mirror of
https://github.com/comfyanonymous/ComfyUI.git
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bbb8864778
* feat: Add search_aliases field to node schema
Adds `search_aliases` field to improve node discoverability. Users can define alternative search terms for nodes (e.g., "text concat" → StringConcatenate).
Changes:
- Add `search_aliases: list[str]` to V3 Schema
- Add `SEARCH_ALIASES` support for V1 nodes
- Include field in `/object_info` response
- Add aliases to high-priority core nodes
V1 usage:
```python
class MyNode:
SEARCH_ALIASES = ["alt name", "synonym"]
```
V3 usage:
```python
io.Schema(
node_id="MyNode",
search_aliases=["alt name", "synonym"],
...
)
```
## Related PRs
- Frontend: Comfy-Org/ComfyUI_frontend#XXXX (draft - merge after this)
- Docs: Comfy-Org/docs#XXXX (draft - merge after stable)
* Propagate search_aliases through V3 Schema.get_v1_info to NodeInfoV1
* feat: add SEARCH_ALIASES for core nodes (#12016)
Add search aliases to 22 core nodes in nodes.py to improve node discoverability:
- Checkpoint/model loaders: CheckpointLoader, DiffusersLoader
- Conditioning nodes: ConditioningAverage, ConditioningSetArea, ConditioningSetMask, ConditioningZeroOut
- Style nodes: StyleModelApply
- Image nodes: LoadImageMask, LoadImageOutput, ImageBatch, ImageInvert, ImagePadForOutpaint
- Latent nodes: LoadLatent, SaveLatent, LatentBlend, LatentComposite, LatentCrop, LatentFlip, LatentFromBatch, LatentUpscale, LatentUpscaleBy, RepeatLatentBatch
* feat: add SEARCH_ALIASES for image, mask, and string nodes (#12017)
Add search aliases to nodes in comfy_extras for better discoverability:
- nodes_mask.py: mask manipulation nodes
- nodes_images.py: image processing nodes
- nodes_post_processing.py: post-processing effect nodes
- nodes_string.py: string manipulation nodes
- nodes_compositing.py: compositing nodes
- nodes_morphology.py: morphological operation nodes
- nodes_latent.py: latent space nodes
Uses search_aliases parameter in io.Schema() for v3 nodes.
* feat: add SEARCH_ALIASES for audio and video nodes (#12018)
Add search aliases to audio and video nodes for better discoverability:
- nodes_audio.py: audio loading, saving, and processing nodes
- nodes_video.py: video loading and processing nodes
- nodes_wan.py: WAN model nodes
Uses search_aliases parameter in io.Schema() for v3 nodes.
* feat: add SEARCH_ALIASES for model and misc nodes (#12019)
Add search aliases to model-related and miscellaneous nodes:
- Model nodes: nodes_model_merging.py, nodes_model_advanced.py, nodes_lora_extract.py
- Sampler nodes: nodes_custom_sampler.py, nodes_align_your_steps.py
- Control nodes: nodes_controlnet.py, nodes_attention_multiply.py, nodes_hooks.py
- Training nodes: nodes_train.py, nodes_dataset.py
- Utility nodes: nodes_logic.py, nodes_canny.py, nodes_differential_diffusion.py
- Architecture-specific: nodes_sd3.py, nodes_pixart.py, nodes_lumina2.py, nodes_kandinsky5.py, nodes_hidream.py, nodes_fresca.py, nodes_hunyuan3d.py
- Media nodes: nodes_load_3d.py, nodes_webcam.py, nodes_preview_any.py, nodes_wanmove.py
Uses search_aliases parameter in io.Schema() for v3 nodes, SEARCH_ALIASES class attribute for legacy nodes.
74 lines
2.5 KiB
Python
74 lines
2.5 KiB
Python
# code adapted from https://github.com/exx8/differential-diffusion
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from typing_extensions import override
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import torch
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from comfy_api.latest import ComfyExtension, io
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class DifferentialDiffusion(io.ComfyNode):
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@classmethod
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def define_schema(cls):
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return io.Schema(
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node_id="DifferentialDiffusion",
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search_aliases=["inpaint gradient", "variable denoise strength"],
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display_name="Differential Diffusion",
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category="_for_testing",
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inputs=[
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io.Model.Input("model"),
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io.Float.Input(
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"strength",
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default=1.0,
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min=0.0,
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max=1.0,
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step=0.01,
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optional=True,
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),
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],
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outputs=[io.Model.Output()],
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is_experimental=True,
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)
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@classmethod
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def execute(cls, model, strength=1.0) -> io.NodeOutput:
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model = model.clone()
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model.set_model_denoise_mask_function(lambda *args, **kwargs: cls.forward(*args, **kwargs, strength=strength))
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return io.NodeOutput(model)
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@classmethod
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def forward(cls, sigma: torch.Tensor, denoise_mask: torch.Tensor, extra_options: dict, strength: float):
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model = extra_options["model"]
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step_sigmas = extra_options["sigmas"]
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sigma_to = model.inner_model.model_sampling.sigma_min
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if step_sigmas[-1] > sigma_to:
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sigma_to = step_sigmas[-1]
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sigma_from = step_sigmas[0]
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ts_from = model.inner_model.model_sampling.timestep(sigma_from)
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ts_to = model.inner_model.model_sampling.timestep(sigma_to)
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current_ts = model.inner_model.model_sampling.timestep(sigma[0])
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threshold = (current_ts - ts_to) / (ts_from - ts_to)
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# Generate the binary mask based on the threshold
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binary_mask = (denoise_mask >= threshold).to(denoise_mask.dtype)
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# Blend binary mask with the original denoise_mask using strength
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if strength and strength < 1:
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blended_mask = strength * binary_mask + (1 - strength) * denoise_mask
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return blended_mask
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else:
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return binary_mask
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class DifferentialDiffusionExtension(ComfyExtension):
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@override
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async def get_node_list(self) -> list[type[io.ComfyNode]]:
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return [
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DifferentialDiffusion,
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]
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async def comfy_entrypoint() -> DifferentialDiffusionExtension:
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return DifferentialDiffusionExtension()
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