add board dropdown to use instead of whichever board theyre viewing

.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@v4
-      with:
-        version: 8.15.6
-        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 you have tested the changes in this PR. Provide enough detail that a reviewer can reproduce your tests.-->
-
-## 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==0.6.0
-        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-14
-            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-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
-and/or Work shall terminate as of the date such litigation is asserted
-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,
-with or without modifications, provided that You meet the following
-conditions: Use-based restrictions as referenced in paragraph 5 MUST
-be included as an enforceable provision by You in any type of legal
-agreement (e.g. a license) governing the use and/or distribution of
-the Model or Derivatives of the Model, and You shall give notice to
-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
-for lawful purposes and in accordance with the License. Use may
-include creating any content with, finetuning, updating, running,
-training, evaluating and/or reparametrizing the Model. You shall
-require all of Your users who use the Model or a Derivative of the
-Model to comply with the terms of this paragraph (paragraph 5).
-
-The Output You Generate.  Except as set forth herein, Licensor claims
-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
-suggest endorsement or misrepresent the relationship between the
-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
-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 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
-has been advised of the possibility of such damages.
-
-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

@@ -1,76 +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!)"
-	@echo "openapi                  Generate the OpenAPI schema for the app, outputting to stdout"
-
-# 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
-
-# Generate the OpenAPI Schema for the app
-openapi:
-	python scripts/generate_openapi_schema.py

README.md

@@ -1,142 +1,22 @@
 <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]
-
-[![discord badge]][discord link] [![latest release badge]][latest release link] [![github stars badge]][github stars link] [![github forks badge]][github forks link] [![CI checks on main badge]][CI checks on main link] [![latest commit to main badge]][latest commit to main link] [![github open issues badge]][github open issues link] [![github open prs badge]][github open prs link] [![translation status badge]][translation status link]
-
-</div>
-
-Invoke is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. Invoke offers an industry leading web-based UI, and serves as the foundation for multiple commercial products.
-
-Invoke is available in two editions:
-
-| **Community Edition**                                                                                                      | **Professional Edition**                                                                            |
-|----------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------|
-| **For users looking for a locally installed, self-hosted and self-managed service**                                         | **For users or teams looking for a cloud-hosted, fully managed service**                            |
-| - Free to use under a commercially-friendly license                                                                         | - Monthly subscription fee with three different plan levels                                         |
-| - Download and install on compatible hardware                                                                               | - Offers additional benefits, including multi-user support, improved model training, and more                          |
-| - Includes all core studio features: generate, refine, iterate on images, and build workflows                               | - Hosted in the cloud for easy, secure model access and scalability                                               |
-| Quick Start -> [Installation and Updates][installation docs]                                                                     | More Information -> [www.invoke.com/pricing](https://www.invoke.com/pricing)                        |
+# Invoke AI - Generative AI for Professional Creatives
+## Professional Creative Tools for Stable Diffusion, Custom-Trained Models, and more. 
+  To learn more about Invoke AI, get started instantly, or implement our Business solutions, visit [invoke.ai](https://invoke.ai)
 
 
-![Highlighted Features - Canvas and Workflows](https://github.com/invoke-ai/InvokeAI/assets/31807370/708f7a82-084f-4860-bfbe-e2588c53548d)
+[![discord badge]][discord link]
 
-# Documentation
-| **Quick Links**                                                                                                      | 
-|----------------------------------------------------------------------------------------------------------------------------|
-|  [Installation and Updates][installation docs] - [Documentation and Tutorials][docs home] - [Bug Reports][github issues] - [Contributing][contributing docs]  | 
+[![latest release badge]][latest release link] [![github stars badge]][github stars link] [![github forks badge]][github forks link]
 
-</div>
+[![CI checks on main badge]][CI checks on main link] [![latest commit to main badge]][latest commit to main link]
 
-## Quick Start
+[![github open issues badge]][github open issues link] [![github open prs badge]][github open prs link] [![translation status badge]][translation status link]
 
-1. Download and unzip the installer from the bottom of the [latest release][latest release link].
-2. Run the installer script.
-
-   - **Windows**: Double-click on the `install.bat` script.
-   - **macOS**: Open a Terminal window, drag the file `install.sh` from Finder into the Terminal, and press enter.
-   - **Linux**: Run `install.sh`.
-
-3. When prompted, enter a location for the install and select your GPU type.
-4. Once the install finishes, find the directory you selected during install. The default location is `C:\Users\Username\invokeai` for Windows or `~/invokeai` for Linux/macOS.
-5. Run the launcher script (`invoke.bat` for Windows, `invoke.sh` for macOS and Linux) the same way you ran the installer script in step 2.
-6. Select option 1 to start the application. Once it starts up, open your browser and go to <http://localhost:9090>.
-7. Open the model manager tab to install a starter model and then you'll be ready to generate.
-
-More detail, including hardware requirements and manual install instructions, are available in the [installation documentation][installation docs].
-
-## Docker Container
-
-We publish official container images in Github Container Registry: https://github.com/invoke-ai/InvokeAI/pkgs/container/invokeai. Both CUDA and ROCm images are available. Check the above link for relevant tags.
-
-> [!IMPORTANT]
-> Ensure that Docker is set up to use the GPU. Refer to [NVIDIA][nvidia docker docs] or [AMD][amd docker docs] documentation.
-
-### Generate!
-
-Run the container, modifying the command as necessary:
-
-```bash
-docker run --runtime=nvidia --gpus=all --publish 9090:9090 ghcr.io/invoke-ai/invokeai
-```
-
-Then open `http://localhost:9090` and install some models using the Model Manager tab to begin generating.
-
-For ROCm, add `--device /dev/kfd --device /dev/dri` to the `docker run` command.
-
-### Persist your data
-
-You will likely want to persist your workspace outside of the container. Use the `--volume /home/myuser/invokeai:/invokeai` flag to mount some local directory (using its **absolute** path) to the `/invokeai` path inside the container. Your generated images and models will reside there. You can use this directory with other InvokeAI installations, or switch between runtime directories as needed.
-
-### DIY
-
-Build your own image and customize the environment to match your needs using our `docker-compose` stack. See [README.md](./docker/README.md) in the [docker](./docker) directory.
-
-## Troubleshooting, FAQ and Support
-
-Please review our [FAQ][faq] for solutions to common installation problems and other issues.
-
-For more help, please join our [Discord][discord link].
-
-## Features
-
-Full details on features can be found in [our documentation][features docs].
-
-### Web Server & UI
-
-Invoke runs a locally hosted web server & React UI with an industry-leading user experience.
-
-### Unified Canvas
-
-The Unified Canvas is a fully integrated canvas implementation with support for all core generation capabilities, in/out-painting, 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
-
-Invoke offers a fully featured workflow management solution, enabling users to combine the power of node-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.
-
-### Board & Gallery Management
-
-Invoke features 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.
-
-### Other features
-
-- Support for both ckpt and diffusers models
-- SD1.5, SD2.0, and SDXL support
-- Upscaling Tools
-- Embedding Manager & Support
-- Model Manager & Support
-- Workflow creation & management
-- Node-Based Architecture
-
-## 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][contributing docs], joining the [#dev-chat] or the GitHub discussion board.
-
-We hope you enjoy using Invoke as much as we enjoy creating it, and we hope you will elect to become part of our community.
-
-## Thanks
-
-Invoke is a combined effort of [passionate and talented people from across the world][contributors]. We thank them for their time, hard work and effort.
-
-Original portions of the software are Copyright © 2024 by respective contributors.
-
-[features docs]: https://invoke-ai.github.io/InvokeAI/features/
-[faq]: https://invoke-ai.github.io/InvokeAI/help/FAQ/
-[contributors]: https://invoke-ai.github.io/InvokeAI/other/CONTRIBUTORS/
-[invoke.com]: https://www.invoke.com/about
-[github issues]: https://github.com/invoke-ai/InvokeAI/issues
-[docs home]: https://invoke-ai.github.io/InvokeAI
-[installation docs]: https://invoke-ai.github.io/InvokeAI/installation/INSTALLATION/
-[#dev-chat]: https://discord.com/channels/1020123559063990373/1049495067846524939
-[contributing docs]: https://invoke-ai.github.io/InvokeAI/contributing/CONTRIBUTING/
 [CI checks on main badge]: https://flat.badgen.net/github/checks/invoke-ai/InvokeAI/main?label=CI%20status%20on%20main&cache=900&icon=github
-[CI checks on main link]: https://github.com/invoke-ai/InvokeAI/actions?query=branch%3Amain
+[CI checks on main link]:https://github.com/invoke-ai/InvokeAI/actions?query=branch%3Amain
 [discord badge]: https://flat.badgen.net/discord/members/ZmtBAhwWhy?icon=discord
 [discord link]: https://discord.gg/ZmtBAhwWhy
 [github forks badge]: https://flat.badgen.net/github/forks/invoke-ai/InvokeAI?icon=github
@@ -150,8 +30,363 @@ Original portions of the software are Copyright © 2024 by respective contributo
 [latest commit to main badge]: https://flat.badgen.net/github/last-commit/invoke-ai/InvokeAI/main?icon=github&color=yellow&label=last%20dev%20commit&cache=900
 [latest commit to main link]: https://github.com/invoke-ai/InvokeAI/commits/main
 [latest release badge]: https://flat.badgen.net/github/release/invoke-ai/InvokeAI/development?icon=github
-[latest release link]: https://github.com/invoke-ai/InvokeAI/releases/latest
+[latest release link]: https://github.com/invoke-ai/InvokeAI/releases
 [translation status badge]: https://hosted.weblate.org/widgets/invokeai/-/svg-badge.svg
 [translation status link]: https://hosted.weblate.org/engage/invokeai/
-[nvidia docker docs]: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
-[amd docker docs]: https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html
+
+</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
+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)] [<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/">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>]
+
+<div align="center">
+
+![canvas preview](https://github.com/invoke-ai/InvokeAI/raw/main/docs/assets/canvas_preview.png)
+
+</div>
+
+## Table of Contents
+
+Table of Contents 📝
+
+**Getting Started**
+1. 🏁 [Quick Start](#quick-start) 
+3. 🖥️ [Hardware Requirements](#hardware-requirements) 
+
+**More About Invoke**
+1. 🌟 [Features](#features) 
+2. 📣 [Latest Changes](#latest-changes) 
+3. 🛠️ [Troubleshooting](#troubleshooting) 
+
+**Supporting the Project**
+1. 🤝 [Contributing](#contributing) 
+2. 👥 [Contributors](#contributors) 
+3. 💕 [Support](#support) 
+
+## Quick Start
+
+For full installation and upgrade instructions, please see:
+[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.
+
+### Automatic Installer (suggested for 1st time users)
+
+1. Go to the bottom of the [Latest Release Page](https://github.com/invoke-ai/InvokeAI/releases/latest)
+
+2. Download the .zip file for your OS (Windows/macOS/Linux).
+
+3. Unzip the file.
+
+4. **Windows:** double-click on the `install.bat` script. **macOS:** Open a Terminal window, drag the file `install.sh` from Finder
+into the Terminal, and press return. **Linux:** run `install.sh`.
+
+5. You'll be asked to confirm the location of the folder in which
+to install InvokeAI and its image generation model files. Pick a
+location with at least 15 GB of free memory. More if you plan on
+installing lots of models.
+
+6. Wait while the installer does its thing. After installing the software,
+the installer will launch a script that lets you configure InvokeAI and
+select a set of starting image generation models.
+
+7. Find the folder that InvokeAI was installed into (it is not the
+same as the unpacked zip file directory!) The default location of this
+folder (if you didn't change it in step 5) is `~/invokeai` on
+Linux/Mac systems, and `C:\Users\YourName\invokeai` on Windows. This directory will contain launcher scripts named `invoke.sh` and `invoke.bat`.
+
+8. On Windows systems, double-click on the `invoke.bat` file. On
+macOS, open a Terminal window, drag `invoke.sh` from the folder into
+the Terminal, and press return. On Linux, run `invoke.sh`
+
+9. Press 2 to open the "browser-based UI", press enter/return, wait a
+minute or two for Stable Diffusion to start up, then open your browser
+and go to http://localhost:9090.
+
+10. Type `banana sushi` in the box on the top left and click `Invoke`
+
+### Command-Line Installation (for developers and users familiar with Terminals)
+
+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:
+
+    ```terminal
+    mkdir invokeai
+    ````
+
+3. Create a virtual environment named `.venv` inside this directory and activate it:
+
+    ```terminal
+    cd invokeai
+    python -m venv .venv --prompt InvokeAI
+    ```
+
+4. Activate the virtual environment (do it every time you run InvokeAI)
+
+    _For Linux/Mac users:_
+
+    ```sh
+    source .venv/bin/activate
+    ```
+
+    _For Windows users:_
+
+    ```ps
+    .venv\Scripts\activate
+    ```
+
+5. Install the InvokeAI module and its dependencies. Choose the command suited for your platform & GPU.
+
+    _For Windows/Linux with an NVIDIA GPU:_
+
+    ```terminal
+    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/rocm5.4.2
+    ```
+
+    _For non-GPU systems:_
+    ```terminal
+    pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/cpu
+    ``` 
+
+    _For Macintoshes, either Intel or M1/M2:_
+
+    ```sh
+    pip install InvokeAI --use-pep517
+    ```
+
+6. Configure InvokeAI and install a starting set of image generation models (you only need to do this once):
+
+    ```terminal
+    invokeai-configure
+    ```
+
+7. Launch the web server (do it every time you run InvokeAI):
+
+    ```terminal
+    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,
+using `source .venv/bin/activate` or `.venv\Scripts\activate`.
+
+## Detailed Installation Instructions
+
+This fork is supported across Linux, Windows and Macintosh. Linux
+users can use either an Nvidia-based card (with CUDA support) or an
+AMD card (using the ROCm driver). For full installation and upgrade
+instructions, please see:
+[InvokeAI Installation Overview](https://invoke-ai.github.io/InvokeAI/installation/INSTALL_SOURCE/)
+
+<a name="migrating-to-3"></a>
+### Migrating a v2.3 InvokeAI root directory
+
+The InvokeAI root directory is where the InvokeAI startup file,
+installed models, and generated images are stored. It is ordinarily
+named `invokeai` and located in your home directory. The contents and
+layout of this directory has changed between versions 2.3 and 3.0 and
+cannot be used directly.
+
+We currently recommend that you use the installer to create a new root
+directory named differently from the 2.3 one, e.g. `invokeai-3` and
+then use a migration script to copy your 2.3 models into the new
+location. However, if you choose, you can upgrade this directory in
+place.  This section gives both recipes.
+
+#### Creating a new root directory and migrating old models
+
+This is the safer recipe because it leaves your old root directory in
+place to fall back on.
+
+1. Follow the instructions above to create and install InvokeAI in a
+directory that has a different name from the 2.3 invokeai directory.
+In this example, we will use "invokeai-3"
+
+2. When you are prompted to select models to install, select a minimal
+set of models, such as stable-diffusion-v1.5 only.
+
+3. After installation is complete launch `invokeai.sh` (Linux/Mac) or
+`invokeai.bat` and select option 8 "Open the developers console". This
+will take you to the command line.
+
+4. Issue the command `invokeai-migrate3 --from /path/to/v2.3-root --to
+/path/to/invokeai-3-root`. Provide the correct `--from` and `--to`
+paths for your v2.3 and v3.0 root directories respectively.
+
+This will copy and convert your old models from 2.3 format to 3.0
+format and create a new `models` directory in the 3.0 directory. The
+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.
+
+#### Migrating in place
+
+For the adventurous, you may do an in-place upgrade from 2.3 to 3.0
+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.
+
+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 [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
+update it to the 3.0 format. The following files will be replaced:
+
+  - The invokeai.init file, replaced by invokeai.yaml
+  - The models directory
+  - The configs/models.yaml model index
+  
+The original versions of these files will be saved with the suffix
+".orig" appended to the end. Once you have confirmed that the upgrade
+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.
+
+#### 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. 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
+
+InvokeAI is supported across Linux, Windows and macOS. Linux
+users can use either an Nvidia-based card (with CUDA support) or an
+AMD card (using the ROCm driver).
+
+### System
+
+You will need one of the following:
+
+- 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)
+
+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
+to render 512x512 images.
+
+**Memory** - At least 12 GB Main Memory RAM.
+
+**Disk** - At least 12 GB of free disk space for the machine learning model, Python, and all its dependencies.
+
+## Features
+
+Feature documentation can be reviewed by navigating to [the InvokeAI Documentation page](https://invoke-ai.github.io/InvokeAI/features/)
+
+### *Web Server & UI*
+
+InvokeAI offers a locally hosted Web Server & React Frontend, with an industry leading user experience. The Web-based UI allows for simple and intuitive workflows, and is responsive for use on mobile devices and tablets accessing the web server.
+
+### *Unified Canvas*
+
+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.
+
+### *Node Architecture & Editor (Beta)*
+
+Invoke AI's backend is built on a graph-based execution architecture. This allows for customizable generation pipelines to be developed by professional users looking to create specific workflows to support their production use-cases, and will be extended in the future with additional capabilities.
+
+### *Board & Gallery Management*
+
+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. 
+
+### Other features
+
+- *Support for both ckpt and diffusers models*
+- *SD 2.0, 2.1 support*
+- *Upscaling Tools*
+- *Embedding Manager & Support*
+- *Model Manager & Support*
+- *Node-Based Architecture*
+- *Node-Based Plug-&-Play UI (Beta)*
+- *SDXL Support* (Coming soon)
+
+### Latest Changes
+
+For our latest changes, view our [Release
+Notes](https://github.com/invoke-ai/InvokeAI/releases) and the
+[CHANGELOG](docs/CHANGELOG.md).
+
+### Troubleshooting
+
+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
+
+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.
+
+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, 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
+to become part of our community.
+
+Welcome to InvokeAI!
+
+### 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
+their time, hard work and effort.
+
+### Support
+
+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

@@ -1,27 +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 `cuda` or `rocm` to enable GPU support in the container accordingly.
-# GPU_DRIVER=cuda #| rocm
-
-## CONTAINER_UID can be set to the UID of the user on the host system that should own the files in the container.
-## It is usually not necessary to change this. Use `id -u` on the host system to find the UID.
-# CONTAINER_UID=1000

docker/Dockerfile

@@ -1,124 +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 use pnpm@8.x
-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

@@ -1,117 +0,0 @@
-# Invoke in Docker
-
-First things first:
-
-- Ensure that Docker can use your [NVIDIA][nvidia docker docs] or [AMD][amd docker docs] GPU.
-- This document assumes a Linux system, but should work similarly under Windows with WSL2.
-- We don't recommend running Invoke in Docker on macOS at this time. It works, but very slowly.
-
-## Quickstart
-
-No `docker compose`, no persistence, single command, using the official images:
-
-**CUDA (NVIDIA GPU):**
-
-```bash
-docker run --runtime=nvidia --gpus=all --publish 9090:9090 ghcr.io/invoke-ai/invokeai
-```
-
-**ROCm (AMD GPU):**
-
-```bash
-docker run --device /dev/kfd --device /dev/dri --publish 9090:9090 ghcr.io/invoke-ai/invokeai:main-rocm
-```
-
-Open `http://localhost:9090` in your browser once the container finishes booting, install some models, and generate away!
-
-### Data persistence
-
-To persist your generated images and downloaded models outside of the container, add a `--volume/-v` flag to the above command, e.g.:
-
-```bash
-docker run --volume /some/local/path:/invokeai {...etc...}
-```
-
-`/some/local/path/invokeai` will contain all your data.
-It can *usually* be reused between different installs of Invoke. Tread with caution and read the release notes!
-
-## Customize the container
-
-The included `run.sh` script is a convenience wrapper around `docker compose`. It can be helpful for passing additional build arguments to `docker compose`. Alternatively, the familiar `docker compose` commands work just as well.
-
-```bash
-cd docker
-cp .env.sample .env
-# edit .env to your liking if you need to; it is well commented.
-./run.sh
-```
-
-It will take a few minutes to build the image the first time. Once the application starts up, open `http://localhost:9090` in your browser to invoke!
-
->[!TIP]
->When using the `run.sh` script, the container will continue running after Ctrl+C. To shut it down, use the `docker compose down` command.
-
-## Docker setup in detail
-
-#### Linux
-
-1. Ensure buildkit 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 probably won't work. Update to a recent version.
-3. Ensure docker daemon is able to access the GPU.
-    - [NVIDIA docs](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
-    - [AMD docs](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html)
-
-#### macOS
-
-> [!TIP]
-> You'll be better off installing Invoke directly on your system, because Docker can not use the GPU on macOS.
-
-If you are still reading:
-
-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 the 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 the desired location of the InvokeAI runtime directory. It may be an existing directory from a previous installation (post 4.0.0).
-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`. Navigate to the Model Manager tab and install some models before 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/NVIDIA/AMD 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 before running `./run.sh`.
-
-## 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=cuda
-```
-
-Any environment variables supported by InvokeAI can be set here. See the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.
-
----
-
-[nvidia docker docs]: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
-[amd docker docs]: https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html

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

@@ -1,54 +0,0 @@
-# Copyright (c) 2023 Eugene Brodsky https://github.com/ebr
-
-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-cuda:
-    <<: *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}" || true
-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

@@ -1,36 +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
 
-  # create .env file if it doesn't exist, otherwise docker compose will fail
-  touch .env
+source ./env.sh
 
-  # parse .env file for build args
-  build_args=$(awk '$1 ~ /=[^$]/ && $0 !~ /^#/ {print "--build-arg " $0 " "}' .env) &&
-  profile="$(awk -F '=' '/GPU_DRIVER/ {print $2}' .env)"
+# Create outputs directory if it does not exist
+[[ -d ./outputs ]] || mkdir ./outputs
 
-  # default to 'cuda' profile
-  [[ -z "$profile" ]] && profile="cuda"
+echo -e "You are using these values:\n"
+echo -e "Volumename:\t${VOLUMENAME}"
+echo -e "Invokeai_tag:\t${CONTAINER_IMAGE}"
+echo -e "local Models:\t${MODELSPATH:-unset}\n"
 
-  local service_name="invokeai-$profile"
+docker run \
+  --interactive \
+  --tty \
+  --rm \
+  --platform="${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}" ${@:+$@}
 
-  if [[ ! -z "$build_args" ]]; then
-    printf "%s\n" "docker compose build args:"
-    printf "%s\n" "$build_args"
+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

@@ -1,334 +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.
-
-Two job types are defined. `DownloadJob` and
-`MultiFileDownloadJob`. The former is 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.
-
-The `MultiFileDownloadJob` is used for diffusers model downloads,
-which contain multiple files and directories under a common root:
-
-| **Field**      | **Type**        |  **Default**  | **Description** |
-|----------------|-----------------|---------------|-----------------|
-| _Fields passed in at job creation time_                               |
-| `download_parts` | Set[DownloadJob]|               | Component download jobs |
-| `dest`           | Path            |               | Where to download to              |
-| `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           |
-| _Fields updated over the course of the download task_
-| `status`         | DownloadJobStatus|              | Status code                                |
-| `download_path`  | Path |              | Path to the root of the downloaded files |
-| `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|
-
-Note that the MultiFileDownloadJob does not support the `priority`,
-`job_started`, `job_ended` or `content_type` attributes. You can get
-these from the individual download jobs in `download_parts`.
-
-
-### 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, on_start, on_progress, on_complete, on_cancelled, on_error)
-
-Create a new download job and put it on the queue, returning the
-DownloadJob object.
-
-#### multifile_job = queue.multifile_download(parts, dest, access_token, on_start, on_progress, on_complete, on_cancelled, on_error)
-
-This is similar to download(), but instead of taking a single source,
-it accepts a `parts` argument consisting of a list of
-`RemoteModelFile` objects. Each part corresponds to a URL/Path pair,
-where the URL is the location of the remote file, and the Path is the
-destination.
-
-`RemoteModelFile` can be imported from `invokeai.backend.model_manager.metadata`, and
-consists of a url/path pair. Note that the path *must* be relative.
-
-The method returns a `MultiFileDownloadJob`.
-
-
-```
-from invokeai.backend.model_manager.metadata import RemoteModelFile
-remote_file_1 = RemoteModelFile(url='http://www.foo.bar/my/pytorch_model.safetensors'',
-                                path='my_model/textencoder/pytorch_model.safetensors'
-			 			  )
-remote_file_2 = RemoteModelFile(url='http://www.bar.baz/vae.ckpt',
-                                path='my_model/vae/diffusers_model.safetensors'
-			 			  )
-job = queue.multifile_download(parts=[remote_file_1, remote_file_2],
-                               dest='/tmp/downloads',
-                               on_progress=TqdmProgress().update)
-queue.wait_for_job(job)
-print(f"The files were downloaded to {job.download_path}")
-```
-
-#### 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

@@ -1,6 +1,6 @@
-# Nodes
+# Invocations
 
-Features in InvokeAI are added in the form of modular nodes systems called
+Features in InvokeAI are added in the form of modular node-like systems called
 **Invocations**.
 
 An Invocation is simply a single operation that takes in some inputs and gives
@@ -9,38 +9,13 @@ complex functionality.
 
 ## Invocations Directory
 
-InvokeAI Nodes can be found in the `invokeai/app/invocations` directory. These
-can be used as examples to create your own nodes.
+InvokeAI Invocations can be found in the `invokeai/app/invocations` directory.
 
-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.
+You can add your new functionality to one of the existing Invocations in this
+directory or create a new file in this directory as per your needs.
 
-Example `nodes` subfolder structure:
-
-```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
-```
-
-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
-```
+**Note:** _All Invocations must be inside this directory for InvokeAI to
+recognize them as valid Invocations._
 
 ## Creating A New Invocation
 
@@ -54,13 +29,12 @@ 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`.
+- The name of every Invocation must end with the word `Invocation` in order for
+  it to be recognized as an Invocation.
 - 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.
+- Every Invocation must have a unique `type` field defined which becomes its
+  indentifier.
 - 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
@@ -69,11 +43,12 @@ The first set of things we need to do when creating a new Invocation are -
 So let us do that.
 
 ```python
-from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
+from typing import Literal
+from .baseinvocation import BaseInvocation
 
-@invocation('resize')
 class ResizeInvocation(BaseInvocation):
     '''Resizes an image'''
+    type: Literal['resize'] = 'resize'
 ```
 
 That's great.
@@ -87,10 +62,8 @@ our Invocation takes.
 
 ### **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.
+Every Invocation input is a pydantic `Field` and like everything else 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
@@ -103,50 +76,55 @@ 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
+from typing import Literal, Union
+from pydantic import Field
+
+from .baseinvocation import BaseInvocation
+from ..models.image import ImageField
 
-@invocation('resize')
 class ResizeInvocation(BaseInvocation):
+    '''Resizes an image'''
+    type: Literal['resize'] = 'resize'
 
     # Inputs
-    image: ImageField = InputField(description="The input image")
+    image: Union[ImageField, None] = Field(description="The input image", default=None)
 ```
 
 Let us break down our input code.
 
 ```python
-image: ImageField = InputField(description="The input image")
+image: Union[ImageField, None] = Field(description="The input image", default=None)
 ```
 
-| 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.                |
+| Part      | Value                                                | Description                                                                                        |
+| --------- | ---------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
+| Name      | `image`                                              | The variable that will hold our image                                                              |
+| Type Hint | `Union[ImageField, None]`                            | The types for our field. Indicates that the image can either be an `ImageField` type or `None`     |
+| Field     | `Field(description="The input image", default=None)` | The image variable is a field which needs a description and a default value that we set to `None`. |
 
 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
+from typing import Literal, Union
+from pydantic import Field
+
+from .baseinvocation import BaseInvocation
+from ..models.image import ImageField
 
-@invocation('resize')
 class ResizeInvocation(BaseInvocation):
     '''Resizes an image'''
+    type: Literal['resize'] = 'resize'
 
-    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")
+    # Inputs
+    image: Union[ImageField, None] = Field(description="The input image", default=None)
+    width: int = Field(default=512, ge=64, le=2048, description="Width of the new image")
+    height: int = Field(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.
+As you might have noticed, we added two new parameters to the field type for
+`width` and `height` called `gt` and `le`. These basically stand for _greater
+than or equal to_ and _less than or equal to_. There are various other param
+types for field that you can find on the **pydantic** documentation.
 
 **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._
@@ -163,16 +141,20 @@ 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
+from typing import Literal, Union
+from pydantic import Field
+
+from .baseinvocation import BaseInvocation, InvocationContext
+from ..models.image import ImageField
 
-@invocation('resize')
 class ResizeInvocation(BaseInvocation):
     '''Resizes an image'''
+    type: Literal['resize'] = 'resize'
 
-    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")
+    # Inputs
+    image: Union[ImageField, None] = Field(description="The input image", default=None)
+    width: int = Field(default=512, ge=64, le=2048, description="Width of the new image")
+    height: int = Field(default=512, ge=64, le=2048, description="Height of the new image")
 
     def invoke(self, context: InvocationContext):
         pass
@@ -191,17 +173,21 @@ 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
+from typing import Literal, Union
+from pydantic import Field
+
+from .baseinvocation import BaseInvocation, InvocationContext
+from ..models.image import ImageField
+from .image import ImageOutput
 
-@invocation('resize')
 class ResizeInvocation(BaseInvocation):
     '''Resizes an image'''
+    type: Literal['resize'] = 'resize'
 
-    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")
+    # Inputs
+    image: Union[ImageField, None] = Field(description="The input image", default=None)
+    width: int = Field(default=512, ge=64, le=2048, description="Width of the new image")
+    height: int = Field(default=512, ge=64, le=2048, description="Height of the new image")
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         pass
@@ -209,38 +195,57 @@ class ResizeInvocation(BaseInvocation):
 
 Perfect. Now that we have our Invocation setup, let us do what we want to do.
 
-- We will first load the image using one of the services provided by InvokeAI to
-  load the image.
+- We will first load the image. Generally we do this using the `PIL` library but
+  we can use 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.
 
 So let's do that.
 
 ```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
+from typing import Literal, Union
+from pydantic import Field
+
+from .baseinvocation import BaseInvocation, InvocationContext
+from ..models.image import ImageField, ResourceOrigin, ImageCategory
+from .image import ImageOutput
 
-@invocation("resize")
 class ResizeInvocation(BaseInvocation):
-    """Resizes an image"""
+    '''Resizes an image'''
+    type: Literal['resize'] = 'resize'
 
-    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")
+    # Inputs
+    image: Union[ImageField, None] = Field(description="The input image", default=None)
+    width: int = Field(default=512, ge=64, le=2048, description="Width of the new image")
+    height: int = Field(default=512, ge=64, le=2048, description="Height of the new image")
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        # Load the input image as a PIL image
-        image = context.images.get_pil(self.image.image_name)
+        # Load the image using InvokeAI's predefined Image Service.
+        image = context.services.images.get_pil_image(self.image.image_origin, self.image.image_name)
 
-        # Resize the image
+        # Resizing the image
+        # Because we used the above service, we already have a PIL image. So we can simply resize.
         resized_image = image.resize((self.width, self.height))
 
-        # Save the image
-        image_dto = context.images.save(image=resized_image)
+        # Preparing the image for output using InvokeAI's predefined Image Service.
+        output_image = context.services.images.create(
+            image=resized_image,
+            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 an ImageOutput
-        return ImageOutput.build(image_dto)
+        # Returning the Image
+        return ImageOutput(
+            image=ImageField(
+                image_name=output_image.image_name,
+                image_origin=output_image.image_origin,
+            ),
+            width=output_image.width,
+            height=output_image.height,
+        )
 ```
 
 **Note:** Do not be overwhelmed by the `ImageOutput` process. InvokeAI has a
@@ -248,24 +253,6 @@ 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.
 
-### Customization
-
-We can use the `@invocation` decorator to provide some additional info to the
-UI, like a custom title, tags and category.
-
-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.
-
-```python
-@invocation("resize", title="My Resizer", tags=["resize", "image"], category="My Invocations", version="1.0.0")
-class ResizeInvocation(BaseInvocation):
-    """Resizes an image"""
-
-    image: ImageField = InputField(description="The input image")
-    ...
-```
-
 That's it. You made your own **Resize Invocation**.
 
 ## Result
@@ -283,73 +270,27 @@ new Invocation ready to be used.
 
 ![resize node editor](../assets/contributing/resize_node_editor.png)
 
-## Contributing Nodes
+# Advanced
 
-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.
-
-```python
-from .baseinvocation import BaseInvocationOutput, OutputField, invocation_output
-from .primitives import ImageField, ColorField
-
-@invocation_output('image_color_string_output')
-class ImageColorStringOutput(BaseInvocationOutput):
-    '''Base class for nodes that output a single image'''
-
-    image: ImageField = OutputField(description="The image")
-    color: ColorField = OutputField(description="The color")
-    text: str = OutputField(description="The string")
-```
-
-That's all there is to it.
-
-### Custom Input Fields
+## 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.
+existing input types in InvokeAI do not meet your requirements. In such cases,
+you can create your own input types.
 
 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
+**Good 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.
+  `docstring` to describe your input field.
 - Keep your field in the same file as the Invocation that it is made for or in
   another file where it is relevant.
 
@@ -364,13 +305,10 @@ class ColorField(BaseModel):
     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.
+Perfect. Now let us create our custom inputs for our field. This is exactly
+similar 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.
 
 ```python
 class ColorField(BaseModel):
@@ -385,11 +323,468 @@ 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')
+color: ColorField = Field(default=ColorField(r=0, g=0, b=0, a=0), description='Background color of an image')
 ```
 
-### Using the custom field
+**Extra Config**
 
-When you start the UI, your custom field will be automatically recognized.
+All input fields also take an additional `Config` class that you can use to do
+various advanced things like setting required parameters and etc.
 
-Custom fields only support connection inputs in the Workflow Editor.
+Let us do that for our _ColorField_ and enforce all the values because we did
+not define any defaults for our fields.
+
+```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")
+
+    class Config:
+        schema_extra = {"required": ["r", "g", "b", "a"]}
+```
+
+Now it becomes mandatory for the user to supply all the values required by our
+input field.
+
+We will discuss the `Config` class in extra detail later in this guide and how
+you can use it to make your Invocations more robust.
+
+## 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 put together a custom output type for an Invocation that returns _width_,
+_height_ and _background_color_ that we need to create a blank image.
+
+- A custom output type is a class that derives from the parent class of
+  `BaseInvocationOutput`.
+- It is not mandatory but we recommend using names ending with `Output` for
+  output types. So we'll call our class `BlankImageOutput`
+- It is not mandatory but we highly recommend adding a `docstring` to describe
+  what your output type is for.
+- Like Invocations, each output type should have a `type` variable that is
+  **unique**
+
+Now that we know the basic rules for creating a new output type, let us go ahead
+and make it.
+
+```python
+from typing import Literal
+from pydantic import Field
+
+from .baseinvocation import BaseInvocationOutput
+
+class BlankImageOutput(BaseInvocationOutput):
+    '''Base output type for creating a blank image'''
+    type: Literal['blank_image_output'] = 'blank_image_output'
+
+    # Inputs
+    width: int = Field(description='Width of blank image')
+    height: int = Field(description='Height of blank image')
+    bg_color: ColorField = Field(description='Background color of blank image')
+
+    class Config:
+        schema_extra = {"required": ["type", "width", "height", "bg_color"]}
+```
+
+All set. We now have an output type that requires what we need to create a
+blank_image. And if you noticed it, we even used the `Config` class to ensure
+the fields are required.
+
+## Custom Configuration
+
+As you might have noticed when making inputs and outputs, we used a class called
+`Config` from _pydantic_ to further customize them. Because our inputs and
+outputs essentially inherit from _pydantic_'s `BaseModel` class, all
+[configuration options](https://docs.pydantic.dev/latest/usage/schema/#schema-customization)
+that are valid for _pydantic_ classes are also valid for our inputs and outputs.
+You can do the same for your Invocations too but InvokeAI makes our life a
+little bit easier on that end.
+
+InvokeAI provides a custom configuration class called `InvocationConfig`
+particularly for configuring Invocations. This is exactly the same as the raw
+`Config` class from _pydantic_ with some extra stuff on top to help faciliate
+parsing of the scheme in the frontend UI.
+
+At the current moment, tihs `InvocationConfig` class is further improved with
+the following features related the `ui`.
+
+| Config Option | Field Type                                                                                                    | Example                                                                                                               |
+| ------------- | ------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------- |
+| type_hints    | `Dict[str, Literal["integer", "float", "boolean", "string", "enum", "image", "latents", "model", "control"]]` | `type_hint: "model"` provides type hints related to the model like displaying a list of available models              |
+| tags          | `List[str]`                                                                                                   | `tags: ['resize', 'image']` will classify your invocation under the tags of resize and image.                         |
+| title         | `str`                                                                                                         | `title: 'Resize Image` will rename your to this custom title rather than infer from the name of the Invocation class. |
+
+So let us update your `ResizeInvocation` with some extra configuration and see
+how that works.
+
+```python
+from typing import Literal, Union
+from pydantic import Field
+
+from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
+from ..models.image import ImageField, ResourceOrigin, ImageCategory
+from .image import ImageOutput
+
+class ResizeInvocation(BaseInvocation):
+    '''Resizes an image'''
+    type: Literal['resize'] = 'resize'
+
+    # Inputs
+    image: Union[ImageField, None] = Field(description="The input image", default=None)
+    width: int = Field(default=512, ge=64, le=2048, description="Width of the new image")
+    height: int = Field(default=512, ge=64, le=2048, description="Height of the new image")
+
+    class Config(InvocationConfig):
+        schema_extra: {
+            ui: {
+                tags: ['resize', 'image'],
+                title: ['My Custom Resize']
+            }
+        }
+
+    def invoke(self, context: InvocationContext) -> ImageOutput:
+        # Load the image using InvokeAI's predefined Image Service.
+        image = context.services.images.get_pil_image(self.image.image_origin, self.image.image_name)
+
+        # Resizing the image
+        # Because we used the above service, we already have a PIL image. So we can simply resize.
+        resized_image = image.resize((self.width, self.height))
+
+        # Preparing the image for output using InvokeAI's predefined Image Service.
+        output_image = context.services.images.create(
+            image=resized_image,
+            image_origin=ResourceOrigin.INTERNAL,
+            image_category=ImageCategory.GENERAL,
+            node_id=self.id,
+            session_id=context.graph_execution_state_id,
+            is_intermediate=self.is_intermediate,
+        )
+
+        # Returning the Image
+        return ImageOutput(
+            image=ImageField(
+                image_name=output_image.image_name,
+                image_origin=output_image.image_origin,
+            ),
+            width=output_image.width,
+            height=output_image.height,
+        )
+```
+
+We now customized our code to let the frontend know that our Invocation falls
+under `resize` and `image` categories. So when the user searches for these
+particular words, our Invocation will show up too.
+
+We also set a custom title for our Invocation. So instead of being called
+`Resize`, it will be called `My Custom Resize`.
+
+As simple as that.
+
+As time goes by, InvokeAI will further improve and add more customizability for
+Invocation configuration. We will have more documentation regarding this at a
+later time.
+
+# **[TODO]**
+
+## Custom Components For Frontend
+
+Every backend input type should have a corresponding frontend component so the
+UI knows what to render when you use a particular field type.
+
+If you are using existing field types, we already have components for those. So
+you don't have to worry about creating anything new. But this might not always
+be the case. Sometimes you might want to create new field types and have the
+frontend UI deal with it in a different way.
+
+This is where we venture into the world of React and Javascript and create our
+own new components for our Invocations. Do not fear the world of JS. It's
+actually pretty straightforward.
+
+Let us create a new component for our custom color field we created above. When
+we use a color field, let us say we want the UI to display a color picker for
+the user to pick from rather than entering values. That is what we will build
+now.
+
+---
+
+# OLD -- TO BE DELETED OR MOVED LATER
+
+---
+
+## Creating a new invocation
+
+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.
+
+An invocation looks like this:
+
+```py
+class UpscaleInvocation(BaseInvocation):
+    """Upscales an image."""
+
+    # fmt: off
+    type: Literal["upscale"] = "upscale"
+
+    # Inputs
+    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
+
+    # Schema customisation
+    class Config(InvocationConfig):
+        schema_extra = {
+            "ui": {
+                "tags": ["upscaling", "image"],
+            },
+        }
+
+    def invoke(self, context: InvocationContext) -> ImageOutput:
+        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,
+        )
+
+```
+
+Each portion is important to implement correctly.
+
+### Class definition and type
+
+```py
+class UpscaleInvocation(BaseInvocation):
+    """Upscales an image."""
+    type: Literal['upscale'] = 'upscale'
+```
+
+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.
+
+### Inputs
+
+```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:
+        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,
+        )
+```
+
+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`.
+
+Before being called, the invocation will have all of its fields set from
+defaults, inputs, and finally links (overriding in that order).
+
+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.
+
+### 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
+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
+```
+
+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
+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
+
+    # Add schema customization
+    class Config:
+        schema_extra = {"required": ["type", "image", "width", "height"]}
+```
+
+With the customization in place, the schema will now show these properties as
+required, obviating the need for extensive null checks in client code.
+
+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!