Feature/raster blend boolean

docs/RELEASE.md

@@ -16,7 +16,9 @@ The launcher uses GitHub as the source of truth for available releases.
 
 ## General Prep
 
-Make a developer call-out for PRs to merge. Merge and test things out. Bump the version by editing `invokeai/version/invokeai_version.py`.
+Make a developer call-out for PRs to merge. Merge and test things
+out. Create a branch with a name like user/chore/vX.X.X-prep and bump the version by editing
+`invokeai/version/invokeai_version.py` and commit locally.
 
 ## Release Workflow
 
@@ -26,14 +28,14 @@ It is triggered on **tag push**, when the tag matches `v*`.
 
 ### Triggering the Workflow
 
-Ensure all commits that should be in the release are merged, and you have pulled them locally.
-
-Double-check that you have checked out the commit that will represent the release (typically the latest commit on `main`).
+Ensure all commits that should be in the release are merged into this branch, and that you have pulled them locally.
 
 Run `make tag-release` to tag the current commit and kick off the workflow. You will be prompted to provide a message - use the version specifier.
 
 If this version's tag already exists for some reason (maybe you had to make a last minute change), the script will overwrite it.
 
+Push the commit to trigger the workflow.
+
 > In case you cannot use the Make target, the release may also be dispatched [manually] via GH.
 
 ### Workflow Jobs and Process
@@ -89,7 +91,7 @@ The publish jobs will not run if any of the previous jobs fail.
 
 They use [GitHub environments], which are configured as [trusted publishers] on PyPI.
 
-Both jobs require a @hipsterusername or @psychedelicious to approve them from the workflow's **Summary** tab.
+Both jobs require a @lstein or @blessedcoolant to approve them from the workflow's **Summary** tab.
 
 - Click the **Review deployments** button
 - Select the environment (either `testpypi` or `pypi` - typically you select both)
@@ -101,7 +103,7 @@ Both jobs require a @hipsterusername or @psychedelicious to approve them from th
 
 Check the [python infrastructure status page] for incidents.
 
-If there are no incidents, contact @hipsterusername or @lstein, who have owner access to GH and PyPI, to see if access has expired or something like that.
+If there are no incidents, contact @lstein or @blessedcoolant, who have owner access to GH and PyPI, to see if access has expired or something like that.
 
 #### `publish-testpypi` Job
 

invokeai/app/api/routers/workflows.py

@@ -223,6 +223,15 @@ async def get_workflow_thumbnail(
         raise HTTPException(status_code=404)
 
 
+@workflows_router.get("/tags", operation_id="get_all_tags")
+async def get_all_tags(
+    categories: Optional[list[WorkflowCategory]] = Query(default=None, description="The categories to include"),
+) -> list[str]:
+    """Gets all unique tags from workflows"""
+
+    return ApiDependencies.invoker.services.workflow_records.get_all_tags(categories=categories)
+
+
 @workflows_router.get("/counts_by_tag", operation_id="get_counts_by_tag")
 async def get_counts_by_tag(
     tags: list[str] = Query(description="The tags to get counts for"),

invokeai/app/invocations/fields.py

@@ -243,6 +243,12 @@ class BoardField(BaseModel):
     board_id: str = Field(description="The id of the board")
 
 
+class StylePresetField(BaseModel):
+    """A style preset primitive field"""
+
+    style_preset_id: str = Field(description="The id of the style preset")
+
+
 class DenoiseMaskField(BaseModel):
     """An inpaint mask field"""
 
@@ -327,6 +333,11 @@ class ZImageConditioningField(BaseModel):
     """A Z-Image conditioning tensor primitive value"""
 
     conditioning_name: str = Field(description="The name of conditioning tensor")
+    mask: Optional[TensorField] = Field(
+        default=None,
+        description="The mask associated with this conditioning tensor for regional prompting. "
+        "Excluded regions should be set to False, included regions should be set to True.",
+    )
 
 
 class ConditioningField(BaseModel):

invokeai/app/invocations/prompt_template.py

@@ -0,0 +1,57 @@
+from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
+from invokeai.app.invocations.fields import InputField, OutputField, StylePresetField, UIComponent
+from invokeai.app.services.shared.invocation_context import InvocationContext
+
+
+@invocation_output("prompt_template_output")
+class PromptTemplateOutput(BaseInvocationOutput):
+    """Output for the Prompt Template node"""
+
+    positive_prompt: str = OutputField(description="The positive prompt with the template applied")
+    negative_prompt: str = OutputField(description="The negative prompt with the template applied")
+
+
+@invocation(
+    "prompt_template",
+    title="Prompt Template",
+    tags=["prompt", "template", "style", "preset"],
+    category="prompt",
+    version="1.0.0",
+)
+class PromptTemplateInvocation(BaseInvocation):
+    """Applies a Style Preset template to positive and negative prompts.
+
+    Select a Style Preset and provide positive/negative prompts. The node replaces
+    {prompt} placeholders in the template with your input prompts.
+    """
+
+    style_preset: StylePresetField = InputField(
+        description="The Style Preset to use as a template",
+    )
+    positive_prompt: str = InputField(
+        default="",
+        description="The positive prompt to insert into the template's {prompt} placeholder",
+        ui_component=UIComponent.Textarea,
+    )
+    negative_prompt: str = InputField(
+        default="",
+        description="The negative prompt to insert into the template's {prompt} placeholder",
+        ui_component=UIComponent.Textarea,
+    )
+
+    def invoke(self, context: InvocationContext) -> PromptTemplateOutput:
+        # Fetch the style preset from the database
+        style_preset = context._services.style_preset_records.get(self.style_preset.style_preset_id)
+
+        # Get the template prompts
+        positive_template = style_preset.preset_data.positive_prompt
+        negative_template = style_preset.preset_data.negative_prompt
+
+        # Replace {prompt} placeholder with the input prompts
+        rendered_positive = positive_template.replace("{prompt}", self.positive_prompt)
+        rendered_negative = negative_template.replace("{prompt}", self.negative_prompt)
+
+        return PromptTemplateOutput(
+            positive_prompt=rendered_positive,
+            negative_prompt=rendered_negative,
+        )

invokeai/app/invocations/z_image_control.py

@@ -0,0 +1,112 @@
+# Copyright (c) 2024, Lincoln D. Stein and the InvokeAI Development Team
+"""Z-Image Control invocation for spatial conditioning."""
+
+from pydantic import BaseModel, Field
+
+from invokeai.app.invocations.baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    Classification,
+    invocation,
+    invocation_output,
+)
+from invokeai.app.invocations.fields import (
+    FieldDescriptions,
+    ImageField,
+    InputField,
+    OutputField,
+)
+from invokeai.app.invocations.model import ModelIdentifierField
+from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.backend.model_manager.taxonomy import BaseModelType, ModelType
+
+
+class ZImageControlField(BaseModel):
+    """A Z-Image control conditioning field for spatial control (Canny, HED, Depth, Pose, MLSD)."""
+
+    image_name: str = Field(description="The name of the preprocessed control image")
+    control_model: ModelIdentifierField = Field(description="The Z-Image ControlNet adapter model")
+    control_context_scale: float = Field(
+        default=0.75,
+        ge=0.0,
+        le=2.0,
+        description="The strength of the control signal. Recommended range: 0.65-0.80.",
+    )
+    begin_step_percent: float = Field(
+        default=0.0,
+        ge=0.0,
+        le=1.0,
+        description="When the control is first applied (% of total steps)",
+    )
+    end_step_percent: float = Field(
+        default=1.0,
+        ge=0.0,
+        le=1.0,
+        description="When the control is last applied (% of total steps)",
+    )
+
+
+@invocation_output("z_image_control_output")
+class ZImageControlOutput(BaseInvocationOutput):
+    """Z-Image Control output containing control configuration."""
+
+    control: ZImageControlField = OutputField(description="Z-Image control conditioning")
+
+
+@invocation(
+    "z_image_control",
+    title="Z-Image ControlNet",
+    tags=["image", "z-image", "control", "controlnet"],
+    category="control",
+    version="1.1.0",
+    classification=Classification.Prototype,
+)
+class ZImageControlInvocation(BaseInvocation):
+    """Configure Z-Image ControlNet for spatial conditioning.
+
+    Takes a preprocessed control image (e.g., Canny edges, depth map, pose)
+    and a Z-Image ControlNet adapter model to enable spatial control.
+
+    Supports 5 control modes: Canny, HED, Depth, Pose, MLSD.
+    Recommended control_context_scale: 0.65-0.80.
+    """
+
+    image: ImageField = InputField(
+        description="The preprocessed control image (Canny, HED, Depth, Pose, or MLSD)",
+    )
+    control_model: ModelIdentifierField = InputField(
+        description=FieldDescriptions.controlnet_model,
+        title="Control Model",
+        ui_model_base=BaseModelType.ZImage,
+        ui_model_type=ModelType.ControlNet,
+    )
+    control_context_scale: float = InputField(
+        default=0.75,
+        ge=0.0,
+        le=2.0,
+        description="Strength of the control signal. Recommended range: 0.65-0.80.",
+        title="Control Scale",
+    )
+    begin_step_percent: float = InputField(
+        default=0.0,
+        ge=0.0,
+        le=1.0,
+        description="When the control is first applied (% of total steps)",
+    )
+    end_step_percent: float = InputField(
+        default=1.0,
+        ge=0.0,
+        le=1.0,
+        description="When the control is last applied (% of total steps)",
+    )
+
+    def invoke(self, context: InvocationContext) -> ZImageControlOutput:
+        return ZImageControlOutput(
+            control=ZImageControlField(
+                image_name=self.image.image_name,
+                control_model=self.control_model,
+                control_context_scale=self.control_context_scale,
+                begin_step_percent=self.begin_step_percent,
+                end_step_percent=self.end_step_percent,
+            )
+        )