chore: bump version

.dev_scripts/diff_images.py

@@ -20,13 +20,13 @@ def calc_images_mean_L1(image1_path, image2_path):
 
 def parse_args():
     parser = argparse.ArgumentParser()
-    parser.add_argument("image1_path")
-    parser.add_argument("image2_path")
+    parser.add_argument('image1_path')
+    parser.add_argument('image2_path')
     args = parser.parse_args()
     return args
 
 
-if __name__ == "__main__":
+if __name__ == '__main__':
     args = parse_args()
     mean_L1 = calc_images_mean_L1(args.image1_path, args.image2_path)
     print(mean_L1)

.dockerignore

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

.git-blame-ignore-revs

@@ -1,2 +1 @@
 b3dccfaeb636599c02effc377cdd8a87d658256c
-218b6d0546b990fc449c876fb99f44b50c4daa35

.gitattributes

@@ -2,4 +2,3 @@
 # Only affects text files and ignores other file types.
 # For more info see: https://www.aleksandrhovhannisyan.com/blog/crlf-vs-lf-normalizing-line-endings-in-git/
 * text=auto
-docker/** text eol=lf

.github/CODEOWNERS

@@ -1,32 +1,34 @@
 # continuous integration
-/.github/workflows/  @lstein @blessedcoolant @hipsterusername @ebr
+/.github/workflows/  @lstein @blessedcoolant
 
 # documentation
-/docs/ @lstein @blessedcoolant @hipsterusername @Millu
-/mkdocs.yml @lstein  @blessedcoolant @hipsterusername @Millu
+/docs/ @lstein @blessedcoolant @hipsterusername
+/mkdocs.yml @lstein  @blessedcoolant
 
 # nodes
-/invokeai/app/ @Kyle0654 @blessedcoolant @psychedelicious @brandonrising @hipsterusername
+/invokeai/app/ @Kyle0654 @blessedcoolant
 
 # installation and configuration
-/pyproject.toml  @lstein @blessedcoolant @hipsterusername
-/docker/  @lstein @blessedcoolant @hipsterusername @ebr
-/scripts/ @ebr @lstein @hipsterusername
-/installer/ @lstein @ebr @hipsterusername
-/invokeai/assets @lstein @ebr @hipsterusername
-/invokeai/configs @lstein @hipsterusername
-/invokeai/version @lstein @blessedcoolant @hipsterusername
+/pyproject.toml  @lstein @blessedcoolant
+/docker/  @lstein @blessedcoolant
+/scripts/ @ebr @lstein
+/installer/ @lstein @ebr
+/invokeai/assets @lstein @ebr
+/invokeai/configs @lstein
+/invokeai/version @lstein @blessedcoolant
 
 # web ui
-/invokeai/frontend @blessedcoolant @psychedelicious @lstein @maryhipp @hipsterusername
-/invokeai/backend @blessedcoolant @psychedelicious @lstein @maryhipp @hipsterusername
+/invokeai/frontend @blessedcoolant @psychedelicious @lstein @maryhipp
+/invokeai/backend @blessedcoolant @psychedelicious @lstein @maryhipp
 
 # generation, model management, postprocessing
-/invokeai/backend  @damian0815 @lstein @blessedcoolant @gregghelt2 @StAlKeR7779 @brandonrising @ryanjdick @hipsterusername
+/invokeai/backend  @damian0815 @lstein @blessedcoolant @jpphoto @gregghelt2 @StAlKeR7779
 
 # front ends
-/invokeai/frontend/CLI @lstein @hipsterusername
-/invokeai/frontend/install @lstein @ebr @hipsterusername
-/invokeai/frontend/merge @lstein @blessedcoolant @hipsterusername
-/invokeai/frontend/training @lstein @blessedcoolant @hipsterusername
-/invokeai/frontend/web @psychedelicious @blessedcoolant @maryhipp @hipsterusername
+/invokeai/frontend/CLI @lstein
+/invokeai/frontend/install @lstein @ebr  
+/invokeai/frontend/merge @lstein @blessedcoolant 
+/invokeai/frontend/training @lstein @blessedcoolant 
+/invokeai/frontend/web @psychedelicious @blessedcoolant @maryhipp 
+
+

.github/ISSUE_TEMPLATE/BUG_REPORT.yml

@@ -6,6 +6,10 @@ title: '[bug]: '
 
 labels: ['bug']
 
+# assignees:
+#   - moderator_bot
+#   - lstein
+
 body:
   - type: markdown
     attributes:
@@ -14,9 +18,10 @@ body:
 
   - type: checkboxes
     attributes:
-      label: Is there an existing issue for this problem?
+      label: Is there an existing issue for this?
       description: |
-        Please [search](https://github.com/invoke-ai/InvokeAI/issues) first to see if an issue already exists for the problem.
+        Please use the [search function](https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen+label%3Abug)
+        irst to see if an issue already exists for the bug you encountered.
       options:
         - label: I have searched the existing issues
           required: true
@@ -28,119 +33,80 @@ body:
   - type: dropdown
     id: os_dropdown
     attributes:
-      label: Operating system
-      description: Your computer's operating system.
+      label: OS
+      description: Which operating System did you use when the bug occured
       multiple: false
       options:
         - 'Linux'
         - 'Windows'
         - 'macOS'
-        - 'other'
     validations:
       required: true
 
   - type: dropdown
     id: gpu_dropdown
     attributes:
-      label: GPU vendor
-      description: Your GPU's vendor.
+      label: GPU
+      description: Which kind of Graphic-Adapter is your System using
       multiple: false
       options:
-        - 'Nvidia (CUDA)'
-        - 'AMD (ROCm)'
-        - 'Apple Silicon (MPS)'
-        - 'None (CPU)'
+        - 'cuda'
+        - 'amd'
+        - 'mps'
+        - 'cpu'
     validations:
       required: true
 
-  - type: input
-    id: gpu_model
-    attributes:
-      label: GPU model
-      description: Your GPU's model. If on Apple Silicon, this is your Mac's chip. Leave blank if on CPU.
-      placeholder: ex. RTX 2080 Ti, Mac M1 Pro
-    validations:
-      required: false
-
   - type: input
     id: vram
     attributes:
-      label: GPU VRAM
-      description: Your GPU's VRAM. If on Apple Silicon, this is your Mac's unified memory. Leave blank if on CPU.
+      label: VRAM
+      description: Size of the VRAM if known
       placeholder: 8GB
     validations:
       required: false
-
+      
   - type: input
     id: version-number
     attributes:
-      label: Version number
+      label: What version did you experience this issue on?
       description: |
-        The version of Invoke you have installed. If it is not the latest version, please update and try again to confirm the issue still exists. If you are testing main, please include the commit hash instead.
-      placeholder: ex. 3.6.1
+        Please share the version of Invoke AI that you experienced the issue on. If this is not the latest version, please update first to confirm the issue still exists. If you are testing main, please include the commit hash instead.
+      placeholder: X.X.X
     validations:
       required: true
 
-  - type: input
-    id: browser-version
-    attributes:
-      label: Browser
-      description: Your web browser and version.
-      placeholder: ex. Firefox 123.0b3
-    validations:
-      required: true
-
-  - type: textarea
-    id: python-deps
-    attributes:
-      label: Python dependencies
-      description: |
-        If the problem occurred during image generation, click the gear icon at the bottom left corner, click "About", click the copy button and then paste here.
-    validations:
-      required: false
-
   - type: textarea
     id: what-happened
     attributes:
-      label: What happened
+      label: What happened?
       description: |
-        Describe what happened. Include any relevant error messages, stack traces and screenshots here.
-      placeholder: I clicked button X and then Y happened.
+        Briefly describe what happened, what you expected to happen and how to reproduce this bug.
+      placeholder: When using the webinterface and right-clicking on button X instead of the popup-menu there error Y appears
     validations:
       required: true
 
   - type: textarea
-    id: what-you-expected
     attributes:
-      label: What you expected to happen
-      description: Describe what you expected to happen.
-      placeholder: I expected Z to happen.
-    validations:
-      required: true
-
-  - type: textarea
-    id: how-to-repro
-    attributes:
-      label: How to reproduce the problem
-      description: List steps to reproduce the problem.
-      placeholder: Start the app, generate an image with these settings, then click button X.
+      label: Screenshots
+      description: If applicable, add screenshots to help explain your problem
+      placeholder: this is what the result looked like <screenshot>
     validations:
       required: false
 
   - type: textarea
-    id: additional-context
     attributes:
       label: Additional context
-      description: Any other context that might help us to understand the problem.
+      description: Add any other context about the problem here
       placeholder: Only happens when there is full moon and Friday the 13th on Christmas Eve 🎅🏻
     validations:
       required: false
 
   - type: input
-    id: discord-username
+    id: contact
     attributes:
-      label: Discord username
-      description: If you are on the Invoke discord and would prefer to be contacted there, please provide your username.
-      placeholder: supercoolusername123
+      label: Contact Details
+      description: __OPTIONAL__ How can we get in touch with you if we need more info (besides this issue)?
+      placeholder: ex. email@example.com, discordname, twitter, ...
     validations:
       required: false

.github/ISSUE_TEMPLATE/FEATURE_REQUEST.yml

@@ -1,5 +1,5 @@
 name: Feature Request
-description: Contribute a idea or request a new feature
+description: Commit a idea or Request a new feature
 title: '[enhancement]: '
 labels: ['enhancement']
 # assignees:
@@ -9,14 +9,14 @@ body:
   - type: markdown
     attributes:
       value: |
-        Thanks for taking the time to fill out this feature request!
+        Thanks for taking the time to fill out this Feature request!
 
   - type: checkboxes
     attributes:
       label: Is there an existing issue for this?
       description: |
         Please make use of the [search function](https://github.com/invoke-ai/InvokeAI/labels/enhancement)
-        to see if a similar issue already exists for the feature you want to request
+        to see if a simmilar issue already exists for the feature you want to request
       options:
         - label: I have searched the existing issues
           required: true
@@ -34,9 +34,12 @@ body:
     id: whatisexpected
     attributes:
       label: What should this feature add?
-      description: Explain the functionality this feature should add. Feature requests should be for single features. Please create multiple requests if you want to request multiple features.
+      description: Please try to explain the functionality this feature should add
       placeholder: |
-        I'd like a button that creates an image of banana sushi every time I press it. Each image should be different. There should be a toggle next to the button that enables strawberry mode, in which the images are of strawberry sushi instead.
+        Instead of one huge textfield, it would be nice to have forms for bug-reports, feature-requests, ...
+        Great benefits with automatic labeling, assigning and other functionalitys not available in that form
+        via old-fashioned markdown-templates. I would also love to see the use of a moderator bot 🤖 like
+        https://github.com/marketplace/actions/issue-moderator-with-commands to auto close old issues and other things
     validations:
       required: true
 
@@ -48,6 +51,6 @@ body:
 
   - type: textarea
     attributes:
-      label: Additional Content
+      label: Aditional Content
       description: Add any other context or screenshots about the feature request here.
-      placeholder: This is a mockup of the design how I imagine it <screenshot>
+      placeholder: This is a Mockup of the design how I imagine it <screenshot>

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

@@ -1,33 +0,0 @@
-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
-
-    - name: setup cache
-      uses: actions/cache@v4
-      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/pr_labels.yml

@@ -1,59 +0,0 @@
-root:
-- changed-files:
-  - any-glob-to-any-file: '*'
-
-python-deps:
-- changed-files:
-  - any-glob-to-any-file: 'pyproject.toml'
-
-python:
-- changed-files:
-  - all-globs-to-any-file: 
-    - 'invokeai/**'
-    - '!invokeai/frontend/web/**'
-
-python-tests:
-- changed-files:
-  - any-glob-to-any-file: 'tests/**'
-
-ci-cd:
-- changed-files:
-  - any-glob-to-any-file: .github/**
-
-docker:
-- changed-files:
-  - any-glob-to-any-file: docker/**
-
-installer:
-- changed-files:
-  - any-glob-to-any-file: installer/**
-
-docs:
-- changed-files:
-  - any-glob-to-any-file: docs/**
-
-invocations:
-- changed-files:
-  - any-glob-to-any-file: 'invokeai/app/invocations/**'
-
-backend:
-- changed-files:
-  - any-glob-to-any-file: 'invokeai/backend/**'
-
-api:
-- changed-files:
-  - any-glob-to-any-file: 'invokeai/app/api/**'
-
-services:
-- changed-files:
-  - any-glob-to-any-file: 'invokeai/app/services/**'
-
-frontend-deps:
-- changed-files:
-  - any-glob-to-any-file:
-    - '**/*/package.json'
-    - '**/*/pnpm-lock.yaml'
-
-frontend:
-- changed-files:
-  - any-glob-to-any-file: 'invokeai/frontend/web/**'

.github/pull_request_template.md

@@ -1,21 +0,0 @@
-## Summary
-
-<!--A description of the changes in this PR. Include the kind of change (fix, feature, docs, etc), the "why" and the "how". Screenshots or videos are useful for frontend changes.-->
-
-## Related Issues / Discussions
-
-<!--WHEN APPLICABLE: List any related issues or discussions on github or discord. If this PR closes an issue, please use the "Closes #1234" format, so that the issue will be automatically closed when the PR merges.-->
-
-## QA Instructions
-
-<!--WHEN APPLICABLE: Describe how we can test the changes in this PR.-->
-
-## Merge Plan
-
-<!--WHEN APPLICABLE: Large PRs, or PRs that touch sensitive things like DB schemas, may need some care when merging. For example, a careful rebase by the change author, timing to not interfere with a pending release, or a message to contributors on discord after merging.-->
-
-## Checklist
-
-- [ ] _The PR has a short but descriptive title, suitable for a changelog_
-- [ ] _Tests added / updated (if applicable)_
-- [ ] _Documentation added / updated (if applicable)_

.github/workflows/build-container.yml

@@ -3,13 +3,15 @@ on:
   push:
     branches:
       - 'main'
+      - 'update/ci/docker/*'
+      - 'update/docker/*'
+      - 'dev/ci/docker/*'
+      - 'dev/docker/*'
     paths:
       - 'pyproject.toml'
       - '.dockerignore'
       - 'invokeai/**'
       - 'docker/Dockerfile'
-      - 'docker/docker-entrypoint.sh'
-      - 'workflows/build-container.yml'
     tags:
       - 'v*.*.*'
   workflow_dispatch:
@@ -24,31 +26,23 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        gpu-driver:
-        - cuda
-        - cpu
-        - rocm
+        flavor:
+          - rocm
+          - cuda
+          - cpu
+        include:
+          - flavor: rocm
+            pip-extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
+          - flavor: cuda
+            pip-extra-index-url: ''
+          - flavor: cpu
+            pip-extra-index-url: 'https://download.pytorch.org/whl/cpu'
     runs-on: ubuntu-latest
-    name: ${{ matrix.gpu-driver }}
+    name: ${{ matrix.flavor }}
     env:
-      # torch/arm64 does not support GPU currently, so arm64 builds
-      # would not be GPU-accelerated.
-      # re-enable arm64 if there is sufficient demand.
-      # PLATFORMS: 'linux/amd64,linux/arm64'
-      PLATFORMS: 'linux/amd64'
+      PLATFORMS: 'linux/amd64,linux/arm64'
+      DOCKERFILE: 'docker/Dockerfile'
     steps:
-      - name: Free up more disk space on the runner
-        # https://github.com/actions/runner-images/issues/2840#issuecomment-1284059930
-        run: |
-          echo "----- Free space before cleanup"
-          df -h
-          sudo rm -rf /usr/share/dotnet
-          sudo rm -rf "$AGENT_TOOLSDIRECTORY"
-          sudo swapoff /mnt/swapfile
-          sudo rm -rf /mnt/swapfile
-          echo "----- Free space after cleanup"
-          df -h
-
       - name: Checkout
         uses: actions/checkout@v3
 
@@ -59,7 +53,7 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           images: |
             ghcr.io/${{ github.repository }}
-            ${{ env.DOCKERHUB_REPOSITORY }}
+            ${{ vars.DOCKERHUB_REPOSITORY }}
           tags: |
             type=ref,event=branch
             type=ref,event=tag
@@ -68,8 +62,8 @@ jobs:
             type=pep440,pattern={{major}}
             type=sha,enable=true,prefix=sha-,format=short
           flavor: |
-            latest=${{ matrix.gpu-driver == 'cuda' && github.ref == 'refs/heads/main' }}
-            suffix=-${{ matrix.gpu-driver }},onlatest=false
+            latest=${{ matrix.flavor == 'cuda' && github.ref == 'refs/heads/main' }}
+            suffix=-${{ matrix.flavor }},onlatest=false
 
       - name: Set up QEMU
         uses: docker/setup-qemu-action@v2
@@ -87,34 +81,34 @@ jobs:
           username: ${{ github.repository_owner }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
-      # - name: Login to Docker Hub
-      #   if: github.event_name != 'pull_request' && vars.DOCKERHUB_REPOSITORY != ''
-      #   uses: docker/login-action@v2
-      #   with:
-      #     username: ${{ secrets.DOCKERHUB_USERNAME }}
-      #     password: ${{ secrets.DOCKERHUB_TOKEN }}
+      - name: Login to Docker Hub
+        if: github.event_name != 'pull_request' && vars.DOCKERHUB_REPOSITORY != ''
+        uses: docker/login-action@v2
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
 
       - name: Build container
-        timeout-minutes: 40
         id: docker_build
         uses: docker/build-push-action@v4
         with:
           context: .
-          file: docker/Dockerfile
+          file: ${{ env.DOCKERFILE }}
           platforms: ${{ env.PLATFORMS }}
           push: ${{ github.ref == 'refs/heads/main' || github.ref_type == 'tag' }}
           tags: ${{ steps.meta.outputs.tags }}
           labels: ${{ steps.meta.outputs.labels }}
+          build-args: PIP_EXTRA_INDEX_URL=${{ matrix.pip-extra-index-url }}
           cache-from: |
-            type=gha,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}
-            type=gha,scope=main-${{ matrix.gpu-driver }}
-          cache-to: type=gha,mode=max,scope=${{ github.ref_name }}-${{ matrix.gpu-driver }}
+            type=gha,scope=${{ github.ref_name }}-${{ matrix.flavor }}
+            type=gha,scope=main-${{ matrix.flavor }}
+          cache-to: type=gha,mode=max,scope=${{ github.ref_name }}-${{ matrix.flavor }}
 
-      # - name: Docker Hub Description
-      #   if: github.ref == 'refs/heads/main' || github.ref == 'refs/tags/*' && vars.DOCKERHUB_REPOSITORY != ''
-      #   uses: peter-evans/dockerhub-description@v3
-      #   with:
-      #     username: ${{ secrets.DOCKERHUB_USERNAME }}
-      #     password: ${{ secrets.DOCKERHUB_TOKEN }}
-      #     repository: ${{ vars.DOCKERHUB_REPOSITORY }}
-      #     short-description: ${{ github.event.repository.description }}
+      - name: Docker Hub Description
+        if: github.ref == 'refs/heads/main' || github.ref == 'refs/tags/*' && vars.DOCKERHUB_REPOSITORY != ''
+        uses: peter-evans/dockerhub-description@v3
+        with:
+          username: ${{ secrets.DOCKERHUB_USERNAME }}
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+          repository: ${{ vars.DOCKERHUB_REPOSITORY }}
+          short-description: ${{ github.event.repository.description }}

.github/workflows/build-installer.yml

@@ -1,45 +0,0 @@
-# Builds and uploads the installer and python build artifacts.
-
-name: build installer
-
-on:
-  workflow_dispatch:
-  workflow_call:
-
-jobs:
-  build-installer:
-    runs-on: ubuntu-latest
-    timeout-minutes: 5 # expected run time: <2 min
-    steps:
-      - name: checkout
-        uses: actions/checkout@v4
-
-      - name: setup python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.10'
-          cache: pip
-          cache-dependency-path: pyproject.toml
-
-      - name: install pypa/build
-        run: pip install --upgrade build
-
-      - name: setup frontend
-        uses: ./.github/actions/install-frontend-deps
-
-      - name: create installer
-        id: create_installer
-        run: ./create_installer.sh
-        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: installer
-          path: ${{ steps.create_installer.outputs.INSTALLER_PATH }}

.github/workflows/close-inactive-issues.yml

@@ -1,11 +1,11 @@
 name: Close inactive issues
 on:
   schedule:
-    - cron: "00 4 * * *"
+    - cron: "00 6 * * *"
 
 env:
-  DAYS_BEFORE_ISSUE_STALE: 30
-  DAYS_BEFORE_ISSUE_CLOSE: 14
+  DAYS_BEFORE_ISSUE_STALE: 14
+  DAYS_BEFORE_ISSUE_CLOSE: 28
 
 jobs:
   close-issues:
@@ -14,7 +14,7 @@ jobs:
       issues: write
       pull-requests: write
     steps:
-      - uses: actions/stale@v8
+      - uses: actions/stale@v5
         with:
           days-before-issue-stale: ${{ env.DAYS_BEFORE_ISSUE_STALE }}
           days-before-issue-close: ${{ env.DAYS_BEFORE_ISSUE_CLOSE }}
@@ -23,6 +23,5 @@ jobs:
           close-issue-message: "Due to inactivity, this issue was automatically closed. If you are still experiencing the issue, please recreate the issue."
           days-before-pr-stale: -1
           days-before-pr-close: -1
-          exempt-issue-labels: "Active Issue"
           repo-token: ${{ secrets.GITHUB_TOKEN }}
           operations-per-run: 500

.github/workflows/frontend-checks.yml

@@ -1,80 +0,0 @@
-# Runs frontend code quality checks.
-#
-# Checks for changes to frontend files before running the checks.
-# If always_run is true, always runs the checks.
-
-name: 'frontend checks'
-
-on:
-  push:
-    branches:
-      - 'main'
-  pull_request:
-    types:
-      - 'ready_for_review'
-      - 'opened'
-      - 'synchronize'
-  merge_group:
-  workflow_dispatch:
-    inputs:
-      always_run:
-        description: 'Always run the checks'
-        required: true
-        type: boolean
-        default: true
-  workflow_call:
-    inputs:
-      always_run:
-        description: 'Always run the checks'
-        required: true
-        type: boolean
-        default: true
-
-defaults:
-  run:
-    working-directory: invokeai/frontend/web
-
-jobs:
-  frontend-checks:
-    runs-on: ubuntu-latest
-    timeout-minutes: 10 # expected run time: <2 min
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: check for changed frontend files
-        if: ${{ inputs.always_run != true }}
-        id: changed-files
-        uses: tj-actions/changed-files@v42
-        with:
-          files_yaml: |
-            frontend:
-              - 'invokeai/frontend/web/**'
-
-      - name: install dependencies
-        if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
-        uses: ./.github/actions/install-frontend-deps
-
-      - name: tsc
-        if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
-        run: 'pnpm lint:tsc'
-        shell: bash
-
-      - name: dpdm
-        if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
-        run: 'pnpm lint:dpdm'
-        shell: bash
-
-      - name: eslint
-        if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
-        run: 'pnpm lint:eslint'
-        shell: bash
-
-      - name: prettier
-        if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
-        run: 'pnpm lint:prettier'
-        shell: bash
-
-      - name: knip
-        if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
-        run: 'pnpm lint:knip'
-        shell: bash

.github/workflows/frontend-tests.yml

@@ -1,60 +0,0 @@
-# Runs frontend tests.
-#
-# Checks for changes to frontend files before running the tests.
-# If always_run is true, always runs the tests.
-
-name: 'frontend tests'
-
-on:
-  push:
-    branches:
-      - 'main'
-  pull_request:
-    types:
-      - 'ready_for_review'
-      - 'opened'
-      - 'synchronize'
-  merge_group:
-  workflow_dispatch:
-    inputs:
-      always_run:
-        description: 'Always run the tests'
-        required: true
-        type: boolean
-        default: true
-  workflow_call:
-    inputs:
-      always_run:
-        description: 'Always run the tests'
-        required: true
-        type: boolean
-        default: true
-
-defaults:
-  run:
-    working-directory: invokeai/frontend/web
-
-jobs:
-  frontend-tests:
-    runs-on: ubuntu-latest
-    timeout-minutes: 10 # expected run time: <2 min
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: check for changed frontend files
-        if: ${{ inputs.always_run != true }}
-        id: changed-files
-        uses: tj-actions/changed-files@v42
-        with:
-          files_yaml: |
-            frontend:
-              - 'invokeai/frontend/web/**'
-
-      - name: install dependencies
-        if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
-        uses: ./.github/actions/install-frontend-deps
-
-      - name: vitest
-        if: ${{ steps.changed-files.outputs.frontend_any_changed == 'true' || inputs.always_run == true }}
-        run: 'pnpm test:no-watch'
-        shell: bash

.github/workflows/label-pr.yml

@@ -1,18 +0,0 @@
-name: 'label PRs'
-on:
-  - pull_request_target
-
-jobs:
-  labeler:
-    permissions:
-      contents: read
-      pull-requests: write
-    runs-on: ubuntu-latest
-    steps:
-      - name: checkout
-        uses: actions/checkout@v4
-
-      - name: label PRs
-        uses: actions/labeler@v5
-        with:
-          configuration-path: .github/pr_labels.yml

.github/workflows/lint-frontend.yml

@@ -0,0 +1,37 @@
+name: Lint frontend
+
+on:
+  pull_request:
+    paths:
+      - 'invokeai/frontend/web/**'
+    types:
+      - 'ready_for_review'
+      - 'opened'
+      - 'synchronize'
+  push:
+    branches:
+      - 'main'
+    paths:
+      - 'invokeai/frontend/web/**'
+  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 18
+        uses: actions/setup-node@v3
+        with:
+          node-version: '18'
+      - uses: actions/checkout@v3
+      - run: 'yarn install --frozen-lockfile'
+      - run: 'yarn run lint:tsc'
+      - run: 'yarn run lint:madge'
+      - run: 'yarn run lint:eslint'
+      - run: 'yarn run lint:prettier'

.github/workflows/mkdocs-material.yml

@@ -1,49 +1,51 @@
-# This is a mostly a copy-paste from https://github.com/squidfunk/mkdocs-material/blob/master/docs/publishing-your-site.md
-
-name: mkdocs
-
+name: mkdocs-material
 on:
   push:
     branches:
-      - main
-  workflow_dispatch:
+      - 'refs/heads/v2.3'
 
 permissions:
-  contents: write
+    contents: write
 
 jobs:
-  deploy:
+  mkdocs-material:
     if: github.event.pull_request.draft == false
     runs-on: ubuntu-latest
     env:
       REPO_URL: '${{ github.server_url }}/${{ github.repository }}'
       REPO_NAME: '${{ github.repository }}'
       SITE_URL: 'https://${{ github.repository_owner }}.github.io/InvokeAI'
-
     steps:
-      - name: checkout
-        uses: actions/checkout@v4
+      - name: checkout sources
+        uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
 
       - name: setup python
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v4
         with:
           python-version: '3.10'
           cache: pip
           cache-dependency-path: pyproject.toml
 
-      - name: set cache id
-        run: echo "cache_id=$(date --utc '+%V')" >> $GITHUB_ENV
+      - name: install requirements
+        env:
+          PIP_USE_PEP517: 1
+        run: |
+          python -m \
+            pip install ".[docs]"
 
-      - name: use cache
-        uses: actions/cache@v4
-        with:
-          key: mkdocs-material-${{ env.cache_id }}
-          path: .cache
-          restore-keys: |
-            mkdocs-material-
+      - name: confirm buildability
+        run: |
+          python -m \
+            mkdocs build \
+            --clean \
+            --verbose
 
-      - name: install dependencies
-        run: python -m pip install ".[docs]"
-
-      - name: build & deploy
-        run: mkdocs gh-deploy --force
+      - name: deploy to gh-pages
+        if: ${{ github.ref == 'refs/heads/v2.3' }}
+        run: |
+          python -m \
+            mkdocs gh-deploy \
+            --clean \
+            --force

.github/workflows/pyflakes.yml

@@ -0,0 +1,20 @@
+on:
+  pull_request:
+  push:
+    branches:
+      - main
+      - development
+      - 'release-candidate-*'
+
+jobs:
+  pyflakes:
+    name: runner / pyflakes
+    if: github.event.pull_request.draft == false
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - name: pyflakes
+        uses: reviewdog/action-pyflakes@v1
+        with:
+          github_token: ${{ secrets.GITHUB_TOKEN }}
+          reporter: github-pr-review

.github/workflows/pypi-release.yml

@@ -0,0 +1,41 @@
+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' || github.ref == 'refs/heads/v2.3'
+        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/python-checks.yml

@@ -1,76 +0,0 @@
-# Runs python code quality checks.
-#
-# Checks for changes to python files before running the checks.
-# If always_run is true, always runs the checks.
-#
-# TODO: Add mypy or pyright to the checks.
-
-name: 'python checks'
-
-on:
-  push:
-    branches:
-      - 'main'
-  pull_request:
-    types:
-      - 'ready_for_review'
-      - 'opened'
-      - 'synchronize'
-  merge_group:
-  workflow_dispatch:
-    inputs:
-      always_run:
-        description: 'Always run the checks'
-        required: true
-        type: boolean
-        default: true
-  workflow_call:
-    inputs:
-      always_run:
-        description: 'Always run the checks'
-        required: true
-        type: boolean
-        default: true
-
-jobs:
-  python-checks:
-    runs-on: ubuntu-latest
-    timeout-minutes: 5 # expected run time: <1 min
-    steps:
-      - name: checkout
-        uses: actions/checkout@v4
-
-      - name: check for changed python files
-        if: ${{ inputs.always_run != true }}
-        id: changed-files
-        uses: tj-actions/changed-files@v42
-        with:
-          files_yaml: |
-            python:
-              - 'pyproject.toml'
-              - 'invokeai/**'
-              - '!invokeai/frontend/web/**'
-              - 'tests/**'
-
-      - name: setup python
-        if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.10'
-          cache: pip
-          cache-dependency-path: pyproject.toml
-
-      - name: install ruff
-        if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        run: pip install ruff
-        shell: bash
-
-      - name: ruff check
-        if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        run: ruff check --output-format=github .
-        shell: bash
-
-      - name: ruff format
-        if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        run: ruff format --check .
-        shell: bash

.github/workflows/python-tests.yml

@@ -1,106 +0,0 @@
-# Runs python tests on a matrix of python versions and platforms.
-#
-# Checks for changes to python files before running the tests.
-# If always_run is true, always runs the tests.
-
-name: 'python tests'
-
-on:
-  push:
-    branches:
-      - 'main'
-  pull_request:
-    types:
-      - 'ready_for_review'
-      - 'opened'
-      - 'synchronize'
-  merge_group:
-  workflow_dispatch:
-    inputs:
-      always_run:
-        description: 'Always run the tests'
-        required: true
-        type: boolean
-        default: true
-  workflow_call:
-    inputs:
-      always_run:
-        description: 'Always run the tests'
-        required: true
-        type: boolean
-        default: true
-
-concurrency:
-  group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
-  cancel-in-progress: true
-
-jobs:
-  matrix:
-    strategy:
-      matrix:
-        python-version:
-          - '3.10'
-          - '3.11'
-        platform:
-          - linux-cuda-11_7
-          - linux-rocm-5_2
-          - linux-cpu
-          - macos-default
-          - windows-cpu
-        include:
-          - platform: linux-cuda-11_7
-            os: ubuntu-22.04
-            github-env: $GITHUB_ENV
-          - platform: linux-rocm-5_2
-            os: ubuntu-22.04
-            extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
-            github-env: $GITHUB_ENV
-          - platform: linux-cpu
-            os: ubuntu-22.04
-            extra-index-url: 'https://download.pytorch.org/whl/cpu'
-            github-env: $GITHUB_ENV
-          - platform: macos-default
-            os: macOS-12
-            github-env: $GITHUB_ENV
-          - platform: windows-cpu
-            os: windows-2022
-            github-env: $env:GITHUB_ENV
-    name: 'py${{ matrix.python-version }}: ${{ matrix.platform }}'
-    runs-on: ${{ matrix.os }}
-    timeout-minutes: 15 # expected run time: 2-6 min, depending on platform
-    env:
-      PIP_USE_PEP517: '1'
-    steps:
-      - name: checkout
-        uses: actions/checkout@v4
-
-      - name: check for changed python files
-        if: ${{ inputs.always_run != true }}
-        id: changed-files
-        uses: tj-actions/changed-files@v42
-        with:
-          files_yaml: |
-            python:
-              - 'pyproject.toml'
-              - 'invokeai/**'
-              - '!invokeai/frontend/web/**'
-              - 'tests/**'
-
-      - name: setup python
-        if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        uses: actions/setup-python@v5
-        with:
-          python-version: ${{ matrix.python-version }}
-          cache: pip
-          cache-dependency-path: pyproject.toml
-
-      - name: install dependencies
-        if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        env:
-          PIP_EXTRA_INDEX_URL: ${{ matrix.extra-index-url }}
-        run: >
-          pip3 install --editable=".[test]"
-
-      - name: run pytest
-        if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        run: pytest

.github/workflows/release.yml

@@ -1,108 +0,0 @@
-# Main release workflow. Triggered on tag push or manual trigger.
-#
-# - Runs all code checks and tests
-# - Verifies the app version matches the tag version.
-# - Builds the installer and build, uploading them as artifacts.
-# - Publishes to TestPyPI and PyPI. Both are conditional on the previous steps passing and require a manual approval.
-#
-# See docs/RELEASE.md for more information on the release process.
-
-name: release
-
-on:
-  push:
-    tags:
-      - 'v*'
-  workflow_dispatch:
-
-jobs:
-  check-version:
-    runs-on: ubuntu-latest
-    steps:
-      - name: checkout
-        uses: actions/checkout@v4
-
-      - name: check python version
-        uses: samuelcolvin/check-python-version@v4
-        id: check-python-version
-        with:
-          version_file_path: invokeai/version/invokeai_version.py
-
-  frontend-checks:
-    uses: ./.github/workflows/frontend-checks.yml
-    with:
-      always_run: true
-
-  frontend-tests:
-    uses: ./.github/workflows/frontend-tests.yml
-    with:
-      always_run: true
-
-  python-checks:
-    uses: ./.github/workflows/python-checks.yml
-    with:
-      always_run: true
-
-  python-tests:
-    uses: ./.github/workflows/python-tests.yml
-    with:
-      always_run: true
-
-  build:
-    uses: ./.github/workflows/build-installer.yml
-
-  publish-testpypi:
-    runs-on: ubuntu-latest
-    timeout-minutes: 5 # expected run time: <1 min
-    needs:
-      [
-        check-version,
-        frontend-checks,
-        frontend-tests,
-        python-checks,
-        python-tests,
-        build,
-      ]
-    environment:
-      name: testpypi
-      url: https://test.pypi.org/p/invokeai
-    permissions:
-      id-token: write
-    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
-    timeout-minutes: 5 # expected run time: <1 min
-    needs:
-      [
-        check-version,
-        frontend-checks,
-        frontend-tests,
-        python-checks,
-        python-tests,
-        build,
-      ]
-    environment:
-      name: pypi
-      url: https://pypi.org/p/invokeai
-    permissions:
-      id-token: write
-    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/test-invoke-pip-skip.yml

@@ -0,0 +1,50 @@
+name: Test invoke.py pip
+
+# This is a dummy stand-in for the actual tests
+# we don't need to run python tests on non-Python changes
+# But PRs require passing tests to be mergeable
+
+on:
+  pull_request:
+    paths:
+      - '**'
+      - '!pyproject.toml'
+      - '!invokeai/**'
+      - '!tests/**'
+      - 'invokeai/frontend/web/**'
+  merge_group:
+  workflow_dispatch:
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  matrix:
+    if: github.event.pull_request.draft == false
+    strategy:
+      matrix:
+        python-version:
+          - '3.10'
+        pytorch:
+          - linux-cuda-11_7
+          - linux-rocm-5_2
+          - linux-cpu
+          - macos-default
+          - windows-cpu
+        include:
+          - pytorch: linux-cuda-11_7
+            os: ubuntu-22.04
+          - pytorch: linux-rocm-5_2
+            os: ubuntu-22.04
+          - pytorch: linux-cpu
+            os: ubuntu-22.04
+          - pytorch: macos-default
+            os: macOS-12
+          - pytorch: windows-cpu
+            os: windows-2022
+    name: ${{ matrix.pytorch }} on ${{ matrix.python-version }}
+    runs-on: ${{ matrix.os }}
+    steps:
+      - name: skip
+        run: echo "no build required"

.github/workflows/test-invoke-pip.yml

@@ -0,0 +1,123 @@
+name: Test invoke.py pip
+on:
+  push:
+    branches:
+      - 'main'
+    paths:
+      - 'pyproject.toml'
+      - 'invokeai/**'
+      - '!invokeai/frontend/web/**'
+  pull_request:
+    paths:
+      - 'pyproject.toml'
+      - 'invokeai/**'
+      - 'tests/**'
+      - '!invokeai/frontend/web/**'
+    types:
+      - 'ready_for_review'
+      - 'opened'
+      - 'synchronize'
+  merge_group:
+  workflow_dispatch:
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  matrix:
+    if: github.event.pull_request.draft == false
+    strategy:
+      matrix:
+        python-version:
+          # - '3.9'
+          - '3.10'
+        pytorch:
+          - linux-cuda-11_7
+          - linux-rocm-5_2
+          - linux-cpu
+          - macos-default
+          - windows-cpu
+        include:
+          - pytorch: linux-cuda-11_7
+            os: ubuntu-22.04
+            github-env: $GITHUB_ENV
+          - pytorch: linux-rocm-5_2
+            os: ubuntu-22.04
+            extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
+            github-env: $GITHUB_ENV
+          - pytorch: linux-cpu
+            os: ubuntu-22.04
+            extra-index-url: 'https://download.pytorch.org/whl/cpu'
+            github-env: $GITHUB_ENV
+          - pytorch: macos-default
+            os: macOS-12
+            github-env: $GITHUB_ENV
+          - pytorch: windows-cpu
+            os: windows-2022
+            github-env: $env:GITHUB_ENV
+    name: ${{ matrix.pytorch }} on ${{ matrix.python-version }}
+    runs-on: ${{ matrix.os }}
+    env:
+      PIP_USE_PEP517: '1'
+    steps:
+      - name: Checkout sources
+        id: checkout-sources
+        uses: actions/checkout@v3
+
+      - name: set test prompt to main branch validation
+        run: echo "TEST_PROMPTS=tests/validate_pr_prompt.txt" >> ${{ matrix.github-env }}
+
+      - name: setup python
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+          cache: pip
+          cache-dependency-path: pyproject.toml
+
+      - name: install invokeai
+        env:
+          PIP_EXTRA_INDEX_URL: ${{ matrix.extra-index-url }}
+        run: >
+          pip3 install
+          --editable=".[test]"
+
+      - name: run pytest
+        id: run-pytest
+        run: pytest
+
+      # - name: run invokeai-configure
+      #   env:
+      #     HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGINGFACE_TOKEN }}
+      #   run: >
+      #     invokeai-configure
+      #     --yes
+      #     --default_only
+      #     --full-precision
+      #   # can't use fp16 weights without a GPU
+
+      # - name: run invokeai
+      #   id: run-invokeai
+      #   env:
+      #     # Set offline mode to make sure configure preloaded successfully.
+      #     HF_HUB_OFFLINE: 1
+      #     HF_DATASETS_OFFLINE: 1
+      #     TRANSFORMERS_OFFLINE: 1
+      #     INVOKEAI_OUTDIR: ${{ github.workspace }}/results
+      #   run: >
+      #     invokeai
+      #     --no-patchmatch
+      #     --no-nsfw_checker
+      #     --precision=float32
+      #     --always_use_cpu
+      #     --use_memory_db
+      #     --outdir ${{ env.INVOKEAI_OUTDIR }}/${{ matrix.python-version }}/${{ matrix.pytorch }}
+      #     --from_file ${{ env.TEST_PROMPTS }}
+
+      # - name: Archive results
+      #   env:
+      #     INVOKEAI_OUTDIR: ${{ github.workspace }}/results
+      #   uses: actions/upload-artifact@v3
+      #   with:
+      #     name: results
+      #     path: ${{ env.INVOKEAI_OUTDIR }}

.gitignore

@@ -1,4 +1,22 @@
+# ignore default image save location and model symbolic link
 .idea/
+embeddings/
+outputs/
+models/ldm/stable-diffusion-v1/model.ckpt
+**/restoration/codeformer/weights
+
+# ignore user models config
+configs/models.user.yaml
+config/models.user.yml
+invokeai.init
+.version
+.last_model
+
+# ignore the Anaconda/Miniconda installer used while building Docker image
+anaconda.sh
+
+# ignore a directory which serves as a place for initial images
+inputs/
 
 # Byte-compiled / optimized / DLL files
 __pycache__/
@@ -16,10 +34,11 @@ __pycache__/
 .Python
 build/
 develop-eggs/
-dist/
+# dist/
 downloads/
 eggs/
 .eggs/
+lib/
 lib64/
 parts/
 sdist/
@@ -133,10 +152,12 @@ celerybeat.pid
 
 # Environments
 .env
-.venv*
+.venv
 env/
 venv/
 ENV/
+env.bak/
+venv.bak/
 
 # Spyder project settings
 .spyderproject
@@ -169,17 +190,44 @@ cython_debug/
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
 
+src
 **/__pycache__/
+outputs
 
+# Logs and associated folders
+# created from generated embeddings.
+logs
+testtube
+checkpoints
 # If it's a Mac
 .DS_Store
 
+invokeai/frontend/yarn.lock
+invokeai/frontend/node_modules
+
 # Let the frontend manage its own gitignore
 !invokeai/frontend/web/*
 
 # Scratch folder
 .scratch/
 .vscode/
+gfpgan/
+models/ldm/stable-diffusion-v1/*.sha256
+
+
+# GFPGAN model files
+gfpgan/
+
+# config file (will be created by installer)
+configs/models.yaml
+
+# ignore initfile
+.invokeai
+
+# ignore environment.yml and requirements.txt
+# these are links to the real files in environments-and-requirements
+environment.yml
+requirements.txt
 
 # source installer files
 installer/*zip
@@ -187,4 +235,3 @@ installer/install.bat
 installer/install.sh
 installer/update.bat
 installer/update.sh
-installer/InvokeAI-Installer/

.pre-commit-config.yaml

@@ -1,24 +0,0 @@
-# See https://pre-commit.com/ for usage and config
-repos:
-- repo: local
-  hooks:
-  - id: black
-    name: black
-    stages: [commit]
-    language: system
-    entry: black
-    types: [python]
-
-  - id: flake8
-    name: flake8
-    stages: [commit]
-    language: system
-    entry: flake8
-    types: [python]
-
-  - id: isort
-    name: isort
-    stages: [commit]
-    language: system
-    entry: isort
-    types: [python]

.prettierrc.yaml

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

LICENSE

@@ -1,176 +1,21 @@
-                                 Apache License
-                           Version 2.0, January 2004
-                        http://www.apache.org/licenses/
+MIT License
 
-   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+Copyright (c) 2022 InvokeAI Team
 
-   1. Definitions.
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
 
-      "License" shall mean the terms and conditions for use, reproduction,
-      and distribution as defined by Sections 1 through 9 of this document.
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
 
-      "Licensor" shall mean the copyright owner or entity authorized by
-      the copyright owner that is granting the License.
-
-      "Legal Entity" shall mean the union of the acting entity and all
-      other entities that control, are controlled by, or are under common
-      control with that entity. For the purposes of this definition,
-      "control" means (i) the power, direct or indirect, to cause the
-      direction or management of such entity, whether by contract or
-      otherwise, or (ii) ownership of fifty percent (50%) or more of the
-      outstanding shares, or (iii) beneficial ownership of such entity.
-
-      "You" (or "Your") shall mean an individual or Legal Entity
-      exercising permissions granted by this License.
-
-      "Source" form shall mean the preferred form for making modifications,
-      including but not limited to software source code, documentation
-      source, and configuration files.
-
-      "Object" form shall mean any form resulting from mechanical
-      transformation or translation of a Source form, including but
-      not limited to compiled object code, generated documentation,
-      and conversions to other media types.
-
-      "Work" shall mean the work of authorship, whether in Source or
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-      form, that is based on (or derived from) the Work and for which the
-      editorial revisions, annotations, elaborations, or other modifications
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-      on behalf of whom a Contribution has been received by Licensor and
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-   2. Grant of Copyright License. Subject to the terms and conditions of
-      this License, each Contributor hereby grants to You a perpetual,
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-   4. Redistribution. You may reproduce and distribute copies of the
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-      You may add Your own copyright statement to Your modifications and
-      may provide additional or different license terms and conditions
-      for use, reproduction, or distribution of Your modifications, or
-      for any such Derivative Works as a whole, provided Your use,
-      reproduction, and distribution of the Work otherwise complies with
-      the conditions stated in this License.
-
-   5. Submission of Contributions. Unless You explicitly state otherwise,
-      any Contribution intentionally submitted for inclusion in the Work
-      by You to the Licensor shall be under the terms and conditions of
-      this License, without any additional terms or conditions.
-      Notwithstanding the above, nothing herein shall supersede or modify
-      the terms of any separate license agreement you may have executed
-      with Licensor regarding such Contributions.
-
-   6. Trademarks. This License does not grant permission to use the trade
-      names, trademarks, service marks, or product names of the Licensor,
-      except as required for reasonable and customary use in describing the
-      origin of the Work and reproducing the content of the NOTICE file.
-
-   7. Disclaimer of Warranty. Unless required by applicable law or
-      agreed to in writing, Licensor provides the Work (and each
-      Contributor provides its Contributions) on an "AS IS" BASIS,
-      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
-      implied, including, without limitation, any warranties or conditions
-      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
-      PARTICULAR PURPOSE. You are solely responsible for determining the
-      appropriateness of using or redistributing the Work and assume any
-      risks associated with Your exercise of permissions under this License.
-
-   8. Limitation of Liability. In no event and under no legal theory,
-      whether in tort (including negligence), contract, or otherwise,
-      unless required by applicable law (such as deliberate and grossly
-      negligent acts) or agreed to in writing, shall any Contributor be
-      liable to You for damages, including any direct, indirect, special,
-      incidental, or consequential damages of any character arising as a
-      result of this License or out of the use or inability to use the
-      Work (including but not limited to damages for loss of goodwill,
-      work stoppage, computer failure or malfunction, or any and all
-      other commercial damages or losses), even if such Contributor
-      has been advised of the possibility of such damages.
-
-   9. Accepting Warranty or Additional Liability. While redistributing
-      the Work or Derivative Works thereof, You may choose to offer,
-      and charge a fee for, acceptance of support, warranty, indemnity,
-      or other liability obligations and/or rights consistent with this
-      License. However, in accepting such obligations, You may act only
-      on Your own behalf and on Your sole responsibility, not on behalf
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-      defend, and hold each Contributor harmless for any liability
-      incurred by, or claims asserted against, such Contributor by reason
-      of your accepting any such warranty or additional liability.
-
-   
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

LICENSE-SDXL.txt

@@ -1,290 +0,0 @@
-Copyright (c) 2023 Stability AI
-CreativeML Open RAIL++-M License dated July 26, 2023
-
-Section I: PREAMBLE
-
-Multimodal generative models are being widely adopted and used, and
-have the potential to transform the way artists, among other
-individuals, conceive and benefit from AI or ML technologies as a tool
-for content creation.
-
-Notwithstanding the current and potential benefits that these
-artifacts can bring to society at large, there are also concerns about
-potential misuses of them, either due to their technical limitations
-or ethical considerations.
-
-In short, this license strives for both the open and responsible
-downstream use of the accompanying model. When it comes to the open
-character, we took inspiration from open source permissive licenses
-regarding the grant of IP rights. Referring to the downstream
-responsible use, we added use-based restrictions not permitting the
-use of the model in very specific scenarios, in order for the licensor
-to be able to enforce the license in case potential misuses of the
-Model may occur. At the same time, we strive to promote open and
-responsible research on generative models for art and content
-generation.
-
-Even though downstream derivative versions of the model could be
-released under different licensing terms, the latter will always have
-to include - at minimum - the same use-based restrictions as the ones
-in the original license (this license). We believe in the intersection
-between open and responsible AI development; thus, this agreement aims
-to strike a balance between both in order to enable responsible
-open-science in the field of AI.
-
-This CreativeML Open RAIL++-M License governs the use of the model
-(and its derivatives) and is informed by the model card associated
-with the model.
-
-NOW THEREFORE, You and Licensor agree as follows:
-
-Definitions
-
-"License" means the terms and conditions for use, reproduction, and
-Distribution as defined in this document.
-
-"Data" means a collection of information and/or content extracted from
-the dataset used with the Model, including to train, pretrain, or
-otherwise evaluate the Model. The Data is not licensed under this
-License.
-
-"Output" means the results of operating a Model as embodied in
-informational content resulting therefrom.
-
-"Model" means any accompanying machine-learning based assemblies
-(including checkpoints), consisting of learnt weights, parameters
-(including optimizer states), corresponding to the model architecture
-as embodied in the Complementary Material, that have been trained or
-tuned, in whole or in part on the Data, using the Complementary
-Material.
-
-"Derivatives of the Model" means all modifications to the Model, works
-based on the Model, or any other model which is created or initialized
-by transfer of patterns of the weights, parameters, activations or
-output of the Model, to the other model, in order to cause the other
-model to perform similarly to the Model, including - but not limited
-to - distillation methods entailing the use of intermediate data
-representations or methods based on the generation of synthetic data
-by the Model for training the other model.
-
-"Complementary Material" means the accompanying source code and
-scripts used to define, run, load, benchmark or evaluate the Model,
-and used to prepare data for training or evaluation, if any. This
-includes any accompanying documentation, tutorials, examples, etc, if
-any.
-
-"Distribution" means any transmission, reproduction, publication or
-other sharing of the Model or Derivatives of the Model to a third
-party, including providing the Model as a hosted service made
-available by electronic or other remote means - e.g. API-based or web
-access.
-
-"Licensor" means the copyright owner or entity authorized by the
-copyright owner that is granting the License, including the persons or
-entities that may have rights in the Model and/or distributing the
-Model.
-
-"You" (or "Your") means an individual or Legal Entity exercising
-permissions granted by this License and/or making use of the Model for
-whichever purpose and in any field of use, including usage of the
-Model in an end-use application - e.g. chatbot, translator, image
-generator.
-
-"Third Parties" means individuals or legal entities that are not under
-common control with Licensor or You.
-
-"Contribution" means any work of authorship, including the original
-version of the Model and any modifications or additions to that Model
-or Derivatives of the Model thereof, that is intentionally submitted
-to Licensor for inclusion in the Model by the copyright owner or by an
-individual or Legal Entity authorized to submit on behalf of the
-copyright owner. For the purposes of this definition, "submitted"
-means any form of electronic, verbal, or written communication sent to
-the Licensor or its representatives, including but not limited to
-communication on electronic mailing lists, source code control
-systems, and issue tracking systems that are managed by, or on behalf
-of, the Licensor for the purpose of discussing and improving the
-Model, but excluding communication that is conspicuously marked or
-otherwise designated in writing by the copyright owner as "Not a
-Contribution."
-
-"Contributor" means Licensor and any individual or Legal Entity on
-behalf of whom a Contribution has been received by Licensor and
-subsequently incorporated within the Model.
-
-Section II: INTELLECTUAL PROPERTY RIGHTS
-
-Both copyright and patent grants apply to the Model, Derivatives of
-the Model and Complementary Material. The Model and Derivatives of the
-Model are subject to additional terms as described in
-
-Section III.
-
-Grant of Copyright License. Subject to the terms and conditions of
-this License, each Contributor hereby grants to You a perpetual,
-worldwide, non-exclusive, no-charge, royalty-free, irrevocable
-copyright license to reproduce, prepare, publicly display, publicly
-perform, sublicense, and distribute the Complementary Material, the
-Model, and Derivatives of the Model.
-
-Grant of Patent License. Subject to the terms and conditions of this
-License and where and as applicable, each Contributor hereby grants to
-You a perpetual, worldwide, non-exclusive, no-charge, royalty-free,
-irrevocable (except as stated in this paragraph) patent license to
-make, have made, use, offer to sell, sell, import, and otherwise
-transfer the Model and the Complementary Material, where such license
-applies only to those patent claims licensable by such Contributor
-that are necessarily infringed by their Contribution(s) alone or by
-combination of their Contribution(s) with the Model to which such
-Contribution(s) was submitted. If You institute patent litigation
-against any entity (including a cross-claim or counterclaim in a
-lawsuit) alleging that the Model and/or Complementary Material or a
-Contribution incorporated within the Model and/or Complementary
-Material constitutes direct or contributory patent infringement, then
-any patent licenses granted to You under this License for the Model
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-or filed.
-
-Section III: CONDITIONS OF USAGE, DISTRIBUTION AND REDISTRIBUTION
-
-Distribution and Redistribution. You may host for Third Party remote
-access purposes (e.g. software-as-a-service), reproduce and distribute
-copies of the Model or Derivatives of the Model thereof in any medium,
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-conditions: Use-based restrictions as referenced in paragraph 5 MUST
-be included as an enforceable provision by You in any type of legal
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-subsequent users You Distribute to, that the Model or Derivatives of
-the Model are subject to paragraph 5. This provision does not apply to
-the use of Complementary Material. You must give any Third Party
-recipients of the Model or Derivatives of the Model a copy of this
-License; You must cause any modified files to carry prominent notices
-stating that You changed the files; You must retain all copyright,
-patent, trademark, and attribution notices excluding those notices
-that do not pertain to any part of the Model, Derivatives of the
-Model. You may add Your own copyright statement to Your modifications
-and may provide additional or different license terms and conditions -
-respecting paragraph 4.a. - for use, reproduction, or Distribution of
-Your modifications, or for any such Derivatives of the Model as a
-whole, provided Your use, reproduction, and Distribution of the Model
-otherwise complies with the conditions stated in this License.
-
-Use-based restrictions. The restrictions set forth in Attachment A are
-considered Use-based restrictions. Therefore You cannot use the Model
-and the Derivatives of the Model for the specified restricted
-uses. You may use the Model subject to this License, including only
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-training, evaluating and/or reparametrizing the Model. You shall
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-Model to comply with the terms of this paragraph (paragraph 5).
-
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-no rights in the Output You generate using the Model. You are
-accountable for the Output you generate and its subsequent uses. No
-use of the output can contravene any provision as stated in the
-License.
-
-Section IV: OTHER PROVISIONS
-
-Updates and Runtime Restrictions. To the maximum extent permitted by
-law, Licensor reserves the right to restrict (remotely or otherwise)
-usage of the Model in violation of this License.
-
-Trademarks and related. Nothing in this License permits You to make
-use of Licensors’ trademarks, trade names, logos or to otherwise
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-parties; and any rights not expressly granted herein are reserved by
-the Licensors.
-
-Disclaimer of Warranty. Unless required by applicable law or agreed to
-in writing, Licensor provides the Model and the Complementary Material
-(and each Contributor provides its Contributions) on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
-implied, including, without limitation, any warranties or conditions
-of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
-PARTICULAR PURPOSE. You are solely responsible for determining the
-appropriateness of using or redistributing the Model, Derivatives of
-the Model, and the Complementary Material and assume any risks
-associated with Your exercise of permissions under this License.
-
-Limitation of Liability. In no event and under no legal theory,
-whether in tort (including negligence), contract, or otherwise, unless
-required by applicable law (such as deliberate and grossly negligent
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-for damages, including any direct, indirect, special, incidental, or
-consequential damages of any character arising as a result of this
-License or out of the use or inability to use the Model and the
-Complementary Material (including but not limited to damages for loss
-of goodwill, work stoppage, computer failure or malfunction, or any
-and all other commercial damages or losses), even if such Contributor
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-
-Accepting Warranty or Additional Liability. While redistributing the
-Model, Derivatives of the Model and the Complementary Material
-thereof, You may choose to offer, and charge a fee for, acceptance of
-support, warranty, indemnity, or other liability obligations and/or
-rights consistent with this License. However, in accepting such
-obligations, You may act only on Your own behalf and on Your sole
-responsibility, not on behalf of any other Contributor, and only if
-You agree to indemnify, defend, and hold each Contributor harmless for
-any liability incurred by, or claims asserted against, such
-Contributor by reason of your accepting any such warranty or
-additional liability.
-
-If any provision of this License is held to be invalid, illegal or
-unenforceable, the remaining provisions shall be unaffected thereby
-and remain valid as if such provision had not been set forth herein.
-
-
-END OF TERMS AND CONDITIONS
-
-Attachment A
-
-Use Restrictions
-
-You agree not to use the Model or Derivatives of the Model:
-
-* In any way that violates any applicable national, federal, state,
-local or international law or regulation;
-
-* For the purpose of exploiting, harming or attempting to exploit or
-harm minors in any way;
-
-* To generate or disseminate verifiably false information and/or
-  content with the purpose of harming others;
-
-* To generate or disseminate personal identifiable information that
-  can be used to harm an individual;
-
-* To defame, disparage or otherwise harass others;
-
-* For fully automated decision making that adversely impacts an
-  individual’s legal rights or otherwise creates or modifies a
-  binding, enforceable obligation;
-
-* For any use intended to or which has the effect of discriminating
-  against or harming individuals or groups based on online or offline
-  social behavior or known or predicted personal or personality
-  characteristics;
-
-* To exploit any of the vulnerabilities of a specific group of persons
-  based on their age, social, physical or mental characteristics, in
-  order to materially distort the behavior of a person pertaining to
-  that group in a manner that causes or is likely to cause that person
-  or another person physical or psychological harm;
-
-* For any use intended to or which has the effect of discriminating
-  against individuals or groups based on legally protected
-  characteristics or categories;
-
-* To provide medical advice and medical results interpretation;
-
-* To generate or disseminate information for the purpose to be used
-  for administration of justice, law enforcement, immigration or
-  asylum processes, such as predicting an individual will commit
-  fraud/crime commitment (e.g. by text profiling, drawing causal
-  relationships between assertions made in documents, indiscriminate
-  and arbitrarily-targeted use).
-

Makefile

@@ -1,72 +0,0 @@
-# simple Makefile with scripts that are otherwise hard to remember
-# to use, run from the repo root `make <command>`
-
-default: help
-
-help:
-	@echo Developer commands:
-	@echo
-	@echo "ruff                     Run ruff, fixing any safely-fixable errors and formatting"
-	@echo "ruff-unsafe              Run ruff, fixing all fixable errors and formatting"
-	@echo "mypy                     Run mypy using the config in pyproject.toml to identify type mismatches and other coding errors"
-	@echo "mypy-all                 Run mypy ignoring the config in pyproject.tom but still ignoring missing imports"
-	@echo "test                     Run the unit tests."
-	@echo "update-config-docstring  Update the app's config docstring so mkdocs can autogenerate it correctly."
-	@echo "frontend-install         Install the pnpm modules needed for the front end"
-	@echo "frontend-build           Build the frontend in order to run on localhost:9090"
-	@echo "frontend-dev             Run the frontend in developer mode on localhost:5173"
-	@echo "frontend-typegen         Generate types for the frontend from the OpenAPI schema"
-	@echo "installer-zip            Build the installer .zip file for the current version"
-	@echo "tag-release              Tag the GitHub repository with the current version (use at release time only!)"
-
-# Runs ruff, fixing any safely-fixable errors and formatting
-ruff:
-	ruff check . --fix
-	ruff format .
-
-# Runs ruff, fixing all errors it can fix and formatting
-ruff-unsafe:
-	ruff check . --fix --unsafe-fixes
-	ruff format .
-
-# Runs mypy, using the config in pyproject.toml
-mypy:
-	mypy scripts/invokeai-web.py
-
-# Runs mypy, ignoring the config in pyproject.toml but still ignoring missing (untyped) imports
-# (many files are ignored by the config, so this is useful for checking all files)
-mypy-all:
-	mypy scripts/invokeai-web.py --config-file= --ignore-missing-imports
-
-# Run the unit tests
-test:
-	pytest ./tests
-
-# Update config docstring
-update-config-docstring:
-	python scripts/update_config_docstring.py
-
-# Install the pnpm modules needed for the front end
-frontend-install:
-	rm -rf invokeai/frontend/web/node_modules
-	cd invokeai/frontend/web && pnpm install
-
-# Build the frontend
-frontend-build:
-	cd invokeai/frontend/web && pnpm build
-
-# Run the frontend in dev mode
-frontend-dev:
-	cd invokeai/frontend/web && pnpm dev
-
-frontend-typegen:
-	cd invokeai/frontend/web && python ../../../scripts/generate_openapi_schema.py | pnpm typegen
-
-# Installer zip file
-installer-zip:
-	cd installer && ./create_installer.sh
-
-# Tag the release
-tag-release:
-	cd installer && ./tag_release.sh
-

README.md

@@ -1,10 +1,10 @@
 <div align="center">
 
-![project hero](https://github.com/invoke-ai/InvokeAI/assets/31807370/6e3728c7-e90e-4711-905c-3b55844ff5be)
+![project hero](https://github.com/invoke-ai/InvokeAI/assets/31807370/1a917d94-e099-4fa1-a70f-7dd8d0691018)
 
-# Invoke - Professional Creative AI Tools for Visual Media 
-##  To learn more about Invoke, or implement our Business solutions, visit [invoke.com](https://www.invoke.com/about)
-  
+# Invoke AI - Generative AI for Professional Creatives
+## Image Generation for Stable Diffusion, Custom-Trained Models, and more. 
+  Learn more about us and get started instantly at [invoke.ai](https://invoke.ai)
 
 
 [![discord badge]][discord link]
@@ -36,6 +36,15 @@
 
 </div>
 
+_**Note: This is an alpha release. Bugs are expected and not all
+features are fully implemented. Please use the GitHub [Issues
+pages](https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen)
+to report unexpected problems. Also note that InvokeAI root directory
+which contains models, outputs and configuration files, has changed
+between the 2.x and 3.x release. If you wish to use your v2.3 root
+directory with v3.0, please follow the directions in [Migrating a 2.3
+root directory to 3.0](#migrating-to-3).**_
+
 InvokeAI is a leading creative engine built to empower professionals
 and enthusiasts alike. Generate and create stunning visual media using
 the latest AI-driven technologies. InvokeAI offers an industry leading
@@ -43,22 +52,20 @@ Web Interface, interactive Command Line Interface, and also serves as
 the foundation for multiple commercial products.
 
 **Quick links**: [[How to
-  Install](https://invoke-ai.github.io/InvokeAI/installation/INSTALLATION/)] [<a
+  Install](https://invoke-ai.github.io/InvokeAI/#installation)] [<a
   href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a
   href="https://invoke-ai.github.io/InvokeAI/">Documentation and
-  Tutorials</a>]
-  [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>]
+  Tutorials</a>] [<a
+  href="https://github.com/invoke-ai/InvokeAI/">Code and
+  Downloads</a>] [<a
+  href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>]
   [<a
   href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion,
-  Ideas & Q&A</a>] 
-   [<a
-  href="https://invoke-ai.github.io/InvokeAI/contributing/CONTRIBUTING/">Contributing</a>] 
+  Ideas & Q&A</a>]
 
 <div align="center">
 
-
-![Highlighted Features - Canvas and Workflows](https://github.com/invoke-ai/InvokeAI/assets/31807370/708f7a82-084f-4860-bfbe-e2588c53548d)
-
+![canvas preview](https://github.com/invoke-ai/InvokeAI/raw/main/docs/assets/canvas_preview.png)
 
 </div>
 
@@ -83,7 +90,7 @@ Table of Contents 📝
 ## Quick Start
 
 For full installation and upgrade instructions, please see:
-[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/INSTALLATION/)
+[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/)
 
 If upgrading from version 2.3, please read [Migrating a 2.3 root
 directory to 3.0](#migrating-to-3) first.
@@ -125,10 +132,8 @@ and go to http://localhost:9090.
 
 ### Command-Line Installation (for developers and users familiar with Terminals)
 
-You must have Python 3.10 through 3.11 installed on your machine. Earlier or
-later versions are not supported.
-Node.js also needs to be installed along with `pnpm` (can be installed with
-the command `npm install -g pnpm` if needed)
+You must have Python 3.9 or 3.10 installed on your machine. Earlier or later versions are
+not supported.
 
 1. Open a command-line window on your machine. The PowerShell is recommended for Windows.
 2. Create a directory to install InvokeAI into. You'll need at least 15 GB of free space:
@@ -163,13 +168,13 @@ the command `npm install -g pnpm` if needed)
     _For Windows/Linux with an NVIDIA GPU:_
 
     ```terminal
-    pip install "InvokeAI[xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu121
+    pip install "InvokeAI[xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu117
     ```
 
     _For Linux with an AMD GPU:_
 
     ```sh
-    pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.6
+    pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.4.2
     ```
 
     _For non-GPU systems:_
@@ -177,7 +182,7 @@ the command `npm install -g pnpm` if needed)
     pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/cpu
     ``` 
 
-    _For Macintoshes, either Intel or M1/M2/M3:_
+    _For Macintoshes, either Intel or M1/M2:_
 
     ```sh
     pip install InvokeAI --use-pep517
@@ -186,18 +191,16 @@ the command `npm install -g pnpm` if needed)
 6. Configure InvokeAI and install a starting set of image generation models (you only need to do this once):
 
     ```terminal
-    invokeai-configure --root .
+    invokeai-configure
     ```
-	Don't miss the dot at the end!
 
 7. Launch the web server (do it every time you run InvokeAI):
 
     ```terminal
-    invokeai-web
+    invokeai --web
     ```
 
 8. Point your browser to http://localhost:9090 to bring up the web interface.
-
 9. Type `banana sushi` in the box on the top left and click `Invoke`.
 
 Be sure to activate the virtual environment each time before re-launching InvokeAI,
@@ -252,27 +255,22 @@ old models directory (which contains the models selected at install
 time) will be renamed `models.orig` and can be deleted once you have
 confirmed that the migration was successful.
 
- If you wish, you can pass the 2.3 root directory to both `--from` and
-`--to` in order to update in place. Warning: this directory will no
-longer be usable with InvokeAI 2.3.
-
 #### Migrating in place
 
 For the adventurous, you may do an in-place upgrade from 2.3 to 3.0
-without touching the command line. ***This recipe does not work on
-Windows platforms due to a bug in the Windows version of the 2.3
-upgrade script.** See the next section for a Windows recipe.
-
-##### For Mac and Linux Users:
+without touching the command line. The recipe is as follows>
 
 1. Launch the InvokeAI launcher script in your current v2.3 root directory.
 
 2. Select option [9] "Update InvokeAI" to bring up the updater dialog.
 
-3. Select option [1] to upgrade to the latest release.
+3a. During the alpha release phase, select option [3] and manually
+enter the tag name `v3.0.0+a2`.
+
+3b. Once 3.0 is released, 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 [6] "Re-run the configure script to fix a broken
+menu. Select option [7] "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
@@ -288,50 +286,14 @@ worked, you can safely remove these files. Alternatively you can
 restore a working v2.3 directory by removing the new files and
 restoring the ".orig" files' original names.
 
-##### For Windows Users:
-
-Windows Users can upgrade with the
-
-1. Enter the 2.3 root directory you wish to upgrade
-2. Launch `invoke.sh` or `invoke.bat`
-3. Select the "Developer's console" option [8]
-4. Type the following commands
-
-```
-pip install "invokeai @ https://github.com/invoke-ai/InvokeAI/archive/refs/tags/v3.0.0" --use-pep517 --upgrade
-invokeai-configure --root .
-```
-(Replace `v3.0.0` with the current release number if this document is out of date).
-
-The first command will install and upgrade new software to run
-InvokeAI. The second will prepare the 2.3 directory for use with 3.0.
-You may now launch the WebUI in the usual way, by selecting option [1]
-from the launcher script
-
-#### Migrating Images
+#### Migration Caveats
 
 The migration script will migrate your invokeai settings and models,
 including textual inversion models, LoRAs and merges that you may have
 installed previously. However it does **not** migrate the generated
-images stored in your 2.3-format outputs directory. To do this, you 
-need to run an additional step:
-
-1. From a working InvokeAI 3.0 root directory, start the launcher and
-enter menu option [8] to open the "developer's console".
-
-2. At the developer's console command line, type the command:
-
-```bash
-invokeai-import-images
-```
-
-3. This will lead you through the process of confirming the desired
-   source and destination for the imported images. The images will
-   appear in the gallery board of your choice, and contain the
-   original prompt, model name, and other parameters used to generate
-   the image.
-   
-(Many kudos to **techjedi** for contributing this script.)
+images stored in your 2.3-format outputs directory. The released
+version of 3.0 is expected to have an interface for importing an
+entire directory of image files as a batch.
 
 ## Hardware Requirements
 
@@ -343,12 +305,9 @@ AMD card (using the ROCm driver).
 
 You will need one of the following:
 
-- An NVIDIA-based graphics card with 4 GB or more VRAM memory. 6-8 GB
-  of VRAM is highly recommended for rendering using the Stable
-  Diffusion XL models
+- An NVIDIA-based graphics card with 4 GB or more VRAM memory.
 - An Apple computer with an M1 chip.
-- An AMD-based graphics card with 4GB or more VRAM memory (Linux
-  only), 6-8 GB for XL rendering.
+- An AMD-based graphics card with 4GB or more VRAM memory. (Linux only)
 
 We do not recommend the GTX 1650 or 1660 series video cards. They are
 unable to run in half-precision mode and do not have sufficient VRAM
@@ -370,24 +329,24 @@ InvokeAI offers a locally hosted Web Server & React Frontend, with an industry l
 
 The Unified Canvas is a fully integrated canvas implementation with support for all core generation capabilities, in/outpainting, brush tools, and more. This creative tool unlocks the capability for artists to create with AI as a creative collaborator, and can be used to augment AI-generated imagery, sketches, photography, renders, and more.
 
-### *Workflows & Nodes*
+### *Advanced Prompt Syntax*
 
-InvokeAI offers a fully featured workflow management solution, enabling users to combine the power of nodes based workflows with the easy of a UI. This allows for customizable generation pipelines to be developed and shared by users looking to create specific workflows to support their production use-cases.
+Invoke AI's advanced prompt syntax allows for token weighting, cross-attention control, and prompt blending, allowing for fine-tuned tweaking of your invocations and exploration of the latent space. 
 
-### *Board & Gallery Management*
+### *Command Line Interface*
 
-Invoke AI provides an organized gallery system for easily storing, accessing, and remixing your content in the Invoke workspace. Images can be dragged/dropped onto any Image-base UI element in the application, and rich metadata within the Image allows for easy recall of key prompts or settings used in your workflow. 
+For users utilizing a terminal-based environment, or who want to take advantage of CLI features, InvokeAI offers an extensive and actively supported command-line interface that provides the full suite of generation functionality available in the tool.
 
 ### Other features
 
 - *Support for both ckpt and diffusers models*
-- *SD 2.0, 2.1, XL support*
-- *Upscaling Tools*
+- *SD 2.0, 2.1 support*
+- *Upscaling & Face Restoration Tools*
 - *Embedding Manager & Support*
 - *Model Manager & Support*
-- *Workflow creation & management*
 - *Node-Based Architecture*
-
+- *Node-Based Plug-&-Play UI (Beta)*
+- *Boards & Gallery Management
 
 ### Latest Changes
 
@@ -395,21 +354,23 @@ For our latest changes, view our [Release
 Notes](https://github.com/invoke-ai/InvokeAI/releases) and the
 [CHANGELOG](docs/CHANGELOG.md).
 
-### Troubleshooting / FAQ
+### Troubleshooting
 
-Please check out our **[FAQ](https://invoke-ai.github.io/InvokeAI/help/FAQ/)** to get solutions for common installation
-problems and other issues. For more help, please join our [Discord][discord link]
+Please check out our **[Q&A](https://invoke-ai.github.io/InvokeAI/help/TROUBLESHOOT/#faq)** to get solutions for common installation
+problems and other issues.
 
-## Contributing
+## 🤝 Contributing
 
 Anyone who wishes to contribute to this project, whether documentation, features, bug fixes, code
 cleanup, testing, or code reviews, is very much encouraged to do so.
 
-Get started with contributing by reading our [Contribution documentation](https://invoke-ai.github.io/InvokeAI/contributing/CONTRIBUTING/), joining the [#dev-chat](https://discord.com/channels/1020123559063990373/1049495067846524939) or the GitHub discussion board.
+To join, just raise your hand on the InvokeAI Discord server (#dev-chat) or the GitHub discussion board.
+
+If you'd like to help with translation, please see our [translation guide](docs/other/TRANSLATION.md).
 
 If you are unfamiliar with how
-to contribute to GitHub projects, we have a new contributor checklist you can follow to get started contributing: 
-[New Contributor Checklist](https://invoke-ai.github.io/InvokeAI/contributing/contribution_guides/newContributorChecklist/).
+to contribute to GitHub projects, here is a
+[Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github). A full set of contribution guidelines, along with templates, are in progress. You can **make your pull request against the "main" branch**.
 
 We hope you enjoy using our software as much as we enjoy creating it,
 and we hope that some of those of you who are reading this will elect
@@ -417,7 +378,7 @@ to become part of our community.
 
 Welcome to InvokeAI!
 
-### Contributors
+### 👥 Contributors
 
 This fork is a combined effort of various people from across the world.
 [Check out the list of all these amazing people](https://invoke-ai.github.io/InvokeAI/other/CONTRIBUTORS/). We thank them for
@@ -425,7 +386,7 @@ their time, hard work and effort.
 
 ### Support
 
-For support, please use this repository's GitHub Issues tracking service, or join the [Discord][discord link].
+For support, please use this repository's GitHub Issues tracking service, or join the Discord.
 
 Original portions of the software are Copyright (c) 2023 by respective contributors.
 

docker/.env.sample

@@ -1,26 +0,0 @@
-## Make a copy of this file named `.env` and fill in the values below.
-## Any environment variables supported by InvokeAI can be specified here,
-## in addition to the examples below.
-
-## INVOKEAI_ROOT is the path *on the host system* where Invoke will store its data.
-## It is mounted into the container and allows both containerized and non-containerized usage of Invoke.
-# Usually this is the only variable you need to set. It can be relative or absolute.
-# INVOKEAI_ROOT=~/invokeai
-
-## HOST_INVOKEAI_ROOT and CONTAINER_INVOKEAI_ROOT can be used to control the on-host
-## and in-container paths separately, if needed.
-## HOST_INVOKEAI_ROOT is the path on the docker host's filesystem where Invoke will store data.
-## If relative, it will be relative to the docker directory in which the docker-compose.yml file is located
-## CONTAINER_INVOKEAI_ROOT is the path within the container where Invoke will expect to find the runtime directory.
-## It MUST be absolute. There is usually no need to change this.
-# HOST_INVOKEAI_ROOT=../../invokeai-data
-# CONTAINER_INVOKEAI_ROOT=/invokeai
-
-## INVOKEAI_PORT is the port on which the InvokeAI web interface will be available
-# INVOKEAI_PORT=9090
-
-## GPU_DRIVER can be set to either `nvidia` or `rocm` to enable GPU support in the container accordingly.
-# GPU_DRIVER=nvidia #| rocm
-
-## CONTAINER_UID can be set to the UID of the user on the host system that should own the files in the container.
-# CONTAINER_UID=1000

docker/Dockerfile

@@ -1,123 +1,107 @@
-# syntax=docker/dockerfile:1.4
+# syntax=docker/dockerfile:1
 
-## Builder stage
+ARG PYTHON_VERSION=3.9
+##################
+##  base image  ##
+##################
+FROM --platform=${TARGETPLATFORM} python:${PYTHON_VERSION}-slim AS python-base
 
-FROM library/ubuntu:23.04 AS builder
+LABEL org.opencontainers.image.authors="mauwii@outlook.de"
 
-ARG DEBIAN_FRONTEND=noninteractive
-RUN rm -f /etc/apt/apt.conf.d/docker-clean; echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
-    --mount=type=cache,target=/var/lib/apt,sharing=locked \
-    apt update && apt-get install -y \
-        git \
-        python3-venv \
-        python3-pip \
-        build-essential
+# Prepare apt for buildkit cache
+RUN rm -f /etc/apt/apt.conf.d/docker-clean \
+  && echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' >/etc/apt/apt.conf.d/keep-cache
 
-ENV INVOKEAI_SRC=/opt/invokeai
-ENV VIRTUAL_ENV=/opt/venv/invokeai
+# Install dependencies
+RUN \
+  --mount=type=cache,target=/var/cache/apt,sharing=locked \
+  --mount=type=cache,target=/var/lib/apt,sharing=locked \
+  apt-get update \
+  && apt-get install -y \
+    --no-install-recommends \
+    libgl1-mesa-glx=20.3.* \
+    libglib2.0-0=2.66.* \
+    libopencv-dev=4.5.*
 
-ENV PATH="$VIRTUAL_ENV/bin:$PATH"
-ARG GPU_DRIVER=cuda
-ARG TARGETPLATFORM="linux/amd64"
-# unused but available
-ARG BUILDPLATFORM
+# Set working directory and env
+ARG APPDIR=/usr/src
+ARG APPNAME=InvokeAI
+WORKDIR ${APPDIR}
+ENV PATH ${APPDIR}/${APPNAME}/bin:$PATH
+# Keeps Python from generating .pyc files in the container
+ENV PYTHONDONTWRITEBYTECODE 1
+# Turns off buffering for easier container logging
+ENV PYTHONUNBUFFERED 1
+# Don't fall back to legacy build system
+ENV PIP_USE_PEP517=1
 
-WORKDIR ${INVOKEAI_SRC}
+#######################
+##  build pyproject  ##
+#######################
+FROM python-base AS pyproject-builder
 
-COPY invokeai ./invokeai
-COPY pyproject.toml ./
+# Install build dependencies
+RUN \
+  --mount=type=cache,target=/var/cache/apt,sharing=locked \
+  --mount=type=cache,target=/var/lib/apt,sharing=locked \
+  apt-get update \
+  && apt-get install -y \
+    --no-install-recommends \
+    build-essential=12.9 \
+    gcc=4:10.2.* \
+    python3-dev=3.9.*
 
-# Editable mode helps use the same image for development:
-# the local working copy can be bind-mounted into the image
-# at path defined by ${INVOKEAI_SRC}
-# NOTE: there are no pytorch builds for arm64 + cuda, only cpu
-# x86_64/CUDA is default
-RUN --mount=type=cache,target=/root/.cache/pip \
-    python3 -m venv ${VIRTUAL_ENV} &&\
-    if [ "$TARGETPLATFORM" = "linux/arm64" ] || [ "$GPU_DRIVER" = "cpu" ]; then \
-        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cpu"; \
-    elif [ "$GPU_DRIVER" = "rocm" ]; then \
-        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/rocm5.6"; \
-    else \
-        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cu121"; \
-    fi &&\
+# Prepare pip for buildkit cache
+ARG PIP_CACHE_DIR=/var/cache/buildkit/pip
+ENV PIP_CACHE_DIR ${PIP_CACHE_DIR}
+RUN mkdir -p ${PIP_CACHE_DIR}
 
-    # xformers + triton fails to install on arm64
-    if [ "$GPU_DRIVER" = "cuda" ] && [ "$TARGETPLATFORM" = "linux/amd64" ]; then \
-        pip install $extra_index_url_arg -e ".[xformers]"; \
-    else \
-        pip install $extra_index_url_arg -e "."; \
-    fi
+# Create virtual environment
+RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
+  python3 -m venv "${APPNAME}" \
+  --upgrade-deps
 
-# #### Build the Web UI ------------------------------------
+# Install requirements
+COPY --link pyproject.toml .
+COPY --link invokeai/version/invokeai_version.py invokeai/version/__init__.py invokeai/version/
+ARG PIP_EXTRA_INDEX_URL
+ENV PIP_EXTRA_INDEX_URL ${PIP_EXTRA_INDEX_URL}
+RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
+  "${APPNAME}"/bin/pip install .
 
-FROM node:20-slim AS web-builder
-ENV PNPM_HOME="/pnpm"
-ENV PATH="$PNPM_HOME:$PATH"
-RUN corepack enable
+# Install pyproject.toml
+COPY --link . .
+RUN --mount=type=cache,target=${PIP_CACHE_DIR} \
+  "${APPNAME}/bin/pip" install .
 
-WORKDIR /build
-COPY invokeai/frontend/web/ ./
-RUN --mount=type=cache,target=/pnpm/store \
-    pnpm install --frozen-lockfile
-RUN npx vite build
-
-#### Runtime stage ---------------------------------------
-
-FROM library/ubuntu:23.04 AS runtime
-
-ARG DEBIAN_FRONTEND=noninteractive
-ENV PYTHONUNBUFFERED=1
-ENV PYTHONDONTWRITEBYTECODE=1
-
-RUN apt update && apt install -y --no-install-recommends \
-        git \
-        curl \
-        vim \
-        tmux \
-        ncdu \
-        iotop \
-        bzip2 \
-        gosu \
-        magic-wormhole \
-        libglib2.0-0 \
-        libgl1-mesa-glx \
-        python3-venv \
-        python3-pip \
-        build-essential \
-        libopencv-dev \
-        libstdc++-10-dev &&\
-    apt-get clean && apt-get autoclean
-
-
-ENV INVOKEAI_SRC=/opt/invokeai
-ENV VIRTUAL_ENV=/opt/venv/invokeai
-ENV INVOKEAI_ROOT=/invokeai
-ENV INVOKEAI_HOST=0.0.0.0
-ENV INVOKEAI_PORT=9090
-ENV PATH="$VIRTUAL_ENV/bin:$INVOKEAI_SRC:$PATH"
-ENV CONTAINER_UID=${CONTAINER_UID:-1000}
-ENV CONTAINER_GID=${CONTAINER_GID:-1000}
-
-# --link requires buldkit w/ dockerfile syntax 1.4
-COPY --link --from=builder ${INVOKEAI_SRC} ${INVOKEAI_SRC}
-COPY --link --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
-COPY --link --from=web-builder /build/dist ${INVOKEAI_SRC}/invokeai/frontend/web/dist
-
-# Link amdgpu.ids for ROCm builds
-# contributed by https://github.com/Rubonnek
-RUN mkdir -p "/opt/amdgpu/share/libdrm" &&\
-  ln -s "/usr/share/libdrm/amdgpu.ids" "/opt/amdgpu/share/libdrm/amdgpu.ids"
-
-WORKDIR ${INVOKEAI_SRC}
-
-# build patchmatch
-RUN cd /usr/lib/$(uname -p)-linux-gnu/pkgconfig/ && ln -sf opencv4.pc opencv.pc
+# Build patchmatch
 RUN python3 -c "from patchmatch import patch_match"
 
-RUN mkdir -p ${INVOKEAI_ROOT} && chown -R ${CONTAINER_UID}:${CONTAINER_GID} ${INVOKEAI_ROOT}
+#####################
+##  runtime image  ##
+#####################
+FROM python-base AS runtime
 
-COPY docker/docker-entrypoint.sh ./
-ENTRYPOINT ["/opt/invokeai/docker-entrypoint.sh"]
-CMD ["invokeai-web"]
+# Create a new user
+ARG UNAME=appuser
+RUN useradd \
+  --no-log-init \
+  -m \
+  -U \
+  "${UNAME}"
+
+# Create volume directory
+ARG VOLUME_DIR=/data
+RUN mkdir -p "${VOLUME_DIR}" \
+  && chown -hR "${UNAME}:${UNAME}" "${VOLUME_DIR}"
+
+# Setup runtime environment
+USER ${UNAME}:${UNAME}
+COPY --chown=${UNAME}:${UNAME} --from=pyproject-builder ${APPDIR}/${APPNAME} ${APPNAME}
+ENV INVOKEAI_ROOT ${VOLUME_DIR}
+ENV TRANSFORMERS_CACHE ${VOLUME_DIR}/.cache
+ENV INVOKE_MODEL_RECONFIGURE "--yes --default_only"
+EXPOSE 9090
+ENTRYPOINT [ "invokeai" ]
+CMD [ "--web", "--host", "0.0.0.0", "--port", "9090" ]
+VOLUME [ "${VOLUME_DIR}" ]

docker/README.md

@@ -1,88 +0,0 @@
-# InvokeAI Containerized
-
-All commands should be run within the `docker` directory: `cd docker`
-
-## Quickstart :rocket:
-
-On a known working Linux+Docker+CUDA (Nvidia) system, execute `./run.sh` in this directory. It will take a few minutes - depending on your internet speed - to install the core models. Once the application starts up, open `http://localhost:9090` in your browser to Invoke!
-
-For more configuration options (using an AMD GPU, custom root directory location, etc): read on.
-
-## Detailed setup
-
-#### Linux
-
-1. Ensure builkit is enabled in the Docker daemon settings (`/etc/docker/daemon.json`)
-2. Install the `docker compose` plugin using your package manager, or follow a [tutorial](https://docs.docker.com/compose/install/linux/#install-using-the-repository).
-    - The deprecated `docker-compose` (hyphenated) CLI continues to work for now.
-3. Ensure docker daemon is able to access the GPU.
-    - You may need to install [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
-
-#### macOS
-
-1. Ensure Docker has at least 16GB RAM
-2. Enable VirtioFS for file sharing
-3. Enable `docker compose` V2 support
-
-This is done via Docker Desktop preferences
-
-### Configure Invoke environment
-
-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. Execute `run.sh`
-
-The image will be built automatically if needed.
-
-The runtime directory (holding models and outputs) will be created in the location specified by `INVOKEAI_ROOT`. The default location is `~/invokeai`. The runtime directory will be populated with the base configs and models necessary to start generating.
-
-### Use a GPU
-
-- Linux is *recommended* for GPU support in Docker.
-- WSL2 is *required* for Windows.
-- only `x86_64` architecture is supported.
-
-The Docker daemon on the system must be already set up to use the GPU. In case of Linux, this involves installing `nvidia-docker-runtime` and configuring the `nvidia` runtime as default. Steps will be different for AMD. Please see Docker documentation for the most up-to-date instructions for using your GPU with Docker.
-
-To use an AMD GPU, set `GPU_DRIVER=rocm` in your `.env` file.
-
-## 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 `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.
-
-Values are optional, but setting `INVOKEAI_ROOT` is highly recommended. The default is `~/invokeai`. Example:
-
-```bash
-INVOKEAI_ROOT=/Volumes/WorkDrive/invokeai
-HUGGINGFACE_TOKEN=the_actual_token
-CONTAINER_UID=1000
-GPU_DRIVER=nvidia
-```
-
-Any environment variables supported by InvokeAI can be set here - please see the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.
-
-## Even Moar Customizing!
-
-See the `docker-compose.yml` file. The `command` instruction can be uncommented and used to run arbitrary startup commands. Some examples below.
-
-### Reconfigure the runtime directory
-
-Can be used to download additional models from the supported model list
-
-In conjunction with `INVOKEAI_ROOT` can be also used to initialize a runtime directory
-
-```yaml
-command:
-  - invokeai-configure
-  - --yes
-```
-
-Or install models:
-
-```yaml
-command:
-  - invokeai-model-install
-```

docker/build.sh

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

docker/docker-compose.yml

@@ -1,56 +0,0 @@
-# Copyright (c) 2023 Eugene Brodsky https://github.com/ebr
-
-version: '3.8'
-
-x-invokeai: &invokeai
-    image: "local/invokeai:latest"
-    build:
-      context: ..
-      dockerfile: docker/Dockerfile
-
-    # Create a .env file in the same directory as this docker-compose.yml file
-    # and populate it with environment variables. See .env.sample
-    env_file:
-      - .env
-
-    # variables without a default will automatically inherit from the host environment
-    environment:
-      # if set, CONTAINER_INVOKEAI_ROOT will override the Invoke runtime directory location *inside* the container
-      - INVOKEAI_ROOT=${CONTAINER_INVOKEAI_ROOT:-/invokeai}
-      - HF_HOME
-    ports:
-      - "${INVOKEAI_PORT:-9090}:${INVOKEAI_PORT:-9090}"
-    volumes:
-      - type: bind
-        source: ${HOST_INVOKEAI_ROOT:-${INVOKEAI_ROOT:-~/invokeai}}
-        target: ${CONTAINER_INVOKEAI_ROOT:-/invokeai}
-        bind:
-          create_host_path: true
-      - ${HF_HOME:-~/.cache/huggingface}:${HF_HOME:-/invokeai/.cache/huggingface}
-    tty: true
-    stdin_open: true
-
-
-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/docker-entrypoint.sh

@@ -1,41 +0,0 @@
-#!/bin/bash
-set -e -o pipefail
-
-### Container entrypoint
-# Runs the CMD as defined by the Dockerfile or passed to `docker run`
-# Can be used to configure the runtime dir
-# Bypass by using ENTRYPOINT or `--entrypoint`
-
-### Set INVOKEAI_ROOT pointing to a valid runtime directory
-# Otherwise configure the runtime dir first.
-
-### Set the CONTAINER_UID envvar to match your user.
-# Ensures files created in the container are owned by you:
-#   docker run --rm -it -v /some/path:/invokeai -e CONTAINER_UID=$(id -u) <this image>
-# Default UID: 1000 chosen due to popularity on Linux systems. Possibly 501 on MacOS.
-
-USER_ID=${CONTAINER_UID:-1000}
-USER=ubuntu
-usermod -u ${USER_ID} ${USER} 1>/dev/null
-
-### Set the $PUBLIC_KEY env var to enable SSH access.
-# We do not install openssh-server in the image by default to avoid bloat.
-# but it is useful to have the full SSH server e.g. on Runpod.
-# (use SCP to copy files to/from the image, etc)
-if [[ -v "PUBLIC_KEY" ]] && [[ ! -d "${HOME}/.ssh" ]]; then
-    apt-get update
-    apt-get install -y openssh-server
-    pushd "$HOME"
-    mkdir -p .ssh
-    echo "${PUBLIC_KEY}" > .ssh/authorized_keys
-    chmod -R 700 .ssh
-    popd
-    service ssh start
-fi
-
-mkdir -p "${INVOKEAI_ROOT}"
-chown --recursive ${USER} "${INVOKEAI_ROOT}"
-cd "${INVOKEAI_ROOT}"
-
-# Run the CMD as the Container User (not root).
-exec gosu ${USER} "$@"

docker/env.sh

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

docker/run.sh

@@ -1,32 +1,41 @@
 #!/usr/bin/env bash
-set -e -o pipefail
+set -e
 
-run() {
-  local scriptdir=$(dirname "${BASH_SOURCE[0]}")
-  cd "$scriptdir" || exit 1
+# How to use: https://invoke-ai.github.io/InvokeAI/installation/040_INSTALL_DOCKER/
 
-  local build_args=""
-  local profile=""
+SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
+cd "$SCRIPTDIR" || exit 1
 
-  touch .env
-  build_args=$(awk '$1 ~ /=[^$]/ && $0 !~ /^#/ {print "--build-arg " $0 " "}' .env) &&
-  profile="$(awk -F '=' '/GPU_DRIVER/ {print $2}' .env)"
+source ./env.sh
 
-  [[ -z "$profile" ]] && profile="nvidia"
+# Create outputs directory if it does not exist
+[[ -d ./outputs ]] || mkdir ./outputs
 
-  local service_name="invokeai-$profile"
+echo -e "You are using these values:\n"
+echo -e "Volumename:\t${VOLUMENAME}"
+echo -e "Invokeai_tag:\t${CONTAINER_IMAGE}"
+echo -e "local Models:\t${MODELSPATH:-unset}\n"
 
-  if [[ ! -z "$build_args" ]]; then
-    printf "%s\n" "docker compose build args:"
-    printf "%s\n" "$build_args"
+docker run \
+  --interactive \
+  --tty \
+  --rm \
+  --platform="${PLATFORM}" \
+  --name="${REPOSITORY_NAME}" \
+  --hostname="${REPOSITORY_NAME}" \
+  --mount type=volume,volume-driver=local,source="${VOLUMENAME}",target=/data \
+  --mount type=bind,source="$(pwd)"/outputs/,target=/data/outputs/ \
+  ${MODELSPATH:+--mount="type=bind,source=${MODELSPATH},target=/data/models"} \
+  ${HUGGING_FACE_HUB_TOKEN:+--env="HUGGING_FACE_HUB_TOKEN=${HUGGING_FACE_HUB_TOKEN}"} \
+  --publish=9090:9090 \
+  --cap-add=sys_nice \
+  ${GPU_FLAGS:+--gpus="${GPU_FLAGS}"} \
+  "${CONTAINER_IMAGE}" ${@:+$@}
+
+echo -e "\nCleaning trash folder ..."
+for f in outputs/.Trash*; do
+  if [ -e "$f" ]; then
+    rm -Rf "$f"
+    break
   fi
-
-  docker compose build $build_args $service_name
-  unset build_args
-
-  printf "%s\n" "starting service $service_name"
-  docker compose --profile "$profile" up -d "$service_name"
-  docker compose logs -f
-}
-
-run
+done

docker/runpod-readme.md

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

docs/CHANGELOG.md

@@ -488,7 +488,7 @@ sections describe what's new for InvokeAI.
 
 - A choice of installer scripts that automate installation and configuration.
   See
-  [Installation](installation/INSTALLATION.md).
+  [Installation](installation/index.md).
 - A streamlined manual installation process that works for both Conda and
   PIP-only installs. See
   [Manual Installation](installation/020_INSTALL_MANUAL.md).
@@ -617,6 +617,8 @@ sections describe what's new for InvokeAI.
 - `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains for
   backward compatibility.
 - Completely new WebGUI - launch with `python3 scripts/invoke.py --web`
+- Support for [inpainting](deprecated/INPAINTING.md) and
+  [outpainting](features/OUTPAINTING.md)
 - img2img runs on all k\* samplers
 - Support for
   [negative prompts](features/PROMPTS.md#negative-and-unconditioned-prompts)
@@ -657,7 +659,7 @@ sections describe what's new for InvokeAI.
 
 ## v1.13 <small>(3 September 2022)</small>
 
-- Support image variations (see [VARIATIONS](deprecated/VARIATIONS.md)
+- Support image variations (see [VARIATIONS](features/VARIATIONS.md)
   ([Kevin Gibbons](https://github.com/bakkot) and many contributors and
   reviewers)
 - Supports a Google Colab notebook for a standalone server running on Google

docs/RELEASE.md

@@ -1,173 +0,0 @@
-# Release Process
-
-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**, when the tag matches `v*`. 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.
-
-> Because commits are reference-counted, it is safe to create a release branch, tag it, let the workflow run, then delete the branch. So long as the tag exists, that commit will exist.
-
-### Triggering the Workflow
-
-Run `make tag-release` to tag the current commit and kick off the workflow.
-
-The release may also be dispatched [manually].
-
-### Workflow Jobs and Process
-
-The workflow consists of a number of concurrently-run jobs, and two final publish jobs.
-
-The publish jobs require manual approval and are only run if the other jobs succeed.
-
-#### `check-version` Job
-
-This job checks that the git ref matches the app version. It matches the ref against the `__version__` variable in `invokeai/version/invokeai_version.py`.
-
-When the workflow is triggered by tag push, the ref is the tag. If the workflow is run manually, the ref is the target selected from the **Use workflow from** dropdown.
-
-This job uses [samuelcolvin/check-python-version].
-
-> 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.
-
-#### Check and Test Jobs
-
-- **`python-tests`**: runs `pytest` on matrix of platforms
-- **`python-checks`**: runs `ruff` (format and lint)
-- **`frontend-tests`**: runs `vitest`
-- **`frontend-checks`**: runs `prettier` (format), `eslint` (lint), `dpdm` (circular refs), `tsc` (static type check) and `knip` (unused imports)
-
-> **TODO** We should add `mypy` or `pyright` to the **`check-python`** job.
-
-> **TODO** We should add an end-to-end test job that generates an image.
-
-#### `build-installer` Job
-
-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
-
-#### Sanity Check & Smoke Test
-
-At this point, the release workflow pauses as the remaining publish jobs require approval. Time to test the installer.
-
-Because the installer pulls from PyPI, and we haven't published to PyPI yet, you will need to install from the wheel:
-
-- Download and unzip `dist.zip` and the installer from the **Summary** tab of the workflow
-- Run the installer script using the `--wheel` CLI arg, pointing at the wheel:
-
-  ```sh
-  ./install.sh --wheel ../InvokeAI-4.0.0rc6-py3-none-any.whl
-  ```
-
-- Install to a temporary directory so you get the new user experience
-- Download a model and generate
-
-> The same wheel file is bundled in the installer and in the `dist` artifact, which is uploaded to PyPI. You should end up with the exactly the same installation as if the installer got the wheel from PyPI.
-
-##### Something isn't right
-
-If testing reveals any issues, no worries. Cancel the workflow, which will cancel the pending publish jobs (you didn't approve them prematurely, right?).
-
-Now you can start from the top:
-
-- Fix the issues and PR the fixes per usual
-- Get the PR approved and merged per usual
-- Switch to `main` and pull in the fixes
-- Run `make tag-release` to move the tag to `HEAD` (which has the fixes) and kick off the release workflow again
-- Re-do the sanity check
-
-#### PyPI Publish Jobs
-
-The publish jobs will run if any of the previous jobs fail.
-
-They 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**
-
-> **If the version already exists on PyPI, the publish jobs will fail.** PyPI only allows a given 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.
-
-##### Failing PyPI Publish
-
-Check the [python infrastructure status page] for incidents.
-
-If there are no incidents, contact @hipsterusername or @lstein, who have owner access to GH and PyPI, to see if access has expired or something like that.
-
-#### `publish-testpypi` Job
-
-Publishes the distribution on the [Test PyPI] index, using the `testpypi` GitHub environment.
-
-This job is not required for the production PyPI publish, but included just in case you want to test the PyPI release.
-
-If approved and successful, you could try out the test release like this:
-
-```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` Job
-
-Publishes the distribution on the production PyPI index, using the `pypi` GitHub environment.
-
-## Publish the GitHub Release with installer
-
-Once the release is published to PyPI, it's time to publish the GitHub release.
-
-1. [Draft a new release] on GitHub, choosing the tag that triggered the release.
-1. 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.
-1. Use `scripts/get_external_contributions.py` to get a list of external contributions to shout out in the release notes.
-1. Upload the zip file created in **`build`** job into the Assets section of the release notes.
-1. Check **Set as a pre-release** if it's a pre-release.
-1. Check **Create a discussion for this release**.
-1. Publish the release.
-1. Announce the release in Discord.
-
-> **TODO** Workflows can create a GitHub 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.
-
-## Manual Build
-
-The `build installer` workflow can be dispatched manually. This is useful to test the installer for a given branch or tag.
-
-No checks are run, it just builds.
-
-## Manual Release
-
-The `release` workflow can be dispatched manually. You must dispatch the workflow from the right tag, else it will fail the version check.
-
-This functionality is available as a fallback in case something goes wonky. Typically, releases should be triggered via tag push as described above.
-
-[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]: #manual-release
-[python infrastructure status page]: https://status.python.org/

docs/contributing/CONTRIBUTING.md

@@ -1,43 +1,42 @@
-# Contributing
+## Welcome to Invoke AI
+
+We're thrilled to have you here and we're excited for you to contribute. 
 
 Invoke AI originated as a project built by the community, and that vision carries forward today as we aim to build the best pro-grade tools available. We work together to incorporate the latest in AI/ML research, making these tools available in over 20 languages to artists and creatives around the world as part of our fully permissive OSS project designed for individual users to self-host and use.
 
+Here are some guidelines to help you get started:
 
-# Methods of Contributing to Invoke AI
-Anyone who wishes to contribute to InvokeAI, whether features, bug fixes, code cleanup, testing, code reviews, documentation or translation is very much encouraged to do so.
+### Technical Prerequisites
 
-## Development
-If you’d like to help with development, please see our [development guide](contribution_guides/development.md). 
+Front-end: You'll need a working knowledge of React and TypeScript.
 
-**New Contributors:** If you’re unfamiliar with contributing to open source projects, take a look at our [new contributor guide](contribution_guides/newContributorChecklist.md).
+Back-end: Depending on the scope of your contribution, you may need to know SQLite, FastAPI, Python, and Socketio. Also, a good majority of the backend logic involved in processing images is built in a modular way using a concept called "Nodes", which are isolated functions that carry out individual, discrete operations. This design allows for easy contributions of novel pipelines and capabilities.
 
-## Nodes
-If you’d like to add a Node, please see our [nodes contribution guide](../nodes/contributingNodes.md).
+### How to Submit Contributions
 
-## Support and Triaging
-Helping support other users in [Discord](https://discord.gg/ZmtBAhwWhy) and on Github are valuable forms of contribution that we greatly appreciate. 
+To start contributing, please follow these steps:
 
-We receive many issues and requests for help from users. We're limited in bandwidth relative to our the user base, so providing answers to questions or helping identify causes of issues is very helpful. By doing this, you enable us to spend time on the highest priority work. 
+1. Familiarize yourself with our roadmap and open projects to see where your skills and interests align. These documents can serve as a source of inspiration.
+2. Open a Pull Request (PR) with a clear description of the feature you're adding or the problem you're solving. Make sure your contribution aligns with the project's vision.
+3. Adhere to general best practices. This includes assuming interoperability with other nodes, keeping the scope of your functions as small as possible, and organizing your code according to our architecture documents.
 
-## Documentation
-If you’d like to help with documentation, please see our [documentation guide](contribution_guides/documentation.md).
+### Types of Contributions We're Looking For
 
-## Translation
-If you'd like to help with translation, please see our [translation guide](contribution_guides/translation.md).
+We welcome all contributions that improve the project. Right now, we're especially looking for:
 
-## Tutorials 
-Please reach out to @imic or @hipsterusername on [Discord](https://discord.gg/ZmtBAhwWhy) to help create tutorials for InvokeAI.
+1. Quality of life (QOL) enhancements on the front-end.
+2. New backend capabilities added through nodes.
+3. Incorporating additional optimizations from the broader open-source software community.
 
-We hope you enjoy using our software as much as we enjoy creating it, and we hope that some of those of you who are reading this will elect to become part of our contributor community.
+### Communication and Decision-making Process
 
+Project maintainers and code owners review PRs to ensure they align with the project's goals. They may provide design or architectural guidance, suggestions on user experience, or provide more significant feedback on the contribution itself. Expect to receive feedback on your submissions, and don't hesitate to ask questions or propose changes.
 
-# Contributors
+For more robust discussions, or if you're planning to add capabilities not currently listed on our roadmap, please reach out to us on our Discord server. That way, we can ensure your proposed contribution aligns with the project's direction before you start writing code.
 
-This project is a combined effort of dedicated people from across the world. [Check out the list of all these amazing people](https://invoke-ai.github.io/InvokeAI/other/CONTRIBUTORS/). We thank them for their time, hard work and effort.
+### Code of Conduct and Contribution Expectations
 
-# Code of Conduct
-
-The InvokeAI community is a welcoming place, and we want your help in maintaining that. Please review our [Code of Conduct](https://github.com/invoke-ai/InvokeAI/blob/main/CODE_OF_CONDUCT.md) to learn more - it's essential to maintaining a respectful and inclusive environment.
+We want everyone in our community to have a positive experience. To facilitate this, we've established a code of conduct and a statement of values that we expect all contributors to adhere to. Please take a moment to review these documents—they're essential to maintaining a respectful and inclusive environment.
 
 By making a contribution to this project, you certify that:
 
@@ -49,11 +48,6 @@ By making a contribution to this project, you certify that:
 This disclaimer is not a license and does not grant any rights or permissions. You must obtain necessary permissions and licenses, including from third parties, before contributing to this project.
 
 This disclaimer is provided "as is" without warranty of any kind, whether expressed or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose, or non-infringement. In no event shall the authors or copyright holders be liable for any claim, damages, or other liability, whether in an action of contract, tort, or otherwise, arising from, out of, or in connection with the contribution or the use or other dealings in the contribution.
-# Support
-
-For support, please use this repository's [GitHub Issues](https://github.com/invoke-ai/InvokeAI/issues), or join the [Discord](https://discord.gg/ZmtBAhwWhy).
-
-Original portions of the software are Copyright (c) 2023 by respective contributors.
 
 ---
 

docs/contributing/DOWNLOAD_QUEUE.md

@@ -1,277 +0,0 @@
-# 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/INVOCATIONS.md

@@ -1,395 +1,277 @@
-# Nodes
+# Invocations
 
-Features in InvokeAI are added in the form of modular nodes systems called
-**Invocations**.
+Invocations represent a single operation, its inputs, and its outputs. These
+operations and their outputs can be chained together to generate and modify
+images.
 
-An Invocation is simply a single operation that takes in some inputs and gives
-out some outputs. We can then chain multiple Invocations together to create more
-complex functionality.
+## Creating a new invocation
 
-## Invocations Directory
+To create a new invocation, either find the appropriate module file in
+`/ldm/invoke/app/invocations` to add your invocation to, or create a new one in
+that folder. All invocations in that folder will be discovered and made
+available to the CLI and API automatically. Invocations make use of
+[typing](https://docs.python.org/3/library/typing.html) and
+[pydantic](https://pydantic-docs.helpmanual.io/) for validation and integration
+into the CLI and API.
 
-InvokeAI Nodes can be found in the `invokeai/app/invocations` directory. These
-can be used as examples to create your own nodes.
-
-New nodes should be added to a subfolder in `nodes` direction found at the root
-level of the InvokeAI installation location. Nodes added to this folder will be
-able to be used upon application startup.
-
-Example `nodes` subfolder structure:
+An invocation looks like this:
 
 ```py
-├── __init__.py # Invoke-managed custom node loader
-│
-├── cool_node
-│   ├── __init__.py # see example below
-│   └── cool_node.py
-│
-└── my_node_pack
-    ├── __init__.py # see example below
-    ├── tasty_node.py
-    ├── bodacious_node.py
-    ├── utils.py
-    └── extra_nodes
-        └── fancy_node.py
-```
+class UpscaleInvocation(BaseInvocation):
+    """Upscales an image."""
 
-Each node folder must have an `__init__.py` file that imports its nodes. Only
-nodes imported in the `__init__.py` file are loaded. See the README in the nodes
-folder for more examples:
-
-```py
-from .cool_node import CoolInvocation
-```
-
-## Creating A New Invocation
-
-In order to understand the process of creating a new Invocation, let us actually
-create one.
-
-In our example, let us create an Invocation that will take in an image, resize
-it and output the resized image.
-
-The first set of things we need to do when creating a new Invocation are -
-
-- Create a new class that derives from a predefined parent class called
-  `BaseInvocation`.
-- Every Invocation must have a `docstring` that describes what this Invocation
-  does.
-- While not strictly required, we suggest every invocation class name ends in
-  "Invocation", eg "CropImageInvocation".
-- Every Invocation must use the `@invocation` decorator to provide its unique
-  invocation type. You may also provide its title, tags and category using the
-  decorator.
-- Invocations are strictly typed. We make use of the native
-  [typing](https://docs.python.org/3/library/typing.html) library and the
-  installed [pydantic](https://pydantic-docs.helpmanual.io/) library for
-  validation.
-
-So let us do that.
-
-```python
-from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-
-@invocation('resize')
-class ResizeInvocation(BaseInvocation):
-    '''Resizes an image'''
-```
-
-That's great.
-
-Now we have setup the base of our new Invocation. Let us think about what inputs
-our Invocation takes.
-
-- We need an `image` that we are going to resize.
-- We will need new `width` and `height` values to which we need to resize the
-  image to.
-
-### **Inputs**
-
-Every Invocation input must be defined using the `InputField` function. This is
-a wrapper around the pydantic `Field` function, which handles a few extra things
-and provides type hints. Like everything else, this should be strictly typed and
-defined.
-
-So let us create these inputs for our Invocation. First up, the `image` input we
-need. Generally, we can use standard variable types in Python but InvokeAI
-already has a custom `ImageField` type that handles all the stuff that is needed
-for image inputs.
-
-But what is this `ImageField` ..? It is a special class type specifically
-written to handle how images are dealt with in InvokeAI. We will cover how to
-create your own custom field types later in this guide. For now, let's go ahead
-and use it.
-
-```python
-from invokeai.app.invocations.baseinvocation import BaseInvocation, InputField, invocation
-from invokeai.app.invocations.primitives import ImageField
-
-@invocation('resize')
-class ResizeInvocation(BaseInvocation):
+    # fmt: off
+    type: Literal["upscale"] = "upscale"
 
     # Inputs
-    image: ImageField = InputField(description="The input image")
-```
+    image: Union[ImageField, None] = Field(description="The input image", default=None)
+    strength: float                = Field(default=0.75, gt=0, le=1, description="The strength")
+    level: Literal[2, 4]           = Field(default=2, description="The upscale level")
+    # fmt: on
 
-Let us break down our input code.
-
-```python
-image: ImageField = InputField(description="The input image")
-```
-
-| Part      | Value                                       | Description                                                                     |
-| --------- | ------------------------------------------- | ------------------------------------------------------------------------------- |
-| Name      | `image`                                     | The variable that will hold our image                                           |
-| Type Hint | `ImageField`                                | The types for our field. Indicates that the image must be an `ImageField` type. |
-| Field     | `InputField(description="The input image")` | The image variable is an `InputField` which needs a description.                |
-
-Great. Now let us create our other inputs for `width` and `height`
-
-```python
-from invokeai.app.invocations.baseinvocation import BaseInvocation, InputField, invocation
-from invokeai.app.invocations.primitives import ImageField
-
-@invocation('resize')
-class ResizeInvocation(BaseInvocation):
-    '''Resizes an image'''
-
-    image: ImageField = InputField(description="The input image")
-    width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
-    height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
-```
-
-As you might have noticed, we added two new arguments to the `InputField`
-definition for `width` and `height`, called `gt` and `le`. They stand for
-_greater than or equal to_ and _less than or equal to_.
-
-These impose contraints on those fields, and will raise an exception if the
-values do not meet the constraints. Field constraints are provided by
-**pydantic**, so anything you see in the **pydantic docs** will work.
-
-**Note:** _Any time it is possible to define constraints for our field, we
-should do it so the frontend has more information on how to parse this field._
-
-Perfect. We now have our inputs. Let us do something with these.
-
-### **Invoke Function**
-
-The `invoke` function is where all the magic happens. This function provides you
-the `context` parameter that is of the type `InvocationContext` which will give
-you access to the current context of the generation and all the other services
-that are provided by it by InvokeAI.
-
-Let us create this function first.
-
-```python
-from invokeai.app.invocations.baseinvocation import BaseInvocation, InputField, invocation, InvocationContext
-from invokeai.app.invocations.primitives import ImageField
-
-@invocation('resize')
-class ResizeInvocation(BaseInvocation):
-    '''Resizes an image'''
-
-    image: ImageField = InputField(description="The input image")
-    width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
-    height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
-
-    def invoke(self, context: InvocationContext):
-        pass
-```
-
-### **Outputs**
-
-The output of our Invocation will be whatever is returned by this `invoke`
-function. Like with our inputs, we need to strongly type and define our outputs
-too.
-
-What is our output going to be? Another image. Normally you'd have to create a
-type for this but InvokeAI already offers you an `ImageOutput` type that handles
-all the necessary info related to image outputs. So let us use that.
-
-We will cover how to create your own output types later in this guide.
-
-```python
-from invokeai.app.invocations.baseinvocation import BaseInvocation, InputField, invocation, InvocationContext
-from invokeai.app.invocations.primitives import ImageField
-from invokeai.app.invocations.image import ImageOutput
-
-@invocation('resize')
-class ResizeInvocation(BaseInvocation):
-    '''Resizes an image'''
-
-    image: ImageField = InputField(description="The input image")
-    width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
-    height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
+    # Schema customisation
+    class Config(InvocationConfig):
+        schema_extra = {
+            "ui": {
+                "tags": ["upscaling", "image"],
+            },
+        }
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        pass
+        image = context.services.images.get_pil_image(
+            self.image.image_origin, self.image.image_name
+        )
+        results = context.services.restoration.upscale_and_reconstruct(
+            image_list=[[image, 0]],
+            upscale=(self.level, self.strength),
+            strength=0.0,  # GFPGAN strength
+            save_original=False,
+            image_callback=None,
+        )
+
+        # Results are image and seed, unwrap for now
+        # TODO: can this return multiple results?
+        image_dto = context.services.images.create(
+            image=results[0][0],
+            image_origin=ResourceOrigin.INTERNAL,
+            image_category=ImageCategory.GENERAL,
+            node_id=self.id,
+            session_id=context.graph_execution_state_id,
+            is_intermediate=self.is_intermediate,
+        )
+
+        return ImageOutput(
+            image=ImageField(
+                image_name=image_dto.image_name,
+                image_origin=image_dto.image_origin,
+            ),
+            width=image_dto.width,
+            height=image_dto.height,
+        )
+
 ```
 
-Perfect. Now that we have our Invocation setup, let us do what we want to do.
+Each portion is important to implement correctly.
 
-- We will first load the image using one of the services provided by InvokeAI to
-  load the image.
-- We will resize the image using `PIL` to our input data.
-- We will output this image in the format we set above.
+### Class definition and type
 
-So let's do that.
+```py
+class UpscaleInvocation(BaseInvocation):
+    """Upscales an image."""
+    type: Literal['upscale'] = 'upscale'
+```
 
-```python
-from invokeai.app.invocations.baseinvocation import BaseInvocation, InputField, invocation, InvocationContext
-from invokeai.app.invocations.primitives import ImageField
-from invokeai.app.invocations.image import ImageOutput, ResourceOrigin, ImageCategory
+All invocations must derive from `BaseInvocation`. They should have a docstring
+that declares what they do in a single, short line. They should also have a
+`type` with a type hint that's `Literal["command_name"]`, where `command_name`
+is what the user will type on the CLI or use in the API to create this
+invocation. The `command_name` must be unique. The `type` must be assigned to
+the value of the literal in the type hint.
 
-@invocation("resize")
-class ResizeInvocation(BaseInvocation):
-    """Resizes an image"""
+### Inputs
 
-    image: ImageField = InputField(description="The input image")
-    width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
-    height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
+```py
+    # Inputs
+    image: Union[ImageField,None] = Field(description="The input image")
+    strength: float               = Field(default=0.75, gt=0, le=1, description="The strength")
+    level: Literal[2,4]           = Field(default=2, description="The upscale level")
+```
 
+Inputs consist of three parts: a name, a type hint, and a `Field` with default,
+description, and validation information. For example:
+
+| Part      | Value                                                         | Description                                                                                                               |
+| --------- | ------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------- |
+| Name      | `strength`                                                    | This field is referred to as `strength`                                                                                   |
+| Type Hint | `float`                                                       | This field must be of type `float`                                                                                        |
+| Field     | `Field(default=0.75, gt=0, le=1, description="The strength")` | The default value is `0.75`, the value must be in the range (0,1], and help text will show "The strength" for this field. |
+
+Notice that `image` has type `Union[ImageField,None]`. The `Union` allows this
+field to be parsed with `None` as a value, which enables linking to previous
+invocations. All fields should either provide a default value or allow `None` as
+a value, so that they can be overwritten with a linked output from another
+invocation.
+
+The special type `ImageField` is also used here. All images are passed as
+`ImageField`, which protects them from pydantic validation errors (since images
+only ever come from links).
+
+Finally, note that for all linking, the `type` of the linked fields must match.
+If the `name` also matches, then the field can be **automatically linked** to a
+previous invocation by name and matching.
+
+### Config
+
+```py
+    # Schema customisation
+    class Config(InvocationConfig):
+        schema_extra = {
+            "ui": {
+                "tags": ["upscaling", "image"],
+            },
+        }
+```
+
+This is an optional configuration for the invocation. It inherits from
+pydantic's model `Config` class, and it used primarily to customize the
+autogenerated OpenAPI schema.
+
+The UI relies on the OpenAPI schema in two ways:
+
+- An API client & Typescript types are generated from it. This happens at build
+  time.
+- The node editor parses the schema into a template used by the UI to create the
+  node editor UI. This parsing happens at runtime.
+
+In this example, a `ui` key has been added to the `schema_extra` dict to provide
+some tags for the UI, to facilitate filtering nodes.
+
+See the Schema Generation section below for more information.
+
+### Invoke Function
+
+```py
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        # Load the input image as a PIL image
-        image = context.images.get_pil(self.image.image_name)
+        image = context.services.images.get_pil_image(
+            self.image.image_origin, self.image.image_name
+        )
+        results = context.services.restoration.upscale_and_reconstruct(
+            image_list=[[image, 0]],
+            upscale=(self.level, self.strength),
+            strength=0.0,  # GFPGAN strength
+            save_original=False,
+            image_callback=None,
+        )
 
-        # Resize the image
-        resized_image = image.resize((self.width, self.height))
+        # Results are image and seed, unwrap for now
+        # TODO: can this return multiple results?
+        image_dto = context.services.images.create(
+            image=results[0][0],
+            image_origin=ResourceOrigin.INTERNAL,
+            image_category=ImageCategory.GENERAL,
+            node_id=self.id,
+            session_id=context.graph_execution_state_id,
+            is_intermediate=self.is_intermediate,
+        )
 
-        # Save the image
-        image_dto = context.images.save(image=resized_image)
-
-        # Return an ImageOutput
-        return ImageOutput.build(image_dto)
+        return ImageOutput(
+            image=ImageField(
+                image_name=image_dto.image_name,
+                image_origin=image_dto.image_origin,
+            ),
+            width=image_dto.width,
+            height=image_dto.height,
+        )
 ```
 
-**Note:** Do not be overwhelmed by the `ImageOutput` process. InvokeAI has a
-certain way that the images need to be dispatched in order to be stored and read
-correctly. In 99% of the cases when dealing with an image output, you can simply
-copy-paste the template above.
+The `invoke` function is the last portion of an invocation. It is provided an
+`InvocationContext` which contains services to perform work as well as a
+`session_id` for use as needed. It should return a class with output values that
+derives from `BaseInvocationOutput`.
 
-### Customization
+Before being called, the invocation will have all of its fields set from
+defaults, inputs, and finally links (overriding in that order).
 
-We can use the `@invocation` decorator to provide some additional info to the
-UI, like a custom title, tags and category.
+Assume that this invocation may be running simultaneously with other
+invocations, may be running on another machine, or in other interesting
+scenarios. If you need functionality, please provide it as a service in the
+`InvocationServices` class, and make sure it can be overridden.
 
-We also encourage providing a version. This must be a
-[semver](https://semver.org/) version string ("$MAJOR.$MINOR.$PATCH"). The UI
-will let users know if their workflow is using a mismatched version of the node.
+### Outputs
+
+```py
+class ImageOutput(BaseInvocationOutput):
+    """Base class for invocations that output an image"""
+
+    # fmt: off
+    type: Literal["image_output"] = "image_output"
+    image:      ImageField = Field(default=None, description="The output image")
+    width:             int = Field(description="The width of the image in pixels")
+    height:            int = Field(description="The height of the image in pixels")
+    # fmt: on
+
+    class Config:
+        schema_extra = {"required": ["type", "image", "width", "height"]}
+```
+
+Output classes look like an invocation class without the invoke method. Prefer
+to use an existing output class if available, and prefer to name inputs the same
+as outputs when possible, to promote automatic invocation linking.
+
+## Schema Generation
+
+Invocation, output and related classes are used to generate an OpenAPI schema.
+
+### Required Properties
+
+The schema generation treat all properties with default values as optional. This
+makes sense internally, but when when using these classes via the generated
+schema, we end up with e.g. the `ImageOutput` class having its `image` property
+marked as optional.
+
+We know that this property will always be present, so the additional logic
+needed to always check if the property exists adds a lot of extraneous cruft.
+
+To fix this, we can leverage `pydantic`'s
+[schema customisation](https://docs.pydantic.dev/usage/schema/#schema-customization)
+to mark properties that we know will always be present as required.
+
+Here's that `ImageOutput` class, without the needed schema customisation:
 
 ```python
-@invocation("resize", title="My Resizer", tags=["resize", "image"], category="My Invocations", version="1.0.0")
-class ResizeInvocation(BaseInvocation):
-    """Resizes an image"""
+class ImageOutput(BaseInvocationOutput):
+    """Base class for invocations that output an image"""
 
-    image: ImageField = InputField(description="The input image")
-    ...
+    # fmt: off
+    type: Literal["image_output"] = "image_output"
+    image:      ImageField = Field(default=None, description="The output image")
+    width:             int = Field(description="The width of the image in pixels")
+    height:            int = Field(description="The height of the image in pixels")
+    # fmt: on
 ```
 
-That's it. You made your own **Resize Invocation**.
-
-## Result
-
-Once you make your Invocation correctly, the rest of the process is fully
-automated for you.
-
-When you launch InvokeAI, you can go to `http://localhost:9090/docs` and see
-your new Invocation show up there with all the relevant info.
-
-![resize invocation](../assets/contributing/resize_invocation.png)
-
-When you launch the frontend UI, you can go to the Node Editor tab and find your
-new Invocation ready to be used.
-
-![resize node editor](../assets/contributing/resize_node_editor.png)
-
-## Contributing Nodes
-
-Once you've created a Node, the next step is to share it with the community! The
-best way to do this is to submit a Pull Request to add the Node to the
-[Community Nodes](nodes/communityNodes) list. If you're not sure how to do that,
-take a look a at our [contributing nodes overview](contributingNodes).
-
-## Advanced
-
-### Custom Output Types
-
-Like with custom inputs, sometimes you might find yourself needing custom
-outputs that InvokeAI does not provide. We can easily set one up.
-
-Now that you are familiar with Invocations and Inputs, let us use that knowledge
-to create an output that has an `image` field, a `color` field and a `string`
-field.
-
-- An invocation output is a class that derives from the parent class of
-  `BaseInvocationOutput`.
-- All invocation outputs must use the `@invocation_output` decorator to provide
-  their unique output type.
-- Output fields must use the provided `OutputField` function. This is very
-  similar to the `InputField` function described earlier - it's a wrapper around
-  `pydantic`'s `Field()`.
-- It is not mandatory but we recommend using names ending with `Output` for
-  output types.
-- It is not mandatory but we highly recommend adding a `docstring` to describe
-  what your output type is for.
-
-Now that we know the basic rules for creating a new output type, let us go ahead
-and make it.
+The OpenAPI schema that results from this `ImageOutput` will have the `type`,
+`image`, `width` and `height` properties marked as optional, even though we know
+they will always have a value.
 
 ```python
-from .baseinvocation import BaseInvocationOutput, OutputField, invocation_output
-from .primitives import ImageField, ColorField
+class ImageOutput(BaseInvocationOutput):
+    """Base class for invocations that output an image"""
 
-@invocation_output('image_color_string_output')
-class ImageColorStringOutput(BaseInvocationOutput):
-    '''Base class for nodes that output a single image'''
+    # fmt: off
+    type: Literal["image_output"] = "image_output"
+    image:      ImageField = Field(default=None, description="The output image")
+    width:             int = Field(description="The width of the image in pixels")
+    height:            int = Field(description="The height of the image in pixels")
+    # fmt: on
 
-    image: ImageField = OutputField(description="The image")
-    color: ColorField = OutputField(description="The color")
-    text: str = OutputField(description="The string")
+    # Add schema customization
+    class Config:
+        schema_extra = {"required": ["type", "image", "width", "height"]}
 ```
 
-That's all there is to it.
+With the customization in place, the schema will now show these properties as
+required, obviating the need for extensive null checks in client code.
 
-### Custom Input Fields
-
-Now that you know how to create your own Invocations, let us dive into slightly
-more advanced topics.
-
-While creating your own Invocations, you might run into a scenario where the
-existing fields in InvokeAI do not meet your requirements. In such cases, you
-can create your own fields.
-
-Let us create one as an example. Let us say we want to create a color input
-field that represents a color code. But before we start on that here are some
-general good practices to keep in mind.
-
-### Best Practices
-
-- There is no naming convention for input fields but we highly recommend that
-  you name it something appropriate like `ColorField`.
-- It is not mandatory but it is heavily recommended to add a relevant
-  `docstring` to describe your field.
-- Keep your field in the same file as the Invocation that it is made for or in
-  another file where it is relevant.
-
-All input types a class that derive from the `BaseModel` type from `pydantic`.
-So let's create one.
-
-```python
-from pydantic import BaseModel
-
-class ColorField(BaseModel):
-    '''A field that holds the rgba values of a color'''
-    pass
-```
-
-Perfect. Now let us create the properties for our field. This is similar to how
-you created input fields for your Invocation. All the same rules apply. Let us
-create four fields representing the _red(r)_, _blue(b)_, _green(g)_ and
-_alpha(a)_ channel of the color.
-
-> Technically, the properties are _also_ called fields - but in this case, it
-> refers to a `pydantic` field.
-
-```python
-class ColorField(BaseModel):
-    '''A field that holds the rgba values of a color'''
-    r: int = Field(ge=0, le=255, description="The red channel")
-    g: int = Field(ge=0, le=255, description="The green channel")
-    b: int = Field(ge=0, le=255, description="The blue channel")
-    a: int = Field(ge=0, le=255, description="The alpha channel")
-```
-
-That's it. We now have a new input field type that we can use in our Invocations
-like this.
-
-```python
-color: ColorField = InputField(default=ColorField(r=0, g=0, b=0, a=0), description='Background color of an image')
-```
-
-### Using the custom field
-
-When you start the UI, your custom field will be automatically recognized.
-
-Custom fields only support connection inputs in the Workflow Editor.
+See this `pydantic` issue for discussion on this solution:
+<https://github.com/pydantic/pydantic/discussions/4577>

docs/contributing/LOCAL_DEVELOPMENT.md

@@ -35,244 +35,49 @@ access.
 
 ## Backend
 
-The backend is contained within the `./invokeai/backend` and `./invokeai/app` directories.
-To get started please install the development dependencies.
+The backend is contained within the `./invokeai/backend` folder structure. To
+get started however please install the development dependencies.
 
 From the root of the repository run the following command. Note the use of `"`.
 
 ```zsh
-pip install ".[dev,test]"
+pip install ".[test]"
 ```
 
-These are optional groups of packages which are defined within the `pyproject.toml`
-and will be required for testing the changes you make to the code.
+This in an optional group of packages which is defined within the
+`pyproject.toml` and will be required for testing the changes you make the the
+code.
 
-### Tests
+### Running Tests
 
-See the [tests documentation](./TESTS.md) for information about running and writing tests.
-### Reloading Changes
+We use [pytest](https://docs.pytest.org/en/7.2.x/) for our test suite. Tests can
+be found under the `./tests` folder and can be run with a single `pytest`
+command. Optionally, to review test coverage you can append `--cov`.
 
-Experimenting with changes to the Python source code is a drag if you have to re-start the server —
-and re-load those multi-gigabyte models —
-after every change.
+```zsh
+pytest --cov
+```
 
-For a faster development workflow, add the `--dev_reload` flag when starting the server.
-The server will watch for changes to all the Python files in the `invokeai` directory and apply those changes to the
-running server on the fly.
+Test outcomes and coverage will be reported in the terminal. In addition a more
+detailed report is created in both XML and HTML format in the `./coverage`
+folder. The HTML one in particular can help identify missing statements
+requiring tests to ensure coverage. This can be run by opening
+`./coverage/html/index.html`.
 
-This will allow you to avoid restarting the server (and reloading models) in most cases, but there are some caveats; see
-the [jurigged documentation](https://github.com/breuleux/jurigged#caveats) for details.
+For example.
 
+```zsh
+pytest --cov; open ./coverage/html/index.html
+```
+
+??? info "HTML coverage report output"
+
+    ![html-overview](../assets/contributing/html-overview.png)
+
+    ![html-detail](../assets/contributing/html-detail.png)
 
 ## Front End
 
 <!--#TODO: get input from blessedcoolant here, for the moment inserted the frontend README via snippets extension.-->
 
 --8<-- "invokeai/frontend/web/README.md"
-
-## Developing InvokeAI in VSCode
-
-VSCode offers some nice tools:
-
-- python debugger
-- automatic `venv` activation
-- remote dev (e.g. run InvokeAI on a beefy linux desktop while you type in
-  comfort on your macbook)
-
-### Setup
-
-You'll need the
-[Python](https://marketplace.visualstudio.com/items?itemName=ms-python.python)
-and
-[Pylance](https://marketplace.visualstudio.com/items?itemName=ms-python.vscode-pylance)
-extensions installed first.
-
-It's also really handy to install the `Jupyter` extensions:
-
-- [Jupyter](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter)
-- [Jupyter Cell Tags](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.vscode-jupyter-cell-tags)
-- [Jupyter Notebook Renderers](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter-renderers)
-- [Jupyter Slide Show](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.vscode-jupyter-slideshow)
-
-#### InvokeAI workspace
-
-Creating a VSCode workspace for working on InvokeAI is highly recommended. It
-can hold InvokeAI-specific settings and configs.
-
-To make a workspace:
-
-- Open the InvokeAI repo dir in VSCode
-- `File` > `Save Workspace As` > save it _outside_ the repo
-
-#### Default python interpreter (i.e. automatic virtual environment activation)
-
-- Use command palette to run command
-  `Preferences: Open Workspace Settings (JSON)`
-- Add `python.defaultInterpreterPath` to `settings`, pointing to your `venv`'s
-  python
-
-Should look something like this:
-
-```jsonc
-{
-  // I like to have all InvokeAI-related folders in my workspace
-  "folders": [
-    {
-      // repo root
-      "path": "InvokeAI"
-    },
-    {
-      // InvokeAI root dir, where `invokeai.yaml` lives
-      "path": "/path/to/invokeai_root"
-    }
-  ],
-  "settings": {
-    // Where your InvokeAI `venv`'s python executable lives
-    "python.defaultInterpreterPath": "/path/to/invokeai_root/.venv/bin/python"
-  }
-}
-```
-
-Now when you open the VSCode integrated terminal, or do anything that needs to
-run python, it will automatically be in your InvokeAI virtual environment.
-
-Bonus: When you create a Jupyter notebook, when you run it, you'll be prompted
-for the python interpreter to run in. This will default to your `venv` python,
-and so you'll have access to the same python environment as the InvokeAI app.
-
-This is _super_ handy.
-
-#### Enabling Type-Checking with Pylance
-
-We use python's typing system in InvokeAI. PR reviews will include checking that types are present and correct. We don't enforce types with `mypy` at this time, but that is on the horizon.
-
-Using a code analysis tool to automatically type check your code (and types) is very important when writing with types. These tools provide immediate feedback in your editor when types are incorrect, and following their suggestions lead to fewer runtime bugs.
-
-Pylance, installed at the beginning of this guide, is the de-facto python LSP (language server protocol). It provides type checking in the editor (among many other features). Once installed, you do need to enable type checking manually:
-
-- Open a python file
-- Look along the status bar in VSCode for `{ } Python`
-- Click the `{ }`
-- Turn type checking on - basic is fine
-
-You'll now see red squiggly lines where type issues are detected. Hover your cursor over the indicated symbols to see what's wrong.
-
-In 99% of cases when the type checker says there is a problem, there really is a problem, and you should take some time to understand and resolve what it is pointing out.
-
-#### Debugging configs with `launch.json`
-
-Debugging configs are managed in a `launch.json` file. Like most VSCode configs,
-these can be scoped to a workspace or folder.
-
-Follow the [official guide](https://code.visualstudio.com/docs/python/debugging)
-to set up your `launch.json` and try it out.
-
-Now we can create the InvokeAI debugging configs:
-
-```jsonc
-{
-  // Use IntelliSense to learn about possible attributes.
-  // Hover to view descriptions of existing attributes.
-  // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
-  "version": "0.2.0",
-  "configurations": [
-    {
-      // Run the InvokeAI backend & serve the pre-built UI
-      "name": "InvokeAI Web",
-      "type": "python",
-      "request": "launch",
-      "program": "scripts/invokeai-web.py",
-      "args": [
-        // Your InvokeAI root dir (where `invokeai.yaml` lives)
-        "--root",
-        "/path/to/invokeai_root",
-        // Access the app from anywhere on your local network
-        "--host",
-        "0.0.0.0"
-      ],
-      "justMyCode": true
-    },
-    {
-      // Run the nodes-based CLI
-      "name": "InvokeAI CLI",
-      "type": "python",
-      "request": "launch",
-      "program": "scripts/invokeai-cli.py",
-      "justMyCode": true
-    },
-    {
-      // Run tests
-      "name": "InvokeAI Test",
-      "type": "python",
-      "request": "launch",
-      "module": "pytest",
-      "args": ["--capture=no"],
-      "justMyCode": true
-    },
-    {
-      // Run a single test
-      "name": "InvokeAI Single Test",
-      "type": "python",
-      "request": "launch",
-      "module": "pytest",
-      "args": [
-        // Change this to point to the specific test you are working on
-        "tests/nodes/test_invoker.py"
-      ],
-      "justMyCode": true
-    },
-    {
-      // This is the default, useful to just run a single file
-      "name": "Python: File",
-      "type": "python",
-      "request": "launch",
-      "program": "${file}",
-      "justMyCode": true
-    }
-  ]
-}
-```
-
-You'll see these configs in the debugging configs drop down. Running them will
-start InvokeAI with attached debugger, in the correct environment, and work just
-like the normal app.
-
-Enjoy debugging InvokeAI with ease (not that we have any bugs of course).
-
-#### Remote dev
-
-This is very easy to set up and provides the same very smooth experience as
-local development. Environments and debugging, as set up above, just work,
-though you'd need to recreate the workspace and debugging configs on the remote.
-
-Consult the
-[official guide](https://code.visualstudio.com/docs/remote/remote-overview) to
-get it set up.
-
-Suggest using VSCode's included settings sync so that your remote dev host has
-all the same app settings and extensions automagically.
-
-##### One remote dev gotcha
-
-I've found the automatic port forwarding to be very flakey. You can disable it
-in `Preferences: Open Remote Settings (ssh: hostname)`. Search for
-`remote.autoForwardPorts` and untick the box.
-
-To forward ports very reliably, use SSH on the remote dev client (e.g. your
-macbook). Here's how to forward both backend API port (`9090`) and the frontend
-live dev server port (`5173`):
-
-```bash
-ssh \
-    -L 9090:localhost:9090 \
-    -L 5173:localhost:5173 \
-    user@remote-dev-host
-```
-
-The forwarding stops when you close the terminal window, so suggest to do this
-_outside_ the VSCode integrated terminal in case you need to restart VSCode for
-an extension update or something
-
-Now, on your remote dev client, you can open `localhost:9090` and access the UI,
-now served from the remote dev host, just the same as if it was running on the
-client.

docs/contributing/TESTS.md

@@ -1,89 +0,0 @@
-# InvokeAI Backend Tests
-
-We use `pytest` to run the backend python tests. (See [pyproject.toml](/pyproject.toml) for the default `pytest` options.)
-
-## Fast vs. Slow
-All tests are categorized as either 'fast' (no test annotation) or 'slow' (annotated with the `@pytest.mark.slow` decorator).
-
-'Fast' tests are run to validate every PR, and are fast enough that they can be run routinely during development.
-
-'Slow' tests are currently only run manually on an ad-hoc basis. In the future, they may be automated to run nightly. Most developers are only expected to run the 'slow' tests that directly relate to the feature(s) that they are working on.
-
-As a rule of thumb, tests should be marked as 'slow' if there is a chance that they take >1s (e.g. on a CPU-only machine with slow internet connection). Common examples of slow tests are tests that depend on downloading a model, or running model inference.
-
-## Running Tests
-
-Below are some common test commands:
-```bash
-# Run the fast tests. (This implicitly uses the configured default option: `-m "not slow"`.)
-pytest tests/
-
-# Equivalent command to run the fast tests.
-pytest tests/ -m "not slow"
-
-# Run the slow tests.
-pytest tests/ -m "slow"
-
-# Run the slow tests from a specific file.
-pytest tests/path/to/slow_test.py -m "slow"
-
-# Run all tests (fast and slow).
-pytest tests -m ""
-```
-
-## Test Organization
-
-All backend tests are in the [`tests/`](/tests/) directory. This directory mirrors the organization of the `invokeai/` directory. For example, tests for `invokeai/model_management/model_manager.py` would be found in `tests/model_management/test_model_manager.py`.
-
-TODO: The above statement is aspirational. A re-organization of legacy tests is required to make it true.
-
-## Tests that depend on models
-
-There are a few things to keep in mind when adding tests that depend on models.
-
-1. If a required model is not already present, it should automatically be downloaded as part of the test setup.
-2. If a model is already downloaded, it should not be re-downloaded unnecessarily.
-3. Take reasonable care to keep the total number of models required for the tests low. Whenever possible, re-use models that are already required for other tests. If you are adding a new model, consider including a comment to explain why it is required/unique.
-
-There are several utilities to help with model setup for tests. Here is a sample test that depends on a model:
-```python
-import pytest
-import torch
-
-from invokeai.backend.model_management.models.base import BaseModelType, ModelType
-from invokeai.backend.util.test_utils import install_and_load_model
-
-@pytest.mark.slow
-def test_model(model_installer, torch_device):
-    model_info = install_and_load_model(
-        model_installer=model_installer,
-        model_path_id_or_url="HF/dummy_model_id",
-        model_name="dummy_model",
-        base_model=BaseModelType.StableDiffusion1,
-        model_type=ModelType.Dummy,
-    )
-
-    dummy_input = build_dummy_input(torch_device)
-
-    with torch.no_grad(), model_info as model:
-        model.to(torch_device, dtype=torch.float32)
-        output = model(dummy_input)
-
-    # Validate output...
-
-```
-
-## Test Coverage
-
-To review test coverage, append `--cov` to your pytest command:
-```bash
-pytest tests/ --cov
-```
-
-Test outcomes and coverage will be reported in the terminal. In addition, a more detailed report is created in both XML and HTML format in the `./coverage` folder. The HTML output is particularly helpful in identifying untested statements where coverage should be improved. The HTML report can be viewed by opening `./coverage/html/index.html`.
-
-??? info "HTML coverage report output"
-
-    ![html-overview](../assets/contributing/html-overview.png)
-
-    ![html-detail](../assets/contributing/html-detail.png)

docs/contributing/contribution_guides/development.md

@@ -1,49 +0,0 @@
-# Development
-
-## **What do I need to know to help?**
-
-If you are looking to help to with a code contribution, InvokeAI uses several different technologies under the hood: Python (Pydantic, FastAPI, diffusers) and Typescript (React, Redux Toolkit, ChakraUI, Mantine, Konva). Familiarity with StableDiffusion and image generation concepts is helpful, but not essential. 
-
-
-## **Get Started**
-
-To get started, take a look at our [new contributors checklist](newContributorChecklist.md)
-
-Once you're setup, for more information, you can review the documentation specific to your area of interest:
-
-* #### [InvokeAI Architecure](../ARCHITECTURE.md)
-* #### [Frontend Documentation](https://github.com/invoke-ai/InvokeAI/tree/main/invokeai/frontend/web)
-* #### [Node Documentation](../INVOCATIONS.md)
-* #### [Local Development](../LOCAL_DEVELOPMENT.md)
-
-
-
-If you don't feel ready to make a code contribution yet, no problem! You can also help out in other ways, such as [documentation](documentation.md), [translation](translation.md) or helping support other users and triage issues as they're reported in GitHub.
-
-There are two paths to making a development contribution: 
-
-1. Choosing an open issue to address. Open issues can be found in the [Issues](https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen) section of the InvokeAI repository. These are tagged by the issue type (bug, enhancement, etc.) along with the “good first issues” tag denoting if they are suitable for first time contributors.
-    1. Additional items can be found on our [roadmap](https://github.com/orgs/invoke-ai/projects/7). The roadmap is organized in terms of priority, and contains features of varying size and complexity. If there is an inflight item you’d like to help with, reach out to the contributor assigned to the item to see how you can help. 
-2. Opening a new issue or feature to add. **Please make sure you have searched through existing issues before creating new ones.**
-
-*Regardless of what you choose, please post in the  [#dev-chat](https://discord.com/channels/1020123559063990373/1049495067846524939) channel of the Discord before you start development in order to confirm that the issue or feature is aligned with the current direction of the project. We value our contributors time and effort and want to ensure that no one’s time is being misspent.*
-
-## Best Practices: 
-* Keep your pull requests small. Smaller pull requests are more likely to be accepted and merged
-* Comments! Commenting your code helps reviewers easily understand your contribution
-* Use Python and Typescript’s typing systems, and consider using an editor with [LSP](https://microsoft.github.io/language-server-protocol/) support to streamline development
-* Make all communications public. This ensure knowledge is shared with the whole community
-
-## **Where can I go for help?**
-
-If you need help, you can ask questions in the [#dev-chat](https://discord.com/channels/1020123559063990373/1049495067846524939) channel of the Discord.
-
-For frontend related work, **@psychedelicious** is the best person to reach out to. 
-
-For backend related work, please reach out to **@blessedcoolant**, **@lstein**, **@StAlKeR7779** or **@psychedelicious**.
-
-
-## **What does the Code of Conduct mean for me?**
-
-Our [Code of Conduct](../../CODE_OF_CONDUCT.md)  means that you are responsible for treating everyone on the project with respect and courtesy regardless of their identity. If you are the victim of any inappropriate behavior or comments as described in our Code of Conduct, we are here for you and will do the best to ensure that the abuser is reprimanded appropriately, per our code.
-

docs/contributing/contribution_guides/documentation.md

@@ -1,13 +0,0 @@
-# Documentation
-
-Documentation is an important part of any open source project. It provides a clear and concise way to communicate how the software works, how to use it, and how to troubleshoot issues. Without proper documentation, it can be difficult for users to understand the purpose and functionality of the project. 
-
-## Contributing
-
-All documentation is maintained in the InvokeAI GitHub repository. If you come across documentation that is out of date or incorrect, please submit a pull request with the necessary changes. 
-
-When updating or creating documentation, please keep in mind InvokeAI is a tool for everyone, not just those who have familiarity with generative art. 
-
-## Help & Questions
-
-Please ping @imic or @hipsterusername in the [Discord](https://discord.com/channels/1020123559063990373/1049495067846524939) if you have any questions.

docs/contributing/contribution_guides/newContributorChecklist.md

@@ -1,68 +0,0 @@
-# New Contributor Guide
-
-If you're a new contributor to InvokeAI or Open Source Projects, this is the guide for you. 
-
-## New Contributor Checklist
-- [x] Set up your local development environment & fork of InvokAI by following [the steps outlined here](../../installation/020_INSTALL_MANUAL.md#developer-install)
-- [x] Set up your local tooling with [this guide](InvokeAI/contributing/LOCAL_DEVELOPMENT/#developing-invokeai-in-vscode). Feel free to skip this step if you already have tooling you're comfortable with. 
-- [x] Familiarize yourself with [Git](https://www.atlassian.com/git) & our project structure by reading through the [development documentation](development.md)
-- [x] Join the [#dev-chat](https://discord.com/channels/1020123559063990373/1049495067846524939) channel of the Discord
-- [x] Choose an issue to work on! This can be achieved by asking in the #dev-chat channel, tackling a [good first issue](https://github.com/invoke-ai/InvokeAI/contribute) or finding an item on the [roadmap](https://github.com/orgs/invoke-ai/projects/7). If nothing in any of those places catches your eye, feel free to work on something of interest to you! 
-- [x] Make your first Pull Request with the guide below
-- [x] Happy development! Don't be afraid to ask for help - we're happy to help you contribute!
-
-
-## How do I make a contribution?
-
-Never made an open source contribution before? Wondering how contributions work in our project? Here's a quick rundown!
-
-Before starting these steps, ensure you have your local environment [configured for development](../LOCAL_DEVELOPMENT.md).
-
-1.  Find a [good first issue](https://github.com/invoke-ai/InvokeAI/contribute) that you are interested in addressing or a feature that you would like to add. Then, reach out to our team in the [#dev-chat](https://discord.com/channels/1020123559063990373/1049495067846524939) channel of the Discord to ensure you are  setup for success. 
-2. Fork the [InvokeAI](https://github.com/invoke-ai/InvokeAI) repository to your GitHub profile. This means that you will have a copy of the repository under **your-GitHub-username/InvokeAI**.
-3. Clone the repository to your local machine using:
-```bash
-git clone https://github.com/your-GitHub-username/InvokeAI.git
-```
-If you're unfamiliar with using Git through the commandline, [GitHub Desktop](https://desktop.github.com) is a easy-to-use alternative with a UI. You can do all the same steps listed here, but through the interface. 
-4. Create a new branch for your fix using:
-```bash
-git checkout -b branch-name-here
-```
-5. Make the appropriate changes for the issue you are trying to address or the feature that you want to add.
-6. Add the file contents of the changed files to the "snapshot" git uses to manage the state of the project, also known as the index:
-```bash
-git add -A
-```
-7. Store the contents of the index with a descriptive message.
-```bash
-git commit -m "Insert a short message of the changes made here"
-```
-8. Push the changes to the remote repository using
-```bash
-git push origin branch-name-here
-```
-9. Submit a pull request to the **main** branch of the InvokeAI repository. If you're not sure how to, [follow this guide](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request)
-10. Title the pull request with a short description of the changes made and the issue or bug number associated with your change. For example, you can title an issue like so "Added more log outputting to resolve #1234".
-11. In the description of the pull request, explain the changes that you made, any issues you think exist with the pull request you made, and any questions you have for the maintainer. It's OK if your pull request is not perfect (no pull request is), the reviewer will be able to help you fix any problems and improve it!
-12. Wait for the pull request to be reviewed by other collaborators.
-13. Make changes to the pull request if the reviewer(s) recommend them.
-14. Celebrate your success after your pull request is merged!
-
-If you’d like to learn more about contributing to Open Source projects, here is a [Getting Started Guide](https://opensource.com/article/19/7/create-pull-request-github). 
-
-
-## Best Practices: 
-* Keep your pull requests small. Smaller pull requests are more likely to be accepted and merged
-* Comments! Commenting your code helps reviewers easily understand your contribution
-* Use Python and Typescript’s typing systems, and consider using an editor with [LSP](https://microsoft.github.io/language-server-protocol/) support to streamline development
-* Make all communications public. This ensure knowledge is shared with the whole community
-
-
-## **Where can I go for help?**
-
-If you need help, you can ask questions in the [#dev-chat](https://discord.com/channels/1020123559063990373/1049495067846524939) channel of the Discord.
-
-For frontend related work, **@pyschedelicious** is the best person to reach out to. 
-
-For backend related work, please reach out to **@blessedcoolant**, **@lstein**, **@StAlKeR7779** or **@pyschedelicious**.

docs/contributing/contribution_guides/translation.md

@@ -1,19 +0,0 @@
-# Translation
-
-InvokeAI uses [Weblate](https://weblate.org/) for translation. Weblate is a FOSS project providing a scalable translation service. Weblate automates the tedious parts of managing translation of a growing project, and the service is generously provided at no cost to FOSS projects like InvokeAI.
-
-## Contributing
-
-If you'd like to contribute by adding or updating a translation, please visit our [Weblate project](https://hosted.weblate.org/engage/invokeai/). You'll need to sign in with your GitHub account (a number of other accounts are supported, including Google).
-
-Once signed in, select a language and then the Web UI component. From here you can Browse and Translate strings from English to your chosen language. Zen mode offers a simpler translation experience.
-
-Your changes will be attributed to you in the automated PR process; you don't need to do anything else.
-
-## Help & Questions
-
-Please check Weblate's [documentation](https://docs.weblate.org/en/latest/index.html) or ping @Harvestor on [Discord](https://discord.com/channels/1020123559063990373/1049495067846524939) if you have any questions.
-
-## Thanks
-
-Thanks to the InvokeAI community for their efforts to translate the project!

docs/contributing/contribution_guides/tutorials.md

@@ -1,11 +0,0 @@
-# Tutorials
-
-Tutorials help new & existing users expand their abilty to use InvokeAI to the full extent of our features and services.  
-
-Currently, we have a set of tutorials available on our [YouTube channel](https://www.youtube.com/@invokeai), but as InvokeAI continues to evolve with new updates, we want to ensure that we are giving our users the resources they need to succeed. 
-
-Tutorials can be in the form of videos or article walkthroughs on a subject of your choice. We recommend focusing tutorials on the key image generation methods, or on a specific component within one of the image generation methods.
-
-## Contributing
-
-Please reach out to @imic or @hipsterusername on [Discord](https://discord.gg/ZmtBAhwWhy) to help create tutorials for InvokeAI.

docs/contributing/frontend/OVERVIEW.md

@@ -1,133 +0,0 @@
-# Invoke UI
-
-Invoke's UI is made possible by many contributors and open-source libraries. Thank you!
-
-## Dev environment
-
-### Setup
-
-1. Install [node] and [pnpm].
-1. Run `pnpm i` to install all packages.
-
-#### Run in dev mode
-
-1. From `invokeai/frontend/web/`, run `pnpm dev`.
-1. From repo root, run `python scripts/invokeai-web.py`.
-1. Point your browser to the dev server address, e.g. <http://localhost:5173/>
-
-### Package scripts
-
-- `dev`: run the frontend in dev mode, enabling hot reloading
-- `build`: run all checks (madge, eslint, prettier, tsc) and then build the frontend
-- `typegen`: generate types from the OpenAPI schema (see [Type generation])
-- `lint:dpdm`: check circular dependencies
-- `lint:eslint`: check code quality
-- `lint:prettier`: check code formatting
-- `lint:tsc`: check type issues
-- `lint:knip`: check for unused exports or objects (failures here are just suggestions, not hard fails)
-- `lint`: run all checks concurrently
-- `fix`: run `eslint` and `prettier`, fixing fixable issues
-
-### Type generation
-
-We use [openapi-typescript] to generate types from the app's OpenAPI schema.
-
-The generated types are committed to the repo in [schema.ts].
-
-```sh
-# from the repo root, start the server
-python scripts/invokeai-web.py
-# from invokeai/frontend/web/, run the script
-pnpm typegen
-```
-
-### Localization
-
-We use [i18next] for localization, but translation to languages other than English happens on our [Weblate] project.
-
-Only the English source strings should be changed on this repo.
-
-### VSCode
-
-#### Example debugger config
-
-```jsonc
-{
-  "version": "0.2.0",
-  "configurations": [
-    {
-      "type": "chrome",
-      "request": "launch",
-      "name": "Invoke UI",
-      "url": "http://localhost:5173",
-      "webRoot": "${workspaceFolder}/invokeai/frontend/web"
-    }
-  ]
-}
-```
-
-#### Remote dev
-
-We've noticed an intermittent timeout issue with the VSCode remote dev port forwarding.
-
-We suggest disabling the editor's port forwarding feature and doing it manually via SSH:
-
-```sh
-ssh -L 9090:localhost:9090 -L 5173:localhost:5173 user@host
-```
-
-## Contributing Guidelines
-
-Thanks for your interest in contributing to the Invoke Web UI!
-
-Please follow these guidelines when contributing.
-
-### Check in before investing your time
-
-Please check in before you invest your time on anything besides a trivial fix, in case it conflicts with ongoing work or isn't aligned with the vision for the app.
-
-If a feature request or issue doesn't already exist for the thing you want to work on, please create one.
-
-Ping `@psychedelicious` on [discord] in the `#frontend-dev` channel or in the feature request / issue you want to work on - we're happy to chat.
-
-### Code conventions
-
-- This is a fairly complex app with a deep component tree. Please use memoization (`useCallback`, `useMemo`, `memo`) with enthusiasm.
-- If you need to add some global, ephemeral state, please use [nanostores] if possible.
-- Be careful with your redux selectors. If they need to be parameterized, consider creating them inside a `useMemo`.
-- Feel free to use `lodash` (via `lodash-es`) to make the intent of your code clear.
-- Please add comments describing the "why", not the "how" (unless it is really arcane).
-
-### Commit format
-
-Please use the [conventional commits] spec for the web UI, with a scope of "ui":
-
-- `chore(ui): bump deps`
-- `chore(ui): lint`
-- `feat(ui): add some cool new feature`
-- `fix(ui): fix some bug`
-
-### Submitting a PR
-
-- Ensure your branch is tidy. Use an interactive rebase to clean up the commit history and reword the commit messages if they are not descriptive.
-- Run `pnpm lint`. Some issues are auto-fixable with `pnpm fix`.
-- Fill out the PR form when creating the PR.
-  - It doesn't need to be super detailed, but a screenshot or video is nice if you changed something visually.
-  - If a section isn't relevant, delete it. There are no UI tests at this time.
-
-## Other docs
-
-- [Workflows - Design and Implementation]
-- [State Management]
-
-[node]: https://nodejs.org/en/download/
-[pnpm]: https://github.com/pnpm/pnpm
-[discord]: https://discord.gg/ZmtBAhwWhy
-[i18next]: https://github.com/i18next/react-i18next
-[Weblate]: https://hosted.weblate.org/engage/invokeai/
-[openapi-typescript]: https://github.com/drwpow/openapi-typescript
-[Type generation]: #type-generation
-[schema.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/services/api/schema.ts
-[conventional commits]: https://www.conventionalcommits.org/en/v1.0.0/
-[Workflows - Design and Implementation]: ./WORKFLOWS.md
-[State Management]: ./STATE_MGMT.md

docs/contributing/frontend/STATE_MGMT.md

@@ -1,38 +0,0 @@
-# State Management
-
-The app makes heavy use of Redux Toolkit, its Query library, and `nanostores`.
-
-## Redux
-
-TODO
-
-## `nanostores`
-
-[nanostores] is a tiny state management library. It provides both imperative and declarative APIs.
-
-### Example
-
-```ts
-export const $myStringOption = atom<string | null>(null);
-
-// Outside a component, or within a callback for performance-critical logic
-$myStringOption.get();
-$myStringOption.set('new value');
-
-// Inside a component
-const myStringOption = useStore($myStringOption);
-```
-
-### Where to put nanostores
-
-- For global application state, export your stores from `invokeai/frontend/web/src/app/store/nanostores/`.
-- For feature state, create a file for the stores next to the redux slice definition (e.g. `invokeai/frontend/web/src/features/myFeature/myFeatureNanostores.ts`).
-- For hooks with global state, export the store from the same file the hook is in, or put it next to the hook.
-
-### When to use nanostores
-
-- For non-serializable data that needs to be available throughout the app, use `nanostores` instead of a global.
-- For ephemeral global state (i.e. state that does not need to be persisted), use `nanostores` instead of redux.
-- For performance-critical code and in callbacks, redux selectors can be problematic due to the declarative reactivity system. Consider refactoring to use `nanostores` if there's a **measurable** performance issue.
-
-[nanostores]: https://github.com/nanostores/nanostores/

docs/contributing/frontend/WORKFLOWS.md

@@ -1,315 +0,0 @@
-# Workflows - Design and Implementation
-
-> This document describes, at a high level, the design and implementation of workflows in the InvokeAI frontend. There are a substantial number of implementation details not included, but which are hopefully clear from the code.
-
-InvokeAI's backend uses graphs, composed of **nodes** and **edges**, to process data and generate images.
-
-Nodes have any number of **input fields** and **output fields**. Edges connect nodes together via their inputs and outputs. Fields have data types which dictate how they may be connected.
-
-During execution, a nodes' outputs may be passed along to any number of other nodes' inputs.
-
-Workflows are an enriched abstraction over a graph.
-
-## Design
-
-InvokeAI provide two ways to build graphs in the frontend: the [Linear UI](#linear-ui) and [Workflow Editor](#workflow-editor).
-
-To better understand the use case and challenges related to workflows, we will review both of these modes.
-
-### Linear UI
-
-This includes the **Text to Image**, **Image to Image** and **Unified Canvas** tabs.
-
-The user-managed parameters on these tabs are stored as simple objects in the application state. When the user invokes, adding a generation to the queue, we internally build a graph from these parameters.
-
-This logic can be fairly complex due to the range of features available and their interactions. Depending on the parameters selected, the graph may be very different. Building graphs in code can be challenging - you are trying to construct a non-linear structure in a linear context.
-
-The simplest graph building logic is for **Text to Image** with a SD1.5 model: [buildLinearTextToImageGraph.ts]
-
-There are many other graph builders in the same directory for different tabs or base models (e.g. SDXL). Some are pretty hairy.
-
-In the Linear UI, we go straight from **simple application state** to **graph** via these builders.
-
-### Workflow Editor
-
-The Workflow Editor is a visual graph editor, allowing users to draw edges from node to node to construct a graph. This _far_ more approachable way to create complex graphs.
-
-InvokeAI uses the [reactflow] library to power the Workflow Editor. It provides both a graph editor UI and manages its own internal graph state.
-
-#### Workflows
-
-A workflow is a representation of a graph plus additional metadata:
-
-- Name
-- Description
-- Version
-- Notes
-- [Exposed fields](#workflow-linear-view)
-- Author, tags, category, etc.
-
-Workflows should have other qualities:
-
-- Portable: you should be able to load a workflow created by another person.
-- Resilient: you should be able to "upgrade" a workflow as the application changes.
-- Abstract: as much as is possible, workflows should not be married to the specific implementation details of the application.
-
-To support these qualities, workflows are serializable, have a versioned schemas, and represent graphs as minimally as possible. Fortunately, the reactflow state for nodes and edges works perfectly for this.
-
-##### Workflow -> reactflow state -> InvokeAI graph
-
-Given a workflow, we need to be able to derive reactflow state and/or an InvokeAI graph from it.
-
-The first step - workflow to reactflow state - is very simple. The logic is in [nodesSlice.ts], in the `workflowLoaded` reducer.
-
-The reactflow state is, however, structurally incompatible with our backend's graph structure. When a user invokes on a Workflow, we need to convert the reactflow state into an InvokeAI graph. This is far simpler than the graph building logic from the Linear UI:
-[buildNodesGraph.ts]
-
-##### Nodes vs Invocations
-
-We often use the terms "node" and "invocation" interchangeably, but they may refer to different things in the frontend.
-
-reactflow [has its own definitions][reactflow-concepts] of "node", "edge" and "handle" which are closely related to InvokeAI graph concepts.
-
-- A reactflow node is related to an InvokeAI invocation. It has a "data" property, which holds the InvokeAI-specific invocation data.
-- A reactflow edge is roughly equivalent to an InvokeAI edge.
-- A reactflow handle is roughly equivalent to an InvokeAI input or output field.
-
-##### Workflow Linear View
-
-Graphs are very capable data structures, but not everyone wants to work with them all the time.
-
-To allow less technical users - or anyone who wants a less visually noisy workspace - to benefit from the power of nodes, InvokeAI has a workflow feature called the Linear View.
-
-A workflow input field can be added to this Linear View, and its input component can be presented similarly to the Linear UI tabs. Internally, we add the field to the workflow's list of exposed fields.
-
-#### OpenAPI Schema
-
-OpenAPI is a schema specification that can represent complex data structures and relationships. The backend is capable of generating an OpenAPI schema for all invocations.
-
-When the UI connects, it requests this schema and parses each invocation into an **invocation template**. Invocation templates have a number of properties, like title, description and type, but the most important ones are their input and output **field templates**.
-
-Invocation and field templates are the "source of truth" for graphs, because they indicate what the backend is able to process.
-
-When a user adds a new node to their workflow, these templates are used to instantiate a node with fields instantiated from the input and output field templates.
-
-##### Field Instances and Templates
-
-Field templates consist of:
-
-- Name: the identifier of the field, its variable name in python
-- Type: derived from the field's type annotation in python (e.g. IntegerField, ImageField, MainModelField)
-- Constraints: derived from the field's creation args in python (e.g. minimum value for an integer)
-- Default value: optionally provided in the field's creation args (e.g. 42 for an integer)
-
-Field instances are created from the templates and have name, type and optionally a value.
-
-The type of the field determines the UI components that are rendered for it.
-
-A field instance's name associates it with its template.
-
-##### Stateful vs Stateless Fields
-
-**Stateful** fields store their value in the frontend graph. Think primitives, model identifiers, images, etc. Fields are only stateful if the frontend allows the user to directly input a value for them.
-
-Many field types, however, are **stateless**. An example is a `UNetField`, which contains some data describing a UNet. Users cannot directly provide this data - it is created and consumed in the backend.
-
-Stateless fields do not store their value in the node, so their field instances do not have values.
-
-"Custom" fields will always be treated as stateless fields.
-
-##### Collection and Scalar Fields
-
-Field types have a name and two flags which may identify it as a **collection** or **collection or scalar** field.
-
-If a field is annotated in python as a list, its field type is parsed and flagged as a **collection** type (e.g. `list[int]`).
-
-If it is annotated as a union of a type and list, the type will be flagged as a **collection or scalar** type (e.g. `Union[int, list[int]]`). Fields may not be unions of different types (e.g. `Union[int, list[str]]` and `Union[int, str]` are not allowed).
-
-## Implementation
-
-The majority of data structures in the backend are [pydantic] models. Pydantic provides OpenAPI schemas for all models and we then generate TypeScript types from those.
-
-The OpenAPI schema is parsed at runtime into our invocation templates.
-
-Workflows and all related data are modeled in the frontend using [zod]. Related types are inferred from the zod schemas.
-
-> In python, invocations are pydantic models with fields. These fields become node inputs. The invocation's `invoke()` function returns a pydantic model - its output. Like the invocation itself, the output model has any number of fields, which become node outputs.
-
-### zod Schemas and Types
-
-The zod schemas, inferred types, and type guards are in [types/].
-
-Roughly order from lowest-level to highest:
-
-- `common.ts`: stateful field data, and couple other misc types
-- `field.ts`: fields - types, values, instances, templates
-- `invocation.ts`: invocations and other node types
-- `workflow.ts`: workflows and constituents
-
-We customize the OpenAPI schema to include additional properties on invocation and field schemas. To facilitate parsing this schema into templates, we modify/wrap the types from [openapi-types] in `openapi.ts`.
-
-### OpenAPI Schema Parsing
-
-The entrypoint for OpenAPI schema parsing is [parseSchema.ts].
-
-General logic flow:
-
-- Iterate over all invocation schema objects
-  - Extract relevant invocation-level attributes (e.g. title, type, version, etc)
-  - Iterate over the invocation's input fields
-    - [Parse each field's type](#parsing-field-types)
-    - [Build a field input template](#building-field-input-templates) from the type - either a stateful template or "generic" stateless template
-  - Iterate over the invocation's output fields
-    - Parse the field's type (same as inputs)
-    - [Build a field output template](#building-field-output-templates)
-  - Assemble the attributes and fields into an invocation template
-
-Most of these involve very straightforward `reduce`s, but the less intuitive steps are detailed below.
-
-#### Parsing Field Types
-
-Field types are represented as structured objects:
-
-```ts
-type FieldType = {
-  name: string;
-  isCollection: boolean;
-  isCollectionOrScalar: boolean;
-};
-```
-
-The parsing logic is in `parseFieldType.ts`.
-
-There are 4 general cases for field type parsing.
-
-##### Primitive Types
-
-When a field is annotated as a primitive values (e.g. `int`, `str`, `float`), the field type parsing is fairly straightforward. The field is represented by a simple OpenAPI **schema object**, which has a `type` property.
-
-We create a field type name from this `type` string (e.g. `string` -> `StringField`).
-
-##### Complex Types
-
-When a field is annotated as a pydantic model (e.g. `ImageField`, `MainModelField`, `ControlField`), it is represented as a **reference object**. Reference objects are pointers to another schema or reference object within the schema.
-
-We need to **dereference** the schema to pull these out. Dereferencing may require recursion. We use the reference object's name directly for the field type name.
-
-> Unfortunately, at this time, we've had limited success using external libraries to deference at runtime, so we do this ourselves.
-
-##### Collection Types
-
-When a field is annotated as a list of a single type, the schema object has an `items` property. They may be a schema object or reference object and must be parsed to determine the item type.
-
-We use the item type for field type name, adding `isCollection: true` to the field type.
-
-##### Collection or Scalar Types
-
-When a field is annotated as a union of a type and list of that type, the schema object has an `anyOf` property, which holds a list of valid types for the union.
-
-After verifying that the union has two members (a type and list of the same type), we use the type for field type name, adding `isCollectionOrScalar: true` to the field type.
-
-##### Optional Fields
-
-In OpenAPI v3.1, when an object is optional, it is put into an `anyOf` along with a primitive schema object with `type: 'null'`.
-
-Handling this adds a fair bit of complexity, as we now must filter out the `'null'` types and work with the remaining types as described above.
-
-If there is a single remaining schema object, we must recursively call to `parseFieldType()` to get parse it.
-
-#### Building Field Input Templates
-
-Now that we have a field type, we can build an input template for the field.
-
-Stateful fields all get a function to build their template, while stateless fields are constructed directly. This is possible because stateless fields have no default value or constraints.
-
-See [buildFieldInputTemplate.ts].
-
-#### Building Field Output Templates
-
-Field outputs are similar to stateless fields - they do not have any value in the frontend. When building their templates, we don't need a special function for each field type.
-
-See [buildFieldOutputTemplate.ts].
-
-### Managing reactflow State
-
-As described above, the workflow editor state is the essentially the reactflow state, plus some extra metadata.
-
-We provide reactflow with an array of nodes and edges via redux, and a number of [event handlers][reactflow-events]. These handlers dispatch redux actions, managing nodes and edges.
-
-The pieces of redux state relevant to workflows are:
-
-- `state.nodes.nodes`: the reactflow nodes state
-- `state.nodes.edges`: the reactflow edges state
-- `state.nodes.workflow`: the workflow metadata
-
-#### Building Nodes and Edges
-
-A reactflow node has a few important top-level properties:
-
-- `id`: unique identifier
-- `type`: a string that maps to a react component to render the node
-- `position`: XY coordinates
-- `data`: arbitrary data
-
-When the user adds a node, we build **invocation node data**, storing it in `data`. Invocation properties (e.g. type, version, label, etc.) are copied from the invocation template. Inputs and outputs are built from the invocation template's field templates.
-
-See [buildInvocationNode.ts].
-
-Edges are managed by reactflow, but briefly, they consist of:
-
-- `source`: id of the source node
-- `sourceHandle`: id of the source node handle (output field)
-- `target`: id of the target node
-- `targetHandle`: id of the target node handle (input field)
-
-> Edge creation is gated behind validation logic. This validation compares the input and output field types and overall graph state.
-
-#### Building a Workflow
-
-Building a workflow entity is as simple as dropping the nodes, edges and metadata into an object.
-
-Each node and edge is parsed with a zod schema, which serves to strip out any unneeded data.
-
-See [buildWorkflow.ts].
-
-#### Loading a Workflow
-
-Workflows may be loaded from external sources or the user's local instance. In all cases, the workflow needs to be handled with care, as an untrusted object.
-
-Loading has a few stages which may throw or warn if there are problems:
-
-- Parsing the workflow data structure itself, [migrating](#workflow-migrations) it if necessary (throws)
-- Check for a template for each node (warns)
-- Check each node's version against its template (warns)
-- Validate the source and target of each edge (warns)
-
-This validation occurs in [validateWorkflow.ts].
-
-If there are no fatal errors, the workflow is then stored in redux state.
-
-### Workflow Migrations
-
-When the workflow schema changes, we may need to perform some data migrations. This occurs as workflows are loaded. zod schemas for each workflow schema version is retained to facilitate migrations.
-
-Previous schemas are in folders in `invokeai/frontend/web/src/features/nodes/types/`, eg `v1/`.
-
-Migration logic is in [migrations.ts].
-
-<!-- links -->
-
-[pydantic]: https://github.com/pydantic/pydantic 'pydantic'
-[zod]: https://github.com/colinhacks/zod 'zod'
-[openapi-types]: https://github.com/kogosoftwarellc/open-api/tree/main/packages/openapi-types 'openapi-types'
-[reactflow]: https://github.com/xyflow/xyflow 'reactflow'
-[reactflow-concepts]: https://reactflow.dev/learn/concepts/terms-and-definitions
-[reactflow-events]: https://reactflow.dev/api-reference/react-flow#event-handlers
-[buildWorkflow.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/features/nodes/util/workflow/buildWorkflow.ts
-[nodesSlice.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts
-[buildLinearTextToImageGraph.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/features/nodes/util/graph/buildLinearTextToImageGraph.ts
-[buildNodesGraph.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/features/nodes/util/graph/buildNodesGraph.ts
-[buildInvocationNode.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/features/nodes/util/node/buildInvocationNode.ts
-[validateWorkflow.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/features/nodes/util/workflow/validateWorkflow.ts
-[migrations.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/features/nodes/util/workflow/migrations.ts
-[parseSchema.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/features/nodes/util/schema/parseSchema.ts
-[buildFieldInputTemplate.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/features/nodes/util/schema/buildFieldInputTemplate.ts
-[buildFieldOutputTemplate.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/features/nodes/util/schema/buildFieldOutputTemplate.ts

docs/deprecated/CLI.md

@@ -0,0 +1,589 @@
+---
+title: Command-Line Interface
+---
+
+# :material-bash: CLI
+
+## **Interactive Command Line Interface**
+
+The InvokeAI command line interface (CLI) provides scriptable access
+to InvokeAI's features.Some advanced features are only available
+through the CLI, though they eventually find their way into the WebUI.
+
+The CLI is accessible from the `invoke.sh`/`invoke.bat` launcher by
+selecting option (1). Alternatively, it can be launched directly from
+the command line by activating the InvokeAI environment and giving the
+command:
+
+```bash
+invokeai
+```
+
+After some startup messages, you will be presented with the `invoke> `
+prompt. Here you can type prompts to generate images and issue other
+commands to load and manipulate generative models. The CLI has a large
+number of command-line options that control its behavior. To get a
+concise summary of the options, call `invokeai` with the `--help` argument:
+
+```bash
+invokeai --help
+```
+
+The script uses the readline library to allow for in-line editing, command
+history (++up++ and ++down++), autocompletion, and more. To help keep track of
+which prompts generated which images, the script writes a log file of image
+names and prompts to the selected output directory.
+
+Here is a typical session
+
+```bash
+PS1:C:\Users\fred> invokeai
+* Initializing, be patient...
+* Initializing, be patient...
+>> Initialization file /home/lstein/invokeai/invokeai.init found. Loading...
+>> Internet connectivity is True
+>> InvokeAI, version 2.3.0-rc5
+>> InvokeAI runtime directory is "/home/lstein/invokeai"
+>> GFPGAN Initialized
+>> CodeFormer Initialized
+>> ESRGAN Initialized
+>> Using device_type cuda
+>> xformers memory-efficient attention is available and enabled
+     (...more initialization messages...)
+* Initialization done! Awaiting your command (-h for help, 'q' to quit)
+invoke> ashley judd riding a camel -n2 -s150
+Outputs:
+   outputs/img-samples/00009.png: "ashley judd riding a camel" -n2 -s150 -S 416354203
+   outputs/img-samples/00010.png: "ashley judd riding a camel" -n2 -s150 -S 1362479620
+
+invoke> "there's a fly in my soup" -n6 -g
+    outputs/img-samples/00011.png: "there's a fly in my soup" -n6 -g -S 2685670268
+    seeds for individual rows: [2685670268, 1216708065, 2335773498, 822223658, 714542046, 3395302430]
+invoke> q
+```
+
+![invoke-py-demo](../assets/dream-py-demo.png)
+
+## Arguments
+
+The script recognizes a series of command-line switches that will
+change important global defaults, such as the directory for image
+outputs and the location of the model weight files.
+
+### List of arguments recognized at the command line
+
+These command-line arguments can be passed to `invoke.py` when you first run it
+from the Windows, Mac or Linux command line. Some set defaults that can be
+overridden on a per-prompt basis (see
+[List of prompt arguments](#list-of-prompt-arguments). Others
+
+| Argument <img width="240" align="right"/> | Shortcut <img width="100" align="right"/> | Default <img width="320" align="right"/>       | Description                                                                                          |
+| ----------------------------------------- | ----------------------------------------- | ---------------------------------------------- | ---------------------------------------------------------------------------------------------------- |
+| `--help`                                  | `-h`                                      |                                                | Print a concise help message.                                                                        |
+| `--outdir <path>`                         | `-o<path>`                                | `outputs/img_samples`                          | Location for generated images.                                                                       |
+| `--prompt_as_dir`                         | `-p`                                      | `False`                                        | Name output directories using the prompt text.                                                       |
+| `--from_file <path>`                      |                                           | `None`                                         | Read list of prompts from a file. Use `-` to read from standard input                                |
+| `--model <modelname>`                     |                                           | `stable-diffusion-1.5`                         | Loads the initial model specified in configs/models.yaml. |
+| `--ckpt_convert `           |                                                         | `False`                                        | If provided both .ckpt and .safetensors files will be auto-converted into diffusers format in memory |
+| `--autoconvert <path>`                    |                          | `None`                                        | On startup, scan the indicated directory for new .ckpt/.safetensor files and automatically convert and import them |
+| `--precision`                             |                                           | `fp16`                                         | Provide `fp32` for full precision mode, `fp16` for half-precision. `fp32` needed for Macintoshes and some NVidia cards. |
+| `--png_compression <0-9>`                 | `-z<0-9>`                                 | `6`                                            | Select level of compression for output files, from 0 (no compression) to 9 (max compression)         |
+| `--safety-checker`                        |                                           | `False`                                        | Activate safety checker for NSFW and other potentially disturbing imagery                            |
+| `--patchmatch`, `--no-patchmatch`                 |                                   | `--patchmatch`                                        | Load/Don't load the PatchMatch inpainting extension    |
+| `--xformers`, `--no-xformers`                 |                                   | `--xformers`                                        | Load/Don't load the Xformers memory-efficient attention module (CUDA only)    |
+| `--web`                                   |                                           | `False`                                        | Start in web server mode                                                                             |
+| `--host <ip addr>`                        |                                           | `localhost`                                    | Which network interface web server should listen on. Set to 0.0.0.0 to listen on any.                |
+| `--port <port>`                           |                                           | `9090`                                         | Which port web server should listen for requests on.                                                 |
+| `--config <path>`                         |                                           | `configs/models.yaml`                          | Configuration file for models and their weights.                                                     |
+| `--iterations <int>`                      | `-n<int>`                                 | `1`                                            | How many images to generate per prompt.                                                              |
+| `--width <int>`                           | `-W<int>`                                 | `512`                                    | Width of generated image                                                                                                                                                                                                                         |
+| `--height <int>`                          | `-H<int>`                                 | `512`                                    | Height of generated image                                                                                                        | `--steps <int>`                           | `-s<int>`                                 | `50`                                     | How many steps of refinement to apply                                                                                                                                                                                                            |
+| `--strength <float>`                      | `-s<float>` | `0.75`  | For img2img: how hard to try to match the prompt to the initial image. Ranges from 0.0-0.99, with higher values replacing the initial image completely. |
+| `--fit`                                   | `-F`        | `False` | For img2img: scale the init image to fit into the specified -H and -W dimensions                                                                             |
+| `--grid`                                  | `-g`                                      | `False`                                        | Save all image series as a grid rather than individually.                                            |
+| `--sampler <sampler>`                     | `-A<sampler>`                             | `k_lms`                                        | Sampler to use. Use `-h` to get list of available samplers.                                          |
+| `--seamless`                              |                                           | `False`                                        | Create interesting effects by tiling elements of the image.                                          |
+| `--embedding_path <path>`                 |                                           | `None`                                         | Path to pre-trained embedding manager checkpoints, for custom models                                 |
+| `--gfpgan_model_path`                     |                                           | `experiments/pretrained_models/GFPGANv1.4.pth` | Path to GFPGAN model file.                                              |
+| `--free_gpu_mem`                          |                                           | `False`                                        | Free GPU memory after sampling, to allow image decoding and saving in low VRAM conditions            |
+| `--precision`                             |                                           | `auto`                                         | Set model precision, default is selected by device. Options: auto, float32, float16, autocast        |
+
+!!! warning "These arguments are deprecated but still work"
+
+    <div align="center" markdown>
+
+    | Argument           |  Shortcut  |  Default            |  Description |
+    |--------------------|------------|---------------------|--------------|
+    | `--full_precision`  |             | `False`                | Same as `--precision=fp32`|
+    | `--weights <path>`   |            | `None`                | Path to weights file; use `--model stable-diffusion-1.4` instead |
+    | `--laion400m`        | `-l`         | `False`               | Use older LAION400m weights; use `--model=laion400m` instead |
+
+    </div>
+
+!!! tip
+
+      On Windows systems, you may run into
+      problems when passing the invoke script standard backslashed path
+      names because the Python interpreter treats "\" as an escape.
+      You can either double your slashes (ick): `C:\\path\\to\\my\\file`, or
+      use Linux/Mac style forward slashes (better): `C:/path/to/my/file`.
+
+## The .invokeai initialization file
+
+To start up invoke.py with your preferred settings, place your desired
+startup options in a file in your home directory named `.invokeai` The
+file should contain the startup options as you would type them on the
+command line (`--steps=10 --grid`), one argument per line, or a
+mixture of both using any of the accepted command switch formats:
+
+!!! example "my unmodified initialization file"
+
+    ```bash title="~/.invokeai" linenums="1"
+    # InvokeAI initialization file
+    # This is the InvokeAI initialization file, which contains command-line default values.
+    # Feel free to edit. If anything goes wrong, you can re-initialize this file by deleting
+    # or renaming it and then running invokeai-configure again.
+
+    # The --root option below points to the folder in which InvokeAI stores its models, configs and outputs.
+    --root="/Users/mauwii/invokeai"
+
+    # the --outdir option controls the default location of image files.
+    --outdir="/Users/mauwii/invokeai/outputs"
+
+    # You may place other  frequently-used startup commands here, one or more per line.
+    # Examples:
+    # --web --host=0.0.0.0
+    # --steps=20
+    # -Ak_euler_a -C10.0
+    ```
+
+!!! note
+
+    The  initialization file only accepts the command line arguments.
+    There are additional arguments that you can provide on the `invoke>` command
+    line (such as `-n` or `--iterations`) that cannot be entered into this file.
+    Also be alert for empty blank lines at the end of the file, which will cause
+    an arguments error at startup time.
+
+## List of prompt arguments
+
+After the invoke.py script initializes, it will present you with a `invoke>`
+prompt. Here you can enter information to generate images from text
+([txt2img](#txt2img)), to embellish an existing image or sketch
+([img2img](#img2img)), or to selectively alter chosen regions of the image
+([inpainting](#inpainting)).
+
+### txt2img
+
+!!! example ""
+
+    ```bash
+    invoke> waterfall and rainbow -W640 -H480
+    ```
+
+    This will create the requested image with the dimensions 640 (width)
+    and 480 (height).
+
+Here are the invoke> command that apply to txt2img:
+
+| Argument <img width="680" align="right"/> | Shortcut <img width="420" align="right"/> | Default <img width="480" align="right"/> | Description                                                                                                                                                                                                                                      |
+| ----------------------------------------- | ----------------------------------------- | ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
+| "my prompt"                               |                                           |                                          | Text prompt to use. The quotation marks are optional.                                                                                                                                                                                            |
+| `--width <int>`                           | `-W<int>`                                 | `512`                                    | Width of generated image                                                                                                                                                                                                                         |
+| `--height <int>`                          | `-H<int>`                                 | `512`                                    | Height of generated image                                                                                                                                                                                                                        |
+| `--iterations <int>`                      | `-n<int>`                                 | `1`                                      | How many images to generate from this prompt                                                                                                                                                                                                     |
+| `--steps <int>`                           | `-s<int>`                                 | `50`                                     | How many steps of refinement to apply                                                                                                                                                                                                            |
+| `--cfg_scale <float>`                     | `-C<float>`                               | `7.5`                                    | How hard to try to match the prompt to the generated image; any number greater than 1.0 works, but the useful range is roughly 5.0 to 20.0                                                                                                       |
+| `--seed <int>`                            | `-S<int>`                                 | `None`                                   | Set the random seed for the next series of images. This can be used to recreate an image generated previously.                                                                                                                                   |
+| `--sampler <sampler>`                     | `-A<sampler>`                             | `k_lms`                                  | Sampler to use. Use -h to get list of available samplers.                                                                                                                                                                                        |
+| `--karras_max <int>`                      |                                           | `29`                                     | When using k\_\* samplers, set the maximum number of steps before shifting from using the Karras noise schedule (good for low step counts) to the LatentDiffusion noise schedule (good for high step counts) This value is sticky. [29]          |
+| `--hires_fix`                             |                                           |                                          | Larger images often have duplication artefacts. This option suppresses duplicates by generating the image at low res, and then using img2img to increase the resolution                                                                          |
+| `--png_compression <0-9>`                 | `-z<0-9>`                                 | `6`                                      | Select level of compression for output files, from 0 (no compression) to 9 (max compression)                                                                                                                                                     |
+| `--grid`                                  | `-g`                                      | `False`                                  | Turn on grid mode to return a single image combining all the images generated by this prompt                                                                                                                                                     |
+| `--individual`                            | `-i`                                      | `True`                                   | Turn off grid mode (deprecated; leave off --grid instead)                                                                                                                                                                                        |
+| `--outdir <path>`                         | `-o<path>`                                | `outputs/img_samples`                    | Temporarily change the location of these images                                                                                                                                                                                                  |
+| `--seamless`                              |                                           | `False`                                  | Activate seamless tiling for interesting effects                                                                                                                                                                                                 |
+| `--seamless_axes`                         |                                           | `x,y`                                    | Specify which axes to use circular convolution on.                                                                                                                                                                                               |
+| `--log_tokenization`                      | `-t`                                      | `False`                                  | Display a color-coded list of the parsed tokens derived from the prompt                                                                                                                                                                          |
+| `--skip_normalization`                    | `-x`                                      | `False`                                  | Weighted subprompts will not be normalized. See [Weighted Prompts](../features/OTHER.md#weighted-prompts)                                                                                                                                                  |
+| `--upscale <int> <float>`                 | `-U <int> <float>`                        | `-U 1 0.75`                              | Upscale image by magnification factor (2, 4), and set strength of upscaling (0.0-1.0). If strength not set, will default to 0.75.                                                                                                                |
+| `--facetool_strength <float>`             | `-G <float> `                             | `-G0`                                    | Fix faces (defaults to using the GFPGAN algorithm); argument indicates how hard the algorithm should try (0.0-1.0)                                                                                                                               |
+| `--facetool <name>`                       | `-ft <name>`                              | `-ft gfpgan`                             | Select face restoration algorithm to use: gfpgan, codeformer                                                                                                                                                                                     |
+| `--codeformer_fidelity`                   | `-cf <float>`                             | `0.75`                                   | Used along with CodeFormer. Takes values between 0 and 1. 0 produces high quality but low accuracy. 1 produces high accuracy but low quality                                                                                                     |
+| `--save_original`                         | `-save_orig`                              | `False`                                  | When upscaling or fixing faces, this will cause the original image to be saved rather than replaced.                                                                                                                                             |
+| `--variation <float>`                     | `-v<float>`                               | `0.0`                                    | Add a bit of noise (0.0=none, 1.0=high) to the image in order to generate a series of variations. Usually used in combination with `-S<seed>` and `-n<int>` to generate a series a riffs on a starting image. See [Variations](../features/VARIATIONS.md). |
+| `--with_variations <pattern>`             |                                           | `None`                                   | Combine two or more variations. See [Variations](../features/VARIATIONS.md) for now to use this.                                                                                                                                                           |
+| `--save_intermediates <n>`                |                                           | `None`                                   | Save the image from every nth step into an "intermediates" folder inside the output directory                                                                                                                                                    |
+| `--h_symmetry_time_pct <float>`           |                                           | `None`                                   | Create symmetry along the X axis at the desired percent complete of the generation process. (Must be between 0.0 and 1.0; set to a very small number like 0.0001 for just after the first step of generation.)                                   |
+| `--v_symmetry_time_pct <float>`           |                                           | `None`                                   | Create symmetry along the Y axis at the desired percent complete of the generation process. (Must be between 0.0 and 1.0; set to a very small number like 0.0001 for just after the first step of generation.)                                   |
+
+!!! note
+
+    the width and height of the image must be multiples of 64. You can
+    provide different values, but they will be rounded down to the nearest multiple
+    of 64.
+
+!!! example "This is a example of img2img"
+
+    ```bash
+    invoke> waterfall and rainbow -I./vacation-photo.png -W640 -H480 --fit
+    ```
+
+This will modify the indicated vacation photograph by making it more like the
+prompt. Results will vary greatly depending on what is in the image. We also ask
+to --fit the image into a box no bigger than 640x480. Otherwise the image size
+will be identical to the provided photo and you may run out of memory if it is
+large.
+
+In addition to the command-line options recognized by txt2img, img2img accepts
+additional options:
+
+| Argument <img width="160" align="right"/> | Shortcut    | Default | Description                                                                                                                                |
+| ----------------------------------------- | ----------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
+| `--init_img <path>`                       | `-I<path>`  | `None`  | Path to the initialization image                                                                                                           |
+| `--fit`                                   | `-F`        | `False` | Scale the image to fit into the specified -H and -W dimensions                                                                             |
+| `--strength <float>`                      | `-s<float>` | `0.75`  | How hard to try to match the prompt to the initial image. Ranges from 0.0-0.99, with higher values replacing the initial image completely. |
+
+### inpainting
+
+!!! example ""
+
+    ```bash
+    invoke> waterfall and rainbow -I./vacation-photo.png -M./vacation-mask.png -W640 -H480 --fit
+    ```
+
+    This will do the same thing as img2img, but image alterations will
+    only occur within transparent areas defined by the mask file specified
+    by `-M`. You may also supply just a single initial image with the areas
+    to overpaint made transparent, but you must be careful not to destroy
+    the pixels underneath when you create the transparent areas. See
+    [Inpainting](INPAINTING.md) for details.
+
+inpainting accepts all the arguments used for txt2img and img2img, as well as
+the --mask (-M) and --text_mask (-tm) arguments:
+
+| Argument <img width="100" align="right"/> | Shortcut                 | Default | Description                                                                                      |
+| ----------------------------------------- | ------------------------ | ------- | ------------------------------------------------------------------------------------------------ |
+| `--init_mask <path>`                      | `-M<path>`               | `None`  | Path to an image the same size as the initial_image, with areas for inpainting made transparent. |
+| `--invert_mask `                          |                          | False   | If true, invert the mask so that transparent areas are opaque and vice versa.                    |
+| `--text_mask <prompt> [<float>]`          | `-tm <prompt> [<float>]` | <none>  | Create a mask from a text prompt describing part of the image                                    |
+
+The mask may either be an image with transparent areas, in which case the
+inpainting will occur in the transparent areas only, or a black and white image,
+in which case all black areas will be painted into.
+
+`--text_mask` (short form `-tm`) is a way to generate a mask using a text
+description of the part of the image to replace. For example, if you have an
+image of a breakfast plate with a bagel, toast and scrambled eggs, you can
+selectively mask the bagel and replace it with a piece of cake this way:
+
+```bash
+invoke> a piece of cake -I /path/to/breakfast.png -tm bagel
+```
+
+The algorithm uses <a
+href="https://github.com/timojl/clipseg">clipseg</a> to classify different
+regions of the image. The classifier puts out a confidence score for each region
+it identifies. Generally regions that score above 0.5 are reliable, but if you
+are getting too much or too little masking you can adjust the threshold down (to
+get more mask), or up (to get less). In this example, by passing `-tm` a higher
+value, we are insisting on a more stringent classification.
+
+```bash
+invoke> a piece of cake -I /path/to/breakfast.png -tm bagel 0.6
+```
+
+### Custom Styles and Subjects
+
+You can load and use hundreds of community-contributed Textual
+Inversion models just by typing the appropriate trigger phrase. Please
+see [Concepts Library](../features/CONCEPTS.md) for more details.
+
+## Other Commands
+
+The CLI offers a number of commands that begin with "!".
+
+### Postprocessing images
+
+To postprocess a file using face restoration or upscaling, use the `!fix`
+command.
+
+#### `!fix`
+
+This command runs a post-processor on a previously-generated image. It takes a
+PNG filename or path and applies your choice of the `-U`, `-G`, or `--embiggen`
+switches in order to fix faces or upscale. If you provide a filename, the script
+will look for it in the current output directory. Otherwise you can provide a
+full or partial path to the desired file.
+
+Some examples:
+
+!!! example "Upscale to 4X its original size and fix faces using codeformer"
+
+    ```bash
+    invoke> !fix 0000045.4829112.png -G1 -U4 -ft codeformer
+    ```
+
+!!! example "Use the GFPGAN algorithm to fix faces, then upscale to 3X using --embiggen"
+
+    ```bash
+    invoke> !fix 0000045.4829112.png -G0.8 -ft gfpgan
+    >> fixing outputs/img-samples/0000045.4829112.png
+    >> retrieved seed 4829112 and prompt "boy enjoying a banana split"
+    >> GFPGAN - Restoring Faces for image seed:4829112
+    Outputs:
+    [1] outputs/img-samples/000017.4829112.gfpgan-00.png: !fix "outputs/img-samples/0000045.4829112.png" -s 50 -S  -W 512 -H 512 -C 7.5 -A k_lms -G 0.8
+    ```
+
+#### `!mask`
+
+This command takes an image, a text prompt, and uses the `clipseg` algorithm to
+automatically generate a mask of the area that matches the text prompt. It is
+useful for debugging the text masking process prior to inpainting with the
+`--text_mask` argument. See [INPAINTING.md] for details.
+
+### Model selection and importation
+
+The CLI allows you to add new models on the fly, as well as to switch
+among them rapidly without leaving the script. There are several
+different model formats, each described in the [Model Installation
+Guide](../installation/050_INSTALLING_MODELS.md).
+
+#### `!models`
+
+This prints out a list of the models defined in `config/models.yaml'. The active
+model is bold-faced
+
+Example:
+
+<pre>
+inpainting-1.5            not loaded  Stable Diffusion inpainting model
+<b>stable-diffusion-1.5          active  Stable Diffusion v1.5</b>
+waifu-diffusion           not loaded  Waifu Diffusion v1.4
+</pre>
+
+#### `!switch <model>`
+
+This quickly switches from one model to another without leaving the CLI script.
+`invoke.py` uses a memory caching system; once a model has been loaded,
+switching back and forth is quick. The following example shows this in action.
+Note how the second column of the `!models` table changes to `cached` after a
+model is first loaded, and that the long initialization step is not needed when
+loading a cached model.
+
+#### `!import_model <hugging_face_repo_ID>`
+
+This imports and installs a `diffusers`-style model that is stored on
+the [HuggingFace Web Site](https://huggingface.co). You can look up
+any [Stable Diffusion diffusers
+model](https://huggingface.co/models?library=diffusers) and install it
+with a command like the following:
+
+```bash
+!import_model prompthero/openjourney
+```
+
+#### `!import_model <path/to/diffusers/directory>`
+
+If you have a copy of a `diffusers`-style model saved to disk, you can
+import it by passing the path to model's top-level directory.
+
+#### `!import_model <url>`
+
+For a `.ckpt` or `.safetensors` file, if you have a direct download
+URL for the file, you can provide it to `!import_model` and the file
+will be downloaded and installed for you.
+
+#### `!import_model <path/to/model/weights.ckpt>`
+
+This command imports a new model weights file into InvokeAI, makes it available
+for image generation within the script, and writes out the configuration for the
+model into `config/models.yaml` for use in subsequent sessions.
+
+Provide `!import_model` with the path to a weights file ending in `.ckpt`. If
+you type a partial path and press tab, the CLI will autocomplete. Although it
+will also autocomplete to `.vae` files, these are not currenty supported (but
+will be soon).
+
+When you hit return, the CLI will prompt you to fill in additional information
+about the model, including the short name you wish to use for it with the
+`!switch` command, a brief description of the model, the default image width and
+height to use with this model, and the model's configuration file. The latter
+three fields are automatically filled with reasonable defaults. In the example
+below, the bold-faced text shows what the user typed in with the exception of
+the width, height and configuration file paths, which were filled in
+automatically.
+
+#### `!import_model <path/to/directory_of_models>`
+
+If you provide the path of a directory that contains one or more
+`.ckpt` or `.safetensors` files, the CLI will scan the directory and
+interactively offer to import the models it finds there. Also see the
+`--autoconvert` command-line option.
+
+#### `!edit_model <name_of_model>`
+
+The `!edit_model` command can be used to modify a model that is already defined
+in `config/models.yaml`. Call it with the short name of the model you wish to
+modify, and it will allow you to modify the model's `description`, `weights` and
+other fields.
+
+Example:
+
+<pre>
+invoke> <b>!edit_model waifu-diffusion</b>
+>> Editing model waifu-diffusion from configuration file ./configs/models.yaml
+description: <b>Waifu diffusion v1.4beta</b>
+weights: models/ldm/stable-diffusion-v1/<b>model-epoch10-float16.ckpt</b>
+config: configs/stable-diffusion/v1-inference.yaml
+width: 512
+height: 512
+
+>> New configuration:
+waifu-diffusion:
+  config: configs/stable-diffusion/v1-inference.yaml
+  description: Waifu diffusion v1.4beta
+  weights: models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt
+  height: 512
+  width: 512
+
+OK to import [n]? y
+>> Caching model stable-diffusion-1.4 in system RAM
+>> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch10-float16.ckpt
+...
+</pre>
+
+### History processing
+
+The CLI provides a series of convenient commands for reviewing previous actions,
+retrieving them, modifying them, and re-running them.
+
+#### `!history`
+
+The invoke script keeps track of all the commands you issue during a session,
+allowing you to re-run them. On Mac and Linux systems, it also writes the
+command-line history out to disk, giving you access to the most recent 1000
+commands issued.
+
+The `!history` command will return a numbered list of all the commands issued
+during the session (Windows), or the most recent 1000 commands (Mac|Linux). You
+can then repeat a command by using the command `!NNN`, where "NNN" is the
+history line number. For example:
+
+!!! example ""
+
+    ```bash
+    invoke> !history
+    ...
+    [14] happy woman sitting under tree wearing broad hat and flowing garment
+    [15] beautiful woman sitting under tree wearing broad hat and flowing garment
+    [18] beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6
+    [20] watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
+    [21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
+    ...
+    invoke> !20
+    invoke> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
+    ```
+
+####`!fetch`
+
+This command retrieves the generation parameters from a previously generated
+image and either loads them into the command line (Linux|Mac), or prints them
+out in a comment for copy-and-paste (Windows). You may provide either the name
+of a file in the current output directory, or a full file path. Specify path to
+a folder with image png files, and wildcard \*.png to retrieve the dream command
+used to generate the images, and save them to a file commands.txt for further
+processing.
+
+!!! example "load the generation command for a single png file"
+
+    ```bash
+    invoke> !fetch 0000015.8929913.png
+    # the script returns the next line, ready for editing and running:
+    invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
+    ```
+
+!!! example "fetch the generation commands from a batch of files and store them into `selected.txt`"
+
+    ```bash
+    invoke> !fetch outputs\selected-imgs\*.png selected.txt
+    ```
+
+#### `!replay`
+
+This command replays a text file generated by !fetch or created manually
+
+!!! example
+
+    ```bash
+    invoke> !replay outputs\selected-imgs\selected.txt
+    ```
+
+!!! note
+
+    These commands may behave unexpectedly if given a PNG file that was
+    not generated by InvokeAI.
+
+#### `!search <search string>`
+
+This is similar to !history but it only returns lines that contain
+`search string`. For example:
+
+```bash
+invoke> !search surreal
+[21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
+```
+
+#### `!clear`
+
+This clears the search history from memory and disk. Be advised that this
+operation is irreversible and does not issue any warnings!
+
+## Command-line editing and completion
+
+The command-line offers convenient history tracking, editing, and command
+completion.
+
+- To scroll through previous commands and potentially edit/reuse them, use the
+  ++up++ and ++down++ keys.
+- To edit the current command, use the ++left++ and ++right++ keys to position
+  the cursor, and then ++backspace++, ++delete++ or insert characters.
+- To move to the very beginning of the command, type ++ctrl+a++ (or
+  ++command+a++ on the Mac)
+- To move to the end of the command, type ++ctrl+e++.
+- To cut a section of the command, position the cursor where you want to start
+  cutting and type ++ctrl+k++
+- To paste a cut section back in, position the cursor where you want to paste,
+  and type ++ctrl+y++
+
+Windows users can get similar, but more limited, functionality if they launch
+`invoke.py` with the `winpty` program and have the `pyreadline3` library
+installed:
+
+```batch
+> winpty python scripts\invoke.py
+```
+
+On the Mac and Linux platforms, when you exit invoke.py, the last 1000 lines of
+your command-line history will be saved. When you restart `invoke.py`, you can
+access the saved history using the ++up++ key.
+
+In addition, limited command-line completion is installed. In various contexts,
+you can start typing your command and press ++tab++. A list of potential
+completions will be presented to you. You can then type a little more, hit
+++tab++ again, and eventually autocomplete what you want.
+
+When specifying file paths using the one-letter shortcuts, the CLI will attempt
+to complete pathnames for you. This is most handy for the `-I` (init image) and
+`-M` (init mask) paths. To initiate completion, start the path with a slash
+(`/`) or `./`. For example:
+
+```bash
+invoke> zebra with a mustache -I./test-pictures<TAB>
+-I./test-pictures/Lincoln-and-Parrot.png  -I./test-pictures/zebra.jpg        -I./test-pictures/madonna.png
+-I./test-pictures/bad-sketch.png          -I./test-pictures/man_with_eagle/
+```
+
+You can then type ++z++, hit ++tab++ again, and it will autofill to `zebra.jpg`.
+
+More text completion features (such as autocompleting seeds) are on their way.