Invoke 3.0 Dockerfile
InvokeAI 3.0 has a completely different structure and tries to auto-download everything. There may be better solutions for this such as skipping model downloads or similar, but after initial run the container should start quickly. Most of the symlinks should capture the models roughly into the existing structure used in stable-diffusion-webui-docker repo but further testing should be done. Docker file is based on upstream invokeai's Dockerfile
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FROM alpine:3.17 as xformers
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# syntax=docker/dockerfile:1.4
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RUN apk add --no-cache aria2
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RUN aria2c -x 5 --dir / --out wheel.whl 'https://github.com/AbdBarho/stable-diffusion-webui-docker/releases/download/6.0.0/xformers-0.0.21.dev544-cp310-cp310-manylinux2014_x86_64-pytorch201.whl'
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## Builder stage
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FROM pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime
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FROM library/ubuntu:22.04 AS builder
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ENV DEBIAN_FRONTEND=noninteractive PIP_EXISTS_ACTION=w PIP_PREFER_BINARY=1
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ARG DEBIAN_FRONTEND=noninteractive
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RUN rm -f /etc/apt/apt.conf.d/docker-clean; echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache
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RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
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--mount=type=cache,target=/var/lib/apt,sharing=locked \
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apt update && apt-get install -y \
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git \
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python3.10-venv \
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python3-pip \
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build-essential
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# patch match:
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#ENV INVOKE_AI_ROOT=/InvokeAI
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# https://github.com/invoke-ai/InvokeAI/blob/main/docs/installation/INSTALL_PATCHMATCH.md
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ENV INVOKEAI_SRC=/opt/invokeai
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RUN --mount=type=cache,target=/var/cache/apt \
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ENV VIRTUAL_ENV=/opt/venv/invokeai
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apt-get update && \
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apt-get install make g++ git libopencv-dev -y && \
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apt-get clean && \
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cd /usr/lib/x86_64-linux-gnu/pkgconfig/ && \
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ln -sf opencv4.pc opencv.pc
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ENV PATH="$VIRTUAL_ENV/bin:$PATH"
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ARG TORCH_VERSION=2.0.1
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ARG TORCHVISION_VERSION=0.15.2
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ARG GPU_DRIVER=cuda
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ARG TARGETPLATFORM="linux/amd64"
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# unused but available
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ARG BUILDPLATFORM
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ENV ROOT=/InvokeAI
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WORKDIR ${INVOKEAI_SRC}
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RUN git clone https://github.com/invoke-ai/InvokeAI.git ${ROOT}
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WORKDIR ${ROOT}
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# Install pytorch before all other pip packages
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# NOTE: there are no pytorch builds for arm64 + cuda, only cpu
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# x86_64/CUDA is default
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RUN --mount=type=cache,target=/root/.cache/pip \
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RUN --mount=type=cache,target=/root/.cache/pip \
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git reset --hard f3b2e02921927d9317255b1c3811f47bd40a2bf9 && \
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python3 -m venv ${VIRTUAL_ENV} &&\
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pip install -e .
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if [ "$TARGETPLATFORM" = "linux/arm64" ] || [ "$GPU_DRIVER" = "cpu" ]; then \
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extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cpu"; \
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elif [ "$GPU_DRIVER" = "rocm" ]; then \
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extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/rocm5.4.2"; \
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else \
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extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cu118"; \
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fi &&\
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pip install $extra_index_url_arg \
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torch==$TORCH_VERSION \
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torchvision==$TORCHVISION_VERSION
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RUN git clone https://github.com/invoke-ai/InvokeAI.git ${INVOKEAI_SRC}
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ARG BRANCH=main SHA=f3b2e02921927d9317255b1c3811f47bd40a2bf9
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# Install the local package.
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# Editable mode helps use the same image for development:
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# the local working copy can be bind-mounted into the image
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# at path defined by ${INVOKEAI_SRC}
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#COPY invokeai ./invokeai
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#COPY pyproject.toml ./
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#RUN cp ${INVOKEAI_SRC}/pyproject.toml ./
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RUN --mount=type=cache,target=/root/.cache/pip \
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RUN --mount=type=cache,target=/root/.cache/pip \
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git fetch && \
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# xformers + triton fails to install on arm64
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git reset --hard && \
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if [ "$GPU_DRIVER" = "cuda" ] && [ "$TARGETPLATFORM" = "linux/amd64" ]; then \
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git checkout ${BRANCH} && \
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pip install -e ".[xformers]"; \
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git reset --hard ${SHA} && \
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else \
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pip install -U -e .
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pip install -e "."; \
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fi
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RUN --mount=type=cache,target=/root/.cache/pip \
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# #### Build the Web UI ------------------------------------
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--mount=type=bind,from=xformers,source=/wheel.whl,target=/xformers-0.0.21-cp310-cp310-linux_x86_64.whl \
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pip install -U opencv-python-headless triton /xformers-0.0.21-cp310-cp310-linux_x86_64.whl && \
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ENV INVOKEAI_SRC=/opt/invokeai
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python3 -c "from patchmatch import patch_match"
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FROM node:18 AS web-builder
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WORKDIR /build
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COPY --from=builder /opt/invokeai/invokeai/frontend/web/ ./
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RUN --mount=type=cache,target=/usr/lib/node_modules \
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npm install --include dev
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RUN --mount=type=cache,target=/usr/lib/node_modules \
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yarn vite build
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COPY . /docker/
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#### Runtime stage ---------------------------------------
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ENV NVIDIA_VISIBLE_DEVICES=all
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FROM library/ubuntu:22.04 AS runtime
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ENV PYTHONUNBUFFERED=1 PRELOAD=false HF_HOME=/root/.cache/huggingface CONFIG_DIR=/data/config/invoke CLI_ARGS=""
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EXPOSE 7860
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ENTRYPOINT ["/docker/entrypoint.sh"]
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ARG DEBIAN_FRONTEND=noninteractive
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CMD invokeai --web --host 0.0.0.0 --port 7860 --root_dir ${ROOT} --config ${CONFIG_DIR}/models.yaml \
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ENV PYTHONUNBUFFERED=1
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--outdir /output/invoke --embedding_directory /data/embeddings/ --lora_directory /data/models/Lora \
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ENV PYTHONDONTWRITEBYTECODE=1
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--no-nsfw_checker --no-safety_checker ${CLI_ARGS}
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RUN apt update && apt install -y --no-install-recommends \
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git \
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curl \
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vim \
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tmux \
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ncdu \
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iotop \
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bzip2 \
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gosu \
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libglib2.0-0 \
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libgl1-mesa-glx \
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python3-venv \
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python3-pip \
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build-essential \
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libopencv-dev \
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libstdc++-10-dev &&\
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apt-get clean && apt-get autoclean
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# globally add magic-wormhole
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# for ease of transferring data to and from the container
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# when running in sandboxed cloud environments; e.g. Runpod etc.
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RUN pip install magic-wormhole
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ENV INVOKEAI_SRC=/opt/invokeai
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ENV VIRTUAL_ENV=/opt/venv/invokeai
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ENV INVOKEAI_ROOT=/invokeai
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ENV PATH="$VIRTUAL_ENV/bin:$INVOKEAI_SRC:$PATH"
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# --link requires buldkit w/ dockerfile syntax 1.4
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COPY --link --from=builder ${INVOKEAI_SRC} ${INVOKEAI_SRC}
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COPY --link --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
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COPY --link --from=web-builder /build/dist ${INVOKEAI_SRC}/invokeai/frontend/web/dist
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# Link amdgpu.ids for ROCm builds
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# contributed by https://github.com/Rubonnek
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RUN mkdir -p "/opt/amdgpu/share/libdrm" &&\
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ln -s "/usr/share/libdrm/amdgpu.ids" "/opt/amdgpu/share/libdrm/amdgpu.ids"
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WORKDIR ${INVOKEAI_SRC}
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# build patchmatch
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RUN cd /usr/lib/$(uname -p)-linux-gnu/pkgconfig/ && ln -sf opencv4.pc opencv.pc
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RUN python3 -c "from patchmatch import patch_match"
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# Create unprivileged user and make the local dir
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RUN useradd --create-home --shell /bin/bash -u 1000 --comment "container local user" invoke
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RUN mkdir -p ${INVOKEAI_ROOT} && chown -R invoke:invoke ${INVOKEAI_ROOT}
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# Create autoimport directories
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RUN mkdir -p ${INVOKEAI_ROOT}/autoimport/embedding
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RUN mkdir ${INVOKEAI_ROOT}/autoimport/main
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RUN mkdir ${INVOKEAI_ROOT}/autoimport/lora
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RUN mkdir ${INVOKEAI_ROOT}/autoimport/controlnet
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# AbdBarho file structure
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RUN mkdir -p ${INVOKEAI_ROOT}/models/core/upscaling
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RUN ln -s /data/models/Stable-diffusion/ ${INVOKEAI_ROOT}/autoimport/main/
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RUN ln -s /data/embeddings/ ${INVOKEAI_ROOT}/autoimport/embedding/
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RUN ln -s /data/models/Lora ${INVOKEAI_ROOT}/autoimport/lora/
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RUN ln -s /data/models/ControlNet ${INVOKEAI_ROOT}/autoimport/controlnet/
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RUN rm -rf ${INVOKEAI_ROOT}/models/core/upscaling/realesrgan && \
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ln -s /data/models/RealESRGAN ${INVOKEAI_ROOT}/models/core/upscaling/realesrgan
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RUN rm -rf ${INVOKEAI_ROOT}/models/core/convert && \
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ln -s /data/models/invoke/ ${INVOKEAI_ROOT}/models/core/convert
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#COPY docker/docker-entrypoint.sh ./
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RUN cp ${INVOKEAI_SRC}/docker/docker-entrypoint.sh ./
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ENTRYPOINT ["/opt/invokeai/docker-entrypoint.sh"]
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CMD ["invokeai-web", "--port", "7860", "--host", "0.0.0.0", "--outdir", "/output/invoke", "--conf_path", "/data/config/invoke/configs/models.yaml", "--db_dir", "/data/config/invoke/database"]
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