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.github/workflows/frontend-checks.yml

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@@ -44,7 +44,12 @@ jobs:
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- name: check for changed frontend files
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if: ${{ inputs.always_run != true }}
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id: changed-files
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uses: tj-actions/changed-files@v42
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# Pinned to the _hash_ for v45.0.9 to prevent supply-chain attacks.
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# See:
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# - CVE-2025-30066
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# - https://www.stepsecurity.io/blog/harden-runner-detection-tj-actions-changed-files-action-is-compromised
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# - https://github.com/tj-actions/changed-files/issues/2463
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uses: tj-actions/changed-files@a284dc1814e3fd07f2e34267fc8f81227ed29fb8
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with:
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files_yaml: |
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frontend:

.github/workflows/frontend-tests.yml

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- name: check for changed frontend files
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if: ${{ inputs.always_run != true }}
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id: changed-files
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uses: tj-actions/changed-files@v42
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# Pinned to the _hash_ for v45.0.9 to prevent supply-chain attacks.
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# See:
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# - CVE-2025-30066
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# - https://www.stepsecurity.io/blog/harden-runner-detection-tj-actions-changed-files-action-is-compromised
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# - https://github.com/tj-actions/changed-files/issues/2463
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uses: tj-actions/changed-files@a284dc1814e3fd07f2e34267fc8f81227ed29fb8
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with:
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files_yaml: |
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frontend:

.github/workflows/python-checks.yml

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- name: check for changed python files
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if: ${{ inputs.always_run != true }}
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id: changed-files
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uses: tj-actions/changed-files@v42
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# Pinned to the _hash_ for v45.0.9 to prevent supply-chain attacks.
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# See:
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# - CVE-2025-30066
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# - https://www.stepsecurity.io/blog/harden-runner-detection-tj-actions-changed-files-action-is-compromised
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# - https://github.com/tj-actions/changed-files/issues/2463
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uses: tj-actions/changed-files@a284dc1814e3fd07f2e34267fc8f81227ed29fb8
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with:
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files_yaml: |
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python:

.github/workflows/python-tests.yml

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- name: check for changed python files
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if: ${{ inputs.always_run != true }}
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id: changed-files
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uses: tj-actions/changed-files@v42
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# Pinned to the _hash_ for v45.0.9 to prevent supply-chain attacks.
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# See:
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# - CVE-2025-30066
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# - https://www.stepsecurity.io/blog/harden-runner-detection-tj-actions-changed-files-action-is-compromised
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# - https://github.com/tj-actions/changed-files/issues/2463
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uses: tj-actions/changed-files@a284dc1814e3fd07f2e34267fc8f81227ed29fb8
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with:
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files_yaml: |
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python:

.github/workflows/typegen-checks.yml

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- name: check for changed files
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if: ${{ inputs.always_run != true }}
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id: changed-files
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uses: tj-actions/changed-files@v42
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# Pinned to the _hash_ for v45.0.9 to prevent supply-chain attacks.
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# See:
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# - CVE-2025-30066
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# - https://www.stepsecurity.io/blog/harden-runner-detection-tj-actions-changed-files-action-is-compromised
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# - https://github.com/tj-actions/changed-files/issues/2463
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uses: tj-actions/changed-files@a284dc1814e3fd07f2e34267fc8f81227ed29fb8
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with:
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files_yaml: |
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src:

invokeai/app/invocations/compel.py

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@invocation(
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"compel",
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title="Prompt",
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title="Prompt - SD1.5",
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tags=["prompt", "compel"],
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category="conditioning",
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version="1.2.0",
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version="1.2.1",
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)
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class CompelInvocation(BaseInvocation):
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"""Parse prompt using compel package to conditioning."""
@@ -233,10 +233,10 @@ def _lora_loader() -> Iterator[Tuple[ModelPatchRaw, float]]:
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@invocation(
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"sdxl_compel_prompt",
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title="SDXL Prompt",
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title="Prompt - SDXL",
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tags=["sdxl", "compel", "prompt"],
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category="conditioning",
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version="1.2.0",
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version="1.2.1",
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)
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class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
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"""Parse prompt using compel package to conditioning."""
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@invocation(
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"sdxl_refiner_compel_prompt",
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title="SDXL Refiner Prompt",
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title="Prompt - SDXL Refiner",
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tags=["sdxl", "compel", "prompt"],
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category="conditioning",
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version="1.1.1",
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version="1.1.2",
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)
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class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
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"""Parse prompt using compel package to conditioning."""
@@ -376,10 +376,10 @@ class CLIPSkipInvocationOutput(BaseInvocationOutput):
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@invocation(
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"clip_skip",
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title="CLIP Skip",
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title="Apply CLIP Skip - SD1.5, SDXL",
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tags=["clipskip", "clip", "skip"],
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category="conditioning",
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version="1.1.0",
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version="1.1.1",
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)
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class CLIPSkipInvocation(BaseInvocation):
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"""Skip layers in clip text_encoder model."""

invokeai/app/invocations/controlnet_image_processors.py

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@@ -87,7 +87,7 @@ class ControlOutput(BaseInvocationOutput):
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control: ControlField = OutputField(description=FieldDescriptions.control)
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@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet", version="1.1.2")
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@invocation("controlnet", title="ControlNet - SD1.5, SDXL", tags=["controlnet"], category="controlnet", version="1.1.3")
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class ControlNetInvocation(BaseInvocation):
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"""Collects ControlNet info to pass to other nodes"""
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invokeai/app/invocations/denoise_latents.py

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@@ -127,10 +127,10 @@ def get_scheduler(
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@invocation(
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"denoise_latents",
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title="Denoise Latents",
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title="Denoise - SD1.5, SDXL",
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tags=["latents", "denoise", "txt2img", "t2i", "t2l", "img2img", "i2i", "l2l"],
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category="latents",
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version="1.5.3",
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version="1.5.4",
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)
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class DenoiseLatentsInvocation(BaseInvocation):
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"""Denoises noisy latents to decodable images"""

invokeai/app/invocations/fields.py

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@@ -59,6 +59,7 @@ class UIType(str, Enum, metaclass=MetaEnum):
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ControlLoRAModel = "ControlLoRAModelField"
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SigLipModel = "SigLipModelField"
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FluxReduxModel = "FluxReduxModelField"
62+
LlavaOnevisionModel = "LLaVAModelField"
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# endregion
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# region Misc Field Types
@@ -205,6 +206,7 @@ class FieldDescriptions:
205206
freeu_b2 = "Scaling factor for stage 2 to amplify the contributions of backbone features."
206207
instantx_control_mode = "The control mode for InstantX ControlNet union models. Ignored for other ControlNet models. The standard mapping is: canny (0), tile (1), depth (2), blur (3), pose (4), gray (5), low quality (6). Negative values will be treated as 'None'."
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flux_redux_conditioning = "FLUX Redux conditioning tensor"
209+
vllm_model = "The VLLM model to use"
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class ImageField(BaseModel):

invokeai/app/invocations/flux_control_lora_loader.py

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@@ -21,10 +21,10 @@ class FluxControlLoRALoaderOutput(BaseInvocationOutput):
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@invocation(
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"flux_control_lora_loader",
24-
title="Flux Control LoRA",
24+
title="Control LoRA - FLUX",
2525
tags=["lora", "model", "flux"],
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category="model",
27-
version="1.1.0",
27+
version="1.1.1",
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classification=Classification.Prototype,
2929
)
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class FluxControlLoRALoaderInvocation(BaseInvocation):

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