translationBot(ui): update translation (Spanish)

Currently translated at 30.5% (380 of 1243 strings)

Co-authored-by: gallegonovato <fran-carro@hotmail.es>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/es/
Translation: InvokeAI/Web UI

README.md

@@ -12,7 +12,7 @@
 
 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.
 
-[Installation][installation docs] - [Documentation and Tutorials][docs home] - [Bug Reports][github issues] - [Contributing][contributing docs]
+[Installation and Updates][installation docs] - [Documentation and Tutorials][docs home] - [Bug Reports][github issues] - [Contributing][contributing docs]
 
 <div align="center">
 

docs/contributing/frontend/WORKFLOWS.md

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

docs/features/CONTROLNET.md

@@ -165,7 +165,7 @@ Additionally, each  section can be expanded with the "Show Advanced" button in o
 There are several ways to install IP-Adapter models with an existing InvokeAI installation:
 
 1. Through the command line interface launched from the invoke.sh / invoke.bat scripts, option [4] to download models.
-2. Through the Model Manager UI with models from the *Tools* section of [www.models.invoke.ai](https://www.models.invoke.ai). To do this, copy the repo ID from the desired model page, and paste it in the Add Model field of the model manager. **Note** Both the IP-Adapter and the Image Encoder must be installed for IP-Adapter to work. For example, the [SD 1.5 IP-Adapter](https://models.invoke.ai/InvokeAI/ip_adapter_plus_sd15) and [SD1.5 Image Encoder](https://models.invoke.ai/InvokeAI/ip_adapter_sd_image_encoder) must be installed to use IP-Adapter with SD1.5 based models.  
+2. Through the Model Manager UI with models from the *Tools* section of [models.invoke.ai](https://models.invoke.ai). To do this, copy the repo ID from the desired model page, and paste it in the Add Model field of the model manager. **Note** Both the IP-Adapter and the Image Encoder must be installed for IP-Adapter to work. For example, the [SD 1.5 IP-Adapter](https://models.invoke.ai/InvokeAI/ip_adapter_plus_sd15) and [SD1.5 Image Encoder](https://models.invoke.ai/InvokeAI/ip_adapter_sd_image_encoder) must be installed to use IP-Adapter with SD1.5 based models.  
 3. **Advanced -- Not recommended ** Manually downloading the IP-Adapter and Image Encoder files - Image Encoder folders shouid be placed in the `models\any\clip_vision` folders. IP Adapter Model folders should be placed in the relevant `ip-adapter` folder of relevant base model folder of Invoke root directory. For example, for the SDXL IP-Adapter, files should be added to the `model/sdxl/ip_adapter/` folder. 
 
 #### Using IP-Adapter

docs/features/TRAINING.md

@@ -4,278 +4,6 @@ title: Training
 
 # :material-file-document: Training
 
-# Textual Inversion Training
-## **Personalizing Text-to-Image Generation**
+Invoke Training has moved to its own repository, with a dedicated UI for accessing common scripts like Textual Inversion and LoRA training.
 
-You may personalize the generated images to provide your own styles or objects
-by training a new LDM checkpoint and introducing a new vocabulary to the fixed
-model as a (.pt) embeddings file. Alternatively, you may use or train
-HuggingFace Concepts embeddings files (.bin) from
-<https://huggingface.co/sd-concepts-library> and its associated
-notebooks.
-
-## **Hardware and Software Requirements**
-
-You will need a GPU to perform training in a reasonable length of
-time, and at least 12 GB of VRAM. We recommend using the [`xformers`
-library](../installation/070_INSTALL_XFORMERS.md) to accelerate the
-training process further. During training, about ~8 GB is temporarily
-needed in order to store intermediate models, checkpoints and logs.
-
-## **Preparing for Training**
-
-To train, prepare a folder that contains 3-5 images that illustrate
-the object or concept. It is good to provide a variety of examples or
-poses to avoid overtraining the system. Format these images as PNG
-(preferred) or JPG. You do not need to resize or crop the images in
-advance, but for more control you may wish to do so.
-
-Place the training images in a directory on the machine InvokeAI runs
-on. We recommend placing them in a subdirectory of the
-`text-inversion-training-data` folder located in the InvokeAI root
-directory, ordinarily `~/invokeai` (Linux/Mac), or
-`C:\Users\your_name\invokeai` (Windows). For example, to create an
-embedding for the "psychedelic" style, you'd place the training images
-into the directory
-`~invokeai/text-inversion-training-data/psychedelic`.
-
-## **Launching Training Using the Console Front End**
-
-InvokeAI 2.3 and higher comes with a text console-based training front
-end. From within the `invoke.sh`/`invoke.bat` Invoke launcher script,
-start training tool selecting choice (3):
-
-```sh
-1 "Generate images with a browser-based interface"
-2 "Explore InvokeAI nodes using a command-line interface"
-3 "Textual inversion training"
-4 "Merge models (diffusers type only)"
-5 "Download and install models"
-6 "Change InvokeAI startup options"
-7 "Re-run the configure script to fix a broken install or to complete a major upgrade"
-8 "Open the developer console"
-9 "Update InvokeAI"
-```
-
-Alternatively, you can select option (8) or from the command line, with the InvokeAI virtual environment active,
-you can then launch the front end with the command `invokeai-ti --gui`.
-
-This will launch a text-based front end that will look like this:
-
-<figure markdown>
-![ti-frontend](../assets/textual-inversion/ti-frontend.png)
-</figure>
-
-The interface is keyboard-based. Move from field to field using
-control-N (^N) to move to the next field and control-P (^P) to the
-previous one. <Tab> and <shift-TAB> work as well. Once a field is
-active, use the cursor keys. In a checkbox group, use the up and down
-cursor keys to move from choice to choice, and <space> to select a
-choice. In a scrollbar, use the left and right cursor keys to increase
-and decrease the value of the scroll. In textfields, type the desired
-values.
-
-The number of parameters may look intimidating, but in most cases the
-predefined defaults work fine. The red circled fields in the above
-illustration are the ones you will adjust most frequently.
-
-### Model Name
-
-This will list all the diffusers models that are currently
-installed. Select the one you wish to use as the basis for your
-embedding. Be aware that if you use a SD-1.X-based model for your
-training, you will only be able to use this embedding with other
-SD-1.X-based models. Similarly, if you train on SD-2.X, you will only
-be able to use the embeddings with models based on SD-2.X.
-
-### Trigger Term
-
-This is the prompt term you will use to trigger the embedding. Type a
-single word or phrase you wish to use as the trigger, example
-"psychedelic" (without angle brackets). Within InvokeAI, you will then
-be able to activate the trigger using the syntax `<psychedelic>`.
-
-### Initializer
-
-This is a single character that is used internally during the training
-process as a placeholder for the trigger term. It defaults to "*" and
-can usually be left alone.
-
-### Resume from last saved checkpoint
-
-As training proceeds, textual inversion will write a series of
-intermediate files that can be used to resume training from where it
-was left off in the case of an interruption. This checkbox will be
-automatically selected if you provide a previously used trigger term
-and at least one checkpoint file is found on disk.
-
-Note that as of 20 January 2023, resume does not seem to be working
-properly due to an issue with the upstream code.
-
-### Data Training Directory
-
-This is the location of the images to be used for training. When you
-select a trigger term like "my-trigger", the frontend will prepopulate
-this field with `~/invokeai/text-inversion-training-data/my-trigger`,
-but you can change the path to wherever you want.
-
-### Output Destination Directory
-
-This is the location of the logs, checkpoint files, and embedding
-files created during training. When you select a trigger term like
-"my-trigger", the frontend will prepopulate this field with
-`~/invokeai/text-inversion-output/my-trigger`, but you can change the
-path to wherever you want.
-
-### Image resolution
-
-The images in the training directory will be automatically scaled to
-the value you use here. For best results, you will want to use the
-same default resolution of the underlying model (512 pixels for
-SD-1.5, 768 for the larger version of SD-2.1).
-
-### Center crop images
-
-If this is selected, your images will be center cropped to make them
-square before resizing them to the desired resolution. Center cropping
-can indiscriminately cut off the top of subjects' heads for portrait
-aspect images, so if you have images like this, you may wish to use a
-photoeditor to manually crop them to a square aspect ratio.
-
-### Mixed precision
-
-Select the floating point precision for the embedding. "no" will
-result in a full 32-bit precision, "fp16" will provide 16-bit
-precision, and "bf16" will provide mixed precision (only available
-when XFormers is used).
-
-### Max training steps
-
-How many steps the training will take before the model converges. Most
-training sets will converge with 2000-3000 steps.
-
-### Batch size
-
-This adjusts how many training images are processed simultaneously in
-each step. Higher values will cause the training process to run more
-quickly, but use more memory. The default size will run with GPUs with
-as little as 12 GB.
-
-### Learning rate
-
-The rate at which the system adjusts its internal weights during
-training. Higher values risk overtraining (getting the same image each
-time), and lower values will take more steps to train a good
-model. The default of 0.0005 is conservative; you may wish to increase
-it to 0.005 to speed up training.
-
-### Scale learning rate by number of GPUs, steps and batch size
-
-If this is selected (the default) the system will adjust the provided
-learning rate to improve performance.
-
-### Use xformers acceleration
-
-This will activate XFormers memory-efficient attention. You need to
-have XFormers installed for this to have an effect.
-
-### Learning rate scheduler
-
-This adjusts how the learning rate changes over the course of
-training. The default "constant" means to use a constant learning rate
-for the entire training session. The other values scale the learning
-rate according to various formulas.
-
-Only "constant" is supported by the XFormers library.
-
-### Gradient accumulation steps
-
-This is a parameter that allows you to use bigger batch sizes than
-your GPU's VRAM would ordinarily accommodate, at the cost of some
-performance.
-
-### Warmup steps
-
-If "constant_with_warmup" is selected in the learning rate scheduler,
-then this provides the number of warmup steps. Warmup steps have a
-very low learning rate, and are one way of preventing early
-overtraining.
-
-## The training run
-
-Start the training run by advancing to the OK button (bottom right)
-and pressing <enter>. A series of progress messages will be displayed
-as the training process proceeds. This may take an hour or two,
-depending on settings and the speed of your system. Various log and
-checkpoint files will be written into the output directory (ordinarily
-`~/invokeai/text-inversion-output/my-model/`)
-
-At the end of successful training, the system will copy the file
-`learned_embeds.bin` into the InvokeAI root directory's `embeddings`
-directory, using a subdirectory named after the trigger token. For
-example, if the trigger token was `psychedelic`, then look for the
-embeddings file in
-`~/invokeai/embeddings/psychedelic/learned_embeds.bin`
-
-You may now launch InvokeAI and try out a prompt that uses the trigger
-term. For example `a plate of banana sushi in <psychedelic> style`.
-
-## **Training with the Command-Line Script**
-
-Training can also be done using a traditional command-line script. It
-can be launched from within the "developer's console", or from the
-command line after activating InvokeAI's virtual environment.
-
-It accepts a large number of arguments, which can be summarized by
-passing the `--help` argument:
-
-```sh
-invokeai-ti --help
-```
-
-Typical usage is shown here:
-```sh
-invokeai-ti \
-       --model=stable-diffusion-1.5 \
-       --resolution=512 \
-       --learnable_property=style \
-       --initializer_token='*' \
-       --placeholder_token='<psychedelic>' \
-       --train_data_dir=/home/lstein/invokeai/training-data/psychedelic \
-       --output_dir=/home/lstein/invokeai/text-inversion-training/psychedelic \
-       --scale_lr \
-       --train_batch_size=8 \
-       --gradient_accumulation_steps=4 \
-       --max_train_steps=3000 \
-       --learning_rate=0.0005 \
-       --resume_from_checkpoint=latest \
-       --lr_scheduler=constant \
-       --mixed_precision=fp16 \
-       --only_save_embeds
-```
-
-## Troubleshooting
-
-### `Cannot load embedding for <trigger>. It was trained on a model with token dimension 1024, but the current model has token dimension 768`
-
-Messages like this indicate you trained the embedding on a different base model than the currently selected one.
-
-For example, in the error above, the training was done on SD2.1 (768x768) but it was used on SD1.5 (512x512).
-
-## Reading
-
-For more information on textual inversion, please see the following
-resources:
-
-* The [textual inversion repository](https://github.com/rinongal/textual_inversion) and
-  associated paper for details and limitations.
-* [HuggingFace's textual inversion training
-  page](https://huggingface.co/docs/diffusers/training/text_inversion)
-* [HuggingFace example script
-  documentation](https://github.com/huggingface/diffusers/tree/main/examples/textual_inversion)
-  (Note that this script is similar to, but not identical, to
-  `textual_inversion`, but produces embed files that are completely compatible.
-
----
-
-copyright (c) 2023, Lincoln Stein and the InvokeAI Development Team
+You can find more by visiting the repo at https://github.com/invoke-ai/invoke-training

docs/installation/010_INSTALL_AUTOMATED.md

@@ -1,8 +1,10 @@
-# Automatic Install
+# Automatic Install & Updates
 
-The installer is used for both new installs and updates.
+**The same packaged installer file can be used for both new installs and updates.**
+Using the installer for updates will leave everything you've added since installation, and just update the core libraries used to run Invoke.
+Simply use the same path you installed to originally.
 
-Both release and pre-release versions can be installed using it. It also supports install a wheel if needed.
+Both release and pre-release versions can be installed using the installer. It also supports install through a wheel if needed.
 
 Be sure to review the [installation requirements] and ensure your system has everything it needs to install Invoke.
 
@@ -96,7 +98,7 @@ Updating is exactly the same as installing - download the latest installer, choo
 
 If you have installation issues, please review the [FAQ]. You can also [create an issue] or ask for help on [discord].
 
-[installation requirements]: INSTALLATION.md#installation-requirements
+[installation requirements]: INSTALL_REQUIREMENTS.md
 [FAQ]: ../help/FAQ.md
 [install some models]: 050_INSTALLING_MODELS.md
 [configuration docs]: ../features/CONFIGURATION.md

docs/installation/020_INSTALL_MANUAL.md

@@ -10,7 +10,7 @@ InvokeAI is distributed as a python package on PyPI, installable with `pip`. The
 
 ### Requirements
 
-Before you start, go through the [installation requirements].
+Before you start, go through the [installation requirements](./INSTALL_REQUIREMENTS.md).
 
 ### Installation Walkthrough
 
@@ -79,7 +79,7 @@ Before you start, go through the [installation requirements].
 
 1. Install the InvokeAI Package. The base command is `pip install InvokeAI --use-pep517`, but you may need to change this depending on your system and the desired features.
 
-    - You may need to provide an [extra index URL]. Select your platform configuration using [this tool on the PyTorch website]. Copy the `--extra-index-url` string from this and append it to your install command.
+    - You may need to provide an [extra index URL](https://pip.pypa.io/en/stable/cli/pip_install/#cmdoption-extra-index-url). Select your platform configuration using [this tool on the PyTorch website](https://pytorch.org/get-started/locally/). Copy the `--extra-index-url` string from this and append it to your install command.
 
         !!! example "Install with an extra index URL"
 
@@ -116,4 +116,4 @@ Before you start, go through the [installation requirements].
 
     !!! warning
 
-        If the virtual environment is _not_ inside the root directory, then you _must_ specify the path to the root directory with `--root_dir \path\to\invokeai` or the `INVOKEAI_ROOT` environment variable.
+        If the virtual environment is _not_ inside the root directory, then you _must_ specify the path to the root directory with `--root \path\to\invokeai` or the `INVOKEAI_ROOT` environment variable.

docs/installation/INSTALLATION.md

@@ -1,4 +1,4 @@
-# Installation Overview
+# Installation and Updating Overview
 
 Before installing, review the [installation requirements] to ensure your system is set up properly.
 
@@ -6,14 +6,21 @@ See the [FAQ] for frequently-encountered installation issues.
 
 If you need more help, join our [discord] or [create an issue].
 
-<h2>Automatic Install</h2>
+<h2>Automatic Install & Updates </h2>
 
 ✅ The automatic install is the best way to run InvokeAI. Check out the [installation guide] to get started.
 
+⬆️ The same installer is also the best way to update InvokeAI - Simply rerun it for the same folder you installed to.
+
+The installation process simply manages installation for the core libraries & application dependencies that run Invoke.
+Any models, images, or other assets in the Invoke root folder won't be affected by the installation process.
+
 <h2>Manual Install</h2>
 
 If you are familiar with python and want more control over the packages that are installed, you can [install InvokeAI manually via PyPI].
 
+Updates are managed by reinstalling the latest version through PyPi.
+
 <h2>Developer Install</h2>
 
 If you want to contribute to InvokeAI, consult the [developer install guide].

docs/installation/INSTALL_REQUIREMENTS.md

@@ -37,13 +37,13 @@ Invoke runs best with a dedicated GPU, but will fall back to running on CPU, alb
     === "Nvidia"
 
         ```
-        Any GPU with at least 8GB VRAM. Linux only.
+        Any GPU with at least 8GB VRAM.
         ```
 
     === "AMD"
 
         ```
-        Any GPU with at least 16GB VRAM.
+        Any GPU with at least 16GB VRAM. Linux only.
         ```
 
     === "Mac"

installer/templates/invoke.bat.in

@@ -10,8 +10,7 @@ set INVOKEAI_ROOT=.
 echo Desired action:
 echo 1. Generate images with the browser-based interface
 echo 2. Open the developer console
-echo 3. Run the InvokeAI image database maintenance script
-echo 4. Command-line help
+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.
@@ -34,9 +33,6 @@ IF /I "%choice%" == "1" (
     echo *** Type `exit` to quit this shell and deactivate the Python virtual environment ***
     call cmd /k
 ) ELSE IF /I "%choice%" == "3" (
-   echo Running the db maintenance script...
-   python .venv\Scripts\invokeai-db-maintenance.exe
-) ELSE IF /I "%choice%" == "4" (
     echo Displaying command line help...
     python .venv\Scripts\invokeai-web.exe --help %*
     pause

installer/templates/invoke.sh.in

@@ -47,11 +47,6 @@ do_choice() {
         bash --init-file "$file_name"
         ;;
     3)
-        clear
-        printf "Running the db maintenance script\n"
-        invokeai-db-maintenance --root ${INVOKEAI_ROOT}
-        ;;
-    4)
         clear
         printf "Command-line help\n"
         invokeai-web --help
@@ -71,8 +66,7 @@ do_line_input() {
     printf "What would you like to do?\n"
     printf "1: Generate images using the browser-based interface\n"
     printf "2: Open the developer console\n"
-    printf "3: Run the InvokeAI image database maintenance script\n"
-    printf "4: Command-line help\n"
+    printf "3: Command-line help\n"
     printf "Q: Quit\n\n"
     printf "To update, download and run the installer from https://github.com/invoke-ai/InvokeAI/releases/latest.\n\n"
     read -p "Please enter 1-4, Q: [1] " yn

invokeai/app/api/routers/app_info.py

@@ -13,7 +13,6 @@ from pydantic import BaseModel, Field
 from invokeai.app.invocations.upscale import ESRGAN_MODELS
 from invokeai.app.services.invocation_cache.invocation_cache_common import InvocationCacheStatus
 from invokeai.backend.image_util.infill_methods.patchmatch import PatchMatch
-from invokeai.backend.image_util.safety_checker import SafetyChecker
 from invokeai.backend.util.logging import logging
 from invokeai.version import __version__
 
@@ -109,9 +108,7 @@ async def get_config() -> AppConfig:
         upscaling_models.append(str(Path(model).stem))
     upscaler = Upscaler(upscaling_method="esrgan", upscaling_models=upscaling_models)
 
-    nsfw_methods = []
-    if SafetyChecker.safety_checker_available():
-        nsfw_methods.append("nsfw_checker")
+    nsfw_methods = ["nsfw_checker"]
 
     watermarking_methods = ["invisible_watermark"]
 

invokeai/app/api/routers/images.py

@@ -6,13 +6,12 @@ from fastapi import BackgroundTasks, Body, HTTPException, Path, Query, Request,
 from fastapi.responses import FileResponse
 from fastapi.routing import APIRouter
 from PIL import Image
-from pydantic import BaseModel, Field, ValidationError
+from pydantic import BaseModel, Field, JsonValue
 
-from invokeai.app.invocations.fields import MetadataField, MetadataFieldValidator
+from invokeai.app.invocations.fields import MetadataField
 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.workflow_records.workflow_records_common import WorkflowWithoutID, WorkflowWithoutIDValidator
 
 from ..dependencies import ApiDependencies
 
@@ -42,13 +41,17 @@ async def upload_image(
     board_id: Optional[str] = Query(default=None, description="The board to add this image to, if any"),
     session_id: Optional[str] = Query(default=None, description="The session ID associated with this upload, if any"),
     crop_visible: Optional[bool] = Query(default=False, description="Whether to crop the image"),
+    metadata: Optional[JsonValue] = Body(
+        default=None, description="The metadata to associate with the image", embed=True
+    ),
 ) -> ImageDTO:
     """Uploads an image"""
     if not file.content_type or not file.content_type.startswith("image"):
         raise HTTPException(status_code=415, detail="Not an image")
 
-    metadata = None
-    workflow = None
+    _metadata = None
+    _workflow = None
+    _graph = None
 
     contents = await file.read()
     try:
@@ -62,22 +65,28 @@ async def upload_image(
 
     # TODO: retain non-invokeai metadata on upload?
     # attempt to parse metadata from image
-    metadata_raw = pil_image.info.get("invokeai_metadata", None)
-    if metadata_raw:
-        try:
-            metadata = MetadataFieldValidator.validate_json(metadata_raw)
-        except ValidationError:
-            ApiDependencies.invoker.services.logger.warn("Failed to parse metadata for uploaded image")
-            pass
+    metadata_raw = metadata if isinstance(metadata, str) else pil_image.info.get("invokeai_metadata", None)
+    if isinstance(metadata_raw, str):
+        _metadata = metadata_raw
+    else:
+        ApiDependencies.invoker.services.logger.debug("Failed to parse metadata for uploaded image")
+        pass
 
     # attempt to parse workflow from image
     workflow_raw = pil_image.info.get("invokeai_workflow", None)
-    if workflow_raw is not None:
-        try:
-            workflow = WorkflowWithoutIDValidator.validate_json(workflow_raw)
-        except ValidationError:
-            ApiDependencies.invoker.services.logger.warn("Failed to parse metadata for uploaded image")
-            pass
+    if isinstance(workflow_raw, str):
+        _workflow = workflow_raw
+    else:
+        ApiDependencies.invoker.services.logger.debug("Failed to parse workflow for uploaded image")
+        pass
+
+    # attempt to extract graph from image
+    graph_raw = pil_image.info.get("invokeai_graph", None)
+    if isinstance(graph_raw, str):
+        _graph = graph_raw
+    else:
+        ApiDependencies.invoker.services.logger.debug("Failed to parse graph for uploaded image")
+        pass
 
     try:
         image_dto = ApiDependencies.invoker.services.images.create(
@@ -86,8 +95,9 @@ async def upload_image(
             image_category=image_category,
             session_id=session_id,
             board_id=board_id,
-            metadata=metadata,
-            workflow=workflow,
+            metadata=_metadata,
+            workflow=_workflow,
+            graph=_graph,
             is_intermediate=is_intermediate,
         )
 
@@ -185,14 +195,21 @@ async def get_image_metadata(
         raise HTTPException(status_code=404)
 
 
+class WorkflowAndGraphResponse(BaseModel):
+    workflow: Optional[str] = Field(description="The workflow used to generate the image, as stringified JSON")
+    graph: Optional[str] = Field(description="The graph used to generate the image, as stringified JSON")
+
+
 @images_router.get(
-    "/i/{image_name}/workflow", operation_id="get_image_workflow", response_model=Optional[WorkflowWithoutID]
+    "/i/{image_name}/workflow", operation_id="get_image_workflow", response_model=WorkflowAndGraphResponse
 )
 async def get_image_workflow(
     image_name: str = Path(description="The name of image whose workflow to get"),
-) -> Optional[WorkflowWithoutID]:
+) -> WorkflowAndGraphResponse:
     try:
-        return ApiDependencies.invoker.services.images.get_workflow(image_name)
+        workflow = ApiDependencies.invoker.services.images.get_workflow(image_name)
+        graph = ApiDependencies.invoker.services.images.get_graph(image_name)
+        return WorkflowAndGraphResponse(workflow=workflow, graph=graph)
     except Exception:
         raise HTTPException(status_code=404)
 

invokeai/app/api/routers/model_manager.py

@@ -6,7 +6,7 @@ import pathlib
 import shutil
 import traceback
 from copy import deepcopy
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Type
 
 from fastapi import Body, Path, Query, Response, UploadFile
 from fastapi.responses import FileResponse
@@ -16,6 +16,7 @@ from pydantic import AnyHttpUrl, BaseModel, ConfigDict, Field
 from starlette.exceptions import HTTPException
 from typing_extensions import Annotated
 
+from invokeai.app.services.model_images.model_images_common import ModelImageFileNotFoundException
 from invokeai.app.services.model_install import ModelInstallJob
 from invokeai.app.services.model_records import (
     DuplicateModelException,
@@ -52,6 +53,13 @@ class ModelsList(BaseModel):
     model_config = ConfigDict(use_enum_values=True)
 
 
+def add_cover_image_to_model_config(config: AnyModelConfig, dependencies: Type[ApiDependencies]) -> AnyModelConfig:
+    """Add a cover image URL to a model configuration."""
+    cover_image = dependencies.invoker.services.model_images.get_url(config.key)
+    config.cover_image = cover_image
+    return config
+
+
 ##############################################################################
 # These are example inputs and outputs that are used in places where Swagger
 # is unable to generate a correct example.
@@ -118,8 +126,7 @@ async def list_model_records(
             record_store.search_by_attr(model_type=model_type, model_name=model_name, model_format=model_format)
         )
     for model in found_models:
-        cover_image = ApiDependencies.invoker.services.model_images.get_url(model.key)
-        model.cover_image = cover_image
+        model = add_cover_image_to_model_config(model, ApiDependencies)
     return ModelsList(models=found_models)
 
 
@@ -160,12 +167,9 @@ async def get_model_record(
     key: str = Path(description="Key of the model record to fetch."),
 ) -> AnyModelConfig:
     """Get a model record"""
-    record_store = ApiDependencies.invoker.services.model_manager.store
     try:
-        config: AnyModelConfig = record_store.get_model(key)
-        cover_image = ApiDependencies.invoker.services.model_images.get_url(key)
-        config.cover_image = cover_image
-        return config
+        config = ApiDependencies.invoker.services.model_manager.store.get_model(key)
+        return add_cover_image_to_model_config(config, ApiDependencies)
     except UnknownModelException as e:
         raise HTTPException(status_code=404, detail=str(e))
 
@@ -294,14 +298,15 @@ async def update_model_record(
     installer = ApiDependencies.invoker.services.model_manager.install
     try:
         record_store.update_model(key, changes=changes)
-        model_response: AnyModelConfig = installer.sync_model_path(key)
+        config = installer.sync_model_path(key)
+        config = add_cover_image_to_model_config(config, ApiDependencies)
         logger.info(f"Updated model: {key}")
     except UnknownModelException as e:
         raise HTTPException(status_code=404, detail=str(e))
     except ValueError as e:
         logger.error(str(e))
         raise HTTPException(status_code=409, detail=str(e))
-    return model_response
+    return config
 
 
 @model_manager_router.get(
@@ -648,6 +653,14 @@ async def convert_model(
         logger.error(str(e))
         raise HTTPException(status_code=409, detail=str(e))
 
+    # Update the model image if the model had one
+    try:
+        model_image = ApiDependencies.invoker.services.model_images.get(key)
+        ApiDependencies.invoker.services.model_images.save(model_image, new_key)
+        ApiDependencies.invoker.services.model_images.delete(key)
+    except ModelImageFileNotFoundException:
+        pass
+
     # delete the original safetensors file
     installer.delete(key)
 
@@ -655,7 +668,8 @@ async def convert_model(
     shutil.rmtree(cache_path)
 
     # return the config record for the new diffusers directory
-    new_config: AnyModelConfig = store.get_model(new_key)
+    new_config = store.get_model(new_key)
+    new_config = add_cover_image_to_model_config(new_config, ApiDependencies)
     return new_config
 
 

invokeai/app/api_app.py

@@ -164,6 +164,12 @@ def custom_openapi() -> dict[str, Any]:
     for schema_key, schema_json in additional_schemas[1]["$defs"].items():
         openapi_schema["components"]["schemas"][schema_key] = schema_json
 
+    openapi_schema["components"]["schemas"]["InvocationOutputMap"] = {
+        "type": "object",
+        "properties": {},
+        "required": [],
+    }
+
     # Add a reference to the output type to additionalProperties of the invoker schema
     for invoker in all_invocations:
         invoker_name = invoker.__name__  # type: ignore [attr-defined] # this is a valid attribute
@@ -172,6 +178,8 @@ def custom_openapi() -> dict[str, Any]:
         invoker_schema = openapi_schema["components"]["schemas"][f"{invoker_name}"]
         outputs_ref = {"$ref": f"#/components/schemas/{output_type_title}"}
         invoker_schema["output"] = outputs_ref
+        openapi_schema["components"]["schemas"]["InvocationOutputMap"]["properties"][invoker.get_type()] = outputs_ref
+        openapi_schema["components"]["schemas"]["InvocationOutputMap"]["required"].append(invoker.get_type())
         invoker_schema["class"] = "invocation"
 
     # This code no longer seems to be necessary?

invokeai/app/invocations/controlnet_image_processors.py

@@ -24,7 +24,6 @@ from pydantic import BaseModel, Field, field_validator, model_validator
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
     ImageField,
-    Input,
     InputField,
     OutputField,
     UIType,
@@ -80,13 +79,13 @@ class ControlOutput(BaseInvocationOutput):
     control: ControlField = OutputField(description=FieldDescriptions.control)
 
 
-@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.1")
+@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.2")
 class ControlNetInvocation(BaseInvocation):
     """Collects ControlNet info to pass to other nodes"""
 
     image: ImageField = InputField(description="The control image")
     control_model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.controlnet_model, input=Input.Direct, ui_type=UIType.ControlNetModel
+        description=FieldDescriptions.controlnet_model, ui_type=UIType.ControlNetModel
     )
     control_weight: Union[float, List[float]] = InputField(
         default=1.0, ge=-1, le=2, description="The weight given to the ControlNet"

invokeai/app/invocations/image.py

@@ -1,6 +1,5 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-from pathlib import Path
 from typing import Literal, Optional
 
 import cv2
@@ -504,7 +503,7 @@ class ImageInverseLerpInvocation(BaseInvocation, WithMetadata, WithBoard):
     title="Blur NSFW Image",
     tags=["image", "nsfw"],
     category="image",
-    version="1.2.2",
+    version="1.2.3",
 )
 class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata, WithBoard):
     """Add blur to NSFW-flagged images"""
@@ -516,23 +515,12 @@ class ImageNSFWBlurInvocation(BaseInvocation, WithMetadata, WithBoard):
 
         logger = context.logger
         logger.debug("Running NSFW checker")
-        if SafetyChecker.has_nsfw_concept(image):
-            logger.info("A potentially NSFW image has been detected. Image will be blurred.")
-            blurry_image = image.filter(filter=ImageFilter.GaussianBlur(radius=32))
-            caution = self._get_caution_img()
-            blurry_image.paste(caution, (0, 0), caution)
-            image = blurry_image
+        image = SafetyChecker.blur_if_nsfw(image)
 
         image_dto = context.images.save(image=image)
 
         return ImageOutput.build(image_dto)
 
-    def _get_caution_img(self) -> Image.Image:
-        import invokeai.app.assets.images as image_assets
-
-        caution = Image.open(Path(image_assets.__path__[0]) / "caution.png")
-        return caution.resize((caution.width // 2, caution.height // 2))
-
 
 @invocation(
     "img_watermark",

invokeai/app/invocations/ip_adapter.py

@@ -5,7 +5,7 @@ from pydantic import BaseModel, Field, field_validator, model_validator
 from typing_extensions import Self
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
-from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, TensorField, UIType
+from invokeai.app.invocations.fields import FieldDescriptions, InputField, OutputField, TensorField, UIType
 from invokeai.app.invocations.model import ModelIdentifierField
 from invokeai.app.invocations.primitives import ImageField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
@@ -58,7 +58,7 @@ class IPAdapterOutput(BaseInvocationOutput):
 CLIP_VISION_MODEL_MAP = {"ViT-H": "ip_adapter_sd_image_encoder", "ViT-G": "ip_adapter_sdxl_image_encoder"}
 
 
-@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.4.0")
+@invocation("ip_adapter", title="IP-Adapter", tags=["ip_adapter", "control"], category="ip_adapter", version="1.4.1")
 class IPAdapterInvocation(BaseInvocation):
     """Collects IP-Adapter info to pass to other nodes."""
 
@@ -67,7 +67,6 @@ class IPAdapterInvocation(BaseInvocation):
     ip_adapter_model: ModelIdentifierField = InputField(
         description="The IP-Adapter model.",
         title="IP-Adapter Model",
-        input=Input.Direct,
         ui_order=-1,
         ui_type=UIType.IPAdapterModel,
     )

invokeai/app/invocations/latent.py

@@ -586,13 +586,6 @@ class DenoiseLatentsInvocation(BaseInvocation):
         unet: UNet2DConditionModel,
         scheduler: Scheduler,
     ) -> StableDiffusionGeneratorPipeline:
-        # TODO:
-        # configure_model_padding(
-        #    unet,
-        #    self.seamless,
-        #    self.seamless_axes,
-        # )
-
         class FakeVae:
             class FakeVaeConfig:
                 def __init__(self) -> None:

invokeai/app/invocations/model.py

@@ -11,6 +11,7 @@ from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType,
 from .baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
+    Classification,
     invocation,
     invocation_output,
 )
@@ -93,19 +94,46 @@ class ModelLoaderOutput(UNetOutput, CLIPOutput, VAEOutput):
     pass
 
 
+@invocation_output("model_identifier_output")
+class ModelIdentifierOutput(BaseInvocationOutput):
+    """Model identifier output"""
+
+    model: ModelIdentifierField = OutputField(description="Model identifier", title="Model")
+
+
+@invocation(
+    "model_identifier",
+    title="Model identifier",
+    tags=["model"],
+    category="model",
+    version="1.0.0",
+    classification=Classification.Prototype,
+)
+class ModelIdentifierInvocation(BaseInvocation):
+    """Selects any model, outputting it its identifier. Be careful with this one! The identifier will be accepted as
+    input for any model, even if the model types don't match. If you connect this to a mismatched input, you'll get an
+    error."""
+
+    model: ModelIdentifierField = InputField(description="The model to select", title="Model")
+
+    def invoke(self, context: InvocationContext) -> ModelIdentifierOutput:
+        if not context.models.exists(self.model.key):
+            raise Exception(f"Unknown model {self.model.key}")
+
+        return ModelIdentifierOutput(model=self.model)
+
+
 @invocation(
     "main_model_loader",
     title="Main Model",
     tags=["model"],
     category="model",
-    version="1.0.2",
+    version="1.0.3",
 )
 class MainModelLoaderInvocation(BaseInvocation):
     """Loads a main model, outputting its submodels."""
 
-    model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.main_model, input=Input.Direct, ui_type=UIType.MainModel
-    )
+    model: ModelIdentifierField = InputField(description=FieldDescriptions.main_model, ui_type=UIType.MainModel)
     # TODO: precision?
 
     def invoke(self, context: InvocationContext) -> ModelLoaderOutput:
@@ -134,12 +162,12 @@ class LoRALoaderOutput(BaseInvocationOutput):
     clip: Optional[CLIPField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
 
 
-@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.2")
+@invocation("lora_loader", title="LoRA", tags=["model"], category="model", version="1.0.3")
 class LoRALoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
     lora: ModelIdentifierField = InputField(
-        description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA", ui_type=UIType.LoRAModel
+        description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
     )
     weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
     unet: Optional[UNetField] = InputField(
@@ -190,6 +218,75 @@ class LoRALoaderInvocation(BaseInvocation):
         return output
 
 
+@invocation_output("lora_selector_output")
+class LoRASelectorOutput(BaseInvocationOutput):
+    """Model loader output"""
+
+    lora: LoRAField = OutputField(description="LoRA model and weight", title="LoRA")
+
+
+@invocation("lora_selector", title="LoRA Selector", tags=["model"], category="model", version="1.0.1")
+class LoRASelectorInvocation(BaseInvocation):
+    """Selects a LoRA model and weight."""
+
+    lora: ModelIdentifierField = InputField(
+        description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
+    )
+    weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
+
+    def invoke(self, context: InvocationContext) -> LoRASelectorOutput:
+        return LoRASelectorOutput(lora=LoRAField(lora=self.lora, weight=self.weight))
+
+
+@invocation("lora_collection_loader", title="LoRA Collection Loader", tags=["model"], category="model", version="1.0.0")
+class LoRACollectionLoader(BaseInvocation):
+    """Applies a collection of LoRAs to the provided UNet and CLIP models."""
+
+    loras: LoRAField | list[LoRAField] = InputField(
+        description="LoRA models and weights. May be a single LoRA or collection.", title="LoRAs"
+    )
+    unet: Optional[UNetField] = InputField(
+        default=None,
+        description=FieldDescriptions.unet,
+        input=Input.Connection,
+        title="UNet",
+    )
+    clip: Optional[CLIPField] = InputField(
+        default=None,
+        description=FieldDescriptions.clip,
+        input=Input.Connection,
+        title="CLIP",
+    )
+
+    def invoke(self, context: InvocationContext) -> LoRALoaderOutput:
+        output = LoRALoaderOutput()
+        loras = self.loras if isinstance(self.loras, list) else [self.loras]
+        added_loras: list[str] = []
+
+        for lora in loras:
+            if lora.lora.key in added_loras:
+                continue
+
+            if not context.models.exists(lora.lora.key):
+                raise Exception(f"Unknown lora: {lora.lora.key}!")
+
+            assert lora.lora.base in (BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2)
+
+            added_loras.append(lora.lora.key)
+
+            if self.unet is not None:
+                if output.unet is None:
+                    output.unet = self.unet.model_copy(deep=True)
+                output.unet.loras.append(lora)
+
+            if self.clip is not None:
+                if output.clip is None:
+                    output.clip = self.clip.model_copy(deep=True)
+                output.clip.loras.append(lora)
+
+        return output
+
+
 @invocation_output("sdxl_lora_loader_output")
 class SDXLLoRALoaderOutput(BaseInvocationOutput):
     """SDXL LoRA Loader Output"""
@@ -204,13 +301,13 @@ class SDXLLoRALoaderOutput(BaseInvocationOutput):
     title="SDXL LoRA",
     tags=["lora", "model"],
     category="model",
-    version="1.0.2",
+    version="1.0.3",
 )
 class SDXLLoRALoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
     lora: ModelIdentifierField = InputField(
-        description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA", ui_type=UIType.LoRAModel
+        description=FieldDescriptions.lora_model, title="LoRA", ui_type=UIType.LoRAModel
     )
     weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
     unet: Optional[UNetField] = InputField(
@@ -279,12 +376,78 @@ class SDXLLoRALoaderInvocation(BaseInvocation):
         return output
 
 
-@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.2")
+@invocation(
+    "sdxl_lora_collection_loader",
+    title="SDXL LoRA Collection Loader",
+    tags=["model"],
+    category="model",
+    version="1.0.0",
+)
+class SDXLLoRACollectionLoader(BaseInvocation):
+    """Applies a collection of SDXL LoRAs to the provided UNet and CLIP models."""
+
+    loras: LoRAField | list[LoRAField] = InputField(
+        description="LoRA models and weights. May be a single LoRA or collection.", title="LoRAs"
+    )
+    unet: Optional[UNetField] = InputField(
+        default=None,
+        description=FieldDescriptions.unet,
+        input=Input.Connection,
+        title="UNet",
+    )
+    clip: Optional[CLIPField] = InputField(
+        default=None,
+        description=FieldDescriptions.clip,
+        input=Input.Connection,
+        title="CLIP",
+    )
+    clip2: Optional[CLIPField] = InputField(
+        default=None,
+        description=FieldDescriptions.clip,
+        input=Input.Connection,
+        title="CLIP 2",
+    )
+
+    def invoke(self, context: InvocationContext) -> SDXLLoRALoaderOutput:
+        output = SDXLLoRALoaderOutput()
+        loras = self.loras if isinstance(self.loras, list) else [self.loras]
+        added_loras: list[str] = []
+
+        for lora in loras:
+            if lora.lora.key in added_loras:
+                continue
+
+            if not context.models.exists(lora.lora.key):
+                raise Exception(f"Unknown lora: {lora.lora.key}!")
+
+            assert lora.lora.base is BaseModelType.StableDiffusionXL
+
+            added_loras.append(lora.lora.key)
+
+            if self.unet is not None:
+                if output.unet is None:
+                    output.unet = self.unet.model_copy(deep=True)
+                output.unet.loras.append(lora)
+
+            if self.clip is not None:
+                if output.clip is None:
+                    output.clip = self.clip.model_copy(deep=True)
+                output.clip.loras.append(lora)
+
+            if self.clip2 is not None:
+                if output.clip2 is None:
+                    output.clip2 = self.clip2.model_copy(deep=True)
+                output.clip2.loras.append(lora)
+
+        return output
+
+
+@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model", version="1.0.3")
 class VAELoaderInvocation(BaseInvocation):
     """Loads a VAE model, outputting a VaeLoaderOutput"""
 
     vae_model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.vae_model, input=Input.Direct, title="VAE", ui_type=UIType.VAEModel
+        description=FieldDescriptions.vae_model, title="VAE", ui_type=UIType.VAEModel
     )
 
     def invoke(self, context: InvocationContext) -> VAEOutput:

invokeai/app/invocations/sdxl.py

@@ -1,4 +1,4 @@
-from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIType
+from invokeai.app.invocations.fields import FieldDescriptions, InputField, OutputField, UIType
 from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.model_manager import SubModelType
 
@@ -30,12 +30,12 @@ class SDXLRefinerModelLoaderOutput(BaseInvocationOutput):
     vae: VAEField = OutputField(description=FieldDescriptions.vae, title="VAE")
 
 
-@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model", version="1.0.2")
+@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model", version="1.0.3")
 class SDXLModelLoaderInvocation(BaseInvocation):
     """Loads an sdxl base model, outputting its submodels."""
 
     model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.sdxl_main_model, input=Input.Direct, ui_type=UIType.SDXLMainModel
+        description=FieldDescriptions.sdxl_main_model, ui_type=UIType.SDXLMainModel
     )
     # TODO: precision?
 
@@ -67,13 +67,13 @@ class SDXLModelLoaderInvocation(BaseInvocation):
     title="SDXL Refiner Model",
     tags=["model", "sdxl", "refiner"],
     category="model",
-    version="1.0.2",
+    version="1.0.3",
 )
 class SDXLRefinerModelLoaderInvocation(BaseInvocation):
     """Loads an sdxl refiner model, outputting its submodels."""
 
     model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.sdxl_refiner_model, input=Input.Direct, ui_type=UIType.SDXLRefinerModel
+        description=FieldDescriptions.sdxl_refiner_model, ui_type=UIType.SDXLRefinerModel
     )
     # TODO: precision?
 

invokeai/app/invocations/t2i_adapter.py

@@ -8,7 +8,7 @@ from invokeai.app.invocations.baseinvocation import (
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField, OutputField, UIType
+from invokeai.app.invocations.fields import FieldDescriptions, ImageField, InputField, OutputField, UIType
 from invokeai.app.invocations.model import ModelIdentifierField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.app.services.shared.invocation_context import InvocationContext
@@ -45,7 +45,7 @@ class T2IAdapterOutput(BaseInvocationOutput):
 
 
 @invocation(
-    "t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.2"
+    "t2i_adapter", title="T2I-Adapter", tags=["t2i_adapter", "control"], category="t2i_adapter", version="1.0.3"
 )
 class T2IAdapterInvocation(BaseInvocation):
     """Collects T2I-Adapter info to pass to other nodes."""
@@ -55,7 +55,6 @@ class T2IAdapterInvocation(BaseInvocation):
     t2i_adapter_model: ModelIdentifierField = InputField(
         description="The T2I-Adapter model.",
         title="T2I-Adapter Model",
-        input=Input.Direct,
         ui_order=-1,
         ui_type=UIType.T2IAdapterModel,
     )

invokeai/app/services/events/events_base.py

@@ -122,6 +122,8 @@ class EventServiceBase:
         source_node_id: str,
         error_type: str,
         error: str,
+        user_id: str | None,
+        project_id: str | None,
     ) -> None:
         """Emitted when an invocation has completed"""
         self.__emit_queue_event(
@@ -135,6 +137,8 @@ class EventServiceBase:
                 "source_node_id": source_node_id,
                 "error_type": error_type,
                 "error": error,
+                "user_id": user_id,
+                "project_id": project_id,
             },
         )
 

invokeai/app/services/image_files/image_files_base.py

@@ -4,9 +4,6 @@ from typing import Optional
 
 from PIL.Image import Image as PILImageType
 
-from invokeai.app.invocations.fields import MetadataField
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
-
 
 class ImageFileStorageBase(ABC):
     """Low-level service responsible for storing and retrieving image files."""
@@ -33,8 +30,9 @@ class ImageFileStorageBase(ABC):
         self,
         image: PILImageType,
         image_name: str,
-        metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowWithoutID] = None,
+        metadata: Optional[str] = None,
+        workflow: Optional[str] = None,
+        graph: Optional[str] = None,
         thumbnail_size: int = 256,
     ) -> None:
         """Saves an image and a 256x256 WEBP thumbnail. Returns a tuple of the image name, thumbnail name, and created timestamp."""
@@ -46,6 +44,11 @@ class ImageFileStorageBase(ABC):
         pass
 
     @abstractmethod
-    def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:
+    def get_workflow(self, image_name: str) -> Optional[str]:
         """Gets the workflow of an image."""
         pass
+
+    @abstractmethod
+    def get_graph(self, image_name: str) -> Optional[str]:
+        """Gets the graph of an image."""
+        pass

invokeai/app/services/image_files/image_files_disk.py

@@ -7,9 +7,7 @@ from PIL import Image, PngImagePlugin
 from PIL.Image import Image as PILImageType
 from send2trash import send2trash
 
-from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.invoker import Invoker
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 from invokeai.app.util.thumbnails import get_thumbnail_name, make_thumbnail
 
 from .image_files_base import ImageFileStorageBase
@@ -56,8 +54,9 @@ class DiskImageFileStorage(ImageFileStorageBase):
         self,
         image: PILImageType,
         image_name: str,
-        metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowWithoutID] = None,
+        metadata: Optional[str] = None,
+        workflow: Optional[str] = None,
+        graph: Optional[str] = None,
         thumbnail_size: int = 256,
     ) -> None:
         try:
@@ -68,13 +67,14 @@ class DiskImageFileStorage(ImageFileStorageBase):
             info_dict = {}
 
             if metadata is not None:
-                metadata_json = metadata.model_dump_json()
-                info_dict["invokeai_metadata"] = metadata_json
-                pnginfo.add_text("invokeai_metadata", metadata_json)
+                info_dict["invokeai_metadata"] = metadata
+                pnginfo.add_text("invokeai_metadata", metadata)
             if workflow is not None:
-                workflow_json = workflow.model_dump_json()
-                info_dict["invokeai_workflow"] = workflow_json
-                pnginfo.add_text("invokeai_workflow", workflow_json)
+                info_dict["invokeai_workflow"] = workflow
+                pnginfo.add_text("invokeai_workflow", workflow)
+            if graph is not None:
+                info_dict["invokeai_graph"] = graph
+                pnginfo.add_text("invokeai_graph", graph)
 
             # When saving the image, the image object's info field is not populated. We need to set it
             image.info = info_dict
@@ -129,11 +129,18 @@ class DiskImageFileStorage(ImageFileStorageBase):
         path = path if isinstance(path, Path) else Path(path)
         return path.exists()
 
-    def get_workflow(self, image_name: str) -> WorkflowWithoutID | None:
+    def get_workflow(self, image_name: str) -> str | None:
         image = self.get(image_name)
         workflow = image.info.get("invokeai_workflow", None)
-        if workflow is not None:
-            return WorkflowWithoutID.model_validate_json(workflow)
+        if isinstance(workflow, str):
+            return workflow
+        return None
+
+    def get_graph(self, image_name: str) -> str | None:
+        image = self.get(image_name)
+        graph = image.info.get("invokeai_graph", None)
+        if isinstance(graph, str):
+            return graph
         return None
 
     def __validate_storage_folders(self) -> None:

invokeai/app/services/image_records/image_records_base.py

@@ -80,7 +80,7 @@ class ImageRecordStorageBase(ABC):
         starred: Optional[bool] = False,
         session_id: Optional[str] = None,
         node_id: Optional[str] = None,
-        metadata: Optional[MetadataField] = None,
+        metadata: Optional[str] = None,
     ) -> datetime:
         """Saves an image record."""
         pass

invokeai/app/services/image_records/image_records_sqlite.py

@@ -328,10 +328,9 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
         starred: Optional[bool] = False,
         session_id: Optional[str] = None,
         node_id: Optional[str] = None,
-        metadata: Optional[MetadataField] = None,
+        metadata: Optional[str] = None,
     ) -> datetime:
         try:
-            metadata_json = metadata.model_dump_json() if metadata is not None else None
             self._lock.acquire()
             self._cursor.execute(
                 """--sql
@@ -358,7 +357,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
                     height,
                     node_id,
                     session_id,
-                    metadata_json,
+                    metadata,
                     is_intermediate,
                     starred,
                     has_workflow,

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.workflow_records.workflow_records_common import WorkflowWithoutID
 
 
 class ImageServiceABC(ABC):
@@ -51,8 +50,9 @@ class ImageServiceABC(ABC):
         session_id: Optional[str] = None,
         board_id: Optional[str] = None,
         is_intermediate: Optional[bool] = False,
-        metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowWithoutID] = None,
+        metadata: Optional[str] = None,
+        workflow: Optional[str] = None,
+        graph: Optional[str] = None,
     ) -> ImageDTO:
         """Creates an image, storing the file and its metadata."""
         pass
@@ -87,7 +87,12 @@ class ImageServiceABC(ABC):
         pass
 
     @abstractmethod
-    def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:
+    def get_workflow(self, image_name: str) -> Optional[str]:
+        """Gets an image's workflow."""
+        pass
+
+    @abstractmethod
+    def get_graph(self, image_name: str) -> Optional[str]:
         """Gets an image's workflow."""
         pass
 

invokeai/app/services/images/images_default.py

@@ -5,7 +5,6 @@ from PIL.Image import Image as PILImageType
 from invokeai.app.invocations.fields import MetadataField
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.shared.pagination import OffsetPaginatedResults
-from invokeai.app.services.workflow_records.workflow_records_common import WorkflowWithoutID
 
 from ..image_files.image_files_common import (
     ImageFileDeleteException,
@@ -42,8 +41,9 @@ class ImageService(ImageServiceABC):
         session_id: Optional[str] = None,
         board_id: Optional[str] = None,
         is_intermediate: Optional[bool] = False,
-        metadata: Optional[MetadataField] = None,
-        workflow: Optional[WorkflowWithoutID] = None,
+        metadata: Optional[str] = None,
+        workflow: Optional[str] = None,
+        graph: Optional[str] = None,
     ) -> ImageDTO:
         if image_origin not in ResourceOrigin:
             raise InvalidOriginException
@@ -64,7 +64,7 @@ class ImageService(ImageServiceABC):
                 image_category=image_category,
                 width=width,
                 height=height,
-                has_workflow=workflow is not None,
+                has_workflow=workflow is not None or graph is not None,
                 # Meta fields
                 is_intermediate=is_intermediate,
                 # Nullable fields
@@ -75,7 +75,7 @@ class ImageService(ImageServiceABC):
             if board_id is not None:
                 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
+                image_name=image_name, image=image, metadata=metadata, workflow=workflow, graph=graph
             )
             image_dto = self.get_dto(image_name)
 
@@ -157,7 +157,7 @@ class ImageService(ImageServiceABC):
             self.__invoker.services.logger.error("Problem getting image metadata")
             raise e
 
-    def get_workflow(self, image_name: str) -> Optional[WorkflowWithoutID]:
+    def get_workflow(self, image_name: str) -> Optional[str]:
         try:
             return self.__invoker.services.image_files.get_workflow(image_name)
         except ImageFileNotFoundException:
@@ -167,6 +167,16 @@ class ImageService(ImageServiceABC):
             self.__invoker.services.logger.error("Problem getting image workflow")
             raise
 
+    def get_graph(self, image_name: str) -> Optional[str]:
+        try:
+            return self.__invoker.services.image_files.get_graph(image_name)
+        except ImageFileNotFoundException:
+            self.__invoker.services.logger.error("Image file not found")
+            raise
+        except Exception:
+            self.__invoker.services.logger.error("Problem getting image graph")
+            raise
+
     def get_path(self, image_name: str, thumbnail: bool = False) -> str:
         try:
             return str(self.__invoker.services.image_files.get_path(image_name, thumbnail))

invokeai/app/services/session_processor/session_processor_default.py

@@ -237,6 +237,8 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                 source_node_id=source_invocation_id,
                                 error_type=e.__class__.__name__,
                                 error=error,
+                                user_id=None,
+                                project_id=None,
                             )
                             pass
 

invokeai/app/services/shared/invocation_context.py

@@ -180,9 +180,9 @@ class ImagesInterface(InvocationContextInterface):
         # If `metadata` is provided directly, use that. Else, use the metadata provided by `WithMetadata`, falling back to None.
         metadata_ = None
         if metadata:
-            metadata_ = metadata
-        elif isinstance(self._data.invocation, WithMetadata):
-            metadata_ = self._data.invocation.metadata
+            metadata_ = metadata.model_dump_json()
+        elif isinstance(self._data.invocation, WithMetadata) and self._data.invocation.metadata:
+            metadata_ = self._data.invocation.metadata.model_dump_json()
 
         # If `board_id` is provided directly, use that. Else, use the board provided by `WithBoard`, falling back to None.
         board_id_ = None
@@ -191,6 +191,14 @@ class ImagesInterface(InvocationContextInterface):
         elif isinstance(self._data.invocation, WithBoard) and self._data.invocation.board:
             board_id_ = self._data.invocation.board.board_id
 
+        workflow_ = None
+        if self._data.queue_item.workflow:
+            workflow_ = self._data.queue_item.workflow.model_dump_json()
+
+        graph_ = None
+        if self._data.queue_item.session.graph:
+            graph_ = self._data.queue_item.session.graph.model_dump_json()
+
         return self._services.images.create(
             image=image,
             is_intermediate=self._data.invocation.is_intermediate,
@@ -198,7 +206,8 @@ class ImagesInterface(InvocationContextInterface):
             board_id=board_id_,
             metadata=metadata_,
             image_origin=ResourceOrigin.INTERNAL,
-            workflow=self._data.queue_item.workflow,
+            workflow=workflow_,
+            graph=graph_,
             session_id=self._data.queue_item.session_id,
             node_id=self._data.invocation.id,
         )

invokeai/backend/image_util/__init__.py

@@ -4,5 +4,4 @@ Initialization file for invokeai.backend.image_util methods.
 
 from .infill_methods.patchmatch import PatchMatch  # noqa: F401
 from .pngwriter import PngWriter, PromptFormatter, retrieve_metadata, write_metadata  # noqa: F401
-from .seamless import configure_model_padding  # noqa: F401
 from .util import InitImageResizer, make_grid  # noqa: F401

invokeai/backend/image_util/safety_checker.py

@@ -8,7 +8,7 @@ from pathlib import Path
 
 import numpy as np
 from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
-from PIL import Image
+from PIL import Image, ImageFilter
 from transformers import AutoFeatureExtractor
 
 import invokeai.backend.util.logging as logger
@@ -16,6 +16,7 @@ from invokeai.app.services.config.config_default import get_config
 from invokeai.backend.util.devices import TorchDevice
 from invokeai.backend.util.silence_warnings import SilenceWarnings
 
+repo_id = "CompVis/stable-diffusion-safety-checker"
 CHECKER_PATH = "core/convert/stable-diffusion-safety-checker"
 
 
@@ -24,30 +25,30 @@ class SafetyChecker:
     Wrapper around SafetyChecker model.
     """
 
-    safety_checker = None
     feature_extractor = None
-    tried_load: bool = False
+    safety_checker = None
 
     @classmethod
     def _load_safety_checker(cls):
-        if cls.tried_load:
+        if cls.safety_checker is not None and cls.feature_extractor is not None:
             return
 
         try:
-            cls.safety_checker = StableDiffusionSafetyChecker.from_pretrained(get_config().models_path / CHECKER_PATH)
-            cls.feature_extractor = AutoFeatureExtractor.from_pretrained(get_config().models_path / CHECKER_PATH)
+            model_path = get_config().models_path / CHECKER_PATH
+            if model_path.exists():
+                cls.feature_extractor = AutoFeatureExtractor.from_pretrained(model_path)
+                cls.safety_checker = StableDiffusionSafetyChecker.from_pretrained(model_path)
+            else:
+                model_path.mkdir(parents=True, exist_ok=True)
+                cls.feature_extractor = AutoFeatureExtractor.from_pretrained(repo_id)
+                cls.feature_extractor.save_pretrained(model_path, safe_serialization=True)
+                cls.safety_checker = StableDiffusionSafetyChecker.from_pretrained(repo_id)
+                cls.safety_checker.save_pretrained(model_path, safe_serialization=True)
         except Exception as e:
             logger.warning(f"Could not load NSFW checker: {str(e)}")
-        cls.tried_load = True
-
-    @classmethod
-    def safety_checker_available(cls) -> bool:
-        return Path(get_config().models_path, CHECKER_PATH).exists()
 
     @classmethod
     def has_nsfw_concept(cls, image: Image.Image) -> bool:
-        if not cls.safety_checker_available() and cls.tried_load:
-            return False
         cls._load_safety_checker()
         if cls.safety_checker is None or cls.feature_extractor is None:
             return False
@@ -60,3 +61,24 @@ class SafetyChecker:
         with SilenceWarnings():
             checked_image, has_nsfw_concept = cls.safety_checker(images=x_image, clip_input=features.pixel_values)
         return has_nsfw_concept[0]
+
+    @classmethod
+    def blur_if_nsfw(cls, image: Image.Image) -> Image.Image:
+        if cls.has_nsfw_concept(image):
+            logger.warning("A potentially NSFW image has been detected. Image will be blurred.")
+            blurry_image = image.filter(filter=ImageFilter.GaussianBlur(radius=32))
+            caution = cls._get_caution_img()
+            # Center the caution image on the blurred image
+            x = (blurry_image.width - caution.width) // 2
+            y = (blurry_image.height - caution.height) // 2
+            blurry_image.paste(caution, (x, y), caution)
+            image = blurry_image
+
+        return image
+
+    @classmethod
+    def _get_caution_img(cls) -> Image.Image:
+        import invokeai.app.assets.images as image_assets
+
+        caution = Image.open(Path(image_assets.__path__[0]) / "caution.png")
+        return caution.resize((caution.width // 2, caution.height // 2))

invokeai/backend/image_util/seamless.py

@@ -1,52 +0,0 @@
-import torch.nn as nn
-
-
-def _conv_forward_asymmetric(self, input, weight, bias):
-    """
-    Patch for Conv2d._conv_forward that supports asymmetric padding
-    """
-    working = nn.functional.pad(input, self.asymmetric_padding["x"], mode=self.asymmetric_padding_mode["x"])
-    working = nn.functional.pad(working, self.asymmetric_padding["y"], mode=self.asymmetric_padding_mode["y"])
-    return nn.functional.conv2d(
-        working,
-        weight,
-        bias,
-        self.stride,
-        nn.modules.utils._pair(0),
-        self.dilation,
-        self.groups,
-    )
-
-
-def configure_model_padding(model, seamless, seamless_axes):
-    """
-    Modifies the 2D convolution layers to use a circular padding mode based on
-    the `seamless` and `seamless_axes` options.
-    """
-    # TODO: get an explicit interface for this in diffusers: https://github.com/huggingface/diffusers/issues/556
-    for m in model.modules():
-        if isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
-            if seamless:
-                m.asymmetric_padding_mode = {}
-                m.asymmetric_padding = {}
-                m.asymmetric_padding_mode["x"] = "circular" if ("x" in seamless_axes) else "constant"
-                m.asymmetric_padding["x"] = (
-                    m._reversed_padding_repeated_twice[0],
-                    m._reversed_padding_repeated_twice[1],
-                    0,
-                    0,
-                )
-                m.asymmetric_padding_mode["y"] = "circular" if ("y" in seamless_axes) else "constant"
-                m.asymmetric_padding["y"] = (
-                    0,
-                    0,
-                    m._reversed_padding_repeated_twice[2],
-                    m._reversed_padding_repeated_twice[3],
-                )
-                m._conv_forward = _conv_forward_asymmetric.__get__(m, nn.Conv2d)
-            else:
-                m._conv_forward = nn.Conv2d._conv_forward.__get__(m, nn.Conv2d)
-                if hasattr(m, "asymmetric_padding_mode"):
-                    del m.asymmetric_padding_mode
-                if hasattr(m, "asymmetric_padding"):
-                    del m.asymmetric_padding

invokeai/backend/stable_diffusion/seamless.py

@@ -1,89 +1,51 @@
-from __future__ import annotations
-
 from contextlib import contextmanager
-from typing import Callable, List, Union
+from typing import Callable, List, Optional, Tuple, Union
 
+import torch
 import torch.nn as nn
 from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
 from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny
+from diffusers.models.lora import LoRACompatibleConv
 from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
 
 
-def _conv_forward_asymmetric(self, input, weight, bias):
-    """
-    Patch for Conv2d._conv_forward that supports asymmetric padding
-    """
-    working = nn.functional.pad(input, self.asymmetric_padding["x"], mode=self.asymmetric_padding_mode["x"])
-    working = nn.functional.pad(working, self.asymmetric_padding["y"], mode=self.asymmetric_padding_mode["y"])
-    return nn.functional.conv2d(
-        working,
-        weight,
-        bias,
-        self.stride,
-        nn.modules.utils._pair(0),
-        self.dilation,
-        self.groups,
-    )
-
-
 @contextmanager
 def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL, AutoencoderTiny], seamless_axes: List[str]):
     if not seamless_axes:
         yield
         return
 
-    # Callable: (input: Tensor, weight: Tensor, bias: Optional[Tensor]) -> Tensor
-    to_restore: list[tuple[nn.Conv2d | nn.ConvTranspose2d, Callable]] = []
+    # override conv_forward
+    # https://github.com/huggingface/diffusers/issues/556#issuecomment-1993287019
+    def _conv_forward_asymmetric(self, input: torch.Tensor, weight: torch.Tensor, bias: Optional[torch.Tensor] = None):
+        self.paddingX = (self._reversed_padding_repeated_twice[0], self._reversed_padding_repeated_twice[1], 0, 0)
+        self.paddingY = (0, 0, self._reversed_padding_repeated_twice[2], self._reversed_padding_repeated_twice[3])
+        working = torch.nn.functional.pad(input, self.paddingX, mode=x_mode)
+        working = torch.nn.functional.pad(working, self.paddingY, mode=y_mode)
+        return torch.nn.functional.conv2d(
+            working, weight, bias, self.stride, torch.nn.modules.utils._pair(0), self.dilation, self.groups
+        )
+
+    original_layers: List[Tuple[nn.Conv2d, Callable]] = []
+
     try:
-        # Hard coded to skip down block layers, allowing for seamless tiling at the expense of prompt adherence
-        skipped_layers = 1
-        for m_name, m in model.named_modules():
-            if not isinstance(m, (nn.Conv2d, nn.ConvTranspose2d)):
-                continue
+        x_mode = "circular" if "x" in seamless_axes else "constant"
+        y_mode = "circular" if "y" in seamless_axes else "constant"
 
-            if isinstance(model, UNet2DConditionModel) and m_name.startswith("down_blocks.") and ".resnets." in m_name:
-                # down_blocks.1.resnets.1.conv1
-                _, block_num, _, resnet_num, submodule_name = m_name.split(".")
-                block_num = int(block_num)
-                resnet_num = int(resnet_num)
+        conv_layers: List[torch.nn.Conv2d] = []
 
-                if block_num >= len(model.down_blocks) - skipped_layers:
-                    continue
+        for module in model.modules():
+            if isinstance(module, torch.nn.Conv2d):
+                conv_layers.append(module)
 
-                # Skip the second resnet (could be configurable)
-                if resnet_num > 0:
-                    continue
-
-                # Skip Conv2d layers (could be configurable)
-                if submodule_name == "conv2":
-                    continue
-
-            m.asymmetric_padding_mode = {}
-            m.asymmetric_padding = {}
-            m.asymmetric_padding_mode["x"] = "circular" if ("x" in seamless_axes) else "constant"
-            m.asymmetric_padding["x"] = (
-                m._reversed_padding_repeated_twice[0],
-                m._reversed_padding_repeated_twice[1],
-                0,
-                0,
-            )
-            m.asymmetric_padding_mode["y"] = "circular" if ("y" in seamless_axes) else "constant"
-            m.asymmetric_padding["y"] = (
-                0,
-                0,
-                m._reversed_padding_repeated_twice[2],
-                m._reversed_padding_repeated_twice[3],
-            )
-
-            to_restore.append((m, m._conv_forward))
-            m._conv_forward = _conv_forward_asymmetric.__get__(m, nn.Conv2d)
+        for layer in conv_layers:
+            if isinstance(layer, LoRACompatibleConv) and layer.lora_layer is None:
+                layer.lora_layer = lambda *x: 0
+            original_layers.append((layer, layer._conv_forward))
+            layer._conv_forward = _conv_forward_asymmetric.__get__(layer, torch.nn.Conv2d)
 
         yield
 
     finally:
-        for module, orig_conv_forward in to_restore:
-            module._conv_forward = orig_conv_forward
-            if hasattr(module, "asymmetric_padding_mode"):
-                del module.asymmetric_padding_mode
-            if hasattr(module, "asymmetric_padding"):
-                del module.asymmetric_padding
+        for layer, orig_conv_forward in original_layers:
+            layer._conv_forward = orig_conv_forward

invokeai/frontend/web/.eslintrc.js

@@ -10,6 +10,8 @@ module.exports = {
     'path/no-relative-imports': ['error', { maxDepth: 0 }],
     // https://github.com/edvardchen/eslint-plugin-i18next/blob/HEAD/docs/rules/no-literal-string.md
     'i18next/no-literal-string': 'error',
+    // https://eslint.org/docs/latest/rules/no-console
+    'no-console': 'error',
   },
   overrides: [
     /**

invokeai/frontend/web/.gitignore

@@ -43,4 +43,5 @@ stats.html
 yalc.lock
 
 # vitest
-tsconfig.vitest-temp.json
+tsconfig.vitest-temp.json
+coverage/

invokeai/frontend/web/package.json

@@ -35,6 +35,7 @@
     "storybook": "storybook dev -p 6006",
     "build-storybook": "storybook build",
     "test": "vitest",
+    "test:ui": "vitest --coverage --ui",
     "test:no-watch": "vitest --no-watch"
   },
   "madge": {
@@ -52,47 +53,48 @@
   },
   "dependencies": {
     "@chakra-ui/react-use-size": "^2.1.0",
-    "@dagrejs/dagre": "^1.1.1",
-    "@dagrejs/graphlib": "^2.2.1",
+    "@dagrejs/dagre": "^1.1.2",
+    "@dagrejs/graphlib": "^2.2.2",
     "@dnd-kit/core": "^6.1.0",
     "@dnd-kit/sortable": "^8.0.0",
     "@dnd-kit/utilities": "^3.2.2",
-    "@fontsource-variable/inter": "^5.0.17",
+    "@fontsource-variable/inter": "^5.0.18",
     "@invoke-ai/ui-library": "^0.0.25",
     "@nanostores/react": "^0.7.2",
-    "@reduxjs/toolkit": "2.2.2",
+    "@reduxjs/toolkit": "2.2.3",
     "@roarr/browser-log-writer": "^1.3.0",
     "chakra-react-select": "^4.7.6",
     "compare-versions": "^6.1.0",
     "dateformat": "^5.0.3",
-    "framer-motion": "^11.0.22",
-    "i18next": "^23.10.1",
-    "i18next-http-backend": "^2.5.0",
+    "fracturedjsonjs": "^4.0.1",
+    "framer-motion": "^11.1.8",
+    "i18next": "^23.11.3",
+    "i18next-http-backend": "^2.5.1",
     "idb-keyval": "^6.2.1",
     "jsondiffpatch": "^0.6.0",
     "konva": "^9.3.6",
     "lodash-es": "^4.17.21",
-    "nanostores": "^0.10.0",
+    "nanostores": "^0.10.3",
     "new-github-issue-url": "^1.0.0",
-    "overlayscrollbars": "^2.6.1",
-    "overlayscrollbars-react": "^0.5.5",
+    "overlayscrollbars": "^2.7.3",
+    "overlayscrollbars-react": "^0.5.6",
     "query-string": "^9.0.0",
-    "react": "^18.2.0",
+    "react": "^18.3.1",
     "react-colorful": "^5.6.1",
-    "react-dom": "^18.2.0",
+    "react-dom": "^18.3.1",
     "react-dropzone": "^14.2.3",
     "react-error-boundary": "^4.0.13",
-    "react-hook-form": "^7.51.2",
+    "react-hook-form": "^7.51.4",
     "react-hotkeys-hook": "4.5.0",
-    "react-i18next": "^14.1.0",
-    "react-icons": "^5.0.1",
+    "react-i18next": "^14.1.1",
+    "react-icons": "^5.2.0",
     "react-konva": "^18.2.10",
-    "react-redux": "9.1.0",
-    "react-resizable-panels": "^2.0.16",
+    "react-redux": "9.1.2",
+    "react-resizable-panels": "^2.0.19",
     "react-select": "5.8.0",
     "react-use": "^17.5.0",
-    "react-virtuoso": "^4.7.5",
-    "reactflow": "^11.10.4",
+    "react-virtuoso": "^4.7.10",
+    "reactflow": "^11.11.3",
     "redux-dynamic-middlewares": "^2.2.0",
     "redux-remember": "^5.1.0",
     "redux-undo": "^1.1.0",
@@ -104,8 +106,8 @@
     "use-device-pixel-ratio": "^1.1.2",
     "use-image": "^1.1.1",
     "uuid": "^9.0.1",
-    "zod": "^3.22.4",
-    "zod-validation-error": "^3.0.3"
+    "zod": "^3.23.6",
+    "zod-validation-error": "^3.2.0"
   },
   "peerDependencies": {
     "@chakra-ui/react": "^2.8.2",
@@ -116,40 +118,42 @@
   "devDependencies": {
     "@invoke-ai/eslint-config-react": "^0.0.14",
     "@invoke-ai/prettier-config-react": "^0.0.7",
-    "@storybook/addon-essentials": "^8.0.4",
-    "@storybook/addon-interactions": "^8.0.4",
-    "@storybook/addon-links": "^8.0.4",
-    "@storybook/addon-storysource": "^8.0.4",
-    "@storybook/manager-api": "^8.0.4",
-    "@storybook/react": "^8.0.4",
-    "@storybook/react-vite": "^8.0.4",
-    "@storybook/theming": "^8.0.4",
+    "@storybook/addon-essentials": "^8.0.10",
+    "@storybook/addon-interactions": "^8.0.10",
+    "@storybook/addon-links": "^8.0.10",
+    "@storybook/addon-storysource": "^8.0.10",
+    "@storybook/manager-api": "^8.0.10",
+    "@storybook/react": "^8.0.10",
+    "@storybook/react-vite": "^8.0.10",
+    "@storybook/theming": "^8.0.10",
     "@types/dateformat": "^5.0.2",
     "@types/lodash-es": "^4.17.12",
-    "@types/node": "^20.11.30",
-    "@types/react": "^18.2.73",
-    "@types/react-dom": "^18.2.22",
+    "@types/node": "^20.12.10",
+    "@types/react": "^18.3.1",
+    "@types/react-dom": "^18.3.0",
     "@types/uuid": "^9.0.8",
     "@vitejs/plugin-react-swc": "^3.6.0",
+    "@vitest/coverage-v8": "^1.5.0",
+    "@vitest/ui": "^1.5.0",
     "concurrently": "^8.2.2",
     "dpdm": "^3.14.0",
     "eslint": "^8.57.0",
     "eslint-plugin-i18next": "^6.0.3",
     "eslint-plugin-path": "^1.3.0",
-    "knip": "^5.6.1",
+    "knip": "^5.12.3",
     "openapi-types": "^12.1.3",
     "openapi-typescript": "^6.7.5",
     "prettier": "^3.2.5",
     "rollup-plugin-visualizer": "^5.12.0",
-    "storybook": "^8.0.4",
+    "storybook": "^8.0.10",
     "ts-toolbelt": "^9.6.0",
     "tsafe": "^1.6.6",
-    "typescript": "^5.4.3",
-    "vite": "^5.2.6",
-    "vite-plugin-css-injected-by-js": "^3.5.0",
-    "vite-plugin-dts": "^3.8.0",
+    "typescript": "^5.4.5",
+    "vite": "^5.2.11",
+    "vite-plugin-css-injected-by-js": "^3.5.1",
+    "vite-plugin-dts": "^3.9.1",
     "vite-plugin-eslint": "^1.8.1",
     "vite-tsconfig-paths": "^4.3.2",
-    "vitest": "^1.4.0"
+    "vitest": "^1.6.0"
   }
 }

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

@@ -76,7 +76,9 @@
         "aboutHeading": "Nutzen Sie Ihre kreative Energie",
         "toResolve": "Lösen",
         "add": "Hinzufügen",
-        "loglevel": "Protokoll Stufe"
+        "loglevel": "Protokoll Stufe",
+        "selected": "Ausgewählt",
+        "beta": "Beta"
     },
     "gallery": {
         "galleryImageSize": "Bildgröße",
@@ -86,7 +88,7 @@
         "noImagesInGallery": "Keine Bilder in der Galerie",
         "loading": "Lade",
         "deleteImage_one": "Lösche Bild",
-        "deleteImage_other": "",
+        "deleteImage_other": "Lösche {{count}} Bilder",
         "copy": "Kopieren",
         "download": "Runterladen",
         "setCurrentImage": "Setze aktuelle Bild",
@@ -397,7 +399,14 @@
         "cancel": "Stornieren",
         "defaultSettingsSaved": "Standardeinstellungen gespeichert",
         "addModels": "Model hinzufügen",
-        "deleteModelImage": "Lösche Model Bild"
+        "deleteModelImage": "Lösche Model Bild",
+        "hfTokenInvalidErrorMessage": "Falscher oder fehlender HuggingFace Schlüssel.",
+        "huggingFaceRepoID": "HuggingFace Repo ID",
+        "hfToken": "HuggingFace Schlüssel",
+        "hfTokenInvalid": "Falscher oder fehlender HF Schlüssel",
+        "huggingFacePlaceholder": "besitzer/model-name",
+        "hfTokenSaved": "HF Schlüssel gespeichert",
+        "hfTokenUnableToVerify": "Konnte den HF Schlüssel nicht validieren"
     },
     "parameters": {
         "images": "Bilder",
@@ -686,7 +695,11 @@
         "hands": "Hände",
         "dwOpenpose": "DW Openpose",
         "dwOpenposeDescription": "Posenschätzung mit DW Openpose",
-        "selectCLIPVisionModel": "Wähle ein CLIP Vision Model aus"
+        "selectCLIPVisionModel": "Wähle ein CLIP Vision Model aus",
+        "ipAdapterMethod": "Methode",
+        "composition": "Nur Komposition",
+        "full": "Voll",
+        "style": "Nur Style"
     },
     "queue": {
         "status": "Status",
@@ -717,7 +730,6 @@
         "resume": "Wieder aufnehmen",
         "item": "Auftrag",
         "notReady": "Warteschlange noch nicht bereit",
-        "queueCountPrediction": "{{promptsCount}} Prompts × {{iterations}} Iterationen -> {{count}} Generationen",
         "clearQueueAlertDialog": "\"Die Warteschlange leeren\" stoppt den aktuellen Prozess und leert die Warteschlange komplett.",
         "completedIn": "Fertig in",
         "cancelBatchSucceeded": "Stapel abgebrochen",

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

@@ -2,6 +2,7 @@
     "accessibility": {
         "about": "About",
         "createIssue": "Create Issue",
+        "submitSupportTicket": "Submit Support Ticket",
         "invokeProgressBar": "Invoke progress bar",
         "menu": "Menu",
         "mode": "Mode",
@@ -142,8 +143,13 @@
         "blue": "Blue",
         "alpha": "Alpha",
         "selected": "Selected",
-        "viewer": "Viewer",
-        "tab": "Tab"
+        "tab": "Tab",
+        "viewing": "Viewing",
+        "viewingDesc": "Review images in a large gallery view",
+        "editing": "Editing",
+        "editingDesc": "Edit on the Control Layers canvas",
+        "enabled": "Enabled",
+        "disabled": "Disabled"
     },
     "controlnet": {
         "controlAdapter_one": "Control Adapter",
@@ -258,7 +264,6 @@
         "queue": "Queue",
         "queueFront": "Add to Front of Queue",
         "queueBack": "Add to Queue",
-        "queueCountPrediction": "{{promptsCount}} prompts \u00d7 {{iterations}} iterations -> {{count}} generations",
         "queueEmpty": "Queue Empty",
         "enqueueing": "Queueing Batch",
         "resume": "Resume",
@@ -311,7 +316,13 @@
         "batchFailedToQueue": "Failed to Queue Batch",
         "graphQueued": "Graph queued",
         "graphFailedToQueue": "Failed to queue graph",
-        "openQueue": "Open Queue"
+        "openQueue": "Open Queue",
+        "prompts_one": "Prompt",
+        "prompts_other": "Prompts",
+        "iterations_one": "Iteration",
+        "iterations_other": "Iterations",
+        "generations_one": "Generation",
+        "generations_other": "Generations"
     },
     "invocationCache": {
         "invocationCache": "Invocation Cache",
@@ -364,8 +375,7 @@
         "bulkDownloadRequestFailed": "Problem Preparing Download",
         "bulkDownloadFailed": "Download Failed",
         "problemDeletingImages": "Problem Deleting Images",
-        "problemDeletingImagesDesc": "One or more images could not be deleted",
-        "switchTo": "Switch to {{ tab }} (Z)"
+        "problemDeletingImagesDesc": "One or more images could not be deleted"
     },
     "hotkeys": {
         "searchHotkeys": "Search Hotkeys",
@@ -589,13 +599,9 @@
             "desc": "Upscale the current image",
             "title": "Upscale"
         },
-        "backToEditor": {
-            "desc": "Closes the Image Viewer and shows the Editor View (Text to Image tab only)",
-            "title": "Back to Editor"
-        },
-        "openImageViewer": {
-            "desc": "Opens the Image Viewer (Text to Image tab only)",
-            "title": "Open Image Viewer"
+        "toggleViewer": {
+            "desc": "Switches between the Image Viewer and workspace for the current tab.",
+            "title": "Toggle Image Viewer"
         }
     },
     "metadata": {
@@ -771,10 +777,15 @@
         "cannotConnectOutputToOutput": "Cannot connect output to output",
         "cannotConnectToSelf": "Cannot connect to self",
         "cannotDuplicateConnection": "Cannot create duplicate connections",
+        "cannotMixAndMatchCollectionItemTypes": "Cannot mix and match collection item types",
+        "missingNode": "Missing invocation node",
+        "missingInvocationTemplate": "Missing invocation template",
+        "missingFieldTemplate": "Missing field template",
         "nodePack": "Node pack",
         "collection": "Collection",
-        "collectionFieldType": "{{name}} Collection",
-        "collectionOrScalarFieldType": "{{name}} Collection|Scalar",
+        "singleFieldType": "{{name}} (Single)",
+        "collectionFieldType": "{{name}} (Collection)",
+        "collectionOrScalarFieldType": "{{name}} (Single or Collection)",
         "colorCodeEdges": "Color-Code Edges",
         "colorCodeEdgesHelp": "Color-code edges according to their connected fields",
         "connectionWouldCreateCycle": "Connection would create a cycle",
@@ -876,6 +887,7 @@
         "versionUnknown": " Version Unknown",
         "workflow": "Workflow",
         "graph": "Graph",
+        "noGraph": "No Graph",
         "workflowAuthor": "Author",
         "workflowContact": "Contact",
         "workflowDescription": "Short Description",
@@ -888,7 +900,10 @@
         "zoomInNodes": "Zoom In",
         "zoomOutNodes": "Zoom Out",
         "betaDesc": "This invocation is in beta. Until it is stable, it may have breaking changes during app updates. We plan to support this invocation long-term.",
-        "prototypeDesc": "This invocation is a prototype. It may have breaking changes during app updates and may be removed at any time."
+        "prototypeDesc": "This invocation is a prototype. It may have breaking changes during app updates and may be removed at any time.",
+        "imageAccessError": "Unable to find image {{image_name}}, resetting to default",
+        "boardAccessError": "Unable to find board {{board_id}}, resetting to default",
+        "modelAccessError": "Unable to find model {{key}}, resetting to default"
     },
     "parameters": {
         "aspect": "Aspect",
@@ -936,17 +951,30 @@
             "noModelSelected": "No model selected",
             "noPrompts": "No prompts generated",
             "noNodesInGraph": "No nodes in graph",
-            "systemDisconnected": "System disconnected"
+            "systemDisconnected": "System disconnected",
+            "layer": {
+                "initialImageNoImageSelected": "no initial image selected",
+                "controlAdapterNoModelSelected": "no Control Adapter model selected",
+                "controlAdapterIncompatibleBaseModel": "incompatible Control Adapter base model",
+                "controlAdapterNoImageSelected": "no Control Adapter image selected",
+                "controlAdapterImageNotProcessed": "Control Adapter image not processed",
+                "t2iAdapterIncompatibleDimensions": "T2I Adapter requires image dimension to be multiples of {{multiple}}",
+                "ipAdapterNoModelSelected": "no IP adapter selected",
+                "ipAdapterIncompatibleBaseModel": "incompatible IP Adapter base model",
+                "ipAdapterNoImageSelected": "no IP Adapter image selected",
+                "rgNoPromptsOrIPAdapters": "no text prompts or IP Adapters",
+                "rgNoRegion": "no region selected"
+            }
         },
         "maskBlur": "Mask Blur",
         "negativePromptPlaceholder": "Negative Prompt",
+        "globalNegativePromptPlaceholder": "Global Negative Prompt",
         "noiseThreshold": "Noise Threshold",
         "patchmatchDownScaleSize": "Downscale",
         "perlinNoise": "Perlin Noise",
         "positivePromptPlaceholder": "Positive Prompt",
+        "globalPositivePromptPlaceholder": "Global Positive Prompt",
         "iterations": "Iterations",
-        "iterationsWithCount_one": "{{count}} Iteration",
-        "iterationsWithCount_other": "{{count}} Iterations",
         "scale": "Scale",
         "scaleBeforeProcessing": "Scale Before Processing",
         "scaledHeight": "Scaled H",
@@ -1048,8 +1076,9 @@
     },
     "toast": {
         "addedToBoard": "Added to board",
-        "baseModelChangedCleared_one": "Base model changed, cleared or disabled {{count}} incompatible submodel",
-        "baseModelChangedCleared_other": "Base model changed, cleared or disabled {{count}} incompatible submodels",
+        "baseModelChanged": "Base Model Changed",
+        "baseModelChangedCleared_one": "Cleared or disabled {{count}} incompatible submodel",
+        "baseModelChangedCleared_other": "Cleared or disabled {{count}} incompatible submodels",
         "canceled": "Processing Canceled",
         "canvasCopiedClipboard": "Canvas Copied to Clipboard",
         "canvasDownloaded": "Canvas Downloaded",
@@ -1070,10 +1099,17 @@
         "metadataLoadFailed": "Failed to load metadata",
         "modelAddedSimple": "Model Added to Queue",
         "modelImportCanceled": "Model Import Canceled",
+        "outOfMemoryError": "Out of Memory Error",
+        "outOfMemoryErrorDesc": "Your current generation settings exceed system capacity. Please adjust your settings and try again.",
         "parameters": "Parameters",
-        "parameterNotSet": "{{parameter}} not set",
-        "parameterSet": "{{parameter}} set",
-        "parametersNotSet": "Parameters Not Set",
+        "parameterSet": "Parameter Recalled",
+        "parameterSetDesc": "Recalled {{parameter}}",
+        "parameterNotSet": "Parameter Recalled",
+        "parameterNotSetDesc": "Unable to recall {{parameter}}",
+        "parameterNotSetDescWithMessage": "Unable to recall {{parameter}}: {{message}}",
+        "parametersSet": "Parameters Recalled",
+        "parametersNotSet": "Parameters Not Recalled",
+        "errorCopied": "Error Copied",
         "problemCopyingCanvas": "Problem Copying Canvas",
         "problemCopyingCanvasDesc": "Unable to export base layer",
         "problemCopyingImage": "Unable to Copy Image",
@@ -1093,11 +1129,13 @@
         "sentToImageToImage": "Sent To Image To Image",
         "sentToUnifiedCanvas": "Sent to Unified Canvas",
         "serverError": "Server Error",
+        "sessionRef": "Session: {{sessionId}}",
         "setAsCanvasInitialImage": "Set as canvas initial image",
         "setCanvasInitialImage": "Set canvas initial image",
         "setControlImage": "Set as control image",
         "setInitialImage": "Set as initial image",
         "setNodeField": "Set as node field",
+        "somethingWentWrong": "Something Went Wrong",
         "uploadFailed": "Upload failed",
         "uploadFailedInvalidUploadDesc": "Must be single PNG or JPEG image",
         "uploadInitialImage": "Upload Initial Image",
@@ -1534,10 +1572,9 @@
         "moveForward": "Move Forward",
         "moveBackward": "Move Backward",
         "brushSize": "Brush Size",
-        "controlLayers": "Control Layers (BETA)",
+        "controlLayers": "Control Layers",
         "globalMaskOpacity": "Global Mask Opacity",
         "autoNegative": "Auto Negative",
-        "toggleVisibility": "Toggle Layer Visibility",
         "deletePrompt": "Delete Prompt",
         "resetRegion": "Reset Region",
         "debugLayers": "Debug Layers",
@@ -1548,8 +1585,6 @@
         "addIPAdapter": "Add $t(common.ipAdapter)",
         "regionalGuidance": "Regional Guidance",
         "regionalGuidanceLayer": "$t(controlLayers.regionalGuidance) $t(unifiedCanvas.layer)",
-        "controlNetLayer": "$t(common.controlNet) $t(unifiedCanvas.layer)",
-        "ipAdapterLayer": "$t(common.ipAdapter) $t(unifiedCanvas.layer)",
         "opacity": "Opacity",
         "globalControlAdapter": "Global $t(controlnet.controlAdapter_one)",
         "globalControlAdapterLayer": "Global $t(controlnet.controlAdapter_one) $t(unifiedCanvas.layer)",
@@ -1560,7 +1595,9 @@
         "opacityFilter": "Opacity Filter",
         "clearProcessor": "Clear Processor",
         "resetProcessor": "Reset Processor to Defaults",
-        "noLayersAdded": "No Layers Added"
+        "noLayersAdded": "No Layers Added",
+        "layers_one": "Layer",
+        "layers_other": "Layers"
     },
     "ui": {
         "tabs": {

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

@@ -25,7 +25,24 @@
         "areYouSure": "¿Estas seguro?",
         "batch": "Administrador de lotes",
         "modelManager": "Administrador de modelos",
-        "communityLabel": "Comunidad"
+        "communityLabel": "Comunidad",
+        "direction": "Dirección",
+        "ai": "Ia",
+        "add": "Añadir",
+        "auto": "Automático",
+        "copyError": "Error $t(gallery.copy)",
+        "details": "Detalles",
+        "or": "o",
+        "checkpoint": "Punto de control",
+        "controlNet": "ControlNet",
+        "aboutHeading": "Sea dueño de su poder creativo",
+        "advanced": "Avanzado",
+        "data": "Fecha",
+        "delete": "Borrar",
+        "copy": "Copiar",
+        "beta": "Beta",
+        "on": "En",
+        "aboutDesc": "¿Utilizas Invoke para trabajar? Mira aquí:"
     },
     "gallery": {
         "galleryImageSize": "Tamaño de la imagen",
@@ -365,7 +382,7 @@
         "canvasMerged": "Lienzo consolidado",
         "sentToImageToImage": "Enviar hacia Imagen a Imagen",
         "sentToUnifiedCanvas": "Enviar hacia Lienzo Consolidado",
-        "parametersNotSet": "Parámetros no establecidos",
+        "parametersNotSet": "Parámetros no recuperados",
         "metadataLoadFailed": "Error al cargar metadatos",
         "serverError": "Error en el servidor",
         "canceled": "Procesando la cancelación",
@@ -373,7 +390,8 @@
         "uploadFailedInvalidUploadDesc": "Debe ser una sola imagen PNG o JPEG",
         "parameterSet": "Conjunto de parámetros",
         "parameterNotSet": "Parámetro no configurado",
-        "problemCopyingImage": "No se puede copiar la imagen"
+        "problemCopyingImage": "No se puede copiar la imagen",
+        "errorCopied": "Error al copiar"
     },
     "tooltip": {
         "feature": {
@@ -443,7 +461,13 @@
         "previousImage": "Imagen anterior",
         "nextImage": "Siguiente imagen",
         "showOptionsPanel": "Mostrar el panel lateral",
-        "menu": "Menú"
+        "menu": "Menú",
+        "showGalleryPanel": "Mostrar panel de galería",
+        "loadMore": "Cargar más",
+        "about": "Acerca de",
+        "createIssue": "Crear un problema",
+        "resetUI": "Interfaz de usuario $t(accessibility.reset)",
+        "mode": "Modo"
     },
     "nodes": {
         "zoomInNodes": "Acercar",
@@ -456,5 +480,68 @@
         "reloadNodeTemplates": "Recargar las plantillas de nodos",
         "loadWorkflow": "Cargar el flujo de trabajo",
         "downloadWorkflow": "Descargar el flujo de trabajo en un archivo JSON"
+    },
+    "boards": {
+        "autoAddBoard": "Agregar panel automáticamente",
+        "changeBoard": "Cambiar el panel",
+        "clearSearch": "Borrar la búsqueda",
+        "deleteBoard": "Borrar el panel",
+        "selectBoard": "Seleccionar un panel",
+        "uncategorized": "Sin categoría",
+        "cancel": "Cancelar",
+        "addBoard": "Agregar un panel",
+        "movingImagesToBoard_one": "Moviendo {{count}} imagen al panel:",
+        "movingImagesToBoard_many": "Moviendo {{count}} imágenes al panel:",
+        "movingImagesToBoard_other": "Moviendo {{count}} imágenes al panel:",
+        "bottomMessage": "Al eliminar este panel y las imágenes que contiene, se restablecerán las funciones que los estén utilizando actualmente.",
+        "deleteBoardAndImages": "Borrar el panel y las imágenes",
+        "loading": "Cargando...",
+        "deletedBoardsCannotbeRestored": "Los paneles eliminados no se pueden restaurar",
+        "move": "Mover",
+        "menuItemAutoAdd": "Agregar automáticamente a este panel",
+        "searchBoard": "Buscando paneles…",
+        "topMessage": "Este panel contiene imágenes utilizadas en las siguientes funciones:",
+        "downloadBoard": "Descargar panel",
+        "deleteBoardOnly": "Borrar solo el panel",
+        "myBoard": "Mi panel",
+        "noMatching": "No hay paneles que coincidan"
+    },
+    "accordions": {
+        "compositing": {
+            "title": "Composición",
+            "infillTab": "Relleno"
+        },
+        "generation": {
+            "title": "Generación"
+        },
+        "image": {
+            "title": "Imagen"
+        },
+        "control": {
+            "title": "Control"
+        },
+        "advanced": {
+            "options": "$t(accordions.advanced.title) opciones",
+            "title": "Avanzado"
+        }
+    },
+    "ui": {
+        "tabs": {
+            "generationTab": "$t(ui.tabs.generation) $t(common.tab)",
+            "canvas": "Lienzo",
+            "generation": "Generación",
+            "queue": "Cola",
+            "queueTab": "$t(ui.tabs.queue) $t(common.tab)",
+            "workflows": "Flujos de trabajo",
+            "models": "Modelos",
+            "modelsTab": "$t(ui.tabs.models) $t(common.tab)",
+            "canvasTab": "$t(ui.tabs.canvas) $t(common.tab)",
+            "workflowsTab": "$t(ui.tabs.workflows) $t(common.tab)"
+        }
+    },
+    "controlLayers": {
+        "layers_one": "Capa",
+        "layers_many": "Capas",
+        "layers_other": "Capas"
     }
 }

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

@@ -5,7 +5,7 @@
         "reportBugLabel": "Segnala un errore",
         "settingsLabel": "Impostazioni",
         "img2img": "Immagine a Immagine",
-        "unifiedCanvas": "Tela unificata",
+        "unifiedCanvas": "Tela",
         "nodes": "Flussi di lavoro",
         "upload": "Caricamento",
         "load": "Carica",
@@ -74,7 +74,18 @@
         "file": "File",
         "toResolve": "Da risolvere",
         "add": "Aggiungi",
-        "loglevel": "Livello di log"
+        "loglevel": "Livello di log",
+        "beta": "Beta",
+        "positivePrompt": "Prompt positivo",
+        "negativePrompt": "Prompt negativo",
+        "selected": "Selezionato",
+        "goTo": "Vai a",
+        "editor": "Editor",
+        "tab": "Scheda",
+        "viewing": "Visualizza",
+        "viewingDesc": "Rivedi le immagini in un'ampia vista della galleria",
+        "editing": "Modifica",
+        "editingDesc": "Modifica nell'area Livelli di controllo"
     },
     "gallery": {
         "galleryImageSize": "Dimensione dell'immagine",
@@ -180,8 +191,8 @@
             "desc": "Mostra le informazioni sui metadati dell'immagine corrente"
         },
         "sendToImageToImage": {
-            "title": "Invia a Immagine a Immagine",
-            "desc": "Invia l'immagine corrente a da Immagine a Immagine"
+            "title": "Invia a Generazione da immagine",
+            "desc": "Invia l'immagine corrente a Generazione da immagine"
         },
         "deleteImage": {
             "title": "Elimina immagine",
@@ -334,6 +345,10 @@
         "remixImage": {
             "desc": "Utilizza tutti i parametri tranne il seme dell'immagine corrente",
             "title": "Remixa l'immagine"
+        },
+        "toggleViewer": {
+            "title": "Attiva/disattiva il visualizzatore di immagini",
+            "desc": "Passa dal Visualizzatore immagini all'area di lavoro per la scheda corrente."
         }
     },
     "modelManager": {
@@ -471,8 +486,8 @@
         "scaledHeight": "Altezza ridimensionata",
         "infillMethod": "Metodo di riempimento",
         "tileSize": "Dimensione piastrella",
-        "sendToImg2Img": "Invia a Immagine a Immagine",
-        "sendToUnifiedCanvas": "Invia a Tela Unificata",
+        "sendToImg2Img": "Invia a Generazione da immagine",
+        "sendToUnifiedCanvas": "Invia alla Tela",
         "downloadImage": "Scarica l'immagine",
         "usePrompt": "Usa Prompt",
         "useSeed": "Usa Seme",
@@ -508,13 +523,24 @@
             "incompatibleBaseModelForControlAdapter": "Il modello dell'adattatore di controllo #{{number}} non è compatibile con il modello principale.",
             "missingNodeTemplate": "Modello di nodo mancante",
             "missingInputForField": "{{nodeLabel}} -> {{fieldLabel}} ingresso mancante",
-            "missingFieldTemplate": "Modello di campo mancante"
+            "missingFieldTemplate": "Modello di campo mancante",
+            "imageNotProcessedForControlAdapter": "L'immagine dell'adattatore di controllo #{{number}} non è stata elaborata",
+            "layer": {
+                "initialImageNoImageSelected": "Nessuna immagine iniziale selezionata",
+                "t2iAdapterIncompatibleDimensions": "L'adattatore T2I richiede che la dimensione dell'immagine sia un multiplo di {{multiple}}",
+                "controlAdapterNoModelSelected": "Nessun modello di Adattatore di Controllo selezionato",
+                "controlAdapterIncompatibleBaseModel": "Il modello base dell'adattatore di controllo non è compatibile",
+                "controlAdapterNoImageSelected": "Nessuna immagine dell'adattatore di controllo selezionata",
+                "controlAdapterImageNotProcessed": "Immagine dell'adattatore di controllo non elaborata",
+                "ipAdapterNoModelSelected": "Nessun adattatore IP selezionato",
+                "ipAdapterIncompatibleBaseModel": "Il modello base dell'adattatore IP non è compatibile",
+                "ipAdapterNoImageSelected": "Nessuna immagine dell'adattatore IP selezionata",
+                "rgNoPromptsOrIPAdapters": "Nessun prompt o adattatore IP",
+                "rgNoRegion": "Nessuna regione selezionata"
+            }
         },
         "useCpuNoise": "Usa la CPU per generare rumore",
         "iterations": "Iterazioni",
-        "iterationsWithCount_one": "{{count}} Iterazione",
-        "iterationsWithCount_many": "{{count}} Iterazioni",
-        "iterationsWithCount_other": "{{count}} Iterazioni",
         "isAllowedToUpscale": {
             "useX2Model": "L'immagine è troppo grande per l'ampliamento con il modello x4, utilizza il modello x2",
             "tooLarge": "L'immagine è troppo grande per l'ampliamento, seleziona un'immagine più piccola"
@@ -534,7 +560,10 @@
         "infillMosaicMinColor": "Colore minimo",
         "infillMosaicMaxColor": "Colore massimo",
         "infillMosaicTileHeight": "Altezza piastrella",
-        "infillColorValue": "Colore di riempimento"
+        "infillColorValue": "Colore di riempimento",
+        "globalSettings": "Impostazioni globali",
+        "globalPositivePromptPlaceholder": "Prompt positivo globale",
+        "globalNegativePromptPlaceholder": "Prompt negativo globale"
     },
     "settings": {
         "models": "Modelli",
@@ -559,7 +588,7 @@
         "intermediatesCleared_one": "Cancellata {{count}} immagine intermedia",
         "intermediatesCleared_many": "Cancellate {{count}} immagini intermedie",
         "intermediatesCleared_other": "Cancellate {{count}} immagini intermedie",
-        "clearIntermediatesDesc1": "La cancellazione delle immagini intermedie ripristinerà lo stato di Tela Unificata e ControlNet.",
+        "clearIntermediatesDesc1": "La cancellazione delle immagini intermedie ripristinerà lo stato della Tela e degli Adattatori di Controllo.",
         "intermediatesClearedFailed": "Problema con la cancellazione delle immagini intermedie",
         "clearIntermediatesWithCount_one": "Cancella {{count}} immagine intermedia",
         "clearIntermediatesWithCount_many": "Cancella {{count}} immagini intermedie",
@@ -575,8 +604,8 @@
         "imageCopied": "Immagine copiata",
         "imageNotLoadedDesc": "Impossibile trovare l'immagine",
         "canvasMerged": "Tela unita",
-        "sentToImageToImage": "Inviato a Immagine a Immagine",
-        "sentToUnifiedCanvas": "Inviato a Tela Unificata",
+        "sentToImageToImage": "Inviato a Generazione da immagine",
+        "sentToUnifiedCanvas": "Inviato alla Tela",
         "parametersNotSet": "Parametri non impostati",
         "metadataLoadFailed": "Impossibile caricare i metadati",
         "serverError": "Errore del Server",
@@ -795,7 +824,7 @@
         "float": "In virgola mobile",
         "currentImageDescription": "Visualizza l'immagine corrente nell'editor dei nodi",
         "fieldTypesMustMatch": "I tipi di campo devono corrispondere",
-        "edge": "Bordo",
+        "edge": "Collegamento",
         "currentImage": "Immagine corrente",
         "integer": "Numero Intero",
         "inputMayOnlyHaveOneConnection": "L'ingresso può avere solo una connessione",
@@ -808,8 +837,8 @@
         "unableToUpdateNodes_other": "Impossibile aggiornare {{count}} nodi",
         "addLinearView": "Aggiungi alla vista Lineare",
         "unknownErrorValidatingWorkflow": "Errore sconosciuto durante la convalida del flusso di lavoro",
-        "collectionFieldType": "{{name}} Raccolta",
-        "collectionOrScalarFieldType": "{{name}} Raccolta|Scalare",
+        "collectionFieldType": "{{name}} (Raccolta)",
+        "collectionOrScalarFieldType": "{{name}} (Singola o Raccolta)",
         "nodeVersion": "Versione Nodo",
         "inputFieldTypeParseError": "Impossibile analizzare il tipo di campo di input {{node}}.{{field}} ({{message}})",
         "unsupportedArrayItemType": "Tipo di elemento dell'array non supportato \"{{type}}\"",
@@ -845,7 +874,15 @@
         "resetToDefaultValue": "Ripristina il valore predefinito",
         "noFieldsViewMode": "Questo flusso di lavoro non ha campi selezionati da visualizzare. Visualizza il flusso di lavoro completo per configurare i valori.",
         "edit": "Modifica",
-        "graph": "Grafico"
+        "graph": "Grafico",
+        "showEdgeLabelsHelp": "Mostra etichette sui collegamenti, che indicano i nodi collegati",
+        "showEdgeLabels": "Mostra le etichette del collegamento",
+        "cannotMixAndMatchCollectionItemTypes": "Impossibile combinare e abbinare i tipi di elementi della raccolta",
+        "noGraph": "Nessun grafico",
+        "missingNode": "Nodo di invocazione mancante",
+        "missingInvocationTemplate": "Modello di invocazione mancante",
+        "missingFieldTemplate": "Modello di campo mancante",
+        "singleFieldType": "{{name}} (Singola)"
     },
     "boards": {
         "autoAddBoard": "Aggiungi automaticamente bacheca",
@@ -922,7 +959,7 @@
         "colorMapTileSize": "Dimensione piastrella",
         "mediapipeFaceDescription": "Rilevamento dei volti tramite Mediapipe",
         "hedDescription": "Rilevamento dei bordi nidificati olisticamente",
-        "setControlImageDimensions": "Imposta le dimensioni dell'immagine di controllo su L/A",
+        "setControlImageDimensions": "Copia le dimensioni in L/A (ottimizza per il modello)",
         "maxFaces": "Numero massimo di volti",
         "addT2IAdapter": "Aggiungi $t(common.t2iAdapter)",
         "addControlNet": "Aggiungi $t(common.controlNet)",
@@ -951,12 +988,17 @@
         "mediapipeFace": "Mediapipe Volto",
         "ip_adapter": "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.ipAdapter))",
         "t2i_adapter": "$t(controlnet.controlAdapter_one) #{{number}} ($t(common.t2iAdapter))",
-        "selectCLIPVisionModel": "Seleziona un modello CLIP Vision"
+        "selectCLIPVisionModel": "Seleziona un modello CLIP Vision",
+        "ipAdapterMethod": "Metodo",
+        "full": "Completo",
+        "composition": "Solo la composizione",
+        "style": "Solo lo stile",
+        "beginEndStepPercentShort": "Inizio/Fine %",
+        "setControlImageDimensionsForce": "Copia le dimensioni in L/A (ignora il modello)"
     },
     "queue": {
         "queueFront": "Aggiungi all'inizio della coda",
         "queueBack": "Aggiungi alla coda",
-        "queueCountPrediction": "{{promptsCount}} prompt × {{iterations}} iterazioni -> {{count}} generazioni",
         "queue": "Coda",
         "status": "Stato",
         "pruneSucceeded": "Rimossi {{item_count}} elementi completati dalla coda",
@@ -993,7 +1035,7 @@
         "cancelBatchSucceeded": "Lotto annullato",
         "clearTooltip": "Annulla e cancella tutti gli elementi",
         "current": "Attuale",
-        "pauseTooltip": "Sospende l'elaborazione",
+        "pauseTooltip": "Sospendi l'elaborazione",
         "failed": "Falliti",
         "cancelItem": "Annulla l'elemento",
         "next": "Prossimo",
@@ -1011,7 +1053,16 @@
         "graphFailedToQueue": "Impossibile mettere in coda il grafico",
         "batchFieldValues": "Valori Campi Lotto",
         "time": "Tempo",
-        "openQueue": "Apri coda"
+        "openQueue": "Apri coda",
+        "iterations_one": "Iterazione",
+        "iterations_many": "Iterazioni",
+        "iterations_other": "Iterazioni",
+        "prompts_one": "Prompt",
+        "prompts_many": "Prompt",
+        "prompts_other": "Prompt",
+        "generations_one": "Generazione",
+        "generations_many": "Generazioni",
+        "generations_other": "Generazioni"
     },
     "models": {
         "noMatchingModels": "Nessun modello corrispondente",
@@ -1394,6 +1445,12 @@
             "paragraphs": [
                 "La dimensione del bordo del passaggio di coerenza."
             ]
+        },
+        "ipAdapterMethod": {
+            "heading": "Metodo",
+            "paragraphs": [
+                "Metodo con cui applicare l'adattatore IP corrente."
+            ]
         }
     },
     "sdxl": {
@@ -1522,5 +1579,55 @@
         "compatibleEmbeddings": "Incorporamenti compatibili",
         "addPromptTrigger": "Aggiungi Trigger nel prompt",
         "noMatchingTriggers": "Nessun Trigger corrispondente"
+    },
+    "controlLayers": {
+        "opacityFilter": "Filtro opacità",
+        "deleteAll": "Cancella tutto",
+        "addLayer": "Aggiungi Livello",
+        "moveToFront": "Sposta in primo piano",
+        "moveToBack": "Sposta in fondo",
+        "moveForward": "Sposta avanti",
+        "moveBackward": "Sposta indietro",
+        "brushSize": "Dimensioni del pennello",
+        "globalMaskOpacity": "Opacità globale della maschera",
+        "autoNegative": "Auto Negativo",
+        "deletePrompt": "Cancella il prompt",
+        "debugLayers": "Debug dei Livelli",
+        "rectangle": "Rettangolo",
+        "maskPreviewColor": "Colore anteprima maschera",
+        "addPositivePrompt": "Aggiungi $t(common.positivePrompt)",
+        "addNegativePrompt": "Aggiungi $t(common.negativePrompt)",
+        "addIPAdapter": "Aggiungi $t(common.ipAdapter)",
+        "regionalGuidance": "Guida regionale",
+        "regionalGuidanceLayer": "$t(unifiedCanvas.layer) $t(controlLayers.regionalGuidance)",
+        "opacity": "Opacità",
+        "globalControlAdapter": "$t(controlnet.controlAdapter_one) Globale",
+        "globalControlAdapterLayer": "$t(controlnet.controlAdapter_one) - $t(unifiedCanvas.layer) Globale",
+        "globalIPAdapter": "$t(common.ipAdapter) Globale",
+        "globalIPAdapterLayer": "$t(common.ipAdapter) - $t(unifiedCanvas.layer) Globale",
+        "globalInitialImage": "Immagine iniziale",
+        "globalInitialImageLayer": "$t(controlLayers.globalInitialImage) - $t(unifiedCanvas.layer) Globale",
+        "clearProcessor": "Cancella processore",
+        "resetProcessor": "Ripristina il processore alle impostazioni predefinite",
+        "noLayersAdded": "Nessun livello aggiunto",
+        "resetRegion": "Reimposta la regione",
+        "controlLayers": "Livelli di controllo",
+        "layers_one": "Livello",
+        "layers_many": "Livelli",
+        "layers_other": "Livelli"
+    },
+    "ui": {
+        "tabs": {
+            "generation": "Generazione",
+            "generationTab": "$t(ui.tabs.generation) $t(common.tab)",
+            "canvas": "Tela",
+            "canvasTab": "$t(ui.tabs.canvas) $t(common.tab)",
+            "workflows": "Flussi di lavoro",
+            "workflowsTab": "$t(ui.tabs.workflows) $t(common.tab)",
+            "models": "Modelli",
+            "modelsTab": "$t(ui.tabs.models) $t(common.tab)",
+            "queue": "Coda",
+            "queueTab": "$t(ui.tabs.queue) $t(common.tab)"
+        }
     }
 }

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

@@ -570,7 +570,6 @@
         "pauseSucceeded": "処理が一時停止されました",
         "queueFront": "キューの先頭へ追加",
         "queueBack": "キューに追加",
-        "queueCountPrediction": "{{promptsCount}} プロンプト × {{iterations}} イテレーション -> {{count}} 枚生成",
         "pause": "一時停止",
         "queue": "キュー",
         "pauseTooltip": "処理を一時停止",

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

@@ -505,7 +505,6 @@
         "completed": "완성된",
         "queueBack": "Queue에 추가",
         "cancelFailed": "항목 취소 중 발생한 문제",
-        "queueCountPrediction": "Queue에 {{predicted}} 추가",
         "batchQueued": "Batch Queued",
         "pauseFailed": "프로세서 중지 중 발생한 문제",
         "clearFailed": "Queue 제거 중 발생한 문제",

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

@@ -6,7 +6,7 @@
         "settingsLabel": "Instellingen",
         "img2img": "Afbeelding naar afbeelding",
         "unifiedCanvas": "Centraal canvas",
-        "nodes": "Werkstroom-editor",
+        "nodes": "Werkstromen",
         "upload": "Upload",
         "load": "Laad",
         "statusDisconnected": "Niet verbonden",
@@ -34,7 +34,60 @@
         "controlNet": "ControlNet",
         "imageFailedToLoad": "Kan afbeelding niet laden",
         "learnMore": "Meer informatie",
-        "advanced": "Uitgebreid"
+        "advanced": "Uitgebreid",
+        "file": "Bestand",
+        "installed": "Geïnstalleerd",
+        "notInstalled": "Niet $t(common.installed)",
+        "simple": "Eenvoudig",
+        "somethingWentWrong": "Er ging iets mis",
+        "add": "Voeg toe",
+        "checkpoint": "Checkpoint",
+        "details": "Details",
+        "outputs": "Uitvoeren",
+        "save": "Bewaar",
+        "nextPage": "Volgende pagina",
+        "blue": "Blauw",
+        "alpha": "Alfa",
+        "red": "Rood",
+        "editor": "Editor",
+        "folder": "Map",
+        "format": "structuur",
+        "goTo": "Ga naar",
+        "template": "Sjabloon",
+        "input": "Invoer",
+        "loglevel": "Logboekniveau",
+        "safetensors": "Safetensors",
+        "saveAs": "Bewaar als",
+        "created": "Gemaakt",
+        "green": "Groen",
+        "tab": "Tab",
+        "positivePrompt": "Positieve prompt",
+        "negativePrompt": "Negatieve prompt",
+        "selected": "Geselecteerd",
+        "orderBy": "Sorteer op",
+        "prevPage": "Vorige pagina",
+        "beta": "Bèta",
+        "copyError": "$t(gallery.copy) Fout",
+        "toResolve": "Op te lossen",
+        "aboutDesc": "Gebruik je Invoke voor het werk? Kijk dan naar:",
+        "aboutHeading": "Creatieve macht voor jou",
+        "copy": "Kopieer",
+        "data": "Gegevens",
+        "or": "of",
+        "updated": "Bijgewerkt",
+        "outpaint": "outpainten",
+        "viewing": "Bekijken",
+        "viewingDesc": "Beoordeel afbeelding in een grote galerijweergave",
+        "editing": "Bewerken",
+        "editingDesc": "Bewerk op het canvas Stuurlagen",
+        "ai": "ai",
+        "inpaint": "inpainten",
+        "unknown": "Onbekend",
+        "delete": "Verwijder",
+        "direction": "Richting",
+        "error": "Fout",
+        "localSystem": "Lokaal systeem",
+        "unknownError": "Onbekende fout"
     },
     "gallery": {
         "galleryImageSize": "Afbeeldingsgrootte",
@@ -310,10 +363,41 @@
         "modelSyncFailed": "Synchronisatie modellen mislukt",
         "modelDeleteFailed": "Model kon niet verwijderd worden",
         "convertingModelBegin": "Model aan het converteren. Even geduld.",
-        "predictionType": "Soort voorspelling (voor Stable Diffusion 2.x-modellen en incidentele Stable Diffusion 1.x-modellen)",
+        "predictionType": "Soort voorspelling",
         "advanced": "Uitgebreid",
         "modelType": "Soort model",
-        "vaePrecision": "Nauwkeurigheid VAE"
+        "vaePrecision": "Nauwkeurigheid VAE",
+        "loraTriggerPhrases": "LoRA-triggerzinnen",
+        "urlOrLocalPathHelper": "URL's zouden moeten wijzen naar een los bestand. Lokale paden kunnen wijzen naar een los bestand of map voor een individueel Diffusers-model.",
+        "modelName": "Modelnaam",
+        "path": "Pad",
+        "triggerPhrases": "Triggerzinnen",
+        "typePhraseHere": "Typ zin hier in",
+        "useDefaultSettings": "Gebruik standaardinstellingen",
+        "modelImageDeleteFailed": "Fout bij verwijderen modelafbeelding",
+        "modelImageUpdated": "Modelafbeelding bijgewerkt",
+        "modelImageUpdateFailed": "Fout bij bijwerken modelafbeelding",
+        "noMatchingModels": "Geen overeenkomende modellen",
+        "scanPlaceholder": "Pad naar een lokale map",
+        "noModelsInstalled": "Geen modellen geïnstalleerd",
+        "noModelsInstalledDesc1": "Installeer modellen met de",
+        "noModelSelected": "Geen model geselecteerd",
+        "starterModels": "Beginnermodellen",
+        "textualInversions": "Tekstuele omkeringen",
+        "upcastAttention": "Upcast-aandacht",
+        "uploadImage": "Upload afbeelding",
+        "mainModelTriggerPhrases": "Triggerzinnen hoofdmodel",
+        "urlOrLocalPath": "URL of lokaal pad",
+        "scanFolderHelper": "De map zal recursief worden ingelezen voor modellen. Dit kan enige tijd in beslag nemen voor erg grote mappen.",
+        "simpleModelPlaceholder": "URL of pad naar een lokaal pad of Diffusers-map",
+        "modelSettings": "Modelinstellingen",
+        "pathToConfig": "Pad naar configuratie",
+        "prune": "Snoei",
+        "pruneTooltip": "Snoei voltooide importeringen uit wachtrij",
+        "repoVariant": "Repovariant",
+        "scanFolder": "Lees map in",
+        "scanResults": "Resultaten inlezen",
+        "source": "Bron"
     },
     "parameters": {
         "images": "Afbeeldingen",
@@ -353,13 +437,13 @@
         "copyImage": "Kopieer afbeelding",
         "denoisingStrength": "Sterkte ontruisen",
         "scheduler": "Planner",
-        "seamlessXAxis": "X-as",
-        "seamlessYAxis": "Y-as",
+        "seamlessXAxis": "Naadloze tegels in x-as",
+        "seamlessYAxis": "Naadloze tegels in y-as",
         "clipSkip": "Overslaan CLIP",
         "negativePromptPlaceholder": "Negatieve prompt",
         "controlNetControlMode": "Aansturingsmodus",
         "positivePromptPlaceholder": "Positieve prompt",
-        "maskBlur": "Vervaag",
+        "maskBlur": "Vervaging van masker",
         "invoke": {
             "noNodesInGraph": "Geen knooppunten in graaf",
             "noModelSelected": "Geen model ingesteld",
@@ -369,11 +453,25 @@
             "missingInputForField": "{{nodeLabel}} -> {{fieldLabel}} invoer ontbreekt",
             "noControlImageForControlAdapter": "Controle-adapter #{{number}} heeft geen controle-afbeelding",
             "noModelForControlAdapter": "Control-adapter #{{number}} heeft geen model ingesteld staan.",
-            "incompatibleBaseModelForControlAdapter": "Model van controle-adapter #{{number}} is ongeldig in combinatie met het hoofdmodel.",
+            "incompatibleBaseModelForControlAdapter": "Model van controle-adapter #{{number}} is niet compatibel met het hoofdmodel.",
             "systemDisconnected": "Systeem is niet verbonden",
             "missingNodeTemplate": "Knooppuntsjabloon ontbreekt",
             "missingFieldTemplate": "Veldsjabloon ontbreekt",
-            "addingImagesTo": "Bezig met toevoegen van afbeeldingen aan"
+            "addingImagesTo": "Bezig met toevoegen van afbeeldingen aan",
+            "layer": {
+                "initialImageNoImageSelected": "geen initiële afbeelding geselecteerd",
+                "controlAdapterNoModelSelected": "geen controle-adaptermodel geselecteerd",
+                "controlAdapterIncompatibleBaseModel": "niet-compatibele basismodel voor controle-adapter",
+                "controlAdapterNoImageSelected": "geen afbeelding voor controle-adapter geselecteerd",
+                "controlAdapterImageNotProcessed": "Afbeelding voor controle-adapter niet verwerkt",
+                "ipAdapterIncompatibleBaseModel": "niet-compatibele basismodel voor IP-adapter",
+                "ipAdapterNoImageSelected": "geen afbeelding voor IP-adapter geselecteerd",
+                "rgNoRegion": "geen gebied geselecteerd",
+                "rgNoPromptsOrIPAdapters": "geen tekstprompts of IP-adapters",
+                "t2iAdapterIncompatibleDimensions": "T2I-adapter vereist een afbeelding met afmetingen met een veelvoud van 64",
+                "ipAdapterNoModelSelected": "geen IP-adapter geselecteerd"
+            },
+            "imageNotProcessedForControlAdapter": "De afbeelding van controle-adapter #{{number}} is niet verwerkt"
         },
         "isAllowedToUpscale": {
             "useX2Model": "Afbeelding is te groot om te vergroten met het x4-model. Gebruik hiervoor het x2-model",
@@ -383,9 +481,26 @@
         "useCpuNoise": "Gebruik CPU-ruis",
         "imageActions": "Afbeeldingshandeling",
         "iterations": "Iteraties",
-        "iterationsWithCount_one": "{{count}} iteratie",
-        "iterationsWithCount_other": "{{count}} iteraties",
-        "coherenceMode": "Modus"
+        "coherenceMode": "Modus",
+        "infillColorValue": "Vulkleur",
+        "remixImage": "Meng afbeelding opnieuw",
+        "setToOptimalSize": "Optimaliseer grootte voor het model",
+        "setToOptimalSizeTooSmall": "$t(parameters.setToOptimalSize) (is mogelijk te klein)",
+        "aspect": "Beeldverhouding",
+        "infillMosaicTileWidth": "Breedte tegel",
+        "setToOptimalSizeTooLarge": "$t(parameters.setToOptimalSize) (is mogelijk te groot)",
+        "lockAspectRatio": "Zet beeldverhouding vast",
+        "infillMosaicTileHeight": "Hoogte tegel",
+        "globalNegativePromptPlaceholder": "Globale negatieve prompt",
+        "globalPositivePromptPlaceholder": "Globale positieve prompt",
+        "useSize": "Gebruik grootte",
+        "swapDimensions": "Wissel afmetingen om",
+        "globalSettings": "Globale instellingen",
+        "coherenceEdgeSize": "Randgrootte",
+        "coherenceMinDenoise": "Min. ontruising",
+        "infillMosaicMinColor": "Min. kleur",
+        "infillMosaicMaxColor": "Max. kleur",
+        "cfgRescaleMultiplier": "Vermenigvuldiger voor CFG-herschaling"
     },
     "settings": {
         "models": "Modellen",
@@ -412,7 +527,12 @@
         "intermediatesCleared_one": "{{count}} tussentijdse afbeelding gewist",
         "intermediatesCleared_other": "{{count}} tussentijdse afbeeldingen gewist",
         "clearIntermediatesDesc1": "Als je tussentijdse afbeeldingen wist, dan wordt de staat hersteld van je canvas en van ControlNet.",
-        "intermediatesClearedFailed": "Fout bij wissen van tussentijdse afbeeldingen"
+        "intermediatesClearedFailed": "Fout bij wissen van tussentijdse afbeeldingen",
+        "clearIntermediatesDisabled": "Wachtrij moet leeg zijn om tussentijdse afbeeldingen te kunnen leegmaken",
+        "enableInformationalPopovers": "Schakel informatieve hulpballonnen in",
+        "enableInvisibleWatermark": "Schakel onzichtbaar watermerk in",
+        "enableNSFWChecker": "Schakel NSFW-controle in",
+        "reloadingIn": "Opnieuw laden na"
     },
     "toast": {
         "uploadFailed": "Upload mislukt",
@@ -427,8 +547,8 @@
         "connected": "Verbonden met server",
         "canceled": "Verwerking geannuleerd",
         "uploadFailedInvalidUploadDesc": "Moet een enkele PNG- of JPEG-afbeelding zijn",
-        "parameterNotSet": "Parameter niet ingesteld",
-        "parameterSet": "Instellen parameters",
+        "parameterNotSet": "{{parameter}} niet ingesteld",
+        "parameterSet": "{{parameter}} ingesteld",
         "problemCopyingImage": "Kan Afbeelding Niet Kopiëren",
         "baseModelChangedCleared_one": "Basismodel is gewijzigd: {{count}} niet-compatibel submodel weggehaald of uitgeschakeld",
         "baseModelChangedCleared_other": "Basismodel is gewijzigd: {{count}} niet-compatibele submodellen weggehaald of uitgeschakeld",
@@ -445,11 +565,11 @@
         "maskSavedAssets": "Masker bewaard in Assets",
         "problemDownloadingCanvas": "Fout bij downloaden van canvas",
         "problemMergingCanvas": "Fout bij samenvoegen canvas",
-        "setCanvasInitialImage": "Ingesteld als initiële canvasafbeelding",
+        "setCanvasInitialImage": "Initiële canvasafbeelding ingesteld",
         "imageUploaded": "Afbeelding geüpload",
         "addedToBoard": "Toegevoegd aan bord",
         "workflowLoaded": "Werkstroom geladen",
-        "modelAddedSimple": "Model toegevoegd",
+        "modelAddedSimple": "Model toegevoegd aan wachtrij",
         "problemImportingMaskDesc": "Kan masker niet exporteren",
         "problemCopyingCanvas": "Fout bij kopiëren canvas",
         "problemSavingCanvas": "Fout bij bewaren canvas",
@@ -461,7 +581,18 @@
         "maskSentControlnetAssets": "Masker gestuurd naar ControlNet en Assets",
         "canvasSavedGallery": "Canvas bewaard in galerij",
         "imageUploadFailed": "Fout bij uploaden afbeelding",
-        "problemImportingMask": "Fout bij importeren masker"
+        "problemImportingMask": "Fout bij importeren masker",
+        "workflowDeleted": "Werkstroom verwijderd",
+        "invalidUpload": "Ongeldige upload",
+        "uploadInitialImage": "Initiële afbeelding uploaden",
+        "setAsCanvasInitialImage": "Ingesteld als initiële afbeelding voor canvas",
+        "problemRetrievingWorkflow": "Fout bij ophalen van werkstroom",
+        "parameters": "Parameters",
+        "modelImportCanceled": "Importeren model geannuleerd",
+        "problemDeletingWorkflow": "Fout bij verwijderen van werkstroom",
+        "prunedQueue": "Wachtrij gesnoeid",
+        "problemDownloadingImage": "Fout bij downloaden afbeelding",
+        "resetInitialImage": "Initiële afbeelding hersteld"
     },
     "tooltip": {
         "feature": {
@@ -535,7 +666,11 @@
         "showOptionsPanel": "Toon zijscherm",
         "menu": "Menu",
         "showGalleryPanel": "Toon deelscherm Galerij",
-        "loadMore": "Laad meer"
+        "loadMore": "Laad meer",
+        "about": "Over",
+        "mode": "Modus",
+        "resetUI": "$t(accessibility.reset) UI",
+        "createIssue": "Maak probleem aan"
     },
     "nodes": {
         "zoomOutNodes": "Uitzoomen",
@@ -549,7 +684,7 @@
         "loadWorkflow": "Laad werkstroom",
         "downloadWorkflow": "Download JSON van werkstroom",
         "scheduler": "Planner",
-        "missingTemplate": "Ontbrekende sjabloon",
+        "missingTemplate": "Ongeldig knooppunt: knooppunt {{node}} van het soort {{type}} heeft een ontbrekend sjabloon (niet geïnstalleerd?)",
         "workflowDescription": "Korte beschrijving",
         "versionUnknown": " Versie onbekend",
         "noNodeSelected": "Geen knooppunt gekozen",
@@ -565,7 +700,7 @@
         "integer": "Geheel getal",
         "nodeTemplate": "Sjabloon knooppunt",
         "nodeOpacity": "Dekking knooppunt",
-        "unableToLoadWorkflow": "Kan werkstroom niet valideren",
+        "unableToLoadWorkflow": "Fout bij laden werkstroom",
         "snapToGrid": "Lijn uit op raster",
         "noFieldsLinearview": "Geen velden toegevoegd aan lineaire weergave",
         "nodeSearch": "Zoek naar knooppunten",
@@ -616,11 +751,56 @@
         "unknownField": "Onbekend veld",
         "colorCodeEdges": "Kleurgecodeerde randen",
         "unknownNode": "Onbekend knooppunt",
-        "mismatchedVersion": "Heeft niet-overeenkomende versie",
+        "mismatchedVersion": "Ongeldig knooppunt: knooppunt {{node}} van het soort {{type}} heeft een niet-overeenkomende versie (probeer het bij te werken?)",
         "addNodeToolTip": "Voeg knooppunt toe (Shift+A, spatie)",
         "loadingNodes": "Bezig met laden van knooppunten...",
         "snapToGridHelp": "Lijn knooppunten uit op raster bij verplaatsing",
-        "workflowSettings": "Instellingen werkstroomeditor"
+        "workflowSettings": "Instellingen werkstroomeditor",
+        "addLinearView": "Voeg toe aan lineaire weergave",
+        "nodePack": "Knooppuntpakket",
+        "unknownInput": "Onbekende invoer: {{name}}",
+        "sourceNodeFieldDoesNotExist": "Ongeldige rand: bron-/uitvoerveld {{node}}.{{field}} bestaat niet",
+        "collectionFieldType": "Verzameling {{name}}",
+        "deletedInvalidEdge": "Ongeldige hoek {{source}} -> {{target}} verwijderd",
+        "graph": "Grafiek",
+        "targetNodeDoesNotExist": "Ongeldige rand: doel-/invoerknooppunt {{node}} bestaat niet",
+        "resetToDefaultValue": "Herstel naar standaardwaarden",
+        "editMode": "Bewerk in Werkstroom-editor",
+        "showEdgeLabels": "Toon randlabels",
+        "showEdgeLabelsHelp": "Toon labels aan randen, waarmee de verbonden knooppunten mee worden aangegeven",
+        "clearWorkflowDesc2": "Je huidige werkstroom heeft niet-bewaarde wijzigingen.",
+        "unableToParseFieldType": "fout bij bepalen soort veld",
+        "sourceNodeDoesNotExist": "Ongeldige rand: bron-/uitvoerknooppunt {{node}} bestaat niet",
+        "unsupportedArrayItemType": "niet-ondersteunde soort van het array-onderdeel \"{{type}}\"",
+        "targetNodeFieldDoesNotExist": "Ongeldige rand: doel-/invoerveld {{node}}.{{field}} bestaat niet",
+        "reorderLinearView": "Herorden lineaire weergave",
+        "newWorkflowDesc": "Een nieuwe werkstroom aanmaken?",
+        "collectionOrScalarFieldType": "Verzameling|scalair {{name}}",
+        "newWorkflow": "Nieuwe werkstroom",
+        "unknownErrorValidatingWorkflow": "Onbekende fout bij valideren werkstroom",
+        "unsupportedAnyOfLength": "te veel union-leden ({{count}})",
+        "unknownOutput": "Onbekende uitvoer: {{name}}",
+        "viewMode": "Gebruik in lineaire weergave",
+        "unableToExtractSchemaNameFromRef": "fout bij het extraheren van de schemanaam via de ref",
+        "unsupportedMismatchedUnion": "niet-overeenkomende soort CollectionOrScalar met basissoorten {{firstType}} en {{secondType}}",
+        "unknownNodeType": "Onbekend soort knooppunt",
+        "edit": "Bewerk",
+        "updateAllNodes": "Werk knooppunten bij",
+        "allNodesUpdated": "Alle knooppunten bijgewerkt",
+        "nodeVersion": "Knooppuntversie",
+        "newWorkflowDesc2": "Je huidige werkstroom heeft niet-bewaarde wijzigingen.",
+        "clearWorkflow": "Maak werkstroom leeg",
+        "clearWorkflowDesc": "Deze werkstroom leegmaken en met een nieuwe beginnen?",
+        "inputFieldTypeParseError": "Fout bij bepalen van het soort invoerveld {{node}}.{{field}} ({{message}})",
+        "outputFieldTypeParseError": "Fout bij het bepalen van het soort uitvoerveld {{node}}.{{field}} ({{message}})",
+        "unableToExtractEnumOptions": "fout bij extraheren enumeratie-opties",
+        "unknownFieldType": "Soort $t(nodes.unknownField): {{type}}",
+        "unableToGetWorkflowVersion": "Fout bij ophalen schemaversie van werkstroom",
+        "betaDesc": "Deze uitvoering is in bèta. Totdat deze stabiel is kunnen er wijzigingen voorkomen gedurende app-updates die zaken kapotmaken. We zijn van plan om deze uitvoering op lange termijn te gaan ondersteunen.",
+        "prototypeDesc": "Deze uitvoering is een prototype. Er kunnen wijzigingen voorkomen gedurende app-updates die zaken kapotmaken. Deze kunnen op een willekeurig moment verwijderd worden.",
+        "noFieldsViewMode": "Deze werkstroom heeft geen geselecteerde velden om te tonen. Bekijk de volledige werkstroom om de waarden te configureren.",
+        "unableToUpdateNodes_one": "Fout bij bijwerken van {{count}} knooppunt",
+        "unableToUpdateNodes_other": "Fout bij bijwerken van {{count}} knooppunten"
     },
     "controlnet": {
         "amult": "a_mult",
@@ -693,9 +873,28 @@
         "canny": "Canny",
         "depthZoeDescription": "Genereer diepteblad via Zoe",
         "hedDescription": "Herkenning van holistisch-geneste randen",
-        "setControlImageDimensions": "Stel afmetingen controle-afbeelding in op B/H",
+        "setControlImageDimensions": "Kopieer grootte naar B/H (optimaliseer voor model)",
         "scribble": "Krabbel",
-        "maxFaces": "Max. gezichten"
+        "maxFaces": "Max. gezichten",
+        "dwOpenpose": "DW Openpose",
+        "depthAnything": "Depth Anything",
+        "base": "Basis",
+        "hands": "Handen",
+        "selectCLIPVisionModel": "Selecteer een CLIP Vision-model",
+        "modelSize": "Modelgrootte",
+        "small": "Klein",
+        "large": "Groot",
+        "resizeSimple": "Wijzig grootte (eenvoudig)",
+        "beginEndStepPercentShort": "Begin-/eind-%",
+        "depthAnythingDescription": "Genereren dieptekaart d.m.v. de techniek Depth Anything",
+        "face": "Gezicht",
+        "body": "Lichaam",
+        "dwOpenposeDescription": "Schatting menselijke pose d.m.v. DW Openpose",
+        "ipAdapterMethod": "Methode",
+        "full": "Volledig",
+        "style": "Alleen stijl",
+        "composition": "Alleen samenstelling",
+        "setControlImageDimensionsForce": "Kopieer grootte naar B/H (negeer model)"
     },
     "dynamicPrompts": {
         "seedBehaviour": {
@@ -708,7 +907,10 @@
         "maxPrompts": "Max. prompts",
         "promptsWithCount_one": "{{count}} prompt",
         "promptsWithCount_other": "{{count}} prompts",
-        "dynamicPrompts": "Dynamische prompts"
+        "dynamicPrompts": "Dynamische prompts",
+        "showDynamicPrompts": "Toon dynamische prompts",
+        "loading": "Genereren van dynamische prompts...",
+        "promptsPreview": "Voorvertoning prompts"
     },
     "popovers": {
         "noiseUseCPU": {
@@ -721,7 +923,7 @@
         },
         "paramScheduler": {
             "paragraphs": [
-                "De planner bepaalt hoe ruis per iteratie wordt toegevoegd aan een afbeelding of hoe een monster wordt bijgewerkt op basis van de uitvoer van een model."
+                "De planner gebruikt gedurende het genereringsproces."
             ],
             "heading": "Planner"
         },
@@ -808,8 +1010,8 @@
         },
         "clipSkip": {
             "paragraphs": [
-                "Kies hoeveel CLIP-modellagen je wilt overslaan.",
-                "Bepaalde modellen werken beter met bepaalde Overslaan CLIP-instellingen."
+                "Aantal over te slaan CLIP-modellagen.",
+                "Bepaalde modellen zijn beter geschikt met bepaalde Overslaan CLIP-instellingen."
             ],
             "heading": "Overslaan CLIP"
         },
@@ -940,7 +1142,6 @@
         "completed": "Voltooid",
         "queueBack": "Voeg toe aan wachtrij",
         "cancelFailed": "Fout bij annuleren onderdeel",
-        "queueCountPrediction": "Voeg {{predicted}} toe aan wachtrij",
         "batchQueued": "Reeks in wachtrij geplaatst",
         "pauseFailed": "Fout bij onderbreken verwerker",
         "clearFailed": "Fout bij wissen van wachtrij",
@@ -994,17 +1195,26 @@
         "denoisingStrength": "Sterkte ontruising",
         "refinermodel": "Verfijningsmodel",
         "posAestheticScore": "Positieve esthetische score",
-        "concatPromptStyle": "Plak prompt- en stijltekst aan elkaar",
+        "concatPromptStyle": "Koppelen van prompt en stijl",
         "loading": "Bezig met laden...",
         "steps": "Stappen",
-        "posStylePrompt": "Positieve-stijlprompt"
+        "posStylePrompt": "Positieve-stijlprompt",
+        "freePromptStyle": "Handmatige stijlprompt",
+        "refinerSteps": "Aantal stappen verfijner"
     },
     "models": {
         "noMatchingModels": "Geen overeenkomend modellen",
         "loading": "bezig met laden",
         "noMatchingLoRAs": "Geen overeenkomende LoRA's",
         "noModelsAvailable": "Geen modellen beschikbaar",
-        "selectModel": "Kies een model"
+        "selectModel": "Kies een model",
+        "noLoRAsInstalled": "Geen LoRA's geïnstalleerd",
+        "noRefinerModelsInstalled": "Geen SDXL-verfijningsmodellen geïnstalleerd",
+        "defaultVAE": "Standaard-VAE",
+        "lora": "LoRA",
+        "esrganModel": "ESRGAN-model",
+        "addLora": "Voeg LoRA toe",
+        "concepts": "Concepten"
     },
     "boards": {
         "autoAddBoard": "Voeg automatisch bord toe",
@@ -1022,7 +1232,13 @@
         "downloadBoard": "Download bord",
         "changeBoard": "Wijzig bord",
         "loading": "Bezig met laden...",
-        "clearSearch": "Maak zoekopdracht leeg"
+        "clearSearch": "Maak zoekopdracht leeg",
+        "deleteBoard": "Verwijder bord",
+        "deleteBoardAndImages": "Verwijder bord en afbeeldingen",
+        "deleteBoardOnly": "Verwijder alleen bord",
+        "deletedBoardsCannotbeRestored": "Verwijderde borden kunnen niet worden hersteld",
+        "movingImagesToBoard_one": "Verplaatsen van {{count}} afbeelding naar bord:",
+        "movingImagesToBoard_other": "Verplaatsen van {{count}} afbeeldingen naar bord:"
     },
     "invocationCache": {
         "disable": "Schakel uit",
@@ -1039,5 +1255,39 @@
         "clear": "Wis",
         "maxCacheSize": "Max. grootte cache",
         "cacheSize": "Grootte cache"
+    },
+    "accordions": {
+        "generation": {
+            "title": "Genereren"
+        },
+        "image": {
+            "title": "Afbeelding"
+        },
+        "advanced": {
+            "title": "Geavanceerd",
+            "options": "$t(accordions.advanced.title) Opties"
+        },
+        "control": {
+            "title": "Besturing"
+        },
+        "compositing": {
+            "title": "Samenstellen",
+            "coherenceTab": "Coherentiefase",
+            "infillTab": "Invullen"
+        }
+    },
+    "hrf": {
+        "upscaleMethod": "Opschaalmethode",
+        "metadata": {
+            "strength": "Sterkte oplossing voor hoge resolutie",
+            "method": "Methode oplossing voor hoge resolutie",
+            "enabled": "Oplossing voor hoge resolutie ingeschakeld"
+        },
+        "hrf": "Oplossing voor hoge resolutie",
+        "enableHrf": "Schakel oplossing in voor hoge resolutie"
+    },
+    "prompt": {
+        "addPromptTrigger": "Voeg prompttrigger toe",
+        "compatibleEmbeddings": "Compatibele embeddings"
     }
 }

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

@@ -76,7 +76,18 @@
         "localSystem": "Локальная система",
         "aboutDesc": "Используя Invoke для работы? Проверьте это:",
         "add": "Добавить",
-        "loglevel": "Уровень логов"
+        "loglevel": "Уровень логов",
+        "beta": "Бета",
+        "selected": "Выбрано",
+        "positivePrompt": "Позитивный запрос",
+        "negativePrompt": "Негативный запрос",
+        "editor": "Редактор",
+        "goTo": "Перейти к",
+        "tab": "Вкладка",
+        "viewing": "Просмотр",
+        "editing": "Редактирование",
+        "viewingDesc": "Просмотр изображений в режиме большой галереи",
+        "editingDesc": "Редактировать на холсте слоёв управления"
     },
     "gallery": {
         "galleryImageSize": "Размер изображений",
@@ -87,8 +98,8 @@
         "deleteImagePermanent": "Удаленные изображения невозможно восстановить.",
         "deleteImageBin": "Удаленные изображения будут отправлены в корзину вашей операционной системы.",
         "deleteImage_one": "Удалить изображение",
-        "deleteImage_few": "",
-        "deleteImage_many": "",
+        "deleteImage_few": "Удалить {{count}} изображения",
+        "deleteImage_many": "Удалить {{count}} изображений",
         "assets": "Ресурсы",
         "autoAssignBoardOnClick": "Авто-назначение доски по клику",
         "deleteSelection": "Удалить выделенное",
@@ -336,6 +347,10 @@
         "remixImage": {
             "desc": "Используйте все параметры, кроме сида из текущего изображения",
             "title": "Ремикс изображения"
+        },
+        "toggleViewer": {
+            "title": "Переключить просмотр изображений",
+            "desc": "Переключение между средством просмотра изображений и рабочей областью для текущей вкладки."
         }
     },
     "modelManager": {
@@ -512,7 +527,8 @@
             "missingNodeTemplate": "Отсутствует шаблон узла",
             "missingFieldTemplate": "Отсутствует шаблон поля",
             "addingImagesTo": "Добавление изображений в",
-            "invoke": "Создать"
+            "invoke": "Создать",
+            "imageNotProcessedForControlAdapter": "Изображение адаптера контроля №{{number}} не обрабатывается"
         },
         "isAllowedToUpscale": {
             "useX2Model": "Изображение слишком велико для увеличения с помощью модели x4. Используйте модель x2",
@@ -523,9 +539,6 @@
         "useCpuNoise": "Использовать шум CPU",
         "imageActions": "Действия с изображениями",
         "iterations": "Кол-во",
-        "iterationsWithCount_one": "{{count}} Интеграция",
-        "iterationsWithCount_few": "{{count}} Итерации",
-        "iterationsWithCount_many": "{{count}} Итераций",
         "useSize": "Использовать размер",
         "coherenceMode": "Режим",
         "aspect": "Соотношение",
@@ -541,7 +554,10 @@
         "infillMosaicTileHeight": "Высота плиток",
         "infillMosaicMinColor": "Мин цвет",
         "infillMosaicMaxColor": "Макс цвет",
-        "infillColorValue": "Цвет заливки"
+        "infillColorValue": "Цвет заливки",
+        "globalSettings": "Глобальные настройки",
+        "globalNegativePromptPlaceholder": "Глобальный негативный запрос",
+        "globalPositivePromptPlaceholder": "Глобальный запрос"
     },
     "settings": {
         "models": "Модели",
@@ -706,7 +722,9 @@
         "coherenceModeBoxBlur": "коробчатое размытие",
         "discardCurrent": "Отбросить текущее",
         "invertBrushSizeScrollDirection": "Инвертировать прокрутку для размера кисти",
-        "initialFitImageSize": "Подогнать размер изображения при перебросе"
+        "initialFitImageSize": "Подогнать размер изображения при перебросе",
+        "hideBoundingBox": "Скрыть ограничительную рамку",
+        "showBoundingBox": "Показать ограничительную рамку"
     },
     "accessibility": {
         "uploadImage": "Загрузить изображение",
@@ -849,7 +867,10 @@
         "editMode": "Открыть в редакторе узлов",
         "resetToDefaultValue": "Сбросить к стандартному значкнию",
         "edit": "Редактировать",
-        "noFieldsViewMode": "В этом рабочем процессе нет выбранных полей для отображения. Просмотрите полный рабочий процесс для настройки значений."
+        "noFieldsViewMode": "В этом рабочем процессе нет выбранных полей для отображения. Просмотрите полный рабочий процесс для настройки значений.",
+        "graph": "График",
+        "showEdgeLabels": "Показать метки на ребрах",
+        "showEdgeLabelsHelp": "Показать метки на ребрах, указывающие на соединенные узлы"
     },
     "controlnet": {
         "amult": "a_mult",
@@ -917,8 +938,8 @@
         "lineartAnime": "Контурный рисунок в стиле аниме",
         "mediapipeFaceDescription": "Обнаружение лиц с помощью Mediapipe",
         "hedDescription": "Целостное обнаружение границ",
-        "setControlImageDimensions": "Установите размеры контрольного изображения на Ш/В",
-        "scribble": "каракули",
+        "setControlImageDimensions": "Скопируйте размер в Ш/В (оптимизируйте для модели)",
+        "scribble": "Штрихи",
         "maxFaces": "Макс Лица",
         "mlsdDescription": "Минималистичный детектор отрезков линии",
         "resizeSimple": "Изменить размер (простой)",
@@ -933,7 +954,18 @@
         "small": "Маленький",
         "body": "Тело",
         "hands": "Руки",
-        "selectCLIPVisionModel": "Выбрать модель CLIP Vision"
+        "selectCLIPVisionModel": "Выбрать модель CLIP Vision",
+        "ipAdapterMethod": "Метод",
+        "full": "Всё",
+        "mlsd": "M-LSD",
+        "h": "H",
+        "style": "Только стиль",
+        "dwOpenpose": "DW Openpose",
+        "pidi": "PIDI",
+        "composition": "Только композиция",
+        "hed": "HED",
+        "beginEndStepPercentShort": "Начало/конец %",
+        "setControlImageDimensionsForce": "Скопируйте размер в Ш/В (игнорируйте модель)"
     },
     "boards": {
         "autoAddBoard": "Авто добавление Доски",
@@ -1312,6 +1344,12 @@
             "paragraphs": [
                 "Плавно укладывайте изображение вдоль вертикальной оси."
             ]
+        },
+        "ipAdapterMethod": {
+            "heading": "Метод",
+            "paragraphs": [
+                "Метод, с помощью которого применяется текущий IP-адаптер."
+            ]
         }
     },
     "metadata": {
@@ -1359,7 +1397,6 @@
         "completed": "Выполнено",
         "queueBack": "Добавить в очередь",
         "cancelFailed": "Проблема с отменой элемента",
-        "queueCountPrediction": "{{promptsCount}} запросов × {{iterations}} изображений -> {{count}} генераций",
         "batchQueued": "Пакетная очередь",
         "pauseFailed": "Проблема с приостановкой рендеринга",
         "clearFailed": "Проблема с очисткой очереди",
@@ -1475,7 +1512,11 @@
         "projectWorkflows": "Рабочие процессы проекта",
         "defaultWorkflows": "Стандартные рабочие процессы",
         "name": "Имя",
-        "noRecentWorkflows": "Нет последних рабочих процессов"
+        "noRecentWorkflows": "Нет последних рабочих процессов",
+        "loadWorkflow": "Рабочий процесс $t(common.load)",
+        "convertGraph": "Конвертировать график",
+        "loadFromGraph": "Загрузка рабочего процесса из графика",
+        "autoLayout": "Автоматическое расположение"
     },
     "hrf": {
         "enableHrf": "Включить исправление высокого разрешения",
@@ -1528,5 +1569,55 @@
         "addPromptTrigger": "Добавить триггер запроса",
         "compatibleEmbeddings": "Совместимые встраивания",
         "noMatchingTriggers": "Нет соответствующих триггеров"
+    },
+    "controlLayers": {
+        "moveToBack": "На задний план",
+        "moveForward": "Переместить вперёд",
+        "moveBackward": "Переместить назад",
+        "brushSize": "Размер кисти",
+        "controlLayers": "Слои управления",
+        "globalMaskOpacity": "Глобальная непрозрачность маски",
+        "autoNegative": "Авто негатив",
+        "deletePrompt": "Удалить запрос",
+        "resetRegion": "Сбросить регион",
+        "debugLayers": "Слои отладки",
+        "rectangle": "Прямоугольник",
+        "maskPreviewColor": "Цвет предпросмотра маски",
+        "addNegativePrompt": "Добавить $t(common.negativePrompt)",
+        "regionalGuidance": "Региональная точность",
+        "opacity": "Непрозрачность",
+        "globalControlAdapter": "Глобальный $t(controlnet.controlAdapter_one)",
+        "globalControlAdapterLayer": "Глобальный $t(controlnet.controlAdapter_one) $t(unifiedCanvas.layer)",
+        "globalIPAdapter": "Глобальный $t(common.ipAdapter)",
+        "globalIPAdapterLayer": "Глобальный $t(common.ipAdapter) $t(unifiedCanvas.layer)",
+        "opacityFilter": "Фильтр непрозрачности",
+        "deleteAll": "Удалить всё",
+        "addLayer": "Добавить слой",
+        "moveToFront": "На передний план",
+        "addPositivePrompt": "Добавить $t(common.positivePrompt)",
+        "addIPAdapter": "Добавить $t(common.ipAdapter)",
+        "regionalGuidanceLayer": "$t(controlLayers.regionalGuidance) $t(unifiedCanvas.layer)",
+        "resetProcessor": "Сброс процессора по умолчанию",
+        "clearProcessor": "Чистый процессор",
+        "globalInitialImage": "Глобальное исходное изображение",
+        "globalInitialImageLayer": "$t(controlLayers.globalInitialImage) $t(unifiedCanvas.layer)",
+        "noLayersAdded": "Без слоев",
+        "layers_one": "Слой",
+        "layers_few": "Слоя",
+        "layers_many": "Слоев"
+    },
+    "ui": {
+        "tabs": {
+            "generation": "Генерация",
+            "canvas": "Холст",
+            "workflowsTab": "$t(ui.tabs.workflows) $t(common.tab)",
+            "models": "Модели",
+            "generationTab": "$t(ui.tabs.generation) $t(common.tab)",
+            "workflows": "Рабочие процессы",
+            "canvasTab": "$t(ui.tabs.canvas) $t(common.tab)",
+            "queueTab": "$t(ui.tabs.queue) $t(common.tab)",
+            "modelsTab": "$t(ui.tabs.models) $t(common.tab)",
+            "queue": "Очередь"
+        }
     }
 }

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

@@ -66,7 +66,7 @@
         "saveAs": "保存为",
         "ai": "ai",
         "or": "或",
-        "aboutDesc": "使用 Invoke 工作？查看：",
+        "aboutDesc": "使用 Invoke 工作？来看看：",
         "add": "添加",
         "loglevel": "日志级别",
         "copy": "复制",
@@ -445,7 +445,6 @@
             "useX2Model": "图像太大，无法使用 x4 模型，使用 x2 模型作为替代",
             "tooLarge": "图像太大无法进行放大，请选择更小的图像"
         },
-        "iterationsWithCount_other": "{{count}} 次迭代生成",
         "cfgRescaleMultiplier": "CFG 重缩放倍数",
         "useSize": "使用尺寸",
         "setToOptimalSize": "优化模型大小",
@@ -853,7 +852,6 @@
         "pruneSucceeded": "从队列修剪 {{item_count}} 个已完成的项目",
         "notReady": "无法排队",
         "batchFailedToQueue": "批次加入队列失败",
-        "queueCountPrediction": "{{promptsCount}} 提示词 × {{iterations}} 迭代次数 -> {{count}} 次生成",
         "batchQueued": "加入队列的批次",
         "front": "前",
         "pruneTooltip": "修剪 {{item_count}} 个已完成的项目",

invokeai/frontend/web/scripts/typegen.js

@@ -1,3 +1,4 @@
+/* eslint-disable no-console */
 import fs from 'node:fs';
 
 import openapiTS from 'openapi-typescript';

invokeai/frontend/web/src/app/components/App.tsx

@@ -21,10 +21,10 @@ import i18n from 'i18n';
 import { size } from 'lodash-es';
 import { memo, useCallback, useEffect } from 'react';
 import { ErrorBoundary } from 'react-error-boundary';
+import { useGetOpenAPISchemaQuery } from 'services/api/endpoints/appInfo';
 
 import AppErrorBoundaryFallback from './AppErrorBoundaryFallback';
 import PreselectedImage from './PreselectedImage';
-import Toaster from './Toaster';
 
 const DEFAULT_CONFIG = {};
 
@@ -46,6 +46,7 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage }: Props) => {
   useSocketIO();
   useGlobalModifiersInit();
   useGlobalHotkeys();
+  useGetOpenAPISchemaQuery();
 
   const { dropzone, isHandlingUpload, setIsHandlingUpload } = useFullscreenDropzone();
 
@@ -94,7 +95,6 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage }: Props) => {
       <DeleteImageModal />
       <ChangeBoardModal />
       <DynamicPromptsModal />
-      <Toaster />
       <PreselectedImage selectedImage={selectedImage} />
     </ErrorBoundary>
   );

invokeai/frontend/web/src/app/components/AppErrorBoundaryFallback.tsx

@@ -1,5 +1,8 @@
-import { Button, Flex, Heading, Link, Text, useToast } from '@invoke-ai/ui-library';
+import { Button, Flex, Heading, Image, Link, Text } from '@invoke-ai/ui-library';
+import { useAppSelector } from 'app/store/storeHooks';
+import { toast } from 'features/toast/toast';
 import newGithubIssueUrl from 'new-github-issue-url';
+import InvokeLogoYellow from 'public/assets/images/invoke-symbol-ylw-lrg.svg';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiArrowCounterClockwiseBold, PiArrowSquareOutBold, PiCopyBold } from 'react-icons/pi';
@@ -11,31 +14,39 @@ type Props = {
 };
 
 const AppErrorBoundaryFallback = ({ error, resetErrorBoundary }: Props) => {
-  const toast = useToast();
   const { t } = useTranslation();
+  const isLocal = useAppSelector((s) => s.config.isLocal);
 
   const handleCopy = useCallback(() => {
     const text = JSON.stringify(serializeError(error), null, 2);
     navigator.clipboard.writeText(`\`\`\`\n${text}\n\`\`\``);
     toast({
-      title: 'Error Copied',
+      id: 'ERROR_COPIED',
+      title: t('toast.errorCopied'),
     });
-  }, [error, toast]);
+  }, [error, t]);
 
-  const url = useMemo(
-    () =>
-      newGithubIssueUrl({
+  const url = useMemo(() => {
+    if (isLocal) {
+      return newGithubIssueUrl({
         user: 'invoke-ai',
         repo: 'InvokeAI',
         template: 'BUG_REPORT.yml',
         title: `[bug]: ${error.name}: ${error.message}`,
-      }),
-    [error.message, error.name]
-  );
+      });
+    } else {
+      return 'https://support.invoke.ai/support/tickets/new';
+    }
+  }, [error.message, error.name, isLocal]);
+
   return (
     <Flex layerStyle="body" w="100vw" h="100vh" alignItems="center" justifyContent="center" p={4}>
       <Flex layerStyle="first" flexDir="column" borderRadius="base" justifyContent="center" gap={8} p={16}>
-        <Heading>{t('common.somethingWentWrong')}</Heading>
+        <Flex alignItems="center" gap="2">
+          <Image src={InvokeLogoYellow} alt="invoke-logo" w="24px" h="24px" minW="24px" minH="24px" userSelect="none" />
+          <Heading fontSize="2xl">{t('common.somethingWentWrong')}</Heading>
+        </Flex>
+
         <Flex
           layerStyle="second"
           px={8}
@@ -57,7 +68,9 @@ const AppErrorBoundaryFallback = ({ error, resetErrorBoundary }: Props) => {
             {t('common.copyError')}
           </Button>
           <Link href={url} isExternal>
-            <Button leftIcon={<PiArrowSquareOutBold />}>{t('accessibility.createIssue')}</Button>
+            <Button leftIcon={<PiArrowSquareOutBold />}>
+              {isLocal ? t('accessibility.createIssue') : t('accessibility.submitSupportTicket')}
+            </Button>
           </Link>
         </Flex>
       </Flex>

invokeai/frontend/web/src/app/components/Toaster.ts

@@ -1,44 +0,0 @@
-import { useToast } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { addToast, clearToastQueue } from 'features/system/store/systemSlice';
-import type { MakeToastArg } from 'features/system/util/makeToast';
-import { makeToast } from 'features/system/util/makeToast';
-import { memo, useCallback, useEffect } from 'react';
-
-/**
- * Logical component. Watches the toast queue and makes toasts when the queue is not empty.
- * @returns null
- */
-const Toaster = () => {
-  const dispatch = useAppDispatch();
-  const toastQueue = useAppSelector((s) => s.system.toastQueue);
-  const toast = useToast();
-  useEffect(() => {
-    toastQueue.forEach((t) => {
-      toast(t);
-    });
-    toastQueue.length > 0 && dispatch(clearToastQueue());
-  }, [dispatch, toast, toastQueue]);
-
-  return null;
-};
-
-/**
- * Returns a function that can be used to make a toast.
- * @example
- * const toaster = useAppToaster();
- * toaster('Hello world!');
- * toaster({ title: 'Hello world!', status: 'success' });
- * @returns A function that can be used to make a toast.
- * @see makeToast
- * @see MakeToastArg
- * @see UseToastOptions
- */
-export const useAppToaster = () => {
-  const dispatch = useAppDispatch();
-  const toaster = useCallback((arg: MakeToastArg) => dispatch(addToast(makeToast(arg))), [dispatch]);
-
-  return toaster;
-};
-
-export default memo(Toaster);

invokeai/frontend/web/src/app/hooks/useSocketIO.ts

@@ -67,6 +67,8 @@ export const useSocketIO = () => {
 
     if ($isDebugging.get() || import.meta.env.MODE === 'development') {
       window.$socketOptions = $socketOptions;
+      // This is only enabled manually for debugging, console is allowed.
+      /* eslint-disable-next-line no-console */
       console.log('Socket initialized', socket);
     }
 
@@ -75,6 +77,8 @@ export const useSocketIO = () => {
     return () => {
       if ($isDebugging.get() || import.meta.env.MODE === 'development') {
         window.$socketOptions = undefined;
+        // This is only enabled manually for debugging, console is allowed.
+        /* eslint-disable-next-line no-console */
         console.log('Socket teardown', socket);
       }
       socket.disconnect();

invokeai/frontend/web/src/app/store/middleware/debugLoggerMiddleware.ts

@@ -1,3 +1,6 @@
+/* eslint-disable no-console */
+// This is only enabled manually for debugging, console is allowed.
+
 import type { Middleware, MiddlewareAPI } from '@reduxjs/toolkit';
 import { diff } from 'jsondiffpatch';
 

invokeai/frontend/web/src/app/store/middleware/devtools/actionSanitizer.ts

@@ -1,7 +1,6 @@
 import type { UnknownAction } from '@reduxjs/toolkit';
 import { deepClone } from 'common/util/deepClone';
 import { isAnyGraphBuilt } from 'features/nodes/store/actions';
-import { nodeTemplatesBuilt } from 'features/nodes/store/nodesSlice';
 import { appInfoApi } from 'services/api/endpoints/appInfo';
 import type { Graph } from 'services/api/types';
 import { socketGeneratorProgress } from 'services/events/actions';
@@ -25,13 +24,6 @@ export const actionSanitizer = <A extends UnknownAction>(action: A): A => {
     };
   }
 
-  if (nodeTemplatesBuilt.match(action)) {
-    return {
-      ...action,
-      payload: '<Node templates omitted>',
-    };
-  }
-
   if (socketGeneratorProgress.match(action)) {
     const sanitized = deepClone(action);
     if (sanitized.payload.data.progress_image) {

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts

@@ -41,12 +41,10 @@ import { addGeneratorProgressEventListener } from 'app/store/middleware/listener
 import { addGraphExecutionStateCompleteEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketGraphExecutionStateComplete';
 import { addInvocationCompleteEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete';
 import { addInvocationErrorEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationError';
-import { addInvocationRetrievalErrorEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationRetrievalError';
 import { addInvocationStartedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationStarted';
 import { addModelInstallEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall';
 import { addModelLoadEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketModelLoad';
 import { addSocketQueueItemStatusChangedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketQueueItemStatusChanged';
-import { addSessionRetrievalErrorEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketSessionRetrievalError';
 import { addSocketSubscribedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketSubscribed';
 import { addSocketUnsubscribedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketUnsubscribed';
 import { addStagingAreaImageSavedListener } from 'app/store/middleware/listenerMiddleware/listeners/stagingAreaImageSaved';
@@ -114,8 +112,6 @@ addSocketSubscribedEventListener(startAppListening);
 addSocketUnsubscribedEventListener(startAppListening);
 addModelLoadEventListener(startAppListening);
 addModelInstallEventListener(startAppListening);
-addSessionRetrievalErrorEventListener(startAppListening);
-addInvocationRetrievalErrorEventListener(startAppListening);
 addSocketQueueItemStatusChangedEventListener(startAppListening);
 addBulkDownloadListeners(startAppListening);
 

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/addCommitStagingAreaImageListener.ts

@@ -8,7 +8,7 @@ import {
   resetCanvas,
   setInitialCanvasImage,
 } from 'features/canvas/store/canvasSlice';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { queueApi } from 'services/api/endpoints/queue';
 
@@ -30,22 +30,20 @@ export const addCommitStagingAreaImageListener = (startAppListening: AppStartLis
         req.reset();
         if (canceled > 0) {
           log.debug(`Canceled ${canceled} canvas batches`);
-          dispatch(
-            addToast({
-              title: t('queue.cancelBatchSucceeded'),
-              status: 'success',
-            })
-          );
+          toast({
+            id: 'CANCEL_BATCH_SUCCEEDED',
+            title: t('queue.cancelBatchSucceeded'),
+            status: 'success',
+          });
         }
         dispatch(canvasBatchIdsReset());
       } catch {
         log.error('Failed to cancel canvas batches');
-        dispatch(
-          addToast({
-            title: t('queue.cancelBatchFailed'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'CANCEL_BATCH_FAILED',
+          title: t('queue.cancelBatchFailed'),
+          status: 'error',
+        });
       }
     },
   });

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/batchEnqueued.ts

@@ -1,8 +1,8 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
-import { toast } from 'common/util/toast';
 import { zPydanticValidationError } from 'features/system/store/zodSchemas';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { truncate, upperFirst } from 'lodash-es';
 import { queueApi } from 'services/api/endpoints/queue';
@@ -16,18 +16,15 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
       const arg = action.meta.arg.originalArgs;
       logger('queue').debug({ enqueueResult: parseify(response) }, 'Batch enqueued');
 
-      if (!toast.isActive('batch-queued')) {
-        toast({
-          id: 'batch-queued',
-          title: t('queue.batchQueued'),
-          description: t('queue.batchQueuedDesc', {
-            count: response.enqueued,
-            direction: arg.prepend ? t('queue.front') : t('queue.back'),
-          }),
-          duration: 1000,
-          status: 'success',
-        });
-      }
+      toast({
+        id: 'QUEUE_BATCH_SUCCEEDED',
+        title: t('queue.batchQueued'),
+        status: 'success',
+        description: t('queue.batchQueuedDesc', {
+          count: response.enqueued,
+          direction: arg.prepend ? t('queue.front') : t('queue.back'),
+        }),
+      });
     },
   });
 
@@ -40,9 +37,10 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
 
       if (!response) {
         toast({
+          id: 'QUEUE_BATCH_FAILED',
           title: t('queue.batchFailedToQueue'),
           status: 'error',
-          description: 'Unknown Error',
+          description: t('common.unknownError'),
         });
         logger('queue').error({ batchConfig: parseify(arg), error: parseify(response) }, t('queue.batchFailedToQueue'));
         return;
@@ -52,7 +50,7 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
       if (result.success) {
         result.data.data.detail.map((e) => {
           toast({
-            id: 'batch-failed-to-queue',
+            id: 'QUEUE_BATCH_FAILED',
             title: truncate(upperFirst(e.msg), { length: 128 }),
             status: 'error',
             description: truncate(
@@ -64,9 +62,10 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
         });
       } else if (response.status !== 403) {
         toast({
+          id: 'QUEUE_BATCH_FAILED',
           title: t('queue.batchFailedToQueue'),
-          description: t('common.unknownError'),
           status: 'error',
+          description: t('common.unknownError'),
         });
       }
       logger('queue').error({ batchConfig: parseify(arg), error: parseify(response) }, t('queue.batchFailedToQueue'));

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/boardAndImagesDeleted.ts

@@ -21,7 +21,7 @@ export const addDeleteBoardAndImagesFulfilledListener = (startAppListening: AppS
 
       const { canvas, nodes, controlAdapters, controlLayers } = getState();
       deleted_images.forEach((image_name) => {
-        const imageUsage = getImageUsage(canvas, nodes, controlAdapters, controlLayers.present, image_name);
+        const imageUsage = getImageUsage(canvas, nodes.present, controlAdapters, controlLayers.present, image_name);
 
         if (imageUsage.isCanvasImage && !wasCanvasReset) {
           dispatch(resetCanvas());

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/bulkDownload.tsx

@@ -1,8 +1,7 @@
-import type { UseToastOptions } from '@invoke-ai/ui-library';
 import { ExternalLink } from '@invoke-ai/ui-library';
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { toast } from 'common/util/toast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 import {
@@ -28,7 +27,6 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
         // Show the response message if it exists, otherwise show the default message
         description: action.payload.response || t('gallery.bulkDownloadRequestedDesc'),
         duration: null,
-        isClosable: true,
       });
     },
   });
@@ -40,9 +38,9 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
 
       // There isn't any toast to update if we get this event.
       toast({
+        id: 'BULK_DOWNLOAD_REQUEST_FAILED',
         title: t('gallery.bulkDownloadRequestFailed'),
-        status: 'success',
-        isClosable: true,
+        status: 'error',
       });
     },
   });
@@ -65,7 +63,7 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
       // TODO(psyche): This URL may break in in some environments (e.g. Nvidia workbench) but we need to test it first
       const url = `/api/v1/images/download/${bulk_download_item_name}`;
 
-      const toastOptions: UseToastOptions = {
+      toast({
         id: bulk_download_item_name,
         title: t('gallery.bulkDownloadReady', 'Download ready'),
         status: 'success',
@@ -77,14 +75,7 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
           />
         ),
         duration: null,
-        isClosable: true,
-      };
-
-      if (toast.isActive(bulk_download_item_name)) {
-        toast.update(bulk_download_item_name, toastOptions);
-      } else {
-        toast(toastOptions);
-      }
+      });
     },
   });
 
@@ -95,20 +86,13 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
 
       const { bulk_download_item_name } = action.payload.data;
 
-      const toastOptions: UseToastOptions = {
+      toast({
         id: bulk_download_item_name,
         title: t('gallery.bulkDownloadFailed'),
         status: 'error',
         description: action.payload.data.error,
         duration: null,
-        isClosable: true,
-      };
-
-      if (toast.isActive(bulk_download_item_name)) {
-        toast.update(bulk_download_item_name, toastOptions);
-      } else {
-        toast(toastOptions);
-      }
+      });
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasCopiedToClipboard.ts

@@ -2,14 +2,14 @@ import { $logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasCopiedToClipboard } from 'features/canvas/store/actions';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
-import { addToast } from 'features/system/store/systemSlice';
 import { copyBlobToClipboard } from 'features/system/util/copyBlobToClipboard';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 
 export const addCanvasCopiedToClipboardListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasCopiedToClipboard,
-    effect: async (action, { dispatch, getState }) => {
+    effect: async (action, { getState }) => {
       const moduleLog = $logger.get().child({ namespace: 'canvasCopiedToClipboardListener' });
       const state = getState();
 
@@ -19,22 +19,20 @@ export const addCanvasCopiedToClipboardListener = (startAppListening: AppStartLi
         copyBlobToClipboard(blob);
       } catch (err) {
         moduleLog.error(String(err));
-        dispatch(
-          addToast({
-            title: t('toast.problemCopyingCanvas'),
-            description: t('toast.problemCopyingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'CANVAS_COPY_FAILED',
+          title: t('toast.problemCopyingCanvas'),
+          description: t('toast.problemCopyingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
-      dispatch(
-        addToast({
-          title: t('toast.canvasCopiedClipboard'),
-          status: 'success',
-        })
-      );
+      toast({
+        id: 'CANVAS_COPY_SUCCEEDED',
+        title: t('toast.canvasCopiedClipboard'),
+        status: 'success',
+      });
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasDownloadedAsImage.ts

@@ -3,13 +3,13 @@ import type { AppStartListening } from 'app/store/middleware/listenerMiddleware'
 import { canvasDownloadedAsImage } from 'features/canvas/store/actions';
 import { downloadBlob } from 'features/canvas/util/downloadBlob';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 
 export const addCanvasDownloadedAsImageListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: canvasDownloadedAsImage,
-    effect: async (action, { dispatch, getState }) => {
+    effect: async (action, { getState }) => {
       const moduleLog = $logger.get().child({ namespace: 'canvasSavedToGalleryListener' });
       const state = getState();
 
@@ -18,18 +18,17 @@ export const addCanvasDownloadedAsImageListener = (startAppListening: AppStartLi
         blob = await getBaseLayerBlob(state);
       } catch (err) {
         moduleLog.error(String(err));
-        dispatch(
-          addToast({
-            title: t('toast.problemDownloadingCanvas'),
-            description: t('toast.problemDownloadingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'CANVAS_DOWNLOAD_FAILED',
+          title: t('toast.problemDownloadingCanvas'),
+          description: t('toast.problemDownloadingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
       downloadBlob(blob, 'canvas.png');
-      dispatch(addToast({ title: t('toast.canvasDownloaded'), status: 'success' }));
+      toast({ id: 'CANVAS_DOWNLOAD_SUCCEEDED', title: t('toast.canvasDownloaded'), status: 'success' });
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasImageToControlNet.ts

@@ -3,7 +3,7 @@ import type { AppStartListening } from 'app/store/middleware/listenerMiddleware'
 import { canvasImageToControlAdapter } from 'features/canvas/store/actions';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
 import { controlAdapterImageChanged } from 'features/controlAdapters/store/controlAdaptersSlice';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -20,13 +20,12 @@ export const addCanvasImageToControlNetListener = (startAppListening: AppStartLi
         blob = await getBaseLayerBlob(state, true);
       } catch (err) {
         log.error(String(err));
-        dispatch(
-          addToast({
-            title: t('toast.problemSavingCanvas'),
-            description: t('toast.problemSavingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'PROBLEM_SAVING_CANVAS',
+          title: t('toast.problemSavingCanvas'),
+          description: t('toast.problemSavingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -43,7 +42,7 @@ export const addCanvasImageToControlNetListener = (startAppListening: AppStartLi
           crop_visible: false,
           postUploadAction: {
             type: 'TOAST',
-            toastOptions: { title: t('toast.canvasSentControlnetAssets') },
+            title: t('toast.canvasSentControlnetAssets'),
           },
         })
       ).unwrap();

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMaskSavedToGallery.ts

@@ -2,7 +2,7 @@ import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { canvasMaskSavedToGallery } from 'features/canvas/store/actions';
 import { getCanvasData } from 'features/canvas/util/getCanvasData';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -29,13 +29,12 @@ export const addCanvasMaskSavedToGalleryListener = (startAppListening: AppStartL
 
       if (!maskBlob) {
         log.error('Problem getting mask layer blob');
-        dispatch(
-          addToast({
-            title: t('toast.problemSavingMask'),
-            description: t('toast.problemSavingMaskDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'PROBLEM_SAVING_MASK',
+          title: t('toast.problemSavingMask'),
+          description: t('toast.problemSavingMaskDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -52,7 +51,7 @@ export const addCanvasMaskSavedToGalleryListener = (startAppListening: AppStartL
           crop_visible: true,
           postUploadAction: {
             type: 'TOAST',
-            toastOptions: { title: t('toast.maskSavedAssets') },
+            title: t('toast.maskSavedAssets'),
           },
         })
       );

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMaskToControlNet.ts

@@ -3,7 +3,7 @@ import type { AppStartListening } from 'app/store/middleware/listenerMiddleware'
 import { canvasMaskToControlAdapter } from 'features/canvas/store/actions';
 import { getCanvasData } from 'features/canvas/util/getCanvasData';
 import { controlAdapterImageChanged } from 'features/controlAdapters/store/controlAdaptersSlice';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -30,13 +30,12 @@ export const addCanvasMaskToControlNetListener = (startAppListening: AppStartLis
 
       if (!maskBlob) {
         log.error('Problem getting mask layer blob');
-        dispatch(
-          addToast({
-            title: t('toast.problemImportingMask'),
-            description: t('toast.problemImportingMaskDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'PROBLEM_IMPORTING_MASK',
+          title: t('toast.problemImportingMask'),
+          description: t('toast.problemImportingMaskDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -53,7 +52,7 @@ export const addCanvasMaskToControlNetListener = (startAppListening: AppStartLis
           crop_visible: false,
           postUploadAction: {
             type: 'TOAST',
-            toastOptions: { title: t('toast.maskSentControlnetAssets') },
+            title: t('toast.maskSentControlnetAssets'),
           },
         })
       ).unwrap();

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasMerged.ts

@@ -4,7 +4,7 @@ import { canvasMerged } from 'features/canvas/store/actions';
 import { $canvasBaseLayer } from 'features/canvas/store/canvasNanostore';
 import { setMergedCanvas } from 'features/canvas/store/canvasSlice';
 import { getFullBaseLayerBlob } from 'features/canvas/util/getFullBaseLayerBlob';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -17,13 +17,12 @@ export const addCanvasMergedListener = (startAppListening: AppStartListening) =>
 
       if (!blob) {
         moduleLog.error('Problem getting base layer blob');
-        dispatch(
-          addToast({
-            title: t('toast.problemMergingCanvas'),
-            description: t('toast.problemMergingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'PROBLEM_MERGING_CANVAS',
+          title: t('toast.problemMergingCanvas'),
+          description: t('toast.problemMergingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -31,13 +30,12 @@ export const addCanvasMergedListener = (startAppListening: AppStartListening) =>
 
       if (!canvasBaseLayer) {
         moduleLog.error('Problem getting canvas base layer');
-        dispatch(
-          addToast({
-            title: t('toast.problemMergingCanvas'),
-            description: t('toast.problemMergingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'PROBLEM_MERGING_CANVAS',
+          title: t('toast.problemMergingCanvas'),
+          description: t('toast.problemMergingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -54,7 +52,7 @@ export const addCanvasMergedListener = (startAppListening: AppStartListening) =>
           is_intermediate: true,
           postUploadAction: {
             type: 'TOAST',
-            toastOptions: { title: t('toast.canvasMerged') },
+            title: t('toast.canvasMerged'),
           },
         })
       ).unwrap();

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/canvasSavedToGallery.ts

@@ -1,8 +1,9 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { parseify } from 'common/util/serialize';
 import { canvasSavedToGallery } from 'features/canvas/store/actions';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -18,13 +19,12 @@ export const addCanvasSavedToGalleryListener = (startAppListening: AppStartListe
         blob = await getBaseLayerBlob(state);
       } catch (err) {
         log.error(String(err));
-        dispatch(
-          addToast({
-            title: t('toast.problemSavingCanvas'),
-            description: t('toast.problemSavingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'CANVAS_SAVE_FAILED',
+          title: t('toast.problemSavingCanvas'),
+          description: t('toast.problemSavingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -41,7 +41,10 @@ export const addCanvasSavedToGalleryListener = (startAppListening: AppStartListe
           crop_visible: true,
           postUploadAction: {
             type: 'TOAST',
-            toastOptions: { title: t('toast.canvasSavedGallery') },
+            title: t('toast.canvasSavedGallery'),
+          },
+          metadata: {
+            _canvas_objects: parseify(state.canvas.layerState.objects),
           },
         })
       );

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlAdapterPreprocessor.ts

@@ -1,60 +1,57 @@
 import { isAnyOf } from '@reduxjs/toolkit';
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import type { AppDispatch } from 'app/store/store';
 import { parseify } from 'common/util/serialize';
 import {
   caLayerImageChanged,
-  caLayerIsProcessingImageChanged,
   caLayerModelChanged,
   caLayerProcessedImageChanged,
   caLayerProcessorConfigChanged,
+  caLayerProcessorPendingBatchIdChanged,
+  caLayerRecalled,
   isControlAdapterLayer,
 } from 'features/controlLayers/store/controlLayersSlice';
 import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
 import { isImageOutput } from 'features/nodes/types/common';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { isEqual } from 'lodash-es';
-import { imagesApi } from 'services/api/endpoints/images';
+import { getImageDTO } from 'services/api/endpoints/images';
 import { queueApi } from 'services/api/endpoints/queue';
-import type { BatchConfig, ImageDTO } from 'services/api/types';
+import type { BatchConfig } from 'services/api/types';
 import { socketInvocationComplete } from 'services/events/actions';
+import { assert } from 'tsafe';
 
-const matcher = isAnyOf(caLayerImageChanged, caLayerProcessorConfigChanged, caLayerModelChanged);
+const matcher = isAnyOf(caLayerImageChanged, caLayerProcessorConfigChanged, caLayerModelChanged, caLayerRecalled);
 
 const DEBOUNCE_MS = 300;
 const log = logger('session');
 
+/**
+ * Simple helper to cancel a batch and reset the pending batch ID
+ */
+const cancelProcessorBatch = async (dispatch: AppDispatch, layerId: string, batchId: string) => {
+  const req = dispatch(queueApi.endpoints.cancelByBatchIds.initiate({ batch_ids: [batchId] }));
+  log.trace({ batchId }, 'Cancelling existing preprocessor batch');
+  try {
+    await req.unwrap();
+  } catch {
+    // no-op
+  } finally {
+    req.reset();
+    // Always reset the pending batch ID - the cancel req could fail if the batch doesn't exist
+    dispatch(caLayerProcessorPendingBatchIdChanged({ layerId, batchId: null }));
+  }
+};
+
 export const addControlAdapterPreprocessor = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher,
-    effect: async (action, { dispatch, getState, getOriginalState, cancelActiveListeners, delay, take }) => {
-      const { layerId } = action.payload;
-      const precheckLayerOriginal = getOriginalState()
-        .controlLayers.present.layers.filter(isControlAdapterLayer)
-        .find((l) => l.id === layerId);
-      const precheckLayer = getState()
-        .controlLayers.present.layers.filter(isControlAdapterLayer)
-        .find((l) => l.id === layerId);
-
-      // Conditions to bail
-      const layerDoesNotExist = !precheckLayer;
-      const layerHasNoImage = !precheckLayer?.controlAdapter.image;
-      const layerHasNoProcessorConfig = !precheckLayer?.controlAdapter.processorConfig;
-      const layerIsAlreadyProcessingImage = precheckLayer?.controlAdapter.isProcessingImage;
-      const areImageAndProcessorUnchanged =
-        isEqual(precheckLayer?.controlAdapter.image, precheckLayerOriginal?.controlAdapter.image) &&
-        isEqual(precheckLayer?.controlAdapter.processorConfig, precheckLayerOriginal?.controlAdapter.processorConfig);
-
-      if (
-        layerDoesNotExist ||
-        layerHasNoImage ||
-        layerHasNoProcessorConfig ||
-        areImageAndProcessorUnchanged ||
-        layerIsAlreadyProcessingImage
-      ) {
-        return;
-      }
+    effect: async (action, { dispatch, getState, getOriginalState, cancelActiveListeners, delay, take, signal }) => {
+      const layerId = caLayerRecalled.match(action) ? action.payload.id : action.payload.layerId;
+      const state = getState();
+      const originalState = getOriginalState();
 
       // Cancel any in-progress instances of this listener
       cancelActiveListeners();
@@ -62,27 +59,55 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
 
       // Delay before starting actual work
       await delay(DEBOUNCE_MS);
-      dispatch(caLayerIsProcessingImageChanged({ layerId, isProcessingImage: true }));
 
-      // Double-check that we are still eligible for processing
-      const state = getState();
       const layer = state.controlLayers.present.layers.filter(isControlAdapterLayer).find((l) => l.id === layerId);
-      const image = layer?.controlAdapter.image;
-      const config = layer?.controlAdapter.processorConfig;
 
-      // If we have no image or there is no processor config, bail
-      if (!layer || !image || !config) {
+      if (!layer) {
         return;
       }
 
-      // @ts-expect-error: TS isn't able to narrow the typing of buildNode and `config` will error...
-      const processorNode = CA_PROCESSOR_DATA[config.type].buildNode(image, config);
+      // We should only process if the processor settings or image have changed
+      const originalLayer = originalState.controlLayers.present.layers
+        .filter(isControlAdapterLayer)
+        .find((l) => l.id === layerId);
+      const originalImage = originalLayer?.controlAdapter.image;
+      const originalConfig = originalLayer?.controlAdapter.processorConfig;
+
+      const image = layer.controlAdapter.image;
+      const config = layer.controlAdapter.processorConfig;
+
+      if (isEqual(config, originalConfig) && isEqual(image, originalImage)) {
+        // Neither config nor image have changed, we can bail
+        return;
+      }
+
+      if (!image || !config) {
+        // - If we have no image, we have nothing to process
+        // - If we have no processor config, we have nothing to process
+        // Clear the processed image and bail
+        dispatch(caLayerProcessedImageChanged({ layerId, imageDTO: null }));
+        return;
+      }
+
+      // At this point, the user has stopped fiddling with the processor settings and there is a processor selected.
+
+      // If there is a pending processor batch, cancel it.
+      if (layer.controlAdapter.processorPendingBatchId) {
+        cancelProcessorBatch(dispatch, layerId, layer.controlAdapter.processorPendingBatchId);
+      }
+
+      // TODO(psyche): I can't get TS to be happy, it thinkgs `config` is `never` but it should be inferred from the generic... I'll just cast it for now
+      const processorNode = CA_PROCESSOR_DATA[config.type].buildNode(image, config as never);
       const enqueueBatchArg: BatchConfig = {
         prepend: true,
         batch: {
           graph: {
             nodes: {
-              [processorNode.id]: { ...processorNode, is_intermediate: true },
+              [processorNode.id]: {
+                ...processorNode,
+                // Control images are always intermediate - do not save to gallery
+                is_intermediate: true,
+              },
             },
             edges: [],
           },
@@ -90,16 +115,21 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
         },
       };
 
+      // Kick off the processor batch
+      const req = dispatch(
+        queueApi.endpoints.enqueueBatch.initiate(enqueueBatchArg, {
+          fixedCacheKey: 'enqueueBatch',
+        })
+      );
+
       try {
-        const req = dispatch(
-          queueApi.endpoints.enqueueBatch.initiate(enqueueBatchArg, {
-            fixedCacheKey: 'enqueueBatch',
-          })
-        );
         const enqueueResult = await req.unwrap();
-        req.reset();
+        // TODO(psyche): Update the pydantic models, pretty sure we will _always_ have a batch_id here, but the model says it's optional
+        assert(enqueueResult.batch.batch_id, 'Batch ID not returned from queue');
+        dispatch(caLayerProcessorPendingBatchIdChanged({ layerId, batchId: enqueueResult.batch.batch_id }));
         log.debug({ enqueueResult: parseify(enqueueResult) }, t('queue.graphQueued'));
 
+        // Wait for the processor node to complete
         const [invocationCompleteAction] = await take(
           (action): action is ReturnType<typeof socketInvocationComplete> =>
             socketInvocationComplete.match(action) &&
@@ -108,48 +138,50 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
         );
 
         // We still have to check the output type
-        if (isImageOutput(invocationCompleteAction.payload.data.result)) {
-          const { image_name } = invocationCompleteAction.payload.data.result.image;
+        assert(
+          isImageOutput(invocationCompleteAction.payload.data.result),
+          `Processor did not return an image output, got: ${invocationCompleteAction.payload.data.result}`
+        );
+        const { image_name } = invocationCompleteAction.payload.data.result.image;
 
-          // Wait for the ImageDTO to be received
-          const [{ payload }] = await take(
-            (action) =>
-              imagesApi.endpoints.getImageDTO.matchFulfilled(action) && action.payload.image_name === image_name
-          );
+        const imageDTO = await getImageDTO(image_name);
+        assert(imageDTO, "Failed to fetch processor output's image DTO");
 
-          const imageDTO = payload as ImageDTO;
-
-          log.debug({ layerId, imageDTO }, 'ControlNet image processed');
-
-          // Update the processed image in the store
-          dispatch(
-            caLayerProcessedImageChanged({
-              layerId,
-              imageDTO,
-            })
-          );
-          dispatch(caLayerIsProcessingImageChanged({ layerId, isProcessingImage: false }));
-        }
+        // Whew! We made it. Update the layer with the processed image
+        log.debug({ layerId, imageDTO }, 'ControlNet image processed');
+        dispatch(caLayerProcessedImageChanged({ layerId, imageDTO }));
+        dispatch(caLayerProcessorPendingBatchIdChanged({ layerId, batchId: null }));
       } catch (error) {
-        console.log(error);
-        log.error({ enqueueBatchArg: parseify(enqueueBatchArg) }, t('queue.graphFailedToQueue'));
-        dispatch(caLayerIsProcessingImageChanged({ layerId, isProcessingImage: false }));
+        if (signal.aborted) {
+          // The listener was canceled - we need to cancel the pending processor batch, if there is one (could have changed by now).
+          const pendingBatchId = getState()
+            .controlLayers.present.layers.filter(isControlAdapterLayer)
+            .find((l) => l.id === layerId)?.controlAdapter.processorPendingBatchId;
+          if (pendingBatchId) {
+            cancelProcessorBatch(dispatch, layerId, pendingBatchId);
+          }
+          log.trace('Control Adapter preprocessor cancelled');
+        } else {
+          // Some other error condition...
+          log.error({ enqueueBatchArg: parseify(enqueueBatchArg) }, t('queue.graphFailedToQueue'));
 
-        if (error instanceof Object) {
-          if ('data' in error && 'status' in error) {
-            if (error.status === 403) {
-              dispatch(caLayerImageChanged({ layerId, imageDTO: null }));
-              return;
+          if (error instanceof Object) {
+            if ('data' in error && 'status' in error) {
+              if (error.status === 403) {
+                dispatch(caLayerImageChanged({ layerId, imageDTO: null }));
+                return;
+              }
             }
           }
-        }
 
-        dispatch(
-          addToast({
+          toast({
+            id: 'GRAPH_QUEUE_FAILED',
             title: t('queue.graphFailedToQueue'),
             status: 'error',
-          })
-        );
+          });
+        }
+      } finally {
+        req.reset();
       }
     },
   });

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed.ts

@@ -10,7 +10,7 @@ import {
 } from 'features/controlAdapters/store/controlAdaptersSlice';
 import { isControlNetOrT2IAdapter } from 'features/controlAdapters/store/types';
 import { isImageOutput } from 'features/nodes/types/common';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 import { queueApi } from 'services/api/endpoints/queue';
@@ -108,12 +108,11 @@ export const addControlNetImageProcessedListener = (startAppListening: AppStartL
           }
         }
 
-        dispatch(
-          addToast({
-            title: t('queue.graphFailedToQueue'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'GRAPH_QUEUE_FAILED',
+          title: t('queue.graphFailedToQueue'),
+          status: 'error',
+        });
       }
     },
   });

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedCanvas.ts

@@ -8,8 +8,8 @@ import { blobToDataURL } from 'features/canvas/util/blobToDataURL';
 import { getCanvasData } from 'features/canvas/util/getCanvasData';
 import { getCanvasGenerationMode } from 'features/canvas/util/getCanvasGenerationMode';
 import { canvasGraphBuilt } from 'features/nodes/store/actions';
-import { buildCanvasGraph } from 'features/nodes/util/graph/buildCanvasGraph';
 import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
+import { buildCanvasGraph } from 'features/nodes/util/graph/canvas/buildCanvasGraph';
 import { imagesApi } from 'services/api/endpoints/images';
 import { queueApi } from 'services/api/endpoints/queue';
 import type { ImageDTO } from 'services/api/types';

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear.ts

@@ -1,8 +1,9 @@
 import { enqueueRequested } from 'app/store/actions';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { buildGenerationTabGraph } from 'features/nodes/util/graph/buildGenerationTabGraph';
-import { buildGenerationTabSDXLGraph } from 'features/nodes/util/graph/buildGenerationTabSDXLGraph';
+import { isImageViewerOpenChanged } from 'features/gallery/store/gallerySlice';
 import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
+import { buildGenerationTabGraph } from 'features/nodes/util/graph/generation/buildGenerationTabGraph';
+import { buildGenerationTabSDXLGraph } from 'features/nodes/util/graph/generation/buildGenerationTabSDXLGraph';
 import { queueApi } from 'services/api/endpoints/queue';
 
 export const addEnqueueRequestedLinear = (startAppListening: AppStartListening) => {
@@ -11,12 +12,13 @@ export const addEnqueueRequestedLinear = (startAppListening: AppStartListening)
       enqueueRequested.match(action) && action.payload.tabName === 'generation',
     effect: async (action, { getState, dispatch }) => {
       const state = getState();
+      const { shouldShowProgressInViewer } = state.ui;
       const model = state.generation.model;
       const { prepend } = action.payload;
 
       let graph;
 
-      if (model && model.base === 'sdxl') {
+      if (model?.base === 'sdxl') {
         graph = await buildGenerationTabSDXLGraph(state);
       } else {
         graph = await buildGenerationTabGraph(state);
@@ -29,7 +31,14 @@ export const addEnqueueRequestedLinear = (startAppListening: AppStartListening)
           fixedCacheKey: 'enqueueBatch',
         })
       );
-      req.reset();
+      try {
+        await req.unwrap();
+        if (shouldShowProgressInViewer) {
+          dispatch(isImageViewerOpenChanged(true));
+        }
+      } finally {
+        req.reset();
+      }
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/enqueueRequestedNodes.ts

@@ -11,9 +11,9 @@ export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) =
       enqueueRequested.match(action) && action.payload.tabName === 'workflows',
     effect: async (action, { getState, dispatch }) => {
       const state = getState();
-      const { nodes, edges } = state.nodes;
+      const { nodes, edges } = state.nodes.present;
       const workflow = state.workflow;
-      const graph = buildNodesGraph(state.nodes);
+      const graph = buildNodesGraph(state.nodes.present);
       const builtWorkflow = buildWorkflowWithValidation({
         nodes,
         edges,
@@ -39,7 +39,11 @@ export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) =
           fixedCacheKey: 'enqueueBatch',
         })
       );
-      req.reset();
+      try {
+        await req.unwrap();
+      } finally {
+        req.reset();
+      }
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema.ts

@@ -1,7 +1,7 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
-import { nodeTemplatesBuilt } from 'features/nodes/store/nodesSlice';
+import { $templates } from 'features/nodes/store/nodesSlice';
 import { parseSchema } from 'features/nodes/util/schema/parseSchema';
 import { size } from 'lodash-es';
 import { appInfoApi } from 'services/api/endpoints/appInfo';
@@ -9,7 +9,7 @@ import { appInfoApi } from 'services/api/endpoints/appInfo';
 export const addGetOpenAPISchemaListener = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher: appInfoApi.endpoints.getOpenAPISchema.matchFulfilled,
-    effect: (action, { dispatch, getState }) => {
+    effect: (action, { getState }) => {
       const log = logger('system');
       const schemaJSON = action.payload;
 
@@ -20,7 +20,7 @@ export const addGetOpenAPISchemaListener = (startAppListening: AppStartListening
 
       log.debug({ nodeTemplates: parseify(nodeTemplates) }, `Built ${size(nodeTemplates)} node templates`);
 
-      dispatch(nodeTemplatesBuilt(nodeTemplates));
+      $templates.set(nodeTemplates);
     },
   });
 

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageDeleted.ts

@@ -29,7 +29,7 @@ import type { ImageDTO } from 'services/api/types';
 import { imagesSelectors } from 'services/api/util';
 
 const deleteNodesImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
-  state.nodes.nodes.forEach((node) => {
+  state.nodes.present.nodes.forEach((node) => {
     if (!isInvocationNode(node)) {
       return;
     }
@@ -73,25 +73,25 @@ const deleteControlAdapterImages = (state: RootState, dispatch: AppDispatch, ima
 const deleteControlLayerImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
   state.controlLayers.present.layers.forEach((l) => {
     if (isRegionalGuidanceLayer(l)) {
-      if (l.ipAdapters.some((ipa) => ipa.image?.imageName === imageDTO.image_name)) {
+      if (l.ipAdapters.some((ipa) => ipa.image?.name === imageDTO.image_name)) {
         dispatch(layerDeleted(l.id));
       }
     }
     if (isControlAdapterLayer(l)) {
       if (
-        l.controlAdapter.image?.imageName === imageDTO.image_name ||
-        l.controlAdapter.processedImage?.imageName === imageDTO.image_name
+        l.controlAdapter.image?.name === imageDTO.image_name ||
+        l.controlAdapter.processedImage?.name === imageDTO.image_name
       ) {
         dispatch(layerDeleted(l.id));
       }
     }
     if (isIPAdapterLayer(l)) {
-      if (l.ipAdapter.image?.imageName === imageDTO.image_name) {
+      if (l.ipAdapter.image?.name === imageDTO.image_name) {
         dispatch(layerDeleted(l.id));
       }
     }
     if (isInitialImageLayer(l)) {
-      if (l.image?.imageName === imageDTO.image_name) {
+      if (l.image?.name === imageDTO.image_name) {
         dispatch(layerDeleted(l.id));
       }
     }

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/imageUploaded.ts

@@ -1,4 +1,3 @@
-import type { UseToastOptions } from '@invoke-ai/ui-library';
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { setInitialCanvasImage } from 'features/canvas/store/canvasSlice';
@@ -14,7 +13,7 @@ import {
 } from 'features/controlLayers/store/controlLayersSlice';
 import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
 import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { omit } from 'lodash-es';
 import { boardsApi } from 'services/api/endpoints/boards';
@@ -42,16 +41,17 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
         return;
       }
 
-      const DEFAULT_UPLOADED_TOAST: UseToastOptions = {
+      const DEFAULT_UPLOADED_TOAST = {
+        id: 'IMAGE_UPLOADED',
         title: t('toast.imageUploaded'),
         status: 'success',
-      };
+      } as const;
 
       // default action - just upload and alert user
       if (postUploadAction?.type === 'TOAST') {
-        const { toastOptions } = postUploadAction;
         if (!autoAddBoardId || autoAddBoardId === 'none') {
-          dispatch(addToast({ ...DEFAULT_UPLOADED_TOAST, ...toastOptions }));
+          const title = postUploadAction.title || DEFAULT_UPLOADED_TOAST.title;
+          toast({ ...DEFAULT_UPLOADED_TOAST, title });
         } else {
           // Add this image to the board
           dispatch(
@@ -70,24 +70,20 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
             ? `${t('toast.addedToBoard')} ${board.board_name}`
             : `${t('toast.addedToBoard')} ${autoAddBoardId}`;
 
-          dispatch(
-            addToast({
-              ...DEFAULT_UPLOADED_TOAST,
-              description,
-            })
-          );
+          toast({
+            ...DEFAULT_UPLOADED_TOAST,
+            description,
+          });
         }
         return;
       }
 
       if (postUploadAction?.type === 'SET_CANVAS_INITIAL_IMAGE') {
         dispatch(setInitialCanvasImage(imageDTO, selectOptimalDimension(state)));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setAsCanvasInitialImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setAsCanvasInitialImage'),
+        });
         return;
       }
 
@@ -105,68 +101,56 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
             controlImage: imageDTO.image_name,
           })
         );
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setControlImage'),
+        });
         return;
       }
 
       if (postUploadAction?.type === 'SET_CA_LAYER_IMAGE') {
         const { layerId } = postUploadAction;
         dispatch(caLayerImageChanged({ layerId, imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setControlImage'),
+        });
       }
 
       if (postUploadAction?.type === 'SET_IPA_LAYER_IMAGE') {
         const { layerId } = postUploadAction;
         dispatch(ipaLayerImageChanged({ layerId, imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setControlImage'),
+        });
       }
 
       if (postUploadAction?.type === 'SET_RG_LAYER_IP_ADAPTER_IMAGE') {
         const { layerId, ipAdapterId } = postUploadAction;
         dispatch(rgLayerIPAdapterImageChanged({ layerId, ipAdapterId, imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setControlImage'),
+        });
       }
 
       if (postUploadAction?.type === 'SET_II_LAYER_IMAGE') {
         const { layerId } = postUploadAction;
         dispatch(iiLayerImageChanged({ layerId, imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: t('toast.setControlImage'),
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: t('toast.setControlImage'),
+        });
       }
 
       if (postUploadAction?.type === 'SET_NODES_IMAGE') {
         const { nodeId, fieldName } = postUploadAction;
         dispatch(fieldImageValueChanged({ nodeId, fieldName, value: imageDTO }));
-        dispatch(
-          addToast({
-            ...DEFAULT_UPLOADED_TOAST,
-            description: `${t('toast.setNodeField')} ${fieldName}`,
-          })
-        );
+        toast({
+          ...DEFAULT_UPLOADED_TOAST,
+          description: `${t('toast.setNodeField')} ${fieldName}`,
+        });
         return;
       }
     },
@@ -174,7 +158,7 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
 
   startAppListening({
     matcher: imagesApi.endpoints.uploadImage.matchRejected,
-    effect: (action, { dispatch }) => {
+    effect: (action) => {
       const log = logger('images');
       const sanitizedData = {
         arg: {
@@ -183,13 +167,11 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
         },
       };
       log.error({ ...sanitizedData }, 'Image upload failed');
-      dispatch(
-        addToast({
-          title: t('toast.imageUploadFailed'),
-          description: action.error.message,
-          status: 'error',
-        })
-      );
+      toast({
+        title: t('toast.imageUploadFailed'),
+        description: action.error.message,
+        status: 'error',
+      });
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/modelSelected.ts

@@ -8,8 +8,7 @@ import { loraRemoved } from 'features/lora/store/loraSlice';
 import { modelSelected } from 'features/parameters/store/actions';
 import { modelChanged, vaeSelected } from 'features/parameters/store/generationSlice';
 import { zParameterModel } from 'features/parameters/types/parameterSchemas';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { forEach } from 'lodash-es';
 
@@ -60,16 +59,14 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
         });
 
         if (modelsCleared > 0) {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('toast.baseModelChangedCleared', {
-                  count: modelsCleared,
-                }),
-                status: 'warning',
-              })
-            )
-          );
+          toast({
+            id: 'BASE_MODEL_CHANGED',
+            title: t('toast.baseModelChanged'),
+            description: t('toast.baseModelChangedCleared', {
+              count: modelsCleared,
+            }),
+            status: 'warning',
+          });
         }
       }
 

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/setDefaultSettings.ts

@@ -19,8 +19,7 @@ import {
   isParameterWidth,
   zParameterVAEModel,
 } from 'features/parameters/types/parameterSchemas';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { modelConfigsAdapterSelectors, modelsApi } from 'services/api/endpoints/models';
 import { isNonRefinerMainModelConfig } from 'services/api/types';
@@ -109,7 +108,7 @@ export const addSetDefaultSettingsListener = (startAppListening: AppStartListeni
           }
         }
 
-        dispatch(addToast(makeToast({ title: t('toast.parameterSet', { parameter: 'Default settings' }) })));
+        toast({ id: 'PARAMETER_SET', title: t('toast.parameterSet', { parameter: 'Default settings' }) });
       }
     },
   });

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketGeneratorProgress.ts

@@ -1,5 +1,8 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
+import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
+import { zNodeStatus } from 'features/nodes/types/invocation';
 import { socketGeneratorProgress } from 'services/events/actions';
 
 const log = logger('socketio');
@@ -9,6 +12,14 @@ export const addGeneratorProgressEventListener = (startAppListening: AppStartLis
     actionCreator: socketGeneratorProgress,
     effect: (action) => {
       log.trace(action.payload, `Generator progress`);
+      const { source_node_id, step, total_steps, progress_image } = action.payload.data;
+      const nes = deepClone($nodeExecutionStates.get()[source_node_id]);
+      if (nes) {
+        nes.status = zNodeStatus.enum.IN_PROGRESS;
+        nes.progress = (step + 1) / total_steps;
+        nes.progressImage = progress_image ?? null;
+        upsertExecutionState(nes.nodeId, nes);
+      }
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete.ts

@@ -1,10 +1,18 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
 import { parseify } from 'common/util/serialize';
 import { addImageToStagingArea } from 'features/canvas/store/canvasSlice';
-import { boardIdSelected, galleryViewChanged, imageSelected } from 'features/gallery/store/gallerySlice';
+import {
+  boardIdSelected,
+  galleryViewChanged,
+  imageSelected,
+  isImageViewerOpenChanged,
+} from 'features/gallery/store/gallerySlice';
 import { IMAGE_CATEGORIES } from 'features/gallery/store/types';
+import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
 import { isImageOutput } from 'features/nodes/types/common';
+import { zNodeStatus } from 'features/nodes/types/invocation';
 import { CANVAS_OUTPUT } from 'features/nodes/util/graph/constants';
 import { boardsApi } from 'services/api/endpoints/boards';
 import { imagesApi } from 'services/api/endpoints/images';
@@ -23,7 +31,7 @@ export const addInvocationCompleteEventListener = (startAppListening: AppStartLi
       const { data } = action.payload;
       log.debug({ data: parseify(data) }, `Invocation complete (${action.payload.data.node.type})`);
 
-      const { result, node, queue_batch_id } = data;
+      const { result, node, queue_batch_id, source_node_id } = data;
       // This complete event has an associated image output
       if (isImageOutput(result) && !nodeTypeDenylist.includes(node.type)) {
         const { image_name } = result.image;
@@ -101,9 +109,20 @@ export const addInvocationCompleteEventListener = (startAppListening: AppStartLi
             }
 
             dispatch(imageSelected(imageDTO));
+            dispatch(isImageViewerOpenChanged(true));
           }
         }
       }
+
+      const nes = deepClone($nodeExecutionStates.get()[source_node_id]);
+      if (nes) {
+        nes.status = zNodeStatus.enum.COMPLETED;
+        if (nes.progress !== null) {
+          nes.progress = 1;
+        }
+        nes.outputs.push(result);
+        upsertExecutionState(nes.nodeId, nes);
+      }
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationError.ts

@@ -1,14 +1,66 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
+import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
+import { zNodeStatus } from 'features/nodes/types/invocation';
+import { toast } from 'features/toast/toast';
+import ToastWithSessionRefDescription from 'features/toast/ToastWithSessionRefDescription';
+import { t } from 'i18next';
+import { startCase } from 'lodash-es';
 import { socketInvocationError } from 'services/events/actions';
 
 const log = logger('socketio');
 
+const getTitle = (errorType: string) => {
+  if (errorType === 'OutOfMemoryError') {
+    return t('toast.outOfMemoryError');
+  }
+  return t('toast.serverError');
+};
+
+const getDescription = (errorType: string, sessionId: string, isLocal?: boolean) => {
+  if (!isLocal) {
+    if (errorType === 'OutOfMemoryError') {
+      return ToastWithSessionRefDescription({
+        message: t('toast.outOfMemoryDescription'),
+        sessionId,
+      });
+    }
+    return ToastWithSessionRefDescription({
+      message: errorType,
+      sessionId,
+    });
+  }
+  return errorType;
+};
+
 export const addInvocationErrorEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketInvocationError,
-    effect: (action) => {
+    effect: (action, { getState }) => {
       log.error(action.payload, `Invocation error (${action.payload.data.node.type})`);
+      const { source_node_id, error_type, graph_execution_state_id } = action.payload.data;
+      const nes = deepClone($nodeExecutionStates.get()[source_node_id]);
+      if (nes) {
+        nes.status = zNodeStatus.enum.FAILED;
+        nes.error = action.payload.data.error;
+        nes.progress = null;
+        nes.progressImage = null;
+        upsertExecutionState(nes.nodeId, nes);
+      }
+
+      const errorType = startCase(error_type);
+      const sessionId = graph_execution_state_id;
+      const { isLocal } = getState().config;
+
+      toast({
+        id: `INVOCATION_ERROR_${errorType}`,
+        title: getTitle(errorType),
+        status: 'error',
+        duration: null,
+        description: getDescription(errorType, sessionId, isLocal),
+        updateDescription: isLocal ? true : false,
+      });
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationRetrievalError.ts

@@ -1,14 +0,0 @@
-import { logger } from 'app/logging/logger';
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { socketInvocationRetrievalError } from 'services/events/actions';
-
-const log = logger('socketio');
-
-export const addInvocationRetrievalErrorEventListener = (startAppListening: AppStartListening) => {
-  startAppListening({
-    actionCreator: socketInvocationRetrievalError,
-    effect: (action) => {
-      log.error(action.payload, `Invocation retrieval error (${action.payload.data.graph_execution_state_id})`);
-    },
-  });
-};

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationStarted.ts

@@ -1,5 +1,8 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
+import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
+import { zNodeStatus } from 'features/nodes/types/invocation';
 import { socketInvocationStarted } from 'services/events/actions';
 
 const log = logger('socketio');
@@ -9,6 +12,12 @@ export const addInvocationStartedEventListener = (startAppListening: AppStartLis
     actionCreator: socketInvocationStarted,
     effect: (action) => {
       log.debug(action.payload, `Invocation started (${action.payload.data.node.type})`);
+      const { source_node_id } = action.payload.data;
+      const nes = deepClone($nodeExecutionStates.get()[source_node_id]);
+      if (nes) {
+        nes.status = zNodeStatus.enum.IN_PROGRESS;
+        upsertExecutionState(nes.nodeId, nes);
+      }
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketQueueItemStatusChanged.ts

@@ -1,5 +1,9 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
+import { $nodeExecutionStates } from 'features/nodes/hooks/useExecutionState';
+import { zNodeStatus } from 'features/nodes/types/invocation';
+import { forEach } from 'lodash-es';
 import { queueApi, queueItemsAdapter } from 'services/api/endpoints/queue';
 import { socketQueueItemStatusChanged } from 'services/events/actions';
 
@@ -54,6 +58,21 @@ export const addSocketQueueItemStatusChangedEventListener = (startAppListening:
       dispatch(
         queueApi.util.invalidateTags(['CurrentSessionQueueItem', 'NextSessionQueueItem', 'InvocationCacheStatus'])
       );
+
+      if (['in_progress'].includes(action.payload.data.queue_item.status)) {
+        forEach($nodeExecutionStates.get(), (nes) => {
+          if (!nes) {
+            return;
+          }
+          const clone = deepClone(nes);
+          clone.status = zNodeStatus.enum.PENDING;
+          clone.error = null;
+          clone.progress = null;
+          clone.progressImage = null;
+          clone.outputs = [];
+          $nodeExecutionStates.setKey(clone.nodeId, clone);
+        });
+      }
     },
   });
 };

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketSessionRetrievalError.ts

@@ -1,14 +0,0 @@
-import { logger } from 'app/logging/logger';
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { socketSessionRetrievalError } from 'services/events/actions';
-
-const log = logger('socketio');
-
-export const addSessionRetrievalErrorEventListener = (startAppListening: AppStartListening) => {
-  startAppListening({
-    actionCreator: socketSessionRetrievalError,
-    effect: (action) => {
-      log.error(action.payload, `Session retrieval error (${action.payload.data.graph_execution_state_id})`);
-    },
-  });
-};

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/stagingAreaImageSaved.ts

@@ -1,6 +1,6 @@
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { stagingAreaImageSaved } from 'features/canvas/store/actions';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -29,15 +29,14 @@ export const addStagingAreaImageSavedListener = (startAppListening: AppStartList
             })
           );
         }
-        dispatch(addToast({ title: t('toast.imageSaved'), status: 'success' }));
+        toast({ id: 'IMAGE_SAVED', title: t('toast.imageSaved'), status: 'success' });
       } catch (error) {
-        dispatch(
-          addToast({
-            title: t('toast.imageSavingFailed'),
-            description: (error as Error)?.message,
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'IMAGE_SAVE_FAILED',
+          title: t('toast.imageSavingFailed'),
+          description: (error as Error)?.message,
+          status: 'error',
+        });
       }
     },
   });

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested.ts

@@ -1,12 +1,11 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { updateAllNodesRequested } from 'features/nodes/store/actions';
-import { nodeReplaced } from 'features/nodes/store/nodesSlice';
+import { $templates, nodesChanged } from 'features/nodes/store/nodesSlice';
 import { NodeUpdateError } from 'features/nodes/types/error';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { getNeedsUpdate, updateNode } from 'features/nodes/util/node/nodeUpdate';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 
 export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartListening) => {
@@ -14,7 +13,8 @@ export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartLi
     actionCreator: updateAllNodesRequested,
     effect: (action, { dispatch, getState }) => {
       const log = logger('nodes');
-      const { nodes, templates } = getState().nodes;
+      const { nodes } = getState().nodes.present;
+      const templates = $templates.get();
 
       let unableToUpdateCount = 0;
 
@@ -24,13 +24,18 @@ export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartLi
           unableToUpdateCount++;
           return;
         }
-        if (!getNeedsUpdate(node, template)) {
+        if (!getNeedsUpdate(node.data, template)) {
           // No need to increment the count here, since we're not actually updating
           return;
         }
         try {
           const updatedNode = updateNode(node, template);
-          dispatch(nodeReplaced({ nodeId: updatedNode.id, node: updatedNode }));
+          dispatch(
+            nodesChanged([
+              { type: 'remove', id: updatedNode.id },
+              { type: 'add', item: updatedNode },
+            ])
+          );
         } catch (e) {
           if (e instanceof NodeUpdateError) {
             unableToUpdateCount++;
@@ -44,24 +49,18 @@ export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartLi
             count: unableToUpdateCount,
           })
         );
-        dispatch(
-          addToast(
-            makeToast({
-              title: t('nodes.unableToUpdateNodes', {
-                count: unableToUpdateCount,
-              }),
-            })
-          )
-        );
+        toast({
+          id: 'UNABLE_TO_UPDATE_NODES',
+          title: t('nodes.unableToUpdateNodes', {
+            count: unableToUpdateCount,
+          }),
+        });
       } else {
-        dispatch(
-          addToast(
-            makeToast({
-              title: t('nodes.allNodesUpdated'),
-              status: 'success',
-            })
-          )
-        );
+        toast({
+          id: 'ALL_NODES_UPDATED',
+          title: t('nodes.allNodesUpdated'),
+          status: 'success',
+        });
       }
     },
   });

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/upscaleRequested.ts

@@ -4,7 +4,7 @@ import type { AppStartListening } from 'app/store/middleware/listenerMiddleware'
 import { parseify } from 'common/util/serialize';
 import { buildAdHocUpscaleGraph } from 'features/nodes/util/graph/buildAdHocUpscaleGraph';
 import { createIsAllowedToUpscaleSelector } from 'features/parameters/hooks/useIsAllowedToUpscale';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { queueApi } from 'services/api/endpoints/queue';
 import type { BatchConfig, ImageDTO } from 'services/api/types';
@@ -29,12 +29,11 @@ export const addUpscaleRequestedListener = (startAppListening: AppStartListening
           { imageDTO },
           t(detailTKey ?? 'parameters.isAllowedToUpscale.tooLarge') // should never coalesce
         );
-        dispatch(
-          addToast({
-            title: t(detailTKey ?? 'parameters.isAllowedToUpscale.tooLarge'), // should never coalesce
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'NOT_ALLOWED_TO_UPSCALE',
+          title: t(detailTKey ?? 'parameters.isAllowedToUpscale.tooLarge'), // should never coalesce
+          status: 'error',
+        });
         return;
       }
 
@@ -65,12 +64,11 @@ export const addUpscaleRequestedListener = (startAppListening: AppStartListening
         if (error instanceof Object && 'status' in error && error.status === 403) {
           return;
         } else {
-          dispatch(
-            addToast({
-              title: t('queue.graphFailedToQueue'),
-              status: 'error',
-            })
-          );
+          toast({
+            id: 'GRAPH_QUEUE_FAILED',
+            title: t('queue.graphFailedToQueue'),
+            status: 'error',
+          });
         }
       }
     },

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested.ts

@@ -2,50 +2,64 @@ import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { workflowLoaded, workflowLoadRequested } from 'features/nodes/store/actions';
+import { $templates } from 'features/nodes/store/nodesSlice';
 import { $flow } from 'features/nodes/store/reactFlowInstance';
+import type { Templates } from 'features/nodes/store/types';
 import { WorkflowMigrationError, WorkflowVersionError } from 'features/nodes/types/error';
+import { graphToWorkflow } from 'features/nodes/util/workflow/graphToWorkflow';
 import { validateWorkflow } from 'features/nodes/util/workflow/validateWorkflow';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
+import { checkBoardAccess, checkImageAccess, checkModelAccess } from 'services/api/hooks/accessChecks';
+import type { GraphAndWorkflowResponse, NonNullableGraph } from 'services/api/types';
 import { z } from 'zod';
 import { fromZodError } from 'zod-validation-error';
 
+const getWorkflow = async (data: GraphAndWorkflowResponse, templates: Templates) => {
+  if (data.workflow) {
+    // Prefer to load the workflow if it's available - it has more information
+    const parsed = JSON.parse(data.workflow);
+    return await validateWorkflow(parsed, templates, checkImageAccess, checkBoardAccess, checkModelAccess);
+  } else if (data.graph) {
+    // Else we fall back on the graph, using the graphToWorkflow function to convert and do layout
+    const parsed = JSON.parse(data.graph);
+    const workflow = graphToWorkflow(parsed as NonNullableGraph, true);
+    return await validateWorkflow(workflow, templates, checkImageAccess, checkBoardAccess, checkModelAccess);
+  } else {
+    throw new Error('No workflow or graph provided');
+  }
+};
+
 export const addWorkflowLoadRequestedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: workflowLoadRequested,
-    effect: (action, { dispatch, getState }) => {
+    effect: async (action, { dispatch }) => {
       const log = logger('nodes');
-      const { workflow, asCopy } = action.payload;
-      const nodeTemplates = getState().nodes.templates;
+      const { data, asCopy } = action.payload;
+      const nodeTemplates = $templates.get();
 
       try {
-        const { workflow: validatedWorkflow, warnings } = validateWorkflow(workflow, nodeTemplates);
+        const { workflow, warnings } = await getWorkflow(data, nodeTemplates);
 
         if (asCopy) {
           // If we're loading a copy, we need to remove the ID so that the backend will create a new workflow
-          delete validatedWorkflow.id;
+          delete workflow.id;
         }
 
-        dispatch(workflowLoaded(validatedWorkflow));
+        dispatch(workflowLoaded(workflow));
         if (!warnings.length) {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('toast.workflowLoaded'),
-                status: 'success',
-              })
-            )
-          );
+          toast({
+            id: 'WORKFLOW_LOADED',
+            title: t('toast.workflowLoaded'),
+            status: 'success',
+          });
         } else {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('toast.loadedWithWarnings'),
-                status: 'warning',
-              })
-            )
-          );
+          toast({
+            id: 'WORKFLOW_LOADED',
+            title: t('toast.loadedWithWarnings'),
+            status: 'warning',
+          });
+
           warnings.forEach(({ message, ...rest }) => {
             log.warn(rest, message);
           });
@@ -58,54 +72,42 @@ export const addWorkflowLoadRequestedListener = (startAppListening: AppStartList
         if (e instanceof WorkflowVersionError) {
           // The workflow version was not recognized in the valid list of versions
           log.error({ error: parseify(e) }, e.message);
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: e.message,
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: e.message,
+          });
         } else if (e instanceof WorkflowMigrationError) {
           // There was a problem migrating the workflow to the latest version
           log.error({ error: parseify(e) }, e.message);
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: e.message,
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: e.message,
+          });
         } else if (e instanceof z.ZodError) {
           // There was a problem validating the workflow itself
           const { message } = fromZodError(e, {
             prefix: t('nodes.workflowValidation'),
           });
           log.error({ error: parseify(e) }, message);
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: message,
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: message,
+          });
         } else {
           // Some other error occurred
           log.error({ error: parseify(e) }, t('nodes.unknownErrorValidatingWorkflow'));
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: t('nodes.unknownErrorValidatingWorkflow'),
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: t('nodes.unknownErrorValidatingWorkflow'),
+          });
         }
       }
     },

invokeai/frontend/web/src/app/store/store.ts

@@ -21,7 +21,8 @@ import { galleryPersistConfig, gallerySlice } from 'features/gallery/store/galle
 import { hrfPersistConfig, hrfSlice } from 'features/hrf/store/hrfSlice';
 import { loraPersistConfig, loraSlice } from 'features/lora/store/loraSlice';
 import { modelManagerV2PersistConfig, modelManagerV2Slice } from 'features/modelManagerV2/store/modelManagerV2Slice';
-import { nodesPersistConfig, nodesSlice } from 'features/nodes/store/nodesSlice';
+import { nodesPersistConfig, nodesSlice, nodesUndoableConfig } from 'features/nodes/store/nodesSlice';
+import { workflowSettingsPersistConfig, workflowSettingsSlice } from 'features/nodes/store/workflowSettingsSlice';
 import { workflowPersistConfig, workflowSlice } from 'features/nodes/store/workflowSlice';
 import { generationPersistConfig, generationSlice } from 'features/parameters/store/generationSlice';
 import { postprocessingPersistConfig, postprocessingSlice } from 'features/parameters/store/postprocessingSlice';
@@ -50,7 +51,7 @@ const allReducers = {
   [canvasSlice.name]: canvasSlice.reducer,
   [gallerySlice.name]: gallerySlice.reducer,
   [generationSlice.name]: generationSlice.reducer,
-  [nodesSlice.name]: nodesSlice.reducer,
+  [nodesSlice.name]: undoable(nodesSlice.reducer, nodesUndoableConfig),
   [postprocessingSlice.name]: postprocessingSlice.reducer,
   [systemSlice.name]: systemSlice.reducer,
   [configSlice.name]: configSlice.reducer,
@@ -66,6 +67,7 @@ const allReducers = {
   [workflowSlice.name]: workflowSlice.reducer,
   [hrfSlice.name]: hrfSlice.reducer,
   [controlLayersSlice.name]: undoable(controlLayersSlice.reducer, controlLayersUndoableConfig),
+  [workflowSettingsSlice.name]: workflowSettingsSlice.reducer,
   [api.reducerPath]: api.reducer,
 };
 
@@ -111,6 +113,7 @@ const persistConfigs: { [key in keyof typeof allReducers]?: PersistConfig } = {
   [modelManagerV2PersistConfig.name]: modelManagerV2PersistConfig,
   [hrfPersistConfig.name]: hrfPersistConfig,
   [controlLayersPersistConfig.name]: controlLayersPersistConfig,
+  [workflowSettingsPersistConfig.name]: workflowSettingsPersistConfig,
 };
 
 const unserialize: UnserializeFunction = (data, key) => {

invokeai/frontend/web/src/app/types/invokeai.ts

@@ -74,6 +74,7 @@ export type AppConfig = {
   maxUpscalePixels?: number;
   metadataFetchDebounce?: number;
   workflowFetchDebounce?: number;
+  isLocal?: boolean;
   sd: {
     defaultModel?: string;
     disabledControlNetModels: string[];

invokeai/frontend/web/src/common/components/IAIDndImage.tsx

@@ -70,6 +70,7 @@ const IAIDndImage = (props: IAIDndImageProps) => {
     onMouseOver,
     onMouseOut,
     dataTestId,
+    ...rest
   } = props;
 
   const [isHovered, setIsHovered] = useState(false);
@@ -138,6 +139,7 @@ const IAIDndImage = (props: IAIDndImageProps) => {
           minH={minSize ? minSize : undefined}
           userSelect="none"
           cursor={isDragDisabled || !imageDTO ? 'default' : 'pointer'}
+          {...rest}
         >
           {imageDTO && (
             <Flex

invokeai/frontend/web/src/common/hooks/useCopyImageToClipboard.ts

@@ -1,11 +1,10 @@
-import { useAppToaster } from 'app/components/Toaster';
 import { useImageUrlToBlob } from 'common/hooks/useImageUrlToBlob';
 import { copyBlobToClipboard } from 'features/system/util/copyBlobToClipboard';
+import { toast } from 'features/toast/toast';
 import { useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 
 export const useCopyImageToClipboard = () => {
-  const toaster = useAppToaster();
   const { t } = useTranslation();
   const imageUrlToBlob = useImageUrlToBlob();
 
@@ -16,12 +15,11 @@ export const useCopyImageToClipboard = () => {
   const copyImageToClipboard = useCallback(
     async (image_url: string) => {
       if (!isClipboardAPIAvailable) {
-        toaster({
+        toast({
+          id: 'PROBLEM_COPYING_IMAGE',
           title: t('toast.problemCopyingImage'),
           description: "Your browser doesn't support the Clipboard API.",
           status: 'error',
-          duration: 2500,
-          isClosable: true,
         });
       }
       try {
@@ -33,23 +31,21 @@ export const useCopyImageToClipboard = () => {
 
         copyBlobToClipboard(blob);
 
-        toaster({
+        toast({
+          id: 'IMAGE_COPIED',
           title: t('toast.imageCopied'),
           status: 'success',
-          duration: 2500,
-          isClosable: true,
         });
       } catch (err) {
-        toaster({
+        toast({
+          id: 'PROBLEM_COPYING_IMAGE',
           title: t('toast.problemCopyingImage'),
           description: String(err),
           status: 'error',
-          duration: 2500,
-          isClosable: true,
         });
       }
     },
-    [imageUrlToBlob, isClipboardAPIAvailable, t, toaster]
+    [imageUrlToBlob, isClipboardAPIAvailable, t]
   );
 
   return { isClipboardAPIAvailable, copyImageToClipboard };

invokeai/frontend/web/src/common/hooks/useDownloadImage.ts

@@ -1,13 +1,12 @@
 import { useStore } from '@nanostores/react';
-import { useAppToaster } from 'app/components/Toaster';
 import { $authToken } from 'app/store/nanostores/authToken';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { imageDownloaded } from 'features/gallery/store/actions';
+import { toast } from 'features/toast/toast';
 import { useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 
 export const useDownloadImage = () => {
-  const toaster = useAppToaster();
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
   const authToken = useStore($authToken);
@@ -37,16 +36,15 @@ export const useDownloadImage = () => {
         window.URL.revokeObjectURL(url);
         dispatch(imageDownloaded());
       } catch (err) {
-        toaster({
+        toast({
+          id: 'PROBLEM_DOWNLOADING_IMAGE',
           title: t('toast.problemDownloadingImage'),
           description: String(err),
           status: 'error',
-          duration: 2500,
-          isClosable: true,
         });
       }
     },
-    [t, toaster, dispatch, authToken]
+    [t, dispatch, authToken]
   );
 
   return { downloadImage };

invokeai/frontend/web/src/common/hooks/useFullscreenDropzone.ts

@@ -1,6 +1,6 @@
-import { useAppToaster } from 'app/components/Toaster';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
+import { toast } from 'features/toast/toast';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import { useCallback, useEffect, useState } from 'react';
 import type { Accept, FileRejection } from 'react-dropzone';
@@ -26,7 +26,6 @@ const selectPostUploadAction = createMemoizedSelector(activeTabNameSelector, (ac
 
 export const useFullscreenDropzone = () => {
   const { t } = useTranslation();
-  const toaster = useAppToaster();
   const postUploadAction = useAppSelector(selectPostUploadAction);
   const autoAddBoardId = useAppSelector((s) => s.gallery.autoAddBoardId);
   const [isHandlingUpload, setIsHandlingUpload] = useState<boolean>(false);
@@ -37,13 +36,14 @@ export const useFullscreenDropzone = () => {
     (rejection: FileRejection) => {
       setIsHandlingUpload(true);
 
-      toaster({
+      toast({
+        id: 'UPLOAD_FAILED',
         title: t('toast.uploadFailed'),
         description: rejection.errors.map((error) => error.message).join('\n'),
         status: 'error',
       });
     },
-    [t, toaster]
+    [t]
   );
 
   const fileAcceptedCallback = useCallback(
@@ -62,7 +62,8 @@ export const useFullscreenDropzone = () => {
   const onDrop = useCallback(
     (acceptedFiles: Array<File>, fileRejections: Array<FileRejection>) => {
       if (fileRejections.length > 1) {
-        toaster({
+        toast({
+          id: 'UPLOAD_FAILED',
           title: t('toast.uploadFailed'),
           description: t('toast.uploadFailedInvalidUploadDesc'),
           status: 'error',
@@ -78,7 +79,7 @@ export const useFullscreenDropzone = () => {
         fileAcceptedCallback(file);
       });
     },
-    [t, toaster, fileAcceptedCallback, fileRejectionCallback]
+    [t, fileAcceptedCallback, fileRejectionCallback]
   );
 
   const onDragOver = useCallback(() => {

invokeai/frontend/web/src/common/hooks/useGroupedModelCombobox.ts

@@ -13,6 +13,7 @@ type UseGroupedModelComboboxArg<T extends AnyModelConfig> = {
   onChange: (value: T | null) => void;
   getIsDisabled?: (model: T) => boolean;
   isLoading?: boolean;
+  groupByType?: boolean;
 };
 
 type UseGroupedModelComboboxReturn = {
@@ -23,17 +24,21 @@ type UseGroupedModelComboboxReturn = {
   noOptionsMessage: () => string;
 };
 
+const groupByBaseFunc = <T extends AnyModelConfig>(model: T) => model.base.toUpperCase();
+const groupByBaseAndTypeFunc = <T extends AnyModelConfig>(model: T) =>
+  `${model.base.toUpperCase()} / ${model.type.replaceAll('_', ' ').toUpperCase()}`;
+
 export const useGroupedModelCombobox = <T extends AnyModelConfig>(
   arg: UseGroupedModelComboboxArg<T>
 ): UseGroupedModelComboboxReturn => {
   const { t } = useTranslation();
   const base_model = useAppSelector((s) => s.generation.model?.base ?? 'sdxl');
-  const { modelConfigs, selectedModel, getIsDisabled, onChange, isLoading } = arg;
+  const { modelConfigs, selectedModel, getIsDisabled, onChange, isLoading, groupByType = false } = arg;
   const options = useMemo<GroupBase<ComboboxOption>[]>(() => {
     if (!modelConfigs) {
       return [];
     }
-    const groupedModels = groupBy(modelConfigs, 'base');
+    const groupedModels = groupBy(modelConfigs, groupByType ? groupByBaseAndTypeFunc : groupByBaseFunc);
     const _options = reduce(
       groupedModels,
       (acc, val, label) => {
@@ -49,9 +54,9 @@ export const useGroupedModelCombobox = <T extends AnyModelConfig>(
       },
       [] as GroupBase<ComboboxOption>[]
     );
-    _options.sort((a) => (a.label === base_model ? -1 : 1));
+    _options.sort((a) => (a.label?.split('/')[0]?.toLowerCase().includes(base_model) ? -1 : 1));
     return _options;
-  }, [getIsDisabled, modelConfigs, base_model]);
+  }, [modelConfigs, groupByType, getIsDisabled, base_model]);
 
   const value = useMemo(
     () =>

invokeai/frontend/web/src/common/hooks/useIsReadyToEnqueue.ts

@@ -1,3 +1,4 @@
+import { useStore } from '@nanostores/react';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import {
@@ -6,187 +7,230 @@ import {
 } from 'features/controlAdapters/store/controlAdaptersSlice';
 import { isControlNetOrT2IAdapter } from 'features/controlAdapters/store/types';
 import { selectControlLayersSlice } from 'features/controlLayers/store/controlLayersSlice';
+import type { Layer } from 'features/controlLayers/store/types';
 import { selectDynamicPromptsSlice } from 'features/dynamicPrompts/store/dynamicPromptsSlice';
 import { getShouldProcessPrompt } from 'features/dynamicPrompts/util/getShouldProcessPrompt';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { $templates, selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import type { Templates } from 'features/nodes/store/types';
+import { selectWorkflowSettingsSlice } from 'features/nodes/store/workflowSettingsSlice';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { selectGenerationSlice } from 'features/parameters/store/generationSlice';
 import { selectSystemSlice } from 'features/system/store/systemSlice';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import i18n from 'i18next';
-import { forEach } from 'lodash-es';
+import { forEach, upperFirst } from 'lodash-es';
+import { useMemo } from 'react';
 import { getConnectedEdges } from 'reactflow';
 
-const selector = createMemoizedSelector(
-  [
-    selectControlAdaptersSlice,
-    selectGenerationSlice,
-    selectSystemSlice,
-    selectNodesSlice,
-    selectDynamicPromptsSlice,
-    selectControlLayersSlice,
-    activeTabNameSelector,
-  ],
-  (controlAdapters, generation, system, nodes, dynamicPrompts, controlLayers, activeTabName) => {
-    const { model } = generation;
-    const { positivePrompt } = controlLayers.present;
+const LAYER_TYPE_TO_TKEY: Record<Layer['type'], string> = {
+  initial_image_layer: 'controlLayers.globalInitialImage',
+  control_adapter_layer: 'controlLayers.globalControlAdapter',
+  ip_adapter_layer: 'controlLayers.globalIPAdapter',
+  regional_guidance_layer: 'controlLayers.regionalGuidance',
+};
 
-    const { isConnected } = system;
+const createSelector = (templates: Templates) =>
+  createMemoizedSelector(
+    [
+      selectControlAdaptersSlice,
+      selectGenerationSlice,
+      selectSystemSlice,
+      selectNodesSlice,
+      selectWorkflowSettingsSlice,
+      selectDynamicPromptsSlice,
+      selectControlLayersSlice,
+      activeTabNameSelector,
+    ],
+    (controlAdapters, generation, system, nodes, workflowSettings, dynamicPrompts, controlLayers, activeTabName) => {
+      const { model } = generation;
+      const { size } = controlLayers.present;
+      const { positivePrompt } = controlLayers.present;
 
-    const reasons: string[] = [];
+      const { isConnected } = system;
 
-    // Cannot generate if not connected
-    if (!isConnected) {
-      reasons.push(i18n.t('parameters.invoke.systemDisconnected'));
-    }
+      const reasons: { prefix?: string; content: string }[] = [];
 
-    if (activeTabName === 'workflows') {
-      if (nodes.shouldValidateGraph) {
-        if (!nodes.nodes.length) {
-          reasons.push(i18n.t('parameters.invoke.noNodesInGraph'));
+      // Cannot generate if not connected
+      if (!isConnected) {
+        reasons.push({ content: i18n.t('parameters.invoke.systemDisconnected') });
+      }
+
+      if (activeTabName === 'workflows') {
+        if (workflowSettings.shouldValidateGraph) {
+          if (!nodes.nodes.length) {
+            reasons.push({ content: i18n.t('parameters.invoke.noNodesInGraph') });
+          }
+
+          nodes.nodes.forEach((node) => {
+            if (!isInvocationNode(node)) {
+              return;
+            }
+
+            const nodeTemplate = templates[node.data.type];
+
+            if (!nodeTemplate) {
+              // Node type not found
+              reasons.push({ content: i18n.t('parameters.invoke.missingNodeTemplate') });
+              return;
+            }
+
+            const connectedEdges = getConnectedEdges([node], nodes.edges);
+
+            forEach(node.data.inputs, (field) => {
+              const fieldTemplate = nodeTemplate.inputs[field.name];
+              const hasConnection = connectedEdges.some(
+                (edge) => edge.target === node.id && edge.targetHandle === field.name
+              );
+
+              if (!fieldTemplate) {
+                reasons.push({ content: i18n.t('parameters.invoke.missingFieldTemplate') });
+                return;
+              }
+
+              if (fieldTemplate.required && field.value === undefined && !hasConnection) {
+                reasons.push({
+                  content: i18n.t('parameters.invoke.missingInputForField', {
+                    nodeLabel: node.data.label || nodeTemplate.title,
+                    fieldLabel: field.label || fieldTemplate.title,
+                  }),
+                });
+                return;
+              }
+            });
+          });
+        }
+      } else {
+        if (dynamicPrompts.prompts.length === 0 && getShouldProcessPrompt(positivePrompt)) {
+          reasons.push({ content: i18n.t('parameters.invoke.noPrompts') });
         }
 
-        nodes.nodes.forEach((node) => {
-          if (!isInvocationNode(node)) {
-            return;
-          }
+        if (!model) {
+          reasons.push({ content: i18n.t('parameters.invoke.noModelSelected') });
+        }
 
-          const nodeTemplate = nodes.templates[node.data.type];
+        if (activeTabName === 'generation') {
+          // Handling for generation tab
+          controlLayers.present.layers
+            .filter((l) => l.isEnabled)
+            .forEach((l, i) => {
+              const layerLiteral = i18n.t('controlLayers.layers_one');
+              const layerNumber = i + 1;
+              const layerType = i18n.t(LAYER_TYPE_TO_TKEY[l.type]);
+              const prefix = `${layerLiteral} #${layerNumber} (${layerType})`;
+              const problems: string[] = [];
+              if (l.type === 'control_adapter_layer') {
+                // Must have model
+                if (!l.controlAdapter.model) {
+                  problems.push(i18n.t('parameters.invoke.layer.controlAdapterNoModelSelected'));
+                }
+                // Model base must match
+                if (l.controlAdapter.model?.base !== model?.base) {
+                  problems.push(i18n.t('parameters.invoke.layer.controlAdapterIncompatibleBaseModel'));
+                }
+                // Must have a control image OR, if it has a processor, it must have a processed image
+                if (!l.controlAdapter.image) {
+                  problems.push(i18n.t('parameters.invoke.layer.controlAdapterNoImageSelected'));
+                } else if (l.controlAdapter.processorConfig && !l.controlAdapter.processedImage) {
+                  problems.push(i18n.t('parameters.invoke.layer.controlAdapterImageNotProcessed'));
+                }
+                // T2I Adapters require images have dimensions that are multiples of 64 (SD1.5) or 32 (SDXL)
+                if (l.controlAdapter.type === 't2i_adapter') {
+                  const multiple = model?.base === 'sdxl' ? 32 : 64;
+                  if (size.width % multiple !== 0 || size.height % multiple !== 0) {
+                    problems.push(i18n.t('parameters.invoke.layer.t2iAdapterIncompatibleDimensions', { multiple }));
+                  }
+                }
+              }
 
-          if (!nodeTemplate) {
-            // Node type not found
-            reasons.push(i18n.t('parameters.invoke.missingNodeTemplate'));
-            return;
-          }
+              if (l.type === 'ip_adapter_layer') {
+                // Must have model
+                if (!l.ipAdapter.model) {
+                  problems.push(i18n.t('parameters.invoke.layer.ipAdapterNoModelSelected'));
+                }
+                // Model base must match
+                if (l.ipAdapter.model?.base !== model?.base) {
+                  problems.push(i18n.t('parameters.invoke.layer.ipAdapterIncompatibleBaseModel'));
+                }
+                // Must have an image
+                if (!l.ipAdapter.image) {
+                  problems.push(i18n.t('parameters.invoke.layer.ipAdapterNoImageSelected'));
+                }
+              }
 
-          const connectedEdges = getConnectedEdges([node], nodes.edges);
+              if (l.type === 'initial_image_layer') {
+                // Must have an image
+                if (!l.image) {
+                  problems.push(i18n.t('parameters.invoke.layer.initialImageNoImageSelected'));
+                }
+              }
 
-          forEach(node.data.inputs, (field) => {
-            const fieldTemplate = nodeTemplate.inputs[field.name];
-            const hasConnection = connectedEdges.some(
-              (edge) => edge.target === node.id && edge.targetHandle === field.name
-            );
+              if (l.type === 'regional_guidance_layer') {
+                // Must have a region
+                if (l.maskObjects.length === 0) {
+                  problems.push(i18n.t('parameters.invoke.layer.rgNoRegion'));
+                }
+                // Must have at least 1 prompt or IP Adapter
+                if (l.positivePrompt === null && l.negativePrompt === null && l.ipAdapters.length === 0) {
+                  problems.push(i18n.t('parameters.invoke.layer.rgNoPromptsOrIPAdapters'));
+                }
+                l.ipAdapters.forEach((ipAdapter) => {
+                  // Must have model
+                  if (!ipAdapter.model) {
+                    problems.push(i18n.t('parameters.invoke.layer.ipAdapterNoModelSelected'));
+                  }
+                  // Model base must match
+                  if (ipAdapter.model?.base !== model?.base) {
+                    problems.push(i18n.t('parameters.invoke.layer.ipAdapterIncompatibleBaseModel'));
+                  }
+                  // Must have an image
+                  if (!ipAdapter.image) {
+                    problems.push(i18n.t('parameters.invoke.layer.ipAdapterNoImageSelected'));
+                  }
+                });
+              }
 
-            if (!fieldTemplate) {
-              reasons.push(i18n.t('parameters.invoke.missingFieldTemplate'));
-              return;
-            }
+              if (problems.length) {
+                const content = upperFirst(problems.join(', '));
+                reasons.push({ prefix, content });
+              }
+            });
+        } else {
+          // Handling for all other tabs
+          selectControlAdapterAll(controlAdapters)
+            .filter((ca) => ca.isEnabled)
+            .forEach((ca, i) => {
+              if (!ca.isEnabled) {
+                return;
+              }
 
-            if (fieldTemplate.required && field.value === undefined && !hasConnection) {
-              reasons.push(
-                i18n.t('parameters.invoke.missingInputForField', {
-                  nodeLabel: node.data.label || nodeTemplate.title,
-                  fieldLabel: field.label || fieldTemplate.title,
-                })
-              );
-              return;
-            }
-          });
-        });
-      }
-    } else {
-      if (dynamicPrompts.prompts.length === 0 && getShouldProcessPrompt(positivePrompt)) {
-        reasons.push(i18n.t('parameters.invoke.noPrompts'));
+              if (!ca.model) {
+                reasons.push({ content: i18n.t('parameters.invoke.noModelForControlAdapter', { number: i + 1 }) });
+              } else if (ca.model.base !== model?.base) {
+                // This should never happen, just a sanity check
+                reasons.push({
+                  content: i18n.t('parameters.invoke.incompatibleBaseModelForControlAdapter', { number: i + 1 }),
+                });
+              }
+
+              if (
+                !ca.controlImage ||
+                (isControlNetOrT2IAdapter(ca) && !ca.processedControlImage && ca.processorType !== 'none')
+              ) {
+                reasons.push({
+                  content: i18n.t('parameters.invoke.noControlImageForControlAdapter', { number: i + 1 }),
+                });
+              }
+            });
+        }
       }
 
-      if (!model) {
-        reasons.push(i18n.t('parameters.invoke.noModelSelected'));
-      }
-
-      if (activeTabName === 'generation') {
-        // Handling for generation tab
-        controlLayers.present.layers
-          .filter((l) => l.isEnabled)
-          .flatMap((l) => {
-            if (l.type === 'control_adapter_layer') {
-              return l.controlAdapter;
-            } else if (l.type === 'ip_adapter_layer') {
-              return l.ipAdapter;
-            } else if (l.type === 'regional_guidance_layer') {
-              return l.ipAdapters;
-            }
-            return [];
-          })
-          .forEach((ca, i) => {
-            const hasNoModel = !ca.model;
-            const mismatchedModelBase = ca.model?.base !== model?.base;
-            const hasNoImage = !ca.image;
-            const imageNotProcessed =
-              (ca.type === 'controlnet' || ca.type === 't2i_adapter') && !ca.processedImage && ca.processorConfig;
-
-            if (hasNoModel) {
-              reasons.push(
-                i18n.t('parameters.invoke.noModelForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-            if (mismatchedModelBase) {
-              // This should never happen, just a sanity check
-              reasons.push(
-                i18n.t('parameters.invoke.incompatibleBaseModelForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-            if (hasNoImage) {
-              reasons.push(
-                i18n.t('parameters.invoke.noControlImageForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-            if (imageNotProcessed) {
-              reasons.push(
-                i18n.t('parameters.invoke.imageNotProcessedForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-          });
-      } else {
-        // Handling for all other tabs
-        selectControlAdapterAll(controlAdapters)
-          .filter((ca) => ca.isEnabled)
-          .forEach((ca, i) => {
-            if (!ca.isEnabled) {
-              return;
-            }
-
-            if (!ca.model) {
-              reasons.push(
-                i18n.t('parameters.invoke.noModelForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            } else if (ca.model.base !== model?.base) {
-              // This should never happen, just a sanity check
-              reasons.push(
-                i18n.t('parameters.invoke.incompatibleBaseModelForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-
-            if (
-              !ca.controlImage ||
-              (isControlNetOrT2IAdapter(ca) && !ca.processedControlImage && ca.processorType !== 'none')
-            ) {
-              reasons.push(
-                i18n.t('parameters.invoke.noControlImageForControlAdapter', {
-                  number: i + 1,
-                })
-              );
-            }
-          });
-      }
+      return { isReady: !reasons.length, reasons };
     }
-
-    return { isReady: !reasons.length, reasons };
-  }
-);
+  );
 
 export const useIsReadyToEnqueue = () => {
-  const { isReady, reasons } = useAppSelector(selector);
-  return { isReady, reasons };
+  const templates = useStore($templates);
+  const selector = useMemo(() => createSelector(templates), [templates]);
+  const value = useAppSelector(selector);
+  return value;
 };

invokeai/frontend/web/src/common/util/toast.ts

@@ -1,6 +0,0 @@
-import { createStandaloneToast, theme, TOAST_OPTIONS } from '@invoke-ai/ui-library';
-
-export const { toast } = createStandaloneToast({
-  theme: theme,
-  defaultOptions: TOAST_OPTIONS.defaultOptions,
-});

invokeai/frontend/web/src/features/canvas/components/IAICanvasToolbar/IAICanvasToolbar.tsx

@@ -21,8 +21,6 @@ import {
   setShouldShowBoundingBox,
 } from 'features/canvas/store/canvasSlice';
 import type { CanvasLayer } from 'features/canvas/store/canvasTypes';
-import { LAYER_NAMES_DICT } from 'features/canvas/store/canvasTypes';
-import { ViewerButton } from 'features/gallery/components/ImageViewer/ViewerButton';
 import { memo, useCallback, useMemo } from 'react';
 import { useHotkeys } from 'react-hotkeys-hook';
 import { useTranslation } from 'react-i18next';
@@ -217,110 +215,107 @@ const IAICanvasToolbar = () => {
     [dispatch, isMaskEnabled]
   );
 
-  const value = useMemo(() => LAYER_NAMES_DICT.filter((o) => o.value === layer)[0], [layer]);
+  const layerOptions = useMemo<{ label: string; value: CanvasLayer }[]>(
+    () => [
+      { label: t('unifiedCanvas.base'), value: 'base' },
+      { label: t('unifiedCanvas.mask'), value: 'mask' },
+    ],
+    [t]
+  );
+  const layerValue = useMemo(() => layerOptions.filter((o) => o.value === layer)[0] ?? null, [layer, layerOptions]);
 
   return (
-    <Flex w="full" gap={2} alignItems="center">
-      <Flex flex={1} justifyContent="center">
-        <Flex gap={2} marginInlineEnd="auto" />
-      </Flex>
-      <Flex flex={1} gap={2} justifyContent="center">
-        <Tooltip label={`${t('unifiedCanvas.layer')} (Q)`}>
-          <FormControl isDisabled={isStaging} w="5rem">
-            <Combobox value={value} options={LAYER_NAMES_DICT} onChange={handleChangeLayer} />
-          </FormControl>
-        </Tooltip>
+    <Flex alignItems="center" gap={2} flexWrap="wrap">
+      <Tooltip label={`${t('unifiedCanvas.layer')} (Q)`}>
+        <FormControl isDisabled={isStaging} w="5rem">
+          <Combobox value={layerValue} options={layerOptions} onChange={handleChangeLayer} />
+        </FormControl>
+      </Tooltip>
 
-        <IAICanvasMaskOptions />
-        <IAICanvasToolChooserOptions />
+      <IAICanvasMaskOptions />
+      <IAICanvasToolChooserOptions />
 
-        <ButtonGroup>
-          <IconButton
-            aria-label={`${t('unifiedCanvas.move')} (V)`}
-            tooltip={`${t('unifiedCanvas.move')} (V)`}
-            icon={<PiHandGrabbingBold />}
-            isChecked={tool === 'move' || isStaging}
-            onClick={handleSelectMoveTool}
-          />
-          <IconButton
-            aria-label={`${shouldShowBoundingBox ? t('unifiedCanvas.hideBoundingBox') : t('unifiedCanvas.showBoundingBox')} (Shift + H)`}
-            tooltip={`${shouldShowBoundingBox ? t('unifiedCanvas.hideBoundingBox') : t('unifiedCanvas.showBoundingBox')} (Shift + H)`}
-            icon={shouldShowBoundingBox ? <PiEyeBold /> : <PiEyeSlashBold />}
-            onClick={handleSetShouldShowBoundingBox}
-            isDisabled={isStaging}
-          />
-          <IconButton
-            aria-label={`${t('unifiedCanvas.resetView')} (R)`}
-            tooltip={`${t('unifiedCanvas.resetView')} (R)`}
-            icon={<PiCrosshairSimpleBold />}
-            onClick={handleClickResetCanvasView}
-          />
-        </ButtonGroup>
+      <ButtonGroup>
+        <IconButton
+          aria-label={`${t('unifiedCanvas.move')} (V)`}
+          tooltip={`${t('unifiedCanvas.move')} (V)`}
+          icon={<PiHandGrabbingBold />}
+          isChecked={tool === 'move' || isStaging}
+          onClick={handleSelectMoveTool}
+        />
+        <IconButton
+          aria-label={`${shouldShowBoundingBox ? t('unifiedCanvas.hideBoundingBox') : t('unifiedCanvas.showBoundingBox')} (Shift + H)`}
+          tooltip={`${shouldShowBoundingBox ? t('unifiedCanvas.hideBoundingBox') : t('unifiedCanvas.showBoundingBox')} (Shift + H)`}
+          icon={shouldShowBoundingBox ? <PiEyeBold /> : <PiEyeSlashBold />}
+          onClick={handleSetShouldShowBoundingBox}
+          isDisabled={isStaging}
+        />
+        <IconButton
+          aria-label={`${t('unifiedCanvas.resetView')} (R)`}
+          tooltip={`${t('unifiedCanvas.resetView')} (R)`}
+          icon={<PiCrosshairSimpleBold />}
+          onClick={handleClickResetCanvasView}
+        />
+      </ButtonGroup>
 
-        <ButtonGroup>
+      <ButtonGroup>
+        <IconButton
+          aria-label={`${t('unifiedCanvas.mergeVisible')} (Shift+M)`}
+          tooltip={`${t('unifiedCanvas.mergeVisible')} (Shift+M)`}
+          icon={<PiStackBold />}
+          onClick={handleMergeVisible}
+          isDisabled={isStaging}
+        />
+        <IconButton
+          aria-label={`${t('unifiedCanvas.saveToGallery')} (Shift+S)`}
+          tooltip={`${t('unifiedCanvas.saveToGallery')} (Shift+S)`}
+          icon={<PiFloppyDiskBold />}
+          onClick={handleSaveToGallery}
+          isDisabled={isStaging}
+        />
+        {isClipboardAPIAvailable && (
           <IconButton
-            aria-label={`${t('unifiedCanvas.mergeVisible')} (Shift+M)`}
-            tooltip={`${t('unifiedCanvas.mergeVisible')} (Shift+M)`}
-            icon={<PiStackBold />}
-            onClick={handleMergeVisible}
+            aria-label={`${t('unifiedCanvas.copyToClipboard')} (Cmd/Ctrl+C)`}
+            tooltip={`${t('unifiedCanvas.copyToClipboard')} (Cmd/Ctrl+C)`}
+            icon={<PiCopyBold />}
+            onClick={handleCopyImageToClipboard}
             isDisabled={isStaging}
           />
-          <IconButton
-            aria-label={`${t('unifiedCanvas.saveToGallery')} (Shift+S)`}
-            tooltip={`${t('unifiedCanvas.saveToGallery')} (Shift+S)`}
-            icon={<PiFloppyDiskBold />}
-            onClick={handleSaveToGallery}
-            isDisabled={isStaging}
-          />
-          {isClipboardAPIAvailable && (
-            <IconButton
-              aria-label={`${t('unifiedCanvas.copyToClipboard')} (Cmd/Ctrl+C)`}
-              tooltip={`${t('unifiedCanvas.copyToClipboard')} (Cmd/Ctrl+C)`}
-              icon={<PiCopyBold />}
-              onClick={handleCopyImageToClipboard}
-              isDisabled={isStaging}
-            />
-          )}
-          <IconButton
-            aria-label={`${t('unifiedCanvas.downloadAsImage')} (Shift+D)`}
-            tooltip={`${t('unifiedCanvas.downloadAsImage')} (Shift+D)`}
-            icon={<PiDownloadSimpleBold />}
-            onClick={handleDownloadAsImage}
-            isDisabled={isStaging}
-          />
-        </ButtonGroup>
-        <ButtonGroup>
-          <IAICanvasUndoButton />
-          <IAICanvasRedoButton />
-        </ButtonGroup>
+        )}
+        <IconButton
+          aria-label={`${t('unifiedCanvas.downloadAsImage')} (Shift+D)`}
+          tooltip={`${t('unifiedCanvas.downloadAsImage')} (Shift+D)`}
+          icon={<PiDownloadSimpleBold />}
+          onClick={handleDownloadAsImage}
+          isDisabled={isStaging}
+        />
+      </ButtonGroup>
+      <ButtonGroup>
+        <IAICanvasUndoButton />
+        <IAICanvasRedoButton />
+      </ButtonGroup>
 
-        <ButtonGroup>
-          <IconButton
-            aria-label={`${t('common.upload')}`}
-            tooltip={`${t('common.upload')}`}
-            icon={<PiUploadSimpleBold />}
-            isDisabled={isStaging}
-            {...getUploadButtonProps()}
-          />
-          <input {...getUploadInputProps()} />
-          <IconButton
-            aria-label={`${t('unifiedCanvas.clearCanvas')}`}
-            tooltip={`${t('unifiedCanvas.clearCanvas')}`}
-            icon={<PiTrashSimpleBold />}
-            onClick={handleResetCanvas}
-            colorScheme="error"
-            isDisabled={isStaging}
-          />
-        </ButtonGroup>
-        <ButtonGroup>
-          <IAICanvasSettingsButtonPopover />
-        </ButtonGroup>
-      </Flex>
-      <Flex flex={1} justifyContent="center">
-        <Flex gap={2} marginInlineStart="auto">
-          <ViewerButton />
-        </Flex>
-      </Flex>
+      <ButtonGroup>
+        <IconButton
+          aria-label={`${t('common.upload')}`}
+          tooltip={`${t('common.upload')}`}
+          icon={<PiUploadSimpleBold />}
+          isDisabled={isStaging}
+          {...getUploadButtonProps()}
+        />
+        <input {...getUploadInputProps()} />
+        <IconButton
+          aria-label={`${t('unifiedCanvas.clearCanvas')}`}
+          tooltip={`${t('unifiedCanvas.clearCanvas')}`}
+          icon={<PiTrashSimpleBold />}
+          onClick={handleResetCanvas}
+          colorScheme="error"
+          isDisabled={isStaging}
+        />
+      </ButtonGroup>
+      <ButtonGroup>
+        <IAICanvasSettingsButtonPopover />
+      </ButtonGroup>
     </Flex>
   );
 };

invokeai/frontend/web/src/features/canvas/store/canvasTypes.ts

@@ -5,11 +5,6 @@ import { z } from 'zod';
 
 export type CanvasLayer = 'base' | 'mask';
 
-export const LAYER_NAMES_DICT: { label: string; value: CanvasLayer }[] = [
-  { label: 'Base', value: 'base' },
-  { label: 'Mask', value: 'mask' },
-];
-
 const zBoundingBoxScaleMethod = z.enum(['none', 'auto', 'manual']);
 export type BoundingBoxScaleMethod = z.infer<typeof zBoundingBoxScaleMethod>;
 export const isBoundingBoxScaleMethod = (v: unknown): v is BoundingBoxScaleMethod =>

invokeai/frontend/web/src/features/controlAdapters/store/types.ts

@@ -5,22 +5,7 @@ import type {
   ParameterT2IAdapterModel,
 } from 'features/parameters/types/parameterSchemas';
 import type { components } from 'services/api/schema';
-import type {
-  CannyImageProcessorInvocation,
-  ColorMapImageProcessorInvocation,
-  ContentShuffleImageProcessorInvocation,
-  DepthAnythingImageProcessorInvocation,
-  DWOpenposeImageProcessorInvocation,
-  HedImageProcessorInvocation,
-  LineartAnimeImageProcessorInvocation,
-  LineartImageProcessorInvocation,
-  MediapipeFaceProcessorInvocation,
-  MidasDepthImageProcessorInvocation,
-  MlsdImageProcessorInvocation,
-  NormalbaeImageProcessorInvocation,
-  PidiImageProcessorInvocation,
-  ZoeDepthImageProcessorInvocation,
-} from 'services/api/types';
+import type { Invocation } from 'services/api/types';
 import type { O } from 'ts-toolbelt';
 import { z } from 'zod';
 
@@ -28,20 +13,20 @@ import { z } from 'zod';
  * Any ControlNet processor node
  */
 export type ControlAdapterProcessorNode =
-  | CannyImageProcessorInvocation
-  | ColorMapImageProcessorInvocation
-  | ContentShuffleImageProcessorInvocation
-  | DepthAnythingImageProcessorInvocation
-  | HedImageProcessorInvocation
-  | LineartAnimeImageProcessorInvocation
-  | LineartImageProcessorInvocation
-  | MediapipeFaceProcessorInvocation
-  | MidasDepthImageProcessorInvocation
-  | MlsdImageProcessorInvocation
-  | NormalbaeImageProcessorInvocation
-  | DWOpenposeImageProcessorInvocation
-  | PidiImageProcessorInvocation
-  | ZoeDepthImageProcessorInvocation;
+  | Invocation<'canny_image_processor'>
+  | Invocation<'color_map_image_processor'>
+  | Invocation<'content_shuffle_image_processor'>
+  | Invocation<'depth_anything_image_processor'>
+  | Invocation<'hed_image_processor'>
+  | Invocation<'lineart_anime_image_processor'>
+  | Invocation<'lineart_image_processor'>
+  | Invocation<'mediapipe_face_processor'>
+  | Invocation<'midas_depth_image_processor'>
+  | Invocation<'mlsd_image_processor'>
+  | Invocation<'normalbae_image_processor'>
+  | Invocation<'dw_openpose_image_processor'>
+  | Invocation<'pidi_image_processor'>
+  | Invocation<'zoe_depth_image_processor'>;
 
 /**
  * Any ControlNet processor type
@@ -71,7 +56,7 @@ export const isControlAdapterProcessorType = (v: unknown): v is ControlAdapterPr
  * The Canny processor node, with parameters flagged as required
  */
 export type RequiredCannyImageProcessorInvocation = O.Required<
-  CannyImageProcessorInvocation,
+  Invocation<'canny_image_processor'>,
   'type' | 'low_threshold' | 'high_threshold' | 'image_resolution' | 'detect_resolution'
 >;
 
@@ -79,7 +64,7 @@ export type RequiredCannyImageProcessorInvocation = O.Required<
  * The Color Map processor node, with parameters flagged as required
  */
 export type RequiredColorMapImageProcessorInvocation = O.Required<
-  ColorMapImageProcessorInvocation,
+  Invocation<'color_map_image_processor'>,
   'type' | 'color_map_tile_size'
 >;
 
@@ -87,7 +72,7 @@ export type RequiredColorMapImageProcessorInvocation = O.Required<
  * The ContentShuffle processor node, with parameters flagged as required
  */
 export type RequiredContentShuffleImageProcessorInvocation = O.Required<
-  ContentShuffleImageProcessorInvocation,
+  Invocation<'content_shuffle_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution' | 'w' | 'h' | 'f'
 >;
 
@@ -95,7 +80,7 @@ export type RequiredContentShuffleImageProcessorInvocation = O.Required<
  * The DepthAnything processor node, with parameters flagged as required
  */
 export type RequiredDepthAnythingImageProcessorInvocation = O.Required<
-  DepthAnythingImageProcessorInvocation,
+  Invocation<'depth_anything_image_processor'>,
   'type' | 'model_size' | 'resolution' | 'offload'
 >;
 
@@ -108,7 +93,7 @@ export const isDepthAnythingModelSize = (v: unknown): v is DepthAnythingModelSiz
  * The HED processor node, with parameters flagged as required
  */
 export type RequiredHedImageProcessorInvocation = O.Required<
-  HedImageProcessorInvocation,
+  Invocation<'hed_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution' | 'scribble'
 >;
 
@@ -116,7 +101,7 @@ export type RequiredHedImageProcessorInvocation = O.Required<
  * The Lineart Anime processor node, with parameters flagged as required
  */
 export type RequiredLineartAnimeImageProcessorInvocation = O.Required<
-  LineartAnimeImageProcessorInvocation,
+  Invocation<'lineart_anime_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution'
 >;
 
@@ -124,7 +109,7 @@ export type RequiredLineartAnimeImageProcessorInvocation = O.Required<
  * The Lineart processor node, with parameters flagged as required
  */
 export type RequiredLineartImageProcessorInvocation = O.Required<
-  LineartImageProcessorInvocation,
+  Invocation<'lineart_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution' | 'coarse'
 >;
 
@@ -132,7 +117,7 @@ export type RequiredLineartImageProcessorInvocation = O.Required<
  * The MediapipeFace processor node, with parameters flagged as required
  */
 export type RequiredMediapipeFaceProcessorInvocation = O.Required<
-  MediapipeFaceProcessorInvocation,
+  Invocation<'mediapipe_face_processor'>,
   'type' | 'max_faces' | 'min_confidence' | 'image_resolution' | 'detect_resolution'
 >;
 
@@ -140,7 +125,7 @@ export type RequiredMediapipeFaceProcessorInvocation = O.Required<
  * The MidasDepth processor node, with parameters flagged as required
  */
 export type RequiredMidasDepthImageProcessorInvocation = O.Required<
-  MidasDepthImageProcessorInvocation,
+  Invocation<'midas_depth_image_processor'>,
   'type' | 'a_mult' | 'bg_th' | 'image_resolution' | 'detect_resolution'
 >;
 
@@ -148,7 +133,7 @@ export type RequiredMidasDepthImageProcessorInvocation = O.Required<
  * The MLSD processor node, with parameters flagged as required
  */
 export type RequiredMlsdImageProcessorInvocation = O.Required<
-  MlsdImageProcessorInvocation,
+  Invocation<'mlsd_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution' | 'thr_v' | 'thr_d'
 >;
 
@@ -156,7 +141,7 @@ export type RequiredMlsdImageProcessorInvocation = O.Required<
  * The NormalBae processor node, with parameters flagged as required
  */
 export type RequiredNormalbaeImageProcessorInvocation = O.Required<
-  NormalbaeImageProcessorInvocation,
+  Invocation<'normalbae_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution'
 >;
 
@@ -164,7 +149,7 @@ export type RequiredNormalbaeImageProcessorInvocation = O.Required<
  * The DW Openpose processor node, with parameters flagged as required
  */
 export type RequiredDWOpenposeImageProcessorInvocation = O.Required<
-  DWOpenposeImageProcessorInvocation,
+  Invocation<'dw_openpose_image_processor'>,
   'type' | 'image_resolution' | 'draw_body' | 'draw_face' | 'draw_hands'
 >;
 
@@ -172,14 +157,14 @@ export type RequiredDWOpenposeImageProcessorInvocation = O.Required<
  * The Pidi processor node, with parameters flagged as required
  */
 export type RequiredPidiImageProcessorInvocation = O.Required<
-  PidiImageProcessorInvocation,
+  Invocation<'pidi_image_processor'>,
   'type' | 'detect_resolution' | 'image_resolution' | 'safe' | 'scribble'
 >;
 
 /**
  * The ZoeDepth processor node, with parameters flagged as required
  */
-export type RequiredZoeDepthImageProcessorInvocation = O.Required<ZoeDepthImageProcessorInvocation, 'type'>;
+export type RequiredZoeDepthImageProcessorInvocation = O.Required<Invocation<'zoe_depth_image_processor'>, 'type'>;
 
 /**
  * Any ControlNet Processor node, with its parameters flagged as required

invokeai/frontend/web/src/features/controlLayers/components/AddLayerButton.tsx

@@ -18,7 +18,12 @@ export const AddLayerButton = memo(() => {
 
   return (
     <Menu>
-      <MenuButton as={Button} leftIcon={<PiPlusBold />} variant="ghost">
+      <MenuButton
+        as={Button}
+        leftIcon={<PiPlusBold />}
+        variant="ghost"
+        data-testid="control-layers-add-layer-menu-button"
+      >
         {t('controlLayers.addLayer')}
       </MenuButton>
       <MenuList>