chore: bump version to v5.10.0dev3

This allows it to pull in sentencepiece on its own. In 0.10.0, it didn't have this package listed as a dependency, but in recent releases it does. So we are able to remove sentencepiece as an explicit dep.

.github/CODEOWNERS

@@ -2,11 +2,11 @@
 /.github/workflows/  @lstein @blessedcoolant @hipsterusername @ebr @jazzhaiku
 
 # documentation
-/docs/ @lstein @blessedcoolant @hipsterusername @Millu
-/mkdocs.yml @lstein  @blessedcoolant @hipsterusername @Millu
+/docs/ @lstein @blessedcoolant @hipsterusername @psychedelicious
+/mkdocs.yml @lstein @blessedcoolant @hipsterusername @psychedelicious
 
 # nodes
-/invokeai/app/ @Kyle0654 @blessedcoolant @psychedelicious @brandonrising @hipsterusername @jazzhaiku
+/invokeai/app/ @blessedcoolant @psychedelicious @brandonrising @hipsterusername @jazzhaiku
 
 # installation and configuration
 /pyproject.toml  @lstein @blessedcoolant @hipsterusername
@@ -22,7 +22,7 @@
 /invokeai/backend @blessedcoolant @psychedelicious @lstein @maryhipp @hipsterusername
 
 # generation, model management, postprocessing
-/invokeai/backend  @damian0815 @lstein @blessedcoolant @gregghelt2 @StAlKeR7779 @brandonrising @ryanjdick @hipsterusername @jazzhaiku
+/invokeai/backend  @lstein @blessedcoolant @brandonrising @hipsterusername @jazzhaiku
 
 # front ends
 /invokeai/frontend/CLI @lstein @hipsterusername

.github/workflows/build-installer.yml

@@ -17,7 +17,7 @@ jobs:
       - name: setup python
         uses: actions/setup-python@v5
         with:
-          python-version: '3.10'
+          python-version: '3.12'
           cache: pip
           cache-dependency-path: pyproject.toml
 

docs/installation/manual.md

@@ -64,7 +64,7 @@ The following commands vary depending on the version of Invoke being installed a
 
 5. Choose a version to install. Review the [GitHub releases page](https://github.com/invoke-ai/InvokeAI/releases).
 
-6. Determine the package package specifier to use when installing. This is a performance optimization.
+6. Determine the package specifier to use when installing. This is a performance optimization.
 
     - If you have an Nvidia 20xx series GPU or older, use `invokeai[xformers]`.
     - If you have an Nvidia 30xx series GPU or newer, or do not have an Nvidia GPU, use `invokeai`.

invokeai/app/api/routers/session_queue.py

@@ -2,7 +2,7 @@ from typing import Optional
 
 from fastapi import Body, Path, Query
 from fastapi.routing import APIRouter
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 
 from invokeai.app.api.dependencies import ApiDependencies
 from invokeai.app.services.session_processor.session_processor_common import SessionProcessorStatus
@@ -15,6 +15,7 @@ from invokeai.app.services.session_queue.session_queue_common import (
     CancelByDestinationResult,
     ClearResult,
     EnqueueBatchResult,
+    FieldIdentifier,
     PruneResult,
     RetryItemsResult,
     SessionQueueCountsByDestination,
@@ -34,6 +35,12 @@ class SessionQueueAndProcessorStatus(BaseModel):
     processor: SessionProcessorStatus
 
 
+class ValidationRunData(BaseModel):
+    workflow_id: str = Field(description="The id of the workflow being published.")
+    input_fields: list[FieldIdentifier] = Body(description="The input fields for the published workflow")
+    output_fields: list[FieldIdentifier] = Body(description="The output fields for the published workflow")
+
+
 @session_queue_router.post(
     "/{queue_id}/enqueue_batch",
     operation_id="enqueue_batch",
@@ -45,6 +52,10 @@ async def enqueue_batch(
     queue_id: str = Path(description="The queue id to perform this operation on"),
     batch: Batch = Body(description="Batch to process"),
     prepend: bool = Body(default=False, description="Whether or not to prepend this batch in the queue"),
+    validation_run_data: Optional[ValidationRunData] = Body(
+        default=None,
+        description="The validation run data to use for this batch. This is only used if this is a validation run.",
+    ),
 ) -> EnqueueBatchResult:
     """Processes a batch and enqueues the output graphs for execution."""
 

invokeai/app/api/routers/workflows.py

@@ -106,6 +106,7 @@ async def list_workflows(
     tags: Optional[list[str]] = Query(default=None, description="The tags of workflow to get"),
     query: Optional[str] = Query(default=None, description="The text to query by (matches name and description)"),
     has_been_opened: Optional[bool] = Query(default=None, description="Whether to include/exclude recent workflows"),
+    is_published: Optional[bool] = Query(default=None, description="Whether to include/exclude published workflows"),
 ) -> PaginatedResults[WorkflowRecordListItemWithThumbnailDTO]:
     """Gets a page of workflows"""
     workflows_with_thumbnails: list[WorkflowRecordListItemWithThumbnailDTO] = []
@@ -118,6 +119,7 @@ async def list_workflows(
         categories=categories,
         tags=tags,
         has_been_opened=has_been_opened,
+        is_published=is_published,
     )
     for workflow in workflows.items:
         workflows_with_thumbnails.append(

invokeai/app/invocations/controlnet.py

@@ -0,0 +1,128 @@
+# Invocations for ControlNet image preprocessors
+# initial implementation by Gregg Helt, 2023
+from typing import List, Union
+
+from pydantic import BaseModel, Field, field_validator, model_validator
+
+from invokeai.app.invocations.baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    Classification,
+    invocation,
+    invocation_output,
+)
+from invokeai.app.invocations.fields import (
+    FieldDescriptions,
+    ImageField,
+    InputField,
+    OutputField,
+    UIType,
+)
+from invokeai.app.invocations.model import ModelIdentifierField
+from invokeai.app.invocations.primitives import ImageOutput
+from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
+from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.app.util.controlnet_utils import CONTROLNET_MODE_VALUES, CONTROLNET_RESIZE_VALUES, heuristic_resize
+from invokeai.backend.image_util.util import np_to_pil, pil_to_np
+
+
+class ControlField(BaseModel):
+    image: ImageField = Field(description="The control image")
+    control_model: ModelIdentifierField = Field(description="The ControlNet model to use")
+    control_weight: Union[float, List[float]] = Field(default=1, description="The weight given to the ControlNet")
+    begin_step_percent: float = Field(
+        default=0, ge=0, le=1, description="When the ControlNet is first applied (% of total steps)"
+    )
+    end_step_percent: float = Field(
+        default=1, ge=0, le=1, description="When the ControlNet is last applied (% of total steps)"
+    )
+    control_mode: CONTROLNET_MODE_VALUES = Field(default="balanced", description="The control mode to use")
+    resize_mode: CONTROLNET_RESIZE_VALUES = Field(default="just_resize", description="The resize mode to use")
+
+    @field_validator("control_weight")
+    @classmethod
+    def validate_control_weight(cls, v):
+        validate_weights(v)
+        return v
+
+    @model_validator(mode="after")
+    def validate_begin_end_step_percent(self):
+        validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
+        return self
+
+
+@invocation_output("control_output")
+class ControlOutput(BaseInvocationOutput):
+    """node output for ControlNet info"""
+
+    # Outputs
+    control: ControlField = OutputField(description=FieldDescriptions.control)
+
+
+@invocation("controlnet", title="ControlNet - SD1.5, SDXL", tags=["controlnet"], category="controlnet", version="1.1.3")
+class ControlNetInvocation(BaseInvocation):
+    """Collects ControlNet info to pass to other nodes"""
+
+    image: ImageField = InputField(description="The control image")
+    control_model: ModelIdentifierField = InputField(
+        description=FieldDescriptions.controlnet_model, ui_type=UIType.ControlNetModel
+    )
+    control_weight: Union[float, List[float]] = InputField(
+        default=1.0, ge=-1, le=2, description="The weight given to the ControlNet"
+    )
+    begin_step_percent: float = InputField(
+        default=0, ge=0, le=1, description="When the ControlNet is first applied (% of total steps)"
+    )
+    end_step_percent: float = InputField(
+        default=1, ge=0, le=1, description="When the ControlNet is last applied (% of total steps)"
+    )
+    control_mode: CONTROLNET_MODE_VALUES = InputField(default="balanced", description="The control mode used")
+    resize_mode: CONTROLNET_RESIZE_VALUES = InputField(default="just_resize", description="The resize mode used")
+
+    @field_validator("control_weight")
+    @classmethod
+    def validate_control_weight(cls, v):
+        validate_weights(v)
+        return v
+
+    @model_validator(mode="after")
+    def validate_begin_end_step_percent(self) -> "ControlNetInvocation":
+        validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
+        return self
+
+    def invoke(self, context: InvocationContext) -> ControlOutput:
+        return ControlOutput(
+            control=ControlField(
+                image=self.image,
+                control_model=self.control_model,
+                control_weight=self.control_weight,
+                begin_step_percent=self.begin_step_percent,
+                end_step_percent=self.end_step_percent,
+                control_mode=self.control_mode,
+                resize_mode=self.resize_mode,
+            ),
+        )
+
+
+@invocation(
+    "heuristic_resize",
+    title="Heuristic Resize",
+    tags=["image, controlnet"],
+    category="image",
+    version="1.0.1",
+    classification=Classification.Prototype,
+)
+class HeuristicResizeInvocation(BaseInvocation):
+    """Resize an image using a heuristic method. Preserves edge maps."""
+
+    image: ImageField = InputField(description="The image to resize")
+    width: int = InputField(default=512, ge=1, description="The width to resize to (px)")
+    height: int = InputField(default=512, ge=1, description="The height to resize to (px)")
+
+    def invoke(self, context: InvocationContext) -> ImageOutput:
+        image = context.images.get_pil(self.image.image_name, "RGB")
+        np_img = pil_to_np(image)
+        np_resized = heuristic_resize(np_img, (self.width, self.height))
+        resized = np_to_pil(np_resized)
+        image_dto = context.images.save(image=resized)
+        return ImageOutput.build(image_dto)

invokeai/app/invocations/controlnet_image_processors.py

@@ -1,716 +0,0 @@
-# Invocations for ControlNet image preprocessors
-# initial implementation by Gregg Helt, 2023
-# heavily leverages controlnet_aux package: https://github.com/patrickvonplaten/controlnet_aux
-from builtins import bool, float
-from pathlib import Path
-from typing import Dict, List, Literal, Union
-
-import cv2
-import numpy as np
-from controlnet_aux import (
-    ContentShuffleDetector,
-    LeresDetector,
-    MediapipeFaceDetector,
-    MidasDetector,
-    MLSDdetector,
-    NormalBaeDetector,
-    PidiNetDetector,
-    SamDetector,
-    ZoeDetector,
-)
-from controlnet_aux.util import HWC3, ade_palette
-from PIL import Image
-from pydantic import BaseModel, Field, field_validator, model_validator
-from transformers import pipeline
-from transformers.pipelines import DepthEstimationPipeline
-
-from invokeai.app.invocations.baseinvocation import (
-    BaseInvocation,
-    BaseInvocationOutput,
-    Classification,
-    invocation,
-    invocation_output,
-)
-from invokeai.app.invocations.fields import (
-    FieldDescriptions,
-    ImageField,
-    InputField,
-    OutputField,
-    UIType,
-    WithBoard,
-    WithMetadata,
-)
-from invokeai.app.invocations.model import ModelIdentifierField
-from invokeai.app.invocations.primitives import ImageOutput
-from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
-from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.app.util.controlnet_utils import CONTROLNET_MODE_VALUES, CONTROLNET_RESIZE_VALUES, heuristic_resize
-from invokeai.backend.image_util.canny import get_canny_edges
-from invokeai.backend.image_util.depth_anything.depth_anything_pipeline import DepthAnythingPipeline
-from invokeai.backend.image_util.dw_openpose import DWPOSE_MODELS, DWOpenposeDetector
-from invokeai.backend.image_util.hed import HEDProcessor
-from invokeai.backend.image_util.lineart import LineartProcessor
-from invokeai.backend.image_util.lineart_anime import LineartAnimeProcessor
-from invokeai.backend.image_util.util import np_to_pil, pil_to_np
-
-
-class ControlField(BaseModel):
-    image: ImageField = Field(description="The control image")
-    control_model: ModelIdentifierField = Field(description="The ControlNet model to use")
-    control_weight: Union[float, List[float]] = Field(default=1, description="The weight given to the ControlNet")
-    begin_step_percent: float = Field(
-        default=0, ge=0, le=1, description="When the ControlNet is first applied (% of total steps)"
-    )
-    end_step_percent: float = Field(
-        default=1, ge=0, le=1, description="When the ControlNet is last applied (% of total steps)"
-    )
-    control_mode: CONTROLNET_MODE_VALUES = Field(default="balanced", description="The control mode to use")
-    resize_mode: CONTROLNET_RESIZE_VALUES = Field(default="just_resize", description="The resize mode to use")
-
-    @field_validator("control_weight")
-    @classmethod
-    def validate_control_weight(cls, v):
-        validate_weights(v)
-        return v
-
-    @model_validator(mode="after")
-    def validate_begin_end_step_percent(self):
-        validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
-        return self
-
-
-@invocation_output("control_output")
-class ControlOutput(BaseInvocationOutput):
-    """node output for ControlNet info"""
-
-    # Outputs
-    control: ControlField = OutputField(description=FieldDescriptions.control)
-
-
-@invocation("controlnet", title="ControlNet - SD1.5, SDXL", tags=["controlnet"], category="controlnet", version="1.1.3")
-class ControlNetInvocation(BaseInvocation):
-    """Collects ControlNet info to pass to other nodes"""
-
-    image: ImageField = InputField(description="The control image")
-    control_model: ModelIdentifierField = InputField(
-        description=FieldDescriptions.controlnet_model, ui_type=UIType.ControlNetModel
-    )
-    control_weight: Union[float, List[float]] = InputField(
-        default=1.0, ge=-1, le=2, description="The weight given to the ControlNet"
-    )
-    begin_step_percent: float = InputField(
-        default=0, ge=0, le=1, description="When the ControlNet is first applied (% of total steps)"
-    )
-    end_step_percent: float = InputField(
-        default=1, ge=0, le=1, description="When the ControlNet is last applied (% of total steps)"
-    )
-    control_mode: CONTROLNET_MODE_VALUES = InputField(default="balanced", description="The control mode used")
-    resize_mode: CONTROLNET_RESIZE_VALUES = InputField(default="just_resize", description="The resize mode used")
-
-    @field_validator("control_weight")
-    @classmethod
-    def validate_control_weight(cls, v):
-        validate_weights(v)
-        return v
-
-    @model_validator(mode="after")
-    def validate_begin_end_step_percent(self) -> "ControlNetInvocation":
-        validate_begin_end_step(self.begin_step_percent, self.end_step_percent)
-        return self
-
-    def invoke(self, context: InvocationContext) -> ControlOutput:
-        return ControlOutput(
-            control=ControlField(
-                image=self.image,
-                control_model=self.control_model,
-                control_weight=self.control_weight,
-                begin_step_percent=self.begin_step_percent,
-                end_step_percent=self.end_step_percent,
-                control_mode=self.control_mode,
-                resize_mode=self.resize_mode,
-            ),
-        )
-
-
-# This invocation exists for other invocations to subclass it - do not register with @invocation!
-class ImageProcessorInvocation(BaseInvocation, WithMetadata, WithBoard):
-    """Base class for invocations that preprocess images for ControlNet"""
-
-    image: ImageField = InputField(description="The image to process")
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        # superclass just passes through image without processing
-        return image
-
-    def load_image(self, context: InvocationContext) -> Image.Image:
-        # allows override for any special formatting specific to the preprocessor
-        return context.images.get_pil(self.image.image_name, "RGB")
-
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        self._context = context
-        raw_image = self.load_image(context)
-        # image type should be PIL.PngImagePlugin.PngImageFile ?
-        processed_image = self.run_processor(raw_image)
-
-        # currently can't see processed image in node UI without a showImage node,
-        #    so for now setting image_type to RESULT instead of INTERMEDIATE so will get saved in gallery
-        image_dto = context.images.save(image=processed_image)
-
-        """Builds an ImageOutput and its ImageField"""
-        processed_image_field = ImageField(image_name=image_dto.image_name)
-        return ImageOutput(
-            image=processed_image_field,
-            # width=processed_image.width,
-            width=image_dto.width,
-            # height=processed_image.height,
-            height=image_dto.height,
-            # mode=processed_image.mode,
-        )
-
-
-@invocation(
-    "canny_image_processor",
-    title="Canny Processor",
-    tags=["controlnet", "canny"],
-    category="controlnet",
-    version="1.3.3",
-    classification=Classification.Deprecated,
-)
-class CannyImageProcessorInvocation(ImageProcessorInvocation):
-    """Canny edge detection for ControlNet"""
-
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-    low_threshold: int = InputField(
-        default=100, ge=0, le=255, description="The low threshold of the Canny pixel gradient (0-255)"
-    )
-    high_threshold: int = InputField(
-        default=200, ge=0, le=255, description="The high threshold of the Canny pixel gradient (0-255)"
-    )
-
-    def load_image(self, context: InvocationContext) -> Image.Image:
-        # Keep alpha channel for Canny processing to detect edges of transparent areas
-        return context.images.get_pil(self.image.image_name, "RGBA")
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        processed_image = get_canny_edges(
-            image,
-            self.low_threshold,
-            self.high_threshold,
-            detect_resolution=self.detect_resolution,
-            image_resolution=self.image_resolution,
-        )
-        return processed_image
-
-
-@invocation(
-    "hed_image_processor",
-    title="HED (softedge) Processor",
-    tags=["controlnet", "hed", "softedge"],
-    category="controlnet",
-    version="1.2.3",
-    classification=Classification.Deprecated,
-)
-class HedImageProcessorInvocation(ImageProcessorInvocation):
-    """Applies HED edge detection to image"""
-
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-    # safe not supported in controlnet_aux v0.0.3
-    # safe: bool = InputField(default=False, description=FieldDescriptions.safe_mode)
-    scribble: bool = InputField(default=False, description=FieldDescriptions.scribble_mode)
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        hed_processor = HEDProcessor()
-        processed_image = hed_processor.run(
-            image,
-            detect_resolution=self.detect_resolution,
-            image_resolution=self.image_resolution,
-            # safe not supported in controlnet_aux v0.0.3
-            # safe=self.safe,
-            scribble=self.scribble,
-        )
-        return processed_image
-
-
-@invocation(
-    "lineart_image_processor",
-    title="Lineart Processor",
-    tags=["controlnet", "lineart"],
-    category="controlnet",
-    version="1.2.3",
-    classification=Classification.Deprecated,
-)
-class LineartImageProcessorInvocation(ImageProcessorInvocation):
-    """Applies line art processing to image"""
-
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-    coarse: bool = InputField(default=False, description="Whether to use coarse mode")
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        lineart_processor = LineartProcessor()
-        processed_image = lineart_processor.run(
-            image, detect_resolution=self.detect_resolution, image_resolution=self.image_resolution, coarse=self.coarse
-        )
-        return processed_image
-
-
-@invocation(
-    "lineart_anime_image_processor",
-    title="Lineart Anime Processor",
-    tags=["controlnet", "lineart", "anime"],
-    category="controlnet",
-    version="1.2.3",
-    classification=Classification.Deprecated,
-)
-class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
-    """Applies line art anime processing to image"""
-
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        processor = LineartAnimeProcessor()
-        processed_image = processor.run(
-            image,
-            detect_resolution=self.detect_resolution,
-            image_resolution=self.image_resolution,
-        )
-        return processed_image
-
-
-@invocation(
-    "midas_depth_image_processor",
-    title="Midas Depth Processor",
-    tags=["controlnet", "midas"],
-    category="controlnet",
-    version="1.2.4",
-    classification=Classification.Deprecated,
-)
-class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
-    """Applies Midas depth processing to image"""
-
-    a_mult: float = InputField(default=2.0, ge=0, description="Midas parameter `a_mult` (a = a_mult * PI)")
-    bg_th: float = InputField(default=0.1, ge=0, description="Midas parameter `bg_th`")
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-    # depth_and_normal not supported in controlnet_aux v0.0.3
-    # depth_and_normal: bool = InputField(default=False, description="whether to use depth and normal mode")
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        # TODO: replace from_pretrained() calls with context.models.download_and_cache() (or similar)
-        midas_processor = MidasDetector.from_pretrained("lllyasviel/Annotators")
-        processed_image = midas_processor(
-            image,
-            a=np.pi * self.a_mult,
-            bg_th=self.bg_th,
-            image_resolution=self.image_resolution,
-            detect_resolution=self.detect_resolution,
-            # dept_and_normal not supported in controlnet_aux v0.0.3
-            # depth_and_normal=self.depth_and_normal,
-        )
-        return processed_image
-
-
-@invocation(
-    "normalbae_image_processor",
-    title="Normal BAE Processor",
-    tags=["controlnet"],
-    category="controlnet",
-    version="1.2.3",
-    classification=Classification.Deprecated,
-)
-class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
-    """Applies NormalBae processing to image"""
-
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        normalbae_processor = NormalBaeDetector.from_pretrained("lllyasviel/Annotators")
-        processed_image = normalbae_processor(
-            image, detect_resolution=self.detect_resolution, image_resolution=self.image_resolution
-        )
-        return processed_image
-
-
-@invocation(
-    "mlsd_image_processor",
-    title="MLSD Processor",
-    tags=["controlnet", "mlsd"],
-    category="controlnet",
-    version="1.2.3",
-    classification=Classification.Deprecated,
-)
-class MlsdImageProcessorInvocation(ImageProcessorInvocation):
-    """Applies MLSD processing to image"""
-
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-    thr_v: float = InputField(default=0.1, ge=0, description="MLSD parameter `thr_v`")
-    thr_d: float = InputField(default=0.1, ge=0, description="MLSD parameter `thr_d`")
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        mlsd_processor = MLSDdetector.from_pretrained("lllyasviel/Annotators")
-        processed_image = mlsd_processor(
-            image,
-            detect_resolution=self.detect_resolution,
-            image_resolution=self.image_resolution,
-            thr_v=self.thr_v,
-            thr_d=self.thr_d,
-        )
-        return processed_image
-
-
-@invocation(
-    "pidi_image_processor",
-    title="PIDI Processor",
-    tags=["controlnet", "pidi"],
-    category="controlnet",
-    version="1.2.3",
-    classification=Classification.Deprecated,
-)
-class PidiImageProcessorInvocation(ImageProcessorInvocation):
-    """Applies PIDI processing to image"""
-
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-    safe: bool = InputField(default=False, description=FieldDescriptions.safe_mode)
-    scribble: bool = InputField(default=False, description=FieldDescriptions.scribble_mode)
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        pidi_processor = PidiNetDetector.from_pretrained("lllyasviel/Annotators")
-        processed_image = pidi_processor(
-            image,
-            detect_resolution=self.detect_resolution,
-            image_resolution=self.image_resolution,
-            safe=self.safe,
-            scribble=self.scribble,
-        )
-        return processed_image
-
-
-@invocation(
-    "content_shuffle_image_processor",
-    title="Content Shuffle Processor",
-    tags=["controlnet", "contentshuffle"],
-    category="controlnet",
-    version="1.2.3",
-    classification=Classification.Deprecated,
-)
-class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
-    """Applies content shuffle processing to image"""
-
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-    h: int = InputField(default=512, ge=0, description="Content shuffle `h` parameter")
-    w: int = InputField(default=512, ge=0, description="Content shuffle `w` parameter")
-    f: int = InputField(default=256, ge=0, description="Content shuffle `f` parameter")
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        content_shuffle_processor = ContentShuffleDetector()
-        processed_image = content_shuffle_processor(
-            image,
-            detect_resolution=self.detect_resolution,
-            image_resolution=self.image_resolution,
-            h=self.h,
-            w=self.w,
-            f=self.f,
-        )
-        return processed_image
-
-
-# should work with controlnet_aux >= 0.0.4 and timm <= 0.6.13
-@invocation(
-    "zoe_depth_image_processor",
-    title="Zoe (Depth) Processor",
-    tags=["controlnet", "zoe", "depth"],
-    category="controlnet",
-    version="1.2.3",
-    classification=Classification.Deprecated,
-)
-class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
-    """Applies Zoe depth processing to image"""
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        zoe_depth_processor = ZoeDetector.from_pretrained("lllyasviel/Annotators")
-        processed_image = zoe_depth_processor(image)
-        return processed_image
-
-
-@invocation(
-    "mediapipe_face_processor",
-    title="Mediapipe Face Processor",
-    tags=["controlnet", "mediapipe", "face"],
-    category="controlnet",
-    version="1.2.4",
-    classification=Classification.Deprecated,
-)
-class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
-    """Applies mediapipe face processing to image"""
-
-    max_faces: int = InputField(default=1, ge=1, description="Maximum number of faces to detect")
-    min_confidence: float = InputField(default=0.5, ge=0, le=1, description="Minimum confidence for face detection")
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        mediapipe_face_processor = MediapipeFaceDetector()
-        processed_image = mediapipe_face_processor(
-            image,
-            max_faces=self.max_faces,
-            min_confidence=self.min_confidence,
-            image_resolution=self.image_resolution,
-            detect_resolution=self.detect_resolution,
-        )
-        return processed_image
-
-
-@invocation(
-    "leres_image_processor",
-    title="Leres (Depth) Processor",
-    tags=["controlnet", "leres", "depth"],
-    category="controlnet",
-    version="1.2.3",
-    classification=Classification.Deprecated,
-)
-class LeresImageProcessorInvocation(ImageProcessorInvocation):
-    """Applies leres processing to image"""
-
-    thr_a: float = InputField(default=0, description="Leres parameter `thr_a`")
-    thr_b: float = InputField(default=0, description="Leres parameter `thr_b`")
-    boost: bool = InputField(default=False, description="Whether to use boost mode")
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        leres_processor = LeresDetector.from_pretrained("lllyasviel/Annotators")
-        processed_image = leres_processor(
-            image,
-            thr_a=self.thr_a,
-            thr_b=self.thr_b,
-            boost=self.boost,
-            detect_resolution=self.detect_resolution,
-            image_resolution=self.image_resolution,
-        )
-        return processed_image
-
-
-@invocation(
-    "tile_image_processor",
-    title="Tile Resample Processor",
-    tags=["controlnet", "tile"],
-    category="controlnet",
-    version="1.2.3",
-    classification=Classification.Deprecated,
-)
-class TileResamplerProcessorInvocation(ImageProcessorInvocation):
-    """Tile resampler processor"""
-
-    # res: int = InputField(default=512, ge=0, le=1024, description="The pixel resolution for each tile")
-    down_sampling_rate: float = InputField(default=1.0, ge=1.0, le=8.0, description="Down sampling rate")
-
-    # tile_resample copied from sd-webui-controlnet/scripts/processor.py
-    def tile_resample(
-        self,
-        np_img: np.ndarray,
-        res=512,  # never used?
-        down_sampling_rate=1.0,
-    ):
-        np_img = HWC3(np_img)
-        if down_sampling_rate < 1.1:
-            return np_img
-        H, W, C = np_img.shape
-        H = int(float(H) / float(down_sampling_rate))
-        W = int(float(W) / float(down_sampling_rate))
-        np_img = cv2.resize(np_img, (W, H), interpolation=cv2.INTER_AREA)
-        return np_img
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        np_img = np.array(image, dtype=np.uint8)
-        processed_np_image = self.tile_resample(
-            np_img,
-            # res=self.tile_size,
-            down_sampling_rate=self.down_sampling_rate,
-        )
-        processed_image = Image.fromarray(processed_np_image)
-        return processed_image
-
-
-@invocation(
-    "segment_anything_processor",
-    title="Segment Anything Processor",
-    tags=["controlnet", "segmentanything"],
-    category="controlnet",
-    version="1.2.4",
-    classification=Classification.Deprecated,
-)
-class SegmentAnythingProcessorInvocation(ImageProcessorInvocation):
-    """Applies segment anything processing to image"""
-
-    detect_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.detect_res)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        # segment_anything_processor = SamDetector.from_pretrained("ybelkada/segment-anything", subfolder="checkpoints")
-        segment_anything_processor = SamDetectorReproducibleColors.from_pretrained(
-            "ybelkada/segment-anything", subfolder="checkpoints"
-        )
-        np_img = np.array(image, dtype=np.uint8)
-        processed_image = segment_anything_processor(
-            np_img, image_resolution=self.image_resolution, detect_resolution=self.detect_resolution
-        )
-        return processed_image
-
-
-class SamDetectorReproducibleColors(SamDetector):
-    # overriding SamDetector.show_anns() method to use reproducible colors for segmentation image
-    #     base class show_anns() method randomizes colors,
-    #     which seems to also lead to non-reproducible image generation
-    # so using ADE20k color palette instead
-    def show_anns(self, anns: List[Dict]):
-        if len(anns) == 0:
-            return
-        sorted_anns = sorted(anns, key=(lambda x: x["area"]), reverse=True)
-        h, w = anns[0]["segmentation"].shape
-        final_img = Image.fromarray(np.zeros((h, w, 3), dtype=np.uint8), mode="RGB")
-        palette = ade_palette()
-        for i, ann in enumerate(sorted_anns):
-            m = ann["segmentation"]
-            img = np.empty((m.shape[0], m.shape[1], 3), dtype=np.uint8)
-            # doing modulo just in case number of annotated regions exceeds number of colors in palette
-            ann_color = palette[i % len(palette)]
-            img[:, :] = ann_color
-            final_img.paste(Image.fromarray(img, mode="RGB"), (0, 0), Image.fromarray(np.uint8(m * 255)))
-        return np.array(final_img, dtype=np.uint8)
-
-
-@invocation(
-    "color_map_image_processor",
-    title="Color Map Processor",
-    tags=["controlnet"],
-    category="controlnet",
-    version="1.2.3",
-    classification=Classification.Deprecated,
-)
-class ColorMapImageProcessorInvocation(ImageProcessorInvocation):
-    """Generates a color map from the provided image"""
-
-    color_map_tile_size: int = InputField(default=64, ge=1, description=FieldDescriptions.tile_size)
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        np_image = np.array(image, dtype=np.uint8)
-        height, width = np_image.shape[:2]
-
-        width_tile_size = min(self.color_map_tile_size, width)
-        height_tile_size = min(self.color_map_tile_size, height)
-
-        color_map = cv2.resize(
-            np_image,
-            (width // width_tile_size, height // height_tile_size),
-            interpolation=cv2.INTER_CUBIC,
-        )
-        color_map = cv2.resize(color_map, (width, height), interpolation=cv2.INTER_NEAREST)
-        color_map = Image.fromarray(color_map)
-        return color_map
-
-
-DEPTH_ANYTHING_MODEL_SIZES = Literal["large", "base", "small", "small_v2"]
-# DepthAnything V2 Small model is licensed under Apache 2.0 but not the base and large models.
-DEPTH_ANYTHING_MODELS = {
-    "large": "LiheYoung/depth-anything-large-hf",
-    "base": "LiheYoung/depth-anything-base-hf",
-    "small": "LiheYoung/depth-anything-small-hf",
-    "small_v2": "depth-anything/Depth-Anything-V2-Small-hf",
-}
-
-
-@invocation(
-    "depth_anything_image_processor",
-    title="Depth Anything Processor",
-    tags=["controlnet", "depth", "depth anything"],
-    category="controlnet",
-    version="1.1.3",
-    classification=Classification.Deprecated,
-)
-class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation):
-    """Generates a depth map based on the Depth Anything algorithm"""
-
-    model_size: DEPTH_ANYTHING_MODEL_SIZES = InputField(
-        default="small_v2", description="The size of the depth model to use"
-    )
-    resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        def load_depth_anything(model_path: Path):
-            depth_anything_pipeline = pipeline(model=str(model_path), task="depth-estimation", local_files_only=True)
-            assert isinstance(depth_anything_pipeline, DepthEstimationPipeline)
-            return DepthAnythingPipeline(depth_anything_pipeline)
-
-        with self._context.models.load_remote_model(
-            source=DEPTH_ANYTHING_MODELS[self.model_size], loader=load_depth_anything
-        ) as depth_anything_detector:
-            assert isinstance(depth_anything_detector, DepthAnythingPipeline)
-            depth_map = depth_anything_detector.generate_depth(image)
-
-            # Resizing to user target specified size
-            new_height = int(image.size[1] * (self.resolution / image.size[0]))
-            depth_map = depth_map.resize((self.resolution, new_height))
-
-            return depth_map
-
-
-@invocation(
-    "dw_openpose_image_processor",
-    title="DW Openpose Image Processor",
-    tags=["controlnet", "dwpose", "openpose"],
-    category="controlnet",
-    version="1.1.1",
-    classification=Classification.Deprecated,
-)
-class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation):
-    """Generates an openpose pose from an image using DWPose"""
-
-    draw_body: bool = InputField(default=True)
-    draw_face: bool = InputField(default=False)
-    draw_hands: bool = InputField(default=False)
-    image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
-
-    def run_processor(self, image: Image.Image) -> Image.Image:
-        onnx_det = self._context.models.download_and_cache_model(DWPOSE_MODELS["yolox_l.onnx"])
-        onnx_pose = self._context.models.download_and_cache_model(DWPOSE_MODELS["dw-ll_ucoco_384.onnx"])
-
-        dw_openpose = DWOpenposeDetector(onnx_det=onnx_det, onnx_pose=onnx_pose)
-        processed_image = dw_openpose(
-            image,
-            draw_face=self.draw_face,
-            draw_hands=self.draw_hands,
-            draw_body=self.draw_body,
-            resolution=self.image_resolution,
-        )
-        return processed_image
-
-
-@invocation(
-    "heuristic_resize",
-    title="Heuristic Resize",
-    tags=["image, controlnet"],
-    category="image",
-    version="1.0.1",
-    classification=Classification.Prototype,
-)
-class HeuristicResizeInvocation(BaseInvocation):
-    """Resize an image using a heuristic method. Preserves edge maps."""
-
-    image: ImageField = InputField(description="The image to resize")
-    width: int = InputField(default=512, ge=1, description="The width to resize to (px)")
-    height: int = InputField(default=512, ge=1, description="The height to resize to (px)")
-
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.images.get_pil(self.image.image_name, "RGB")
-        np_img = pil_to_np(image)
-        np_resized = heuristic_resize(np_img, (self.width, self.height))
-        resized = np_to_pil(np_resized)
-        image_dto = context.images.save(image=resized)
-        return ImageOutput.build(image_dto)

invokeai/app/invocations/denoise_latents.py

@@ -22,7 +22,7 @@ from transformers import CLIPVisionModelWithProjection
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
 from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
-from invokeai.app.invocations.controlnet_image_processors import ControlField
+from invokeai.app.invocations.controlnet import ControlField
 from invokeai.app.invocations.fields import (
     ConditioningField,
     DenoiseMaskField,

invokeai/app/invocations/dw_openpose.py

@@ -4,7 +4,7 @@ from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
 from invokeai.app.invocations.fields import ImageField, InputField, WithBoard, WithMetadata
 from invokeai.app.invocations.primitives import ImageOutput
 from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector2
+from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector
 
 
 @invocation(
@@ -25,20 +25,20 @@ class DWOpenposeDetectionInvocation(BaseInvocation, WithMetadata, WithBoard):
     def invoke(self, context: InvocationContext) -> ImageOutput:
         image = context.images.get_pil(self.image.image_name, "RGB")
 
-        onnx_det_path = context.models.download_and_cache_model(DWOpenposeDetector2.get_model_url_det())
-        onnx_pose_path = context.models.download_and_cache_model(DWOpenposeDetector2.get_model_url_pose())
+        onnx_det_path = context.models.download_and_cache_model(DWOpenposeDetector.get_model_url_det())
+        onnx_pose_path = context.models.download_and_cache_model(DWOpenposeDetector.get_model_url_pose())
 
         loaded_session_det = context.models.load_local_model(
-            onnx_det_path, DWOpenposeDetector2.create_onnx_inference_session
+            onnx_det_path, DWOpenposeDetector.create_onnx_inference_session
         )
         loaded_session_pose = context.models.load_local_model(
-            onnx_pose_path, DWOpenposeDetector2.create_onnx_inference_session
+            onnx_pose_path, DWOpenposeDetector.create_onnx_inference_session
         )
 
         with loaded_session_det as session_det, loaded_session_pose as session_pose:
             assert isinstance(session_det, ort.InferenceSession)
             assert isinstance(session_pose, ort.InferenceSession)
-            detector = DWOpenposeDetector2(session_det=session_det, session_pose=session_pose)
+            detector = DWOpenposeDetector(session_det=session_det, session_pose=session_pose)
             detected_image = detector.run(
                 image,
                 draw_face=self.draw_face,

invokeai/app/invocations/metadata_linked.py

@@ -14,7 +14,7 @@ from invokeai.app.invocations.baseinvocation import (
     invocation,
     invocation_output,
 )
-from invokeai.app.invocations.controlnet_image_processors import ControlField, ControlNetInvocation
+from invokeai.app.invocations.controlnet import ControlField, ControlNetInvocation
 from invokeai.app.invocations.denoise_latents import DenoiseLatentsInvocation
 from invokeai.app.invocations.fields import (
     FieldDescriptions,

invokeai/app/invocations/tiled_multi_diffusion_denoise_latents.py

@@ -9,7 +9,7 @@ from pydantic import field_validator
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
 from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
-from invokeai.app.invocations.controlnet_image_processors import ControlField
+from invokeai.app.invocations.controlnet import ControlField
 from invokeai.app.invocations.denoise_latents import DenoiseLatentsInvocation, get_scheduler
 from invokeai.app.invocations.fields import (
     ConditioningField,

invokeai/app/services/model_records/model_records_sql.py

@@ -302,7 +302,10 @@ class ModelRecordServiceSQL(ModelRecordServiceBase):
                 # We catch this error so that the app can still run if there are invalid model configs in the database.
                 # One reason that an invalid model config might be in the database is if someone had to rollback from a
                 # newer version of the app that added a new model type.
-                self._logger.warning(f"Found an invalid model config in the database. Ignoring this model. ({row[0]})")
+                row_data = f"{row[0][:64]}..." if len(row[0]) > 64 else row[0]
+                self._logger.warning(
+                    f"Found an invalid model config in the database. Ignoring this model. ({row_data})"
+                )
             else:
                 results.append(model_config)
 

invokeai/app/services/session_queue/session_queue_common.py

@@ -201,6 +201,12 @@ def get_workflow(queue_item_dict: dict) -> Optional[WorkflowWithoutID]:
     return None
 
 
+class FieldIdentifier(BaseModel):
+    kind: Literal["input", "output"] = Field(description="The kind of field")
+    node_id: str = Field(description="The ID of the node")
+    field_name: str = Field(description="The name of the field")
+
+
 class SessionQueueItemWithoutGraph(BaseModel):
     """Session queue item without the full graph. Used for serialization."""
 
@@ -237,6 +243,20 @@ class SessionQueueItemWithoutGraph(BaseModel):
     retried_from_item_id: Optional[int] = Field(
         default=None, description="The item_id of the queue item that this item was retried from"
     )
+    is_api_validation_run: bool = Field(
+        default=False,
+        description="Whether this queue item is an API validation run.",
+    )
+    published_workflow_id: Optional[str] = Field(
+        default=None,
+        description="The ID of the published workflow associated with this queue item",
+    )
+    api_input_fields: Optional[list[FieldIdentifier]] = Field(
+        default=None, description="The fields that were used as input to the API"
+    )
+    api_output_fields: Optional[list[FieldIdentifier]] = Field(
+        default=None, description="The nodes that were used as output from the API"
+    )
 
     @classmethod
     def queue_item_dto_from_dict(cls, queue_item_dict: dict) -> "SessionQueueItemDTO":

invokeai/app/services/workflow_records/workflow_records_base.py

@@ -47,6 +47,7 @@ class WorkflowRecordsStorageBase(ABC):
         query: Optional[str],
         tags: Optional[list[str]],
         has_been_opened: Optional[bool],
+        is_published: Optional[bool],
     ) -> PaginatedResults[WorkflowRecordListItemDTO]:
         """Gets many workflows."""
         pass
@@ -56,6 +57,7 @@ class WorkflowRecordsStorageBase(ABC):
         self,
         categories: list[WorkflowCategory],
         has_been_opened: Optional[bool] = None,
+        is_published: Optional[bool] = None,
     ) -> dict[str, int]:
         """Gets a dictionary of counts for each of the provided categories."""
         pass
@@ -66,6 +68,7 @@ class WorkflowRecordsStorageBase(ABC):
         tags: list[str],
         categories: Optional[list[WorkflowCategory]] = None,
         has_been_opened: Optional[bool] = None,
+        is_published: Optional[bool] = None,
     ) -> dict[str, int]:
         """Gets a dictionary of counts for each of the provided tags."""
         pass

invokeai/app/services/workflow_records/workflow_records_common.py

@@ -67,6 +67,7 @@ class WorkflowWithoutID(BaseModel):
     # This is typed as optional to prevent errors when pulling workflows from the DB. The frontend adds a default form if
     # it is None.
     form: dict[str, JsonValue] | None = Field(default=None, description="The form of the workflow.")
+    is_published: bool | None = Field(default=None, description="Whether the workflow is published or not.")
 
     model_config = ConfigDict(extra="ignore")
 
@@ -101,6 +102,7 @@ class WorkflowRecordDTOBase(BaseModel):
     opened_at: Optional[Union[datetime.datetime, str]] = Field(
         default=None, description="The opened timestamp of the workflow."
     )
+    is_published: bool | None = Field(default=None, description="Whether the workflow is published or not.")
 
 
 class WorkflowRecordDTO(WorkflowRecordDTOBase):

invokeai/app/services/workflow_records/workflow_records_sqlite.py

@@ -119,6 +119,7 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
         query: Optional[str] = None,
         tags: Optional[list[str]] = None,
         has_been_opened: Optional[bool] = None,
+        is_published: Optional[bool] = None,
     ) -> PaginatedResults[WorkflowRecordListItemDTO]:
         # sanitize!
         assert order_by in WorkflowRecordOrderBy
@@ -241,6 +242,7 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
         tags: list[str],
         categories: Optional[list[WorkflowCategory]] = None,
         has_been_opened: Optional[bool] = None,
+        is_published: Optional[bool] = None,
     ) -> dict[str, int]:
         if not tags:
             return {}
@@ -292,6 +294,7 @@ class SqliteWorkflowRecordsStorage(WorkflowRecordsStorageBase):
         self,
         categories: list[WorkflowCategory],
         has_been_opened: Optional[bool] = None,
+        is_published: Optional[bool] = None,
     ) -> dict[str, int]:
         cursor = self._conn.cursor()
         result: dict[str, int] = {}

invokeai/app/util/startup_utils.py

@@ -65,9 +65,6 @@ def apply_monkeypatches() -> None:
 
     import invokeai.backend.util.hotfixes  # noqa: F401 (monkeypatching on import)
 
-    if torch.backends.mps.is_available():
-        import invokeai.backend.util.mps_fixes  # noqa: F401 (monkeypatching on import)
-
 
 def register_mime_types() -> None:
     """Register additional mime types for windows."""

invokeai/backend/image_util/dw_openpose/__init__.py

@@ -5,62 +5,14 @@ import huggingface_hub
 import numpy as np
 import onnxruntime as ort
 import torch
-from controlnet_aux.util import resize_image
 from PIL import Image
 
 from invokeai.backend.image_util.dw_openpose.onnxdet import inference_detector
 from invokeai.backend.image_util.dw_openpose.onnxpose import inference_pose
 from invokeai.backend.image_util.dw_openpose.utils import NDArrayInt, draw_bodypose, draw_facepose, draw_handpose
-from invokeai.backend.image_util.dw_openpose.wholebody import Wholebody
 from invokeai.backend.image_util.util import np_to_pil
 from invokeai.backend.util.devices import TorchDevice
 
-DWPOSE_MODELS = {
-    "yolox_l.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true",
-    "dw-ll_ucoco_384.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true",
-}
-
-
-def draw_pose(
-    pose: Dict[str, NDArrayInt | Dict[str, NDArrayInt]],
-    H: int,
-    W: int,
-    draw_face: bool = True,
-    draw_body: bool = True,
-    draw_hands: bool = True,
-    resolution: int = 512,
-) -> Image.Image:
-    bodies = pose["bodies"]
-    faces = pose["faces"]
-    hands = pose["hands"]
-
-    assert isinstance(bodies, dict)
-    candidate = bodies["candidate"]
-
-    assert isinstance(bodies, dict)
-    subset = bodies["subset"]
-
-    canvas = np.zeros(shape=(H, W, 3), dtype=np.uint8)
-
-    if draw_body:
-        canvas = draw_bodypose(canvas, candidate, subset)
-
-    if draw_hands:
-        assert isinstance(hands, np.ndarray)
-        canvas = draw_handpose(canvas, hands)
-
-    if draw_face:
-        assert isinstance(hands, np.ndarray)
-        canvas = draw_facepose(canvas, faces)  # type: ignore
-
-    dwpose_image: Image.Image = resize_image(
-        canvas,
-        resolution,
-    )
-    dwpose_image = Image.fromarray(dwpose_image)
-
-    return dwpose_image
-
 
 class DWOpenposeDetector:
     """
@@ -68,62 +20,6 @@ class DWOpenposeDetector:
     Credits: https://github.com/IDEA-Research/DWPose
     """
 
-    def __init__(self, onnx_det: Path, onnx_pose: Path) -> None:
-        self.pose_estimation = Wholebody(onnx_det=onnx_det, onnx_pose=onnx_pose)
-
-    def __call__(
-        self,
-        image: Image.Image,
-        draw_face: bool = False,
-        draw_body: bool = True,
-        draw_hands: bool = False,
-        resolution: int = 512,
-    ) -> Image.Image:
-        np_image = np.array(image)
-        H, W, C = np_image.shape
-
-        with torch.no_grad():
-            candidate, subset = self.pose_estimation(np_image)
-            nums, keys, locs = candidate.shape
-            candidate[..., 0] /= float(W)
-            candidate[..., 1] /= float(H)
-            body = candidate[:, :18].copy()
-            body = body.reshape(nums * 18, locs)
-            score = subset[:, :18]
-            for i in range(len(score)):
-                for j in range(len(score[i])):
-                    if score[i][j] > 0.3:
-                        score[i][j] = int(18 * i + j)
-                    else:
-                        score[i][j] = -1
-
-            un_visible = subset < 0.3
-            candidate[un_visible] = -1
-
-            # foot = candidate[:, 18:24]
-
-            faces = candidate[:, 24:92]
-
-            hands = candidate[:, 92:113]
-            hands = np.vstack([hands, candidate[:, 113:]])
-
-            bodies = {"candidate": body, "subset": score}
-            pose = {"bodies": bodies, "hands": hands, "faces": faces}
-
-            return draw_pose(
-                pose, H, W, draw_face=draw_face, draw_hands=draw_hands, draw_body=draw_body, resolution=resolution
-            )
-
-
-class DWOpenposeDetector2:
-    """
-    Code from the original implementation of the DW Openpose Detector.
-    Credits: https://github.com/IDEA-Research/DWPose
-
-    This implementation is similar to DWOpenposeDetector, with some alterations to allow the onnx models to be loaded
-    and managed by the model manager.
-    """
-
     hf_repo_id = "yzd-v/DWPose"
     hf_filename_onnx_det = "yolox_l.onnx"
     hf_filename_onnx_pose = "dw-ll_ucoco_384.onnx"
@@ -213,7 +109,7 @@ class DWOpenposeDetector2:
             bodies = {"candidate": body, "subset": score}
             pose = {"bodies": bodies, "hands": hands, "faces": faces}
 
-            return DWOpenposeDetector2.draw_pose(
+            return DWOpenposeDetector.draw_pose(
                 pose, H, W, draw_face=draw_face, draw_hands=draw_hands, draw_body=draw_body
             )
 

invokeai/backend/image_util/dw_openpose/utils.py

@@ -3,7 +3,6 @@
 import math
 
 import cv2
-import matplotlib
 import numpy as np
 import numpy.typing as npt
 
@@ -127,11 +126,13 @@ def draw_handpose(canvas: NDArrayInt, all_hand_peaks: NDArrayInt) -> NDArrayInt:
             x2 = int(x2 * W)
             y2 = int(y2 * H)
             if x1 > eps and y1 > eps and x2 > eps and y2 > eps:
+                hsv_color = np.array([[[ie / float(len(edges)) * 180, 255, 255]]], dtype=np.uint8)
+                rgb_color = cv2.cvtColor(hsv_color, cv2.COLOR_HSV2RGB)[0, 0]
                 cv2.line(
                     canvas,
                     (x1, y1),
                     (x2, y2),
-                    matplotlib.colors.hsv_to_rgb([ie / float(len(edges)), 1.0, 1.0]) * 255,
+                    rgb_color.tolist(),
                     thickness=2,
                 )
 

invokeai/backend/image_util/dw_openpose/wholebody.py

@@ -1,44 +0,0 @@
-# Code from the original DWPose Implementation: https://github.com/IDEA-Research/DWPose
-# Modified pathing to suit Invoke
-
-
-from pathlib import Path
-
-import numpy as np
-import onnxruntime as ort
-
-from invokeai.app.services.config.config_default import get_config
-from invokeai.backend.image_util.dw_openpose.onnxdet import inference_detector
-from invokeai.backend.image_util.dw_openpose.onnxpose import inference_pose
-from invokeai.backend.util.devices import TorchDevice
-
-config = get_config()
-
-
-class Wholebody:
-    def __init__(self, onnx_det: Path, onnx_pose: Path):
-        device = TorchDevice.choose_torch_device()
-
-        providers = ["CUDAExecutionProvider"] if device.type == "cuda" else ["CPUExecutionProvider"]
-
-        self.session_det = ort.InferenceSession(path_or_bytes=onnx_det, providers=providers)
-        self.session_pose = ort.InferenceSession(path_or_bytes=onnx_pose, providers=providers)
-
-    def __call__(self, oriImg):
-        det_result = inference_detector(self.session_det, oriImg)
-        keypoints, scores = inference_pose(self.session_pose, det_result, oriImg)
-
-        keypoints_info = np.concatenate((keypoints, scores[..., None]), axis=-1)
-        # compute neck joint
-        neck = np.mean(keypoints_info[:, [5, 6]], axis=1)
-        # neck score when visualizing pred
-        neck[:, 2:4] = np.logical_and(keypoints_info[:, 5, 2:4] > 0.3, keypoints_info[:, 6, 2:4] > 0.3).astype(int)
-        new_keypoints_info = np.insert(keypoints_info, 17, neck, axis=1)
-        mmpose_idx = [17, 6, 8, 10, 7, 9, 12, 14, 16, 13, 15, 2, 1, 4, 3]
-        openpose_idx = [1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17]
-        new_keypoints_info[:, openpose_idx] = new_keypoints_info[:, mmpose_idx]
-        keypoints_info = new_keypoints_info
-
-        keypoints, scores = keypoints_info[..., :2], keypoints_info[..., 2]
-
-        return keypoints, scores

invokeai/backend/util/mps_fixes.py

@@ -1,245 +0,0 @@
-import math
-
-import diffusers
-import torch
-
-if torch.backends.mps.is_available():
-    torch.empty = torch.zeros
-
-
-_torch_layer_norm = torch.nn.functional.layer_norm
-
-
-def new_layer_norm(input, normalized_shape, weight=None, bias=None, eps=1e-05):
-    if input.device.type == "mps" and input.dtype == torch.float16:
-        input = input.float()
-        if weight is not None:
-            weight = weight.float()
-        if bias is not None:
-            bias = bias.float()
-        return _torch_layer_norm(input, normalized_shape, weight, bias, eps).half()
-    else:
-        return _torch_layer_norm(input, normalized_shape, weight, bias, eps)
-
-
-torch.nn.functional.layer_norm = new_layer_norm
-
-
-_torch_tensor_permute = torch.Tensor.permute
-
-
-def new_torch_tensor_permute(input, *dims):
-    result = _torch_tensor_permute(input, *dims)
-    if input.device == "mps" and input.dtype == torch.float16:
-        result = result.contiguous()
-    return result
-
-
-torch.Tensor.permute = new_torch_tensor_permute
-
-
-_torch_lerp = torch.lerp
-
-
-def new_torch_lerp(input, end, weight, *, out=None):
-    if input.device.type == "mps" and input.dtype == torch.float16:
-        input = input.float()
-        end = end.float()
-        if isinstance(weight, torch.Tensor):
-            weight = weight.float()
-        if out is not None:
-            out_fp32 = torch.zeros_like(out, dtype=torch.float32)
-        else:
-            out_fp32 = None
-        result = _torch_lerp(input, end, weight, out=out_fp32)
-        if out is not None:
-            out.copy_(out_fp32.half())
-            del out_fp32
-        return result.half()
-
-    else:
-        return _torch_lerp(input, end, weight, out=out)
-
-
-torch.lerp = new_torch_lerp
-
-
-_torch_interpolate = torch.nn.functional.interpolate
-
-
-def new_torch_interpolate(
-    input,
-    size=None,
-    scale_factor=None,
-    mode="nearest",
-    align_corners=None,
-    recompute_scale_factor=None,
-    antialias=False,
-):
-    if input.device.type == "mps" and input.dtype == torch.float16:
-        return _torch_interpolate(
-            input.float(), size, scale_factor, mode, align_corners, recompute_scale_factor, antialias
-        ).half()
-    else:
-        return _torch_interpolate(input, size, scale_factor, mode, align_corners, recompute_scale_factor, antialias)
-
-
-torch.nn.functional.interpolate = new_torch_interpolate
-
-# TODO: refactor it
-_SlicedAttnProcessor = diffusers.models.attention_processor.SlicedAttnProcessor
-
-
-class ChunkedSlicedAttnProcessor:
-    r"""
-    Processor for implementing sliced attention.
-
-    Args:
-        slice_size (`int`, *optional*):
-            The number of steps to compute attention. Uses as many slices as `attention_head_dim // slice_size`, and
-            `attention_head_dim` must be a multiple of the `slice_size`.
-    """
-
-    def __init__(self, slice_size):
-        assert isinstance(slice_size, int)
-        slice_size = 1  # TODO: maybe implement chunking in batches too when enough memory
-        self.slice_size = slice_size
-        self._sliced_attn_processor = _SlicedAttnProcessor(slice_size)
-
-    def __call__(self, attn, hidden_states, encoder_hidden_states=None, attention_mask=None):
-        if self.slice_size != 1 or attn.upcast_attention:
-            return self._sliced_attn_processor(attn, hidden_states, encoder_hidden_states, attention_mask)
-
-        residual = hidden_states
-
-        input_ndim = hidden_states.ndim
-
-        if input_ndim == 4:
-            batch_size, channel, height, width = hidden_states.shape
-            hidden_states = hidden_states.view(batch_size, channel, height * width).transpose(1, 2)
-
-        batch_size, sequence_length, _ = (
-            hidden_states.shape if encoder_hidden_states is None else encoder_hidden_states.shape
-        )
-        attention_mask = attn.prepare_attention_mask(attention_mask, sequence_length, batch_size)
-
-        if attn.group_norm is not None:
-            hidden_states = attn.group_norm(hidden_states.transpose(1, 2)).transpose(1, 2)
-
-        query = attn.to_q(hidden_states)
-        dim = query.shape[-1]
-        query = attn.head_to_batch_dim(query)
-
-        if encoder_hidden_states is None:
-            encoder_hidden_states = hidden_states
-        elif attn.norm_cross:
-            encoder_hidden_states = attn.norm_encoder_hidden_states(encoder_hidden_states)
-
-        key = attn.to_k(encoder_hidden_states)
-        value = attn.to_v(encoder_hidden_states)
-        key = attn.head_to_batch_dim(key)
-        value = attn.head_to_batch_dim(value)
-
-        batch_size_attention, query_tokens, _ = query.shape
-        hidden_states = torch.zeros(
-            (batch_size_attention, query_tokens, dim // attn.heads), device=query.device, dtype=query.dtype
-        )
-
-        chunk_tmp_tensor = torch.empty(
-            self.slice_size, query.shape[1], key.shape[1], dtype=query.dtype, device=query.device
-        )
-
-        for i in range(batch_size_attention // self.slice_size):
-            start_idx = i * self.slice_size
-            end_idx = (i + 1) * self.slice_size
-
-            query_slice = query[start_idx:end_idx]
-            key_slice = key[start_idx:end_idx]
-            attn_mask_slice = attention_mask[start_idx:end_idx] if attention_mask is not None else None
-
-            self.get_attention_scores_chunked(
-                attn,
-                query_slice,
-                key_slice,
-                attn_mask_slice,
-                hidden_states[start_idx:end_idx],
-                value[start_idx:end_idx],
-                chunk_tmp_tensor,
-            )
-
-        hidden_states = attn.batch_to_head_dim(hidden_states)
-
-        # linear proj
-        hidden_states = attn.to_out[0](hidden_states)
-        # dropout
-        hidden_states = attn.to_out[1](hidden_states)
-
-        if input_ndim == 4:
-            hidden_states = hidden_states.transpose(-1, -2).reshape(batch_size, channel, height, width)
-
-        if attn.residual_connection:
-            hidden_states = hidden_states + residual
-
-        hidden_states = hidden_states / attn.rescale_output_factor
-
-        return hidden_states
-
-    def get_attention_scores_chunked(self, attn, query, key, attention_mask, hidden_states, value, chunk):
-        # batch size = 1
-        assert query.shape[0] == 1
-        assert key.shape[0] == 1
-        assert value.shape[0] == 1
-        assert hidden_states.shape[0] == 1
-
-        # dtype = query.dtype
-        if attn.upcast_attention:
-            query = query.float()
-            key = key.float()
-
-        # out_item_size = query.dtype.itemsize
-        # if attn.upcast_attention:
-        #    out_item_size = torch.float32.itemsize
-        out_item_size = query.element_size()
-        if attn.upcast_attention:
-            out_item_size = 4
-
-        chunk_size = 2**29
-
-        out_size = query.shape[1] * key.shape[1] * out_item_size
-        chunks_count = min(query.shape[1], math.ceil((out_size - 1) / chunk_size))
-        chunk_step = max(1, int(query.shape[1] / chunks_count))
-
-        key = key.transpose(-1, -2)
-
-        def _get_chunk_view(tensor, start, length):
-            if start + length > tensor.shape[1]:
-                length = tensor.shape[1] - start
-            # print(f"view: [{tensor.shape[0]},{tensor.shape[1]},{tensor.shape[2]}] - start: {start}, length: {length}")
-            return tensor[:, start : start + length]
-
-        for chunk_pos in range(0, query.shape[1], chunk_step):
-            if attention_mask is not None:
-                torch.baddbmm(
-                    _get_chunk_view(attention_mask, chunk_pos, chunk_step),
-                    _get_chunk_view(query, chunk_pos, chunk_step),
-                    key,
-                    beta=1,
-                    alpha=attn.scale,
-                    out=chunk,
-                )
-            else:
-                torch.baddbmm(
-                    torch.zeros((1, 1, 1), device=query.device, dtype=query.dtype),
-                    _get_chunk_view(query, chunk_pos, chunk_step),
-                    key,
-                    beta=0,
-                    alpha=attn.scale,
-                    out=chunk,
-                )
-            chunk = chunk.softmax(dim=-1)
-            torch.bmm(chunk, value, out=_get_chunk_view(hidden_states, chunk_pos, chunk_step))
-
-        # del chunk
-
-
-diffusers.models.attention_processor.SlicedAttnProcessor = ChunkedSlicedAttnProcessor

invokeai/frontend/web/package.json

@@ -150,7 +150,7 @@
     "prettier": "^3.3.3",
     "rollup-plugin-visualizer": "^5.12.0",
     "storybook": "^8.3.4",
-    "tsafe": "^1.7.5",
+    "tsafe": "^1.8.5",
     "type-fest": "^4.26.1",
     "typescript": "^5.6.2",
     "vite": "^6.1.0",

invokeai/frontend/web/pnpm-lock.yaml

@@ -284,8 +284,8 @@ devDependencies:
     specifier: ^8.3.4
     version: 8.3.4
   tsafe:
-    specifier: ^1.7.5
-    version: 1.7.5
+    specifier: ^1.8.5
+    version: 1.8.5
   type-fest:
     specifier: ^4.26.1
     version: 4.26.1
@@ -8791,8 +8791,8 @@ packages:
     resolution: {integrity: sha512-tLJxacIQUM82IR7JO1UUkKlYuUTmoY9HBJAmNWFzheSlDS5SPMcNIepejHJa4BpPQLAcbRhRf3GDJzyj6rbKvA==}
     dev: false
 
-  /tsafe@1.7.5:
-    resolution: {integrity: sha512-tbNyyBSbwfbilFfiuXkSOj82a6++ovgANwcoqBAcO9/REPoZMEQoE8kWPeO0dy5A2D/2Lajr8Ohue5T0ifIvLQ==}
+  /tsafe@1.8.5:
+    resolution: {integrity: sha512-LFWTWQrW6rwSY+IBNFl2ridGfUzVsPwrZ26T4KUJww/py8rzaQ/SY+MIz6YROozpUCaRcuISqagmlwub9YT9kw==}
     dev: true
 
   /tsconfck@3.1.5(typescript@5.6.2):

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

@@ -1706,6 +1706,7 @@
         "noRecentWorkflows": "No Recent Workflows",
         "private": "Private",
         "shared": "Shared",
+        "published": "Published",
         "browseWorkflows": "Browse Workflows",
         "deselectAll": "Deselect All",
         "recommended": "Recommended For You",
@@ -1783,7 +1784,39 @@
             "textPlaceholder": "Empty Text",
             "workflowBuilderAlphaWarning": "The workflow builder is currently in alpha. There may be breaking changes before the stable release.",
             "minimum": "Minimum",
-            "maximum": "Maximum"
+            "maximum": "Maximum",
+            "publish": "Publish",
+            "published": "Published",
+            "unpublish": "Unpublish",
+            "workflowLocked": "Workflow Locked",
+            "workflowLockedPublished": "Published workflows are locked for editing.\nYou can unpublish the workflow to edit it, or make a copy of it.",
+            "workflowLockedDuringPublishing": "Workflow is locked while configuring for publishing.",
+            "selectOutputNode": "Select Output Node",
+            "changeOutputNode": "Change Output Node",
+            "publishedWorkflowOutputs": "Outputs",
+            "publishedWorkflowInputs": "Inputs",
+            "unpublishableInputs": "These unpublishable inputs will be omitted",
+            "noPublishableInputs": "No publishable inputs",
+            "noOutputNodeSelected": "No output node selected",
+            "cannotPublish": "Cannot publish workflow",
+            "publishWarnings": "Warnings",
+            "errorWorkflowHasUnsavedChanges": "Workflow has unsaved changes",
+            "errorWorkflowHasBatchOrGeneratorNodes": "Workflow has batch and/or generator nodes",
+            "errorWorkflowHasInvalidGraph": "Workflow graph invalid (hover Invoke button for details)",
+            "errorWorkflowHasNoOutputNode": "No output node selected",
+            "warningWorkflowHasNoPublishableInputFields": "No publishable input fields selected - published workflow will run with only default values",
+            "warningWorkflowHasUnpublishableInputFields": "Workflow has some unpublishable inputs - these will be omitted from the published workflow",
+            "publishFailed": "Publish failed",
+            "publishFailedDesc": "There was a problem publishing the workflow. Please try again.",
+            "publishSuccess": "Your workflow is being published",
+            "publishSuccessDesc": "Check your <LinkComponent>Project Dashboard</LinkComponent> to see its progress.",
+            "publishInProgress": "Publishing in progress",
+            "publishedWorkflowIsLocked": "Published workflow is locked",
+            "publishingValidationRun": "Publishing Validation Run",
+            "publishingValidationRunInProgress": "Publishing validation run in progress.",
+            "publishedWorkflowsLocked": "Published workflows are locked and cannot be edited or run. Either unpublish the workflow or save a copy to edit or run this workflow.",
+            "selectingOutputNode": "Selecting output node",
+            "selectingOutputNodeDesc": "Click a node to select it as the workflow's output node."
         }
     },
     "controlLayers": {

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

@@ -1,7 +0,0 @@
-import { createAction } from '@reduxjs/toolkit';
-import type { TabName } from 'features/ui/store/uiTypes';
-
-export const enqueueRequested = createAction<{
-  tabName: TabName;
-  prepend: boolean;
-}>('app/enqueueRequested');

invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/index.ts

@@ -10,7 +10,6 @@ import { addDeleteBoardAndImagesFulfilledListener } from 'app/store/middleware/l
 import { addBoardIdSelectedListener } from 'app/store/middleware/listenerMiddleware/listeners/boardIdSelected';
 import { addBulkDownloadListeners } from 'app/store/middleware/listenerMiddleware/listeners/bulkDownload';
 import { addEnqueueRequestedLinear } from 'app/store/middleware/listenerMiddleware/listeners/enqueueRequestedLinear';
-import { addEnqueueRequestedNodes } from 'app/store/middleware/listenerMiddleware/listeners/enqueueRequestedNodes';
 import { addGalleryImageClickedListener } from 'app/store/middleware/listenerMiddleware/listeners/galleryImageClicked';
 import { addGalleryOffsetChangedListener } from 'app/store/middleware/listenerMiddleware/listeners/galleryOffsetChanged';
 import { addGetOpenAPISchemaListener } from 'app/store/middleware/listenerMiddleware/listeners/getOpenAPISchema';
@@ -63,7 +62,6 @@ addGalleryImageClickedListener(startAppListening);
 addGalleryOffsetChangedListener(startAppListening);
 
 // User Invoked
-addEnqueueRequestedNodes(startAppListening);
 addEnqueueRequestedLinear(startAppListening);
 addEnqueueRequestedUpscale(startAppListening);
 addAnyEnqueuedListener(startAppListening);

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

@@ -5,7 +5,7 @@ import { buildAdHocPostProcessingGraph } from 'features/nodes/util/graph/buildAd
 import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { enqueueMutationFixedCacheKeyOptions, queueApi } from 'services/api/endpoints/queue';
-import type { BatchConfig, ImageDTO } from 'services/api/types';
+import type { EnqueueBatchArg, ImageDTO } from 'services/api/types';
 import type { JsonObject } from 'type-fest';
 
 const log = logger('queue');
@@ -19,7 +19,7 @@ export const addAdHocPostProcessingRequestedListener = (startAppListening: AppSt
       const { imageDTO } = action.payload;
       const state = getState();
 
-      const enqueueBatchArg: BatchConfig = {
+      const enqueueBatchArg: EnqueueBatchArg = {
         prepend: true,
         batch: {
           graph: await buildAdHocPostProcessingGraph({

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

@@ -1,5 +1,5 @@
+import { createAction } from '@reduxjs/toolkit';
 import { logger } from 'app/logging/logger';
-import { enqueueRequested } from 'app/store/actions';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { extractMessageFromAssertionError } from 'common/util/extractMessageFromAssertionError';
 import { withResult, withResultAsync } from 'common/util/result';
@@ -17,10 +17,11 @@ import { assert, AssertionError } from 'tsafe';
 
 const log = logger('generation');
 
+export const enqueueRequestedCanvas = createAction<{ prepend: boolean }>('app/enqueueRequestedCanvas');
+
 export const addEnqueueRequestedLinear = (startAppListening: AppStartListening) => {
   startAppListening({
-    predicate: (action): action is ReturnType<typeof enqueueRequested> =>
-      enqueueRequested.match(action) && action.payload.tabName === 'canvas',
+    actionCreator: enqueueRequestedCanvas,
     effect: async (action, { getState, dispatch }) => {
       log.debug('Enqueue requested');
       const state = getState();

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

@@ -1,5 +1,5 @@
+import { createAction } from '@reduxjs/toolkit';
 import { logger } from 'app/logging/logger';
-import { enqueueRequested } from 'app/store/actions';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { prepareLinearUIBatch } from 'features/nodes/util/graph/buildLinearBatchConfig';
@@ -9,10 +9,11 @@ import { enqueueMutationFixedCacheKeyOptions, queueApi } from 'services/api/endp
 
 const log = logger('generation');
 
+export const enqueueRequestedUpscaling = createAction<{ prepend: boolean }>('app/enqueueRequestedUpscaling');
+
 export const addEnqueueRequestedUpscale = (startAppListening: AppStartListening) => {
   startAppListening({
-    predicate: (action): action is ReturnType<typeof enqueueRequested> =>
-      enqueueRequested.match(action) && action.payload.tabName === 'upscaling',
+    actionCreator: enqueueRequestedUpscaling,
     effect: async (action, { getState, dispatch }) => {
       const state = getState();
       const { prepend } = action.payload;

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

@@ -3,6 +3,7 @@ import { autoBatchEnhancer, combineReducers, configureStore } from '@reduxjs/too
 import { logger } from 'app/logging/logger';
 import { idbKeyValDriver } from 'app/store/enhancers/reduxRemember/driver';
 import { errorHandler } from 'app/store/enhancers/reduxRemember/errors';
+import { getDebugLoggerMiddleware } from 'app/store/middleware/debugLoggerMiddleware';
 import { deepClone } from 'common/util/deepClone';
 import { changeBoardModalSlice } from 'features/changeBoardModal/store/slice';
 import { canvasSettingsPersistConfig, canvasSettingsSlice } from 'features/controlLayers/store/canvasSettingsSlice';
@@ -175,6 +176,7 @@ export const createStore = (uniqueStoreKey?: string, persist = true) =>
         .concat(api.middleware)
         .concat(dynamicMiddlewares)
         .concat(authToastMiddleware)
+        .concat(getDebugLoggerMiddleware())
         .prepend(listenerMiddleware.middleware),
     enhancers: (getDefaultEnhancers) => {
       const _enhancers = getDefaultEnhancers().concat(autoBatchEnhancer());

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

@@ -74,6 +74,7 @@ export type AppConfig = {
   allowPrivateBoards: boolean;
   allowPrivateStylePresets: boolean;
   allowClientSideUpload: boolean;
+  allowPublishWorkflows: boolean;
   disabledTabs: TabName[];
   disabledFeatures: AppFeature[];
   disabledSDFeatures: SDFeature[];

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

@@ -14,7 +14,7 @@ export const useGlobalHotkeys = () => {
   useRegisteredHotkeys({
     id: 'invoke',
     category: 'app',
-    callback: queue.queueBack,
+    callback: queue.enqueueBack,
     options: {
       enabled: !queue.isDisabled && !queue.isLoading,
       preventDefault: true,
@@ -26,7 +26,7 @@ export const useGlobalHotkeys = () => {
   useRegisteredHotkeys({
     id: 'invokeFront',
     category: 'app',
-    callback: queue.queueFront,
+    callback: queue.enqueueFront,
     options: {
       enabled: !queue.isDisabled && !queue.isLoading,
       preventDefault: true,

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

@@ -54,7 +54,7 @@ import { atom, computed } from 'nanostores';
 import type { Logger } from 'roarr';
 import { getImageDTO } from 'services/api/endpoints/images';
 import { enqueueMutationFixedCacheKeyOptions, queueApi } from 'services/api/endpoints/queue';
-import type { BatchConfig, ImageDTO, S } from 'services/api/types';
+import type { EnqueueBatchArg, ImageDTO, S } from 'services/api/types';
 import { QueueError } from 'services/events/errors';
 import type { Param0 } from 'tsafe';
 import { assert } from 'tsafe';
@@ -291,7 +291,7 @@ export class CanvasStateApiModule extends CanvasModuleBase {
      */
     const origin = getPrefixedId(graph.id);
 
-    const batch: BatchConfig = {
+    const batch: EnqueueBatchArg = {
       prepend,
       batch: {
         graph: graph.getGraph(),

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

@@ -2,7 +2,9 @@ import type { SystemStyleObject } from '@invoke-ai/ui-library';
 import { FocusRegionWrapper } from 'common/components/FocusRegionWrapper';
 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 { TopCenterPanel } from 'features/nodes/components/flow/panels/TopPanel/TopCenterPanel';
+import { TopLeftPanel } from 'features/nodes/components/flow/panels/TopPanel/TopLeftPanel';
+import { TopRightPanel } from 'features/nodes/components/flow/panels/TopPanel/TopRightPanel';
 import WorkflowEditorSettings from 'features/nodes/components/flow/panels/TopRightPanel/WorkflowEditorSettings';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -32,7 +34,9 @@ const NodeEditor = () => {
         <>
           <Flow />
           <AddNodeCmdk />
-          <TopPanel />
+          <TopLeftPanel />
+          <TopCenterPanel />
+          <TopRightPanel />
           <BottomLeftPanel />
           <MinimapPanel />
         </>

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

@@ -18,6 +18,7 @@ import { CommandEmpty, CommandItem, CommandList, CommandRoot } from 'cmdk';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import { useBuildNode } from 'features/nodes/hooks/useBuildNode';
+import { useIsWorkflowEditorLocked } from 'features/nodes/hooks/useIsWorkflowEditorLocked';
 import {
   $addNodeCmdk,
   $cursorPos,
@@ -146,6 +147,7 @@ export const AddNodeCmdk = memo(() => {
   const [searchTerm, setSearchTerm] = useState('');
   const addNode = useAddNode();
   const tab = useAppSelector(selectActiveTab);
+  const isLocked = useIsWorkflowEditorLocked();
   // Filtering the list is expensive - debounce the search term to avoid stutters
   const [debouncedSearchTerm] = useDebounce(searchTerm, 300);
   const isOpen = useStore($addNodeCmdk);
@@ -160,8 +162,8 @@ export const AddNodeCmdk = memo(() => {
     id: 'addNode',
     category: 'workflows',
     callback: open,
-    options: { enabled: tab === 'workflows', preventDefault: true },
-    dependencies: [open, tab],
+    options: { enabled: tab === 'workflows' && !isLocked, preventDefault: true },
+    dependencies: [open, tab, isLocked],
   });
 
   const onChange = useCallback((e: ChangeEvent<HTMLInputElement>) => {

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

@@ -4,6 +4,7 @@ import type {
   EdgeChange,
   HandleType,
   NodeChange,
+  NodeMouseHandler,
   OnEdgesChange,
   OnInit,
   OnMoveEnd,
@@ -16,8 +17,10 @@ import type {
 import { Background, ReactFlow, useStore as useReactFlowStore, useUpdateNodeInternals } from '@xyflow/react';
 import { useAppDispatch, useAppSelector, useAppStore } from 'app/store/storeHooks';
 import { useFocusRegion, useIsRegionFocused } from 'common/hooks/focus';
+import { $isSelectingOutputNode, $outputNodeId } from 'features/nodes/components/sidePanel/workflow/publish';
 import { useConnection } from 'features/nodes/hooks/useConnection';
 import { useIsValidConnection } from 'features/nodes/hooks/useIsValidConnection';
+import { useIsWorkflowEditorLocked } from 'features/nodes/hooks/useIsWorkflowEditorLocked';
 import { useNodeCopyPaste } from 'features/nodes/hooks/useNodeCopyPaste';
 import { useSyncExecutionState } from 'features/nodes/hooks/useNodeExecutionState';
 import {
@@ -44,7 +47,7 @@ import {
 import { connectionToEdge } from 'features/nodes/store/util/reactFlowUtil';
 import { selectSelectionMode, selectShouldSnapToGrid } from 'features/nodes/store/workflowSettingsSlice';
 import { NO_DRAG_CLASS, NO_PAN_CLASS, NO_WHEEL_CLASS } from 'features/nodes/types/constants';
-import type { AnyEdge, AnyNode } from 'features/nodes/types/invocation';
+import { type AnyEdge, type AnyNode, isInvocationNode } from 'features/nodes/types/invocation';
 import { useRegisteredHotkeys } from 'features/system/components/HotkeysModal/useHotkeyData';
 import type { CSSProperties, MouseEvent } from 'react';
 import { memo, useCallback, useMemo, useRef } from 'react';
@@ -92,6 +95,8 @@ export const Flow = memo(() => {
   const updateNodeInternals = useUpdateNodeInternals();
   const store = useAppStore();
   const isWorkflowsFocused = useIsRegionFocused('workflows');
+  const isLocked = useIsWorkflowEditorLocked();
+
   useFocusRegion('workflows', flowWrapper);
 
   useSyncExecutionState();
@@ -215,7 +220,7 @@ export const Flow = memo(() => {
     id: 'copySelection',
     category: 'workflows',
     callback: copySelection,
-    options: { preventDefault: true },
+    options: { enabled: isWorkflowsFocused && !isLocked, preventDefault: true },
     dependencies: [copySelection],
   });
 
@@ -244,24 +249,24 @@ export const Flow = memo(() => {
     id: 'selectAll',
     category: 'workflows',
     callback: selectAll,
-    options: { enabled: isWorkflowsFocused, preventDefault: true },
-    dependencies: [selectAll, isWorkflowsFocused],
+    options: { enabled: isWorkflowsFocused && !isLocked, preventDefault: true },
+    dependencies: [selectAll, isWorkflowsFocused, isLocked],
   });
 
   useRegisteredHotkeys({
     id: 'pasteSelection',
     category: 'workflows',
     callback: pasteSelection,
-    options: { enabled: isWorkflowsFocused, preventDefault: true },
-    dependencies: [pasteSelection],
+    options: { enabled: isWorkflowsFocused && !isLocked, preventDefault: true },
+    dependencies: [pasteSelection, isLocked, isWorkflowsFocused],
   });
 
   useRegisteredHotkeys({
     id: 'pasteSelectionWithEdges',
     category: 'workflows',
     callback: pasteSelectionWithEdges,
-    options: { enabled: isWorkflowsFocused, preventDefault: true },
-    dependencies: [pasteSelectionWithEdges],
+    options: { enabled: isWorkflowsFocused && !isLocked, preventDefault: true },
+    dependencies: [pasteSelectionWithEdges, isLocked, isWorkflowsFocused],
   });
 
   useRegisteredHotkeys({
@@ -270,8 +275,8 @@ export const Flow = memo(() => {
     callback: () => {
       dispatch(undo());
     },
-    options: { enabled: isWorkflowsFocused && mayUndo, preventDefault: true },
-    dependencies: [mayUndo],
+    options: { enabled: isWorkflowsFocused && !isLocked && mayUndo, preventDefault: true },
+    dependencies: [mayUndo, isLocked, isWorkflowsFocused],
   });
 
   useRegisteredHotkeys({
@@ -280,8 +285,8 @@ export const Flow = memo(() => {
     callback: () => {
       dispatch(redo());
     },
-    options: { enabled: isWorkflowsFocused && mayRedo, preventDefault: true },
-    dependencies: [mayRedo],
+    options: { enabled: isWorkflowsFocused && !isLocked && mayRedo, preventDefault: true },
+    dependencies: [mayRedo, isLocked, isWorkflowsFocused],
   });
 
   const onEscapeHotkey = useCallback(() => {
@@ -318,10 +323,22 @@ export const Flow = memo(() => {
     id: 'deleteSelection',
     category: 'workflows',
     callback: deleteSelection,
-    options: { preventDefault: true, enabled: isWorkflowsFocused },
-    dependencies: [deleteSelection, isWorkflowsFocused],
+    options: { preventDefault: true, enabled: isWorkflowsFocused && !isLocked },
+    dependencies: [deleteSelection, isWorkflowsFocused, isLocked],
   });
 
+  const onNodeClick = useCallback<NodeMouseHandler<AnyNode>>((e, node) => {
+    if (!$isSelectingOutputNode.get()) {
+      return;
+    }
+    if (!isInvocationNode(node)) {
+      return;
+    }
+    const { id } = node.data;
+    $outputNodeId.set(id);
+    $isSelectingOutputNode.set(false);
+  }, []);
+
   return (
     <ReactFlow<AnyNode, AnyEdge>
       id="workflow-editor"
@@ -332,6 +349,7 @@ export const Flow = memo(() => {
       nodes={nodes}
       edges={edges}
       onInit={onInit}
+      onNodeClick={onNodeClick}
       onMouseMove={onMouseMove}
       onNodesChange={onNodesChange}
       onEdgesChange={onEdgesChange}
@@ -344,6 +362,12 @@ export const Flow = memo(() => {
       onMoveEnd={handleMoveEnd}
       connectionLineComponent={CustomConnectionLine}
       isValidConnection={isValidConnection}
+      edgesFocusable={!isLocked}
+      edgesReconnectable={!isLocked}
+      nodesDraggable={!isLocked}
+      nodesConnectable={!isLocked}
+      nodesFocusable={!isLocked}
+      elementsSelectable={!isLocked}
       minZoom={0.1}
       snapToGrid={shouldSnapToGrid}
       snapGrid={snapGrid}

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

@@ -1,5 +1,5 @@
 import { Handle, Position } from '@xyflow/react';
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
+import { useNodeTemplateOrThrow } from 'features/nodes/hooks/useNodeTemplateOrThrow';
 import { map } from 'lodash-es';
 import type { CSSProperties } from 'react';
 import { memo } from 'react';
@@ -19,7 +19,7 @@ const collapsedHandleStyles: CSSProperties = {
 };
 
 const InvocationNodeCollapsedHandles = ({ nodeId }: Props) => {
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
 
   if (!template) {
     return null;

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

@@ -1,9 +1,9 @@
 import { Flex, Icon, Text, Tooltip } from '@invoke-ai/ui-library';
 import { compare } from 'compare-versions';
-import { useNodeLabel } from 'features/nodes/hooks/useNodeLabel';
 import { useNodeNeedsUpdate } from 'features/nodes/hooks/useNodeNeedsUpdate';
 import { useInvocationNodeNotes } from 'features/nodes/hooks/useNodeNotes';
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
+import { useNodeTemplateOrThrow } from 'features/nodes/hooks/useNodeTemplateOrThrow';
+import { useNodeUserTitleSafe } from 'features/nodes/hooks/useNodeUserTitleSafe';
 import { useNodeVersion } from 'features/nodes/hooks/useNodeVersion';
 import { memo, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -27,9 +27,9 @@ InvocationNodeInfoIcon.displayName = 'InvocationNodeInfoIcon';
 
 const TooltipContent = memo(({ nodeId }: { nodeId: string }) => {
   const notes = useInvocationNodeNotes(nodeId);
-  const label = useNodeLabel(nodeId);
+  const label = useNodeUserTitleSafe(nodeId);
   const version = useNodeVersion(nodeId);
-  const nodeTemplate = useNodeTemplate(nodeId);
+  const nodeTemplate = useNodeTemplateOrThrow(nodeId);
   const { t } = useTranslation();
 
   const title = useMemo(() => {

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

@@ -8,7 +8,7 @@ import {
   Textarea,
 } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
-import { useInputFieldDescriptionSafe } from 'features/nodes/hooks/useInputFieldDescriptionSafe';
+import { useInputFieldUserDescriptionSafe } from 'features/nodes/hooks/useInputFieldUserDescriptionSafe';
 import { fieldDescriptionChanged } from 'features/nodes/store/nodesSlice';
 import { NO_DRAG_CLASS, NO_PAN_CLASS, NO_WHEEL_CLASS } from 'features/nodes/types/constants';
 import type { ChangeEvent } from 'react';
@@ -48,7 +48,7 @@ InputFieldDescriptionPopover.displayName = 'InputFieldDescriptionPopover';
 const Content = memo(({ nodeId, fieldName }: Props) => {
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
-  const description = useInputFieldDescriptionSafe(nodeId, fieldName);
+  const description = useInputFieldUserDescriptionSafe(nodeId, fieldName);
   const onChange = useCallback(
     (e: ChangeEvent<HTMLTextAreaElement>) => {
       dispatch(fieldDescriptionChanged({ nodeId, fieldName, val: e.target.value }));

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

@@ -7,7 +7,7 @@ import { InputFieldResetToDefaultValueIconButton } from 'features/nodes/componen
 import { useNodeFieldDnd } from 'features/nodes/components/sidePanel/builder/dnd-hooks';
 import { useInputFieldIsConnected } from 'features/nodes/hooks/useInputFieldIsConnected';
 import { useInputFieldIsInvalid } from 'features/nodes/hooks/useInputFieldIsInvalid';
-import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplate';
+import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplateOrThrow';
 import { NO_DRAG_CLASS } from 'features/nodes/types/constants';
 import type { FieldInputTemplate } from 'features/nodes/types/field';
 import { memo, useRef } from 'react';
@@ -100,7 +100,7 @@ const DirectField = memo(({ nodeId, fieldName, isInvalid, isConnected, fieldTemp
   const draggableRef = useRef<HTMLDivElement>(null);
   const dragHandleRef = useRef<HTMLDivElement>(null);
 
-  const isDragging = useNodeFieldDnd({ nodeId, fieldName }, fieldTemplate, draggableRef, dragHandleRef);
+  const isDragging = useNodeFieldDnd(nodeId, fieldName, fieldTemplate, draggableRef, dragHandleRef);
 
   return (
     <InputFieldWrapper>

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

@@ -7,7 +7,8 @@ import {
   useIsConnectionInProgress,
   useIsConnectionStartField,
 } from 'features/nodes/hooks/useFieldConnectionState';
-import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplate';
+import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplateOrThrow';
+import { useIsWorkflowEditorLocked } from 'features/nodes/hooks/useIsWorkflowEditorLocked';
 import { useFieldTypeName } from 'features/nodes/hooks/usePrettyFieldType';
 import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
 import type { FieldInputTemplate } from 'features/nodes/types/field';
@@ -105,9 +106,16 @@ type HandleCommonProps = {
 };
 
 const IdleHandle = memo(({ fieldTemplate, fieldTypeName, fieldColor, isModelField }: HandleCommonProps) => {
+  const isLocked = useIsWorkflowEditorLocked();
   return (
     <Tooltip label={fieldTypeName} placement="start" openDelay={HANDLE_TOOLTIP_OPEN_DELAY}>
-      <Handle type="target" id={fieldTemplate.name} position={Position.Left} style={handleStyles}>
+      <Handle
+        type="target"
+        id={fieldTemplate.name}
+        position={Position.Left}
+        style={handleStyles}
+        isConnectable={!isLocked}
+      >
         <Box
           sx={sx}
           data-cardinality={fieldTemplate.type.cardinality}
@@ -130,6 +138,7 @@ const ConnectionInProgressHandle = memo(
     const { t } = useTranslation();
     const isConnectionStartField = useIsConnectionStartField(nodeId, fieldName, 'target');
     const connectionError = useConnectionErrorTKey(nodeId, fieldName, 'target');
+    const isLocked = useIsWorkflowEditorLocked();
 
     const tooltip = useMemo(() => {
       if (connectionError !== null) {
@@ -140,7 +149,13 @@ const ConnectionInProgressHandle = memo(
 
     return (
       <Tooltip label={tooltip} placement="start" openDelay={HANDLE_TOOLTIP_OPEN_DELAY}>
-        <Handle type="target" id={fieldTemplate.name} position={Position.Left} style={handleStyles}>
+        <Handle
+          type="target"
+          id={fieldTemplate.name}
+          position={Position.Left}
+          style={handleStyles}
+          isConnectable={!isLocked}
+        >
           <Box
             sx={sx}
             data-cardinality={fieldTemplate.type.cardinality}

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

@@ -17,7 +17,7 @@ import { StringFieldDropdown } from 'features/nodes/components/flow/nodes/Invoca
 import { StringFieldInput } from 'features/nodes/components/flow/nodes/Invocation/fields/StringField/StringFieldInput';
 import { StringFieldTextarea } from 'features/nodes/components/flow/nodes/Invocation/fields/StringField/StringFieldTextarea';
 import { useInputFieldInstance } from 'features/nodes/hooks/useInputFieldInstance';
-import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplate';
+import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplateOrThrow';
 import {
   isBoardFieldInputInstance,
   isBoardFieldInputTemplate,

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

@@ -9,8 +9,8 @@ import {
   useIsConnectionStartField,
 } from 'features/nodes/hooks/useFieldConnectionState';
 import { useInputFieldIsConnected } from 'features/nodes/hooks/useInputFieldIsConnected';
-import { useInputFieldLabelSafe } from 'features/nodes/hooks/useInputFieldLabelSafe';
-import { useInputFieldTemplateTitle } from 'features/nodes/hooks/useInputFieldTemplateTitle';
+import { useInputFieldTemplateTitleOrThrow } from 'features/nodes/hooks/useInputFieldTemplateTitleOrThrow';
+import { useInputFieldUserTitleSafe } from 'features/nodes/hooks/useInputFieldUserTitleSafe';
 import { fieldLabelChanged } from 'features/nodes/store/nodesSlice';
 import { HANDLE_TOOLTIP_OPEN_DELAY, NO_FIT_ON_DOUBLE_CLICK_CLASS } from 'features/nodes/types/constants';
 import type { MouseEvent } from 'react';
@@ -43,8 +43,8 @@ interface Props {
 export const InputFieldTitle = memo((props: Props) => {
   const { nodeId, fieldName, isInvalid, isDragging } = props;
   const inputRef = useRef<HTMLInputElement>(null);
-  const label = useInputFieldLabelSafe(nodeId, fieldName);
-  const fieldTemplateTitle = useInputFieldTemplateTitle(nodeId, fieldName);
+  const label = useInputFieldUserTitleSafe(nodeId, fieldName);
+  const fieldTemplateTitle = useInputFieldTemplateTitleOrThrow(nodeId, fieldName);
   const { t } = useTranslation();
   const isConnected = useInputFieldIsConnected(nodeId, fieldName);
   const isConnectionStartField = useIsConnectionStartField(nodeId, fieldName, 'target');

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

@@ -1,7 +1,7 @@
 import { Flex, ListItem, Text, UnorderedList } from '@invoke-ai/ui-library';
 import { useInputFieldErrors } from 'features/nodes/hooks/useInputFieldErrors';
 import { useInputFieldInstance } from 'features/nodes/hooks/useInputFieldInstance';
-import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplate';
+import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplateOrThrow';
 import { useFieldTypeName } from 'features/nodes/hooks/usePrettyFieldType';
 import { startCase } from 'lodash-es';
 import { memo, useMemo } from 'react';

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

@@ -7,6 +7,7 @@ import {
   useIsConnectionInProgress,
   useIsConnectionStartField,
 } from 'features/nodes/hooks/useFieldConnectionState';
+import { useIsWorkflowEditorLocked } from 'features/nodes/hooks/useIsWorkflowEditorLocked';
 import { useOutputFieldTemplate } from 'features/nodes/hooks/useOutputFieldTemplate';
 import { useFieldTypeName } from 'features/nodes/hooks/usePrettyFieldType';
 import { HANDLE_TOOLTIP_OPEN_DELAY } from 'features/nodes/types/constants';
@@ -105,9 +106,17 @@ type HandleCommonProps = {
 };
 
 const IdleHandle = memo(({ fieldTemplate, fieldTypeName, fieldColor, isModelField }: HandleCommonProps) => {
+  const isLocked = useIsWorkflowEditorLocked();
+
   return (
     <Tooltip label={fieldTypeName} placement="start" openDelay={HANDLE_TOOLTIP_OPEN_DELAY}>
-      <Handle type="source" id={fieldTemplate.name} position={Position.Right} style={handleStyles}>
+      <Handle
+        type="source"
+        id={fieldTemplate.name}
+        position={Position.Right}
+        style={handleStyles}
+        isConnectable={!isLocked}
+      >
         <Box
           sx={sx}
           data-cardinality={fieldTemplate.type.cardinality}
@@ -130,6 +139,7 @@ const ConnectionInProgressHandle = memo(
     const { t } = useTranslation();
     const isConnectionStartField = useIsConnectionStartField(nodeId, fieldName, 'target');
     const connectionErrorTKey = useConnectionErrorTKey(nodeId, fieldName, 'target');
+    const isLocked = useIsWorkflowEditorLocked();
 
     const tooltip = useMemo(() => {
       if (connectionErrorTKey !== null) {
@@ -140,7 +150,13 @@ const ConnectionInProgressHandle = memo(
 
     return (
       <Tooltip label={tooltip} placement="start" openDelay={HANDLE_TOOLTIP_OPEN_DELAY}>
-        <Handle type="source" id={fieldTemplate.name} position={Position.Right} style={handleStyles}>
+        <Handle
+          type="source"
+          id={fieldTemplate.name}
+          position={Position.Right}
+          style={handleStyles}
+          isConnectable={!isLocked}
+        >
           <Box
             sx={sx}
             data-cardinality={fieldTemplate.type.cardinality}

invokeai/frontend/web/src/features/nodes/components/flow/nodes/common/NodeTitle.tsx

@@ -3,8 +3,8 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { useEditable } from 'common/hooks/useEditable';
 import { useBatchGroupColorToken } from 'features/nodes/hooks/useBatchGroupColorToken';
 import { useBatchGroupId } from 'features/nodes/hooks/useBatchGroupId';
-import { useNodeLabel } from 'features/nodes/hooks/useNodeLabel';
-import { useNodeTemplateTitle } from 'features/nodes/hooks/useNodeTemplateTitle';
+import { useNodeTemplateTitleSafe } from 'features/nodes/hooks/useNodeTemplateTitleSafe';
+import { useNodeUserTitleSafe } from 'features/nodes/hooks/useNodeUserTitleSafe';
 import { nodeLabelChanged } from 'features/nodes/store/nodesSlice';
 import { NO_FIT_ON_DOUBLE_CLICK_CLASS } from 'features/nodes/types/constants';
 import { memo, useCallback, useMemo, useRef } from 'react';
@@ -17,10 +17,10 @@ type Props = {
 
 const NodeTitle = ({ nodeId, title }: Props) => {
   const dispatch = useAppDispatch();
-  const label = useNodeLabel(nodeId);
+  const label = useNodeUserTitleSafe(nodeId);
   const batchGroupId = useBatchGroupId(nodeId);
   const batchGroupColorToken = useBatchGroupColorToken(batchGroupId);
-  const templateTitle = useNodeTemplateTitle(nodeId);
+  const templateTitle = useNodeTemplateTitleSafe(nodeId);
   const { t } = useTranslation();
   const inputRef = useRef<HTMLInputElement>(null);
 

invokeai/frontend/web/src/features/nodes/components/flow/nodes/common/NodeWrapper.tsx

@@ -1,6 +1,7 @@
 import type { ChakraProps, SystemStyleObject } from '@invoke-ai/ui-library';
 import { Box, useGlobalMenuClose } from '@invoke-ai/ui-library';
 import { useAppSelector } from 'app/store/storeHooks';
+import { useIsWorkflowEditorLocked } from 'features/nodes/hooks/useIsWorkflowEditorLocked';
 import { useMouseOverFormField, useMouseOverNode } from 'features/nodes/hooks/useMouseOverNode';
 import { useNodeExecutionState } from 'features/nodes/hooks/useNodeExecutionState';
 import { useZoomToNode } from 'features/nodes/hooks/useZoomToNode';
@@ -62,6 +63,12 @@ const containerSx: SystemStyleObject = {
     display: 'block',
     shadow: '0 0 0 3px var(--invoke-colors-blue-300)',
   },
+  '&[data-is-editor-locked="true"]': {
+    '& *': {
+      cursor: 'not-allowed',
+      pointerEvents: 'none',
+    },
+  },
 };
 
 const shadowsSx: SystemStyleObject = {
@@ -98,7 +105,8 @@ const NodeWrapper = (props: NodeWrapperProps) => {
   const { nodeId, width, children, selected } = props;
   const mouseOverNode = useMouseOverNode(nodeId);
   const mouseOverFormField = useMouseOverFormField(nodeId);
-  const zoomToNode = useZoomToNode();
+  const zoomToNode = useZoomToNode(nodeId);
+  const isLocked = useIsWorkflowEditorLocked();
 
   const executionState = useNodeExecutionState(nodeId);
   const isInProgress = executionState?.status === zNodeStatus.enum.IN_PROGRESS;
@@ -126,9 +134,9 @@ const NodeWrapper = (props: NodeWrapperProps) => {
         // This target is marked as not fitting the view on double click
         return;
       }
-      zoomToNode(nodeId);
+      zoomToNode();
     },
-    [nodeId, zoomToNode]
+    [zoomToNode]
   );
 
   return (
@@ -141,6 +149,7 @@ const NodeWrapper = (props: NodeWrapperProps) => {
       sx={containerSx}
       width={width || NODE_WIDTH}
       opacity={opacity}
+      data-is-editor-locked={isLocked}
       data-is-selected={selected}
       data-is-mouse-over-form-field={mouseOverFormField.isMouseOverFormField}
     >

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

@@ -0,0 +1,15 @@
+import { Flex } from '@invoke-ai/ui-library';
+import { useAppSelector } from 'app/store/storeHooks';
+import { WorkflowName } from 'features/nodes/components/sidePanel/WorkflowName';
+import { selectWorkflowName } from 'features/nodes/store/workflowSlice';
+import { memo } from 'react';
+
+export const TopCenterPanel = memo(() => {
+  const name = useAppSelector(selectWorkflowName);
+  return (
+    <Flex gap={2} top={2} left="50%" transform="translateX(-50%)" position="absolute" pointerEvents="none">
+      {!!name.length && <WorkflowName />}
+    </Flex>
+  );
+});
+TopCenterPanel.displayName = 'TopCenterPanel';

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

@@ -0,0 +1,64 @@
+import { Alert, AlertDescription, AlertIcon, AlertTitle, Box, Flex } from '@invoke-ai/ui-library';
+import { useStore } from '@nanostores/react';
+import { useAppSelector } from 'app/store/storeHooks';
+import AddNodeButton from 'features/nodes/components/flow/panels/TopPanel/AddNodeButton';
+import UpdateNodesButton from 'features/nodes/components/flow/panels/TopPanel/UpdateNodesButton';
+import {
+  $isInPublishFlow,
+  $isSelectingOutputNode,
+  useIsValidationRunInProgress,
+} from 'features/nodes/components/sidePanel/workflow/publish';
+import { useIsWorkflowEditorLocked } from 'features/nodes/hooks/useIsWorkflowEditorLocked';
+import { selectWorkflowIsPublished } from 'features/nodes/store/workflowSlice';
+import { memo } from 'react';
+import { useTranslation } from 'react-i18next';
+
+export const TopLeftPanel = memo(() => {
+  const isLocked = useIsWorkflowEditorLocked();
+  const isInPublishFlow = useStore($isInPublishFlow);
+  const isPublished = useAppSelector(selectWorkflowIsPublished);
+  const isValidationRunInProgress = useIsValidationRunInProgress();
+  const isSelectingOutputNode = useStore($isSelectingOutputNode);
+
+  const { t } = useTranslation();
+  return (
+    <Flex gap={2} top={2} left={2} position="absolute" alignItems="flex-start" pointerEvents="none">
+      {!isLocked && (
+        <Flex gap="2">
+          <AddNodeButton />
+          <UpdateNodesButton />
+        </Flex>
+      )}
+      {isLocked && (
+        <Alert status="info" borderRadius="base" fontSize="sm" shadow="md" w="fit-content">
+          <AlertIcon />
+          <Box>
+            <AlertTitle>{t('workflows.builder.workflowLocked')}</AlertTitle>
+            {isValidationRunInProgress && (
+              <AlertDescription whiteSpace="pre-wrap">
+                {t('workflows.builder.publishingValidationRunInProgress')}
+              </AlertDescription>
+            )}
+            {isInPublishFlow && !isValidationRunInProgress && !isSelectingOutputNode && (
+              <AlertDescription whiteSpace="pre-wrap">
+                {t('workflows.builder.workflowLockedDuringPublishing')}
+              </AlertDescription>
+            )}
+            {isInPublishFlow && !isValidationRunInProgress && isSelectingOutputNode && (
+              <AlertDescription whiteSpace="pre-wrap">
+                {t('workflows.builder.selectingOutputNodeDesc')}
+              </AlertDescription>
+            )}
+            {isPublished && (
+              <AlertDescription whiteSpace="pre-wrap">
+                {t('workflows.builder.workflowLockedPublished')}
+              </AlertDescription>
+            )}
+          </Box>
+        </Alert>
+      )}
+    </Flex>
+  );
+});
+
+TopLeftPanel.displayName = 'TopLeftPanel';

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

@@ -1,40 +0,0 @@
-import { Flex, IconButton, Spacer } from '@invoke-ai/ui-library';
-import { useAppSelector } from 'app/store/storeHooks';
-import AddNodeButton from 'features/nodes/components/flow/panels/TopPanel/AddNodeButton';
-import ClearFlowButton from 'features/nodes/components/flow/panels/TopPanel/ClearFlowButton';
-import SaveWorkflowButton from 'features/nodes/components/flow/panels/TopPanel/SaveWorkflowButton';
-import UpdateNodesButton from 'features/nodes/components/flow/panels/TopPanel/UpdateNodesButton';
-import { useWorkflowEditorSettingsModal } from 'features/nodes/components/flow/panels/TopRightPanel/WorkflowEditorSettings';
-import { WorkflowName } from 'features/nodes/components/sidePanel/WorkflowName';
-import { selectWorkflowName } from 'features/nodes/store/workflowSlice';
-import { memo } from 'react';
-import { useTranslation } from 'react-i18next';
-import { PiGearSixFill } from 'react-icons/pi';
-
-const TopCenterPanel = () => {
-  const name = useAppSelector(selectWorkflowName);
-  const modal = useWorkflowEditorSettingsModal();
-
-  const { t } = useTranslation();
-  return (
-    <Flex gap={2} top={2} left={2} right={2} position="absolute" alignItems="flex-start" pointerEvents="none">
-      <Flex gap="2">
-        <AddNodeButton />
-        <UpdateNodesButton />
-      </Flex>
-      <Spacer />
-      {!!name.length && <WorkflowName />}
-      <Spacer />
-      <ClearFlowButton />
-      <SaveWorkflowButton />
-      <IconButton
-        pointerEvents="auto"
-        aria-label={t('workflows.workflowEditorMenu')}
-        icon={<PiGearSixFill />}
-        onClick={modal.setTrue}
-      />
-    </Flex>
-  );
-};
-
-export default memo(TopCenterPanel);

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

@@ -0,0 +1,34 @@
+import { Flex, IconButton } from '@invoke-ai/ui-library';
+import ClearFlowButton from 'features/nodes/components/flow/panels/TopPanel/ClearFlowButton';
+import SaveWorkflowButton from 'features/nodes/components/flow/panels/TopPanel/SaveWorkflowButton';
+import { useWorkflowEditorSettingsModal } from 'features/nodes/components/flow/panels/TopRightPanel/WorkflowEditorSettings';
+import { useIsWorkflowEditorLocked } from 'features/nodes/hooks/useIsWorkflowEditorLocked';
+import { memo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiGearSixFill } from 'react-icons/pi';
+
+export const TopRightPanel = memo(() => {
+  const modal = useWorkflowEditorSettingsModal();
+  const isLocked = useIsWorkflowEditorLocked();
+
+  const { t } = useTranslation();
+
+  if (isLocked) {
+    return null;
+  }
+
+  return (
+    <Flex gap={2} top={2} right={2} position="absolute" alignItems="flex-end" pointerEvents="none">
+      <ClearFlowButton />
+      <SaveWorkflowButton />
+      <IconButton
+        pointerEvents="auto"
+        aria-label={t('workflows.workflowEditorMenu')}
+        icon={<PiGearSixFill />}
+        onClick={modal.setTrue}
+      />
+    </Flex>
+  );
+});
+
+TopRightPanel.displayName = 'TopRightPanel';

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

@@ -1,5 +1,4 @@
 import { Box } from '@invoke-ai/ui-library';
-import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import { HorizontalResizeHandle } from 'features/ui/components/tabs/ResizeHandle';
 import type { CSSProperties } from 'react';
 import { memo, useCallback, useRef } from 'react';
@@ -23,23 +22,21 @@ export const EditModeLeftPanelContent = memo(() => {
 
   return (
     <Box position="relative" w="full" h="full">
-      <ScrollableContent>
-        <PanelGroup
-          ref={panelGroupRef}
-          id="workflow-panel-group"
-          autoSaveId="workflow-panel-group"
-          direction="vertical"
-          style={panelGroupStyles}
-        >
-          <Panel id="workflow" collapsible minSize={25}>
-            <WorkflowFieldsLinearViewPanel />
-          </Panel>
-          <HorizontalResizeHandle onDoubleClick={handleDoubleClickHandle} />
-          <Panel id="inspector" collapsible minSize={25}>
-            <WorkflowNodeInspectorPanel />
-          </Panel>
-        </PanelGroup>
-      </ScrollableContent>
+      <PanelGroup
+        ref={panelGroupRef}
+        id="workflow-panel-group"
+        autoSaveId="workflow-panel-group"
+        direction="vertical"
+        style={panelGroupStyles}
+      >
+        <Panel id="workflow" collapsible minSize={25}>
+          <WorkflowFieldsLinearViewPanel />
+        </Panel>
+        <HorizontalResizeHandle onDoubleClick={handleDoubleClickHandle} />
+        <Panel id="inspector" collapsible minSize={25}>
+          <WorkflowNodeInspectorPanel />
+        </Panel>
+      </PanelGroup>
     </Box>
   );
 });

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

@@ -0,0 +1,25 @@
+import { Button, Flex, Heading, Text } from '@invoke-ai/ui-library';
+import { useSaveOrSaveAsWorkflow } from 'features/workflowLibrary/hooks/useSaveOrSaveAsWorkflow';
+import { memo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiCopyBold, PiLockOpenBold } from 'react-icons/pi';
+
+export const PublishedWorkflowPanelContent = memo(() => {
+  const { t } = useTranslation();
+  const saveAs = useSaveOrSaveAsWorkflow();
+  return (
+    <Flex flexDir="column" w="full" h="full" gap={2} alignItems="center">
+      <Heading size="md" pt={32}>
+        {t('workflows.builder.workflowLocked')}
+      </Heading>
+      <Text fontSize="md">{t('workflows.builder.publishedWorkflowsLocked')}</Text>
+      <Button size="md" onClick={saveAs} variant="ghost" leftIcon={<PiCopyBold />}>
+        {t('common.saveAs')}
+      </Button>
+      <Button size="md" onClick={undefined} variant="ghost" leftIcon={<PiLockOpenBold />}>
+        {t('workflows.builder.unpublish')}
+      </Button>
+    </Flex>
+  );
+});
+PublishedWorkflowPanelContent.displayName = 'PublishedWorkflowPanelContent';

invokeai/frontend/web/src/features/nodes/components/sidePanel/WorkflowListMenu/ActiveWorkflowNameAndActions.tsx

@@ -2,7 +2,7 @@ import { Flex, Spacer } from '@invoke-ai/ui-library';
 import { useAppSelector } from 'app/store/storeHooks';
 import { WorkflowListMenuTrigger } from 'features/nodes/components/sidePanel/WorkflowListMenu/WorkflowListMenuTrigger';
 import { WorkflowViewEditToggleButton } from 'features/nodes/components/sidePanel/WorkflowViewEditToggleButton';
-import { selectWorkflowMode } from 'features/nodes/store/workflowSlice';
+import { selectWorkflowIsPublished, selectWorkflowMode } from 'features/nodes/store/workflowSlice';
 import { WorkflowLibraryMenu } from 'features/workflowLibrary/components/WorkflowLibraryMenu/WorkflowLibraryMenu';
 import { memo } from 'react';
 
@@ -10,12 +10,13 @@ import SaveWorkflowButton from './SaveWorkflowButton';
 
 export const ActiveWorkflowNameAndActions = memo(() => {
   const mode = useAppSelector(selectWorkflowMode);
+  const isPublished = useAppSelector(selectWorkflowIsPublished);
 
   return (
     <Flex w="full" alignItems="center" gap={1} minW={0}>
       <WorkflowListMenuTrigger />
       <Spacer />
-      {mode === 'edit' && <SaveWorkflowButton />}
+      {mode === 'edit' && !isPublished && <SaveWorkflowButton />}
       <WorkflowViewEditToggleButton />
       <WorkflowLibraryMenu />
     </Flex>

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

@@ -1,22 +1,30 @@
 import { Flex } from '@invoke-ai/ui-library';
+import { useStore } from '@nanostores/react';
 import { useAppSelector } from 'app/store/storeHooks';
 import { EditModeLeftPanelContent } from 'features/nodes/components/sidePanel/EditModeLeftPanelContent';
+import { PublishedWorkflowPanelContent } from 'features/nodes/components/sidePanel/PublishedWorkflowPanelContent';
+import { $isInPublishFlow } from 'features/nodes/components/sidePanel/workflow/publish';
+import { PublishWorkflowPanelContent } from 'features/nodes/components/sidePanel/workflow/PublishWorkflowPanelContent';
 import { ActiveWorkflowDescription } from 'features/nodes/components/sidePanel/WorkflowListMenu/ActiveWorkflowDescription';
 import { ActiveWorkflowNameAndActions } from 'features/nodes/components/sidePanel/WorkflowListMenu/ActiveWorkflowNameAndActions';
-import { selectWorkflowMode } from 'features/nodes/store/workflowSlice';
+import { selectWorkflowIsPublished, selectWorkflowMode } from 'features/nodes/store/workflowSlice';
 import { memo } from 'react';
 
 import { ViewModeLeftPanelContent } from './viewMode/ViewModeLeftPanelContent';
 
 const WorkflowsTabLeftPanel = () => {
   const mode = useAppSelector(selectWorkflowMode);
+  const isPublished = useAppSelector(selectWorkflowIsPublished);
+  const isInPublishFlow = useStore($isInPublishFlow);
 
   return (
     <Flex w="full" h="full" gap={2} flexDir="column">
-      <ActiveWorkflowNameAndActions />
-      {mode === 'view' && <ActiveWorkflowDescription />}
-      {mode === 'view' && <ViewModeLeftPanelContent />}
-      {mode === 'edit' && <EditModeLeftPanelContent />}
+      {isInPublishFlow && <PublishWorkflowPanelContent />}
+      {!isInPublishFlow && <ActiveWorkflowNameAndActions />}
+      {!isInPublishFlow && !isPublished && mode === 'view' && <ActiveWorkflowDescription />}
+      {!isInPublishFlow && !isPublished && mode === 'view' && <ViewModeLeftPanelContent />}
+      {!isInPublishFlow && !isPublished && mode === 'edit' && <EditModeLeftPanelContent />}
+      {isPublished && <PublishedWorkflowPanelContent />}
     </Flex>
   );
 };

invokeai/frontend/web/src/features/nodes/components/sidePanel/builder/FormElementEditModeHeader.tsx

@@ -67,11 +67,8 @@ FormElementEditModeHeader.displayName = 'FormElementEditModeHeader';
 const ZoomToNodeButton = memo(({ element }: { element: NodeFieldElement }) => {
   const { t } = useTranslation();
   const { nodeId } = element.data.fieldIdentifier;
-  const zoomToNode = useZoomToNode();
+  const zoomToNode = useZoomToNode(nodeId);
   const mouseOverFormField = useMouseOverFormField(nodeId);
-  const onClick = useCallback(() => {
-    zoomToNode(nodeId);
-  }, [nodeId, zoomToNode]);
 
   return (
     <IconButton
@@ -79,7 +76,7 @@ const ZoomToNodeButton = memo(({ element }: { element: NodeFieldElement }) => {
       onMouseOut={mouseOverFormField.handleMouseOut}
       tooltip={t('workflows.builder.zoomToNode')}
       aria-label={t('workflows.builder.zoomToNode')}
-      onClick={onClick}
+      onClick={zoomToNode}
       icon={<PiGpsFixBold />}
       variant="link"
       size="sm"

invokeai/frontend/web/src/features/nodes/components/sidePanel/builder/NodeFieldElementDescriptionEditable.tsx

@@ -2,8 +2,8 @@ import { FormHelperText, Textarea } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { linkifyOptions, linkifySx } from 'common/components/linkify';
 import { useEditable } from 'common/hooks/useEditable';
-import { useInputFieldDescriptionSafe } from 'features/nodes/hooks/useInputFieldDescriptionSafe';
-import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplate';
+import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplateOrThrow';
+import { useInputFieldUserDescriptionSafe } from 'features/nodes/hooks/useInputFieldUserDescriptionSafe';
 import { fieldDescriptionChanged } from 'features/nodes/store/nodesSlice';
 import type { NodeFieldElement } from 'features/nodes/types/workflow';
 import Linkify from 'linkify-react';
@@ -13,7 +13,7 @@ export const NodeFieldElementDescriptionEditable = memo(({ el }: { el: NodeField
   const { data } = el;
   const { fieldIdentifier } = data;
   const dispatch = useAppDispatch();
-  const description = useInputFieldDescriptionSafe(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
+  const description = useInputFieldUserDescriptionSafe(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
   const fieldTemplate = useInputFieldTemplateOrThrow(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
   const inputRef = useRef<HTMLTextAreaElement>(null);
 

invokeai/frontend/web/src/features/nodes/components/sidePanel/builder/NodeFieldElementEditMode.tsx

@@ -39,7 +39,7 @@ export const NodeFieldElementEditMode = memo(({ el }: { el: NodeFieldElement })
   return (
     <Flex ref={draggableRef} id={id} className={NODE_FIELD_CLASS_NAME} sx={sx} data-parent-layout={containerCtx.layout}>
       <NodeFieldElementEditModeContent dragHandleRef={dragHandleRef} el={el} isDragging={isDragging} />
-      <NodeFieldElementOverlay element={el} />
+      <NodeFieldElementOverlay nodeId={el.data.fieldIdentifier.nodeId} />
       <DndListDropIndicator activeDropRegion={activeDropRegion} gap="var(--invoke-space-4)" />
     </Flex>
   );
@@ -105,9 +105,9 @@ const nodeFieldOverlaySx: SystemStyleObject = {
   },
 };
 
-const NodeFieldElementOverlay = memo(({ element }: { element: NodeFieldElement }) => {
-  const mouseOverNode = useMouseOverNode(element.data.fieldIdentifier.nodeId);
-  const mouseOverFormField = useMouseOverFormField(element.data.fieldIdentifier.nodeId);
+export const NodeFieldElementOverlay = memo(({ nodeId }: { nodeId: string }) => {
+  const mouseOverNode = useMouseOverNode(nodeId);
+  const mouseOverFormField = useMouseOverFormField(nodeId);
 
   return (
     <Box

invokeai/frontend/web/src/features/nodes/components/sidePanel/builder/NodeFieldElementLabel.tsx

@@ -1,14 +1,14 @@
 import { Flex, FormLabel, Spacer } from '@invoke-ai/ui-library';
 import { NodeFieldElementResetToInitialValueIconButton } from 'features/nodes/components/flow/nodes/Invocation/fields/NodeFieldElementResetToInitialValueIconButton';
-import { useInputFieldLabelSafe } from 'features/nodes/hooks/useInputFieldLabelSafe';
-import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplate';
+import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplateOrThrow';
+import { useInputFieldUserTitleSafe } from 'features/nodes/hooks/useInputFieldUserTitleSafe';
 import type { NodeFieldElement } from 'features/nodes/types/workflow';
 import { memo, useMemo } from 'react';
 
 export const NodeFieldElementLabel = memo(({ el }: { el: NodeFieldElement }) => {
   const { data } = el;
   const { fieldIdentifier } = data;
-  const label = useInputFieldLabelSafe(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
+  const label = useInputFieldUserTitleSafe(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
   const fieldTemplate = useInputFieldTemplateOrThrow(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
 
   const _label = useMemo(() => label || fieldTemplate.title, [label, fieldTemplate.title]);

invokeai/frontend/web/src/features/nodes/components/sidePanel/builder/NodeFieldElementLabelEditable.tsx

@@ -2,8 +2,8 @@ import { Flex, FormLabel, Input, Spacer } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { useEditable } from 'common/hooks/useEditable';
 import { NodeFieldElementResetToInitialValueIconButton } from 'features/nodes/components/flow/nodes/Invocation/fields/NodeFieldElementResetToInitialValueIconButton';
-import { useInputFieldLabelSafe } from 'features/nodes/hooks/useInputFieldLabelSafe';
-import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplate';
+import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplateOrThrow';
+import { useInputFieldUserTitleSafe } from 'features/nodes/hooks/useInputFieldUserTitleSafe';
 import { fieldLabelChanged } from 'features/nodes/store/nodesSlice';
 import type { NodeFieldElement } from 'features/nodes/types/workflow';
 import { memo, useCallback, useRef } from 'react';
@@ -12,7 +12,7 @@ export const NodeFieldElementLabelEditable = memo(({ el }: { el: NodeFieldElemen
   const { data } = el;
   const { fieldIdentifier } = data;
   const dispatch = useAppDispatch();
-  const label = useInputFieldLabelSafe(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
+  const label = useInputFieldUserTitleSafe(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
   const fieldTemplate = useInputFieldTemplateOrThrow(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
   const inputRef = useRef<HTMLInputElement>(null);
 

invokeai/frontend/web/src/features/nodes/components/sidePanel/builder/NodeFieldElementSettings.tsx

@@ -15,7 +15,7 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import { NodeFieldElementFloatSettings } from 'features/nodes/components/sidePanel/builder/NodeFieldElementFloatSettings';
 import { NodeFieldElementIntegerSettings } from 'features/nodes/components/sidePanel/builder/NodeFieldElementIntegerSettings';
 import { NodeFieldElementStringSettings } from 'features/nodes/components/sidePanel/builder/NodeFieldElementStringSettings';
-import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplate';
+import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplateOrThrow';
 import { formElementNodeFieldDataChanged } from 'features/nodes/store/workflowSlice';
 import {
   isFloatFieldInputTemplate,

invokeai/frontend/web/src/features/nodes/components/sidePanel/builder/NodeFieldElementViewMode.tsx

@@ -5,8 +5,9 @@ import { InputFieldGate } from 'features/nodes/components/flow/nodes/Invocation/
 import { InputFieldRenderer } from 'features/nodes/components/flow/nodes/Invocation/fields/InputFieldRenderer';
 import { useContainerContext } from 'features/nodes/components/sidePanel/builder/contexts';
 import { NodeFieldElementLabel } from 'features/nodes/components/sidePanel/builder/NodeFieldElementLabel';
-import { useInputFieldDescriptionSafe } from 'features/nodes/hooks/useInputFieldDescriptionSafe';
-import { useInputFieldTemplateOrThrow, useInputFieldTemplateSafe } from 'features/nodes/hooks/useInputFieldTemplate';
+import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplateOrThrow';
+import { useInputFieldTemplateSafe } from 'features/nodes/hooks/useInputFieldTemplateSafe';
+import { useInputFieldUserDescriptionSafe } from 'features/nodes/hooks/useInputFieldUserDescriptionSafe';
 import type { NodeFieldElement } from 'features/nodes/types/workflow';
 import { NODE_FIELD_CLASS_NAME } from 'features/nodes/types/workflow';
 import Linkify from 'linkify-react';
@@ -36,7 +37,7 @@ const useFormatFallbackLabel = () => {
 export const NodeFieldElementViewMode = memo(({ el }: { el: NodeFieldElement }) => {
   const { id, data } = el;
   const { fieldIdentifier, showDescription } = data;
-  const description = useInputFieldDescriptionSafe(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
+  const description = useInputFieldUserDescriptionSafe(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
   const fieldTemplate = useInputFieldTemplateSafe(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
   const containerCtx = useContainerContext();
   const formatFallbackLabel = useFormatFallbackLabel();
@@ -69,7 +70,7 @@ NodeFieldElementViewMode.displayName = 'NodeFieldElementViewMode';
 const NodeFieldElementViewModeContent = memo(({ el }: { el: NodeFieldElement }) => {
   const { data } = el;
   const { fieldIdentifier, showDescription } = data;
-  const description = useInputFieldDescriptionSafe(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
+  const description = useInputFieldUserDescriptionSafe(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
   const fieldTemplate = useInputFieldTemplateOrThrow(fieldIdentifier.nodeId, fieldIdentifier.fieldName);
 
   const _description = useMemo(

invokeai/frontend/web/src/features/nodes/components/sidePanel/builder/dnd-hooks.ts

@@ -1,4 +1,6 @@
 import { combine } from '@atlaskit/pragmatic-drag-and-drop/combine';
+import type { DropTargetRecord } from '@atlaskit/pragmatic-drag-and-drop/dist/types/internal-types';
+import type { ElementDragPayload } from '@atlaskit/pragmatic-drag-and-drop/element/adapter';
 import {
   draggable,
   dropTargetForElements,
@@ -33,7 +35,7 @@ import {
   selectFormRootElementId,
   selectWorkflowSlice,
 } from 'features/nodes/store/workflowSlice';
-import type { FieldIdentifier, FieldInputTemplate, StatefulFieldValue } from 'features/nodes/types/field';
+import type { FieldInputTemplate, StatefulFieldValue } from 'features/nodes/types/field';
 import type { ElementId, FormElement } from 'features/nodes/types/workflow';
 import { buildNodeFieldElement, isContainerElement } from 'features/nodes/types/workflow';
 import type { RefObject } from 'react';
@@ -58,6 +60,27 @@ const isFormElementDndData = (data: Record<string | symbol, unknown>): data is F
   return uniqueFormElementDndKey in data;
 };
 
+const uniqueNodeFieldDndKey = Symbol('node-field');
+type NodeFieldDndData = {
+  [uniqueNodeFieldDndKey]: true;
+  nodeId: string;
+  fieldName: string;
+  fieldTemplate: FieldInputTemplate;
+};
+const buildNodeFieldDndData = (
+  nodeId: string,
+  fieldName: string,
+  fieldTemplate: FieldInputTemplate
+): NodeFieldDndData => ({
+  [uniqueNodeFieldDndKey]: true,
+  nodeId,
+  fieldName,
+  fieldTemplate,
+});
+const isNodeFieldDndData = (data: Record<string | symbol, unknown>): data is NodeFieldDndData => {
+  return uniqueNodeFieldDndKey in data;
+};
+
 /**
  * Flashes an element by changing its background color. Used to indicate that an element has been moved.
  * @param elementId The id of the element to flash
@@ -133,6 +156,27 @@ const useGetInitialValue = () => {
   return _getInitialValue;
 };
 
+const getSourceElement = (source: ElementDragPayload) => {
+  if (isNodeFieldDndData(source.data)) {
+    const { nodeId, fieldName, fieldTemplate } = source.data;
+    return buildNodeFieldElement(nodeId, fieldName, fieldTemplate.type);
+  }
+
+  if (isFormElementDndData(source.data)) {
+    return source.data.element;
+  }
+
+  return null;
+};
+
+const getTargetElement = (target: DropTargetRecord) => {
+  if (isFormElementDndData(target.data)) {
+    return target.data.element;
+  }
+
+  return null;
+};
+
 /**
  * Singleton hook that monitors for builder dnd events and dispatches actions accordingly.
  */
@@ -156,20 +200,20 @@ export const useBuilderDndMonitor = () => {
 
   useEffect(() => {
     return monitorForElements({
-      canMonitor: ({ source }) => isFormElementDndData(source.data),
+      canMonitor: ({ source }) => isFormElementDndData(source.data) || isNodeFieldDndData(source.data),
       onDrop: ({ location, source }) => {
         const target = location.current.dropTargets[0];
         if (!target) {
           return;
         }
 
-        if (!isFormElementDndData(source.data) || !isFormElementDndData(target.data)) {
+        const sourceElement = getSourceElement(source);
+        const targetElement = getTargetElement(target);
+
+        if (!sourceElement || !targetElement) {
           return;
         }
 
-        const sourceElement = source.data.element;
-        const targetElement = target.data.element;
-
         if (sourceElement.id === targetElement.id) {
           // Dropping on self is a no-op
           return;
@@ -359,8 +403,15 @@ export const useFormElementDnd = (
         element: draggableElement,
         // TODO(psyche): This causes a kinda jittery behaviour - need a better heuristic to determine stickiness
         getIsSticky: () => false,
-        canDrop: ({ source }) =>
-          isFormElementDndData(source.data) && source.data.element.id !== getElement(elementId).parentId,
+        canDrop: ({ source }) => {
+          if (isNodeFieldDndData(source.data)) {
+            return true;
+          }
+          if (isFormElementDndData(source.data)) {
+            return source.data.element.id !== getElement(elementId).parentId;
+          }
+          return false;
+        },
         getData: ({ input }) => {
           const element = getElement(elementId);
 
@@ -423,8 +474,16 @@ export const useRootElementDropTarget = (droppableRef: RefObject<HTMLDivElement>
       dropTargetForElements({
         element: droppableElement,
         getIsSticky: () => false,
-        canDrop: ({ source }) =>
-          getElement(rootElementId, isContainerElement).data.children.length === 0 && isFormElementDndData(source.data),
+        canDrop: ({ source }) => {
+          const rootElement = getElement(rootElementId, isContainerElement);
+          if (rootElement.data.children.length !== 0) {
+            return false;
+          }
+          if (isNodeFieldDndData(source.data) || isFormElementDndData(source.data)) {
+            return true;
+          }
+          return false;
+        },
         getData: ({ input }) => {
           const element = getElement(rootElementId, isContainerElement);
 
@@ -455,7 +514,8 @@ export const useRootElementDropTarget = (droppableRef: RefObject<HTMLDivElement>
 /**
  * Hook that provides dnd functionality for node fields.
  *
- * @param fieldIdentifier The identifier of the node field
+ * @param nodeId: The id of the node
+ * @param fieldName: The name of the field
  * @param fieldTemplate The template of the node field, required to build the form element
  * @param draggableRef The ref of the draggable HTML element
  * @param dragHandleRef The ref of the drag handle HTML element
@@ -463,7 +523,8 @@ export const useRootElementDropTarget = (droppableRef: RefObject<HTMLDivElement>
  * @returns Whether the node field is currently being dragged
  */
 export const useNodeFieldDnd = (
-  fieldIdentifier: FieldIdentifier,
+  nodeId: string,
+  fieldName: string,
   fieldTemplate: FieldInputTemplate,
   draggableRef: RefObject<HTMLElement>,
   dragHandleRef: RefObject<HTMLElement>
@@ -481,12 +542,7 @@ export const useNodeFieldDnd = (
       draggable({
         element: draggableElement,
         dragHandle: dragHandleElement,
-        getInitialData: () => {
-          const { nodeId, fieldName } = fieldIdentifier;
-          const { type } = fieldTemplate;
-          const element = buildNodeFieldElement(nodeId, fieldName, type);
-          return buildFormElementDndData(element);
-        },
+        getInitialData: () => buildNodeFieldDndData(nodeId, fieldName, fieldTemplate),
         onDragStart: () => {
           setIsDragging(true);
         },
@@ -495,7 +551,7 @@ export const useNodeFieldDnd = (
         },
       })
     );
-  }, [dragHandleRef, draggableRef, fieldIdentifier, fieldTemplate]);
+  }, [dragHandleRef, draggableRef, fieldName, fieldTemplate, nodeId]);
 
   return isDragging;
 };

invokeai/frontend/web/src/features/nodes/components/sidePanel/builder/use-add-node-field-to-root.ts

@@ -1,6 +1,6 @@
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { useInputFieldInstance } from 'features/nodes/hooks/useInputFieldInstance';
-import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplate';
+import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplateOrThrow';
 import { formElementAdded, selectFormRootElementId } from 'features/nodes/store/workflowSlice';
 import { buildNodeFieldElement } from 'features/nodes/types/workflow';
 import { useCallback } from 'react';

invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorDetailsTab.tsx

@@ -5,7 +5,7 @@ import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableCon
 import { InvocationNodeNotesTextarea } from 'features/nodes/components/flow/nodes/Invocation/InvocationNodeNotesTextarea';
 import { TemplateGate } from 'features/nodes/components/sidePanel/inspector/NodeTemplateGate';
 import { useNodeNeedsUpdate } from 'features/nodes/hooks/useNodeNeedsUpdate';
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
+import { useNodeTemplateOrThrow } from 'features/nodes/hooks/useNodeTemplateOrThrow';
 import { useNodeVersion } from 'features/nodes/hooks/useNodeVersion';
 import { selectLastSelectedNodeId } from 'features/nodes/store/selectors';
 import { memo } from 'react';
@@ -36,7 +36,7 @@ export default memo(InspectorDetailsTab);
 const Content = memo(({ nodeId }: { nodeId: string }) => {
   const { t } = useTranslation();
   const version = useNodeVersion(nodeId);
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const needsUpdate = useNodeNeedsUpdate(nodeId);
 
   return (

invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorOutputsTab.tsx

@@ -5,7 +5,7 @@ import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableCon
 import DataViewer from 'features/gallery/components/ImageMetadataViewer/DataViewer';
 import { TemplateGate } from 'features/nodes/components/sidePanel/inspector/NodeTemplateGate';
 import { useNodeExecutionState } from 'features/nodes/hooks/useNodeExecutionState';
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
+import { useNodeTemplateOrThrow } from 'features/nodes/hooks/useNodeTemplateOrThrow';
 import { selectLastSelectedNodeId } from 'features/nodes/store/selectors';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -37,7 +37,7 @@ const getKey = (result: AnyInvocationOutput, i: number) => `${result.type}-${i}`
 
 const Content = memo(({ nodeId }: { nodeId: string }) => {
   const { t } = useTranslation();
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const nes = useNodeExecutionState(nodeId);
 
   if (!nes || nes.outputs.length === 0) {

invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorTabEditableNodeTitle.tsx

@@ -1,8 +1,8 @@
 import { Flex, Input, Text } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import { useEditable } from 'common/hooks/useEditable';
-import { useNodeLabel } from 'features/nodes/hooks/useNodeLabel';
-import { useNodeTemplateTitle } from 'features/nodes/hooks/useNodeTemplateTitle';
+import { useNodeTemplateTitleSafe } from 'features/nodes/hooks/useNodeTemplateTitleSafe';
+import { useNodeUserTitleSafe } from 'features/nodes/hooks/useNodeUserTitleSafe';
 import { nodeLabelChanged } from 'features/nodes/store/nodesSlice';
 import { memo, useCallback, useRef } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -14,8 +14,8 @@ type Props = {
 
 const InspectorTabEditableNodeTitle = ({ nodeId, title }: Props) => {
   const dispatch = useAppDispatch();
-  const label = useNodeLabel(nodeId);
-  const templateTitle = useNodeTemplateTitle(nodeId);
+  const label = useNodeUserTitleSafe(nodeId);
+  const templateTitle = useNodeTemplateTitleSafe(nodeId);
   const { t } = useTranslation();
   const inputRef = useRef<HTMLInputElement>(null);
   const onChange = useCallback(

invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorTemplateTab.tsx

@@ -2,7 +2,7 @@ import { useAppSelector } from 'app/store/storeHooks';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import DataViewer from 'features/gallery/components/ImageMetadataViewer/DataViewer';
 import { TemplateGate } from 'features/nodes/components/sidePanel/inspector/NodeTemplateGate';
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
+import { useNodeTemplateOrThrow } from 'features/nodes/hooks/useNodeTemplateOrThrow';
 import { selectLastSelectedNodeId } from 'features/nodes/store/selectors';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -29,7 +29,7 @@ export default memo(NodeTemplateInspector);
 
 const Content = memo(({ nodeId }: { nodeId: string }) => {
   const { t } = useTranslation();
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
 
   return <DataViewer data={template} label={t('nodes.nodeTemplate')} bg="base.850" color="base.200" />;
 });

invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/NodeTemplateGate.tsx

@@ -1,4 +1,4 @@
-import { useNodeTemplateSafe } from 'features/nodes/hooks/useNodeTemplate';
+import { useNodeTemplateSafe } from 'features/nodes/hooks/useNodeTemplateSafe';
 import type { PropsWithChildren, ReactNode } from 'react';
 import { memo } from 'react';
 

invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/PublishWorkflowPanelContent.tsx

@@ -0,0 +1,445 @@
+import type { ButtonProps } from '@invoke-ai/ui-library';
+import {
+  Button,
+  ButtonGroup,
+  Divider,
+  Flex,
+  ListItem,
+  Spacer,
+  Text,
+  Tooltip,
+  UnorderedList,
+} from '@invoke-ai/ui-library';
+import { useStore } from '@nanostores/react';
+import { logger } from 'app/logging/logger';
+import { $projectUrl } from 'app/store/nanostores/projectId';
+import { useAppSelector } from 'app/store/storeHooks';
+import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
+import { withResultAsync } from 'common/util/result';
+import { parseify } from 'common/util/serialize';
+import { ExternalLink } from 'features/gallery/components/ImageViewer/NoContentForViewer';
+import { NodeFieldElementOverlay } from 'features/nodes/components/sidePanel/builder/NodeFieldElementEditMode';
+import {
+  $isInPublishFlow,
+  $isReadyToDoValidationRun,
+  $isSelectingOutputNode,
+  $outputNodeId,
+  $validationRunBatchId,
+  usePublishInputs,
+} from 'features/nodes/components/sidePanel/workflow/publish';
+import { useInputFieldTemplateTitleOrThrow } from 'features/nodes/hooks/useInputFieldTemplateTitleOrThrow';
+import { useInputFieldUserTitleOrThrow } from 'features/nodes/hooks/useInputFieldUserTitleOrThrow';
+import { useMouseOverFormField } from 'features/nodes/hooks/useMouseOverNode';
+import { useNodeTemplateTitleOrThrow } from 'features/nodes/hooks/useNodeTemplateTitleOrThrow';
+import { useNodeUserTitleOrThrow } from 'features/nodes/hooks/useNodeUserTitleOrThrow';
+import { useOutputFieldNames } from 'features/nodes/hooks/useOutputFieldNames';
+import { useOutputFieldTemplate } from 'features/nodes/hooks/useOutputFieldTemplate';
+import { useZoomToNode } from 'features/nodes/hooks/useZoomToNode';
+import { selectHasBatchOrGeneratorNodes } from 'features/nodes/store/selectors';
+import { selectIsWorkflowSaved } from 'features/nodes/store/workflowSlice';
+import { useEnqueueWorkflows } from 'features/queue/hooks/useEnqueueWorkflows';
+import { $isReadyToEnqueue } from 'features/queue/store/readiness';
+import { selectAllowPublishWorkflows } from 'features/system/store/configSlice';
+import { toast } from 'features/toast/toast';
+import type { PropsWithChildren } from 'react';
+import { memo, useCallback, useMemo } from 'react';
+import { Trans, useTranslation } from 'react-i18next';
+import { PiArrowLineRightBold, PiLightningFill, PiXBold } from 'react-icons/pi';
+import { serializeError } from 'serialize-error';
+import { assert } from 'tsafe';
+
+const log = logger('generation');
+
+export const PublishWorkflowPanelContent = memo(() => {
+  return (
+    <Flex flexDir="column" gap={2} h="full">
+      <ButtonGroup isAttached={false} size="sm" variant="ghost">
+        <Spacer />
+        <CancelPublishButton />
+        <PublishWorkflowButton />
+      </ButtonGroup>
+      <ScrollableContent>
+        <Flex flexDir="column" gap={2} w="full" h="full">
+          <OutputFields />
+          <PublishableInputFields />
+          <UnpublishableInputFields />
+        </Flex>
+      </ScrollableContent>
+    </Flex>
+  );
+});
+PublishWorkflowPanelContent.displayName = 'PublishWorkflowPanelContent';
+
+const OutputFields = memo(() => {
+  const { t } = useTranslation();
+  const outputNodeId = useStore($outputNodeId);
+
+  return (
+    <Flex flexDir="column" borderWidth={1} borderRadius="base" gap={2} p={2}>
+      <Flex alignItems="center">
+        <Text fontWeight="semibold">{t('workflows.builder.publishedWorkflowOutputs')}</Text>
+        <Spacer />
+        <SelectOutputNodeButton variant="link" size="sm" />
+      </Flex>
+
+      <Divider />
+      {!outputNodeId && (
+        <Text fontWeight="semibold" color="error.300">
+          {t('workflows.builder.noOutputNodeSelected')}
+        </Text>
+      )}
+      {outputNodeId && <OutputFieldsContent outputNodeId={outputNodeId} />}
+    </Flex>
+  );
+});
+OutputFields.displayName = 'OutputFields';
+
+const OutputFieldsContent = memo(({ outputNodeId }: { outputNodeId: string }) => {
+  const outputFieldNames = useOutputFieldNames(outputNodeId);
+
+  return (
+    <>
+      {outputFieldNames.map((fieldName) => (
+        <NodeOutputFieldPreview key={`${outputNodeId}-${fieldName}`} nodeId={outputNodeId} fieldName={fieldName} />
+      ))}
+    </>
+  );
+});
+OutputFieldsContent.displayName = 'OutputFieldsContent';
+
+const PublishableInputFields = memo(() => {
+  const { t } = useTranslation();
+  const inputs = usePublishInputs();
+
+  if (inputs.publishable.length === 0) {
+    return (
+      <Flex flexDir="column" borderWidth={1} borderRadius="base" gap={2} p={2}>
+        <Text fontWeight="semibold" color="warning.300">
+          {t('workflows.builder.noPublishableInputs')}
+        </Text>
+      </Flex>
+    );
+  }
+
+  return (
+    <Flex flexDir="column" borderWidth={1} borderRadius="base" gap={2} p={2}>
+      <Text fontWeight="semibold">{t('workflows.builder.publishedWorkflowInputs')}</Text>
+      <Divider />
+      {inputs.publishable.map(({ nodeId, fieldName }) => {
+        return <NodeInputFieldPreview key={`${nodeId}-${fieldName}`} nodeId={nodeId} fieldName={fieldName} />;
+      })}
+    </Flex>
+  );
+});
+PublishableInputFields.displayName = 'PublishableInputFields';
+
+const UnpublishableInputFields = memo(() => {
+  const { t } = useTranslation();
+  const inputs = usePublishInputs();
+
+  if (inputs.unpublishable.length === 0) {
+    return null;
+  }
+
+  return (
+    <Flex flexDir="column" borderWidth={1} borderRadius="base" gap={2} p={2}>
+      <Text fontWeight="semibold" color="warning.300">
+        {t('workflows.builder.unpublishableInputs')}
+      </Text>
+      <Divider />
+      {inputs.unpublishable.map(({ nodeId, fieldName }) => {
+        return <NodeInputFieldPreview key={`${nodeId}-${fieldName}`} nodeId={nodeId} fieldName={fieldName} />;
+      })}
+    </Flex>
+  );
+});
+UnpublishableInputFields.displayName = 'UnpublishableInputFields';
+
+const SelectOutputNodeButton = memo((props: ButtonProps) => {
+  const { t } = useTranslation();
+  const outputNodeId = useStore($outputNodeId);
+  const isSelectingOutputNode = useStore($isSelectingOutputNode);
+  const onClick = useCallback(() => {
+    $outputNodeId.set(null);
+    $isSelectingOutputNode.set(true);
+  }, []);
+  return (
+    <Button
+      leftIcon={<PiArrowLineRightBold />}
+      isDisabled={isSelectingOutputNode}
+      tooltip={isSelectingOutputNode ? t('workflows.builder.selectingOutputNodeDesc') : undefined}
+      onClick={onClick}
+      {...props}
+    >
+      {isSelectingOutputNode
+        ? t('workflows.builder.selectingOutputNode')
+        : outputNodeId
+          ? t('workflows.builder.changeOutputNode')
+          : t('workflows.builder.selectOutputNode')}
+    </Button>
+  );
+});
+SelectOutputNodeButton.displayName = 'SelectOutputNodeButton';
+
+const CancelPublishButton = memo(() => {
+  const { t } = useTranslation();
+  const onClick = useCallback(() => {
+    $isInPublishFlow.set(false);
+    $isSelectingOutputNode.set(false);
+    $outputNodeId.set(null);
+  }, []);
+  return (
+    <Button leftIcon={<PiXBold />} onClick={onClick}>
+      {t('common.cancel')}
+    </Button>
+  );
+});
+CancelPublishButton.displayName = 'CancelDeployButton';
+
+const PublishWorkflowButton = memo(() => {
+  const { t } = useTranslation();
+  const isReadyToDoValidationRun = useStore($isReadyToDoValidationRun);
+  const isReadyToEnqueue = useStore($isReadyToEnqueue);
+  const isWorkflowSaved = useAppSelector(selectIsWorkflowSaved);
+  const hasBatchOrGeneratorNodes = useAppSelector(selectHasBatchOrGeneratorNodes);
+  const outputNodeId = useStore($outputNodeId);
+  const isSelectingOutputNode = useStore($isSelectingOutputNode);
+  const inputs = usePublishInputs();
+  const allowPublishWorkflows = useAppSelector(selectAllowPublishWorkflows);
+
+  const projectUrl = useStore($projectUrl);
+
+  const enqueue = useEnqueueWorkflows();
+  const onClick = useCallback(async () => {
+    const result = await withResultAsync(() => enqueue(true, true));
+    if (result.isErr()) {
+      toast({
+        id: 'TOAST_PUBLISH_FAILED',
+        status: 'error',
+        title: t('workflows.builder.publishFailed'),
+        description: t('workflows.builder.publishFailedDesc'),
+        duration: null,
+      });
+      log.error({ error: serializeError(result.error) }, 'Failed to enqueue batch');
+    } else {
+      toast({
+        id: 'TOAST_PUBLISH_SUCCESSFUL',
+        status: 'success',
+        title: t('workflows.builder.publishSuccess'),
+        description: (
+          <Trans
+            i18nKey="workflows.builder.publishSuccessDesc"
+            components={{
+              LinkComponent: <ExternalLink href={projectUrl ?? ''} />,
+            }}
+          />
+        ),
+        duration: null,
+      });
+      assert(result.value.enqueueResult.batch.batch_id);
+      $validationRunBatchId.set(result.value.enqueueResult.batch.batch_id);
+      log.debug(parseify(result.value), 'Enqueued batch');
+    }
+  }, [enqueue, projectUrl, t]);
+
+  return (
+    <PublishTooltip
+      isWorkflowSaved={isWorkflowSaved}
+      hasBatchOrGeneratorNodes={hasBatchOrGeneratorNodes}
+      isReadyToEnqueue={isReadyToEnqueue}
+      hasOutputNode={outputNodeId !== null && !isSelectingOutputNode}
+      hasPublishableInputs={inputs.publishable.length > 0}
+      hasUnpublishableInputs={inputs.unpublishable.length > 0}
+    >
+      <Button
+        leftIcon={<PiLightningFill />}
+        isDisabled={
+          !allowPublishWorkflows ||
+          !isReadyToEnqueue ||
+          !isWorkflowSaved ||
+          hasBatchOrGeneratorNodes ||
+          !isReadyToDoValidationRun ||
+          !(outputNodeId !== null && !isSelectingOutputNode)
+        }
+        onClick={onClick}
+      >
+        {t('workflows.builder.publish')}
+      </Button>
+    </PublishTooltip>
+  );
+});
+PublishWorkflowButton.displayName = 'DoValidationRunButton';
+
+const NodeInputFieldPreview = memo(({ nodeId, fieldName }: { nodeId: string; fieldName: string }) => {
+  const mouseOverFormField = useMouseOverFormField(nodeId);
+  const nodeUserTitle = useNodeUserTitleOrThrow(nodeId);
+  const nodeTemplateTitle = useNodeTemplateTitleOrThrow(nodeId);
+  const fieldUserTitle = useInputFieldUserTitleOrThrow(nodeId, fieldName);
+  const fieldTemplateTitle = useInputFieldTemplateTitleOrThrow(nodeId, fieldName);
+  const zoomToNode = useZoomToNode(nodeId);
+
+  return (
+    <Flex
+      flexDir="column"
+      position="relative"
+      p={2}
+      borderRadius="base"
+      onMouseOver={mouseOverFormField.handleMouseOver}
+      onMouseOut={mouseOverFormField.handleMouseOut}
+      onClick={zoomToNode}
+    >
+      <Text fontWeight="semibold">{`${nodeUserTitle || nodeTemplateTitle} -> ${fieldUserTitle || fieldTemplateTitle}`}</Text>
+      <Text variant="subtext">{`${nodeId} -> ${fieldName}`}</Text>
+      <NodeFieldElementOverlay nodeId={nodeId} />
+    </Flex>
+  );
+});
+NodeInputFieldPreview.displayName = 'NodeInputFieldPreview';
+
+const NodeOutputFieldPreview = memo(({ nodeId, fieldName }: { nodeId: string; fieldName: string }) => {
+  const mouseOverFormField = useMouseOverFormField(nodeId);
+  const nodeUserTitle = useNodeUserTitleOrThrow(nodeId);
+  const nodeTemplateTitle = useNodeTemplateTitleOrThrow(nodeId);
+  const fieldTemplate = useOutputFieldTemplate(nodeId, fieldName);
+  const zoomToNode = useZoomToNode(nodeId);
+
+  return (
+    <Flex
+      flexDir="column"
+      position="relative"
+      p={2}
+      borderRadius="base"
+      onMouseOver={mouseOverFormField.handleMouseOver}
+      onMouseOut={mouseOverFormField.handleMouseOut}
+      onClick={zoomToNode}
+    >
+      <Text fontWeight="semibold">{`${nodeUserTitle || nodeTemplateTitle} -> ${fieldTemplate.title}`}</Text>
+      <Text variant="subtext">{`${nodeId} -> ${fieldName}`}</Text>
+      <NodeFieldElementOverlay nodeId={nodeId} />
+    </Flex>
+  );
+});
+NodeOutputFieldPreview.displayName = 'NodeOutputFieldPreview';
+
+export const StartPublishFlowButton = memo(() => {
+  const { t } = useTranslation();
+  const allowPublishWorkflows = useAppSelector(selectAllowPublishWorkflows);
+  const isReadyToEnqueue = useStore($isReadyToEnqueue);
+  const isWorkflowSaved = useAppSelector(selectIsWorkflowSaved);
+  const hasBatchOrGeneratorNodes = useAppSelector(selectHasBatchOrGeneratorNodes);
+  const inputs = usePublishInputs();
+
+  const onClick = useCallback(() => {
+    $isInPublishFlow.set(true);
+  }, []);
+
+  return (
+    <PublishTooltip
+      isWorkflowSaved={isWorkflowSaved}
+      hasBatchOrGeneratorNodes={hasBatchOrGeneratorNodes}
+      isReadyToEnqueue={isReadyToEnqueue}
+      hasOutputNode={true}
+      hasPublishableInputs={inputs.publishable.length > 0}
+      hasUnpublishableInputs={inputs.unpublishable.length > 0}
+    >
+      <Button
+        onClick={onClick}
+        leftIcon={<PiLightningFill />}
+        variant="ghost"
+        size="sm"
+        isDisabled={!allowPublishWorkflows || !isReadyToEnqueue || !isWorkflowSaved || hasBatchOrGeneratorNodes}
+      >
+        {t('workflows.builder.publish')}
+      </Button>
+    </PublishTooltip>
+  );
+});
+
+StartPublishFlowButton.displayName = 'StartPublishFlowButton';
+
+const PublishTooltip = memo(
+  ({
+    isWorkflowSaved,
+    hasBatchOrGeneratorNodes,
+    isReadyToEnqueue,
+    hasOutputNode,
+    hasPublishableInputs,
+    hasUnpublishableInputs,
+    children,
+  }: PropsWithChildren<{
+    isWorkflowSaved: boolean;
+    hasBatchOrGeneratorNodes: boolean;
+    isReadyToEnqueue: boolean;
+    hasOutputNode: boolean;
+    hasPublishableInputs: boolean;
+    hasUnpublishableInputs: boolean;
+  }>) => {
+    const { t } = useTranslation();
+    const warnings = useMemo(() => {
+      const _warnings: string[] = [];
+      if (!hasPublishableInputs) {
+        _warnings.push(t('workflows.builder.warningWorkflowHasNoPublishableInputFields'));
+      }
+      if (hasUnpublishableInputs) {
+        _warnings.push(t('workflows.builder.warningWorkflowHasUnpublishableInputFields'));
+      }
+      return _warnings;
+    }, [hasPublishableInputs, hasUnpublishableInputs, t]);
+    const errors = useMemo(() => {
+      const _errors: string[] = [];
+      if (!isWorkflowSaved) {
+        _errors.push(t('workflows.builder.errorWorkflowHasUnsavedChanges'));
+      }
+      if (hasBatchOrGeneratorNodes) {
+        _errors.push(t('workflows.builder.errorWorkflowHasBatchOrGeneratorNodes'));
+      }
+      if (!isReadyToEnqueue) {
+        _errors.push(t('workflows.builder.errorWorkflowHasInvalidGraph'));
+      }
+      if (!hasOutputNode) {
+        _errors.push(t('workflows.builder.errorWorkflowHasNoOutputNode'));
+      }
+      return _errors;
+    }, [hasBatchOrGeneratorNodes, hasOutputNode, isReadyToEnqueue, isWorkflowSaved, t]);
+
+    if (errors.length === 0 && warnings.length === 0) {
+      return children;
+    }
+
+    return (
+      <Tooltip
+        label={
+          <Flex flexDir="column">
+            {errors.length > 0 && (
+              <>
+                <Text color="error.700" fontWeight="semibold">
+                  {t('workflows.builder.cannotPublish')}:
+                </Text>
+                <UnorderedList>
+                  {errors.map((problem, index) => (
+                    <ListItem key={index}>{problem}</ListItem>
+                  ))}
+                </UnorderedList>
+              </>
+            )}
+            {warnings.length > 0 && (
+              <>
+                <Text color="warning.700" fontWeight="semibold">
+                  {t('workflows.builder.publishWarnings')}:
+                </Text>
+                <UnorderedList>
+                  {warnings.map((problem, index) => (
+                    <ListItem key={index}>{problem}</ListItem>
+                  ))}
+                </UnorderedList>
+              </>
+            )}
+          </Flex>
+        }
+      >
+        {children}
+      </Tooltip>
+    );
+  }
+);
+PublishTooltip.displayName = 'PublishTooltip';

invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLibrary/WorkflowLibraryListItemActions/LockedWorkflowIcon.tsx

@@ -0,0 +1,23 @@
+import { IconButton, Tooltip } from '@invoke-ai/ui-library';
+import { memo } from 'react';
+import { useTranslation } from 'react-i18next';
+import { PiLockBold } from 'react-icons/pi';
+
+export const LockedWorkflowIcon = memo(() => {
+  const { t } = useTranslation();
+
+  return (
+    <Tooltip label={t('workflows.builder.publishedWorkflowsLocked')} closeOnScroll>
+      <IconButton
+        size="sm"
+        cursor="not-allowed"
+        variant="link"
+        alignSelf="stretch"
+        aria-label={t('workflows.builder.publishedWorkflowsLocked')}
+        icon={<PiLockBold />}
+      />
+    </Tooltip>
+  );
+});
+
+LockedWorkflowIcon.displayName = 'LockedWorkflowIcon';

invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLibrary/WorkflowLibrarySideNav.tsx

@@ -26,6 +26,7 @@ import {
   workflowLibraryTagToggled,
   workflowLibraryViewChanged,
 } from 'features/nodes/store/workflowLibrarySlice';
+import { selectAllowPublishWorkflows } from 'features/system/store/configSlice';
 import { NewWorkflowButton } from 'features/workflowLibrary/components/NewWorkflowButton';
 import { UploadWorkflowButton } from 'features/workflowLibrary/components/UploadWorkflowButton';
 import { OverlayScrollbarsComponent } from 'overlayscrollbars-react';
@@ -39,13 +40,12 @@ export const WorkflowLibrarySideNav = () => {
   const { t } = useTranslation();
   const categoryOptions = useStore($workflowLibraryCategoriesOptions);
   const view = useAppSelector(selectWorkflowLibraryView);
+  const allowPublishWorkflows = useAppSelector(selectAllowPublishWorkflows);
 
   return (
     <Flex h="full" minH={0} overflow="hidden" flexDir="column" w={64} gap={0}>
-      <Flex flexDir="column" w="full" pb={2}>
+      <Flex flexDir="column" w="full" pb={2} gap={2}>
         <WorkflowLibraryViewButton view="recent">{t('workflows.recentlyOpened')}</WorkflowLibraryViewButton>
-      </Flex>
-      <Flex flexDir="column" w="full" pb={2}>
         <WorkflowLibraryViewButton view="yours">{t('workflows.yourWorkflows')}</WorkflowLibraryViewButton>
         {categoryOptions.includes('project') && (
           <Collapse in={view === 'yours' || view === 'shared' || view === 'private'}>
@@ -60,6 +60,9 @@ export const WorkflowLibrarySideNav = () => {
             </Flex>
           </Collapse>
         )}
+        {allowPublishWorkflows && (
+          <WorkflowLibraryViewButton view="published">{t('workflows.published')}</WorkflowLibraryViewButton>
+        )}
       </Flex>
       <Flex h="full" minH={0} overflow="hidden" flexDir="column">
         <BrowseWorkflowsButton />

invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLibrary/WorkflowList.tsx

@@ -36,6 +36,8 @@ const getCategories = (view: WorkflowLibraryView): WorkflowCategory[] => {
       return ['user'];
     case 'shared':
       return ['project'];
+    case 'published':
+      return ['user', 'project', 'default'];
     default:
       assert<Equals<typeof view, never>>(false);
   }
@@ -66,6 +68,7 @@ const useInfiniteQueryAry = () => {
       query: debouncedSearchTerm,
       tags: view === 'defaults' ? selectedTags : [],
       has_been_opened: getHasBeenOpened(view),
+      is_published: view === 'published' ? true : undefined,
     } satisfies Parameters<typeof useListWorkflowsInfiniteInfiniteQuery>[0];
   }, [orderBy, direction, view, debouncedSearchTerm, selectedTags]);
 

invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLibrary/WorkflowListItem.tsx

@@ -1,6 +1,7 @@
 import type { SystemStyleObject } from '@invoke-ai/ui-library';
 import { Badge, Flex, Icon, Image, Spacer, Text } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { LockedWorkflowIcon } from 'features/nodes/components/sidePanel/workflow/WorkflowLibrary/WorkflowLibraryListItemActions/LockedWorkflowIcon';
 import { ShareWorkflowButton } from 'features/nodes/components/sidePanel/workflow/WorkflowLibrary/WorkflowLibraryListItemActions/ShareWorkflow';
 import { selectWorkflowId, workflowModeChanged } from 'features/nodes/store/workflowSlice';
 import { useLoadWorkflowWithDialog } from 'features/workflowLibrary/components/LoadWorkflowConfirmationAlertDialog';
@@ -54,7 +55,6 @@ export const WorkflowListItem = memo(({ workflow }: { workflow: WorkflowRecordLi
       position="relative"
       role="button"
       onClick={handleClickLoad}
-      cursor="pointer"
       bg="base.750"
       borderRadius="base"
       w="full"
@@ -81,7 +81,7 @@ export const WorkflowListItem = memo(({ workflow }: { workflow: WorkflowRecordLi
           <Flex gap={2} alignItems="flex-start" justifyContent="space-between" w="full">
             <Text noOfLines={2}>{workflow.name}</Text>
             <Flex gap={2} alignItems="center">
-              {isActive && (
+              {isActive && !workflow.is_published && (
                 <Badge
                   color="invokeBlue.400"
                   borderColor="invokeBlue.700"
@@ -93,6 +93,18 @@ export const WorkflowListItem = memo(({ workflow }: { workflow: WorkflowRecordLi
                   {t('workflows.opened')}
                 </Badge>
               )}
+              {workflow.is_published && (
+                <Badge
+                  color="invokeGreen.400"
+                  borderColor="invokeGreen.700"
+                  borderWidth={1}
+                  bg="transparent"
+                  flexShrink={0}
+                  variant="subtle"
+                >
+                  {t('workflows.builder.published')}
+                </Badge>
+              )}
               {workflow.category === 'project' && <Icon as={PiUsersBold} color="base.200" />}
               {workflow.category === 'default' && (
                 <Image
@@ -119,8 +131,10 @@ export const WorkflowListItem = memo(({ workflow }: { workflow: WorkflowRecordLi
             </Text>
           )}
           <Spacer />
-          {workflow.category === 'default' && <ViewWorkflow workflowId={workflow.workflow_id} />}
-          {workflow.category !== 'default' && (
+          {workflow.category === 'default' && !workflow.is_published && (
+            <ViewWorkflow workflowId={workflow.workflow_id} />
+          )}
+          {workflow.category !== 'default' && !workflow.is_published && (
             <>
               <EditWorkflow workflowId={workflow.workflow_id} />
               <DownloadWorkflow workflowId={workflow.workflow_id} />
@@ -128,6 +142,7 @@ export const WorkflowListItem = memo(({ workflow }: { workflow: WorkflowRecordLi
             </>
           )}
           {workflow.category === 'project' && <ShareWorkflowButton workflow={workflow} />}
+          {workflow.is_published && <LockedWorkflowIcon />}
         </Flex>
       </Flex>
     </Flex>

invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowPanel.tsx

@@ -1,5 +1,8 @@
-import { Tab, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
+import { Spacer, Tab, TabList, TabPanel, TabPanels, Tabs } from '@invoke-ai/ui-library';
+import { useAppSelector } from 'app/store/storeHooks';
 import { WorkflowBuilder } from 'features/nodes/components/sidePanel/builder/WorkflowBuilder';
+import { StartPublishFlowButton } from 'features/nodes/components/sidePanel/workflow/PublishWorkflowPanelContent';
+import { selectAllowPublishWorkflows } from 'features/system/store/configSlice';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
 
@@ -8,12 +11,15 @@ import WorkflowJSONTab from './WorkflowJSONTab';
 
 const WorkflowFieldsLinearViewPanel = () => {
   const { t } = useTranslation();
+  const allowPublishWorkflows = useAppSelector(selectAllowPublishWorkflows);
   return (
     <Tabs variant="enclosed" display="flex" w="full" h="full" flexDir="column">
       <TabList>
         <Tab>{t('workflows.builder.builder')}</Tab>
         <Tab>{t('common.details')}</Tab>
         <Tab>JSON</Tab>
+        <Spacer />
+        {allowPublishWorkflows && <StartPublishFlowButton />}
       </TabList>
 
       <TabPanels h="full" pt={2}>

invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/publish.ts

@@ -0,0 +1,90 @@
+import { useStore } from '@nanostores/react';
+import { createSelector } from '@reduxjs/toolkit';
+import { skipToken } from '@reduxjs/toolkit/query';
+import { useAppSelector } from 'app/store/storeHooks';
+import { $templates } from 'features/nodes/store/nodesSlice';
+import { selectNodesSlice } from 'features/nodes/store/selectors';
+import type { Templates } from 'features/nodes/store/types';
+import { selectWorkflowFormNodeFieldFieldIdentifiersDeduped } from 'features/nodes/store/workflowSlice';
+import type { FieldIdentifier } from 'features/nodes/types/field';
+import { isBoardFieldType } from 'features/nodes/types/field';
+import { isInvocationNode } from 'features/nodes/types/invocation';
+import { atom, computed } from 'nanostores';
+import { useMemo } from 'react';
+import { useGetBatchStatusQuery } from 'services/api/endpoints/queue';
+import { assert } from 'tsafe';
+
+export const $isInPublishFlow = atom(false);
+export const $outputNodeId = atom<string | null>(null);
+export const $isSelectingOutputNode = atom(false);
+export const $isReadyToDoValidationRun = computed(
+  [$isInPublishFlow, $outputNodeId, $isSelectingOutputNode],
+  (isInPublishFlow, outputNodeId, isSelectingOutputNode) => {
+    return isInPublishFlow && outputNodeId !== null && !isSelectingOutputNode;
+  }
+);
+export const $validationRunBatchId = atom<string | null>(null);
+
+export const useIsValidationRunInProgress = () => {
+  const validationRunBatchId = useStore($validationRunBatchId);
+  const { isValidationRunInProgress } = useGetBatchStatusQuery(
+    validationRunBatchId ? { batch_id: validationRunBatchId } : skipToken,
+    {
+      selectFromResult: ({ currentData }) => {
+        if (!currentData) {
+          return { isValidationRunInProgress: false };
+        }
+        if (currentData && currentData.in_progress > 0) {
+          return { isValidationRunInProgress: true };
+        }
+        return { isValidationRunInProgress: false };
+      },
+    }
+  );
+  return validationRunBatchId !== null || isValidationRunInProgress;
+};
+
+export const selectFieldIdentifiersWithInvocationTypes = createSelector(
+  selectWorkflowFormNodeFieldFieldIdentifiersDeduped,
+  selectNodesSlice,
+  (fieldIdentifiers, nodes) => {
+    const result: { nodeId: string; fieldName: string; type: string }[] = [];
+    for (const fieldIdentifier of fieldIdentifiers) {
+      const node = nodes.nodes.find((node) => node.id === fieldIdentifier.nodeId);
+      assert(isInvocationNode(node), `Node ${fieldIdentifier.nodeId} not found`);
+      result.push({ nodeId: fieldIdentifier.nodeId, fieldName: fieldIdentifier.fieldName, type: node.data.type });
+    }
+
+    return result;
+  }
+);
+
+export const getPublishInputs = (fieldIdentifiers: (FieldIdentifier & { type: string })[], templates: Templates) => {
+  // Certain field types are not allowed to be input fields on a published workflow
+  const publishable: FieldIdentifier[] = [];
+  const unpublishable: FieldIdentifier[] = [];
+  for (const fieldIdentifier of fieldIdentifiers) {
+    const fieldTemplate = templates[fieldIdentifier.type]?.inputs[fieldIdentifier.fieldName];
+    if (!fieldTemplate) {
+      unpublishable.push(fieldIdentifier);
+      continue;
+    }
+    if (isBoardFieldType(fieldTemplate.type)) {
+      unpublishable.push(fieldIdentifier);
+      continue;
+    }
+    publishable.push(fieldIdentifier);
+  }
+  return { publishable, unpublishable };
+};
+
+export const usePublishInputs = () => {
+  const templates = useStore($templates);
+  const fieldIdentifiersWithInvocationTypes = useAppSelector(selectFieldIdentifiersWithInvocationTypes);
+  const fieldIdentifiers = useMemo(
+    () => getPublishInputs(fieldIdentifiersWithInvocationTypes, templates),
+    [fieldIdentifiersWithInvocationTypes, templates]
+  );
+
+  return fieldIdentifiers;
+};

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

@@ -1,6 +1,6 @@
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplate';
+import { useInputFieldTemplateOrThrow } from 'features/nodes/hooks/useInputFieldTemplateOrThrow';
 import { fieldValueReset } from 'features/nodes/store/nodesSlice';
 import { selectNodesSlice } from 'features/nodes/store/selectors';
 import { isInvocationNode } from 'features/nodes/types/invocation';

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

@@ -1,10 +1,11 @@
 import { useNodeData } from 'features/nodes/hooks/useNodeData';
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import type { FieldInputTemplate } from 'features/nodes/types/field';
 import { isSingleOrCollection } from 'features/nodes/types/field';
 import { TEMPLATE_BUILDER_MAP } from 'features/nodes/util/schema/buildFieldInputTemplate';
 import { useMemo } from 'react';
 
+import { useNodeTemplateOrThrow } from './useNodeTemplateOrThrow';
+
 const isConnectionInputField = (field: FieldInputTemplate) => {
   return (
     (field.input === 'connection' && !isSingleOrCollection(field.type)) || !(field.type.name in TEMPLATE_BUILDER_MAP)
@@ -19,7 +20,7 @@ const isAnyOrDirectInputField = (field: FieldInputTemplate) => {
 };
 
 export const useInputFieldNamesMissing = (nodeId: string) => {
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const node = useNodeData(nodeId);
   const fieldNames = useMemo(() => {
     const instanceFields = new Set(Object.keys(node.inputs));
@@ -30,7 +31,7 @@ export const useInputFieldNamesMissing = (nodeId: string) => {
 };
 
 export const useInputFieldNamesAnyOrDirect = (nodeId: string) => {
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const fieldNames = useMemo(() => {
     const anyOrDirectFields: string[] = [];
     for (const [fieldName, fieldTemplate] of Object.entries(template.inputs)) {
@@ -44,7 +45,7 @@ export const useInputFieldNamesAnyOrDirect = (nodeId: string) => {
 };
 
 export const useInputFieldNamesConnection = (nodeId: string) => {
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const fieldNames = useMemo(() => {
     const connectionFields: string[] = [];
     for (const [fieldName, fieldTemplate] of Object.entries(template.inputs)) {

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

@@ -1,8 +1,9 @@
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import type { FieldInputTemplate } from 'features/nodes/types/field';
 import { useMemo } from 'react';
 import { assert } from 'tsafe';
 
+import { useNodeTemplateOrThrow } from './useNodeTemplateOrThrow';
+
 /**
  * Returns the template for a specific input field of a node.
  *
@@ -13,7 +14,7 @@ import { assert } from 'tsafe';
  * @throws Will throw an error if the template for the input field is not found.
  */
 export const useInputFieldTemplateOrThrow = (nodeId: string, fieldName: string): FieldInputTemplate => {
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const fieldTemplate = useMemo(() => {
     const _fieldTemplate = template.inputs[fieldName];
     assert(_fieldTemplate, `Template for input field ${fieldName} not found.`);
@@ -21,17 +22,3 @@ export const useInputFieldTemplateOrThrow = (nodeId: string, fieldName: string):
   }, [fieldName, template.inputs]);
   return fieldTemplate;
 };
-
-/**
- * Returns the template for a specific input field of a node.
- *
- * **Note:** This function is a safe version of `useInputFieldTemplate` and will not throw an error if the template is not found.
- *
- * @param nodeId - The ID of the node.
- * @param fieldName - The name of the input field.
- */
-export const useInputFieldTemplateSafe = (nodeId: string, fieldName: string): FieldInputTemplate | null => {
-  const template = useNodeTemplate(nodeId);
-  const fieldTemplate = useMemo(() => template.inputs[fieldName] ?? null, [fieldName, template.inputs]);
-  return fieldTemplate;
-};

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

@@ -0,0 +1,17 @@
+import { useNodeTemplateSafe } from 'features/nodes/hooks/useNodeTemplateSafe';
+import type { FieldInputTemplate } from 'features/nodes/types/field';
+import { useMemo } from 'react';
+
+/**
+ * Returns the template for a specific input field of a node.
+ *
+ * **Note:** This function is a safe version of `useInputFieldTemplate` and will not throw an error if the template is not found.
+ *
+ * @param nodeId - The ID of the node.
+ * @param fieldName - The name of the input field.
+ */
+export const useInputFieldTemplateSafe = (nodeId: string, fieldName: string): FieldInputTemplate | null => {
+  const template = useNodeTemplateSafe(nodeId);
+  const fieldTemplate = useMemo(() => template?.inputs[fieldName] ?? null, [fieldName, template?.inputs]);
+  return fieldTemplate;
+};

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

@@ -1,9 +1,10 @@
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import { useMemo } from 'react';
 import { assert } from 'tsafe';
 
-export const useInputFieldTemplateTitle = (nodeId: string, fieldName: string): string => {
-  const template = useNodeTemplate(nodeId);
+import { useNodeTemplateOrThrow } from './useNodeTemplateOrThrow';
+
+export const useInputFieldTemplateTitleOrThrow = (nodeId: string, fieldName: string): string => {
+  const template = useNodeTemplateOrThrow(nodeId);
 
   const title = useMemo(() => {
     const fieldTemplate = template.inputs[fieldName];

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

@@ -11,7 +11,7 @@ import { useMemo } from 'react';
  * @param nodeId The ID of the node
  * @param fieldName The name of the field
  */
-export const useInputFieldDescriptionSafe = (nodeId: string, fieldName: string) => {
+export const useInputFieldUserDescriptionSafe = (nodeId: string, fieldName: string) => {
   const selector = useMemo(
     () =>
       createSelector(

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

@@ -0,0 +1,23 @@
+import { createSelector } from '@reduxjs/toolkit';
+import { useAppSelector } from 'app/store/storeHooks';
+import { selectFieldInputInstance, selectNodesSlice } from 'features/nodes/store/selectors';
+import { useMemo } from 'react';
+
+/**
+ * Gets the user-defined title of an input field for a given node.
+ *
+ * If the node doesn't exist or is not an invocation node, an error is thrown.
+ *
+ * @param nodeId The ID of the node
+ * @param fieldName The name of the field
+ */
+export const useInputFieldUserTitleOrThrow = (nodeId: string, fieldName: string): string => {
+  const selector = useMemo(
+    () => createSelector(selectNodesSlice, (nodes) => selectFieldInputInstance(nodes, nodeId, fieldName).label),
+    [fieldName, nodeId]
+  );
+
+  const title = useAppSelector(selector);
+
+  return title;
+};

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

@@ -4,21 +4,21 @@ import { selectFieldInputInstanceSafe, selectNodesSlice } from 'features/nodes/s
 import { useMemo } from 'react';
 
 /**
- * Gets the user-defined label of an input field for a given node.
+ * Gets the user-defined title of an input field for a given node.
  *
  * If the node doesn't exist or is not an invocation node, an empty string is returned.
  *
  * @param nodeId The ID of the node
  * @param fieldName The name of the field
  */
-export const useInputFieldLabelSafe = (nodeId: string, fieldName: string): string => {
+export const useInputFieldUserTitleSafe = (nodeId: string, fieldName: string): string => {
   const selector = useMemo(
     () =>
       createSelector(selectNodesSlice, (nodes) => selectFieldInputInstanceSafe(nodes, nodeId, fieldName)?.label ?? ''),
     [fieldName, nodeId]
   );
 
-  const label = useAppSelector(selector);
+  const title = useAppSelector(selector);
 
-  return label;
+  return title;
 };

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

@@ -1,9 +1,10 @@
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import { isBatchNodeType, isGeneratorNodeType } from 'features/nodes/types/invocation';
 import { useMemo } from 'react';
 
+import { useNodeTemplateOrThrow } from './useNodeTemplateOrThrow';
+
 export const useIsExecutableNode = (nodeId: string) => {
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const isExecutableNode = useMemo(
     () => !isBatchNodeType(template.type) && !isGeneratorNodeType(template.type),
     [template]

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

@@ -0,0 +1,13 @@
+import { useStore } from '@nanostores/react';
+import { useAppSelector } from 'app/store/storeHooks';
+import { $isInPublishFlow, useIsValidationRunInProgress } from 'features/nodes/components/sidePanel/workflow/publish';
+import { selectWorkflowIsPublished } from 'features/nodes/store/workflowSlice';
+
+export const useIsWorkflowEditorLocked = () => {
+  const isInPublishFlow = useStore($isInPublishFlow);
+  const isPublished = useAppSelector(selectWorkflowIsPublished);
+  const isValidationRunInProgress = useIsValidationRunInProgress();
+
+  const isLocked = isInPublishFlow || isPublished || isValidationRunInProgress;
+  return isLocked;
+};

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

@@ -1,9 +1,10 @@
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import type { Classification } from 'features/nodes/types/common';
 import { useMemo } from 'react';
 
+import { useNodeTemplateOrThrow } from './useNodeTemplateOrThrow';
+
 export const useNodeClassification = (nodeId: string): Classification => {
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const classification = useMemo(() => template.classification, [template]);
   return classification;
 };

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

@@ -1,9 +1,10 @@
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import { some } from 'lodash-es';
 import { useMemo } from 'react';
 
+import { useNodeTemplateOrThrow } from './useNodeTemplateOrThrow';
+
 export const useNodeHasImageOutput = (nodeId: string): boolean => {
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const hasImageOutput = useMemo(
     () =>
       some(

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

@@ -1,12 +1,13 @@
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import { useNodeType } from 'features/nodes/hooks/useNodeType';
 import { useNodeVersion } from 'features/nodes/hooks/useNodeVersion';
 import { useMemo } from 'react';
 
+import { useNodeTemplateOrThrow } from './useNodeTemplateOrThrow';
+
 export const useNodeNeedsUpdate = (nodeId: string) => {
   const type = useNodeType(nodeId);
   const version = useNodeVersion(nodeId);
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const needsUpdate = useMemo(() => {
     if (type !== template.type) {
       return true;

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

@@ -5,7 +5,7 @@ import type { InvocationTemplate } from 'features/nodes/types/invocation';
 import { useMemo } from 'react';
 import { assert } from 'tsafe';
 
-export const useNodeTemplate = (nodeId: string): InvocationTemplate => {
+export const useNodeTemplateOrThrow = (nodeId: string): InvocationTemplate => {
   const templates = useStore($templates);
   const type = useNodeType(nodeId);
   const template = useMemo(() => {
@@ -15,10 +15,3 @@ export const useNodeTemplate = (nodeId: string): InvocationTemplate => {
   }, [templates, type]);
   return template;
 };
-
-export const useNodeTemplateSafe = (nodeId: string): InvocationTemplate | null => {
-  const templates = useStore($templates);
-  const type = useNodeType(nodeId);
-  const template = useMemo(() => templates[type] ?? null, [templates, type]);
-  return template;
-};

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

@@ -0,0 +1,12 @@
+import { useStore } from '@nanostores/react';
+import { useNodeType } from 'features/nodes/hooks/useNodeType';
+import { $templates } from 'features/nodes/store/nodesSlice';
+import type { InvocationTemplate } from 'features/nodes/types/invocation';
+import { useMemo } from 'react';
+
+export const useNodeTemplateSafe = (nodeId: string): InvocationTemplate | null => {
+  const templates = useStore($templates);
+  const type = useNodeType(nodeId);
+  const template = useMemo(() => templates[type] ?? null, [templates, type]);
+  return template;
+};

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

@@ -0,0 +1,25 @@
+import { useStore } from '@nanostores/react';
+import { createSelector } from '@reduxjs/toolkit';
+import { useAppSelector } from 'app/store/storeHooks';
+import { $templates } from 'features/nodes/store/nodesSlice';
+import { selectNodesSlice } from 'features/nodes/store/selectors';
+import { isInvocationNode } from 'features/nodes/types/invocation';
+import { useMemo } from 'react';
+import { assert } from 'tsafe';
+
+export const useNodeTemplateTitleOrThrow = (nodeId: string): string => {
+  const templates = useStore($templates);
+  const selector = useMemo(
+    () =>
+      createSelector(selectNodesSlice, (nodesSlice) => {
+        const node = nodesSlice.nodes.find((node) => node.id === nodeId);
+        assert(isInvocationNode(node), 'Node not found');
+        const template = templates[node.data.type];
+        assert(template, 'Template not found');
+        return template.title;
+      }),
+    [nodeId, templates]
+  );
+  const title = useAppSelector(selector);
+  return title;
+};

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

@@ -6,7 +6,7 @@ import { selectNodesSlice } from 'features/nodes/store/selectors';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { useMemo } from 'react';
 
-export const useNodeTemplateTitle = (nodeId: string): string | null => {
+export const useNodeTemplateTitleSafe = (nodeId: string): string | null => {
   const templates = useStore($templates);
   const selector = useMemo(
     () =>

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

@@ -0,0 +1,21 @@
+import { createSelector } from '@reduxjs/toolkit';
+import { useAppSelector } from 'app/store/storeHooks';
+import { selectNodesSlice } from 'features/nodes/store/selectors';
+import { isInvocationNode } from 'features/nodes/types/invocation';
+import { useMemo } from 'react';
+import { assert } from 'tsafe';
+
+export const useNodeUserTitleOrThrow = (nodeId: string) => {
+  const selector = useMemo(
+    () =>
+      createSelector(selectNodesSlice, (nodesSlice) => {
+        const node = nodesSlice.nodes.find((node) => node.id === nodeId);
+        assert(isInvocationNode(node), 'Node not found');
+        return node.data.label;
+      }),
+    [nodeId]
+  );
+
+  const title = useAppSelector(selector);
+  return title;
+};

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

@@ -3,16 +3,16 @@ import { useAppSelector } from 'app/store/storeHooks';
 import { selectNodesSlice } from 'features/nodes/store/selectors';
 import { useMemo } from 'react';
 
-export const useNodeLabel = (nodeId: string) => {
+export const useNodeUserTitleSafe = (nodeId: string) => {
   const selector = useMemo(
     () =>
       createSelector(selectNodesSlice, (nodesSlice) => {
         const node = nodesSlice.nodes.find((node) => node.id === nodeId);
-        return node?.data.label;
+        return node?.data.label ?? null;
       }),
     [nodeId]
   );
 
-  const label = useAppSelector(selector);
-  return label;
+  const title = useAppSelector(selector);
+  return title;
 };

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

@@ -1,10 +1,11 @@
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import { getSortedFilteredFieldNames } from 'features/nodes/util/node/getSortedFilteredFieldNames';
 import { map } from 'lodash-es';
 import { useMemo } from 'react';
 
+import { useNodeTemplateOrThrow } from './useNodeTemplateOrThrow';
+
 export const useOutputFieldNames = (nodeId: string): string[] => {
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const fieldNames = useMemo(() => getSortedFilteredFieldNames(map(template.outputs)), [template.outputs]);
   return fieldNames;
 };

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

@@ -1,10 +1,11 @@
-import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import type { FieldOutputTemplate } from 'features/nodes/types/field';
 import { useMemo } from 'react';
 import { assert } from 'tsafe';
 
+import { useNodeTemplateOrThrow } from './useNodeTemplateOrThrow';
+
 export const useOutputFieldTemplate = (nodeId: string, fieldName: string): FieldOutputTemplate => {
-  const template = useNodeTemplate(nodeId);
+  const template = useNodeTemplateOrThrow(nodeId);
   const fieldTemplate = useMemo(() => {
     const _fieldTemplate = template.outputs[fieldName];
     assert(_fieldTemplate, `Template for output field ${fieldName} not found`);

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

@@ -4,14 +4,14 @@ import { useCallback } from 'react';
 
 const log = logger('workflows');
 
-export const useZoomToNode = () => {
-  const zoomToNode = useCallback((nodeId: string) => {
+export const useZoomToNode = (nodeId: string) => {
+  const zoomToNode = useCallback(() => {
     const flow = $flow.get();
     if (!flow) {
       log.warn('No flow instance found, cannot zoom to node');
       return;
     }
     flow.fitView({ duration: 300, maxZoom: 1.5, nodes: [{ id: nodeId }] });
-  }, []);
+  }, [nodeId]);
   return zoomToNode;
 };

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

@@ -4,7 +4,7 @@ import type { RootState } from 'app/store/store';
 import type { NodesState } from 'features/nodes/store/types';
 import type { FieldInputInstance } from 'features/nodes/types/field';
 import type { AnyNode, InvocationNode, InvocationNodeData } from 'features/nodes/types/invocation';
-import { isInvocationNode } from 'features/nodes/types/invocation';
+import { isBatchNode, isGeneratorNode, isInvocationNode } from 'features/nodes/types/invocation';
 import { assert } from 'tsafe';
 
 export const selectNode = (nodesSlice: NodesState, nodeId: string): AnyNode => {
@@ -81,3 +81,7 @@ export const selectMayRedo = createSelector(
   (state: RootState) => state.nodes,
   (nodes) => nodes.future.length > 0
 );
+
+export const selectHasBatchOrGeneratorNodes = createSelector(selectNodes, (nodes) =>
+  nodes.filter(isInvocationNode).some((node) => isBatchNode(node) || isGeneratorNode(node))
+);

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

@@ -5,7 +5,7 @@ import type { WorkflowCategory } from 'features/nodes/types/workflow';
 import { atom, computed } from 'nanostores';
 import type { SQLiteDirection, WorkflowRecordOrderBy } from 'services/api/types';
 
-export type WorkflowLibraryView = 'recent' | 'yours' | 'private' | 'shared' | 'defaults';
+export type WorkflowLibraryView = 'recent' | 'yours' | 'private' | 'shared' | 'defaults' | 'published';
 
 type WorkflowLibraryState = {
   view: WorkflowLibraryView;