WIP - not working

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

@@ -9,9 +9,9 @@ runs:
         node-version: '18'
 
     - name: setup pnpm
-      uses: pnpm/action-setup@v4
+      uses: pnpm/action-setup@v2
       with:
-        version: 8.15.6
+        version: 8
         run_install: false
 
     - name: get pnpm store directory

.github/pull_request_template.md

@@ -8,7 +8,7 @@
 
 ## QA Instructions
 
-<!--WHEN APPLICABLE: Describe how you have tested the changes in this PR. Provide enough detail that a reviewer can reproduce your tests.-->
+<!--WHEN APPLICABLE: Describe how we can test the changes in this PR.-->
 
 ## Merge Plan
 
@@ -19,4 +19,3 @@
 - [ ] _The PR has a short but descriptive title, suitable for a changelog_
 - [ ] _Tests added / updated (if applicable)_
 - [ ] _Documentation added / updated (if applicable)_
-- [ ] _Updated `What's New` copy (if doing a release after this PR)_

.github/workflows/build-container.yml

@@ -13,12 +13,6 @@ on:
     tags:
       - 'v*.*.*'
   workflow_dispatch:
-    inputs:
-      push-to-registry:
-        description: Push the built image to the container registry
-        required: false
-        type: boolean
-        default: false
 
 permissions:
   contents: write
@@ -56,15 +50,16 @@ jobs:
           df -h
 
       - name: Checkout
-        uses: actions/checkout@v4
+        uses: actions/checkout@v3
 
       - name: Docker meta
         id: meta
-        uses: docker/metadata-action@v5
+        uses: docker/metadata-action@v4
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
           images: |
             ghcr.io/${{ github.repository }}
+            ${{ env.DOCKERHUB_REPOSITORY }}
           tags: |
             type=ref,event=branch
             type=ref,event=tag
@@ -77,33 +72,49 @@ jobs:
             suffix=-${{ matrix.gpu-driver }},onlatest=false
 
       - name: Set up QEMU
-        uses: docker/setup-qemu-action@v3
+        uses: docker/setup-qemu-action@v2
 
       - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
+        uses: docker/setup-buildx-action@v2
         with:
           platforms: ${{ env.PLATFORMS }}
 
       - name: Login to GitHub Container Registry
         if: github.event_name != 'pull_request'
-        uses: docker/login-action@v3
+        uses: docker/login-action@v2
         with:
           registry: ghcr.io
           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: Build container
         timeout-minutes: 40
         id: docker_build
-        uses: docker/build-push-action@v6
+        uses: docker/build-push-action@v4
         with:
           context: .
           file: docker/Dockerfile
           platforms: ${{ env.PLATFORMS }}
-          push: ${{ github.ref == 'refs/heads/main' || github.ref_type == 'tag' || github.event.inputs.push-to-registry }}
+          push: ${{ github.ref == 'refs/heads/main' || github.ref_type == 'tag' }}
           tags: ${{ steps.meta.outputs.tags }}
           labels: ${{ steps.meta.outputs.labels }}
           cache-from: |
             type=gha,scope=${{ 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 }}
+
+      # - 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/python-checks.yml

@@ -62,7 +62,7 @@ jobs:
 
       - name: install ruff
         if: ${{ steps.changed-files.outputs.python_any_changed == 'true' || inputs.always_run == true }}
-        run: pip install ruff==0.6.0
+        run: pip install ruff
         shell: bash
 
       - name: ruff check

.github/workflows/python-tests.yml

@@ -60,7 +60,7 @@ jobs:
             extra-index-url: 'https://download.pytorch.org/whl/cpu'
             github-env: $GITHUB_ENV
           - platform: macos-default
-            os: macOS-14
+            os: macOS-12
             github-env: $GITHUB_ENV
           - platform: windows-cpu
             os: windows-2022

Makefile

@@ -18,8 +18,6 @@ help:
 	@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"
-	@echo "docs                     Serve the mkdocs site with live reload"
 
 # Runs ruff, fixing any safely-fixable errors and formatting
 ruff:
@@ -72,11 +70,3 @@ installer-zip:
 tag-release:
 	cd installer && ./tag_release.sh
 
-# Generate the OpenAPI Schema for the app
-openapi:
-	python scripts/generate_openapi_schema.py
-
-# Serve the mkdocs site w/ live reload
-.PHONY: docs
-docs:
-	mkdocs serve

README.md

@@ -2,141 +2,21 @@
 
 ![project hero](https://github.com/invoke-ai/InvokeAI/assets/31807370/6e3728c7-e90e-4711-905c-3b55844ff5be)
 
-# 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 - Professional Creative AI Tools for Visual Media 
+##  To learn more about Invoke, or implement our Business solutions, visit [invoke.com](https://www.invoke.com/about)
+  
 
 
-![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, SDXL, and FLUX 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/database/
-[faq]: https://invoke-ai.github.io/InvokeAI/faq/
-[contributors]: https://invoke-ai.github.io/InvokeAI/contributing/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/
-[#dev-chat]: https://discord.com/channels/1020123559063990373/1049495067846524939
-[contributing docs]: https://invoke-ai.github.io/InvokeAI/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 +30,402 @@ 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>
+
+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/INSTALLATION/)] [<a
+  href="https://discord.gg/ZmtBAhwWhy">Discord Server</a>] [<a
+  href="https://invoke-ai.github.io/InvokeAI/">Documentation and
+  Tutorials</a>]
+  [<a href="https://github.com/invoke-ai/InvokeAI/issues">Bug Reports</a>]
+  [<a
+  href="https://github.com/invoke-ai/InvokeAI/discussions">Discussion,
+  Ideas & Q&A</a>] 
+   [<a
+  href="https://invoke-ai.github.io/InvokeAI/contributing/CONTRIBUTING/">Contributing</a>] 
+
+<div align="center">
+
+
+![Highlighted Features - Canvas and Workflows](https://github.com/invoke-ai/InvokeAI/assets/31807370/708f7a82-084f-4860-bfbe-e2588c53548d)
+
+
+</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/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 3.10 through 3.11 installed on your machine. Earlier or
+later versions are not supported.
+Node.js also needs to be installed along with `pnpm` (can be installed with
+the command `npm install -g pnpm` if needed)
+
+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/cu121
+    ```
+
+    _For Linux with an AMD GPU:_
+
+    ```sh
+    pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.6
+    ```
+
+    _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/M3:_
+
+    ```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 --root .
+    ```
+	Don't miss the dot at the end!
+
+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.
+
+ If you wish, you can pass the 2.3 root directory to both `--from` and
+`--to` in order to update in place. Warning: this directory will no
+longer be usable with InvokeAI 2.3.
+
+#### Migrating in place
+
+For the adventurous, you may do an in-place upgrade from 2.3 to 3.0
+without touching the command line. ***This recipe does not work on
+Windows platforms due to a bug in the Windows version of the 2.3
+upgrade script.** See the next section for a Windows recipe.
+
+##### For Mac and Linux Users:
+
+1. Launch the InvokeAI launcher script in your current v2.3 root directory.
+
+2. Select option [9] "Update InvokeAI" to bring up the updater dialog.
+
+3. Select option [1] to upgrade to the latest release.
+
+4. Once the upgrade is finished you will be returned to the launcher
+menu. Select option [6] "Re-run the configure script to fix a broken
+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.
+
+##### For Windows Users:
+
+Windows Users can upgrade with the
+
+1. Enter the 2.3 root directory you wish to upgrade
+2. Launch `invoke.sh` or `invoke.bat`
+3. Select the "Developer's console" option [8]
+4. Type the following commands
+
+```
+pip install "invokeai @ https://github.com/invoke-ai/InvokeAI/archive/refs/tags/v3.0.0" --use-pep517 --upgrade
+invokeai-configure --root .
+```
+(Replace `v3.0.0` with the current release number if this document is out of date).
+
+The first command will install and upgrade new software to run
+InvokeAI. The second will prepare the 2.3 directory for use with 3.0.
+You may now launch the WebUI in the usual way, by selecting option [1]
+from the launcher script
+
+#### Migrating Images
+
+The migration script will migrate your invokeai settings and models,
+including textual inversion models, LoRAs and merges that you may have
+installed previously. However it does **not** migrate the generated
+images stored in your 2.3-format outputs directory. To do this, you 
+need to run an additional step:
+
+1. From a working InvokeAI 3.0 root directory, start the launcher and
+enter menu option [8] to open the "developer's console".
+
+2. At the developer's console command line, type the command:
+
+```bash
+invokeai-import-images
+```
+
+3. This will lead you through the process of confirming the desired
+   source and destination for the imported images. The images will
+   appear in the gallery board of your choice, and contain the
+   original prompt, model name, and other parameters used to generate
+   the image.
+   
+(Many kudos to **techjedi** for contributing this script.)
+
+## 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. 6-8 GB
+  of VRAM is highly recommended for rendering using the Stable
+  Diffusion XL models
+- An Apple computer with an M1 chip.
+- An AMD-based graphics card with 4GB or more VRAM memory (Linux
+  only), 6-8 GB for XL rendering.
+
+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.
+
+### *Workflows & Nodes*
+
+InvokeAI offers a fully featured workflow management solution, enabling users to combine the power of nodes based workflows with the easy of a UI. This allows for customizable generation pipelines to be developed and shared by users looking to create specific workflows to support their production use-cases.
+
+### *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, XL support*
+- *Upscaling Tools*
+- *Embedding Manager & Support*
+- *Model Manager & Support*
+- *Workflow creation & management*
+- *Node-Based Architecture*
+
+
+### Latest Changes
+
+For our latest changes, view our [Release
+Notes](https://github.com/invoke-ai/InvokeAI/releases) and the
+[CHANGELOG](docs/CHANGELOG.md).
+
+### Troubleshooting / FAQ
+
+Please check out our **[FAQ](https://invoke-ai.github.io/InvokeAI/help/FAQ/)** to get solutions for common installation
+problems and other issues. For more help, please join our [Discord][discord link]
+
+## Contributing
+
+Anyone who wishes to contribute to this project, whether documentation, features, bug fixes, code
+cleanup, testing, or code reviews, is very much encouraged to do so.
+
+Get started with contributing by reading our [Contribution documentation](https://invoke-ai.github.io/InvokeAI/contributing/CONTRIBUTING/), joining the [#dev-chat](https://discord.com/channels/1020123559063990373/1049495067846524939) or the GitHub discussion board.
+
+If you are unfamiliar with how
+to contribute to GitHub projects, we have a new contributor checklist you can follow to get started contributing: 
+[New Contributor Checklist](https://invoke-ai.github.io/InvokeAI/contributing/contribution_guides/newContributorChecklist/).
+
+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][discord link].
+
+Original portions of the software are Copyright (c) 2023 by respective contributors.
+

docker/.env.sample

@@ -19,9 +19,8 @@
 ## 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
+## GPU_DRIVER can be set to either `nvidia` or `rocm` to enable GPU support in the container accordingly.
+# GPU_DRIVER=nvidia #| rocm
 
 ## CONTAINER_UID can be set to the UID of the user on the host system that should own the files in the container.
-## It is usually not necessary to change this. Use `id -u` on the host system to find the UID.
 # CONTAINER_UID=1000

docker/Dockerfile

@@ -38,9 +38,9 @@ RUN --mount=type=cache,target=/root/.cache/pip \
     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/rocm6.1"; \
+        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/cu124"; \
+        extra_index_url_arg="--extra-index-url https://download.pytorch.org/whl/cu121"; \
     fi &&\
 
     # xformers + triton fails to install on arm64
@@ -55,7 +55,6 @@ RUN --mount=type=cache,target=/root/.cache/pip \
 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
 
 WORKDIR /build

docker/README.md

@@ -1,88 +1,41 @@
-# Invoke in Docker
+# InvokeAI Containerized
 
-First things first:
+All commands should be run within the `docker` directory: `cd docker`
 
-- 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 :rocket:
 
-## Quickstart
+On a known working Linux+Docker+CUDA (Nvidia) system, execute `./run.sh` in this directory. It will take a few minutes - depending on your internet speed - to install the core models. Once the application starts up, open `http://localhost:9090` in your browser to Invoke!
 
-No `docker compose`, no persistence, single command, using the official images:
+For more configuration options (using an AMD GPU, custom root directory location, etc): read on.
 
-**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
+## Detailed setup
 
 #### Linux
 
-1. Ensure buildkit is enabled in the Docker daemon settings (`/etc/docker/daemon.json`)
+1. Ensure builkit is enabled in the Docker daemon settings (`/etc/docker/daemon.json`)
 2. Install the `docker compose` plugin using your package manager, or follow a [tutorial](https://docs.docker.com/compose/install/linux/#install-using-the-repository).
-    - The deprecated `docker-compose` (hyphenated) CLI probably won't work. Update to a recent version.
+    - The deprecated `docker-compose` (hyphenated) CLI continues to work for now.
 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)
+    - You may need to install [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.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.
+This is done via Docker Desktop preferences
 
-### Configure the Invoke Environment
+### Configure Invoke environment
 
-1. Make a copy of `.env.sample` and name it `.env` (`cp .env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to the desired location of the InvokeAI runtime directory. It may be an existing directory from a previous installation (post 4.0.0).
+1. Make a copy of `.env.sample` and name it `.env` (`cp .env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to:
+    a. the desired location of the InvokeAI runtime directory, or
+    b. an existing, v3.0.0 compatible runtime directory.
 1. Execute `run.sh`
 
 The image will be built automatically if needed.
 
-The runtime directory (holding models and outputs) will be created in the location specified by `INVOKEAI_ROOT`. The default location is `~/invokeai`. Navigate to the Model Manager tab and install some models before generating.
+The runtime directory (holding models and outputs) will be created in the location specified by `INVOKEAI_ROOT`. The default location is `~/invokeai`. The runtime directory will be populated with the base configs and models necessary to start generating.
 
 ### Use a GPU
 
@@ -90,9 +43,9 @@ The runtime directory (holding models and outputs) will be created in the locati
 - 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.
+The Docker daemon on the system must be already set up to use the GPU. In case of Linux, this involves installing `nvidia-docker-runtime` and configuring the `nvidia` runtime as default. Steps will be different for AMD. Please see Docker documentation for the most up-to-date instructions for using your GPU with Docker.
 
-To use an AMD GPU, set `GPU_DRIVER=rocm` in your `.env` file before running `./run.sh`.
+To use an AMD GPU, set `GPU_DRIVER=rocm` in your `.env` file.
 
 ## Customize
 
@@ -106,12 +59,30 @@ Values are optional, but setting `INVOKEAI_ROOT` is highly recommended. The defa
 INVOKEAI_ROOT=/Volumes/WorkDrive/invokeai
 HUGGINGFACE_TOKEN=the_actual_token
 CONTAINER_UID=1000
-GPU_DRIVER=cuda
+GPU_DRIVER=nvidia
 ```
 
-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.
+Any environment variables supported by InvokeAI can be set here - please see the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.
 
----
+## Even Moar Customizing!
 
-[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
+See the `docker-compose.yml` file. The `command` instruction can be uncommented and used to run arbitrary startup commands. Some examples below.
+
+### Reconfigure the runtime directory
+
+Can be used to download additional models from the supported model list
+
+In conjunction with `INVOKEAI_ROOT` can be also used to initialize a runtime directory
+
+```yaml
+command:
+  - invokeai-configure
+  - --yes
+```
+
+Or install models:
+
+```yaml
+command:
+  - invokeai-model-install
+```

docker/docker-compose.yml

@@ -1,7 +1,9 @@
 # Copyright (c) 2023 Eugene Brodsky https://github.com/ebr
 
+version: '3.8'
+
 x-invokeai: &invokeai
-    image: "ghcr.io/invoke-ai/invokeai:latest"
+    image: "local/invokeai:latest"
     build:
       context: ..
       dockerfile: docker/Dockerfile
@@ -30,7 +32,7 @@ x-invokeai: &invokeai
 
 
 services:
-  invokeai-cuda:
+  invokeai-nvidia:
     <<: *invokeai
     deploy:
       resources:

docker/docker-entrypoint.sh

@@ -23,18 +23,18 @@ usermod -u ${USER_ID} ${USER} 1>/dev/null
 # but it is useful to have the full SSH server e.g. on Runpod.
 # (use SCP to copy files to/from the image, etc)
 if [[ -v "PUBLIC_KEY" ]] && [[ ! -d "${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
+    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
+chown --recursive ${USER} "${INVOKEAI_ROOT}"
 cd "${INVOKEAI_ROOT}"
 
 # Run the CMD as the Container User (not root).

docker/run.sh

@@ -8,15 +8,11 @@ run() {
   local build_args=""
   local profile=""
 
-  # create .env file if it doesn't exist, otherwise docker compose will fail
   touch .env
-
-  # parse .env file for build args
   build_args=$(awk '$1 ~ /=[^$]/ && $0 !~ /^#/ {print "--build-arg " $0 " "}' .env) &&
   profile="$(awk -F '=' '/GPU_DRIVER/ {print $2}' .env)"
 
-  # default to 'cuda' profile
-  [[ -z "$profile" ]] && profile="cuda"
+  [[ -z "$profile" ]] && profile="nvidia"
 
   local service_name="invokeai-$profile"
 

docs/CHANGELOG.md

@@ -0,0 +1,815 @@
+---
+title: Changelog
+---
+
+# :octicons-log-16: **Changelog**
+
+## v2.3.5 <small>(22 May 2023)</small>
+
+This release (along with the post1 and post2 follow-on releases) expands support for additional LoRA and LyCORIS models, upgrades diffusers versions, and fixes a few bugs.
+
+### LoRA and LyCORIS Support Improvement
+
+    A number of LoRA/LyCORIS fine-tune files (those which alter the text encoder as well as the unet model) were not having the desired effect in InvokeAI. This bug has now been fixed. Full documentation of LoRA support is available at InvokeAI LoRA Support.
+    Previously, InvokeAI did not distinguish between LoRA/LyCORIS models based on Stable Diffusion v1.5 vs those based on v2.0 and 2.1, leading to a crash when an incompatible model was loaded. This has now been fixed. In addition, the web pulldown menus for LoRA and Textual Inversion selection have been enhanced to show only those files that are compatible with the currently-selected Stable Diffusion model.
+    Support for the newer LoKR LyCORIS files has been added.
+
+### Library Updates and Speed/Reproducibility Advancements
+The major enhancement in this version is that NVIDIA users no longer need to decide between speed and reproducibility. Previously, if you activated the Xformers library, you would see improvements in speed and memory usage, but multiple images generated with the same seed and other parameters would be slightly different from each other. This is no longer the case. Relative to 2.3.5 you will see improved performance when running without Xformers, and even better performance when Xformers is activated. In both cases, images generated with the same settings will be identical.
+
+Here are the new library versions:
+Library 	Version
+Torch 	2.0.0
+Diffusers 	0.16.1
+Xformers 	0.0.19
+Compel 	1.1.5
+Other Improvements
+
+### Performance Improvements
+
+    When a model is loaded for the first time, InvokeAI calculates its checksum for incorporation into the PNG metadata. This process could take up to a minute on network-mounted disks and WSL mounts. This release noticeably speeds up the process.
+
+### Bug Fixes
+
+    The "import models from directory" and "import from URL" functionality in the console-based model installer has now been fixed.
+    When running the WebUI, we have reduced the number of times that InvokeAI reaches out to HuggingFace to fetch the list of embeddable Textual Inversion models. We have also caught and fixed a problem with the updater not correctly detecting when another instance of the updater is running 
+
+
+## v2.3.4 <small>(7 April 2023)</small>
+
+What's New in 2.3.4
+
+This features release adds support for LoRA (Low-Rank Adaptation) and LyCORIS (Lora beYond Conventional) models, as well as some minor bug fixes.
+### LoRA and LyCORIS Support
+
+LoRA files contain fine-tuning weights that enable particular styles, subjects or concepts to be applied to generated images. LyCORIS files are an extended variant of LoRA. InvokeAI supports the most common LoRA/LyCORIS format, which ends in the suffix .safetensors. You will find numerous LoRA and LyCORIS models for download at Civitai, and a small but growing number at Hugging Face. Full documentation of LoRA support is available at InvokeAI LoRA Support.( Pre-release note: this page will only be available after release)
+
+To use LoRA/LyCORIS models in InvokeAI:
+
+    Download the .safetensors files of your choice and place in /path/to/invokeai/loras. This directory was not present in earlier version of InvokeAI but will be created for you the first time you run the command-line or web client. You can also create the directory manually.
+
+    Add withLora(lora-file,weight) to your prompts. The weight is optional and will default to 1.0. A few examples, assuming that a LoRA file named loras/sushi.safetensors is present:
+
+family sitting at dinner table eating sushi withLora(sushi,0.9)
+family sitting at dinner table eating sushi withLora(sushi, 0.75)
+family sitting at dinner table eating sushi withLora(sushi)
+
+Multiple withLora() prompt fragments are allowed. The weight can be arbitrarily large, but the useful range is roughly 0.5 to 1.0. Higher weights make the LoRA's influence stronger. Negative weights are also allowed, which can lead to some interesting effects.
+
+    Generate as you usually would! If you find that the image is too "crisp" try reducing the overall CFG value or reducing individual LoRA weights. As is the case with all fine-tunes, you'll get the best results when running the LoRA on top of the model similar to, or identical with, the one that was used during the LoRA's training. Don't try to load a SD 1.x-trained LoRA into a SD 2.x model, and vice versa. This will trigger a non-fatal error message and generation will not proceed.
+
+    You can change the location of the loras directory by passing the --lora_directory option to `invokeai.
+
+### New WebUI LoRA and Textual Inversion Buttons
+
+This version adds two new web interface buttons for inserting LoRA and Textual Inversion triggers into the prompt as shown in the screenshot below.
+
+Clicking on one or the other of the buttons will bring up a menu of available LoRA/LyCORIS or Textual Inversion trigger terms. Select a menu item to insert the properly-formatted withLora() or <textual-inversion> prompt fragment into the positive prompt. The number in parentheses indicates the number of trigger terms currently in the prompt. You may click the button again and deselect the LoRA or trigger to remove it from the prompt, or simply edit the prompt directly.
+
+Currently terms are inserted into the positive prompt textbox only. However, some textual inversion embeddings are designed to be used with negative prompts. To move a textual inversion trigger into the negative prompt, simply cut and paste it.
+
+By default the Textual Inversion menu only shows locally installed models found at startup time in /path/to/invokeai/embeddings. However, InvokeAI has the ability to dynamically download and install additional Textual Inversion embeddings from the HuggingFace Concepts Library. You may choose to display the most popular of these (with five or more likes) in the Textual Inversion menu by going to Settings and turning on "Show Textual Inversions from HF Concepts Library." When this option is activated, the locally-installed TI embeddings will be shown first, followed by uninstalled terms from Hugging Face. See The Hugging Face Concepts Library and Importing Textual Inversion files for more information.
+### Minor features and fixes
+
+This release changes model switching behavior so that the command-line and Web UIs save the last model used and restore it the next time they are launched. It also improves the behavior of the installer so that the pip utility is kept up to date.
+  
+### Known Bugs in 2.3.4
+
+These are known bugs in the release.
+
+    The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
+    Windows Defender will sometimes raise Trojan or backdoor alerts for the codeformer.pth face restoration model, as well as the CIDAS/clipseg and runwayml/stable-diffusion-v1.5 models. These are false positives and can be safely ignored. InvokeAI performs a malware scan on all models as they are loaded. For additional security, you should use safetensors models whenever they are available.
+
+
+## v2.3.3 <small>(28 March 2023)</small>
+
+This is a bugfix and minor feature release.
+### Bugfixes
+
+Since version 2.3.2 the following bugs have been fixed:
+Bugs
+
+    When using legacy checkpoints with an external VAE, the VAE file is now scanned for malware prior to loading. Previously only the main model weights file was scanned.
+    Textual inversion will select an appropriate batchsize based on whether xformers is active, and will default to xformers enabled if the library is detected.
+    The batch script log file names have been fixed to be compatible with Windows.
+    Occasional corruption of the .next_prefix file (which stores the next output file name in sequence) on Windows systems is now detected and corrected.
+    Support loading of legacy config files that have no personalization (textual inversion) section.
+    An infinite loop when opening the developer's console from within the invoke.sh script has been corrected.
+    Documentation fixes, including a recipe for detecting and fixing problems with the AMD GPU ROCm driver.
+
+Enhancements
+
+    It is now possible to load and run several community-contributed SD-2.0 based models, including the often-requested "Illuminati" model.
+    The "NegativePrompts" embedding file, and others like it, can now be loaded by placing it in the InvokeAI embeddings directory.
+    If no --model is specified at launch time, InvokeAI will remember the last model used and restore it the next time it is launched.
+    On Linux systems, the invoke.sh launcher now uses a prettier console-based interface. To take advantage of it, install the dialog package using your package manager (e.g. sudo apt install dialog).
+    When loading legacy models (safetensors/ckpt) you can specify a custom config file and/or a VAE by placing like-named files in the same directory as the model following this example:
+
+my-favorite-model.ckpt
+my-favorite-model.yaml
+my-favorite-model.vae.pt      # or my-favorite-model.vae.safetensors
+
+### Known Bugs in 2.3.3
+
+These are known bugs in the release.
+
+    The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
+    Windows Defender will sometimes raise Trojan or backdoor alerts for the codeformer.pth face restoration model, as well as the CIDAS/clipseg and runwayml/stable-diffusion-v1.5 models. These are false positives and can be safely ignored. InvokeAI performs a malware scan on all models as they are loaded. For additional security, you should use safetensors models whenever they are available.
+
+
+## v2.3.2 <small>(11 March 2023)</small>
+This is a bugfix and minor feature release.
+
+### Bugfixes
+
+Since version 2.3.1 the following bugs have been fixed:
+
+    Black images appearing for potential NSFW images when generating with legacy checkpoint models and both --no-nsfw_checker and --ckpt_convert turned on.
+    Black images appearing when generating from models fine-tuned on Stable-Diffusion-2-1-base. When importing V2-derived models, you may be asked to select whether the model was derived from a "base" model (512 pixels) or the 768-pixel SD-2.1 model.
+    The "Use All" button was not restoring the Hi-Res Fix setting on the WebUI
+    When using the model installer console app, models failed to import correctly when importing from directories with spaces in their names. A similar issue with the output directory was also fixed.
+    Crashes that occurred during model merging.
+    Restore previous naming of Stable Diffusion base and 768 models.
+    Upgraded to latest versions of diffusers, transformers, safetensors and accelerate libraries upstream. We hope that this will fix the assertion NDArray > 2**32 issue that MacOS users have had when generating images larger than 768x768 pixels. Please report back.
+
+As part of the upgrade to diffusers, the location of the diffusers-based models has changed from models/diffusers to models/hub. When you launch InvokeAI for the first time, it will prompt you to OK a one-time move. This should be quick and harmless, but if you have modified your models/diffusers directory in some way, for example using symlinks, you may wish to cancel the migration and make appropriate adjustments.
+New "Invokeai-batch" script
+
+### Invoke AI Batch
+2.3.2 introduces a new command-line only script called invokeai-batch that can be used to generate hundreds of images from prompts and settings that vary systematically. This can be used to try the same prompt across multiple combinations of models, steps, CFG settings and so forth. It also allows you to template prompts and generate a combinatorial list like:
+
+a shack in the mountains, photograph
+a shack in the mountains, watercolor
+a shack in the mountains, oil painting
+a chalet in the mountains, photograph
+a chalet in the mountains, watercolor
+a chalet in the mountains, oil painting
+a shack in the desert, photograph
+...
+
+If you have a system with multiple GPUs, or a single GPU with lots of VRAM, you can parallelize generation across the combinatorial set, reducing wait times and using your system's resources efficiently (make sure you have good GPU cooling).
+
+To try invokeai-batch out. Launch the "developer's console" using the invoke launcher script, or activate the invokeai virtual environment manually. From the console, give the command invokeai-batch --help in order to learn how the script works and create your first template file for dynamic prompt generation.
+
+
+### Known Bugs in 2.3.2
+
+These are known bugs in the release.
+
+    The Ancestral DPMSolverMultistepScheduler (k_dpmpp_2a) sampler is not yet implemented for diffusers models and will disappear from the WebUI Sampler menu when a diffusers model is selected.
+    Windows Defender will sometimes raise a Trojan alert for the codeformer.pth face restoration model. As far as we have been able to determine, this is a false positive and can be safely whitelisted.
+
+
+## v2.3.1 <small>(22 February 2023)</small>
+This is primarily a bugfix release, but it does provide several new features that will improve the user experience.
+
+### Enhanced support for model management
+
+InvokeAI now makes it convenient to add, remove and modify models. You can individually import models that are stored on your local system, scan an entire folder and its subfolders for models and import them automatically, and even directly import models from the internet by providing their download URLs. You also have the option of designating a local folder to scan for new models each time InvokeAI is restarted.
+
+There are three ways of accessing the model management features:
+
+    From the WebUI, click on the cube to the right of the model selection menu. This will bring up a form that allows you to import models individually from your local disk or scan a directory for models to import.
+
+    Using the Model Installer App
+
+Choose option (5) download and install models from the invoke launcher script to start a new console-based application for model management. You can use this to select from a curated set of starter models, or import checkpoint, safetensors, and diffusers models from a local disk or the internet. The example below shows importing two checkpoint URLs from popular SD sites and a HuggingFace diffusers model using its Repository ID. It also shows how to designate a folder to be scanned at startup time for new models to import.
+
+Command-line users can start this app using the command invokeai-model-install.
+
+    Using the Command Line Client (CLI)
+
+The !install_model and !convert_model commands have been enhanced to allow entering of URLs and local directories to scan and import. The first command installs .ckpt and .safetensors files as-is. The second one converts them into the faster diffusers format before installation.
+
+Internally InvokeAI is able to probe the contents of a .ckpt or .safetensors file to distinguish among v1.x, v2.x and inpainting models. This means that you do not need to include "inpaint" in your model names to use an inpainting model. Note that Stable Diffusion v2.x models will be autoconverted into a diffusers model the first time you use it.
+
+Please see INSTALLING MODELS for more information on model management.
+
+### An Improved Installer Experience
+
+The installer now launches a console-based UI for setting and changing commonly-used startup options:
+
+After selecting the desired options, the installer installs several support models needed by InvokeAI's face reconstruction and upscaling features and then launches the interface for selecting and installing models shown earlier. At any time, you can edit the startup options by launching invoke.sh/invoke.bat and entering option (6) change InvokeAI startup options
+
+Command-line users can launch the new configure app using invokeai-configure.
+
+This release also comes with a renewed updater. To do an update without going through a whole reinstallation, launch invoke.sh or invoke.bat and choose option (9) update InvokeAI . This will bring you to a screen that prompts you to update to the latest released version, to the most current development version, or any released or unreleased version you choose by selecting the tag or branch of the desired version.
+
+Command-line users can run this interface by typing invokeai-configure
+
+### Image Symmetry Options
+
+There are now features to generate horizontal and vertical symmetry during generation. The way these work is to wait until a selected step in the generation process and then to turn on a mirror image effect. In addition to generating some cool images, you can also use this to make side-by-side comparisons of how an image will look with more or fewer steps. Access this option from the WebUI by selecting Symmetry from the image generation settings, or within the CLI by using the options --h_symmetry_time_pct and --v_symmetry_time_pct (these can be abbreviated to --h_sym and --v_sym like all other options).
+
+### A New Unified Canvas Look
+
+This release introduces a beta version of the WebUI Unified Canvas. To try it out, open up the settings dialogue in the WebUI (gear icon) and select Use Canvas Beta Layout:
+
+Refresh the screen and go to to Unified Canvas (left side of screen, third icon from the top). The new layout is designed to provide more space to work in and to keep the image controls close to the image itself:
+
+Model conversion and merging within the WebUI
+
+The WebUI now has an intuitive interface for model merging, as well as for permanent conversion of models from legacy .ckpt/.safetensors formats into diffusers format. These options are also available directly from the invoke.sh/invoke.bat scripts.
+An easier way to contribute translations to the WebUI
+
+We have migrated our translation efforts to Weblate, a FOSS translation product. Maintaining the growing project's translations is now far simpler for the maintainers and community. Please review our brief translation guide for more information on how to contribute.
+Numerous internal bugfixes and performance issues
+
+### Bug Fixes
+This releases quashes multiple bugs that were reported in 2.3.0. Major internal changes include upgrading to diffusers 0.13.0, and using the compel library for prompt parsing. See Detailed Change Log for a detailed list of bugs caught and squished.
+Summary of InvokeAI command line scripts (all accessible via the launcher menu)
+Command 	Description
+invokeai 	Command line interface
+invokeai --web 	Web interface
+invokeai-model-install 	Model installer with console forms-based front end
+invokeai-ti --gui 	Textual inversion, with a console forms-based front end
+invokeai-merge --gui 	Model merging, with a console forms-based front end
+invokeai-configure 	Startup configuration; can also be used to reinstall support models
+invokeai-update 	InvokeAI software updater
+
+### Known Bugs in 2.3.1
+
+These are known bugs in the release.
+    MacOS users generating 768x768 pixel images or greater using diffusers models may experience a hard crash with assertion NDArray > 2**32 This appears to be an issu...
+
+
+
+## v2.3.0 <small>(15 January 2023)</small>
+
+**Transition to diffusers
+
+Version 2.3 provides support for both the traditional `.ckpt` weight
+checkpoint files as well as the HuggingFace `diffusers` format. This
+introduces several changes you should know about.
+
+1. The models.yaml format has been updated. There are now two
+   different type of configuration stanza. The traditional ckpt
+   one will look like this, with a `format` of `ckpt` and a
+   `weights` field that points to the absolute or ROOTDIR-relative
+   location of the ckpt file.
+
+   ```
+   inpainting-1.5:
+      description: RunwayML SD 1.5 model optimized for inpainting (4.27 GB)
+      repo_id: runwayml/stable-diffusion-inpainting
+      format: ckpt
+      width: 512
+      height: 512
+      weights: models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
+      config: configs/stable-diffusion/v1-inpainting-inference.yaml
+      vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
+   ```
+
+  A configuration stanza for a diffusers model hosted at HuggingFace will look like this,
+  with a `format` of `diffusers` and a `repo_id` that points to the
+  repository ID of the model on HuggingFace:
+
+  ```
+  stable-diffusion-2.1:
+  description: Stable Diffusion version 2.1 diffusers model (5.21 GB)
+  repo_id: stabilityai/stable-diffusion-2-1
+  format: diffusers
+  ```
+
+  A configuration stanza for a diffuers model stored locally should
+  look like this, with a `format` of `diffusers`, but a `path` field
+  that points at the directory that contains `model_index.json`:
+
+  ```
+  waifu-diffusion:
+  description: Latest waifu diffusion 1.4
+  format: diffusers
+  path: models/diffusers/hakurei-haifu-diffusion-1.4
+  ```
+
+2. In order of precedence, InvokeAI will now use HF_HOME, then
+   XDG_CACHE_HOME, then finally default to `ROOTDIR/models` to
+   store HuggingFace diffusers models.
+
+   Consequently, the format of the models directory has changed to
+   mimic the HuggingFace cache directory. When HF_HOME and XDG_HOME
+   are not set, diffusers models are now automatically downloaded
+   and retrieved from the directory `ROOTDIR/models/diffusers`,
+   while other models are stored in the directory
+   `ROOTDIR/models/hub`. This organization is the same as that used
+   by HuggingFace for its cache management.
+
+   This allows you to share diffusers and ckpt model files easily with
+   other machine learning applications that use the HuggingFace
+   libraries. To do this, set the environment variable HF_HOME
+   before starting up InvokeAI to tell it what directory to
+   cache models in. To tell InvokeAI to use the standard HuggingFace
+   cache directory, you would set HF_HOME like this (Linux/Mac):
+
+   `export HF_HOME=~/.cache/huggingface`
+
+   Both HuggingFace and InvokeAI will fall back to the XDG_CACHE_HOME
+   environment variable if HF_HOME is not set; this path
+   takes precedence over `ROOTDIR/models` to allow for the same sharing
+   with other machine learning applications that use HuggingFace
+   libraries.
+
+3. If you upgrade to InvokeAI 2.3.* from an earlier version, there
+   will be a one-time migration from the old models directory format
+   to the new one. You will see a message about this the first time
+   you start `invoke.py`.
+
+4. Both the front end back ends of the model manager have been
+   rewritten to accommodate diffusers. You can import models using
+   their local file path, using their URLs, or their HuggingFace
+   repo_ids. On the command line, all these syntaxes work:
+
+   ```
+   !import_model stabilityai/stable-diffusion-2-1-base
+   !import_model /opt/sd-models/sd-1.4.ckpt
+   !import_model https://huggingface.co/Fictiverse/Stable_Diffusion_PaperCut_Model/blob/main/PaperCut_v1.ckpt
+   ```
+
+**KNOWN BUGS (15 January 2023)
+
+1. On CUDA systems, the 768 pixel stable-diffusion-2.0 and
+   stable-diffusion-2.1 models can only be run as `diffusers` models
+   when the `xformer` library is installed and configured. Without
+   `xformers`, InvokeAI returns black images.
+
+2. Inpainting and outpainting have regressed in quality.
+
+Both these issues are being actively worked on.
+
+## v2.2.4 <small>(11 December 2022)</small>
+
+**the `invokeai` directory**
+
+Previously there were two directories to worry about, the directory that
+contained the InvokeAI source code and the launcher scripts, and the `invokeai`
+directory that contained the models files, embeddings, configuration and
+outputs. With the 2.2.4 release, this dual system is done away with, and
+everything, including the `invoke.bat` and `invoke.sh` launcher scripts, now
+live in a directory named `invokeai`. By default this directory is located in
+your home directory (e.g. `\Users\yourname` on Windows), but you can select
+where it goes at install time.
+
+After installation, you can delete the install directory (the one that the zip
+file creates when it unpacks). Do **not** delete or move the `invokeai`
+directory!
+
+**Initialization file `invokeai/invokeai.init`**
+
+You can place frequently-used startup options in this file, such as the default
+number of steps or your preferred sampler. To keep everything in one place, this
+file has now been moved into the `invokeai` directory and is named
+`invokeai.init`.
+
+**To update from Version 2.2.3**
+
+The easiest route is to download and unpack one of the 2.2.4 installer files.
+When it asks you for the location of the `invokeai` runtime directory, respond
+with the path to the directory that contains your 2.2.3 `invokeai`. That is, if
+`invokeai` lives at `C:\Users\fred\invokeai`, then answer with `C:\Users\fred`
+and answer "Y" when asked if you want to reuse the directory.
+
+The `update.sh` (`update.bat`) script that came with the 2.2.3 source installer
+does not know about the new directory layout and won't be fully functional.
+
+**To update to 2.2.5 (and beyond) there's now an update path**
+
+As they become available, you can update to more recent versions of InvokeAI
+using an `update.sh` (`update.bat`) script located in the `invokeai` directory.
+Running it without any arguments will install the most recent version of
+InvokeAI. Alternatively, you can get set releases by running the `update.sh`
+script with an argument in the command shell. This syntax accepts the path to
+the desired release's zip file, which you can find by clicking on the green
+"Code" button on this repository's home page.
+
+**Other 2.2.4 Improvements**
+
+- Fix InvokeAI GUI initialization by @addianto in #1687
+- fix link in documentation by @lstein in #1728
+- Fix broken link by @ShawnZhong in #1736
+- Remove reference to binary installer by @lstein in #1731
+- documentation fixes for 2.2.3 by @lstein in #1740
+- Modify installer links to point closer to the source installer by @ebr in
+  #1745
+- add documentation warning about 1650/60 cards by @lstein in #1753
+- Fix Linux source URL in installation docs by @andybearman in #1756
+- Make install instructions discoverable in readme by @damian0815 in #1752
+- typo fix by @ofirkris in #1755
+- Non-interactive model download (support HUGGINGFACE_TOKEN) by @ebr in #1578
+- fix(srcinstall): shell installer - cp scripts instead of linking by @tildebyte
+  in #1765
+- stability and usage improvements to binary & source installers by @lstein in
+  #1760
+- fix off-by-one bug in cross-attention-control by @damian0815 in #1774
+- Eventually update APP_VERSION to 2.2.3 by @spezialspezial in #1768
+- invoke script cds to its location before running by @lstein in #1805
+- Make PaperCut and VoxelArt models load again by @lstein in #1730
+- Fix --embedding_directory / --embedding_path not working by @blessedcoolant in
+  #1817
+- Clean up readme by @hipsterusername in #1820
+- Optimized Docker build with support for external working directory by @ebr in
+  #1544
+- disable pushing the cloud container by @mauwii in #1831
+- Fix docker push github action and expand with additional metadata by @ebr in
+  #1837
+- Fix Broken Link To Notebook by @VedantMadane in #1821
+- Account for flat models by @spezialspezial in #1766
+- Update invoke.bat.in isolate environment variables by @lynnewu in #1833
+- Arch Linux Specific PatchMatch Instructions & fixing conda install on linux by
+  @SammCheese in #1848
+- Make force free GPU memory work in img2img by @addianto in #1844
+- New installer by @lstein
+
+## v2.2.3 <small>(2 December 2022)</small>
+
+!!! Note
+
+    This point release removes references to the binary installer from the
+    installation guide. The binary installer is not stable at the current
+    time. First time users are encouraged to use the "source" installer as
+    described in [Installing InvokeAI with the Source Installer](installation/deprecated_documentation/INSTALL_SOURCE.md)
+
+With InvokeAI 2.2, this project now provides enthusiasts and professionals a
+robust workflow solution for creating AI-generated and human facilitated
+compositions. Additional enhancements have been made as well, improving safety,
+ease of use, and installation.
+
+Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a
+512x768 image (and less for smaller images), and is compatible with
+Windows/Linux/Mac (M1 & M2).
+
+You can see the [release video](https://youtu.be/hIYBfDtKaus) here, which
+introduces the main WebUI enhancement for version 2.2 -
+[The Unified Canvas](features/UNIFIED_CANVAS.md). This new workflow is the
+biggest enhancement added to the WebUI to date, and unlocks a stunning amount of
+potential for users to create and iterate on their creations. The following
+sections describe what's new for InvokeAI.
+
+## v2.2.2 <small>(30 November 2022)</small>
+
+!!! note
+
+    The binary installer is not ready for prime time. First time users are recommended to install via the "source" installer accessible through the links at the bottom of this page.****
+
+With InvokeAI 2.2, this project now provides enthusiasts and professionals a
+robust workflow solution for creating AI-generated and human facilitated
+compositions. Additional enhancements have been made as well, improving safety,
+ease of use, and installation.
+
+Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a
+512x768 image (and less for smaller images), and is compatible with
+Windows/Linux/Mac (M1 & M2).
+
+You can see the [release video](https://youtu.be/hIYBfDtKaus) here, which
+introduces the main WebUI enhancement for version 2.2 -
+[The Unified Canvas](https://invoke-ai.github.io/InvokeAI/features/UNIFIED_CANVAS/).
+This new workflow is the biggest enhancement added to the WebUI to date, and
+unlocks a stunning amount of potential for users to create and iterate on their
+creations. The following sections describe what's new for InvokeAI.
+
+## v2.2.0 <small>(2 December 2022)</small>
+
+With InvokeAI 2.2, this project now provides enthusiasts and professionals a
+robust workflow solution for creating AI-generated and human facilitated
+compositions. Additional enhancements have been made as well, improving safety,
+ease of use, and installation.
+
+Optimized for efficiency, InvokeAI needs only ~3.5GB of VRAM to generate a
+512x768 image (and less for smaller images), and is compatible with
+Windows/Linux/Mac (M1 & M2).
+
+You can see the [release video](https://youtu.be/hIYBfDtKaus) here, which
+introduces the main WebUI enhancement for version 2.2 -
+[The Unified Canvas](features/UNIFIED_CANVAS.md). This new workflow is the
+biggest enhancement added to the WebUI to date, and unlocks a stunning amount of
+potential for users to create and iterate on their creations. The following
+sections describe what's new for InvokeAI.
+
+## v2.1.3 <small>(13 November 2022)</small>
+
+- A choice of installer scripts that automate installation and configuration.
+  See
+  [Installation](installation/INSTALLATION.md).
+- A streamlined manual installation process that works for both Conda and
+  PIP-only installs. See
+  [Manual Installation](installation/020_INSTALL_MANUAL.md).
+- The ability to save frequently-used startup options (model to load, steps,
+  sampler, etc) in a `.invokeai` file. See
+  [Client](deprecated/CLI.md)
+- Support for AMD GPU cards (non-CUDA) on Linux machines.
+- Multiple bugs and edge cases squashed.
+
+## v2.1.0 <small>(2 November 2022)</small>
+
+- update mac instructions to use invokeai for env name by @willwillems in #1030
+- Update .gitignore by @blessedcoolant in #1040
+- reintroduce fix for m1 from #579 missing after merge by @skurovec in #1056
+- Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in #1060
+- Print out the device type which is used by @manzke in #1073
+- Hires Addition by @hipsterusername in #1063
+- fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by
+  @skurovec in #1081
+- Forward dream.py to invoke.py using the same interpreter, add deprecation
+  warning by @db3000 in #1077
+- fix noisy images at high step counts by @lstein in #1086
+- Generalize facetool strength argument by @db3000 in #1078
+- Enable fast switching among models at the invoke> command line by @lstein in
+  #1066
+- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in #1095
+- Update generate.py by @unreleased in #1109
+- Update 'ldm' env to 'invokeai' in troubleshooting steps by @19wolf in #1125
+- Fixed documentation typos and resolved merge conflicts by @rupeshs in #1123
+- Fix broken doc links, fix malaprop in the project subtitle by @majick in #1131
+- Only output facetool parameters if enhancing faces by @db3000 in #1119
+- Update gitignore to ignore codeformer weights at new location by
+  @spezialspezial in #1136
+- fix links to point to invoke-ai.github.io #1117 by @mauwii in #1143
+- Rework-mkdocs by @mauwii in #1144
+- add option to CLI and pngwriter that allows user to set PNG compression level
+  by @lstein in #1127
+- Fix img2img DDIM index out of bound by @wfng92 in #1137
+- Fix gh actions by @mauwii in #1128
+- update mac instructions to use invokeai for env name by @willwillems in #1030
+- Update .gitignore by @blessedcoolant in #1040
+- reintroduce fix for m1 from #579 missing after merge by @skurovec in #1056
+- Update Stable_Diffusion_AI_Notebook.ipynb (Take 2) by @ChloeL19 in #1060
+- Print out the device type which is used by @manzke in #1073
+- Hires Addition by @hipsterusername in #1063
+- fix for "1 leaked semaphore objects to clean up at shutdown" on M1 by
+  @skurovec in #1081
+- Forward dream.py to invoke.py using the same interpreter, add deprecation
+  warning by @db3000 in #1077
+- fix noisy images at high step counts by @lstein in #1086
+- Generalize facetool strength argument by @db3000 in #1078
+- Enable fast switching among models at the invoke> command line by @lstein in
+  #1066
+- Fix Typo, committed changing ldm environment to invokeai by @jdries3 in #1095
+- Fixed documentation typos and resolved merge conflicts by @rupeshs in #1123
+- Only output facetool parameters if enhancing faces by @db3000 in #1119
+- add option to CLI and pngwriter that allows user to set PNG compression level
+  by @lstein in #1127
+- Fix img2img DDIM index out of bound by @wfng92 in #1137
+- Add text prompt to inpaint mask support by @lstein in #1133
+- Respect http[s] protocol when making socket.io middleware by @damian0815 in
+  #976
+- WebUI: Adds Codeformer support by @psychedelicious in #1151
+- Skips normalizing prompts for web UI metadata by @psychedelicious in #1165
+- Add Asymmetric Tiling by @carson-katri in #1132
+- Web UI: Increases max CFG Scale to 200 by @psychedelicious in #1172
+- Corrects color channels in face restoration; Fixes #1167 by @psychedelicious
+  in #1175
+- Flips channels using array slicing instead of using OpenCV by @psychedelicious
+  in #1178
+- Fix typo in docs: s/Formally/Formerly by @noodlebox in #1176
+- fix clipseg loading problems by @lstein in #1177
+- Correct color channels in upscale using array slicing by @wfng92 in #1181
+- Web UI: Filters existing images when adding new images; Fixes #1085 by
+  @psychedelicious in #1171
+- fix a number of bugs in textual inversion by @lstein in #1190
+- Improve !fetch, add !replay command by @ArDiouscuros in #882
+- Fix generation of image with s>1000 by @holstvoogd in #951
+- Web UI: Gallery improvements by @psychedelicious in #1198
+- Update CLI.md by @krummrey in #1211
+- outcropping improvements by @lstein in #1207
+- add support for loading VAE autoencoders by @lstein in #1216
+- remove duplicate fix_func for MPS by @wfng92 in #1210
+- Metadata storage and retrieval fixes by @lstein in #1204
+- nix: add shell.nix file by @Cloudef in #1170
+- Web UI: Changes vite dist asset paths to relative by @psychedelicious in #1185
+- Web UI: Removes isDisabled from PromptInput by @psychedelicious in #1187
+- Allow user to generate images with initial noise as on M1 / mps system by
+  @ArDiouscuros in #981
+- feat: adding filename format template by @plucked in #968
+- Web UI: Fixes broken bundle by @psychedelicious in #1242
+- Support runwayML custom inpainting model by @lstein in #1243
+- Update IMG2IMG.md by @talitore in #1262
+- New dockerfile - including a build- and a run- script as well as a GH-Action
+  by @mauwii in #1233
+- cut over from karras to model noise schedule for higher steps by @lstein in
+  #1222
+- Prompt tweaks by @lstein in #1268
+- Outpainting implementation by @Kyle0654 in #1251
+- fixing aspect ratio on hires by @tjennings in #1249
+- Fix-build-container-action by @mauwii in #1274
+- handle all unicode characters by @damian0815 in #1276
+- adds models.user.yml to .gitignore by @JakeHL in #1281
+- remove debug branch, set fail-fast to false by @mauwii in #1284
+- Protect-secrets-on-pr by @mauwii in #1285
+- Web UI: Adds initial inpainting implementation by @psychedelicious in #1225
+- fix environment-mac.yml - tested on x64 and arm64 by @mauwii in #1289
+- Use proper authentication to download model by @mauwii in #1287
+- Prevent indexing error for mode RGB by @spezialspezial in #1294
+- Integrate sd-v1-5 model into test matrix (easily expandable), remove
+  unecesarry caches by @mauwii in #1293
+- add --no-interactive to configure_invokeai step by @mauwii in #1302
+- 1-click installer and updater. Uses micromamba to install git and conda into a
+  contained environment (if necessary) before running the normal installation
+  script by @cmdr2 in #1253
+- configure_invokeai.py script downloads the weight files by @lstein in #1290
+
+## v2.0.1 <small>(13 October 2022)</small>
+
+- fix noisy images at high step count when using k\* samplers
+- dream.py script now calls invoke.py module directly rather than via a new
+  python process (which could break the environment)
+
+## v2.0.0 <small>(9 October 2022)</small>
+
+- `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`
+- img2img runs on all k\* samplers
+- Support for
+  [negative prompts](features/PROMPTS.md#negative-and-unconditioned-prompts)
+- Support for CodeFormer face reconstruction
+- Support for Textual Inversion on Macintoshes
+- Support in both WebGUI and CLI for
+  [post-processing of previously-generated images](features/POSTPROCESS.md)
+  using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E
+  infinite canvas), and "embiggen" upscaling. See the `!fix` command.
+- New `--hires` option on `invoke>` line allows
+  [larger images to be created without duplicating elements](deprecated/CLI.md#this-is-an-example-of-txt2img),
+  at the cost of some performance.
+- New `--perlin` and `--threshold` options allow you to add and control
+  variation during image generation (see
+  [Thresholding and Perlin Noise Initialization](features/OTHER.md#thresholding-and-perlin-noise-initialization-options))
+- Extensive metadata now written into PNG files, allowing reliable regeneration
+  of images and tweaking of previous settings.
+- Command-line completion in `invoke.py` now works on Windows, Linux and Mac
+  platforms.
+- Improved [command-line completion behavior](deprecated/CLI.md) New commands
+  added:
+  - List command-line history with `!history`
+  - Search command-line history with `!search`
+  - Clear history with `!clear`
+- Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto
+  configure. To switch away from auto use the new flag like
+  `--precision=float32`.
+
+## v1.14 <small>(11 September 2022)</small>
+
+- Memory optimizations for small-RAM cards. 512x512 now possible on 4 GB GPUs.
+- Full support for Apple hardware with M1 or M2 chips.
+- Add "seamless mode" for circular tiling of image. Generates beautiful effects.
+  ([prixt](https://github.com/prixt)).
+- Inpainting support.
+- Improved web server GUI.
+- Lots of code and documentation cleanups.
+
+## v1.13 <small>(3 September 2022)</small>
+
+- Support image variations (see [VARIATIONS](deprecated/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
+  hardware [Arturo Mendivil](https://github.com/artmen1516)
+- WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling
+  [Kevin Gibbons](https://github.com/bakkot)
+- WebUI supports incremental display of in-progress images during generation
+  [Kevin Gibbons](https://github.com/bakkot)
+- A new configuration file scheme that allows new models (including upcoming
+  stable-diffusion-v1.5) to be added without altering the code.
+  ([David Wager](https://github.com/maddavid12))
+- Can specify --grid on invoke.py command line as the default.
+- Miscellaneous internal bug and stability fixes.
+- Works on M1 Apple hardware.
+- Multiple bug fixes.
+
+---
+
+## v1.12 <small>(28 August 2022)</small>
+
+- Improved file handling, including ability to read prompts from standard input.
+  (kudos to [Yunsaki](https://github.com/yunsaki)
+- The web server is now integrated with the invoke.py script. Invoke by adding
+  --web to the invoke.py command arguments.
+- Face restoration and upscaling via GFPGAN and Real-ESGAN are now automatically
+  enabled if the GFPGAN directory is located as a sibling to Stable Diffusion.
+  VRAM requirements are modestly reduced. Thanks to both
+  [Blessedcoolant](https://github.com/blessedcoolant) and
+  [Oceanswave](https://github.com/oceanswave) for their work on this.
+- You can now swap samplers on the invoke> command line.
+  [Blessedcoolant](https://github.com/blessedcoolant)
+
+---
+
+## v1.11 <small>(26 August 2022)</small>
+
+- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module.
+  (kudos to [Oceanswave](https://github.com/Oceanswave)
+- You now can specify a seed of -1 to use the previous image's seed, -2 to use
+  the seed for the image generated before that, etc. Seed memory only extends
+  back to the previous command, but will work on all images generated with the
+  -n# switch.
+- Variant generation support temporarily disabled pending more general solution.
+- Created a feature branch named **yunsaki-morphing-invoke** which adds
+  experimental support for iteratively modifying the prompt and its parameters.
+  Please
+  see[Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86) for
+  a synopsis of how this works. Note that when this feature is eventually added
+  to the main branch, it will may be modified significantly.
+
+---
+
+## v1.10 <small>(25 August 2022)</small>
+
+- A barebones but fully functional interactive web server for online generation
+  of txt2img and img2img.
+
+---
+
+## v1.09 <small>(24 August 2022)</small>
+
+- A new -v option allows you to generate multiple variants of an initial image
+  in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave).
+  [ See this discussion in the PR for examples and details on use](https://github.com/lstein/stable-diffusion/pull/71#issuecomment-1226700810))
+- Added ability to personalize text to image generation (kudos to
+  [Oceanswave](https://github.com/Oceanswave) and
+  [nicolai256](https://github.com/nicolai256))
+- Enabled all of the samplers from k_diffusion
+
+---
+
+## v1.08 <small>(24 August 2022)</small>
+
+- Escape single quotes on the invoke> command before trying to parse. This
+  avoids parse errors.
+- Removed instruction to get Python3.8 as first step in Windows install.
+  Anaconda3 does it for you.
+- Added bounds checks for numeric arguments that could cause crashes.
+- Cleaned up the copyright and license agreement files.
+
+---
+
+## v1.07 <small>(23 August 2022)</small>
+
+- Image filenames will now never fill gaps in the sequence, but will be assigned
+  the next higher name in the chosen directory. This ensures that the alphabetic
+  and chronological sort orders are the same.
+
+---
+
+## v1.06 <small>(23 August 2022)</small>
+
+- Added weighted prompt support contributed by
+  [xraxra](https://github.com/xraxra)
+- Example of using weighted prompts to tweak a demonic figure contributed by
+  [bmaltais](https://github.com/bmaltais)
+
+---
+
+## v1.05 <small>(22 August 2022 - after the drop)</small>
+
+- Filenames now use the following formats: 000010.95183149.png -- Two files
+  produced by the same command (e.g. -n2), 000010.26742632.png -- distinguished
+  by a different seed.
+
+  000011.455191342.01.png -- Two files produced by the same command using
+  000011.455191342.02.png -- a batch size>1 (e.g. -b2). They have the same seed.
+
+  000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid
+  can be regenerated with the indicated key
+
+- It should no longer be possible for one image to overwrite another
+- You can use the "cd" and "pwd" commands at the invoke> prompt to set and
+  retrieve the path of the output directory.
+
+---
+
+## v1.04 <small>(22 August 2022 - after the drop)</small>
+
+- Updated README to reflect installation of the released weights.
+- Suppressed very noisy and inconsequential warning when loading the frozen CLIP
+  tokenizer.
+
+---
+
+## v1.03 <small>(22 August 2022)</small>
+
+- The original txt2img and img2img scripts from the CompViz repository have been
+  moved into a subfolder named "orig_scripts", to reduce confusion.
+
+---
+
+## v1.02 <small>(21 August 2022)</small>
+
+- A copy of the prompt and all of its switches and options is now stored in the
+  corresponding image in a tEXt metadata field named "Dream". You can read the
+  prompt using scripts/images2prompt.py, or an image editor that allows you to
+  explore the full metadata. **Please run "conda env update" to load the k_lms
+  dependencies!!**
+
+---
+
+## v1.01 <small>(21 August 2022)</small>
+
+- added k_lms sampling. **Please run "conda env update" to load the k_lms
+  dependencies!!**
+- use half precision arithmetic by default, resulting in faster execution and
+  lower memory requirements Pass argument --full_precision to invoke.py to get
+  slower but more accurate image generation
+
+---
+
+## Links
+
+- **[Read Me](index.md)**

docs/contributing/CONTRIBUTING.md

@@ -1,42 +1,41 @@
 # Contributing
 
-Invoke 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.
+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.
 
-We welcome contributions, whether features, bug fixes, code cleanup, testing, code reviews, documentation or translation. Please check in with us before diving in to code to ensure your work aligns with our vision.
+
+# 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.
 
 ## Development
-
-If you’d like to help with development, please see our [development guide](contribution_guides/development.md).
+If you’d like to help with development, please see our [development guide](contribution_guides/development.md). 
 
 **New Contributors:** If you’re unfamiliar with contributing to open source projects, take a look at our [new contributor guide](contribution_guides/newContributorChecklist.md).
 
 ## Nodes
-
 If you’d like to add a Node, please see our [nodes contribution guide](../nodes/contributingNodes.md).
 
 ## 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. 
 
-Helping support other users in [Discord](https://discord.gg/ZmtBAhwWhy) and on Github are valuable forms of contribution that we greatly appreciate.
-
-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.
+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. 
 
 ## Documentation
-
 If you’d like to help with documentation, please see our [documentation guide](contribution_guides/documentation.md).
 
 ## Translation
-
 If you'd like to help with translation, please see our [translation guide](contribution_guides/translation.md).
 
-## Tutorials
+## Tutorials 
+Please reach out to @imic or @hipsterusername on [Discord](https://discord.gg/ZmtBAhwWhy) to help create tutorials for InvokeAI.
 
-Please reach out to @hipsterusername on [Discord](https://discord.gg/ZmtBAhwWhy) to help create tutorials for InvokeAI.
+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.
 
-## Contributors
+
+# Contributors
 
 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
+# 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.
 
@@ -50,3 +49,12 @@ 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.
+
+---
+
+Remember, your contributions help make this project great. We're excited to see what you'll bring to our community!

docs/contributing/DOWNLOAD_QUEUE.md

@@ -128,8 +128,7 @@ 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
+The only job type currently implemented is `DownloadJob`, a pydantic object with the
 following fields:
 
 | **Field**      | **Type**        |  **Default**  | **Description** |
@@ -139,7 +138,7 @@ following fields:
 | `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_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           |
@@ -191,33 +190,6 @@ 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
@@ -279,40 +251,11 @@ jobs using `list_jobs()`, fetch a single job by its with
 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)
+#### job = queue.download(source, dest, priority, access_token)
 
 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.

docs/contributing/INVOCATIONS.md

@@ -144,7 +144,7 @@ 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 constraints on those fields, and will raise an exception if the
+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.
 

docs/contributing/LOCAL_DEVELOPMENT.md

@@ -1,10 +1,21 @@
 # Local Development
 
-If you want to contribute, you will need to set up a [local development environment](./dev-environment.md).
+If you are looking to contribute you will need to have a local development
+environment. See the
+[Developer Install](../installation/020_INSTALL_MANUAL.md#developer-install) for
+full details.
+
+Broadly this involves cloning the repository, installing the pre-reqs, and
+InvokeAI (in editable form). Assuming this is working, choose your area of
+focus.
 
 ## Documentation
 
-We use [mkdocs](https://www.mkdocs.org) for our documentation with the [material theme](https://squidfunk.github.io/mkdocs-material/). Documentation is written in markdown files under the `./docs` folder and then built into a static website for hosting with GitHub Pages at [invoke-ai.github.io/InvokeAI](https://invoke-ai.github.io/InvokeAI).
+We use [mkdocs](https://www.mkdocs.org) for our documentation with the
+[material theme](https://squidfunk.github.io/mkdocs-material/). Documentation is
+written in markdown files under the `./docs` folder and then built into a static
+website for hosting with GitHub Pages at
+[invoke-ai.github.io/InvokeAI](https://invoke-ai.github.io/InvokeAI).
 
 To contribute to the documentation you'll need to install the dependencies. Note
 the use of `"`.
@@ -39,7 +50,6 @@ and will be required for testing the changes you make to the code.
 ### Tests
 
 See the [tests documentation](./TESTS.md) for information about running and writing tests.
-
 ### Reloading Changes
 
 Experimenting with changes to the Python source code is a drag if you have to re-start the server —
@@ -53,6 +63,7 @@ running server on the fly.
 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.
 
+
 ## Front End
 
 <!--#TODO: get input from blessedcoolant here, for the moment inserted the frontend README via snippets extension.-->
@@ -239,7 +250,7 @@ Consult the
 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 automatically.
+all the same app settings and extensions automagically.
 
 ##### One remote dev gotcha
 

docs/contributing/MODEL_MANAGER.md

@@ -397,25 +397,26 @@ In the event you wish to create a new installer, you may use the
 following initialization pattern:
 
 ```
-from invokeai.app.services.config import get_config
+from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.model_records import ModelRecordServiceSQL
 from invokeai.app.services.model_install import ModelInstallService
 from invokeai.app.services.download import DownloadQueueService
-from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
+from invokeai.app.services.shared.sqlite import SqliteDatabase
 from invokeai.backend.util.logging import InvokeAILogger
 
-config = get_config()
+config = InvokeAIAppConfig.get_config()
+config.parse_args()
 
 logger = InvokeAILogger.get_logger(config=config)
-db = SqliteDatabase(config.db_path, logger)
-record_store = ModelRecordServiceSQL(db, logger)
+db = SqliteDatabase(config, logger)
+record_store = ModelRecordServiceSQL(db)
 queue = DownloadQueueService()
 queue.start()
 
-installer = ModelInstallService(app_config=config,
+installer = ModelInstallService(app_config=config, 
                                 record_store=record_store,
-                                download_queue=queue
-                                )
+              download_queue=queue
+           )
 installer.start()
 ```
 
@@ -1366,20 +1367,12 @@ the in-memory loaded model:
 | `model`        | AnyModel               | The instantiated model (details below) |
 | `locker`       | ModelLockerBase        | A context manager that mediates the movement of the model into VRAM |
 
-### get_model_by_key(key, [submodel]) -> LoadedModel
-
-The `get_model_by_key()` method will retrieve the model using its
-unique database key. For example:
-
-loaded_model = loader.get_model_by_key('f13dd932c0c35c22dcb8d6cda4203764', SubModelType('vae'))
-
-`get_model_by_key()` may raise any of the following exceptions:
-
-* `UnknownModelException`   -- key not in database
-* `ModelNotFoundException`  -- key in database but model not found at path
-* `NotImplementedException` -- the loader doesn't know how to load this type of model
-
-### Using the Loaded Model in Inference
+Because the loader can return multiple model types, it is typed to
+return `AnyModel`, a Union `ModelMixin`, `torch.nn.Module`,
+`IAIOnnxRuntimeModel`, `IPAdapter`, `IPAdapterPlus`, and
+`EmbeddingModelRaw`. `ModelMixin` is the base class of all diffusers
+models, `EmbeddingModelRaw` is used for LoRA and TextualInversion
+models. The others are obvious.
 
 `LoadedModel` acts as a context manager. The context loads the model
 into the execution device (e.g. VRAM on CUDA systems), locks the model
@@ -1387,33 +1380,17 @@ in the execution device for the duration of the context, and returns
 the model. Use it like this:
 
 ```
-loaded_model_= loader.get_model_by_key('f13dd932c0c35c22dcb8d6cda4203764', SubModelType('vae'))
-with loaded_model as vae:
+model_info = loader.get_model_by_key('f13dd932c0c35c22dcb8d6cda4203764', SubModelType('vae'))
+with model_info as vae:
  image = vae.decode(latents)[0]
 ```
 
-The object returned by the LoadedModel context manager is an
-`AnyModel`, which is a Union of `ModelMixin`, `torch.nn.Module`,
-`IAIOnnxRuntimeModel`, `IPAdapter`, `IPAdapterPlus`, and
-`EmbeddingModelRaw`. `ModelMixin` is the base class of all diffusers
-models, `EmbeddingModelRaw` is used for LoRA and TextualInversion
-models. The others are obvious.
-
-In addition, you may call `LoadedModel.model_on_device()`, a context
-manager that returns a tuple of the model's state dict in CPU and the
-model itself in VRAM. It is used to optimize the LoRA patching and
-unpatching process:
-
-```
-loaded_model_= loader.get_model_by_key('f13dd932c0c35c22dcb8d6cda4203764', SubModelType('vae'))
-with loaded_model.model_on_device() as (state_dict, vae):
- image = vae.decode(latents)[0]
-```
-
-Since not all models have state dicts, the `state_dict` return value
-can be None.
-
+`get_model_by_key()` may raise any of the following exceptions:
 
+* `UnknownModelException`   -- key not in database
+* `ModelNotFoundException`  -- key in database but model not found at path
+* `NotImplementedException` -- the loader doesn't know how to load this type of model
+  
 ### Emitting model loading events
 
 When the `context` argument is passed to `load_model_*()`, it will
@@ -1601,59 +1578,3 @@ This method takes a model key, looks it up using the
 `ModelRecordServiceBase` object in `mm.store`, and passes the returned
 model configuration to `load_model_by_config()`.  It may raise a
 `NotImplementedException`.
-
-## Invocation Context Model Manager API
-
-Within invocations, the following methods are available from the
-`InvocationContext` object:
-
-### context.download_and_cache_model(source) -> Path
-
-This method accepts a `source` of a remote model, downloads and caches
-it locally, and then returns a Path to the local model. The source can
-be a direct download URL or a HuggingFace repo_id.
-
-In the case of HuggingFace repo_id, the following variants are
-recognized:
-
-* stabilityai/stable-diffusion-v4           -- default model
-* stabilityai/stable-diffusion-v4:fp16      -- fp16 variant
-* stabilityai/stable-diffusion-v4:fp16:vae  -- the fp16 vae subfolder
-* stabilityai/stable-diffusion-v4:onnx:vae  -- the onnx variant vae subfolder
-
-You can also point at an arbitrary individual file within a repo_id
-directory using this syntax:
-
-* stabilityai/stable-diffusion-v4::/checkpoints/sd4.safetensors
-
-### context.load_local_model(model_path, [loader]) -> LoadedModel
-
-This method loads a local model from the indicated path, returning a
-`LoadedModel`. The optional loader is a Callable that accepts a Path
-to the object, and returns a `AnyModel` object. If no loader is
-provided, then the method will use `torch.load()` for a .ckpt or .bin
-checkpoint file, `safetensors.torch.load_file()` for a safetensors
-checkpoint file, or `cls.from_pretrained()` for a directory that looks
-like a diffusers directory.
-
-### context.load_remote_model(source, [loader]) -> LoadedModel
-
-This method accepts a `source` of a remote model, downloads and caches
-it locally, loads it, and returns a `LoadedModel`. The source can be a
-direct download URL or a HuggingFace repo_id.
-
-In the case of HuggingFace repo_id, the following variants are
-recognized:
-
-* stabilityai/stable-diffusion-v4           -- default model
-* stabilityai/stable-diffusion-v4:fp16      -- fp16 variant
-* stabilityai/stable-diffusion-v4:fp16:vae  -- the fp16 vae subfolder
-* stabilityai/stable-diffusion-v4:onnx:vae  -- the onnx variant vae subfolder
-
-You can also point at an arbitrary individual file within a repo_id
-directory using this syntax:
-
-* stabilityai/stable-diffusion-v4::/checkpoints/sd4.safetensors
-
-
-

docs/contributing/contribution_guides/development.md

@@ -2,7 +2,7 @@
 
 ## **What do I need to know to help?**
 
-If you are looking to help 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. 
+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**

docs/contributing/contribution_guides/documentation.md

@@ -1,13 +1,13 @@
 # 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.
+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 our [GitHub repository](https://github.com/invoke-ai/InvokeAI). If you come across documentation that is out of date or incorrect, please submit a pull request with the necessary changes.
+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 Invoke is a tool for everyone, not just those who have familiarity with generative art.
+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 @hipsterusername on [Discord](https://discord.gg/ZmtBAhwWhy) if you have any 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

@@ -1,56 +1,47 @@
 # New Contributor Guide
 
-If you're a new contributor to InvokeAI or Open Source Projects, this is the guide for you.
+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](../dev-environment.md)
-- [x] Set up your local tooling with [this guide](../LOCAL_DEVELOPMENT.md). Feel free to skip this step if you already have tooling you're comfortable with.
+- [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] 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.
+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
-    ```
-
+```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
-    ```
-
+```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"
-    ```
-
+```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
-    ```
-
+```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!
@@ -58,20 +49,20 @@ If you're unfamiliar with using Git through the commandline, [GitHub Desktop](ht
 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).
+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
+## 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
 
-- 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 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

@@ -16,4 +16,4 @@ Please check Weblate's [documentation](https://docs.weblate.org/en/latest/index
 
 ## Thanks
 
-Thanks to the InvokeAI community for their efforts to translate the project!
+Thanks to the InvokeAI community for their efforts to translate the project!

docs/contributing/contribution_guides/tutorials.md

@@ -1,6 +1,6 @@
 # Tutorials
 
-Tutorials help new & existing users expand their ability to use InvokeAI to the full extent of our features and services.  
+Tutorials help new & existing users expand their abilty to use InvokeAI to the full extent of our features and services.  
 
 Currently, we have a set of tutorials available on our [YouTube channel](https://www.youtube.com/@invokeai), but as InvokeAI continues to evolve with new updates, we want to ensure that we are giving our users the resources they need to succeed. 
 
@@ -8,4 +8,4 @@ Tutorials can be in the form of videos or article walkthroughs on a subject of y
 
 ## Contributing
 
-Please reach out to @imic or @hipsterusername on [Discord](https://discord.gg/ZmtBAhwWhy) to help create tutorials for InvokeAI.
+Please reach out to @imic or @hipsterusername on [Discord](https://discord.gg/ZmtBAhwWhy) to help create tutorials for InvokeAI.

docs/contributing/contributors.md

@@ -1,54 +0,0 @@
----
-title: Contributors
----
-
-We thank [all contributors](https://github.com/invoke-ai/InvokeAI/graphs/contributors) for their time and hard work!
-
-## **Original Author**
-
-- [Lincoln D. Stein](mailto:lincoln.stein@gmail.com)
-
-## **Current Core Team**
-
-- @lstein (Lincoln Stein) - Co-maintainer
-- @blessedcoolant - Co-maintainer
-- @hipsterusername (Kent Keirsey) - Co-maintainer, CEO, Positive Vibes
-- @psychedelicious (Spencer Mabrito) - Web Team Leader
-- @joshistoast (Josh Corbett) - Web Development
-- @cheerio (Mary Rogers) - Lead Engineer & Web App Development
-- @ebr (Eugene Brodsky) - Cloud/DevOps/Sofware engineer; your friendly neighbourhood cluster-autoscaler
-- @sunija - Standalone version
-- @brandon (Brandon Rising) - Platform, Infrastructure, Backend Systems
-- @ryanjdick (Ryan Dick) - Machine Learning & Training
-- @JPPhoto - Core image generation nodes
-- @dunkeroni - Image generation backend
-- @SkunkWorxDark - Image generation backend
-- @glimmerleaf (Devon Hopkins) - Community Wizard
-- @gogurt enjoyer - Discord moderator and end user support
-- @whosawhatsis - Discord moderator and end user support
-- @dwringer - Discord moderator and end user support
-- @526christian - Discord moderator and end user support
-- @harvester62 - Discord moderator and end user support
-
-## **Honored Team Alumni**
-
-- @StAlKeR7779 (Sergey Borisov) - Torch stack, ONNX, model management, optimization
-- @damian0815 - Attention Systems and Compel Maintainer
-- @netsvetaev (Artur) - Localization support
-- @Kyle0654 (Kyle Schouviller) - Node Architect and General Backend Wizard
-- @tildebyte - Installation and configuration
-- @mauwii (Matthias Wilde) - Installation, release, continuous integration
-- @chainchompa (Jennifer Player) - Web Development & Chain-Chomping
-- @millu (Millun Atluri) - Community Wizard, Documentation, Node-wrangler,
-- @genomancer (Gregg Helt) - Controlnet support
-- @keturn (Kevin Turner) - Diffusers
-
-## **Original CompVis (Stable Diffusion) Authors**
-
-- [Robin Rombach](https://github.com/rromb)
-- [Patrick von Platen](https://github.com/patrickvonplaten)
-- [ablattmann](https://github.com/ablattmann)
-- [Patrick Esser](https://github.com/pesser)
-- [owenvincent](https://github.com/owenvincent)
-- [apolinario](https://github.com/apolinario)
-- [Charles Packer](https://github.com/cpacker)

docs/contributing/dev-environment.md

@@ -1,102 +0,0 @@
-# Dev Environment
-
-To make changes to Invoke's backend, frontend, or documentation, you'll need to set up a dev environment.
-
-If you just want to use Invoke, you should use the [installer][installer link].
-
-!!! info "Why do I need the frontend toolchain?"
-
-    The repo doesn't contain a build of the frontend. You'll be responsible for rebuilding it every time you pull in new changes, or run it in dev mode (which incurs a substantial performance penalty).
-
-!!! warning
-
-    Invoke uses a SQLite database. When you run the application as a dev install, you accept responsibility for your database. This means making regular backups (especially before pulling) and/or fixing it yourself in the event that a PR introduces a schema change.
-
-    If you don't need to persist your db, you can use an ephemeral in-memory database by setting `use_memory_db: true` in your `invokeai.yaml` file. You'll also want to set `scan_models_on_startup: true` so that your models are registered on startup.
-
-## Setup
-
-1. Run through the [requirements][requirements link].
-2. [Fork and clone][forking link] the [InvokeAI repo][repo link].
-3. Create an directory for user data (images, models, db, etc). This is typically at `~/invokeai`, but if you already have a non-dev install, you may want to create a separate directory for the dev install.
-4. Create a python virtual environment inside the directory you just created:
-
-      ```sh
-      python3 -m venv .venv --prompt InvokeAI-Dev
-      ```
-
-5. Activate the venv (you'll need to do this every time you want to run the app):
-
-        ```sh
-        source .venv/bin/activate
-        ```
-
-6. Install the repo as an [editable install][editable install link]:
-
-      ```sh
-      pip install -e ".[dev,test,xformers]" --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu121
-      ```
-
-      Refer to the [manual installation][manual install link]] instructions for more determining the correct install options. `xformers` is optional, but `dev` and `test` are not.
-
-7. Install the frontend dev toolchain:
-
-   - [`nodejs`](https://nodejs.org/) (recommend v20 LTS)
-   - [`pnpm`](https://pnpm.io/8.x/installation) (must be v8 - not v9!)
-
-8. Do a production build of the frontend:
-
-      ```sh
-      cd PATH_TO_INVOKEAI_REPO/invokeai/frontend/web
-      pnpm i
-      pnpm build
-      ```
-
-9. Start the application:
-
-      ```sh
-      cd PATH_TO_INVOKEAI_REPO
-      python scripts/invokeai-web.py
-      ```
-
-10. Access the UI at `localhost:9090`.
-
-## Updating the UI
-
-You'll need to run `pnpm build` every time you pull in new changes. Another option is to skip the build and instead run the app in dev mode:
-
-```sh
-pnpm dev
-```
-
-This starts a dev server at `localhost:5173`, which you will use instead of `localhost:9090`.
-
-The dev mode is substantially slower than the production build but may be more convenient if you just need to test things out.
-
-## Documentation
-
-The documentation is built with `mkdocs`. To preview it locally, you need a additional set of packages installed.
-
-```sh
-# after activating the venv
-pip install -e ".[docs]"
-```
-
-Then, you can start a live docs dev server, which will auto-refresh when you edit the docs:
-
-```sh
-mkdocs serve
-```
-
-On macOS and Linux, there is a `make` target for this:
-
-```sh
-make docs
-```
-
-[installer link]: ../installation/installer.md
-[forking link]: https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/fork-a-repo
-[requirements link]: ../installation/requirements.md
-[repo link]: https://github.com/invoke-ai/InvokeAI
-[manual install link]: ../installation/manual.md
-[editable install link]: https://pip.pypa.io/en/latest/cli/pip_install/#cmdoption-e

docs/contributing/frontend/OVERVIEW.md

@@ -4,42 +4,52 @@ Invoke's UI is made possible by many contributors and open-source libraries. Tha
 
 ## Dev environment
 
-Follow the [dev environment](../dev-environment.md) guide to get set up. Run the UI using `pnpm dev`.
+### Setup
 
-## Package scripts
+1. Install [node] and [pnpm].
+1. Run `pnpm i` to install all packages.
+
+#### Run in dev mode
+
+1. From `invokeai/frontend/web/`, run `pnpm dev`.
+1. From repo root, run `python scripts/invokeai-web.py`.
+1. Point your browser to the dev server address, e.g. <http://localhost:5173/>
+
+### Package scripts
 
 - `dev`: run the frontend in dev mode, enabling hot reloading
-- `build`: run all checks (dpdm, eslint, prettier, tsc, knip) and then build the frontend
+- `build`: run all checks (madge, eslint, prettier, tsc) and then build the frontend
+- `typegen`: generate types from the OpenAPI schema (see [Type generation])
 - `lint:dpdm`: check circular dependencies
 - `lint:eslint`: check code quality
 - `lint:prettier`: check code formatting
 - `lint:tsc`: check type issues
-- `lint:knip`: check for unused exports or objects
+- `lint:knip`: check for unused exports or objects (failures here are just suggestions, not hard fails)
 - `lint`: run all checks concurrently
 - `fix`: run `eslint` and `prettier`, fixing fixable issues
-- `test:ui`: run `vitest` with the fancy web UI
 
-## Type generation
+### Type generation
 
-We use [openapi-typescript] to generate types from the app's OpenAPI schema. The generated types are committed to the repo in [schema.ts].
+We use [openapi-typescript] to generate types from the app's OpenAPI schema.
 
-If you make backend changes, it's important to regenerate the frontend types:
+The generated types are committed to the repo in [schema.ts].
 
 ```sh
-cd invokeai/frontend/web && python ../../../scripts/generate_openapi_schema.py | pnpm typegen
+# from the repo root, start the server
+python scripts/invokeai-web.py
+# from invokeai/frontend/web/, run the script
+pnpm typegen
 ```
 
-On macOS and Linux, you can run `make frontend-typegen` as a shortcut for the above snippet.
-
-## Localization
+### Localization
 
 We use [i18next] for localization, but translation to languages other than English happens on our [Weblate] project.
 
-Only the English source strings (i.e. `en.json`) should be changed on this repo.
+Only the English source strings should be changed on this repo.
 
-## VSCode
+### VSCode
 
-### Example debugger config
+#### Example debugger config
 
 ```jsonc
 {
@@ -56,7 +66,7 @@ Only the English source strings (i.e. `en.json`) should be changed on this repo.
 }
 ```
 
-### Remote dev
+#### Remote dev
 
 We've noticed an intermittent timeout issue with the VSCode remote dev port forwarding.
 
@@ -72,7 +82,7 @@ Thanks for your interest in contributing to the Invoke Web UI!
 
 Please follow these guidelines when contributing.
 
-## Check in before investing your time
+### Check in before investing your time
 
 Please check in before you invest your time on anything besides a trivial fix, in case it conflicts with ongoing work or isn't aligned with the vision for the app.
 
@@ -80,7 +90,7 @@ If a feature request or issue doesn't already exist for the thing you want to wo
 
 Ping `@psychedelicious` on [discord] in the `#frontend-dev` channel or in the feature request / issue you want to work on - we're happy to chat.
 
-## Code conventions
+### Code conventions
 
 - This is a fairly complex app with a deep component tree. Please use memoization (`useCallback`, `useMemo`, `memo`) with enthusiasm.
 - If you need to add some global, ephemeral state, please use [nanostores] if possible.
@@ -88,7 +98,7 @@ Ping `@psychedelicious` on [discord] in the `#frontend-dev` channel or in the fe
 - Feel free to use `lodash` (via `lodash-es`) to make the intent of your code clear.
 - Please add comments describing the "why", not the "how" (unless it is really arcane).
 
-## Commit format
+### Commit format
 
 Please use the [conventional commits] spec for the web UI, with a scope of "ui":
 
@@ -97,32 +107,27 @@ Please use the [conventional commits] spec for the web UI, with a scope of "ui":
 - `feat(ui): add some cool new feature`
 - `fix(ui): fix some bug`
 
-## Tests
-
-We don't do any UI testing at this time, but consider adding tests for sensitive logic.
-
-We use `vitest`, and tests should be next to the file they are testing. If the logic is in `something.ts`, the tests should be in `something.test.ts`.
-
-In some situations, we may want to test types. For example, if you use `zod` to create a schema that should match a generated type, it's best to add a test to confirm that the types match. Use `tsafe`'s assert for this.
-
-## Submitting a PR
+### Submitting a PR
 
 - Ensure your branch is tidy. Use an interactive rebase to clean up the commit history and reword the commit messages if they are not descriptive.
 - Run `pnpm lint`. Some issues are auto-fixable with `pnpm fix`.
 - Fill out the PR form when creating the PR.
   - It doesn't need to be super detailed, but a screenshot or video is nice if you changed something visually.
-  - If a section isn't relevant, delete it.
+  - If a section isn't relevant, delete it. There are no UI tests at this time.
 
 ## Other docs
 
 - [Workflows - Design and Implementation]
 - [State Management]
 
+[node]: https://nodejs.org/en/download/
+[pnpm]: https://github.com/pnpm/pnpm
 [discord]: https://discord.gg/ZmtBAhwWhy
 [i18next]: https://github.com/i18next/react-i18next
 [Weblate]: https://hosted.weblate.org/engage/invokeai/
-[openapi-typescript]: https://github.com/openapi-ts/openapi-typescript
+[openapi-typescript]: https://github.com/drwpow/openapi-typescript
+[Type generation]: #type-generation
 [schema.ts]: https://github.com/invoke-ai/InvokeAI/blob/main/invokeai/frontend/web/src/services/api/schema.ts
 [conventional commits]: https://www.conventionalcommits.org/en/v1.0.0/
-[Workflows - Design and Implementation]: ./workflows.md
-[State Management]: ./state-management.md
+[Workflows - Design and Implementation]: ./WORKFLOWS.md
+[State Management]: ./STATE_MGMT.md

docs/contributing/frontend/STATE_MGMT.md

@@ -4,7 +4,7 @@ The app makes heavy use of Redux Toolkit, its Query library, and `nanostores`.
 
 ## Redux
 
-We use RTK extensively - slices, entity adapters, queries, reselect, the whole 9 yards. Their [docs](https://redux-toolkit.js.org/) are excellent.
+TODO
 
 ## `nanostores`
 

docs/contributing/frontend/WORKFLOWS.md

@@ -117,13 +117,13 @@ Stateless fields do not store their value in the node, so their field instances
 
 "Custom" fields will always be treated as stateless fields.
 
-##### Single and Collection Fields
+##### Collection and Scalar Fields
 
-Field types have a name and cardinality property which may identify it as a **SINGLE**, **COLLECTION** or **SINGLE_OR_COLLECTION** field.
+Field types have a name and two flags which may identify it as a **collection** or **collection or scalar** field.
 
-- If a field is annotated in python as a singular value or class, its field type is parsed as a **SINGLE** type (e.g. `int`, `ImageField`, `str`).
-- If a field is annotated in python as a list, its field type is parsed as a **COLLECTION** type (e.g. `list[int]`).
-- If it is annotated as a union of a type and list, the type will be parsed as a **SINGLE_OR_COLLECTION** type (e.g. `Union[int, list[int]]`). Fields may not be unions of different types (e.g. `Union[int, list[str]]` and `Union[int, str]` are not allowed).
+If a field is annotated in python as a list, its field type is parsed and flagged as a **collection** type (e.g. `list[int]`).
+
+If it is annotated as a union of a type and list, the type will be flagged as a **collection or scalar** type (e.g. `Union[int, list[int]]`). Fields may not be unions of different types (e.g. `Union[int, list[str]]` and `Union[int, str]` are not allowed).
 
 ## Implementation
 
@@ -173,7 +173,8 @@ Field types are represented as structured objects:
 ```ts
 type FieldType = {
   name: string;
-  cardinality: 'SINGLE' | 'COLLECTION' | 'SINGLE_OR_COLLECTION';
+  isCollection: boolean;
+  isCollectionOrScalar: boolean;
 };
 ```
 
@@ -185,7 +186,7 @@ There are 4 general cases for field type parsing.
 
 When a field is annotated as a primitive values (e.g. `int`, `str`, `float`), the field type parsing is fairly straightforward. The field is represented by a simple OpenAPI **schema object**, which has a `type` property.
 
-We create a field type name from this `type` string (e.g. `string` -> `StringField`). The cardinality is `"SINGLE"`.
+We create a field type name from this `type` string (e.g. `string` -> `StringField`).
 
 ##### Complex Types
 
@@ -199,13 +200,13 @@ We need to **dereference** the schema to pull these out. Dereferencing may requi
 
 When a field is annotated as a list of a single type, the schema object has an `items` property. They may be a schema object or reference object and must be parsed to determine the item type.
 
-We use the item type for field type name. The cardinality is `"COLLECTION"`.
+We use the item type for field type name, adding `isCollection: true` to the field type.
 
-##### Single or Collection Types
+##### Collection or Scalar Types
 
 When a field is annotated as a union of a type and list of that type, the schema object has an `anyOf` property, which holds a list of valid types for the union.
 
-After verifying that the union has two members (a type and list of the same type), we use the type for field type name, with cardinality `"SINGLE_OR_COLLECTION"`.
+After verifying that the union has two members (a type and list of the same type), we use the type for field type name, adding `isCollectionOrScalar: true` to the field type.
 
 ##### Optional Fields
 

docs/features/CONFIGURATION.md

@@ -51,11 +51,13 @@ The settings in this file will override the defaults. You only need
 to change this file if the default for a particular setting doesn't
 work for you.
 
-You'll find an example file next to `invokeai.yaml` that shows the default values.
-
 Some settings, like [Model Marketplace API Keys], require the YAML
 to be formatted correctly. Here is a [basic guide to YAML files].
 
+You can fix a broken `invokeai.yaml` by deleting it and running the
+configuration script again -- option [6] in the launcher, "Re-run the
+configure script".
+
 #### Custom Config File Location
 
 You can use any config file with the `--config` CLI arg. Pass in the path to the `invokeai.yaml` file you want to use.
@@ -90,9 +92,10 @@ Following the table are additional explanations for certain settings.
 <!-- prettier-ignore-start -->
 ::: invokeai.app.services.config.config_default.InvokeAIAppConfig
     options:
-        show_root_heading: false
+        heading_level: 4
         members: false
         show_docstring_description: false
+        group_by_category: true
         show_category_heading: false
 <!-- prettier-ignore-end -->
 
@@ -154,12 +157,12 @@ log_handlers:
   locally or to a remote logging machine. `syslog` offers a variety
   of configuration options:
 
-```yaml
-syslog=/dev/log`      - log to the /dev/log device
-syslog=localhost`     - log to the network logger running on the local machine
-syslog=localhost:512` - same as above, but using a non-standard port
-syslog=fredserver,facility=LOG_USER,socktype=SOCK_DRAM`
-- Log to LAN-connected server "fredserver" using the facility LOG_USER and datagram packets.
+```
+  syslog=/dev/log`      - log to the /dev/log device
+  syslog=localhost`     - log to the network logger running on the local machine
+  syslog=localhost:512` - same as above, but using a non-standard port
+  syslog=fredserver,facility=LOG_USER,socktype=SOCK_DRAM`
+                        - Log to LAN-connected server "fredserver" using the facility LOG_USER and datagram packets.
 ```
 
 - `http` can be used to log to a remote web server. The server must be
@@ -168,8 +171,8 @@ syslog=fredserver,facility=LOG_USER,socktype=SOCK_DRAM`
   indicating whether the message should be submitted using the GET or
   POST method.
 
-```yaml
-http=http://my.server/path/to/logger,method=POST
+```
+ http=http://my.server/path/to/logger,method=POST
 ```
 
 The `log_format` option provides several alternative formats:

docs/features/CONTROLNET.md

@@ -0,0 +1,181 @@
+---
+title: Control Adapters
+---
+
+# :material-loupe: Control Adapters
+
+## ControlNet
+
+ControlNet is a powerful set of features developed by the open-source
+community (notably, Stanford researcher
+[**@ilyasviel**](https://github.com/lllyasviel)) that allows you to
+apply a secondary neural network model to your image generation
+process in Invoke.
+
+With ControlNet, you can get more control over the output of your
+image generation, providing you with a way to direct the network
+towards generating images that better fit your desired style or
+outcome.
+
+ControlNet works by analyzing an input image, pre-processing that
+image to identify relevant information that can be interpreted by each
+specific ControlNet model, and then inserting that control information
+into the generation process. This can be used to adjust the style,
+composition, or other aspects of the image to better achieve a
+specific result.
+
+#### Installation
+
+InvokeAI provides access to a series of ControlNet models that provide
+different effects or styles in your generated images.
+
+To install ControlNet Models:
+
+1. The easiest way to install them is
+to use the InvokeAI model installer application. Use the
+`invoke.sh`/`invoke.bat` launcher to select item [4] and then navigate
+to the CONTROLNETS section. Select the models you wish to install and
+press "APPLY CHANGES". You may also enter additional HuggingFace
+repo_ids in the "Additional models" textbox. 
+2. Using the "Add Model" function of the  model manager, enter the HuggingFace Repo ID of the ControlNet. The ID is in the format "author/repoName"
+
+
+_Be aware that some ControlNet models require additional code
+functionality in order to work properly, so just installing a
+third-party ControlNet model may not have the desired effect._ Please
+read and follow the documentation for installing a third party model
+not currently included among InvokeAI's default list.
+
+Currently InvokeAI **only** supports 🤗 Diffusers-format ControlNet models. These are
+folders that contain the files `config.json` and/or
+`diffusion_pytorch_model.safetensors` and
+`diffusion_pytorch_model.fp16.safetensors`. The name of the folder is
+the name of the model.
+
+🤗 Diffusers-format ControlNet models are available at HuggingFace
+(http://huggingface.co) and accessed via their repo IDs (identifiers
+in the format "author/modelname").
+
+#### ControlNet Models
+The models currently supported include:
+
+**Canny**:
+
+When the Canny model is used in ControlNet, Invoke will attempt to generate images that match the edges detected. 
+
+Canny edge detection works by detecting the edges in an image by looking for abrupt changes in intensity. It is known for its ability to detect edges accurately while reducing noise and false edges, and the preprocessor can identify more information by decreasing the thresholds.
+
+**M-LSD**: 
+
+M-LSD is another edge detection algorithm used in ControlNet. It stands for Multi-Scale Line Segment Detector. 
+
+It detects straight line segments in an image by analyzing the local structure of the image at multiple scales.  It can be useful for architectural imagery, or anything where straight-line structural information is needed for the resulting output. 
+
+**Lineart**: 
+
+The Lineart model in ControlNet generates line drawings from an input image. The resulting pre-processed image is a simplified version of the original, with only the outlines of objects visible.The Lineart model in ControlNet is known for its ability to accurately capture the contours of the objects in an input sketch. 
+
+**Lineart Anime**: 
+
+A variant of the Lineart model that generates line drawings with a distinct style inspired by anime and manga art styles.
+
+**Depth**: 
+A model that generates depth maps of images, allowing you to create more realistic 3D models or to simulate depth effects in post-processing.
+
+**Normal Map (BAE):** 
+A model that generates normal maps from input images, allowing for more realistic lighting effects in 3D rendering.
+		
+**Image Segmentation**: 
+A model that divides input images into segments or regions, each of which corresponds to a different object or part of the image. (More details coming soon)
+
+**QR Code Monster**:
+A model that helps generate creative QR codes that still scan. Can also be used to create images with text, logos or shapes within them. 
+
+**Openpose**: 
+The OpenPose control model allows for the identification of the general pose of a character by pre-processing an existing image with a clear human structure. With advanced options, Openpose can also detect the face or hands in the image. 
+
+*Note:* The DWPose Processor has replaced the OpenPose processor in Invoke. Workflows and generations that relied on the OpenPose Processor will need to be updated to use the DWPose Processor instead.
+
+**Mediapipe Face**:
+
+The MediaPipe Face identification processor is able to clearly identify facial features in order to capture vivid expressions of human faces.
+
+**Tile**:
+
+The Tile model fills out details in the image to match the image, rather than the prompt. The Tile Model is a versatile tool that offers a range of functionalities. Its primary capabilities can be boiled down to two main behaviors:
+
+- It can reinterpret specific details within an image and create fresh, new elements.
+- It has the ability to disregard global instructions if there's a discrepancy between them and the local context or specific parts of the image. In such cases, it uses the local context to guide the process.
+
+The Tile Model can be a powerful tool in your arsenal for enhancing image quality and details. If there are undesirable elements in your images, such as blurriness caused by resizing, this model can effectively eliminate these issues, resulting in cleaner, crisper images. Moreover, it can generate and add refined details to your images, improving their overall quality and appeal. 
+
+**Pix2Pix (experimental)**
+
+With Pix2Pix, you can input an image into the controlnet, and then "instruct" the model to change it using your prompt. For example, you can say "Make it winter" to add more wintry elements to a scene.
+
+Each of these models can be adjusted and combined with other ControlNet models to achieve different results, giving you even more control over your image generation process.
+
+
+### Using ControlNet
+
+To use ControlNet, you can simply select the desired model and adjust both the ControlNet and Pre-processor settings to achieve the desired result. You can also use multiple ControlNet models at the same time, allowing you to achieve even more complex effects or styles in your generated images.
+
+
+Each ControlNet has two settings that are applied to the ControlNet.
+
+Weight - Strength of the Controlnet model applied to the generation for the section, defined by start/end.
+
+Start/End  - 0 represents the start of the generation, 1 represents the end. The Start/end setting controls what steps during the generation process have the ControlNet applied.
+
+Additionally, each ControlNet section can be expanded in order to manipulate settings for the image pre-processor that adjusts your uploaded image before using it in when you Invoke.
+
+## T2I-Adapter
+[T2I-Adapter](https://github.com/TencentARC/T2I-Adapter) is a tool similar to ControlNet that allows for control over the generation process by providing control information during the generation process. T2I-Adapter models tend to be smaller and more efficient than ControlNets. 
+
+##### Installation
+To install T2I-Adapter Models:
+
+1. The easiest way to install models is
+to use the InvokeAI model installer application. Use the
+`invoke.sh`/`invoke.bat` launcher to select item [5] and then navigate
+to the T2I-Adapters section. Select the models you wish to install and
+press "APPLY CHANGES". You may also enter additional HuggingFace
+repo_ids in the "Additional models" textbox. 
+2. Using the "Add Model" function of the  model manager, enter the HuggingFace Repo ID of the T2I-Adapter. The ID is in the format "author/repoName"
+
+#### Usage
+Each T2I Adapter has two settings that are applied.
+
+Weight - Strength of the model applied to the generation for the section, defined by start/end.
+
+Start/End  - 0 represents the start of the generation, 1 represents the end. The Start/end setting controls what steps during the generation process have the ControlNet applied.
+
+Additionally, each  section can be expanded with the "Show Advanced" button in order to manipulate settings for the image pre-processor that adjusts your uploaded image before using it in during the generation process.
+
+
+## IP-Adapter
+
+[IP-Adapter](https://ip-adapter.github.io) is a tooling that allows for image prompt capabilities with text-to-image diffusion models. IP-Adapter works by analyzing the given image prompt to extract features, then passing those features to the UNet along with any other conditioning provided. 
+
+![IP-Adapter + T2I](https://github.com/tencent-ailab/IP-Adapter/raw/main/assets/demo/ip_adpter_plus_multi.jpg)
+
+![IP-Adapter + IMG2IMG](https://raw.githubusercontent.com/tencent-ailab/IP-Adapter/main/assets/demo/image-to-image.jpg)
+
+#### Installation
+There are several ways to install IP-Adapter models with an existing InvokeAI installation:
+
+1. Through the command line interface launched from the invoke.sh / invoke.bat scripts, option [4] to download models.
+2. Through the Model Manager UI with models from the *Tools* section of [www.models.invoke.ai](https://www.models.invoke.ai). To do this, copy the repo ID from the desired model page, and paste it in the Add Model field of the model manager. **Note** Both the IP-Adapter and the Image Encoder must be installed for IP-Adapter to work. For example, the [SD 1.5 IP-Adapter](https://models.invoke.ai/InvokeAI/ip_adapter_plus_sd15) and [SD1.5 Image Encoder](https://models.invoke.ai/InvokeAI/ip_adapter_sd_image_encoder) must be installed to use IP-Adapter with SD1.5 based models.  
+3. **Advanced -- Not recommended ** Manually downloading the IP-Adapter and Image Encoder files - Image Encoder folders shouid be placed in the `models\any\clip_vision` folders. IP Adapter Model folders should be placed in the relevant `ip-adapter` folder of relevant base model folder of Invoke root directory. For example, for the SDXL IP-Adapter, files should be added to the `model/sdxl/ip_adapter/` folder. 
+
+#### Using IP-Adapter
+
+IP-Adapter can be used by navigating to the *Control Adapters* options and enabling IP-Adapter. 
+
+IP-Adapter requires an image to be used as the Image Prompt. It can also be used in conjunction with text prompts, Image-to-Image, Inpainting, Outpainting, ControlNets and LoRAs.
+
+
+Each IP-Adapter has two settings that are applied to the IP-Adapter:
+
+* Weight - Strength of the IP-Adapter model applied to the generation for the section, defined by start/end
+* Start/End  - 0 represents the start of the generation, 1 represents the end. The Start/end setting controls what steps during the generation process have the IP-Adapter applied.

docs/features/DATABASE.md

@@ -2,11 +2,13 @@
 title: Database
 ---
 
+# Invoke's SQLite Database
+
 Invoke uses a SQLite database to store image, workflow, model, and execution data.
 
 We take great care to ensure your data is safe, by utilizing transactions and a database migration system.
 
-Even so, when testing a prerelease version of the app, we strongly suggest either backing up your database or using an in-memory database. This ensures any prelease hiccups or databases schema changes will not cause problems for your data.
+Even so, when testing an prerelease version of the app, we strongly suggest either backing up your database or using an in-memory database. This ensures any prelease hiccups or databases schema changes will not cause problems for your data.
 
 ## Database Backup
 
@@ -22,10 +24,12 @@ SQLite can run on an in-memory database. Your existing database is untouched whe
 
 This is very useful for testing, as there is no chance of a database change modifying your "physical" database.
 
-To run Invoke with a memory database, edit your `invokeai.yaml` file and add `use_memory_db: true`:
+To run Invoke with a memory database, edit your `invokeai.yaml` file, and add `use_memory_db: true` to the `Paths:` stanza:
 
 ```yaml
-use_memory_db: true
+InvokeAI:
+  Development:
+    use_memory_db: true
 ```
 
 Delete this line (or set it to `false`) to use your main database.

docs/features/IMG2IMG.md

@@ -0,0 +1,151 @@
+---
+title: Image-to-Image
+---
+
+# :material-image-multiple: Image-to-Image
+
+InvokeAI provides an "img2img" feature that lets you seed your
+creations with an initial drawing or photo. This is a really cool
+feature that tells stable diffusion to build the prompt on top of the
+image you provide, preserving the original's basic shape and layout.
+
+For a walkthrough of using Image-to-Image in the Web UI, see [InvokeAI
+Web Server](./WEB.md#image-to-image).
+
+The main difference between `img2img` and `prompt2img` is the starting point.
+While `prompt2img` always starts with pure gaussian noise and progressively
+refines it over the requested number of steps, `img2img` skips some of these
+earlier steps (how many it skips is indirectly controlled by the `--strength`
+parameter), and uses instead your initial image mixed with gaussian noise as the
+starting image.
+
+**Let's start** by thinking about vanilla `prompt2img`, just generating an image
+from a prompt. If the step count is 10, then the "latent space" (Stable
+Diffusion's internal representation of the image) for the prompt "fire" with
+seed `1592514025` develops something like this:
+
+!!! example ""
+
+    <figure markdown>
+    ![latent steps](../assets/img2img/000019.steps.png){ width=720 }
+    </figure>
+
+Put simply: starting from a frame of fuzz/static, SD finds details in each frame
+that it thinks look like "fire" and brings them a little bit more into focus,
+gradually scrubbing out the fuzz until a clear image remains.
+
+**When you use `img2img`** some of the earlier steps are cut, and instead an
+initial image of your choice is used. But because of how the maths behind Stable
+Diffusion works, this image needs to be mixed with just the right amount of
+noise (fuzz/static) for where it is being inserted. This is where the strength
+parameter comes in. Depending on the set strength, your image will be inserted
+into the sequence at the appropriate point, with just the right amount of noise.
+
+### A concrete example
+
+!!! example "I want SD to draw a fire based on this hand-drawn image"
+
+    ![drawing of a fireplace](../assets/img2img/fire-drawing.png){ align=left }
+
+    Let's only do 10 steps, to make it easier to see what's happening. If strength
+    is `0.7`, this is what the internal steps the algorithm has to take will look
+    like:
+
+    <figure markdown>
+    ![gravity32](../assets/img2img/000032.steps.gravity.png)
+    </figure>
+
+    With strength `0.4`, the steps look more like this:
+
+    <figure markdown>
+    ![gravity30](../assets/img2img/000030.steps.gravity.png)
+    </figure>
+
+Notice how much more fuzzy the starting image is for strength `0.7` compared to
+`0.4`, and notice also how much longer the sequence is with `0.7`:
+
+|                             | strength = 0.7                                                | strength = 0.4                                                |
+| --------------------------- | ------------------------------------------------------------- | ------------------------------------------------------------- |
+| initial image that SD sees  | ![step-0](../assets/img2img/000032.step-0.png)                | ![step-0](../assets/img2img/000030.step-0.png)                |
+| steps argument to `invoke>` | `-S10`                                                        | `-S10`                                                        |
+| steps actually taken        | `7`                                                           | `4`                                                           |
+| latent space at each step   | ![gravity32](../assets/img2img/000032.steps.gravity.png)      | ![gravity30](../assets/img2img/000030.steps.gravity.png)      |
+| output                      | ![000032.1592514025](../assets/img2img/000032.1592514025.png) | ![000030.1592514025](../assets/img2img/000030.1592514025.png) |
+
+Both of the outputs look kind of like what I was thinking of. With the strength
+higher, my input becomes more vague, _and_ Stable Diffusion has more steps to
+refine its output. But it's not really making what I want, which is a picture of
+cheery open fire. With the strength lower, my input is more clear, _but_ Stable
+Diffusion has less chance to refine itself, so the result ends up inheriting all
+the problems of my bad drawing.
+
+If you want to try this out yourself, all of these are using a seed of
+`1592514025` with a width/height of `384`, step count `10`, the
+`k_lms` sampler, and the single-word prompt `"fire"`.
+
+### Compensating for the reduced step count
+
+After putting this guide together I was curious to see how the difference would
+be if I increased the step count to compensate, so that SD could have the same
+amount of steps to develop the image regardless of the strength. So I ran the
+generation again using the same seed, but this time adapting the step count to
+give each generation 20 steps.
+
+Here's strength `0.4` (note step count `50`, which is `20 ÷ 0.4` to make sure SD
+does `20` steps from my image):
+
+<figure markdown>
+![000035.1592514025](../assets/img2img/000035.1592514025.png)
+</figure>
+
+and here is strength `0.7` (note step count `30`, which is roughly `20 ÷ 0.7` to
+make sure SD does `20` steps from my image):
+
+<figure markdown>
+![000046.1592514025](../assets/img2img/000046.1592514025.png)
+</figure>
+
+In both cases the image is nice and clean and "finished", but because at
+strength `0.7` Stable Diffusion has been give so much more freedom to improve on
+my badly-drawn flames, they've come out looking much better. You can really see
+the difference when looking at the latent steps. There's more noise on the first
+image with strength `0.7`:
+
+<figure markdown>
+![gravity46](../assets/img2img/000046.steps.gravity.png)
+</figure>
+
+than there is for strength `0.4`:
+
+<figure markdown>
+![gravity35](../assets/img2img/000035.steps.gravity.png)
+</figure>
+
+and that extra noise gives the algorithm more choices when it is evaluating how
+to denoise any particular pixel in the image.
+
+Unfortunately, it seems that `img2img` is very sensitive to the step count.
+Here's strength `0.7` with a step count of `29` (SD did 19 steps from my image):
+
+<figure markdown>
+![gravity45](../assets/img2img/000045.1592514025.png)
+</figure>
+
+By comparing the latents we can sort of see that something got interpreted
+differently enough on the third or fourth step to lead to a rather different
+interpretation of the flames.
+
+<figure markdown>
+![gravity46](../assets/img2img/000046.steps.gravity.png)
+</figure>
+
+<figure markdown>
+![gravity45](../assets/img2img/000045.steps.gravity.png)
+</figure>
+
+This is the result of a difference in the de-noising "schedule" - basically the
+noise has to be cleaned by a certain degree each step or the model won't
+"converge" on the image properly (see
+[stable diffusion blog](https://huggingface.co/blog/stable_diffusion) for more
+about that). A different step count means a different schedule, which means
+things get interpreted slightly differently at every step.

docs/features/LOGGING.md

@@ -0,0 +1,171 @@
+---
+title: Controlling Logging
+---
+
+# :material-image-off: Controlling Logging
+
+## Controlling How InvokeAI Logs Status Messages
+
+InvokeAI logs status messages using a configurable logging system. You
+can log to the terminal window, to a designated file on the local
+machine, to the syslog facility on a Linux or Mac, or to a properly
+configured web server. You can configure several logs at the same
+time, and control the level of message logged and the logging format
+(to a limited extent).
+
+Three command-line options control logging:
+
+### `--log_handlers <handler1> <handler2> ...`
+
+This option activates one or more log handlers. Options are "console",
+"file", "syslog" and "http". To specify more than one, separate them
+by spaces:
+
+```bash
+invokeai-web --log_handlers console syslog=/dev/log file=C:\Users\fred\invokeai.log
+```
+
+The format of these options is described below.
+
+### `--log_format {plain|color|legacy|syslog}`
+
+This controls the format of log messages written to the console. Only
+the "console" log handler is currently affected by this setting.
+
+* "plain" provides formatted messages like this:
+
+```bash
+
+[2023-05-24 23:18:2[2023-05-24 23:18:50,352]::[InvokeAI]::DEBUG --> this is a debug message
+[2023-05-24 23:18:50,352]::[InvokeAI]::INFO --> this is an informational messages
+[2023-05-24 23:18:50,352]::[InvokeAI]::WARNING --> this is a warning
+[2023-05-24 23:18:50,352]::[InvokeAI]::ERROR --> this is an error
+[2023-05-24 23:18:50,352]::[InvokeAI]::CRITICAL --> this is a critical error
+```
+
+* "color" produces similar output, but the text will be color coded to
+indicate the severity of the message.
+
+* "legacy" produces output similar to InvokeAI versions 2.3 and earlier:
+
+```bash
+### this is a critical error
+*** this is an error
+** this is a warning
+>> this is an informational messages
+   | this is a debug message
+```
+
+* "syslog" produces messages suitable for syslog entries:
+
+```bash
+InvokeAI [2691178] <CRITICAL> this is a critical error
+InvokeAI [2691178] <ERROR> this is an error
+InvokeAI [2691178] <WARNING> this is a warning
+InvokeAI [2691178] <INFO> this is an informational messages
+InvokeAI [2691178] <DEBUG> this is a debug message
+```
+
+(note that the date, time and hostname will be added by the syslog
+system)
+
+### `--log_level {debug|info|warning|error|critical}`
+
+Providing this command-line option will cause only messages at the
+specified level or above to be emitted.
+
+## Console logging
+
+When "console" is provided to `--log_handlers`, messages will be
+written to the command line window in which InvokeAI was launched. By
+default, the color formatter will be used unless overridden by
+`--log_format`.
+
+## File logging
+
+When "file" is provided to `--log_handlers`, entries will be written
+to the file indicated in the path argument. By default, the "plain"
+format will be used:
+
+```bash
+invokeai-web --log_handlers file=/var/log/invokeai.log
+```
+
+## Syslog logging
+
+When "syslog" is requested, entries will be sent to the syslog
+system. There are a variety of ways to control where the log message
+is sent:
+
+* Send to the local machine using the `/dev/log` socket:
+
+```
+invokeai-web --log_handlers syslog=/dev/log
+```
+
+* Send to the local machine using a UDP message:
+
+```
+invokeai-web --log_handlers syslog=localhost
+```
+
+* Send to the local machine using a UDP message on a nonstandard
+  port:
+
+```
+invokeai-web --log_handlers syslog=localhost:512
+```
+
+* Send to a remote machine named "loghost" on the local LAN using
+  facility LOG_USER and UDP packets:
+
+```
+invokeai-web --log_handlers syslog=loghost,facility=LOG_USER,socktype=SOCK_DGRAM
+```
+
+This can be abbreviated `syslog=loghost`, as LOG_USER and SOCK_DGRAM
+are defaults.
+
+* Send to a remote machine named "loghost" using the facility LOCAL0
+  and using a TCP socket:
+
+```
+invokeai-web --log_handlers syslog=loghost,facility=LOG_LOCAL0,socktype=SOCK_STREAM
+```
+
+If no arguments are specified (just a bare "syslog"), then the logging
+system will look for a UNIX socket named `/dev/log`, and if not found
+try to send a UDP message to `localhost`. The Macintosh OS used to
+support logging to a socket named `/var/run/syslog`, but this feature
+has since been disabled.
+
+## Web logging
+
+If you have access to a web server that is configured to log messages
+when a particular URL is requested, you can log using the "http"
+method:
+
+```
+invokeai-web --log_handlers http=http://my.server/path/to/logger,method=POST
+```
+
+The optional [,method=] part can be used to specify whether the URL
+accepts GET (default) or POST messages.
+
+Currently password authentication and SSL are not supported.
+
+## Using the configuration file
+
+You can set and forget logging options by adding a "Logging" section
+to `invokeai.yaml`:
+
+```
+InvokeAI:
+  [... other settings...]
+  Logging:
+    log_handlers:
+       - console
+       - syslog=/dev/log
+    log_level: info
+    log_format: color
+```

docs/features/LORAS.md

@@ -0,0 +1,50 @@
+---
+title: LoRAs & LCM-LoRAs
+---
+
+# :material-library-shelves: LoRAs & LCM-LoRAs
+
+With the advances in research, many new capabilities are available to customize the knowledge and understanding of novel concepts not originally contained in the base model. 
+
+## LoRAs
+
+Low-Rank Adaptation (LoRA) files are models that customize the output of Stable Diffusion
+image generation.  Larger than embeddings, but much smaller than full
+models, they augment SD with improved understanding of subjects and
+artistic styles.
+
+Unlike TI files, LoRAs do not introduce novel vocabulary into the
+model's known tokens. Instead, LoRAs augment the model's weights that
+are applied to generate imagery. LoRAs may be supplied with a
+"trigger" word that they have been explicitly trained on, or may
+simply apply their effect without being triggered.
+
+LoRAs are typically stored in .safetensors files, which are the most
+secure way to store and transmit these types of weights.
+
+To use these when generating, open the LoRA menu item in the options
+panel, select the LoRAs you want to apply and ensure that they have
+the appropriate weight recommended by the model provider. Typically,
+most LoRAs perform best at a weight of .75-1.
+
+
+## LCM-LoRAs
+Latent Consistency Models (LCMs) allowed a reduced number of steps to be used to generate images with Stable Diffusion. These are created by distilling base models, creating models that only require a small number of steps to generate images. However, LCMs require that any fine-tune of a base model be distilled to be used as an LCM. 
+
+LCM-LoRAs are models that provide the benefit of LCMs but are able to be used as LoRAs and applied to any fine tune of a base model. LCM-LoRAs are created by training a small number of adapters, rather than distilling the entire fine-tuned base model. The resulting LoRA can be used the same way as a standard LoRA, but with a greatly reduced step count. This enables SDXL images to be generated up to 10x faster than without the use of LCM-LoRAs. 
+
+
+**Using LCM-LoRAs**
+
+LCM-LoRAs are natively supported in InvokeAI throughout the application. To get started, install any diffusers format LCM-LoRAs using the model manager and select it in the LoRA field.
+
+There are a number parameter differences when using LCM-LoRAs and standard generation: 
+
+- When using LCM-LoRAs, the LoRA strength should be lower than if using a standard LoRA, with 0.35 recommended as a starting point.  
+- The LCM scheduler should be used for generation
+- CFG-Scale should be reduced to ~1
+- Steps should be reduced in the range of 4-8
+
+Standard LoRAs can also be used alongside LCM-LoRAs, but will also require a lower strength, with 0.45 being recommended as a starting point. 
+
+More information can be found here: https://huggingface.co/blog/lcm_lora#fast-inference-with-sdxl-lcm-loras

docs/features/MODEL_MERGING.md

@@ -0,0 +1,77 @@
+---
+title: Model Merging
+---
+
+InvokeAI provides the ability to merge two or three diffusers-type models into a new merged model. The
+resulting model will combine characteristics of the original, and can
+be used to teach an old model new tricks.
+
+## How to Merge Models
+
+Model Merging can be be done by navigating to the Model Manager and clicking the "Merge Models" tab. From there, you can select the models and settings you want to use to merge th models. 
+
+## Settings
+
+* Model Selection: there are three multiple choice fields that
+  display all the diffusers-style models that InvokeAI knows about.
+  If you do not see the model you are looking for, then it is probably
+  a legacy checkpoint model and needs to be converted using the
+  "Convert" option in the Web-based Model Manager tab.
+  
+  You must select at least two models to merge. The third can be left
+  at "None" if you desire.
+
+* Alpha: This is the ratio to use when combining models. It ranges
+  from 0 to 1. The higher the value, the more weight is given to the
+  2d and (optionally) 3d models. So if you have two models named "A"
+  and "B", an alpha value of 0.25 will give you a merged model that is
+  25% A and 75% B.
+
+* Interpolation Method: This is the method used to combine
+  weights. The options are "weighted_sum" (the default), "sigmoid",
+  "inv_sigmoid" and "add_difference". Each produces slightly different
+  results. When three models are in use, only "add_difference" is
+  available.
+
+* Save Location: The location you want the merged model to be saved in. Default is in the InvokeAI root folder
+
+* Name for merged model: This is the name for the new model. Please
+  use InvokeAI conventions - only alphanumeric letters and the
+  characters ".+-".
+
+* Ignore Mismatches / Force: Not all models are compatible with each other. The merge
+  script will check for compatibility and refuse to merge ones that
+  are incompatible. Set this checkbox to try merging anyway.
+
+
+
+You may run the merge script by starting the invoke launcher
+(`invoke.sh` or `invoke.bat`) and choosing the option (4) for _merge
+models_. This will launch a text-based interactive user interface that
+prompts you to select the models to merge, how to merge them, and the
+merged model name.
+
+Alternatively you may activate InvokeAI's virtual environment from the
+command line, and call the script via `merge_models --gui` to open up
+a version that has a nice graphical front end. To get the commandline-
+only version, omit `--gui`.
+
+The user interface for the text-based interactive script is
+straightforward. It shows you a series of setting fields. Use control-N (^N)
+to move to the next field, and control-P (^P) to move to the previous
+one. You can also use TAB and shift-TAB to move forward and
+backward. Once you are in a multiple choice field, use the up and down
+cursor arrows to move to your desired selection, and press <SPACE> or
+<ENTER> to select it. Change text fields by typing in them, and adjust
+scrollbars using the left and right arrow keys.
+
+Once you are happy with your settings, press the OK button. Note that
+there may be two pages of settings, depending on the height of your
+screen, and the OK button may be on the second page. Advance past the
+last field of the first page to get to the second page, and reverse
+this to get back.
+
+If the merge runs successfully, it will create a new diffusers model
+under the selected name and register it with InvokeAI.
+
+

docs/features/OTHER.md

@@ -0,0 +1,51 @@
+---
+title: Others
+---
+
+# :fontawesome-regular-share-from-square: Others
+
+## **Google Colab**
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg){ align="right" }](https://colab.research.google.com/github/lstein/stable-diffusion/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb)
+
+Open and follow instructions to use an isolated environment running Dream.
+
+Output Example:
+
+![Colab Notebook](../assets/colab_notebook.png)
+
+---
+
+## **Invisible Watermark**
+
+In keeping with the principles for responsible AI generation, and to
+help AI researchers avoid synthetic images contaminating their
+training sets, InvokeAI adds an invisible watermark to each of the
+final images it generates. The watermark consists of the text
+"InvokeAI" and can be viewed using the
+[invisible-watermarks](https://github.com/ShieldMnt/invisible-watermark)
+tool.
+
+Watermarking is controlled using the `invisible-watermark` setting in
+`invokeai.yaml`. To turn it off, add the following line under the `Features`
+category.
+
+```
+invisible_watermark: false
+```
+
+
+## **Weighted Prompts**
+
+You may weight different sections of the prompt to tell the sampler to attach different levels of
+priority to them, by adding `:<percent>` to the end of the section you wish to up- or downweight. For
+example consider this prompt:
+
+```bash
+(tabby cat):0.25 (white duck):0.75 hybrid
+```
+
+This will tell the sampler to invest 25% of its effort on the tabby cat aspect of the image and 75%
+on the white duck aspect (surprisingly, this example actually works). The prompt weights can use any
+combination of integers and floating point numbers, and they do not need to add up to 1.
+

docs/features/POSTPROCESS.md

@@ -0,0 +1,41 @@
+---
+title: Postprocessing
+---
+
+# :material-image-edit: Postprocessing
+
+This sections details the ability to improve faces and upscale images.
+
+## Face Fixing
+
+As of InvokeAI 3.0, the easiest way to improve faces created during image generation is through the Inpainting functionality of the Unified Canvas. Simply add the image containing the faces that you would like to improve to the canvas, mask the face to be improved and run the invocation. For best results, make sure to use an inpainting specific model; these are usually identified by the "-inpainting" term in the model name. 
+
+## Upscaling
+
+Open the upscaling dialog by clicking on the "expand" icon located
+above the image display area in the Web UI:
+
+<figure markdown>
+![upscale1](../assets/features/upscale-dialog.png)
+</figure>
+
+The default upscaling option is Real-ESRGAN x2 Plus, which will scale your image by a factor of two. This means upscaling a 512x512 image will result in a new 1024x1024 image.
+
+Other options are the x4 upscalers, which will scale your image by a factor of 4. 
+
+
+!!! note
+
+    Real-ESRGAN is memory intensive. In order to avoid crashes and memory overloads
+    during the Stable Diffusion process, these effects are applied after Stable Diffusion has completed
+    its work.
+
+    In single image generations, you will see the output right away but when you are using multiple
+    iterations, the images will first be generated and then upscaled after that
+    process is complete. While the image generation is taking place, you will still be able to preview
+    the base images.
+
+## How to disable
+
+If, for some reason, you do not wish to load the ESRGAN libraries,
+you can disable them on the invoke.py command line with the `--no_esrgan` options.

docs/features/PROMPTS.md

@@ -0,0 +1,308 @@
+---
+title: Prompting-Features
+---
+
+# :octicons-command-palette-24: Prompting-Features
+
+## **Prompt Syntax Features**
+
+The InvokeAI prompting language has the following features:
+
+### Attention weighting
+
+Append a word or phrase with `-` or `+`, or a weight between `0` and `2`
+(`1`=default), to decrease or increase "attention" (= a mix of per-token CFG
+weighting multiplier and, for `-`, a weighted blend with the prompt without the
+term).
+
+The following syntax is recognised:
+
+- single words without parentheses: `a tall thin man picking apricots+`
+- single or multiple words with parentheses:
+  `a tall thin man picking (apricots)+` `a tall thin man picking (apricots)-`
+  `a tall thin man (picking apricots)+` `a tall thin man (picking apricots)-`
+- more effect with more symbols `a tall thin man (picking apricots)++`
+- nesting `a tall thin man (picking apricots+)++` (`apricots` effectively gets
+  `+++`)
+- all of the above with explicit numbers `a tall thin man picking (apricots)1.1`
+  `a tall thin man (picking (apricots)1.3)1.1`. (`+` is equivalent to 1.1, `++`
+  is pow(1.1,2), `+++` is pow(1.1,3), etc; `-` means 0.9, `--` means pow(0.9,2),
+  etc.)
+
+You can use this to increase or decrease the amount of something. Starting from
+this prompt of `a man picking apricots from a tree`, let's see what happens if
+we increase and decrease how much attention we want Stable Diffusion to pay to
+the word `apricots`:
+
+<figure markdown>
+
+![an AI generated image of a man picking apricots from a tree](../assets/prompt_syntax/apricots-0.png)
+
+</figure>
+
+Using `-` to reduce apricot-ness:
+
+| `a man picking apricots- from a tree`                                                                                          | `a man picking apricots-- from a tree`                                                                                                        | `a man picking apricots--- from a tree`                                                                                                    |
+| ------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
+| ![an AI generated image of a man picking apricots from a tree, with smaller apricots](../assets/prompt_syntax/apricots--1.png) | ![an AI generated image of a man picking apricots from a tree, with even smaller and fewer apricots](../assets/prompt_syntax/apricots--2.png) | ![an AI generated image of a man picking apricots from a tree, with very few very small apricots](../assets/prompt_syntax/apricots--3.png) |
+
+Using `+` to increase apricot-ness:
+
+| `a man picking apricots+ from a tree`                                                                                                      | `a man picking apricots++ from a tree`                                                                                                              | `a man picking apricots+++ from a tree`                                                                                                                     | `a man picking apricots++++ from a tree`                                                                                                                                           | `a man picking apricots+++++ from a tree`                                                                                                                                                                           |
+| ------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| ![an AI generated image of a man picking apricots from a tree, with larger, more vibrant apricots](../assets/prompt_syntax/apricots-1.png) | ![an AI generated image of a man picking apricots from a tree with even larger, even more vibrant apricots](../assets/prompt_syntax/apricots-2.png) | ![an AI generated image of a man picking apricots from a tree, but the man has been replaced by a pile of apricots](../assets/prompt_syntax/apricots-3.png) | ![an AI generated image of a man picking apricots from a tree, but the man has been replaced by a mound of giant melting-looking apricots](../assets/prompt_syntax/apricots-4.png) | ![an AI generated image of a man picking apricots from a tree, but the man and the leaves and parts of the ground have all been replaced by giant melting-looking apricots](../assets/prompt_syntax/apricots-5.png) |
+
+You can also change the balance between different parts of a prompt. For
+example, below is a `mountain man`:
+
+<figure markdown>
+
+![an AI generated image of a mountain man](../assets/prompt_syntax/mountain-man.png)
+
+</figure>
+
+And here he is with more mountain:
+
+| `mountain+ man`                                | `mountain++ man`                               | `mountain+++ man`                              |
+| ---------------------------------------------- | ---------------------------------------------- | ---------------------------------------------- |
+| ![](../assets/prompt_syntax/mountain1-man.png) | ![](../assets/prompt_syntax/mountain2-man.png) | ![](../assets/prompt_syntax/mountain3-man.png) |
+
+Or, alternatively, with more man:
+
+| `mountain man+`                                | `mountain man++`                               | `mountain man+++`                              | `mountain man++++`                             |
+| ---------------------------------------------- | ---------------------------------------------- | ---------------------------------------------- | ---------------------------------------------- |
+| ![](../assets/prompt_syntax/mountain-man1.png) | ![](../assets/prompt_syntax/mountain-man2.png) | ![](../assets/prompt_syntax/mountain-man3.png) | ![](../assets/prompt_syntax/mountain-man4.png) |
+
+### Prompt Blending
+
+- `("a tall thin man picking apricots", "a tall thin man picking pears").blend(1,1)`
+- The existing prompt blending using `:<weight>` will continue to be supported -
+  `("a tall thin man picking apricots", "a tall thin man picking pears").blend(1,1)`
+  is equivalent to
+  `a tall thin man picking apricots:1 a tall thin man picking pears:1` in the
+  old syntax.
+- Attention weights can be nested inside blends.
+- Non-normalized blends are supported by passing `no_normalize` as an additional
+  argument to the blend weights, eg
+  `("a tall thin man picking apricots", "a tall thin man picking pears").blend(1,-1,no_normalize)`.
+  very fun to explore local maxima in the feature space, but also easy to
+  produce garbage output.
+
+See the section below on "Prompt Blending" for more information about how this
+works.
+
+### Prompt Conjunction  
+Join multiple clauses together to create a conjoined prompt. Each clause will be passed to CLIP separately. 
+
+For example, the prompt: 
+
+```bash
+"A mystical valley surround by towering granite cliffs, watercolor, warm"
+```
+
+Can be used with .and():
+```bash
+("A mystical valley", "surround by towering granite cliffs", "watercolor", "warm").and()
+```
+
+Each will give you different results - try them out and see what you prefer!
+
+
+
+### Cross-Attention Control ('prompt2prompt')
+
+Sometimes an image you generate is almost right, and you just want to change one
+detail without affecting the rest. You could use a photo editor and inpainting
+to overpaint the area, but that's a pain. Here's where `prompt2prompt` comes in
+handy.
+
+Generate an image with a given prompt, record the seed of the image, and then
+use the `prompt2prompt` syntax to substitute words in the original prompt for
+words in a new prompt. This works for `img2img` as well.
+
+For example, consider the prompt `a cat.swap(dog) playing with a ball in the forest`. Normally, because the words interact with each other when doing a stable diffusion image generation, these two prompts would generate different compositions:
+  - `a cat playing with a ball in the forest`
+  - `a dog playing with a ball in the forest`
+
+| `a cat playing with a ball in the forest` | `a dog playing with a ball in the forest` |
+| --- | --- |
+| img | img |
+
+
+      - For multiple word swaps, use parentheses: `a (fluffy cat).swap(barking dog) playing with a ball in the forest`.
+      - To swap a comma, use quotes: `a ("fluffy, grey cat").swap("big, barking dog") playing with a ball in the forest`.
+- Supports options `t_start` and `t_end` (each 0-1) loosely corresponding to (bloc97's)[(https://github.com/bloc97/CrossAttentionControl)] `prompt_edit_tokens_start/_end` but with the math swapped to make it easier to
+  intuitively understand. `t_start` and `t_end` are used to control on which steps cross-attention control should run. With the default values `t_start=0` and `t_end=1`, cross-attention control is active on every step of image generation. Other values can be used to turn cross-attention control off for part of the image generation process.
+    - For example, if doing a diffusion with 10 steps for the prompt is `a cat.swap(dog, t_start=0.3, t_end=1.0) playing with a ball in the forest`, the first 3 steps will be run as `a cat playing with a ball in the forest`, while the last 7 steps will run as `a dog playing with a ball in the forest`, but the pixels that represent `dog` will be locked to the pixels that would have represented `cat` if the `cat` prompt had been used instead.
+    - Conversely, for `a cat.swap(dog, t_start=0, t_end=0.7) playing with a ball in the forest`, the first 7 steps will run as `a dog playing with a ball in the forest` with the pixels that represent `dog` locked to the same pixels that would have represented `cat` if the `cat` prompt was being used instead. The final 3 steps will just run `a cat playing with a ball in the forest`.
+    > For img2img, the step sequence does not start at 0 but instead at `(1.0-strength)` - so if the img2img `strength` is `0.7`, `t_start` and `t_end` must both be greater than `0.3` (`1.0-0.7`) to have any effect.
+
+Prompt2prompt `.swap()` is not compatible with xformers, which will be temporarily disabled when doing a `.swap()` - so you should expect to use more VRAM and run slower that with xformers enabled.
+
+The `prompt2prompt` code is based off
+[bloc97's colab](https://github.com/bloc97/CrossAttentionControl).
+
+### Escaping parentheses and speech marks 
+
+If the model you are using has parentheses () or speech marks "" as part of its
+syntax, you will need to "escape" these using a backslash, so that`(my_keyword)`
+becomes `\(my_keyword\)`. Otherwise, the prompt parser will attempt to interpret
+the parentheses as part of the prompt syntax and it will get confused.
+
+---
+
+## **Prompt Blending**
+
+You may blend together prompts to explore the AI's
+latent semantic space and generate interesting (and often surprising!)
+variations. The syntax is:
+
+```bash
+("prompt #1", "prompt #2").blend(0.25, 0.75)
+```
+
+This will tell the sampler to blend 25% of the concept of prompt #1 with 75%
+of the concept of prompt #2. It is recommended to keep the sum of the weights to around 1.0, but interesting things might happen if you go outside of this range.
+
+Because you are exploring the "mind" of the AI, the AI's way of mixing two
+concepts may not match yours, leading to surprising effects. To illustrate, here
+are three images generated using various combinations of blend weights. As
+usual, unless you fix the seed, the prompts will give you different results each
+time you run them.
+
+Let's examine how this affects image generation results:
+
+
+```bash
+"blue sphere, red cube, hybrid"
+```
+
+This example doesn't use blending at all and represents the default way of mixing
+concepts.
+
+<figure markdown>
+
+![blue-sphere-red-cube-hyprid](../assets/prompt-blending/blue-sphere-red-cube-hybrid.png)
+
+</figure>
+
+It's interesting to see how the AI expressed the concept of "cube" within the sphere. If you look closely, there is depth there, so the enclosing frame is actually a cube.
+
+<figure markdown>
+
+```bash
+("blue sphere", "red cube").blend(0.25, 0.75)
+```
+
+![blue-sphere-25-red-cube-75](../assets/prompt-blending/blue-sphere-0.25-red-cube-0.75-hybrid.png)
+
+</figure>
+
+Now that's interesting. We get an image with a resemblance of a red cube, with a hint of blue shadows which represents a melding of concepts within the AI's "latent space" of semantic representations. 
+
+<figure markdown>
+
+```bash
+("blue sphere", "red cube").blend(0.75, 0.25)
+```
+
+![blue-sphere-75-red-cube-25](../assets/prompt-blending/blue-sphere-0.75-red-cube-0.25-hybrid.png)
+
+</figure>
+
+Definitely more blue-spherey. 
+
+<figure markdown>
+
+```bash
+("blue sphere", "red cube").blend(0.5, 0.5)
+```
+</figure>
+
+<figure markdown>
+![blue-sphere-5-red-cube-5-hybrid](../assets/prompt-blending/blue-sphere-0.5-red-cube-0.5-hybrid.png)
+</figure>
+
+
+Whoa...! I see blue and red, and if I squint, spheres and cubes.
+
+
+
+## Dynamic Prompts
+
+Dynamic Prompts are a powerful feature designed to produce a variety of prompts based on user-defined options. Using a special syntax, you can construct a prompt with multiple possibilities, and the system will automatically generate a series of permutations based on your settings. This is extremely beneficial for ideation, exploring various scenarios, or testing different concepts swiftly and efficiently.
+
+### Structure of a Dynamic Prompt
+
+A Dynamic Prompt comprises of regular text, supplemented with alternatives enclosed within curly braces {} and separated by a vertical bar |. For example: {option1|option2|option3}. The system will then select one of the options to include in the final prompt. This flexible system allows for options to be placed throughout the text as needed.
+
+Furthermore, Dynamic Prompts can designate multiple selections from a single group of options. This feature is triggered by prefixing the options with a numerical value followed by $$. For example, in {2$$option1|option2|option3}, the system will select two distinct options from the set.
+### Creating Dynamic Prompts
+
+To create a Dynamic Prompt, follow these steps:
+
+    Draft your sentence or phrase, identifying words or phrases with multiple possible options.
+    Encapsulate the different options within curly braces {}.
+    Within the braces, separate each option using a vertical bar |.
+    If you want to include multiple options from a single group, prefix with the desired number and $$.
+
+For instance: A {house|apartment|lodge|cottage} in {summer|winter|autumn|spring} designed in {style1|style2|style3}.
+### How Dynamic Prompts Work
+
+Once a Dynamic Prompt is configured, the system generates an array of combinations using the options provided. Each group of options in curly braces is treated independently, with the system selecting one option from each group. For a prefixed set (e.g., 2$$), the system will select two distinct options.
+
+For example, the following prompts could be generated from the above Dynamic Prompt:
+
+    A house in summer designed in style1, style2
+    A lodge in autumn designed in style3, style1
+    A cottage in winter designed in style2, style3
+    And many more!
+
+When the `Combinatorial` setting is on, Invoke will disable the "Images" selection, and generate every combination up until the setting for Max Prompts is reached.
+When the `Combinatorial` setting is off, Invoke will randomly generate combinations up until the setting for Images has been reached.
+
+
+
+### Tips and Tricks for Using Dynamic Prompts
+
+Below are some useful strategies for creating Dynamic Prompts:
+
+    Utilize Dynamic Prompts to generate a wide spectrum of prompts, perfect for brainstorming and exploring diverse ideas.
+    Ensure that the options within a group are contextually relevant to the part of the sentence where they are used. For instance, group building types together, and seasons together.
+    Apply the 2$$ prefix when you want to incorporate more than one option from a single group. This becomes quite handy when mixing and matching different elements.
+    Experiment with different quantities for the prefix. For example, 3$$ will select three distinct options.
+    Be aware of coherence in your prompts. Although the system can generate all possible combinations, not all may semantically make sense. Therefore, carefully choose the options for each group.
+    Always review and fine-tune the generated prompts as needed. While Dynamic Prompts can help you generate a multitude of combinations, the final polishing and refining remain in your hands.
+
+
+## SDXL Prompting
+
+Prompting with SDXL is slightly different than prompting with SD1.5 or SD2.1 models - SDXL expects a prompt _and_ a style. 
+
+
+### Prompting 
+<figure markdown>
+
+![SDXL prompt boxes in InvokeAI](../assets/prompt_syntax/sdxl-prompt.png)
+
+</figure>
+
+In the prompt box, enter a positive or negative prompt as you normally would. 
+
+For the style box you can enter a style that you want the image to be generated in. You can use styles from this example list, or any other style you wish: anime, photographic, digital art, comic book, fantasy art, analog film, neon punk, isometric, low poly, origami, line art, cinematic, 3d model, pixel art, etc.
+
+
+### Concatenated Prompts
+
+
+InvokeAI also has the option to concatenate the prompt and style inputs, by pressing the "link" button in the Positive Prompt box. 
+
+This concatenates the prompt & style inputs, and passes the joined prompt and style to the SDXL model. 
+![SDXL concatenated prompt boxes in InvokeAI](../assets/prompt_syntax/sdxl-prompt-concatenated.png)
+
+
+
+
+
+
+

docs/features/TEXTUAL_INVERSIONS.md

@@ -0,0 +1,55 @@
+## Using Textual Inversion Files
+
+Textual inversion (TI) files are small models that customize the output of
+Stable Diffusion image generation. They can augment SD with specialized subjects
+and artistic styles. They are also known as "embeds" in the machine learning
+world.
+
+Each TI file introduces one or more vocabulary terms to the SD model. These are
+known in InvokeAI as "triggers." Triggers are denoted using angle brackets 
+as in "<trigger-phrase>". The two most common type of
+TI files that you'll encounter are `.pt` and `.bin` files, which are produced by
+different TI training packages. InvokeAI supports both formats, but its
+[built-in TI training system](TRAINING.md) produces `.pt`.
+
+[Hugging Face](https://huggingface.co/sd-concepts-library) has
+amassed a large library of >800 community-contributed TI files covering a
+broad range of subjects and styles. You can also install your own or others' TI files 
+by placing them in the designated directory for the compatible model type
+
+### An Example
+
+Here are a few examples to illustrate how it works. All these images
+were generated using the legacy command-line client and the Stable
+Diffusion 1.5 model:
+
+|         Japanese gardener          | Japanese gardener <ghibli-face> | Japanese gardener <hoi4-leaders> | Japanese gardener <cartoona-animals> |
+| :--------------------------------: | :-----------------------------------: | :------------------------------------: | :----------------------------------------: |
+| ![](../assets/concepts/image1.png) |  ![](../assets/concepts/image2.png)   |   ![](../assets/concepts/image3.png)   |     ![](../assets/concepts/image4.png)     |
+
+You can also combine styles and concepts:
+
+<figure markdown>
+  | A portrait of &lt;alf&gt; in &lt;cartoona-animal&gt; style |
+  | :--------------------------------------------------------: |
+  | ![](../assets/concepts/image5.png)                         |
+</figure>
+
+
+## Installing your Own TI Files
+
+You may install any number of `.pt` and `.bin` files simply by copying them into
+the `embedding` directory of the corresponding InvokeAI models directory (usually `invokeai`
+in your home directory). For example, you can simply move a Stable Diffusion 1.5 embedding file to
+the `sd-1/embedding` folder. Be careful not to overwrite one file with another.
+For example, TI files generated by the Hugging Face toolkit share the named
+`learned_embedding.bin`. You can rename these, or use subdirectories to keep them distinct.
+
+At startup time, InvokeAI will scan the various `embedding` directories and load any TI
+files it finds there for compatible models. At startup you will see a message similar to this one:
+
+```bash
+>> Current embedding manager terms: <HOI4-Leader>, <princess-knight>
+```
+To use these when generating, simply type the `<` key in your prompt to open the Textual Inversion WebUI and 
+select the embedding you'd like to use. This UI has type-ahead support, so you can easily find supported embeddings.

docs/features/TRAINING.md

@@ -0,0 +1,281 @@
+---
+title: Training
+---
+
+# :material-file-document: Training
+
+# Textual Inversion Training
+## **Personalizing Text-to-Image Generation**
+
+You may personalize the generated images to provide your own styles or objects
+by training a new LDM checkpoint and introducing a new vocabulary to the fixed
+model as a (.pt) embeddings file. Alternatively, you may use or train
+HuggingFace Concepts embeddings files (.bin) from
+<https://huggingface.co/sd-concepts-library> and its associated
+notebooks.
+
+## **Hardware and Software Requirements**
+
+You will need a GPU to perform training in a reasonable length of
+time, and at least 12 GB of VRAM. We recommend using the [`xformers`
+library](../installation/070_INSTALL_XFORMERS.md) to accelerate the
+training process further. During training, about ~8 GB is temporarily
+needed in order to store intermediate models, checkpoints and logs.
+
+## **Preparing for Training**
+
+To train, prepare a folder that contains 3-5 images that illustrate
+the object or concept. It is good to provide a variety of examples or
+poses to avoid overtraining the system. Format these images as PNG
+(preferred) or JPG. You do not need to resize or crop the images in
+advance, but for more control you may wish to do so.
+
+Place the training images in a directory on the machine InvokeAI runs
+on. We recommend placing them in a subdirectory of the
+`text-inversion-training-data` folder located in the InvokeAI root
+directory, ordinarily `~/invokeai` (Linux/Mac), or
+`C:\Users\your_name\invokeai` (Windows). For example, to create an
+embedding for the "psychedelic" style, you'd place the training images
+into the directory
+`~invokeai/text-inversion-training-data/psychedelic`.
+
+## **Launching Training Using the Console Front End**
+
+InvokeAI 2.3 and higher comes with a text console-based training front
+end. From within the `invoke.sh`/`invoke.bat` Invoke launcher script,
+start training tool selecting choice (3):
+
+```sh
+1 "Generate images with a browser-based interface"
+2 "Explore InvokeAI nodes using a command-line interface"
+3 "Textual inversion training"
+4 "Merge models (diffusers type only)"
+5 "Download and install models"
+6 "Change InvokeAI startup options"
+7 "Re-run the configure script to fix a broken install or to complete a major upgrade"
+8 "Open the developer console"
+9 "Update InvokeAI"
+```
+
+Alternatively, you can select option (8) or from the command line, with the InvokeAI virtual environment active,
+you can then launch the front end with the command `invokeai-ti --gui`.
+
+This will launch a text-based front end that will look like this:
+
+<figure markdown>
+![ti-frontend](../assets/textual-inversion/ti-frontend.png)
+</figure>
+
+The interface is keyboard-based. Move from field to field using
+control-N (^N) to move to the next field and control-P (^P) to the
+previous one. <Tab> and <shift-TAB> work as well. Once a field is
+active, use the cursor keys. In a checkbox group, use the up and down
+cursor keys to move from choice to choice, and <space> to select a
+choice. In a scrollbar, use the left and right cursor keys to increase
+and decrease the value of the scroll. In textfields, type the desired
+values.
+
+The number of parameters may look intimidating, but in most cases the
+predefined defaults work fine. The red circled fields in the above
+illustration are the ones you will adjust most frequently.
+
+### Model Name
+
+This will list all the diffusers models that are currently
+installed. Select the one you wish to use as the basis for your
+embedding. Be aware that if you use a SD-1.X-based model for your
+training, you will only be able to use this embedding with other
+SD-1.X-based models. Similarly, if you train on SD-2.X, you will only
+be able to use the embeddings with models based on SD-2.X.
+
+### Trigger Term
+
+This is the prompt term you will use to trigger the embedding. Type a
+single word or phrase you wish to use as the trigger, example
+"psychedelic" (without angle brackets). Within InvokeAI, you will then
+be able to activate the trigger using the syntax `<psychedelic>`.
+
+### Initializer
+
+This is a single character that is used internally during the training
+process as a placeholder for the trigger term. It defaults to "*" and
+can usually be left alone.
+
+### Resume from last saved checkpoint
+
+As training proceeds, textual inversion will write a series of
+intermediate files that can be used to resume training from where it
+was left off in the case of an interruption. This checkbox will be
+automatically selected if you provide a previously used trigger term
+and at least one checkpoint file is found on disk.
+
+Note that as of 20 January 2023, resume does not seem to be working
+properly due to an issue with the upstream code.
+
+### Data Training Directory
+
+This is the location of the images to be used for training. When you
+select a trigger term like "my-trigger", the frontend will prepopulate
+this field with `~/invokeai/text-inversion-training-data/my-trigger`,
+but you can change the path to wherever you want.
+
+### Output Destination Directory
+
+This is the location of the logs, checkpoint files, and embedding
+files created during training. When you select a trigger term like
+"my-trigger", the frontend will prepopulate this field with
+`~/invokeai/text-inversion-output/my-trigger`, but you can change the
+path to wherever you want.
+
+### Image resolution
+
+The images in the training directory will be automatically scaled to
+the value you use here. For best results, you will want to use the
+same default resolution of the underlying model (512 pixels for
+SD-1.5, 768 for the larger version of SD-2.1).
+
+### Center crop images
+
+If this is selected, your images will be center cropped to make them
+square before resizing them to the desired resolution. Center cropping
+can indiscriminately cut off the top of subjects' heads for portrait
+aspect images, so if you have images like this, you may wish to use a
+photoeditor to manually crop them to a square aspect ratio.
+
+### Mixed precision
+
+Select the floating point precision for the embedding. "no" will
+result in a full 32-bit precision, "fp16" will provide 16-bit
+precision, and "bf16" will provide mixed precision (only available
+when XFormers is used).
+
+### Max training steps
+
+How many steps the training will take before the model converges. Most
+training sets will converge with 2000-3000 steps.
+
+### Batch size
+
+This adjusts how many training images are processed simultaneously in
+each step. Higher values will cause the training process to run more
+quickly, but use more memory. The default size will run with GPUs with
+as little as 12 GB.
+
+### Learning rate
+
+The rate at which the system adjusts its internal weights during
+training. Higher values risk overtraining (getting the same image each
+time), and lower values will take more steps to train a good
+model. The default of 0.0005 is conservative; you may wish to increase
+it to 0.005 to speed up training.
+
+### Scale learning rate by number of GPUs, steps and batch size
+
+If this is selected (the default) the system will adjust the provided
+learning rate to improve performance.
+
+### Use xformers acceleration
+
+This will activate XFormers memory-efficient attention. You need to
+have XFormers installed for this to have an effect.
+
+### Learning rate scheduler
+
+This adjusts how the learning rate changes over the course of
+training. The default "constant" means to use a constant learning rate
+for the entire training session. The other values scale the learning
+rate according to various formulas.
+
+Only "constant" is supported by the XFormers library.
+
+### Gradient accumulation steps
+
+This is a parameter that allows you to use bigger batch sizes than
+your GPU's VRAM would ordinarily accommodate, at the cost of some
+performance.
+
+### Warmup steps
+
+If "constant_with_warmup" is selected in the learning rate scheduler,
+then this provides the number of warmup steps. Warmup steps have a
+very low learning rate, and are one way of preventing early
+overtraining.
+
+## The training run
+
+Start the training run by advancing to the OK button (bottom right)
+and pressing <enter>. A series of progress messages will be displayed
+as the training process proceeds. This may take an hour or two,
+depending on settings and the speed of your system. Various log and
+checkpoint files will be written into the output directory (ordinarily
+`~/invokeai/text-inversion-output/my-model/`)
+
+At the end of successful training, the system will copy the file
+`learned_embeds.bin` into the InvokeAI root directory's `embeddings`
+directory, using a subdirectory named after the trigger token. For
+example, if the trigger token was `psychedelic`, then look for the
+embeddings file in
+`~/invokeai/embeddings/psychedelic/learned_embeds.bin`
+
+You may now launch InvokeAI and try out a prompt that uses the trigger
+term. For example `a plate of banana sushi in <psychedelic> style`.
+
+## **Training with the Command-Line Script**
+
+Training can also be done using a traditional command-line script. It
+can be launched from within the "developer's console", or from the
+command line after activating InvokeAI's virtual environment.
+
+It accepts a large number of arguments, which can be summarized by
+passing the `--help` argument:
+
+```sh
+invokeai-ti --help
+```
+
+Typical usage is shown here:
+```sh
+invokeai-ti \
+       --model=stable-diffusion-1.5 \
+       --resolution=512 \
+       --learnable_property=style \
+       --initializer_token='*' \
+       --placeholder_token='<psychedelic>' \
+       --train_data_dir=/home/lstein/invokeai/training-data/psychedelic \
+       --output_dir=/home/lstein/invokeai/text-inversion-training/psychedelic \
+       --scale_lr \
+       --train_batch_size=8 \
+       --gradient_accumulation_steps=4 \
+       --max_train_steps=3000 \
+       --learning_rate=0.0005 \
+       --resume_from_checkpoint=latest \
+       --lr_scheduler=constant \
+       --mixed_precision=fp16 \
+       --only_save_embeds
+```
+
+## Troubleshooting
+
+### `Cannot load embedding for <trigger>. It was trained on a model with token dimension 1024, but the current model has token dimension 768`
+
+Messages like this indicate you trained the embedding on a different base model than the currently selected one.
+
+For example, in the error above, the training was done on SD2.1 (768x768) but it was used on SD1.5 (512x512).
+
+## Reading
+
+For more information on textual inversion, please see the following
+resources:
+
+* The [textual inversion repository](https://github.com/rinongal/textual_inversion) and
+  associated paper for details and limitations.
+* [HuggingFace's textual inversion training
+  page](https://huggingface.co/docs/diffusers/training/text_inversion)
+* [HuggingFace example script
+  documentation](https://github.com/huggingface/diffusers/tree/main/examples/textual_inversion)
+  (Note that this script is similar to, but not identical, to
+  `textual_inversion`, but produces embed files that are completely compatible.
+
+---
+
+copyright (c) 2023, Lincoln Stein and the InvokeAI Development Team

docs/features/UNIFIED_CANVAS.md

@@ -0,0 +1,283 @@
+---
+title: Unified Canvas
+---
+
+The Unified Canvas is a tool designed to streamline and simplify the process of
+composing an image using Stable Diffusion. It offers artists all of the
+available Stable Diffusion generation modes (Text To Image, Image To Image,
+Inpainting, and Outpainting) as a single unified workflow. The flexibility of
+the tool allows you to tweak and edit image generations, extend images beyond
+their initial size, and to create new content in a freeform way both inside and
+outside of existing images.
+
+This document explains the basics of using the Unified Canvas, introducing you
+to its features and tools one by one. It also describes some of the more
+advanced tools available to power users of the Canvas.
+
+## Basics
+
+The Unified Canvas consists of two layers: the **Base Layer** and the **Mask
+Layer**. You can swap from one layer to the other by selecting the layer you
+want in the drop-down menu on the top left corner of the Unified Canvas, or by
+pressing the (Q) hotkey.
+
+### Base Layer
+
+The **Base Layer** is the image content currently managed by the Canvas, and can
+be exported at any time to the gallery by using the **Save to Gallery** option.
+When the Base Layer is selected, the Brush (B) and Eraser (E) tools will
+directly manipulate the base layer. Any images uploaded to the Canvas, or sent
+to the Unified Canvas from the gallery, will clear out all existing content and
+set the Base layer to the new image.
+
+### Staging Area
+
+When you generate images, they will display in the Canvas's **Staging Area**,
+alongside the Staging Area toolbar buttons. While the Staging Area is active,
+you cannot interact with the Canvas itself.
+
+<figure markdown>
+
+![staging area](../assets/canvas/staging_area.png)
+
+</figure>
+
+Accepting generations will commit the new generation to the **Base Layer**. You
+can review all generated images using the Prev/Next arrows, save any individual
+generations to your gallery (without committing to the Base layer) or discard
+generations. While you can Undo a discard in an individual Canvas session, any
+generations that are not saved will be lost when the Canvas resets.
+
+### Mask Layer
+
+The **Mask Layer** consists of any masked sections that have been created to
+inform Inpainting generations. You can paint a new mask, or edit an existing
+mask, using the Brush tool and the Eraser with the Mask layer set as your Active
+layer. Any masked areas will only affect generation inside of the current
+bounding box.
+
+### Bounding Box
+
+When generating a new image, Invoke will process and apply new images within the
+area denoted by the **Bounding Box**. The Width & Height settings of the
+Bounding Box, as well as its location within the Unified Canvas and pixels or
+empty space that it encloses, determine how new invocations are generated - see
+[Inpainting & Outpainting](#inpainting-and-outpainting) below. The Bounding Box
+can be moved and resized using the Move (V) tool. It can also be resized using
+the Bounding Box options in the Options Panel. By using these controls you can
+generate larger or smaller images, control which sections of the image are being
+processed, as well as control Bounding Box tools like the Bounding Box
+fill/erase.
+
+### <a name="inpainting-and-outpainting"></a> Inpainting & Outpainting
+
+"Inpainting" means asking the AI to refine part of an image while leaving the
+rest alone. For example, updating a portrait of your grandmother to have her
+wear a biker's jacket.
+
+|                         masked original                         |                                       inpaint result                                       |
+| :-------------------------------------------------------------: | :----------------------------------------------------------------------------------------: |
+| ![granny with a mask applied](../assets/canvas/mask_granny.png) | ![just like magic, granny with a biker's jacket](../assets/canvas/biker_jacket_granny.png) |
+
+"Outpainting" means asking the AI to expand the original image beyond its
+original borders, making a bigger image that's still based on the original. For
+example, extending the above image of your Grandmother in a biker's jacket to
+include her wearing jeans (and while we're at it, a motorcycle!)
+
+<figure markdown>
+
+![more magic - granny with a tattooed arm, denim pants, and an obscured motorcycle](../assets/canvas/biker_granny.png)
+
+</figure>
+
+When you are using the Unified Canvas, Invoke decides automatically whether to
+do Inpainting, Outpainting, ImageToImage, or TextToImage by looking inside the
+area enclosed by the Bounding Box. It chooses the appropriate type of generation
+based on whether the Bounding Box contains empty (transparent) areas on the Base
+layer, or whether it contains colored areas from previous generations (or from
+painted brushstrokes) on the Base layer, and/or whether the Mask layer contains
+any brushstrokes. See [Generation Methods](#generation-methods) below for more
+information.
+
+## Getting Started
+
+To get started with the Unified Canvas, you will want to generate a new base
+layer using Txt2Img or importing an initial image. We'll refer to either of
+these methods as the "initial image" in the below guide.
+
+From there, you can consider the following techniques to augment your image:
+
+- **New Images**: Move the bounding box to an empty area of the Canvas, type in
+  your prompt, and Invoke, to generate a new image using the Text to Image
+  function.
+- **Image Correction**: Use the color picker and brush tool to paint corrections
+  on the image, switch to the Mask layer, and brush a mask over your painted
+  area to use **Inpainting**. You can also use the **ImageToImage** generation
+  method to invoke new interpretations of the image.
+- **Image Expansion**: Move the bounding box to include a portion of your
+  initial image, and a portion of transparent/empty pixels, then Invoke using a
+  prompt that describes what you'd like to see in that area. This will Outpaint
+  the image. You'll typically find more coherent results if you keep about
+  50-60% of the original image in the bounding box. Make sure that the Image To
+  Image Strength slider is set to a high value - you may need to set it higher
+  than you are used to.
+- **New Content on Existing Images**: If you want to add new details or objects
+  into your image, use the brush tool to paint a sketch of what you'd like to
+  see on the image, switch to the Mask layer, and brush a mask over your painted
+  area to use **Inpainting**. If the masked area is small, consider using a
+  smaller bounding box to take advantage of Invoke's automatic Scaling features,
+  which can help to produce better details.
+- **And more**: There are a number of creative ways to use the Canvas, and the
+  above are just starting points. We're excited to see what you come up with!
+
+## <a name="generation-methods"></a> Generation Methods
+
+The Canvas can use all generation methods available (Txt2Img, Img2Img,
+Inpainting, and Outpainting), and these will be automatically selected and used
+based on the current selection area within the Bounding Box.
+
+### Text to Image
+
+If the Bounding Box is placed over an area of Canvas with an **empty Base
+Layer**, invoking a new image will use **TextToImage**. This generates an
+entirely new image based on your prompt.
+
+### Image to Image
+
+If the Bounding Box is placed over an area of Canvas with an **existing Base
+Layer area with no transparent pixels or masks**, invoking a new image will use
+**ImageToImage**. This uses the image within the bounding box and your prompt to
+interpret a new image. The image will be closer to your original image at lower
+Image to Image strengths.
+
+### Inpainting
+
+If the Bounding Box is placed over an area of Canvas with an **existing Base
+Layer and any pixels selected using the Mask layer**, invoking a new image will
+use **Inpainting**. Inpainting uses the existing colors/forms in the masked area
+in order to generate a new image for the masked area only. The unmasked portion
+of the image will remain the same. Image to Image strength applies to the
+inpainted area.
+
+If you desire something completely different from the original image in your new
+generation (i.e., if you want Invoke to ignore existing colors/forms), consider
+toggling the Inpaint Replace setting on, and use high values for both Inpaint
+Replace and Image To Image Strength.
+
+!!! note
+
+    By default, the **Scale Before Processing** option &mdash; which
+    inpaints more coherent details by generating at a larger resolution and then
+    scaling &mdash; is only activated when the Bounding Box is relatively small.
+    To get the best inpainting results you should therefore resize your Bounding
+    Box to the smallest area that contains your mask and enough surrounding detail
+    to help Stable Diffusion understand the context of what you want it to draw.
+    You should also update your prompt so that it describes _just_ the area within
+    the Bounding Box.
+
+### Outpainting
+
+If the Bounding Box is placed over an area of Canvas partially filled by an
+existing Base Layer area and partially by transparent pixels or masks, invoking
+a new image will use **Outpainting**, as well as **Inpainting** any masked
+areas.
+
+---
+
+## Advanced Features
+
+Features with non-obvious behavior are detailed below, in order to provide
+clarity on the intent and common use cases we expect for utilizing them.
+
+### Toolbar
+
+#### Mask Options
+
+- **Enable Mask** - This flag can be used to Enable or Disable the currently
+  painted mask. If you have painted a mask, but you don't want it affect the
+  next invocation, but you _also_ don't want to delete it, then you can set this
+  option to Disable. When you want the mask back, set this back to Enable.
+- **Preserve Masked Area** - When enabled, Preserve Masked Area inverts the
+  effect of the Mask on the Inpainting process. Pixels in masked areas will be
+  kept unchanged, and unmasked areas will be regenerated.
+
+#### Creative Tools
+
+- **Brush - Base/Mask Modes** - The Brush tool switches automatically between
+  different modes of operation for the Base and Mask layers respectively.
+    - On the Base layer, the brush will directly paint on the Canvas using the
+      color selected on the Brush Options menu.
+    - On the Mask layer, the brush will create a new mask. If you're finding the
+      mask difficult to see over the existing content of the Unified Canvas, you
+      can change the color it is drawn with using the color selector on the Mask
+      Options dropdown.
+- **Erase Bounding Box** - On the Base layer, erases all pixels within the
+  Bounding Box.
+- **Fill Bounding Box** - On the Base layer, fills all pixels within the
+  Bounding Box with the currently selected color.
+
+#### Canvas Tools
+
+- **Move Tool** - Allows for manipulation of the Canvas view (by dragging on the
+  Canvas, outside the bounding box), the Bounding Box (by dragging the edges of
+  the box), or the Width/Height of the Bounding Box (by dragging one of the 9
+  directional handles).
+- **Reset View** - Click to re-orients the view to the center of the Bounding
+  Box.
+- **Merge Visible** - If your browser is having performance problems drawing the
+  image in the Unified Canvas, click this to consolidate all of the information
+  currently being rendered by your browser into a merged copy of the image. This
+  lowers the resource requirements and should improve performance.
+
+### Compositing / Seam Correction
+
+When doing Inpainting or Outpainting, Invoke needs to merge the pixels generated
+by Stable Diffusion into your existing image. This is achieved through compositing - the area around the the boundary between your image and the new generation is
+automatically blended to produce a seamless output. In a fully automatic
+process, a mask is generated to cover the boundary, and then the area of the boundary is
+Inpainted.
+
+Although the default options should work well most of the time, sometimes it can
+help to alter the parameters that control the Compositing. A larger blur and
+a blur setting  have been noted as producing
+consistently strong results . Strength of 0.7 is best for reducing hard seams.
+
+- **Mode** - What part of the image will have the the Compositing applied to it.
+  - **Mask edge** will apply Compositing to the edge of the masked area
+  - **Mask** will apply Compositing to the entire masked area
+  - **Unmasked** will apply Compositing to the entire image
+- **Steps** - Number of generation steps that will occur during the Coherence Pass, similar to Denoising Steps. Higher step counts will generally have better results.
+- **Strength** - How much noise is added for the Coherence Pass, similar to Denoising Strength. A strength of 0 will result in an unchanged image, while a strength of 1 will result in an image with a completely new area as defined by the Mode setting.
+- **Blur** - Adjusts the pixel radius of the the mask. A larger blur radius will cause the mask to extend past the visibly masked area, while too small of a blur radius will result in a mask that is smaller than the visibly masked area.
+- **Blur Method** - The method of blur applied to the masked area. 
+
+
+### Infill & Scaling
+
+- **Scale Before Processing & W/H**: When generating images with a bounding box
+  smaller than the optimized W/H of the model (e.g., 512x512 for SD1.5), this
+  feature first generates at a larger size with the same aspect ratio, and then
+  scales that image down to fill the selected area. This is particularly useful
+  when inpainting very small details. Scaling is optional but is enabled by
+  default.
+- **Inpaint Replace**: When Inpainting, the default method is to utilize the
+  existing RGB values of the Base layer to inform the generation process. If
+  Inpaint Replace is enabled, noise is generated and blended with the existing
+  pixels (completely replacing the original RGB values at an Inpaint Replace
+  value of 1). This can help generate more variation from the pixels on the Base
+  layers.
+    - When using Inpaint Replace you should use a higher Image To Image Strength
+      value, especially at higher Inpaint Replace values
+- **Infill Method**: Invoke currently supports two methods for producing RGB
+  values for use in the Outpainting process: Patchmatch and Tile. We believe
+  that Patchmatch is the superior method, however we provide support for Tile in
+  case Patchmatch cannot be installed or is unavailable on your computer.
+- **Tile Size**: The Tile method for Outpainting sources small portions of the
+  original image and randomly place these into the areas being Outpainted. This
+  value sets the size of those tiles.
+
+## Hot Keys
+
+The Unified Canvas is a tool that excels when you use hotkeys. You can view the
+full list of keyboard shortcuts, updated with all new features, by clicking the
+Keyboard Shortcuts icon at the top right of the InvokeAI WebUI.

docs/features/UTILITIES.md

@@ -0,0 +1,336 @@
+---
+title: Command-line Utilities
+---
+
+# :material-file-document: Utilities
+
+# Command-line Utilities
+
+InvokeAI comes with several scripts that are accessible via the
+command line. To access these commands, start the "developer's
+console" from the launcher (`invoke.bat` menu item [7]). Users who are
+familiar with Python can alternatively activate InvokeAI's virtual
+environment (typically, but not necessarily `invokeai/.venv`).
+
+In the developer's console, type the script's name to run it. To get a
+synopsis of what a utility does and the command-line arguments it
+accepts, pass it the `-h` argument, e.g.
+
+```bash
+invokeai-merge -h
+```
+## **invokeai-web**
+
+This script launches the web server and is effectively identical to
+selecting option [1] in the launcher. An advantage of launching the
+server from the command line is that you can override any setting
+configuration option in `invokeai.yaml` using like-named command-line
+arguments. For example, to temporarily change the size of the RAM
+cache to 7 GB, you can launch as follows:
+
+```bash
+invokeai-web --ram 7
+```
+
+## **invokeai-merge**
+
+This is the model merge script, the same as launcher option [3]. Call
+it with the `--gui` command-line argument to start the interactive
+console-based GUI. Alternatively, you can run it non-interactively
+using command-line arguments as illustrated in the example below which
+merges models named `stable-diffusion-1.5` and `inkdiffusion` into a new model named
+`my_new_model`:
+
+```bash
+invokeai-merge --force --base-model sd-1 --models stable-diffusion-1.5 inkdiffusion --merged_model_name my_new_model
+```
+
+## **invokeai-ti**
+
+This is the textual inversion training script that is run by launcher
+option [2]. Call it with `--gui` to run the interactive console-based
+front end. It can also be run non-interactively. It has about a
+zillion arguments, but a typical training session can be launched
+with:
+
+```bash
+invokeai-ti --model stable-diffusion-1.5 \
+            --placeholder_token 'jello' \
+            --learnable_property object \
+			--num_train_epochs 50 \
+			--train_data_dir /path/to/training/images \
+			--output_dir /path/to/trained/model
+```
+
+(Note that \\ is the Linux/Mac long-line continuation character. Use ^
+in Windows).
+
+## **invokeai-install**
+
+This is the console-based model install script that is run by launcher
+option [4]. If called without arguments, it will launch the
+interactive console-based interface. It can also be used
+non-interactively to list, add and remove models as shown by these
+examples:
+
+* This will download and install three models from CivitAI, HuggingFace,
+and local disk:
+
+```bash
+invokeai-install --add https://civitai.com/api/download/models/161302 ^
+                  gsdf/Counterfeit-V3.0  ^
+				  D:\Models\merge_model_two.safetensors
+```
+(Note that ^ is the Windows long-line continuation character. Use \\ on
+Linux/Mac).
+
+* This will list installed models of type `main`:
+
+```bash
+invokeai-model-install --list-models main
+```
+
+* This will delete the models named `voxel-ish` and `realisticVision`:
+
+```bash
+invokeai-model-install --delete voxel-ish realisticVision
+```
+
+## **invokeai-configure**
+
+This is the console-based configure script that ran when InvokeAI was
+first installed. You can run it again at any time to change the
+configuration, repair a broken install.
+
+Called without any arguments, `invokeai-configure` enters interactive
+mode with two screens. The first screen is a form that provides access
+to most of InvokeAI's configuration options. The second screen lets
+you download, add, and delete models interactively. When you exit the
+second screen, the script will add any missing "support models"
+needed for core functionality, and any selected "sd weights" which are
+the model checkpoint/diffusers files.
+
+This behavior can be changed via a series of command-line
+arguments. Here are some of the useful ones:
+
+* `invokeai-configure --skip-sd-weights --skip-support-models`
+This will run just the configuration part of the utility, skipping
+downloading of support models and stable diffusion weights.
+
+* `invokeai-configure --yes`
+This will run the configure script non-interactively. It will set the
+configuration options to their default values, install/repair support
+models, and download the "recommended" set of SD models.
+
+* `invokeai-configure --yes --default_only` 
+This will run the configure script non-interactively. In contrast to
+the previous command, it will only download the default SD model,
+Stable Diffusion v1.5
+
+* `invokeai-configure --yes --default_only --skip-sd-weights` 
+This is similar to the previous command, but will not download any
+SD models at all. It is usually used to repair a broken install.
+
+By default, `invokeai-configure` runs on the currently active InvokeAI
+root folder. To run it against a different root, pass it the `--root
+</path/to/root>` argument.
+
+Lastly, you can use `invokeai-configure` to create a working root
+directory entirely from scratch. Assuming you wish to make a root directory
+named `InvokeAI-New`, run this command:
+
+```bash
+invokeai-configure --root InvokeAI-New --yes --default_only
+```
+This will create a minimally functional root directory. You can now
+launch the web server against it with `invokeai-web --root InvokeAI-New`.
+
+## **invokeai-update**
+
+This is the interactive console-based script that is run by launcher
+menu item [8] to update to a new version of InvokeAI. It takes no
+command-line arguments.
+
+## **invokeai-metadata**
+
+This is a script which takes a list of InvokeAI-generated images and
+outputs their metadata in the same JSON format that you get from the
+`</>` button in the Web GUI. For example:
+
+```bash
+$ invokeai-metadata ffe2a115-b492-493c-afff-7679aa034b50.png
+ffe2a115-b492-493c-afff-7679aa034b50.png:
+{
+    "app_version": "3.1.0",
+    "cfg_scale": 8.0,
+    "clip_skip": 0,
+    "controlnets": [],
+    "generation_mode": "sdxl_txt2img",
+    "height": 1024,
+    "loras": [],
+    "model": {
+        "base_model": "sdxl",
+        "model_name": "stable-diffusion-xl-base-1.0",
+        "model_type": "main"
+    },
+    "negative_prompt": "",
+    "negative_style_prompt": "",
+    "positive_prompt": "military grade sushi dinner for shock troopers",
+    "positive_style_prompt": "",
+    "rand_device": "cpu",
+    "refiner_cfg_scale": 7.5,
+    "refiner_model": {
+        "base_model": "sdxl-refiner",
+        "model_name": "sd_xl_refiner_1.0",
+        "model_type": "main"
+    },
+    "refiner_negative_aesthetic_score": 2.5,
+    "refiner_positive_aesthetic_score": 6.0,
+    "refiner_scheduler": "euler",
+    "refiner_start": 0.8,
+    "refiner_steps": 20,
+    "scheduler": "euler",
+    "seed": 387129902,
+    "steps": 25,
+    "width": 1024
+}
+```
+
+You may list multiple files on the command line.
+
+## **invokeai-import-images**
+
+InvokeAI uses a database to store information about images it
+generated, and just copying the image files from one InvokeAI root
+directory to another does not automatically import those images into
+the destination's gallery. This script allows you to bulk import
+images generated by one instance of InvokeAI into a gallery maintained
+by another. It also works on images generated by older versions of
+InvokeAI, going way back to version 1.
+
+This script has an interactive mode only. The following example shows
+it in action:
+
+```bash
+$ invokeai-import-images
+===============================================================================
+This script will import images generated by earlier versions of
+InvokeAI into the currently installed root directory:
+   /home/XXXX/invokeai-main
+If this is not what you want to do, type ctrl-C now to cancel.
+===============================================================================
+= Configuration & Settings
+Found invokeai.yaml file at /home/XXXX/invokeai-main/invokeai.yaml:
+  Database : /home/XXXX/invokeai-main/databases/invokeai.db
+  Outputs  : /home/XXXX/invokeai-main/outputs/images
+ 
+Use these paths for import (yes) or choose different ones (no) [Yn]:
+Inputs: Specify absolute path containing InvokeAI .png images to import: /home/XXXX/invokeai-2.3/outputs/images/
+Include files from subfolders recursively [yN]?
+
+Options for board selection for imported images:
+1) Select an existing board name. (found 4)
+2) Specify a board name to create/add to.
+3) Create/add to board named 'IMPORT'.
+4) Create/add to board named 'IMPORT' with the current datetime string appended (.e.g IMPORT_20230919T203519Z).
+5) Create/add to board named 'IMPORT' with a the original file app_version appended (.e.g IMPORT_2.2.5).
+Specify desired board option: 3
+
+===============================================================================
+= Import Settings Confirmation
+
+Database File Path               : /home/XXXX/invokeai-main/databases/invokeai.db
+Outputs/Images Directory         : /home/XXXX/invokeai-main/outputs/images
+Import Image Source Directory    : /home/XXXX/invokeai-2.3/outputs/images/
+  Recurse Source SubDirectories  : No
+Count of .png file(s) found      : 5785
+Board name option specified      : IMPORT
+Database backup will be taken at : /home/XXXX/invokeai-main/databases/backup
+
+Notes about the import process:
+- Source image files will not be modified, only copied to the outputs directory.
+- If the same file name already exists in the destination, the file will be skipped.
+- If the same file name already has a record in the database, the file will be skipped.
+- Invoke AI metadata tags will be updated/written into the imported copy only.
+- On the imported copy, only Invoke AI known tags (latest and legacy) will be retained (dream, sd-metadata, invokeai, invokeai_metadata)
+- A property 'imported_app_version' will be added to metadata that can be viewed in the UI's metadata viewer.
+- The new 3.x InvokeAI outputs folder structure is flat so recursively found source imges will all be placed into the single outputs/images folder.
+ 
+Do you wish to continue with the import [Yn] ?
+
+Making DB Backup at /home/lstein/invokeai-main/databases/backup/backup-20230919T203519Z-invokeai.db...Done!
+
+===============================================================================
+Importing /home/XXXX/invokeai-2.3/outputs/images/17d09907-297d-4db3-a18a-60b337feac66.png
+... (5785 more lines) ...
+===============================================================================
+= Import Complete - Elpased Time: 0.28 second(s)
+
+Source File(s)                          : 5785
+Total Imported                          : 5783
+Skipped b/c file already exists on disk : 1
+Skipped b/c file already exists in db   : 0
+Errors during import                    : 1
+```
+## **invokeai-db-maintenance**
+
+This script helps maintain the integrity of your InvokeAI database by
+finding and fixing three problems that can arise over time:
+
+1. An image was manually deleted from the outputs directory, leaving a
+   dangling image record in the InvokeAI database. This will cause a
+   black image to appear in the gallery. This is an "orphaned database
+   image record." The script can fix this by running a "clean"
+   operation on the database, removing the orphaned entries.
+   
+2. An image is present in the outputs directory but there is no
+   corresponding entry in the database. This can happen when the image
+   is added manually to the outputs directory, or if a crash occurred
+   after the image was generated but before the database was
+   completely updated. The symptom is that the image is present in the
+   outputs folder but doesn't appear in the InvokeAI gallery. This is
+   called an "orphaned image file." The script can fix this problem by
+   running an "archive" operation in which orphaned files are moved
+   into a directory named `outputs/images-archive`. If you wish, you
+   can then run `invokeai-image-import` to reimport these images back
+   into the database.
+   
+3. The thumbnail for an image is missing, again causing a black
+   gallery thumbnail. This is fixed by running the "thumbnaiils"
+   operation, which simply regenerates and re-registers the missing
+   thumbnail.
+   
+You can find and fix all three of these problems in a single go by
+executing this command:
+
+```bash
+invokeai-db-maintenance --operation all
+```
+
+Or you can run just the clean and thumbnail operations like this:
+
+```bash
+invokeai-db-maintenance -operation clean, thumbnail
+```
+
+If called without any arguments, the script will ask you which
+operations you wish to perform.
+
+## **invokeai-migrate3**
+
+This script will migrate settings and models (but not images!) from an
+InvokeAI v2.3 root folder to an InvokeAI 3.X folder. Call it with the
+source and destination root folders like this:
+
+```bash
+invokeai-migrate3 --from ~/invokeai-2.3 --to invokeai-3.1.1
+```
+
+Both directories must previously have been properly created and
+initialized by `invokeai-configure`. If you wish to migrate the images
+contained in the older root as well, you can use the
+`invokeai-image-migrate` script described earlier.
+
+---
+
+Copyright (c) 2023, Lincoln Stein and the InvokeAI Development Team

docs/features/WATERMARK+NSFW.md

@@ -0,0 +1,96 @@
+---
+title: Watermarking, NSFW Image Checking
+---
+
+# :material-image-off: Invisible Watermark and the NSFW Checker
+
+## Watermarking
+
+InvokeAI does not apply watermarking to images by default. However,
+many computer scientists working in the field of generative AI worry
+that a flood of computer-generated imagery will contaminate the image
+data sets needed to train future generations of generative models.
+
+InvokeAI offers an optional watermarking mode that writes a small bit
+of text, **InvokeAI**, into each image that it generates using an
+"invisible" watermarking library that spreads the information
+throughout the image in a way that is not perceptible to the human
+eye. If you are planning to share your generated images on
+internet-accessible services, we encourage you to activate the
+invisible watermark mode in order to help preserve the digital image
+environment.
+
+The downside of watermarking is that it increases the size of the
+image moderately, and has been reported by some individuals to degrade
+image quality. Your mileage may vary.
+
+To read the watermark in an image, activate the InvokeAI virtual
+environment (called the "developer's console" in the launcher) and run
+the command:
+
+```
+invisible-watermark -a decode -t bytes -m dwtDct -l 64 /path/to/image.png
+```
+
+## The NSFW ("Safety") Checker
+
+Stable Diffusion 1.5-based image generation models will produce sexual
+imagery if deliberately prompted, and will occasionally produce such
+images when this is not intended. Such images are colloquially known
+as "Not Safe for Work" (NSFW). This behavior is due to the nature of
+the training set that Stable Diffusion was trained on, which culled
+millions of "aesthetic" images from the Internet.
+
+You may not wish to be exposed to these images, and in some
+jurisdictions it may be illegal to publicly distribute such imagery,
+including mounting a publicly-available server that provides
+unfiltered images to the public. Furthermore, the [Stable Diffusion
+weights
+License](https://github.com/invoke-ai/InvokeAI/blob/main/LICENSE-SD1+SD2.txt),
+and the [Stable Diffusion XL
+License][https://github.com/invoke-ai/InvokeAI/blob/main/LICENSE-SDXL.txt]
+both forbid the models from being used to "exploit any of the
+vulnerabilities of a specific group of persons."
+
+For these reasons Stable Diffusion offers a "safety checker," a
+machine learning model trained to recognize potentially disturbing
+imagery. When a potentially NSFW image is detected, the checker will
+blur the image and paste a warning icon on top. The checker can be
+turned on and off in the Web interface under Settings.
+
+## Caveats
+
+There are a number of caveats that you need to be aware of.
+
+### Accuracy
+
+The checker is [not perfect](https://arxiv.org/abs/2210.04610).It will
+occasionally flag innocuous images (false positives), and will
+frequently miss violent and gory imagery (false negatives). It rarely
+fails to flag sexual imagery, but this has been known to happen. For
+these reasons, the InvokeAI team prefers to refer to the software as a
+"NSFW Checker" rather than "safety checker."
+
+### Memory Usage and Performance
+
+The NSFW checker consumes an additional 1.2G of GPU VRAM on top of the
+3.4G of VRAM used by Stable Diffusion v1.5 (this is with
+half-precision arithmetic). This means that the checker will not run
+successfully on GPU cards with less than 6GB VRAM, and will reduce the
+size of the images that you can produce.
+
+The checker also introduces a slight performance penalty. Images will
+take ~1 second longer to generate when the checker is
+activated. Generally this is not noticeable.
+
+### Intermediate Images in the Web UI
+
+The checker only operates on the final image produced by the Stable
+Diffusion algorithm. If you are using the Web UI and have enabled the
+display of intermediate images, you will briefly be exposed to a
+low-resolution (mosaicized) version of the final image before it is
+flagged by the checker and replaced by a fully blurred version. You
+are encouraged to turn **off** intermediate image rendering when you
+are using the checker. Future versions of InvokeAI will apply
+additional blurring to intermediate images when the checker is active.
+

docs/features/WEB.md

@@ -0,0 +1,325 @@
+---
+title: InvokeAI Web Server
+---
+
+# :material-web: InvokeAI Web Server
+
+## Quick guided walkthrough of the WebUI's features
+
+While most of the WebUI's features are intuitive, here is a guided walkthrough
+through its various components.
+
+### Launching the WebUI
+
+To run the InvokeAI web server, start the `invoke.sh`/`invoke.bat`
+script and select option (1). Alternatively, with the InvokeAI
+environment active, run `invokeai-web`:
+
+```bash
+invokeai-web
+```
+
+You can then connect to the server by pointing your web browser at
+http://localhost:9090. To reach the server from a different machine on your LAN,
+you may launch the web server with the `--host` argument and either the IP
+address of the host you are running it on, or the wildcard `0.0.0.0`. For
+example:
+
+```bash
+invoke.sh --host 0.0.0.0
+```
+
+or
+
+```bash
+invokeai-web --host 0.0.0.0
+```
+
+### The InvokeAI Web Interface
+
+![Invoke Web Server - Major Components](../assets/invoke-web-server-1.png){:width="640px"}
+
+The screenshot above shows the Text to Image tab of the WebUI. There are three
+main sections:
+
+1. A **control panel** on the left, which contains various settings
+   for text to image generation. The most important part is the text
+   field (currently showing `fantasy painting, horned demon`) for
+   entering the positive text prompt, another text field right below it for an
+   optional negative text prompt (concepts to exclude), and a _Invoke_ button 
+   to begin the image rendering process.
+
+2. The **current image** section in the middle, which shows a large
+   format version of the image you are currently working on. A series
+   of buttons at the top lets you modify and manipulate the image in
+   various ways.
+
+3. A **gallery** section on the left that contains a history of the images you
+   have generated. These images are read and written to the directory specified
+   in the `INVOKEAIROOT/invokeai.yaml` initialization file, usually a directory
+   named `outputs` in `INVOKEAIROOT`.
+
+In addition to these three elements, there are a series of icons for changing
+global settings, reporting bugs, and changing the theme on the upper right.
+
+There are also a series of icons to the left of the control panel (see
+highlighted area in the screenshot below) which select among a series of tabs
+for performing different types of operations.
+
+<figure markdown>
+![Invoke Web Server - Control Panel](../assets/invoke-web-server-2.png){:width="512px"}
+</figure>
+
+From top to bottom, these are:
+
+1. Text to Image - generate images from text
+2. Image to Image - from an uploaded starting image (drawing or photograph)
+   generate a new one, modified by the text prompt
+3. Unified Canvas - Interactively combine multiple images, extend them
+   with outpainting,and modify interior portions of the image with
+   inpainting, erase portions of a starting image and have the AI fill in
+   the erased region from a text prompt.
+4. Node Editor - (experimental) this panel allows you to create
+   pipelines of common operations and combine them into workflows.
+5. Model Manager - this panel allows you to import and configure new
+   models using URLs, local paths, or HuggingFace diffusers repo_ids.
+
+## Walkthrough
+
+The following walkthrough will exercise most (but not all) of the WebUI's
+feature set.
+
+### Text to Image
+
+1. Launch the WebUI using launcher option [1] and connect to it with
+   your browser by accessing `http://localhost:9090`. If the browser
+   and server are running on different machines on your LAN, add the
+   option `--host 0.0.0.0` to the `invoke.sh` launch command line and connect to
+   the machine hosting the web server using its IP address or domain
+   name.
+
+2. If all goes well, the WebUI should come up and you'll see a green dot
+   meaning `connected`  on the upper right.
+
+![Invoke Web Server - Control Panel](../assets/invoke-control-panel-1.png){ align=right width=300px }
+
+#### Basics
+
+1.  Generate an image by typing _bluebird_ into the large prompt field
+    on the upper left and then clicking on the Invoke button or pressing
+	the return button.
+	After a short wait, you'll see a large image of a bluebird in the
+    image panel, and a new thumbnail in the gallery on the right.
+
+    If you need more room on the screen, you can turn the gallery off
+    by typing the **g** hotkey. You can turn it back on later by clicking the
+    image icon that appears in the gallery's place. The list of hotkeys can
+	be found by clicking on the keyboard icon above the image gallery.
+
+2.  Generate a bunch of bluebird images by increasing the number of
+    requested images by adjusting the Images counter just below the Invoke
+    button. As each is generated, it will be added to the gallery. You can
+    switch the active image by clicking on the gallery thumbnails.
+	
+	If you'd like to watch the image generation progress, click the hourglass
+	icon above the main image area. As generation progresses, you'll see
+	increasingly detailed versions of the ultimate image.
+
+3.  Try playing with different settings, including changing the main
+    model, the image width and height, the Scheduler, the Steps and
+    the CFG scale.
+	
+	The _Model_ changes the main model. Thousands of custom models are
+	now available, which generate a variety of image styles and
+	subjects. While InvokeAI comes with a few starter models, it is
+	easy to import new models into the application. See [Installing
+	Models](../installation/050_INSTALLING_MODELS.md) for more details.
+
+    Image _Width_ and _Height_ do what you'd expect. However, be aware that
+    larger images consume more VRAM memory and take longer to generate.
+
+    The _Scheduler_ controls how the AI selects the image to display. Some
+    samplers are more "creative" than others and will produce a wider range of
+    variations (see next section). Some samplers run faster than others.
+
+    _Steps_ controls how many noising/denoising/sampling steps the AI will take.
+    The higher this value, the more refined the image will be, but the longer
+    the image will take to generate. A typical strategy is to generate images
+    with a low number of steps in order to select one to work on further, and
+    then regenerate it using a higher number of steps.
+
+    The _CFG Scale_ controls how hard the AI tries to match the generated image
+    to the input prompt. You can go as high or low as you like, but generally
+    values greater than 20 won't improve things much, and values lower than 5
+    will produce unexpected images. There are complex interactions between
+    _Steps_, _CFG Scale_ and the _Scheduler_, so experiment to find out what works
+    for you.
+	
+	The _Seed_ controls the series of values returned by InvokeAI's
+    random number generator. Each unique seed value will generate a different
+	image. To regenerate a previous image, simply use the original image's
+	seed value. A slider to the right of the _Seed_ field will change the
+	seed each time an image is generated.
+
+![Invoke Web Server - Control Panel 2](../assets/control-panel-2.png){ align=right width=400px }
+
+4.  To regenerate a previously-generated image, select the image you
+    want and click the asterisk ("*") button at the top of the
+    image. This loads the text prompt and other original settings into
+    the control panel. If you then press _Invoke_ it will regenerate
+    the image exactly. You can also selectively modify the prompt or
+    other settings to tweak the image.
+
+    Alternatively, you may click on the "sprouting plant icon" to load
+    just the image's seed, and leave other settings unchanged or the
+    quote icon to load just the positive and negative prompts.
+
+5.  To regenerate a Stable Diffusion image that was generated by another SD
+    package, you need to know its text prompt and its _Seed_. Copy-paste the
+    prompt into the prompt box, unset the _Randomize Seed_ control in the
+    control panel, and copy-paste the desired _Seed_ into its text field. When
+    you Invoke, you will get something similar to the original image. It will
+    not be exact unless you also set the correct values for the original
+    sampler, CFG, steps and dimensions, but it will (usually) be close.
+	
+6.  To save an image, right click on it to bring up a menu that will
+	let you download the image, save it to a named image gallery, and
+	copy it to the clipboard, among other things.
+
+#### Upscaling
+
+![Invoke Web Server - Upscaling](../assets/upscaling.png){ align=right width=400px }
+
+"Upscaling" is the process of increasing the size of an image while
+    retaining the sharpness. InvokeAI uses an external library called
+    "ESRGAN" to do this. To invoke upscaling, simply select an image
+    and press the "expanding arrows" button above it. You can select
+    between 2X and 4X upscaling, and adjust the upscaling strength,
+    which has much the same meaning as in facial reconstruction. Try
+    running this on one of your previously-generated images.
+
+### Image to Image
+
+InvokeAI lets you take an existing image and use it as the basis for a new
+creation. You can use any sort of image, including a photograph, a scanned
+sketch, or a digital drawing, as long as it is in PNG or JPEG format.
+
+For this tutorial, we'll use the file named
+[Lincoln-and-Parrot-512.png](../assets/Lincoln-and-Parrot-512.png).
+
+1.  Click on the _Image to Image_ tab icon, which is the second icon
+    from the top on the left-hand side of the screen. This will bring
+    you to a screen similar to the one shown here:
+
+    ![Invoke Web Server - Image to Image Tab](../assets/invoke-web-server-6.png){ width="640px" }
+
+2.  Drag-and-drop the Lincoln-and-Parrot image into the Image panel, or click
+    the blank area to get an upload dialog. The image will load into an area
+    marked _Initial Image_. (The WebUI will also load the most
+    recently-generated image from the gallery into a section on the left, but
+    this image will be replaced in the next step.)
+
+3.  Go to the prompt box and type _old sea captain with raven on shoulder_ and
+    press Invoke. A derived image will appear to the right of the original one:
+
+    ![Invoke Web Server - Image to Image example](../assets/invoke-web-server-7.png){:width="640px"}
+
+4.  Experiment with the different settings. The most influential one in Image to
+    Image is _Denoising Strength_ located about midway down the control
+    panel. By default it is set to 0.75, but can range from 0.0 to 0.99. The
+    higher the value, the more of the original image the AI will replace. A
+    value of 0 will leave the initial image completely unchanged, while 0.99
+    will replace it completely. However, the _Scheduler_ and _CFG Scale_ also
+    influence the final result. You can also generate variations in the same way
+    as described in Text to Image.
+
+5.  What if we only want to change certain part(s) of the image and
+    leave the rest intact? This is called Inpainting, and you can do
+    it in the [Unified Canvas](UNIFIED_CANVAS.md). The Unified Canvas
+    also allows you to extend borders of the image and fill in the
+    blank areas, a process called outpainting.
+
+6.  Would you like to modify a previously-generated image using the Image to
+    Image facility? Easy! While in the Image to Image panel, drag and drop any
+	image in the gallery into the Initial Image area, and it will be ready for
+	use. You can do the same thing with the main image display. Click on the
+	_Send to_ icon to get a menu of
+	commands and choose "Send to Image to Image".
+	
+	![Send To Icon](../assets/send-to-icon.png) 
+
+### Textual Inversion, LoRA and ControlNet
+
+InvokeAI supports several different types of model files that
+extending the capabilities of the main model by adding artistic
+styles, special effects, or subjects. By mixing and matching textual
+inversion, LoRA and ControlNet models, you can achieve many
+interesting and beautiful effects.
+
+We will give an example using a LoRA model named "Ink Scenery". This
+LoRA, which can be downloaded from Civitai (civitai.com), is
+specialized to paint landscapes that look like they were made with
+dripping india ink. To install this LoRA, we first download it and 
+put it into the `autoimport/lora` folder located inside the
+`invokeai` root directory. After restarting the web server, the
+LoRA will now become available for use.
+
+To see this LoRA at work, we'll first generate an image without it
+using the standard `stable-diffusion-v1-5` model. Choose this
+model and enter the prompt "mountains, ink". Here is a typical
+generated image, a mountain range rendered in ink and watercolor
+wash:
+
+![Ink Scenery without LoRA](../assets/lora-example-0.png){ width=512px }
+
+Now let's install and activate the Ink Scenery LoRA. Go to
+https://civitai.com/models/78605/ink-scenery-or and download the LoRA
+model file to `invokeai/autoimport/lora` and restart the web
+server. (Alternatively, you can use [InvokeAI's Web Model
+Manager](../installation/050_INSTALLING_MODELS.md) to download and
+install the LoRA directly by typing its URL into the _Import
+Models_->_Location_ field).
+
+Scroll down the control panel until you get to the LoRA accordion
+section, and open it:
+
+![LoRA Section](../assets/lora-example-1.png){ width=512px }
+
+Click the popup menu and select "Ink scenery". (If it isn't there, then
+the model wasn't installed to the right place, or perhaps you forgot
+to restart the web server.) The LoRA section will change to look like this:
+
+![LoRA Section Loaded](../assets/lora-example-2.png){ width=512px }
+
+Note that there is now a slider control for _Ink scenery_. The slider
+controls how much influence the LoRA model will have on the generated
+image.
+
+Run the "mountains, ink" prompt again and observe the change in style:
+
+![Ink Scenery](../assets/lora-example-3.png){ width=512px }
+
+Try adjusting the weight slider for larger and smaller weights and
+generate the image after each adjustment. The higher the weight, the
+more influence the LoRA will have.
+
+To remove the LoRA completely, just click on its trash can icon.
+
+Multiple LoRAs can be added simultaneously and combined with textual
+inversions and ControlNet models. Please see [Textual Inversions and
+LoRAs](CONCEPTS.md) and [Using ControlNet](CONTROLNET.md) for details.
+
+## Summary
+
+This walkthrough just skims the surface of the many things InvokeAI
+can do. Please see [Features](index.md) for more detailed reference
+guides.
+
+## Acknowledgements
+
+A huge shout-out to the core team working to make the Web GUI a reality,
+including [psychedelicious](https://github.com/psychedelicious),
+[Kyle0654](https://github.com/Kyle0654) and
+[blessedcoolant](https://github.com/blessedcoolant).
+[hipsterusername](https://github.com/hipsterusername) was the team's unofficial
+cheerleader and added tooltips/docs.

docs/features/WEBUIHOTKEYS.md

@@ -0,0 +1,75 @@
+---
+title: WebUI Hotkey List
+---
+
+# :material-keyboard: **WebUI Hotkey List**
+
+## App Hotkeys
+
+| Setting         | Hotkey             |
+| --------------- | ------------------ |
+| ++ctrl+enter++  | Invoke             |
+| ++shift+x++     | Cancel             |
+| ++alt+a++       | Focus Prompt       |
+| ++o++           | Toggle Options     |
+| ++shift+o++     | Pin Options        |
+| ++z++           | Toggle Viewer      |
+| ++g++           | Toggle Gallery     |
+| ++f++           | Maximize Workspace |
+| ++1++ - ++5++   | Change Tabs        |
+| ++"`"++         | Toggle Console     |
+
+## General Hotkeys
+
+| Setting        | Hotkey                 |
+| -------------- | ---------------------- |
+| ++p++          | Set Prompt             |
+| ++s++          | Set Seed               |
+| ++a++          | Set Parameters         |
+| ++shift+r++    | Restore Faces          |
+| ++shift+u++    | Upscale                |
+| ++i++          | Show Info              |
+| ++shift+i++    | Send To Image To Image |
+| ++del++        | Delete Image           |
+| ++esc++        | Close Panels           |
+
+## Gallery Hotkeys
+
+| Setting               | Hotkey                      |
+| ----------------------| --------------------------- |
+| ++arrow-left++        | Previous Image              |
+| ++arrow-right++       | Next Image                  |
+| ++shift+g++           | Toggle Gallery Pin          |
+| ++shift+arrow-up++    | Increase Gallery Image Size |
+| ++shift+arrow-down++  | Decrease Gallery Image Size |
+
+## Unified Canvas Hotkeys
+
+| Setting                           | Hotkey                 |
+| --------------------------------- | ---------------------- |
+| ++b++                             | Select Brush           |
+| ++e++                             | Select Eraser          |
+| ++bracket-left++                  | Decrease Brush Size    |
+| ++bracket-right++                 | Increase Brush Size    |
+| ++shift+bracket-left++            | Decrease Brush Opacity |
+| ++shift+bracket-right++           | Increase Brush Opacity |
+| ++v++                             | Move Tool              |
+| ++shift+f++                       | Fill Bounding Box      |
+| ++del++ / ++backspace++           | Erase Bounding Box     |
+| ++c++                             | Select Color Picker    |
+| ++n++                             | Toggle Snap            |
+| ++"Hold Space"++                  | Quick Toggle Move      |
+| ++q++                             | Toggle Layer           |
+| ++shift+c++                       | Clear Mask             |
+| ++h++                             | Hide Mask              |
+| ++shift+h++                       | Show/Hide Bounding Box |
+| ++shift+m++                       | Merge Visible          |
+| ++shift+s++                       | Save To Gallery        |
+| ++ctrl+c++                        | Copy To Clipboard      |
+| ++shift+d++                       | Download Image         |
+| ++ctrl+z++                        | Undo                   |
+| ++ctrl+y++ / ++ctrl+shift+z++     | Redo                   |
+| ++r++                             | Reset View             |
+| ++arrow-left++                    | Previous Staging Image |
+| ++arrow-right++                   | Next Staging Image     |
+| ++enter++                         | Accept Staging Image   |

docs/features/gallery.md

@@ -1,92 +0,0 @@
----
-title: InvokeAI Gallery Panel
----
-
-# :material-web: InvokeAI Gallery Panel
-
-## Quick guided walkthrough of the Gallery Panel's features
-
-The Gallery Panel is a fast way to review, find, and make use of images you've
-generated and loaded. The Gallery is divided into Boards. The Uncategorized board is always 
-present but you can create your own for better organization.
-
-![image](../assets/gallery/gallery.png)
-
-### Board Display and Settings
-
-At the very top of the Gallery Panel are the boards disclosure and settings buttons.
-
-![image](../assets/gallery/top_controls.png)
-
-The disclosure button shows the name of the currently selected board and allows you to show and hide the board thumbnails (shown in the image below).
-
-![image](../assets/gallery/board_thumbnails.png)
-
-The settings button opens a list of options.
-
-![image](../assets/gallery/board_settings.png)
-
-- ***Image Size*** this slider lets you control the size of the image previews (images of three different sizes).
-- ***Auto-Switch to New Images*** if you turn this on, whenever a new image is generated, it will automatically be loaded into the current image panel on the Text to Image tab and into the result panel on the [Image to Image](IMG2IMG.md) tab. This will happen invisibly if you are on any other tab when the image is generated.
-- ***Auto-Assign Board on Click*** whenever an image is generated or saved, it always gets put in a board. The board it gets put into is marked with AUTO (image of board marked). Turning on Auto-Assign Board on Click will make whichever board you last selected be the destination when you click Invoke. That means you can click Invoke, select a different board, and then click Invoke again and the two images will be put in two different boards. (bold)It's the board selected when Invoke is clicked that's used, not the board that's selected when the image is finished generating.(bold) Turning this off, enables the Auto-Add Board drop down which lets you set one specific board to always put generated images into. This also enables and disables the Auto-add to this Board menu item described below.
-- ***Always Show Image Size Badge*** this toggles whether to show image sizes for each image preview (show two images, one with sizes shown, one without)
-
-Below these two buttons, you'll see the Search Boards text entry area. You use this to search for specific boards by the name of the board.
-Next to it is the Add Board (+) button which lets you add new boards. Boards can be renamed by clicking on the name of the board under its thumbnail and typing in the new name.
-
-### Board Thumbnail Menu
-
-Each board has a context menu (ctrl+click / right-click).
-
-![image](../assets/gallery/thumbnail_menu.png)
-
-- ***Auto-add to this Board*** if you've disabled Auto-Assign Board on Click in the board settings, you can use this option to set this board to be where new images are put.
-- ***Download Board*** this will add all the images in the board into a zip file and provide a link to it in a notification (image of notification)
-- ***Delete Board*** this will delete the board
-> [!CAUTION]
-> This will delete all the images in the board and the board itself.
-
-### Board Contents
-
-Every board is organized by two tabs, Images and Assets.
-
-![image](../assets/gallery/board_tabs.png)
-
-Images are the Invoke-generated images that are placed into the board. Assets are images that you upload into Invoke to be used as an [Image Prompt](https://support.invoke.ai/support/solutions/articles/151000159340-using-the-image-prompt-adapter-ip-adapter-) or in the [Image to Image](IMG2IMG.md) tab.
-
-### Image Thumbnail Menu
-
-Every image generated by Invoke has its generation information stored as text inside the image file itself. This can be read directly by selecting the image and clicking on the Info button ![image](../assets/gallery/info_button.png) in any of the image result panels. 
-
-Each image also has a context menu (ctrl+click / right-click).
-
-![image](../assets/gallery/image_menu.png)
-
- The options are (items marked with an * will not work with images that lack generation information):
-- ***Open in New Tab*** this will open the image alone in a new browser tab, separate from the Invoke interface.
-- ***Download Image*** this will trigger your browser to download the image.
-- ***Load Workflow **** this will load any workflow settings into the Workflow tab and automatically open it.
-- ***Remix Image **** this will load all of the image's generation information, (bold)excluding its Seed, into the left hand control panel
-- ***Use Prompt **** this will load only the image's text prompts into the left-hand control panel
-- ***Use Seed **** this will load only the image's Seed into the left-hand control panel
-- ***Use All **** this will load all of the image's generation information into the left-hand control panel
-- ***Send to Image to Image*** this will put the image into the left-hand panel in the Image to Image tab and automatically open it
-- ***Send to Unified Canvas*** This will (bold)replace whatever is already present(bold) in the Unified Canvas tab with the image and automatically open the tab
-- ***Change Board*** this will oipen a small window that will let you move the image to a different board. This is the same as dragging the image to that board's thumbnail.
-- ***Star Image*** this will add the image to the board's list of starred images that are always kept at the top of the gallery. This is the same as clicking on the star on the top right-hand side of the image that appears when you hover over the image with the mouse
-- ***Delete Image*** this will delete the image from the board
-> [!CAUTION] 
-> This will delete the image entirely from Invoke.
-
-## Summary
-
-This walkthrough only covers the Gallery interface and Boards. Actually generating images is handled by [Prompts](PROMPTS.md), the [Image to Image](IMG2IMG.md) tab, and the [Unified Canvas](UNIFIED_CANVAS.md).
-
-## Acknowledgements
-
-A huge shout-out to the core team working to make the Web GUI a reality,
-including [psychedelicious](https://github.com/psychedelicious),
-[Kyle0654](https://github.com/Kyle0654) and
-[blessedcoolant](https://github.com/blessedcoolant).
-[hipsterusername](https://github.com/hipsterusername) was the team's unofficial
-cheerleader and added tooltips/docs.

docs/features/index.md

@@ -0,0 +1,62 @@
+---
+title: Overview
+---
+
+Here you can find the documentation for InvokeAI's various features.
+
+## The [Getting Started Guide](../help/gettingStartedWithAI) 
+A getting started guide for those new to AI image generation. 
+
+## The Basics
+### * The [Web User Interface](WEB.md)
+Guide to the Web interface. Also see the [WebUI Hotkeys Reference Guide](WEBUIHOTKEYS.md)
+
+### * The [Unified Canvas](UNIFIED_CANVAS.md)
+Build complex scenes by combine and modifying multiple images in a stepwise
+fashion. This feature combines img2img, inpainting and outpainting in
+a single convenient digital artist-optimized user interface.
+
+## Image Generation
+### * [Prompt Engineering](PROMPTS.md)
+Get the images you want with the InvokeAI  prompt engineering language.
+
+### * The [LoRA, LyCORIS, LCM-LoRA Models](CONCEPTS.md)
+Add custom subjects and styles using a variety of fine-tuned models.
+
+### * [ControlNet](CONTROLNET.md)
+Learn how to install and use ControlNet models for fine control over
+image output.
+
+### * [Image-to-Image Guide](IMG2IMG.md)
+Use a seed image to build new creations.
+
+## Model Management
+
+### * [Model Installation](../installation/050_INSTALLING_MODELS.md)
+Learn how to import third-party models and switch among them. This
+guide also covers optimizing models to load quickly.
+
+### * [Merging Models](MODEL_MERGING.md)
+Teach an old model new tricks. Merge 2-3 models together to create a
+new model that combines characteristics of the originals.
+
+### * [Textual Inversion](TEXTUAL_INVERSIONS.md)
+Personalize models by adding your own style or subjects.
+
+## Other Features
+
+### * [The NSFW Checker](WATERMARK+NSFW.md)
+Prevent InvokeAI from displaying unwanted racy images.
+
+### * [Controlling Logging](LOGGING.md)
+Control how InvokeAI logs status messages.
+
+### * [Command-line Utilities](UTILITIES.md)
+A list of the command-line utilities available with InvokeAI.
+
+<!-- OUT OF DATE
+### * [Miscellaneous](OTHER.md)
+Run InvokeAI on Google Colab, generate images with repeating patterns,
+batch process a file of prompts, increase the "creativity" of image
+generation by adding initial noise, and more!
+-->

docs/help/FAQ.md

@@ -2,7 +2,7 @@
 
 !!! info "How to Reinstall"
 
-    Many issues can be resolved by re-installing the application. You won't lose any data by re-installing. We suggest downloading the [latest release](https://github.com/invoke-ai/InvokeAI/releases/latest) and using it to re-install the application. Consult the [installer guide](./installation/installer.md) for more information.
+    Many issues can be resolved by re-installing the application. You won't lose any data by re-installing. We suggest downloading the [latest release](https://github.com/invoke-ai/InvokeAI/releases/latest) and using it to re-install the application. Consult the [installer guide](../installation/010_INSTALL_AUTOMATED.md) for more information.
 
     When you run the installer, you'll have an option to select the version to install. If you aren't ready to upgrade, you choose the current version to fix a broken install.
 
@@ -40,25 +40,6 @@ Follow the same steps to scan and import the missing models.
 - Check the `ram` setting in `invokeai.yaml`. This setting tells Invoke how much of your system RAM can be used to cache models. Having this too high or too low can slow things down. That said, it's generally safest to not set this at all and instead let Invoke manage it.
 - Check the `vram` setting in `invokeai.yaml`. This setting tells Invoke how much of your GPU VRAM can be used to cache models. Counter-intuitively, if this setting is too high, Invoke will need to do a lot of shuffling of models as it juggles the VRAM cache and the currently-loaded model. The default value of 0.25 is generally works well for GPUs without 16GB or more VRAM. Even on a 24GB card, the default works well.
 - Check that your generations are happening on your GPU (if you have one). InvokeAI will log what is being used for generation upon startup. If your GPU isn't used, re-install to ensure the correct versions of torch get installed.
-- If you are on Windows, you may have exceeded your GPU's VRAM capacity and are using slower [shared GPU memory](#shared-gpu-memory-windows). There's a guide to opt out of this behaviour in the linked FAQ entry.
-
-## Shared GPU Memory (Windows)
-
-!!! tip "Nvidia GPUs with driver 536.40"
-
-    This only applies to current Nvidia cards with driver 536.40 or later, released in June 2023.
-
-When the GPU doesn't have enough VRAM for a task, Windows is able to allocate some of its CPU RAM to the GPU. This is much slower than VRAM, but it does allow the system to generate when it otherwise might no have enough VRAM.
-
-When shared GPU memory is used, generation slows down dramatically - but at least it doesn't crash.
-
-If you'd like to opt out of this behavior and instead get an error when you exceed your GPU's VRAM, follow [this guide from Nvidia](https://nvidia.custhelp.com/app/answers/detail/a_id/5490).
-
-Here's how to get the python path required in the linked guide:
-
-- Run `invoke.bat`.
-- Select option 2 for developer console.
-- At least one python path will be printed. Copy the path that includes your invoke installation directory (typically the first).
 
 ## Installer cannot find python (Windows)
 
@@ -92,7 +73,7 @@ Most example images with prompts that you'll find on the internet have been gene
 
 During a zip file installation or an update, installation stops with an error like this:
 
-![broken-dependency-screenshot](./assets/troubleshooting/broken-dependency.png){:width="800px"}
+![broken-dependency-screenshot](../assets/troubleshooting/broken-dependency.png){:width="800px"}
 
 To resolve this, re-install the application as described above.
 
@@ -154,18 +135,6 @@ This is caused by an invalid setting in the `invokeai.yaml` configuration file.
 
 Check the [configuration docs] for more detail about the settings and how to specify them.
 
-## `ModuleNotFoundError: No module named 'controlnet_aux'`
-
-`controlnet_aux` is a dependency of Invoke and appears to have been packaged or distributed strangely. Sometimes, it doesn't install correctly. This is outside our control.
-
-If you encounter this error, the solution is to remove the package from the `pip` cache and re-run the Invoke installer so a fresh, working version of `controlnet_aux` can be downloaded and installed:
-
-- Run the Invoke launcher
-- Choose the developer console option
-- Run this command: `pip cache remove controlnet_aux`
-- Close the terminal window
-- Download and run the [installer][latest release], selecting your current install location
-
 ## Out of Memory Issues
 
 The models are large, VRAM is expensive, and you may find yourself
@@ -196,22 +165,6 @@ tips to reduce the problem:
     === "12GB VRAM GPU"
 
         This should be sufficient to generate larger images up to about 1280x1280.
-  
-## Checkpoint Models Load Slowly or Use Too Much RAM
-
-The difference between diffusers models (a folder containing multiple
-subfolders) and checkpoint models (a file ending with .safetensors or
-.ckpt) is that InvokeAI is able to load diffusers models into memory
-incrementally, while checkpoint models must be loaded all at
-once. With very large models, or systems with limited RAM, you may
-experience slowdowns and other memory-related issues when loading
-checkpoint models.
-
-To solve this, go to the Model Manager tab (the cube), select the
-checkpoint model that's giving you trouble, and press the "Convert"
-button in the upper right of your browser window. This will convert the
-checkpoint into a diffusers model, after which loading should be
-faster and less memory-intensive.
 
 ## Memory Leak (Linux)
 
@@ -251,10 +204,10 @@ To better understand how the `glibc` memory allocator works, see these reference
 
 Note the differences between memory allocated as chunks in an arena vs. memory allocated with `mmap`. Under `glibc`'s default configuration, most model tensors get allocated as chunks in an arena making them vulnerable to the problem of fragmentation.
 
-[model install docs]: ./installation/models.md
-[system requirements]: ./installation/requirements.md
+[model install docs]: ../installation/050_INSTALLING_MODELS.md
+[system requirements]: ../installation/INSTALL_REQUIREMENTS.md
 [latest release]: https://github.com/invoke-ai/InvokeAI/releases/latest
 [create an issue]: https://github.com/invoke-ai/InvokeAI/issues
 [discord]: https://discord.gg/ZmtBAhwWhy
-[configuration docs]: ./configuration.md
+[configuration docs]: ../features/CONFIGURATION.md
 [access token]: https://huggingface.co/docs/hub/security-tokens#how-to-manage-user-access-tokens

docs/help/diffusion.md

@@ -20,7 +20,7 @@ When you generate an image using text-to-image, multiple steps occur in latent s
 4. The VAE decodes the final latent image from latent space into image space.
 
 Image-to-image is a similar process, with only step 1 being different:
-1. The input image is encoded from image space into latent space by the VAE. Noise is then added to the input latent image. Denoising Strength dictates how many noise steps are added, and the amount of noise added at each step. A Denoising Strength of 0 means there are 0 steps and no noise added, resulting in an unchanged image, while a Denoising Strength of 1 results in the image being completely replaced with noise and a full set of denoising steps are performance. The process is then the same as steps 2-4 in the text-to-image process. 
+1. The input image is encoded from image space into latent space by the VAE. Noise is then added to the input latent image. Denoising Strength dictates how may noise steps are added, and the amount of noise added at each step. A Denoising Strength of 0 means there are 0 steps and no noise added, resulting in an unchanged image, while a Denoising Strength of 1 results in the image being completely replaced with noise and a full set of denoising steps are performance. The process is then the same as steps 2-4 in the text-to-image process. 
 
 Furthermore, a model provides the CLIP prompt tokenizer, the VAE, and a U-Net (where noise prediction occurs given a prompt and initial noise tensor).
 

docs/img/invoke-symbol-wht-lrg.svg

@@ -1,3 +0,0 @@
-<svg width="66" height="66" viewBox="0 0 66 66" fill="none" xmlns="http://www.w3.org/2000/svg">
-<path d="M43.9137 16H63.1211V3H3.12109V16H22.3285L43.9137 50H63.1211V63H3.12109V50H22.3285" stroke="white" stroke-width="5"/>
-</svg>

docs/index.md

@@ -1,75 +1,181 @@
 ---
-title: Invoke
+title: Home
 ---
 
 <!--
-  The docs are generated with using mkdocs: https://www.mkdocs.org/
+  The Docs you find here (/docs/*) are built and deployed via mkdocs. If you want to run a local version to verify your changes, it's as simple as::
 
-  To preview the docs locally, first install the requirements:
-  ```sh
-  pip install -e ".[docs]"
+  ```bash
+  pip install -r docs/requirements-mkdocs.txt
+  mkdocs serve
   ```
-
-  Then run the mkdocs server with `mkdocs serve`, or, on Unix systems, `make docs`.
 -->
 
 <!-- CSS styling -->
+<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.1/css/fontawesome.min.css">
+<style>
+    .button {
+      width: 100%;
+      max-width: 100%;
+      height: 50px;
+      background-color: #35A4DB;
+      color: #fff;
+      font-size: 16px;
+      border: none;
+      cursor: pointer;
+      border-radius: 0.2rem;
+    }
+
+    .button-container {
+      display: grid;
+      grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+      gap: 20px;
+      justify-content: center;
+    }
+
+    .button:hover {
+      background-color: #526CFE;
+    }
+</style>
+
+
 
 <div align="center" markdown>
 
+
 [![project logo](https://github.com/invoke-ai/InvokeAI/assets/31807370/6e3728c7-e90e-4711-905c-3b55844ff5be)](https://github.com/invoke-ai/InvokeAI)
 
 [![discord badge]][discord link]
+
 [![latest release badge]][latest release link]
 [![github stars badge]][github stars link]
 [![github forks badge]][github forks link]
-[![latest commit to main badge]][latest commit to main link]
+
+<!-- [![CI checks on main badge]][ci checks on main link]
+[![CI checks on dev badge]][ci checks on dev link]
+[![latest commit to dev badge]][latest commit to dev link] -->
+
 [![github open issues badge]][github open issues link]
 [![github open prs badge]][github open prs link]
 
+[ci checks on dev badge]:
+  https://flat.badgen.net/github/checks/invoke-ai/InvokeAI/development?label=CI%20status%20on%20dev&cache=900&icon=github
+[ci checks on dev link]:
+  https://github.com/invoke-ai/InvokeAI/actions?query=branch%3Adevelopment
+[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/workflows/test-invoke-conda.yml
 [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
-[github forks link]: https://useful-forks.github.io/?repo=lstein%2Fstable-diffusion
-[github open issues badge]: https://flat.badgen.net/github/open-issues/invoke-ai/InvokeAI?icon=github
-[github open issues link]: https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen
-[github open prs badge]: https://flat.badgen.net/github/open-prs/invoke-ai/InvokeAI?icon=github
-[github open prs link]: https://github.com/invoke-ai/InvokeAI/pulls?q=is%3Apr+is%3Aopen
-[github stars badge]: https://flat.badgen.net/github/stars/invoke-ai/InvokeAI?icon=github
+[github forks badge]:
+  https://flat.badgen.net/github/forks/invoke-ai/InvokeAI?icon=github
+[github forks link]:
+  https://useful-forks.github.io/?repo=lstein%2Fstable-diffusion
+[github open issues badge]:
+  https://flat.badgen.net/github/open-issues/invoke-ai/InvokeAI?icon=github
+[github open issues link]:
+  https://github.com/invoke-ai/InvokeAI/issues?q=is%3Aissue+is%3Aopen
+[github open prs badge]:
+  https://flat.badgen.net/github/open-prs/invoke-ai/InvokeAI?icon=github
+[github open prs link]:
+  https://github.com/invoke-ai/InvokeAI/pulls?q=is%3Apr+is%3Aopen
+[github stars badge]:
+  https://flat.badgen.net/github/stars/invoke-ai/InvokeAI?icon=github
 [github stars link]: https://github.com/invoke-ai/InvokeAI/stargazers
-[latest commit to main badge]: https://flat.badgen.net/github/last-commit/invoke-ai/InvokeAI/main?icon=github&color=yellow&label=last%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 commit to dev badge]:
+  https://flat.badgen.net/github/last-commit/invoke-ai/InvokeAI/development?icon=github&color=yellow&label=last%20dev%20commit&cache=900
+[latest commit to dev 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
 
 </div>
 
-<a href="https://github.com/invoke-ai/InvokeAI">Invoke</a> 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.
+<a href="https://github.com/invoke-ai/InvokeAI">InvokeAI</a> is an
+implementation of Stable Diffusion, the open source text-to-image and
+image-to-image generator. It provides a streamlined process with various new
+features and options to aid the image generation process. It runs on Windows,
+Mac and Linux machines, and runs on GPU cards with as little as 4 GB of RAM.
 
 <div align="center"><img src="assets/invoke-web-server-1.png" width=640></div>
 
-## Installation
+## :octicons-link-24: Quick Links
 
-The [installer script](installation/installer.md) is the easiest way to install and update the application.
+<div class="button-container">
+    <a href="installation/INSTALLATION"> <button class="button">Installation</button> </a>
+    <a href="features/"> <button class="button">Features</button> </a>
+    <a href="help/gettingStartedWithAI/"> <button class="button">Getting Started</button> </a>
+    <a href="help/FAQ/"> <button class="button">FAQ</button> </a>
+    <a href="contributing/CONTRIBUTING/"> <button class="button">Contributing</button> </a>
+    <a href="https://github.com/invoke-ai/InvokeAI/"> <button class="button">Code and Downloads</button> </a>
+    <a href="https://github.com/invoke-ai/InvokeAI/issues"> <button class="button">Bug Reports </button> </a>
+    <a href="https://discord.gg/ZmtBAhwWhy"> <button class="button"> Join the Discord Server!</button> </a>
+</div>
 
-You can also install Invoke as python package [via PyPI](installation/manual.md) or [docker](installation/docker.md).
 
-See the [installation section](./installation/index.md) for more information.
+## :octicons-gift-24: InvokeAI Features
 
-## Help
+### Installation
+  - [Automated Installer](installation/010_INSTALL_AUTOMATED.md)
+  - [Manual Installation](installation/020_INSTALL_MANUAL.md)
+  - [Docker Installation](installation/040_INSTALL_DOCKER.md)
 
-Please first check the [FAQ](./faq.md) to see if there is a fix for your issue or answer to your question.
+### The InvokeAI Web Interface
+- [WebUI overview](features/WEB.md)
+- [WebUI hotkey reference guide](features/WEBUIHOTKEYS.md)
+- [WebUI Unified Canvas for Img2Img, inpainting and outpainting](features/UNIFIED_CANVAS.md)
 
-If you still have a problem, [create an issue](https://github.com/invoke-ai/InvokeAI/issues) or ask for help on [Discord](https://discord.gg/ZmtBAhwWhy).
+<!-- separator -->
 
-## Training
+### Image Management
+- [Image2Image](features/IMG2IMG.md)
+- [Adding custom styles and subjects](features/CONCEPTS.md)
+- [Upscaling and Face Reconstruction](features/POSTPROCESS.md)
+- [Other Features](features/OTHER.md)
 
-Invoke Training has moved to its own repository, with a dedicated UI for accessing common scripts like Textual Inversion and LoRA training.
+<!-- separator -->
+### Model Management
+- [Installing](installation/050_INSTALLING_MODELS.md)
+- [Model Merging](features/MODEL_MERGING.md)
+- [ControlNet Models](features/CONTROLNET.md)
+- [Style/Subject Concepts and Embeddings](features/CONCEPTS.md)
+- [Watermarking and the Not Safe for Work (NSFW) Checker](features/WATERMARK+NSFW.md)
+<!-- seperator -->
+### Prompt Engineering
+- [Prompt Syntax](features/PROMPTS.md)
 
-You can find more by visiting the repo at <https://github.com/invoke-ai/invoke-training>.
+### InvokeAI Configuration
+- [Guide to InvokeAI Runtime Settings](features/CONFIGURATION.md)
+- [Database Maintenance and other Command Line Utilities](features/UTILITIES.md)
 
-## Contributing
+## :material-target: Troubleshooting
 
-We welcome contributions, big and small. Please review our [contributing guide](contributing/index.md) if you'd like make a contribution.
+Please check out our **[:material-frequently-asked-questions:
+FAQ](help/FAQ/)** to
+get solutions for common installation problems and other issues.
+
+## :octicons-repo-push-24: 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. 
+
+[Please take a look at our Contribution documentation to learn more about contributing to InvokeAI. 
+](contributing/CONTRIBUTING.md)
+
+## :octicons-person-24: Contributors
+
+This software is a combined effort of various people from across the world.
+[Check out the list of all these amazing people](other/CONTRIBUTORS.md). We
+thank them for their time, hard work and effort.
+
+## :octicons-question-24: Support
+
+For support, please use this repository's GitHub Issues tracking service. Feel
+free to send me an email if you use and like the script.
+
+Original portions of the software are Copyright (c) 2022-23
+by [The InvokeAI Team](https://github.com/invoke-ai).
 
-This software is a combined effort of [people across the world](contributing/contributors.md). We thank them for their time, hard work and effort!

docs/installation/010_INSTALL_AUTOMATED.md

@@ -1,12 +1,8 @@
-# Automatic Install & Updates
+# Automatic Install
 
-!!! tip "Use the installer to update"
+The installer is used for both new installs and updates.
 
-    Using the installer for updates will not erase any of your data (images, models, boards, etc). It only updates the core libraries used to run Invoke.
-
-    Simply use the same path you installed to originally to update your existing installation.
-
-Both release and pre-release versions can be installed using the installer. It also supports install through a wheel if needed.
+Both release and pre-release versions can be installed using it. It also supports install a wheel if needed.
 
 Be sure to review the [installation requirements] and ensure your system has everything it needs to install Invoke.
 
@@ -74,18 +70,12 @@ Find the install location you selected earlier. Double-click the launcher script
 
 Choose the first option to run the UI. After a series of startup messages, you'll see something like this:
 
-```sh
+```
 Uvicorn running on http://127.0.0.1:9090 (Press CTRL+C to quit)
 ```
 
 Copy the URL into your browser and you should see the UI.
 
-## Improved Outpainting with PatchMatch
-
-PatchMatch is an extra add-on that can improve outpainting. Windows users are in luck - it works out of the box.
-
-On macOS and Linux, a few extra steps are needed to set it up. See the [PatchMatch installation guide](./patchmatch.md).
-
 ## First-time Setup
 
 You will need to [install some models] before you can generate.
@@ -94,7 +84,7 @@ Check the [configuration docs] for details on configuring the application.
 
 ## Updating
 
-Updating is exactly the same as installing - download the latest installer, choose the latest version, enter your existing installation path, and the app will update. None of your data (images, models, boards, etc) will be erased.
+Updating is exactly the same as installing - download the latest installer, choose the latest version and off you go.
 
 !!! info "Dependency Resolution Issues"
 
@@ -106,10 +96,10 @@ Updating is exactly the same as installing - download the latest installer, choo
 
 If you have installation issues, please review the [FAQ]. You can also [create an issue] or ask for help on [discord].
 
-[installation requirements]: ./requirements.md
-[FAQ]: ../faq.md
-[install some models]: ./models.md
-[configuration docs]: ../configuration.md
+[installation requirements]: INSTALLATION.md#installation-requirements
+[FAQ]: ../help/FAQ.md
+[install some models]: 050_INSTALLING_MODELS.md
+[configuration docs]: ../features/CONFIGURATION.md
 [latest release]: https://github.com/invoke-ai/InvokeAI/releases/latest
 [create an issue]: https://github.com/invoke-ai/InvokeAI/issues
 [discord]: https://discord.gg/ZmtBAhwWhy

docs/installation/020_INSTALL_MANUAL.md

@@ -1,36 +1,40 @@
 # Manual Install
 
-!!! warning
+!!! warning "This is for Advanced Users"
 
     **Python experience is mandatory.**
 
-    If you want to use Invoke locally, you should probably use the [installer](./installer.md).
-
-    If you want to contribute to Invoke, instead follow the [dev environment](../contributing/dev-environment.md) guide.
+## Introduction
 
 InvokeAI is distributed as a python package on PyPI, installable with `pip`. There are a few things that are handled by the installer and launcher that you'll need to manage manually, described in this guide.
 
-## Requirements
+### Requirements
 
-Before you start, go through the [installation requirements](./requirements.md).
+Before you start, go through the [installation requirements].
 
-## Walkthrough
+### Installation Walkthrough
 
-1. Create a directory to contain your InvokeAI library, configuration files, and models. This is known as the "runtime" or "root" directory, and typically lives in your home directory under the name `invokeai`.
+1. Create a directory to contain your InvokeAI library, configuration
+    files, and models. This is known as the "runtime" or "root"
+    directory, and often lives in your home directory under the name `invokeai`.
+
+    We will refer to this directory as `INVOKEAI_ROOT`. For convenience, create an environment variable pointing to the directory.
 
     === "Linux/macOS"
 
         ```bash
-        mkdir ~/invokeai
+        export INVOKEAI_ROOT=~/invokeai
+        mkdir $INVOKEAI_ROOT
         ```
 
     === "Windows (PowerShell)"
 
         ```bash
-        mkdir $Home/invokeai
+        Set-Variable -Name INVOKEAI_ROOT -Value $Home/invokeai
+        mkdir $INVOKEAI_ROOT
         ```
 
-1. Enter the root directory and create a virtual Python environment within it named `.venv`.
+1. Enter the root (invokeai) directory and create a virtual Python environment within it named `.venv`.
 
     !!! warning "Virtual Environment Location"
 
@@ -38,19 +42,10 @@ Before you start, go through the [installation requirements](./requirements.md).
 
         If you choose a different location for the venv, then you _must_ set the `INVOKEAI_ROOT` environment variable or specify the root directory using the `--root` CLI arg.
 
-    === "Linux/macOS"
-
-        ```bash
-        cd ~/invokeai
-        python3 -m venv .venv --prompt InvokeAI
-        ```
-
-    === "Windows (PowerShell)"
-
-        ```bash
-        cd $Home/invokeai
-        python3 -m venv .venv --prompt InvokeAI
-        ```
+    ```terminal
+    cd $INVOKEAI_ROOT
+    python3 -m venv .venv --prompt InvokeAI
+    ```
 
 1. Activate the new environment:
 
@@ -68,11 +63,13 @@ Before you start, go through the [installation requirements](./requirements.md).
 
     !!! info "Permissions Error (Windows)"
 
-        If you get a permissions error at this point, run this command and try again.
+        If you get a permissions error at this point, run this command and try again
 
         `Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser`
 
-    The command-line prompt should change to to show `(InvokeAI)`, indicating the venv is active.
+    The command-line prompt should change to to show `(InvokeAI)` at the beginning of the prompt.
+
+    The following steps should be run while inside the `INVOKEAI_ROOT` directory.
 
 1. Make sure that pip is installed in your virtual environment and up to date:
 
@@ -82,19 +79,23 @@ Before you start, go through the [installation requirements](./requirements.md).
 
 1. Install the InvokeAI Package. The base command is `pip install InvokeAI --use-pep517`, but you may need to change this depending on your system and the desired features.
 
-    - You may need to provide an [extra index URL](https://pip.pypa.io/en/stable/cli/pip_install/#cmdoption-extra-index-url). Select your platform configuration using [this tool on the PyTorch website](https://pytorch.org/get-started/locally/). Copy the `--extra-index-url` string from this and append it to your install command.
+    - You may need to provide an [extra index URL]. Select your platform configuration using [this tool on the PyTorch website]. Copy the `--extra-index-url` string from this and append it to your install command.
 
-        ```bash
-        pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu121
-        ```
+        !!! example "Install with an extra index URL"
 
-    - If you have a CUDA GPU and want to install with `xformers`, you need to add an option to the package name. Note that `xformers` is not strictly necessary. PyTorch includes an implementation of the SDP attention algorithm with similar performance for most GPUs.
+            ```bash
+            pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/cu121
+            ```
 
-        ```bash
-        pip install "InvokeAI[xformers]" --use-pep517
-        ```
+    - If you have a CUDA GPU and want to install with `xformers`, you need to add an option to the package name. Note that `xformers` is not necessary. PyTorch includes an implementation of the SDP attention algorithm with the same performance.
 
-1. Deactivate and reactivate your venv so that the invokeai-specific commands become available in the environment:
+        !!! example "Install with `xformers`"
+
+            ```bash
+            pip install "InvokeAI[xformers]" --use-pep517
+            ```
+
+1. Deactivate and reactivate your runtime directory so that the invokeai-specific commands become available in the environment:
 
     === "Linux/macOS"
 
@@ -115,4 +116,4 @@ Before you start, go through the [installation requirements](./requirements.md).
 
     !!! warning
 
-        If the virtual environment is _not_ inside the root directory, then you _must_ specify the path to the root directory with `--root \path\to\invokeai` or the `INVOKEAI_ROOT` environment variable.
+        If the virtual environment is _not_ inside the root directory, then you _must_ specify the path to the root directory with `--root_dir \path\to\invokeai` or the `INVOKEAI_ROOT` environment variable.

docs/installation/040_INSTALL_DOCKER.md

@@ -0,0 +1,112 @@
+---
+title: Installing with Docker
+---
+
+# :fontawesome-brands-docker: Docker
+
+!!! warning "macOS and AMD GPU Users"
+
+    We highly recommend to Install InvokeAI locally using [these instructions](INSTALLATION.md),
+    because Docker containers can not access the GPU on macOS.
+
+!!! warning "AMD GPU Users"
+
+    Container support for AMD GPUs has been reported to work by the community, but has not received
+    extensive testing. Please make sure to set the `GPU_DRIVER=rocm` environment variable (see below), and
+    use the `build.sh` script to build the image for this to take effect at build time.
+
+!!! tip "Linux and Windows Users"
+
+    For optimal performance, configure your Docker daemon to access your machine's GPU.
+    Docker Desktop on Windows [includes GPU support](https://www.docker.com/blog/wsl-2-gpu-support-for-docker-desktop-on-nvidia-gpus/).
+    Linux users should install and configure the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
+
+## Why containers?
+
+They provide a flexible, reliable way to build and deploy InvokeAI.
+See [Processes](https://12factor.net/processes) under the Twelve-Factor App
+methodology for details on why running applications in such a stateless fashion is important.
+
+The container is configured for CUDA by default, but can be built to support AMD GPUs
+by setting the `GPU_DRIVER=rocm` environment variable at Docker image build time.
+
+Developers on Apple silicon (M1/M2/M3): You
+[can't access your GPU cores from Docker containers](https://github.com/pytorch/pytorch/issues/81224)
+and performance is reduced compared with running it directly on macOS but for
+development purposes it's fine. Once you're done with development tasks on your
+laptop you can build for the target platform and architecture and deploy to
+another environment with NVIDIA GPUs on-premises or in the cloud.
+
+## TL;DR
+
+This assumes properly configured Docker on Linux or Windows/WSL2. Read on for detailed customization options.
+
+    ```bash
+    # docker compose commands should be run from the `docker` directory
+    cd docker
+    docker compose up
+    ```
+
+## Installation in a Linux container (desktop)
+
+### Prerequisites
+
+#### Install [Docker](https://github.com/santisbon/guides#docker)
+
+On the [Docker Desktop app](https://docs.docker.com/get-docker/), go to
+Preferences, Resources, Advanced. Increase the CPUs and Memory to avoid this
+[Issue](https://github.com/invoke-ai/InvokeAI/issues/342). You may need to
+increase Swap and Disk image size too.
+
+#### Get a Huggingface-Token
+
+Besides the Docker Agent you will need an Account on
+[huggingface.co](https://huggingface.co/join).
+
+After you succesfully registered your account, go to
+[huggingface.co/settings/tokens](https://huggingface.co/settings/tokens), create
+a token and copy it, since you will need in for the next step.
+
+### Setup
+
+Set up your environmnent variables. In the `docker` directory, make a copy of `.env.sample` and name it `.env`. Make changes as necessary.
+
+Any environment variables supported by InvokeAI can be set here - please see the [CONFIGURATION](../features/CONFIGURATION.md) for further detail.
+
+At a minimum, you might want to set the `INVOKEAI_ROOT` environment variable
+to point to the location where you wish to store your InvokeAI models, configuration, and outputs.
+
+<figure markdown>
+
+| Environment-Variable <img width="220" align="right"/> | Default value <img width="360" align="right"/> | Description                                                                                                                                                                                       |
+| ----------------------------------------------------- | ---------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `INVOKEAI_ROOT`                                       | `~/invokeai`                                   | **Required** - the location of your InvokeAI root directory. It will be created if it does not exist.
+| `HUGGING_FACE_HUB_TOKEN`                              |                                                | InvokeAI will work without it, but some of the integrations with HuggingFace (like downloading from models from private repositories) may not work|
+| `GPU_DRIVER`                                          | `cuda`                                         | Optionally change this to `rocm` to build the image for AMD GPUs. NOTE: Use the `build.sh` script to build the image for this to take effect.
+
+</figure>
+
+#### Build the Image
+
+Use the standard `docker compose build` command from within the `docker` directory.
+
+If using an AMD GPU:
+    a: set the `GPU_DRIVER=rocm` environment variable in `docker-compose.yml` and continue using `docker compose build` as usual, or
+    b: set `GPU_DRIVER=rocm` in the `.env` file and use the `build.sh` script, provided for convenience
+
+#### Run the Container
+
+Use the standard `docker compose up` command, and generally the `docker compose` [CLI](https://docs.docker.com/compose/reference/) as usual.
+
+Once the container starts up (and configures the InvokeAI root directory if this is a new installation), you can access InvokeAI at [http://localhost:9090](http://localhost:9090)
+
+## Troubleshooting / FAQ
+
+- Q: I am running on Windows under WSL2, and am seeing a "no such file or directory" error.
+- A: Your `docker-entrypoint.sh` file likely has Windows (CRLF) as opposed to Unix (LF) line endings,
+    and you may have cloned this repository before the issue was fixed. To solve this, please change
+    the line endings in the `docker-entrypoint.sh` file to `LF`. You can do this in VSCode
+    (`Ctrl+P` and search for "line endings"), or by using the `dos2unix` utility in WSL.
+    Finally, you may delete `docker-entrypoint.sh` followed by  `git pull; git checkout docker/docker-entrypoint.sh`
+    to reset the file to its most recent version.
+    For more information on this issue, please see the [Docker Desktop documentation](https://docs.docker.com/desktop/troubleshoot/topics/#avoid-unexpected-syntax-errors-use-unix-style-line-endings-for-files-in-containers)

docs/installation/050_INSTALLING_MODELS.md

@@ -1,4 +1,4 @@
-# Models
+# Installing Models
 
 ## Checkpoint and Diffusers Models
 
@@ -15,7 +15,7 @@ Today, there are thousands of models, fine tuned to excel at specific styles, ge
     - `safetensors`: Single file, like `.ckpt` files. Prevents malware from lurking in a model.
     - `diffusers`: Splits the model components into separate files, allowing very fast loading.
 
-    InvokeAI supports all three formats.
+    InvokeAI supports all three formats. Our backend will convert models to `diffusers` format before running them. This is a transparent process.
 
 ## Starter Models
 
@@ -27,7 +27,7 @@ Some models carry license terms that limit their use in commercial applications
 
 ## Other Models
 
-There are a few ways to install other models:
+You can install other models using the Model Manager. You'll find tabs for the following install methods:
 
 - **URL or Local Path**: Provide the path to a model on your computer, or a direct link to the model. Some sites require you to use an API token to download models, which you can [set up in the config file].
 - **HuggingFace**: Paste a HF Repo ID to install it. If there are multiple models in the repo, you'll get a list to choose from. Repo IDs look like this: `XpucT/Deliberate`. There is a copy button on each repo to copy the ID.
@@ -49,4 +49,4 @@ In this situation, you may need to provide some additional information to identi
 
     Add `:v2` to the repo ID and use that when installing the model: `monster-labs/control_v1p_sd15_qrcode_monster:v2`
 
-[set up in the config file]: ../configuration.md#model-marketplace-api-keys
+[set up in the config file]: ../../features/CONFIGURATION#model-marketplace-api-keys

docs/installation/060_INSTALL_PATCHMATCH.md

@@ -0,0 +1,110 @@
+---
+title: Installing PyPatchMatch
+---
+
+# :material-image-size-select-large: Installing PyPatchMatch
+
+pypatchmatch is a Python module for inpainting images. It is not needed to run
+InvokeAI, but it greatly improves the quality of inpainting and outpainting and
+is recommended.
+
+Unfortunately, it is a C++ optimized module and installation can be somewhat
+challenging. This guide leads you through the steps.
+
+## Windows
+
+You're in luck! On Windows platforms PyPatchMatch will install automatically on
+Windows systems with no extra intervention.
+
+## Macintosh
+
+You need to have opencv installed so that pypatchmatch can be built:
+
+```bash
+brew install opencv
+```
+
+The next time you start `invoke`, after successfully installing opencv, pypatchmatch will be built.
+
+## Linux
+
+Prior to installing PyPatchMatch, you need to take the following steps:
+
+### Debian Based Distros
+
+1. Install the `build-essential` tools:
+
+    ```sh
+    sudo apt update
+    sudo apt install build-essential
+    ```
+
+2. Install `opencv`:
+
+    ```sh
+    sudo apt install python3-opencv libopencv-dev
+    ```
+
+3. Activate the environment you use for invokeai, either with `conda` or with a
+   virtual environment.
+
+4. Install pypatchmatch:
+
+    ```sh
+    pip install pypatchmatch
+    ```
+
+5. Confirm that pypatchmatch is installed. At the command-line prompt enter
+   `python`, and then at the `>>>` line type
+   `from patchmatch import patch_match`: It should look like the following:
+
+    ```py
+    Python 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] on linux
+    Type "help", "copyright", "credits" or "license" for more information.
+    >>> from patchmatch import patch_match
+    Compiling and loading c extensions from "/home/lstein/Projects/InvokeAI/.invokeai-env/src/pypatchmatch/patchmatch".
+    rm -rf build/obj libpatchmatch.so
+    mkdir: created directory 'build/obj'
+    mkdir: created directory 'build/obj/csrc/'
+    [dep] csrc/masked_image.cpp ...
+    [dep] csrc/nnf.cpp ...
+    [dep] csrc/inpaint.cpp ...
+    [dep] csrc/pyinterface.cpp ...
+    [CC] csrc/pyinterface.cpp ...
+    [CC] csrc/inpaint.cpp ...
+    [CC] csrc/nnf.cpp ...
+    [CC] csrc/masked_image.cpp ...
+    [link] libpatchmatch.so ...
+    ```
+
+### Arch Based Distros
+
+1. Install the `base-devel` package:
+
+    ```sh
+    sudo pacman -Syu
+    sudo pacman -S --needed base-devel
+    ```
+
+2. Install `opencv` and `blas`:
+
+    ```sh
+    sudo pacman -S opencv blas
+    ```
+
+    or for CUDA support
+
+    ```sh
+    sudo pacman -S opencv-cuda blas
+    ```
+    
+3. Fix the naming of the `opencv` package configuration file:
+
+    ```sh
+    cd /usr/lib/pkgconfig/
+    ln -sf opencv4.pc opencv.pc
+    ```
+
+[**Next, Follow Steps 4-6 from the Debian Section above**](#linux)
+
+If you see no errors you're ready to go!

docs/installation/INSTALLATION.md

@@ -0,0 +1,41 @@
+# Installation Overview
+
+Before installing, review the [installation requirements] to ensure your system is set up properly.
+
+See the [FAQ] for frequently-encountered installation issues.
+
+If you need more help, join our [discord] or [create an issue].
+
+<h2>Automatic Install</h2>
+
+✅ The automatic install is the best way to run InvokeAI. Check out the [installation guide] to get started.
+
+<h2>Manual Install</h2>
+
+If you are familiar with python and want more control over the packages that are installed, you can [install InvokeAI manually via PyPI].
+
+<h2>Developer Install</h2>
+
+If you want to contribute to InvokeAI, consult the [developer install guide].
+
+<h2>Docker Install</h2>
+
+This method is recommended for those familiar with running Docker containers.
+
+We offer a method for creating Docker containers containing InvokeAI and its dependencies. This method is recommended for individuals with experience with Docker containers and understand the pluses and minuses of a container-based install.
+
+See the [docker installation guide].
+
+<h2>Other Installation Guides</h2>
+
+- [PyPatchMatch](060_INSTALL_PATCHMATCH.md)
+- [Installing Models](050_INSTALLING_MODELS.md)
+
+[install InvokeAI manually via PyPI]: 020_INSTALL_MANUAL.md
+[developer install guide]: INSTALL_DEVELOPMENT.md
+[docker installation guide]: 040_INSTALL_DOCKER.md
+[installation guide]: 010_INSTALL_AUTOMATED.md
+[FAQ]: ../help/FAQ.md
+[discord]: discord.gg/invoke-ai
+[create an issue]: https://github.com/invoke-ai/InvokeAI/issues
+[installation requirements]: INSTALL_REQUIREMENTS.md

docs/installation/INSTALL_DEVELOPMENT.md

@@ -0,0 +1,36 @@
+# Developer Install
+
+!!! warning
+
+    InvokeAI uses a SQLite database. By running on `main`, you accept responsibility for your database. This
+    means making regular backups (especially before pulling) and/or fixing it yourself in the event that a
+    PR introduces a schema change.
+
+    If you don't need persistent backend storage, you can use an ephemeral in-memory database by setting
+    `use_memory_db: true` in your `invokeai.yaml` file. You'll also want to set `scan_models_on_startup: true`
+    so that your models are registered on startup.
+
+    If this is untenable, you should run the application via the official installer or a manual install of the
+    python package from PyPI. These releases will not break your database.
+
+If you have an interest in how InvokeAI works, or you would like to add features or bugfixes, you are encouraged to install the source code for InvokeAI.
+
+!!! info "Why do I need the frontend toolchain?"
+
+    The repo doesn't contain a build of the frontend. You'll be responsible for rebuilding it (or running it in dev mode) to use the app, as described in the [frontend dev toolchain] docs.
+
+<h2> Installation </h2>
+
+1. [Fork and clone] the [InvokeAI repo].
+1. Follow the [manual installation] docs to create a new virtual environment for the development install.
+   - When installing the InvokeAI package, add `-e` to the command so you get an [editable install].
+1. Install the [frontend dev toolchain] and do a production build of the UI as described.
+1. You can now run the app as described in the [manual installation] docs.
+
+As described in the [frontend dev toolchain] docs, you can run the UI using a dev server. If you do this, you won't need to continually rebuild the frontend. Instead, you run the dev server and use the app with the server URL it provides.
+
+[Fork and clone]: https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/fork-a-repo
+[InvokeAI repo]: https://github.com/invoke-ai/InvokeAI
+[frontend dev toolchain]: ../contributing/frontend/OVERVIEW.md
+[manual installation]: ./020_INSTALL_MANUAL.md
+[editable install]: https://pip.pypa.io/en/latest/cli/pip_install/#cmdoption-e

docs/installation/INSTALL_REQUIREMENTS.md

@@ -37,13 +37,13 @@ Invoke runs best with a dedicated GPU, but will fall back to running on CPU, alb
     === "Nvidia"
 
         ```
-        Any GPU with at least 8GB VRAM.
+        Any GPU with at least 8GB VRAM. Linux only.
         ```
 
     === "AMD"
 
         ```
-        Any GPU with at least 16GB VRAM. Linux only.
+        Any GPU with at least 16GB VRAM.
         ```
 
     === "Mac"
@@ -177,5 +177,5 @@ An alternative to installing ROCm locally is to use a [ROCm docker container] to
 [Nvidia Container Runtime]: https://developer.nvidia.com/container-runtime
 [linux install instructions]: https://docs.python-guide.org/starting/install3/linux/
 [Microsoft Visual C++ Redistributable]: https://learn.microsoft.com/en-US/cpp/windows/latest-supported-vc-redist?view=msvc-170
-[an official installer]: https://www.python.org/downloads/
+[an official installer]: https://www.python.org/downloads/release/python-3118/
 [CUDA Toolkit Downloads]: https://developer.nvidia.com/cuda-downloads

docs/installation/docker.md

@@ -1,87 +0,0 @@
----
-title: Docker
----
-
-!!! warning "macOS users"
-
-    Docker can not access the GPU on macOS, so your generation speeds will be slow. Use the [installer](./installer.md) instead.
-
-!!! tip "Linux and Windows Users"
-
-    Configure Docker to access your machine's GPU.
-    Docker Desktop on Windows [includes GPU support](https://www.docker.com/blog/wsl-2-gpu-support-for-docker-desktop-on-nvidia-gpus/).
-    Linux users should follow the [NVIDIA](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) or [AMD](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html) documentation.
-
-## TL;DR
-
-Ensure your Docker setup is able to use your GPU. Then:
-
-    ```bash
-    docker run --runtime=nvidia --gpus=all --publish 9090:9090 ghcr.io/invoke-ai/invokeai
-    ```
-
-Once the container starts up, open <http://localhost:9090> in your browser, install some models, and start generating.
-
-## Build-It-Yourself
-
-All the docker materials are located inside the [docker](https://github.com/invoke-ai/InvokeAI/tree/main/docker) directory in the Git repo.
-
-    ```bash
-    cd docker
-    cp .env.sample .env
-    docker compose up
-    ```
-
-We also ship the `run.sh` convenience script. See the `docker/README.md` file for detailed instructions on how to customize the docker setup to your needs.
-
-### Prerequisites
-
-#### Install [Docker](https://github.com/santisbon/guides#docker)
-
-On the [Docker Desktop app](https://docs.docker.com/get-docker/), go to
-Preferences, Resources, Advanced. Increase the CPUs and Memory to avoid this
-[Issue](https://github.com/invoke-ai/InvokeAI/issues/342). You may need to
-increase Swap and Disk image size too.
-
-### Setup
-
-Set up your environment variables. In the `docker` directory, make a copy of `.env.sample` and name it `.env`. Make changes as necessary.
-
-Any environment variables supported by InvokeAI can be set here - please see the [CONFIGURATION](../configuration.md) for further detail.
-
-At a minimum, you might want to set the `INVOKEAI_ROOT` environment variable
-to point to the location where you wish to store your InvokeAI models, configuration, and outputs.
-
-<figure markdown>
-
-| Environment-Variable <img width="220" align="right"/> | Default value <img width="360" align="right"/> | Description                                                                                                                                        |
-| ----------------------------------------------------- | ---------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
-| `INVOKEAI_ROOT`                                       | `~/invokeai`                                   | **Required** - the location of your InvokeAI root directory. It will be created if it does not exist.                                              |
-| `HUGGING_FACE_HUB_TOKEN`                              |                                                | InvokeAI will work without it, but some of the integrations with HuggingFace (like downloading from models from private repositories) may not work |
-| `GPU_DRIVER`                                          | `cuda`                                         | Optionally change this to `rocm` to build the image for AMD GPUs. NOTE: Use the `build.sh` script to build the image for this to take effect.      |
-
-</figure>
-
-#### Build the Image
-
-Use the standard `docker compose build` command from within the `docker` directory.
-
-If using an AMD GPU:
-a: set the `GPU_DRIVER=rocm` environment variable in `docker-compose.yml` and continue using `docker compose build` as usual, or
-b: set `GPU_DRIVER=rocm` in the `.env` file and use the `build.sh` script, provided for convenience
-
-#### Run the Container
-
-Use the standard `docker compose up` command, and generally the `docker compose` [CLI](https://docs.docker.com/compose/reference/) as usual.
-
-Once the container starts up (and configures the InvokeAI root directory if this is a new installation), you can access InvokeAI at [http://localhost:9090](http://localhost:9090)
-
-## Troubleshooting / FAQ
-
-- Q: I am running on Windows under WSL2, and am seeing a "no such file or directory" error.
-- A: Your `docker-entrypoint.sh` might have has Windows (CRLF) line endings, depending how you cloned the repository.
-  To solve this, change the line endings in the `docker-entrypoint.sh` file to `LF`. You can do this in VSCode
-  (`Ctrl+P` and search for "line endings"), or by using the `dos2unix` utility in WSL.
-  Finally, you may delete `docker-entrypoint.sh` followed by `git pull; git checkout docker/docker-entrypoint.sh`
-  to reset the file to its most recent version.
-  For more information on this issue, see [Docker Desktop documentation](https://docs.docker.com/desktop/troubleshoot/topics/#avoid-unexpected-syntax-errors-use-unix-style-line-endings-for-files-in-containers)

docs/installation/index.md

@@ -1,36 +0,0 @@
-# Installation and Updating Overview
-
-Before installing, review the [installation requirements](./requirements.md) to ensure your system is set up properly.
-
-See the [FAQ](../faq.md) for frequently-encountered installation issues.
-
-If you need more help, join our [discord](https://discord.gg/ZmtBAhwWhy) or [create a GitHub issue](https://github.com/invoke-ai/InvokeAI/issues).
-
-## Automated Installer & Updates
-
-✅ The automated [installer](./installer.md) is the best way to install Invoke.
-
-⬆️ The same installer is also the best way to update Invoke - simply rerun it for the same folder you installed to.
-
-The installation process simply manages installation for the core libraries & application dependencies that run Invoke.
-
-Models, images, or other assets in the Invoke root folder won't be affected by the installation process.
-
-## Manual Install
-
-If you are familiar with python and want more control over the packages that are installed, you can [install Invoke manually via PyPI](./manual.md).
-
-Updates are managed by reinstalling the latest version through PyPi.
-
-## Developer Install
-
-If you want to contribute to InvokeAI, you'll need to set up a [dev environment](../contributing/dev-environment.md).
-
-## Docker
-
-Invoke publishes docker images. See the [docker installation guide](./docker.md) for details.
-
-## Other Installation Guides
-
-- [PyPatchMatch](./patchmatch.md)
-- [Installing Models](./models.md)

docs/installation/patchmatch.md

@@ -1,121 +0,0 @@
----
-title: Installing PyPatchMatch
----
-
-PatchMatch is an algorithm used to infill images. It can greatly improve outpainting results. PyPatchMatch is a python wrapper around a C++ implementation of the algorithm.
-
-It uses the image data around the target area as a reference to generate new image data of a similar character and quality.
-
-## Why Use PatchMatch
-
-In the context of image generation, "outpainting" refers to filling in a transparent area using AI-generated image data. But the AI can't generate without some initial data. We need to first fill in the transparent area with _something_.
-
-The first step in "outpainting" then, is to fill in the transparent area with something. Generally, you get better results when that initial infill resembles the rest of the image.
-
-Because PatchMatch generates image data so similar to the rest of the image, it works very well as the first step in outpainting, typically producing better results than other infill methods supported by Invoke (e.g. LaMA, cv2 infill, random tiles).
-
-### Performance Caveat
-
-PatchMatch is CPU-bound, and the amount of time it takes increases proportionally as the infill area increases. While the numbers certainly vary depending on system specs, you can expect a noticeable slowdown once you start infilling areas around 512x512 pixels. 1024x1024 pixels can take several seconds to infill.
-
-## Installation
-
-Unfortunately, installation can be somewhat challenging, as it requires some things that `pip` cannot install for you.
-
-## Windows
-
-You're in luck! On Windows platforms PyPatchMatch will install automatically on
-Windows systems with no extra intervention.
-
-## Macintosh
-
-You need to have opencv installed so that pypatchmatch can be built:
-
-```bash
-brew install opencv
-```
-
-The next time you start `invoke`, after successfully installing opencv, pypatchmatch will be built.
-
-## Linux
-
-Prior to installing PyPatchMatch, you need to take the following steps:
-
-### Debian Based Distros
-
-1. Install the `build-essential` tools:
-
-   ```sh
-   sudo apt update
-   sudo apt install build-essential
-   ```
-
-2. Install `opencv`:
-
-   ```sh
-   sudo apt install python3-opencv libopencv-dev
-   ```
-
-3. Activate the environment you use for invokeai, either with `conda` or with a
-   virtual environment.
-
-4. Install pypatchmatch:
-
-   ```sh
-   pip install pypatchmatch
-   ```
-
-5. Confirm that pypatchmatch is installed. At the command-line prompt enter
-   `python`, and then at the `>>>` line type
-   `from patchmatch import patch_match`: It should look like the following:
-
-   ```py
-   Python 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] on linux
-   Type "help", "copyright", "credits" or "license" for more information.
-   >>> from patchmatch import patch_match
-   Compiling and loading c extensions from "/home/lstein/Projects/InvokeAI/.invokeai-env/src/pypatchmatch/patchmatch".
-   rm -rf build/obj libpatchmatch.so
-   mkdir: created directory 'build/obj'
-   mkdir: created directory 'build/obj/csrc/'
-   [dep] csrc/masked_image.cpp ...
-   [dep] csrc/nnf.cpp ...
-   [dep] csrc/inpaint.cpp ...
-   [dep] csrc/pyinterface.cpp ...
-   [CC] csrc/pyinterface.cpp ...
-   [CC] csrc/inpaint.cpp ...
-   [CC] csrc/nnf.cpp ...
-   [CC] csrc/masked_image.cpp ...
-   [link] libpatchmatch.so ...
-   ```
-
-### Arch Based Distros
-
-1. Install the `base-devel` package:
-
-   ```sh
-   sudo pacman -Syu
-   sudo pacman -S --needed base-devel
-   ```
-
-2. Install `opencv`, `blas`, and required dependencies:
-
-   ```sh
-   sudo pacman -S opencv blas fmt glew vtk hdf5
-   ```
-
-   or for CUDA support
-
-   ```sh
-   sudo pacman -S opencv-cuda blas fmt glew vtk hdf5
-   ```
-
-3. Fix the naming of the `opencv` package configuration file:
-
-   ```sh
-   cd /usr/lib/pkgconfig/
-   ln -sf opencv4.pc opencv.pc
-   ```
-
-[**Next, Follow Steps 4-6 from the Debian Section above**](#linux)
-
-If you see no errors you're ready to go!

docs/javascripts/init_kapa_widget.js

@@ -0,0 +1,10 @@
+document.addEventListener("DOMContentLoaded", function () {
+  var script = document.createElement("script");
+  script.src = "https://widget.kapa.ai/kapa-widget.bundle.js";
+  script.setAttribute("data-website-id", "b5973bb1-476b-451e-8cf4-98de86745a10");
+  script.setAttribute("data-project-name", "Invoke.AI");
+  script.setAttribute("data-project-color", "#11213C");
+  script.setAttribute("data-project-logo", "https://avatars.githubusercontent.com/u/113954515?s=280&v=4");
+  script.async = true;
+  document.head.appendChild(script);
+});

docs/javascripts/tablesort.js

@@ -0,0 +1,7 @@
+document$.subscribe(function() {
+    var tables = document.querySelectorAll("article table:not([class])")
+    tables.forEach(function(table) {
+      new Tablesort(table)
+    })
+  })
+  

docs/nodes/INVOCATION_API.md

@@ -1,33 +1,30 @@
 # Invocation API
 
-Each invocation's `invoke` method is provided a single arg - the Invocation Context.
+Each invocation's `invoke` method is provided a single arg - the Invocation
+Context.
 
-This object provides an API the invocation can use to interact with application services, for example:
+This object provides access to various methods, used to interact with the
+application. Loading and saving images, logging messages, etc.
 
-- Saving images
-- Logging messages
-- Loading models
+!!! warning ""
+
+    This API may shift slightly until the release of v4.0.0 as we work through a few final updates to the Model Manager.
 
 ```py
 class MyInvocation(BaseInvocation):
   ...
   def invoke(self, context: InvocationContext) -> ImageOutput:
-      # Load an image
-      image_pil = context.images.get_pil(self.image.image_name)
+      image_pil = context.images.get_pil(image_name)
       # Do something to the image
-      output_image = do_something_cool(image_pil)
-      # Save the image
-      image_dto = context.images.save(output_image)
+      image_dto = context.images.save(image_pil)
       # Log a message
       context.logger.info(f"Did something cool, image saved!")
-      # Return the output
-      return ImageOutput.build(image_dto)
       ...
 ```
 
 The full API is documented below.
 
-## Mixins
+## Invocation Mixins
 
 Two important mixins are provided to facilitate working with metadata and gallery boards.
 

docs/nodes/NODES_MIGRATION_V3_V4.md

@@ -57,7 +57,7 @@ to footgun.
 
 In v4.0.0, this object has been refactored to be much simpler.
 
-See the [invocation API docs](./invocation-api.md) for full details of the API.
+See [INVOCATION_API](./INVOCATION_API.md) for full details of the API.
 
 !!! warning ""
 

docs/nodes/communityNodes.md

@@ -10,7 +10,7 @@ The suggested method is to use `git clone` to clone the repository the node is f
 
 If you'd prefer, you can also just download the whole node folder from the linked repository and add it to the `nodes` folder. 
 
-To use a community workflow, download the `.json` node graph file and load it into Invoke AI via the **Load Workflow** button in the Workflow Editor. 
+To use a community workflow, download the the `.json` node graph file and load it into Invoke AI via the **Load Workflow** button in the Workflow Editor. 
 
 - Community Nodes
     + [Adapters-Linked](#adapters-linked-nodes)
@@ -21,7 +21,6 @@ To use a community workflow, download the `.json` node graph file and load it in
     + [Clothing Mask](#clothing-mask)
     + [Contrast Limited Adaptive Histogram Equalization](#contrast-limited-adaptive-histogram-equalization)
     + [Depth Map from Wavefront OBJ](#depth-map-from-wavefront-obj)
-    + [Enhance Detail](#enhance-detail)
     + [Film Grain](#film-grain)
     + [Generative Grammar-Based Prompt Nodes](#generative-grammar-based-prompt-nodes)
     + [GPT2RandomPromptMaker](#gpt2randompromptmaker)
@@ -40,9 +39,7 @@ To use a community workflow, download the `.json` node graph file and load it in
     + [Match Histogram](#match-histogram)
     + [Metadata-Linked](#metadata-linked-nodes)
     + [Negative Image](#negative-image)
-    + [Nightmare Promptgen](#nightmare-promptgen)
-    + [Ollama](#ollama-node)
-    + [One Button Prompt](#one-button-prompt)
+    + [Nightmare Promptgen](#nightmare-promptgen)    
     + [Oobabooga](#oobabooga)
     + [Prompt Tools](#prompt-tools)
     + [Remote Image](#remote-image)
@@ -82,7 +79,7 @@ Note: These are inherited from the core nodes so any update to the core nodes sh
 
 **Example Usage:**
 </br>
-<img src="https://raw.githubusercontent.com/skunkworxdark/autostereogram_nodes/refs/heads/main/images/spider.png" width="200" /> -> <img src="https://raw.githubusercontent.com/skunkworxdark/autostereogram_nodes/refs/heads/main/images/spider-depth.png" width="200" /> -> <img src="https://raw.githubusercontent.com/skunkworxdark/autostereogram_nodes/refs/heads/main/images/spider-dots.png" width="200" /> <img src="https://raw.githubusercontent.com/skunkworxdark/autostereogram_nodes/refs/heads/main/images/spider-pattern.png" width="200" />
+<img src="https://github.com/skunkworxdark/autostereogram_nodes/blob/main/images/spider.png" width="200" /> -> <img src="https://github.com/skunkworxdark/autostereogram_nodes/blob/main/images/spider-depth.png" width="200" /> -> <img src="https://github.com/skunkworxdark/autostereogram_nodes/raw/main/images/spider-dots.png" width="200" /> <img src="https://github.com/skunkworxdark/autostereogram_nodes/raw/main/images/spider-pattern.png" width="200" />
 
 --------------------------------
 ### Average Images
@@ -143,17 +140,6 @@ To be imported, an .obj must use triangulated meshes, so make sure to enable tha
 **Example Usage:**
 </br><img src="https://raw.githubusercontent.com/dwringer/depth-from-obj-node/main/depth_from_obj_usage.jpg" width="500" />
 
---------------------------------
-### Enhance Detail
-
-**Description:** A single node that can enhance the detail in an image. Increase or decrease details in an image using a guided filter (as opposed to the typical Gaussian blur used by most sharpening filters.) Based on the `Enhance Detail` ComfyUI node from  https://github.com/spacepxl/ComfyUI-Image-Filters
-
-**Node Link:** https://github.com/skunkworxdark/enhance-detail-node
-
-**Example Usage:**
-</br>
-<img src="https://raw.githubusercontent.com/skunkworxdark/enhance-detail-node/refs/heads/main/images/Comparison.png" />
-
 --------------------------------
 ### Film Grain
 
@@ -320,7 +306,7 @@ View:
 **Node Link:** https://github.com/helix4u/load_video_frame
 
 **Output Example:** 
-<img src="https://raw.githubusercontent.com/helix4u/load_video_frame/refs/heads/main/_git_assets/dance1736978273.gif" width="500" />
+<img src="https://raw.githubusercontent.com/helix4u/load_video_frame/main/_git_assets/testmp4_embed_converted.gif" width="500" />
 
 --------------------------------
 ### Make 3D
@@ -361,7 +347,7 @@ See full docs here: https://github.com/skunkworxdark/Prompt-tools-nodes/edit/mai
 
 **Output Examples** 
 
-<img src="https://github.com/skunkworxdark/match_histogram/assets/21961335/ed12f329-a0ef-444a-9bae-129ed60d6097" />
+<img src="https://github.com/skunkworxdark/match_histogram/assets/21961335/ed12f329-a0ef-444a-9bae-129ed60d6097" width="300" />
 
 --------------------------------
 ### Metadata Linked Nodes
@@ -403,34 +389,6 @@ View:
 
 **Node Link:** [https://github.com/gogurtenjoyer/nightmare-promptgen](https://github.com/gogurtenjoyer/nightmare-promptgen)
 
---------------------------------
-### Ollama Node
-
-**Description:** Uses Ollama API to expand text prompts for text-to-image generation using local LLMs. Works great for expanding basic prompts into detailed natural language prompts for Flux. Also provides a toggle to unload the LLM model immediately after expanding, to free up VRAM for Invoke to continue the image generation workflow.
-
-**Node Link:** https://github.com/Jonseed/Ollama-Node
-
-**Example Node Graph:**  https://github.com/Jonseed/Ollama-Node/blob/main/Ollama-Node-Flux-example.json
-
-**View:** 
-
-![ollama node](https://raw.githubusercontent.com/Jonseed/Ollama-Node/a3e7cdc55e394cb89c1ea7ed54e106c212c85e8c/ollama-node-screenshot.png)
-
---------------------------------
-### One Button Prompt
-
-<img src="https://raw.githubusercontent.com/AIrjen/OneButtonPrompt_X_InvokeAI/refs/heads/main/images/background.png" width="800" />
-
-**Description:** an extensive suite of auto prompt generation and prompt helper nodes based on extensive logic. Get creative with the best prompt generator in the world. 
-
-The main node generates interesting prompts based on a set of parameters. There are also some additional nodes such as Auto Negative Prompt, One Button Artify, Create Prompt Variant and other cool prompt toys to play around with.
-
-**Node Link:** [https://github.com/AIrjen/OneButtonPrompt_X_InvokeAI](https://github.com/AIrjen/OneButtonPrompt_X_InvokeAI)
-
-**Nodes:**
-
-<img src="https://raw.githubusercontent.com/AIrjen/OneButtonPrompt_X_InvokeAI/refs/heads/main/images/OBP_nodes_invokeai.png" width="800" />
-
 --------------------------------
 ### Oobabooga
 
@@ -469,7 +427,7 @@ This node works best with SDXL models, especially as the style can be described
 5. `Prompt Strength Combine` - Combines weighted prompts for .and()/.blend()
 6. `CSV To Index String` - Gets a string from a CSV by index. Includes a Random index option
 
-The following Nodes are now included in v3.2 of Invoke and are no longer in this set of tools.<br>
+The following Nodes are now included in v3.2 of Invoke and are nolonger in this set of tools.<br>
 - `Prompt Join` -> `String Join`
 - `Prompt Join Three` -> `String Join Three`
 - `Prompt Replace` -> `String Replace`
@@ -482,7 +440,7 @@ See full docs here: https://github.com/skunkworxdark/Prompt-tools-nodes/edit/mai
 
 **Workflow Examples** 
 
-<img src="https://raw.githubusercontent.com/skunkworxdark/prompt-tools/refs/heads/main/images/CSVToIndexStringNode.png"/>
+<img src="https://github.com/skunkworxdark/prompt-tools/blob/main/images/CSVToIndexStringNode.png" width="300" />
 
 --------------------------------
 ### Remote Image
@@ -498,7 +456,7 @@ See full docs here: https://github.com/skunkworxdark/Prompt-tools-nodes/edit/mai
 
 ### BriaAI Remove Background
 
-**Description**: Implements one click background removal with BriaAI's new version 1.4 model which seems to be producing better results than any other previous background removal tool.
+**Description**: Implements one click background removal with BriaAI's new version 1.4 model which seems to be be producing better results than any other previous background removal tool.
 
 **Node Link:** https://github.com/blessedcoolant/invoke_bria_rmbg
 
@@ -620,7 +578,7 @@ See full docs here: https://github.com/skunkworxdark/XYGrid_nodes/edit/main/READ
 
 **Output Examples** 
 
-<img src="https://raw.githubusercontent.com/skunkworxdark/XYGrid_nodes/refs/heads/main/images/collage.png" />
+<img src="https://github.com/skunkworxdark/XYGrid_nodes/blob/main/images/collage.png" width="300" />
 
 
 --------------------------------

docs/nodes/exampleWorkflows.md

@@ -0,0 +1,18 @@
+# Example Workflows
+
+We've curated some example workflows for you to get started with Workflows in InvokeAI! These can also be found in the Workflow Library, located in the Workflow Editor of Invoke.
+
+To use them, right click on your desired workflow, follow the link to GitHub and click the "⬇" button to download the raw file. You can then use the "Load Workflow" functionality in InvokeAI to load the workflow and start generating images!
+
+If you're interested in finding more workflows, checkout the [#share-your-workflows](https://discord.com/channels/1020123559063990373/1130291608097661000) channel in the InvokeAI Discord.
+
+* [SD1.5 / SD2 Text to Image](https://github.com/invoke-ai/InvokeAI/blob/main/docs/workflows/Text_to_Image.json)
+* [SDXL Text to Image](https://github.com/invoke-ai/InvokeAI/blob/main/docs/workflows/SDXL_Text_to_Image.json)
+* [SDXL Text to Image with Refiner](https://github.com/invoke-ai/InvokeAI/blob/main/docs/workflows/SDXL_w_Refiner_Text_to_Image.json)
+* [Multi ControlNet (Canny & Depth)](https://github.com/invoke-ai/InvokeAI/blob/main/docs/workflows/Multi_ControlNet_Canny_and_Depth.json)
+* [Tiled Upscaling with ControlNet](https://github.com/invoke-ai/InvokeAI/blob/main/docs/workflows/ESRGAN_img2img_upscale_w_Canny_ControlNet.json)
+* [Prompt From File](https://github.com/invoke-ai/InvokeAI/blob/main/docs/workflows/Prompt_from_File.json)
+* [Face Detailer with IP-Adapter & ControlNet](https://github.com/invoke-ai/InvokeAI/blob/main/docs/workflows/Face_Detailer_with_IP-Adapter_and_Canny.json)
+* [FaceMask](https://github.com/invoke-ai/InvokeAI/blob/main/docs/workflows/FaceMask.json)
+* [FaceOff with 2x Face Scaling](https://github.com/invoke-ai/InvokeAI/blob/main/docs/workflows/FaceOff_FaceScale2x.json)
+* [QR Code Monster](https://github.com/invoke-ai/InvokeAI/blob/main/docs/workflows/QR_Code_Monster.json)

docs/nodes/overview.md

@@ -1,7 +1,6 @@
 # Nodes
 
 ## What are Nodes?
-
 An Node is simply a single operation that takes in inputs and returns
 out outputs. Multiple nodes can be linked together to create more
 complex functionality. All InvokeAI features are added through nodes.
@@ -14,10 +13,14 @@ Individual nodes are made up of the following:
 - Outputs: Edge points on the right side of the node window where you connect to inputs on other nodes.
 - Options: Various options which are either manually configured, or overridden by connecting an output from another node to the input.
 
-With nodes, you can can easily extend the image generation capabilities of InvokeAI, and allow you build workflows that suit your needs.
 
-You can read more about nodes and the node editor [here](../nodes/NODES.md).
+With nodes, you can can easily extend the image generation capabilities of InvokeAI, and allow you build workflows that suit your needs. 
+
+You can read more about nodes and the node editor [here](../nodes/NODES.md). 
+
+To get started with nodes, take a look at some of our examples for [common workflows](../nodes/exampleWorkflows.md)
 
 ## Downloading New Nodes
+To download a new node, visit our list of [Community Nodes](../nodes/communityNodes.md). These are nodes that have been created by the community, for the community. 
+
 
-To download a new node, visit our list of [Community Nodes](../nodes/communityNodes.md). These are nodes that have been created by the community, for the community.

docs/other/CONTRIBUTORS.md

@@ -0,0 +1,380 @@
+---
+title: Contributors
+---
+
+# :octicons-person-24: Contributors
+
+The list of all the amazing people who have contributed to the various features that you get to
+experience in this fork.
+
+We thank them for all of their time and hard work.
+
+## **Original Author**
+
+- [Lincoln D. Stein](mailto:lincoln.stein@gmail.com)
+
+## **Current Core Team**
+
+* @lstein (Lincoln Stein) - Co-maintainer
+* @blessedcoolant - Co-maintainer
+* @hipsterusername (Kent Keirsey) - Co-maintainer, CEO, Positive Vibes
+* @psychedelicious (Spencer Mabrito) - Web Team Leader
+* @chainchompa (Jennifer Player) - Web Development & Chain-Chomping
+* @josh is toast (Josh Corbett) - Web Development
+* @cheerio (Mary Rogers) - Lead Engineer & Web App Development
+* @ebr (Eugene Brodsky) - Cloud/DevOps/Sofware engineer; your friendly neighbourhood cluster-autoscaler
+* @sunija - Standalone version
+* @genomancer (Gregg Helt) - Controlnet support
+* @brandon (Brandon Rising) - Platform, Infrastructure, Backend Systems
+* @ryanjdick (Ryan Dick) - Machine Learning & Training
+* @JPPhoto - Core image generation nodes
+* @dunkeroni - Image generation backend
+* @SkunkWorxDark - Image generation backend
+* @keturn (Kevin Turner) - Diffusers
+* @millu (Millun Atluri) - Community Wizard, Documentation, Node-wrangler, 
+* @glimmerleaf (Devon Hopkins) - Community Wizard
+* @gogurt enjoyer - Discord moderator and end user support
+* @whosawhatsis - Discord moderator and end user support
+* @dwinrger - Discord moderator and end user support
+* @526christian - Discord moderator and end user support
+* @harvester62 -  Discord moderator and end user support
+
+
+## **Honored Team Alumni**
+
+* @StAlKeR7779 (Sergey Borisov) - Torch stack, ONNX, model management, optimization
+* @damian0815 - Attention Systems and Compel Maintainer
+* @netsvetaev (Artur) - Localization support
+* @Kyle0654 (Kyle Schouviller) - Node Architect and General Backend Wizard
+* @tildebyte - Installation and configuration
+* @mauwii (Matthias Wilde) - Installation, release, continuous integration
+
+
+## **Full List of Contributors by Commit Name**
+
+- 이승석
+- AbdBarho
+- ablattmann
+- AdamOStark
+- Adam Rice
+- Airton Silva
+- Aldo Hoeben
+- Alexander Eichhorn
+- Alexandre D. Roberge
+- Alexandre Macabies
+- Alfie John
+- Andreas Rozek
+- Andre LaBranche
+- Andy Bearman
+- Andy Luhrs
+- Andy Pilate
+- Anonymous
+- Anthony Monthe
+- Any-Winter-4079
+- apolinario
+- Ar7ific1al
+- ArDiouscuros
+- Armando C. Santisbon
+- Arnold Cordewiner
+- Arthur Holstvoogd
+- artmen1516
+- Artur
+- Arturo Mendivil
+- Ben Alkov
+- Benjamin Warner
+- Bernard Maltais
+- blessedcoolant
+- blhook
+- BlueAmulet
+- Bouncyknighter
+- Brandon
+- Brandon Rising
+- Brent Ozar
+- Brian Racer
+- bsilvereagle
+- c67e708d
+- camenduru
+- CapableWeb
+- Carson Katri
+- chainchompa
+- Chloe
+- Chris Dawson
+- Chris Hayes
+- Chris Jones
+- chromaticist
+- Claus F. Strasburger
+- cmdr2
+- cody
+- Conor Reid
+- Cora Johnson-Roberson
+- coreco
+- cosmii02
+- cpacker
+- Cragin Godley
+- creachec
+- CrypticWit
+- d8ahazard
+- damian
+- damian0815
+- Damian at mba
+- Damian Stewart
+- Daniel Manzke
+- Danny Beer
+- Dan Sully
+- Darren Ringer
+- David Burnett
+- David Ford
+- David Regla
+- David Sisco
+- David Wager
+- Daya Adianto
+- db3000
+- DekitaRPG
+- Denis Olshin
+- Dennis
+- dependabot[bot]
+- Dmitry Parnas
+- Dobrynia100
+- Dominic Letz
+- DrGunnarMallon
+- Drun555
+- dunkeroni
+- Edward Johan
+- elliotsayes
+- Elrik
+- ElrikUnderlake
+- Eric Khun
+- Eric Wolf
+- Eugene
+- Eugene Brodsky
+- ExperimentalCyborg
+- Fabian Bahl
+- Fabio 'MrWHO' Torchetti
+- Fattire
+- fattire
+- Felipe Nogueira
+- Félix Sanz
+- figgefigge
+- Gabriel Mackievicz Telles
+- gabrielrotbart
+- gallegonovato
+- Gérald LONLAS
+- Gille
+- GitHub Actions Bot
+- glibesyck
+- gogurtenjoyer
+- Gohsuke Shimada
+- greatwolf
+- greentext2
+- Gregg Helt
+- H4rk
+- Håvard Gulldahl
+- henry
+- Henry van Megen
+- hipsterusername
+- hj
+- Hosted Weblate
+- Iman Karim
+- ismail ihsan bülbül
+- ItzAttila
+- Ivan Efimov
+- jakehl
+- Jakub Kolčář
+- JamDon2
+- James Reynolds
+- Jan Skurovec
+- Jari Vetoniemi
+- Jason Toffaletti
+- Jaulustus
+- Jeff Mahoney
+- Jennifer Player
+- jeremy
+- Jeremy Clark
+- JigenD
+- Jim Hays
+- Johan Roxendal
+- Johnathon Selstad
+- Jonathan
+- Jordan Hewitt
+- Joseph Dries III
+- Josh Corbett
+- JPPhoto
+- jspraul
+- junzi
+- Justin Wong
+- Juuso V
+- Kaspar Emanuel
+- Katsuyuki-Karasawa
+- Keerigan45
+- Kent Keirsey
+- Kevin Brack
+- Kevin Coakley
+- Kevin Gibbons
+- Kevin Schaul
+- Kevin Turner
+- Kieran Klaassen
+- krummrey
+- Kyle
+- Kyle Lacy
+- Kyle Schouviller
+- Lawrence Norton
+- LemonDouble
+- Leo Pasanen
+- Lincoln Stein
+- LoganPederson
+- Lynne Whitehorn
+- majick
+- Marco Labarile
+- Marta Nahorniuk
+- Martin Kristiansen
+- Mary Hipp
+- maryhipp
+- Mary Hipp Rogers
+- mastercaster
+- mastercaster9000
+- Matthias Wild
+- mauwii
+- michaelk71
+- mickr777
+- Mihai
+- Mihail Dumitrescu
+- Mikhail Tishin
+- Millun Atluri
+- Minjune Song
+- Mitchell Allain
+- mitien
+- mofuzz
+- Muhammad Usama
+- Name
+- _nderscore
+- Neil Wang
+- nekowaiz
+- nemuruibai
+- Netzer R
+- Nicholas Koh
+- Nicholas Körfer
+- nicolai256
+- Niek van der Maas
+- noodlebox
+- Nuno Coração
+- ofirkris
+- Olivier Louvignes
+- owenvincent
+- pand4z31
+- Patrick Esser
+- Patrick Tien
+- Patrick von Platen
+- Paul Curry
+- Paul Sajna
+- pejotr
+- Peter Baylies
+- Peter Lin
+- plucked
+- prixt
+- psychedelicious
+- psychedelicious@windows
+- Rainer Bernhardt
+- Riccardo Giovanetti
+- Rich Jones
+- rmagur1203
+- Rob Baines
+- Robert Bolender
+- Robin Rombach
+- Rohan Barar
+- Rohinish
+- rpagliuca
+- rromb
+- Rupesh Sreeraman
+- Ryan
+- Ryan Cao
+- Ryan Dick
+- Saifeddine
+- Saifeddine ALOUI
+- Sam
+- SammCheese
+- Sam McLeod
+- Sammy
+- sammyf
+- Samuel Husso
+- Saurav Maheshkar
+- Scott Lahteine
+- Sean McLellan
+- Sebastian Aigner
+- Sergey Borisov
+- Sergey Krashevich
+- Shapor Naghibzadeh
+- Shawn Zhong
+- Simona Liliac
+- Simon Vans-Colina
+- skunkworxdark
+- slashtechno
+- SoheilRezaei
+- Song, Pengcheng
+- spezialspezial
+- ssantos
+- StAlKeR7779
+- Stefan Tobler
+- Stephan Koglin-Fischer
+- SteveCaruso
+- Steve Martinelli
+- Steven Frank
+- Surisen
+- System X - Files
+- Taylor Kems
+- techicode
+- techybrain-dev
+- tesseractcat
+- thealanle
+- Thomas
+- tildebyte
+- Tim Cabbage
+- Tom
+- Tom Elovi Spruce
+- Tom Gouville
+- tomosuto
+- Travco
+- Travis Palmer
+- tyler
+- unknown
+- user1
+- vedant-3010
+- Vedant Madane
+- veprogames
+- wa.code
+- wfng92
+- whjms
+- whosawhatsis
+- Will
+- William Becher
+- William Chong
+- Wilson E. Alvarez
+- woweenie
+- Wubbbi
+- xra
+- Yeung Yiu Hung
+- ymgenesis
+- Yorzaren
+- Yosuke Shinya
+- yun saki
+- ZachNagengast
+- Zadagu
+- zeptofine
+- Zerdoumi
+- Васянатор
+- 冯不游
+- 唐澤 克幸
+
+## **Original CompVis (Stable Diffusion) Authors**
+
+- [Robin Rombach](https://github.com/rromb)
+- [Patrick von Platen](https://github.com/patrickvonplaten)
+- [ablattmann](https://github.com/ablattmann)
+- [Patrick Esser](https://github.com/pesser)
+- [owenvincent](https://github.com/owenvincent)
+- [apolinario](https://github.com/apolinario)
+- [Charles Packer](https://github.com/cpacker)
+
+---
+
+_If you have contributed and don't see your name on the list of contributors, please let one of the
+collaborators know about the omission, or feel free to make a pull request._

docs/other/README-CompViz.md

@@ -0,0 +1,255 @@
+---
+title: CompViz-Readme
+---
+
+# _README from [CompViz/stable-diffusion](https://github.com/CompVis/stable-diffusion)_
+
+_Stable Diffusion was made possible thanks to a collaboration with
+[Stability AI](https://stability.ai/) and [Runway](https://runwayml.com/) and
+builds upon our previous work:_
+
+[**High-Resolution Image Synthesis with Latent Diffusion Models**](https://ommer-lab.com/research/latent-diffusion-models/)<br/>
+[Robin Rombach](https://github.com/rromb)\*,
+[Andreas Blattmann](https://github.com/ablattmann)\*,
+[Dominik Lorenz](https://github.com/qp-qp)\,
+[Patrick Esser](https://github.com/pesser),
+[Björn Ommer](https://hci.iwr.uni-heidelberg.de/Staff/bommer)<br/>
+
+## **CVPR '22 Oral**
+
+which is available on [GitHub](https://github.com/CompVis/latent-diffusion). PDF
+at [arXiv](https://arxiv.org/abs/2112.10752). Please also visit our
+[Project page](https://ommer-lab.com/research/latent-diffusion-models/).
+
+![txt2img-stable2](../assets/stable-samples/txt2img/merged-0006.png)
+[Stable Diffusion](#stable-diffusion-v1) is a latent text-to-image diffusion
+model. Thanks to a generous compute donation from
+[Stability AI](https://stability.ai/) and support from
+[LAION](https://laion.ai/), we were able to train a Latent Diffusion Model on
+512x512 images from a subset of the [LAION-5B](https://laion.ai/blog/laion-5b/)
+database. Similar to Google's [Imagen](https://arxiv.org/abs/2205.11487), this
+model uses a frozen CLIP ViT-L/14 text encoder to condition the model on text
+prompts. With its 860M UNet and 123M text encoder, the model is relatively
+lightweight and runs on a GPU with at least 10GB VRAM. See
+[this section](#stable-diffusion-v1) below and the
+[model card](https://huggingface.co/CompVis/stable-diffusion).
+
+## Requirements
+
+A suitable [conda](https://conda.io/) environment named `ldm` can be created and
+activated with:
+
+```
+conda env create
+conda activate ldm
+```
+
+Note that the first line may be abbreviated `conda env create`, since conda will
+look for `environment.yml` by default.
+
+You can also update an existing
+[latent diffusion](https://github.com/CompVis/latent-diffusion) environment by
+running
+
+```bash
+conda install pytorch torchvision -c pytorch
+pip install transformers==4.19.2
+pip install -e .
+```
+
+## Stable Diffusion v1
+
+Stable Diffusion v1 refers to a specific configuration of the model architecture
+that uses a downsampling-factor 8 autoencoder with an 860M UNet and CLIP
+ViT-L/14 text encoder for the diffusion model. The model was pretrained on
+256x256 images and then finetuned on 512x512 images.
+
+\*Note: Stable Diffusion v1 is a general text-to-image diffusion model and
+therefore mirrors biases and (mis-)conceptions that are present in its training
+data. Details on the training procedure and data, as well as the intended use of
+the model can be found in the corresponding
+[model card](https://huggingface.co/CompVis/stable-diffusion). Research into the
+safe deployment of general text-to-image models is an ongoing effort. To prevent
+misuse and harm, we currently provide access to the checkpoints only for
+[academic research purposes upon request](https://stability.ai/academia-access-form).
+**This is an experiment in safe and community-driven publication of a capable
+and general text-to-image model. We are working on a public release with a more
+permissive license that also incorporates ethical considerations.\***
+
+[Request access to Stable Diffusion v1 checkpoints for academic research](https://stability.ai/academia-access-form)
+
+### Weights
+
+We currently provide three checkpoints, `sd-v1-1.ckpt`, `sd-v1-2.ckpt` and
+`sd-v1-3.ckpt`, which were trained as follows,
+
+- `sd-v1-1.ckpt`: 237k steps at resolution `256x256` on
+  [laion2B-en](https://huggingface.co/datasets/laion/laion2B-en). 194k steps at
+  resolution `512x512` on
+  [laion-high-resolution](https://huggingface.co/datasets/laion/laion-high-resolution)
+  (170M examples from LAION-5B with resolution `>= 1024x1024`).
+- `sd-v1-2.ckpt`: Resumed from `sd-v1-1.ckpt`. 515k steps at resolution
+  `512x512` on "laion-improved-aesthetics" (a subset of laion2B-en, filtered to
+  images with an original size `>= 512x512`, estimated aesthetics score `> 5.0`,
+  and an estimated watermark probability `< 0.5`. The watermark estimate is from
+  the LAION-5B metadata, the aesthetics score is estimated using an
+  [improved aesthetics estimator](https://github.com/christophschuhmann/improved-aesthetic-predictor)).
+- `sd-v1-3.ckpt`: Resumed from `sd-v1-2.ckpt`. 195k steps at resolution
+  `512x512` on "laion-improved-aesthetics" and 10\% dropping of the
+  text-conditioning to improve
+  [classifier-free guidance sampling](https://arxiv.org/abs/2207.12598).
+
+Evaluations with different classifier-free guidance scales (1.5, 2.0, 3.0, 4.0,
+5.0, 6.0, 7.0, 8.0) and 50 PLMS sampling steps show the relative improvements of
+the checkpoints: ![sd evaluation results](../assets/v1-variants-scores.jpg)
+
+### Text-to-Image with Stable Diffusion
+
+![txt2img-stable2](../assets/stable-samples/txt2img/merged-0005.png)
+![txt2img-stable2](../assets/stable-samples/txt2img/merged-0007.png)
+
+Stable Diffusion is a latent diffusion model conditioned on the (non-pooled)
+text embeddings of a CLIP ViT-L/14 text encoder.
+
+#### Sampling Script
+
+After [obtaining the weights](#weights), link them
+
+```
+mkdir -p models/ldm/stable-diffusion-v1/
+ln -s <path/to/model.ckpt> models/ldm/stable-diffusion-v1/model.ckpt
+```
+
+and sample with
+
+```
+python scripts/txt2img.py --prompt "a photograph of an astronaut riding a horse" --plms
+```
+
+By default, this uses a guidance scale of `--scale 7.5`,
+[Katherine Crowson's implementation](https://github.com/CompVis/latent-diffusion/pull/51)
+of the [PLMS](https://arxiv.org/abs/2202.09778) sampler, and renders images of
+size 512x512 (which it was trained on) in 50 steps. All supported arguments are
+listed below (type `python scripts/txt2img.py --help`).
+
+```commandline
+usage: txt2img.py [-h] [--prompt [PROMPT]] [--outdir [OUTDIR]] [--skip_grid] [--skip_save] [--ddim_steps DDIM_STEPS] [--plms] [--laion400m] [--fixed_code] [--ddim_eta DDIM_ETA] [--n_iter N_ITER] [--H H] [--W W] [--C C] [--f F] [--n_samples N_SAMPLES] [--n_rows N_ROWS]
+                  [--scale SCALE] [--from-file FROM_FILE] [--config CONFIG] [--ckpt CKPT] [--seed SEED] [--precision {full,autocast}]
+
+optional arguments:
+  -h, --help            show this help message and exit
+  --prompt [PROMPT]     the prompt to render
+  --outdir [OUTDIR]     dir to write results to
+  --skip_grid           do not save a grid, only individual samples. Helpful when evaluating lots of samples
+  --skip_save           do not save individual samples. For speed measurements.
+  --ddim_steps DDIM_STEPS
+                        number of ddim sampling steps
+  --plms                use plms sampling
+  --laion400m           uses the LAION400M model
+  --fixed_code          if enabled, uses the same starting code across samples
+  --ddim_eta DDIM_ETA   ddim eta (eta=0.0 corresponds to deterministic sampling
+  --n_iter N_ITER       sample this often
+  --H H                 image height, in pixel space
+  --W W                 image width, in pixel space
+  --C C                 latent channels
+  --f F                 downsampling factor
+  --n_samples N_SAMPLES
+                        how many samples to produce for each given prompt. A.k.a. batch size
+                        (note that the seeds for each image in the batch will be unavailable)
+  --n_rows N_ROWS       rows in the grid (default: n_samples)
+  --scale SCALE         unconditional guidance scale: eps = eps(x, empty) + scale * (eps(x, cond) - eps(x, empty))
+  --from-file FROM_FILE
+                        if specified, load prompts from this file
+  --config CONFIG       path to config which constructs model
+  --ckpt CKPT           path to checkpoint of model
+  --seed SEED           the seed (for reproducible sampling)
+  --precision {full,autocast}
+                        evaluate at this precision
+
+```
+
+Note: The inference config for all v1 versions is designed to be used with
+EMA-only checkpoints. For this reason `use_ema=False` is set in the
+configuration, otherwise the code will try to switch from non-EMA to EMA
+weights. If you want to examine the effect of EMA vs no EMA, we provide "full"
+checkpoints which contain both types of weights. For these, `use_ema=False` will
+load and use the non-EMA weights.
+
+#### Diffusers Integration
+
+Another way to download and sample Stable Diffusion is by using the
+[diffusers library](https://github.com/huggingface/diffusers/tree/main#new--stable-diffusion-is-now-fully-compatible-with-diffusers)
+
+```py
+# make sure you're logged in with `huggingface-cli login`
+from torch import autocast
+from diffusers import StableDiffusionPipeline, LMSDiscreteScheduler
+
+pipe = StableDiffusionPipeline.from_pretrained(
+	"CompVis/stable-diffusion-v1-3-diffusers",
+	use_auth_token=True
+)
+
+prompt = "a photo of an astronaut riding a horse on mars"
+with autocast("cuda"):
+    image = pipe(prompt)["sample"][0]
+
+image.save("astronaut_rides_horse.png")
+```
+
+### Image Modification with Stable Diffusion
+
+By using a diffusion-denoising mechanism as first proposed by
+[SDEdit](https://arxiv.org/abs/2108.01073), the model can be used for different
+tasks such as text-guided image-to-image translation and upscaling. Similar to
+the txt2img sampling script, we provide a script to perform image modification
+with Stable Diffusion.
+
+The following describes an example where a rough sketch made in
+[Pinta](https://www.pinta-project.com/) is converted into a detailed artwork.
+
+```
+python scripts/img2img.py --prompt "A fantasy landscape, trending on artstation" --init-img <path-to-img.jpg> --strength 0.8
+```
+
+Here, strength is a value between 0.0 and 1.0, that controls the amount of noise
+that is added to the input image. Values that approach 1.0 allow for lots of
+variations but will also produce images that are not semantically consistent
+with the input. See the following example.
+
+**Input**
+
+![sketch-in](../assets/stable-samples/img2img/sketch-mountains-input.jpg)
+
+**Outputs**
+
+![out3](../assets/stable-samples/img2img/mountains-3.png)
+![out2](../assets/stable-samples/img2img/mountains-2.png)
+
+This procedure can, for example, also be used to upscale samples from the base
+model.
+
+## Comments
+
+- Our codebase for the diffusion models builds heavily on
+  [OpenAI's ADM codebase](https://github.com/openai/guided-diffusion) and
+  [https://github.com/lucidrains/denoising-diffusion-pytorch](https://github.com/lucidrains/denoising-diffusion-pytorch).
+  Thanks for open-sourcing!
+
+- The implementation of the transformer encoder is from
+  [x-transformers](https://github.com/lucidrains/x-transformers) by
+  [lucidrains](https://github.com/lucidrains?tab=repositories).
+
+## BibTeX
+
+```
+@misc{rombach2021highresolution,
+      title={High-Resolution Image Synthesis with Latent Diffusion Models},
+      author={Robin Rombach and Andreas Blattmann and Dominik Lorenz and Patrick Esser and Björn Ommer},
+      year={2021},
+      eprint={2112.10752},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+
+```

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docs/workflows/QR_Code_Monster.json

@@ -0,0 +1,758 @@
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+}

docs/workflows/Text_to_Image.json

@@ -0,0 +1,798 @@
+{
+  "name": "Text to Image - SD1.5",
+  "author": "InvokeAI",
+  "description": "Sample text to image workflow for Stable Diffusion 1.5/2",
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+  "notes": "",
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+      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "target": "7d8bf987-284f-413a-b2fd-d825445a5d6c",
+      "type": "default",
+      "sourceHandle": "clip",
+      "targetHandle": "clip"
+    },
+    {
+      "id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8clip-93dc02a4-d05b-48ed-b99c-c9b616af3402clip",
+      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "target": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
+      "type": "default",
+      "sourceHandle": "clip",
+      "targetHandle": "clip"
+    },
+    {
+      "id": "reactflow__edge-55705012-79b9-4aac-9f26-c0b10309785bnoise-eea2702a-19fb-45b5-9d75-56b4211ec03cnoise",
+      "source": "55705012-79b9-4aac-9f26-c0b10309785b",
+      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "type": "default",
+      "sourceHandle": "noise",
+      "targetHandle": "noise"
+    },
+    {
+      "id": "reactflow__edge-7d8bf987-284f-413a-b2fd-d825445a5d6cconditioning-eea2702a-19fb-45b5-9d75-56b4211ec03cpositive_conditioning",
+      "source": "7d8bf987-284f-413a-b2fd-d825445a5d6c",
+      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "type": "default",
+      "sourceHandle": "conditioning",
+      "targetHandle": "positive_conditioning"
+    },
+    {
+      "id": "reactflow__edge-93dc02a4-d05b-48ed-b99c-c9b616af3402conditioning-eea2702a-19fb-45b5-9d75-56b4211ec03cnegative_conditioning",
+      "source": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
+      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "type": "default",
+      "sourceHandle": "conditioning",
+      "targetHandle": "negative_conditioning"
+    },
+    {
+      "id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8unet-eea2702a-19fb-45b5-9d75-56b4211ec03cunet",
+      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "type": "default",
+      "sourceHandle": "unet",
+      "targetHandle": "unet"
+    },
+    {
+      "id": "reactflow__edge-eea2702a-19fb-45b5-9d75-56b4211ec03clatents-58c957f5-0d01-41fc-a803-b2bbf0413d4flatents",
+      "source": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "target": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
+      "type": "default",
+      "sourceHandle": "latents",
+      "targetHandle": "latents"
+    },
+    {
+      "id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8vae-58c957f5-0d01-41fc-a803-b2bbf0413d4fvae",
+      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "target": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
+      "type": "default",
+      "sourceHandle": "vae",
+      "targetHandle": "vae"
+    }
+  ]
+}

flake.lock

@@ -2,11 +2,11 @@
   "nodes": {
     "nixpkgs": {
       "locked": {
-        "lastModified": 1727955264,
-        "narHash": "sha256-lrd+7mmb5NauRoMa8+J1jFKYVa+rc8aq2qc9+CxPDKc=",
+        "lastModified": 1690630721,
+        "narHash": "sha256-Y04onHyBQT4Erfr2fc82dbJTfXGYrf4V0ysLUYnPOP8=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "71cd616696bd199ef18de62524f3df3ffe8b9333",
+        "rev": "d2b52322f35597c62abf56de91b0236746b2a03d",
         "type": "github"
       },
       "original": {

flake.nix

@@ -34,7 +34,7 @@
             cudaPackages.cudnn
             cudaPackages.cuda_nvrtc
             cudatoolkit
-            pkg-config
+            pkgconfig
             libconfig
             cmake
             blas
@@ -66,7 +66,7 @@
             black
 
             # Frontend.
-            pnpm_8
+            yarn
             nodejs
           ];
           LD_LIBRARY_PATH = pkgs.lib.makeLibraryPath buildInputs;

installer/install.sh.in

@@ -12,7 +12,7 @@ MINIMUM_PYTHON_VERSION=3.10.0
 MAXIMUM_PYTHON_VERSION=3.11.100
 PYTHON=""
 for candidate in python3.11 python3.10 python3 python ; do
-    if ppath=`which $candidate 2>/dev/null`; then
+    if ppath=`which $candidate`; then
         # when using `pyenv`, the executable for an inactive Python version will exist but will not be operational
         # we check that this found executable can actually run
         if [ $($candidate --version &>/dev/null; echo ${PIPESTATUS}) -gt 0 ]; then continue; fi
@@ -30,11 +30,10 @@ done
 if [ -z "$PYTHON" ]; then
     echo "A suitable Python interpreter could not be found"
     echo "Please install Python $MINIMUM_PYTHON_VERSION or higher (maximum $MAXIMUM_PYTHON_VERSION) before running this script. See instructions at $INSTRUCTIONS for help."
+    echo "For the best user experience we suggest enlarging or maximizing this window now."
     read -p "Press any key to exit"
     exit -1
 fi
 
-echo "For the best user experience we suggest enlarging or maximizing this window now."
-
 exec $PYTHON ./lib/main.py ${@}
 read -p "Press any key to exit"

installer/lib/installer.py

@@ -245,9 +245,6 @@ class InvokeAiInstance:
 
         pip = local[self.pip]
 
-        # Uninstall xformers if it is present; the correct version of it will be reinstalled if needed
-        _ = pip["uninstall", "-yqq", "xformers"] & FG
-
         pipeline = pip[
             "install",
             "--require-virtualenv",
@@ -285,6 +282,12 @@ class InvokeAiInstance:
             shutil.copy(src, dest)
             os.chmod(dest, 0o0755)
 
+    def update(self):
+        pass
+
+    def remove(self):
+        pass
+
 
 ### Utility functions ###
 
@@ -399,7 +402,7 @@ def get_torch_source() -> Tuple[str | None, str | None]:
     :rtype: list
     """
 
-    from messages import GpuType, select_gpu
+    from messages import select_gpu
 
     # device can be one of: "cuda", "rocm", "cpu", "cuda_and_dml, autodetect"
     device = select_gpu()
@@ -409,22 +412,16 @@ def get_torch_source() -> Tuple[str | None, str | None]:
     url = None
     optional_modules: str | None = None
     if OS == "Linux":
-        if device == GpuType.ROCM:
-            url = "https://download.pytorch.org/whl/rocm6.1"
-        elif device == GpuType.CPU:
+        if device.value == "rocm":
+            url = "https://download.pytorch.org/whl/rocm5.6"
+        elif device.value == "cpu":
             url = "https://download.pytorch.org/whl/cpu"
-        elif device == GpuType.CUDA:
-            url = "https://download.pytorch.org/whl/cu124"
-            optional_modules = "[onnx-cuda]"
-        elif device == GpuType.CUDA_WITH_XFORMERS:
-            url = "https://download.pytorch.org/whl/cu124"
+        elif device.value == "cuda":
+            # CUDA uses the default PyPi index
             optional_modules = "[xformers,onnx-cuda]"
     elif OS == "Windows":
-        if device == GpuType.CUDA:
-            url = "https://download.pytorch.org/whl/cu124"
-            optional_modules = "[onnx-cuda]"
-        elif device == GpuType.CUDA_WITH_XFORMERS:
-            url = "https://download.pytorch.org/whl/cu124"
+        if device.value == "cuda":
+            url = "https://download.pytorch.org/whl/cu121"
             optional_modules = "[xformers,onnx-cuda]"
         elif device.value == "cpu":
             # CPU  uses the default PyPi index, no optional modules

installer/lib/messages.py

@@ -206,7 +206,6 @@ def dest_path(dest: Optional[str | Path] = None) -> Path | None:
 
 
 class GpuType(Enum):
-    CUDA_WITH_XFORMERS = "xformers"
     CUDA = "cuda"
     ROCM = "rocm"
     CPU = "cpu"
@@ -222,15 +221,11 @@ def select_gpu() -> GpuType:
         return GpuType.CPU
 
     nvidia = (
-        "an [gold1 b]NVIDIA[/] RTX 3060 or newer GPU using CUDA",
+        "an [gold1 b]NVIDIA[/] GPU (using CUDA™)",
         GpuType.CUDA,
     )
-    vintage_nvidia = (
-        "an [gold1 b]NVIDIA[/] RTX 20xx or older GPU using CUDA+xFormers",
-        GpuType.CUDA_WITH_XFORMERS,
-    )
     amd = (
-        "an [gold1 b]AMD[/] GPU using ROCm",
+        "an [gold1 b]AMD[/] GPU (using ROCm™)",
         GpuType.ROCM,
     )
     cpu = (
@@ -240,13 +235,14 @@ def select_gpu() -> GpuType:
 
     options = []
     if OS == "Windows":
-        options = [nvidia, vintage_nvidia, cpu]
+        options = [nvidia, cpu]
     if OS == "Linux":
-        options = [nvidia, vintage_nvidia, amd, cpu]
+        options = [nvidia, amd, cpu]
     elif OS == "Darwin":
         options = [cpu]
 
     if len(options) == 1:
+        print(f'Your platform [gold1]{OS}-{ARCH}[/] only supports the "{options[0][1]}" driver. Proceeding with that.')
         return options[0][1]
 
     options = {str(i): opt for i, opt in enumerate(options, 1)}
@@ -259,7 +255,7 @@ def select_gpu() -> GpuType:
                     [
                         f"Detected the [gold1]{OS}-{ARCH}[/] platform",
                         "",
-                        "See [deep_sky_blue1]https://invoke-ai.github.io/InvokeAI/installation/requirements/[/] to ensure your system meets the minimum requirements.",
+                        "See [deep_sky_blue1]https://invoke-ai.github.io/InvokeAI/#system[/] to ensure your system meets the minimum requirements.",
                         "",
                         "[red3]🠶[/] [b]Your GPU drivers must be correctly installed before using InvokeAI![/] [red3]🠴[/]",
                     ]

installer/templates/invoke.bat.in

@@ -10,10 +10,11 @@ set INVOKEAI_ROOT=.
 echo Desired action:
 echo 1. Generate images with the browser-based interface
 echo 2. Open the developer console
-echo 3. Command-line help
+echo 3. Run the InvokeAI image database maintenance script
+echo 4. Command-line help
 echo Q - Quit
 echo.
-echo To update, download and run the installer from https://github.com/invoke-ai/InvokeAI/releases/latest
+echo To update, download and run the installer from https://github.com/invoke-ai/InvokeAI/releases/latest.
 echo.
 set /P choice="Please enter 1-4, Q: [1] "
 if not defined choice set choice=1
@@ -33,6 +34,9 @@ IF /I "%choice%" == "1" (
     echo *** Type `exit` to quit this shell and deactivate the Python virtual environment ***
     call cmd /k
 ) ELSE IF /I "%choice%" == "3" (
+   echo Running the db maintenance script...
+   python .venv\Scripts\invokeai-db-maintenance.exe
+) ELSE IF /I "%choice%" == "4" (
     echo Displaying command line help...
     python .venv\Scripts\invokeai-web.exe --help %*
     pause

installer/templates/invoke.sh.in

@@ -17,7 +17,7 @@
 set -eu
 
 # Ensure we're in the correct folder in case user's CWD is somewhere else
-scriptdir=$(dirname $(readlink -f "$0"))
+scriptdir=$(dirname "$0")
 cd "$scriptdir"
 
 . .venv/bin/activate
@@ -47,6 +47,11 @@ do_choice() {
         bash --init-file "$file_name"
         ;;
     3)
+        clear
+        printf "Running the db maintenance script\n"
+        invokeai-db-maintenance --root ${INVOKEAI_ROOT}
+        ;;
+    4)
         clear
         printf "Command-line help\n"
         invokeai-web --help
@@ -66,9 +71,10 @@ do_line_input() {
     printf "What would you like to do?\n"
     printf "1: Generate images using the browser-based interface\n"
     printf "2: Open the developer console\n"
-    printf "3: Command-line help\n"
+    printf "3: Run the InvokeAI image database maintenance script\n"
+    printf "4: Command-line help\n"
     printf "Q: Quit\n\n"
-    printf "To update, download and run the installer from https://github.com/invoke-ai/InvokeAI/releases/latest\n\n"
+    printf "To update, download and run the installer from https://github.com/invoke-ai/InvokeAI/releases/latest.\n\n"
     read -p "Please enter 1-4, Q: [1] " yn
     choice=${yn:='1'}
     do_choice $choice

invokeai/app/api/dependencies.py

@@ -1,45 +1,40 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-import asyncio
 from logging import Logger
 
 import torch
 
-from invokeai.app.services.board_image_records.board_image_records_sqlite import SqliteBoardImageRecordStorage
-from invokeai.app.services.board_images.board_images_default import BoardImagesService
-from invokeai.app.services.board_records.board_records_sqlite import SqliteBoardRecordStorage
-from invokeai.app.services.boards.boards_default import BoardService
-from invokeai.app.services.bulk_download.bulk_download_default import BulkDownloadService
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.download.download_default import DownloadQueueService
-from invokeai.app.services.events.events_fastapievents import FastAPIEventService
-from invokeai.app.services.image_files.image_files_disk import DiskImageFileStorage
-from invokeai.app.services.image_records.image_records_sqlite import SqliteImageRecordStorage
-from invokeai.app.services.images.images_default import ImageService
-from invokeai.app.services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
-from invokeai.app.services.invocation_services import InvocationServices
-from invokeai.app.services.invocation_stats.invocation_stats_default import InvocationStatsService
-from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.model_images.model_images_default import ModelImageFileStorageDisk
-from invokeai.app.services.model_manager.model_manager_default import ModelManagerService
-from invokeai.app.services.model_records.model_records_sql import ModelRecordServiceSQL
-from invokeai.app.services.names.names_default import SimpleNameService
 from invokeai.app.services.object_serializer.object_serializer_disk import ObjectSerializerDisk
 from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
-from invokeai.app.services.session_processor.session_processor_default import (
-    DefaultSessionProcessor,
-    DefaultSessionRunner,
-)
-from invokeai.app.services.session_queue.session_queue_sqlite import SqliteSessionQueue
 from invokeai.app.services.shared.sqlite.sqlite_util import init_db
-from invokeai.app.services.style_preset_images.style_preset_images_disk import StylePresetImageFileStorageDisk
-from invokeai.app.services.style_preset_records.style_preset_records_sqlite import SqliteStylePresetRecordsStorage
-from invokeai.app.services.urls.urls_default import LocalUrlService
-from invokeai.app.services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
 from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.version.invokeai_version import __version__
 
+from ..services.board_image_records.board_image_records_sqlite import SqliteBoardImageRecordStorage
+from ..services.board_images.board_images_default import BoardImagesService
+from ..services.board_records.board_records_sqlite import SqliteBoardRecordStorage
+from ..services.boards.boards_default import BoardService
+from ..services.bulk_download.bulk_download_default import BulkDownloadService
+from ..services.config import InvokeAIAppConfig
+from ..services.download import DownloadQueueService
+from ..services.image_files.image_files_disk import DiskImageFileStorage
+from ..services.image_records.image_records_sqlite import SqliteImageRecordStorage
+from ..services.images.images_default import ImageService
+from ..services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
+from ..services.invocation_services import InvocationServices
+from ..services.invocation_stats.invocation_stats_default import InvocationStatsService
+from ..services.invoker import Invoker
+from ..services.model_images.model_images_default import ModelImageFileStorageDisk
+from ..services.model_manager.model_manager_default import ModelManagerService
+from ..services.model_records import ModelRecordServiceSQL
+from ..services.names.names_default import SimpleNameService
+from ..services.session_processor.session_processor_default import DefaultSessionProcessor
+from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
+from ..services.urls.urls_default import LocalUrlService
+from ..services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
+from .events import FastAPIEventService
+
 
 # TODO: is there a better way to achieve this?
 def check_internet() -> bool:
@@ -66,12 +61,7 @@ class ApiDependencies:
     invoker: Invoker
 
     @staticmethod
-    def initialize(
-        config: InvokeAIAppConfig,
-        event_handler_id: int,
-        loop: asyncio.AbstractEventLoop,
-        logger: Logger = logger,
-    ) -> None:
+    def initialize(config: InvokeAIAppConfig, event_handler_id: int, logger: Logger = logger) -> None:
         logger.info(f"InvokeAI version {__version__}")
         logger.info(f"Root directory = {str(config.root_path)}")
 
@@ -82,7 +72,6 @@ class ApiDependencies:
         image_files = DiskImageFileStorage(f"{output_folder}/images")
 
         model_images_folder = config.models_path
-        style_presets_folder = config.style_presets_path
 
         db = init_db(config=config, logger=logger, image_files=image_files)
 
@@ -93,7 +82,7 @@ class ApiDependencies:
         board_images = BoardImagesService()
         board_records = SqliteBoardRecordStorage(db=db)
         boards = BoardService()
-        events = FastAPIEventService(event_handler_id, loop=loop)
+        events = FastAPIEventService(event_handler_id)
         bulk_download = BulkDownloadService()
         image_records = SqliteImageRecordStorage(db=db)
         images = ImageService()
@@ -104,22 +93,20 @@ class ApiDependencies:
         conditioning = ObjectSerializerForwardCache(
             ObjectSerializerDisk[ConditioningFieldData](output_folder / "conditioning", ephemeral=True)
         )
-        download_queue_service = DownloadQueueService(app_config=configuration, event_bus=events)
+        download_queue_service = DownloadQueueService(event_bus=events)
         model_images_service = ModelImageFileStorageDisk(model_images_folder / "model_images")
         model_manager = ModelManagerService.build_model_manager(
             app_config=configuration,
-            model_record_service=ModelRecordServiceSQL(db=db, logger=logger),
+            model_record_service=ModelRecordServiceSQL(db=db),
             download_queue=download_queue_service,
             events=events,
         )
         names = SimpleNameService()
         performance_statistics = InvocationStatsService()
-        session_processor = DefaultSessionProcessor(session_runner=DefaultSessionRunner())
+        session_processor = DefaultSessionProcessor()
         session_queue = SqliteSessionQueue(db=db)
         urls = LocalUrlService()
         workflow_records = SqliteWorkflowRecordsStorage(db=db)
-        style_preset_records = SqliteStylePresetRecordsStorage(db=db)
-        style_preset_image_files = StylePresetImageFileStorageDisk(style_presets_folder / "images")
 
         services = InvocationServices(
             board_image_records=board_image_records,
@@ -145,8 +132,6 @@ class ApiDependencies:
             workflow_records=workflow_records,
             tensors=tensors,
             conditioning=conditioning,
-            style_preset_records=style_preset_records,
-            style_preset_image_files=style_preset_image_files,
         )
 
         ApiDependencies.invoker = Invoker(services)

invokeai/app/api/events.py

@@ -0,0 +1,52 @@
+# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
+
+import asyncio
+import threading
+from queue import Empty, Queue
+from typing import Any
+
+from fastapi_events.dispatcher import dispatch
+
+from ..services.events.events_base import EventServiceBase
+
+
+class FastAPIEventService(EventServiceBase):
+    event_handler_id: int
+    __queue: Queue
+    __stop_event: threading.Event
+
+    def __init__(self, event_handler_id: int) -> None:
+        self.event_handler_id = event_handler_id
+        self.__queue = Queue()
+        self.__stop_event = threading.Event()
+        asyncio.create_task(self.__dispatch_from_queue(stop_event=self.__stop_event))
+
+        super().__init__()
+
+    def stop(self, *args, **kwargs):
+        self.__stop_event.set()
+        self.__queue.put(None)
+
+    def dispatch(self, event_name: str, payload: Any) -> None:
+        self.__queue.put({"event_name": event_name, "payload": payload})
+
+    async def __dispatch_from_queue(self, stop_event: threading.Event):
+        """Get events on from the queue and dispatch them, from the correct thread"""
+        while not stop_event.is_set():
+            try:
+                event = self.__queue.get(block=False)
+                if not event:  # Probably stopping
+                    continue
+
+                dispatch(
+                    event.get("event_name"),
+                    payload=event.get("payload"),
+                    middleware_id=self.event_handler_id,
+                )
+
+            except Empty:
+                await asyncio.sleep(0.1)
+                pass
+
+            except asyncio.CancelledError as e:
+                raise e  # Raise a proper error

invokeai/app/api/routers/app_info.py

@@ -10,13 +10,15 @@ from fastapi import Body
 from fastapi.routing import APIRouter
 from pydantic import BaseModel, Field
 
-from invokeai.app.api.dependencies import ApiDependencies
 from invokeai.app.invocations.upscale import ESRGAN_MODELS
 from invokeai.app.services.invocation_cache.invocation_cache_common import InvocationCacheStatus
-from invokeai.backend.image_util.infill_methods.patchmatch import PatchMatch
+from invokeai.backend.image_util.patchmatch import PatchMatch
+from invokeai.backend.image_util.safety_checker import SafetyChecker
 from invokeai.backend.util.logging import logging
 from invokeai.version import __version__
 
+from ..dependencies import ApiDependencies
+
 
 class LogLevel(int, Enum):
     NotSet = logging.NOTSET
@@ -40,8 +42,6 @@ class AppVersion(BaseModel):
 
     version: str = Field(description="App version")
 
-    highlights: Optional[list[str]] = Field(default=None, description="Highlights of release")
-
 
 class AppDependencyVersions(BaseModel):
     """App depencency Versions Response"""
@@ -100,7 +100,7 @@ async def get_app_deps() -> AppDependencyVersions:
 
 @app_router.get("/config", operation_id="get_config", status_code=200, response_model=AppConfig)
 async def get_config() -> AppConfig:
-    infill_methods = ["lama", "tile", "cv2", "color"]  # TODO: add mosaic back
+    infill_methods = ["tile", "lama", "cv2"]
     if PatchMatch.patchmatch_available():
         infill_methods.append("patchmatch")
 
@@ -109,7 +109,9 @@ async def get_config() -> AppConfig:
         upscaling_models.append(str(Path(model).stem))
     upscaler = Upscaler(upscaling_method="esrgan", upscaling_models=upscaling_models)
 
-    nsfw_methods = ["nsfw_checker"]
+    nsfw_methods = []
+    if SafetyChecker.safety_checker_available():
+        nsfw_methods.append("nsfw_checker")
 
     watermarking_methods = ["invisible_watermark"]