feat: implement full-platform STT API (v2.3 consensus plan)

Batch+realtime transcription API: faster-whisper engine w/ EngineOwner
(single GPU owner, OOM downgrade chain, persisted attempted_profiles),
hardware-adaptive device manager (T0-T3 VRAM tiers), Redis/in-proc job
queue w/ leases + crash recovery, postprocess (glossary/rules/LLM w/
egress guard), privacy-first result store (UUID keys, source deleted
after transcribe), retention sweeper, API-key auth (HMAC digests,
scopes, job ownership), WebSocket realtime lane (LocalAgreement),
CLI (detect/transcribe/bench/serve/key), Docker, benchmark runner.

127 mock-based tests pass; ruff clean. Includes verification checklist
and autoplan review notes.

docker/Dockerfile.cpu

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+# luke_scribe CPU 이미지
+FROM python:3.12-slim
+
+RUN apt-get update && apt-get install -y --no-install-recommends ffmpeg \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+COPY pyproject.toml README.md ./
+COPY src/ ./src/
+
+RUN pip install --no-cache-dir -e ".[engine,api]" \
+    && pip install --no-cache-dir "faster-whisper>=1.0.3"
+
+ENV LUKESCRIBE_DEVICE=cpu \
+    LUKESCRIBE_QUEUE_BACKEND=redis \
+    LUKESCRIBE_HOST=0.0.0.0 \
+    LUKESCRIBE_PORT=8000
+
+EXPOSE 8000
+CMD ["python", "-m", "luke_scribe.cli", "serve"]

docker/Dockerfile.gpu

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+# luke_scribe GPU 이미지 — CUDA 12 + cuDNN 9 + faster-whisper
+# 기준: NVIDIA CUDA 12 런타임, cc>=7.0 GPU (T4 이상 권장)
+FROM nvidia/cuda:12.4.1-runtime-ubuntu22.04
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    python3.11 python3-pip python3-venv ffmpeg \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+COPY pyproject.toml README.md ./
+COPY src/ ./src/
+
+RUN python3.11 -m venv /opt/venv \
+    && . /opt/venv/bin/activate \
+    && pip install --no-cache-dir -e ".[engine,gpu,api]" \
+    && pip install --no-cache-dir "faster-whisper>=1.0.3"
+
+ENV PATH="/opt/venv/bin:$PATH" \
+    LUKESCRIBE_DEVICE=auto \
+    LUKESCRIBE_QUEUE_BACKEND=redis \
+    LUKESCRIBE_HOST=0.0.0.0 \
+    LUKESCRIBE_PORT=8000 \
+    NVIDIA_VISIBLE_DEVICES=all
+
+EXPOSE 8000
+CMD ["python", "-m", "luke_scribe.cli", "serve"]

docker/docker-compose.yml

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+# luke_scribe 프로덕션 compose — API + Redis + 워커 + 공유 스토어
+# 사용법: docker compose --profile gpu up -d   (또는 --profile cpu)
+services:
+  redis:
+    image: redis:7-alpine
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "redis-cli", "ping"]
+      interval: 5s
+      timeout: 3s
+      retries: 5
+
+  api:
+    build:
+      context: ..
+      dockerfile: docker/Dockerfile.cpu
+    profiles: ["cpu"]
+    depends_on:
+      redis:
+        condition: service_healthy
+    environment:
+      LUKESCRIBE_QUEUE_BACKEND: redis
+      LUKESCRIBE_REDIS_URL: redis://redis:6379/0
+      LUKESCRIBE_API_KEYS: ${LUKESCRIBE_API_KEYS:?API 키 필요}
+    volumes:
+      - luke-store:/data/luke-scribe
+    ports:
+      - "8000:8000"
+
+  api-gpu:
+    build:
+      context: ..
+      dockerfile: docker/Dockerfile.gpu
+    profiles: ["gpu"]
+    depends_on:
+      redis:
+        condition: service_healthy
+    environment:
+      LUKESCRIBE_QUEUE_BACKEND: redis
+      LUKESCRIBE_REDIS_URL: redis://redis:6379/0
+      LUKESCRIBE_API_KEYS: ${LUKESCRIBE_API_KEYS:?API 키 필요}
+    volumes:
+      - luke-store:/data/luke-scribe
+    ports:
+      - "8000:8000"
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+
+  worker:
+    build:
+      context: ..
+      dockerfile: docker/Dockerfile.cpu
+    profiles: ["cpu"]
+    depends_on:
+      redis:
+        condition: service_healthy
+    environment:
+      LUKESCRIBE_QUEUE_BACKEND: redis
+      LUKESCRIBE_REDIS_URL: redis://redis:6379/0
+    command: ["python", "-m", "luke_scribe.cli", "serve"]
+    volumes:
+      - luke-store:/data/luke-scribe
+
+volumes:
+  luke-store: