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auto-stock/.claude/settings.local.json
shuim 19d25e5528 perf: NAS 도커 빌드 시간 단축 — CPU 전용 torch + 빌드 캐시 마운트 
DS1517+(Atom C2538)에서 빌드가 30분 이상 걸리던 원인 두 가지를 제거.

1. PyTorch CPU 전용 휠 사용 (backend)
   PyPI 기본 torch 휠은 nvidia-cublas/cudnn 등 CUDA 패키지를 수 GB
   함께 내려받는데 NAS에는 GPU가 없어 전부 불필요했다.
   download.pytorch.org/whl/cpu 에서 먼저 설치하면 requirements.txt 의
   torch 줄은 충족되어 건너뛴다. ml_ensemble 은 이미 지연 임포트라 동작 동일.

2. pip/npm 캐시를 빌드 간 재사용 (backend, mcp-server, frontend)
   --no-cache-dir 제거하고 RUN --mount=type=cache 로 전환.
   requirements.txt 가 바뀌어도 받아둔 휠은 재다운로드하지 않는다.
   Jenkinsfile 에 DOCKER_BUILDKIT/COMPOSE_DOCKER_CLI_BUILD 추가.

부수: frontend Dockerfile 의 FromAsCasing 경고 정리 (as build → AS build).
세 Dockerfile 모두 docker build --check 통과.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-09-19 23:57:21 +09:00

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},
"enableAllProjectMcpServers": true,
"enabledMcpjsonServers": [
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],
"hooks": {
"UserPromptSubmit": [
{
"hooks": [
{
"type": "command",
"command": "python3 \"$CLAUDE_PROJECT_DIR/.claude/hooks/auto-orchestrate.py\"",
"timeout": 10,
"statusMessage": "오케스트레이션 모드 판정 중..."
}
]
}
]
}
}
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