33 lines
1.6 KiB
Docker
33 lines
1.6 KiB
Docker
FROM python:3.11-slim
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WORKDIR /app
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# 系统依赖（OCR、图像处理所需的共享库）
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RUN apt-get update && apt-get install -y --no-install-recommends \
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libgl1 libglib2.0-0 libsm6 libxext6 libxrender1 \
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&& rm -rf /var/lib/apt/lists/*
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COPY requirements.txt .
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RUN pip install --no-cache-dir -r requirements.txt
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COPY app/ ./app/
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# 构建时预下载模型（需要实际转换才会触发 HuggingFace 模型下载）
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RUN python -c "\
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import tempfile, os; \
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pdf = b'%PDF-1.4\n1 0 obj<</Type/Catalog/Pages 2 0 R>>endobj\n2 0 obj<</Type/Pages/Kids[3 0 R]/Count 1>>endobj\n3 0 obj<</Type/Page/MediaBox[0 0 612 792]/Parent 2 0 R/Contents 4 0 R/Resources<</Font<</F1 5 0 R>>>>>>endobj\n4 0 obj<</Length 44>>stream\nBT /F1 12 Tf 100 700 Td (hello) Tj ET\nendstream\nendobj\n5 0 obj<</Type/Font/Subtype/Type1/BaseFont/Helvetica>>endobj\nxref\n0 6\n0000000000 65535 f \n0000000009 00000 n \n0000000058 00000 n \n0000000115 00000 n \n0000000266 00000 n \n0000000360 00000 n \ntrailer<</Size 6/Root 1 0 R>>\nstartxref\n454\n%%EOF'; \
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f = tempfile.NamedTemporaryFile(suffix='.pdf', delete=False); f.write(pdf); f.close(); \
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from docling.document_converter import DocumentConverter; \
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conv = DocumentConverter(); \
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try: conv.convert(f.name) \
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except: pass \
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finally: os.unlink(f.name); \
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print('Models pre-downloaded successfully')"
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EXPOSE 3007
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HEALTHCHECK --interval=30s --timeout=10s --retries=3 --start-period=120s \
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CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:3007/health')" || exit 1
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CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "3007"]
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