feat(api): change implementation for path endpoint

- `MetadataModule` is stateless and needed in places where the `InvocationContext` is not available, so have not made it a `service`
- Handles loading/parsing/building metadata, and creating png info objects
- added tests for MetadataModule
- Lifted thumbnail stuff to util

.github/CODEOWNERS

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

.gitignore

@@ -9,8 +9,6 @@ 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

@@ -148,11 +148,6 @@ 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.init` in your home directory). You can change the default at any
+`.invokeai` 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

@@ -3,8 +3,6 @@
 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
@@ -62,9 +60,7 @@ class ApiDependencies:
 
         latents = ForwardCacheLatentsStorage(DiskLatentsStorage(f'{output_folder}/latents'))
 
-        metadata = PngMetadataService()
-
-        images = DiskImageStorage(f'{output_folder}/images', metadata_service=metadata)
+        images = DiskImageStorage(f'{output_folder}/images')
 
         # TODO: build a file/path manager?
         db_location = os.path.join(output_folder, "invokeai.db")
@@ -74,7 +70,6 @@ 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(0.1)
+                await asyncio.sleep(0.001)
                 pass
 
             except asyncio.CancelledError as e:

invokeai/app/api/models/images.py

@@ -1,19 +1,7 @@
-from typing import Optional
 from pydantic import BaseModel, Field
 
 from invokeai.app.models.image import ImageType
-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"
-    )
+from invokeai.app.modules.metadata import ImageMetadata
 
 
 class ImageResponse(BaseModel):
@@ -23,12 +11,11 @@ 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: ImageResponseMetadata = Field(description="The image's metadata")
+    metadata: ImageMetadata = 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

@@ -3,16 +3,16 @@ import io
 from datetime import datetime, timezone
 import json
 import os
-from typing import Any
 import uuid
 
 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, ImageResponseMetadata
-from invokeai.app.services.metadata import InvokeAIMetadata
+from invokeai.app.api.models.images import ImageResponse
+from invokeai.app.modules.metadata import ImageMetadata, InvokeAIMetadata
 from invokeai.app.services.item_storage import PaginatedResults
+from invokeai.app.util.image_paths import build_image_path
 
 from ...services.image_storage import ImageType
 from ..dependencies import ApiDependencies
@@ -35,6 +35,18 @@ async def get_image(
         return FileResponse(path)
     else:
         raise HTTPException(status_code=404)
+    
+@images_router.get("/path/{image_type}/{image_name}", operation_id="get_image_path")
+async def get_image_path(
+    image_type: ImageType = Path(description="The type of image to get"),
+    image_name: str = Path(description="The name of the image to get"),
+) -> str:
+    """Gets a result location"""
+
+    path = build_image_path(image_type=image_type, image_name=image_name)
+
+    return path
+
 
 
 @images_router.get(
@@ -75,7 +87,6 @@ async def upload_image(
         raise HTTPException(status_code=415, detail="Not an image")
 
     contents = await file.read()
-
     try:
         img = Image.open(io.BytesIO(contents))
     except:
@@ -83,22 +94,27 @@ async def upload_image(
         raise HTTPException(status_code=415, detail="Failed to read image")
 
     filename = f"{uuid.uuid4()}_{str(int(datetime.now(timezone.utc).timestamp()))}.png"
-
     (image_path, thumbnail_path, ctime) = ApiDependencies.invoker.services.images.save(
         ImageType.UPLOAD, filename, img
     )
 
-    invokeai_metadata = ApiDependencies.invoker.services.metadata.get_metadata(img)
+    # TODO: handle old `sd-metadata` style metadata
+    invokeai_metadata = img.info.get("invokeai", None)
 
+    if invokeai_metadata is not None:
+        invokeai_metadata = InvokeAIMetadata(**json.loads(invokeai_metadata))
+
+    # TODO: should creation of this object should happen elsewhere?
     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(
+        metadata=ImageMetadata(
             created=ctime,
             width=img.width,
             height=img.height,
+            mode=img.mode,
             invokeai=invokeai_metadata,
         ),
     )

invokeai/app/cli_app.py

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

invokeai/app/invocations/cv.py

@@ -8,6 +8,7 @@ from PIL import Image, ImageOps
 from pydantic import BaseModel, Field
 
 from invokeai.app.models.image import ImageField, ImageType
+from invokeai.app.modules.metadata import MetadataModule
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
 from .image import ImageOutput, build_image_output
 
@@ -57,8 +58,8 @@ class CvInpaintInvocation(BaseInvocation, CvInvocationConfig):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
         
         context.services.images.save(image_type, image_name, image_inpainted, metadata)

invokeai/app/invocations/generate.py

@@ -4,14 +4,13 @@ from functools import partial
 from typing import Literal, Optional, Union
 
 import numpy as np
-from diffusers import ControlNetModel
 from torch import Tensor
-import torch
 
 from pydantic import BaseModel, Field
 
 from invokeai.app.models.image import ImageField, ImageType
 from invokeai.app.invocations.util.choose_model import choose_model
+from invokeai.app.modules.metadata import MetadataModule
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
 from .image import ImageOutput, build_image_output
 from ...backend.generator import Txt2Img, Img2Img, Inpaint, InvokeAIGenerator
@@ -55,9 +54,6 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
     seamless:   bool = Field(default=False, description="Whether or not to generate an image that can tile without seams", )
     model:       str = Field(default="", description="The model to use (currently ignored)")
     progress_images: bool = Field(default=False, description="Whether or not to produce progress images during generation",  )
-    control_model: Optional[str] = Field(default=None, description="The control model to use")
-    control_image: Optional[ImageField] = Field(default=None, description="The processed control image")
-    # control_strength: Optional[float] = Field(default=1.0, ge=0, le=1, description="The strength of the controlnet")
     # fmt: on
 
     # TODO: pass this an emitter method or something? or a session for dispatching?
@@ -70,41 +66,25 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
         stable_diffusion_step_callback(
             context=context,
             intermediate_state=intermediate_state,
-            node=self.dict(),
+            invocation_dict=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)
 
-        # loading controlnet image (currently requires pre-processed image)
-        control_image = (
-            None if self.control_image is None
-            else context.services.images.get(
-                self.control_image.image_type, self.control_image.image_name
-            )
-        )
-        # loading controlnet model
-        if (self.control_model is None or self.control_model==''):
-            control_model = None
-        else:
-            # FIXME: change this to dropdown menu?
-            control_model = ControlNetModel.from_pretrained(self.control_model,
-                                                            torch_dtype=torch.float16).to("cuda")
-
         # 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]
 
-        txt2img = Txt2Img(model, control_model=control_model)
-        outputs = txt2img.generate(
+        outputs = Txt2Img(model).generate(
             prompt=self.prompt,
             step_callback=partial(self.dispatch_progress, context, source_node_id),
-            control_image=control_image,
             **self.dict(
-                exclude={"prompt", "control_image" }
+                exclude={"prompt"}
             ),  # Shorthand for passing all of the parameters above manually
         )
         # Outputs is an infinite iterator that will return a new InvokeAIGeneratorOutput object
@@ -119,8 +99,8 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
 
         context.services.images.save(
@@ -157,7 +137,7 @@ class ImageToImageInvocation(TextToImageInvocation):
         stable_diffusion_step_callback(
             context=context,
             intermediate_state=intermediate_state,
-            node=self.dict(),
+            invocation_dict=self.dict(),
             source_node_id=source_node_id,
         )
 
@@ -204,8 +184,8 @@ class ImageToImageInvocation(TextToImageInvocation):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
 
         context.services.images.save(image_type, image_name, result_image, metadata)
@@ -239,7 +219,7 @@ class InpaintInvocation(ImageToImageInvocation):
         stable_diffusion_step_callback(
             context=context,
             intermediate_state=intermediate_state,
-            node=self.dict(),
+            invocation_dict=self.dict(),
             source_node_id=source_node_id,
         )
 
@@ -290,8 +270,8 @@ class InpaintInvocation(ImageToImageInvocation):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
 
         context.services.images.save(image_type, image_name, result_image, metadata)

invokeai/app/invocations/image.py

@@ -6,6 +6,8 @@ import numpy
 from PIL import Image, ImageFilter, ImageOps
 from pydantic import BaseModel, Field
 
+from invokeai.app.modules.metadata import MetadataModule
+
 from ..models.image import ImageField, ImageType
 from .baseinvocation import (
     BaseInvocation,
@@ -34,6 +36,7 @@ class ImageOutput(BaseInvocationOutput):
     image:      ImageField = Field(default=None, description="The output image")
     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")
+    mode:    Optional[str] = Field(default=None, description="The image mode (ie pixel format)")
     # fmt: on
 
     class Config:
@@ -148,8 +151,8 @@ class CropImageInvocation(BaseInvocation, PILInvocationConfig):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
         
         context.services.images.save(image_type, image_name, image_crop, metadata)
@@ -206,8 +209,8 @@ class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
         
         context.services.images.save(image_type, image_name, new_image, metadata)
@@ -243,8 +246,8 @@ class MaskFromAlphaInvocation(BaseInvocation, PILInvocationConfig):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
 
         context.services.images.save(image_type, image_name, image_mask, metadata)
@@ -280,8 +283,8 @@ class BlurInvocation(BaseInvocation, PILInvocationConfig):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
 
         context.services.images.save(image_type, image_name, blur_image, metadata)
@@ -317,8 +320,8 @@ class LerpInvocation(BaseInvocation, PILInvocationConfig):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
 
         context.services.images.save(image_type, image_name, lerp_image, metadata)
@@ -359,8 +362,8 @@ class InverseLerpInvocation(BaseInvocation, PILInvocationConfig):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
 
         context.services.images.save(image_type, image_name, ilerp_image, metadata)

invokeai/app/invocations/latent.py

@@ -6,6 +6,7 @@ from pydantic import BaseModel, Field
 import torch
 
 from invokeai.app.invocations.util.choose_model import choose_model
+from invokeai.app.modules.metadata import MetadataModule
 
 from invokeai.app.util.step_callback import stable_diffusion_step_callback
 
@@ -31,8 +32,6 @@ 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"""
@@ -177,7 +176,7 @@ class TextToLatentsInvocation(BaseInvocation):
         stable_diffusion_step_callback(
             context=context,
             intermediate_state=intermediate_state,
-            node=self.dict(),
+            invocation_dict=self.dict(),
             source_node_id=source_node_id,
         )
 
@@ -359,8 +358,8 @@ class LatentsToImageInvocation(BaseInvocation):
                 context.graph_execution_state_id, self.id
             )
 
-            metadata = context.services.metadata.build_metadata(
-                session_id=context.graph_execution_state_id, node=self
+            metadata = MetadataModule.build_metadata(
+                session_id=context.graph_execution_state_id, invocation=self
             )
 
             context.services.images.save(image_type, image_name, image, metadata)

invokeai/app/invocations/reconstruct.py

@@ -3,6 +3,7 @@ from typing import Literal, Union
 from pydantic import Field
 
 from invokeai.app.models.image import ImageField, ImageType
+from invokeai.app.modules.metadata import MetadataModule
 
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
 from .image import ImageOutput, build_image_output
@@ -44,8 +45,8 @@ class RestoreFaceInvocation(BaseInvocation):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
 
         context.services.images.save(image_type, image_name, results[0][0], metadata)

invokeai/app/invocations/upscale.py

@@ -5,6 +5,7 @@ from typing import Literal, Union
 from pydantic import Field
 
 from invokeai.app.models.image import ImageField, ImageType
+from invokeai.app.modules.metadata import MetadataModule
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
 from .image import ImageOutput, build_image_output
 
@@ -48,8 +49,8 @@ class UpscaleInvocation(BaseInvocation):
             context.graph_execution_state_id, self.id
         )
 
-        metadata = context.services.metadata.build_metadata(
-            session_id=context.graph_execution_state_id, node=self
+        metadata = MetadataModule.build_metadata(
+            session_id=context.graph_execution_state_id, invocation=self
         )
 
         context.services.images.save(image_type, image_name, results[0][0], metadata)

invokeai/app/models/image.py

@@ -9,14 +9,6 @@ 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"""
 
@@ -26,4 +18,6 @@ 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/modules/metadata.py

@@ -0,0 +1,180 @@
+import json
+from typing import Any, Dict, Literal, Optional
+from PIL import Image, PngImagePlugin
+from pydantic import (
+    BaseModel,
+    Extra,
+    Field,
+    StrictBool,
+    StrictInt,
+    StrictStr,
+    ValidationError,
+    root_validator,
+)
+
+from invokeai.app.models.image import ImageType
+
+
+class MetadataImageField(BaseModel):
+    """A non-nullable version of ImageField"""
+
+    image_type: Literal[tuple([t.value for t in ImageType])]  # type: ignore
+    image_name: StrictStr
+
+
+class MetadataLatentsField(BaseModel):
+    """A non-nullable version of LatentsField"""
+
+    latents_name: StrictStr
+
+
+# Union of all valid metadata field types - use mostly strict types
+NodeMetadataFieldTypes = (
+    StrictStr | StrictInt | float | StrictBool  # we want to cast ints to floats here
+)
+
+
+class NodeMetadataField(BaseModel):
+    """Helper class used as a hack for arbitrary metadata field keys."""
+
+    __root__: Dict[StrictStr, NodeMetadataFieldTypes]
+
+
+# `extra=Extra.allow` allows this to model any potential node with `id` and `type` fields
+class NodeMetadata(BaseModel, extra=Extra.allow):
+    """Node metadata model, used for validation of metadata."""
+
+    @root_validator
+    def validate_node_metadata(cls, values: dict[str, Any]) -> dict[str, Any]:
+        """Parses the node metadata, ignoring invalid values"""
+        parsed: dict[str, Any] = {}
+
+        # Conditionally build the parsed metadata, silently skipping invalid values
+        for name, value in values.items():
+            # explicitly parse `id` and `type` as strings
+            if name == "id":
+                if type(value) is not str:
+                    continue
+                parsed[name] = value
+            elif name == "type":
+                if type(value) is not str:
+                    continue
+                parsed[name] = value
+            else:
+                try:
+                    if type(value) is dict:
+                        # we only allow certain dicts, else just ignore the value entirely
+                        if "image_name" in value or "image_type" in value:
+                            # parse as an ImageField
+                            parsed[name] = MetadataImageField.parse_obj(value)
+                        elif "latents_name" in value:
+                            # this is a LatentsField
+                            parsed[name] = MetadataLatentsField.parse_obj(value)
+                    else:
+                        # hack to get parse and validate arbitrary keys
+                        NodeMetadataField.parse_obj({name: value})
+                        parsed[name] = value
+                except ValidationError:
+                    # TODO: do we want to somehow alert when metadata is not fully valid?
+                    continue
+        return parsed
+
+
+class InvokeAIMetadata(BaseModel):
+    session_id: Optional[StrictStr] = Field(
+        description="The session in which this image was created"
+    )
+    node: Optional[NodeMetadata] = Field(description="The node that created this image")
+
+    @root_validator(pre=True)
+    def validate_invokeai_metadata(cls, values: dict[str, Any]) -> dict[str, Any]:
+        parsed: dict[str, Any] = {}
+        # Conditionally build the parsed metadata, silently skipping invalid values
+        for name, value in values.items():
+            if name == "session_id":
+                if type(value) is not str:
+                    continue
+                parsed[name] = value
+            elif name == "node":
+                try:
+                    p = NodeMetadata.parse_obj(value)
+                    # check for empty NodeMetadata object
+                    if len(p.dict().items()) == 0:
+                        continue
+                except ValidationError:
+                    continue
+                parsed[name] = value
+
+        return parsed
+
+
+class ImageMetadata(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")
+    mode: str = Field(description="The color mode of the image")
+    invokeai: Optional[InvokeAIMetadata] = Field(
+        description="The image's InvokeAI-specific metadata"
+    )
+
+
+class MetadataModule:
+    """Handles loading metadata from images and parsing it."""
+
+    # TODO: Support parsing old format metadata **hurk**
+
+    @staticmethod
+    def _load_metadata(image: Image.Image, key="invokeai") -> Any:
+        """Loads a specific info entry from a PIL Image."""
+
+        raw_metadata = image.info.get(key)
+
+        # metadata should always be a dict
+        if type(raw_metadata) is not str:
+            return None
+
+        loaded_metadata = json.loads(raw_metadata)
+
+        return loaded_metadata
+
+    @staticmethod
+    def _parse_invokeai_metadata(
+        metadata: Any,
+    ) -> InvokeAIMetadata | None:
+        """Parses an object as InvokeAI metadata."""
+        if type(metadata) is not dict:
+            return None
+
+        parsed_metadata = InvokeAIMetadata.parse_obj(metadata)
+
+        return parsed_metadata
+
+    @staticmethod
+    def get_metadata(image: Image.Image) -> InvokeAIMetadata | None:
+        """Gets the InvokeAI metadata from a PIL Image, skipping invalid values"""
+        loaded_metadata = MetadataModule._load_metadata(image)
+        parsed_metadata = MetadataModule._parse_invokeai_metadata(loaded_metadata)
+
+        return parsed_metadata
+
+    @staticmethod
+    def build_metadata(
+        session_id: StrictStr, invocation: BaseModel
+    ) -> InvokeAIMetadata:
+        """Builds an InvokeAIMetadata object"""
+        metadata = InvokeAIMetadata(
+            session_id=session_id, node=NodeMetadata(**invocation.dict())
+        )
+
+        return metadata
+
+    @staticmethod
+    def build_png_info(metadata: InvokeAIMetadata | None):
+        png_info = PngImagePlugin.PngInfo()
+
+        if metadata is not None:
+            png_info.add_text("invokeai", metadata.json())
+
+        return png_info

invokeai/app/services/events.py

@@ -2,7 +2,7 @@
 
 from typing import Any
 from invokeai.app.api.models.images import ProgressImage
-from invokeai.app.util.misc import get_timestamp
+from invokeai.app.util.get_timestamp import get_timestamp
 
 
 class EventServiceBase:
@@ -14,7 +14,6 @@ class EventServiceBase:
         pass
 
     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 +24,7 @@ class EventServiceBase:
     def emit_generator_progress(
         self,
         graph_execution_state_id: str,
-        node: dict,
+        invocation_dict: dict,
         source_node_id: str,
         progress_image: ProgressImage | None,
         step: int,
@@ -36,11 +35,12 @@ class EventServiceBase:
             event_name="generator_progress",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
-                node=node,
+                invocation=invocation_dict,
                 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,
+                timestamp=get_timestamp(),
             ),
         )
 
@@ -48,24 +48,26 @@ class EventServiceBase:
         self,
         graph_execution_state_id: str,
         result: dict,
-        node: dict,
+        invocation_dict: dict,
         source_node_id: str,
     ) -> None:
         """Emitted when an invocation has completed"""
+        print(result)
         self.__emit_session_event(
             event_name="invocation_complete",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
-                node=node,
+                invocation=invocation_dict,
                 source_node_id=source_node_id,
                 result=result,
+                timestamp=get_timestamp(),
             ),
         )
 
     def emit_invocation_error(
         self,
         graph_execution_state_id: str,
-        node: dict,
+        invocation_dict: dict,
         source_node_id: str,
         error: str,
     ) -> None:
@@ -74,22 +76,24 @@ class EventServiceBase:
             event_name="invocation_error",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
-                node=node,
+                invocation=invocation_dict,
                 source_node_id=source_node_id,
                 error=error,
+                timestamp=get_timestamp(),
             ),
         )
 
     def emit_invocation_started(
-        self, graph_execution_state_id: str, node: dict, source_node_id: str
+        self, graph_execution_state_id: str, invocation_dict: 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,
-                node=node,
+                invocation=invocation_dict,
                 source_node_id=source_node_id,
+                timestamp=get_timestamp(),
             ),
         )
 
@@ -99,5 +103,6 @@ class EventServiceBase:
             event_name="graph_execution_state_complete",
             payload=dict(
                 graph_execution_state_id=graph_execution_state_id,
+                timestamp=get_timestamp(),
             ),
         )

invokeai/app/services/image_storage.py

@@ -1,25 +1,27 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
+import datetime
 import os
+import json
 from glob import glob
 from abc import ABC, abstractmethod
 from pathlib import Path
 from queue import Queue
-from typing import Dict, List, Tuple
+from typing import Any, Dict, List, Tuple
 
 from PIL.Image import Image
 import PIL.Image as PILImage
-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 PIL import PngImagePlugin
+from invokeai.app.api.models.images import ImageResponse
+from invokeai.app.models.image import  ImageType
+from invokeai.app.modules.metadata import ImageMetadata, InvokeAIMetadata, MetadataModule
 from invokeai.app.services.item_storage import PaginatedResults
-from invokeai.app.util.misc import get_timestamp
+from invokeai.app.util.get_timestamp import get_timestamp
+from invokeai.app.util.image_paths import build_image_path
 from invokeai.app.util.thumbnails import get_thumbnail_name, make_thumbnail
 
+from invokeai.backend.image_util import PngWriter
+
 
 class ImageStorageBase(ABC):
     """Responsible for storing and retrieving images."""
@@ -46,18 +48,14 @@ class ImageStorageBase(ABC):
 
     # TODO: make this a bit more flexible for e.g. cloud storage
     @abstractmethod
-    def validate_path(self, path: str) -> bool:
+    def validate_path(
+        self, path: str
+    ) -> bool:
         """Validates an image path."""
         pass
 
     @abstractmethod
-    def save(
-        self,
-        image_type: ImageType,
-        image_name: str,
-        image: Image,
-        metadata: InvokeAIMetadata | None = None,
-    ) -> Tuple[str, str, int]:
+    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
 
@@ -78,14 +76,12 @@ class DiskImageStorage(ImageStorageBase):
     __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, metadata_service: MetadataServiceBase):
+    def __init__(self, output_folder: str):
         self.__output_folder = 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)
 
@@ -118,22 +114,22 @@ 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)
+            
+            invokeai_metadata = MetadataModule.get_metadata(img)
 
             page_of_images.append(
                 ImageResponse(
                     image_type=image_type.value,
                     image_name=filename,
-                    # 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",
+                    image_url=build_image_path(image_type.value, filename),
+                    thumbnail_url = build_image_path(image_type.value, filename, True),
                     # TODO: Creation of this object should happen elsewhere (?), just making it fit here so it works
-                    metadata=ImageResponseMetadata(
+                    metadata=ImageMetadata(
                         created=int(os.path.getctime(path)),
                         width=img.width,
                         height=img.height,
-                        invokeai=invokeai_metadata,
+                        mode=img.mode,
+                        invokeai=invokeai_metadata
                     ),
                 )
             )
@@ -176,31 +172,26 @@ class DiskImageStorage(ImageStorageBase):
 
         return path
 
-    def validate_path(self, path: str) -> bool:
+    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
+    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)
 
         thumbnail_name = get_thumbnail_name(image_name)
         thumbnail_path = self.get_path(image_type, thumbnail_name, is_thumbnail=True)
+
+        png_info = MetadataModule.build_png_info(metadata=metadata)
+
+        image.save(image_path, "PNG", pnginfo=png_info)
+
         thumbnail_image = make_thumbnail(image)
         thumbnail_image.save(thumbnail_path)
 

invokeai/app/services/invocation_services.py

@@ -1,5 +1,4 @@
 # 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
@@ -15,7 +14,6 @@ class InvocationServices:
     events: EventServiceBase
     latents: LatentsStorageBase
     images: ImageStorageBase
-    metadata: MetadataServiceBase
     queue: InvocationQueueABC
     model_manager: ModelManager
     restoration: RestorationServices
@@ -31,7 +29,6 @@ class InvocationServices:
             events: EventServiceBase,
             latents: LatentsStorageBase,
             images: ImageStorageBase,
-            metadata: MetadataServiceBase,
             queue: InvocationQueueABC,
             graph_library: ItemStorageABC["LibraryGraph"],
             graph_execution_manager: ItemStorageABC["GraphExecutionState"],
@@ -42,7 +39,6 @@ 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

@@ -1,96 +0,0 @@
-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

@@ -49,7 +49,7 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                 # Send starting event
                 self.__invoker.services.events.emit_invocation_started(
                     graph_execution_state_id=graph_execution_state.id,
-                    node=invocation.dict(),
+                    invocation_dict=invocation.dict(),
                     source_node_id=source_node_id
                 )
 
@@ -79,7 +79,7 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                     # Send complete event
                     self.__invoker.services.events.emit_invocation_complete(
                         graph_execution_state_id=graph_execution_state.id,
-                        node=invocation.dict(),
+                        invocation_dict=invocation.dict(),
                         source_node_id=source_node_id,
                         result=outputs.dict(),
                     )
@@ -104,7 +104,7 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                     # Send error event
                     self.__invoker.services.events.emit_invocation_error(
                         graph_execution_state_id=graph_execution_state.id,
-                        node=invocation.dict(),
+                        invocation_dict=invocation.dict(),
                         source_node_id=source_node_id,
                         error=error,
                     )

invokeai/app/util/image_paths.py

@@ -0,0 +1,12 @@
+from typing import Optional
+from invokeai.app.models.image import ImageType
+from invokeai.app.util.thumbnails import get_thumbnail_name
+
+
+def build_image_path(image_type: ImageType, image_name: str, is_thumbnail: Optional[bool] = False) -> str:
+    """Gets path to access an image"""
+    if is_thumbnail is None:
+        return f"api/v1/images/{image_type}/{image_name}"
+    else:
+        thumbnail_name = get_thumbnail_name(image_name)
+        return f"api/v1/images/{image_type}/thumbnails/{thumbnail_name}"

invokeai/app/util/step_callback.py

@@ -9,7 +9,7 @@ from ...backend.stable_diffusion import PipelineIntermediateState
 def stable_diffusion_step_callback(
     context: InvocationContext,
     intermediate_state: PipelineIntermediateState,
-    node: dict,
+    invocation_dict: dict,
     source_node_id: str,
 ):
     if context.services.queue.is_canceled(context.graph_execution_state_id):
@@ -47,9 +47,9 @@ def stable_diffusion_step_callback(
 
     context.services.events.emit_generator_progress(
         graph_execution_state_id=context.graph_execution_state_id,
-        node=node,
+        invocation_dict=invocation_dict,
         source_node_id=source_node_id,
         progress_image=ProgressImage(width=width, height=height, dataURL=dataURL),
         step=intermediate_state.step,
-        total_steps=node["steps"],
+        total_steps=invocation_dict["steps"],
     )

invokeai/backend/__init__.py

@@ -10,7 +10,7 @@ from .generator import (
     Img2Img,
     Inpaint
 )
-from .model_management import ModelManager, SDModelComponent
+from .model_management import ModelManager
 from .safety_checker import SafetyChecker
 from .args import Args
 from .globals import Globals

invokeai/backend/generator/base.py

@@ -86,11 +86,9 @@ class InvokeAIGenerator(metaclass=ABCMeta):
     def __init__(self,
                  model_info: dict,
                  params: InvokeAIGeneratorBasicParams=InvokeAIGeneratorBasicParams(),
-                 **kwargs,
                  ):
         self.model_info=model_info
         self.params=params
-        self.kwargs = kwargs
 
     def generate(self,
                  prompt: str='',
@@ -131,12 +129,9 @@ class InvokeAIGenerator(metaclass=ABCMeta):
             model=model,
             scheduler_name=generator_args.get('scheduler')
         )
-
-        # get conditioning from prompt via Compel package
-        uc, c, extra_conditioning_info = get_uc_and_c_and_ec(prompt, model=model)
-
+        uc, c, extra_conditioning_info = get_uc_and_c_and_ec(prompt,model=model)
         gen_class = self._generator_class()
-        generator = gen_class(model, self.params.precision, **self.kwargs)
+        generator = gen_class(model, self.params.precision)
         if self.params.variation_amount > 0:
             generator.set_variation(generator_args.get('seed'),
                                     generator_args.get('variation_amount'),
@@ -286,7 +281,7 @@ class Generator:
     precision: str
     model: DiffusionPipeline
 
-    def __init__(self, model: DiffusionPipeline, precision: str, **kwargs):
+    def __init__(self, model: DiffusionPipeline, precision: str):
         self.model = model
         self.precision = precision
         self.seed = None
@@ -359,6 +354,7 @@ class Generator:
         seed = seed if seed is not None and seed >= 0 else self.new_seed()
         first_seed = seed
         seed, initial_noise = self.generate_initial_noise(seed, width, height)
+
         # There used to be an additional self.model.ema_scope() here, but it breaks
         # the inpaint-1.5 model. Not sure what it did.... ?
         with scope(self.model.device.type):

invokeai/backend/generator/txt2img.py

@@ -4,10 +4,6 @@ invokeai.backend.generator.txt2img inherits from invokeai.backend.generator
 import PIL.Image
 import torch
 
-from typing import Any, Callable, Dict, List, Optional, Tuple, Union
-from diffusers.models.controlnet import ControlNetModel, ControlNetOutput
-from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_controlnet import MultiControlNetModel
-
 from ..stable_diffusion import (
     ConditioningData,
     PostprocessingSettings,
@@ -17,13 +13,8 @@ from .base import Generator
 
 
 class Txt2Img(Generator):
-    def __init__(self, model, precision,
-                 control_model: Optional[Union[ControlNetModel, List[ControlNetModel]]] = None,
-                 **kwargs):
-        self.control_model = control_model
-        if isinstance(self.control_model, list):
-            self.control_model = MultiControlNetModel(self.control_model)
-        super().__init__(model, precision, **kwargs)
+    def __init__(self, model, precision):
+        super().__init__(model, precision)
 
     @torch.no_grad()
     def get_make_image(
@@ -51,12 +42,9 @@ class Txt2Img(Generator):
         kwargs are 'width' and 'height'
         """
         self.perlin = perlin
-        control_image = kwargs.get("control_image", None)
-        do_classifier_free_guidance = cfg_scale > 1.0
 
         # noinspection PyTypeChecker
         pipeline: StableDiffusionGeneratorPipeline = self.model
-        pipeline.control_model = self.control_model
         pipeline.scheduler = sampler
 
         uc, c, extra_conditioning_info = conditioning
@@ -73,37 +61,6 @@ class Txt2Img(Generator):
             ),
         ).add_scheduler_args_if_applicable(pipeline.scheduler, eta=ddim_eta)
 
-        # FIXME: still need to test with different widths, heights, devices, dtypes
-        #        and add in batch_size, num_images_per_prompt?
-        if control_image is not None:
-            if isinstance(self.control_model, ControlNetModel):
-                control_image = pipeline.prepare_control_image(
-                    image=control_image,
-                    do_classifier_free_guidance=do_classifier_free_guidance,
-                    width=width,
-                    height=height,
-                    # batch_size=batch_size * num_images_per_prompt,
-                    # num_images_per_prompt=num_images_per_prompt,
-                    device=self.control_model.device,
-                    dtype=self.control_model.dtype,
-                )
-            elif isinstance(self.control_model, MultiControlNetModel):
-                images = []
-                for image_ in control_image:
-                    image_ = self.model.prepare_control_image(
-                        image=image_,
-                        do_classifier_free_guidance=do_classifier_free_guidance,
-                        width=width,
-                        height=height,
-                        # batch_size=batch_size * num_images_per_prompt,
-                        # num_images_per_prompt=num_images_per_prompt,
-                        device=self.control_model.device,
-                        dtype=self.control_model.dtype,
-                    )
-                    images.append(image_)
-                control_image = images
-            kwargs["control_image"] = control_image
-
         def make_image(x_T: torch.Tensor, _: int) -> PIL.Image.Image:
             pipeline_output = pipeline.image_from_embeddings(
                 latents=torch.zeros_like(x_T, dtype=self.torch_dtype()),
@@ -111,7 +68,6 @@ class Txt2Img(Generator):
                 num_inference_steps=steps,
                 conditioning_data=conditioning_data,
                 callback=step_callback,
-                **kwargs,
             )
 
             if (

invokeai/backend/model_management/__init__.py

@@ -5,7 +5,6 @@ from .convert_ckpt_to_diffusers import (
     convert_ckpt_to_diffusers,
     load_pipeline_from_original_stable_diffusion_ckpt,
 )
-from .model_manager import ModelManager,SDModelComponent
-
+from .model_manager import ModelManager
 
 

invokeai/backend/stable_diffusion/diffusers_pipeline.py

@@ -9,20 +9,16 @@ from typing import Any, Callable, Generic, List, Optional, Type, TypeVar, Union
 
 import einops
 import PIL.Image
-import numpy as np
 from accelerate.utils import set_seed
 import psutil
 import torch
 import torchvision.transforms as T
 from compel import EmbeddingsProvider
 from diffusers.models import AutoencoderKL, UNet2DConditionModel
-from diffusers.models.controlnet import ControlNetModel, ControlNetOutput
 from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
 from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion import (
     StableDiffusionPipeline,
 )
-from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_controlnet import MultiControlNetModel
-
 from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_img2img import (
     StableDiffusionImg2ImgPipeline,
 )
@@ -31,7 +27,6 @@ from diffusers.pipelines.stable_diffusion.safety_checker import (
 )
 from diffusers.schedulers import KarrasDiffusionSchedulers
 from diffusers.schedulers.scheduling_utils import SchedulerMixin, SchedulerOutput
-from diffusers.utils import PIL_INTERPOLATION
 from diffusers.utils.import_utils import is_xformers_available
 from diffusers.utils.outputs import BaseOutput
 from torchvision.transforms.functional import resize as tv_resize
@@ -309,7 +304,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         feature_extractor: Optional[CLIPFeatureExtractor],
         requires_safety_checker: bool = False,
         precision: str = "float32",
-        control_model: ControlNetModel = None,
     ):
         super().__init__(
             vae,
@@ -330,8 +324,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             scheduler=scheduler,
             safety_checker=safety_checker,
             feature_extractor=feature_extractor,
-            # FIXME: can't currently register control module
-            # control_model=control_model,
         )
         self.invokeai_diffuser = InvokeAIDiffuserComponent(
             self.unet, self._unet_forward, is_running_diffusers=True
@@ -351,7 +343,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
 
         self._model_group = FullyLoadedModelGroup(self.unet.device)
         self._model_group.install(*self._submodels)
-        self.control_model = control_model
 
     def _adjust_memory_efficient_attention(self, latents: torch.Tensor):
         """
@@ -454,15 +445,8 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
     @property
     def _submodels(self) -> Sequence[torch.nn.Module]:
         module_names, _, _ = self.extract_init_dict(dict(self.config))
-        submodels = []
-        for name in module_names.keys():
-            if hasattr(self, name):
-                value = getattr(self, name)
-            else:
-                value = getattr(self.config, name)
-            if isinstance(value, torch.nn.Module):
-                submodels.append(value)
-        return submodels
+        values = [getattr(self, name) for name in module_names.keys()]
+        return [m for m in values if isinstance(m, torch.nn.Module)]
 
     def image_from_embeddings(
         self,
@@ -473,7 +457,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         noise: torch.Tensor,
         callback: Callable[[PipelineIntermediateState], None] = None,
         run_id=None,
-        **kwargs,
     ) -> InvokeAIStableDiffusionPipelineOutput:
         r"""
         Function invoked when calling the pipeline for generation.
@@ -494,7 +477,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             noise=noise,
             run_id=run_id,
             callback=callback,
-            **kwargs,
         )
         # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699
         torch.cuda.empty_cache()
@@ -519,7 +501,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         additional_guidance: List[Callable] = None,
         run_id=None,
         callback: Callable[[PipelineIntermediateState], None] = None,
-        **kwargs,
     ) -> tuple[torch.Tensor, Optional[AttentionMapSaver]]:
         if timesteps is None:
             self.scheduler.set_timesteps(
@@ -537,7 +518,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             additional_guidance=additional_guidance,
             run_id=run_id,
             callback=callback,
-            **kwargs,
         )
         return result.latents, result.attention_map_saver
 
@@ -550,7 +530,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         noise: torch.Tensor,
         run_id: str = None,
         additional_guidance: List[Callable] = None,
-        **kwargs,
     ):
         self._adjust_memory_efficient_attention(latents)
         if run_id is None:
@@ -565,7 +544,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             yield PipelineIntermediateState(
                 run_id=run_id,
                 step=-1,
-                timestep=self.scheduler.config.num_train_timesteps,
+                timestep=self.scheduler.num_train_timesteps,
                 latents=latents,
             )
 
@@ -589,7 +568,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
                     step_index=i,
                     total_step_count=len(timesteps),
                     additional_guidance=additional_guidance,
-                    **kwargs,
                 )
                 latents = step_output.prev_sample
 
@@ -630,7 +608,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         step_index: int,
         total_step_count: int,
         additional_guidance: List[Callable] = None,
-        **kwargs,
     ):
         # invokeai_diffuser has batched timesteps, but diffusers schedulers expect a single value
         timestep = t[0]
@@ -642,33 +619,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         #     i.e. before or after passing it to InvokeAIDiffuserComponent
         latent_model_input = self.scheduler.scale_model_input(latents, timestep)
 
-        if (self.control_model is not None) and (kwargs.get("control_image") is not None):
-            control_image = kwargs.get("control_image") # should be a processed tensor derived from the control image(s)
-            control_scale = kwargs.get("control_scale", 1.0)  # control_scale default is 1.0
-            # handling case where using multiple control models but only specifying single control_scale
-            #     so reshape control_scale to match number of control models
-            if isinstance(self.control_model, MultiControlNetModel) and isinstance(control_scale, float):
-                control_scale = [control_scale] * len(self.control_model.nets)
-            if conditioning_data.guidance_scale > 1.0:
-                # expand the latents input to control model if doing classifier free guidance
-                #    (which I think for now is always true, there is conditional elsewhere that stops execution if
-                #     classifier_free_guidance is <= 1.0 ?)
-                latent_control_input = torch.cat([latent_model_input] * 2)
-            else:
-                latent_control_input = latent_model_input
-            # controlnet inference
-            down_block_res_samples, mid_block_res_sample = self.control_model(
-                latent_control_input,
-                timestep,
-                encoder_hidden_states=torch.cat([conditioning_data.unconditioned_embeddings,
-                                                 conditioning_data.text_embeddings]),
-                controlnet_cond=control_image,
-                conditioning_scale=control_scale,
-                return_dict=False,
-            )
-        else:
-            down_block_res_samples, mid_block_res_sample = None, None
-
         # predict the noise residual
         noise_pred = self.invokeai_diffuser.do_diffusion_step(
             latent_model_input,
@@ -678,8 +628,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             conditioning_data.guidance_scale,
             step_index=step_index,
             total_step_count=total_step_count,
-            down_block_additional_residuals=down_block_res_samples,
-            mid_block_additional_residual=mid_block_res_sample,
         )
 
         # compute the previous noisy sample x_t -> x_t-1
@@ -701,7 +649,6 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
         t,
         text_embeddings,
         cross_attention_kwargs: Optional[dict[str, Any]] = None,
-        **kwargs,
     ):
         """predict the noise residual"""
         if is_inpainting_model(self.unet) and latents.size(1) == 4:
@@ -721,8 +668,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
 
         # First three args should be positional, not keywords, so torch hooks can see them.
         return self.unet(
-            latents, t, text_embeddings, cross_attention_kwargs=cross_attention_kwargs,
-            **kwargs,
+            latents, t, text_embeddings, cross_attention_kwargs=cross_attention_kwargs
         ).sample
 
     def img2img_from_embeddings(
@@ -969,7 +915,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
     @property
     def channels(self) -> int:
         """Compatible with DiffusionWrapper"""
-        return self.unet.config.in_channels
+        return self.unet.in_channels
 
     def decode_latents(self, latents):
         # Explicit call to get the vae loaded, since `decode` isn't the forward method.
@@ -984,48 +930,3 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
             debug_image(
                 img, f"latents {msg} {i+1}/{len(decoded)}", debug_status=True
             )
-
-    # Copied from diffusers pipeline_stable_diffusion_controlnet.py
-    # Returns torch.Tensor of shape (batch_size, 3, height, width)
-    def prepare_control_image(
-        self,
-        image,
-        width=512,
-        height=512,
-        batch_size=1,
-        num_images_per_prompt=1,
-        device="cuda",
-        dtype=torch.float16,
-        do_classifier_free_guidance=True,
-    ):
-        if not isinstance(image, torch.Tensor):
-            if isinstance(image, PIL.Image.Image):
-                image = [image]
-
-            if isinstance(image[0], PIL.Image.Image):
-                images = []
-                for image_ in image:
-                    image_ = image_.convert("RGB")
-                    image_ = image_.resize((width, height), resample=PIL_INTERPOLATION["lanczos"])
-                    image_ = np.array(image_)
-                    image_ = image_[None, :]
-                    images.append(image_)
-                image = images
-                image = np.concatenate(image, axis=0)
-                image = np.array(image).astype(np.float32) / 255.0
-                image = image.transpose(0, 3, 1, 2)
-                image = torch.from_numpy(image)
-            elif isinstance(image[0], torch.Tensor):
-                image = torch.cat(image, dim=0)
-
-        image_batch_size = image.shape[0]
-        if image_batch_size == 1:
-            repeat_by = batch_size
-        else:
-            # image batch size is the same as prompt batch size
-            repeat_by = num_images_per_prompt
-        image = image.repeat_interleave(repeat_by, dim=0)
-        image = image.to(device=device, dtype=dtype)
-        if do_classifier_free_guidance:
-            image = torch.cat([image] * 2)
-        return image

invokeai/backend/stable_diffusion/diffusion/cross_attention_control.py

@@ -1,6 +1,7 @@
 # adapted from bloc97's CrossAttentionControl colab
 # https://github.com/bloc97/CrossAttentionControl
 
+
 import enum
 import math
 from typing import Callable, Optional
@@ -9,7 +10,8 @@ import diffusers
 import psutil
 import torch
 from compel.cross_attention_control import Arguments
-from diffusers.models.attention_processor import AttentionProcessor
+from diffusers.models.cross_attention import AttnProcessor
+from diffusers.models.unet_2d_condition import UNet2DConditionModel
 from torch import nn
 
 from ...util import torch_dtype
@@ -186,7 +188,7 @@ class Context:
 
 class InvokeAICrossAttentionMixin:
     """
-    Enable InvokeAI-flavoured Attention calculation, which does aggressive low-memory slicing and calls
+    Enable InvokeAI-flavoured CrossAttention calculation, which does aggressive low-memory slicing and calls
     through both to an attention_slice_wrangler and a slicing_strategy_getter for custom attention map wrangling
     and dymamic slicing strategy selection.
     """
@@ -207,7 +209,7 @@ class InvokeAICrossAttentionMixin:
         Set custom attention calculator to be called when attention is calculated
         :param wrangler: Callback, with args (module, suggested_attention_slice, dim, offset, slice_size),
         which returns either the suggested_attention_slice or an adjusted equivalent.
-            `module` is the current Attention module for which the callback is being invoked.
+            `module` is the current CrossAttention module for which the callback is being invoked.
             `suggested_attention_slice` is the default-calculated attention slice
             `dim` is -1 if the attenion map has not been sliced, or 0 or 1 for dimension-0 or dimension-1 slicing.
                 If `dim` is >= 0, `offset` and `slice_size` specify the slice start and length.
@@ -343,11 +345,11 @@ class InvokeAICrossAttentionMixin:
 def restore_default_cross_attention(
     model,
     is_running_diffusers: bool,
-    restore_attention_processor: Optional[AttentionProcessor] = None,
+    restore_attention_processor: Optional[AttnProcessor] = None,
 ):
     if is_running_diffusers:
         unet = model
-        unet.set_attn_processor(restore_attention_processor or AttnProcessor())
+        unet.set_attn_processor(restore_attention_processor or CrossAttnProcessor())
     else:
         remove_attention_function(model)
 
@@ -406,9 +408,12 @@ def override_cross_attention(model, context: Context, is_running_diffusers=False
 def get_cross_attention_modules(
     model, which: CrossAttentionType
 ) -> list[tuple[str, InvokeAICrossAttentionMixin]]:
+    from ldm.modules.attention import CrossAttention  # avoid circular import
 
     cross_attention_class: type = (
         InvokeAIDiffusersCrossAttention
+        if isinstance(model, UNet2DConditionModel)
+        else CrossAttention
     )
     which_attn = "attn1" if which is CrossAttentionType.SELF else "attn2"
     attention_module_tuples = [
@@ -423,10 +428,10 @@ def get_cross_attention_modules(
         print(
             f"Error! CrossAttentionControl found an unexpected number of {cross_attention_class} modules in the model "
             + f"(expected {expected_count}, found {cross_attention_modules_in_model_count}). Either monkey-patching failed "
-            + "or some assumption has changed about the structure of the model itself. Please fix the monkey-patching, "
+            + f"or some assumption has changed about the structure of the model itself. Please fix the monkey-patching, "
             + f"and/or update the {expected_count} above to an appropriate number, and/or find and inform someone who knows "
-            + "what it means. This error is non-fatal, but it is likely that .swap() and attention map display will not "
-            + "work properly until it is fixed."
+            + f"what it means. This error is non-fatal, but it is likely that .swap() and attention map display will not "
+            + f"work properly until it is fixed."
         )
     return attention_module_tuples
 
@@ -545,7 +550,7 @@ def get_mem_free_total(device):
 
 
 class InvokeAIDiffusersCrossAttention(
-    diffusers.models.attention.Attention, InvokeAICrossAttentionMixin
+    diffusers.models.attention.CrossAttention, InvokeAICrossAttentionMixin
 ):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
@@ -567,8 +572,8 @@ class InvokeAIDiffusersCrossAttention(
 """
 # base implementation
 
-class AttnProcessor:
-    def __call__(self, attn: Attention, hidden_states, encoder_hidden_states=None, attention_mask=None):
+class CrossAttnProcessor:
+    def __call__(self, attn: CrossAttention, hidden_states, encoder_hidden_states=None, attention_mask=None):
         batch_size, sequence_length, _ = hidden_states.shape
         attention_mask = attn.prepare_attention_mask(attention_mask, sequence_length)
 
@@ -596,9 +601,9 @@ class AttnProcessor:
 from dataclasses import dataclass, field
 
 import torch
-from diffusers.models.attention_processor import (
-    Attention,
-    AttnProcessor,
+from diffusers.models.cross_attention import (
+    CrossAttention,
+    CrossAttnProcessor,
     SlicedAttnProcessor,
 )
 
@@ -648,7 +653,7 @@ class SlicedSwapCrossAttnProcesser(SlicedAttnProcessor):
 
     def __call__(
         self,
-        attn: Attention,
+        attn: CrossAttention,
         hidden_states,
         encoder_hidden_states=None,
         attention_mask=None,

invokeai/backend/stable_diffusion/diffusion/shared_invokeai_diffusion.py

@@ -5,7 +5,7 @@ from typing import Any, Callable, Dict, Optional, Union
 
 import numpy as np
 import torch
-from diffusers.models.attention_processor import AttentionProcessor
+from diffusers.models.cross_attention import AttnProcessor
 from typing_extensions import TypeAlias
 
 from invokeai.backend.globals import Globals
@@ -101,7 +101,7 @@ class InvokeAIDiffuserComponent:
 
     def override_cross_attention(
         self, conditioning: ExtraConditioningInfo, step_count: int
-    ) -> Dict[str, AttentionProcessor]:
+    ) -> Dict[str, AttnProcessor]:
         """
         setup cross attention .swap control. for diffusers this replaces the attention processor, so
         the previous attention processor is returned so that the caller can restore it later.
@@ -118,7 +118,7 @@ class InvokeAIDiffuserComponent:
         )
 
     def restore_default_cross_attention(
-        self, restore_attention_processor: Optional["AttentionProcessor"] = None
+        self, restore_attention_processor: Optional["AttnProcessor"] = None
     ):
         self.conditioning = None
         self.cross_attention_control_context = None
@@ -168,7 +168,6 @@ class InvokeAIDiffuserComponent:
         unconditional_guidance_scale: float,
         step_index: Optional[int] = None,
         total_step_count: Optional[int] = None,
-        **kwargs,
     ):
         """
         :param x: current latents
@@ -197,7 +196,7 @@ class InvokeAIDiffuserComponent:
 
         if wants_hybrid_conditioning:
             unconditioned_next_x, conditioned_next_x = self._apply_hybrid_conditioning(
-                x, sigma, unconditioning, conditioning, **kwargs,
+                x, sigma, unconditioning, conditioning
             )
         elif wants_cross_attention_control:
             (
@@ -209,14 +208,13 @@ class InvokeAIDiffuserComponent:
                 unconditioning,
                 conditioning,
                 cross_attention_control_types_to_do,
-                **kwargs,
             )
         elif self.sequential_guidance:
             (
                 unconditioned_next_x,
                 conditioned_next_x,
             ) = self._apply_standard_conditioning_sequentially(
-                x, sigma, unconditioning, conditioning, **kwargs,
+                x, sigma, unconditioning, conditioning
             )
 
         else:
@@ -224,7 +222,7 @@ class InvokeAIDiffuserComponent:
                 unconditioned_next_x,
                 conditioned_next_x,
             ) = self._apply_standard_conditioning(
-                x, sigma, unconditioning, conditioning, **kwargs,
+                x, sigma, unconditioning, conditioning
             )
 
         combined_next_x = self._combine(
@@ -264,20 +262,20 @@ class InvokeAIDiffuserComponent:
             # TODO remove when compvis codepath support is dropped
             if step_index is None and sigma is None:
                 raise ValueError(
-                    "Either step_index or sigma is required when doing cross attention control, but both are None."
+                    f"Either step_index or sigma is required when doing cross attention control, but both are None."
                 )
             percent_through = self.estimate_percent_through(step_index, sigma)
         return percent_through
 
     # methods below are called from do_diffusion_step and should be considered private to this class.
 
-    def _apply_standard_conditioning(self, x, sigma, unconditioning, conditioning, **kwargs):
+    def _apply_standard_conditioning(self, x, sigma, unconditioning, conditioning):
         # fast batched path
         x_twice = torch.cat([x] * 2)
         sigma_twice = torch.cat([sigma] * 2)
         both_conditionings = torch.cat([unconditioning, conditioning])
         both_results = self.model_forward_callback(
-            x_twice, sigma_twice, both_conditionings, **kwargs,
+            x_twice, sigma_twice, both_conditionings
         )
         unconditioned_next_x, conditioned_next_x = both_results.chunk(2)
         if conditioned_next_x.device.type == "mps":
@@ -291,17 +289,16 @@ class InvokeAIDiffuserComponent:
         sigma,
         unconditioning: torch.Tensor,
         conditioning: torch.Tensor,
-        **kwargs,
     ):
         # low-memory sequential path
-        unconditioned_next_x = self.model_forward_callback(x, sigma, unconditioning, **kwargs)
-        conditioned_next_x = self.model_forward_callback(x, sigma, conditioning, **kwargs)
+        unconditioned_next_x = self.model_forward_callback(x, sigma, unconditioning)
+        conditioned_next_x = self.model_forward_callback(x, sigma, conditioning)
         if conditioned_next_x.device.type == "mps":
             # prevent a result filled with zeros. seems to be a torch bug.
             conditioned_next_x = conditioned_next_x.clone()
         return unconditioned_next_x, conditioned_next_x
 
-    def _apply_hybrid_conditioning(self, x, sigma, unconditioning, conditioning, **kwargs):
+    def _apply_hybrid_conditioning(self, x, sigma, unconditioning, conditioning):
         assert isinstance(conditioning, dict)
         assert isinstance(unconditioning, dict)
         x_twice = torch.cat([x] * 2)
@@ -316,7 +313,7 @@ class InvokeAIDiffuserComponent:
             else:
                 both_conditionings[k] = torch.cat([unconditioning[k], conditioning[k]])
         unconditioned_next_x, conditioned_next_x = self.model_forward_callback(
-            x_twice, sigma_twice, both_conditionings, **kwargs,
+            x_twice, sigma_twice, both_conditionings
         ).chunk(2)
         return unconditioned_next_x, conditioned_next_x
 
@@ -327,7 +324,6 @@ class InvokeAIDiffuserComponent:
         unconditioning,
         conditioning,
         cross_attention_control_types_to_do,
-        **kwargs,
     ):
         if self.is_running_diffusers:
             return self._apply_cross_attention_controlled_conditioning__diffusers(
@@ -336,7 +332,6 @@ class InvokeAIDiffuserComponent:
                 unconditioning,
                 conditioning,
                 cross_attention_control_types_to_do,
-                **kwargs,
             )
         else:
             return self._apply_cross_attention_controlled_conditioning__compvis(
@@ -345,7 +340,6 @@ class InvokeAIDiffuserComponent:
                 unconditioning,
                 conditioning,
                 cross_attention_control_types_to_do,
-                **kwargs,
             )
 
     def _apply_cross_attention_controlled_conditioning__diffusers(
@@ -355,7 +349,6 @@ class InvokeAIDiffuserComponent:
         unconditioning,
         conditioning,
         cross_attention_control_types_to_do,
-        **kwargs,
     ):
         context: Context = self.cross_attention_control_context
 
@@ -371,7 +364,6 @@ class InvokeAIDiffuserComponent:
             sigma,
             unconditioning,
             {"swap_cross_attn_context": cross_attn_processor_context},
-            **kwargs,
         )
 
         # do requested cross attention types for conditioning (positive prompt)
@@ -383,7 +375,6 @@ class InvokeAIDiffuserComponent:
             sigma,
             conditioning,
             {"swap_cross_attn_context": cross_attn_processor_context},
-            **kwargs,
         )
         return unconditioned_next_x, conditioned_next_x
 
@@ -394,7 +385,6 @@ class InvokeAIDiffuserComponent:
         unconditioning,
         conditioning,
         cross_attention_control_types_to_do,
-        **kwargs,
     ):
         # print('pct', percent_through, ': doing cross attention control on', cross_attention_control_types_to_do)
         # slower non-batched path (20% slower on mac MPS)
@@ -408,13 +398,13 @@ class InvokeAIDiffuserComponent:
         context: Context = self.cross_attention_control_context
 
         try:
-            unconditioned_next_x = self.model_forward_callback(x, sigma, unconditioning, **kwargs)
+            unconditioned_next_x = self.model_forward_callback(x, sigma, unconditioning)
 
             # process x using the original prompt, saving the attention maps
             # print("saving attention maps for", cross_attention_control_types_to_do)
             for ca_type in cross_attention_control_types_to_do:
                 context.request_save_attention_maps(ca_type)
-            _ = self.model_forward_callback(x, sigma, conditioning, **kwargs,)
+            _ = self.model_forward_callback(x, sigma, conditioning)
             context.clear_requests(cleanup=False)
 
             # process x again, using the saved attention maps to control where self.edited_conditioning will be applied
@@ -425,7 +415,7 @@ class InvokeAIDiffuserComponent:
                 self.conditioning.cross_attention_control_args.edited_conditioning
             )
             conditioned_next_x = self.model_forward_callback(
-                x, sigma, edited_conditioning, **kwargs,
+                x, sigma, edited_conditioning
             )
             context.clear_requests(cleanup=True)
 
@@ -609,6 +599,7 @@ class InvokeAIDiffuserComponent:
         )
 
         # below is fugly omg
+        num_actual_conditionings = len(c_or_weighted_c_list)
         conditionings = [uc] + [c for c, weight in weighted_cond_list]
         weights = [1] + [weight for c, weight in weighted_cond_list]
         chunk_count = ceil(len(conditionings) / 2)

invokeai/frontend/install/invokeai_update.py

@@ -1,9 +1,10 @@
-'''
+"""
 Minimalist updater script. Prompts user for the tag or branch to update to and runs
 pip install <path_to_git_source>.
-'''
+"""
 import os
 import platform
+
 import requests
 from rich import box, print
 from rich.console import Console, Group, group
@@ -15,10 +16,8 @@ from rich.text import Text
 
 from invokeai.version import __version__
 
-INVOKE_AI_SRC="https://github.com/invoke-ai/InvokeAI/archive"
-INVOKE_AI_TAG="https://github.com/invoke-ai/InvokeAI/archive/refs/tags"
-INVOKE_AI_BRANCH="https://github.com/invoke-ai/InvokeAI/archive/refs/heads"
-INVOKE_AI_REL="https://api.github.com/repos/invoke-ai/InvokeAI/releases"
+INVOKE_AI_SRC = "https://github.com/invoke-ai/InvokeAI/archive"
+INVOKE_AI_REL = "https://api.github.com/repos/invoke-ai/InvokeAI/releases"
 
 OS = platform.uname().system
 ARCH = platform.uname().machine
@@ -29,22 +28,22 @@ if OS == "Windows":
 else:
     console = Console(style=Style(color="grey74", bgcolor="grey19"))
 
-def get_versions()->dict:
+
+def get_versions() -> dict:
     return requests.get(url=INVOKE_AI_REL).json()
 
+
 def welcome(versions: dict):
-    
     @group()
     def text():
-        yield f'InvokeAI Version: [bold yellow]{__version__}'
-        yield ''
-        yield 'This script will update InvokeAI to the latest release, or to a development version of your choice.'
-        yield ''
-        yield '[bold yellow]Options:'
-        yield f'''[1] Update to the latest official release ([italic]{versions[0]['tag_name']}[/italic])
+        yield f"InvokeAI Version: [bold yellow]{__version__}"
+        yield ""
+        yield "This script will update InvokeAI to the latest release, or to a development version of your choice."
+        yield ""
+        yield "[bold yellow]Options:"
+        yield f"""[1] Update to the latest official release ([italic]{versions[0]['tag_name']}[/italic])
 [2] Update to the bleeding-edge development version ([italic]main[/italic])
-[3] Manually enter the [bold]tag name[/bold] for the version you wish to update to
-[4] Manually enter the [bold]branch name[/bold] for the version you wish to update to'''        
+[3] Manually enter the tag or branch name you wish to update"""
 
     console.rule()
     print(
@@ -60,41 +59,33 @@ def welcome(versions: dict):
     )
     console.line()
 
+
 def main():
     versions = get_versions()
     welcome(versions)
 
     tag = None
-    branch = None
-    release = None
-    choice = Prompt.ask('Choice:',choices=['1','2','3','4'],default='1')
-    
-    if choice=='1':
-        release = versions[0]['tag_name']
-    elif choice=='2':
-        release = 'main'
-    elif choice=='3':
-        tag = Prompt.ask('Enter an InvokeAI tag name')
-    elif choice=='4':
-        branch = Prompt.ask('Enter an InvokeAI branch name')
+    choice = Prompt.ask("Choice:", choices=["1", "2", "3"], default="1")
 
-    print(f':crossed_fingers: Upgrading to [yellow]{tag if tag else release}[/yellow]')
-    if release:
-        cmd = f'pip install {INVOKE_AI_SRC}/{release}.zip --use-pep517 --upgrade'
-    elif tag:
-        cmd = f'pip install {INVOKE_AI_TAG}/{tag}.zip --use-pep517 --upgrade'
+    if choice == "1":
+        tag = versions[0]["tag_name"]
+    elif choice == "2":
+        tag = "main"
+    elif choice == "3":
+        tag = Prompt.ask("Enter an InvokeAI tag or branch name")
+
+    print(f":crossed_fingers: Upgrading to [yellow]{tag}[/yellow]")
+    cmd = f"pip install {INVOKE_AI_SRC}/{tag}.zip --use-pep517"
+    print("")
+    print("")
+    if os.system(cmd) == 0:
+        print(f":heavy_check_mark: Upgrade successful")
     else:
-        cmd = f'pip install {INVOKE_AI_BRANCH}/{branch}.zip --use-pep517 --upgrade'
-    print('')
-    print('')
-    if os.system(cmd)==0:
-        print(f':heavy_check_mark: Upgrade successful')
-    else:
-        print(f':exclamation: [bold red]Upgrade failed[/red bold]')
-    
+        print(f":exclamation: [bold red]Upgrade failed[/red bold]")
+
+
 if __name__ == "__main__":
     try:
         main()
     except KeyboardInterrupt:
         pass
-

invokeai/frontend/web/index.d.ts

@@ -81,7 +81,6 @@ interface InvokeProps extends PropsWithChildren {
   disabledTabs?: InvokeTabName[];
   token?: string;
   shouldTransformUrls?: boolean;
-  shouldFetchImages?: boolean;
 }
 
 declare function Invoke(props: InvokeProps): JSX.Element;

invokeai/frontend/web/package.json

@@ -6,7 +6,6 @@
     "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",
@@ -54,7 +53,6 @@
     "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",

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": "Hochladen",
+        "upload": "Upload",
         "close": "Schließen",
         "load": "Laden",
         "statusConnected": "Verbunden",
@@ -41,34 +41,12 @@
         "statusUpscaling": "Hochskalierung",
         "statusUpscalingESRGAN": "Hochskalierung (ESRGAN)",
         "statusLoadingModel": "Laden des Modells",
-        "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"
+        "statusModelChanged": "Modell Geändert"
     },
     "gallery": {
         "generations": "Erzeugungen",
         "showGenerations": "Zeige Erzeugnisse",
-        "uploads": "Hochgelades",
+        "uploads": "Uploads",
         "showUploads": "Zeige Uploads",
         "galleryImageSize": "Bildgröße",
         "galleryImageResetSize": "Größe zurücksetzen",
@@ -334,11 +312,7 @@
         "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.",
-        "customConfig": "Benutzerdefinierte Konfiguration",
-        "invokeRoot": "InvokeAI Ordner",
-        "formMessageDiffusersVAELocationDesc": "Falls nicht angegeben, sucht InvokeAI nach der VAE-Datei innerhalb des oben angegebenen Modell Speicherortes.",
-        "checkpointModels": "Kontrollpunkte"
+        "deleteMsg2": "Dadurch wird die Modellprüfpunktdatei nicht von Ihrer Festplatte gelöscht. Sie können sie bei Bedarf erneut hinzufügen."
     },
     "parameters": {
         "images": "Bilder",
@@ -396,10 +370,7 @@
         "useInitImg": "Ausgangsbild verwenden",
         "deleteImage": "Bild löschen",
         "initialImage": "Ursprüngliches Bild",
-        "showOptionsPanel": "Optionsleiste zeigen",
-        "cancel": {
-            "setType": "Abbruchart festlegen"
-        }
+        "showOptionsPanel": "Optionsleiste zeigen"
     },
     "settings": {
         "displayInProgress": "Bilder in Bearbeitung anzeigen",
@@ -518,25 +489,5 @@
         "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": "Exit Viewer",
+        "exitViewer": "ExitViewer",
         "zoomIn": "Zoom In",
         "zoomOut": "Zoom Out",
         "rotateCounterClockwise": "Rotate Counter-Clockwise",
@@ -19,8 +19,7 @@
         "toggleAutoscroll": "Toggle autoscroll",
         "toggleLogViewer": "Toggle Log Viewer",
         "showGallery": "Show Gallery",
-        "showOptionsPanel": "Show Options Panel",
-        "menu": "Menu"
+        "showOptionsPanel": "Show Options Panel"
     },
     "common": {
         "hotkeysLabel": "Hotkeys",

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

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

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

@@ -1,122 +0,0 @@
-{
-    "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

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

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

@@ -37,43 +37,7 @@
         "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",
-        "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"
+        "statusModelChanged": "モデルを変更"
     },
     "gallery": {
         "uploads": "アップロード",
@@ -82,14 +46,11 @@
         "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": "1カラムレイアウト",
+        "singleColumnLayout": "シングルカラムレイアウト",
         "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",
-        "generations": "生成",
-        "showGenerations": "生成過程を見る",
-        "autoSwitchNewImages": "新しい画像に自動切替"
+        "noImagesInGallery": "ギャラリーに画像がありません"
     },
     "hotkeys": {
         "keyboardShortcuts": "キーボードショートカット",
@@ -98,16 +59,14 @@
         "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",
-            "title": "Invoke"
+            "desc": "画像を生成"
         },
         "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",
-            "title": "プロジェクトにフォーカス"
+            "desc": "プロンプトテキストボックスにフォーカス"
         },
         "toggleOptions": {
             "title": "オプションパネルのトグル",
@@ -451,27 +410,5 @@
         "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

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

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

@@ -62,18 +62,7 @@
         "statusConvertingModel": "Omzetten van model",
         "statusModelConverted": "Model omgezet",
         "statusMergingModels": "Samenvoegen van modellen",
-        "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"
+        "statusMergedModels": "Modellen samengevoegd"
     },
     "gallery": {
         "generations": "Gegenereerde afbeeldingen",
@@ -312,7 +301,7 @@
         "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",
@@ -402,13 +391,7 @@
         "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",
-        "v2_base": "v2 (512px)",
-        "v2_768": "v2 (768px)",
-        "none": "geen",
-        "addDifference": "Voeg verschil toe",
-        "scanForModels": "Scan naar modellen",
-        "pickModelType": "Kies modelsoort"
+        "weightedSum": "Gewogen som"
     },
     "parameters": {
         "images": "Afbeeldingen",
@@ -578,7 +561,7 @@
         "autoSaveToGallery": "Bewaar automatisch naar galerij",
         "saveBoxRegionOnly": "Bewaar alleen tekengebied",
         "limitStrokesToBox": "Beperk streken tot tekenvak",
-        "showCanvasDebugInfo": "Toon aanvullende canvasgegevens",
+        "showCanvasDebugInfo": "Toon foutopsporingsgegevens canvas",
         "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.",
@@ -604,27 +587,5 @@
         "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": "Единый холст",
+        "unifiedCanvas": "Универсальный холст",
         "nodes": "Ноды",
         "langRussian": "Русский",
         "nodesDesc": "Cистема генерации изображений на основе нодов (узлов) уже разрабатывается. Следите за новостями об этой замечательной функции.",
@@ -53,28 +53,7 @@
         "loading": "Загрузка",
         "loadingInvokeAI": "Загрузка Invoke AI",
         "back": "Назад",
-        "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"
+        "statusConvertingModel": "Конвертация модели"
     },
     "gallery": {
         "generations": "Генерации",
@@ -93,11 +72,11 @@
         "noImagesInGallery": "Изображений нет"
     },
     "hotkeys": {
-        "keyboardShortcuts": "Горячие клавиши",
+        "keyboardShortcuts": "Клавиатурные сокращения",
         "appHotkeys": "Горячие клавиши приложения",
         "generalHotkeys": "Общие горячие клавиши",
         "galleryHotkeys": "Горячие клавиши галереи",
-        "unifiedCanvasHotkeys": "Горячие клавиши Единого холста",
+        "unifiedCanvasHotkeys": "Горячие клавиши универсального холста",
         "invoke": {
             "title": "Invoke",
             "desc": "Сгенерировать изображение"
@@ -287,12 +266,12 @@
             "desc": "Сбросить вид холста"
         },
         "previousStagingImage": {
-            "title": "Предыдущее изображение",
-            "desc": "Предыдущая область изображения"
+            "title": "Previous Staging Image",
+            "desc": "Предыдущее изображение"
         },
         "nextStagingImage": {
-            "title": "Следующее изображение",
-            "desc": "Следующая область изображения"
+            "title": "Next Staging Image",
+            "desc": "Следующее изображение"
         },
         "acceptStagingImage": {
             "title": "Принять изображение",
@@ -374,42 +353,7 @@
         "modelConverted": "Модель преобразована",
         "invokeRoot": "Каталог InvokeAI",
         "modelsMerged": "Модели объединены",
-        "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)"
+        "mergeModels": "Объединить модели"
     },
     "parameters": {
         "images": "Изображения",
@@ -436,7 +380,7 @@
         "scale": "Масштаб",
         "otherOptions": "Другие параметры",
         "seamlessTiling": "Бесшовный узор",
-        "hiresOptim": "Оптимизация High Res",
+        "hiresOptim": "Высокое разрешение",
         "imageFit": "Уместить изображение",
         "codeformerFidelity": "Точность",
         "seamSize": "Размер шва",
@@ -453,11 +397,11 @@
         "infillScalingHeader": "Заполнение и масштабирование",
         "img2imgStrength": "Сила обработки img2img",
         "toggleLoopback": "Зациклить обработку",
-        "invoke": "Invoke",
+        "invoke": "Вызвать",
         "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 Единый холст",
+        "sendToUnifiedCanvas": "Отправить на холст",
         "copyImageToLink": "Скопировать ссылку",
         "downloadImage": "Скачать",
         "openInViewer": "Открыть в просмотрщике",
@@ -469,24 +413,7 @@
         "info": "Метаданные",
         "deleteImage": "Удалить изображение",
         "initialImage": "Исходное изображение",
-        "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"
+        "showOptionsPanel": "Показать панель настроек"
     },
     "settings": {
         "models": "Модели",
@@ -496,11 +423,10 @@
         "displayHelpIcons": "Показывать значки подсказок",
         "useCanvasBeta": "Показывать инструменты слева (Beta UI)",
         "enableImageDebugging": "Включить отладку",
-        "resetWebUI": "Сброс настроек Web UI",
+        "resetWebUI": "Вернуть умолчания",
         "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.",
-        "useSlidersForAll": "Использовать ползунки для всех параметров"
+        "resetComplete": "Интерфейс сброшен. Обновите эту страницу."
     },
     "toast": {
         "tempFoldersEmptied": "Временная папка очищена",
@@ -515,7 +441,7 @@
         "imageSavedToGallery": "Изображение сохранено в галерею",
         "canvasMerged": "Холст объединен",
         "sentToImageToImage": "Отправить в img2img",
-        "sentToUnifiedCanvas": "Отправлено на Единый холст",
+        "sentToUnifiedCanvas": "Отправить на холст",
         "parametersSet": "Параметры заданы",
         "parametersNotSet": "Параметры не заданы",
         "parametersNotSetDesc": "Не найдены метаданные изображения.",
@@ -532,11 +458,7 @@
         "metadataLoadFailed": "Не удалось загрузить метаданные",
         "initialImageSet": "Исходное изображение задано",
         "initialImageNotSet": "Исходное изображение не задано",
-        "initialImageNotSetDesc": "Не получилось загрузить исходное изображение",
-        "serverError": "Ошибка сервера",
-        "disconnected": "Отключено от сервера",
-        "connected": "Подключено к серверу",
-        "canceled": "Обработка отменена"
+        "initialImageNotSetDesc": "Не получилось загрузить исходное изображение"
     },
     "tooltip": {
         "feature": {
@@ -585,7 +507,7 @@
         "autoSaveToGallery": "Автосохранение в галерее",
         "saveBoxRegionOnly": "Сохранять только выделение",
         "limitStrokesToBox": "Ограничить штрихи выделением",
-        "showCanvasDebugInfo": "Показать доп. информацию о холсте",
+        "showCanvasDebugInfo": "Показать отладку холста",
         "clearCanvasHistory": "Очистить историю холста",
         "clearHistory": "Очистить историю",
         "clearCanvasHistoryMessage": "Очистка истории холста оставляет текущий холст нетронутым, но удаляет историю отмен и повторов.",
@@ -613,26 +535,6 @@
         "betaPreserveMasked": "Сохранять маскируемую область"
     },
     "accessibility": {
-        "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"
+        "modelSelect": "Выбор модели"
     }
 }

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

@@ -1,254 +0,0 @@
-{
-    "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

@@ -1,64 +0,0 @@
-{
-    "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",
@@ -43,38 +43,7 @@
         "statusUpscaling": "Збільшення",
         "statusUpscalingESRGAN": "Збільшення (ESRGAN)",
         "statusLoadingModel": "Завантаження моделі",
-        "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"
+        "statusModelChanged": "Модель змінено"
     },
     "gallery": {
         "generations": "Генерації",
@@ -315,15 +284,15 @@
         "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",
@@ -350,66 +319,7 @@
         "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.",
-        "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"
+        "deleteMsg2": "Це не призведе до видалення файлу моделі з диску. Позніше ви можете додати його знову."
     },
     "parameters": {
         "images": "Зображення",
@@ -436,7 +346,7 @@
         "scale": "Масштаб",
         "otherOptions": "інші параметри",
         "seamlessTiling": "Безшовний узор",
-        "hiresOptim": "Оптимізація High Res",
+        "hiresOptim": "Висока роздільна здатність",
         "imageFit": "Вмістити зображення",
         "codeformerFidelity": "Точність",
         "seamSize": "Размір шву",
@@ -469,24 +379,7 @@
         "info": "Метадані",
         "deleteImage": "Видалити зображення",
         "initialImage": "Початкове зображення",
-        "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"
+        "showOptionsPanel": "Показати панель налаштувань"
     },
     "settings": {
         "models": "Моделі",
@@ -499,8 +392,7 @@
         "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.",
-        "useSlidersForAll": "Використовувати повзунки для всіх параметрів"
+        "resetComplete": "Інтерфейс скинуто. Оновіть цю сторінку."
     },
     "toast": {
         "tempFoldersEmptied": "Тимчасова папка очищена",
@@ -518,25 +410,21 @@
         "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",
-        "serverError": "Помилка сервера",
-        "disconnected": "Відключено від сервера",
-        "connected": "Підключено до сервера",
-        "canceled": "Обробку скасовано"
+        "initialImageNotSetDesc": "Не вдалося завантажити початкове зображення"
     },
     "tooltip": {
         "feature": {
@@ -585,10 +473,10 @@
         "autoSaveToGallery": "Автозбереження до галереї",
         "saveBoxRegionOnly": "Зберiгати тiльки видiлення",
         "limitStrokesToBox": "Обмежити штрихи виділенням",
-        "showCanvasDebugInfo": "Показати дод. інформацію про полотно",
+        "showCanvasDebugInfo": "Показати налаштування полотна",
         "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",
@@ -611,28 +499,5 @@
         "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

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

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

@@ -481,22 +481,5 @@
         "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

@@ -18,7 +18,6 @@ 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();
 
@@ -27,7 +26,6 @@ interface Props extends PropsWithChildren {
     disabledPanels: string[];
     disabledTabs: InvokeTabName[];
     shouldTransformUrls?: boolean;
-    shouldFetchImages: boolean;
   };
 }
 
@@ -52,10 +50,6 @@ const App = (props: Props) => {
     );
   }, [dispatch, props.options.shouldTransformUrls]);
 
-  useEffect(() => {
-    dispatch(setShouldFetchImages(props.options.shouldFetchImages));
-  }, [dispatch, props.options.shouldFetchImages]);
-
   useEffect(() => {
     setColorMode(['light'].includes(currentTheme) ? 'light' : 'dark');
   }, [setColorMode, currentTheme]);
@@ -73,12 +67,7 @@ const App = (props: Props) => {
           h={APP_HEIGHT}
         >
           {props.children || <SiteHeader />}
-          <Flex
-            gap={4}
-            w={{ base: '100vw', xl: 'full' }}
-            h="full"
-            flexDir={{ base: 'column', xl: 'row' }}
-          >
+          <Flex gap={4} w="full" h="full">
             <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(64)).map(
-  (_x, i) => (i + 1) * 64
+export const WIDTHS: Array<number> = Array.from(Array(65)).map(
+  (_x, i) => i * 64
 );
 
 // Valid image heights
-export const HEIGHTS: Array<number> = Array.from(Array(64)).map(
-  (_x, i) => (i + 1) * 64
+export const HEIGHTS: Array<number> = Array.from(Array(65)).map(
+  (_x, i) => i * 64
 );
 
 // Valid upscaling levels
@@ -60,5 +60,3 @@ 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/common/hooks/useResolution.ts

@@ -1,18 +0,0 @@
-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

@@ -1,119 +0,0 @@
-/**
- * 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/parseMetadata.ts

@@ -1,169 +0,0 @@
-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

@@ -30,7 +30,6 @@ interface Props extends PropsWithChildren {
   disabledTabs?: InvokeTabName[];
   token?: string;
   shouldTransformUrls?: boolean;
-  shouldFetchImages?: boolean;
 }
 
 export default function Component({
@@ -40,7 +39,6 @@ export default function Component({
   token,
   children,
   shouldTransformUrls,
-  shouldFetchImages = false,
 }: Props) {
   useEffect(() => {
     // configure API client token
@@ -72,12 +70,7 @@ export default function Component({
           <React.Suspense fallback={<Loading showText />}>
             <ThemeLocaleProvider>
               <App
-                options={{
-                  disabledPanels,
-                  disabledTabs,
-                  shouldTransformUrls,
-                  shouldFetchImages,
-                }}
+                options={{ disabledPanels, disabledTabs, shouldTransformUrls }}
               >
                 {children}
               </App>

invokeai/frontend/web/src/features/gallery/components/CurrentImageButtons.tsx

@@ -101,8 +101,8 @@ const currentImageButtonsSelector = createSelector(
       shouldShowImageDetails,
       activeTabName,
       isLightboxOpen,
-      shouldHidePreview,
       selectedImage,
+      shouldHidePreview,
     };
   },
   {
@@ -132,8 +132,8 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
     // currentImage,
     isLightboxOpen,
     activeTabName,
-    shouldHidePreview,
     selectedImage,
+    shouldHidePreview,
   } = useAppSelector(currentImageButtonsSelector);
   const { getUrl, shouldTransformUrls } = useGetUrl();
 
@@ -151,17 +151,11 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
   };
 
   const handleCopyImage = async () => {
-    if (!selectedImage?.url) {
-      return;
-    }
+    if (!selectedImage) return;
 
-    const url = getUrl(selectedImage.url);
-
-    if (!url) {
-      return;
-    }
-
-    const blob = await fetch(url).then((res) => res.blob());
+    const blob = await fetch(getUrl(selectedImage.url)).then((res) =>
+      res.blob()
+    );
     const data = [new ClipboardItem({ [blob.type]: blob })];
 
     await navigator.clipboard.write(data);
@@ -181,10 +175,6 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
         : window.location.toString() + selectedImage.url
       : '';
 
-    if (!url) {
-      return;
-    }
-
     navigator.clipboard.writeText(url).then(() => {
       toast({
         title: t('toast.imageLinkCopied'),
@@ -435,10 +425,9 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
   return (
     <Flex
       sx={{
-        flexWrap: 'wrap',
         justifyContent: 'center',
         alignItems: 'center',
-        gap: 2,
+        columnGap: '0.5em',
       }}
       {...props}
     >
@@ -487,7 +476,7 @@ const CurrentImageButtons = (props: CurrentImageButtonsProps) => {
               {t('parameters.copyImageToLink')}
             </IAIButton>
 
-            <Link download={true} href={getUrl(selectedImage?.url)}>
+            <Link download={true} href={getUrl(selectedImage!.url)}>
               <IAIButton leftIcon={<FaDownload />} size="sm" w="100%">
                 {t('parameters.downloadImage')}
               </IAIButton>

invokeai/frontend/web/src/features/gallery/components/CurrentImageDisplay.tsx

@@ -1,7 +1,6 @@
 import { Flex, Icon } from '@chakra-ui/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/storeHooks';
-import { systemSelector } from 'features/system/store/systemSelectors';
 import { isEqual } from 'lodash';
 
 import { MdPhoto } from 'react-icons/md';
@@ -13,12 +12,12 @@ import CurrentImageButtons from './CurrentImageButtons';
 import CurrentImagePreview from './CurrentImagePreview';
 
 export const currentImageDisplaySelector = createSelector(
-  [systemSelector, selectedImageSelector],
-  (system, selectedImage) => {
-    const { progressImage } = system;
+  [gallerySelector, selectedImageSelector],
+  (gallery, selectedImage) => {
+    const { currentImage, intermediateImage } = gallery;
 
     return {
-      hasAnImageToDisplay: selectedImage || progressImage,
+      hasAnImageToDisplay: selectedImage || intermediateImage,
     };
   },
   {

invokeai/frontend/web/src/features/gallery/components/CurrentImageHidden.tsx

@@ -13,7 +13,7 @@ const CurrentImageHidden = () => {
         color: 'base.400',
       }}
     >
-      <FaEyeSlash fontSize="25vh" />
+      <FaEyeSlash size={'30vh'} />
     </Flex>
   );
 };

invokeai/frontend/web/src/features/gallery/components/CurrentImagePreview.tsx

@@ -41,8 +41,8 @@ export const imagesSelector = createSelector(
 
     return {
       shouldShowImageDetails,
-      shouldHidePreview,
       imageToDisplay,
+      shouldHidePreview,
     };
   },
   {

invokeai/frontend/web/src/features/gallery/components/ImageGalleryContent.tsx

@@ -254,7 +254,7 @@ const ImageGalleryContent = () => {
                   const isSelected = currentImageUuid === name;
                   return (
                     <HoverableImage
-                      key={`${name}-${image.thumbnail}`}
+                      key={name}
                       image={image}
                       isSelected={isSelected}
                     />

invokeai/frontend/web/src/features/gallery/components/ImageGalleryPanel.tsx

@@ -26,8 +26,6 @@ import {
 import { isStagingSelector } from 'features/canvas/store/canvasSelectors';
 import { requestCanvasRescale } from 'features/canvas/store/thunks/requestCanvasScale';
 import { lightboxSelector } from 'features/lightbox/store/lightboxSelectors';
-import useResolution from 'common/hooks/useResolution';
-import { Flex } from '@chakra-ui/react';
 
 const GALLERY_TAB_WIDTHS: Record<
   InvokeTabName,
@@ -99,8 +97,6 @@ export default function ImageGalleryPanel() {
     shouldPinGallery && dispatch(requestCanvasRescale());
   };
 
-  const resolution = useResolution();
-
   useHotkeys(
     'g',
     () => {
@@ -183,53 +179,25 @@ export default function ImageGalleryPanel() {
     [galleryImageMinimumWidth]
   );
 
-  const calcGalleryMinHeight = () => {
-    if (resolution === 'desktop') return;
-    return 300;
-  };
-
-  const imageGalleryContent = () => {
-    return (
-      <Flex
-        w="100vw"
-        h={{ base: 300, xl: '100vh' }}
-        paddingRight={{ base: 8, xl: 0 }}
-        paddingBottom={{ base: 4, xl: 0 }}
-      >
-        <ImageGalleryContent />
-      </Flex>
-    );
-  };
-
-  const resizableImageGalleryContent = () => {
-    return (
-      <ResizableDrawer
-        direction="right"
-        isResizable={isResizable || !shouldPinGallery}
-        isOpen={shouldShowGallery}
-        onClose={handleCloseGallery}
-        isPinned={shouldPinGallery && !isLightboxOpen}
-        minWidth={
-          shouldPinGallery
-            ? GALLERY_TAB_WIDTHS[activeTabName].galleryMinWidth
-            : 200
-        }
-        maxWidth={
-          shouldPinGallery
-            ? GALLERY_TAB_WIDTHS[activeTabName].galleryMaxWidth
-            : undefined
-        }
-        minHeight={calcGalleryMinHeight()}
-      >
-        <ImageGalleryContent />
-      </ResizableDrawer>
-    );
-  };
-
-  const renderImageGallery = () => {
-    if (['mobile', 'tablet'].includes(resolution)) return imageGalleryContent();
-    return resizableImageGalleryContent();
-  };
-
-  return renderImageGallery();
+  return (
+    <ResizableDrawer
+      direction="right"
+      isResizable={isResizable || !shouldPinGallery}
+      isOpen={shouldShowGallery}
+      onClose={handleCloseGallery}
+      isPinned={shouldPinGallery && !isLightboxOpen}
+      minWidth={
+        shouldPinGallery
+          ? GALLERY_TAB_WIDTHS[activeTabName].galleryMinWidth
+          : 200
+      }
+      maxWidth={
+        shouldPinGallery
+          ? GALLERY_TAB_WIDTHS[activeTabName].galleryMaxWidth
+          : undefined
+      }
+    >
+      <ImageGalleryContent />
+    </ResizableDrawer>
+  );
 }

invokeai/frontend/web/src/features/gallery/components/ImageMetaDataViewer/ImageMetadataViewer.tsx

@@ -192,21 +192,21 @@ const ImageMetadataViewer = memo(({ image }: ImageMetadataViewerProps) => {
             <MetadataItem
               label="Seed"
               value={node.seed}
-              onClick={() => dispatch(setSeed(Number(node.seed)))}
+              onClick={() => dispatch(setSeed(node.seed))}
             />
           )}
           {node.threshold !== undefined && (
             <MetadataItem
               label="Noise Threshold"
               value={node.threshold}
-              onClick={() => dispatch(setThreshold(Number(node.threshold)))}
+              onClick={() => dispatch(setThreshold(node.threshold))}
             />
           )}
           {node.perlin !== undefined && (
             <MetadataItem
               label="Perlin Noise"
               value={node.perlin}
-              onClick={() => dispatch(setPerlin(Number(node.perlin)))}
+              onClick={() => dispatch(setPerlin(node.perlin))}
             />
           )}
           {node.scheduler && (
@@ -220,14 +220,14 @@ const ImageMetadataViewer = memo(({ image }: ImageMetadataViewerProps) => {
             <MetadataItem
               label="Steps"
               value={node.steps}
-              onClick={() => dispatch(setSteps(Number(node.steps)))}
+              onClick={() => dispatch(setSteps(node.steps))}
             />
           )}
           {node.cfg_scale !== undefined && (
             <MetadataItem
               label="CFG scale"
               value={node.cfg_scale}
-              onClick={() => dispatch(setCfgScale(Number(node.cfg_scale)))}
+              onClick={() => dispatch(setCfgScale(node.cfg_scale))}
             />
           )}
           {node.variations && node.variations.length > 0 && (
@@ -257,14 +257,14 @@ const ImageMetadataViewer = memo(({ image }: ImageMetadataViewerProps) => {
             <MetadataItem
               label="Width"
               value={node.width}
-              onClick={() => dispatch(setWidth(Number(node.width)))}
+              onClick={() => dispatch(setWidth(node.width))}
             />
           )}
           {node.height && (
             <MetadataItem
               label="Height"
               value={node.height}
-              onClick={() => dispatch(setHeight(Number(node.height)))}
+              onClick={() => dispatch(setHeight(node.height))}
             />
           )}
           {/* {init_image_path && (
@@ -279,9 +279,7 @@ const ImageMetadataViewer = memo(({ image }: ImageMetadataViewerProps) => {
             <MetadataItem
               label="Image to image strength"
               value={node.strength}
-              onClick={() =>
-                dispatch(setImg2imgStrength(Number(node.strength)))
-              }
+              onClick={() => dispatch(setImg2imgStrength(node.strength))}
             />
           )}
           {node.fit && (

invokeai/frontend/web/src/features/gallery/store/resultsSlice.ts

@@ -1,8 +1,4 @@
-import {
-  PayloadAction,
-  createEntityAdapter,
-  createSlice,
-} from '@reduxjs/toolkit';
+import { createEntityAdapter, createSlice } from '@reduxjs/toolkit';
 import { Image } from 'app/invokeai';
 import { invocationComplete } from 'services/events/actions';
 
@@ -17,7 +13,6 @@ import {
   extractTimestampFromImageName,
 } from 'services/util/deserializeImageField';
 import { deserializeImageResponse } from 'services/util/deserializeImageResponse';
-import { imageReceived, thumbnailReceived } from 'services/thunks/image';
 
 // use `createEntityAdapter` to create a slice for results images
 // https://redux-toolkit.js.org/api/createEntityAdapter#overview
@@ -39,9 +34,12 @@ type AdditionalResultsState = {
   pages: number; // the total number of pages available
   isLoading: boolean; // whether we are loading more images or not, mostly a placeholder
   nextPage: number; // the next page to request
-  shouldFetchImages: boolean; // whether we need to re-fetch images or not
 };
 
+// export type ResultsState = ReturnType<
+//   typeof resultsAdapter.getInitialState<AdditionalResultsState>
+// >;
+
 export const initialResultsState =
   resultsAdapter.getInitialState<AdditionalResultsState>({
     // provide the additional initial state
@@ -49,7 +47,6 @@ export const initialResultsState =
     pages: 0,
     isLoading: false,
     nextPage: 0,
-    shouldFetchImages: false,
   });
 
 export type ResultsState = typeof initialResultsState;
@@ -64,10 +61,6 @@ const resultsSlice = createSlice({
     // here we just use the function itself as the reducer. we'll call this on `invocation_complete`
     // to add a single result
     resultAdded: resultsAdapter.upsertOne,
-
-    setShouldFetchImages: (state, action: PayloadAction<boolean>) => {
-      state.shouldFetchImages = action.payload;
-    },
   },
   extraReducers: (builder) => {
     // here we can respond to a fulfilled call of the `getNextResultsPage` thunk
@@ -104,15 +97,12 @@ const resultsSlice = createSlice({
      */
     builder.addCase(invocationComplete, (state, action) => {
       const { data } = action.payload;
-      const { result, node, graph_execution_state_id } = data;
+      const { result, invocation, graph_execution_state_id } = data;
 
       if (isImageOutput(result)) {
         const name = result.image.image_name;
         const type = result.image.image_type;
-        // if we need to refetch, set URLs to placeholder for now
-        const { url, thumbnail } = state.shouldFetchImages
-          ? { url: '', thumbnail: '' }
-          : buildImageUrls(type, name);
+        const { url, thumbnail } = buildImageUrls(type, name);
 
         const timestamp = extractTimestampFromImageName(name);
 
@@ -125,9 +115,10 @@ const resultsSlice = createSlice({
             created: timestamp,
             width: result.width, // TODO: add tese dimensions
             height: result.height,
+            mode: result.mode,
             invokeai: {
               session_id: graph_execution_state_id,
-              ...(node ? { node } : {}),
+              invocation,
             },
           },
         };
@@ -135,30 +126,6 @@ const resultsSlice = createSlice({
         resultsAdapter.addOne(state, image);
       }
     });
-
-    builder.addCase(imageReceived.fulfilled, (state, action) => {
-      const { imagePath } = action.payload;
-      const { imageName } = action.meta.arg;
-
-      resultsAdapter.updateOne(state, {
-        id: imageName,
-        changes: {
-          url: imagePath,
-        },
-      });
-    });
-
-    builder.addCase(thumbnailReceived.fulfilled, (state, action) => {
-      const { thumbnailPath } = action.payload;
-      const { imageName } = action.meta.arg;
-
-      resultsAdapter.updateOne(state, {
-        id: imageName,
-        changes: {
-          thumbnail: thumbnailPath,
-        },
-      });
-    });
   },
 });
 
@@ -172,6 +139,6 @@ export const {
   selectTotal: selectResultsTotal,
 } = resultsAdapter.getSelectors<RootState>((state) => state.results);
 
-export const { resultAdded, setShouldFetchImages } = resultsSlice.actions;
+export const { resultAdded } = resultsSlice.actions;
 
 export default resultsSlice.reducer;

invokeai/frontend/web/src/features/gallery/store/uploadsSlice.ts

@@ -66,8 +66,16 @@ const uploadsSlice = createSlice({
      */
     builder.addCase(imageUploaded.fulfilled, (state, action) => {
       const { location, response } = action.payload;
+      const { image_name, image_url, image_type, metadata, thumbnail_url } =
+        response;
 
-      const uploadedImage = deserializeImageResponse(response);
+      const uploadedImage: Image = {
+        name: image_name,
+        url: image_url,
+        thumbnail: thumbnail_url,
+        type: 'uploads',
+        metadata,
+      };
 
       uploadsAdapter.addOne(state, uploadedImage);
     });

invokeai/frontend/web/src/features/nodes/components/AddNodeMenu.tsx

@@ -1,7 +1,7 @@
 import { v4 as uuidv4 } from 'uuid';
 
 import 'reactflow/dist/style.css';
-import { memo, useCallback } from 'react';
+import { useCallback } from 'react';
 import {
   Tooltip,
   Menu,
@@ -10,7 +10,7 @@ import {
   MenuItem,
   IconButton,
 } from '@chakra-ui/react';
-import { FaEllipsisV, FaPlus } from 'react-icons/fa';
+import { FaPlus } from 'react-icons/fa';
 import { useAppDispatch, useAppSelector } from 'app/storeHooks';
 import { nodeAdded } from '../store/nodesSlice';
 import { cloneDeep, map } from 'lodash';
@@ -18,10 +18,8 @@ import { RootState } from 'app/store';
 import { useBuildInvocation } from '../hooks/useBuildInvocation';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/hooks/useToastWatcher';
-import { IAIIconButton } from 'exports';
-import { AnyInvocationType } from 'services/events/types';
 
-const AddNodeMenu = () => {
+export const AddNodeMenu = () => {
   const dispatch = useAppDispatch();
 
   const invocationTemplates = useAppSelector(
@@ -31,7 +29,7 @@ const AddNodeMenu = () => {
   const buildInvocation = useBuildInvocation();
 
   const addNode = useCallback(
-    (nodeType: AnyInvocationType) => {
+    (nodeType: string) => {
       const invocation = buildInvocation(nodeType);
 
       if (!invocation) {
@@ -49,13 +47,9 @@ const AddNodeMenu = () => {
   );
 
   return (
-    <Menu isLazy>
-      <MenuButton
-        as={IAIIconButton}
-        aria-label="Add Node"
-        icon={<FaEllipsisV />}
-      />
-      <MenuList overflowY="scroll" height={400}>
+    <Menu>
+      <MenuButton as={IconButton} aria-label="Add Node" icon={<FaPlus />} />
+      <MenuList>
         {map(invocationTemplates, ({ title, description, type }, key) => {
           return (
             <Tooltip key={key} label={description} placement="end" hasArrow>
@@ -67,5 +61,3 @@ const AddNodeMenu = () => {
     </Menu>
   );
 };
-
-export default memo(AddNodeMenu);

invokeai/frontend/web/src/features/nodes/components/FieldHandle.tsx

@@ -1,5 +1,5 @@
 import { Tooltip } from '@chakra-ui/react';
-import { CSSProperties, memo, useMemo } from 'react';
+import { CSSProperties, useMemo } from 'react';
 import {
   Handle,
   Position,
@@ -19,11 +19,11 @@ const handleBaseStyles: CSSProperties = {
 };
 
 const inputHandleStyles: CSSProperties = {
-  left: '-1rem',
+  left: '-1.7rem',
 };
 
 const outputHandleStyles: CSSProperties = {
-  right: '-0.5rem',
+  right: '-1.7rem',
 };
 
 const requiredConnectionStyles: CSSProperties = {
@@ -38,12 +38,13 @@ type FieldHandleProps = {
   styles?: CSSProperties;
 };
 
-const FieldHandle = (props: FieldHandleProps) => {
+export const FieldHandle = (props: FieldHandleProps) => {
   const { nodeId, field, isValidConnection, handleType, styles } = props;
   const { name, title, type, description } = field;
 
   return (
     <Tooltip
+      key={name}
       label={type}
       placement={handleType === 'target' ? 'start' : 'end'}
       hasArrow
@@ -66,5 +67,3 @@ const FieldHandle = (props: FieldHandleProps) => {
     </Tooltip>
   );
 };
-
-export default memo(FieldHandle);

invokeai/frontend/web/src/features/nodes/components/FieldTypeLegend.tsx

@@ -1,25 +1,18 @@
 import 'reactflow/dist/style.css';
-import { Tooltip, Badge, Flex } from '@chakra-ui/react';
+import { Tooltip, Badge, HStack } from '@chakra-ui/react';
 import { map } from 'lodash';
 import { FIELDS } from '../types/constants';
-import { memo } from 'react';
 
-const FieldTypeLegend = () => {
+export const FieldTypeLegend = () => {
   return (
-    <Flex gap={2} flexDirection={{ base: 'column', xl: 'row' }}>
+    <HStack>
       {map(FIELDS, ({ title, description, color }, key) => (
         <Tooltip key={key} label={description}>
-          <Badge
-            colorScheme={color}
-            sx={{ userSelect: 'none' }}
-            textAlign="center"
-          >
+          <Badge colorScheme={color} sx={{ userSelect: 'none' }}>
             {title}
           </Badge>
         </Tooltip>
       ))}
-    </Flex>
+    </HStack>
   );
 };
-
-export default memo(FieldTypeLegend);

invokeai/frontend/web/src/features/nodes/components/Flow.tsx

@@ -1,11 +1,15 @@
 import {
   Background,
+  Controls,
+  MiniMap,
   OnConnect,
   OnEdgesChange,
   OnNodesChange,
   ReactFlow,
+  ConnectionLineType,
   OnConnectStart,
   OnConnectEnd,
+  Panel,
 } from 'reactflow';
 import { useAppDispatch, useAppSelector } from 'app/storeHooks';
 import { RootState } from 'app/store';
@@ -18,12 +22,10 @@ import {
 } from '../store/nodesSlice';
 import { useCallback } from 'react';
 import { InvocationComponent } from './InvocationComponent';
-import TopLeftPanel from './panels/TopLeftPanel';
-import TopRightPanel from './panels/TopRightPanel';
-import TopCenterPanel from './panels/TopCenterPanel';
-import BottomLeftPanel from './panels/BottomLeftPanel.tsx';
-import MinimapPanel from './panels/MinimapPanel';
-import NodeSearch from './search/NodeSearch';
+import { AddNodeMenu } from './AddNodeMenu';
+import { FieldTypeLegend } from './FieldTypeLegend';
+import { Button } from '@chakra-ui/react';
+import { nodesGraphBuilt } from 'services/thunks/session';
 
 const nodeTypes = { invocation: InvocationComponent };
 
@@ -60,8 +62,15 @@ export const Flow = () => {
     [dispatch]
   );
 
-  const onConnectEnd: OnConnectEnd = useCallback(() => {
-    dispatch(connectionEnded());
+  const onConnectEnd: OnConnectEnd = useCallback(
+    (event) => {
+      dispatch(connectionEnded());
+    },
+    [dispatch]
+  );
+
+  const handleInvoke = useCallback(() => {
+    dispatch(nodesGraphBuilt());
   }, [dispatch]);
 
   return (
@@ -78,13 +87,18 @@ export const Flow = () => {
         style: { strokeWidth: 2 },
       }}
     >
-      <NodeSearch />
-      {/* <TopLeftPanel /> */}
-      <TopCenterPanel />
-      <TopRightPanel />
-      <BottomLeftPanel />
+      <Panel position="top-left">
+        <AddNodeMenu />
+      </Panel>
+      <Panel position="top-center">
+        <Button onClick={handleInvoke}>Will it blend?</Button>
+      </Panel>
+      <Panel position="top-right">
+        <FieldTypeLegend />
+      </Panel>
       <Background />
-      <MinimapPanel />
+      <Controls />
+      <MiniMap nodeStrokeWidth={3} zoomable pannable />
     </ReactFlow>
   );
 };

invokeai/frontend/web/src/features/nodes/components/IAINode/IAINodeHeader.tsx

@@ -1,39 +0,0 @@
-import { Flex, Heading, Tooltip, Icon } from '@chakra-ui/react';
-import { InvocationTemplate } from 'features/nodes/types/types';
-import { memo, MutableRefObject } from 'react';
-import { FaInfoCircle } from 'react-icons/fa';
-
-interface IAINodeHeaderProps {
-  nodeId: string;
-  template: InvocationTemplate;
-}
-
-const IAINodeHeader = (props: IAINodeHeaderProps) => {
-  const { nodeId, template } = props;
-  return (
-    <Flex
-      borderTopRadius="md"
-      justifyContent="space-between"
-      background="base.700"
-      px={2}
-      py={1}
-      alignItems="center"
-    >
-      <Tooltip label={nodeId}>
-        <Heading size="xs" fontWeight={600} color="base.100">
-          {template.title}
-        </Heading>
-      </Tooltip>
-      <Tooltip
-        label={template.description}
-        placement="top"
-        hasArrow
-        shouldWrapChildren
-      >
-        <Icon color="base.300" as={FaInfoCircle} h="min-content" />
-      </Tooltip>
-    </Flex>
-  );
-};
-
-export default memo(IAINodeHeader);

invokeai/frontend/web/src/features/nodes/components/IAINode/IAINodeInputs.tsx

@@ -1,148 +0,0 @@
-import {
-  InputFieldTemplate,
-  InputFieldValue,
-  InvocationTemplate,
-} from 'features/nodes/types/types';
-import { memo, ReactNode, useCallback } from 'react';
-import { map } from 'lodash';
-import { useAppSelector } from 'app/storeHooks';
-import { RootState } from 'app/store';
-import {
-  Box,
-  Flex,
-  FormControl,
-  FormLabel,
-  HStack,
-  Tooltip,
-  Divider,
-} from '@chakra-ui/react';
-import FieldHandle from '../FieldHandle';
-import { useIsValidConnection } from 'features/nodes/hooks/useIsValidConnection';
-import InputFieldComponent from '../InputFieldComponent';
-import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
-
-interface IAINodeInputProps {
-  nodeId: string;
-
-  input: InputFieldValue;
-  template?: InputFieldTemplate | undefined;
-  connected: boolean;
-}
-
-function IAINodeInput(props: IAINodeInputProps) {
-  const { nodeId, input, template, connected } = props;
-  const isValidConnection = useIsValidConnection();
-
-  return (
-    <Box
-      position="relative"
-      borderColor={
-        !template
-          ? 'error.400'
-          : !connected &&
-            ['always', 'connectionOnly'].includes(
-              String(template?.inputRequirement)
-            ) &&
-            input.value === undefined
-          ? 'warning.400'
-          : undefined
-      }
-    >
-      <FormControl isDisabled={!template ? true : connected} pl={2}>
-        {!template ? (
-          <HStack justifyContent="space-between" alignItems="center">
-            <FormLabel>Unknown input: {input.name}</FormLabel>
-          </HStack>
-        ) : (
-          <>
-            <HStack justifyContent="space-between" alignItems="center">
-              <HStack>
-                <Tooltip
-                  label={template?.description}
-                  placement="top"
-                  hasArrow
-                  shouldWrapChildren
-                  openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
-                >
-                  <FormLabel>{template?.title}</FormLabel>
-                </Tooltip>
-              </HStack>
-              <InputFieldComponent
-                nodeId={nodeId}
-                field={input}
-                template={template}
-              />
-            </HStack>
-
-            {!['never', 'directOnly'].includes(
-              template?.inputRequirement ?? ''
-            ) && (
-              <FieldHandle
-                nodeId={nodeId}
-                field={template}
-                isValidConnection={isValidConnection}
-                handleType="target"
-              />
-            )}
-          </>
-        )}
-      </FormControl>
-    </Box>
-  );
-}
-
-interface IAINodeInputsProps {
-  nodeId: string;
-  template: InvocationTemplate;
-  inputs: Record<string, InputFieldValue>;
-}
-
-const IAINodeInputs = (props: IAINodeInputsProps) => {
-  const { nodeId, template, inputs } = props;
-
-  const edges = useAppSelector((state: RootState) => state.nodes.edges);
-
-  const renderIAINodeInputs = useCallback(() => {
-    const IAINodeInputsToRender: ReactNode[] = [];
-    const inputSockets = map(inputs);
-
-    inputSockets.forEach((inputSocket, index) => {
-      const inputTemplate = template.inputs[inputSocket.name];
-
-      const isConnected = Boolean(
-        edges.filter((connectedInput) => {
-          return (
-            connectedInput.target === nodeId &&
-            connectedInput.targetHandle === inputSocket.name
-          );
-        }).length
-      );
-
-      if (index < inputSockets.length) {
-        IAINodeInputsToRender.push(
-          <Divider key={`${inputSocket.id}.divider`} />
-        );
-      }
-
-      IAINodeInputsToRender.push(
-        <IAINodeInput
-          key={inputSocket.id}
-          nodeId={nodeId}
-          input={inputSocket}
-          template={inputTemplate}
-          connected={isConnected}
-        />
-      );
-    });
-
-    return (
-      <Flex flexDir="column" gap={2} p={2}>
-        {IAINodeInputsToRender}
-      </Flex>
-    );
-  }, [edges, inputs, nodeId, template.inputs]);
-
-  return renderIAINodeInputs();
-};
-
-export default memo(IAINodeInputs);

invokeai/frontend/web/src/features/nodes/components/IAINode/IAINodeOutputs.tsx

@@ -1,97 +0,0 @@
-import {
-  InvocationTemplate,
-  OutputFieldTemplate,
-  OutputFieldValue,
-} from 'features/nodes/types/types';
-import { memo, ReactNode, useCallback } from 'react';
-import { map } from 'lodash';
-import { useAppSelector } from 'app/storeHooks';
-import { RootState } from 'app/store';
-import { Box, Flex, FormControl, FormLabel, HStack } from '@chakra-ui/react';
-import FieldHandle from '../FieldHandle';
-import { useIsValidConnection } from 'features/nodes/hooks/useIsValidConnection';
-
-interface IAINodeOutputProps {
-  nodeId: string;
-  output: OutputFieldValue;
-  template?: OutputFieldTemplate | undefined;
-  connected: boolean;
-}
-
-function IAINodeOutput(props: IAINodeOutputProps) {
-  const { nodeId, output, template, connected } = props;
-  const isValidConnection = useIsValidConnection();
-
-  return (
-    <Box position="relative">
-      <FormControl isDisabled={!template ? true : connected} paddingRight={3}>
-        {!template ? (
-          <HStack justifyContent="space-between" alignItems="center">
-            <FormLabel color="error.400">
-              Unknown Output: {output.name}
-            </FormLabel>
-          </HStack>
-        ) : (
-          <>
-            <FormLabel textAlign="end" padding={1}>
-              {template?.title}
-            </FormLabel>
-            <FieldHandle
-              key={output.id}
-              nodeId={nodeId}
-              field={template}
-              isValidConnection={isValidConnection}
-              handleType="source"
-            />
-          </>
-        )}
-      </FormControl>
-    </Box>
-  );
-}
-
-interface IAINodeOutputsProps {
-  nodeId: string;
-  template: InvocationTemplate;
-  outputs: Record<string, OutputFieldValue>;
-}
-
-const IAINodeOutputs = (props: IAINodeOutputsProps) => {
-  const { nodeId, template, outputs } = props;
-
-  const edges = useAppSelector((state: RootState) => state.nodes.edges);
-
-  const renderIAINodeOutputs = useCallback(() => {
-    const IAINodeOutputsToRender: ReactNode[] = [];
-    const outputSockets = map(outputs);
-
-    outputSockets.forEach((outputSocket) => {
-      const outputTemplate = template.outputs[outputSocket.name];
-
-      const isConnected = Boolean(
-        edges.filter((connectedInput) => {
-          return (
-            connectedInput.source === nodeId &&
-            connectedInput.sourceHandle === outputSocket.name
-          );
-        }).length
-      );
-
-      IAINodeOutputsToRender.push(
-        <IAINodeOutput
-          key={outputSocket.id}
-          nodeId={nodeId}
-          output={outputSocket}
-          template={outputTemplate}
-          connected={isConnected}
-        />
-      );
-    });
-
-    return <Flex flexDir="column">{IAINodeOutputsToRender}</Flex>;
-  }, [edges, nodeId, outputs, template.outputs]);
-
-  return renderIAINodeOutputs();
-};
-
-export default memo(IAINodeOutputs);

invokeai/frontend/web/src/features/nodes/components/IAINode/IAINodeResizer.tsx

@@ -1,24 +0,0 @@
-import { NODE_MIN_WIDTH } from 'app/constants';
-import { memo } from 'react';
-import { NodeResizeControl, NodeResizerProps } from 'reactflow';
-
-const IAINodeResizer = (props: NodeResizerProps) => {
-  const { ...rest } = props;
-  return (
-    <NodeResizeControl
-      style={{
-        position: 'absolute',
-        border: 'none',
-        background: 'transparent',
-        width: 15,
-        height: 15,
-        bottom: 0,
-        right: 0,
-      }}
-      minWidth={NODE_MIN_WIDTH}
-      {...rest}
-    ></NodeResizeControl>
-  );
-};
-
-export default memo(IAINodeResizer);

invokeai/frontend/web/src/features/nodes/components/InputFieldComponent.tsx

@@ -1,14 +1,13 @@
 import { Box } from '@chakra-ui/react';
-import { memo } from 'react';
 import { InputFieldTemplate, InputFieldValue } from '../types/types';
-import ArrayInputFieldComponent from './fields/ArrayInputFieldComponent';
-import BooleanInputFieldComponent from './fields/BooleanInputFieldComponent';
-import EnumInputFieldComponent from './fields/EnumInputFieldComponent';
-import ImageInputFieldComponent from './fields/ImageInputFieldComponent';
-import LatentsInputFieldComponent from './fields/LatentsInputFieldComponent';
-import ModelInputFieldComponent from './fields/ModelInputFieldComponent';
-import NumberInputFieldComponent from './fields/NumberInputFieldComponent';
-import StringInputFieldComponent from './fields/StringInputFieldComponent';
+import { ArrayInputFieldComponent } from './fields/ArrayInputField.tsx';
+import { BooleanInputFieldComponent } from './fields/BooleanInputFieldComponent';
+import { EnumInputFieldComponent } from './fields/EnumInputFieldComponent';
+import { ImageInputFieldComponent } from './fields/ImageInputFieldComponent';
+import { LatentsInputFieldComponent } from './fields/LatentsInputFieldComponent';
+import { ModelInputFieldComponent } from './fields/ModelInputFieldComponent';
+import { NumberInputFieldComponent } from './fields/NumberInputFieldComponent';
+import { StringInputFieldComponent } from './fields/StringInputFieldComponent';
 
 type InputFieldComponentProps = {
   nodeId: string;
@@ -17,7 +16,7 @@ type InputFieldComponentProps = {
 };
 
 // build an individual input element based on the schema
-const InputFieldComponent = (props: InputFieldComponentProps) => {
+export const InputFieldComponent = (props: InputFieldComponentProps) => {
   const { nodeId, field, template } = props;
   const { type, value } = field;
 
@@ -106,5 +105,3 @@ const InputFieldComponent = (props: InputFieldComponentProps) => {
 
   return <Box p={2}>Unknown field type: {type}</Box>;
 };
-
-export default memo(InputFieldComponent);

invokeai/frontend/web/src/features/nodes/components/InvocationComponent.tsx

@@ -1,100 +1,242 @@
-import { NodeProps } from 'reactflow';
-import { Box, Flex, Icon, useToken } from '@chakra-ui/react';
-import { FaExclamationCircle } from 'react-icons/fa';
-import { InvocationTemplate, InvocationValue } from '../types/types';
-
-import { memo, PropsWithChildren, useMemo } from 'react';
-import IAINodeOutputs from './IAINode/IAINodeOutputs';
-import IAINodeInputs from './IAINode/IAINodeInputs';
-import IAINodeHeader from './IAINode/IAINodeHeader';
-import IAINodeResizer from './IAINode/IAINodeResizer';
-import { RootState } from 'app/store';
-import { AnyInvocationType } from 'services/events/types';
+import { NodeProps, useReactFlow } from 'reactflow';
+import {
+  Box,
+  Flex,
+  FormControl,
+  FormLabel,
+  Heading,
+  HStack,
+  Tooltip,
+  Icon,
+  Code,
+  Text,
+} from '@chakra-ui/react';
+import { FaExclamationCircle, FaInfoCircle } from 'react-icons/fa';
+import { InvocationValue } from '../types/types';
+import { InputFieldComponent } from './InputFieldComponent';
+import { FieldHandle } from './FieldHandle';
+import { isEqual, map, size } from 'lodash';
+import { memo, useMemo, useRef } from 'react';
+import { useIsValidConnection } from '../hooks/useIsValidConnection';
 import { createSelector } from '@reduxjs/toolkit';
+import { RootState } from 'app/store';
 import { useAppSelector } from 'app/storeHooks';
-import { NODE_MIN_WIDTH } from 'app/constants';
+import { useGetInvocationTemplate } from '../hooks/useInvocationTemplate';
 
-type InvocationComponentWrapperProps = PropsWithChildren & {
-  selected: boolean;
-};
-
-const InvocationComponentWrapper = (props: InvocationComponentWrapperProps) => {
-  const [nodeSelectedOutline, nodeShadow] = useToken('shadows', [
-    'nodeSelectedOutline',
-    'dark-lg',
-  ]);
-
-  return (
-    <Box
-      sx={{
-        position: 'relative',
-        borderRadius: 'md',
-        minWidth: NODE_MIN_WIDTH,
-        boxShadow: props.selected
-          ? `${nodeSelectedOutline}, ${nodeShadow}`
-          : `${nodeShadow}`,
-      }}
-    >
-      {props.children}
-    </Box>
-  );
-};
-
-const makeTemplateSelector = (type: AnyInvocationType) =>
-  createSelector(
-    [(state: RootState) => state.nodes],
-    (nodes) => {
-      const template = nodes.invocationTemplates[type];
-      if (!template) {
-        return;
-      }
-      return template;
+const connectedInputFieldsSelector = createSelector(
+  [(state: RootState) => state.nodes.edges],
+  (edges) => {
+    // return edges.map((e) => e.targetHandle);
+    return edges;
+  },
+  {
+    memoizeOptions: {
+      resultEqualityCheck: isEqual,
     },
-    {
-      memoizeOptions: {
-        resultEqualityCheck: (
-          a: InvocationTemplate | undefined,
-          b: InvocationTemplate | undefined
-        ) => a !== undefined && b !== undefined && a.type === b.type,
-      },
-    }
-  );
+  }
+);
 
 export const InvocationComponent = memo((props: NodeProps<InvocationValue>) => {
   const { id: nodeId, data, selected } = props;
   const { type, inputs, outputs } = data;
 
-  const templateSelector = useMemo(() => makeTemplateSelector(type), [type]);
+  const isValidConnection = useIsValidConnection();
 
-  const template = useAppSelector(templateSelector);
+  const connectedInputs = useAppSelector(connectedInputFieldsSelector);
+  const getInvocationTemplate = useGetInvocationTemplate();
+  // TODO: determine if a field/handle is connected and disable the input if so
 
-  if (!template) {
+  const template = useRef(getInvocationTemplate(type));
+
+  if (!template.current) {
     return (
-      <InvocationComponentWrapper selected={selected}>
+      <Box
+        sx={{
+          padding: 4,
+          bg: 'base.800',
+          borderRadius: 'md',
+          boxShadow: 'dark-lg',
+          borderWidth: 2,
+          borderColor: selected ? 'base.400' : 'transparent',
+        }}
+      >
         <Flex sx={{ alignItems: 'center', justifyContent: 'center' }}>
           <Icon color="base.400" boxSize={32} as={FaExclamationCircle}></Icon>
-          <IAINodeResizer />
         </Flex>
-      </InvocationComponentWrapper>
+      </Box>
     );
   }
 
   return (
-    <InvocationComponentWrapper selected={selected}>
-      <IAINodeHeader nodeId={nodeId} template={template} />
-      <Flex
-        sx={{
-          flexDirection: 'column',
-          borderBottomRadius: 'md',
-          bg: 'base.800',
-          py: 2,
-        }}
-      >
-        <IAINodeOutputs nodeId={nodeId} outputs={outputs} template={template} />
-        <IAINodeInputs nodeId={nodeId} inputs={inputs} template={template} />
+    <Box
+      sx={{
+        padding: 4,
+        bg: 'base.800',
+        borderRadius: 'md',
+        boxShadow: 'dark-lg',
+        borderWidth: 2,
+        borderColor: selected ? 'base.400' : 'transparent',
+      }}
+    >
+      <Flex flexDirection="column" gap={2}>
+        <>
+          <Code>{nodeId}</Code>
+          <HStack justifyContent="space-between">
+            <Heading size="sm" fontWeight={500} color="base.100">
+              {template.current.title}
+            </Heading>
+            <Tooltip
+              label={template.current.description}
+              placement="top"
+              hasArrow
+              shouldWrapChildren
+            >
+              <Icon color="base.300" as={FaInfoCircle} />
+            </Tooltip>
+          </HStack>
+          {map(inputs, (input, i) => {
+            const { id: fieldId } = input;
+            const inputTemplate = template.current?.inputs[input.name];
+
+            if (!inputTemplate) {
+              return (
+                <Box
+                  key={fieldId}
+                  position="relative"
+                  p={2}
+                  borderWidth={1}
+                  borderRadius="md"
+                  sx={{
+                    borderColor: 'error.400',
+                  }}
+                >
+                  <FormControl isDisabled={true}>
+                    <HStack justifyContent="space-between" alignItems="center">
+                      <FormLabel>Unknown input: {input.name}</FormLabel>
+                    </HStack>
+                  </FormControl>
+                </Box>
+              );
+            }
+
+            const isConnected = Boolean(
+              connectedInputs.filter((connectedInput) => {
+                return (
+                  connectedInput.target === nodeId &&
+                  connectedInput.targetHandle === input.name
+                );
+              }).length
+            );
+
+            return (
+              <Box
+                key={fieldId}
+                position="relative"
+                p={2}
+                borderWidth={1}
+                borderRadius="md"
+                sx={{
+                  borderColor:
+                    !isConnected &&
+                    ['always', 'connectionOnly'].includes(
+                      String(inputTemplate?.inputRequirement)
+                    ) &&
+                    input.value === undefined
+                      ? 'warning.400'
+                      : undefined,
+                }}
+              >
+                <FormControl isDisabled={isConnected}>
+                  <HStack justifyContent="space-between" alignItems="center">
+                    <FormLabel>{inputTemplate?.title}</FormLabel>
+                    <Tooltip
+                      label={inputTemplate?.description}
+                      placement="top"
+                      hasArrow
+                      shouldWrapChildren
+                    >
+                      <Icon color="base.400" as={FaInfoCircle} />
+                    </Tooltip>
+                  </HStack>
+                  <InputFieldComponent
+                    nodeId={nodeId}
+                    field={input}
+                    template={inputTemplate}
+                  />
+                </FormControl>
+                {!['never', 'directOnly'].includes(
+                  inputTemplate?.inputRequirement ?? ''
+                ) && (
+                  <FieldHandle
+                    nodeId={nodeId}
+                    field={inputTemplate}
+                    isValidConnection={isValidConnection}
+                    handleType="target"
+                  />
+                )}
+              </Box>
+            );
+          })}
+          {map(outputs).map((output, i) => {
+            const outputTemplate = template.current?.outputs[output.name];
+
+            const isConnected = Boolean(
+              connectedInputs.filter((connectedInput) => {
+                return (
+                  connectedInput.source === nodeId &&
+                  connectedInput.sourceHandle === output.name
+                );
+              }).length
+            );
+
+            if (!outputTemplate) {
+              return (
+                <Box
+                  key={output.id}
+                  position="relative"
+                  p={2}
+                  borderWidth={1}
+                  borderRadius="md"
+                  sx={{
+                    borderColor: 'error.400',
+                  }}
+                >
+                  <FormControl isDisabled={true}>
+                    <HStack justifyContent="space-between" alignItems="center">
+                      <FormLabel>Unknown output: {output.name}</FormLabel>
+                    </HStack>
+                  </FormControl>
+                </Box>
+              );
+            }
+
+            return (
+              <Box
+                key={output.id}
+                position="relative"
+                p={2}
+                borderWidth={1}
+                borderRadius="md"
+              >
+                <FormControl isDisabled={isConnected}>
+                  <FormLabel textAlign="end">
+                    {outputTemplate?.title} Output
+                  </FormLabel>
+                </FormControl>
+                <FieldHandle
+                  key={output.id}
+                  nodeId={nodeId}
+                  field={outputTemplate}
+                  isValidConnection={isValidConnection}
+                  handleType="source"
+                />
+              </Box>
+            );
+          })}
+        </>
       </Flex>
-      <IAINodeResizer />
-    </InvocationComponentWrapper>
+      <Flex></Flex>
+    </Box>
   );
 });
 

invokeai/frontend/web/src/features/nodes/components/NodeEditor.tsx

@@ -3,15 +3,21 @@ import { Box } from '@chakra-ui/react';
 import { ReactFlowProvider } from 'reactflow';
 
 import { Flow } from './Flow';
-import { memo } from 'react';
+import { useAppSelector } from 'app/storeHooks';
+import { RootState } from 'app/store';
+import { buildNodesGraph } from '../util/nodesGraphBuilder/buildNodesGraph';
 
 const NodeEditor = () => {
+  const state = useAppSelector((state: RootState) => state);
+
+  const graph = buildNodesGraph(state);
+
   return (
     <Box
       sx={{
         position: 'relative',
         width: 'full',
-        height: { base: '100vh', xl: 'full' },
+        height: 'full',
         borderRadius: 'md',
         bg: 'base.850',
       }}
@@ -19,8 +25,22 @@ const NodeEditor = () => {
       <ReactFlowProvider>
         <Flow />
       </ReactFlowProvider>
+      <Box
+        as="pre"
+        fontFamily="monospace"
+        position="absolute"
+        top={2}
+        left={2}
+        width="full"
+        height="full"
+        userSelect="none"
+        pointerEvents="none"
+        opacity={0.7}
+      >
+        <Box w="50%">{JSON.stringify(graph, null, 2)}</Box>
+      </Box>
     </Box>
   );
 };
 
-export default memo(NodeEditor);
+export default NodeEditor;

invokeai/frontend/web/src/features/nodes/components/NodeGraphOverlay.tsx

@@ -1,30 +0,0 @@
-import { Box } from '@chakra-ui/react';
-import { RootState } from 'app/store';
-import { useAppSelector } from 'app/storeHooks';
-import { memo } from 'react';
-import { buildNodesGraph } from '../util/nodesGraphBuilder/buildNodesGraph';
-
-const NodeGraphOverlay = () => {
-  const state = useAppSelector((state: RootState) => state);
-  const graph = buildNodesGraph(state);
-
-  return (
-    <Box
-      as="pre"
-      fontFamily="monospace"
-      position="absolute"
-      top={10}
-      right={2}
-      opacity={0.7}
-      background="base.800"
-      p={2}
-      maxHeight={500}
-      overflowY="scroll"
-      borderRadius="md"
-    >
-      {JSON.stringify(graph, null, 2)}
-    </Box>
-  );
-};
-
-export default memo(NodeGraphOverlay);

invokeai/frontend/web/src/features/nodes/components/ViewportControls.tsx

@@ -1,59 +0,0 @@
-import { ButtonGroup } from '@chakra-ui/react';
-import { useAppDispatch, useAppSelector } from 'app/storeHooks';
-import { IAIIconButton } from 'exports';
-import { memo, useCallback } from 'react';
-import { FaCode, FaExpand, FaMinus, FaPlus } from 'react-icons/fa';
-import { useReactFlow } from 'reactflow';
-import { shouldShowGraphOverlayChanged } from '../store/nodesSlice';
-
-const ViewportControls = () => {
-  const { zoomIn, zoomOut, fitView } = useReactFlow();
-  const dispatch = useAppDispatch();
-  const shouldShowGraphOverlay = useAppSelector(
-    (state) => state.nodes.shouldShowGraphOverlay
-  );
-
-  const handleClickedZoomIn = useCallback(() => {
-    zoomIn();
-  }, [zoomIn]);
-
-  const handleClickedZoomOut = useCallback(() => {
-    zoomOut();
-  }, [zoomOut]);
-
-  const handleClickedFitView = useCallback(() => {
-    fitView();
-  }, [fitView]);
-
-  const handleClickedToggleGraphOverlay = useCallback(() => {
-    dispatch(shouldShowGraphOverlayChanged(!shouldShowGraphOverlay));
-  }, [shouldShowGraphOverlay, dispatch]);
-
-  return (
-    <ButtonGroup isAttached orientation="vertical">
-      <IAIIconButton
-        onClick={handleClickedZoomIn}
-        aria-label="Zoom In"
-        icon={<FaPlus />}
-      />
-      <IAIIconButton
-        onClick={handleClickedZoomOut}
-        aria-label="Zoom Out"
-        icon={<FaMinus />}
-      />
-      <IAIIconButton
-        onClick={handleClickedFitView}
-        aria-label="Fit to Viewport"
-        icon={<FaExpand />}
-      />
-      <IAIIconButton
-        isChecked={shouldShowGraphOverlay}
-        onClick={handleClickedToggleGraphOverlay}
-        aria-label="Show/Hide Graph"
-        icon={<FaCode />}
-      />
-    </ButtonGroup>
-  );
-};
-
-export default memo(ViewportControls);

invokeai/frontend/web/src/features/nodes/components/fields/ArrayInputField.tsx.tsx

@@ -1,17 +1,14 @@
 import {
   ArrayInputFieldTemplate,
   ArrayInputFieldValue,
-} from 'features/nodes/types/types';
-import { memo } from 'react';
-import { FaList } from 'react-icons/fa';
+} from 'features/nodes/types';
+import { FaImage, FaList } from 'react-icons/fa';
 import { FieldComponentProps } from './types';
 
-const ArrayInputFieldComponent = (
+export const ArrayInputFieldComponent = (
   props: FieldComponentProps<ArrayInputFieldValue, ArrayInputFieldTemplate>
 ) => {
   const { nodeId, field } = props;
 
   return <FaList />;
 };
-
-export default memo(ArrayInputFieldComponent);

invokeai/frontend/web/src/features/nodes/components/fields/BooleanInputFieldComponent.tsx

@@ -4,11 +4,11 @@ import { fieldValueChanged } from 'features/nodes/store/nodesSlice';
 import {
   BooleanInputFieldTemplate,
   BooleanInputFieldValue,
-} from 'features/nodes/types/types';
-import { ChangeEvent, memo } from 'react';
+} from 'features/nodes/types';
+import { ChangeEvent } from 'react';
 import { FieldComponentProps } from './types';
 
-const BooleanInputFieldComponent = (
+export const BooleanInputFieldComponent = (
   props: FieldComponentProps<BooleanInputFieldValue, BooleanInputFieldTemplate>
 ) => {
   const { nodeId, field } = props;
@@ -29,5 +29,3 @@ const BooleanInputFieldComponent = (
     <Switch onChange={handleValueChanged} isChecked={field.value}></Switch>
   );
 };
-
-export default memo(BooleanInputFieldComponent);

invokeai/frontend/web/src/features/nodes/components/fields/EnumInputFieldComponent.tsx

@@ -4,11 +4,11 @@ import { fieldValueChanged } from 'features/nodes/store/nodesSlice';
 import {
   EnumInputFieldTemplate,
   EnumInputFieldValue,
-} from 'features/nodes/types/types';
-import { ChangeEvent, memo } from 'react';
+} from 'features/nodes/types';
+import { ChangeEvent } from 'react';
 import { FieldComponentProps } from './types';
 
-const EnumInputFieldComponent = (
+export const EnumInputFieldComponent = (
   props: FieldComponentProps<EnumInputFieldValue, EnumInputFieldTemplate>
 ) => {
   const { nodeId, field, template } = props;
@@ -33,5 +33,3 @@ const EnumInputFieldComponent = (
     </Select>
   );
 };
-
-export default memo(EnumInputFieldComponent);

invokeai/frontend/web/src/features/nodes/components/fields/ImageInputFieldComponent.tsx

@@ -8,13 +8,13 @@ import { fieldValueChanged } from 'features/nodes/store/nodesSlice';
 import {
   ImageInputFieldTemplate,
   ImageInputFieldValue,
-} from 'features/nodes/types/types';
-import { DragEvent, memo, useCallback, useState } from 'react';
+} from 'features/nodes/types';
+import { DragEvent, useCallback, useState } from 'react';
 import { FaImage } from 'react-icons/fa';
 import { ImageType } from 'services/api';
 import { FieldComponentProps } from './types';
 
-const ImageInputFieldComponent = (
+export const ImageInputFieldComponent = (
   props: FieldComponentProps<ImageInputFieldValue, ImageInputFieldTemplate>
 ) => {
   const { nodeId, field } = props;
@@ -62,5 +62,3 @@ const ImageInputFieldComponent = (
     </Box>
   );
 };
-
-export default memo(ImageInputFieldComponent);

invokeai/frontend/web/src/features/nodes/components/fields/LatentsInputFieldComponent.tsx

@@ -1,16 +1,13 @@
 import {
   LatentsInputFieldTemplate,
   LatentsInputFieldValue,
-} from 'features/nodes/types/types';
-import { memo } from 'react';
+} from 'features/nodes/types';
 import { FieldComponentProps } from './types';
 
-const LatentsInputFieldComponent = (
+export const LatentsInputFieldComponent = (
   props: FieldComponentProps<LatentsInputFieldValue, LatentsInputFieldTemplate>
 ) => {
   const { nodeId, field } = props;
 
   return null;
 };
-
-export default memo(LatentsInputFieldComponent);

invokeai/frontend/web/src/features/nodes/components/fields/ModelInputFieldComponent.tsx

@@ -6,13 +6,13 @@ import { fieldValueChanged } from 'features/nodes/store/nodesSlice';
 import {
   ModelInputFieldTemplate,
   ModelInputFieldValue,
-} from 'features/nodes/types/types';
+} from 'features/nodes/types';
 import {
   selectModelsById,
   selectModelsIds,
 } from 'features/system/store/modelSlice';
 import { isEqual, map } from 'lodash';
-import { ChangeEvent, memo } from 'react';
+import { ChangeEvent } from 'react';
 import { FieldComponentProps } from './types';
 
 const availableModelsSelector = createSelector(
@@ -28,7 +28,7 @@ const availableModelsSelector = createSelector(
   }
 );
 
-const ModelInputFieldComponent = (
+export const ModelInputFieldComponent = (
   props: FieldComponentProps<ModelInputFieldValue, ModelInputFieldTemplate>
 ) => {
   const { nodeId, field } = props;
@@ -55,5 +55,3 @@ const ModelInputFieldComponent = (
     </Select>
   );
 };
-
-export default memo(ModelInputFieldComponent);

invokeai/frontend/web/src/features/nodes/components/fields/NumberInputFieldComponent.tsx

@@ -12,11 +12,10 @@ import {
   FloatInputFieldValue,
   IntegerInputFieldTemplate,
   IntegerInputFieldValue,
-} from 'features/nodes/types/types';
-import { memo } from 'react';
+} from 'features/nodes/types';
 import { FieldComponentProps } from './types';
 
-const NumberInputFieldComponent = (
+export const NumberInputFieldComponent = (
   props: FieldComponentProps<
     IntegerInputFieldValue | FloatInputFieldValue,
     IntegerInputFieldTemplate | FloatInputFieldTemplate
@@ -40,5 +39,3 @@ const NumberInputFieldComponent = (
     </NumberInput>
   );
 };
-
-export default memo(NumberInputFieldComponent);

invokeai/frontend/web/src/features/nodes/components/fields/StringInputFieldComponent.tsx

@@ -4,11 +4,11 @@ import { fieldValueChanged } from 'features/nodes/store/nodesSlice';
 import {
   StringInputFieldTemplate,
   StringInputFieldValue,
-} from 'features/nodes/types/types';
-import { ChangeEvent, memo } from 'react';
+} from 'features/nodes/types';
+import { ChangeEvent } from 'react';
 import { FieldComponentProps } from './types';
 
-const StringInputFieldComponent = (
+export const StringInputFieldComponent = (
   props: FieldComponentProps<StringInputFieldValue, StringInputFieldTemplate>
 ) => {
   const { nodeId, field } = props;
@@ -27,5 +27,3 @@ const StringInputFieldComponent = (
 
   return <Input onChange={handleValueChanged} value={field.value}></Input>;
 };
-
-export default memo(StringInputFieldComponent);

invokeai/frontend/web/src/features/nodes/components/panels/BottomLeftPanel.tsx.tsx

@@ -1,11 +0,0 @@
-import { memo } from 'react';
-import { Panel } from 'reactflow';
-import ViewportControls from '../ViewportControls';
-
-const BottomLeftPanel = () => (
-  <Panel position="bottom-left">
-    <ViewportControls />
-  </Panel>
-);
-
-export default memo(BottomLeftPanel);

invokeai/frontend/web/src/features/nodes/components/panels/MinimapPanel.tsx

@@ -1,34 +0,0 @@
-import { RootState } from 'app/store';
-import { useAppSelector } from 'app/storeHooks';
-import { CSSProperties, memo } from 'react';
-import { MiniMap } from 'reactflow';
-
-const MinimapStyle: CSSProperties = {
-  background: 'var(--invokeai-colors-base-500)',
-};
-
-const MinimapPanel = () => {
-  const currentTheme = useAppSelector(
-    (state: RootState) => state.ui.currentTheme
-  );
-
-  return (
-    <MiniMap
-      nodeStrokeWidth={3}
-      pannable
-      zoomable
-      nodeBorderRadius={30}
-      style={MinimapStyle}
-      nodeColor={
-        currentTheme === 'light'
-          ? 'var(--invokeai-colors-accent-700)'
-          : currentTheme === 'green'
-          ? 'var(--invokeai-colors-accent-600)'
-          : 'var(--invokeai-colors-accent-700)'
-      }
-      maskColor="var(--invokeai-colors-base-700)"
-    />
-  );
-};
-
-export default memo(MinimapPanel);

invokeai/frontend/web/src/features/nodes/components/panels/TopCenterPanel.tsx

@@ -1,32 +0,0 @@
-import { HStack } from '@chakra-ui/react';
-import { useAppDispatch } from 'app/storeHooks';
-import IAIButton from 'common/components/IAIButton';
-import { memo, useCallback } from 'react';
-import { Panel } from 'reactflow';
-import { receivedOpenAPISchema } from 'services/thunks/schema';
-import { nodesGraphBuilt } from 'services/thunks/session';
-
-const TopCenterPanel = () => {
-  const dispatch = useAppDispatch();
-
-  const handleInvoke = useCallback(() => {
-    dispatch(nodesGraphBuilt());
-  }, [dispatch]);
-
-  const handleReloadSchema = useCallback(() => {
-    dispatch(receivedOpenAPISchema());
-  }, [dispatch]);
-
-  return (
-    <Panel position="top-center">
-      <HStack>
-        <IAIButton colorScheme="accent" onClick={handleInvoke}>
-          Will it blend?
-        </IAIButton>
-        <IAIButton onClick={handleReloadSchema}>Reload Schema</IAIButton>
-      </HStack>
-    </Panel>
-  );
-};
-
-export default memo(TopCenterPanel);

invokeai/frontend/web/src/features/nodes/components/panels/TopLeftPanel.tsx

@@ -1,11 +0,0 @@
-import { memo } from 'react';
-import { Panel } from 'reactflow';
-import AddNodeMenu from '../AddNodeMenu';
-
-const TopLeftPanel = () => (
-  <Panel position="top-left">
-    <AddNodeMenu />
-  </Panel>
-);
-
-export default memo(TopLeftPanel);

invokeai/frontend/web/src/features/nodes/components/panels/TopRightPanel.tsx

@@ -1,21 +0,0 @@
-import { RootState } from 'app/store';
-import { useAppSelector } from 'app/storeHooks';
-import { memo } from 'react';
-import { Panel } from 'reactflow';
-import FieldTypeLegend from '../FieldTypeLegend';
-import NodeGraphOverlay from '../NodeGraphOverlay';
-
-const TopRightPanel = () => {
-  const shouldShowGraphOverlay = useAppSelector(
-    (state: RootState) => state.nodes.shouldShowGraphOverlay
-  );
-
-  return (
-    <Panel position="top-right">
-      <FieldTypeLegend />
-      {shouldShowGraphOverlay && <NodeGraphOverlay />}
-    </Panel>
-  );
-};
-
-export default memo(TopRightPanel);

invokeai/frontend/web/src/features/nodes/components/search/NodeSearch.tsx

@@ -1,211 +0,0 @@
-import { Box, Flex } from '@chakra-ui/layout';
-import { RootState } from 'app/store';
-import { useAppDispatch, useAppSelector } from 'app/storeHooks';
-import IAIInput from 'common/components/IAIInput';
-import { Panel } from 'reactflow';
-import { map } from 'lodash';
-import {
-  ChangeEvent,
-  FocusEvent,
-  KeyboardEvent,
-  memo,
-  ReactNode,
-  useCallback,
-  useRef,
-  useState,
-} from 'react';
-import { Tooltip } from '@chakra-ui/tooltip';
-import { AnyInvocationType } from 'services/events/types';
-import { useBuildInvocation } from 'features/nodes/hooks/useBuildInvocation';
-import { makeToast } from 'features/system/hooks/useToastWatcher';
-import { addToast } from 'features/system/store/systemSlice';
-import { nodeAdded } from '../../store/nodesSlice';
-import Fuse from 'fuse.js';
-import { InvocationTemplate } from 'features/nodes/types/types';
-
-interface NodeListItemProps {
-  title: string;
-  description: string;
-  type: AnyInvocationType;
-  isSelected: boolean;
-  addNode: (nodeType: AnyInvocationType) => void;
-}
-
-const NodeListItem = (props: NodeListItemProps) => {
-  const { title, description, type, isSelected, addNode } = props;
-  return (
-    <Tooltip label={description} placement="end" hasArrow>
-      <Box
-        px={4}
-        onClick={() => addNode(type)}
-        background={isSelected ? 'base.600' : 'none'}
-        _hover={{
-          background: 'base.600',
-          cursor: 'pointer',
-        }}
-      >
-        {title}
-      </Box>
-    </Tooltip>
-  );
-};
-
-NodeListItem.displayName = 'NodeListItem';
-
-const NodeSearch = () => {
-  const invocationTemplates = useAppSelector(
-    (state: RootState) => state.nodes.invocationTemplates
-  );
-
-  const nodes = map(invocationTemplates);
-  const [filteredNodes, setFilteredNodes] = useState<
-    Fuse.FuseResult<InvocationTemplate>[]
-  >([]);
-
-  const buildInvocation = useBuildInvocation();
-  const dispatch = useAppDispatch();
-
-  const [searchText, setSearchText] = useState<string>('');
-  const [showNodeList, setShowNodeList] = useState<boolean>(false);
-  const [focusedIndex, setFocusedIndex] = useState<number>(-1);
-  const nodeSearchRef = useRef<HTMLDivElement>(null);
-
-  const fuseOptions = {
-    findAllMatches: true,
-    threshold: 0,
-    ignoreLocation: true,
-    keys: ['title', 'type', 'tags'],
-  };
-
-  const fuse = new Fuse(nodes, fuseOptions);
-
-  const findNode = (e: ChangeEvent<HTMLInputElement>) => {
-    setSearchText(e.target.value);
-    setFilteredNodes(fuse.search(e.target.value));
-    setShowNodeList(true);
-  };
-
-  const addNode = useCallback(
-    (nodeType: AnyInvocationType) => {
-      const invocation = buildInvocation(nodeType);
-
-      if (!invocation) {
-        const toast = makeToast({
-          status: 'error',
-          title: `Unknown Invocation type ${nodeType}`,
-        });
-        dispatch(addToast(toast));
-        return;
-      }
-
-      dispatch(nodeAdded(invocation));
-    },
-    [dispatch, buildInvocation]
-  );
-
-  const renderNodeList = () => {
-    const nodeListToRender: ReactNode[] = [];
-
-    if (searchText.length > 0) {
-      filteredNodes.forEach(({ item }, index) => {
-        const { title, description, type } = item;
-        if (title.toLowerCase().includes(searchText)) {
-          nodeListToRender.push(
-            <NodeListItem
-              key={index}
-              title={title}
-              description={description}
-              type={type}
-              isSelected={focusedIndex === index}
-              addNode={addNode}
-            />
-          );
-        }
-      });
-    } else {
-      nodes.forEach(({ title, description, type }, index) => {
-        nodeListToRender.push(
-          <NodeListItem
-            key={index}
-            title={title}
-            description={description}
-            type={type}
-            isSelected={focusedIndex === index}
-            addNode={addNode}
-          />
-        );
-      });
-    }
-
-    return (
-      <Flex flexDirection="column" background="base.900" borderRadius={6}>
-        {nodeListToRender}
-      </Flex>
-    );
-  };
-
-  const searchKeyHandler = (e: KeyboardEvent<HTMLDivElement>) => {
-    const { key } = e;
-    let nextIndex = 0;
-
-    if (key === 'ArrowDown') {
-      setShowNodeList(true);
-      if (searchText.length > 0) {
-        nextIndex = (focusedIndex + 1) % filteredNodes.length;
-      } else {
-        nextIndex = (focusedIndex + 1) % nodes.length;
-      }
-    }
-
-    if (key === 'ArrowUp') {
-      setShowNodeList(true);
-      if (searchText.length > 0) {
-        nextIndex =
-          (focusedIndex + filteredNodes.length - 1) % filteredNodes.length;
-      } else {
-        nextIndex = (focusedIndex + nodes.length - 1) % nodes.length;
-      }
-    }
-
-    // # TODO Handle Blur
-    // if (key === 'Escape') {
-    // }
-
-    if (key === 'Enter') {
-      let selectedNodeType: AnyInvocationType;
-
-      if (searchText.length > 0) {
-        selectedNodeType = filteredNodes[focusedIndex].item.type;
-      } else {
-        selectedNodeType = nodes[focusedIndex].type;
-      }
-
-      addNode(selectedNodeType);
-      setShowNodeList(false);
-    }
-
-    setFocusedIndex(nextIndex);
-  };
-
-  const searchInputBlurHandler = (e: FocusEvent<HTMLDivElement>) => {
-    if (!e.currentTarget.contains(e.relatedTarget)) setShowNodeList(false);
-  };
-
-  return (
-    <Panel position="top-left">
-      <Flex
-        flexDirection="column"
-        tabIndex={1}
-        onKeyDown={searchKeyHandler}
-        onFocus={() => setShowNodeList(true)}
-        onBlur={searchInputBlurHandler}
-        ref={nodeSearchRef}
-      >
-        <IAIInput value={searchText} onChange={findNode} />
-        {showNodeList && renderNodeList()}
-      </Flex>
-    </Panel>
-  );
-};
-
-export default memo(NodeSearch);

invokeai/frontend/web/src/features/nodes/hooks/useBuildInvocation.ts

@@ -1,9 +1,7 @@
-import { createSelector } from '@reduxjs/toolkit';
 import { RootState } from 'app/store';
 import { useAppSelector } from 'app/storeHooks';
 import { reduce } from 'lodash';
-import { useCallback } from 'react';
-import { Node, useReactFlow } from 'reactflow';
+import { Node } from 'reactflow';
 import { AnyInvocationType } from 'services/events/types';
 import { v4 as uuidv4 } from 'uuid';
 import {
@@ -13,82 +11,68 @@ import {
 } from '../types/types';
 import { buildInputFieldValue } from '../util/fieldValueBuilders';
 
-const templatesSelector = createSelector(
-  [(state: RootState) => state.nodes],
-  (nodes) => nodes.invocationTemplates,
-  { memoizeOptions: { resultEqualityCheck: (a, b) => true } }
-);
-
 export const useBuildInvocation = () => {
-  const invocationTemplates = useAppSelector(templatesSelector);
-
-  const flow = useReactFlow();
-
-  return useCallback(
-    (type: AnyInvocationType) => {
-      const template = invocationTemplates[type];
-
-      if (template === undefined) {
-        console.error(`Unable to find template ${type}.`);
-        return;
-      }
-
-      const nodeId = uuidv4();
-
-      const inputs = reduce(
-        template.inputs,
-        (inputsAccumulator, inputTemplate, inputName) => {
-          const fieldId = uuidv4();
-
-          const inputFieldValue: InputFieldValue = buildInputFieldValue(
-            fieldId,
-            inputTemplate
-          );
-
-          inputsAccumulator[inputName] = inputFieldValue;
-
-          return inputsAccumulator;
-        },
-        {} as Record<string, InputFieldValue>
-      );
-
-      const outputs = reduce(
-        template.outputs,
-        (outputsAccumulator, outputTemplate, outputName) => {
-          const fieldId = uuidv4();
-
-          const outputFieldValue: OutputFieldValue = {
-            id: fieldId,
-            name: outputName,
-            type: outputTemplate.type,
-          };
-
-          outputsAccumulator[outputName] = outputFieldValue;
-
-          return outputsAccumulator;
-        },
-        {} as Record<string, OutputFieldValue>
-      );
-
-      const { x, y } = flow.project({
-        x: window.innerWidth / 2.5,
-        y: window.innerHeight / 8,
-      });
-
-      const invocation: Node<InvocationValue> = {
-        id: nodeId,
-        type: 'invocation',
-        position: { x: x, y: y },
-        data: {
-          id: nodeId,
-          type,
-          inputs,
-          outputs,
-        },
-      };
-
-      return invocation;
-    },
-    [invocationTemplates, flow]
+  const invocationTemplates = useAppSelector(
+    (state: RootState) => state.nodes.invocationTemplates
   );
+
+  return (type: AnyInvocationType) => {
+    const template = invocationTemplates[type];
+
+    if (template === undefined) {
+      console.error(`Unable to find template ${type}.`);
+      return;
+    }
+
+    const nodeId = uuidv4();
+
+    const inputs = reduce(
+      template.inputs,
+      (inputsAccumulator, inputTemplate, inputName) => {
+        const fieldId = uuidv4();
+
+        const inputFieldValue: InputFieldValue = buildInputFieldValue(
+          fieldId,
+          inputTemplate
+        );
+
+        inputsAccumulator[inputName] = inputFieldValue;
+
+        return inputsAccumulator;
+      },
+      {} as Record<string, InputFieldValue>
+    );
+
+    const outputs = reduce(
+      template.outputs,
+      (outputsAccumulator, outputTemplate, outputName) => {
+        const fieldId = uuidv4();
+
+        const outputFieldValue: OutputFieldValue = {
+          id: fieldId,
+          name: outputName,
+          type: outputTemplate.type,
+        };
+
+        outputsAccumulator[outputName] = outputFieldValue;
+
+        return outputsAccumulator;
+      },
+      {} as Record<string, OutputFieldValue>
+    );
+
+    const invocation: Node<InvocationValue> = {
+      id: nodeId,
+      type: 'invocation',
+      position: { x: 0, y: 0 },
+      data: {
+        id: nodeId,
+        type,
+        inputs,
+        outputs,
+      },
+    };
+
+    return invocation;
+  };
 };

invokeai/frontend/web/src/features/nodes/hooks/useInvocationTemplate.ts

@@ -0,0 +1,16 @@
+import { useAppSelector } from 'app/storeHooks';
+import { invocationTemplatesSelector } from '../store/selectors/invocationTemplatesSelector';
+
+export const useGetInvocationTemplate = () => {
+  const invocationTemplates = useAppSelector(invocationTemplatesSelector);
+
+  return (invocationType: string) => {
+    const template = invocationTemplates[invocationType];
+
+    if (!template) {
+      return;
+    }
+
+    return template;
+  };
+};

invokeai/frontend/web/src/features/nodes/store/nodesSlice.ts

@@ -24,7 +24,6 @@ export type NodesState = {
   invocationTemplates: Record<string, InvocationTemplate>;
   connectionStartParams: OnConnectStartParams | null;
   lastGraph: Graph | null;
-  shouldShowGraphOverlay: boolean;
 };
 
 export const initialNodesState: NodesState = {
@@ -34,7 +33,6 @@ export const initialNodesState: NodesState = {
   invocationTemplates: {},
   connectionStartParams: null,
   lastGraph: null,
-  shouldShowGraphOverlay: false,
 };
 
 const nodesSlice = createSlice({
@@ -79,9 +77,6 @@ const nodesSlice = createSlice({
         state.nodes[nodeIndex].data.inputs[fieldName].value = value;
       }
     },
-    shouldShowGraphOverlayChanged: (state, action: PayloadAction<boolean>) => {
-      state.shouldShowGraphOverlay = action.payload;
-    },
   },
   extraReducers(builder) {
     builder.addCase(receivedOpenAPISchema.fulfilled, (state, action) => {
@@ -103,7 +98,6 @@ export const {
   connectionMade,
   connectionStarted,
   connectionEnded,
-  shouldShowGraphOverlayChanged,
 } = nodesSlice.actions;
 
 export default nodesSlice.reducer;

invokeai/frontend/web/src/features/nodes/types/constants.ts

@@ -22,55 +22,46 @@ const getColorTokenCssVariable = (color: string) =>
 
 export const FIELDS: Record<FieldType, FieldUIConfig> = {
   integer: {
-    color: 'red',
     colorCssVar: getColorTokenCssVariable('red'),
     title: 'Integer',
     description: 'Integers are whole numbers, without a decimal point.',
   },
   float: {
-    color: 'orange',
     colorCssVar: getColorTokenCssVariable('orange'),
     title: 'Float',
     description: 'Floats are numbers with a decimal point.',
   },
   string: {
-    color: 'yellow',
     colorCssVar: getColorTokenCssVariable('yellow'),
     title: 'String',
     description: 'Strings are text.',
   },
   boolean: {
-    color: 'green',
     colorCssVar: getColorTokenCssVariable('green'),
     title: 'Boolean',
     description: 'Booleans are true or false.',
   },
   enum: {
-    color: 'blue',
     colorCssVar: getColorTokenCssVariable('blue'),
     title: 'Enum',
     description: 'Enums are values that may be one of a number of options.',
   },
   image: {
-    color: 'purple',
     colorCssVar: getColorTokenCssVariable('purple'),
     title: 'Image',
     description: 'Images may be passed between nodes.',
   },
   latents: {
-    color: 'pink',
     colorCssVar: getColorTokenCssVariable('pink'),
     title: 'Latents',
     description: 'Latents may be passed between nodes.',
   },
   model: {
-    color: 'teal',
     colorCssVar: getColorTokenCssVariable('teal'),
     title: 'Model',
     description: 'Models are models.',
   },
   array: {
-    color: 'gray',
     colorCssVar: getColorTokenCssVariable('gray'),
     title: 'Array',
     description: 'TODO: Array type description.',

invokeai/frontend/web/src/features/nodes/types/types.ts

@@ -39,7 +39,6 @@ export type InvocationTemplate = {
 };
 
 export type FieldUIConfig = {
-  color: string;
   colorCssVar: string;
   title: string;
   description: string;

invokeai/frontend/web/src/features/parameters/components/PromptInput/PromptInput.tsx

@@ -76,7 +76,7 @@ const PromptInput = () => {
           onKeyDown={handleKeyDown}
           resize="vertical"
           ref={promptRef}
-          minH={{ base: 20, lg: 40 }}
+          minH={40}
         />
       </FormControl>
     </Box>

invokeai/frontend/web/src/features/system/components/InvokeAILogoComponent.tsx

@@ -10,28 +10,19 @@ const InvokeAILogoComponent = () => {
 
   return (
     <Flex alignItems="center" gap={3} ps={1}>
-      <Image
-        src={InvokeAILogoImage}
-        alt="invoke-ai-logo"
-        w="32px"
-        h="32px"
-        minW="32px"
-        minH="32px"
-      />
-      <Flex gap={3} display={{ base: 'inherit', sm: 'none', md: 'inherit' }}>
-        <Text fontSize="xl">
-          invoke <strong>ai</strong>
-        </Text>
-        <Text
-          sx={{
-            fontWeight: 300,
-            marginTop: 1,
-          }}
-          variant="subtext"
-        >
-          {appVersion}
-        </Text>
-      </Flex>
+      <Image src={InvokeAILogoImage} alt="invoke-ai-logo" w="32px" h="32px" />
+      <Text fontSize="xl">
+        invoke <strong>ai</strong>
+      </Text>
+      <Text
+        sx={{
+          fontWeight: 300,
+          marginTop: 1,
+        }}
+        variant="subtext"
+      >
+        {appVersion}
+      </Text>
     </Flex>
   );
 };

invokeai/frontend/web/src/features/system/components/SiteHeader.tsx

@@ -1,68 +1,126 @@
-import { Flex, Grid } from '@chakra-ui/react';
-import { useState } from 'react';
-import ModelSelect from './ModelSelect';
-import StatusIndicator from './StatusIndicator';
+import { Flex, Grid, Link } from '@chakra-ui/react';
+
+import { FaBug, FaCube, FaDiscord, FaGithub, FaKeyboard } from 'react-icons/fa';
+
+import IAIIconButton from 'common/components/IAIIconButton';
+
+import HotkeysModal from './HotkeysModal/HotkeysModal';
+
+import ModelManagerModal from './ModelManager/ModelManagerModal';
+import ModelSelect from './ModelSelect';
+import SettingsModal from './SettingsModal/SettingsModal';
+import StatusIndicator from './StatusIndicator';
+import ThemeChanger from './ThemeChanger';
+
+import LanguagePicker from './LanguagePicker';
 
-import InvokeAILogoComponent from './InvokeAILogoComponent';
-import SiteHeaderMenu from './SiteHeaderMenu';
-import useResolution from 'common/hooks/useResolution';
-import { FaBars } from 'react-icons/fa';
-import { IAIIconButton } from 'exports';
 import { useTranslation } from 'react-i18next';
+import { MdSettings } from 'react-icons/md';
+import InvokeAILogoComponent from './InvokeAILogoComponent';
 
 /**
  * Header, includes color mode toggle, settings button, status message.
  */
 const SiteHeader = () => {
-  const [menuOpened, setMenuOpened] = useState(false);
-  const resolution = useResolution();
   const { t } = useTranslation();
 
   return (
-    <Grid
-      gridTemplateColumns={{ base: 'auto', sm: 'auto max-content' }}
-      paddingRight={{ base: 10, xl: 0 }}
-      gap={2}
-    >
-      <Flex justifyContent={{ base: 'center', sm: 'start' }}>
-        <InvokeAILogoComponent />
-      </Flex>
-      <Flex
-        alignItems="center"
-        gap={2}
-        justifyContent={{ base: 'center', sm: 'start' }}
-      >
+    <Grid gridTemplateColumns="auto max-content">
+      <InvokeAILogoComponent />
+
+      <Flex alignItems="center" gap={2}>
         <StatusIndicator />
 
         <ModelSelect />
 
-        {resolution === 'desktop' ? (
-          <SiteHeaderMenu />
-        ) : (
+        <ModelManagerModal>
           <IAIIconButton
-            icon={<FaBars />}
-            aria-label={t('accessibility.menu')}
-            background={menuOpened ? 'base.800' : 'none'}
-            _hover={{ background: menuOpened ? 'base.800' : 'none' }}
-            onClick={() => setMenuOpened(!menuOpened)}
-            p={0}
-          ></IAIIconButton>
-        )}
-      </Flex>
+            aria-label={t('modelManager.modelManager')}
+            tooltip={t('modelManager.modelManager')}
+            size="sm"
+            variant="link"
+            data-variant="link"
+            fontSize={20}
+            icon={<FaCube />}
+          />
+        </ModelManagerModal>
 
-      {resolution !== 'desktop' && menuOpened && (
-        <Flex
-          position="absolute"
-          right={6}
-          top={{ base: 28, sm: 16 }}
-          backgroundColor="base.800"
-          padding={4}
-          borderRadius={4}
-          zIndex={{ base: 99, xl: 0 }}
+        <HotkeysModal>
+          <IAIIconButton
+            aria-label={t('common.hotkeysLabel')}
+            tooltip={t('common.hotkeysLabel')}
+            size="sm"
+            variant="link"
+            data-variant="link"
+            fontSize={20}
+            icon={<FaKeyboard />}
+          />
+        </HotkeysModal>
+
+        <ThemeChanger />
+
+        <LanguagePicker />
+
+        <Link
+          isExternal
+          href="http://github.com/invoke-ai/InvokeAI/issues"
+          marginBottom="-0.25rem"
         >
-          <SiteHeaderMenu />
-        </Flex>
-      )}
+          <IAIIconButton
+            aria-label={t('common.reportBugLabel')}
+            tooltip={t('common.reportBugLabel')}
+            variant="link"
+            data-variant="link"
+            fontSize={20}
+            size="sm"
+            icon={<FaBug />}
+          />
+        </Link>
+
+        <Link
+          isExternal
+          href="http://github.com/invoke-ai/InvokeAI"
+          marginBottom="-0.25rem"
+        >
+          <IAIIconButton
+            aria-label={t('common.githubLabel')}
+            tooltip={t('common.githubLabel')}
+            variant="link"
+            data-variant="link"
+            fontSize={20}
+            size="sm"
+            icon={<FaGithub />}
+          />
+        </Link>
+
+        <Link
+          isExternal
+          href="https://discord.gg/ZmtBAhwWhy"
+          marginBottom="-0.25rem"
+        >
+          <IAIIconButton
+            aria-label={t('common.discordLabel')}
+            tooltip={t('common.discordLabel')}
+            variant="link"
+            data-variant="link"
+            fontSize={20}
+            size="sm"
+            icon={<FaDiscord />}
+          />
+        </Link>
+
+        <SettingsModal>
+          <IAIIconButton
+            aria-label={t('common.settingsLabel')}
+            tooltip={t('common.settingsLabel')}
+            variant="link"
+            data-variant="link"
+            fontSize={22}
+            size="sm"
+            icon={<MdSettings />}
+          />
+        </SettingsModal>
+      </Flex>
     </Grid>
   );
 };

invokeai/frontend/web/src/features/system/components/SiteHeaderMenu.tsx

@@ -1,113 +0,0 @@
-import { Flex, Link } from '@chakra-ui/react';
-import { useTranslation } from 'react-i18next';
-import { FaCube, FaKeyboard, FaBug, FaGithub, FaDiscord } from 'react-icons/fa';
-import { MdSettings } from 'react-icons/md';
-import HotkeysModal from './HotkeysModal/HotkeysModal';
-import LanguagePicker from './LanguagePicker';
-import ModelManagerModal from './ModelManager/ModelManagerModal';
-import SettingsModal from './SettingsModal/SettingsModal';
-import ThemeChanger from './ThemeChanger';
-import IAIIconButton from 'common/components/IAIIconButton';
-
-const SiteHeaderMenu = () => {
-  const { t } = useTranslation();
-
-  return (
-    <Flex
-      alignItems="center"
-      flexDirection={{ base: 'column', xl: 'row' }}
-      gap={{ base: 4, xl: 1 }}
-    >
-      <ModelManagerModal>
-        <IAIIconButton
-          aria-label={t('modelManager.modelManager')}
-          tooltip={t('modelManager.modelManager')}
-          size="sm"
-          variant="link"
-          data-variant="link"
-          fontSize={20}
-          icon={<FaCube />}
-        />
-      </ModelManagerModal>
-
-      <HotkeysModal>
-        <IAIIconButton
-          aria-label={t('common.hotkeysLabel')}
-          tooltip={t('common.hotkeysLabel')}
-          size="sm"
-          variant="link"
-          data-variant="link"
-          fontSize={20}
-          icon={<FaKeyboard />}
-        />
-      </HotkeysModal>
-
-      <ThemeChanger />
-
-      <LanguagePicker />
-
-      <Link
-        isExternal
-        href="http://github.com/invoke-ai/InvokeAI/issues"
-        marginBottom="-0.25rem"
-      >
-        <IAIIconButton
-          aria-label={t('common.reportBugLabel')}
-          tooltip={t('common.reportBugLabel')}
-          variant="link"
-          data-variant="link"
-          fontSize={20}
-          size="sm"
-          icon={<FaBug />}
-        />
-      </Link>
-
-      <Link
-        isExternal
-        href="http://github.com/invoke-ai/InvokeAI"
-        marginBottom="-0.25rem"
-      >
-        <IAIIconButton
-          aria-label={t('common.githubLabel')}
-          tooltip={t('common.githubLabel')}
-          variant="link"
-          data-variant="link"
-          fontSize={20}
-          size="sm"
-          icon={<FaGithub />}
-        />
-      </Link>
-
-      <Link
-        isExternal
-        href="https://discord.gg/ZmtBAhwWhy"
-        marginBottom="-0.25rem"
-      >
-        <IAIIconButton
-          aria-label={t('common.discordLabel')}
-          tooltip={t('common.discordLabel')}
-          variant="link"
-          data-variant="link"
-          fontSize={20}
-          size="sm"
-          icon={<FaDiscord />}
-        />
-      </Link>
-
-      <SettingsModal>
-        <IAIIconButton
-          aria-label={t('common.settingsLabel')}
-          tooltip={t('common.settingsLabel')}
-          variant="link"
-          data-variant="link"
-          fontSize={22}
-          size="sm"
-          icon={<MdSettings />}
-        />
-      </SettingsModal>
-    </Flex>
-  );
-};
-
-SiteHeaderMenu.displayName = 'SiteHeaderMenu';
-export default SiteHeaderMenu;