51 lines
1.8 KiB
Markdown
51 lines
1.8 KiB
Markdown
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# Dockerfile
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See [here](https://github.com/vllm-project/vllm/blob/main/Dockerfile) for the main Dockerfile to construct
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the image for running an OpenAI compatible server with vLLM. More information about deploying with Docker can be found [here](https://docs.vllm.ai/en/stable/serving/deploying_with_docker.html).
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Below is a visual representation of the multi-stage Dockerfile. The build graph contains the following nodes:
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- All build stages
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- The default build target (highlighted in grey)
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- External images (with dashed borders)
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The edges of the build graph represent:
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- FROM ... dependencies (with a solid line and a full arrow head)
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- COPY --from=... dependencies (with a dashed line and an empty arrow head)
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- RUN --mount=(.\*)from=... dependencies (with a dotted line and an empty diamond arrow head)
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> ```{figure} ../../assets/dev/dockerfile-stages-dependency.png
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> :align: center
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> :alt: query
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> :width: 100%
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> ```
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>
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> Made using: <https://github.com/patrickhoefler/dockerfilegraph>
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>
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> Commands to regenerate the build graph (make sure to run it **from the \`root\` directory of the vLLM repository** where the dockerfile is present):
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>
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> ```bash
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> dockerfilegraph -o png --legend --dpi 200 --max-label-length 50 --filename Dockerfile
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> ```
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>
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> or in case you want to run it directly with the docker image:
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>
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> ```bash
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> docker run \
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> --rm \
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> --user "$(id -u):$(id -g)" \
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> --workdir /workspace \
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> --volume "$(pwd)":/workspace \
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> ghcr.io/patrickhoefler/dockerfilegraph:alpine \
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> --output png \
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> --dpi 200 \
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> --max-label-length 50 \
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> --filename Dockerfile \
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> --legend
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> ```
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>
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> (To run it for a different file, you can pass in a different argument to the flag `--filename`.)
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