mirror of
https://github.com/dogkeeper886/ollama37.git
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8380ca93f8
- Add LD_LIBRARY_PATH to CMake and build steps for GCC 10 libraries - Copy GCC 10 runtime libraries (libstdc++.so.6, libgcc_s.so.1) to output - Update runtime Dockerfile to use minimal CUDA runtime packages - Add -buildvcs=false flag to Go build to avoid Git VCS errors - Simplify runtime container to only include necessary CUDA libraries - Fix library path configuration for proper runtime library loading
47 lines
1.5 KiB
Docker
47 lines
1.5 KiB
Docker
FROM rockylinux/rockylinux:8
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# Install only CUDA runtime libraries (not the full toolkit)
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# The host system provides the NVIDIA driver at runtime via --gpus flag
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RUN dnf -y install dnf-plugins-core\
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&& dnf -y config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo\
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&& dnf -y install cuda-cudart-11-4 libcublas-11-4 \
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&& dnf clean all
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# Create directory structure
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RUN mkdir -p /usr/local/bin /usr/local/lib/ollama
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# Copy the ollama binary from build output
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COPY docker/output/ollama /usr/local/bin/ollama
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# Copy all shared libraries from build output (includes ollama libs + GCC 10 runtime libs)
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COPY docker/output/lib/ /usr/local/lib/ollama/
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# Set library path to include our ollama libraries first
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# This includes:
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# - Ollama CUDA/GGML libraries
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# - GCC 10 runtime libraries (libstdc++.so.6, libgcc_s.so.1)
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# - System CUDA libraries
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ENV LD_LIBRARY_PATH=/usr/local/lib/ollama:/usr/local/cuda-11.4/lib64:/usr/lib64
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# Base image already sets these, but we can override if needed:
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# NVIDIA_DRIVER_CAPABILITIES=compute,utility
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# NVIDIA_VISIBLE_DEVICES=all
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# Ollama server configuration
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ENV OLLAMA_HOST=0.0.0.0:11434
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# Expose the Ollama API port
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EXPOSE 11434
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# Create a data directory for models
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RUN mkdir -p /root/.ollama
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VOLUME ["/root/.ollama"]
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# Health check
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HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
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CMD /usr/local/bin/ollama list || exit 1
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# Set entrypoint and default command
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ENTRYPOINT ["/usr/local/bin/ollama"]
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CMD ["serve"]
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