init repo

Dockerfile

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+# DocProcesser Dockerfile
+# Optimized for RTX 5080 GPU deployment
+
+# Use NVIDIA CUDA base image with Python 3.11
+FROM nvidia/cuda:12.8.0-runtime-ubuntu24.04
+
+# Set environment variables
+ENV PYTHONUNBUFFERED=1 \
+    PYTHONDONTWRITEBYTECODE=1 \
+    PIP_NO_CACHE_DIR=1 \
+    PIP_DISABLE_PIP_VERSION_CHECK=1
+
+# Set working directory
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    python3.11 \
+    python3.11-venv \
+    python3.11-dev \
+    python3-pip \
+    libgl1-mesa-glx \
+    libglib2.0-0 \
+    libsm6 \
+    libxext6 \
+    libxrender-dev \
+    libgomp1 \
+    curl \
+    && rm -rf /var/lib/apt/lists/* \
+    && ln -sf /usr/bin/python3.11 /usr/bin/python \
+    && ln -sf /usr/bin/python3.11 /usr/bin/python3
+
+# Install uv for fast package management
+RUN curl -LsSf https://astral.sh/uv/install.sh | sh
+ENV PATH="/root/.local/bin:$PATH"
+
+# Copy dependency files first for better caching
+COPY pyproject.toml ./
+
+# Create virtual environment and install dependencies
+RUN uv venv /app/.venv
+ENV PATH="/app/.venv/bin:$PATH"
+ENV VIRTUAL_ENV="/app/.venv"
+
+RUN uv pip install -i https://pypi.tuna.tsinghua.edu.cn/simple -e .
+
+# Copy application code
+COPY app/ ./app/
+
+# Create model directories (models should be mounted at runtime)
+RUN mkdir -p /app/app/model/DocLayout /app/app/model/PP-DocLayout
+
+# Expose port
+EXPOSE 8053
+
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
+    CMD curl -f http://localhost:8053/health || exit 1
+
+# Run the application
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8053", "--workers", "1"]
+