chore: ruff E721

Looks like in the latest version of ruff, E721 was added or changed and now catches something it didn't before.

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

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

.github/pull_request_template.md

@@ -8,7 +8,7 @@
 
 ## QA Instructions
 
-<!--WHEN APPLICABLE: Describe how you have tested the changes in this PR. Provide enough detail that a reviewer can reproduce your tests.-->
+<!--WHEN APPLICABLE: Describe how we can test the changes in this PR.-->
 
 ## Merge Plan
 

README.md

@@ -12,24 +12,12 @@
 
 Invoke is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. Invoke offers an industry leading web-based UI, and serves as the foundation for multiple commercial products.
 
-Invoke is available in two editions:
-
-| **Community Edition**                                                                                                      | **Professional Edition**                                                                            |
-|----------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------|
-| **For users looking for a locally installed, self-hosted and self-managed service**                                         | **For users or teams looking for a cloud-hosted, fully managed service**                            |
-| - Free to use under a commercially-friendly license                                                                         | - Monthly subscription fee with three different plan levels                                         |
-| - Download and install on compatible hardware                                                                               | - Offers additional benefits, including multi-user support, improved model training, and more                          |
-| - Includes all core studio features: generate, refine, iterate on images, and build workflows                               | - Hosted in the cloud for easy, secure model access and scalability                                               |
-| Quick Start -> [Installation and Updates][installation docs]                                                                     | More Information -> [www.invoke.com/pricing](https://www.invoke.com/pricing)                        |
+[Installation and Updates][installation docs] - [Documentation and Tutorials][docs home] - [Bug Reports][github issues] - [Contributing][contributing docs]
 
+<div align="center">
 
 ![Highlighted Features - Canvas and Workflows](https://github.com/invoke-ai/InvokeAI/assets/31807370/708f7a82-084f-4860-bfbe-e2588c53548d)
 
-# Documentation
-| **Quick Links**                                                                                                      | 
-|----------------------------------------------------------------------------------------------------------------------------|
-|  [Installation and Updates][installation docs] - [Documentation and Tutorials][docs home] - [Bug Reports][github issues] - [Contributing][contributing docs]  | 
-
 </div>
 
 ## Quick Start
@@ -49,33 +37,6 @@ Invoke is available in two editions:
 
 More detail, including hardware requirements and manual install instructions, are available in the [installation documentation][installation docs].
 
-## Docker Container
-
-We publish official container images in Github Container Registry: https://github.com/invoke-ai/InvokeAI/pkgs/container/invokeai. Both CUDA and ROCm images are available. Check the above link for relevant tags.
-
-> [!IMPORTANT]
-> Ensure that Docker is set up to use the GPU. Refer to [NVIDIA][nvidia docker docs] or [AMD][amd docker docs] documentation.
-
-### Generate!
-
-Run the container, modifying the command as necessary:
-
-```bash
-docker run --runtime=nvidia --gpus=all --publish 9090:9090 ghcr.io/invoke-ai/invokeai
-```
-
-Then open `http://localhost:9090` and install some models using the Model Manager tab to begin generating.
-
-For ROCm, add `--device /dev/kfd --device /dev/dri` to the `docker run` command.
-
-### Persist your data
-
-You will likely want to persist your workspace outside of the container. Use the `--volume /home/myuser/invokeai:/invokeai` flag to mount some local directory (using its **absolute** path) to the `/invokeai` path inside the container. Your generated images and models will reside there. You can use this directory with other InvokeAI installations, or switch between runtime directories as needed.
-
-### DIY
-
-Build your own image and customize the environment to match your needs using our `docker-compose` stack. See [README.md](./docker/README.md) in the [docker](./docker) directory.
-
 ## Troubleshooting, FAQ and Support
 
 Please review our [FAQ][faq] for solutions to common installation problems and other issues.
@@ -153,5 +114,3 @@ Original portions of the software are Copyright © 2024 by respective contributo
 [latest release link]: https://github.com/invoke-ai/InvokeAI/releases/latest
 [translation status badge]: https://hosted.weblate.org/widgets/invokeai/-/svg-badge.svg
 [translation status link]: https://hosted.weblate.org/engage/invokeai/
-[nvidia docker docs]: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
-[amd docker docs]: https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html

docker/.env.sample

@@ -19,9 +19,8 @@
 ## INVOKEAI_PORT is the port on which the InvokeAI web interface will be available
 # INVOKEAI_PORT=9090
 
-## GPU_DRIVER can be set to either `cuda` or `rocm` to enable GPU support in the container accordingly.
-# GPU_DRIVER=cuda #| rocm
+## GPU_DRIVER can be set to either `nvidia` or `rocm` to enable GPU support in the container accordingly.
+# GPU_DRIVER=nvidia #| rocm
 
 ## CONTAINER_UID can be set to the UID of the user on the host system that should own the files in the container.
-## It is usually not necessary to change this. Use `id -u` on the host system to find the UID.
 # CONTAINER_UID=1000

docker/README.md

@@ -1,75 +1,41 @@
-# Invoke in Docker
+# InvokeAI Containerized
 
-- Ensure that Docker can use the GPU on your system
-- This documentation assumes Linux, but should work similarly under Windows with WSL2
-- We don't recommend running Invoke in Docker on macOS at this time. It works, but very slowly.
+All commands should be run within the `docker` directory: `cd docker`
 
-## Quickstart :lightning:
+## Quickstart :rocket:
 
-No `docker compose`, no persistence, just a simple one-liner using the official images:
+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!
 
-**CUDA:**
+For more configuration options (using an AMD GPU, custom root directory location, etc): read on.
 
-```bash
-docker run --runtime=nvidia --gpus=all --publish 9090:9090 ghcr.io/invoke-ai/invokeai
-```
-
-**ROCm:**
-
-```bash
-docker run --device /dev/kfd --device /dev/dri --publish 9090:9090 ghcr.io/invoke-ai/invokeai:main-rocm
-```
-
-Open `http://localhost:9090` in your browser once the container finishes booting, install some models, and generate away!
-
-> [!TIP]
-> To persist your data (including downloaded models) outside of the container, add a `--volume/-v` flag to the above command, e.g.: `docker run --volume /some/local/path:/invokeai <...the rest of the command>`
-
-## Customize the container
-
-We ship the `run.sh` script, which is a convenient wrapper around `docker compose` for cases where custom image build args are needed. Alternatively, the familiar `docker compose` commands work just as well.
-
-```bash
-cd docker
-cp .env.sample .env
-# edit .env to your liking if you need to; it is well commented.
-./run.sh
-```
-
-It will take a few minutes to build the image the first time. Once the application starts up, open `http://localhost:9090` in your browser to invoke!
-
-## Docker setup in detail
+## Detailed setup
 
 #### Linux
 
 1. Ensure builkit is enabled in the Docker daemon settings (`/etc/docker/daemon.json`)
 2. Install the `docker compose` plugin using your package manager, or follow a [tutorial](https://docs.docker.com/compose/install/linux/#install-using-the-repository).
-    - The deprecated `docker-compose` (hyphenated) CLI probably won't work. Update to a recent version.
+    - The deprecated `docker-compose` (hyphenated) CLI continues to work for now.
 3. Ensure docker daemon is able to access the GPU.
-    - [NVIDIA docs](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
-    - [AMD docs](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html)
+    - You may need to install [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
 
 #### macOS
 
-> [!TIP]
-> You'll be better off installing Invoke directly on your system, because Docker can not use the GPU on macOS.
-
-If you are still reading:
-
 1. Ensure Docker has at least 16GB RAM
 2. Enable VirtioFS for file sharing
 3. Enable `docker compose` V2 support
 
-This is done via Docker Desktop preferences.
+This is done via Docker Desktop preferences
 
-### Configure the Invoke Environment
+### Configure Invoke environment
 
-1. Make a copy of `.env.sample` and name it `.env` (`cp .env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to the desired location of the InvokeAI runtime directory. It may be an existing directory from a previous installation (post 4.0.0).
+1. Make a copy of `.env.sample` and name it `.env` (`cp .env.sample .env` (Mac/Linux) or `copy example.env .env` (Windows)). Make changes as necessary. Set `INVOKEAI_ROOT` to an absolute path to:
+    a. the desired location of the InvokeAI runtime directory, or
+    b. an existing, v3.0.0 compatible runtime directory.
 1. Execute `run.sh`
 
 The image will be built automatically if needed.
 
-The runtime directory (holding models and outputs) will be created in the location specified by `INVOKEAI_ROOT`. The default location is `~/invokeai`. Navigate to the Model Manager tab and install some models before generating.
+The runtime directory (holding models and outputs) will be created in the location specified by `INVOKEAI_ROOT`. The default location is `~/invokeai`. The runtime directory will be populated with the base configs and models necessary to start generating.
 
 ### Use a GPU
 
@@ -77,9 +43,9 @@ The runtime directory (holding models and outputs) will be created in the locati
 - WSL2 is *required* for Windows.
 - only `x86_64` architecture is supported.
 
-The Docker daemon on the system must be already set up to use the GPU. In case of Linux, this involves installing `nvidia-docker-runtime` and configuring the `nvidia` runtime as default. Steps will be different for AMD. Please see Docker/NVIDIA/AMD documentation for the most up-to-date instructions for using your GPU with Docker.
+The Docker daemon on the system must be already set up to use the GPU. In case of Linux, this involves installing `nvidia-docker-runtime` and configuring the `nvidia` runtime as default. Steps will be different for AMD. Please see Docker documentation for the most up-to-date instructions for using your GPU with Docker.
 
-To use an AMD GPU, set `GPU_DRIVER=rocm` in your `.env` file before running `./run.sh`.
+To use an AMD GPU, set `GPU_DRIVER=rocm` in your `.env` file.
 
 ## Customize
 
@@ -93,10 +59,10 @@ Values are optional, but setting `INVOKEAI_ROOT` is highly recommended. The defa
 INVOKEAI_ROOT=/Volumes/WorkDrive/invokeai
 HUGGINGFACE_TOKEN=the_actual_token
 CONTAINER_UID=1000
-GPU_DRIVER=cuda
+GPU_DRIVER=nvidia
 ```
 
-Any environment variables supported by InvokeAI can be set here. See the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.
+Any environment variables supported by InvokeAI can be set here - please see the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.
 
 ## Even More Customizing!
 

docker/docker-compose.yml

@@ -1,5 +1,7 @@
 # Copyright (c) 2023 Eugene Brodsky https://github.com/ebr
 
+version: '3.8'
+
 x-invokeai: &invokeai
     image: "local/invokeai:latest"
     build:
@@ -30,7 +32,7 @@ x-invokeai: &invokeai
 
 
 services:
-  invokeai-cuda:
+  invokeai-nvidia:
     <<: *invokeai
     deploy:
       resources:

docker/docker-entrypoint.sh

@@ -23,18 +23,18 @@ usermod -u ${USER_ID} ${USER} 1>/dev/null
 # but it is useful to have the full SSH server e.g. on Runpod.
 # (use SCP to copy files to/from the image, etc)
 if [[ -v "PUBLIC_KEY" ]] && [[ ! -d "${HOME}/.ssh" ]]; then
-  apt-get update
-  apt-get install -y openssh-server
-  pushd "$HOME"
-  mkdir -p .ssh
-  echo "${PUBLIC_KEY}" >.ssh/authorized_keys
-  chmod -R 700 .ssh
-  popd
-  service ssh start
+    apt-get update
+    apt-get install -y openssh-server
+    pushd "$HOME"
+    mkdir -p .ssh
+    echo "${PUBLIC_KEY}" > .ssh/authorized_keys
+    chmod -R 700 .ssh
+    popd
+    service ssh start
 fi
 
 mkdir -p "${INVOKEAI_ROOT}"
-chown --recursive ${USER} "${INVOKEAI_ROOT}" || true
+chown --recursive ${USER} "${INVOKEAI_ROOT}"
 cd "${INVOKEAI_ROOT}"
 
 # Run the CMD as the Container User (not root).

docker/run.sh

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

docs/contributing/MODEL_MANAGER.md

@@ -408,7 +408,7 @@ config = get_config()
 
 logger = InvokeAILogger.get_logger(config=config)
 db = SqliteDatabase(config.db_path, logger)
-record_store = ModelRecordServiceSQL(db, logger)
+record_store = ModelRecordServiceSQL(db)
 queue = DownloadQueueService()
 queue.start()
 

docs/installation/040_INSTALL_DOCKER.md

@@ -4,37 +4,50 @@ title: Installing with Docker
 
 # :fontawesome-brands-docker: Docker
 
-!!! warning "macOS users"
+!!! warning "macOS and AMD GPU Users"
 
-    Docker can not access the GPU on macOS, so your generation speeds will be slow. [Install InvokeAI](INSTALLATION.md) instead.
+    We highly recommend to Install InvokeAI locally using [these instructions](INSTALLATION.md),
+    because Docker containers can not access the GPU on macOS.
+
+!!! warning "AMD GPU Users"
+
+    Container support for AMD GPUs has been reported to work by the community, but has not received
+    extensive testing. Please make sure to set the `GPU_DRIVER=rocm` environment variable (see below), and
+    use the `build.sh` script to build the image for this to take effect at build time.
 
 !!! tip "Linux and Windows Users"
 
-    Configure Docker to access your machine's GPU.
+    For optimal performance, configure your Docker daemon to access your machine's GPU.
     Docker Desktop on Windows [includes GPU support](https://www.docker.com/blog/wsl-2-gpu-support-for-docker-desktop-on-nvidia-gpus/).
-    Linux users should follow the [NVIDIA](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) or [AMD](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html) documentation.
+    Linux users should install and configure the [NVIDIA Container Toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
+
+## Why containers?
+
+They provide a flexible, reliable way to build and deploy InvokeAI.
+See [Processes](https://12factor.net/processes) under the Twelve-Factor App
+methodology for details on why running applications in such a stateless fashion is important.
+
+The container is configured for CUDA by default, but can be built to support AMD GPUs
+by setting the `GPU_DRIVER=rocm` environment variable at Docker image build time.
+
+Developers on Apple silicon (M1/M2/M3): You
+[can't access your GPU cores from Docker containers](https://github.com/pytorch/pytorch/issues/81224)
+and performance is reduced compared with running it directly on macOS but for
+development purposes it's fine. Once you're done with development tasks on your
+laptop you can build for the target platform and architecture and deploy to
+another environment with NVIDIA GPUs on-premises or in the cloud.
 
 ## TL;DR
 
-Ensure your Docker setup is able to use your GPU. Then:
-
-    ```bash
-    docker run --runtime=nvidia --gpus=all --publish 9090:9090 ghcr.io/invoke-ai/invokeai
-    ```
-
-Once the container starts up, open http://localhost:9090 in your browser, install some models, and start generating.
-
-## Build-It-Yourself
-
-All the docker materials are located inside the [docker](https://github.com/invoke-ai/InvokeAI/tree/main/docker) directory in the Git repo.
+This assumes properly configured Docker on Linux or Windows/WSL2. Read on for detailed customization options.
 
     ```bash
+    # docker compose commands should be run from the `docker` directory
     cd docker
-    cp .env.sample .env
     docker compose up
     ```
 
-We also ship the `run.sh` convenience script. See the `docker/README.md` file for detailed instructions on how to customize the docker setup to your needs.
+## Installation in a Linux container (desktop)
 
 ### Prerequisites
 
@@ -45,9 +58,18 @@ Preferences, Resources, Advanced. Increase the CPUs and Memory to avoid this
 [Issue](https://github.com/invoke-ai/InvokeAI/issues/342). You may need to
 increase Swap and Disk image size too.
 
+#### Get a Huggingface-Token
+
+Besides the Docker Agent you will need an Account on
+[huggingface.co](https://huggingface.co/join).
+
+After you succesfully registered your account, go to
+[huggingface.co/settings/tokens](https://huggingface.co/settings/tokens), create
+a token and copy it, since you will need in for the next step.
+
 ### Setup
 
-Set up your environment variables. In the `docker` directory, make a copy of `.env.sample` and name it `.env`. Make changes as necessary.
+Set up your environmnent variables. In the `docker` directory, make a copy of `.env.sample` and name it `.env`. Make changes as necessary.
 
 Any environment variables supported by InvokeAI can be set here - please see the [CONFIGURATION](../features/CONFIGURATION.md) for further detail.
 
@@ -81,9 +103,10 @@ Once the container starts up (and configures the InvokeAI root directory if this
 ## Troubleshooting / FAQ
 
 - Q: I am running on Windows under WSL2, and am seeing a "no such file or directory" error.
-- A: Your `docker-entrypoint.sh` might have has Windows (CRLF) line endings, depending how you cloned the repository.
-    To solve this, change the line endings in the `docker-entrypoint.sh` file to `LF`. You can do this in VSCode
+- A: Your `docker-entrypoint.sh` file likely has Windows (CRLF) as opposed to Unix (LF) line endings,
+    and you may have cloned this repository before the issue was fixed. To solve this, please change
+    the line endings in the `docker-entrypoint.sh` file to `LF`. You can do this in VSCode
     (`Ctrl+P` and search for "line endings"), or by using the `dos2unix` utility in WSL.
     Finally, you may delete `docker-entrypoint.sh` followed by  `git pull; git checkout docker/docker-entrypoint.sh`
     to reset the file to its most recent version.
-    For more information on this issue, see [Docker Desktop documentation](https://docs.docker.com/desktop/troubleshoot/topics/#avoid-unexpected-syntax-errors-use-unix-style-line-endings-for-files-in-containers)
+    For more information on this issue, please see the [Docker Desktop documentation](https://docs.docker.com/desktop/troubleshoot/topics/#avoid-unexpected-syntax-errors-use-unix-style-line-endings-for-files-in-containers)

installer/templates/invoke.bat.in

@@ -13,7 +13,7 @@ echo 2. Open the developer console
 echo 3. Command-line help
 echo Q - Quit
 echo.
-echo To update, download and run the installer from https://github.com/invoke-ai/InvokeAI/releases/latest
+echo To update, download and run the installer from https://github.com/invoke-ai/InvokeAI/releases/latest.
 echo.
 set /P choice="Please enter 1-4, Q: [1] "
 if not defined choice set choice=1

invokeai/app/api/dependencies.py

@@ -4,39 +4,37 @@ from logging import Logger
 
 import torch
 
-from invokeai.app.services.board_image_records.board_image_records_sqlite import SqliteBoardImageRecordStorage
-from invokeai.app.services.board_images.board_images_default import BoardImagesService
-from invokeai.app.services.board_records.board_records_sqlite import SqliteBoardRecordStorage
-from invokeai.app.services.boards.boards_default import BoardService
-from invokeai.app.services.bulk_download.bulk_download_default import BulkDownloadService
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.download.download_default import DownloadQueueService
-from invokeai.app.services.events.events_fastapievents import FastAPIEventService
-from invokeai.app.services.image_files.image_files_disk import DiskImageFileStorage
-from invokeai.app.services.image_records.image_records_sqlite import SqliteImageRecordStorage
-from invokeai.app.services.images.images_default import ImageService
-from invokeai.app.services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
-from invokeai.app.services.invocation_services import InvocationServices
-from invokeai.app.services.invocation_stats.invocation_stats_default import InvocationStatsService
-from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.model_images.model_images_default import ModelImageFileStorageDisk
-from invokeai.app.services.model_manager.model_manager_default import ModelManagerService
-from invokeai.app.services.model_records.model_records_sql import ModelRecordServiceSQL
-from invokeai.app.services.names.names_default import SimpleNameService
 from invokeai.app.services.object_serializer.object_serializer_disk import ObjectSerializerDisk
 from invokeai.app.services.object_serializer.object_serializer_forward_cache import ObjectSerializerForwardCache
-from invokeai.app.services.session_processor.session_processor_default import (
-    DefaultSessionProcessor,
-    DefaultSessionRunner,
-)
-from invokeai.app.services.session_queue.session_queue_sqlite import SqliteSessionQueue
 from invokeai.app.services.shared.sqlite.sqlite_util import init_db
-from invokeai.app.services.urls.urls_default import LocalUrlService
-from invokeai.app.services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
 from invokeai.backend.util.logging import InvokeAILogger
 from invokeai.version.invokeai_version import __version__
 
+from ..services.board_image_records.board_image_records_sqlite import SqliteBoardImageRecordStorage
+from ..services.board_images.board_images_default import BoardImagesService
+from ..services.board_records.board_records_sqlite import SqliteBoardRecordStorage
+from ..services.boards.boards_default import BoardService
+from ..services.bulk_download.bulk_download_default import BulkDownloadService
+from ..services.config import InvokeAIAppConfig
+from ..services.download import DownloadQueueService
+from ..services.events.events_fastapievents import FastAPIEventService
+from ..services.image_files.image_files_disk import DiskImageFileStorage
+from ..services.image_records.image_records_sqlite import SqliteImageRecordStorage
+from ..services.images.images_default import ImageService
+from ..services.invocation_cache.invocation_cache_memory import MemoryInvocationCache
+from ..services.invocation_services import InvocationServices
+from ..services.invocation_stats.invocation_stats_default import InvocationStatsService
+from ..services.invoker import Invoker
+from ..services.model_images.model_images_default import ModelImageFileStorageDisk
+from ..services.model_manager.model_manager_default import ModelManagerService
+from ..services.model_records import ModelRecordServiceSQL
+from ..services.names.names_default import SimpleNameService
+from ..services.session_processor.session_processor_default import DefaultSessionProcessor, DefaultSessionRunner
+from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
+from ..services.urls.urls_default import LocalUrlService
+from ..services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
+
 
 # TODO: is there a better way to achieve this?
 def check_internet() -> bool:
@@ -99,7 +97,7 @@ class ApiDependencies:
         model_images_service = ModelImageFileStorageDisk(model_images_folder / "model_images")
         model_manager = ModelManagerService.build_model_manager(
             app_config=configuration,
-            model_record_service=ModelRecordServiceSQL(db=db, logger=logger),
+            model_record_service=ModelRecordServiceSQL(db=db),
             download_queue=download_queue_service,
             events=events,
         )

invokeai/app/api/routers/app_info.py

@@ -10,13 +10,14 @@ from fastapi import Body
 from fastapi.routing import APIRouter
 from pydantic import BaseModel, Field
 
-from invokeai.app.api.dependencies import ApiDependencies
 from invokeai.app.invocations.upscale import ESRGAN_MODELS
 from invokeai.app.services.invocation_cache.invocation_cache_common import InvocationCacheStatus
 from invokeai.backend.image_util.infill_methods.patchmatch import PatchMatch
 from invokeai.backend.util.logging import logging
 from invokeai.version import __version__
 
+from ..dependencies import ApiDependencies
+
 
 class LogLevel(int, Enum):
     NotSet = logging.NOTSET

invokeai/app/api/routers/board_images.py

@@ -2,7 +2,7 @@ from fastapi import Body, HTTPException
 from fastapi.routing import APIRouter
 from pydantic import BaseModel, Field
 
-from invokeai.app.api.dependencies import ApiDependencies
+from ..dependencies import ApiDependencies
 
 board_images_router = APIRouter(prefix="/v1/board_images", tags=["boards"])
 

invokeai/app/api/routers/boards.py

@@ -4,11 +4,12 @@ from fastapi import Body, HTTPException, Path, Query
 from fastapi.routing import APIRouter
 from pydantic import BaseModel, Field
 
-from invokeai.app.api.dependencies import ApiDependencies
-from invokeai.app.services.board_records.board_records_common import BoardChanges, UncategorizedImageCounts
+from invokeai.app.services.board_records.board_records_common import BoardChanges
 from invokeai.app.services.boards.boards_common import BoardDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 
+from ..dependencies import ApiDependencies
+
 boards_router = APIRouter(prefix="/v1/boards", tags=["boards"])
 
 
@@ -31,7 +32,6 @@ class DeleteBoardResult(BaseModel):
 )
 async def create_board(
     board_name: str = Query(description="The name of the board to create"),
-    is_private: bool = Query(default=False, description="Whether the board is private"),
 ) -> BoardDTO:
     """Creates a board"""
     try:
@@ -118,13 +118,15 @@ async def list_boards(
     all: Optional[bool] = Query(default=None, description="Whether to list all boards"),
     offset: Optional[int] = Query(default=None, description="The page offset"),
     limit: Optional[int] = Query(default=None, description="The number of boards per page"),
-    include_archived: bool = Query(default=False, description="Whether or not to include archived boards in list"),
 ) -> Union[OffsetPaginatedResults[BoardDTO], list[BoardDTO]]:
     """Gets a list of boards"""
     if all:
-        return ApiDependencies.invoker.services.boards.get_all(include_archived)
+        return ApiDependencies.invoker.services.boards.get_all()
     elif offset is not None and limit is not None:
-        return ApiDependencies.invoker.services.boards.get_many(offset, limit, include_archived)
+        return ApiDependencies.invoker.services.boards.get_many(
+            offset,
+            limit,
+        )
     else:
         raise HTTPException(
             status_code=400,
@@ -146,14 +148,3 @@ async def list_all_board_image_names(
         board_id,
     )
     return image_names
-
-
-@boards_router.get(
-    "/uncategorized/counts",
-    operation_id="get_uncategorized_image_counts",
-    response_model=UncategorizedImageCounts,
-)
-async def get_uncategorized_image_counts() -> UncategorizedImageCounts:
-    """Gets count of images and assets for uncategorized images (images with no board assocation)"""
-
-    return ApiDependencies.invoker.services.board_records.get_uncategorized_image_counts()

invokeai/app/api/routers/download_queue.py

@@ -8,12 +8,13 @@ from fastapi.routing import APIRouter
 from pydantic.networks import AnyHttpUrl
 from starlette.exceptions import HTTPException
 
-from invokeai.app.api.dependencies import ApiDependencies
 from invokeai.app.services.download import (
     DownloadJob,
     UnknownJobIDException,
 )
 
+from ..dependencies import ApiDependencies
+
 download_queue_router = APIRouter(prefix="/v1/download_queue", tags=["download_queue"])
 
 

invokeai/app/api/routers/images.py

@@ -8,16 +8,12 @@ from fastapi.routing import APIRouter
 from PIL import Image
 from pydantic import BaseModel, Field, JsonValue
 
-from invokeai.app.api.dependencies import ApiDependencies
 from invokeai.app.invocations.fields import MetadataField
-from invokeai.app.services.image_records.image_records_common import (
-    ImageCategory,
-    ImageRecordChanges,
-    ResourceOrigin,
-)
+from invokeai.app.services.image_records.image_records_common import ImageCategory, ImageRecordChanges, ResourceOrigin
 from invokeai.app.services.images.images_common import ImageDTO, ImageUrlsDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.shared.sqlite.sqlite_common import SQLiteDirection
+
+from ..dependencies import ApiDependencies
 
 images_router = APIRouter(prefix="/v1/images", tags=["images"])
 
@@ -233,14 +229,21 @@ async def get_image_workflow(
 )
 async def get_image_full(
     image_name: str = Path(description="The name of full-resolution image file to get"),
-) -> Response:
+) -> FileResponse:
     """Gets a full-resolution image file"""
 
     try:
         path = ApiDependencies.invoker.services.images.get_path(image_name)
-        with open(path, "rb") as f:
-            content = f.read()
-        response = Response(content, media_type="image/png")
+
+        if not ApiDependencies.invoker.services.images.validate_path(path):
+            raise HTTPException(status_code=404)
+
+        response = FileResponse(
+            path,
+            media_type="image/png",
+            filename=image_name,
+            content_disposition_type="inline",
+        )
         response.headers["Cache-Control"] = f"max-age={IMAGE_MAX_AGE}"
         return response
     except Exception:
@@ -261,14 +264,15 @@ async def get_image_full(
 )
 async def get_image_thumbnail(
     image_name: str = Path(description="The name of thumbnail image file to get"),
-) -> Response:
+) -> FileResponse:
     """Gets a thumbnail image file"""
 
     try:
         path = ApiDependencies.invoker.services.images.get_path(image_name, thumbnail=True)
-        with open(path, "rb") as f:
-            content = f.read()
-        response = Response(content, media_type="image/webp")
+        if not ApiDependencies.invoker.services.images.validate_path(path):
+            raise HTTPException(status_code=404)
+
+        response = FileResponse(path, media_type="image/webp", content_disposition_type="inline")
         response.headers["Cache-Control"] = f"max-age={IMAGE_MAX_AGE}"
         return response
     except Exception:
@@ -312,14 +316,16 @@ async def list_image_dtos(
     ),
     offset: int = Query(default=0, description="The page offset"),
     limit: int = Query(default=10, description="The number of images per page"),
-    order_dir: SQLiteDirection = Query(default=SQLiteDirection.Descending, description="The order of sort"),
-    starred_first: bool = Query(default=True, description="Whether to sort by starred images first"),
-    search_term: Optional[str] = Query(default=None, description="The term to search for"),
 ) -> OffsetPaginatedResults[ImageDTO]:
     """Gets a list of image DTOs"""
 
     image_dtos = ApiDependencies.invoker.services.images.get_many(
-        offset, limit, starred_first, order_dir, image_origin, categories, is_intermediate, board_id, search_term
+        offset,
+        limit,
+        image_origin,
+        categories,
+        is_intermediate,
+        board_id,
     )
 
     return image_dtos

invokeai/app/api/routers/model_manager.py

@@ -3,9 +3,9 @@
 
 import io
 import pathlib
+import shutil
 import traceback
 from copy import deepcopy
-from tempfile import TemporaryDirectory
 from typing import Any, Dict, List, Optional, Type
 
 from fastapi import Body, Path, Query, Response, UploadFile
@@ -16,10 +16,10 @@ from pydantic import AnyHttpUrl, BaseModel, ConfigDict, Field
 from starlette.exceptions import HTTPException
 from typing_extensions import Annotated
 
-from invokeai.app.api.dependencies import ApiDependencies
 from invokeai.app.services.model_images.model_images_common import ModelImageFileNotFoundException
 from invokeai.app.services.model_install.model_install_common import ModelInstallJob
 from invokeai.app.services.model_records import (
+    DuplicateModelException,
     InvalidModelException,
     ModelRecordChanges,
     UnknownModelException,
@@ -30,12 +30,15 @@ from invokeai.backend.model_manager.config import (
     MainCheckpointConfig,
     ModelFormat,
     ModelType,
+    SubModelType,
 )
 from invokeai.backend.model_manager.metadata.fetch.huggingface import HuggingFaceMetadataFetch
 from invokeai.backend.model_manager.metadata.metadata_base import ModelMetadataWithFiles, UnknownMetadataException
 from invokeai.backend.model_manager.search import ModelSearch
 from invokeai.backend.model_manager.starter_models import STARTER_MODELS, StarterModel, StarterModelWithoutDependencies
 
+from ..dependencies import ApiDependencies
+
 model_manager_router = APIRouter(prefix="/v2/models", tags=["model_manager"])
 
 # images are immutable; set a high max-age
@@ -171,6 +174,18 @@ async def get_model_record(
         raise HTTPException(status_code=404, detail=str(e))
 
 
+# @model_manager_router.get("/summary", operation_id="list_model_summary")
+# async def list_model_summary(
+#     page: int = Query(default=0, description="The page to get"),
+#     per_page: int = Query(default=10, description="The number of models per page"),
+#     order_by: ModelRecordOrderBy = Query(default=ModelRecordOrderBy.Default, description="The attribute to order by"),
+# ) -> PaginatedResults[ModelSummary]:
+#     """Gets a page of model summary data."""
+#     record_store = ApiDependencies.invoker.services.model_manager.store
+#     results: PaginatedResults[ModelSummary] = record_store.list_models(page=page, per_page=per_page, order_by=order_by)
+#     return results
+
+
 class FoundModel(BaseModel):
     path: str = Field(description="Path to the model")
     is_installed: bool = Field(description="Whether or not the model is already installed")
@@ -731,36 +746,39 @@ async def convert_model(
         logger.error(f"The model with key {key} is not a main checkpoint model.")
         raise HTTPException(400, f"The model with key {key} is not a main checkpoint model.")
 
-    with TemporaryDirectory(dir=ApiDependencies.invoker.services.configuration.models_path) as tmpdir:
-        convert_path = pathlib.Path(tmpdir) / pathlib.Path(model_config.path).stem
-        converted_model = loader.load_model(model_config)
-        # write the converted file to the convert path
-        raw_model = converted_model.model
-        assert hasattr(raw_model, "save_pretrained")
-        raw_model.save_pretrained(convert_path)
-        assert convert_path.exists()
+    # loading the model will convert it into a cached diffusers file
+    try:
+        cc_size = loader.convert_cache.max_size
+        if cc_size == 0:  # temporary set the convert cache to a positive number so that cached model is written
+            loader._convert_cache.max_size = 1.0
+        loader.load_model(model_config, submodel_type=SubModelType.Scheduler)
+    finally:
+        loader._convert_cache.max_size = cc_size
 
-        # temporarily rename the original safetensors file so that there is no naming conflict
-        original_name = model_config.name
-        model_config.name = f"{original_name}.DELETE"
-        changes = ModelRecordChanges(name=model_config.name)
-        store.update_model(key, changes=changes)
+    # Get the path of the converted model from the loader
+    cache_path = loader.convert_cache.cache_path(key)
+    assert cache_path.exists()
 
-        # install the diffusers
-        try:
-            new_key = installer.install_path(
-                convert_path,
-                config={
-                    "name": original_name,
-                    "description": model_config.description,
-                    "hash": model_config.hash,
-                    "source": model_config.source,
-                },
-            )
-        except Exception as e:
-            logger.error(str(e))
-            store.update_model(key, changes=ModelRecordChanges(name=original_name))
-            raise HTTPException(status_code=409, detail=str(e))
+    # temporarily rename the original safetensors file so that there is no naming conflict
+    original_name = model_config.name
+    model_config.name = f"{original_name}.DELETE"
+    changes = ModelRecordChanges(name=model_config.name)
+    store.update_model(key, changes=changes)
+
+    # install the diffusers
+    try:
+        new_key = installer.install_path(
+            cache_path,
+            config={
+                "name": original_name,
+                "description": model_config.description,
+                "hash": model_config.hash,
+                "source": model_config.source,
+            },
+        )
+    except DuplicateModelException as e:
+        logger.error(str(e))
+        raise HTTPException(status_code=409, detail=str(e))
 
     # Update the model image if the model had one
     try:
@@ -773,8 +791,8 @@ async def convert_model(
     # delete the original safetensors file
     installer.delete(key)
 
-    # delete the temporary directory
-    # shutil.rmtree(cache_path)
+    # delete the cached version
+    shutil.rmtree(cache_path)
 
     # return the config record for the new diffusers directory
     new_config = store.get_model(new_key)

invokeai/app/api/routers/session_queue.py

@@ -4,7 +4,6 @@ from fastapi import Body, Path, Query
 from fastapi.routing import APIRouter
 from pydantic import BaseModel
 
-from invokeai.app.api.dependencies import ApiDependencies
 from invokeai.app.services.session_processor.session_processor_common import SessionProcessorStatus
 from invokeai.app.services.session_queue.session_queue_common import (
     QUEUE_ITEM_STATUS,
@@ -20,6 +19,8 @@ from invokeai.app.services.session_queue.session_queue_common import (
 )
 from invokeai.app.services.shared.pagination import CursorPaginatedResults
 
+from ..dependencies import ApiDependencies
+
 session_queue_router = APIRouter(prefix="/v1/queue", tags=["queue"])
 
 

invokeai/app/api_app.py

@@ -20,9 +20,14 @@ from torch.backends.mps import is_available as is_mps_available
 # noinspection PyUnresolvedReferences
 import invokeai.backend.util.hotfixes  # noqa: F401 (monkeypatching on import)
 import invokeai.frontend.web as web_dir
-from invokeai.app.api.dependencies import ApiDependencies
 from invokeai.app.api.no_cache_staticfiles import NoCacheStaticFiles
-from invokeai.app.api.routers import (
+from invokeai.app.services.config.config_default import get_config
+from invokeai.app.util.custom_openapi import get_openapi_func
+from invokeai.backend.util.devices import TorchDevice
+
+from ..backend.util.logging import InvokeAILogger
+from .api.dependencies import ApiDependencies
+from .api.routers import (
     app_info,
     board_images,
     boards,
@@ -33,11 +38,7 @@ from invokeai.app.api.routers import (
     utilities,
     workflows,
 )
-from invokeai.app.api.sockets import SocketIO
-from invokeai.app.services.config.config_default import get_config
-from invokeai.app.util.custom_openapi import get_openapi_func
-from invokeai.backend.util.devices import TorchDevice
-from invokeai.backend.util.logging import InvokeAILogger
+from .api.sockets import SocketIO
 
 app_config = get_config()
 
@@ -161,7 +162,6 @@ def invoke_api() -> None:
         # Taken from https://waylonwalker.com/python-find-available-port/, thanks Waylon!
         # https://github.com/WaylonWalker
         with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
-            s.settimeout(1)
             if s.connect_ex(("localhost", port)) == 0:
                 return find_port(port=port + 1)
             else:

invokeai/app/invocations/baseinvocation.py

@@ -40,7 +40,7 @@ from invokeai.app.util.misc import uuid_string
 from invokeai.backend.util.logging import InvokeAILogger
 
 if TYPE_CHECKING:
-    from invokeai.app.services.invocation_services import InvocationServices
+    from ..services.invocation_services import InvocationServices
 
 logger = InvokeAILogger.get_logger()
 

invokeai/app/invocations/collections.py

@@ -4,12 +4,13 @@
 import numpy as np
 from pydantic import ValidationInfo, field_validator
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.fields import InputField
 from invokeai.app.invocations.primitives import IntegerCollectionOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.misc import SEED_MAX
 
+from .baseinvocation import BaseInvocation, invocation
+from .fields import InputField
+
 
 @invocation(
     "range", title="Integer Range", tags=["collection", "integer", "range"], category="collections", version="1.0.0"

invokeai/app/invocations/compel.py

@@ -5,7 +5,6 @@ from compel import Compel, ReturnedEmbeddingsType
 from compel.prompt_parser import Blend, Conjunction, CrossAttentionControlSubstitute, FlattenedPrompt, Fragment
 from transformers import CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
 from invokeai.app.invocations.fields import (
     ConditioningField,
     FieldDescriptions,
@@ -15,7 +14,6 @@ from invokeai.app.invocations.fields import (
     TensorField,
     UIComponent,
 )
-from invokeai.app.invocations.model import CLIPField
 from invokeai.app.invocations.primitives import ConditioningOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.ti_utils import generate_ti_list
@@ -28,6 +26,9 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
 )
 from invokeai.backend.util.devices import TorchDevice
 
+from .baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
+from .model import CLIPField
+
 # unconditioned: Optional[torch.Tensor]
 
 

invokeai/app/invocations/constants.py

@@ -1,5 +1,6 @@
 from typing import Literal
 
+from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP
 from invokeai.backend.util.devices import TorchDevice
 
 LATENT_SCALE_FACTOR = 8
@@ -10,6 +11,9 @@ factor is hard-coded to a literal '8' rather than using this constant.
 The ratio of image:latent dimensions is LATENT_SCALE_FACTOR:1, or 8:1.
 """
 
+SCHEDULER_NAME_VALUES = Literal[tuple(SCHEDULER_MAP.keys())]
+"""A literal type representing the valid scheduler names."""
+
 IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F"]
 """A literal type for PIL image modes supported by Invoke"""
 

invokeai/app/invocations/controlnet_image_processors.py

@@ -22,13 +22,6 @@ from controlnet_aux.util import HWC3, ade_palette
 from PIL import Image
 from pydantic import BaseModel, Field, field_validator, model_validator
 
-from invokeai.app.invocations.baseinvocation import (
-    BaseInvocation,
-    BaseInvocationOutput,
-    Classification,
-    invocation,
-    invocation_output,
-)
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
     ImageField,
@@ -52,6 +45,8 @@ from invokeai.backend.image_util.lineart_anime import LineartAnimeProcessor
 from invokeai.backend.image_util.util import np_to_pil, pil_to_np
 from invokeai.backend.util.devices import TorchDevice
 
+from .baseinvocation import BaseInvocation, BaseInvocationOutput, Classification, invocation, invocation_output
+
 
 class ControlField(BaseModel):
     image: ImageField = Field(description="The control image")

invokeai/app/invocations/cv.py

@@ -5,11 +5,13 @@ import cv2 as cv
 import numpy
 from PIL import Image, ImageOps
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.fields import ImageField, InputField, WithBoard, WithMetadata
+from invokeai.app.invocations.fields import ImageField
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 
+from .baseinvocation import BaseInvocation, invocation
+from .fields import InputField, WithBoard, WithMetadata
+
 
 @invocation("cv_inpaint", title="OpenCV Inpaint", tags=["opencv", "inpaint"], category="inpaint", version="1.3.1")
 class CvInpaintInvocation(BaseInvocation, WithMetadata, WithBoard):

invokeai/app/invocations/denoise_latents.py

@@ -17,7 +17,7 @@ from torchvision.transforms.functional import resize as tv_resize
 from transformers import CLIPVisionModelWithProjection
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
+from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR, SCHEDULER_NAME_VALUES
 from invokeai.app.invocations.controlnet_image_processors import ControlField
 from invokeai.app.invocations.fields import (
     ConditioningField,
@@ -54,7 +54,6 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     TextConditioningRegions,
 )
 from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP
-from invokeai.backend.stable_diffusion.schedulers.schedulers import SCHEDULER_NAME_VALUES
 from invokeai.backend.util.devices import TorchDevice
 from invokeai.backend.util.hotfixes import ControlNetModel
 from invokeai.backend.util.mask import to_standard_float_mask

invokeai/app/invocations/fields.py

@@ -160,7 +160,6 @@ class FieldDescriptions:
     fp32 = "Whether or not to use full float32 precision"
     precision = "Precision to use"
     tiled = "Processing using overlapping tiles (reduce memory consumption)"
-    vae_tile_size = "The tile size for VAE tiling in pixels (image space). If set to 0, the default tile size for the model will be used. Larger tile sizes generally produce better results at the cost of higher memory usage."
     detect_res = "Pixel resolution for detection"
     image_res = "Pixel resolution for output image"
     safe_mode = "Whether or not to use safe mode"

invokeai/app/invocations/image.py

@@ -6,7 +6,6 @@ import cv2
 import numpy
 from PIL import Image, ImageChops, ImageFilter, ImageOps
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
 from invokeai.app.invocations.constants import IMAGE_MODES
 from invokeai.app.invocations.fields import (
     ColorField,
@@ -22,6 +21,8 @@ from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.safety_checker import SafetyChecker
 
+from .baseinvocation import BaseInvocation, Classification, invocation
+
 
 @invocation("show_image", title="Show Image", tags=["image"], category="image", version="1.0.1")
 class ShowImageInvocation(BaseInvocation):

invokeai/app/invocations/image_to_latents.py

@@ -1,4 +1,3 @@
-from contextlib import nullcontext
 from functools import singledispatchmethod
 
 import einops
@@ -13,7 +12,7 @@ from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
 from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.constants import DEFAULT_PRECISION, LATENT_SCALE_FACTOR
+from invokeai.app.invocations.constants import DEFAULT_PRECISION
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
     ImageField,
@@ -25,7 +24,6 @@ from invokeai.app.invocations.primitives import LatentsOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.model_manager import LoadedModel
 from invokeai.backend.stable_diffusion.diffusers_pipeline import image_resized_to_grid_as_tensor
-from invokeai.backend.stable_diffusion.vae_tiling import patch_vae_tiling_params
 
 
 @invocation(
@@ -33,7 +31,7 @@ from invokeai.backend.stable_diffusion.vae_tiling import patch_vae_tiling_params
     title="Image to Latents",
     tags=["latents", "image", "vae", "i2l"],
     category="latents",
-    version="1.1.0",
+    version="1.0.2",
 )
 class ImageToLatentsInvocation(BaseInvocation):
     """Encodes an image into latents."""
@@ -46,17 +44,12 @@ class ImageToLatentsInvocation(BaseInvocation):
         input=Input.Connection,
     )
     tiled: bool = InputField(default=False, description=FieldDescriptions.tiled)
-    # NOTE: tile_size = 0 is a special value. We use this rather than `int | None`, because the workflow UI does not
-    # offer a way to directly set None values.
-    tile_size: int = InputField(default=0, multiple_of=8, description=FieldDescriptions.vae_tile_size)
     fp32: bool = InputField(default=DEFAULT_PRECISION == torch.float32, description=FieldDescriptions.fp32)
 
     @staticmethod
-    def vae_encode(
-        vae_info: LoadedModel, upcast: bool, tiled: bool, image_tensor: torch.Tensor, tile_size: int = 0
-    ) -> torch.Tensor:
+    def vae_encode(vae_info: LoadedModel, upcast: bool, tiled: bool, image_tensor: torch.Tensor) -> torch.Tensor:
         with vae_info as vae:
-            assert isinstance(vae, (AutoencoderKL, AutoencoderTiny))
+            assert isinstance(vae, torch.nn.Module)
             orig_dtype = vae.dtype
             if upcast:
                 vae.to(dtype=torch.float32)
@@ -88,18 +81,9 @@ class ImageToLatentsInvocation(BaseInvocation):
             else:
                 vae.disable_tiling()
 
-            tiling_context = nullcontext()
-            if tile_size > 0:
-                tiling_context = patch_vae_tiling_params(
-                    vae,
-                    tile_sample_min_size=tile_size,
-                    tile_latent_min_size=tile_size // LATENT_SCALE_FACTOR,
-                    tile_overlap_factor=0.25,
-                )
-
             # non_noised_latents_from_image
             image_tensor = image_tensor.to(device=vae.device, dtype=vae.dtype)
-            with torch.inference_mode(), tiling_context:
+            with torch.inference_mode():
                 latents = ImageToLatentsInvocation._encode_to_tensor(vae, image_tensor)
 
             latents = vae.config.scaling_factor * latents
@@ -117,9 +101,7 @@ class ImageToLatentsInvocation(BaseInvocation):
         if image_tensor.dim() == 3:
             image_tensor = einops.rearrange(image_tensor, "c h w -> 1 c h w")
 
-        latents = self.vae_encode(
-            vae_info=vae_info, upcast=self.fp32, tiled=self.tiled, image_tensor=image_tensor, tile_size=self.tile_size
-        )
+        latents = self.vae_encode(vae_info, self.fp32, self.tiled, image_tensor)
 
         latents = latents.to("cpu")
         name = context.tensors.save(tensor=latents)

invokeai/app/invocations/infill.py

@@ -3,9 +3,7 @@ from typing import Literal, get_args
 
 from PIL import Image
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.fields import ColorField, ImageField, InputField, WithBoard, WithMetadata
-from invokeai.app.invocations.image import PIL_RESAMPLING_MAP, PIL_RESAMPLING_MODES
+from invokeai.app.invocations.fields import ColorField, ImageField
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.misc import SEED_MAX
@@ -16,6 +14,10 @@ from invokeai.backend.image_util.infill_methods.patchmatch import PatchMatch, in
 from invokeai.backend.image_util.infill_methods.tile import infill_tile
 from invokeai.backend.util.logging import InvokeAILogger
 
+from .baseinvocation import BaseInvocation, invocation
+from .fields import InputField, WithBoard, WithMetadata
+from .image import PIL_RESAMPLING_MAP, PIL_RESAMPLING_MODES
+
 logger = InvokeAILogger.get_logger()
 
 

invokeai/app/invocations/latents_to_image.py

@@ -1,5 +1,3 @@
-from contextlib import nullcontext
-
 import torch
 from diffusers.image_processor import VaeImageProcessor
 from diffusers.models.attention_processor import (
@@ -10,9 +8,10 @@ from diffusers.models.attention_processor import (
 )
 from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
 from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny
+from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.constants import DEFAULT_PRECISION, LATENT_SCALE_FACTOR
+from invokeai.app.invocations.constants import DEFAULT_PRECISION
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
     Input,
@@ -25,7 +24,6 @@ from invokeai.app.invocations.model import VAEField
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.stable_diffusion import set_seamless
-from invokeai.backend.stable_diffusion.vae_tiling import patch_vae_tiling_params
 from invokeai.backend.util.devices import TorchDevice
 
 
@@ -34,7 +32,7 @@ from invokeai.backend.util.devices import TorchDevice
     title="Latents to Image",
     tags=["latents", "image", "vae", "l2i"],
     category="latents",
-    version="1.3.0",
+    version="1.2.2",
 )
 class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Generates an image from latents."""
@@ -48,9 +46,6 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
         input=Input.Connection,
     )
     tiled: bool = InputField(default=False, description=FieldDescriptions.tiled)
-    # NOTE: tile_size = 0 is a special value. We use this rather than `int | None`, because the workflow UI does not
-    # offer a way to directly set None values.
-    tile_size: int = InputField(default=0, multiple_of=8, description=FieldDescriptions.vae_tile_size)
     fp32: bool = InputField(default=DEFAULT_PRECISION == torch.float32, description=FieldDescriptions.fp32)
 
     @torch.no_grad()
@@ -58,9 +53,9 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
         latents = context.tensors.load(self.latents.latents_name)
 
         vae_info = context.models.load(self.vae.vae)
-        assert isinstance(vae_info.model, (AutoencoderKL, AutoencoderTiny))
+        assert isinstance(vae_info.model, (UNet2DConditionModel, AutoencoderKL, AutoencoderTiny))
         with set_seamless(vae_info.model, self.vae.seamless_axes), vae_info as vae:
-            assert isinstance(vae, (AutoencoderKL, AutoencoderTiny))
+            assert isinstance(vae, torch.nn.Module)
             latents = latents.to(vae.device)
             if self.fp32:
                 vae.to(dtype=torch.float32)
@@ -92,19 +87,10 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
             else:
                 vae.disable_tiling()
 
-            tiling_context = nullcontext()
-            if self.tile_size > 0:
-                tiling_context = patch_vae_tiling_params(
-                    vae,
-                    tile_sample_min_size=self.tile_size,
-                    tile_latent_min_size=self.tile_size // LATENT_SCALE_FACTOR,
-                    tile_overlap_factor=0.25,
-                )
-
             # clear memory as vae decode can request a lot
             TorchDevice.empty_cache()
 
-            with torch.inference_mode(), tiling_context:
+            with torch.inference_mode():
                 # copied from diffusers pipeline
                 latents = latents / vae.config.scaling_factor
                 image = vae.decode(latents, return_dict=False)[0]

invokeai/app/invocations/math.py

@@ -5,11 +5,12 @@ from typing import Literal
 import numpy as np
 from pydantic import ValidationInfo, field_validator
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
 from invokeai.app.invocations.fields import FieldDescriptions, InputField
 from invokeai.app.invocations.primitives import FloatOutput, IntegerOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 
+from .baseinvocation import BaseInvocation, invocation
+
 
 @invocation("add", title="Add Integers", tags=["math", "add"], category="math", version="1.0.1")
 class AddInvocation(BaseInvocation):

invokeai/app/invocations/metadata.py

@@ -14,7 +14,8 @@ from invokeai.app.invocations.fields import (
 from invokeai.app.invocations.model import ModelIdentifierField
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.controlnet_utils import CONTROLNET_MODE_VALUES, CONTROLNET_RESIZE_VALUES
-from invokeai.version.invokeai_version import __version__
+
+from ...version import __version__
 
 
 class MetadataItemField(BaseModel):

invokeai/app/invocations/model.py

@@ -3,17 +3,18 @@ from typing import List, Optional
 
 from pydantic import BaseModel, Field
 
-from invokeai.app.invocations.baseinvocation import (
+from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIType
+from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.app.shared.models import FreeUConfig
+from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelType, SubModelType
+
+from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
     Classification,
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIType
-from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.app.shared.models import FreeUConfig
-from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, ModelType, SubModelType
 
 
 class ModelIdentifierField(BaseModel):

invokeai/app/invocations/noise.py

@@ -4,12 +4,18 @@
 import torch
 from pydantic import field_validator
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
 from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
 from invokeai.app.invocations.fields import FieldDescriptions, InputField, LatentsField, OutputField
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.misc import SEED_MAX
-from invokeai.backend.util.devices import TorchDevice
+
+from ...backend.util.devices import TorchDevice
+from .baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    invocation,
+    invocation_output,
+)
 
 """
 Utilities

invokeai/app/invocations/param_easing.py

@@ -39,11 +39,12 @@ from easing_functions import (
 )
 from matplotlib.ticker import MaxNLocator
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.fields import InputField
 from invokeai.app.invocations.primitives import FloatCollectionOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 
+from .baseinvocation import BaseInvocation, invocation
+from .fields import InputField
+
 
 @invocation(
     "float_range",

invokeai/app/invocations/primitives.py

@@ -4,7 +4,6 @@ from typing import Optional
 
 import torch
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
 from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
 from invokeai.app.invocations.fields import (
     ColorField,
@@ -22,6 +21,13 @@ from invokeai.app.invocations.fields import (
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.shared.invocation_context import InvocationContext
 
+from .baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    invocation,
+    invocation_output,
+)
+
 """
 Primitives: Boolean, Integer, Float, String, Image, Latents, Conditioning, Color
 - primitive nodes

invokeai/app/invocations/prompt.py

@@ -5,11 +5,12 @@ import numpy as np
 from dynamicprompts.generators import CombinatorialPromptGenerator, RandomPromptGenerator
 from pydantic import field_validator
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.fields import InputField, UIComponent
 from invokeai.app.invocations.primitives import StringCollectionOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 
+from .baseinvocation import BaseInvocation, invocation
+from .fields import InputField, UIComponent
+
 
 @invocation(
     "dynamic_prompt",

invokeai/app/invocations/scheduler.py

@@ -1,4 +1,5 @@
 from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
+from invokeai.app.invocations.constants import SCHEDULER_NAME_VALUES
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
     InputField,
@@ -6,7 +7,6 @@ from invokeai.app.invocations.fields import (
     UIType,
 )
 from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.backend.stable_diffusion.schedulers.schedulers import SCHEDULER_NAME_VALUES
 
 
 @invocation_output("scheduler_output")

invokeai/app/invocations/sdxl.py

@@ -1,9 +1,15 @@
-from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
 from invokeai.app.invocations.fields import FieldDescriptions, InputField, OutputField, UIType
-from invokeai.app.invocations.model import CLIPField, ModelIdentifierField, UNetField, VAEField
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.model_manager import SubModelType
 
+from .baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    invocation,
+    invocation_output,
+)
+from .model import CLIPField, ModelIdentifierField, UNetField, VAEField
+
 
 @invocation_output("sdxl_model_loader_output")
 class SDXLModelLoaderOutput(BaseInvocationOutput):

invokeai/app/invocations/strings.py

@@ -2,11 +2,17 @@
 
 import re
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
-from invokeai.app.invocations.fields import InputField, OutputField, UIComponent
-from invokeai.app.invocations.primitives import StringOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 
+from .baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    invocation,
+    invocation_output,
+)
+from .fields import InputField, OutputField, UIComponent
+from .primitives import StringOutput
+
 
 @invocation_output("string_pos_neg_output")
 class StringPosNegOutput(BaseInvocationOutput):

invokeai/app/invocations/tiled_multi_diffusion_denoise_latents.py

@@ -8,7 +8,7 @@ from diffusers.schedulers.scheduling_utils import SchedulerMixin
 from pydantic import field_validator
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
-from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
+from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR, SCHEDULER_NAME_VALUES
 from invokeai.app.invocations.controlnet_image_processors import ControlField
 from invokeai.app.invocations.denoise_latents import DenoiseLatentsInvocation, get_scheduler
 from invokeai.app.invocations.fields import (
@@ -29,7 +29,6 @@ from invokeai.backend.stable_diffusion.multi_diffusion_pipeline import (
     MultiDiffusionPipeline,
     MultiDiffusionRegionConditioning,
 )
-from invokeai.backend.stable_diffusion.schedulers.schedulers import SCHEDULER_NAME_VALUES
 from invokeai.backend.tiles.tiles import (
     calc_tiles_min_overlap,
 )

invokeai/app/invocations/upscale.py

@@ -6,13 +6,15 @@ import numpy as np
 from PIL import Image
 from pydantic import ConfigDict
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.fields import ImageField, InputField, WithBoard, WithMetadata
+from invokeai.app.invocations.fields import ImageField
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.image_util.basicsr.rrdbnet_arch import RRDBNet
 from invokeai.backend.image_util.realesrgan.realesrgan import RealESRGAN
 
+from .baseinvocation import BaseInvocation, invocation
+from .fields import InputField, WithBoard, WithMetadata
+
 # TODO: Populate this from disk?
 # TODO: Use model manager to load?
 ESRGAN_MODELS = Literal[

invokeai/app/services/board_image_records/board_image_records_sqlite.py

@@ -2,11 +2,12 @@ import sqlite3
 import threading
 from typing import Optional, cast
 
-from invokeai.app.services.board_image_records.board_image_records_base import BoardImageRecordStorageBase
 from invokeai.app.services.image_records.image_records_common import ImageRecord, deserialize_image_record
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 
+from .board_image_records_base import BoardImageRecordStorageBase
+
 
 class SqliteBoardImageRecordStorage(BoardImageRecordStorageBase):
     _conn: sqlite3.Connection

invokeai/app/services/board_images/board_images_default.py

@@ -1,8 +1,9 @@
 from typing import Optional
 
-from invokeai.app.services.board_images.board_images_base import BoardImagesServiceABC
 from invokeai.app.services.invoker import Invoker
 
+from .board_images_base import BoardImagesServiceABC
+
 
 class BoardImagesService(BoardImagesServiceABC):
     __invoker: Invoker

invokeai/app/services/board_records/board_records_base.py

@@ -1,8 +1,9 @@
 from abc import ABC, abstractmethod
 
-from invokeai.app.services.board_records.board_records_common import BoardChanges, BoardRecord, UncategorizedImageCounts
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 
+from .board_records_common import BoardChanges, BoardRecord
+
 
 class BoardRecordStorageBase(ABC):
     """Low-level service responsible for interfacing with the board record store."""
@@ -39,17 +40,16 @@ class BoardRecordStorageBase(ABC):
 
     @abstractmethod
     def get_many(
-        self, offset: int = 0, limit: int = 10, include_archived: bool = False
+        self,
+        offset: int = 0,
+        limit: int = 10,
     ) -> OffsetPaginatedResults[BoardRecord]:
         """Gets many board records."""
         pass
 
     @abstractmethod
-    def get_all(self, include_archived: bool = False) -> list[BoardRecord]:
+    def get_all(
+        self,
+    ) -> list[BoardRecord]:
         """Gets all board records."""
         pass
-
-    @abstractmethod
-    def get_uncategorized_image_counts(self) -> UncategorizedImageCounts:
-        """Gets count of images and assets for uncategorized images (images with no board assocation)."""
-        pass

invokeai/app/services/board_records/board_records_common.py

@@ -1,5 +1,5 @@
 from datetime import datetime
-from typing import Any, Optional, Union
+from typing import Optional, Union
 
 from pydantic import BaseModel, Field
 
@@ -22,29 +22,19 @@ class BoardRecord(BaseModelExcludeNull):
     """The updated timestamp of the image."""
     cover_image_name: Optional[str] = Field(default=None, description="The name of the cover image of the board.")
     """The name of the cover image of the board."""
-    archived: bool = Field(description="Whether or not the board is archived.")
-    """Whether or not the board is archived."""
-    is_private: Optional[bool] = Field(default=None, description="Whether the board is private.")
-    """Whether the board is private."""
-    image_count: int = Field(description="The number of images in the board.")
-    asset_count: int = Field(description="The number of assets in the board.")
 
 
-def deserialize_board_record(board_dict: dict[str, Any]) -> BoardRecord:
+def deserialize_board_record(board_dict: dict) -> BoardRecord:
     """Deserializes a board record."""
 
     # Retrieve all the values, setting "reasonable" defaults if they are not present.
 
     board_id = board_dict.get("board_id", "unknown")
     board_name = board_dict.get("board_name", "unknown")
-    cover_image_name = board_dict.get("cover_image_name", None)
+    cover_image_name = board_dict.get("cover_image_name", "unknown")
     created_at = board_dict.get("created_at", get_iso_timestamp())
     updated_at = board_dict.get("updated_at", get_iso_timestamp())
     deleted_at = board_dict.get("deleted_at", get_iso_timestamp())
-    archived = board_dict.get("archived", False)
-    is_private = board_dict.get("is_private", False)
-    image_count = board_dict.get("image_count", 0)
-    asset_count = board_dict.get("asset_count", 0)
 
     return BoardRecord(
         board_id=board_id,
@@ -53,40 +43,30 @@ def deserialize_board_record(board_dict: dict[str, Any]) -> BoardRecord:
         created_at=created_at,
         updated_at=updated_at,
         deleted_at=deleted_at,
-        archived=archived,
-        is_private=is_private,
-        image_count=image_count,
-        asset_count=asset_count,
     )
 
 
 class BoardChanges(BaseModel, extra="forbid"):
     board_name: Optional[str] = Field(default=None, description="The board's new name.")
     cover_image_name: Optional[str] = Field(default=None, description="The name of the board's new cover image.")
-    archived: Optional[bool] = Field(default=None, description="Whether or not the board is archived")
 
 
 class BoardRecordNotFoundException(Exception):
     """Raised when an board record is not found."""
 
-    def __init__(self, message: str = "Board record not found"):
+    def __init__(self, message="Board record not found"):
         super().__init__(message)
 
 
 class BoardRecordSaveException(Exception):
     """Raised when an board record cannot be saved."""
 
-    def __init__(self, message: str = "Board record not saved"):
+    def __init__(self, message="Board record not saved"):
         super().__init__(message)
 
 
 class BoardRecordDeleteException(Exception):
     """Raised when an board record cannot be deleted."""
 
-    def __init__(self, message: str = "Board record not deleted"):
+    def __init__(self, message="Board record not deleted"):
         super().__init__(message)
-
-
-class UncategorizedImageCounts(BaseModel):
-    image_count: int = Field(description="The number of uncategorized images.")
-    asset_count: int = Field(description="The number of uncategorized assets.")

invokeai/app/services/board_records/board_records_sqlite.py

@@ -1,116 +1,20 @@
 import sqlite3
 import threading
-from dataclasses import dataclass
 from typing import Union, cast
 
-from invokeai.app.services.board_records.board_records_base import BoardRecordStorageBase
-from invokeai.app.services.board_records.board_records_common import (
+from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
+from invokeai.app.util.misc import uuid_string
+
+from .board_records_base import BoardRecordStorageBase
+from .board_records_common import (
     BoardChanges,
     BoardRecord,
     BoardRecordDeleteException,
     BoardRecordNotFoundException,
     BoardRecordSaveException,
-    UncategorizedImageCounts,
     deserialize_board_record,
 )
-from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
-from invokeai.app.util.misc import uuid_string
-
-BASE_BOARD_RECORD_QUERY = """
-    -- This query retrieves board records, joining with the board_images and images tables to get image counts and cover image names.
-    -- It is not a complete query, as it is missing a GROUP BY or WHERE clause (and is unterminated).
-    SELECT b.board_id,
-        b.board_name,
-        b.created_at,
-        b.updated_at,
-        b.archived,
-        -- Count the number of images in the board, alias image_count
-        COUNT(
-            CASE
-                WHEN i.image_category in ('general') -- "Images" are images in the 'general' category
-                AND i.is_intermediate = 0 THEN 1 -- Intermediates are not counted
-            END
-        ) AS image_count,
-        -- Count the number of assets in the board, alias asset_count
-        COUNT(
-            CASE
-                WHEN i.image_category in ('control', 'mask', 'user', 'other') -- "Assets" are images in any of the other categories ('control', 'mask', 'user', 'other')
-                AND i.is_intermediate = 0 THEN 1 -- Intermediates are not counted
-            END
-        ) AS asset_count,
-        -- Get the name of the the most recent image in the board, alias cover_image_name
-        (
-            SELECT bi.image_name
-            FROM board_images bi
-                JOIN images i ON bi.image_name = i.image_name
-            WHERE bi.board_id = b.board_id
-                AND i.is_intermediate = 0 -- Intermediates cannot be cover images
-            ORDER BY i.created_at DESC -- Sort by created_at to get the most recent image
-            LIMIT 1
-        ) AS cover_image_name
-    FROM boards b
-        LEFT JOIN board_images bi ON b.board_id = bi.board_id
-        LEFT JOIN images i ON bi.image_name = i.image_name
-    """
-
-
-@dataclass
-class PaginatedBoardRecordsQueries:
-    main_query: str
-    total_count_query: str
-
-
-def get_paginated_list_board_records_queries(include_archived: bool) -> PaginatedBoardRecordsQueries:
-    """Gets a query to retrieve a paginated list of board records."""
-
-    archived_condition = "WHERE b.archived = 0" if not include_archived else ""
-
-    # The GROUP BY must be added _after_ the WHERE clause!
-    main_query = f"""
-        {BASE_BOARD_RECORD_QUERY}
-        {archived_condition}
-        GROUP BY b.board_id,
-            b.board_name,
-            b.created_at,
-            b.updated_at
-        ORDER BY b.created_at DESC
-        LIMIT ? OFFSET ?;
-        """
-
-    total_count_query = f"""
-        SELECT COUNT(*)
-        FROM boards b
-        {archived_condition};
-        """
-
-    return PaginatedBoardRecordsQueries(main_query=main_query, total_count_query=total_count_query)
-
-
-def get_list_all_board_records_query(include_archived: bool) -> str:
-    """Gets a query to retrieve all board records."""
-
-    archived_condition = "WHERE b.archived = 0" if not include_archived else ""
-
-    # The GROUP BY must be added _after_ the WHERE clause!
-    return f"""
-        {BASE_BOARD_RECORD_QUERY}
-        {archived_condition}
-        GROUP BY b.board_id,
-            b.board_name,
-            b.created_at,
-            b.updated_at
-        ORDER BY b.created_at DESC;
-        """
-
-
-def get_board_record_query() -> str:
-    """Gets a query to retrieve a board record."""
-
-    return f"""
-        {BASE_BOARD_RECORD_QUERY}
-        WHERE b.board_id = ?;
-        """
 
 
 class SqliteBoardRecordStorage(BoardRecordStorageBase):
@@ -173,7 +77,11 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
         try:
             self._lock.acquire()
             self._cursor.execute(
-                get_board_record_query(),
+                """--sql
+                SELECT *
+                FROM boards
+                WHERE board_id = ?;
+                """,
                 (board_id,),
             )
 
@@ -185,7 +93,7 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
             self._lock.release()
         if result is None:
             raise BoardRecordNotFoundException
-        return deserialize_board_record(dict(result))
+        return BoardRecord(**dict(result))
 
     def update(
         self,
@@ -217,17 +125,6 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
                     (changes.cover_image_name, board_id),
                 )
 
-            # Change the archived status of a board
-            if changes.archived is not None:
-                self._cursor.execute(
-                    """--sql
-                    UPDATE boards
-                    SET archived = ?
-                    WHERE board_id = ?;
-                    """,
-                    (changes.archived, board_id),
-                )
-
             self._conn.commit()
         except sqlite3.Error as e:
             self._conn.rollback()
@@ -237,22 +134,36 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
         return self.get(board_id)
 
     def get_many(
-        self, offset: int = 0, limit: int = 10, include_archived: bool = False
+        self,
+        offset: int = 0,
+        limit: int = 10,
     ) -> OffsetPaginatedResults[BoardRecord]:
         try:
             self._lock.acquire()
 
-            queries = get_paginated_list_board_records_queries(include_archived=include_archived)
-
+            # Get all the boards
             self._cursor.execute(
-                queries.main_query,
+                """--sql
+                SELECT *
+                FROM boards
+                ORDER BY created_at DESC
+                LIMIT ? OFFSET ?;
+                """,
                 (limit, offset),
             )
 
             result = cast(list[sqlite3.Row], self._cursor.fetchall())
             boards = [deserialize_board_record(dict(r)) for r in result]
 
-            self._cursor.execute(queries.total_count_query)
+            # Get the total number of boards
+            self._cursor.execute(
+                """--sql
+                SELECT COUNT(*)
+                FROM boards
+                WHERE 1=1;
+                """
+            )
+
             count = cast(int, self._cursor.fetchone()[0])
 
             return OffsetPaginatedResults[BoardRecord](items=boards, offset=offset, limit=limit, total=count)
@@ -263,12 +174,24 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
         finally:
             self._lock.release()
 
-    def get_all(self, include_archived: bool = False) -> list[BoardRecord]:
+    def get_all(
+        self,
+    ) -> list[BoardRecord]:
         try:
             self._lock.acquire()
-            self._cursor.execute(get_list_all_board_records_query(include_archived=include_archived))
+
+            # Get all the boards
+            self._cursor.execute(
+                """--sql
+                SELECT *
+                FROM boards
+                ORDER BY created_at DESC
+                """
+            )
+
             result = cast(list[sqlite3.Row], self._cursor.fetchall())
             boards = [deserialize_board_record(dict(r)) for r in result]
+
             return boards
 
         except sqlite3.Error as e:
@@ -276,28 +199,3 @@ class SqliteBoardRecordStorage(BoardRecordStorageBase):
             raise e
         finally:
             self._lock.release()
-
-    def get_uncategorized_image_counts(self) -> UncategorizedImageCounts:
-        try:
-            self._lock.acquire()
-            query = """
-                -- Get the count of uncategorized images and assets.
-                SELECT
-                    CASE
-                        WHEN i.image_category = 'general' THEN 'image_count' -- "Images" are images in the 'general' category
-                        ELSE 'asset_count' -- "Assets" are images in any of the other categories ('control', 'mask', 'user', 'other')
-                    END AS category_type,
-                    COUNT(*) AS unassigned_count
-                FROM images i
-                LEFT JOIN board_images bi ON i.image_name = bi.image_name
-                WHERE bi.board_id IS NULL -- Uncategorized images have no board association
-                AND i.is_intermediate = 0 -- Omit intermediates from the counts
-                GROUP BY category_type; -- Group by category_type alias, as derived from the image_category column earlier
-                """
-            self._cursor.execute(query)
-            results = self._cursor.fetchall()
-            image_count = dict(results)["image_count"]
-            asset_count = dict(results)["asset_count"]
-            return UncategorizedImageCounts(image_count=image_count, asset_count=asset_count)
-        finally:
-            self._lock.release()

invokeai/app/services/boards/boards_base.py

@@ -1,9 +1,10 @@
 from abc import ABC, abstractmethod
 
 from invokeai.app.services.board_records.board_records_common import BoardChanges
-from invokeai.app.services.boards.boards_common import BoardDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 
+from .boards_common import BoardDTO
+
 
 class BoardServiceABC(ABC):
     """High-level service for board management."""
@@ -43,12 +44,16 @@ class BoardServiceABC(ABC):
 
     @abstractmethod
     def get_many(
-        self, offset: int = 0, limit: int = 10, include_archived: bool = False
+        self,
+        offset: int = 0,
+        limit: int = 10,
     ) -> OffsetPaginatedResults[BoardDTO]:
         """Gets many boards."""
         pass
 
     @abstractmethod
-    def get_all(self, include_archived: bool = False) -> list[BoardDTO]:
+    def get_all(
+        self,
+    ) -> list[BoardDTO]:
         """Gets all boards."""
         pass

invokeai/app/services/boards/boards_common.py

@@ -1,8 +1,23 @@
-from invokeai.app.services.board_records.board_records_common import BoardRecord
+from typing import Optional
+
+from pydantic import Field
+
+from ..board_records.board_records_common import BoardRecord
 
 
-# TODO(psyche): BoardDTO is now identical to BoardRecord. We should consider removing it.
 class BoardDTO(BoardRecord):
-    """Deserialized board record."""
+    """Deserialized board record with cover image URL and image count."""
 
-    pass
+    cover_image_name: Optional[str] = Field(description="The name of the board's cover image.")
+    """The URL of the thumbnail of the most recent image in the board."""
+    image_count: int = Field(description="The number of images in the board.")
+    """The number of images in the board."""
+
+
+def board_record_to_dto(board_record: BoardRecord, cover_image_name: Optional[str], image_count: int) -> BoardDTO:
+    """Converts a board record to a board DTO."""
+    return BoardDTO(
+        **board_record.model_dump(exclude={"cover_image_name"}),
+        cover_image_name=cover_image_name,
+        image_count=image_count,
+    )

invokeai/app/services/boards/boards_default.py

@@ -1,9 +1,11 @@
 from invokeai.app.services.board_records.board_records_common import BoardChanges
-from invokeai.app.services.boards.boards_base import BoardServiceABC
 from invokeai.app.services.boards.boards_common import BoardDTO
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
 
+from .boards_base import BoardServiceABC
+from .boards_common import board_record_to_dto
+
 
 class BoardService(BoardServiceABC):
     __invoker: Invoker
@@ -16,11 +18,17 @@ class BoardService(BoardServiceABC):
         board_name: str,
     ) -> BoardDTO:
         board_record = self.__invoker.services.board_records.save(board_name)
-        return BoardDTO.model_validate(board_record.model_dump())
+        return board_record_to_dto(board_record, None, 0)
 
     def get_dto(self, board_id: str) -> BoardDTO:
         board_record = self.__invoker.services.board_records.get(board_id)
-        return BoardDTO.model_validate(board_record.model_dump())
+        cover_image = self.__invoker.services.image_records.get_most_recent_image_for_board(board_record.board_id)
+        if cover_image:
+            cover_image_name = cover_image.image_name
+        else:
+            cover_image_name = None
+        image_count = self.__invoker.services.board_image_records.get_image_count_for_board(board_id)
+        return board_record_to_dto(board_record, cover_image_name, image_count)
 
     def update(
         self,
@@ -28,19 +36,44 @@ class BoardService(BoardServiceABC):
         changes: BoardChanges,
     ) -> BoardDTO:
         board_record = self.__invoker.services.board_records.update(board_id, changes)
-        return BoardDTO.model_validate(board_record.model_dump())
+        cover_image = self.__invoker.services.image_records.get_most_recent_image_for_board(board_record.board_id)
+        if cover_image:
+            cover_image_name = cover_image.image_name
+        else:
+            cover_image_name = None
+
+        image_count = self.__invoker.services.board_image_records.get_image_count_for_board(board_id)
+        return board_record_to_dto(board_record, cover_image_name, image_count)
 
     def delete(self, board_id: str) -> None:
         self.__invoker.services.board_records.delete(board_id)
 
-    def get_many(
-        self, offset: int = 0, limit: int = 10, include_archived: bool = False
-    ) -> OffsetPaginatedResults[BoardDTO]:
-        board_records = self.__invoker.services.board_records.get_many(offset, limit, include_archived)
-        board_dtos = [BoardDTO.model_validate(r.model_dump()) for r in board_records.items]
+    def get_many(self, offset: int = 0, limit: int = 10) -> OffsetPaginatedResults[BoardDTO]:
+        board_records = self.__invoker.services.board_records.get_many(offset, limit)
+        board_dtos = []
+        for r in board_records.items:
+            cover_image = self.__invoker.services.image_records.get_most_recent_image_for_board(r.board_id)
+            if cover_image:
+                cover_image_name = cover_image.image_name
+            else:
+                cover_image_name = None
+
+            image_count = self.__invoker.services.board_image_records.get_image_count_for_board(r.board_id)
+            board_dtos.append(board_record_to_dto(r, cover_image_name, image_count))
+
         return OffsetPaginatedResults[BoardDTO](items=board_dtos, offset=offset, limit=limit, total=len(board_dtos))
 
-    def get_all(self, include_archived: bool = False) -> list[BoardDTO]:
-        board_records = self.__invoker.services.board_records.get_all(include_archived)
-        board_dtos = [BoardDTO.model_validate(r.model_dump()) for r in board_records]
+    def get_all(self) -> list[BoardDTO]:
+        board_records = self.__invoker.services.board_records.get_all()
+        board_dtos = []
+        for r in board_records:
+            cover_image = self.__invoker.services.image_records.get_most_recent_image_for_board(r.board_id)
+            if cover_image:
+                cover_image_name = cover_image.image_name
+            else:
+                cover_image_name = None
+
+            image_count = self.__invoker.services.board_image_records.get_image_count_for_board(r.board_id)
+            board_dtos.append(board_record_to_dto(r, cover_image_name, image_count))
+
         return board_dtos

invokeai/app/services/bulk_download/bulk_download_default.py

@@ -4,7 +4,6 @@ from typing import Optional, Union
 from zipfile import ZipFile
 
 from invokeai.app.services.board_records.board_records_common import BoardRecordNotFoundException
-from invokeai.app.services.bulk_download.bulk_download_base import BulkDownloadBase
 from invokeai.app.services.bulk_download.bulk_download_common import (
     DEFAULT_BULK_DOWNLOAD_ID,
     BulkDownloadException,
@@ -16,6 +15,8 @@ from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.util.misc import uuid_string
 
+from .bulk_download_base import BulkDownloadBase
+
 
 class BulkDownloadService(BulkDownloadBase):
     def start(self, invoker: Invoker) -> None:

invokeai/app/services/config/__init__.py

@@ -1,6 +1,7 @@
 """Init file for InvokeAI configure package."""
 
 from invokeai.app.services.config.config_common import PagingArgumentParser
-from invokeai.app.services.config.config_default import InvokeAIAppConfig, get_config
+
+from .config_default import InvokeAIAppConfig, get_config
 
 __all__ = ["InvokeAIAppConfig", "get_config", "PagingArgumentParser"]

invokeai/app/services/config/config_default.py

@@ -3,7 +3,6 @@
 
 from __future__ import annotations
 
-import copy
 import locale
 import os
 import re
@@ -26,13 +25,14 @@ DB_FILE = Path("invokeai.db")
 LEGACY_INIT_FILE = Path("invokeai.init")
 DEFAULT_RAM_CACHE = 10.0
 DEFAULT_VRAM_CACHE = 0.25
+DEFAULT_CONVERT_CACHE = 20.0
 DEVICE = Literal["auto", "cpu", "cuda", "cuda:1", "mps"]
 PRECISION = Literal["auto", "float16", "bfloat16", "float32"]
 ATTENTION_TYPE = Literal["auto", "normal", "xformers", "sliced", "torch-sdp"]
 ATTENTION_SLICE_SIZE = Literal["auto", "balanced", "max", 1, 2, 3, 4, 5, 6, 7, 8]
 LOG_FORMAT = Literal["plain", "color", "syslog", "legacy"]
 LOG_LEVEL = Literal["debug", "info", "warning", "error", "critical"]
-CONFIG_SCHEMA_VERSION = "4.0.2"
+CONFIG_SCHEMA_VERSION = "4.0.1"
 
 
 def get_default_ram_cache_size() -> float:
@@ -85,7 +85,7 @@ class InvokeAIAppConfig(BaseSettings):
         log_tokenization: Enable logging of parsed prompt tokens.
         patchmatch: Enable patchmatch inpaint code.
         models_dir: Path to the models directory.
-        convert_cache_dir: Path to the converted models cache directory (DEPRECATED, but do not delete because it is needed for migration from previous versions).
+        convert_cache_dir: Path to the converted models cache directory. When loading a non-diffusers model, it will be converted and store on disk at this location.
         download_cache_dir: Path to the directory that contains dynamically downloaded models.
         legacy_conf_dir: Path to directory of legacy checkpoint config files.
         db_dir: Path to InvokeAI databases directory.
@@ -102,6 +102,7 @@ class InvokeAIAppConfig(BaseSettings):
         profiles_dir: Path to profiles output directory.
         ram: Maximum memory amount used by memory model cache for rapid switching (GB).
         vram: Amount of VRAM reserved for model storage (GB).
+        convert_cache: Maximum size of on-disk converted models cache (GB).
         lazy_offload: Keep models in VRAM until their space is needed.
         log_memory_usage: If True, a memory snapshot will be captured before and after every model cache operation, and the result will be logged (at debug level). There is a time cost to capturing the memory snapshots, so it is recommended to only enable this feature if you are actively inspecting the model cache's behaviour.
         device: Preferred execution device. `auto` will choose the device depending on the hardware platform and the installed torch capabilities.<br>Valid values: `auto`, `cpu`, `cuda`, `cuda:1`, `mps`
@@ -147,7 +148,7 @@ class InvokeAIAppConfig(BaseSettings):
 
     # PATHS
     models_dir:                    Path = Field(default=Path("models"),     description="Path to the models directory.")
-    convert_cache_dir:             Path = Field(default=Path("models/.convert_cache"), description="Path to the converted models cache directory (DEPRECATED, but do not delete because it is needed for migration from previous versions).")
+    convert_cache_dir:             Path = Field(default=Path("models/.convert_cache"), description="Path to the converted models cache directory. When loading a non-diffusers model, it will be converted and store on disk at this location.")
     download_cache_dir:            Path = Field(default=Path("models/.download_cache"), description="Path to the directory that contains dynamically downloaded models.")
     legacy_conf_dir:               Path = Field(default=Path("configs"), description="Path to directory of legacy checkpoint config files.")
     db_dir:                        Path = Field(default=Path("databases"),  description="Path to InvokeAI databases directory.")
@@ -169,8 +170,9 @@ class InvokeAIAppConfig(BaseSettings):
     profiles_dir:                  Path = Field(default=Path("profiles"),   description="Path to profiles output directory.")
 
     # CACHE
-    ram:                           float = Field(default_factory=get_default_ram_cache_size, gt=0, description="Maximum memory amount used by memory model cache for rapid switching (GB).")
-    vram:                          float = Field(default=DEFAULT_VRAM_CACHE, ge=0, description="Amount of VRAM reserved for model storage (GB).")
+    ram:                          float = Field(default_factory=get_default_ram_cache_size, gt=0, description="Maximum memory amount used by memory model cache for rapid switching (GB).")
+    vram:                         float = Field(default=DEFAULT_VRAM_CACHE, ge=0, description="Amount of VRAM reserved for model storage (GB).")
+    convert_cache:                float = Field(default=DEFAULT_CONVERT_CACHE, ge=0, description="Maximum size of on-disk converted models cache (GB).")
     lazy_offload:                  bool = Field(default=True,               description="Keep models in VRAM until their space is needed.")
     log_memory_usage:              bool = Field(default=False,              description="If True, a memory snapshot will be captured before and after every model cache operation, and the result will be logged (at debug level). There is a time cost to capturing the memory snapshots, so it is recommended to only enable this feature if you are actively inspecting the model cache's behaviour.")
 
@@ -355,14 +357,14 @@ class DefaultInvokeAIAppConfig(InvokeAIAppConfig):
         return (init_settings,)
 
 
-def migrate_v3_config_dict(config_dict: dict[str, Any]) -> dict[str, Any]:
-    """Migrate a v3 config dictionary to a v4.0.0.
+def migrate_v3_config_dict(config_dict: dict[str, Any]) -> InvokeAIAppConfig:
+    """Migrate a v3 config dictionary to a current config object.
 
     Args:
         config_dict: A dictionary of settings from a v3 config file.
 
     Returns:
-        An `InvokeAIAppConfig` config dict.
+        An instance of `InvokeAIAppConfig` with the migrated settings.
 
     """
     parsed_config_dict: dict[str, Any] = {}
@@ -396,41 +398,32 @@ def migrate_v3_config_dict(config_dict: dict[str, Any]) -> dict[str, Any]:
             elif k in InvokeAIAppConfig.model_fields:
                 # skip unknown fields
                 parsed_config_dict[k] = v
-    parsed_config_dict["schema_version"] = "4.0.0"
-    return parsed_config_dict
+    # When migrating the config file, we should not include currently-set environment variables.
+    config = DefaultInvokeAIAppConfig.model_validate(parsed_config_dict)
+
+    return config
 
 
-def migrate_v4_0_0_to_4_0_1_config_dict(config_dict: dict[str, Any]) -> dict[str, Any]:
-    """Migrate v4.0.0 config dictionary to a v4.0.1 config dictionary
+def migrate_v4_0_0_config_dict(config_dict: dict[str, Any]) -> InvokeAIAppConfig:
+    """Migrate v4.0.0 config dictionary to a current config object.
 
     Args:
         config_dict: A dictionary of settings from a v4.0.0 config file.
 
     Returns:
-        A config dict with the settings migrated to v4.0.1.
+        An instance of `InvokeAIAppConfig` with the migrated settings.
     """
-    parsed_config_dict: dict[str, Any] = copy.deepcopy(config_dict)
-    # precision "autocast" was replaced by "auto" in v4.0.1
-    if parsed_config_dict.get("precision") == "autocast":
-        parsed_config_dict["precision"] = "auto"
-    parsed_config_dict["schema_version"] = "4.0.1"
-    return parsed_config_dict
-
-
-def migrate_v4_0_1_to_4_0_2_config_dict(config_dict: dict[str, Any]) -> dict[str, Any]:
-    """Migrate v4.0.1 config dictionary to a v4.0.2 config dictionary.
-
-    Args:
-        config_dict: A dictionary of settings from a v4.0.1 config file.
-
-    Returns:
-        An config dict with the settings migrated to v4.0.2.
-    """
-    parsed_config_dict: dict[str, Any] = copy.deepcopy(config_dict)
-    # convert_cache was removed in 4.0.2
-    parsed_config_dict.pop("convert_cache", None)
-    parsed_config_dict["schema_version"] = "4.0.2"
-    return parsed_config_dict
+    parsed_config_dict: dict[str, Any] = {}
+    for k, v in config_dict.items():
+        # autocast was removed from precision in v4.0.1
+        if k == "precision" and v == "autocast":
+            parsed_config_dict["precision"] = "auto"
+        else:
+            parsed_config_dict[k] = v
+        if k == "schema_version":
+            parsed_config_dict[k] = CONFIG_SCHEMA_VERSION
+    config = DefaultInvokeAIAppConfig.model_validate(parsed_config_dict)
+    return config
 
 
 def load_and_migrate_config(config_path: Path) -> InvokeAIAppConfig:
@@ -444,31 +437,27 @@ def load_and_migrate_config(config_path: Path) -> InvokeAIAppConfig:
     """
     assert config_path.suffix == ".yaml"
     with open(config_path, "rt", encoding=locale.getpreferredencoding()) as file:
-        loaded_config_dict: dict[str, Any] = yaml.safe_load(file)
+        loaded_config_dict = yaml.safe_load(file)
 
     assert isinstance(loaded_config_dict, dict)
 
-    migrated = False
     if "InvokeAI" in loaded_config_dict:
-        migrated = True
-        loaded_config_dict = migrate_v3_config_dict(loaded_config_dict)  # pyright: ignore [reportUnknownArgumentType]
-    if loaded_config_dict["schema_version"] == "4.0.0":
-        migrated = True
-        loaded_config_dict = migrate_v4_0_0_to_4_0_1_config_dict(loaded_config_dict)
-    if loaded_config_dict["schema_version"] == "4.0.1":
-        migrated = True
-        loaded_config_dict = migrate_v4_0_1_to_4_0_2_config_dict(loaded_config_dict)
-
-    if migrated:
+        # This is a v3 config file, attempt to migrate it
         shutil.copy(config_path, config_path.with_suffix(".yaml.bak"))
         try:
-            # load and write without environment variables
-            migrated_config = DefaultInvokeAIAppConfig.model_validate(loaded_config_dict)
-            migrated_config.write_file(config_path)
+            # loaded_config_dict could be the wrong shape, but we will catch all exceptions below
+            migrated_config = migrate_v3_config_dict(loaded_config_dict)  # pyright: ignore [reportUnknownArgumentType]
         except Exception as e:
             shutil.copy(config_path.with_suffix(".yaml.bak"), config_path)
             raise RuntimeError(f"Failed to load and migrate v3 config file {config_path}: {e}") from e
+        migrated_config.write_file(config_path)
+        return migrated_config
 
+    if loaded_config_dict["schema_version"] == "4.0.0":
+        loaded_config_dict = migrate_v4_0_0_config_dict(loaded_config_dict)
+        loaded_config_dict.write_file(config_path)
+
+    # Attempt to load as a v4 config file
     try:
         # Meta is not included in the model fields, so we need to validate it separately
         config = InvokeAIAppConfig.model_validate(loaded_config_dict)

invokeai/app/services/download/__init__.py

@@ -1,13 +1,13 @@
 """Init file for download queue."""
 
-from invokeai.app.services.download.download_base import (
+from .download_base import (
     DownloadJob,
     DownloadJobStatus,
     DownloadQueueServiceBase,
     MultiFileDownloadJob,
     UnknownJobIDException,
 )
-from invokeai.app.services.download.download_default import DownloadQueueService, TqdmProgress
+from .download_default import DownloadQueueService, TqdmProgress
 
 __all__ = [
     "DownloadJob",

invokeai/app/services/download/download_default.py

@@ -16,7 +16,12 @@ from requests import HTTPError
 from tqdm import tqdm
 
 from invokeai.app.services.config import InvokeAIAppConfig, get_config
-from invokeai.app.services.download.download_base import (
+from invokeai.app.services.events.events_base import EventServiceBase
+from invokeai.app.util.misc import get_iso_timestamp
+from invokeai.backend.model_manager.metadata import RemoteModelFile
+from invokeai.backend.util.logging import InvokeAILogger
+
+from .download_base import (
     DownloadEventHandler,
     DownloadExceptionHandler,
     DownloadJob,
@@ -28,10 +33,6 @@ from invokeai.app.services.download.download_base import (
     ServiceInactiveException,
     UnknownJobIDException,
 )
-from invokeai.app.services.events.events_base import EventServiceBase
-from invokeai.app.util.misc import get_iso_timestamp
-from invokeai.backend.model_manager.metadata import RemoteModelFile
-from invokeai.backend.util.logging import InvokeAILogger
 
 # Maximum number of bytes to download during each call to requests.iter_content()
 DOWNLOAD_CHUNK_SIZE = 100000
@@ -184,7 +185,7 @@ class DownloadQueueService(DownloadQueueServiceBase):
             job = DownloadJob(
                 source=url,
                 dest=path,
-                access_token=access_token or self._lookup_access_token(url),
+                access_token=access_token,
             )
             mfdj.download_parts.add(job)
             self._download_part2parent[job.source] = mfdj

invokeai/app/services/events/events_fastapievents.py

@@ -6,11 +6,12 @@ from queue import Empty, Queue
 
 from fastapi_events.dispatcher import dispatch
 
-from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.events.events_common import (
     EventBase,
 )
 
+from .events_base import EventServiceBase
+
 
 class FastAPIEventService(EventServiceBase):
     def __init__(self, event_handler_id: int) -> None:

invokeai/app/services/image_files/image_files_disk.py

@@ -7,15 +7,12 @@ from PIL import Image, PngImagePlugin
 from PIL.Image import Image as PILImageType
 from send2trash import send2trash
 
-from invokeai.app.services.image_files.image_files_base import ImageFileStorageBase
-from invokeai.app.services.image_files.image_files_common import (
-    ImageFileDeleteException,
-    ImageFileNotFoundException,
-    ImageFileSaveException,
-)
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.util.thumbnails import get_thumbnail_name, make_thumbnail
 
+from .image_files_base import ImageFileStorageBase
+from .image_files_common import ImageFileDeleteException, ImageFileNotFoundException, ImageFileSaveException
+
 
 class DiskImageFileStorage(ImageFileStorageBase):
     """Stores images on disk"""

invokeai/app/services/image_records/image_records_base.py

@@ -3,14 +3,9 @@ from datetime import datetime
 from typing import Optional
 
 from invokeai.app.invocations.fields import MetadataField
-from invokeai.app.services.image_records.image_records_common import (
-    ImageCategory,
-    ImageRecord,
-    ImageRecordChanges,
-    ResourceOrigin,
-)
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.shared.sqlite.sqlite_common import SQLiteDirection
+
+from .image_records_common import ImageCategory, ImageRecord, ImageRecordChanges, ResourceOrigin
 
 
 class ImageRecordStorageBase(ABC):
@@ -42,13 +37,10 @@ class ImageRecordStorageBase(ABC):
         self,
         offset: int = 0,
         limit: int = 10,
-        starred_first: bool = True,
-        order_dir: SQLiteDirection = SQLiteDirection.Descending,
         image_origin: Optional[ResourceOrigin] = None,
         categories: Optional[list[ImageCategory]] = None,
         is_intermediate: Optional[bool] = None,
         board_id: Optional[str] = None,
-        search_term: Optional[str] = None,
     ) -> OffsetPaginatedResults[ImageRecord]:
         """Gets a page of image records."""
         pass

invokeai/app/services/image_records/image_records_sqlite.py

@@ -4,8 +4,11 @@ from datetime import datetime
 from typing import Optional, Union, cast
 
 from invokeai.app.invocations.fields import MetadataField, MetadataFieldValidator
-from invokeai.app.services.image_records.image_records_base import ImageRecordStorageBase
-from invokeai.app.services.image_records.image_records_common import (
+from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
+
+from .image_records_base import ImageRecordStorageBase
+from .image_records_common import (
     IMAGE_DTO_COLS,
     ImageCategory,
     ImageRecord,
@@ -16,9 +19,6 @@ from invokeai.app.services.image_records.image_records_common import (
     ResourceOrigin,
     deserialize_image_record,
 )
-from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.shared.sqlite.sqlite_common import SQLiteDirection
-from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 
 
 class SqliteImageRecordStorage(ImageRecordStorageBase):
@@ -144,13 +144,10 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
         self,
         offset: int = 0,
         limit: int = 10,
-        starred_first: bool = True,
-        order_dir: SQLiteDirection = SQLiteDirection.Descending,
         image_origin: Optional[ResourceOrigin] = None,
         categories: Optional[list[ImageCategory]] = None,
         is_intermediate: Optional[bool] = None,
         board_id: Optional[str] = None,
-        search_term: Optional[str] = None,
     ) -> OffsetPaginatedResults[ImageRecord]:
         try:
             self._lock.acquire()
@@ -211,21 +208,9 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
                 """
                 query_params.append(board_id)
 
-            # Search term condition
-            if search_term:
-                query_conditions += """--sql
-                AND images.metadata LIKE ?
-                """
-                query_params.append(f"%{search_term.lower()}%")
-
-            if starred_first:
-                query_pagination = f"""--sql
-                ORDER BY images.starred DESC, images.created_at {order_dir.value} LIMIT ? OFFSET ?
-                """
-            else:
-                query_pagination = f"""--sql
-                ORDER BY images.created_at {order_dir.value} LIMIT ? OFFSET ?
-                """
+            query_pagination = """--sql
+            ORDER BY images.starred DESC, images.created_at DESC LIMIT ? OFFSET ?
+            """
 
             # Final images query with pagination
             images_query += query_conditions + query_pagination + ";"

invokeai/app/services/images/images_base.py

@@ -12,7 +12,6 @@ from invokeai.app.services.image_records.image_records_common import (
 )
 from invokeai.app.services.images.images_common import ImageDTO
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.shared.sqlite.sqlite_common import SQLiteDirection
 
 
 class ImageServiceABC(ABC):
@@ -117,13 +116,10 @@ class ImageServiceABC(ABC):
         self,
         offset: int = 0,
         limit: int = 10,
-        starred_first: bool = True,
-        order_dir: SQLiteDirection = SQLiteDirection.Descending,
         image_origin: Optional[ResourceOrigin] = None,
         categories: Optional[list[ImageCategory]] = None,
         is_intermediate: Optional[bool] = None,
         board_id: Optional[str] = None,
-        search_term: Optional[str] = None,
     ) -> OffsetPaginatedResults[ImageDTO]:
         """Gets a paginated list of image DTOs."""
         pass

invokeai/app/services/images/images_default.py

@@ -3,12 +3,15 @@ from typing import Optional
 from PIL.Image import Image as PILImageType
 
 from invokeai.app.invocations.fields import MetadataField
-from invokeai.app.services.image_files.image_files_common import (
+from invokeai.app.services.invoker import Invoker
+from invokeai.app.services.shared.pagination import OffsetPaginatedResults
+
+from ..image_files.image_files_common import (
     ImageFileDeleteException,
     ImageFileNotFoundException,
     ImageFileSaveException,
 )
-from invokeai.app.services.image_records.image_records_common import (
+from ..image_records.image_records_common import (
     ImageCategory,
     ImageRecord,
     ImageRecordChanges,
@@ -19,11 +22,8 @@ from invokeai.app.services.image_records.image_records_common import (
     InvalidOriginException,
     ResourceOrigin,
 )
-from invokeai.app.services.images.images_base import ImageServiceABC
-from invokeai.app.services.images.images_common import ImageDTO, image_record_to_dto
-from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.shared.sqlite.sqlite_common import SQLiteDirection
+from .images_base import ImageServiceABC
+from .images_common import ImageDTO, image_record_to_dto
 
 
 class ImageService(ImageServiceABC):
@@ -73,12 +73,7 @@ class ImageService(ImageServiceABC):
                 session_id=session_id,
             )
             if board_id is not None:
-                try:
-                    self.__invoker.services.board_image_records.add_image_to_board(
-                        board_id=board_id, image_name=image_name
-                    )
-                except Exception as e:
-                    self.__invoker.services.logger.warn(f"Failed to add image to board {board_id}: {str(e)}")
+                self.__invoker.services.board_image_records.add_image_to_board(board_id=board_id, image_name=image_name)
             self.__invoker.services.image_files.save(
                 image_name=image_name, image=image, metadata=metadata, workflow=workflow, graph=graph
             )
@@ -207,25 +202,19 @@ class ImageService(ImageServiceABC):
         self,
         offset: int = 0,
         limit: int = 10,
-        starred_first: bool = True,
-        order_dir: SQLiteDirection = SQLiteDirection.Descending,
         image_origin: Optional[ResourceOrigin] = None,
         categories: Optional[list[ImageCategory]] = None,
         is_intermediate: Optional[bool] = None,
         board_id: Optional[str] = None,
-        search_term: Optional[str] = None,
     ) -> OffsetPaginatedResults[ImageDTO]:
         try:
             results = self.__invoker.services.image_records.get_many(
                 offset,
                 limit,
-                starred_first,
-                order_dir,
                 image_origin,
                 categories,
                 is_intermediate,
                 board_id,
-                search_term,
             )
 
             image_dtos = [

invokeai/app/services/invocation_services.py

@@ -10,28 +10,29 @@ if TYPE_CHECKING:
 
     import torch
 
-    from invokeai.app.services.board_image_records.board_image_records_base import BoardImageRecordStorageBase
-    from invokeai.app.services.board_images.board_images_base import BoardImagesServiceABC
-    from invokeai.app.services.board_records.board_records_base import BoardRecordStorageBase
-    from invokeai.app.services.boards.boards_base import BoardServiceABC
-    from invokeai.app.services.bulk_download.bulk_download_base import BulkDownloadBase
-    from invokeai.app.services.config import InvokeAIAppConfig
-    from invokeai.app.services.download import DownloadQueueServiceBase
-    from invokeai.app.services.events.events_base import EventServiceBase
-    from invokeai.app.services.image_files.image_files_base import ImageFileStorageBase
-    from invokeai.app.services.image_records.image_records_base import ImageRecordStorageBase
-    from invokeai.app.services.images.images_base import ImageServiceABC
-    from invokeai.app.services.invocation_cache.invocation_cache_base import InvocationCacheBase
-    from invokeai.app.services.invocation_stats.invocation_stats_base import InvocationStatsServiceBase
-    from invokeai.app.services.model_images.model_images_base import ModelImageFileStorageBase
-    from invokeai.app.services.model_manager.model_manager_base import ModelManagerServiceBase
-    from invokeai.app.services.names.names_base import NameServiceBase
-    from invokeai.app.services.session_processor.session_processor_base import SessionProcessorBase
-    from invokeai.app.services.session_queue.session_queue_base import SessionQueueBase
-    from invokeai.app.services.urls.urls_base import UrlServiceBase
-    from invokeai.app.services.workflow_records.workflow_records_base import WorkflowRecordsStorageBase
     from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningFieldData
 
+    from .board_image_records.board_image_records_base import BoardImageRecordStorageBase
+    from .board_images.board_images_base import BoardImagesServiceABC
+    from .board_records.board_records_base import BoardRecordStorageBase
+    from .boards.boards_base import BoardServiceABC
+    from .bulk_download.bulk_download_base import BulkDownloadBase
+    from .config import InvokeAIAppConfig
+    from .download import DownloadQueueServiceBase
+    from .events.events_base import EventServiceBase
+    from .image_files.image_files_base import ImageFileStorageBase
+    from .image_records.image_records_base import ImageRecordStorageBase
+    from .images.images_base import ImageServiceABC
+    from .invocation_cache.invocation_cache_base import InvocationCacheBase
+    from .invocation_stats.invocation_stats_base import InvocationStatsServiceBase
+    from .model_images.model_images_base import ModelImageFileStorageBase
+    from .model_manager.model_manager_base import ModelManagerServiceBase
+    from .names.names_base import NameServiceBase
+    from .session_processor.session_processor_base import SessionProcessorBase
+    from .session_queue.session_queue_base import SessionQueueBase
+    from .urls.urls_base import UrlServiceBase
+    from .workflow_records.workflow_records_base import WorkflowRecordsStorageBase
+
 
 class InvocationServices:
     """Services that can be used by invocations"""

invokeai/app/services/invocation_stats/invocation_stats_default.py

@@ -9,8 +9,11 @@ import torch
 
 import invokeai.backend.util.logging as logger
 from invokeai.app.invocations.baseinvocation import BaseInvocation
-from invokeai.app.services.invocation_stats.invocation_stats_base import InvocationStatsServiceBase
-from invokeai.app.services.invocation_stats.invocation_stats_common import (
+from invokeai.app.services.invoker import Invoker
+from invokeai.backend.model_manager.load.model_cache import CacheStats
+
+from .invocation_stats_base import InvocationStatsServiceBase
+from .invocation_stats_common import (
     GESStatsNotFoundError,
     GraphExecutionStats,
     GraphExecutionStatsSummary,
@@ -19,8 +22,6 @@ from invokeai.app.services.invocation_stats.invocation_stats_common import (
     NodeExecutionStats,
     NodeExecutionStatsSummary,
 )
-from invokeai.app.services.invoker import Invoker
-from invokeai.backend.model_manager.load.model_cache import CacheStats
 
 # Size of 1GB in bytes.
 GB = 2**30

invokeai/app/services/invoker.py

@@ -1,7 +1,7 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
 
-from invokeai.app.services.invocation_services import InvocationServices
+from .invocation_services import InvocationServices
 
 
 class Invoker:

invokeai/app/services/model_images/model_images_default.py

@@ -5,14 +5,15 @@ from PIL.Image import Image as PILImageType
 from send2trash import send2trash
 
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.model_images.model_images_base import ModelImageFileStorageBase
-from invokeai.app.services.model_images.model_images_common import (
+from invokeai.app.util.misc import uuid_string
+from invokeai.app.util.thumbnails import make_thumbnail
+
+from .model_images_base import ModelImageFileStorageBase
+from .model_images_common import (
     ModelImageFileDeleteException,
     ModelImageFileNotFoundException,
     ModelImageFileSaveException,
 )
-from invokeai.app.util.misc import uuid_string
-from invokeai.app.util.thumbnails import make_thumbnail
 
 
 class ModelImageFileStorageDisk(ModelImageFileStorageBase):

invokeai/app/services/model_install/__init__.py

@@ -1,7 +1,9 @@
 """Initialization file for model install service package."""
 
-from invokeai.app.services.model_install.model_install_base import ModelInstallServiceBase
-from invokeai.app.services.model_install.model_install_common import (
+from .model_install_base import (
+    ModelInstallServiceBase,
+)
+from .model_install_common import (
     HFModelSource,
     InstallStatus,
     LocalModelSource,
@@ -10,7 +12,7 @@ from invokeai.app.services.model_install.model_install_common import (
     UnknownInstallJobException,
     URLModelSource,
 )
-from invokeai.app.services.model_install.model_install_default import ModelInstallService
+from .model_install_default import ModelInstallService
 
 __all__ = [
     "ModelInstallServiceBase",

invokeai/app/services/model_install/model_install_default.py

@@ -23,16 +23,6 @@ from invokeai.app.services.download import DownloadQueueServiceBase, MultiFileDo
 from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.model_install.model_install_base import ModelInstallServiceBase
-from invokeai.app.services.model_install.model_install_common import (
-    MODEL_SOURCE_TO_TYPE_MAP,
-    HFModelSource,
-    InstallStatus,
-    LocalModelSource,
-    ModelInstallJob,
-    ModelSource,
-    StringLikeSource,
-    URLModelSource,
-)
 from invokeai.app.services.model_records import DuplicateModelException, ModelRecordServiceBase
 from invokeai.app.services.model_records.model_records_base import ModelRecordChanges
 from invokeai.backend.model_manager.config import (
@@ -57,6 +47,17 @@ from invokeai.backend.util.catch_sigint import catch_sigint
 from invokeai.backend.util.devices import TorchDevice
 from invokeai.backend.util.util import slugify
 
+from .model_install_common import (
+    MODEL_SOURCE_TO_TYPE_MAP,
+    HFModelSource,
+    InstallStatus,
+    LocalModelSource,
+    ModelInstallJob,
+    ModelSource,
+    StringLikeSource,
+    URLModelSource,
+)
+
 TMPDIR_PREFIX = "tmpinstall_"
 
 
@@ -847,7 +848,7 @@ class ModelInstallService(ModelInstallServiceBase):
         with self._lock:
             if install_job := self._download_cache.pop(download_job.id, None):
                 assert excp is not None
-                self._set_error(install_job, excp)
+                install_job.set_error(excp)
                 self._download_queue.cancel_job(download_job)
 
                 # Let other threads know that the number of downloads has changed

invokeai/app/services/model_load/__init__.py

@@ -1,6 +1,6 @@
 """Initialization file for model load service module."""
 
-from invokeai.app.services.model_load.model_load_base import ModelLoadServiceBase
-from invokeai.app.services.model_load.model_load_default import ModelLoadService
+from .model_load_base import ModelLoadServiceBase
+from .model_load_default import ModelLoadService
 
 __all__ = ["ModelLoadServiceBase", "ModelLoadService"]

invokeai/app/services/model_load/model_load_base.py

@@ -7,6 +7,7 @@ from typing import Callable, Optional
 
 from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType
 from invokeai.backend.model_manager.load import LoadedModel, LoadedModelWithoutConfig
+from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
 
 
@@ -27,6 +28,11 @@ class ModelLoadServiceBase(ABC):
     def ram_cache(self) -> ModelCacheBase[AnyModel]:
         """Return the RAM cache used by this loader."""
 
+    @property
+    @abstractmethod
+    def convert_cache(self) -> ModelConvertCacheBase:
+        """Return the checkpoint convert cache used by this loader."""
+
     @abstractmethod
     def load_model_from_path(
         self, model_path: Path, loader: Optional[Callable[[Path], AnyModel]] = None

invokeai/app/services/model_load/model_load_default.py

@@ -10,7 +10,6 @@ from torch import load as torch_load
 
 from invokeai.app.services.config import InvokeAIAppConfig
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.model_load.model_load_base import ModelLoadServiceBase
 from invokeai.backend.model_manager import AnyModel, AnyModelConfig, SubModelType
 from invokeai.backend.model_manager.load import (
     LoadedModel,
@@ -18,11 +17,14 @@ from invokeai.backend.model_manager.load import (
     ModelLoaderRegistry,
     ModelLoaderRegistryBase,
 )
+from invokeai.backend.model_manager.load.convert_cache import ModelConvertCacheBase
 from invokeai.backend.model_manager.load.model_cache.model_cache_base import ModelCacheBase
 from invokeai.backend.model_manager.load.model_loaders.generic_diffusers import GenericDiffusersLoader
 from invokeai.backend.util.devices import TorchDevice
 from invokeai.backend.util.logging import InvokeAILogger
 
+from .model_load_base import ModelLoadServiceBase
+
 
 class ModelLoadService(ModelLoadServiceBase):
     """Wrapper around ModelLoaderRegistry."""
@@ -31,6 +33,7 @@ class ModelLoadService(ModelLoadServiceBase):
         self,
         app_config: InvokeAIAppConfig,
         ram_cache: ModelCacheBase[AnyModel],
+        convert_cache: ModelConvertCacheBase,
         registry: Optional[Type[ModelLoaderRegistryBase]] = ModelLoaderRegistry,
     ):
         """Initialize the model load service."""
@@ -39,6 +42,7 @@ class ModelLoadService(ModelLoadServiceBase):
         self._logger = logger
         self._app_config = app_config
         self._ram_cache = ram_cache
+        self._convert_cache = convert_cache
         self._registry = registry
 
     def start(self, invoker: Invoker) -> None:
@@ -49,6 +53,11 @@ class ModelLoadService(ModelLoadServiceBase):
         """Return the RAM cache used by this loader."""
         return self._ram_cache
 
+    @property
+    def convert_cache(self) -> ModelConvertCacheBase:
+        """Return the checkpoint convert cache used by this loader."""
+        return self._convert_cache
+
     def load_model(self, model_config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> LoadedModel:
         """
         Given a model's configuration, load it and return the LoadedModel object.
@@ -67,6 +76,7 @@ class ModelLoadService(ModelLoadServiceBase):
             app_config=self._app_config,
             logger=self._logger,
             ram_cache=self._ram_cache,
+            convert_cache=self._convert_cache,
         ).load_model(model_config, submodel_type)
 
         if hasattr(self, "_invoker"):

invokeai/app/services/model_manager/__init__.py

@@ -1,9 +1,10 @@
 """Initialization file for model manager service."""
 
-from invokeai.app.services.model_manager.model_manager_default import ModelManagerService, ModelManagerServiceBase
 from invokeai.backend.model_manager import AnyModel, AnyModelConfig, BaseModelType, ModelType, SubModelType
 from invokeai.backend.model_manager.load import LoadedModel
 
+from .model_manager_default import ModelManagerService, ModelManagerServiceBase
+
 __all__ = [
     "ModelManagerServiceBase",
     "ModelManagerService",

invokeai/app/services/model_manager/model_manager_base.py

@@ -5,13 +5,14 @@ from abc import ABC, abstractmethod
 import torch
 from typing_extensions import Self
 
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.download.download_base import DownloadQueueServiceBase
-from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.model_install.model_install_base import ModelInstallServiceBase
-from invokeai.app.services.model_load.model_load_base import ModelLoadServiceBase
-from invokeai.app.services.model_records.model_records_base import ModelRecordServiceBase
+
+from ..config import InvokeAIAppConfig
+from ..download import DownloadQueueServiceBase
+from ..events.events_base import EventServiceBase
+from ..model_install import ModelInstallServiceBase
+from ..model_load import ModelLoadServiceBase
+from ..model_records import ModelRecordServiceBase
 
 
 class ModelManagerServiceBase(ABC):

invokeai/app/services/model_manager/model_manager_default.py

@@ -6,20 +6,19 @@ from typing import Optional
 import torch
 from typing_extensions import Self
 
-from invokeai.app.services.config.config_default import InvokeAIAppConfig
-from invokeai.app.services.download.download_base import DownloadQueueServiceBase
-from invokeai.app.services.events.events_base import EventServiceBase
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.model_install.model_install_base import ModelInstallServiceBase
-from invokeai.app.services.model_install.model_install_default import ModelInstallService
-from invokeai.app.services.model_load.model_load_base import ModelLoadServiceBase
-from invokeai.app.services.model_load.model_load_default import ModelLoadService
-from invokeai.app.services.model_manager.model_manager_base import ModelManagerServiceBase
-from invokeai.app.services.model_records.model_records_base import ModelRecordServiceBase
-from invokeai.backend.model_manager.load import ModelCache, ModelLoaderRegistry
+from invokeai.backend.model_manager.load import ModelCache, ModelConvertCache, ModelLoaderRegistry
 from invokeai.backend.util.devices import TorchDevice
 from invokeai.backend.util.logging import InvokeAILogger
 
+from ..config import InvokeAIAppConfig
+from ..download import DownloadQueueServiceBase
+from ..events.events_base import EventServiceBase
+from ..model_install import ModelInstallService, ModelInstallServiceBase
+from ..model_load import ModelLoadService, ModelLoadServiceBase
+from ..model_records import ModelRecordServiceBase
+from .model_manager_base import ModelManagerServiceBase
+
 
 class ModelManagerService(ModelManagerServiceBase):
     """
@@ -87,9 +86,11 @@ class ModelManagerService(ModelManagerServiceBase):
             logger=logger,
             execution_device=execution_device or TorchDevice.choose_torch_device(),
         )
+        convert_cache = ModelConvertCache(cache_path=app_config.convert_cache_path, max_size=app_config.convert_cache)
         loader = ModelLoadService(
             app_config=app_config,
             ram_cache=ram_cache,
+            convert_cache=convert_cache,
             registry=ModelLoaderRegistry,
         )
         installer = ModelInstallService(

invokeai/app/services/model_records/model_records_sql.py

@@ -40,24 +40,12 @@ Typical usage:
 """
 
 import json
-import logging
 import sqlite3
 from math import ceil
 from pathlib import Path
 from typing import List, Optional, Union
 
-import pydantic
-
-from invokeai.app.services.model_records.model_records_base import (
-    DuplicateModelException,
-    ModelRecordChanges,
-    ModelRecordOrderBy,
-    ModelRecordServiceBase,
-    ModelSummary,
-    UnknownModelException,
-)
 from invokeai.app.services.shared.pagination import PaginatedResults
-from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
 from invokeai.backend.model_manager.config import (
     AnyModelConfig,
     BaseModelType,
@@ -66,11 +54,21 @@ from invokeai.backend.model_manager.config import (
     ModelType,
 )
 
+from ..shared.sqlite.sqlite_database import SqliteDatabase
+from .model_records_base import (
+    DuplicateModelException,
+    ModelRecordChanges,
+    ModelRecordOrderBy,
+    ModelRecordServiceBase,
+    ModelSummary,
+    UnknownModelException,
+)
+
 
 class ModelRecordServiceSQL(ModelRecordServiceBase):
     """Implementation of the ModelConfigStore ABC using a SQL database."""
 
-    def __init__(self, db: SqliteDatabase, logger: logging.Logger):
+    def __init__(self, db: SqliteDatabase):
         """
         Initialize a new object from preexisting sqlite3 connection and threading lock objects.
 
@@ -79,7 +77,6 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
         super().__init__()
         self._db = db
         self._cursor = db.conn.cursor()
-        self._logger = logger
 
     @property
     def db(self) -> SqliteDatabase:
@@ -295,20 +292,7 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
                 tuple(bindings),
             )
             result = self._cursor.fetchall()
-
-        # Parse the model configs.
-        results: list[AnyModelConfig] = []
-        for row in result:
-            try:
-                model_config = ModelConfigFactory.make_config(json.loads(row[0]), timestamp=row[1])
-            except pydantic.ValidationError:
-                # We catch this error so that the app can still run if there are invalid model configs in the database.
-                # One reason that an invalid model config might be in the database is if someone had to rollback from a
-                # newer version of the app that added a new model type.
-                self._logger.warning(f"Found an invalid model config in the database. Ignoring this model. ({row[0]})")
-            else:
-                results.append(model_config)
-
+            results = [ModelConfigFactory.make_config(json.loads(x[0]), timestamp=x[1]) for x in result]
         return results
 
     def search_by_path(self, path: Union[str, Path]) -> List[AnyModelConfig]:

invokeai/app/services/names/names_default.py

@@ -1,6 +1,7 @@
-from invokeai.app.services.names.names_base import NameServiceBase
 from invokeai.app.util.misc import uuid_string
 
+from .names_base import NameServiceBase
+
 
 class SimpleNameService(NameServiceBase):
     """Creates image names from UUIDs."""

invokeai/app/services/session_processor/session_processor_default.py

@@ -13,24 +13,24 @@ from invokeai.app.services.events.events_common import (
     register_events,
 )
 from invokeai.app.services.invocation_stats.invocation_stats_common import GESStatsNotFoundError
-from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.session_processor.session_processor_base import (
-    InvocationServices,
     OnAfterRunNode,
     OnAfterRunSession,
     OnBeforeRunNode,
     OnBeforeRunSession,
     OnNodeError,
     OnNonFatalProcessorError,
-    SessionProcessorBase,
-    SessionRunnerBase,
 )
-from invokeai.app.services.session_processor.session_processor_common import CanceledException, SessionProcessorStatus
+from invokeai.app.services.session_processor.session_processor_common import CanceledException
 from invokeai.app.services.session_queue.session_queue_common import SessionQueueItem, SessionQueueItemNotFoundError
 from invokeai.app.services.shared.graph import NodeInputError
 from invokeai.app.services.shared.invocation_context import InvocationContextData, build_invocation_context
 from invokeai.app.util.profiler import Profiler
 
+from ..invoker import Invoker
+from .session_processor_base import InvocationServices, SessionProcessorBase, SessionRunnerBase
+from .session_processor_common import SessionProcessorStatus
+
 
 class DefaultSessionRunner(SessionRunnerBase):
     """Processes a single session's invocations."""

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

@@ -14,8 +14,6 @@ from invokeai.app.services.shared.sqlite_migrator.migrations.migration_8 import
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_9 import build_migration_9
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_10 import build_migration_10
 from invokeai.app.services.shared.sqlite_migrator.migrations.migration_11 import build_migration_11
-from invokeai.app.services.shared.sqlite_migrator.migrations.migration_12 import build_migration_12
-from invokeai.app.services.shared.sqlite_migrator.migrations.migration_13 import build_migration_13
 from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_impl import SqliteMigrator
 
 
@@ -47,8 +45,6 @@ def init_db(config: InvokeAIAppConfig, logger: Logger, image_files: ImageFileSto
     migrator.register_migration(build_migration_9())
     migrator.register_migration(build_migration_10())
     migrator.register_migration(build_migration_11(app_config=config, logger=logger))
-    migrator.register_migration(build_migration_12(app_config=config))
-    migrator.register_migration(build_migration_13())
     migrator.run_migrations()
 
     return db

invokeai/app/services/shared/sqlite_migrator/migrations/migration_12.py

@@ -1,35 +0,0 @@
-import shutil
-import sqlite3
-
-from invokeai.app.services.config import InvokeAIAppConfig
-from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
-
-
-class Migration12Callback:
-    def __init__(self, app_config: InvokeAIAppConfig) -> None:
-        self._app_config = app_config
-
-    def __call__(self, cursor: sqlite3.Cursor) -> None:
-        self._remove_model_convert_cache_dir()
-
-    def _remove_model_convert_cache_dir(self) -> None:
-        """
-        Removes unused model convert cache directory
-        """
-        convert_cache = self._app_config.convert_cache_path
-        shutil.rmtree(convert_cache, ignore_errors=True)
-
-
-def build_migration_12(app_config: InvokeAIAppConfig) -> Migration:
-    """
-    Build the migration from database version 11 to 12.
-
-    This migration removes the now-unused model convert cache directory.
-    """
-    migration_12 = Migration(
-        from_version=11,
-        to_version=12,
-        callback=Migration12Callback(app_config),
-    )
-
-    return migration_12

invokeai/app/services/shared/sqlite_migrator/migrations/migration_13.py

@@ -1,31 +0,0 @@
-import sqlite3
-
-from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
-
-
-class Migration13Callback:
-    def __call__(self, cursor: sqlite3.Cursor) -> None:
-        self._add_archived_col(cursor)
-
-    def _add_archived_col(self, cursor: sqlite3.Cursor) -> None:
-        """
-        - Adds `archived` columns to the board table.
-        """
-
-        cursor.execute("ALTER TABLE boards ADD COLUMN archived BOOLEAN DEFAULT FALSE;")
-
-
-def build_migration_13() -> Migration:
-    """
-    Build the migration from database version 12 to 13..
-
-    This migration does the following:
-    - Adds `archived` columns to the board table.
-    """
-    migration_13 = Migration(
-        from_version=12,
-        to_version=13,
-        callback=Migration13Callback(),
-    )
-
-    return migration_13

invokeai/app/services/urls/urls_default.py

@@ -1,6 +1,6 @@
 import os
 
-from invokeai.app.services.urls.urls_base import UrlServiceBase
+from .urls_base import UrlServiceBase
 
 
 class LocalUrlService(UrlServiceBase):

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

@@ -2,7 +2,7 @@
   "name": "ESRGAN Upscaling with Canny ControlNet",
   "author": "InvokeAI",
   "description": "Sample workflow for using Upscaling with ControlNet with SD1.5",
-  "version": "2.1.0",
+  "version": "2.0.0",
   "contact": "invoke@invoke.ai",
   "tags": "upscale, controlnet, default",
   "notes": "",
@@ -36,13 +36,14 @@
     "version": "3.0.0",
     "category": "default"
   },
+  "id": "0e71a27e-a22b-4a9b-b20a-6d789abff2bc",
   "nodes": [
     {
-      "id": "63b6ab7e-5b05-4d1b-a3b1-42d8e53ce16b",
+      "id": "e8bf67fe-67de-4227-87eb-79e86afdfc74",
       "type": "invocation",
       "data": {
-        "id": "63b6ab7e-5b05-4d1b-a3b1-42d8e53ce16b",
-        "version": "1.2.0",
+        "id": "e8bf67fe-67de-4227-87eb-79e86afdfc74",
+        "version": "1.1.1",
         "nodePack": "invokeai",
         "label": "",
         "notes": "",
@@ -56,10 +57,6 @@
           "clip": {
             "name": "clip",
             "label": ""
-          },
-          "mask": {
-            "name": "mask",
-            "label": ""
           }
         },
         "isOpen": true,
@@ -68,63 +65,79 @@
       },
       "position": {
         "x": 1250,
-        "y": 1200
+        "y": 1500
       }
     },
     {
-      "id": "5ca498a4-c8c8-4580-a396-0c984317205d",
+      "id": "d8ace142-c05f-4f1d-8982-88dc7473958d",
       "type": "invocation",
       "data": {
-        "id": "5ca498a4-c8c8-4580-a396-0c984317205d",
-        "version": "1.1.0",
+        "id": "d8ace142-c05f-4f1d-8982-88dc7473958d",
+        "version": "1.0.2",
         "nodePack": "invokeai",
         "label": "",
         "notes": "",
-        "type": "i2l",
+        "type": "main_model_loader",
         "inputs": {
-          "image": {
-            "name": "image",
-            "label": ""
-          },
-          "vae": {
-            "name": "vae",
-            "label": ""
-          },
-          "tiled": {
-            "name": "tiled",
+          "model": {
+            "name": "model",
             "label": "",
-            "value": false
-          },
-          "tile_size": {
-            "name": "tile_size",
-            "label": "",
-            "value": 0
-          },
-          "fp32": {
-            "name": "fp32",
-            "label": "",
-            "value": false
+            "value": {
+              "key": "5cd43ca0-dd0a-418d-9f7e-35b2b9d5e106",
+              "hash": "blake3:6987f323017f597213cc3264250edf57056d21a40a0a85d83a1a33a7d44dc41a",
+              "name": "Deliberate_v5",
+              "base": "sd-1",
+              "type": "main"
+            }
           }
         },
-        "isOpen": false,
+        "isOpen": true,
         "isIntermediate": true,
         "useCache": true
       },
       "position": {
-        "x": 1650,
-        "y": 1675
+        "x": 700,
+        "y": 1375
       }
     },
     {
-      "id": "3ed9b2ef-f4ec-40a7-94db-92e63b583ec0",
+      "id": "771bdf6a-0813-4099-a5d8-921a138754d4",
       "type": "invocation",
       "data": {
-        "id": "3ed9b2ef-f4ec-40a7-94db-92e63b583ec0",
-        "version": "1.3.0",
+        "id": "771bdf6a-0813-4099-a5d8-921a138754d4",
+        "version": "1.0.2",
         "nodePack": "invokeai",
         "label": "",
         "notes": "",
-        "type": "l2i",
+        "type": "image",
+        "inputs": {
+          "image": {
+            "name": "image",
+            "label": "Image To Upscale",
+            "value": {
+              "image_name": "d2e42ba6-d420-496b-82db-91c9b75956c1.png"
+            }
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": 344.5593065887157,
+        "y": 1698.161491368619
+      }
+    },
+    {
+      "id": "f7564dd2-9539-47f2-ac13-190804461f4e",
+      "type": "invocation",
+      "data": {
+        "id": "f7564dd2-9539-47f2-ac13-190804461f4e",
+        "version": "1.3.2",
+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "esrgan",
         "inputs": {
           "board": {
             "name": "board",
@@ -134,37 +147,81 @@
             "name": "metadata",
             "label": ""
           },
-          "latents": {
-            "name": "latents",
+          "image": {
+            "name": "image",
             "label": ""
           },
-          "vae": {
-            "name": "vae",
-            "label": ""
-          },
-          "tiled": {
-            "name": "tiled",
-            "label": "",
-            "value": false
+          "model_name": {
+            "name": "model_name",
+            "label": "Upscaler Model",
+            "value": "RealESRGAN_x2plus.pth"
           },
           "tile_size": {
             "name": "tile_size",
             "label": "",
-            "value": 0
-          },
-          "fp32": {
-            "name": "fp32",
-            "label": "",
-            "value": false
+            "value": 400
           }
         },
         "isOpen": true,
-        "isIntermediate": false,
+        "isIntermediate": true,
         "useCache": true
       },
       "position": {
-        "x": 2559.4751127537957,
-        "y": 1246.6000376741406
+        "x": 717.3863693661265,
+        "y": 1721.9215053134815
+      }
+    },
+    {
+      "id": "1d887701-df21-4966-ae6e-a7d82307d7bd",
+      "type": "invocation",
+      "data": {
+        "id": "1d887701-df21-4966-ae6e-a7d82307d7bd",
+        "version": "1.3.2",
+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "canny_image_processor",
+        "inputs": {
+          "board": {
+            "name": "board",
+            "label": ""
+          },
+          "metadata": {
+            "name": "metadata",
+            "label": ""
+          },
+          "image": {
+            "name": "image",
+            "label": ""
+          },
+          "detect_resolution": {
+            "name": "detect_resolution",
+            "label": "",
+            "value": 512
+          },
+          "image_resolution": {
+            "name": "image_resolution",
+            "label": "",
+            "value": 512
+          },
+          "low_threshold": {
+            "name": "low_threshold",
+            "label": "",
+            "value": 100
+          },
+          "high_threshold": {
+            "name": "high_threshold",
+            "label": "",
+            "value": 200
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": 1200,
+        "y": 1900
       }
     },
     {
@@ -172,7 +229,7 @@
       "type": "invocation",
       "data": {
         "id": "ca1d020c-89a8-4958-880a-016d28775cfa",
-        "version": "1.1.2",
+        "version": "1.1.1",
         "nodePack": "invokeai",
         "label": "",
         "notes": "",
@@ -228,193 +285,6 @@
         "y": 1902.9649340196056
       }
     },
-    {
-      "id": "1d887701-df21-4966-ae6e-a7d82307d7bd",
-      "type": "invocation",
-      "data": {
-        "id": "1d887701-df21-4966-ae6e-a7d82307d7bd",
-        "version": "1.3.3",
-        "nodePack": "invokeai",
-        "label": "",
-        "notes": "",
-        "type": "canny_image_processor",
-        "inputs": {
-          "board": {
-            "name": "board",
-            "label": ""
-          },
-          "metadata": {
-            "name": "metadata",
-            "label": ""
-          },
-          "image": {
-            "name": "image",
-            "label": ""
-          },
-          "detect_resolution": {
-            "name": "detect_resolution",
-            "label": "",
-            "value": 512
-          },
-          "image_resolution": {
-            "name": "image_resolution",
-            "label": "",
-            "value": 512
-          },
-          "low_threshold": {
-            "name": "low_threshold",
-            "label": "",
-            "value": 100
-          },
-          "high_threshold": {
-            "name": "high_threshold",
-            "label": "",
-            "value": 200
-          }
-        },
-        "isOpen": true,
-        "isIntermediate": true,
-        "useCache": true
-      },
-      "position": {
-        "x": 1200,
-        "y": 1900
-      }
-    },
-    {
-      "id": "d8ace142-c05f-4f1d-8982-88dc7473958d",
-      "type": "invocation",
-      "data": {
-        "id": "d8ace142-c05f-4f1d-8982-88dc7473958d",
-        "version": "1.0.3",
-        "nodePack": "invokeai",
-        "label": "",
-        "notes": "",
-        "type": "main_model_loader",
-        "inputs": {
-          "model": {
-            "name": "model",
-            "label": "",
-            "value": {
-              "key": "5cd43ca0-dd0a-418d-9f7e-35b2b9d5e106",
-              "hash": "blake3:6987f323017f597213cc3264250edf57056d21a40a0a85d83a1a33a7d44dc41a",
-              "name": "Deliberate_v5",
-              "base": "sd-1",
-              "type": "main"
-            }
-          }
-        },
-        "isOpen": true,
-        "isIntermediate": true,
-        "useCache": true
-      },
-      "position": {
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-        "y": 1375
-      }
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-    {
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-      "type": "invocation",
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-        "id": "e8bf67fe-67de-4227-87eb-79e86afdfc74",
-        "version": "1.2.0",
-        "nodePack": "invokeai",
-        "label": "",
-        "notes": "",
-        "type": "compel",
-        "inputs": {
-          "prompt": {
-            "name": "prompt",
-            "label": "",
-            "value": ""
-          },
-          "clip": {
-            "name": "clip",
-            "label": ""
-          },
-          "mask": {
-            "name": "mask",
-            "label": ""
-          }
-        },
-        "isOpen": true,
-        "isIntermediate": true,
-        "useCache": true
-      },
-      "position": {
-        "x": 1250,
-        "y": 1500
-      }
-    },
-    {
-      "id": "771bdf6a-0813-4099-a5d8-921a138754d4",
-      "type": "invocation",
-      "data": {
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-        "version": "1.0.2",
-        "nodePack": "invokeai",
-        "label": "",
-        "notes": "",
-        "type": "image",
-        "inputs": {
-          "image": {
-            "name": "image",
-            "label": "Image To Upscale"
-          }
-        },
-        "isOpen": true,
-        "isIntermediate": true,
-        "useCache": true
-      },
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-        "y": 1698.161491368619
-      }
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-    {
-      "id": "f7564dd2-9539-47f2-ac13-190804461f4e",
-      "type": "invocation",
-      "data": {
-        "id": "f7564dd2-9539-47f2-ac13-190804461f4e",
-        "version": "1.3.2",
-        "nodePack": "invokeai",
-        "label": "",
-        "notes": "",
-        "type": "esrgan",
-        "inputs": {
-          "board": {
-            "name": "board",
-            "label": ""
-          },
-          "metadata": {
-            "name": "metadata",
-            "label": ""
-          },
-          "image": {
-            "name": "image",
-            "label": ""
-          },
-          "model_name": {
-            "name": "model_name",
-            "label": "Upscaler Model",
-            "value": "RealESRGAN_x2plus.pth"
-          },
-          "tile_size": {
-            "name": "tile_size",
-            "label": "",
-            "value": 400
-          }
-        },
-        "isOpen": true,
-        "isIntermediate": true,
-        "useCache": true
-      },
-      "position": {
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-        "y": 1721.9215053134815
-      }
-    },
     {
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       "type": "invocation",
@@ -543,6 +413,122 @@
         "y": 1232.6219060454753
       }
     },
+    {
+      "id": "3ed9b2ef-f4ec-40a7-94db-92e63b583ec0",
+      "type": "invocation",
+      "data": {
+        "id": "3ed9b2ef-f4ec-40a7-94db-92e63b583ec0",
+        "version": "1.2.2",
+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "l2i",
+        "inputs": {
+          "board": {
+            "name": "board",
+            "label": ""
+          },
+          "metadata": {
+            "name": "metadata",
+            "label": ""
+          },
+          "latents": {
+            "name": "latents",
+            "label": ""
+          },
+          "vae": {
+            "name": "vae",
+            "label": ""
+          },
+          "tiled": {
+            "name": "tiled",
+            "label": "",
+            "value": false
+          },
+          "fp32": {
+            "name": "fp32",
+            "label": "",
+            "value": false
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": false,
+        "useCache": true
+      },
+      "position": {
+        "x": 2559.4751127537957,
+        "y": 1246.6000376741406
+      }
+    },
+    {
+      "id": "5ca498a4-c8c8-4580-a396-0c984317205d",
+      "type": "invocation",
+      "data": {
+        "id": "5ca498a4-c8c8-4580-a396-0c984317205d",
+        "version": "1.0.2",
+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "i2l",
+        "inputs": {
+          "image": {
+            "name": "image",
+            "label": ""
+          },
+          "vae": {
+            "name": "vae",
+            "label": ""
+          },
+          "tiled": {
+            "name": "tiled",
+            "label": "",
+            "value": false
+          },
+          "fp32": {
+            "name": "fp32",
+            "label": "",
+            "value": false
+          }
+        },
+        "isOpen": false,
+        "isIntermediate": true,
+        "useCache": true
+      },
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+        "y": 1675
+      }
+    },
+    {
+      "id": "63b6ab7e-5b05-4d1b-a3b1-42d8e53ce16b",
+      "type": "invocation",
+      "data": {
+        "id": "63b6ab7e-5b05-4d1b-a3b1-42d8e53ce16b",
+        "version": "1.1.1",
+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "compel",
+        "inputs": {
+          "prompt": {
+            "name": "prompt",
+            "label": "",
+            "value": ""
+          },
+          "clip": {
+            "name": "clip",
+            "label": ""
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": 1250,
+        "y": 1200
+      }
+    },
     {
       "id": "eb8f6f8a-c7b1-4914-806e-045ee2717a35",
       "type": "invocation",

invokeai/app/services/workflow_records/default_workflows/Face Detailer with IP-Adapter & Canny (See Note in Details).json

@@ -2,7 +2,7 @@
   "name": "Face Detailer with IP-Adapter & Canny (See Note in Details)",
   "author": "kosmoskatten",
   "description": "A workflow to add detail to and improve faces. This workflow is most effective when used with a model that creates realistic outputs. ",
-  "version": "2.1.0",
+  "version": "2.0.0",
   "contact": "invoke@invoke.ai",
   "tags": "face detailer, IP-Adapter, Canny",
   "notes": "Set this image as the blur mask: https://i.imgur.com/Gxi61zP.png",
@@ -37,349 +37,16 @@
     }
   ],
   "meta": {
-    "version": "3.0.0",
-    "category": "default"
+    "category": "default",
+    "version": "3.0.0"
   },
   "nodes": [
-    {
-      "id": "c6359181-6479-40ec-bf3a-b7e8451683b8",
-      "type": "invocation",
-      "data": {
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-        "version": "1.0.3",
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-        "type": "main_model_loader",
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-        "isOpen": true,
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-        "useCache": true
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-        "type": "canny_image_processor",
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-            "value": 512
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-            "value": 512
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-            "value": 100
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@@ -393,10 +60,6 @@
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@@ -588,6 +251,45 @@
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invokeai/app/services/workflow_records/default_workflows/Multi ControlNet (Canny & Depth).json

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@@ -37,218 +37,24 @@
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+        "type": "image",
         "inputs": {
           "image": {
             "name": "image",
-            "label": ""
-          },
-          "control_model": {
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-            "label": "Control Model (select canny)",
-            "value": {
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-              "hash": "blake3:260c7f8e10aefea9868cfc68d89970e91033bd37132b14b903e70ee05ebf530e",
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-              "base": "sd-1",
-              "type": "controlnet"
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-            "value": 1
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-            "value": 0
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-            "value": 1
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-            "label": "",
-            "value": "balanced"
-          },
-          "resize_mode": {
-            "name": "resize_mode",
-            "label": "",
-            "value": "just_resize"
+            "label": "Depth Input Image"
           }
         },
         "isOpen": true,
@@ -256,101 +62,8 @@
         "useCache": true
       },
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-        "y": -618.4221638099414
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-        "type": "compel",
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-            "label": "Positive Prompt",
-            "value": ""
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-          "clip": {
-            "name": "clip",
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-        "isOpen": true,
-        "isIntermediate": true,
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-      "type": "invocation",
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-        "type": "compel",
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-        "isOpen": true,
-        "isIntermediate": true,
-        "useCache": true
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-      "position": {
-        "x": 4075,
-        "y": -825
+        "x": 3666.135718057363,
+        "y": 186.66887319822808
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     {
@@ -358,7 +71,7 @@
       "type": "invocation",
       "data": {
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-        "version": "1.1.2",
+        "version": "1.1.1",
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         "notes": "",
@@ -415,19 +128,24 @@
       }
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+      "id": "273e3f96-49ea-4dc5-9d5b-9660390f14e1",
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       "data": {
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-        "version": "1.0.2",
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+        "version": "1.1.1",
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         "notes": "",
-        "type": "image",
+        "type": "compel",
         "inputs": {
-          "image": {
-            "name": "image",
-            "label": "Depth Input Image"
+          "prompt": {
+            "name": "prompt",
+            "label": "Negative Prompt",
+            "value": ""
+          },
+          "clip": {
+            "name": "clip",
+            "label": ""
           }
         },
         "isOpen": true,
@@ -435,8 +153,124 @@
         "useCache": true
       },
       "position": {
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-        "y": 186.66887319822808
+        "x": 4075,
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+    {
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+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "main_model_loader",
+        "inputs": {
+          "model": {
+            "name": "model",
+            "label": ""
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": 3600,
+        "y": -1000
+      }
+    },
+    {
+      "id": "7ce68934-3419-42d4-ac70-82cfc9397306",
+      "type": "invocation",
+      "data": {
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+        "version": "1.1.1",
+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "compel",
+        "inputs": {
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+            "name": "prompt",
+            "label": "Positive Prompt",
+            "value": ""
+          },
+          "clip": {
+            "name": "clip",
+            "label": ""
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
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+      }
+    },
+    {
+      "id": "d204d184-f209-4fae-a0a1-d152800844e1",
+      "type": "invocation",
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+        "version": "1.1.1",
+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "controlnet",
+        "inputs": {
+          "image": {
+            "name": "image",
+            "label": ""
+          },
+          "control_model": {
+            "name": "control_model",
+            "label": "Control Model (select canny)",
+            "value": {
+              "key": "5bdaacf7-a7a3-4fb8-b394-cc0ffbb8941d",
+              "hash": "blake3:260c7f8e10aefea9868cfc68d89970e91033bd37132b14b903e70ee05ebf530e",
+              "name": "sd-controlnet-canny",
+              "base": "sd-1",
+              "type": "controlnet"
+            }
+          },
+          "control_weight": {
+            "name": "control_weight",
+            "label": "",
+            "value": 1
+          },
+          "begin_step_percent": {
+            "name": "begin_step_percent",
+            "label": "",
+            "value": 0
+          },
+          "end_step_percent": {
+            "name": "end_step_percent",
+            "label": "",
+            "value": 1
+          },
+          "control_mode": {
+            "name": "control_mode",
+            "label": "",
+            "value": "balanced"
+          },
+          "resize_mode": {
+            "name": "resize_mode",
+            "label": "",
+            "value": "just_resize"
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": 4479.68542130465,
+        "y": -618.4221638099414
       }
     },
     {
@@ -488,6 +322,159 @@
         "y": -575
       }
     },
+    {
+      "id": "018b1214-c2af-43a7-9910-fb687c6726d7",
+      "type": "invocation",
+      "data": {
+        "id": "018b1214-c2af-43a7-9910-fb687c6726d7",
+        "version": "1.2.3",
+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "midas_depth_image_processor",
+        "inputs": {
+          "board": {
+            "name": "board",
+            "label": ""
+          },
+          "metadata": {
+            "name": "metadata",
+            "label": ""
+          },
+          "image": {
+            "name": "image",
+            "label": ""
+          },
+          "a_mult": {
+            "name": "a_mult",
+            "label": "",
+            "value": 2
+          },
+          "bg_th": {
+            "name": "bg_th",
+            "label": "",
+            "value": 0.1
+          },
+          "detect_resolution": {
+            "name": "detect_resolution",
+            "label": "",
+            "value": 512
+          },
+          "image_resolution": {
+            "name": "image_resolution",
+            "label": "",
+            "value": 512
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
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+      "position": {
+        "x": 4082.783145980783,
+        "y": 0.01629251229994111
+      }
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+    {
+      "id": "c826ba5e-9676-4475-b260-07b85e88753c",
+      "type": "invocation",
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+        "version": "1.3.2",
+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "canny_image_processor",
+        "inputs": {
+          "board": {
+            "name": "board",
+            "label": ""
+          },
+          "metadata": {
+            "name": "metadata",
+            "label": ""
+          },
+          "image": {
+            "name": "image",
+            "label": ""
+          },
+          "detect_resolution": {
+            "name": "detect_resolution",
+            "label": "",
+            "value": 512
+          },
+          "image_resolution": {
+            "name": "image_resolution",
+            "label": "",
+            "value": 512
+          },
+          "low_threshold": {
+            "name": "low_threshold",
+            "label": "",
+            "value": 100
+          },
+          "high_threshold": {
+            "name": "high_threshold",
+            "label": "",
+            "value": 200
+          }
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+        "isIntermediate": true,
+        "useCache": true
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+    {
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+        "notes": "",
+        "type": "l2i",
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+          },
+          "metadata": {
+            "name": "metadata",
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+          "latents": {
+            "name": "latents",
+            "label": ""
+          },
+          "vae": {
+            "name": "vae",
+            "label": ""
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+          "tiled": {
+            "name": "tiled",
+            "label": "",
+            "value": false
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+          "fp32": {
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+            "value": false
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+        "isIntermediate": false,
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invokeai/app/services/workflow_records/default_workflows/Prompt from File.json

@@ -2,7 +2,7 @@
   "name": "Prompt from File",
   "author": "InvokeAI",
   "description": "Sample workflow using Prompt from File node",
-  "version": "2.1.0",
+  "version": "2.0.0",
   "contact": "invoke@invoke.ai",
   "tags": "text2image, prompt from file, default",
   "notes": "",
@@ -37,127 +37,16 @@
     }
   ],
   "meta": {
-    "version": "3.0.0",
-    "category": "default"
+    "category": "default",
+    "version": "3.0.0"
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   "nodes": [
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     {
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       "type": "invocation",
       "data": {
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-        "version": "1.2.0",
+        "version": "1.1.1",
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@@ -171,10 +60,6 @@
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-            "label": ""
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         "isOpen": false,
@@ -256,6 +141,61 @@
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       }
     },
+    {
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+      "type": "invocation",
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+        "version": "1.0.2",
+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "main_model_loader",
+        "inputs": {
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+            "name": "model",
+            "label": ""
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
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+        "y": -375
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+    },
+    {
+      "id": "fc9d0e35-a6de-4a19-84e1-c72497c823f6",
+      "type": "invocation",
+      "data": {
+        "id": "fc9d0e35-a6de-4a19-84e1-c72497c823f6",
+        "version": "1.1.1",
+        "nodePack": "invokeai",
+        "label": "",
+        "notes": "",
+        "type": "compel",
+        "inputs": {
+          "prompt": {
+            "name": "prompt",
+            "label": "",
+            "value": ""
+          },
+          "clip": {
+            "name": "clip",
+            "label": ""
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+        "isOpen": false,
+        "isIntermediate": true,
+        "useCache": true
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       "type": "invocation",
@@ -328,6 +268,53 @@
         "y": -50
       }
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+    {
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+        "type": "l2i",
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+          "latents": {
+            "name": "latents",
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+          "vae": {
+            "name": "vae",
+            "label": ""
+          },
+          "tiled": {
+            "name": "tiled",
+            "label": "",
+            "value": false
+          },
+          "fp32": {
+            "name": "fp32",
+            "label": "",
+            "value": false
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invokeai/app/services/workflow_records/default_workflows/Text to Image - SD1.5.json

@@ -2,7 +2,7 @@
   "name": "Text to Image - SD1.5",
   "author": "InvokeAI",
   "description": "Sample text to image workflow for Stable Diffusion 1.5/2",
-  "version": "2.1.0",
+  "version": "2.0.0",
   "contact": "invoke@invoke.ai",
   "tags": "text2image, SD1.5, SD2, default",
   "notes": "",
@@ -33,127 +33,16 @@
     }
   ],
   "meta": {
-    "version": "3.0.0",
-    "category": "default"
+    "category": "default",
+    "version": "3.0.0"
   },
   "nodes": [
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@@ -167,10 +56,6 @@
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@@ -223,6 +108,61 @@
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@@ -340,6 +280,53 @@
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invokeai/app/services/workflow_records/default_workflows/Text to Image - SDXL.json

@@ -2,7 +2,7 @@
   "name": "Text to Image - SDXL",
   "author": "InvokeAI",
   "description": "Sample text to image workflow for SDXL",
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+  "version": "2.0.0",
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@@ -29,271 +29,10 @@
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@@ -349,6 +88,75 @@
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+        "notes": "",
+        "type": "sdxl_compel_prompt",
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+            "label": "Negative Prompt",
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+            "value": 1024
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+            "value": 1024
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+            "value": 1024
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       "type": "invocation",
@@ -421,6 +229,154 @@
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+        "notes": "",
+        "type": "sdxl_model_loader",
+        "inputs": {
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+            "value": {
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+              "hash": "blake3:d279309ea6e5ee6e8fd52504275865cc280dac71cbf528c5b07c98b888bddaba",
+              "name": "dreamshaper-xl-v2-turbo",
+              "base": "sdxl",
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+        "label": "SDXL Positive Compel Prompt",
+        "notes": "",
+        "type": "sdxl_compel_prompt",
+        "inputs": {
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+            "label": "Positive Prompt",
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+            "value": ""
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+            "value": 1024
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@@ -508,6 +464,37 @@
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+        "type": "vae_loader",
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invokeai/app/services/workflow_records/default_workflows/Text to Image with LoRA.json

@@ -2,7 +2,7 @@
   "name": "Text to Image with LoRA",
   "author": "InvokeAI",
   "description": "Simple text to image workflow with a LoRA",
-  "version": "2.1.0",
+  "version": "2.0.0",
   "contact": "invoke@invoke.ai",
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   "notes": "",
@@ -37,83 +37,28 @@
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   ],
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+    "category": "default",
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-        "version": "1.3.0",
-        "label": "",
-        "notes": "",
-        "type": "l2i",
-        "inputs": {
-          "board": {
-            "name": "board",
-            "label": ""
-          },
-          "metadata": {
-            "name": "metadata",
-            "label": ""
-          },
-          "latents": {
-            "name": "latents",
-            "label": ""
-          },
-          "vae": {
-            "name": "vae",
-            "label": ""
-          },
-          "tiled": {
-            "name": "tiled",
-            "label": "",
-            "value": false
-          },
-          "tile_size": {
-            "name": "tile_size",
-            "label": "",
-            "value": 0
-          },
-          "fp32": {
-            "name": "fp32",
-            "label": "",
-            "value": false
-          }
-        },
-        "isOpen": true,
-        "isIntermediate": false,
-        "useCache": true
-      },
-      "position": {
-        "x": 4450,
-        "y": -550
-      }
-    },
-    {
-      "id": "c3fa6872-2599-4a82-a596-b3446a66cf8b",
-      "type": "invocation",
-      "data": {
-        "id": "c3fa6872-2599-4a82-a596-b3446a66cf8b",
-        "version": "1.2.0",
+        "id": "85b77bb2-c67a-416a-b3e8-291abe746c44",
+        "version": "1.1.1",
         "label": "",
         "notes": "",
         "type": "compel",
         "inputs": {
           "prompt": {
             "name": "prompt",
-            "label": "Positive Prompt",
-            "value": "super cute tiger cub"
+            "label": "Negative Prompt",
+            "value": ""
           },
           "clip": {
             "name": "clip",
             "label": ""
-          },
-          "mask": {
-            "name": "mask",
-            "label": ""
           }
         },
         "isOpen": true,
@@ -122,7 +67,31 @@
       },
       "position": {
         "x": 3425,
-        "y": -575
+        "y": -300
+      }
+    },
+    {
+      "id": "24e9d7ed-4836-4ec4-8f9e-e747721f9818",
+      "type": "invocation",
+      "data": {
+        "id": "24e9d7ed-4836-4ec4-8f9e-e747721f9818",
+        "version": "1.0.2",
+        "label": "",
+        "notes": "",
+        "type": "main_model_loader",
+        "inputs": {
+          "model": {
+            "name": "model",
+            "label": ""
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": 2500,
+        "y": -600
       }
     },
     {
@@ -130,7 +99,7 @@
       "type": "invocation",
       "data": {
         "id": "c41e705b-f2e3-4d1a-83c4-e34bb9344966",
-        "version": "1.0.3",
+        "version": "1.0.2",
         "label": "",
         "notes": "",
         "type": "lora_loader",
@@ -163,51 +132,23 @@
       }
     },
     {
-      "id": "24e9d7ed-4836-4ec4-8f9e-e747721f9818",
+      "id": "c3fa6872-2599-4a82-a596-b3446a66cf8b",
       "type": "invocation",
       "data": {
-        "id": "24e9d7ed-4836-4ec4-8f9e-e747721f9818",
-        "version": "1.0.3",
-        "label": "",
-        "notes": "",
-        "type": "main_model_loader",
-        "inputs": {
-          "model": {
-            "name": "model",
-            "label": ""
-          }
-        },
-        "isOpen": true,
-        "isIntermediate": true,
-        "useCache": true
-      },
-      "position": {
-        "x": 2500,
-        "y": -600
-      }
-    },
-    {
-      "id": "85b77bb2-c67a-416a-b3e8-291abe746c44",
-      "type": "invocation",
-      "data": {
-        "id": "85b77bb2-c67a-416a-b3e8-291abe746c44",
-        "version": "1.2.0",
+        "id": "c3fa6872-2599-4a82-a596-b3446a66cf8b",
+        "version": "1.1.1",
         "label": "",
         "notes": "",
         "type": "compel",
         "inputs": {
           "prompt": {
             "name": "prompt",
-            "label": "Negative Prompt",
-            "value": ""
+            "label": "Positive Prompt",
+            "value": "super cute tiger cub"
           },
           "clip": {
             "name": "clip",
             "label": ""
-          },
-          "mask": {
-            "name": "mask",
-            "label": ""
           }
         },
         "isOpen": true,
@@ -216,7 +157,7 @@
       },
       "position": {
         "x": 3425,
-        "y": -300
+        "y": -575
       }
     },
     {
@@ -374,6 +315,52 @@
         "x": 3425,
         "y": 0
       }
+    },
+    {
+      "id": "a9683c0a-6b1f-4a5e-8187-c57e764b3400",
+      "type": "invocation",
+      "data": {
+        "id": "a9683c0a-6b1f-4a5e-8187-c57e764b3400",
+        "version": "1.2.2",
+        "label": "",
+        "notes": "",
+        "type": "l2i",
+        "inputs": {
+          "board": {
+            "name": "board",
+            "label": ""
+          },
+          "metadata": {
+            "name": "metadata",
+            "label": ""
+          },
+          "latents": {
+            "name": "latents",
+            "label": ""
+          },
+          "vae": {
+            "name": "vae",
+            "label": ""
+          },
+          "tiled": {
+            "name": "tiled",
+            "label": "",
+            "value": false
+          },
+          "fp32": {
+            "name": "fp32",
+            "label": "",
+            "value": false
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": false,
+        "useCache": true
+      },
+      "position": {
+        "x": 4450,
+        "y": -550
+      }
     }
   ],
   "edges": [

invokeai/app/services/workflow_records/default_workflows/Tiled Upscaling (Beta).json

@@ -2,7 +2,7 @@
   "name": "Tiled Upscaling (Beta)",
   "author": "Invoke",
   "description": "A workflow to upscale an input image with tiled upscaling. ",
-  "version": "2.1.0",
+  "version": "2.0.0",
   "contact": "invoke@invoke.ai",
   "tags": "tiled, upscaling, sd1.5",
   "notes": "",
@@ -41,318 +41,10 @@
     }
   ],
   "meta": {
-    "version": "3.0.0",
-    "category": "default"
+    "category": "default",
+    "version": "3.0.0"
   },
   "nodes": [
-    {
-      "id": "2ff466b8-5e2a-4d8f-923a-a3884c7ecbc5",
-      "type": "invocation",
-      "data": {
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-        "version": "1.0.3",
-        "label": "",
-        "notes": "",
-        "type": "main_model_loader",
-        "inputs": {
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-            "label": ""
-          }
-        },
-        "isOpen": true,
-        "isIntermediate": true,
-        "useCache": true
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-      "position": {
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-        "type": "ip_adapter",
-        "inputs": {
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-            "name": "image",
-            "label": ""
-          },
-          "ip_adapter_model": {
-            "name": "ip_adapter_model",
-            "label": "IP-Adapter Model (select ip_adapter_sd15)",
-            "value": {
-              "key": "1cc210bb-4d0a-4312-b36c-b5d46c43768e",
-              "hash": "blake3:3d669dffa7471b357b4df088b99ffb6bf4d4383d5e0ef1de5ec1c89728a3d5a5",
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-              "base": "sd-1",
-              "type": "ip_adapter"
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-          },
-          "clip_vision_model": {
-            "name": "clip_vision_model",
-            "label": "",
-            "value": "ViT-H"
-          },
-          "weight": {
-            "name": "weight",
-            "label": "",
-            "value": 0.2
-          },
-          "method": {
-            "name": "method",
-            "label": "",
-            "value": "full"
-          },
-          "begin_step_percent": {
-            "name": "begin_step_percent",
-            "label": "",
-            "value": 0
-          },
-          "end_step_percent": {
-            "name": "end_step_percent",
-            "label": "",
-            "value": 1
-          },
-          "mask": {
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-            "label": ""
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-        "isOpen": true,
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-        "version": "1.3.0",
-        "label": "",
-        "notes": "",
-        "type": "l2i",
-        "inputs": {
-          "board": {
-            "name": "board",
-            "label": ""
-          },
-          "metadata": {
-            "name": "metadata",
-            "label": ""
-          },
-          "latents": {
-            "name": "latents",
-            "label": ""
-          },
-          "vae": {
-            "name": "vae",
-            "label": ""
-          },
-          "tiled": {
-            "name": "tiled",
-            "label": "",
-            "value": false
-          },
-          "tile_size": {
-            "name": "tile_size",
-            "label": "",
-            "value": 0
-          },
-          "fp32": {
-            "name": "fp32",
-            "label": "",
-            "value": false
-          }
-        },
-        "isOpen": true,
-        "isIntermediate": true,
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-        "notes": "",
-        "type": "controlnet",
-        "inputs": {
-          "image": {
-            "name": "image",
-            "label": ""
-          },
-          "control_model": {
-            "name": "control_model",
-            "label": "Control Model (select contro_v11f1e_sd15_tile)",
-            "value": {
-              "key": "773843c8-db1f-4502-8f65-59782efa7960",
-              "hash": "blake3:f0812e13758f91baf4e54b7dbb707b70642937d3b2098cd2b94cc36d3eba308e",
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-              "base": "sd-1",
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-            "value": 1
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-            "label": "",
-            "value": 0
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-          "end_step_percent": {
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-            "label": "Structural Control",
-            "value": 1
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-          "control_mode": {
-            "name": "control_mode",
-            "label": "",
-            "value": "more_control"
-          },
-          "resize_mode": {
-            "name": "resize_mode",
-            "label": "",
-            "value": "just_resize"
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-        "isOpen": true,
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-        "type": "i2l",
-        "inputs": {
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-            "name": "image",
-            "label": ""
-          },
-          "vae": {
-            "name": "vae",
-            "label": ""
-          },
-          "tiled": {
-            "name": "tiled",
-            "label": "",
-            "value": false
-          },
-          "tile_size": {
-            "name": "tile_size",
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-            "value": 0
-          },
-          "fp32": {
-            "name": "fp32",
-            "label": "",
-            "value": false
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-        "isOpen": false,
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-        "useCache": true
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-    },
-    {
-      "id": "947c3f88-0305-4695-8355-df4abac64b1c",
-      "type": "invocation",
-      "data": {
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-        "version": "1.2.0",
-        "label": "",
-        "notes": "",
-        "type": "compel",
-        "inputs": {
-          "prompt": {
-            "name": "prompt",
-            "label": "",
-            "value": ""
-          },
-          "clip": {
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-            "label": ""
-          },
-          "mask": {
-            "name": "mask",
-            "label": ""
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-        "isOpen": true,
-        "isIntermediate": true,
-        "useCache": true
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-      "position": {
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-    },
-    {
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-      "type": "invocation",
-      "data": {
-        "id": "9b2d8c58-ce8f-4162-a5a1-48de854040d6",
-        "version": "1.2.0",
-        "label": "",
-        "notes": "",
-        "type": "compel",
-        "inputs": {
-          "prompt": {
-            "name": "prompt",
-            "label": "Positive Prompt",
-            "value": ""
-          },
-          "clip": {
-            "name": "clip",
-            "label": ""
-          },
-          "mask": {
-            "name": "mask",
-            "label": ""
-          }
-        },
-        "isOpen": true,
-        "isIntermediate": true,
-        "useCache": true
-      },
-      "position": {
-        "x": -4014.4136788915944,
-        "y": -1243.5677253775948
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-    },
     {
       "id": "b875cae6-d8a3-4fdc-b969-4d53cbd03f9a",
       "type": "invocation",
@@ -489,6 +181,64 @@
         "y": 3.422855503409039
       }
     },
+    {
+      "id": "9b2d8c58-ce8f-4162-a5a1-48de854040d6",
+      "type": "invocation",
+      "data": {
+        "id": "9b2d8c58-ce8f-4162-a5a1-48de854040d6",
+        "version": "1.1.1",
+        "label": "",
+        "notes": "",
+        "type": "compel",
+        "inputs": {
+          "prompt": {
+            "name": "prompt",
+            "label": "Positive Prompt",
+            "value": ""
+          },
+          "clip": {
+            "name": "clip",
+            "label": ""
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": -4014.4136788915944,
+        "y": -1243.5677253775948
+      }
+    },
+    {
+      "id": "947c3f88-0305-4695-8355-df4abac64b1c",
+      "type": "invocation",
+      "data": {
+        "id": "947c3f88-0305-4695-8355-df4abac64b1c",
+        "version": "1.1.1",
+        "label": "",
+        "notes": "",
+        "type": "compel",
+        "inputs": {
+          "prompt": {
+            "name": "prompt",
+            "label": "",
+            "value": ""
+          },
+          "clip": {
+            "name": "clip",
+            "label": ""
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": -4014.4136788915944,
+        "y": -968.5677253775948
+      }
+    },
     {
       "id": "b3513fed-ed42-408d-b382-128fdb0de523",
       "type": "invocation",
@@ -629,6 +379,104 @@
         "y": -29.08699277598673
       }
     },
+    {
+      "id": "338b883c-3728-4f18-b3a6-6e7190c2f850",
+      "type": "invocation",
+      "data": {
+        "id": "338b883c-3728-4f18-b3a6-6e7190c2f850",
+        "version": "1.0.2",
+        "label": "",
+        "notes": "",
+        "type": "i2l",
+        "inputs": {
+          "image": {
+            "name": "image",
+            "label": ""
+          },
+          "vae": {
+            "name": "vae",
+            "label": ""
+          },
+          "tiled": {
+            "name": "tiled",
+            "label": "",
+            "value": false
+          },
+          "fp32": {
+            "name": "fp32",
+            "label": "",
+            "value": false
+          }
+        },
+        "isOpen": false,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": -2908.4791167517287,
+        "y": -408.87504820159086
+      }
+    },
+    {
+      "id": "d334f2da-016a-4524-9911-bdab85546888",
+      "type": "invocation",
+      "data": {
+        "id": "d334f2da-016a-4524-9911-bdab85546888",
+        "version": "1.1.1",
+        "label": "",
+        "notes": "",
+        "type": "controlnet",
+        "inputs": {
+          "image": {
+            "name": "image",
+            "label": ""
+          },
+          "control_model": {
+            "name": "control_model",
+            "label": "Control Model (select contro_v11f1e_sd15_tile)",
+            "value": {
+              "key": "773843c8-db1f-4502-8f65-59782efa7960",
+              "hash": "blake3:f0812e13758f91baf4e54b7dbb707b70642937d3b2098cd2b94cc36d3eba308e",
+              "name": "control_v11f1e_sd15_tile",
+              "base": "sd-1",
+              "type": "controlnet"
+            }
+          },
+          "control_weight": {
+            "name": "control_weight",
+            "label": "",
+            "value": 1
+          },
+          "begin_step_percent": {
+            "name": "begin_step_percent",
+            "label": "",
+            "value": 0
+          },
+          "end_step_percent": {
+            "name": "end_step_percent",
+            "label": "Structural Control",
+            "value": 1
+          },
+          "control_mode": {
+            "name": "control_mode",
+            "label": "",
+            "value": "more_control"
+          },
+          "resize_mode": {
+            "name": "resize_mode",
+            "label": "",
+            "value": "just_resize"
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": -2481.9569385477016,
+        "y": -181.06590482739782
+      }
+    },
     {
       "id": "1011539e-85de-4e02-a003-0b22358491b8",
       "type": "invocation",
@@ -715,6 +563,52 @@
         "y": -1006.415909408244
       }
     },
+    {
+      "id": "b76fe66f-7884-43ad-b72c-fadc81d7a73c",
+      "type": "invocation",
+      "data": {
+        "id": "b76fe66f-7884-43ad-b72c-fadc81d7a73c",
+        "version": "1.2.2",
+        "label": "",
+        "notes": "",
+        "type": "l2i",
+        "inputs": {
+          "board": {
+            "name": "board",
+            "label": ""
+          },
+          "metadata": {
+            "name": "metadata",
+            "label": ""
+          },
+          "latents": {
+            "name": "latents",
+            "label": ""
+          },
+          "vae": {
+            "name": "vae",
+            "label": ""
+          },
+          "tiled": {
+            "name": "tiled",
+            "label": "",
+            "value": false
+          },
+          "fp32": {
+            "name": "fp32",
+            "label": "",
+            "value": false
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": -1999.770193862987,
+        "y": -1075
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+    },
     {
       "id": "ab6f5dda-4b60-4ddf-99f2-f61fb5937527",
       "type": "invocation",
@@ -885,6 +779,56 @@
         "y": -78.2819050861178
       }
     },
+    {
+      "id": "287f134f-da8d-41d1-884e-5940e8f7b816",
+      "type": "invocation",
+      "data": {
+        "id": "287f134f-da8d-41d1-884e-5940e8f7b816",
+        "version": "1.2.2",
+        "label": "",
+        "notes": "",
+        "type": "ip_adapter",
+        "inputs": {
+          "image": {
+            "name": "image",
+            "label": ""
+          },
+          "ip_adapter_model": {
+            "name": "ip_adapter_model",
+            "label": "IP-Adapter Model (select ip_adapter_sd15)",
+            "value": {
+              "key": "1cc210bb-4d0a-4312-b36c-b5d46c43768e",
+              "hash": "blake3:3d669dffa7471b357b4df088b99ffb6bf4d4383d5e0ef1de5ec1c89728a3d5a5",
+              "name": "ip_adapter_sd15",
+              "base": "sd-1",
+              "type": "ip_adapter"
+            }
+          },
+          "weight": {
+            "name": "weight",
+            "label": "",
+            "value": 0.2
+          },
+          "begin_step_percent": {
+            "name": "begin_step_percent",
+            "label": "",
+            "value": 0
+          },
+          "end_step_percent": {
+            "name": "end_step_percent",
+            "label": "",
+            "value": 1
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": -2855.8555540799207,
+        "y": -183.58854843775742
+      }
+    },
     {
       "id": "1f86c8bf-06f9-4e28-abee-02f46f445ac4",
       "type": "invocation",
@@ -955,6 +899,30 @@
         "y": -41.810810454906914
       }
     },
+    {
+      "id": "2ff466b8-5e2a-4d8f-923a-a3884c7ecbc5",
+      "type": "invocation",
+      "data": {
+        "id": "2ff466b8-5e2a-4d8f-923a-a3884c7ecbc5",
+        "version": "1.0.2",
+        "label": "",
+        "notes": "",
+        "type": "main_model_loader",
+        "inputs": {
+          "model": {
+            "name": "model",
+            "label": ""
+          }
+        },
+        "isOpen": true,
+        "isIntermediate": true,
+        "useCache": true
+      },
+      "position": {
+        "x": -4514.466823162653,
+        "y": -1235.7908800002283
+      }
+    },
     {
       "id": "f5d9bf3b-2646-4b17-9894-20fd2b4218ea",
       "type": "invocation",

invokeai/app/util/step_callback.py

@@ -5,8 +5,9 @@ from PIL import Image
 
 from invokeai.app.services.session_processor.session_processor_common import CanceledException, ProgressImage
 from invokeai.backend.model_manager.config import BaseModelType
-from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState
-from invokeai.backend.util.util import image_to_dataURL
+
+from ...backend.stable_diffusion import PipelineIntermediateState
+from ...backend.util.util import image_to_dataURL
 
 if TYPE_CHECKING:
     from invokeai.app.services.events.events_base import EventServiceBase

invokeai/backend/image_util/__init__.py

@@ -2,11 +2,6 @@
 Initialization file for invokeai.backend.image_util methods.
 """
 
-from invokeai.backend.image_util.infill_methods.patchmatch import PatchMatch  # noqa: F401
-from invokeai.backend.image_util.pngwriter import (  # noqa: F401
-    PngWriter,
-    PromptFormatter,
-    retrieve_metadata,
-    write_metadata,
-)
-from invokeai.backend.image_util.util import InitImageResizer, make_grid  # noqa: F401
+from .infill_methods.patchmatch import PatchMatch  # noqa: F401
+from .pngwriter import PngWriter, PromptFormatter, retrieve_metadata, write_metadata  # noqa: F401
+from .util import InitImageResizer, make_grid  # noqa: F401

invokeai/backend/image_util/basicsr/rrdbnet_arch.py

@@ -2,7 +2,7 @@ import torch
 from torch import nn as nn
 from torch.nn import functional as F
 
-from invokeai.backend.image_util.basicsr.arch_util import default_init_weights, make_layer, pixel_unshuffle
+from .arch_util import default_init_weights, make_layer, pixel_unshuffle
 
 
 class ResidualDenseBlock(nn.Module):

invokeai/backend/image_util/depth_anything/model/dpt.py

@@ -4,7 +4,7 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
-from invokeai.backend.image_util.depth_anything.model.blocks import FeatureFusionBlock, _make_scratch
+from .blocks import FeatureFusionBlock, _make_scratch
 
 torchhub_path = Path(__file__).parent.parent / "torchhub"
 

invokeai/backend/image_util/dw_openpose/wholebody.py

@@ -8,10 +8,11 @@ import numpy as np
 import onnxruntime as ort
 
 from invokeai.app.services.config.config_default import get_config
-from invokeai.backend.image_util.dw_openpose.onnxdet import inference_detector
-from invokeai.backend.image_util.dw_openpose.onnxpose import inference_pose
 from invokeai.backend.util.devices import TorchDevice
 
+from .onnxdet import inference_detector
+from .onnxpose import inference_pose
+
 config = get_config()
 
 

invokeai/backend/image_util/lineart_anime.py

@@ -98,7 +98,7 @@ class UnetSkipConnectionBlock(nn.Module):
         """
         super(UnetSkipConnectionBlock, self).__init__()
         self.outermost = outermost
-        if isinstance(norm_layer, functools.partial):
+        if type(norm_layer) == functools.partial:
             use_bias = norm_layer.func == nn.InstanceNorm2d
         else:
             use_bias = norm_layer == nn.InstanceNorm2d

invokeai/backend/ip_adapter/ip_adapter.py

@@ -11,8 +11,9 @@ from PIL import Image
 from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
 
 from invokeai.backend.ip_adapter.ip_attention_weights import IPAttentionWeights
-from invokeai.backend.ip_adapter.resampler import Resampler
-from invokeai.backend.raw_model import RawModel
+
+from ..raw_model import RawModel
+from .resampler import Resampler
 
 
 class IPAdapterStateDict(TypedDict):
@@ -135,11 +136,11 @@ class IPAdapter(RawModel):
         self._image_proj_model.to(device=self.device, dtype=self.dtype, non_blocking=non_blocking)
         self.attn_weights.to(device=self.device, dtype=self.dtype, non_blocking=non_blocking)
 
-    def calc_size(self) -> int:
-        # HACK(ryand): Fix this issue with circular imports.
-        from invokeai.backend.model_manager.load.model_util import calc_module_size
+    def calc_size(self):
+        # workaround for circular import
+        from invokeai.backend.model_manager.load.model_util import calc_model_size_by_data
 
-        return calc_module_size(self._image_proj_model) + calc_module_size(self.attn_weights)
+        return calc_model_size_by_data(self._image_proj_model) + calc_model_size_by_data(self.attn_weights)
 
     def _init_image_proj_model(
         self, state_dict: dict[str, torch.Tensor]

invokeai/backend/lora.py

@@ -10,9 +10,10 @@ from safetensors.torch import load_file
 from typing_extensions import Self
 
 from invokeai.backend.model_manager import BaseModelType
-from invokeai.backend.raw_model import RawModel
 from invokeai.backend.util.devices import TorchDevice
 
+from .raw_model import RawModel
+
 
 class LoRALayerBase:
     # rank: Optional[int]

invokeai/backend/model_manager/__init__.py

@@ -1,6 +1,6 @@
 """Re-export frequently-used symbols from the Model Manager backend."""
 
-from invokeai.backend.model_manager.config import (
+from .config import (
     AnyModel,
     AnyModelConfig,
     BaseModelType,
@@ -13,9 +13,9 @@ from invokeai.backend.model_manager.config import (
     SchedulerPredictionType,
     SubModelType,
 )
-from invokeai.backend.model_manager.load import LoadedModel
-from invokeai.backend.model_manager.probe import ModelProbe
-from invokeai.backend.model_manager.search import ModelSearch
+from .load import LoadedModel
+from .probe import ModelProbe
+from .search import ModelSearch
 
 __all__ = [
     "AnyModel",