refactor: extract operator operations into StoreOperationsMixin
Move knowledge-entry lifecycle, rerun/auto/manual search drivers, LLM summary management, manual knowledge registration, and keyword-candidate collection/ promotion into a mixin; CopyrighterStore inherits it. Drop now-unused imports; point the rollback test at store_serialization._stable_id. sqlite_store.py 1598 -> 874 lines (5333 -> 874, -84%).
This commit is contained in:
유창욱
parent
3bc07d94c3
commit
b575d2ee06
3 changed files with 771 additions and 734 deletions
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@ -16,7 +16,6 @@ from rights_filter.analysis.face_person_detection import HeuristicFacePersonDete
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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.risk_scoring import RiskScorer
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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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EvidenceSource,
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@ -30,7 +29,7 @@ from rights_filter.integrations.cloud_vision_web_detection import (
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from rights_filter.integrations.env_clients import ProviderRuntime, build_provider_runtime
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from rights_filter.integrations.external_policy import ExternalApiPolicy
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from rights_filter.jobs.batch_analyzer import BatchAnalyzer, SubmissionImage
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from rights_filter.server.image_store import LocalSubmissionImageStore, SUPPORTED_IMAGE_SUFFIXES
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from rights_filter.server.image_store import LocalSubmissionImageStore
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from rights_filter.server.store_constants import (
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DEFAULT_COVERAGE_GOOD_THRESHOLD,
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DEFAULT_COVERAGE_WARN_THRESHOLD,
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@ -49,6 +48,7 @@ from rights_filter.server.store_remote_fetch import (
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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_operations import StoreOperationsMixin
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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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@ -59,24 +59,23 @@ from rights_filter.server.store_schema import (
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)
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from rights_filter.server.store_serialization import (
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_default_evidence_contribution,
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_domain_evidence_from_ui,
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_evidence_id,
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_evidence_matches_provider,
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_evidence_payload,
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_knowledge_type_value,
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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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_stable_id,
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_submission_payload,
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_submission_search_hint_evidence,
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_timestamp_id,
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_watchlist_source_evidence,
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)
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from rights_filter.server.store_text import _text_list, _unique_texts
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class CopyrighterStore(StorePersistenceMixin, StoreSearchCandidatesMixin, StoreEnrichmentMixin):
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class CopyrighterStore(
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StorePersistenceMixin,
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StoreSearchCandidatesMixin,
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StoreEnrichmentMixin,
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StoreOperationsMixin,
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):
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def __init__(
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self,
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db_path: Path | str,
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@ -774,730 +773,6 @@ class CopyrighterStore(StorePersistenceMixin, StoreSearchCandidatesMixin, StoreE
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)
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return self.review(submission_id)
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def promote_watchlist_entry(self, entry_id: str) -> dict[str, Any]:
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entry = self._get("knowledge_entries", entry_id)
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if entry.get("entryStatus") != "watchlist":
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raise ValueError("knowledge entry is not a watchlist candidate")
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entry["entryStatus"] = "confirmed"
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entry["active"] = True
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entry["excludedReason"] = ""
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entry["confirmedAt"] = _now_label()
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entry["confirmedBy"] = "rights.ops"
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self._put("knowledge_entries", entry_id, entry)
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self.add_audit_event(
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"rights.ops",
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"Watchlist candidate promoted",
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str(entry.get("name", entry_id)),
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"promoted into confirmed reference DB",
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)
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return self.bootstrap()
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def exclude_watchlist_entry(self, entry_id: str, reason: str = "") -> dict[str, Any]:
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entry = self._get("knowledge_entries", entry_id)
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if entry.get("entryStatus") not in {"watchlist", "confirmed"}:
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raise ValueError("knowledge entry cannot be excluded")
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entry["entryStatus"] = "excluded"
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entry["active"] = False
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entry["excludedReason"] = reason.strip() or "오탐 또는 무관 후보"
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entry["excludedAt"] = _now_label()
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entry["excludedBy"] = "rights.ops"
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self._put("knowledge_entries", entry_id, entry)
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self.add_audit_event(
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"rights.ops",
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"Watchlist candidate excluded",
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str(entry.get("name", entry_id)),
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entry["excludedReason"],
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)
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return self.bootstrap()
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def update_knowledge_entry(self, entry_id: str, payload: dict[str, Any]) -> dict[str, Any]:
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entry = self._get("knowledge_entries", entry_id)
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updates: dict[str, Any] = {}
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if "aliases" in payload:
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updates["aliases"] = _text_list(payload.get("aliases"))
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if "keywords" in payload:
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updates["keywords"] = _text_list(payload.get("keywords"))
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if "memo" in payload:
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updates["memo"] = str(payload.get("memo", "")).strip()
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if not updates:
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raise ValueError("aliases, keywords, memo 중 수정할 값이 필요합니다")
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before = {key: entry.get(key) for key in updates}
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entry.update(updates)
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self._put("knowledge_entries", entry_id, entry)
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self.add_audit_event(
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"rights.ops",
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"Knowledge entry updated",
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str(entry.get("name", entry_id)),
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f"{json.dumps(before, ensure_ascii=False)} -> {json.dumps(updates, ensure_ascii=False)}",
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)
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return self.bootstrap()
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def deactivate_knowledge_entry(self, entry_id: str, reason: str = "") -> dict[str, Any]:
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entry = self._get("knowledge_entries", entry_id)
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if entry.get("entryStatus", "confirmed") != "confirmed":
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raise ValueError("확정 DB 항목만 비활성화할 수 있습니다")
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if not entry.get("active", False):
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raise ValueError("이미 비활성 상태입니다")
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entry["active"] = False
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entry["deactivatedAt"] = _now_label()
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entry["deactivatedBy"] = "rights.ops"
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entry["deactivatedReason"] = reason.strip()
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self._put("knowledge_entries", entry_id, entry)
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self.add_audit_event(
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"rights.ops",
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"Knowledge entry deactivated",
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str(entry.get("name", entry_id)),
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reason.strip() or "운영자 비활성화",
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)
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return self.bootstrap()
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def reactivate_knowledge_entry(self, entry_id: str, reason: str) -> dict[str, Any]:
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if not reason.strip():
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raise ValueError("재활성에는 사유 메모가 필요합니다")
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entry = self._get("knowledge_entries", entry_id)
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if entry.get("entryStatus", "confirmed") != "confirmed":
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raise ValueError("확정 DB 항목만 재활성화할 수 있습니다")
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if entry.get("active", False):
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raise ValueError("이미 활성 상태입니다")
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entry["active"] = True
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entry["reactivatedAt"] = _now_label()
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entry["reactivatedBy"] = "rights.ops"
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entry["reactivatedReason"] = reason.strip()
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self._put("knowledge_entries", entry_id, entry)
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self.add_audit_event(
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"rights.ops",
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"Knowledge entry reactivated",
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str(entry.get("name", entry_id)),
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reason.strip(),
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)
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return self.bootstrap()
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def _create_or_update_watchlist_entry(
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self,
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submission_id: str,
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decision: str,
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memo: str,
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image_store: LocalSubmissionImageStore | None,
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*,
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conn: sqlite3.Connection | None = None,
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) -> None:
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submission = self._get("submissions", submission_id, conn=conn)
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evidence = self._evidence_by_submission().get(submission_id, [])
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selected_evidence = _watchlist_source_evidence(evidence)
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selected_evidence_ids = [str(item.get("id", "")) for item in selected_evidence if item.get("id")]
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sample_fingerprints = self._watchlist_fingerprints(submission_id, image_store)
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entry_id = _stable_id("kb-watchlist", submission_id)
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try:
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existing = self._get("knowledge_entries", entry_id, conn=conn)
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except KeyError:
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existing = {}
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keywords = _unique_texts(
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[
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*[str(item) for item in submission.get("reasons", [])[:3]],
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*[str(item.get("title", "")) for item in selected_evidence[:3]],
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]
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)
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entry = {
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**existing,
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"id": entry_id,
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"name": submission.get("derivedPreview", {}).get("entryName") or f"{submission.get('title', submission_id)} / {submission_id}",
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"type": "rejected_image",
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"aliases": _unique_texts([submission_id, str(submission.get("title", ""))]),
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"keywords": keywords,
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"memo": memo.strip() or ("보류 판정으로 자동 생성" if decision == "held" else "반려 판정으로 자동 생성"),
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"provenance": "automatic",
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"active": True,
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"entryStatus": "watchlist",
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"originDecisionStatus": decision,
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"sourceDecision": f"DEC-{submission_id}",
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"sourceSubmissionId": submission_id,
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"sourceEvidenceIds": selected_evidence_ids,
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"sampleFingerprints": sample_fingerprints or _text_list(existing.get("sampleFingerprints")),
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"imageAsset": str(submission.get("asset", "")),
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"imageFacts": submission.get("fileFacts", {}),
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"contributionCount": int(existing.get("contributionCount", 0) or 0),
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"matchedSubmissionIds": _text_list(existing.get("matchedSubmissionIds")),
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"lastOriginDecisionAt": _now_label(),
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}
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self._put("knowledge_entries", entry_id, entry, conn=conn)
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def _watchlist_fingerprints(
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self,
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submission_id: str,
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image_store: LocalSubmissionImageStore | None,
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) -> list[str]:
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if image_store is None:
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return []
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try:
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fingerprints = FingerprintService().fingerprints_for(
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image_store.image_payload(submission_id).content
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)
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except Exception:
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return []
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return [fingerprints.perceptual]
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def rerun_enrichment(
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self,
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submission_id: str,
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image_store: LocalSubmissionImageStore | None = None,
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) -> dict[str, Any]:
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submission = self._get("submissions", submission_id)
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score_before = int(submission.get("riskScore", 0) or 0)
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evidence_before = {
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str(item.get("id", "")): item
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for item in self._evidence_by_submission().get(submission_id, [])
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}
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submission["lastAnalysis"] = _now_label()
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self._put("submissions", submission_id, submission)
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evidence = {
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"id": f"ev-{submission_id}-rerun-{_timestamp_id()}",
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"group": "internal",
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"source": "fingerprint",
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"title": "재분석 요청이 접수됨",
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"confidence": 0,
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"query": "",
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"domain": "internal",
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"url": "",
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"retrievedAt": _now_label(),
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"contributed": False,
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"sourceEvidenceIds": [],
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"status": "queued",
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}
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self._put("evidence", evidence["id"], {**evidence, "submission_id": submission_id})
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if image_store is not None:
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self._rerun_internal_analysis(submission_id, image_store)
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google_evidence = self._rerun_google_image_search(submission_id, image_store)
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query_source_evidence = [
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*google_evidence,
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*_submission_search_hint_evidence(submission),
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]
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self._auto_naver_search(submission_id, query_source_evidence, image_store)
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self._auto_google_custom_search(submission_id, query_source_evidence, image_store)
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self._ensure_llm_summary(submission_id)
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self.add_audit_event("rights.ops", "Analysis run created", submission_id, "operator rerun")
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self._rescore_submission(submission_id)
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self._sync_submission_provider_state()
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evidence_after = {
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str(item.get("id", "")): item
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for item in self._evidence_for_submission(submission_id)
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}
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rerun_marker_prefix = f"ev-{submission_id}-rerun-"
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# LLM 요약은 재분석마다 삭제 후 재생성되어 id가 항상 바뀌므로(요약의
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# source_evidence_ids에 타임스탬프 마커 id가 섞임) diff에 포함하면
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# 변경이 없어도 매번 신규+제거로 잡힌다 — diff 대상에서 제외한다.
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added_ids = [
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evidence_id
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for evidence_id in evidence_after
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if evidence_id not in evidence_before
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and not evidence_id.startswith(rerun_marker_prefix)
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and str(evidence_after[evidence_id].get("source", "")) != "llm"
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]
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removed_items = [
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evidence_before[evidence_id]
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for evidence_id in evidence_before
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if evidence_id not in evidence_after
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and str(evidence_before[evidence_id].get("source", "")) != "llm"
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]
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refreshed = self._get("submissions", submission_id)
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refreshed["lastRerunDiff"] = {
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"at": _now_label(),
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"scoreBefore": score_before,
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"scoreAfter": int(refreshed.get("riskScore", 0) or 0),
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"addedEvidenceIds": added_ids,
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"removedEvidenceIds": [str(item.get("id", "")) for item in removed_items],
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"removedSummaries": [
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{"source": str(item.get("source", "")), "reason": str(item.get("title", ""))}
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for item in removed_items
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],
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}
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self._put("submissions", submission_id, refreshed)
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return self.review(submission_id)
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def run_auto_search(
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self,
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submission_id: str,
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image_store: LocalSubmissionImageStore | None = None,
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) -> dict[str, Any]:
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submission = self._get("submissions", submission_id)
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submission["lastAnalysis"] = _now_label()
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self._put("submissions", submission_id, submission)
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existing_evidence = self._evidence_by_submission().get(submission_id, [])
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query_source_evidence = [
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_domain_evidence_from_ui(item)
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for item in existing_evidence
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if item.get("source") in {"google", "naver", "face", "fingerprint", "llm", "failure"}
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]
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query_source_evidence.extend(_submission_search_hint_evidence(submission))
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self._auto_naver_search(submission_id, query_source_evidence, image_store)
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self._auto_google_custom_search(submission_id, query_source_evidence, image_store)
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self._ensure_llm_summary(submission_id)
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self._rescore_submission(submission_id)
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self._sync_submission_provider_state()
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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"auto-search / {submission_id}",
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"operator request for auto text search",
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)
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return self.review(submission_id)
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def manual_search(
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self,
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submission_id: str,
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provider: str,
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query: str,
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image_store: LocalSubmissionImageStore | None = None,
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) -> dict[str, Any]:
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submission = self._get("submissions", submission_id)
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provider_payload = self._get("providers", provider)
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if not provider_payload["enabled"]:
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raise ValueError(f"{provider} provider disabled")
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domain_evidence, provider_call_count = self._manual_search_evidence(
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submission_id,
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provider,
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query,
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image_store,
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)
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for item in domain_evidence:
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evidence = _evidence_payload(submission_id, item)
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evidence["status"] = "manual"
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self._put("evidence", evidence["id"], evidence)
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submission.setdefault("queryHistory", []).insert(
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0,
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{
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"provider": provider,
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"query": query,
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"status": "manual",
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"timestamp": _now_label(),
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"count": len(domain_evidence),
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},
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)
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self._put("submissions", submission_id, submission)
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if any(
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item.source in {EvidenceSource.SEARCH_SKIPPED, EvidenceSource.ENRICHMENT_FAILURE}
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for item in domain_evidence
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):
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provider_payload["lastFailure"] = domain_evidence[0].reason if domain_evidence else f"{provider} search failed"
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else:
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provider_payload["lastSuccess"] = _now_label()
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provider_payload["lastFailure"] = "없음"
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self._apply_provider_usage_delta(provider, provider_call_count, provider_payload)
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self._ensure_llm_summary(submission_id)
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if image_store is not None:
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self._rescore_submission(submission_id)
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self._sync_submission_provider_state()
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self.add_audit_event("rights.ops", "Provider called", f"{provider} / {submission_id}", f"manual text query: {query}")
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return self.review(submission_id)
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def _ensure_llm_summaries_for_existing_source_evidence(self, queue_id: str | None = None) -> None:
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for submission in self._all("submissions", queue_id=queue_id):
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self._ensure_llm_summary(str(submission["id"]), only_if_missing=True)
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def _ensure_llm_summary(self, submission_id: str, *, only_if_missing: bool = False) -> bool:
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if self.provider_runtime.llm_assistant is None:
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return False
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llm_provider = self._get("providers", "llm")
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if not llm_provider.get("enabled"):
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return False
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evidence_payloads = self._evidence_by_submission().get(submission_id, [])
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if only_if_missing and any(
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_evidence_matches_provider(item, "llm") and _provider_item_has_result(item)
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for item in evidence_payloads
|
||||
):
|
||||
return False
|
||||
|
||||
source_evidence = [
|
||||
_domain_evidence_from_ui(item)
|
||||
for item in evidence_payloads
|
||||
if item.get("source") in {"fingerprint", "face", "google", "naver"}
|
||||
]
|
||||
if not source_evidence:
|
||||
return False
|
||||
|
||||
llm_evidence = self.provider_runtime.llm_assistant.summarize(
|
||||
submission_id,
|
||||
source_evidence,
|
||||
)
|
||||
self._delete_llm_summary_evidence(submission_id)
|
||||
self._put(
|
||||
"evidence",
|
||||
_evidence_id(submission_id, llm_evidence),
|
||||
_evidence_payload(submission_id, llm_evidence),
|
||||
)
|
||||
if llm_evidence.source == EvidenceSource.ENRICHMENT_FAILURE:
|
||||
llm_provider["lastFailure"] = llm_evidence.reason
|
||||
else:
|
||||
llm_provider["lastSuccess"] = _now_label()
|
||||
llm_provider["lastFailure"] = "없음"
|
||||
self._apply_provider_usage_delta("llm", 1, llm_provider)
|
||||
return True
|
||||
|
||||
def _delete_llm_summary_evidence(self, submission_id: str) -> None:
|
||||
with self._connect() as conn:
|
||||
conn.execute(
|
||||
"""
|
||||
delete from evidence
|
||||
where submission_id = ?
|
||||
and (
|
||||
source = 'llm'
|
||||
or (
|
||||
source = 'failure'
|
||||
and json_extract(payload, '$.title') like 'LLM assistance failed%'
|
||||
)
|
||||
)
|
||||
""",
|
||||
(submission_id,),
|
||||
)
|
||||
|
||||
def _manual_search_evidence(
|
||||
self,
|
||||
submission_id: str,
|
||||
provider: str,
|
||||
query: str,
|
||||
image_store: LocalSubmissionImageStore | None,
|
||||
) -> tuple[list[Evidence], int]:
|
||||
if provider == "naver":
|
||||
if self.provider_runtime.naver_adapter is None:
|
||||
raise ValueError(f"{provider} provider not connected")
|
||||
promoter = SearchResultPromoter()
|
||||
can_compare_search_images = self._can_compare_search_result_images(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
domain_evidence = self.provider_runtime.naver_adapter.search(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
domain_evidence = promoter.promote(domain_evidence)
|
||||
call_count = 1 if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in domain_evidence) else 0
|
||||
similarity_evidence: list[Evidence] = []
|
||||
if can_compare_search_images and image_store is not None:
|
||||
similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
domain_evidence,
|
||||
image_store,
|
||||
status="manual",
|
||||
)
|
||||
page_similarity_evidence: list[Evidence] = []
|
||||
if can_compare_search_images and image_store is not None and not similarity_evidence:
|
||||
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):
|
||||
call_count += 1
|
||||
page_evidence = promoter.promote(page_evidence)
|
||||
domain_evidence.extend(page_evidence)
|
||||
page_similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
page_evidence,
|
||||
image_store,
|
||||
status="manual",
|
||||
)
|
||||
if (
|
||||
can_compare_search_images
|
||||
and image_store is not None
|
||||
and not similarity_evidence
|
||||
and not page_similarity_evidence
|
||||
):
|
||||
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):
|
||||
call_count += 1
|
||||
web_evidence = promoter.promote(web_evidence)
|
||||
domain_evidence.extend(web_evidence)
|
||||
self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
web_evidence,
|
||||
image_store,
|
||||
status="manual",
|
||||
)
|
||||
return domain_evidence, call_count
|
||||
|
||||
if provider == "google_search":
|
||||
if self.provider_runtime.google_custom_search_adapter is None:
|
||||
raise ValueError(f"{provider} provider not connected")
|
||||
can_compare_search_images = self._can_compare_search_result_images(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
domain_evidence = self.provider_runtime.google_custom_search_adapter.search_images(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.google_custom_search_policy,
|
||||
)
|
||||
call_count = 1 if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in domain_evidence) else 0
|
||||
similarity_evidence: list[Evidence] = []
|
||||
if can_compare_search_images and image_store is not None:
|
||||
similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
domain_evidence,
|
||||
image_store,
|
||||
status="manual",
|
||||
)
|
||||
if can_compare_search_images and image_store is not None and not similarity_evidence:
|
||||
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):
|
||||
call_count += 1
|
||||
domain_evidence.extend(web_evidence)
|
||||
self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
web_evidence,
|
||||
image_store,
|
||||
status="manual",
|
||||
)
|
||||
return domain_evidence, call_count
|
||||
|
||||
raise ValueError(f"{provider} provider not connected")
|
||||
|
||||
def register_manual_knowledge_entry(self, payload: dict[str, Any]) -> dict[str, Any]:
|
||||
name = str(payload.get("name", "")).strip()
|
||||
if not name:
|
||||
raise ValueError("knowledge name required")
|
||||
|
||||
entry_id = f"kb-manual-{_timestamp_id()}"
|
||||
image_record = self._store_manual_knowledge_image(entry_id, payload.get("image"))
|
||||
sample_fingerprints = [image_record["perceptualFingerprint"]] if image_record else []
|
||||
entry = {
|
||||
"id": entry_id,
|
||||
"name": name,
|
||||
"type": _knowledge_type_value(str(payload.get("type", "other"))),
|
||||
"aliases": _text_list(payload.get("aliases")),
|
||||
"keywords": _text_list(payload.get("keywords")),
|
||||
"memo": str(payload.get("memo", "")).strip(),
|
||||
"provenance": "manual",
|
||||
"active": True,
|
||||
"entryStatus": "confirmed",
|
||||
"sourceDecision": "",
|
||||
"sampleFingerprints": sample_fingerprints,
|
||||
"imageAsset": image_record["asset"] if image_record else "",
|
||||
"imageFacts": image_record["facts"] if image_record else {},
|
||||
}
|
||||
self._put("knowledge_entries", entry_id, entry)
|
||||
self.add_audit_event(
|
||||
"rights.ops",
|
||||
"Knowledge entry manually created",
|
||||
name,
|
||||
"manual image reference" if image_record else "manual text reference",
|
||||
)
|
||||
return entry
|
||||
|
||||
def collect_keyword_candidates(self, query: str, provider: str = "naver") -> dict[str, Any]:
|
||||
query = query.strip()
|
||||
if not query:
|
||||
raise ValueError("collection query required")
|
||||
if provider not in {"naver", "google_search"}:
|
||||
raise ValueError(f"{provider} provider not supported for candidate collection")
|
||||
|
||||
self._sync_provider_payloads()
|
||||
provider_payload = self._get("providers", provider)
|
||||
if not provider_payload["enabled"]:
|
||||
raise ValueError(f"{provider} provider disabled")
|
||||
if provider == "naver" and self.provider_runtime.naver_adapter is None:
|
||||
raise ValueError("naver provider not connected")
|
||||
if provider == "google_search" and self.provider_runtime.google_custom_search_adapter is None:
|
||||
raise ValueError("google_search provider not connected")
|
||||
|
||||
self._clear_collection_candidates()
|
||||
if provider == "google_search":
|
||||
domain_evidence = self.provider_runtime.google_custom_search_adapter.search_images(
|
||||
"candidate-collection",
|
||||
query,
|
||||
self.provider_runtime.google_custom_search_policy,
|
||||
)
|
||||
else:
|
||||
domain_evidence = self.provider_runtime.naver_adapter.search(
|
||||
"candidate-collection",
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
collected = 0
|
||||
provider_call_count = 1 if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in domain_evidence) else 0
|
||||
for candidate in self._collection_candidates_from_evidence(query, domain_evidence, provider):
|
||||
self._put("collection_candidates", candidate["id"], candidate)
|
||||
collected += 1
|
||||
|
||||
if provider == "google_search" and collected == 0:
|
||||
web_evidence = self.provider_runtime.google_custom_search_adapter.search_web_pages(
|
||||
"candidate-collection",
|
||||
query,
|
||||
self.provider_runtime.google_custom_search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in web_evidence):
|
||||
provider_call_count += 1
|
||||
domain_evidence.extend(web_evidence)
|
||||
for candidate in self._collection_candidates_from_evidence(query, web_evidence, provider):
|
||||
self._put("collection_candidates", candidate["id"], candidate)
|
||||
collected += 1
|
||||
if provider == "naver" and collected == 0:
|
||||
page_evidence = self.provider_runtime.naver_adapter.search_pages(
|
||||
"candidate-collection",
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in page_evidence):
|
||||
provider_call_count += 1
|
||||
domain_evidence.extend(page_evidence)
|
||||
for candidate in self._collection_candidates_from_evidence(query, page_evidence, provider):
|
||||
self._put("collection_candidates", candidate["id"], candidate)
|
||||
collected += 1
|
||||
if provider == "naver" and collected == 0:
|
||||
web_evidence = self.provider_runtime.naver_adapter.search_web_pages(
|
||||
"candidate-collection",
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in web_evidence):
|
||||
provider_call_count += 1
|
||||
domain_evidence.extend(web_evidence)
|
||||
for candidate in self._collection_candidates_from_evidence(query, web_evidence, provider):
|
||||
self._put("collection_candidates", candidate["id"], candidate)
|
||||
collected += 1
|
||||
|
||||
if any(
|
||||
item.source in {EvidenceSource.SEARCH_SKIPPED, EvidenceSource.ENRICHMENT_FAILURE}
|
||||
for item in domain_evidence
|
||||
):
|
||||
provider_payload["lastFailure"] = domain_evidence[0].reason if domain_evidence else f"{provider} collection failed"
|
||||
else:
|
||||
provider_payload["lastSuccess"] = _now_label()
|
||||
provider_payload["lastFailure"] = "없음"
|
||||
self._apply_provider_usage_delta(provider, provider_call_count, provider_payload)
|
||||
self.add_audit_event("rights.ops", "Keyword candidates collected", provider, f"{query} · {collected} candidates")
|
||||
payload = self.bootstrap()
|
||||
payload["collected"] = collected
|
||||
return payload
|
||||
|
||||
def promote_collection_candidate(self, candidate_id: str, payload: dict[str, Any]) -> dict[str, Any]:
|
||||
with self._write_lock:
|
||||
candidate = self._get("collection_candidates", candidate_id)
|
||||
# Idempotent: a double-click / retry must not create a second
|
||||
# confirmed knowledge entry for the same candidate.
|
||||
if candidate.get("status") == "promoted" and candidate.get("promotedKnowledgeId"):
|
||||
return self.bootstrap()
|
||||
# Deterministic id so a racing retry upserts the same row instead of
|
||||
# minting a new timestamped id.
|
||||
entry_id = _stable_id("kb-candidate", candidate_id)
|
||||
query = str(candidate.get("query", ""))
|
||||
name = str(payload.get("name", "")).strip() or str(candidate.get("title", "")).strip() or query
|
||||
memo = str(payload.get("memo", "")).strip() or f"키워드 후보 수집에서 편입: {query}"
|
||||
entry = {
|
||||
"id": entry_id,
|
||||
"name": name,
|
||||
"type": _knowledge_type_value(str(payload.get("type", "rejected_reference"))),
|
||||
"aliases": _text_list(payload.get("aliases")) or [query],
|
||||
"keywords": _text_list(payload.get("keywords")) or [query],
|
||||
"memo": memo,
|
||||
"provenance": "manual",
|
||||
"active": True,
|
||||
"entryStatus": "confirmed",
|
||||
"sourceDecision": "",
|
||||
"sourceCandidate": candidate_id,
|
||||
"sampleFingerprints": _text_list(candidate.get("sampleFingerprints")),
|
||||
"imageAsset": str(candidate.get("imageAsset", "")),
|
||||
"imageFacts": candidate.get("imageFacts", {}),
|
||||
}
|
||||
with self._transaction() as conn:
|
||||
self._put("knowledge_entries", entry_id, entry, conn=conn)
|
||||
candidate["status"] = "promoted"
|
||||
candidate["promotedKnowledgeId"] = entry_id
|
||||
self._put("collection_candidates", candidate_id, candidate, conn=conn)
|
||||
self.add_audit_event(
|
||||
"rights.ops", "Knowledge entry manually created", name,
|
||||
f"promoted candidate {candidate_id}", conn=conn,
|
||||
)
|
||||
return self.bootstrap()
|
||||
|
||||
def promote_collection_candidates(self, payload: dict[str, Any]) -> dict[str, Any]:
|
||||
candidate_ids = _unique_texts(_text_list(payload.get("candidate_ids", payload.get("candidateIds"))))
|
||||
if not candidate_ids:
|
||||
raise ValueError("candidate_ids required")
|
||||
|
||||
candidates = [self._get("collection_candidates", candidate_id) for candidate_id in candidate_ids]
|
||||
sample_fingerprints = _unique_texts(
|
||||
fingerprint
|
||||
for candidate in candidates
|
||||
for fingerprint in _text_list(candidate.get("sampleFingerprints"))
|
||||
)
|
||||
if not sample_fingerprints:
|
||||
raise ValueError("selected candidates have no sample fingerprints")
|
||||
|
||||
entry_id = f"kb-candidate-{_timestamp_id()}"
|
||||
queries = _unique_texts(str(candidate.get("query", "")) for candidate in candidates)
|
||||
image_assets = _unique_texts(str(candidate.get("imageAsset", "")) for candidate in candidates)
|
||||
image_facts = [
|
||||
candidate.get("imageFacts", {})
|
||||
for candidate in candidates
|
||||
if isinstance(candidate.get("imageFacts", {}), dict) and candidate.get("imageFacts", {})
|
||||
]
|
||||
fallback_name = next(
|
||||
(
|
||||
str(candidate.get("title", "")).strip() or str(candidate.get("query", "")).strip()
|
||||
for candidate in candidates
|
||||
if str(candidate.get("title", "")).strip() or str(candidate.get("query", "")).strip()
|
||||
),
|
||||
"Collected reference",
|
||||
)
|
||||
name = str(payload.get("name", "")).strip() or fallback_name
|
||||
memo = str(payload.get("memo", "")).strip() or f"Promoted from collected candidates: {', '.join(queries)}"
|
||||
entry = {
|
||||
"id": entry_id,
|
||||
"name": name,
|
||||
"type": _knowledge_type_value(str(payload.get("type", "rejected_reference"))),
|
||||
"aliases": _text_list(payload.get("aliases")) or queries,
|
||||
"keywords": _text_list(payload.get("keywords")) or queries,
|
||||
"memo": memo,
|
||||
"provenance": "manual",
|
||||
"active": True,
|
||||
"entryStatus": "confirmed",
|
||||
"sourceDecision": "",
|
||||
"sourceCandidate": candidate_ids[0] if len(candidate_ids) == 1 else "",
|
||||
"sourceCandidates": candidate_ids,
|
||||
"sampleFingerprints": sample_fingerprints,
|
||||
"imageAsset": image_assets[0] if image_assets else "",
|
||||
"imageAssets": image_assets,
|
||||
"imageFacts": {
|
||||
"samples": len(candidates),
|
||||
"queries": queries,
|
||||
"items": image_facts,
|
||||
},
|
||||
}
|
||||
self._put("knowledge_entries", entry_id, entry)
|
||||
for candidate in candidates:
|
||||
candidate["status"] = "promoted"
|
||||
candidate["promotedKnowledgeId"] = entry_id
|
||||
self._put("collection_candidates", str(candidate["id"]), candidate)
|
||||
self.add_audit_event(
|
||||
"rights.ops",
|
||||
"Knowledge entry manually created",
|
||||
name,
|
||||
f"promoted {len(candidates)} collected candidates",
|
||||
)
|
||||
return self.bootstrap()
|
||||
|
||||
def providers(self) -> list[dict[str, Any]]:
|
||||
return self._all("providers")
|
||||
|
||||
|
|
|
|||
761
src/rights_filter/server/store_operations.py
Normal file
761
src/rights_filter/server/store_operations.py
Normal file
|
|
@ -0,0 +1,761 @@
|
|||
"""Operator-facing operations for CopyrighterStore, as a mixin.
|
||||
|
||||
Knowledge-entry lifecycle (watchlist promote/exclude, update/deactivate/
|
||||
reactivate), rerun/auto/manual search drivers, LLM summary management, manual
|
||||
knowledge registration, and keyword-candidate collection/promotion. Mixed into
|
||||
CopyrighterStore; relies on persistence + enrichment + search-candidate methods
|
||||
and self.* attributes provided by the host class. Behavior unchanged.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import re
|
||||
import sqlite3
|
||||
from typing import Any
|
||||
|
||||
from rights_filter.analysis.fingerprints import FingerprintService
|
||||
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 (
|
||||
_domain_evidence_from_ui,
|
||||
_evidence_id,
|
||||
_evidence_matches_provider,
|
||||
_evidence_payload,
|
||||
_knowledge_type_value,
|
||||
_now_label,
|
||||
_provider_item_has_result,
|
||||
_stable_id,
|
||||
_submission_search_hint_evidence,
|
||||
_timestamp_id,
|
||||
_watchlist_source_evidence,
|
||||
)
|
||||
from rights_filter.server.store_text import _text_list, _unique_texts
|
||||
|
||||
|
||||
class StoreOperationsMixin:
|
||||
def promote_watchlist_entry(self, entry_id: str) -> dict[str, Any]:
|
||||
entry = self._get("knowledge_entries", entry_id)
|
||||
if entry.get("entryStatus") != "watchlist":
|
||||
raise ValueError("knowledge entry is not a watchlist candidate")
|
||||
entry["entryStatus"] = "confirmed"
|
||||
entry["active"] = True
|
||||
entry["excludedReason"] = ""
|
||||
entry["confirmedAt"] = _now_label()
|
||||
entry["confirmedBy"] = "rights.ops"
|
||||
self._put("knowledge_entries", entry_id, entry)
|
||||
self.add_audit_event(
|
||||
"rights.ops",
|
||||
"Watchlist candidate promoted",
|
||||
str(entry.get("name", entry_id)),
|
||||
"promoted into confirmed reference DB",
|
||||
)
|
||||
return self.bootstrap()
|
||||
|
||||
def exclude_watchlist_entry(self, entry_id: str, reason: str = "") -> dict[str, Any]:
|
||||
entry = self._get("knowledge_entries", entry_id)
|
||||
if entry.get("entryStatus") not in {"watchlist", "confirmed"}:
|
||||
raise ValueError("knowledge entry cannot be excluded")
|
||||
entry["entryStatus"] = "excluded"
|
||||
entry["active"] = False
|
||||
entry["excludedReason"] = reason.strip() or "오탐 또는 무관 후보"
|
||||
entry["excludedAt"] = _now_label()
|
||||
entry["excludedBy"] = "rights.ops"
|
||||
self._put("knowledge_entries", entry_id, entry)
|
||||
self.add_audit_event(
|
||||
"rights.ops",
|
||||
"Watchlist candidate excluded",
|
||||
str(entry.get("name", entry_id)),
|
||||
entry["excludedReason"],
|
||||
)
|
||||
return self.bootstrap()
|
||||
|
||||
def update_knowledge_entry(self, entry_id: str, payload: dict[str, Any]) -> dict[str, Any]:
|
||||
entry = self._get("knowledge_entries", entry_id)
|
||||
updates: dict[str, Any] = {}
|
||||
if "aliases" in payload:
|
||||
updates["aliases"] = _text_list(payload.get("aliases"))
|
||||
if "keywords" in payload:
|
||||
updates["keywords"] = _text_list(payload.get("keywords"))
|
||||
if "memo" in payload:
|
||||
updates["memo"] = str(payload.get("memo", "")).strip()
|
||||
if not updates:
|
||||
raise ValueError("aliases, keywords, memo 중 수정할 값이 필요합니다")
|
||||
|
||||
before = {key: entry.get(key) for key in updates}
|
||||
entry.update(updates)
|
||||
self._put("knowledge_entries", entry_id, entry)
|
||||
self.add_audit_event(
|
||||
"rights.ops",
|
||||
"Knowledge entry updated",
|
||||
str(entry.get("name", entry_id)),
|
||||
f"{json.dumps(before, ensure_ascii=False)} -> {json.dumps(updates, ensure_ascii=False)}",
|
||||
)
|
||||
return self.bootstrap()
|
||||
|
||||
def deactivate_knowledge_entry(self, entry_id: str, reason: str = "") -> dict[str, Any]:
|
||||
entry = self._get("knowledge_entries", entry_id)
|
||||
if entry.get("entryStatus", "confirmed") != "confirmed":
|
||||
raise ValueError("확정 DB 항목만 비활성화할 수 있습니다")
|
||||
if not entry.get("active", False):
|
||||
raise ValueError("이미 비활성 상태입니다")
|
||||
entry["active"] = False
|
||||
entry["deactivatedAt"] = _now_label()
|
||||
entry["deactivatedBy"] = "rights.ops"
|
||||
entry["deactivatedReason"] = reason.strip()
|
||||
self._put("knowledge_entries", entry_id, entry)
|
||||
self.add_audit_event(
|
||||
"rights.ops",
|
||||
"Knowledge entry deactivated",
|
||||
str(entry.get("name", entry_id)),
|
||||
reason.strip() or "운영자 비활성화",
|
||||
)
|
||||
return self.bootstrap()
|
||||
|
||||
def reactivate_knowledge_entry(self, entry_id: str, reason: str) -> dict[str, Any]:
|
||||
if not reason.strip():
|
||||
raise ValueError("재활성에는 사유 메모가 필요합니다")
|
||||
entry = self._get("knowledge_entries", entry_id)
|
||||
if entry.get("entryStatus", "confirmed") != "confirmed":
|
||||
raise ValueError("확정 DB 항목만 재활성화할 수 있습니다")
|
||||
if entry.get("active", False):
|
||||
raise ValueError("이미 활성 상태입니다")
|
||||
entry["active"] = True
|
||||
entry["reactivatedAt"] = _now_label()
|
||||
entry["reactivatedBy"] = "rights.ops"
|
||||
entry["reactivatedReason"] = reason.strip()
|
||||
self._put("knowledge_entries", entry_id, entry)
|
||||
self.add_audit_event(
|
||||
"rights.ops",
|
||||
"Knowledge entry reactivated",
|
||||
str(entry.get("name", entry_id)),
|
||||
reason.strip(),
|
||||
)
|
||||
return self.bootstrap()
|
||||
|
||||
def _create_or_update_watchlist_entry(
|
||||
self,
|
||||
submission_id: str,
|
||||
decision: str,
|
||||
memo: str,
|
||||
image_store: LocalSubmissionImageStore | None,
|
||||
*,
|
||||
conn: sqlite3.Connection | None = None,
|
||||
) -> None:
|
||||
submission = self._get("submissions", submission_id, conn=conn)
|
||||
evidence = self._evidence_by_submission().get(submission_id, [])
|
||||
selected_evidence = _watchlist_source_evidence(evidence)
|
||||
selected_evidence_ids = [str(item.get("id", "")) for item in selected_evidence if item.get("id")]
|
||||
sample_fingerprints = self._watchlist_fingerprints(submission_id, image_store)
|
||||
|
||||
entry_id = _stable_id("kb-watchlist", submission_id)
|
||||
try:
|
||||
existing = self._get("knowledge_entries", entry_id, conn=conn)
|
||||
except KeyError:
|
||||
existing = {}
|
||||
|
||||
keywords = _unique_texts(
|
||||
[
|
||||
*[str(item) for item in submission.get("reasons", [])[:3]],
|
||||
*[str(item.get("title", "")) for item in selected_evidence[:3]],
|
||||
]
|
||||
)
|
||||
entry = {
|
||||
**existing,
|
||||
"id": entry_id,
|
||||
"name": submission.get("derivedPreview", {}).get("entryName") or f"{submission.get('title', submission_id)} / {submission_id}",
|
||||
"type": "rejected_image",
|
||||
"aliases": _unique_texts([submission_id, str(submission.get("title", ""))]),
|
||||
"keywords": keywords,
|
||||
"memo": memo.strip() or ("보류 판정으로 자동 생성" if decision == "held" else "반려 판정으로 자동 생성"),
|
||||
"provenance": "automatic",
|
||||
"active": True,
|
||||
"entryStatus": "watchlist",
|
||||
"originDecisionStatus": decision,
|
||||
"sourceDecision": f"DEC-{submission_id}",
|
||||
"sourceSubmissionId": submission_id,
|
||||
"sourceEvidenceIds": selected_evidence_ids,
|
||||
"sampleFingerprints": sample_fingerprints or _text_list(existing.get("sampleFingerprints")),
|
||||
"imageAsset": str(submission.get("asset", "")),
|
||||
"imageFacts": submission.get("fileFacts", {}),
|
||||
"contributionCount": int(existing.get("contributionCount", 0) or 0),
|
||||
"matchedSubmissionIds": _text_list(existing.get("matchedSubmissionIds")),
|
||||
"lastOriginDecisionAt": _now_label(),
|
||||
}
|
||||
self._put("knowledge_entries", entry_id, entry, conn=conn)
|
||||
|
||||
def _watchlist_fingerprints(
|
||||
self,
|
||||
submission_id: str,
|
||||
image_store: LocalSubmissionImageStore | None,
|
||||
) -> list[str]:
|
||||
if image_store is None:
|
||||
return []
|
||||
try:
|
||||
fingerprints = FingerprintService().fingerprints_for(
|
||||
image_store.image_payload(submission_id).content
|
||||
)
|
||||
except Exception:
|
||||
return []
|
||||
return [fingerprints.perceptual]
|
||||
|
||||
def rerun_enrichment(
|
||||
self,
|
||||
submission_id: str,
|
||||
image_store: LocalSubmissionImageStore | None = None,
|
||||
) -> dict[str, Any]:
|
||||
submission = self._get("submissions", submission_id)
|
||||
score_before = int(submission.get("riskScore", 0) or 0)
|
||||
evidence_before = {
|
||||
str(item.get("id", "")): item
|
||||
for item in self._evidence_by_submission().get(submission_id, [])
|
||||
}
|
||||
submission["lastAnalysis"] = _now_label()
|
||||
self._put("submissions", submission_id, submission)
|
||||
evidence = {
|
||||
"id": f"ev-{submission_id}-rerun-{_timestamp_id()}",
|
||||
"group": "internal",
|
||||
"source": "fingerprint",
|
||||
"title": "재분석 요청이 접수됨",
|
||||
"confidence": 0,
|
||||
"query": "",
|
||||
"domain": "internal",
|
||||
"url": "",
|
||||
"retrievedAt": _now_label(),
|
||||
"contributed": False,
|
||||
"sourceEvidenceIds": [],
|
||||
"status": "queued",
|
||||
}
|
||||
self._put("evidence", evidence["id"], {**evidence, "submission_id": submission_id})
|
||||
|
||||
if image_store is not None:
|
||||
self._rerun_internal_analysis(submission_id, image_store)
|
||||
google_evidence = self._rerun_google_image_search(submission_id, image_store)
|
||||
query_source_evidence = [
|
||||
*google_evidence,
|
||||
*_submission_search_hint_evidence(submission),
|
||||
]
|
||||
self._auto_naver_search(submission_id, query_source_evidence, image_store)
|
||||
self._auto_google_custom_search(submission_id, query_source_evidence, image_store)
|
||||
|
||||
self._ensure_llm_summary(submission_id)
|
||||
|
||||
self.add_audit_event("rights.ops", "Analysis run created", submission_id, "operator rerun")
|
||||
self._rescore_submission(submission_id)
|
||||
self._sync_submission_provider_state()
|
||||
|
||||
evidence_after = {
|
||||
str(item.get("id", "")): item
|
||||
for item in self._evidence_for_submission(submission_id)
|
||||
}
|
||||
rerun_marker_prefix = f"ev-{submission_id}-rerun-"
|
||||
# LLM 요약은 재분석마다 삭제 후 재생성되어 id가 항상 바뀌므로(요약의
|
||||
# source_evidence_ids에 타임스탬프 마커 id가 섞임) diff에 포함하면
|
||||
# 변경이 없어도 매번 신규+제거로 잡힌다 — diff 대상에서 제외한다.
|
||||
added_ids = [
|
||||
evidence_id
|
||||
for evidence_id in evidence_after
|
||||
if evidence_id not in evidence_before
|
||||
and not evidence_id.startswith(rerun_marker_prefix)
|
||||
and str(evidence_after[evidence_id].get("source", "")) != "llm"
|
||||
]
|
||||
removed_items = [
|
||||
evidence_before[evidence_id]
|
||||
for evidence_id in evidence_before
|
||||
if evidence_id not in evidence_after
|
||||
and str(evidence_before[evidence_id].get("source", "")) != "llm"
|
||||
]
|
||||
refreshed = self._get("submissions", submission_id)
|
||||
refreshed["lastRerunDiff"] = {
|
||||
"at": _now_label(),
|
||||
"scoreBefore": score_before,
|
||||
"scoreAfter": int(refreshed.get("riskScore", 0) or 0),
|
||||
"addedEvidenceIds": added_ids,
|
||||
"removedEvidenceIds": [str(item.get("id", "")) for item in removed_items],
|
||||
"removedSummaries": [
|
||||
{"source": str(item.get("source", "")), "reason": str(item.get("title", ""))}
|
||||
for item in removed_items
|
||||
],
|
||||
}
|
||||
self._put("submissions", submission_id, refreshed)
|
||||
return self.review(submission_id)
|
||||
|
||||
def run_auto_search(
|
||||
self,
|
||||
submission_id: str,
|
||||
image_store: LocalSubmissionImageStore | None = None,
|
||||
) -> dict[str, Any]:
|
||||
submission = self._get("submissions", submission_id)
|
||||
submission["lastAnalysis"] = _now_label()
|
||||
self._put("submissions", submission_id, submission)
|
||||
|
||||
existing_evidence = self._evidence_by_submission().get(submission_id, [])
|
||||
query_source_evidence = [
|
||||
_domain_evidence_from_ui(item)
|
||||
for item in existing_evidence
|
||||
if item.get("source") in {"google", "naver", "face", "fingerprint", "llm", "failure"}
|
||||
]
|
||||
query_source_evidence.extend(_submission_search_hint_evidence(submission))
|
||||
|
||||
self._auto_naver_search(submission_id, query_source_evidence, image_store)
|
||||
self._auto_google_custom_search(submission_id, query_source_evidence, image_store)
|
||||
|
||||
self._ensure_llm_summary(submission_id)
|
||||
self._rescore_submission(submission_id)
|
||||
self._sync_submission_provider_state()
|
||||
self.add_audit_event(
|
||||
"rights.ops",
|
||||
"Provider called",
|
||||
f"auto-search / {submission_id}",
|
||||
"operator request for auto text search",
|
||||
)
|
||||
return self.review(submission_id)
|
||||
|
||||
def manual_search(
|
||||
self,
|
||||
submission_id: str,
|
||||
provider: str,
|
||||
query: str,
|
||||
image_store: LocalSubmissionImageStore | None = None,
|
||||
) -> dict[str, Any]:
|
||||
submission = self._get("submissions", submission_id)
|
||||
provider_payload = self._get("providers", provider)
|
||||
if not provider_payload["enabled"]:
|
||||
raise ValueError(f"{provider} provider disabled")
|
||||
|
||||
domain_evidence, provider_call_count = self._manual_search_evidence(
|
||||
submission_id,
|
||||
provider,
|
||||
query,
|
||||
image_store,
|
||||
)
|
||||
for item in domain_evidence:
|
||||
evidence = _evidence_payload(submission_id, item)
|
||||
evidence["status"] = "manual"
|
||||
self._put("evidence", evidence["id"], evidence)
|
||||
|
||||
submission.setdefault("queryHistory", []).insert(
|
||||
0,
|
||||
{
|
||||
"provider": provider,
|
||||
"query": query,
|
||||
"status": "manual",
|
||||
"timestamp": _now_label(),
|
||||
"count": len(domain_evidence),
|
||||
},
|
||||
)
|
||||
self._put("submissions", submission_id, submission)
|
||||
if any(
|
||||
item.source in {EvidenceSource.SEARCH_SKIPPED, EvidenceSource.ENRICHMENT_FAILURE}
|
||||
for item in domain_evidence
|
||||
):
|
||||
provider_payload["lastFailure"] = domain_evidence[0].reason if domain_evidence else f"{provider} search failed"
|
||||
else:
|
||||
provider_payload["lastSuccess"] = _now_label()
|
||||
provider_payload["lastFailure"] = "없음"
|
||||
self._apply_provider_usage_delta(provider, provider_call_count, provider_payload)
|
||||
self._ensure_llm_summary(submission_id)
|
||||
if image_store is not None:
|
||||
self._rescore_submission(submission_id)
|
||||
self._sync_submission_provider_state()
|
||||
self.add_audit_event("rights.ops", "Provider called", f"{provider} / {submission_id}", f"manual text query: {query}")
|
||||
return self.review(submission_id)
|
||||
|
||||
def _ensure_llm_summaries_for_existing_source_evidence(self, queue_id: str | None = None) -> None:
|
||||
for submission in self._all("submissions", queue_id=queue_id):
|
||||
self._ensure_llm_summary(str(submission["id"]), only_if_missing=True)
|
||||
|
||||
def _ensure_llm_summary(self, submission_id: str, *, only_if_missing: bool = False) -> bool:
|
||||
if self.provider_runtime.llm_assistant is None:
|
||||
return False
|
||||
|
||||
llm_provider = self._get("providers", "llm")
|
||||
if not llm_provider.get("enabled"):
|
||||
return False
|
||||
|
||||
evidence_payloads = self._evidence_by_submission().get(submission_id, [])
|
||||
if only_if_missing and any(
|
||||
_evidence_matches_provider(item, "llm") and _provider_item_has_result(item)
|
||||
for item in evidence_payloads
|
||||
):
|
||||
return False
|
||||
|
||||
source_evidence = [
|
||||
_domain_evidence_from_ui(item)
|
||||
for item in evidence_payloads
|
||||
if item.get("source") in {"fingerprint", "face", "google", "naver"}
|
||||
]
|
||||
if not source_evidence:
|
||||
return False
|
||||
|
||||
llm_evidence = self.provider_runtime.llm_assistant.summarize(
|
||||
submission_id,
|
||||
source_evidence,
|
||||
)
|
||||
self._delete_llm_summary_evidence(submission_id)
|
||||
self._put(
|
||||
"evidence",
|
||||
_evidence_id(submission_id, llm_evidence),
|
||||
_evidence_payload(submission_id, llm_evidence),
|
||||
)
|
||||
if llm_evidence.source == EvidenceSource.ENRICHMENT_FAILURE:
|
||||
llm_provider["lastFailure"] = llm_evidence.reason
|
||||
else:
|
||||
llm_provider["lastSuccess"] = _now_label()
|
||||
llm_provider["lastFailure"] = "없음"
|
||||
self._apply_provider_usage_delta("llm", 1, llm_provider)
|
||||
return True
|
||||
|
||||
def _delete_llm_summary_evidence(self, submission_id: str) -> None:
|
||||
with self._connect() as conn:
|
||||
conn.execute(
|
||||
"""
|
||||
delete from evidence
|
||||
where submission_id = ?
|
||||
and (
|
||||
source = 'llm'
|
||||
or (
|
||||
source = 'failure'
|
||||
and json_extract(payload, '$.title') like 'LLM assistance failed%'
|
||||
)
|
||||
)
|
||||
""",
|
||||
(submission_id,),
|
||||
)
|
||||
|
||||
def _manual_search_evidence(
|
||||
self,
|
||||
submission_id: str,
|
||||
provider: str,
|
||||
query: str,
|
||||
image_store: LocalSubmissionImageStore | None,
|
||||
) -> tuple[list[Evidence], int]:
|
||||
if provider == "naver":
|
||||
if self.provider_runtime.naver_adapter is None:
|
||||
raise ValueError(f"{provider} provider not connected")
|
||||
promoter = SearchResultPromoter()
|
||||
can_compare_search_images = self._can_compare_search_result_images(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
domain_evidence = self.provider_runtime.naver_adapter.search(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
domain_evidence = promoter.promote(domain_evidence)
|
||||
call_count = 1 if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in domain_evidence) else 0
|
||||
similarity_evidence: list[Evidence] = []
|
||||
if can_compare_search_images and image_store is not None:
|
||||
similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
domain_evidence,
|
||||
image_store,
|
||||
status="manual",
|
||||
)
|
||||
page_similarity_evidence: list[Evidence] = []
|
||||
if can_compare_search_images and image_store is not None and not similarity_evidence:
|
||||
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):
|
||||
call_count += 1
|
||||
page_evidence = promoter.promote(page_evidence)
|
||||
domain_evidence.extend(page_evidence)
|
||||
page_similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
page_evidence,
|
||||
image_store,
|
||||
status="manual",
|
||||
)
|
||||
if (
|
||||
can_compare_search_images
|
||||
and image_store is not None
|
||||
and not similarity_evidence
|
||||
and not page_similarity_evidence
|
||||
):
|
||||
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):
|
||||
call_count += 1
|
||||
web_evidence = promoter.promote(web_evidence)
|
||||
domain_evidence.extend(web_evidence)
|
||||
self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
web_evidence,
|
||||
image_store,
|
||||
status="manual",
|
||||
)
|
||||
return domain_evidence, call_count
|
||||
|
||||
if provider == "google_search":
|
||||
if self.provider_runtime.google_custom_search_adapter is None:
|
||||
raise ValueError(f"{provider} provider not connected")
|
||||
can_compare_search_images = self._can_compare_search_result_images(
|
||||
submission_id,
|
||||
image_store,
|
||||
)
|
||||
domain_evidence = self.provider_runtime.google_custom_search_adapter.search_images(
|
||||
submission_id,
|
||||
query,
|
||||
self.provider_runtime.google_custom_search_policy,
|
||||
)
|
||||
call_count = 1 if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in domain_evidence) else 0
|
||||
similarity_evidence: list[Evidence] = []
|
||||
if can_compare_search_images and image_store is not None:
|
||||
similarity_evidence = self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
domain_evidence,
|
||||
image_store,
|
||||
status="manual",
|
||||
)
|
||||
if can_compare_search_images and image_store is not None and not similarity_evidence:
|
||||
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):
|
||||
call_count += 1
|
||||
domain_evidence.extend(web_evidence)
|
||||
self._sync_search_result_image_similarity(
|
||||
submission_id,
|
||||
web_evidence,
|
||||
image_store,
|
||||
status="manual",
|
||||
)
|
||||
return domain_evidence, call_count
|
||||
|
||||
raise ValueError(f"{provider} provider not connected")
|
||||
|
||||
def register_manual_knowledge_entry(self, payload: dict[str, Any]) -> dict[str, Any]:
|
||||
name = str(payload.get("name", "")).strip()
|
||||
if not name:
|
||||
raise ValueError("knowledge name required")
|
||||
|
||||
entry_id = f"kb-manual-{_timestamp_id()}"
|
||||
image_record = self._store_manual_knowledge_image(entry_id, payload.get("image"))
|
||||
sample_fingerprints = [image_record["perceptualFingerprint"]] if image_record else []
|
||||
entry = {
|
||||
"id": entry_id,
|
||||
"name": name,
|
||||
"type": _knowledge_type_value(str(payload.get("type", "other"))),
|
||||
"aliases": _text_list(payload.get("aliases")),
|
||||
"keywords": _text_list(payload.get("keywords")),
|
||||
"memo": str(payload.get("memo", "")).strip(),
|
||||
"provenance": "manual",
|
||||
"active": True,
|
||||
"entryStatus": "confirmed",
|
||||
"sourceDecision": "",
|
||||
"sampleFingerprints": sample_fingerprints,
|
||||
"imageAsset": image_record["asset"] if image_record else "",
|
||||
"imageFacts": image_record["facts"] if image_record else {},
|
||||
}
|
||||
self._put("knowledge_entries", entry_id, entry)
|
||||
self.add_audit_event(
|
||||
"rights.ops",
|
||||
"Knowledge entry manually created",
|
||||
name,
|
||||
"manual image reference" if image_record else "manual text reference",
|
||||
)
|
||||
return entry
|
||||
|
||||
def collect_keyword_candidates(self, query: str, provider: str = "naver") -> dict[str, Any]:
|
||||
query = query.strip()
|
||||
if not query:
|
||||
raise ValueError("collection query required")
|
||||
if provider not in {"naver", "google_search"}:
|
||||
raise ValueError(f"{provider} provider not supported for candidate collection")
|
||||
|
||||
self._sync_provider_payloads()
|
||||
provider_payload = self._get("providers", provider)
|
||||
if not provider_payload["enabled"]:
|
||||
raise ValueError(f"{provider} provider disabled")
|
||||
if provider == "naver" and self.provider_runtime.naver_adapter is None:
|
||||
raise ValueError("naver provider not connected")
|
||||
if provider == "google_search" and self.provider_runtime.google_custom_search_adapter is None:
|
||||
raise ValueError("google_search provider not connected")
|
||||
|
||||
self._clear_collection_candidates()
|
||||
if provider == "google_search":
|
||||
domain_evidence = self.provider_runtime.google_custom_search_adapter.search_images(
|
||||
"candidate-collection",
|
||||
query,
|
||||
self.provider_runtime.google_custom_search_policy,
|
||||
)
|
||||
else:
|
||||
domain_evidence = self.provider_runtime.naver_adapter.search(
|
||||
"candidate-collection",
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
collected = 0
|
||||
provider_call_count = 1 if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in domain_evidence) else 0
|
||||
for candidate in self._collection_candidates_from_evidence(query, domain_evidence, provider):
|
||||
self._put("collection_candidates", candidate["id"], candidate)
|
||||
collected += 1
|
||||
|
||||
if provider == "google_search" and collected == 0:
|
||||
web_evidence = self.provider_runtime.google_custom_search_adapter.search_web_pages(
|
||||
"candidate-collection",
|
||||
query,
|
||||
self.provider_runtime.google_custom_search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in web_evidence):
|
||||
provider_call_count += 1
|
||||
domain_evidence.extend(web_evidence)
|
||||
for candidate in self._collection_candidates_from_evidence(query, web_evidence, provider):
|
||||
self._put("collection_candidates", candidate["id"], candidate)
|
||||
collected += 1
|
||||
if provider == "naver" and collected == 0:
|
||||
page_evidence = self.provider_runtime.naver_adapter.search_pages(
|
||||
"candidate-collection",
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in page_evidence):
|
||||
provider_call_count += 1
|
||||
domain_evidence.extend(page_evidence)
|
||||
for candidate in self._collection_candidates_from_evidence(query, page_evidence, provider):
|
||||
self._put("collection_candidates", candidate["id"], candidate)
|
||||
collected += 1
|
||||
if provider == "naver" and collected == 0:
|
||||
web_evidence = self.provider_runtime.naver_adapter.search_web_pages(
|
||||
"candidate-collection",
|
||||
query,
|
||||
self.provider_runtime.search_policy,
|
||||
)
|
||||
if any(item.source != EvidenceSource.SEARCH_SKIPPED for item in web_evidence):
|
||||
provider_call_count += 1
|
||||
domain_evidence.extend(web_evidence)
|
||||
for candidate in self._collection_candidates_from_evidence(query, web_evidence, provider):
|
||||
self._put("collection_candidates", candidate["id"], candidate)
|
||||
collected += 1
|
||||
|
||||
if any(
|
||||
item.source in {EvidenceSource.SEARCH_SKIPPED, EvidenceSource.ENRICHMENT_FAILURE}
|
||||
for item in domain_evidence
|
||||
):
|
||||
provider_payload["lastFailure"] = domain_evidence[0].reason if domain_evidence else f"{provider} collection failed"
|
||||
else:
|
||||
provider_payload["lastSuccess"] = _now_label()
|
||||
provider_payload["lastFailure"] = "없음"
|
||||
self._apply_provider_usage_delta(provider, provider_call_count, provider_payload)
|
||||
self.add_audit_event("rights.ops", "Keyword candidates collected", provider, f"{query} · {collected} candidates")
|
||||
payload = self.bootstrap()
|
||||
payload["collected"] = collected
|
||||
return payload
|
||||
|
||||
def promote_collection_candidate(self, candidate_id: str, payload: dict[str, Any]) -> dict[str, Any]:
|
||||
with self._write_lock:
|
||||
candidate = self._get("collection_candidates", candidate_id)
|
||||
# Idempotent: a double-click / retry must not create a second
|
||||
# confirmed knowledge entry for the same candidate.
|
||||
if candidate.get("status") == "promoted" and candidate.get("promotedKnowledgeId"):
|
||||
return self.bootstrap()
|
||||
# Deterministic id so a racing retry upserts the same row instead of
|
||||
# minting a new timestamped id.
|
||||
entry_id = _stable_id("kb-candidate", candidate_id)
|
||||
query = str(candidate.get("query", ""))
|
||||
name = str(payload.get("name", "")).strip() or str(candidate.get("title", "")).strip() or query
|
||||
memo = str(payload.get("memo", "")).strip() or f"키워드 후보 수집에서 편입: {query}"
|
||||
entry = {
|
||||
"id": entry_id,
|
||||
"name": name,
|
||||
"type": _knowledge_type_value(str(payload.get("type", "rejected_reference"))),
|
||||
"aliases": _text_list(payload.get("aliases")) or [query],
|
||||
"keywords": _text_list(payload.get("keywords")) or [query],
|
||||
"memo": memo,
|
||||
"provenance": "manual",
|
||||
"active": True,
|
||||
"entryStatus": "confirmed",
|
||||
"sourceDecision": "",
|
||||
"sourceCandidate": candidate_id,
|
||||
"sampleFingerprints": _text_list(candidate.get("sampleFingerprints")),
|
||||
"imageAsset": str(candidate.get("imageAsset", "")),
|
||||
"imageFacts": candidate.get("imageFacts", {}),
|
||||
}
|
||||
with self._transaction() as conn:
|
||||
self._put("knowledge_entries", entry_id, entry, conn=conn)
|
||||
candidate["status"] = "promoted"
|
||||
candidate["promotedKnowledgeId"] = entry_id
|
||||
self._put("collection_candidates", candidate_id, candidate, conn=conn)
|
||||
self.add_audit_event(
|
||||
"rights.ops", "Knowledge entry manually created", name,
|
||||
f"promoted candidate {candidate_id}", conn=conn,
|
||||
)
|
||||
return self.bootstrap()
|
||||
|
||||
def promote_collection_candidates(self, payload: dict[str, Any]) -> dict[str, Any]:
|
||||
candidate_ids = _unique_texts(_text_list(payload.get("candidate_ids", payload.get("candidateIds"))))
|
||||
if not candidate_ids:
|
||||
raise ValueError("candidate_ids required")
|
||||
|
||||
candidates = [self._get("collection_candidates", candidate_id) for candidate_id in candidate_ids]
|
||||
sample_fingerprints = _unique_texts(
|
||||
fingerprint
|
||||
for candidate in candidates
|
||||
for fingerprint in _text_list(candidate.get("sampleFingerprints"))
|
||||
)
|
||||
if not sample_fingerprints:
|
||||
raise ValueError("selected candidates have no sample fingerprints")
|
||||
|
||||
entry_id = f"kb-candidate-{_timestamp_id()}"
|
||||
queries = _unique_texts(str(candidate.get("query", "")) for candidate in candidates)
|
||||
image_assets = _unique_texts(str(candidate.get("imageAsset", "")) for candidate in candidates)
|
||||
image_facts = [
|
||||
candidate.get("imageFacts", {})
|
||||
for candidate in candidates
|
||||
if isinstance(candidate.get("imageFacts", {}), dict) and candidate.get("imageFacts", {})
|
||||
]
|
||||
fallback_name = next(
|
||||
(
|
||||
str(candidate.get("title", "")).strip() or str(candidate.get("query", "")).strip()
|
||||
for candidate in candidates
|
||||
if str(candidate.get("title", "")).strip() or str(candidate.get("query", "")).strip()
|
||||
),
|
||||
"Collected reference",
|
||||
)
|
||||
name = str(payload.get("name", "")).strip() or fallback_name
|
||||
memo = str(payload.get("memo", "")).strip() or f"Promoted from collected candidates: {', '.join(queries)}"
|
||||
entry = {
|
||||
"id": entry_id,
|
||||
"name": name,
|
||||
"type": _knowledge_type_value(str(payload.get("type", "rejected_reference"))),
|
||||
"aliases": _text_list(payload.get("aliases")) or queries,
|
||||
"keywords": _text_list(payload.get("keywords")) or queries,
|
||||
"memo": memo,
|
||||
"provenance": "manual",
|
||||
"active": True,
|
||||
"entryStatus": "confirmed",
|
||||
"sourceDecision": "",
|
||||
"sourceCandidate": candidate_ids[0] if len(candidate_ids) == 1 else "",
|
||||
"sourceCandidates": candidate_ids,
|
||||
"sampleFingerprints": sample_fingerprints,
|
||||
"imageAsset": image_assets[0] if image_assets else "",
|
||||
"imageAssets": image_assets,
|
||||
"imageFacts": {
|
||||
"samples": len(candidates),
|
||||
"queries": queries,
|
||||
"items": image_facts,
|
||||
},
|
||||
}
|
||||
self._put("knowledge_entries", entry_id, entry)
|
||||
for candidate in candidates:
|
||||
candidate["status"] = "promoted"
|
||||
candidate["promotedKnowledgeId"] = entry_id
|
||||
self._put("collection_candidates", str(candidate["id"]), candidate)
|
||||
self.add_audit_event(
|
||||
"rights.ops",
|
||||
"Knowledge entry manually created",
|
||||
name,
|
||||
f"promoted {len(candidates)} collected candidates",
|
||||
)
|
||||
return self.bootstrap()
|
||||
|
||||
|
|
@ -14,6 +14,7 @@ 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 import store_serialization as store_serialization_module
|
||||
from rights_filter.server.sqlite_store import CopyrighterStore
|
||||
from rights_filter.integrations.env_clients import build_provider_runtime
|
||||
|
||||
|
|
@ -8040,7 +8041,7 @@ def test_record_decision_rolls_back_when_audit_fails(tmp_path: Path, monkeypatch
|
|||
# The status change must roll back atomically with the failed audit write.
|
||||
assert store._get("submissions", "SUB-1")["decisionStatus"] == "unreviewed"
|
||||
with pytest.raises(KeyError):
|
||||
store._get("knowledge_entries", sqlite_store_module._stable_id("kb-watchlist", "SUB-1"))
|
||||
store._get("knowledge_entries", store_serialization_module._stable_id("kb-watchlist", "SUB-1"))
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
|
|
|
|||
Loading…
Reference in a new issue