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Update Dockerfile and install runai-model-streamer[gcs] package #26464

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merged 1 commit into from
Oct 9, 2025
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Update Dockerfile and install runai-model-streamer[gcs] package #26464

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2 changes: 1 addition & 1 deletion docker/Dockerfile
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Expand Up @@ -542,7 +542,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
else \
BITSANDBYTES_VERSION="0.46.1"; \
fi; \
uv pip install --system accelerate hf_transfer modelscope "bitsandbytes>=${BITSANDBYTES_VERSION}" 'timm>=1.0.17' 'runai-model-streamer[s3]>=0.14.0'
uv pip install --system accelerate hf_transfer modelscope "bitsandbytes>=${BITSANDBYTES_VERSION}" 'timm>=1.0.17' 'runai-model-streamer[s3,gcs]>=0.14.0'
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high

For reproducible builds, especially in a production Docker image (vllm-openai-base), it's crucial to pin dependency versions. The packages accelerate, hf_transfer, and modelscope are not pinned to a specific version. This could lead to unexpected issues or breakages in the future if a new version of these packages is released with breaking changes.

I recommend pinning these packages to known working versions using ==. For example:

    uv pip install --system \
        accelerate==<known_good_version> \
        hf_transfer==<known_good_version> \
        modelscope==<known_good_version> \
        "bitsandbytes>=${BITSANDBYTES_VERSION}" \
        'timm>=1.0.17' \
        'runai-model-streamer[s3,gcs]>=0.14.0'

While other packages in this line have minimum versions (>=), using exact versions (==) is generally safer for production images to ensure build stability.


ENV VLLM_USAGE_SOURCE production-docker-image

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