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Merge 2e5c147fb5 into dd86b15521

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Christian Byrne 2026-02-02 21:47:25 +08:00 committed by GitHub
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69 changed files with 442 additions and 294 deletions
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5
comfy_api_nodes/nodes_bfl.py
View File

@ -57,6 +57,7 @@ class FluxProUltraImageNode(IO.ComfyNode):
tooltip="Whether to perform upsampling on the prompt. "
"If active, automatically modifies the prompt for more creative generation, "
"but results are nondeterministic (same seed will not produce exactly the same result).",
advanced=True,
),
IO.Int.Input(
"seed",
@ -200,6 +201,7 @@ class FluxKontextProImageNode(IO.ComfyNode):
"prompt_upsampling",
default=False,
tooltip="Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result).",
advanced=True,
),
IO.Image.Input(
"input_image",
@ -296,6 +298,7 @@ class FluxProExpandNode(IO.ComfyNode):
tooltip="Whether to perform upsampling on the prompt. "
"If active, automatically modifies the prompt for more creative generation, "
"but results are nondeterministic (same seed will not produce exactly the same result).",
advanced=True,
),
IO.Int.Input(
"top",
@ -433,6 +436,7 @@ class FluxProFillNode(IO.ComfyNode):
tooltip="Whether to perform upsampling on the prompt. "
"If active, automatically modifies the prompt for more creative generation, "
"but results are nondeterministic (same seed will not produce exactly the same result).",
advanced=True,
),
IO.Float.Input(
"guidance",
@ -577,6 +581,7 @@ class Flux2ProImageNode(IO.ComfyNode):
default=True,
tooltip="Whether to perform upsampling on the prompt. "
"If active, automatically modifies the prompt for more creative generation.",
advanced=True,
),
IO.Image.Input("images", optional=True, tooltip="Up to 9 images to be used as references."),
],

13
comfy_api_nodes/nodes_bytedance.py
View File

@ -114,6 +114,7 @@ class ByteDanceImageNode(IO.ComfyNode):
default=False,
tooltip='Whether to add an "AI generated" watermark to the image',
optional=True,
advanced=True,
),
],
outputs=[
@ -259,12 +260,14 @@ class ByteDanceSeedreamNode(IO.ComfyNode):
default=False,
tooltip='Whether to add an "AI generated" watermark to the image.',
optional=True,
advanced=True,
),
IO.Boolean.Input(
"fail_on_partial",
default=True,
tooltip="If enabled, abort execution if any requested images are missing or return an error.",
optional=True,
advanced=True,
),
],
outputs=[
@ -432,18 +435,21 @@ class ByteDanceTextToVideoNode(IO.ComfyNode):
tooltip="Specifies whether to fix the camera. The platform appends an instruction "
"to fix the camera to your prompt, but does not guarantee the actual effect.",
optional=True,
advanced=True,
),
IO.Boolean.Input(
"watermark",
default=False,
tooltip='Whether to add an "AI generated" watermark to the video.',
optional=True,
advanced=True,
),
IO.Boolean.Input(
"generate_audio",
default=False,
tooltip="This parameter is ignored for any model except seedance-1-5-pro.",
optional=True,
advanced=True,
),
],
outputs=[
@ -561,18 +567,21 @@ class ByteDanceImageToVideoNode(IO.ComfyNode):
tooltip="Specifies whether to fix the camera. The platform appends an instruction "
"to fix the camera to your prompt, but does not guarantee the actual effect.",
optional=True,
advanced=True,
),
IO.Boolean.Input(
"watermark",
default=False,
tooltip='Whether to add an "AI generated" watermark to the video.',
optional=True,
advanced=True,
),
IO.Boolean.Input(
"generate_audio",
default=False,
tooltip="This parameter is ignored for any model except seedance-1-5-pro.",
optional=True,
advanced=True,
),
],
outputs=[
@ -694,18 +703,21 @@ class ByteDanceFirstLastFrameNode(IO.ComfyNode):
tooltip="Specifies whether to fix the camera. The platform appends an instruction "
"to fix the camera to your prompt, but does not guarantee the actual effect.",
optional=True,
advanced=True,
),
IO.Boolean.Input(
"watermark",
default=False,
tooltip='Whether to add an "AI generated" watermark to the video.',
optional=True,
advanced=True,
),
IO.Boolean.Input(
"generate_audio",
default=False,
tooltip="This parameter is ignored for any model except seedance-1-5-pro.",
optional=True,
advanced=True,
),
],
outputs=[
@ -834,6 +846,7 @@ class ByteDanceImageReferenceNode(IO.ComfyNode):
default=False,
tooltip='Whether to add an "AI generated" watermark to the video.',
optional=True,
advanced=True,
),
],
outputs=[

5
comfy_api_nodes/nodes_gemini.py
View File

@ -308,6 +308,7 @@ class GeminiNode(IO.ComfyNode):
default="",
optional=True,
tooltip="Foundational instructions that dictate an AI's behavior.",
advanced=True,
),
],
outputs=[
@ -585,6 +586,7 @@ class GeminiImage(IO.ComfyNode):
tooltip="Choose 'IMAGE' for image-only output, or "
"'IMAGE+TEXT' to return both the generated image and a text response.",
optional=True,
advanced=True,
),
IO.String.Input(
"system_prompt",
@ -592,6 +594,7 @@ class GeminiImage(IO.ComfyNode):
default=GEMINI_IMAGE_SYS_PROMPT,
optional=True,
tooltip="Foundational instructions that dictate an AI's behavior.",
advanced=True,
),
],
outputs=[
@ -706,6 +709,7 @@ class GeminiImage2(IO.ComfyNode):
options=["IMAGE+TEXT", "IMAGE"],
tooltip="Choose 'IMAGE' for image-only output, or "
"'IMAGE+TEXT' to return both the generated image and a text response.",
advanced=True,
),
IO.Image.Input(
"images",
@ -725,6 +729,7 @@ class GeminiImage2(IO.ComfyNode):
default=GEMINI_IMAGE_SYS_PROMPT,
optional=True,
tooltip="Foundational instructions that dictate an AI's behavior.",
advanced=True,
),
],
outputs=[

5
comfy_api_nodes/nodes_ideogram.py
View File

@ -261,6 +261,7 @@ class IdeogramV1(IO.ComfyNode):
default="AUTO",
tooltip="Determine if MagicPrompt should be used in generation",
optional=True,
advanced=True,
),
IO.Int.Input(
"seed",
@ -394,6 +395,7 @@ class IdeogramV2(IO.ComfyNode):
default="AUTO",
tooltip="Determine if MagicPrompt should be used in generation",
optional=True,
advanced=True,
),
IO.Int.Input(
"seed",
@ -411,6 +413,7 @@ class IdeogramV2(IO.ComfyNode):
default="NONE",
tooltip="Style type for generation (V2 only)",
optional=True,
advanced=True,
),
IO.String.Input(
"negative_prompt",
@ -564,6 +567,7 @@ class IdeogramV3(IO.ComfyNode):
default="AUTO",
tooltip="Determine if MagicPrompt should be used in generation",
optional=True,
advanced=True,
),
IO.Int.Input(
"seed",
@ -590,6 +594,7 @@ class IdeogramV3(IO.ComfyNode):
default="DEFAULT",
tooltip="Controls the trade-off between generation speed and quality",
optional=True,
advanced=True,
),
IO.Image.Input(
"character_image",

8
comfy_api_nodes/nodes_kling.py
View File

@ -2007,6 +2007,7 @@ class KlingLipSyncTextToVideoNode(IO.ComfyNode):
max=2.0,
display_mode=IO.NumberDisplay.slider,
tooltip="Speech Rate. Valid range: 0.8~2.0, accurate to one decimal place.",
advanced=True,
),
],
outputs=[
@ -2128,6 +2129,7 @@ class KlingImageGenerationNode(IO.ComfyNode):
IO.Combo.Input(
"image_type",
options=[i.value for i in KlingImageGenImageReferenceType],
advanced=True,
),
IO.Float.Input(
"image_fidelity",
@ -2137,6 +2139,7 @@ class KlingImageGenerationNode(IO.ComfyNode):
step=0.01,
display_mode=IO.NumberDisplay.slider,
tooltip="Reference intensity for user-uploaded images",
advanced=True,
),
IO.Float.Input(
"human_fidelity",
@ -2146,6 +2149,7 @@ class KlingImageGenerationNode(IO.ComfyNode):
step=0.01,
display_mode=IO.NumberDisplay.slider,
tooltip="Subject reference similarity",
advanced=True,
),
IO.Combo.Input(
"model_name",
@ -2260,7 +2264,7 @@ class TextToVideoWithAudio(IO.ComfyNode):
IO.Combo.Input("mode", options=["pro"]),
IO.Combo.Input("aspect_ratio", options=["16:9", "9:16", "1:1"]),
IO.Combo.Input("duration", options=[5, 10]),
IO.Boolean.Input("generate_audio", default=True),
IO.Boolean.Input("generate_audio", default=True, advanced=True),
],
outputs=[
IO.Video.Output(),
@ -2328,7 +2332,7 @@ class ImageToVideoWithAudio(IO.ComfyNode):
IO.String.Input("prompt", multiline=True, tooltip="Positive text prompt."),
IO.Combo.Input("mode", options=["pro"]),
IO.Combo.Input("duration", options=[5, 10]),
IO.Boolean.Input("generate_audio", default=True),
IO.Boolean.Input("generate_audio", default=True, advanced=True),
],
outputs=[
IO.Video.Output(),

2
comfy_api_nodes/nodes_ltxv.py
View File

@ -74,6 +74,7 @@ class TextToVideoNode(IO.ComfyNode):
default=False,
optional=True,
tooltip="When true, the generated video will include AI-generated audio matching the scene.",
advanced=True,
),
],
outputs=[
@ -151,6 +152,7 @@ class ImageToVideoNode(IO.ComfyNode):
default=False,
optional=True,
tooltip="When true, the generated video will include AI-generated audio matching the scene.",
advanced=True,
),
],
outputs=[

8
comfy_api_nodes/nodes_magnific.py
View File

@ -86,11 +86,13 @@ class MagnificImageUpscalerCreativeNode(IO.ComfyNode):
IO.Combo.Input(
"engine",
options=["automatic", "magnific_illusio", "magnific_sharpy", "magnific_sparkle"],
advanced=True,
),
IO.Boolean.Input(
"auto_downscale",
default=False,
tooltip="Automatically downscale input image if output would exceed maximum pixel limit.",
advanced=True,
),
],
outputs=[
@ -242,6 +244,7 @@ class MagnificImageUpscalerPreciseV2Node(IO.ComfyNode):
"auto_downscale",
default=False,
tooltip="Automatically downscale input image if output would exceed maximum resolution.",
advanced=True,
),
],
outputs=[
@ -392,6 +395,7 @@ class MagnificImageStyleTransferNode(IO.ComfyNode):
"softy",
],
tooltip="Processing engine selection.",
advanced=True,
),
IO.DynamicCombo.Input(
"portrait_mode",
@ -420,6 +424,7 @@ class MagnificImageStyleTransferNode(IO.ComfyNode):
default=True,
tooltip="When disabled, expect each generation to introduce a degree of randomness, "
"leading to more diverse outcomes.",
advanced=True,
),
],
outputs=[
@ -534,16 +539,19 @@ class MagnificImageRelightNode(IO.ComfyNode):
"interpolate_from_original",
default=False,
tooltip="Restricts generation freedom to match original more closely.",
advanced=True,
),
IO.Boolean.Input(
"change_background",
default=True,
tooltip="Modifies background based on prompt/reference.",
advanced=True,
),
IO.Boolean.Input(
"preserve_details",
default=True,
tooltip="Maintains texture and fine details from original.",
advanced=True,
),
IO.DynamicCombo.Input(
"advanced_settings",

11
comfy_api_nodes/nodes_meshy.py
View File

@ -61,11 +61,12 @@ class MeshyTextToModelNode(IO.ComfyNode):
],
tooltip="When set to false, returns an unprocessed triangular mesh.",
),
IO.Combo.Input("symmetry_mode", options=["auto", "on", "off"]),
IO.Combo.Input("symmetry_mode", options=["auto", "on", "off"], advanced=True),
IO.Combo.Input(
"pose_mode",
options=["", "A-pose", "T-pose"],
tooltip="Specify the pose mode for the generated model.",
advanced=True,
),
IO.Int.Input(
"seed",
@ -152,6 +153,7 @@ class MeshyRefineNode(IO.ComfyNode):
tooltip="Generate PBR Maps (metallic, roughness, normal) in addition to the base color. "
"Note: this should be set to false when using Sculpture style, "
"as Sculpture style generates its own set of PBR maps.",
advanced=True,
),
IO.String.Input(
"texture_prompt",
@ -290,6 +292,7 @@ class MeshyImageToModelNode(IO.ComfyNode):
"pose_mode",
options=["", "A-pose", "T-pose"],
tooltip="Specify the pose mode for the generated model.",
advanced=True,
),
IO.Int.Input(
"seed",
@ -414,7 +417,7 @@ class MeshyMultiImageToModelNode(IO.ComfyNode):
],
tooltip="When set to false, returns an unprocessed triangular mesh.",
),
IO.Combo.Input("symmetry_mode", options=["auto", "on", "off"]),
IO.Combo.Input("symmetry_mode", options=["auto", "on", "off"], advanced=True),
IO.DynamicCombo.Input(
"should_texture",
options=[
@ -451,6 +454,7 @@ class MeshyMultiImageToModelNode(IO.ComfyNode):
"pose_mode",
options=["", "A-pose", "T-pose"],
tooltip="Specify the pose mode for the generated model.",
advanced=True,
),
IO.Int.Input(
"seed",
@ -698,8 +702,9 @@ class MeshyTextureNode(IO.ComfyNode):
tooltip="Use the original UV of the model instead of generating new UVs. "
"When enabled, Meshy preserves existing textures from the uploaded model. "
"If the model has no original UV, the quality of the output might not be as good.",
advanced=True,
),
IO.Boolean.Input("pbr", default=False),
IO.Boolean.Input("pbr", default=False, advanced=True),
IO.String.Input(
"text_style_prompt",
default="",

3
comfy_api_nodes/nodes_openai.py
View File

@ -588,6 +588,7 @@ class OpenAIChatNode(IO.ComfyNode):
"persist_context",
default=False,
tooltip="This parameter is deprecated and has no effect.",
advanced=True,
),
IO.Combo.Input(
"model",
@ -862,6 +863,7 @@ class OpenAIChatConfig(IO.ComfyNode):
options=["auto", "disabled"],
default="auto",
tooltip="The truncation strategy to use for the model response. auto: If the context of this response and previous ones exceeds the model's context window size, the model will truncate the response to fit the context window by dropping input items in the middle of the conversation.disabled: If a model response will exceed the context window size for a model, the request will fail with a 400 error",
advanced=True,
),
IO.Int.Input(
"max_output_tokens",
@ -870,6 +872,7 @@ class OpenAIChatConfig(IO.ComfyNode):
max=16384,
tooltip="An upper bound for the number of tokens that can be generated for a response, including visible output tokens",
optional=True,
advanced=True,
),
IO.String.Input(
"instructions",

2
comfy_api_nodes/nodes_rodin.py
View File

@ -473,7 +473,7 @@ class Rodin3D_Gen2(IO.ComfyNode):
default="500K-Triangle",
optional=True,
),
IO.Boolean.Input("TAPose", default=False),
IO.Boolean.Input("TAPose", default=False, advanced=True),
],
outputs=[IO.String.Output(display_name="3D Model Path")],
hidden=[

12
comfy_api_nodes/nodes_stability.py
View File

@ -86,6 +86,7 @@ class StabilityStableImageUltraNode(IO.ComfyNode):
"style_preset",
options=get_stability_style_presets(),
tooltip="Optional desired style of generated image.",
advanced=True,
),
IO.Int.Input(
"seed",
@ -107,6 +108,7 @@ class StabilityStableImageUltraNode(IO.ComfyNode):
tooltip="A blurb of text describing what you do not wish to see in the output image. This is an advanced feature.",
force_input=True,
optional=True,
advanced=True,
),
IO.Float.Input(
"image_denoise",
@ -218,6 +220,7 @@ class StabilityStableImageSD_3_5Node(IO.ComfyNode):
"style_preset",
options=get_stability_style_presets(),
tooltip="Optional desired style of generated image.",
advanced=True,
),
IO.Float.Input(
"cfg_scale",
@ -247,6 +250,7 @@ class StabilityStableImageSD_3_5Node(IO.ComfyNode):
tooltip="Keywords of what you do not wish to see in the output image. This is an advanced feature.",
force_input=True,
optional=True,
advanced=True,
),
IO.Float.Input(
"image_denoise",
@ -384,6 +388,7 @@ class StabilityUpscaleConservativeNode(IO.ComfyNode):
tooltip="Keywords of what you do not wish to see in the output image. This is an advanced feature.",
force_input=True,
optional=True,
advanced=True,
),
],
outputs=[
@ -474,6 +479,7 @@ class StabilityUpscaleCreativeNode(IO.ComfyNode):
"style_preset",
options=get_stability_style_presets(),
tooltip="Optional desired style of generated image.",
advanced=True,
),
IO.Int.Input(
"seed",
@ -491,6 +497,7 @@ class StabilityUpscaleCreativeNode(IO.ComfyNode):
tooltip="Keywords of what you do not wish to see in the output image. This is an advanced feature.",
force_input=True,
optional=True,
advanced=True,
),
],
outputs=[
@ -659,6 +666,7 @@ class StabilityTextToAudio(IO.ComfyNode):
step=1,
tooltip="Controls the number of sampling steps.",
optional=True,
advanced=True,
),
],
outputs=[
@ -736,6 +744,7 @@ class StabilityAudioToAudio(IO.ComfyNode):
step=1,
tooltip="Controls the number of sampling steps.",
optional=True,
advanced=True,
),
IO.Float.Input(
"strength",
@ -829,6 +838,7 @@ class StabilityAudioInpaint(IO.ComfyNode):
step=1,
tooltip="Controls the number of sampling steps.",
optional=True,
advanced=True,
),
IO.Int.Input(
"mask_start",
@ -837,6 +847,7 @@ class StabilityAudioInpaint(IO.ComfyNode):
max=190,
step=1,
optional=True,
advanced=True,
),
IO.Int.Input(
"mask_end",
@ -845,6 +856,7 @@ class StabilityAudioInpaint(IO.ComfyNode):
max=190,
step=1,
optional=True,
advanced=True,
),
],
outputs=[

16
comfy_api_nodes/nodes_topaz.py
View File

@ -63,12 +63,14 @@ class TopazImageEnhance(IO.ComfyNode):
"subject_detection",
options=["All", "Foreground", "Background"],
optional=True,
advanced=True,
),
IO.Boolean.Input(
"face_enhancement",
default=True,
optional=True,
tooltip="Enhance faces (if present) during processing.",
advanced=True,
),
IO.Float.Input(
"face_enhancement_creativity",
@ -79,6 +81,7 @@ class TopazImageEnhance(IO.ComfyNode):
display_mode=IO.NumberDisplay.number,
optional=True,
tooltip="Set the creativity level for face enhancement.",
advanced=True,
),
IO.Float.Input(
"face_enhancement_strength",
@ -89,6 +92,7 @@ class TopazImageEnhance(IO.ComfyNode):
display_mode=IO.NumberDisplay.number,
optional=True,
tooltip="Controls how sharp enhanced faces are relative to the background.",
advanced=True,
),
IO.Boolean.Input(
"crop_to_fill",
@ -96,6 +100,7 @@ class TopazImageEnhance(IO.ComfyNode):
optional=True,
tooltip="By default, the image is letterboxed when the output aspect ratio differs. "
"Enable to crop the image to fill the output dimensions.",
advanced=True,
),
IO.Int.Input(
"output_width",
@ -106,6 +111,7 @@ class TopazImageEnhance(IO.ComfyNode):
display_mode=IO.NumberDisplay.number,
optional=True,
tooltip="Zero value means to calculate automatically (usually it will be original size or output_height if specified).",
advanced=True,
),
IO.Int.Input(
"output_height",
@ -116,6 +122,7 @@ class TopazImageEnhance(IO.ComfyNode):
display_mode=IO.NumberDisplay.number,
optional=True,
tooltip="Zero value means to output in the same height as original or output width.",
advanced=True,
),
IO.Int.Input(
"creativity",
@ -131,12 +138,14 @@ class TopazImageEnhance(IO.ComfyNode):
default=True,
optional=True,
tooltip="Preserve subjects' facial identity.",
advanced=True,
),
IO.Boolean.Input(
"color_preservation",
default=True,
optional=True,
tooltip="Preserve the original colors.",
advanced=True,
),
],
outputs=[
@ -234,9 +243,10 @@ class TopazVideoEnhance(IO.ComfyNode):
default="low",
tooltip="Creativity level (applies only to Starlight (Astra) Creative).",
optional=True,
advanced=True,
),
IO.Boolean.Input("interpolation_enabled", default=False, optional=True),
IO.Combo.Input("interpolation_model", options=["apo-8"], default="apo-8", optional=True),
IO.Combo.Input("interpolation_model", options=["apo-8"], default="apo-8", optional=True, advanced=True),
IO.Int.Input(
"interpolation_slowmo",
default=1,
@ -246,6 +256,7 @@ class TopazVideoEnhance(IO.ComfyNode):
tooltip="Slow-motion factor applied to the input video. "
"For example, 2 makes the output twice as slow and doubles the duration.",
optional=True,
advanced=True,
),
IO.Int.Input(
"interpolation_frame_rate",
@ -261,6 +272,7 @@ class TopazVideoEnhance(IO.ComfyNode):
default=False,
tooltip="Analyze the input for duplicate frames and remove them.",
optional=True,
advanced=True,
),
IO.Float.Input(
"interpolation_duplicate_threshold",
@ -271,6 +283,7 @@ class TopazVideoEnhance(IO.ComfyNode):
display_mode=IO.NumberDisplay.number,
tooltip="Detection sensitivity for duplicate frames.",
optional=True,
advanced=True,
),
IO.Combo.Input(
"dynamic_compression_level",
@ -278,6 +291,7 @@ class TopazVideoEnhance(IO.ComfyNode):
default="Low",
tooltip="CQP level.",
optional=True,
advanced=True,
),
],
outputs=[

78
comfy_api_nodes/nodes_tripo.py
View File

@ -98,13 +98,13 @@ class TripoTextToModelNode(IO.ComfyNode):
IO.Combo.Input("style", options=TripoStyle, default="None", optional=True),
IO.Boolean.Input("texture", default=True, optional=True),
IO.Boolean.Input("pbr", default=True, optional=True),
IO.Int.Input("image_seed", default=42, optional=True),
IO.Int.Input("model_seed", default=42, optional=True),
IO.Int.Input("texture_seed", default=42, optional=True),
IO.Combo.Input("texture_quality", default="standard", options=["standard", "detailed"], optional=True),
IO.Int.Input("face_limit", default=-1, min=-1, max=2000000, optional=True),
IO.Boolean.Input("quad", default=False, optional=True),
IO.Combo.Input("geometry_quality", default="standard", options=["standard", "detailed"], optional=True),
IO.Int.Input("image_seed", default=42, optional=True, advanced=True),
IO.Int.Input("model_seed", default=42, optional=True, advanced=True),
IO.Int.Input("texture_seed", default=42, optional=True, advanced=True),
IO.Combo.Input("texture_quality", default="standard", options=["standard", "detailed"], optional=True, advanced=True),
IO.Int.Input("face_limit", default=-1, min=-1, max=2000000, optional=True, advanced=True),
IO.Boolean.Input("quad", default=False, optional=True, advanced=True),
IO.Combo.Input("geometry_quality", default="standard", options=["standard", "detailed"], optional=True, advanced=True),
],
outputs=[
IO.String.Output(display_name="model_file"),
@ -218,18 +218,18 @@ class TripoImageToModelNode(IO.ComfyNode):
IO.Combo.Input("style", options=TripoStyle, default="None", optional=True),
IO.Boolean.Input("texture", default=True, optional=True),
IO.Boolean.Input("pbr", default=True, optional=True),
IO.Int.Input("model_seed", default=42, optional=True),
IO.Int.Input("model_seed", default=42, optional=True, advanced=True),
IO.Combo.Input(
"orientation", options=TripoOrientation, default=TripoOrientation.DEFAULT, optional=True
"orientation", options=TripoOrientation, default=TripoOrientation.DEFAULT, optional=True, advanced=True
),
IO.Int.Input("texture_seed", default=42, optional=True),
IO.Combo.Input("texture_quality", default="standard", options=["standard", "detailed"], optional=True),
IO.Int.Input("texture_seed", default=42, optional=True, advanced=True),
IO.Combo.Input("texture_quality", default="standard", options=["standard", "detailed"], optional=True, advanced=True),
IO.Combo.Input(
"texture_alignment", default="original_image", options=["original_image", "geometry"], optional=True
"texture_alignment", default="original_image", options=["original_image", "geometry"], optional=True, advanced=True
),
IO.Int.Input("face_limit", default=-1, min=-1, max=500000, optional=True),
IO.Boolean.Input("quad", default=False, optional=True),
IO.Combo.Input("geometry_quality", default="standard", options=["standard", "detailed"], optional=True),
IO.Int.Input("face_limit", default=-1, min=-1, max=500000, optional=True, advanced=True),
IO.Boolean.Input("quad", default=False, optional=True, advanced=True),
IO.Combo.Input("geometry_quality", default="standard", options=["standard", "detailed"], optional=True, advanced=True),
],
outputs=[
IO.String.Output(display_name="model_file"),
@ -354,18 +354,19 @@ class TripoMultiviewToModelNode(IO.ComfyNode):
options=TripoOrientation,
default=TripoOrientation.DEFAULT,
optional=True,
advanced=True,
),
IO.Boolean.Input("texture", default=True, optional=True),
IO.Boolean.Input("pbr", default=True, optional=True),
IO.Int.Input("model_seed", default=42, optional=True),
IO.Int.Input("texture_seed", default=42, optional=True),
IO.Combo.Input("texture_quality", default="standard", options=["standard", "detailed"], optional=True),
IO.Int.Input("model_seed", default=42, optional=True, advanced=True),
IO.Int.Input("texture_seed", default=42, optional=True, advanced=True),
IO.Combo.Input("texture_quality", default="standard", options=["standard", "detailed"], optional=True, advanced=True),
IO.Combo.Input(
"texture_alignment", default="original_image", options=["original_image", "geometry"], optional=True
"texture_alignment", default="original_image", options=["original_image", "geometry"], optional=True, advanced=True
),
IO.Int.Input("face_limit", default=-1, min=-1, max=500000, optional=True),
IO.Boolean.Input("quad", default=False, optional=True),
IO.Combo.Input("geometry_quality", default="standard", options=["standard", "detailed"], optional=True),
IO.Int.Input("face_limit", default=-1, min=-1, max=500000, optional=True, advanced=True),
IO.Boolean.Input("quad", default=False, optional=True, advanced=True),
IO.Combo.Input("geometry_quality", default="standard", options=["standard", "detailed"], optional=True, advanced=True),
],
outputs=[
IO.String.Output(display_name="model_file"),
@ -480,10 +481,10 @@ class TripoTextureNode(IO.ComfyNode):
IO.Custom("MODEL_TASK_ID").Input("model_task_id"),
IO.Boolean.Input("texture", default=True, optional=True),
IO.Boolean.Input("pbr", default=True, optional=True),
IO.Int.Input("texture_seed", default=42, optional=True),
IO.Combo.Input("texture_quality", default="standard", options=["standard", "detailed"], optional=True),
IO.Int.Input("texture_seed", default=42, optional=True, advanced=True),
IO.Combo.Input("texture_quality", default="standard", options=["standard", "detailed"], optional=True, advanced=True),
IO.Combo.Input(
"texture_alignment", default="original_image", options=["original_image", "geometry"], optional=True
"texture_alignment", default="original_image", options=["original_image", "geometry"], optional=True, advanced=True
),
],
outputs=[
@ -684,13 +685,14 @@ class TripoConversionNode(IO.ComfyNode):
inputs=[
IO.Custom("MODEL_TASK_ID,RIG_TASK_ID,RETARGET_TASK_ID").Input("original_model_task_id"),
IO.Combo.Input("format", options=["GLTF", "USDZ", "FBX", "OBJ", "STL", "3MF"]),
IO.Boolean.Input("quad", default=False, optional=True),
IO.Boolean.Input("quad", default=False, optional=True, advanced=True),
IO.Int.Input(
"face_limit",
default=-1,
min=-1,
max=2000000,
optional=True,
advanced=True,
),
IO.Int.Input(
"texture_size",
@ -698,47 +700,53 @@ class TripoConversionNode(IO.ComfyNode):
min=128,
max=4096,
optional=True,
advanced=True,
),
IO.Combo.Input(
"texture_format",
options=["BMP", "DPX", "HDR", "JPEG", "OPEN_EXR", "PNG", "TARGA", "TIFF", "WEBP"],
default="JPEG",
optional=True,
advanced=True,
),
IO.Boolean.Input("force_symmetry", default=False, optional=True),
IO.Boolean.Input("flatten_bottom", default=False, optional=True),
IO.Boolean.Input("force_symmetry", default=False, optional=True, advanced=True),
IO.Boolean.Input("flatten_bottom", default=False, optional=True, advanced=True),
IO.Float.Input(
"flatten_bottom_threshold",
default=0.0,
min=0.0,
max=1.0,
optional=True,
advanced=True,
),
IO.Boolean.Input("pivot_to_center_bottom", default=False, optional=True),
IO.Boolean.Input("pivot_to_center_bottom", default=False, optional=True, advanced=True),
IO.Float.Input(
"scale_factor",
default=1.0,
min=0.0,
optional=True,
advanced=True,
),
IO.Boolean.Input("with_animation", default=False, optional=True),
IO.Boolean.Input("pack_uv", default=False, optional=True),
IO.Boolean.Input("bake", default=False, optional=True),
IO.String.Input("part_names", default="", optional=True), # comma-separated list
IO.Boolean.Input("with_animation", default=False, optional=True, advanced=True),
IO.Boolean.Input("pack_uv", default=False, optional=True, advanced=True),
IO.Boolean.Input("bake", default=False, optional=True, advanced=True),
IO.String.Input("part_names", default="", optional=True, advanced=True), # comma-separated list
IO.Combo.Input(
"fbx_preset",
options=["blender", "mixamo", "3dsmax"],
default="blender",
optional=True,
advanced=True,
),
IO.Boolean.Input("export_vertex_colors", default=False, optional=True),
IO.Boolean.Input("export_vertex_colors", default=False, optional=True, advanced=True),
IO.Combo.Input(
"export_orientation",
options=["align_image", "default"],
default="default",
optional=True,
advanced=True,
),
IO.Boolean.Input("animate_in_place", default=False, optional=True),
IO.Boolean.Input("animate_in_place", default=False, optional=True, advanced=True),
],
outputs=[],
hidden=[

4
comfy_api_nodes/nodes_veo2.py
View File

@ -81,6 +81,7 @@ class VeoVideoGenerationNode(IO.ComfyNode):
default=True,
tooltip="Whether to enhance the prompt with AI assistance",
optional=True,
advanced=True,
),
IO.Combo.Input(
"person_generation",
@ -88,6 +89,7 @@ class VeoVideoGenerationNode(IO.ComfyNode):
default="ALLOW",
tooltip="Whether to allow generating people in the video",
optional=True,
advanced=True,
),
IO.Int.Input(
"seed",
@ -299,6 +301,7 @@ class Veo3VideoGenerationNode(VeoVideoGenerationNode):
default=True,
tooltip="This parameter is deprecated and ignored.",
optional=True,
advanced=True,
),
IO.Combo.Input(
"person_generation",
@ -306,6 +309,7 @@ class Veo3VideoGenerationNode(VeoVideoGenerationNode):
default="ALLOW",
tooltip="Whether to allow generating people in the video",
optional=True,
advanced=True,
),
IO.Int.Input(
"seed",

20
comfy_api_nodes/nodes_vidu.py
View File

@ -111,12 +111,14 @@ class ViduTextToVideoNode(IO.ComfyNode):
options=["1080p"],
tooltip="Supported values may vary by model & duration",
optional=True,
advanced=True,
),
IO.Combo.Input(
"movement_amplitude",
options=["auto", "small", "medium", "large"],
tooltip="The movement amplitude of objects in the frame",
optional=True,
advanced=True,
),
],
outputs=[
@ -207,12 +209,14 @@ class ViduImageToVideoNode(IO.ComfyNode):
options=["1080p"],
tooltip="Supported values may vary by model & duration",
optional=True,
advanced=True,
),
IO.Combo.Input(
"movement_amplitude",
options=["auto", "small", "medium", "large"],
tooltip="The movement amplitude of objects in the frame",
optional=True,
advanced=True,
),
],
outputs=[
@ -313,12 +317,14 @@ class ViduReferenceVideoNode(IO.ComfyNode):
options=["1080p"],
tooltip="Supported values may vary by model & duration",
optional=True,
advanced=True,
),
IO.Combo.Input(
"movement_amplitude",
options=["auto", "small", "medium", "large"],
tooltip="The movement amplitude of objects in the frame",
optional=True,
advanced=True,
),
],
outputs=[
@ -425,12 +431,14 @@ class ViduStartEndToVideoNode(IO.ComfyNode):
options=["1080p"],
tooltip="Supported values may vary by model & duration",
optional=True,
advanced=True,
),
IO.Combo.Input(
"movement_amplitude",
options=["auto", "small", "medium", "large"],
tooltip="The movement amplitude of objects in the frame",
optional=True,
advanced=True,
),
],
outputs=[
@ -510,11 +518,12 @@ class Vidu2TextToVideoNode(IO.ComfyNode):
control_after_generate=True,
),
IO.Combo.Input("aspect_ratio", options=["16:9", "9:16", "3:4", "4:3", "1:1"]),
IO.Combo.Input("resolution", options=["720p", "1080p"]),
IO.Combo.Input("resolution", options=["720p", "1080p"], advanced=True),
IO.Boolean.Input(
"background_music",
default=False,
tooltip="Whether to add background music to the generated video.",
advanced=True,
),
],
outputs=[
@ -608,11 +617,13 @@ class Vidu2ImageToVideoNode(IO.ComfyNode):
IO.Combo.Input(
"resolution",
options=["720p", "1080p"],
advanced=True,
),
IO.Combo.Input(
"movement_amplitude",
options=["auto", "small", "medium", "large"],
tooltip="The movement amplitude of objects in the frame.",
advanced=True,
),
],
outputs=[
@ -726,6 +737,7 @@ class Vidu2ReferenceVideoNode(IO.ComfyNode):
"audio",
default=False,
tooltip="When enabled video will contain generated speech and background music based on the prompt.",
advanced=True,
),
IO.Int.Input(
"duration",
@ -745,11 +757,12 @@ class Vidu2ReferenceVideoNode(IO.ComfyNode):
control_after_generate=True,
),
IO.Combo.Input("aspect_ratio", options=["16:9", "9:16", "4:3", "3:4", "1:1"]),
IO.Combo.Input("resolution", options=["720p", "1080p"]),
IO.Combo.Input("resolution", options=["720p", "1080p"], advanced=True),
IO.Combo.Input(
"movement_amplitude",
options=["auto", "small", "medium", "large"],
tooltip="The movement amplitude of objects in the frame.",
advanced=True,
),
],
outputs=[
@ -863,11 +876,12 @@ class Vidu2StartEndToVideoNode(IO.ComfyNode):
display_mode=IO.NumberDisplay.number,
control_after_generate=True,
),
IO.Combo.Input("resolution", options=["720p", "1080p"]),
IO.Combo.Input("resolution", options=["720p", "1080p"], advanced=True),
IO.Combo.Input(
"movement_amplitude",
options=["auto", "small", "medium", "large"],
tooltip="The movement amplitude of objects in the frame.",
advanced=True,
),
],
outputs=[

13
comfy_api_nodes/nodes_wan.py
View File

@ -227,12 +227,14 @@ class WanTextToImageApi(IO.ComfyNode):
default=True,
tooltip="Whether to enhance the prompt with AI assistance.",
optional=True,
advanced=True,
),
IO.Boolean.Input(
"watermark",
default=False,
tooltip="Whether to add an AI-generated watermark to the result.",
optional=True,
advanced=True,
),
],
outputs=[
@ -355,6 +357,7 @@ class WanImageToImageApi(IO.ComfyNode):
default=False,
tooltip="Whether to add an AI-generated watermark to the result.",
optional=True,
advanced=True,
),
],
outputs=[
@ -495,18 +498,21 @@ class WanTextToVideoApi(IO.ComfyNode):
default=False,
optional=True,
tooltip="If no audio input is provided, generate audio automatically.",
advanced=True,
),
IO.Boolean.Input(
"prompt_extend",
default=True,
tooltip="Whether to enhance the prompt with AI assistance.",
optional=True,
advanced=True,
),
IO.Boolean.Input(
"watermark",
default=False,
tooltip="Whether to add an AI-generated watermark to the result.",
optional=True,
advanced=True,
),
IO.Combo.Input(
"shot_type",
@ -515,6 +521,7 @@ class WanTextToVideoApi(IO.ComfyNode):
"single continuous shot or multiple shots with cuts. "
"This parameter takes effect only when prompt_extend is True.",
optional=True,
advanced=True,
),
],
outputs=[
@ -667,18 +674,21 @@ class WanImageToVideoApi(IO.ComfyNode):
default=False,
optional=True,
tooltip="If no audio input is provided, generate audio automatically.",
advanced=True,
),
IO.Boolean.Input(
"prompt_extend",
default=True,
tooltip="Whether to enhance the prompt with AI assistance.",
optional=True,
advanced=True,
),
IO.Boolean.Input(
"watermark",
default=False,
tooltip="Whether to add an AI-generated watermark to the result.",
optional=True,
advanced=True,
),
IO.Combo.Input(
"shot_type",
@ -687,6 +697,7 @@ class WanImageToVideoApi(IO.ComfyNode):
"single continuous shot or multiple shots with cuts. "
"This parameter takes effect only when prompt_extend is True.",
optional=True,
advanced=True,
),
],
outputs=[
@ -839,11 +850,13 @@ class WanReferenceVideoApi(IO.ComfyNode):
options=["single", "multi"],
tooltip="Specifies the shot type for the generated video, that is, whether the video is a "
"single continuous shot or multiple shots with cuts.",
advanced=True,
),
IO.Boolean.Input(
"watermark",
default=False,
tooltip="Whether to add an AI-generated watermark to the result.",
advanced=True,
),
],
outputs=[

6
comfy_extras/nodes_advanced_samplers.py
View File

@ -47,8 +47,8 @@ class SamplerLCMUpscale(io.ComfyNode):
node_id="SamplerLCMUpscale",
category="sampling/custom_sampling/samplers",
inputs=[
io.Float.Input("scale_ratio", default=1.0, min=0.1, max=20.0, step=0.01),
io.Int.Input("scale_steps", default=-1, min=-1, max=1000, step=1),
io.Float.Input("scale_ratio", default=1.0, min=0.1, max=20.0, step=0.01, advanced=True),
io.Int.Input("scale_steps", default=-1, min=-1, max=1000, step=1, advanced=True),
io.Combo.Input("upscale_method", options=cls.UPSCALE_METHODS),
],
outputs=[io.Sampler.Output()],
@ -94,7 +94,7 @@ class SamplerEulerCFGpp(io.ComfyNode):
display_name="SamplerEulerCFG++",
category="_for_testing", # "sampling/custom_sampling/samplers"
inputs=[
io.Combo.Input("version", options=["regular", "alternative"]),
io.Combo.Input("version", options=["regular", "alternative"], advanced=True),
],
outputs=[io.Sampler.Output()],
is_experimental=True,

3
comfy_extras/nodes_apg.py
View File

@ -26,6 +26,7 @@ class APG(io.ComfyNode):
max=10.0,
step=0.01,
tooltip="Controls the scale of the parallel guidance vector. Default CFG behavior at a setting of 1.",
advanced=True,
),
io.Float.Input(
"norm_threshold",
@ -34,6 +35,7 @@ class APG(io.ComfyNode):
max=50.0,
step=0.1,
tooltip="Normalize guidance vector to this value, normalization disable at a setting of 0.",
advanced=True,
),
io.Float.Input(
"momentum",
@ -42,6 +44,7 @@ class APG(io.ComfyNode):
max=1.0,
step=0.01,
tooltip="Controls a running average of guidance during diffusion, disabled at a setting of 0.",
advanced=True,
),
],
outputs=[io.Model.Output()],

32
comfy_extras/nodes_attention_multiply.py
View File

@ -28,10 +28,10 @@ class UNetSelfAttentionMultiply(io.ComfyNode):
category="_for_testing/attention_experiments",
inputs=[
io.Model.Input("model"),
io.Float.Input("q", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("k", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("v", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("out", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("q", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("k", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("v", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("out", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
],
outputs=[io.Model.Output()],
is_experimental=True,
@ -51,10 +51,10 @@ class UNetCrossAttentionMultiply(io.ComfyNode):
category="_for_testing/attention_experiments",
inputs=[
io.Model.Input("model"),
io.Float.Input("q", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("k", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("v", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("out", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("q", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("k", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("v", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("out", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
],
outputs=[io.Model.Output()],
is_experimental=True,
@ -75,10 +75,10 @@ class CLIPAttentionMultiply(io.ComfyNode):
category="_for_testing/attention_experiments",
inputs=[
io.Clip.Input("clip"),
io.Float.Input("q", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("k", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("v", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("out", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("q", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("k", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("v", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("out", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
],
outputs=[io.Clip.Output()],
is_experimental=True,
@ -109,10 +109,10 @@ class UNetTemporalAttentionMultiply(io.ComfyNode):
category="_for_testing/attention_experiments",
inputs=[
io.Model.Input("model"),
io.Float.Input("self_structural", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("self_temporal", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("cross_structural", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("cross_temporal", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("self_structural", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("self_temporal", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("cross_structural", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
io.Float.Input("cross_temporal", default=1.0, min=0.0, max=10.0, step=0.01, advanced=True),
],
outputs=[io.Model.Output()],
is_experimental=True,

5
comfy_extras/nodes_audio.py
View File

@ -22,7 +22,8 @@ class EmptyLatentAudio(IO.ComfyNode):
inputs=[
IO.Float.Input("seconds", default=47.6, min=1.0, max=1000.0, step=0.1),
IO.Int.Input(
"batch_size", default=1, min=1, max=4096, tooltip="The number of latent images in the batch."
"batch_size", default=1, min=1, max=4096, tooltip="The number of latent images in the batch.",
advanced=True,
),
],
outputs=[IO.Latent.Output()],
@ -645,6 +646,7 @@ class EmptyAudio(IO.ComfyNode):
tooltip="Sample rate of the empty audio clip.",
min=1,
max=192000,
advanced=True,
),
IO.Int.Input(
"channels",
@ -652,6 +654,7 @@ class EmptyAudio(IO.ComfyNode):
min=1,
max=2,
tooltip="Number of audio channels (1 for mono, 2 for stereo).",
advanced=True,
),
],
outputs=[IO.Audio.Output()],

8
comfy_extras/nodes_camera_trajectory.py
View File

@ -174,10 +174,10 @@ class WanCameraEmbedding(io.ComfyNode):
io.Int.Input("height", default=480, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("length", default=81, min=1, max=nodes.MAX_RESOLUTION, step=4),
io.Float.Input("speed", default=1.0, min=0, max=10.0, step=0.1, optional=True),
io.Float.Input("fx", default=0.5, min=0, max=1, step=0.000000001, optional=True),
io.Float.Input("fy", default=0.5, min=0, max=1, step=0.000000001, optional=True),
io.Float.Input("cx", default=0.5, min=0, max=1, step=0.01, optional=True),
io.Float.Input("cy", default=0.5, min=0, max=1, step=0.01, optional=True),
io.Float.Input("fx", default=0.5, min=0, max=1, step=0.000000001, optional=True, advanced=True),
io.Float.Input("fy", default=0.5, min=0, max=1, step=0.000000001, optional=True, advanced=True),
io.Float.Input("cx", default=0.5, min=0, max=1, step=0.01, optional=True, advanced=True),
io.Float.Input("cy", default=0.5, min=0, max=1, step=0.01, optional=True, advanced=True),
],
outputs=[
io.WanCameraEmbedding.Output(display_name="camera_embedding"),

3
comfy_extras/nodes_chroma_radiance.py
View File

@ -48,6 +48,7 @@ class ChromaRadianceOptions(io.ComfyNode):
min=0.0,
max=1.0,
tooltip="First sigma that these options will be in effect.",
advanced=True,
),
io.Float.Input(
id="end_sigma",
@ -55,12 +56,14 @@ class ChromaRadianceOptions(io.ComfyNode):
min=0.0,
max=1.0,
tooltip="Last sigma that these options will be in effect.",
advanced=True,
),
io.Int.Input(
id="nerf_tile_size",
default=-1,
min=-1,
tooltip="Allows overriding the default NeRF tile size. -1 means use the default (32). 0 means use non-tiling mode (may require a lot of VRAM).",
advanced=True,
),
],
outputs=[io.Model.Output()],

4
comfy_extras/nodes_clip_sdxl.py
View File

@ -35,8 +35,8 @@ class CLIPTextEncodeSDXL(io.ComfyNode):
io.Clip.Input("clip"),
io.Int.Input("width", default=1024, min=0, max=nodes.MAX_RESOLUTION),
io.Int.Input("height", default=1024, min=0, max=nodes.MAX_RESOLUTION),
io.Int.Input("crop_w", default=0, min=0, max=nodes.MAX_RESOLUTION),
io.Int.Input("crop_h", default=0, min=0, max=nodes.MAX_RESOLUTION),
io.Int.Input("crop_w", default=0, min=0, max=nodes.MAX_RESOLUTION, advanced=True),
io.Int.Input("crop_h", default=0, min=0, max=nodes.MAX_RESOLUTION, advanced=True),
io.Int.Input("target_width", default=1024, min=0, max=nodes.MAX_RESOLUTION),
io.Int.Input("target_height", default=1024, min=0, max=nodes.MAX_RESOLUTION),
io.String.Input("text_g", multiline=True, dynamic_prompts=True),

4
comfy_extras/nodes_cond.py
View File

@ -38,8 +38,8 @@ class T5TokenizerOptions(io.ComfyNode):
category="_for_testing/conditioning",
inputs=[
io.Clip.Input("clip"),
io.Int.Input("min_padding", default=0, min=0, max=10000, step=1),
io.Int.Input("min_length", default=0, min=0, max=10000, step=1),
io.Int.Input("min_padding", default=0, min=0, max=10000, step=1, advanced=True),
io.Int.Input("min_length", default=0, min=0, max=10000, step=1, advanced=True),
],
outputs=[io.Clip.Output()],
is_experimental=True,

12
comfy_extras/nodes_context_windows.py
View File

@ -14,15 +14,15 @@ class ContextWindowsManualNode(io.ComfyNode):
description="Manually set context windows.",
inputs=[
io.Model.Input("model", tooltip="The model to apply context windows to during sampling."),
io.Int.Input("context_length", min=1, default=16, tooltip="The length of the context window."),
io.Int.Input("context_overlap", min=0, default=4, tooltip="The overlap of the context window."),
io.Int.Input("context_length", min=1, default=16, tooltip="The length of the context window.", advanced=True),
io.Int.Input("context_overlap", min=0, default=4, tooltip="The overlap of the context window.", advanced=True),
io.Combo.Input("context_schedule", options=[
comfy.context_windows.ContextSchedules.STATIC_STANDARD,
comfy.context_windows.ContextSchedules.UNIFORM_STANDARD,
comfy.context_windows.ContextSchedules.UNIFORM_LOOPED,
comfy.context_windows.ContextSchedules.BATCHED,
], tooltip="The stride of the context window."),
io.Int.Input("context_stride", min=1, default=1, tooltip="The stride of the context window; only applicable to uniform schedules."),
io.Int.Input("context_stride", min=1, default=1, tooltip="The stride of the context window; only applicable to uniform schedules.", advanced=True),
io.Boolean.Input("closed_loop", default=False, tooltip="Whether to close the context window loop; only applicable to looped schedules."),
io.Combo.Input("fuse_method", options=comfy.context_windows.ContextFuseMethods.LIST_STATIC, default=comfy.context_windows.ContextFuseMethods.PYRAMID, tooltip="The method to use to fuse the context windows."),
io.Int.Input("dim", min=0, max=5, default=0, tooltip="The dimension to apply the context windows to."),
@ -67,15 +67,15 @@ class WanContextWindowsManualNode(ContextWindowsManualNode):
schema.description = "Manually set context windows for WAN-like models (dim=2)."
schema.inputs = [
io.Model.Input("model", tooltip="The model to apply context windows to during sampling."),
io.Int.Input("context_length", min=1, max=nodes.MAX_RESOLUTION, step=4, default=81, tooltip="The length of the context window."),
io.Int.Input("context_overlap", min=0, default=30, tooltip="The overlap of the context window."),
io.Int.Input("context_length", min=1, max=nodes.MAX_RESOLUTION, step=4, default=81, tooltip="The length of the context window.", advanced=True),
io.Int.Input("context_overlap", min=0, default=30, tooltip="The overlap of the context window.", advanced=True),
io.Combo.Input("context_schedule", options=[
comfy.context_windows.ContextSchedules.STATIC_STANDARD,
comfy.context_windows.ContextSchedules.UNIFORM_STANDARD,
comfy.context_windows.ContextSchedules.UNIFORM_LOOPED,
comfy.context_windows.ContextSchedules.BATCHED,
], tooltip="The stride of the context window."),
io.Int.Input("context_stride", min=1, default=1, tooltip="The stride of the context window; only applicable to uniform schedules."),
io.Int.Input("context_stride", min=1, default=1, tooltip="The stride of the context window; only applicable to uniform schedules.", advanced=True),
io.Boolean.Input("closed_loop", default=False, tooltip="Whether to close the context window loop; only applicable to looped schedules."),
io.Combo.Input("fuse_method", options=comfy.context_windows.ContextFuseMethods.LIST_STATIC, default=comfy.context_windows.ContextFuseMethods.PYRAMID, tooltip="The method to use to fuse the context windows."),
io.Boolean.Input("freenoise", default=False, tooltip="Whether to apply FreeNoise noise shuffling, improves window blending."),

4
comfy_extras/nodes_controlnet.py
View File

@ -48,8 +48,8 @@ class ControlNetInpaintingAliMamaApply(io.ComfyNode):
io.Image.Input("image"),
io.Mask.Input("mask"),
io.Float.Input("strength", default=1.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001),
io.Float.Input("end_percent", default=1.0, min=0.0, max=1.0, step=0.001),
io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001, advanced=True),
io.Float.Input("end_percent", default=1.0, min=0.0, max=1.0, step=0.001, advanced=True),
],
outputs=[
io.Conditioning.Output(display_name="positive"),

110
comfy_extras/nodes_custom_sampler.py
View File

@ -50,9 +50,9 @@ class KarrasScheduler(io.ComfyNode):
category="sampling/custom_sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False),
io.Float.Input("sigma_min", default=0.0291675, min=0.0, max=5000.0, step=0.01, round=False),
io.Float.Input("rho", default=7.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
io.Float.Input("sigma_min", default=0.0291675, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
io.Float.Input("rho", default=7.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
],
outputs=[io.Sigmas.Output()]
)
@ -72,8 +72,8 @@ class ExponentialScheduler(io.ComfyNode):
category="sampling/custom_sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False),
io.Float.Input("sigma_min", default=0.0291675, min=0.0, max=5000.0, step=0.01, round=False),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
io.Float.Input("sigma_min", default=0.0291675, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
],
outputs=[io.Sigmas.Output()]
)
@ -93,9 +93,9 @@ class PolyexponentialScheduler(io.ComfyNode):
category="sampling/custom_sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False),
io.Float.Input("sigma_min", default=0.0291675, min=0.0, max=5000.0, step=0.01, round=False),
io.Float.Input("rho", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
io.Float.Input("sigma_min", default=0.0291675, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
io.Float.Input("rho", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
],
outputs=[io.Sigmas.Output()]
)
@ -115,10 +115,10 @@ class LaplaceScheduler(io.ComfyNode):
category="sampling/custom_sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False),
io.Float.Input("sigma_min", default=0.0291675, min=0.0, max=5000.0, step=0.01, round=False),
io.Float.Input("mu", default=0.0, min=-10.0, max=10.0, step=0.1, round=False),
io.Float.Input("beta", default=0.5, min=0.0, max=10.0, step=0.1, round=False),
io.Float.Input("sigma_max", default=14.614642, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
io.Float.Input("sigma_min", default=0.0291675, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
io.Float.Input("mu", default=0.0, min=-10.0, max=10.0, step=0.1, round=False, advanced=True),
io.Float.Input("beta", default=0.5, min=0.0, max=10.0, step=0.1, round=False, advanced=True),
],
outputs=[io.Sigmas.Output()]
)
@ -164,8 +164,8 @@ class BetaSamplingScheduler(io.ComfyNode):
inputs=[
io.Model.Input("model"),
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("alpha", default=0.6, min=0.0, max=50.0, step=0.01, round=False),
io.Float.Input("beta", default=0.6, min=0.0, max=50.0, step=0.01, round=False),
io.Float.Input("alpha", default=0.6, min=0.0, max=50.0, step=0.01, round=False, advanced=True),
io.Float.Input("beta", default=0.6, min=0.0, max=50.0, step=0.01, round=False, advanced=True),
],
outputs=[io.Sigmas.Output()]
)
@ -185,9 +185,9 @@ class VPScheduler(io.ComfyNode):
category="sampling/custom_sampling/schedulers",
inputs=[
io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input("beta_d", default=19.9, min=0.0, max=5000.0, step=0.01, round=False), #TODO: fix default values
io.Float.Input("beta_min", default=0.1, min=0.0, max=5000.0, step=0.01, round=False),
io.Float.Input("eps_s", default=0.001, min=0.0, max=1.0, step=0.0001, round=False),
io.Float.Input("beta_d", default=19.9, min=0.0, max=5000.0, step=0.01, round=False, advanced=True), #TODO: fix default values
io.Float.Input("beta_min", default=0.1, min=0.0, max=5000.0, step=0.01, round=False, advanced=True),
io.Float.Input("eps_s", default=0.001, min=0.0, max=1.0, step=0.0001, round=False, advanced=True),
],
outputs=[io.Sigmas.Output()]
)
@ -398,9 +398,9 @@ class SamplerDPMPP_3M_SDE(io.ComfyNode):
node_id="SamplerDPMPP_3M_SDE",
category="sampling/custom_sampling/samplers",
inputs=[
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Combo.Input("noise_device", options=['gpu', 'cpu']),
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Combo.Input("noise_device", options=['gpu', 'cpu'], advanced=True),
],
outputs=[io.Sampler.Output()]
)
@ -424,9 +424,9 @@ class SamplerDPMPP_2M_SDE(io.ComfyNode):
category="sampling/custom_sampling/samplers",
inputs=[
io.Combo.Input("solver_type", options=['midpoint', 'heun']),
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Combo.Input("noise_device", options=['gpu', 'cpu']),
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Combo.Input("noise_device", options=['gpu', 'cpu'], advanced=True),
],
outputs=[io.Sampler.Output()]
)
@ -450,10 +450,10 @@ class SamplerDPMPP_SDE(io.ComfyNode):
node_id="SamplerDPMPP_SDE",
category="sampling/custom_sampling/samplers",
inputs=[
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("r", default=0.5, min=0.0, max=100.0, step=0.01, round=False),
io.Combo.Input("noise_device", options=['gpu', 'cpu']),
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("r", default=0.5, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Combo.Input("noise_device", options=['gpu', 'cpu'], advanced=True),
],
outputs=[io.Sampler.Output()]
)
@ -496,8 +496,8 @@ class SamplerEulerAncestral(io.ComfyNode):
node_id="SamplerEulerAncestral",
category="sampling/custom_sampling/samplers",
inputs=[
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
],
outputs=[io.Sampler.Output()]
)
@ -538,7 +538,7 @@ class SamplerLMS(io.ComfyNode):
return io.Schema(
node_id="SamplerLMS",
category="sampling/custom_sampling/samplers",
inputs=[io.Int.Input("order", default=4, min=1, max=100)],
inputs=[io.Int.Input("order", default=4, min=1, max=100, advanced=True)],
outputs=[io.Sampler.Output()]
)
@ -556,16 +556,16 @@ class SamplerDPMAdaptative(io.ComfyNode):
node_id="SamplerDPMAdaptative",
category="sampling/custom_sampling/samplers",
inputs=[
io.Int.Input("order", default=3, min=2, max=3),
io.Float.Input("rtol", default=0.05, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("atol", default=0.0078, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("h_init", default=0.05, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("pcoeff", default=0.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("icoeff", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("dcoeff", default=0.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("accept_safety", default=0.81, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("eta", default=0.0, min=0.0, max=100.0, step=0.01, round=False),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Int.Input("order", default=3, min=2, max=3, advanced=True),
io.Float.Input("rtol", default=0.05, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("atol", default=0.0078, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("h_init", default=0.05, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("pcoeff", default=0.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("icoeff", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("dcoeff", default=0.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("accept_safety", default=0.81, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("eta", default=0.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
],
outputs=[io.Sampler.Output()]
)
@ -588,9 +588,9 @@ class SamplerER_SDE(io.ComfyNode):
category="sampling/custom_sampling/samplers",
inputs=[
io.Combo.Input("solver_type", options=["ER-SDE", "Reverse-time SDE", "ODE"]),
io.Int.Input("max_stage", default=3, min=1, max=3),
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, tooltip="Stochastic strength of reverse-time SDE.\nWhen eta=0, it reduces to deterministic ODE. This setting doesn't apply to ER-SDE solver type."),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Int.Input("max_stage", default=3, min=1, max=3, advanced=True),
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, tooltip="Stochastic strength of reverse-time SDE.\nWhen eta=0, it reduces to deterministic ODE. This setting doesn't apply to ER-SDE solver type.", advanced=True),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
],
outputs=[io.Sampler.Output()]
)
@ -625,14 +625,14 @@ class SamplerSASolver(io.ComfyNode):
category="sampling/custom_sampling/samplers",
inputs=[
io.Model.Input("model"),
io.Float.Input("eta", default=1.0, min=0.0, max=10.0, step=0.01, round=False),
io.Float.Input("sde_start_percent", default=0.2, min=0.0, max=1.0, step=0.001),
io.Float.Input("sde_end_percent", default=0.8, min=0.0, max=1.0, step=0.001),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False),
io.Int.Input("predictor_order", default=3, min=1, max=6),
io.Int.Input("corrector_order", default=4, min=0, max=6),
io.Boolean.Input("use_pece"),
io.Boolean.Input("simple_order_2"),
io.Float.Input("eta", default=1.0, min=0.0, max=10.0, step=0.01, round=False, advanced=True),
io.Float.Input("sde_start_percent", default=0.2, min=0.0, max=1.0, step=0.001, advanced=True),
io.Float.Input("sde_end_percent", default=0.8, min=0.0, max=1.0, step=0.001, advanced=True),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, advanced=True),
io.Int.Input("predictor_order", default=3, min=1, max=6, advanced=True),
io.Int.Input("corrector_order", default=4, min=0, max=6, advanced=True),
io.Boolean.Input("use_pece", advanced=True),
io.Boolean.Input("simple_order_2", advanced=True),
],
outputs=[io.Sampler.Output()]
)
@ -669,9 +669,9 @@ class SamplerSEEDS2(io.ComfyNode):
category="sampling/custom_sampling/samplers",
inputs=[
io.Combo.Input("solver_type", options=["phi_1", "phi_2"]),
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, tooltip="Stochastic strength"),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, tooltip="SDE noise multiplier"),
io.Float.Input("r", default=0.5, min=0.01, max=1.0, step=0.01, round=False, tooltip="Relative step size for the intermediate stage (c2 node)"),
io.Float.Input("eta", default=1.0, min=0.0, max=100.0, step=0.01, round=False, tooltip="Stochastic strength", advanced=True),
io.Float.Input("s_noise", default=1.0, min=0.0, max=100.0, step=0.01, round=False, tooltip="SDE noise multiplier", advanced=True),
io.Float.Input("r", default=0.5, min=0.01, max=1.0, step=0.01, round=False, tooltip="Relative step size for the intermediate stage (c2 node)", advanced=True),
],
outputs=[io.Sampler.Output()],
description=(
@ -728,7 +728,7 @@ class SamplerCustom(io.ComfyNode):
category="sampling/custom_sampling",
inputs=[
io.Model.Input("model"),
io.Boolean.Input("add_noise", default=True),
io.Boolean.Input("add_noise", default=True, advanced=True),
io.Int.Input("noise_seed", default=0, min=0, max=0xffffffffffffffff, control_after_generate=True),
io.Float.Input("cfg", default=8.0, min=0.0, max=100.0, step=0.1, round=0.01),
io.Conditioning.Input("positive"),

10
comfy_extras/nodes_dataset.py
View File

@ -222,6 +222,7 @@ class SaveImageDataSetToFolderNode(io.ComfyNode):
"filename_prefix",
default="image",
tooltip="Prefix for saved image filenames.",
advanced=True,
),
],
outputs=[],
@ -262,6 +263,7 @@ class SaveImageTextDataSetToFolderNode(io.ComfyNode):
"filename_prefix",
default="image",
tooltip="Prefix for saved image filenames.",
advanced=True,
),
],
outputs=[],
@ -741,6 +743,7 @@ class NormalizeImagesNode(ImageProcessingNode):
min=0.0,
max=1.0,
tooltip="Mean value for normalization.",
advanced=True,
),
io.Float.Input(
"std",
@ -748,6 +751,7 @@ class NormalizeImagesNode(ImageProcessingNode):
min=0.001,
max=1.0,
tooltip="Standard deviation for normalization.",
advanced=True,
),
]
@ -961,6 +965,7 @@ class ImageDeduplicationNode(ImageProcessingNode):
min=0.0,
max=1.0,
tooltip="Similarity threshold (0-1). Higher means more similar. Images above this threshold are considered duplicates.",
advanced=True,
),
]
@ -1039,6 +1044,7 @@ class ImageGridNode(ImageProcessingNode):
min=32,
max=2048,
tooltip="Width of each cell in the grid.",
advanced=True,
),
io.Int.Input(
"cell_height",
@ -1046,9 +1052,10 @@ class ImageGridNode(ImageProcessingNode):
min=32,
max=2048,
tooltip="Height of each cell in the grid.",
advanced=True,
),
io.Int.Input(
"padding", default=4, min=0, max=50, tooltip="Padding between images."
"padding", default=4, min=0, max=50, tooltip="Padding between images.", advanced=True
),
]
@ -1339,6 +1346,7 @@ class SaveTrainingDataset(io.ComfyNode):
min=1,
max=100000,
tooltip="Number of samples per shard file.",
advanced=True,
),
],
outputs=[],

16
comfy_extras/nodes_easycache.py
View File

@ -343,10 +343,10 @@ class EasyCacheNode(io.ComfyNode):
is_experimental=True,
inputs=[
io.Model.Input("model", tooltip="The model to add EasyCache to."),
io.Float.Input("reuse_threshold", min=0.0, default=0.2, max=3.0, step=0.01, tooltip="The threshold for reusing cached steps."),
io.Float.Input("start_percent", min=0.0, default=0.15, max=1.0, step=0.01, tooltip="The relative sampling step to begin use of EasyCache."),
io.Float.Input("end_percent", min=0.0, default=0.95, max=1.0, step=0.01, tooltip="The relative sampling step to end use of EasyCache."),
io.Boolean.Input("verbose", default=False, tooltip="Whether to log verbose information."),
io.Float.Input("reuse_threshold", min=0.0, default=0.2, max=3.0, step=0.01, tooltip="The threshold for reusing cached steps.", advanced=True),
io.Float.Input("start_percent", min=0.0, default=0.15, max=1.0, step=0.01, tooltip="The relative sampling step to begin use of EasyCache.", advanced=True),
io.Float.Input("end_percent", min=0.0, default=0.95, max=1.0, step=0.01, tooltip="The relative sampling step to end use of EasyCache.", advanced=True),
io.Boolean.Input("verbose", default=False, tooltip="Whether to log verbose information.", advanced=True),
],
outputs=[
io.Model.Output(tooltip="The model with EasyCache."),
@ -476,10 +476,10 @@ class LazyCacheNode(io.ComfyNode):
is_experimental=True,
inputs=[
io.Model.Input("model", tooltip="The model to add LazyCache to."),
io.Float.Input("reuse_threshold", min=0.0, default=0.2, max=3.0, step=0.01, tooltip="The threshold for reusing cached steps."),
io.Float.Input("start_percent", min=0.0, default=0.15, max=1.0, step=0.01, tooltip="The relative sampling step to begin use of LazyCache."),
io.Float.Input("end_percent", min=0.0, default=0.95, max=1.0, step=0.01, tooltip="The relative sampling step to end use of LazyCache."),
io.Boolean.Input("verbose", default=False, tooltip="Whether to log verbose information."),
io.Float.Input("reuse_threshold", min=0.0, default=0.2, max=3.0, step=0.01, tooltip="The threshold for reusing cached steps.", advanced=True),
io.Float.Input("start_percent", min=0.0, default=0.15, max=1.0, step=0.01, tooltip="The relative sampling step to begin use of LazyCache.", advanced=True),
io.Float.Input("end_percent", min=0.0, default=0.95, max=1.0, step=0.01, tooltip="The relative sampling step to end use of LazyCache.", advanced=True),
io.Boolean.Input("verbose", default=False, tooltip="Whether to log verbose information.", advanced=True),
],
outputs=[
io.Model.Output(tooltip="The model with LazyCache."),

3
comfy_extras/nodes_eps.py
View File

@ -28,6 +28,7 @@ class EpsilonScaling(io.ComfyNode):
max=1.5,
step=0.001,
display_mode=io.NumberDisplay.number,
advanced=True,
),
],
outputs=[
@ -97,6 +98,7 @@ class TemporalScoreRescaling(io.ComfyNode):
max=100.0,
step=0.001,
display_mode=io.NumberDisplay.number,
advanced=True,
),
io.Float.Input(
"tsr_sigma",
@ -109,6 +111,7 @@ class TemporalScoreRescaling(io.ComfyNode):
max=100.0,
step=0.001,
display_mode=io.NumberDisplay.number,
advanced=True,
),
],
outputs=[

1
comfy_extras/nodes_flux.py
View File

@ -161,6 +161,7 @@ class FluxKontextMultiReferenceLatentMethod(io.ComfyNode):
io.Combo.Input(
"reference_latents_method",
options=["offset", "index", "uxo/uno", "index_timestep_zero"],
advanced=True,
),
],
outputs=[

16
comfy_extras/nodes_freelunch.py
View File

@ -32,10 +32,10 @@ class FreeU(IO.ComfyNode):
category="model_patches/unet",
inputs=[
IO.Model.Input("model"),
IO.Float.Input("b1", default=1.1, min=0.0, max=10.0, step=0.01),
IO.Float.Input("b2", default=1.2, min=0.0, max=10.0, step=0.01),
IO.Float.Input("s1", default=0.9, min=0.0, max=10.0, step=0.01),
IO.Float.Input("s2", default=0.2, min=0.0, max=10.0, step=0.01),
IO.Float.Input("b1", default=1.1, min=0.0, max=10.0, step=0.01, advanced=True),
IO.Float.Input("b2", default=1.2, min=0.0, max=10.0, step=0.01, advanced=True),
IO.Float.Input("s1", default=0.9, min=0.0, max=10.0, step=0.01, advanced=True),
IO.Float.Input("s2", default=0.2, min=0.0, max=10.0, step=0.01, advanced=True),
],
outputs=[
IO.Model.Output(),
@ -79,10 +79,10 @@ class FreeU_V2(IO.ComfyNode):
category="model_patches/unet",
inputs=[
IO.Model.Input("model"),
IO.Float.Input("b1", default=1.3, min=0.0, max=10.0, step=0.01),
IO.Float.Input("b2", default=1.4, min=0.0, max=10.0, step=0.01),
IO.Float.Input("s1", default=0.9, min=0.0, max=10.0, step=0.01),
IO.Float.Input("s2", default=0.2, min=0.0, max=10.0, step=0.01),
IO.Float.Input("b1", default=1.3, min=0.0, max=10.0, step=0.01, advanced=True),
IO.Float.Input("b2", default=1.4, min=0.0, max=10.0, step=0.01, advanced=True),
IO.Float.Input("s1", default=0.9, min=0.0, max=10.0, step=0.01, advanced=True),
IO.Float.Input("s2", default=0.2, min=0.0, max=10.0, step=0.01, advanced=True),
],
outputs=[
IO.Model.Output(),

6
comfy_extras/nodes_fresca.py
View File

@ -65,11 +65,11 @@ class FreSca(io.ComfyNode):
inputs=[
io.Model.Input("model"),
io.Float.Input("scale_low", default=1.0, min=0, max=10, step=0.01,
tooltip="Scaling factor for low-frequency components"),
tooltip="Scaling factor for low-frequency components", advanced=True),
io.Float.Input("scale_high", default=1.25, min=0, max=10, step=0.01,
tooltip="Scaling factor for high-frequency components"),
tooltip="Scaling factor for high-frequency components", advanced=True),
io.Int.Input("freq_cutoff", default=20, min=1, max=10000, step=1,
tooltip="Number of frequency indices around center to consider as low-frequency"),
tooltip="Number of frequency indices around center to consider as low-frequency", advanced=True),
],
outputs=[
io.Model.Output(),

2
comfy_extras/nodes_gits.py
View File

@ -342,7 +342,7 @@ class GITSScheduler(io.ComfyNode):
node_id="GITSScheduler",
category="sampling/custom_sampling/schedulers",
inputs=[
io.Float.Input("coeff", default=1.20, min=0.80, max=1.50, step=0.05),
io.Float.Input("coeff", default=1.20, min=0.80, max=1.50, step=0.05, advanced=True),
io.Int.Input("steps", default=10, min=2, max=1000),
io.Float.Input("denoise", default=1.0, min=0.0, max=1.0, step=0.01),
],

8
comfy_extras/nodes_hooks.py
View File

@ -233,8 +233,8 @@ class SetClipHooks:
return {
"required": {
"clip": ("CLIP",),
"apply_to_conds": ("BOOLEAN", {"default": True}),
"schedule_clip": ("BOOLEAN", {"default": False})
"apply_to_conds": ("BOOLEAN", {"default": True, "advanced": True}),
"schedule_clip": ("BOOLEAN", {"default": False, "advanced": True})
},
"optional": {
"hooks": ("HOOKS",)
@ -512,7 +512,7 @@ class CreateHookKeyframesInterpolated:
"start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
"end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}),
"keyframes_count": ("INT", {"default": 5, "min": 2, "max": 100, "step": 1}),
"print_keyframes": ("BOOLEAN", {"default": False}),
"print_keyframes": ("BOOLEAN", {"default": False, "advanced": True}),
},
"optional": {
"prev_hook_kf": ("HOOK_KEYFRAMES",),
@ -557,7 +557,7 @@ class CreateHookKeyframesFromFloats:
"floats_strength": ("FLOATS", {"default": -1, "min": -1, "step": 0.001, "forceInput": True}),
"start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.001}),
"end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.001}),
"print_keyframes": ("BOOLEAN", {"default": False}),
"print_keyframes": ("BOOLEAN", {"default": False, "advanced": True}),
},
"optional": {
"prev_hook_kf": ("HOOK_KEYFRAMES",),

15
comfy_extras/nodes_hunyuan.py
View File

@ -46,7 +46,7 @@ class EmptyHunyuanLatentVideo(io.ComfyNode):
io.Int.Input("width", default=848, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("height", default=480, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("length", default=25, min=1, max=nodes.MAX_RESOLUTION, step=4),
io.Int.Input("batch_size", default=1, min=1, max=4096),
io.Int.Input("batch_size", default=1, min=1, max=4096, advanced=True),
],
outputs=[
io.Latent.Output(),
@ -89,7 +89,7 @@ class HunyuanVideo15ImageToVideo(io.ComfyNode):
io.Int.Input("width", default=848, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("height", default=480, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("length", default=33, min=1, max=nodes.MAX_RESOLUTION, step=4),
io.Int.Input("batch_size", default=1, min=1, max=4096),
io.Int.Input("batch_size", default=1, min=1, max=4096, advanced=True),
io.Image.Input("start_image", optional=True),
io.ClipVisionOutput.Input("clip_vision_output", optional=True),
],
@ -138,7 +138,7 @@ class HunyuanVideo15SuperResolution(io.ComfyNode):
io.Image.Input("start_image", optional=True),
io.ClipVisionOutput.Input("clip_vision_output", optional=True),
io.Latent.Input("latent"),
io.Float.Input("noise_augmentation", default=0.70, min=0.0, max=1.0, step=0.01),
io.Float.Input("noise_augmentation", default=0.70, min=0.0, max=1.0, step=0.01, advanced=True),
],
outputs=[
@ -285,6 +285,7 @@ class TextEncodeHunyuanVideo_ImageToVideo(io.ComfyNode):
min=1,
max=512,
tooltip="How much the image influences things vs the text prompt. Higher number means more influence from the text prompt.",
advanced=True,
),
],
outputs=[
@ -312,8 +313,8 @@ class HunyuanImageToVideo(io.ComfyNode):
io.Int.Input("width", default=848, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("height", default=480, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("length", default=53, min=1, max=nodes.MAX_RESOLUTION, step=4),
io.Int.Input("batch_size", default=1, min=1, max=4096),
io.Combo.Input("guidance_type", options=["v1 (concat)", "v2 (replace)", "custom"]),
io.Int.Input("batch_size", default=1, min=1, max=4096, advanced=True),
io.Combo.Input("guidance_type", options=["v1 (concat)", "v2 (replace)", "custom"], advanced=True),
io.Image.Input("start_image", optional=True),
],
outputs=[
@ -360,7 +361,7 @@ class EmptyHunyuanImageLatent(io.ComfyNode):
inputs=[
io.Int.Input("width", default=2048, min=64, max=nodes.MAX_RESOLUTION, step=32),
io.Int.Input("height", default=2048, min=64, max=nodes.MAX_RESOLUTION, step=32),
io.Int.Input("batch_size", default=1, min=1, max=4096),
io.Int.Input("batch_size", default=1, min=1, max=4096, advanced=True),
],
outputs=[
io.Latent.Output(),
@ -384,7 +385,7 @@ class HunyuanRefinerLatent(io.ComfyNode):
io.Conditioning.Input("positive"),
io.Conditioning.Input("negative"),
io.Latent.Input("latent"),
io.Float.Input("noise_augmentation", default=0.10, min=0.0, max=1.0, step=0.01),
io.Float.Input("noise_augmentation", default=0.10, min=0.0, max=1.0, step=0.01, advanced=True),
],
outputs=[

6
comfy_extras/nodes_hunyuan3d.py
View File

@ -106,8 +106,8 @@ class VAEDecodeHunyuan3D(IO.ComfyNode):
inputs=[
IO.Latent.Input("samples"),
IO.Vae.Input("vae"),
IO.Int.Input("num_chunks", default=8000, min=1000, max=500000),
IO.Int.Input("octree_resolution", default=256, min=16, max=512),
IO.Int.Input("num_chunks", default=8000, min=1000, max=500000, advanced=True),
IO.Int.Input("octree_resolution", default=256, min=16, max=512, advanced=True),
],
outputs=[
IO.Voxel.Output(),
@ -456,7 +456,7 @@ class VoxelToMesh(IO.ComfyNode):
category="3d",
inputs=[
IO.Voxel.Input("voxel"),
IO.Combo.Input("algorithm", options=["surface net", "basic"]),
IO.Combo.Input("algorithm", options=["surface net", "basic"], advanced=True),
IO.Float.Input("threshold", default=0.6, min=-1.0, max=1.0, step=0.01),
],
outputs=[

8
comfy_extras/nodes_hypertile.py
View File

@ -30,10 +30,10 @@ class HyperTile(io.ComfyNode):
category="model_patches/unet",
inputs=[
io.Model.Input("model"),
io.Int.Input("tile_size", default=256, min=1, max=2048),
io.Int.Input("swap_size", default=2, min=1, max=128),
io.Int.Input("max_depth", default=0, min=0, max=10),
io.Boolean.Input("scale_depth", default=False),
io.Int.Input("tile_size", default=256, min=1, max=2048, advanced=True),
io.Int.Input("swap_size", default=2, min=1, max=128, advanced=True),
io.Int.Input("max_depth", default=0, min=0, max=10, advanced=True),
io.Boolean.Input("scale_depth", default=False, advanced=True),
],
outputs=[
io.Model.Output(),

16
comfy_extras/nodes_images.py
View File

@ -138,9 +138,9 @@ class SaveAnimatedWEBP(IO.ComfyNode):
IO.Image.Input("images"),
IO.String.Input("filename_prefix", default="ComfyUI"),
IO.Float.Input("fps", default=6.0, min=0.01, max=1000.0, step=0.01),
IO.Boolean.Input("lossless", default=True),
IO.Int.Input("quality", default=80, min=0, max=100),
IO.Combo.Input("method", options=list(cls.COMPRESS_METHODS.keys())),
IO.Boolean.Input("lossless", default=True, advanced=True),
IO.Int.Input("quality", default=80, min=0, max=100, advanced=True),
IO.Combo.Input("method", options=list(cls.COMPRESS_METHODS.keys()), advanced=True),
# "num_frames": ("INT", {"default": 0, "min": 0, "max": 8192}),
],
hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
@ -175,7 +175,7 @@ class SaveAnimatedPNG(IO.ComfyNode):
IO.Image.Input("images"),
IO.String.Input("filename_prefix", default="ComfyUI"),
IO.Float.Input("fps", default=6.0, min=0.01, max=1000.0, step=0.01),
IO.Int.Input("compress_level", default=4, min=0, max=9),
IO.Int.Input("compress_level", default=4, min=0, max=9, advanced=True),
],
hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo],
is_output_node=True,
@ -212,8 +212,8 @@ class ImageStitch(IO.ComfyNode):
IO.Image.Input("image1"),
IO.Combo.Input("direction", options=["right", "down", "left", "up"], default="right"),
IO.Boolean.Input("match_image_size", default=True),
IO.Int.Input("spacing_width", default=0, min=0, max=1024, step=2),
IO.Combo.Input("spacing_color", options=["white", "black", "red", "green", "blue"], default="white"),
IO.Int.Input("spacing_width", default=0, min=0, max=1024, step=2, advanced=True),
IO.Combo.Input("spacing_color", options=["white", "black", "red", "green", "blue"], default="white", advanced=True),
IO.Image.Input("image2", optional=True),
],
outputs=[IO.Image.Output()],
@ -383,8 +383,8 @@ class ResizeAndPadImage(IO.ComfyNode):
IO.Image.Input("image"),
IO.Int.Input("target_width", default=512, min=1, max=nodes.MAX_RESOLUTION, step=1),
IO.Int.Input("target_height", default=512, min=1, max=nodes.MAX_RESOLUTION, step=1),
IO.Combo.Input("padding_color", options=["white", "black"]),
IO.Combo.Input("interpolation", options=["area", "bicubic", "nearest-exact", "bilinear", "lanczos"]),
IO.Combo.Input("padding_color", options=["white", "black"], advanced=True),
IO.Combo.Input("interpolation", options=["area", "bicubic", "nearest-exact", "bilinear", "lanczos"], advanced=True),
],
outputs=[IO.Image.Output()],
)

6
comfy_extras/nodes_latent.py
View File

@ -412,9 +412,9 @@ class LatentOperationSharpen(io.ComfyNode):
category="latent/advanced/operations",
is_experimental=True,
inputs=[
io.Int.Input("sharpen_radius", default=9, min=1, max=31, step=1),
io.Float.Input("sigma", default=1.0, min=0.1, max=10.0, step=0.1),
io.Float.Input("alpha", default=0.1, min=0.0, max=5.0, step=0.01),
io.Int.Input("sharpen_radius", default=9, min=1, max=31, step=1, advanced=True),
io.Float.Input("sigma", default=1.0, min=0.1, max=10.0, step=0.1, advanced=True),
io.Float.Input("alpha", default=0.1, min=0.0, max=5.0, step=0.01, advanced=True),
],
outputs=[
io.LatentOperation.Output(),

4
comfy_extras/nodes_load_3d.py
View File

@ -82,8 +82,8 @@ class Preview3D(IO.ComfyNode):
is_output_node=True,
inputs=[
IO.String.Input("model_file", default="", multiline=False),
IO.Load3DCamera.Input("camera_info", optional=True),
IO.Image.Input("bg_image", optional=True),
IO.Load3DCamera.Input("camera_info", optional=True, advanced=True),
IO.Image.Input("bg_image", optional=True, advanced=True),
],
outputs=[],
)

6
comfy_extras/nodes_lora_extract.py
View File

@ -83,9 +83,9 @@ class LoraSave(io.ComfyNode):
category="_for_testing",
inputs=[
io.String.Input("filename_prefix", default="loras/ComfyUI_extracted_lora"),
io.Int.Input("rank", default=8, min=1, max=4096, step=1),
io.Combo.Input("lora_type", options=tuple(LORA_TYPES.keys())),
io.Boolean.Input("bias_diff", default=True),
io.Int.Input("rank", default=8, min=1, max=4096, step=1, advanced=True),
io.Combo.Input("lora_type", options=tuple(LORA_TYPES.keys()), advanced=True),
io.Boolean.Input("bias_diff", default=True, advanced=True),
io.Model.Input(
"model_diff",
tooltip="The ModelSubtract output to be converted to a lora.",

2
comfy_extras/nodes_lt.py
View File

@ -450,6 +450,7 @@ class LTXVScheduler(io.ComfyNode):
id="stretch",
default=True,
tooltip="Stretch the sigmas to be in the range [terminal, 1].",
advanced=True,
),
io.Float.Input(
id="terminal",
@ -458,6 +459,7 @@ class LTXVScheduler(io.ComfyNode):
max=0.99,
step=0.01,
tooltip="The terminal value of the sigmas after stretching.",
advanced=True,
),
io.Latent.Input("latent", optional=True),
],

1
comfy_extras/nodes_lt_audio.py
View File

@ -189,6 +189,7 @@ class LTXAVTextEncoderLoader(io.ComfyNode):
io.Combo.Input(
"device",
options=["default", "cpu"],
advanced=True,
)
],
outputs=[io.Clip.Output()],

4
comfy_extras/nodes_lumina2.py
View File

@ -12,8 +12,8 @@ class RenormCFG(io.ComfyNode):
category="advanced/model",
inputs=[
io.Model.Input("model"),
io.Float.Input("cfg_trunc", default=100, min=0.0, max=100.0, step=0.01),
io.Float.Input("renorm_cfg", default=1.0, min=0.0, max=100.0, step=0.01),
io.Float.Input("cfg_trunc", default=100, min=0.0, max=100.0, step=0.01, advanced=True),
io.Float.Input("renorm_cfg", default=1.0, min=0.0, max=100.0, step=0.01, advanced=True),
],
outputs=[
io.Model.Output(),

2
comfy_extras/nodes_mask.py
View File

@ -348,7 +348,7 @@ class GrowMask(IO.ComfyNode):
inputs=[
IO.Mask.Input("mask"),
IO.Int.Input("expand", default=0, min=-nodes.MAX_RESOLUTION, max=nodes.MAX_RESOLUTION, step=1),
IO.Boolean.Input("tapered_corners", default=True),
IO.Boolean.Input("tapered_corners", default=True, advanced=True),
],
outputs=[IO.Mask.Output()],
)

16
comfy_extras/nodes_model_advanced.py
View File

@ -53,7 +53,7 @@ class ModelSamplingDiscrete:
def INPUT_TYPES(s):
return {"required": { "model": ("MODEL",),
"sampling": (["eps", "v_prediction", "lcm", "x0", "img_to_img"],),
"zsnr": ("BOOLEAN", {"default": False}),
"zsnr": ("BOOLEAN", {"default": False, "advanced": True}),
}}
RETURN_TYPES = ("MODEL",)
@ -153,8 +153,8 @@ class ModelSamplingFlux:
@classmethod
def INPUT_TYPES(s):
return {"required": { "model": ("MODEL",),
"max_shift": ("FLOAT", {"default": 1.15, "min": 0.0, "max": 100.0, "step":0.01}),
"base_shift": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 100.0, "step":0.01}),
"max_shift": ("FLOAT", {"default": 1.15, "min": 0.0, "max": 100.0, "step":0.01, "advanced": True}),
"base_shift": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 100.0, "step":0.01, "advanced": True}),
"width": ("INT", {"default": 1024, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 8}),
"height": ("INT", {"default": 1024, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 8}),
}}
@ -190,8 +190,8 @@ class ModelSamplingContinuousEDM:
def INPUT_TYPES(s):
return {"required": { "model": ("MODEL",),
"sampling": (["v_prediction", "edm", "edm_playground_v2.5", "eps", "cosmos_rflow"],),
"sigma_max": ("FLOAT", {"default": 120.0, "min": 0.0, "max": 1000.0, "step":0.001, "round": False}),
"sigma_min": ("FLOAT", {"default": 0.002, "min": 0.0, "max": 1000.0, "step":0.001, "round": False}),
"sigma_max": ("FLOAT", {"default": 120.0, "min": 0.0, "max": 1000.0, "step":0.001, "round": False, "advanced": True}),
"sigma_min": ("FLOAT", {"default": 0.002, "min": 0.0, "max": 1000.0, "step":0.001, "round": False, "advanced": True}),
}}
RETURN_TYPES = ("MODEL",)
@ -235,8 +235,8 @@ class ModelSamplingContinuousV:
def INPUT_TYPES(s):
return {"required": { "model": ("MODEL",),
"sampling": (["v_prediction"],),
"sigma_max": ("FLOAT", {"default": 500.0, "min": 0.0, "max": 1000.0, "step":0.001, "round": False}),
"sigma_min": ("FLOAT", {"default": 0.03, "min": 0.0, "max": 1000.0, "step":0.001, "round": False}),
"sigma_max": ("FLOAT", {"default": 500.0, "min": 0.0, "max": 1000.0, "step":0.001, "round": False, "advanced": True}),
"sigma_min": ("FLOAT", {"default": 0.03, "min": 0.0, "max": 1000.0, "step":0.001, "round": False, "advanced": True}),
}}
RETURN_TYPES = ("MODEL",)
@ -303,7 +303,7 @@ class ModelComputeDtype:
@classmethod
def INPUT_TYPES(s):
return {"required": { "model": ("MODEL",),
"dtype": (["default", "fp32", "fp16", "bf16"],),
"dtype": (["default", "fp32", "fp16", "bf16"], {"advanced": True}),
}}
RETURN_TYPES = ("MODEL",)

8
comfy_extras/nodes_model_downscale.py
View File

@ -13,11 +13,11 @@ class PatchModelAddDownscale(io.ComfyNode):
category="model_patches/unet",
inputs=[
io.Model.Input("model"),
io.Int.Input("block_number", default=3, min=1, max=32, step=1),
io.Int.Input("block_number", default=3, min=1, max=32, step=1, advanced=True),
io.Float.Input("downscale_factor", default=2.0, min=0.1, max=9.0, step=0.001),
io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001),
io.Float.Input("end_percent", default=0.35, min=0.0, max=1.0, step=0.001),
io.Boolean.Input("downscale_after_skip", default=True),
io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001, advanced=True),
io.Float.Input("end_percent", default=0.35, min=0.0, max=1.0, step=0.001, advanced=True),
io.Boolean.Input("downscale_after_skip", default=True, advanced=True),
io.Combo.Input("downscale_method", options=cls.UPSCALE_METHODS),
io.Combo.Input("upscale_method", options=cls.UPSCALE_METHODS),
],

28
comfy_extras/nodes_model_merging_model_specific.py
View File

@ -7,7 +7,7 @@ class ModelMergeSD1(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["time_embed."] = argument
arg_dict["label_emb."] = argument
@ -34,7 +34,7 @@ class ModelMergeSDXL(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["time_embed."] = argument
arg_dict["label_emb."] = argument
@ -60,7 +60,7 @@ class ModelMergeSD3_2B(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["pos_embed."] = argument
arg_dict["x_embedder."] = argument
@ -84,7 +84,7 @@ class ModelMergeAuraflow(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["init_x_linear."] = argument
arg_dict["positional_encoding"] = argument
@ -111,7 +111,7 @@ class ModelMergeFlux1(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["img_in."] = argument
arg_dict["time_in."] = argument
@ -137,7 +137,7 @@ class ModelMergeSD35_Large(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["pos_embed."] = argument
arg_dict["x_embedder."] = argument
@ -160,7 +160,7 @@ class ModelMergeMochiPreview(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["pos_frequencies."] = argument
arg_dict["t_embedder."] = argument
@ -182,7 +182,7 @@ class ModelMergeLTXV(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["patchify_proj."] = argument
arg_dict["adaln_single."] = argument
@ -204,7 +204,7 @@ class ModelMergeCosmos7B(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["pos_embedder."] = argument
arg_dict["extra_pos_embedder."] = argument
@ -228,7 +228,7 @@ class ModelMergeCosmos14B(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["pos_embedder."] = argument
arg_dict["extra_pos_embedder."] = argument
@ -253,7 +253,7 @@ class ModelMergeWAN2_1(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["patch_embedding."] = argument
arg_dict["time_embedding."] = argument
@ -276,7 +276,7 @@ class ModelMergeCosmosPredict2_2B(comfy_extras.nodes_model_merging.ModelMergeBlo
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["pos_embedder."] = argument
arg_dict["x_embedder."] = argument
@ -299,7 +299,7 @@ class ModelMergeCosmosPredict2_14B(comfy_extras.nodes_model_merging.ModelMergeBl
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["pos_embedder."] = argument
arg_dict["x_embedder."] = argument
@ -322,7 +322,7 @@ class ModelMergeQwenImage(comfy_extras.nodes_model_merging.ModelMergeBlocks):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "advanced": True})
arg_dict["pos_embeds."] = argument
arg_dict["img_in."] = argument

4
comfy_extras/nodes_perpneg.py
View File

@ -29,7 +29,7 @@ class PerpNeg(io.ComfyNode):
inputs=[
io.Model.Input("model"),
io.Conditioning.Input("empty_conditioning"),
io.Float.Input("neg_scale", default=1.0, min=0.0, max=100.0, step=0.01),
io.Float.Input("neg_scale", default=1.0, min=0.0, max=100.0, step=0.01, advanced=True),
],
outputs=[
io.Model.Output(),
@ -134,7 +134,7 @@ class PerpNegGuider(io.ComfyNode):
io.Conditioning.Input("negative"),
io.Conditioning.Input("empty_conditioning"),
io.Float.Input("cfg", default=8.0, min=0.0, max=100.0, step=0.1, round=0.01),
io.Float.Input("neg_scale", default=1.0, min=0.0, max=100.0, step=0.01),
io.Float.Input("neg_scale", default=1.0, min=0.0, max=100.0, step=0.01, advanced=True),
],
outputs=[
io.Guider.Output(),

8
comfy_extras/nodes_post_processing.py
View File

@ -179,9 +179,9 @@ class Sharpen(io.ComfyNode):
category="image/postprocessing",
inputs=[
io.Image.Input("image"),
io.Int.Input("sharpen_radius", default=1, min=1, max=31, step=1),
io.Float.Input("sigma", default=1.0, min=0.1, max=10.0, step=0.01),
io.Float.Input("alpha", default=1.0, min=0.0, max=5.0, step=0.01),
io.Int.Input("sharpen_radius", default=1, min=1, max=31, step=1, advanced=True),
io.Float.Input("sigma", default=1.0, min=0.1, max=10.0, step=0.01, advanced=True),
io.Float.Input("alpha", default=1.0, min=0.0, max=5.0, step=0.01, advanced=True),
],
outputs=[
io.Image.Output(),
@ -225,7 +225,7 @@ class ImageScaleToTotalPixels(io.ComfyNode):
io.Image.Input("image"),
io.Combo.Input("upscale_method", options=cls.upscale_methods),
io.Float.Input("megapixels", default=1.0, min=0.01, max=16.0, step=0.01),
io.Int.Input("resolution_steps", default=1, min=1, max=256),
io.Int.Input("resolution_steps", default=1, min=1, max=256, advanced=True),
],
outputs=[
io.Image.Output(),

2
comfy_extras/nodes_qwen.py
View File

@ -116,7 +116,7 @@ class EmptyQwenImageLayeredLatentImage(io.ComfyNode):
inputs=[
io.Int.Input("width", default=640, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("height", default=640, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("layers", default=3, min=0, max=nodes.MAX_RESOLUTION, step=1),
io.Int.Input("layers", default=3, min=0, max=nodes.MAX_RESOLUTION, step=1, advanced=True),
io.Int.Input("batch_size", default=1, min=1, max=4096),
],
outputs=[

12
comfy_extras/nodes_rope.py
View File

@ -12,14 +12,14 @@ class ScaleROPE(io.ComfyNode):
is_experimental=True,
inputs=[
io.Model.Input("model"),
io.Float.Input("scale_x", default=1.0, min=0.0, max=100.0, step=0.1),
io.Float.Input("shift_x", default=0.0, min=-256.0, max=256.0, step=0.1),
io.Float.Input("scale_x", default=1.0, min=0.0, max=100.0, step=0.1, advanced=True),
io.Float.Input("shift_x", default=0.0, min=-256.0, max=256.0, step=0.1, advanced=True),
io.Float.Input("scale_y", default=1.0, min=0.0, max=100.0, step=0.1),
io.Float.Input("shift_y", default=0.0, min=-256.0, max=256.0, step=0.1),
io.Float.Input("scale_y", default=1.0, min=0.0, max=100.0, step=0.1, advanced=True),
io.Float.Input("shift_y", default=0.0, min=-256.0, max=256.0, step=0.1, advanced=True),
io.Float.Input("scale_t", default=1.0, min=0.0, max=100.0, step=0.1),
io.Float.Input("shift_t", default=0.0, min=-256.0, max=256.0, step=0.1),
io.Float.Input("scale_t", default=1.0, min=0.0, max=100.0, step=0.1, advanced=True),
io.Float.Input("shift_t", default=0.0, min=-256.0, max=256.0, step=0.1, advanced=True),
],

2
comfy_extras/nodes_sag.py
View File

@ -117,7 +117,7 @@ class SelfAttentionGuidance(io.ComfyNode):
inputs=[
io.Model.Input("model"),
io.Float.Input("scale", default=0.5, min=-2.0, max=5.0, step=0.01),
io.Float.Input("blur_sigma", default=2.0, min=0.0, max=10.0, step=0.1),
io.Float.Input("blur_sigma", default=2.0, min=0.0, max=10.0, step=0.1, advanced=True),
],
outputs=[
io.Model.Output(),

8
comfy_extras/nodes_sd3.py
View File

@ -72,7 +72,7 @@ class CLIPTextEncodeSD3(io.ComfyNode):
io.String.Input("clip_l", multiline=True, dynamic_prompts=True),
io.String.Input("clip_g", multiline=True, dynamic_prompts=True),
io.String.Input("t5xxl", multiline=True, dynamic_prompts=True),
io.Combo.Input("empty_padding", options=["none", "empty_prompt"]),
io.Combo.Input("empty_padding", options=["none", "empty_prompt"], advanced=True),
],
outputs=[
io.Conditioning.Output(),
@ -179,10 +179,10 @@ class SkipLayerGuidanceSD3(io.ComfyNode):
description="Generic version of SkipLayerGuidance node that can be used on every DiT model.",
inputs=[
io.Model.Input("model"),
io.String.Input("layers", default="7, 8, 9", multiline=False),
io.String.Input("layers", default="7, 8, 9", multiline=False, advanced=True),
io.Float.Input("scale", default=3.0, min=0.0, max=10.0, step=0.1),
io.Float.Input("start_percent", default=0.01, min=0.0, max=1.0, step=0.001),
io.Float.Input("end_percent", default=0.15, min=0.0, max=1.0, step=0.001),
io.Float.Input("start_percent", default=0.01, min=0.0, max=1.0, step=0.001, advanced=True),
io.Float.Input("end_percent", default=0.15, min=0.0, max=1.0, step=0.001, advanced=True),
],
outputs=[
io.Model.Output(),

2
comfy_extras/nodes_sdupscale.py
View File

@ -15,7 +15,7 @@ class SD_4XUpscale_Conditioning(io.ComfyNode):
io.Conditioning.Input("positive"),
io.Conditioning.Input("negative"),
io.Float.Input("scale_ratio", default=4.0, min=0.0, max=10.0, step=0.01),
io.Float.Input("noise_augmentation", default=0.0, min=0.0, max=1.0, step=0.001),
io.Float.Input("noise_augmentation", default=0.0, min=0.0, max=1.0, step=0.001, advanced=True),
],
outputs=[
io.Conditioning.Output(display_name="positive"),

16
comfy_extras/nodes_slg.py
View File

@ -21,11 +21,11 @@ class SkipLayerGuidanceDiT(io.ComfyNode):
is_experimental=True,
inputs=[
io.Model.Input("model"),
io.String.Input("double_layers", default="7, 8, 9"),
io.String.Input("single_layers", default="7, 8, 9"),
io.String.Input("double_layers", default="7, 8, 9", advanced=True),
io.String.Input("single_layers", default="7, 8, 9", advanced=True),
io.Float.Input("scale", default=3.0, min=0.0, max=10.0, step=0.1),
io.Float.Input("start_percent", default=0.01, min=0.0, max=1.0, step=0.001),
io.Float.Input("end_percent", default=0.15, min=0.0, max=1.0, step=0.001),
io.Float.Input("start_percent", default=0.01, min=0.0, max=1.0, step=0.001, advanced=True),
io.Float.Input("end_percent", default=0.15, min=0.0, max=1.0, step=0.001, advanced=True),
io.Float.Input("rescaling_scale", default=0.0, min=0.0, max=10.0, step=0.01),
],
outputs=[
@ -101,10 +101,10 @@ class SkipLayerGuidanceDiTSimple(io.ComfyNode):
is_experimental=True,
inputs=[
io.Model.Input("model"),
io.String.Input("double_layers", default="7, 8, 9"),
io.String.Input("single_layers", default="7, 8, 9"),
io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001),
io.Float.Input("end_percent", default=1.0, min=0.0, max=1.0, step=0.001),
io.String.Input("double_layers", default="7, 8, 9", advanced=True),
io.String.Input("single_layers", default="7, 8, 9", advanced=True),
io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001, advanced=True),
io.Float.Input("end_percent", default=1.0, min=0.0, max=1.0, step=0.001, advanced=True),
],
outputs=[
io.Model.Output(),

4
comfy_extras/nodes_stable3d.py
View File

@ -75,8 +75,8 @@ class StableZero123_Conditioning_Batched(io.ComfyNode):
io.Int.Input("batch_size", default=1, min=1, max=4096),
io.Float.Input("elevation", default=0.0, min=-180.0, max=180.0, step=0.1, round=False),
io.Float.Input("azimuth", default=0.0, min=-180.0, max=180.0, step=0.1, round=False),
io.Float.Input("elevation_batch_increment", default=0.0, min=-180.0, max=180.0, step=0.1, round=False),
io.Float.Input("azimuth_batch_increment", default=0.0, min=-180.0, max=180.0, step=0.1, round=False)
io.Float.Input("elevation_batch_increment", default=0.0, min=-180.0, max=180.0, step=0.1, round=False, advanced=True),
io.Float.Input("azimuth_batch_increment", default=0.0, min=-180.0, max=180.0, step=0.1, round=False, advanced=True)
],
outputs=[
io.Conditioning.Output(display_name="positive"),

4
comfy_extras/nodes_stable_cascade.py
View File

@ -33,7 +33,7 @@ class StableCascade_EmptyLatentImage(io.ComfyNode):
inputs=[
io.Int.Input("width", default=1024, min=256, max=nodes.MAX_RESOLUTION, step=8),
io.Int.Input("height", default=1024, min=256, max=nodes.MAX_RESOLUTION, step=8),
io.Int.Input("compression", default=42, min=4, max=128, step=1),
io.Int.Input("compression", default=42, min=4, max=128, step=1, advanced=True),
io.Int.Input("batch_size", default=1, min=1, max=4096),
],
outputs=[
@ -62,7 +62,7 @@ class StableCascade_StageC_VAEEncode(io.ComfyNode):
inputs=[
io.Image.Input("image"),
io.Vae.Input("vae"),
io.Int.Input("compression", default=42, min=4, max=128, step=1),
io.Int.Input("compression", default=42, min=4, max=128, step=1, advanced=True),
],
outputs=[
io.Latent.Output(display_name="stage_c"),

26
comfy_extras/nodes_string.py
View File

@ -169,7 +169,7 @@ class StringContains(io.ComfyNode):
inputs=[
io.String.Input("string", multiline=True),
io.String.Input("substring", multiline=True),
io.Boolean.Input("case_sensitive", default=True),
io.Boolean.Input("case_sensitive", default=True, advanced=True),
],
outputs=[
io.Boolean.Output(display_name="contains"),
@ -198,7 +198,7 @@ class StringCompare(io.ComfyNode):
io.String.Input("string_a", multiline=True),
io.String.Input("string_b", multiline=True),
io.Combo.Input("mode", options=["Starts With", "Ends With", "Equal"]),
io.Boolean.Input("case_sensitive", default=True),
io.Boolean.Input("case_sensitive", default=True, advanced=True),
],
outputs=[
io.Boolean.Output(),
@ -233,9 +233,9 @@ class RegexMatch(io.ComfyNode):
inputs=[
io.String.Input("string", multiline=True),
io.String.Input("regex_pattern", multiline=True),
io.Boolean.Input("case_insensitive", default=True),
io.Boolean.Input("multiline", default=False),
io.Boolean.Input("dotall", default=False),
io.Boolean.Input("case_insensitive", default=True, advanced=True),
io.Boolean.Input("multiline", default=False, advanced=True),
io.Boolean.Input("dotall", default=False, advanced=True),
],
outputs=[
io.Boolean.Output(display_name="matches"),
@ -275,10 +275,10 @@ class RegexExtract(io.ComfyNode):
io.String.Input("string", multiline=True),
io.String.Input("regex_pattern", multiline=True),
io.Combo.Input("mode", options=["First Match", "All Matches", "First Group", "All Groups"]),
io.Boolean.Input("case_insensitive", default=True),
io.Boolean.Input("multiline", default=False),
io.Boolean.Input("dotall", default=False),
io.Int.Input("group_index", default=1, min=0, max=100),
io.Boolean.Input("case_insensitive", default=True, advanced=True),
io.Boolean.Input("multiline", default=False, advanced=True),
io.Boolean.Input("dotall", default=False, advanced=True),
io.Int.Input("group_index", default=1, min=0, max=100, advanced=True),
],
outputs=[
io.String.Output(),
@ -351,10 +351,10 @@ class RegexReplace(io.ComfyNode):
io.String.Input("string", multiline=True),
io.String.Input("regex_pattern", multiline=True),
io.String.Input("replace", multiline=True),
io.Boolean.Input("case_insensitive", default=True, optional=True),
io.Boolean.Input("multiline", default=False, optional=True),
io.Boolean.Input("dotall", default=False, optional=True, tooltip="When enabled, the dot (.) character will match any character including newline characters. When disabled, dots won't match newlines."),
io.Int.Input("count", default=0, min=0, max=100, optional=True, tooltip="Maximum number of replacements to make. Set to 0 to replace all occurrences (default). Set to 1 to replace only the first match, 2 for the first two matches, etc."),
io.Boolean.Input("case_insensitive", default=True, optional=True, advanced=True),
io.Boolean.Input("multiline", default=False, optional=True, advanced=True),
io.Boolean.Input("dotall", default=False, optional=True, advanced=True, tooltip="When enabled, the dot (.) character will match any character including newline characters. When disabled, dots won't match newlines."),
io.Int.Input("count", default=0, min=0, max=100, optional=True, advanced=True, tooltip="Maximum number of replacements to make. Set to 0 to replace all occurrences (default). Set to 1 to replace only the first match, 2 for the first two matches, etc."),
],
outputs=[
io.String.Output(),

1
comfy_extras/nodes_torch_compile.py
View File

@ -16,6 +16,7 @@ class TorchCompileModel(io.ComfyNode):
io.Combo.Input(
"backend",
options=["inductor", "cudagraphs"],
advanced=True,
),
],
outputs=[io.Model.Output()],

7
comfy_extras/nodes_train.py
View File

@ -871,6 +871,7 @@ class TrainLoraNode(io.ComfyNode):
min=1,
max=1024,
tooltip="The number of gradient accumulation steps to use for training.",
advanced=True,
),
io.Int.Input(
"steps",
@ -899,6 +900,7 @@ class TrainLoraNode(io.ComfyNode):
options=["AdamW", "Adam", "SGD", "RMSprop"],
default="AdamW",
tooltip="The optimizer to use for training.",
advanced=True,
),
io.Combo.Input(
"loss_function",
@ -918,23 +920,27 @@ class TrainLoraNode(io.ComfyNode):
options=["bf16", "fp32"],
default="bf16",
tooltip="The dtype to use for training.",
advanced=True,
),
io.Combo.Input(
"lora_dtype",
options=["bf16", "fp32"],
default="bf16",
tooltip="The dtype to use for lora.",
advanced=True,
),
io.Combo.Input(
"algorithm",
options=list(adapter_maps.keys()),
default=list(adapter_maps.keys())[0],
tooltip="The algorithm to use for training.",
advanced=True,
),
io.Boolean.Input(
"gradient_checkpointing",
default=True,
tooltip="Use gradient checkpointing for training.",
advanced=True,
),
io.Combo.Input(
"existing_lora",
@ -951,6 +957,7 @@ class TrainLoraNode(io.ComfyNode):
"bypass_mode",
default=False,
tooltip="Enable bypass mode for training. When enabled, adapters are applied via forward hooks instead of weight modification. Useful for quantized models where weights cannot be directly modified.",
advanced=True,
),
],
outputs=[

8
comfy_extras/nodes_video.py
View File

@ -22,9 +22,9 @@ class SaveWEBM(io.ComfyNode):
inputs=[
io.Image.Input("images"),
io.String.Input("filename_prefix", default="ComfyUI"),
io.Combo.Input("codec", options=["vp9", "av1"]),
io.Combo.Input("codec", options=["vp9", "av1"], advanced=True),
io.Float.Input("fps", default=24.0, min=0.01, max=1000.0, step=0.01),
io.Float.Input("crf", default=32.0, min=0, max=63.0, step=1, tooltip="Higher crf means lower quality with a smaller file size, lower crf means higher quality higher filesize."),
io.Float.Input("crf", default=32.0, min=0, max=63.0, step=1, tooltip="Higher crf means lower quality with a smaller file size, lower crf means higher quality higher filesize.", advanced=True),
],
hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo],
is_output_node=True,
@ -77,8 +77,8 @@ class SaveVideo(io.ComfyNode):
inputs=[
io.Video.Input("video", tooltip="The video to save."),
io.String.Input("filename_prefix", default="video/ComfyUI", tooltip="The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes."),
io.Combo.Input("format", options=Types.VideoContainer.as_input(), default="auto", tooltip="The format to save the video as."),
io.Combo.Input("codec", options=Types.VideoCodec.as_input(), default="auto", tooltip="The codec to use for the video."),
io.Combo.Input("format", options=Types.VideoContainer.as_input(), default="auto", tooltip="The format to save the video as.", advanced=True),
io.Combo.Input("codec", options=Types.VideoCodec.as_input(), default="auto", tooltip="The codec to use for the video.", advanced=True),
],
hidden=[io.Hidden.prompt, io.Hidden.extra_pnginfo],
is_output_node=True,

8
comfy_extras/nodes_video_model.py
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@ -32,9 +32,9 @@ class SVD_img2vid_Conditioning:
"width": ("INT", {"default": 1024, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 8}),
"height": ("INT", {"default": 576, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 8}),
"video_frames": ("INT", {"default": 14, "min": 1, "max": 4096}),
"motion_bucket_id": ("INT", {"default": 127, "min": 1, "max": 1023}),
"motion_bucket_id": ("INT", {"default": 127, "min": 1, "max": 1023, "advanced": True}),
"fps": ("INT", {"default": 6, "min": 1, "max": 1024}),
"augmentation_level": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 10.0, "step": 0.01})
"augmentation_level": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 10.0, "step": 0.01, "advanced": True})
}}
RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "LATENT")
RETURN_NAMES = ("positive", "negative", "latent")
@ -60,7 +60,7 @@ class VideoLinearCFGGuidance:
@classmethod
def INPUT_TYPES(s):
return {"required": { "model": ("MODEL",),
"min_cfg": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step":0.5, "round": 0.01}),
"min_cfg": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step":0.5, "round": 0.01, "advanced": True}),
}}
RETURN_TYPES = ("MODEL",)
FUNCTION = "patch"
@ -84,7 +84,7 @@ class VideoTriangleCFGGuidance:
@classmethod
def INPUT_TYPES(s):
return {"required": { "model": ("MODEL",),
"min_cfg": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step":0.5, "round": 0.01}),
"min_cfg": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step":0.5, "round": 0.01, "advanced": True}),
}}
RETURN_TYPES = ("MODEL",)
FUNCTION = "patch"

6
comfy_extras/nodes_wan.py
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@ -717,8 +717,8 @@ class WanTrackToVideo(io.ComfyNode):
io.Int.Input("height", default=480, min=16, max=nodes.MAX_RESOLUTION, step=16),
io.Int.Input("length", default=81, min=1, max=nodes.MAX_RESOLUTION, step=4),
io.Int.Input("batch_size", default=1, min=1, max=4096),
io.Float.Input("temperature", default=220.0, min=1.0, max=1000.0, step=0.1),
io.Int.Input("topk", default=2, min=1, max=10),
io.Float.Input("temperature", default=220.0, min=1.0, max=1000.0, step=0.1, advanced=True),
io.Int.Input("topk", default=2, min=1, max=10, advanced=True),
io.Image.Input("start_image"),
io.ClipVisionOutput.Input("clip_vision_output", optional=True),
],
@ -1323,7 +1323,7 @@ class WanInfiniteTalkToVideo(io.ComfyNode):
io.ClipVisionOutput.Input("clip_vision_output", optional=True),
io.Image.Input("start_image", optional=True),
io.AudioEncoderOutput.Input("audio_encoder_output_1"),
io.Int.Input("motion_frame_count", default=9, min=1, max=33, step=1, tooltip="Number of previous frames to use as motion context."),
io.Int.Input("motion_frame_count", default=9, min=1, max=33, step=1, tooltip="Number of previous frames to use as motion context.", advanced=True),
io.Float.Input("audio_scale", default=1.0, min=-10.0, max=10.0, step=0.01),
io.Image.Input("previous_frames", optional=True),
],

4
comfy_extras/nodes_wanmove.py
View File

@ -252,9 +252,9 @@ class WanMoveVisualizeTracks(io.ComfyNode):
io.Image.Input("images"),
io.Tracks.Input("tracks", optional=True),
io.Int.Input("line_resolution", default=24, min=1, max=1024),
io.Int.Input("circle_size", default=12, min=1, max=128),
io.Int.Input("circle_size", default=12, min=1, max=128, advanced=True),
io.Float.Input("opacity", default=0.75, min=0.0, max=1.0, step=0.01),
io.Int.Input("line_width", default=16, min=1, max=128),
io.Int.Input("line_width", default=16, min=1, max=128, advanced=True),
],
outputs=[
io.Image.Output(),

4
comfy_extras/nodes_webcam.py
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@ -11,8 +11,8 @@ class WebcamCapture(nodes.LoadImage):
return {
"required": {
"image": ("WEBCAM", {}),
"width": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1}),
"height": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1}),
"width": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1, "advanced": True}),
"height": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 1, "advanced": True}),
"capture_on_queue": ("BOOLEAN", {"default": True}),
}
}

2
comfy_extras/nodes_zimage.py
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@ -16,7 +16,7 @@ class TextEncodeZImageOmni(io.ComfyNode):
io.Clip.Input("clip"),
io.ClipVision.Input("image_encoder", optional=True),
io.String.Input("prompt", multiline=True, dynamic_prompts=True),
io.Boolean.Input("auto_resize_images", default=True),
io.Boolean.Input("auto_resize_images", default=True, advanced=True),
io.Vae.Input("vae", optional=True),
io.Image.Input("image1", optional=True),
io.Image.Input("image2", optional=True),

28
nodes.py
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@ -320,10 +320,10 @@ class VAEDecodeTiled:
@classmethod
def INPUT_TYPES(s):
return {"required": {"samples": ("LATENT", ), "vae": ("VAE", ),
"tile_size": ("INT", {"default": 512, "min": 64, "max": 4096, "step": 32}),
"overlap": ("INT", {"default": 64, "min": 0, "max": 4096, "step": 32}),
"temporal_size": ("INT", {"default": 64, "min": 8, "max": 4096, "step": 4, "tooltip": "Only used for video VAEs: Amount of frames to decode at a time."}),
"temporal_overlap": ("INT", {"default": 8, "min": 4, "max": 4096, "step": 4, "tooltip": "Only used for video VAEs: Amount of frames to overlap."}),
"tile_size": ("INT", {"default": 512, "min": 64, "max": 4096, "step": 32, "advanced": True}),
"overlap": ("INT", {"default": 64, "min": 0, "max": 4096, "step": 32, "advanced": True}),
"temporal_size": ("INT", {"default": 64, "min": 8, "max": 4096, "step": 4, "tooltip": "Only used for video VAEs: Amount of frames to decode at a time.", "advanced": True}),
"temporal_overlap": ("INT", {"default": 8, "min": 4, "max": 4096, "step": 4, "tooltip": "Only used for video VAEs: Amount of frames to overlap.", "advanced": True}),
}}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "decode"
@ -367,10 +367,10 @@ class VAEEncodeTiled:
@classmethod
def INPUT_TYPES(s):
return {"required": {"pixels": ("IMAGE", ), "vae": ("VAE", ),
"tile_size": ("INT", {"default": 512, "min": 64, "max": 4096, "step": 64}),
"overlap": ("INT", {"default": 64, "min": 0, "max": 4096, "step": 32}),
"temporal_size": ("INT", {"default": 64, "min": 8, "max": 4096, "step": 4, "tooltip": "Only used for video VAEs: Amount of frames to encode at a time."}),
"temporal_overlap": ("INT", {"default": 8, "min": 4, "max": 4096, "step": 4, "tooltip": "Only used for video VAEs: Amount of frames to overlap."}),
"tile_size": ("INT", {"default": 512, "min": 64, "max": 4096, "step": 64, "advanced": True}),
"overlap": ("INT", {"default": 64, "min": 0, "max": 4096, "step": 32, "advanced": True}),
"temporal_size": ("INT", {"default": 64, "min": 8, "max": 4096, "step": 4, "tooltip": "Only used for video VAEs: Amount of frames to encode at a time.", "advanced": True}),
"temporal_overlap": ("INT", {"default": 8, "min": 4, "max": 4096, "step": 4, "tooltip": "Only used for video VAEs: Amount of frames to overlap.", "advanced": True}),
}}
RETURN_TYPES = ("LATENT",)
FUNCTION = "encode"
@ -654,7 +654,7 @@ class CLIPSetLastLayer:
@classmethod
def INPUT_TYPES(s):
return {"required": { "clip": ("CLIP", ),
"stop_at_clip_layer": ("INT", {"default": -1, "min": -24, "max": -1, "step": 1}),
"stop_at_clip_layer": ("INT", {"default": -1, "min": -24, "max": -1, "step": 1, "advanced": True}),
}}
RETURN_TYPES = ("CLIP",)
FUNCTION = "set_last_layer"
@ -1594,7 +1594,7 @@ class KSamplerAdvanced:
def INPUT_TYPES(s):
return {"required":
{"model": ("MODEL",),
"add_noise": (["enable", "disable"], ),
"add_noise": (["enable", "disable"], {"advanced": True}),
"noise_seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "control_after_generate": True}),
"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
"cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0, "step":0.1, "round": 0.01}),
@ -1603,9 +1603,9 @@ class KSamplerAdvanced:
"positive": ("CONDITIONING", ),
"negative": ("CONDITIONING", ),
"latent_image": ("LATENT", ),
"start_at_step": ("INT", {"default": 0, "min": 0, "max": 10000}),
"end_at_step": ("INT", {"default": 10000, "min": 0, "max": 10000}),
"return_with_leftover_noise": (["disable", "enable"], ),
"start_at_step": ("INT", {"default": 0, "min": 0, "max": 10000, "advanced": True}),
"end_at_step": ("INT", {"default": 10000, "min": 0, "max": 10000, "advanced": True}),
"return_with_leftover_noise": (["disable", "enable"], {"advanced": True}),
}
}
@ -1974,7 +1974,7 @@ class ImagePadForOutpaint:
"top": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 8}),
"right": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 8}),
"bottom": ("INT", {"default": 0, "min": 0, "max": MAX_RESOLUTION, "step": 8}),
"feathering": ("INT", {"default": 40, "min": 0, "max": MAX_RESOLUTION, "step": 1}),
"feathering": ("INT", {"default": 40, "min": 0, "max": MAX_RESOLUTION, "step": 1, "advanced": True}),
}
}