chore(omc): record GPT-4o correction finding + P2 API progress (hotpaths)

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

.omc/project-memory.json

@@ -1,22 +1,38 @@
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   "projectRoot": "/root/luke_scribe",
   "techStack": {
     "languages": [
-      "Python"
+      {
+        "name": "Python",
+        "version": null,
+        "confidence": "high",
+        "markers": [
+          "pyproject.toml"
+        ]
+      }
     ],
     "frameworks": [
-      "FastAPI · faster-whisper/CTranslate2 · Redis/RQ(no-fork) · pydantic v2 · ffmpeg · Silero VAD"
+      {
+        "name": "fastapi",
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+        "category": "backend"
+      },
+      {
+        "name": "pytest",
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+        "category": "testing"
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-    "packageManager": "uv",
-    "runtime": "Python 3.11+"
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-    "lintCommand": "uv run ruff check src/ tests/",
-    "devCommand": "uv run luke-scribe detect",
+    "buildCommand": null,
+    "testCommand": "export PATH=\"$HOME/.local/bin:$HOME/.cargo/bin:$PATH\"\nclip=\"samples/ko_en/clips/GDG 인천 - EmbeddingGemma 200% 활용하기 - 지주영.m4a\"\nffmpeg -nostdin -ss 70 -t 12 -i \"$clip\" -ac 1 -ar 16000 -y /tmp/api_smoke.wav 2>/dev/null\nls -l /tmp/api_smoke.wav\necho \"=== pytest 재확인(413 수정 후) ===\"; uv run pytest -q 2>&1 | tail -3",
+    "lintCommand": "ruff check",
+    "devCommand": null,
     "scripts": {}
   },
   "conventions": {
@@ -29,9 +45,10 @@
     "isMonorepo": false,
     "workspaces": [],
     "mainDirectories": [
-      "src/luke_scribe (계획, 미생성)"
+      "src",
+      "tests"
     ],
-    "gitBranches": "main"
+    "gitBranches": null
   },
   "customNotes": [
     {
@@ -57,10 +74,61 @@
       "source": "manual",
       "category": "status",
       "content": "P1 진행(2026-06-07): ✅ detect(능력등급 T0~T3, 1050→T0_CPU 명시강등) · ✅ transcribe(faster-whisper CPU 검증: JFK 11s 클립 정확 전사, model_used 출력) · 단위테스트 10개 통과. 코드 존재함(더 이상 0%). 남음: word-ts/format 출력옵션·Silero VAD 옵션화, VRAM 실측 probe(정적추정 대체), bench(라벨 KO+EN 샘플셋 필요), 상위 tier(T2/T3) Colab 검증, P2(API+Redis/RQ). 브랜치 feat/p1-core."
+    },
+    {
+      "timestamp": 1780926195887,
+      "source": "manual",
+      "category": "finding",
+      "content": "검증된 발견(2026-06-07): KO+EN 혼용어 음차 문제의 open-vocab 해법 = 사내 GPT-4o 텍스트 후처리 보정. faster-whisper(turbo)가 음차로 망친 영문 용어를 hotwords 등록 없이 문맥+지식으로 복원. 실증(EmbeddingGemma 강연 90초 슬라이스): 인베딩 점마→Embedding Gemma, 재미나이→Gemini, 점마→Gemma, 랭기징→Language, 구글 포 디벨로퍼스→Google for Developers (5/5, 일반 한국어는 보존). 게이트=OpenAI 호환(baseURL http://192.168.0.123:8080/v1, model copilot-gpt-4o, API키 필요·키는 메모리에 저장 안 함; localhost:8080은 사용자 머신 터널이라 샌드박스선 미도달) → 사내 호출이라 외부 egress 0(프라이버시 OK). 함의: hotwords는 등록된 것만 잡아 불충분, LLM 문맥보정이 '모르는 용어'까지 커버. 단서: (1) 'Embedding Gemma' 띄어쓰기(공식 EmbeddingGemma)→rules/glossary 정규화 병행 필요, (2) LLM이 아는/추론가능 용어만·초신조어는 confidence 플래그→휴먼, (3) 샘플1개라 과교정 추가검증, (4) 게이트 경로 불안정(401→timeout→reset)→재시도 필요(스크립트에 반영). 작은 컨텍스트는 청크+러닝글로서리로 우회. PoC=scripts/llm_correct.py → 승격 대상 postprocess/llm.py(confidence-gated·청크·backend=internal·감사로그) + transcribe --correct 플래그."
     }
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