43 lines
1.7 KiB
Docker
43 lines
1.7 KiB
Docker
# 基础镜像配置 vLLM 或 LMDeploy ，请根据实际需要选择其中一个，要求 amd64(x86-64) CPU + Cambricon MLU.
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# Base image containing the LMDEPLOY inference environment, requiring amd64(x86-64) CPU + Cambricon MLU.
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FROM crpi-4crprmm5baj1v8iv.cn-hangzhou.personal.cr.aliyuncs.com/lmdeploy_dlinfer/camb:qwen2.5_vl
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ARG BACKEND=lmdeploy
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# Base image containing the vLLM inference environment, requiring amd64(x86-64) CPU + Cambricon MLU.
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# FROM crpi-vofi3w62lkohhxsp.cn-shanghai.personal.cr.aliyuncs.com/opendatalab-mineru/mlu:vllm0.8.3-torch2.6.0-torchmlu1.26.1-ubuntu22.04-py310
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# ARG BACKEND=vllm
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# Install Noto fonts for Chinese characters
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RUN apt-get update && \
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apt-get install -y \
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fonts-noto-core \
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fonts-noto-cjk \
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fontconfig && \
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fc-cache -fv && \
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apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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# Install mineru latest
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RUN /bin/bash -c '\
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if [ "$BACKEND" = "vllm" ]; then \
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source /torch/venv3/pytorch_infer/bin/activate; \
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fi && \
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python3 -m pip install -U pip -i https://mirrors.aliyun.com/pypi/simple && \
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python3 -m pip install "mineru[core]>=2.7.4" \
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numpy==1.26.4 \
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opencv-python==4.11.0.86 \
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-i https://mirrors.aliyun.com/pypi/simple && \
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python3 -m pip install $(if [ "$BACKEND" = "lmdeploy" ]; then echo "accelerate==1.2.0"; else echo "transformers==4.50.3"; fi) && \
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python3 -m pip cache purge'
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# Download models and update the configuration file
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RUN /bin/bash -c '\
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if [ "$BACKEND" = "vllm" ]; then \
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source /torch/venv3/pytorch_infer/bin/activate; \
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fi && \
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mineru-models-download -s modelscope -m all'
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WORKDIR /workspace
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# Set the entry point to activate the virtual environment and run the command line tool
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ENTRYPOINT ["/bin/bash", "-c", "export MINERU_MODEL_SOURCE=local && exec \"$@\"", "--"]
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