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__pycache__/
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*.py[cod]
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input
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models
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notebooks
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output
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# 3.10.11-bullseye, has python, git, but relatively small (<250MB)
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ARG BASE_IMAGE="python@sha256:88fb365ea5d52ec8f5799f40a4742b9fb3c91dac92f7048eabaae194a25ccc28"
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ARG GPU_MAKE="nvidia"
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ARG UID=1000
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ARG GID=1000
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FROM ${BASE_IMAGE}
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ARG GPU_MAKE
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ARG UID
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ARG GID
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SHELL [ "/bin/bash", "-uec"]
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RUN \
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--mount=target=/var/lib/apt/lists,type=cache,sharing=locked \
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--mount=target=/var/cache/apt,type=cache,sharing=locked \
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<<'EOF'
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apt-get update
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apt-get install -yq git-lfs
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echo "comfyui" >> /etc/hostname
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EOF
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# run instructions as user
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USER ${UID}:${GID}
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# run python from future venv
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ENV PATH="/app/venv/bin:${PATH}"
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# copy context to obvious location
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COPY --chown=${UID}:${GID} ./ /app
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# create cache directory *with user permissions*
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WORKDIR /app/.cache
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# default to app directory
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WORKDIR /app
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# set pip cache location
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ENV XDG_CACHE_HOME="/app/.cache/pip"
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# run with mounted cache
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RUN --mount=type=cache,target=/app/.cache,uid=${UID},gid=${GID} <<'EOF'
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mkdir -p /app/.cache/transformers
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# choose package index based on chosen hardware
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if [ "${GPU_MAKE}" = "nvidia" ]; then
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EXTRA_INDEX_URL="https://download.pytorch.org/whl/cu118"
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EXTRAS="xformers"
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elif [ "${GPU_MAKE}" = "amd" ]; then
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EXTRA_INDEX_URL="https://download.pytorch.org/whl/rocm5.4.2"
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EXTRAS=""
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elif [ "${GPU_MAKE}" = "cpu" ]; then
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EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu"
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EXTRAS=""
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else
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echo "Unknown GPU_MAKE provided as docker build arg."
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exit 2
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fi
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# create virtual environment to manage packages
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python -m venv venv
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# install framework packages
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pip install \
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--extra-index-url "${EXTRA_INDEX_URL}" \
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install \
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torch \
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torchvision \
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torchaudio \
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${EXTRAS}
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pip install -r requirements.txt
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EOF
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# default environment variables
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ENV COMFYUI_ADDRESS=0.0.0.0
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ENV COMFYUI_PORT=8188
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ENV COMFYUI_EXTRA_ARGS=""
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ENV TRANSFORMERS_CACHE="/app/.cache/transformers"
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# default start command
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CMD bash -c "python -u main.py --listen ${COMFYUI_ADDRESS} --port ${COMFYUI_PORT} ${COMFYUI_EXTRA_ARGS}"
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version: "3.9"
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services:
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comfyui:
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user: "1000:1000"
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build: .
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: 1
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capabilities: [gpu]
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ports:
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- "8188:8188"
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volumes:
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- "./models:/app/models"
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- "./input:/app/input"
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- "./temp:/app/output/temp"
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- "./output:/app/output"
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