603 lines
25 KiB
Docker
603 lines
25 KiB
Docker
# ==============================================================================
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# ConvertX-CN 官方 Docker Image
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# 版本：v0.1.11
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# ==============================================================================
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#
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# 📦 Image 說明：
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# - 這是 ConvertX-CN 官方 Docker Hub Image 的生產 Dockerfile
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# - 已內建完整功能，無需額外擴充
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# - ⚠️ 所有模型已在 build 階段預下載，runtime 不依賴網路
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#
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# 🌍 內建語言支援：
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# - OCR: 英文、繁體中文、簡體中文、日文、韓文、德文、法文
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# - Locale: en_US, zh_TW, zh_CN, ja_JP, ko_KR, de_DE, fr_FR
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# - 字型: Noto CJK, Liberation, 標楷體
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# - LaTeX: CJK、德文、法文、阿拉伯語、希伯來語
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#
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# 🤖 預下載模型清單：
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# - PDFMathTranslate: DocLayout-YOLO ONNX（佈局分析）
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# - BabelDOC: 完整資源包（透過 --warmup）
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# - MinerU: PDF-Extract-Kit-1.0（Pipeline 模型）
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# 包含：DocLayout-YOLO, YOLOv8 MFD, UniMERNet, PaddleOCR, LayoutReader, SLANet
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#
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# 📊 Image 大小：約 8-12 GB（含模型）
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#
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# ⚠️ Base Image：使用 debian:bookworm（穩定版）
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# - 確保 Multi-Arch (amd64/arm64) 構建穩定性
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# - 避免 trixie (testing) 套件同步不穩定問題
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#
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# ==============================================================================
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FROM debian:bookworm-slim AS base
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LABEL org.opencontainers.image.source="https://github.com/pi-docket/ConvertX-CN"
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LABEL org.opencontainers.image.description="ConvertX-CN - 精簡版檔案轉換服務"
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WORKDIR /app
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# 配置 APT 重試機制（解決 Multi-Arch Build 時的網路不穩定問題）
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RUN echo 'Acquire::Retries "5";' > /etc/apt/apt.conf.d/80-retries \
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&& echo 'Acquire::http::Timeout "120";' >> /etc/apt/apt.conf.d/80-retries \
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&& echo 'Acquire::https::Timeout "120";' >> /etc/apt/apt.conf.d/80-retries \
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&& echo 'Acquire::ftp::Timeout "120";' >> /etc/apt/apt.conf.d/80-retries \
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&& echo 'DPkg::Lock::Timeout "120";' >> /etc/apt/apt.conf.d/80-retries
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# install bun
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RUN apt-get update && apt-get install -y --no-install-recommends \
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curl \
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unzip \
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ca-certificates \
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&& rm -rf /var/lib/apt/lists/*
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# if architecture is arm64, use the arm64 version of bun
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RUN ARCH=$(uname -m) && \
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if [ "$ARCH" = "aarch64" ]; then \
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curl -fsSL -o bun-linux-aarch64.zip https://github.com/oven-sh/bun/releases/download/bun-v1.3.6/bun-linux-aarch64.zip; \
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else \
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curl -fsSL -o bun-linux-x64-baseline.zip https://github.com/oven-sh/bun/releases/download/bun-v1.3.6/bun-linux-x64-baseline.zip; \
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fi
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RUN unzip -j bun-linux-*.zip -d /usr/local/bin && \
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rm bun-linux-*.zip && \
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chmod +x /usr/local/bin/bun
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# install dependencies into temp directory
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# this will cache them and speed up future builds
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FROM base AS install
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RUN mkdir -p /temp/dev
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COPY package.json bun.lock /temp/dev/
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RUN cd /temp/dev && bun install --frozen-lockfile
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# install with --production (exclude devDependencies)
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RUN mkdir -p /temp/prod
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COPY package.json bun.lock /temp/prod/
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RUN cd /temp/prod && bun install --frozen-lockfile --production
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FROM base AS prerelease
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WORKDIR /app
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COPY --from=install /temp/dev/node_modules node_modules
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COPY . .
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# ENV NODE_ENV=production
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RUN bun run build
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# copy production dependencies and source code into final image
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FROM base AS release
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# ==============================================================================
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# 依賴安裝（分段安裝，優化 Multi-Arch Build 穩定性）
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# ==============================================================================
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#
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# ✅ 核心轉換工具：完整保留
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# ✅ TexLive：完整 CJK + 德法 + 阿拉伯/希伯來語
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# ✅ OCR：7 種主要語言
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# ✅ 字型：Noto CJK + Liberation + 標楷體
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# ✅ OpenCV：電腦視覺轉換支援
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# ✅ 額外影片編解碼器
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# ✅ PDFMathTranslate：PDF 翻譯引擎
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#
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# 📝 分段安裝說明：
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# - 將套件拆分為多個 RUN 層，避免 QEMU 模擬時記憶體不足
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# - 每段安裝後清理 apt cache，減少中間層大小
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# - 最終 squash 時會合併為單一層
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#
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# ==============================================================================
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# 配置 APT 重試機制（解決 Multi-Arch Build 時的網路不穩定問題）
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RUN echo 'Acquire::Retries "5";' > /etc/apt/apt.conf.d/80-retries \
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&& echo 'Acquire::http::Timeout "120";' >> /etc/apt/apt.conf.d/80-retries \
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&& echo 'Acquire::https::Timeout "120";' >> /etc/apt/apt.conf.d/80-retries \
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&& echo 'Acquire::ftp::Timeout "120";' >> /etc/apt/apt.conf.d/80-retries \
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&& echo 'APT::Get::Assume-Yes "true";' >> /etc/apt/apt.conf.d/80-retries \
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&& echo 'DPkg::Lock::Timeout "120";' >> /etc/apt/apt.conf.d/80-retries
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# 階段 1：基礎系統工具
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RUN apt-get update --fix-missing && apt-get install -y --no-install-recommends \
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locales \
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ca-certificates \
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curl \
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&& rm -rf /var/lib/apt/lists/*
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# 階段 2：核心轉換工具（小型）
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# 注意：dasel 和 resvg 在 bookworm 中不存在，後續用二進位檔案安裝
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RUN apt-get update --fix-missing && apt-get install -y --no-install-recommends \
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assimp-utils \
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dcraw \
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dvisvgm \
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ghostscript \
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graphicsmagick \
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mupdf-tools \
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poppler-utils \
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potrace \
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&& rm -rf /var/lib/apt/lists/*
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# 階段 2.1：安裝 dasel（從 GitHub 下載二進位檔案）
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RUN ARCH=$(uname -m) && \
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if [ "$ARCH" = "aarch64" ]; then \
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DASEL_ARCH="linux_arm64"; \
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else \
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DASEL_ARCH="linux_amd64"; \
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fi && \
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curl -sSLf "https://github.com/TomWright/dasel/releases/download/v2.8.1/dasel_${DASEL_ARCH}" -o /usr/local/bin/dasel && \
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chmod +x /usr/local/bin/dasel
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# 階段 2.2：安裝 resvg（從 GitHub 下載二進位檔案）
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# 注意：resvg 官方只提供 x86_64 版本，ARM64 需從源碼編譯或跳過
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RUN ARCH=$(uname -m) && \
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if [ "$ARCH" = "aarch64" ]; then \
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echo "⚠️ resvg 沒有 ARM64 預編譯版本，跳過安裝（可改用 ImageMagick 或 Inkscape 替代）"; \
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else \
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curl -sSLf "https://github.com/linebender/resvg/releases/download/v0.44.0/resvg-linux-x86_64.tar.gz" -o /tmp/resvg.tar.gz && \
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tar -xzf /tmp/resvg.tar.gz -C /tmp/ && \
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mv /tmp/resvg /usr/local/bin/resvg && \
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chmod +x /usr/local/bin/resvg && \
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rm -rf /tmp/resvg.tar.gz; \
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fi
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# 階段 3：影音處理工具
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RUN apt-get update --fix-missing && apt-get install -y --no-install-recommends \
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ffmpeg \
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libavcodec-extra \
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libva2 \
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&& rm -rf /var/lib/apt/lists/*
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# 階段 4：圖像處理工具
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# 注意：bookworm 使用 imagemagick（版本 6），trixie 才有 imagemagick-7
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RUN apt-get update --fix-missing && apt-get install -y --no-install-recommends \
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imagemagick \
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inkscape \
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libheif-examples \
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libjxl-tools \
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libvips-tools \
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&& rm -rf /var/lib/apt/lists/*
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# 階段 5：文件處理工具
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RUN apt-get update --fix-missing && apt-get install -y --no-install-recommends \
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calibre \
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libemail-outlook-message-perl \
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pandoc \
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&& rm -rf /var/lib/apt/lists/*
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# 階段 6：LibreOffice（最大的套件，單獨安裝）
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RUN apt-get update --fix-missing && apt-get install -y --no-install-recommends \
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libreoffice \
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&& rm -rf /var/lib/apt/lists/*
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# 階段 7：TexLive 基礎
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RUN apt-get update --fix-missing && apt-get install -y --no-install-recommends \
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texlive-base \
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texlive-latex-base \
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texlive-latex-recommended \
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texlive-fonts-recommended \
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texlive-xetex \
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latexmk \
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lmodern \
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&& rm -rf /var/lib/apt/lists/*
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# 階段 8：TexLive 語言包
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RUN apt-get update --fix-missing && apt-get install -y --no-install-recommends \
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texlive-lang-cjk \
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texlive-lang-german \
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texlive-lang-french \
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texlive-lang-arabic \
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texlive-lang-other \
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&& rm -rf /var/lib/apt/lists/*
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# 階段 9：OCR 支援
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RUN apt-get update --fix-missing && apt-get install -y --no-install-recommends \
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tesseract-ocr \
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tesseract-ocr-eng \
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tesseract-ocr-chi-tra \
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tesseract-ocr-chi-sim \
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tesseract-ocr-jpn \
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tesseract-ocr-kor \
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tesseract-ocr-deu \
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tesseract-ocr-fra \
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&& rm -rf /var/lib/apt/lists/*
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# 階段 10：字型
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RUN apt-get update --fix-missing && apt-get install -y --no-install-recommends \
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fonts-noto-cjk \
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fonts-noto-core \
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fonts-noto-color-emoji \
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fonts-liberation \
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&& rm -rf /var/lib/apt/lists/*
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# 階段 11：Python 依賴
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RUN apt-get update --fix-missing && apt-get install -y --no-install-recommends \
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python3 \
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python3-pip \
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python3-numpy \
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python3-tinycss2 \
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python3-opencv \
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pipx \
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&& rm -rf /var/lib/apt/lists/*
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# 階段 12：安裝 Python 工具（pipx）+ huggingface_hub（用於模型下載）
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# 注意：Debian bookworm 使用 PEP 668，需要 --break-system-packages 來安裝系統級套件
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# 注意：markitdown[all] 可能依賴 transformers 或其他 HuggingFace 套件，需清理 cache
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RUN pipx install "markitdown[all]" \
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&& pip3 install --no-cache-dir --break-system-packages huggingface_hub \
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&& rm -rf /root/.cache/huggingface /root/.cache/pip /tmp/*
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# 階段 12-A：安裝 pdf2zh（PDFMathTranslate 引擎）
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# 注意：pipx install 可能觸發依賴套件的隱式下載，結尾必須清理 cache
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RUN pipx install "pdf2zh" \
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&& rm -rf /root/.cache/huggingface /root/.cache/pip /tmp/*
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# 階段 12-B：安裝 babeldoc（BabelDOC 引擎）
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# BabelDOC 是一個 PDF 翻譯工具，與 pdf2zh 類似但使用不同的翻譯方式
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# 注意：babeldoc 依賴 transformers，安裝時可能觸發模型 cache
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RUN (pipx install "babeldoc" || echo "⚠️ babeldoc 安裝失敗，跳過...") \
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&& rm -rf /root/.cache/huggingface /root/.cache/pip /tmp/*
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# 階段 13：安裝 mineru（可能在 arm64 上有問題，加入錯誤處理）
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# 🔴 關鍵：mineru[all] 依賴大量 HuggingFace 套件，安裝過程可能觸發模型下載
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# 必須在同一 RUN 內清理 cache，否則會在 layer diff 中產生數 GB 的重複資料
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RUN (pipx install "mineru[all]" || echo "⚠️ mineru 安裝失敗（可能是 arm64 相容性問題），跳過...") \
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&& rm -rf /root/.cache/huggingface /root/.cache/pip /root/.cache/torch /tmp/*
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# 最終清理（延後到模型下載完成後）
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# Add pipx bin directory to PATH（必須在模型下載前設定）
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ENV PATH="/root/.local/bin:${PATH}"
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# ==============================================================================
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# 🔥 模型預下載區塊（Docker Build 階段）
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# ==============================================================================
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#
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# ⚠️ 重要原則：
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# - 所有模型必須在 build 階段下載完成
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# - runtime 完全不依賴外部網路
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# - 禁止任何隱式下載行為
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#
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# 📦 預下載的模型清單：
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# 1. PDFMathTranslate / pdf2zh
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# - DocLayout-YOLO ONNX 模型（佈局分析）
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# - BabelDOC 相關資源（透過 --warmup）
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# 2. MinerU / magic-pdf
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# - DocLayout-YOLO（佈局分析）
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# - YOLOv8 MFD（公式偵測）
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# - UniMERNet（公式辨識）
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# - PaddleOCR（文字辨識）
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# - LayoutReader（閱讀順序）
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# - SLANet / UNet（表格辨識）
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#
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# ==============================================================================
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# 🔧 BuildKit 優化說明：
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# ==============================================================================
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# 解決 "no space left on device" 的核心策略：
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#
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# 1. 【單一 RUN 原則】
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# 所有模型下載 + cache 清理必須在同一個 RUN 中完成
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# 這樣 BuildKit 在計算 layer diff 時，只會看到「最終狀態」
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# 而不是「下載的 blob cache + 複製的模型」兩份資料
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#
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# 2. 【HuggingFace cache 必須刪除】
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# snapshot_download 會在 ~/.cache/huggingface/hub 下建立：
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# - blobs/：實際的模型檔案（用 SHA256 命名）
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# - snapshots/：指向 blobs 的 symlink 或複製
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# 當 local_dir_use_symlinks=False 時，檔案會被「複製」到目標目錄
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# 如果不刪除 cache，同一份模型會以兩份大小進入 layer diff
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#
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# 3. 【避免 overlayfs 重複壓縮】
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# exporting layers 時，BuildKit 會：
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# - 計算每層的 diff（新增/修改的檔案）
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# - 壓縮 diff 並寫入 /var/lib/buildkit/runc-overlayfs/
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# 如果 cache 沒刪，diff 會包含 cache + 目標目錄，壓縮時空間翻倍
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#
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# ==============================================================================
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# ------------------------------------------------------------------------------
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# 階段 14-UNIFIED：所有模型下載 + 快取清理（單一 RUN 避免 layer 爆炸）
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# ------------------------------------------------------------------------------
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# 🔑 關鍵：這個 RUN 必須包含所有下載操作，並在結尾清理所有 cache
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# 這樣 overlayfs 的 diff 只包含「最終需要的模型檔案」
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# 而不是「cache 結構 + 模型副本」
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# ------------------------------------------------------------------------------
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RUN set -eux && \
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echo "===========================================================" && \
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echo "🚀 開始統一模型下載（單一 RUN 優化 BuildKit layer）" && \
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echo "===========================================================" && \
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\
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# ========================================
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# [1/5] PDFMathTranslate DocLayout-YOLO ONNX 模型
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# ========================================
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echo "" && \
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echo "📥 [1/5] 下載 DocLayout-YOLO ONNX 模型..." && \
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mkdir -p /models/pdfmathtranslate && \
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python3 -c " \
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from huggingface_hub import snapshot_download; \
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snapshot_download( \
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repo_id='wybxc/DocLayout-YOLO-DocStructBench-onnx', \
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local_dir='/models/pdfmathtranslate', \
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allow_patterns=['*.onnx'], \
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local_dir_use_symlinks=False \
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)" && \
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echo "✅ DocLayout-YOLO ONNX 下載完成" && \
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ls -lh /models/pdfmathtranslate/*.onnx 2>/dev/null || ls -lh /models/pdfmathtranslate/ && \
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\
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# 🔥 立即清理 HuggingFace cache（關鍵！避免 blob 重複）
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rm -rf /root/.cache/huggingface && \
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\
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# ========================================
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# [2/5] BabelDOC 資源預下載
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# ========================================
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# 策略：使用 --generate-offline-assets 生成離線包
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# 這比 --warmup 更穩定，因為可以完整驗證所有資源
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echo "" && \
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echo "📥 [2/5] 執行 BabelDOC 資源預下載..." && \
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if command -v babeldoc >/dev/null 2>&1; then \
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BABELDOC_MAX_RETRIES=3; \
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BABELDOC_RETRY_COUNT=0; \
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BABELDOC_SUCCESS=false; \
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mkdir -p /tmp/babeldoc-offline && \
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while [ $BABELDOC_RETRY_COUNT -lt $BABELDOC_MAX_RETRIES ]; do \
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BABELDOC_RETRY_COUNT=$((BABELDOC_RETRY_COUNT + 1)); \
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echo "🔄 BabelDOC 資源下載嘗試 $BABELDOC_RETRY_COUNT/$BABELDOC_MAX_RETRIES..."; \
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if timeout 600 babeldoc --generate-offline-assets /tmp/babeldoc-offline 2>&1; then \
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echo "✅ BabelDOC 離線資源包生成成功"; \
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OFFLINE_PKG=$(ls /tmp/babeldoc-offline/offline_assets_*.zip 2>/dev/null | head -1); \
|
||
if [ -n "$OFFLINE_PKG" ] && [ -f "$OFFLINE_PKG" ]; then \
|
||
echo "📦 找到離線包: $OFFLINE_PKG"; \
|
||
if babeldoc --restore-offline-assets "$OFFLINE_PKG" 2>&1; then \
|
||
echo "✅ BabelDOC 資源已成功恢復到快取"; \
|
||
BABELDOC_SUCCESS=true; \
|
||
break; \
|
||
else \
|
||
echo "⚠️ 資源恢復失敗，重試..."; \
|
||
fi; \
|
||
else \
|
||
echo "⚠️ 未找到離線包，嘗試 warmup 模式..."; \
|
||
if timeout 600 babeldoc --warmup 2>&1; then \
|
||
BABELDOC_SUCCESS=true; \
|
||
break; \
|
||
fi; \
|
||
fi; \
|
||
else \
|
||
echo "⚠️ BabelDOC 資源下載失敗或超時（10分鐘），等待 30 秒後重試..."; \
|
||
sleep 30; \
|
||
fi; \
|
||
done; \
|
||
rm -rf /tmp/babeldoc-offline; \
|
||
if [ "$BABELDOC_SUCCESS" = "true" ]; then \
|
||
echo "✅ BabelDOC 資源預下載完成"; \
|
||
else \
|
||
echo "⚠️ BabelDOC 資源下載在 $BABELDOC_MAX_RETRIES 次嘗試後仍失敗"; \
|
||
echo " BabelDOC 功能將在 runtime 時按需下載資源"; \
|
||
fi; \
|
||
else \
|
||
echo "⚠️ babeldoc 命令不存在，跳過資源預下載"; \
|
||
fi && \
|
||
echo "✅ BabelDOC 步驟完成" && \
|
||
\
|
||
# ========================================
|
||
# [3/5] PDFMathTranslate 多語言字型
|
||
# ========================================
|
||
echo "" && \
|
||
echo "📥 [3/5] 下載 PDFMathTranslate 多語言字型..." && \
|
||
mkdir -p /app && \
|
||
curl -fSL -o /app/GoNotoKurrent-Regular.ttf \
|
||
"https://github.com/satbyy/go-noto-universal/releases/download/v7.0/GoNotoKurrent-Regular.ttf" && \
|
||
curl -fSL -o /app/SourceHanSerifCN-Regular.ttf \
|
||
"https://github.com/timelic/source-han-serif/releases/download/main/SourceHanSerifCN-Regular.ttf" && \
|
||
curl -fSL -o /app/SourceHanSerifTW-Regular.ttf \
|
||
"https://github.com/timelic/source-han-serif/releases/download/main/SourceHanSerifTW-Regular.ttf" && \
|
||
curl -fSL -o /app/SourceHanSerifJP-Regular.ttf \
|
||
"https://github.com/timelic/source-han-serif/releases/download/main/SourceHanSerifJP-Regular.ttf" && \
|
||
curl -fSL -o /app/SourceHanSerifKR-Regular.ttf \
|
||
"https://github.com/timelic/source-han-serif/releases/download/main/SourceHanSerifKR-Regular.ttf" && \
|
||
echo "✅ 字型下載完成" && \
|
||
\
|
||
# ========================================
|
||
# [4/5] MinerU Pipeline 模型
|
||
# ========================================
|
||
echo "" && \
|
||
echo "📥 [4/5] 下載 MinerU Pipeline 模型..." && \
|
||
ARCH=$(uname -m) && \
|
||
if [ "$ARCH" = "aarch64" ]; then \
|
||
echo "⚠️ ARM64 架構：MinerU 可能不完全支援，嘗試下載模型..."; \
|
||
fi && \
|
||
if command -v mineru-models-download >/dev/null 2>&1; then \
|
||
echo "使用 mineru-models-download CLI..."; \
|
||
mineru-models-download -s huggingface -m pipeline 2>&1 || true; \
|
||
echo "mineru.json 內容："; \
|
||
cat /root/mineru.json 2>/dev/null || echo "(未生成)"; \
|
||
else \
|
||
echo "mineru-models-download 不可用，跳過 MinerU 模型下載"; \
|
||
fi && \
|
||
echo "✅ MinerU 模型下載步驟完成" && \
|
||
\
|
||
# 🔥 再次清理 HuggingFace cache（MinerU 也會產生）
|
||
rm -rf /root/.cache/huggingface && \
|
||
\
|
||
# ========================================
|
||
# [5/5] 驗證 + mineru.json 補充
|
||
# ========================================
|
||
echo "" && \
|
||
echo "📥 [5/5] 驗證 MinerU 設定檔..." && \
|
||
mkdir -p /root && \
|
||
if [ -f /root/mineru.json ]; then \
|
||
echo "✅ mineru.json 已由 mineru-models-download 生成"; \
|
||
cat /root/mineru.json; \
|
||
else \
|
||
echo "⚠️ mineru.json 不存在，建立預設設定..."; \
|
||
echo '{"models-dir":{"pipeline":"","vlm":""},"model-source":"huggingface","latex-delimiter-config":{"display":{"left":"$$","right":"$$"},"inline":{"left":"$","right":"$"}}}' > /root/mineru.json; \
|
||
fi && \
|
||
echo "" && \
|
||
\
|
||
# ========================================
|
||
# 🔥 最終 Cache 清理（關鍵！避免 overlayfs diff 爆炸）
|
||
# ========================================
|
||
echo "===========================================================" && \
|
||
echo "🧹 清理所有下載快取（降低 layer diff 大小）" && \
|
||
echo "===========================================================" && \
|
||
# HuggingFace Hub cache（最大宗！包含所有 blob）
|
||
rm -rf /root/.cache/huggingface && \
|
||
# pip / Python build cache
|
||
rm -rf /root/.cache/pip && \
|
||
rm -rf /root/.cache/uv && \
|
||
# pipx cache
|
||
rm -rf /root/.local/pipx/.cache && \
|
||
# 通用 cache 目錄
|
||
rm -rf /tmp/* && \
|
||
rm -rf /var/tmp/* && \
|
||
# Python bytecode cache（可選，節省少量空間）
|
||
find /root/.local -type d -name "__pycache__" -exec rm -rf {} + 2>/dev/null || true && \
|
||
find /usr -type d -name "__pycache__" -exec rm -rf {} + 2>/dev/null || true && \
|
||
\
|
||
echo "" && \
|
||
echo "===========================================================" && \
|
||
echo "📋 模型檔案驗證" && \
|
||
echo "===========================================================" && \
|
||
echo "" && \
|
||
echo "🔹 PDFMathTranslate 模型：" && \
|
||
ONNX_COUNT=$(find /models/pdfmathtranslate -name "*.onnx" 2>/dev/null | wc -l) && \
|
||
if [ "$ONNX_COUNT" -gt 0 ]; then \
|
||
echo " ✅ 找到 $ONNX_COUNT 個 ONNX 模型："; \
|
||
ls -lh /models/pdfmathtranslate/*.onnx 2>/dev/null || find /models/pdfmathtranslate -name "*.onnx" -exec ls -lh {} \;; \
|
||
else \
|
||
echo " ❌ /models/pdfmathtranslate 中沒有 ONNX 模型"; \
|
||
fi && \
|
||
echo "" && \
|
||
echo "🔹 PDFMathTranslate 字型：" && \
|
||
ls -lh /app/*.ttf 2>/dev/null || echo " ⚠️ 無字型檔案" && \
|
||
echo "" && \
|
||
echo "🔹 BabelDOC 快取：" && \
|
||
if [ -d "/root/.cache/babeldoc" ]; then \
|
||
echo " ✅ BabelDOC 快取目錄存在"; \
|
||
du -sh /root/.cache/babeldoc 2>/dev/null || true; \
|
||
else \
|
||
echo " ⚠️ BabelDOC 快取目錄不存在（可能需要 runtime 下載）"; \
|
||
fi && \
|
||
echo "" && \
|
||
echo "🔹 MinerU 模型目錄：" && \
|
||
if [ -f /root/mineru.json ]; then \
|
||
MINERU_PIPELINE_DIR=$(python3 -c "import json; f=open('/root/mineru.json'); d=json.load(f); print(d.get('models-dir',{}).get('pipeline',''))" 2>/dev/null || echo ""); \
|
||
if [ -n "$MINERU_PIPELINE_DIR" ] && [ -d "$MINERU_PIPELINE_DIR" ]; then \
|
||
echo " ✅ MinerU Pipeline 模型目錄存在: $MINERU_PIPELINE_DIR"; \
|
||
du -sh "$MINERU_PIPELINE_DIR" 2>/dev/null || true; \
|
||
else \
|
||
echo " ⚠️ MinerU Pipeline 模型目錄不存在或未設定"; \
|
||
echo " 設定路徑: ${MINERU_PIPELINE_DIR:-'(未設定)'}"; \
|
||
fi; \
|
||
else \
|
||
echo " ⚠️ mineru.json 不存在（MinerU 未正確安裝）"; \
|
||
fi && \
|
||
echo "" && \
|
||
echo "🔹 確認 HuggingFace cache 已清除：" && \
|
||
if [ -d "/root/.cache/huggingface" ]; then \
|
||
echo " ❌ 警告：HuggingFace cache 仍存在！"; \
|
||
du -sh /root/.cache/huggingface 2>/dev/null || true; \
|
||
else \
|
||
echo " ✅ HuggingFace cache 已清除"; \
|
||
fi && \
|
||
echo "" && \
|
||
echo "===========================================================" && \
|
||
echo "✅ 模型下載完成，所有快取已清理" && \
|
||
echo "==========================================================="
|
||
|
||
# PDFMathTranslate 環境變數
|
||
ENV PDFMATHTRANSLATE_MODELS_PATH="/models/pdfmathtranslate"
|
||
ENV NOTO_FONT_PATH="/app/GoNotoKurrent-Regular.ttf"
|
||
|
||
# BabelDOC 環境變數
|
||
ENV BABELDOC_CACHE_PATH="/root/.cache/babeldoc"
|
||
ENV BABELDOC_SERVICE="google"
|
||
|
||
# MinerU 環境變數
|
||
# 注意：如果 build 時模型下載成功，mineru.json 會設定為 local
|
||
# 如果下載失敗，允許 runtime 從 huggingface 下載
|
||
# ENV MINERU_MODEL_SOURCE="local" # 由 mineru.json 控制
|
||
# ENV HF_HUB_OFFLINE="1" # 不強制離線，允許 fallback
|
||
|
||
# ==============================================================================
|
||
# 最終清理（模型下載完成後）
|
||
# ==============================================================================
|
||
RUN rm -rf /usr/share/doc/texlive* \
|
||
&& rm -rf /usr/share/texlive/texmf-dist/doc \
|
||
&& rm -rf /usr/share/doc/* \
|
||
&& rm -rf /usr/share/man/* \
|
||
&& rm -rf /usr/share/info/*
|
||
|
||
# ==============================================================================
|
||
# 設定 locale（支援中文 PDF 避免亂碼）
|
||
# ==============================================================================
|
||
RUN sed -i 's/# en_US.UTF-8 UTF-8/en_US.UTF-8 UTF-8/' /etc/locale.gen && \
|
||
sed -i 's/# zh_TW.UTF-8 UTF-8/zh_TW.UTF-8 UTF-8/' /etc/locale.gen && \
|
||
sed -i 's/# zh_CN.UTF-8 UTF-8/zh_CN.UTF-8 UTF-8/' /etc/locale.gen && \
|
||
sed -i 's/# ja_JP.UTF-8 UTF-8/ja_JP.UTF-8 UTF-8/' /etc/locale.gen && \
|
||
sed -i 's/# ko_KR.UTF-8 UTF-8/ko_KR.UTF-8 UTF-8/' /etc/locale.gen && \
|
||
sed -i 's/# de_DE.UTF-8 UTF-8/de_DE.UTF-8 UTF-8/' /etc/locale.gen && \
|
||
sed -i 's/# fr_FR.UTF-8 UTF-8/fr_FR.UTF-8 UTF-8/' /etc/locale.gen && \
|
||
locale-gen
|
||
|
||
# 預設使用 zh_TW.UTF-8 確保中文 PDF 正確顯示
|
||
ENV LANG=zh_TW.UTF-8
|
||
ENV LC_ALL=zh_TW.UTF-8
|
||
|
||
# ==============================================================================
|
||
# 安裝自訂字型（標楷體等台灣常用字型）
|
||
# ==============================================================================
|
||
RUN mkdir -p /usr/share/fonts/truetype/custom
|
||
COPY fonts/ /usr/share/fonts/truetype/custom/
|
||
RUN fc-cache -fv
|
||
|
||
# ==============================================================================
|
||
# Install VTracer binary（向量追蹤工具）
|
||
# ==============================================================================
|
||
RUN ARCH=$(uname -m) && \
|
||
if [ "$ARCH" = "aarch64" ]; then \
|
||
VTRACER_ASSET="vtracer-aarch64-unknown-linux-musl.tar.gz"; \
|
||
else \
|
||
VTRACER_ASSET="vtracer-x86_64-unknown-linux-musl.tar.gz"; \
|
||
fi && \
|
||
curl -L -o /tmp/vtracer.tar.gz "https://github.com/visioncortex/vtracer/releases/download/0.6.4/${VTRACER_ASSET}" && \
|
||
tar -xzf /tmp/vtracer.tar.gz -C /tmp/ && \
|
||
mv /tmp/vtracer /usr/local/bin/vtracer && \
|
||
chmod +x /usr/local/bin/vtracer && \
|
||
rm /tmp/vtracer.tar.gz
|
||
|
||
COPY --from=install /temp/prod/node_modules node_modules
|
||
COPY --from=prerelease /app/public/ /app/public/
|
||
COPY --from=prerelease /app/dist /app/dist
|
||
|
||
# 複製模型驗證腳本
|
||
COPY scripts/verify-models.sh /app/scripts/verify-models.sh
|
||
RUN chmod +x /app/scripts/verify-models.sh
|
||
|
||
RUN mkdir data
|
||
|
||
EXPOSE 3000/tcp
|
||
|
||
# ==============================================================================
|
||
# 環境變數
|
||
# ==============================================================================
|
||
# Calibre 需要
|
||
ENV QTWEBENGINE_CHROMIUM_FLAGS="--no-sandbox"
|
||
# Pandoc PDF 引擎（使用 pdflatex 以獲得最佳相容性）
|
||
ENV PANDOC_PDF_ENGINE=pdflatex
|
||
# Node 環境
|
||
ENV NODE_ENV=production
|
||
# PDFMathTranslate 預設翻譯服務（可透過環境變數覆寫）
|
||
ENV PDFMATHTRANSLATE_SERVICE="google"
|
||
|
||
ENTRYPOINT [ "bun", "run", "dist/src/index.js" ]
|