_module, "HeuristicFacePersonDetector", lambda: OneFaceBoxDetector())
|
||||
static_dir, image_store, store = _png_fixtures(tmp_path)
|
||||
server = build_server(host="127.0.0.1", port=0, store=store, image_store=image_store, static_dir=static_dir)
|
||||
_start(server)
|
||||
|
|
|
|||
|
|
@ -12,6 +12,7 @@ from rights_filter.analysis.preprocessing import ImagePayload, build_face_crop_d
|
|||
from rights_filter.domain.records import Evidence, EvidenceSource
|
||||
from rights_filter.server.image_store import LocalSubmissionImageStore
|
||||
from rights_filter.server import sqlite_store as sqlite_store_module
|
||||
from rights_filter.server import store_enrichment as store_enrichment_module
|
||||
from rights_filter.server import store_remote_fetch as remote_fetch_module
|
||||
from rights_filter.server.sqlite_store import CopyrighterStore
|
||||
from rights_filter.integrations.env_clients import build_provider_runtime
|
||||
|
|
@ -100,6 +101,7 @@ class OneFaceDetector:
|
|||
@pytest.fixture(autouse=True)
|
||||
def use_explicit_test_face_detector(monkeypatch):
|
||||
monkeypatch.setattr(sqlite_store_module, "HeuristicFacePersonDetector", lambda: OneFaceDetector())
|
||||
monkeypatch.setattr(store_enrichment_module, "HeuristicFacePersonDetector", lambda: OneFaceDetector())
|
||||
|
||||
|
||||
def _image_store(tmp_path: Path) -> LocalSubmissionImageStore:
|
||||
|
|
@ -1012,10 +1014,12 @@ def test_sqlite_store_refreshes_existing_local_face_evidence_when_reloaded(tmp_p
|
|||
store.initialize()
|
||||
|
||||
monkeypatch.setattr(sqlite_store_module, "HeuristicFacePersonDetector", lambda: NoFaceDetector())
|
||||
monkeypatch.setattr(store_enrichment_module, "HeuristicFacePersonDetector", lambda: NoFaceDetector())
|
||||
store.seed_from_image_store(image_store)
|
||||
assert not any(item["source"] == "face" for item in store.review("SUB-DB1")["evidence"])
|
||||
|
||||
monkeypatch.setattr(sqlite_store_module, "HeuristicFacePersonDetector", lambda: OneFaceDetector())
|
||||
monkeypatch.setattr(store_enrichment_module, "HeuristicFacePersonDetector", lambda: OneFaceDetector())
|
||||
imported = store.seed_from_image_store(image_store)
|
||||
review = store.review("SUB-DB1")
|
||||
|
||||
|
|
@ -7415,6 +7419,7 @@ def test_sqlite_store_rerun_enrichment_runs_google_web_detection_on_face_crop_wh
|
|||
store = CopyrighterStore(tmp_path / "copyrighter.sqlite3", provider_runtime=runtime)
|
||||
store.initialize()
|
||||
monkeypatch.setattr(sqlite_store_module, "HeuristicFacePersonDetector", lambda: OneFaceDetector())
|
||||
monkeypatch.setattr(store_enrichment_module, "HeuristicFacePersonDetector", lambda: OneFaceDetector())
|
||||
store.seed_from_image_store(image_store)
|
||||
calls_after_seed = len(transport.calls)
|
||||
|
||||
|
|
@ -7493,6 +7498,7 @@ def test_sqlite_store_compares_face_crop_search_result_images_against_crop_finge
|
|||
)
|
||||
store.initialize()
|
||||
monkeypatch.setattr(sqlite_store_module, "HeuristicFacePersonDetector", lambda: BoxedFaceDetector())
|
||||
monkeypatch.setattr(store_enrichment_module, "HeuristicFacePersonDetector", lambda: BoxedFaceDetector())
|
||||
store.seed_from_image_store(image_store)
|
||||
|
||||
review = store.rerun_enrichment("SUB-FACE1", image_store)
|
||||
|
|
@ -7585,6 +7591,7 @@ def test_sqlite_store_compares_face_crop_search_result_page_images_against_crop_
|
|||
)
|
||||
store.initialize()
|
||||
monkeypatch.setattr(sqlite_store_module, "HeuristicFacePersonDetector", lambda: BoxedFaceDetector())
|
||||
monkeypatch.setattr(store_enrichment_module, "HeuristicFacePersonDetector", lambda: BoxedFaceDetector())
|
||||
store.seed_from_image_store(image_store)
|
||||
|
||||
review = store.rerun_enrichment("SUB-FACE1", image_store)
|
||||
|
|
@ -7670,6 +7677,7 @@ def test_sqlite_store_rerun_enrichment_uses_face_crop_page_title_for_naver_searc
|
|||
)
|
||||
store.initialize()
|
||||
monkeypatch.setattr(sqlite_store_module, "HeuristicFacePersonDetector", lambda: BoxedFaceDetector())
|
||||
monkeypatch.setattr(store_enrichment_module, "HeuristicFacePersonDetector", lambda: BoxedFaceDetector())
|
||||
store.seed_from_image_store(image_store)
|
||||
calls_after_seed = len(transport.calls)
|
||||
|
||||
|
|
|
|||
Loading…
Reference in a new issue