Merge branch 'main' into depth_anything_v2

docker/Dockerfile

@@ -55,6 +55,7 @@ RUN --mount=type=cache,target=/root/.cache/pip \
 FROM node:20-slim AS web-builder
 ENV PNPM_HOME="/pnpm"
 ENV PATH="$PNPM_HOME:$PATH"
+RUN corepack use pnpm@8.x
 RUN corepack enable
 
 WORKDIR /build

invokeai/app/invocations/denoise_latents.py

@@ -37,9 +37,9 @@ from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.controlnet_utils import prepare_control_image
 from invokeai.backend.ip_adapter.ip_adapter import IPAdapter
 from invokeai.backend.lora import LoRAModelRaw
-from invokeai.backend.model_manager import BaseModelType
+from invokeai.backend.model_manager import BaseModelType, ModelVariantType
 from invokeai.backend.model_patcher import ModelPatcher
-from invokeai.backend.stable_diffusion import PipelineIntermediateState, set_seamless
+from invokeai.backend.stable_diffusion import PipelineIntermediateState
 from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext, DenoiseInputs
 from invokeai.backend.stable_diffusion.diffusers_pipeline import (
     ControlNetData,
@@ -60,8 +60,12 @@ from invokeai.backend.stable_diffusion.diffusion_backend import StableDiffusionB
 from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
 from invokeai.backend.stable_diffusion.extensions.controlnet import ControlNetExt
 from invokeai.backend.stable_diffusion.extensions.freeu import FreeUExt
+from invokeai.backend.stable_diffusion.extensions.inpaint import InpaintExt
+from invokeai.backend.stable_diffusion.extensions.inpaint_model import InpaintModelExt
 from invokeai.backend.stable_diffusion.extensions.preview import PreviewExt
 from invokeai.backend.stable_diffusion.extensions.rescale_cfg import RescaleCFGExt
+from invokeai.backend.stable_diffusion.extensions.seamless import SeamlessExt
+from invokeai.backend.stable_diffusion.extensions.t2i_adapter import T2IAdapterExt
 from invokeai.backend.stable_diffusion.extensions_manager import ExtensionsManager
 from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP
 from invokeai.backend.stable_diffusion.schedulers.schedulers import SCHEDULER_NAME_VALUES
@@ -498,6 +502,33 @@ class DenoiseLatentsInvocation(BaseInvocation):
                 )
             )
 
+    @staticmethod
+    def parse_t2i_adapter_field(
+        exit_stack: ExitStack,
+        context: InvocationContext,
+        t2i_adapters: Optional[Union[T2IAdapterField, list[T2IAdapterField]]],
+        ext_manager: ExtensionsManager,
+    ) -> None:
+        if t2i_adapters is None:
+            return
+
+        # Handle the possibility that t2i_adapters could be a list or a single T2IAdapterField.
+        if isinstance(t2i_adapters, T2IAdapterField):
+            t2i_adapters = [t2i_adapters]
+
+        for t2i_adapter_field in t2i_adapters:
+            ext_manager.add_extension(
+                T2IAdapterExt(
+                    node_context=context,
+                    model_id=t2i_adapter_field.t2i_adapter_model,
+                    image=context.images.get_pil(t2i_adapter_field.image.image_name),
+                    weight=t2i_adapter_field.weight,
+                    begin_step_percent=t2i_adapter_field.begin_step_percent,
+                    end_step_percent=t2i_adapter_field.end_step_percent,
+                    resize_mode=t2i_adapter_field.resize_mode,
+                )
+            )
+
     def prep_ip_adapter_image_prompts(
         self,
         context: InvocationContext,
@@ -707,7 +738,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
         else:
             masked_latents = torch.where(mask < 0.5, 0.0, latents)
 
-        return 1 - mask, masked_latents, self.denoise_mask.gradient
+        return mask, masked_latents, self.denoise_mask.gradient
 
     @staticmethod
     def prepare_noise_and_latents(
@@ -765,10 +796,6 @@ class DenoiseLatentsInvocation(BaseInvocation):
         dtype = TorchDevice.choose_torch_dtype()
 
         seed, noise, latents = self.prepare_noise_and_latents(context, self.noise, self.latents)
-        latents = latents.to(device=device, dtype=dtype)
-        if noise is not None:
-            noise = noise.to(device=device, dtype=dtype)
-
         _, _, latent_height, latent_width = latents.shape
 
         conditioning_data = self.get_conditioning_data(
@@ -801,21 +828,6 @@ class DenoiseLatentsInvocation(BaseInvocation):
             denoising_end=self.denoising_end,
         )
 
-        denoise_ctx = DenoiseContext(
-            inputs=DenoiseInputs(
-                orig_latents=latents,
-                timesteps=timesteps,
-                init_timestep=init_timestep,
-                noise=noise,
-                seed=seed,
-                scheduler_step_kwargs=scheduler_step_kwargs,
-                conditioning_data=conditioning_data,
-                attention_processor_cls=CustomAttnProcessor2_0,
-            ),
-            unet=None,
-            scheduler=scheduler,
-        )
-
         # get the unet's config so that we can pass the base to sd_step_callback()
         unet_config = context.models.get_config(self.unet.unet.key)
 
@@ -833,6 +845,40 @@ class DenoiseLatentsInvocation(BaseInvocation):
         if self.unet.freeu_config:
             ext_manager.add_extension(FreeUExt(self.unet.freeu_config))
 
+        ### seamless
+        if self.unet.seamless_axes:
+            ext_manager.add_extension(SeamlessExt(self.unet.seamless_axes))
+
+        ### inpaint
+        mask, masked_latents, is_gradient_mask = self.prep_inpaint_mask(context, latents)
+        # NOTE: We used to identify inpainting models by inpecting the shape of the loaded UNet model weights. Now we
+        # use the ModelVariantType config. During testing, there was a report of a user with models that had an
+        # incorrect ModelVariantType value. Re-installing the model fixed the issue. If this issue turns out to be
+        # prevalent, we will have to revisit how we initialize the inpainting extensions.
+        if unet_config.variant == ModelVariantType.Inpaint:
+            ext_manager.add_extension(InpaintModelExt(mask, masked_latents, is_gradient_mask))
+        elif mask is not None:
+            ext_manager.add_extension(InpaintExt(mask, is_gradient_mask))
+
+        # Initialize context for modular denoise
+        latents = latents.to(device=device, dtype=dtype)
+        if noise is not None:
+            noise = noise.to(device=device, dtype=dtype)
+        denoise_ctx = DenoiseContext(
+            inputs=DenoiseInputs(
+                orig_latents=latents,
+                timesteps=timesteps,
+                init_timestep=init_timestep,
+                noise=noise,
+                seed=seed,
+                scheduler_step_kwargs=scheduler_step_kwargs,
+                conditioning_data=conditioning_data,
+                attention_processor_cls=CustomAttnProcessor2_0,
+            ),
+            unet=None,
+            scheduler=scheduler,
+        )
+
         # context for loading additional models
         with ExitStack() as exit_stack:
             # later should be smth like:
@@ -840,6 +886,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
             #    ext = extension_field.to_extension(exit_stack, context, ext_manager)
             #    ext_manager.add_extension(ext)
             self.parse_controlnet_field(exit_stack, context, self.control, ext_manager)
+            self.parse_t2i_adapter_field(exit_stack, context, self.t2i_adapter, ext_manager)
 
             # ext: t2i/ip adapter
             ext_manager.run_callback(ExtensionCallbackType.SETUP, denoise_ctx)
@@ -871,6 +918,10 @@ class DenoiseLatentsInvocation(BaseInvocation):
         seed, noise, latents = self.prepare_noise_and_latents(context, self.noise, self.latents)
 
         mask, masked_latents, gradient_mask = self.prep_inpaint_mask(context, latents)
+        # At this point, the mask ranges from 0 (leave unchanged) to 1 (inpaint).
+        # We invert the mask here for compatibility with the old backend implementation.
+        if mask is not None:
+            mask = 1 - mask
 
         # TODO(ryand): I have hard-coded `do_classifier_free_guidance=True` to mirror the behaviour of ControlNets,
         # below. Investigate whether this is appropriate.
@@ -915,7 +966,7 @@ class DenoiseLatentsInvocation(BaseInvocation):
             ExitStack() as exit_stack,
             unet_info.model_on_device() as (model_state_dict, unet),
             ModelPatcher.apply_freeu(unet, self.unet.freeu_config),
-            set_seamless(unet, self.unet.seamless_axes),  # FIXME
+            SeamlessExt.static_patch_model(unet, self.unet.seamless_axes),  # FIXME
             # Apply the LoRA after unet has been moved to its target device for faster patching.
             ModelPatcher.apply_lora_unet(
                 unet,

invokeai/app/invocations/latents_to_image.py

@@ -24,7 +24,7 @@ from invokeai.app.invocations.fields import (
 from invokeai.app.invocations.model import VAEField
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.backend.stable_diffusion import set_seamless
+from invokeai.backend.stable_diffusion.extensions.seamless import SeamlessExt
 from invokeai.backend.stable_diffusion.vae_tiling import patch_vae_tiling_params
 from invokeai.backend.util.devices import TorchDevice
 
@@ -59,7 +59,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
 
         vae_info = context.models.load(self.vae.vae)
         assert isinstance(vae_info.model, (AutoencoderKL, AutoencoderTiny))
-        with set_seamless(vae_info.model, self.vae.seamless_axes), vae_info as vae:
+        with SeamlessExt.static_patch_model(vae_info.model, self.vae.seamless_axes), vae_info as vae:
             assert isinstance(vae, (AutoencoderKL, AutoencoderTiny))
             latents = latents.to(vae.device)
             if self.fp32:

invokeai/backend/model_manager/load/model_loaders/stable_diffusion.py

@@ -98,6 +98,9 @@ class StableDiffusionDiffusersModel(GenericDiffusersLoader):
                 ModelVariantType.Normal: StableDiffusionXLPipeline,
                 ModelVariantType.Inpaint: StableDiffusionXLInpaintPipeline,
             },
+            BaseModelType.StableDiffusionXLRefiner: {
+                ModelVariantType.Normal: StableDiffusionXLPipeline,
+            },
         }
         assert isinstance(config, MainCheckpointConfig)
         try:

invokeai/backend/model_manager/starter_models.py

@@ -187,164 +187,171 @@ STARTER_MODELS: list[StarterModel] = [
     # endregion
     # region ControlNet
     StarterModel(
-        name="QRCode Monster",
+        name="QRCode Monster v2 (SD1.5)",
         base=BaseModelType.StableDiffusion1,
-        source="monster-labs/control_v1p_sd15_qrcode_monster",
+        source="monster-labs/control_v1p_sd15_qrcode_monster::v2",
-        description="Controlnet model that generates scannable creative QR codes",
+        description="ControlNet model that generates scannable creative QR codes",
+        type=ModelType.ControlNet,
+    ),
+    StarterModel(
+        name="QRCode Monster (SDXL)",
+        base=BaseModelType.StableDiffusionXL,
+        source="monster-labs/control_v1p_sdxl_qrcode_monster",
+        description="ControlNet model that generates scannable creative QR codes",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="canny",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11p_sd15_canny",
-        description="Controlnet weights trained on sd-1.5 with canny conditioning.",
+        description="ControlNet weights trained on sd-1.5 with canny conditioning.",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="inpaint",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11p_sd15_inpaint",
-        description="Controlnet weights trained on sd-1.5 with canny conditioning, inpaint version",
+        description="ControlNet weights trained on sd-1.5 with canny conditioning, inpaint version",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="mlsd",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11p_sd15_mlsd",
-        description="Controlnet weights trained on sd-1.5 with canny conditioning, MLSD version",
+        description="ControlNet weights trained on sd-1.5 with canny conditioning, MLSD version",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="depth",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11f1p_sd15_depth",
-        description="Controlnet weights trained on sd-1.5 with depth conditioning",
+        description="ControlNet weights trained on sd-1.5 with depth conditioning",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="normal_bae",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11p_sd15_normalbae",
-        description="Controlnet weights trained on sd-1.5 with normalbae image conditioning",
+        description="ControlNet weights trained on sd-1.5 with normalbae image conditioning",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="seg",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11p_sd15_seg",
-        description="Controlnet weights trained on sd-1.5 with seg image conditioning",
+        description="ControlNet weights trained on sd-1.5 with seg image conditioning",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="lineart",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11p_sd15_lineart",
-        description="Controlnet weights trained on sd-1.5 with lineart image conditioning",
+        description="ControlNet weights trained on sd-1.5 with lineart image conditioning",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="lineart_anime",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11p_sd15s2_lineart_anime",
-        description="Controlnet weights trained on sd-1.5 with anime image conditioning",
+        description="ControlNet weights trained on sd-1.5 with anime image conditioning",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="openpose",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11p_sd15_openpose",
-        description="Controlnet weights trained on sd-1.5 with openpose image conditioning",
+        description="ControlNet weights trained on sd-1.5 with openpose image conditioning",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="scribble",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11p_sd15_scribble",
-        description="Controlnet weights trained on sd-1.5 with scribble image conditioning",
+        description="ControlNet weights trained on sd-1.5 with scribble image conditioning",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="softedge",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11p_sd15_softedge",
-        description="Controlnet weights trained on sd-1.5 with soft edge conditioning",
+        description="ControlNet weights trained on sd-1.5 with soft edge conditioning",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="shuffle",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11e_sd15_shuffle",
-        description="Controlnet weights trained on sd-1.5 with shuffle image conditioning",
+        description="ControlNet weights trained on sd-1.5 with shuffle image conditioning",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="tile",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11f1e_sd15_tile",
-        description="Controlnet weights trained on sd-1.5 with tiled image conditioning",
+        description="ControlNet weights trained on sd-1.5 with tiled image conditioning",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="ip2p",
         base=BaseModelType.StableDiffusion1,
         source="lllyasviel/control_v11e_sd15_ip2p",
-        description="Controlnet weights trained on sd-1.5 with ip2p conditioning.",
+        description="ControlNet weights trained on sd-1.5 with ip2p conditioning.",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="canny-sdxl",
         base=BaseModelType.StableDiffusionXL,
-        source="xinsir/controlnet-canny-sdxl-1.0",
+        source="xinsir/controlNet-canny-sdxl-1.0",
-        description="Controlnet weights trained on sdxl-1.0 with canny conditioning, by Xinsir.",
+        description="ControlNet weights trained on sdxl-1.0 with canny conditioning, by Xinsir.",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="depth-sdxl",
         base=BaseModelType.StableDiffusionXL,
-        source="diffusers/controlnet-depth-sdxl-1.0",
+        source="diffusers/controlNet-depth-sdxl-1.0",
-        description="Controlnet weights trained on sdxl-1.0 with depth conditioning.",
+        description="ControlNet weights trained on sdxl-1.0 with depth conditioning.",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="softedge-dexined-sdxl",
         base=BaseModelType.StableDiffusionXL,
-        source="SargeZT/controlnet-sd-xl-1.0-softedge-dexined",
+        source="SargeZT/controlNet-sd-xl-1.0-softedge-dexined",
-        description="Controlnet weights trained on sdxl-1.0 with dexined soft edge preprocessing.",
+        description="ControlNet weights trained on sdxl-1.0 with dexined soft edge preprocessing.",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="depth-16bit-zoe-sdxl",
         base=BaseModelType.StableDiffusionXL,
-        source="SargeZT/controlnet-sd-xl-1.0-depth-16bit-zoe",
+        source="SargeZT/controlNet-sd-xl-1.0-depth-16bit-zoe",
-        description="Controlnet weights trained on sdxl-1.0 with Zoe's preprocessor (16 bits).",
+        description="ControlNet weights trained on sdxl-1.0 with Zoe's preprocessor (16 bits).",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="depth-zoe-sdxl",
         base=BaseModelType.StableDiffusionXL,
-        source="diffusers/controlnet-zoe-depth-sdxl-1.0",
+        source="diffusers/controlNet-zoe-depth-sdxl-1.0",
-        description="Controlnet weights trained on sdxl-1.0 with Zoe's preprocessor (32 bits).",
+        description="ControlNet weights trained on sdxl-1.0 with Zoe's preprocessor (32 bits).",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="openpose-sdxl",
         base=BaseModelType.StableDiffusionXL,
-        source="xinsir/controlnet-openpose-sdxl-1.0",
+        source="xinsir/controlNet-openpose-sdxl-1.0",
-        description="Controlnet weights trained on sdxl-1.0 compatible with the DWPose processor by Xinsir.",
+        description="ControlNet weights trained on sdxl-1.0 compatible with the DWPose processor by Xinsir.",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="scribble-sdxl",
         base=BaseModelType.StableDiffusionXL,
-        source="xinsir/controlnet-scribble-sdxl-1.0",
+        source="xinsir/controlNet-scribble-sdxl-1.0",
-        description="Controlnet weights trained on sdxl-1.0 compatible with various lineart processors and black/white sketches by Xinsir.",
+        description="ControlNet weights trained on sdxl-1.0 compatible with various lineart processors and black/white sketches by Xinsir.",
         type=ModelType.ControlNet,
     ),
     StarterModel(
         name="tile-sdxl",
         base=BaseModelType.StableDiffusionXL,
-        source="xinsir/controlnet-tile-sdxl-1.0",
+        source="xinsir/controlNet-tile-sdxl-1.0",
-        description="Controlnet weights trained on sdxl-1.0 with tiled image conditioning",
+        description="ControlNet weights trained on sdxl-1.0 with tiled image conditioning",
         type=ModelType.ControlNet,
     ),
     # endregion

invokeai/backend/stable_diffusion/__init__.py

@@ -7,11 +7,9 @@ from invokeai.backend.stable_diffusion.diffusers_pipeline import (  # noqa: F401
     StableDiffusionGeneratorPipeline,
 )
 from invokeai.backend.stable_diffusion.diffusion import InvokeAIDiffuserComponent  # noqa: F401
-from invokeai.backend.stable_diffusion.seamless import set_seamless  # noqa: F401
 
 __all__ = [
     "PipelineIntermediateState",
     "StableDiffusionGeneratorPipeline",
     "InvokeAIDiffuserComponent",
-    "set_seamless",
 ]

invokeai/backend/stable_diffusion/extensions/inpaint.py

@@ -0,0 +1,120 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Optional
+
+import einops
+import torch
+from diffusers import UNet2DConditionModel
+
+from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
+from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase, callback
+
+if TYPE_CHECKING:
+    from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext
+
+
+class InpaintExt(ExtensionBase):
+    """An extension for inpainting with non-inpainting models. See `InpaintModelExt` for inpainting with inpainting
+    models.
+    """
+
+    def __init__(
+        self,
+        mask: torch.Tensor,
+        is_gradient_mask: bool,
+    ):
+        """Initialize InpaintExt.
+        Args:
+            mask (torch.Tensor): The inpainting mask. Shape: (1, 1, latent_height, latent_width). Values are
+                expected to be in the range [0, 1]. A value of 1 means that the corresponding 'pixel' should not be
+                inpainted.
+            is_gradient_mask (bool): If True, mask is interpreted as a gradient mask meaning that the mask values range
+                from 0 to 1. If False, mask is interpreted as binary mask meaning that the mask values are either 0 or
+                1.
+        """
+        super().__init__()
+        self._mask = mask
+        self._is_gradient_mask = is_gradient_mask
+
+        # Noise, which used to noisify unmasked part of image
+        # if noise provided to context, then it will be used
+        # if no noise provided, then noise will be generated based on seed
+        self._noise: Optional[torch.Tensor] = None
+
+    @staticmethod
+    def _is_normal_model(unet: UNet2DConditionModel):
+        """Checks if the provided UNet belongs to a regular model.
+        The `in_channels` of a UNet vary depending on model type:
+        - normal - 4
+        - depth - 5
+        - inpaint - 9
+        """
+        return unet.conv_in.in_channels == 4
+
+    def _apply_mask(self, ctx: DenoiseContext, latents: torch.Tensor, t: torch.Tensor) -> torch.Tensor:
+        batch_size = latents.size(0)
+        mask = einops.repeat(self._mask, "b c h w -> (repeat b) c h w", repeat=batch_size)
+        if t.dim() == 0:
+            # some schedulers expect t to be one-dimensional.
+            # TODO: file diffusers bug about inconsistency?
+            t = einops.repeat(t, "-> batch", batch=batch_size)
+        # Noise shouldn't be re-randomized between steps here. The multistep schedulers
+        # get very confused about what is happening from step to step when we do that.
+        mask_latents = ctx.scheduler.add_noise(ctx.inputs.orig_latents, self._noise, t)
+        # TODO: Do we need to also apply scheduler.scale_model_input? Or is add_noise appropriately scaled already?
+        # mask_latents = self.scheduler.scale_model_input(mask_latents, t)
+        mask_latents = einops.repeat(mask_latents, "b c h w -> (repeat b) c h w", repeat=batch_size)
+        if self._is_gradient_mask:
+            threshold = (t.item()) / ctx.scheduler.config.num_train_timesteps
+            mask_bool = mask < 1 - threshold
+            masked_input = torch.where(mask_bool, latents, mask_latents)
+        else:
+            masked_input = torch.lerp(latents, mask_latents.to(dtype=latents.dtype), mask.to(dtype=latents.dtype))
+        return masked_input
+
+    @callback(ExtensionCallbackType.PRE_DENOISE_LOOP)
+    def init_tensors(self, ctx: DenoiseContext):
+        if not self._is_normal_model(ctx.unet):
+            raise ValueError(
+                "InpaintExt should be used only on normal (non-inpainting) models. This could be caused by an "
+                "inpainting model that was incorrectly marked as a non-inpainting model. In some cases, this can be "
+                "fixed by removing and re-adding the model (so that it gets re-probed)."
+            )
+
+        self._mask = self._mask.to(device=ctx.latents.device, dtype=ctx.latents.dtype)
+
+        self._noise = ctx.inputs.noise
+        # 'noise' might be None if the latents have already been noised (e.g. when running the SDXL refiner).
+        # We still need noise for inpainting, so we generate it from the seed here.
+        if self._noise is None:
+            self._noise = torch.randn(
+                ctx.latents.shape,
+                dtype=torch.float32,
+                device="cpu",
+                generator=torch.Generator(device="cpu").manual_seed(ctx.seed),
+            ).to(device=ctx.latents.device, dtype=ctx.latents.dtype)
+
+    # Use negative order to make extensions with default order work with patched latents
+    @callback(ExtensionCallbackType.PRE_STEP, order=-100)
+    def apply_mask_to_initial_latents(self, ctx: DenoiseContext):
+        ctx.latents = self._apply_mask(ctx, ctx.latents, ctx.timestep)
+
+    # TODO: redo this with preview events rewrite
+    # Use negative order to make extensions with default order work with patched latents
+    @callback(ExtensionCallbackType.POST_STEP, order=-100)
+    def apply_mask_to_step_output(self, ctx: DenoiseContext):
+        timestep = ctx.scheduler.timesteps[-1]
+        if hasattr(ctx.step_output, "denoised"):
+            ctx.step_output.denoised = self._apply_mask(ctx, ctx.step_output.denoised, timestep)
+        elif hasattr(ctx.step_output, "pred_original_sample"):
+            ctx.step_output.pred_original_sample = self._apply_mask(ctx, ctx.step_output.pred_original_sample, timestep)
+        else:
+            ctx.step_output.pred_original_sample = self._apply_mask(ctx, ctx.step_output.prev_sample, timestep)
+
+    # Restore unmasked part after the last step is completed
+    @callback(ExtensionCallbackType.POST_DENOISE_LOOP)
+    def restore_unmasked(self, ctx: DenoiseContext):
+        if self._is_gradient_mask:
+            ctx.latents = torch.where(self._mask < 1, ctx.latents, ctx.inputs.orig_latents)
+        else:
+            ctx.latents = torch.lerp(ctx.latents, ctx.inputs.orig_latents, self._mask)

invokeai/backend/stable_diffusion/extensions/inpaint_model.py

@@ -0,0 +1,88 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Optional
+
+import torch
+from diffusers import UNet2DConditionModel
+
+from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
+from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase, callback
+
+if TYPE_CHECKING:
+    from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext
+
+
+class InpaintModelExt(ExtensionBase):
+    """An extension for inpainting with inpainting models. See `InpaintExt` for inpainting with non-inpainting
+    models.
+    """
+
+    def __init__(
+        self,
+        mask: Optional[torch.Tensor],
+        masked_latents: Optional[torch.Tensor],
+        is_gradient_mask: bool,
+    ):
+        """Initialize InpaintModelExt.
+        Args:
+            mask (Optional[torch.Tensor]): The inpainting mask. Shape: (1, 1, latent_height, latent_width). Values are
+                expected to be in the range [0, 1]. A value of 1 means that the corresponding 'pixel' should not be
+                inpainted.
+            masked_latents (Optional[torch.Tensor]): Latents of initial image, with masked out by black color inpainted area.
+                If mask provided, then too should be provided. Shape: (1, 1, latent_height, latent_width)
+            is_gradient_mask (bool): If True, mask is interpreted as a gradient mask meaning that the mask values range
+                from 0 to 1. If False, mask is interpreted as binary mask meaning that the mask values are either 0 or
+                1.
+        """
+        super().__init__()
+        if mask is not None and masked_latents is None:
+            raise ValueError("Source image required for inpaint mask when inpaint model used!")
+
+        # Inverse mask, because inpaint models treat mask as: 0 - remain same, 1 - inpaint
+        self._mask = None
+        if mask is not None:
+            self._mask = 1 - mask
+        self._masked_latents = masked_latents
+        self._is_gradient_mask = is_gradient_mask
+
+    @staticmethod
+    def _is_inpaint_model(unet: UNet2DConditionModel):
+        """Checks if the provided UNet belongs to a regular model.
+        The `in_channels` of a UNet vary depending on model type:
+        - normal - 4
+        - depth - 5
+        - inpaint - 9
+        """
+        return unet.conv_in.in_channels == 9
+
+    @callback(ExtensionCallbackType.PRE_DENOISE_LOOP)
+    def init_tensors(self, ctx: DenoiseContext):
+        if not self._is_inpaint_model(ctx.unet):
+            raise ValueError("InpaintModelExt should be used only on inpaint models!")
+
+        if self._mask is None:
+            self._mask = torch.ones_like(ctx.latents[:1, :1])
+        self._mask = self._mask.to(device=ctx.latents.device, dtype=ctx.latents.dtype)
+
+        if self._masked_latents is None:
+            self._masked_latents = torch.zeros_like(ctx.latents[:1])
+        self._masked_latents = self._masked_latents.to(device=ctx.latents.device, dtype=ctx.latents.dtype)
+
+    # Do last so that other extensions works with normal latents
+    @callback(ExtensionCallbackType.PRE_UNET, order=1000)
+    def append_inpaint_layers(self, ctx: DenoiseContext):
+        batch_size = ctx.unet_kwargs.sample.shape[0]
+        b_mask = torch.cat([self._mask] * batch_size)
+        b_masked_latents = torch.cat([self._masked_latents] * batch_size)
+        ctx.unet_kwargs.sample = torch.cat(
+            [ctx.unet_kwargs.sample, b_mask, b_masked_latents],
+            dim=1,
+        )
+
+    # Restore unmasked part as inpaint model can change unmasked part slightly
+    @callback(ExtensionCallbackType.POST_DENOISE_LOOP)
+    def restore_unmasked(self, ctx: DenoiseContext):
+        if self._is_gradient_mask:
+            ctx.latents = torch.where(self._mask > 0, ctx.latents, ctx.inputs.orig_latents)
+        else:
+            ctx.latents = torch.lerp(ctx.inputs.orig_latents, ctx.latents, self._mask)

invokeai/backend/stable_diffusion/extensions/seamless.py

@@ -0,0 +1,71 @@
+from __future__ import annotations
+
+from contextlib import contextmanager
+from typing import Callable, Dict, List, Optional, Tuple
+
+import torch
+import torch.nn as nn
+from diffusers import UNet2DConditionModel
+from diffusers.models.lora import LoRACompatibleConv
+
+from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase
+
+
+class SeamlessExt(ExtensionBase):
+    def __init__(
+        self,
+        seamless_axes: List[str],
+    ):
+        super().__init__()
+        self._seamless_axes = seamless_axes
+
+    @contextmanager
+    def patch_unet(self, unet: UNet2DConditionModel, cached_weights: Optional[Dict[str, torch.Tensor]] = None):
+        with self.static_patch_model(
+            model=unet,
+            seamless_axes=self._seamless_axes,
+        ):
+            yield
+
+    @staticmethod
+    @contextmanager
+    def static_patch_model(
+        model: torch.nn.Module,
+        seamless_axes: List[str],
+    ):
+        if not seamless_axes:
+            yield
+            return
+
+        x_mode = "circular" if "x" in seamless_axes else "constant"
+        y_mode = "circular" if "y" in seamless_axes else "constant"
+
+        # override conv_forward
+        # https://github.com/huggingface/diffusers/issues/556#issuecomment-1993287019
+        def _conv_forward_asymmetric(
+            self, input: torch.Tensor, weight: torch.Tensor, bias: Optional[torch.Tensor] = None
+        ):
+            self.paddingX = (self._reversed_padding_repeated_twice[0], self._reversed_padding_repeated_twice[1], 0, 0)
+            self.paddingY = (0, 0, self._reversed_padding_repeated_twice[2], self._reversed_padding_repeated_twice[3])
+            working = torch.nn.functional.pad(input, self.paddingX, mode=x_mode)
+            working = torch.nn.functional.pad(working, self.paddingY, mode=y_mode)
+            return torch.nn.functional.conv2d(
+                working, weight, bias, self.stride, torch.nn.modules.utils._pair(0), self.dilation, self.groups
+            )
+
+        original_layers: List[Tuple[nn.Conv2d, Callable]] = []
+        try:
+            for layer in model.modules():
+                if not isinstance(layer, torch.nn.Conv2d):
+                    continue
+
+                if isinstance(layer, LoRACompatibleConv) and layer.lora_layer is None:
+                    layer.lora_layer = lambda *x: 0
+                original_layers.append((layer, layer._conv_forward))
+                layer._conv_forward = _conv_forward_asymmetric.__get__(layer, torch.nn.Conv2d)
+
+            yield
+
+        finally:
+            for layer, orig_conv_forward in original_layers:
+                layer._conv_forward = orig_conv_forward

invokeai/backend/stable_diffusion/extensions/t2i_adapter.py

@@ -0,0 +1,120 @@
+from __future__ import annotations
+
+import math
+from typing import TYPE_CHECKING, List, Optional, Union
+
+import torch
+from diffusers import T2IAdapter
+from PIL.Image import Image
+
+from invokeai.app.util.controlnet_utils import prepare_control_image
+from invokeai.backend.model_manager import BaseModelType
+from invokeai.backend.stable_diffusion.diffusion.conditioning_data import ConditioningMode
+from invokeai.backend.stable_diffusion.extension_callback_type import ExtensionCallbackType
+from invokeai.backend.stable_diffusion.extensions.base import ExtensionBase, callback
+
+if TYPE_CHECKING:
+    from invokeai.app.invocations.model import ModelIdentifierField
+    from invokeai.app.services.shared.invocation_context import InvocationContext
+    from invokeai.app.util.controlnet_utils import CONTROLNET_RESIZE_VALUES
+    from invokeai.backend.stable_diffusion.denoise_context import DenoiseContext
+
+
+class T2IAdapterExt(ExtensionBase):
+    def __init__(
+        self,
+        node_context: InvocationContext,
+        model_id: ModelIdentifierField,
+        image: Image,
+        weight: Union[float, List[float]],
+        begin_step_percent: float,
+        end_step_percent: float,
+        resize_mode: CONTROLNET_RESIZE_VALUES,
+    ):
+        super().__init__()
+        self._node_context = node_context
+        self._model_id = model_id
+        self._image = image
+        self._weight = weight
+        self._resize_mode = resize_mode
+        self._begin_step_percent = begin_step_percent
+        self._end_step_percent = end_step_percent
+
+        self._adapter_state: Optional[List[torch.Tensor]] = None
+
+        # The max_unet_downscale is the maximum amount that the UNet model downscales the latent image internally.
+        model_config = self._node_context.models.get_config(self._model_id.key)
+        if model_config.base == BaseModelType.StableDiffusion1:
+            self._max_unet_downscale = 8
+        elif model_config.base == BaseModelType.StableDiffusionXL:
+            self._max_unet_downscale = 4
+        else:
+            raise ValueError(f"Unexpected T2I-Adapter base model type: '{model_config.base}'.")
+
+    @callback(ExtensionCallbackType.SETUP)
+    def setup(self, ctx: DenoiseContext):
+        t2i_model: T2IAdapter
+        with self._node_context.models.load(self._model_id) as t2i_model:
+            _, _, latents_height, latents_width = ctx.inputs.orig_latents.shape
+
+            self._adapter_state = self._run_model(
+                model=t2i_model,
+                image=self._image,
+                latents_height=latents_height,
+                latents_width=latents_width,
+            )
+
+    def _run_model(
+        self,
+        model: T2IAdapter,
+        image: Image,
+        latents_height: int,
+        latents_width: int,
+    ):
+        # Resize the T2I-Adapter input image.
+        # We select the resize dimensions so that after the T2I-Adapter's total_downscale_factor is applied, the
+        # result will match the latent image's dimensions after max_unet_downscale is applied.
+        input_height = latents_height // self._max_unet_downscale * model.total_downscale_factor
+        input_width = latents_width // self._max_unet_downscale * model.total_downscale_factor
+
+        # Note: We have hard-coded `do_classifier_free_guidance=False`. This is because we only want to prepare
+        # a single image. If CFG is enabled, we will duplicate the resultant tensor after applying the
+        # T2I-Adapter model.
+        #
+        # Note: We re-use the `prepare_control_image(...)` from ControlNet for T2I-Adapter, because it has many
+        # of the same requirements (e.g. preserving binary masks during resize).
+        t2i_image = prepare_control_image(
+            image=image,
+            do_classifier_free_guidance=False,
+            width=input_width,
+            height=input_height,
+            num_channels=model.config["in_channels"],
+            device=model.device,
+            dtype=model.dtype,
+            resize_mode=self._resize_mode,
+        )
+
+        return model(t2i_image)
+
+    @callback(ExtensionCallbackType.PRE_UNET)
+    def pre_unet_step(self, ctx: DenoiseContext):
+        # skip if model not active in current step
+        total_steps = len(ctx.inputs.timesteps)
+        first_step = math.floor(self._begin_step_percent * total_steps)
+        last_step = math.ceil(self._end_step_percent * total_steps)
+        if ctx.step_index < first_step or ctx.step_index > last_step:
+            return
+
+        weight = self._weight
+        if isinstance(weight, list):
+            weight = weight[ctx.step_index]
+
+        adapter_state = self._adapter_state
+        if ctx.conditioning_mode == ConditioningMode.Both:
+            adapter_state = [torch.cat([v] * 2) for v in adapter_state]
+
+        if ctx.unet_kwargs.down_intrablock_additional_residuals is None:
+            ctx.unet_kwargs.down_intrablock_additional_residuals = [v * weight for v in adapter_state]
+        else:
+            for i, value in enumerate(adapter_state):
+                ctx.unet_kwargs.down_intrablock_additional_residuals[i] += value * weight

invokeai/backend/stable_diffusion/seamless.py

@@ -1,51 +0,0 @@
-from contextlib import contextmanager
-from typing import Callable, List, Optional, Tuple, Union
-
-import torch
-import torch.nn as nn
-from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
-from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny
-from diffusers.models.lora import LoRACompatibleConv
-from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
-
-
-@contextmanager
-def set_seamless(model: Union[UNet2DConditionModel, AutoencoderKL, AutoencoderTiny], seamless_axes: List[str]):
-    if not seamless_axes:
-        yield
-        return
-
-    # override conv_forward
-    # https://github.com/huggingface/diffusers/issues/556#issuecomment-1993287019
-    def _conv_forward_asymmetric(self, input: torch.Tensor, weight: torch.Tensor, bias: Optional[torch.Tensor] = None):
-        self.paddingX = (self._reversed_padding_repeated_twice[0], self._reversed_padding_repeated_twice[1], 0, 0)
-        self.paddingY = (0, 0, self._reversed_padding_repeated_twice[2], self._reversed_padding_repeated_twice[3])
-        working = torch.nn.functional.pad(input, self.paddingX, mode=x_mode)
-        working = torch.nn.functional.pad(working, self.paddingY, mode=y_mode)
-        return torch.nn.functional.conv2d(
-            working, weight, bias, self.stride, torch.nn.modules.utils._pair(0), self.dilation, self.groups
-        )
-
-    original_layers: List[Tuple[nn.Conv2d, Callable]] = []
-
-    try:
-        x_mode = "circular" if "x" in seamless_axes else "constant"
-        y_mode = "circular" if "y" in seamless_axes else "constant"
-
-        conv_layers: List[torch.nn.Conv2d] = []
-
-        for module in model.modules():
-            if isinstance(module, torch.nn.Conv2d):
-                conv_layers.append(module)
-
-        for layer in conv_layers:
-            if isinstance(layer, LoRACompatibleConv) and layer.lora_layer is None:
-                layer.lora_layer = lambda *x: 0
-            original_layers.append((layer, layer._conv_forward))
-            layer._conv_forward = _conv_forward_asymmetric.__get__(layer, torch.nn.Conv2d)
-
-        yield
-
-    finally:
-        for layer, orig_conv_forward in original_layers:
-            layer._conv_forward = orig_conv_forward

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

@@ -31,7 +31,8 @@
         "deleteBoard": "Delete Board",
         "deleteBoardAndImages": "Delete Board and Images",
         "deleteBoardOnly": "Delete Board Only",
-        "deletedBoardsCannotbeRestored": "Deleted boards cannot be restored",
+        "deletedBoardsCannotbeRestored": "Deleted boards cannot be restored. Selecting 'Delete Board Only' will move images to an uncategorized state.",
+        "deletedPrivateBoardsCannotbeRestored": "Deleted boards cannot be restored. Selecting 'Delete Board Only' will move images to a private uncategorized state for the image's creator.",
         "hideBoards": "Hide Boards",
         "loading": "Loading...",
         "menuItemAutoAdd": "Auto-add to this Board",
@@ -105,6 +106,7 @@
         "negativePrompt": "Negative Prompt",
         "discordLabel": "Discord",
         "dontAskMeAgain": "Don't ask me again",
+        "dontShowMeThese": "Don't show me these",
         "editor": "Editor",
         "error": "Error",
         "file": "File",
@@ -1099,6 +1101,8 @@
         "displayInProgress": "Display Progress Images",
         "enableImageDebugging": "Enable Image Debugging",
         "enableInformationalPopovers": "Enable Informational Popovers",
+        "informationalPopoversDisabled": "Informational Popovers Disabled",
+        "informationalPopoversDisabledDesc": "Informational popovers have been disabled. Enable them in Settings.",
         "enableInvisibleWatermark": "Enable Invisible Watermark",
         "enableNSFWChecker": "Enable NSFW Checker",
         "general": "General",
@@ -1506,6 +1510,30 @@
         "seamlessTilingYAxis": {
             "heading": "Seamless Tiling Y Axis",
             "paragraphs": ["Seamlessly tile an image along the vertical axis."]
+        },
+        "upscaleModel": {
+            "heading": "Upscale Model",
+            "paragraphs": [
+                "The upscale model scales the image to the output size before details are added. Any supported upscale model may be used, but some are specialized for different kinds of images, like photos or line drawings."
+            ]
+        },
+        "scale": {
+            "heading": "Scale",
+            "paragraphs": [
+                "Scale controls the output image size, and is based on a multiple of the input image resolution. For example a 2x upscale on a 1024x1024 image would produce a 2048 x 2048 output."
+            ]
+        },
+        "creativity": {
+            "heading": "Creativity",
+            "paragraphs": [
+                "Creativity controls the amount of freedom granted to the model when adding details. Low creativity stays close to the original image, while high creativity allows for more change. When using a prompt, high creativity increases the influence of the prompt."
+            ]
+        },
+        "structure": {
+            "heading": "Structure",
+            "paragraphs": [
+                "Structure controls how closely the output image will keep to the layout of the original. Low structure allows major changes, while high structure strictly maintains the original composition and layout."
+            ]
         }
     },
     "unifiedCanvas": {

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

@@ -10,32 +10,32 @@ import {
 import { boardsApi } from 'services/api/endpoints/boards';
 import { imagesApi } from 'services/api/endpoints/images';
 
+// Type inference doesn't work for this if you inline it in the listener for some reason
+const matchAnyBoardDeleted = isAnyOf(
+  imagesApi.endpoints.deleteBoard.matchFulfilled,
+  imagesApi.endpoints.deleteBoardAndImages.matchFulfilled
+);
+
 export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartListening) => {
   /**
    * The auto-add board shouldn't be set to an archived board or deleted board. When we archive a board, delete
    * a board, or change a the archived board visibility flag, we may need to reset the auto-add board.
    */
   startAppListening({
-    matcher: isAnyOf(
+    matcher: matchAnyBoardDeleted,
-      // If a board is deleted, we'll need to reset the auto-add board
-      imagesApi.endpoints.deleteBoard.matchFulfilled,
-      imagesApi.endpoints.deleteBoardAndImages.matchFulfilled
-    ),
     effect: async (action, { dispatch, getState }) => {
       const state = getState();
-      const queryArgs = selectListBoardsQueryArgs(state);
+      const deletedBoardId = action.meta.arg.originalArgs;
-      const queryResult = boardsApi.endpoints.listAllBoards.select(queryArgs)(state);
       const { autoAddBoardId, selectedBoardId } = state.gallery;
 
-      if (!queryResult.data) {
+      // If the deleted board was currently selected, we should reset the selected board to uncategorized
-        return;
+      if (deletedBoardId === selectedBoardId) {
-      }
-
-      if (!queryResult.data.find((board) => board.board_id === selectedBoardId)) {
         dispatch(boardIdSelected({ boardId: 'none' }));
         dispatch(galleryViewChanged('images'));
       }
-      if (!queryResult.data.find((board) => board.board_id === autoAddBoardId)) {
+
+      // If the deleted board was selected for auto-add, we should reset the auto-add board to uncategorized
+      if (deletedBoardId === autoAddBoardId) {
         dispatch(autoAddBoardIdChanged('none'));
       }
     },
@@ -46,14 +46,8 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
     matcher: boardsApi.endpoints.updateBoard.matchFulfilled,
     effect: async (action, { dispatch, getState }) => {
       const state = getState();
-      const queryArgs = selectListBoardsQueryArgs(state);
-      const queryResult = boardsApi.endpoints.listAllBoards.select(queryArgs)(state);
       const { shouldShowArchivedBoards } = state.gallery;
 
-      if (!queryResult.data) {
-        return;
-      }
-
       const wasArchived = action.meta.arg.originalArgs.changes.archived === true;
 
       if (wasArchived && !shouldShowArchivedBoards) {
@@ -71,7 +65,7 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
       const shouldShowArchivedBoards = action.payload;
 
       // We only need to take action if we have just hidden archived boards.
-      if (!shouldShowArchivedBoards) {
+      if (shouldShowArchivedBoards) {
         return;
       }
 
@@ -86,14 +80,16 @@ export const addArchivedOrDeletedBoardListener = (startAppListening: AppStartLis
 
       // Handle the case where selected board is archived
       const selectedBoard = queryResult.data.find((b) => b.board_id === selectedBoardId);
-      if (selectedBoard && selectedBoard.archived) {
+      if (!selectedBoard || selectedBoard.archived) {
+        // If we can't find the selected board or it's archived, we should reset the selected board to uncategorized
         dispatch(boardIdSelected({ boardId: 'none' }));
         dispatch(galleryViewChanged('images'));
       }
 
       // Handle the case where auto-add board is archived
       const autoAddBoard = queryResult.data.find((b) => b.board_id === autoAddBoardId);
-      if (autoAddBoard && autoAddBoard.archived) {
+      if (!autoAddBoard || autoAddBoard.archived) {
+        // If we can't find the auto-add board or it's archived, we should reset the selected board to uncategorized
         dispatch(autoAddBoardIdChanged('none'));
       }
     },

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

@@ -10,9 +10,12 @@ import {
   PopoverContent,
   PopoverTrigger,
   Portal,
+  Spacer,
   Text,
 } from '@invoke-ai/ui-library';
-import { useAppSelector } from 'app/store/storeHooks';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { setShouldEnableInformationalPopovers } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { merge, omit } from 'lodash-es';
 import type { ReactElement } from 'react';
 import { memo, useCallback, useMemo } from 'react';
@@ -71,7 +74,7 @@ type ContentProps = {
 
 const Content = ({ data, feature }: ContentProps) => {
   const { t } = useTranslation();
-
+  const dispatch = useAppDispatch();
   const heading = useMemo<string | undefined>(() => t(`popovers.${feature}.heading`), [feature, t]);
 
   const paragraphs = useMemo<string[]>(
@@ -82,16 +85,25 @@ const Content = ({ data, feature }: ContentProps) => {
     [feature, t]
   );
 
-  const handleClick = useCallback(() => {
+  const onClickLearnMore = useCallback(() => {
     if (!data?.href) {
       return;
     }
     window.open(data.href);
   }, [data?.href]);
 
+  const onClickDontShowMeThese = useCallback(() => {
+    dispatch(setShouldEnableInformationalPopovers(false));
+    toast({
+      title: t('settings.informationalPopoversDisabled'),
+      description: t('settings.informationalPopoversDisabledDesc'),
+      status: 'info',
+    });
+  }, [dispatch, t]);
+
   return (
-    <PopoverContent w={96}>
+    <PopoverContent maxW={300}>
-      <PopoverCloseButton />
+      <PopoverCloseButton top={2} />
       <PopoverBody>
         <Flex gap={2} flexDirection="column" alignItems="flex-start">
           {heading && (
@@ -116,21 +128,20 @@ const Content = ({ data, feature }: ContentProps) => {
           {paragraphs.map((p) => (
             <Text key={p}>{p}</Text>
           ))}
-          {data?.href && (
+
-            <>
           <Divider />
-              <Button
+          <Flex alignItems="center" justifyContent="space-between" w="full">
-                pt={1}
+            <Button onClick={onClickDontShowMeThese} variant="link" size="sm">
-                onClick={handleClick}
+              {t('common.dontShowMeThese')}
-                leftIcon={<PiArrowSquareOutBold />}
+            </Button>
-                alignSelf="flex-end"
+            <Spacer />
-                variant="link"
+            {data?.href && (
-              >
+              <Button onClick={onClickLearnMore} leftIcon={<PiArrowSquareOutBold />} variant="link" size="sm">
                 {t('common.learnMore') ?? heading}
               </Button>
-            </>
             )}
           </Flex>
+        </Flex>
       </PopoverBody>
     </PopoverContent>
   );

invokeai/frontend/web/src/common/components/InformationalPopover/constants.ts

@@ -53,7 +53,11 @@ export type Feature =
   | 'refinerCfgScale'
   | 'scaleBeforeProcessing'
   | 'seamlessTilingXAxis'
-  | 'seamlessTilingYAxis';
+  | 'seamlessTilingYAxis'
+  | 'upscaleModel'
+  | 'scale'
+  | 'creativity'
+  | 'structure';
 
 export type PopoverData = PopoverProps & {
   image?: string;

invokeai/frontend/web/src/features/gallery/components/Boards/DeleteBoardModal.tsx

@@ -120,7 +120,11 @@ const DeleteBoardModal = (props: Props) => {
                   bottomMessage={t('boards.bottomMessage')}
                 />
               )}
-              <Text>{t('boards.deletedBoardsCannotbeRestored')}</Text>
+              <Text>
+                {boardToDelete.is_private
+                  ? t('boards.deletedPrivateBoardsCannotbeRestored')
+                  : t('boards.deletedBoardsCannotbeRestored')}
+              </Text>
               <Text>
                 {canRestoreDeletedImagesFromBin ? t('gallery.deleteImageBin') : t('gallery.deleteImagePermanent')}
               </Text>

invokeai/frontend/web/src/features/modelManagerV2/hooks/useControlNetOrT2IAdapterDefaultSettings.ts

@@ -1,15 +1,10 @@
-import { skipToken } from '@reduxjs/toolkit/query';
 import { isNil } from 'lodash-es';
 import { useMemo } from 'react';
-import { useGetModelConfigWithTypeGuard } from 'services/api/hooks/useGetModelConfigWithTypeGuard';
+import type { ControlNetModelConfig, T2IAdapterModelConfig } from 'services/api/types';
-import { isControlNetOrT2IAdapterModelConfig } from 'services/api/types';
-
-export const useControlNetOrT2IAdapterDefaultSettings = (modelKey?: string | null) => {
-  const { modelConfig, isLoading } = useGetModelConfigWithTypeGuard(
-    modelKey ?? skipToken,
-    isControlNetOrT2IAdapterModelConfig
-  );
 
+export const useControlNetOrT2IAdapterDefaultSettings = (
+  modelConfig: ControlNetModelConfig | T2IAdapterModelConfig
+) => {
   const defaultSettingsDefaults = useMemo(() => {
     return {
       preprocessor: {
@@ -19,5 +14,5 @@ export const useControlNetOrT2IAdapterDefaultSettings = (modelKey?: string | nul
     };
   }, [modelConfig?.default_settings]);
 
-  return { defaultSettingsDefaults, isLoading };
+  return defaultSettingsDefaults;
 };

invokeai/frontend/web/src/features/modelManagerV2/hooks/useMainModelDefaultSettings.ts

@@ -1,12 +1,9 @@
-import { skipToken } from '@reduxjs/toolkit/query';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
-import { getOptimalDimension } from 'features/parameters/util/optimalDimension';
 import { selectConfigSlice } from 'features/system/store/configSlice';
 import { isNil } from 'lodash-es';
 import { useMemo } from 'react';
-import { useGetModelConfigWithTypeGuard } from 'services/api/hooks/useGetModelConfigWithTypeGuard';
+import type { MainModelConfig } from 'services/api/types';
-import { isNonRefinerMainModelConfig } from 'services/api/types';
 
 const initialStatesSelector = createMemoizedSelector(selectConfigSlice, (config) => {
   const { steps, guidance, scheduler, cfgRescaleMultiplier, vaePrecision, width, height } = config.sd;
@@ -22,9 +19,7 @@ const initialStatesSelector = createMemoizedSelector(selectConfigSlice, (config)
   };
 });
 
-export const useMainModelDefaultSettings = (modelKey?: string | null) => {
+export const useMainModelDefaultSettings = (modelConfig: MainModelConfig) => {
-  const { modelConfig, isLoading } = useGetModelConfigWithTypeGuard(modelKey ?? skipToken, isNonRefinerMainModelConfig);
-
   const {
     initialSteps,
     initialCfg,
@@ -81,5 +76,5 @@ export const useMainModelDefaultSettings = (modelKey?: string | null) => {
     initialHeight,
   ]);
 
-  return { defaultSettingsDefaults, isLoading, optimalDimension: getOptimalDimension(modelConfig) };
+  return defaultSettingsDefaults;
 };

invokeai/frontend/web/src/features/modelManagerV2/store/modelManagerV2Slice.ts

@@ -1,6 +1,6 @@
 import type { PayloadAction } from '@reduxjs/toolkit';
 import { createSlice } from '@reduxjs/toolkit';
-import type { PersistConfig } from 'app/store/store';
+import type { PersistConfig, RootState } from 'app/store/store';
 import type { ModelType } from 'services/api/types';
 
 export type FilterableModelType = Exclude<ModelType, 'onnx' | 'clip_vision'> | 'refiner';
@@ -50,6 +50,8 @@ export const modelManagerV2Slice = createSlice({
 export const { setSelectedModelKey, setSearchTerm, setFilteredModelType, setSelectedModelMode, setScanPath } =
   modelManagerV2Slice.actions;
 
+export const selectModelManagerV2Slice = (state: RootState) => state.modelmanagerV2;
+
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
 const migrateModelManagerState = (state: any): any => {
   if (!('_version' in state)) {

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/HuggingFaceFolder/HuggingFaceForm.tsx

@@ -1,13 +1,13 @@
 import { Button, Flex, FormControl, FormErrorMessage, FormHelperText, FormLabel, Input } from '@invoke-ai/ui-library';
 import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
 import type { ChangeEventHandler } from 'react';
-import { useCallback, useState } from 'react';
+import { memo, useCallback, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useLazyGetHuggingFaceModelsQuery } from 'services/api/endpoints/models';
 
 import { HuggingFaceResults } from './HuggingFaceResults';
 
-export const HuggingFaceForm = () => {
+export const HuggingFaceForm = memo(() => {
   const [huggingFaceRepo, setHuggingFaceRepo] = useState('');
   const [displayResults, setDisplayResults] = useState(false);
   const [errorMessage, setErrorMessage] = useState('');
@@ -66,4 +66,6 @@ export const HuggingFaceForm = () => {
       {data && data.urls && displayResults && <HuggingFaceResults results={data.urls} />}
     </Flex>
   );
-};
+});
+
+HuggingFaceForm.displayName = 'HuggingFaceForm';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/HuggingFaceFolder/HuggingFaceResultItem.tsx

@@ -1,13 +1,13 @@
 import { Flex, IconButton, Text } from '@invoke-ai/ui-library';
 import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
-import { useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiPlusBold } from 'react-icons/pi';
 
 type Props = {
   result: string;
 };
-export const HuggingFaceResultItem = ({ result }: Props) => {
+export const HuggingFaceResultItem = memo(({ result }: Props) => {
   const { t } = useTranslation();
 
   const [installModel] = useInstallModel();
@@ -27,4 +27,6 @@ export const HuggingFaceResultItem = ({ result }: Props) => {
       <IconButton aria-label={t('modelManager.install')} icon={<PiPlusBold />} onClick={onClick} size="sm" />
     </Flex>
   );
-};
+});
+
+HuggingFaceResultItem.displayName = 'HuggingFaceResultItem';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/HuggingFaceFolder/HuggingFaceResults.tsx

@@ -11,7 +11,7 @@ import {
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
 import type { ChangeEventHandler } from 'react';
-import { useCallback, useMemo, useState } from 'react';
+import { memo, useCallback, useMemo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiXBold } from 'react-icons/pi';
 
@@ -21,7 +21,7 @@ type HuggingFaceResultsProps = {
   results: string[];
 };
 
-export const HuggingFaceResults = ({ results }: HuggingFaceResultsProps) => {
+export const HuggingFaceResults = memo(({ results }: HuggingFaceResultsProps) => {
   const { t } = useTranslation();
   const [searchTerm, setSearchTerm] = useState('');
 
@@ -93,4 +93,6 @@ export const HuggingFaceResults = ({ results }: HuggingFaceResultsProps) => {
       </Flex>
     </>
   );
-};
+});
+
+HuggingFaceResults.displayName = 'HuggingFaceResults';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/InstallModelForm.tsx

@@ -1,7 +1,7 @@
 import { Button, Checkbox, Flex, FormControl, FormHelperText, FormLabel, Input } from '@invoke-ai/ui-library';
 import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
 import { t } from 'i18next';
-import { useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 
@@ -10,7 +10,7 @@ type SimpleImportModelConfig = {
   inplace: boolean;
 };
 
-export const InstallModelForm = () => {
+export const InstallModelForm = memo(() => {
   const [installModel, { isLoading }] = useInstallModel();
 
   const { register, handleSubmit, formState, reset } = useForm<SimpleImportModelConfig>({
@@ -74,4 +74,6 @@ export const InstallModelForm = () => {
       </Flex>
     </form>
   );
-};
+});
+
+InstallModelForm.displayName = 'InstallModelForm';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelInstallQueue/ModelInstallQueue.tsx

@@ -2,12 +2,12 @@ import { Box, Button, Flex, Heading } from '@invoke-ai/ui-library';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import { useListModelInstallsQuery, usePruneCompletedModelInstallsMutation } from 'services/api/endpoints/models';
 
 import { ModelInstallQueueItem } from './ModelInstallQueueItem';
 
-export const ModelInstallQueue = () => {
+export const ModelInstallQueue = memo(() => {
   const { data } = useListModelInstallsQuery();
 
   const [_pruneCompletedModelInstalls] = usePruneCompletedModelInstallsMutation();
@@ -61,4 +61,6 @@ export const ModelInstallQueue = () => {
       </Box>
     </Flex>
   );
-};
+});
+
+ModelInstallQueue.displayName = 'ModelInstallQueue';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ModelInstallQueue/ModelInstallQueueItem.tsx

@@ -2,7 +2,7 @@ import { Flex, IconButton, Progress, Text, Tooltip } from '@invoke-ai/ui-library
 import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { isNil } from 'lodash-es';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import { PiXBold } from 'react-icons/pi';
 import { useCancelModelInstallMutation } from 'services/api/endpoints/models';
 import type { ModelInstallJob } from 'services/api/types';
@@ -25,7 +25,7 @@ const formatBytes = (bytes: number) => {
   return `${bytes.toFixed(2)} ${units[i]}`;
 };
 
-export const ModelInstallQueueItem = (props: ModelListItemProps) => {
+export const ModelInstallQueueItem = memo((props: ModelListItemProps) => {
   const { installJob } = props;
 
   const [deleteImportModel] = useCancelModelInstallMutation();
@@ -124,7 +124,9 @@ export const ModelInstallQueueItem = (props: ModelListItemProps) => {
       />
     </Flex>
   );
-};
+});
+
+ModelInstallQueueItem.displayName = 'ModelInstallQueueItem';
 
 type TooltipLabelProps = {
   installJob: ModelInstallJob;
@@ -132,7 +134,7 @@ type TooltipLabelProps = {
   source: string;
 };
 
-const TooltipLabel = ({ name, source, installJob }: TooltipLabelProps) => {
+const TooltipLabel = memo(({ name, source, installJob }: TooltipLabelProps) => {
   const progressString = useMemo(() => {
     if (installJob.status !== 'downloading' || installJob.bytes === undefined || installJob.total_bytes === undefined) {
       return '';
@@ -156,4 +158,6 @@ const TooltipLabel = ({ name, source, installJob }: TooltipLabelProps) => {
       )}
     </>
   );
-};
+});
+
+TooltipLabel.displayName = 'TooltipLabel';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanFolder/ScanFolderForm.tsx

@@ -2,13 +2,13 @@ import { Button, Flex, FormControl, FormErrorMessage, FormHelperText, FormLabel,
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { setScanPath } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import type { ChangeEventHandler } from 'react';
-import { useCallback, useState } from 'react';
+import { memo, useCallback, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useLazyScanFolderQuery } from 'services/api/endpoints/models';
 
 import { ScanModelsResults } from './ScanFolderResults';
 
-export const ScanModelsForm = () => {
+export const ScanModelsForm = memo(() => {
   const scanPath = useAppSelector((state) => state.modelmanagerV2.scanPath);
   const dispatch = useAppDispatch();
   const [errorMessage, setErrorMessage] = useState('');
@@ -56,4 +56,6 @@ export const ScanModelsForm = () => {
       {data && <ScanModelsResults results={data} />}
     </Flex>
   );
-};
+});
+
+ScanModelsForm.displayName = 'ScanModelsForm';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanFolder/ScanFolderResultItem.tsx

@@ -1,5 +1,5 @@
 import { Badge, Box, Flex, IconButton, Text } from '@invoke-ai/ui-library';
-import { useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiPlusBold } from 'react-icons/pi';
 import type { ScanFolderResponse } from 'services/api/endpoints/models';
@@ -8,7 +8,7 @@ type Props = {
   result: ScanFolderResponse[number];
   installModel: (source: string) => void;
 };
-export const ScanModelResultItem = ({ result, installModel }: Props) => {
+export const ScanModelResultItem = memo(({ result, installModel }: Props) => {
   const { t } = useTranslation();
 
   const handleInstall = useCallback(() => {
@@ -30,4 +30,6 @@ export const ScanModelResultItem = ({ result, installModel }: Props) => {
       </Box>
     </Flex>
   );
-};
+});
+
+ScanModelResultItem.displayName = 'ScanModelResultItem';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/ScanFolder/ScanFolderResults.tsx

@@ -14,7 +14,7 @@ import {
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
 import type { ChangeEvent, ChangeEventHandler } from 'react';
-import { useCallback, useMemo, useState } from 'react';
+import { memo, useCallback, useMemo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiXBold } from 'react-icons/pi';
 import type { ScanFolderResponse } from 'services/api/endpoints/models';
@@ -25,7 +25,7 @@ type ScanModelResultsProps = {
   results: ScanFolderResponse;
 };
 
-export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
+export const ScanModelsResults = memo(({ results }: ScanModelResultsProps) => {
   const { t } = useTranslation();
   const [searchTerm, setSearchTerm] = useState('');
   const [inplace, setInplace] = useState(true);
@@ -116,4 +116,6 @@ export const ScanModelsResults = ({ results }: ScanModelResultsProps) => {
       </Flex>
     </>
   );
-};
+});
+
+ScanModelsResults.displayName = 'ScanModelsResults';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/StarterModels/StartModelsResultItem.tsx

@@ -1,7 +1,7 @@
 import { Badge, Box, Flex, IconButton, Text } from '@invoke-ai/ui-library';
 import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
 import ModelBaseBadge from 'features/modelManagerV2/subpanels/ModelManagerPanel/ModelBaseBadge';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiPlusBold } from 'react-icons/pi';
 import type { GetStarterModelsResponse } from 'services/api/endpoints/models';
@@ -9,7 +9,7 @@ import type { GetStarterModelsResponse } from 'services/api/endpoints/models';
 type Props = {
   result: GetStarterModelsResponse[number];
 };
-export const StarterModelsResultItem = ({ result }: Props) => {
+export const StarterModelsResultItem = memo(({ result }: Props) => {
   const { t } = useTranslation();
   const allSources = useMemo(() => {
     const _allSources = [{ source: result.source, config: { name: result.name, description: result.description } }];
@@ -47,4 +47,6 @@ export const StarterModelsResultItem = ({ result }: Props) => {
       </Box>
     </Flex>
   );
-};
+});
+
+StarterModelsResultItem.displayName = 'StarterModelsResultItem';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/StarterModels/StarterModelsForm.tsx

@@ -1,10 +1,11 @@
 import { Flex } from '@invoke-ai/ui-library';
 import { FetchingModelsLoader } from 'features/modelManagerV2/subpanels/ModelManagerPanel/FetchingModelsLoader';
+import { memo } from 'react';
 import { useGetStarterModelsQuery } from 'services/api/endpoints/models';
 
 import { StarterModelsResults } from './StarterModelsResults';
 
-export const StarterModelsForm = () => {
+export const StarterModelsForm = memo(() => {
   const { isLoading, data } = useGetStarterModelsQuery();
 
   return (
@@ -13,4 +14,6 @@ export const StarterModelsForm = () => {
       {data && <StarterModelsResults results={data} />}
     </Flex>
   );
-};
+});
+
+StarterModelsForm.displayName = 'StarterModelsForm';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/AddModelPanel/StarterModels/StarterModelsResults.tsx

@@ -1,7 +1,7 @@
 import { Flex, IconButton, Input, InputGroup, InputRightElement } from '@invoke-ai/ui-library';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import type { ChangeEventHandler } from 'react';
-import { useCallback, useMemo, useState } from 'react';
+import { memo, useCallback, useMemo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiXBold } from 'react-icons/pi';
 import type { GetStarterModelsResponse } from 'services/api/endpoints/models';
@@ -12,7 +12,7 @@ type StarterModelsResultsProps = {
   results: NonNullable<GetStarterModelsResponse>;
 };
 
-export const StarterModelsResults = ({ results }: StarterModelsResultsProps) => {
+export const StarterModelsResults = memo(({ results }: StarterModelsResultsProps) => {
   const { t } = useTranslation();
   const [searchTerm, setSearchTerm] = useState('');
 
@@ -79,4 +79,6 @@ export const StarterModelsResults = ({ results }: StarterModelsResultsProps) =>
       </Flex>
     </Flex>
   );
-};
+});
+
+StarterModelsResults.displayName = 'StarterModelsResults';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/InstallModels.tsx

@@ -2,7 +2,7 @@ import { Box, Flex, Heading, Tab, TabList, TabPanel, TabPanels, Tabs } from '@in
 import { useStore } from '@nanostores/react';
 import { StarterModelsForm } from 'features/modelManagerV2/subpanels/AddModelPanel/StarterModels/StarterModelsForm';
 import { atom } from 'nanostores';
-import { useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 
 import { HuggingFaceForm } from './AddModelPanel/HuggingFaceFolder/HuggingFaceForm';
@@ -12,7 +12,7 @@ import { ScanModelsForm } from './AddModelPanel/ScanFolder/ScanFolderForm';
 
 export const $installModelsTab = atom(0);
 
-export const InstallModels = () => {
+export const InstallModels = memo(() => {
   const { t } = useTranslation();
   const index = useStore($installModelsTab);
   const onChange = useCallback((index: number) => {
@@ -49,4 +49,6 @@ export const InstallModels = () => {
       </Box>
     </Flex>
   );
-};
+});
+
+InstallModels.displayName = 'InstallModels';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManager.tsx

@@ -1,14 +1,14 @@
 import { Button, Flex, Heading } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
-import { useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiPlusBold } from 'react-icons/pi';
 
 import ModelList from './ModelManagerPanel/ModelList';
 import { ModelListNavigation } from './ModelManagerPanel/ModelListNavigation';
 
-export const ModelManager = () => {
+export const ModelManager = memo(() => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
   const handleClickAddModel = useCallback(() => {
@@ -29,4 +29,6 @@ export const ModelManager = () => {
       </Flex>
     </Flex>
   );
-};
+});
+
+ModelManager.displayName = 'ModelManager';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelList.tsx

@@ -21,7 +21,8 @@ import { FetchingModelsLoader } from './FetchingModelsLoader';
 import { ModelListWrapper } from './ModelListWrapper';
 
 const ModelList = () => {
-  const { searchTerm, filteredModelType } = useAppSelector((s) => s.modelmanagerV2);
+  const filteredModelType = useAppSelector((s) => s.modelmanagerV2.filteredModelType);
+  const searchTerm = useAppSelector((s) => s.modelmanagerV2.searchTerm);
   const { t } = useTranslation();
 
   const [mainModels, { isLoading: isLoadingMainModels }] = useMainModels();

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListItem.tsx

@@ -1,7 +1,8 @@
 import type { SystemStyleObject } from '@invoke-ai/ui-library';
 import { ConfirmationAlertDialog, Flex, IconButton, Spacer, Text, useDisclosure } from '@invoke-ai/ui-library';
+import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
+import { selectModelManagerV2Slice, setSelectedModelKey } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import ModelBaseBadge from 'features/modelManagerV2/subpanels/ModelManagerPanel/ModelBaseBadge';
 import ModelFormatBadge from 'features/modelManagerV2/subpanels/ModelManagerPanel/ModelFormatBadge';
 import { toast } from 'features/toast/toast';
@@ -23,15 +24,21 @@ const sx: SystemStyleObject = {
   "&[aria-selected='true']": { bg: 'base.700' },
 };
 
-const ModelListItem = (props: ModelListItemProps) => {
+const ModelListItem = ({ model }: ModelListItemProps) => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
-  const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
+  const selectIsSelected = useMemo(
+    () =>
+      createSelector(
+        selectModelManagerV2Slice,
+        (modelManagerV2Slice) => modelManagerV2Slice.selectedModelKey === model.key
+      ),
+    [model.key]
+  );
+  const isSelected = useAppSelector(selectIsSelected);
   const [deleteModel] = useDeleteModelsMutation();
   const { isOpen, onOpen, onClose } = useDisclosure();
 
-  const { model } = props;
-
   const handleSelectModel = useCallback(() => {
     dispatch(setSelectedModelKey(model.key));
   }, [model.key, dispatch]);
@@ -43,11 +50,6 @@ const ModelListItem = (props: ModelListItemProps) => {
     },
     [onOpen]
   );
-
-  const isSelected = useMemo(() => {
-    return selectedModelKey === model.key;
-  }, [selectedModelKey, model.key]);
-
   const handleModelDelete = useCallback(() => {
     deleteModel({ key: model.key })
       .unwrap()

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListNavigation.tsx

@@ -3,12 +3,12 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { setSearchTerm } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { t } from 'i18next';
 import type { ChangeEventHandler } from 'react';
-import { useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import { PiXBold } from 'react-icons/pi';
 
 import { ModelTypeFilter } from './ModelTypeFilter';
 
-export const ModelListNavigation = () => {
+export const ModelListNavigation = memo(() => {
   const dispatch = useAppDispatch();
   const searchTerm = useAppSelector((s) => s.modelmanagerV2.searchTerm);
 
@@ -49,4 +49,6 @@ export const ModelListNavigation = () => {
       </InputGroup>
     </Flex>
   );
-};
+});
+
+ModelListNavigation.displayName = 'ModelListNavigation';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelListWrapper.tsx

@@ -1,4 +1,5 @@
 import { StickyScrollable } from 'features/system/components/StickyScrollable';
+import { memo } from 'react';
 import type { AnyModelConfig } from 'services/api/types';
 
 import ModelListItem from './ModelListItem';
@@ -8,7 +9,7 @@ type ModelListWrapperProps = {
   modelList: AnyModelConfig[];
 };
 
-export const ModelListWrapper = (props: ModelListWrapperProps) => {
+export const ModelListWrapper = memo((props: ModelListWrapperProps) => {
   const { title, modelList } = props;
   return (
     <StickyScrollable title={title} contentSx={{ gap: 1, p: 2 }}>
@@ -17,4 +18,6 @@ export const ModelListWrapper = (props: ModelListWrapperProps) => {
       ))}
     </StickyScrollable>
   );
-};
+});
+
+ModelListWrapper.displayName = 'ModelListWrapper';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelManagerPanel/ModelTypeFilter.tsx

@@ -2,12 +2,12 @@ import { Button, Menu, MenuButton, MenuItem, MenuList } from '@invoke-ai/ui-libr
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import type { FilterableModelType } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { setFilteredModelType } from 'features/modelManagerV2/store/modelManagerV2Slice';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiFunnelBold } from 'react-icons/pi';
 import { objectKeys } from 'tsafe';
 
-export const ModelTypeFilter = () => {
+export const ModelTypeFilter = memo(() => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
   const MODEL_TYPE_LABELS: Record<FilterableModelType, string> = useMemo(
@@ -57,4 +57,6 @@ export const ModelTypeFilter = () => {
       </MenuList>
     </Menu>
   );
-};
+});
+
+ModelTypeFilter.displayName = 'ModelTypeFilter';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPane.tsx

@@ -1,14 +1,17 @@
 import { Box } from '@invoke-ai/ui-library';
 import { useAppSelector } from 'app/store/storeHooks';
+import { memo } from 'react';
 
 import { InstallModels } from './InstallModels';
 import { Model } from './ModelPanel/Model';
 
-export const ModelPane = () => {
+export const ModelPane = memo(() => {
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
   return (
     <Box layerStyle="first" p={4} borderRadius="base" w="50%" h="full">
       {selectedModelKey ? <Model key={selectedModelKey} /> : <InstallModels />}
     </Box>
   );
-};
+});
+
+ModelPane.displayName = 'ModelPane';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ControlNetOrT2IAdapterDefaultSettings/ControlNetOrT2IAdapterDefaultSettings.tsx

@@ -1,26 +1,28 @@
-import { Button, Flex, Heading, SimpleGrid, Text } from '@invoke-ai/ui-library';
+import { Button, Flex, Heading, SimpleGrid } from '@invoke-ai/ui-library';
-import { useAppSelector } from 'app/store/storeHooks';
 import { useControlNetOrT2IAdapterDefaultSettings } from 'features/modelManagerV2/hooks/useControlNetOrT2IAdapterDefaultSettings';
 import { DefaultPreprocessor } from 'features/modelManagerV2/subpanels/ModelPanel/ControlNetOrT2IAdapterDefaultSettings/DefaultPreprocessor';
 import type { FormField } from 'features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/MainModelDefaultSettings';
 import { toast } from 'features/toast/toast';
-import { useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
 import { PiCheckBold } from 'react-icons/pi';
 import { useUpdateModelMutation } from 'services/api/endpoints/models';
+import type { ControlNetModelConfig, T2IAdapterModelConfig } from 'services/api/types';
 
 export type ControlNetOrT2IAdapterDefaultSettingsFormData = {
   preprocessor: FormField<string>;
 };
 
-export const ControlNetOrT2IAdapterDefaultSettings = () => {
+type Props = {
-  const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
+  modelConfig: ControlNetModelConfig | T2IAdapterModelConfig;
+};
+
+export const ControlNetOrT2IAdapterDefaultSettings = memo(({ modelConfig }: Props) => {
   const { t } = useTranslation();
 
-  const { defaultSettingsDefaults, isLoading: isLoadingDefaultSettings } =
+  const defaultSettingsDefaults = useControlNetOrT2IAdapterDefaultSettings(modelConfig);
-    useControlNetOrT2IAdapterDefaultSettings(selectedModelKey);
 
   const [updateModel, { isLoading: isLoadingUpdateModel }] = useUpdateModelMutation();
 
@@ -30,16 +32,12 @@ export const ControlNetOrT2IAdapterDefaultSettings = () => {
 
   const onSubmit = useCallback<SubmitHandler<ControlNetOrT2IAdapterDefaultSettingsFormData>>(
     (data) => {
-      if (!selectedModelKey) {
-        return;
-      }
-
       const body = {
         preprocessor: data.preprocessor.isEnabled ? data.preprocessor.value : null,
       };
 
       updateModel({
-        key: selectedModelKey,
+        key: modelConfig.key,
         body: { default_settings: body },
       })
         .unwrap()
@@ -61,13 +59,9 @@ export const ControlNetOrT2IAdapterDefaultSettings = () => {
           }
         });
     },
-    [selectedModelKey, reset, updateModel, t]
+    [updateModel, modelConfig.key, t, reset]
   );
 
-  if (isLoadingDefaultSettings) {
-    return <Text>{t('common.loading')}</Text>;
-  }
-
   return (
     <>
       <Flex gap="4" justifyContent="space-between" w="full" pb={4}>
@@ -89,4 +83,6 @@ export const ControlNetOrT2IAdapterDefaultSettings = () => {
       </SimpleGrid>
     </>
   );
-};
+});
+
+ControlNetOrT2IAdapterDefaultSettings.displayName = 'ControlNetOrT2IAdapterDefaultSettings';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ControlNetOrT2IAdapterDefaultSettings/DefaultPreprocessor.tsx

@@ -4,7 +4,7 @@ import { InformationalPopover } from 'common/components/InformationalPopover/Inf
 import type { ControlNetOrT2IAdapterDefaultSettingsFormData } from 'features/modelManagerV2/subpanels/ModelPanel/ControlNetOrT2IAdapterDefaultSettings/ControlNetOrT2IAdapterDefaultSettings';
 import type { FormField } from 'features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/MainModelDefaultSettings';
 import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
@@ -28,7 +28,7 @@ const OPTIONS = [
 
 type DefaultSchedulerType = ControlNetOrT2IAdapterDefaultSettingsFormData['preprocessor'];
 
-export function DefaultPreprocessor(props: UseControllerProps<ControlNetOrT2IAdapterDefaultSettingsFormData>) {
+export const DefaultPreprocessor = memo((props: UseControllerProps<ControlNetOrT2IAdapterDefaultSettingsFormData>) => {
   const { t } = useTranslation();
   const { field } = useController(props);
 
@@ -63,4 +63,6 @@ export function DefaultPreprocessor(props: UseControllerProps<ControlNetOrT2IAda
       <Combobox isDisabled={isDisabled} value={value} options={OPTIONS} onChange={onChange} />
     </FormControl>
   );
-}
+});
+
+DefaultPreprocessor.displayName = 'DefaultPreprocessor';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultCfgRescaleMultiplier.tsx

@@ -2,7 +2,7 @@ import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } f
 import { useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
@@ -11,7 +11,7 @@ import type { MainModelDefaultSettingsFormData } from './MainModelDefaultSetting
 
 type DefaultCfgRescaleMultiplierType = MainModelDefaultSettingsFormData['cfgRescaleMultiplier'];
 
-export function DefaultCfgRescaleMultiplier(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
+export const DefaultCfgRescaleMultiplier = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
   const { field } = useController(props);
 
   const sliderMin = useAppSelector((s) => s.config.sd.cfgRescaleMultiplier.sliderMin);
@@ -74,4 +74,6 @@ export function DefaultCfgRescaleMultiplier(props: UseControllerProps<MainModelD
       </Flex>
     </FormControl>
   );
-}
+});
+
+DefaultCfgRescaleMultiplier.displayName = 'DefaultCfgRescaleMultiplier';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultCfgScale.tsx

@@ -2,7 +2,7 @@ import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } f
 import { useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
@@ -11,7 +11,7 @@ import type { MainModelDefaultSettingsFormData } from './MainModelDefaultSetting
 
 type DefaultCfgType = MainModelDefaultSettingsFormData['cfgScale'];
 
-export function DefaultCfgScale(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
+export const DefaultCfgScale = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
   const { field } = useController(props);
 
   const sliderMin = useAppSelector((s) => s.config.sd.guidance.sliderMin);
@@ -74,4 +74,6 @@ export function DefaultCfgScale(props: UseControllerProps<MainModelDefaultSettin
       </Flex>
     </FormControl>
   );
-}
+});
+
+DefaultCfgScale.displayName = 'DefaultCfgScale';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultHeight.tsx

@@ -2,7 +2,7 @@ import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } f
 import { useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
@@ -16,7 +16,7 @@ type Props = {
   optimalDimension: number;
 };
 
-export function DefaultHeight({ control, optimalDimension }: Props) {
+export const DefaultHeight = memo(({ control, optimalDimension }: Props) => {
   const { field } = useController({ control, name: 'height' });
   const sliderMin = useAppSelector((s) => s.config.sd.height.sliderMin);
   const sliderMax = useAppSelector((s) => s.config.sd.height.sliderMax);
@@ -78,4 +78,6 @@ export function DefaultHeight({ control, optimalDimension }: Props) {
       </Flex>
     </FormControl>
   );
-}
+});
+
+DefaultHeight.displayName = 'DefaultHeight';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultScheduler.tsx

@@ -4,7 +4,7 @@ import { InformationalPopover } from 'common/components/InformationalPopover/Inf
 import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
 import { SCHEDULER_OPTIONS } from 'features/parameters/types/constants';
 import { isParameterScheduler } from 'features/parameters/types/parameterSchemas';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
@@ -13,7 +13,7 @@ import type { MainModelDefaultSettingsFormData } from './MainModelDefaultSetting
 
 type DefaultSchedulerType = MainModelDefaultSettingsFormData['scheduler'];
 
-export function DefaultScheduler(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
+export const DefaultScheduler = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
   const { t } = useTranslation();
   const { field } = useController(props);
 
@@ -51,4 +51,6 @@ export function DefaultScheduler(props: UseControllerProps<MainModelDefaultSetti
       <Combobox isDisabled={isDisabled} value={value} options={SCHEDULER_OPTIONS} onChange={onChange} />
     </FormControl>
   );
-}
+});
+
+DefaultScheduler.displayName = 'DefaultScheduler';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultSteps.tsx

@@ -2,7 +2,7 @@ import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } f
 import { useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
@@ -11,7 +11,7 @@ import type { MainModelDefaultSettingsFormData } from './MainModelDefaultSetting
 
 type DefaultSteps = MainModelDefaultSettingsFormData['steps'];
 
-export function DefaultSteps(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
+export const DefaultSteps = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
   const { field } = useController(props);
 
   const sliderMin = useAppSelector((s) => s.config.sd.steps.sliderMin);
@@ -74,4 +74,6 @@ export function DefaultSteps(props: UseControllerProps<MainModelDefaultSettingsF
       </Flex>
     </FormControl>
   );
-}
+});
+
+DefaultSteps.displayName = 'DefaultSteps';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultVae.tsx

@@ -4,7 +4,7 @@ import { skipToken } from '@reduxjs/toolkit/query';
 import { useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
@@ -15,7 +15,7 @@ import type { MainModelDefaultSettingsFormData } from './MainModelDefaultSetting
 
 type DefaultVaeType = MainModelDefaultSettingsFormData['vae'];
 
-export function DefaultVae(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
+export const DefaultVae = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
   const { t } = useTranslation();
   const { field } = useController(props);
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
@@ -64,4 +64,6 @@ export function DefaultVae(props: UseControllerProps<MainModelDefaultSettingsFor
       <Combobox isDisabled={isDisabled} value={value} options={compatibleOptions} onChange={onChange} />
     </FormControl>
   );
-}
+});
+
+DefaultVae.displayName = 'DefaultVae';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultVaePrecision.tsx

@@ -3,7 +3,7 @@ import { Combobox, Flex, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
 import { isParameterPrecision } from 'features/parameters/types/parameterSchemas';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
@@ -17,7 +17,7 @@ const options = [
 
 type DefaultVaePrecisionType = MainModelDefaultSettingsFormData['vaePrecision'];
 
-export function DefaultVaePrecision(props: UseControllerProps<MainModelDefaultSettingsFormData>) {
+export const DefaultVaePrecision = memo((props: UseControllerProps<MainModelDefaultSettingsFormData>) => {
   const { t } = useTranslation();
   const { field } = useController(props);
 
@@ -52,4 +52,6 @@ export function DefaultVaePrecision(props: UseControllerProps<MainModelDefaultSe
       <Combobox isDisabled={isDisabled} value={value} options={options} onChange={onChange} />
     </FormControl>
   );
-}
+});
+
+DefaultVaePrecision.displayName = 'DefaultVaePrecision';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultWidth.tsx

@@ -2,7 +2,7 @@ import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } f
 import { useAppSelector } from 'app/store/storeHooks';
 import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { SettingToggle } from 'features/modelManagerV2/subpanels/ModelPanel/SettingToggle';
-import { useCallback, useMemo } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
 import { useController } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
@@ -16,7 +16,7 @@ type Props = {
   optimalDimension: number;
 };
 
-export function DefaultWidth({ control, optimalDimension }: Props) {
+export const DefaultWidth = memo(({ control, optimalDimension }: Props) => {
   const { field } = useController({ control, name: 'width' });
   const sliderMin = useAppSelector((s) => s.config.sd.width.sliderMin);
   const sliderMax = useAppSelector((s) => s.config.sd.width.sliderMax);
@@ -78,4 +78,6 @@ export function DefaultWidth({ control, optimalDimension }: Props) {
       </Flex>
     </FormControl>
   );
-}
+});
+
+DefaultWidth.displayName = 'DefaultWidth';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/MainModelDefaultSettings.tsx

@@ -1,16 +1,18 @@
-import { Button, Flex, Heading, SimpleGrid, Text } from '@invoke-ai/ui-library';
+import { Button, Flex, Heading, SimpleGrid } from '@invoke-ai/ui-library';
 import { useAppSelector } from 'app/store/storeHooks';
 import { useMainModelDefaultSettings } from 'features/modelManagerV2/hooks/useMainModelDefaultSettings';
 import { DefaultHeight } from 'features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultHeight';
 import { DefaultWidth } from 'features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultWidth';
 import type { ParameterScheduler } from 'features/parameters/types/parameterSchemas';
+import { getOptimalDimension } from 'features/parameters/util/optimalDimension';
 import { toast } from 'features/toast/toast';
-import { useCallback } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
 import { PiCheckBold } from 'react-icons/pi';
 import { useUpdateModelMutation } from 'services/api/endpoints/models';
+import type { MainModelConfig } from 'services/api/types';
 
 import { DefaultCfgRescaleMultiplier } from './DefaultCfgRescaleMultiplier';
 import { DefaultCfgScale } from './DefaultCfgScale';
@@ -35,16 +37,16 @@ export type MainModelDefaultSettingsFormData = {
   height: FormField<number>;
 };
 
-export const MainModelDefaultSettings = () => {
+type Props = {
+  modelConfig: MainModelConfig;
+};
+
+export const MainModelDefaultSettings = memo(({ modelConfig }: Props) => {
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
   const { t } = useTranslation();
 
-  const {
+  const defaultSettingsDefaults = useMainModelDefaultSettings(modelConfig);
-    defaultSettingsDefaults,
+  const optimalDimension = useMemo(() => getOptimalDimension(modelConfig), [modelConfig]);
-    isLoading: isLoadingDefaultSettings,
-    optimalDimension,
-  } = useMainModelDefaultSettings(selectedModelKey);
-
   const [updateModel, { isLoading: isLoadingUpdateModel }] = useUpdateModelMutation();
 
   const { handleSubmit, control, formState, reset } = useForm<MainModelDefaultSettingsFormData>({
@@ -94,10 +96,6 @@ export const MainModelDefaultSettings = () => {
     [selectedModelKey, reset, updateModel, t]
   );
 
-  if (isLoadingDefaultSettings) {
-    return <Text>{t('common.loading')}</Text>;
-  }
-
   return (
     <>
       <Flex gap="4" justifyContent="space-between" w="full" pb={4}>
@@ -126,4 +124,6 @@ export const MainModelDefaultSettings = () => {
       </SimpleGrid>
     </>
   );
-};
+});
+
+MainModelDefaultSettings.displayName = 'MainModelDefaultSettings';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/Model.tsx

@@ -1,120 +1,47 @@
-import { Button, Flex, Heading, Spacer, Text } from '@invoke-ai/ui-library';
+import { useAppSelector } from 'app/store/storeHooks';
-import { skipToken } from '@reduxjs/toolkit/query';
+import { IAINoContentFallback, IAINoContentFallbackWithSpinner } from 'common/components/IAIImageFallback';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { memo, useMemo } from 'react';
-import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
-import { ModelConvertButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelConvertButton';
-import { ModelEditButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelEditButton';
-import { toast } from 'features/toast/toast';
-import { useCallback } from 'react';
-import type { SubmitHandler } from 'react-hook-form';
-import { useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
-import { PiCheckBold, PiXBold } from 'react-icons/pi';
+import { PiExclamationMarkBold } from 'react-icons/pi';
-import type { UpdateModelArg } from 'services/api/endpoints/models';
+import { modelConfigsAdapterSelectors, useGetModelConfigsQuery } from 'services/api/endpoints/models';
-import { useGetModelConfigQuery, useUpdateModelMutation } from 'services/api/endpoints/models';
 
-import ModelImageUpload from './Fields/ModelImageUpload';
 import { ModelEdit } from './ModelEdit';
 import { ModelView } from './ModelView';
 
-export const Model = () => {
+export const Model = memo(() => {
   const { t } = useTranslation();
   const selectedModelMode = useAppSelector((s) => s.modelmanagerV2.selectedModelMode);
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
-  const { data, isLoading } = useGetModelConfigQuery(selectedModelKey ?? skipToken);
+  const { data: modelConfigs, isLoading } = useGetModelConfigsQuery();
-  const [updateModel, { isLoading: isSubmitting }] = useUpdateModelMutation();
+  const modelConfig = useMemo(() => {
-  const dispatch = useAppDispatch();
+    if (!modelConfigs) {
+      return null;
+    }
+    if (selectedModelKey === null) {
+      return null;
+    }
+    const modelConfig = modelConfigsAdapterSelectors.selectById(modelConfigs, selectedModelKey);
 
-  const form = useForm<UpdateModelArg['body']>({
+    if (!modelConfig) {
-    defaultValues: data,
+      return null;
-    mode: 'onChange',
-  });
-
-  const onSubmit = useCallback<SubmitHandler<UpdateModelArg['body']>>(
-    (values) => {
-      if (!data?.key) {
-        return;
     }
 
-      const responseBody: UpdateModelArg = {
+    return modelConfig;
-        key: data.key,
+  }, [modelConfigs, selectedModelKey]);
-        body: values,
-      };
-
-      updateModel(responseBody)
-        .unwrap()
-        .then((payload) => {
-          form.reset(payload, { keepDefaultValues: true });
-          dispatch(setSelectedModelMode('view'));
-          toast({
-            id: 'MODEL_UPDATED',
-            title: t('modelManager.modelUpdated'),
-            status: 'success',
-          });
-        })
-        .catch((_) => {
-          form.reset();
-          toast({
-            id: 'MODEL_UPDATE_FAILED',
-            title: t('modelManager.modelUpdateFailed'),
-            status: 'error',
-          });
-        });
-    },
-    [dispatch, data?.key, form, t, updateModel]
-  );
-
-  const handleClickCancel = useCallback(() => {
-    dispatch(setSelectedModelMode('view'));
-  }, [dispatch]);
 
   if (isLoading) {
-    return <Text>{t('common.loading')}</Text>;
+    return <IAINoContentFallbackWithSpinner label={t('common.loading')} />;
   }
 
-  if (!data) {
+  if (!modelConfig) {
-    return <Text>{t('common.somethingWentWrong')}</Text>;
+    return <IAINoContentFallback label={t('common.somethingWentWrong')} icon={PiExclamationMarkBold} />;
   }
 
-  return (
+  if (selectedModelMode === 'view') {
-    <Flex flexDir="column" gap={4}>
+    return <ModelView modelConfig={modelConfig} />;
-      <Flex alignItems="flex-start" gap={4}>
+  }
-        <ModelImageUpload model_key={selectedModelKey} model_image={data.cover_image} />
+
-        <Flex flexDir="column" gap={1} flexGrow={1} minW={0}>
+  return <ModelEdit modelConfig={modelConfig} />;
-          <Flex gap={2}>
+});
-            <Heading as="h2" fontSize="lg" noOfLines={1} wordBreak="break-all">
+
-              {data.name}
+Model.displayName = 'Model';
-            </Heading>
-            <Spacer />
-            {selectedModelMode === 'view' && <ModelConvertButton modelKey={selectedModelKey} />}
-            {selectedModelMode === 'view' && <ModelEditButton />}
-            {selectedModelMode === 'edit' && (
-              <Button size="sm" onClick={handleClickCancel} leftIcon={<PiXBold />}>
-                {t('common.cancel')}
-              </Button>
-            )}
-            {selectedModelMode === 'edit' && (
-              <Button
-                size="sm"
-                colorScheme="invokeYellow"
-                leftIcon={<PiCheckBold />}
-                onClick={form.handleSubmit(onSubmit)}
-                isLoading={isSubmitting}
-                isDisabled={Boolean(Object.keys(form.formState.errors).length)}
-              >
-                {t('common.save')}
-              </Button>
-            )}
-          </Flex>
-          {data.source && (
-            <Text variant="subtext" noOfLines={1} wordBreak="break-all">
-              {t('modelManager.source')}: {data?.source}
-            </Text>
-          )}
-          <Text noOfLines={3}>{data.description}</Text>
-        </Flex>
-      </Flex>
-      {selectedModelMode === 'view' ? <ModelView /> : <ModelEdit form={form} onSubmit={onSubmit} />}
-    </Flex>
-  );
-};

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelAttrView.tsx

@@ -1,11 +1,12 @@
 import { FormControl, FormLabel, Text } from '@invoke-ai/ui-library';
+import { memo } from 'react';
 
 interface Props {
   label: string;
   value: string | null | undefined;
 }
 
-export const ModelAttrView = ({ label, value }: Props) => {
+export const ModelAttrView = memo(({ label, value }: Props) => {
   return (
     <FormControl flexDir="column" alignItems="flex-start" gap={0}>
       <FormLabel>{label}</FormLabel>
@@ -14,4 +15,6 @@ export const ModelAttrView = ({ label, value }: Props) => {
       </Text>
     </FormControl>
   );
-};
+});
+
+ModelAttrView.displayName = 'ModelAttrView';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelConvertButton.tsx

@@ -8,52 +8,46 @@ import {
   UnorderedList,
   useDisclosure,
 } from '@invoke-ai/ui-library';
-import { skipToken } from '@reduxjs/toolkit/query';
 import { toast } from 'features/toast/toast';
-import { useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
-import { useConvertModelMutation, useGetModelConfigQuery } from 'services/api/endpoints/models';
+import { useConvertModelMutation } from 'services/api/endpoints/models';
+import type { CheckpointModelConfig } from 'services/api/types';
 
 interface ModelConvertProps {
-  modelKey: string | null;
+  modelConfig: CheckpointModelConfig;
 }
 
-export const ModelConvertButton = (props: ModelConvertProps) => {
+export const ModelConvertButton = memo(({ modelConfig }: ModelConvertProps) => {
-  const { modelKey } = props;
   const { t } = useTranslation();
-  const { data } = useGetModelConfigQuery(modelKey ?? skipToken);
   const [convertModel, { isLoading }] = useConvertModelMutation();
   const { isOpen, onOpen, onClose } = useDisclosure();
 
   const modelConvertHandler = useCallback(() => {
-    if (!data || isLoading) {
+    if (!modelConfig || isLoading) {
       return;
     }
 
-    const toastId = `CONVERTING_MODEL_${data.key}`;
+    const toastId = `CONVERTING_MODEL_${modelConfig.key}`;
     toast({
       id: toastId,
-      title: `${t('modelManager.convertingModelBegin')}: ${data?.name}`,
+      title: `${t('modelManager.convertingModelBegin')}: ${modelConfig.name}`,
       status: 'info',
     });
 
-    convertModel(data?.key)
+    convertModel(modelConfig.key)
       .unwrap()
       .then(() => {
-        toast({ id: toastId, title: `${t('modelManager.modelConverted')}: ${data?.name}`, status: 'success' });
+        toast({ id: toastId, title: `${t('modelManager.modelConverted')}: ${modelConfig.name}`, status: 'success' });
       })
       .catch(() => {
         toast({
           id: toastId,
-          title: `${t('modelManager.modelConversionFailed')}: ${data?.name}`,
+          title: `${t('modelManager.modelConversionFailed')}: ${modelConfig.name}`,
           status: 'error',
         });
       });
-  }, [data, isLoading, t, convertModel]);
+  }, [modelConfig, isLoading, t, convertModel]);
-
-  if (data?.format !== 'checkpoint') {
-    return;
-  }
 
   return (
     <>
@@ -68,7 +62,7 @@ export const ModelConvertButton = (props: ModelConvertProps) => {
         🧨 {t('modelManager.convert')}
       </Button>
       <ConfirmationAlertDialog
-        title={`${t('modelManager.convert')} ${data?.name}`}
+        title={`${t('modelManager.convert')} ${modelConfig.name}`}
         acceptCallback={modelConvertHandler}
         acceptButtonText={`${t('modelManager.convert')}`}
         isOpen={isOpen}
@@ -96,4 +90,6 @@ export const ModelConvertButton = (props: ModelConvertProps) => {
       </ConfirmationAlertDialog>
     </>
   );
-};
+});
+
+ModelConvertButton.displayName = 'ModelConvertButton';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEdit.tsx

@@ -1,4 +1,5 @@
 import {
+  Button,
   Checkbox,
   Flex,
   FormControl,
@@ -7,47 +8,102 @@ import {
   Heading,
   Input,
   SimpleGrid,
-  Text,
   Textarea,
 } from '@invoke-ai/ui-library';
-import { skipToken } from '@reduxjs/toolkit/query';
+import { useAppDispatch } from 'app/store/storeHooks';
-import { useAppSelector } from 'app/store/storeHooks';
+import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
-import type { SubmitHandler, UseFormReturn } from 'react-hook-form';
+import { ModelHeader } from 'features/modelManagerV2/subpanels/ModelPanel/ModelHeader';
+import { toast } from 'features/toast/toast';
+import { memo, useCallback } from 'react';
+import { type SubmitHandler, useForm } from 'react-hook-form';
 import { useTranslation } from 'react-i18next';
-import type { UpdateModelArg } from 'services/api/endpoints/models';
+import { PiCheckBold, PiXBold } from 'react-icons/pi';
-import { useGetModelConfigQuery } from 'services/api/endpoints/models';
+import { type UpdateModelArg, useUpdateModelMutation } from 'services/api/endpoints/models';
+import type { AnyModelConfig } from 'services/api/types';
 
 import BaseModelSelect from './Fields/BaseModelSelect';
 import ModelVariantSelect from './Fields/ModelVariantSelect';
 import PredictionTypeSelect from './Fields/PredictionTypeSelect';
 
 type Props = {
-  form: UseFormReturn<UpdateModelArg['body']>;
+  modelConfig: AnyModelConfig;
-  onSubmit: SubmitHandler<UpdateModelArg['body']>;
 };
 
 const stringFieldOptions = {
   validate: (value?: string | null) => (value && value.trim().length > 3) || 'Must be at least 3 characters',
 };
 
-export const ModelEdit = ({ form }: Props) => {
+export const ModelEdit = memo(({ modelConfig }: Props) => {
-  const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
-  const { data, isLoading } = useGetModelConfigQuery(selectedModelKey ?? skipToken);
   const { t } = useTranslation();
+  const [updateModel, { isLoading: isSubmitting }] = useUpdateModelMutation();
+  const dispatch = useAppDispatch();
 
-  if (isLoading) {
+  const form = useForm<UpdateModelArg['body']>({
-    return <Text>{t('common.loading')}</Text>;
+    defaultValues: modelConfig,
-  }
+    mode: 'onChange',
+  });
 
-  if (!data) {
+  const onSubmit = useCallback<SubmitHandler<UpdateModelArg['body']>>(
-    return <Text>{t('common.somethingWentWrong')}</Text>;
+    (values) => {
-  }
+      const responseBody: UpdateModelArg = {
+        key: modelConfig.key,
+        body: values,
+      };
+
+      updateModel(responseBody)
+        .unwrap()
+        .then((payload) => {
+          form.reset(payload, { keepDefaultValues: true });
+          dispatch(setSelectedModelMode('view'));
+          toast({
+            id: 'MODEL_UPDATED',
+            title: t('modelManager.modelUpdated'),
+            status: 'success',
+          });
+        })
+        .catch((_) => {
+          form.reset();
+          toast({
+            id: 'MODEL_UPDATE_FAILED',
+            title: t('modelManager.modelUpdateFailed'),
+            status: 'error',
+          });
+        });
+    },
+    [dispatch, modelConfig.key, form, t, updateModel]
+  );
+
+  const handleClickCancel = useCallback(() => {
+    dispatch(setSelectedModelMode('view'));
+  }, [dispatch]);
 
   return (
+    <Flex flexDir="column" gap={4}>
+      <ModelHeader modelConfig={modelConfig}>
+        <Button flexShrink={0} size="sm" onClick={handleClickCancel} leftIcon={<PiXBold />}>
+          {t('common.cancel')}
+        </Button>
+        <Button
+          flexShrink={0}
+          size="sm"
+          colorScheme="invokeYellow"
+          leftIcon={<PiCheckBold />}
+          onClick={form.handleSubmit(onSubmit)}
+          isLoading={isSubmitting}
+          isDisabled={Boolean(Object.keys(form.formState.errors).length)}
+        >
+          {t('common.save')}
+        </Button>
+      </ModelHeader>
       <Flex flexDir="column" h="full">
         <form>
           <Flex w="full" justifyContent="space-between" gap={4} alignItems="center">
-          <FormControl flexDir="column" alignItems="flex-start" gap={1} isInvalid={Boolean(form.formState.errors.name)}>
+            <FormControl
+              flexDir="column"
+              alignItems="flex-start"
+              gap={1}
+              isInvalid={Boolean(form.formState.errors.name)}
+            >
               <FormLabel>{t('modelManager.modelName')}</FormLabel>
               <Input {...form.register('name', stringFieldOptions)} size="md" />
 
@@ -72,13 +128,13 @@ export const ModelEdit = ({ form }: Props) => {
                 <FormLabel>{t('modelManager.baseModel')}</FormLabel>
                 <BaseModelSelect control={form.control} />
               </FormControl>
-            {data.type === 'main' && (
+              {modelConfig.type === 'main' && (
                 <FormControl flexDir="column" alignItems="flex-start" gap={1}>
                   <FormLabel>{t('modelManager.variant')}</FormLabel>
                   <ModelVariantSelect control={form.control} />
                 </FormControl>
               )}
-            {data.type === 'main' && data.format === 'checkpoint' && (
+              {modelConfig.type === 'main' && modelConfig.format === 'checkpoint' && (
                 <>
                   <FormControl flexDir="column" alignItems="flex-start" gap={1}>
                     <FormLabel>{t('modelManager.pathToConfig')}</FormLabel>
@@ -98,5 +154,8 @@ export const ModelEdit = ({ form }: Props) => {
           </Flex>
         </form>
       </Flex>
+    </Flex>
   );
-};
+});
+
+ModelEdit.displayName = 'ModelEdit';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelEditButton.tsx

@@ -1,11 +1,11 @@
 import { Button } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
-import { useCallback } from 'react';
+import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { IoPencil } from 'react-icons/io5';
 
-export const ModelEditButton = () => {
+export const ModelEditButton = memo(() => {
   const { t } = useTranslation();
   const dispatch = useAppDispatch();
 
@@ -18,4 +18,6 @@ export const ModelEditButton = () => {
       {t('modelManager.edit')}
     </Button>
   );
-};
+});
+
+ModelEditButton.displayName = 'ModelEditButton';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelHeader.tsx

@@ -0,0 +1,36 @@
+import { Flex, Heading, Spacer, Text } from '@invoke-ai/ui-library';
+import ModelImageUpload from 'features/modelManagerV2/subpanels/ModelPanel/Fields/ModelImageUpload';
+import type { PropsWithChildren } from 'react';
+import { memo } from 'react';
+import { useTranslation } from 'react-i18next';
+import type { AnyModelConfig } from 'services/api/types';
+
+type Props = PropsWithChildren<{
+  modelConfig: AnyModelConfig;
+}>;
+
+export const ModelHeader = memo(({ modelConfig, children }: Props) => {
+  const { t } = useTranslation();
+  return (
+    <Flex alignItems="flex-start" gap={4}>
+      <ModelImageUpload model_key={modelConfig.key} model_image={modelConfig.cover_image} />
+      <Flex flexDir="column" gap={1} flexGrow={1} minW={0}>
+        <Flex gap={2}>
+          <Heading as="h2" fontSize="lg" noOfLines={1} wordBreak="break-all">
+            {modelConfig.name}
+          </Heading>
+          <Spacer />
+          {children}
+        </Flex>
+        {modelConfig.source && (
+          <Text variant="subtext" noOfLines={1} wordBreak="break-all">
+            {t('modelManager.source')}: {modelConfig.source}
+          </Text>
+        )}
+        <Text noOfLines={3}>{modelConfig.description}</Text>
+      </Flex>
+    </Flex>
+  );
+});
+
+ModelHeader.displayName = 'ModelHeader';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/ModelView.tsx

@@ -1,55 +1,67 @@
-import { Box, Flex, SimpleGrid, Text } from '@invoke-ai/ui-library';
+import { Box, Flex, SimpleGrid } from '@invoke-ai/ui-library';
-import { skipToken } from '@reduxjs/toolkit/query';
-import { useAppSelector } from 'app/store/storeHooks';
 import { ControlNetOrT2IAdapterDefaultSettings } from 'features/modelManagerV2/subpanels/ModelPanel/ControlNetOrT2IAdapterDefaultSettings/ControlNetOrT2IAdapterDefaultSettings';
+import { ModelConvertButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelConvertButton';
+import { ModelEditButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelEditButton';
+import { ModelHeader } from 'features/modelManagerV2/subpanels/ModelPanel/ModelHeader';
 import { TriggerPhrases } from 'features/modelManagerV2/subpanels/ModelPanel/TriggerPhrases';
+import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
-import { useGetModelConfigQuery } from 'services/api/endpoints/models';
+import type { AnyModelConfig } from 'services/api/types';
 
 import { MainModelDefaultSettings } from './MainModelDefaultSettings/MainModelDefaultSettings';
 import { ModelAttrView } from './ModelAttrView';
 
-export const ModelView = () => {
+type Props = {
+  modelConfig: AnyModelConfig;
+};
+
+export const ModelView = memo(({ modelConfig }: Props) => {
   const { t } = useTranslation();
-  const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
-  const { data, isLoading } = useGetModelConfigQuery(selectedModelKey ?? skipToken);
-
-  if (isLoading) {
-    return <Text>{t('common.loading')}</Text>;
-  }
-
-  if (!data) {
-    return <Text>{t('common.somethingWentWrong')}</Text>;
-  }
   return (
+    <Flex flexDir="column" gap={4}>
+      <ModelHeader modelConfig={modelConfig}>
+        {modelConfig.format === 'checkpoint' && modelConfig.type === 'main' && (
+          <ModelConvertButton modelConfig={modelConfig} />
+        )}
+        <ModelEditButton />
+      </ModelHeader>
       <Flex flexDir="column" h="full" gap={4}>
         <Box layerStyle="second" borderRadius="base" p={4}>
           <SimpleGrid columns={2} gap={4}>
-          <ModelAttrView label={t('modelManager.baseModel')} value={data.base} />
+            <ModelAttrView label={t('modelManager.baseModel')} value={modelConfig.base} />
-          <ModelAttrView label={t('modelManager.modelType')} value={data.type} />
+            <ModelAttrView label={t('modelManager.modelType')} value={modelConfig.type} />
-          <ModelAttrView label={t('common.format')} value={data.format} />
+            <ModelAttrView label={t('common.format')} value={modelConfig.format} />
-          <ModelAttrView label={t('modelManager.path')} value={data.path} />
+            <ModelAttrView label={t('modelManager.path')} value={modelConfig.path} />
-          {data.type === 'main' && <ModelAttrView label={t('modelManager.variant')} value={data.variant} />}
+            {modelConfig.type === 'main' && (
-          {data.type === 'main' && data.format === 'diffusers' && data.repo_variant && (
+              <ModelAttrView label={t('modelManager.variant')} value={modelConfig.variant} />
-            <ModelAttrView label={t('modelManager.repoVariant')} value={data.repo_variant} />
             )}
-          {data.type === 'main' && data.format === 'checkpoint' && (
+            {modelConfig.type === 'main' && modelConfig.format === 'diffusers' && modelConfig.repo_variant && (
+              <ModelAttrView label={t('modelManager.repoVariant')} value={modelConfig.repo_variant} />
+            )}
+            {modelConfig.type === 'main' && modelConfig.format === 'checkpoint' && (
               <>
-              <ModelAttrView label={t('modelManager.pathToConfig')} value={data.config_path} />
+                <ModelAttrView label={t('modelManager.pathToConfig')} value={modelConfig.config_path} />
-              <ModelAttrView label={t('modelManager.predictionType')} value={data.prediction_type} />
+                <ModelAttrView label={t('modelManager.predictionType')} value={modelConfig.prediction_type} />
-              <ModelAttrView label={t('modelManager.upcastAttention')} value={`${data.upcast_attention}`} />
+                <ModelAttrView label={t('modelManager.upcastAttention')} value={`${modelConfig.upcast_attention}`} />
               </>
             )}
-          {data.type === 'ip_adapter' && data.format === 'invokeai' && (
+            {modelConfig.type === 'ip_adapter' && modelConfig.format === 'invokeai' && (
-            <ModelAttrView label={t('modelManager.imageEncoderModelId')} value={data.image_encoder_model_id} />
+              <ModelAttrView label={t('modelManager.imageEncoderModelId')} value={modelConfig.image_encoder_model_id} />
             )}
           </SimpleGrid>
         </Box>
         <Box layerStyle="second" borderRadius="base" p={4}>
-        {data.type === 'main' && data.base !== 'sdxl-refiner' && <MainModelDefaultSettings />}
+          {modelConfig.type === 'main' && modelConfig.base !== 'sdxl-refiner' && (
-        {(data.type === 'controlnet' || data.type === 't2i_adapter') && <ControlNetOrT2IAdapterDefaultSettings />}
+            <MainModelDefaultSettings modelConfig={modelConfig} />
-        {(data.type === 'main' || data.type === 'lora') && <TriggerPhrases />}
+          )}
+          {(modelConfig.type === 'controlnet' || modelConfig.type === 't2i_adapter') && (
+            <ControlNetOrT2IAdapterDefaultSettings modelConfig={modelConfig} />
+          )}
+          {(modelConfig.type === 'main' || modelConfig.type === 'lora') && <TriggerPhrases modelConfig={modelConfig} />}
         </Box>
       </Flex>
+    </Flex>
   );
-};
+});
+
+ModelView.displayName = 'ModelView';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/SettingToggle.tsx

@@ -1,4 +1,4 @@
-import { Switch } from '@invoke-ai/ui-library';
+import { Switch, typedMemo } from '@invoke-ai/ui-library';
 import type { ChangeEvent } from 'react';
 import { useCallback, useMemo } from 'react';
 import type { UseControllerProps } from 'react-hook-form';
@@ -6,7 +6,7 @@ import { useController } from 'react-hook-form';
 
 import type { FormField } from './MainModelDefaultSettings/MainModelDefaultSettings';
 
-export function SettingToggle<T, F extends Record<string, FormField<T>>>(props: UseControllerProps<F>) {
+export const SettingToggle = typedMemo(<T, F extends Record<string, FormField<T>>>(props: UseControllerProps<F>) => {
   const { field } = useController(props);
 
   const value = useMemo(() => {
@@ -25,4 +25,6 @@ export function SettingToggle<T, F extends Record<string, FormField<T>>>(props:
   );
 
   return <Switch size="sm" isChecked={value} onChange={onChange} />;
-}
+});
+
+SettingToggle.displayName = 'SettingToggle';

invokeai/frontend/web/src/features/modelManagerV2/subpanels/ModelPanel/TriggerPhrases.tsx

@@ -9,19 +9,19 @@ import {
   TagCloseButton,
   TagLabel,
 } from '@invoke-ai/ui-library';
-import { skipToken } from '@reduxjs/toolkit/query';
-import { useAppSelector } from 'app/store/storeHooks';
 import type { ChangeEvent } from 'react';
-import { useCallback, useMemo, useState } from 'react';
+import { memo, useCallback, useMemo, useState } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiPlusBold } from 'react-icons/pi';
-import { useGetModelConfigQuery, useUpdateModelMutation } from 'services/api/endpoints/models';
+import { useUpdateModelMutation } from 'services/api/endpoints/models';
-import { isLoRAModelConfig, isNonRefinerMainModelConfig } from 'services/api/types';
+import type { LoRAModelConfig, MainModelConfig } from 'services/api/types';
 
-export const TriggerPhrases = () => {
+type Props = {
+  modelConfig: MainModelConfig | LoRAModelConfig;
+};
+
+export const TriggerPhrases = memo(({ modelConfig }: Props) => {
   const { t } = useTranslation();
-  const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
-  const { currentData: modelConfig } = useGetModelConfigQuery(selectedModelKey ?? skipToken);
   const [phrase, setPhrase] = useState('');
 
   const [updateModel, { isLoading }] = useUpdateModelMutation();
@@ -31,9 +31,6 @@ export const TriggerPhrases = () => {
   }, []);
 
   const triggerPhrases = useMemo(() => {
-    if (!modelConfig || (!isNonRefinerMainModelConfig(modelConfig) && !isLoRAModelConfig(modelConfig))) {
-      return [];
-    }
     return modelConfig?.trigger_phrases || [];
   }, [modelConfig]);
 
@@ -48,10 +45,6 @@ export const TriggerPhrases = () => {
   }, [phrase, triggerPhrases]);
 
   const addTriggerPhrase = useCallback(async () => {
-    if (!selectedModelKey) {
-      return;
-    }
-
     if (!phrase.length || triggerPhrases.includes(phrase)) {
       return;
     }
@@ -59,22 +52,18 @@ export const TriggerPhrases = () => {
     setPhrase('');
 
     await updateModel({
-      key: selectedModelKey,
+      key: modelConfig.key,
       body: { trigger_phrases: [...triggerPhrases, phrase] },
     }).unwrap();
-  }, [updateModel, selectedModelKey, phrase, triggerPhrases]);
+  }, [phrase, triggerPhrases, updateModel, modelConfig.key]);
 
   const removeTriggerPhrase = useCallback(
     async (phraseToRemove: string) => {
-      if (!selectedModelKey) {
-        return;
-      }
-
       const filteredPhrases = triggerPhrases.filter((p) => p !== phraseToRemove);
 
-      await updateModel({ key: selectedModelKey, body: { trigger_phrases: filteredPhrases } }).unwrap();
+      await updateModel({ key: modelConfig.key, body: { trigger_phrases: filteredPhrases } }).unwrap();
     },
-    [updateModel, selectedModelKey, triggerPhrases]
+    [triggerPhrases, updateModel, modelConfig]
   );
 
   const onTriggerPhraseAddFormSubmit = useCallback(
@@ -103,7 +92,9 @@ export const TriggerPhrases = () => {
                 {t('common.add')}
               </Button>
             </Flex>
-            {!!errors.length && errors.map((error) => <FormErrorMessage key={error}>{error}</FormErrorMessage>)}
+            {errors.map((error) => (
+              <FormErrorMessage key={error}>{error}</FormErrorMessage>
+            ))}
           </Flex>
         </FormControl>
       </form>
@@ -118,4 +109,6 @@ export const TriggerPhrases = () => {
       </Flex>
     </Flex>
   );
-};
+});
+
+TriggerPhrases.displayName = 'TriggerPhrases';

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

@@ -59,17 +59,19 @@ const pasteSelection = (withEdgesToCopiedNodes?: boolean) => {
     for (const edge of copiedEdges) {
       if (edge.source === node.id) {
         edge.source = id;
-        edge.id = edge.id.replace(node.data.id, id);
+      } else if (edge.target === node.id) {
-      }
-      if (edge.target === node.id) {
         edge.target = id;
-        edge.id = edge.id.replace(node.data.id, id);
       }
     }
     node.id = id;
     node.data.id = id;
   });
 
+  copiedEdges.forEach((edge) => {
+    // Copied edges need a fresh id too
+    edge.id = uuidv4();
+  });
+
   const nodeChanges: NodeChange[] = [];
   const edgeChanges: EdgeChange[] = [];
   // Deselect existing nodes

invokeai/frontend/web/src/features/parameters/components/Upscale/ParamCreativity.tsx

@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { creativityChanged } from 'features/parameters/store/upscaleSlice';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -25,7 +26,9 @@ const ParamCreativity = () => {
 
   return (
     <FormControl>
+      <InformationalPopover feature="creativity">
         <FormLabel>{t('upscaling.creativity')}</FormLabel>
+      </InformationalPopover>
       <CompositeSlider
         value={creativity}
         defaultValue={initial}

invokeai/frontend/web/src/features/parameters/components/Upscale/ParamSpandrelModel.tsx

@@ -1,5 +1,6 @@
 import { Box, Combobox, FormControl, FormLabel, Tooltip } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { useModelCombobox } from 'common/hooks/useModelCombobox';
 import { upscaleModelChanged } from 'features/parameters/store/upscaleSlice';
 import { memo, useCallback, useMemo } from 'react';
@@ -37,7 +38,9 @@ const ParamSpandrelModel = () => {
 
   return (
     <FormControl orientation="vertical">
+      <InformationalPopover feature="upscaleModel">
         <FormLabel>{t('upscaling.upscaleModel')}</FormLabel>
+      </InformationalPopover>
       <Tooltip label={tooltipLabel}>
         <Box w="full">
           <Combobox

invokeai/frontend/web/src/features/parameters/components/Upscale/ParamStructure.tsx

@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { structureChanged } from 'features/parameters/store/upscaleSlice';
 import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -25,7 +26,9 @@ const ParamStructure = () => {
 
   return (
     <FormControl>
+      <InformationalPopover feature="structure">
         <FormLabel>{t('upscaling.structure')}</FormLabel>
+      </InformationalPopover>
       <CompositeSlider
         value={structure}
         defaultValue={initial}

invokeai/frontend/web/src/features/settingsAccordions/components/AdvancedSettingsAccordion/AdvancedSettingsAccordion.tsx

@@ -64,7 +64,7 @@ export const AdvancedSettingsAccordion = memo(() => {
   const badges = useAppSelector(selectBadges);
   const { t } = useTranslation();
   const { isOpen, onToggle } = useStandaloneAccordionToggle({
-    id: 'advanced-settings',
+    id: `'advanced-settings-${activeTabName}`,
     defaultIsOpen: false,
   });
 

invokeai/frontend/web/src/features/settingsAccordions/components/GenerationSettingsAccordion/GenerationSettingsAccordion.tsx

@@ -14,6 +14,7 @@ import ParamMainModelSelect from 'features/parameters/components/MainModel/Param
 import { UseDefaultSettingsButton } from 'features/parameters/components/MainModel/UseDefaultSettingsButton';
 import { useExpanderToggle } from 'features/settingsAccordions/hooks/useExpanderToggle';
 import { useStandaloneAccordionToggle } from 'features/settingsAccordions/hooks/useStandaloneAccordionToggle';
+import { activeTabNameSelector } from 'features/ui/store/uiSelectors';
 import { filter } from 'lodash-es';
 import { memo, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -26,6 +27,7 @@ const formLabelProps: FormLabelProps = {
 export const GenerationSettingsAccordion = memo(() => {
   const { t } = useTranslation();
   const modelConfig = useSelectedModelConfig();
+  const activeTabName = useAppSelector(activeTabNameSelector);
   const selectBadges = useMemo(
     () =>
       createMemoizedSelector(selectLoraSlice, (lora) => {
@@ -42,8 +44,8 @@ export const GenerationSettingsAccordion = memo(() => {
     defaultIsOpen: false,
   });
   const { isOpen: isOpenAccordion, onToggle: onToggleAccordion } = useStandaloneAccordionToggle({
-    id: 'generation-settings',
+    id: `generation-settings-${activeTabName}`,
-    defaultIsOpen: true,
+    defaultIsOpen: activeTabName !== 'upscaling',
   });
 
   return (

invokeai/frontend/web/src/features/settingsAccordions/components/UpscaleSettingsAccordion/UpscaleScaleSlider.tsx

@@ -1,5 +1,6 @@
 import { CompositeNumberInput, CompositeSlider, Flex, FormControl, FormLabel } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { InformationalPopover } from 'common/components/InformationalPopover/InformationalPopover';
 import { scaleChanged } from 'features/parameters/store/upscaleSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -22,7 +23,9 @@ export const UpscaleScaleSlider = memo(() => {
 
   return (
     <FormControl orientation="vertical" gap={0}>
+      <InformationalPopover feature="scale">
         <FormLabel m={0}>{t('upscaling.scale')}</FormLabel>
+      </InformationalPopover>
       <Flex w="full" gap={4}>
         <CompositeSlider
           min={2}

invokeai/frontend/web/src/features/settingsAccordions/hooks/useStandaloneAccordionToggle.ts

@@ -18,5 +18,6 @@ export const useStandaloneAccordionToggle = (arg: UseStandaloneAccordionToggleAr
   const onToggle = useCallback(() => {
     dispatch(accordionStateChanged({ id: arg.id, isOpen: !isOpen }));
   }, [arg.id, dispatch, isOpen]);
+
   return { isOpen, onToggle };
 };

invokeai/frontend/web/src/features/system/store/systemSlice.ts

@@ -27,7 +27,7 @@ const initialSystemState: SystemState = {
   language: 'en',
   shouldUseNSFWChecker: false,
   shouldUseWatermarker: false,
-  shouldEnableInformationalPopovers: false,
+  shouldEnableInformationalPopovers: true,
   status: 'DISCONNECTED',
   cancellations: [],
 };

invokeai/frontend/web/src/services/api/endpoints/models.ts

@@ -242,7 +242,6 @@ export const modelsApi = api.injectEndpoints({
         }
         return tags;
       },
-      keepUnusedDataFor: 60 * 60 * 1000 * 24, // 1 day (infinite)
       transformResponse: (response: GetModelConfigsResponse) => {
         return modelConfigsAdapter.setAll(modelConfigsAdapter.getInitialState(), response.models);
       },

invokeai/frontend/web/src/services/api/types.ts

@@ -54,7 +54,7 @@ export type T2IAdapterModelConfig = S['T2IAdapterConfig'];
 export type SpandrelImageToImageModelConfig = S['SpandrelImageToImageConfig'];
 type TextualInversionModelConfig = S['TextualInversionFileConfig'] | S['TextualInversionFolderConfig'];
 type DiffusersModelConfig = S['MainDiffusersConfig'];
-type CheckpointModelConfig = S['MainCheckpointConfig'];
+export type CheckpointModelConfig = S['MainCheckpointConfig'];
 type CLIPVisionDiffusersConfig = S['CLIPVisionDiffusersConfig'];
 export type MainModelConfig = DiffusersModelConfig | CheckpointModelConfig;
 export type AnyModelConfig =

invokeai/version/invokeai_version.py

@@ -1 +1 @@
-__version__ = "4.2.7rc1"
+__version__ = "4.2.7"