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..

91 Commits

Author SHA1 Message Date
70def37280 Move quantization scripts to a scripts/ subdir. 2024-08-23 18:08:37 +00:00
8af3c72de7 Update docs for T5 quantization script. 2024-08-23 18:07:14 +00:00
6405214940 Remove all references to optimum-quanto and downgrade diffusers. 2024-08-23 18:04:17 +00:00
544ab296e7 Update the T5 8-bit quantized starter model to use the BnB LLM.int8() variant. 2024-08-23 18:04:15 +00:00
86e49c423c Fixes to the T5XXL quantization script. 2024-08-23 18:03:23 +00:00
6d838fa997 Add script for quantizing a T5 model. 2024-08-23 18:03:23 +00:00
29595ce059 Switch flux to using its own conditioning field 2024-08-23 13:50:01 -04:00
9ae190fc3e Only import bnb quantize file if bitsandbytes is installed 2024-08-23 13:36:14 -04:00
5f5f535dc0 Load and unload clip/t5 encoders and run inference separately in text encoding 2024-08-23 13:28:05 -04:00
d09269ce75 Update macos test vm to macOS-14 2024-08-22 16:28:09 -04:00
708a4f68da Run FLUX VAE decoding in the user's preferred dtype rather than float32. Tested, and seems to work well at float16. 2024-08-22 18:16:43 +00:00
08633c3f04 Move prepare_latent_image_patches(...) to sampling.py with all of the related FLUX inference code. 2024-08-22 17:18:43 +00:00
4eca99574b Rename field positive_prompt -> prompt. 2024-08-22 16:18:33 +00:00
a27250a95e Add comment about incorrect T5 Tokenizer size calculation. 2024-08-22 16:09:46 +00:00
35d8e6a05b Tidy is_schnell detection logic. 2024-08-22 16:03:54 +00:00
afd4913a1b Make FLUX get_noise(...) consistent across devices/dtypes. 2024-08-22 15:56:30 +00:00
6afb1be872 Mark FLUX nodes as prototypes. 2024-08-22 15:29:59 +00:00
001d1b6e35 Attribute black-forest-labs/flux for much of the flux code 2024-08-21 15:54:07 -04:00
9b0cb37b7c Don't install bitsandbytes on macOS 2024-08-21 15:54:07 -04:00
377fcaf49c added FLUX dev to starter models 2024-08-21 15:47:19 -04:00
7861c1d779 Undo changes to the v2 dir of frontend types 2024-08-21 15:44:38 -04:00
3d251b4b93 Run ruff 2024-08-21 15:37:27 -04:00
fc760d3719 Remove automatic install of models during flux model loader, remove no longer used import function on context 2024-08-21 15:34:47 -04:00
0ce9faae7d Fix max_seq_len field description. 2024-08-21 19:17:39 +00:00
42bbab74b3 Add docs to the quantization scripts. 2024-08-21 19:08:28 +00:00
203542c7a8 Update load_flux_model_bnb_llm_int8.py to work with a single-file FLUX transformer checkpoint. 2024-08-21 19:08:16 +00:00
7f62033f1f Fix bug in InvokeInt8Params that was causing it to use double the necessary VRAM. 2024-08-21 19:08:00 +00:00
d2cb6889c5 add better workflow name 2024-08-21 14:52:23 -04:00
71088623a7 add better workflow description 2024-08-21 14:49:05 -04:00
25482c031b fix(worker) fix T5 type 2024-08-21 14:45:46 -04:00
68a917aed5 update default workflow 2024-08-21 14:45:46 -04:00
04e861ba5a fix schema 2024-08-21 14:41:58 -04:00
e063008246 tsc and lint fix 2024-08-21 14:36:44 -04:00
fe636bb6ca feat(ui): create new field for t5 encoder models in nodes 2024-08-21 14:36:44 -04:00
ec6981a860 fix(ui): pass base/type when installing models, add flux formats to MM badges 2024-08-21 14:36:44 -04:00
d5a55789f9 fix(ui): only exclude flux main models from linear UI dropdown, not model manager list 2024-08-21 14:36:44 -04:00
09d1f75fe9 add FLUX schnell starter models and submodels as dependenices or adhoc download options 2024-08-21 14:27:35 -04:00
c095af65fb add case for clip embed models in probe 2024-08-21 14:27:35 -04:00
2c72295b1c update flux_model_loader node to take a T5 encoder from node field instead of hardcoded list, assume all models have been downloaded 2024-08-21 14:27:34 -04:00
e41025ddc7 Move requantize.py to the quatnization/ dir. 2024-08-21 18:21:44 +00:00
38c2e7801f Add docs to the requantize(...) function explaining why it was copied from optimum-quanto. 2024-08-21 18:19:47 +00:00
d11dc6ddd0 Remove duplicate log_time(...) function. 2024-08-21 18:10:24 +00:00
8b0b496c2d More flux loader cleanup 2024-08-21 12:37:25 -04:00
ada483f65e Various styling and exception type updates 2024-08-21 11:59:04 -04:00
0913d062d8 Switch inheritance class of flux model loaders 2024-08-21 11:30:16 -04:00
d4872253a1 Update doc string for import_local_model and remove access_token since it's only usable for local file paths 2024-08-21 11:18:07 -04:00
e680cf76f6 Address minor review comments. 2024-08-21 13:45:22 +00:00
253b2b1dc6 Rename t5Encoder -> t5_encoder. 2024-08-21 13:27:54 +00:00
5edec7f105 add default workflow for flux t2i 2024-08-21 09:11:17 -04:00
ae9a1549ae exclude flux models from main model dropdown 2024-08-21 09:11:17 -04:00
c819da8859 Some cleanup of the tags and description of flux nodes 2024-08-21 09:11:15 -04:00
e19f079cb2 Add t5 encoders and clip embeds to the model manager 2024-08-21 09:10:53 -04:00
dd24f83d43 Fix styling/lint 2024-08-21 09:10:22 -04:00
da766f5a7e Fix support for 8b quantized t5 encoders, update exception messages in flux loaders 2024-08-21 09:10:22 -04:00
120e1cf1e9 Add tqdm progress bar to FLUX denoising. 2024-08-21 09:10:22 -04:00
5e2351f3bf Fix FLUX output image clamping. And a few other minor fixes to make inference work with the full bfloat16 FLUX transformer model. 2024-08-21 09:10:22 -04:00
d705c3cf0e Select dev/schnell based on state dict, use correct max seq len based on dev/schnell, and shift in inference, separate vae flux params into separate config 2024-08-21 09:10:20 -04:00
115f350f6f Install sub directories with folders correctly, ensure consistent dtype of tensors in flux pipeline and vae 2024-08-21 09:09:39 -04:00
be6cb2c07c Working inference node with quantized bnb nf4 checkpoint 2024-08-21 09:09:39 -04:00
4fb5529493 Remove unused param on _run_vae_decoding in flux text to image 2024-08-21 09:09:39 -04:00
b43ee0b837 Add nf4 bnb quantized format 2024-08-21 09:09:39 -04:00
3312fe8fc4 Run ruff, setup initial text to image node 2024-08-21 09:09:39 -04:00
01a2449dae Add backend functions and classes for Flux implementation, Update the way flux encoders/tokenizers are loaded for prompt encoding, Update way flux vae is loaded 2024-08-21 09:09:37 -04:00
cfe9d0ce0a Some UI cleanup, regenerate schema 2024-08-21 09:08:22 -04:00
46b6314482 Run Ruff 2024-08-21 09:06:38 -04:00
46d5107ff1 Run Ruff 2024-08-21 09:06:38 -04:00
6ea1278d22 Manage quantization of models within the loader 2024-08-21 09:06:34 -04:00
4556b57382 Remove changes to v1 workflow 2024-08-21 09:04:40 -04:00
f425d3aa3c Setup flux model loading in the UI 2024-08-21 09:04:37 -04:00
d7a39a4d67 WIP on moving from diffusers to FLUX 2024-08-21 08:59:19 -04:00
3e8a550fab More improvements for LLM.int8() - not fully tested. 2024-08-21 08:59:19 -04:00
0e96794c6e LLM.int8() quantization is working, but still some rough edges to solve. 2024-08-21 08:59:19 -04:00
23a7328a66 Clean up NF4 implementation. 2024-08-21 08:59:19 -04:00
c3cf8c3b6b NF4 inference working 2024-08-21 08:59:19 -04:00
110d58d107 NF4 loading working... I think. 2024-08-21 08:59:19 -04:00
3480e06688 wip 2024-08-21 08:59:19 -04:00
3ba60e1656 Split a FluxTextEncoderInvocation out from the FluxTextToImageInvocation. This has the advantage that we benfit from automatic caching when the prompt isn't changed. 2024-08-21 08:59:19 -04:00
cdd47b657b Make quantized loading fast for both T5XXL and FLUX transformer. 2024-08-21 08:59:19 -04:00
68c712d254 Make quantized loading fast. 2024-08-21 08:59:19 -04:00
44d7a74b88 WIP - experimentation 2024-08-21 08:59:19 -04:00
e8fb8f4d12 Make float16 inference work with FLUX on 24GB GPU. 2024-08-21 08:59:19 -04:00
9381211508 Add support for 8-bit quantizatino of the FLUX T5XXL text encoder. 2024-08-21 08:59:19 -04:00
8cce4a40d4 Make 8-bit quantization save/reload work for the FLUX transformer. Reload is still very slow with the current optimum.quanto implementation. 2024-08-21 08:59:19 -04:00
4833746698 Minor improvements to FLUX workflow. 2024-08-21 08:59:19 -04:00
8b9bf55bba Got FLUX schnell working with 8-bit quantization. Still lots of rough edges to clean up. 2024-08-21 08:59:19 -04:00
7b199fed4f Use the FluxPipeline.encode_prompt() api rather than trying to run the two text encoders separately. 2024-08-21 08:59:18 -04:00
4c7bb06f13 Add sentencepiece dependency for the T5 tokenizer. 2024-08-21 08:59:18 -04:00
13513465c8 First draft of FluxTextToImageInvocation. 2024-08-21 08:59:18 -04:00
d5a949e6c3 Update HF download logic to work for black-forest-labs/FLUX.1-schnell. 2024-08-21 08:59:18 -04:00
eb38295263 Update imports for compatibility with bumped diffusers version. 2024-08-21 08:59:18 -04:00
73ae85cdea Bump diffusers version to include FLUX support. 2024-08-21 08:59:18 -04:00
844 changed files with 29600 additions and 22374 deletions

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@ -1,22 +1,20 @@
# Invoke in Docker
First things first:
- Ensure that Docker can use your [NVIDIA][nvidia docker docs] or [AMD][amd docker docs] GPU.
- This document assumes a Linux system, but should work similarly under Windows with WSL2.
- Ensure that Docker can use the GPU on your system
- This documentation assumes Linux, but should work similarly under Windows with WSL2
- We don't recommend running Invoke in Docker on macOS at this time. It works, but very slowly.
## Quickstart
## Quickstart :lightning:
No `docker compose`, no persistence, single command, using the official images:
No `docker compose`, no persistence, just a simple one-liner using the official images:
**CUDA (NVIDIA GPU):**
**CUDA:**
```bash
docker run --runtime=nvidia --gpus=all --publish 9090:9090 ghcr.io/invoke-ai/invokeai
```
**ROCm (AMD GPU):**
**ROCm:**
```bash
docker run --device /dev/kfd --device /dev/dri --publish 9090:9090 ghcr.io/invoke-ai/invokeai:main-rocm
@ -24,20 +22,12 @@ docker run --device /dev/kfd --device /dev/dri --publish 9090:9090 ghcr.io/invok
Open `http://localhost:9090` in your browser once the container finishes booting, install some models, and generate away!
### Data persistence
To persist your generated images and downloaded models outside of the container, add a `--volume/-v` flag to the above command, e.g.:
```bash
docker run --volume /some/local/path:/invokeai {...etc...}
```
`/some/local/path/invokeai` will contain all your data.
It can *usually* be reused between different installs of Invoke. Tread with caution and read the release notes!
> [!TIP]
> To persist your data (including downloaded models) outside of the container, add a `--volume/-v` flag to the above command, e.g.: `docker run --volume /some/local/path:/invokeai <...the rest of the command>`
## Customize the container
The included `run.sh` script is a convenience wrapper around `docker compose`. It can be helpful for passing additional build arguments to `docker compose`. Alternatively, the familiar `docker compose` commands work just as well.
We ship the `run.sh` script, which is a convenient wrapper around `docker compose` for cases where custom image build args are needed. Alternatively, the familiar `docker compose` commands work just as well.
```bash
cd docker
@ -48,14 +38,11 @@ cp .env.sample .env
It will take a few minutes to build the image the first time. Once the application starts up, open `http://localhost:9090` in your browser to invoke!
>[!TIP]
>When using the `run.sh` script, the container will continue running after Ctrl+C. To shut it down, use the `docker compose down` command.
## Docker setup in detail
#### Linux
1. Ensure buildkit is enabled in the Docker daemon settings (`/etc/docker/daemon.json`)
1. Ensure builkit is enabled in the Docker daemon settings (`/etc/docker/daemon.json`)
2. Install the `docker compose` plugin using your package manager, or follow a [tutorial](https://docs.docker.com/compose/install/linux/#install-using-the-repository).
- The deprecated `docker-compose` (hyphenated) CLI probably won't work. Update to a recent version.
3. Ensure docker daemon is able to access the GPU.
@ -111,7 +98,25 @@ GPU_DRIVER=cuda
Any environment variables supported by InvokeAI can be set here. See the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.
---
## Even More Customizing!
[nvidia docker docs]: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html
[amd docker docs]: https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html
See the `docker-compose.yml` file. The `command` instruction can be uncommented and used to run arbitrary startup commands. Some examples below.
### Reconfigure the runtime directory
Can be used to download additional models from the supported model list
In conjunction with `INVOKEAI_ROOT` can be also used to initialize a runtime directory
```yaml
command:
- invokeai-configure
- --yes
```
Or install models:
```yaml
command:
- invokeai-model-install
```

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@ -11,7 +11,6 @@ from invokeai.app.services.session_queue.session_queue_common import (
Batch,
BatchStatus,
CancelByBatchIDsResult,
CancelByOriginResult,
ClearResult,
EnqueueBatchResult,
PruneResult,
@ -106,19 +105,6 @@ async def cancel_by_batch_ids(
return ApiDependencies.invoker.services.session_queue.cancel_by_batch_ids(queue_id=queue_id, batch_ids=batch_ids)
@session_queue_router.put(
"/{queue_id}/cancel_by_origin",
operation_id="cancel_by_origin",
responses={200: {"model": CancelByBatchIDsResult}},
)
async def cancel_by_origin(
queue_id: str = Path(description="The queue id to perform this operation on"),
origin: str = Query(description="The origin to cancel all queue items for"),
) -> CancelByOriginResult:
"""Immediately cancels all queue items with the given origin"""
return ApiDependencies.invoker.services.session_queue.cancel_by_origin(queue_id=queue_id, origin=origin)
@session_queue_router.put(
"/{queue_id}/clear",
operation_id="clear",

View File

@ -13,7 +13,6 @@ from invokeai.app.invocations.fields import (
)
from invokeai.app.invocations.model import TransformerField, VAEField
from invokeai.app.invocations.primitives import ImageOutput
from invokeai.app.services.session_processor.session_processor_common import CanceledException
from invokeai.app.services.shared.invocation_context import InvocationContext
from invokeai.backend.flux.model import Flux
from invokeai.backend.flux.modules.autoencoder import AutoEncoder
@ -109,35 +108,6 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
with transformer_info as transformer:
assert isinstance(transformer, Flux)
def step_callback() -> None:
if context.util.is_canceled():
raise CanceledException
# TODO: Make this look like the image before re-enabling
# latent_image = unpack(img.float(), self.height, self.width)
# latent_image = latent_image.squeeze() # Remove unnecessary dimensions
# flattened_tensor = latent_image.reshape(-1) # Flatten to shape [48*128*128]
# # Create a new tensor of the required shape [255, 255, 3]
# latent_image = flattened_tensor[: 255 * 255 * 3].reshape(255, 255, 3) # Reshape to RGB format
# # Convert to a NumPy array and then to a PIL Image
# image = Image.fromarray(latent_image.cpu().numpy().astype(np.uint8))
# (width, height) = image.size
# width *= 8
# height *= 8
# dataURL = image_to_dataURL(image, image_format="JPEG")
# # TODO: move this whole function to invocation context to properly reference these variables
# context._services.events.emit_invocation_denoise_progress(
# context._data.queue_item,
# context._data.invocation,
# state,
# ProgressImage(dataURL=dataURL, width=width, height=height),
# )
x = denoise(
model=transformer,
img=img,
@ -146,7 +116,6 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
txt_ids=txt_ids,
vec=clip_embeddings,
timesteps=timesteps,
step_callback=step_callback,
guidance=self.guidance,
)

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@ -6,19 +6,13 @@ import cv2
import numpy
from PIL import Image, ImageChops, ImageFilter, ImageOps
from invokeai.app.invocations.baseinvocation import (
BaseInvocation,
Classification,
invocation,
invocation_output,
)
from invokeai.app.invocations.baseinvocation import BaseInvocation, Classification, invocation
from invokeai.app.invocations.constants import IMAGE_MODES
from invokeai.app.invocations.fields import (
ColorField,
FieldDescriptions,
ImageField,
InputField,
OutputField,
WithBoard,
WithMetadata,
)
@ -1013,62 +1007,3 @@ class MaskFromIDInvocation(BaseInvocation, WithMetadata, WithBoard):
image_dto = context.images.save(image=mask, image_category=ImageCategory.MASK)
return ImageOutput.build(image_dto)
@invocation_output("canvas_v2_mask_and_crop_output")
class CanvasV2MaskAndCropOutput(ImageOutput):
offset_x: int = OutputField(description="The x offset of the image, after cropping")
offset_y: int = OutputField(description="The y offset of the image, after cropping")
@invocation(
"canvas_v2_mask_and_crop",
title="Canvas V2 Mask and Crop",
tags=["image", "mask", "id"],
category="image",
version="1.0.0",
classification=Classification.Prototype,
)
class CanvasV2MaskAndCropInvocation(BaseInvocation, WithMetadata, WithBoard):
"""Handles Canvas V2 image output masking and cropping"""
source_image: ImageField | None = InputField(
default=None,
description="The source image onto which the masked generated image is pasted. If omitted, the masked generated image is returned with transparency.",
)
generated_image: ImageField = InputField(description="The image to apply the mask to")
mask: ImageField = InputField(description="The mask to apply")
mask_blur: int = InputField(default=0, ge=0, description="The amount to blur the mask by")
def _prepare_mask(self, mask: Image.Image) -> Image.Image:
mask_array = numpy.array(mask)
kernel = numpy.ones((self.mask_blur, self.mask_blur), numpy.uint8)
dilated_mask_array = cv2.erode(mask_array, kernel, iterations=3)
dilated_mask = Image.fromarray(dilated_mask_array)
if self.mask_blur > 0:
mask = dilated_mask.filter(ImageFilter.GaussianBlur(self.mask_blur))
return ImageOps.invert(mask.convert("L"))
def invoke(self, context: InvocationContext) -> CanvasV2MaskAndCropOutput:
mask = self._prepare_mask(context.images.get_pil(self.mask.image_name))
if self.source_image:
generated_image = context.images.get_pil(self.generated_image.image_name)
source_image = context.images.get_pil(self.source_image.image_name)
source_image.paste(generated_image, (0, 0), mask)
image_dto = context.images.save(image=source_image)
else:
generated_image = context.images.get_pil(self.generated_image.image_name)
generated_image.putalpha(mask)
image_dto = context.images.save(image=generated_image)
# bbox = image.getbbox()
# image = image.crop(bbox)
return CanvasV2MaskAndCropOutput(
image=ImageField(image_name=image_dto.image_name),
offset_x=0,
offset_y=0,
width=image_dto.width,
height=image_dto.height,
)

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@ -1,6 +1,7 @@
import copy
from typing import List, Literal, Optional
import yaml
from pydantic import BaseModel, Field
from invokeai.app.invocations.baseinvocation import (
@ -13,7 +14,6 @@ from invokeai.app.invocations.baseinvocation import (
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, OutputField, UIType
from invokeai.app.services.shared.invocation_context import InvocationContext
from invokeai.app.shared.models import FreeUConfig
from invokeai.backend.flux.util import max_seq_lengths
from invokeai.backend.model_manager.config import (
AnyModelConfig,
BaseModelType,
@ -188,13 +188,17 @@ class FluxModelLoaderInvocation(BaseInvocation):
vae = self._get_model(context, SubModelType.VAE)
transformer_config = context.models.get_config(transformer)
assert isinstance(transformer_config, CheckpointConfigBase)
legacy_config_path = context.config.get().legacy_conf_path / transformer_config.config_path
config_path = legacy_config_path.as_posix()
with open(config_path, "r") as stream:
flux_conf = yaml.safe_load(stream)
return FluxModelLoaderOutput(
transformer=TransformerField(transformer=transformer),
clip=CLIPField(tokenizer=tokenizer, text_encoder=clip_encoder, loras=[], skipped_layers=0),
t5_encoder=T5EncoderField(tokenizer=tokenizer2, text_encoder=t5_encoder),
vae=VAEField(vae=vae),
max_seq_len=max_seq_lengths[transformer_config.config_path],
max_seq_len=flux_conf["max_seq_len"],
)
def _get_model(self, context: InvocationContext, submodel: SubModelType) -> ModelIdentifierField:

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@ -88,7 +88,6 @@ class QueueItemEventBase(QueueEventBase):
item_id: int = Field(description="The ID of the queue item")
batch_id: str = Field(description="The ID of the queue batch")
origin: str | None = Field(default=None, description="The origin of the batch")
class InvocationEventBase(QueueItemEventBase):
@ -96,6 +95,8 @@ class InvocationEventBase(QueueItemEventBase):
session_id: str = Field(description="The ID of the session (aka graph execution state)")
queue_id: str = Field(description="The ID of the queue")
item_id: int = Field(description="The ID of the queue item")
batch_id: str = Field(description="The ID of the queue batch")
session_id: str = Field(description="The ID of the session (aka graph execution state)")
invocation: AnyInvocation = Field(description="The ID of the invocation")
invocation_source_id: str = Field(description="The ID of the prepared invocation's source node")
@ -113,7 +114,6 @@ class InvocationStartedEvent(InvocationEventBase):
queue_id=queue_item.queue_id,
item_id=queue_item.item_id,
batch_id=queue_item.batch_id,
origin=queue_item.origin,
session_id=queue_item.session_id,
invocation=invocation,
invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
@ -147,7 +147,6 @@ class InvocationDenoiseProgressEvent(InvocationEventBase):
queue_id=queue_item.queue_id,
item_id=queue_item.item_id,
batch_id=queue_item.batch_id,
origin=queue_item.origin,
session_id=queue_item.session_id,
invocation=invocation,
invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
@ -185,7 +184,6 @@ class InvocationCompleteEvent(InvocationEventBase):
queue_id=queue_item.queue_id,
item_id=queue_item.item_id,
batch_id=queue_item.batch_id,
origin=queue_item.origin,
session_id=queue_item.session_id,
invocation=invocation,
invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
@ -218,7 +216,6 @@ class InvocationErrorEvent(InvocationEventBase):
queue_id=queue_item.queue_id,
item_id=queue_item.item_id,
batch_id=queue_item.batch_id,
origin=queue_item.origin,
session_id=queue_item.session_id,
invocation=invocation,
invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
@ -256,7 +253,6 @@ class QueueItemStatusChangedEvent(QueueItemEventBase):
queue_id=queue_item.queue_id,
item_id=queue_item.item_id,
batch_id=queue_item.batch_id,
origin=queue_item.origin,
session_id=queue_item.session_id,
status=queue_item.status,
error_type=queue_item.error_type,
@ -283,14 +279,12 @@ class BatchEnqueuedEvent(QueueEventBase):
description="The number of invocations initially requested to be enqueued (may be less than enqueued if queue was full)"
)
priority: int = Field(description="The priority of the batch")
origin: str | None = Field(default=None, description="The origin of the batch")
@classmethod
def build(cls, enqueue_result: EnqueueBatchResult) -> "BatchEnqueuedEvent":
return cls(
queue_id=enqueue_result.queue_id,
batch_id=enqueue_result.batch.batch_id,
origin=enqueue_result.batch.origin,
enqueued=enqueue_result.enqueued,
requested=enqueue_result.requested,
priority=enqueue_result.priority,

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@ -6,7 +6,6 @@ from invokeai.app.services.session_queue.session_queue_common import (
Batch,
BatchStatus,
CancelByBatchIDsResult,
CancelByOriginResult,
CancelByQueueIDResult,
ClearResult,
EnqueueBatchResult,
@ -96,11 +95,6 @@ class SessionQueueBase(ABC):
"""Cancels all queue items with matching batch IDs"""
pass
@abstractmethod
def cancel_by_origin(self, queue_id: str, origin: str) -> CancelByOriginResult:
"""Cancels all queue items with the given batch origin"""
pass
@abstractmethod
def cancel_by_queue_id(self, queue_id: str) -> CancelByQueueIDResult:
"""Cancels all queue items with matching queue ID"""

View File

@ -77,7 +77,6 @@ BatchDataCollection: TypeAlias = list[list[BatchDatum]]
class Batch(BaseModel):
batch_id: str = Field(default_factory=uuid_string, description="The ID of the batch")
origin: str | None = Field(default=None, description="The origin of this batch.")
data: Optional[BatchDataCollection] = Field(default=None, description="The batch data collection.")
graph: Graph = Field(description="The graph to initialize the session with")
workflow: Optional[WorkflowWithoutID] = Field(
@ -196,7 +195,6 @@ class SessionQueueItemWithoutGraph(BaseModel):
status: QUEUE_ITEM_STATUS = Field(default="pending", description="The status of this queue item")
priority: int = Field(default=0, description="The priority of this queue item")
batch_id: str = Field(description="The ID of the batch associated with this queue item")
origin: str | None = Field(default=None, description="The origin of this queue item. ")
session_id: str = Field(
description="The ID of the session associated with this queue item. The session doesn't exist in graph_executions until the queue item is executed."
)
@ -296,7 +294,6 @@ class SessionQueueStatus(BaseModel):
class BatchStatus(BaseModel):
queue_id: str = Field(..., description="The ID of the queue")
batch_id: str = Field(..., description="The ID of the batch")
origin: str | None = Field(..., description="The origin of the batch")
pending: int = Field(..., description="Number of queue items with status 'pending'")
in_progress: int = Field(..., description="Number of queue items with status 'in_progress'")
completed: int = Field(..., description="Number of queue items with status 'complete'")
@ -331,12 +328,6 @@ class CancelByBatchIDsResult(BaseModel):
canceled: int = Field(..., description="Number of queue items canceled")
class CancelByOriginResult(BaseModel):
"""Result of canceling by list of batch ids"""
canceled: int = Field(..., description="Number of queue items canceled")
class CancelByQueueIDResult(CancelByBatchIDsResult):
"""Result of canceling by queue id"""
@ -442,7 +433,6 @@ class SessionQueueValueToInsert(NamedTuple):
field_values: Optional[str] # field_values json
priority: int # priority
workflow: Optional[str] # workflow json
origin: str | None
ValuesToInsert: TypeAlias = list[SessionQueueValueToInsert]
@ -463,7 +453,6 @@ def prepare_values_to_insert(queue_id: str, batch: Batch, priority: int, max_new
json.dumps(field_values, default=to_jsonable_python) if field_values else None, # field_values (json)
priority, # priority
json.dumps(workflow, default=to_jsonable_python) if workflow else None, # workflow (json)
batch.origin, # origin
)
)
return values_to_insert

View File

@ -10,7 +10,6 @@ from invokeai.app.services.session_queue.session_queue_common import (
Batch,
BatchStatus,
CancelByBatchIDsResult,
CancelByOriginResult,
CancelByQueueIDResult,
ClearResult,
EnqueueBatchResult,
@ -128,8 +127,8 @@ class SqliteSessionQueue(SessionQueueBase):
self.__cursor.executemany(
"""--sql
INSERT INTO session_queue (queue_id, session, session_id, batch_id, field_values, priority, workflow, origin)
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
INSERT INTO session_queue (queue_id, session, session_id, batch_id, field_values, priority, workflow)
VALUES (?, ?, ?, ?, ?, ?, ?)
""",
values_to_insert,
)
@ -418,7 +417,11 @@ class SqliteSessionQueue(SessionQueueBase):
)
self.__conn.commit()
if current_queue_item is not None and current_queue_item.batch_id in batch_ids:
self._set_queue_item_status(current_queue_item.item_id, "canceled")
batch_status = self.get_batch_status(queue_id=queue_id, batch_id=current_queue_item.batch_id)
queue_status = self.get_queue_status(queue_id=queue_id)
self.__invoker.services.events.emit_queue_item_status_changed(
current_queue_item, batch_status, queue_status
)
except Exception:
self.__conn.rollback()
raise
@ -426,46 +429,6 @@ class SqliteSessionQueue(SessionQueueBase):
self.__lock.release()
return CancelByBatchIDsResult(canceled=count)
def cancel_by_origin(self, queue_id: str, origin: str) -> CancelByOriginResult:
try:
current_queue_item = self.get_current(queue_id)
self.__lock.acquire()
where = """--sql
WHERE
queue_id == ?
AND origin == ?
AND status != 'canceled'
AND status != 'completed'
AND status != 'failed'
"""
params = (queue_id, origin)
self.__cursor.execute(
f"""--sql
SELECT COUNT(*)
FROM session_queue
{where};
""",
params,
)
count = self.__cursor.fetchone()[0]
self.__cursor.execute(
f"""--sql
UPDATE session_queue
SET status = 'canceled'
{where};
""",
params,
)
self.__conn.commit()
if current_queue_item is not None and current_queue_item.origin == origin:
self._set_queue_item_status(current_queue_item.item_id, "canceled")
except Exception:
self.__conn.rollback()
raise
finally:
self.__lock.release()
return CancelByOriginResult(canceled=count)
def cancel_by_queue_id(self, queue_id: str) -> CancelByQueueIDResult:
try:
current_queue_item = self.get_current(queue_id)
@ -578,8 +541,7 @@ class SqliteSessionQueue(SessionQueueBase):
started_at,
session_id,
batch_id,
queue_id,
origin
queue_id
FROM session_queue
WHERE queue_id = ?
"""
@ -659,7 +621,7 @@ class SqliteSessionQueue(SessionQueueBase):
self.__lock.acquire()
self.__cursor.execute(
"""--sql
SELECT status, count(*), origin
SELECT status, count(*)
FROM session_queue
WHERE
queue_id = ?
@ -671,7 +633,6 @@ class SqliteSessionQueue(SessionQueueBase):
result = cast(list[sqlite3.Row], self.__cursor.fetchall())
total = sum(row[1] for row in result)
counts: dict[str, int] = {row[0]: row[1] for row in result}
origin = result[0]["origin"] if result else None
except Exception:
self.__conn.rollback()
raise
@ -680,7 +641,6 @@ class SqliteSessionQueue(SessionQueueBase):
return BatchStatus(
batch_id=batch_id,
origin=origin,
queue_id=queue_id,
pending=counts.get("pending", 0),
in_progress=counts.get("in_progress", 0),

View File

@ -17,7 +17,6 @@ from invokeai.app.services.shared.sqlite_migrator.migrations.migration_11 import
from invokeai.app.services.shared.sqlite_migrator.migrations.migration_12 import build_migration_12
from invokeai.app.services.shared.sqlite_migrator.migrations.migration_13 import build_migration_13
from invokeai.app.services.shared.sqlite_migrator.migrations.migration_14 import build_migration_14
from invokeai.app.services.shared.sqlite_migrator.migrations.migration_15 import build_migration_15
from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_impl import SqliteMigrator
@ -52,7 +51,6 @@ def init_db(config: InvokeAIAppConfig, logger: Logger, image_files: ImageFileSto
migrator.register_migration(build_migration_12(app_config=config))
migrator.register_migration(build_migration_13())
migrator.register_migration(build_migration_14())
migrator.register_migration(build_migration_15())
migrator.run_migrations()
return db

View File

@ -1,31 +0,0 @@
import sqlite3
from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
class Migration15Callback:
def __call__(self, cursor: sqlite3.Cursor) -> None:
self._add_origin_col(cursor)
def _add_origin_col(self, cursor: sqlite3.Cursor) -> None:
"""
- Adds `origin` column to the session queue table.
"""
cursor.execute("ALTER TABLE session_queue ADD COLUMN origin TEXT;")
def build_migration_15() -> Migration:
"""
Build the migration from database version 14 to 15.
This migration does the following:
- Adds `origin` column to the session queue table.
"""
migration_15 = Migration(
from_version=14,
to_version=15,
callback=Migration15Callback(),
)
return migration_15

View File

@ -1,81 +1,35 @@
{
"name": "FLUX Text to Image",
"author": "InvokeAI",
"description": "A simple text-to-image workflow using FLUX dev or schnell models. Prerequisite model downloads: T5 Encoder, CLIP-L Encoder, and FLUX VAE. Quantized and un-quantized versions can be found in the starter models tab within your Model Manager. We recommend 4 steps for FLUX schnell models and 30 steps for FLUX dev models.",
"description": "A simple text-to-image workflow using FLUX dev or schnell models. Prerequisite model downloads: T5 Encoder, CLIP-L Encoder, and FLUX VAE. These can be found in the starter models tab within your Model Manager.",
"version": "1.0.0",
"contact": "",
"tags": "text2image, flux",
"notes": "Prerequisite model downloads: T5 Encoder, CLIP-L Encoder, and FLUX VAE. Quantized and un-quantized versions can be found in the starter models tab within your Model Manager. We recommend 4 steps for FLUX schnell models and 30 steps for FLUX dev models.",
"notes": "",
"exposedFields": [
{
"nodeId": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
"nodeId": "fd1274a3-c56d-4a96-aa21-83d14c920f08",
"fieldName": "model"
},
{
"nodeId": "01f674f8-b3d1-4df1-acac-6cb8e0bfb63c",
"fieldName": "prompt"
},
{
"nodeId": "159bdf1b-79e7-4174-b86e-d40e646964c8",
"fieldName": "num_steps"
},
{
"nodeId": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
"nodeId": "fd1274a3-c56d-4a96-aa21-83d14c920f08",
"fieldName": "t5_encoder"
},
{
"nodeId": "0fa90f47-79cd-4d84-9445-f0b1065e0c3c",
"fieldName": "positive_prompt"
}
],
"meta": {
"version": "3.0.0",
"category": "default"
},
"nodes": [
"nodes": [
{
"id": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
"id": "0fa90f47-79cd-4d84-9445-f0b1065e0c3c",
"type": "invocation",
"data": {
"id": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
"type": "flux_model_loader",
"version": "1.0.3",
"label": "",
"notes": "",
"isOpen": true,
"isIntermediate": true,
"useCache": false,
"inputs": {
"model": {
"name": "model",
"label": "Model (Starter Models can be found in Model Manager)",
"value": {
"key": "f04a7a2f-c74d-4538-8d5e-879a53501662",
"hash": "random:4875da7a9508444ffa706f61961c260d0c6729f6181a86b31fad06df1277b850",
"name": "FLUX Dev (Quantized)",
"base": "flux",
"type": "main"
}
},
"t5_encoder": {
"name": "t5_encoder",
"label": "T 5 Encoder (Starter Models can be found in Model Manager)",
"value": {
"key": "20dcd9ec-5fbb-4012-8401-049e707da5e5",
"hash": "random:f986be43ff3502169e4adbdcee158afb0e0a65a1edc4cab16ae59963630cfd8f",
"name": "t5_bnb_int8_quantized_encoder",
"base": "any",
"type": "t5_encoder"
}
}
}
},
"position": {
"x": 337.09365228062825,
"y": 40.63469521079861
}
},
{
"id": "01f674f8-b3d1-4df1-acac-6cb8e0bfb63c",
"type": "invocation",
"data": {
"id": "01f674f8-b3d1-4df1-acac-6cb8e0bfb63c",
"id": "0fa90f47-79cd-4d84-9445-f0b1065e0c3c",
"type": "flux_text_encoder",
"version": "1.0.0",
"label": "",
@ -94,19 +48,61 @@
},
"t5_max_seq_len": {
"name": "t5_max_seq_len",
"label": "T5 Max Seq Len",
"label": "",
"value": 256
},
"prompt": {
"name": "prompt",
"positive_prompt": {
"name": "positive_prompt",
"label": "",
"value": "a cat"
"value": ""
}
}
},
"position": {
"x": 824.1970602278849,
"y": 146.98251001061735
"x": 817.9049777916891,
"y": 137.19130248771572
}
},
{
"id": "fd1274a3-c56d-4a96-aa21-83d14c920f08",
"type": "invocation",
"data": {
"id": "fd1274a3-c56d-4a96-aa21-83d14c920f08",
"type": "flux_model_loader",
"version": "1.0.3",
"label": "",
"notes": "",
"isOpen": true,
"isIntermediate": true,
"useCache": true,
"inputs": {
"model": {
"name": "model",
"label": "",
"value": {
"key": "a1deb125-2781-482c-8a71-9a22e76fd956",
"hash": "random:40bd0a5b8b2c6edf8f5611e049000329b952efc6a1a24b4f77ca4ae3dbecaf6a",
"name": "flux1-schnell-bnb_nf4",
"base": "flux",
"type": "main"
}
},
"t5_encoder": {
"name": "t5_encoder",
"label": "T5 Encoder (Model Manager -> Starter Models)",
"value": {
"key": "798baafd-63bd-4799-8600-5db43662f3aa",
"hash": "random:4495f3ac1650e9d5969c365e951a9cffee526573a15f9f4c997e1c63550444fd",
"name": "t5_8b_quantized_encoder",
"base": "any",
"type": "t5_encoder"
}
}
}
},
"position": {
"x": 343.41871407356723,
"y": -1.0211223664301414
}
},
{
@ -150,7 +146,7 @@
"notes": "",
"isOpen": true,
"isIntermediate": false,
"useCache": true,
"useCache": false,
"inputs": {
"board": {
"name": "board",
@ -184,8 +180,8 @@
},
"num_steps": {
"name": "num_steps",
"label": "Steps (Recommend 30 for Dev, 4 for Schnell)",
"value": 30
"label": "",
"value": 4
},
"guidance": {
"name": "guidance",
@ -207,53 +203,53 @@
],
"edges": [
{
"id": "reactflow__edge-4f0207c2-ff40-41fd-b047-ad33fbb1c33amax_seq_len-01f674f8-b3d1-4df1-acac-6cb8e0bfb63ct5_max_seq_len",
"id": "reactflow__edge-0fa90f47-79cd-4d84-9445-f0b1065e0c3cconditioning-159bdf1b-79e7-4174-b86e-d40e646964c8positive_text_conditioning",
"type": "default",
"source": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
"target": "01f674f8-b3d1-4df1-acac-6cb8e0bfb63c",
"source": "0fa90f47-79cd-4d84-9445-f0b1065e0c3c",
"target": "159bdf1b-79e7-4174-b86e-d40e646964c8",
"sourceHandle": "conditioning",
"targetHandle": "positive_text_conditioning"
},
{
"id": "reactflow__edge-fd1274a3-c56d-4a96-aa21-83d14c920f08max_seq_len-0fa90f47-79cd-4d84-9445-f0b1065e0c3ct5_max_seq_len",
"type": "default",
"source": "fd1274a3-c56d-4a96-aa21-83d14c920f08",
"target": "0fa90f47-79cd-4d84-9445-f0b1065e0c3c",
"sourceHandle": "max_seq_len",
"targetHandle": "t5_max_seq_len"
},
{
"id": "reactflow__edge-4f0207c2-ff40-41fd-b047-ad33fbb1c33avae-159bdf1b-79e7-4174-b86e-d40e646964c8vae",
"id": "reactflow__edge-fd1274a3-c56d-4a96-aa21-83d14c920f08t5_encoder-0fa90f47-79cd-4d84-9445-f0b1065e0c3ct5_encoder",
"type": "default",
"source": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
"source": "fd1274a3-c56d-4a96-aa21-83d14c920f08",
"target": "0fa90f47-79cd-4d84-9445-f0b1065e0c3c",
"sourceHandle": "t5_encoder",
"targetHandle": "t5_encoder"
},
{
"id": "reactflow__edge-fd1274a3-c56d-4a96-aa21-83d14c920f08clip-0fa90f47-79cd-4d84-9445-f0b1065e0c3cclip",
"type": "default",
"source": "fd1274a3-c56d-4a96-aa21-83d14c920f08",
"target": "0fa90f47-79cd-4d84-9445-f0b1065e0c3c",
"sourceHandle": "clip",
"targetHandle": "clip"
},
{
"id": "reactflow__edge-fd1274a3-c56d-4a96-aa21-83d14c920f08vae-159bdf1b-79e7-4174-b86e-d40e646964c8vae",
"type": "default",
"source": "fd1274a3-c56d-4a96-aa21-83d14c920f08",
"target": "159bdf1b-79e7-4174-b86e-d40e646964c8",
"sourceHandle": "vae",
"targetHandle": "vae"
},
{
"id": "reactflow__edge-4f0207c2-ff40-41fd-b047-ad33fbb1c33atransformer-159bdf1b-79e7-4174-b86e-d40e646964c8transformer",
"id": "reactflow__edge-fd1274a3-c56d-4a96-aa21-83d14c920f08transformer-159bdf1b-79e7-4174-b86e-d40e646964c8transformer",
"type": "default",
"source": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
"source": "fd1274a3-c56d-4a96-aa21-83d14c920f08",
"target": "159bdf1b-79e7-4174-b86e-d40e646964c8",
"sourceHandle": "transformer",
"targetHandle": "transformer"
},
{
"id": "reactflow__edge-4f0207c2-ff40-41fd-b047-ad33fbb1c33at5_encoder-01f674f8-b3d1-4df1-acac-6cb8e0bfb63ct5_encoder",
"type": "default",
"source": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
"target": "01f674f8-b3d1-4df1-acac-6cb8e0bfb63c",
"sourceHandle": "t5_encoder",
"targetHandle": "t5_encoder"
},
{
"id": "reactflow__edge-4f0207c2-ff40-41fd-b047-ad33fbb1c33aclip-01f674f8-b3d1-4df1-acac-6cb8e0bfb63cclip",
"type": "default",
"source": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
"target": "01f674f8-b3d1-4df1-acac-6cb8e0bfb63c",
"sourceHandle": "clip",
"targetHandle": "clip"
},
{
"id": "reactflow__edge-01f674f8-b3d1-4df1-acac-6cb8e0bfb63cconditioning-159bdf1b-79e7-4174-b86e-d40e646964c8positive_text_conditioning",
"type": "default",
"source": "01f674f8-b3d1-4df1-acac-6cb8e0bfb63c",
"target": "159bdf1b-79e7-4174-b86e-d40e646964c8",
"sourceHandle": "conditioning",
"targetHandle": "positive_text_conditioning"
},
{
"id": "reactflow__edge-4754c534-a5f3-4ad0-9382-7887985e668cvalue-159bdf1b-79e7-4174-b86e-d40e646964c8seed",
"type": "default",

View File

@ -20,6 +20,10 @@ class AutoEncoderParams:
shift_factor: float
def swish(x: Tensor) -> Tensor:
return x * torch.sigmoid(x)
class AttnBlock(nn.Module):
def __init__(self, in_channels: int):
super().__init__()
@ -67,11 +71,11 @@ class ResnetBlock(nn.Module):
def forward(self, x):
h = x
h = self.norm1(h)
h = torch.nn.functional.silu(h)
h = swish(h)
h = self.conv1(h)
h = self.norm2(h)
h = torch.nn.functional.silu(h)
h = swish(h)
h = self.conv2(h)
if self.in_channels != self.out_channels:
@ -173,7 +177,7 @@ class Encoder(nn.Module):
h = self.mid.block_2(h)
# end
h = self.norm_out(h)
h = torch.nn.functional.silu(h)
h = swish(h)
h = self.conv_out(h)
return h
@ -252,7 +256,7 @@ class Decoder(nn.Module):
# end
h = self.norm_out(h)
h = torch.nn.functional.silu(h)
h = swish(h)
h = self.conv_out(h)
return h

View File

@ -108,7 +108,6 @@ def denoise(
vec: Tensor,
# sampling parameters
timesteps: list[float],
step_callback: Callable[[], None],
guidance: float = 4.0,
):
dtype = model.txt_in.bias.dtype
@ -135,7 +134,6 @@ def denoise(
)
img = img + (t_prev - t_curr) * pred
step_callback()
return img

View File

@ -1,71 +0,0 @@
# Initially pulled from https://github.com/black-forest-labs/flux
from dataclasses import dataclass
from typing import Dict, Literal
from invokeai.backend.flux.model import FluxParams
from invokeai.backend.flux.modules.autoencoder import AutoEncoderParams
@dataclass
class ModelSpec:
params: FluxParams
ae_params: AutoEncoderParams
ckpt_path: str | None
ae_path: str | None
repo_id: str | None
repo_flow: str | None
repo_ae: str | None
max_seq_lengths: Dict[str, Literal[256, 512]] = {
"flux-dev": 512,
"flux-schnell": 256,
}
ae_params = {
"flux": AutoEncoderParams(
resolution=256,
in_channels=3,
ch=128,
out_ch=3,
ch_mult=[1, 2, 4, 4],
num_res_blocks=2,
z_channels=16,
scale_factor=0.3611,
shift_factor=0.1159,
)
}
params = {
"flux-dev": FluxParams(
in_channels=64,
vec_in_dim=768,
context_in_dim=4096,
hidden_size=3072,
mlp_ratio=4.0,
num_heads=24,
depth=19,
depth_single_blocks=38,
axes_dim=[16, 56, 56],
theta=10_000,
qkv_bias=True,
guidance_embed=True,
),
"flux-schnell": FluxParams(
in_channels=64,
vec_in_dim=768,
context_in_dim=4096,
hidden_size=3072,
mlp_ratio=4.0,
num_heads=24,
depth=19,
depth_single_blocks=38,
axes_dim=[16, 56, 56],
theta=10_000,
qkv_bias=True,
guidance_embed=False,
),
}

View File

@ -109,7 +109,8 @@ class ModelFormat(str, Enum):
EmbeddingFolder = "embedding_folder"
InvokeAI = "invokeai"
T5Encoder = "t5_encoder"
BnbQuantizedLlmInt8b = "bnb_quantized_int8b"
T5Encoder8b = "t5_encoder_8b"
T5Encoder4b = "t5_encoder_4b"
BnbQuantizednf4b = "bnb_quantized_nf4b"
@ -226,12 +227,12 @@ class T5EncoderConfig(T5EncoderConfigBase):
return Tag(f"{ModelType.T5Encoder.value}.{ModelFormat.T5Encoder.value}")
class T5EncoderBnbQuantizedLlmInt8bConfig(T5EncoderConfigBase):
format: Literal[ModelFormat.BnbQuantizedLlmInt8b] = ModelFormat.BnbQuantizedLlmInt8b
class T5Encoder8bConfig(T5EncoderConfigBase):
format: Literal[ModelFormat.T5Encoder8b] = ModelFormat.T5Encoder8b
@staticmethod
def get_tag() -> Tag:
return Tag(f"{ModelType.T5Encoder.value}.{ModelFormat.BnbQuantizedLlmInt8b.value}")
return Tag(f"{ModelType.T5Encoder.value}.{ModelFormat.T5Encoder8b.value}")
class LoRALyCORISConfig(LoRAConfigBase):
@ -469,7 +470,7 @@ AnyModelConfig = Annotated[
Annotated[LoRALyCORISConfig, LoRALyCORISConfig.get_tag()],
Annotated[LoRADiffusersConfig, LoRADiffusersConfig.get_tag()],
Annotated[T5EncoderConfig, T5EncoderConfig.get_tag()],
Annotated[T5EncoderBnbQuantizedLlmInt8bConfig, T5EncoderBnbQuantizedLlmInt8bConfig.get_tag()],
Annotated[T5Encoder8bConfig, T5Encoder8bConfig.get_tag()],
Annotated[TextualInversionFileConfig, TextualInversionFileConfig.get_tag()],
Annotated[TextualInversionFolderConfig, TextualInversionFolderConfig.get_tag()],
Annotated[IPAdapterInvokeAIConfig, IPAdapterInvokeAIConfig.get_tag()],

View File

@ -1,18 +1,19 @@
# Copyright (c) 2024, Brandon W. Rising and the InvokeAI Development Team
"""Class for Flux model loading in InvokeAI."""
from dataclasses import fields
from pathlib import Path
from typing import Optional
from typing import Any, Optional
import accelerate
import torch
import yaml
from safetensors.torch import load_file
from transformers import AutoConfig, AutoModelForTextEncoding, CLIPTextModel, CLIPTokenizer, T5EncoderModel, T5Tokenizer
from invokeai.app.services.config.config_default import get_config
from invokeai.backend.flux.model import Flux
from invokeai.backend.flux.modules.autoencoder import AutoEncoder
from invokeai.backend.flux.util import ae_params, params
from invokeai.backend.flux.model import Flux, FluxParams
from invokeai.backend.flux.modules.autoencoder import AutoEncoder, AutoEncoderParams
from invokeai.backend.model_manager import (
AnyModel,
AnyModelConfig,
@ -26,21 +27,22 @@ from invokeai.backend.model_manager.config import (
CLIPEmbedDiffusersConfig,
MainBnbQuantized4bCheckpointConfig,
MainCheckpointConfig,
T5EncoderBnbQuantizedLlmInt8bConfig,
T5Encoder8bConfig,
T5EncoderConfig,
VAECheckpointConfig,
)
from invokeai.backend.model_manager.load.load_default import ModelLoader
from invokeai.backend.model_manager.load.model_loader_registry import ModelLoaderRegistry
from invokeai.backend.quantization.bnb_llm_int8 import quantize_model_llm_int8
from invokeai.backend.quantization.bnb_nf4 import quantize_model_nf4
from invokeai.backend.util.silence_warnings import SilenceWarnings
try:
from invokeai.backend.quantization.bnb_llm_int8 import quantize_model_llm_int8
from invokeai.backend.quantization.bnb_nf4 import quantize_model_nf4
bnb_available = True
bnb_nf4_available = True
except ImportError:
bnb_available = False
bnb_nf4_available = False
app_config = get_config()
@ -57,9 +59,17 @@ class FluxVAELoader(ModelLoader):
if not isinstance(config, VAECheckpointConfig):
raise ValueError("Only VAECheckpointConfig models are currently supported here.")
model_path = Path(config.path)
legacy_config_path = app_config.legacy_conf_path / config.config_path
config_path = legacy_config_path.as_posix()
with open(config_path, "r") as stream:
flux_conf = yaml.safe_load(stream)
dataclass_fields = {f.name for f in fields(AutoEncoderParams)}
filtered_data = {k: v for k, v in flux_conf["params"].items() if k in dataclass_fields}
params = AutoEncoderParams(**filtered_data)
with SilenceWarnings():
model = AutoEncoder(ae_params[config.config_path])
model = AutoEncoder(params)
sd = load_file(model_path)
model.load_state_dict(sd, assign=True)
model.to(dtype=self._torch_dtype)
@ -81,17 +91,17 @@ class ClipCheckpointModel(ModelLoader):
match submodel_type:
case SubModelType.Tokenizer:
return CLIPTokenizer.from_pretrained(Path(config.path) / "tokenizer")
return CLIPTokenizer.from_pretrained(config.path)
case SubModelType.TextEncoder:
return CLIPTextModel.from_pretrained(Path(config.path) / "text_encoder")
return CLIPTextModel.from_pretrained(config.path)
raise ValueError(
f"Only Tokenizer and TextEncoder submodels are currently supported. Received: {submodel_type.value if submodel_type else 'None'}"
)
@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.T5Encoder, format=ModelFormat.BnbQuantizedLlmInt8b)
class BnbQuantizedLlmInt8bCheckpointModel(ModelLoader):
@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.T5Encoder, format=ModelFormat.T5Encoder8b)
class T5Encoder8bCheckpointModel(ModelLoader):
"""Class to load main models."""
def _load_model(
@ -99,12 +109,9 @@ class BnbQuantizedLlmInt8bCheckpointModel(ModelLoader):
config: AnyModelConfig,
submodel_type: Optional[SubModelType] = None,
) -> AnyModel:
if not isinstance(config, T5EncoderBnbQuantizedLlmInt8bConfig):
raise ValueError("Only T5EncoderBnbQuantizedLlmInt8bConfig models are currently supported here.")
if not bnb_available:
raise ImportError(
"The bnb modules are not available. Please install bitsandbytes if available on your platform."
)
if not isinstance(config, T5Encoder8bConfig):
raise ValueError("Only T5Encoder8bConfig models are currently supported here.")
match submodel_type:
case SubModelType.Tokenizer2:
return T5Tokenizer.from_pretrained(Path(config.path) / "tokenizer_2", max_length=512)
@ -153,7 +160,9 @@ class T5EncoderCheckpointModel(ModelLoader):
case SubModelType.Tokenizer2:
return T5Tokenizer.from_pretrained(Path(config.path) / "tokenizer_2", max_length=512)
case SubModelType.TextEncoder2:
return T5EncoderModel.from_pretrained(Path(config.path) / "text_encoder_2")
return T5EncoderModel.from_pretrained(
Path(config.path) / "text_encoder_2"
) # TODO: Fix hf subfolder install
raise ValueError(
f"Only Tokenizer and TextEncoder submodels are currently supported. Received: {submodel_type.value if submodel_type else 'None'}"
@ -171,10 +180,14 @@ class FluxCheckpointModel(ModelLoader):
) -> AnyModel:
if not isinstance(config, CheckpointConfigBase):
raise ValueError("Only CheckpointConfigBase models are currently supported here.")
legacy_config_path = app_config.legacy_conf_path / config.config_path
config_path = legacy_config_path.as_posix()
with open(config_path, "r") as stream:
flux_conf = yaml.safe_load(stream)
match submodel_type:
case SubModelType.Transformer:
return self._load_from_singlefile(config)
return self._load_from_singlefile(config, flux_conf)
raise ValueError(
f"Only Transformer submodels are currently supported. Received: {submodel_type.value if submodel_type else 'None'}"
@ -183,12 +196,16 @@ class FluxCheckpointModel(ModelLoader):
def _load_from_singlefile(
self,
config: AnyModelConfig,
flux_conf: Any,
) -> AnyModel:
assert isinstance(config, MainCheckpointConfig)
model_path = Path(config.path)
dataclass_fields = {f.name for f in fields(FluxParams)}
filtered_data = {k: v for k, v in flux_conf["params"].items() if k in dataclass_fields}
params = FluxParams(**filtered_data)
with SilenceWarnings():
model = Flux(params[config.config_path])
model = Flux(params)
sd = load_file(model_path)
model.load_state_dict(sd, assign=True)
return model
@ -205,10 +222,14 @@ class FluxBnbQuantizednf4bCheckpointModel(ModelLoader):
) -> AnyModel:
if not isinstance(config, CheckpointConfigBase):
raise ValueError("Only CheckpointConfigBase models are currently supported here.")
legacy_config_path = app_config.legacy_conf_path / config.config_path
config_path = legacy_config_path.as_posix()
with open(config_path, "r") as stream:
flux_conf = yaml.safe_load(stream)
match submodel_type:
case SubModelType.Transformer:
return self._load_from_singlefile(config)
return self._load_from_singlefile(config, flux_conf)
raise ValueError(
f"Only Transformer submodels are currently supported. Received: {submodel_type.value if submodel_type else 'None'}"
@ -217,17 +238,21 @@ class FluxBnbQuantizednf4bCheckpointModel(ModelLoader):
def _load_from_singlefile(
self,
config: AnyModelConfig,
flux_conf: Any,
) -> AnyModel:
assert isinstance(config, MainBnbQuantized4bCheckpointConfig)
if not bnb_available:
if not bnb_nf4_available:
raise ImportError(
"The bnb modules are not available. Please install bitsandbytes if available on your platform."
"The bnb_nf4 module is not available. Please install bitsandbytes if available on your platform."
)
model_path = Path(config.path)
dataclass_fields = {f.name for f in fields(FluxParams)}
filtered_data = {k: v for k, v in flux_conf["params"].items() if k in dataclass_fields}
params = FluxParams(**filtered_data)
with SilenceWarnings():
with accelerate.init_empty_weights():
model = Flux(params[config.config_path])
model = Flux(params)
model = quantize_model_nf4(model, modules_to_not_convert=set(), compute_dtype=torch.bfloat16)
sd = load_file(model_path)
model.load_state_dict(sd, assign=True)

View File

@ -329,17 +329,9 @@ class ModelProbe(object):
checkpoint = ModelProbe._scan_and_load_checkpoint(model_path)
state_dict = checkpoint.get("state_dict") or checkpoint
if "guidance_in.out_layer.weight" in state_dict:
# For flux, this is a key in invokeai.backend.flux.util.params
# Due to model type and format being the descriminator for model configs this
# is used rather than attempting to support flux with separate model types and format
# If changed in the future, please fix me
config_file = "flux-dev"
config_file = "flux/flux1-dev.yaml"
else:
# For flux, this is a key in invokeai.backend.flux.util.params
# Due to model type and format being the descriminator for model configs this
# is used rather than attempting to support flux with separate model types and format
# If changed in the future, please fix me
config_file = "flux-schnell"
config_file = "flux/flux1-schnell.yaml"
else:
config_file = LEGACY_CONFIGS[base_type][variant_type]
if isinstance(config_file, dict): # need another tier for sd-2.x models
@ -353,11 +345,7 @@ class ModelProbe(object):
)
elif model_type is ModelType.VAE:
config_file = (
# For flux, this is a key in invokeai.backend.flux.util.ae_params
# Due to model type and format being the descriminator for model configs this
# is used rather than attempting to support flux with separate model types and format
# If changed in the future, please fix me
"flux"
"flux/flux1-vae.yaml"
if base_type is BaseModelType.Flux
else "stable-diffusion/v1-inference.yaml"
if base_type is BaseModelType.StableDiffusion1

View File

@ -66,14 +66,14 @@ t5_8b_quantized_encoder = StarterModel(
source="InvokeAI/t5-v1_1-xxl::bnb_llm_int8",
description="T5-XXL text encoder with bitsandbytes LLM.int8() quantization (used in FLUX pipelines). ~5GB",
type=ModelType.T5Encoder,
format=ModelFormat.BnbQuantizedLlmInt8b,
format=ModelFormat.T5Encoder8b,
)
clip_l_encoder = StarterModel(
name="clip-vit-large-patch14",
base=BaseModelType.Any,
source="InvokeAI/clip-vit-large-patch14-text-encoder::bfloat16",
description="CLIP-L text encoder (used in FLUX pipelines). ~250MB",
source="openai/clip-vit-large-patch14",
description="CLIP-L text encoder (used in FLUX pipelines). ~3GB",
type=ModelType.CLIPEmbed,
)
@ -94,7 +94,7 @@ STARTER_MODELS: list[StarterModel] = [
name="FLUX Schnell (Quantized)",
base=BaseModelType.Flux,
source="InvokeAI/flux_schnell::transformer/bnb_nf4/flux1-schnell-bnb_nf4.safetensors",
description="FLUX schnell transformer quantized to bitsandbytes NF4 format. Total size with dependencies: ~12GB",
description="FLUX schnell transformer quantized to bitsandbytes NF4 format. Total size with dependencies: ~14GB",
type=ModelType.Main,
dependencies=[t5_8b_quantized_encoder, flux_vae, clip_l_encoder],
),
@ -102,7 +102,7 @@ STARTER_MODELS: list[StarterModel] = [
name="FLUX Dev (Quantized)",
base=BaseModelType.Flux,
source="InvokeAI/flux_dev::transformer/bnb_nf4/flux1-dev-bnb_nf4.safetensors",
description="FLUX dev transformer quantized to bitsandbytes NF4 format. Total size with dependencies: ~12GB",
description="FLUX dev transformer quantized to bitsandbytes NF4 format. Total size with dependencies: ~16GB",
type=ModelType.Main,
dependencies=[t5_8b_quantized_encoder, flux_vae, clip_l_encoder],
),
@ -118,7 +118,7 @@ STARTER_MODELS: list[StarterModel] = [
name="FLUX Dev",
base=BaseModelType.Flux,
source="InvokeAI/flux_dev::transformer/base/flux1-dev.safetensors",
description="FLUX dev transformer in bfloat16. Total size with dependencies: ~33GB",
description="FLUX dev transformer in bfloat16. Total size with dependencies: ~34GB",
type=ModelType.Main,
dependencies=[t5_base_encoder, flux_vae, clip_l_encoder],
),

View File

@ -1,10 +1,10 @@
from pathlib import Path
import accelerate
from flux.model import Flux
from flux.util import configs as flux_configs
from safetensors.torch import load_file, save_file
from invokeai.backend.flux.model import Flux
from invokeai.backend.flux.util import params
from invokeai.backend.quantization.bnb_llm_int8 import quantize_model_llm_int8
from invokeai.backend.quantization.scripts.load_flux_model_bnb_nf4 import log_time
@ -22,11 +22,11 @@ def main():
with log_time("Intialize FLUX transformer on meta device"):
# TODO(ryand): Determine if this is a schnell model or a dev model and load the appropriate config.
p = params["flux-schnell"]
params = flux_configs["flux-schnell"].params
# Initialize the model on the "meta" device.
with accelerate.init_empty_weights():
model = Flux(p)
model = Flux(params)
# TODO(ryand): We may want to add some modules to not quantize here (e.g. the proj_out layer). See the accelerate
# `get_keys_to_not_convert(...)` function for a heuristic to determine which modules to not quantize.

View File

@ -4,10 +4,10 @@ from pathlib import Path
import accelerate
import torch
from flux.model import Flux
from flux.util import configs as flux_configs
from safetensors.torch import load_file, save_file
from invokeai.backend.flux.model import Flux
from invokeai.backend.flux.util import params
from invokeai.backend.quantization.bnb_nf4 import quantize_model_nf4
@ -35,11 +35,11 @@ def main():
# inference_dtype = torch.bfloat16
with log_time("Intialize FLUX transformer on meta device"):
# TODO(ryand): Determine if this is a schnell model or a dev model and load the appropriate config.
p = params["flux-schnell"]
params = flux_configs["flux-schnell"].params
# Initialize the model on the "meta" device.
with accelerate.init_empty_weights():
model = Flux(p)
model = Flux(params)
# TODO(ryand): We may want to add some modules to not quantize here (e.g. the proj_out layer). See the accelerate
# `get_keys_to_not_convert(...)` function for a heuristic to determine which modules to not quantize.

View File

@ -3,7 +3,7 @@ from typing import Any, Dict, List, Optional, Tuple, Union
import diffusers
import torch
from diffusers.configuration_utils import ConfigMixin, register_to_config
from diffusers.loaders import FromOriginalControlNetMixin
from diffusers.loaders.single_file_model import FromOriginalModelMixin
from diffusers.models.attention_processor import AttentionProcessor, AttnProcessor
from diffusers.models.controlnet import ControlNetConditioningEmbedding, ControlNetOutput, zero_module
from diffusers.models.embeddings import (
@ -32,7 +32,7 @@ from invokeai.backend.util.logging import InvokeAILogger
logger = InvokeAILogger.get_logger(__name__)
class ControlNetModel(ModelMixin, ConfigMixin, FromOriginalControlNetMixin):
class ControlNetModel(ModelMixin, ConfigMixin, FromOriginalModelMixin):
"""
A ControlNet model.

View File

@ -0,0 +1,19 @@
repo_id: "black-forest-labs/FLUX.1-dev"
repo_ae: "ae.safetensors"
max_seq_len: 512
params:
in_channels: 64
vec_in_dim: 768
context_in_dim: 4096
hidden_size: 3072
mlp_ratio: 4.0
num_heads: 24
depth: 19
depth_single_blocks: 38
axes_dim:
- 16
- 56
- 56
theta: 10_000
qkv_bias: True
guidance_embed: True

View File

@ -0,0 +1,19 @@
repo_id: "black-forest-labs/FLUX.1-schnell"
repo_ae: "ae.safetensors"
max_seq_len: 256
params:
in_channels: 64
vec_in_dim: 768
context_in_dim: 4096
hidden_size: 3072
mlp_ratio: 4.0
num_heads: 24
depth: 19
depth_single_blocks: 38
axes_dim:
- 16
- 56
- 56
theta: 10_000
qkv_bias: True
guidance_embed: False

View File

@ -0,0 +1,16 @@
repo_id: "black-forest-labs/FLUX.1-schnell"
repo_path: "ae.safetensors"
params:
resolution: 256
in_channels: 3
ch: 128
out_ch: 3
ch_mult:
- 1
- 2
- 4
- 4
num_res_blocks: 2
z_channels: 16
scale_factor: 0.3611
shift_factor: 0.1159

View File

@ -12,10 +12,6 @@ module.exports = {
'i18next/no-literal-string': 'error',
// https://eslint.org/docs/latest/rules/no-console
'no-console': 'error',
// https://eslint.org/docs/latest/rules/no-promise-executor-return
'no-promise-executor-return': 'error',
// https://eslint.org/docs/latest/rules/require-await
'require-await': 'error',
},
overrides: [
/**

View File

@ -1,5 +1,5 @@
import { PropsWithChildren, memo, useEffect } from 'react';
import { modelChanged } from '../src/features/controlLayers/store/paramsSlice';
import { modelChanged } from '../src/features/parameters/store/generationSlice';
import { useAppDispatch } from '../src/app/store/storeHooks';
import { useGlobalModifiersInit } from '@invoke-ai/ui-library';
/**
@ -10,9 +10,7 @@ export const ReduxInit = memo((props: PropsWithChildren) => {
const dispatch = useAppDispatch();
useGlobalModifiersInit();
useEffect(() => {
dispatch(
modelChanged({ model: { key: 'test_model', hash: 'some_hash', name: 'some name', base: 'sd-1', type: 'main' } })
);
dispatch(modelChanged({ key: 'test_model', hash: 'some_hash', name: 'some name', base: 'sd-1', type: 'main' }));
}, []);
return props.children;

View File

@ -9,8 +9,6 @@ const config: KnipConfig = {
'src/services/api/schema.ts',
'src/features/nodes/types/v1/**',
'src/features/nodes/types/v2/**',
// TODO(psyche): maybe we can clean up these utils after canvas v2 release
'src/features/controlLayers/konva/util.ts',
],
ignoreBinaries: ['only-allow'],
paths: {

View File

@ -24,7 +24,7 @@
"build": "pnpm run lint && vite build",
"typegen": "node scripts/typegen.js",
"preview": "vite preview",
"lint:knip": "knip --tags=-knipignore",
"lint:knip": "knip",
"lint:dpdm": "dpdm --no-warning --no-tree --transform --exit-code circular:1 src/main.tsx",
"lint:eslint": "eslint --max-warnings=0 .",
"lint:prettier": "prettier --check .",
@ -52,17 +52,17 @@
}
},
"dependencies": {
"@chakra-ui/react-use-size": "^2.1.0",
"@dagrejs/dagre": "^1.1.3",
"@dagrejs/graphlib": "^2.2.3",
"@dnd-kit/core": "^6.1.0",
"@dnd-kit/sortable": "^8.0.0",
"@dnd-kit/utilities": "^3.2.2",
"@fontsource-variable/inter": "^5.0.20",
"@invoke-ai/ui-library": "^0.0.32",
"@invoke-ai/ui-library": "^0.0.29",
"@nanostores/react": "^0.7.3",
"@reduxjs/toolkit": "2.2.3",
"@roarr/browser-log-writer": "^1.3.0",
"async-mutex": "^0.5.0",
"chakra-react-select": "^4.9.1",
"compare-versions": "^6.1.1",
"dateformat": "^5.0.3",
@ -74,8 +74,6 @@
"jsondiffpatch": "^0.6.0",
"konva": "^9.3.14",
"lodash-es": "^4.17.21",
"lru-cache": "^11.0.0",
"nanoid": "^5.0.7",
"nanostores": "^0.11.2",
"new-github-issue-url": "^1.0.0",
"overlayscrollbars": "^2.10.0",
@ -90,6 +88,7 @@
"react-hotkeys-hook": "4.5.0",
"react-i18next": "^14.1.3",
"react-icons": "^5.2.1",
"react-konva": "^18.2.10",
"react-redux": "9.1.2",
"react-resizable-panels": "^2.0.23",
"react-select": "5.8.0",
@ -103,9 +102,9 @@
"roarr": "^7.21.1",
"serialize-error": "^11.0.3",
"socket.io-client": "^4.7.5",
"stable-hash": "^0.0.4",
"use-debounce": "^10.0.2",
"use-device-pixel-ratio": "^1.1.2",
"use-image": "^1.1.1",
"uuid": "^10.0.0",
"zod": "^3.23.8",
"zod-validation-error": "^3.3.1"

View File

@ -5,6 +5,9 @@ settings:
excludeLinksFromLockfile: false
dependencies:
'@chakra-ui/react-use-size':
specifier: ^2.1.0
version: 2.1.0(react@18.3.1)
'@dagrejs/dagre':
specifier: ^1.1.3
version: 1.1.3
@ -24,8 +27,8 @@ dependencies:
specifier: ^5.0.20
version: 5.0.20
'@invoke-ai/ui-library':
specifier: ^0.0.32
version: 0.0.32(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.20)(@types/react@18.3.3)(i18next@23.12.2)(react-dom@18.3.1)(react@18.3.1)
specifier: ^0.0.29
version: 0.0.29(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@fontsource-variable/inter@5.0.20)(@types/react@18.3.3)(i18next@23.12.2)(react-dom@18.3.1)(react@18.3.1)
'@nanostores/react':
specifier: ^0.7.3
version: 0.7.3(nanostores@0.11.2)(react@18.3.1)
@ -35,12 +38,9 @@ dependencies:
'@roarr/browser-log-writer':
specifier: ^1.3.0
version: 1.3.0
async-mutex:
specifier: ^0.5.0
version: 0.5.0
chakra-react-select:
specifier: ^4.9.1
version: 4.9.1(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.13.3)(@types/react@18.3.3)(react-dom@18.3.1)(react@18.3.1)
version: 4.9.1(@chakra-ui/form-control@2.2.0)(@chakra-ui/icon@3.2.0)(@chakra-ui/layout@2.3.1)(@chakra-ui/media-query@3.3.0)(@chakra-ui/menu@2.2.1)(@chakra-ui/spinner@2.1.0)(@chakra-ui/system@2.6.2)(@emotion/react@11.13.0)(@types/react@18.3.3)(react-dom@18.3.1)(react@18.3.1)
compare-versions:
specifier: ^6.1.1
version: 6.1.1
@ -71,12 +71,6 @@ dependencies:
lodash-es:
specifier: ^4.17.21
version: 4.17.21
lru-cache:
specifier: ^11.0.0
version: 11.0.0
nanoid:
specifier: ^5.0.7
version: 5.0.7
nanostores:
specifier: ^0.11.2
version: 0.11.2
@ -119,6 +113,9 @@ dependencies:
react-icons:
specifier: ^5.2.1
version: 5.2.1(react@18.3.1)
react-konva:
specifier: ^18.2.10
version: 18.2.10(konva@9.3.14)(react-dom@18.3.1)(react@18.3.1)
react-redux:
specifier: 9.1.2
version: 9.1.2(@types/react@18.3.3)(react@18.3.1)(redux@5.0.1)
@ -158,15 +155,15 @@ dependencies:
socket.io-client:
specifier: ^4.7.5
version: 4.7.5
stable-hash:
specifier: ^0.0.4
version: 0.0.4
use-debounce:
specifier: ^10.0.2
version: 10.0.2(react@18.3.1)
use-device-pixel-ratio:
specifier: ^1.1.2
version: 1.1.2(react@18.3.1)
use-image:
specifier: ^1.1.1
version: 1.1.1(react-dom@18.3.1)(react@18.3.1)
uuid:
specifier: ^10.0.0
version: 10.0.0
@ -1752,13 +1749,6 @@ packages:
dependencies:
regenerator-runtime: 0.14.1
/@babel/runtime@7.25.4:
resolution: {integrity: sha512-DSgLeL/FNcpXuzav5wfYvHCGvynXkJbn3Zvc3823AEe9nPwW9IK4UoCSS5yGymmQzN0pCPvivtgS6/8U2kkm1w==}
engines: {node: '>=6.9.0'}
dependencies:
regenerator-runtime: 0.14.1
dev: false
/@babel/template@7.24.0:
resolution: {integrity: sha512-Bkf2q8lMB0AFpX0NFEqSbx1OkTHf0f+0j82mkw+ZpzBnkk7e9Ql0891vlfgi+kHwOk8tQjiQHpqh4LaSa0fKEA==}
engines: {node: '>=6.9.0'}
@ -1845,7 +1835,7 @@ packages:
'@chakra-ui/react-use-controllable-state': 2.1.0(react@18.3.1)
'@chakra-ui/react-use-merge-refs': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/transition': 2.1.0(framer-motion@10.18.0)(react@18.3.1)
framer-motion: 10.18.0(react-dom@18.3.1)(react@18.3.1)
react: 18.3.1
@ -1861,7 +1851,7 @@ packages:
'@chakra-ui/react-context': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/spinner': 2.1.0(@chakra-ui/system@2.6.2)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -1879,7 +1869,7 @@ packages:
'@chakra-ui/react-children-utils': 2.0.6(react@18.3.1)
'@chakra-ui/react-context': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -1892,7 +1882,7 @@ packages:
'@chakra-ui/react-children-utils': 2.0.6(react@18.3.1)
'@chakra-ui/react-context': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -1912,7 +1902,7 @@ packages:
'@chakra-ui/react-use-merge-refs': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/spinner': 2.1.0(@chakra-ui/system@2.6.2)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -1923,7 +1913,7 @@ packages:
react: '>=18'
dependencies:
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -1942,7 +1932,7 @@ packages:
'@chakra-ui/react-use-safe-layout-effect': 2.1.0(react@18.3.1)
'@chakra-ui/react-use-update-effect': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/visually-hidden': 2.2.0(@chakra-ui/system@2.6.2)(react@18.3.1)
'@zag-js/focus-visible': 0.16.0
react: 18.3.1
@ -1965,7 +1955,7 @@ packages:
react: '>=18'
dependencies:
'@chakra-ui/icon': 3.2.0(@chakra-ui/system@2.6.2)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -1984,7 +1974,7 @@ packages:
'@chakra-ui/system': '>=2.0.0'
react: '>=18'
dependencies:
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -1999,13 +1989,13 @@ packages:
react: 18.3.1
dev: false
/@chakra-ui/css-reset@2.3.0(@emotion/react@11.13.3)(react@18.3.1):
/@chakra-ui/css-reset@2.3.0(@emotion/react@11.13.0)(react@18.3.1):
resolution: {integrity: sha512-cQwwBy5O0jzvl0K7PLTLgp8ijqLPKyuEMiDXwYzl95seD3AoeuoCLyzZcJtVqaUZ573PiBdAbY/IlZcwDOItWg==}
peerDependencies:
'@emotion/react': '>=10.0.35'
react: '>=18'
dependencies:
'@emotion/react': 11.13.3(@types/react@18.3.3)(react@18.3.1)
'@emotion/react': 11.13.0(@types/react@18.3.3)(react@18.3.1)
react: 18.3.1
dev: false
@ -2038,7 +2028,7 @@ packages:
'@chakra-ui/react-use-safe-layout-effect': 2.1.0(react@18.3.1)
'@chakra-ui/react-use-update-effect': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -2069,7 +2059,7 @@ packages:
'@chakra-ui/react-types': 2.0.7(react@18.3.1)
'@chakra-ui/react-use-merge-refs': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -2092,7 +2082,7 @@ packages:
react: '>=18'
dependencies:
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -2103,7 +2093,7 @@ packages:
react: '>=18'
dependencies:
'@chakra-ui/icon': 3.2.0(@chakra-ui/system@2.6.2)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -2115,7 +2105,7 @@ packages:
dependencies:
'@chakra-ui/react-use-safe-layout-effect': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -2130,7 +2120,7 @@ packages:
'@chakra-ui/react-children-utils': 2.0.6(react@18.3.1)
'@chakra-ui/react-context': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -2146,7 +2136,7 @@ packages:
'@chakra-ui/react-children-utils': 2.0.6(react@18.3.1)
'@chakra-ui/react-context': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -2171,7 +2161,7 @@ packages:
'@chakra-ui/breakpoint-utils': 2.0.8
'@chakra-ui/react-env': 3.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -2196,7 +2186,7 @@ packages:
'@chakra-ui/react-use-outside-click': 2.2.0(react@18.3.1)
'@chakra-ui/react-use-update-effect': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/transition': 2.1.0(framer-motion@10.18.0)(react@18.3.1)
framer-motion: 10.18.0(react-dom@18.3.1)(react@18.3.1)
react: 18.3.1
@ -2223,7 +2213,7 @@ packages:
'@chakra-ui/react-use-outside-click': 2.2.0(react@18.3.1)
'@chakra-ui/react-use-update-effect': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/transition': 2.1.0(framer-motion@11.3.24)(react@18.3.1)
framer-motion: 11.3.24(react-dom@18.3.1)(react@18.3.1)
react: 18.3.1
@ -2244,7 +2234,7 @@ packages:
'@chakra-ui/react-types': 2.0.7(react@18.3.1)
'@chakra-ui/react-use-merge-refs': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/transition': 2.1.0(framer-motion@10.18.0)(react@18.3.1)
aria-hidden: 1.2.4
framer-motion: 10.18.0(react-dom@18.3.1)(react@18.3.1)
@ -2273,7 +2263,7 @@ packages:
'@chakra-ui/react-use-safe-layout-effect': 2.1.0(react@18.3.1)
'@chakra-ui/react-use-update-effect': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -2297,7 +2287,7 @@ packages:
'@chakra-ui/react-use-controllable-state': 2.1.0(react@18.3.1)
'@chakra-ui/react-use-merge-refs': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
@ -2319,7 +2309,7 @@ packages:
'@chakra-ui/react-use-focus-on-pointer-down': 2.1.0(react@18.3.1)
'@chakra-ui/react-use-merge-refs': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
framer-motion: 10.18.0(react-dom@18.3.1)(react@18.3.1)
react: 18.3.1
dev: false
@ -2354,11 +2344,11 @@ packages:
react: '>=18'
dependencies:
'@chakra-ui/react-context': 2.1.0(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
react: 18.3.1
dev: false
/@chakra-ui/provider@2.4.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react-dom@18.3.1)(react@18.3.1):
/@chakra-ui/provider@2.4.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react-dom@18.3.1)(react@18.3.1):
resolution: {integrity: sha512-w0Tef5ZCJK1mlJorcSjItCSbyvVuqpvyWdxZiVQmE6fvSJR83wZof42ux0+sfWD+I7rHSfj+f9nzhNaEWClysw==}
peerDependencies:
'@emotion/react': ^11.0.0
@ -2366,13 +2356,13 @@ packages:
react: '>=18'
react-dom: '>=18'
dependencies:
'@chakra-ui/css-reset': 2.3.0(@emotion/react@11.13.3)(react@18.3.1)
'@chakra-ui/css-reset': 2.3.0(@emotion/react@11.13.0)(react@18.3.1)
'@chakra-ui/portal': 2.1.0(react-dom@18.3.1)(react@18.3.1)
'@chakra-ui/react-env': 3.1.0(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/utils': 2.0.15
'@emotion/react': 11.13.3(@types/react@18.3.3)(react@18.3.1)
'@emotion/styled': 11.13.0(@emotion/react@11.13.3)(@types/react@18.3.3)(react@18.3.1)
'@emotion/react': 11.13.0(@types/react@18.3.3)(react@18.3.1)
'@emotion/styled': 11.13.0(@emotion/react@11.13.0)(@types/react@18.3.3)(react@18.3.1)
react: 18.3.1
react-dom: 18.3.1(react@18.3.1)
dev: false
@ -2388,7 +2378,7 @@ packages:
'@chakra-ui/react-types': 2.0.7(react@18.3.1)
'@chakra-ui/react-use-merge-refs': 2.1.0(react@18.3.1)
'@chakra-ui/shared-utils': 2.0.5
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
'@zag-js/focus-visible': 0.16.0
react: 18.3.1
dev: false
@ -2588,7 +2578,7 @@ packages:
react: 18.3.1
dev: false
/@chakra-ui/react@2.8.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(@types/react@18.3.3)(framer-motion@10.18.0)(react-dom@18.3.1)(react@18.3.1):
/@chakra-ui/react@2.8.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(@types/react@18.3.3)(framer-motion@10.18.0)(react-dom@18.3.1)(react@18.3.1):
resolution: {integrity: sha512-Hn0moyxxyCDKuR9ywYpqgX8dvjqwu9ArwpIb9wHNYjnODETjLwazgNIliCVBRcJvysGRiV51U2/JtJVrpeCjUQ==}
peerDependencies:
'@emotion/react': ^11.0.0
@ -2607,7 +2597,7 @@ packages:
'@chakra-ui/close-button': 2.1.1(@chakra-ui/system@2.6.2)(react@18.3.1)
'@chakra-ui/control-box': 2.1.0(@chakra-ui/system@2.6.2)(react@18.3.1)
'@chakra-ui/counter': 2.1.0(react@18.3.1)
'@chakra-ui/css-reset': 2.3.0(@emotion/react@11.13.3)(react@18.3.1)
'@chakra-ui/css-reset': 2.3.0(@emotion/react@11.13.0)(react@18.3.1)
'@chakra-ui/editable': 3.1.0(@chakra-ui/system@2.6.2)(react@18.3.1)
'@chakra-ui/focus-lock': 2.1.0(@types/react@18.3.3)(react@18.3.1)
'@chakra-ui/form-control': 2.2.0(@chakra-ui/system@2.6.2)(react@18.3.1)
@ -2626,7 +2616,7 @@ packages:
'@chakra-ui/popper': 3.1.0(react@18.3.1)
'@chakra-ui/portal': 2.1.0(react-dom@18.3.1)(react@18.3.1)
'@chakra-ui/progress': 2.2.0(@chakra-ui/system@2.6.2)(react@18.3.1)
'@chakra-ui/provider': 2.4.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react-dom@18.3.1)(react@18.3.1)
'@chakra-ui/provider': 2.4.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react-dom@18.3.1)(react@18.3.1)
'@chakra-ui/radio': 2.1.2(@chakra-ui/system@2.6.2)(react@18.3.1)
'@chakra-ui/react-env': 3.1.0(react@18.3.1)
'@chakra-ui/select': 2.1.2(@chakra-ui/system@2.6.2)(react@18.3.1)
@ -2638,7 +2628,7 @@ packages:
'@chakra-ui/stepper': 2.3.1(@chakra-ui/system@2.6.2)(react@18.3.1)
'@chakra-ui/styled-system': 2.9.2
'@chakra-ui/switch': 2.1.2(@chakra-ui/system@2.6.2)(framer-motion@10.18.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
'@chakra-ui/table': 2.1.0(@chakra-ui/system@2.6.2)(react@18.3.1)
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@ -2650,8 +2640,8 @@ packages:
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@ -2667,7 +2657,7 @@ packages:
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@ -2684,7 +2674,7 @@ packages:
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@ -2694,7 +2684,7 @@ packages:
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react: '>=18'
dependencies:
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@ -2714,7 +2704,7 @@ packages:
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@ -2725,7 +2715,7 @@ packages:
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@ -2738,7 +2728,7 @@ packages:
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@ -2751,7 +2741,7 @@ packages:
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@ -2772,12 +2762,12 @@ packages:
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@ -2790,8 +2780,8 @@ packages:
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@ -2804,7 +2794,7 @@ packages:
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@ -2823,7 +2813,7 @@ packages:
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@ -2835,7 +2825,7 @@ packages:
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@ -2847,7 +2837,7 @@ packages:
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@ -2898,7 +2888,7 @@ packages:
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@ -2921,7 +2911,7 @@ packages:
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react-dom: 18.3.1(react@18.3.1)
@ -2964,7 +2954,7 @@ packages:
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react: '>=18'
dependencies:
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@ -3047,10 +3037,10 @@ packages:
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@ -3138,8 +3128,8 @@ packages:
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@ -3147,10 +3137,10 @@ packages:
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@ -3171,12 +3161,12 @@ packages:
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@ -3199,11 +3189,11 @@ packages:
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@ -3212,14 +3202,14 @@ packages:
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@ -3571,8 +3561,8 @@ packages:
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@ -3582,14 +3572,14 @@ packages:
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@ -5212,6 +5202,12 @@ packages:
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@ -6133,7 +6123,7 @@ packages:
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peerDependencies:
'@chakra-ui/form-control': ^2.0.0
@ -6153,8 +6143,8 @@ packages:
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'@chakra-ui/menu': 2.2.1(@chakra-ui/system@2.6.2)(framer-motion@11.3.24)(react@18.3.1)
'@chakra-ui/spinner': 2.1.0(@chakra-ui/system@2.6.2)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.3)(@emotion/styled@11.13.0)(react@18.3.1)
'@emotion/react': 11.13.3(@types/react@18.3.3)(react@18.3.1)
'@chakra-ui/system': 2.6.2(@emotion/react@11.13.0)(@emotion/styled@11.13.0)(react@18.3.1)
'@emotion/react': 11.13.0(@types/react@18.3.3)(react@18.3.1)
react: 18.3.1
react-dom: 18.3.1(react@18.3.1)
react-select: 5.8.0(@types/react@18.3.3)(react-dom@18.3.1)(react@18.3.1)
@ -7579,7 +7569,7 @@ packages:
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engines: {node: '>=10'}
dependencies:
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tslib: 2.6.3
dev: false
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@ -7618,7 +7608,7 @@ packages:
dependencies:
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react-dom: 18.3.1(react@18.3.1)
tslib: 2.7.0
tslib: 2.6.3
optionalDependencies:
'@emotion/is-prop-valid': 0.8.8
dev: false
@ -8394,6 +8384,15 @@ packages:
set-function-name: 2.0.2
dev: true
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react: 18.3.1
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engines: {node: '>=14'}
@ -8711,11 +8710,6 @@ packages:
engines: {node: 14 || >=16.14}
dev: true
/lru-cache@11.0.0:
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engines: {node: 20 || >=22}
dev: false
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dependencies:
@ -9003,12 +8997,6 @@ packages:
hasBin: true
dev: true
/nanoid@5.0.7:
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engines: {node: ^18 || >=20}
hasBin: true
dev: false
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engines: {node: ^18.0.0 || >=20.0.0}
@ -9626,7 +9614,7 @@ packages:
peerDependencies:
react: ^15.3.0 || ^16.0.0 || ^17.0.0 || ^18.0.0
dependencies:
'@babel/runtime': 7.25.4
'@babel/runtime': 7.25.0
react: 18.3.1
dev: false
@ -9721,7 +9709,7 @@ packages:
'@types/react':
optional: true
dependencies:
'@babel/runtime': 7.25.4
'@babel/runtime': 7.25.0
'@types/react': 18.3.3
focus-lock: 1.3.5
prop-types: 15.8.1
@ -9783,7 +9771,7 @@ packages:
react-native:
optional: true
dependencies:
'@babel/runtime': 7.25.4
'@babel/runtime': 7.25.0
html-parse-stringify: 3.0.1
i18next: 23.12.2
react: 18.3.1
@ -9813,6 +9801,33 @@ packages:
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dev: true
/react-konva@18.2.10(konva@9.3.14)(react-dom@18.3.1)(react@18.3.1):
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peerDependencies:
konva: ^8.0.1 || ^7.2.5 || ^9.0.0
react: '>=18.0.0'
react-dom: '>=18.0.0'
dependencies:
'@types/react-reconciler': 0.28.8
its-fine: 1.2.5(react@18.3.1)
konva: 9.3.14
react: 18.3.1
react-dom: 18.3.1(react@18.3.1)
react-reconciler: 0.29.2(react@18.3.1)
scheduler: 0.23.2
dev: false
/react-reconciler@0.29.2(react@18.3.1):
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engines: {node: '>=0.10.0'}
peerDependencies:
react: ^18.3.1
dependencies:
loose-envify: 1.4.0
react: 18.3.1
scheduler: 0.23.2
dev: false
/react-redux@9.1.2(@types/react@18.3.3)(react@18.3.1)(redux@5.0.1):
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peerDependencies:
@ -9845,7 +9860,7 @@ packages:
'@types/react': 18.3.3
react: 18.3.1
react-style-singleton: 2.2.1(@types/react@18.3.3)(react@18.3.1)
tslib: 2.7.0
tslib: 2.6.3
dev: false
/react-remove-scroll@2.5.10(@types/react@18.3.3)(react@18.3.1):
@ -9862,7 +9877,7 @@ packages:
react: 18.3.1
react-remove-scroll-bar: 2.3.6(@types/react@18.3.3)(react@18.3.1)
react-style-singleton: 2.2.1(@types/react@18.3.3)(react@18.3.1)
tslib: 2.7.0
tslib: 2.6.3
use-callback-ref: 1.3.2(@types/react@18.3.3)(react@18.3.1)
use-sidecar: 1.1.2(@types/react@18.3.3)(react@18.3.1)
dev: false
@ -9912,7 +9927,7 @@ packages:
get-nonce: 1.0.1
invariant: 2.2.4
react: 18.3.1
tslib: 2.7.0
tslib: 2.6.3
dev: false
/react-transition-group@4.4.5(react-dom@18.3.1)(react@18.3.1):
@ -10610,10 +10625,6 @@ packages:
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dev: true
/stable-hash@0.0.4:
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dev: false
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dependencies:
@ -11052,10 +11063,6 @@ packages:
/tslib@2.6.3:
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dev: false
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engines: {node: '>= 6'}
@ -11303,7 +11310,7 @@ packages:
dependencies:
'@types/react': 18.3.3
react: 18.3.1
tslib: 2.7.0
tslib: 2.6.3
dev: false
/use-debounce@10.0.2(react@18.3.1):
@ -11323,6 +11330,16 @@ packages:
react: 18.3.1
dev: false
/use-image@1.1.1(react-dom@18.3.1)(react@18.3.1):
resolution: {integrity: sha512-n4YO2k8AJG/BcDtxmBx8Aa+47kxY5m335dJiCQA5tTeVU4XdhrhqR6wT0WISRXwdMEOv5CSjqekDZkEMiiWaYQ==}
peerDependencies:
react: '>=16.8.0'
react-dom: '>=16.8.0'
dependencies:
react: 18.3.1
react-dom: 18.3.1(react@18.3.1)
dev: false
/use-isomorphic-layout-effect@1.1.2(@types/react@18.3.3)(react@18.3.1):
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peerDependencies:
@ -11349,7 +11366,7 @@ packages:
'@types/react': 18.3.3
detect-node-es: 1.1.0
react: 18.3.1
tslib: 2.7.0
tslib: 2.6.3
dev: false
/use-sync-external-store@1.2.0(react@18.3.1):

View File

@ -80,7 +80,6 @@
"aboutDesc": "Using Invoke for work? Check out:",
"aboutHeading": "Own Your Creative Power",
"accept": "Accept",
"apply": "Apply",
"add": "Add",
"advanced": "Advanced",
"ai": "ai",
@ -116,7 +115,6 @@
"githubLabel": "Github",
"goTo": "Go to",
"hotkeysLabel": "Hotkeys",
"loadingImage": "Loading Image",
"imageFailedToLoad": "Unable to Load Image",
"img2img": "Image To Image",
"inpaint": "inpaint",
@ -327,10 +325,6 @@
"canceled": "Canceled",
"completedIn": "Completed in",
"batch": "Batch",
"origin": "Origin",
"originCanvas": "Canvas",
"originWorkflows": "Workflows",
"originOther": "Other",
"batchFieldValues": "Batch Field Values",
"item": "Item",
"session": "Session",
@ -1102,6 +1096,7 @@
"confirmOnDelete": "Confirm On Delete",
"developer": "Developer",
"displayInProgress": "Display Progress Images",
"enableImageDebugging": "Enable Image Debugging",
"enableInformationalPopovers": "Enable Informational Popovers",
"informationalPopoversDisabled": "Informational Popovers Disabled",
"informationalPopoversDisabledDesc": "Informational popovers have been disabled. Enable them in Settings.",
@ -1568,7 +1563,7 @@
"copyToClipboard": "Copy to Clipboard",
"cursorPosition": "Cursor Position",
"darkenOutsideSelection": "Darken Outside Selection",
"discardAll": "Discard All & Cancel Pending Generations",
"discardAll": "Discard All",
"discardCurrent": "Discard Current",
"downloadAsImage": "Download As Image",
"enableMask": "Enable Mask",
@ -1646,124 +1641,41 @@
"storeNotInitialized": "Store is not initialized"
},
"controlLayers": {
"clearHistory": "Clear History",
"generateMode": "Generate",
"generateModeDesc": "Create individual images. Generated images are added directly to the gallery.",
"composeMode": "Compose",
"composeModeDesc": "Compose your work iterative. Generated images are added back to the canvas.",
"autoSave": "Auto-save to Gallery",
"resetCanvas": "Reset Canvas",
"resetAll": "Reset All",
"clearCaches": "Clear Caches",
"recalculateRects": "Recalculate Rects",
"clipToBbox": "Clip Strokes to Bbox",
"deleteAll": "Delete All",
"addLayer": "Add Layer",
"duplicate": "Duplicate",
"moveToFront": "Move to Front",
"moveToBack": "Move to Back",
"moveForward": "Move Forward",
"moveBackward": "Move Backward",
"brushSize": "Brush Size",
"width": "Width",
"zoom": "Zoom",
"resetView": "Reset View",
"controlLayers": "Control Layers",
"globalMaskOpacity": "Global Mask Opacity",
"autoNegative": "Auto Negative",
"enableAutoNegative": "Enable Auto Negative",
"disableAutoNegative": "Disable Auto Negative",
"deletePrompt": "Delete Prompt",
"resetRegion": "Reset Region",
"debugLayers": "Debug Layers",
"rectangle": "Rectangle",
"maskFill": "Mask Fill",
"maskPreviewColor": "Mask Preview Color",
"addPositivePrompt": "Add $t(common.positivePrompt)",
"addNegativePrompt": "Add $t(common.negativePrompt)",
"addIPAdapter": "Add $t(common.ipAdapter)",
"regionalGuidance": "Regional Guidance",
"regionalGuidanceLayer": "$t(controlLayers.regionalGuidance) $t(unifiedCanvas.layer)",
"raster": "Raster",
"rasterLayer_one": "Raster Layer",
"controlLayer_one": "Control Layer",
"inpaintMask_one": "Inpaint Mask",
"regionalGuidance_one": "Regional Guidance",
"ipAdapter_one": "IP Adapter",
"rasterLayer_other": "Raster Layers",
"controlLayer_other": "Control Layers",
"inpaintMask_other": "Inpaint Masks",
"regionalGuidance_other": "Regional Guidance",
"ipAdapter_other": "IP Adapters",
"opacity": "Opacity",
"regionalGuidance_withCount_hidden": "Regional Guidance ({{count}} hidden)",
"controlAdapters_withCount_hidden": "Control Adapters ({{count}} hidden)",
"controlLayers_withCount_hidden": "Control Layers ({{count}} hidden)",
"rasterLayers_withCount_hidden": "Raster Layers ({{count}} hidden)",
"ipAdapters_withCount_hidden": "IP Adapters ({{count}} hidden)",
"inpaintMasks_withCount_hidden": "Inpaint Masks ({{count}} hidden)",
"regionalGuidance_withCount_visible": "Regional Guidance ({{count}})",
"controlAdapters_withCount_visible": "Control Adapters ({{count}})",
"controlLayers_withCount_visible": "Control Layers ({{count}})",
"rasterLayers_withCount_visible": "Raster Layers ({{count}})",
"ipAdapters_withCount_visible": "IP Adapters ({{count}})",
"inpaintMasks_withCount_visible": "Inpaint Masks ({{count}})",
"globalControlAdapter": "Global $t(controlnet.controlAdapter_one)",
"globalControlAdapterLayer": "Global $t(controlnet.controlAdapter_one) $t(unifiedCanvas.layer)",
"globalIPAdapter": "Global $t(common.ipAdapter)",
"globalIPAdapterLayer": "Global $t(common.ipAdapter) $t(unifiedCanvas.layer)",
"globalInitialImage": "Global Initial Image",
"globalInitialImageLayer": "$t(controlLayers.globalInitialImage) $t(unifiedCanvas.layer)",
"layer": "Layer",
"opacityFilter": "Opacity Filter",
"clearProcessor": "Clear Processor",
"resetProcessor": "Reset Processor to Defaults",
"noLayersAdded": "No Layers Added",
"layers_one": "Layer",
"layers_other": "Layers",
"objects_zero": "empty",
"objects_one": "{{count}} object",
"objects_other": "{{count}} objects",
"convertToControlLayer": "Convert to Control Layer",
"convertToRasterLayer": "Convert to Raster Layer",
"transparency": "Transparency",
"enableTransparencyEffect": "Enable Transparency Effect",
"disableTransparencyEffect": "Disable Transparency Effect",
"hidingType": "Hiding {{type}}",
"showingType": "Showing {{type}}",
"dynamicGrid": "Dynamic Grid",
"logDebugInfo": "Log Debug Info",
"locked": "Locked",
"unlocked": "Unlocked",
"deleteSelected": "Delete Selected",
"deleteAll": "Delete All",
"fill": {
"fillStyle": "Fill Style",
"solid": "Solid",
"grid": "Grid",
"crosshatch": "Crosshatch",
"vertical": "Vertical",
"horizontal": "Horizontal",
"diagonal": "Diagonal"
},
"tool": {
"brush": "Brush",
"eraser": "Eraser",
"rectangle": "Rectangle",
"bbox": "Bbox",
"move": "Move",
"view": "View",
"transform": "Transform",
"colorPicker": "Color Picker"
},
"filter": {
"filter": "Filter",
"filters": "Filters",
"filterType": "Filter Type",
"preview": "Preview",
"apply": "Apply",
"cancel": "Cancel"
}
"layers_other": "Layers"
},
"upscaling": {
"upscale": "Upscale",
"creativity": "Creativity",
"exceedsMaxSize": "Upscale settings exceed max size limit",
"exceedsMaxSizeDetails": "Max upscale limit is {{maxUpscaleDimension}}x{{maxUpscaleDimension}} pixels. Please try a smaller image or decrease your scale selection.",
@ -1848,30 +1760,5 @@
"upscaling": "Upscaling",
"upscalingTab": "$t(ui.tabs.upscaling) $t(common.tab)"
}
},
"system": {
"enableLogging": "Enable Logging",
"logLevel": {
"logLevel": "Log Level",
"trace": "Trace",
"debug": "Debug",
"info": "Info",
"warn": "Warn",
"error": "Error",
"fatal": "Fatal"
},
"logNamespaces": {
"logNamespaces": "Log Namespaces",
"gallery": "Gallery",
"models": "Models",
"config": "Config",
"canvas": "Canvas",
"generation": "Generation",
"workflows": "Workflows",
"system": "System",
"events": "Events",
"queue": "Queue",
"metadata": "Metadata"
}
}
}

View File

@ -929,7 +929,7 @@
"missingInvocationTemplate": "Modello di invocazione mancante",
"missingFieldTemplate": "Modello di campo mancante",
"singleFieldType": "{{name}} (Singola)",
"imageAccessError": "Impossibile trovare l'immagine {{image_name}}, ripristino ai valori predefiniti",
"imageAccessError": "Impossibile trovare l'immagine {{image_name}}, ripristino delle impostazioni predefinite",
"boardAccessError": "Impossibile trovare la bacheca {{board_id}}, ripristino ai valori predefiniti",
"modelAccessError": "Impossibile trovare il modello {{key}}, ripristino ai valori predefiniti"
},
@ -1782,13 +1782,7 @@
"updatePromptTemplate": "Aggiorna il modello di prompt",
"type": "Tipo",
"promptTemplatesDesc2": "Utilizza la stringa segnaposto <Pre>{{placeholder}}</Pre> per specificare dove inserire il tuo prompt nel modello.",
"importTemplates": "Importa modelli di prompt (CSV/JSON)",
"exportDownloaded": "Esportazione completata",
"exportFailed": "Impossibile generare e scaricare il file CSV",
"exportPromptTemplates": "Esporta i miei modelli di prompt (CSV)",
"positivePromptColumn": "'prompt' o 'positive_prompt'",
"noTemplates": "Nessun modello",
"acceptedColumnsKeys": "Colonne/chiavi accettate:",
"templateActions": "Azioni modello"
"importTemplates": "Importa modelli di prompt",
"importTemplatesDesc": "Il formato deve essere un CSV con colonne 'name' e 'prompt' o 'positive_prompt' e 'negative_prompt' incluse, oppure un file JSON con chiavi 'name' e 'prompt' o 'positive_prompt' e 'negative_prompt"
}
}

View File

@ -91,8 +91,7 @@
"enabled": "Включено",
"disabled": "Отключено",
"comparingDesc": "Сравнение двух изображений",
"comparing": "Сравнение",
"dontShowMeThese": "Не показывай мне это"
"comparing": "Сравнение"
},
"gallery": {
"galleryImageSize": "Размер изображений",
@ -154,11 +153,7 @@
"showArchivedBoards": "Показать архивированные доски",
"searchImages": "Поиск по метаданным",
"displayBoardSearch": "Отобразить поиск досок",
"displaySearch": "Отобразить поиск",
"exitBoardSearch": "Выйти из поиска досок",
"go": "Перейти",
"exitSearch": "Выйти из поиска",
"jump": "Пыгнуть"
"displaySearch": "Отобразить поиск"
},
"hotkeys": {
"keyboardShortcuts": "Горячие клавиши",
@ -381,10 +376,6 @@
"toggleViewer": {
"title": "Переключить просмотр изображений",
"desc": "Переключение между средством просмотра изображений и рабочей областью для текущей вкладки."
},
"postProcess": {
"desc": "Обработайте текущее изображение с помощью выбранной модели постобработки",
"title": "Обработать изображение"
}
},
"modelManager": {
@ -598,10 +589,7 @@
"infillColorValue": "Цвет заливки",
"globalSettings": "Глобальные настройки",
"globalNegativePromptPlaceholder": "Глобальный негативный запрос",
"globalPositivePromptPlaceholder": "Глобальный запрос",
"postProcessing": "Постобработка (Shift + U)",
"processImage": "Обработка изображения",
"sendToUpscale": "Отправить на увеличение"
"globalPositivePromptPlaceholder": "Глобальный запрос"
},
"settings": {
"models": "Модели",
@ -635,9 +623,7 @@
"intermediatesCleared_many": "Очищено {{count}} промежуточных",
"clearIntermediatesDesc1": "Очистка промежуточных элементов приведет к сбросу состояния Canvas и ControlNet.",
"intermediatesClearedFailed": "Проблема очистки промежуточных",
"reloadingIn": "Перезагрузка через",
"informationalPopoversDisabled": "Информационные всплывающие окна отключены",
"informationalPopoversDisabledDesc": "Информационные всплывающие окна были отключены. Включите их в Настройках."
"reloadingIn": "Перезагрузка через"
},
"toast": {
"uploadFailed": "Загрузка не удалась",
@ -708,9 +694,7 @@
"sessionRef": "Сессия: {{sessionId}}",
"outOfMemoryError": "Ошибка нехватки памяти",
"outOfMemoryErrorDesc": "Ваши текущие настройки генерации превышают возможности системы. Пожалуйста, измените настройки и повторите попытку.",
"somethingWentWrong": "Что-то пошло не так",
"importFailed": "Импорт неудачен",
"importSuccessful": "Импорт успешен"
"somethingWentWrong": "Что-то пошло не так"
},
"tooltip": {
"feature": {
@ -1033,8 +1017,7 @@
"composition": "Только композиция",
"hed": "HED",
"beginEndStepPercentShort": "Начало/конец %",
"setControlImageDimensionsForce": "Скопируйте размер в Ш/В (игнорируйте модель)",
"depthAnythingSmallV2": "Small V2"
"setControlImageDimensionsForce": "Скопируйте размер в Ш/В (игнорируйте модель)"
},
"boards": {
"autoAddBoard": "Авто добавление Доски",
@ -1059,7 +1042,7 @@
"downloadBoard": "Скачать доску",
"deleteBoard": "Удалить доску",
"deleteBoardAndImages": "Удалить доску и изображения",
"deletedBoardsCannotbeRestored": "Удаленные доски не могут быть восстановлены. Выбор «Удалить только доску» переведет изображения в состояние без категории.",
"deletedBoardsCannotbeRestored": "Удаленные доски не подлежат восстановлению",
"assetsWithCount_one": "{{count}} ассет",
"assetsWithCount_few": "{{count}} ассета",
"assetsWithCount_many": "{{count}} ассетов",
@ -1074,11 +1057,7 @@
"boards": "Доски",
"addPrivateBoard": "Добавить личную доску",
"private": "Личные доски",
"shared": "Общие доски",
"hideBoards": "Скрыть доски",
"viewBoards": "Просмотреть доски",
"noBoards": "Нет досок {{boardType}}",
"deletedPrivateBoardsCannotbeRestored": "Удаленные доски не могут быть восстановлены. Выбор «Удалить только доску» переведет изображения в приватное состояние без категории для создателя изображения."
"shared": "Общие доски"
},
"dynamicPrompts": {
"seedBehaviour": {
@ -1438,30 +1417,6 @@
"paragraphs": [
"Метод, с помощью которого применяется текущий IP-адаптер."
]
},
"structure": {
"paragraphs": [
"Структура контролирует, насколько точно выходное изображение будет соответствовать макету оригинала. Низкая структура допускает значительные изменения, в то время как высокая структура строго сохраняет исходную композицию и макет."
],
"heading": "Структура"
},
"scale": {
"paragraphs": [
"Масштаб управляет размером выходного изображения и основывается на кратном разрешении входного изображения. Например, при увеличении в 2 раза изображения 1024x1024 на выходе получится 2048 x 2048."
],
"heading": "Масштаб"
},
"creativity": {
"paragraphs": [
"Креативность контролирует степень свободы, предоставляемой модели при добавлении деталей. При низкой креативности модель остается близкой к оригинальному изображению, в то время как высокая креативность позволяет вносить больше изменений. При использовании подсказки высокая креативность увеличивает влияние подсказки."
],
"heading": "Креативность"
},
"upscaleModel": {
"heading": "Модель увеличения",
"paragraphs": [
"Модель увеличения масштаба масштабирует изображение до выходного размера перед добавлением деталей. Можно использовать любую поддерживаемую модель масштабирования, но некоторые из них специализированы для различных видов изображений, например фотографий или линейных рисунков."
]
}
},
"metadata": {
@ -1738,78 +1693,7 @@
"canvasTab": "$t(ui.tabs.canvas) $t(common.tab)",
"queueTab": "$t(ui.tabs.queue) $t(common.tab)",
"modelsTab": "$t(ui.tabs.models) $t(common.tab)",
"queue": "Очередь",
"upscaling": "Увеличение",
"upscalingTab": "$t(ui.tabs.upscaling) $t(common.tab)"
"queue": "Очередь"
}
},
"upscaling": {
"exceedsMaxSize": "Параметры масштабирования превышают максимальный размер",
"exceedsMaxSizeDetails": "Максимальный предел масштабирования составляет {{maxUpscaleDimension}}x{{maxUpscaleDimension}} пикселей. Пожалуйста, попробуйте использовать меньшее изображение или уменьшите масштаб.",
"structure": "Структура",
"missingTileControlNetModel": "Не установлены подходящие модели ControlNet",
"missingUpscaleInitialImage": "Отсутствует увеличиваемое изображение",
"missingUpscaleModel": "Отсутствует увеличивающая модель",
"creativity": "Креативность",
"upscaleModel": "Модель увеличения",
"scale": "Масштаб",
"mainModelDesc": "Основная модель (архитектура SD1.5 или SDXL)",
"upscaleModelDesc": "Модель увеличения (img2img)",
"postProcessingModel": "Модель постобработки",
"tileControlNetModelDesc": "Модель ControlNet для выбранной архитектуры основной модели",
"missingModelsWarning": "Зайдите в <LinkComponent>Менеджер моделей</LinkComponent> чтоб установить необходимые модели:",
"postProcessingMissingModelWarning": "Посетите <LinkComponent>Менеджер моделей</LinkComponent>, чтобы установить модель постобработки (img2img)."
},
"stylePresets": {
"noMatchingTemplates": "Нет подходящих шаблонов",
"promptTemplatesDesc1": "Шаблоны подсказок добавляют текст к подсказкам, которые вы пишете в окне подсказок.",
"sharedTemplates": "Общие шаблоны",
"templateDeleted": "Шаблон запроса удален",
"toggleViewMode": "Переключить режим просмотра",
"type": "Тип",
"unableToDeleteTemplate": "Не получилось удалить шаблон запроса",
"viewModeTooltip": "Вот как будет выглядеть ваш запрос с выбранным шаблоном. Чтобы его отредактировать, щелкните в любом месте текстового поля.",
"viewList": "Просмотреть список шаблонов",
"active": "Активно",
"choosePromptTemplate": "Выберите шаблон запроса",
"defaultTemplates": "Стандартные шаблоны",
"deleteImage": "Удалить изображение",
"deleteTemplate": "Удалить шаблон",
"deleteTemplate2": "Вы уверены, что хотите удалить этот шаблон? Это нельзя отменить.",
"editTemplate": "Редактировать шаблон",
"exportPromptTemplates": "Экспорт моих шаблонов запроса (CSV)",
"exportDownloaded": "Экспорт скачан",
"exportFailed": "Невозможно сгенерировать и загрузить CSV",
"flatten": "Объединить выбранный шаблон с текущим запросом",
"acceptedColumnsKeys": "Принимаемые столбцы/ключи:",
"positivePromptColumn": "'prompt' или 'positive_prompt'",
"insertPlaceholder": "Вставить заполнитель",
"name": "Имя",
"negativePrompt": "Негативный запрос",
"promptTemplatesDesc3": "Если вы не используете заполнитель, шаблон будет добавлен в конец запроса.",
"positivePrompt": "Позитивный запрос",
"preview": "Предпросмотр",
"private": "Приватный",
"templateActions": "Действия с шаблоном",
"updatePromptTemplate": "Обновить шаблон запроса",
"uploadImage": "Загрузить изображение",
"useForTemplate": "Использовать для шаблона запроса",
"clearTemplateSelection": "Очистить выбор шаблона",
"copyTemplate": "Копировать шаблон",
"createPromptTemplate": "Создать шаблон запроса",
"importTemplates": "Импортировать шаблоны запроса (CSV/JSON)",
"nameColumn": "'name'",
"negativePromptColumn": "'negative_prompt'",
"myTemplates": "Мои шаблоны",
"noTemplates": "Нет шаблонов",
"promptTemplatesDesc2": "Используйте строку-заполнитель <Pre>{{placeholder}}</Pre>, чтобы указать место, куда должен быть включен ваш запрос в шаблоне.",
"searchByName": "Поиск по имени",
"shared": "Общий"
},
"upsell": {
"inviteTeammates": "Пригласите членов команды",
"professional": "Профессионал",
"professionalUpsell": "Доступно в профессиональной версии Invoke. Нажмите здесь или посетите invoke.com/pricing для получения более подробной информации.",
"shareAccess": "Поделиться доступом"
}
}

View File

@ -38,7 +38,7 @@ async function generateTypes(schema) {
process.stdout.write(`\nOK!\r\n`);
}
function main() {
async function main() {
const encoding = 'utf-8';
if (process.stdin.isTTY) {

View File

@ -6,7 +6,6 @@ import { appStarted } from 'app/store/middleware/listenerMiddleware/listeners/ap
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import type { PartialAppConfig } from 'app/types/invokeai';
import ImageUploadOverlay from 'common/components/ImageUploadOverlay';
import { useScopeFocusWatcher } from 'common/hooks/interactionScopes';
import { useClearStorage } from 'common/hooks/useClearStorage';
import { useFullscreenDropzone } from 'common/hooks/useFullscreenDropzone';
import { useGlobalHotkeys } from 'common/hooks/useGlobalHotkeys';
@ -14,13 +13,12 @@ import ChangeBoardModal from 'features/changeBoardModal/components/ChangeBoardMo
import DeleteImageModal from 'features/deleteImageModal/components/DeleteImageModal';
import { DynamicPromptsModal } from 'features/dynamicPrompts/components/DynamicPromptsPreviewModal';
import { useStarterModelsToast } from 'features/modelManagerV2/hooks/useStarterModelsToast';
import { ClearQueueConfirmationsAlertDialog } from 'features/queue/components/ClearQueueConfirmationAlertDialog';
import { StylePresetModal } from 'features/stylePresets/components/StylePresetForm/StylePresetModal';
import { configChanged } from 'features/system/store/configSlice';
import { selectLanguage } from 'features/system/store/systemSelectors';
import { AppContent } from 'features/ui/components/AppContent';
import { languageSelector } from 'features/system/store/systemSelectors';
import InvokeTabs from 'features/ui/components/InvokeTabs';
import type { InvokeTabName } from 'features/ui/store/tabMap';
import { setActiveTab } from 'features/ui/store/uiSlice';
import type { TabName } from 'features/ui/store/uiTypes';
import { useGetAndLoadLibraryWorkflow } from 'features/workflowLibrary/hooks/useGetAndLoadLibraryWorkflow';
import { AnimatePresence } from 'framer-motion';
import i18n from 'i18n';
@ -41,11 +39,11 @@ interface Props {
action: 'sendToImg2Img' | 'sendToCanvas' | 'useAllParameters';
};
selectedWorkflowId?: string;
destination?: TabName | undefined;
destination?: InvokeTabName | undefined;
}
const App = ({ config = DEFAULT_CONFIG, selectedImage, selectedWorkflowId, destination }: Props) => {
const language = useAppSelector(selectLanguage);
const language = useAppSelector(languageSelector);
const logger = useLogger('system');
const dispatch = useAppDispatch();
const clearStorage = useClearStorage();
@ -95,7 +93,6 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage, selectedWorkflowId, desti
useStarterModelsToast();
useSyncQueueStatus();
useScopeFocusWatcher();
return (
<ErrorBoundary onReset={handleReset} FallbackComponent={AppErrorBoundaryFallback}>
@ -108,7 +105,7 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage, selectedWorkflowId, desti
{...dropzone.getRootProps()}
>
<input {...dropzone.getInputProps()} />
<AppContent />
<InvokeTabs />
<AnimatePresence>
{dropzone.isDragActive && isHandlingUpload && (
<ImageUploadOverlay dropzone={dropzone} setIsHandlingUpload={setIsHandlingUpload} />
@ -119,7 +116,6 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage, selectedWorkflowId, desti
<ChangeBoardModal />
<DynamicPromptsModal />
<StylePresetModal />
<ClearQueueConfirmationsAlertDialog />
<PreselectedImage selectedImage={selectedImage} />
</ErrorBoundary>
);

View File

@ -1,7 +1,5 @@
import { Button, Flex, Heading, Image, Link, Text } from '@invoke-ai/ui-library';
import { createSelector } from '@reduxjs/toolkit';
import { useAppSelector } from 'app/store/storeHooks';
import { selectConfigSlice } from 'features/system/store/configSlice';
import { toast } from 'features/toast/toast';
import newGithubIssueUrl from 'new-github-issue-url';
import InvokeLogoYellow from 'public/assets/images/invoke-symbol-ylw-lrg.svg';
@ -15,11 +13,9 @@ type Props = {
resetErrorBoundary: () => void;
};
const selectIsLocal = createSelector(selectConfigSlice, (config) => config.isLocal);
const AppErrorBoundaryFallback = ({ error, resetErrorBoundary }: Props) => {
const { t } = useTranslation();
const isLocal = useAppSelector(selectIsLocal);
const isLocal = useAppSelector((s) => s.config.isLocal);
const handleCopy = useCallback(() => {
const text = JSON.stringify(serializeError(error), null, 2);

View File

@ -19,7 +19,7 @@ import type { PartialAppConfig } from 'app/types/invokeai';
import Loading from 'common/components/Loading/Loading';
import AppDndContext from 'features/dnd/components/AppDndContext';
import type { WorkflowCategory } from 'features/nodes/types/workflow';
import type { TabName } from 'features/ui/store/uiTypes';
import type { InvokeTabName } from 'features/ui/store/tabMap';
import type { PropsWithChildren, ReactNode } from 'react';
import React, { lazy, memo, useEffect, useMemo } from 'react';
import { Provider } from 'react-redux';
@ -45,7 +45,7 @@ interface Props extends PropsWithChildren {
action: 'sendToImg2Img' | 'sendToCanvas' | 'useAllParameters';
};
selectedWorkflowId?: string;
destination?: TabName;
destination?: InvokeTabName;
customStarUi?: CustomStarUi;
socketOptions?: Partial<ManagerOptions & SocketOptions>;
isDebugging?: boolean;

View File

@ -2,7 +2,7 @@ import { useStore } from '@nanostores/react';
import { $authToken } from 'app/store/nanostores/authToken';
import { $baseUrl } from 'app/store/nanostores/baseUrl';
import { $isDebugging } from 'app/store/nanostores/isDebugging';
import { useAppStore } from 'app/store/nanostores/store';
import { useAppDispatch } from 'app/store/storeHooks';
import type { MapStore } from 'nanostores';
import { atom, map } from 'nanostores';
import { useEffect, useMemo } from 'react';
@ -18,19 +18,14 @@ declare global {
}
}
export type AppSocket = Socket<ServerToClientEvents, ClientToServerEvents>;
export const $socket = atom<AppSocket | null>(null);
export const $socketOptions = map<Partial<ManagerOptions & SocketOptions>>({});
const $isSocketInitialized = atom<boolean>(false);
export const $isConnected = atom<boolean>(false);
/**
* Initializes the socket.io connection and sets up event listeners.
*/
export const useSocketIO = () => {
const { dispatch, getState } = useAppStore();
const dispatch = useAppDispatch();
const baseUrl = useStore($baseUrl);
const authToken = useStore($authToken);
const addlSocketOptions = useStore($socketOptions);
@ -66,9 +61,8 @@ export const useSocketIO = () => {
return;
}
const socket: AppSocket = io(socketUrl, socketOptions);
$socket.set(socket);
setEventListeners({ socket, dispatch, getState, setIsConnected: $isConnected.set });
const socket: Socket<ServerToClientEvents, ClientToServerEvents> = io(socketUrl, socketOptions);
setEventListeners({ dispatch, socket });
socket.connect();
if ($isDebugging.get() || import.meta.env.MODE === 'development') {
@ -90,5 +84,5 @@ export const useSocketIO = () => {
socket.disconnect();
$isSocketInitialized.set(false);
};
}, [dispatch, getState, socketOptions, socketUrl]);
}, [dispatch, socketOptions, socketUrl]);
};

View File

@ -15,21 +15,21 @@ export const BASE_CONTEXT = {};
export const $logger = atom<Logger>(Roarr.child(BASE_CONTEXT));
export const zLogNamespace = z.enum([
'canvas',
'config',
'events',
'gallery',
'generation',
'metadata',
'models',
'system',
'queue',
'workflows',
]);
export type LogNamespace = z.infer<typeof zLogNamespace>;
export type LoggerNamespace =
| 'images'
| 'models'
| 'config'
| 'canvas'
| 'generation'
| 'nodes'
| 'system'
| 'socketio'
| 'session'
| 'queue'
| 'dnd'
| 'controlLayers';
export const logger = (namespace: LogNamespace) => $logger.get().child({ namespace });
export const logger = (namespace: LoggerNamespace) => $logger.get().child({ namespace });
export const zLogLevel = z.enum(['trace', 'debug', 'info', 'warn', 'error', 'fatal']);
export type LogLevel = z.infer<typeof zLogLevel>;

View File

@ -1,41 +1,29 @@
import { createLogWriter } from '@roarr/browser-log-writer';
import { useAppSelector } from 'app/store/storeHooks';
import {
selectSystemLogIsEnabled,
selectSystemLogLevel,
selectSystemLogNamespaces,
} from 'features/system/store/systemSlice';
import { useEffect, useMemo } from 'react';
import { ROARR, Roarr } from 'roarr';
import type { LogNamespace } from './logger';
import type { LoggerNamespace } from './logger';
import { $logger, BASE_CONTEXT, LOG_LEVEL_MAP, logger } from './logger';
export const useLogger = (namespace: LogNamespace) => {
const logLevel = useAppSelector(selectSystemLogLevel);
const logNamespaces = useAppSelector(selectSystemLogNamespaces);
const logIsEnabled = useAppSelector(selectSystemLogIsEnabled);
export const useLogger = (namespace: LoggerNamespace) => {
const consoleLogLevel = useAppSelector((s) => s.system.consoleLogLevel);
const shouldLogToConsole = useAppSelector((s) => s.system.shouldLogToConsole);
// The provided Roarr browser log writer uses localStorage to config logging to console
useEffect(() => {
if (logIsEnabled) {
if (shouldLogToConsole) {
// Enable console log output
localStorage.setItem('ROARR_LOG', 'true');
// Use a filter to show only logs of the given level
let filter = `context.logLevel:>=${LOG_LEVEL_MAP[logLevel]}`;
if (logNamespaces.length > 0) {
filter += ` AND (${logNamespaces.map((ns) => `context.namespace:${ns}`).join(' OR ')})`;
} else {
filter += ' AND context.namespace:undefined';
}
localStorage.setItem('ROARR_FILTER', filter);
localStorage.setItem('ROARR_FILTER', `context.logLevel:>=${LOG_LEVEL_MAP[consoleLogLevel]}`);
} else {
// Disable console log output
localStorage.setItem('ROARR_LOG', 'false');
}
ROARR.write = createLogWriter();
}, [logLevel, logIsEnabled, logNamespaces]);
}, [consoleLogLevel, shouldLogToConsole]);
// Update the module-scoped logger context as needed
useEffect(() => {

View File

@ -1,7 +1,7 @@
import { createAction } from '@reduxjs/toolkit';
import type { TabName } from 'features/ui/store/uiTypes';
import type { InvokeTabName } from 'features/ui/store/tabMap';
export const enqueueRequested = createAction<{
tabName: TabName;
tabName: InvokeTabName;
prepend: boolean;
}>('app/enqueueRequested');

View File

@ -1,3 +1,2 @@
export const STORAGE_PREFIX = '@@invokeai-';
export const EMPTY_ARRAY = [];
export const EMPTY_OBJECT = {};

View File

@ -1,6 +1,5 @@
import { createDraftSafeSelectorCreator, createSelectorCreator, lruMemoize } from '@reduxjs/toolkit';
import type { GetSelectorsOptions } from '@reduxjs/toolkit/dist/entities/state_selectors';
import type { RootState } from 'app/store/store';
import { isEqual } from 'lodash-es';
/**
@ -20,5 +19,3 @@ export const getSelectorsOptions: GetSelectorsOptions = {
argsMemoize: lruMemoize,
}),
};
export const createMemoizedAppSelector = createMemoizedSelector.withTypes<RootState>();

View File

@ -1,4 +1,5 @@
import { logger } from 'app/logging/logger';
import { parseify } from 'common/util/serialize';
import { PersistError, RehydrateError } from 'redux-remember';
import { serializeError } from 'serialize-error';
@ -40,6 +41,6 @@ export const errorHandler = (err: PersistError | RehydrateError) => {
} else if (err instanceof RehydrateError) {
log.error({ error: serializeError(err) }, 'Problem rehydrating state');
} else {
log.error({ error: serializeError(err) }, 'Problem in persistence layer');
log.error({ error: parseify(err) }, 'Problem in persistence layer');
}
};

View File

@ -1,7 +1,9 @@
import type { UnknownAction } from '@reduxjs/toolkit';
import { deepClone } from 'common/util/deepClone';
import { isAnyGraphBuilt } from 'features/nodes/store/actions';
import { appInfoApi } from 'services/api/endpoints/appInfo';
import type { Graph } from 'services/api/types';
import { socketGeneratorProgress } from 'services/events/actions';
export const actionSanitizer = <A extends UnknownAction>(action: A): A => {
if (isAnyGraphBuilt(action)) {
@ -22,5 +24,13 @@ export const actionSanitizer = <A extends UnknownAction>(action: A): A => {
};
}
if (socketGeneratorProgress.match(action)) {
const sanitized = deepClone(action);
if (sanitized.payload.data.progress_image) {
sanitized.payload.data.progress_image.dataURL = '<Progress image omitted>';
}
return sanitized;
}
return action;
};

View File

@ -1,7 +1,7 @@
import type { TypedStartListening } from '@reduxjs/toolkit';
import { createListenerMiddleware } from '@reduxjs/toolkit';
import { addAdHocPostProcessingRequestedListener } from 'app/store/middleware/listenerMiddleware/listeners/addAdHocPostProcessingRequestedListener';
import { addStagingListeners } from 'app/store/middleware/listenerMiddleware/listeners/addCommitStagingAreaImageListener';
import { addCommitStagingAreaImageListener } from 'app/store/middleware/listenerMiddleware/listeners/addCommitStagingAreaImageListener';
import { addAnyEnqueuedListener } from 'app/store/middleware/listenerMiddleware/listeners/anyEnqueued';
import { addAppConfigReceivedListener } from 'app/store/middleware/listenerMiddleware/listeners/appConfigReceived';
import { addAppStartedListener } from 'app/store/middleware/listenerMiddleware/listeners/appStarted';
@ -9,6 +9,17 @@ import { addBatchEnqueuedListener } from 'app/store/middleware/listenerMiddlewar
import { addDeleteBoardAndImagesFulfilledListener } from 'app/store/middleware/listenerMiddleware/listeners/boardAndImagesDeleted';
import { addBoardIdSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/boardIdSelected';
import { addBulkDownloadListeners } from 'app/store/middleware/listenerMiddleware/listeners/bulkDownload';
import { addCanvasCopiedToClipboardListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasCopiedToClipboard';
import { addCanvasDownloadedAsImageListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasDownloadedAsImage';
import { addCanvasImageToControlNetListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasImageToControlNet';
import { addCanvasMaskSavedToGalleryListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasMaskSavedToGallery';
import { addCanvasMaskToControlNetListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasMaskToControlNet';
import { addCanvasMergedListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasMerged';
import { addCanvasSavedToGalleryListener } from 'app/store/middleware/listenerMiddleware/listeners/canvasSavedToGallery';
import { addControlAdapterPreprocessor } from 'app/store/middleware/listenerMiddleware/listeners/controlAdapterPreprocessor';
import { addControlNetAutoProcessListener } from 'app/store/middleware/listenerMiddleware/listeners/controlNetAutoProcess';
import { addControlNetImageProcessedListener } from 'app/store/middleware/listenerMiddleware/listeners/controlNetImageProcessed';
import { addEnqueueRequestedCanvasListener } from 'app/store/middleware/listenerMiddleware/listeners/enqueueRequestedCanvas';
import { addEnqueueRequestedLinear } from 'app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear';
import { addEnqueueRequestedNodes } from 'app/store/middleware/listenerMiddleware/listeners/enqueueRequestedNodes';
import { addGalleryImageClickedListener } from 'app/store/middleware/listenerMiddleware/listeners/galleryImageClicked';
@ -26,7 +37,16 @@ import { addModelSelectedListener } from 'app/store/middleware/listenerMiddlewar
import { addModelsLoadedListener } from 'app/store/middleware/listenerMiddleware/listeners/modelsLoaded';
import { addDynamicPromptsListener } from 'app/store/middleware/listenerMiddleware/listeners/promptChanged';
import { addSetDefaultSettingsListener } from 'app/store/middleware/listenerMiddleware/listeners/setDefaultSettings';
import { addSocketConnectedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketConnected';
import { addSocketConnectedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketConnected';
import { addSocketDisconnectedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketDisconnected';
import { addGeneratorProgressEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketGeneratorProgress';
import { addInvocationCompleteEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationComplete';
import { addInvocationErrorEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationError';
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 { addStagingAreaImageSavedListener } from 'app/store/middleware/listenerMiddleware/listeners/stagingAreaImageSaved';
import { addUpdateAllNodesRequestedListener } from 'app/store/middleware/listenerMiddleware/listeners/updateAllNodesRequested';
import { addWorkflowLoadRequestedListener } from 'app/store/middleware/listenerMiddleware/listeners/workflowLoadRequested';
import type { AppDispatch, RootState } from 'app/store/store';
@ -63,6 +83,7 @@ addGalleryImageClickedListener(startAppListening);
addGalleryOffsetChangedListener(startAppListening);
// User Invoked
addEnqueueRequestedCanvasListener(startAppListening);
addEnqueueRequestedNodes(startAppListening);
addEnqueueRequestedLinear(startAppListening);
addEnqueueRequestedUpscale(startAppListening);
@ -70,23 +91,32 @@ addAnyEnqueuedListener(startAppListening);
addBatchEnqueuedListener(startAppListening);
// Canvas actions
// addCanvasSavedToGalleryListener(startAppListening);
// addCanvasMaskSavedToGalleryListener(startAppListening);
// addCanvasImageToControlNetListener(startAppListening);
// addCanvasMaskToControlNetListener(startAppListening);
// addCanvasDownloadedAsImageListener(startAppListening);
// addCanvasCopiedToClipboardListener(startAppListening);
// addCanvasMergedListener(startAppListening);
// addStagingAreaImageSavedListener(startAppListening);
// addCommitStagingAreaImageListener(startAppListening);
addStagingListeners(startAppListening);
addCanvasSavedToGalleryListener(startAppListening);
addCanvasMaskSavedToGalleryListener(startAppListening);
addCanvasImageToControlNetListener(startAppListening);
addCanvasMaskToControlNetListener(startAppListening);
addCanvasDownloadedAsImageListener(startAppListening);
addCanvasCopiedToClipboardListener(startAppListening);
addCanvasMergedListener(startAppListening);
addStagingAreaImageSavedListener(startAppListening);
addCommitStagingAreaImageListener(startAppListening);
// Socket.IO
addGeneratorProgressEventListener(startAppListening);
addInvocationCompleteEventListener(startAppListening);
addInvocationErrorEventListener(startAppListening);
addInvocationStartedEventListener(startAppListening);
addSocketConnectedEventListener(startAppListening);
// Gallery bulk download
addSocketDisconnectedEventListener(startAppListening);
addModelLoadEventListener(startAppListening);
addModelInstallEventListener(startAppListening);
addSocketQueueItemStatusChangedEventListener(startAppListening);
addBulkDownloadListeners(startAppListening);
// ControlNet
addControlNetImageProcessedListener(startAppListening);
addControlNetAutoProcessListener(startAppListening);
// Boards
addImageAddedToBoardFulfilledListener(startAppListening);
addImageRemovedFromBoardFulfilledListener(startAppListening);
@ -118,4 +148,4 @@ addAdHocPostProcessingRequestedListener(startAppListening);
addDynamicPromptsListener(startAppListening);
addSetDefaultSettingsListener(startAppListening);
// addControlAdapterPreprocessor(startAppListening);
addControlAdapterPreprocessor(startAppListening);

View File

@ -1,21 +1,21 @@
import { createAction } from '@reduxjs/toolkit';
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import type { SerializableObject } from 'common/types';
import { parseify } from 'common/util/serialize';
import { buildAdHocPostProcessingGraph } from 'features/nodes/util/graph/buildAdHocPostProcessingGraph';
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';
const log = logger('queue');
export const adHocPostProcessingRequested = createAction<{ imageDTO: ImageDTO }>(`upscaling/postProcessingRequested`);
export const addAdHocPostProcessingRequestedListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: adHocPostProcessingRequested,
effect: async (action, { dispatch, getState }) => {
const log = logger('session');
const { imageDTO } = action.payload;
const state = getState();
@ -39,9 +39,9 @@ export const addAdHocPostProcessingRequestedListener = (startAppListening: AppSt
const enqueueResult = await req.unwrap();
req.reset();
log.debug({ enqueueResult } as SerializableObject, t('queue.graphQueued'));
log.debug({ enqueueResult: parseify(enqueueResult) }, t('queue.graphQueued'));
} catch (error) {
log.error({ enqueueBatchArg } as SerializableObject, t('queue.graphFailedToQueue'));
log.error({ enqueueBatchArg: parseify(enqueueBatchArg) }, t('queue.graphFailedToQueue'));
if (error instanceof Object && 'status' in error && error.status === 403) {
return;

View File

@ -23,7 +23,7 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
*/
startAppListening({
matcher: matchAnyBoardDeleted,
effect: (action, { dispatch, getState }) => {
effect: async (action, { dispatch, getState }) => {
const state = getState();
const deletedBoardId = action.meta.arg.originalArgs;
const { autoAddBoardId, selectedBoardId } = state.gallery;
@ -44,7 +44,7 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
// If we archived a board, it may end up hidden. If it's selected or the auto-add board, we should reset those.
startAppListening({
matcher: boardsApi.endpoints.updateBoard.matchFulfilled,
effect: (action, { dispatch, getState }) => {
effect: async (action, { dispatch, getState }) => {
const state = getState();
const { shouldShowArchivedBoards } = state.gallery;
@ -61,7 +61,7 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
// When we hide archived boards, if the selected or the auto-add board is archived, we should reset those.
startAppListening({
actionCreator: shouldShowArchivedBoardsChanged,
effect: (action, { dispatch, getState }) => {
effect: async (action, { dispatch, getState }) => {
const shouldShowArchivedBoards = action.payload;
// We only need to take action if we have just hidden archived boards.
@ -100,7 +100,7 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
*/
startAppListening({
matcher: boardsApi.endpoints.listAllBoards.matchFulfilled,
effect: (action, { dispatch, getState }) => {
effect: async (action, { dispatch, getState }) => {
const boards = action.payload;
const state = getState();
const { selectedBoardId, autoAddBoardId } = state.gallery;

View File

@ -1,37 +1,33 @@
import { isAnyOf } from '@reduxjs/toolkit';
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import {
sessionStagingAreaImageAccepted,
sessionStagingAreaReset,
} from 'features/controlLayers/store/canvasSessionSlice';
import { rasterLayerAdded } from 'features/controlLayers/store/canvasSlice';
import { selectCanvasSlice } from 'features/controlLayers/store/selectors';
import type { CanvasRasterLayerState } from 'features/controlLayers/store/types';
import { imageDTOToImageObject } from 'features/controlLayers/store/types';
canvasBatchIdsReset,
commitStagingAreaImage,
discardStagedImages,
resetCanvas,
setInitialCanvasImage,
} from 'features/canvas/store/canvasSlice';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { queueApi } from 'services/api/endpoints/queue';
import { $lastCanvasProgressEvent } from 'services/events/setEventListeners';
import { assert } from 'tsafe';
const log = logger('canvas');
const matcher = isAnyOf(commitStagingAreaImage, discardStagedImages, resetCanvas, setInitialCanvasImage);
export const addStagingListeners = (startAppListening: AppStartListening) => {
export const addCommitStagingAreaImageListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: sessionStagingAreaReset,
effect: async (_, { dispatch }) => {
matcher,
effect: async (_, { dispatch, getState }) => {
const log = logger('canvas');
const state = getState();
const { batchIds } = state.canvas;
try {
const req = dispatch(
queueApi.endpoints.cancelByBatchOrigin.initiate(
{ origin: 'canvas' },
{ fixedCacheKey: 'cancelByBatchOrigin' }
)
queueApi.endpoints.cancelByBatchIds.initiate({ batch_ids: batchIds }, { fixedCacheKey: 'cancelByBatchIds' })
);
const { canceled } = await req.unwrap();
req.reset();
$lastCanvasProgressEvent.set(null);
if (canceled > 0) {
log.debug(`Canceled ${canceled} canvas batches`);
toast({
@ -40,6 +36,7 @@ export const addStagingListeners = (startAppListening: AppStartListening) => {
status: 'success',
});
}
dispatch(canvasBatchIdsReset());
} catch {
log.error('Failed to cancel canvas batches');
toast({
@ -50,26 +47,4 @@ export const addStagingListeners = (startAppListening: AppStartListening) => {
}
},
});
startAppListening({
actionCreator: sessionStagingAreaImageAccepted,
effect: (action, api) => {
const { index } = action.payload;
const state = api.getState();
const stagingAreaImage = state.canvasSession.stagedImages[index];
assert(stagingAreaImage, 'No staged image found to accept');
const { x, y } = selectCanvasSlice(state).bbox.rect;
const { imageDTO, offsetX, offsetY } = stagingAreaImage;
const imageObject = imageDTOToImageObject(imageDTO);
const overrides: Partial<CanvasRasterLayerState> = {
position: { x: x + offsetX, y: y + offsetY },
objects: [imageObject],
};
api.dispatch(rasterLayerAdded({ overrides, isSelected: true }));
api.dispatch(sessionStagingAreaReset());
},
});
};

View File

@ -4,7 +4,7 @@ import { queueApi, selectQueueStatus } from 'services/api/endpoints/queue';
export const addAnyEnqueuedListener = (startAppListening: AppStartListening) => {
startAppListening({
matcher: queueApi.endpoints.enqueueBatch.matchFulfilled,
effect: (_, { dispatch, getState }) => {
effect: async (_, { dispatch, getState }) => {
const { data } = selectQueueStatus(getState());
if (!data || data.processor.is_started) {

View File

@ -1,14 +1,14 @@
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { setInfillMethod } from 'features/controlLayers/store/paramsSlice';
import { setInfillMethod } from 'features/parameters/store/generationSlice';
import { shouldUseNSFWCheckerChanged, shouldUseWatermarkerChanged } from 'features/system/store/systemSlice';
import { appInfoApi } from 'services/api/endpoints/appInfo';
export const addAppConfigReceivedListener = (startAppListening: AppStartListening) => {
startAppListening({
matcher: appInfoApi.endpoints.getAppConfig.matchFulfilled,
effect: (action, { getState, dispatch }) => {
effect: async (action, { getState, dispatch }) => {
const { infill_methods = [], nsfw_methods = [], watermarking_methods = [] } = action.payload;
const infillMethod = getState().params.infillMethod;
const infillMethod = getState().generation.infillMethod;
if (!infill_methods.includes(infillMethod)) {
// if there is no infill method, set it to the first one

View File

@ -6,7 +6,7 @@ export const appStarted = createAction('app/appStarted');
export const addAppStartedListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: appStarted,
effect: (action, { unsubscribe, cancelActiveListeners }) => {
effect: async (action, { unsubscribe, cancelActiveListeners }) => {
// this should only run once
cancelActiveListeners();
unsubscribe();

View File

@ -1,30 +1,27 @@
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import type { SerializableObject } from 'common/types';
import { parseify } from 'common/util/serialize';
import { zPydanticValidationError } from 'features/system/store/zodSchemas';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { truncate, upperFirst } from 'lodash-es';
import { serializeError } from 'serialize-error';
import { queueApi } from 'services/api/endpoints/queue';
const log = logger('queue');
export const addBatchEnqueuedListener = (startAppListening: AppStartListening) => {
// success
startAppListening({
matcher: queueApi.endpoints.enqueueBatch.matchFulfilled,
effect: (action) => {
const enqueueResult = action.payload;
effect: async (action) => {
const response = action.payload;
const arg = action.meta.arg.originalArgs;
log.debug({ enqueueResult } as SerializableObject, 'Batch enqueued');
logger('queue').debug({ enqueueResult: parseify(response) }, 'Batch enqueued');
toast({
id: 'QUEUE_BATCH_SUCCEEDED',
title: t('queue.batchQueued'),
status: 'success',
description: t('queue.batchQueuedDesc', {
count: enqueueResult.enqueued,
count: response.enqueued,
direction: arg.prepend ? t('queue.front') : t('queue.back'),
}),
});
@ -34,9 +31,9 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
// error
startAppListening({
matcher: queueApi.endpoints.enqueueBatch.matchRejected,
effect: (action) => {
effect: async (action) => {
const response = action.payload;
const batchConfig = action.meta.arg.originalArgs;
const arg = action.meta.arg.originalArgs;
if (!response) {
toast({
@ -45,7 +42,7 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
status: 'error',
description: t('common.unknownError'),
});
log.error({ batchConfig } as SerializableObject, t('queue.batchFailedToQueue'));
logger('queue').error({ batchConfig: parseify(arg), error: parseify(response) }, t('queue.batchFailedToQueue'));
return;
}
@ -71,7 +68,7 @@ export const addBatchEnqueuedListener = (startAppListening: AppStartListening) =
description: t('common.unknownError'),
});
}
log.error({ batchConfig, error: serializeError(response) } as SerializableObject, t('queue.batchFailedToQueue'));
logger('queue').error({ batchConfig: parseify(arg), error: parseify(response) }, t('queue.batchFailedToQueue'));
},
});
};

View File

@ -1,31 +1,47 @@
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { selectCanvasSlice } from 'features/controlLayers/store/selectors';
import { resetCanvas } from 'features/canvas/store/canvasSlice';
import { controlAdaptersReset } from 'features/controlAdapters/store/controlAdaptersSlice';
import { allLayersDeleted } from 'features/controlLayers/store/controlLayersSlice';
import { getImageUsage } from 'features/deleteImageModal/store/selectors';
import { nodeEditorReset } from 'features/nodes/store/nodesSlice';
import { selectNodesSlice } from 'features/nodes/store/selectors';
import { imagesApi } from 'services/api/endpoints/images';
export const addDeleteBoardAndImagesFulfilledListener = (startAppListening: AppStartListening) => {
startAppListening({
matcher: imagesApi.endpoints.deleteBoardAndImages.matchFulfilled,
effect: (action, { dispatch, getState }) => {
effect: async (action, { dispatch, getState }) => {
const { deleted_images } = action.payload;
// Remove all deleted images from the UI
let wasCanvasReset = false;
let wasNodeEditorReset = false;
let wereControlAdaptersReset = false;
let wereControlLayersReset = false;
const state = getState();
const nodes = selectNodesSlice(state);
const canvas = selectCanvasSlice(state);
const { canvas, nodes, controlAdapters, controlLayers } = getState();
deleted_images.forEach((image_name) => {
const imageUsage = getImageUsage(nodes, canvas, image_name);
const imageUsage = getImageUsage(canvas, nodes.present, controlAdapters, controlLayers.present, image_name);
if (imageUsage.isCanvasImage && !wasCanvasReset) {
dispatch(resetCanvas());
wasCanvasReset = true;
}
if (imageUsage.isNodesImage && !wasNodeEditorReset) {
dispatch(nodeEditorReset());
wasNodeEditorReset = true;
}
if (imageUsage.isControlImage && !wereControlAdaptersReset) {
dispatch(controlAdaptersReset());
wereControlAdaptersReset = true;
}
if (imageUsage.isControlLayerImage && !wereControlLayersReset) {
dispatch(allLayersDeleted());
wereControlLayersReset = true;
}
});
},
});

View File

@ -1,15 +1,21 @@
import { ExternalLink } from '@invoke-ai/ui-library';
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { imagesApi } from 'services/api/endpoints/images';
import {
socketBulkDownloadComplete,
socketBulkDownloadError,
socketBulkDownloadStarted,
} from 'services/events/actions';
const log = logger('gallery');
const log = logger('images');
export const addBulkDownloadListeners = (startAppListening: AppStartListening) => {
startAppListening({
matcher: imagesApi.endpoints.bulkDownloadImages.matchFulfilled,
effect: (action) => {
effect: async (action) => {
log.debug(action.payload, 'Bulk download requested');
// If we have an item name, we are processing the bulk download locally and should use it as the toast id to
@ -27,7 +33,7 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
startAppListening({
matcher: imagesApi.endpoints.bulkDownloadImages.matchRejected,
effect: () => {
effect: async () => {
log.debug('Bulk download request failed');
// There isn't any toast to update if we get this event.
@ -38,4 +44,55 @@ export const addBulkDownloadListeners = (startAppListening: AppStartListening) =
});
},
});
startAppListening({
actionCreator: socketBulkDownloadStarted,
effect: async (action) => {
// This should always happen immediately after the bulk download request, so we don't need to show a toast here.
log.debug(action.payload.data, 'Bulk download preparation started');
},
});
startAppListening({
actionCreator: socketBulkDownloadComplete,
effect: async (action) => {
log.debug(action.payload.data, 'Bulk download preparation completed');
const { bulk_download_item_name } = action.payload.data;
// 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}`;
toast({
id: bulk_download_item_name,
title: t('gallery.bulkDownloadReady', 'Download ready'),
status: 'success',
description: (
<ExternalLink
label={t('gallery.clickToDownload', 'Click here to download')}
href={url}
download={bulk_download_item_name}
/>
),
duration: null,
});
},
});
startAppListening({
actionCreator: socketBulkDownloadError,
effect: async (action) => {
log.debug(action.payload.data, 'Bulk download preparation failed');
const { bulk_download_item_name } = action.payload.data;
toast({
id: bulk_download_item_name,
title: t('gallery.bulkDownloadFailed'),
status: 'error',
description: action.payload.data.error,
duration: null,
});
},
});
};

View File

@ -0,0 +1,38 @@
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 { 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, { getState }) => {
const moduleLog = $logger.get().child({ namespace: 'canvasCopiedToClipboardListener' });
const state = getState();
try {
const blob = getBaseLayerBlob(state);
copyBlobToClipboard(blob);
} catch (err) {
moduleLog.error(String(err));
toast({
id: 'CANVAS_COPY_FAILED',
title: t('toast.problemCopyingCanvas'),
description: t('toast.problemCopyingCanvasDesc'),
status: 'error',
});
return;
}
toast({
id: 'CANVAS_COPY_SUCCEEDED',
title: t('toast.canvasCopiedClipboard'),
status: 'success',
});
},
});
};

View File

@ -0,0 +1,34 @@
import { $logger } from 'app/logging/logger';
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 { toast } from 'features/toast/toast';
import { t } from 'i18next';
export const addCanvasDownloadedAsImageListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: canvasDownloadedAsImage,
effect: async (action, { getState }) => {
const moduleLog = $logger.get().child({ namespace: 'canvasSavedToGalleryListener' });
const state = getState();
let blob;
try {
blob = await getBaseLayerBlob(state);
} catch (err) {
moduleLog.error(String(err));
toast({
id: 'CANVAS_DOWNLOAD_FAILED',
title: t('toast.problemDownloadingCanvas'),
description: t('toast.problemDownloadingCanvasDesc'),
status: 'error',
});
return;
}
downloadBlob(blob, 'canvas.png');
toast({ id: 'CANVAS_DOWNLOAD_SUCCEEDED', title: t('toast.canvasDownloaded'), status: 'success' });
},
});
};

View File

@ -0,0 +1,60 @@
import { logger } from 'app/logging/logger';
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 { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { imagesApi } from 'services/api/endpoints/images';
export const addCanvasImageToControlNetListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: canvasImageToControlAdapter,
effect: async (action, { dispatch, getState }) => {
const log = logger('canvas');
const state = getState();
const { id } = action.payload;
let blob: Blob;
try {
blob = await getBaseLayerBlob(state, true);
} catch (err) {
log.error(String(err));
toast({
id: 'PROBLEM_SAVING_CANVAS',
title: t('toast.problemSavingCanvas'),
description: t('toast.problemSavingCanvasDesc'),
status: 'error',
});
return;
}
const { autoAddBoardId } = state.gallery;
const imageDTO = await dispatch(
imagesApi.endpoints.uploadImage.initiate({
file: new File([blob], 'savedCanvas.png', {
type: 'image/png',
}),
image_category: 'control',
is_intermediate: true,
board_id: autoAddBoardId === 'none' ? undefined : autoAddBoardId,
crop_visible: false,
postUploadAction: {
type: 'TOAST',
title: t('toast.canvasSentControlnetAssets'),
},
})
).unwrap();
const { image_name } = imageDTO;
dispatch(
controlAdapterImageChanged({
id,
controlImage: image_name,
})
);
},
});
};

View File

@ -0,0 +1,60 @@
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 { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { imagesApi } from 'services/api/endpoints/images';
export const addCanvasMaskSavedToGalleryListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: canvasMaskSavedToGallery,
effect: async (action, { dispatch, getState }) => {
const log = logger('canvas');
const state = getState();
const canvasBlobsAndImageData = await getCanvasData(
state.canvas.layerState,
state.canvas.boundingBoxCoordinates,
state.canvas.boundingBoxDimensions,
state.canvas.isMaskEnabled,
state.canvas.shouldPreserveMaskedArea
);
if (!canvasBlobsAndImageData) {
return;
}
const { maskBlob } = canvasBlobsAndImageData;
if (!maskBlob) {
log.error('Problem getting mask layer blob');
toast({
id: 'PROBLEM_SAVING_MASK',
title: t('toast.problemSavingMask'),
description: t('toast.problemSavingMaskDesc'),
status: 'error',
});
return;
}
const { autoAddBoardId } = state.gallery;
dispatch(
imagesApi.endpoints.uploadImage.initiate({
file: new File([maskBlob], 'canvasMaskImage.png', {
type: 'image/png',
}),
image_category: 'mask',
is_intermediate: false,
board_id: autoAddBoardId === 'none' ? undefined : autoAddBoardId,
crop_visible: true,
postUploadAction: {
type: 'TOAST',
title: t('toast.maskSavedAssets'),
},
})
);
},
});
};

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import { logger } from 'app/logging/logger';
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 { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { imagesApi } from 'services/api/endpoints/images';
export const addCanvasMaskToControlNetListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: canvasMaskToControlAdapter,
effect: async (action, { dispatch, getState }) => {
const log = logger('canvas');
const state = getState();
const { id } = action.payload;
const canvasBlobsAndImageData = await getCanvasData(
state.canvas.layerState,
state.canvas.boundingBoxCoordinates,
state.canvas.boundingBoxDimensions,
state.canvas.isMaskEnabled,
state.canvas.shouldPreserveMaskedArea
);
if (!canvasBlobsAndImageData) {
return;
}
const { maskBlob } = canvasBlobsAndImageData;
if (!maskBlob) {
log.error('Problem getting mask layer blob');
toast({
id: 'PROBLEM_IMPORTING_MASK',
title: t('toast.problemImportingMask'),
description: t('toast.problemImportingMaskDesc'),
status: 'error',
});
return;
}
const { autoAddBoardId } = state.gallery;
const imageDTO = await dispatch(
imagesApi.endpoints.uploadImage.initiate({
file: new File([maskBlob], 'canvasMaskImage.png', {
type: 'image/png',
}),
image_category: 'mask',
is_intermediate: true,
board_id: autoAddBoardId === 'none' ? undefined : autoAddBoardId,
crop_visible: false,
postUploadAction: {
type: 'TOAST',
title: t('toast.maskSentControlnetAssets'),
},
})
).unwrap();
const { image_name } = imageDTO;
dispatch(
controlAdapterImageChanged({
id,
controlImage: image_name,
})
);
},
});
};

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import { $logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
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 { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { imagesApi } from 'services/api/endpoints/images';
export const addCanvasMergedListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: canvasMerged,
effect: async (action, { dispatch }) => {
const moduleLog = $logger.get().child({ namespace: 'canvasCopiedToClipboardListener' });
const blob = await getFullBaseLayerBlob();
if (!blob) {
moduleLog.error('Problem getting base layer blob');
toast({
id: 'PROBLEM_MERGING_CANVAS',
title: t('toast.problemMergingCanvas'),
description: t('toast.problemMergingCanvasDesc'),
status: 'error',
});
return;
}
const canvasBaseLayer = $canvasBaseLayer.get();
if (!canvasBaseLayer) {
moduleLog.error('Problem getting canvas base layer');
toast({
id: 'PROBLEM_MERGING_CANVAS',
title: t('toast.problemMergingCanvas'),
description: t('toast.problemMergingCanvasDesc'),
status: 'error',
});
return;
}
const baseLayerRect = canvasBaseLayer.getClientRect({
relativeTo: canvasBaseLayer.getParent() ?? undefined,
});
const imageDTO = await dispatch(
imagesApi.endpoints.uploadImage.initiate({
file: new File([blob], 'mergedCanvas.png', {
type: 'image/png',
}),
image_category: 'general',
is_intermediate: true,
postUploadAction: {
type: 'TOAST',
title: t('toast.canvasMerged'),
},
})
).unwrap();
// TODO: I can't figure out how to do the type narrowing in the `take()` so just brute forcing it here
const { image_name } = imageDTO;
dispatch(
setMergedCanvas({
kind: 'image',
layer: 'base',
imageName: image_name,
...baseLayerRect,
})
);
},
});
};

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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 { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { imagesApi } from 'services/api/endpoints/images';
export const addCanvasSavedToGalleryListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: canvasSavedToGallery,
effect: async (action, { dispatch, getState }) => {
const log = logger('canvas');
const state = getState();
let blob;
try {
blob = await getBaseLayerBlob(state);
} catch (err) {
log.error(String(err));
toast({
id: 'CANVAS_SAVE_FAILED',
title: t('toast.problemSavingCanvas'),
description: t('toast.problemSavingCanvasDesc'),
status: 'error',
});
return;
}
const { autoAddBoardId } = state.gallery;
dispatch(
imagesApi.endpoints.uploadImage.initiate({
file: new File([blob], 'savedCanvas.png', {
type: 'image/png',
}),
image_category: 'general',
is_intermediate: false,
board_id: autoAddBoardId === 'none' ? undefined : autoAddBoardId,
crop_visible: true,
postUploadAction: {
type: 'TOAST',
title: t('toast.canvasSavedGallery'),
},
metadata: {
_canvas_objects: parseify(state.canvas.layerState.objects),
},
})
);
},
});
};

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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,
caLayerModelChanged,
caLayerProcessedImageChanged,
caLayerProcessorConfigChanged,
caLayerProcessorPendingBatchIdChanged,
caLayerRecalled,
isControlAdapterLayer,
} from 'features/controlLayers/store/controlLayersSlice';
import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { isEqual } from 'lodash-es';
import { getImageDTO } from 'services/api/endpoints/images';
import { queueApi } from 'services/api/endpoints/queue';
import type { BatchConfig } from 'services/api/types';
import { socketInvocationComplete } from 'services/events/actions';
import { assert } from 'tsafe';
const matcher = isAnyOf(
caLayerImageChanged,
caLayerProcessedImageChanged,
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, 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();
log.trace('Control Layer CA auto-process triggered');
// Delay before starting actual work
await delay(DEBOUNCE_MS);
const layer = state.controlLayers.present.layers.filter(isControlAdapterLayer).find((l) => l.id === layerId);
if (!layer) {
return;
}
// 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 processedImage = layer.controlAdapter.processedImage;
const config = layer.controlAdapter.processorConfig;
if (isEqual(config, originalConfig) && isEqual(image, originalImage) && processedImage) {
// 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,
// Control images are always intermediate - do not save to gallery
is_intermediate: true,
},
},
edges: [],
},
runs: 1,
},
};
// Kick off the processor batch
const req = dispatch(
queueApi.endpoints.enqueueBatch.initiate(enqueueBatchArg, {
fixedCacheKey: 'enqueueBatch',
})
);
try {
const enqueueResult = await req.unwrap();
// 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) &&
action.payload.data.batch_id === enqueueResult.batch.batch_id &&
action.payload.data.invocation_source_id === processorNode.id
);
// We still have to check the output type
assert(
invocationCompleteAction.payload.data.result.type === 'image_output',
`Processor did not return an image output, got: ${invocationCompleteAction.payload.data.result}`
);
const { image_name } = invocationCompleteAction.payload.data.result.image;
const imageDTO = await getImageDTO(image_name);
assert(imageDTO, "Failed to fetch processor output's image DTO");
// 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) {
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;
}
}
}
toast({
id: 'GRAPH_QUEUE_FAILED',
title: t('queue.graphFailedToQueue'),
status: 'error',
});
}
} finally {
req.reset();
}
},
});
};

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import type { AnyListenerPredicate } from '@reduxjs/toolkit';
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import type { RootState } from 'app/store/store';
import { controlAdapterImageProcessed } from 'features/controlAdapters/store/actions';
import {
controlAdapterAutoConfigToggled,
controlAdapterImageChanged,
controlAdapterModelChanged,
controlAdapterProcessorParamsChanged,
controlAdapterProcessortTypeChanged,
selectControlAdapterById,
} from 'features/controlAdapters/store/controlAdaptersSlice';
import { isControlNetOrT2IAdapter } from 'features/controlAdapters/store/types';
type AnyControlAdapterParamChangeAction =
| ReturnType<typeof controlAdapterProcessorParamsChanged>
| ReturnType<typeof controlAdapterModelChanged>
| ReturnType<typeof controlAdapterImageChanged>
| ReturnType<typeof controlAdapterProcessortTypeChanged>
| ReturnType<typeof controlAdapterAutoConfigToggled>;
const predicate: AnyListenerPredicate<RootState> = (action, state, prevState) => {
const isActionMatched =
controlAdapterProcessorParamsChanged.match(action) ||
controlAdapterModelChanged.match(action) ||
controlAdapterImageChanged.match(action) ||
controlAdapterProcessortTypeChanged.match(action) ||
controlAdapterAutoConfigToggled.match(action);
if (!isActionMatched) {
return false;
}
const { id } = action.payload;
const prevCA = selectControlAdapterById(prevState.controlAdapters, id);
const ca = selectControlAdapterById(state.controlAdapters, id);
if (!prevCA || !isControlNetOrT2IAdapter(prevCA) || !ca || !isControlNetOrT2IAdapter(ca)) {
return false;
}
if (controlAdapterAutoConfigToggled.match(action)) {
// do not process if the user just disabled auto-config
if (prevCA.shouldAutoConfig === true) {
return false;
}
}
const { controlImage, processorType, shouldAutoConfig } = ca;
if (controlAdapterModelChanged.match(action) && !shouldAutoConfig) {
// do not process if the action is a model change but the processor settings are dirty
return false;
}
const isProcessorSelected = processorType !== 'none';
const hasControlImage = Boolean(controlImage);
return isProcessorSelected && hasControlImage;
};
const DEBOUNCE_MS = 300;
/**
* Listener that automatically processes a ControlNet image when its processor parameters are changed.
*
* The network request is debounced.
*/
export const addControlNetAutoProcessListener = (startAppListening: AppStartListening) => {
startAppListening({
predicate,
effect: async (action, { dispatch, cancelActiveListeners, delay }) => {
const log = logger('session');
const { id } = (action as AnyControlAdapterParamChangeAction).payload;
// Cancel any in-progress instances of this listener
cancelActiveListeners();
log.trace('ControlNet auto-process triggered');
// Delay before starting actual work
await delay(DEBOUNCE_MS);
dispatch(controlAdapterImageProcessed({ id }));
},
});
};

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import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { parseify } from 'common/util/serialize';
import { controlAdapterImageProcessed } from 'features/controlAdapters/store/actions';
import {
controlAdapterImageChanged,
controlAdapterProcessedImageChanged,
pendingControlImagesCleared,
selectControlAdapterById,
} from 'features/controlAdapters/store/controlAdaptersSlice';
import { isControlNetOrT2IAdapter } from 'features/controlAdapters/store/types';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { imagesApi } from 'services/api/endpoints/images';
import { queueApi } from 'services/api/endpoints/queue';
import type { BatchConfig, ImageDTO } from 'services/api/types';
import { socketInvocationComplete } from 'services/events/actions';
export const addControlNetImageProcessedListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: controlAdapterImageProcessed,
effect: async (action, { dispatch, getState, take }) => {
const log = logger('session');
const { id } = action.payload;
const ca = selectControlAdapterById(getState().controlAdapters, id);
if (!ca?.controlImage || !isControlNetOrT2IAdapter(ca)) {
log.error('Unable to process ControlNet image');
return;
}
if (ca.processorType === 'none' || ca.processorNode.type === 'none') {
return;
}
// ControlNet one-off procressing graph is just the processor node, no edges.
// Also we need to grab the image.
const nodeId = ca.processorNode.id;
const enqueueBatchArg: BatchConfig = {
prepend: true,
batch: {
graph: {
nodes: {
[ca.processorNode.id]: {
...ca.processorNode,
is_intermediate: true,
use_cache: false,
image: { image_name: ca.controlImage },
},
},
edges: [],
},
runs: 1,
},
};
try {
const req = dispatch(
queueApi.endpoints.enqueueBatch.initiate(enqueueBatchArg, {
fixedCacheKey: 'enqueueBatch',
})
);
const enqueueResult = await req.unwrap();
req.reset();
log.debug({ enqueueResult: parseify(enqueueResult) }, t('queue.graphQueued'));
const [invocationCompleteAction] = await take(
(action): action is ReturnType<typeof socketInvocationComplete> =>
socketInvocationComplete.match(action) &&
action.payload.data.batch_id === enqueueResult.batch.batch_id &&
action.payload.data.invocation_source_id === nodeId
);
// We still have to check the output type
if (invocationCompleteAction.payload.data.result.type === 'image_output') {
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 processedControlImage = payload as ImageDTO;
log.debug({ controlNetId: action.payload, processedControlImage }, 'ControlNet image processed');
// Update the processed image in the store
dispatch(
controlAdapterProcessedImageChanged({
id,
processedControlImage: processedControlImage.image_name,
})
);
}
} catch (error) {
log.error({ enqueueBatchArg: parseify(enqueueBatchArg) }, t('queue.graphFailedToQueue'));
if (error instanceof Object) {
if ('data' in error && 'status' in error) {
if (error.status === 403) {
dispatch(pendingControlImagesCleared());
dispatch(controlAdapterImageChanged({ id, controlImage: null }));
return;
}
}
}
toast({
id: 'GRAPH_QUEUE_FAILED',
title: t('queue.graphFailedToQueue'),
status: 'error',
});
}
},
});
};

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import { logger } from 'app/logging/logger';
import { enqueueRequested } from 'app/store/actions';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import openBase64ImageInTab from 'common/util/openBase64ImageInTab';
import { parseify } from 'common/util/serialize';
import { canvasBatchIdAdded, stagingAreaInitialized } from 'features/canvas/store/canvasSlice';
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 { 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';
/**
* This listener is responsible invoking the canvas. This involves a number of steps:
*
* 1. Generate image blobs from the canvas layers
* 2. Determine the generation mode from the layers (txt2img, img2img, inpaint)
* 3. Build the canvas graph
* 4. Create the session with the graph
* 5. Upload the init image if necessary
* 6. Upload the mask image if necessary
* 7. Update the init and mask images with the session ID
* 8. Initialize the staging area if not yet initialized
* 9. Dispatch the sessionReadyToInvoke action to invoke the session
*/
export const addEnqueueRequestedCanvasListener = (startAppListening: AppStartListening) => {
startAppListening({
predicate: (action): action is ReturnType<typeof enqueueRequested> =>
enqueueRequested.match(action) && action.payload.tabName === 'canvas',
effect: async (action, { getState, dispatch }) => {
const log = logger('queue');
const { prepend } = action.payload;
const state = getState();
const { layerState, boundingBoxCoordinates, boundingBoxDimensions, isMaskEnabled, shouldPreserveMaskedArea } =
state.canvas;
// Build canvas blobs
const canvasBlobsAndImageData = await getCanvasData(
layerState,
boundingBoxCoordinates,
boundingBoxDimensions,
isMaskEnabled,
shouldPreserveMaskedArea
);
if (!canvasBlobsAndImageData) {
log.error('Unable to create canvas data');
return;
}
const { baseBlob, baseImageData, maskBlob, maskImageData } = canvasBlobsAndImageData;
// Determine the generation mode
const generationMode = getCanvasGenerationMode(baseImageData, maskImageData);
if (state.system.enableImageDebugging) {
const baseDataURL = await blobToDataURL(baseBlob);
const maskDataURL = await blobToDataURL(maskBlob);
openBase64ImageInTab([
{ base64: maskDataURL, caption: 'mask b64' },
{ base64: baseDataURL, caption: 'image b64' },
]);
}
log.debug(`Generation mode: ${generationMode}`);
// Temp placeholders for the init and mask images
let canvasInitImage: ImageDTO | undefined;
let canvasMaskImage: ImageDTO | undefined;
// For img2img and inpaint/outpaint, we need to upload the init images
if (['img2img', 'inpaint', 'outpaint'].includes(generationMode)) {
// upload the image, saving the request id
canvasInitImage = await dispatch(
imagesApi.endpoints.uploadImage.initiate({
file: new File([baseBlob], 'canvasInitImage.png', {
type: 'image/png',
}),
image_category: 'general',
is_intermediate: true,
})
).unwrap();
}
// For inpaint/outpaint, we also need to upload the mask layer
if (['inpaint', 'outpaint'].includes(generationMode)) {
// upload the image, saving the request id
canvasMaskImage = await dispatch(
imagesApi.endpoints.uploadImage.initiate({
file: new File([maskBlob], 'canvasMaskImage.png', {
type: 'image/png',
}),
image_category: 'mask',
is_intermediate: true,
})
).unwrap();
}
const graph = await buildCanvasGraph(state, generationMode, canvasInitImage, canvasMaskImage);
log.debug({ graph: parseify(graph) }, `Canvas graph built`);
// currently this action is just listened to for logging
dispatch(canvasGraphBuilt(graph));
const batchConfig = prepareLinearUIBatch(state, graph, prepend);
try {
const req = dispatch(
queueApi.endpoints.enqueueBatch.initiate(batchConfig, {
fixedCacheKey: 'enqueueBatch',
})
);
const enqueueResult = await req.unwrap();
req.reset();
const batchId = enqueueResult.batch.batch_id as string; // we know the is a string, backend provides it
// Prep the canvas staging area if it is not yet initialized
if (!state.canvas.layerState.stagingArea.boundingBox) {
dispatch(
stagingAreaInitialized({
boundingBox: {
...state.canvas.boundingBoxCoordinates,
...state.canvas.boundingBoxDimensions,
},
})
);
}
// Associate the session with the canvas session ID
dispatch(canvasBatchIdAdded(batchId));
} catch {
// no-op
}
},
});
};

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import { logger } from 'app/logging/logger';
import { enqueueRequested } from 'app/store/actions';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import type { SerializableObject } from 'common/types';
import type { Result } from 'common/util/result';
import { isErr, withResult, withResultAsync } from 'common/util/result';
import { $canvasManager } from 'features/controlLayers/konva/CanvasManager';
import { sessionStagingAreaReset, sessionStartedStaging } from 'features/controlLayers/store/canvasSessionSlice';
import { isImageViewerOpenChanged } from 'features/gallery/store/gallerySlice';
import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
import { buildSD1Graph } from 'features/nodes/util/graph/generation/buildSD1Graph';
import { buildSDXLGraph } from 'features/nodes/util/graph/generation/buildSDXLGraph';
import type { Graph } from 'features/nodes/util/graph/generation/Graph';
import { serializeError } from 'serialize-error';
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';
import type { Invocation } from 'services/api/types';
import { assert } from 'tsafe';
const log = logger('generation');
export const addEnqueueRequestedLinear = (startAppListening: AppStartListening) => {
startAppListening({
@ -23,77 +12,33 @@ export const addEnqueueRequestedLinear = (startAppListening: AppStartListening)
enqueueRequested.match(action) && action.payload.tabName === 'generation',
effect: async (action, { getState, dispatch }) => {
const state = getState();
const model = state.params.model;
const { shouldShowProgressInViewer } = state.ui;
const model = state.generation.model;
const { prepend } = action.payload;
const manager = $canvasManager.get();
assert(manager, 'No model found in state');
let graph;
let didStartStaging = false;
if (!state.canvasSession.isStaging && state.canvasSession.mode === 'compose') {
dispatch(sessionStartedStaging());
didStartStaging = true;
if (model?.base === 'sdxl') {
graph = await buildGenerationTabSDXLGraph(state);
} else {
graph = await buildGenerationTabGraph(state);
}
const abortStaging = () => {
if (didStartStaging && getState().canvasSession.isStaging) {
dispatch(sessionStagingAreaReset());
}
};
let buildGraphResult: Result<
{ g: Graph; noise: Invocation<'noise'>; posCond: Invocation<'compel' | 'sdxl_compel_prompt'> },
Error
>;
assert(model, 'No model found in state');
const base = model.base;
switch (base) {
case 'sdxl':
buildGraphResult = await withResultAsync(() => buildSDXLGraph(state, manager));
break;
case 'sd-1':
case `sd-2`:
buildGraphResult = await withResultAsync(() => buildSD1Graph(state, manager));
break;
default:
assert(false, `No graph builders for base ${base}`);
}
if (isErr(buildGraphResult)) {
log.error({ error: serializeError(buildGraphResult.error) }, 'Failed to build graph');
abortStaging();
return;
}
const { g, noise, posCond } = buildGraphResult.value;
const prepareBatchResult = withResult(() => prepareLinearUIBatch(state, g, prepend, noise, posCond));
if (isErr(prepareBatchResult)) {
log.error({ error: serializeError(prepareBatchResult.error) }, 'Failed to prepare batch');
abortStaging();
return;
}
const batchConfig = prepareLinearUIBatch(state, graph, prepend);
const req = dispatch(
queueApi.endpoints.enqueueBatch.initiate(prepareBatchResult.value, {
queueApi.endpoints.enqueueBatch.initiate(batchConfig, {
fixedCacheKey: 'enqueueBatch',
})
);
req.reset();
const enqueueResult = await withResultAsync(() => req.unwrap());
if (isErr(enqueueResult)) {
log.error({ error: serializeError(enqueueResult.error) }, 'Failed to enqueue batch');
abortStaging();
return;
try {
await req.unwrap();
if (shouldShowProgressInViewer) {
dispatch(isImageViewerOpenChanged(true));
}
} finally {
req.reset();
}
log.debug({ batchConfig: prepareBatchResult.value } as SerializableObject, 'Enqueued batch');
},
});
};

View File

@ -1,6 +1,5 @@
import { enqueueRequested } from 'app/store/actions';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { selectNodesSlice } from 'features/nodes/store/selectors';
import { buildNodesGraph } from 'features/nodes/util/graph/buildNodesGraph';
import { buildWorkflowWithValidation } from 'features/nodes/util/workflow/buildWorkflow';
import { queueApi } from 'services/api/endpoints/queue';
@ -12,12 +11,12 @@ export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) =
enqueueRequested.match(action) && action.payload.tabName === 'workflows',
effect: async (action, { getState, dispatch }) => {
const state = getState();
const nodes = selectNodesSlice(state);
const { nodes, edges } = state.nodes.present;
const workflow = state.workflow;
const graph = buildNodesGraph(nodes);
const graph = buildNodesGraph(state.nodes.present);
const builtWorkflow = buildWorkflowWithValidation({
nodes: nodes.nodes,
edges: nodes.edges,
nodes,
edges,
workflow,
});
@ -30,8 +29,7 @@ export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) =
batch: {
graph,
workflow: builtWorkflow,
runs: state.params.iterations,
origin: 'workflows',
runs: state.generation.iterations,
},
prepend: action.payload.prepend,
};

View File

@ -14,9 +14,9 @@ export const addEnqueueRequestedUpscale = (startAppListening: AppStartListening)
const { shouldShowProgressInViewer } = state.ui;
const { prepend } = action.payload;
const { g, noise, posCond } = await buildMultidiffusionUpscaleGraph(state);
const graph = await buildMultidiffusionUpscaleGraph(state);
const batchConfig = prepareLinearUIBatch(state, g, prepend, noise, posCond);
const batchConfig = prepareLinearUIBatch(state, graph, prepend);
const req = dispatch(
queueApi.endpoints.enqueueBatch.initiate(batchConfig, {

View File

@ -27,7 +27,7 @@ export const galleryImageClicked = createAction<{
export const addGalleryImageClickedListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: galleryImageClicked,
effect: (action, { dispatch, getState }) => {
effect: async (action, { dispatch, getState }) => {
const { imageDTO, shiftKey, ctrlKey, metaKey, altKey } = action.payload;
const state = getState();
const queryArgs = selectListImagesQueryArgs(state);

View File

@ -1,27 +1,24 @@
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import type { SerializableObject } from 'common/types';
import { parseify } from 'common/util/serialize';
import { $templates } from 'features/nodes/store/nodesSlice';
import { parseSchema } from 'features/nodes/util/schema/parseSchema';
import { size } from 'lodash-es';
import { serializeError } from 'serialize-error';
import { appInfoApi } from 'services/api/endpoints/appInfo';
const log = logger('system');
export const addGetOpenAPISchemaListener = (startAppListening: AppStartListening) => {
startAppListening({
matcher: appInfoApi.endpoints.getOpenAPISchema.matchFulfilled,
effect: (action, { getState }) => {
const log = logger('system');
const schemaJSON = action.payload;
log.debug({ schemaJSON: parseify(schemaJSON) } as SerializableObject, 'Received OpenAPI schema');
log.debug({ schemaJSON: parseify(schemaJSON) }, 'Received OpenAPI schema');
const { nodesAllowlist, nodesDenylist } = getState().config;
const nodeTemplates = parseSchema(schemaJSON, nodesAllowlist, nodesDenylist);
log.debug({ nodeTemplates } as SerializableObject, `Built ${size(nodeTemplates)} node templates`);
log.debug({ nodeTemplates: parseify(nodeTemplates) }, `Built ${size(nodeTemplates)} node templates`);
$templates.set(nodeTemplates);
},
@ -33,7 +30,8 @@ export const addGetOpenAPISchemaListener = (startAppListening: AppStartListening
// If action.meta.condition === true, the request was canceled/skipped because another request was in flight or
// the value was already in the cache. We don't want to log these errors.
if (!action.meta.condition) {
log.error({ error: serializeError(action.error) }, 'Problem retrieving OpenAPI Schema');
const log = logger('system');
log.error({ error: parseify(action.error) }, 'Problem retrieving OpenAPI Schema');
}
},
});

View File

@ -2,13 +2,15 @@ import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { imagesApi } from 'services/api/endpoints/images';
const log = logger('gallery');
export const addImageAddedToBoardFulfilledListener = (startAppListening: AppStartListening) => {
startAppListening({
matcher: imagesApi.endpoints.addImageToBoard.matchFulfilled,
effect: (action) => {
const log = logger('images');
const { board_id, imageDTO } = action.meta.arg.originalArgs;
// TODO: update listImages cache for this board
log.debug({ board_id, imageDTO }, 'Image added to board');
},
});
@ -16,7 +18,9 @@ export const addImageAddedToBoardFulfilledListener = (startAppListening: AppStar
startAppListening({
matcher: imagesApi.endpoints.addImageToBoard.matchRejected,
effect: (action) => {
const log = logger('images');
const { board_id, imageDTO } = action.meta.arg.originalArgs;
log.debug({ board_id, imageDTO }, 'Problem adding image to board');
},
});

View File

@ -1,9 +1,20 @@
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import type { AppDispatch, RootState } from 'app/store/store';
import { entityDeleted, ipaImageChanged } from 'features/controlLayers/store/canvasSlice';
import { selectCanvasSlice } from 'features/controlLayers/store/selectors';
import { getEntityIdentifier } from 'features/controlLayers/store/types';
import { resetCanvas } from 'features/canvas/store/canvasSlice';
import {
controlAdapterImageChanged,
controlAdapterProcessedImageChanged,
selectControlAdapterAll,
} from 'features/controlAdapters/store/controlAdaptersSlice';
import { isControlNetOrT2IAdapter } from 'features/controlAdapters/store/types';
import {
isControlAdapterLayer,
isInitialImageLayer,
isIPAdapterLayer,
isRegionalGuidanceLayer,
layerDeleted,
} from 'features/controlLayers/store/controlLayersSlice';
import { imageDeletionConfirmed } from 'features/deleteImageModal/store/actions';
import { isModalOpenChanged } from 'features/deleteImageModal/store/slice';
import { selectListImagesQueryArgs } from 'features/gallery/store/gallerySelectors';
@ -15,10 +26,6 @@ import { forEach, intersectionBy } from 'lodash-es';
import { imagesApi } from 'services/api/endpoints/images';
import type { ImageDTO } from 'services/api/types';
const log = logger('gallery');
//TODO(psyche): handle image deletion (canvas sessions?)
// Some utils to delete images from different parts of the app
const deleteNodesImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
state.nodes.present.nodes.forEach((node) => {
@ -40,37 +47,52 @@ const deleteNodesImages = (state: RootState, dispatch: AppDispatch, imageDTO: Im
});
};
// const deleteControlAdapterImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
// state.canvas.present.controlAdapters.entities.forEach(({ id, imageObject, processedImageObject }) => {
// if (
// imageObject?.image.image_name === imageDTO.image_name ||
// processedImageObject?.image.image_name === imageDTO.image_name
// ) {
// dispatch(caImageChanged({ id, imageDTO: null }));
// dispatch(caProcessedImageChanged({ id, imageDTO: null }));
// }
// });
// };
const deleteIPAdapterImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
selectCanvasSlice(state).ipAdapters.entities.forEach((entity) => {
if (entity.ipAdapter.image?.image_name === imageDTO.image_name) {
dispatch(ipaImageChanged({ entityIdentifier: getEntityIdentifier(entity), imageDTO: null }));
const deleteControlAdapterImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
forEach(selectControlAdapterAll(state.controlAdapters), (ca) => {
if (
ca.controlImage === imageDTO.image_name ||
(isControlNetOrT2IAdapter(ca) && ca.processedControlImage === imageDTO.image_name)
) {
dispatch(
controlAdapterImageChanged({
id: ca.id,
controlImage: null,
})
);
dispatch(
controlAdapterProcessedImageChanged({
id: ca.id,
processedControlImage: null,
})
);
}
});
};
const deleteLayerImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
selectCanvasSlice(state).rasterLayers.entities.forEach(({ id, objects }) => {
let shouldDelete = false;
for (const obj of objects) {
if (obj.type === 'image' && obj.image.image_name === imageDTO.image_name) {
shouldDelete = true;
break;
const deleteControlLayerImages = (state: RootState, dispatch: AppDispatch, imageDTO: ImageDTO) => {
state.controlLayers.present.layers.forEach((l) => {
if (isRegionalGuidanceLayer(l)) {
if (l.ipAdapters.some((ipa) => ipa.image?.name === imageDTO.image_name)) {
dispatch(layerDeleted(l.id));
}
}
if (shouldDelete) {
dispatch(entityDeleted({ entityIdentifier: { id, type: 'raster_layer' } }));
if (isControlAdapterLayer(l)) {
if (
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?.name === imageDTO.image_name) {
dispatch(layerDeleted(l.id));
}
}
if (isInitialImageLayer(l)) {
if (l.image?.name === imageDTO.image_name) {
dispatch(layerDeleted(l.id));
}
}
});
};
@ -123,10 +145,14 @@ export const addImageDeletionListeners = (startAppListening: AppStartListening)
}
}
// We need to reset the features where the image is in use - none of these work if their image(s) don't exist
if (imageUsage.isCanvasImage) {
dispatch(resetCanvas());
}
deleteControlAdapterImages(state, dispatch, imageDTO);
deleteNodesImages(state, dispatch, imageDTO);
// deleteControlAdapterImages(state, dispatch, imageDTO);
deleteIPAdapterImages(state, dispatch, imageDTO);
deleteLayerImages(state, dispatch, imageDTO);
deleteControlLayerImages(state, dispatch, imageDTO);
} catch {
// no-op
} finally {
@ -163,11 +189,14 @@ export const addImageDeletionListeners = (startAppListening: AppStartListening)
// We need to reset the features where the image is in use - none of these work if their image(s) don't exist
if (imagesUsage.some((i) => i.isCanvasImage)) {
dispatch(resetCanvas());
}
imageDTOs.forEach((imageDTO) => {
deleteControlAdapterImages(state, dispatch, imageDTO);
deleteNodesImages(state, dispatch, imageDTO);
// deleteControlAdapterImages(state, dispatch, imageDTO);
deleteIPAdapterImages(state, dispatch, imageDTO);
deleteLayerImages(state, dispatch, imageDTO);
deleteControlLayerImages(state, dispatch, imageDTO);
});
} catch {
// no-op
@ -191,6 +220,7 @@ export const addImageDeletionListeners = (startAppListening: AppStartListening)
startAppListening({
matcher: imagesApi.endpoints.deleteImage.matchFulfilled,
effect: (action) => {
const log = logger('images');
log.debug({ imageDTO: action.meta.arg.originalArgs }, 'Image deleted');
},
});
@ -198,6 +228,7 @@ export const addImageDeletionListeners = (startAppListening: AppStartListening)
startAppListening({
matcher: imagesApi.endpoints.deleteImage.matchRejected,
effect: (action) => {
const log = logger('images');
log.debug({ imageDTO: action.meta.arg.originalArgs }, 'Unable to delete image');
},
});

View File

@ -1,19 +1,28 @@
import { createAction } from '@reduxjs/toolkit';
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { parseify } from 'common/util/serialize';
import { setInitialCanvasImage } from 'features/canvas/store/canvasSlice';
import {
controlLayerAdded,
ipaImageChanged,
rasterLayerAdded,
rgIPAdapterImageChanged,
} from 'features/controlLayers/store/canvasSlice';
import { selectCanvasSlice } from 'features/controlLayers/store/selectors';
import type { CanvasControlLayerState, CanvasRasterLayerState } from 'features/controlLayers/store/types';
import { imageDTOToImageObject } from 'features/controlLayers/store/types';
controlAdapterImageChanged,
controlAdapterIsEnabledChanged,
} from 'features/controlAdapters/store/controlAdaptersSlice';
import {
caLayerImageChanged,
iiLayerImageChanged,
ipaLayerImageChanged,
rgLayerIPAdapterImageChanged,
} from 'features/controlLayers/store/controlLayersSlice';
import type { TypesafeDraggableData, TypesafeDroppableData } from 'features/dnd/types';
import { isValidDrop } from 'features/dnd/util/isValidDrop';
import { imageToCompareChanged, isImageViewerOpenChanged, selectionChanged } from 'features/gallery/store/gallerySlice';
import {
imageSelected,
imageToCompareChanged,
isImageViewerOpenChanged,
selectionChanged,
} from 'features/gallery/store/gallerySlice';
import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
import { upscaleInitialImageChanged } from 'features/parameters/store/upscaleSlice';
import { imagesApi } from 'services/api/endpoints/images';
@ -22,12 +31,11 @@ export const dndDropped = createAction<{
activeData: TypesafeDraggableData;
}>('dnd/dndDropped');
const log = logger('system');
export const addImageDroppedListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: dndDropped,
effect: (action, { dispatch, getState }) => {
effect: async (action, { dispatch, getState }) => {
const log = logger('dnd');
const { activeData, overData } = action.payload;
if (!isValidDrop(overData, activeData)) {
return;
@ -38,22 +46,80 @@ export const addImageDroppedListener = (startAppListening: AppStartListening) =>
} else if (activeData.payloadType === 'GALLERY_SELECTION') {
log.debug({ activeData, overData }, `Images (${getState().gallery.selection.length}) dropped`);
} else if (activeData.payloadType === 'NODE_FIELD') {
log.debug({ activeData, overData }, 'Node field dropped');
log.debug({ activeData: parseify(activeData), overData: parseify(overData) }, 'Node field dropped');
} else {
log.debug({ activeData, overData }, `Unknown payload dropped`);
}
/**
* Image dropped on current image
*/
if (
overData.actionType === 'SET_CURRENT_IMAGE' &&
activeData.payloadType === 'IMAGE_DTO' &&
activeData.payload.imageDTO
) {
dispatch(imageSelected(activeData.payload.imageDTO));
dispatch(isImageViewerOpenChanged(true));
return;
}
/**
* Image dropped on ControlNet
*/
if (
overData.actionType === 'SET_CONTROL_ADAPTER_IMAGE' &&
activeData.payloadType === 'IMAGE_DTO' &&
activeData.payload.imageDTO
) {
const { id } = overData.context;
dispatch(
controlAdapterImageChanged({
id,
controlImage: activeData.payload.imageDTO.image_name,
})
);
dispatch(
controlAdapterIsEnabledChanged({
id,
isEnabled: true,
})
);
return;
}
/**
* Image dropped on Control Adapter Layer
*/
if (
overData.actionType === 'SET_CA_LAYER_IMAGE' &&
activeData.payloadType === 'IMAGE_DTO' &&
activeData.payload.imageDTO
) {
const { layerId } = overData.context;
dispatch(
caLayerImageChanged({
layerId,
imageDTO: activeData.payload.imageDTO,
})
);
return;
}
/**
* Image dropped on IP Adapter Layer
*/
if (
overData.actionType === 'SET_IPA_IMAGE' &&
overData.actionType === 'SET_IPA_LAYER_IMAGE' &&
activeData.payloadType === 'IMAGE_DTO' &&
activeData.payload.imageDTO
) {
const { id } = overData.context;
const { layerId } = overData.context;
dispatch(
ipaImageChanged({ entityIdentifier: { id, type: 'ip_adapter' }, imageDTO: activeData.payload.imageDTO })
ipaLayerImageChanged({
layerId,
imageDTO: activeData.payload.imageDTO,
})
);
return;
}
@ -62,14 +128,14 @@ export const addImageDroppedListener = (startAppListening: AppStartListening) =>
* Image dropped on RG Layer IP Adapter
*/
if (
overData.actionType === 'SET_RG_IP_ADAPTER_IMAGE' &&
overData.actionType === 'SET_RG_LAYER_IP_ADAPTER_IMAGE' &&
activeData.payloadType === 'IMAGE_DTO' &&
activeData.payload.imageDTO
) {
const { id, ipAdapterId } = overData.context;
const { layerId, ipAdapterId } = overData.context;
dispatch(
rgIPAdapterImageChanged({
entityIdentifier: { id, type: 'regional_guidance' },
rgLayerIPAdapterImageChanged({
layerId,
ipAdapterId,
imageDTO: activeData.payload.imageDTO,
})
@ -78,38 +144,32 @@ export const addImageDroppedListener = (startAppListening: AppStartListening) =>
}
/**
* Image dropped on Raster layer
* Image dropped on II Layer Image
*/
if (
overData.actionType === 'ADD_RASTER_LAYER_FROM_IMAGE' &&
overData.actionType === 'SET_II_LAYER_IMAGE' &&
activeData.payloadType === 'IMAGE_DTO' &&
activeData.payload.imageDTO
) {
const imageObject = imageDTOToImageObject(activeData.payload.imageDTO);
const { x, y } = selectCanvasSlice(getState()).bbox.rect;
const overrides: Partial<CanvasRasterLayerState> = {
objects: [imageObject],
position: { x, y },
};
dispatch(rasterLayerAdded({ overrides, isSelected: true }));
const { layerId } = overData.context;
dispatch(
iiLayerImageChanged({
layerId,
imageDTO: activeData.payload.imageDTO,
})
);
return;
}
/**
* Image dropped on Raster layer
* Image dropped on Canvas
*/
if (
overData.actionType === 'ADD_CONTROL_LAYER_FROM_IMAGE' &&
overData.actionType === 'SET_CANVAS_INITIAL_IMAGE' &&
activeData.payloadType === 'IMAGE_DTO' &&
activeData.payload.imageDTO
) {
const imageObject = imageDTOToImageObject(activeData.payload.imageDTO);
const { x, y } = selectCanvasSlice(getState()).bbox.rect;
const overrides: Partial<CanvasControlLayerState> = {
objects: [imageObject],
position: { x, y },
};
dispatch(controlLayerAdded({ overrides, isSelected: true }));
dispatch(setInitialCanvasImage(activeData.payload.imageDTO, selectOptimalDimension(getState())));
return;
}

View File

@ -2,13 +2,13 @@ import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { imagesApi } from 'services/api/endpoints/images';
const log = logger('gallery');
export const addImageRemovedFromBoardFulfilledListener = (startAppListening: AppStartListening) => {
startAppListening({
matcher: imagesApi.endpoints.removeImageFromBoard.matchFulfilled,
effect: (action) => {
const log = logger('images');
const imageDTO = action.meta.arg.originalArgs;
log.debug({ imageDTO }, 'Image removed from board');
},
});
@ -16,7 +16,9 @@ export const addImageRemovedFromBoardFulfilledListener = (startAppListening: App
startAppListening({
matcher: imagesApi.endpoints.removeImageFromBoard.matchRejected,
effect: (action) => {
const log = logger('images');
const imageDTO = action.meta.arg.originalArgs;
log.debug({ imageDTO }, 'Problem removing image from board');
},
});

View File

@ -6,17 +6,16 @@ import { imagesToDeleteSelected, isModalOpenChanged } from 'features/deleteImage
export const addImageToDeleteSelectedListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: imagesToDeleteSelected,
effect: (action, { dispatch, getState }) => {
effect: async (action, { dispatch, getState }) => {
const imageDTOs = action.payload;
const state = getState();
const { shouldConfirmOnDelete } = state.system;
const imagesUsage = selectImageUsage(getState());
const isImageInUse =
imagesUsage.some((i) => i.isLayerImage) ||
imagesUsage.some((i) => i.isControlAdapterImage) ||
imagesUsage.some((i) => i.isIPAdapterImage) ||
imagesUsage.some((i) => i.isLayerImage);
imagesUsage.some((i) => i.isCanvasImage) ||
imagesUsage.some((i) => i.isControlImage) ||
imagesUsage.some((i) => i.isNodesImage);
if (shouldConfirmOnDelete || isImageInUse) {
dispatch(isModalOpenChanged(true));

View File

@ -1,8 +1,19 @@
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { ipaImageChanged, rgIPAdapterImageChanged } from 'features/controlLayers/store/canvasSlice';
import { setInitialCanvasImage } from 'features/canvas/store/canvasSlice';
import {
controlAdapterImageChanged,
controlAdapterIsEnabledChanged,
} from 'features/controlAdapters/store/controlAdaptersSlice';
import {
caLayerImageChanged,
iiLayerImageChanged,
ipaLayerImageChanged,
rgLayerIPAdapterImageChanged,
} from 'features/controlLayers/store/controlLayersSlice';
import { selectListBoardsQueryArgs } from 'features/gallery/store/gallerySelectors';
import { fieldImageValueChanged } from 'features/nodes/store/nodesSlice';
import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
import { upscaleInitialImageChanged } from 'features/parameters/store/upscaleSlice';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
@ -10,12 +21,11 @@ import { omit } from 'lodash-es';
import { boardsApi } from 'services/api/endpoints/boards';
import { imagesApi } from 'services/api/endpoints/images';
const log = logger('gallery');
export const addImageUploadedFulfilledListener = (startAppListening: AppStartListening) => {
startAppListening({
matcher: imagesApi.endpoints.uploadImage.matchFulfilled,
effect: (action, { dispatch, getState }) => {
const log = logger('images');
const imageDTO = action.payload;
const state = getState();
const { autoAddBoardId } = state.gallery;
@ -71,6 +81,15 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
return;
}
if (postUploadAction?.type === 'SET_CANVAS_INITIAL_IMAGE') {
dispatch(setInitialCanvasImage(imageDTO, selectOptimalDimension(state)));
toast({
...DEFAULT_UPLOADED_TOAST,
description: t('toast.setAsCanvasInitialImage'),
});
return;
}
if (postUploadAction?.type === 'SET_UPSCALE_INITIAL_IMAGE') {
dispatch(upscaleInitialImageChanged(imageDTO));
toast({
@ -80,33 +99,70 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
return;
}
// if (postUploadAction?.type === 'SET_CA_IMAGE') {
// const { id } = postUploadAction;
// dispatch(caImageChanged({ id, imageDTO }));
// toast({ ...DEFAULT_UPLOADED_TOAST, description: t('toast.setControlImage') });
// return;
// }
if (postUploadAction?.type === 'SET_IPA_IMAGE') {
if (postUploadAction?.type === 'SET_CONTROL_ADAPTER_IMAGE') {
const { id } = postUploadAction;
dispatch(ipaImageChanged({ entityIdentifier: { id, type: 'ip_adapter' }, imageDTO }));
toast({ ...DEFAULT_UPLOADED_TOAST, description: t('toast.setControlImage') });
dispatch(
controlAdapterIsEnabledChanged({
id,
isEnabled: true,
})
);
dispatch(
controlAdapterImageChanged({
id,
controlImage: imageDTO.image_name,
})
);
toast({
...DEFAULT_UPLOADED_TOAST,
description: t('toast.setControlImage'),
});
return;
}
if (postUploadAction?.type === 'SET_RG_IP_ADAPTER_IMAGE') {
const { id, ipAdapterId } = postUploadAction;
dispatch(
rgIPAdapterImageChanged({ entityIdentifier: { id, type: 'regional_guidance' }, ipAdapterId, imageDTO })
);
toast({ ...DEFAULT_UPLOADED_TOAST, description: t('toast.setControlImage') });
return;
if (postUploadAction?.type === 'SET_CA_LAYER_IMAGE') {
const { layerId } = postUploadAction;
dispatch(caLayerImageChanged({ layerId, imageDTO }));
toast({
...DEFAULT_UPLOADED_TOAST,
description: t('toast.setControlImage'),
});
}
if (postUploadAction?.type === 'SET_IPA_LAYER_IMAGE') {
const { layerId } = postUploadAction;
dispatch(ipaLayerImageChanged({ layerId, imageDTO }));
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 }));
toast({
...DEFAULT_UPLOADED_TOAST,
description: t('toast.setControlImage'),
});
}
if (postUploadAction?.type === 'SET_II_LAYER_IMAGE') {
const { layerId } = postUploadAction;
dispatch(iiLayerImageChanged({ layerId, imageDTO }));
toast({
...DEFAULT_UPLOADED_TOAST,
description: t('toast.setControlImage'),
});
}
if (postUploadAction?.type === 'SET_NODES_IMAGE') {
const { nodeId, fieldName } = postUploadAction;
dispatch(fieldImageValueChanged({ nodeId, fieldName, value: imageDTO }));
toast({ ...DEFAULT_UPLOADED_TOAST, description: `${t('toast.setNodeField')} ${fieldName}` });
toast({
...DEFAULT_UPLOADED_TOAST,
description: `${t('toast.setNodeField')} ${fieldName}`,
});
return;
}
},
@ -115,6 +171,7 @@ export const addImageUploadedFulfilledListener = (startAppListening: AppStartLis
startAppListening({
matcher: imagesApi.endpoints.uploadImage.matchRejected,
effect: (action) => {
const log = logger('images');
const sanitizedData = {
arg: {
...omit(action.meta.arg.originalArgs, ['file', 'postUploadAction']),

View File

@ -6,7 +6,7 @@ import type { ImageDTO } from 'services/api/types';
export const addImagesStarredListener = (startAppListening: AppStartListening) => {
startAppListening({
matcher: imagesApi.endpoints.starImages.matchFulfilled,
effect: (action, { dispatch, getState }) => {
effect: async (action, { dispatch, getState }) => {
const { updated_image_names: starredImages } = action.payload;
const state = getState();

View File

@ -6,7 +6,7 @@ import type { ImageDTO } from 'services/api/types';
export const addImagesUnstarredListener = (startAppListening: AppStartListening) => {
startAppListening({
matcher: imagesApi.endpoints.unstarImages.matchFulfilled,
effect: (action, { dispatch, getState }) => {
effect: async (action, { dispatch, getState }) => {
const { updated_image_names: unstarredImages } = action.payload;
const state = getState();

View File

@ -1,18 +1,23 @@
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { loraDeleted } from 'features/controlLayers/store/lorasSlice';
import { modelChanged, vaeSelected } from 'features/controlLayers/store/paramsSlice';
import {
controlAdapterIsEnabledChanged,
selectControlAdapterAll,
} from 'features/controlAdapters/store/controlAdaptersSlice';
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 { toast } from 'features/toast/toast';
import { t } from 'i18next';
const log = logger('models');
import { forEach } from 'lodash-es';
export const addModelSelectedListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: modelSelected,
effect: (action, { getState, dispatch }) => {
const log = logger('models');
const state = getState();
const result = zParameterModel.safeParse(action.payload);
@ -24,36 +29,34 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
const newModel = result.data;
const newBaseModel = newModel.base;
const didBaseModelChange = state.params.model?.base !== newBaseModel;
const didBaseModelChange = state.generation.model?.base !== newBaseModel;
if (didBaseModelChange) {
// we may need to reset some incompatible submodels
let modelsCleared = 0;
// handle incompatible loras
state.loras.loras.forEach((lora) => {
forEach(state.lora.loras, (lora, id) => {
if (lora.model.base !== newBaseModel) {
dispatch(loraDeleted({ id: lora.id }));
dispatch(loraRemoved(id));
modelsCleared += 1;
}
});
// handle incompatible vae
const { vae } = state.params;
const { vae } = state.generation;
if (vae && vae.base !== newBaseModel) {
dispatch(vaeSelected(null));
modelsCleared += 1;
}
// handle incompatible controlnets
// state.canvas.present.controlAdapters.entities.forEach((ca) => {
// if (ca.model?.base !== newBaseModel) {
// modelsCleared += 1;
// if (ca.isEnabled) {
// dispatch(entityIsEnabledToggled({ entityIdentifier: { id: ca.id, type: 'control_adapter' } }));
// }
// }
// });
selectControlAdapterAll(state.controlAdapters).forEach((ca) => {
if (ca.model?.base !== newBaseModel) {
dispatch(controlAdapterIsEnabledChanged({ id: ca.id, isEnabled: false }));
modelsCleared += 1;
}
});
if (modelsCleared > 0) {
toast({
@ -67,7 +70,7 @@ export const addModelSelectedListener = (startAppListening: AppStartListening) =
}
}
dispatch(modelChanged({ model: newModel, previousModel: state.params.model }));
dispatch(modelChanged(newModel, state.generation.model));
},
});
};

View File

@ -1,42 +1,36 @@
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import type { AppDispatch, RootState } from 'app/store/store';
import type { SerializableObject } from 'common/types';
import type { JSONObject } from 'common/types';
import {
bboxHeightChanged,
bboxWidthChanged,
controlLayerModelChanged,
ipaModelChanged,
rgIPAdapterModelChanged,
} from 'features/controlLayers/store/canvasSlice';
import { loraDeleted } from 'features/controlLayers/store/lorasSlice';
import { modelChanged, refinerModelChanged, vaeSelected } from 'features/controlLayers/store/paramsSlice';
import { selectCanvasSlice } from 'features/controlLayers/store/selectors';
import { getEntityIdentifier } from 'features/controlLayers/store/types';
import { calculateNewSize } from 'features/parameters/components/DocumentSize/calculateNewSize';
controlAdapterModelCleared,
selectControlAdapterAll,
} from 'features/controlAdapters/store/controlAdaptersSlice';
import { heightChanged, widthChanged } from 'features/controlLayers/store/controlLayersSlice';
import { loraRemoved } from 'features/lora/store/loraSlice';
import { calculateNewSize } from 'features/parameters/components/ImageSize/calculateNewSize';
import { modelChanged, vaeSelected } from 'features/parameters/store/generationSlice';
import { postProcessingModelChanged, upscaleModelChanged } from 'features/parameters/store/upscaleSlice';
import { zParameterModel, zParameterVAEModel } from 'features/parameters/types/parameterSchemas';
import { getIsSizeOptimal, getOptimalDimension } from 'features/parameters/util/optimalDimension';
import { refinerModelChanged } from 'features/sdxl/store/sdxlSlice';
import { forEach } from 'lodash-es';
import type { Logger } from 'roarr';
import { modelConfigsAdapterSelectors, modelsApi } from 'services/api/endpoints/models';
import type { AnyModelConfig } from 'services/api/types';
import {
isControlNetOrT2IAdapterModelConfig,
isIPAdapterModelConfig,
isLoRAModelConfig,
isNonRefinerMainModelConfig,
isRefinerMainModelModelConfig,
isSpandrelImageToImageModelConfig,
isVAEModelConfig,
} from 'services/api/types';
const log = logger('models');
export const addModelsLoadedListener = (startAppListening: AppStartListening) => {
startAppListening({
predicate: modelsApi.endpoints.getModelConfigs.matchFulfilled,
effect: (action, { getState, dispatch }) => {
effect: async (action, { getState, dispatch }) => {
// models loaded, we need to ensure the selected model is available and if not, select the first one
const log = logger('models');
log.info({ models: action.payload.entities }, `Models loaded (${action.payload.ids.length})`);
const state = getState();
@ -49,7 +43,6 @@ export const addModelsLoadedListener = (startAppListening: AppStartListening) =>
handleLoRAModels(models, state, dispatch, log);
handleControlAdapterModels(models, state, dispatch, log);
handleSpandrelImageToImageModels(models, state, dispatch, log);
handleIPAdapterModels(models, state, dispatch, log);
},
});
};
@ -58,15 +51,15 @@ type ModelHandler = (
models: AnyModelConfig[],
state: RootState,
dispatch: AppDispatch,
log: Logger<SerializableObject>
log: Logger<JSONObject>
) => undefined;
const handleMainModels: ModelHandler = (models, state, dispatch, log) => {
const currentModel = state.params.model;
const currentModel = state.generation.model;
const mainModels = models.filter(isNonRefinerMainModelConfig);
if (mainModels.length === 0) {
// No models loaded at all
dispatch(modelChanged({ model: null }));
dispatch(modelChanged(null));
return;
}
@ -81,16 +74,25 @@ const handleMainModels: ModelHandler = (models, state, dispatch, log) => {
if (defaultModelInList) {
const result = zParameterModel.safeParse(defaultModelInList);
if (result.success) {
dispatch(modelChanged({ model: defaultModelInList, previousModel: currentModel }));
const { bbox } = selectCanvasSlice(state);
dispatch(modelChanged(defaultModelInList, currentModel));
const optimalDimension = getOptimalDimension(defaultModelInList);
if (getIsSizeOptimal(bbox.rect.width, bbox.rect.height, optimalDimension)) {
if (
getIsSizeOptimal(
state.controlLayers.present.size.width,
state.controlLayers.present.size.height,
optimalDimension
)
) {
return;
}
const { width, height } = calculateNewSize(bbox.aspectRatio.value, optimalDimension * optimalDimension);
const { width, height } = calculateNewSize(
state.controlLayers.present.size.aspectRatio.value,
optimalDimension * optimalDimension
);
dispatch(bboxWidthChanged({ width }));
dispatch(bboxHeightChanged({ height }));
dispatch(widthChanged({ width }));
dispatch(heightChanged({ height }));
return;
}
}
@ -102,11 +104,11 @@ const handleMainModels: ModelHandler = (models, state, dispatch, log) => {
return;
}
dispatch(modelChanged({ model: result.data, previousModel: currentModel }));
dispatch(modelChanged(result.data, currentModel));
};
const handleRefinerModels: ModelHandler = (models, state, dispatch, _log) => {
const currentRefinerModel = state.params.refinerModel;
const currentRefinerModel = state.sdxl.refinerModel;
const refinerModels = models.filter(isRefinerMainModelModelConfig);
if (models.length === 0) {
// No models loaded at all
@ -125,7 +127,7 @@ const handleRefinerModels: ModelHandler = (models, state, dispatch, _log) => {
};
const handleVAEModels: ModelHandler = (models, state, dispatch, log) => {
const currentVae = state.params.vae;
const currentVae = state.generation.vae;
if (currentVae === null) {
// null is a valid VAE! it means "use the default with the main model"
@ -158,47 +160,28 @@ const handleVAEModels: ModelHandler = (models, state, dispatch, log) => {
};
const handleLoRAModels: ModelHandler = (models, state, dispatch, _log) => {
const loraModels = models.filter(isLoRAModelConfig);
state.loras.loras.forEach((lora) => {
const isLoRAAvailable = loraModels.some((m) => m.key === lora.model.key);
const loras = state.lora.loras;
forEach(loras, (lora, id) => {
const isLoRAAvailable = models.some((m) => m.key === lora.model.key);
if (isLoRAAvailable) {
return;
}
dispatch(loraDeleted({ id: lora.id }));
dispatch(loraRemoved(id));
});
};
const handleControlAdapterModels: ModelHandler = (models, state, dispatch, _log) => {
const caModels = models.filter(isControlNetOrT2IAdapterModelConfig);
selectCanvasSlice(state).controlLayers.entities.forEach((entity) => {
const isModelAvailable = caModels.some((m) => m.key === entity.controlAdapter.model?.key);
selectControlAdapterAll(state.controlAdapters).forEach((ca) => {
const isModelAvailable = models.some((m) => m.key === ca.model?.key);
if (isModelAvailable) {
return;
}
dispatch(controlLayerModelChanged({ entityIdentifier: getEntityIdentifier(entity), modelConfig: null }));
});
};
const handleIPAdapterModels: ModelHandler = (models, state, dispatch, _log) => {
const ipaModels = models.filter(isIPAdapterModelConfig);
selectCanvasSlice(state).ipAdapters.entities.forEach((entity) => {
const isModelAvailable = ipaModels.some((m) => m.key === entity.ipAdapter.model?.key);
if (isModelAvailable) {
return;
}
dispatch(ipaModelChanged({ entityIdentifier: getEntityIdentifier(entity), modelConfig: null }));
});
selectCanvasSlice(state).regions.entities.forEach((entity) => {
entity.ipAdapters.forEach(({ id: ipAdapterId, model }) => {
const isModelAvailable = ipaModels.some((m) => m.key === model?.key);
if (isModelAvailable) {
return;
}
dispatch(
rgIPAdapterModelChanged({ entityIdentifier: getEntityIdentifier(entity), ipAdapterId, modelConfig: null })
);
});
dispatch(controlAdapterModelCleared({ id: ca.id }));
});
};

View File

@ -1,6 +1,6 @@
import { isAnyOf } from '@reduxjs/toolkit';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { positivePromptChanged } from 'features/controlLayers/store/paramsSlice';
import { positivePromptChanged } from 'features/controlLayers/store/controlLayersSlice';
import {
combinatorialToggled,
isErrorChanged,
@ -13,9 +13,8 @@ import {
import { getShouldProcessPrompt } from 'features/dynamicPrompts/util/getShouldProcessPrompt';
import { getPresetModifiedPrompts } from 'features/nodes/util/graph/graphBuilderUtils';
import { activeStylePresetIdChanged } from 'features/stylePresets/store/stylePresetSlice';
import { stylePresetsApi } from 'services/api/endpoints/stylePresets';
import { utilitiesApi } from 'services/api/endpoints/utilities';
import { socketConnected } from 'services/events/setEventListeners';
import { socketConnected } from 'services/events/actions';
const matcher = isAnyOf(
positivePromptChanged,
@ -23,8 +22,7 @@ const matcher = isAnyOf(
maxPromptsChanged,
maxPromptsReset,
socketConnected,
activeStylePresetIdChanged,
stylePresetsApi.endpoints.listStylePresets.matchFulfilled
activeStylePresetIdChanged
);
export const addDynamicPromptsListener = (startAppListening: AppStartListening) => {

View File

@ -1,5 +1,6 @@
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { bboxHeightChanged, bboxWidthChanged } from 'features/controlLayers/store/canvasSlice';
import { heightChanged, widthChanged } from 'features/controlLayers/store/controlLayersSlice';
import { setDefaultSettings } from 'features/parameters/store/actions';
import {
setCfgRescaleMultiplier,
setCfgScale,
@ -7,8 +8,7 @@ import {
setSteps,
vaePrecisionChanged,
vaeSelected,
} from 'features/controlLayers/store/paramsSlice';
import { setDefaultSettings } from 'features/parameters/store/actions';
} from 'features/parameters/store/generationSlice';
import {
isParameterCFGRescaleMultiplier,
isParameterCFGScale,
@ -30,7 +30,7 @@ export const addSetDefaultSettingsListener = (startAppListening: AppStartListeni
effect: async (action, { dispatch, getState }) => {
const state = getState();
const currentModel = state.params.model;
const currentModel = state.generation.model;
if (!currentModel) {
return;
@ -98,13 +98,13 @@ export const addSetDefaultSettingsListener = (startAppListening: AppStartListeni
const setSizeOptions = { updateAspectRatio: true, clamp: true };
if (width) {
if (isParameterWidth(width)) {
dispatch(bboxWidthChanged({ width, ...setSizeOptions }));
dispatch(widthChanged({ width, ...setSizeOptions }));
}
}
if (height) {
if (isParameterHeight(height)) {
dispatch(bboxHeightChanged({ height, ...setSizeOptions }));
dispatch(heightChanged({ height, ...setSizeOptions }));
}
}

View File

@ -6,9 +6,9 @@ import { atom } from 'nanostores';
import { api } from 'services/api';
import { modelsApi } from 'services/api/endpoints/models';
import { queueApi, selectQueueStatus } from 'services/api/endpoints/queue';
import { socketConnected } from 'services/events/setEventListeners';
import { socketConnected } from 'services/events/actions';
const log = logger('events');
const log = logger('socketio');
const $isFirstConnection = atom(true);

View File

@ -0,0 +1,14 @@
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { socketDisconnected } from 'services/events/actions';
const log = logger('socketio');
export const addSocketDisconnectedEventListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: socketDisconnected,
effect: () => {
log.debug('Disconnected');
},
});
};

View File

@ -0,0 +1,26 @@
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 { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
import { zNodeStatus } from 'features/nodes/types/invocation';
import { socketGeneratorProgress } from 'services/events/actions';
const log = logger('socketio');
export const addGeneratorProgressEventListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: socketGeneratorProgress,
effect: (action) => {
log.trace(parseify(action.payload), `Generator progress`);
const { invocation_source_id, step, total_steps, progress_image } = action.payload.data;
const nes = deepClone($nodeExecutionStates.get()[invocation_source_id]);
if (nes) {
nes.status = zNodeStatus.enum.IN_PROGRESS;
nes.progress = (step + 1) / total_steps;
nes.progressImage = progress_image ?? null;
upsertExecutionState(nes.nodeId, nes);
}
},
});
};

View File

@ -0,0 +1,122 @@
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,
isImageViewerOpenChanged,
offsetChanged,
} from 'features/gallery/store/gallerySlice';
import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
import { zNodeStatus } from 'features/nodes/types/invocation';
import { CANVAS_OUTPUT } from 'features/nodes/util/graph/constants';
import { boardsApi } from 'services/api/endpoints/boards';
import { imagesApi } from 'services/api/endpoints/images';
import { getCategories, getListImagesUrl } from 'services/api/util';
import { socketInvocationComplete } from 'services/events/actions';
// These nodes output an image, but do not actually *save* an image, so we don't want to handle the gallery logic on them
const nodeTypeDenylist = ['load_image', 'image'];
const log = logger('socketio');
export const addInvocationCompleteEventListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: socketInvocationComplete,
effect: async (action, { dispatch, getState }) => {
const { data } = action.payload;
log.debug({ data: parseify(data) }, `Invocation complete (${data.invocation.type})`);
const { result, invocation_source_id } = data;
// This complete event has an associated image output
if (data.result.type === 'image_output' && !nodeTypeDenylist.includes(data.invocation.type)) {
const { image_name } = data.result.image;
const { canvas, gallery } = getState();
// This populates the `getImageDTO` cache
const imageDTORequest = dispatch(
imagesApi.endpoints.getImageDTO.initiate(image_name, {
forceRefetch: true,
})
);
const imageDTO = await imageDTORequest.unwrap();
imageDTORequest.unsubscribe();
// Add canvas images to the staging area
if (canvas.batchIds.includes(data.batch_id) && data.invocation_source_id === CANVAS_OUTPUT) {
dispatch(addImageToStagingArea(imageDTO));
}
if (!imageDTO.is_intermediate) {
// update the total images for the board
dispatch(
boardsApi.util.updateQueryData('getBoardImagesTotal', imageDTO.board_id ?? 'none', (draft) => {
// eslint-disable-next-line @typescript-eslint/no-unused-vars
draft.total += 1;
})
);
dispatch(
imagesApi.util.invalidateTags([
{ type: 'Board', id: imageDTO.board_id ?? 'none' },
{
type: 'ImageList',
id: getListImagesUrl({
board_id: imageDTO.board_id ?? 'none',
categories: getCategories(imageDTO),
}),
},
])
);
const { shouldAutoSwitch } = gallery;
// If auto-switch is enabled, select the new image
if (shouldAutoSwitch) {
// if auto-add is enabled, switch the gallery view and board if needed as the image comes in
if (gallery.galleryView !== 'images') {
dispatch(galleryViewChanged('images'));
}
if (imageDTO.board_id && imageDTO.board_id !== gallery.selectedBoardId) {
dispatch(
boardIdSelected({
boardId: imageDTO.board_id,
selectedImageName: imageDTO.image_name,
})
);
}
dispatch(offsetChanged({ offset: 0 }));
if (!imageDTO.board_id && gallery.selectedBoardId !== 'none') {
dispatch(
boardIdSelected({
boardId: 'none',
selectedImageName: imageDTO.image_name,
})
);
}
dispatch(imageSelected(imageDTO));
dispatch(isImageViewerOpenChanged(true));
}
}
}
const nes = deepClone($nodeExecutionStates.get()[invocation_source_id]);
if (nes) {
nes.status = zNodeStatus.enum.COMPLETED;
if (nes.progress !== null) {
nes.progress = 1;
}
nes.outputs.push(result);
upsertExecutionState(nes.nodeId, nes);
}
},
});
};

View File

@ -0,0 +1,31 @@
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 { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
import { zNodeStatus } from 'features/nodes/types/invocation';
import { socketInvocationError } from 'services/events/actions';
const log = logger('socketio');
export const addInvocationErrorEventListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: socketInvocationError,
effect: (action) => {
const { invocation_source_id, invocation, error_type, error_message, error_traceback } = action.payload.data;
log.error(parseify(action.payload), `Invocation error (${invocation.type})`);
const nes = deepClone($nodeExecutionStates.get()[invocation_source_id]);
if (nes) {
nes.status = zNodeStatus.enum.FAILED;
nes.progress = null;
nes.progressImage = null;
nes.error = {
error_type,
error_message,
error_traceback,
};
upsertExecutionState(nes.nodeId, nes);
}
},
});
};

View File

@ -0,0 +1,24 @@
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 { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
import { zNodeStatus } from 'features/nodes/types/invocation';
import { socketInvocationStarted } from 'services/events/actions';
const log = logger('socketio');
export const addInvocationStartedEventListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: socketInvocationStarted,
effect: (action) => {
log.debug(parseify(action.payload), `Invocation started (${action.payload.data.invocation.type})`);
const { invocation_source_id } = action.payload.data;
const nes = deepClone($nodeExecutionStates.get()[invocation_source_id]);
if (nes) {
nes.status = zNodeStatus.enum.IN_PROGRESS;
upsertExecutionState(nes.nodeId, nes);
}
},
});
};

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@ -0,0 +1,196 @@
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { api, LIST_TAG } from 'services/api';
import { modelsApi } from 'services/api/endpoints/models';
import {
socketModelInstallCancelled,
socketModelInstallComplete,
socketModelInstallDownloadProgress,
socketModelInstallDownloadsComplete,
socketModelInstallDownloadStarted,
socketModelInstallError,
socketModelInstallStarted,
} from 'services/events/actions';
/**
* A model install has two main stages - downloading and installing. All these events are namespaced under `model_install_`
* which is a bit misleading. For example, a `model_install_started` event is actually fired _after_ the model has fully
* downloaded and is being "physically" installed.
*
* Note: the download events are only fired for remote model installs, not local.
*
* Here's the expected flow:
* - API receives install request, model manager preps the install
* - `model_install_download_started` fired when the download starts
* - `model_install_download_progress` fired continually until the download is complete
* - `model_install_download_complete` fired when the download is complete
* - `model_install_started` fired when the "physical" installation starts
* - `model_install_complete` fired when the installation is complete
* - `model_install_cancelled` fired if the installation is cancelled
* - `model_install_error` fired if the installation has an error
*/
const selectModelInstalls = modelsApi.endpoints.listModelInstalls.select();
export const addModelInstallEventListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: socketModelInstallDownloadStarted,
effect: async (action, { dispatch, getState }) => {
const { id } = action.payload.data;
const { data } = selectModelInstalls(getState());
if (!data || !data.find((m) => m.id === id)) {
dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
} else {
dispatch(
modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
const modelImport = draft.find((m) => m.id === id);
if (modelImport) {
modelImport.status = 'downloading';
}
return draft;
})
);
}
},
});
startAppListening({
actionCreator: socketModelInstallStarted,
effect: async (action, { dispatch, getState }) => {
const { id } = action.payload.data;
const { data } = selectModelInstalls(getState());
if (!data || !data.find((m) => m.id === id)) {
dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
} else {
dispatch(
modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
const modelImport = draft.find((m) => m.id === id);
if (modelImport) {
modelImport.status = 'running';
}
return draft;
})
);
}
},
});
startAppListening({
actionCreator: socketModelInstallDownloadProgress,
effect: async (action, { dispatch, getState }) => {
const { bytes, total_bytes, id } = action.payload.data;
const { data } = selectModelInstalls(getState());
if (!data || !data.find((m) => m.id === id)) {
dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
} else {
dispatch(
modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
const modelImport = draft.find((m) => m.id === id);
if (modelImport) {
modelImport.bytes = bytes;
modelImport.total_bytes = total_bytes;
modelImport.status = 'downloading';
}
return draft;
})
);
}
},
});
startAppListening({
actionCreator: socketModelInstallComplete,
effect: (action, { dispatch, getState }) => {
const { id } = action.payload.data;
const { data } = selectModelInstalls(getState());
if (!data || !data.find((m) => m.id === id)) {
dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
} else {
dispatch(
modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
const modelImport = draft.find((m) => m.id === id);
if (modelImport) {
modelImport.status = 'completed';
}
return draft;
})
);
}
dispatch(api.util.invalidateTags([{ type: 'ModelConfig', id: LIST_TAG }]));
dispatch(api.util.invalidateTags([{ type: 'ModelScanFolderResults', id: LIST_TAG }]));
},
});
startAppListening({
actionCreator: socketModelInstallError,
effect: (action, { dispatch, getState }) => {
const { id, error, error_type } = action.payload.data;
const { data } = selectModelInstalls(getState());
if (!data || !data.find((m) => m.id === id)) {
dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
} else {
dispatch(
modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
const modelImport = draft.find((m) => m.id === id);
if (modelImport) {
modelImport.status = 'error';
modelImport.error_reason = error_type;
modelImport.error = error;
}
return draft;
})
);
}
},
});
startAppListening({
actionCreator: socketModelInstallCancelled,
effect: (action, { dispatch, getState }) => {
const { id } = action.payload.data;
const { data } = selectModelInstalls(getState());
if (!data || !data.find((m) => m.id === id)) {
dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
} else {
dispatch(
modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
const modelImport = draft.find((m) => m.id === id);
if (modelImport) {
modelImport.status = 'cancelled';
}
return draft;
})
);
}
},
});
startAppListening({
actionCreator: socketModelInstallDownloadsComplete,
effect: (action, { dispatch, getState }) => {
const { id } = action.payload.data;
const { data } = selectModelInstalls(getState());
if (!data || !data.find((m) => m.id === id)) {
dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
} else {
dispatch(
modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
const modelImport = draft.find((m) => m.id === id);
if (modelImport) {
modelImport.status = 'downloads_done';
}
return draft;
})
);
}
},
});
};

View File

@ -0,0 +1,42 @@
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { socketModelLoadComplete, socketModelLoadStarted } from 'services/events/actions';
const log = logger('socketio');
export const addModelLoadEventListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: socketModelLoadStarted,
effect: (action) => {
const { config, submodel_type } = action.payload.data;
const { name, base, type } = config;
const extras: string[] = [base, type];
if (submodel_type) {
extras.push(submodel_type);
}
const message = `Model load started: ${name} (${extras.join(', ')})`;
log.debug(action.payload, message);
},
});
startAppListening({
actionCreator: socketModelLoadComplete,
effect: (action) => {
const { config, submodel_type } = action.payload.data;
const { name, base, type } = config;
const extras: string[] = [base, type];
if (submodel_type) {
extras.push(submodel_type);
}
const message = `Model load complete: ${name} (${extras.join(', ')})`;
log.debug(action.payload, message);
},
});
};

View File

@ -0,0 +1,114 @@
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 ErrorToastDescription, { getTitleFromErrorType } from 'features/toast/ErrorToastDescription';
import { toast } from 'features/toast/toast';
import { forEach } from 'lodash-es';
import { queueApi, queueItemsAdapter } from 'services/api/endpoints/queue';
import { socketQueueItemStatusChanged } from 'services/events/actions';
const log = logger('socketio');
export const addSocketQueueItemStatusChangedEventListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: socketQueueItemStatusChanged,
effect: async (action, { dispatch, getState }) => {
// we've got new status for the queue item, batch and queue
const {
item_id,
session_id,
status,
started_at,
updated_at,
completed_at,
batch_status,
queue_status,
error_type,
error_message,
error_traceback,
} = action.payload.data;
log.debug(action.payload, `Queue item ${item_id} status updated: ${status}`);
// Update this specific queue item in the list of queue items (this is the queue item DTO, without the session)
dispatch(
queueApi.util.updateQueryData('listQueueItems', undefined, (draft) => {
queueItemsAdapter.updateOne(draft, {
id: String(item_id),
changes: {
status,
started_at,
updated_at: updated_at ?? undefined,
completed_at: completed_at ?? undefined,
error_type,
error_message,
error_traceback,
},
});
})
);
// Update the queue status (we do not get the processor status here)
dispatch(
queueApi.util.updateQueryData('getQueueStatus', undefined, (draft) => {
if (!draft) {
return;
}
Object.assign(draft.queue, queue_status);
})
);
// Update the batch status
dispatch(
queueApi.util.updateQueryData('getBatchStatus', { batch_id: batch_status.batch_id }, () => batch_status)
);
// Invalidate caches for things we cannot update
// TODO: technically, we could possibly update the current session queue item, but feels safer to just request it again
dispatch(
queueApi.util.invalidateTags([
'CurrentSessionQueueItem',
'NextSessionQueueItem',
'InvocationCacheStatus',
{ type: 'SessionQueueItem', id: item_id },
])
);
if (status === 'in_progress') {
forEach($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 = [];
$nodeExecutionStates.setKey(clone.nodeId, clone);
});
} else if (status === 'failed' && error_type) {
const isLocal = getState().config.isLocal ?? true;
const sessionId = session_id;
toast({
id: `INVOCATION_ERROR_${error_type}`,
title: getTitleFromErrorType(error_type),
status: 'error',
duration: null,
updateDescription: isLocal,
description: (
<ErrorToastDescription
errorType={error_type}
errorMessage={error_message}
sessionId={sessionId}
isLocal={isLocal}
/>
),
});
}
},
});
};

View File

@ -0,0 +1,43 @@
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { stagingAreaImageSaved } from 'features/canvas/store/actions';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { imagesApi } from 'services/api/endpoints/images';
export const addStagingAreaImageSavedListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: stagingAreaImageSaved,
effect: async (action, { dispatch, getState }) => {
const { imageDTO } = action.payload;
try {
const newImageDTO = await dispatch(
imagesApi.endpoints.changeImageIsIntermediate.initiate({
imageDTO,
is_intermediate: false,
})
).unwrap();
// we may need to add it to the autoadd board
const { autoAddBoardId } = getState().gallery;
if (autoAddBoardId && autoAddBoardId !== 'none') {
await dispatch(
imagesApi.endpoints.addImageToBoard.initiate({
imageDTO: newImageDTO,
board_id: autoAddBoardId,
})
);
}
toast({ id: 'IMAGE_SAVED', title: t('toast.imageSaved'), status: 'success' });
} catch (error) {
toast({
id: 'IMAGE_SAVE_FAILED',
title: t('toast.imageSavingFailed'),
description: (error as Error)?.message,
status: 'error',
});
}
},
});
};

View File

@ -2,20 +2,18 @@ import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { updateAllNodesRequested } from 'features/nodes/store/actions';
import { $templates, nodesChanged } from 'features/nodes/store/nodesSlice';
import { selectNodes } from 'features/nodes/store/selectors';
import { NodeUpdateError } from 'features/nodes/types/error';
import { isInvocationNode } from 'features/nodes/types/invocation';
import { getNeedsUpdate, updateNode } from 'features/nodes/util/node/nodeUpdate';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
const log = logger('workflows');
export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartListening) => {
startAppListening({
actionCreator: updateAllNodesRequested,
effect: (action, { dispatch, getState }) => {
const nodes = selectNodes(getState());
const log = logger('nodes');
const { nodes } = getState().nodes.present;
const templates = $templates.get();
let unableToUpdateCount = 0;

View File

@ -1,6 +1,6 @@
import { logger } from 'app/logging/logger';
import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
import { $nodeExecutionStates } from 'features/nodes/hooks/useExecutionState';
import { parseify } from 'common/util/serialize';
import { workflowLoaded, workflowLoadRequested } from 'features/nodes/store/actions';
import { $templates } from 'features/nodes/store/nodesSlice';
import { $needsFit } from 'features/nodes/store/reactFlowInstance';
@ -10,14 +10,11 @@ import { graphToWorkflow } from 'features/nodes/util/workflow/graphToWorkflow';
import { validateWorkflow } from 'features/nodes/util/workflow/validateWorkflow';
import { toast } from 'features/toast/toast';
import { t } from 'i18next';
import { serializeError } from 'serialize-error';
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 log = logger('workflows');
const getWorkflow = async (data: GraphAndWorkflowResponse, templates: Templates) => {
if (data.workflow) {
// Prefer to load the workflow if it's available - it has more information
@ -37,6 +34,7 @@ export const addWorkflowLoadRequestedListener = (startAppListening: AppStartList
startAppListening({
actionCreator: workflowLoadRequested,
effect: async (action, { dispatch }) => {
const log = logger('nodes');
const { data, asCopy } = action.payload;
const nodeTemplates = $templates.get();
@ -48,7 +46,6 @@ export const addWorkflowLoadRequestedListener = (startAppListening: AppStartList
delete workflow.id;
}
$nodeExecutionStates.set({});
dispatch(workflowLoaded(workflow));
if (!warnings.length) {
toast({
@ -72,7 +69,7 @@ export const addWorkflowLoadRequestedListener = (startAppListening: AppStartList
} catch (e) {
if (e instanceof WorkflowVersionError) {
// The workflow version was not recognized in the valid list of versions
log.error({ error: serializeError(e) }, e.message);
log.error({ error: parseify(e) }, e.message);
toast({
id: 'UNABLE_TO_VALIDATE_WORKFLOW',
title: t('nodes.unableToValidateWorkflow'),
@ -81,7 +78,7 @@ export const addWorkflowLoadRequestedListener = (startAppListening: AppStartList
});
} else if (e instanceof WorkflowMigrationError) {
// There was a problem migrating the workflow to the latest version
log.error({ error: serializeError(e) }, e.message);
log.error({ error: parseify(e) }, e.message);
toast({
id: 'UNABLE_TO_VALIDATE_WORKFLOW',
title: t('nodes.unableToValidateWorkflow'),
@ -93,7 +90,7 @@ export const addWorkflowLoadRequestedListener = (startAppListening: AppStartList
const { message } = fromZodError(e, {
prefix: t('nodes.workflowValidation'),
});
log.error({ error: serializeError(e) }, message);
log.error({ error: parseify(e) }, message);
toast({
id: 'UNABLE_TO_VALIDATE_WORKFLOW',
title: t('nodes.unableToValidateWorkflow'),
@ -102,7 +99,7 @@ export const addWorkflowLoadRequestedListener = (startAppListening: AppStartList
});
} else {
// Some other error occurred
log.error({ error: serializeError(e) }, t('nodes.unknownErrorValidatingWorkflow'));
log.error({ error: parseify(e) }, t('nodes.unknownErrorValidatingWorkflow'));
toast({
id: 'UNABLE_TO_VALIDATE_WORKFLOW',
title: t('nodes.unableToValidateWorkflow'),

View File

@ -1,5 +1,4 @@
import { useStore } from '@nanostores/react';
import type { AppStore } from 'app/store/store';
import type { createStore } from 'app/store/store';
import { atom } from 'nanostores';
// Inject socket options and url into window for debugging
@ -23,7 +22,7 @@ class ReduxStoreNotInitialized extends Error {
}
}
export const $store = atom<Readonly<AppStore | undefined>>();
export const $store = atom<Readonly<ReturnType<typeof createStore>> | undefined>();
export const getStore = () => {
const store = $store.get();
@ -32,11 +31,3 @@ export const getStore = () => {
}
return store;
};
export const useAppStore = () => {
const store = useStore($store);
if (!store) {
throw new ReduxStoreNotInitialized();
}
return store;
};

View File

@ -3,31 +3,37 @@ import { autoBatchEnhancer, combineReducers, configureStore } from '@reduxjs/too
import { logger } from 'app/logging/logger';
import { idbKeyValDriver } from 'app/store/enhancers/reduxRemember/driver';
import { errorHandler } from 'app/store/enhancers/reduxRemember/errors';
import type { SerializableObject } from 'common/types';
import { deepClone } from 'common/util/deepClone';
import type { JSONObject } from 'common/types';
import { canvasPersistConfig, canvasSlice } from 'features/canvas/store/canvasSlice';
import { changeBoardModalSlice } from 'features/changeBoardModal/store/slice';
import { canvasSessionPersistConfig, canvasSessionSlice } from 'features/controlLayers/store/canvasSessionSlice';
import { canvasSettingsPersistConfig, canvasSettingsSlice } from 'features/controlLayers/store/canvasSettingsSlice';
import { canvasPersistConfig, canvasSlice, canvasUndoableConfig } from 'features/controlLayers/store/canvasSlice';
import { lorasPersistConfig, lorasSlice } from 'features/controlLayers/store/lorasSlice';
import { paramsPersistConfig, paramsSlice } from 'features/controlLayers/store/paramsSlice';
import { toolPersistConfig, toolSlice } from 'features/controlLayers/store/toolSlice';
import {
controlAdaptersPersistConfig,
controlAdaptersSlice,
} from 'features/controlAdapters/store/controlAdaptersSlice';
import {
controlLayersPersistConfig,
controlLayersSlice,
controlLayersUndoableConfig,
} from 'features/controlLayers/store/controlLayersSlice';
import { deleteImageModalSlice } from 'features/deleteImageModal/store/slice';
import { dynamicPromptsPersistConfig, dynamicPromptsSlice } from 'features/dynamicPrompts/store/dynamicPromptsSlice';
import { galleryPersistConfig, gallerySlice } from 'features/gallery/store/gallerySlice';
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, 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 { upscalePersistConfig, upscaleSlice } from 'features/parameters/store/upscaleSlice';
import { queueSlice } from 'features/queue/store/queueSlice';
import { sdxlPersistConfig, sdxlSlice } from 'features/sdxl/store/sdxlSlice';
import { stylePresetPersistConfig, stylePresetSlice } from 'features/stylePresets/store/stylePresetSlice';
import { configSlice } from 'features/system/store/configSlice';
import { systemPersistConfig, systemSlice } from 'features/system/store/systemSlice';
import { uiPersistConfig, uiSlice } from 'features/ui/store/uiSlice';
import { diff } from 'jsondiffpatch';
import { keys, mergeWith, omit, pick } from 'lodash-es';
import { defaultsDeep, keys, omit, pick } from 'lodash-es';
import dynamicMiddlewares from 'redux-dynamic-middlewares';
import type { SerializeFunction, UnserializeFunction } from 'redux-remember';
import { rememberEnhancer, rememberReducer } from 'redux-remember';
@ -42,31 +48,29 @@ import { actionsDenylist } from './middleware/devtools/actionsDenylist';
import { stateSanitizer } from './middleware/devtools/stateSanitizer';
import { listenerMiddleware } from './middleware/listenerMiddleware';
const log = logger('system');
const allReducers = {
[api.reducerPath]: api.reducer,
[canvasSlice.name]: canvasSlice.reducer,
[gallerySlice.name]: gallerySlice.reducer,
[generationSlice.name]: generationSlice.reducer,
[nodesSlice.name]: undoable(nodesSlice.reducer, nodesUndoableConfig),
[systemSlice.name]: systemSlice.reducer,
[configSlice.name]: configSlice.reducer,
[uiSlice.name]: uiSlice.reducer,
[controlAdaptersSlice.name]: controlAdaptersSlice.reducer,
[dynamicPromptsSlice.name]: dynamicPromptsSlice.reducer,
[deleteImageModalSlice.name]: deleteImageModalSlice.reducer,
[changeBoardModalSlice.name]: changeBoardModalSlice.reducer,
[loraSlice.name]: loraSlice.reducer,
[modelManagerV2Slice.name]: modelManagerV2Slice.reducer,
[sdxlSlice.name]: sdxlSlice.reducer,
[queueSlice.name]: queueSlice.reducer,
[workflowSlice.name]: workflowSlice.reducer,
[hrfSlice.name]: hrfSlice.reducer,
[canvasSlice.name]: undoable(canvasSlice.reducer, canvasUndoableConfig),
[controlLayersSlice.name]: undoable(controlLayersSlice.reducer, controlLayersUndoableConfig),
[workflowSettingsSlice.name]: workflowSettingsSlice.reducer,
[api.reducerPath]: api.reducer,
[upscaleSlice.name]: upscaleSlice.reducer,
[stylePresetSlice.name]: stylePresetSlice.reducer,
[paramsSlice.name]: paramsSlice.reducer,
[toolSlice.name]: toolSlice.reducer,
[canvasSettingsSlice.name]: canvasSettingsSlice.reducer,
[canvasSessionSlice.name]: canvasSessionSlice.reducer,
[lorasSlice.name]: lorasSlice.reducer,
};
const rootReducer = combineReducers(allReducers);
@ -96,26 +100,27 @@ export type PersistConfig<T = any> = {
};
const persistConfigs: { [key in keyof typeof allReducers]?: PersistConfig } = {
[canvasPersistConfig.name]: canvasPersistConfig,
[galleryPersistConfig.name]: galleryPersistConfig,
[generationPersistConfig.name]: generationPersistConfig,
[nodesPersistConfig.name]: nodesPersistConfig,
[systemPersistConfig.name]: systemPersistConfig,
[workflowPersistConfig.name]: workflowPersistConfig,
[uiPersistConfig.name]: uiPersistConfig,
[controlAdaptersPersistConfig.name]: controlAdaptersPersistConfig,
[dynamicPromptsPersistConfig.name]: dynamicPromptsPersistConfig,
[sdxlPersistConfig.name]: sdxlPersistConfig,
[loraPersistConfig.name]: loraPersistConfig,
[modelManagerV2PersistConfig.name]: modelManagerV2PersistConfig,
[hrfPersistConfig.name]: hrfPersistConfig,
[canvasPersistConfig.name]: canvasPersistConfig,
[controlLayersPersistConfig.name]: controlLayersPersistConfig,
[workflowSettingsPersistConfig.name]: workflowSettingsPersistConfig,
[upscalePersistConfig.name]: upscalePersistConfig,
[stylePresetPersistConfig.name]: stylePresetPersistConfig,
[paramsPersistConfig.name]: paramsPersistConfig,
[toolPersistConfig.name]: toolPersistConfig,
[canvasSettingsPersistConfig.name]: canvasSettingsPersistConfig,
[canvasSessionPersistConfig.name]: canvasSessionPersistConfig,
[lorasPersistConfig.name]: lorasPersistConfig,
};
const unserialize: UnserializeFunction = (data, key) => {
const log = logger('system');
const persistConfig = persistConfigs[key as keyof typeof persistConfigs];
if (!persistConfig) {
throw new Error(`No persist config for slice "${key}"`);
@ -125,21 +130,17 @@ const unserialize: UnserializeFunction = (data, key) => {
const parsed = JSON.parse(data);
// strip out old keys
const stripped = pick(deepClone(parsed), keys(initialState));
const stripped = pick(parsed, keys(initialState));
// run (additive) migrations
const migrated = migrate(stripped);
/*
* Merge in initial state as default values, covering any missing keys. You might be tempted to use _.defaultsDeep,
* but that merges arrays by index and partial objects by key. Using an identity function as the customizer results
* in behaviour like defaultsDeep, but doesn't overwrite any values that are not undefined in the migrated state.
*/
const transformed = mergeWith(migrated, initialState, (objVal) => objVal);
// merge in initial state as default values, covering any missing keys
const transformed = defaultsDeep(migrated, initialState);
log.debug(
{
persistedData: parsed,
rehydratedData: transformed,
diff: diff(parsed, transformed) as SerializableObject, // this is always serializable
diff: diff(parsed, transformed) as JSONObject, // this is always serializable
},
`Rehydrated slice "${key}"`
);
@ -201,8 +202,7 @@ export const createStore = (uniqueStoreKey?: string, persist = true) =>
},
});
export type AppStore = ReturnType<typeof createStore>;
export type RootState = ReturnType<AppStore['getState']>;
export type RootState = ReturnType<ReturnType<typeof createStore>['getState']>;
// eslint-disable-next-line @typescript-eslint/no-explicit-any
export type AppThunkDispatch = ThunkDispatch<RootState, any, UnknownAction>;
export type AppDispatch = ReturnType<typeof createStore>['dispatch'];

View File

@ -1,6 +1,6 @@
import type { FilterType } from 'features/controlLayers/store/types';
import type { CONTROLNET_PROCESSORS } from 'features/controlAdapters/store/constants';
import type { ParameterPrecision, ParameterScheduler } from 'features/parameters/types/parameterSchemas';
import type { TabName } from 'features/ui/store/uiTypes';
import type { InvokeTabName } from 'features/ui/store/tabMap';
import type { O } from 'ts-toolbelt';
/**
@ -72,7 +72,7 @@ export type AppConfig = {
maxUpscaleDimension?: number;
allowPrivateBoards: boolean;
allowPrivateStylePresets: boolean;
disabledTabs: TabName[];
disabledTabs: InvokeTabName[];
disabledFeatures: AppFeature[];
disabledSDFeatures: SDFeature[];
nodesAllowlist: string[] | undefined;
@ -83,7 +83,7 @@ export type AppConfig = {
sd: {
defaultModel?: string;
disabledControlNetModels: string[];
disabledControlNetProcessors: FilterType[];
disabledControlNetProcessors: (keyof typeof CONTROLNET_PROCESSORS)[];
// Core parameters
iterations: NumericalParameterConfig;
width: NumericalParameterConfig; // initial value comes from model

View File

@ -33,23 +33,28 @@ type IAINoImageFallbackProps = FlexProps & {
};
export const IAINoContentFallback = memo((props: IAINoImageFallbackProps) => {
const { icon = PiImageBold, boxSize = 16, ...rest } = props;
const { icon = PiImageBold, boxSize = 16, sx, ...rest } = props;
const styles = useMemo(
() => ({
w: 'full',
h: 'full',
alignItems: 'center',
justifyContent: 'center',
borderRadius: 'base',
flexDir: 'column',
gap: 2,
userSelect: 'none',
opacity: 0.7,
color: 'base.500',
fontSize: 'md',
...sx,
}),
[sx]
);
return (
<Flex
w="full"
h="full"
alignItems="center"
justifyContent="center"
borderRadius="base"
flexDir="column"
gap={2}
userSelect="none"
opacity={0.7}
color="base.500"
fontSize="md"
{...rest}
>
<Flex sx={styles} {...rest}>
{icon && <Icon as={icon} boxSize={boxSize} opacity={0.7} />}
{props.label && <Text textAlign="center">{props.label}</Text>}
</Flex>

View File

@ -13,9 +13,8 @@ import {
Spacer,
Text,
} from '@invoke-ai/ui-library';
import { createSelector } from '@reduxjs/toolkit';
import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
import { selectSystemSlice, setShouldEnableInformationalPopovers } from 'features/system/store/systemSlice';
import { setShouldEnableInformationalPopovers } from 'features/system/store/systemSlice';
import { toast } from 'features/toast/toast';
import { merge, omit } from 'lodash-es';
import type { ReactElement } from 'react';
@ -32,13 +31,8 @@ type Props = {
children: ReactElement;
};
const selectShouldEnableInformationalPopovers = createSelector(
selectSystemSlice,
(system) => system.shouldEnableInformationalPopovers
);
export const InformationalPopover = memo(({ feature, children, inPortal = true, ...rest }: Props) => {
const shouldEnableInformationalPopovers = useAppSelector(selectShouldEnableInformationalPopovers);
const shouldEnableInformationalPopovers = useAppSelector((s) => s.system.shouldEnableInformationalPopovers);
const data = useMemo(() => POPOVER_DATA[feature], [feature]);

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