Release/v3.6.0 (#5485)

## What type of PR is this? (check all applicable)

Release v3.6.0

## Have you discussed this change with the InvokeAI team?
- [X] Yes
- [ ] No, because:

      
## Have you updated all relevant documentation?
- [X] Yes
- [ ] No


## Description
Invoke v3.6.0

## QA Instructions, Screenshots, Recordings



[InvokeAI-installer-v3.6.0.zip](https://github.com/invoke-ai/InvokeAI/files/13923761/InvokeAI-installer-v3.6.0.zip)

## [optional] Are there any post deployment tasks we need to perform?
1. Release on PyPi
2. Release on GitHub
3. Announce in #releases

.github/CODEOWNERS

@@ -1,5 +1,5 @@
 # continuous integration
-/.github/workflows/  @lstein @blessedcoolant @hipsterusername
+/.github/workflows/  @lstein @blessedcoolant @hipsterusername @ebr
 
 # documentation
 /docs/ @lstein @blessedcoolant @hipsterusername @Millu
@@ -10,7 +10,7 @@
 
 # installation and configuration
 /pyproject.toml  @lstein @blessedcoolant @hipsterusername
-/docker/  @lstein @blessedcoolant @hipsterusername
+/docker/  @lstein @blessedcoolant @hipsterusername @ebr
 /scripts/ @ebr @lstein @hipsterusername
 /installer/ @lstein @ebr @hipsterusername
 /invokeai/assets @lstein @ebr @hipsterusername
@@ -26,9 +26,7 @@
 
 # front ends
 /invokeai/frontend/CLI @lstein @hipsterusername
-/invokeai/frontend/install @lstein @ebr @hipsterusername 
+/invokeai/frontend/install @lstein @ebr @hipsterusername
 /invokeai/frontend/merge @lstein @blessedcoolant @hipsterusername
 /invokeai/frontend/training @lstein @blessedcoolant @hipsterusername
 /invokeai/frontend/web @psychedelicious @blessedcoolant @maryhipp @hipsterusername
-
-

.github/workflows/build-container.yml

@@ -40,10 +40,14 @@ jobs:
       - name: Free up more disk space on the runner
         # https://github.com/actions/runner-images/issues/2840#issuecomment-1284059930
         run: |
+          echo "----- Free space before cleanup"
+          df -h
           sudo rm -rf /usr/share/dotnet
           sudo rm -rf "$AGENT_TOOLSDIRECTORY"
           sudo swapoff /mnt/swapfile
           sudo rm -rf /mnt/swapfile
+          echo "----- Free space after cleanup"
+          df -h
 
       - name: Checkout
         uses: actions/checkout@v3
@@ -91,6 +95,7 @@ jobs:
       #     password: ${{ secrets.DOCKERHUB_TOKEN }}
 
       - name: Build container
+        timeout-minutes: 40
         id: docker_build
         uses: docker/build-push-action@v4
         with:

README.md

@@ -1,10 +1,10 @@
 <div align="center">
 
-![project hero](https://github.com/invoke-ai/InvokeAI/assets/31807370/1a917d94-e099-4fa1-a70f-7dd8d0691018)
+![project hero](https://github.com/invoke-ai/InvokeAI/assets/31807370/6e3728c7-e90e-4711-905c-3b55844ff5be)
 
-# Invoke AI - Generative AI for Professional Creatives
-## Professional Creative Tools for Stable Diffusion, Custom-Trained Models, and more. 
-  To learn more about Invoke AI, get started instantly, or implement our Business solutions, visit [invoke.ai](https://invoke.ai)
+# 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)
+  
 
 
 [![discord badge]][discord link]
@@ -56,7 +56,9 @@ the foundation for multiple commercial products.
 
 <div align="center">
 
-![canvas preview](https://github.com/invoke-ai/InvokeAI/raw/main/docs/assets/canvas_preview.png)
+
+![Highlighted Features - Canvas and Workflows](https://github.com/invoke-ai/InvokeAI/assets/31807370/708f7a82-084f-4860-bfbe-e2588c53548d)
+
 
 </div>
 

docker/.env.sample

@@ -2,14 +2,17 @@
 ## Any environment variables supported by InvokeAI can be specified here,
 ## in addition to the examples below.
 
-# INVOKEAI_ROOT is the path to a path on the local filesystem where InvokeAI will store data.
+# HOST_INVOKEAI_ROOT is the path on the docker host's filesystem where InvokeAI will store data.
 # Outputs will also be stored here by default.
-# This **must** be an absolute path.
-INVOKEAI_ROOT=
+# If relative, it will be relative to the docker directory in which the docker-compose.yml file is located
+#HOST_INVOKEAI_ROOT=../../invokeai-data
+
+# INVOKEAI_ROOT is the path to the root of the InvokeAI repository within the container.
+# INVOKEAI_ROOT=~/invokeai
 
 # Get this value from your HuggingFace account settings page.
 # HUGGING_FACE_HUB_TOKEN=
 
 ## optional variables specific to the docker setup.
-# GPU_DRIVER=cuda # or rocm
+# GPU_DRIVER=nvidia #| rocm
 # CONTAINER_UID=1000

docker/Dockerfile

@@ -59,7 +59,7 @@ RUN --mount=type=cache,target=/root/.cache/pip \
 
 # #### Build the Web UI ------------------------------------
 
-FROM node:18-slim AS web-builder
+FROM node:20-slim AS web-builder
 ENV PNPM_HOME="/pnpm"
 ENV PATH="$PNPM_HOME:$PATH"
 RUN corepack enable
@@ -68,7 +68,7 @@ WORKDIR /build
 COPY invokeai/frontend/web/ ./
 RUN --mount=type=cache,target=/pnpm/store \
     pnpm install --frozen-lockfile
-RUN pnpm run build
+RUN npx vite build
 
 #### Runtime stage ---------------------------------------
 

docker/README.md

@@ -1,6 +1,14 @@
 # InvokeAI Containerized
 
-All commands are to be run from the `docker` directory: `cd docker`
+All commands should be run within the `docker` directory: `cd docker`
+
+## Quickstart :rocket:
+
+On a known working Linux+Docker+CUDA (Nvidia) system, execute `./run.sh` in this directory. It will take a few minutes - depending on your internet speed - to install the core models. Once the application starts up, open `http://localhost:9090` in your browser to Invoke!
+
+For more configuration options (using an AMD GPU, custom root directory location, etc): read on.
+
+## Detailed setup
 
 #### Linux
 
@@ -18,7 +26,7 @@ All commands are to be run from the `docker` directory: `cd docker`
 
 This is done via Docker Desktop preferences
 
-## Quickstart
+### Configure Invoke environment
 
 1. Make a copy of `env.sample` and name it `.env` (`cp env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to:
     a. the desired location of the InvokeAI runtime directory, or
@@ -37,19 +45,21 @@ The runtime directory (holding models and outputs) will be created in the locati
 
 The Docker daemon on the system must be already set up to use the GPU. In case of Linux, this involves installing `nvidia-docker-runtime` and configuring the `nvidia` runtime as default. Steps will be different for AMD. Please see Docker documentation for the most up-to-date instructions for using your GPU with Docker.
 
+To use an AMD GPU, set `GPU_DRIVER=rocm` in your `.env` file.
+
 ## Customize
 
 Check the `.env.sample` file. It contains some environment variables for running in Docker. Copy it, name it `.env`, and fill it in with your own values. Next time you run `run.sh`, your custom values will be used.
 
 You can also set these values in `docker-compose.yml` directly, but `.env` will help avoid conflicts when code is updated.
 
-Example (values are optional, but setting `INVOKEAI_ROOT` is highly recommended):
+Values are optional, but setting `INVOKEAI_ROOT` is highly recommended. The default is `~/invokeai`. Example:
 
 ```bash
 INVOKEAI_ROOT=/Volumes/WorkDrive/invokeai
 HUGGINGFACE_TOKEN=the_actual_token
 CONTAINER_UID=1000
-GPU_DRIVER=cuda
+GPU_DRIVER=nvidia
 ```
 
 Any environment variables supported by InvokeAI can be set here - please see the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.

docker/docker-compose.yml

@@ -21,7 +21,9 @@ x-invokeai: &invokeai
     ports:
       - "${INVOKEAI_PORT:-9090}:9090"
     volumes:
-      - ${INVOKEAI_ROOT:-~/invokeai}:${INVOKEAI_ROOT:-/invokeai}
+      - type: bind
+        source: ${HOST_INVOKEAI_ROOT:-${INVOKEAI_ROOT:-~/invokeai}}
+        target: ${INVOKEAI_ROOT:-/invokeai}
       - ${HF_HOME:-~/.cache/huggingface}:${HF_HOME:-/invokeai/.cache/huggingface}
       # - ${INVOKEAI_MODELS_DIR:-${INVOKEAI_ROOT:-/invokeai/models}}
       # - ${INVOKEAI_MODELS_CONFIG_PATH:-${INVOKEAI_ROOT:-/invokeai/configs/models.yaml}}

docker/run.sh

@@ -1,5 +1,5 @@
 #!/usr/bin/env bash
-set -e
+set -e -o pipefail
 
 run() {
   local scriptdir=$(dirname "${BASH_SOURCE[0]}")
@@ -8,14 +8,18 @@ run() {
   local build_args=""
   local profile=""
 
-  [[ -f ".env" ]] &&
-    build_args=$(awk '$1 ~ /=[^$]/ && $0 !~ /^#/ {print "--build-arg " $0 " "}' .env) &&
-    profile="$(awk -F '=' '/GPU_DRIVER/ {print $2}' .env)"
+  touch .env
+  build_args=$(awk '$1 ~ /=[^$]/ && $0 !~ /^#/ {print "--build-arg " $0 " "}' .env) &&
+  profile="$(awk -F '=' '/GPU_DRIVER/ {print $2}' .env)"
+
+  [[ -z "$profile" ]] && profile="nvidia"
 
   local service_name="invokeai-$profile"
 
-  printf "%s\n" "docker compose build args:"
-  printf "%s\n" "$build_args"
+  if [[ ! -z "$build_args" ]]; then
+    printf "%s\n" "docker compose build args:"
+    printf "%s\n" "$build_args"
+  fi
 
   docker compose build $build_args
   unset build_args

docs/deprecated/2to3.md

@@ -0,0 +1,53 @@
+## :octicons-log-16: Important Changes Since Version 2.3
+
+### Nodes
+
+Behind the scenes, InvokeAI has been completely rewritten to support
+"nodes," small unitary operations that can be combined into graphs to
+form arbitrary workflows. For example, there is a prompt node that
+processes the prompt string and feeds it to a text2latent node that
+generates a latent image. The latents are then fed to a latent2image
+node that translates the latent image into a PNG.
+
+The WebGUI has a node editor that allows you to graphically design and
+execute custom node graphs. The ability to save and load graphs is
+still a work in progress, but coming soon.
+
+### Command-Line Interface Retired
+
+All "invokeai" command-line interfaces have been retired as of version
+3.4.
+
+To launch the Web GUI from the command-line, use the command
+`invokeai-web` rather than the traditional `invokeai --web`.
+
+### ControlNet
+
+This version of InvokeAI features ControlNet, a system that allows you
+to achieve exact poses for human and animal figures by providing a
+model to follow. Full details are found in [ControlNet](features/CONTROLNET.md)
+
+### New Schedulers
+
+The list of schedulers has been completely revamped and brought up to date:
+
+| **Short Name** | **Scheduler**                   | **Notes**                   |
+|----------------|---------------------------------|-----------------------------|
+| **ddim**       | DDIMScheduler                   |                             |
+| **ddpm**       | DDPMScheduler                   |                             |
+| **deis**       | DEISMultistepScheduler          |                             |
+| **lms**        | LMSDiscreteScheduler            |                             |
+| **pndm**       | PNDMScheduler                   |                             |
+| **heun**       | HeunDiscreteScheduler           | original noise schedule     |
+| **heun_k**     | HeunDiscreteScheduler           | using karras noise schedule |
+| **euler**      | EulerDiscreteScheduler          | original noise schedule     |
+| **euler_k**    | EulerDiscreteScheduler          | using karras noise schedule |
+| **kdpm_2**     | KDPM2DiscreteScheduler          |                             |
+| **kdpm_2_a**   | KDPM2AncestralDiscreteScheduler |                             |
+| **dpmpp_2s**   | DPMSolverSinglestepScheduler    |                             |
+| **dpmpp_2m**   | DPMSolverMultistepScheduler     | original noise scnedule     |
+| **dpmpp_2m_k** | DPMSolverMultistepScheduler     | using karras noise schedule |
+| **unipc**      | UniPCMultistepScheduler         | CPU only                    |
+| **lcm**        | LCMScheduler                    |                             |
+
+Please see [3.0.0 Release Notes](https://github.com/invoke-ai/InvokeAI/releases/tag/v3.0.0) for further details.

docs/features/UNIFIED_CANVAS.md

@@ -229,29 +229,28 @@ clarity on the intent and common use cases we expect for utilizing them.
   currently being rendered by your browser into a merged copy of the image. This
   lowers the resource requirements and should improve performance.
 
-### Seam Correction
+### Compositing / Seam Correction
 
 When doing Inpainting or Outpainting, Invoke needs to merge the pixels generated
-by Stable Diffusion into your existing image. To do this, the area around the
-`seam` at the boundary between your image and the new generation is
+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 seam, and then the area of the seam is
+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 seam Inpainting. A wider seam and
-a blur setting of about 1/3 of the seam have been noted as producing
-consistently strong results (e.g. 96 wide and 16 blur - adds up to 32 blur with
-both sides). Seam strength of 0.7 is best for reducing hard seams.
+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. 
 
-- **Seam Size** - The size of the seam masked area. Set higher to make a larger
-  mask around the seam.
-- **Seam Blur** - The size of the blur that is applied on _each_ side of the
-  masked area.
-- **Seam Strength** - The Image To Image Strength parameter used for the
-  Inpainting generation that is applied to the seam area.
-- **Seam Steps** - The number of generation steps that should be used to Inpaint
-  the seam.
 
 ### Infill & Scaling
 

docs/index.md

@@ -18,7 +18,7 @@ title: Home
       width: 100%;
       max-width: 100%;
       height: 50px;
-      background-color: #448AFF;
+      background-color: #35A4DB;
       color: #fff;
       font-size: 16px;
       border: none;
@@ -43,7 +43,7 @@ title: Home
 <div align="center" markdown>
 
 
-[![project logo](assets/invoke_ai_banner.png)](https://github.com/invoke-ai/InvokeAI)
+[![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]
 
@@ -145,60 +145,6 @@ Mac and Linux machines, and runs on GPU cards with as little as 4 GB of RAM.
 - [Guide to InvokeAI Runtime Settings](features/CONFIGURATION.md)
 - [Database Maintenance and other Command Line Utilities](features/UTILITIES.md)
 
-## :octicons-log-16: Important Changes Since Version 2.3
-
-### Nodes
-
-Behind the scenes, InvokeAI has been completely rewritten to support
-"nodes," small unitary operations that can be combined into graphs to
-form arbitrary workflows. For example, there is a prompt node that
-processes the prompt string and feeds it to a text2latent node that
-generates a latent image. The latents are then fed to a latent2image
-node that translates the latent image into a PNG.
-
-The WebGUI has a node editor that allows you to graphically design and
-execute custom node graphs. The ability to save and load graphs is
-still a work in progress, but coming soon.
-
-### Command-Line Interface Retired
-
-All "invokeai" command-line interfaces have been retired as of version
-3.4.
-
-To launch the Web GUI from the command-line, use the command
-`invokeai-web` rather than the traditional `invokeai --web`.
-
-### ControlNet
-
-This version of InvokeAI features ControlNet, a system that allows you
-to achieve exact poses for human and animal figures by providing a
-model to follow. Full details are found in [ControlNet](features/CONTROLNET.md)
-
-### New Schedulers
-
-The list of schedulers has been completely revamped and brought up to date:
-
-| **Short Name** | **Scheduler**                   | **Notes**                   |
-|----------------|---------------------------------|-----------------------------|
-| **ddim**       | DDIMScheduler                   |                             |
-| **ddpm**       | DDPMScheduler                   |                             |
-| **deis**       | DEISMultistepScheduler          |                             |
-| **lms**        | LMSDiscreteScheduler            |                             |
-| **pndm**       | PNDMScheduler                   |                             |
-| **heun**       | HeunDiscreteScheduler           | original noise schedule     |
-| **heun_k**     | HeunDiscreteScheduler           | using karras noise schedule |
-| **euler**      | EulerDiscreteScheduler          | original noise schedule     |
-| **euler_k**    | EulerDiscreteScheduler          | using karras noise schedule |
-| **kdpm_2**     | KDPM2DiscreteScheduler          |                             |
-| **kdpm_2_a**   | KDPM2AncestralDiscreteScheduler |                             |
-| **dpmpp_2s**   | DPMSolverSinglestepScheduler    |                             |
-| **dpmpp_2m**   | DPMSolverMultistepScheduler     | original noise scnedule     |
-| **dpmpp_2m_k** | DPMSolverMultistepScheduler     | using karras noise schedule |
-| **unipc**      | UniPCMultistepScheduler         | CPU only                    |
-| **lcm**        | LCMScheduler                    |                             |
-
-Please see [3.0.0 Release Notes](https://github.com/invoke-ai/InvokeAI/releases/tag/v3.0.0) for further details.
-
 ## :material-target: Troubleshooting
 
 Please check out our **[:material-frequently-asked-questions:

docs/javascripts/init_kapa_widget.js

@@ -1,10 +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);
-});
+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/nodes/NODES.md

@@ -6,10 +6,17 @@ If you're not familiar with Diffusion, take a look at our [Diffusion Overview.](
 
 ## Features
 
+### Workflow Library
+The Workflow Library enables you to save workflows to the Invoke database, allowing you to easily creating, modify and share workflows as needed. 
+
+A curated set of workflows are provided by default - these are designed to help explain important nodes' usage in the Workflow Editor.
+
+![workflow_library](../assets/nodes/workflow_library.png)
+
 ### Linear View
 The Workflow Editor allows you to create a UI for your workflow, to make it easier to iterate on your generations. 
 
-To add an input to the Linear UI, right click on the input label and select "Add to Linear View".
+To add an input to the Linear UI, right click on the **input label** and select "Add to Linear View".
 
 The Linear UI View will also be part of the saved workflow, allowing you share workflows and enable other to use them, regardless of complexity. 
 
@@ -30,7 +37,7 @@ Any node or input field can be renamed in the workflow editor. If the input fiel
 Nodes have a "Use Cache" option in their footer. This allows for performance improvements by using the previously cached values during the workflow processing. 
 
 
-## Important Concepts 
+## Important Nodes & Concepts 
 
 There are several node grouping concepts that can be examined with a narrow focus. These (and other) groupings can be pieced together to make up functional graph setups, and are important to understanding how groups of nodes work together as part of a whole. Note that the screenshots below aren't examples of complete functioning node graphs (see Examples).
 
@@ -56,7 +63,7 @@ The ImageToLatents node takes in a pixel image and a VAE and outputs a latents.
 
 It is common to want to use both the same seed (for continuity) and random seeds (for variety). To define a seed, simply enter it into the 'Seed' field on a noise node. Conversely, the RandomInt node generates a random integer between 'Low' and 'High', and can be used as input to the 'Seed' edge point on a noise node to randomize your seed.
 
-![groupsrandseed](../assets/nodes/groupsrandseed.png)
+![groupsrandseed](../assets/nodes/groupsnoise.png)
 
 ### ControlNet
 

docs/nodes/communityNodes.md

@@ -36,7 +36,8 @@ To use a community workflow, download the the `.json` node graph file and load i
     + [Mask Operations](#mask-operations)
     + [Match Histogram](#match-histogram)
     + [Metadata-Linked](#metadata-linked-nodes)
-    + [Negative Image](#negative-image)    
+    + [Negative Image](#negative-image)
+    + [Nightmare Promptgen](#nightmare-promptgen)    
     + [Oobabooga](#oobabooga)
     + [Prompt Tools](#prompt-tools)
     + [Remote Image](#remote-image)
@@ -346,6 +347,13 @@ Node Link: https://github.com/VeyDlin/negative-image-node
 View:
 </br><img src="https://raw.githubusercontent.com/VeyDlin/negative-image-node/master/.readme/node.png" width="500" />
 
+--------------------------------
+### Nightmare Promptgen
+
+**Description:** Nightmare Prompt Generator - Uses a local text generation model to create unique imaginative (but usually nightmarish) prompts for InvokeAI. By default, it allows you to choose from some gpt-neo models I finetuned on over 2500 of my own InvokeAI prompts in Compel format, but you're able to add your own, as well. Offers support for replacing any troublesome words with a random choice from list you can also define.
+
+**Node Link:** [https://github.com/gogurtenjoyer/nightmare-promptgen](https://github.com/gogurtenjoyer/nightmare-promptgen)
+
 --------------------------------
 ### Oobabooga
 

docs/nodes/exampleWorkflows.md

@@ -1,6 +1,6 @@
 # Example Workflows
 
-We've curated some example workflows for you to get started with Workflows in InvokeAI
+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!
 

docs/other/CONTRIBUTORS.md

@@ -215,6 +215,7 @@ We thank them for all of their time and hard work.
 - Robert Bolender
 - Robin Rombach
 - Rohan Barar
+- rohinish404
 - rpagliuca
 - rromb
 - Rupesh Sreeraman

docs/stylesheets/extra.css

@@ -0,0 +1,5 @@
+:root {
+    --md-primary-fg-color:        #35A4DB;
+    --md-primary-fg-color--light: #35A4DB;
+    --md-primary-fg-color--dark:  #35A4DB;
+  }

docs/workflows/Text_to_Image.json

@@ -1,8 +1,8 @@
 {
-  "name": "Text to Image",
+  "name": "Text to Image - SD1.5",
   "author": "InvokeAI",
   "description": "Sample text to image workflow for Stable Diffusion 1.5/2",
-  "version": "1.0.1",
+  "version": "1.1.0",
   "contact": "invoke@invoke.ai",
   "tags": "text2image, SD1.5, SD2, default",
   "notes": "",
@@ -18,10 +18,19 @@
     {
       "nodeId": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
       "fieldName": "prompt"
+    },
+    {
+      "nodeId": "55705012-79b9-4aac-9f26-c0b10309785b",
+      "fieldName": "width"
+    },
+    {
+      "nodeId": "55705012-79b9-4aac-9f26-c0b10309785b",
+      "fieldName": "height"
     }
   ],
   "meta": {
-    "version": "1.0.0"
+    "category": "default",
+    "version": "2.0.0"
   },
   "nodes": [
     {
@@ -30,44 +39,56 @@
       "data": {
         "id": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
         "type": "compel",
+        "label": "Negative Compel Prompt",
+        "isOpen": true,
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+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "ImageField"
+            }
           },
           "width": {
             "id": "c8c907d8-1066-49d1-b9a6-83bdcd53addc",
             "name": "width",
-            "type": "integer",
-            "fieldKind": "output"
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            }
           },
           "height": {
             "id": "230f359c-b4ea-436c-b372-332d7dcdca85",
             "name": "height",
-            "type": "integer",
-            "fieldKind": "output"
+            "fieldKind": "output",
+            "type": {
+              "isCollection": false,
+              "isCollectionOrScalar": false,
+              "name": "IntegerField"
+            }
           }
-        },
-        "label": "",
-        "isOpen": true,
-        "notes": "",
-        "embedWorkflow": false,
-        "isIntermediate": false,
-        "useCache": true,
-        "version": "1.0.0"
+        }
       },
       "width": 320,
-      "height": 267,
+      "height": 266,
       "position": {
-        "x": 2037.9648469717395,
-        "y": 426.10844427600136
+        "x": 1800,
+        "y": 25
       }
     }
   ],
   "edges": [
     {
-      "source": "ea94bc37-d995-4a83-aa99-4af42479f2f2",
-      "sourceHandle": "value",
-      "target": "55705012-79b9-4aac-9f26-c0b10309785b",
-      "targetHandle": "seed",
       "id": "reactflow__edge-ea94bc37-d995-4a83-aa99-4af42479f2f2value-55705012-79b9-4aac-9f26-c0b10309785bseed",
-      "type": "default"
+      "source": "ea94bc37-d995-4a83-aa99-4af42479f2f2",
+      "target": "55705012-79b9-4aac-9f26-c0b10309785b",
+      "type": "default",
+      "sourceHandle": "value",
+      "targetHandle": "seed"
     },
     {
-      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
-      "sourceHandle": "clip",
-      "target": "7d8bf987-284f-413a-b2fd-d825445a5d6c",
-      "targetHandle": "clip",
       "id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8clip-7d8bf987-284f-413a-b2fd-d825445a5d6cclip",
-      "type": "default"
-    },
-    {
       "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "target": "7d8bf987-284f-413a-b2fd-d825445a5d6c",
+      "type": "default",
       "sourceHandle": "clip",
-      "target": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
-      "targetHandle": "clip",
+      "targetHandle": "clip"
+    },
+    {
       "id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8clip-93dc02a4-d05b-48ed-b99c-c9b616af3402clip",
-      "type": "default"
+      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "target": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
+      "type": "default",
+      "sourceHandle": "clip",
+      "targetHandle": "clip"
     },
     {
-      "source": "55705012-79b9-4aac-9f26-c0b10309785b",
-      "sourceHandle": "noise",
-      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
-      "targetHandle": "noise",
       "id": "reactflow__edge-55705012-79b9-4aac-9f26-c0b10309785bnoise-eea2702a-19fb-45b5-9d75-56b4211ec03cnoise",
-      "type": "default"
+      "source": "55705012-79b9-4aac-9f26-c0b10309785b",
+      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "type": "default",
+      "sourceHandle": "noise",
+      "targetHandle": "noise"
     },
     {
-      "source": "7d8bf987-284f-413a-b2fd-d825445a5d6c",
-      "sourceHandle": "conditioning",
-      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
-      "targetHandle": "positive_conditioning",
       "id": "reactflow__edge-7d8bf987-284f-413a-b2fd-d825445a5d6cconditioning-eea2702a-19fb-45b5-9d75-56b4211ec03cpositive_conditioning",
-      "type": "default"
-    },
-    {
-      "source": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
+      "source": "7d8bf987-284f-413a-b2fd-d825445a5d6c",
+      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
+      "type": "default",
       "sourceHandle": "conditioning",
-      "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
-      "targetHandle": "negative_conditioning",
+      "targetHandle": "positive_conditioning"
+    },
+    {
       "id": "reactflow__edge-93dc02a4-d05b-48ed-b99c-c9b616af3402conditioning-eea2702a-19fb-45b5-9d75-56b4211ec03cnegative_conditioning",
-      "type": "default"
-    },
-    {
-      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
-      "sourceHandle": "unet",
+      "source": "93dc02a4-d05b-48ed-b99c-c9b616af3402",
       "target": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
-      "targetHandle": "unet",
+      "type": "default",
+      "sourceHandle": "conditioning",
+      "targetHandle": "negative_conditioning"
+    },
+    {
       "id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8unet-eea2702a-19fb-45b5-9d75-56b4211ec03cunet",
-      "type": "default"
-    },
-    {
-      "source": "eea2702a-19fb-45b5-9d75-56b4211ec03c",
-      "sourceHandle": "latents",
-      "target": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
-      "targetHandle": "latents",
-      "id": "reactflow__edge-eea2702a-19fb-45b5-9d75-56b4211ec03clatents-58c957f5-0d01-41fc-a803-b2bbf0413d4flatents",
-      "type": "default"
-    },
-    {
       "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
-      "sourceHandle": "vae",
+      "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",
-      "targetHandle": "vae",
+      "type": "default",
+      "sourceHandle": "latents",
+      "targetHandle": "latents"
+    },
+    {
       "id": "reactflow__edge-c8d55139-f380-4695-b7f2-8b3d1e1e3db8vae-58c957f5-0d01-41fc-a803-b2bbf0413d4fvae",
-      "type": "default"
+      "source": "c8d55139-f380-4695-b7f2-8b3d1e1e3db8",
+      "target": "58c957f5-0d01-41fc-a803-b2bbf0413d4f",
+      "type": "default",
+      "sourceHandle": "vae",
+      "targetHandle": "vae"
     }
   ]
-}
+}

installer/lib/installer.py

@@ -241,12 +241,12 @@ class InvokeAiInstance:
             pip[
                 "install",
                 "--require-virtualenv",
-                "numpy~=1.24.0",  # choose versions that won't be uninstalled during phase 2
+                "numpy==1.26.3",  # choose versions that won't be uninstalled during phase 2
                 "urllib3~=1.26.0",
                 "requests~=2.28.0",
-                "torch==2.1.1",
+                "torch==2.1.2",
                 "torchmetrics==0.11.4",
-                "torchvision>=0.16.1",
+                "torchvision==0.16.2",
                 "--force-reinstall",
                 "--find-links" if find_links is not None else None,
                 find_links,

invokeai/app/api/routers/utilities.py

@@ -23,10 +23,11 @@ class DynamicPromptsResponse(BaseModel):
 )
 async def parse_dynamicprompts(
     prompt: str = Body(description="The prompt to parse with dynamicprompts"),
-    max_prompts: int = Body(default=1000, description="The max number of prompts to generate"),
+    max_prompts: int = Body(ge=1, le=10000, default=1000, description="The max number of prompts to generate"),
     combinatorial: bool = Body(default=True, description="Whether to use the combinatorial generator"),
 ) -> DynamicPromptsResponse:
     """Creates a batch process"""
+    max_prompts = min(max_prompts, 10000)
     generator: Union[RandomPromptGenerator, CombinatorialPromptGenerator]
     try:
         error: Optional[str] = None

invokeai/app/api_app.py

@@ -76,7 +76,7 @@ mimetypes.add_type("text/css", ".css")
 
 # Create the app
 # TODO: create this all in a method so configuration/etc. can be passed in?
-app = FastAPI(title="Invoke AI", docs_url=None, redoc_url=None, separate_input_output_schemas=False)
+app = FastAPI(title="Invoke - Community Edition", docs_url=None, redoc_url=None, separate_input_output_schemas=False)
 
 # Add event handler
 event_handler_id: int = id(app)
@@ -205,8 +205,8 @@ app.openapi = custom_openapi  # type: ignore [method-assign] # this is a valid a
 def overridden_swagger() -> HTMLResponse:
     return get_swagger_ui_html(
         openapi_url=app.openapi_url,  # type: ignore [arg-type] # this is always a string
-        title=app.title,
-        swagger_favicon_url="/static/docs/favicon.ico",
+        title=f"{app.title} - Swagger UI",
+        swagger_favicon_url="static/docs/invoke-favicon-docs.svg",
     )
 
 
@@ -214,8 +214,8 @@ def overridden_swagger() -> HTMLResponse:
 def overridden_redoc() -> HTMLResponse:
     return get_redoc_html(
         openapi_url=app.openapi_url,  # type: ignore [arg-type] # this is always a string
-        title=app.title,
-        redoc_favicon_url="/static/docs/favicon.ico",
+        title=f"{app.title} - Redoc",
+        redoc_favicon_url="static/docs/invoke-favicon-docs.svg",
     )
 
 
@@ -229,7 +229,7 @@ if (web_root_path / "dist").exists():
     def get_index() -> FileResponse:
         return FileResponse(Path(web_root_path, "dist/index.html"), headers={"Cache-Control": "no-store"})
 
-    # # Must mount *after* the other routes else it borks em
+    # Must mount *after* the other routes else it borks em
     app.mount("/assets", StaticFiles(directory=Path(web_root_path, "dist/assets/")), name="assets")
     app.mount("/locales", StaticFiles(directory=Path(web_root_path, "dist/locales/")), name="locales")
 

invokeai/app/invocations/controlnet_image_processors.py

@@ -24,9 +24,10 @@ from controlnet_aux import (
 )
 from controlnet_aux.util import HWC3, ade_palette
 from PIL import Image
-from pydantic import BaseModel, ConfigDict, Field, field_validator
+from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
 
 from invokeai.app.invocations.primitives import ImageField, ImageOutput
+from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.app.services.image_records.image_records_common import ImageCategory, ResourceOrigin
 from invokeai.app.shared.fields import FieldDescriptions
 
@@ -75,17 +76,16 @@ class ControlField(BaseModel):
     resize_mode: CONTROLNET_RESIZE_VALUES = Field(default="just_resize", description="The resize mode to use")
 
     @field_validator("control_weight")
+    @classmethod
     def validate_control_weight(cls, v):
-        """Validate that all control weights in the valid range"""
-        if isinstance(v, list):
-            for i in v:
-                if i < -1 or i > 2:
-                    raise ValueError("Control weights must be within -1 to 2 range")
-        else:
-            if v < -1 or v > 2:
-                raise ValueError("Control weights must be within -1 to 2 range")
+        validate_weights(v)
         return v
 
+    @model_validator(mode="after")
+    def validate_begin_end_step_percent(self):
+        validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
+        return self
+
 
 @invocation_output("control_output")
 class ControlOutput(BaseInvocationOutput):
@@ -95,17 +95,17 @@ class ControlOutput(BaseInvocationOutput):
     control: ControlField = OutputField(description=FieldDescriptions.control)
 
 
-@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.0")
+@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.1")
 class ControlNetInvocation(BaseInvocation):
     """Collects ControlNet info to pass to other nodes"""
 
     image: ImageField = InputField(description="The control image")
     control_model: ControlNetModelField = InputField(description=FieldDescriptions.controlnet_model, input=Input.Direct)
     control_weight: Union[float, List[float]] = InputField(
-        default=1.0, description="The weight given to the ControlNet"
+        default=1.0, ge=-1, le=2, description="The weight given to the ControlNet"
     )
     begin_step_percent: float = InputField(
-        default=0, ge=-1, le=2, description="When the ControlNet is first applied (% of total steps)"
+        default=0, ge=0, le=1, description="When the ControlNet is first applied (% of total steps)"
     )
     end_step_percent: float = InputField(
         default=1, ge=0, le=1, description="When the ControlNet is last applied (% of total steps)"
@@ -113,6 +113,17 @@ class ControlNetInvocation(BaseInvocation):
     control_mode: CONTROLNET_MODE_VALUES = InputField(default="balanced", description="The control mode used")
     resize_mode: CONTROLNET_RESIZE_VALUES = InputField(default="just_resize", description="The resize mode used")
 
+    @field_validator("control_weight")
+    @classmethod
+    def validate_control_weight(cls, v):
+        validate_weights(v)
+        return v
+
+    @model_validator(mode="after")
+    def validate_begin_end_step_percent(self) -> "ControlNetInvocation":
+        validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
+        return self
+
     def invoke(self, context: InvocationContext) -> ControlOutput:
         return ControlOutput(
             control=ControlField(

invokeai/app/invocations/ip_adapter.py

@@ -2,7 +2,7 @@ import os
 from builtins import float
 from typing import List, Union
 
-from pydantic import BaseModel, ConfigDict, Field
+from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
 
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
@@ -15,6 +15,7 @@ from invokeai.app.invocations.baseinvocation import (
     invocation_output,
 )
 from invokeai.app.invocations.primitives import ImageField
+from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.backend.model_management.models.base import BaseModelType, ModelType
 from invokeai.backend.model_management.models.ip_adapter import get_ip_adapter_image_encoder_model_id
@@ -39,7 +40,6 @@ class IPAdapterField(BaseModel):
     ip_adapter_model: IPAdapterModelField = Field(description="The IP-Adapter model to use.")
     image_encoder_model: CLIPVisionModelField = Field(description="The name of the CLIP image encoder model.")
     weight: Union[float, List[float]] = Field(default=1, description="The weight given to the ControlNet")
-    # weight: float = Field(default=1.0, ge=0, description="The weight of the IP-Adapter.")
     begin_step_percent: float = Field(
         default=0, ge=0, le=1, description="When the IP-Adapter is first applied (% of total steps)"
     )
@@ -47,6 +47,17 @@ class IPAdapterField(BaseModel):
         default=1, ge=0, le=1, description="When the IP-Adapter is last applied (% of total steps)"
     )
 
+    @field_validator("weight")
+    @classmethod
+    def validate_ip_adapter_weight(cls, v):
+        validate_weights(v)
+        return v
+
+    @model_validator(mode="after")
+    def validate_begin_end_step_percent(self):
+        validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
+        return self
+
 
 @invocation_output("ip_adapter_output")
 class IPAdapterOutput(BaseInvocationOutput):
@@ -54,7 +65,7 @@ class IPAdapterOutput(BaseInvocationOutput):
     ip_adapter: IPAdapterField = OutputField(description=FieldDescriptions.ip_adapter, title="IP-Adapter")
 
 
-@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.1.0")
+@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.1.1")
 class IPAdapterInvocation(BaseInvocation):
     """Collects IP-Adapter info to pass to other nodes."""
 
@@ -64,18 +75,27 @@ class IPAdapterInvocation(BaseInvocation):
         description="The IP-Adapter model.", title="IP-Adapter Model", input=Input.Direct, ui_order=-1
     )
 
-    # weight: float = InputField(default=1.0, description="The weight of the IP-Adapter.", ui_type=UIType.Float)
     weight: Union[float, List[float]] = InputField(
-        default=1, ge=-1, description="The weight given to the IP-Adapter", title="Weight"
+        default=1, description="The weight given to the IP-Adapter", title="Weight"
     )
-
     begin_step_percent: float = InputField(
-        default=0, ge=-1, le=2, description="When the IP-Adapter is first applied (% of total steps)"
+        default=0, ge=0, le=1, description="When the IP-Adapter is first applied (% of total steps)"
     )
     end_step_percent: float = InputField(
         default=1, ge=0, le=1, description="When the IP-Adapter is last applied (% of total steps)"
     )
 
+    @field_validator("weight")
+    @classmethod
+    def validate_ip_adapter_weight(cls, v):
+        validate_weights(v)
+        return v
+
+    @model_validator(mode="after")
+    def validate_begin_end_step_percent(self):
+        validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
+        return self
+
     def invoke(self, context: InvocationContext) -> IPAdapterOutput:
         # Lookup the CLIP Vision encoder that is intended to be used with the IP-Adapter model.
         ip_adapter_info = context.services.model_manager.model_info(

invokeai/app/invocations/latent.py

@@ -220,7 +220,7 @@ def get_scheduler(
     title="Denoise Latents",
     tags=["latents", "denoise", "txt2img", "t2i", "t2l", "img2img", "i2i", "l2l"],
     category="latents",
-    version="1.5.0",
+    version="1.5.1",
 )
 class DenoiseLatentsInvocation(BaseInvocation):
     """Denoises noisy latents to decodable images"""
@@ -279,7 +279,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
         ui_order=7,
     )
     cfg_rescale_multiplier: float = InputField(
-        default=0, ge=0, lt=1, description=FieldDescriptions.cfg_rescale_multiplier
+        title="CFG Rescale Multiplier", default=0, ge=0, lt=1, description=FieldDescriptions.cfg_rescale_multiplier
     )
     latents: Optional[LatentsField] = InputField(
         default=None,

invokeai/app/invocations/t2i_adapter.py

@@ -1,6 +1,6 @@
 from typing import Union
 
-from pydantic import BaseModel, ConfigDict, Field
+from pydantic import BaseModel, ConfigDict, Field, field_validator, model_validator
 
 from invokeai.app.invocations.baseinvocation import (
     BaseInvocation,
@@ -14,6 +14,7 @@ from invokeai.app.invocations.baseinvocation import (
 )
 from invokeai.app.invocations.controlnet_image_processors import CONTROLNET_RESIZE_VALUES
 from invokeai.app.invocations.primitives import ImageField
+from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.app.shared.fields import FieldDescriptions
 from invokeai.backend.model_management.models.base import BaseModelType
 
@@ -37,6 +38,17 @@ class T2IAdapterField(BaseModel):
     )
     resize_mode: CONTROLNET_RESIZE_VALUES = Field(default="just_resize", description="The resize mode to use")
 
+    @field_validator("weight")
+    @classmethod
+    def validate_ip_adapter_weight(cls, v):
+        validate_weights(v)
+        return v
+
+    @model_validator(mode="after")
+    def validate_begin_end_step_percent(self):
+        validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
+        return self
+
 
 @invocation_output("t2i_adapter_output")
 class T2IAdapterOutput(BaseInvocationOutput):
@@ -44,7 +56,7 @@ class T2IAdapterOutput(BaseInvocationOutput):
 
 
 @invocation(
-    "t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.0"
+    "t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.1"
 )
 class T2IAdapterInvocation(BaseInvocation):
     """Collects T2I-Adapter info to pass to other nodes."""
@@ -61,7 +73,7 @@ class T2IAdapterInvocation(BaseInvocation):
         default=1, ge=0, description="The weight given to the T2I-Adapter", title="Weight"
     )
     begin_step_percent: float = InputField(
-        default=0, ge=-1, le=2, description="When the T2I-Adapter is first applied (% of total steps)"
+        default=0, ge=0, le=1, description="When the T2I-Adapter is first applied (% of total steps)"
     )
     end_step_percent: float = InputField(
         default=1, ge=0, le=1, description="When the T2I-Adapter is last applied (% of total steps)"
@@ -71,6 +83,17 @@ class T2IAdapterInvocation(BaseInvocation):
         description="The resize mode applied to the T2I-Adapter input image so that it matches the target output size.",
     )
 
+    @field_validator("weight")
+    @classmethod
+    def validate_ip_adapter_weight(cls, v):
+        validate_weights(v)
+        return v
+
+    @model_validator(mode="after")
+    def validate_begin_end_step_percent(self):
+        validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
+        return self
+
     def invoke(self, context: InvocationContext) -> T2IAdapterOutput:
         return T2IAdapterOutput(
             t2i_adapter=T2IAdapterField(

invokeai/app/invocations/util.py

@@ -0,0 +1,14 @@
+from typing import Union
+
+
+def validate_weights(weights: Union[float, list[float]]) -> None:
+    """Validate that all control weights in the valid range"""
+    to_validate = weights if isinstance(weights, list) else [weights]
+    if any(i < -1 or i > 2 for i in to_validate):
+        raise ValueError("Control weights must be within -1 to 2 range")
+
+
+def validate_begin_end_step(begin_step_percent: float, end_step_percent: float) -> None:
+    """Validate that begin_step_percent is less than end_step_percent"""
+    if begin_step_percent >= end_step_percent:
+        raise ValueError("Begin step percent must be less than or equal to end step percent")

invokeai/app/services/config/__init__.py

@@ -1,5 +1,7 @@
 """Init file for InvokeAI configure package."""
 
+from invokeai.app.services.config.config_common import PagingArgumentParser
+
 from .config_default import InvokeAIAppConfig, get_invokeai_config
 
-__all__ = ["InvokeAIAppConfig", "get_invokeai_config"]
+__all__ = ["InvokeAIAppConfig", "get_invokeai_config", "PagingArgumentParser"]

invokeai/app/services/config/config_default.py

@@ -263,7 +263,7 @@ class InvokeAIAppConfig(InvokeAISettings):
 
     # DEVICE
     device              : Literal["auto", "cpu", "cuda", "cuda:1", "mps"] = Field(default="auto", description="Generation device", json_schema_extra=Categories.Device)
-    precision           : Literal["auto", "float16", "float32", "autocast"] = Field(default="auto", description="Floating point precision", json_schema_extra=Categories.Device)
+    precision           : Literal["auto", "float16", "bfloat16", "float32", "autocast"] = Field(default="auto", description="Floating point precision", json_schema_extra=Categories.Device)
 
     # GENERATION
     sequential_guidance : bool = Field(default=False, description="Whether to calculate guidance in serial instead of in parallel, lowering memory requirements", json_schema_extra=Categories.Generation)

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

@@ -167,6 +167,9 @@ class Migration2Callback:
             except ImageFileNotFoundException:
                 self._logger.warning(f"Image {image_name} not found, skipping")
                 continue
+            except Exception as e:
+                self._logger.warning(f"Error while checking image {image_name}, skipping: {e}")
+                continue
             if "invokeai_workflow" in pil_image.info:
                 try:
                     UnsafeWorkflowWithVersionValidator.validate_json(pil_image.info.get("invokeai_workflow", ""))

invokeai/app/services/workflow_records/default_workflows/ESRGAN Upscaling with Canny ControlNet.json

@@ -1,5 +1,4 @@
 {
-  "id": "6bfa0b3a-7090-4cd9-ad2d-a4b8662b6e71",
   "name": "ESRGAN Upscaling with Canny ControlNet",
   "author": "InvokeAI",
   "description": "Sample workflow for using Upscaling with ControlNet with SD1.5",
@@ -77,12 +76,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 256,
       "position": {
         "x": 1250,
         "y": 1500
-      }
+      },
+      "width": 320,
+      "height": 219
     },
     {
       "id": "d8ace142-c05f-4f1d-8982-88dc7473958d",
@@ -148,12 +147,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 227,
       "position": {
         "x": 700,
         "y": 1375
-      }
+      },
+      "width": 320,
+      "height": 193
     },
     {
       "id": "771bdf6a-0813-4099-a5d8-921a138754d4",
@@ -214,12 +213,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 225,
       "position": {
         "x": 375,
         "y": 1900
-      }
+      },
+      "width": 320,
+      "height": 189
     },
     {
       "id": "f7564dd2-9539-47f2-ac13-190804461f4e",
@@ -315,12 +314,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 340,
       "position": {
         "x": 775,
         "y": 1900
-      }
+      },
+      "width": 320,
+      "height": 295
     },
     {
       "id": "1d887701-df21-4966-ae6e-a7d82307d7bd",
@@ -416,12 +415,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 340,
       "position": {
         "x": 1200,
         "y": 1900
-      }
+      },
+      "width": 320,
+      "height": 293
     },
     {
       "id": "ca1d020c-89a8-4958-880a-016d28775cfa",
@@ -434,7 +433,7 @@
         "notes": "",
         "isIntermediate": true,
         "useCache": true,
-        "version": "1.1.0",
+        "version": "1.1.1",
         "nodePack": "invokeai",
         "inputs": {
           "image": {
@@ -459,7 +458,7 @@
               "name": "ControlNetModelField"
             },
             "value": {
-              "model_name": "sd-controlnet-canny",
+              "model_name": "canny",
               "base_model": "sd-1"
             }
           },
@@ -537,12 +536,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 511,
       "position": {
         "x": 1650,
         "y": 1900
-      }
+      },
+      "width": 320,
+      "height": 451
     },
     {
       "id": "f50624ce-82bf-41d0-bdf7-8aab11a80d48",
@@ -640,12 +639,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 32,
       "position": {
         "x": 1650,
         "y": 1775
-      }
+      },
+      "width": 320,
+      "height": 24
     },
     {
       "id": "c3737554-8d87-48ff-a6f8-e71d2867f434",
@@ -658,7 +657,7 @@
         "notes": "",
         "isIntermediate": true,
         "useCache": true,
-        "version": "1.5.0",
+        "version": "1.5.1",
         "nodePack": "invokeai",
         "inputs": {
           "positive_conditioning": {
@@ -866,12 +865,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 705,
       "position": {
         "x": 2128.740065979906,
         "y": 1232.6219060454753
-      }
+      },
+      "width": 320,
+      "height": 612
     },
     {
       "id": "3ed9b2ef-f4ec-40a7-94db-92e63b583ec0",
@@ -978,12 +977,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 267,
       "position": {
         "x": 2559.4751127537957,
         "y": 1246.6000376741406
-      }
+      },
+      "width": 320,
+      "height": 224
     },
     {
       "id": "5ca498a4-c8c8-4580-a396-0c984317205d",
@@ -1079,12 +1078,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 32,
       "position": {
         "x": 1650,
         "y": 1675
-      }
+      },
+      "width": 320,
+      "height": 24
     },
     {
       "id": "63b6ab7e-5b05-4d1b-a3b1-42d8e53ce16b",
@@ -1137,12 +1136,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 256,
       "position": {
         "x": 1250,
         "y": 1200
-      }
+      },
+      "width": 320,
+      "height": 219
     },
     {
       "id": "eb8f6f8a-c7b1-4914-806e-045ee2717a35",
@@ -1195,168 +1194,168 @@
           }
         }
       },
-      "width": 320,
-      "height": 32,
       "position": {
         "x": 1650,
         "y": 1600
-      }
+      },
+      "width": 320,
+      "height": 24
     }
   ],
   "edges": [
     {
       "id": "5ca498a4-c8c8-4580-a396-0c984317205d-f50624ce-82bf-41d0-bdf7-8aab11a80d48-collapsed",
+      "type": "collapsed",
       "source": "5ca498a4-c8c8-4580-a396-0c984317205d",
-      "target": "f50624ce-82bf-41d0-bdf7-8aab11a80d48",
-      "type": "collapsed"
+      "target": "f50624ce-82bf-41d0-bdf7-8aab11a80d48"
     },
     {
       "id": "eb8f6f8a-c7b1-4914-806e-045ee2717a35-f50624ce-82bf-41d0-bdf7-8aab11a80d48-collapsed",
+      "type": "collapsed",
       "source": "eb8f6f8a-c7b1-4914-806e-045ee2717a35",
-      "target": "f50624ce-82bf-41d0-bdf7-8aab11a80d48",
-      "type": "collapsed"
+      "target": "f50624ce-82bf-41d0-bdf7-8aab11a80d48"
     },
     {
       "id": "reactflow__edge-771bdf6a-0813-4099-a5d8-921a138754d4image-f7564dd2-9539-47f2-ac13-190804461f4eimage",
+      "type": "default",
       "source": "771bdf6a-0813-4099-a5d8-921a138754d4",
       "target": "f7564dd2-9539-47f2-ac13-190804461f4e",
-      "type": "default",
       "sourceHandle": "image",
       "targetHandle": "image"
     },
     {
       "id": "reactflow__edge-f7564dd2-9539-47f2-ac13-190804461f4eimage-1d887701-df21-4966-ae6e-a7d82307d7bdimage",
+      "type": "default",
       "source": "f7564dd2-9539-47f2-ac13-190804461f4e",
       "target": "1d887701-df21-4966-ae6e-a7d82307d7bd",
-      "type": "default",
       "sourceHandle": "image",
       "targetHandle": "image"
     },
     {
       "id": "reactflow__edge-5ca498a4-c8c8-4580-a396-0c984317205dwidth-f50624ce-82bf-41d0-bdf7-8aab11a80d48width",
+      "type": "default",
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       "target": "f50624ce-82bf-41d0-bdf7-8aab11a80d48",
-      "type": "default",
       "sourceHandle": "width",
       "targetHandle": "width"
     },
     {
       "id": "reactflow__edge-5ca498a4-c8c8-4580-a396-0c984317205dheight-f50624ce-82bf-41d0-bdf7-8aab11a80d48height",
+      "type": "default",
       "source": "5ca498a4-c8c8-4580-a396-0c984317205d",
       "target": "f50624ce-82bf-41d0-bdf7-8aab11a80d48",
-      "type": "default",
       "sourceHandle": "height",
       "targetHandle": "height"
     },
     {
       "id": "reactflow__edge-f50624ce-82bf-41d0-bdf7-8aab11a80d48noise-c3737554-8d87-48ff-a6f8-e71d2867f434noise",
+      "type": "default",
       "source": "f50624ce-82bf-41d0-bdf7-8aab11a80d48",
       "target": "c3737554-8d87-48ff-a6f8-e71d2867f434",
-      "type": "default",
       "sourceHandle": "noise",
       "targetHandle": "noise"
     },
     {
       "id": "reactflow__edge-5ca498a4-c8c8-4580-a396-0c984317205dlatents-c3737554-8d87-48ff-a6f8-e71d2867f434latents",
+      "type": "default",
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       "target": "c3737554-8d87-48ff-a6f8-e71d2867f434",
-      "type": "default",
       "sourceHandle": "latents",
       "targetHandle": "latents"
     },
     {
       "id": "reactflow__edge-e8bf67fe-67de-4227-87eb-79e86afdfc74conditioning-c3737554-8d87-48ff-a6f8-e71d2867f434negative_conditioning",
+      "type": "default",
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       "target": "c3737554-8d87-48ff-a6f8-e71d2867f434",
-      "type": "default",
       "sourceHandle": "conditioning",
       "targetHandle": "negative_conditioning"
     },
     {
       "id": "reactflow__edge-63b6ab7e-5b05-4d1b-a3b1-42d8e53ce16bconditioning-c3737554-8d87-48ff-a6f8-e71d2867f434positive_conditioning",
+      "type": "default",
       "source": "63b6ab7e-5b05-4d1b-a3b1-42d8e53ce16b",
       "target": "c3737554-8d87-48ff-a6f8-e71d2867f434",
-      "type": "default",
       "sourceHandle": "conditioning",
       "targetHandle": "positive_conditioning"
     },
     {
       "id": "reactflow__edge-d8ace142-c05f-4f1d-8982-88dc7473958dclip-63b6ab7e-5b05-4d1b-a3b1-42d8e53ce16bclip",
+      "type": "default",
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       "target": "63b6ab7e-5b05-4d1b-a3b1-42d8e53ce16b",
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     },
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       "id": "reactflow__edge-d8ace142-c05f-4f1d-8982-88dc7473958dclip-e8bf67fe-67de-4227-87eb-79e86afdfc74clip",
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       "source": "d8ace142-c05f-4f1d-8982-88dc7473958d",
       "target": "e8bf67fe-67de-4227-87eb-79e86afdfc74",
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     },
     {
       "id": "reactflow__edge-1d887701-df21-4966-ae6e-a7d82307d7bdimage-ca1d020c-89a8-4958-880a-016d28775cfaimage",
+      "type": "default",
       "source": "1d887701-df21-4966-ae6e-a7d82307d7bd",
       "target": "ca1d020c-89a8-4958-880a-016d28775cfa",
-      "type": "default",
       "sourceHandle": "image",
       "targetHandle": "image"
     },
     {
       "id": "reactflow__edge-ca1d020c-89a8-4958-880a-016d28775cfacontrol-c3737554-8d87-48ff-a6f8-e71d2867f434control",
+      "type": "default",
       "source": "ca1d020c-89a8-4958-880a-016d28775cfa",
       "target": "c3737554-8d87-48ff-a6f8-e71d2867f434",
-      "type": "default",
       "sourceHandle": "control",
       "targetHandle": "control"
     },
     {
       "id": "reactflow__edge-c3737554-8d87-48ff-a6f8-e71d2867f434latents-3ed9b2ef-f4ec-40a7-94db-92e63b583ec0latents",
+      "type": "default",
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       "target": "3ed9b2ef-f4ec-40a7-94db-92e63b583ec0",
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       "sourceHandle": "latents",
       "targetHandle": "latents"
     },
     {
       "id": "reactflow__edge-d8ace142-c05f-4f1d-8982-88dc7473958dvae-3ed9b2ef-f4ec-40a7-94db-92e63b583ec0vae",
+      "type": "default",
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       "target": "3ed9b2ef-f4ec-40a7-94db-92e63b583ec0",
-      "type": "default",
       "sourceHandle": "vae",
       "targetHandle": "vae"
     },
     {
       "id": "reactflow__edge-f7564dd2-9539-47f2-ac13-190804461f4eimage-5ca498a4-c8c8-4580-a396-0c984317205dimage",
+      "type": "default",
       "source": "f7564dd2-9539-47f2-ac13-190804461f4e",
       "target": "5ca498a4-c8c8-4580-a396-0c984317205d",
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       "targetHandle": "image"
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+      "type": "default",
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       "target": "c3737554-8d87-48ff-a6f8-e71d2867f434",
-      "type": "default",
       "sourceHandle": "unet",
       "targetHandle": "unet"
     },
     {
       "id": "reactflow__edge-d8ace142-c05f-4f1d-8982-88dc7473958dvae-5ca498a4-c8c8-4580-a396-0c984317205dvae",
+      "type": "default",
       "source": "d8ace142-c05f-4f1d-8982-88dc7473958d",
       "target": "5ca498a4-c8c8-4580-a396-0c984317205d",
-      "type": "default",
       "sourceHandle": "vae",
       "targetHandle": "vae"
     },
     {
       "id": "reactflow__edge-eb8f6f8a-c7b1-4914-806e-045ee2717a35value-f50624ce-82bf-41d0-bdf7-8aab11a80d48seed",
+      "type": "default",
       "source": "eb8f6f8a-c7b1-4914-806e-045ee2717a35",
       "target": "f50624ce-82bf-41d0-bdf7-8aab11a80d48",
-      "type": "default",
       "sourceHandle": "value",
       "targetHandle": "seed"
     }

invokeai/app/services/workflow_records/default_workflows/Multi ControlNet (Canny & Depth).json

@@ -1,5 +1,4 @@
 {
-  "id": "1e385b84-86f8-452e-9697-9e5abed20518",
   "name": "Multi ControlNet (Canny & Depth)",
   "author": "InvokeAI",
   "description": "A sample workflow using canny & depth ControlNets to guide the generation process. ",
@@ -93,12 +92,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 225,
       "position": {
         "x": 3625,
         "y": -75
-      }
+      },
+      "width": 320,
+      "height": 189
     },
     {
       "id": "a33199c2-8340-401e-b8a2-42ffa875fc1c",
@@ -111,7 +110,7 @@
         "notes": "",
         "isIntermediate": true,
         "useCache": true,
-        "version": "1.1.0",
+        "version": "1.1.1",
         "nodePack": "invokeai",
         "inputs": {
           "image": {
@@ -136,7 +135,7 @@
               "name": "ControlNetModelField"
             },
             "value": {
-              "model_name": "sd-controlnet-depth",
+              "model_name": "depth",
               "base_model": "sd-1"
             }
           },
@@ -214,12 +213,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 511,
       "position": {
         "x": 4477.604342844504,
         "y": -49.39005411272677
-      }
+      },
+      "width": 320,
+      "height": 451
     },
     {
       "id": "273e3f96-49ea-4dc5-9d5b-9660390f14e1",
@@ -272,12 +271,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 256,
       "position": {
         "x": 4075,
         "y": -825
-      }
+      },
+      "width": 320,
+      "height": 219
     },
     {
       "id": "54486974-835b-4d81-8f82-05f9f32ce9e9",
@@ -343,12 +342,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 227,
       "position": {
         "x": 3600,
         "y": -1000
-      }
+      },
+      "width": 320,
+      "height": 193
     },
     {
       "id": "7ce68934-3419-42d4-ac70-82cfc9397306",
@@ -401,12 +400,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 256,
       "position": {
         "x": 4075,
         "y": -1125
-      }
+      },
+      "width": 320,
+      "height": 219
     },
     {
       "id": "d204d184-f209-4fae-a0a1-d152800844e1",
@@ -419,7 +418,7 @@
         "notes": "",
         "isIntermediate": true,
         "useCache": true,
-        "version": "1.1.0",
+        "version": "1.1.1",
         "nodePack": "invokeai",
         "inputs": {
           "image": {
@@ -444,7 +443,7 @@
               "name": "ControlNetModelField"
             },
             "value": {
-              "model_name": "sd-controlnet-canny",
+              "model_name": "canny",
               "base_model": "sd-1"
             }
           },
@@ -522,12 +521,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 511,
       "position": {
         "x": 4479.68542130465,
         "y": -618.4221638099414
-      }
+      },
+      "width": 320,
+      "height": 451
     },
     {
       "id": "c4b23e64-7986-40c4-9cad-46327b12e204",
@@ -588,12 +587,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 225,
       "position": {
         "x": 3625,
         "y": -425
-      }
+      },
+      "width": 320,
+      "height": 189
     },
     {
       "id": "ca4d5059-8bfb-447f-b415-da0faba5a143",
@@ -633,12 +632,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 104,
       "position": {
         "x": 4875,
         "y": -575
-      }
+      },
+      "width": 320,
+      "height": 87
     },
     {
       "id": "018b1214-c2af-43a7-9910-fb687c6726d7",
@@ -734,12 +733,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 340,
       "position": {
         "x": 4100,
         "y": -75
-      }
+      },
+      "width": 320,
+      "height": 293
     },
     {
       "id": "c826ba5e-9676-4475-b260-07b85e88753c",
@@ -835,12 +834,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 340,
       "position": {
         "x": 4095.757337055795,
         "y": -455.63440891935863
-      }
+      },
+      "width": 320,
+      "height": 293
     },
     {
       "id": "9db25398-c869-4a63-8815-c6559341ef12",
@@ -947,12 +946,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 267,
       "position": {
         "x": 5675,
         "y": -825
-      }
+      },
+      "width": 320,
+      "height": 224
     },
     {
       "id": "ac481b7f-08bf-4a9d-9e0c-3a82ea5243ce",
@@ -965,7 +964,7 @@
         "notes": "",
         "isIntermediate": true,
         "useCache": true,
-        "version": "1.5.0",
+        "version": "1.5.1",
         "nodePack": "invokeai",
         "inputs": {
           "positive_conditioning": {
@@ -1173,12 +1172,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 705,
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invokeai/app/services/workflow_records/default_workflows/Prompt from File.json

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invokeai/app/services/workflow_records/default_workflows/SDXL Text to Image.json

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invokeai/app/services/workflow_records/default_workflows/Text to Image - SD1.5.json

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invokeai/app/services/workflow_records/default_workflows/Text to Image with LoRA.json

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-      }
+      },
+      "width": 320,
+      "height": 24
     },
     {
       "id": "6fd74a17-6065-47a5-b48b-f4e2b8fa7953",
@@ -685,12 +684,12 @@
           }
         }
       },
-      "width": 320,
-      "height": 32,
       "position": {
         "x": 3425,
         "y": 0
-      }
+      },
+      "width": 320,
+      "height": 24
     },
     {
       "id": "a9683c0a-6b1f-4a5e-8187-c57e764b3400",
@@ -796,106 +795,106 @@
           }
         }
       },
-      "width": 320,
-      "height": 267,
       "position": {
         "x": 4450,
         "y": -550
-      }
+      },
+      "width": 320,
+      "height": 224
     }
   ],
   "edges": [
     {
       "id": "6fd74a17-6065-47a5-b48b-f4e2b8fa7953-ea18915f-2c5b-4569-b725-8e9e9122e8d3-collapsed",
+      "type": "collapsed",
       "source": "6fd74a17-6065-47a5-b48b-f4e2b8fa7953",
-      "target": "ea18915f-2c5b-4569-b725-8e9e9122e8d3",
-      "type": "collapsed"
+      "target": "ea18915f-2c5b-4569-b725-8e9e9122e8d3"
     },
     {
       "id": "reactflow__edge-24e9d7ed-4836-4ec4-8f9e-e747721f9818clip-c41e705b-f2e3-4d1a-83c4-e34bb9344966clip",
+      "type": "default",
       "source": "24e9d7ed-4836-4ec4-8f9e-e747721f9818",
       "target": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
-      "type": "default",
       "sourceHandle": "clip",
       "targetHandle": "clip"
     },
     {
       "id": "reactflow__edge-c41e705b-f2e3-4d1a-83c4-e34bb9344966clip-c3fa6872-2599-4a82-a596-b3446a66cf8bclip",
+      "type": "default",
       "source": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
       "target": "c3fa6872-2599-4a82-a596-b3446a66cf8b",
-      "type": "default",
       "sourceHandle": "clip",
       "targetHandle": "clip"
     },
     {
       "id": "reactflow__edge-24e9d7ed-4836-4ec4-8f9e-e747721f9818unet-c41e705b-f2e3-4d1a-83c4-e34bb9344966unet",
+      "type": "default",
       "source": "24e9d7ed-4836-4ec4-8f9e-e747721f9818",
       "target": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
-      "type": "default",
       "sourceHandle": "unet",
       "targetHandle": "unet"
     },
     {
       "id": "reactflow__edge-c41e705b-f2e3-4d1a-83c4-e34bb9344966unet-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63unet",
+      "type": "default",
       "source": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
       "target": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
-      "type": "default",
       "sourceHandle": "unet",
       "targetHandle": "unet"
     },
     {
       "id": "reactflow__edge-85b77bb2-c67a-416a-b3e8-291abe746c44conditioning-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63negative_conditioning",
+      "type": "default",
       "source": "85b77bb2-c67a-416a-b3e8-291abe746c44",
       "target": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
-      "type": "default",
       "sourceHandle": "conditioning",
       "targetHandle": "negative_conditioning"
     },
     {
       "id": "reactflow__edge-c3fa6872-2599-4a82-a596-b3446a66cf8bconditioning-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63positive_conditioning",
+      "type": "default",
       "source": "c3fa6872-2599-4a82-a596-b3446a66cf8b",
       "target": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
-      "type": "default",
       "sourceHandle": "conditioning",
       "targetHandle": "positive_conditioning"
     },
     {
       "id": "reactflow__edge-ea18915f-2c5b-4569-b725-8e9e9122e8d3noise-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63noise",
+      "type": "default",
       "source": "ea18915f-2c5b-4569-b725-8e9e9122e8d3",
       "target": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
-      "type": "default",
       "sourceHandle": "noise",
       "targetHandle": "noise"
     },
     {
       "id": "reactflow__edge-6fd74a17-6065-47a5-b48b-f4e2b8fa7953value-ea18915f-2c5b-4569-b725-8e9e9122e8d3seed",
+      "type": "default",
       "source": "6fd74a17-6065-47a5-b48b-f4e2b8fa7953",
       "target": "ea18915f-2c5b-4569-b725-8e9e9122e8d3",
-      "type": "default",
       "sourceHandle": "value",
       "targetHandle": "seed"
     },
     {
       "id": "reactflow__edge-ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63latents-a9683c0a-6b1f-4a5e-8187-c57e764b3400latents",
+      "type": "default",
       "source": "ad487d0c-dcbb-49c5-bb8e-b28d4cbc5a63",
       "target": "a9683c0a-6b1f-4a5e-8187-c57e764b3400",
-      "type": "default",
       "sourceHandle": "latents",
       "targetHandle": "latents"
     },
     {
       "id": "reactflow__edge-24e9d7ed-4836-4ec4-8f9e-e747721f9818vae-a9683c0a-6b1f-4a5e-8187-c57e764b3400vae",
+      "type": "default",
       "source": "24e9d7ed-4836-4ec4-8f9e-e747721f9818",
       "target": "a9683c0a-6b1f-4a5e-8187-c57e764b3400",
-      "type": "default",
       "sourceHandle": "vae",
       "targetHandle": "vae"
     },
     {
       "id": "reactflow__edge-c41e705b-f2e3-4d1a-83c4-e34bb9344966clip-85b77bb2-c67a-416a-b3e8-291abe746c44clip",
+      "type": "default",
       "source": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
       "target": "85b77bb2-c67a-416a-b3e8-291abe746c44",
-      "type": "default",
       "sourceHandle": "clip",
       "targetHandle": "clip"
     }

invokeai/app/services/workflow_records/workflow_records_sqlite.py

@@ -169,7 +169,7 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
 
             self._cursor.execute(count_query, count_params)
             total = self._cursor.fetchone()[0]
-            pages = int(total / per_page) + 1
+            pages = total // per_page + (total % per_page > 0)
 
             return PaginatedResults(
                 items=workflows,

invokeai/backend/model_management/detect_baked_in_vae.py

@@ -0,0 +1,31 @@
+# Copyright (c) 2024 Lincoln Stein and the InvokeAI Development Team
+"""
+This module exports the function has_baked_in_sdxl_vae().
+It returns True if an SDXL checkpoint model has the original SDXL 1.0 VAE,
+which doesn't work properly in fp16 mode.
+"""
+
+import hashlib
+from pathlib import Path
+
+from safetensors.torch import load_file
+
+SDXL_1_0_VAE_HASH = "bc40b16c3a0fa4625abdfc01c04ffc21bf3cefa6af6c7768ec61eb1f1ac0da51"
+
+
+def has_baked_in_sdxl_vae(checkpoint_path: Path) -> bool:
+    """Return true if the checkpoint contains a custom (non SDXL-1.0) VAE."""
+    hash = _vae_hash(checkpoint_path)
+    return hash != SDXL_1_0_VAE_HASH
+
+
+def _vae_hash(checkpoint_path: Path) -> str:
+    checkpoint = load_file(checkpoint_path, device="cpu")
+    vae_keys = [x for x in checkpoint.keys() if x.startswith("first_stage_model.")]
+    hash = hashlib.new("sha256")
+    for key in vae_keys:
+        value = checkpoint[key]
+        hash.update(bytes(key, "UTF-8"))
+        hash.update(bytes(str(value), "UTF-8"))
+
+    return hash.hexdigest()

invokeai/backend/model_management/lora.py

@@ -13,6 +13,7 @@ from safetensors.torch import load_file
 from transformers import CLIPTextModel, CLIPTokenizer
 
 from invokeai.app.shared.models import FreeUConfig
+from invokeai.backend.model_management.model_load_optimizations import skip_torch_weight_init
 
 from .models.lora import LoRAModel
 
@@ -211,11 +212,17 @@ class ModelPatcher:
                 for i in range(ti_embedding.shape[0]):
                     new_tokens_added += ti_tokenizer.add_tokens(_get_trigger(ti_name, i))
 
-            # modify text_encoder
-            text_encoder.resize_token_embeddings(init_tokens_count + new_tokens_added, pad_to_multiple_of)
+            # Modify text_encoder.
+            # resize_token_embeddings(...) constructs a new torch.nn.Embedding internally. Initializing the weights of
+            # this embedding is slow and unnecessary, so we wrap this step in skip_torch_weight_init() to save some
+            # time.
+            with skip_torch_weight_init():
+                text_encoder.resize_token_embeddings(init_tokens_count + new_tokens_added, pad_to_multiple_of)
             model_embeddings = text_encoder.get_input_embeddings()
 
-            for ti_name, _ in ti_list:
+            for ti_name, ti in ti_list:
+                ti_embedding = _get_ti_embedding(text_encoder.get_input_embeddings(), ti)
+
                 ti_tokens = []
                 for i in range(ti_embedding.shape[0]):
                     embedding = ti_embedding[i]

invokeai/backend/model_management/model_probe.py

@@ -370,6 +370,8 @@ class LoRACheckpointProbe(CheckpointProbeBase):
             return BaseModelType.StableDiffusion1
         elif token_vector_length == 1024:
             return BaseModelType.StableDiffusion2
+        elif token_vector_length == 1280:
+            return BaseModelType.StableDiffusionXL  # recognizes format at https://civitai.com/models/224641
         elif token_vector_length == 2048:
             return BaseModelType.StableDiffusionXL
         else:

invokeai/backend/model_management/models/sdxl.py

@@ -1,11 +1,16 @@
 import json
 import os
 from enum import Enum
+from pathlib import Path
 from typing import Literal, Optional
 
 from omegaconf import OmegaConf
 from pydantic import Field
 
+from invokeai.app.services.config import InvokeAIAppConfig
+from invokeai.backend.model_management.detect_baked_in_vae import has_baked_in_sdxl_vae
+from invokeai.backend.util.logging import InvokeAILogger
+
 from .base import (
     BaseModelType,
     DiffusersModel,
@@ -116,14 +121,28 @@ class StableDiffusionXLModel(DiffusersModel):
         # The convert script adapted from the diffusers package uses
         # strings for the base model type. To avoid making too many
         # source code changes, we simply translate here
+        if Path(output_path).exists():
+            return output_path
+
         if isinstance(config, cls.CheckpointConfig):
             from invokeai.backend.model_management.models.stable_diffusion import _convert_ckpt_and_cache
 
+            # Hack in VAE-fp16 fix - If model sdxl-vae-fp16-fix is installed,
+            # then we bake it into the converted model unless there is already
+            # a nonstandard VAE installed.
+            kwargs = {}
+            app_config = InvokeAIAppConfig.get_config()
+            vae_path = app_config.models_path / "sdxl/vae/sdxl-vae-fp16-fix"
+            if vae_path.exists() and not has_baked_in_sdxl_vae(Path(model_path)):
+                InvokeAILogger.get_logger().warning("No baked-in VAE detected. Inserting sdxl-vae-fp16-fix.")
+                kwargs["vae_path"] = vae_path
+
             return _convert_ckpt_and_cache(
                 version=base_model,
                 model_config=config,
                 output_path=output_path,
                 use_safetensors=False,  # corrupts sdxl models for some reason
+                **kwargs,
             )
         else:
             return model_path

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -276,7 +276,11 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             self.disable_attention_slicing()
             return
         elif config.attention_type == "torch-sdp":
-            raise Exception("torch-sdp attention slicing not yet implemented")
+            if hasattr(torch.nn.functional, "scaled_dot_product_attention"):
+                # diffusers enables sdp automatically
+                return
+            else:
+                raise Exception("torch-sdp attention slicing not available")
 
         # the remainder if this code is called when attention_type=='auto'
         if self.unet.device.type == "cuda":
@@ -284,7 +288,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
                 self.enable_xformers_memory_efficient_attention()
                 return
             elif hasattr(torch.nn.functional, "scaled_dot_product_attention"):
-                # diffusers enable sdp automatically
+                # diffusers enables sdp automatically
                 return
 
         if self.unet.device.type == "cpu" or self.unet.device.type == "mps":

invokeai/backend/util/devices.py

@@ -34,18 +34,23 @@ def choose_precision(device: torch.device) -> str:
     if device.type == "cuda":
         device_name = torch.cuda.get_device_name(device)
         if not ("GeForce GTX 1660" in device_name or "GeForce GTX 1650" in device_name):
-            return "float16"
+            if config.precision == "bfloat16":
+                return "bfloat16"
+            else:
+                return "float16"
     elif device.type == "mps":
         return "float16"
     return "float32"
 
 
 def torch_dtype(device: torch.device) -> torch.dtype:
-    if config.full_precision:
-        return torch.float32
-    if choose_precision(device) == "float16":
+    precision = choose_precision(device)
+    if precision == "float16":
         return torch.float16
+    if precision == "bfloat16":
+        return torch.bfloat16
     else:
+        # "auto", "autocast", "float32"
         return torch.float32
 
 

invokeai/frontend/install/invokeai_update.py

@@ -68,12 +68,9 @@ def welcome(latest_release: str, latest_prerelease: str):
         yield ""
         yield "This script will update InvokeAI to the latest release, or to the development version of your choice."
         yield ""
-        yield "When updating to an arbitrary tag or branch, be aware that the front end may be mismatched to the backend,"
-        yield "making the web frontend unusable. Please downgrade to the latest release if this happens."
-        yield ""
         yield "[bold yellow]Options:"
         yield f"""[1] Update to the latest [bold]official release[/bold] ([italic]{latest_release}[/italic])
-[2] Update to the latest [bold]pre-release[/bold] (may be buggy; caveat emptor!) ([italic]{latest_prerelease}[/italic])
+[2] Update to the latest [bold]pre-release[/bold] (may be buggy, database backups are recommended before installation; caveat emptor!) ([italic]{latest_prerelease}[/italic])
 [3] Manually enter the [bold]version[/bold] you wish to update to"""
 
     console.rule()

invokeai/frontend/web/.eslintignore

@@ -7,4 +7,4 @@ stats.html
 index.html
 .yarn/
 *.scss
-src/services/api/schema.d.ts
+src/services/api/schema.ts

invokeai/frontend/web/.eslintrc.js

@@ -28,12 +28,16 @@ module.exports = {
     'i18next',
     'path',
     'unused-imports',
+    'simple-import-sort',
+    'eslint-plugin-import',
+    // These rules are too strict for normal usage, but are useful for optimizing rerenders
+    // '@arthurgeron/react-usememo',
   ],
   root: true,
   rules: {
     'path/no-relative-imports': ['error', { maxDepth: 0 }],
     curly: 'error',
-    'i18next/no-literal-string': 2,
+    'i18next/no-literal-string': 'warn',
     'react/jsx-no-bind': ['error', { allowBind: true }],
     'react/jsx-curly-brace-presence': [
       'error',
@@ -43,6 +47,7 @@ module.exports = {
     'no-var': 'error',
     'brace-style': 'error',
     'prefer-template': 'error',
+    'import/no-duplicates': 'error',
     radix: 'error',
     'space-before-blocks': 'error',
     'import/prefer-default-export': 'off',
@@ -57,6 +62,18 @@ module.exports = {
         argsIgnorePattern: '^_',
       },
     ],
+    // These rules are too strict for normal usage, but are useful for optimizing rerenders
+    // '@arthurgeron/react-usememo/require-usememo': [
+    //   'warn',
+    //   {
+    //     strict: false,
+    //     checkHookReturnObject: false,
+    //     fix: { addImports: true },
+    //     checkHookCalls: false,
+
+    //   },
+    // ],
+    // '@arthurgeron/react-usememo/require-memo': 'warn',
     '@typescript-eslint/ban-ts-comment': 'warn',
     '@typescript-eslint/no-explicit-any': 'warn',
     '@typescript-eslint/no-empty-interface': [
@@ -65,7 +82,26 @@ module.exports = {
         allowSingleExtends: true,
       },
     ],
+    '@typescript-eslint/consistent-type-imports': [
+      'error',
+      {
+        prefer: 'type-imports',
+        fixStyle: 'separate-type-imports',
+        disallowTypeAnnotations: true,
+      },
+    ],
+    '@typescript-eslint/no-import-type-side-effects': 'error',
+    'simple-import-sort/imports': 'error',
+    'simple-import-sort/exports': 'error',
   },
+  overrides: [
+    {
+      files: ['*.stories.tsx'],
+      rules: {
+        'i18next/no-literal-string': 'off',
+      },
+    },
+  ],
   settings: {
     react: {
       version: 'detect',

invokeai/frontend/web/.gitignore

@@ -8,6 +8,7 @@ pnpm-debug.log*
 lerna-debug.log*
 
 node_modules
+.pnpm-store
 # We want to distribute the repo
 dist
 dist/**

invokeai/frontend/web/.prettierignore

@@ -9,7 +9,8 @@ index.html
 .yarn/
 .yalc/
 *.scss
-src/services/api/schema.d.ts
+src/services/api/schema.ts
 static/
 src/theme/css/overlayscrollbars.css
+src/theme_/css/overlayscrollbars.css
 pnpm-lock.yaml

invokeai/frontend/web/.storybook/ReduxInit.tsx

@@ -0,0 +1,25 @@
+import { PropsWithChildren, memo, useEffect } from 'react';
+import { modelChanged } from '../src/features/parameters/store/generationSlice';
+import { useAppDispatch } from '../src/app/store/storeHooks';
+import { useGlobalModifiersInit } from '../src/common/hooks/useGlobalModifiers';
+/**
+ * Initializes some state for storybook. Must be in a different component
+ * so that it is run inside the redux context.
+ */
+export const ReduxInit = memo((props: PropsWithChildren) => {
+  const dispatch = useAppDispatch();
+  useGlobalModifiersInit();
+  useEffect(() => {
+    dispatch(
+      modelChanged({
+        model_name: 'test_model',
+        base_model: 'sd-1',
+        model_type: 'main',
+      })
+    );
+  }, []);
+
+  return props.children;
+});
+
+ReduxInit.displayName = 'ReduxInit';

invokeai/frontend/web/.storybook/main.ts

@@ -6,6 +6,7 @@ const config: StorybookConfig = {
     '@storybook/addon-links',
     '@storybook/addon-essentials',
     '@storybook/addon-interactions',
+    '@storybook/addon-storysource',
   ],
   framework: {
     name: '@storybook/react-vite',

invokeai/frontend/web/.storybook/preview.tsx

@@ -1,16 +1,17 @@
 import { Preview } from '@storybook/react';
 import { themes } from '@storybook/theming';
 import i18n from 'i18next';
-import React from 'react';
 import { initReactI18next } from 'react-i18next';
 import { Provider } from 'react-redux';
-import GlobalHotkeys from '../src/app/components/GlobalHotkeys';
 import ThemeLocaleProvider from '../src/app/components/ThemeLocaleProvider';
+import { $baseUrl } from '../src/app/store/nanostores/baseUrl';
 import { createStore } from '../src/app/store/store';
+import { Container } from '@chakra-ui/react';
 // TODO: Disabled for IDE performance issues with our translation JSON
 // eslint-disable-next-line @typescript-eslint/ban-ts-comment
 // @ts-ignore
 import translationEN from '../public/locales/en.json';
+import { ReduxInit } from './ReduxInit';
 
 i18n.use(initReactI18next).init({
   lng: 'en',
@@ -25,17 +26,21 @@ i18n.use(initReactI18next).init({
 });
 
 const store = createStore(undefined, false);
+$baseUrl.set('http://localhost:9090');
 
 const preview: Preview = {
   decorators: [
-    (Story) => (
-      <Provider store={store}>
-        <ThemeLocaleProvider>
-          <GlobalHotkeys />
-          <Story />
-        </ThemeLocaleProvider>
-      </Provider>
-    ),
+    (Story) => {
+      return (
+        <Provider store={store}>
+          <ThemeLocaleProvider>
+            <ReduxInit>
+              <Story />
+            </ReduxInit>
+          </ThemeLocaleProvider>
+        </Provider>
+      );
+    },
   ],
   parameters: {
     docs: {

invokeai/frontend/web/.unimportedrc.json

@@ -0,0 +1,15 @@
+{
+  "entry": ["src/main.tsx"],
+  "extensions": [".ts", ".tsx"],
+  "ignorePatterns": [
+    "**/node_modules/**",
+    "dist/**",
+    "public/**",
+    "**/*.stories.tsx",
+    "config/**"
+  ],
+  "ignoreUnresolved": [],
+  "ignoreUnimported": ["src/i18.d.ts", "vite.config.ts", "src/vite-env.d.ts"],
+  "respectGitignore": true,
+  "ignoreUnused": []
+}

invokeai/frontend/web/config/common.mts

@@ -1,6 +1,6 @@
 import react from '@vitejs/plugin-react-swc';
 import { visualizer } from 'rollup-plugin-visualizer';
-import { PluginOption, UserConfig } from 'vite';
+import type { PluginOption, UserConfig } from 'vite';
 import eslint from 'vite-plugin-eslint';
 import tsconfigPaths from 'vite-tsconfig-paths';
 

invokeai/frontend/web/config/vite.app.config.mts

@@ -1,5 +1,6 @@
-import { UserConfig } from 'vite';
-import { commonPlugins } from './common';
+import type { UserConfig } from 'vite';
+
+import { commonPlugins } from './common.mjs';
 
 export const appConfig: UserConfig = {
   base: './',

invokeai/frontend/web/config/vite.package.config.mts

@@ -1,8 +1,9 @@
 import path from 'path';
-import { UserConfig } from 'vite';
-import dts from 'vite-plugin-dts';
+import type { UserConfig } from 'vite';
 import cssInjectedByJsPlugin from 'vite-plugin-css-injected-by-js';
-import { commonPlugins } from './common';
+import dts from 'vite-plugin-dts';
+
+import { commonPlugins } from './common.mjs';
 
 export const packageConfig: UserConfig = {
   base: './',

invokeai/frontend/web/index.html

@@ -1,24 +1,26 @@
 <!DOCTYPE html>
 <html lang="en">
-  <head>
-    <meta charset="UTF-8" />
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate">
-    <meta http-equiv="Pragma" content="no-cache">
-    <meta http-equiv="Expires" content="0">
-    <title>InvokeAI - A Stable Diffusion Toolkit</title>
-    <link rel="shortcut icon" type="icon" href="favicon.ico" />
-    <style>
-      html,
-      body {
-        padding: 0;
-        margin: 0;
-      }
-    </style>
-  </head>
 
-  <body dir="ltr">
-    <div id="root"></div>
-    <script type="module" src="/src/main.tsx"></script>
-  </body>
-</html>
+<head>
+  <meta charset="UTF-8" />
+  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+  <meta http-equiv="Cache-Control" content="no-cache, no-store, must-revalidate">
+  <meta http-equiv="Pragma" content="no-cache">
+  <meta http-equiv="Expires" content="0">
+  <title>Invoke - Community Edition</title>
+  <link rel="icon" type="icon" href="assets/images/invoke-favicon.svg" />
+  <style>
+    html,
+    body {
+      padding: 0;
+      margin: 0;
+    }
+  </style>
+</head>
+
+<body dir="ltr">
+  <div id="root"></div>
+  <script type="module" src="/src/main.tsx"></script>
+</body>
+
+</html>

invokeai/frontend/web/package.json

@@ -31,13 +31,17 @@
     "lint": "concurrently -g -n eslint,prettier,tsc,madge -c cyan,green,magenta,yellow \"pnpm run lint:eslint\" \"pnpm run lint:prettier\" \"pnpm run lint:tsc\" \"pnpm run lint:madge\"",
     "fix": "eslint --fix . && prettier --log-level warn --write .",
     "preinstall": "npx only-allow pnpm",
-    "postinstall": "patch-package && pnpm run theme",
+    "postinstall": "pnpm run theme",
     "theme": "chakra-cli tokens src/theme/theme.ts",
     "theme:watch": "chakra-cli tokens src/theme/theme.ts --watch",
     "storybook": "storybook dev -p 6006",
-    "build-storybook": "storybook build"
+    "build-storybook": "storybook build",
+    "unimported": "npx unimported"
   },
   "madge": {
+    "excludeRegExp": [
+      "^index.ts$"
+    ],
     "detectiveOptions": {
       "ts": {
         "skipTypeImports": true
@@ -53,56 +57,57 @@
     "@chakra-ui/layout": "^2.3.1",
     "@chakra-ui/portal": "^2.1.0",
     "@chakra-ui/react": "^2.8.2",
+    "@chakra-ui/react-use-size": "^2.1.0",
     "@chakra-ui/styled-system": "^2.9.2",
     "@chakra-ui/theme-tools": "^2.1.2",
     "@dagrejs/graphlib": "^2.1.13",
     "@dnd-kit/core": "^6.1.0",
     "@dnd-kit/utilities": "^3.2.2",
-    "@emotion/react": "^11.11.1",
+    "@emotion/react": "^11.11.3",
     "@emotion/styled": "^11.11.0",
     "@fontsource-variable/inter": "^5.0.16",
-    "@mantine/core": "^6.0.19",
-    "@mantine/form": "^6.0.19",
-    "@mantine/hooks": "^6.0.19",
+    "@mantine/form": "6.0.21",
     "@nanostores/react": "^0.7.1",
-    "@reduxjs/toolkit": "^2.0.1",
+    "@reduxjs/toolkit": "2.0.1",
     "@roarr/browser-log-writer": "^1.3.0",
-    "@storybook/manager-api": "^7.6.4",
-    "@storybook/theming": "^7.6.4",
+    "chakra-react-select": "^4.7.6",
     "compare-versions": "^6.1.0",
     "dateformat": "^5.0.3",
-    "framer-motion": "^10.16.15",
-    "i18next": "^23.7.8",
+    "framer-motion": "^10.17.9",
+    "i18next": "^23.7.16",
     "i18next-http-backend": "^2.4.2",
     "idb-keyval": "^6.2.1",
-    "konva": "^9.2.3",
+    "jsondiffpatch": "^0.6.0",
+    "konva": "^9.3.0",
     "lodash-es": "^4.17.21",
     "nanostores": "^0.9.5",
     "new-github-issue-url": "^1.0.0",
-    "overlayscrollbars": "^2.4.5",
+    "overlayscrollbars": "^2.4.6",
     "overlayscrollbars-react": "^0.5.3",
-    "patch-package": "^8.0.0",
     "query-string": "^8.1.0",
     "react": "^18.2.0",
     "react-colorful": "^5.6.1",
     "react-dom": "^18.2.0",
     "react-dropzone": "^14.2.3",
-    "react-error-boundary": "^4.0.11",
-    "react-hotkeys-hook": "4.4.1",
-    "react-i18next": "^13.5.0",
+    "react-error-boundary": "^4.0.12",
+    "react-hook-form": "^7.49.2",
+    "react-hotkeys-hook": "4.4.3",
+    "react-i18next": "^14.0.0",
     "react-icons": "^4.12.0",
     "react-konva": "^18.2.10",
-    "react-redux": "^9.0.2",
-    "react-resizable-panels": "^0.0.55",
+    "react-redux": "9.0.4",
+    "react-resizable-panels": "^1.0.8",
+    "react-select": "5.8.0",
+    "react-textarea-autosize": "^8.5.3",
     "react-use": "^17.4.2",
     "react-virtuoso": "^4.6.2",
     "reactflow": "^11.10.1",
     "redux-dynamic-middlewares": "^2.2.0",
-    "redux-remember": "^5.0.0",
+    "redux-remember": "^5.1.0",
     "roarr": "^7.21.0",
     "serialize-error": "^11.0.3",
-    "socket.io-client": "^4.7.2",
-    "type-fest": "^4.8.3",
+    "socket.io-client": "^4.7.3",
+    "type-fest": "^4.9.0",
     "use-debounce": "^10.0.0",
     "use-image": "^1.1.1",
     "uuid": "^9.0.1",
@@ -117,44 +122,56 @@
     "ts-toolbelt": "^9.6.0"
   },
   "devDependencies": {
+    "@arthurgeron/eslint-plugin-react-usememo": "^2.2.3",
     "@chakra-ui/cli": "^2.4.1",
-    "@storybook/addon-essentials": "^7.6.4",
-    "@storybook/addon-interactions": "^7.6.4",
-    "@storybook/addon-links": "^7.6.4",
-    "@storybook/blocks": "^7.6.4",
-    "@storybook/react": "^7.6.4",
-    "@storybook/react-vite": "^7.6.4",
-    "@storybook/test": "^7.6.4",
+    "@storybook/addon-docs": "^7.6.7",
+    "@storybook/addon-essentials": "^7.6.7",
+    "@storybook/addon-interactions": "^7.6.7",
+    "@storybook/addon-links": "^7.6.7",
+    "@storybook/addon-storysource": "^7.6.7",
+    "@storybook/blocks": "^7.6.7",
+    "@storybook/manager-api": "^7.6.7",
+    "@storybook/react": "^7.6.7",
+    "@storybook/react-vite": "^7.6.7",
+    "@storybook/test": "^7.6.7",
+    "@storybook/theming": "^7.6.7",
     "@types/dateformat": "^5.0.2",
     "@types/lodash-es": "^4.17.12",
-    "@types/node": "^20.9.0",
-    "@types/react": "^18.2.37",
-    "@types/react-dom": "^18.2.17",
+    "@types/node": "^20.10.7",
+    "@types/react": "^18.2.47",
+    "@types/react-dom": "^18.2.18",
     "@types/uuid": "^9.0.7",
-    "@typescript-eslint/eslint-plugin": "^6.13.2",
-    "@typescript-eslint/parser": "^6.13.2",
+    "@typescript-eslint/eslint-plugin": "^6.18.0",
+    "@typescript-eslint/parser": "^6.18.0",
     "@vitejs/plugin-react-swc": "^3.5.0",
     "concurrently": "^8.2.2",
-    "eslint": "^8.55.0",
+    "eslint": "^8.56.0",
     "eslint-config-prettier": "^9.1.0",
     "eslint-plugin-i18next": "^6.0.3",
-    "eslint-plugin-path": "^1.2.2",
+    "eslint-plugin-import": "^2.29.1",
+    "eslint-plugin-path": "^1.2.3",
     "eslint-plugin-react": "^7.33.2",
     "eslint-plugin-react-hooks": "^4.6.0",
+    "eslint-plugin-simple-import-sort": "^10.0.0",
     "eslint-plugin-storybook": "^0.6.15",
     "eslint-plugin-unused-imports": "^3.0.0",
     "madge": "^6.1.0",
     "openapi-types": "^12.1.3",
-    "openapi-typescript": "^6.7.2",
-    "prettier": "^3.1.0",
-    "rollup-plugin-visualizer": "^5.10.0",
-    "storybook": "^7.6.4",
+    "openapi-typescript": "^6.7.3",
+    "prettier": "^3.1.1",
+    "rollup-plugin-visualizer": "^5.12.0",
+    "storybook": "^7.6.7",
     "ts-toolbelt": "^9.6.0",
     "typescript": "^5.3.3",
-    "vite": "^4.5.1",
-    "vite-plugin-css-injected-by-js": "^3.3.0",
-    "vite-plugin-dts": "^3.6.4",
+    "vite": "^5.0.11",
+    "vite-plugin-css-injected-by-js": "^3.3.1",
+    "vite-plugin-dts": "^3.7.0",
     "vite-plugin-eslint": "^1.8.1",
-    "vite-tsconfig-paths": "^4.2.2"
+    "vite-tsconfig-paths": "^4.2.3"
+  },
+  "pnpm": {
+    "patchedDependencies": {
+      "reselect@5.0.1": "patches/reselect@5.0.1.patch"
+    }
   }
 }

invokeai/frontend/web/public/assets/images/invoke-avatar-circle.svg

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invokeai/frontend/web/public/assets/images/invoke-avatar-square.svg

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invokeai/frontend/web/public/assets/images/invoke-favicon.svg

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invokeai/frontend/web/public/assets/images/invoke-symbol-char-lrg.svg

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invokeai/frontend/web/public/assets/images/invoke-symbol-char-sml.svg

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invokeai/frontend/web/public/assets/images/invoke-symbol-wht-lrg.svg

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

@@ -83,10 +83,6 @@
             "title": "خيارات التثبيت",
             "desc": "ثبت لوحة الخيارات"
         },
-        "toggleViewer": {
-            "title": "تبديل العارض",
-            "desc": "فتح وإغلاق مشاهد الصور"
-        },
         "toggleGallery": {
             "title": "تبديل المعرض",
             "desc": "فتح وإغلاق درابزين المعرض"
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             "title": "الصورة التالية",
             "desc": "عرض الصورة التالية في الصالة"
         },
-        "toggleGalleryPin": {
-            "title": "تبديل تثبيت الصالة",
-            "desc": "يثبت ويفتح تثبيت الصالة على الواجهة الرسومية"
-        },
         "increaseGalleryThumbSize": {
             "title": "زيادة حجم صورة الصالة",
             "desc": "يزيد حجم الصور المصغرة في الصالة"