Docker拉取命令

docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v4.1.0-cpu
docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v4.1.0-cpu  docker.io/xprobe/xinference:v4.1.0-cpu

Containerd拉取命令

ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v4.1.0-cpu
ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v4.1.0-cpu  docker.io/xprobe/xinference:v4.1.0-cpu

Shell快速替换命令

sed -i 's#xprobe/xinference:v4.1.0-cpu#swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v4.1.0-cpu#' deployment.yaml

Ansible快速分发-Docker

#ansible k8s -m shell -a 'docker pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v4.1.0-cpu && docker tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v4.1.0-cpu  docker.io/xprobe/xinference:v4.1.0-cpu'

Ansible快速分发-Containerd

#ansible k8s -m shell -a 'ctr images pull swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v4.1.0-cpu && ctr images tag  swr.cn-north-4.myhuaweicloud.com/ddn-k8s/docker.io/xprobe/xinference:v4.1.0-cpu  docker.io/xprobe/xinference:v4.1.0-cpu'

镜像构建历史

# 2026-10-25 15:41:26  0.00B 设置默认要执行的命令
CMD ["/bin/bash"]
                        
# 2026-10-25 15:41:26  0.00B 配置容器启动时运行的命令
ENTRYPOINT []
                        
# 2026-10-25 15:41:26  264.24MB 执行命令并创建新的镜像层
RUN |1 PIP_INDEX=https://pypi.org/simple /bin/sh -c NO_WEB_UI=1 pip install -i "$PIP_INDEX" --no-deps "." &&     python -c "import onnxruntime as ort; assert 'CPUExecutionProvider' in ort.get_available_providers(); assert 'CUDAExecutionProvider' not in ort.get_available_providers()" # buildkit
                        
# 2026-10-25 15:41:08  0.00B 设置工作目录为/opt/inference
WORKDIR /opt/inference
                        
# 2026-10-25 15:41:08  6.17MB 复制新文件或目录到容器中
COPY /opt/inference/xinference/ui/web/dist /opt/inference/xinference/ui/web/dist # buildkit
                        
# 2026-10-25 15:41:08  245.13MB 复制新文件或目录到容器中
COPY . /opt/inference # buildkit
                        
# 2026-10-25 15:41:06  492.63MB 执行命令并创建新的镜像层
RUN |1 PIP_INDEX=https://pypi.org/simple /bin/sh -c /opt/conda/bin/conda create -n ffmpeg-env -c conda-forge 'ffmpeg<7' -y &&     ln -s /opt/conda/envs/ffmpeg-env/bin/ffmpeg /usr/local/bin/ffmpeg &&     ln -s /opt/conda/envs/ffmpeg-env/bin/ffprobe /usr/local/bin/ffprobe &&     /opt/conda/bin/conda clean --all -y # buildkit
                        
# 2026-10-25 15:40:24  6.64GB 执行命令并创建新的镜像层
RUN |1 PIP_INDEX=https://pypi.org/simple /bin/sh -c python -m pip install --upgrade -i "$PIP_INDEX" pip "setuptools<82" wheel "packaging>=24.2" &&     pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu &&     pip install -i "$PIP_INDEX" --upgrade-strategy only-if-needed -r /opt/inference/xinference/deploy/docker/requirements_cpu/requirements_cpu-base.txt &&     pip install -i "$PIP_INDEX" --no-build-isolation "gptqmodel<6.0.0" &&     pip install -i "$PIP_INDEX" --upgrade-strategy only-if-needed -r /opt/inference/xinference/deploy/docker/requirements_cpu/requirements_cpu-ml.txt &&     pip install -i "$PIP_INDEX" --only-binary=pynini --upgrade-strategy only-if-needed -r /opt/inference/xinference/deploy/docker/requirements_cpu/requirements_cpu-models.txt &&     pip install -i "$PIP_INDEX" "xllamacpp" &&     pip install -i "$PIP_INDEX" "kernels==0.14.1" # buildkit
                        
# 2026-10-25 15:35:14  2.88KB 复制新文件或目录到容器中
COPY xinference/deploy/docker/requirements_cpu/ /opt/inference/xinference/deploy/docker/requirements_cpu/ # buildkit
                        
# 2026-10-25 15:35:14  0.00B 定义构建参数
ARG PIP_INDEX=https://pypi.org/simple
                        
# 2026-10-25 15:35:14  577.79MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get -y update   && apt install -y build-essential curl procps git libgl1   && apt-get -yq clean # buildkit
                        
# 2024-12-18 00:27:42  353.86MB 执行命令并创建新的镜像层
RUN |6 INSTALLER_URL_LINUX64=https://repo.anaconda.com/miniconda/Miniconda3-py312_24.11.1-0-Linux-x86_64.sh SHA256SUM_LINUX64=636b209b00b6673471f846581829d4b96b9c3378679925a59a584257c3fef5a3 INSTALLER_URL_S390X=https://repo.anaconda.com/miniconda/Miniconda3-py312_24.11.1-0-Linux-s390x.sh SHA256SUM_S390X=105bce6b0137f574147b8fdfd5e3a7d6c92f3ea9fbf3e0de61331ea43586e9af INSTALLER_URL_AARCH64=https://repo.anaconda.com/miniconda/Miniconda3-py312_24.11.1-0-Linux-aarch64.sh SHA256SUM_AARCH64=9180a2f1fab799fd76e9ef914643269dcf5bad9d455623b905b87f5d39ae140f /bin/sh -c set -x &&     UNAME_M="$(uname -m)" &&     if [ "${UNAME_M}" = "x86_64" ]; then         INSTALLER_URL="${INSTALLER_URL_LINUX64}";         SHA256SUM="${SHA256SUM_LINUX64}";     elif [ "${UNAME_M}" = "s390x" ]; then         INSTALLER_URL="${INSTALLER_URL_S390X}";         SHA256SUM="${SHA256SUM_S390X}";     elif [ "${UNAME_M}" = "aarch64" ]; then         INSTALLER_URL="${INSTALLER_URL_AARCH64}";         SHA256SUM="${SHA256SUM_AARCH64}";     fi &&     wget "${INSTALLER_URL}" -O miniconda.sh -q &&     echo "${SHA256SUM} miniconda.sh" > shasum &&     sha256sum --check --status shasum &&     mkdir -p /opt &&     bash miniconda.sh -b -p /opt/conda &&     rm miniconda.sh shasum &&     ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh &&     echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc &&     echo "conda activate base" >> ~/.bashrc &&     find /opt/conda/ -follow -type f -name '*.a' -delete &&     find /opt/conda/ -follow -type f -name '*.js.map' -delete &&     /opt/conda/bin/conda clean -afy # buildkit
                        
# 2024-12-18 00:27:27  0.00B 定义构建参数
ARG SHA256SUM_AARCH64=9180a2f1fab799fd76e9ef914643269dcf5bad9d455623b905b87f5d39ae140f
                        
# 2024-12-18 00:27:27  0.00B 定义构建参数
ARG INSTALLER_URL_AARCH64=https://repo.anaconda.com/miniconda/Miniconda3-py312_24.11.1-0-Linux-aarch64.sh
                        
# 2024-12-18 00:27:27  0.00B 定义构建参数
ARG SHA256SUM_S390X=105bce6b0137f574147b8fdfd5e3a7d6c92f3ea9fbf3e0de61331ea43586e9af
                        
# 2024-12-18 00:27:27  0.00B 定义构建参数
ARG INSTALLER_URL_S390X=https://repo.anaconda.com/miniconda/Miniconda3-py312_24.11.1-0-Linux-s390x.sh
                        
# 2024-12-18 00:27:27  0.00B 定义构建参数
ARG SHA256SUM_LINUX64=636b209b00b6673471f846581829d4b96b9c3378679925a59a584257c3fef5a3
                        
# 2024-12-18 00:27:27  0.00B 定义构建参数
ARG INSTALLER_URL_LINUX64=https://repo.anaconda.com/miniconda/Miniconda3-py312_24.11.1-0-Linux-x86_64.sh
                        
# 2024-12-18 00:27:27  0.00B 设置默认要执行的命令
CMD ["/bin/bash"]
                        
# 2024-12-18 00:27:27  0.00B 设置环境变量 PATH
ENV PATH=/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
                        
# 2024-12-18 00:27:27  176.68MB 执行命令并创建新的镜像层
RUN /bin/sh -c apt-get update -q &&     apt-get install -q -y --no-install-recommends         bzip2         ca-certificates         git         libglib2.0-0         libsm6         libxext6         libxrender1         mercurial         openssh-client         procps         subversion         wget     && apt-get clean     && rm -rf /var/lib/apt/lists/* # buildkit
                        
# 2024-12-18 00:27:27  0.00B 设置环境变量 LANG LC_ALL
ENV LANG=C.UTF-8 LC_ALL=C.UTF-8
                        
# 2024-12-18 00:27:27  0.00B 添加元数据标签
LABEL maintainer=Anaconda, Inc
                        
# 2024-12-02 08:00:00  74.82MB 
# debian.sh --arch 'amd64' out/ 'bookworm' '@1733097600'
                        
                    

镜像信息

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        "Cmd": [
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        "ArgsEscaped": true,
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