mirror of
https://github.com/snapotter-hq/SnapOtter.git
synced 2026-08-03 07:46:42 +02:00
feat: unified Docker image with GPU auto-detection
- Remove VARIANT/GPU build args, single image for all platforms - amd64: nvidia/cuda base with GPU Python packages - arm64: node base with CPU Python packages - Add tini as PID 1 for proper signal handling - Replace npx tsx with node --import tsx - Split pip install into base + tool layers for better caching - Add NVIDIA_VISIBLE_DEVICES env vars for container toolkit - Suppress Python ML library log noise - Increase healthcheck start-period to 60s - Remove STIRLING_VARIANT env var - Remove lama-cleaner from pip installs
This commit is contained in:
+67
-78
@@ -1,12 +1,9 @@
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# syntax=docker/dockerfile:1
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# ============================================
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# Stirling Image - Production Dockerfile
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# Multi-stage build for single-container deployment
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# Stirling Image - Unified Production Dockerfile
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# Single image: GPU auto-detected on amd64, CPU on arm64
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# ============================================
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ARG VARIANT=full
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ARG GPU=false
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# ============================================
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# Stage 1: Build the frontend (Vite + React)
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# ============================================
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@@ -39,25 +36,22 @@ RUN --mount=type=cache,id=turbo-cache,target=/app/.turbo \
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pnpm --filter @stirling-image/web build
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# ============================================
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# Stage 2: Base image selection
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# Stage 2: Platform-specific base images
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# ============================================
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FROM node:22-bookworm AS base-cpu
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FROM nvidia/cuda:12.6.3-runtime-ubuntu24.04 AS base-gpu
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# Select base: GPU=false -> base-cpu, GPU=true -> base-gpu
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FROM base-cpu AS production-base-false
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FROM base-gpu AS production-base-true
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FROM node:22-bookworm AS base-linux-arm64
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FROM nvidia/cuda:12.6.3-runtime-ubuntu24.04 AS base-linux-amd64
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# ============================================
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# Stage 3: Production runtime
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# ============================================
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FROM production-base-${GPU} AS production
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ARG TARGETOS
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ARG TARGETARCH
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FROM base-${TARGETOS}-${TARGETARCH} AS production
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ARG VARIANT
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ARG GPU
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ARG TARGETARCH
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# Install Node.js when using CUDA base (node:22-bookworm already has it)
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RUN if [ "$GPU" = "true" ]; then \
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# Install Node.js on amd64 (CUDA base has no Node; arm64 base already has it)
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RUN if [ "$TARGETARCH" = "amd64" ]; then \
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apt-get update && apt-get install -y --no-install-recommends \
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curl ca-certificates gnupg && \
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mkdir -p /etc/apt/keyrings && \
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@@ -71,67 +65,55 @@ RUN if [ "$GPU" = "true" ]; then \
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RUN corepack enable && corepack prepare pnpm@9.15.4 --activate
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# System dependencies shared by all variants
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# System dependencies (all platforms)
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RUN apt-get update && apt-get install -y --no-install-recommends \
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tini \
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imagemagick \
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libraw-dev \
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potrace \
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curl \
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gosu \
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libheif-examples \
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python3 python3-pip python3-venv python3-dev \
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tesseract-ocr tesseract-ocr-eng tesseract-ocr-deu tesseract-ocr-fra tesseract-ocr-spa \
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build-essential \
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libgl1 libglib2.0-0 \
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&& rm -rf /var/lib/apt/lists/*
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# Python/ML system dependencies (full variant only)
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RUN if [ "$VARIANT" = "full" ]; then \
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apt-get update && apt-get install -y --no-install-recommends \
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python3 python3-pip python3-venv python3-dev \
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tesseract-ocr tesseract-ocr-eng tesseract-ocr-deu tesseract-ocr-fra tesseract-ocr-spa \
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build-essential \
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libgl1 libglib2.0-0 \
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&& rm -rf /var/lib/apt/lists/* \
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# Python venv - Layer 1: Base packages (rarely change, ~3 GB)
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RUN python3 -m venv /opt/venv && \
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/opt/venv/bin/pip install --upgrade pip && \
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/opt/venv/bin/pip install \
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Pillow==11.1.0 \
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numpy==1.26.4 \
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opencv-python-headless==4.10.0.84
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# Platform-conditional ONNX runtime
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RUN if [ "$TARGETARCH" = "amd64" ]; then \
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/opt/venv/bin/pip install onnxruntime-gpu==1.20.1 \
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; else \
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/opt/venv/bin/pip install onnxruntime==1.20.1 \
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; fi
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# Python venv + ML packages + model weights (full variant only)
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COPY packages/ai/python/requirements.txt /tmp/requirements.txt
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COPY packages/ai/python/requirements-gpu.txt /tmp/requirements-gpu.txt
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RUN if [ "$VARIANT" = "full" ]; then \
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python3 -m venv /opt/venv && \
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/opt/venv/bin/pip install --upgrade pip && \
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if [ "$GPU" = "true" ]; then \
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/opt/venv/bin/pip install \
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Pillow numpy opencv-python-headless onnxruntime-gpu && \
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(/opt/venv/bin/pip install rembg || echo "WARNING: rembg not installed") && \
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(/opt/venv/bin/pip install realesrgan \
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--extra-index-url https://download.pytorch.org/whl/cu126 \
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|| echo "WARNING: realesrgan not installed") && \
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(/opt/venv/bin/pip install paddlepaddle-gpu paddleocr || echo "WARNING: PaddleOCR not installed") && \
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(/opt/venv/bin/pip install mediapipe || echo "WARNING: mediapipe not installed") && \
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(/opt/venv/bin/pip install lama-cleaner || echo "WARNING: lama-cleaner not installed") && \
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(/opt/venv/bin/pip install seam-carving || echo "WARNING: seam-carving not installed") \
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; else \
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/opt/venv/bin/pip install \
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Pillow numpy opencv-python-headless onnxruntime && \
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(/opt/venv/bin/pip install "rembg[cpu]" || echo "WARNING: rembg not installed") && \
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(/opt/venv/bin/pip install realesrgan || echo "WARNING: realesrgan not installed") && \
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(/opt/venv/bin/pip install paddlepaddle paddleocr || echo "WARNING: PaddleOCR not installed") && \
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(/opt/venv/bin/pip install mediapipe || echo "WARNING: mediapipe not installed") && \
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(/opt/venv/bin/pip install lama-cleaner || echo "WARNING: lama-cleaner not installed") && \
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(/opt/venv/bin/pip install seam-carving || echo "WARNING: seam-carving not installed") \
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; fi \
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; fi && rm -f /tmp/requirements.txt /tmp/requirements-gpu.txt
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# Python venv - Layer 2: Tool packages (change occasionally, ~2 GB)
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RUN if [ "$TARGETARCH" = "amd64" ]; then \
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/opt/venv/bin/pip install rembg==2.0.62 && \
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/opt/venv/bin/pip install realesrgan==0.3.0 \
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--extra-index-url https://download.pytorch.org/whl/cu126 && \
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/opt/venv/bin/pip install paddlepaddle-gpu==3.0.0 paddleocr==2.9.1 \
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; else \
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/opt/venv/bin/pip install "rembg[cpu]==2.0.62" && \
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/opt/venv/bin/pip install realesrgan==0.3.0 && \
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/opt/venv/bin/pip install paddlepaddle==3.0.0 paddleocr==2.9.1 \
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; fi
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RUN /opt/venv/bin/pip install \
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mediapipe==0.10.21 \
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seam-carving==1.1.0
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# Pre-download and verify all ML models
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COPY docker/download_models.py /tmp/download_models.py
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RUN if [ "$VARIANT" = "full" ]; then \
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/opt/venv/bin/python3 /tmp/download_models.py && \
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/opt/venv/bin/python3 -c "\
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try: \
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from paddleocr import PaddleOCR; \
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print('Downloading PaddleOCR models...'); \
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ocr = PaddleOCR(use_angle_cls=True, lang='en', show_log=False); \
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print('PaddleOCR models ready'); \
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except: print('PaddleOCR model pre-download skipped') \
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" 2>/dev/null || echo "WARNING: Could not pre-download PaddleOCR models" \
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; fi && rm -f /tmp/download_models.py
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RUN /opt/venv/bin/python3 /tmp/download_models.py && rm -f /tmp/download_models.py
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WORKDIR /app
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@@ -151,10 +133,8 @@ RUN --mount=type=cache,id=pnpm-store,target=/root/.local/share/pnpm/store/v3 \
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pnpm install --frozen-lockfile --prod
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# Remove build tools no longer needed in production
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RUN if [ "$VARIANT" = "full" ]; then \
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apt-get purge -y --auto-remove build-essential python3-dev && \
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rm -rf /var/lib/apt/lists/* \
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; fi
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RUN apt-get purge -y --auto-remove build-essential python3-dev && \
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rm -rf /var/lib/apt/lists/*
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# Copy source code for API (tsx runs TS directly - no build step needed)
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COPY apps/api/src ./apps/api/src
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@@ -170,9 +150,9 @@ COPY packages/ai/python ./packages/ai/python
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COPY --from=builder /app/apps/web/dist ./apps/web/dist
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# Create required directories
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RUN mkdir -p /data /tmp/workspace
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RUN mkdir -p /data /data/files /tmp/workspace
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# Environment defaults (matching PRD Section 16.1)
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# Environment defaults
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ENV PORT=1349 \
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NODE_ENV=production \
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AUTH_ENABLED=true \
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@@ -192,13 +172,20 @@ ENV PORT=1349 \
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MAX_BATCH_SIZE=200 \
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CONCURRENT_JOBS=3 \
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MAX_MEGAPIXELS=100 \
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RATE_LIMIT_PER_MIN=100 \
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STIRLING_VARIANT=${VARIANT}
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RATE_LIMIT_PER_MIN=100
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# NVIDIA Container Toolkit env vars (harmless on non-GPU systems)
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ENV NVIDIA_VISIBLE_DEVICES=all \
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NVIDIA_DRIVER_CAPABILITIES=compute,utility
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# Suppress noisy ML library output in docker logs
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ENV PYTHONWARNINGS=ignore \
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TF_CPP_MIN_LOG_LEVEL=3 \
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PADDLE_PDX_DISABLE_MODEL_SOURCE_CHECK=True
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# Create non-root user for runtime
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RUN groupadd -r stirling && useradd -r -g stirling -d /app -s /sbin/nologin stirling
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RUN chown -R stirling:stirling /app /data /tmp/workspace && \
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([ -d /opt/venv ] && chown -R stirling:stirling /opt/venv || true)
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RUN chown -R stirling:stirling /app /data /tmp/workspace /opt/venv
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# Entrypoint fixes volume permissions then drops to stirling via gosu
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COPY docker/entrypoint.sh /usr/local/bin/entrypoint.sh
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@@ -206,8 +193,10 @@ RUN chmod +x /usr/local/bin/entrypoint.sh
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EXPOSE 1349
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HEALTHCHECK --interval=30s --timeout=5s --start-period=15s --retries=3 \
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HEALTHCHECK --interval=30s --timeout=5s --start-period=60s --retries=3 \
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CMD curl -f http://localhost:1349/api/v1/health || exit 1
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ENTRYPOINT ["entrypoint.sh"]
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CMD ["npx", "tsx", "apps/api/src/index.ts"]
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# tini as PID 1 for zombie reaping + signal forwarding
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# node --import tsx replaces npx tsx to avoid npx eating signals
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ENTRYPOINT ["tini", "--", "entrypoint.sh"]
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CMD ["node", "--import", "tsx", "apps/api/src/index.ts"]
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