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pass "id" in Schema inputs as an arg instead of kwarg

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bigcat88 2025-07-24 22:03:50 +03:00
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commit f569823738
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17 changed files with 154 additions and 154 deletions
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22
comfy_extras/v3/nodes_audio.py
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@ -19,14 +19,14 @@ class ConditioningStableAudio(io.ComfyNode):
node_id="ConditioningStableAudio_V3", node_id="ConditioningStableAudio_V3",
category="conditioning", category="conditioning",
inputs=[ inputs=[
io.Conditioning.Input(id="positive"), io.Conditioning.Input("positive"),
io.Conditioning.Input(id="negative"), io.Conditioning.Input("negative"),
io.Float.Input(id="seconds_start", default=0.0, min=0.0, max=1000.0, step=0.1), io.Float.Input("seconds_start", default=0.0, min=0.0, max=1000.0, step=0.1),
io.Float.Input(id="seconds_total", default=47.0, min=0.0, max=1000.0, step=0.1), io.Float.Input("seconds_total", default=47.0, min=0.0, max=1000.0, step=0.1),
], ],
outputs=[ outputs=[
io.Conditioning.Output(id="positive_out", display_name="positive"), io.Conditioning.Output(display_name="positive"),
io.Conditioning.Output(id="negative_out", display_name="negative"), io.Conditioning.Output(display_name="negative"),
], ],
) )
@ -49,7 +49,7 @@ class EmptyLatentAudio(io.ComfyNode):
node_id="EmptyLatentAudio_V3", node_id="EmptyLatentAudio_V3",
category="latent/audio", category="latent/audio",
inputs=[ inputs=[
io.Float.Input(id="seconds", default=47.6, min=1.0, max=1000.0, step=0.1), io.Float.Input("seconds", default=47.6, min=1.0, max=1000.0, step=0.1),
io.Int.Input( io.Int.Input(
id="batch_size", default=1, min=1, max=4096, tooltip="The number of latent images in the batch." id="batch_size", default=1, min=1, max=4096, tooltip="The number of latent images in the batch."
), ),
@ -200,8 +200,8 @@ class VAEDecodeAudio(io.ComfyNode):
node_id="VAEDecodeAudio_V3", node_id="VAEDecodeAudio_V3",
category="latent/audio", category="latent/audio",
inputs=[ inputs=[
io.Latent.Input(id="samples"), io.Latent.Input("samples"),
io.Vae.Input(id="vae"), io.Vae.Input("vae"),
], ],
outputs=[io.Audio.Output()], outputs=[io.Audio.Output()],
) )
@ -222,8 +222,8 @@ class VAEEncodeAudio(io.ComfyNode):
node_id="VAEEncodeAudio_V3", node_id="VAEEncodeAudio_V3",
category="latent/audio", category="latent/audio",
inputs=[ inputs=[
io.Audio.Input(id="audio"), io.Audio.Input("audio"),
io.Vae.Input(id="vae"), io.Vae.Input("vae"),
], ],
outputs=[io.Latent.Output()], outputs=[io.Latent.Output()],
) )

2
comfy_extras/v3/nodes_differential_diffusion.py
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@ -13,7 +13,7 @@ class DifferentialDiffusion(io.ComfyNode):
display_name="Differential Diffusion _V3", display_name="Differential Diffusion _V3",
category="_for_testing", category="_for_testing",
inputs=[ inputs=[
io.Model.Input(id="model"), io.Model.Input("model"),
], ],
outputs=[ outputs=[
io.Model.Output(), io.Model.Output(),

16
comfy_extras/v3/nodes_flux.py
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@ -32,10 +32,10 @@ class CLIPTextEncodeFlux(io.ComfyNode):
node_id="CLIPTextEncodeFlux_V3", node_id="CLIPTextEncodeFlux_V3",
category="advanced/conditioning/flux", category="advanced/conditioning/flux",
inputs=[ inputs=[
io.Clip.Input(id="clip"), io.Clip.Input("clip"),
io.String.Input(id="clip_l", multiline=True, dynamic_prompts=True), io.String.Input("clip_l", multiline=True, dynamic_prompts=True),
io.String.Input(id="t5xxl", multiline=True, dynamic_prompts=True), io.String.Input("t5xxl", multiline=True, dynamic_prompts=True),
io.Float.Input(id="guidance", default=3.5, min=0.0, max=100.0, step=0.1), io.Float.Input("guidance", default=3.5, min=0.0, max=100.0, step=0.1),
], ],
outputs=[ outputs=[
io.Conditioning.Output(), io.Conditioning.Output(),
@ -58,7 +58,7 @@ class FluxDisableGuidance(io.ComfyNode):
category="advanced/conditioning/flux", category="advanced/conditioning/flux",
description="This node completely disables the guidance embed on Flux and Flux like models", description="This node completely disables the guidance embed on Flux and Flux like models",
inputs=[ inputs=[
io.Conditioning.Input(id="conditioning"), io.Conditioning.Input("conditioning"),
], ],
outputs=[ outputs=[
io.Conditioning.Output(), io.Conditioning.Output(),
@ -78,8 +78,8 @@ class FluxGuidance(io.ComfyNode):
node_id="FluxGuidance_V3", node_id="FluxGuidance_V3",
category="advanced/conditioning/flux", category="advanced/conditioning/flux",
inputs=[ inputs=[
io.Conditioning.Input(id="conditioning"), io.Conditioning.Input("conditioning"),
io.Float.Input(id="guidance", default=3.5, min=0.0, max=100.0, step=0.1), io.Float.Input("guidance", default=3.5, min=0.0, max=100.0, step=0.1),
], ],
outputs=[ outputs=[
io.Conditioning.Output(), io.Conditioning.Output(),
@ -100,7 +100,7 @@ class FluxKontextImageScale(io.ComfyNode):
category="advanced/conditioning/flux", category="advanced/conditioning/flux",
description="This node resizes the image to one that is more optimal for flux kontext.", description="This node resizes the image to one that is more optimal for flux kontext.",
inputs=[ inputs=[
io.Image.Input(id="image"), io.Image.Input("image"),
], ],
outputs=[ outputs=[
io.Image.Output(), io.Image.Output(),

20
comfy_extras/v3/nodes_freelunch.py
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@ -35,11 +35,11 @@ class FreeU(io.ComfyNode):
node_id="FreeU_V3", node_id="FreeU_V3",
category="model_patches/unet", category="model_patches/unet",
inputs=[ inputs=[
io.Model.Input(id="model"), io.Model.Input("model"),
io.Float.Input(id="b1", default=1.1, 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),
io.Float.Input(id="b2", default=1.2, 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(id="s1", default=0.9, 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(id="s2", default=0.2, 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),
], ],
outputs=[ outputs=[
io.Model.Output(), io.Model.Output(),
@ -80,11 +80,11 @@ class FreeU_V2(io.ComfyNode):
node_id="FreeU_V2_V3", node_id="FreeU_V2_V3",
category="model_patches/unet", category="model_patches/unet",
inputs=[ inputs=[
io.Model.Input(id="model"), io.Model.Input("model"),
io.Float.Input(id="b1", default=1.3, 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),
io.Float.Input(id="b2", default=1.4, 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(id="s1", default=0.9, 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(id="s2", default=0.2, 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),
], ],
outputs=[ outputs=[
io.Model.Output(), io.Model.Output(),

8
comfy_extras/v3/nodes_fresca.py
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@ -65,12 +65,12 @@ class FreSca(io.ComfyNode):
category="_for_testing", category="_for_testing",
description="Applies frequency-dependent scaling to the guidance", description="Applies frequency-dependent scaling to the guidance",
inputs=[ inputs=[
io.Model.Input(id="model"), io.Model.Input("model"),
io.Float.Input(id="scale_low", default=1.0, min=0, max=10, step=0.01, 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"),
io.Float.Input(id="scale_high", default=1.25, min=0, max=10, step=0.01, 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"),
io.Int.Input(id="freq_cutoff", default=20, min=1, max=10000, step=1, 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"),
], ],
outputs=[ outputs=[

6
comfy_extras/v3/nodes_gits.py
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@ -343,9 +343,9 @@ class GITSScheduler(io.ComfyNode):
node_id="GITSScheduler_V3", node_id="GITSScheduler_V3",
category="sampling/custom_sampling/schedulers", category="sampling/custom_sampling/schedulers",
inputs=[ inputs=[
io.Float.Input(id="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),
io.Int.Input(id="steps", default=10, min=2, max=1000), io.Int.Input("steps", default=10, min=2, max=1000),
io.Float.Input(id="denoise", default=1.0, min=0.0, max=1.0, step=0.01), io.Float.Input("denoise", default=1.0, min=0.0, max=1.0, step=0.01),
], ],
outputs=[ outputs=[
io.Sigmas.Output(), io.Sigmas.Output(),

10
comfy_extras/v3/nodes_hypertile.py
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@ -33,11 +33,11 @@ class HyperTile(io.ComfyNode):
node_id="HyperTile_V3", node_id="HyperTile_V3",
category="model_patches/unet", category="model_patches/unet",
inputs=[ inputs=[
io.Model.Input(id="model"), io.Model.Input("model"),
io.Int.Input(id="tile_size", default=256, min=1, max=2048), io.Int.Input("tile_size", default=256, min=1, max=2048),
io.Int.Input(id="swap_size", default=2, min=1, max=128), io.Int.Input("swap_size", default=2, min=1, max=128),
io.Int.Input(id="max_depth", default=0, min=0, max=10), io.Int.Input("max_depth", default=0, min=0, max=10),
io.Boolean.Input(id="scale_depth", default=False), io.Boolean.Input("scale_depth", default=False),
], ],
outputs=[ outputs=[
io.Model.Output(), io.Model.Output(),

8
comfy_extras/v3/nodes_ip2p.py
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@ -12,10 +12,10 @@ class InstructPixToPixConditioning(io.ComfyNode):
node_id="InstructPixToPixConditioning_V3", node_id="InstructPixToPixConditioning_V3",
category="conditioning/instructpix2pix", category="conditioning/instructpix2pix",
inputs=[ inputs=[
io.Conditioning.Input(id="positive"), io.Conditioning.Input("positive"),
io.Conditioning.Input(id="negative"), io.Conditioning.Input("negative"),
io.Vae.Input(id="vae"), io.Vae.Input("vae"),
io.Image.Input(id="pixels"), io.Image.Input("pixels"),
], ],
outputs=[ outputs=[
io.Conditioning.Output(display_name="positive"), io.Conditioning.Output(display_name="positive"),

42
comfy_extras/v3/nodes_latent.py
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@ -24,8 +24,8 @@ class LatentAdd(io.ComfyNode):
node_id="LatentAdd_V3", node_id="LatentAdd_V3",
category="latent/advanced", category="latent/advanced",
inputs=[ inputs=[
io.Latent.Input(id="samples1"), io.Latent.Input("samples1"),
io.Latent.Input(id="samples2"), io.Latent.Input("samples2"),
], ],
outputs=[ outputs=[
io.Latent.Output(), io.Latent.Output(),
@ -52,8 +52,8 @@ class LatentApplyOperation(io.ComfyNode):
category="latent/advanced/operations", category="latent/advanced/operations",
is_experimental=True, is_experimental=True,
inputs=[ inputs=[
io.Latent.Input(id="samples"), io.Latent.Input("samples"),
io.LatentOperation.Input(id="operation"), io.LatentOperation.Input("operation"),
], ],
outputs=[ outputs=[
io.Latent.Output(), io.Latent.Output(),
@ -77,8 +77,8 @@ class LatentApplyOperationCFG(io.ComfyNode):
category="latent/advanced/operations", category="latent/advanced/operations",
is_experimental=True, is_experimental=True,
inputs=[ inputs=[
io.Model.Input(id="model"), io.Model.Input("model"),
io.LatentOperation.Input(id="operation"), io.LatentOperation.Input("operation"),
], ],
outputs=[ outputs=[
io.Model.Output(), io.Model.Output(),
@ -108,8 +108,8 @@ class LatentBatch(io.ComfyNode):
node_id="LatentBatch_V3", node_id="LatentBatch_V3",
category="latent/batch", category="latent/batch",
inputs=[ inputs=[
io.Latent.Input(id="samples1"), io.Latent.Input("samples1"),
io.Latent.Input(id="samples2"), io.Latent.Input("samples2"),
], ],
outputs=[ outputs=[
io.Latent.Output(), io.Latent.Output(),
@ -137,8 +137,8 @@ class LatentBatchSeedBehavior(io.ComfyNode):
node_id="LatentBatchSeedBehavior_V3", node_id="LatentBatchSeedBehavior_V3",
category="latent/advanced", category="latent/advanced",
inputs=[ inputs=[
io.Latent.Input(id="samples"), io.Latent.Input("samples"),
io.Combo.Input(id="seed_behavior", options=["random", "fixed"], default="fixed"), io.Combo.Input("seed_behavior", options=["random", "fixed"], default="fixed"),
], ],
outputs=[ outputs=[
io.Latent.Output(), io.Latent.Output(),
@ -166,9 +166,9 @@ class LatentInterpolate(io.ComfyNode):
node_id="LatentInterpolate_V3", node_id="LatentInterpolate_V3",
category="latent/advanced", category="latent/advanced",
inputs=[ inputs=[
io.Latent.Input(id="samples1"), io.Latent.Input("samples1"),
io.Latent.Input(id="samples2"), io.Latent.Input("samples2"),
io.Float.Input(id="ratio", default=1.0, min=0.0, max=1.0, step=0.01), io.Float.Input("ratio", default=1.0, min=0.0, max=1.0, step=0.01),
], ],
outputs=[ outputs=[
io.Latent.Output(), io.Latent.Output(),
@ -205,8 +205,8 @@ class LatentMultiply(io.ComfyNode):
node_id="LatentMultiply_V3", node_id="LatentMultiply_V3",
category="latent/advanced", category="latent/advanced",
inputs=[ inputs=[
io.Latent.Input(id="samples"), io.Latent.Input("samples"),
io.Float.Input(id="multiplier", default=1.0, min=-10.0, max=10.0, step=0.01), io.Float.Input("multiplier", default=1.0, min=-10.0, max=10.0, step=0.01),
], ],
outputs=[ outputs=[
io.Latent.Output(), io.Latent.Output(),
@ -230,9 +230,9 @@ class LatentOperationSharpen(io.ComfyNode):
category="latent/advanced/operations", category="latent/advanced/operations",
is_experimental=True, is_experimental=True,
inputs=[ inputs=[
io.Int.Input(id="sharpen_radius", default=9, min=1, max=31, step=1), io.Int.Input("sharpen_radius", default=9, min=1, max=31, step=1),
io.Float.Input(id="sigma", default=1.0, min=0.1, max=10.0, step=0.1), io.Float.Input("sigma", default=1.0, min=0.1, max=10.0, step=0.1),
io.Float.Input(id="alpha", default=0.1, min=0.0, max=5.0, step=0.01), io.Float.Input("alpha", default=0.1, min=0.0, max=5.0, step=0.01),
], ],
outputs=[ outputs=[
io.LatentOperation.Output(), io.LatentOperation.Output(),
@ -272,7 +272,7 @@ class LatentOperationTonemapReinhard(io.ComfyNode):
category="latent/advanced/operations", category="latent/advanced/operations",
is_experimental=True, is_experimental=True,
inputs=[ inputs=[
io.Float.Input(id="multiplier", default=1.0, min=0.0, max=100.0, step=0.01), io.Float.Input("multiplier", default=1.0, min=0.0, max=100.0, step=0.01),
], ],
outputs=[ outputs=[
io.LatentOperation.Output(), io.LatentOperation.Output(),
@ -306,8 +306,8 @@ class LatentSubtract(io.ComfyNode):
node_id="LatentSubtract_V3", node_id="LatentSubtract_V3",
category="latent/advanced", category="latent/advanced",
inputs=[ inputs=[
io.Latent.Input(id="samples1"), io.Latent.Input("samples1"),
io.Latent.Input(id="samples2"), io.Latent.Input("samples2"),
], ],
outputs=[ outputs=[
io.Latent.Output(), io.Latent.Output(),

24
comfy_extras/v3/nodes_load_3d.py
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@ -35,10 +35,10 @@ class Load3D(io.ComfyNode):
category="3d", category="3d",
is_experimental=True, is_experimental=True,
inputs=[ inputs=[
io.Combo.Input(id="model_file", options=sorted(files), upload=io.UploadType.model), io.Combo.Input("model_file", options=sorted(files), upload=io.UploadType.model),
io.Load3D.Input(id="image"), io.Load3D.Input("image"),
io.Int.Input(id="width", default=1024, min=1, max=4096, step=1), io.Int.Input("width", default=1024, min=1, max=4096, step=1),
io.Int.Input(id="height", default=1024, min=1, max=4096, step=1), io.Int.Input("height", default=1024, min=1, max=4096, step=1),
], ],
outputs=[ outputs=[
io.Image.Output(display_name="image"), io.Image.Output(display_name="image"),
@ -96,10 +96,10 @@ class Load3DAnimation(io.ComfyNode):
category="3d", category="3d",
is_experimental=True, is_experimental=True,
inputs=[ inputs=[
io.Combo.Input(id="model_file", options=sorted(files), upload=io.UploadType.model), io.Combo.Input("model_file", options=sorted(files), upload=io.UploadType.model),
io.Load3DAnimation.Input(id="image"), io.Load3DAnimation.Input("image"),
io.Int.Input(id="width", default=1024, min=1, max=4096, step=1), io.Int.Input("width", default=1024, min=1, max=4096, step=1),
io.Int.Input(id="height", default=1024, min=1, max=4096, step=1), io.Int.Input("height", default=1024, min=1, max=4096, step=1),
], ],
outputs=[ outputs=[
io.Image.Output(display_name="image"), io.Image.Output(display_name="image"),
@ -140,8 +140,8 @@ class Preview3D(io.ComfyNode):
is_experimental=True, is_experimental=True,
is_output_node=True, is_output_node=True,
inputs=[ inputs=[
io.String.Input(id="model_file", default="", multiline=False), io.String.Input("model_file", default="", multiline=False),
io.Load3DCamera.Input(id="camera_info", optional=True), io.Load3DCamera.Input("camera_info", optional=True),
], ],
outputs=[], outputs=[],
) )
@ -161,8 +161,8 @@ class Preview3DAnimation(io.ComfyNode):
is_experimental=True, is_experimental=True,
is_output_node=True, is_output_node=True,
inputs=[ inputs=[
io.String.Input(id="model_file", default="", multiline=False), io.String.Input("model_file", default="", multiline=False),
io.Load3DCamera.Input(id="camera_info", optional=True), io.Load3DCamera.Input("camera_info", optional=True),
], ],
outputs=[], outputs=[],
) )

8
comfy_extras/v3/nodes_lora_extract.py
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@ -91,10 +91,10 @@ class LoraSave(io.ComfyNode):
category="_for_testing", category="_for_testing",
is_output_node=True, is_output_node=True,
inputs=[ inputs=[
io.String.Input(id="filename_prefix", default="loras/ComfyUI_extracted_lora"), io.String.Input("filename_prefix", default="loras/ComfyUI_extracted_lora"),
io.Int.Input(id="rank", default=8, min=1, max=4096, step=1), io.Int.Input("rank", default=8, min=1, max=4096, step=1),
io.Combo.Input(id="lora_type", options=list(LORA_TYPES.keys())), io.Combo.Input("lora_type", options=list(LORA_TYPES.keys())),
io.Boolean.Input(id="bias_diff", default=True), io.Boolean.Input("bias_diff", default=True),
io.Model.Input( io.Model.Input(
id="model_diff", optional=True, tooltip="The ModelSubtract output to be converted to a lora." id="model_diff", optional=True, tooltip="The ModelSubtract output to be converted to a lora."
), ),

88
comfy_extras/v3/nodes_lt.py
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@ -93,10 +93,10 @@ class EmptyLTXVLatentVideo(io.ComfyNode):
node_id="EmptyLTXVLatentVideo_V3", node_id="EmptyLTXVLatentVideo_V3",
category="latent/video/ltxv", category="latent/video/ltxv",
inputs=[ inputs=[
io.Int.Input(id="width", default=768, min=64, max=nodes.MAX_RESOLUTION, step=32), io.Int.Input("width", default=768, min=64, max=nodes.MAX_RESOLUTION, step=32),
io.Int.Input(id="height", default=512, min=64, max=nodes.MAX_RESOLUTION, step=32), io.Int.Input("height", default=512, min=64, max=nodes.MAX_RESOLUTION, step=32),
io.Int.Input(id="length", default=97, min=1, max=nodes.MAX_RESOLUTION, step=8), io.Int.Input("length", default=97, min=1, max=nodes.MAX_RESOLUTION, step=8),
io.Int.Input(id="batch_size", default=1, min=1, max=4096), io.Int.Input("batch_size", default=1, min=1, max=4096),
], ],
outputs=[ outputs=[
io.Latent.Output(), io.Latent.Output(),
@ -122,10 +122,10 @@ class LTXVAddGuide(io.ComfyNode):
node_id="LTXVAddGuide_V3", node_id="LTXVAddGuide_V3",
category="conditioning/video_models", category="conditioning/video_models",
inputs=[ inputs=[
io.Conditioning.Input(id="positive"), io.Conditioning.Input("positive"),
io.Conditioning.Input(id="negative"), io.Conditioning.Input("negative"),
io.Vae.Input(id="vae"), io.Vae.Input("vae"),
io.Latent.Input(id="latent"), io.Latent.Input("latent"),
io.Image.Input( io.Image.Input(
id="image", id="image",
tooltip="Image or video to condition the latent video on. Must be 8*n + 1 frames. " tooltip="Image or video to condition the latent video on. Must be 8*n + 1 frames. "
@ -141,12 +141,12 @@ class LTXVAddGuide(io.ComfyNode):
"For videos with 9+ frames, frame_idx must be divisible by 8, otherwise it will be rounded " "For videos with 9+ frames, frame_idx must be divisible by 8, otherwise it will be rounded "
"down to the nearest multiple of 8. Negative values are counted from the end of the video.", "down to the nearest multiple of 8. Negative values are counted from the end of the video.",
), ),
io.Float.Input(id="strength", default=1.0, min=0.0, max=1.0, step=0.01), io.Float.Input("strength", default=1.0, min=0.0, max=1.0, step=0.01),
], ],
outputs=[ outputs=[
io.Conditioning.Output(id="positive_out", display_name="positive"), io.Conditioning.Output(display_name="positive"),
io.Conditioning.Output(id="negative_out", display_name="negative"), io.Conditioning.Output(display_name="negative"),
io.Latent.Output(id="latent_out", display_name="latent"), io.Latent.Output(display_name="latent"),
], ],
) )
@ -282,13 +282,13 @@ class LTXVConditioning(io.ComfyNode):
node_id="LTXVConditioning_V3", node_id="LTXVConditioning_V3",
category="conditioning/video_models", category="conditioning/video_models",
inputs=[ inputs=[
io.Conditioning.Input(id="positive"), io.Conditioning.Input("positive"),
io.Conditioning.Input(id="negative"), io.Conditioning.Input("negative"),
io.Float.Input(id="frame_rate", default=25.0, min=0.0, max=1000.0, step=0.01), io.Float.Input("frame_rate", default=25.0, min=0.0, max=1000.0, step=0.01),
], ],
outputs=[ outputs=[
io.Conditioning.Output(id="positive_out", display_name="positive"), io.Conditioning.Output(display_name="positive"),
io.Conditioning.Output(id="negative_out", display_name="negative"), io.Conditioning.Output(display_name="negative"),
], ],
) )
@ -306,14 +306,14 @@ class LTXVCropGuides(io.ComfyNode):
node_id="LTXVCropGuides_V3", node_id="LTXVCropGuides_V3",
category="conditioning/video_models", category="conditioning/video_models",
inputs=[ inputs=[
io.Conditioning.Input(id="positive"), io.Conditioning.Input("positive"),
io.Conditioning.Input(id="negative"), io.Conditioning.Input("negative"),
io.Latent.Input(id="latent"), io.Latent.Input("latent"),
], ],
outputs=[ outputs=[
io.Conditioning.Output(id="positive_out", display_name="positive"), io.Conditioning.Output(display_name="positive"),
io.Conditioning.Output(id="negative_out", display_name="negative"), io.Conditioning.Output(display_name="negative"),
io.Latent.Output(id="latent_out", display_name="latent"), io.Latent.Output(display_name="latent"),
], ],
) )
@ -342,19 +342,19 @@ class LTXVImgToVideo(io.ComfyNode):
node_id="LTXVImgToVideo_V3", node_id="LTXVImgToVideo_V3",
category="conditioning/video_models", category="conditioning/video_models",
inputs=[ inputs=[
io.Conditioning.Input(id="positive"), io.Conditioning.Input("positive"),
io.Conditioning.Input(id="negative"), io.Conditioning.Input("negative"),
io.Vae.Input(id="vae"), io.Vae.Input("vae"),
io.Image.Input(id="image"), io.Image.Input("image"),
io.Int.Input(id="width", default=768, min=64, max=nodes.MAX_RESOLUTION, step=32), io.Int.Input("width", default=768, min=64, max=nodes.MAX_RESOLUTION, step=32),
io.Int.Input(id="height", default=512, min=64, max=nodes.MAX_RESOLUTION, step=32), io.Int.Input("height", default=512, min=64, max=nodes.MAX_RESOLUTION, step=32),
io.Int.Input(id="length", default=97, min=9, max=nodes.MAX_RESOLUTION, step=8), io.Int.Input("length", default=97, min=9, max=nodes.MAX_RESOLUTION, step=8),
io.Int.Input(id="batch_size", default=1, min=1, max=4096), io.Int.Input("batch_size", default=1, min=1, max=4096),
io.Float.Input(id="strength", default=1.0, min=0.0, max=1.0), io.Float.Input("strength", default=1.0, min=0.0, max=1.0),
], ],
outputs=[ outputs=[
io.Conditioning.Output(id="positive_out", display_name="positive"), io.Conditioning.Output(display_name="positive"),
io.Conditioning.Output(id="negative_out", display_name="negative"), io.Conditioning.Output(display_name="negative"),
io.Latent.Output(display_name="latent"), io.Latent.Output(display_name="latent"),
], ],
) )
@ -390,13 +390,13 @@ class LTXVPreprocess(io.ComfyNode):
node_id="LTXVPreprocess_V3", node_id="LTXVPreprocess_V3",
category="image", category="image",
inputs=[ inputs=[
io.Image.Input(id="image"), io.Image.Input("image"),
io.Int.Input( io.Int.Input(
id="img_compression", default=35, min=0, max=100, tooltip="Amount of compression to apply on image." id="img_compression", default=35, min=0, max=100, tooltip="Amount of compression to apply on image."
), ),
], ],
outputs=[ outputs=[
io.Image.Output(id="output_image", display_name="output_image"), io.Image.Output(display_name="output_image"),
], ],
) )
@ -415,9 +415,9 @@ class LTXVScheduler(io.ComfyNode):
node_id="LTXVScheduler_V3", node_id="LTXVScheduler_V3",
category="sampling/custom_sampling/schedulers", category="sampling/custom_sampling/schedulers",
inputs=[ inputs=[
io.Int.Input(id="steps", default=20, min=1, max=10000), io.Int.Input("steps", default=20, min=1, max=10000),
io.Float.Input(id="max_shift", default=2.05, min=0.0, max=100.0, step=0.01), io.Float.Input("max_shift", default=2.05, min=0.0, max=100.0, step=0.01),
io.Float.Input(id="base_shift", default=0.95, min=0.0, max=100.0, step=0.01), io.Float.Input("base_shift", default=0.95, min=0.0, max=100.0, step=0.01),
io.Boolean.Input( io.Boolean.Input(
id="stretch", id="stretch",
default=True, default=True,
@ -431,7 +431,7 @@ class LTXVScheduler(io.ComfyNode):
step=0.01, step=0.01,
tooltip="The terminal value of the sigmas after stretching.", tooltip="The terminal value of the sigmas after stretching.",
), ),
io.Latent.Input(id="latent", optional=True), io.Latent.Input("latent", optional=True),
], ],
outputs=[ outputs=[
io.Sigmas.Output(), io.Sigmas.Output(),
@ -478,10 +478,10 @@ class ModelSamplingLTXV(io.ComfyNode):
node_id="ModelSamplingLTXV_V3", node_id="ModelSamplingLTXV_V3",
category="advanced/model", category="advanced/model",
inputs=[ inputs=[
io.Model.Input(id="model"), io.Model.Input("model"),
io.Float.Input(id="max_shift", default=2.05, min=0.0, max=100.0, step=0.01), io.Float.Input("max_shift", default=2.05, min=0.0, max=100.0, step=0.01),
io.Float.Input(id="base_shift", default=0.95, min=0.0, max=100.0, step=0.01), io.Float.Input("base_shift", default=0.95, min=0.0, max=100.0, step=0.01),
io.Latent.Input(id="latent", optional=True), io.Latent.Input("latent", optional=True),
], ],
outputs=[ outputs=[
io.Model.Output(), io.Model.Output(),

12
comfy_extras/v3/nodes_lumina2.py
View File

@ -27,9 +27,9 @@ class CLIPTextEncodeLumina2(io.ComfyNode):
description="Encodes a system prompt and a user prompt using a CLIP model into an embedding " description="Encodes a system prompt and a user prompt using a CLIP model into an embedding "
"that can be used to guide the diffusion model towards generating specific images.", "that can be used to guide the diffusion model towards generating specific images.",
inputs=[ inputs=[
io.Combo.Input(id="system_prompt", options=list(cls.SYSTEM_PROMPT.keys()), tooltip=cls.SYSTEM_PROMPT_TIP), io.Combo.Input("system_prompt", options=list(cls.SYSTEM_PROMPT.keys()), tooltip=cls.SYSTEM_PROMPT_TIP),
io.String.Input(id="user_prompt", multiline=True, dynamic_prompts=True, tooltip="The text to be encoded."), io.String.Input("user_prompt", multiline=True, dynamic_prompts=True, tooltip="The text to be encoded."),
io.Clip.Input(id="clip", tooltip="The CLIP model used for encoding the text."), io.Clip.Input("clip", tooltip="The CLIP model used for encoding the text."),
], ],
outputs=[ outputs=[
io.Conditioning.Output(tooltip="A conditioning containing the embedded text used to guide the diffusion model."), io.Conditioning.Output(tooltip="A conditioning containing the embedded text used to guide the diffusion model."),
@ -56,9 +56,9 @@ class RenormCFG(io.ComfyNode):
node_id="RenormCFG_V3", node_id="RenormCFG_V3",
category="advanced/model", category="advanced/model",
inputs=[ inputs=[
io.Model.Input(id="model"), io.Model.Input("model"),
io.Float.Input(id="cfg_trunc", default=100, 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),
io.Float.Input(id="renorm_cfg", default=1.0, 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),
], ],
outputs=[ outputs=[
io.Model.Output(), io.Model.Output(),

20
comfy_extras/v3/nodes_morphology.py
View File

@ -23,12 +23,12 @@ class ImageRGBToYUV(io.ComfyNode):
node_id="ImageRGBToYUV_V3", node_id="ImageRGBToYUV_V3",
category="image/batch", category="image/batch",
inputs=[ inputs=[
io.Image.Input(id="image"), io.Image.Input("image"),
], ],
outputs=[ outputs=[
io.Image.Output(id="Y", display_name="Y"), io.Image.Output(display_name="Y"),
io.Image.Output(id="U", display_name="U"), io.Image.Output(display_name="U"),
io.Image.Output(id="V", display_name="V"), io.Image.Output(display_name="V"),
], ],
) )
@ -45,9 +45,9 @@ class ImageYUVToRGB(io.ComfyNode):
node_id="ImageYUVToRGB_V3", node_id="ImageYUVToRGB_V3",
category="image/batch", category="image/batch",
inputs=[ inputs=[
io.Image.Input(id="Y"), io.Image.Input("Y"),
io.Image.Input(id="U"), io.Image.Input("U"),
io.Image.Input(id="V"), io.Image.Input("V"),
], ],
outputs=[ outputs=[
io.Image.Output(), io.Image.Output(),
@ -68,9 +68,9 @@ class Morphology(io.ComfyNode):
display_name="ImageMorphology _V3", display_name="ImageMorphology _V3",
category="image/postprocessing", category="image/postprocessing",
inputs=[ inputs=[
io.Image.Input(id="image"), io.Image.Input("image"),
io.Combo.Input(id="operation", options=["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"]), io.Combo.Input("operation", options=["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"]),
io.Int.Input(id="kernel_size", default=3, min=3, max=999, step=1), io.Int.Input("kernel_size", default=3, min=3, max=999, step=1),
], ],
outputs=[ outputs=[
io.Image.Output(), io.Image.Output(),

6
comfy_extras/v3/nodes_optimalsteps.py
View File

@ -33,9 +33,9 @@ class OptimalStepsScheduler(io.ComfyNode):
node_id="OptimalStepsScheduler_V3", node_id="OptimalStepsScheduler_V3",
category="sampling/custom_sampling/schedulers", category="sampling/custom_sampling/schedulers",
inputs=[ inputs=[
io.Combo.Input(id="model_type", options=["FLUX", "Wan", "Chroma"]), io.Combo.Input("model_type", options=["FLUX", "Wan", "Chroma"]),
io.Int.Input(id="steps", default=20, min=3, max=1000), io.Int.Input("steps", default=20, min=3, max=1000),
io.Float.Input(id="denoise", default=1.0, min=0.0, max=1.0, step=0.01), io.Float.Input("denoise", default=1.0, min=0.0, max=1.0, step=0.01),
], ],
outputs=[ outputs=[
io.Sigmas.Output(), io.Sigmas.Output(),

4
comfy_extras/v3/nodes_pag.py
View File

@ -17,8 +17,8 @@ class PerturbedAttentionGuidance(io.ComfyNode):
node_id="PerturbedAttentionGuidance_V3", node_id="PerturbedAttentionGuidance_V3",
category="model_patches/unet", category="model_patches/unet",
inputs=[ inputs=[
io.Model.Input(id="model"), io.Model.Input("model"),
io.Float.Input(id="scale", default=3.0, min=0.0, max=100.0, step=0.01, round=0.01), io.Float.Input("scale", default=3.0, min=0.0, max=100.0, step=0.01, round=0.01),
], ],
outputs=[ outputs=[
io.Model.Output(), io.Model.Output(),

12
comfy_extras/v3/nodes_perpneg.py
View File

@ -88,12 +88,12 @@ class PerpNegGuider(io.ComfyNode):
node_id="PerpNegGuider_V3", node_id="PerpNegGuider_V3",
category="_for_testing", category="_for_testing",
inputs=[ inputs=[
io.Model.Input(id="model"), io.Model.Input("model"),
io.Conditioning.Input(id="positive"), io.Conditioning.Input("positive"),
io.Conditioning.Input(id="negative"), io.Conditioning.Input("negative"),
io.Conditioning.Input(id="empty_conditioning"), io.Conditioning.Input("empty_conditioning"),
io.Float.Input(id="cfg", default=8.0, min=0.0, max=100.0, step=0.1, round=0.01), io.Float.Input("cfg", default=8.0, min=0.0, max=100.0, step=0.1, round=0.01),
io.Float.Input(id="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),
], ],
outputs=[ outputs=[
io.Guider.Output(), io.Guider.Output(),