3f7b3a9cf2
Image rights / copyright detection system: SQLite store, HTTP app, search integrations (Naver, Google Custom Search, Google Cloud Vision web detection), image analysis (fingerprints, face/person detection, evidence enrichment, risk scoring), an admin/review layer, governance and retention policies, batch jobs, and a browser-based operator GUI. This baseline incorporates a full code-review remediation pass (46 fixes; 358 tests passing). Highlights: CRITICAL - Prevent evidence cascade-delete during the schema-constraint migration by disabling FK enforcement around the table rebuild. Security - Sandbox served media (neutralize stored XSS from uploaded/collected SVGs) via CSP + nosniff on the untrusted media routes. - Strip embedded EXIF/GPS from external image derivatives before they are sent to third-party APIs. - Return a clean 404 (not an uncaught StopIteration) for PATCH on an unknown provider. Correctness - LLM-summary failures no longer add +30 to the risk score. - Decode only explicit JS escapes so Korean image URLs are not mangled. - Consume search quota only after a successful request. - Naver/Google adapters map responses inside the failure boundary, so a malformed response degrades to evidence instead of crashing enrichment. - Domain-aware provider attribution; face-box IoU de-duplication; count searches (not result items); per-box crop isolation; clamp evidence confidence and Google CSE num; real submittedEpoch; and more. Robustness - Offline LLM connect fast-fails (short connect timeout) so seed/reload requests are not stalled; full read timeout preserved for generation. - Malformed numeric env vars fall back to defaults instead of crashing startup. Performance - Per-submission evidence reads (no full-table scan per rescore), audit-log LIMIT, lazy active-store lookup, hoisted timestamps. Tests - ~24 regression tests added pinning the above fixes. Runtime data (data/, outputs/, *.sqlite3, *.log), secrets (.env), and node_modules are gitignored.
97 lines
2.1 KiB
JavaScript
97 lines
2.1 KiB
JavaScript
(function attachOperatorLabels(global) {
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const riskLabels = {
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high: "높음",
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medium: "중간",
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low: "낮음",
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failed: "실패",
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pending: "대기",
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};
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const decisionLabels = {
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unreviewed: "미심사",
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held: "보류",
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rejected: "반려",
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approved: "승인",
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corrected: "보정됨",
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};
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const providerLabels = {
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internal: "내부 분석",
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naver: "네이버 검색",
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naver_blog: "네이버 블로그 검색",
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naver_web: "네이버 웹문서 검색",
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google: "구글 이미지",
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google_search: "구글 근거 검색",
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llm: "내부 요약",
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};
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const sourceLabels = {
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internal: "내부",
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fingerprint: "이미지 유사도",
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face: "얼굴/인물 감지",
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naver: "네이버",
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google: "구글",
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llm: "내부 요약",
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failure: "실패",
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};
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const providerStatusLabels = {
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ok: "정상",
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covered: "근거 있음",
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empty: "결과 없음",
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failed: "실패",
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disabled: "중지",
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skipped: "건너뜀",
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pending: "미실행",
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not_run: "미실행",
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};
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const candidateStatusLabels = {
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candidate: "후보",
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promoted: "반영됨",
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};
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const evidenceStatusLabels = {
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used_for_judgment: "판단에 사용",
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irrelevant: "무관",
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false_positive: "오탐",
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ignored: "미사용",
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pending: "보류",
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};
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const knowledgeStatusLabels = {
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confirmed: "확정 DB",
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watchlist: "주의 후보",
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excluded: "제외됨",
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};
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const provenanceLabels = {
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manual: "수동 등록",
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automatic: "자동 등록",
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external_evidence: "외부 근거",
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};
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const knowledgeTypeLabels = {
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celebrity: "연예인/유명인",
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public_figure: "연예인/유명인",
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work: "작품",
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character: "캐릭터",
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game: "게임",
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rejected_image: "반려 이미지",
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rejected_reference: "반려 이미지",
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other: "기타",
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};
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global.OperatorLabels = {
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riskLabels,
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decisionLabels,
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providerLabels,
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sourceLabels,
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providerStatusLabels,
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candidateStatusLabels,
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evidenceStatusLabels,
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knowledgeStatusLabels,
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provenanceLabels,
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knowledgeTypeLabels,
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};
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})(window);
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