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.fingerprints import FingerprintService
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from rights_filter.analysis.internal_analyzer import InternalAnalyzer
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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.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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from rights_filter.domain.records import (
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Evidence,
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Evidence,
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EvidenceSource,
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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.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.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.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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from rights_filter.server.store_constants import (
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DEFAULT_COVERAGE_GOOD_THRESHOLD,
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DEFAULT_COVERAGE_GOOD_THRESHOLD,
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DEFAULT_COVERAGE_WARN_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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_fetch_url_bytes,
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)
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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_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_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_search_candidates import StoreSearchCandidatesMixin
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from rights_filter.server.store_schema import (
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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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)
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from rights_filter.server.store_serialization import (
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from rights_filter.server.store_serialization import (
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_default_evidence_contribution,
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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_id,
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_evidence_matches_provider,
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_evidence_matches_provider,
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_evidence_payload,
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_evidence_payload,
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_knowledge_type_value,
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_now_label,
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_now_label,
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_provider_item_failed,
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_provider_item_failed,
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_provider_item_has_result,
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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_payload,
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_submission_search_hint_evidence,
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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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)
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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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def __init__(
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self,
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self,
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db_path: Path | str,
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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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)
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return self.review(submission_id)
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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 = [
|
|
||||||
_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()
|
|
||||||
|
|
||||||
def providers(self) -> list[dict[str, Any]]:
|
def providers(self) -> list[dict[str, Any]]:
|
||||||
return self._all("providers")
|
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 sqlite_store as sqlite_store_module
|
||||||
from rights_filter.server import store_enrichment as store_enrichment_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_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.server.sqlite_store import CopyrighterStore
|
||||||
from rights_filter.integrations.env_clients import build_provider_runtime
|
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.
|
# The status change must roll back atomically with the failed audit write.
|
||||||
assert store._get("submissions", "SUB-1")["decisionStatus"] == "unreviewed"
|
assert store._get("submissions", "SUB-1")["decisionStatus"] == "unreviewed"
|
||||||
with pytest.raises(KeyError):
|
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(
|
@pytest.mark.parametrize(
|
||||||
|
|
|
||||||
Loading…
Reference in a new issue