mirror of
https://github.com/tcsenpai/youlama.git
synced 2025-06-04 02:10:21 +00:00
38 lines
1.1 KiB
Docker
38 lines
1.1 KiB
Docker
FROM nvidia/cuda:12.3.2-cudnn9-devel-ubuntu22.04
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# Set environment variables
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ENV DEBIAN_FRONTEND=noninteractive
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ENV PYTHONUNBUFFERED=1
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# Define the path to PyTorch's bundled NVIDIA libraries (adjust if necessary for your specific Python version/setup)
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# This path assumes nvidia-cudnn-cuXX or similar packages install here.
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ENV PYTORCH_NVIDIA_LIBS_DIR /usr/local/lib/python3.10/dist-packages/nvidia/cudnn/lib
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# Prepend PyTorch's NVIDIA library directory to LD_LIBRARY_PATH
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# Also include the standard NVIDIA paths that the base image might set for other CUDA components.
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ENV LD_LIBRARY_PATH=${PYTORCH_NVIDIA_LIBS_DIR}:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
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# Install system dependencies
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RUN apt-get update && apt-get install -y \
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python3.10 \
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python3-pip \
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ffmpeg \
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&& rm -rf /var/lib/apt/lists/*
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# Set working directory
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WORKDIR /app
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# Copy requirements first to leverage Docker cache
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COPY requirements.txt .
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# Install Python dependencies
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RUN pip3 install --no-cache-dir -r requirements.txt
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# Copy application code
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COPY . .
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# Expose port
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EXPOSE 7860
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# Set entrypoint
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ENTRYPOINT ["python3", "app.py"] |