Rename essentials_category to main_category

The field is used for top-level tabs in the node library, not just
the Essentials tab. Rename to main_category to support Partner Nodes,
Basic, and other main categories.

Amp-Thread-ID: https://ampcode.com/threads/T-019c2b69-81c1-71c3-8096-450a39e20910

app/node_replace_manager.py

@@ -1,38 +0,0 @@
-from __future__ import annotations
-
-from aiohttp import web
-
-from typing import TYPE_CHECKING
-if TYPE_CHECKING:
-    from comfy_api.latest._node_replace import NodeReplace
-
-
-class NodeReplaceManager:
-    """Manages node replacement registrations."""
-
-    def __init__(self):
-        self._replacements: dict[str, list[NodeReplace]] = {}
-
-    def register(self, node_replace: NodeReplace):
-        """Register a node replacement mapping."""
-        self._replacements.setdefault(node_replace.old_node_id, []).append(node_replace)
-
-    def get_replacement(self, old_node_id: str) -> list[NodeReplace] | None:
-        """Get replacements for an old node ID."""
-        return self._replacements.get(old_node_id)
-
-    def has_replacement(self, old_node_id: str) -> bool:
-        """Check if a replacement exists for an old node ID."""
-        return old_node_id in self._replacements
-
-    def as_dict(self):
-        """Serialize all replacements to dict."""
-        return {
-            k: [v.as_dict() for v in v_list]
-            for k, v_list in self._replacements.items()
-        }
-
-    def add_routes(self, routes):
-        @routes.get("/node_replacements")
-        async def get_node_replacements(request):
-            return web.json_response(self.as_dict())

comfy/ldm/ace/ace_step15.py

@@ -183,7 +183,7 @@ class AceStepAttention(nn.Module):
             else:
                 attn_bias = window_bias
 
-        attn_output = optimized_attention(query_states, key_states, value_states, self.num_heads, attn_bias, skip_reshape=True, low_precision_attention=False)
+        attn_output = optimized_attention(query_states, key_states, value_states, self.num_heads, attn_bias, skip_reshape=True)
         attn_output = self.o_proj(attn_output)
 
         return attn_output
@@ -1035,7 +1035,8 @@ class AceStepConditionGenerationModel(nn.Module):
                     audio_codes = torch.nn.functional.pad(audio_codes, (0, math.ceil(src_latents.shape[1] / 5) - audio_codes.shape[1]), "constant", 35847)
                 lm_hints_5Hz = self.tokenizer.quantizer.get_output_from_indices(audio_codes, dtype=text_hidden_states.dtype)
             else:
-                lm_hints_5Hz, indices = self.tokenizer.tokenize(refer_audio_acoustic_hidden_states_packed)
+                assert False
+                # TODO ?
 
             lm_hints = self.detokenizer(lm_hints_5Hz)
 

comfy/ldm/modules/attention.py

@@ -524,9 +524,6 @@ def attention_pytorch(q, k, v, heads, mask=None, attn_precision=None, skip_resha
 
 @wrap_attn
 def attention_sage(q, k, v, heads, mask=None, attn_precision=None, skip_reshape=False, skip_output_reshape=False, **kwargs):
-    if kwargs.get("low_precision_attention", True) is False:
-        return attention_pytorch(q, k, v, heads, mask=mask, skip_reshape=skip_reshape, skip_output_reshape=skip_output_reshape, **kwargs)
-
     exception_fallback = False
     if skip_reshape:
         b, _, _, dim_head = q.shape

comfy/model_base.py

@@ -1548,7 +1548,6 @@ class ACEStep15(BaseModel):
     def extra_conds(self, **kwargs):
         out = super().extra_conds(**kwargs)
         device = kwargs["device"]
-        noise = kwargs["noise"]
 
         cross_attn = kwargs.get("cross_attn", None)
         if cross_attn is not None:
@@ -1572,19 +1571,15 @@ class ACEStep15(BaseModel):
                                         1.4844e-01,  9.4727e-02,  3.8477e-01, -1.2578e+00, -3.3203e-01,
                                         -8.5547e-01,  4.3359e-01,  4.2383e-01, -8.9453e-01, -5.0391e-01,
                                         -5.6152e-02, -2.9219e+00, -2.4658e-02,  5.0391e-01,  9.8438e-01,
-                                        7.2754e-02, -2.1582e-01,  6.3672e-01,  1.0000e+00]]], device=device).movedim(-1, 1).repeat(1, 1, noise.shape[2])
-            pass_audio_codes = True
+                                        7.2754e-02, -2.1582e-01,  6.3672e-01,  1.0000e+00]]], device=device).movedim(-1, 1).repeat(1, 1, 750)
         else:
-            refer_audio = refer_audio[-1][:, :, :noise.shape[2]]
-            pass_audio_codes = False
-
-        if pass_audio_codes:
-            audio_codes = kwargs.get("audio_codes", None)
-            if audio_codes is not None:
-                out['audio_codes'] = comfy.conds.CONDRegular(torch.tensor(audio_codes, device=device))
-                refer_audio = refer_audio[:, :, :750]
-
+            refer_audio = refer_audio[-1]
         out['refer_audio'] = comfy.conds.CONDRegular(refer_audio)
+
+        audio_codes = kwargs.get("audio_codes", None)
+        if audio_codes is not None:
+            out['audio_codes'] = comfy.conds.CONDRegular(torch.tensor(audio_codes, device=device))
+
         return out
 
 class Omnigen2(BaseModel):

comfy/ops.py

@@ -54,8 +54,6 @@ try:
             SDPA_BACKEND_PRIORITY.insert(0, SDPBackend.CUDNN_ATTENTION)
 
             def scaled_dot_product_attention(q, k, v, *args, **kwargs):
-                if q.nelement() < 1024 * 128:  # arbitrary number, for small inputs cudnn attention seems slower
-                    return torch.nn.functional.scaled_dot_product_attention(q, k, v, *args, **kwargs)
                 with sdpa_kernel(SDPA_BACKEND_PRIORITY, set_priority=True):
                     return torch.nn.functional.scaled_dot_product_attention(q, k, v, *args, **kwargs)
         else:

comfy/text_encoders/ace15.py

@@ -101,7 +101,9 @@ def sample_manual_loop_no_classes(
     return output_audio_codes
 
 
-def generate_audio_codes(model, positive, negative, min_tokens=1, max_tokens=1024, seed=0, cfg_scale=2.0, temperature=0.85, top_p=0.9, top_k=0):
+def generate_audio_codes(model, positive, negative, min_tokens=1, max_tokens=1024, seed=0):
+    cfg_scale = 2.0
+
     positive = [[token for token, _ in inner_list] for inner_list in positive]
     negative = [[token for token, _ in inner_list] for inner_list in negative]
     positive = positive[0]
@@ -118,7 +120,7 @@ def generate_audio_codes(model, positive, negative, min_tokens=1, max_tokens=102
         positive = [model.special_tokens["pad"]] * pos_pad + positive
 
     paddings = [pos_pad, neg_pad]
-    return sample_manual_loop_no_classes(model, [positive, negative], paddings, cfg_scale=cfg_scale, temperature=temperature, top_p=top_p, top_k=top_k, seed=seed, min_tokens=min_tokens, max_new_tokens=max_tokens)
+    return sample_manual_loop_no_classes(model, [positive, negative], paddings, cfg_scale=cfg_scale, seed=seed, min_tokens=min_tokens, max_new_tokens=max_tokens)
 
 
 class ACE15Tokenizer(sd1_clip.SD1Tokenizer):
@@ -135,12 +137,6 @@ class ACE15Tokenizer(sd1_clip.SD1Tokenizer):
         language = kwargs.get("language", "en")
         seed = kwargs.get("seed", 0)
 
-        generate_audio_codes = kwargs.get("generate_audio_codes", True)
-        cfg_scale = kwargs.get("cfg_scale", 2.0)
-        temperature = kwargs.get("temperature", 0.85)
-        top_p = kwargs.get("top_p", 0.9)
-        top_k = kwargs.get("top_k", 0.0)
-
         duration = math.ceil(duration)
         meta_lm = 'bpm: {}\nduration: {}\nkeyscale: {}\ntimesignature: {}'.format(bpm, duration, keyscale, timesignature)
         lm_template = "<|im_start|>system\n# Instruction\nGenerate audio semantic tokens based on the given conditions:\n\n<|im_end|>\n<|im_start|>user\n# Caption\n{}\n{}\n<|im_end|>\n<|im_start|>assistant\n<think>\n{}\n</think>\n\n<|im_end|>\n"
@@ -151,14 +147,7 @@ class ACE15Tokenizer(sd1_clip.SD1Tokenizer):
 
         out["lyrics"] = self.qwen3_06b.tokenize_with_weights("# Languages\n{}\n\n# Lyric{}<|endoftext|><|endoftext|>".format(language, lyrics), return_word_ids, disable_weights=True, **kwargs)
         out["qwen3_06b"] = self.qwen3_06b.tokenize_with_weights("# Instruction\nGenerate audio semantic tokens based on the given conditions:\n\n# Caption\n{}# Metas\n{}<|endoftext|>\n<|endoftext|>".format(text, meta_cap), return_word_ids, **kwargs)
-        out["lm_metadata"] = {"min_tokens": duration * 5,
-                              "seed": seed,
-                              "generate_audio_codes": generate_audio_codes,
-                              "cfg_scale": cfg_scale,
-                              "temperature": temperature,
-                              "top_p": top_p,
-                              "top_k": top_k,
-                              }
+        out["lm_metadata"] = {"min_tokens": duration * 5, "seed": seed}
         return out
 
 
@@ -214,14 +203,10 @@ class ACE15TEModel(torch.nn.Module):
         self.qwen3_06b.set_clip_options({"layer": [0]})
         lyrics_embeds, _, extra_l = self.qwen3_06b.encode_token_weights(token_weight_pairs_lyrics)
 
-        out = {"conditioning_lyrics": lyrics_embeds[:, 0]}
-
         lm_metadata = token_weight_pairs["lm_metadata"]
-        if lm_metadata["generate_audio_codes"]:
-            audio_codes = generate_audio_codes(getattr(self, self.lm_model, self.qwen3_06b), token_weight_pairs["lm_prompt"], token_weight_pairs["lm_prompt_negative"], min_tokens=lm_metadata["min_tokens"], max_tokens=lm_metadata["min_tokens"], seed=lm_metadata["seed"], cfg_scale=lm_metadata["cfg_scale"], temperature=lm_metadata["temperature"], top_p=lm_metadata["top_p"], top_k=lm_metadata["top_k"])
-            out["audio_codes"] = [audio_codes]
+        audio_codes = generate_audio_codes(getattr(self, self.lm_model, self.qwen3_06b), token_weight_pairs["lm_prompt"], token_weight_pairs["lm_prompt_negative"], min_tokens=lm_metadata["min_tokens"], max_tokens=lm_metadata["min_tokens"], seed=lm_metadata["seed"])
 
-        return base_out, None, out
+        return base_out, None, {"conditioning_lyrics": lyrics_embeds[:, 0], "audio_codes": [audio_codes]}
 
     def set_clip_options(self, options):
         self.qwen3_06b.set_clip_options(options)

comfy_api/latest/__init__.py

@@ -10,7 +10,6 @@ from ._input_impl import VideoFromFile, VideoFromComponents
 from ._util import VideoCodec, VideoContainer, VideoComponents, MESH, VOXEL, File3D
 from . import _io_public as io
 from . import _ui_public as ui
-from . import _node_replace_public as node_replace
 from comfy_execution.utils import get_executing_context
 from comfy_execution.progress import get_progress_state, PreviewImageTuple
 from PIL import Image
@@ -22,14 +21,6 @@ class ComfyAPI_latest(ComfyAPIBase):
     VERSION = "latest"
     STABLE = False
 
-    class NodeReplacement(ProxiedSingleton):
-        async def register(self, node_replace: 'node_replace.NodeReplace') -> None:
-            """Register a node replacement mapping."""
-            from server import PromptServer
-            PromptServer.instance.node_replace_manager.register(node_replace)
-
-    node_replacement: NodeReplacement
-
     class Execution(ProxiedSingleton):
         async def set_progress(
             self,
@@ -140,5 +131,4 @@ __all__ = [
     "IO",
     "ui",
     "UI",
-    "node_replace",
 ]

comfy_api/latest/_io.py

@@ -1309,6 +1309,7 @@ class NodeInfoV1:
     api_node: bool=None
     price_badge: dict | None = None
     search_aliases: list[str]=None
+    main_category: str=None
 
 
 @dataclass
@@ -1430,6 +1431,8 @@ class Schema:
     """Flags a node as expandable, allowing NodeOutput to include 'expand' property."""
     accept_all_inputs: bool=False
     """When True, all inputs from the prompt will be passed to the node as kwargs, even if not defined in the schema."""
+    main_category: str | None = None
+    """Optional main category for top-level tabs in the node library (e.g., 'Basic', 'Image Tools', 'Partner Nodes')."""
 
     def validate(self):
         '''Validate the schema:
@@ -1536,6 +1539,7 @@ class Schema:
             python_module=getattr(cls, "RELATIVE_PYTHON_MODULE", "nodes"),
             price_badge=self.price_badge.as_dict(self.inputs) if self.price_badge is not None else None,
             search_aliases=self.search_aliases if self.search_aliases else None,
+            main_category=self.main_category,
         )
         return info
 

comfy_api/latest/_node_replace.py

@@ -1,94 +0,0 @@
-from __future__ import annotations
-
-from typing import Any
-
-
-class NodeReplace:
-    """
-    Defines a possible node replacement, mapping inputs and outputs of the old node to the new node.
-
-    Also supports assigning specific values to the input widgets of the new node.
-    """
-    def __init__(self,
-        new_node_id: str,
-        old_node_id: str,
-        old_widget_ids: list[str] | None=None,
-        input_mapping: list[InputMap] | None=None,
-        output_mapping: list[OutputMap] | None=None,
-    ):
-        self.new_node_id = new_node_id
-        self.old_node_id = old_node_id
-        self.old_widget_ids = old_widget_ids
-        self.input_mapping = input_mapping
-        self.output_mapping = output_mapping
-
-    def as_dict(self):
-        """Create serializable representation of the node replacement."""
-        return {
-            "new_node_id": self.new_node_id,
-            "old_node_id": self.old_node_id,
-            "old_widget_ids": self.old_widget_ids,
-            "input_mapping": [m.as_dict() for m in self.input_mapping] if self.input_mapping else None,
-            "output_mapping": [m.as_dict() for m in self.output_mapping] if self.output_mapping else None,
-        }
-
-
-class InputMap:
-    """
-    Map inputs of node replacement.
-
-    Use InputMap.OldId or InputMap.SetValue for mapping purposes.
-    """
-    class _Assign:
-        def __init__(self, assign_type: str):
-            self.assign_type = assign_type
-
-        def as_dict(self):
-            return {
-                "assign_type": self.assign_type,
-            }
-
-    class OldId(_Assign):
-        """Connect the input of the old node with given id to new node when replacing."""
-        def __init__(self, old_id: str):
-            super().__init__("old_id")
-            self.old_id = old_id
-
-        def as_dict(self):
-            return super().as_dict() | {
-                "old_id": self.old_id,
-            }
-
-    class SetValue(_Assign):
-        """Use the given value for the input of the new node when replacing; assumes input is a widget."""
-        def __init__(self, value: Any):
-            super().__init__("set_value")
-            self.value = value
-
-        def as_dict(self):
-            return super().as_dict() | {
-                "value": self.value,
-            }
-
-    def __init__(self, new_id: str, assign: OldId | SetValue):
-        self.new_id = new_id
-        self.assign = assign
-
-    def as_dict(self):
-        return {
-            "new_id": self.new_id,
-            "assign": self.assign.as_dict(),
-        }
-
-
-class OutputMap:
-    """Map outputs of node replacement via indexes, as that's how outputs are stored."""
-    def __init__(self, new_idx: int, old_idx: int):
-        self.new_idx = new_idx
-        self.old_idx = old_idx
-
-    def as_dict(self):
-        return {
-            "new_idx": self.new_idx,
-            "old_idx": self.old_idx,
-        }

comfy_api/latest/_node_replace_public.py

@@ -1 +0,0 @@
-from ._node_replace import *  # noqa: F403

comfy_api/v0_0_2/__init__.py

@@ -6,7 +6,7 @@ from comfy_api.latest import (
 )
 from typing import Type, TYPE_CHECKING
 from comfy_api.internal.async_to_sync import create_sync_class
-from comfy_api.latest import io, ui, IO, UI, ComfyExtension, node_replace  #noqa: F401
+from comfy_api.latest import io, ui, IO, UI, ComfyExtension  #noqa: F401
 
 
 class ComfyAPIAdapter_v0_0_2(ComfyAPI_latest):
@@ -46,5 +46,4 @@ __all__ = [
     "IO",
     "ui",
     "UI",
-    "node_replace",
 ]

comfy_api_nodes/nodes_hunyuan3d.py

@@ -37,6 +37,7 @@ class TencentTextToModelNode(IO.ComfyNode):
             node_id="TencentTextToModelNode",
             display_name="Hunyuan3D: Text to Model (Pro)",
             category="api node/3d/Tencent",
+            main_category="3D",
             inputs=[
                 IO.Combo.Input(
                     "model",
@@ -147,6 +148,7 @@ class TencentImageToModelNode(IO.ComfyNode):
             node_id="TencentImageToModelNode",
             display_name="Hunyuan3D: Image(s) to Model (Pro)",
             category="api node/3d/Tencent",
+            main_category="3D",
             inputs=[
                 IO.Combo.Input(
                     "model",

comfy_api_nodes/nodes_kling.py

@@ -1936,6 +1936,7 @@ class KlingLipSyncAudioToVideoNode(IO.ComfyNode):
             node_id="KlingLipSyncAudioToVideoNode",
             display_name="Kling Lip Sync Video with Audio",
             category="api node/video/Kling",
+            main_category="Video Generation",
             description="Kling Lip Sync Audio to Video Node. Syncs mouth movements in a video file to the audio content of an audio file. When using, ensure that the audio contains clearly distinguishable vocals and that the video contains a distinct face. The audio file should not be larger than 5MB. The video file should not be larger than 100MB, should have height/width between 720px and 1920px, and should be between 2s and 10s in length.",
             inputs=[
                 IO.Video.Input("video"),

comfy_api_nodes/nodes_openai.py

@@ -576,6 +576,7 @@ class OpenAIChatNode(IO.ComfyNode):
             node_id="OpenAIChatNode",
             display_name="OpenAI ChatGPT",
             category="api node/text/OpenAI",
+            main_category="Text Generation",
             description="Generate text responses from an OpenAI model.",
             inputs=[
                 IO.String.Input(

comfy_api_nodes/nodes_recraft.py

@@ -963,6 +963,7 @@ class RecraftRemoveBackgroundNode(IO.ComfyNode):
             node_id="RecraftRemoveBackgroundNode",
             display_name="Recraft Remove Background",
             category="api node/image/Recraft",
+            main_category="Image Tools",
             description="Remove background from image, and return processed image and mask.",
             inputs=[
                 IO.Image.Input("image"),

comfy_api_nodes/nodes_stability.py

@@ -624,6 +624,7 @@ class StabilityTextToAudio(IO.ComfyNode):
             node_id="StabilityTextToAudio",
             display_name="Stability AI Text To Audio",
             category="api node/audio/Stability AI",
+            main_category="Audio",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.Combo.Input(

comfy_extras/nodes_ace.py

@@ -44,18 +44,13 @@ class TextEncodeAceStepAudio15(io.ComfyNode):
                 io.Combo.Input("timesignature", options=['2', '3', '4', '6']),
                 io.Combo.Input("language", options=["en", "ja", "zh", "es", "de", "fr", "pt", "ru", "it", "nl", "pl", "tr", "vi", "cs", "fa", "id", "ko", "uk", "hu", "ar", "sv", "ro", "el"]),
                 io.Combo.Input("keyscale", options=[f"{root} {quality}" for quality in ["major", "minor"] for root in ["C", "C#", "Db", "D", "D#", "Eb", "E", "F", "F#", "Gb", "G", "G#", "Ab", "A", "A#", "Bb", "B"]]),
-                io.Boolean.Input("generate_audio_codes", default=True, tooltip="Enable the LLM that generates audio codes. This can be slow but will increase the quality of the generated audio. Turn this off if you are giving the model an audio reference.", advanced=True),
-                io.Float.Input("cfg_scale", default=2.0, min=0.0, max=100.0, step=0.1, advanced=True),
-                io.Float.Input("temperature", default=0.85, min=0.0, max=2.0, step=0.01, advanced=True),
-                io.Float.Input("top_p", default=0.9, min=0.0, max=2000.0, step=0.01, advanced=True),
-                io.Int.Input("top_k", default=0, min=0, max=100, advanced=True),
             ],
             outputs=[io.Conditioning.Output()],
         )
 
     @classmethod
-    def execute(cls, clip, tags, lyrics, seed, bpm, duration, timesignature, language, keyscale, generate_audio_codes, cfg_scale, temperature, top_p, top_k) -> io.NodeOutput:
-        tokens = clip.tokenize(tags, lyrics=lyrics, bpm=bpm, duration=duration, timesignature=int(timesignature), language=language, keyscale=keyscale, seed=seed, generate_audio_codes=generate_audio_codes, cfg_scale=cfg_scale, temperature=temperature, top_p=top_p, top_k=top_k)
+    def execute(cls, clip, tags, lyrics, seed, bpm, duration, timesignature, language, keyscale) -> io.NodeOutput:
+        tokens = clip.tokenize(tags, lyrics=lyrics, bpm=bpm, duration=duration, timesignature=int(timesignature), language=language, keyscale=keyscale, seed=seed)
         conditioning = clip.encode_from_tokens_scheduled(tokens)
         return io.NodeOutput(conditioning)
 
@@ -105,15 +100,14 @@ class EmptyAceStep15LatentAudio(io.ComfyNode):
         latent = torch.zeros([batch_size, 64, length], device=comfy.model_management.intermediate_device())
         return io.NodeOutput({"samples": latent, "type": "audio"})
 
-class ReferenceAudio(io.ComfyNode):
+class ReferenceTimbreAudio(io.ComfyNode):
     @classmethod
     def define_schema(cls):
         return io.Schema(
             node_id="ReferenceTimbreAudio",
-            display_name="Reference Audio",
             category="advanced/conditioning/audio",
             is_experimental=True,
-            description="This node sets the reference audio for ace step 1.5",
+            description="This node sets the reference audio for timbre (for ace step 1.5)",
             inputs=[
                 io.Conditioning.Input("conditioning"),
                 io.Latent.Input("latent", optional=True),
@@ -137,7 +131,7 @@ class AceExtension(ComfyExtension):
             EmptyAceStepLatentAudio,
             TextEncodeAceStepAudio15,
             EmptyAceStep15LatentAudio,
-            ReferenceAudio,
+            ReferenceTimbreAudio,
         ]
 
 async def comfy_entrypoint() -> AceExtension:

comfy_extras/nodes_audio.py

@@ -129,6 +129,7 @@ class SaveAudio(IO.ComfyNode):
             search_aliases=["export flac"],
             display_name="Save Audio (FLAC)",
             category="audio",
+            main_category="Audio",
             inputs=[
                 IO.Audio.Input("audio"),
                 IO.String.Input("filename_prefix", default="audio/ComfyUI"),
@@ -270,6 +271,7 @@ class LoadAudio(IO.ComfyNode):
             search_aliases=["import audio", "open audio", "audio file"],
             display_name="Load Audio",
             category="audio",
+            main_category="Audio",
             inputs=[
                 IO.Combo.Input("audio", upload=IO.UploadType.audio, options=sorted(files)),
             ],

comfy_extras/nodes_canny.py

@@ -12,6 +12,7 @@ class Canny(io.ComfyNode):
             node_id="Canny",
             search_aliases=["edge detection", "outline", "contour detection", "line art"],
             category="image/preprocessors",
+            main_category="Image Tools/Preprocessing",
             inputs=[
                 io.Image.Input("image"),
                 io.Float.Input("low_threshold", default=0.4, min=0.01, max=0.99, step=0.01),

comfy_extras/nodes_hunyuan3d.py

@@ -621,6 +621,7 @@ class SaveGLB(IO.ComfyNode):
             display_name="Save 3D Model",
             search_aliases=["export 3d model", "save mesh"],
             category="3d",
+            main_category="Basic",
             is_output_node=True,
             inputs=[
                 IO.MultiType.Input(

comfy_extras/nodes_images.py

@@ -25,6 +25,7 @@ class ImageCrop(IO.ComfyNode):
             search_aliases=["trim"],
             display_name="Image Crop",
             category="image/transform",
+            main_category="Image Tools",
             inputs=[
                 IO.Image.Input("image"),
                 IO.Int.Input("width", default=512, min=1, max=nodes.MAX_RESOLUTION, step=1),
@@ -537,6 +538,7 @@ class ImageRotate(IO.ComfyNode):
             node_id="ImageRotate",
             search_aliases=["turn", "flip orientation"],
             category="image/transform",
+            main_category="Image Tools",
             inputs=[
                 IO.Image.Input("image"),
                 IO.Combo.Input("rotation", options=["none", "90 degrees", "180 degrees", "270 degrees"]),

comfy_extras/nodes_load_3d.py

@@ -31,6 +31,7 @@ class Load3D(IO.ComfyNode):
             node_id="Load3D",
             display_name="Load 3D & Animation",
             category="3d",
+            main_category="Basic",
             is_experimental=True,
             inputs=[
                 IO.Combo.Input("model_file", options=sorted(files), upload=IO.UploadType.model),

comfy_extras/nodes_post_processing.py

@@ -77,6 +77,7 @@ class Blur(io.ComfyNode):
         return io.Schema(
             node_id="ImageBlur",
             category="image/postprocessing",
+            main_category="Image Tools",
             inputs=[
                 io.Image.Input("image"),
                 io.Int.Input("blur_radius", default=1, min=1, max=31, step=1),
@@ -655,103 +656,6 @@ class BatchImagesMasksLatentsNode(io.ComfyNode):
             batched = batch_masks(values)
         return io.NodeOutput(batched)
 
-
-from comfy_api.latest import node_replace
-from server import PromptServer
-
-def _register(nr: node_replace.NodeReplace):
-    """Helper to register replacements via PromptServer."""
-    PromptServer.instance.node_replace_manager.register(nr)
-
-async def register_replacements():
-    """Register all built-in node replacements."""
-    register_replacements_longeredge()
-    register_replacements_batchimages()
-    register_replacements_upscaleimage()
-    register_replacements_controlnet()
-    register_replacements_load3d()
-    register_replacements_preview3d()
-    register_replacements_svdimg2vid()
-    register_replacements_conditioningavg()
-
-def register_replacements_longeredge():
-    # No dynamic inputs here
-    _register(node_replace.NodeReplace(
-            new_node_id="ImageScaleToMaxDimension",
-            old_node_id="ResizeImagesByLongerEdge",
-            old_widget_ids=["longer_edge"],
-            input_mapping=[
-                node_replace.InputMap(new_id="image", assign=node_replace.InputMap.OldId("images")),
-                node_replace.InputMap(new_id="largest_size", assign=node_replace.InputMap.OldId("longer_edge")),
-                node_replace.InputMap(new_id="upscale_method", assign=node_replace.InputMap.SetValue("lanczos")),
-            ],
-            # just to test the frontend output_mapping code, does nothing really here
-            output_mapping=[node_replace.OutputMap(new_idx=0, old_idx=0)],
-        ))
-
-def register_replacements_batchimages():
-    # BatchImages node uses Autogrow
-    _register(node_replace.NodeReplace(
-            new_node_id="BatchImagesNode",
-            old_node_id="ImageBatch",
-            input_mapping=[
-                node_replace.InputMap(new_id="images.image0", assign=node_replace.InputMap.OldId("image1")),
-                node_replace.InputMap(new_id="images.image1", assign=node_replace.InputMap.OldId("image2")),
-            ],
-        ))
-
-def register_replacements_upscaleimage():
-    # ResizeImageMaskNode uses DynamicCombo
-    _register(node_replace.NodeReplace(
-            new_node_id="ResizeImageMaskNode",
-            old_node_id="ImageScaleBy",
-            old_widget_ids=["upscale_method", "scale_by"],
-            input_mapping=[
-                node_replace.InputMap(new_id="input", assign=node_replace.InputMap.OldId("image")),
-                node_replace.InputMap(new_id="resize_type", assign=node_replace.InputMap.SetValue("scale by multiplier")),
-                node_replace.InputMap(new_id="resize_type.multiplier", assign=node_replace.InputMap.OldId("scale_by")),
-                node_replace.InputMap(new_id="scale_method", assign=node_replace.InputMap.OldId("upscale_method")),
-            ],
-        ))
-
-def register_replacements_controlnet():
-    # T2IAdapterLoader → ControlNetLoader
-    _register(node_replace.NodeReplace(
-            new_node_id="ControlNetLoader",
-            old_node_id="T2IAdapterLoader",
-            input_mapping=[
-                node_replace.InputMap(new_id="control_net_name", assign=node_replace.InputMap.OldId("t2i_adapter_name")),
-            ],
-        ))
-
-def register_replacements_load3d():
-    # Load3DAnimation merged into Load3D
-    _register(node_replace.NodeReplace(
-            new_node_id="Load3D",
-            old_node_id="Load3DAnimation",
-        ))
-
-def register_replacements_preview3d():
-    # Preview3DAnimation merged into Preview3D
-    _register(node_replace.NodeReplace(
-            new_node_id="Preview3D",
-            old_node_id="Preview3DAnimation",
-        ))
-
-def register_replacements_svdimg2vid():
-    # Typo fix: SDV → SVD
-    _register(node_replace.NodeReplace(
-            new_node_id="SVD_img2vid_Conditioning",
-            old_node_id="SDV_img2vid_Conditioning",
-        ))
-
-def register_replacements_conditioningavg():
-    # Typo fix: trailing space in node name
-    _register(node_replace.NodeReplace(
-            new_node_id="ConditioningAverage",
-            old_node_id="ConditioningAverage ",
-        ))
-
 class PostProcessingExtension(ComfyExtension):
     @override
     async def get_node_list(self) -> list[type[io.ComfyNode]]:
@@ -769,5 +673,4 @@ class PostProcessingExtension(ComfyExtension):
         ]
 
 async def comfy_entrypoint() -> PostProcessingExtension:
-    await register_replacements()
     return PostProcessingExtension()

comfy_extras/nodes_video.py

@@ -73,6 +73,7 @@ class SaveVideo(io.ComfyNode):
             search_aliases=["export video"],
             display_name="Save Video",
             category="image/video",
+            main_category="Basic",
             description="Saves the input images to your ComfyUI output directory.",
             inputs=[
                 io.Video.Input("video", tooltip="The video to save."),
@@ -146,6 +147,7 @@ class GetVideoComponents(io.ComfyNode):
             search_aliases=["extract frames", "split video", "video to images", "demux"],
             display_name="Get Video Components",
             category="image/video",
+            main_category="Video Tools",
             description="Extracts all components from a video: frames, audio, and framerate.",
             inputs=[
                 io.Video.Input("video", tooltip="The video to extract components from."),
@@ -174,6 +176,7 @@ class LoadVideo(io.ComfyNode):
             search_aliases=["import video", "open video", "video file"],
             display_name="Load Video",
             category="image/video",
+            main_category="Basic",
             inputs=[
                 io.Combo.Input("file", options=sorted(files), upload=io.UploadType.video),
             ],

nodes.py

@@ -69,6 +69,7 @@ class CLIPTextEncode(ComfyNodeABC):
     FUNCTION = "encode"
 
     CATEGORY = "conditioning"
+    MAIN_CATEGORY = "Basic"
     DESCRIPTION = "Encodes a text prompt using a CLIP model into an embedding that can be used to guide the diffusion model towards generating specific images."
     SEARCH_ALIASES = ["text", "prompt", "text prompt", "positive prompt", "negative prompt", "encode text", "text encoder", "encode prompt"]
 
@@ -667,6 +668,8 @@ class CLIPSetLastLayer:
         return (clip,)
 
 class LoraLoader:
+    MAIN_CATEGORY = "Image Generation"
+
     def __init__(self):
         self.loaded_lora = None
 
@@ -1648,6 +1651,7 @@ class SaveImage:
     OUTPUT_NODE = True
 
     CATEGORY = "image"
+    MAIN_CATEGORY = "Basic"
     DESCRIPTION = "Saves the input images to your ComfyUI output directory."
     SEARCH_ALIASES = ["save", "save image", "export image", "output image", "write image", "download"]
 
@@ -1706,6 +1710,7 @@ class LoadImage:
                 }
 
     CATEGORY = "image"
+    MAIN_CATEGORY = "Basic"
     SEARCH_ALIASES = ["load image", "open image", "import image", "image input", "upload image", "read image", "image loader"]
 
     RETURN_TYPES = ("IMAGE", "MASK")
@@ -1863,6 +1868,7 @@ class ImageScale:
     FUNCTION = "upscale"
 
     CATEGORY = "image/upscaling"
+    MAIN_CATEGORY = "Image Tools"
     SEARCH_ALIASES = ["resize", "resize image", "scale image", "image resize", "zoom", "zoom in", "change size"]
 
     def upscale(self, image, upscale_method, width, height, crop):
@@ -1902,6 +1908,7 @@ class ImageScaleBy:
 
 class ImageInvert:
     SEARCH_ALIASES = ["reverse colors"]
+    MAIN_CATEGORY = "Image Tools"
 
     @classmethod
     def INPUT_TYPES(s):
@@ -1918,6 +1925,7 @@ class ImageInvert:
 
 class ImageBatch:
     SEARCH_ALIASES = ["combine images", "merge images", "stack images"]
+    MAIN_CATEGORY = "Image Tools"
 
     @classmethod
     def INPUT_TYPES(s):

server.py

@@ -40,7 +40,6 @@ from app.user_manager import UserManager
 from app.model_manager import ModelFileManager
 from app.custom_node_manager import CustomNodeManager
 from app.subgraph_manager import SubgraphManager
-from app.node_replace_manager import NodeReplaceManager
 from typing import Optional, Union
 from api_server.routes.internal.internal_routes import InternalRoutes
 from protocol import BinaryEventTypes
@@ -205,7 +204,6 @@ class PromptServer():
         self.model_file_manager = ModelFileManager()
         self.custom_node_manager = CustomNodeManager()
         self.subgraph_manager = SubgraphManager()
-        self.node_replace_manager = NodeReplaceManager()
         self.internal_routes = InternalRoutes(self)
         self.supports = ["custom_nodes_from_web"]
         self.prompt_queue = execution.PromptQueue(self)
@@ -689,6 +687,10 @@ class PromptServer():
                 info['api_node'] = obj_class.API_NODE
 
             info['search_aliases'] = getattr(obj_class, 'SEARCH_ALIASES', [])
+
+            if hasattr(obj_class, 'MAIN_CATEGORY'):
+                info['main_category'] = obj_class.MAIN_CATEGORY
+
             return info
 
         @routes.get("/object_info")
@@ -997,7 +999,6 @@ class PromptServer():
         self.model_file_manager.add_routes(self.routes)
         self.custom_node_manager.add_routes(self.routes, self.app, nodes.LOADED_MODULE_DIRS.items())
         self.subgraph_manager.add_routes(self.routes, nodes.LOADED_MODULE_DIRS.items())
-        self.node_replace_manager.add_routes(self.routes)
         self.app.add_subapp('/internal', self.internal_routes.get_app())
 
         # Prefix every route with /api for easier matching for delegation.