whoops

- Fix the ANSI escape codes for macOS
- Add check for python binary name to `tag_release.sh`
- Print `git remote -v` in `tag_release.sh`

.github/actions/install-frontend-deps/action.yml

@@ -0,0 +1,33 @@
+name: Install frontend dependencies
+description: Installs frontend dependencies with pnpm, with caching
+runs:
+  using: 'composite'
+  steps:
+    - name: Setup Node 18
+      uses: actions/setup-node@v4
+      with:
+        node-version: '18'
+
+    - name: Setup pnpm
+      uses: pnpm/action-setup@v2
+      with:
+        version: 8
+        run_install: false
+
+    - name: Get pnpm store directory
+      shell: bash
+      run: |
+        echo "STORE_PATH=$(pnpm store path --silent)" >> $GITHUB_ENV
+
+    - uses: actions/cache@v3
+      name: Setup pnpm cache
+      with:
+        path: ${{ env.STORE_PATH }}
+        key: ${{ runner.os }}-pnpm-store-${{ hashFiles('**/pnpm-lock.yaml') }}
+        restore-keys: |
+          ${{ runner.os }}-pnpm-store-
+
+    - name: Install frontend dependencies
+      run: pnpm install --prefer-frozen-lockfile
+      shell: bash
+      working-directory: invokeai/frontend/web

.github/actions/install-python-deps/action.yml

@@ -0,0 +1,11 @@
+name: Install python dependencies
+description: Install python dependencies with pip, with caching
+runs:
+  using: 'composite'
+  steps:
+    - name: Setup python
+      uses: actions/setup-python@v5
+      with:
+        python-version: '3.10'
+        cache: pip
+        cache-dependency-path: pyproject.toml

.github/workflows/build-container.yml

@@ -11,7 +11,7 @@ on:
       - 'docker/docker-entrypoint.sh'
       - 'workflows/build-container.yml'
     tags:
-      - 'v*'
+      - 'v*.*.*'
   workflow_dispatch:
 
 permissions:

.github/workflows/check-frontend.yml

@@ -0,0 +1,34 @@
+name: 'Check: frontend'
+
+on:
+  workflow_dispatch:
+  workflow_call:
+
+defaults:
+  run:
+    working-directory: invokeai/frontend/web
+
+jobs:
+  check-frontend:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up frontend
+        uses: ./.github/actions/install-frontend-deps
+
+      - name: Run tsc check
+        run: 'pnpm run lint:tsc'
+        shell: bash
+
+      - name: Run madge check
+        run: 'pnpm run lint:madge'
+        shell: bash
+
+      - name: Run eslint check
+        run: 'pnpm run lint:eslint'
+        shell: bash
+
+      - name: Run prettier check
+        run: 'pnpm run lint:prettier'
+        shell: bash

.github/workflows/check-pytest.yml

@@ -1,15 +1,8 @@
-name: Test invoke.py pip
+name: 'Check: pytest'
+
 on:
-  push:
-    branches:
-      - 'main'
-  pull_request:
-    types:
-      - 'ready_for_review'
-      - 'opened'
-      - 'synchronize'
-  merge_group:
   workflow_dispatch:
+  workflow_call:
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
@@ -17,11 +10,9 @@ concurrency:
 
 jobs:
   matrix:
-    if: github.event.pull_request.draft == false
     strategy:
       matrix:
         python-version:
-          # - '3.9'
           - '3.10'
         pytorch:
           - linux-cuda-11_7
@@ -52,27 +43,12 @@ jobs:
     env:
       PIP_USE_PEP517: '1'
     steps:
-      - name: Checkout sources
-        id: checkout-sources
-        uses: actions/checkout@v3
-
-      - name: Check for changed python files
-        id: changed-files
-        uses: tj-actions/changed-files@v37
-        with:
-          files_yaml: |
-            python:
-              - 'pyproject.toml'
-              - 'invokeai/**'
-              - '!invokeai/frontend/web/**'
-              - 'tests/**'
+      - uses: actions/checkout@v4
 
       - name: set test prompt to main branch validation
-        if: steps.changed-files.outputs.python_any_changed == 'true'
         run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> ${{ matrix.github-env }}
 
       - name: setup python
-        if: steps.changed-files.outputs.python_any_changed == 'true'
         uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
@@ -80,7 +56,6 @@ jobs:
           cache-dependency-path: pyproject.toml
 
       - name: install invokeai
-        if: steps.changed-files.outputs.python_any_changed == 'true'
         env:
           PIP_EXTRA_INDEX_URL: ${{ matrix.extra-index-url }}
         run: >
@@ -88,7 +63,6 @@ jobs:
           --editable=".[test]"
 
       - name: run pytest
-        if: steps.changed-files.outputs.python_any_changed == 'true'
         id: run-pytest
         run: pytest
 

.github/workflows/check-python.yml

@@ -0,0 +1,26 @@
+name: 'Check: python'
+
+on:
+  workflow_dispatch:
+  workflow_call:
+
+jobs:
+  check-backend:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install python dependencies
+        uses: ./.github/actions/install-python-deps
+
+      - name: Install ruff
+        run: pip install ruff
+        shell: bash
+
+      - name: Ruff check
+        run: ruff check --output-format=github .
+        shell: bash
+
+      - name: Ruff format
+        run: ruff format --check .
+        shell: bash

.github/workflows/lint-frontend.yml

@@ -1,43 +0,0 @@
-name: Lint frontend
-
-on:
-  pull_request:
-    types:
-      - 'ready_for_review'
-      - 'opened'
-      - 'synchronize'
-  push:
-    branches:
-      - 'main'
-  merge_group:
-  workflow_dispatch:
-
-defaults:
-  run:
-    working-directory: invokeai/frontend/web
-
-jobs:
-  lint-frontend:
-    if: github.event.pull_request.draft == false
-    runs-on: ubuntu-22.04
-    steps:
-      - name: Setup Node 20
-        uses: actions/setup-node@v4
-        with:
-          node-version: '20'
-      - name: Checkout
-        uses: actions/checkout@v4
-      - name: Setup pnpm
-        uses: pnpm/action-setup@v2
-        with:
-          version: 8
-      - name: Install dependencies
-        run: 'pnpm install --prefer-frozen-lockfile'
-      - name: Typescript
-        run: 'pnpm run lint:tsc'
-      - name: Madge
-        run: 'pnpm run lint:madge'
-      - name: ESLint
-        run: 'pnpm run lint:eslint'
-      - name: Prettier
-        run: 'pnpm run lint:prettier'

.github/workflows/on-change-check-frontend.yml

@@ -0,0 +1,34 @@
+name: 'On change: run check-frontend'
+
+on:
+  push:
+    branches:
+      - 'main'
+  pull_request:
+    types:
+      - 'ready_for_review'
+      - 'opened'
+      - 'synchronize'
+  merge_group:
+
+jobs:
+  check-changed-frontend-files:
+    if: github.event.pull_request.draft == false
+    runs-on: ubuntu-latest
+    outputs:
+      frontend_any_changed: ${{ steps.changed-files.outputs.frontend_any_changed }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Check for changed frontend files
+        id: changed-files
+        uses: tj-actions/changed-files@v40
+        with:
+          files_yaml: |
+            frontend:
+              - 'invokeai/frontend/web/**'
+
+  run-check-frontend:
+    needs: check-changed-frontend-files
+    if: ${{ needs.check-changed-frontend-files.outputs.frontend_any_changed == 'true' }}
+    uses: ./.github/workflows/check-frontend.yml

.github/workflows/on-change-check-python.yml

@@ -0,0 +1,37 @@
+name: 'On change: run check-python'
+
+on:
+  push:
+    branches:
+      - 'main'
+  pull_request:
+    types:
+      - 'ready_for_review'
+      - 'opened'
+      - 'synchronize'
+  merge_group:
+
+jobs:
+  check-changed-python-files:
+    if: github.event.pull_request.draft == false
+    runs-on: ubuntu-latest
+    outputs:
+      python_any_changed: ${{ steps.changed-files.outputs.python_any_changed }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Check for changed python files
+        id: changed-files
+        uses: tj-actions/changed-files@v40
+        with:
+          files_yaml: |
+            python:
+              - 'pyproject.toml'
+              - 'invokeai/**'
+              - '!invokeai/frontend/web/**'
+              - 'tests/**'
+
+  run-check-python:
+    needs: check-changed-python-files
+    if: ${{ needs.check-changed-python-files.outputs.python_any_changed == 'true' }}
+    uses: ./.github/workflows/check-python.yml

.github/workflows/on-change-pytest.yml

@@ -0,0 +1,37 @@
+name: 'On change: run pytest'
+
+on:
+  push:
+    branches:
+      - 'main'
+  pull_request:
+    types:
+      - 'ready_for_review'
+      - 'opened'
+      - 'synchronize'
+  merge_group:
+
+jobs:
+  check-changed-python-files:
+    if: github.event.pull_request.draft == false
+    runs-on: ubuntu-latest
+    outputs:
+      python_any_changed: ${{ steps.changed-files.outputs.python_any_changed }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Check for changed python files
+        id: changed-files
+        uses: tj-actions/changed-files@v40
+        with:
+          files_yaml: |
+            python:
+              - 'pyproject.toml'
+              - 'invokeai/**'
+              - '!invokeai/frontend/web/**'
+              - 'tests/**'
+
+  run-pytest:
+    needs: check-changed-python-files
+    if: ${{ needs.check-changed-python-files.outputs.python_any_changed == 'true' }}
+    uses: ./.github/workflows/check-pytest.yml

.github/workflows/pypi-release.yml

@@ -1,41 +0,0 @@
-name: PyPI Release
-
-on:
-  push:
-    paths:
-      - 'invokeai/version/invokeai_version.py'
-  workflow_dispatch:
-
-jobs:
-  release:
-    if: github.repository == 'invoke-ai/InvokeAI'
-    runs-on: ubuntu-22.04
-    env:
-      TWINE_USERNAME: __token__
-      TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
-      TWINE_NON_INTERACTIVE: 1
-    steps:
-      - name: checkout sources
-        uses: actions/checkout@v3
-
-      - name: install deps
-        run: pip install --upgrade build twine
-
-      - name: build package
-        run: python3 -m build
-
-      - name: check distribution
-        run: twine check dist/*
-
-      - name: check PyPI versions
-        if: github.ref == 'refs/heads/main' || startsWith(github.ref, 'refs/heads/release/')
-        run: |
-          pip install --upgrade requests
-          python -c "\
-          import scripts.pypi_helper; \
-          EXISTS=scripts.pypi_helper.local_on_pypi(); \
-          print(f'PACKAGE_EXISTS={EXISTS}')" >> $GITHUB_ENV
-
-      - name: upload package
-        if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != ''
-        run: twine upload dist/*

.github/workflows/pypi-release.yml.old

@@ -0,0 +1,67 @@
+name: PyPI Release
+
+on:
+  workflow_dispatch:
+    inputs:
+      publish_package:
+        description: 'Publish build on PyPi? [true/false]'
+        required: true
+        default: 'false'
+
+jobs:
+  build-and-release:
+    if: github.repository == 'invoke-ai/InvokeAI'
+    runs-on: ubuntu-22.04
+    env:
+      TWINE_USERNAME: __token__
+      TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
+      TWINE_NON_INTERACTIVE: 1
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Setup Node 18
+        uses: actions/setup-node@v4
+        with:
+          node-version: '18'
+
+      - name: Setup pnpm
+        uses: pnpm/action-setup@v2
+        with:
+          version: '8.12.1'
+
+      - name: Install frontend dependencies
+        run: pnpm install --prefer-frozen-lockfile
+        working-directory: invokeai/frontend/web
+
+      - name: Build frontend
+        run: pnpm run build
+        working-directory: invokeai/frontend/web
+
+      - name: Install python dependencies
+        run: pip install --upgrade build twine
+
+      - name: Build python package
+        run: python3 -m build
+
+      - name: Upload build as workflow artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: dist
+          path: dist
+
+      - name: Check distribution
+        run: twine check dist/*
+
+      - name: Check PyPI versions
+        if: github.ref == 'refs/heads/main' || startsWith(github.ref, 'refs/heads/release/')
+        run: |
+          pip install --upgrade requests
+          python -c "\
+          import scripts.pypi_helper; \
+          EXISTS=scripts.pypi_helper.local_on_pypi(); \
+          print(f'PACKAGE_EXISTS={EXISTS}')" >> $GITHUB_ENV
+
+      - name: Publish build on PyPi
+        if: env.PACKAGE_EXISTS == 'False' && env.TWINE_PASSWORD != '' && github.event.inputs.publish_package == 'true'
+        run: twine upload dist/*

.github/workflows/release.yml

@@ -0,0 +1,103 @@
+name: Release
+
+on:
+  push:
+    tags:
+      - 'v*.*.*'
+  workflow_dispatch:
+    inputs:
+      skip_code_checks:
+        description: 'Skip code checks'
+        required: true
+        default: true
+        type: boolean
+
+jobs:
+  check-version:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: samuelcolvin/check-python-version@v4
+        id: check-python-version
+        with:
+          version_file_path: invokeai/version/invokeai_version.py
+
+  check-frontend:
+    if: github.event.inputs.skip_code_checks != 'true'
+    uses: ./.github/workflows/check-frontend.yml
+
+  check-python:
+    if: github.event.inputs.skip_code_checks != 'true'
+    uses: ./.github/workflows/check-python.yml
+
+  check-pytest:
+    if: github.event.inputs.skip_code_checks != 'true'
+    uses: ./.github/workflows/check-pytest.yml
+
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install python dependencies
+        uses: ./.github/actions/install-python-deps
+
+      - name: Install pypa/build
+        run: pip install --upgrade build
+
+      - name: Setup frontend
+        uses: ./.github/actions/install-frontend-deps
+
+      - name: Run create_installer.sh
+        id: create_installer
+        run: ./create_installer.sh --skip_frontend_checks
+        working-directory: installer
+
+      - name: Upload python distribution artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: dist
+          path: ${{ steps.create_installer.outputs.DIST_PATH }}
+
+      - name: Upload installer artifact
+        uses: actions/upload-artifact@v4
+        with:
+          name: ${{ steps.create_installer.outputs.INSTALLER_FILENAME }}
+          path: ${{ steps.create_installer.outputs.INSTALLER_PATH }}
+
+  publish-testpypi:
+    runs-on: ubuntu-latest
+    needs: [check-version, check-frontend, check-python, check-pytest, build]
+    if: github.event_name != 'workflow_dispatch'
+    environment:
+      name: testpypi
+      url: https://test.pypi.org/p/invokeai
+    steps:
+      - name: Download distribution from build job
+        uses: actions/download-artifact@v4
+        with:
+          name: dist
+          path: dist/
+
+      - name: Publish distribution to TestPyPI
+        uses: pypa/gh-action-pypi-publish@release/v1
+        with:
+          repository-url: https://test.pypi.org/legacy/
+
+  publish-pypi:
+    runs-on: ubuntu-latest
+    needs: [check-version, check-frontend, check-python, check-pytest, build]
+    if: github.event_name != 'workflow_dispatch'
+    environment:
+      name: pypi
+      url: https://pypi.org/p/invokeai
+    steps:
+      - name: Download distribution from build job
+        uses: actions/download-artifact@v4
+        with:
+          name: dist
+          path: dist/
+
+      - name: Publish distribution to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1

.github/workflows/style-checks.yml

@@ -1,24 +0,0 @@
-name: style checks
-
-on:
-  pull_request:
-  push:
-    branches: main
-
-jobs:
-  ruff:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v3
-
-      - name: Setup Python
-        uses: actions/setup-python@v4
-        with:
-          python-version: '3.10'
-
-      - name: Install dependencies with pip
-        run: |
-          pip install ruff
-
-      - run: ruff check --output-format=github .
-      - run: ruff format --check .

.prettierrc.yaml

@@ -7,7 +7,7 @@ embeddedLanguageFormatting: auto
 overrides:
   - files: '*.md'
     options:
-      proseWrap: always
+      proseWrap: preserve
       printWidth: 80
       parser: markdown
       cursorOffset: -1

README.md

@@ -270,7 +270,7 @@ upgrade script.** See the next section for a Windows recipe.
 3. Select option [1] to upgrade to the latest release.
 
 4. Once the upgrade is finished you will be returned to the launcher
-menu. Select option [7] "Re-run the configure script to fix a broken
+menu. Select option [6] "Re-run the configure script to fix a broken
 install or to complete a major upgrade".
 
 This will run the configure script against the v2.3 directory and

docker/Dockerfile

@@ -59,14 +59,16 @@ RUN --mount=type=cache,target=/root/.cache/pip \
 
 # #### Build the Web UI ------------------------------------
 
-FROM node:18 AS web-builder
+FROM node:18-slim AS web-builder
+ENV PNPM_HOME="/pnpm"
+ENV PATH="$PNPM_HOME:$PATH"
+RUN corepack enable
+
 WORKDIR /build
 COPY invokeai/frontend/web/ ./
-RUN --mount=type=cache,target=/usr/lib/node_modules \
-    npm install --include dev
-RUN --mount=type=cache,target=/usr/lib/node_modules \
-    yarn vite build
-
+RUN --mount=type=cache,target=/pnpm/store \
+    pnpm install --frozen-lockfile
+RUN pnpm run build
 
 #### Runtime stage ---------------------------------------
 

docker/README.md

@@ -23,7 +23,7 @@ This is done via Docker Desktop preferences
 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`
+1. Execute `run.sh`
 
 The image will be built automatically if needed.
 
@@ -39,7 +39,7 @@ The Docker daemon on the system must be already set up to use the GPU. In case o
 
 ## 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.
+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 `run.sh`, 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.
 

docker/build.sh

@@ -1,11 +0,0 @@
-#!/usr/bin/env bash
-set -e
-
-build_args=""
-
-[[ -f ".env" ]] && build_args=$(awk '$1 ~ /\=[^$]/ {print "--build-arg " $0 " "}' .env)
-
-echo "docker compose build args:"
-echo $build_args
-
-docker compose build $build_args

docker/docker-compose.yml

@@ -2,23 +2,8 @@
 
 version: '3.8'
 
-services:
-  invokeai:
+x-invokeai: &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]
-    # For AMD support, comment out the deploy section above and uncomment the devices section below:
-    #devices:
-    #  - /dev/kfd:/dev/kfd
-    #  - /dev/dri:/dev/dri
     build:
       context: ..
       dockerfile: docker/Dockerfile
@@ -50,3 +35,27 @@ services:
     #   - |
     #     invokeai-model-install --yes --default-only --config_file ${INVOKEAI_ROOT}/config_custom.yaml
     #     invokeai-nodes-web --host 0.0.0.0
+
+services:
+  invokeai-nvidia:
+    <<: *invokeai
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+
+  invokeai-cpu:
+    <<: *invokeai
+    profiles:
+      - cpu
+
+  invokeai-rocm:
+    <<: *invokeai
+    devices:
+      - /dev/kfd:/dev/kfd
+      - /dev/dri:/dev/dri
+    profiles:
+      - rocm

docker/run.sh

@@ -1,11 +1,28 @@
 #!/usr/bin/env bash
 set -e
 
-# This script is provided for backwards compatibility with the old docker setup.
-# it doesn't do much aside from wrapping the usual docker compose CLI.
+run() {
+  local scriptdir=$(dirname "${BASH_SOURCE[0]}")
+  cd "$scriptdir" || exit 1
 
-SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
-cd "$SCRIPTDIR" || exit 1
+  local build_args=""
+  local profile=""
 
-docker compose up -d
-docker compose logs -f
+  [[ -f ".env" ]] &&
+    build_args=$(awk '$1 ~ /=[^$]/ && $0 !~ /^#/ {print "--build-arg " $0 " "}' .env) &&
+    profile="$(awk -F '=' '/GPU_DRIVER/ {print $2}' .env)"
+
+  local service_name="invokeai-$profile"
+
+  printf "%s\n" "docker compose build args:"
+  printf "%s\n" "$build_args"
+
+  docker compose build $build_args
+  unset build_args
+
+  printf "%s\n" "starting service $service_name"
+  docker compose --profile "$profile" up -d "$service_name"
+  docker compose logs -f
+}
+
+run

docs/RELEASE.md

@@ -0,0 +1,157 @@
+# Release
+
+The app is published in twice, in different build formats.
+
+- A [PyPI] distribution. This includes both a source distribution and built distribution (a wheel). Users install with `pip install invokeai`. The updater uses this build.
+- An installer on the [InvokeAI Releases Page]. This is a zip file with install scripts and a wheel. This is only used for new installs.
+
+## General Prep
+
+Make a developer call-out for PRs to merge. Merge and test things out.
+
+While the release workflow does not include end-to-end tests, it does pause before publishing so you can download and test the final build.
+
+## Release Workflow
+
+The `release.yml` workflow runs a number of jobs to handle code checks, tests, build and publish on PyPI.
+
+It is triggered on **tag push**. It doesn't matter if you've prepped a release branch like `release/v3.5.0` or are releasing from `main` - it works the same.
+
+!!! info
+
+    Commits are reference-counted, so as long as a something points to a commit, that commit will not be garbage-collected'd from the repo.
+
+    It is safe to create a release branch, tag it and have the workflow do its thing, then delete the branch. So long as the tag is not deleted, that snapshot of the repo will forever exist at the tag.
+
+### Pushing the Tag
+
+Run `make tag-release` to tag the current commit and kick off the workflow.
+
+### Tag Push Example
+
+Any tag push will trigger the workflow, but it will publish only if the git ref (the tag) matches the app version.
+
+Say `invokeai_version.py` looks like this:
+
+```py
+__version__ = "3.5.0rc2"
+```
+
+- If you push tag `v3.5.0rc2`, the workflow will trigger and run. If the checks and build succeed, you'll be able to publish the release.
+
+- If you push tag `v3.5.0rc3` or `banana-sushi`, the workflow will trigger and run. Even if the checks and build succeed, you'll _will not_ be able to publish the release, because the tag doesn't match the app version.
+
+!!! info
+
+    Any valid [version specifier] works, so long as the tag matches the version. The release workflow works exactly the same for `RC`, `post`, `dev`, etc.
+
+### code quality jobs
+
+Three jobs are run concurrently:
+
+- **`pytest`**: runs `pytest` on matrix of platforms
+- **`check-python`**: runs `ruff` (format and lint)
+- **`check-frontend`**: runs `prettier` (format), `eslint` (lint), `madge` (circular refs) and `tsc` (static type check)
+
+If any fail, the release workflow bails.
+
+!!! info Future Enhancement
+
+    We should add `mypy` or `pyright` to the **`check-python`** job at some point.
+
+### `build`
+
+This sets up both python and frontend dependencies and builds the python package. Internally, this runs `installer/create_installer.sh` and uploads two artifacts:
+
+- **`dist`**: the python distribution, to be published on PyPI
+- **`InvokeAI-installer-${VERSION}.zip`**: the installer to be included in the GitHub release
+
+!!! info
+
+    The installer uses the uses the same wheel file that is included in the PyPI distribution, so you _should_ get exactly the same thing using the installer or PyPI dist.
+
+### Sanity Check & Smoke Test
+
+At this point, the release workflow pauses (the remaining jobs all require approval).
+
+The maintainer who is running this release should go to the **Summary** tab of the workflow, download the installer and test it.
+
+You could also download the `dist`, unzip it and install directly from the wheel. That same wheel will be uploaded to PyPI.
+
+### Publish
+
+The publish jobs use [GitHub environments], which are configured as [trusted publishers] on PyPI.
+
+Both jobs require a maintainer to approve them from the workflow's **Summary** tab.
+
+- Click the **Review deployments** button
+- Select the environment (either `testpypi` or `pypi`)
+- Click **Approve and deploy**
+
+#### Skip and Failure Conditions
+
+The publish jobs may skip or fail in certain situations:
+
+- **If code checks or build fail, the jobs will be skipped.**
+- **If code checks were skipped, the jobs will be skipped.** This can only happen when [manually] running the workflow.
+- **If the git ref targetted by the workflow doesn't match the app version, the jobs will fail.** This protects us from accidentally publishing the wrong version to PyPI. This is achieved with [samuelcolvin/check-python-version].
+- **If the version already exists on PyPI, the jobs will fail.** PyPI only allows a particular version to be published once - you cannot change it. If version published on PyPI has a problem, you'll need to "fail forward" by bumping the app version and publishing a followup release.
+
+#### `publish-testpypi`
+
+Publishes the distribution on the [Test PyPI] index using the `testpypi` GitHub environment.
+
+This job is optional:
+
+- It is not require for the final `publish-pypi` job to run.
+- The wheel used in the installer and PyPI dist (uploaded as artifacts from the workflow, as described above) are identical, so this job _should_ be extraneous.
+
+That said, you could approve it and then test installing from PyPI before running the production PyPI publish job:
+
+```sh
+# Create a new virtual environment
+python -m venv ~/.test-invokeai-dist --prompt test-invokeai-dist
+# Install the distribution from Test PyPI
+pip install --index-url https://test.pypi.org/simple/ invokeai
+# Run and test the app
+invokeai-web
+# Cleanup
+deactivate
+rm -rf ~/.test-invokeai-dist
+```
+
+#### `publish-pypi`
+
+Publishes the distribution on the production PyPI index, using the `pypi` GitHub environment.
+
+Once this finishes, `pip install invokeai` will get the release!
+
+## Publish the GitHub RC with installer
+
+1. [Draft a new release] on GitHub, choosing the tag that initiated the release.
+2. Write the release notes, describing important changes. The **Generate release notes** button automatically inserts the changelog and new contributors, and you can copy/paste the intro from previous releases.
+3. Upload the zip file created in [Build the installer] into the Assets section of the release notes. You can also upload the zip into the body of the release notes, since it can be hard for users to find the Assets section.
+4. Check the **Set as a pre-release** and **Create a discussion for this release** checkboxes at the bottom of the release page.
+5. Publish the pre-release.
+6. Announce the pre-release in Discord.
+
+!!! info Future Enhancement
+
+    Workflows can do things like create a release from a template and upload release assets. One popular action to handle this is [ncipollo/release-action]. A future enhancement to the release process could set this up.
+
+## Manually Running the Release Workflow
+
+The release workflow can be kicked off manually. This is useful to get an installer build and test it out without needing to push a tag.
+
+When run this way, you'll see **Skip code checks** checkbox. This allows the workflow to run without the time-consuming 3 code quality check jobs. The publish jobs will be skipped if enabled.
+
+[InvokeAI Releases Page]: https://github.com/invoke-ai/InvokeAI/releases
+[PyPI]: https://pypi.org/
+[Draft a new release]: https://github.com/invoke-ai/InvokeAI/releases/new
+[Test PyPI]: https://test.pypi.org/
+[version specifier]: https://packaging.python.org/en/latest/specifications/version-specifiers/
+[ncipollo/release-action]: https://github.com/ncipollo/release-action
+[GitHub environments]: https://docs.github.com/en/actions/deployment/targeting-different-environments/using-environments-for-deployment
+[trusted publishers]: https://docs.pypi.org/trusted-publishers/
+[samuelcolvin/check-python-version]: https://github.com/samuelcolvin/check-python-version
+[manually]: #manually-running-the-release-workflow

docs/contributing/DOWNLOAD_QUEUE.md

@@ -0,0 +1,277 @@
+# The InvokeAI Download Queue
+
+The DownloadQueueService provides a multithreaded parallel download
+queue for arbitrary URLs, with queue prioritization, event handling,
+and restart capabilities.
+
+## Simple Example
+
+```
+from invokeai.app.services.download import DownloadQueueService, TqdmProgress
+
+download_queue = DownloadQueueService()
+for url in ['https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/a-painting-of-a-fire.png?raw=true',
+            'https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/birdhouse.png?raw=true',
+            'https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/missing.png',
+            'https://civitai.com/api/download/models/152309?type=Model&format=SafeTensor',
+            ]:
+
+    # urls start downloading as soon as download() is called
+    download_queue.download(source=url,
+                            dest='/tmp/downloads',
+                            on_progress=TqdmProgress().update
+                            )
+
+download_queue.join()  # wait for all downloads to finish
+for job in download_queue.list_jobs():
+    print(job.model_dump_json(exclude_none=True, indent=4),"\n")
+```
+
+Output:
+
+```
+{
+    "source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/a-painting-of-a-fire.png?raw=true",
+    "dest": "/tmp/downloads",
+    "id": 0,
+    "priority": 10,
+    "status": "completed",
+    "download_path": "/tmp/downloads/a-painting-of-a-fire.png",
+    "job_started": "2023-12-04T05:34:41.742174",
+    "job_ended": "2023-12-04T05:34:42.592035",
+    "bytes": 666734,
+    "total_bytes": 666734
+} 
+
+{
+    "source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/birdhouse.png?raw=true",
+    "dest": "/tmp/downloads",
+    "id": 1,
+    "priority": 10,
+    "status": "completed",
+    "download_path": "/tmp/downloads/birdhouse.png",
+    "job_started": "2023-12-04T05:34:41.741975",
+    "job_ended": "2023-12-04T05:34:42.652841",
+    "bytes": 774949,
+    "total_bytes": 774949
+}
+
+{
+    "source": "https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/assets/missing.png",
+    "dest": "/tmp/downloads",
+    "id": 2,
+    "priority": 10,
+    "status": "error",
+    "job_started": "2023-12-04T05:34:41.742079",
+    "job_ended": "2023-12-04T05:34:42.147625",
+    "bytes": 0,
+    "total_bytes": 0,
+    "error_type": "HTTPError(Not Found)",
+    "error": "Traceback (most recent call last):\n  File \"/home/lstein/Projects/InvokeAI/invokeai/app/services/download/download_default.py\", line 182, in _download_next_item\n    self._do_download(job)\n  File \"/home/lstein/Projects/InvokeAI/invokeai/app/services/download/download_default.py\", line 206, in _do_download\n    raise HTTPError(resp.reason)\nrequests.exceptions.HTTPError: Not Found\n"
+}
+
+{
+    "source": "https://civitai.com/api/download/models/152309?type=Model&format=SafeTensor",
+    "dest": "/tmp/downloads",
+    "id": 3,
+    "priority": 10,
+    "status": "completed",
+    "download_path": "/tmp/downloads/xl_more_art-full_v1.safetensors",
+    "job_started": "2023-12-04T05:34:42.147645",
+    "job_ended": "2023-12-04T05:34:43.735990",
+    "bytes": 719020768,
+    "total_bytes": 719020768
+} 
+```
+
+##  The API
+
+The default download queue is `DownloadQueueService`, an
+implementation of ABC `DownloadQueueServiceBase`. It juggles multiple
+background download requests and provides facilities for interrogating
+and cancelling the requests. Access to a current or past download task
+is mediated via `DownloadJob` objects which report the current status
+of a job request
+
+### The Queue Object
+
+A default download queue is located in
+`ApiDependencies.invoker.services.download_queue`. However, you can
+create additional instances if you need to isolate your queue from the
+main one.
+
+```
+queue = DownloadQueueService(event_bus=events)
+```
+
+`DownloadQueueService()` takes three optional arguments:
+
+| **Argument** | **Type**          |  **Default**  | **Description** |
+|----------------|-----------------|---------------|-----------------|
+| `max_parallel_dl`  | int                         | 5    | Maximum number of simultaneous downloads allowed |
+| `event_bus` | EventServiceBase   | None | System-wide FastAPI event bus for reporting download events |
+| `requests_session` | requests.sessions.Session   | None | An alternative requests Session object to use for the download |
+
+`max_parallel_dl` specifies how many download jobs are allowed to run
+simultaneously. Each will run in a different thread of execution.
+
+`event_bus` is an EventServiceBase, typically the one created at
+InvokeAI startup. If present, download events are periodically emitted
+on this bus to allow clients to follow download progress.
+
+`requests_session` is a url library requests Session object. It is
+used for testing.
+
+### The Job object
+
+The queue operates on a series of download job objects. These objects
+specify the source and destination of the download, and keep track of
+the progress of the download.
+
+The only job type currently implemented is `DownloadJob`, a pydantic object with the
+following fields:
+
+| **Field**      | **Type**        |  **Default**  | **Description** |
+|----------------|-----------------|---------------|-----------------|
+| _Fields passed in at job creation time_                               |
+| `source`         | AnyHttpUrl      |               | Where to download from |
+| `dest`           | Path            |               | Where to download to              |
+| `access_token`   | str             |               | [optional] string containing authentication token for access |
+| `on_start`       | Callable        |               | [optional] callback when the download starts |
+| `on_progress`    | Callable        |               | [optional] callback called at intervals during download progress |
+| `on_complete`    | Callable        |               | [optional] callback called after successful download completion |
+| `on_error`       | Callable        |               | [optional] callback called after an error occurs  |
+| `id`             | int             | auto assigned | Job ID, an integer >= 0           |
+| `priority`       | int             | 10            | Job priority. Lower priorities run before higher priorities |
+|                                                                                                        |
+| _Fields updated over the course of the download task_
+| `status`         | DownloadJobStatus|              | Status code                                |
+| `download_path`  | Path |              | Path to the location of the downloaded file |
+| `job_started`    | float            |              | Timestamp for when the job started running |
+| `job_ended`      | float            |              | Timestamp for when the job completed or errored out |
+| `job_sequence`   | int              |              | A counter that is incremented each time a model is dequeued |
+| `bytes`          | int              | 0            | Bytes downloaded so far   |
+| `total_bytes`    | int              | 0            | Total size of the file at the remote site  |
+| `error_type`     | str              |              | String version of the exception that caused an error during download |
+| `error`          | str              |              | String version of the traceback associated with an error |
+| `cancelled`      | bool             | False        | Set to true if the job was cancelled by the caller|
+
+When you create a job, you can assign it a `priority`. If multiple
+jobs are queued, the job with the lowest priority runs first.
+
+Every job has a `source` and a `dest`. `source` is a pydantic.networks AnyHttpUrl object.
+The `dest` is a path on the local filesystem that specifies the
+destination for the downloaded object. Its semantics are
+described below.
+
+When the job is submitted, it is assigned a numeric `id`. The id can
+then be used to fetch the job object from the queue.
+
+The `status` field is updated by the queue to indicate where the job
+is in its lifecycle. Values are defined in the string enum
+`DownloadJobStatus`, a symbol available from
+`invokeai.app.services.download_manager`. Possible values are:
+
+| **Value**    |   **String Value**  | ** Description ** |
+|--------------|---------------------|-------------------|
+| `WAITING`      | waiting           | Job is on the queue but not yet running|
+| `RUNNING`      | running           | The download is started                |
+| `COMPLETED`    | completed         | Job has finished its work without an error |
+| `ERROR`        | error             | Job encountered an error and will not run again|
+
+`job_started` and `job_ended` indicate when the job
+was started (using a python timestamp) and when it completed.
+
+In case of an error, the job's status will be set to `DownloadJobStatus.ERROR`, the text of the
+Exception that caused the error will be placed in the `error_type`
+field and the traceback that led to the error will be in `error`.
+
+A cancelled job will have status `DownloadJobStatus.ERROR` and an
+`error_type` field of "DownloadJobCancelledException". In addition,
+the job's `cancelled` property will be set to True.
+
+### Callbacks
+
+Download jobs can be associated with a series of callbacks, each with
+the signature `Callable[["DownloadJob"], None]`. The callbacks are assigned
+using optional arguments `on_start`, `on_progress`, `on_complete` and
+`on_error`. When the corresponding event occurs, the callback wil be
+invoked and passed the job. The callback will be run in a `try:`
+context in the same thread as the download job. Any exceptions that
+occur during execution of the callback will be caught and converted
+into a log error message, thereby allowing the download to continue.
+
+#### `TqdmProgress`
+
+The `invokeai.app.services.download.download_default` module defines a
+class named `TqdmProgress` which can be used as an `on_progress`
+handler to display a completion bar in the console. Use as follows:
+
+```
+from invokeai.app.services.download import TqdmProgress
+
+download_queue.download(source='http://some.server.somewhere/some_file',
+                        dest='/tmp/downloads',
+                        on_progress=TqdmProgress().update
+                        )
+
+```
+
+### Events
+
+If the queue was initialized with the InvokeAI event bus (the case
+when using `ApiDependencies.invoker.services.download_queue`), then
+download events will also be issued on the bus. The events are:
+
+* `download_started` -- This is issued when a job is taken off the
+queue and a request is made to the remote server for the URL headers, but before any data
+has been downloaded. The event payload will contain the keys `source`
+and `download_path`. The latter contains the path that the URL will be
+downloaded to.
+
+* `download_progress -- This is issued periodically as the download
+runs. The payload contains the keys `source`, `download_path`,
+`current_bytes` and `total_bytes`. The latter two fields can be
+used to display the percent complete.
+
+* `download_complete` -- This is issued when the download completes
+successfully. The payload contains the keys `source`, `download_path`
+and `total_bytes`.
+
+* `download_error` -- This is issued when the download stops because
+of an error condition. The payload contains the fields `error_type`
+and `error`. The former is the text representation of the exception,
+and the latter is a traceback showing where the error occurred.
+
+### Job control
+
+To create a job call the queue's `download()` method. You can list all
+jobs using `list_jobs()`, fetch a single job by its with
+`id_to_job()`, cancel a running job with `cancel_job()`, cancel all
+running jobs with `cancel_all_jobs()`, and wait for all jobs to finish
+with `join()`.
+
+#### job = queue.download(source, dest, priority, access_token)
+
+Create a new download job and put it on the queue, returning the
+DownloadJob object.
+
+#### jobs = queue.list_jobs()
+
+Return a list of all active and inactive `DownloadJob`s.
+
+#### job = queue.id_to_job(id)
+
+Return the job corresponding to given ID.
+
+Return a list of all active and inactive `DownloadJob`s.
+
+#### queue.prune_jobs()
+
+Remove inactive (complete or errored) jobs from the listing returned
+by `list_jobs()`.
+
+#### queue.join()
+
+Block until all pending jobs have run to completion or errored out.
+

docs/contributing/contribution_guides/contributingToFrontend.md

@@ -46,17 +46,18 @@ We encourage you to ping @psychedelicious and @blessedcoolant on [Discord](http
 ```bash
 node --version
 ```
-2. Install [yarn classic](https://classic.yarnpkg.com/lang/en/) and confirm it is installed by running this:
+
+2. Install [pnpm](https://pnpm.io/) and confirm it is installed by running this:
 ```bash
-npm install --global yarn
-yarn --version
+npm install --global pnpm
+pnpm --version
 ```
 
-From `invokeai/frontend/web/` run `yarn install` to get everything set up.
+From `invokeai/frontend/web/` run `pnpm install` to get everything set up.
 
 Start everything in dev mode:
 1. Ensure your virtual environment is running
-2. Start the dev server: `yarn dev`
+2. Start the dev server: `pnpm dev`
 3. Start the InvokeAI Nodes backend: `python scripts/invokeai-web.py # run from the repo root`
 4. Point your browser to the dev server address e.g. [http://localhost:5173/](http://localhost:5173/)
 
@@ -72,4 +73,4 @@ For a number of technical and logistical reasons, we need to commit UI build art
 
 If you submit a PR, there is a good chance we will ask you to include a separate commit with a build of the app.
 
-To build for production, run `yarn build`.
+To build for production, run `pnpm build`.

docs/nodes/communityNodes.md

@@ -13,6 +13,7 @@ If you'd prefer, you can also just download the whole node folder from the linke
 To use a community workflow, download the the `.json` node graph file and load it into Invoke AI via the **Load Workflow** button in the Workflow Editor. 
 
 - Community Nodes
+    + [Adapters-Linked](#adapters-linked-nodes)
     + [Average Images](#average-images)
     + [Clean Image Artifacts After Cut](#clean-image-artifacts-after-cut)
     + [Close Color Mask](#close-color-mask) 
@@ -32,8 +33,9 @@ To use a community workflow, download the the `.json` node graph file and load i
     + [Image Resize Plus](#image-resize-plus)
     + [Load Video Frame](#load-video-frame)
     + [Make 3D](#make-3d)
-    + [Mask Operations](#mask-operations)    
+    + [Mask Operations](#mask-operations)
     + [Match Histogram](#match-histogram)
+    + [Metadata-Linked](#metadata-linked-nodes)
     + [Negative Image](#negative-image)    
     + [Oobabooga](#oobabooga)
     + [Prompt Tools](#prompt-tools)
@@ -51,6 +53,19 @@ To use a community workflow, download the the `.json` node graph file and load i
 - [Help](#help)
 
 
+--------------------------------
+### Adapters Linked Nodes
+
+**Description:** A set of nodes for linked adapters (ControlNet, IP-Adaptor & T2I-Adapter). This allows multiple adapters to be chained together without using a `collect` node which means it can be used inside an `iterate` node without any collecting on every iteration issues.
+
+- `ControlNet-Linked` - Collects ControlNet info to pass to other nodes.
+- `IP-Adapter-Linked` - Collects IP-Adapter info to pass to other nodes.
+- `T2I-Adapter-Linked` - Collects T2I-Adapter info to pass to other nodes.
+
+Note: These are inherited from the core nodes so any update to the core nodes should be reflected in these. 
+
+**Node Link:** https://github.com/skunkworxdark/adapters-linked-nodes
+
 --------------------------------
 ### Average Images
 
@@ -307,6 +322,20 @@ See full docs here: https://github.com/skunkworxdark/Prompt-tools-nodes/edit/mai
 
 <img src="https://github.com/skunkworxdark/match_histogram/assets/21961335/ed12f329-a0ef-444a-9bae-129ed60d6097" width="300" />
 
+--------------------------------
+### Metadata Linked Nodes
+
+**Description:** A set of nodes for Metadata. Collect Metadata from within an `iterate` node & extract metadata from an image.
+
+- `Metadata Item Linked` - Allows collecting of metadata while within an iterate node with no need for a collect node or conversion to metadata node.
+- `Metadata From Image` - Provides Metadata from an image.
+- `Metadata To String` - Extracts a String value of a label from metadata.
+- `Metadata To Integer` - Extracts an Integer value of a label from metadata.
+- `Metadata To Float` - Extracts a Float value of a label from metadata.
+- `Metadata To Scheduler` - Extracts a Scheduler value of a label from metadata.
+
+**Node Link:** https://github.com/skunkworxdark/metadata-linked-nodes
+
 --------------------------------
 ### Negative Image
 

installer/create_installer.sh

@@ -2,12 +2,12 @@
 
 set -e
 
-BCYAN="\e[1;36m"
-BYELLOW="\e[1;33m"
-BGREEN="\e[1;32m"
-BRED="\e[1;31m"
-RED="\e[31m"
-RESET="\e[0m"
+BCYAN="\033[1;36m"
+BYELLOW="\033[1;33m"
+BGREEN="\033[1;32m"
+BRED="\033[1;31m"
+RED="\033[31m"
+RESET="\033[0m"
 
 function is_bin_in_path {
     builtin type -P "$1" &>/dev/null
@@ -19,11 +19,6 @@ function git_show {
 
 cd "$(dirname "$0")"
 
-echo -e "${BYELLOW}This script must be run from the installer directory!${RESET}"
-echo "The current working directory is $(pwd)"
-read -p "If that looks right, press any key to proceed, or CTRL-C to exit..."
-echo
-
 # Some machines only have `python3` in PATH, others have `python` - make an alias.
 # We can use a function to approximate an alias within a non-interactive shell.
 if ! is_bin_in_path python && is_bin_in_path python3; then
@@ -32,7 +27,7 @@ if ! is_bin_in_path python && is_bin_in_path python3; then
     }
 fi
 
-if [[ -v "VIRTUAL_ENV" ]]; then
+if [ -n "${VIRTUAL_ENV+set}" ]; then
     # we can't just call 'deactivate' because this function is not exported
     # to the environment of this script from the bash process that runs the script
     echo -e "${BRED}A virtual environment is activated. Please deactivate it before proceeding.${RESET}"
@@ -43,8 +38,7 @@ VERSION=$(
     cd ..
     python -c "from invokeai.version import __version__ as version; print(version)"
 )
-PATCH=""
-VERSION="v${VERSION}${PATCH}"
+VERSION="v${VERSION}"
 
 echo -e "${BGREEN}HEAD${RESET}:"
 git_show
@@ -59,8 +53,14 @@ echo
 pnpm i --frozen-lockfile
 echo
 echo "Building frontend..."
+if [[ -v CI ]]; then
+    # In CI, we have already done the frontend checks and can just build
+    pnpm vite build
+else
+    # This runs all the frontend checks and builds
+    pnpm build
+fi
 echo
-pnpm build
 popd
 
 # ---------------------- BACKEND ----------------------
@@ -77,7 +77,7 @@ fi
 
 rm -rf ../build
 
-python -m build --wheel --outdir dist/ ../.
+python -m build --outdir dist/ ../.
 
 # ----------------------
 
@@ -91,12 +91,14 @@ rm -rf InvokeAI-Installer
 
 # copy content
 mkdir InvokeAI-Installer
-for f in templates lib *.txt *.reg; do
+for f in templates *.txt *.reg; do
     cp -r ${f} InvokeAI-Installer/
 done
+mkdir InvokeAI-Installer/lib
+cp lib/*.py InvokeAI-Installer/lib
 
-# Move the wheel
-mv dist/*.whl InvokeAI-Installer/lib/
+# Copy the wheel
+cp dist/*.whl InvokeAI-Installer/lib/
 
 # Install scripts
 # Mac/Linux
@@ -107,10 +109,21 @@ chmod a+x InvokeAI-Installer/install.sh
 perl -p -e "s/^set INVOKEAI_VERSION=.*/set INVOKEAI_VERSION=$VERSION/" install.bat.in >InvokeAI-Installer/install.bat
 cp WinLongPathsEnabled.reg InvokeAI-Installer/
 
-# Zip everything up
-zip -r InvokeAI-installer-$VERSION.zip InvokeAI-Installer
+FILENAME=InvokeAI-installer-$VERSION.zip
 
-# clean up
-rm -rf InvokeAI-Installer tmp dist
+# Zip everything up
+zip -r $FILENAME InvokeAI-Installer
+
+if [[ ! -v CI ]]; then
+    # clean up, but only if we are not in a github action
+    rm -rf InvokeAI-Installer tmp dist ../invokeai/frontend/web/dist/
+fi
+
+if [[ -v CI ]]; then
+    # Set the output variable for github action
+    echo "INSTALLER_FILENAME=$FILENAME" >>$GITHUB_OUTPUT
+    echo "INSTALLER_PATH=installer/$FILENAME" >>$GITHUB_OUTPUT
+    echo "DIST_PATH=installer/dist/" >>$GITHUB_OUTPUT
+fi
 
 exit 0

installer/tag_release.sh

@@ -2,12 +2,16 @@
 
 set -e
 
-BCYAN="\e[1;36m"
-BYELLOW="\e[1;33m"
-BGREEN="\e[1;32m"
-BRED="\e[1;31m"
-RED="\e[31m"
-RESET="\e[0m"
+BCYAN="\033[1;36m"
+BYELLOW="\033[1;33m"
+BGREEN="\033[1;32m"
+BRED="\033[1;31m"
+RED="\033[31m"
+RESET="\033[0m"
+
+function is_bin_in_path {
+    builtin type -P "$1" &>/dev/null
+}
 
 function does_tag_exist {
     git rev-parse --quiet --verify "refs/tags/$1" >/dev/null
@@ -21,6 +25,14 @@ function git_show {
     git show -s --format='%h %s' $1
 }
 
+# Some machines only have `python3` in PATH, others have `python` - make an alias.
+# We can use a function to approximate an alias within a non-interactive shell.
+if ! is_bin_in_path python && is_bin_in_path python3; then
+    function python {
+        python3 "$@"
+    }
+fi
+
 VERSION=$(
     cd ..
     python -c "from invokeai.version import __version__ as version; print(version)"
@@ -45,27 +57,31 @@ echo -e "${BGREEN}HEAD${RESET}:"
 git_show
 echo
 
-echo -e -n "Create tags ${BCYAN}${VERSION}${RESET} and ${BCYAN}${LATEST_TAG}${RESET} @ ${BGREEN}HEAD${RESET}, ${RED}deleting existing tags on remote${RESET}? "
+echo -e "${BGREEN}git remote -v${RESET}:"
+git remote -v
+echo
+
+echo -e -n "Create tags ${BCYAN}${VERSION}${RESET} and ${BCYAN}${LATEST_TAG}${RESET} @ ${BGREEN}HEAD${RESET}, ${RED}deleting existing tags on origin remote${RESET}? "
 read -e -p 'y/n [n]: ' input
 RESPONSE=${input:='n'}
 if [ "$RESPONSE" == 'y' ]; then
     echo
-    echo -e "Deleting ${BCYAN}${VERSION}${RESET} tag on remote..."
-    git push --delete origin $VERSION
+    echo -e "Deleting ${BCYAN}${VERSION}${RESET} tag on origin remote..."
+    git push origin :refs/tags/$VERSION
 
-    echo -e "Tagging ${BGREEN}HEAD${RESET} with ${BCYAN}${VERSION}${RESET} locally..."
+    echo -e "Tagging ${BGREEN}HEAD${RESET} with ${BCYAN}${VERSION}${RESET} on locally..."
     if ! git tag -fa $VERSION; then
         echo "Existing/invalid tag"
         exit -1
     fi
 
-    echo -e "Deleting ${BCYAN}${LATEST_TAG}${RESET} tag on remote..."
-    git push --delete origin $LATEST_TAG
+    echo -e "Deleting ${BCYAN}${LATEST_TAG}${RESET} tag on origin remote..."
+    git push origin :refs/tags/$LATEST_TAG
 
     echo -e "Tagging ${BGREEN}HEAD${RESET} with ${BCYAN}${LATEST_TAG}${RESET} locally..."
     git tag -fa $LATEST_TAG
 
-    echo -e "Pushing updated tags to remote..."
+    echo -e "Pushing updated tags to origin remote..."
     git push origin --tags
 fi
 exit 0

invokeai/app/api/dependencies.py

@@ -11,6 +11,7 @@ from ..services.board_images.board_images_default import BoardImagesService
 from ..services.board_records.board_records_sqlite import SqliteBoardRecordStorage
 from ..services.boards.boards_default import BoardService
 from ..services.config import InvokeAIAppConfig
+from ..services.download import DownloadQueueService
 from ..services.image_files.image_files_disk import DiskImageFileStorage
 from ..services.image_records.image_records_sqlite import SqliteImageRecordStorage
 from ..services.images.images_default import ImageService
@@ -29,8 +30,7 @@ from ..services.model_records import ModelRecordServiceSQL
 from ..services.names.names_default import SimpleNameService
 from ..services.session_processor.session_processor_default import DefaultSessionProcessor
 from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
-from ..services.shared.default_graphs import create_system_graphs
-from ..services.shared.graph import GraphExecutionState, LibraryGraph
+from ..services.shared.graph import GraphExecutionState
 from ..services.urls.urls_default import LocalUrlService
 from ..services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
 from .events import FastAPIEventService
@@ -80,13 +80,13 @@ class ApiDependencies:
         boards = BoardService()
         events = FastAPIEventService(event_handler_id)
         graph_execution_manager = SqliteItemStorage[GraphExecutionState](db=db, table_name="graph_executions")
-        graph_library = SqliteItemStorage[LibraryGraph](db=db, table_name="graphs")
         image_records = SqliteImageRecordStorage(db=db)
         images = ImageService()
         invocation_cache = MemoryInvocationCache(max_cache_size=config.node_cache_size)
         latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f"{output_folder}/latents"))
         model_manager = ModelManagerService(config, logger)
         model_record_service = ModelRecordServiceSQL(db=db)
+        download_queue_service = DownloadQueueService(event_bus=events)
         model_install_service = ModelInstallService(
             app_config=config, record_store=model_record_service, event_bus=events
         )
@@ -107,7 +107,6 @@ class ApiDependencies:
             configuration=configuration,
             events=events,
             graph_execution_manager=graph_execution_manager,
-            graph_library=graph_library,
             image_files=image_files,
             image_records=image_records,
             images=images,
@@ -116,6 +115,7 @@ class ApiDependencies:
             logger=logger,
             model_manager=model_manager,
             model_records=model_record_service,
+            download_queue=download_queue_service,
             model_install=model_install_service,
             names=names,
             performance_statistics=performance_statistics,
@@ -127,8 +127,6 @@ class ApiDependencies:
             workflow_records=workflow_records,
         )
 
-        create_system_graphs(services.graph_library)
-
         ApiDependencies.invoker = Invoker(services)
         db.clean()
 

invokeai/app/api/routers/download_queue.py

@@ -0,0 +1,111 @@
+# Copyright (c) 2023 Lincoln D. Stein
+"""FastAPI route for the download queue."""
+
+from typing import List, Optional
+
+from fastapi import Body, Path, Response
+from fastapi.routing import APIRouter
+from pydantic.networks import AnyHttpUrl
+from starlette.exceptions import HTTPException
+
+from invokeai.app.services.download import (
+    DownloadJob,
+    UnknownJobIDException,
+)
+
+from ..dependencies import ApiDependencies
+
+download_queue_router = APIRouter(prefix="/v1/download_queue", tags=["download_queue"])
+
+
+@download_queue_router.get(
+    "/",
+    operation_id="list_downloads",
+)
+async def list_downloads() -> List[DownloadJob]:
+    """Get a list of active and inactive jobs."""
+    queue = ApiDependencies.invoker.services.download_queue
+    return queue.list_jobs()
+
+
+@download_queue_router.patch(
+    "/",
+    operation_id="prune_downloads",
+    responses={
+        204: {"description": "All completed jobs have been pruned"},
+        400: {"description": "Bad request"},
+    },
+)
+async def prune_downloads():
+    """Prune completed and errored jobs."""
+    queue = ApiDependencies.invoker.services.download_queue
+    queue.prune_jobs()
+    return Response(status_code=204)
+
+
+@download_queue_router.post(
+    "/i/",
+    operation_id="download",
+)
+async def download(
+    source: AnyHttpUrl = Body(description="download source"),
+    dest: str = Body(description="download destination"),
+    priority: int = Body(default=10, description="queue priority"),
+    access_token: Optional[str] = Body(default=None, description="token for authorization to download"),
+) -> DownloadJob:
+    """Download the source URL to the file or directory indicted in dest."""
+    queue = ApiDependencies.invoker.services.download_queue
+    return queue.download(source, dest, priority, access_token)
+
+
+@download_queue_router.get(
+    "/i/{id}",
+    operation_id="get_download_job",
+    responses={
+        200: {"description": "Success"},
+        404: {"description": "The requested download JobID could not be found"},
+    },
+)
+async def get_download_job(
+    id: int = Path(description="ID of the download job to fetch."),
+) -> DownloadJob:
+    """Get a download job using its ID."""
+    try:
+        job = ApiDependencies.invoker.services.download_queue.id_to_job(id)
+        return job
+    except UnknownJobIDException as e:
+        raise HTTPException(status_code=404, detail=str(e))
+
+
+@download_queue_router.delete(
+    "/i/{id}",
+    operation_id="cancel_download_job",
+    responses={
+        204: {"description": "Job has been cancelled"},
+        404: {"description": "The requested download JobID could not be found"},
+    },
+)
+async def cancel_download_job(
+    id: int = Path(description="ID of the download job to cancel."),
+):
+    """Cancel a download job using its ID."""
+    try:
+        queue = ApiDependencies.invoker.services.download_queue
+        job = queue.id_to_job(id)
+        queue.cancel_job(job)
+        return Response(status_code=204)
+    except UnknownJobIDException as e:
+        raise HTTPException(status_code=404, detail=str(e))
+
+
+@download_queue_router.delete(
+    "/i",
+    operation_id="cancel_all_download_jobs",
+    responses={
+        204: {"description": "Download jobs have been cancelled"},
+    },
+)
+async def cancel_all_download_jobs():
+    """Cancel all download jobs."""
+    ApiDependencies.invoker.services.download_queue.cancel_all_jobs()
+    return Response(status_code=204)

invokeai/app/api/routers/model_records.py

@@ -26,7 +26,7 @@ from invokeai.backend.model_manager.config import (
 
 from ..dependencies import ApiDependencies
 
-model_records_router = APIRouter(prefix="/v1/model/record", tags=["model_manager_v2"])
+model_records_router = APIRouter(prefix="/v1/model/record", tags=["model_manager_v2_unstable"])
 
 
 class ModelsList(BaseModel):
@@ -45,6 +45,9 @@ async def list_model_records(
     base_models: Optional[List[BaseModelType]] = Query(default=None, description="Base models to include"),
     model_type: Optional[ModelType] = Query(default=None, description="The type of model to get"),
     model_name: Optional[str] = Query(default=None, description="Exact match on the name of the model"),
+    model_format: Optional[str] = Query(
+        default=None, description="Exact match on the format of the model (e.g. 'diffusers')"
+    ),
 ) -> ModelsList:
     """Get a list of models."""
     record_store = ApiDependencies.invoker.services.model_records
@@ -52,10 +55,14 @@ async def list_model_records(
     if base_models:
         for base_model in base_models:
             found_models.extend(
-                record_store.search_by_attr(base_model=base_model, model_type=model_type, model_name=model_name)
+                record_store.search_by_attr(
+                    base_model=base_model, model_type=model_type, model_name=model_name, model_format=model_format
+                )
             )
     else:
-        found_models.extend(record_store.search_by_attr(model_type=model_type, model_name=model_name))
+        found_models.extend(
+            record_store.search_by_attr(model_type=model_type, model_name=model_name, model_format=model_format)
+        )
     return ModelsList(models=found_models)
 
 

invokeai/app/api_app.py

@@ -45,6 +45,7 @@ if True:  # hack to make flake8 happy with imports coming after setting up the c
         app_info,
         board_images,
         boards,
+        download_queue,
         images,
         model_records,
         models,
@@ -116,6 +117,7 @@ app.include_router(sessions.session_router, prefix="/api")
 app.include_router(utilities.utilities_router, prefix="/api")
 app.include_router(models.models_router, prefix="/api")
 app.include_router(model_records.model_records_router, prefix="/api")
+app.include_router(download_queue.download_queue_router, prefix="/api")
 app.include_router(images.images_router, prefix="/api")
 app.include_router(boards.boards_router, prefix="/api")
 app.include_router(board_images.board_images_router, prefix="/api")

invokeai/app/invocations/compel.py

@@ -1,4 +1,3 @@
-import re
 from dataclasses import dataclass
 from typing import List, Optional, Union
 
@@ -17,6 +16,7 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
 from ...backend.model_management.lora import ModelPatcher
 from ...backend.model_management.models import ModelNotFoundException, ModelType
 from ...backend.util.devices import torch_dtype
+from ..util.ti_utils import extract_ti_triggers_from_prompt
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
@@ -87,7 +87,7 @@ class CompelInvocation(BaseInvocation):
         # loras = [(context.services.model_manager.get_model(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
 
         ti_list = []
-        for trigger in re.findall(r"<[a-zA-Z0-9., _-]+>", self.prompt):
+        for trigger in extract_ti_triggers_from_prompt(self.prompt):
             name = trigger[1:-1]
             try:
                 ti_list.append(
@@ -210,7 +210,7 @@ class SDXLPromptInvocationBase:
         # loras = [(context.services.model_manager.get_model(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
 
         ti_list = []
-        for trigger in re.findall(r"<[a-zA-Z0-9., _-]+>", prompt):
+        for trigger in extract_ti_triggers_from_prompt(prompt):
             name = trigger[1:-1]
             try:
                 ti_list.append(

invokeai/app/invocations/onnx.py

@@ -1,7 +1,6 @@
 # Copyright (c) 2023 Borisov Sergey (https://github.com/StAlKeR7779)
 
 import inspect
-import re
 
 # from contextlib import ExitStack
 from typing import List, Literal, Union
@@ -21,6 +20,7 @@ from invokeai.backend import BaseModelType, ModelType, SubModelType
 from ...backend.model_management import ONNXModelPatcher
 from ...backend.stable_diffusion import PipelineIntermediateState
 from ...backend.util import choose_torch_device
+from ..util.ti_utils import extract_ti_triggers_from_prompt
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
@@ -78,7 +78,7 @@ class ONNXPromptInvocation(BaseInvocation):
             ]
 
             ti_list = []
-            for trigger in re.findall(r"<[a-zA-Z0-9., _-]+>", self.prompt):
+            for trigger in extract_ti_triggers_from_prompt(self.prompt):
                 name = trigger[1:-1]
                 try:
                     ti_list.append(

invokeai/app/invocations/tiles.py

@@ -77,7 +77,7 @@ class CalculateImageTilesInvocation(BaseInvocation):
     title="Calculate Image Tiles Even Split",
     tags=["tiles"],
     category="tiles",
-    version="1.0.0",
+    version="1.1.0",
     classification=Classification.Beta,
 )
 class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
@@ -97,11 +97,11 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
         ge=1,
         description="Number of tiles to divide image into on the y axis",
     )
-    overlap_fraction: float = InputField(
-        default=0.25,
+    overlap: int = InputField(
+        default=128,
         ge=0,
-        lt=1,
-        description="Overlap between adjacent tiles as a fraction of the tile's dimensions (0-1)",
+        multiple_of=8,
+        description="The overlap, in pixels, between adjacent tiles.",
     )
 
     def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
@@ -110,7 +110,7 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
             image_width=self.image_width,
             num_tiles_x=self.num_tiles_x,
             num_tiles_y=self.num_tiles_y,
-            overlap_fraction=self.overlap_fraction,
+            overlap=self.overlap,
         )
         return CalculateImageTilesOutput(tiles=tiles)
 

invokeai/app/services/config/config_default.py

@@ -356,7 +356,7 @@ class InvokeAIAppConfig(InvokeAISettings):
         else:
             root = self.find_root().expanduser().absolute()
         self.root = root  # insulate ourselves from relative paths that may change
-        return root
+        return root.resolve()
 
     @property
     def root_dir(self) -> Path:

invokeai/app/services/download/__init__.py

@@ -0,0 +1,12 @@
+"""Init file for download queue."""
+from .download_base import DownloadJob, DownloadJobStatus, DownloadQueueServiceBase, UnknownJobIDException
+from .download_default import DownloadQueueService, TqdmProgress
+
+__all__ = [
+    "DownloadJob",
+    "DownloadQueueServiceBase",
+    "DownloadQueueService",
+    "TqdmProgress",
+    "DownloadJobStatus",
+    "UnknownJobIDException",
+]

invokeai/app/services/download/download_base.py

@@ -0,0 +1,217 @@
+# Copyright (c) 2023 Lincoln D. Stein and the InvokeAI Development Team
+"""Model download service."""
+
+from abc import ABC, abstractmethod
+from enum import Enum
+from functools import total_ordering
+from pathlib import Path
+from typing import Any, Callable, List, Optional
+
+from pydantic import BaseModel, Field, PrivateAttr
+from pydantic.networks import AnyHttpUrl
+
+
+class DownloadJobStatus(str, Enum):
+    """State of a download job."""
+
+    WAITING = "waiting"  # not enqueued, will not run
+    RUNNING = "running"  # actively downloading
+    COMPLETED = "completed"  # finished running
+    CANCELLED = "cancelled"  # user cancelled
+    ERROR = "error"  # terminated with an error message
+
+
+class DownloadJobCancelledException(Exception):
+    """This exception is raised when a download job is cancelled."""
+
+
+class UnknownJobIDException(Exception):
+    """This exception is raised when an invalid job id is referened."""
+
+
+class ServiceInactiveException(Exception):
+    """This exception is raised when user attempts to initiate a download before the service is started."""
+
+
+DownloadEventHandler = Callable[["DownloadJob"], None]
+
+
+@total_ordering
+class DownloadJob(BaseModel):
+    """Class to monitor and control a model download request."""
+
+    # required variables to be passed in on creation
+    source: AnyHttpUrl = Field(description="Where to download from. Specific types specified in child classes.")
+    dest: Path = Field(description="Destination of downloaded model on local disk; a directory or file path")
+    access_token: Optional[str] = Field(default=None, description="authorization token for protected resources")
+    # automatically assigned on creation
+    id: int = Field(description="Numeric ID of this job", default=-1)  # default id is a sentinel
+    priority: int = Field(default=10, description="Queue priority; lower values are higher priority")
+
+    # set internally during download process
+    status: DownloadJobStatus = Field(default=DownloadJobStatus.WAITING, description="Status of the download")
+    download_path: Optional[Path] = Field(default=None, description="Final location of downloaded file")
+    job_started: Optional[str] = Field(default=None, description="Timestamp for when the download job started")
+    job_ended: Optional[str] = Field(
+        default=None, description="Timestamp for when the download job ende1d (completed or errored)"
+    )
+    bytes: int = Field(default=0, description="Bytes downloaded so far")
+    total_bytes: int = Field(default=0, description="Total file size (bytes)")
+
+    # set when an error occurs
+    error_type: Optional[str] = Field(default=None, description="Name of exception that caused an error")
+    error: Optional[str] = Field(default=None, description="Traceback of the exception that caused an error")
+
+    # internal flag
+    _cancelled: bool = PrivateAttr(default=False)
+
+    # optional event handlers passed in on creation
+    _on_start: Optional[DownloadEventHandler] = PrivateAttr(default=None)
+    _on_progress: Optional[DownloadEventHandler] = PrivateAttr(default=None)
+    _on_complete: Optional[DownloadEventHandler] = PrivateAttr(default=None)
+    _on_cancelled: Optional[DownloadEventHandler] = PrivateAttr(default=None)
+    _on_error: Optional[DownloadEventHandler] = PrivateAttr(default=None)
+
+    def __le__(self, other: "DownloadJob") -> bool:
+        """Return True if this job's priority is less than another's."""
+        return self.priority <= other.priority
+
+    def cancel(self) -> None:
+        """Call to cancel the job."""
+        self._cancelled = True
+
+    # cancelled and the callbacks are private attributes in order to prevent
+    # them from being serialized and/or used in the Json Schema
+    @property
+    def cancelled(self) -> bool:
+        """Call to cancel the job."""
+        return self._cancelled
+
+    @property
+    def on_start(self) -> Optional[DownloadEventHandler]:
+        """Return the on_start event handler."""
+        return self._on_start
+
+    @property
+    def on_progress(self) -> Optional[DownloadEventHandler]:
+        """Return the on_progress event handler."""
+        return self._on_progress
+
+    @property
+    def on_complete(self) -> Optional[DownloadEventHandler]:
+        """Return the on_complete event handler."""
+        return self._on_complete
+
+    @property
+    def on_error(self) -> Optional[DownloadEventHandler]:
+        """Return the on_error event handler."""
+        return self._on_error
+
+    @property
+    def on_cancelled(self) -> Optional[DownloadEventHandler]:
+        """Return the on_cancelled event handler."""
+        return self._on_cancelled
+
+    def set_callbacks(
+        self,
+        on_start: Optional[DownloadEventHandler] = None,
+        on_progress: Optional[DownloadEventHandler] = None,
+        on_complete: Optional[DownloadEventHandler] = None,
+        on_cancelled: Optional[DownloadEventHandler] = None,
+        on_error: Optional[DownloadEventHandler] = None,
+    ) -> None:
+        """Set the callbacks for download events."""
+        self._on_start = on_start
+        self._on_progress = on_progress
+        self._on_complete = on_complete
+        self._on_error = on_error
+        self._on_cancelled = on_cancelled
+
+
+class DownloadQueueServiceBase(ABC):
+    """Multithreaded queue for downloading models via URL."""
+
+    @abstractmethod
+    def start(self, *args: Any, **kwargs: Any) -> None:
+        """Start the download worker threads."""
+
+    @abstractmethod
+    def stop(self, *args: Any, **kwargs: Any) -> None:
+        """Stop the download worker threads."""
+
+    @abstractmethod
+    def download(
+        self,
+        source: AnyHttpUrl,
+        dest: Path,
+        priority: int = 10,
+        access_token: Optional[str] = None,
+        on_start: Optional[DownloadEventHandler] = None,
+        on_progress: Optional[DownloadEventHandler] = None,
+        on_complete: Optional[DownloadEventHandler] = None,
+        on_cancelled: Optional[DownloadEventHandler] = None,
+        on_error: Optional[DownloadEventHandler] = None,
+    ) -> DownloadJob:
+        """
+        Create a download job.
+
+        :param source: Source of the download as a URL.
+        :param dest: Path to download to. See below.
+        :param on_start, on_progress, on_complete, on_error: Callbacks for the indicated
+         events.
+        :returns: A DownloadJob object for monitoring the state of the download.
+
+        The `dest` argument is a Path object. Its behavior is:
+
+        1. If the path exists and is a directory, then the URL contents will be downloaded
+            into that directory using the filename indicated in the response's `Content-Disposition` field.
+            If no content-disposition is present, then the last component of the URL will be used (similar to
+            wget's behavior).
+        2. If the path does not exist, then it is taken as the name of a new file to create with the downloaded
+           content.
+        3. If the path exists and is an existing file, then the downloader will try to resume the download from
+           the end of the existing file.
+
+        """
+        pass
+
+    @abstractmethod
+    def list_jobs(self) -> List[DownloadJob]:
+        """
+        List active download jobs.
+
+        :returns List[DownloadJob]: List of download jobs whose state is not "completed."
+        """
+        pass
+
+    @abstractmethod
+    def id_to_job(self, id: int) -> DownloadJob:
+        """
+        Return the DownloadJob corresponding to the integer ID.
+
+        :param id: ID of the DownloadJob.
+
+        Exceptions:
+        * UnknownJobIDException
+        """
+        pass
+
+    @abstractmethod
+    def cancel_all_jobs(self):
+        """Cancel all active and enquedjobs."""
+        pass
+
+    @abstractmethod
+    def prune_jobs(self):
+        """Prune completed and errored queue items from the job list."""
+        pass
+
+    @abstractmethod
+    def cancel_job(self, job: DownloadJob):
+        """Cancel the job, clearing partial downloads and putting it into ERROR state."""
+        pass
+
+    @abstractmethod
+    def join(self):
+        """Wait until all jobs are off the queue."""
+        pass

invokeai/app/services/download/download_default.py

@@ -0,0 +1,418 @@
+# Copyright (c) 2023, Lincoln D. Stein
+"""Implementation of multithreaded download queue for invokeai."""
+
+import os
+import re
+import threading
+import traceback
+from logging import Logger
+from pathlib import Path
+from queue import Empty, PriorityQueue
+from typing import Any, Dict, List, Optional, Set
+
+import requests
+from pydantic.networks import AnyHttpUrl
+from requests import HTTPError
+from tqdm import tqdm
+
+from invokeai.app.services.events.events_base import EventServiceBase
+from invokeai.app.util.misc import get_iso_timestamp
+from invokeai.backend.util.logging import InvokeAILogger
+
+from .download_base import (
+    DownloadEventHandler,
+    DownloadJob,
+    DownloadJobCancelledException,
+    DownloadJobStatus,
+    DownloadQueueServiceBase,
+    ServiceInactiveException,
+    UnknownJobIDException,
+)
+
+# Maximum number of bytes to download during each call to requests.iter_content()
+DOWNLOAD_CHUNK_SIZE = 100000
+
+
+class DownloadQueueService(DownloadQueueServiceBase):
+    """Class for queued download of models."""
+
+    _jobs: Dict[int, DownloadJob]
+    _max_parallel_dl: int = 5
+    _worker_pool: Set[threading.Thread]
+    _queue: PriorityQueue[DownloadJob]
+    _stop_event: threading.Event
+    _lock: threading.Lock
+    _logger: Logger
+    _events: Optional[EventServiceBase] = None
+    _next_job_id: int = 0
+    _accept_download_requests: bool = False
+    _requests: requests.sessions.Session
+
+    def __init__(
+        self,
+        max_parallel_dl: int = 5,
+        event_bus: Optional[EventServiceBase] = None,
+        requests_session: Optional[requests.sessions.Session] = None,
+    ):
+        """
+        Initialize DownloadQueue.
+
+        :param max_parallel_dl: Number of simultaneous downloads allowed [5].
+        :param requests_session: Optional requests.sessions.Session object, for unit tests.
+        """
+        self._jobs = {}
+        self._next_job_id = 0
+        self._queue = PriorityQueue()
+        self._stop_event = threading.Event()
+        self._worker_pool = set()
+        self._lock = threading.Lock()
+        self._logger = InvokeAILogger.get_logger("DownloadQueueService")
+        self._event_bus = event_bus
+        self._requests = requests_session or requests.Session()
+        self._accept_download_requests = False
+        self._max_parallel_dl = max_parallel_dl
+
+    def start(self, *args: Any, **kwargs: Any) -> None:
+        """Start the download worker threads."""
+        with self._lock:
+            if self._worker_pool:
+                raise Exception("Attempt to start the download service twice")
+            self._stop_event.clear()
+            self._start_workers(self._max_parallel_dl)
+            self._accept_download_requests = True
+
+    def stop(self, *args: Any, **kwargs: Any) -> None:
+        """Stop the download worker threads."""
+        with self._lock:
+            if not self._worker_pool:
+                raise Exception("Attempt to stop the download service before it was started")
+            self._accept_download_requests = False  # reject attempts to add new jobs to queue
+            queued_jobs = [x for x in self.list_jobs() if x.status == DownloadJobStatus.WAITING]
+            active_jobs = [x for x in self.list_jobs() if x.status == DownloadJobStatus.RUNNING]
+            if queued_jobs:
+                self._logger.warning(f"Cancelling {len(queued_jobs)} queued downloads")
+            if active_jobs:
+                self._logger.info(f"Waiting for {len(active_jobs)} active download jobs to complete")
+            with self._queue.mutex:
+                self._queue.queue.clear()
+            self.join()  # wait for all active jobs to finish
+            self._stop_event.set()
+            self._worker_pool.clear()
+
+    def download(
+        self,
+        source: AnyHttpUrl,
+        dest: Path,
+        priority: int = 10,
+        access_token: Optional[str] = None,
+        on_start: Optional[DownloadEventHandler] = None,
+        on_progress: Optional[DownloadEventHandler] = None,
+        on_complete: Optional[DownloadEventHandler] = None,
+        on_cancelled: Optional[DownloadEventHandler] = None,
+        on_error: Optional[DownloadEventHandler] = None,
+    ) -> DownloadJob:
+        """Create a download job and return its ID."""
+        if not self._accept_download_requests:
+            raise ServiceInactiveException(
+                "The download service is not currently accepting requests. Please call start() to initialize the service."
+            )
+        with self._lock:
+            id = self._next_job_id
+            self._next_job_id += 1
+            job = DownloadJob(
+                id=id,
+                source=source,
+                dest=dest,
+                priority=priority,
+                access_token=access_token,
+            )
+            job.set_callbacks(
+                on_start=on_start,
+                on_progress=on_progress,
+                on_complete=on_complete,
+                on_cancelled=on_cancelled,
+                on_error=on_error,
+            )
+            self._jobs[id] = job
+            self._queue.put(job)
+        return job
+
+    def join(self) -> None:
+        """Wait for all jobs to complete."""
+        self._queue.join()
+
+    def list_jobs(self) -> List[DownloadJob]:
+        """List all the jobs."""
+        return list(self._jobs.values())
+
+    def prune_jobs(self) -> None:
+        """Prune completed and errored queue items from the job list."""
+        with self._lock:
+            to_delete = set()
+            for job_id, job in self._jobs.items():
+                if self._in_terminal_state(job):
+                    to_delete.add(job_id)
+            for job_id in to_delete:
+                del self._jobs[job_id]
+
+    def id_to_job(self, id: int) -> DownloadJob:
+        """Translate a job ID into a DownloadJob object."""
+        try:
+            return self._jobs[id]
+        except KeyError as excp:
+            raise UnknownJobIDException("Unrecognized job") from excp
+
+    def cancel_job(self, job: DownloadJob) -> None:
+        """
+        Cancel the indicated job.
+
+        If it is running it will be stopped.
+        job.status will be set to DownloadJobStatus.CANCELLED
+        """
+        with self._lock:
+            job.cancel()
+
+    def cancel_all_jobs(self, preserve_partial: bool = False) -> None:
+        """Cancel all jobs (those not in enqueued, running or paused state)."""
+        for job in self._jobs.values():
+            if not self._in_terminal_state(job):
+                self.cancel_job(job)
+
+    def _in_terminal_state(self, job: DownloadJob) -> bool:
+        return job.status in [
+            DownloadJobStatus.COMPLETED,
+            DownloadJobStatus.CANCELLED,
+            DownloadJobStatus.ERROR,
+        ]
+
+    def _start_workers(self, max_workers: int) -> None:
+        """Start the requested number of worker threads."""
+        self._stop_event.clear()
+        for i in range(0, max_workers):  # noqa B007
+            worker = threading.Thread(target=self._download_next_item, daemon=True)
+            self._logger.debug(f"Download queue worker thread {worker.name} starting.")
+            worker.start()
+            self._worker_pool.add(worker)
+
+    def _download_next_item(self) -> None:
+        """Worker thread gets next job on priority queue."""
+        done = False
+        while not done:
+            if self._stop_event.is_set():
+                done = True
+                continue
+            try:
+                job = self._queue.get(timeout=1)
+            except Empty:
+                continue
+
+            try:
+                job.job_started = get_iso_timestamp()
+                self._do_download(job)
+                self._signal_job_complete(job)
+
+            except (OSError, HTTPError) as excp:
+                job.error_type = excp.__class__.__name__ + f"({str(excp)})"
+                job.error = traceback.format_exc()
+                self._signal_job_error(job)
+            except DownloadJobCancelledException:
+                self._signal_job_cancelled(job)
+                self._cleanup_cancelled_job(job)
+
+            finally:
+                job.job_ended = get_iso_timestamp()
+                self._queue.task_done()
+        self._logger.debug(f"Download queue worker thread {threading.current_thread().name} exiting.")
+
+    def _do_download(self, job: DownloadJob) -> None:
+        """Do the actual download."""
+        url = job.source
+        header = {"Authorization": f"Bearer {job.access_token}"} if job.access_token else {}
+        open_mode = "wb"
+
+        # Make a streaming request. This will retrieve headers including
+        # content-length and content-disposition, but not fetch any content itself
+        resp = self._requests.get(str(url), headers=header, stream=True)
+        if not resp.ok:
+            raise HTTPError(resp.reason)
+        content_length = int(resp.headers.get("content-length", 0))
+        job.total_bytes = content_length
+
+        if job.dest.is_dir():
+            file_name = os.path.basename(str(url.path))  # default is to use the last bit of the URL
+
+            if match := re.search('filename="(.+)"', resp.headers.get("Content-Disposition", "")):
+                remote_name = match.group(1)
+                if self._validate_filename(job.dest.as_posix(), remote_name):
+                    file_name = remote_name
+
+            job.download_path = job.dest / file_name
+
+        else:
+            job.dest.parent.mkdir(parents=True, exist_ok=True)
+            job.download_path = job.dest
+
+        assert job.download_path
+
+        # Don't clobber an existing file. See commit 82c2c85202f88c6d24ff84710f297cfc6ae174af
+        # for code that instead resumes an interrupted download.
+        if job.download_path.exists():
+            raise OSError(f"[Errno 17] File {job.download_path} exists")
+
+        # append ".downloading" to the path
+        in_progress_path = self._in_progress_path(job.download_path)
+
+        # signal caller that the download is starting. At this point, key fields such as
+        # download_path and total_bytes will be populated. We call it here because the might
+        # discover that the local file is already complete and generate a COMPLETED status.
+        self._signal_job_started(job)
+
+        # "range not satisfiable" - local file is at least as large as the remote file
+        if resp.status_code == 416 or (content_length > 0 and job.bytes >= content_length):
+            self._logger.warning(f"{job.download_path}: complete file found. Skipping.")
+            return
+
+        # "partial content" - local file is smaller than remote file
+        elif resp.status_code == 206 or job.bytes > 0:
+            self._logger.warning(f"{job.download_path}: partial file found. Resuming")
+
+        # some other error
+        elif resp.status_code != 200:
+            raise HTTPError(resp.reason)
+
+        self._logger.debug(f"{job.source}: Downloading {job.download_path}")
+        report_delta = job.total_bytes / 100  # report every 1% change
+        last_report_bytes = 0
+
+        # DOWNLOAD LOOP
+        with open(in_progress_path, open_mode) as file:
+            for data in resp.iter_content(chunk_size=DOWNLOAD_CHUNK_SIZE):
+                if job.cancelled:
+                    raise DownloadJobCancelledException("Job was cancelled at caller's request")
+
+                job.bytes += file.write(data)
+                if (job.bytes - last_report_bytes >= report_delta) or (job.bytes >= job.total_bytes):
+                    last_report_bytes = job.bytes
+                    self._signal_job_progress(job)
+
+        # if we get here we are done and can rename the file to the original dest
+        in_progress_path.rename(job.download_path)
+
+    def _validate_filename(self, directory: str, filename: str) -> bool:
+        pc_name_max = os.pathconf(directory, "PC_NAME_MAX") if hasattr(os, "pathconf") else 260  # hardcoded for windows
+        pc_path_max = (
+            os.pathconf(directory, "PC_PATH_MAX") if hasattr(os, "pathconf") else 32767
+        )  # hardcoded for windows with long names enabled
+        if "/" in filename:
+            return False
+        if filename.startswith(".."):
+            return False
+        if len(filename) > pc_name_max:
+            return False
+        if len(os.path.join(directory, filename)) > pc_path_max:
+            return False
+        return True
+
+    def _in_progress_path(self, path: Path) -> Path:
+        return path.with_name(path.name + ".downloading")
+
+    def _signal_job_started(self, job: DownloadJob) -> None:
+        job.status = DownloadJobStatus.RUNNING
+        if job.on_start:
+            try:
+                job.on_start(job)
+            except Exception as e:
+                self._logger.error(e)
+        if self._event_bus:
+            assert job.download_path
+            self._event_bus.emit_download_started(str(job.source), job.download_path.as_posix())
+
+    def _signal_job_progress(self, job: DownloadJob) -> None:
+        if job.on_progress:
+            try:
+                job.on_progress(job)
+            except Exception as e:
+                self._logger.error(e)
+        if self._event_bus:
+            assert job.download_path
+            self._event_bus.emit_download_progress(
+                str(job.source),
+                download_path=job.download_path.as_posix(),
+                current_bytes=job.bytes,
+                total_bytes=job.total_bytes,
+            )
+
+    def _signal_job_complete(self, job: DownloadJob) -> None:
+        job.status = DownloadJobStatus.COMPLETED
+        if job.on_complete:
+            try:
+                job.on_complete(job)
+            except Exception as e:
+                self._logger.error(e)
+        if self._event_bus:
+            assert job.download_path
+            self._event_bus.emit_download_complete(
+                str(job.source), download_path=job.download_path.as_posix(), total_bytes=job.total_bytes
+            )
+
+    def _signal_job_cancelled(self, job: DownloadJob) -> None:
+        job.status = DownloadJobStatus.CANCELLED
+        if job.on_cancelled:
+            try:
+                job.on_cancelled(job)
+            except Exception as e:
+                self._logger.error(e)
+        if self._event_bus:
+            self._event_bus.emit_download_cancelled(str(job.source))
+
+    def _signal_job_error(self, job: DownloadJob) -> None:
+        job.status = DownloadJobStatus.ERROR
+        if job.on_error:
+            try:
+                job.on_error(job)
+            except Exception as e:
+                self._logger.error(e)
+        if self._event_bus:
+            assert job.error_type
+            assert job.error
+            self._event_bus.emit_download_error(str(job.source), error_type=job.error_type, error=job.error)
+
+    def _cleanup_cancelled_job(self, job: DownloadJob) -> None:
+        self._logger.warning(f"Cleaning up leftover files from cancelled download job {job.download_path}")
+        try:
+            if job.download_path:
+                partial_file = self._in_progress_path(job.download_path)
+                partial_file.unlink()
+        except OSError as excp:
+            self._logger.warning(excp)
+
+
+# Example on_progress event handler to display a TQDM status bar
+# Activate with:
+#   download_service.download('http://foo.bar/baz', '/tmp', on_progress=TqdmProgress().job_update
+class TqdmProgress(object):
+    """TQDM-based progress bar object to use in on_progress handlers."""
+
+    _bars: Dict[int, tqdm]  # the tqdm object
+    _last: Dict[int, int]  # last bytes downloaded
+
+    def __init__(self) -> None:  # noqa D107
+        self._bars = {}
+        self._last = {}
+
+    def update(self, job: DownloadJob) -> None:  # noqa D102
+        job_id = job.id
+        # new job
+        if job_id not in self._bars:
+            assert job.download_path
+            dest = Path(job.download_path).name
+            self._bars[job_id] = tqdm(
+                desc=dest,
+                initial=0,
+                total=job.total_bytes,
+                unit="iB",
+                unit_scale=True,
+            )
+            self._last[job_id] = 0
+        self._bars[job_id].update(job.bytes - self._last[job_id])
+        self._last[job_id] = job.bytes

invokeai/app/services/events/events_base.py

@@ -17,6 +17,7 @@ from invokeai.backend.model_management.models.base import BaseModelType, ModelTy
 
 class EventServiceBase:
     queue_event: str = "queue_event"
+    download_event: str = "download_event"
     model_event: str = "model_event"
 
     """Basic event bus, to have an empty stand-in when not needed"""
@@ -32,6 +33,13 @@ class EventServiceBase:
             payload={"event": event_name, "data": payload},
         )
 
+    def __emit_download_event(self, event_name: str, payload: dict) -> None:
+        payload["timestamp"] = get_timestamp()
+        self.dispatch(
+            event_name=EventServiceBase.download_event,
+            payload={"event": event_name, "data": payload},
+        )
+
     def __emit_model_event(self, event_name: str, payload: dict) -> None:
         payload["timestamp"] = get_timestamp()
         self.dispatch(
@@ -323,6 +331,79 @@ class EventServiceBase:
             payload={"queue_id": queue_id},
         )
 
+    def emit_download_started(self, source: str, download_path: str) -> None:
+        """
+        Emit when a download job is started.
+
+        :param url: The downloaded url
+        """
+        self.__emit_download_event(
+            event_name="download_started",
+            payload={"source": source, "download_path": download_path},
+        )
+
+    def emit_download_progress(self, source: str, download_path: str, current_bytes: int, total_bytes: int) -> None:
+        """
+        Emit "download_progress" events at regular intervals during a download job.
+
+        :param source: The downloaded source
+        :param download_path: The local downloaded file
+        :param current_bytes: Number of bytes downloaded so far
+        :param total_bytes: The size of the file being downloaded (if known)
+        """
+        self.__emit_download_event(
+            event_name="download_progress",
+            payload={
+                "source": source,
+                "download_path": download_path,
+                "current_bytes": current_bytes,
+                "total_bytes": total_bytes,
+            },
+        )
+
+    def emit_download_complete(self, source: str, download_path: str, total_bytes: int) -> None:
+        """
+        Emit a "download_complete" event at the end of a successful download.
+
+        :param source: Source URL
+        :param download_path: Path to the locally downloaded file
+        :param total_bytes: The size of the downloaded file
+        """
+        self.__emit_download_event(
+            event_name="download_complete",
+            payload={
+                "source": source,
+                "download_path": download_path,
+                "total_bytes": total_bytes,
+            },
+        )
+
+    def emit_download_cancelled(self, source: str) -> None:
+        """Emit a "download_cancelled" event in the event that the download was cancelled by user."""
+        self.__emit_download_event(
+            event_name="download_cancelled",
+            payload={
+                "source": source,
+            },
+        )
+
+    def emit_download_error(self, source: str, error_type: str, error: str) -> None:
+        """
+        Emit a "download_error" event when an download job encounters an exception.
+
+        :param source: Source URL
+        :param error_type: The name of the exception that raised the error
+        :param error: The traceback from this error
+        """
+        self.__emit_download_event(
+            event_name="download_error",
+            payload={
+                "source": source,
+                "error_type": error_type,
+                "error": error,
+            },
+        )
+
     def emit_model_install_started(self, source: str) -> None:
         """
         Emitted when an install job is started.

invokeai/app/services/invocation_services.py

@@ -11,6 +11,7 @@ if TYPE_CHECKING:
     from .board_records.board_records_base import BoardRecordStorageBase
     from .boards.boards_base import BoardServiceABC
     from .config import InvokeAIAppConfig
+    from .download import DownloadQueueServiceBase
     from .events.events_base import EventServiceBase
     from .image_files.image_files_base import ImageFileStorageBase
     from .image_records.image_records_base import ImageRecordStorageBase
@@ -27,7 +28,7 @@ if TYPE_CHECKING:
     from .names.names_base import NameServiceBase
     from .session_processor.session_processor_base import SessionProcessorBase
     from .session_queue.session_queue_base import SessionQueueBase
-    from .shared.graph import GraphExecutionState, LibraryGraph
+    from .shared.graph import GraphExecutionState
     from .urls.urls_base import UrlServiceBase
     from .workflow_records.workflow_records_base import WorkflowRecordsStorageBase
 
@@ -43,7 +44,6 @@ class InvocationServices:
     configuration: "InvokeAIAppConfig"
     events: "EventServiceBase"
     graph_execution_manager: "ItemStorageABC[GraphExecutionState]"
-    graph_library: "ItemStorageABC[LibraryGraph]"
     images: "ImageServiceABC"
     image_records: "ImageRecordStorageBase"
     image_files: "ImageFileStorageBase"
@@ -51,6 +51,7 @@ class InvocationServices:
     logger: "Logger"
     model_manager: "ModelManagerServiceBase"
     model_records: "ModelRecordServiceBase"
+    download_queue: "DownloadQueueServiceBase"
     model_install: "ModelInstallServiceBase"
     processor: "InvocationProcessorABC"
     performance_statistics: "InvocationStatsServiceBase"
@@ -71,7 +72,6 @@ class InvocationServices:
         configuration: "InvokeAIAppConfig",
         events: "EventServiceBase",
         graph_execution_manager: "ItemStorageABC[GraphExecutionState]",
-        graph_library: "ItemStorageABC[LibraryGraph]",
         images: "ImageServiceABC",
         image_files: "ImageFileStorageBase",
         image_records: "ImageRecordStorageBase",
@@ -79,6 +79,7 @@ class InvocationServices:
         logger: "Logger",
         model_manager: "ModelManagerServiceBase",
         model_records: "ModelRecordServiceBase",
+        download_queue: "DownloadQueueServiceBase",
         model_install: "ModelInstallServiceBase",
         processor: "InvocationProcessorABC",
         performance_statistics: "InvocationStatsServiceBase",
@@ -97,7 +98,6 @@ class InvocationServices:
         self.configuration = configuration
         self.events = events
         self.graph_execution_manager = graph_execution_manager
-        self.graph_library = graph_library
         self.images = images
         self.image_files = image_files
         self.image_records = image_records
@@ -105,6 +105,7 @@ class InvocationServices:
         self.logger = logger
         self.model_manager = model_manager
         self.model_records = model_records
+        self.download_queue = download_queue
         self.model_install = model_install
         self.processor = processor
         self.performance_statistics = performance_statistics

invokeai/app/services/model_install/model_install_base.py

@@ -11,7 +11,6 @@ from typing_extensions import Annotated
 
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.events import EventServiceBase
-from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.model_records import ModelRecordServiceBase
 from invokeai.backend.model_manager import AnyModelConfig
 
@@ -157,12 +156,12 @@ class ModelInstallServiceBase(ABC):
         :param event_bus: InvokeAI event bus for reporting events to.
         """
 
-    def start(self, invoker: Invoker) -> None:
-        """Call at InvokeAI startup time."""
-        self.sync_to_config()
+    @abstractmethod
+    def start(self, *args: Any, **kwarg: Any) -> None:
+        """Start the installer service."""
 
     @abstractmethod
-    def stop(self) -> None:
+    def stop(self, *args: Any, **kwarg: Any) -> None:
         """Stop the model install service. After this the objection can be safely deleted."""
 
     @property

invokeai/app/services/model_install/model_install_default.py

@@ -71,7 +71,6 @@ class ModelInstallService(ModelInstallServiceBase):
         self._install_queue = Queue()
         self._cached_model_paths = set()
         self._models_installed = set()
-        self._start_installer_thread()
 
     @property
     def app_config(self) -> InvokeAIAppConfig:  # noqa D102
@@ -85,8 +84,13 @@ class ModelInstallService(ModelInstallServiceBase):
     def event_bus(self) -> Optional[EventServiceBase]:  # noqa D102
         return self._event_bus
 
-    def stop(self, *args, **kwargs) -> None:
-        """Stop the install thread; after this the object can be deleted and garbage collected."""
+    def start(self, *args: Any, **kwarg: Any) -> None:
+        """Start the installer thread."""
+        self._start_installer_thread()
+        self.sync_to_config()
+
+    def stop(self, *args: Any, **kwarg: Any) -> None:
+        """Stop the installer thread; after this the object can be deleted and garbage collected."""
         self._install_queue.put(STOP_JOB)
 
     def _start_installer_thread(self) -> None:

invokeai/app/services/model_records/model_records_base.py

@@ -7,7 +7,7 @@ from abc import ABC, abstractmethod
 from pathlib import Path
 from typing import List, Optional, Union
 
-from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelType
+from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelFormat, ModelType
 
 
 class DuplicateModelException(Exception):
@@ -106,6 +106,7 @@ class ModelRecordServiceBase(ABC):
         model_name: Optional[str] = None,
         base_model: Optional[BaseModelType] = None,
         model_type: Optional[ModelType] = None,
+        model_format: Optional[ModelFormat] = None,
     ) -> List[AnyModelConfig]:
         """
         Return models matching name, base and/or type.
@@ -113,6 +114,7 @@ class ModelRecordServiceBase(ABC):
         :param model_name: Filter by name of model (optional)
         :param base_model: Filter by base model (optional)
         :param model_type: Filter by type of model (optional)
+        :param model_format: Filter by model format (e.g. "diffusers") (optional)
 
         If none of the optional filters are passed, will return all
         models in the database.

invokeai/app/services/model_records/model_records_sql.py

@@ -49,6 +49,7 @@ from invokeai.backend.model_manager.config import (
     AnyModelConfig,
     BaseModelType,
     ModelConfigFactory,
+    ModelFormat,
     ModelType,
 )
 
@@ -225,6 +226,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         model_name: Optional[str] = None,
         base_model: Optional[BaseModelType] = None,
         model_type: Optional[ModelType] = None,
+        model_format: Optional[ModelFormat] = None,
     ) -> List[AnyModelConfig]:
         """
         Return models matching name, base and/or type.
@@ -232,6 +234,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         :param model_name: Filter by name of model (optional)
         :param base_model: Filter by base model (optional)
         :param model_type: Filter by type of model (optional)
+        :param model_format: Filter by model format (e.g. "diffusers") (optional)
 
         If none of the optional filters are passed, will return all
         models in the database.
@@ -248,6 +251,9 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         if model_type:
             where_clause.append("type=?")
             bindings.append(model_type)
+        if model_format:
+            where_clause.append("format=?")
+            bindings.append(model_format)
         where = f"WHERE {' AND '.join(where_clause)}" if where_clause else ""
         with self._db.lock:
             self._cursor.execute(

invokeai/app/services/shared/sqlite/sqlite_util.py

@@ -5,6 +5,7 @@ from invokeai.app.services.image_files.image_files_base import ImageFileStorageB
 from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_1 import build_migration_1
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_2 import build_migration_2
+from invokeai.app.services.shared.sqlite_migrator.migrations.migration_3 import build_migration_3
 from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_impl import SqliteMigrator
 
 
@@ -27,6 +28,7 @@ def init_db(config: InvokeAIAppConfig, logger: Logger, image_files: ImageFileSto
     migrator = SqliteMigrator(db=db)
     migrator.register_migration(build_migration_1())
     migrator.register_migration(build_migration_2(image_files=image_files, logger=logger))
+    migrator.register_migration(build_migration_3())
     migrator.run_migrations()
 
     return db

invokeai/app/services/shared/sqlite_migrator/migrations/migration_2.py

@@ -11,6 +11,8 @@ from invokeai.app.services.workflow_records.workflow_records_common import (
     UnsafeWorkflowWithVersionValidator,
 )
 
+from .util.migrate_yaml_config_1 import MigrateModelYamlToDb1
+
 
 class Migration2Callback:
     def __init__(self, image_files: ImageFileStorageBase, logger: Logger):
@@ -24,6 +26,7 @@ class Migration2Callback:
         self._add_workflow_library(cursor)
         self._drop_model_manager_metadata(cursor)
         self._recreate_model_config(cursor)
+        self._migrate_model_config_records(cursor)
         self._migrate_embedded_workflows(cursor)
 
     def _add_images_has_workflow(self, cursor: sqlite3.Cursor) -> None:
@@ -131,6 +134,11 @@ class Migration2Callback:
             """
         )
 
+    def _migrate_model_config_records(self, cursor: sqlite3.Cursor) -> None:
+        """After updating the model config table, we repopulate it."""
+        model_record_migrator = MigrateModelYamlToDb1(cursor)
+        model_record_migrator.migrate()
+
     def _migrate_embedded_workflows(self, cursor: sqlite3.Cursor) -> None:
         """
         In the v3.5.0 release, InvokeAI changed how it handles embedded workflows. The `images` table in

invokeai/app/services/shared/sqlite_migrator/migrations/migration_3.py

@@ -0,0 +1,75 @@
+import sqlite3
+
+from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
+
+from .util.migrate_yaml_config_1 import MigrateModelYamlToDb1
+
+
+class Migration3Callback:
+    def __init__(self) -> None:
+        pass
+
+    def __call__(self, cursor: sqlite3.Cursor) -> None:
+        self._drop_model_manager_metadata(cursor)
+        self._recreate_model_config(cursor)
+        self._migrate_model_config_records(cursor)
+
+    def _drop_model_manager_metadata(self, cursor: sqlite3.Cursor) -> None:
+        """Drops the `model_manager_metadata` table."""
+        cursor.execute("DROP TABLE IF EXISTS model_manager_metadata;")
+
+    def _recreate_model_config(self, cursor: sqlite3.Cursor) -> None:
+        """
+        Drops the `model_config` table, recreating it.
+
+        In 3.4.0, this table used explicit columns but was changed to use json_extract 3.5.0.
+
+        Because this table is not used in production, we are able to simply drop it and recreate it.
+        """
+
+        cursor.execute("DROP TABLE IF EXISTS model_config;")
+
+        cursor.execute(
+            """--sql
+            CREATE TABLE IF NOT EXISTS model_config (
+                id TEXT NOT NULL PRIMARY KEY,
+                -- The next 3 fields are enums in python, unrestricted string here
+                base TEXT GENERATED ALWAYS as (json_extract(config, '$.base')) VIRTUAL NOT NULL,
+                type TEXT GENERATED ALWAYS as (json_extract(config, '$.type')) VIRTUAL NOT NULL,
+                name TEXT GENERATED ALWAYS as (json_extract(config, '$.name')) VIRTUAL NOT NULL,
+                path TEXT GENERATED ALWAYS as (json_extract(config, '$.path')) VIRTUAL NOT NULL,
+                format TEXT GENERATED ALWAYS as (json_extract(config, '$.format')) VIRTUAL NOT NULL,
+                original_hash TEXT, -- could be null
+                -- Serialized JSON representation of the whole config object,
+                -- which will contain additional fields from subclasses
+                config TEXT NOT NULL,
+                created_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
+                -- Updated via trigger
+                updated_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
+                -- unique constraint on combo of name, base and type
+                UNIQUE(name, base, type)
+            );
+            """
+        )
+
+    def _migrate_model_config_records(self, cursor: sqlite3.Cursor) -> None:
+        """After updating the model config table, we repopulate it."""
+        model_record_migrator = MigrateModelYamlToDb1(cursor)
+        model_record_migrator.migrate()
+
+
+def build_migration_3() -> Migration:
+    """
+    Build the migration from database version 2 to 3.
+
+    This migration does the following:
+    - Drops the `model_config` table, recreating it
+    - Migrates data from `models.yaml` into the `model_config` table
+    """
+    migration_3 = Migration(
+        from_version=2,
+        to_version=3,
+        callback=Migration3Callback(),
+    )
+
+    return migration_3

invokeai/app/services/shared/sqlite_migrator/migrations/util/migrate_yaml_config_1.py

@@ -1,8 +1,12 @@
 # Copyright (c) 2023 Lincoln D. Stein
 """Migrate from the InvokeAI v2 models.yaml format to the v3 sqlite format."""
 
+import json
+import sqlite3
 from hashlib import sha1
 from logging import Logger
+from pathlib import Path
+from typing import Optional
 
 from omegaconf import DictConfig, OmegaConf
 from pydantic import TypeAdapter
@@ -10,13 +14,12 @@ from pydantic import TypeAdapter
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.model_records import (
     DuplicateModelException,
-    ModelRecordServiceSQL,
     UnknownModelException,
 )
-from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 from invokeai.backend.model_manager.config import (
     AnyModelConfig,
     BaseModelType,
+    ModelConfigFactory,
     ModelType,
 )
 from invokeai.backend.model_manager.hash import FastModelHash
@@ -25,9 +28,9 @@ from invokeai.backend.util.logging import InvokeAILogger
 ModelsValidator = TypeAdapter(AnyModelConfig)
 
 
-class MigrateModelYamlToDb:
+class MigrateModelYamlToDb1:
     """
-    Migrate the InvokeAI models.yaml format (VERSION 3.0.0) to SQL3 database format (VERSION 3.2.0)
+    Migrate the InvokeAI models.yaml format (VERSION 3.0.0) to SQL3 database format (VERSION 3.5.0).
 
     The class has one externally useful method, migrate(), which scans the
     currently models.yaml file and imports all its entries into invokeai.db.
@@ -41,17 +44,13 @@ class MigrateModelYamlToDb:
 
     config: InvokeAIAppConfig
     logger: Logger
+    cursor: sqlite3.Cursor
 
-    def __init__(self) -> None:
+    def __init__(self, cursor: sqlite3.Cursor = None) -> None:
         self.config = InvokeAIAppConfig.get_config()
         self.config.parse_args()
         self.logger = InvokeAILogger.get_logger()
-
-    def get_db(self) -> ModelRecordServiceSQL:
-        """Fetch the sqlite3 database for this installation."""
-        db_path = None if self.config.use_memory_db else self.config.db_path
-        db = SqliteDatabase(db_path=db_path, logger=self.logger, verbose=self.config.log_sql)
-        return ModelRecordServiceSQL(db)
+        self.cursor = cursor
 
     def get_yaml(self) -> DictConfig:
         """Fetch the models.yaml DictConfig for this installation."""
@@ -62,8 +61,10 @@ class MigrateModelYamlToDb:
 
     def migrate(self) -> None:
         """Do the migration from models.yaml to invokeai.db."""
-        db = self.get_db()
-        yaml = self.get_yaml()
+        try:
+            yaml = self.get_yaml()
+        except OSError:
+            return
 
         for model_key, stanza in yaml.items():
             if model_key == "__metadata__":
@@ -86,22 +87,62 @@ class MigrateModelYamlToDb:
             new_config: AnyModelConfig = ModelsValidator.validate_python(stanza)  # type: ignore # see https://github.com/pydantic/pydantic/discussions/7094
 
             try:
-                if original_record := db.search_by_path(stanza.path):
-                    key = original_record[0].key
+                if original_record := self._search_by_path(stanza.path):
+                    key = original_record.key
                     self.logger.info(f"Updating model {model_name} with information from models.yaml using key {key}")
-                    db.update_model(key, new_config)
+                    self._update_model(key, new_config)
                 else:
                     self.logger.info(f"Adding model {model_name} with key {model_key}")
-                    db.add_model(new_key, new_config)
+                    self._add_model(new_key, new_config)
             except DuplicateModelException:
                 self.logger.warning(f"Model {model_name} is already in the database")
             except UnknownModelException:
                 self.logger.warning(f"Model at {stanza.path} could not be found in database")
 
+    def _search_by_path(self, path: Path) -> Optional[AnyModelConfig]:
+        self.cursor.execute(
+            """--sql
+            SELECT config FROM model_config
+            WHERE path=?;
+            """,
+            (str(path),),
+        )
+        results = [ModelConfigFactory.make_config(json.loads(x[0])) for x in self.cursor.fetchall()]
+        return results[0] if results else None
 
-def main():
-    MigrateModelYamlToDb().migrate()
+    def _update_model(self, key: str, config: AnyModelConfig) -> None:
+        record = ModelConfigFactory.make_config(config, key=key)  # ensure it is a valid config obect
+        json_serialized = record.model_dump_json()  # and turn it into a json string.
+        self.cursor.execute(
+            """--sql
+            UPDATE model_config
+            SET
+                config=?
+            WHERE id=?;
+            """,
+            (json_serialized, key),
+        )
+        if self.cursor.rowcount == 0:
+            raise UnknownModelException("model not found")
 
-
-if __name__ == "__main__":
-    main()
+    def _add_model(self, key: str, config: AnyModelConfig) -> None:
+        record = ModelConfigFactory.make_config(config, key=key)  # ensure it is a valid config obect.
+        json_serialized = record.model_dump_json()  # and turn it into a json string.
+        try:
+            self.cursor.execute(
+                """--sql
+                INSERT INTO model_config (
+                   id,
+                   original_hash,
+                   config
+                  )
+                VALUES (?,?,?);
+                """,
+                (
+                    key,
+                    record.original_hash,
+                    json_serialized,
+                ),
+            )
+        except sqlite3.IntegrityError as exc:
+            raise DuplicateModelException(f"{record.name}: model is already in database") from exc

invokeai/app/services/workflow_records/default_workflows/Prompt from File.json

@@ -0,0 +1,975 @@
+{
+  "name": "Prompt from File",
+  "author": "InvokeAI",
+  "description": "Sample workflow using Prompt from File node",
+  "version": "0.1.0",
+  "contact": "invoke@invoke.ai",
+  "tags": "text2image, prompt from file, default",
+  "notes": "",
+  "exposedFields": [
+    {
+      "nodeId": "d6353b7f-b447-4e17-8f2e-80a88c91d426",
+      "fieldName": "model"
+    },
+    {
+      "nodeId": "1b7e0df8-8589-4915-a4ea-c0088f15d642",
+      "fieldName": "file_path"
+    }
+  ],
+  "meta": {
+    "category": "default",
+    "version": "2.0.0"
+  },
+  "id": "d1609af5-eb0a-4f73-b573-c9af96a8d6bf",
+  "nodes": [
+    {
+      "id": "c2eaf1ba-5708-4679-9e15-945b8b432692",
+      "type": "invocation",
+      "data": {
+        "id": "c2eaf1ba-5708-4679-9e15-945b8b432692",
+        "type": "compel",
+        "label": "",
+        "isOpen": false,
+        "notes": "",
+        "isIntermediate": true,
+        "useCache": true,
+        "version": "1.0.0",
+        "nodePack": "invokeai",
+        "inputs": {
+          "prompt": {
+            "id": "dcdf3f6d-9b96-4bcd-9b8d-f992fefe4f62",
+            "name": "prompt",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "StringField"
+            },
+            "value": ""
+          },
+          "clip": {
+            "id": "3f1981c9-d8a9-42eb-a739-4f120eb80745",
+            "name": "clip",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "ClipField"
+            }
+          }
+        },
+        "outputs": {
+          "conditioning": {
+            "id": "46205e6c-c5e2-44cb-9c82-1cd20b95674a",
+            "name": "conditioning",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "ConditioningField"
+            }
+          }
+        }
+      },
+      "width": 320,
+      "height": 32,
+      "position": {
+        "x": 925,
+        "y": -200
+      }
+    },
+    {
+      "id": "1b7e0df8-8589-4915-a4ea-c0088f15d642",
+      "type": "invocation",
+      "data": {
+        "id": "1b7e0df8-8589-4915-a4ea-c0088f15d642",
+        "type": "prompt_from_file",
+        "label": "Prompts from File",
+        "isOpen": true,
+        "notes": "",
+        "isIntermediate": true,
+        "useCache": true,
+        "version": "1.0.1",
+        "nodePack": "invokeai",
+        "inputs": {
+          "file_path": {
+            "id": "37e37684-4f30-4ec8-beae-b333e550f904",
+            "name": "file_path",
+            "fieldKind": "input",
+            "label": "Prompts File Path",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "StringField"
+            },
+            "value": ""
+          },
+          "pre_prompt": {
+            "id": "7de02feb-819a-4992-bad3-72a30920ddea",
+            "name": "pre_prompt",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "StringField"
+            },
+            "value": ""
+          },
+          "post_prompt": {
+            "id": "95f191d8-a282-428e-bd65-de8cb9b7513a",
+            "name": "post_prompt",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "StringField"
+            },
+            "value": ""
+          },
+          "start_line": {
+            "id": "efee9a48-05ab-4829-8429-becfa64a0782",
+            "name": "start_line",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            },
+            "value": 1
+          },
+          "max_prompts": {
+            "id": "abebb428-3d3d-49fd-a482-4e96a16fff08",
+            "name": "max_prompts",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            },
+            "value": 1
+          }
+        },
+        "outputs": {
+          "collection": {
+            "id": "77d5d7f1-9877-4ab1-9a8c-33e9ffa9abf3",
+            "name": "collection",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": true,
+              "isCollectionOrScalar": false,
+              "name": "StringField"
+            }
+          }
+        }
+      },
+      "width": 320,
+      "height": 580,
+      "position": {
+        "x": 475,
+        "y": -400
+      }
+    },
+    {
+      "id": "1b89067c-3f6b-42c8-991f-e3055789b251",
+      "type": "invocation",
+      "data": {
+        "id": "1b89067c-3f6b-42c8-991f-e3055789b251",
+        "type": "iterate",
+        "label": "",
+        "isOpen": false,
+        "notes": "",
+        "isIntermediate": true,
+        "useCache": true,
+        "version": "1.1.0",
+        "inputs": {
+          "collection": {
+            "id": "4c564bf8-5ed6-441e-ad2c-dda265d5785f",
+            "name": "collection",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": true,
+              "isCollectionOrScalar": false,
+              "name": "CollectionField"
+            }
+          }
+        },
+        "outputs": {
+          "item": {
+            "id": "36340f9a-e7a5-4afa-b4b5-313f4e292380",
+            "name": "item",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "CollectionItemField"
+            }
+          },
+          "index": {
+            "id": "1beca95a-2159-460f-97ff-c8bab7d89336",
+            "name": "index",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            }
+          },
+          "total": {
+            "id": "ead597b8-108e-4eda-88a8-5c29fa2f8df9",
+            "name": "total",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            }
+          }
+        }
+      },
+      "width": 320,
+      "height": 32,
+      "position": {
+        "x": 925,
+        "y": -400
+      }
+    },
+    {
+      "id": "d6353b7f-b447-4e17-8f2e-80a88c91d426",
+      "type": "invocation",
+      "data": {
+        "id": "d6353b7f-b447-4e17-8f2e-80a88c91d426",
+        "type": "main_model_loader",
+        "label": "",
+        "isOpen": true,
+        "notes": "",
+        "isIntermediate": true,
+        "useCache": true,
+        "version": "1.0.0",
+        "nodePack": "invokeai",
+        "inputs": {
+          "model": {
+            "id": "3f264259-3418-47d5-b90d-b6600e36ae46",
+            "name": "model",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "MainModelField"
+            },
+            "value": {
+              "model_name": "stable-diffusion-v1-5",
+              "base_model": "sd-1",
+              "model_type": "main"
+            }
+          }
+        },
+        "outputs": {
+          "unet": {
+            "id": "8e182ea2-9d0a-4c02-9407-27819288d4b5",
+            "name": "unet",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "UNetField"
+            }
+          },
+          "clip": {
+            "id": "d67d9d30-058c-46d5-bded-3d09d6d1aa39",
+            "name": "clip",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "ClipField"
+            }
+          },
+          "vae": {
+            "id": "89641601-0429-4448-98d5-190822d920d8",
+            "name": "vae",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "VaeField"
+            }
+          }
+        }
+      },
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invokeai/app/services/workflow_records/default_workflows/Text to Image with LoRA.json

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+          "value": {
+            "id": "c64878fa-53b1-4202-b88a-cfb854216a57",
+            "name": "value",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            }
+          }
+        }
+      },
+      "width": 320,
+      "height": 32,
+      "position": {
+        "x": 3425,
+        "y": 0
+      }
+    },
+    {
+      "id": "a9683c0a-6b1f-4a5e-8187-c57e764b3400",
+      "type": "invocation",
+      "data": {
+        "id": "a9683c0a-6b1f-4a5e-8187-c57e764b3400",
+        "type": "l2i",
+        "label": "",
+        "isOpen": true,
+        "notes": "",
+        "isIntermediate": false,
+        "useCache": true,
+        "version": "1.2.0",
+        "inputs": {
+          "metadata": {
+            "id": "b1982e8a-14ad-4029-a697-beb30af8340f",
+            "name": "metadata",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "MetadataField"
+            }
+          },
+          "latents": {
+            "id": "f7669388-9f91-46cc-94fc-301fa7041c3e",
+            "name": "latents",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "LatentsField"
+            }
+          },
+          "vae": {
+            "id": "c6f2d4db-4d0a-4e3d-acb4-b5c5a228a3e2",
+            "name": "vae",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "VaeField"
+            }
+          },
+          "tiled": {
+            "id": "19ef7d31-d96f-4e94-b7e5-95914e9076fc",
+            "name": "tiled",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "BooleanField"
+            },
+            "value": false
+          },
+          "fp32": {
+            "id": "a9454533-8ab7-4225-b411-646dc5e76d00",
+            "name": "fp32",
+            "fieldKind": "input",
+            "label": "",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "BooleanField"
+            },
+            "value": false
+          }
+        },
+        "outputs": {
+          "image": {
+            "id": "4f81274e-e216-47f3-9fb6-f97493a40e6f",
+            "name": "image",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "ImageField"
+            }
+          },
+          "width": {
+            "id": "61a9acfb-1547-4f1e-8214-e89bd3855ee5",
+            "name": "width",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            }
+          },
+          "height": {
+            "id": "b15cc793-4172-4b07-bcf4-5627bbc7d0d7",
+            "name": "height",
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            }
+          }
+        }
+      },
+      "width": 320,
+      "height": 267,
+      "position": {
+        "x": 4450,
+        "y": -550
+      }
+    }
+  ],
+  "edges": [
+    {
+      "id": "6fd74a17-6065-47a5-b48b-f4e2b8fa7953-ea18915f-2c5b-4569-b725-8e9e9122e8d3-collapsed",
+      "source": "6fd74a17-6065-47a5-b48b-f4e2b8fa7953",
+      "target": "ea18915f-2c5b-4569-b725-8e9e9122e8d3",
+      "type": "collapsed"
+    },
+    {
+      "id": "reactflow__edge-24e9d7ed-4836-4ec4-8f9e-e747721f9818clip-c41e705b-f2e3-4d1a-83c4-e34bb9344966clip",
+      "source": "24e9d7ed-4836-4ec4-8f9e-e747721f9818",
+      "target": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
+      "type": "default",
+      "sourceHandle": "clip",
+      "targetHandle": "clip"
+    },
+    {
+      "id": "reactflow__edge-c41e705b-f2e3-4d1a-83c4-e34bb9344966clip-c3fa6872-2599-4a82-a596-b3446a66cf8bclip",
+      "source": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
+      "target": "c3fa6872-2599-4a82-a596-b3446a66cf8b",
+      "type": "default",
+      "sourceHandle": "clip",
+      "targetHandle": "clip"
+    },
+    {
+      "id": "reactflow__edge-24e9d7ed-4836-4ec4-8f9e-e747721f9818unet-c41e705b-f2e3-4d1a-83c4-e34bb9344966unet",
+      "source": "24e9d7ed-4836-4ec4-8f9e-e747721f9818",
+      "target": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
+      "type": "default",
+      "sourceHandle": "unet",
+      "targetHandle": "unet"
+    },
+    {
+      "id": "reactflow__edge-c41e705b-f2e3-4d1a-83c4-e34bb9344966unet-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63unet",
+      "source": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
+      "target": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
+      "type": "default",
+      "sourceHandle": "unet",
+      "targetHandle": "unet"
+    },
+    {
+      "id": "reactflow__edge-85b77bb2-c67a-416a-b3e8-291abe746c44conditioning-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63negative_conditioning",
+      "source": "85b77bb2-c67a-416a-b3e8-291abe746c44",
+      "target": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
+      "type": "default",
+      "sourceHandle": "conditioning",
+      "targetHandle": "negative_conditioning"
+    },
+    {
+      "id": "reactflow__edge-c3fa6872-2599-4a82-a596-b3446a66cf8bconditioning-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63positive_conditioning",
+      "source": "c3fa6872-2599-4a82-a596-b3446a66cf8b",
+      "target": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
+      "type": "default",
+      "sourceHandle": "conditioning",
+      "targetHandle": "positive_conditioning"
+    },
+    {
+      "id": "reactflow__edge-ea18915f-2c5b-4569-b725-8e9e9122e8d3noise-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63noise",
+      "source": "ea18915f-2c5b-4569-b725-8e9e9122e8d3",
+      "target": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
+      "type": "default",
+      "sourceHandle": "noise",
+      "targetHandle": "noise"
+    },
+    {
+      "id": "reactflow__edge-6fd74a17-6065-47a5-b48b-f4e2b8fa7953value-ea18915f-2c5b-4569-b725-8e9e9122e8d3seed",
+      "source": "6fd74a17-6065-47a5-b48b-f4e2b8fa7953",
+      "target": "ea18915f-2c5b-4569-b725-8e9e9122e8d3",
+      "type": "default",
+      "sourceHandle": "value",
+      "targetHandle": "seed"
+    },
+    {
+      "id": "reactflow__edge-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63latents-a9683c0a-6b1f-4a5e-8187-c57e764b3400latents",
+      "source": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
+      "target": "a9683c0a-6b1f-4a5e-8187-c57e764b3400",
+      "type": "default",
+      "sourceHandle": "latents",
+      "targetHandle": "latents"
+    },
+    {
+      "id": "reactflow__edge-24e9d7ed-4836-4ec4-8f9e-e747721f9818vae-a9683c0a-6b1f-4a5e-8187-c57e764b3400vae",
+      "source": "24e9d7ed-4836-4ec4-8f9e-e747721f9818",
+      "target": "a9683c0a-6b1f-4a5e-8187-c57e764b3400",
+      "type": "default",
+      "sourceHandle": "vae",
+      "targetHandle": "vae"
+    },
+    {
+      "id": "reactflow__edge-c41e705b-f2e3-4d1a-83c4-e34bb9344966clip-85b77bb2-c67a-416a-b3e8-291abe746c44clip",
+      "source": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
+      "target": "85b77bb2-c67a-416a-b3e8-291abe746c44",
+      "type": "default",
+      "sourceHandle": "clip",
+      "targetHandle": "clip"
+    }
+  ]
+}

invokeai/app/util/ti_utils.py

@@ -0,0 +1,8 @@
+import re
+
+
+def extract_ti_triggers_from_prompt(prompt: str) -> list[str]:
+    ti_triggers = []
+    for trigger in re.findall(r"<[a-zA-Z0-9., _-]+>", prompt):
+        ti_triggers.append(trigger)
+    return ti_triggers

invokeai/backend/install/check_root.py

@@ -28,7 +28,7 @@ def check_invokeai_root(config: InvokeAIAppConfig):
         print("== STARTUP ABORTED ==")
         print("** One or more necessary files is missing from your InvokeAI root directory **")
         print("** Please rerun the configuration script to fix this problem. **")
-        print("** From the launcher, selection option [7]. **")
+        print("** From the launcher, selection option [6]. **")
         print(
             '** From the command line, activate the virtual environment and run "invokeai-configure --yes --skip-sd-weights" **'
         )

invokeai/backend/model_management/model_probe.py

@@ -389,7 +389,7 @@ class TextualInversionCheckpointProbe(CheckpointProbeBase):
         elif "clip_g" in checkpoint:
             token_dim = checkpoint["clip_g"].shape[-1]
         else:
-            token_dim = list(checkpoint.values())[0].shape[0]
+            token_dim = list(checkpoint.values())[0].shape[-1]
         if token_dim == 768:
             return BaseModelType.StableDiffusion1
         elif token_dim == 1024:

invokeai/backend/model_management/util.py

@@ -9,7 +9,7 @@ def lora_token_vector_length(checkpoint: dict) -> int:
     :param checkpoint: The checkpoint
     """
 
-    def _get_shape_1(key, tensor, checkpoint):
+    def _get_shape_1(key: str, tensor, checkpoint) -> int:
         lora_token_vector_length = None
 
         if "." not in key:
@@ -57,6 +57,10 @@ def lora_token_vector_length(checkpoint: dict) -> int:
     for key, tensor in checkpoint.items():
         if key.startswith("lora_unet_") and ("_attn2_to_k." in key or "_attn2_to_v." in key):
             lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
+        elif key.startswith("lora_unet_") and (
+            "time_emb_proj.lora_down" in key
+        ):  # recognizes format at https://civitai.com/models/224641
+            lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
         elif key.startswith("lora_te") and "_self_attn_" in key:
             tmp_length = _get_shape_1(key, tensor, checkpoint)
             if key.startswith("lora_te_"):

invokeai/backend/model_manager/probe.py

@@ -400,6 +400,8 @@ class LoRACheckpointProbe(CheckpointProbeBase):
             return BaseModelType.StableDiffusion1
         elif token_vector_length == 1024:
             return BaseModelType.StableDiffusion2
+        elif token_vector_length == 1280:
+            return BaseModelType.StableDiffusionXL  # recognizes format at https://civitai.com/models/224641
         elif token_vector_length == 2048:
             return BaseModelType.StableDiffusionXL
         else:

invokeai/backend/tiles/tiles.py

@@ -102,7 +102,7 @@ def calc_tiles_with_overlap(
 
 
 def calc_tiles_even_split(
-    image_height: int, image_width: int, num_tiles_x: int, num_tiles_y: int, overlap_fraction: float = 0
+    image_height: int, image_width: int, num_tiles_x: int, num_tiles_y: int, overlap: int = 0
 ) -> list[Tile]:
     """Calculate the tile coordinates for a given image shape with the number of tiles requested.
 
@@ -111,31 +111,35 @@ def calc_tiles_even_split(
         image_width (int): The image width in px.
         num_x_tiles (int): The number of tile to split the image into on the X-axis.
         num_y_tiles (int): The number of tile to split the image into on the Y-axis.
-        overlap_fraction (float, optional): The target overlap as fraction of the tiles size. Defaults to 0.
+        overlap (int, optional): The overlap between adjacent tiles in pixels. Defaults to 0.
 
     Returns:
         list[Tile]: A list of tiles that cover the image shape. Ordered from left-to-right, top-to-bottom.
     """
-
-    # Ensure tile size is divisible by 8
+    # Ensure the image is divisible by LATENT_SCALE_FACTOR
     if image_width % LATENT_SCALE_FACTOR != 0 or image_height % LATENT_SCALE_FACTOR != 0:
         raise ValueError(f"image size (({image_width}, {image_height})) must be divisible by {LATENT_SCALE_FACTOR}")
 
-    # Calculate the overlap size based on the percentage and adjust it to be divisible by 8 (rounding up)
-    overlap_x = LATENT_SCALE_FACTOR * math.ceil(
-        int((image_width / num_tiles_x) * overlap_fraction) / LATENT_SCALE_FACTOR
-    )
-    overlap_y = LATENT_SCALE_FACTOR * math.ceil(
-        int((image_height / num_tiles_y) * overlap_fraction) / LATENT_SCALE_FACTOR
-    )
-
     # Calculate the tile size based on the number of tiles and overlap, and ensure it's divisible by 8 (rounding down)
-    tile_size_x = LATENT_SCALE_FACTOR * math.floor(
-        ((image_width + overlap_x * (num_tiles_x - 1)) // num_tiles_x) / LATENT_SCALE_FACTOR
-    )
-    tile_size_y = LATENT_SCALE_FACTOR * math.floor(
-        ((image_height + overlap_y * (num_tiles_y - 1)) // num_tiles_y) / LATENT_SCALE_FACTOR
-    )
+    if num_tiles_x > 1:
+        # ensure the overlap is not more than the maximum overlap if we only have 1 tile then we dont care about overlap
+        assert overlap <= image_width - (LATENT_SCALE_FACTOR * (num_tiles_x - 1))
+        tile_size_x = LATENT_SCALE_FACTOR * math.floor(
+            ((image_width + overlap * (num_tiles_x - 1)) // num_tiles_x) / LATENT_SCALE_FACTOR
+        )
+        assert overlap < tile_size_x
+    else:
+        tile_size_x = image_width
+
+    if num_tiles_y > 1:
+        # ensure the overlap is not more than the maximum overlap if we only have 1 tile then we dont care about overlap
+        assert overlap <= image_height - (LATENT_SCALE_FACTOR * (num_tiles_y - 1))
+        tile_size_y = LATENT_SCALE_FACTOR * math.floor(
+            ((image_height + overlap * (num_tiles_y - 1)) // num_tiles_y) / LATENT_SCALE_FACTOR
+        )
+        assert overlap < tile_size_y
+    else:
+        tile_size_y = image_height
 
     # tiles[y * num_tiles_x + x] is the tile for the y'th row, x'th column.
     tiles: list[Tile] = []
@@ -143,7 +147,7 @@ def calc_tiles_even_split(
     # Calculate tile coordinates. (Ignore overlap values for now.)
     for tile_idx_y in range(num_tiles_y):
         # Calculate the top and bottom of the row
-        top = tile_idx_y * (tile_size_y - overlap_y)
+        top = tile_idx_y * (tile_size_y - overlap)
         bottom = min(top + tile_size_y, image_height)
         # For the last row adjust bottom to be the height of the image
         if tile_idx_y == num_tiles_y - 1:
@@ -151,7 +155,7 @@ def calc_tiles_even_split(
 
         for tile_idx_x in range(num_tiles_x):
             # Calculate the left & right coordinate of each tile
-            left = tile_idx_x * (tile_size_x - overlap_x)
+            left = tile_idx_x * (tile_size_x - overlap)
             right = min(left + tile_size_x, image_width)
             # For the last tile in the row adjust right to be the width of the image
             if tile_idx_x == num_tiles_x - 1:

invokeai/backend/util/devices.py

@@ -1,11 +1,9 @@
 from __future__ import annotations
 
-import platform
 from contextlib import nullcontext
 from typing import Union
 
 import torch
-from packaging import version
 from torch import autocast
 
 from invokeai.app.services.config import InvokeAIAppConfig
@@ -37,7 +35,7 @@ def choose_precision(device: torch.device) -> str:
         device_name = torch.cuda.get_device_name(device)
         if not ("GeForce GTX 1660" in device_name or "GeForce GTX 1650" in device_name):
             return "float16"
-    elif device.type == "mps" and version.parse(platform.mac_ver()[0]) < version.parse("14.0.0"):
+    elif device.type == "mps":
         return "float16"
     return "float32"
 

invokeai/frontend/install/invokeai_update.py

@@ -4,6 +4,7 @@ pip install <path_to_git_source>.
 """
 import os
 import platform
+from distutils.version import LooseVersion
 
 import pkg_resources
 import psutil
@@ -31,10 +32,6 @@ else:
     console = Console(style=Style(color="grey74", bgcolor="grey19"))
 
 
-def get_versions() -> dict:
-    return requests.get(url=INVOKE_AI_REL).json()
-
-
 def invokeai_is_running() -> bool:
     for p in psutil.process_iter():
         try:
@@ -50,6 +47,20 @@ def invokeai_is_running() -> bool:
     return False
 
 
+def get_pypi_versions():
+    url = "https://pypi.org/pypi/invokeai/json"
+    try:
+        data = requests.get(url).json()
+    except Exception:
+        raise Exception("Unable to fetch version information from PyPi")
+
+    versions = list(data["releases"].keys())
+    versions.sort(key=LooseVersion, reverse=True)
+    latest_version = [v for v in versions if "rc" not in v][0]
+    latest_release_candidate = [v for v in versions if "rc" in v][0]
+    return latest_version, latest_release_candidate, versions
+
+
 def welcome(latest_release: str, latest_prerelease: str):
     @group()
     def text():
@@ -63,8 +74,7 @@ def welcome(latest_release: str, latest_prerelease: str):
         yield "[bold yellow]Options:"
         yield f"""[1] Update to the latest [bold]official release[/bold] ([italic]{latest_release}[/italic])
 [2] Update to the latest [bold]pre-release[/bold] (may be buggy; caveat emptor!) ([italic]{latest_prerelease}[/italic])
-[3] Manually enter the [bold]tag name[/bold] for the version you wish to update to
-[4] Manually enter the [bold]branch name[/bold] for the version you wish to update to"""
+[3] Manually enter the [bold]version[/bold] you wish to update to"""
 
     console.rule()
     print(
@@ -92,44 +102,35 @@ def get_extras():
 
 
 def main():
-    versions = get_versions()
-    released_versions = [x for x in versions if not (x["draft"] or x["prerelease"])]
-    prerelease_versions = [x for x in versions if not x["draft"] and x["prerelease"]]
-    latest_release = released_versions[0]["tag_name"] if len(released_versions) else None
-    latest_prerelease = prerelease_versions[0]["tag_name"] if len(prerelease_versions) else None
-
     if invokeai_is_running():
         print(":exclamation: [bold red]Please terminate all running instances of InvokeAI before updating.[/red bold]")
         input("Press any key to continue...")
         return
 
+    latest_release, latest_prerelease, versions = get_pypi_versions()
+
     welcome(latest_release, latest_prerelease)
 
-    tag = None
-    branch = None
-    release = None
-    choice = Prompt.ask("Choice:", choices=["1", "2", "3", "4"], default="1")
+    release = latest_release
+    choice = Prompt.ask("Choice:", choices=["1", "2", "3"], default="1")
 
     if choice == "1":
         release = latest_release
     elif choice == "2":
         release = latest_prerelease
     elif choice == "3":
-        while not tag:
-            tag = Prompt.ask("Enter an InvokeAI tag name")
-    elif choice == "4":
-        while not branch:
-            branch = Prompt.ask("Enter an InvokeAI branch name")
+        while True:
+            release = Prompt.ask("Enter an InvokeAI version")
+            release.strip()
+            if release in versions:
+                break
+            print(f":exclamation: [bold red]'{release}' is not a recognized InvokeAI release.[/red bold]")
 
     extras = get_extras()
 
-    print(f":crossed_fingers: Upgrading to [yellow]{tag or release or branch}[/yellow]")
-    if release:
-        cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_SRC}/{release}.zip" --use-pep517 --upgrade'
-    elif tag:
-        cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_TAG}/{tag}.zip" --use-pep517 --upgrade'
-    else:
-        cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_BRANCH}/{branch}.zip" --use-pep517 --upgrade'
+    print(f":crossed_fingers: Upgrading to [yellow]{release}[/yellow]")
+    cmd = f'pip install "invokeai{extras}=={release}" --use-pep517 --upgrade'
+
     print("")
     print("")
     if os.system(cmd) == 0:

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

@@ -727,9 +727,6 @@
         "showMinimapnodes": "Mostrar el minimapa",
         "reloadNodeTemplates": "Recargar las plantillas de nodos",
         "loadWorkflow": "Cargar el flujo de trabajo",
-        "resetWorkflow": "Reiniciar e flujo de trabajo",
-        "resetWorkflowDesc": "¿Está seguro de que deseas restablecer este flujo de trabajo?",
-        "resetWorkflowDesc2": "Al reiniciar el flujo de trabajo se borrarán todos los nodos, aristas y detalles del flujo de trabajo.",
         "downloadWorkflow": "Descargar el flujo de trabajo en un archivo JSON"
     }
 }

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

@@ -898,11 +898,8 @@
         "zoomInNodes": "Ingrandire",
         "fitViewportNodes": "Adatta vista",
         "showGraphNodes": "Mostra sovrapposizione grafico",
-        "resetWorkflowDesc2": "Il ripristino dell'editor del flusso di lavoro cancellerà tutti i nodi, le connessioni e i dettagli del flusso di lavoro. I flussi di lavoro salvati non saranno interessati.",
         "reloadNodeTemplates": "Ricarica i modelli di nodo",
         "loadWorkflow": "Importa flusso di lavoro JSON",
-        "resetWorkflow": "Reimposta l'editor del flusso di lavoro",
-        "resetWorkflowDesc": "Sei sicuro di voler reimpostare l'editor del flusso di lavoro?",
         "downloadWorkflow": "Esporta flusso di lavoro JSON",
         "scheduler": "Campionatore",
         "addNode": "Aggiungi nodo",
@@ -1112,7 +1109,10 @@
         "deletedInvalidEdge": "Eliminata connessione non valida {{source}} -> {{target}}",
         "unknownInput": "Input sconosciuto: {{name}}",
         "prototypeDesc": "Questa invocazione è un prototipo. Potrebbe subire modifiche sostanziali durante gli aggiornamenti dell'app e potrebbe essere rimossa in qualsiasi momento.",
-        "betaDesc": "Questa invocazione è in versione beta. Fino a quando non sarà stabile, potrebbe subire modifiche importanti durante gli aggiornamenti dell'app. Abbiamo intenzione di supportare questa invocazione a lungo termine."
+        "betaDesc": "Questa invocazione è in versione beta. Fino a quando non sarà stabile, potrebbe subire modifiche importanti durante gli aggiornamenti dell'app. Abbiamo intenzione di supportare questa invocazione a lungo termine.",
+        "newWorkflow": "Nuovo flusso di lavoro",
+        "newWorkflowDesc": "Creare un nuovo flusso di lavoro?",
+        "newWorkflowDesc2": "Il flusso di lavoro attuale presenta modifiche non salvate."
     },
     "boards": {
         "autoAddBoard": "Aggiungi automaticamente bacheca",
@@ -1619,7 +1619,6 @@
         "saveWorkflow": "Salva flusso di lavoro",
         "openWorkflow": "Apri flusso di lavoro",
         "clearWorkflowSearchFilter": "Cancella il filtro di ricerca del flusso di lavoro",
-        "workflowEditorReset": "Reimpostazione dell'editor del flusso di lavoro",
         "workflowLibrary": "Libreria",
         "noRecentWorkflows": "Nessun flusso di lavoro recente",
         "workflowSaved": "Flusso di lavoro salvato",
@@ -1633,7 +1632,10 @@
         "deleteWorkflow": "Elimina flusso di lavoro",
         "workflows": "Flussi di lavoro",
         "noDescription": "Nessuna descrizione",
-        "userWorkflows": "I miei flussi di lavoro"
+        "userWorkflows": "I miei flussi di lavoro",
+        "newWorkflowCreated": "Nuovo flusso di lavoro creato",
+        "downloadWorkflow": "Salva su file",
+        "uploadWorkflow": "Carica da file"
     },
     "app": {
         "storeNotInitialized": "Il negozio non è inizializzato"

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

@@ -844,9 +844,6 @@
         "hideLegendNodes": "Typelegende veld verbergen",
         "reloadNodeTemplates": "Herlaad knooppuntsjablonen",
         "loadWorkflow": "Laad werkstroom",
-        "resetWorkflow": "Herstel werkstroom",
-        "resetWorkflowDesc": "Weet je zeker dat je deze werkstroom wilt herstellen?",
-        "resetWorkflowDesc2": "Herstel van een werkstroom haalt alle knooppunten, randen en werkstroomdetails weg.",
         "downloadWorkflow": "Download JSON van werkstroom",
         "booleanPolymorphicDescription": "Een verzameling Booleanse waarden.",
         "scheduler": "Planner",

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

@@ -909,9 +909,6 @@
         "hideLegendNodes": "Скрыть тип поля",
         "showMinimapnodes": "Показать миникарту",
         "loadWorkflow": "Загрузить рабочий процесс",
-        "resetWorkflowDesc2": "Сброс рабочего процесса очистит все узлы, ребра и детали рабочего процесса.",
-        "resetWorkflow": "Сбросить рабочий процесс",
-        "resetWorkflowDesc": "Вы уверены, что хотите сбросить этот рабочий процесс?",
         "reloadNodeTemplates": "Перезагрузить шаблоны узлов",
         "downloadWorkflow": "Скачать JSON рабочего процесса",
         "booleanPolymorphicDescription": "Коллекция логических значений.",
@@ -1599,7 +1596,6 @@
         "saveWorkflow": "Сохранить рабочий процесс",
         "openWorkflow": "Открытый рабочий процесс",
         "clearWorkflowSearchFilter": "Очистить фильтр поиска рабочих процессов",
-        "workflowEditorReset": "Сброс редактора рабочих процессов",
         "workflowLibrary": "Библиотека",
         "downloadWorkflow": "Скачать рабочий процесс",
         "noRecentWorkflows": "Нет недавних рабочих процессов",

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

@@ -892,11 +892,8 @@
     },
     "nodes": {
         "zoomInNodes": "放大",
-        "resetWorkflowDesc": "是否确定要重置工作流编辑器?",
-        "resetWorkflow": "重置工作流编辑器",
         "loadWorkflow": "加载工作流",
         "zoomOutNodes": "缩小",
-        "resetWorkflowDesc2": "重置工作流编辑器将清除所有节点、边际和节点图详情。不影响已保存的工作流。",
         "reloadNodeTemplates": "重载节点模板",
         "hideGraphNodes": "隐藏节点图信息",
         "fitViewportNodes": "自适应视图",
@@ -1122,7 +1119,10 @@
         "deletedInvalidEdge": "已删除无效的边缘 {{source}} -> {{target}}",
         "unknownInput": "未知输入：{{name}}",
         "prototypeDesc": "此调用是一个原型 (prototype)。它可能会在本项目更新期间发生破坏性更改，并且随时可能被删除。",
-        "betaDesc": "此调用尚处于测试阶段。在稳定之前，它可能会在项目更新期间发生破坏性更改。本项目计划长期支持这种调用。"
+        "betaDesc": "此调用尚处于测试阶段。在稳定之前，它可能会在项目更新期间发生破坏性更改。本项目计划长期支持这种调用。",
+        "newWorkflow": "新建工作流",
+        "newWorkflowDesc": "是否创建一个新的工作流？",
+        "newWorkflowDesc2": "当前工作流有未保存的更改。"
     },
     "controlnet": {
         "resize": "直接缩放",
@@ -1637,9 +1637,8 @@
         "saveWorkflow": "保存工作流",
         "openWorkflow": "打开工作流",
         "clearWorkflowSearchFilter": "清除工作流检索过滤器",
-        "workflowEditorReset": "工作流编辑器重置",
         "workflowLibrary": "工作流库",
-        "downloadWorkflow": "下载工作流",
+        "downloadWorkflow": "保存到文件",
         "noRecentWorkflows": "无最近工作流",
         "workflowSaved": "已保存工作流",
         "workflowIsOpen": "工作流已打开",
@@ -1652,8 +1651,9 @@
         "deleteWorkflow": "删除工作流",
         "workflows": "工作流",
         "noDescription": "无描述",
-        "uploadWorkflow": "上传工作流",
-        "userWorkflows": "我的工作流"
+        "uploadWorkflow": "从文件中加载",
+        "userWorkflows": "我的工作流",
+        "newWorkflowCreated": "已创建新的工作流"
     },
     "app": {
         "storeNotInitialized": "商店尚未初始化"

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

@@ -34,6 +34,7 @@ import { actionSanitizer } from './middleware/devtools/actionSanitizer';
 import { actionsDenylist } from './middleware/devtools/actionsDenylist';
 import { stateSanitizer } from './middleware/devtools/stateSanitizer';
 import { listenerMiddleware } from './middleware/listenerMiddleware';
+import { authToastMiddleware } from 'services/api/authToastMiddleware';
 
 const allReducers = {
   canvas: canvasReducer,
@@ -96,6 +97,7 @@ export const createStore = (uniqueStoreKey?: string, persist = true) =>
       })
         .concat(api.middleware)
         .concat(dynamicMiddlewares)
+        .concat(authToastMiddleware)
         .prepend(listenerMiddleware.middleware),
     enhancers: (getDefaultEnhancers) => {
       const _enhancers = getDefaultEnhancers().concat(autoBatchEnhancer());

invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/WorkflowName.tsx

@@ -2,11 +2,14 @@ import { Text } from '@chakra-ui/layout';
 import { useAppSelector } from 'app/store/storeHooks';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
+import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
 
 const TopCenterPanel = () => {
   const { t } = useTranslation();
   const name = useAppSelector((state) => state.workflow.name);
   const isTouched = useAppSelector((state) => state.workflow.isTouched);
+  const isWorkflowLibraryEnabled =
+    useFeatureStatus('workflowLibrary').isFeatureEnabled;
 
   return (
     <Text
@@ -19,7 +22,7 @@ const TopCenterPanel = () => {
       opacity={0.8}
     >
       {name || t('workflows.unnamedWorkflow')}
-      {isTouched ? ` (${t('common.unsaved')})` : ''}
+      {isTouched && isWorkflowLibraryEnabled ? ` (${t('common.unsaved')})` : ''}
     </Text>
   );
 };

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasImageToImageGraph.ts

@@ -144,6 +144,7 @@ export const buildCanvasImageToImageGraph = (
         type: 'l2i',
         id: CANVAS_OUTPUT,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [
@@ -255,6 +256,7 @@ export const buildCanvasImageToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -295,6 +297,7 @@ export const buildCanvasImageToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     (graph.nodes[IMAGE_TO_LATENTS] as ImageToLatentsInvocation).image =

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasInpaintGraph.ts

@@ -191,6 +191,7 @@ export const buildCanvasInpaintGraph = (
         id: CANVAS_OUTPUT,
         is_intermediate,
         reference: canvasInitImage,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasOutpaintGraph.ts

@@ -199,6 +199,7 @@ export const buildCanvasOutpaintGraph = (
         type: 'color_correct',
         id: CANVAS_OUTPUT,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLImageToImageGraph.ts

@@ -266,6 +266,7 @@ export const buildCanvasSDXLImageToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -306,6 +307,7 @@ export const buildCanvasSDXLImageToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     (graph.nodes[IMAGE_TO_LATENTS] as ImageToLatentsInvocation).image =

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLInpaintGraph.ts

@@ -196,6 +196,7 @@ export const buildCanvasSDXLInpaintGraph = (
         id: CANVAS_OUTPUT,
         is_intermediate,
         reference: canvasInitImage,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLOutpaintGraph.ts

@@ -204,6 +204,7 @@ export const buildCanvasSDXLOutpaintGraph = (
         type: 'color_correct',
         id: CANVAS_OUTPUT,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasSDXLTextToImageGraph.ts

@@ -258,6 +258,7 @@ export const buildCanvasSDXLTextToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -288,6 +289,7 @@ export const buildCanvasSDXLTextToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     graph.edges.push({

invokeai/frontend/web/src/features/nodes/util/graph/buildCanvasTextToImageGraph.ts

@@ -246,6 +246,7 @@ export const buildCanvasTextToImageGraph = (
       is_intermediate,
       width: width,
       height: height,
+      use_cache: false,
     };
 
     graph.edges.push(
@@ -276,6 +277,7 @@ export const buildCanvasTextToImageGraph = (
       id: CANVAS_OUTPUT,
       is_intermediate,
       fp32,
+      use_cache: false,
     };
 
     graph.edges.push({

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearImageToImageGraph.ts

@@ -143,6 +143,7 @@ export const buildLinearImageToImageGraph = (
         // },
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLImageToImageGraph.ts

@@ -154,6 +154,7 @@ export const buildLinearSDXLImageToImageGraph = (
         // },
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearSDXLTextToImageGraph.ts

@@ -127,6 +127,7 @@ export const buildLinearSDXLTextToImageGraph = (
         id: LATENTS_TO_IMAGE,
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearTextToImageGraph.ts

@@ -146,6 +146,7 @@ export const buildLinearTextToImageGraph = (
         id: LATENTS_TO_IMAGE,
         fp32,
         is_intermediate,
+        use_cache: false,
       },
     },
     edges: [

invokeai/frontend/web/src/services/api/authToastMiddleware.ts

@@ -5,12 +5,10 @@ import { t } from 'i18next';
 import { z } from 'zod';
 
 const zRejectedForbiddenAction = z.object({
-  action: z.object({
-    payload: z.object({
-      status: z.literal(403),
-      data: z.object({
-        detail: z.string(),
-      }),
+  payload: z.object({
+    status: z.literal(403),
+    data: z.object({
+      detail: z.string(),
     }),
   }),
 });
@@ -22,8 +20,8 @@ export const authToastMiddleware: Middleware =
         const parsed = zRejectedForbiddenAction.parse(action);
         const { dispatch } = api;
         const customMessage =
-          parsed.action.payload.data.detail !== 'Forbidden'
-            ? parsed.action.payload.data.detail
+          parsed.payload.data.detail !== 'Forbidden'
+            ? parsed.payload.data.detail
             : undefined;
         dispatch(
           addToast({
@@ -32,7 +30,7 @@ export const authToastMiddleware: Middleware =
             description: customMessage,
           })
         );
-      } catch {
+      } catch (error) {
         // no-op
       }
     }

invokeai/version/invokeai_version.py

@@ -1 +1 @@
-__version__ = "3.4.0post2"
+__version__ = "3.5.0dev1"

mkdocs.yml

@@ -172,6 +172,8 @@ nav:
         - Adding Tests: 'contributing/TESTS.md'
       - Documentation: 'contributing/contribution_guides/documentation.md'
       - Nodes: 'contributing/INVOCATIONS.md'
+      - Model Manager: 'contributing/MODEL_MANAGER.md'
+      - Download Queue: 'contributing/DOWNLOAD_QUEUE.md'
       - Translation: 'contributing/contribution_guides/translation.md'
       - Tutorials: 'contributing/contribution_guides/tutorials.md'
     - Changelog: 'CHANGELOG.md'

pyproject.toml

@@ -105,6 +105,7 @@ dependencies = [
   "pytest>6.0.0",
   "pytest-cov",
   "pytest-datadir",
+  "requests_testadapter",
 ]
 "xformers" = [
   "xformers==0.0.23; sys_platform!='darwin'",
@@ -138,7 +139,6 @@ dependencies = [
 "invokeai-node-web" = "invokeai.app.api_app:invoke_api"
 "invokeai-import-images" = "invokeai.frontend.install.import_images:main"
 "invokeai-db-maintenance" = "invokeai.backend.util.db_maintenance:main"
-"invokeai-migrate-models-to-db" = "invokeai.backend.model_manager.migrate_to_db:main"
 
 [project.urls]
 "Homepage" = "https://invoke-ai.github.io/InvokeAI/"

tests/aa_nodes/test_graph_execution_state.py

@@ -26,7 +26,6 @@ from invokeai.app.services.shared.graph import (
     Graph,
     GraphExecutionState,
     IterateInvocation,
-    LibraryGraph,
 )
 from invokeai.backend.util.logging import InvokeAILogger
 from tests.fixtures.sqlite_database import create_mock_sqlite_database
@@ -61,7 +60,6 @@ def mock_services() -> InvocationServices:
         configuration=configuration,
         events=TestEventService(),
         graph_execution_manager=graph_execution_manager,
-        graph_library=SqliteItemStorage[LibraryGraph](db=db, table_name="graphs"),
         image_files=None,  # type: ignore
         image_records=None,  # type: ignore
         images=None,  # type: ignore
@@ -70,6 +68,7 @@ def mock_services() -> InvocationServices:
         logger=logging,  # type: ignore
         model_manager=None,  # type: ignore
         model_records=None,  # type: ignore
+        download_queue=None,  # type: ignore
         model_install=None,  # type: ignore
         names=None,  # type: ignore
         performance_statistics=InvocationStatsService(),

tests/aa_nodes/test_invoker.py

@@ -24,7 +24,7 @@ from invokeai.app.services.invocation_stats.invocation_stats_default import Invo
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.item_storage.item_storage_sqlite import SqliteItemStorage
 from invokeai.app.services.session_queue.session_queue_common import DEFAULT_QUEUE_ID
-from invokeai.app.services.shared.graph import Graph, GraphExecutionState, GraphInvocation, LibraryGraph
+from invokeai.app.services.shared.graph import Graph, GraphExecutionState, GraphInvocation
 
 
 @pytest.fixture
@@ -66,7 +66,6 @@ def mock_services() -> InvocationServices:
         configuration=configuration,
         events=TestEventService(),
         graph_execution_manager=graph_execution_manager,
-        graph_library=SqliteItemStorage[LibraryGraph](db=db, table_name="graphs"),
         image_files=None,  # type: ignore
         image_records=None,  # type: ignore
         images=None,  # type: ignore
@@ -75,6 +74,7 @@ def mock_services() -> InvocationServices:
         logger=logging,  # type: ignore
         model_manager=None,  # type: ignore
         model_records=None,  # type: ignore
+        download_queue=None,  # type: ignore
         model_install=None,  # type: ignore
         names=None,  # type: ignore
         performance_statistics=InvocationStatsService(),

tests/app/services/download/test_download_queue.py

@@ -0,0 +1,223 @@
+"""Test the queued download facility"""
+import re
+import time
+from pathlib import Path
+from typing import Any, Dict, List
+
+import pytest
+import requests
+from pydantic import BaseModel
+from pydantic.networks import AnyHttpUrl
+from requests.sessions import Session
+from requests_testadapter import TestAdapter
+
+from invokeai.app.services.download import DownloadJob, DownloadJobStatus, DownloadQueueService
+from invokeai.app.services.events.events_base import EventServiceBase
+
+# Prevent pytest deprecation warnings
+TestAdapter.__test__ = False
+
+
+@pytest.fixture
+def session() -> requests.sessions.Session:
+    sess = requests.Session()
+    for i in ["12345", "9999", "54321"]:
+        content = (
+            b"I am a safetensors file " + bytearray(i, "utf-8") + bytearray(32_000)
+        )  # for pause tests, must make content large
+        sess.mount(
+            f"http://www.civitai.com/models/{i}",
+            TestAdapter(
+                content,
+                headers={
+                    "Content-Length": len(content),
+                    "Content-Disposition": f'filename="mock{i}.safetensors"',
+                },
+            ),
+        )
+
+    # here are some malformed URLs to test
+    # missing the content length
+    sess.mount(
+        "http://www.civitai.com/models/missing",
+        TestAdapter(
+            b"Missing content length",
+            headers={
+                "Content-Disposition": 'filename="missing.txt"',
+            },
+        ),
+    )
+    # not found test
+    sess.mount("http://www.civitai.com/models/broken", TestAdapter(b"Not found", status=404))
+
+    return sess
+
+
+class DummyEvent(BaseModel):
+    """Dummy Event to use with Dummy Event service."""
+
+    event_name: str
+    payload: Dict[str, Any]
+
+
+# A dummy event service for testing event issuing
+class DummyEventService(EventServiceBase):
+    """Dummy event service for testing."""
+
+    events: List[DummyEvent]
+
+    def __init__(self) -> None:
+        super().__init__()
+        self.events = []
+
+    def dispatch(self, event_name: str, payload: Any) -> None:
+        """Dispatch an event by appending it to self.events."""
+        self.events.append(DummyEvent(event_name=payload["event"], payload=payload["data"]))
+
+
+def test_basic_queue_download(tmp_path: Path, session: Session) -> None:
+    events = set()
+
+    def event_handler(job: DownloadJob) -> None:
+        events.add(job.status)
+
+    queue = DownloadQueueService(
+        requests_session=session,
+    )
+    queue.start()
+    job = queue.download(
+        source=AnyHttpUrl("http://www.civitai.com/models/12345"),
+        dest=tmp_path,
+        on_start=event_handler,
+        on_progress=event_handler,
+        on_complete=event_handler,
+        on_error=event_handler,
+    )
+    assert isinstance(job, DownloadJob), "expected the job to be of type DownloadJobBase"
+    assert isinstance(job.id, int), "expected the job id to be numeric"
+    queue.join()
+
+    assert job.status == DownloadJobStatus("completed"), "expected job status to be completed"
+    assert Path(tmp_path, "mock12345.safetensors").exists(), f"expected {tmp_path}/mock12345.safetensors to exist"
+
+    assert events == {DownloadJobStatus.RUNNING, DownloadJobStatus.COMPLETED}
+    queue.stop()
+
+
+def test_errors(tmp_path: Path, session: Session) -> None:
+    queue = DownloadQueueService(
+        requests_session=session,
+    )
+    queue.start()
+
+    for bad_url in ["http://www.civitai.com/models/broken", "http://www.civitai.com/models/missing"]:
+        queue.download(AnyHttpUrl(bad_url), dest=tmp_path)
+
+    queue.join()
+    jobs = queue.list_jobs()
+    print(jobs)
+    assert len(jobs) == 2
+    jobs_dict = {str(x.source): x for x in jobs}
+    assert jobs_dict["http://www.civitai.com/models/broken"].status == DownloadJobStatus.ERROR
+    assert jobs_dict["http://www.civitai.com/models/broken"].error_type == "HTTPError(NOT FOUND)"
+    assert jobs_dict["http://www.civitai.com/models/missing"].status == DownloadJobStatus.COMPLETED
+    assert jobs_dict["http://www.civitai.com/models/missing"].total_bytes == 0
+    queue.stop()
+
+
+def test_event_bus(tmp_path: Path, session: Session) -> None:
+    event_bus = DummyEventService()
+
+    queue = DownloadQueueService(requests_session=session, event_bus=event_bus)
+    queue.start()
+    queue.download(
+        source=AnyHttpUrl("http://www.civitai.com/models/12345"),
+        dest=tmp_path,
+    )
+    queue.join()
+    events = event_bus.events
+    assert len(events) == 3
+    assert events[0].payload["timestamp"] <= events[1].payload["timestamp"]
+    assert events[1].payload["timestamp"] <= events[2].payload["timestamp"]
+    assert events[0].event_name == "download_started"
+    assert events[1].event_name == "download_progress"
+    assert events[1].payload["total_bytes"] > 0
+    assert events[1].payload["current_bytes"] <= events[1].payload["total_bytes"]
+    assert events[2].event_name == "download_complete"
+    assert events[2].payload["total_bytes"] == 32029
+
+    # test a failure
+    event_bus.events = []  # reset our accumulator
+    queue.download(source=AnyHttpUrl("http://www.civitai.com/models/broken"), dest=tmp_path)
+    queue.join()
+    events = event_bus.events
+    print("\n".join([x.model_dump_json() for x in events]))
+    assert len(events) == 1
+    assert events[0].event_name == "download_error"
+    assert events[0].payload["error_type"] == "HTTPError(NOT FOUND)"
+    assert events[0].payload["error"] is not None
+    assert re.search(r"requests.exceptions.HTTPError: NOT FOUND", events[0].payload["error"])
+    queue.stop()
+
+
+def test_broken_callbacks(tmp_path: Path, session: requests.sessions.Session, capsys) -> None:
+    queue = DownloadQueueService(
+        requests_session=session,
+    )
+    queue.start()
+
+    callback_ran = False
+
+    def broken_callback(job: DownloadJob) -> None:
+        nonlocal callback_ran
+        callback_ran = True
+        print(1 / 0)  # deliberate error here
+
+    job = queue.download(
+        source=AnyHttpUrl("http://www.civitai.com/models/12345"),
+        dest=tmp_path,
+        on_progress=broken_callback,
+    )
+
+    queue.join()
+    assert job.status == DownloadJobStatus.COMPLETED  # should complete even though the callback is borked
+    assert Path(tmp_path, "mock12345.safetensors").exists()
+    assert callback_ran
+    # LS: The pytest capsys fixture does not seem to be working. I can see the
+    # correct stderr message in the pytest log, but it is not appearing in
+    # capsys.readouterr().
+    # captured = capsys.readouterr()
+    # assert re.search("division by zero", captured.err)
+    queue.stop()
+
+
+def test_cancel(tmp_path: Path, session: requests.sessions.Session) -> None:
+    event_bus = DummyEventService()
+
+    queue = DownloadQueueService(requests_session=session, event_bus=event_bus)
+    queue.start()
+
+    cancelled = False
+
+    def slow_callback(job: DownloadJob) -> None:
+        time.sleep(2)
+
+    def cancelled_callback(job: DownloadJob) -> None:
+        nonlocal cancelled
+        cancelled = True
+
+    job = queue.download(
+        source=AnyHttpUrl("http://www.civitai.com/models/12345"),
+        dest=tmp_path,
+        on_start=slow_callback,
+        on_cancelled=cancelled_callback,
+    )
+    queue.cancel_job(job)
+    queue.join()
+
+    assert job.status == DownloadJobStatus.CANCELLED
+    assert cancelled
+    events = event_bus.events
+    assert events[-1].event_name == "download_cancelled"
+    assert events[-1].payload["source"] == "http://www.civitai.com/models/12345"
+    queue.stop()

tests/app/services/model_install/test_model_install.py

@@ -48,11 +48,13 @@ def store(
 
 @pytest.fixture
 def installer(app_config: InvokeAIAppConfig, store: ModelRecordServiceBase) -> ModelInstallServiceBase:
-    return ModelInstallService(
+    installer = ModelInstallService(
         app_config=app_config,
         record_store=store,
         event_bus=DummyEventService(),
     )
+    installer.start()
+    return installer
 
 
 class DummyEvent(BaseModel):

tests/backend/tiles/test_tiles.py

@@ -305,9 +305,7 @@ def test_calc_tiles_min_overlap_input_validation(
 
 def test_calc_tiles_even_split_single_tile():
     """Test calc_tiles_even_split() behavior when a single tile covers the image."""
-    tiles = calc_tiles_even_split(
-        image_height=512, image_width=1024, num_tiles_x=1, num_tiles_y=1, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=512, image_width=1024, num_tiles_x=1, num_tiles_y=1, overlap=64)
 
     expected_tiles = [
         Tile(
@@ -322,36 +320,34 @@ def test_calc_tiles_even_split_single_tile():
 def test_calc_tiles_even_split_evenly_divisible():
     """Test calc_tiles_even_split() behavior when the image is evenly covered by multiple tiles."""
     # Parameters mimic roughly the same output as the original tile generations of the same test name
-    tiles = calc_tiles_even_split(
-        image_height=576, image_width=1600, num_tiles_x=3, num_tiles_y=2, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=576, image_width=1600, num_tiles_x=3, num_tiles_y=2, overlap=64)
 
     expected_tiles = [
         # Row 0
         Tile(
-            coords=TBLR(top=0, bottom=320, left=0, right=624),
-            overlap=TBLR(top=0, bottom=72, left=0, right=136),
+            coords=TBLR(top=0, bottom=320, left=0, right=576),
+            overlap=TBLR(top=0, bottom=64, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=320, left=488, right=1112),
-            overlap=TBLR(top=0, bottom=72, left=136, right=136),
+            coords=TBLR(top=0, bottom=320, left=512, right=1088),
+            overlap=TBLR(top=0, bottom=64, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=320, left=976, right=1600),
-            overlap=TBLR(top=0, bottom=72, left=136, right=0),
+            coords=TBLR(top=0, bottom=320, left=1024, right=1600),
+            overlap=TBLR(top=0, bottom=64, left=64, right=0),
         ),
         # Row 1
         Tile(
-            coords=TBLR(top=248, bottom=576, left=0, right=624),
-            overlap=TBLR(top=72, bottom=0, left=0, right=136),
+            coords=TBLR(top=256, bottom=576, left=0, right=576),
+            overlap=TBLR(top=64, bottom=0, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=248, bottom=576, left=488, right=1112),
-            overlap=TBLR(top=72, bottom=0, left=136, right=136),
+            coords=TBLR(top=256, bottom=576, left=512, right=1088),
+            overlap=TBLR(top=64, bottom=0, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=248, bottom=576, left=976, right=1600),
-            overlap=TBLR(top=72, bottom=0, left=136, right=0),
+            coords=TBLR(top=256, bottom=576, left=1024, right=1600),
+            overlap=TBLR(top=64, bottom=0, left=64, right=0),
         ),
     ]
     assert tiles == expected_tiles
@@ -360,36 +356,34 @@ def test_calc_tiles_even_split_evenly_divisible():
 def test_calc_tiles_even_split_not_evenly_divisible():
     """Test calc_tiles_even_split() behavior when the image requires 'uneven' overlaps to achieve proper coverage."""
     # Parameters mimic roughly the same output as the original tile generations of the same test name
-    tiles = calc_tiles_even_split(
-        image_height=400, image_width=1200, num_tiles_x=3, num_tiles_y=2, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=400, image_width=1200, num_tiles_x=3, num_tiles_y=2, overlap=64)
 
     expected_tiles = [
         # Row 0
         Tile(
-            coords=TBLR(top=0, bottom=224, left=0, right=464),
-            overlap=TBLR(top=0, bottom=56, left=0, right=104),
+            coords=TBLR(top=0, bottom=232, left=0, right=440),
+            overlap=TBLR(top=0, bottom=64, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=224, left=360, right=824),
-            overlap=TBLR(top=0, bottom=56, left=104, right=104),
+            coords=TBLR(top=0, bottom=232, left=376, right=816),
+            overlap=TBLR(top=0, bottom=64, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=224, left=720, right=1200),
-            overlap=TBLR(top=0, bottom=56, left=104, right=0),
+            coords=TBLR(top=0, bottom=232, left=752, right=1200),
+            overlap=TBLR(top=0, bottom=64, left=64, right=0),
         ),
         # Row 1
         Tile(
-            coords=TBLR(top=168, bottom=400, left=0, right=464),
-            overlap=TBLR(top=56, bottom=0, left=0, right=104),
+            coords=TBLR(top=168, bottom=400, left=0, right=440),
+            overlap=TBLR(top=64, bottom=0, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=168, bottom=400, left=360, right=824),
-            overlap=TBLR(top=56, bottom=0, left=104, right=104),
+            coords=TBLR(top=168, bottom=400, left=376, right=816),
+            overlap=TBLR(top=64, bottom=0, left=64, right=64),
         ),
         Tile(
-            coords=TBLR(top=168, bottom=400, left=720, right=1200),
-            overlap=TBLR(top=56, bottom=0, left=104, right=0),
+            coords=TBLR(top=168, bottom=400, left=752, right=1200),
+            overlap=TBLR(top=64, bottom=0, left=64, right=0),
         ),
     ]
 
@@ -399,28 +393,26 @@ def test_calc_tiles_even_split_not_evenly_divisible():
 def test_calc_tiles_even_split_difficult_size():
     """Test calc_tiles_even_split() behavior when the image is a difficult size to spilt evenly and keep div8."""
     # Parameters are a difficult size for other tile gen routines to calculate
-    tiles = calc_tiles_even_split(
-        image_height=1000, image_width=1000, num_tiles_x=2, num_tiles_y=2, overlap_fraction=0.25
-    )
+    tiles = calc_tiles_even_split(image_height=1000, image_width=1000, num_tiles_x=2, num_tiles_y=2, overlap=64)
 
     expected_tiles = [
         # Row 0
         Tile(
-            coords=TBLR(top=0, bottom=560, left=0, right=560),
-            overlap=TBLR(top=0, bottom=128, left=0, right=128),
+            coords=TBLR(top=0, bottom=528, left=0, right=528),
+            overlap=TBLR(top=0, bottom=64, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=0, bottom=560, left=432, right=1000),
-            overlap=TBLR(top=0, bottom=128, left=128, right=0),
+            coords=TBLR(top=0, bottom=528, left=464, right=1000),
+            overlap=TBLR(top=0, bottom=64, left=64, right=0),
         ),
         # Row 1
         Tile(
-            coords=TBLR(top=432, bottom=1000, left=0, right=560),
-            overlap=TBLR(top=128, bottom=0, left=0, right=128),
+            coords=TBLR(top=464, bottom=1000, left=0, right=528),
+            overlap=TBLR(top=64, bottom=0, left=0, right=64),
         ),
         Tile(
-            coords=TBLR(top=432, bottom=1000, left=432, right=1000),
-            overlap=TBLR(top=128, bottom=0, left=128, right=0),
+            coords=TBLR(top=464, bottom=1000, left=464, right=1000),
+            overlap=TBLR(top=64, bottom=0, left=64, right=0),
         ),
     ]
 
@@ -428,11 +420,13 @@ def test_calc_tiles_even_split_difficult_size():
 
 
 @pytest.mark.parametrize(
-    ["image_height", "image_width", "num_tiles_x", "num_tiles_y", "overlap_fraction", "raises"],
+    ["image_height", "image_width", "num_tiles_x", "num_tiles_y", "overlap", "raises"],
     [
-        (128, 128, 1, 1, 0.25, False),  # OK
+        (128, 128, 1, 1, 127, False),  # OK
         (128, 128, 1, 1, 0, False),  # OK
-        (128, 128, 2, 1, 0, False),  # OK
+        (128, 128, 2, 2, 0, False),  # OK
+        (128, 128, 2, 1, 120, True),  # overlap equals tile_height.
+        (128, 128, 1, 2, 120, True),  # overlap equals tile_width.
         (127, 127, 1, 1, 0, True),  # image size must be dividable by 8
     ],
 )
@@ -441,15 +435,15 @@ def test_calc_tiles_even_split_input_validation(
     image_width: int,
     num_tiles_x: int,
     num_tiles_y: int,
-    overlap_fraction: float,
+    overlap: int,
     raises: bool,
 ):
     """Test that calc_tiles_even_split() raises an exception if the inputs are invalid."""
     if raises:
-        with pytest.raises(ValueError):
-            calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap_fraction)
+        with pytest.raises((AssertionError, ValueError)):
+            calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap)
     else:
-        calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap_fraction)
+        calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap)
 
 
 #############################################