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9 changed files with 62 additions and 82 deletions

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@ -260,7 +260,7 @@ def resolve_cast_module_with_vbar(s, dtype, device, bias_dtype, compute_dtype, w
def cast_bias_weight(s, input=None, dtype=None, device=None, bias_dtype=None, offloadable=False, compute_dtype=None, want_requant=False):
# NOTE: offloadable=False is a legacy mode and if you are a custom node author reading this please pass
# NOTE: offloadable=False is a a legacy and if you are a custom node author reading this please pass
# offloadable=True and call uncast_bias_weight() after your last usage of the weight/bias. This
# will add async-offload support to your cast and improve performance.
if input is not None:

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@ -543,7 +543,7 @@ class AudioConcat(IO.ComfyNode):
return IO.Schema(
node_id="AudioConcat",
search_aliases=["join audio", "combine audio", "append audio"],
display_name="Audio Concat",
display_name="Concatenate Audio",
description="Concatenates the audio1 to audio2 in the specified direction.",
category="audio",
inputs=[
@ -597,7 +597,7 @@ class AudioMerge(IO.ComfyNode):
return IO.Schema(
node_id="AudioMerge",
search_aliases=["mix audio", "overlay audio", "layer audio"],
display_name="Audio Merge",
display_name="Merge Audio",
description="Combine two audio tracks by overlaying their waveforms.",
category="audio",
inputs=[
@ -667,7 +667,7 @@ class AudioAdjustVolume(IO.ComfyNode):
return IO.Schema(
node_id="AudioAdjustVolume",
search_aliases=["audio gain", "loudness", "audio level"],
display_name="Audio Adjust Volume",
display_name="Adjust Audio Volume",
category="audio",
inputs=[
IO.Audio.Input("audio"),

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@ -47,8 +47,8 @@ class LoadImageDataSetFromFolderNode(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="LoadImageDataSetFromFolder",
display_name="Load Image Dataset from Folder",
category="dataset",
display_name="Load Image (from Folder)",
category="image",
is_experimental=True,
inputs=[
io.Combo.Input(
@ -403,7 +403,7 @@ class ImageProcessingNode(io.ComfyNode):
return io.Schema(
node_id=cls.node_id,
display_name=cls.display_name or cls.node_id,
category="dataset/image",
category=cls.category,
is_experimental=True,
is_input_list=is_group, # True for group, False for individual
inputs=inputs,
@ -627,8 +627,10 @@ class TextProcessingNode(io.ComfyNode):
class ResizeImagesByShorterEdgeNode(ImageProcessingNode):
node_id = "ResizeImagesByShorterEdge"
display_name = "Resize Images by Shorter Edge"
display_name = "Resize Images by Shorter Edge (DEPRECATED)"
category = "image/transform"
description = "Resize images so that the shorter edge matches the specified length while preserving aspect ratio."
is_deprecated = True # This node is superseded by Resize Image/Mask with resize_type = scale shorter dimension
extra_inputs = [
io.Int.Input(
"shorter_edge",
@ -655,8 +657,10 @@ class ResizeImagesByShorterEdgeNode(ImageProcessingNode):
class ResizeImagesByLongerEdgeNode(ImageProcessingNode):
node_id = "ResizeImagesByLongerEdge"
display_name = "Resize Images by Longer Edge"
display_name = "Resize Images by Longer Edge (DEPRECATED)"
category = "image/transform"
description = "Resize images so that the longer edge matches the specified length while preserving aspect ratio."
is_deprecated = True # This node is superseded by Resize Image/Mask with resize_type = scale longer dimension
extra_inputs = [
io.Int.Input(
"longer_edge",
@ -686,8 +690,10 @@ class ResizeImagesByLongerEdgeNode(ImageProcessingNode):
class CenterCropImagesNode(ImageProcessingNode):
node_id = "CenterCropImages"
display_name = "Center Crop Images"
description = "Center crop all images to the specified dimensions."
search_aliases=["crop", "cut", "trim"]
display_name="Crop Image (Center)"
category="image/transform"
description = "Center crop an image to the specified dimensions."
extra_inputs = [
io.Int.Input("width", default=512, min=1, max=8192, tooltip="Crop width."),
io.Int.Input("height", default=512, min=1, max=8192, tooltip="Crop height."),
@ -706,10 +712,11 @@ class CenterCropImagesNode(ImageProcessingNode):
class RandomCropImagesNode(ImageProcessingNode):
node_id = "RandomCropImages"
display_name = "Random Crop Images"
description = (
"Randomly crop all images to the specified dimensions (for data augmentation)."
)
search_aliases=["crop", "cut", "trim"]
display_name = "Crop Image (Random)"
category="image/transform"
description = "Randomly crop an image to the specified dimensions."
extra_inputs = [
io.Int.Input("width", default=512, min=1, max=8192, tooltip="Crop width."),
io.Int.Input("height", default=512, min=1, max=8192, tooltip="Crop height."),
@ -734,7 +741,9 @@ class RandomCropImagesNode(ImageProcessingNode):
class NormalizeImagesNode(ImageProcessingNode):
node_id = "NormalizeImages"
search_aliases=["normalize", "align"]
display_name = "Normalize Images"
category = "image/transform"
description = "Normalize images using mean and standard deviation."
extra_inputs = [
io.Float.Input(
@ -762,8 +771,10 @@ class NormalizeImagesNode(ImageProcessingNode):
class AdjustBrightnessNode(ImageProcessingNode):
node_id = "AdjustBrightness"
search_aliases=["brightness"]
display_name = "Adjust Brightness"
description = "Adjust brightness of all images."
category="image/adjustments"
description = "Adjust the brightness of an image."
extra_inputs = [
io.Float.Input(
"factor",
@ -781,8 +792,10 @@ class AdjustBrightnessNode(ImageProcessingNode):
class AdjustContrastNode(ImageProcessingNode):
node_id = "AdjustContrast"
search_aliases=["contrast"]
display_name = "Adjust Contrast"
description = "Adjust contrast of all images."
category="image/adjustments"
description = "Adjust the contrast of an image."
extra_inputs = [
io.Float.Input(
"factor",
@ -800,8 +813,10 @@ class AdjustContrastNode(ImageProcessingNode):
class ShuffleDatasetNode(ImageProcessingNode):
node_id = "ShuffleDataset"
display_name = "Shuffle Image Dataset"
description = "Randomly shuffle the order of images in the dataset."
search_aliases=["shuffle", "randomize", "mix"]
display_name = "Shuffle Images"
category = "image/batch"
description = "Randomly shuffle the order of images in a list."
is_group_process = True # Requires full list to shuffle
extra_inputs = [
io.Int.Input(
@ -823,13 +838,15 @@ class ShuffleImageTextDatasetNode(io.ComfyNode):
def define_schema(cls):
return io.Schema(
node_id="ShuffleImageTextDataset",
display_name="Shuffle Image-Text Dataset",
category="dataset/image",
search_aliases=["shuffle", "randomize", "mix"],
display_name = "Shuffle Pairs of Image-Text",
category = "image/batch",
description = "Randomly shuffle the order of pairs of image-text in a list.",
is_experimental=True,
is_input_list=True,
inputs=[
io.Image.Input("images", tooltip="List of images to shuffle."),
io.String.Input("texts", tooltip="List of texts to shuffle."),
io.String.Input("texts", tooltip="List of texts to shuffle.", force_input=True),
io.Int.Input(
"seed",
default=0,
@ -952,11 +969,13 @@ class StripWhitespaceNode(TextProcessingNode):
class ImageDeduplicationNode(ImageProcessingNode):
"""Remove duplicate or very similar images from the dataset using perceptual hashing."""
"""Remove duplicate or very similar images from a list using perceptual hashing."""
node_id = "ImageDeduplication"
display_name = "Image Deduplication"
description = "Remove duplicate or very similar images from the dataset."
search_aliases=["deduplicate", "remove duplicates", "similarity filter"]
display_name = "Deduplicate Images"
category = "image/batch"
description = "Remove duplicate or very similar images from a list."
is_group_process = True # Requires full list to compare images
extra_inputs = [
io.Float.Input(
@ -1026,7 +1045,9 @@ class ImageGridNode(ImageProcessingNode):
"""Combine multiple images into a single grid/collage."""
node_id = "ImageGrid"
display_name = "Image Grid"
searrch_aliases=["grid", "collage", "combine"]
display_name = "Make Image Grid"
category="image/batch"
description = "Arrange multiple images into a grid layout."
is_group_process = True # Requires full list to create grid
is_output_list = False # Outputs single grid image
@ -1102,9 +1123,12 @@ class MergeImageListsNode(ImageProcessingNode):
"""Merge multiple image lists into a single list."""
node_id = "MergeImageLists"
display_name = "Merge Image Lists"
search_aliases=["list", "merge list", "make list"]
display_name = "Merge Image Lists (DEPRECATED)"
category = "image/batch"
description = "Concatenate multiple image lists into one."
is_group_process = True # Receives images as list
is_deprecated = True # This node is superseded by Create List
@classmethod
def _group_process(cls, images):

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@ -419,7 +419,7 @@ class VoxelToMeshBasic(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="VoxelToMeshBasic",
display_name="Voxel to Mesh (Basic)",
display_name="Voxel to Mesh (Basic) (DEPRECATED)",
category="3d",
inputs=[
IO.Voxel.Input("voxel"),
@ -427,7 +427,8 @@ class VoxelToMeshBasic(IO.ComfyNode):
],
outputs=[
IO.Mesh.Output(),
]
],
is_deprecated=True,
)
@classmethod
@ -455,7 +456,7 @@ class VoxelToMesh(IO.ComfyNode):
category="3d",
inputs=[
IO.Voxel.Input("voxel"),
IO.Combo.Input("algorithm", options=["surface net", "basic"], advanced=True),
IO.Combo.Input("algorithm", options=["surface net", "basic"]),
IO.Float.Input("threshold", default=0.6, min=-1.0, max=1.0, step=0.01),
],
outputs=[

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@ -55,9 +55,10 @@ class ImageCropV2(IO.ComfyNode):
def define_schema(cls):
return IO.Schema(
node_id="ImageCropV2",
search_aliases=["trim"],
search_aliases=["crop", "cut", "trim"],
display_name="Crop Image",
category="image/transform",
description = "Crop an image to the specified dimensions.",
essentials_category="Image Tools",
has_intermediate_output=True,
inputs=[

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@ -77,7 +77,7 @@ class EmptyLTXVLatentVideo(io.ComfyNode):
@classmethod
def execute(cls, width, height, length, batch_size=1) -> io.NodeOutput:
latent = torch.zeros([batch_size, 128, ((length - 1) // 8) + 1, height // 32, width // 32], device=comfy.model_management.intermediate_device())
return io.NodeOutput({"samples": latent, "downscale_ratio_spacial": 32})
return io.NodeOutput({"samples": latent})
generate = execute # TODO: remove

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@ -11,8 +11,8 @@ class LTXVAudioVAELoader(io.ComfyNode):
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="LTXVAudioVAELoader",
display_name="LTXV Audio VAE Loader",
category="audio",
display_name="Load LTXV Audio VAE",
category="loaders",
inputs=[
io.Combo.Input(
"ckpt_name",
@ -40,7 +40,7 @@ class LTXVAudioVAEEncode(VAEEncodeAudio):
return io.Schema(
node_id="LTXVAudioVAEEncode",
display_name="LTXV Audio VAE Encode",
category="audio",
category="latent/audio",
inputs=[
io.Audio.Input("audio", tooltip="The audio to be encoded."),
io.Vae.Input(
@ -63,7 +63,7 @@ class LTXVAudioVAEDecode(io.ComfyNode):
return io.Schema(
node_id="LTXVAudioVAEDecode",
display_name="LTXV Audio VAE Decode",
category="audio",
category="latent/audio",
inputs=[
io.Latent.Input("samples", tooltip="The latent to be decoded."),
io.Vae.Input(

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@ -1,41 +1,10 @@
import re
import json
import string
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io
class StringFormat(io.ComfyNode):
@classmethod
def define_schema(cls) -> io.Schema:
autogrow = io.Autogrow.TemplateNames(
input=io.AnyType.Input("value"),
names=list(string.ascii_lowercase),
min=0,
)
return io.Schema(
node_id="StringFormat",
display_name="Format Text",
category="text",
search_aliases=["string", "format"],
description="Same as Python's string format method. Supports all of Python's format options and features.",
inputs=[
io.Autogrow.Input("values", template=autogrow),
io.String.Input("f_string", default="{a}", multiline=True),
],
outputs=[
io.String.Output(),
],
)
@classmethod
def execute(
cls, values: io.Autogrow.Type, f_string: str
) -> io.NodeOutput:
return io.NodeOutput(f_string.format(**values))
class StringConcatenate(io.ComfyNode):
@classmethod
def define_schema(cls):
@ -444,7 +413,6 @@ class StringExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [
StringFormat,
StringConcatenate,
StringSubstring,
StringLength,

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@ -4160,10 +4160,6 @@ paths:
name:
type: string
description: Display name for the API key
description:
type: string
description: User-provided description of the key's purpose
maxLength: 5000
responses:
"201":
description: API key created
@ -7681,16 +7677,11 @@ components:
required:
- id
- name
- description
properties:
id:
type: string
name:
type: string
description:
type: string
maxLength: 5000
description: User-provided description of the key's purpose. Always present in responses; empty string when no description was supplied on create.
prefix:
type: string
description: First few characters of the key for identification
@ -7711,17 +7702,12 @@ components:
required:
- id
- name
- description
- key
properties:
id:
type: string
name:
type: string
description:
type: string
maxLength: 5000
description: User-provided description of the key's purpose. Always present in responses; empty string when no description was supplied on create.
key:
type: string
description: Full API key value (only returned on creation)