chore: release v4.2.9.dev10

stupid events

invokeai/app/invocations/fields.py

@@ -45,11 +45,13 @@ class UIType(str, Enum, metaclass=MetaEnum):
     SDXLRefinerModel = "SDXLRefinerModelField"
     ONNXModel = "ONNXModelField"
     VAEModel = "VAEModelField"
+    FluxVAEModel = "FluxVAEModelField"
     LoRAModel = "LoRAModelField"
     ControlNetModel = "ControlNetModelField"
     IPAdapterModel = "IPAdapterModelField"
     T2IAdapterModel = "T2IAdapterModelField"
     T5EncoderModel = "T5EncoderModelField"
+    CLIPEmbedModel = "CLIPEmbedModelField"
     SpandrelImageToImageModel = "SpandrelImageToImageModelField"
     # endregion
 
@@ -128,6 +130,7 @@ class FieldDescriptions:
     noise = "Noise tensor"
     clip = "CLIP (tokenizer, text encoder, LoRAs) and skipped layer count"
     t5_encoder = "T5 tokenizer and text encoder"
+    clip_embed_model = "CLIP Embed loader"
     unet = "UNet (scheduler, LoRAs)"
     transformer = "Transformer"
     vae = "VAE"

invokeai/app/invocations/flux_text_encoder.py

@@ -40,7 +40,10 @@ class FluxTextEncoderInvocation(BaseInvocation):
 
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> FluxConditioningOutput:
-        t5_embeddings, clip_embeddings = self._encode_prompt(context)
+        # Note: The T5 and CLIP encoding are done in separate functions to ensure that all model references are locally
+        # scoped. This ensures that the T5 model can be freed and gc'd before loading the CLIP model (if necessary).
+        t5_embeddings = self._t5_encode(context)
+        clip_embeddings = self._clip_encode(context)
         conditioning_data = ConditioningFieldData(
             conditionings=[FLUXConditioningInfo(clip_embeds=clip_embeddings, t5_embeds=t5_embeddings)]
         )
@@ -48,12 +51,7 @@ class FluxTextEncoderInvocation(BaseInvocation):
         conditioning_name = context.conditioning.save(conditioning_data)
         return FluxConditioningOutput.build(conditioning_name)
 
-    def _encode_prompt(self, context: InvocationContext) -> tuple[torch.Tensor, torch.Tensor]:
-        # Load CLIP.
-        clip_tokenizer_info = context.models.load(self.clip.tokenizer)
-        clip_text_encoder_info = context.models.load(self.clip.text_encoder)
-
-        # Load T5.
+    def _t5_encode(self, context: InvocationContext) -> torch.Tensor:
         t5_tokenizer_info = context.models.load(self.t5_encoder.tokenizer)
         t5_text_encoder_info = context.models.load(self.t5_encoder.text_encoder)
 
@@ -70,6 +68,15 @@ class FluxTextEncoderInvocation(BaseInvocation):
 
             prompt_embeds = t5_encoder(prompt)
 
+        assert isinstance(prompt_embeds, torch.Tensor)
+        return prompt_embeds
+
+    def _clip_encode(self, context: InvocationContext) -> torch.Tensor:
+        clip_tokenizer_info = context.models.load(self.clip.tokenizer)
+        clip_text_encoder_info = context.models.load(self.clip.text_encoder)
+
+        prompt = [self.prompt]
+
         with (
             clip_text_encoder_info as clip_text_encoder,
             clip_tokenizer_info as clip_tokenizer,
@@ -81,6 +88,5 @@ class FluxTextEncoderInvocation(BaseInvocation):
 
             pooled_prompt_embeds = clip_encoder(prompt)
 
-        assert isinstance(prompt_embeds, torch.Tensor)
         assert isinstance(pooled_prompt_embeds, torch.Tensor)
-        return prompt_embeds, pooled_prompt_embeds
+        return pooled_prompt_embeds

invokeai/app/invocations/flux_text_to_image.py

@@ -58,13 +58,7 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
 
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        # Load the conditioning data.
-        cond_data = context.conditioning.load(self.positive_text_conditioning.conditioning_name)
-        assert len(cond_data.conditionings) == 1
-        flux_conditioning = cond_data.conditionings[0]
-        assert isinstance(flux_conditioning, FLUXConditioningInfo)
-
-        latents = self._run_diffusion(context, flux_conditioning.clip_embeds, flux_conditioning.t5_embeds)
+        latents = self._run_diffusion(context)
         image = self._run_vae_decoding(context, latents)
         image_dto = context.images.save(image=image)
         return ImageOutput.build(image_dto)
@@ -72,12 +66,20 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
     def _run_diffusion(
         self,
         context: InvocationContext,
-        clip_embeddings: torch.Tensor,
-        t5_embeddings: torch.Tensor,
     ):
-        transformer_info = context.models.load(self.transformer.transformer)
         inference_dtype = torch.bfloat16
 
+        # Load the conditioning data.
+        cond_data = context.conditioning.load(self.positive_text_conditioning.conditioning_name)
+        assert len(cond_data.conditionings) == 1
+        flux_conditioning = cond_data.conditionings[0]
+        assert isinstance(flux_conditioning, FLUXConditioningInfo)
+        flux_conditioning = flux_conditioning.to(dtype=inference_dtype)
+        t5_embeddings = flux_conditioning.t5_embeds
+        clip_embeddings = flux_conditioning.clip_embeds
+
+        transformer_info = context.models.load(self.transformer.transformer)
+
         # Prepare input noise.
         x = get_noise(
             num_samples=1,
@@ -88,24 +90,19 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
             seed=self.seed,
         )
 
-        img, img_ids = prepare_latent_img_patches(x)
+        x, img_ids = prepare_latent_img_patches(x)
 
         is_schnell = "schnell" in transformer_info.config.config_path
 
         timesteps = get_schedule(
             num_steps=self.num_steps,
-            image_seq_len=img.shape[1],
+            image_seq_len=x.shape[1],
             shift=not is_schnell,
         )
 
         bs, t5_seq_len, _ = t5_embeddings.shape
         txt_ids = torch.zeros(bs, t5_seq_len, 3, dtype=inference_dtype, device=TorchDevice.choose_torch_device())
 
-        # HACK(ryand): Manually empty the cache. Currently we don't check the size of the model before loading it from
-        # disk. Since the transformer model is large (24GB), there's a good chance that it will OOM on 32GB RAM systems
-        # if the cache is not empty.
-        context.models._services.model_manager.load.ram_cache.make_room(24 * 2**30)
-
         with transformer_info as transformer:
             assert isinstance(transformer, Flux)
 
@@ -140,7 +137,7 @@ class FluxTextToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
 
             x = denoise(
                 model=transformer,
-                img=img,
+                img=x,
                 img_ids=img_ids,
                 txt=t5_embeddings,
                 txt_ids=txt_ids,

invokeai/app/invocations/model.py

@@ -157,7 +157,7 @@ class FluxModelLoaderOutput(BaseInvocationOutput):
     title="Flux Main Model",
     tags=["model", "flux"],
     category="model",
-    version="1.0.3",
+    version="1.0.4",
     classification=Classification.Prototype,
 )
 class FluxModelLoaderInvocation(BaseInvocation):
@@ -169,23 +169,35 @@ class FluxModelLoaderInvocation(BaseInvocation):
         input=Input.Direct,
     )
 
-    t5_encoder: ModelIdentifierField = InputField(
-        description=FieldDescriptions.t5_encoder,
-        ui_type=UIType.T5EncoderModel,
+    t5_encoder_model: ModelIdentifierField = InputField(
+        description=FieldDescriptions.t5_encoder, ui_type=UIType.T5EncoderModel, input=Input.Direct, title="T5 Encoder"
+    )
+
+    clip_embed_model: ModelIdentifierField = InputField(
+        description=FieldDescriptions.clip_embed_model,
+        ui_type=UIType.CLIPEmbedModel,
         input=Input.Direct,
+        title="CLIP Embed",
+    )
+
+    vae_model: ModelIdentifierField = InputField(
+        description=FieldDescriptions.vae_model, ui_type=UIType.FluxVAEModel, title="VAE"
     )
 
     def invoke(self, context: InvocationContext) -> FluxModelLoaderOutput:
-        model_key = self.model.key
+        for key in [self.model.key, self.t5_encoder_model.key, self.clip_embed_model.key, self.vae_model.key]:
+            if not context.models.exists(key):
+                raise ValueError(f"Unknown model: {key}")
+
+        transformer = self.model.model_copy(update={"submodel_type": SubModelType.Transformer})
+        vae = self.vae_model.model_copy(update={"submodel_type": SubModelType.VAE})
+
+        tokenizer = self.clip_embed_model.model_copy(update={"submodel_type": SubModelType.Tokenizer})
+        clip_encoder = self.clip_embed_model.model_copy(update={"submodel_type": SubModelType.TextEncoder})
+
+        tokenizer2 = self.t5_encoder_model.model_copy(update={"submodel_type": SubModelType.Tokenizer2})
+        t5_encoder = self.t5_encoder_model.model_copy(update={"submodel_type": SubModelType.TextEncoder2})
 
-        if not context.models.exists(model_key):
-            raise ValueError(f"Unknown model: {model_key}")
-        transformer = self._get_model(context, SubModelType.Transformer)
-        tokenizer = self._get_model(context, SubModelType.Tokenizer)
-        tokenizer2 = self._get_model(context, SubModelType.Tokenizer2)
-        clip_encoder = self._get_model(context, SubModelType.TextEncoder)
-        t5_encoder = self._get_model(context, SubModelType.TextEncoder2)
-        vae = self._get_model(context, SubModelType.VAE)
         transformer_config = context.models.get_config(transformer)
         assert isinstance(transformer_config, CheckpointConfigBase)
 
@@ -197,52 +209,6 @@ class FluxModelLoaderInvocation(BaseInvocation):
             max_seq_len=max_seq_lengths[transformer_config.config_path],
         )
 
-    def _get_model(self, context: InvocationContext, submodel: SubModelType) -> ModelIdentifierField:
-        match submodel:
-            case SubModelType.Transformer:
-                return self.model.model_copy(update={"submodel_type": SubModelType.Transformer})
-            case SubModelType.VAE:
-                return self._pull_model_from_mm(
-                    context,
-                    SubModelType.VAE,
-                    "FLUX.1-schnell_ae",
-                    ModelType.VAE,
-                    BaseModelType.Flux,
-                )
-            case submodel if submodel in [SubModelType.Tokenizer, SubModelType.TextEncoder]:
-                return self._pull_model_from_mm(
-                    context,
-                    submodel,
-                    "clip-vit-large-patch14",
-                    ModelType.CLIPEmbed,
-                    BaseModelType.Any,
-                )
-            case submodel if submodel in [SubModelType.Tokenizer2, SubModelType.TextEncoder2]:
-                return self._pull_model_from_mm(
-                    context,
-                    submodel,
-                    self.t5_encoder.name,
-                    ModelType.T5Encoder,
-                    BaseModelType.Any,
-                )
-            case _:
-                raise Exception(f"{submodel.value} is not a supported submodule for a flux model")
-
-    def _pull_model_from_mm(
-        self,
-        context: InvocationContext,
-        submodel: SubModelType,
-        name: str,
-        type: ModelType,
-        base: BaseModelType,
-    ):
-        if models := context.models.search_by_attrs(name=name, base=base, type=type):
-            if len(models) != 1:
-                raise Exception(f"Multiple models detected for selected model with name {name}")
-            return ModelIdentifierField.from_config(models[0]).model_copy(update={"submodel_type": submodel})
-        else:
-            raise ValueError(f"Please install the {base}:{type} model named {name} via starter models")
-
 
 @invocation(
     "main_model_loader",

invokeai/app/services/events/events_common.py

@@ -88,7 +88,8 @@ class QueueItemEventBase(QueueEventBase):
 
     item_id: int = Field(description="The ID of the queue item")
     batch_id: str = Field(description="The ID of the queue batch")
-    origin: str | None = Field(default=None, description="The origin of the batch")
+    origin: str | None = Field(default=None, description="The origin of the queue item")
+    destination: str | None = Field(default=None, description="The destination of the queue item")
 
 
 class InvocationEventBase(QueueItemEventBase):
@@ -114,6 +115,7 @@ class InvocationStartedEvent(InvocationEventBase):
             item_id=queue_item.item_id,
             batch_id=queue_item.batch_id,
             origin=queue_item.origin,
+            destination=queue_item.destination,
             session_id=queue_item.session_id,
             invocation=invocation,
             invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
@@ -148,6 +150,7 @@ class InvocationDenoiseProgressEvent(InvocationEventBase):
             item_id=queue_item.item_id,
             batch_id=queue_item.batch_id,
             origin=queue_item.origin,
+            destination=queue_item.destination,
             session_id=queue_item.session_id,
             invocation=invocation,
             invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
@@ -186,6 +189,7 @@ class InvocationCompleteEvent(InvocationEventBase):
             item_id=queue_item.item_id,
             batch_id=queue_item.batch_id,
             origin=queue_item.origin,
+            destination=queue_item.destination,
             session_id=queue_item.session_id,
             invocation=invocation,
             invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
@@ -219,6 +223,7 @@ class InvocationErrorEvent(InvocationEventBase):
             item_id=queue_item.item_id,
             batch_id=queue_item.batch_id,
             origin=queue_item.origin,
+            destination=queue_item.destination,
             session_id=queue_item.session_id,
             invocation=invocation,
             invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
@@ -257,6 +262,7 @@ class QueueItemStatusChangedEvent(QueueItemEventBase):
             item_id=queue_item.item_id,
             batch_id=queue_item.batch_id,
             origin=queue_item.origin,
+            destination=queue_item.destination,
             session_id=queue_item.session_id,
             status=queue_item.status,
             error_type=queue_item.error_type,

invokeai/app/services/session_queue/session_queue_common.py

@@ -77,7 +77,14 @@ BatchDataCollection: TypeAlias = list[list[BatchDatum]]
 
 class Batch(BaseModel):
     batch_id: str = Field(default_factory=uuid_string, description="The ID of the batch")
-    origin: str | None = Field(default=None, description="The origin of this batch.")
+    origin: str | None = Field(
+        default=None,
+        description="The origin of this queue item. This data is used by the frontend to determine how to handle results.",
+    )
+    destination: str | None = Field(
+        default=None,
+        description="The origin of this queue item. This data is used by the frontend to determine how to handle results",
+    )
     data: Optional[BatchDataCollection] = Field(default=None, description="The batch data collection.")
     graph: Graph = Field(description="The graph to initialize the session with")
     workflow: Optional[WorkflowWithoutID] = Field(
@@ -196,7 +203,14 @@ class SessionQueueItemWithoutGraph(BaseModel):
     status: QUEUE_ITEM_STATUS = Field(default="pending", description="The status of this queue item")
     priority: int = Field(default=0, description="The priority of this queue item")
     batch_id: str = Field(description="The ID of the batch associated with this queue item")
-    origin: str | None = Field(default=None, description="The origin of this queue item. ")
+    origin: str | None = Field(
+        default=None,
+        description="The origin of this queue item. This data is used by the frontend to determine how to handle results.",
+    )
+    destination: str | None = Field(
+        default=None,
+        description="The origin of this queue item. This data is used by the frontend to determine how to handle results",
+    )
     session_id: str = Field(
         description="The ID of the session associated with this queue item. The session doesn't exist in graph_executions until the queue item is executed."
     )
@@ -297,6 +311,7 @@ class BatchStatus(BaseModel):
     queue_id: str = Field(..., description="The ID of the queue")
     batch_id: str = Field(..., description="The ID of the batch")
     origin: str | None = Field(..., description="The origin of the batch")
+    destination: str | None = Field(..., description="The destination of the batch")
     pending: int = Field(..., description="Number of queue items with status 'pending'")
     in_progress: int = Field(..., description="Number of queue items with status 'in_progress'")
     completed: int = Field(..., description="Number of queue items with status 'complete'")
@@ -443,6 +458,7 @@ class SessionQueueValueToInsert(NamedTuple):
     priority: int  # priority
     workflow: Optional[str]  # workflow json
     origin: str | None
+    destination: str | None
 
 
 ValuesToInsert: TypeAlias = list[SessionQueueValueToInsert]
@@ -464,6 +480,7 @@ def prepare_values_to_insert(queue_id: str, batch: Batch, priority: int, max_new
                 priority,  # priority
                 json.dumps(workflow, default=to_jsonable_python) if workflow else None,  # workflow (json)
                 batch.origin,  # origin
+                batch.destination,  # destination
             )
         )
     return values_to_insert

invokeai/app/services/session_queue/session_queue_sqlite.py

@@ -128,8 +128,8 @@ class SqliteSessionQueue(SessionQueueBase):
 
             self.__cursor.executemany(
                 """--sql
-                INSERT INTO session_queue (queue_id, session, session_id, batch_id, field_values, priority, workflow, origin)
-                VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+                INSERT INTO session_queue (queue_id, session, session_id, batch_id, field_values, priority, workflow, origin, destination)
+                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
                 """,
                 values_to_insert,
             )
@@ -579,7 +579,8 @@ class SqliteSessionQueue(SessionQueueBase):
                     session_id,
                     batch_id,
                     queue_id,
-                    origin
+                    origin,
+                    destination
                 FROM session_queue
                 WHERE queue_id = ?
             """
@@ -659,7 +660,7 @@ class SqliteSessionQueue(SessionQueueBase):
             self.__lock.acquire()
             self.__cursor.execute(
                 """--sql
-                SELECT status, count(*), origin
+                SELECT status, count(*), origin, destination
                 FROM session_queue
                 WHERE
                   queue_id = ?
@@ -672,6 +673,7 @@ class SqliteSessionQueue(SessionQueueBase):
             total = sum(row[1] for row in result)
             counts: dict[str, int] = {row[0]: row[1] for row in result}
             origin = result[0]["origin"] if result else None
+            destination = result[0]["destination"] if result else None
         except Exception:
             self.__conn.rollback()
             raise
@@ -681,6 +683,7 @@ class SqliteSessionQueue(SessionQueueBase):
         return BatchStatus(
             batch_id=batch_id,
             origin=origin,
+            destination=destination,
             queue_id=queue_id,
             pending=counts.get("pending", 0),
             in_progress=counts.get("in_progress", 0),

invokeai/app/services/shared/sqlite_migrator/migrations/migration_15.py

@@ -10,9 +10,11 @@ class Migration15Callback:
     def _add_origin_col(self, cursor: sqlite3.Cursor) -> None:
         """
         - Adds `origin` column to the session queue table.
+        - Adds `destination` column to the session queue table.
         """
 
         cursor.execute("ALTER TABLE session_queue ADD COLUMN origin TEXT;")
+        cursor.execute("ALTER TABLE session_queue ADD COLUMN destination TEXT;")
 
 
 def build_migration_15() -> Migration:
@@ -21,6 +23,7 @@ def build_migration_15() -> Migration:
 
     This migration does the following:
         - Adds `origin` column to the session queue table.
+        - Adds `destination` column to the session queue table.
     """
     migration_15 = Migration(
         from_version=14,

invokeai/app/services/workflow_records/default_workflows/Flux Text to Image.json

@@ -2,13 +2,13 @@
   "name": "FLUX Text to Image",
   "author": "InvokeAI",
   "description": "A simple text-to-image workflow using FLUX dev or schnell models. Prerequisite model downloads: T5 Encoder, CLIP-L Encoder, and FLUX VAE. Quantized and un-quantized versions can be found in the starter models tab within your Model Manager. We recommend 4 steps for FLUX schnell models and 30 steps for FLUX dev models.",
-  "version": "1.0.0",
+  "version": "1.0.4",
   "contact": "",
   "tags": "text2image, flux",
   "notes": "Prerequisite model downloads: T5 Encoder, CLIP-L Encoder, and FLUX VAE. Quantized and un-quantized versions can be found in the starter models tab within your Model Manager. We recommend 4 steps for FLUX schnell models and 30 steps for FLUX dev models.",
   "exposedFields": [
     {
-      "nodeId": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
+      "nodeId": "f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90",
       "fieldName": "model"
     },
     {
@@ -20,8 +20,8 @@
       "fieldName": "num_steps"
     },
     {
-      "nodeId": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
-      "fieldName": "t5_encoder"
+      "nodeId": "f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90",
+      "fieldName": "t5_encoder_model"
     }
   ],
   "meta": {
@@ -30,12 +30,12 @@
   },
   "nodes": [
     {
-      "id": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
+      "id": "f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90",
       "type": "invocation",
       "data": {
-        "id": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
+        "id": "f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90",
         "type": "flux_model_loader",
-        "version": "1.0.3",
+        "version": "1.0.4",
         "label": "",
         "notes": "",
         "isOpen": true,
@@ -44,31 +44,25 @@
         "inputs": {
           "model": {
             "name": "model",
-            "label": "Model (Starter Models can be found in Model Manager)",
-            "value": {
-              "key": "f04a7a2f-c74d-4538-8d5e-879a53501662",
-              "hash": "random:4875da7a9508444ffa706f61961c260d0c6729f6181a86b31fad06df1277b850",
-              "name": "FLUX Dev (Quantized)",
-              "base": "flux",
-              "type": "main"
-            }
+            "label": ""
           },
-          "t5_encoder": {
-            "name": "t5_encoder",
-            "label": "T 5 Encoder (Starter Models can be found in Model Manager)",
-            "value": {
-              "key": "20dcd9ec-5fbb-4012-8401-049e707da5e5",
-              "hash": "random:f986be43ff3502169e4adbdcee158afb0e0a65a1edc4cab16ae59963630cfd8f",
-              "name": "t5_bnb_int8_quantized_encoder",
-              "base": "any",
-              "type": "t5_encoder"
-            }
+          "t5_encoder_model": {
+            "name": "t5_encoder_model",
+            "label": ""
+          },
+          "clip_embed_model": {
+            "name": "clip_embed_model",
+            "label": ""
+          },
+          "vae_model": {
+            "name": "vae_model",
+            "label": ""
           }
         }
       },
       "position": {
-        "x": 337.09365228062825,
-        "y": 40.63469521079861
+        "x": 381.1882713063478,
+        "y": -95.89663532854017
       }
     },
     {
@@ -207,45 +201,45 @@
   ],
   "edges": [
     {
-      "id": "reactflow__edge-4f0207c2-ff40-41fd-b047-ad33fbb1c33amax_seq_len-01f674f8-b3d1-4df1-acac-6cb8e0bfb63ct5_max_seq_len",
+      "id": "reactflow__edge-f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90max_seq_len-01f674f8-b3d1-4df1-acac-6cb8e0bfb63ct5_max_seq_len",
       "type": "default",
-      "source": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
+      "source": "f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90",
       "target": "01f674f8-b3d1-4df1-acac-6cb8e0bfb63c",
       "sourceHandle": "max_seq_len",
       "targetHandle": "t5_max_seq_len"
     },
     {
-      "id": "reactflow__edge-4f0207c2-ff40-41fd-b047-ad33fbb1c33avae-159bdf1b-79e7-4174-b86e-d40e646964c8vae",
+      "id": "reactflow__edge-f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90vae-159bdf1b-79e7-4174-b86e-d40e646964c8vae",
       "type": "default",
-      "source": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
+      "source": "f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90",
       "target": "159bdf1b-79e7-4174-b86e-d40e646964c8",
       "sourceHandle": "vae",
       "targetHandle": "vae"
     },
     {
-      "id": "reactflow__edge-4f0207c2-ff40-41fd-b047-ad33fbb1c33atransformer-159bdf1b-79e7-4174-b86e-d40e646964c8transformer",
+      "id": "reactflow__edge-f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90t5_encoder-01f674f8-b3d1-4df1-acac-6cb8e0bfb63ct5_encoder",
       "type": "default",
-      "source": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
-      "target": "159bdf1b-79e7-4174-b86e-d40e646964c8",
-      "sourceHandle": "transformer",
-      "targetHandle": "transformer"
-    },
-    {
-      "id": "reactflow__edge-4f0207c2-ff40-41fd-b047-ad33fbb1c33at5_encoder-01f674f8-b3d1-4df1-acac-6cb8e0bfb63ct5_encoder",
-      "type": "default",
-      "source": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
+      "source": "f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90",
       "target": "01f674f8-b3d1-4df1-acac-6cb8e0bfb63c",
       "sourceHandle": "t5_encoder",
       "targetHandle": "t5_encoder"
     },
     {
-      "id": "reactflow__edge-4f0207c2-ff40-41fd-b047-ad33fbb1c33aclip-01f674f8-b3d1-4df1-acac-6cb8e0bfb63cclip",
+      "id": "reactflow__edge-f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90clip-01f674f8-b3d1-4df1-acac-6cb8e0bfb63cclip",
       "type": "default",
-      "source": "4f0207c2-ff40-41fd-b047-ad33fbb1c33a",
+      "source": "f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90",
       "target": "01f674f8-b3d1-4df1-acac-6cb8e0bfb63c",
       "sourceHandle": "clip",
       "targetHandle": "clip"
     },
+    {
+      "id": "reactflow__edge-f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90transformer-159bdf1b-79e7-4174-b86e-d40e646964c8transformer",
+      "type": "default",
+      "source": "f8d9d7c8-9ed7-4bd7-9e42-ab0e89bfac90",
+      "target": "159bdf1b-79e7-4174-b86e-d40e646964c8",
+      "sourceHandle": "transformer",
+      "targetHandle": "transformer"
+    },
     {
       "id": "reactflow__edge-01f674f8-b3d1-4df1-acac-6cb8e0bfb63cconditioning-159bdf1b-79e7-4174-b86e-d40e646964c8positive_text_conditioning",
       "type": "default",

invokeai/backend/flux/sampling.py

@@ -111,16 +111,7 @@ def denoise(
     step_callback: Callable[[], None],
     guidance: float = 4.0,
 ):
-    dtype = model.txt_in.bias.dtype
-
-    # TODO(ryand): This shouldn't be necessary if we manage the dtypes properly in the caller.
-    img = img.to(dtype=dtype)
-    img_ids = img_ids.to(dtype=dtype)
-    txt = txt.to(dtype=dtype)
-    txt_ids = txt_ids.to(dtype=dtype)
-    vec = vec.to(dtype=dtype)
-
-    # this is ignored for schnell
+    # guidance_vec is ignored for schnell.
     guidance_vec = torch.full((img.shape[0],), guidance, device=img.device, dtype=img.dtype)
     for t_curr, t_prev in tqdm(list(zip(timesteps[:-1], timesteps[1:], strict=True))):
         t_vec = torch.full((img.shape[0],), t_curr, dtype=img.dtype, device=img.device)
@@ -168,9 +159,9 @@ def prepare_latent_img_patches(latent_img: torch.Tensor) -> tuple[torch.Tensor,
         img = repeat(img, "1 ... -> bs ...", bs=bs)
 
     # Generate patch position ids.
-    img_ids = torch.zeros(h // 2, w // 2, 3, device=img.device)
-    img_ids[..., 1] = img_ids[..., 1] + torch.arange(h // 2, device=img.device)[:, None]
-    img_ids[..., 2] = img_ids[..., 2] + torch.arange(w // 2, device=img.device)[None, :]
+    img_ids = torch.zeros(h // 2, w // 2, 3, device=img.device, dtype=img.dtype)
+    img_ids[..., 1] = img_ids[..., 1] + torch.arange(h // 2, device=img.device, dtype=img.dtype)[:, None]
+    img_ids[..., 2] = img_ids[..., 2] + torch.arange(w // 2, device=img.device, dtype=img.dtype)[None, :]
     img_ids = repeat(img_ids, "h w c -> b (h w) c", b=bs)
 
     return img, img_ids

invokeai/backend/model_manager/load/load_default.py

@@ -72,6 +72,7 @@ class ModelLoader(ModelLoaderBase):
             pass
 
         config.path = str(self._get_model_path(config))
+        self._ram_cache.make_room(self.get_size_fs(config, Path(config.path), submodel_type))
         loaded_model = self._load_model(config, submodel_type)
 
         self._ram_cache.put(

invokeai/backend/model_manager/load/model_cache/model_cache_base.py

@@ -193,15 +193,6 @@ class ModelCacheBase(ABC, Generic[T]):
         """
         pass
 
-    @abstractmethod
-    def exists(
-        self,
-        key: str,
-        submodel_type: Optional[SubModelType] = None,
-    ) -> bool:
-        """Return true if the model identified by key and submodel_type is in the cache."""
-        pass
-
     @abstractmethod
     def cache_size(self) -> int:
         """Get the total size of the models currently cached."""

invokeai/backend/model_manager/load/model_cache/model_cache_default.py

@@ -1,22 +1,6 @@
 # Copyright (c) 2024 Lincoln D. Stein and the InvokeAI Development team
 # TODO: Add Stalker's proper name to copyright
-"""
-Manage a RAM cache of diffusion/transformer models for fast switching.
-They are moved between GPU VRAM and CPU RAM as necessary. If the cache
-grows larger than a preset maximum, then the least recently used
-model will be cleared and (re)loaded from disk when next needed.
-
-The cache returns context manager generators designed to load the
-model into the GPU within the context, and unload outside the
-context. Use like this:
-
-   cache = ModelCache(max_cache_size=7.5)
-   with cache.get_model('runwayml/stable-diffusion-1-5') as SD1,
-          cache.get_model('stabilityai/stable-diffusion-2') as SD2:
-       do_something_in_GPU(SD1,SD2)
-
-
-"""
+""" """
 
 import gc
 import math
@@ -40,45 +24,64 @@ from invokeai.backend.model_manager.load.model_util import calc_model_size_by_da
 from invokeai.backend.util.devices import TorchDevice
 from invokeai.backend.util.logging import InvokeAILogger
 
-# Maximum size of the cache, in gigs
-# Default is roughly enough to hold three fp16 diffusers models in RAM simultaneously
-DEFAULT_MAX_CACHE_SIZE = 6.0
-
-# amount of GPU memory to hold in reserve for use by generations (GB)
-DEFAULT_MAX_VRAM_CACHE_SIZE = 2.75
-
-# actual size of a gig
-GIG = 1073741824
+# Size of a GB in bytes.
+GB = 2**30
 
 # Size of a MB in bytes.
 MB = 2**20
 
 
 class ModelCache(ModelCacheBase[AnyModel]):
-    """Implementation of ModelCacheBase."""
+    """A cache for managing models in memory.
+
+    The cache is based on two levels of model storage:
+    - execution_device: The device where most models are executed (typically "cuda", "mps", or "cpu").
+    - storage_device: The device where models are offloaded when not in active use (typically "cpu").
+
+    The model cache is based on the following assumptions:
+    - storage_device_mem_size > execution_device_mem_size
+    - disk_to_storage_device_transfer_time >> storage_device_to_execution_device_transfer_time
+
+    A copy of all models in the cache is always kept on the storage_device. A subset of the models also have a copy on
+    the execution_device.
+
+    Models are moved between the storage_device and the execution_device as necessary. Cache size limits are enforced
+    on both the storage_device and the execution_device. The execution_device cache uses a smallest-first offload
+    policy. The storage_device cache uses a least-recently-used (LRU) offload policy.
+
+    Note: Neither of these offload policies has really been compared against alternatives. It's likely that different
+    policies would be better, although the optimal policies are likely heavily dependent on usage patterns and HW
+    configuration.
+
+    The cache returns context manager generators designed to load the model into the execution device (often GPU) within
+    the context, and unload outside the context.
+
+    Example usage:
+    ```
+    cache = ModelCache(max_cache_size=7.5, max_vram_cache_size=6.0)
+    with cache.get_model('runwayml/stable-diffusion-1-5') as SD1:
+        do_something_on_gpu(SD1)
+    ```
+    """
 
     def __init__(
         self,
-        max_cache_size: float = DEFAULT_MAX_CACHE_SIZE,
-        max_vram_cache_size: float = DEFAULT_MAX_VRAM_CACHE_SIZE,
+        max_cache_size: float,
+        max_vram_cache_size: float,
         execution_device: torch.device = torch.device("cuda"),
         storage_device: torch.device = torch.device("cpu"),
-        precision: torch.dtype = torch.float16,
-        sequential_offload: bool = False,
         lazy_offloading: bool = True,
-        sha_chunksize: int = 16777216,
         log_memory_usage: bool = False,
         logger: Optional[Logger] = None,
     ):
         """
         Initialize the model RAM cache.
 
-        :param max_cache_size: Maximum size of the RAM cache [6.0 GB]
+        :param max_cache_size: Maximum size of the storage_device cache in GBs.
+        :param max_vram_cache_size: Maximum size of the execution_device cache in GBs.
         :param execution_device: Torch device to load active model into [torch.device('cuda')]
         :param storage_device: Torch device to save inactive model in [torch.device('cpu')]
-        :param precision: Precision for loaded models [torch.float16]
-        :param lazy_offloading: Keep model in VRAM until another model needs to be loaded
-        :param sequential_offload: Conserve VRAM by loading and unloading each stage of the pipeline sequentially
+        :param lazy_offloading: Keep model in VRAM until another model needs to be loaded.
         :param log_memory_usage: If True, a memory snapshot will be captured before and after every model cache
             operation, and the result will be logged (at debug level). There is a time cost to capturing the memory
             snapshots, so it is recommended to disable this feature unless you are actively inspecting the model cache's
@@ -86,7 +89,6 @@ class ModelCache(ModelCacheBase[AnyModel]):
         """
         # allow lazy offloading only when vram cache enabled
         self._lazy_offloading = lazy_offloading and max_vram_cache_size > 0
-        self._precision: torch.dtype = precision
         self._max_cache_size: float = max_cache_size
         self._max_vram_cache_size: float = max_vram_cache_size
         self._execution_device: torch.device = execution_device
@@ -145,15 +147,6 @@ class ModelCache(ModelCacheBase[AnyModel]):
             total += cache_record.size
         return total
 
-    def exists(
-        self,
-        key: str,
-        submodel_type: Optional[SubModelType] = None,
-    ) -> bool:
-        """Return true if the model identified by key and submodel_type is in the cache."""
-        key = self._make_cache_key(key, submodel_type)
-        return key in self._cached_models
-
     def put(
         self,
         key: str,
@@ -203,7 +196,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
         # more stats
         if self.stats:
             stats_name = stats_name or key
-            self.stats.cache_size = int(self._max_cache_size * GIG)
+            self.stats.cache_size = int(self._max_cache_size * GB)
             self.stats.high_watermark = max(self.stats.high_watermark, self.cache_size())
             self.stats.in_cache = len(self._cached_models)
             self.stats.loaded_model_sizes[stats_name] = max(
@@ -231,10 +224,13 @@ class ModelCache(ModelCacheBase[AnyModel]):
             return model_key
 
     def offload_unlocked_models(self, size_required: int) -> None:
-        """Move any unused models from VRAM."""
-        reserved = self._max_vram_cache_size * GIG
+        """Offload models from the execution_device to make room for size_required.
+
+        :param size_required: The amount of space to clear in the execution_device cache, in bytes.
+        """
+        reserved = self._max_vram_cache_size * GB
         vram_in_use = torch.cuda.memory_allocated() + size_required
-        self.logger.debug(f"{(vram_in_use/GIG):.2f}GB VRAM needed for models; max allowed={(reserved/GIG):.2f}GB")
+        self.logger.debug(f"{(vram_in_use/GB):.2f}GB VRAM needed for models; max allowed={(reserved/GB):.2f}GB")
         for _, cache_entry in sorted(self._cached_models.items(), key=lambda x: x[1].size):
             if vram_in_use <= reserved:
                 break
@@ -245,7 +241,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
                 cache_entry.loaded = False
                 vram_in_use = torch.cuda.memory_allocated() + size_required
                 self.logger.debug(
-                    f"Removing {cache_entry.key} from VRAM to free {(cache_entry.size/GIG):.2f}GB; vram free = {(torch.cuda.memory_allocated()/GIG):.2f}GB"
+                    f"Removing {cache_entry.key} from VRAM to free {(cache_entry.size/GB):.2f}GB; vram free = {(torch.cuda.memory_allocated()/GB):.2f}GB"
                 )
 
         TorchDevice.empty_cache()
@@ -303,7 +299,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
         self.logger.debug(
             f"Moved model '{cache_entry.key}' from {source_device} to"
             f" {target_device} in {(end_model_to_time-start_model_to_time):.2f}s."
-            f"Estimated model size: {(cache_entry.size/GIG):.3f} GB."
+            f"Estimated model size: {(cache_entry.size/GB):.3f} GB."
             f"{get_pretty_snapshot_diff(snapshot_before, snapshot_after)}"
         )
 
@@ -326,14 +322,14 @@ class ModelCache(ModelCacheBase[AnyModel]):
                     f"Moving model '{cache_entry.key}' from {source_device} to"
                     f" {target_device} caused an unexpected change in VRAM usage. The model's"
                     " estimated size may be incorrect. Estimated model size:"
-                    f" {(cache_entry.size/GIG):.3f} GB.\n"
+                    f" {(cache_entry.size/GB):.3f} GB.\n"
                     f"{get_pretty_snapshot_diff(snapshot_before, snapshot_after)}"
                 )
 
     def print_cuda_stats(self) -> None:
         """Log CUDA diagnostics."""
-        vram = "%4.2fG" % (torch.cuda.memory_allocated() / GIG)
-        ram = "%4.2fG" % (self.cache_size() / GIG)
+        vram = "%4.2fG" % (torch.cuda.memory_allocated() / GB)
+        ram = "%4.2fG" % (self.cache_size() / GB)
 
         in_ram_models = 0
         in_vram_models = 0
@@ -353,17 +349,20 @@ class ModelCache(ModelCacheBase[AnyModel]):
                 )
 
     def make_room(self, size: int) -> None:
-        """Make enough room in the cache to accommodate a new model of indicated size."""
-        # calculate how much memory this model will require
-        # multiplier = 2 if self.precision==torch.float32 else 1
+        """Make enough room in the cache to accommodate a new model of indicated size.
+
+        Note: This function deletes all of the cache's internal references to a model in order to free it. If there are
+        external references to the model, there's nothing that the cache can do about it, and those models will not be
+        garbage-collected.
+        """
         bytes_needed = size
-        maximum_size = self.max_cache_size * GIG  # stored in GB, convert to bytes
+        maximum_size = self.max_cache_size * GB  # stored in GB, convert to bytes
         current_size = self.cache_size()
 
         if current_size + bytes_needed > maximum_size:
             self.logger.debug(
-                f"Max cache size exceeded: {(current_size/GIG):.2f}/{self.max_cache_size:.2f} GB, need an additional"
-                f" {(bytes_needed/GIG):.2f} GB"
+                f"Max cache size exceeded: {(current_size/GB):.2f}/{self.max_cache_size:.2f} GB, need an additional"
+                f" {(bytes_needed/GB):.2f} GB"
             )
 
         self.logger.debug(f"Before making_room: cached_models={len(self._cached_models)}")
@@ -380,7 +379,7 @@ class ModelCache(ModelCacheBase[AnyModel]):
 
             if not cache_entry.locked:
                 self.logger.debug(
-                    f"Removing {model_key} from RAM cache to free at least {(size/GIG):.2f} GB (-{(cache_entry.size/GIG):.2f} GB)"
+                    f"Removing {model_key} from RAM cache to free at least {(size/GB):.2f} GB (-{(cache_entry.size/GB):.2f} GB)"
                 )
                 current_size -= cache_entry.size
                 models_cleared += 1

invokeai/backend/quantization/bnb_llm_int8.py

@@ -54,8 +54,10 @@ class InvokeLinear8bitLt(bnb.nn.Linear8bitLt):
 
         # See `bnb.nn.Linear8bitLt._save_to_state_dict()` for the serialization logic of SCB and weight_format.
         scb = state_dict.pop(prefix + "SCB", None)
-        # weight_format is unused, but we pop it so we can validate that there are no unexpected keys.
-        _weight_format = state_dict.pop(prefix + "weight_format", None)
+
+        # Currently, we only support weight_format=0.
+        weight_format = state_dict.pop(prefix + "weight_format", None)
+        assert weight_format == 0
 
         # TODO(ryand): Technically, we should be using `strict`, `missing_keys`, `unexpected_keys`, and `error_msgs`
         # rather than raising an exception to correctly implement this API.
@@ -89,6 +91,14 @@ class InvokeLinear8bitLt(bnb.nn.Linear8bitLt):
             )
             self.bias = bias if bias is None else torch.nn.Parameter(bias)
 
+        # Reset the state. The persisted fields are based on the initialization behaviour in
+        # `bnb.nn.Linear8bitLt.__init__()`.
+        new_state = bnb.MatmulLtState()
+        new_state.threshold = self.state.threshold
+        new_state.has_fp16_weights = False
+        new_state.use_pool = self.state.use_pool
+        self.state = new_state
+
 
 def _convert_linear_layers_to_llm_8bit(
     module: torch.nn.Module, ignore_modules: set[str], outlier_threshold: float, prefix: str = ""

invokeai/backend/stable_diffusion/diffusion/conditioning_data.py

@@ -43,6 +43,11 @@ class FLUXConditioningInfo:
     clip_embeds: torch.Tensor
     t5_embeds: torch.Tensor
 
+    def to(self, device: torch.device | None = None, dtype: torch.dtype | None = None):
+        self.clip_embeds = self.clip_embeds.to(device=device, dtype=dtype)
+        self.t5_embeds = self.t5_embeds.to(device=device, dtype=dtype)
+        return self
+
 
 @dataclass
 class ConditioningFieldData:

invokeai/backend/util/__init__.py

@@ -3,10 +3,9 @@ Initialization file for invokeai.backend.util
 """
 
 from invokeai.backend.util.logging import InvokeAILogger
-from invokeai.backend.util.util import GIG, Chdir, directory_size
+from invokeai.backend.util.util import Chdir, directory_size
 
 __all__ = [
-    "GIG",
     "directory_size",
     "Chdir",
     "InvokeAILogger",

invokeai/backend/util/util.py

@@ -7,9 +7,6 @@ from pathlib import Path
 
 from PIL import Image
 
-# actual size of a gig
-GIG = 1073741824
-
 
 def slugify(value: str, allow_unicode: bool = False) -> str:
     """

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

@@ -164,10 +164,10 @@
         "alpha": "Alpha",
         "selected": "Selected",
         "tab": "Tab",
-        "viewing": "Viewing",
-        "viewingDesc": "Review images in a large gallery view",
-        "editing": "Editing",
-        "editingDesc": "Edit on the Control Layers canvas",
+        "view": "View",
+        "viewDesc": "Review images in a large gallery view",
+        "edit": "Edit",
+        "editDesc": "Edit on the Canvas",
         "comparing": "Comparing",
         "comparingDesc": "Comparing two images",
         "enabled": "Enabled",
@@ -328,9 +328,13 @@
         "completedIn": "Completed in",
         "batch": "Batch",
         "origin": "Origin",
-        "originCanvas": "Canvas",
-        "originWorkflows": "Workflows",
-        "originOther": "Other",
+        "destination": "Destination",
+        "upscaling": "Upscaling",
+        "canvas": "Canvas",
+        "generation": "Generation",
+        "workflows": "Workflows",
+        "other": "Other",
+        "gallery": "Gallery",
         "batchFieldValues": "Batch Field Values",
         "item": "Item",
         "session": "Session",
@@ -702,6 +706,8 @@
         "availableModels": "Available Models",
         "baseModel": "Base Model",
         "cancel": "Cancel",
+        "clipEmbed": "CLIP Embed",
+        "clipVision": "CLIP Vision",
         "config": "Config",
         "convert": "Convert",
         "convertingModelBegin": "Converting Model. Please wait.",
@@ -789,6 +795,7 @@
         "settings": "Settings",
         "simpleModelPlaceholder": "URL or path to a local file or diffusers folder",
         "source": "Source",
+        "spandrelImageToImage": "Image to Image (Spandrel)",
         "starterModels": "Starter Models",
         "starterModelsInModelManager": "Starter Models can be found in Model Manager",
         "syncModels": "Sync Models",
@@ -797,6 +804,7 @@
         "loraTriggerPhrases": "LoRA Trigger Phrases",
         "mainModelTriggerPhrases": "Main Model Trigger Phrases",
         "typePhraseHere": "Type phrase here",
+        "t5Encoder": "T5 Encoder",
         "upcastAttention": "Upcast Attention",
         "uploadImage": "Upload Image",
         "urlOrLocalPath": "URL or Local Path",
@@ -1646,6 +1654,13 @@
         "storeNotInitialized": "Store is not initialized"
     },
     "controlLayers": {
+        "saveCanvasToGallery": "Save Canvas To Gallery",
+        "saveBboxToGallery": "Save Bbox To Gallery",
+        "savedToGalleryOk": "Saved to Gallery",
+        "savedToGalleryError": "Error saving to gallery",
+        "mergeVisible": "Merge Visible",
+        "mergeVisibleOk": "Merged visible layers",
+        "mergeVisibleError": "Error merging visible layers",
         "clearHistory": "Clear History",
         "generateMode": "Generate",
         "generateModeDesc": "Create individual images. Generated images are added directly to the gallery.",
@@ -1675,32 +1690,44 @@
         "deletePrompt": "Delete Prompt",
         "resetRegion": "Reset Region",
         "debugLayers": "Debug Layers",
+        "showHUD": "Show HUD",
         "rectangle": "Rectangle",
         "maskFill": "Mask Fill",
         "addPositivePrompt": "Add $t(common.positivePrompt)",
         "addNegativePrompt": "Add $t(common.negativePrompt)",
         "addIPAdapter": "Add $t(common.ipAdapter)",
+        "addRasterLayer": "Add $t(controlLayers.rasterLayer)",
+        "addControlLayer": "Add $t(controlLayers.controlLayer)",
+        "addInpaintMask": "Add $t(controlLayers.inpaintMask)",
+        "addRegionalGuidance": "Add $t(controlLayers.regionalGuidance)",
         "regionalGuidanceLayer": "$t(controlLayers.regionalGuidance) $t(unifiedCanvas.layer)",
         "raster": "Raster",
-        "rasterLayer_one": "Raster Layer",
-        "controlLayer_one": "Control Layer",
-        "inpaintMask_one": "Inpaint Mask",
-        "regionalGuidance_one": "Regional Guidance",
-        "ipAdapter_one": "IP Adapter",
-        "rasterLayer_other": "Raster Layers",
-        "controlLayer_other": "Control Layers",
-        "inpaintMask_other": "Inpaint Masks",
-        "regionalGuidance_other": "Regional Guidance",
-        "ipAdapter_other": "IP Adapters",
+        "rasterLayer": "Raster Layer",
+        "controlLayer": "Control Layer",
+        "inpaintMask": "Inpaint Mask",
+        "regionalGuidance": "Regional Guidance",
+        "ipAdapter": "IP Adapter",
+        "sendToGallery": "Send To Gallery",
+        "sendToGalleryDesc": "Generations will be sent to the gallery.",
+        "sendToCanvas": "Send To Canvas",
+        "sendToCanvasDesc": "Generations will be staged onto the canvas.",
+        "rasterLayer_withCount_one": "$t(controlLayers.rasterLayer)",
+        "controlLayer_withCount_one": "$t(controlLayers.controlLayer)",
+        "inpaintMask_withCount_one": "$t(controlLayers.inpaintMask)",
+        "regionalGuidance_withCount_one": "$t(controlLayers.regionalGuidance)",
+        "ipAdapter_withCount_one": "$t(controlLayers.ipAdapter)",
+        "rasterLayer_withCount_other": "Raster Layers",
+        "controlLayer_withCount_other": "Control Layers",
+        "inpaintMask_withCount_other": "Inpaint Masks",
+        "regionalGuidance_withCount_other": "Regional Guidance",
+        "ipAdapter_withCount_other": "IP Adapters",
         "opacity": "Opacity",
         "regionalGuidance_withCount_hidden": "Regional Guidance ({{count}} hidden)",
-        "controlAdapters_withCount_hidden": "Control Adapters ({{count}} hidden)",
         "controlLayers_withCount_hidden": "Control Layers ({{count}} hidden)",
         "rasterLayers_withCount_hidden": "Raster Layers ({{count}} hidden)",
         "ipAdapters_withCount_hidden": "IP Adapters ({{count}} hidden)",
         "inpaintMasks_withCount_hidden": "Inpaint Masks ({{count}} hidden)",
         "regionalGuidance_withCount_visible": "Regional Guidance ({{count}})",
-        "controlAdapters_withCount_visible": "Control Adapters ({{count}})",
         "controlLayers_withCount_visible": "Control Layers ({{count}})",
         "rasterLayers_withCount_visible": "Raster Layers ({{count}})",
         "ipAdapters_withCount_visible": "IP Adapters ({{count}})",
@@ -1737,6 +1764,7 @@
         "flipHorizontal": "Flip Horizontal",
         "flipVertical": "Flip Vertical",
         "fill": {
+            "fillColor": "Fill Color",
             "fillStyle": "Fill Style",
             "solid": "Solid",
             "grid": "Grid",

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

@@ -16,6 +16,7 @@ import { DynamicPromptsModal } from 'features/dynamicPrompts/components/DynamicP
 import { useStarterModelsToast } from 'features/modelManagerV2/hooks/useStarterModelsToast';
 import { ClearQueueConfirmationsAlertDialog } from 'features/queue/components/ClearQueueConfirmationAlertDialog';
 import { StylePresetModal } from 'features/stylePresets/components/StylePresetForm/StylePresetModal';
+import { activeStylePresetIdChanged } from 'features/stylePresets/store/stylePresetSlice';
 import RefreshAfterResetModal from 'features/system/components/SettingsModal/RefreshAfterResetModal';
 import SettingsModal from 'features/system/components/SettingsModal/SettingsModal';
 import { configChanged } from 'features/system/store/configSlice';
@@ -43,10 +44,17 @@ interface Props {
     action: 'sendToImg2Img' | 'sendToCanvas' | 'useAllParameters';
   };
   selectedWorkflowId?: string;
-  destination?: TabName | undefined;
+  selectedStylePresetId?: string;
+  destination?: TabName;
 }
 
-const App = ({ config = DEFAULT_CONFIG, selectedImage, selectedWorkflowId, destination }: Props) => {
+const App = ({
+  config = DEFAULT_CONFIG,
+  selectedImage,
+  selectedWorkflowId,
+  selectedStylePresetId,
+  destination,
+}: Props) => {
   const language = useAppSelector(selectLanguage);
   const logger = useLogger('system');
   const dispatch = useAppDispatch();
@@ -85,6 +93,12 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage, selectedWorkflowId, desti
     }
   }, [selectedWorkflowId, getAndLoadWorkflow]);
 
+  useEffect(() => {
+    if (selectedStylePresetId) {
+      dispatch(activeStylePresetIdChanged(selectedStylePresetId));
+    }
+  }, [dispatch, selectedStylePresetId]);
+
   useEffect(() => {
     if (destination) {
       dispatch(setActiveTab(destination));

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

@@ -45,6 +45,7 @@ interface Props extends PropsWithChildren {
     action: 'sendToImg2Img' | 'sendToCanvas' | 'useAllParameters';
   };
   selectedWorkflowId?: string;
+  selectedStylePresetId?: string;
   destination?: TabName;
   customStarUi?: CustomStarUi;
   socketOptions?: Partial<ManagerOptions & SocketOptions>;
@@ -66,6 +67,7 @@ const InvokeAIUI = ({
   queueId,
   selectedImage,
   selectedWorkflowId,
+  selectedStylePresetId,
   destination,
   customStarUi,
   socketOptions,
@@ -227,6 +229,7 @@ const InvokeAIUI = ({
                 config={config}
                 selectedImage={selectedImage}
                 selectedWorkflowId={selectedWorkflowId}
+                selectedStylePresetId={selectedStylePresetId}
                 destination={destination}
               />
             </AppDndContext>

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

@@ -68,7 +68,7 @@ export const addStagingListeners = (startAppListening: AppStartListening) => {
         objects: [imageObject],
       };
 
-      api.dispatch(rasterLayerAdded({ overrides, isSelected: true }));
+      api.dispatch(rasterLayerAdded({ overrides, isSelected: false }));
       api.dispatch(sessionStagingAreaReset());
     },
   });

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

@@ -31,7 +31,7 @@ export const addEnqueueRequestedLinear = (startAppListening: AppStartListening)
 
       let didStartStaging = false;
 
-      if (!state.canvasSession.isStaging && state.canvasSession.mode === 'compose') {
+      if (!state.canvasSession.isStaging && state.canvasSession.sendToCanvas) {
         dispatch(sessionStartedStaging());
         didStartStaging = true;
       }
@@ -70,7 +70,11 @@ export const addEnqueueRequestedLinear = (startAppListening: AppStartListening)
 
       const { g, noise, posCond } = buildGraphResult.value;
 
-      const prepareBatchResult = withResult(() => prepareLinearUIBatch(state, g, prepend, noise, posCond));
+      const destination = state.canvasSession.sendToCanvas ? 'canvas' : 'gallery';
+
+      const prepareBatchResult = withResult(() =>
+        prepareLinearUIBatch(state, g, prepend, noise, posCond, 'generation', destination)
+      );
 
       if (isErr(prepareBatchResult)) {
         log.error({ error: serializeError(prepareBatchResult.error) }, 'Failed to prepare batch');

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

@@ -32,6 +32,7 @@ export const addEnqueueRequestedNodes = (startAppListening: AppStartListening) =
           workflow: builtWorkflow,
           runs: state.params.iterations,
           origin: 'workflows',
+          destination: 'gallery',
         },
         prepend: action.payload.prepend,
       };

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

@@ -16,7 +16,7 @@ export const addEnqueueRequestedUpscale = (startAppListening: AppStartListening)
 
       const { g, noise, posCond } = await buildMultidiffusionUpscaleGraph(state);
 
-      const batchConfig = prepareLinearUIBatch(state, g, prepend, noise, posCond);
+      const batchConfig = prepareLinearUIBatch(state, g, prepend, noise, posCond, 'upscaling', 'gallery');
 
       const req = dispatch(
         queueApi.endpoints.enqueueBatch.initiate(batchConfig, {

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

@@ -0,0 +1,104 @@
+import type { SystemStyleObject } from '@invoke-ai/ui-library';
+import { Box, Flex, IconButton, Tooltip, useToken } from '@invoke-ai/ui-library';
+import type { ReactElement, ReactNode } from 'react';
+import { memo, useCallback, useMemo } from 'react';
+
+type IconSwitchProps = {
+  isChecked: boolean;
+  onChange: (checked: boolean) => void;
+  iconChecked: ReactElement;
+  tooltipChecked?: ReactNode;
+  iconUnchecked: ReactElement;
+  tooltipUnchecked?: ReactNode;
+  ariaLabel: string;
+};
+
+const getSx = (padding: string | number): SystemStyleObject => ({
+  transition: 'left 0.1s ease-in-out, transform 0.1s ease-in-out',
+  '&[data-checked="true"]': {
+    left: `calc(100% - ${padding})`,
+    transform: 'translateX(-100%)',
+  },
+  '&[data-checked="false"]': {
+    left: padding,
+    transform: 'translateX(0)',
+  },
+});
+
+export const IconSwitch = memo(
+  ({
+    isChecked,
+    onChange,
+    iconChecked,
+    tooltipChecked,
+    iconUnchecked,
+    tooltipUnchecked,
+    ariaLabel,
+  }: IconSwitchProps) => {
+    const onUncheck = useCallback(() => {
+      onChange(false);
+    }, [onChange]);
+    const onCheck = useCallback(() => {
+      onChange(true);
+    }, [onChange]);
+
+    const gap = useToken('space', 1.5);
+    const sx = useMemo(() => getSx(gap), [gap]);
+
+    return (
+      <Flex
+        position="relative"
+        bg="base.800"
+        borderRadius="base"
+        alignItems="center"
+        justifyContent="center"
+        h="full"
+        p={gap}
+        gap={gap}
+      >
+        <Box
+          position="absolute"
+          borderRadius="base"
+          bg="invokeBlue.400"
+          w={12}
+          top={gap}
+          bottom={gap}
+          data-checked={isChecked}
+          sx={sx}
+        />
+        <Tooltip hasArrow label={tooltipUnchecked}>
+          <IconButton
+            size="sm"
+            fontSize={16}
+            icon={iconUnchecked}
+            onClick={onUncheck}
+            variant={!isChecked ? 'solid' : 'ghost'}
+            colorScheme={!isChecked ? 'invokeBlue' : 'base'}
+            aria-label={ariaLabel}
+            data-checked={!isChecked}
+            w={12}
+            alignSelf="stretch"
+            h="auto"
+          />
+        </Tooltip>
+        <Tooltip hasArrow label={tooltipChecked}>
+          <IconButton
+            size="sm"
+            fontSize={16}
+            icon={iconChecked}
+            onClick={onCheck}
+            variant={isChecked ? 'solid' : 'ghost'}
+            colorScheme={isChecked ? 'invokeBlue' : 'base'}
+            aria-label={ariaLabel}
+            data-checked={isChecked}
+            w={12}
+            alignSelf="stretch"
+            h="auto"
+          />
+        </Tooltip>
+      </Flex>
+    );
+  }
+);
+
+IconSwitch.displayName = 'IconSwitch';

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

@@ -1,52 +1,74 @@
+import { useStore } from '@nanostores/react';
 import type { WritableAtom } from 'nanostores';
-import { useCallback, useMemo, useState } from 'react';
+import { atom } from 'nanostores';
+import { useCallback, useState } from 'react';
 
-export const useBoolean = (initialValue: boolean) => {
-  const [isTrue, set] = useState(initialValue);
-  const setTrue = useCallback(() => set(true), []);
-  const setFalse = useCallback(() => set(false), []);
-  const toggle = useCallback(() => set((v) => !v), []);
+type UseBoolean = {
+  isTrue: boolean;
+  setTrue: () => void;
+  setFalse: () => void;
+  set: (value: boolean) => void;
+  toggle: () => void;
+};
 
-  const api = useMemo(
-    () => ({
+/**
+ * Creates a hook to manage a boolean state. The boolean is stored in a nanostores atom.
+ * Returns a tuple containing the hook and the atom. Use this for global boolean state.
+ * @param initialValue Initial value of the boolean
+ */
+export const buildUseBoolean = (initialValue: boolean): [() => UseBoolean, WritableAtom<boolean>] => {
+  const $boolean = atom(initialValue);
+
+  const setTrue = () => {
+    $boolean.set(true);
+  };
+  const setFalse = () => {
+    $boolean.set(false);
+  };
+  const set = (value: boolean) => {
+    $boolean.set(value);
+  };
+  const toggle = () => {
+    $boolean.set(!$boolean.get());
+  };
+
+  const useBoolean = () => {
+    const isTrue = useStore($boolean);
+
+    return {
       isTrue,
-      set,
       setTrue,
       setFalse,
+      set,
       toggle,
-    }),
-    [isTrue, set, setTrue, setFalse, toggle]
-  );
+    };
+  };
 
-  return api;
+  return [useBoolean, $boolean] as const;
 };
 
-export const buildUseBoolean = ($boolean: WritableAtom<boolean>) => {
-  return () => {
-    const setTrue = useCallback(() => {
-      $boolean.set(true);
-    }, []);
-    const setFalse = useCallback(() => {
-      $boolean.set(false);
-    }, []);
-    const set = useCallback((value: boolean) => {
-      $boolean.set(value);
-    }, []);
-    const toggle = useCallback(() => {
-      $boolean.set(!$boolean.get());
-    }, []);
+/**
+ * Hook to manage a boolean state. Use this for a local boolean state.
+ * @param initialValue Initial value of the boolean
+ */
+export const useBoolean = (initialValue: boolean) => {
+  const [isTrue, set] = useState(initialValue);
 
-    const api = useMemo(
-      () => ({
-        setTrue,
-        setFalse,
-        set,
-        toggle,
-        $boolean,
-      }),
-      [set, setFalse, setTrue, toggle]
-    );
+  const setTrue = useCallback(() => {
+    set(true);
+  }, [set]);
+  const setFalse = useCallback(() => {
+    set(false);
+  }, [set]);
+  const toggle = useCallback(() => {
+    set((val) => !val);
+  }, [set]);
 
-    return api;
+  return {
+    isTrue,
+    setTrue,
+    setFalse,
+    set,
+    toggle,
   };
 };

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

@@ -1,7 +1,7 @@
 import { useAppDispatch } from 'app/store/storeHooks';
 import { addScope, removeScope, setScopes } from 'common/hooks/interactionScopes';
+import { useClearQueue } from 'features/queue/components/ClearQueueConfirmationAlertDialog';
 import { useCancelCurrentQueueItem } from 'features/queue/hooks/useCancelCurrentQueueItem';
-import { useClearQueue } from 'features/queue/hooks/useClearQueue';
 import { useQueueBack } from 'features/queue/hooks/useQueueBack';
 import { useQueueFront } from 'features/queue/hooks/useQueueFront';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';

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

@@ -31,22 +31,22 @@ export const CanvasAddEntityButtons = memo(() => {
   }, [dispatch]);
 
   return (
-    <Flex flexDir="column" w="full" h="full" alignItems="center" justifyContent="center">
-      <ButtonGroup orientation="vertical" isAttached={false}>
+    <Flex flexDir="column" w="full" h="full" alignItems="center">
+      <ButtonGroup position="relative" orientation="vertical" isAttached={false} top="20%">
         <Button variant="ghost" justifyContent="flex-start" leftIcon={<PiPlusBold />} onClick={addInpaintMask}>
-          {t('controlLayers.inpaintMask', { count: 1 })}
+          {t('controlLayers.inpaintMask')}
         </Button>
         <Button variant="ghost" justifyContent="flex-start" leftIcon={<PiPlusBold />} onClick={addRegionalGuidance}>
-          {t('controlLayers.regionalGuidance', { count: 1 })}
+          {t('controlLayers.regionalGuidance')}
         </Button>
         <Button variant="ghost" justifyContent="flex-start" leftIcon={<PiPlusBold />} onClick={addRasterLayer}>
-          {t('controlLayers.rasterLayer', { count: 1 })}
+          {t('controlLayers.rasterLayer')}
         </Button>
         <Button variant="ghost" justifyContent="flex-start" leftIcon={<PiPlusBold />} onClick={addControlLayer}>
-          {t('controlLayers.controlLayer', { count: 1 })}
+          {t('controlLayers.controlLayer')}
         </Button>
         <Button variant="ghost" justifyContent="flex-start" leftIcon={<PiPlusBold />} onClick={addIPAdapter}>
-          {t('controlLayers.ipAdapter', { count: 1 })}
+          {t('controlLayers.ipAdapter')}
         </Button>
       </ButtonGroup>
     </Flex>

invokeai/frontend/web/src/features/controlLayers/components/CanvasEntityList/EntityListActionBarAddLayerMenuItems.tsx

@@ -33,19 +33,19 @@ export const CanvasEntityListMenuItems = memo(() => {
   return (
     <>
       <MenuItem icon={<PiPlusBold />} onClick={addInpaintMask}>
-        {t('controlLayers.inpaintMask', { count: 1 })}
+        {t('controlLayers.inpaintMask')}
       </MenuItem>
       <MenuItem icon={<PiPlusBold />} onClick={addRegionalGuidance}>
-        {t('controlLayers.regionalGuidance', { count: 1 })}
+        {t('controlLayers.regionalGuidance')}
       </MenuItem>
       <MenuItem icon={<PiPlusBold />} onClick={addRasterLayer}>
-        {t('controlLayers.rasterLayer', { count: 1 })}
+        {t('controlLayers.rasterLayer')}
       </MenuItem>
       <MenuItem icon={<PiPlusBold />} onClick={addControlLayer}>
-        {t('controlLayers.controlLayer', { count: 1 })}
+        {t('controlLayers.controlLayer')}
       </MenuItem>
       <MenuItem icon={<PiPlusBold />} onClick={addIPAdapter}>
-        {t('controlLayers.ipAdapter', { count: 1 })}
+        {t('controlLayers.ipAdapter')}
       </MenuItem>
     </>
   );

invokeai/frontend/web/src/features/controlLayers/components/CanvasEntityList/EntityListActionBarSelectedEntityOpacity.tsx

@@ -157,7 +157,7 @@ export const SelectedEntityOpacity = memo(() => {
             clampValueOnBlur={false}
             variant="outline"
           >
-            <NumberInputField paddingInlineEnd={7} />
+            <NumberInputField paddingInlineEnd={7} _focusVisible={{ zIndex: 0 }} />
             <PopoverTrigger>
               <IconButton
                 aria-label="open-slider"

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

@@ -1,29 +0,0 @@
-import { Button, ButtonGroup } from '@invoke-ai/ui-library';
-import { createSelector } from '@reduxjs/toolkit';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { selectCanvasSessionSlice, sessionModeChanged } from 'features/controlLayers/store/canvasSessionSlice';
-import { memo, useCallback } from 'react';
-import { useTranslation } from 'react-i18next';
-
-const selectCanvasMode = createSelector(selectCanvasSessionSlice, (canvasSession) => canvasSession.mode);
-
-export const CanvasModeSwitcher = memo(() => {
-  const { t } = useTranslation();
-  const dispatch = useAppDispatch();
-  const mode = useAppSelector(selectCanvasMode);
-  const onClickGenerate = useCallback(() => dispatch(sessionModeChanged({ mode: 'generate' })), [dispatch]);
-  const onClickCompose = useCallback(() => dispatch(sessionModeChanged({ mode: 'compose' })), [dispatch]);
-
-  return (
-    <ButtonGroup variant="outline">
-      <Button onClick={onClickGenerate} colorScheme={mode === 'generate' ? 'invokeBlue' : 'base'}>
-        {t('controlLayers.generateMode')}
-      </Button>
-      <Button onClick={onClickCompose} colorScheme={mode === 'compose' ? 'invokeBlue' : 'base'}>
-        {t('controlLayers.composeMode')}
-      </Button>
-    </ButtonGroup>
-  );
-});
-
-CanvasModeSwitcher.displayName = 'CanvasModeSwitcher';

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

@@ -9,6 +9,7 @@ import { memo } from 'react';
 
 export const CanvasPanelContent = memo(() => {
   const hasEntities = useAppSelector(selectHasEntities);
+
   return (
     <CanvasManagerProviderGate>
       <Flex flexDir="column" gap={2} w="full" h="full">

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

@@ -0,0 +1,59 @@
+import { Flex, Text } from '@invoke-ai/ui-library';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { IconSwitch } from 'common/components/IconSwitch';
+import { selectIsComposing, sessionSendToCanvasChanged } from 'features/controlLayers/store/canvasSessionSlice';
+import { memo, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiImageBold, PiPaintBrushBold } from 'react-icons/pi';
+
+const TooltipSendToGallery = memo(() => {
+  const { t } = useTranslation();
+
+  return (
+    <Flex flexDir="column">
+      <Text fontWeight="semibold">{t('controlLayers.sendToGallery')}</Text>
+      <Text fontWeight="normal">{t('controlLayers.sendToGalleryDesc')}</Text>
+    </Flex>
+  );
+});
+
+TooltipSendToGallery.displayName = 'TooltipSendToGallery';
+
+const TooltipSendToCanvas = memo(() => {
+  const { t } = useTranslation();
+
+  return (
+    <Flex flexDir="column">
+      <Text fontWeight="semibold">{t('controlLayers.sendToCanvas')}</Text>
+      <Text fontWeight="normal">{t('controlLayers.sendToCanvasDesc')}</Text>
+    </Flex>
+  );
+});
+
+TooltipSendToCanvas.displayName = 'TooltipSendToCanvas';
+
+export const CanvasSendToToggle = memo(() => {
+  const dispatch = useAppDispatch();
+  const isComposing = useAppSelector(selectIsComposing);
+
+  const onChange = useCallback(
+    (isChecked: boolean) => {
+      dispatch(sessionSendToCanvasChanged(isChecked));
+    },
+    [dispatch]
+  );
+
+  return (
+    <IconSwitch
+      isChecked={isComposing}
+      onChange={onChange}
+      iconUnchecked={<PiImageBold />}
+      tooltipUnchecked={<TooltipSendToGallery />}
+      iconChecked={<PiPaintBrushBold />}
+      tooltipChecked={<TooltipSendToCanvas />}
+      ariaLabel="Toggle canvas mode"
+    />
+  );
+});
+
+CanvasSendToToggle.displayName = 'CanvasSendToToggle';

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

@@ -1,8 +1,7 @@
 import { Spacer } from '@invoke-ai/ui-library';
 import { CanvasEntityContainer } from 'features/controlLayers/components/common/CanvasEntityContainer';
-import { CanvasEntityEnabledToggle } from 'features/controlLayers/components/common/CanvasEntityEnabledToggle';
 import { CanvasEntityHeader } from 'features/controlLayers/components/common/CanvasEntityHeader';
-import { CanvasEntityIsLockedToggle } from 'features/controlLayers/components/common/CanvasEntityIsLockedToggle';
+import { CanvasEntityHeaderCommonActions } from 'features/controlLayers/components/common/CanvasEntityHeaderCommonActions';
 import { CanvasEntityPreviewImage } from 'features/controlLayers/components/common/CanvasEntityPreviewImage';
 import { CanvasEntitySettingsWrapper } from 'features/controlLayers/components/common/CanvasEntitySettingsWrapper';
 import { CanvasEntityEditableTitle } from 'features/controlLayers/components/common/CanvasEntityTitleEdit';
@@ -29,8 +28,7 @@ export const ControlLayer = memo(({ id }: Props) => {
             <CanvasEntityEditableTitle />
             <Spacer />
             <ControlLayerBadges />
-            <CanvasEntityIsLockedToggle />
-            <CanvasEntityEnabledToggle />
+            <CanvasEntityHeaderCommonActions />
           </CanvasEntityHeader>
           <CanvasEntitySettingsWrapper>
             <ControlLayerControlAdapter />

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

@@ -1,19 +1,21 @@
 /* eslint-disable i18next/no-literal-string */
 import { Flex, Spacer } from '@invoke-ai/ui-library';
-import { CanvasModeSwitcher } from 'features/controlLayers/components/CanvasModeSwitcher';
 import { CanvasResetViewButton } from 'features/controlLayers/components/CanvasResetViewButton';
 import { CanvasScale } from 'features/controlLayers/components/CanvasScale';
+import { SaveToGalleryButton } from 'features/controlLayers/components/SaveToGalleryButton';
 import { CanvasSettingsPopover } from 'features/controlLayers/components/Settings/CanvasSettingsPopover';
 import { ToolChooser } from 'features/controlLayers/components/Tool/ToolChooser';
 import { ToolFillColorPicker } from 'features/controlLayers/components/Tool/ToolFillColorPicker';
 import { ToolSettings } from 'features/controlLayers/components/Tool/ToolSettings';
-import { UndoRedoButtonGroup } from 'features/controlLayers/components/UndoRedoButtonGroup';
 import { CanvasManagerProviderGate } from 'features/controlLayers/contexts/CanvasManagerProviderGate';
+import { useCanvasUndoRedo } from 'features/controlLayers/hooks/useCanvasUndoRedo';
 import { ToggleProgressButton } from 'features/gallery/components/ImageViewer/ToggleProgressButton';
-import { ViewerToggleMenu } from 'features/gallery/components/ImageViewer/ViewerToggleMenu';
+import { ViewerToggle } from 'features/gallery/components/ImageViewer/ViewerToggleMenu';
 import { memo } from 'react';
 
 export const ControlLayersToolbar = memo(() => {
+  useCanvasUndoRedo();
+
   return (
     <CanvasManagerProviderGate>
       <Flex w="full" gap={2} alignItems="center">
@@ -26,10 +28,9 @@ export const ControlLayersToolbar = memo(() => {
         <CanvasResetViewButton />
         <Spacer />
         <ToolFillColorPicker />
-        <CanvasModeSwitcher />
-        <UndoRedoButtonGroup />
+        <SaveToGalleryButton />
         <CanvasSettingsPopover />
-        <ViewerToggleMenu />
+        <ViewerToggle />
       </Flex>
     </CanvasManagerProviderGate>
   );

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

@@ -1,53 +1,27 @@
-import { Box, Flex, Text } from '@invoke-ai/ui-library';
-import { useStore } from '@nanostores/react';
+import { Grid, GridItem, Text } from '@invoke-ai/ui-library';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
-import { useCanvasManager } from 'features/controlLayers/contexts/CanvasManagerProviderGate';
 import { selectCanvasSlice } from 'features/controlLayers/store/selectors';
-import { round } from 'lodash-es';
 import { memo } from 'react';
 
 const selectBbox = createSelector(selectCanvasSlice, (canvas) => canvas.bbox);
 
 export const HeadsUpDisplay = memo(() => {
-  const canvasManager = useCanvasManager();
-  const stageAttrs = useStore(canvasManager.stateApi.$stageAttrs);
-  const cursorPos = useStore(canvasManager.stateApi.$lastCursorPos);
-  const isDrawing = useStore(canvasManager.stateApi.$isDrawing);
-  const isMouseDown = useStore(canvasManager.stateApi.$isMouseDown);
-  const lastMouseDownPos = useStore(canvasManager.stateApi.$lastMouseDownPos);
-  const lastAddedPoint = useStore(canvasManager.stateApi.$lastAddedPoint);
   const bbox = useAppSelector(selectBbox);
 
   return (
-    <Flex flexDir="column" bg="blackAlpha.400" borderBottomEndRadius="base" p={2} minW={64} gap={2}>
-      <HUDItem label="Zoom" value={`${round(stageAttrs.scale * 100, 2)}%`} />
-      <HUDItem label="Stage Pos" value={`${round(stageAttrs.x, 3)}, ${round(stageAttrs.y, 3)}`} />
-      <HUDItem
-        label="Stage Size"
-        value={`${round(stageAttrs.width / stageAttrs.scale, 2)}×${round(stageAttrs.height / stageAttrs.scale, 2)} px`}
-      />
-      <HUDItem label="BBox Size" value={`${bbox.rect.width}×${bbox.rect.height} px`} />
-      <HUDItem label="BBox Position" value={`${bbox.rect.x}, ${bbox.rect.y}`} />
-      <HUDItem label="BBox Width % 8" value={round(bbox.rect.width % 8, 2)} />
-      <HUDItem label="BBox Height % 8" value={round(bbox.rect.height % 8, 2)} />
-      <HUDItem label="BBox X % 8" value={round(bbox.rect.x % 8, 2)} />
-      <HUDItem label="BBox Y % 8" value={round(bbox.rect.y % 8, 2)} />
-      <HUDItem
-        label="Cursor Position"
-        value={cursorPos ? `${round(cursorPos.x, 2)}, ${round(cursorPos.y, 2)}` : '?, ?'}
-      />
-      <HUDItem label="Is Drawing" value={isDrawing ? 'True' : 'False'} />
-      <HUDItem label="Is Mouse Down" value={isMouseDown ? 'True' : 'False'} />
-      <HUDItem
-        label="Last Mouse Down Pos"
-        value={lastMouseDownPos ? `${round(lastMouseDownPos.x, 2)}, ${round(lastMouseDownPos.y, 2)}` : '?, ?'}
-      />
-      <HUDItem
-        label="Last Added Point"
-        value={lastAddedPoint ? `${round(lastAddedPoint.x, 2)}, ${round(lastAddedPoint.y, 2)}` : '?, ?'}
-      />
-    </Flex>
+    <Grid
+      bg="base.900"
+      borderBottomEndRadius="base"
+      p={2}
+      gap={2}
+      borderRadius="base"
+      templateColumns="auto auto"
+      opacity={0.6}
+    >
+      <HUDItem label="BBox" value={`${bbox.rect.width}×${bbox.rect.height} px`} />
+      <HUDItem label="Scaled BBox" value={`${bbox.scaledSize.width}×${bbox.scaledSize.height} px`} />
+    </Grid>
   );
 });
 
@@ -55,12 +29,14 @@ HeadsUpDisplay.displayName = 'HeadsUpDisplay';
 
 const HUDItem = memo(({ label, value }: { label: string; value: string | number }) => {
   return (
-    <Box display="inline-block" lineHeight={1}>
-      <Text as="span">{label}: </Text>
-      <Text as="span" fontWeight="semibold">
-        {value}
-      </Text>
-    </Box>
+    <>
+      <GridItem>
+        <Text textAlign="end">{label}: </Text>
+      </GridItem>
+      <GridItem fontWeight="semibold">
+        <Text>{value}</Text>
+      </GridItem>
+    </>
   );
 });
 

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

@@ -1,7 +1,7 @@
 import { Spacer } from '@invoke-ai/ui-library';
 import { CanvasEntityContainer } from 'features/controlLayers/components/common/CanvasEntityContainer';
-import { CanvasEntityEnabledToggle } from 'features/controlLayers/components/common/CanvasEntityEnabledToggle';
 import { CanvasEntityHeader } from 'features/controlLayers/components/common/CanvasEntityHeader';
+import { CanvasEntityHeaderCommonActions } from 'features/controlLayers/components/common/CanvasEntityHeaderCommonActions';
 import { CanvasEntityEditableTitle } from 'features/controlLayers/components/common/CanvasEntityTitleEdit';
 import { IPAdapterSettings } from 'features/controlLayers/components/IPAdapter/IPAdapterSettings';
 import { EntityIdentifierContext } from 'features/controlLayers/contexts/EntityIdentifierContext';
@@ -18,10 +18,10 @@ export const IPAdapter = memo(({ id }: Props) => {
   return (
     <EntityIdentifierContext.Provider value={entityIdentifier}>
       <CanvasEntityContainer>
-        <CanvasEntityHeader ps={4}>
+        <CanvasEntityHeader ps={4} py={5}>
           <CanvasEntityEditableTitle />
           <Spacer />
-          <CanvasEntityEnabledToggle />
+          <CanvasEntityHeaderCommonActions />
         </CanvasEntityHeader>
         <IPAdapterSettings />
       </CanvasEntityContainer>

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

@@ -1,8 +1,7 @@
 import { Spacer } from '@invoke-ai/ui-library';
 import { CanvasEntityContainer } from 'features/controlLayers/components/common/CanvasEntityContainer';
-import { CanvasEntityEnabledToggle } from 'features/controlLayers/components/common/CanvasEntityEnabledToggle';
 import { CanvasEntityHeader } from 'features/controlLayers/components/common/CanvasEntityHeader';
-import { CanvasEntityIsLockedToggle } from 'features/controlLayers/components/common/CanvasEntityIsLockedToggle';
+import { CanvasEntityHeaderCommonActions } from 'features/controlLayers/components/common/CanvasEntityHeaderCommonActions';
 import { CanvasEntityPreviewImage } from 'features/controlLayers/components/common/CanvasEntityPreviewImage';
 import { CanvasEntityEditableTitle } from 'features/controlLayers/components/common/CanvasEntityTitleEdit';
 import { EntityMaskAdapterGate } from 'features/controlLayers/contexts/EntityAdapterContext';
@@ -25,8 +24,7 @@ export const InpaintMask = memo(({ id }: Props) => {
             <CanvasEntityPreviewImage />
             <CanvasEntityEditableTitle />
             <Spacer />
-            <CanvasEntityIsLockedToggle />
-            <CanvasEntityEnabledToggle />
+            <CanvasEntityHeaderCommonActions />
           </CanvasEntityHeader>
         </CanvasEntityContainer>
       </EntityMaskAdapterGate>

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

@@ -1,8 +1,7 @@
 import { Spacer } from '@invoke-ai/ui-library';
 import { CanvasEntityContainer } from 'features/controlLayers/components/common/CanvasEntityContainer';
-import { CanvasEntityEnabledToggle } from 'features/controlLayers/components/common/CanvasEntityEnabledToggle';
 import { CanvasEntityHeader } from 'features/controlLayers/components/common/CanvasEntityHeader';
-import { CanvasEntityIsLockedToggle } from 'features/controlLayers/components/common/CanvasEntityIsLockedToggle';
+import { CanvasEntityHeaderCommonActions } from 'features/controlLayers/components/common/CanvasEntityHeaderCommonActions';
 import { CanvasEntityPreviewImage } from 'features/controlLayers/components/common/CanvasEntityPreviewImage';
 import { CanvasEntityEditableTitle } from 'features/controlLayers/components/common/CanvasEntityTitleEdit';
 import { EntityLayerAdapterGate } from 'features/controlLayers/contexts/EntityAdapterContext';
@@ -25,8 +24,7 @@ export const RasterLayer = memo(({ id }: Props) => {
             <CanvasEntityPreviewImage />
             <CanvasEntityEditableTitle />
             <Spacer />
-            <CanvasEntityIsLockedToggle />
-            <CanvasEntityEnabledToggle />
+            <CanvasEntityHeaderCommonActions />
           </CanvasEntityHeader>
         </CanvasEntityContainer>
       </EntityLayerAdapterGate>

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

@@ -1,8 +1,7 @@
 import { Spacer } from '@invoke-ai/ui-library';
 import { CanvasEntityContainer } from 'features/controlLayers/components/common/CanvasEntityContainer';
-import { CanvasEntityEnabledToggle } from 'features/controlLayers/components/common/CanvasEntityEnabledToggle';
 import { CanvasEntityHeader } from 'features/controlLayers/components/common/CanvasEntityHeader';
-import { CanvasEntityIsLockedToggle } from 'features/controlLayers/components/common/CanvasEntityIsLockedToggle';
+import { CanvasEntityHeaderCommonActions } from 'features/controlLayers/components/common/CanvasEntityHeaderCommonActions';
 import { CanvasEntityPreviewImage } from 'features/controlLayers/components/common/CanvasEntityPreviewImage';
 import { CanvasEntityEditableTitle } from 'features/controlLayers/components/common/CanvasEntityTitleEdit';
 import { RegionalGuidanceBadges } from 'features/controlLayers/components/RegionalGuidance/RegionalGuidanceBadges';
@@ -28,8 +27,7 @@ export const RegionalGuidance = memo(({ id }: Props) => {
             <CanvasEntityEditableTitle />
             <Spacer />
             <RegionalGuidanceBadges />
-            <CanvasEntityIsLockedToggle />
-            <CanvasEntityEnabledToggle />
+            <CanvasEntityHeaderCommonActions />
           </CanvasEntityHeader>
           <RegionalGuidanceSettings />
         </CanvasEntityContainer>

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

@@ -0,0 +1,53 @@
+import { IconButton, useShiftModifier } from '@invoke-ai/ui-library';
+import { logger } from 'app/logging/logger';
+import { buildUseBoolean } from 'common/hooks/useBoolean';
+import { isOk, withResultAsync } from 'common/util/result';
+import { useCanvasManager } from 'features/controlLayers/contexts/CanvasManagerProviderGate';
+import { toast } from 'features/toast/toast';
+import { memo, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiFloppyDiskBold } from 'react-icons/pi';
+import { serializeError } from 'serialize-error';
+
+const log = logger('canvas');
+
+const [useIsSaving] = buildUseBoolean(false);
+
+export const SaveToGalleryButton = memo(() => {
+  const { t } = useTranslation();
+  const shift = useShiftModifier();
+  const canvasManager = useCanvasManager();
+  const isSaving = useIsSaving();
+
+  const onClick = useCallback(async () => {
+    isSaving.setTrue();
+
+    const rect = shift ? canvasManager.stateApi.getBbox().rect : canvasManager.stage.getVisibleRect('raster_layer');
+
+    const result = await withResultAsync(() =>
+      canvasManager.compositor.rasterizeAndUploadCompositeRasterLayer(rect, true)
+    );
+
+    if (isOk(result)) {
+      toast({ title: t('controlLayers.savedToGalleryOk') });
+    } else {
+      log.error({ error: serializeError(result.error) }, 'Failed to save canvas to gallery');
+      toast({ title: t('controlLayers.savedToGalleryError'), status: 'error' });
+    }
+
+    isSaving.setFalse();
+  }, [canvasManager.compositor, canvasManager.stage, canvasManager.stateApi, isSaving, shift, t]);
+
+  return (
+    <IconButton
+      variant="ghost"
+      onClick={onClick}
+      icon={<PiFloppyDiskBold />}
+      isLoading={isSaving.isTrue}
+      aria-label={shift ? t('controlLayers.saveBboxToGallery') : t('controlLayers.saveCanvasToGallery')}
+      tooltip={shift ? t('controlLayers.saveBboxToGallery') : t('controlLayers.saveCanvasToGallery')}
+    />
+  );
+});
+
+SaveToGalleryButton.displayName = 'SaveToGalleryButton';

invokeai/frontend/web/src/features/controlLayers/components/Settings/CanvasSettingsPopover.tsx

@@ -18,6 +18,7 @@ import { CanvasSettingsInvertScrollCheckbox } from 'features/controlLayers/compo
 import { CanvasSettingsLogDebugInfoButton } from 'features/controlLayers/components/Settings/CanvasSettingsLogDebugInfo';
 import { CanvasSettingsRecalculateRectsButton } from 'features/controlLayers/components/Settings/CanvasSettingsRecalculateRectsButton';
 import { CanvasSettingsResetButton } from 'features/controlLayers/components/Settings/CanvasSettingsResetButton';
+import { CanvasSettingsShowHUDSwitch } from 'features/controlLayers/components/Settings/CanvasSettingsShowHUDSwitch';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { RiSettings4Fill } from 'react-icons/ri';
@@ -37,6 +38,7 @@ export const CanvasSettingsPopover = memo(() => {
             <CanvasSettingsInvertScrollCheckbox />
             <CanvasSettingsClipToBboxCheckbox />
             <CanvasSettingsDynamicGridSwitch />
+            <CanvasSettingsShowHUDSwitch />
             <CanvasSettingsResetButton />
             <DebugSettings />
           </Flex>

invokeai/frontend/web/src/features/controlLayers/components/Settings/CanvasSettingsShowHUDSwitch.tsx

@@ -0,0 +1,28 @@
+import { FormControl, FormLabel, Switch } from '@invoke-ai/ui-library';
+import { createSelector } from '@reduxjs/toolkit';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { selectCanvasSettingsSlice, settingsShowHUDToggled } from 'features/controlLayers/store/canvasSettingsSlice';
+import { memo, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+
+const selectShowHUD = createSelector(selectCanvasSettingsSlice, (canvasSettings) => canvasSettings.showHUD);
+
+export const CanvasSettingsShowHUDSwitch = memo(() => {
+  const { t } = useTranslation();
+  const dispatch = useAppDispatch();
+  const showHUD = useAppSelector(selectShowHUD);
+  const onChange = useCallback(() => {
+    dispatch(settingsShowHUDToggled());
+  }, [dispatch]);
+
+  return (
+    <FormControl>
+      <FormLabel m={0} flexGrow={1}>
+        {t('controlLayers.showHUD')}
+      </FormLabel>
+      <Switch size="sm" isChecked={showHUD} onChange={onChange} />
+    </FormControl>
+  );
+});
+
+CanvasSettingsShowHUDSwitch.displayName = 'CanvasSettingsShowHUDSwitch';

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

@@ -8,20 +8,18 @@ import { useAppSelector } from 'app/store/storeHooks';
 import { HeadsUpDisplay } from 'features/controlLayers/components/HeadsUpDisplay';
 import { CanvasManager } from 'features/controlLayers/konva/CanvasManager';
 import { TRANSPARENCY_CHECKER_PATTERN } from 'features/controlLayers/konva/constants';
+import { getPrefixedId } from 'features/controlLayers/konva/util';
 import { selectCanvasSettingsSlice } from 'features/controlLayers/store/canvasSettingsSlice';
 import Konva from 'konva';
 import { memo, useCallback, useEffect, useLayoutEffect, useState } from 'react';
 import { useDevicePixelRatio } from 'use-device-pixel-ratio';
-import { v4 as uuidv4 } from 'uuid';
 
 const log = logger('canvas');
 
-const showHud = false;
-
 // This will log warnings when layers > 5 - maybe use `import.meta.env.MODE === 'development'` instead?
 Konva.showWarnings = false;
 
-const useStageRenderer = (stage: Konva.Stage, container: HTMLDivElement | null, asPreview: boolean) => {
+const useStageRenderer = (stage: Konva.Stage, container: HTMLDivElement | null) => {
   const store = useAppStore();
   const socket = useStore($socket);
   const dpr = useDevicePixelRatio({ round: false });
@@ -42,28 +40,25 @@ const useStageRenderer = (stage: Konva.Stage, container: HTMLDivElement | null,
     const manager = new CanvasManager(stage, container, store, socket);
     manager.initialize();
     return manager.destroy;
-  }, [asPreview, container, socket, stage, store]);
+  }, [container, socket, stage, store]);
 
   useLayoutEffect(() => {
     Konva.pixelRatio = dpr;
   }, [dpr]);
 };
 
-type Props = {
-  asPreview?: boolean;
-};
-
 const selectDynamicGrid = createSelector(selectCanvasSettingsSlice, (canvasSettings) => canvasSettings.dynamicGrid);
+const selectShowHUD = createSelector(selectCanvasSettingsSlice, (canvasSettings) => canvasSettings.showHUD);
 
-export const StageComponent = memo(({ asPreview = false }: Props) => {
+export const StageComponent = memo(() => {
   const dynamicGrid = useAppSelector(selectDynamicGrid);
+  const showHUD = useAppSelector(selectShowHUD);
 
   const [stage] = useState(
     () =>
       new Konva.Stage({
-        id: uuidv4(),
+        id: getPrefixedId('konva_stage'),
         container: document.createElement('div'),
-        listening: !asPreview,
       })
   );
   const [container, setContainer] = useState<HTMLDivElement | null>(null);
@@ -72,7 +67,7 @@ export const StageComponent = memo(({ asPreview = false }: Props) => {
     setContainer(el);
   }, []);
 
-  useStageRenderer(stage, container, asPreview);
+  useStageRenderer(stage, container);
 
   useEffect(
     () => () => {
@@ -106,9 +101,9 @@ export const StageComponent = memo(({ asPreview = false }: Props) => {
         overflow="hidden"
         data-testid="control-layers-canvas"
       />
-      {!asPreview && (
-        <Flex position="absolute" top={0} insetInlineStart={0} pointerEvents="none">
-          {showHud && <HeadsUpDisplay />}
+      {showHUD && (
+        <Flex position="absolute" top={1} insetInlineStart={1} pointerEvents="none">
+          <HeadsUpDisplay />
         </Flex>
       )}
     </Flex>

invokeai/frontend/web/src/features/controlLayers/components/StagingArea/StagingAreaToolbar.tsx

@@ -98,9 +98,9 @@ export const StagingAreaToolbar = memo(() => {
     onPrev,
     {
       preventDefault: true,
-      enabled: isCanvasActive,
+      enabled: isCanvasActive && shouldShowStagedImage && imageCount > 1,
     },
-    [isCanvasActive]
+    [isCanvasActive, shouldShowStagedImage, imageCount]
   );
 
   useHotkeys(
@@ -108,9 +108,9 @@ export const StagingAreaToolbar = memo(() => {
     onNext,
     {
       preventDefault: true,
-      enabled: isCanvasActive,
+      enabled: isCanvasActive && shouldShowStagedImage && imageCount > 1,
     },
-    [isCanvasActive]
+    [isCanvasActive, shouldShowStagedImage, imageCount]
   );
 
   useHotkeys(
@@ -118,9 +118,9 @@ export const StagingAreaToolbar = memo(() => {
     onAccept,
     {
       preventDefault: true,
-      enabled: isCanvasActive,
+      enabled: isCanvasActive && shouldShowStagedImage && imageCount > 1,
     },
-    [isCanvasActive]
+    [isCanvasActive, shouldShowStagedImage, imageCount]
   );
 
   const counterText = useMemo(() => {

invokeai/frontend/web/src/features/controlLayers/components/Tool/ToolFillColorPicker.tsx

@@ -1,4 +1,4 @@
-import { Flex, Popover, PopoverBody, PopoverContent, PopoverTrigger } from '@invoke-ai/ui-library';
+import { Box, Flex, Popover, PopoverBody, PopoverContent, PopoverTrigger, Tooltip } from '@invoke-ai/ui-library';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import IAIColorPicker from 'common/components/IAIColorPicker';
@@ -23,17 +23,13 @@ export const ToolFillColorPicker = memo(() => {
   return (
     <Popover isLazy>
       <PopoverTrigger>
-        <Flex
-          as="button"
-          aria-label={t('controlLayers.brushColor')}
-          borderRadius="full"
-          borderWidth={1}
-          bg={rgbaColorToString(fill)}
-          w={8}
-          h={8}
-          cursor="pointer"
-          tabIndex={-1}
-        />
+        <Flex role="button" aria-label={t('controlLayers.fill.fillColor')} tabIndex={-1} w={8} h={8}>
+          <Tooltip label={t('controlLayers.fill.fillColor')}>
+            <Flex w="full" h="full" alignItems="center" justifyContent="center">
+              <Box borderRadius="full" w={6} h={6} borderWidth={1} bg={rgbaColorToString(fill)} />
+            </Flex>
+          </Tooltip>
+        </Flex>
       </PopoverTrigger>
       <PopoverContent>
         <PopoverBody minH={64}>

invokeai/frontend/web/src/features/controlLayers/components/common/CanvasEntityAddOfTypeButton.tsx

@@ -0,0 +1,70 @@
+import { IconButton } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
+import {
+  controlLayerAdded,
+  inpaintMaskAdded,
+  ipaAdded,
+  rasterLayerAdded,
+  rgAdded,
+} from 'features/controlLayers/store/canvasSlice';
+import type { CanvasEntityIdentifier } from 'features/controlLayers/store/types';
+import { memo, useCallback, useMemo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiPlusBold } from 'react-icons/pi';
+
+type Props = {
+  type: CanvasEntityIdentifier['type'];
+};
+
+export const CanvasEntityAddOfTypeButton = memo(({ type }: Props) => {
+  const { t } = useTranslation();
+  const dispatch = useAppDispatch();
+  const onClick = useCallback(() => {
+    switch (type) {
+      case 'inpaint_mask':
+        dispatch(inpaintMaskAdded({ isSelected: true }));
+        break;
+      case 'regional_guidance':
+        dispatch(rgAdded({ isSelected: true }));
+        break;
+      case 'raster_layer':
+        dispatch(rasterLayerAdded({ isSelected: true }));
+        break;
+      case 'control_layer':
+        dispatch(controlLayerAdded({ isSelected: true }));
+        break;
+      case 'ip_adapter':
+        dispatch(ipaAdded({ isSelected: true }));
+        break;
+    }
+  }, [dispatch, type]);
+
+  const label = useMemo(() => {
+    switch (type) {
+      case 'inpaint_mask':
+        return t('controlLayers.addInpaintMask');
+      case 'regional_guidance':
+        return t('controlLayers.addRegionalGuidance');
+      case 'raster_layer':
+        return t('controlLayers.addRasterLayer');
+      case 'control_layer':
+        return t('controlLayers.addControlLayer');
+      case 'ip_adapter':
+        return t('controlLayers.addIPAdapter');
+    }
+  }, [type, t]);
+
+  return (
+    <IconButton
+      size="sm"
+      aria-label={label}
+      tooltip={label}
+      variant="link"
+      icon={<PiPlusBold />}
+      onClick={onClick}
+      alignSelf="stretch"
+    />
+  );
+});
+
+CanvasEntityAddOfTypeButton.displayName = 'CanvasEntityAddOfTypeButton';

invokeai/frontend/web/src/features/controlLayers/components/common/CanvasEntityDeleteButton.tsx

@@ -0,0 +1,31 @@
+import { IconButton } from '@invoke-ai/ui-library';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { useEntityIdentifierContext } from 'features/controlLayers/contexts/EntityIdentifierContext';
+import { entityDeleted } from 'features/controlLayers/store/canvasSlice';
+import { memo, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiTrashSimpleFill } from 'react-icons/pi';
+
+export const CanvasEntityDeleteButton = memo(() => {
+  const { t } = useTranslation();
+  const entityIdentifier = useEntityIdentifierContext();
+  const dispatch = useAppDispatch();
+  const onClick = useCallback(() => {
+    dispatch(entityDeleted({ entityIdentifier }));
+  }, [dispatch, entityIdentifier]);
+
+  return (
+    <IconButton
+      size="sm"
+      aria-label={t('common.delete')}
+      tooltip={t('common.delete')}
+      variant="link"
+      alignSelf="stretch"
+      icon={<PiTrashSimpleFill />}
+      onClick={onClick}
+      colorScheme="error"
+    />
+  );
+});
+
+CanvasEntityDeleteButton.displayName = 'CanvasEntityDeleteButton';

invokeai/frontend/web/src/features/controlLayers/components/common/CanvasEntityEnabledToggle.tsx

@@ -21,7 +21,8 @@ export const CanvasEntityEnabledToggle = memo(() => {
       size="sm"
       aria-label={t(isEnabled ? 'common.enabled' : 'common.disabled')}
       tooltip={t(isEnabled ? 'common.enabled' : 'common.disabled')}
-      variant="ghost"
+      variant="link"
+      alignSelf="stretch"
       icon={isEnabled ? <PiCircleFill /> : <PiCircleBold />}
       onClick={onClick}
     />

invokeai/frontend/web/src/features/controlLayers/components/common/CanvasEntityGroupList.tsx

@@ -1,11 +1,13 @@
 import type { SystemStyleObject } from '@invoke-ai/ui-library';
 import { Button, Collapse, Flex, Icon, Spacer, Text } from '@invoke-ai/ui-library';
 import { useBoolean } from 'common/hooks/useBoolean';
+import { CanvasEntityAddOfTypeButton } from 'features/controlLayers/components/common/CanvasEntityAddOfTypeButton';
+import { CanvasEntityMergeVisibleButton } from 'features/controlLayers/components/common/CanvasEntityMergeVisibleButton';
 import { CanvasEntityTypeIsHiddenToggle } from 'features/controlLayers/components/common/CanvasEntityTypeIsHiddenToggle';
 import { useEntityTypeTitle } from 'features/controlLayers/hooks/useEntityTypeTitle';
 import type { CanvasEntityIdentifier } from 'features/controlLayers/store/types';
 import type { PropsWithChildren } from 'react';
-import { memo } from 'react';
+import { memo, useMemo } from 'react';
 import { PiCaretDownBold } from 'react-icons/pi';
 
 type Props = PropsWithChildren<{
@@ -20,6 +22,9 @@ const _hover: SystemStyleObject = {
 export const CanvasEntityGroupList = memo(({ isSelected, type, children }: Props) => {
   const title = useEntityTypeTitle(type);
   const collapse = useBoolean(true);
+  const canMergeVisible = useMemo(() => type === 'raster_layer' || type === 'inpaint_mask', [type]);
+  const canHideAll = useMemo(() => type !== 'ip_adapter', [type]);
+
   return (
     <Flex flexDir="column" w="full">
       <Flex w="full">
@@ -53,7 +58,9 @@ export const CanvasEntityGroupList = memo(({ isSelected, type, children }: Props
           </Text>
           <Spacer />
         </Flex>
-        {type !== 'ip_adapter' && <CanvasEntityTypeIsHiddenToggle type={type} />}
+        {canMergeVisible && <CanvasEntityMergeVisibleButton type={type} />}
+        <CanvasEntityAddOfTypeButton type={type} />
+        {canHideAll && <CanvasEntityTypeIsHiddenToggle type={type} />}
       </Flex>
       <Collapse in={collapse.isTrue}>
         <Flex flexDir="column" gap={2} pt={2}>

invokeai/frontend/web/src/features/controlLayers/components/common/CanvasEntityHeader.tsx

@@ -56,7 +56,7 @@ export const CanvasEntityHeader = memo(({ children, ...rest }: FlexProps) => {
   }, [entityIdentifier]);
 
   return (
-    <ContextMenu renderMenu={renderMenu} stopImmediatePropagation>
+    <ContextMenu renderMenu={renderMenu}>
       {(ref) => (
         <Flex ref={ref} gap={2} alignItems="center" p={2} {...rest}>
           {children}

invokeai/frontend/web/src/features/controlLayers/components/common/CanvasEntityHeaderCommonActions.tsx

@@ -0,0 +1,20 @@
+import { Flex } from '@invoke-ai/ui-library';
+import { CanvasEntityDeleteButton } from 'features/controlLayers/components/common/CanvasEntityDeleteButton';
+import { CanvasEntityEnabledToggle } from 'features/controlLayers/components/common/CanvasEntityEnabledToggle';
+import { CanvasEntityIsLockedToggle } from 'features/controlLayers/components/common/CanvasEntityIsLockedToggle';
+import { useEntityIdentifierContext } from 'features/controlLayers/contexts/EntityIdentifierContext';
+import { memo } from 'react';
+
+export const CanvasEntityHeaderCommonActions = memo(() => {
+  const entityIdentifier = useEntityIdentifierContext();
+
+  return (
+    <Flex alignSelf="stretch">
+      {entityIdentifier.type !== 'ip_adapter' && <CanvasEntityIsLockedToggle />}
+      <CanvasEntityEnabledToggle />
+      <CanvasEntityDeleteButton />
+    </Flex>
+  );
+});
+
+CanvasEntityHeaderCommonActions.displayName = 'CanvasEntityHeaderCommonActions';

invokeai/frontend/web/src/features/controlLayers/components/common/CanvasEntityIsLockedToggle.tsx

@@ -21,7 +21,8 @@ export const CanvasEntityIsLockedToggle = memo(() => {
       size="sm"
       aria-label={t(isLocked ? 'controlLayers.locked' : 'controlLayers.unlocked')}
       tooltip={t(isLocked ? 'controlLayers.locked' : 'controlLayers.unlocked')}
-      variant="ghost"
+      variant="link"
+      alignSelf="stretch"
       icon={isLocked ? <PiLockSimpleFill /> : <PiLockSimpleOpenBold />}
       onClick={onClick}
     />

invokeai/frontend/web/src/features/controlLayers/components/common/CanvasEntityMergeVisibleButton.tsx

@@ -0,0 +1,88 @@
+import { IconButton } from '@invoke-ai/ui-library';
+import { logger } from 'app/logging/logger';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { isOk, withResultAsync } from 'common/util/result';
+import { useCanvasManager } from 'features/controlLayers/contexts/CanvasManagerProviderGate';
+import { inpaintMaskAdded, rasterLayerAdded } from 'features/controlLayers/store/canvasSlice';
+import type { CanvasEntityIdentifier } from 'features/controlLayers/store/types';
+import { imageDTOToImageObject } from 'features/controlLayers/store/types';
+import { toast } from 'features/toast/toast';
+import { memo, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiStackBold } from 'react-icons/pi';
+import { serializeError } from 'serialize-error';
+
+const log = logger('canvas');
+
+type Props = {
+  type: CanvasEntityIdentifier['type'];
+};
+
+export const CanvasEntityMergeVisibleButton = memo(({ type }: Props) => {
+  const { t } = useTranslation();
+  const dispatch = useAppDispatch();
+  const canvasManager = useCanvasManager();
+  const onClick = useCallback(async () => {
+    if (type === 'raster_layer') {
+      const rect = canvasManager.stage.getVisibleRect('raster_layer');
+      const result = await withResultAsync(() =>
+        canvasManager.compositor.rasterizeAndUploadCompositeRasterLayer(rect, false)
+      );
+
+      if (isOk(result)) {
+        dispatch(
+          rasterLayerAdded({
+            isSelected: true,
+            overrides: {
+              objects: [imageDTOToImageObject(result.value)],
+              position: { x: Math.floor(rect.x), y: Math.floor(rect.y) },
+            },
+            deleteOthers: true,
+          })
+        );
+        toast({ title: t('controlLayers.mergeVisibleOk') });
+      } else {
+        log.error({ error: serializeError(result.error) }, 'Failed to merge visible');
+        toast({ title: t('controlLayers.mergeVisibleError'), status: 'error' });
+      }
+    } else if (type === 'inpaint_mask') {
+      const rect = canvasManager.stage.getVisibleRect('inpaint_mask');
+      const result = await withResultAsync(() =>
+        canvasManager.compositor.rasterizeAndUploadCompositeInpaintMask(rect, false)
+      );
+
+      if (isOk(result)) {
+        dispatch(
+          inpaintMaskAdded({
+            isSelected: true,
+            overrides: {
+              objects: [imageDTOToImageObject(result.value)],
+              position: { x: Math.floor(rect.x), y: Math.floor(rect.y) },
+            },
+            deleteOthers: true,
+          })
+        );
+        toast({ title: t('controlLayers.mergeVisibleOk') });
+      } else {
+        log.error({ error: serializeError(result.error) }, 'Failed to merge visible');
+        toast({ title: t('controlLayers.mergeVisibleError'), status: 'error' });
+      }
+    } else {
+      log.error({ type }, 'Unsupported type for merge visible');
+    }
+  }, [canvasManager.compositor, canvasManager.stage, dispatch, t, type]);
+
+  return (
+    <IconButton
+      size="sm"
+      aria-label={t('controlLayers.mergeVisible')}
+      tooltip={t('controlLayers.mergeVisible')}
+      variant="link"
+      icon={<PiStackBold />}
+      onClick={onClick}
+      alignSelf="stretch"
+    />
+  );
+});
+
+CanvasEntityMergeVisibleButton.displayName = 'CanvasEntityMergeVisibleButton';

invokeai/frontend/web/src/features/controlLayers/hooks/useCanvasUndoRedo.tsx

@@ -1,16 +1,14 @@
 /* eslint-disable i18next/no-literal-string */
-import { ButtonGroup, IconButton } from '@invoke-ai/ui-library';
 import { useAppSelector } from 'app/store/storeHooks';
+import { useAssertSingleton } from 'common/hooks/useAssertSingleton';
 import { canvasRedo, canvasUndo } from 'features/controlLayers/store/canvasSlice';
 import { selectCanvasMayRedo, selectCanvasMayUndo } from 'features/controlLayers/store/selectors';
-import { memo, useCallback } from 'react';
+import { useCallback } from 'react';
 import { useHotkeys } from 'react-hotkeys-hook';
-import { useTranslation } from 'react-i18next';
-import { PiArrowClockwiseBold, PiArrowCounterClockwiseBold } from 'react-icons/pi';
 import { useDispatch } from 'react-redux';
 
-export const UndoRedoButtonGroup = memo(() => {
-  const { t } = useTranslation();
+export const useCanvasUndoRedo = () => {
+  useAssertSingleton('useCanvasUndoRedo');
   const dispatch = useDispatch();
 
   const mayUndo = useAppSelector(selectCanvasMayUndo);
@@ -27,27 +25,4 @@ export const UndoRedoButtonGroup = memo(() => {
     mayRedo,
     handleRedo,
   ]);
-
-  return (
-    <ButtonGroup isAttached={false}>
-      <IconButton
-        aria-label={t('unifiedCanvas.undo')}
-        tooltip={t('unifiedCanvas.undo')}
-        onClick={handleUndo}
-        icon={<PiArrowCounterClockwiseBold />}
-        isDisabled={!mayUndo}
-        variant="ghost"
-      />
-      <IconButton
-        aria-label={t('unifiedCanvas.redo')}
-        tooltip={t('unifiedCanvas.redo')}
-        onClick={handleRedo}
-        icon={<PiArrowClockwiseBold />}
-        isDisabled={!mayRedo}
-        variant="ghost"
-      />
-    </ButtonGroup>
-  );
-});
-
-UndoRedoButtonGroup.displayName = 'UndoRedoButtonGroup';
+};

invokeai/frontend/web/src/features/controlLayers/hooks/useEntityTitle.ts

@@ -29,15 +29,15 @@ export const useEntityTitle = (entityIdentifier: CanvasEntityIdentifier) => {
 
     const parts: string[] = [];
     if (entityIdentifier.type === 'inpaint_mask') {
-      parts.push(t('controlLayers.inpaintMask', { count: 1 }));
+      parts.push(t('controlLayers.inpaintMask'));
     } else if (entityIdentifier.type === 'control_layer') {
-      parts.push(t('controlLayers.controlLayer', { count: 1 }));
+      parts.push(t('controlLayers.controlLayer'));
     } else if (entityIdentifier.type === 'raster_layer') {
-      parts.push(t('controlLayers.rasterLayer', { count: 1 }));
+      parts.push(t('controlLayers.rasterLayer'));
     } else if (entityIdentifier.type === 'ip_adapter') {
-      parts.push(t('common.ipAdapter', { count: 1 }));
+      parts.push(t('common.ipAdapter'));
     } else if (entityIdentifier.type === 'regional_guidance') {
-      parts.push(t('controlLayers.regionalGuidance', { count: 1 }));
+      parts.push(t('controlLayers.regionalGuidance'));
     } else {
       assert(false, 'Unexpected entity type');
     }

invokeai/frontend/web/src/features/controlLayers/hooks/useEntityTypeString.ts

@@ -8,15 +8,15 @@ export const useEntityTypeString = (type: CanvasEntityIdentifier['type']): strin
   const typeString = useMemo(() => {
     switch (type) {
       case 'control_layer':
-        return t('controlLayers.controlLayer', { count: 0 });
+        return t('controlLayers.controlLayer');
       case 'raster_layer':
-        return t('controlLayers.rasterLayer', { count: 0 });
+        return t('controlLayers.rasterLayer');
       case 'inpaint_mask':
-        return t('controlLayers.inpaintMask', { count: 0 });
+        return t('controlLayers.inpaintMask');
       case 'regional_guidance':
-        return t('controlLayers.regionalGuidance', { count: 0 });
+        return t('controlLayers.regionalGuidance');
       case 'ip_adapter':
-        return t('controlLayers.ipAdapter', { count: 0 });
+        return t('controlLayers.ipAdapter');
       default:
         return '';
     }

invokeai/frontend/web/src/features/controlLayers/konva/CanvasCompositorModule.ts

@@ -147,6 +147,19 @@ export class CanvasCompositorModule extends CanvasModuleABC {
     return stableHash(data);
   };
 
+  rasterizeAndUploadCompositeRasterLayer = async (rect: Rect, saveToGallery: boolean) => {
+    this.log.trace({ rect }, 'Rasterizing composite raster layer');
+
+    const canvas = this.getCompositeRasterLayerCanvas(rect);
+    const blob = await canvasToBlob(canvas);
+
+    if (this.manager._isDebugging) {
+      previewBlob(blob, 'Composite raster layer canvas');
+    }
+
+    return uploadImage(blob, 'composite-raster-layer.png', 'general', !saveToGallery);
+  };
+
   getCompositeRasterLayerImageDTO = async (rect: Rect): Promise<ImageDTO> => {
     let imageDTO: ImageDTO | null = null;
 
@@ -161,19 +174,23 @@ export class CanvasCompositorModule extends CanvasModuleABC {
       }
     }
 
-    this.log.trace({ rect }, 'Rasterizing composite raster layer');
-
-    const canvas = this.getCompositeRasterLayerCanvas(rect);
-    const blob = await canvasToBlob(canvas);
-    if (this.manager._isDebugging) {
-      previewBlob(blob, 'Composite raster layer canvas');
-    }
-
-    imageDTO = await uploadImage(blob, 'composite-raster-layer.png', 'general', true);
+    imageDTO = await this.rasterizeAndUploadCompositeRasterLayer(rect, false);
     this.manager.cache.imageNameCache.set(hash, imageDTO.image_name);
     return imageDTO;
   };
 
+  rasterizeAndUploadCompositeInpaintMask = async (rect: Rect, saveToGallery: boolean) => {
+    this.log.trace({ rect }, 'Rasterizing composite inpaint mask');
+
+    const canvas = this.getCompositeInpaintMaskCanvas(rect);
+    const blob = await canvasToBlob(canvas);
+    if (this.manager._isDebugging) {
+      previewBlob(blob, 'Composite inpaint mask canvas');
+    }
+
+    return uploadImage(blob, 'composite-inpaint-mask.png', 'general', !saveToGallery);
+  };
+
   getCompositeInpaintMaskImageDTO = async (rect: Rect): Promise<ImageDTO> => {
     let imageDTO: ImageDTO | null = null;
 
@@ -188,15 +205,7 @@ export class CanvasCompositorModule extends CanvasModuleABC {
       }
     }
 
-    this.log.trace({ rect }, 'Rasterizing composite inpaint mask');
-
-    const canvas = this.getCompositeInpaintMaskCanvas(rect);
-    const blob = await canvasToBlob(canvas);
-    if (this.manager._isDebugging) {
-      previewBlob(blob, 'Composite inpaint mask canvas');
-    }
-
-    imageDTO = await uploadImage(blob, 'composite-inpaint-mask.png', 'general', true);
+    imageDTO = await this.rasterizeAndUploadCompositeInpaintMask(rect, false);
     this.manager.cache.imageNameCache.set(hash, imageDTO.image_name);
     return imageDTO;
   };

invokeai/frontend/web/src/features/controlLayers/konva/CanvasStageModule.ts

@@ -2,7 +2,7 @@ import type { CanvasManager } from 'features/controlLayers/konva/CanvasManager';
 import { CanvasModuleABC } from 'features/controlLayers/konva/CanvasModuleABC';
 import { CANVAS_SCALE_BY } from 'features/controlLayers/konva/constants';
 import { getPrefixedId, getRectUnion } from 'features/controlLayers/konva/util';
-import type { Coordinate, Dimensions, Rect } from 'features/controlLayers/store/types';
+import type { CanvasEntityIdentifier, Coordinate, Dimensions, Rect } from 'features/controlLayers/store/types';
 import type Konva from 'konva';
 import type { KonvaEventObject } from 'konva/lib/Node';
 import { clamp } from 'lodash-es';
@@ -76,35 +76,36 @@ export class CanvasStageModule extends CanvasModuleABC {
     });
   };
 
-  getVisibleRect = (): Rect => {
+  getVisibleRect = (type?: Exclude<CanvasEntityIdentifier['type'], 'ip_adapter'>): Rect => {
     const rects = [];
 
     for (const adapter of this.manager.adapters.getAll()) {
-      if (adapter.state.isEnabled) {
-        rects.push(adapter.transformer.getRelativeRect());
+      if (!adapter.state.isEnabled) {
+        continue;
       }
+      if (type && adapter.state.type !== type) {
+        continue;
+      }
+      rects.push(adapter.transformer.getRelativeRect());
     }
 
-    const rectUnion = getRectUnion(...rects);
-
-    if (rectUnion.width === 0 || rectUnion.height === 0) {
-      // fall back to the bbox if there is no content
-      return this.manager.stateApi.getBbox().rect;
-    } else {
-      return rectUnion;
-    }
+    return getRectUnion(...rects);
   };
 
   fitBboxToStage = () => {
-    this.log.trace('Fitting bbox to stage');
-    const bbox = this.manager.stateApi.getBbox();
-    this.fitRect(bbox.rect);
+    const { rect } = this.manager.stateApi.getBbox();
+    this.log.trace({ rect }, 'Fitting bbox to stage');
+    this.fitRect(rect);
   };
 
   fitLayersToStage() {
-    this.log.trace('Fitting layers to stage');
     const rect = this.getVisibleRect();
-    this.fitRect(rect);
+    if (rect.width === 0 || rect.height === 0) {
+      this.fitBboxToStage();
+    } else {
+      this.log.trace({ rect }, 'Fitting layers to stage');
+      this.fitRect(rect);
+    }
   }
 
   fitRect = (rect: Rect) => {

invokeai/frontend/web/src/features/controlLayers/konva/CanvasToolModule.ts

@@ -250,12 +250,10 @@ export class CanvasToolModule extends CanvasModuleABC {
     this.konva.colorPicker.group.visible(tool === 'colorPicker');
   };
 
-  render = () => {
+  syncCursorStyle = () => {
     const stage = this.manager.stage;
     const renderedEntityCount = this.manager.stateApi.getRenderedEntityCount();
-    const toolState = this.manager.stateApi.getToolState();
     const selectedEntity = this.manager.stateApi.getSelectedEntity();
-    const cursorPos = this.manager.stateApi.$lastCursorPos.get();
     const isMouseDown = this.manager.stateApi.$isMouseDown.get();
     const tool = this.manager.stateApi.$tool.get();
 
@@ -294,6 +292,158 @@ export class CanvasToolModule extends CanvasModuleABC {
       // Non-drawable layers don't have tools
       stage.container.style.cursor = 'not-allowed';
     }
+  };
+
+  renderBrushTool = (cursorPos: Coordinate) => {
+    const toolState = this.manager.stateApi.getToolState();
+    const brushPreviewFill = this.manager.stateApi.getBrushPreviewFill();
+    const alignedCursorPos = alignCoordForTool(cursorPos, toolState.brush.width);
+    const onePixel = this.manager.stage.getScaledPixels(1);
+    const twoPixels = this.manager.stage.getScaledPixels(2);
+    const radius = toolState.brush.width / 2;
+
+    // The circle is scaled
+    this.konva.brush.fillCircle.setAttrs({
+      x: alignedCursorPos.x,
+      y: alignedCursorPos.y,
+      radius,
+      fill: rgbaColorToString(brushPreviewFill),
+    });
+
+    // But the borders are in screen-pixels
+    this.konva.brush.innerBorder.setAttrs({
+      x: cursorPos.x,
+      y: cursorPos.y,
+      innerRadius: radius,
+      outerRadius: radius + onePixel,
+    });
+    this.konva.brush.outerBorder.setAttrs({
+      x: cursorPos.x,
+      y: cursorPos.y,
+      innerRadius: radius + onePixel,
+      outerRadius: radius + twoPixels,
+    });
+  };
+
+  renderEraserTool = (cursorPos: Coordinate) => {
+    const toolState = this.manager.stateApi.getToolState();
+    const alignedCursorPos = alignCoordForTool(cursorPos, toolState.eraser.width);
+    const onePixel = this.manager.stage.getScaledPixels(1);
+    const twoPixels = this.manager.stage.getScaledPixels(2);
+    const radius = toolState.eraser.width / 2;
+
+    // The circle is scaled
+    this.konva.eraser.fillCircle.setAttrs({
+      x: alignedCursorPos.x,
+      y: alignedCursorPos.y,
+      radius,
+      fill: 'white',
+    });
+
+    // But the borders are in screen-pixels
+    this.konva.eraser.innerBorder.setAttrs({
+      x: cursorPos.x,
+      y: cursorPos.y,
+      innerRadius: radius,
+      outerRadius: radius + onePixel,
+    });
+    this.konva.eraser.outerBorder.setAttrs({
+      x: cursorPos.x,
+      y: cursorPos.y,
+      innerRadius: radius + onePixel,
+      outerRadius: radius + twoPixels,
+    });
+  };
+
+  renderColorPicker = (cursorPos: Coordinate) => {
+    const toolState = this.manager.stateApi.getToolState();
+    const colorUnderCursor = this.manager.stateApi.$colorUnderCursor.get();
+    const colorPickerInnerRadius = this.manager.stage.getScaledPixels(CanvasToolModule.COLOR_PICKER_RADIUS);
+    const colorPickerOuterRadius = this.manager.stage.getScaledPixels(
+      CanvasToolModule.COLOR_PICKER_RADIUS + CanvasToolModule.COLOR_PICKER_THICKNESS
+    );
+    const onePixel = this.manager.stage.getScaledPixels(1);
+    const twoPixels = this.manager.stage.getScaledPixels(2);
+
+    this.konva.colorPicker.newColor.setAttrs({
+      x: cursorPos.x,
+      y: cursorPos.y,
+      fill: rgbColorToString(colorUnderCursor),
+      innerRadius: colorPickerInnerRadius,
+      outerRadius: colorPickerOuterRadius,
+    });
+    this.konva.colorPicker.oldColor.setAttrs({
+      x: cursorPos.x,
+      y: cursorPos.y,
+      fill: rgbColorToString(toolState.fill),
+      innerRadius: colorPickerInnerRadius,
+      outerRadius: colorPickerOuterRadius,
+    });
+    this.konva.colorPicker.innerBorder.setAttrs({
+      x: cursorPos.x,
+      y: cursorPos.y,
+      innerRadius: colorPickerOuterRadius,
+      outerRadius: colorPickerOuterRadius + onePixel,
+    });
+    this.konva.colorPicker.outerBorder.setAttrs({
+      x: cursorPos.x,
+      y: cursorPos.y,
+      innerRadius: colorPickerOuterRadius + onePixel,
+      outerRadius: colorPickerOuterRadius + twoPixels,
+    });
+
+    const size = this.manager.stage.getScaledPixels(CanvasToolModule.COLOR_PICKER_CROSSHAIR_SIZE);
+    const space = this.manager.stage.getScaledPixels(CanvasToolModule.COLOR_PICKER_CROSSHAIR_SPACE);
+    const innerThickness = this.manager.stage.getScaledPixels(CanvasToolModule.COLOR_PICKER_CROSSHAIR_INNER_THICKNESS);
+    const outerThickness = this.manager.stage.getScaledPixels(CanvasToolModule.COLOR_PICKER_CROSSHAIR_OUTER_THICKNESS);
+    this.konva.colorPicker.crosshairNorthOuter.setAttrs({
+      strokeWidth: outerThickness,
+      points: [cursorPos.x, cursorPos.y - size, cursorPos.x, cursorPos.y - space],
+    });
+    this.konva.colorPicker.crosshairNorthInner.setAttrs({
+      strokeWidth: innerThickness,
+      points: [cursorPos.x, cursorPos.y - size, cursorPos.x, cursorPos.y - space],
+    });
+    this.konva.colorPicker.crosshairEastOuter.setAttrs({
+      strokeWidth: outerThickness,
+      points: [cursorPos.x + space, cursorPos.y, cursorPos.x + size, cursorPos.y],
+    });
+    this.konva.colorPicker.crosshairEastInner.setAttrs({
+      strokeWidth: innerThickness,
+      points: [cursorPos.x + space, cursorPos.y, cursorPos.x + size, cursorPos.y],
+    });
+    this.konva.colorPicker.crosshairSouthOuter.setAttrs({
+      strokeWidth: outerThickness,
+      points: [cursorPos.x, cursorPos.y + space, cursorPos.x, cursorPos.y + size],
+    });
+    this.konva.colorPicker.crosshairSouthInner.setAttrs({
+      strokeWidth: innerThickness,
+      points: [cursorPos.x, cursorPos.y + space, cursorPos.x, cursorPos.y + size],
+    });
+    this.konva.colorPicker.crosshairWestOuter.setAttrs({
+      strokeWidth: outerThickness,
+      points: [cursorPos.x - space, cursorPos.y, cursorPos.x - size, cursorPos.y],
+    });
+    this.konva.colorPicker.crosshairWestInner.setAttrs({
+      strokeWidth: innerThickness,
+      points: [cursorPos.x - space, cursorPos.y, cursorPos.x - size, cursorPos.y],
+    });
+  };
+
+  render = () => {
+    const stage = this.manager.stage;
+    const renderedEntityCount = this.manager.stateApi.getRenderedEntityCount();
+    const selectedEntity = this.manager.stateApi.getSelectedEntity();
+    const cursorPos = this.manager.stateApi.$lastCursorPos.get();
+    const tool = this.manager.stateApi.$tool.get();
+
+    const isDrawable =
+      !!selectedEntity &&
+      selectedEntity.state.isEnabled &&
+      !selectedEntity.state.isLocked &&
+      isDrawableEntity(selectedEntity.state);
+
+    this.syncCursorStyle();
 
     stage.setIsDraggable(tool === 'view');
 
@@ -305,136 +455,11 @@ export class CanvasToolModule extends CanvasModuleABC {
 
       // No need to render the brush preview if the cursor position or color is missing
       if (cursorPos && tool === 'brush') {
-        const brushPreviewFill = this.manager.stateApi.getBrushPreviewFill();
-        const alignedCursorPos = alignCoordForTool(cursorPos, toolState.brush.width);
-        const onePixel = this.manager.stage.getScaledPixels(1);
-        const twoPixels = this.manager.stage.getScaledPixels(2);
-        const radius = toolState.brush.width / 2;
-
-        // The circle is scaled
-        this.konva.brush.fillCircle.setAttrs({
-          x: alignedCursorPos.x,
-          y: alignedCursorPos.y,
-          radius,
-          fill: rgbaColorToString(brushPreviewFill),
-        });
-
-        // But the borders are in screen-pixels
-        this.konva.brush.innerBorder.setAttrs({
-          x: cursorPos.x,
-          y: cursorPos.y,
-          innerRadius: radius,
-          outerRadius: radius + onePixel,
-        });
-        this.konva.brush.outerBorder.setAttrs({
-          x: cursorPos.x,
-          y: cursorPos.y,
-          innerRadius: radius + onePixel,
-          outerRadius: radius + twoPixels,
-        });
+        this.renderBrushTool(cursorPos);
       } else if (cursorPos && tool === 'eraser') {
-        const alignedCursorPos = alignCoordForTool(cursorPos, toolState.eraser.width);
-        const onePixel = this.manager.stage.getScaledPixels(1);
-        const twoPixels = this.manager.stage.getScaledPixels(2);
-        const radius = toolState.eraser.width / 2;
-
-        // The circle is scaled
-        this.konva.eraser.fillCircle.setAttrs({
-          x: alignedCursorPos.x,
-          y: alignedCursorPos.y,
-          radius,
-          fill: 'white',
-        });
-
-        // But the borders are in screen-pixels
-        this.konva.eraser.innerBorder.setAttrs({
-          x: cursorPos.x,
-          y: cursorPos.y,
-          innerRadius: radius,
-          outerRadius: radius + onePixel,
-        });
-        this.konva.eraser.outerBorder.setAttrs({
-          x: cursorPos.x,
-          y: cursorPos.y,
-          innerRadius: radius + onePixel,
-          outerRadius: radius + twoPixels,
-        });
+        this.renderEraserTool(cursorPos);
       } else if (cursorPos && tool === 'colorPicker') {
-        const colorUnderCursor = this.manager.stateApi.$colorUnderCursor.get();
-        const colorPickerInnerRadius = this.manager.stage.getScaledPixels(CanvasToolModule.COLOR_PICKER_RADIUS);
-        const colorPickerOuterRadius = this.manager.stage.getScaledPixels(
-          CanvasToolModule.COLOR_PICKER_RADIUS + CanvasToolModule.COLOR_PICKER_THICKNESS
-        );
-        const onePixel = this.manager.stage.getScaledPixels(1);
-        const twoPixels = this.manager.stage.getScaledPixels(2);
-
-        this.konva.colorPicker.newColor.setAttrs({
-          x: cursorPos.x,
-          y: cursorPos.y,
-          fill: rgbColorToString(colorUnderCursor),
-          innerRadius: colorPickerInnerRadius,
-          outerRadius: colorPickerOuterRadius,
-        });
-        this.konva.colorPicker.oldColor.setAttrs({
-          x: cursorPos.x,
-          y: cursorPos.y,
-          fill: rgbColorToString(toolState.fill),
-          innerRadius: colorPickerInnerRadius,
-          outerRadius: colorPickerOuterRadius,
-        });
-        this.konva.colorPicker.innerBorder.setAttrs({
-          x: cursorPos.x,
-          y: cursorPos.y,
-          innerRadius: colorPickerOuterRadius,
-          outerRadius: colorPickerOuterRadius + onePixel,
-        });
-        this.konva.colorPicker.outerBorder.setAttrs({
-          x: cursorPos.x,
-          y: cursorPos.y,
-          innerRadius: colorPickerOuterRadius + onePixel,
-          outerRadius: colorPickerOuterRadius + twoPixels,
-        });
-
-        const size = this.manager.stage.getScaledPixels(CanvasToolModule.COLOR_PICKER_CROSSHAIR_SIZE);
-        const space = this.manager.stage.getScaledPixels(CanvasToolModule.COLOR_PICKER_CROSSHAIR_SPACE);
-        const innerThickness = this.manager.stage.getScaledPixels(
-          CanvasToolModule.COLOR_PICKER_CROSSHAIR_INNER_THICKNESS
-        );
-        const outerThickness = this.manager.stage.getScaledPixels(
-          CanvasToolModule.COLOR_PICKER_CROSSHAIR_OUTER_THICKNESS
-        );
-        this.konva.colorPicker.crosshairNorthOuter.setAttrs({
-          strokeWidth: outerThickness,
-          points: [cursorPos.x, cursorPos.y - size, cursorPos.x, cursorPos.y - space],
-        });
-        this.konva.colorPicker.crosshairNorthInner.setAttrs({
-          strokeWidth: innerThickness,
-          points: [cursorPos.x, cursorPos.y - size, cursorPos.x, cursorPos.y - space],
-        });
-        this.konva.colorPicker.crosshairEastOuter.setAttrs({
-          strokeWidth: outerThickness,
-          points: [cursorPos.x + space, cursorPos.y, cursorPos.x + size, cursorPos.y],
-        });
-        this.konva.colorPicker.crosshairEastInner.setAttrs({
-          strokeWidth: innerThickness,
-          points: [cursorPos.x + space, cursorPos.y, cursorPos.x + size, cursorPos.y],
-        });
-        this.konva.colorPicker.crosshairSouthOuter.setAttrs({
-          strokeWidth: outerThickness,
-          points: [cursorPos.x, cursorPos.y + space, cursorPos.x, cursorPos.y + size],
-        });
-        this.konva.colorPicker.crosshairSouthInner.setAttrs({
-          strokeWidth: innerThickness,
-          points: [cursorPos.x, cursorPos.y + space, cursorPos.x, cursorPos.y + size],
-        });
-        this.konva.colorPicker.crosshairWestOuter.setAttrs({
-          strokeWidth: outerThickness,
-          points: [cursorPos.x - space, cursorPos.y, cursorPos.x - size, cursorPos.y],
-        });
-        this.konva.colorPicker.crosshairWestInner.setAttrs({
-          strokeWidth: innerThickness,
-          points: [cursorPos.x - space, cursorPos.y, cursorPos.x - size, cursorPos.y],
-        });
+        this.renderColorPicker(cursorPos);
       }
 
       this.setToolVisibility(tool, isDrawable);
@@ -864,6 +889,10 @@ export class CanvasToolModule extends CanvasModuleABC {
       this.manager.stateApi.$spaceKey.set(true);
       this.manager.stateApi.$lastCursorPos.set(null);
       this.manager.stateApi.$lastMouseDownPos.set(null);
+    } else if (e.key === 'Alt') {
+      // Select the color picker on alt key down
+      this.manager.stateApi.$toolBuffer.set(this.manager.stateApi.$tool.get());
+      this.manager.stateApi.$tool.set('colorPicker');
     }
   };
 
@@ -880,6 +909,11 @@ export class CanvasToolModule extends CanvasModuleABC {
       this.manager.stateApi.$tool.set(toolBuffer ?? 'move');
       this.manager.stateApi.$toolBuffer.set(null);
       this.manager.stateApi.$spaceKey.set(false);
+    } else if (e.key === 'Alt') {
+      // Revert the tool to the previous tool on alt key up
+      const toolBuffer = this.manager.stateApi.$toolBuffer.get();
+      this.manager.stateApi.$tool.set(toolBuffer ?? 'move');
+      this.manager.stateApi.$toolBuffer.set(null);
     }
   };
 

invokeai/frontend/web/src/features/controlLayers/konva/util.test.ts

@@ -0,0 +1,47 @@
+import { getPrefixedId, getRectUnion } from 'features/controlLayers/konva/util';
+import { describe, expect, it } from 'vitest';
+
+describe('util', () => {
+  describe('getPrefixedId', () => {
+    it('should return a prefixed id', () => {
+      expect(getPrefixedId('foo').split(':')[0]).toBe('foo');
+    });
+  });
+
+  describe('getRectUnion', () => {
+    it('should return the union of rects (2 rects)', () => {
+      const rect1 = { x: 0, y: 0, width: 10, height: 10 };
+      const rect2 = { x: 5, y: 5, width: 10, height: 10 };
+      const union = getRectUnion(rect1, rect2);
+      expect(union).toEqual({ x: 0, y: 0, width: 15, height: 15 });
+    });
+    it('should return the union of rects (3 rects)', () => {
+      const rect1 = { x: 0, y: 0, width: 10, height: 10 };
+      const rect2 = { x: 5, y: 5, width: 10, height: 10 };
+      const rect3 = { x: 10, y: 10, width: 10, height: 10 };
+      const union = getRectUnion(rect1, rect2, rect3);
+      expect(union).toEqual({ x: 0, y: 0, width: 20, height: 20 });
+    });
+    it('should return the union of rects (2 rects none from zero)', () => {
+      const rect1 = { x: 5, y: 5, width: 10, height: 10 };
+      const rect2 = { x: 10, y: 10, width: 10, height: 10 };
+      const union = getRectUnion(rect1, rect2);
+      expect(union).toEqual({ x: 5, y: 5, width: 15, height: 15 });
+    });
+    it('should return the union of rects (2 rects with negative x/y)', () => {
+      const rect1 = { x: -5, y: -5, width: 10, height: 10 };
+      const rect2 = { x: 0, y: 0, width: 10, height: 10 };
+      const union = getRectUnion(rect1, rect2);
+      expect(union).toEqual({ x: -5, y: -5, width: 15, height: 15 });
+    });
+    it('should return the union of the first rect if only one rect is provided', () => {
+      const rect = { x: 0, y: 0, width: 10, height: 10 };
+      const union = getRectUnion(rect);
+      expect(union).toEqual(rect);
+    });
+    it('should fall back on an empty rect if no rects are provided', () => {
+      const union = getRectUnion();
+      expect(union).toEqual({ x: 0, y: 0, width: 0, height: 0 });
+    });
+  });
+});

invokeai/frontend/web/src/features/controlLayers/konva/util.ts

@@ -302,10 +302,13 @@ export const konvaNodeToCanvas = (node: Konva.Node, bbox?: Rect): HTMLCanvasElem
  * @returns A Promise that resolves with Blob of the node cropped to the bounding box
  */
 export const canvasToBlob = (canvas: HTMLCanvasElement): Promise<Blob> => {
-  return new Promise((resolve) => {
+  return new Promise((resolve, reject) => {
     canvas.toBlob((blob) => {
-      assert(blob, 'blob is null');
-      resolve(blob);
+      if (!blob) {
+        reject('Failed to convert canvas to blob');
+      } else {
+        resolve(blob);
+      }
     });
   });
 };
@@ -418,19 +421,25 @@ export function snapToNearest(value: number, candidateValues: number[], threshol
 }
 
 /**
- * Gets the union of two rects
- * @param rect1 The first rect
- * @param rect2 The second rect
+ * Gets the union of any number of rects.
+ * @params rects The rects to union
  * @returns The union of the two rects
  */
 export const getRectUnion = (...rects: Rect[]): Rect => {
+  const firstRect = rects.shift();
+
+  if (!firstRect) {
+    return getEmptyRect();
+  }
+
   const rect = rects.reduce<Rect>((acc, r) => {
     const x = Math.min(acc.x, r.x);
     const y = Math.min(acc.y, r.y);
     const width = Math.max(acc.x + acc.width, r.x + r.width) - x;
     const height = Math.max(acc.y + acc.height, r.y + r.height) - y;
     return { x, y, width, height };
-  }, getEmptyRect());
+  }, firstRect);
+
   return rect;
 };
 

invokeai/frontend/web/src/features/controlLayers/store/canvasSessionSlice.ts

@@ -1,17 +1,17 @@
 import { createAction, createSelector, createSlice, type PayloadAction } from '@reduxjs/toolkit';
 import type { PersistConfig, RootState } from 'app/store/store';
 import { canvasSlice } from 'features/controlLayers/store/canvasSlice';
-import type { SessionMode, StagingAreaImage } from 'features/controlLayers/store/types';
+import type { StagingAreaImage } from 'features/controlLayers/store/types';
 
 export type CanvasSessionState = {
-  mode: SessionMode;
+  sendToCanvas: boolean;
   isStaging: boolean;
   stagedImages: StagingAreaImage[];
   selectedStagedImageIndex: number;
 };
 
 const initialState: CanvasSessionState = {
-  mode: 'generate',
+  sendToCanvas: false,
   isStaging: false,
   stagedImages: [],
   selectedStagedImageIndex: 0,
@@ -27,6 +27,7 @@ export const canvasSessionSlice = createSlice({
     },
     sessionImageStaged: (state, action: PayloadAction<{ stagingAreaImage: StagingAreaImage }>) => {
       const { stagingAreaImage } = action.payload;
+      state.isStaging = true;
       state.stagedImages.push(stagingAreaImage);
       state.selectedStagedImageIndex = state.stagedImages.length - 1;
     },
@@ -50,9 +51,8 @@ export const canvasSessionSlice = createSlice({
       state.stagedImages = [];
       state.selectedStagedImageIndex = 0;
     },
-    sessionModeChanged: (state, action: PayloadAction<{ mode: SessionMode }>) => {
-      const { mode } = action.payload;
-      state.mode = mode;
+    sessionSendToCanvasChanged: (state, action: PayloadAction<boolean>) => {
+      state.sendToCanvas = action.payload;
     },
   },
 });
@@ -64,7 +64,7 @@ export const {
   sessionStagingAreaReset,
   sessionNextStagedImageSelected,
   sessionPrevStagedImageSelected,
-  sessionModeChanged,
+  sessionSendToCanvasChanged,
 } = canvasSessionSlice.actions;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
@@ -85,3 +85,7 @@ export const sessionStagingAreaImageAccepted = createAction<{ index: number }>(
 export const selectCanvasSessionSlice = (s: RootState) => s.canvasSession;
 
 export const selectIsStaging = createSelector(selectCanvasSessionSlice, (canvasSession) => canvasSession.isStaging);
+export const selectIsComposing = createSelector(
+  selectCanvasSessionSlice,
+  (canvasSession) => canvasSession.sendToCanvas
+);

invokeai/frontend/web/src/features/controlLayers/store/canvasSettingsSlice.ts

@@ -35,10 +35,14 @@ export const canvasSettingsSlice = createSlice({
     settingsAutoSaveToggled: (state) => {
       state.autoSave = !state.autoSave;
     },
+    settingsShowHUDToggled: (state) => {
+      state.showHUD = !state.showHUD;
+    },
   },
 });
 
-export const { clipToBboxChanged, settingsAutoSaveToggled, settingsDynamicGridToggled } = canvasSettingsSlice.actions;
+export const { clipToBboxChanged, settingsAutoSaveToggled, settingsDynamicGridToggled, settingsShowHUDToggled } =
+  canvasSettingsSlice.actions;
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
 const migrate = (state: any): any => {

invokeai/frontend/web/src/features/controlLayers/store/canvasSlice.ts

@@ -123,9 +123,14 @@ export const canvasSlice = createSlice({
     rasterLayerAdded: {
       reducer: (
         state,
-        action: PayloadAction<{ id: string; overrides?: Partial<CanvasRasterLayerState>; isSelected?: boolean }>
+        action: PayloadAction<{
+          id: string;
+          overrides?: Partial<CanvasRasterLayerState>;
+          isSelected?: boolean;
+          deleteOthers?: boolean;
+        }>
       ) => {
-        const { id, overrides, isSelected } = action.payload;
+        const { id, overrides, isSelected, deleteOthers } = action.payload;
         const entity: CanvasRasterLayerState = {
           id,
           name: null,
@@ -137,12 +142,25 @@ export const canvasSlice = createSlice({
           position: { x: 0, y: 0 },
         };
         merge(entity, overrides);
-        state.rasterLayers.entities.push(entity);
+
+        if (deleteOthers) {
+          state.rasterLayers.entities = [entity];
+        } else {
+          state.rasterLayers.entities.push(entity);
+        }
+
         if (isSelected) {
           state.selectedEntityIdentifier = getEntityIdentifier(entity);
         }
       },
-      prepare: (payload: { overrides?: Partial<CanvasRasterLayerState>; isSelected?: boolean }) => ({
+      prepare: (payload: {
+        overrides?: Partial<CanvasRasterLayerState>;
+        isSelected?: boolean;
+        /**
+         * asdf
+         */
+        deleteOthers?: boolean;
+      }) => ({
         payload: { ...payload, id: getPrefixedId('raster_layer') },
       }),
     },
@@ -603,9 +621,14 @@ export const canvasSlice = createSlice({
     inpaintMaskAdded: {
       reducer: (
         state,
-        action: PayloadAction<{ id: string; overrides?: Partial<CanvasInpaintMaskState>; isSelected?: boolean }>
+        action: PayloadAction<{
+          id: string;
+          overrides?: Partial<CanvasInpaintMaskState>;
+          isSelected?: boolean;
+          deleteOthers?: boolean;
+        }>
       ) => {
-        const { id, overrides, isSelected } = action.payload;
+        const { id, overrides, isSelected, deleteOthers } = action.payload;
         const entity: CanvasInpaintMaskState = {
           id,
           name: null,
@@ -621,12 +644,22 @@ export const canvasSlice = createSlice({
           },
         };
         merge(entity, overrides);
-        state.inpaintMasks.entities.push(entity);
+
+        if (deleteOthers) {
+          state.inpaintMasks.entities = [entity];
+        } else {
+          state.inpaintMasks.entities.push(entity);
+        }
+
         if (isSelected) {
           state.selectedEntityIdentifier = getEntityIdentifier(entity);
         }
       },
-      prepare: (payload?: { overrides?: Partial<CanvasInpaintMaskState>; isSelected?: boolean }) => ({
+      prepare: (payload?: {
+        overrides?: Partial<CanvasInpaintMaskState>;
+        isSelected?: boolean;
+        deleteOthers?: boolean;
+      }) => ({
         payload: { ...payload, id: getPrefixedId('inpaint_mask') },
       }),
     },

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

@@ -685,8 +685,6 @@ export type StagingAreaImage = {
   offsetY: number;
 };
 
-export type SessionMode = 'generate' | 'compose';
-
 export type CanvasState = {
   _version: 3;
   selectedEntityIdentifier: CanvasEntityIdentifier | null;

invokeai/frontend/web/src/features/gallery/components/ImageViewer/ViewerToggleMenu.tsx

@@ -1,55 +1,61 @@
-import { ButtonGroup, Flex, IconButton, Text, Tooltip } from '@invoke-ai/ui-library';
+import { Flex, Text } from '@invoke-ai/ui-library';
+import { IconSwitch } from 'common/components/IconSwitch';
 import { useImageViewer } from 'features/gallery/components/ImageViewer/useImageViewer';
+import { memo, useCallback } from 'react';
 import { useHotkeys } from 'react-hotkeys-hook';
 import { useTranslation } from 'react-i18next';
 import { PiEyeBold, PiPencilBold } from 'react-icons/pi';
 
-export const ViewerToggleMenu = () => {
+const TooltipEdit = memo(() => {
   const { t } = useTranslation();
+
+  return (
+    <Flex flexDir="column">
+      <Text fontWeight="semibold">{t('common.edit')}</Text>
+      <Text fontWeight="normal">{t('common.editDesc')}</Text>
+    </Flex>
+  );
+});
+TooltipEdit.displayName = 'TooltipEdit';
+
+const TooltipView = memo(() => {
+  const { t } = useTranslation();
+
+  return (
+    <Flex flexDir="column">
+      <Text fontWeight="semibold">{t('common.view')}</Text>
+      <Text fontWeight="normal">{t('common.viewDesc')}</Text>
+    </Flex>
+  );
+});
+TooltipView.displayName = 'TooltipView';
+
+export const ViewerToggle = memo(() => {
   const imageViewer = useImageViewer();
   useHotkeys('z', imageViewer.onToggle, [imageViewer]);
   useHotkeys('esc', imageViewer.onClose, [imageViewer]);
+  const onChange = useCallback(
+    (isChecked: boolean) => {
+      if (isChecked) {
+        imageViewer.onClose();
+      } else {
+        imageViewer.onOpen();
+      }
+    },
+    [imageViewer]
+  );
 
   return (
-    <Flex gap={4} alignItems="center" justifyContent="center">
-      <ButtonGroup size="md">
-        <Tooltip
-          hasArrow
-          label={
-            <Flex flexDir="column">
-              <Text fontWeight="semibold">{t('common.viewing')}</Text>
-              <Text fontWeight="normal">{t('common.viewingDesc')}</Text>
-            </Flex>
-          }
-        >
-          <IconButton
-            icon={<PiEyeBold />}
-            onClick={imageViewer.onOpen}
-            variant={imageViewer.isOpen ? 'solid' : 'outline'}
-            colorScheme={imageViewer.isOpen ? 'invokeBlue' : 'base'}
-            aria-label={t('common.viewing')}
-            w={12}
-          />
-        </Tooltip>
-        <Tooltip
-          hasArrow
-          label={
-            <Flex flexDir="column">
-              <Text fontWeight="semibold">{t('common.editing')}</Text>
-              <Text fontWeight="normal">{t('common.editingDesc')}</Text>
-            </Flex>
-          }
-        >
-          <IconButton
-            icon={<PiPencilBold />}
-            onClick={imageViewer.onClose}
-            variant={!imageViewer.isOpen ? 'solid' : 'outline'}
-            colorScheme={!imageViewer.isOpen ? 'invokeBlue' : 'base'}
-            aria-label={t('common.editing')}
-            w={12}
-          />
-        </Tooltip>
-      </ButtonGroup>
-    </Flex>
+    <IconSwitch
+      isChecked={!imageViewer.isOpen}
+      onChange={onChange}
+      iconUnchecked={<PiEyeBold />}
+      tooltipUnchecked={<TooltipView />}
+      iconChecked={<PiPencilBold />}
+      tooltipChecked={<TooltipEdit />}
+      ariaLabel="Toggle viewer"
+    />
   );
-};
+});
+
+ViewerToggle.displayName = 'ViewerToggle';

invokeai/frontend/web/src/features/gallery/components/ImageViewer/ViewerToolbar.tsx

@@ -7,7 +7,7 @@ import { selectActiveTab } from 'features/ui/store/uiSelectors';
 import { memo } from 'react';
 
 import CurrentImageButtons from './CurrentImageButtons';
-import { ViewerToggleMenu } from './ViewerToggleMenu';
+import { ViewerToggle } from './ViewerToggleMenu';
 
 const selectShowToggle = createSelector(selectActiveTab, (tab) => {
   if (tab === 'upscaling' || tab === 'workflows') {
@@ -31,7 +31,7 @@ export const ViewerToolbar = memo(() => {
       </Flex>
       <Flex flex={1} justifyContent="center">
         <Flex gap={2} marginInlineStart="auto">
-          {showToggle && <ViewerToggleMenu />}
+          {showToggle && <ViewerToggle />}
         </Flex>
       </Flex>
     </Flex>

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

@@ -179,12 +179,12 @@ const ModelList = () => {
         {/* T5 Encoders List */}
         {isLoadingT5EncoderModels && <FetchingModelsLoader loadingMessage="Loading T5 Encoder Models..." />}
         {!isLoadingT5EncoderModels && filteredT5EncoderModels.length > 0 && (
-          <ModelListWrapper title="T5 Encoder" modelList={filteredT5EncoderModels} key="t5-encoder" />
+          <ModelListWrapper title={t('modelManager.t5Encoder')} modelList={filteredT5EncoderModels} key="t5-encoder" />
         )}
         {/* Clip Embed List */}
         {isLoadingClipEmbedModels && <FetchingModelsLoader loadingMessage="Loading Clip Embed Models..." />}
         {!isLoadingClipEmbedModels && filteredClipEmbedModels.length > 0 && (
-          <ModelListWrapper title="Clip Embed" modelList={filteredClipEmbedModels} key="clip-embed" />
+          <ModelListWrapper title={t('modelManager.clipEmbed')} modelList={filteredClipEmbedModels} key="clip-embed" />
         )}
         {/* Spandrel Image to Image List */}
         {isLoadingSpandrelImageToImageModels && (
@@ -192,7 +192,7 @@ const ModelList = () => {
         )}
         {!isLoadingSpandrelImageToImageModels && filteredSpandrelImageToImageModels.length > 0 && (
           <ModelListWrapper
-            title="Image-to-Image"
+            title={t('modelManager.spandrelImageToImage')}
             modelList={filteredSpandrelImageToImageModels}
             key="spandrel-image-to-image"
           />

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

@@ -19,11 +19,10 @@ export const ModelTypeFilter = memo(() => {
       controlnet: 'ControlNet',
       vae: 'VAE',
       t2i_adapter: t('common.t2iAdapter'),
-      t5_encoder: 'T5Encoder',
-      clip_embed: 'Clip Embed',
+      t5_encoder: t('modelManager.t5Encoder'),
+      clip_embed: t('modelManager.clipEmbed'),
       ip_adapter: t('common.ipAdapter'),
-      clip_vision: 'Clip Vision',
-      spandrel_image_to_image: 'Image-to-Image',
+      spandrel_image_to_image: t('modelManager.spandrelImageToImage'),
     }),
     [t]
   );

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

@@ -4,6 +4,7 @@ import { Flex } from '@invoke-ai/ui-library';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import { AddNodeCmdk } from 'features/nodes/components/flow/AddNodeCmdk/AddNodeCmdk';
 import TopPanel from 'features/nodes/components/flow/panels/TopPanel/TopPanel';
+import WorkflowEditorSettings from 'features/nodes/components/flow/panels/TopRightPanel/WorkflowEditorSettings';
 import { LoadWorkflowFromGraphModal } from 'features/workflowLibrary/components/LoadWorkflowFromGraphModal/LoadWorkflowFromGraphModal';
 import { SaveWorkflowAsDialog } from 'features/workflowLibrary/components/SaveWorkflowAsDialog/SaveWorkflowAsDialog';
 import { memo } from 'react';
@@ -39,6 +40,7 @@ const NodeEditor = () => {
           <LoadWorkflowFromGraphModal />
         </>
       )}
+      <WorkflowEditorSettings />
       {isLoading && <IAINoContentFallback label={t('nodes.loadingNodes')} icon={MdDeviceHub} />}
     </Flex>
   );

invokeai/frontend/web/src/features/nodes/components/flow/AddNodeCmdk/AddNodeCmdk.tsx

@@ -12,7 +12,7 @@ import {
   Text,
 } from '@invoke-ai/ui-library';
 import { useStore } from '@nanostores/react';
-import { useAppStore } from 'app/store/storeHooks';
+import { useAppSelector, useAppStore } from 'app/store/storeHooks';
 import { CommandEmpty, CommandItem, CommandList, CommandRoot } from 'cmdk';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
@@ -33,6 +33,7 @@ import { connectionToEdge } from 'features/nodes/store/util/reactFlowUtil';
 import { validateConnectionTypes } from 'features/nodes/store/util/validateConnectionTypes';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { toast } from 'features/toast/toast';
+import { selectActiveTab } from 'features/ui/store/uiSelectors';
 import { memoize } from 'lodash-es';
 import { computed } from 'nanostores';
 import type { ChangeEvent } from 'react';
@@ -162,13 +163,13 @@ const cmdkRootSx: SystemStyleObject = {
 export const AddNodeCmdk = memo(() => {
   const { t } = useTranslation();
   const addNodeCmdk = useAddNodeCmdk();
-  const addNodeCmdkIsOpen = useStore(addNodeCmdk.$boolean);
   const inputRef = useRef<HTMLInputElement>(null);
   const [searchTerm, setSearchTerm] = useState('');
   const addNode = useAddNode();
+  const tab = useAppSelector(selectActiveTab);
   const throttledSearchTerm = useThrottle(searchTerm, 100);
 
-  useHotkeys(['shift+a', 'space'], addNodeCmdk.setTrue, { preventDefault: true });
+  useHotkeys(['shift+a', 'space'], addNodeCmdk.setTrue, { enabled: tab === 'workflows', preventDefault: true }, [tab]);
 
   const onChange = useCallback((e: ChangeEvent<HTMLInputElement>) => {
     setSearchTerm(e.target.value);
@@ -190,7 +191,7 @@ export const AddNodeCmdk = memo(() => {
 
   return (
     <Modal
-      isOpen={addNodeCmdkIsOpen}
+      isOpen={addNodeCmdk.isTrue}
       onClose={onClose}
       useInert={false}
       initialFocusRef={inputRef}

invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/InputFieldRenderer.tsx

@@ -6,6 +6,8 @@ import {
   isBoardFieldInputTemplate,
   isBooleanFieldInputInstance,
   isBooleanFieldInputTemplate,
+  isCLIPEmbedModelFieldInputInstance,
+  isCLIPEmbedModelFieldInputTemplate,
   isColorFieldInputInstance,
   isColorFieldInputTemplate,
   isControlNetModelFieldInputInstance,
@@ -16,6 +18,8 @@ import {
   isFloatFieldInputTemplate,
   isFluxMainModelFieldInputInstance,
   isFluxMainModelFieldInputTemplate,
+  isFluxVAEModelFieldInputInstance,
+  isFluxVAEModelFieldInputTemplate,
   isImageFieldInputInstance,
   isImageFieldInputTemplate,
   isIntegerFieldInputInstance,
@@ -49,10 +53,12 @@ import { memo } from 'react';
 
 import BoardFieldInputComponent from './inputs/BoardFieldInputComponent';
 import BooleanFieldInputComponent from './inputs/BooleanFieldInputComponent';
+import CLIPEmbedModelFieldInputComponent from './inputs/CLIPEmbedModelFieldInputComponent';
 import ColorFieldInputComponent from './inputs/ColorFieldInputComponent';
 import ControlNetModelFieldInputComponent from './inputs/ControlNetModelFieldInputComponent';
 import EnumFieldInputComponent from './inputs/EnumFieldInputComponent';
 import FluxMainModelFieldInputComponent from './inputs/FluxMainModelFieldInputComponent';
+import FluxVAEModelFieldInputComponent from './inputs/FluxVAEModelFieldInputComponent';
 import ImageFieldInputComponent from './inputs/ImageFieldInputComponent';
 import IPAdapterModelFieldInputComponent from './inputs/IPAdapterModelFieldInputComponent';
 import LoRAModelFieldInputComponent from './inputs/LoRAModelFieldInputComponent';
@@ -122,6 +128,13 @@ const InputFieldRenderer = ({ nodeId, fieldName }: InputFieldProps) => {
   if (isT5EncoderModelFieldInputInstance(fieldInstance) && isT5EncoderModelFieldInputTemplate(fieldTemplate)) {
     return <T5EncoderModelFieldInputComponent nodeId={nodeId} field={fieldInstance} fieldTemplate={fieldTemplate} />;
   }
+  if (isCLIPEmbedModelFieldInputInstance(fieldInstance) && isCLIPEmbedModelFieldInputTemplate(fieldTemplate)) {
+    return <CLIPEmbedModelFieldInputComponent nodeId={nodeId} field={fieldInstance} fieldTemplate={fieldTemplate} />;
+  }
+
+  if (isFluxVAEModelFieldInputInstance(fieldInstance) && isFluxVAEModelFieldInputTemplate(fieldTemplate)) {
+    return <FluxVAEModelFieldInputComponent nodeId={nodeId} field={fieldInstance} fieldTemplate={fieldTemplate} />;
+  }
 
   if (isLoRAModelFieldInputInstance(fieldInstance) && isLoRAModelFieldInputTemplate(fieldTemplate)) {
     return <LoRAModelFieldInputComponent nodeId={nodeId} field={fieldInstance} fieldTemplate={fieldTemplate} />;

invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/CLIPEmbedModelFieldInputComponent.tsx

@@ -0,0 +1,60 @@
+import { Combobox, Flex, FormControl, Tooltip } from '@invoke-ai/ui-library';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
+import { fieldCLIPEmbedValueChanged } from 'features/nodes/store/nodesSlice';
+import type { CLIPEmbedModelFieldInputInstance, CLIPEmbedModelFieldInputTemplate } from 'features/nodes/types/field';
+import { memo, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { useClipEmbedModels } from 'services/api/hooks/modelsByType';
+import type { ClipEmbedModelConfig } from 'services/api/types';
+
+import type { FieldComponentProps } from './types';
+
+type Props = FieldComponentProps<CLIPEmbedModelFieldInputInstance, CLIPEmbedModelFieldInputTemplate>;
+
+const CLIPEmbedModelFieldInputComponent = (props: Props) => {
+  const { nodeId, field } = props;
+  const { t } = useTranslation();
+  const disabledTabs = useAppSelector((s) => s.config.disabledTabs);
+  const dispatch = useAppDispatch();
+  const [modelConfigs, { isLoading }] = useClipEmbedModels();
+  const _onChange = useCallback(
+    (value: ClipEmbedModelConfig | null) => {
+      if (!value) {
+        return;
+      }
+      dispatch(
+        fieldCLIPEmbedValueChanged({
+          nodeId,
+          fieldName: field.name,
+          value,
+        })
+      );
+    },
+    [dispatch, field.name, nodeId]
+  );
+  const { options, value, onChange, placeholder, noOptionsMessage } = useGroupedModelCombobox({
+    modelConfigs,
+    onChange: _onChange,
+    isLoading,
+    selectedModel: field.value,
+  });
+
+  return (
+    <Flex w="full" alignItems="center" gap={2}>
+      <Tooltip label={!disabledTabs.includes('models') && t('modelManager.starterModelsInModelManager')}>
+        <FormControl className="nowheel nodrag" isDisabled={!options.length} isInvalid={!value}>
+          <Combobox
+            value={value}
+            placeholder={placeholder}
+            options={options}
+            onChange={onChange}
+            noOptionsMessage={noOptionsMessage}
+          />
+        </FormControl>
+      </Tooltip>
+    </Flex>
+  );
+};
+
+export default memo(CLIPEmbedModelFieldInputComponent);

invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/FluxVAEModelFieldInputComponent.tsx

@@ -0,0 +1,60 @@
+import { Combobox, Flex, FormControl, Tooltip } from '@invoke-ai/ui-library';
+import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
+import { fieldFluxVAEModelValueChanged } from 'features/nodes/store/nodesSlice';
+import type { FluxVAEModelFieldInputInstance, FluxVAEModelFieldInputTemplate } from 'features/nodes/types/field';
+import { memo, useCallback } from 'react';
+import { useTranslation } from 'react-i18next';
+import { useFluxVAEModels } from 'services/api/hooks/modelsByType';
+import type { VAEModelConfig } from 'services/api/types';
+
+import type { FieldComponentProps } from './types';
+
+type Props = FieldComponentProps<FluxVAEModelFieldInputInstance, FluxVAEModelFieldInputTemplate>;
+
+const FluxVAEModelFieldInputComponent = (props: Props) => {
+  const { nodeId, field } = props;
+  const { t } = useTranslation();
+  const disabledTabs = useAppSelector((s) => s.config.disabledTabs);
+  const dispatch = useAppDispatch();
+  const [modelConfigs, { isLoading }] = useFluxVAEModels();
+  const _onChange = useCallback(
+    (value: VAEModelConfig | null) => {
+      if (!value) {
+        return;
+      }
+      dispatch(
+        fieldFluxVAEModelValueChanged({
+          nodeId,
+          fieldName: field.name,
+          value,
+        })
+      );
+    },
+    [dispatch, field.name, nodeId]
+  );
+  const { options, value, onChange, placeholder, noOptionsMessage } = useGroupedModelCombobox({
+    modelConfigs,
+    onChange: _onChange,
+    isLoading,
+    selectedModel: field.value,
+  });
+
+  return (
+    <Flex w="full" alignItems="center" gap={2}>
+      <Tooltip label={!disabledTabs.includes('models') && t('modelManager.starterModelsInModelManager')}>
+        <FormControl className="nowheel nodrag" isDisabled={!options.length} isInvalid={!value}>
+          <Combobox
+            value={value}
+            placeholder={placeholder}
+            options={options}
+            onChange={onChange}
+            noOptionsMessage={noOptionsMessage}
+          />
+        </FormControl>
+      </Tooltip>
+    </Flex>
+  );
+};
+
+export default memo(FluxVAEModelFieldInputComponent);

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

@@ -14,9 +14,9 @@ import {
   ModalHeader,
   ModalOverlay,
   Switch,
-  useDisclosure,
 } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { buildUseBoolean } from 'common/hooks/useBoolean';
 import ReloadNodeTemplatesButton from 'features/nodes/components/flow/panels/TopRightPanel/ReloadSchemaButton';
 import {
   selectionModeChanged,
@@ -32,20 +32,17 @@ import {
   shouldSnapToGridChanged,
   shouldValidateGraphChanged,
 } from 'features/nodes/store/workflowSettingsSlice';
-import type { ChangeEvent, ReactNode } from 'react';
+import type { ChangeEvent } from 'react';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { SelectionMode } from 'reactflow';
 
 const formLabelProps: FormLabelProps = { flexGrow: 1 };
+export const [useWorkflowEditorSettingsModal] = buildUseBoolean(false);
 
-type Props = {
-  children: (props: { onOpen: () => void }) => ReactNode;
-};
-
-const WorkflowEditorSettings = ({ children }: Props) => {
-  const { isOpen, onOpen, onClose } = useDisclosure();
+const WorkflowEditorSettings = () => {
   const dispatch = useAppDispatch();
+  const modal = useWorkflowEditorSettingsModal();
 
   const shouldSnapToGrid = useAppSelector(selectShouldSnapToGrid);
   const selectionMode = useAppSelector(selectSelectionMode);
@@ -99,76 +96,72 @@ const WorkflowEditorSettings = ({ children }: Props) => {
   const { t } = useTranslation();
 
   return (
-    <>
-      {children({ onOpen })}
-
-      <Modal isOpen={isOpen} onClose={onClose} size="2xl" isCentered useInert={false}>
-        <ModalOverlay />
-        <ModalContent>
-          <ModalHeader>{t('nodes.workflowSettings')}</ModalHeader>
-          <ModalCloseButton />
-          <ModalBody>
-            <Flex flexDirection="column" gap={4} py={4}>
-              <Heading size="sm">{t('parameters.general')}</Heading>
-              <FormControlGroup orientation="vertical" formLabelProps={formLabelProps}>
-                <FormControl>
-                  <Flex w="full">
-                    <FormLabel>{t('nodes.animatedEdges')}</FormLabel>
-                    <Switch onChange={handleChangeShouldAnimate} isChecked={shouldAnimateEdges} />
-                  </Flex>
-                  <FormHelperText>{t('nodes.animatedEdgesHelp')}</FormHelperText>
-                </FormControl>
-                <Divider />
-                <FormControl>
-                  <Flex w="full">
-                    <FormLabel>{t('nodes.snapToGrid')}</FormLabel>
-                    <Switch isChecked={shouldSnapToGrid} onChange={handleChangeShouldSnap} />
-                  </Flex>
-                  <FormHelperText>{t('nodes.snapToGridHelp')}</FormHelperText>
-                </FormControl>
-                <Divider />
-                <FormControl>
-                  <Flex w="full">
-                    <FormLabel>{t('nodes.colorCodeEdges')}</FormLabel>
-                    <Switch isChecked={shouldColorEdges} onChange={handleChangeShouldColor} />
-                  </Flex>
-                  <FormHelperText>{t('nodes.colorCodeEdgesHelp')}</FormHelperText>
-                </FormControl>
-                <Divider />
-                <FormControl>
-                  <Flex w="full">
-                    <FormLabel>{t('nodes.fullyContainNodes')}</FormLabel>
-                    <Switch isChecked={selectionMode === SelectionMode.Full} onChange={handleChangeSelectionMode} />
-                  </Flex>
-                  <FormHelperText>{t('nodes.fullyContainNodesHelp')}</FormHelperText>
-                </FormControl>
-                <Divider />
-                <FormControl>
-                  <Flex w="full">
-                    <FormLabel>{t('nodes.showEdgeLabels')}</FormLabel>
-                    <Switch isChecked={shouldShowEdgeLabels} onChange={handleChangeShouldShowEdgeLabels} />
-                  </Flex>
-                  <FormHelperText>{t('nodes.showEdgeLabelsHelp')}</FormHelperText>
-                </FormControl>
-                <Divider />
-                <Heading size="sm" pt={4}>
-                  {t('common.advanced')}
-                </Heading>
-                <FormControl>
-                  <Flex w="full">
-                    <FormLabel>{t('nodes.validateConnections')}</FormLabel>
-                    <Switch isChecked={shouldValidateGraph} onChange={handleChangeShouldValidate} />
-                  </Flex>
-                  <FormHelperText>{t('nodes.validateConnectionsHelp')}</FormHelperText>
-                </FormControl>
-                <Divider />
-              </FormControlGroup>
-              <ReloadNodeTemplatesButton />
-            </Flex>
-          </ModalBody>
-        </ModalContent>
-      </Modal>
-    </>
+    <Modal isOpen={modal.isTrue} onClose={modal.setFalse} size="2xl" isCentered useInert={false}>
+      <ModalOverlay />
+      <ModalContent>
+        <ModalHeader>{t('nodes.workflowSettings')}</ModalHeader>
+        <ModalCloseButton />
+        <ModalBody>
+          <Flex flexDirection="column" gap={4} py={4}>
+            <Heading size="sm">{t('parameters.general')}</Heading>
+            <FormControlGroup orientation="vertical" formLabelProps={formLabelProps}>
+              <FormControl>
+                <Flex w="full">
+                  <FormLabel>{t('nodes.animatedEdges')}</FormLabel>
+                  <Switch onChange={handleChangeShouldAnimate} isChecked={shouldAnimateEdges} />
+                </Flex>
+                <FormHelperText>{t('nodes.animatedEdgesHelp')}</FormHelperText>
+              </FormControl>
+              <Divider />
+              <FormControl>
+                <Flex w="full">
+                  <FormLabel>{t('nodes.snapToGrid')}</FormLabel>
+                  <Switch isChecked={shouldSnapToGrid} onChange={handleChangeShouldSnap} />
+                </Flex>
+                <FormHelperText>{t('nodes.snapToGridHelp')}</FormHelperText>
+              </FormControl>
+              <Divider />
+              <FormControl>
+                <Flex w="full">
+                  <FormLabel>{t('nodes.colorCodeEdges')}</FormLabel>
+                  <Switch isChecked={shouldColorEdges} onChange={handleChangeShouldColor} />
+                </Flex>
+                <FormHelperText>{t('nodes.colorCodeEdgesHelp')}</FormHelperText>
+              </FormControl>
+              <Divider />
+              <FormControl>
+                <Flex w="full">
+                  <FormLabel>{t('nodes.fullyContainNodes')}</FormLabel>
+                  <Switch isChecked={selectionMode === SelectionMode.Full} onChange={handleChangeSelectionMode} />
+                </Flex>
+                <FormHelperText>{t('nodes.fullyContainNodesHelp')}</FormHelperText>
+              </FormControl>
+              <Divider />
+              <FormControl>
+                <Flex w="full">
+                  <FormLabel>{t('nodes.showEdgeLabels')}</FormLabel>
+                  <Switch isChecked={shouldShowEdgeLabels} onChange={handleChangeShouldShowEdgeLabels} />
+                </Flex>
+                <FormHelperText>{t('nodes.showEdgeLabelsHelp')}</FormHelperText>
+              </FormControl>
+              <Divider />
+              <Heading size="sm" pt={4}>
+                {t('common.advanced')}
+              </Heading>
+              <FormControl>
+                <Flex w="full">
+                  <FormLabel>{t('nodes.validateConnections')}</FormLabel>
+                  <Switch isChecked={shouldValidateGraph} onChange={handleChangeShouldValidate} />
+                </Flex>
+                <FormHelperText>{t('nodes.validateConnectionsHelp')}</FormHelperText>
+              </FormControl>
+              <Divider />
+            </FormControlGroup>
+            <ReloadNodeTemplatesButton />
+          </Flex>
+        </ModalBody>
+      </ModalContent>
+    </Modal>
   );
 };
 

invokeai/frontend/web/src/features/nodes/components/sidePanel/NodeEditorPanelGroup.tsx

@@ -3,7 +3,6 @@ import 'reactflow/dist/style.css';
 import { Flex } from '@invoke-ai/ui-library';
 import { useAppSelector } from 'app/store/storeHooks';
 import { selectWorkflowMode } from 'features/nodes/store/workflowSlice';
-import QueueControls from 'features/queue/components/QueueControls';
 import ResizeHandle from 'features/ui/components/tabs/ResizeHandle';
 import { usePanelStorage } from 'features/ui/hooks/usePanelStorage';
 import WorkflowLibraryButton from 'features/workflowLibrary/components/WorkflowLibraryButton';
@@ -34,7 +33,6 @@ const NodeEditorPanelGroup = () => {
 
   return (
     <Flex w="full" h="full" gap={2} flexDir="column">
-      <QueueControls />
       <Flex w="full" justifyContent="space-between" alignItems="center" gap="4" padding={1}>
         <Flex justifyContent="space-between" alignItems="center" gap="4">
           <WorkflowLibraryButton />

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

@@ -2,12 +2,12 @@ import { useStore } from '@nanostores/react';
 import { useAppStore } from 'app/store/storeHooks';
 import { $mouseOverNode } from 'features/nodes/hooks/useMouseOverNode';
 import {
-  $addNodeCmdk,
   $didUpdateEdge,
   $edgePendingUpdate,
   $pendingConnection,
   $templates,
   edgesChanged,
+  useAddNodeCmdk,
 } from 'features/nodes/store/nodesSlice';
 import { selectNodes, selectNodesSlice } from 'features/nodes/store/selectors';
 import { getFirstValidConnection } from 'features/nodes/store/util/getFirstValidConnection';
@@ -21,6 +21,7 @@ export const useConnection = () => {
   const store = useAppStore();
   const templates = useStore($templates);
   const updateNodeInternals = useUpdateNodeInternals();
+  const addNodeCmdk = useAddNodeCmdk();
 
   const onConnectStart = useCallback<OnConnectStart>(
     (event, { nodeId, handleId, handleType }) => {
@@ -107,9 +108,9 @@ export const useConnection = () => {
       $pendingConnection.set(null);
     } else {
       // The mouse is not over a node - we should open the add node popover
-      $addNodeCmdk.set(true);
+      addNodeCmdk.setTrue();
     }
-  }, [store, templates, updateNodeInternals]);
+  }, [addNodeCmdk, store, templates, updateNodeInternals]);
 
   const api = useMemo(() => ({ onConnectStart, onConnect, onConnectEnd }), [onConnectStart, onConnect, onConnectEnd]);
   return api;

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

@@ -7,11 +7,13 @@ import { SHARED_NODE_PROPERTIES } from 'features/nodes/types/constants';
 import type {
   BoardFieldValue,
   BooleanFieldValue,
+  CLIPEmbedModelFieldValue,
   ColorFieldValue,
   ControlNetModelFieldValue,
   EnumFieldValue,
   FieldValue,
   FloatFieldValue,
+  FluxVAEModelFieldValue,
   ImageFieldValue,
   IntegerFieldValue,
   IPAdapterModelFieldValue,
@@ -30,10 +32,12 @@ import type {
 import {
   zBoardFieldValue,
   zBooleanFieldValue,
+  zCLIPEmbedModelFieldValue,
   zColorFieldValue,
   zControlNetModelFieldValue,
   zEnumFieldValue,
   zFloatFieldValue,
+  zFluxVAEModelFieldValue,
   zImageFieldValue,
   zIntegerFieldValue,
   zIPAdapterModelFieldValue,
@@ -347,6 +351,12 @@ export const nodesSlice = createSlice({
     fieldT5EncoderValueChanged: (state, action: FieldValueAction<T5EncoderModelFieldValue>) => {
       fieldValueReducer(state, action, zT5EncoderModelFieldValue);
     },
+    fieldCLIPEmbedValueChanged: (state, action: FieldValueAction<CLIPEmbedModelFieldValue>) => {
+      fieldValueReducer(state, action, zCLIPEmbedModelFieldValue);
+    },
+    fieldFluxVAEModelValueChanged: (state, action: FieldValueAction<FluxVAEModelFieldValue>) => {
+      fieldValueReducer(state, action, zFluxVAEModelFieldValue);
+    },
     fieldEnumModelValueChanged: (state, action: FieldValueAction<EnumFieldValue>) => {
       fieldValueReducer(state, action, zEnumFieldValue);
     },
@@ -409,6 +419,8 @@ export const {
   fieldStringValueChanged,
   fieldVaeModelValueChanged,
   fieldT5EncoderValueChanged,
+  fieldCLIPEmbedValueChanged,
+  fieldFluxVAEModelValueChanged,
   nodeEditorReset,
   nodeIsIntermediateChanged,
   nodeIsOpenChanged,
@@ -432,8 +444,7 @@ export const $didUpdateEdge = atom(false);
 export const $lastEdgeUpdateMouseEvent = atom<MouseEvent | null>(null);
 
 export const $viewport = atom<Viewport>({ x: 0, y: 0, zoom: 1 });
-export const $addNodeCmdk = atom(false);
-export const useAddNodeCmdk = buildUseBoolean($addNodeCmdk);
+export const [useAddNodeCmdk, $addNodeCmdk] = buildUseBoolean(false);
 
 /* eslint-disable-next-line @typescript-eslint/no-explicit-any */
 const migrateNodesState = (state: any): any => {
@@ -514,6 +525,8 @@ export const isAnyNodeOrEdgeMutation = isAnyOf(
   fieldStringValueChanged,
   fieldVaeModelValueChanged,
   fieldT5EncoderValueChanged,
+  fieldCLIPEmbedValueChanged,
+  fieldFluxVAEModelValueChanged,
   nodesChanged,
   nodeIsIntermediateChanged,
   nodeIsOpenChanged,

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

@@ -151,6 +151,14 @@ const zT5EncoderModelFieldType = zFieldTypeBase.extend({
   name: z.literal('T5EncoderModelField'),
   originalType: zStatelessFieldType.optional(),
 });
+const zCLIPEmbedModelFieldType = zFieldTypeBase.extend({
+  name: z.literal('CLIPEmbedModelField'),
+  originalType: zStatelessFieldType.optional(),
+});
+const zFluxVAEModelFieldType = zFieldTypeBase.extend({
+  name: z.literal('FluxVAEModelField'),
+  originalType: zStatelessFieldType.optional(),
+});
 const zSchedulerFieldType = zFieldTypeBase.extend({
   name: z.literal('SchedulerField'),
   originalType: zStatelessFieldType.optional(),
@@ -175,6 +183,8 @@ const zStatefulFieldType = z.union([
   zT2IAdapterModelFieldType,
   zSpandrelImageToImageModelFieldType,
   zT5EncoderModelFieldType,
+  zCLIPEmbedModelFieldType,
+  zFluxVAEModelFieldType,
   zColorFieldType,
   zSchedulerFieldType,
 ]);
@@ -667,7 +677,53 @@ export const isT5EncoderModelFieldInputInstance = (val: unknown): val is T5Encod
 export const isT5EncoderModelFieldInputTemplate = (val: unknown): val is T5EncoderModelFieldInputTemplate =>
   zT5EncoderModelFieldInputTemplate.safeParse(val).success;
 
-// #endregio
+// #endregion
+
+// #region FluxVAEModelField
+
+export const zFluxVAEModelFieldValue = zModelIdentifierField.optional();
+const zFluxVAEModelFieldInputInstance = zFieldInputInstanceBase.extend({
+  value: zFluxVAEModelFieldValue,
+});
+const zFluxVAEModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zFluxVAEModelFieldType,
+  originalType: zFieldType.optional(),
+  default: zFluxVAEModelFieldValue,
+});
+
+export type FluxVAEModelFieldValue = z.infer<typeof zFluxVAEModelFieldValue>;
+
+export type FluxVAEModelFieldInputInstance = z.infer<typeof zFluxVAEModelFieldInputInstance>;
+export type FluxVAEModelFieldInputTemplate = z.infer<typeof zFluxVAEModelFieldInputTemplate>;
+export const isFluxVAEModelFieldInputInstance = (val: unknown): val is FluxVAEModelFieldInputInstance =>
+  zFluxVAEModelFieldInputInstance.safeParse(val).success;
+export const isFluxVAEModelFieldInputTemplate = (val: unknown): val is FluxVAEModelFieldInputTemplate =>
+  zFluxVAEModelFieldInputTemplate.safeParse(val).success;
+
+// #endregion
+
+// #region CLIPEmbedModelField
+
+export const zCLIPEmbedModelFieldValue = zModelIdentifierField.optional();
+const zCLIPEmbedModelFieldInputInstance = zFieldInputInstanceBase.extend({
+  value: zCLIPEmbedModelFieldValue,
+});
+const zCLIPEmbedModelFieldInputTemplate = zFieldInputTemplateBase.extend({
+  type: zCLIPEmbedModelFieldType,
+  originalType: zFieldType.optional(),
+  default: zCLIPEmbedModelFieldValue,
+});
+
+export type CLIPEmbedModelFieldValue = z.infer<typeof zCLIPEmbedModelFieldValue>;
+
+export type CLIPEmbedModelFieldInputInstance = z.infer<typeof zCLIPEmbedModelFieldInputInstance>;
+export type CLIPEmbedModelFieldInputTemplate = z.infer<typeof zCLIPEmbedModelFieldInputTemplate>;
+export const isCLIPEmbedModelFieldInputInstance = (val: unknown): val is CLIPEmbedModelFieldInputInstance =>
+  zCLIPEmbedModelFieldInputInstance.safeParse(val).success;
+export const isCLIPEmbedModelFieldInputTemplate = (val: unknown): val is CLIPEmbedModelFieldInputTemplate =>
+  zCLIPEmbedModelFieldInputTemplate.safeParse(val).success;
+
+// #endregion
 
 // #region SchedulerField
 
@@ -758,6 +814,8 @@ export const zStatefulFieldValue = z.union([
   zT2IAdapterModelFieldValue,
   zSpandrelImageToImageModelFieldValue,
   zT5EncoderModelFieldValue,
+  zFluxVAEModelFieldValue,
+  zCLIPEmbedModelFieldValue,
   zColorFieldValue,
   zSchedulerFieldValue,
 ]);
@@ -788,6 +846,8 @@ const zStatefulFieldInputInstance = z.union([
   zT2IAdapterModelFieldInputInstance,
   zSpandrelImageToImageModelFieldInputInstance,
   zT5EncoderModelFieldInputInstance,
+  zFluxVAEModelFieldInputInstance,
+  zCLIPEmbedModelFieldInputInstance,
   zColorFieldInputInstance,
   zSchedulerFieldInputInstance,
 ]);
@@ -819,6 +879,8 @@ const zStatefulFieldInputTemplate = z.union([
   zT2IAdapterModelFieldInputTemplate,
   zSpandrelImageToImageModelFieldInputTemplate,
   zT5EncoderModelFieldInputTemplate,
+  zFluxVAEModelFieldInputTemplate,
+  zCLIPEmbedModelFieldInputTemplate,
   zColorFieldInputTemplate,
   zSchedulerFieldInputTemplate,
   zStatelessFieldInputTemplate,

invokeai/frontend/web/src/features/nodes/util/graph/buildLinearBatchConfig.ts

@@ -10,7 +10,9 @@ export const prepareLinearUIBatch = (
   g: Graph,
   prepend: boolean,
   noise: Invocation<'noise'>,
-  posCond: Invocation<'compel' | 'sdxl_compel_prompt'>
+  posCond: Invocation<'compel' | 'sdxl_compel_prompt'>,
+  origin: 'generation' | 'workflows' | 'upscaling',
+  destination: 'canvas' | 'gallery'
 ): BatchConfig => {
   const { iterations, model, shouldRandomizeSeed, seed, shouldConcatPrompts } = state.params;
   const { prompts, seedBehaviour } = state.dynamicPrompts;
@@ -103,7 +105,8 @@ export const prepareLinearUIBatch = (
       graph: g.getGraph(),
       runs: 1,
       data,
-      origin: 'canvas',
+      origin,
+      destination,
     },
   };
 

invokeai/frontend/web/src/features/nodes/util/graph/generation/addInpaint.ts

@@ -29,7 +29,7 @@ export const addInpaint = async (
   const canvas = selectCanvasSlice(state);
 
   const { bbox } = canvas;
-  const { mode } = canvasSession;
+  const { sendToCanvas: isComposing } = canvasSession;
 
   const initialImage = await manager.compositor.getCompositeRasterLayerImageDTO(bbox.rect);
   const maskImage = await manager.compositor.getCompositeInpaintMaskImageDTO(bbox.rect);
@@ -99,7 +99,7 @@ export const addInpaint = async (
     g.addEdge(resizeImageToOriginalSize, 'image', canvasPasteBack, 'generated_image');
     g.addEdge(resizeMaskToOriginalSize, 'image', canvasPasteBack, 'mask');
 
-    if (mode === 'generate') {
+    if (!isComposing) {
       canvasPasteBack.source_image = { image_name: initialImage.image_name };
     }
 
@@ -143,7 +143,7 @@ export const addInpaint = async (
 
     g.addEdge(l2i, 'image', canvasPasteBack, 'generated_image');
 
-    if (mode === 'generate') {
+    if (!isComposing) {
       canvasPasteBack.source_image = { image_name: initialImage.image_name };
     }
 

invokeai/frontend/web/src/features/nodes/util/graph/generation/addOutpaint.ts

@@ -30,7 +30,7 @@ export const addOutpaint = async (
   const canvas = selectCanvasSlice(state);
 
   const { bbox } = canvas;
-  const { mode } = canvasSession;
+  const { sendToCanvas: isComposing } = canvasSession;
 
   const initialImage = await manager.compositor.getCompositeRasterLayerImageDTO(bbox.rect);
   const maskImage = await manager.compositor.getCompositeInpaintMaskImageDTO(bbox.rect);
@@ -123,7 +123,7 @@ export const addOutpaint = async (
     g.addEdge(resizeOutputImageToOriginalSize, 'image', canvasPasteBack, 'generated_image');
     g.addEdge(resizeOutputMaskToOriginalSize, 'image', canvasPasteBack, 'mask');
 
-    if (mode === 'generate') {
+    if (!isComposing) {
       canvasPasteBack.source_image = { image_name: initialImage.image_name };
     }
 
@@ -173,7 +173,7 @@ export const addOutpaint = async (
     g.addEdge(createGradientMask, 'expanded_mask_area', canvasPasteBack, 'mask');
     g.addEdge(l2i, 'image', canvasPasteBack, 'generated_image');
 
-    if (mode === 'generate') {
+    if (!isComposing) {
       canvasPasteBack.source_image = { image_name: initialImage.image_name };
     }
 

invokeai/frontend/web/src/features/nodes/util/graph/generation/buildSD1Graph.ts

@@ -282,7 +282,7 @@ export const buildSD1Graph = async (
     canvasOutput = addWatermarker(g, canvasOutput);
   }
 
-  const shouldSaveToGallery = canvasSession.mode === 'generate' || canvasSettings.autoSave;
+  const shouldSaveToGallery = !canvasSession.sendToCanvas || canvasSettings.autoSave;
 
   g.updateNode(canvasOutput, {
     id: getPrefixedId('canvas_output'),

invokeai/frontend/web/src/features/nodes/util/graph/generation/buildSDXLGraph.ts

@@ -285,7 +285,7 @@ export const buildSDXLGraph = async (
     canvasOutput = addWatermarker(g, canvasOutput);
   }
 
-  const shouldSaveToGallery = canvasSession.mode === 'generate' || canvasSettings.autoSave;
+  const shouldSaveToGallery = !canvasSession.sendToCanvas || canvasSettings.autoSave;
 
   g.updateNode(canvasOutput, {
     id: getPrefixedId('canvas_output'),

invokeai/frontend/web/src/features/nodes/util/schema/buildFieldInputInstance.ts

@@ -23,6 +23,8 @@ const FIELD_VALUE_FALLBACK_MAP: Record<StatefulFieldType['name'], FieldValue> =
   VAEModelField: undefined,
   ControlNetModelField: undefined,
   T5EncoderModelField: undefined,
+  FluxVAEModelField: undefined,
+  CLIPEmbedModelField: undefined,
 };
 
 export const buildFieldInputInstance = (id: string, template: FieldInputTemplate): FieldInputInstance => {

invokeai/frontend/web/src/features/nodes/util/schema/buildFieldInputTemplate.ts

@@ -2,6 +2,7 @@ import { FieldParseError } from 'features/nodes/types/error';
 import type {
   BoardFieldInputTemplate,
   BooleanFieldInputTemplate,
+  CLIPEmbedModelFieldInputTemplate,
   ColorFieldInputTemplate,
   ControlNetModelFieldInputTemplate,
   EnumFieldInputTemplate,
@@ -9,6 +10,7 @@ import type {
   FieldType,
   FloatFieldInputTemplate,
   FluxMainModelFieldInputTemplate,
+  FluxVAEModelFieldInputTemplate,
   ImageFieldInputTemplate,
   IntegerFieldInputTemplate,
   IPAdapterModelFieldInputTemplate,
@@ -238,6 +240,34 @@ const buildT5EncoderModelFieldInputTemplate: FieldInputTemplateBuilder<T5Encoder
   return template;
 };
 
+const buildCLIPEmbedModelFieldInputTemplate: FieldInputTemplateBuilder<CLIPEmbedModelFieldInputTemplate> = ({
+  schemaObject,
+  baseField,
+  fieldType,
+}) => {
+  const template: CLIPEmbedModelFieldInputTemplate = {
+    ...baseField,
+    type: fieldType,
+    default: schemaObject.default ?? undefined,
+  };
+
+  return template;
+};
+
+const buildFluxVAEModelFieldInputTemplate: FieldInputTemplateBuilder<FluxVAEModelFieldInputTemplate> = ({
+  schemaObject,
+  baseField,
+  fieldType,
+}) => {
+  const template: FluxVAEModelFieldInputTemplate = {
+    ...baseField,
+    type: fieldType,
+    default: schemaObject.default ?? undefined,
+  };
+
+  return template;
+};
+
 const buildLoRAModelFieldInputTemplate: FieldInputTemplateBuilder<LoRAModelFieldInputTemplate> = ({
   schemaObject,
   baseField,
@@ -423,6 +453,8 @@ export const TEMPLATE_BUILDER_MAP: Record<StatefulFieldType['name'], FieldInputT
   SpandrelImageToImageModelField: buildSpandrelImageToImageModelFieldInputTemplate,
   VAEModelField: buildVAEModelFieldInputTemplate,
   T5EncoderModelField: buildT5EncoderModelFieldInputTemplate,
+  CLIPEmbedModelField: buildCLIPEmbedModelFieldInputTemplate,
+  FluxVAEModelField: buildFluxVAEModelFieldInputTemplate,
 } as const;
 
 export const buildFieldInputTemplate = (

invokeai/frontend/web/src/features/queue/components/ClearQueueButton.tsx

@@ -1,27 +1,26 @@
 import type { ButtonProps } from '@invoke-ai/ui-library';
 import { Button } from '@invoke-ai/ui-library';
-import { useClearQueueConfirmationAlertDialog } from 'features/queue/components/ClearQueueConfirmationAlertDialog';
-import { useClearQueue } from 'features/queue/hooks/useClearQueue';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiTrashSimpleFill } from 'react-icons/pi';
 
+import { useClearQueue } from './ClearQueueConfirmationAlertDialog';
+
 type Props = ButtonProps;
 
 const ClearQueueButton = (props: Props) => {
   const { t } = useTranslation();
-  const dialogState = useClearQueueConfirmationAlertDialog();
-  const { isLoading, isDisabled } = useClearQueue();
+  const clearQueue = useClearQueue();
 
   return (
     <>
       <Button
-        isDisabled={isDisabled}
-        isLoading={isLoading}
+        isDisabled={clearQueue.isDisabled}
+        isLoading={clearQueue.isLoading}
         tooltip={t('queue.clearTooltip')}
         leftIcon={<PiTrashSimpleFill />}
         colorScheme="error"
-        onClick={dialogState.setTrue}
+        onClick={clearQueue.openDialog}
         data-testid={t('queue.clear')}
         {...props}
       >

invokeai/frontend/web/src/features/queue/components/ClearQueueConfirmationAlertDialog.tsx

@@ -1,26 +1,72 @@
 import { ConfirmationAlertDialog, Text } from '@invoke-ai/ui-library';
 import { useStore } from '@nanostores/react';
+import { $isConnected } from 'app/hooks/useSocketIO';
+import { useAppDispatch } from 'app/store/storeHooks';
 import { buildUseBoolean } from 'common/hooks/useBoolean';
-import { useClearQueue } from 'features/queue/hooks/useClearQueue';
-import { atom } from 'nanostores';
-import { memo } from 'react';
+import { listCursorChanged, listPriorityChanged } from 'features/queue/store/queueSlice';
+import { toast } from 'features/toast/toast';
+import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
+import { useClearQueueMutation, useGetQueueStatusQuery } from 'services/api/endpoints/queue';
 
-const $boolean = atom(false);
-export const useClearQueueConfirmationAlertDialog = buildUseBoolean($boolean);
+const [useClearQueueConfirmationAlertDialog] = buildUseBoolean(false);
+
+export const useClearQueue = () => {
+  const { t } = useTranslation();
+  const dispatch = useAppDispatch();
+  const dialog = useClearQueueConfirmationAlertDialog();
+  const { data: queueStatus } = useGetQueueStatusQuery();
+  const isConnected = useStore($isConnected);
+  const [trigger, { isLoading }] = useClearQueueMutation({
+    fixedCacheKey: 'clearQueue',
+  });
+
+  const clearQueue = useCallback(async () => {
+    if (!queueStatus?.queue.total) {
+      return;
+    }
+
+    try {
+      await trigger().unwrap();
+      toast({
+        id: 'QUEUE_CLEAR_SUCCEEDED',
+        title: t('queue.clearSucceeded'),
+        status: 'success',
+      });
+      dispatch(listCursorChanged(undefined));
+      dispatch(listPriorityChanged(undefined));
+    } catch {
+      toast({
+        id: 'QUEUE_CLEAR_FAILED',
+        title: t('queue.clearFailed'),
+        status: 'error',
+      });
+    }
+  }, [queueStatus?.queue.total, trigger, dispatch, t]);
+
+  const isDisabled = useMemo(() => !isConnected || !queueStatus?.queue.total, [isConnected, queueStatus?.queue.total]);
+
+  return {
+    clearQueue,
+    isOpen: dialog.isTrue,
+    openDialog: dialog.setTrue,
+    closeDialog: dialog.setFalse,
+    isLoading,
+    queueStatus,
+    isDisabled,
+  };
+};
 
 export const ClearQueueConfirmationsAlertDialog = memo(() => {
   const { t } = useTranslation();
-  const dialogState = useClearQueueConfirmationAlertDialog();
-  const isOpen = useStore(dialogState.$boolean);
-  const { clearQueue } = useClearQueue();
+  const clearQueue = useClearQueue();
 
   return (
     <ConfirmationAlertDialog
-      isOpen={isOpen}
-      onClose={dialogState.setFalse}
+      isOpen={clearQueue.isOpen}
+      onClose={clearQueue.closeDialog}
       title={t('queue.clearTooltip')}
-      acceptCallback={clearQueue}
+      acceptCallback={clearQueue.clearQueue}
       acceptButtonText={t('queue.clear')}
       useInert={false}
     >

invokeai/frontend/web/src/features/queue/components/ClearQueueIconButton.tsx

@@ -1,67 +1,40 @@
-import type { IconButtonProps } from '@invoke-ai/ui-library';
 import { IconButton, useShiftModifier } from '@invoke-ai/ui-library';
-import { useClearQueueConfirmationAlertDialog } from 'features/queue/components/ClearQueueConfirmationAlertDialog';
+import { QueueCountBadge } from 'features/queue/components/QueueCountBadge';
 import { useCancelCurrentQueueItem } from 'features/queue/hooks/useCancelCurrentQueueItem';
-import { useClearQueue } from 'features/queue/hooks/useClearQueue';
-import { memo } from 'react';
+import { memo, useRef } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiTrashSimpleBold, PiXBold } from 'react-icons/pi';
 
-type ClearQueueButtonProps = Omit<IconButtonProps, 'aria-label'>;
+import { useClearQueue } from './ClearQueueConfirmationAlertDialog';
 
-export const ClearAllQueueIconButton = memo((props: ClearQueueButtonProps) => {
+export const ClearQueueIconButton = memo((_) => {
+  const ref = useRef<HTMLDivElement>(null);
   const { t } = useTranslation();
-  const dialogState = useClearQueueConfirmationAlertDialog();
-  const { isLoading, isDisabled } = useClearQueue();
+  const clearQueue = useClearQueue();
+  const cancelCurrentQueueItem = useCancelCurrentQueueItem();
 
-  return (
-    <IconButton
-      isDisabled={isDisabled}
-      isLoading={isLoading}
-      aria-label={t('queue.clear')}
-      tooltip={t('queue.clearTooltip')}
-      icon={<PiTrashSimpleBold size="16px" />}
-      colorScheme="error"
-      onClick={dialogState.setTrue}
-      data-testid={t('queue.clear')}
-      {...props}
-    />
-  );
-});
-
-ClearAllQueueIconButton.displayName = 'ClearAllQueueIconButton';
-
-const ClearSingleQueueItemIconButton = memo((props: ClearQueueButtonProps) => {
-  const { t } = useTranslation();
-  const { cancelQueueItem, isLoading, isDisabled } = useCancelCurrentQueueItem();
-
-  return (
-    <IconButton
-      isDisabled={isDisabled}
-      isLoading={isLoading}
-      aria-label={t('queue.cancel')}
-      tooltip={t('queue.cancelTooltip')}
-      icon={<PiXBold size="16px" />}
-      colorScheme="error"
-      onClick={cancelQueueItem}
-      data-testid={t('queue.cancel')}
-      {...props}
-    />
-  );
-});
-
-ClearSingleQueueItemIconButton.displayName = 'ClearSingleQueueItemIconButton';
-
-export const ClearQueueIconButton = memo((props: ClearQueueButtonProps) => {
   // Show the single item clear button when shift is pressed
   // Otherwise show the clear queue button
   const shift = useShiftModifier();
 
-  if (shift) {
-    return <ClearAllQueueIconButton {...props} />;
-  }
-
-  return <ClearSingleQueueItemIconButton {...props} />;
+  return (
+    <>
+      <IconButton
+        ref={ref}
+        size="lg"
+        isDisabled={shift ? clearQueue.isDisabled : cancelCurrentQueueItem.isDisabled}
+        isLoading={shift ? clearQueue.isLoading : cancelCurrentQueueItem.isLoading}
+        aria-label={shift ? t('queue.clear') : t('queue.cancel')}
+        tooltip={shift ? t('queue.clearTooltip') : t('queue.cancelTooltip')}
+        icon={shift ? <PiTrashSimpleBold /> : <PiXBold />}
+        colorScheme="error"
+        onClick={shift ? clearQueue.openDialog : cancelCurrentQueueItem.cancelQueueItem}
+        data-testid={shift ? t('queue.clear') : t('queue.cancel')}
+      />
+      {/* The badge is dynamically positioned, needs a ref to the target element */}
+      <QueueCountBadge targetRef={ref} />
+    </>
+  );
 });
 
 ClearQueueIconButton.displayName = 'ClearQueueIconButton';

invokeai/frontend/web/src/features/queue/components/InvokeQueueBackButton.tsx

@@ -15,7 +15,7 @@ export const InvokeQueueBackButton = memo(() => {
   const isLoadingDynamicPrompts = useAppSelector(selectDynamicPromptsIsLoading);
 
   return (
-    <Flex pos="relative" flexGrow={1} minW="240px">
+    <Flex pos="relative" w="192px">
       <QueueIterationsNumberInput />
       <QueueButtonTooltip>
         <Button

invokeai/frontend/web/src/features/queue/components/QueueActionsMenuButton.tsx

@@ -1,120 +0,0 @@
-import {
-  Badge,
-  Box,
-  IconButton,
-  Menu,
-  MenuButton,
-  MenuDivider,
-  MenuItem,
-  MenuList,
-  Portal,
-  useDisclosure,
-} from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import type { Coordinate } from 'features/controlLayers/store/types';
-import { useClearQueueConfirmationAlertDialog } from 'features/queue/components/ClearQueueConfirmationAlertDialog';
-import { useClearQueue } from 'features/queue/hooks/useClearQueue';
-import { usePauseProcessor } from 'features/queue/hooks/usePauseProcessor';
-import { useResumeProcessor } from 'features/queue/hooks/useResumeProcessor';
-import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
-import { setActiveTab } from 'features/ui/store/uiSlice';
-import { memo, useCallback, useEffect, useRef, useState } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiPauseFill, PiPlayFill, PiTrashSimpleBold } from 'react-icons/pi';
-import { RiListCheck, RiPlayList2Fill } from 'react-icons/ri';
-import { useGetQueueStatusQuery } from 'services/api/endpoints/queue';
-
-export const QueueActionsMenuButton = memo(() => {
-  const { isOpen, onOpen, onClose } = useDisclosure();
-  const dispatch = useAppDispatch();
-  const { t } = useTranslation();
-  const [badgePos, setBadgePos] = useState<Coordinate | null>(null);
-  const menuButtonRef = useRef<HTMLButtonElement>(null);
-  const dialogState = useClearQueueConfirmationAlertDialog();
-  const isPauseEnabled = useFeatureStatus('pauseQueue');
-  const isResumeEnabled = useFeatureStatus('resumeQueue');
-  const { queueSize } = useGetQueueStatusQuery(undefined, {
-    selectFromResult: (res) => ({
-      queueSize: res.data ? res.data.queue.pending + res.data.queue.in_progress : 0,
-    }),
-  });
-  const { isLoading: isLoadingClearQueue, isDisabled: isDisabledClearQueue } = useClearQueue();
-  const {
-    resumeProcessor,
-    isLoading: isLoadingResumeProcessor,
-    isDisabled: isDisabledResumeProcessor,
-  } = useResumeProcessor();
-  const {
-    pauseProcessor,
-    isLoading: isLoadingPauseProcessor,
-    isDisabled: isDisabledPauseProcessor,
-  } = usePauseProcessor();
-  const openQueue = useCallback(() => {
-    dispatch(setActiveTab('queue'));
-  }, [dispatch]);
-
-  useEffect(() => {
-    if (menuButtonRef.current) {
-      const { x, y } = menuButtonRef.current.getBoundingClientRect();
-      setBadgePos({ x: x - 10, y: y - 10 });
-    }
-  }, []);
-
-  return (
-    <Box pos="relative">
-      <Menu isOpen={isOpen} onOpen={onOpen} onClose={onClose} placement="bottom-end">
-        <MenuButton ref={menuButtonRef} as={IconButton} aria-label="Queue Actions Menu" icon={<RiListCheck />} />
-        <MenuList>
-          <MenuItem
-            isDestructive
-            icon={<PiTrashSimpleBold size="16px" />}
-            onClick={dialogState.setTrue}
-            isLoading={isLoadingClearQueue}
-            isDisabled={isDisabledClearQueue}
-          >
-            {t('queue.clearTooltip')}
-          </MenuItem>
-          {isResumeEnabled && (
-            <MenuItem
-              icon={<PiPlayFill size="14px" />}
-              onClick={resumeProcessor}
-              isLoading={isLoadingResumeProcessor}
-              isDisabled={isDisabledResumeProcessor}
-            >
-              {t('queue.resumeTooltip')}
-            </MenuItem>
-          )}
-          {isPauseEnabled && (
-            <MenuItem
-              icon={<PiPauseFill size="14px" />}
-              onClick={pauseProcessor}
-              isLoading={isLoadingPauseProcessor}
-              isDisabled={isDisabledPauseProcessor}
-            >
-              {t('queue.pauseTooltip')}
-            </MenuItem>
-          )}
-          <MenuDivider />
-          <MenuItem icon={<RiPlayList2Fill />} onClick={openQueue}>
-            {t('queue.openQueue')}
-          </MenuItem>
-        </MenuList>
-      </Menu>
-      {queueSize > 0 && badgePos !== null && (
-        <Portal>
-          <Badge
-            pos="absolute"
-            insetInlineStart={badgePos.x}
-            insetBlockStart={badgePos.y}
-            colorScheme="invokeYellow"
-            zIndex="docked"
-          >
-            {queueSize}
-          </Badge>
-        </Portal>
-      )}
-    </Box>
-  );
-});
-
-QueueActionsMenuButton.displayName = 'QueueActionsMenuButton';

invokeai/frontend/web/src/features/queue/components/QueueControls.tsx

@@ -1,24 +1,27 @@
-import { ButtonGroup, Flex, Spacer } from '@invoke-ai/ui-library';
+import { Flex, Spacer } from '@invoke-ai/ui-library';
+import { useAppSelector } from 'app/store/storeHooks';
+import { CanvasSendToToggle } from 'features/controlLayers/components/CanvasSendToToggle';
 import { ClearQueueIconButton } from 'features/queue/components/ClearQueueIconButton';
 import QueueFrontButton from 'features/queue/components/QueueFrontButton';
 import ProgressBar from 'features/system/components/ProgressBar';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
+import { selectActiveTab } from 'features/ui/store/uiSelectors';
 import { memo } from 'react';
 
 import { InvokeQueueBackButton } from './InvokeQueueBackButton';
-import { QueueActionsMenuButton } from './QueueActionsMenuButton';
 
 const QueueControls = () => {
   const isPrependEnabled = useFeatureStatus('prependQueue');
+  const tab = useAppSelector(selectActiveTab);
   return (
     <Flex w="full" position="relative" borderRadius="base" gap={2} flexDir="column">
-      <ButtonGroup size="lg" isAttached={false}>
+      <Flex gap={2}>
         {isPrependEnabled && <QueueFrontButton />}
         <InvokeQueueBackButton />
         <Spacer />
-        <QueueActionsMenuButton />
+        {tab === 'generation' && <CanvasSendToToggle />}
         <ClearQueueIconButton />
-      </ButtonGroup>
+      </Flex>
       <ProgressBar />
     </Flex>
   );

invokeai/frontend/web/src/features/queue/components/QueueCountBadge.tsx

@@ -0,0 +1,77 @@
+import { Badge, Portal } from '@invoke-ai/ui-library';
+import { useStore } from '@nanostores/react';
+import { $isParametersPanelOpen } from 'features/ui/store/uiSlice';
+import type { RefObject } from 'react';
+import { memo, useEffect, useState } from 'react';
+import { useGetQueueStatusQuery } from 'services/api/endpoints/queue';
+
+type Props = {
+  targetRef: RefObject<HTMLDivElement>;
+};
+
+export const QueueCountBadge = memo(({ targetRef }: Props) => {
+  const [badgePos, setBadgePos] = useState<{ x: string; y: string } | null>(null);
+  const isParametersPanelOpen = useStore($isParametersPanelOpen);
+  const { queueSize } = useGetQueueStatusQuery(undefined, {
+    selectFromResult: (res) => ({
+      queueSize: res.data ? res.data.queue.pending + res.data.queue.in_progress : 0,
+    }),
+  });
+
+  useEffect(() => {
+    if (!targetRef.current) {
+      return;
+    }
+
+    const target = targetRef.current;
+    const parent = target.parentElement;
+
+    if (!parent) {
+      return;
+    }
+
+    const cb = () => {
+      if (!$isParametersPanelOpen.get()) {
+        return;
+      }
+      const { x, y } = target.getBoundingClientRect();
+      setBadgePos({ x: `${x - 7}px`, y: `${y - 5}px` });
+    };
+
+    const resizeObserver = new ResizeObserver(cb);
+    resizeObserver.observe(parent);
+    cb();
+
+    return () => {
+      resizeObserver.disconnect();
+    };
+  }, [targetRef]);
+
+  if (queueSize === 0) {
+    return null;
+  }
+  if (!badgePos) {
+    return null;
+  }
+  if (!isParametersPanelOpen) {
+    return null;
+  }
+
+  return (
+    <Portal>
+      <Badge
+        pos="absolute"
+        insetInlineStart={badgePos.x}
+        insetBlockStart={badgePos.y}
+        colorScheme="invokeYellow"
+        zIndex="docked"
+        shadow="dark-lg"
+        userSelect="none"
+      >
+        {queueSize}
+      </Badge>
+    </Portal>
+  );
+});
+
+QueueCountBadge.displayName = 'QueueCountBadge';

invokeai/frontend/web/src/features/queue/components/QueueList/QueueItemComponent.tsx

@@ -1,6 +1,7 @@
 import type { ChakraProps, CollapseProps } from '@invoke-ai/ui-library';
 import { ButtonGroup, Collapse, Flex, IconButton, Text } from '@invoke-ai/ui-library';
 import QueueStatusBadge from 'features/queue/components/common/QueueStatusBadge';
+import { useDestinationText } from 'features/queue/components/QueueList/useDestinationText';
 import { useOriginText } from 'features/queue/components/QueueList/useOriginText';
 import { useCancelQueueItem } from 'features/queue/hooks/useCancelQueueItem';
 import { getSecondsFromTimestamps } from 'features/queue/util/getSecondsFromTimestamps';
@@ -52,6 +53,7 @@ const QueueItemComponent = ({ index, item, context }: InnerItemProps) => {
 
   const isCanceled = useMemo(() => ['canceled', 'completed', 'failed'].includes(item.status), [item.status]);
   const originText = useOriginText(item.origin);
+  const destinationText = useDestinationText(item.destination);
 
   const icon = useMemo(() => <PiXBold />, []);
   return (
@@ -76,6 +78,11 @@ const QueueItemComponent = ({ index, item, context }: InnerItemProps) => {
             {originText}
           </Text>
         </Flex>
+        <Flex w={COLUMN_WIDTHS.destination} flexShrink={0}>
+          <Text overflow="hidden" textOverflow="ellipsis" whiteSpace="nowrap" alignItems="center">
+            {destinationText}
+          </Text>
+        </Flex>
         <Flex w={COLUMN_WIDTHS.time} alignItems="center" flexShrink={0}>
           {executionTime || '-'}
         </Flex>

invokeai/frontend/web/src/features/queue/components/QueueList/QueueItemDetail.tsx

@@ -1,5 +1,6 @@
 import { Button, ButtonGroup, Flex, Heading, Spinner, Text } from '@invoke-ai/ui-library';
 import DataViewer from 'features/gallery/components/ImageMetadataViewer/DataViewer';
+import { useDestinationText } from 'features/queue/components/QueueList/useDestinationText';
 import { useOriginText } from 'features/queue/components/QueueList/useOriginText';
 import { useCancelBatch } from 'features/queue/hooks/useCancelBatch';
 import { useCancelQueueItem } from 'features/queue/hooks/useCancelQueueItem';
@@ -17,7 +18,7 @@ type Props = {
 };
 
 const QueueItemComponent = ({ queueItemDTO }: Props) => {
-  const { session_id, batch_id, item_id, origin } = queueItemDTO;
+  const { session_id, batch_id, item_id, origin, destination } = queueItemDTO;
   const { t } = useTranslation();
   const { cancelBatch, isLoading: isLoadingCancelBatch, isCanceled } = useCancelBatch(batch_id);
 
@@ -26,6 +27,7 @@ const QueueItemComponent = ({ queueItemDTO }: Props) => {
   const { data: queueItem } = useGetQueueItemQuery(item_id);
 
   const originText = useOriginText(origin);
+  const destinationText = useDestinationText(destination);
 
   const statusAndTiming = useMemo(() => {
     if (!queueItem) {
@@ -54,6 +56,7 @@ const QueueItemComponent = ({ queueItemDTO }: Props) => {
       >
         <QueueItemData label={t('queue.status')} data={statusAndTiming} />
         <QueueItemData label={t('queue.origin')} data={originText} />
+        <QueueItemData label={t('queue.destination')} data={destinationText} />
         <QueueItemData label={t('queue.item')} data={item_id} />
         <QueueItemData label={t('queue.batch')} data={batch_id} />
         <QueueItemData label={t('queue.session')} data={session_id} />

invokeai/frontend/web/src/features/queue/components/QueueList/QueueListHeader.tsx

@@ -25,6 +25,9 @@ const QueueListHeader = () => {
       <Flex ps={0.5} w={COLUMN_WIDTHS.origin} alignItems="center">
         <Text variant="subtext">{t('queue.origin')}</Text>
       </Flex>
+      <Flex ps={0.5} w={COLUMN_WIDTHS.destination} alignItems="center">
+        <Text variant="subtext">{t('queue.destination')}</Text>
+      </Flex>
       <Flex ps={0.5} w={COLUMN_WIDTHS.time} alignItems="center">
         <Text variant="subtext">{t('queue.time')}</Text>
       </Flex>

invokeai/frontend/web/src/features/queue/components/QueueList/constants.ts

@@ -4,7 +4,8 @@ export const COLUMN_WIDTHS = {
   statusDot: 2,
   time: '4rem',
   origin: '5rem',
+  destination: '6rem',
   batchId: '5rem',
   fieldValues: 'auto',
   actions: 'auto',
-};
+} as const;

invokeai/frontend/web/src/features/queue/components/QueueList/useDestinationText.ts

@@ -0,0 +1,16 @@
+import { useTranslation } from 'react-i18next';
+import type { SessionQueueItemDTO } from 'services/api/types';
+
+export const useDestinationText = (destination: SessionQueueItemDTO['destination']) => {
+  const { t } = useTranslation();
+
+  if (destination === 'canvas') {
+    return t('queue.canvas');
+  }
+
+  if (destination === 'gallery') {
+    return t('queue.gallery');
+  }
+
+  return t('queue.other');
+};

invokeai/frontend/web/src/features/queue/components/QueueList/useOriginText.ts

@@ -4,13 +4,17 @@ import type { SessionQueueItemDTO } from 'services/api/types';
 export const useOriginText = (origin: SessionQueueItemDTO['origin']) => {
   const { t } = useTranslation();
 
-  if (origin === 'canvas') {
-    return t('queue.originCanvas');
+  if (origin === 'generation') {
+    return t('queue.generation');
   }
 
   if (origin === 'workflows') {
-    return t('queue.originWorkflows');
+    return t('queue.workflows');
   }
 
-  return t('queue.originOther');
+  if (origin === 'upscaling') {
+    return t('queue.upscaling');
+  }
+
+  return t('queue.other');
 };