Merge branch 'main' into bbox-ar

.dockerignore

@@ -1,25 +1,9 @@
-# use this file as a whitelist
 *
 !invokeai
-!ldm
 !pyproject.toml
+!docker/docker-entrypoint.sh
+!LICENSE
 
-# ignore frontend/web but whitelist dist
+**/node_modules
-invokeai/frontend/web/
+**/__pycache__
-!invokeai/frontend/web/dist/
+**/*.egg-info
-
-# ignore invokeai/assets but whitelist invokeai/assets/web
-invokeai/assets/
-!invokeai/assets/web/
-
-# Guard against pulling in any models that might exist in the directory tree
-**/*.pt*
-**/*.ckpt
-
-# Byte-compiled / optimized / DLL files
-**/__pycache__/
-**/*.py[cod]
-
-# Distribution / packaging
-**/*.egg-info/
-**/*.egg

.github/workflows/build-container.yml

@@ -3,17 +3,15 @@ on:
   push:
     branches:
       - 'main'
-      - 'update/ci/docker/*'
-      - 'update/docker/*'
-      - 'dev/ci/docker/*'
-      - 'dev/docker/*'
     paths:
       - 'pyproject.toml'
       - '.dockerignore'
       - 'invokeai/**'
       - 'docker/Dockerfile'
+      - 'docker/docker-entrypoint.sh'
+      - 'workflows/build-container.yml'
     tags:
-      - 'v*.*.*'
+      - 'v*'
   workflow_dispatch:
 
 permissions:
@@ -26,23 +24,27 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        flavor:
+        gpu-driver:
-          - rocm
+        - cuda
-          - cuda
+        - cpu
-          - cpu
+        - rocm
-        include:
-          - flavor: rocm
-            pip-extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
-          - flavor: cuda
-            pip-extra-index-url: ''
-          - flavor: cpu
-            pip-extra-index-url: 'https://download.pytorch.org/whl/cpu'
     runs-on: ubuntu-latest
-    name: ${{ matrix.flavor }}
+    name: ${{ matrix.gpu-driver }}
     env:
-      PLATFORMS: 'linux/amd64,linux/arm64'
+      # torch/arm64 does not support GPU currently, so arm64 builds
-      DOCKERFILE: 'docker/Dockerfile'
+      # would not be GPU-accelerated.
+      # re-enable arm64 if there is sufficient demand.
+      # PLATFORMS: 'linux/amd64,linux/arm64'
+      PLATFORMS: 'linux/amd64'
     steps:
+      - name: Free up more disk space on the runner
+        # https://github.com/actions/runner-images/issues/2840#issuecomment-1284059930
+        run: |
+          sudo rm -rf /usr/share/dotnet
+          sudo rm -rf "$AGENT_TOOLSDIRECTORY"
+          sudo swapoff /mnt/swapfile
+          sudo rm -rf /mnt/swapfile
+
       - name: Checkout
         uses: actions/checkout@v3
 
@@ -53,7 +55,7 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           images: |
             ghcr.io/${{ github.repository }}
-            ${{ vars.DOCKERHUB_REPOSITORY }}
+            ${{ env.DOCKERHUB_REPOSITORY }}
           tags: |
             type=ref,event=branch
             type=ref,event=tag
@@ -62,8 +64,8 @@ jobs:
             type=pep440,pattern={{major}}
             type=sha,enable=true,prefix=sha-,format=short
           flavor: |
-            latest=${{ matrix.flavor == 'cuda' && github.ref == 'refs/heads/main' }}
+            latest=${{ matrix.gpu-driver == 'cuda' && github.ref == 'refs/heads/main' }}
-            suffix=-${{ matrix.flavor }},onlatest=false
+            suffix=-${{ matrix.gpu-driver }},onlatest=false
 
       - name: Set up QEMU
         uses: docker/setup-qemu-action@v2
@@ -81,34 +83,33 @@ jobs:
           username: ${{ github.repository_owner }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
-      - name: Login to Docker Hub
+      # - name: Login to Docker Hub
-        if: github.event_name != 'pull_request' && vars.DOCKERHUB_REPOSITORY != ''
+      #   if: github.event_name != 'pull_request' && vars.DOCKERHUB_REPOSITORY != ''
-        uses: docker/login-action@v2
+      #   uses: docker/login-action@v2
-        with:
+      #   with:
-          username: ${{ secrets.DOCKERHUB_USERNAME }}
+      #     username: ${{ secrets.DOCKERHUB_USERNAME }}
-          password: ${{ secrets.DOCKERHUB_TOKEN }}
+      #     password: ${{ secrets.DOCKERHUB_TOKEN }}
 
       - name: Build container
         id: docker_build
         uses: docker/build-push-action@v4
         with:
           context: .
-          file: ${{ env.DOCKERFILE }}
+          file: docker/Dockerfile
           platforms: ${{ env.PLATFORMS }}
           push: ${{ github.ref == 'refs/heads/main' || github.ref_type == 'tag' }}
           tags: ${{ steps.meta.outputs.tags }}
           labels: ${{ steps.meta.outputs.labels }}
-          build-args: PIP_EXTRA_INDEX_URL=${{ matrix.pip-extra-index-url }}
           cache-from: |
-            type=gha,scope=${{ github.ref_name }}-${{ matrix.flavor }}
+            type=gha,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}
-            type=gha,scope=main-${{ matrix.flavor }}
+            type=gha,scope=main-${{ matrix.gpu-driver }}
-          cache-to: type=gha,mode=max,scope=${{ github.ref_name }}-${{ matrix.flavor }}
+          cache-to: type=gha,mode=max,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}
 
-      - name: Docker Hub Description
+      # - name: Docker Hub Description
-        if: github.ref == 'refs/heads/main' || github.ref == 'refs/tags/*' && vars.DOCKERHUB_REPOSITORY != ''
+      #   if: github.ref == 'refs/heads/main' || github.ref == 'refs/tags/*' && vars.DOCKERHUB_REPOSITORY != ''
-        uses: peter-evans/dockerhub-description@v3
+      #   uses: peter-evans/dockerhub-description@v3
-        with:
+      #   with:
-          username: ${{ secrets.DOCKERHUB_USERNAME }}
+      #     username: ${{ secrets.DOCKERHUB_USERNAME }}
-          password: ${{ secrets.DOCKERHUB_TOKEN }}
+      #     password: ${{ secrets.DOCKERHUB_TOKEN }}
-          repository: ${{ vars.DOCKERHUB_REPOSITORY }}
+      #     repository: ${{ vars.DOCKERHUB_REPOSITORY }}
-          short-description: ${{ github.event.repository.description }}
+      #     short-description: ${{ github.event.repository.description }}

docker/.env.sample

@@ -0,0 +1,13 @@
+## Make a copy of this file named `.env` and fill in the values below.
+## Any environment variables supported by InvokeAI can be specified here.
+
+# INVOKEAI_ROOT is the path to a path on the local filesystem where InvokeAI will store data.
+# Outputs will also be stored here by default.
+# This **must** be an absolute path.
+INVOKEAI_ROOT=
+
+HUGGINGFACE_TOKEN=
+
+## optional variables specific to the docker setup
+# GPU_DRIVER=cuda
+# CONTAINER_UID=1000

docker/Dockerfile

@@ -1,107 +1,129 @@
-# syntax=docker/dockerfile:1
+# syntax=docker/dockerfile:1.4
 
-ARG PYTHON_VERSION=3.9
+## Builder stage
-##################
-##  base image  ##
-##################
-FROM --platform=${TARGETPLATFORM} python:${PYTHON_VERSION}-slim AS python-base
 
-LABEL org.opencontainers.image.authors="mauwii@outlook.de"
+FROM library/ubuntu:22.04 AS builder
 
-# Prepare apt for buildkit cache
+ARG DEBIAN_FRONTEND=noninteractive
-RUN rm -f /etc/apt/apt.conf.d/docker-clean \
+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
-  && echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' >/etc/apt/apt.conf.d/keep-cache
+RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
+    --mount=type=cache,target=/var/lib/apt,sharing=locked \
+    apt update && apt-get install -y \
+        git \
+        python3.10-venv \
+        python3-pip \
+        build-essential
 
-# Install dependencies
+ENV INVOKEAI_SRC=/opt/invokeai
-RUN \
+ENV VIRTUAL_ENV=/opt/venv/invokeai
-  --mount=type=cache,target=/var/cache/apt,sharing=locked \
-  --mount=type=cache,target=/var/lib/apt,sharing=locked \
-  apt-get update \
-  && apt-get install -y \
-    --no-install-recommends \
-    libgl1-mesa-glx=20.3.* \
-    libglib2.0-0=2.66.* \
-    libopencv-dev=4.5.*
 
-# Set working directory and env
+ENV PATH="$VIRTUAL_ENV/bin:$PATH"
-ARG APPDIR=/usr/src
+ARG TORCH_VERSION=2.0.1
-ARG APPNAME=InvokeAI
+ARG TORCHVISION_VERSION=0.15.2
-WORKDIR ${APPDIR}
+ARG GPU_DRIVER=cuda
-ENV PATH ${APPDIR}/${APPNAME}/bin:$PATH
+ARG TARGETPLATFORM="linux/amd64"
-# Keeps Python from generating .pyc files in the container
+# unused but available
-ENV PYTHONDONTWRITEBYTECODE 1
+ARG BUILDPLATFORM
-# Turns off buffering for easier container logging
-ENV PYTHONUNBUFFERED 1
-# Don't fall back to legacy build system
-ENV PIP_USE_PEP517=1
 
-#######################
+WORKDIR ${INVOKEAI_SRC}
-##  build pyproject  ##
-#######################
-FROM python-base AS pyproject-builder
 
-# Install build dependencies
+# Install pytorch before all other pip packages
-RUN \
+# NOTE: there are no pytorch builds for arm64 + cuda, only cpu
-  --mount=type=cache,target=/var/cache/apt,sharing=locked \
+# x86_64/CUDA is default
-  --mount=type=cache,target=/var/lib/apt,sharing=locked \
+RUN --mount=type=cache,target=/root/.cache/pip \
-  apt-get update \
+    python3 -m venv ${VIRTUAL_ENV} &&\
-  && apt-get install -y \
+    if [ "$TARGETPLATFORM" = "linux/arm64" ] || [ "$GPU_DRIVER" = "cpu" ]; then \
-    --no-install-recommends \
+        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cpu"; \
-    build-essential=12.9 \
+    elif [ "$GPU_DRIVER" = "rocm" ]; then \
-    gcc=4:10.2.* \
+        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/rocm5.4.2"; \
-    python3-dev=3.9.*
+    else \
+        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cu118"; \
+    fi &&\
+    pip install $extra_index_url_arg \
+        torch==$TORCH_VERSION \
+        torchvision==$TORCHVISION_VERSION
 
-# Prepare pip for buildkit cache
+# Install the local package.
-ARG PIP_CACHE_DIR=/var/cache/buildkit/pip
+# Editable mode helps use the same image for development:
-ENV PIP_CACHE_DIR ${PIP_CACHE_DIR}
+# the local working copy can be bind-mounted into the image
-RUN mkdir -p ${PIP_CACHE_DIR}
+# at path defined by ${INVOKEAI_SRC}
+COPY invokeai ./invokeai
+COPY pyproject.toml ./
+RUN --mount=type=cache,target=/root/.cache/pip \
+    # xformers + triton fails to install on arm64
+    if [ "$GPU_DRIVER" = "cuda" ] && [ "$TARGETPLATFORM" = "linux/amd64" ]; then \
+        pip install -e ".[xformers]"; \
+    else \
+        pip install -e "."; \
+    fi
 
-# Create virtual environment
+# #### Build the Web UI ------------------------------------
-RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
-  python3 -m venv "${APPNAME}" \
-  --upgrade-deps
 
-# Install requirements
+FROM node:18 AS web-builder
-COPY --link pyproject.toml .
+WORKDIR /build
-COPY --link invokeai/version/invokeai_version.py invokeai/version/__init__.py invokeai/version/
+COPY invokeai/frontend/web/ ./
-ARG PIP_EXTRA_INDEX_URL
+RUN --mount=type=cache,target=/usr/lib/node_modules \
-ENV PIP_EXTRA_INDEX_URL ${PIP_EXTRA_INDEX_URL}
+    npm install --include dev
-RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
+RUN --mount=type=cache,target=/usr/lib/node_modules \
-  "${APPNAME}"/bin/pip install .
+    yarn vite build
 
-# Install pyproject.toml
-COPY --link . .
-RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
-  "${APPNAME}/bin/pip" install .
 
-# Build patchmatch
+#### Runtime stage ---------------------------------------
+
+FROM library/ubuntu:22.04 AS runtime
+
+ARG DEBIAN_FRONTEND=noninteractive
+ENV PYTHONUNBUFFERED=1
+ENV PYTHONDONTWRITEBYTECODE=1
+
+RUN apt update && apt install -y --no-install-recommends \
+        git \
+        curl \
+        vim \
+        tmux \
+        ncdu \
+        iotop \
+        bzip2 \
+        gosu \
+        libglib2.0-0 \
+        libgl1-mesa-glx \
+        python3-venv \
+        python3-pip \
+        build-essential \
+        libopencv-dev \
+        libstdc++-10-dev &&\
+    apt-get clean && apt-get autoclean
+
+# globally add magic-wormhole
+# for ease of transferring data to and from the container
+# when running in sandboxed cloud environments; e.g. Runpod etc.
+RUN pip install magic-wormhole
+
+ENV INVOKEAI_SRC=/opt/invokeai
+ENV VIRTUAL_ENV=/opt/venv/invokeai
+ENV INVOKEAI_ROOT=/invokeai
+ENV PATH="$VIRTUAL_ENV/bin:$INVOKEAI_SRC:$PATH"
+
+# --link requires buldkit w/ dockerfile syntax 1.4
+COPY --link --from=builder ${INVOKEAI_SRC} ${INVOKEAI_SRC}
+COPY --link --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
+COPY --link --from=web-builder /build/dist ${INVOKEAI_SRC}/invokeai/frontend/web/dist
+
+# Link amdgpu.ids for ROCm builds
+# contributed by https://github.com/Rubonnek
+RUN mkdir -p "/opt/amdgpu/share/libdrm" &&\
+  ln -s "/usr/share/libdrm/amdgpu.ids" "/opt/amdgpu/share/libdrm/amdgpu.ids"
+
+WORKDIR ${INVOKEAI_SRC}
+
+# build patchmatch
+RUN cd /usr/lib/$(uname -p)-linux-gnu/pkgconfig/ && ln -sf opencv4.pc opencv.pc
 RUN python3 -c "from patchmatch import patch_match"
 
-#####################
+# Create unprivileged user and make the local dir
-##  runtime image  ##
+RUN useradd --create-home --shell /bin/bash -u 1000 --comment "container local user" invoke
-#####################
+RUN mkdir -p ${INVOKEAI_ROOT} && chown -R invoke:invoke ${INVOKEAI_ROOT}
-FROM python-base AS runtime
 
-# Create a new user
+COPY docker/docker-entrypoint.sh ./
-ARG UNAME=appuser
+ENTRYPOINT ["/opt/invokeai/docker-entrypoint.sh"]
-RUN useradd \
+CMD ["invokeai-web", "--host", "0.0.0.0"]
-  --no-log-init \
-  -m \
-  -U \
-  "${UNAME}"
-
-# Create volume directory
-ARG VOLUME_DIR=/data
-RUN mkdir -p "${VOLUME_DIR}" \
-  && chown -hR "${UNAME}:${UNAME}" "${VOLUME_DIR}"
-
-# Setup runtime environment
-USER ${UNAME}:${UNAME}
-COPY --chown=${UNAME}:${UNAME} --from=pyproject-builder ${APPDIR}/${APPNAME} ${APPNAME}
-ENV INVOKEAI_ROOT ${VOLUME_DIR}
-ENV TRANSFORMERS_CACHE ${VOLUME_DIR}/.cache
-ENV INVOKE_MODEL_RECONFIGURE "--yes --default_only"
-EXPOSE 9090
-ENTRYPOINT [ "invokeai" ]
-CMD [ "--web", "--host", "0.0.0.0", "--port", "9090" ]
-VOLUME [ "${VOLUME_DIR}" ]

docker/README.md

@@ -0,0 +1,77 @@
+# InvokeAI Containerized
+
+All commands are to be run from the `docker` directory: `cd docker`
+
+#### Linux
+
+1. Ensure builkit is enabled in the Docker daemon settings (`/etc/docker/daemon.json`)
+2. Install the `docker compose` plugin using your package manager, or follow a [tutorial](https://www.digitalocean.com/community/tutorials/how-to-install-and-use-docker-compose-on-ubuntu-22-04).
+    - The deprecated `docker-compose` (hyphenated) CLI continues to work for now.
+3. Ensure docker daemon is able to access the GPU.
+    - You may need to install [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
+
+#### macOS
+
+1. Ensure Docker has at least 16GB RAM
+2. Enable VirtioFS for file sharing
+3. Enable `docker compose` V2 support
+
+This is done via Docker Desktop preferences
+
+## Quickstart
+
+
+1. Make a copy of `env.sample` and name it `.env` (`cp env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to:
+    a. the desired location of the InvokeAI runtime directory, or
+    b. an existing, v3.0.0 compatible runtime directory.
+1. `docker compose up`
+
+The image will be built automatically if needed.
+
+The runtime directory (holding models and outputs) will be created in the location specified by `INVOKEAI_ROOT`. The default location is `~/invokeai`. The runtime directory will be populated with the base configs and models necessary to start generating.
+
+### Use a GPU
+
+- Linux is *recommended* for GPU support in Docker.
+- WSL2 is *required* for Windows.
+- only `x86_64` architecture is supported.
+
+The Docker daemon on the system must be already set up to use the GPU. In case of Linux, this involves installing `nvidia-docker-runtime` and configuring the `nvidia` runtime as default. Steps will be different for AMD. Please see Docker documentation for the most up-to-date instructions for using your GPU with Docker.
+
+## Customize
+
+Check the `.env.sample` file. It contains some environment variables for running in Docker. Copy it, name it `.env`, and fill it in with your own values. Next time you run `docker compose up`, your custom values will be used.
+
+You can also set these values in `docker compose.yml` directly, but `.env` will help avoid conflicts when code is updated.
+
+Example (most values are optional):
+
+```
+INVOKEAI_ROOT=/Volumes/WorkDrive/invokeai
+HUGGINGFACE_TOKEN=the_actual_token
+CONTAINER_UID=1000
+GPU_DRIVER=cuda
+```
+
+## Even Moar Customizing!
+
+See the `docker compose.yaml` file. The `command` instruction can be uncommented and used to run arbitrary startup commands. Some examples below.
+
+### Reconfigure the runtime directory
+
+Can be used to download additional models from the supported model list
+
+In conjunction with `INVOKEAI_ROOT` can be also used to initialize a runtime directory
+
+```
+command:
+  - invokeai-configure
+  - --yes
+```
+
+Or install models:
+
+```
+command:
+  - invokeai-model-install
+```

docker/build.sh

@@ -1,51 +1,11 @@
 #!/usr/bin/env bash
 set -e
 
-# If you want to build a specific flavor, set the CONTAINER_FLAVOR environment variable
+build_args=""
-#   e.g. CONTAINER_FLAVOR=cpu ./build.sh
-#   Possible Values are:
-#     - cpu
-#     - cuda
-#     - rocm
-#   Don't forget to also set it when executing run.sh
-#   if it is not set, the script will try to detect the flavor by itself.
-#
-# Doc can be found here:
-#   https://invoke-ai.github.io/InvokeAI/installation/040_INSTALL_DOCKER/
 
-SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
+[[ -f ".env" ]] && build_args=$(awk '$1 ~ /\=[^$]/ {print "--build-arg " $0 " "}' .env)
-cd "$SCRIPTDIR" || exit 1
 
-source ./env.sh
+echo "docker-compose build args:"
+echo $build_args
 
-DOCKERFILE=${INVOKE_DOCKERFILE:-./Dockerfile}
+docker-compose build $build_args
-
-# print the settings
-echo -e "You are using these values:\n"
-echo -e "Dockerfile:\t\t${DOCKERFILE}"
-echo -e "index-url:\t\t${PIP_EXTRA_INDEX_URL:-none}"
-echo -e "Volumename:\t\t${VOLUMENAME}"
-echo -e "Platform:\t\t${PLATFORM}"
-echo -e "Container Registry:\t${CONTAINER_REGISTRY}"
-echo -e "Container Repository:\t${CONTAINER_REPOSITORY}"
-echo -e "Container Tag:\t\t${CONTAINER_TAG}"
-echo -e "Container Flavor:\t${CONTAINER_FLAVOR}"
-echo -e "Container Image:\t${CONTAINER_IMAGE}\n"
-
-# Create docker volume
-if [[ -n "$(docker volume ls -f name="${VOLUMENAME}" -q)" ]]; then
-    echo -e "Volume already exists\n"
-else
-    echo -n "creating docker volume "
-    docker volume create "${VOLUMENAME}"
-fi
-
-# Build Container
-docker build \
-    --platform="${PLATFORM:-linux/amd64}" \
-    --tag="${CONTAINER_IMAGE:-invokeai}" \
-    ${CONTAINER_FLAVOR:+--build-arg="CONTAINER_FLAVOR=${CONTAINER_FLAVOR}"} \
-    ${PIP_EXTRA_INDEX_URL:+--build-arg="PIP_EXTRA_INDEX_URL=${PIP_EXTRA_INDEX_URL}"} \
-    ${PIP_PACKAGE:+--build-arg="PIP_PACKAGE=${PIP_PACKAGE}"} \
-    --file="${DOCKERFILE}" \
-    ..

docker/docker-compose.yml

@@ -0,0 +1,48 @@
+# Copyright (c) 2023 Eugene Brodsky https://github.com/ebr
+
+version: '3.8'
+
+services:
+  invokeai:
+    image: "local/invokeai:latest"
+    # edit below to run on a container runtime other than nvidia-container-runtime.
+    # not yet tested with rocm/AMD GPUs
+    # Comment out the "deploy" section to run on CPU only
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+    build:
+      context: ..
+      dockerfile: docker/Dockerfile
+
+    # variables without a default will automatically inherit from the host environment
+    environment:
+      - INVOKEAI_ROOT
+      - HF_HOME
+
+    # Create a .env file in the same directory as this docker-compose.yml file
+    # and populate it with environment variables. See .env.sample
+    env_file:
+      - .env
+
+    ports:
+      - "${INVOKEAI_PORT:-9090}:9090"
+    volumes:
+      - ${INVOKEAI_ROOT:-~/invokeai}:${INVOKEAI_ROOT:-/invokeai}
+      - ${HF_HOME:-~/.cache/huggingface}:${HF_HOME:-/invokeai/.cache/huggingface}
+      # - ${INVOKEAI_MODELS_DIR:-${INVOKEAI_ROOT:-/invokeai/models}}
+      # - ${INVOKEAI_MODELS_CONFIG_PATH:-${INVOKEAI_ROOT:-/invokeai/configs/models.yaml}}
+    tty: true
+    stdin_open: true
+
+    # # Example of running alternative commands/scripts in the container
+    # command:
+    #   - bash
+    #   - -c
+    #   - |
+    #     invokeai-model-install --yes --default-only --config_file ${INVOKEAI_ROOT}/config_custom.yaml
+    #     invokeai-nodes-web --host 0.0.0.0

docker/docker-entrypoint.sh

@@ -0,0 +1,65 @@
+#!/bin/bash
+set -e -o pipefail
+
+### Container entrypoint
+# Runs the CMD as defined by the Dockerfile or passed to `docker run`
+# Can be used to configure the runtime dir
+# Bypass by using ENTRYPOINT or `--entrypoint`
+
+### Set INVOKEAI_ROOT pointing to a valid runtime directory
+# Otherwise configure the runtime dir first.
+
+### Configure the InvokeAI runtime directory (done by default)):
+# docker run --rm -it <this image> --configure
+# or skip with --no-configure
+
+### Set the CONTAINER_UID envvar to match your user.
+# Ensures files created in the container are owned by you:
+#   docker run --rm -it -v /some/path:/invokeai -e CONTAINER_UID=$(id -u) <this image>
+# Default UID: 1000 chosen due to popularity on Linux systems. Possibly 501 on MacOS.
+
+USER_ID=${CONTAINER_UID:-1000}
+USER=invoke
+usermod -u ${USER_ID} ${USER} 1>/dev/null
+
+configure() {
+    # Configure the runtime directory
+    if [[ -f ${INVOKEAI_ROOT}/invokeai.yaml ]]; then
+        echo "${INVOKEAI_ROOT}/invokeai.yaml exists. InvokeAI is already configured."
+        echo "To reconfigure InvokeAI, delete the above file."
+        echo "======================================================================"
+    else
+        mkdir -p ${INVOKEAI_ROOT}
+        chown --recursive ${USER} ${INVOKEAI_ROOT}
+        gosu ${USER} invokeai-configure --yes --default_only
+    fi
+}
+
+## Skip attempting to configure.
+## Must be passed first, before any other args.
+if [[ $1 != "--no-configure" ]]; then
+    configure
+else
+    shift
+fi
+
+### Set the $PUBLIC_KEY env var to enable SSH access.
+# We do not install openssh-server in the image by default to avoid bloat.
+# but it is useful to have the full SSH server e.g. on Runpod.
+# (use SCP to copy files to/from the image, etc)
+if [[ -v "PUBLIC_KEY" ]] && [[ ! -d "${HOME}/.ssh" ]]; then
+    apt-get update
+    apt-get install -y openssh-server
+    pushd $HOME
+    mkdir -p .ssh
+    echo ${PUBLIC_KEY} > .ssh/authorized_keys
+    chmod -R 700 .ssh
+    popd
+    service ssh start
+fi
+
+
+cd ${INVOKEAI_ROOT}
+
+# Run the CMD as the Container User (not root).
+exec gosu ${USER} "$@"

docker/env.sh

@@ -1,54 +0,0 @@
-#!/usr/bin/env bash
-
-# This file is used to set environment variables for the build.sh and run.sh scripts.
-
-# Try to detect the container flavor if no PIP_EXTRA_INDEX_URL got specified
-if [[ -z "$PIP_EXTRA_INDEX_URL" ]]; then
-
-  # Activate virtual environment if not already activated and exists
-  if [[ -z $VIRTUAL_ENV ]]; then
-    [[ -e "$(dirname "${BASH_SOURCE[0]}")/../.venv/bin/activate" ]] \
-      && source "$(dirname "${BASH_SOURCE[0]}")/../.venv/bin/activate" \
-      && echo "Activated virtual environment: $VIRTUAL_ENV"
-  fi
-
-  # Decide which container flavor to build if not specified
-  if [[ -z "$CONTAINER_FLAVOR" ]] && python -c "import torch" &>/dev/null; then
-    # Check for CUDA and ROCm
-    CUDA_AVAILABLE=$(python -c "import torch;print(torch.cuda.is_available())")
-    ROCM_AVAILABLE=$(python -c "import torch;print(torch.version.hip is not None)")
-    if [[ "${CUDA_AVAILABLE}" == "True" ]]; then
-      CONTAINER_FLAVOR="cuda"
-    elif [[ "${ROCM_AVAILABLE}" == "True" ]]; then
-      CONTAINER_FLAVOR="rocm"
-    else
-      CONTAINER_FLAVOR="cpu"
-    fi
-  fi
-
-  # Set PIP_EXTRA_INDEX_URL based on container flavor
-  if [[ "$CONTAINER_FLAVOR" == "rocm" ]]; then
-    PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/rocm"
-  elif [[ "$CONTAINER_FLAVOR" == "cpu" ]]; then
-    PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu"
-  # elif [[ -z "$CONTAINER_FLAVOR" || "$CONTAINER_FLAVOR" == "cuda" ]]; then
-  #   PIP_PACKAGE=${PIP_PACKAGE-".[xformers]"}
-  fi
-fi
-
-# Variables shared by build.sh and run.sh
-REPOSITORY_NAME="${REPOSITORY_NAME-$(basename "$(git rev-parse --show-toplevel)")}"
-REPOSITORY_NAME="${REPOSITORY_NAME,,}"
-VOLUMENAME="${VOLUMENAME-"${REPOSITORY_NAME}_data"}"
-ARCH="${ARCH-$(uname -m)}"
-PLATFORM="${PLATFORM-linux/${ARCH}}"
-INVOKEAI_BRANCH="${INVOKEAI_BRANCH-$(git branch --show)}"
-CONTAINER_REGISTRY="${CONTAINER_REGISTRY-"ghcr.io"}"
-CONTAINER_REPOSITORY="${CONTAINER_REPOSITORY-"$(whoami)/${REPOSITORY_NAME}"}"
-CONTAINER_FLAVOR="${CONTAINER_FLAVOR-cuda}"
-CONTAINER_TAG="${CONTAINER_TAG-"${INVOKEAI_BRANCH##*/}-${CONTAINER_FLAVOR}"}"
-CONTAINER_IMAGE="${CONTAINER_REGISTRY}/${CONTAINER_REPOSITORY}:${CONTAINER_TAG}"
-CONTAINER_IMAGE="${CONTAINER_IMAGE,,}"
-
-# enable docker buildkit
-export DOCKER_BUILDKIT=1

docker/run.sh

@@ -1,41 +1,8 @@
 #!/usr/bin/env bash
 set -e
 
-# How to use: https://invoke-ai.github.io/InvokeAI/installation/040_INSTALL_DOCKER/
-
 SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
 cd "$SCRIPTDIR" || exit 1
 
-source ./env.sh
+docker-compose up --build -d
-
+docker-compose logs -f
-# Create outputs directory if it does not exist
-[[ -d ./outputs ]] || mkdir ./outputs
-
-echo -e "You are using these values:\n"
-echo -e "Volumename:\t${VOLUMENAME}"
-echo -e "Invokeai_tag:\t${CONTAINER_IMAGE}"
-echo -e "local Models:\t${MODELSPATH:-unset}\n"
-
-docker run \
-  --interactive \
-  --tty \
-  --rm \
-  --platform="${PLATFORM}" \
-  --name="${REPOSITORY_NAME}" \
-  --hostname="${REPOSITORY_NAME}" \
-  --mount type=volume,volume-driver=local,source="${VOLUMENAME}",target=/data \
-  --mount type=bind,source="$(pwd)"/outputs/,target=/data/outputs/ \
-  ${MODELSPATH:+--mount="type=bind,source=${MODELSPATH},target=/data/models"} \
-  ${HUGGING_FACE_HUB_TOKEN:+--env="HUGGING_FACE_HUB_TOKEN=${HUGGING_FACE_HUB_TOKEN}"} \
-  --publish=9090:9090 \
-  --cap-add=sys_nice \
-  ${GPU_FLAGS:+--gpus="${GPU_FLAGS}"} \
-  "${CONTAINER_IMAGE}" ${@:+$@}
-
-echo -e "\nCleaning trash folder ..."
-for f in outputs/.Trash*; do
-  if [ -e "$f" ]; then
-    rm -Rf "$f"
-    break
-  fi
-done

docker/runpod-readme.md

@@ -0,0 +1,60 @@
+# InvokeAI - A Stable Diffusion Toolkit
+
+Stable Diffusion distribution by InvokeAI: https://github.com/invoke-ai
+
+The Docker image tracks the `main` branch of the InvokeAI project, which means it includes the latest features, but may contain some bugs.
+
+Your working directory is mounted under the `/workspace` path inside the pod. The models are in `/workspace/invokeai/models`, and outputs are in `/workspace/invokeai/outputs`.
+
+> **Only the /workspace directory will persist between pod restarts!**
+
+> **If you _terminate_ (not just _stop_) the pod, the /workspace will be lost.**
+
+## Quickstart
+
+1. Launch a pod from this template. **It will take about 5-10 minutes to run through the initial setup**. Be patient.
+1. Wait for the application to load.
+    - TIP: you know it's ready when the CPU usage goes idle
+    - You can also check the logs for a line that says "_Point your browser at..._"
+1. Open the Invoke AI web UI: click the `Connect` => `connect over  HTTP` button.
+1. Generate some art!
+
+## Other things you can do
+
+At any point you may edit the pod configuration and set an arbitrary Docker command. For example, you could run a command to downloads some models using `curl`, or fetch some images and place them into your outputs to continue a working session.
+
+If you need to run *multiple commands*, define them in the Docker Command field like this:
+
+`bash -c "cd ${INVOKEAI_ROOT}/outputs; wormhole receive 2-foo-bar; invoke.py --web --host 0.0.0.0"`
+
+### Copying your data in and out of the pod
+
+This image includes a couple of handy tools to help you get the data into the pod (such as your custom models or embeddings), and out of the pod (such as downloading your outputs). Here are your options for getting your data in and out of the pod:
+
+- **SSH server**:
+    1. Make sure to create and set your Public Key in the RunPod settings (follow the official instructions)
+    1. Add an exposed port 22 (TCP) in the pod settings!
+    1. When your pod restarts, you will see a new entry in the `Connect` dialog. Use this SSH server to `scp` or `sftp` your files as necessary, or SSH into the pod using the fully fledged SSH server.
+
+- [**Magic Wormhole**](https://magic-wormhole.readthedocs.io/en/latest/welcome.html):
+    1. On your computer, `pip install magic-wormhole` (see above instructions for details)
+    1. Connect to the command line **using the "light" SSH client** or the browser-based console. _Currently there's a bug where `wormhole` isn't available when connected to "full" SSH server, as described above_.
+    1. `wormhole send /workspace/invokeai/outputs` will send the entire `outputs` directory. You can also send individual files.
+    1. Once packaged, you will see a `wormhole receive <123-some-words>` command. Copy it
+    1. Paste this command into the terminal on your local machine to securely download the payload.
+    1. It works the same in reverse: you can `wormhole send` some models from your computer to the pod. Again, save your files somewhere in `/workspace` or they will be lost when the pod is stopped.
+
+- **RunPod's Cloud Sync feature** may be used to sync the persistent volume to cloud storage. You could, for example, copy the entire `/workspace` to S3, add some custom models to it, and copy it back from S3 when launching new pod configurations. Follow the Cloud Sync instructions.
+
+
+### Disable the NSFW checker
+
+The NSFW checker is enabled by default. To disable it, edit the pod configuration and set the following command:
+
+```
+invoke --web --host 0.0.0.0 --no-nsfw_checker
+```
+
+---
+
+Template ©2023 Eugene Brodsky [ebr](https://github.com/ebr)

installer/lib/installer.py

@@ -248,6 +248,7 @@ class InvokeAiInstance:
                 "install",
                 "--require-virtualenv",
                 "torch~=2.0.0",
+                "torchmetrics==0.11.4",
                 "torchvision>=0.14.1",
                 "--force-reinstall",
                 "--find-links" if find_links is not None else None,

installer/templates/invoke.bat.in

@@ -20,7 +20,7 @@ echo 9. Update InvokeAI
 echo 10. Command-line help
 echo Q - Quit
 set /P choice="Please enter 1-10, Q: [2] "
-if not defined choice set choice=2
+if not defined choice set choice=1
 IF /I "%choice%" == "1" (
     echo Starting the InvokeAI browser-based UI..
     python .venv\Scripts\invokeai-web.exe %*
@@ -56,7 +56,7 @@ IF /I "%choice%" == "1" (
     call cmd /k
 ) ELSE IF /I "%choice%" == "9" (
    echo Running invokeai-update...
-   python .venv\Scripts\invokeai-update.exe %*
+   python -m invokeai.frontend.install.invokeai_update
 ) ELSE IF /I "%choice%" == "10" (
     echo Displaying command line help...
     python .venv\Scripts\invokeai.exe --help %*

installer/templates/invoke.sh.in

@@ -93,7 +93,7 @@ do_choice() {
     9)
         clear
         printf "Update InvokeAI\n"
-        invokeai-update
+        python -m invokeai.frontend.install.invokeai_update
         ;;
     10)
         clear

invokeai/app/api/dependencies.py

@@ -17,6 +17,7 @@ from invokeai.app.services.metadata import CoreMetadataService
 from invokeai.app.services.resource_name import SimpleNameService
 from invokeai.app.services.urls import LocalUrlService
 from invokeai.backend.util.logging import InvokeAILogger
+from invokeai.version.invokeai_version import __version__
 
 from ..services.default_graphs import create_system_graphs
 from ..services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
@@ -58,7 +59,8 @@ class ApiDependencies:
 
     @staticmethod
     def initialize(config, event_handler_id: int, logger: Logger = logger):
-        logger.info(f"Internet connectivity is {config.internet_available}")
+        logger.debug(f'InvokeAI version {__version__}')
+        logger.debug(f"Internet connectivity is {config.internet_available}")
 
         events = FastAPIEventService(event_handler_id)
 

invokeai/app/api_app.py

@@ -1,5 +1,6 @@
-# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
+# Copyright (c) 2022-2023 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
 import asyncio
+import sys
 from inspect import signature
 
 import uvicorn
@@ -20,6 +21,13 @@ from ..backend.util.logging import InvokeAILogger
 app_config = InvokeAIAppConfig.get_config()
 app_config.parse_args()
 logger = InvokeAILogger.getLogger(config=app_config)
+from invokeai.version.invokeai_version import __version__
+
+# we call this early so that the message appears before
+# other invokeai initialization messages
+if app_config.version:
+    print(f'InvokeAI version {__version__}')
+    sys.exit(0)
 
 import invokeai.frontend.web as web_dir
 import mimetypes
@@ -29,6 +37,7 @@ from .api.routers import sessions, models, images, boards, board_images, app_inf
 from .api.sockets import SocketIO
 from .invocations.baseinvocation import BaseInvocation
     
+
 import torch
 if torch.backends.mps.is_available():
     import invokeai.backend.util.mps_fixes

invokeai/app/cli_app.py

@@ -16,6 +16,12 @@ from invokeai.backend.util.logging import InvokeAILogger
 config = InvokeAIAppConfig.get_config()
 config.parse_args()
 logger = InvokeAILogger().getLogger(config=config)
+from invokeai.version.invokeai_version import __version__
+
+# we call this early so that the message appears before other invokeai initialization messages
+if config.version:
+    print(f'InvokeAI version {__version__}')
+    sys.exit(0)
 
 from invokeai.app.services.board_image_record_storage import (
     SqliteBoardImageRecordStorage,
@@ -208,6 +214,7 @@ def invoke_all(context: CliContext):
         raise SessionError()
 
 def invoke_cli():
+    logger.info(f'InvokeAI version {__version__}')
     # get the optional list of invocations to execute on the command line
     parser = config.get_parser()
     parser.add_argument('commands',nargs='*')

invokeai/app/services/config.py

@@ -23,7 +23,8 @@ InvokeAI:
     xformers_enabled: false
     sequential_guidance: false
     precision: float16
-    max_loaded_models: 4
+    max_cache_size: 6
+    max_vram_cache_size: 2.7
     always_use_cpu: false
     free_gpu_mem: false
   Features:
@@ -168,7 +169,7 @@ from argparse import ArgumentParser
 from omegaconf import OmegaConf, DictConfig
 from pathlib import Path
 from pydantic import BaseSettings, Field, parse_obj_as
-from typing import ClassVar, Dict, List, Literal, Union, get_origin, get_type_hints, get_args
+from typing import ClassVar, Dict, List, Set, Literal, Union, get_origin, get_type_hints, get_args
 
 INIT_FILE = Path('invokeai.yaml')
 MODEL_CORE = Path('models/core')
@@ -270,7 +271,8 @@ class InvokeAISettings(BaseSettings):
 
     @classmethod
     def _excluded(self)->List[str]:
-        return ['type','initconf']
+        # combination of deprecated parameters and internal ones
+        return ['type','initconf', 'gpu_mem_reserved', 'max_loaded_models', 'version']
 
     class Config:
         env_file_encoding = 'utf-8'
@@ -363,8 +365,10 @@ setting environment variables INVOKEAI_<setting>.
 
     always_use_cpu      : bool = Field(default=False, description="If true, use the CPU for rendering even if a GPU is available.", category='Memory/Performance')
     free_gpu_mem        : bool = Field(default=False, description="If true, purge model from GPU after each generation.", category='Memory/Performance')
-    max_loaded_models   : int = Field(default=3, gt=0, description="(DEPRECATED: use max_cache_size) Maximum number of models to keep in memory for rapid switching", category='Memory/Performance')
+    max_loaded_models   : int = Field(default=3, gt=0, description="(DEPRECATED: use max_cache_size) Maximum number of models to keep in memory for rapid switching", category='DEPRECATED')
     max_cache_size      : float = Field(default=6.0, gt=0, description="Maximum memory amount used by model cache for rapid switching", category='Memory/Performance')
+    max_vram_cache_size : float = Field(default=2.75, ge=0, description="Amount of VRAM reserved for model storage", category='Memory/Performance')
+    gpu_mem_reserved    : float = Field(default=2.75, ge=0, description="DEPRECATED: use max_vram_cache_size. Amount of VRAM reserved for model storage", category='DEPRECATED')
     precision           : Literal[tuple(['auto','float16','float32','autocast'])] = Field(default='float16',description='Floating point precision', category='Memory/Performance')
     sequential_guidance : bool = Field(default=False, description="Whether to calculate guidance in serial instead of in parallel, lowering memory requirements", category='Memory/Performance')
     xformers_enabled    : bool = Field(default=True, description="Enable/disable memory-efficient attention", category='Memory/Performance')
@@ -389,6 +393,8 @@ setting environment variables INVOKEAI_<setting>.
     # note - would be better to read the log_format values from logging.py, but this creates circular dependencies issues
     log_format          : Literal[tuple(['plain','color','syslog','legacy'])] = Field(default="color", description='Log format. Use "plain" for text-only, "color" for colorized output, "legacy" for 2.3-style logging and "syslog" for syslog-style', category="Logging")
     log_level           : Literal[tuple(["debug","info","warning","error","critical"])] = Field(default="debug", description="Emit logging messages at this level or  higher", category="Logging")
+
+    version             : bool = Field(default=False, description="Show InvokeAI version and exit", category="Other")
     #fmt: on
 
     def parse_args(self, argv: List[str]=None, conf: DictConfig = None, clobber=False):

invokeai/app/services/model_manager_service.py

@@ -258,8 +258,6 @@ class ModelManagerService(ModelManagerServiceBase):
             config_file = config.model_conf_path
         else:
             config_file = config.root_dir / "configs/models.yaml"
-        if not config_file.exists():
-            raise IOError(f"The file {config_file} could not be found.")
             
         logger.debug(f'config file={config_file}')
 

invokeai/app/services/processor.py

@@ -104,6 +104,7 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
 
                 except Exception as e:
                     error = traceback.format_exc()
+                    logger.error(error)
 
                     # Save error
                     graph_execution_state.set_node_error(invocation.id, error)

invokeai/backend/model_management/model_cache.py

@@ -36,6 +36,9 @@ from .models import BaseModelType, ModelType, SubModelType, ModelBase
 # Default is roughly enough to hold three fp16 diffusers models in RAM simultaneously
 DEFAULT_MAX_CACHE_SIZE = 6.0
 
+# amount of GPU memory to hold in reserve for use by generations (GB)
+DEFAULT_MAX_VRAM_CACHE_SIZE= 2.75
+
 # actual size of a gig
 GIG = 1073741824
 
@@ -82,6 +85,7 @@ class ModelCache(object):
     def __init__(
         self,
         max_cache_size: float=DEFAULT_MAX_CACHE_SIZE,
+        max_vram_cache_size: float=DEFAULT_MAX_VRAM_CACHE_SIZE,
         execution_device: torch.device=torch.device('cuda'),
         storage_device: torch.device=torch.device('cpu'),
         precision: torch.dtype=torch.float16,
@@ -99,12 +103,11 @@ class ModelCache(object):
         :param sequential_offload: Conserve VRAM by loading and unloading each stage of the pipeline sequentially
         :param sha_chunksize: Chunksize to use when calculating sha256 model hash
         '''
-        #max_cache_size = 9999
         self.model_infos: Dict[str, ModelBase] = dict()
         self.lazy_offloading = lazy_offloading
-        #self.sequential_offload: bool=sequential_offload
         self.precision: torch.dtype=precision
-        self.max_cache_size: int=max_cache_size
+        self.max_cache_size: float=max_cache_size
+        self.max_vram_cache_size: float=max_vram_cache_size
         self.execution_device: torch.device=execution_device
         self.storage_device: torch.device=storage_device
         self.sha_chunksize=sha_chunksize
@@ -201,14 +204,22 @@ class ModelCache(object):
             self._cache_stack.remove(key)
         self._cache_stack.append(key)
 
-        return self.ModelLocker(self, key, cache_entry.model, gpu_load)
+        return self.ModelLocker(self, key, cache_entry.model, gpu_load, cache_entry.size)
 
     class ModelLocker(object):
-        def __init__(self, cache, key, model, gpu_load):
+        def __init__(self, cache, key, model, gpu_load, size_needed):
+            '''
+            :param cache: The model_cache object
+            :param key: The key of the model to lock in GPU
+            :param model: The model to lock
+            :param gpu_load: True if load into gpu
+            :param size_needed: Size of the model to load
+            '''
             self.gpu_load = gpu_load
             self.cache = cache
             self.key = key
             self.model = model
+            self.size_needed = size_needed
             self.cache_entry = self.cache._cached_models[self.key]
 
         def __enter__(self) -> Any:
@@ -222,7 +233,7 @@ class ModelCache(object):
 
                 try:
                     if self.cache.lazy_offloading:
-                       self.cache._offload_unlocked_models()
+                       self.cache._offload_unlocked_models(self.size_needed)
                        
                     if self.model.device != self.cache.execution_device:
                         self.cache.logger.debug(f'Moving {self.key} into {self.cache.execution_device}')
@@ -337,14 +348,20 @@ class ModelCache(object):
 
         self.logger.debug(f"After unloading: cached_models={len(self._cached_models)}")
 
-
+    def _offload_unlocked_models(self, size_needed: int=0):
-    def _offload_unlocked_models(self):
+        reserved = self.max_vram_cache_size * GIG
-        for model_key, cache_entry in self._cached_models.items():
+        vram_in_use = torch.cuda.memory_allocated()
+        self.logger.debug(f'{(vram_in_use/GIG):.2f}GB VRAM used for models; max allowed={(reserved/GIG):.2f}GB')
+        for model_key, cache_entry in sorted(self._cached_models.items(), key=lambda x:x[1].size):
+            if vram_in_use <= reserved:
+                break
             if not cache_entry.locked and cache_entry.loaded:
                 self.logger.debug(f'Offloading {model_key} from {self.execution_device} into {self.storage_device}')
                 with VRAMUsage() as mem:
                     cache_entry.model.to(self.storage_device)
                 self.logger.debug(f'GPU VRAM freed: {(mem.vram_used/GIG):.2f} GB')
+                vram_in_use += mem.vram_used  # note vram_used is negative
+                self.logger.debug(f'{(vram_in_use/GIG):.2f}GB VRAM used for models; max allowed={(reserved/GIG):.2f}GB')
         
     def _local_model_hash(self, model_path: Union[str, Path]) -> str:
         sha = hashlib.sha256()

invokeai/backend/model_management/model_manager.py

@@ -231,6 +231,7 @@ from __future__ import annotations
 import os
 import hashlib
 import textwrap
+import yaml
 from dataclasses import dataclass
 from pathlib import Path
 from typing import Optional, List, Tuple, Union, Dict, Set, Callable, types
@@ -249,8 +250,8 @@ from .model_cache import ModelCache, ModelLocker
 from .models import (
     BaseModelType, ModelType, SubModelType,
     ModelError, SchedulerPredictionType, MODEL_CLASSES,
-    ModelConfigBase, ModelNotFoundException,
+    ModelConfigBase, ModelNotFoundException, InvalidModelException,
-    )
+)
 
 # We are only starting to number the config file with release 3.
 # The config file version doesn't have to start at release version, but it will help
@@ -274,10 +275,6 @@ class ModelInfo():
     def __exit__(self,*args, **kwargs):
         self.context.__exit__(*args, **kwargs)
 
-class InvalidModelError(Exception):
-    "Raised when an invalid model is requested"
-    pass
-
 class AddModelResult(BaseModel):
     name: str = Field(description="The name of the model after installation")
     model_type: ModelType = Field(description="The type of model")
@@ -314,6 +311,9 @@ class ModelManager(object):
         self.config_path = None
         if isinstance(config, (str, Path)):
             self.config_path = Path(config)
+            if not self.config_path.exists():
+                logger.warning(f'The file {self.config_path} was not found. Initializing a new file')
+                self.initialize_model_config(self.config_path)
             config = OmegaConf.load(self.config_path)
 
         elif not isinstance(config, DictConfig):
@@ -336,6 +336,7 @@ class ModelManager(object):
         self.logger = logger
         self.cache = ModelCache(
             max_cache_size=max_cache_size,
+            max_vram_cache_size = self.app_config.max_vram_cache_size,
             execution_device = device_type,
             precision = precision,
             sequential_offload = sequential_offload,
@@ -386,6 +387,16 @@ class ModelManager(object):
     def _get_model_cache_path(self, model_path):
         return self.app_config.models_path / ".cache" / hashlib.md5(str(model_path).encode()).hexdigest()
 
+    @classmethod
+    def initialize_model_config(cls, config_path: Path):
+        """Create empty config file"""
+        with open(config_path,'w') as yaml_file:
+            yaml_file.write(yaml.dump({'__metadata__':
+                                       {'version':'3.0.0'}
+                                       }
+                                      )
+                            )
+
     def get_model(
         self,
         model_name: str,
@@ -802,6 +813,8 @@ class ModelManager(object):
                                 model_config: ModelConfigBase = model_class.probe_config(str(model_path))
                                 self.models[model_key] = model_config
                                 new_models_found = True
+                            except InvalidModelException:
+                                self.logger.warning(f"Not a valid model: {model_path}")
                             except NotImplementedError as e:
                                 self.logger.warning(e)
 
@@ -853,16 +866,22 @@ class ModelManager(object):
                         scanned_dirs.add(path)
                         continue
                     if any([(path/x).exists() for x in {'config.json','model_index.json','learned_embeds.bin','pytorch_lora_weights.bin'}]):
-                        new_models_found.update(installer.heuristic_import(path))
+                        try:
-                        scanned_dirs.add(path)
+                            new_models_found.update(installer.heuristic_import(path))
+                            scanned_dirs.add(path)
+                        except ValueError as e:
+                            self.logger.warning(str(e))
 
                 for f in files:
                     path = Path(root) / f
                     if path in known_paths or path.parent in scanned_dirs:
                         continue
                     if path.suffix in {'.ckpt','.bin','.pth','.safetensors','.pt'}:
-                        import_result = installer.heuristic_import(path)
+                        try:
-                        new_models_found.update(import_result)
+                            import_result = installer.heuristic_import(path)
+                            new_models_found.update(import_result)
+                        except ValueError as e:
+                            self.logger.warning(str(e))
 
             self.logger.info(f'Scanned {items_scanned} files and directories, imported {len(new_models_found)} models')
             installed.update(new_models_found)

invokeai/backend/model_management/model_probe.py

@@ -59,7 +59,7 @@ class ModelProbe(object):
         elif isinstance(model,(dict,ModelMixin,ConfigMixin)):
             return cls.probe(model_path=None, model=model, prediction_type_helper=prediction_type_helper)
         else:
-            raise Exception("model parameter {model} is neither a Path, nor a model")
+            raise ValueError("model parameter {model} is neither a Path, nor a model")
 
     @classmethod
     def probe(cls,
@@ -237,7 +237,7 @@ class CheckpointProbeBase(ProbeBase):
         elif in_channels == 4:
             return ModelVariantType.Normal
         else:
-            raise Exception("Cannot determine variant type")
+            raise ValueError(f"Cannot determine variant type (in_channels={in_channels}) at {self.checkpoint_path}")
 
 class PipelineCheckpointProbe(CheckpointProbeBase):
     def get_base_type(self)->BaseModelType:
@@ -248,7 +248,7 @@ class PipelineCheckpointProbe(CheckpointProbeBase):
             return BaseModelType.StableDiffusion1
         if key_name in state_dict and state_dict[key_name].shape[-1] == 1024:
             return BaseModelType.StableDiffusion2
-        raise Exception("Cannot determine base type")
+        raise ValueError("Cannot determine base type")
 
     def get_scheduler_prediction_type(self)->SchedulerPredictionType:
         type = self.get_base_type()
@@ -329,7 +329,7 @@ class ControlNetCheckpointProbe(CheckpointProbeBase):
                 return BaseModelType.StableDiffusion2
             elif self.checkpoint_path and self.helper:
                 return self.helper(self.checkpoint_path)
-        raise Exception("Unable to determine base type for {self.checkpoint_path}")
+        raise ValueError("Unable to determine base type for {self.checkpoint_path}")
 
 ########################################################
 # classes for probing folders
@@ -418,7 +418,7 @@ class ControlNetFolderProbe(FolderProbeBase):
     def get_base_type(self)->BaseModelType:
         config_file = self.folder_path / 'config.json'
         if not config_file.exists():
-            raise Exception(f"Cannot determine base type for {self.folder_path}")
+            raise ValueError(f"Cannot determine base type for {self.folder_path}")
         with open(config_file,'r') as file:
             config = json.load(file)
         # no obvious way to distinguish between sd2-base and sd2-768
@@ -435,7 +435,7 @@ class LoRAFolderProbe(FolderProbeBase):
                 model_file = base_file
                 break
         if not model_file:
-            raise Exception('Unknown LoRA format encountered')
+            raise ValueError('Unknown LoRA format encountered')
         return LoRACheckpointProbe(model_file,None).get_base_type()
 
 ############## register probe classes ######

invokeai/backend/model_management/models/__init__.py

@@ -2,7 +2,7 @@ import inspect
 from enum import Enum
 from pydantic import BaseModel
 from typing import Literal, get_origin
-from .base import BaseModelType, ModelType, SubModelType, ModelBase, ModelConfigBase, ModelVariantType, SchedulerPredictionType, ModelError, SilenceWarnings, ModelNotFoundException
+from .base import BaseModelType, ModelType, SubModelType, ModelBase, ModelConfigBase, ModelVariantType, SchedulerPredictionType, ModelError, SilenceWarnings, ModelNotFoundException, InvalidModelException
 from .stable_diffusion import StableDiffusion1Model, StableDiffusion2Model
 from .vae import VaeModel
 from .lora import LoRAModel

invokeai/backend/model_management/models/base.py

@@ -15,6 +15,9 @@ from contextlib import suppress
 from pydantic import BaseModel, Field
 from typing import List, Dict, Optional, Type, Literal, TypeVar, Generic, Callable, Any, Union
 
+class InvalidModelException(Exception):
+    pass
+
 class ModelNotFoundException(Exception):
     pass
 

invokeai/backend/model_management/models/controlnet.py

@@ -13,6 +13,7 @@ from .base import (
     calc_model_size_by_fs,
     calc_model_size_by_data,
     classproperty,
+    InvalidModelException,
 )
 
 class ControlNetModelFormat(str, Enum):
@@ -73,10 +74,18 @@ class ControlNetModel(ModelBase):
 
     @classmethod
     def detect_format(cls, path: str):
+        if not os.path.exists(path):
+            raise ModelNotFoundException()
+
         if os.path.isdir(path):
-            return ControlNetModelFormat.Diffusers
+            if os.path.exists(os.path.join(path, "config.json")):
-        else:
+                return ControlNetModelFormat.Diffusers
-            return ControlNetModelFormat.Checkpoint
+
+        if os.path.isfile(path):
+            if any([path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt", "pth"]]):
+                return ControlNetModelFormat.Checkpoint
+
+        raise InvalidModelException(f"Not a valid model: {path}")
 
     @classmethod
     def convert_if_required(

invokeai/backend/model_management/models/lora.py

@@ -9,6 +9,7 @@ from .base import (
     ModelType,
     SubModelType,
     classproperty,
+    InvalidModelException,
 )
 # TODO: naming
 from ..lora import LoRAModel as LoRAModelRaw
@@ -56,10 +57,18 @@ class LoRAModel(ModelBase):
 
     @classmethod
     def detect_format(cls, path: str):
+        if not os.path.exists(path):
+            raise ModelNotFoundException()
+
         if os.path.isdir(path):
-            return LoRAModelFormat.Diffusers
+            if os.path.exists(os.path.join(path, "pytorch_lora_weights.bin")):
-        else:
+                return LoRAModelFormat.Diffusers
-            return LoRAModelFormat.LyCORIS
+
+        if os.path.isfile(path):
+            if any([path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt"]]):
+                return LoRAModelFormat.LyCORIS
+
+        raise InvalidModelException(f"Not a valid model: {path}")
 
     @classmethod
     def convert_if_required(

invokeai/backend/model_management/models/stable_diffusion.py

@@ -16,6 +16,7 @@ from .base import (
     SilenceWarnings,
     read_checkpoint_meta,
     classproperty,
+    InvalidModelException,
 )
 from invokeai.app.services.config import InvokeAIAppConfig
 from omegaconf import OmegaConf
@@ -98,10 +99,18 @@ class StableDiffusion1Model(DiffusersModel):
 
     @classmethod
     def detect_format(cls, model_path: str):
+        if not os.path.exists(model_path):
+            raise ModelNotFoundException()
+
         if os.path.isdir(model_path):
-            return StableDiffusion1ModelFormat.Diffusers
+            if os.path.exists(os.path.join(model_path, "model_index.json")):
-        else:
+                return StableDiffusion1ModelFormat.Diffusers
-            return StableDiffusion1ModelFormat.Checkpoint
+
+        if os.path.isfile(model_path):
+            if any([model_path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt"]]):
+                return StableDiffusion1ModelFormat.Checkpoint
+
+        raise InvalidModelException(f"Not a valid model: {model_path}")
 
     @classmethod
     def convert_if_required(
@@ -200,10 +209,18 @@ class StableDiffusion2Model(DiffusersModel):
 
     @classmethod
     def detect_format(cls, model_path: str):
+        if not os.path.exists(model_path):
+            raise ModelNotFoundException()
+
         if os.path.isdir(model_path):
-            return StableDiffusion2ModelFormat.Diffusers
+            if os.path.exists(os.path.join(model_path, "model_index.json")):
-        else:
+                return StableDiffusion2ModelFormat.Diffusers
-            return StableDiffusion2ModelFormat.Checkpoint
+
+        if os.path.isfile(model_path):
+            if any([model_path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt"]]):
+                return StableDiffusion2ModelFormat.Checkpoint
+
+        raise InvalidModelException(f"Not a valid model: {model_path}")
 
     @classmethod
     def convert_if_required(

invokeai/backend/model_management/models/textual_inversion.py

@@ -9,6 +9,7 @@ from .base import (
     SubModelType,
     classproperty,
     ModelNotFoundException,
+    InvalidModelException,
 )
 # TODO: naming
 from ..lora import TextualInversionModel as TextualInversionModelRaw
@@ -59,7 +60,18 @@ class TextualInversionModel(ModelBase):
 
     @classmethod
     def detect_format(cls, path: str):
-        return None
+        if not os.path.exists(path):
+            raise ModelNotFoundException()
+
+        if os.path.isdir(path):
+            if os.path.exists(os.path.join(path, "learned_embeds.bin")):
+                return None # diffusers-ti
+
+        if os.path.isfile(path):
+            if any([path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt"]]):
+                return None
+
+        raise InvalidModelException(f"Not a valid model: {path}")
 
     @classmethod
     def convert_if_required(

invokeai/backend/model_management/models/vae.py

@@ -15,6 +15,7 @@ from .base import (
     calc_model_size_by_fs,
     calc_model_size_by_data,
     classproperty,
+    InvalidModelException,
 )
 from invokeai.app.services.config import InvokeAIAppConfig
 from diffusers.utils import is_safetensors_available
@@ -75,10 +76,18 @@ class VaeModel(ModelBase):
 
     @classmethod
     def detect_format(cls, path: str):
+        if not os.path.exists(path):
+            raise ModelNotFoundException()
+
         if os.path.isdir(path):
-            return VaeModelFormat.Diffusers
+            if os.path.exists(os.path.join(path, "config.json")):
-        else:
+                return VaeModelFormat.Diffusers
-            return VaeModelFormat.Checkpoint
+
+        if os.path.isfile(path):
+            if any([path.endswith(f".{ext}") for ext in ["safetensors", "ckpt", "pt"]]):
+                return VaeModelFormat.Checkpoint
+
+        raise InvalidModelException(f"Not a valid model: {path}")
 
     @classmethod
     def convert_if_required(

invokeai/frontend/install/model_install.py

@@ -773,7 +773,7 @@ def main():
     config.parse_args(invoke_args)
     logger = InvokeAILogger().getLogger(config=config)
 
-    if not (config.root_dir / config.conf_path.parent).exists():
+    if not (config.conf_path / 'models.yaml').exists():
         logger.info(
             "Your InvokeAI root directory is not set up. Calling invokeai-configure."
         )

invokeai/frontend/web/dist/index.html

@@ -12,7 +12,7 @@
         margin: 0;
       }
     </style>
-    <script type="module" crossorigin src="./assets/index-581af3d4.js"></script>
+    <script type="module" crossorigin src="./assets/index-078526aa.js"></script>
   </head>
 
   <body dir="ltr">

invokeai/frontend/web/dist/locales/en.json

@@ -53,7 +53,7 @@
         "linear": "Linear",
         "nodes": "Node Editor",
         "batch": "Batch Manager",
-        "modelmanager": "Model Manager",
+        "modelManager": "Model Manager",
         "postprocessing": "Post Processing",
         "nodesDesc": "A node based system for the generation of images is under development currently. Stay tuned for updates about this amazing feature.",
         "postProcessing": "Post Processing",
@@ -527,7 +527,9 @@
         "showOptionsPanel": "Show Options Panel",
         "hidePreview": "Hide Preview",
         "showPreview": "Show Preview",
-        "controlNetControlMode": "Control Mode"
+        "controlNetControlMode": "Control Mode",
+        "clipSkip": "Clip Skip",
+        "aspectRatio": "Ratio"
     },
     "settings": {
         "models": "Models",
@@ -551,7 +553,8 @@
         "generation": "Generation",
         "ui": "User Interface",
         "favoriteSchedulers": "Favorite Schedulers",
-        "favoriteSchedulersPlaceholder": "No schedulers favorited"
+        "favoriteSchedulersPlaceholder": "No schedulers favorited",
+        "showAdvancedOptions": "Show Advanced Options"
     },
     "toast": {
         "serverError": "Server Error",
@@ -669,6 +672,7 @@
     },
     "ui": {
         "showProgressImages": "Show Progress Images",
-        "hideProgressImages": "Hide Progress Images"
+        "hideProgressImages": "Hide Progress Images",
+        "swapSizes": "Swap Sizes"
     }
 }

invokeai/frontend/web/public/locales/en.json

@@ -53,7 +53,7 @@
         "linear": "Linear",
         "nodes": "Node Editor",
         "batch": "Batch Manager",
-        "modelmanager": "Model Manager",
+        "modelManager": "Model Manager",
         "postprocessing": "Post Processing",
         "nodesDesc": "A node based system for the generation of images is under development currently. Stay tuned for updates about this amazing feature.",
         "postProcessing": "Post Processing",
@@ -593,7 +593,10 @@
         "metadataLoadFailed": "Failed to load metadata",
         "initialImageSet": "Initial Image Set",
         "initialImageNotSet": "Initial Image Not Set",
-        "initialImageNotSetDesc": "Could not load initial image"
+        "initialImageNotSetDesc": "Could not load initial image",
+        "nodesSaved": "Nodes Saved",
+        "nodesLoaded": "Nodes Loaded",
+        "nodesLoadedFailed": "Failed To Load Nodes"
     },
     "tooltip": {
         "feature": {
@@ -674,5 +677,10 @@
         "showProgressImages": "Show Progress Images",
         "hideProgressImages": "Hide Progress Images",
         "swapSizes": "Swap Sizes"
+    },
+    "nodes": {
+        "reloadSchema": "Reload Schema",
+        "saveNodes": "Save Nodes",
+        "loadNodes": "Load Nodes"
     }
 }

invokeai/frontend/web/src/app/types/invokeai.ts

@@ -102,6 +102,8 @@ export type AppFeature =
 export type SDFeature =
   | 'controlNet'
   | 'noise'
+  | 'perlinNoise'
+  | 'noiseThreshold'
   | 'variation'
   | 'symmetry'
   | 'seamless'

invokeai/frontend/web/src/features/gallery/components/GalleryImage.tsx

@@ -53,13 +53,15 @@ const GalleryImage = (props: HoverableImageProps) => {
 
   const handleClick = useCallback(
     (e: MouseEvent<HTMLDivElement>) => {
-      if (e.shiftKey) {
+      // multiselect disabled for now
-        dispatch(imageRangeEndSelected(props.imageDTO.image_name));
+      // if (e.shiftKey) {
-      } else if (e.ctrlKey || e.metaKey) {
+      //   dispatch(imageRangeEndSelected(props.imageDTO.image_name));
-        dispatch(imageSelectionToggled(props.imageDTO.image_name));
+      // } else if (e.ctrlKey || e.metaKey) {
-      } else {
+      //   dispatch(imageSelectionToggled(props.imageDTO.image_name));
-        dispatch(imageSelected(props.imageDTO.image_name));
+      // } else {
-      }
+      //   dispatch(imageSelected(props.imageDTO.image_name));
+      // }
+      dispatch(imageSelected(props.imageDTO.image_name));
     },
     [dispatch, props.imageDTO.image_name]
   );
@@ -121,6 +123,7 @@ const GalleryImage = (props: HoverableImageProps) => {
               // withResetIcon // removed bc it's too easy to accidentally delete images
               isDropDisabled={true}
               isUploadDisabled={true}
+              thumbnail={true}
             />
           </Box>
         )}

invokeai/frontend/web/src/features/nodes/components/Flow.tsx

@@ -7,6 +7,7 @@ import {
   OnConnectEnd,
   OnConnectStart,
   OnEdgesChange,
+  OnInit,
   OnNodesChange,
   ReactFlow,
 } from 'reactflow';
@@ -16,6 +17,7 @@ import {
   connectionStarted,
   edgesChanged,
   nodesChanged,
+  setEditorInstance,
 } from '../store/nodesSlice';
 import { InvocationComponent } from './InvocationComponent';
 import ProgressImageNode from './ProgressImageNode';
@@ -67,6 +69,14 @@ export const Flow = () => {
     dispatch(connectionEnded());
   }, [dispatch]);
 
+  const onInit: OnInit = useCallback(
+    (v) => {
+      dispatch(setEditorInstance(v));
+      if (v) v.fitView();
+    },
+    [dispatch]
+  );
+
   return (
     <ReactFlow
       nodeTypes={nodeTypes}
@@ -77,6 +87,7 @@ export const Flow = () => {
       onConnectStart={onConnectStart}
       onConnect={onConnect}
       onConnectEnd={onConnectEnd}
+      onInit={onInit}
       defaultEdgeOptions={{
         style: { strokeWidth: 2 },
       }}

invokeai/frontend/web/src/features/nodes/components/panels/TopCenterPanel.tsx

@@ -1,25 +1,21 @@
 import { HStack } from '@chakra-ui/react';
-import { useAppDispatch } from 'app/store/storeHooks';
-import IAIButton from 'common/components/IAIButton';
-import { memo, useCallback } from 'react';
-import { Panel } from 'reactflow';
-import { receivedOpenAPISchema } from 'services/api/thunks/schema';
-import NodeInvokeButton from '../ui/NodeInvokeButton';
 import CancelButton from 'features/parameters/components/ProcessButtons/CancelButton';
+import { memo } from 'react';
+import { Panel } from 'reactflow';
+import LoadNodesButton from '../ui/LoadNodesButton';
+import NodeInvokeButton from '../ui/NodeInvokeButton';
+import ReloadSchemaButton from '../ui/ReloadSchemaButton';
+import SaveNodesButton from '../ui/SaveNodesButton';
 
 const TopCenterPanel = () => {
-  const dispatch = useAppDispatch();
-
-  const handleReloadSchema = useCallback(() => {
-    dispatch(receivedOpenAPISchema());
-  }, [dispatch]);
-
   return (
     <Panel position="top-center">
       <HStack>
         <NodeInvokeButton />
         <CancelButton />
-        <IAIButton onClick={handleReloadSchema}>Reload Schema</IAIButton>
+        <ReloadSchemaButton />
+        <SaveNodesButton />
+        <LoadNodesButton />
       </HStack>
     </Panel>
   );

invokeai/frontend/web/src/features/nodes/components/ui/LoadNodesButton.tsx

@@ -0,0 +1,79 @@
+import { FileButton } from '@mantine/core';
+import { makeToast } from 'app/components/Toaster';
+import { useAppDispatch } from 'app/store/storeHooks';
+import IAIIconButton from 'common/components/IAIIconButton';
+import { loadFileEdges, loadFileNodes } from 'features/nodes/store/nodesSlice';
+import { addToast } from 'features/system/store/systemSlice';
+import { memo, useCallback, useRef } from 'react';
+import { useTranslation } from 'react-i18next';
+import { FaUpload } from 'react-icons/fa';
+import { useReactFlow } from 'reactflow';
+
+const LoadNodesButton = () => {
+  const { t } = useTranslation();
+  const dispatch = useAppDispatch();
+  const { fitView } = useReactFlow();
+
+  const uploadedFileRef = useRef<() => void>(null);
+
+  const restoreJSONToEditor = useCallback(
+    (v: File | null) => {
+      if (!v) return;
+      const reader = new FileReader();
+      reader.onload = async () => {
+        const json = reader.result;
+        const retrievedNodeTree = await JSON.parse(String(json));
+
+        if (!retrievedNodeTree) {
+          dispatch(
+            addToast(
+              makeToast({
+                title: t('toast.nodesLoadedFailed'),
+                status: 'error',
+              })
+            )
+          );
+        }
+
+        if (retrievedNodeTree) {
+          dispatch(loadFileNodes(retrievedNodeTree.nodes));
+          dispatch(loadFileEdges(retrievedNodeTree.edges));
+          fitView();
+
+          dispatch(
+            addToast(
+              makeToast({ title: t('toast.nodesLoaded'), status: 'success' })
+            )
+          );
+        }
+
+        // Cleanup
+        reader.abort();
+      };
+
+      reader.readAsText(v);
+
+      // Cleanup
+      uploadedFileRef.current?.();
+    },
+    [fitView, dispatch, t]
+  );
+  return (
+    <FileButton
+      resetRef={uploadedFileRef}
+      accept="application/json"
+      onChange={restoreJSONToEditor}
+    >
+      {(props) => (
+        <IAIIconButton
+          icon={<FaUpload />}
+          tooltip={t('nodes.loadNodes')}
+          aria-label={t('nodes.loadNodes')}
+          {...props}
+        />
+      )}
+    </FileButton>
+  );
+};
+
+export default memo(LoadNodesButton);

invokeai/frontend/web/src/features/nodes/components/ui/ReloadSchemaButton.tsx

@@ -0,0 +1,24 @@
+import { useAppDispatch } from 'app/store/storeHooks';
+import IAIIconButton from 'common/components/IAIIconButton';
+import { useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { FaSyncAlt } from 'react-icons/fa';
+import { receivedOpenAPISchema } from 'services/api/thunks/schema';
+
+export default function ReloadSchemaButton() {
+  const { t } = useTranslation();
+  const dispatch = useAppDispatch();
+
+  const handleReloadSchema = useCallback(() => {
+    dispatch(receivedOpenAPISchema());
+  }, [dispatch]);
+
+  return (
+    <IAIIconButton
+      icon={<FaSyncAlt />}
+      tooltip={t('nodes.reloadSchema')}
+      aria-label={t('nodes.reloadSchema')}
+      onClick={handleReloadSchema}
+    />
+  );
+}

invokeai/frontend/web/src/features/nodes/components/ui/SaveNodesButton.tsx

@@ -0,0 +1,45 @@
+import { RootState } from 'app/store/store';
+import { useAppSelector } from 'app/store/storeHooks';
+import IAIIconButton from 'common/components/IAIIconButton';
+import { map, omit } from 'lodash-es';
+import { memo, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { FaSave } from 'react-icons/fa';
+
+const SaveNodesButton = () => {
+  const { t } = useTranslation();
+  const editorInstance = useAppSelector(
+    (state: RootState) => state.nodes.editorInstance
+  );
+
+  const saveEditorToJSON = useCallback(() => {
+    if (editorInstance) {
+      const editorState = editorInstance.toObject();
+
+      editorState.edges = map(editorState.edges, (edge) => {
+        return omit(edge, ['style']);
+      });
+
+      const nodeSetupJSON = new Blob([JSON.stringify(editorState)]);
+      const nodeDownloadElement = document.createElement('a');
+      nodeDownloadElement.href = URL.createObjectURL(nodeSetupJSON);
+      nodeDownloadElement.download = 'MyNodes.json';
+      document.body.appendChild(nodeDownloadElement);
+      nodeDownloadElement.click();
+      // Cleanup
+      nodeDownloadElement.remove();
+    }
+  }, [editorInstance]);
+
+  return (
+    <IAIIconButton
+      icon={<FaSave />}
+      fontSize={18}
+      tooltip={t('nodes.saveNodes')}
+      aria-label={t('nodes.saveNodes')}
+      onClick={saveEditorToJSON}
+    />
+  );
+};
+
+export default memo(SaveNodesButton);

invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts

@@ -13,6 +13,7 @@ import {
   Node,
   NodeChange,
   OnConnectStartParams,
+  ReactFlowInstance,
 } from 'reactflow';
 import { receivedOpenAPISchema } from 'services/api/thunks/schema';
 import { ImageField } from 'services/api/types';
@@ -25,6 +26,7 @@ export type NodesState = {
   invocationTemplates: Record<string, InvocationTemplate>;
   connectionStartParams: OnConnectStartParams | null;
   shouldShowGraphOverlay: boolean;
+  editorInstance: ReactFlowInstance | undefined;
 };
 
 export const initialNodesState: NodesState = {
@@ -34,6 +36,7 @@ export const initialNodesState: NodesState = {
   invocationTemplates: {},
   connectionStartParams: null,
   shouldShowGraphOverlay: false,
+  editorInstance: undefined,
 };
 
 const nodesSlice = createSlice({
@@ -121,6 +124,15 @@ const nodesSlice = createSlice({
     nodeEditorReset: () => {
       return { ...initialNodesState };
     },
+    setEditorInstance: (state, action) => {
+      state.editorInstance = action.payload;
+    },
+    loadFileNodes: (state, action: PayloadAction<Node<InvocationValue>[]>) => {
+      state.nodes = action.payload;
+    },
+    loadFileEdges: (state, action: PayloadAction<Edge[]>) => {
+      state.edges = action.payload;
+    },
   },
   extraReducers: (builder) => {
     builder.addCase(receivedOpenAPISchema.fulfilled, (state, action) => {
@@ -141,6 +153,9 @@ export const {
   nodeTemplatesBuilt,
   nodeEditorReset,
   imageCollectionFieldValueChanged,
+  setEditorInstance,
+  loadFileNodes,
+  loadFileEdges,
 } = nodesSlice.actions;
 
 export default nodesSlice.reducer;

invokeai/frontend/web/src/features/parameters/components/Parameters/Core/ParamAspectRatio.tsx

@@ -3,6 +3,7 @@ import { RootState } from 'app/store/store';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIButton from 'common/components/IAIButton';
 import { setAspectRatio } from 'features/ui/store/uiSlice';
+import { activeTabNameSelector } from '../../../../ui/store/uiSelectors';
 
 const aspectRatios = [
   { name: 'Free', value: null },
@@ -17,6 +18,10 @@ export default function ParamAspectRatio() {
   );
 
   const dispatch = useAppDispatch();
+  const shouldFitToWidthHeight = useAppSelector(
+    (state: RootState) => state.generation.shouldFitToWidthHeight
+  );
+  const activeTabName = useAppSelector(activeTabNameSelector);
 
   return (
     <Flex gap={2} flexGrow={1}>
@@ -26,6 +31,9 @@ export default function ParamAspectRatio() {
             key={ratio.name}
             size="sm"
             isChecked={aspectRatio === ratio.value}
+            isDisabled={
+              activeTabName === 'img2img' ? !shouldFitToWidthHeight : false
+            }
             onClick={() => dispatch(setAspectRatio(ratio.value))}
           >
             {ratio.name}

invokeai/frontend/web/src/features/parameters/components/Parameters/Core/ParamSize.tsx

@@ -8,6 +8,7 @@ import { MdOutlineSwapVert } from 'react-icons/md';
 import ParamAspectRatio from './ParamAspectRatio';
 import ParamHeight from './ParamHeight';
 import ParamWidth from './ParamWidth';
+import { activeTabNameSelector } from '../../../../ui/store/uiSelectors';
 
 export default function ParamSize() {
   const { t } = useTranslation();
@@ -15,6 +16,7 @@ export default function ParamSize() {
   const shouldFitToWidthHeight = useAppSelector(
     (state: RootState) => state.generation.shouldFitToWidthHeight
   );
+  const activeTabName = useAppSelector(activeTabNameSelector);
   return (
     <Flex
       sx={{
@@ -50,13 +52,24 @@ export default function ParamSize() {
           size="sm"
           icon={<MdOutlineSwapVert />}
           fontSize={20}
+          isDisabled={
+            activeTabName === 'img2img' ? !shouldFitToWidthHeight : false
+          }
           onClick={() => dispatch(toggleSize())}
         />
       </Flex>
       <Flex gap={2} alignItems="center">
         <Flex gap={2} flexDirection="column" width="full">
-          <ParamWidth isDisabled={!shouldFitToWidthHeight} />
+          <ParamWidth
-          <ParamHeight isDisabled={!shouldFitToWidthHeight} />
+            isDisabled={
+              activeTabName === 'img2img' ? !shouldFitToWidthHeight : false
+            }
+          />
+          <ParamHeight
+            isDisabled={
+              activeTabName === 'img2img' ? !shouldFitToWidthHeight : false
+            }
+          />
         </Flex>
       </Flex>
     </Flex>

invokeai/frontend/web/src/features/parameters/components/Parameters/Noise/ParamNoiseCollapse.tsx

@@ -27,6 +27,9 @@ const ParamNoiseCollapse = () => {
   const { t } = useTranslation();
 
   const isNoiseEnabled = useFeatureStatus('noise').isFeatureEnabled;
+  const isPerlinNoiseEnabled = useFeatureStatus('perlinNoise').isFeatureEnabled;
+  const isNoiseThresholdEnabled =
+    useFeatureStatus('noiseThreshold').isFeatureEnabled;
 
   const { activeLabel } = useAppSelector(selector);
 
@@ -42,8 +45,8 @@ const ParamNoiseCollapse = () => {
       <Flex sx={{ gap: 2, flexDirection: 'column' }}>
         <ParamNoiseToggle />
         <ParamCpuNoiseToggle />
-        <ParamPerlinNoise />
+        {isPerlinNoiseEnabled && <ParamPerlinNoise />}
-        <ParamNoiseThreshold />
+        {isNoiseThresholdEnabled && <ParamNoiseThreshold />}
       </Flex>
     </IAICollapse>
   );

invokeai/frontend/web/src/features/system/store/configSlice.ts

@@ -6,8 +6,15 @@ import { merge } from 'lodash-es';
 export const initialConfigState: AppConfig = {
   shouldUpdateImagesOnConnect: false,
   disabledTabs: [],
-  disabledFeatures: [],
+  disabledFeatures: ['lightbox', 'faceRestore'],
-  disabledSDFeatures: [],
+  disabledSDFeatures: [
+    'variation',
+    'seamless',
+    'symmetry',
+    'hires',
+    'perlinNoise',
+    'noiseThreshold',
+  ],
   canRestoreDeletedImagesFromBin: true,
   sd: {
     disabledControlNetModels: [],

invokeai/frontend/web/src/features/ui/components/InvokeTabs.tsx

@@ -38,6 +38,7 @@ import NodesTab from './tabs/Nodes/NodesTab';
 import ResizeHandle from './tabs/ResizeHandle';
 import TextToImageTab from './tabs/TextToImage/TextToImageTab';
 import UnifiedCanvasTab from './tabs/UnifiedCanvas/UnifiedCanvasTab';
+import { useFeatureStatus } from '../../system/hooks/useFeatureStatus';
 
 export interface InvokeTabInfo {
   id: InvokeTabName;
@@ -107,6 +108,7 @@ const InvokeTabs = () => {
   const isLightBoxOpen = useAppSelector(
     (state: RootState) => state.lightbox.isLightboxOpen
   );
+  const isLightboxEnabled = useFeatureStatus('lightbox').isFeatureEnabled;
 
   const { shouldPinGallery, shouldPinParametersPanel, shouldShowGallery } =
     useAppSelector((state: RootState) => state.ui);
@@ -119,7 +121,9 @@ const InvokeTabs = () => {
   useHotkeys(
     'z',
     () => {
-      dispatch(setIsLightboxOpen(!isLightBoxOpen));
+      if (isLightboxEnabled) {
+        dispatch(setIsLightboxOpen(!isLightBoxOpen));
+      }
     },
     [isLightBoxOpen]
   );

invokeai/version/invokeai_version.py

@@ -1 +1 @@
-__version__ = "3.0.0+b1"
+__version__ = "3.0.0+b5"

tests/test_config.py

@@ -15,7 +15,7 @@ InvokeAI:
   Features:
     nsfw_checker: False
   Memory/Performance:
-    max_loaded_models: 5
+    max_cache_size: 5
 '''
 )
 
@@ -25,7 +25,7 @@ InvokeAI:
   Features:
     nsfw_checker: true
   Memory/Performance:
-    max_loaded_models: 2
+    max_cache_size: 2
 '''
 )
 
@@ -36,46 +36,46 @@ def test_use_init():
     conf1 = InvokeAIAppConfig.get_config()
     assert conf1
     conf1.parse_args(conf=init1,argv=[])
-    assert conf1.max_loaded_models==5
+    assert conf1.max_cache_size==5
     assert not conf1.nsfw_checker
 
     conf2 = InvokeAIAppConfig.get_config()
     assert conf2
     conf2.parse_args(conf=init2,argv=[])
     assert conf2.nsfw_checker
-    assert conf2.max_loaded_models==2
+    assert conf2.max_cache_size==2
     assert not hasattr(conf2,'invalid_attribute')
     
 def test_argv_override():
     conf = InvokeAIAppConfig.get_config()
-    conf.parse_args(conf=init1,argv=['--nsfw_checker','--max_loaded=10'])
+    conf.parse_args(conf=init1,argv=['--nsfw_checker','--max_cache=10'])
     assert conf.nsfw_checker
-    assert conf.max_loaded_models==10
+    assert conf.max_cache_size==10
     assert conf.outdir==Path('outputs')  # this is the default
     
 def test_env_override():
     # argv overrides 
     conf = InvokeAIAppConfig()
-    conf.parse_args(conf=init1,argv=['--max_loaded=10'])
+    conf.parse_args(conf=init1,argv=['--max_cache=10'])
     assert conf.nsfw_checker==False
     os.environ['INVOKEAI_nsfw_checker'] = 'True'
-    conf.parse_args(conf=init1,argv=['--max_loaded=10'])
+    conf.parse_args(conf=init1,argv=['--max_cache=10'])
     assert conf.nsfw_checker==True
 
     # environment variables should be case insensitive
-    os.environ['InvokeAI_Max_Loaded_Models'] = '15'
+    os.environ['InvokeAI_Max_Cache_Size'] = '15'
     conf = InvokeAIAppConfig()
     conf.parse_args(conf=init1,argv=[])
-    assert conf.max_loaded_models == 15
+    assert conf.max_cache_size == 15
 
     conf = InvokeAIAppConfig()
-    conf.parse_args(conf=init1,argv=['--no-nsfw_checker','--max_loaded=10'])
+    conf.parse_args(conf=init1,argv=['--no-nsfw_checker','--max_cache=10'])
     assert conf.nsfw_checker==False
-    assert conf.max_loaded_models==10
+    assert conf.max_cache_size==10
 
-    conf = InvokeAIAppConfig.get_config(max_loaded_models=20)
+    conf = InvokeAIAppConfig.get_config(max_cache_size=20)
     conf.parse_args(conf=init1,argv=[])
-    assert conf.max_loaded_models==20
+    assert conf.max_cache_size==20
 
 def test_type_coercion():
     conf = InvokeAIAppConfig().get_config()