Merge branch 'main' into bugfix/prevent-cli-crash

.github/CODEOWNERS

@@ -1,16 +1,16 @@
 # continuous integration
-/.github/workflows/ @mauwii @lstein @blessedcoolant
+/.github/workflows/  @lstein @blessedcoolant
 
 # documentation
-/docs/ @lstein @mauwii @tildebyte @blessedcoolant
-/mkdocs.yml @lstein @mauwii @blessedcoolant
+/docs/ @lstein  @tildebyte @blessedcoolant
+/mkdocs.yml @lstein  @blessedcoolant
 
 # nodes
 /invokeai/app/ @Kyle0654 @blessedcoolant
 
 # installation and configuration
-/pyproject.toml @mauwii @lstein @blessedcoolant
-/docker/ @mauwii @lstein @blessedcoolant
+/pyproject.toml  @lstein @blessedcoolant
+/docker/  @lstein @blessedcoolant
 /scripts/ @ebr @lstein
 /installer/ @lstein @ebr
 /invokeai/assets @lstein @ebr
@@ -22,11 +22,11 @@
 /invokeai/backend @blessedcoolant @psychedelicious @lstein
 
 # generation, model management, postprocessing
-/invokeai/backend @keturn @damian0815 @lstein @blessedcoolant @jpphoto
+/invokeai/backend  @damian0815 @lstein @blessedcoolant @jpphoto @gregghelt2
 
 # front ends
 /invokeai/frontend/CLI @lstein
-/invokeai/frontend/install @lstein @ebr @mauwii 
+/invokeai/frontend/install @lstein @ebr  
 /invokeai/frontend/merge @lstein @blessedcoolant @hipsterusername
 /invokeai/frontend/training @lstein @blessedcoolant @hipsterusername
 /invokeai/frontend/web @psychedelicious @blessedcoolant

.gitignore

@@ -9,6 +9,8 @@ models/ldm/stable-diffusion-v1/model.ckpt
 configs/models.user.yaml
 config/models.user.yml
 invokeai.init
+.version
+.last_model
 
 # ignore the Anaconda/Miniconda installer used while building Docker image
 anaconda.sh

README.md

@@ -148,6 +148,11 @@ not supported.
     pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/rocm5.4.2
     ```
 
+    _For non-GPU systems:_
+    ```terminal
+    pip install InvokeAI --use-pep517 --extra-index-url https://download.pytorch.org/whl/cpu
+    ``` 
+
     _For Macintoshes, either Intel or M1/M2:_
 
     ```sh

docs/features/NSFW.md

@@ -32,7 +32,7 @@ turned on and off on the command line using `--nsfw_checker` and
 At installation time, InvokeAI will ask whether the checker should be
 activated by default (neither argument given on the command line). The
 response is stored in the InvokeAI initialization file (usually
-`.invokeai` in your home directory). You can change the default at any
+`invokeai.init` in your home directory). You can change the default at any
 time by opening this file in a text editor and commenting or
 uncommenting the line `--nsfw_checker`.
 

invokeai/app/api/dependencies.py

@@ -3,6 +3,8 @@
 import os
 from argparse import Namespace
 
+from invokeai.app.services.metadata import PngMetadataService, MetadataServiceBase
+
 from ..services.default_graphs import create_system_graphs
 
 from ..services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
@@ -60,7 +62,9 @@ class ApiDependencies:
 
         latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f'{output_folder}/latents'))
 
-        images = DiskImageStorage(f'{output_folder}/images')
+        metadata = PngMetadataService()
+
+        images = DiskImageStorage(f'{output_folder}/images', metadata_service=metadata)
 
         # TODO: build a file/path manager?
         db_location = os.path.join(output_folder, "invokeai.db")
@@ -70,6 +74,7 @@ class ApiDependencies:
             events=events,
             latents=latents,
             images=images,
+            metadata=metadata,
             queue=MemoryInvocationQueue(),
             graph_library=SqliteItemStorage[LibraryGraph](
                 filename=db_location, table_name="graphs"

invokeai/app/api/events.py

@@ -45,7 +45,7 @@ class FastAPIEventService(EventServiceBase):
                 )
 
             except Empty:
-                await asyncio.sleep(0.001)
+                await asyncio.sleep(0.1)
                 pass
 
             except asyncio.CancelledError as e:

invokeai/app/api/models/images.py

@@ -1,7 +1,19 @@
+from typing import Optional
 from pydantic import BaseModel, Field
 
 from invokeai.app.models.image import ImageType
-from invokeai.app.models.metadata import ImageMetadata
+from invokeai.app.services.metadata import InvokeAIMetadata
+
+
+class ImageResponseMetadata(BaseModel):
+    """An image's metadata. Used only in HTTP responses."""
+
+    created: int = Field(description="The creation timestamp of the image")
+    width: int = Field(description="The width of the image in pixels")
+    height: int = Field(description="The height of the image in pixels")
+    invokeai: Optional[InvokeAIMetadata] = Field(
+        description="The image's InvokeAI-specific metadata"
+    )
 
 
 class ImageResponse(BaseModel):
@@ -11,4 +23,12 @@ class ImageResponse(BaseModel):
     image_name: str = Field(description="The name of the image")
     image_url: str = Field(description="The url of the image")
     thumbnail_url: str = Field(description="The url of the image's thumbnail")
-    metadata: ImageMetadata = Field(description="The image's metadata")
+    metadata: ImageResponseMetadata = Field(description="The image's metadata")
+
+
+class ProgressImage(BaseModel):
+    """The progress image sent intermittently during processing"""
+
+    width: int = Field(description="The effective width of the image in pixels")
+    height: int = Field(description="The effective height of the image in pixels")
+    dataURL: str = Field(description="The image data as a b64 data URL")

invokeai/app/api/routers/images.py

@@ -1,13 +1,17 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
-
+import io
 from datetime import datetime, timezone
+import json
+import os
+from typing import Any
 import uuid
 
-from fastapi import Path, Query, Request, UploadFile
+from fastapi import HTTPException, Path, Query, Request, UploadFile
 from fastapi.responses import FileResponse, Response
 from fastapi.routing import APIRouter
 from PIL import Image
-from invokeai.app.api.models.images import ImageResponse
+from invokeai.app.api.models.images import ImageResponse, ImageResponseMetadata
+from invokeai.app.services.metadata import InvokeAIMetadata
 from invokeai.app.services.item_storage import PaginatedResults
 
 from ...services.image_storage import ImageType
@@ -15,70 +19,110 @@ from ..dependencies import ApiDependencies
 
 images_router = APIRouter(prefix="/v1/images", tags=["images"])
 
+
 @images_router.get("/{image_type}/{image_name}", operation_id="get_image")
 async def get_image(
     image_type: ImageType = Path(description="The type of image to get"),
     image_name: str = Path(description="The name of the image to get"),
-):
+) -> FileResponse | Response:
     """Gets a result"""
-    # TODO: This is not really secure at all. At least make sure only output results are served
-    filename = ApiDependencies.invoker.services.images.get_path(image_type, image_name)
-    return FileResponse(filename)
 
-@images_router.get("/{image_type}/thumbnails/{image_name}", operation_id="get_thumbnail")
+    path = ApiDependencies.invoker.services.images.get_path(
+        image_type=image_type, image_name=image_name
+    )
+
+    if ApiDependencies.invoker.services.images.validate_path(path):
+        return FileResponse(path)
+    else:
+        raise HTTPException(status_code=404)
+
+
+@images_router.get(
+    "/{image_type}/thumbnails/{image_name}", operation_id="get_thumbnail"
+)
 async def get_thumbnail(
     image_type: ImageType = Path(description="The type of image to get"),
     image_name: str = Path(description="The name of the image to get"),
-):
+) -> FileResponse | Response:
     """Gets a thumbnail"""
-    # TODO: This is not really secure at all. At least make sure only output results are served
-    filename = ApiDependencies.invoker.services.images.get_path(image_type, 'thumbnails/' + image_name)
-    return FileResponse(filename)
+
+    path = ApiDependencies.invoker.services.images.get_path(
+        image_type=image_type, image_name=image_name, is_thumbnail=True
+    )
+
+    if ApiDependencies.invoker.services.images.validate_path(path):
+        return FileResponse(path)
+    else:
+        raise HTTPException(status_code=404)
 
 
 @images_router.post(
     "/uploads/",
     operation_id="upload_image",
     responses={
-        201: {"description": "The image was uploaded successfully"},
-        404: {"description": "Session not found"},
+        201: {
+            "description": "The image was uploaded successfully",
+            "model": ImageResponse,
+        },
+        415: {"description": "Image upload failed"},
     },
+    status_code=201,
 )
-async def upload_image(file: UploadFile, request: Request):
+async def upload_image(
+    file: UploadFile, request: Request, response: Response
+) -> ImageResponse:
     if not file.content_type.startswith("image"):
-        return Response(status_code=415)
+        raise HTTPException(status_code=415, detail="Not an image")
 
     contents = await file.read()
+
     try:
-        im = Image.open(contents)
+        img = Image.open(io.BytesIO(contents))
     except:
         # Error opening the image
-        return Response(status_code=415)
+        raise HTTPException(status_code=415, detail="Failed to read image")
 
     filename = f"{uuid.uuid4()}_{str(int(datetime.now(timezone.utc).timestamp()))}.png"
-    ApiDependencies.invoker.services.images.save(ImageType.UPLOAD, filename, im)
 
-    return Response(
-        status_code=201,
-        headers={
-            "Location": request.url_for(
-                "get_image", image_type=ImageType.UPLOAD.value, image_name=filename
-            )
-        },
+    (image_path, thumbnail_path, ctime) = ApiDependencies.invoker.services.images.save(
+        ImageType.UPLOAD, filename, img
     )
 
+    invokeai_metadata = ApiDependencies.invoker.services.metadata.get_metadata(img)
+
+    res = ImageResponse(
+        image_type=ImageType.UPLOAD,
+        image_name=filename,
+        image_url=f"api/v1/images/{ImageType.UPLOAD.value}/{filename}",
+        thumbnail_url=f"api/v1/images/{ImageType.UPLOAD.value}/thumbnails/{os.path.splitext(filename)[0]}.webp",
+        metadata=ImageResponseMetadata(
+            created=ctime,
+            width=img.width,
+            height=img.height,
+            invokeai=invokeai_metadata,
+        ),
+    )
+
+    response.status_code = 201
+    response.headers["Location"] = request.url_for(
+        "get_image", image_type=ImageType.UPLOAD.value, image_name=filename
+    )
+
+    return res
+
+
 @images_router.get(
     "/",
     operation_id="list_images",
     responses={200: {"model": PaginatedResults[ImageResponse]}},
 )
 async def list_images(
-    image_type: ImageType = Query(default=ImageType.RESULT, description="The type of images to get"),
+    image_type: ImageType = Query(
+        default=ImageType.RESULT, description="The type of images to get"
+    ),
     page: int = Query(default=0, description="The page of images to get"),
     per_page: int = Query(default=10, description="The number of images per page"),
 ) -> PaginatedResults[ImageResponse]:
     """Gets a list of images"""
-    result = ApiDependencies.invoker.services.images.list(
-        image_type, page, per_page
-    )
+    result = ApiDependencies.invoker.services.images.list(image_type, page, per_page)
     return result

invokeai/app/cli_app.py

@@ -13,6 +13,8 @@ from typing import (
 from pydantic import BaseModel
 from pydantic.fields import Field
 
+from invokeai.app.services.metadata import PngMetadataService
+
 from .services.default_graphs import create_system_graphs
 
 from .services.latent_storage import DiskLatentsStorage, ForwardCacheLatentsStorage
@@ -200,6 +202,8 @@ def invoke_cli():
 
     events = EventServiceBase()
 
+    metadata = PngMetadataService()
+
     output_folder = os.path.abspath(
         os.path.join(os.path.dirname(__file__), "../../../outputs")
     )
@@ -211,7 +215,8 @@ def invoke_cli():
         model_manager=model_manager,
         events=events,
         latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f'{output_folder}/latents')),
-        images=DiskImageStorage(f'{output_folder}/images'),
+        images=DiskImageStorage(f'{output_folder}/images', metadata_service=metadata),
+        metadata=metadata,
         queue=MemoryInvocationQueue(),
         graph_library=SqliteItemStorage[LibraryGraph](
             filename=db_location, table_name="graphs"

invokeai/app/invocations/baseinvocation.py

@@ -95,7 +95,7 @@ class UIConfig(TypedDict, total=False):
         ],
     ]
     tags: List[str]
-
+    title: str
 
 class CustomisedSchemaExtra(TypedDict):
     ui: UIConfig

invokeai/app/invocations/collections.py

@@ -1,16 +1,17 @@
 # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
 
-from typing import Literal
+from typing import Literal, Optional
 
-import cv2 as cv
 import numpy as np
 import numpy.random
-from PIL import Image, ImageOps
 from pydantic import Field
 
-from ..services.image_storage import ImageType
-from .baseinvocation import BaseInvocation, InvocationContext, BaseInvocationOutput
-from .image import ImageField, ImageOutput
+from .baseinvocation import (
+    BaseInvocation,
+    InvocationConfig,
+    InvocationContext,
+    BaseInvocationOutput,
+)
 
 
 class IntCollectionOutput(BaseInvocationOutput):
@@ -33,7 +34,9 @@ class RangeInvocation(BaseInvocation):
     step: int = Field(default=1, description="The step of the range")
 
     def invoke(self, context: InvocationContext) -> IntCollectionOutput:
-        return IntCollectionOutput(collection=list(range(self.start, self.stop, self.step)))
+        return IntCollectionOutput(
+            collection=list(range(self.start, self.stop, self.step))
+        )
 
 
 class RandomRangeInvocation(BaseInvocation):
@@ -43,8 +46,19 @@ class RandomRangeInvocation(BaseInvocation):
 
     # Inputs
     low: int = Field(default=0, description="The inclusive low value")
-    high: int = Field(default=np.iinfo(np.int32).max, description="The exclusive high value")
+    high: int = Field(
+        default=np.iinfo(np.int32).max, description="The exclusive high value"
+    )
     size: int = Field(default=1, description="The number of values to generate")
+    seed: Optional[int] = Field(
+        ge=0,
+        le=np.iinfo(np.int32).max,
+        description="The seed for the RNG",
+        default_factory=lambda: numpy.random.randint(0, np.iinfo(np.int32).max),
+    )
 
     def invoke(self, context: InvocationContext) -> IntCollectionOutput:
-        return IntCollectionOutput(collection=list(numpy.random.randint(self.low, self.high, size=self.size)))
+        rng = np.random.default_rng(self.seed)
+        return IntCollectionOutput(
+            collection=list(rng.integers(low=self.low, high=self.high, size=self.size))
+        )

invokeai/app/invocations/cv.py

@@ -9,7 +9,7 @@ from pydantic import BaseModel, Field
 
 from invokeai.app.models.image import ImageField, ImageType
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output
 
 
 class CvInvocationConfig(BaseModel):
@@ -56,7 +56,14 @@ class CvInpaintInvocation(BaseInvocation, CvInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, image_inpainted)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
         )
+        
+        context.services.images.save(image_type, image_name, image_inpainted, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=image_inpainted,
+        )

invokeai/app/invocations/generate.py

@@ -9,13 +9,12 @@ from torch import Tensor
 from pydantic import BaseModel, Field
 
 from invokeai.app.models.image import ImageField, ImageType
-from invokeai.app.invocations.util.get_model import choose_model
+from invokeai.app.invocations.util.choose_model import choose_model
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output
 from ...backend.generator import Txt2Img, Img2Img, Inpaint, InvokeAIGenerator
 from ...backend.stable_diffusion import PipelineIntermediateState
-from ..models.exceptions import CanceledException
-from ..util.step_callback import diffusers_step_callback_adapter
+from ..util.step_callback import stable_diffusion_step_callback
 
 SAMPLER_NAME_VALUES = Literal[tuple(InvokeAIGenerator.schedulers())]
 
@@ -58,28 +57,31 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
 
     # TODO: pass this an emitter method or something? or a session for dispatching?
     def dispatch_progress(
-        self, context: InvocationContext, intermediate_state: PipelineIntermediateState
+        self,
+        context: InvocationContext,
+        source_node_id: str,
+        intermediate_state: PipelineIntermediateState,
     ) -> None:
-        if (context.services.queue.is_canceled(context.graph_execution_state_id)):
-            raise CanceledException
-
-        step = intermediate_state.step
-        if intermediate_state.predicted_original is not None:
-            # Some schedulers report not only the noisy latents at the current timestep,
-            # but also their estimate so far of what the de-noised latents will be.
-            sample = intermediate_state.predicted_original
-        else:
-            sample = intermediate_state.latents
-        
-        diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
+        stable_diffusion_step_callback(
+            context=context,
+            intermediate_state=intermediate_state,
+            node=self.dict(),
+            source_node_id=source_node_id,
+        )
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         # Handle invalid model parameter
         model = choose_model(context.services.model_manager, self.model)
 
+        # Get the source node id (we are invoking the prepared node)
+        graph_execution_state = context.services.graph_execution_manager.get(
+            context.graph_execution_state_id
+        )
+        source_node_id = graph_execution_state.prepared_source_mapping[self.id]
+
         outputs = Txt2Img(model).generate(
             prompt=self.prompt,
-            step_callback=partial(self.dispatch_progress, context),
+            step_callback=partial(self.dispatch_progress, context, source_node_id),
             **self.dict(
                 exclude={"prompt"}
             ),  # Shorthand for passing all of the parameters above manually
@@ -95,9 +97,18 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, generate_output.image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(
+            image_type, image_name, generate_output.image, metadata
+        )
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=generate_output.image,
         )
 
 
@@ -117,20 +128,17 @@ class ImageToImageInvocation(TextToImageInvocation):
     )
 
     def dispatch_progress(
-        self, context: InvocationContext, intermediate_state: PipelineIntermediateState
-    ) -> None:  
-        if (context.services.queue.is_canceled(context.graph_execution_state_id)):
-            raise CanceledException
-
-        step = intermediate_state.step
-        if intermediate_state.predicted_original is not None:
-            # Some schedulers report not only the noisy latents at the current timestep,
-            # but also their estimate so far of what the de-noised latents will be.
-            sample = intermediate_state.predicted_original
-        else:
-            sample = intermediate_state.latents
-
-        diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
+        self,
+        context: InvocationContext,
+        source_node_id: str,
+        intermediate_state: PipelineIntermediateState,
+    ) -> None:
+        stable_diffusion_step_callback(
+            context=context,
+            intermediate_state=intermediate_state,
+            node=self.dict(),
+            source_node_id=source_node_id,
+        )
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = (
@@ -145,15 +153,21 @@ class ImageToImageInvocation(TextToImageInvocation):
         # Handle invalid model parameter
         model = choose_model(context.services.model_manager, self.model)
 
+        # Get the source node id (we are invoking the prepared node)
+        graph_execution_state = context.services.graph_execution_manager.get(
+            context.graph_execution_state_id
+        )
+        source_node_id = graph_execution_state.prepared_source_mapping[self.id]
+
         outputs = Img2Img(model).generate(
-                prompt=self.prompt,
-                init_image=image,
-                init_mask=mask,
-                step_callback=partial(self.dispatch_progress, context),
-                **self.dict(
-                    exclude={"prompt", "image", "mask"}
-                ),  # Shorthand for passing all of the parameters above manually
-            )
+            prompt=self.prompt,
+            init_image=image,
+            init_mask=mask,
+            step_callback=partial(self.dispatch_progress, context, source_node_id),
+            **self.dict(
+                exclude={"prompt", "image", "mask"}
+            ),  # Shorthand for passing all of the parameters above manually
+        )
 
         # Outputs is an infinite iterator that will return a new InvokeAIGeneratorOutput object
         # each time it is called. We only need the first one.
@@ -168,11 +182,19 @@ class ImageToImageInvocation(TextToImageInvocation):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, result_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
         )
 
+        context.services.images.save(image_type, image_name, result_image, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=result_image,
+        )
+
+
 class InpaintInvocation(ImageToImageInvocation):
     """Generates an image using inpaint."""
 
@@ -188,20 +210,17 @@ class InpaintInvocation(ImageToImageInvocation):
     )
 
     def dispatch_progress(
-        self, context: InvocationContext, intermediate_state: PipelineIntermediateState
-    ) -> None:  
-        if (context.services.queue.is_canceled(context.graph_execution_state_id)):
-            raise CanceledException
-
-        step = intermediate_state.step
-        if intermediate_state.predicted_original is not None:
-            # Some schedulers report not only the noisy latents at the current timestep,
-            # but also their estimate so far of what the de-noised latents will be.
-            sample = intermediate_state.predicted_original
-        else:
-            sample = intermediate_state.latents
-
-        diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
+        self,
+        context: InvocationContext,
+        source_node_id: str,
+        intermediate_state: PipelineIntermediateState,
+    ) -> None:
+        stable_diffusion_step_callback(
+            context=context,
+            intermediate_state=intermediate_state,
+            node=self.dict(),
+            source_node_id=source_node_id,
+        )
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = (
@@ -218,17 +237,23 @@ class InpaintInvocation(ImageToImageInvocation):
         )
 
         # Handle invalid model parameter
-        model = choose_model(context.services.model_manager, self.model)   
+        model = choose_model(context.services.model_manager, self.model)
+
+        # Get the source node id (we are invoking the prepared node)
+        graph_execution_state = context.services.graph_execution_manager.get(
+            context.graph_execution_state_id
+        )
+        source_node_id = graph_execution_state.prepared_source_mapping[self.id]
 
         outputs = Inpaint(model).generate(
-                prompt=self.prompt,
-                init_img=image,
-                init_mask=mask,
-                step_callback=partial(self.dispatch_progress, context),
-                **self.dict(
-                    exclude={"prompt", "image", "mask"}
-                ),  # Shorthand for passing all of the parameters above manually
-            )
+            prompt=self.prompt,
+            init_img=image,
+            init_mask=mask,
+            step_callback=partial(self.dispatch_progress, context, source_node_id),
+            **self.dict(
+                exclude={"prompt", "image", "mask"}
+            ),  # Shorthand for passing all of the parameters above manually
+        )
 
         # Outputs is an infinite iterator that will return a new InvokeAIGeneratorOutput object
         # each time it is called. We only need the first one.
@@ -243,7 +268,14 @@ class InpaintInvocation(ImageToImageInvocation):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, result_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, result_image, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=result_image,
         )

invokeai/app/invocations/image.py

@@ -1,6 +1,5 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-from datetime import datetime, timezone
 from typing import Literal, Optional
 
 import numpy
@@ -8,8 +7,12 @@ from PIL import Image, ImageFilter, ImageOps
 from pydantic import BaseModel, Field
 
 from ..models.image import ImageField, ImageType
-from ..services.invocation_services import InvocationServices
-from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext, InvocationConfig
+from .baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    InvocationContext,
+    InvocationConfig,
+)
 
 
 class PILInvocationConfig(BaseModel):
@@ -22,50 +25,73 @@ class PILInvocationConfig(BaseModel):
             },
         }
 
+
 class ImageOutput(BaseInvocationOutput):
     """Base class for invocations that output an image"""
-    #fmt: off
+
+    # fmt: off
     type: Literal["image"] = "image"
     image:      ImageField = Field(default=None, description="The output image")
-    #fmt: on
+    width:   Optional[int] = Field(default=None, description="The width of the image in pixels")
+    height:  Optional[int] = Field(default=None, description="The height of the image in pixels")
+    # fmt: on
 
     class Config:
         schema_extra = {
-            'required': [
-                'type',
-                'image',
-            ]
+            "required": ["type", "image", "width", "height", "mode"]
         }
 
+
+def build_image_output(
+    image_type: ImageType, image_name: str, image: Image.Image
+) -> ImageOutput:
+    """Builds an ImageOutput and its ImageField"""
+    image_field = ImageField(
+        image_name=image_name,
+        image_type=image_type,
+    )
+    return ImageOutput(
+        image=image_field,
+        width=image.width,
+        height=image.height,
+        mode=image.mode,
+    )
+
+
 class MaskOutput(BaseInvocationOutput):
     """Base class for invocations that output a mask"""
-    #fmt: off
+
+    # fmt: off
     type: Literal["mask"] = "mask"
     mask:      ImageField = Field(default=None, description="The output mask")
-    #fmt: on
+    # fmt: on
 
     class Config:
         schema_extra = {
-            'required': [
-                'type',
-                'mask',
+            "required": [
+                "type",
+                "mask",
             ]
         }
 
-# TODO: this isn't really necessary anymore
+
 class LoadImageInvocation(BaseInvocation):
-    """Load an image from a filename and provide it as output."""
-    #fmt: off
+    """Load an image and provide it as output."""
+
+    # fmt: off
     type: Literal["load_image"] = "load_image"
 
     # Inputs
     image_type: ImageType = Field(description="The type of the image")
     image_name:       str = Field(description="The name of the image")
-    #fmt: on
-
+    # fmt: on
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        return ImageOutput(
-            image=ImageField(image_type=self.image_type, image_name=self.image_name)
+        image = context.services.images.get(self.image_type, self.image_name)
+
+        return build_image_output(
+            image_type=self.image_type,
+            image_name=self.image_name,
+            image=image,
         )
 
 
@@ -86,16 +112,17 @@ class ShowImageInvocation(BaseInvocation):
 
         # TODO: how to handle failure?
 
-        return ImageOutput(
-            image=ImageField(
-                image_type=self.image.image_type, image_name=self.image.image_name
-            )
+        return build_image_output(
+            image_type=self.image.image_type,
+            image_name=self.image.image_name,
+            image=image,
         )
 
 
 class CropImageInvocation(BaseInvocation, PILInvocationConfig):
     """Crops an image to a specified box. The box can be outside of the image."""
-    #fmt: off
+
+    # fmt: off
     type: Literal["crop"] = "crop"
 
     # Inputs
@@ -104,7 +131,7 @@ class CropImageInvocation(BaseInvocation, PILInvocationConfig):
     y:      int = Field(default=0, description="The top y coordinate of the crop rectangle")
     width:  int = Field(default=512, gt=0, description="The width of the crop rectangle")
     height: int = Field(default=512, gt=0, description="The height of the crop rectangle")
-    #fmt: on
+    # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.services.images.get(
@@ -120,15 +147,23 @@ class CropImageInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, image_crop)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+        
+        context.services.images.save(image_type, image_name, image_crop, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=image_crop,
         )
 
 
 class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
     """Pastes an image into another image."""
-    #fmt: off
+
+    # fmt: off
     type: Literal["paste"] = "paste"
 
     # Inputs
@@ -137,7 +172,7 @@ class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
     mask: Optional[ImageField] = Field(default=None, description="The mask to use when pasting")
     x:                     int = Field(default=0, description="The left x coordinate at which to paste the image")
     y:                     int = Field(default=0, description="The top y coordinate at which to paste the image")
-    #fmt: on
+    # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         base_image = context.services.images.get(
@@ -170,21 +205,29 @@ class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, new_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+        
+        context.services.images.save(image_type, image_name, new_image, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=new_image,
         )
 
 
 class MaskFromAlphaInvocation(BaseInvocation, PILInvocationConfig):
     """Extracts the alpha channel of an image as a mask."""
-    #fmt: off
+
+    # fmt: off
     type: Literal["tomask"] = "tomask"
 
     # Inputs
     image: ImageField = Field(default=None, description="The image to create the mask from")
     invert:      bool = Field(default=False, description="Whether or not to invert the mask")
-    #fmt: on
+    # fmt: on
 
     def invoke(self, context: InvocationContext) -> MaskOutput:
         image = context.services.images.get(
@@ -199,22 +242,27 @@ class MaskFromAlphaInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, image_mask)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, image_mask, metadata)
         return MaskOutput(mask=ImageField(image_type=image_type, image_name=image_name))
 
 
 class BlurInvocation(BaseInvocation, PILInvocationConfig):
     """Blurs an image"""
 
-    #fmt: off
+    # fmt: off
     type: Literal["blur"] = "blur"
 
     # Inputs
     image: ImageField = Field(default=None, description="The image to blur")
     radius:     float = Field(default=8.0, ge=0, description="The blur radius")
     blur_type: Literal["gaussian", "box"] = Field(default="gaussian", description="The type of blur")
-    #fmt: on
-    
+    # fmt: on
+
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.services.images.get(
             self.image.image_type, self.image.image_name
@@ -231,22 +279,28 @@ class BlurInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, blur_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, blur_image, metadata)
+        return build_image_output(
+            image_type=image_type, image_name=image_name, image=blur_image
         )
 
 
 class LerpInvocation(BaseInvocation, PILInvocationConfig):
     """Linear interpolation of all pixels of an image"""
-    #fmt: off
+
+    # fmt: off
     type: Literal["lerp"] = "lerp"
 
     # Inputs
     image: ImageField = Field(default=None, description="The image to lerp")
     min: int = Field(default=0, ge=0, le=255, description="The minimum output value")
     max: int = Field(default=255, ge=0, le=255, description="The maximum output value")
-    #fmt: on
+    # fmt: on
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.services.images.get(
@@ -262,23 +316,29 @@ class LerpInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, lerp_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, lerp_image, metadata)
+        return build_image_output(
+            image_type=image_type, image_name=image_name, image=lerp_image
         )
 
 
 class InverseLerpInvocation(BaseInvocation, PILInvocationConfig):
     """Inverse linear interpolation of all pixels of an image"""
-    #fmt: off
+
+    # fmt: off
     type: Literal["ilerp"] = "ilerp"
 
     # Inputs
     image: ImageField = Field(default=None, description="The image to lerp")
     min: int = Field(default=0, ge=0, le=255, description="The minimum input value")
     max: int = Field(default=255, ge=0, le=255, description="The maximum input value")
-    #fmt: on
-    
+    # fmt: on
+
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.services.images.get(
             self.image.image_type, self.image.image_name
@@ -298,7 +358,12 @@ class InverseLerpInvocation(BaseInvocation, PILInvocationConfig):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, ilerp_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
+        )
+
+        context.services.images.save(image_type, image_name, ilerp_image, metadata)
+        return build_image_output(
+            image_type=image_type, image_name=image_name, image=ilerp_image
         )

invokeai/app/invocations/latent.py

@@ -5,9 +5,9 @@ from typing import Literal, Optional
 from pydantic import BaseModel, Field
 import torch
 
-from invokeai.app.models.exceptions import CanceledException
-from invokeai.app.invocations.util.get_model import choose_model
-from invokeai.app.util.step_callback import diffusers_step_callback_adapter
+from invokeai.app.invocations.util.choose_model import choose_model
+
+from invokeai.app.util.step_callback import stable_diffusion_step_callback
 
 from ...backend.model_management.model_manager import ModelManager
 from ...backend.util.devices import choose_torch_device, torch_dtype
@@ -19,7 +19,7 @@ from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationCont
 import numpy as np
 from ..services.image_storage import ImageType
 from .baseinvocation import BaseInvocation, InvocationContext
-from .image import ImageField, ImageOutput
+from .image import ImageField, ImageOutput, build_image_output
 from ...backend.stable_diffusion import PipelineIntermediateState
 from diffusers.schedulers import SchedulerMixin as Scheduler
 import diffusers
@@ -31,6 +31,8 @@ class LatentsField(BaseModel):
 
     latents_name: Optional[str] = Field(default=None, description="The name of the latents")
 
+    class Config:
+        schema_extra = {"required": ["latents_name"]}
 
 class LatentsOutput(BaseInvocationOutput):
     """Base class for invocations that output latents"""
@@ -170,22 +172,15 @@ class TextToLatentsInvocation(BaseInvocation):
 
     # TODO: pass this an emitter method or something? or a session for dispatching?
     def dispatch_progress(
-        self, context: InvocationContext, intermediate_state: PipelineIntermediateState
-    ) -> None:  
-        if (context.services.queue.is_canceled(context.graph_execution_state_id)):
-            raise CanceledException
+        self, context: InvocationContext, source_node_id: str, intermediate_state: PipelineIntermediateState
+    ) -> None:
+        stable_diffusion_step_callback(
+            context=context,
+            intermediate_state=intermediate_state,
+            node=self.dict(),
+            source_node_id=source_node_id,
+        )
 
-        step = intermediate_state.step
-        if intermediate_state.predicted_original is not None:
-            # Some schedulers report not only the noisy latents at the current timestep,
-            # but also their estimate so far of what the de-noised latents will be.
-            sample = intermediate_state.predicted_original
-        else:
-            sample = intermediate_state.latents
-
-        diffusers_step_callback_adapter(sample, step, steps=self.steps, id=self.id, context=context)
-
-    
     def get_model(self, model_manager: ModelManager) -> StableDiffusionGeneratorPipeline:
         model_info = choose_model(model_manager, self.model)
         model_name = model_info['model_name']
@@ -195,7 +190,7 @@ class TextToLatentsInvocation(BaseInvocation):
             model=model,
             scheduler_name=self.scheduler
         )
-        
+
         if isinstance(model, DiffusionPipeline):
             for component in [model.unet, model.vae]:
                 configure_model_padding(component,
@@ -231,8 +226,12 @@ class TextToLatentsInvocation(BaseInvocation):
     def invoke(self, context: InvocationContext) -> LatentsOutput:
         noise = context.services.latents.get(self.noise.latents_name)
 
+        # Get the source node id (we are invoking the prepared node)
+        graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
+        source_node_id = graph_execution_state.prepared_source_mapping[self.id]
+
         def step_callback(state: PipelineIntermediateState):
-            self.dispatch_progress(context, state)
+            self.dispatch_progress(context, source_node_id, state)
 
         model = self.get_model(context.services.model_manager)
         conditioning_data = self.get_conditioning_data(model)
@@ -281,8 +280,12 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
         noise = context.services.latents.get(self.noise.latents_name)
         latent = context.services.latents.get(self.latents.latents_name)
 
+        # Get the source node id (we are invoking the prepared node)
+        graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
+        source_node_id = graph_execution_state.prepared_source_mapping[self.id]
+
         def step_callback(state: PipelineIntermediateState):
-            self.dispatch_progress(context, state)
+            self.dispatch_progress(context, source_node_id, state)
 
         model = self.get_model(context.services.model_manager)
         conditioning_data = self.get_conditioning_data(model)
@@ -292,57 +295,7 @@ class LatentsToLatentsInvocation(TextToLatentsInvocation):
         initial_latents = latent if self.strength < 1.0 else torch.zeros_like(
             latent, device=model.device, dtype=latent.dtype
         )
-        
-        timesteps, _ = model.get_img2img_timesteps(
-            self.steps,
-            self.strength,
-            device=model.device,
-        )
 
-        result_latents, result_attention_map_saver = model.latents_from_embeddings(
-            latents=initial_latents,
-            timesteps=timesteps,
-            noise=noise,
-            num_inference_steps=self.steps,
-            conditioning_data=conditioning_data,
-            callback=step_callback
-        )
-
-        # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699
-        torch.cuda.empty_cache()
-
-        name = f'{context.graph_execution_state_id}__{self.id}'
-        context.services.latents.set(name, result_latents)
-        return LatentsOutput(
-            latents=LatentsField(latents_name=name)
-        )
-
-
-class LatentsToLatentsInvocation(TextToLatentsInvocation):
-    """Generates latents using latents as base image."""
-
-    type: Literal["l2l"] = "l2l"
-
-    # Inputs
-    latents: Optional[LatentsField] = Field(description="The latents to use as a base image")
-    strength: float = Field(default=0.5, description="The strength of the latents to use")
-
-    def invoke(self, context: InvocationContext) -> LatentsOutput:
-        noise = context.services.latents.get(self.noise.latents_name)
-        latent = context.services.latents.get(self.latents.latents_name)
-
-        def step_callback(state: PipelineIntermediateState):
-            self.dispatch_progress(context, state)
-
-        model = self.get_model(context.services.model_manager)
-        conditioning_data = self.get_conditioning_data(model)
-
-        # TODO: Verify the noise is the right size
-
-        initial_latents = latent if self.strength < 1.0 else torch.zeros_like(
-            latent, device=model.device, dtype=latent.dtype
-        )
-        
         timesteps, _ = model.get_img2img_timesteps(
             self.steps,
             self.strength,
@@ -405,7 +358,14 @@ class LatentsToImageInvocation(BaseInvocation):
             image_name = context.services.images.create_name(
                 context.graph_execution_state_id, self.id
             )
-            context.services.images.save(image_type, image_name, image)
-            return ImageOutput(
-                image=ImageField(image_type=image_type, image_name=image_name)
+
+            metadata = context.services.metadata.build_metadata(
+                session_id=context.graph_execution_state_id, node=self
+            )
+
+            context.services.images.save(image_type, image_name, image, metadata)
+            return build_image_output(
+                image_type=image_type,
+                image_name=image_name,
+                image=image
             )

invokeai/app/invocations/reconstruct.py

@@ -1,12 +1,11 @@
-from datetime import datetime, timezone
 from typing import Literal, Union
 
 from pydantic import Field
 
 from invokeai.app.models.image import ImageField, ImageType
-from ..services.invocation_services import InvocationServices
+
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output
 
 class RestoreFaceInvocation(BaseInvocation):
     """Restores faces in an image."""
@@ -44,7 +43,14 @@ class RestoreFaceInvocation(BaseInvocation):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, results[0][0])
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
         )
+
+        context.services.images.save(image_type, image_name, results[0][0], metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=results[0][0]
+        )

invokeai/app/invocations/upscale.py

@@ -1,14 +1,12 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-from datetime import datetime, timezone
 from typing import Literal, Union
 
 from pydantic import Field
 
 from invokeai.app.models.image import ImageField, ImageType
-from ..services.invocation_services import InvocationServices
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output
 
 
 class UpscaleInvocation(BaseInvocation):
@@ -49,7 +47,14 @@ class UpscaleInvocation(BaseInvocation):
         image_name = context.services.images.create_name(
             context.graph_execution_state_id, self.id
         )
-        context.services.images.save(image_type, image_name, results[0][0])
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        metadata = context.services.metadata.build_metadata(
+            session_id=context.graph_execution_state_id, node=self
         )
+
+        context.services.images.save(image_type, image_name, results[0][0], metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=results[0][0]
+        )

invokeai/app/invocations/util/choose_model.py

@@ -1,11 +1,14 @@
-from invokeai.app.invocations.baseinvocation import InvocationContext
 from invokeai.backend.model_management.model_manager import ModelManager
 
 
 def choose_model(model_manager: ModelManager, model_name: str):
     """Returns the default model if the `model_name` not a valid model, else returns the selected model."""
     if model_manager.valid_model(model_name):
-        return model_manager.get_model(model_name)
+        model = model_manager.get_model(model_name)
     else:
-        print(f"* Warning: '{model_name}' is not a valid model name. Using default model instead.")
-        return model_manager.get_model()
+        model = model_manager.get_model()
+        print(
+            f"* Warning: '{model_name}' is not a valid model name. Using default model \'{model['model_name']}\' instead."
+        )
+
+    return model

invokeai/app/models/image.py

@@ -9,6 +9,14 @@ class ImageType(str, Enum):
     UPLOAD = "uploads"
 
 
+def is_image_type(obj):
+    try:
+        ImageType(obj)
+    except ValueError:
+        return False
+    return True
+
+
 class ImageField(BaseModel):
     """An image field used for passing image objects between invocations"""
 
@@ -18,9 +26,4 @@ class ImageField(BaseModel):
     image_name: Optional[str] = Field(default=None, description="The name of the image")
 
     class Config:
-        schema_extra = {
-            "required": [
-                "image_type",
-                "image_name",
-            ]
-        }
+        schema_extra = {"required": ["image_type", "image_name"]}

invokeai/app/models/metadata.py

@@ -1,11 +0,0 @@
-from typing import Optional
-from pydantic import BaseModel, Field
-
-class ImageMetadata(BaseModel):
-    """An image's metadata"""
-
-    timestamp: float = Field(description="The creation timestamp of the image")
-    width: int = Field(description="The width of the image in pixels")
-    height: int = Field(description="The height of the image in pixels")
-    # TODO: figure out metadata
-    sd_metadata: Optional[dict] = Field(default={}, description="The image's SD-specific metadata")

invokeai/app/services/events.py

@@ -1,10 +1,9 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-from typing import Any, Dict, TypedDict
+from typing import Any
+from invokeai.app.api.models.images import ProgressImage
+from invokeai.app.util.misc import get_timestamp
 
-ProgressImage = TypedDict(
-    "ProgressImage", {"dataURL": str, "width": int, "height": int}
-)
 
 class EventServiceBase:
     session_event: str = "session_event"
@@ -14,7 +13,8 @@ class EventServiceBase:
     def dispatch(self, event_name: str, payload: Any) -> None:
         pass
 
-    def __emit_session_event(self, event_name: str, payload: Dict) -> None:
+    def __emit_session_event(self, event_name: str, payload: dict) -> None:
+        payload["timestamp"] = get_timestamp()
         self.dispatch(
             event_name=EventServiceBase.session_event,
             payload=dict(event=event_name, data=payload),
@@ -25,7 +25,8 @@ class EventServiceBase:
     def emit_generator_progress(
         self,
         graph_execution_state_id: str,
-        invocation_id: str,
+        node: dict,
+        source_node_id: str,
         progress_image: ProgressImage | None,
         step: int,
         total_steps: int,
@@ -35,48 +36,60 @@ class EventServiceBase:
             event_name="generator_progress",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
-                progress_image=progress_image,
+                node=node,
+                source_node_id=source_node_id,
+                progress_image=progress_image.dict() if progress_image is not None else None,
                 step=step,
                 total_steps=total_steps,
             ),
         )
 
     def emit_invocation_complete(
-        self, graph_execution_state_id: str, invocation_id: str, result: Dict
+        self,
+        graph_execution_state_id: str,
+        result: dict,
+        node: dict,
+        source_node_id: str,
     ) -> None:
         """Emitted when an invocation has completed"""
         self.__emit_session_event(
             event_name="invocation_complete",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
+                node=node,
+                source_node_id=source_node_id,
                 result=result,
             ),
         )
 
     def emit_invocation_error(
-        self, graph_execution_state_id: str, invocation_id: str, error: str
+        self,
+        graph_execution_state_id: str,
+        node: dict,
+        source_node_id: str,
+        error: str,
     ) -> None:
         """Emitted when an invocation has completed"""
         self.__emit_session_event(
             event_name="invocation_error",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
+                node=node,
+                source_node_id=source_node_id,
                 error=error,
             ),
         )
 
     def emit_invocation_started(
-        self, graph_execution_state_id: str, invocation_id: str
+        self, graph_execution_state_id: str, node: dict, source_node_id: str
     ) -> None:
         """Emitted when an invocation has started"""
         self.__emit_session_event(
             event_name="invocation_started",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
+                node=node,
+                source_node_id=source_node_id,
             ),
         )
 
@@ -84,5 +97,7 @@ class EventServiceBase:
         """Emitted when a session has completed all invocations"""
         self.__emit_session_event(
             event_name="graph_execution_state_complete",
-            payload=dict(graph_execution_state_id=graph_execution_state_id),
+            payload=dict(
+                graph_execution_state_id=graph_execution_state_id,
+            ),
         )

invokeai/app/services/graph.py

@@ -2,7 +2,6 @@
 
 import copy
 import itertools
-import traceback
 import uuid
 from types import NoneType
 from typing import (
@@ -26,7 +25,6 @@ from ..invocations.baseinvocation import (
     BaseInvocationOutput,
     InvocationContext,
 )
-from .invocation_services import InvocationServices
 
 
 class EdgeConnection(BaseModel):
@@ -215,7 +213,7 @@ InvocationOutputsUnion = Union[BaseInvocationOutput.get_all_subclasses_tuple()]
 
 
 class Graph(BaseModel):
-    id: str = Field(description="The id of this graph", default_factory=uuid.uuid4)
+    id: str = Field(description="The id of this graph", default_factory=lambda: uuid.uuid4().__str__())
     # TODO: use a list (and never use dict in a BaseModel) because pydantic/fastapi hates me
     nodes: dict[str, Annotated[InvocationsUnion, Field(discriminator="type")]] = Field(
         description="The nodes in this graph", default_factory=dict
@@ -750,9 +748,7 @@ class Graph(BaseModel):
 class GraphExecutionState(BaseModel):
     """Tracks the state of a graph execution"""
 
-    id: str = Field(
-        description="The id of the execution state", default_factory=uuid.uuid4
-    )
+    id: str = Field(description="The id of the execution state", default_factory=lambda: uuid.uuid4().__str__())
 
     # TODO: Store a reference to the graph instead of the actual graph?
     graph: Graph = Field(description="The graph being executed")
@@ -1171,7 +1167,7 @@ class LibraryGraph(BaseModel):
         if len(v) != len(set(i.alias for i in v)):
             raise ValueError("Duplicate exposed alias")
         return v
-    
+
     @root_validator
     def validate_exposed_nodes(cls, values):
         graph = values['graph']

invokeai/app/services/image_storage.py

@@ -1,24 +1,24 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-import datetime
 import os
 from glob import glob
 from abc import ABC, abstractmethod
-from enum import Enum
 from pathlib import Path
 from queue import Queue
-from typing import Callable, Dict, List
+from typing import Dict, List, Tuple
 
 from PIL.Image import Image
 import PIL.Image as PILImage
-from pydantic import BaseModel
-from invokeai.app.api.models.images import ImageResponse
-from invokeai.app.models.image import ImageField, ImageType
-from invokeai.app.models.metadata import ImageMetadata
+from invokeai.app.api.models.images import ImageResponse, ImageResponseMetadata
+from invokeai.app.models.image import ImageType
+from invokeai.app.services.metadata import (
+    InvokeAIMetadata,
+    MetadataServiceBase,
+    build_invokeai_metadata_pnginfo,
+)
 from invokeai.app.services.item_storage import PaginatedResults
-from invokeai.app.util.save_thumbnail import save_thumbnail
-
-from invokeai.backend.image_util import PngWriter
+from invokeai.app.util.misc import get_timestamp
+from invokeai.app.util.thumbnails import get_thumbnail_name, make_thumbnail
 
 
 class ImageStorageBase(ABC):
@@ -26,12 +26,14 @@ class ImageStorageBase(ABC):
 
     @abstractmethod
     def get(self, image_type: ImageType, image_name: str) -> Image:
+        """Retrieves an image as PIL Image."""
         pass
 
     @abstractmethod
     def list(
         self, image_type: ImageType, page: int = 0, per_page: int = 10
     ) -> PaginatedResults[ImageResponse]:
+        """Gets a paginated list of images."""
         pass
 
     # TODO: make this a bit more flexible for e.g. cloud storage
@@ -39,35 +41,51 @@ class ImageStorageBase(ABC):
     def get_path(
         self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
     ) -> str:
+        """Gets the path to an image or its thumbnail."""
+        pass
+
+    # TODO: make this a bit more flexible for e.g. cloud storage
+    @abstractmethod
+    def validate_path(self, path: str) -> bool:
+        """Validates an image path."""
         pass
 
     @abstractmethod
-    def save(self, image_type: ImageType, image_name: str, image: Image) -> None:
+    def save(
+        self,
+        image_type: ImageType,
+        image_name: str,
+        image: Image,
+        metadata: InvokeAIMetadata | None = None,
+    ) -> Tuple[str, str, int]:
+        """Saves an image and a 256x256 WEBP thumbnail. Returns a tuple of the image path, thumbnail path, and created timestamp."""
         pass
 
     @abstractmethod
     def delete(self, image_type: ImageType, image_name: str) -> None:
+        """Deletes an image and its thumbnail (if one exists)."""
         pass
 
     def create_name(self, context_id: str, node_id: str) -> str:
-        return f"{context_id}_{node_id}_{str(int(datetime.datetime.now(datetime.timezone.utc).timestamp()))}.png"
+        """Creates a unique contextual image filename."""
+        return f"{context_id}_{node_id}_{str(get_timestamp())}.png"
 
 
 class DiskImageStorage(ImageStorageBase):
     """Stores images on disk"""
 
     __output_folder: str
-    __pngWriter: PngWriter
     __cache_ids: Queue  # TODO: this is an incredibly naive cache
     __cache: Dict[str, Image]
     __max_cache_size: int
+    __metadata_service: MetadataServiceBase
 
-    def __init__(self, output_folder: str):
+    def __init__(self, output_folder: str, metadata_service: MetadataServiceBase):
         self.__output_folder = output_folder
-        self.__pngWriter = PngWriter(output_folder)
         self.__cache = dict()
         self.__cache_ids = Queue()
         self.__max_cache_size = 10  # TODO: get this from config
+        self.__metadata_service = metadata_service
 
         Path(output_folder).mkdir(parents=True, exist_ok=True)
 
@@ -100,6 +118,9 @@ class DiskImageStorage(ImageStorageBase):
         for path in page_of_image_paths:
             filename = os.path.basename(path)
             img = PILImage.open(path)
+
+            invokeai_metadata = self.__metadata_service.get_metadata(img)
+
             page_of_images.append(
                 ImageResponse(
                     image_type=image_type.value,
@@ -107,11 +128,12 @@ class DiskImageStorage(ImageStorageBase):
                     # TODO: DiskImageStorage should not be building URLs...?
                     image_url=f"api/v1/images/{image_type.value}/{filename}",
                     thumbnail_url=f"api/v1/images/{image_type.value}/thumbnails/{os.path.splitext(filename)[0]}.webp",
-                    # TODO: Creation of this object should happen elsewhere, just making it fit here so it works
-                    metadata=ImageMetadata(
-                        timestamp=os.path.getctime(path),
+                    # TODO: Creation of this object should happen elsewhere (?), just making it fit here so it works
+                    metadata=ImageResponseMetadata(
+                        created=int(os.path.getctime(path)),
                         width=img.width,
                         height=img.height,
+                        invokeai=invokeai_metadata,
                     ),
                 )
             )
@@ -142,26 +164,50 @@ class DiskImageStorage(ImageStorageBase):
     def get_path(
         self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
     ) -> str:
+        # strip out any relative path shenanigans
+        basename = os.path.basename(image_name)
+
         if is_thumbnail:
             path = os.path.join(
-                self.__output_folder, image_type, "thumbnails", image_name
+                self.__output_folder, image_type, "thumbnails", basename
             )
         else:
-            path = os.path.join(self.__output_folder, image_type, image_name)
+            path = os.path.join(self.__output_folder, image_type, basename)
+
         return path
 
-    def save(self, image_type: ImageType, image_name: str, image: Image) -> None:
-        image_subpath = os.path.join(image_type, image_name)
-        self.__pngWriter.save_image_and_prompt_to_png(
-            image, "", image_subpath, None
-        )  # TODO: just pass full path to png writer
-        save_thumbnail(
-            image=image,
-            filename=image_name,
-            path=os.path.join(self.__output_folder, image_type, "thumbnails"),
-        )
+    def validate_path(self, path: str) -> bool:
+        try:
+            os.stat(path)
+            return True
+        except Exception:
+            return False
+
+    def save(
+        self,
+        image_type: ImageType,
+        image_name: str,
+        image: Image,
+        metadata: InvokeAIMetadata | None = None,
+    ) -> Tuple[str, str, int]:
         image_path = self.get_path(image_type, image_name)
+
+        # TODO: Reading the image and then saving it strips the metadata...
+        if metadata:
+            pnginfo = build_invokeai_metadata_pnginfo(metadata=metadata)
+            image.save(image_path, "PNG", pnginfo=pnginfo)
+        else:
+            image.save(image_path) # this saved image has an empty info
+
+        thumbnail_name = get_thumbnail_name(image_name)
+        thumbnail_path = self.get_path(image_type, thumbnail_name, is_thumbnail=True)
+        thumbnail_image = make_thumbnail(image)
+        thumbnail_image.save(thumbnail_path)
+
         self.__set_cache(image_path, image)
+        self.__set_cache(thumbnail_path, thumbnail_image)
+
+        return (image_path, thumbnail_path, int(os.path.getctime(image_path)))
 
     def delete(self, image_type: ImageType, image_name: str) -> None:
         image_path = self.get_path(image_type, image_name)

invokeai/app/services/invocation_queue.py

@@ -1,30 +1,17 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
+import time
 from abc import ABC, abstractmethod
 from queue import Queue
-import time
+
+from pydantic import BaseModel, Field
 
 
-# TODO: make this serializable
-class InvocationQueueItem:
-    # session_id: str
-    graph_execution_state_id: str
-    invocation_id: str
-    invoke_all: bool
-    timestamp: float
-
-    def __init__(
-        self,
-        # session_id: str,
-        graph_execution_state_id: str,
-        invocation_id: str,
-        invoke_all: bool = False,
-    ):
-        # self.session_id = session_id
-        self.graph_execution_state_id = graph_execution_state_id
-        self.invocation_id = invocation_id
-        self.invoke_all = invoke_all
-        self.timestamp = time.time()
+class InvocationQueueItem(BaseModel):
+    graph_execution_state_id: str = Field(description="The ID of the graph execution state")
+    invocation_id: str = Field(description="The ID of the node being invoked")
+    invoke_all: bool = Field(default=False)
+    timestamp: float = Field(default_factory=time.time)
 
 
 class InvocationQueueABC(ABC):

invokeai/app/services/invocation_services.py

@@ -1,4 +1,5 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
+from invokeai.app.services.metadata import MetadataServiceBase
 from invokeai.backend import ModelManager
 
 from .events import EventServiceBase
@@ -14,6 +15,7 @@ class InvocationServices:
     events: EventServiceBase
     latents: LatentsStorageBase
     images: ImageStorageBase
+    metadata: MetadataServiceBase
     queue: InvocationQueueABC
     model_manager: ModelManager
     restoration: RestorationServices
@@ -29,6 +31,7 @@ class InvocationServices:
             events: EventServiceBase,
             latents: LatentsStorageBase,
             images: ImageStorageBase,
+            metadata: MetadataServiceBase,
             queue: InvocationQueueABC,
             graph_library: ItemStorageABC["LibraryGraph"],
             graph_execution_manager: ItemStorageABC["GraphExecutionState"],
@@ -39,6 +42,7 @@ class InvocationServices:
         self.events = events
         self.latents = latents
         self.images = images
+        self.metadata = metadata
         self.queue = queue
         self.graph_library = graph_library
         self.graph_execution_manager = graph_execution_manager

invokeai/app/services/metadata.py

@@ -0,0 +1,96 @@
+import json
+from abc import ABC, abstractmethod
+from typing import Any, Dict, Optional, TypedDict
+from PIL import Image, PngImagePlugin
+from pydantic import BaseModel
+
+from invokeai.app.models.image import ImageType, is_image_type
+
+
+class MetadataImageField(TypedDict):
+    """Pydantic-less ImageField, used for metadata parsing."""
+
+    image_type: ImageType
+    image_name: str
+
+
+class MetadataLatentsField(TypedDict):
+    """Pydantic-less LatentsField, used for metadata parsing."""
+
+    latents_name: str
+
+
+# TODO: This is a placeholder for `InvocationsUnion` pending resolution of circular imports
+NodeMetadata = Dict[
+    str, str | int | float | bool | MetadataImageField | MetadataLatentsField
+]
+
+
+class InvokeAIMetadata(TypedDict, total=False):
+    """InvokeAI-specific metadata format."""
+
+    session_id: Optional[str]
+    node: Optional[NodeMetadata]
+
+
+def build_invokeai_metadata_pnginfo(
+    metadata: InvokeAIMetadata | None,
+) -> PngImagePlugin.PngInfo:
+    """Builds a PngInfo object with key `"invokeai"` and value `metadata`"""
+    pnginfo = PngImagePlugin.PngInfo()
+
+    if metadata is not None:
+        pnginfo.add_text("invokeai", json.dumps(metadata))
+
+    return pnginfo
+
+
+class MetadataServiceBase(ABC):
+    @abstractmethod
+    def get_metadata(self, image: Image.Image) -> InvokeAIMetadata | None:
+        """Gets the InvokeAI metadata from a PIL Image, skipping invalid values"""
+        pass
+
+    @abstractmethod
+    def build_metadata(
+        self, session_id: str, node: BaseModel
+    ) -> InvokeAIMetadata | None:
+        """Builds an InvokeAIMetadata object"""
+        pass
+
+
+class PngMetadataService(MetadataServiceBase):
+    """Handles loading and building metadata for images."""
+
+    # TODO: Use `InvocationsUnion` to **validate** metadata as representing a fully-functioning node
+    def _load_metadata(self, image: Image.Image) -> dict | None:
+        """Loads a specific info entry from a PIL Image."""
+
+        try:
+            info = image.info.get("invokeai")
+
+            if type(info) is not str:
+                return None
+
+            loaded_metadata = json.loads(info)
+
+            if type(loaded_metadata) is not dict:
+                return None
+
+            if len(loaded_metadata.items()) == 0:
+                return None
+
+            return loaded_metadata
+        except:
+            return None
+
+    def get_metadata(self, image: Image.Image) -> dict | None:
+        """Retrieves an image's metadata as a dict"""
+        loaded_metadata = self._load_metadata(image)
+
+        return loaded_metadata
+
+    def build_metadata(self, session_id: str, node: BaseModel) -> InvokeAIMetadata:
+        metadata = InvokeAIMetadata(session_id=session_id, node=node.dict())
+
+        return metadata

invokeai/app/services/processor.py

@@ -43,10 +43,14 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                     queue_item.invocation_id
                 )
 
+                # get the source node id to provide to clients (the prepared node id is not as useful)
+                source_node_id = graph_execution_state.prepared_source_mapping[invocation.id]
+
                 # Send starting event
                 self.__invoker.services.events.emit_invocation_started(
                     graph_execution_state_id=graph_execution_state.id,
-                    invocation_id=invocation.id,
+                    node=invocation.dict(),
+                    source_node_id=source_node_id
                 )
 
                 # Invoke
@@ -75,7 +79,8 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                     # Send complete event
                     self.__invoker.services.events.emit_invocation_complete(
                         graph_execution_state_id=graph_execution_state.id,
-                        invocation_id=invocation.id,
+                        node=invocation.dict(),
+                        source_node_id=source_node_id,
                         result=outputs.dict(),
                     )
 
@@ -99,7 +104,8 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                     # Send error event
                     self.__invoker.services.events.emit_invocation_error(
                         graph_execution_state_id=graph_execution_state.id,
-                        invocation_id=invocation.id,
+                        node=invocation.dict(),
+                        source_node_id=source_node_id,
                         error=error,
                     )
 

invokeai/app/services/sqlite.py

@@ -35,7 +35,8 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
         self._create_table()
 
     def _create_table(self):
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""CREATE TABLE IF NOT EXISTS {self._table_name} (
                 item TEXT,
@@ -44,27 +45,34 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
             self._cursor.execute(
                 f"""CREATE UNIQUE INDEX IF NOT EXISTS {self._table_name}_id ON {self._table_name}(id);"""
             )
-            self._conn.commit()
+        finally:
+            self._lock.release()
 
     def _parse_item(self, item: str) -> T:
         item_type = get_args(self.__orig_class__)[0]
         return parse_raw_as(item_type, item)
 
     def set(self, item: T):
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""INSERT OR REPLACE INTO {self._table_name} (item) VALUES (?);""",
                 (item.json(),),
             )
             self._conn.commit()
+        finally:
+            self._lock.release()
         self._on_changed(item)
 
     def get(self, id: str) -> Union[T, None]:
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""SELECT item FROM {self._table_name} WHERE id = ?;""", (str(id),)
             )
             result = self._cursor.fetchone()
+        finally:
+            self._lock.release()
 
         if not result:
             return None
@@ -72,15 +80,19 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
         return self._parse_item(result[0])
 
     def delete(self, id: str):
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""DELETE FROM {self._table_name} WHERE id = ?;""", (str(id),)
             )
             self._conn.commit()
+        finally:
+            self._lock.release()
         self._on_deleted(id)
 
     def list(self, page: int = 0, per_page: int = 10) -> PaginatedResults[T]:
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""SELECT item FROM {self._table_name} LIMIT ? OFFSET ?;""",
                 (per_page, page * per_page),
@@ -91,6 +103,8 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
 
             self._cursor.execute(f"""SELECT count(*) FROM {self._table_name};""")
             count = self._cursor.fetchone()[0]
+        finally:
+            self._lock.release()
 
         pageCount = int(count / per_page) + 1
 
@@ -101,7 +115,8 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
     def search(
         self, query: str, page: int = 0, per_page: int = 10
     ) -> PaginatedResults[T]:
-        with self._lock:
+        try:
+            self._lock.acquire()
             self._cursor.execute(
                 f"""SELECT item FROM {self._table_name} WHERE item LIKE ? LIMIT ? OFFSET ?;""",
                 (f"%{query}%", per_page, page * per_page),
@@ -115,6 +130,8 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
                 (f"%{query}%",),
             )
             count = self._cursor.fetchone()[0]
+        finally:
+            self._lock.release()
 
         pageCount = int(count / per_page) + 1
 

invokeai/app/util/misc.py

@@ -0,0 +1,5 @@
+import datetime
+
+
+def get_timestamp():
+    return int(datetime.datetime.now(datetime.timezone.utc).timestamp())

invokeai/app/util/save_thumbnail.py

@@ -1,25 +0,0 @@
-import os
-from PIL import Image
-
-
-def save_thumbnail(
-    image: Image.Image,
-    filename: str,
-    path: str,
-    size: int = 256,
-) -> str:
-    """
-    Saves a thumbnail of an image, returning its path.
-    """
-    base_filename = os.path.splitext(filename)[0]
-    thumbnail_path = os.path.join(path, base_filename + ".webp")
-
-    if os.path.exists(thumbnail_path):
-        return thumbnail_path
-
-    image_copy = image.copy()
-    image_copy.thumbnail(size=(size, size))
-
-    image_copy.save(thumbnail_path, "WEBP")
-
-    return thumbnail_path

invokeai/app/util/step_callback.py

@@ -1,16 +1,41 @@
-import torch
+from invokeai.app.api.models.images import ProgressImage
+from invokeai.app.models.exceptions import CanceledException
 from ..invocations.baseinvocation import InvocationContext
 from ...backend.util.util import image_to_dataURL
 from ...backend.generator.base import Generator
 from ...backend.stable_diffusion import PipelineIntermediateState
 
-def fast_latents_step_callback(
-    sample: torch.Tensor,
-    step: int,
-    steps: int,
-    id: str,
+
+def stable_diffusion_step_callback(
     context: InvocationContext,
+    intermediate_state: PipelineIntermediateState,
+    node: dict,
+    source_node_id: str,
 ):
+    if context.services.queue.is_canceled(context.graph_execution_state_id):
+        raise CanceledException
+
+    # Some schedulers report not only the noisy latents at the current timestep,
+    # but also their estimate so far of what the de-noised latents will be. Use
+    # that estimate if it is available.
+    if intermediate_state.predicted_original is not None:
+        sample = intermediate_state.predicted_original
+    else:
+        sample = intermediate_state.latents
+
+    # TODO: This does not seem to be needed any more?
+    # # txt2img provides a Tensor in the step_callback
+    # # img2img provides a PipelineIntermediateState
+    # if isinstance(sample, PipelineIntermediateState):
+    #     # this was an img2img
+    #     print('img2img')
+    #     latents = sample.latents
+    #     step = sample.step
+    # else:
+    #     print('txt2img')
+    #     latents = sample
+    #     step = intermediate_state.step
+
     # TODO: only output a preview image when requested
     image = Generator.sample_to_lowres_estimated_image(sample)
 
@@ -21,23 +46,10 @@ def fast_latents_step_callback(
     dataURL = image_to_dataURL(image, image_format="JPEG")
 
     context.services.events.emit_generator_progress(
-        context.graph_execution_state_id,
-        id,
-        {"width": width, "height": height, "dataURL": dataURL},
-        step,
-        steps,
+        graph_execution_state_id=context.graph_execution_state_id,
+        node=node,
+        source_node_id=source_node_id,
+        progress_image=ProgressImage(width=width, height=height, dataURL=dataURL),
+        step=intermediate_state.step,
+        total_steps=node["steps"],
     )
-
-
-def diffusers_step_callback_adapter(*cb_args, **kwargs):
-    """
-    txt2img gives us a Tensor in the step_callbak, while img2img gives us a PipelineIntermediateState.
-    This adapter grabs the needed data and passes it along to the callback function.
-    """
-    if isinstance(cb_args[0], PipelineIntermediateState):
-        progress_state: PipelineIntermediateState = cb_args[0]
-        return fast_latents_step_callback(
-            progress_state.latents, progress_state.step, **kwargs
-        )
-    else:
-        return fast_latents_step_callback(*cb_args, **kwargs)

invokeai/app/util/thumbnails.py

@@ -0,0 +1,15 @@
+import os
+from PIL import Image
+
+
+def get_thumbnail_name(image_name: str) -> str:
+    """Formats given an image name, returns the appropriate thumbnail image name"""
+    thumbnail_name = os.path.splitext(image_name)[0] + ".webp"
+    return thumbnail_name
+
+
+def make_thumbnail(image: Image.Image, size: int = 256) -> Image.Image:
+    """Makes a thumbnail from a PIL Image"""
+    thumbnail = image.copy()
+    thumbnail.thumbnail(size=(size, size))
+    return thumbnail

invokeai/backend/stable_diffusion/concepts_lib.py

@@ -57,7 +57,7 @@ class HuggingFaceConceptsLibrary(object):
                 self.concept_list.extend(list(local_concepts_to_add))
                 return self.concept_list
             return self.concept_list
-        else:
+        elif Globals.internet_available is True:
             try:
                 models = self.hf_api.list_models(
                     filter=ModelFilter(model_name="sd-concepts-library/")
@@ -73,6 +73,8 @@ class HuggingFaceConceptsLibrary(object):
                     " ** You may load .bin and .pt file(s) manually using the --embedding_directory argument."
                 )
             return self.concept_list
+        else: 
+            return self.concept_list
 
     def get_concept_model_path(self, concept_name: str) -> str:
         """

invokeai/frontend/web/.eslintignore

@@ -6,3 +6,5 @@ stats.html
 index.html
 .yarn/
 *.scss
+src/services/api/
+src/services/fixtures/*

invokeai/frontend/web/.prettierignore

@@ -3,4 +3,8 @@ dist/
 node_modules/
 patches/
 stats.html
+index.html
 .yarn/
+*.scss
+src/services/api/
+src/services/fixtures/*

invokeai/frontend/web/dist/assets/ThemeLocaleProvider-7791bd91.js

@@ -1,4 +1,4 @@
-import{j as y,cN as Ie,r as _,cO as bt,q as Lr,cP as o,cQ as b,cR as v,cS as S,cT as Vr,cU as ut,cV as vt,cM as ft,cW as mt,n as gt,cX as ht,E as pt}from"./index-f7f41e1f.js";import{d as yt,i as St,T as xt,j as $t,h as kt}from"./storeHooks-eaf47ae3.js";var Or=`
+import{j as y,cO as Ie,r as _,cP as bt,q as Lr,cQ as o,cR as b,cS as v,cT as S,cU as Vr,cV as ut,cW as vt,cN as ft,cX as mt,n as gt,cY as ht,E as pt}from"./index-e53e8108.js";import{d as yt,i as St,T as xt,j as $t,h as kt}from"./storeHooks-5cde7d31.js";var Or=`
   :root {
     --chakra-vh: 100vh;
   }

invokeai/frontend/web/dist/index.html

@@ -12,7 +12,7 @@
         margin: 0;
       }
     </style>
-    <script type="module" crossorigin src="./assets/index-f7f41e1f.js"></script>
+    <script type="module" crossorigin src="./assets/index-e53e8108.js"></script>
     <link rel="stylesheet" href="./assets/index-5483945c.css">
   </head>
 

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

@@ -8,7 +8,6 @@
         "darkTheme": "داكن",
         "lightTheme": "فاتح",
         "greenTheme": "أخضر",
-        "text2img": "نص إلى صورة",
         "img2img": "صورة إلى صورة",
         "unifiedCanvas": "لوحة موحدة",
         "nodes": "عقد",

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

@@ -7,7 +7,6 @@
         "darkTheme": "Dunkel",
         "lightTheme": "Hell",
         "greenTheme": "Grün",
-        "text2img": "Text zu Bild",
         "img2img": "Bild zu Bild",
         "nodes": "Knoten",
         "langGerman": "Deutsch",

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

@@ -505,7 +505,9 @@
         "info": "Info",
         "deleteImage": "Delete Image",
         "initialImage": "Initial Image",
-        "showOptionsPanel": "Show Options Panel"
+        "showOptionsPanel": "Show Options Panel",
+        "hidePreview": "Hide Preview",
+        "showPreview": "Show Preview"
     },
     "settings": {
         "models": "Models",

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

@@ -8,7 +8,6 @@
         "darkTheme": "Oscuro",
         "lightTheme": "Claro",
         "greenTheme": "Verde",
-        "text2img": "Texto a Imagen",
         "img2img": "Imagen a Imagen",
         "unifiedCanvas": "Lienzo Unificado",
         "nodes": "Nodos",
@@ -70,7 +69,11 @@
         "langHebrew": "Hebreo",
         "pinOptionsPanel": "Pin del panel de opciones",
         "loading": "Cargando",
-        "loadingInvokeAI": "Cargando invocar a la IA"
+        "loadingInvokeAI": "Cargando invocar a la IA",
+        "postprocessing": "Tratamiento posterior",
+        "txt2img": "De texto a imagen",
+        "accept": "Aceptar",
+        "cancel": "Cancelar"
     },
     "gallery": {
         "generations": "Generaciones",
@@ -404,7 +407,8 @@
         "none": "ninguno",
         "pickModelType": "Elige el tipo de modelo",
         "v2_768": "v2 (768px)",
-        "addDifference": "Añadir una diferencia"
+        "addDifference": "Añadir una diferencia",
+        "scanForModels": "Buscar modelos"
     },
     "parameters": {
         "images": "Imágenes",
@@ -574,7 +578,7 @@
         "autoSaveToGallery": "Guardar automáticamente en galería",
         "saveBoxRegionOnly": "Guardar solo región dentro de la caja",
         "limitStrokesToBox": "Limitar trazos a la caja",
-        "showCanvasDebugInfo": "Mostrar información de depuración de lienzo",
+        "showCanvasDebugInfo": "Mostrar la información adicional del lienzo",
         "clearCanvasHistory": "Limpiar historial de lienzo",
         "clearHistory": "Limpiar historial",
         "clearCanvasHistoryMessage": "Limpiar el historial de lienzo también restablece completamente el lienzo unificado. Esto incluye todo el historial de deshacer/rehacer, las imágenes en el área de preparación y la capa base del lienzo.",

invokeai/frontend/web/dist/locales/fr.json

@@ -8,7 +8,6 @@
         "darkTheme": "Sombre",
         "lightTheme": "Clair",
         "greenTheme": "Vert",
-        "text2img": "Texte en image",
         "img2img": "Image en image",
         "unifiedCanvas": "Canvas unifié",
         "nodes": "Nœuds",
@@ -47,7 +46,19 @@
         "statusLoadingModel": "Chargement du modèle",
         "statusModelChanged": "Modèle changé",
         "discordLabel": "Discord",
-        "githubLabel": "Github"
+        "githubLabel": "Github",
+        "accept": "Accepter",
+        "statusMergingModels": "Mélange des modèles",
+        "loadingInvokeAI": "Chargement de Invoke AI",
+        "cancel": "Annuler",
+        "langEnglish": "Anglais",
+        "statusConvertingModel": "Conversion du modèle",
+        "statusModelConverted": "Modèle converti",
+        "loading": "Chargement",
+        "pinOptionsPanel": "Épingler la page d'options",
+        "statusMergedModels": "Modèles mélangés",
+        "txt2img": "Texte vers image",
+        "postprocessing": "Post-Traitement"
     },
     "gallery": {
         "generations": "Générations",
@@ -518,5 +529,15 @@
         "betaDarkenOutside": "Assombrir à l'extérieur",
         "betaLimitToBox": "Limiter à la boîte",
         "betaPreserveMasked": "Conserver masqué"
+    },
+    "accessibility": {
+        "uploadImage": "Charger une image",
+        "reset": "Réinitialiser",
+        "nextImage": "Image suivante",
+        "previousImage": "Image précédente",
+        "useThisParameter": "Utiliser ce paramètre",
+        "zoomIn": "Zoom avant",
+        "zoomOut": "Zoom arrière",
+        "showOptionsPanel": "Montrer la page d'options"
     }
 }

invokeai/frontend/web/dist/locales/he.json

@@ -125,7 +125,6 @@
         "langSimplifiedChinese": "סינית",
         "langUkranian": "אוקראינית",
         "langSpanish": "ספרדית",
-        "text2img": "טקסט לתמונה",
         "img2img": "תמונה לתמונה",
         "unifiedCanvas": "קנבס מאוחד",
         "nodes": "צמתים",

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

@@ -8,7 +8,6 @@
         "darkTheme": "Scuro",
         "lightTheme": "Chiaro",
         "greenTheme": "Verde",
-        "text2img": "Testo a Immagine",
         "img2img": "Immagine a Immagine",
         "unifiedCanvas": "Tela unificata",
         "nodes": "Nodi",
@@ -70,7 +69,11 @@
         "loading": "Caricamento in corso",
         "oceanTheme": "Oceano",
         "langHebrew": "Ebraico",
-        "loadingInvokeAI": "Caricamento Invoke AI"
+        "loadingInvokeAI": "Caricamento Invoke AI",
+        "postprocessing": "Post Elaborazione",
+        "txt2img": "Testo a Immagine",
+        "accept": "Accetta",
+        "cancel": "Annulla"
     },
     "gallery": {
         "generations": "Generazioni",
@@ -404,7 +407,8 @@
         "v2_768": "v2 (768px)",
         "none": "niente",
         "addDifference": "Aggiungi differenza",
-        "pickModelType": "Scegli il tipo di modello"
+        "pickModelType": "Scegli il tipo di modello",
+        "scanForModels": "Cerca modelli"
     },
     "parameters": {
         "images": "Immagini",
@@ -574,7 +578,7 @@
         "autoSaveToGallery": "Salvataggio automatico nella Galleria",
         "saveBoxRegionOnly": "Salva solo l'area di selezione",
         "limitStrokesToBox": "Limita i tratti all'area di selezione",
-        "showCanvasDebugInfo": "Mostra informazioni di debug della Tela",
+        "showCanvasDebugInfo": "Mostra ulteriori informazioni sulla Tela",
         "clearCanvasHistory": "Cancella cronologia Tela",
         "clearHistory": "Cancella la cronologia",
         "clearCanvasHistoryMessage": "La cancellazione della cronologia della tela lascia intatta la tela corrente, ma cancella in modo irreversibile la cronologia degli annullamenti e dei ripristini.",
@@ -612,7 +616,7 @@
         "copyMetadataJson": "Copia i metadati JSON",
         "exitViewer": "Esci dal visualizzatore",
         "zoomIn": "Zoom avanti",
-        "zoomOut": "Zoom Indietro",
+        "zoomOut": "Zoom indietro",
         "rotateCounterClockwise": "Ruotare in senso antiorario",
         "rotateClockwise": "Ruotare in senso orario",
         "flipHorizontally": "Capovolgi orizzontalmente",

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

@@ -11,7 +11,6 @@
         "langArabic": "العربية",
         "langEnglish": "English",
         "langDutch": "Nederlands",
-        "text2img": "텍스트->이미지",
         "unifiedCanvas": "통합 캔버스",
         "langFrench": "Français",
         "langGerman": "Deutsch",

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

@@ -8,7 +8,6 @@
         "darkTheme": "Donker",
         "lightTheme": "Licht",
         "greenTheme": "Groen",
-        "text2img": "Tekst naar afbeelding",
         "img2img": "Afbeelding naar afbeelding",
         "unifiedCanvas": "Centraal canvas",
         "nodes": "Knooppunten",

invokeai/frontend/web/dist/locales/pl.json

@@ -8,7 +8,6 @@
         "darkTheme": "Ciemny",
         "lightTheme": "Jasny",
         "greenTheme": "Zielony",
-        "text2img": "Tekst na obraz",
         "img2img": "Obraz na obraz",
         "unifiedCanvas": "Tryb uniwersalny",
         "nodes": "Węzły",

invokeai/frontend/web/dist/locales/pt.json

@@ -20,7 +20,6 @@
         "langSpanish": "Espanhol",
         "langRussian": "Русский",
         "langUkranian": "Украї́нська",
-        "text2img": "Texto para Imagem",
         "img2img": "Imagem para Imagem",
         "unifiedCanvas": "Tela Unificada",
         "nodes": "Nós",

invokeai/frontend/web/dist/locales/pt_BR.json

@@ -8,7 +8,6 @@
         "darkTheme": "Noite",
         "lightTheme": "Dia",
         "greenTheme": "Verde",
-        "text2img": "Texto Para Imagem",
         "img2img": "Imagem Para Imagem",
         "unifiedCanvas": "Tela Unificada",
         "nodes": "Nódulos",

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

@@ -8,7 +8,6 @@
         "darkTheme": "Темная",
         "lightTheme": "Светлая",
         "greenTheme": "Зеленая",
-        "text2img": "Изображение из текста (text2img)",
         "img2img": "Изображение в изображение (img2img)",
         "unifiedCanvas": "Универсальный холст",
         "nodes": "Ноды",

invokeai/frontend/web/dist/locales/uk.json

@@ -8,7 +8,6 @@
         "darkTheme": "Темна",
         "lightTheme": "Світла",
         "greenTheme": "Зелена",
-        "text2img": "Зображення із тексту (text2img)",
         "img2img": "Зображення із зображення (img2img)",
         "unifiedCanvas": "Універсальне полотно",
         "nodes": "Вузли",

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

@@ -8,7 +8,6 @@
         "darkTheme": "暗色",
         "lightTheme": "亮色",
         "greenTheme": "绿色",
-        "text2img": "文字到图像",
         "img2img": "图像到图像",
         "unifiedCanvas": "统一画布",
         "nodes": "节点",

invokeai/frontend/web/dist/locales/zh_Hant.json

@@ -33,7 +33,6 @@
         "langBrPortuguese": "巴西葡萄牙語",
         "langRussian": "俄語",
         "langSpanish": "西班牙語",
-        "text2img": "文字到圖像",
         "unifiedCanvas": "統一畫布"
     }
 }

invokeai/frontend/web/docs/API_CLIENT.md

@@ -0,0 +1,87 @@
+# Generated axios API client
+
+- [Generated axios API client](#generated-axios-api-client)
+  - [Generation](#generation)
+    - [Generate the API client from the nodes web server](#generate-the-api-client-from-the-nodes-web-server)
+    - [Generate the API client from JSON](#generate-the-api-client-from-json)
+      - [Getting the JSON from the nodes web server](#getting-the-json-from-the-nodes-web-server)
+      - [Getting the JSON with a python script](#getting-the-json-with-a-python-script)
+      - [Generate the API client](#generate-the-api-client)
+  - [The generated client](#the-generated-client)
+  - [API client customisation](#api-client-customisation)
+
+This API client is generated by an [openapi code generator](https://github.com/ferdikoomen/openapi-typescript-codegen).
+
+All files in `invokeai/frontend/web/src/services/api/` are made by the generator.
+
+## Generation
+
+The axios client may be generated by from the OpenAPI schema from the nodes web server, or from JSON.
+
+### Generate the API client from the nodes web server
+
+We need to start the nodes web server, which serves the OpenAPI schema to the generator.
+
+1. Start the nodes web server.
+
+```bash
+# from the repo root
+python scripts/invoke-new.py --web
+```
+
+2. Generate the API client.
+
+```bash
+# from invokeai/frontend/web/
+yarn api:web
+```
+
+### Generate the API client from JSON
+
+The JSON can be acquired from the nodes web server, or with a python script.
+
+#### Getting the JSON from the nodes web server
+
+Start the nodes web server as described above, then download the file.
+
+```bash
+# from invokeai/frontend/web/
+curl http://localhost:9090/openapi.json -o openapi.json
+```
+
+#### Getting the JSON with a python script
+
+Run this python script from the repo root, so it can access the nodes server modules.
+
+The script will output `openapi.json` in the repo root. Then we need to move it to `invokeai/frontend/web/`.
+
+```bash
+# from the repo root
+python invokeai/app/util/generate_openapi_json.py
+mv invokeai/app/util/openapi.json invokeai/frontend/web/services/fixtures/
+```
+
+#### Generate the API client
+
+Now we can generate the API client from the JSON.
+
+```bash
+# from invokeai/frontend/web/
+yarn api:file
+```
+
+## The generated client
+
+The client will be written to `invokeai/frontend/web/services/api/`:
+
+- `axios` client
+- TS types
+- An easily parseable schema, which we can use to generate UI
+
+## API client customisation
+
+The generator has a default `request.ts` file that implements a base `axios` client. The generated client uses this base client.
+
+One shortcoming of this is base client is it does not provide response headers unless the response body is empty. To fix this, we provide our own lightly-patched `request.ts`.
+
+To access the headers, call `getHeaders(response)` on any response from the generated api client. This function is exported from `invokeai/frontend/web/src/services/util/getHeaders.ts`.

invokeai/frontend/web/docs/EVENTS.md

@@ -0,0 +1,21 @@
+# Events
+
+Events via `socket.io`
+
+## `actions.ts`
+
+Redux actions for all socket events. Payloads all include a timestamp, and optionally some other data.
+
+Any reducer (or middleware) can respond to the actions.
+
+## `middleware.ts`
+
+Redux middleware for events.
+
+Handles dispatching the event actions. Only put logic here if it can't really go anywhere else.
+
+For example, on connect we want to load images to the gallery if it's not populated. This requires dispatching a thunk, so we need to directly dispatch this in the middleware.
+
+## `types.ts`
+
+Hand-written types for the socket events. Cannot generate these from the server, but fortunately they are few and simple.

invokeai/frontend/web/docs/NODE_EDITOR.md

@@ -0,0 +1,17 @@
+# Node Editor Design
+
+WIP
+
+nodes
+
+everything in `src/features/nodes/`
+
+have a look at `state.nodes.invocation`
+
+- on socket connect, if no schema saved, fetch `localhost:9090/openapi.json`, save JSON to `state.nodes.schema`
+- on fulfilled schema fetch, `parseSchema()` the schema. this outputs a `Record<string, Invocation>` which is saved to `state.nodes.invocations` - `Invocation` is like a template for the node
+- when you add a node, the the `Invocation` template is passed to `InvocationComponent.tsx` to build the UI component for that node
+- inputs/outputs have field types - and each field type gets an `FieldComponent` which includes a dispatcher to write state changes to redux `nodesSlice`
+- `reactflow` sends changes to nodes/edges to redux
+- to invoke, `buildNodesGraph()` state, then send this
+- changed onClick Invoke button actions to build the schema, then when schema builds it dispatches the actual network request to create the session - see `session.ts`

invokeai/frontend/web/docs/PACKAGE_SCRIPTS.md

@@ -0,0 +1,29 @@
+# Package Scripts
+
+WIP walkthrough of `package.json` scripts.
+
+## `theme` & `theme:watch`
+
+These run the Chakra CLI to generate types for the theme, or watch for code change and re-generate the types.
+
+The CLI essentially monkeypatches Chakra's files in `node_modules`.
+
+## `postinstall`
+
+The `postinstall` script patches a few packages and runs the Chakra CLI to generate types for the theme.
+
+### Patch `@chakra-ui/cli`
+
+See: <https://github.com/chakra-ui/chakra-ui/issues/7394>
+
+### Patch `redux-persist`
+
+We want to persist the canvas state to `localStorage` but many canvas operations change data very quickly, so we need to debounce the writes to `localStorage`.
+
+`redux-persist` is unfortunately unmaintained. The repo's current code is nonfunctional, but the last release's code depends on a package that was removed from `npm` for being malware, so we cannot just fork it.
+
+So, we have to patch it directly. Perhaps a better way would be to write a debounced storage adapter, but I couldn't figure out how to do that.
+
+### Patch `redux-deep-persist`
+
+This package makes blacklisting and whitelisting persist configs very simple, but we have to patch it to match `redux-persist` for the types to work.

invokeai/frontend/web/docs/README.md

@@ -1,10 +1,16 @@
 # InvokeAI Web UI
 
+- [InvokeAI Web UI](#invokeai-web-ui)
+  - [Stack](#stack)
+  - [Contributing](#contributing)
+    - [Dev Environment](#dev-environment)
+    - [Production builds](#production-builds)
+
 The UI is a fairly straightforward Typescript React app. The only really fancy stuff is the Unified Canvas.
 
 Code in `invokeai/frontend/web/` if you want to have a look.
 
-## Details
+## Stack
 
 State management is Redux via [Redux Toolkit](https://github.com/reduxjs/redux-toolkit). Communication with server is a mix of HTTP and [socket.io](https://github.com/socketio/socket.io-client) (with a custom redux middleware to help).
 
@@ -32,7 +38,7 @@ Start everything in dev mode:
 
 1. Start the dev server: `yarn dev`
 2. Start the InvokeAI UI per usual: `invokeai --web`
-3. Point your browser to the dev server address e.g. `http://localhost:5173/`
+3. Point your browser to the dev server address e.g. <http://localhost:5173/>
 
 ### Production builds
 

invokeai/frontend/web/index.d.ts

@@ -1,6 +1,7 @@
 import React, { PropsWithChildren } from 'react';
 import { IAIPopoverProps } from '../web/src/common/components/IAIPopover';
 import { IAIIconButtonProps } from '../web/src/common/components/IAIIconButton';
+import { InvokeTabName } from 'features/ui/store/tabMap';
 
 export {};
 
@@ -64,9 +65,26 @@ declare module '@invoke-ai/invoke-ai-ui' {
   declare class SettingsModal extends React.Component<SettingsModalProps> {
     public constructor(props: SettingsModalProps);
   }
+
+  declare class StatusIndicator extends React.Component<StatusIndicatorProps> {
+    public constructor(props: StatusIndicatorProps);
+  }
+
+  declare class ModelSelect extends React.Component<ModelSelectProps> {
+    public constructor(props: ModelSelectProps);
+  }
 }
 
-declare function Invoke(props: PropsWithChildren): JSX.Element;
+interface InvokeProps extends PropsWithChildren {
+  apiUrl?: string;
+  disabledPanels?: string[];
+  disabledTabs?: InvokeTabName[];
+  token?: string;
+  shouldTransformUrls?: boolean;
+  shouldFetchImages?: boolean;
+}
+
+declare function Invoke(props: InvokeProps): JSX.Element;
 
 export {
   ThemeChanger,
@@ -74,5 +92,7 @@ export {
   IAIPopover,
   IAIIconButton,
   SettingsModal,
+  StatusIndicator,
+  ModelSelect,
 };
 export = Invoke;

invokeai/frontend/web/package.json

@@ -5,7 +5,11 @@
   "scripts": {
     "prepare": "cd ../../../ && husky install invokeai/frontend/web/.husky",
     "dev": "concurrently \"vite dev\" \"yarn run theme:watch\"",
+    "dev:nodes": "concurrently \"vite dev --mode nodes\" \"yarn run theme:watch\"",
+    "dev:host": "concurrently \"vite dev --host\" \"yarn run theme:watch\"",
     "build": "yarn run lint && vite build",
+    "api:web": "openapi -i http://localhost:9090/openapi.json -o src/services/api --client axios --useOptions --useUnionTypes --exportSchemas true --indent 2 --request src/services/fixtures/request.ts",
+    "api:file": "openapi -i src/services/fixtures/openapi.json -o src/services/api --client axios --useOptions --useUnionTypes --exportSchemas true --indent 2 --request src/services/fixtures/request.ts",
     "preview": "vite preview",
     "lint:madge": "madge --circular src/main.tsx",
     "lint:eslint": "eslint --max-warnings=0 .",
@@ -41,13 +45,16 @@
     "@chakra-ui/react": "^2.5.1",
     "@chakra-ui/styled-system": "^2.6.1",
     "@chakra-ui/theme-tools": "^2.0.16",
+    "@dagrejs/graphlib": "^2.1.12",
     "@emotion/react": "^11.10.6",
     "@emotion/styled": "^11.10.6",
-    "@reduxjs/toolkit": "^1.9.2",
+    "@fontsource/inter": "^4.5.15",
+    "@reduxjs/toolkit": "^1.9.3",
     "chakra-ui-contextmenu": "^1.0.5",
     "dateformat": "^5.0.3",
     "formik": "^2.2.9",
     "framer-motion": "^9.0.4",
+    "fuse.js": "^6.6.2",
     "i18next": "^22.4.10",
     "i18next-browser-languagedetector": "^7.0.1",
     "i18next-http-backend": "^2.1.1",
@@ -67,15 +74,17 @@
     "react-redux": "^8.0.5",
     "react-transition-group": "^4.4.5",
     "react-zoom-pan-pinch": "^2.6.1",
+    "reactflow": "^11.7.0",
     "redux-deep-persist": "^1.0.7",
+    "redux-dynamic-middlewares": "^2.2.0",
     "redux-persist": "^6.0.0",
     "socket.io-client": "^4.6.0",
     "use-image": "^1.1.0",
     "uuid": "^9.0.0"
   },
   "devDependencies": {
-    "@fontsource/inter": "^4.5.15",
     "@types/dateformat": "^5.0.0",
+    "@types/lodash": "^4.14.194",
     "@types/react": "^18.0.28",
     "@types/react-dom": "^18.0.11",
     "@types/react-transition-group": "^4.4.5",
@@ -83,6 +92,7 @@
     "@typescript-eslint/eslint-plugin": "^5.52.0",
     "@typescript-eslint/parser": "^5.52.0",
     "@vitejs/plugin-react-swc": "^3.2.0",
+    "axios": "^1.3.4",
     "babel-plugin-transform-imports": "^2.0.0",
     "concurrently": "^7.6.0",
     "eslint": "^8.34.0",
@@ -90,13 +100,17 @@
     "eslint-plugin-prettier": "^4.2.1",
     "eslint-plugin-react": "^7.32.2",
     "eslint-plugin-react-hooks": "^4.6.0",
+    "form-data": "^4.0.0",
     "husky": "^8.0.3",
     "lint-staged": "^13.1.2",
     "madge": "^6.0.0",
+    "openapi-types": "^12.1.0",
+    "openapi-typescript-codegen": "^0.23.0",
     "postinstall-postinstall": "^2.1.0",
     "prettier": "^2.8.4",
     "rollup-plugin-visualizer": "^5.9.0",
     "terser": "^5.16.4",
+    "typescript": "4.9.5",
     "vite": "^4.1.2",
     "vite-plugin-eslint": "^1.8.1",
     "vite-tsconfig-paths": "^4.0.5",

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

@@ -18,7 +18,7 @@
         "training": "Training",
         "trainingDesc1": "Ein spezieller Arbeitsablauf zum Trainieren Ihrer eigenen Embeddings und Checkpoints mit Textual Inversion und Dreambooth über die Weboberfläche.",
         "trainingDesc2": "InvokeAI unterstützt bereits das Training von benutzerdefinierten Embeddings mit Textual Inversion unter Verwendung des Hauptskripts.",
-        "upload": "Upload",
+        "upload": "Hochladen",
         "close": "Schließen",
         "load": "Laden",
         "statusConnected": "Verbunden",
@@ -41,12 +41,34 @@
         "statusUpscaling": "Hochskalierung",
         "statusUpscalingESRGAN": "Hochskalierung (ESRGAN)",
         "statusLoadingModel": "Laden des Modells",
-        "statusModelChanged": "Modell Geändert"
+        "statusModelChanged": "Modell Geändert",
+        "cancel": "Abbruch",
+        "accept": "Annehmen",
+        "back": "Zurück",
+        "langEnglish": "Englisch",
+        "langDutch": "Niederländisch",
+        "langFrench": "Französisch",
+        "oceanTheme": "Ozean",
+        "langItalian": "Italienisch",
+        "langPortuguese": "Portogisisch",
+        "langRussian": "Russisch",
+        "langUkranian": "Ukrainisch",
+        "hotkeysLabel": "Tastenkombinationen",
+        "githubLabel": "Github",
+        "discordLabel": "Discord",
+        "txt2img": "Text zu Bild",
+        "postprocessing": "Nachbearbeitung",
+        "langPolish": "Polnisch",
+        "langJapanese": "Japanisch",
+        "langArabic": "Arabisch",
+        "langKorean": "Koreanisch",
+        "langHebrew": "Hebräisch",
+        "langSpanish": "Spanisch"
     },
     "gallery": {
         "generations": "Erzeugungen",
         "showGenerations": "Zeige Erzeugnisse",
-        "uploads": "Uploads",
+        "uploads": "Hochgelades",
         "showUploads": "Zeige Uploads",
         "galleryImageSize": "Bildgröße",
         "galleryImageResetSize": "Größe zurücksetzen",
@@ -312,7 +334,11 @@
         "deleteModel": "Model löschen",
         "deleteConfig": "Konfiguration löschen",
         "deleteMsg1": "Möchten Sie diesen Model-Eintrag wirklich aus InvokeAI löschen?",
-        "deleteMsg2": "Dadurch wird die Modellprüfpunktdatei nicht von Ihrer Festplatte gelöscht. Sie können sie bei Bedarf erneut hinzufügen."
+        "deleteMsg2": "Dadurch wird die Modellprüfpunktdatei nicht von Ihrer Festplatte gelöscht. Sie können sie bei Bedarf erneut hinzufügen.",
+        "customConfig": "Benutzerdefinierte Konfiguration",
+        "invokeRoot": "InvokeAI Ordner",
+        "formMessageDiffusersVAELocationDesc": "Falls nicht angegeben, sucht InvokeAI nach der VAE-Datei innerhalb des oben angegebenen Modell Speicherortes.",
+        "checkpointModels": "Kontrollpunkte"
     },
     "parameters": {
         "images": "Bilder",
@@ -370,7 +396,10 @@
         "useInitImg": "Ausgangsbild verwenden",
         "deleteImage": "Bild löschen",
         "initialImage": "Ursprüngliches Bild",
-        "showOptionsPanel": "Optionsleiste zeigen"
+        "showOptionsPanel": "Optionsleiste zeigen",
+        "cancel": {
+            "setType": "Abbruchart festlegen"
+        }
     },
     "settings": {
         "displayInProgress": "Bilder in Bearbeitung anzeigen",
@@ -489,5 +518,25 @@
         "betaDarkenOutside": "Außen abdunkeln",
         "betaLimitToBox": "Begrenzung auf das Feld",
         "betaPreserveMasked": "Maskiertes bewahren"
+    },
+    "accessibility": {
+        "modelSelect": "Model Auswahl",
+        "uploadImage": "Bild hochladen",
+        "previousImage": "Voriges Bild",
+        "useThisParameter": "Benutze diesen Parameter",
+        "copyMetadataJson": "Kopiere metadata JSON",
+        "zoomIn": "Vergrößern",
+        "rotateClockwise": "Im Uhrzeigersinn drehen",
+        "flipHorizontally": "Horizontal drehen",
+        "flipVertically": "Vertikal drehen",
+        "modifyConfig": "Optionen einstellen",
+        "toggleAutoscroll": "Auroscroll ein/ausschalten",
+        "toggleLogViewer": "Log Betrachter ein/ausschalten",
+        "showGallery": "Zeige Galerie",
+        "showOptionsPanel": "Zeige Optionen",
+        "reset": "Zurücksetzen",
+        "nextImage": "Nächstes Bild",
+        "zoomOut": "Verkleinern",
+        "rotateCounterClockwise": "Gegen den Uhrzeigersinn verdrehen"
     }
 }

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

@@ -8,7 +8,7 @@
         "nextImage": "Next Image",
         "useThisParameter": "Use this parameter",
         "copyMetadataJson": "Copy metadata JSON",
-        "exitViewer": "ExitViewer",
+        "exitViewer": "Exit Viewer",
         "zoomIn": "Zoom In",
         "zoomOut": "Zoom Out",
         "rotateCounterClockwise": "Rotate Counter-Clockwise",
@@ -19,7 +19,8 @@
         "toggleAutoscroll": "Toggle autoscroll",
         "toggleLogViewer": "Toggle Log Viewer",
         "showGallery": "Show Gallery",
-        "showOptionsPanel": "Show Options Panel"
+        "showOptionsPanel": "Show Options Panel",
+        "menu": "Menu"
     },
     "common": {
         "hotkeysLabel": "Hotkeys",
@@ -52,6 +53,7 @@
         "txt2img": "Text To Image",
         "img2img": "Image To Image",
         "unifiedCanvas": "Unified Canvas",
+        "linear": "Linear",
         "nodes": "Nodes",
         "postprocessing": "Post Processing",
         "nodesDesc": "A node based system for the generation of images is under development currently. Stay tuned for updates about this amazing feature.",
@@ -505,7 +507,9 @@
         "info": "Info",
         "deleteImage": "Delete Image",
         "initialImage": "Initial Image",
-        "showOptionsPanel": "Show Options Panel"
+        "showOptionsPanel": "Show Options Panel",
+        "hidePreview": "Hide Preview",
+        "showPreview": "Show Preview"
     },
     "settings": {
         "models": "Models",
@@ -522,6 +526,10 @@
         "resetComplete": "Web UI has been reset. Refresh the page to reload."
     },
     "toast": {
+        "serverError": "Server Error",
+        "disconnected": "Disconnected from Server",
+        "connected": "Connected to Server",
+        "canceled": "Processing Canceled",
         "tempFoldersEmptied": "Temp Folder Emptied",
         "uploadFailed": "Upload failed",
         "uploadFailedMultipleImagesDesc": "Multiple images pasted, may only upload one image at a time",

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

@@ -73,7 +73,8 @@
         "postprocessing": "Tratamiento posterior",
         "txt2img": "De texto a imagen",
         "accept": "Aceptar",
-        "cancel": "Cancelar"
+        "cancel": "Cancelar",
+        "linear": "Lineal"
     },
     "gallery": {
         "generations": "Generaciones",
@@ -483,7 +484,9 @@
         "negativePrompts": "Preguntas negativas",
         "imageToImage": "Imagen a imagen",
         "denoisingStrength": "Intensidad de la eliminación del ruido",
-        "hiresStrength": "Alta resistencia"
+        "hiresStrength": "Alta resistencia",
+        "showPreview": "Mostrar la vista previa",
+        "hidePreview": "Ocultar la vista previa"
     },
     "settings": {
         "models": "Modelos",
@@ -529,7 +532,11 @@
         "metadataLoadFailed": "Error al cargar metadatos",
         "initialImageSet": "Imágen inicial establecida",
         "initialImageNotSet": "Imagen inicial no establecida",
-        "initialImageNotSetDesc": "Error al establecer la imágen inicial"
+        "initialImageNotSetDesc": "Error al establecer la imágen inicial",
+        "serverError": "Error en el servidor",
+        "disconnected": "Desconectado del servidor",
+        "canceled": "Procesando la cancelación",
+        "connected": "Conectado al servidor"
     },
     "tooltip": {
         "feature": {
@@ -625,6 +632,7 @@
         "toggleAutoscroll": "Activar el autodesplazamiento",
         "toggleLogViewer": "Alternar el visor de registros",
         "showGallery": "Mostrar galería",
-        "showOptionsPanel": "Mostrar el panel de opciones"
+        "showOptionsPanel": "Mostrar el panel de opciones",
+        "menu": "Menú"
     }
 }

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

@@ -0,0 +1,122 @@
+{
+    "accessibility": {
+        "reset": "Resetoi",
+        "useThisParameter": "Käytä tätä parametria",
+        "modelSelect": "Mallin Valinta",
+        "exitViewer": "Poistu katselimesta",
+        "uploadImage": "Lataa kuva",
+        "copyMetadataJson": "Kopioi metadata JSON:iin",
+        "invokeProgressBar": "Invoken edistymispalkki",
+        "nextImage": "Seuraava kuva",
+        "previousImage": "Edellinen kuva",
+        "zoomIn": "Lähennä",
+        "flipHorizontally": "Käännä vaakasuoraan",
+        "zoomOut": "Loitonna",
+        "rotateCounterClockwise": "Kierrä vastapäivään",
+        "rotateClockwise": "Kierrä myötäpäivään",
+        "flipVertically": "Käännä pystysuoraan",
+        "showGallery": "Näytä galleria",
+        "modifyConfig": "Muokkaa konfiguraatiota",
+        "toggleAutoscroll": "Kytke automaattinen vieritys",
+        "toggleLogViewer": "Kytke lokin katselutila",
+        "showOptionsPanel": "Näytä asetukset"
+    },
+    "common": {
+        "postProcessDesc2": "Erillinen käyttöliittymä tullaan julkaisemaan helpottaaksemme työnkulkua jälkikäsittelyssä.",
+        "training": "Kouluta",
+        "statusLoadingModel": "Ladataan mallia",
+        "statusModelChanged": "Malli vaihdettu",
+        "statusConvertingModel": "Muunnetaan mallia",
+        "statusModelConverted": "Malli muunnettu",
+        "langFrench": "Ranska",
+        "langItalian": "Italia",
+        "languagePickerLabel": "Kielen valinta",
+        "hotkeysLabel": "Pikanäppäimet",
+        "reportBugLabel": "Raportoi Bugista",
+        "langPolish": "Puola",
+        "themeLabel": "Teema",
+        "langDutch": "Hollanti",
+        "settingsLabel": "Asetukset",
+        "githubLabel": "Github",
+        "darkTheme": "Tumma",
+        "lightTheme": "Vaalea",
+        "greenTheme": "Vihreä",
+        "langGerman": "Saksa",
+        "langPortuguese": "Portugali",
+        "discordLabel": "Discord",
+        "langEnglish": "Englanti",
+        "oceanTheme": "Meren sininen",
+        "langRussian": "Venäjä",
+        "langUkranian": "Ukraina",
+        "langSpanish": "Espanja",
+        "upload": "Lataa",
+        "statusMergedModels": "Mallit yhdistelty",
+        "img2img": "Kuva kuvaksi",
+        "nodes": "Solmut",
+        "nodesDesc": "Solmupohjainen järjestelmä kuvien generoimiseen on parhaillaan kehitteillä. Pysy kuulolla päivityksistä tähän uskomattomaan ominaisuuteen liittyen.",
+        "postProcessDesc1": "Invoke AI tarjoaa monenlaisia jälkikäsittelyominaisuukisa. Kuvan laadun skaalaus sekä kasvojen korjaus ovat jo saatavilla WebUI:ssä. Voit ottaa ne käyttöön lisäasetusten valikosta teksti kuvaksi sekä kuva kuvaksi -välilehdiltä. Voit myös suoraan prosessoida kuvia käyttämällä kuvan toimintapainikkeita nykyisen kuvan yläpuolella tai tarkastelussa.",
+        "postprocessing": "Jälkikäsitellään",
+        "postProcessing": "Jälkikäsitellään",
+        "cancel": "Peruuta",
+        "close": "Sulje",
+        "accept": "Hyväksy",
+        "statusConnected": "Yhdistetty",
+        "statusError": "Virhe",
+        "statusProcessingComplete": "Prosessointi valmis",
+        "load": "Lataa",
+        "back": "Takaisin",
+        "statusGeneratingTextToImage": "Generoidaan tekstiä kuvaksi",
+        "trainingDesc2": "InvokeAI tukee jo mukautettujen upotusten kouluttamista tekstin inversiolla käyttäen pääskriptiä.",
+        "statusDisconnected": "Yhteys katkaistu",
+        "statusPreparing": "Valmistellaan",
+        "statusIterationComplete": "Iteraatio valmis",
+        "statusMergingModels": "Yhdistellään malleja",
+        "statusProcessingCanceled": "Valmistelu peruutettu",
+        "statusSavingImage": "Tallennetaan kuvaa",
+        "statusGeneratingImageToImage": "Generoidaan kuvaa kuvaksi",
+        "statusRestoringFacesGFPGAN": "Korjataan kasvoja (GFPGAN)",
+        "statusRestoringFacesCodeFormer": "Korjataan kasvoja (CodeFormer)",
+        "statusGeneratingInpainting": "Generoidaan sisällemaalausta",
+        "statusGeneratingOutpainting": "Generoidaan ulosmaalausta",
+        "statusRestoringFaces": "Korjataan kasvoja",
+        "pinOptionsPanel": "Kiinnitä asetukset -paneeli",
+        "loadingInvokeAI": "Ladataan Invoke AI:ta",
+        "loading": "Ladataan",
+        "statusGenerating": "Generoidaan",
+        "txt2img": "Teksti kuvaksi",
+        "trainingDesc1": "Erillinen työnkulku omien upotusten ja tarkastuspisteiden kouluttamiseksi käyttäen tekstin inversiota ja dreamboothia selaimen käyttöliittymässä.",
+        "postProcessDesc3": "Invoke AI:n komentorivi tarjoaa paljon muita ominaisuuksia, kuten esimerkiksi Embiggenin.",
+        "unifiedCanvas": "Yhdistetty kanvas",
+        "statusGenerationComplete": "Generointi valmis"
+    },
+    "gallery": {
+        "uploads": "Lataukset",
+        "showUploads": "Näytä lataukset",
+        "galleryImageResetSize": "Resetoi koko",
+        "maintainAspectRatio": "Säilytä kuvasuhde",
+        "galleryImageSize": "Kuvan koko",
+        "pinGallery": "Kiinnitä galleria",
+        "showGenerations": "Näytä generaatiot",
+        "singleColumnLayout": "Yhden sarakkeen asettelu",
+        "generations": "Generoinnit",
+        "gallerySettings": "Gallerian asetukset",
+        "autoSwitchNewImages": "Vaihda uusiin kuviin automaattisesti",
+        "allImagesLoaded": "Kaikki kuvat ladattu",
+        "noImagesInGallery": "Ei kuvia galleriassa",
+        "loadMore": "Lataa lisää"
+    },
+    "hotkeys": {
+        "keyboardShortcuts": "näppäimistön pikavalinnat",
+        "appHotkeys": "Sovelluksen pikanäppäimet",
+        "generalHotkeys": "Yleiset pikanäppäimet",
+        "galleryHotkeys": "Gallerian pikanäppäimet",
+        "unifiedCanvasHotkeys": "Yhdistetyn kanvaan pikanäppäimet",
+        "cancel": {
+            "desc": "Peruuta kuvan luominen",
+            "title": "Peruuta"
+        },
+        "invoke": {
+            "desc": "Luo kuva"
+        }
+    }
+}

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

@@ -73,7 +73,8 @@
         "postprocessing": "Post Elaborazione",
         "txt2img": "Testo a Immagine",
         "accept": "Accetta",
-        "cancel": "Annulla"
+        "cancel": "Annulla",
+        "linear": "Lineare"
     },
     "gallery": {
         "generations": "Generazioni",
@@ -483,7 +484,9 @@
         },
         "hSymmetryStep": "Passi Simmetria Orizzontale",
         "vSymmetryStep": "Passi Simmetria Verticale",
-        "symmetry": "Simmetria"
+        "symmetry": "Simmetria",
+        "hidePreview": "Nascondi l'anteprima",
+        "showPreview": "Mostra l'anteprima"
     },
     "settings": {
         "models": "Modelli",
@@ -529,7 +532,11 @@
         "metadataLoadFailed": "Impossibile caricare i metadati",
         "initialImageSet": "Immagine iniziale impostata",
         "initialImageNotSet": "Immagine iniziale non impostata",
-        "initialImageNotSetDesc": "Impossibile caricare l'immagine iniziale"
+        "initialImageNotSetDesc": "Impossibile caricare l'immagine iniziale",
+        "serverError": "Errore del Server",
+        "disconnected": "Disconnesso dal Server",
+        "connected": "Connesso al Server",
+        "canceled": "Elaborazione annullata"
     },
     "tooltip": {
         "feature": {
@@ -625,6 +632,7 @@
         "showOptionsPanel": "Mostra il pannello opzioni",
         "flipVertically": "Capovolgi verticalmente",
         "toggleAutoscroll": "Attiva/disattiva lo scorrimento automatico",
-        "modifyConfig": "Modifica configurazione"
+        "modifyConfig": "Modifica configurazione",
+        "menu": "Menu"
     }
 }

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

@@ -37,7 +37,43 @@
         "statusUpscaling": "アップスケーリング",
         "statusUpscalingESRGAN": "アップスケーリング (ESRGAN)",
         "statusLoadingModel": "モデルを読み込む",
-        "statusModelChanged": "モデルを変更"
+        "statusModelChanged": "モデルを変更",
+        "cancel": "キャンセル",
+        "accept": "同意",
+        "langBrPortuguese": "Português do Brasil",
+        "langRussian": "Русский",
+        "langSimplifiedChinese": "简体中文",
+        "langUkranian": "Украї́нська",
+        "langSpanish": "Español",
+        "img2img": "img2img",
+        "unifiedCanvas": "Unified Canvas",
+        "statusMergingModels": "モデルのマージ",
+        "statusModelConverted": "変換済モデル",
+        "statusGeneratingInpainting": "Inpaintingを生成",
+        "statusIterationComplete": "Iteration Complete",
+        "statusGeneratingOutpainting": "Outpaintingを生成",
+        "loading": "ロード中",
+        "loadingInvokeAI": "Invoke AIをロード中",
+        "statusConvertingModel": "モデルの変換",
+        "statusMergedModels": "マージ済モデル",
+        "pinOptionsPanel": "オプションパネルを固定",
+        "githubLabel": "Github",
+        "hotkeysLabel": "ホットキー",
+        "langHebrew": "עברית",
+        "discordLabel": "Discord",
+        "langItalian": "Italiano",
+        "langEnglish": "English",
+        "oceanTheme": "オーシャン",
+        "langArabic": "アラビア語",
+        "langDutch": "Nederlands",
+        "langFrench": "Français",
+        "langGerman": "Deutsch",
+        "langPortuguese": "Português",
+        "nodes": "ノード",
+        "langKorean": "한국어",
+        "langPolish": "Polski",
+        "txt2img": "txt2img",
+        "postprocessing": "Post Processing"
     },
     "gallery": {
         "uploads": "アップロード",
@@ -46,11 +82,14 @@
         "galleryImageResetSize": "サイズをリセット",
         "gallerySettings": "ギャラリーの設定",
         "maintainAspectRatio": "アスペクト比を維持",
-        "singleColumnLayout": "シングルカラムレイアウト",
+        "singleColumnLayout": "1カラムレイアウト",
         "pinGallery": "ギャラリーにピン留め",
         "allImagesLoaded": "すべての画像を読み込む",
         "loadMore": "さらに読み込む",
-        "noImagesInGallery": "ギャラリーに画像がありません"
+        "noImagesInGallery": "ギャラリーに画像がありません",
+        "generations": "生成",
+        "showGenerations": "生成過程を見る",
+        "autoSwitchNewImages": "新しい画像に自動切替"
     },
     "hotkeys": {
         "keyboardShortcuts": "キーボードショートカット",
@@ -59,14 +98,16 @@
         "galleryHotkeys": "ギャラリーのホットキー",
         "unifiedCanvasHotkeys": "Unified Canvasのホットキー",
         "invoke": {
-            "desc": "画像を生成"
+            "desc": "画像を生成",
+            "title": "Invoke"
         },
         "cancel": {
             "title": "キャンセル",
             "desc": "画像の生成をキャンセル"
         },
         "focusPrompt": {
-            "desc": "プロンプトテキストボックスにフォーカス"
+            "desc": "プロンプトテキストボックスにフォーカス",
+            "title": "プロジェクトにフォーカス"
         },
         "toggleOptions": {
             "title": "オプションパネルのトグル",
@@ -410,5 +451,27 @@
         "accept": "同意",
         "showHide": "表示/非表示",
         "discardAll": "すべて破棄"
+    },
+    "accessibility": {
+        "modelSelect": "モデルを選択",
+        "invokeProgressBar": "進捗バー",
+        "reset": "リセット",
+        "uploadImage": "画像をアップロード",
+        "previousImage": "前の画像",
+        "nextImage": "次の画像",
+        "useThisParameter": "このパラメータを使用する",
+        "copyMetadataJson": "メタデータをコピー(JSON)",
+        "zoomIn": "ズームイン",
+        "exitViewer": "ExitViewer",
+        "zoomOut": "ズームアウト",
+        "rotateCounterClockwise": "反時計回りに回転",
+        "rotateClockwise": "時計回りに回転",
+        "flipHorizontally": "水平方向に反転",
+        "flipVertically": "垂直方向に反転",
+        "toggleAutoscroll": "自動スクロールの切替",
+        "modifyConfig": "Modify Config",
+        "toggleLogViewer": "Log Viewerの切替",
+        "showGallery": "ギャラリーを表示",
+        "showOptionsPanel": "オプションパネルを表示"
     }
 }

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

@@ -0,0 +1 @@
+{}

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

@@ -62,7 +62,18 @@
         "statusConvertingModel": "Omzetten van model",
         "statusModelConverted": "Model omgezet",
         "statusMergingModels": "Samenvoegen van modellen",
-        "statusMergedModels": "Modellen samengevoegd"
+        "statusMergedModels": "Modellen samengevoegd",
+        "cancel": "Annuleer",
+        "accept": "Akkoord",
+        "langPortuguese": "Português",
+        "pinOptionsPanel": "Zet deelscherm Opties vast",
+        "loading": "Bezig met laden",
+        "loadingInvokeAI": "Bezig met laden van Invoke AI",
+        "oceanTheme": "Oceaan",
+        "langHebrew": "עברית",
+        "langKorean": "한국어",
+        "txt2img": "Tekst naar afbeelding",
+        "postprocessing": "Nabewerking"
     },
     "gallery": {
         "generations": "Gegenereerde afbeeldingen",
@@ -301,7 +312,7 @@
         "name": "Naam",
         "nameValidationMsg": "Geef een naam voor je model",
         "description": "Beschrijving",
-        "descriptionValidationMsg": "Voeg een beschrijving toe voor je model.",
+        "descriptionValidationMsg": "Voeg een beschrijving toe voor je model",
         "config": "Configuratie",
         "configValidationMsg": "Pad naar het configuratiebestand van je model.",
         "modelLocation": "Locatie model",
@@ -391,7 +402,13 @@
         "modelMergeInterpAddDifferenceHelp": "In deze stand wordt model 3 eerst van model 2 afgehaald. Wat daar uitkomt wordt gemengd met model 1, gebruikmakend van de hierboven ingestelde alfawaarde.",
         "inverseSigmoid": "Keer Sigmoid om",
         "sigmoid": "Sigmoid",
-        "weightedSum": "Gewogen som"
+        "weightedSum": "Gewogen som",
+        "v2_base": "v2 (512px)",
+        "v2_768": "v2 (768px)",
+        "none": "geen",
+        "addDifference": "Voeg verschil toe",
+        "scanForModels": "Scan naar modellen",
+        "pickModelType": "Kies modelsoort"
     },
     "parameters": {
         "images": "Afbeeldingen",
@@ -561,7 +578,7 @@
         "autoSaveToGallery": "Bewaar automatisch naar galerij",
         "saveBoxRegionOnly": "Bewaar alleen tekengebied",
         "limitStrokesToBox": "Beperk streken tot tekenvak",
-        "showCanvasDebugInfo": "Toon foutopsporingsgegevens canvas",
+        "showCanvasDebugInfo": "Toon aanvullende canvasgegevens",
         "clearCanvasHistory": "Wis canvasgeschiedenis",
         "clearHistory": "Wis geschiedenis",
         "clearCanvasHistoryMessage": "Het wissen van de canvasgeschiedenis laat het huidige canvas ongemoeid, maar wist onherstelbaar de geschiedenis voor het ongedaan maken en herhalen.",
@@ -587,5 +604,27 @@
         "betaDarkenOutside": "Verduister buiten tekenvak",
         "betaLimitToBox": "Beperk tot tekenvak",
         "betaPreserveMasked": "Behoud masker"
+    },
+    "accessibility": {
+        "exitViewer": "Stop viewer",
+        "zoomIn": "Zoom in",
+        "rotateCounterClockwise": "Draai tegen de klok in",
+        "modelSelect": "Modelkeuze",
+        "invokeProgressBar": "Voortgangsbalk Invoke",
+        "reset": "Herstel",
+        "uploadImage": "Upload afbeelding",
+        "previousImage": "Vorige afbeelding",
+        "nextImage": "Volgende afbeelding",
+        "useThisParameter": "Gebruik deze parameter",
+        "copyMetadataJson": "Kopieer metagegevens-JSON",
+        "zoomOut": "Zoom uit",
+        "rotateClockwise": "Draai met de klok mee",
+        "flipHorizontally": "Spiegel horizontaal",
+        "flipVertically": "Spiegel verticaal",
+        "modifyConfig": "Wijzig configuratie",
+        "toggleAutoscroll": "Autom. scrollen aan/uit",
+        "toggleLogViewer": "Logboekviewer aan/uit",
+        "showGallery": "Toon galerij",
+        "showOptionsPanel": "Toon deelscherm Opties"
     }
 }

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

@@ -9,7 +9,7 @@
         "lightTheme": "Светлая",
         "greenTheme": "Зеленая",
         "img2img": "Изображение в изображение (img2img)",
-        "unifiedCanvas": "Универсальный холст",
+        "unifiedCanvas": "Единый холст",
         "nodes": "Ноды",
         "langRussian": "Русский",
         "nodesDesc": "Cистема генерации изображений на основе нодов (узлов) уже разрабатывается. Следите за новостями об этой замечательной функции.",
@@ -53,7 +53,28 @@
         "loading": "Загрузка",
         "loadingInvokeAI": "Загрузка Invoke AI",
         "back": "Назад",
-        "statusConvertingModel": "Конвертация модели"
+        "statusConvertingModel": "Конвертация модели",
+        "cancel": "Отменить",
+        "accept": "Принять",
+        "oceanTheme": "Океан",
+        "langUkranian": "Украинский",
+        "langEnglish": "Английский",
+        "postprocessing": "Постобработка",
+        "langArabic": "Арабский",
+        "langSpanish": "Испанский",
+        "langSimplifiedChinese": "Китайский (упрощенный)",
+        "langDutch": "Нидерландский",
+        "langFrench": "Французский",
+        "langGerman": "Немецкий",
+        "langHebrew": "Иврит",
+        "langItalian": "Итальянский",
+        "langJapanese": "Японский",
+        "langKorean": "Корейский",
+        "langPolish": "Польский",
+        "langPortuguese": "Португальский",
+        "txt2img": "Текст в изображение (txt2img)",
+        "langBrPortuguese": "Португальский (Бразилия)",
+        "linear": "Линейная обработка"
     },
     "gallery": {
         "generations": "Генерации",
@@ -72,11 +93,11 @@
         "noImagesInGallery": "Изображений нет"
     },
     "hotkeys": {
-        "keyboardShortcuts": "Клавиатурные сокращения",
+        "keyboardShortcuts": "Горячие клавиши",
         "appHotkeys": "Горячие клавиши приложения",
         "generalHotkeys": "Общие горячие клавиши",
         "galleryHotkeys": "Горячие клавиши галереи",
-        "unifiedCanvasHotkeys": "Горячие клавиши универсального холста",
+        "unifiedCanvasHotkeys": "Горячие клавиши Единого холста",
         "invoke": {
             "title": "Invoke",
             "desc": "Сгенерировать изображение"
@@ -266,12 +287,12 @@
             "desc": "Сбросить вид холста"
         },
         "previousStagingImage": {
-            "title": "Previous Staging Image",
-            "desc": "Предыдущее изображение"
+            "title": "Предыдущее изображение",
+            "desc": "Предыдущая область изображения"
         },
         "nextStagingImage": {
-            "title": "Next Staging Image",
-            "desc": "Следующее изображение"
+            "title": "Следующее изображение",
+            "desc": "Следующая область изображения"
         },
         "acceptStagingImage": {
             "title": "Принять изображение",
@@ -353,7 +374,42 @@
         "modelConverted": "Модель преобразована",
         "invokeRoot": "Каталог InvokeAI",
         "modelsMerged": "Модели объединены",
-        "mergeModels": "Объединить модели"
+        "mergeModels": "Объединить модели",
+        "scanForModels": "Просканировать модели",
+        "sigmoid": "Сигмоид",
+        "formMessageDiffusersModelLocation": "Расположение Diffusers-модели",
+        "modelThree": "Модель 3",
+        "modelMergeHeaderHelp2": "Только Diffusers-модели доступны для объединения. Если вы хотите объединить checkpoint-модели, сначала преобразуйте их в Diffusers.",
+        "pickModelType": "Выбрать тип модели",
+        "formMessageDiffusersVAELocation": "Расположение VAE",
+        "v1": "v1",
+        "convertToDiffusersSaveLocation": "Путь сохранения",
+        "customSaveLocation": "Пользовательский путь сохранения",
+        "alpha": "Альфа",
+        "diffusersModels": "Diffusers",
+        "customConfig": "Пользовательский конфиг",
+        "pathToCustomConfig": "Путь к пользовательскому конфигу",
+        "inpainting": "v1 Inpainting",
+        "sameFolder": "В ту же папку",
+        "modelOne": "Модель 1",
+        "mergedModelCustomSaveLocation": "Пользовательский путь",
+        "none": "пусто",
+        "addDifference": "Добавить разницу",
+        "vaeRepoIDValidationMsg": "Онлайн репозиторий VAE",
+        "convertToDiffusersHelpText2": "Этот процесс заменит вашу запись в Model Manager на версию той же модели в Diffusers.",
+        "custom": "Пользовательский",
+        "modelTwo": "Модель 2",
+        "mergedModelSaveLocation": "Путь сохранения",
+        "merge": "Объединить",
+        "interpolationType": "Тип интерполяции",
+        "modelMergeInterpAddDifferenceHelp": "В этом режиме Модель 3 сначала вычитается из Модели 2. Результирующая версия смешивается с Моделью 1 с установленным выше коэффициентом Альфа.",
+        "modelMergeHeaderHelp1": "Вы можете объединить до трех разных моделей, чтобы создать смешанную, соответствующую вашим потребностям.",
+        "modelMergeAlphaHelp": "Альфа влияет на силу смешивания моделей. Более низкие значения альфа приводят к меньшему влиянию второй модели.",
+        "inverseSigmoid": "Обратный Сигмоид",
+        "weightedSum": "Взвешенная сумма",
+        "safetensorModels": "SafeTensors",
+        "v2_768": "v2 (768px)",
+        "v2_base": "v2 (512px)"
     },
     "parameters": {
         "images": "Изображения",
@@ -380,7 +436,7 @@
         "scale": "Масштаб",
         "otherOptions": "Другие параметры",
         "seamlessTiling": "Бесшовный узор",
-        "hiresOptim": "Высокое разрешение",
+        "hiresOptim": "Оптимизация High Res",
         "imageFit": "Уместить изображение",
         "codeformerFidelity": "Точность",
         "seamSize": "Размер шва",
@@ -397,11 +453,11 @@
         "infillScalingHeader": "Заполнение и масштабирование",
         "img2imgStrength": "Сила обработки img2img",
         "toggleLoopback": "Зациклить обработку",
-        "invoke": "Вызвать",
+        "invoke": "Invoke",
         "promptPlaceholder": "Введите запрос здесь (на английском). [исключенные токены], (более значимые)++, (менее значимые)--, swap и blend тоже доступны (смотрите Github)",
         "sendTo": "Отправить",
         "sendToImg2Img": "Отправить в img2img",
-        "sendToUnifiedCanvas": "Отправить на холст",
+        "sendToUnifiedCanvas": "Отправить на Единый холст",
         "copyImageToLink": "Скопировать ссылку",
         "downloadImage": "Скачать",
         "openInViewer": "Открыть в просмотрщике",
@@ -413,7 +469,24 @@
         "info": "Метаданные",
         "deleteImage": "Удалить изображение",
         "initialImage": "Исходное изображение",
-        "showOptionsPanel": "Показать панель настроек"
+        "showOptionsPanel": "Показать панель настроек",
+        "vSymmetryStep": "Шаг верт. симметрии",
+        "cancel": {
+            "immediate": "Отменить немедленно",
+            "schedule": "Отменить после текущей итерации",
+            "isScheduled": "Отмена",
+            "setType": "Установить тип отмены"
+        },
+        "general": "Основное",
+        "hiresStrength": "Сила High Res",
+        "symmetry": "Симметрия",
+        "hSymmetryStep": "Шаг гор. симметрии",
+        "hidePreview": "Скрыть предпросмотр",
+        "imageToImage": "Изображение в изображение",
+        "denoisingStrength": "Сила шумоподавления",
+        "copyImage": "Скопировать изображение",
+        "negativePrompts": "Исключающий запрос",
+        "showPreview": "Показать предпросмотр"
     },
     "settings": {
         "models": "Модели",
@@ -423,10 +496,11 @@
         "displayHelpIcons": "Показывать значки подсказок",
         "useCanvasBeta": "Показывать инструменты слева (Beta UI)",
         "enableImageDebugging": "Включить отладку",
-        "resetWebUI": "Вернуть умолчания",
+        "resetWebUI": "Сброс настроек Web UI",
         "resetWebUIDesc1": "Сброс настроек веб-интерфейса удаляет только локальный кэш браузера с вашими изображениями и настройками. Он не удаляет изображения с диска.",
         "resetWebUIDesc2": "Если изображения не отображаются в галерее или не работает что-то еще, пожалуйста, попробуйте сбросить настройки, прежде чем сообщать о проблеме на GitHub.",
-        "resetComplete": "Интерфейс сброшен. Обновите эту страницу."
+        "resetComplete": "Интерфейс сброшен. Обновите эту страницу.",
+        "useSlidersForAll": "Использовать ползунки для всех параметров"
     },
     "toast": {
         "tempFoldersEmptied": "Временная папка очищена",
@@ -441,7 +515,7 @@
         "imageSavedToGallery": "Изображение сохранено в галерею",
         "canvasMerged": "Холст объединен",
         "sentToImageToImage": "Отправить в img2img",
-        "sentToUnifiedCanvas": "Отправить на холст",
+        "sentToUnifiedCanvas": "Отправлено на Единый холст",
         "parametersSet": "Параметры заданы",
         "parametersNotSet": "Параметры не заданы",
         "parametersNotSetDesc": "Не найдены метаданные изображения.",
@@ -458,7 +532,11 @@
         "metadataLoadFailed": "Не удалось загрузить метаданные",
         "initialImageSet": "Исходное изображение задано",
         "initialImageNotSet": "Исходное изображение не задано",
-        "initialImageNotSetDesc": "Не получилось загрузить исходное изображение"
+        "initialImageNotSetDesc": "Не получилось загрузить исходное изображение",
+        "serverError": "Ошибка сервера",
+        "disconnected": "Отключено от сервера",
+        "connected": "Подключено к серверу",
+        "canceled": "Обработка отменена"
     },
     "tooltip": {
         "feature": {
@@ -507,7 +585,7 @@
         "autoSaveToGallery": "Автосохранение в галерее",
         "saveBoxRegionOnly": "Сохранять только выделение",
         "limitStrokesToBox": "Ограничить штрихи выделением",
-        "showCanvasDebugInfo": "Показать отладку холста",
+        "showCanvasDebugInfo": "Показать доп. информацию о холсте",
         "clearCanvasHistory": "Очистить историю холста",
         "clearHistory": "Очистить историю",
         "clearCanvasHistoryMessage": "Очистка истории холста оставляет текущий холст нетронутым, но удаляет историю отмен и повторов.",
@@ -535,6 +613,26 @@
         "betaPreserveMasked": "Сохранять маскируемую область"
     },
     "accessibility": {
-        "modelSelect": "Выбор модели"
+        "modelSelect": "Выбор модели",
+        "uploadImage": "Загрузить изображение",
+        "nextImage": "Следующее изображение",
+        "previousImage": "Предыдущее изображение",
+        "zoomIn": "Приблизить",
+        "zoomOut": "Отдалить",
+        "rotateClockwise": "Повернуть по часовой стрелке",
+        "rotateCounterClockwise": "Повернуть против часовой стрелки",
+        "flipVertically": "Перевернуть вертикально",
+        "flipHorizontally": "Отразить горизонтально",
+        "toggleAutoscroll": "Включить автопрокрутку",
+        "toggleLogViewer": "Показать или скрыть просмотрщик логов",
+        "showOptionsPanel": "Показать опции",
+        "showGallery": "Показать галерею",
+        "invokeProgressBar": "Индикатор выполнения",
+        "reset": "Сброс",
+        "modifyConfig": "Изменить конфиг",
+        "useThisParameter": "Использовать этот параметр",
+        "copyMetadataJson": "Скопировать метаданные JSON",
+        "exitViewer": "Закрыть просмотрщик",
+        "menu": "Меню"
     }
 }

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

@@ -0,0 +1,254 @@
+{
+    "accessibility": {
+        "copyMetadataJson": "Kopiera metadata JSON",
+        "zoomIn": "Zooma in",
+        "exitViewer": "Avslutningsvisare",
+        "modelSelect": "Välj modell",
+        "uploadImage": "Ladda upp bild",
+        "invokeProgressBar": "Invoke förloppsmätare",
+        "nextImage": "Nästa bild",
+        "toggleAutoscroll": "Växla automatisk rullning",
+        "flipHorizontally": "Vänd vågrätt",
+        "flipVertically": "Vänd lodrätt",
+        "zoomOut": "Zooma ut",
+        "toggleLogViewer": "Växla logvisare",
+        "reset": "Starta om",
+        "previousImage": "Föregående bild",
+        "useThisParameter": "Använd denna parametern",
+        "showGallery": "Visa galleri",
+        "rotateCounterClockwise": "Rotera moturs",
+        "rotateClockwise": "Rotera medurs",
+        "modifyConfig": "Ändra konfiguration",
+        "showOptionsPanel": "Visa inställningspanelen"
+    },
+    "common": {
+        "hotkeysLabel": "Snabbtangenter",
+        "reportBugLabel": "Rapportera bugg",
+        "githubLabel": "Github",
+        "discordLabel": "Discord",
+        "settingsLabel": "Inställningar",
+        "darkTheme": "Mörk",
+        "lightTheme": "Ljus",
+        "greenTheme": "Grön",
+        "oceanTheme": "Hav",
+        "langEnglish": "Engelska",
+        "langDutch": "Nederländska",
+        "langFrench": "Franska",
+        "langGerman": "Tyska",
+        "langItalian": "Italienska",
+        "langArabic": "العربية",
+        "langHebrew": "עברית",
+        "langPolish": "Polski",
+        "langPortuguese": "Português",
+        "langBrPortuguese": "Português do Brasil",
+        "langSimplifiedChinese": "简体中文",
+        "langJapanese": "日本語",
+        "langKorean": "한국어",
+        "langRussian": "Русский",
+        "unifiedCanvas": "Förenad kanvas",
+        "nodesDesc": "Ett nodbaserat system för bildgenerering är under utveckling. Håll utkik för uppdateringar om denna fantastiska funktion.",
+        "langUkranian": "Украї́нська",
+        "langSpanish": "Español",
+        "postProcessDesc2": "Ett dedikerat användargränssnitt kommer snart att släppas för att underlätta mer avancerade arbetsflöden av efterbehandling.",
+        "trainingDesc1": "Ett dedikerat arbetsflöde för träning av dina egna inbäddningar och kontrollpunkter genom Textual Inversion eller Dreambooth från webbgränssnittet.",
+        "trainingDesc2": "InvokeAI stöder redan träning av anpassade inbäddningar med hjälp av Textual Inversion genom huvudscriptet.",
+        "upload": "Ladda upp",
+        "close": "Stäng",
+        "cancel": "Avbryt",
+        "accept": "Acceptera",
+        "statusDisconnected": "Frånkopplad",
+        "statusGeneratingTextToImage": "Genererar text till bild",
+        "statusGeneratingImageToImage": "Genererar Bild till bild",
+        "statusGeneratingInpainting": "Genererar Måla i",
+        "statusGenerationComplete": "Generering klar",
+        "statusModelConverted": "Modell konverterad",
+        "statusMergingModels": "Sammanfogar modeller",
+        "pinOptionsPanel": "Nåla fast inställningspanelen",
+        "loading": "Laddar",
+        "loadingInvokeAI": "Laddar Invoke AI",
+        "statusRestoringFaces": "Återskapar ansikten",
+        "languagePickerLabel": "Språkväljare",
+        "themeLabel": "Tema",
+        "txt2img": "Text till bild",
+        "nodes": "Noder",
+        "img2img": "Bild till bild",
+        "postprocessing": "Efterbehandling",
+        "postProcessing": "Efterbehandling",
+        "load": "Ladda",
+        "training": "Träning",
+        "postProcessDesc1": "Invoke AI erbjuder ett brett utbud av efterbehandlingsfunktioner. Uppskalning och ansiktsåterställning finns redan tillgängligt i webbgränssnittet. Du kommer åt dem ifrån Avancerade inställningar-menyn under Bild till bild-fliken. Du kan också behandla bilder direkt genom att använda knappen bildåtgärder ovanför nuvarande bild eller i bildvisaren.",
+        "postProcessDesc3": "Invoke AI's kommandotolk erbjuder många olika funktioner, bland annat \"Förstora\".",
+        "statusGenerating": "Genererar",
+        "statusError": "Fel",
+        "back": "Bakåt",
+        "statusConnected": "Ansluten",
+        "statusPreparing": "Förbereder",
+        "statusProcessingCanceled": "Bearbetning avbruten",
+        "statusProcessingComplete": "Bearbetning färdig",
+        "statusGeneratingOutpainting": "Genererar Fyll ut",
+        "statusIterationComplete": "Itterering klar",
+        "statusSavingImage": "Sparar bild",
+        "statusRestoringFacesGFPGAN": "Återskapar ansikten (GFPGAN)",
+        "statusRestoringFacesCodeFormer": "Återskapar ansikten (CodeFormer)",
+        "statusUpscaling": "Skala upp",
+        "statusUpscalingESRGAN": "Uppskalning (ESRGAN)",
+        "statusModelChanged": "Modell ändrad",
+        "statusLoadingModel": "Laddar modell",
+        "statusConvertingModel": "Konverterar modell",
+        "statusMergedModels": "Modeller sammanfogade"
+    },
+    "gallery": {
+        "generations": "Generationer",
+        "showGenerations": "Visa generationer",
+        "uploads": "Uppladdningar",
+        "showUploads": "Visa uppladdningar",
+        "galleryImageSize": "Bildstorlek",
+        "allImagesLoaded": "Alla bilder laddade",
+        "loadMore": "Ladda mer",
+        "galleryImageResetSize": "Återställ storlek",
+        "gallerySettings": "Galleriinställningar",
+        "maintainAspectRatio": "Behåll bildförhållande",
+        "pinGallery": "Nåla fast galleri",
+        "noImagesInGallery": "Inga bilder i galleriet",
+        "autoSwitchNewImages": "Ändra automatiskt till nya bilder",
+        "singleColumnLayout": "Enkolumnslayout"
+    },
+    "hotkeys": {
+        "generalHotkeys": "Allmänna snabbtangenter",
+        "galleryHotkeys": "Gallerisnabbtangenter",
+        "unifiedCanvasHotkeys": "Snabbtangenter för sammanslagskanvas",
+        "invoke": {
+            "title": "Anropa",
+            "desc": "Genererar en bild"
+        },
+        "cancel": {
+            "title": "Avbryt",
+            "desc": "Avbryt bildgenerering"
+        },
+        "focusPrompt": {
+            "desc": "Fokusera området för promptinmatning",
+            "title": "Fokusprompt"
+        },
+        "pinOptions": {
+            "desc": "Nåla fast alternativpanelen",
+            "title": "Nåla fast alternativ"
+        },
+        "toggleOptions": {
+            "title": "Växla inställningar",
+            "desc": "Öppna och stäng alternativpanelen"
+        },
+        "toggleViewer": {
+            "title": "Växla visaren",
+            "desc": "Öppna och stäng bildvisaren"
+        },
+        "toggleGallery": {
+            "title": "Växla galleri",
+            "desc": "Öppna eller stäng galleribyrån"
+        },
+        "maximizeWorkSpace": {
+            "title": "Maximera arbetsyta",
+            "desc": "Stäng paneler och maximera arbetsyta"
+        },
+        "changeTabs": {
+            "title": "Växla flik",
+            "desc": "Byt till en annan arbetsyta"
+        },
+        "consoleToggle": {
+            "title": "Växla konsol",
+            "desc": "Öppna och stäng konsol"
+        },
+        "setSeed": {
+            "desc": "Använd seed för nuvarande bild",
+            "title": "välj seed"
+        },
+        "setParameters": {
+            "title": "Välj parametrar",
+            "desc": "Använd alla parametrar från nuvarande bild"
+        },
+        "setPrompt": {
+            "desc": "Använd prompt för nuvarande bild",
+            "title": "Välj prompt"
+        },
+        "restoreFaces": {
+            "title": "Återskapa ansikten",
+            "desc": "Återskapa nuvarande bild"
+        },
+        "upscale": {
+            "title": "Skala upp",
+            "desc": "Skala upp nuvarande bild"
+        },
+        "showInfo": {
+            "title": "Visa info",
+            "desc": "Visa metadata för nuvarande bild"
+        },
+        "sendToImageToImage": {
+            "title": "Skicka till Bild till bild",
+            "desc": "Skicka nuvarande bild till Bild till bild"
+        },
+        "deleteImage": {
+            "title": "Radera bild",
+            "desc": "Radera nuvarande bild"
+        },
+        "closePanels": {
+            "title": "Stäng paneler",
+            "desc": "Stäng öppna paneler"
+        },
+        "previousImage": {
+            "title": "Föregående bild",
+            "desc": "Visa föregående bild"
+        },
+        "nextImage": {
+            "title": "Nästa bild",
+            "desc": "Visa nästa bild"
+        },
+        "toggleGalleryPin": {
+            "title": "Växla gallerinål",
+            "desc": "Nålar fast eller nålar av galleriet i gränssnittet"
+        },
+        "increaseGalleryThumbSize": {
+            "title": "Förstora galleriets bildstorlek",
+            "desc": "Förstora miniatyrbildernas storlek"
+        },
+        "decreaseGalleryThumbSize": {
+            "title": "Minska gelleriets bildstorlek",
+            "desc": "Minska miniatyrbildernas storlek i galleriet"
+        },
+        "decreaseBrushSize": {
+            "desc": "Förminska storleken på kanvas- pensel eller suddgummi",
+            "title": "Minska penselstorlek"
+        },
+        "increaseBrushSize": {
+            "title": "Öka penselstorlek",
+            "desc": "Öka stoleken på kanvas- pensel eller suddgummi"
+        },
+        "increaseBrushOpacity": {
+            "title": "Öka penselns opacitet",
+            "desc": "Öka opaciteten för kanvaspensel"
+        },
+        "decreaseBrushOpacity": {
+            "desc": "Minska kanvaspenselns opacitet",
+            "title": "Minska penselns opacitet"
+        },
+        "moveTool": {
+            "title": "Flytta",
+            "desc": "Tillåt kanvasnavigation"
+        },
+        "fillBoundingBox": {
+            "title": "Fyll ram",
+            "desc": "Fyller ramen med pensels färg"
+        },
+        "keyboardShortcuts": "Snabbtangenter",
+        "appHotkeys": "Appsnabbtangenter",
+        "selectBrush": {
+            "desc": "Välj kanvaspensel",
+            "title": "Välj pensel"
+        },
+        "selectEraser": {
+            "desc": "Välj kanvassuddgummi",
+            "title": "Välj suddgummi"
+        },
+        "eraseBoundingBox": {
+            "title": "Ta bort ram"
+        }
+    }
+}

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

@@ -0,0 +1,64 @@
+{
+    "accessibility": {
+        "invokeProgressBar": "Invoke ilerleme durumu",
+        "nextImage": "Sonraki Resim",
+        "useThisParameter": "Kullanıcı parametreleri",
+        "copyMetadataJson": "Metadata verilerini kopyala (JSON)",
+        "exitViewer": "Görüntüleme Modundan Çık",
+        "zoomIn": "Yakınlaştır",
+        "zoomOut": "Uzaklaştır",
+        "rotateCounterClockwise": "Döndür (Saat yönünün tersine)",
+        "rotateClockwise": "Döndür (Saat yönünde)",
+        "flipHorizontally": "Yatay Çevir",
+        "flipVertically": "Dikey Çevir",
+        "modifyConfig": "Ayarları Değiştir",
+        "toggleAutoscroll": "Otomatik kaydırmayı aç/kapat",
+        "toggleLogViewer": "Günlük Görüntüleyici Aç/Kapa",
+        "showOptionsPanel": "Ayarlar Panelini Göster",
+        "modelSelect": "Model Seçin",
+        "reset": "Sıfırla",
+        "uploadImage": "Resim Yükle",
+        "previousImage": "Önceki Resim",
+        "menu": "Menü",
+        "showGallery": "Galeriyi Göster"
+    },
+    "common": {
+        "hotkeysLabel": "Kısayol Tuşları",
+        "themeLabel": "Tema",
+        "languagePickerLabel": "Dil Seçimi",
+        "reportBugLabel": "Hata Bildir",
+        "githubLabel": "Github",
+        "discordLabel": "Discord",
+        "settingsLabel": "Ayarlar",
+        "darkTheme": "Karanlık Tema",
+        "lightTheme": "Aydınlık Tema",
+        "greenTheme": "Yeşil Tema",
+        "oceanTheme": "Okyanus Tema",
+        "langArabic": "Arapça",
+        "langEnglish": "İngilizce",
+        "langDutch": "Hollandaca",
+        "langFrench": "Fransızca",
+        "langGerman": "Almanca",
+        "langItalian": "İtalyanca",
+        "langJapanese": "Japonca",
+        "langPolish": "Lehçe",
+        "langPortuguese": "Portekizce",
+        "langBrPortuguese": "Portekizcr (Brezilya)",
+        "langRussian": "Rusça",
+        "langSimplifiedChinese": "Çince (Basit)",
+        "langUkranian": "Ukraynaca",
+        "langSpanish": "İspanyolca",
+        "txt2img": "Metinden Resime",
+        "img2img": "Resimden Metine",
+        "linear": "Çizgisel",
+        "nodes": "Düğümler",
+        "postprocessing": "İşlem Sonrası",
+        "postProcessing": "İşlem Sonrası",
+        "postProcessDesc2": "Daha gelişmiş özellikler için ve iş akışını kolaylaştırmak için özel bir kullanıcı arayüzü çok yakında yayınlanacaktır.",
+        "postProcessDesc3": "Invoke AI komut satırı arayüzü, bir çok yeni özellik sunmaktadır.",
+        "langKorean": "Korece",
+        "unifiedCanvas": "Akıllı Tuval",
+        "nodesDesc": "Görüntülerin oluşturulmasında hazırladığımız yeni bir sistem geliştirme aşamasındadır. Bu harika özellikler ve çok daha fazlası için bizi takip etmeye devam edin.",
+        "postProcessDesc1": "Invoke AI son kullanıcıya yönelik bir çok özellik sunar. Görüntü kalitesi yükseltme, yüz restorasyonu WebUI üzerinden kullanılabilir. Metinden resime ve resimden metne araçlarına gelişmiş seçenekler menüsünden ulaşabilirsiniz. İsterseniz mevcut görüntü ekranının üzerindeki veya görüntüleyicideki görüntüyü doğrudan düzenleyebilirsiniz."
+    }
+}

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

@@ -16,9 +16,9 @@
         "postProcessing": "Постобробка",
         "postProcessDesc1": "Invoke AI пропонує широкий спектр функцій постобробки. Збільшення зображення (upscale) та відновлення облич вже доступні в інтерфейсі. Отримайте доступ до них з меню 'Додаткові параметри' на вкладках 'Зображення із тексту' та 'Зображення із зображення'. Обробляйте зображення безпосередньо, використовуючи кнопки дій із зображеннями над поточним зображенням або в режимі перегляду.",
         "postProcessDesc2": "Найближчим часом буде випущено спеціальний інтерфейс для більш сучасних процесів постобробки.",
-        "postProcessDesc3": "Інтерфейс командного рядка Invoke AI пропонує різні інші функції, включаючи збільшення Embiggen",
+        "postProcessDesc3": "Інтерфейс командного рядка Invoke AI пропонує різні інші функції, включаючи збільшення Embiggen.",
         "training": "Навчання",
-        "trainingDesc1": "Спеціальний інтерфейс для навчання власних моделей з використанням Textual Inversion та Dreambooth",
+        "trainingDesc1": "Спеціальний інтерфейс для навчання власних моделей з використанням Textual Inversion та Dreambooth.",
         "trainingDesc2": "InvokeAI вже підтримує навчання моделей за допомогою TI, через інтерфейс командного рядка.",
         "upload": "Завантажити",
         "close": "Закрити",
@@ -43,7 +43,38 @@
         "statusUpscaling": "Збільшення",
         "statusUpscalingESRGAN": "Збільшення (ESRGAN)",
         "statusLoadingModel": "Завантаження моделі",
-        "statusModelChanged": "Модель змінено"
+        "statusModelChanged": "Модель змінено",
+        "cancel": "Скасувати",
+        "accept": "Підтвердити",
+        "back": "Назад",
+        "postprocessing": "Постобробка",
+        "statusModelConverted": "Модель сконвертована",
+        "statusMergingModels": "Злиття моделей",
+        "loading": "Завантаження",
+        "loadingInvokeAI": "Завантаження Invoke AI",
+        "langHebrew": "Іврит",
+        "langKorean": "Корейська",
+        "langPortuguese": "Португальська",
+        "pinOptionsPanel": "Закріпити панель налаштувань",
+        "oceanTheme": "Океан",
+        "langArabic": "Арабська",
+        "langSimplifiedChinese": "Китайська (спрощена)",
+        "langSpanish": "Іспанська",
+        "langEnglish": "Англійська",
+        "langGerman": "Німецька",
+        "langItalian": "Італійська",
+        "langJapanese": "Японська",
+        "langPolish": "Польська",
+        "langBrPortuguese": "Португальська (Бразилія)",
+        "langRussian": "Російська",
+        "githubLabel": "Github",
+        "txt2img": "Текст в зображення (txt2img)",
+        "discordLabel": "Discord",
+        "langDutch": "Голландська",
+        "langFrench": "Французька",
+        "statusMergedModels": "Моделі об'єднані",
+        "statusConvertingModel": "Конвертація моделі",
+        "linear": "Лінійна обробка"
     },
     "gallery": {
         "generations": "Генерації",
@@ -284,15 +315,15 @@
         "description": "Опис",
         "descriptionValidationMsg": "Введіть опис моделі",
         "config": "Файл конфігурації",
-        "configValidationMsg": "Шлях до файлу конфігурації",
+        "configValidationMsg": "Шлях до файлу конфігурації.",
         "modelLocation": "Розташування моделі",
-        "modelLocationValidationMsg": "Шлях до файлу з моделлю",
+        "modelLocationValidationMsg": "Шлях до файлу з моделлю.",
         "vaeLocation": "Розтышування VAE",
-        "vaeLocationValidationMsg": "Шлях до VAE",
+        "vaeLocationValidationMsg": "Шлях до VAE.",
         "width": "Ширина",
-        "widthValidationMsg": "Початкова ширина зображень",
+        "widthValidationMsg": "Початкова ширина зображень.",
         "height": "Висота",
-        "heightValidationMsg": "Початкова висота зображень",
+        "heightValidationMsg": "Початкова висота зображень.",
         "addModel": "Додати модель",
         "updateModel": "Оновити модель",
         "availableModels": "Доступні моделі",
@@ -319,7 +350,66 @@
         "deleteModel": "Видалити модель",
         "deleteConfig": "Видалити конфігурацію",
         "deleteMsg1": "Ви точно хочете видалити модель із InvokeAI?",
-        "deleteMsg2": "Це не призведе до видалення файлу моделі з диску. Позніше ви можете додати його знову."
+        "deleteMsg2": "Це не призведе до видалення файлу моделі з диску. Позніше ви можете додати його знову.",
+        "allModels": "Усі моделі",
+        "diffusersModels": "Diffusers",
+        "scanForModels": "Сканувати моделі",
+        "convert": "Конвертувати",
+        "convertToDiffusers": "Конвертувати в Diffusers",
+        "formMessageDiffusersVAELocationDesc": "Якщо не надано, InvokeAI буде шукати файл VAE в розташуванні моделі, вказаній вище.",
+        "convertToDiffusersHelpText3": "Файл моделі на диску НЕ буде видалено або змінено. Ви можете знову додати його в Model Manager, якщо потрібно.",
+        "customConfig": "Користувальницький конфіг",
+        "invokeRoot": "Каталог InvokeAI",
+        "custom": "Користувальницький",
+        "modelTwo": "Модель 2",
+        "modelThree": "Модель 3",
+        "mergedModelName": "Назва об'єднаної моделі",
+        "alpha": "Альфа",
+        "interpolationType": "Тип інтерполяції",
+        "mergedModelSaveLocation": "Шлях збереження",
+        "mergedModelCustomSaveLocation": "Користувальницький шлях",
+        "invokeAIFolder": "Каталог InvokeAI",
+        "ignoreMismatch": "Ігнорувати невідповідності між вибраними моделями",
+        "modelMergeHeaderHelp2": "Тільки Diffusers-моделі доступні для об'єднання. Якщо ви хочете об'єднати checkpoint-моделі, спочатку перетворіть їх на Diffusers.",
+        "checkpointModels": "Checkpoints",
+        "repo_id": "ID репозиторію",
+        "v2_base": "v2 (512px)",
+        "repoIDValidationMsg": "Онлайн-репозиторій моделі",
+        "formMessageDiffusersModelLocationDesc": "Вкажіть хоча б одне.",
+        "formMessageDiffusersModelLocation": "Шлях до Diffusers-моделі",
+        "v2_768": "v2 (768px)",
+        "formMessageDiffusersVAELocation": "Шлях до VAE",
+        "convertToDiffusersHelpText5": "Переконайтеся, що у вас достатньо місця на диску. Моделі зазвичай займають від 4 до 7 Гб.",
+        "convertToDiffusersSaveLocation": "Шлях збереження",
+        "v1": "v1",
+        "convertToDiffusersHelpText6": "Ви хочете перетворити цю модель?",
+        "inpainting": "v1 Inpainting",
+        "modelConverted": "Модель перетворено",
+        "sameFolder": "У ту ж папку",
+        "statusConverting": "Перетворення",
+        "merge": "Об'єднати",
+        "mergeModels": "Об'єднати моделі",
+        "modelOne": "Модель 1",
+        "sigmoid": "Сігмоїд",
+        "weightedSum": "Зважена сума",
+        "none": "пусто",
+        "addDifference": "Додати різницю",
+        "pickModelType": "Вибрати тип моделі",
+        "convertToDiffusersHelpText4": "Це одноразова дія. Вона може зайняти від 30 до 60 секунд в залежності від характеристик вашого комп'ютера.",
+        "pathToCustomConfig": "Шлях до конфігу користувача",
+        "safetensorModels": "SafeTensors",
+        "addCheckpointModel": "Додати модель Checkpoint/Safetensor",
+        "addDiffuserModel": "Додати Diffusers",
+        "vaeRepoID": "ID репозиторію VAE",
+        "vaeRepoIDValidationMsg": "Онлайн-репозиторій VAE",
+        "modelMergeInterpAddDifferenceHelp": "У цьому режимі Модель 3 спочатку віднімається з Моделі 2. Результуюча версія змішується з Моделью 1 із встановленим вище коефіцієнтом Альфа.",
+        "customSaveLocation": "Користувальницький шлях збереження",
+        "modelMergeAlphaHelp": "Альфа впливає силу змішування моделей. Нижчі значення альфа призводять до меншого впливу другої моделі.",
+        "convertToDiffusersHelpText1": "Ця модель буде конвертована в формат 🧨 Diffusers.",
+        "convertToDiffusersHelpText2": "Цей процес замінить ваш запис в Model Manager на версію тієї ж моделі в Diffusers.",
+        "modelsMerged": "Моделі об'єднані",
+        "modelMergeHeaderHelp1": "Ви можете об'єднати до трьох різних моделей, щоб створити змішану, що відповідає вашим потребам.",
+        "inverseSigmoid": "Зворотній Сігмоїд"
     },
     "parameters": {
         "images": "Зображення",
@@ -346,7 +436,7 @@
         "scale": "Масштаб",
         "otherOptions": "інші параметри",
         "seamlessTiling": "Безшовний узор",
-        "hiresOptim": "Висока роздільна здатність",
+        "hiresOptim": "Оптимізація High Res",
         "imageFit": "Вмістити зображення",
         "codeformerFidelity": "Точність",
         "seamSize": "Размір шву",
@@ -379,7 +469,24 @@
         "info": "Метадані",
         "deleteImage": "Видалити зображення",
         "initialImage": "Початкове зображення",
-        "showOptionsPanel": "Показати панель налаштувань"
+        "showOptionsPanel": "Показати панель налаштувань",
+        "general": "Основне",
+        "cancel": {
+            "immediate": "Скасувати негайно",
+            "schedule": "Скасувати після поточної ітерації",
+            "isScheduled": "Відміна",
+            "setType": "Встановити тип скасування"
+        },
+        "vSymmetryStep": "Крок верт. симетрії",
+        "hiresStrength": "Сила High Res",
+        "hidePreview": "Сховати попередній перегляд",
+        "showPreview": "Показати попередній перегляд",
+        "imageToImage": "Зображення до зображення",
+        "denoisingStrength": "Сила шумоподавлення",
+        "copyImage": "Копіювати зображення",
+        "symmetry": "Симетрія",
+        "hSymmetryStep": "Крок гор. симетрії",
+        "negativePrompts": "Виключний запит"
     },
     "settings": {
         "models": "Моделі",
@@ -392,7 +499,8 @@
         "resetWebUI": "Повернути початкові",
         "resetWebUIDesc1": "Скидання настройок веб-інтерфейсу видаляє лише локальний кеш браузера з вашими зображеннями та налаштуваннями. Це не призводить до видалення зображень з диску.",
         "resetWebUIDesc2": "Якщо зображення не відображаються в галереї або не працює ще щось, спробуйте скинути налаштування, перш ніж повідомляти про проблему на GitHub.",
-        "resetComplete": "Інтерфейс скинуто. Оновіть цю сторінку."
+        "resetComplete": "Інтерфейс скинуто. Оновіть цю сторінку.",
+        "useSlidersForAll": "Використовувати повзунки для всіх параметрів"
     },
     "toast": {
         "tempFoldersEmptied": "Тимчасова папка очищена",
@@ -410,21 +518,25 @@
         "sentToUnifiedCanvas": "Надіслати на полотно",
         "parametersSet": "Параметри задані",
         "parametersNotSet": "Параметри не задані",
-        "parametersNotSetDesc": "Не знайдені метадані цього зображення",
+        "parametersNotSetDesc": "Не знайдені метадані цього зображення.",
         "parametersFailed": "Проблема із завантаженням параметрів",
-        "parametersFailedDesc": "Неможливо завантажити початкове зображення",
+        "parametersFailedDesc": "Неможливо завантажити початкове зображення.",
         "seedSet": "Сід заданий",
         "seedNotSet": "Сід не заданий",
-        "seedNotSetDesc": "Не вдалося знайти сід для зображення",
+        "seedNotSetDesc": "Не вдалося знайти сід для зображення.",
         "promptSet": "Запит заданий",
         "promptNotSet": "Запит не заданий",
-        "promptNotSetDesc": "Не вдалося знайти запит для зображення",
+        "promptNotSetDesc": "Не вдалося знайти запит для зображення.",
         "upscalingFailed": "Збільшення не вдалося",
         "faceRestoreFailed": "Відновлення облич не вдалося",
         "metadataLoadFailed": "Не вдалося завантажити метадані",
         "initialImageSet": "Початкове зображення задане",
         "initialImageNotSet": "Початкове зображення не задане",
-        "initialImageNotSetDesc": "Не вдалося завантажити початкове зображення"
+        "initialImageNotSetDesc": "Не вдалося завантажити початкове зображення",
+        "serverError": "Помилка сервера",
+        "disconnected": "Відключено від сервера",
+        "connected": "Підключено до сервера",
+        "canceled": "Обробку скасовано"
     },
     "tooltip": {
         "feature": {
@@ -473,10 +585,10 @@
         "autoSaveToGallery": "Автозбереження до галереї",
         "saveBoxRegionOnly": "Зберiгати тiльки видiлення",
         "limitStrokesToBox": "Обмежити штрихи виділенням",
-        "showCanvasDebugInfo": "Показати налаштування полотна",
+        "showCanvasDebugInfo": "Показати дод. інформацію про полотно",
         "clearCanvasHistory": "Очистити iсторiю полотна",
         "clearHistory": "Очистити iсторiю",
-        "clearCanvasHistoryMessage": "Очищення історії полотна залишає поточне полотно незайманим, але видаляє історію скасування та повтору",
+        "clearCanvasHistoryMessage": "Очищення історії полотна залишає поточне полотно незайманим, але видаляє історію скасування та повтору.",
         "clearCanvasHistoryConfirm": "Ви впевнені, що хочете очистити історію полотна?",
         "emptyTempImageFolder": "Очистити тимчасову папку",
         "emptyFolder": "Очистити папку",
@@ -499,5 +611,28 @@
         "betaDarkenOutside": "Затемнити зовні",
         "betaLimitToBox": "Обмежити виділенням",
         "betaPreserveMasked": "Зберiгати замасковану область"
+    },
+    "accessibility": {
+        "nextImage": "Наступне зображення",
+        "modelSelect": "Вибір моделі",
+        "invokeProgressBar": "Індикатор виконання",
+        "reset": "Скинути",
+        "uploadImage": "Завантажити зображення",
+        "useThisParameter": "Використовувати цей параметр",
+        "exitViewer": "Вийти з переглядача",
+        "zoomIn": "Збільшити",
+        "zoomOut": "Зменшити",
+        "rotateCounterClockwise": "Обертати проти годинникової стрілки",
+        "rotateClockwise": "Обертати за годинниковою стрілкою",
+        "toggleAutoscroll": "Увімкнути автопрокручування",
+        "toggleLogViewer": "Показати або приховати переглядач журналів",
+        "showGallery": "Показати галерею",
+        "previousImage": "Попереднє зображення",
+        "copyMetadataJson": "Скопіювати метадані JSON",
+        "flipVertically": "Перевернути по вертикалі",
+        "flipHorizontally": "Відобразити по горизонталі",
+        "showOptionsPanel": "Показати опції",
+        "modifyConfig": "Змінити конфігурацію",
+        "menu": "Меню"
     }
 }

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

@@ -0,0 +1 @@
+{}

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

@@ -481,5 +481,22 @@
         "betaDarkenOutside": "暗化外部区域",
         "betaLimitToBox": "限制在框内",
         "betaPreserveMasked": "保留遮罩层"
+    },
+    "accessibility": {
+        "modelSelect": "模型选择",
+        "invokeProgressBar": "Invoke 进度条",
+        "reset": "重置",
+        "nextImage": "下一张图片",
+        "useThisParameter": "使用此参数",
+        "uploadImage": "上传图片",
+        "previousImage": "上一张图片",
+        "copyMetadataJson": "复制JSON元数据",
+        "exitViewer": "退出视口（ExitViewer）",
+        "zoomIn": "放大",
+        "zoomOut": "缩小",
+        "rotateCounterClockwise": "逆时针旋转",
+        "rotateClockwise": "顺时针旋转",
+        "flipHorizontally": "水平翻转",
+        "flipVertically": "垂直翻转"
     }
 }

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

@@ -13,16 +13,48 @@ import { Box, Flex, Grid, Portal, useColorMode } from '@chakra-ui/react';
 import { APP_HEIGHT, APP_WIDTH } from 'theme/util/constants';
 import ImageGalleryPanel from 'features/gallery/components/ImageGalleryPanel';
 import Lightbox from 'features/lightbox/components/Lightbox';
-import { useAppSelector } from './storeHooks';
+import { useAppDispatch, useAppSelector } from './storeHooks';
 import { PropsWithChildren, useEffect } from 'react';
+import { setDisabledPanels, setDisabledTabs } from 'features/ui/store/uiSlice';
+import { InvokeTabName } from 'features/ui/store/tabMap';
+import { shouldTransformUrlsChanged } from 'features/system/store/systemSlice';
+import { setShouldFetchImages } from 'features/gallery/store/resultsSlice';
 
 keepGUIAlive();
 
-const App = (props: PropsWithChildren) => {
+interface Props extends PropsWithChildren {
+  options: {
+    disabledPanels: string[];
+    disabledTabs: InvokeTabName[];
+    shouldTransformUrls?: boolean;
+    shouldFetchImages: boolean;
+  };
+}
+
+const App = (props: Props) => {
   useToastWatcher();
 
   const currentTheme = useAppSelector((state) => state.ui.currentTheme);
   const { setColorMode } = useColorMode();
+  const dispatch = useAppDispatch();
+
+  useEffect(() => {
+    dispatch(setDisabledPanels(props.options.disabledPanels));
+  }, [dispatch, props.options.disabledPanels]);
+
+  useEffect(() => {
+    dispatch(setDisabledTabs(props.options.disabledTabs));
+  }, [dispatch, props.options.disabledTabs]);
+
+  useEffect(() => {
+    dispatch(
+      shouldTransformUrlsChanged(Boolean(props.options.shouldTransformUrls))
+    );
+  }, [dispatch, props.options.shouldTransformUrls]);
+
+  useEffect(() => {
+    dispatch(setShouldFetchImages(props.options.shouldFetchImages));
+  }, [dispatch, props.options.shouldFetchImages]);
 
   useEffect(() => {
     setColorMode(['light'].includes(currentTheme) ? 'light' : 'dark');
@@ -41,7 +73,12 @@ const App = (props: PropsWithChildren) => {
           h={APP_HEIGHT}
         >
           {props.children || <SiteHeader />}
-          <Flex gap={4} w="full" h="full">
+          <Flex
+            gap={4}
+            w={{ base: '100vw', xl: 'full' }}
+            h="full"
+            flexDir={{ base: 'column', xl: 'row' }}
+          >
             <InvokeTabs />
             <ImageGalleryPanel />
           </Flex>

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

@@ -31,13 +31,13 @@ export const DIFFUSERS_SAMPLERS: Array<string> = [
 ];
 
 // Valid image widths
-export const WIDTHS: Array<number> = Array.from(Array(65)).map(
-  (_x, i) => i * 64
+export const WIDTHS: Array<number> = Array.from(Array(64)).map(
+  (_x, i) => (i + 1) * 64
 );
 
 // Valid image heights
-export const HEIGHTS: Array<number> = Array.from(Array(65)).map(
-  (_x, i) => i * 64
+export const HEIGHTS: Array<number> = Array.from(Array(64)).map(
+  (_x, i) => (i + 1) * 64
 );
 
 // Valid upscaling levels
@@ -60,3 +60,5 @@ export const IN_PROGRESS_IMAGE_TYPES: Array<{
   { key: 'Fast', value: 'latents' },
   { key: 'Accurate', value: 'full-res' },
 ];
+
+export const NODE_MIN_WIDTH = 250;

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

@@ -14,6 +14,8 @@
 
 import { InvokeTabName } from 'features/ui/store/tabMap';
 import { IRect } from 'konva/lib/types';
+import { ImageMetadata, ImageType } from 'services/api';
+import { AnyInvocation } from 'services/events/types';
 
 /**
  * TODO:
@@ -113,7 +115,7 @@ export declare type Metadata = SystemGenerationMetadata & {
 };
 
 // An Image has a UUID, url, modified timestamp, width, height and maybe metadata
-export declare type Image = {
+export declare type _Image = {
   uuid: string;
   url: string;
   thumbnail: string;
@@ -124,11 +126,23 @@ export declare type Image = {
   category: GalleryCategory;
   isBase64?: boolean;
   dreamPrompt?: 'string';
+  name?: string;
+};
+
+/**
+ * ResultImage
+ */
+export declare type Image = {
+  name: string;
+  type: ImageType;
+  url: string;
+  thumbnail: string;
+  metadata: ImageMetadata;
 };
 
 // GalleryImages is an array of Image.
 export declare type GalleryImages = {
-  images: Array<Image>;
+  images: Array<_Image>;
 };
 
 /**
@@ -275,7 +289,7 @@ export declare type SystemStatusResponse = SystemStatus;
 
 export declare type SystemConfigResponse = SystemConfig;
 
-export declare type ImageResultResponse = Omit<Image, 'uuid'> & {
+export declare type ImageResultResponse = Omit<_Image, 'uuid'> & {
   boundingBox?: IRect;
   generationMode: InvokeTabName;
 };
@@ -296,7 +310,7 @@ export declare type ErrorResponse = {
 };
 
 export declare type GalleryImagesResponse = {
-  images: Array<Omit<Image, 'uuid'>>;
+  images: Array<Omit<_Image, 'uuid'>>;
   areMoreImagesAvailable: boolean;
   category: GalleryCategory;
 };

invokeai/frontend/web/src/app/selectors/readinessSelector.ts

@@ -20,6 +20,7 @@ export const readinessSelector = createSelector(
       seedWeights,
       initialImage,
       seed,
+      isImageToImageEnabled,
     } = generation;
 
     const { isProcessing, isConnected } = system;
@@ -33,7 +34,7 @@ export const readinessSelector = createSelector(
       reasonsWhyNotReady.push('Missing prompt');
     }
 
-    if (activeTabName === 'img2img' && !initialImage) {
+    if (isImageToImageEnabled && !initialImage) {
       isReady = false;
       reasonsWhyNotReady.push('No initial image selected');
     }

invokeai/frontend/web/src/app/socketio/actions.ts

@@ -13,9 +13,13 @@ import { InvokeTabName } from 'features/ui/store/tabMap';
 export const generateImage = createAction<InvokeTabName>(
   'socketio/generateImage'
 );
-export const runESRGAN = createAction<InvokeAI.Image>('socketio/runESRGAN');
-export const runFacetool = createAction<InvokeAI.Image>('socketio/runFacetool');
-export const deleteImage = createAction<InvokeAI.Image>('socketio/deleteImage');
+export const runESRGAN = createAction<InvokeAI._Image>('socketio/runESRGAN');
+export const runFacetool = createAction<InvokeAI._Image>(
+  'socketio/runFacetool'
+);
+export const deleteImage = createAction<InvokeAI._Image>(
+  'socketio/deleteImage'
+);
 export const requestImages = createAction<GalleryCategory>(
   'socketio/requestImages'
 );

invokeai/frontend/web/src/app/socketio/emitters.ts

@@ -91,7 +91,7 @@ const makeSocketIOEmitters = (
         })
       );
     },
-    emitRunESRGAN: (imageToProcess: InvokeAI.Image) => {
+    emitRunESRGAN: (imageToProcess: InvokeAI._Image) => {
       dispatch(setIsProcessing(true));
 
       const {
@@ -119,7 +119,7 @@ const makeSocketIOEmitters = (
         })
       );
     },
-    emitRunFacetool: (imageToProcess: InvokeAI.Image) => {
+    emitRunFacetool: (imageToProcess: InvokeAI._Image) => {
       dispatch(setIsProcessing(true));
 
       const {
@@ -150,7 +150,7 @@ const makeSocketIOEmitters = (
         })
       );
     },
-    emitDeleteImage: (imageToDelete: InvokeAI.Image) => {
+    emitDeleteImage: (imageToDelete: InvokeAI._Image) => {
       const { url, uuid, category, thumbnail } = imageToDelete;
       dispatch(removeImage(imageToDelete));
       socketio.emit('deleteImage', url, thumbnail, uuid, category);

invokeai/frontend/web/src/app/socketio/listeners.ts

@@ -34,8 +34,9 @@ import type { RootState } from 'app/store';
 import { addImageToStagingArea } from 'features/canvas/store/canvasSlice';
 import {
   clearInitialImage,
+  initialImageSelected,
   setInfillMethod,
-  setInitialImage,
+  // setInitialImage,
   setMaskPath,
 } from 'features/parameters/store/generationSlice';
 import { tabMap } from 'features/ui/store/tabMap';
@@ -142,15 +143,17 @@ const makeSocketIOListeners = (
           }
         }
 
-        if (shouldLoopback) {
-          const activeTabName = tabMap[activeTab];
-          switch (activeTabName) {
-            case 'img2img': {
-              dispatch(setInitialImage(newImage));
-              break;
-            }
-          }
-        }
+        // TODO: fix
+        // if (shouldLoopback) {
+        //   const activeTabName = tabMap[activeTab];
+        //   switch (activeTabName) {
+        //     case 'img2img': {
+        //       dispatch(initialImageSelected(newImage.uuid));
+        //       // dispatch(setInitialImage(newImage));
+        //       break;
+        //     }
+        //   }
+        // }
 
         dispatch(clearIntermediateImage());
 
@@ -262,7 +265,7 @@ const makeSocketIOListeners = (
        */
 
       // Generate a UUID for each image
-      const preparedImages = images.map((image): InvokeAI.Image => {
+      const preparedImages = images.map((image): InvokeAI._Image => {
         return {
           uuid: uuidv4(),
           ...image,
@@ -334,7 +337,7 @@ const makeSocketIOListeners = (
 
       if (
         initialImage === url ||
-        (initialImage as InvokeAI.Image)?.url === url
+        (initialImage as InvokeAI._Image)?.url === url
       ) {
         dispatch(clearInitialImage());
       }

invokeai/frontend/web/src/app/socketio/middleware.ts

@@ -29,6 +29,8 @@ export const socketioMiddleware = () => {
     path: `${window.location.pathname}socket.io`,
   });
 
+  socketio.disconnect();
+
   let areListenersSet = false;
 
   const middleware: Middleware = (store) => (next) => (action) => {

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

@@ -2,18 +2,32 @@ import { combineReducers, configureStore } from '@reduxjs/toolkit';
 
 import { persistReducer } from 'redux-persist';
 import storage from 'redux-persist/lib/storage'; // defaults to localStorage for web
-
+import dynamicMiddlewares from 'redux-dynamic-middlewares';
 import { getPersistConfig } from 'redux-deep-persist';
 
 import canvasReducer from 'features/canvas/store/canvasSlice';
 import galleryReducer from 'features/gallery/store/gallerySlice';
+import resultsReducer from 'features/gallery/store/resultsSlice';
+import uploadsReducer from 'features/gallery/store/uploadsSlice';
 import lightboxReducer from 'features/lightbox/store/lightboxSlice';
 import generationReducer from 'features/parameters/store/generationSlice';
 import postprocessingReducer from 'features/parameters/store/postprocessingSlice';
 import systemReducer from 'features/system/store/systemSlice';
 import uiReducer from 'features/ui/store/uiSlice';
+import modelsReducer from 'features/system/store/modelSlice';
+import nodesReducer from 'features/nodes/store/nodesSlice';
 
 import { socketioMiddleware } from './socketio/middleware';
+import { socketMiddleware } from 'services/events/middleware';
+import { canvasBlacklist } from 'features/canvas/store/canvasPersistBlacklist';
+import { galleryBlacklist } from 'features/gallery/store/galleryPersistBlacklist';
+import { generationBlacklist } from 'features/parameters/store/generationPersistBlacklist';
+import { lightboxBlacklist } from 'features/lightbox/store/lightboxPersistBlacklist';
+import { modelsBlacklist } from 'features/system/store/modelsPersistBlacklist';
+import { nodesBlacklist } from 'features/nodes/store/nodesPersistBlacklist';
+import { postprocessingBlacklist } from 'features/parameters/store/postprocessingPersistBlacklist';
+import { systemBlacklist } from 'features/system/store/systemPersistsBlacklist';
+import { uiBlacklist } from 'features/ui/store/uiPersistBlacklist';
 
 /**
  * redux-persist provides an easy and reliable way to persist state across reloads.
@@ -29,49 +43,18 @@ import { socketioMiddleware } from './socketio/middleware';
  * The necesssary nested persistors with blacklists are configured below.
  */
 
-const canvasBlacklist = [
-  'cursorPosition',
-  'isCanvasInitialized',
-  'doesCanvasNeedScaling',
-].map((blacklistItem) => `canvas.${blacklistItem}`);
-
-const systemBlacklist = [
-  'currentIteration',
-  'currentStatus',
-  'currentStep',
-  'isCancelable',
-  'isConnected',
-  'isESRGANAvailable',
-  'isGFPGANAvailable',
-  'isProcessing',
-  'socketId',
-  'totalIterations',
-  'totalSteps',
-  'openModel',
-  'cancelOptions.cancelAfter',
-].map((blacklistItem) => `system.${blacklistItem}`);
-
-const galleryBlacklist = [
-  'categories',
-  'currentCategory',
-  'currentImage',
-  'currentImageUuid',
-  'shouldAutoSwitchToNewImages',
-  'intermediateImage',
-].map((blacklistItem) => `gallery.${blacklistItem}`);
-
-const lightboxBlacklist = ['isLightboxOpen'].map(
-  (blacklistItem) => `lightbox.${blacklistItem}`
-);
-
 const rootReducer = combineReducers({
-  generation: generationReducer,
-  postprocessing: postprocessingReducer,
-  gallery: galleryReducer,
-  system: systemReducer,
   canvas: canvasReducer,
-  ui: uiReducer,
+  gallery: galleryReducer,
+  generation: generationReducer,
   lightbox: lightboxReducer,
+  models: modelsReducer,
+  nodes: nodesReducer,
+  postprocessing: postprocessingReducer,
+  results: resultsReducer,
+  system: systemReducer,
+  ui: uiReducer,
+  uploads: uploadsReducer,
 });
 
 const rootPersistConfig = getPersistConfig({
@@ -80,23 +63,40 @@ const rootPersistConfig = getPersistConfig({
   rootReducer,
   blacklist: [
     ...canvasBlacklist,
-    ...systemBlacklist,
     ...galleryBlacklist,
+    ...generationBlacklist,
     ...lightboxBlacklist,
+    ...modelsBlacklist,
+    ...nodesBlacklist,
+    ...postprocessingBlacklist,
+    // ...resultsBlacklist,
+    'results',
+    ...systemBlacklist,
+    ...uiBlacklist,
+    // ...uploadsBlacklist,
+    'uploads',
   ],
   debounce: 300,
 });
 
 const persistedReducer = persistReducer(rootPersistConfig, rootReducer);
 
-// Continue with store setup
+// TODO: rip the old middleware out when nodes is complete
+export function buildMiddleware() {
+  if (import.meta.env.MODE === 'nodes' || import.meta.env.MODE === 'package') {
+    return socketMiddleware();
+  } else {
+    return socketioMiddleware();
+  }
+}
+
 export const store = configureStore({
   reducer: persistedReducer,
   middleware: (getDefaultMiddleware) =>
     getDefaultMiddleware({
       immutableCheck: false,
       serializableCheck: false,
-    }).concat(socketioMiddleware()),
+    }).concat(dynamicMiddlewares),
   devTools: {
     // Uncommenting these very rapidly called actions makes the redux dev tools output much more readable
     actionsDenylist: [

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

@@ -0,0 +1,8 @@
+import { createAsyncThunk } from '@reduxjs/toolkit';
+import { AppDispatch, RootState } from './store';
+
+// https://redux-toolkit.js.org/usage/usage-with-typescript#defining-a-pre-typed-createasyncthunk
+export const createAppAsyncThunk = createAsyncThunk.withTypes<{
+  state: RootState;
+  dispatch: AppDispatch;
+}>();

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

@@ -44,12 +44,10 @@ export type IAIFullSliderProps = {
   inputReadOnly?: boolean;
   withReset?: boolean;
   handleReset?: () => void;
-  isResetDisabled?: boolean;
-  isSliderDisabled?: boolean;
-  isInputDisabled?: boolean;
   tooltipSuffix?: string;
   hideTooltip?: boolean;
   isCompact?: boolean;
+  isDisabled?: boolean;
   sliderFormControlProps?: FormControlProps;
   sliderFormLabelProps?: FormLabelProps;
   sliderMarkProps?: Omit<SliderMarkProps, 'value'>;
@@ -80,10 +78,8 @@ const IAISlider = (props: IAIFullSliderProps) => {
     withReset = false,
     hideTooltip = false,
     isCompact = false,
+    isDisabled = false,
     handleReset,
-    isResetDisabled,
-    isSliderDisabled,
-    isInputDisabled,
     sliderFormControlProps,
     sliderFormLabelProps,
     sliderMarkProps,
@@ -149,6 +145,7 @@ const IAISlider = (props: IAIFullSliderProps) => {
             }
           : {}
       }
+      isDisabled={isDisabled}
       {...sliderFormControlProps}
     >
       <FormLabel {...sliderFormLabelProps} mb={-1}>
@@ -166,15 +163,13 @@ const IAISlider = (props: IAIFullSliderProps) => {
           onMouseEnter={() => setShowTooltip(true)}
           onMouseLeave={() => setShowTooltip(false)}
           focusThumbOnChange={false}
-          isDisabled={isSliderDisabled}
-          // width={width}
+          isDisabled={isDisabled}
           {...rest}
         >
           {withSliderMarks && (
             <>
               <SliderMark
                 value={min}
-                // insetInlineStart={0}
                 sx={{
                   insetInlineStart: '0 !important',
                   insetInlineEnd: 'unset !important',
@@ -185,7 +180,6 @@ const IAISlider = (props: IAIFullSliderProps) => {
               </SliderMark>
               <SliderMark
                 value={max}
-                // insetInlineEnd={0}
                 sx={{
                   insetInlineStart: 'unset !important',
                   insetInlineEnd: '0 !important',
@@ -221,7 +215,6 @@ const IAISlider = (props: IAIFullSliderProps) => {
             value={localInputValue}
             onChange={handleInputChange}
             onBlur={handleInputBlur}
-            isDisabled={isInputDisabled}
             {...sliderNumberInputProps}
           >
             <NumberInputField
@@ -246,8 +239,8 @@ const IAISlider = (props: IAIFullSliderProps) => {
             aria-label={t('accessibility.reset')}
             tooltip="Reset"
             icon={<BiReset />}
+            isDisabled={isDisabled}
             onClick={handleResetDisable}
-            isDisabled={isResetDisabled}
             {...sliderIAIIconButtonProps}
           />
         )}

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

@@ -0,0 +1,79 @@
+import { Badge, Box, ButtonGroup, Flex } from '@chakra-ui/react';
+import { RootState } from 'app/store';
+import { useAppDispatch, useAppSelector } from 'app/storeHooks';
+import { clearInitialImage } from 'features/parameters/store/generationSlice';
+import { useCallback } from 'react';
+import IAIIconButton from 'common/components/IAIIconButton';
+import { FaUndo, FaUpload } from 'react-icons/fa';
+import { useTranslation } from 'react-i18next';
+import { Image } from 'app/invokeai';
+
+type ImageToImageOverlayProps = {
+  setIsLoaded: (isLoaded: boolean) => void;
+  image: Image;
+};
+
+const ImageToImageOverlay = ({
+  setIsLoaded,
+  image,
+}: ImageToImageOverlayProps) => {
+  const isImageToImageEnabled = useAppSelector(
+    (state: RootState) => state.generation.isImageToImageEnabled
+  );
+  const dispatch = useAppDispatch();
+  const { t } = useTranslation();
+  const handleResetInitialImage = useCallback(() => {
+    dispatch(clearInitialImage());
+    setIsLoaded(false);
+  }, [dispatch, setIsLoaded]);
+
+  return (
+    <Box
+      sx={{
+        top: 0,
+        left: 0,
+        w: 'full',
+        h: 'full',
+        position: 'absolute',
+      }}
+    >
+      <ButtonGroup
+        sx={{
+          position: 'absolute',
+          top: 0,
+          right: 0,
+          p: 2,
+        }}
+      >
+        <IAIIconButton
+          size="sm"
+          isDisabled={!isImageToImageEnabled}
+          icon={<FaUndo />}
+          aria-label={t('accessibility.reset')}
+          onClick={handleResetInitialImage}
+        />
+        <IAIIconButton
+          size="sm"
+          isDisabled={!isImageToImageEnabled}
+          icon={<FaUpload />}
+          aria-label={t('common.upload')}
+        />
+      </ButtonGroup>
+      <Flex
+        sx={{
+          position: 'absolute',
+          bottom: 0,
+          left: 0,
+          p: 2,
+          alignItems: 'flex-start',
+        }}
+      >
+        <Badge variant="solid" colorScheme="base">
+          {image.metadata?.width} × {image.metadata?.height}
+        </Badge>
+      </Flex>
+    </Box>
+  );
+};
+
+export default ImageToImageOverlay;

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

@@ -2,7 +2,6 @@ import { Box, useToast } from '@chakra-ui/react';
 import { ImageUploaderTriggerContext } from 'app/contexts/ImageUploaderTriggerContext';
 import { useAppDispatch, useAppSelector } from 'app/storeHooks';
 import useImageUploader from 'common/hooks/useImageUploader';
-import { uploadImage } from 'features/gallery/store/thunks/uploadImage';
 import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import { ResourceKey } from 'i18next';
 import {
@@ -15,6 +14,7 @@ import {
 } from 'react';
 import { FileRejection, useDropzone } from 'react-dropzone';
 import { useTranslation } from 'react-i18next';
+import { imageUploaded } from 'services/thunks/image';
 import ImageUploadOverlay from './ImageUploadOverlay';
 
 type ImageUploaderProps = {
@@ -49,7 +49,7 @@ const ImageUploader = (props: ImageUploaderProps) => {
 
   const fileAcceptedCallback = useCallback(
     async (file: File) => {
-      dispatch(uploadImage({ imageFile: file }));
+      dispatch(imageUploaded({ formData: { file } }));
     },
     [dispatch]
   );
@@ -124,7 +124,7 @@ const ImageUploader = (props: ImageUploaderProps) => {
         return;
       }
 
-      dispatch(uploadImage({ imageFile: file }));
+      dispatch(imageUploaded({ formData: { file } }));
     };
     document.addEventListener('paste', pasteImageListener);
     return () => {

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

@@ -0,0 +1,12 @@
+import { Flex, Icon } from '@chakra-ui/react';
+import { FaImage } from 'react-icons/fa';
+
+const SelectImagePlaceholder = () => {
+  return (
+    <Flex sx={{ h: 36, alignItems: 'center', justifyContent: 'center' }}>
+      <Icon color="base.400" boxSize={32} as={FaImage}></Icon>
+    </Flex>
+  );
+};
+
+export default SelectImagePlaceholder;

invokeai/frontend/web/src/common/components/WorkInProgress/NodesWIP.tsx

@@ -1,27 +1,160 @@
-import { Flex, Heading, Text, VStack } from '@chakra-ui/react';
-import { useTranslation } from 'react-i18next';
-import WorkInProgress from './WorkInProgress';
+// import WorkInProgress from './WorkInProgress';
+// import ReactFlow, {
+//   applyEdgeChanges,
+//   applyNodeChanges,
+//   Background,
+//   Controls,
+//   Edge,
+//   Handle,
+//   Node,
+//   NodeTypes,
+//   OnEdgesChange,
+//   OnNodesChange,
+//   Position,
+// } from 'reactflow';
 
-export default function NodesWIP() {
-  const { t } = useTranslation();
-  return (
-    <WorkInProgress>
-      <Flex
-        sx={{
-          flexDirection: 'column',
-          alignItems: 'center',
-          justifyContent: 'center',
-          w: '100%',
-          h: '100%',
-          gap: 4,
-          textAlign: 'center',
-        }}
-      >
-        <Heading>{t('common.nodes')}</Heading>
-        <VStack maxW="50rem" gap={4}>
-          <Text>{t('common.nodesDesc')}</Text>
-        </VStack>
-      </Flex>
-    </WorkInProgress>
-  );
-}
+// import 'reactflow/dist/style.css';
+// import {
+//   Fragment,
+//   FunctionComponent,
+//   ReactNode,
+//   useCallback,
+//   useMemo,
+//   useState,
+// } from 'react';
+// import { OpenAPIV3 } from 'openapi-types';
+// import { filter, map, reduce } from 'lodash';
+// import {
+//   Box,
+//   Flex,
+//   FormControl,
+//   FormLabel,
+//   Input,
+//   Select,
+//   Switch,
+//   Text,
+//   NumberInput,
+//   NumberInputField,
+//   NumberInputStepper,
+//   NumberIncrementStepper,
+//   NumberDecrementStepper,
+//   Tooltip,
+//   chakra,
+//   Badge,
+//   Heading,
+//   VStack,
+//   HStack,
+//   Menu,
+//   MenuButton,
+//   MenuList,
+//   MenuItem,
+//   MenuItemOption,
+//   MenuGroup,
+//   MenuOptionGroup,
+//   MenuDivider,
+//   IconButton,
+// } from '@chakra-ui/react';
+// import { FaPlus } from 'react-icons/fa';
+// import {
+//   FIELD_NAMES as FIELD_NAMES,
+//   FIELDS,
+//   INVOCATION_NAMES as INVOCATION_NAMES,
+//   INVOCATIONS,
+// } from 'features/nodeEditor/constants';
+
+// console.log('invocations', INVOCATIONS);
+
+// const nodeTypes = reduce(
+//   INVOCATIONS,
+//   (acc, val, key) => {
+//     acc[key] = val.component;
+//     return acc;
+//   },
+//   {} as NodeTypes
+// );
+
+// console.log('nodeTypes', nodeTypes);
+
+// // make initial nodes one of every node for now
+// let n = 0;
+// const initialNodes = map(INVOCATIONS, (i) => ({
+//   id: i.type,
+//   type: i.title,
+//   position: { x: (n += 20), y: (n += 20) },
+//   data: {},
+// }));
+
+// console.log('initialNodes', initialNodes);
+
+// export default function NodesWIP() {
+//   const [nodes, setNodes] = useState<Node[]>([]);
+//   const [edges, setEdges] = useState<Edge[]>([]);
+
+//   const onNodesChange: OnNodesChange = useCallback(
+//     (changes) => setNodes((nds) => applyNodeChanges(changes, nds)),
+//     []
+//   );
+
+//   const onEdgesChange: OnEdgesChange = useCallback(
+//     (changes) => setEdges((eds: Edge[]) => applyEdgeChanges(changes, eds)),
+//     []
+//   );
+
+//   return (
+//     <Box
+//       sx={{
+//         position: 'relative',
+//         width: 'full',
+//         height: 'full',
+//         borderRadius: 'md',
+//       }}
+//     >
+//       <ReactFlow
+//         nodeTypes={nodeTypes}
+//         nodes={nodes}
+//         edges={edges}
+//         onNodesChange={onNodesChange}
+//         onEdgesChange={onEdgesChange}
+//       >
+//         <Background />
+//         <Controls />
+//       </ReactFlow>
+//       <HStack sx={{ position: 'absolute', top: 2, right: 2 }}>
+//         {FIELD_NAMES.map((field) => (
+//           <Badge
+//             key={field}
+//             colorScheme={FIELDS[field].color}
+//             sx={{ userSelect: 'none' }}
+//           >
+//             {field}
+//           </Badge>
+//         ))}
+//       </HStack>
+//       <Menu>
+//         <MenuButton
+//           as={IconButton}
+//           aria-label="Options"
+//           icon={<FaPlus />}
+//           sx={{ position: 'absolute', top: 2, left: 2 }}
+//         />
+//         <MenuList>
+//           {INVOCATION_NAMES.map((name) => {
+//             const invocation = INVOCATIONS[name];
+//             return (
+//               <Tooltip
+//                 key={name}
+//                 label={invocation.description}
+//                 placement="end"
+//                 hasArrow
+//               >
+//                 <MenuItem>{invocation.title}</MenuItem>
+//               </Tooltip>
+//             );
+//           })}
+//         </MenuList>
+//       </Menu>
+//     </Box>
+//   );
+// }
+
+export default {};

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

@@ -14,6 +14,8 @@ const WorkInProgress = (props: WorkInProgressProps) => {
         width: '100%',
         height: '100%',
         bg: 'base.850',
+        borderRadius: 'base',
+        position: 'relative',
       }}
     >
       {children}

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

@@ -0,0 +1,18 @@
+import { useBreakpoint } from '@chakra-ui/react';
+
+export default function useResolution():
+  | 'mobile'
+  | 'tablet'
+  | 'desktop'
+  | 'unknown' {
+  const breakpointValue = useBreakpoint();
+
+  const mobileResolutions = ['base', 'sm'];
+  const tabletResolutions = ['md', 'lg'];
+  const desktopResolutions = ['xl', '2xl'];
+
+  if (mobileResolutions.includes(breakpointValue)) return 'mobile';
+  if (tabletResolutions.includes(breakpointValue)) return 'tablet';
+  if (desktopResolutions.includes(breakpointValue)) return 'desktop';
+  return 'unknown';
+}

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

@@ -0,0 +1,119 @@
+/**
+ * PARTIAL ZOD IMPLEMENTATION
+ *
+ * doesn't work well bc like most validators, zod is not built to skip invalid values.
+ * it mostly works but just seems clearer and simpler to manually parse for now.
+ *
+ * in the future it would be really nice if we could use zod for some things:
+ * - zodios (axios + zod): https://github.com/ecyrbe/zodios
+ * - openapi to zodios: https://github.com/astahmer/openapi-zod-client
+ */
+
+// import { z } from 'zod';
+
+// const zMetadataStringField = z.string();
+// export type MetadataStringField = z.infer<typeof zMetadataStringField>;
+
+// const zMetadataIntegerField = z.number().int();
+// export type MetadataIntegerField = z.infer<typeof zMetadataIntegerField>;
+
+// const zMetadataFloatField = z.number();
+// export type MetadataFloatField = z.infer<typeof zMetadataFloatField>;
+
+// const zMetadataBooleanField = z.boolean();
+// export type MetadataBooleanField = z.infer<typeof zMetadataBooleanField>;
+
+// const zMetadataImageField = z.object({
+//   image_type: z.union([
+//     z.literal('results'),
+//     z.literal('uploads'),
+//     z.literal('intermediates'),
+//   ]),
+//   image_name: z.string().min(1),
+// });
+// export type MetadataImageField = z.infer<typeof zMetadataImageField>;
+
+// const zMetadataLatentsField = z.object({
+//   latents_name: z.string().min(1),
+// });
+// export type MetadataLatentsField = z.infer<typeof zMetadataLatentsField>;
+
+// /**
+//  * zod Schema for any node field. Use a `transform()` to manually parse, skipping invalid values.
+//  */
+// const zAnyMetadataField = z.any().transform((val, ctx) => {
+//   // Grab the field name from the path
+//   const fieldName = String(ctx.path[ctx.path.length - 1]);
+
+//   // `id` and `type` must be strings if they exist
+//   if (['id', 'type'].includes(fieldName)) {
+//     const reservedStringPropertyResult = zMetadataStringField.safeParse(val);
+//     if (reservedStringPropertyResult.success) {
+//       return reservedStringPropertyResult.data;
+//     }
+
+//     return;
+//   }
+
+//   // Parse the rest of the fields, only returning the data if the parsing is successful
+
+//   const stringFieldResult = zMetadataStringField.safeParse(val);
+//   if (stringFieldResult.success) {
+//     return stringFieldResult.data;
+//   }
+
+//   const integerFieldResult = zMetadataIntegerField.safeParse(val);
+//   if (integerFieldResult.success) {
+//     return integerFieldResult.data;
+//   }
+
+//   const floatFieldResult = zMetadataFloatField.safeParse(val);
+//   if (floatFieldResult.success) {
+//     return floatFieldResult.data;
+//   }
+
+//   const booleanFieldResult = zMetadataBooleanField.safeParse(val);
+//   if (booleanFieldResult.success) {
+//     return booleanFieldResult.data;
+//   }
+
+//   const imageFieldResult = zMetadataImageField.safeParse(val);
+//   if (imageFieldResult.success) {
+//     return imageFieldResult.data;
+//   }
+
+//   const latentsFieldResult = zMetadataImageField.safeParse(val);
+//   if (latentsFieldResult.success) {
+//     return latentsFieldResult.data;
+//   }
+// });
+
+// /**
+//  * The node metadata schema.
+//  */
+// const zNodeMetadata = z.object({
+//   session_id: z.string().min(1).optional(),
+//   node: z.record(z.string().min(1), zAnyMetadataField).optional(),
+// });
+
+// export type NodeMetadata = z.infer<typeof zNodeMetadata>;
+
+// const zMetadata = z.object({
+//   invokeai: zNodeMetadata.optional(),
+//   'sd-metadata': z.record(z.string().min(1), z.any()).optional(),
+// });
+// export type Metadata = z.infer<typeof zMetadata>;
+
+// export const parseMetadata = (
+//   metadata: Record<string, any>
+// ): Metadata | undefined => {
+//   const result = zMetadata.safeParse(metadata);
+//   if (!result.success) {
+//     console.log(result.error.issues);
+//     return;
+//   }
+
+//   return result.data;
+// };
+
+export default {};

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

@@ -0,0 +1,6 @@
+import dateFormat from 'dateformat';
+
+/**
+ * Get a `now` timestamp with 1s precision, formatted as ISO datetime.
+ */
+export const getTimestamp = () => dateFormat(new Date(), 'isoDateTime');

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

@@ -0,0 +1,28 @@
+import { RootState } from 'app/store';
+import { useAppSelector } from 'app/storeHooks';
+import { OpenAPI } from 'services/api';
+
+export const getUrlAlt = (url: string, shouldTransformUrls: boolean) => {
+  if (OpenAPI.BASE && shouldTransformUrls) {
+    return [OpenAPI.BASE, url].join('/');
+  }
+
+  return url;
+};
+
+export const useGetUrl = () => {
+  const shouldTransformUrls = useAppSelector(
+    (state: RootState) => state.system.shouldTransformUrls
+  );
+
+  return {
+    shouldTransformUrls,
+    getUrl: (url?: string) => {
+      if (OpenAPI.BASE && shouldTransformUrls) {
+        return [OpenAPI.BASE, url].join('/');
+      }
+
+      return url;
+    },
+  };
+};

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

@@ -0,0 +1,169 @@
+import { forEach, size } from 'lodash';
+import { ImageField, LatentsField } from 'services/api';
+
+const OBJECT_TYPESTRING = '[object Object]';
+const STRING_TYPESTRING = '[object String]';
+const NUMBER_TYPESTRING = '[object Number]';
+const BOOLEAN_TYPESTRING = '[object Boolean]';
+const ARRAY_TYPESTRING = '[object Array]';
+
+const isObject = (obj: unknown): obj is Record<string | number, any> =>
+  Object.prototype.toString.call(obj) === OBJECT_TYPESTRING;
+
+const isString = (obj: unknown): obj is string =>
+  Object.prototype.toString.call(obj) === STRING_TYPESTRING;
+
+const isNumber = (obj: unknown): obj is number =>
+  Object.prototype.toString.call(obj) === NUMBER_TYPESTRING;
+
+const isBoolean = (obj: unknown): obj is boolean =>
+  Object.prototype.toString.call(obj) === BOOLEAN_TYPESTRING;
+
+const isArray = (obj: unknown): obj is Array<any> =>
+  Object.prototype.toString.call(obj) === ARRAY_TYPESTRING;
+
+const parseImageField = (imageField: unknown): ImageField | undefined => {
+  // Must be an object
+  if (!isObject(imageField)) {
+    return;
+  }
+
+  // An ImageField must have both `image_name` and `image_type`
+  if (!('image_name' in imageField && 'image_type' in imageField)) {
+    return;
+  }
+
+  // An ImageField's `image_type` must be one of the allowed values
+  if (
+    !['results', 'uploads', 'intermediates'].includes(imageField.image_type)
+  ) {
+    return;
+  }
+
+  // An ImageField's `image_name` must be a string
+  if (typeof imageField.image_name !== 'string') {
+    return;
+  }
+
+  // Build a valid ImageField
+  return {
+    image_type: imageField.image_type,
+    image_name: imageField.image_name,
+  };
+};
+
+const parseLatentsField = (latentsField: unknown): LatentsField | undefined => {
+  // Must be an object
+  if (!isObject(latentsField)) {
+    return;
+  }
+
+  // A LatentsField must have a `latents_name`
+  if (!('latents_name' in latentsField)) {
+    return;
+  }
+
+  // A LatentsField's `latents_name` must be a string
+  if (typeof latentsField.latents_name !== 'string') {
+    return;
+  }
+
+  // Build a valid LatentsField
+  return {
+    latents_name: latentsField.latents_name,
+  };
+};
+
+type NodeMetadata = {
+  [key: string]: string | number | boolean | ImageField | LatentsField;
+};
+
+type InvokeAIMetadata = {
+  session_id?: string;
+  node?: NodeMetadata;
+};
+
+export const parseNodeMetadata = (
+  nodeMetadata: Record<string | number, any>
+): NodeMetadata | undefined => {
+  if (!isObject(nodeMetadata)) {
+    return;
+  }
+
+  const parsed: NodeMetadata = {};
+
+  forEach(nodeMetadata, (nodeItem, nodeKey) => {
+    // `id` and `type` must be strings if they are present
+    if (['id', 'type'].includes(nodeKey)) {
+      if (isString(nodeItem)) {
+        parsed[nodeKey] = nodeItem;
+      }
+      return;
+    }
+
+    // the only valid object types are ImageField and LatentsField
+    if (isObject(nodeItem)) {
+      if ('image_name' in nodeItem || 'image_type' in nodeItem) {
+        const imageField = parseImageField(nodeItem);
+        if (imageField) {
+          parsed[nodeKey] = imageField;
+        }
+        return;
+      }
+
+      if ('latents_name' in nodeItem) {
+        const latentsField = parseLatentsField(nodeItem);
+        if (latentsField) {
+          parsed[nodeKey] = latentsField;
+        }
+        return;
+      }
+    }
+
+    // otherwise we accept any string, number or boolean
+    if (isString(nodeItem) || isNumber(nodeItem) || isBoolean(nodeItem)) {
+      parsed[nodeKey] = nodeItem;
+      return;
+    }
+  });
+
+  if (size(parsed) === 0) {
+    return;
+  }
+
+  return parsed;
+};
+
+export const parseInvokeAIMetadata = (
+  metadata: Record<string | number, any> | undefined
+): InvokeAIMetadata | undefined => {
+  if (metadata === undefined) {
+    return;
+  }
+
+  if (!isObject(metadata)) {
+    return;
+  }
+
+  const parsed: InvokeAIMetadata = {};
+
+  forEach(metadata, (item, key) => {
+    if (key === 'session_id' && isString(item)) {
+      parsed['session_id'] = item;
+    }
+
+    if (key === 'node' && isObject(item)) {
+      const nodeMetadata = parseNodeMetadata(item);
+
+      if (nodeMetadata) {
+        parsed['node'] = nodeMetadata;
+      }
+    }
+  });
+
+  if (size(parsed) === 0) {
+    return;
+  }
+
+  return parsed;
+};

invokeai/frontend/web/src/component.tsx

@@ -1,8 +1,10 @@
-import React, { lazy, PropsWithChildren } from 'react';
+import React, { lazy, PropsWithChildren, useEffect, useState } from 'react';
 import { Provider } from 'react-redux';
 import { PersistGate } from 'redux-persist/integration/react';
-import { store } from './app/store';
+import { buildMiddleware, store } from './app/store';
 import { persistor } from './persistor';
+import { OpenAPI } from 'services/api';
+import { InvokeTabName } from 'features/ui/store/tabMap';
 import '@fontsource/inter/100.css';
 import '@fontsource/inter/200.css';
 import '@fontsource/inter/300.css';
@@ -17,18 +19,68 @@ import Loading from './Loading';
 
 // Localization
 import './i18n';
+import { addMiddleware, resetMiddlewares } from 'redux-dynamic-middlewares';
 
 const App = lazy(() => import('./app/App'));
 const ThemeLocaleProvider = lazy(() => import('./app/ThemeLocaleProvider'));
 
-export default function Component(props: PropsWithChildren) {
+interface Props extends PropsWithChildren {
+  apiUrl?: string;
+  disabledPanels?: string[];
+  disabledTabs?: InvokeTabName[];
+  token?: string;
+  shouldTransformUrls?: boolean;
+  shouldFetchImages?: boolean;
+}
+
+export default function Component({
+  apiUrl,
+  disabledPanels = [],
+  disabledTabs = [],
+  token,
+  children,
+  shouldTransformUrls,
+  shouldFetchImages = false,
+}: Props) {
+  useEffect(() => {
+    // configure API client token
+    if (token) {
+      OpenAPI.TOKEN = token;
+    }
+
+    // configure API client base url
+    if (apiUrl) {
+      OpenAPI.BASE = apiUrl;
+    }
+
+    // reset dynamically added middlewares
+    resetMiddlewares();
+
+    // TODO: at this point, after resetting the middleware, we really ought to clean up the socket
+    // stuff by calling `dispatch(socketReset())`. but we cannot dispatch from here as we are
+    // outside the provider. it's not needed until there is the possibility that we will change
+    // the `apiUrl`/`token` dynamically.
+
+    // rebuild socket middleware with token and apiUrl
+    addMiddleware(buildMiddleware());
+  }, [apiUrl, token]);
+
   return (
     <React.StrictMode>
       <Provider store={store}>
         <PersistGate loading={<Loading />} persistor={persistor}>
           <React.Suspense fallback={<Loading showText />}>
             <ThemeLocaleProvider>
-              <App>{props.children}</App>
+              <App
+                options={{
+                  disabledPanels,
+                  disabledTabs,
+                  shouldTransformUrls,
+                  shouldFetchImages,
+                }}
+              >
+                {children}
+              </App>
             </ThemeLocaleProvider>
           </React.Suspense>
         </PersistGate>