afe420c620
PyTorch default install pulls ~7GB of CUDA libs, exceeding disk on small VMs. Switching to CPU-only saves ~6GB. Also run create_all before alembic so migrations find existing tables on a fresh Postgres. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
43 lines
1.2 KiB
Docker
43 lines
1.2 KiB
Docker
FROM python:3.12-slim
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# Install system dependencies
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RUN apt-get update && apt-get install -y \
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# Build dependencies
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gcc \
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g++ \
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make \
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# Image processing libraries
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libvips42 \
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libvips-dev \
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# ExifTool for metadata extraction
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libimage-exiftool-perl \
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# FFmpeg for video processing
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ffmpeg \
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# Git for some Python packages
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git \
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# PostgreSQL client (for potential future use)
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postgresql-client \
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# Clean up
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&& rm -rf /var/lib/apt/lists/*
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WORKDIR /app
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# Copy requirements first for better caching
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COPY requirements.txt .
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# Install PyTorch CPU-only FIRST so open-clip-torch doesn't pull the full
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# CUDA build (~7 GB). CPU inference is all we need — the heavy lifting
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# happens through ONNX Runtime.
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RUN pip install --no-cache-dir torch torchvision --index-url https://download.pytorch.org/whl/cpu \
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&& pip install --no-cache-dir -r requirements.txt
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# Copy application code
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COPY . .
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# Create necessary directories
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RUN mkdir -p /data/thumbs /data/db /data/proxies /data/models /app/config
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# Expose port
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EXPOSE 8000
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# Run the application
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CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000", "--reload"] |