Merge branch 'master' into feat/load3d-camera-info-intrinsics

comfy/ldm/audio/dit.py

@@ -433,11 +433,11 @@ class Attention(nn.Module):
         if self.differential:
             q, q_diff = q.unbind(dim=1)
             k, k_diff = k.unbind(dim=1)
-            out      = optimized_attention(q,      k,      v, h, skip_reshape=True, transformer_options=transformer_options)
-            out_diff = optimized_attention(q_diff, k_diff, v, h, skip_reshape=True, transformer_options=transformer_options)
+            out      = optimized_attention(q,      k,      v, h, skip_reshape=True, low_precision_attention=False, transformer_options=transformer_options)
+            out_diff = optimized_attention(q_diff, k_diff, v, h, skip_reshape=True, low_precision_attention=False, transformer_options=transformer_options)
             out = out - out_diff
         else:
-            out = optimized_attention(q, k, v, h, skip_reshape=True, transformer_options=transformer_options)
+            out = optimized_attention(q, k, v, h, skip_reshape=True, low_precision_attention=False, transformer_options=transformer_options)
 
         out = self.to_out(out)
 

comfy/ldm/audio/vae_sa3.py

@@ -138,11 +138,11 @@ class Attention(nn.Module):
                 k_diff = _apply_rotary_pos_emb(k_diff.float(), freqs).to(k_dtype)
 
         if self.differential:
-            out = (optimized_attention(q, k, v, h, mask=mask, skip_reshape=True)
-                   - optimized_attention(q_diff, k_diff, v, h, mask=mask, skip_reshape=True))
+            out = (optimized_attention(q, k, v, h, mask=mask, skip_reshape=True, low_precision_attention=False)
+                   - optimized_attention(q_diff, k_diff, v, h, mask=mask, skip_reshape=True, low_precision_attention=False))
             del q, k, v, q_diff, k_diff
         else:
-            out = optimized_attention(q, k, v, h, mask=mask, skip_reshape=True)
+            out = optimized_attention(q, k, v, h, mask=mask, skip_reshape=True, low_precision_attention=False)
             del q, k, v
 
         return self.to_out(out)

comfy/ldm/pixeldit/pid.py

@@ -207,8 +207,9 @@ class PidNet(PixDiT_T2I):
                 f"Flux1/SD3 = 16 channels, Flux2 = 128 channels."
             )
         B = x.shape[0]
-        Hs = x.shape[2] // self.patch_size
-        Ws = x.shape[3] // self.patch_size
+        # Match the backbone's pad_to_patch_size (round up) so the LQ grid lines up with the patch stream.
+        Hs = -(-x.shape[2] // self.patch_size)
+        Ws = -(-x.shape[3] // self.patch_size)
 
         degrade_sigma = degrade_sigma.to(device=x.device, dtype=torch.float32).reshape(-1)
         if degrade_sigma.numel() == 1 and B > 1:

comfy/model_base.py

@@ -1428,6 +1428,23 @@ class PiD(PixelDiTT2I):
             out["degrade_sigma"] = comfy.conds.CONDRegular(degrade_sigma)
         return out
 
+    def resize_cond_for_context_window(self, cond_key, cond_value, window, x_in, device, retain_index_list=[]):
+        if cond_key == "lq_latent" and hasattr(cond_value, "cond") and isinstance(cond_value.cond, torch.Tensor):
+            lq = cond_value.cond
+            dim = window.dim
+            if dim >= lq.ndim:
+                return None
+            lq_proj = self.diffusion_model.lq_proj
+            ratio = lq_proj.sr_scale * lq_proj.latent_spatial_down_factor
+            # Map x window indices -> lq indices (deduplicated, sorted, in-bounds).
+            lq_size = lq.size(dim)
+            lq_indices = sorted({i // ratio for i in window.index_list if 0 <= i // ratio < lq_size})
+            if not lq_indices:
+                return None
+            idx = tuple([slice(None)] * dim + [lq_indices])
+            return cond_value._copy_with(lq[idx].to(device))
+        return super().resize_cond_for_context_window(cond_key, cond_value, window, x_in, device, retain_index_list=retain_index_list)
+
 
 class WAN21(BaseModel):
     def __init__(self, model_config, model_type=ModelType.FLOW, image_to_video=False, device=None):

comfy_api_nodes/apis/beeble.py

@@ -0,0 +1,32 @@
+from pydantic import BaseModel, Field
+
+
+class CreateSwitchXRequest(BaseModel):
+    generation_type: str = Field(...)
+    source_uri: str = Field(...)
+    alpha_mode: str = Field(...)
+    prompt: str | None = Field(None, max_length=2000)
+    reference_image_uri: str | None = Field(None)
+    alpha_uri: str | None = Field(None)
+    max_resolution: int = Field(1080)
+    callback_url: str | None = Field(None)
+    idempotency_key: str | None = Field(None, max_length=256, min_length=1)
+
+
+class SwitchXOutputUrls(BaseModel):
+    render: str | None = Field(None)
+    source: str | None = Field(None)
+    alpha: str | None = Field(None)
+
+
+class SwitchXStatusResponse(BaseModel):
+    id: str = Field(...)
+    status: str = Field(...)
+    progress: int | None = Field(None)
+    generation_type: str | None = Field(None)
+    alpha_mode: str | None = Field(None)
+    output: SwitchXOutputUrls | None = Field(None)
+    error: str | None = Field(None)
+    created_at: str | None = Field(None)
+    modified_at: str | None = Field(None)
+    completed_at: str | None = Field(None)

comfy_api_nodes/nodes_anthropic.py

@@ -155,7 +155,7 @@ class ClaudeNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ClaudeNode",
             display_name="Anthropic Claude",
-            category="api node/text/Anthropic",
+            category="text/partner/Anthropic",
             essentials_category="Text Generation",
             description="Generate text responses with Anthropic's Claude models. "
             "Provide a text prompt and optionally one or more images for multimodal context.",

comfy_api_nodes/nodes_beeble.py

@@ -0,0 +1,404 @@
+from fractions import Fraction
+
+from typing_extensions import override
+
+from comfy_api.latest import IO, ComfyExtension, Input, InputImpl, Types
+from comfy_api_nodes.apis.beeble import (
+    CreateSwitchXRequest,
+    SwitchXStatusResponse,
+)
+from comfy_api_nodes.util import (
+    ApiEndpoint,
+    bytesio_to_image_tensor,
+    convert_mask_to_image,
+    download_url_as_bytesio,
+    download_url_to_image_tensor,
+    download_url_to_video_output,
+    downscale_image_tensor,
+    downscale_video_to_max_pixels,
+    poll_op,
+    sync_op,
+    upload_image_to_comfyapi,
+    upload_video_to_comfyapi,
+    validate_string,
+    validate_video_frame_count,
+)
+
+_MAX_PIXELS = 2_770_000
+_MAX_FRAMES = 240
+_MAX_PROMPT_LEN = 2000
+
+
+def _validate_inputs(prompt: str | None, reference_image: Input.Image | None) -> str | None:
+    """Beeble requires at least one of prompt or reference_image. Returns the cleaned prompt."""
+    cleaned = prompt.strip() if prompt else ""
+    if not cleaned and reference_image is None:
+        raise ValueError("At least one of 'prompt' or 'reference_image' must be provided.")
+    if cleaned:
+        validate_string(cleaned, strip_whitespace=False, max_length=_MAX_PROMPT_LEN)
+    return cleaned or None
+
+
+async def _upload_mask_as_image(
+    cls: type[IO.ComfyNode],
+    mask: Input.Image,
+    *,
+    wait_label: str,
+) -> str:
+    """Encode a single-frame MASK (H, W) or (1, H, W) as a PNG and upload."""
+    if mask.dim() == 2:
+        mask = mask.unsqueeze(0)
+    image = convert_mask_to_image(mask[:1])
+    return await upload_image_to_comfyapi(
+        cls,
+        image,
+        mime_type="image/png",
+        wait_label=wait_label,
+        total_pixels=_MAX_PIXELS,
+    )
+
+
+async def _upload_mask_batch_as_video(
+    cls: type[IO.ComfyNode],
+    mask: Input.Image,
+    *,
+    frame_rate: Fraction,
+    source_frame_count: int,
+    wait_label: str,
+) -> str:
+    """Encode a MASK batch (N, H, W) as a grayscale H.264 MP4 at frame_rate and upload.
+
+    The matte is always downscaled to the pixel budget so it stays within Beeble's limit and
+    keeps the same dimensions as the (similarly downscaled) source — both use the same algorithm
+    from the same starting dimensions, and downscaling is a no-op when already within budget.
+    """
+    if mask.dim() == 2:
+        mask = mask.unsqueeze(0)
+    if mask.shape[0] != source_frame_count:
+        raise ValueError(
+            f"Custom alpha video frame count ({mask.shape[0]}) does not match the "
+            f"source video frame count ({source_frame_count}). The Beeble API requires "
+            "one mask per source frame."
+        )
+    images = downscale_image_tensor(convert_mask_to_image(mask), _MAX_PIXELS)
+    alpha_video = InputImpl.VideoFromComponents(Types.VideoComponents(images=images, audio=None, frame_rate=frame_rate))
+    return await upload_video_to_comfyapi(cls, alpha_video, wait_label=wait_label)
+
+
+def _alpha_mode_input(*, video: bool) -> IO.DynamicCombo.Input:
+    """Build the alpha_mode DynamicCombo with mode-specific extra inputs."""
+    select_keyframe_tooltip = (
+        "First-frame keyframe mask. Beeble propagates this across the video." if video else "Grayscale keyframe mask."
+    )
+    custom_tooltip = (
+        "Per-frame grayscale mask covering the entire video. "
+        "Must have the same frame count as the source. "
+        "Connect a MASK output from SAM3_TrackToMask or similar."
+        if video
+        else "Grayscale mask to apply."
+    )
+    return IO.DynamicCombo.Input(
+        "alpha_mode",
+        tooltip=(
+            "Controls how SwitchX decides what to keep vs. regenerate. "
+            "'auto' isolates the main subject automatically. "
+            "'fill' regenerates the entire frame while preserving geometry. "
+            "'select' propagates a first-frame keyframe across the clip. "
+            "'custom' uses a per-frame alpha matte you provide."
+        ),
+        options=[
+            IO.DynamicCombo.Option("auto", []),
+            IO.DynamicCombo.Option("fill", []),
+            IO.DynamicCombo.Option(
+                "select",
+                [IO.Mask.Input("alpha_keyframe", tooltip=select_keyframe_tooltip)],
+            ),
+            IO.DynamicCombo.Option(
+                "custom",
+                [IO.Mask.Input("alpha_mask", tooltip=custom_tooltip)],
+            ),
+        ],
+    )
+
+
+def _common_inputs(*, source: IO.Input, video: bool) -> list[IO.Input]:
+    return [
+        source,
+        IO.String.Input(
+            "prompt",
+            multiline=True,
+            default="",
+            tooltip=(
+                "Text description of the desired output (max 2000 chars). "
+                "At least one of 'prompt' or 'reference_image' is required."
+            ),
+        ),
+        IO.Image.Input(
+            "reference_image",
+            optional=True,
+            tooltip=(
+                "Reference image whose look (background, lighting, costume) the result "
+                "should adopt. At least one of 'reference_image' or 'prompt' is required."
+            ),
+        ),
+        _alpha_mode_input(video=video),
+        IO.Combo.Input(
+            "max_resolution",
+            options=["1080p", "720p"],
+            default="1080p",
+            tooltip="Maximum output resolution.",
+        ),
+        IO.Int.Input(
+            "seed",
+            default=0,
+            min=0,
+            max=2147483647,
+            control_after_generate=True,
+            tooltip=(
+                "Seed controls whether the node should re-run; " "results are non-deterministic regardless of seed."
+            ),
+        ),
+    ]
+
+
+async def _submit_and_poll(
+    cls: type[IO.ComfyNode],
+    request: CreateSwitchXRequest,
+) -> SwitchXStatusResponse:
+    initial = await sync_op(
+        cls,
+        ApiEndpoint(path="/proxy/beeble/v1/switchx/generations", method="POST"),
+        response_model=SwitchXStatusResponse,
+        data=request,
+    )
+    return await poll_op(
+        cls,
+        ApiEndpoint(path=f"/proxy/beeble/v1/switchx/generations/{initial.id}"),
+        response_model=SwitchXStatusResponse,
+        status_extractor=lambda r: r.status,
+        progress_extractor=lambda r: r.progress,
+    )
+
+
+def _require_output_url(response: SwitchXStatusResponse, name: str) -> str:
+    if response.output is None or getattr(response.output, name) is None:
+        raise RuntimeError(f"Beeble job {response.id} completed without a {name!r} output URL.")
+    return getattr(response.output, name)
+
+
+def _alpha_url(response: SwitchXStatusResponse, mode: str) -> str | None:
+    """URL of the alpha matte, or None when the mode produces no separate matte.
+
+    'fill' selects the whole frame, so Beeble writes no alpha asset even though the status
+    response still returns a (dangling) signed URL for it — fetching it 403s with S3
+    AccessDenied. The other three modes ('auto', 'custom', 'select') all produce a real,
+    downloadable matte.
+    """
+    if mode == "fill" or response.output is None:
+        return None
+    return response.output.alpha
+
+
+class BeebleSwitchXVideoEdit(IO.ComfyNode):
+
+    @classmethod
+    def define_schema(cls) -> IO.Schema:
+        return IO.Schema(
+            node_id="BeebleSwitchXVideoEdit",
+            display_name="Beeble SwitchX Video Edit",
+            category="api node/video/Beeble",
+            description=(
+                "Edit a video with Beeble SwitchX. Switches anything in the scene (background, "
+                "lighting, costume) while preserving the original subject's pixels and motion. "
+                "Provide a reference image and/or text prompt to describe the new look. "
+                "Max 240 frames, max ~2.77MP per frame."
+            ),
+            inputs=_common_inputs(source=IO.Video.Input("video"), video=True),
+            outputs=[
+                IO.Video.Output(display_name="video"),
+                IO.Video.Output(
+                    display_name="alpha",
+                    tooltip="The alpha matte Beeble used. Empty for 'fill' mode, which has no separate matte.",
+                ),
+            ],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+            price_badge=IO.PriceBadge(
+                depends_on=IO.PriceBadgeDepends(widgets=["max_resolution"]),
+                expr="""
+                (
+                  $rate := widgets.max_resolution = "1080p" ? 0.429 : 0.143;
+                  {"type":"usd","usd": $rate, "format":{"suffix":"/30 frames"}}
+                )
+                """,
+            ),
+        )
+
+    @classmethod
+    async def execute(
+        cls,
+        video: Input.Video,
+        prompt: str,
+        alpha_mode: dict,
+        max_resolution: str,
+        seed: int,
+        reference_image: Input.Image | None = None,
+    ) -> IO.NodeOutput:
+        cleaned_prompt = _validate_inputs(prompt, reference_image)
+
+        validate_video_frame_count(video, max_frame_count=_MAX_FRAMES)
+        video = downscale_video_to_max_pixels(video, _MAX_PIXELS)
+
+        mode = alpha_mode["alpha_mode"]
+        alpha_uri: str | None = None
+        if mode == "select":
+            alpha_uri = await _upload_mask_as_image(cls, alpha_mode["alpha_keyframe"], wait_label="Uploading keyframe")
+        elif mode == "custom":
+            alpha_uri = await _upload_mask_batch_as_video(
+                cls,
+                alpha_mode["alpha_mask"],
+                frame_rate=video.get_frame_rate(),
+                source_frame_count=video.get_frame_count(),
+                wait_label="Uploading alpha video",
+            )
+
+        source_uri = await upload_video_to_comfyapi(cls, video, wait_label="Uploading source")
+        reference_uri: str | None = None
+        if reference_image is not None:
+            reference_uri = await upload_image_to_comfyapi(
+                cls,
+                reference_image,
+                mime_type="image/png",
+                wait_label="Uploading reference",
+                total_pixels=_MAX_PIXELS,
+            )
+
+        request = CreateSwitchXRequest(
+            generation_type="video",
+            source_uri=source_uri,
+            alpha_mode=mode,
+            prompt=cleaned_prompt,
+            reference_image_uri=reference_uri,
+            alpha_uri=alpha_uri,
+            max_resolution=1080 if max_resolution == "1080p" else 720,
+        )
+        response = await _submit_and_poll(cls, request)
+
+        render = await download_url_to_video_output(_require_output_url(response, "render"))
+        alpha = None
+        if (alpha_url := _alpha_url(response, mode)) is not None:
+            alpha = await download_url_to_video_output(alpha_url)
+        return IO.NodeOutput(render, alpha)
+
+
+class BeebleSwitchXImageEdit(IO.ComfyNode):
+
+    @classmethod
+    def define_schema(cls) -> IO.Schema:
+        return IO.Schema(
+            node_id="BeebleSwitchXImageEdit",
+            display_name="Beeble SwitchX Image Edit",
+            category="api node/image/Beeble",
+            description=(
+                "Edit a single image with Beeble SwitchX. Switches anything in the scene "
+                "(background, lighting, costume) while preserving the original subject's pixels. "
+                "Provide a reference image and/or text prompt to describe the new look. "
+                "Max ~2.77MP."
+            ),
+            inputs=_common_inputs(source=IO.Image.Input("image"), video=False),
+            outputs=[
+                IO.Image.Output(display_name="image"),
+                IO.Mask.Output(
+                    display_name="alpha",
+                    tooltip="The alpha matte Beeble used. Empty for 'fill' mode, which has no separate matte.",
+                ),
+            ],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+            price_badge=IO.PriceBadge(
+                depends_on=IO.PriceBadgeDepends(widgets=["max_resolution"]),
+                expr="""
+                (
+                  $rate := widgets.max_resolution = "1080p" ? 0.429 : 0.143;
+                  {"type":"usd","usd": $rate}
+                )
+                """,
+            ),
+        )
+
+    @classmethod
+    async def execute(
+        cls,
+        image: Input.Image,
+        prompt: str,
+        alpha_mode: dict,
+        max_resolution: str,
+        seed: int,
+        reference_image: Input.Image | None = None,
+    ) -> IO.NodeOutput:
+        cleaned_prompt = _validate_inputs(prompt, reference_image)
+
+        image = downscale_image_tensor(image, _MAX_PIXELS)
+
+        mode = alpha_mode["alpha_mode"]
+        alpha_uri: str | None = None
+        if mode == "select":
+            alpha_uri = await _upload_mask_as_image(cls, alpha_mode["alpha_keyframe"], wait_label="Uploading keyframe")
+        elif mode == "custom":
+            alpha_uri = await _upload_mask_as_image(cls, alpha_mode["alpha_mask"], wait_label="Uploading alpha")
+
+        source_uri = await upload_image_to_comfyapi(
+            cls,
+            image,
+            mime_type="image/png",
+            wait_label="Uploading source",
+            total_pixels=None,
+        )
+        reference_uri: str | None = None
+        if reference_image is not None:
+            reference_uri = await upload_image_to_comfyapi(
+                cls,
+                reference_image,
+                mime_type="image/png",
+                wait_label="Uploading reference",
+                total_pixels=_MAX_PIXELS,
+            )
+
+        request = CreateSwitchXRequest(
+            generation_type="image",
+            source_uri=source_uri,
+            alpha_mode=mode,
+            prompt=cleaned_prompt,
+            reference_image_uri=reference_uri,
+            alpha_uri=alpha_uri,
+            max_resolution=1080 if max_resolution == "1080p" else 720,
+        )
+        response = await _submit_and_poll(cls, request)
+
+        render = await download_url_to_image_tensor(_require_output_url(response, "render"))
+        alpha_mask = None
+        if (alpha_url := _alpha_url(response, mode)) is not None:
+            alpha_image = bytesio_to_image_tensor(await download_url_as_bytesio(alpha_url), mode="L")
+            alpha_mask = alpha_image.squeeze(-1) if alpha_image.dim() == 4 else alpha_image
+        return IO.NodeOutput(render, alpha_mask)
+
+
+class BeebleExtension(ComfyExtension):
+    @override
+    async def get_node_list(self) -> list[type[IO.ComfyNode]]:
+        return [
+            BeebleSwitchXVideoEdit,
+            BeebleSwitchXImageEdit,
+        ]
+
+
+async def comfy_entrypoint() -> BeebleExtension:
+    return BeebleExtension()

comfy_api_nodes/nodes_bfl.py

@@ -42,7 +42,7 @@ class FluxProUltraImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="FluxProUltraImageNode",
             display_name="Flux 1.1 [pro] Ultra Image",
-            category="api node/image/BFL",
+            category="image/partner/BFL",
             description="Generates images using Flux Pro 1.1 Ultra via api based on prompt and resolution.",
             inputs=[
                 IO.String.Input(
@@ -160,7 +160,7 @@ class FluxKontextProImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id=cls.NODE_ID,
             display_name=cls.DISPLAY_NAME,
-            category="api node/image/BFL",
+            category="image/partner/BFL",
             description="Edits images using Flux.1 Kontext [pro] via api based on prompt and aspect ratio.",
             inputs=[
                 IO.String.Input(
@@ -282,7 +282,7 @@ class FluxProExpandNode(IO.ComfyNode):
         return IO.Schema(
             node_id="FluxProExpandNode",
             display_name="Flux.1 Expand Image",
-            category="api node/image/BFL",
+            category="image/partner/BFL",
             description="Outpaints image based on prompt.",
             inputs=[
                 IO.Image.Input("image"),
@@ -419,7 +419,7 @@ class FluxProFillNode(IO.ComfyNode):
         return IO.Schema(
             node_id="FluxProFillNode",
             display_name="Flux.1 Fill Image",
-            category="api node/image/BFL",
+            category="image/partner/BFL",
             description="Inpaints image based on mask and prompt.",
             inputs=[
                 IO.Image.Input("image"),
@@ -545,7 +545,7 @@ class Flux2ProImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id=cls.NODE_ID,
             display_name=cls.DISPLAY_NAME,
-            category="api node/image/BFL",
+            category="image/partner/BFL",
             description="Generates images synchronously based on prompt and resolution.",
             inputs=[
                 IO.String.Input(
@@ -716,7 +716,7 @@ class Flux2ImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Flux2ImageNode",
             display_name="Flux.2 Image",
-            category="api node/image/BFL",
+            category="image/partner/BFL",
             description="Generate images via Flux.2 [pro] or Flux.2 [max] from a prompt and optional reference images.",
             inputs=[
                 IO.String.Input(

comfy_api_nodes/nodes_bria.py

@@ -31,7 +31,7 @@ class BriaImageEditNode(IO.ComfyNode):
         return IO.Schema(
             node_id="BriaImageEditNode",
             display_name="Bria FIBO Image Edit",
-            category="api node/image/Bria",
+            category="image/partner/Bria",
             description="Edit images using Bria latest model",
             inputs=[
                 IO.Combo.Input("model", options=["FIBO"]),
@@ -169,7 +169,7 @@ class BriaRemoveImageBackground(IO.ComfyNode):
         return IO.Schema(
             node_id="BriaRemoveImageBackground",
             display_name="Bria Remove Image Background",
-            category="api node/image/Bria",
+            category="image/partner/Bria",
             description="Remove the background from an image using Bria RMBG 2.0.",
             inputs=[
                 IO.Image.Input("image"),
@@ -245,7 +245,7 @@ class BriaRemoveVideoBackground(IO.ComfyNode):
         return IO.Schema(
             node_id="BriaRemoveVideoBackground",
             display_name="Bria Remove Video Background",
-            category="api node/video/Bria",
+            category="video/partner/Bria",
             description="Remove the background from a video using Bria. ",
             inputs=[
                 IO.Video.Input("video"),

comfy_api_nodes/nodes_bytedance.py

@@ -359,7 +359,7 @@ class ByteDanceImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDanceImageNode",
             display_name="ByteDance Image",
-            category="api node/image/ByteDance",
+            category="image/partner/ByteDance",
             description="Generate images using ByteDance models via api based on prompt",
             inputs=[
                 IO.Combo.Input("model", options=["seedream-3-0-t2i-250415"]),
@@ -483,7 +483,7 @@ class ByteDanceSeedreamNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDanceSeedreamNode",
             display_name="ByteDance Seedream 4.5 & 5.0",
-            category="api node/image/ByteDance",
+            category="image/partner/ByteDance",
             description="Unified text-to-image generation and precise single-sentence editing at up to 4K resolution.",
             inputs=[
                 IO.Combo.Input(
@@ -745,7 +745,7 @@ class ByteDanceSeedreamNodeV2(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDanceSeedreamNodeV2",
             display_name="ByteDance Seedream 4.5 & 5.0",
-            category="api node/image/ByteDance",
+            category="image/partner/ByteDance",
             description="Unified text-to-image generation and precise single-sentence editing at up to 4K resolution.",
             inputs=[
                 IO.String.Input(
@@ -911,7 +911,7 @@ class ByteDanceTextToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDanceTextToVideoNode",
             display_name="ByteDance Text to Video",
-            category="api node/video/ByteDance",
+            category="video/partner/ByteDance",
             description="Generate video using ByteDance models via api based on prompt",
             inputs=[
                 IO.Combo.Input(
@@ -1039,7 +1039,7 @@ class ByteDanceImageToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDanceImageToVideoNode",
             display_name="ByteDance Image to Video",
-            category="api node/video/ByteDance",
+            category="video/partner/ByteDance",
             description="Generate video using ByteDance models via api based on image and prompt",
             inputs=[
                 IO.Combo.Input(
@@ -1176,7 +1176,7 @@ class ByteDanceFirstLastFrameNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDanceFirstLastFrameNode",
             display_name="ByteDance First-Last-Frame to Video",
-            category="api node/video/ByteDance",
+            category="video/partner/ByteDance",
             description="Generate video using prompt and first and last frames.",
             inputs=[
                 IO.Combo.Input(
@@ -1324,7 +1324,7 @@ class ByteDanceImageReferenceNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDanceImageReferenceNode",
             display_name="ByteDance Reference Images to Video",
-            category="api node/video/ByteDance",
+            category="video/partner/ByteDance",
             description="Generate video using prompt and reference images.",
             inputs=[
                 IO.Combo.Input(
@@ -1567,7 +1567,7 @@ class ByteDance2TextToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDance2TextToVideoNode",
             display_name="ByteDance Seedance 2.0 Text to Video",
-            category="api node/video/ByteDance",
+            category="video/partner/ByteDance",
             description="Generate video using Seedance 2.0 models based on a text prompt.",
             inputs=[
                 IO.DynamicCombo.Input(
@@ -1668,7 +1668,7 @@ class ByteDance2FirstLastFrameNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDance2FirstLastFrameNode",
             display_name="ByteDance Seedance 2.0 First-Last-Frame to Video",
-            category="api node/video/ByteDance",
+            category="video/partner/ByteDance",
             description="Generate video using Seedance 2.0 from a first frame image and optional last frame image.",
             inputs=[
                 IO.DynamicCombo.Input(
@@ -1930,7 +1930,7 @@ class ByteDance2ReferenceNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDance2ReferenceNode",
             display_name="ByteDance Seedance 2.0 Reference to Video",
-            category="api node/video/ByteDance",
+            category="video/partner/ByteDance",
             description="Generate, edit, or extend video using Seedance 2.0 with reference images, "
             "videos, and audio. Supports multimodal reference, video editing, and video extension.",
             inputs=[
@@ -2224,7 +2224,7 @@ class ByteDanceCreateImageAsset(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDanceCreateImageAsset",
             display_name="ByteDance Create Image Asset",
-            category="api node/image/ByteDance",
+            category="image/partner/ByteDance",
             description=(
                 "Create a Seedance 2.0 personal image asset. Uploads the input image and "
                 "registers it in the given asset group. If group_id is empty, runs a real-person "
@@ -2291,7 +2291,7 @@ class ByteDanceCreateVideoAsset(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDanceCreateVideoAsset",
             display_name="ByteDance Create Video Asset",
-            category="api node/video/ByteDance",
+            category="video/partner/ByteDance",
             description=(
                 "Create a Seedance 2.0 personal video asset. Uploads the input video and "
                 "registers it in the given asset group. If group_id is empty, runs a real-person "

comfy_api_nodes/nodes_bytedance_llm.py

@@ -144,7 +144,7 @@ class ByteDanceSeedNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ByteDanceSeedNode",
             display_name="ByteDance Seed",
-            category="api node/text/ByteDance",
+            category="text/partner/ByteDance",
             essentials_category="Text Generation",
             description="Generate text responses with ByteDance's Seed 2.0 models. "
             "Provide a text prompt and optionally one or more images or videos for multimodal context.",

comfy_api_nodes/nodes_elevenlabs.py

@@ -69,7 +69,7 @@ class ElevenLabsSpeechToText(IO.ComfyNode):
         return IO.Schema(
             node_id="ElevenLabsSpeechToText",
             display_name="ElevenLabs Speech to Text",
-            category="api node/audio/ElevenLabs",
+            category="audio/partner/ElevenLabs",
             description="Transcribe audio to text. "
             "Supports automatic language detection, speaker diarization, and audio event tagging.",
             inputs=[
@@ -210,7 +210,7 @@ class ElevenLabsVoiceSelector(IO.ComfyNode):
         return IO.Schema(
             node_id="ElevenLabsVoiceSelector",
             display_name="ElevenLabs Voice Selector",
-            category="api node/audio/ElevenLabs",
+            category="audio/partner/ElevenLabs",
             description="Select a predefined ElevenLabs voice for text-to-speech generation.",
             inputs=[
                 IO.Combo.Input(
@@ -239,7 +239,7 @@ class ElevenLabsTextToSpeech(IO.ComfyNode):
         return IO.Schema(
             node_id="ElevenLabsTextToSpeech",
             display_name="ElevenLabs Text to Speech",
-            category="api node/audio/ElevenLabs",
+            category="audio/partner/ElevenLabs",
             description="Convert text to speech.",
             inputs=[
                 IO.Custom(ELEVENLABS_VOICE).Input(
@@ -414,7 +414,7 @@ class ElevenLabsAudioIsolation(IO.ComfyNode):
         return IO.Schema(
             node_id="ElevenLabsAudioIsolation",
             display_name="ElevenLabs Voice Isolation",
-            category="api node/audio/ElevenLabs",
+            category="audio/partner/ElevenLabs",
             description="Remove background noise from audio, isolating vocals or speech.",
             inputs=[
                 IO.Audio.Input(
@@ -459,7 +459,7 @@ class ElevenLabsTextToSoundEffects(IO.ComfyNode):
         return IO.Schema(
             node_id="ElevenLabsTextToSoundEffects",
             display_name="ElevenLabs Text to Sound Effects",
-            category="api node/audio/ElevenLabs",
+            category="audio/partner/ElevenLabs",
             description="Generate sound effects from text descriptions.",
             inputs=[
                 IO.String.Input(
@@ -555,7 +555,7 @@ class ElevenLabsInstantVoiceClone(IO.ComfyNode):
         return IO.Schema(
             node_id="ElevenLabsInstantVoiceClone",
             display_name="ElevenLabs Instant Voice Clone",
-            category="api node/audio/ElevenLabs",
+            category="audio/partner/ElevenLabs",
             description="Create a cloned voice from audio samples. "
             "Provide 1-8 audio recordings of the voice to clone.",
             inputs=[
@@ -658,7 +658,7 @@ class ElevenLabsSpeechToSpeech(IO.ComfyNode):
         return IO.Schema(
             node_id="ElevenLabsSpeechToSpeech",
             display_name="ElevenLabs Speech to Speech",
-            category="api node/audio/ElevenLabs",
+            category="audio/partner/ElevenLabs",
             description="Transform speech from one voice to another while preserving the original content and emotion.",
             inputs=[
                 IO.Custom(ELEVENLABS_VOICE).Input(
@@ -793,7 +793,7 @@ class ElevenLabsTextToDialogue(IO.ComfyNode):
         return IO.Schema(
             node_id="ElevenLabsTextToDialogue",
             display_name="ElevenLabs Text to Dialogue",
-            category="api node/audio/ElevenLabs",
+            category="audio/partner/ElevenLabs",
             description="Generate multi-speaker dialogue from text. Each dialogue entry has its own text and voice.",
             inputs=[
                 IO.Float.Input(

comfy_api_nodes/nodes_gemini.py

@@ -300,7 +300,7 @@ class GeminiNode(IO.ComfyNode):
         return IO.Schema(
             node_id="GeminiNode",
             display_name="Google Gemini",
-            category="api node/text/Gemini",
+            category="text/partner/Gemini",
             description="Generate text responses with Google's Gemini AI model. "
             "You can provide multiple types of inputs (text, images, audio, video) "
             "as context for generating more relevant and meaningful responses.",
@@ -541,7 +541,7 @@ class GeminiInputFiles(IO.ComfyNode):
         return IO.Schema(
             node_id="GeminiInputFiles",
             display_name="Gemini Input Files",
-            category="api node/text/Gemini",
+            category="text/partner/Gemini",
             description="Loads and prepares input files to include as inputs for Gemini LLM nodes. "
             "The files will be read by the Gemini model when generating a response. "
             "The contents of the text file count toward the token limit. "
@@ -598,7 +598,7 @@ class GeminiImage(IO.ComfyNode):
         return IO.Schema(
             node_id="GeminiImageNode",
             display_name="Nano Banana (Google Gemini Image)",
-            category="api node/image/Gemini",
+            category="image/partner/Gemini",
             description="Edit images synchronously via Google API.",
             inputs=[
                 IO.String.Input(
@@ -731,7 +731,7 @@ class GeminiImage2(IO.ComfyNode):
         return IO.Schema(
             node_id="GeminiImage2Node",
             display_name="Nano Banana Pro (Google Gemini Image)",
-            category="api node/image/Gemini",
+            category="image/partner/Gemini",
             description="Generate or edit images synchronously via Google Vertex API.",
             inputs=[
                 IO.String.Input(
@@ -869,7 +869,7 @@ class GeminiNanoBanana2(IO.ComfyNode):
         return IO.Schema(
             node_id="GeminiNanoBanana2",
             display_name="Nano Banana 2",
-            category="api node/image/Gemini",
+            category="image/partner/Gemini",
             description="Generate or edit images synchronously via Google Vertex API.",
             inputs=[
                 IO.String.Input(
@@ -1085,7 +1085,7 @@ class GeminiNanoBanana2V2(IO.ComfyNode):
         return IO.Schema(
             node_id="GeminiNanoBanana2V2",
             display_name="Nano Banana 2",
-            category="api node/image/Gemini",
+            category="image/partner/Gemini",
             description="Generate or edit images synchronously via Google Vertex API.",
             inputs=[
                 IO.String.Input(

comfy_api_nodes/nodes_grok.py

@@ -49,7 +49,7 @@ class GrokImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="GrokImageNode",
             display_name="Grok Image",
-            category="api node/image/Grok",
+            category="image/partner/Grok",
             description="Generate images using Grok based on a text prompt",
             inputs=[
                 IO.Combo.Input(
@@ -224,7 +224,7 @@ class GrokImageEditNode(IO.ComfyNode):
         return IO.Schema(
             node_id="GrokImageEditNode",
             display_name="Grok Image Edit",
-            category="api node/image/Grok",
+            category="image/partner/Grok",
             description="Modify an existing image based on a text prompt",
             inputs=[
                 IO.Combo.Input(
@@ -366,7 +366,7 @@ class GrokImageEditNodeV2(IO.ComfyNode):
         return IO.Schema(
             node_id="GrokImageEditNodeV2",
             display_name="Grok Image Edit",
-            category="api node/image/Grok",
+            category="image/partner/Grok",
             description="Modify an existing image based on a text prompt",
             inputs=[
                 IO.String.Input(
@@ -503,7 +503,7 @@ class GrokVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="GrokVideoNode",
             display_name="Grok Video",
-            category="api node/video/Grok",
+            category="video/partner/Grok",
             description="Generate video from a prompt or an image",
             inputs=[
                 IO.Combo.Input("model", options=["grok-imagine-video", "grok-imagine-video-beta"]),
@@ -615,7 +615,7 @@ class GrokVideoEditNode(IO.ComfyNode):
         return IO.Schema(
             node_id="GrokVideoEditNode",
             display_name="Grok Video Edit",
-            category="api node/video/Grok",
+            category="video/partner/Grok",
             description="Edit an existing video based on a text prompt.",
             inputs=[
                 IO.Combo.Input("model", options=["grok-imagine-video", "grok-imagine-video-beta"]),
@@ -693,7 +693,7 @@ class GrokVideoReferenceNode(IO.ComfyNode):
         return IO.Schema(
             node_id="GrokVideoReferenceNode",
             display_name="Grok Reference-to-Video",
-            category="api node/video/Grok",
+            category="video/partner/Grok",
             description="Generate video guided by reference images as style and content references.",
             inputs=[
                 IO.String.Input(
@@ -826,7 +826,7 @@ class GrokVideoExtendNode(IO.ComfyNode):
         return IO.Schema(
             node_id="GrokVideoExtendNode",
             display_name="Grok Video Extend",
-            category="api node/video/Grok",
+            category="video/partner/Grok",
             description="Extend an existing video with a seamless continuation based on a text prompt.",
             inputs=[
                 IO.String.Input(

comfy_api_nodes/nodes_hitpaw.py

@@ -71,7 +71,7 @@ class HitPawGeneralImageEnhance(IO.ComfyNode):
         return IO.Schema(
             node_id="HitPawGeneralImageEnhance",
             display_name="HitPaw General Image Enhance",
-            category="api node/image/HitPaw",
+            category="image/partner/HitPaw",
             description="Upscale low-resolution images to super-resolution, eliminate artifacts and noise. "
             f"Maximum output: {MAX_MP_GENERATIVE} megapixels.",
             inputs=[
@@ -201,7 +201,7 @@ class HitPawVideoEnhance(IO.ComfyNode):
         return IO.Schema(
             node_id="HitPawVideoEnhance",
             display_name="HitPaw Video Enhance",
-            category="api node/video/HitPaw",
+            category="video/partner/HitPaw",
             description="Upscale low-resolution videos to high resolution, eliminate artifacts and noise. "
             "Prices shown are per second of video.",
             inputs=[

comfy_api_nodes/nodes_hunyuan3d.py

@@ -123,7 +123,7 @@ class TencentTextToModelNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TencentTextToModelNode",
             display_name="Hunyuan3D: Text to Model",
-            category="api node/3d/Tencent",
+            category="3d/partner/Tencent",
             essentials_category="3D",
             inputs=[
                 IO.Combo.Input(
@@ -242,7 +242,7 @@ class TencentImageToModelNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TencentImageToModelNode",
             display_name="Hunyuan3D: Image(s) to Model",
-            category="api node/3d/Tencent",
+            category="3d/partner/Tencent",
             essentials_category="3D",
             inputs=[
                 IO.Combo.Input(
@@ -415,7 +415,7 @@ class TencentModelTo3DUVNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TencentModelTo3DUVNode",
             display_name="Hunyuan3D: Model to UV",
-            category="api node/3d/Tencent",
+            category="3d/partner/Tencent",
             description="Perform UV unfolding on a 3D model to generate UV texture. "
             "Input model must have less than 30000 faces.",
             inputs=[
@@ -505,7 +505,7 @@ class Tencent3DTextureEditNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Tencent3DTextureEditNode",
             display_name="Hunyuan3D: 3D Texture Edit",
-            category="api node/3d/Tencent",
+            category="3d/partner/Tencent",
             description="After inputting the 3D model, perform 3D model texture redrawing.",
             inputs=[
                 IO.MultiType.Input(
@@ -594,7 +594,7 @@ class Tencent3DPartNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Tencent3DPartNode",
             display_name="Hunyuan3D: 3D Part",
-            category="api node/3d/Tencent",
+            category="3d/partner/Tencent",
             description="Automatically perform component identification and generation based on the model structure.",
             inputs=[
                 IO.MultiType.Input(
@@ -666,7 +666,7 @@ class TencentSmartTopologyNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TencentSmartTopologyNode",
             display_name="Hunyuan3D: Smart Topology",
-            category="api node/3d/Tencent",
+            category="3d/partner/Tencent",
             description="Perform smart retopology on a 3D model. "
             "Supports GLB/OBJ formats; max 200MB; recommended for high-poly models.",
             inputs=[

comfy_api_nodes/nodes_ideogram.py

@@ -234,7 +234,7 @@ class IdeogramV1(IO.ComfyNode):
         return IO.Schema(
             node_id="IdeogramV1",
             display_name="Ideogram V1",
-            category="api node/image/Ideogram",
+            category="image/partner/Ideogram",
             description="Generates images using the Ideogram V1 model.",
             inputs=[
                 IO.String.Input(
@@ -360,7 +360,7 @@ class IdeogramV2(IO.ComfyNode):
         return IO.Schema(
             node_id="IdeogramV2",
             display_name="Ideogram V2",
-            category="api node/image/Ideogram",
+            category="image/partner/Ideogram",
             description="Generates images using the Ideogram V2 model.",
             inputs=[
                 IO.String.Input(
@@ -526,7 +526,7 @@ class IdeogramV3(IO.ComfyNode):
         return IO.Schema(
             node_id="IdeogramV3",
             display_name="Ideogram V3",
-            category="api node/image/Ideogram",
+            category="image/partner/Ideogram",
             description="Generates images using the Ideogram V3 model. "
                         "Supports both regular image generation from text prompts and image editing with mask.",
             inputs=[

comfy_api_nodes/nodes_kling.py

@@ -642,7 +642,7 @@ class KlingCameraControls(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingCameraControls",
             display_name="Kling Camera Controls",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Allows specifying configuration options for Kling Camera Controls and motion control effects.",
             inputs=[
                 IO.Combo.Input("camera_control_type", options=KlingCameraControlType),
@@ -762,7 +762,7 @@ class KlingTextToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingTextToVideoNode",
             display_name="Kling Text to Video",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Kling Text to Video Node",
             inputs=[
                 IO.String.Input("prompt", multiline=True, tooltip="Positive text prompt"),
@@ -849,7 +849,7 @@ class OmniProTextToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingOmniProTextToVideoNode",
             display_name="Kling 3.0 Omni Text to Video",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Use text prompts to generate videos with the latest Kling model.",
             inputs=[
                 IO.Combo.Input("model_name", options=["kling-v3-omni", "kling-video-o1"]),
@@ -998,7 +998,7 @@ class OmniProFirstLastFrameNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingOmniProFirstLastFrameNode",
             display_name="Kling 3.0 Omni First-Last-Frame to Video",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Use a start frame, an optional end frame, or reference images with the latest Kling model.",
             inputs=[
                 IO.Combo.Input("model_name", options=["kling-v3-omni", "kling-video-o1"]),
@@ -1205,7 +1205,7 @@ class OmniProImageToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingOmniProImageToVideoNode",
             display_name="Kling 3.0 Omni Image to Video",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Use up to 7 reference images to generate a video with the latest Kling model.",
             inputs=[
                 IO.Combo.Input("model_name", options=["kling-v3-omni", "kling-video-o1"]),
@@ -1374,7 +1374,7 @@ class OmniProVideoToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingOmniProVideoToVideoNode",
             display_name="Kling 3.0 Omni Video to Video",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Use a video and up to 4 reference images to generate a video with the latest Kling model.",
             inputs=[
                 IO.Combo.Input("model_name", options=["kling-v3-omni", "kling-video-o1"]),
@@ -1485,7 +1485,7 @@ class OmniProEditVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingOmniProEditVideoNode",
             display_name="Kling 3.0 Omni Edit Video",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             essentials_category="Video Generation",
             description="Edit an existing video with the latest model from Kling.",
             inputs=[
@@ -1593,7 +1593,7 @@ class OmniProImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingOmniProImageNode",
             display_name="Kling 3.0 Omni Image",
-            category="api node/image/Kling",
+            category="image/partner/Kling",
             description="Create or edit images with the latest model from Kling.",
             inputs=[
                 IO.Combo.Input("model_name", options=["kling-v3-omni", "kling-image-o1"]),
@@ -1721,7 +1721,7 @@ class KlingCameraControlT2VNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingCameraControlT2VNode",
             display_name="Kling Text to Video (Camera Control)",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Transform text into cinematic videos with professional camera movements that simulate real-world cinematography. Control virtual camera actions including zoom, rotation, pan, tilt, and first-person view, while maintaining focus on your original text.",
             inputs=[
                 IO.String.Input("prompt", multiline=True, tooltip="Positive text prompt"),
@@ -1783,7 +1783,7 @@ class KlingImage2VideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingImage2VideoNode",
             display_name="Kling Image(First Frame) to Video",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             inputs=[
                 IO.Image.Input("start_frame", tooltip="The reference image used to generate the video."),
                 IO.String.Input("prompt", multiline=True, tooltip="Positive text prompt"),
@@ -1882,7 +1882,7 @@ class KlingCameraControlI2VNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingCameraControlI2VNode",
             display_name="Kling Image to Video (Camera Control)",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Transform still images into cinematic videos with professional camera movements that simulate real-world cinematography. Control virtual camera actions including zoom, rotation, pan, tilt, and first-person view, while maintaining focus on your original image.",
             inputs=[
                 IO.Image.Input(
@@ -1953,7 +1953,7 @@ class KlingStartEndFrameNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingStartEndFrameNode",
             display_name="Kling Start-End Frame to Video",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Generate a video sequence that transitions between your provided start and end images. The node creates all frames in between, producing a smooth transformation from the first frame to the last.",
             inputs=[
                 IO.Image.Input(
@@ -2047,7 +2047,7 @@ class KlingVideoExtendNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingVideoExtendNode",
             display_name="Kling Video Extend",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Kling Video Extend Node. Extend videos made by other Kling nodes. The video_id is created by using other Kling Nodes.",
             inputs=[
                 IO.String.Input(
@@ -2128,7 +2128,7 @@ class KlingDualCharacterVideoEffectNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingDualCharacterVideoEffectNode",
             display_name="Kling Dual Character Video Effects",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Achieve different special effects when generating a video based on the effect_scene. First image will be positioned on left side, second on right side of the composite.",
             inputs=[
                 IO.Image.Input("image_left", tooltip="Left side image"),
@@ -2218,7 +2218,7 @@ class KlingSingleImageVideoEffectNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingSingleImageVideoEffectNode",
             display_name="Kling Video Effects",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Achieve different special effects when generating a video based on the effect_scene.",
             inputs=[
                 IO.Image.Input(
@@ -2291,7 +2291,7 @@ class KlingLipSyncAudioToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingLipSyncAudioToVideoNode",
             display_name="Kling Lip Sync Video with Audio",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             essentials_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=[
@@ -2343,7 +2343,7 @@ class KlingLipSyncTextToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingLipSyncTextToVideoNode",
             display_name="Kling Lip Sync Video with Text",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Kling Lip Sync Text to Video Node. Syncs mouth movements in a video file to a text prompt. 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"),
@@ -2411,7 +2411,7 @@ class KlingVirtualTryOnNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingVirtualTryOnNode",
             display_name="Kling Virtual Try On",
-            category="api node/image/Kling",
+            category="image/partner/Kling",
             description="Kling Virtual Try On Node. Input a human image and a cloth image to try on the cloth on the human. You can merge multiple clothing item pictures into one image with a white background.",
             inputs=[
                 IO.Image.Input("human_image"),
@@ -2478,7 +2478,7 @@ class KlingImageGenerationNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingImageGenerationNode",
             display_name="Kling 3.0 Image",
-            category="api node/image/Kling",
+            category="image/partner/Kling",
             description="Kling Image Generation Node. Generate an image from a text prompt with an optional reference image.",
             inputs=[
                 IO.String.Input("prompt", multiline=True, tooltip="Positive text prompt"),
@@ -2615,7 +2615,7 @@ class TextToVideoWithAudio(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingTextToVideoWithAudio",
             display_name="Kling 2.6 Text to Video with Audio",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             inputs=[
                 IO.Combo.Input("model_name", options=["kling-v2-6"]),
                 IO.String.Input("prompt", multiline=True, tooltip="Positive text prompt."),
@@ -2683,7 +2683,7 @@ class ImageToVideoWithAudio(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingImageToVideoWithAudio",
             display_name="Kling 2.6 Image(First Frame) to Video with Audio",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             inputs=[
                 IO.Combo.Input("model_name", options=["kling-v2-6"]),
                 IO.Image.Input("start_frame"),
@@ -2753,7 +2753,7 @@ class MotionControl(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingMotionControl",
             display_name="Kling Motion Control",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             inputs=[
                 IO.String.Input("prompt", multiline=True),
                 IO.Image.Input("reference_image"),
@@ -2854,7 +2854,7 @@ class KlingVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingVideoNode",
             display_name="Kling 3.0 Video",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Generate videos with Kling V3. "
             "Supports text-to-video and image-to-video with optional storyboard multi-prompt and audio generation.",
             inputs=[
@@ -3077,7 +3077,7 @@ class KlingFirstLastFrameNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingFirstLastFrameNode",
             display_name="Kling 3.0 First-Last-Frame to Video",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Generate videos with Kling V3 using first and last frames.",
             inputs=[
                 IO.String.Input("prompt", multiline=True, default=""),
@@ -3202,7 +3202,7 @@ class KlingAvatarNode(IO.ComfyNode):
         return IO.Schema(
             node_id="KlingAvatarNode",
             display_name="Kling Avatar 2.0",
-            category="api node/video/Kling",
+            category="video/partner/Kling",
             description="Generate broadcast-style digital human videos from a single photo and an audio file.",
             inputs=[
                 IO.Image.Input(

comfy_api_nodes/nodes_krea.py

@@ -106,7 +106,7 @@ class Krea2ImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Krea2ImageNode",
             display_name="Krea 2 Image",
-            category="api node/image/Krea",
+            category="image/partner/Krea",
             description=(
                 "Generate images via Krea 2 — pick Medium (expressive illustrations) or "
                 "Large (expressive photorealism). Supports an optional moodboard and up "
@@ -229,7 +229,7 @@ class Krea2StyleReferenceNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Krea2StyleReferenceNode",
             display_name="Krea 2 Style Reference",
-            category="api node/image/Krea",
+            category="image/partner/Krea",
             description=(
                 "Add an image style reference to a Krea 2 generation. Chain multiple Krea 2 "
                 "Style Reference nodes (max 10) and feed the final `style_reference` output "

comfy_api_nodes/nodes_ltxv.py

@@ -50,7 +50,7 @@ class TextToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="LtxvApiTextToVideo",
             display_name="LTXV Text To Video",
-            category="api node/video/LTXV",
+            category="video/partner/LTXV",
             description="Professional-quality videos with customizable duration and resolution.",
             inputs=[
                 IO.Combo.Input("model", options=list(MODELS_MAP.keys())),
@@ -127,7 +127,7 @@ class ImageToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="LtxvApiImageToVideo",
             display_name="LTXV Image To Video",
-            category="api node/video/LTXV",
+            category="video/partner/LTXV",
             description="Professional-quality videos with customizable duration and resolution based on start image.",
             inputs=[
                 IO.Image.Input("image", tooltip="First frame to be used for the video."),

comfy_api_nodes/nodes_luma.py

@@ -46,7 +46,7 @@ class LumaReferenceNode(IO.ComfyNode):
         return IO.Schema(
             node_id="LumaReferenceNode",
             display_name="Luma Reference",
-            category="api node/image/Luma",
+            category="image/partner/Luma",
             description="Holds an image and weight for use with Luma Generate Image node.",
             inputs=[
                 IO.Image.Input(
@@ -85,7 +85,7 @@ class LumaConceptsNode(IO.ComfyNode):
         return IO.Schema(
             node_id="LumaConceptsNode",
             display_name="Luma Concepts",
-            category="api node/video/Luma",
+            category="video/partner/Luma",
             description="Camera Concepts for use with Luma Text to Video and Luma Image to Video nodes.",
             inputs=[
                 IO.Combo.Input(
@@ -134,7 +134,7 @@ class LumaImageGenerationNode(IO.ComfyNode):
         return IO.Schema(
             node_id="LumaImageNode",
             display_name="Luma Text to Image",
-            category="api node/image/Luma",
+            category="image/partner/Luma",
             description="Generates images synchronously based on prompt and aspect ratio.",
             inputs=[
                 IO.String.Input(
@@ -278,7 +278,7 @@ class LumaImageModifyNode(IO.ComfyNode):
         return IO.Schema(
             node_id="LumaImageModifyNode",
             display_name="Luma Image to Image",
-            category="api node/image/Luma",
+            category="image/partner/Luma",
             description="Modifies images synchronously based on prompt and aspect ratio.",
             inputs=[
                 IO.Image.Input(
@@ -371,7 +371,7 @@ class LumaTextToVideoGenerationNode(IO.ComfyNode):
         return IO.Schema(
             node_id="LumaVideoNode",
             display_name="Luma Text to Video",
-            category="api node/video/Luma",
+            category="video/partner/Luma",
             description="Generates videos synchronously based on prompt and output_size.",
             inputs=[
                 IO.String.Input(
@@ -472,7 +472,7 @@ class LumaImageToVideoGenerationNode(IO.ComfyNode):
         return IO.Schema(
             node_id="LumaImageToVideoNode",
             display_name="Luma Image to Video",
-            category="api node/video/Luma",
+            category="video/partner/Luma",
             description="Generates videos synchronously based on prompt, input images, and output_size.",
             inputs=[
                 IO.String.Input(
@@ -724,7 +724,7 @@ class LumaImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="LumaImageNode2",
             display_name="Luma UNI-1 Image",
-            category="api node/image/Luma",
+            category="image/partner/Luma",
             description="Generate images from text using the Luma UNI-1 model.",
             inputs=[
                 IO.String.Input(
@@ -853,7 +853,7 @@ class LumaImageEditNode(IO.ComfyNode):
         return IO.Schema(
             node_id="LumaImageEditNode2",
             display_name="Luma UNI-1 Image Edit",
-            category="api node/image/Luma",
+            category="image/partner/Luma",
             description="Edit an existing image with a text prompt using the Luma UNI-1 model.",
             inputs=[
                 IO.Image.Input(

comfy_api_nodes/nodes_magnific.py

@@ -61,7 +61,7 @@ class MagnificImageUpscalerCreativeNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MagnificImageUpscalerCreativeNode",
             display_name="Magnific Image Upscale (Creative)",
-            category="api node/image/Magnific",
+            category="image/partner/Magnific",
             description="Prompt‑guided enhancement, stylization, and 2x/4x/8x/16x upscaling. "
             "Maximum output: 25.3 megapixels.",
             inputs=[
@@ -240,7 +240,7 @@ class MagnificImageUpscalerPreciseV2Node(IO.ComfyNode):
         return IO.Schema(
             node_id="MagnificImageUpscalerPreciseV2Node",
             display_name="Magnific Image Upscale (Precise V2)",
-            category="api node/image/Magnific",
+            category="image/partner/Magnific",
             description="High-fidelity upscaling with fine control over sharpness, grain, and detail. "
             "Maximum output: 10060×10060 pixels.",
             inputs=[
@@ -400,7 +400,7 @@ class MagnificImageStyleTransferNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MagnificImageStyleTransferNode",
             display_name="Magnific Image Style Transfer",
-            category="api node/image/Magnific",
+            category="image/partner/Magnific",
             description="Transfer the style from a reference image to your input image.",
             inputs=[
                 IO.Image.Input("image", tooltip="The image to apply style transfer to."),
@@ -549,7 +549,7 @@ class MagnificImageRelightNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MagnificImageRelightNode",
             display_name="Magnific Image Relight",
-            category="api node/image/Magnific",
+            category="image/partner/Magnific",
             description="Relight an image with lighting adjustments and optional reference-based light transfer.",
             inputs=[
                 IO.Image.Input("image", tooltip="The image to relight."),
@@ -789,7 +789,7 @@ class MagnificImageSkinEnhancerNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MagnificImageSkinEnhancerNode",
             display_name="Magnific Image Skin Enhancer",
-            category="api node/image/Magnific",
+            category="image/partner/Magnific",
             description="Skin enhancement for portraits with multiple processing modes.",
             inputs=[
                 IO.Image.Input("image", tooltip="The portrait image to enhance."),

comfy_api_nodes/nodes_meshy.py

@@ -33,7 +33,7 @@ class MeshyTextToModelNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MeshyTextToModelNode",
             display_name="Meshy: Text to Model",
-            category="api node/3d/Meshy",
+            category="3d/partner/Meshy",
             inputs=[
                 IO.Combo.Input("model", options=["latest"]),
                 IO.String.Input("prompt", multiline=True, default=""),
@@ -145,7 +145,7 @@ class MeshyRefineNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MeshyRefineNode",
             display_name="Meshy: Refine Draft Model",
-            category="api node/3d/Meshy",
+            category="3d/partner/Meshy",
             description="Refine a previously created draft model.",
             inputs=[
                 IO.Combo.Input("model", options=["latest"]),
@@ -240,7 +240,7 @@ class MeshyImageToModelNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MeshyImageToModelNode",
             display_name="Meshy: Image to Model",
-            category="api node/3d/Meshy",
+            category="3d/partner/Meshy",
             inputs=[
                 IO.Combo.Input("model", options=["latest"]),
                 IO.Image.Input("image"),
@@ -405,7 +405,7 @@ class MeshyMultiImageToModelNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MeshyMultiImageToModelNode",
             display_name="Meshy: Multi-Image to Model",
-            category="api node/3d/Meshy",
+            category="3d/partner/Meshy",
             inputs=[
                 IO.Combo.Input("model", options=["latest"]),
                 IO.Autogrow.Input(
@@ -575,7 +575,7 @@ class MeshyRigModelNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MeshyRigModelNode",
             display_name="Meshy: Rig Model",
-            category="api node/3d/Meshy",
+            category="3d/partner/Meshy",
             description="Provides a rigged character in standard formats. "
             "Auto-rigging is currently not suitable for untextured meshes, non-humanoid assets, "
             "or humanoid assets with unclear limb and body structure.",
@@ -656,7 +656,7 @@ class MeshyAnimateModelNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MeshyAnimateModelNode",
             display_name="Meshy: Animate Model",
-            category="api node/3d/Meshy",
+            category="3d/partner/Meshy",
             description="Apply a specific animation action to a previously rigged character.",
             inputs=[
                 IO.Custom("MESHY_RIGGED_TASK_ID").Input("rig_task_id"),
@@ -722,7 +722,7 @@ class MeshyTextureNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MeshyTextureNode",
             display_name="Meshy: Texture Model",
-            category="api node/3d/Meshy",
+            category="3d/partner/Meshy",
             inputs=[
                 IO.Combo.Input("model", options=["latest"]),
                 IO.Custom("MESHY_TASK_ID").Input("meshy_task_id"),

comfy_api_nodes/nodes_minimax.py

@@ -101,7 +101,7 @@ class MinimaxTextToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MinimaxTextToVideoNode",
             display_name="MiniMax Text to Video",
-            category="api node/video/MiniMax",
+            category="video/partner/MiniMax",
             description="Generates videos synchronously based on a prompt, and optional parameters.",
             inputs=[
                 IO.String.Input(
@@ -163,7 +163,7 @@ class MinimaxImageToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MinimaxImageToVideoNode",
             display_name="MiniMax Image to Video",
-            category="api node/video/MiniMax",
+            category="video/partner/MiniMax",
             description="Generates videos synchronously based on an image and prompt, and optional parameters.",
             inputs=[
                 IO.Image.Input(
@@ -230,7 +230,7 @@ class MinimaxSubjectToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MinimaxSubjectToVideoNode",
             display_name="MiniMax Subject to Video",
-            category="api node/video/MiniMax",
+            category="video/partner/MiniMax",
             description="Generates videos synchronously based on an image and prompt, and optional parameters.",
             inputs=[
                 IO.Image.Input(
@@ -294,7 +294,7 @@ class MinimaxHailuoVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="MinimaxHailuoVideoNode",
             display_name="MiniMax Hailuo Video",
-            category="api node/video/MiniMax",
+            category="video/partner/MiniMax",
             description="Generates videos from prompt, with optional start frame using the new MiniMax Hailuo-02 model.",
             inputs=[
                 IO.String.Input(

comfy_api_nodes/nodes_openai.py

@@ -99,7 +99,7 @@ class OpenAIDalle2(IO.ComfyNode):
         return IO.Schema(
             node_id="OpenAIDalle2",
             display_name="OpenAI DALL·E 2",
-            category="api node/image/OpenAI",
+            category="image/partner/OpenAI",
             description="Generates images synchronously via OpenAI's DALL·E 2 endpoint.",
             inputs=[
                 IO.String.Input(
@@ -249,7 +249,7 @@ class OpenAIDalle3(IO.ComfyNode):
         return IO.Schema(
             node_id="OpenAIDalle3",
             display_name="OpenAI DALL·E 3",
-            category="api node/image/OpenAI",
+            category="image/partner/OpenAI",
             description="Generates images synchronously via OpenAI's DALL·E 3 endpoint.",
             inputs=[
                 IO.String.Input(
@@ -371,7 +371,7 @@ class OpenAIGPTImage1(IO.ComfyNode):
         return IO.Schema(
             node_id="OpenAIGPTImage1",
             display_name="OpenAI GPT Image 2",
-            category="api node/image/OpenAI",
+            category="image/partner/OpenAI",
             description="Generates images synchronously via OpenAI's GPT Image endpoint.",
             is_deprecated=True,
             inputs=[
@@ -695,7 +695,7 @@ class OpenAIGPTImageNodeV2(IO.ComfyNode):
         return IO.Schema(
             node_id="OpenAIGPTImageNodeV2",
             display_name="OpenAI GPT Image 2",
-            category="api node/image/OpenAI",
+            category="image/partner/OpenAI",
             description="Generates images via OpenAI's GPT Image endpoint.",
             inputs=[
                 IO.String.Input(
@@ -962,7 +962,7 @@ class OpenAIChatNode(IO.ComfyNode):
         return IO.Schema(
             node_id="OpenAIChatNode",
             display_name="OpenAI ChatGPT",
-            category="api node/text/OpenAI",
+            category="text/partner/OpenAI",
             essentials_category="Text Generation",
             description="Generate text responses from an OpenAI model.",
             inputs=[
@@ -1201,7 +1201,7 @@ class OpenAIInputFiles(IO.ComfyNode):
         return IO.Schema(
             node_id="OpenAIInputFiles",
             display_name="OpenAI ChatGPT Input Files",
-            category="api node/text/OpenAI",
+            category="text/partner/OpenAI",
             description="Loads and prepares input files (text, pdf, etc.) to include as inputs for the OpenAI Chat Node. The files will be read by the OpenAI model when generating a response. 🛈 TIP: Can be chained together with other OpenAI Input File nodes.",
             inputs=[
                 IO.Combo.Input(
@@ -1248,7 +1248,7 @@ class OpenAIChatConfig(IO.ComfyNode):
         return IO.Schema(
             node_id="OpenAIChatConfig",
             display_name="OpenAI ChatGPT Advanced Options",
-            category="api node/text/OpenAI",
+            category="text/partner/OpenAI",
             description="Allows specifying advanced configuration options for the OpenAI Chat Nodes.",
             inputs=[
                 IO.Combo.Input(

comfy_api_nodes/nodes_openrouter.py

@@ -265,7 +265,7 @@ class OpenRouterLLMNode(IO.ComfyNode):
         return IO.Schema(
             node_id="OpenRouterLLMNode",
             display_name="OpenRouter LLM",
-            category="api node/text/OpenRouter",
+            category="text/partner/OpenRouter",
             essentials_category="Text Generation",
             description=(
                 "Generate text responses through OpenRouter. Routes to a curated set of popular "

comfy_api_nodes/nodes_pixverse.py

@@ -53,7 +53,7 @@ class PixverseTemplateNode(IO.ComfyNode):
         return IO.Schema(
             node_id="PixverseTemplateNode",
             display_name="PixVerse Template",
-            category="api node/video/PixVerse",
+            category="video/partner/PixVerse",
             inputs=[
                 IO.Combo.Input("template", options=list(pixverse_templates.keys())),
             ],
@@ -74,7 +74,7 @@ class PixverseTextToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="PixverseTextToVideoNode",
             display_name="PixVerse Text to Video",
-            category="api node/video/PixVerse",
+            category="video/partner/PixVerse",
             description="Generates videos based on prompt and output_size.",
             inputs=[
                 IO.String.Input(
@@ -192,7 +192,7 @@ class PixverseImageToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="PixverseImageToVideoNode",
             display_name="PixVerse Image to Video",
-            category="api node/video/PixVerse",
+            category="video/partner/PixVerse",
             description="Generates videos based on prompt and output_size.",
             inputs=[
                 IO.Image.Input("image"),
@@ -310,7 +310,7 @@ class PixverseTransitionVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="PixverseTransitionVideoNode",
             display_name="PixVerse Transition Video",
-            category="api node/video/PixVerse",
+            category="video/partner/PixVerse",
             description="Generates videos based on prompt and output_size.",
             inputs=[
                 IO.Image.Input("first_frame"),

comfy_api_nodes/nodes_quiver.py

@@ -62,7 +62,7 @@ class QuiverTextToSVGNode(IO.ComfyNode):
         return IO.Schema(
             node_id="QuiverTextToSVGNode",
             display_name="Quiver Text to SVG",
-            category="api node/image/Quiver",
+            category="image/partner/Quiver",
             description="Generate an SVG from a text prompt using Quiver AI.",
             inputs=[
                 IO.String.Input(
@@ -177,7 +177,7 @@ class QuiverImageToSVGNode(IO.ComfyNode):
         return IO.Schema(
             node_id="QuiverImageToSVGNode",
             display_name="Quiver Image to SVG",
-            category="api node/image/Quiver",
+            category="image/partner/Quiver",
             description="Vectorize a raster image into SVG using Quiver AI.",
             inputs=[
                 IO.Image.Input(

comfy_api_nodes/nodes_recraft.py

@@ -178,7 +178,7 @@ class RecraftColorRGBNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftColorRGB",
             display_name="Recraft Color RGB",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Create Recraft Color by choosing specific RGB values.",
             inputs=[
                 IO.Int.Input("r", default=0, min=0, max=255, tooltip="Red value of color."),
@@ -204,7 +204,7 @@ class RecraftControlsNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftControls",
             display_name="Recraft Controls",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Create Recraft Controls for customizing Recraft generation.",
             inputs=[
                 IO.Custom(RecraftIO.COLOR).Input("colors", optional=True),
@@ -228,7 +228,7 @@ class RecraftStyleV3RealisticImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftStyleV3RealisticImage",
             display_name="Recraft Style - Realistic Image",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Select realistic_image style and optional substyle.",
             inputs=[
                 IO.Combo.Input("substyle", options=get_v3_substyles(cls.RECRAFT_STYLE)),
@@ -253,7 +253,7 @@ class RecraftStyleV3DigitalIllustrationNode(RecraftStyleV3RealisticImageNode):
         return IO.Schema(
             node_id="RecraftStyleV3DigitalIllustration",
             display_name="Recraft Style - Digital Illustration",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Select realistic_image style and optional substyle.",
             inputs=[
                 IO.Combo.Input("substyle", options=get_v3_substyles(cls.RECRAFT_STYLE)),
@@ -272,7 +272,7 @@ class RecraftStyleV3VectorIllustrationNode(RecraftStyleV3RealisticImageNode):
         return IO.Schema(
             node_id="RecraftStyleV3VectorIllustrationNode",
             display_name="Recraft Style - Realistic Image",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Select realistic_image style and optional substyle.",
             inputs=[
                 IO.Combo.Input("substyle", options=get_v3_substyles(cls.RECRAFT_STYLE)),
@@ -291,7 +291,7 @@ class RecraftStyleV3LogoRasterNode(RecraftStyleV3RealisticImageNode):
         return IO.Schema(
             node_id="RecraftStyleV3LogoRaster",
             display_name="Recraft Style - Logo Raster",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Select realistic_image style and optional substyle.",
             inputs=[
                 IO.Combo.Input("substyle", options=get_v3_substyles(cls.RECRAFT_STYLE, include_none=False)),
@@ -308,7 +308,7 @@ class RecraftStyleInfiniteStyleLibrary(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftStyleV3InfiniteStyleLibrary",
             display_name="Recraft Style - Infinite Style Library",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Choose style based on preexisting UUID from Recraft's Infinite Style Library.",
             inputs=[
                 IO.String.Input("style_id", default="", tooltip="UUID of style from Infinite Style Library."),
@@ -331,7 +331,7 @@ class RecraftCreateStyleNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftCreateStyleNode",
             display_name="Recraft Create Style",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Create a custom style from reference images. "
             "Upload 1-5 images to use as style references. "
             "Total size of all images is limited to 5 MB.",
@@ -400,7 +400,7 @@ class RecraftTextToImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftTextToImageNode",
             display_name="Recraft Text to Image",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Generates images synchronously based on prompt and resolution.",
             inputs=[
                 IO.String.Input("prompt", multiline=True, default="", tooltip="Prompt for the image generation."),
@@ -512,7 +512,7 @@ class RecraftImageToImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftImageToImageNode",
             display_name="Recraft Image to Image",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Modify image based on prompt and strength.",
             inputs=[
                 IO.Image.Input("image"),
@@ -630,7 +630,7 @@ class RecraftImageInpaintingNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftImageInpaintingNode",
             display_name="Recraft Image Inpainting",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Modify image based on prompt and mask.",
             inputs=[
                 IO.Image.Input("image"),
@@ -732,7 +732,7 @@ class RecraftTextToVectorNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftTextToVectorNode",
             display_name="Recraft Text to Vector",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Generates SVG synchronously based on prompt and resolution.",
             inputs=[
                 IO.String.Input("prompt", default="", tooltip="Prompt for the image generation.", multiline=True),
@@ -832,7 +832,7 @@ class RecraftVectorizeImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftVectorizeImageNode",
             display_name="Recraft Vectorize Image",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             essentials_category="Image Tools",
             description="Generates SVG synchronously from an input image.",
             inputs=[
@@ -876,7 +876,7 @@ class RecraftReplaceBackgroundNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftReplaceBackgroundNode",
             display_name="Recraft Replace Background",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Replace background on image, based on provided prompt.",
             inputs=[
                 IO.Image.Input("image"),
@@ -963,7 +963,7 @@ class RecraftRemoveBackgroundNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftRemoveBackgroundNode",
             display_name="Recraft Remove Background",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             essentials_category="Image Tools",
             description="Remove background from image, and return processed image and mask.",
             inputs=[
@@ -1012,7 +1012,7 @@ class RecraftCrispUpscaleNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftCrispUpscaleNode",
             display_name="Recraft Crisp Upscale Image",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Upscale image synchronously.\n"
             "Enhances a given raster image using ‘crisp upscale’ tool, "
             "increasing image resolution, making the image sharper and cleaner.",
@@ -1058,7 +1058,7 @@ class RecraftCreativeUpscaleNode(RecraftCrispUpscaleNode):
         return IO.Schema(
             node_id="RecraftCreativeUpscaleNode",
             display_name="Recraft Creative Upscale Image",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Upscale image synchronously.\n"
             "Enhances a given raster image using ‘creative upscale’ tool, "
             "boosting resolution with a focus on refining small details and faces.",
@@ -1086,7 +1086,7 @@ class RecraftV4TextToImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftV4TextToImageNode",
             display_name="Recraft V4 Text to Image",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Generates images using Recraft V4 or V4 Pro models.",
             inputs=[
                 IO.String.Input(
@@ -1210,7 +1210,7 @@ class RecraftV4TextToVectorNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RecraftV4TextToVectorNode",
             display_name="Recraft V4 Text to Vector",
-            category="api node/image/Recraft",
+            category="image/partner/Recraft",
             description="Generates SVG using Recraft V4 or V4 Pro models.",
             inputs=[
                 IO.String.Input(

comfy_api_nodes/nodes_reve.py

@@ -109,7 +109,7 @@ class ReveImageCreateNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ReveImageCreateNode",
             display_name="Reve Image Create",
-            category="api node/image/Reve",
+            category="image/partner/Reve",
             description="Generate images from text descriptions using Reve.",
             inputs=[
                 IO.String.Input(
@@ -200,7 +200,7 @@ class ReveImageEditNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ReveImageEditNode",
             display_name="Reve Image Edit",
-            category="api node/image/Reve",
+            category="image/partner/Reve",
             description="Edit images using natural language instructions with Reve.",
             inputs=[
                 IO.Image.Input("image", tooltip="The image to edit."),
@@ -300,7 +300,7 @@ class ReveImageRemixNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ReveImageRemixNode",
             display_name="Reve Image Remix",
-            category="api node/image/Reve",
+            category="image/partner/Reve",
             description="Combine reference images with text prompts to create new images using Reve.",
             inputs=[
                 IO.Autogrow.Input(

comfy_api_nodes/nodes_rodin.py

@@ -230,7 +230,7 @@ class Rodin3D_Regular(IO.ComfyNode):
         return IO.Schema(
             node_id="Rodin3D_Regular",
             display_name="Rodin 3D Generate - Regular Generate",
-            category="api node/3d/Rodin",
+            category="3d/partner/Rodin",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.Image.Input("Images"),
@@ -289,7 +289,7 @@ class Rodin3D_Detail(IO.ComfyNode):
         return IO.Schema(
             node_id="Rodin3D_Detail",
             display_name="Rodin 3D Generate - Detail Generate",
-            category="api node/3d/Rodin",
+            category="3d/partner/Rodin",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.Image.Input("Images"),
@@ -348,7 +348,7 @@ class Rodin3D_Smooth(IO.ComfyNode):
         return IO.Schema(
             node_id="Rodin3D_Smooth",
             display_name="Rodin 3D Generate - Smooth Generate",
-            category="api node/3d/Rodin",
+            category="3d/partner/Rodin",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.Image.Input("Images"),
@@ -406,7 +406,7 @@ class Rodin3D_Sketch(IO.ComfyNode):
         return IO.Schema(
             node_id="Rodin3D_Sketch",
             display_name="Rodin 3D Generate - Sketch Generate",
-            category="api node/3d/Rodin",
+            category="3d/partner/Rodin",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.Image.Input("Images"),
@@ -468,7 +468,7 @@ class Rodin3D_Gen2(IO.ComfyNode):
         return IO.Schema(
             node_id="Rodin3D_Gen2",
             display_name="Rodin 3D Generate - Gen-2 Generate",
-            category="api node/3d/Rodin",
+            category="3d/partner/Rodin",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.Image.Input("Images"),
@@ -941,7 +941,7 @@ class Rodin3D_Gen25_Image(IO.ComfyNode):
         return IO.Schema(
             node_id="Rodin3D_Gen25_Image",
             display_name="Rodin 3D Gen-2.5 - Image to 3D",
-            category="api node/3d/Rodin",
+            category="3d/partner/Rodin",
             description=(
                 "Generate a 3D model from 1-5 reference images via Rodin Gen-2.5. "
                 "Pick a mode (Fast / Regular / Extreme-High) to tune quality vs. cost."
@@ -1035,7 +1035,7 @@ class Rodin3D_Gen25_Text(IO.ComfyNode):
         return IO.Schema(
             node_id="Rodin3D_Gen25_Text",
             display_name="Rodin 3D Gen-2.5 - Text to 3D",
-            category="api node/3d/Rodin",
+            category="3d/partner/Rodin",
             description=(
                 "Generate a 3D model from a text prompt via Rodin Gen-2.5. "
                 "Pick a mode (Fast / Regular / Extreme-High) to tune quality vs. cost."

comfy_api_nodes/nodes_runway.py

@@ -140,7 +140,7 @@ class RunwayImageToVideoNodeGen3a(IO.ComfyNode):
         return IO.Schema(
             node_id="RunwayImageToVideoNodeGen3a",
             display_name="Runway Image to Video (Gen3a Turbo)",
-            category="api node/video/Runway",
+            category="video/partner/Runway",
             description="Generate a video from a single starting frame using Gen3a Turbo model. "
             "Before diving in, review these best practices to ensure that "
             "your input selections will set your generation up for success: "
@@ -234,7 +234,7 @@ class RunwayImageToVideoNodeGen4(IO.ComfyNode):
         return IO.Schema(
             node_id="RunwayImageToVideoNodeGen4",
             display_name="Runway Image to Video (Gen4 Turbo)",
-            category="api node/video/Runway",
+            category="video/partner/Runway",
             description="Generate a video from a single starting frame using Gen4 Turbo model. "
             "Before diving in, review these best practices to ensure that "
             "your input selections will set your generation up for success: "
@@ -329,7 +329,7 @@ class RunwayFirstLastFrameNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RunwayFirstLastFrameNode",
             display_name="Runway First-Last-Frame to Video",
-            category="api node/video/Runway",
+            category="video/partner/Runway",
             description="Upload first and last keyframes, draft a prompt, and generate a video. "
             "More complex transitions, such as cases where the Last frame is completely different "
             "from the First frame, may benefit from the longer 10s duration. "
@@ -440,7 +440,7 @@ class RunwayTextToImageNode(IO.ComfyNode):
         return IO.Schema(
             node_id="RunwayTextToImageNode",
             display_name="Runway Text to Image",
-            category="api node/image/Runway",
+            category="image/partner/Runway",
             description="Generate an image from a text prompt using Runway's Gen 4 model. "
             "You can also include reference image to guide the generation.",
             inputs=[

comfy_api_nodes/nodes_sonilo.py

@@ -34,7 +34,7 @@ class SoniloVideoToMusic(IO.ComfyNode):
         return IO.Schema(
             node_id="SoniloVideoToMusic",
             display_name="Sonilo Video to Music",
-            category="api node/audio/Sonilo",
+            category="audio/partner/Sonilo",
             description="Generate music from video content using Sonilo's AI model. "
             "Analyzes the video and creates matching music.",
             inputs=[
@@ -99,7 +99,7 @@ class SoniloTextToMusic(IO.ComfyNode):
         return IO.Schema(
             node_id="SoniloTextToMusic",
             display_name="Sonilo Text to Music",
-            category="api node/audio/Sonilo",
+            category="audio/partner/Sonilo",
             description="Generate music from a text prompt using Sonilo's AI model. "
             "Leave duration at 0 to let the model infer it from the prompt.",
             inputs=[

comfy_api_nodes/nodes_sora.py

@@ -34,7 +34,7 @@ class OpenAIVideoSora2(IO.ComfyNode):
         return IO.Schema(
             node_id="OpenAIVideoSora2",
             display_name="OpenAI Sora - Video (DEPRECATED)",
-            category="api node/video/Sora",
+            category="video/partner/Sora",
             description=(
                 "OpenAI video and audio generation.\n\n"
                 "DEPRECATION NOTICE: OpenAI will stop serving the Sora v2 API in September 2026. "

comfy_api_nodes/nodes_stability.py

@@ -62,7 +62,7 @@ class StabilityStableImageUltraNode(IO.ComfyNode):
         return IO.Schema(
             node_id="StabilityStableImageUltraNode",
             display_name="Stability AI Stable Image Ultra",
-            category="api node/image/Stability AI",
+            category="image/partner/Stability AI",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.String.Input(
@@ -197,7 +197,7 @@ class StabilityStableImageSD_3_5Node(IO.ComfyNode):
         return IO.Schema(
             node_id="StabilityStableImageSD_3_5Node",
             display_name="Stability AI Stable Diffusion 3.5 Image",
-            category="api node/image/Stability AI",
+            category="image/partner/Stability AI",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.String.Input(
@@ -354,7 +354,7 @@ class StabilityUpscaleConservativeNode(IO.ComfyNode):
         return IO.Schema(
             node_id="StabilityUpscaleConservativeNode",
             display_name="Stability AI Upscale Conservative",
-            category="api node/image/Stability AI",
+            category="image/partner/Stability AI",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.Image.Input("image"),
@@ -457,7 +457,7 @@ class StabilityUpscaleCreativeNode(IO.ComfyNode):
         return IO.Schema(
             node_id="StabilityUpscaleCreativeNode",
             display_name="Stability AI Upscale Creative",
-            category="api node/image/Stability AI",
+            category="image/partner/Stability AI",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.Image.Input("image"),
@@ -578,7 +578,7 @@ class StabilityUpscaleFastNode(IO.ComfyNode):
         return IO.Schema(
             node_id="StabilityUpscaleFastNode",
             display_name="Stability AI Upscale Fast",
-            category="api node/image/Stability AI",
+            category="image/partner/Stability AI",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.Image.Input("image"),
@@ -630,7 +630,7 @@ class StabilityTextToAudio(IO.ComfyNode):
         return IO.Schema(
             node_id="StabilityTextToAudio",
             display_name="Stability AI Text To Audio",
-            category="api node/audio/Stability AI",
+            category="audio/partner/Stability AI",
             essentials_category="Audio",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
@@ -708,7 +708,7 @@ class StabilityAudioToAudio(IO.ComfyNode):
         return IO.Schema(
             node_id="StabilityAudioToAudio",
             display_name="Stability AI Audio To Audio",
-            category="api node/audio/Stability AI",
+            category="audio/partner/Stability AI",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.Combo.Input(
@@ -802,7 +802,7 @@ class StabilityAudioInpaint(IO.ComfyNode):
         return IO.Schema(
             node_id="StabilityAudioInpaint",
             display_name="Stability AI Audio Inpaint",
-            category="api node/audio/Stability AI",
+            category="audio/partner/Stability AI",
             description=cleandoc(cls.__doc__ or ""),
             inputs=[
                 IO.Combo.Input(

comfy_api_nodes/nodes_topaz.py

@@ -52,7 +52,7 @@ class TopazImageEnhance(IO.ComfyNode):
         return IO.Schema(
             node_id="TopazImageEnhance",
             display_name="Topaz Image Enhance",
-            category="api node/image/Topaz",
+            category="image/partner/Topaz",
             description="Industry-standard upscaling and image enhancement.",
             inputs=[
                 IO.Combo.Input("model", options=["Reimagine"]),
@@ -235,7 +235,7 @@ class TopazVideoEnhance(IO.ComfyNode):
         return IO.Schema(
             node_id="TopazVideoEnhance",
             display_name="Topaz Video Enhance (Legacy)",
-            category="api node/video/Topaz",
+            category="video/partner/Topaz",
             description="Breathe new life into video with powerful upscaling and recovery technology.",
             inputs=[
                 IO.Video.Input("video"),
@@ -475,7 +475,7 @@ class TopazVideoEnhanceV2(IO.ComfyNode):
         return IO.Schema(
             node_id="TopazVideoEnhanceV2",
             display_name="Topaz Video Enhance",
-            category="api node/video/Topaz",
+            category="video/partner/Topaz",
             description="Breathe new life into video with powerful upscaling and recovery technology.",
             inputs=[
                 IO.Video.Input("video"),

comfy_api_nodes/nodes_tripo.py

@@ -80,7 +80,7 @@ class TripoTextToModelNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TripoTextToModelNode",
             display_name="Tripo: Text to Model",
-            category="api node/3d/Tripo",
+            category="3d/partner/Tripo",
             inputs=[
                 IO.String.Input("prompt", multiline=True),
                 IO.String.Input("negative_prompt", multiline=True, optional=True),
@@ -195,7 +195,7 @@ class TripoImageToModelNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TripoImageToModelNode",
             display_name="Tripo: Image to Model",
-            category="api node/3d/Tripo",
+            category="3d/partner/Tripo",
             inputs=[
                 IO.Image.Input("image"),
                 IO.Combo.Input(
@@ -323,7 +323,7 @@ class TripoMultiviewToModelNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TripoMultiviewToModelNode",
             display_name="Tripo: Multiview to Model",
-            category="api node/3d/Tripo",
+            category="3d/partner/Tripo",
             inputs=[
                 IO.Image.Input("image"),
                 IO.Image.Input("image_left", optional=True),
@@ -461,7 +461,7 @@ class TripoTextureNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TripoTextureNode",
             display_name="Tripo: Texture model",
-            category="api node/3d/Tripo",
+            category="3d/partner/Tripo",
             inputs=[
                 IO.Custom("MODEL_TASK_ID").Input("model_task_id"),
                 IO.Boolean.Input("texture", default=True, optional=True),
@@ -528,7 +528,7 @@ class TripoRefineNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TripoRefineNode",
             display_name="Tripo: Refine Draft model",
-            category="api node/3d/Tripo",
+            category="3d/partner/Tripo",
             description="Refine a draft model created by v1.4 Tripo models only.",
             inputs=[
                 IO.Custom("MODEL_TASK_ID").Input("model_task_id", tooltip="Must be a v1.4 Tripo model"),
@@ -568,7 +568,7 @@ class TripoRigNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TripoRigNode",
             display_name="Tripo: Rig model",
-            category="api node/3d/Tripo",
+            category="3d/partner/Tripo",
             inputs=[IO.Custom("MODEL_TASK_ID").Input("original_model_task_id")],
             outputs=[
                 IO.String.Output(display_name="model_file"),  # for backward compatibility only
@@ -605,7 +605,7 @@ class TripoRetargetNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TripoRetargetNode",
             display_name="Tripo: Retarget rigged model",
-            category="api node/3d/Tripo",
+            category="3d/partner/Tripo",
             inputs=[
                 IO.Custom("RIG_TASK_ID").Input("original_model_task_id"),
                 IO.Combo.Input(
@@ -670,7 +670,7 @@ class TripoConversionNode(IO.ComfyNode):
         return IO.Schema(
             node_id="TripoConversionNode",
             display_name="Tripo: Convert model",
-            category="api node/3d/Tripo",
+            category="3d/partner/Tripo",
             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"]),

comfy_api_nodes/nodes_veo2.py

@@ -45,7 +45,7 @@ class VeoVideoGenerationNode(IO.ComfyNode):
         return IO.Schema(
             node_id="VeoVideoGenerationNode",
             display_name="Google Veo 2 Video Generation",
-            category="api node/video/Veo",
+            category="video/partner/Veo",
             description="Generates videos from text prompts using Google's Veo 2 API",
             inputs=[
                 IO.String.Input(
@@ -256,7 +256,7 @@ class Veo3VideoGenerationNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Veo3VideoGenerationNode",
             display_name="Google Veo 3 Video Generation",
-            category="api node/video/Veo",
+            category="video/partner/Veo",
             description="Generates videos from text prompts using Google's Veo 3 API",
             inputs=[
                 IO.String.Input(
@@ -468,7 +468,7 @@ class Veo3FirstLastFrameNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Veo3FirstLastFrameNode",
             display_name="Google Veo 3 First-Last-Frame to Video",
-            category="api node/video/Veo",
+            category="video/partner/Veo",
             description="Generate video using prompt and first and last frames.",
             inputs=[
                 IO.String.Input(

comfy_api_nodes/nodes_vidu.py

@@ -71,7 +71,7 @@ class ViduTextToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ViduTextToVideoNode",
             display_name="Vidu Text To Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate video from a text prompt",
             inputs=[
                 IO.Combo.Input("model", options=["viduq1"], tooltip="Model name"),
@@ -169,7 +169,7 @@ class ViduImageToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ViduImageToVideoNode",
             display_name="Vidu Image To Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate video from image and optional prompt",
             inputs=[
                 IO.Combo.Input("model", options=["viduq1"], tooltip="Model name"),
@@ -273,7 +273,7 @@ class ViduReferenceVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ViduReferenceVideoNode",
             display_name="Vidu Reference To Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate video from multiple images and a prompt",
             inputs=[
                 IO.Combo.Input("model", options=["viduq1"], tooltip="Model name"),
@@ -388,7 +388,7 @@ class ViduStartEndToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ViduStartEndToVideoNode",
             display_name="Vidu Start End To Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate a video from start and end frames and a prompt",
             inputs=[
                 IO.Combo.Input("model", options=["viduq1"], tooltip="Model name"),
@@ -492,7 +492,7 @@ class Vidu2TextToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Vidu2TextToVideoNode",
             display_name="Vidu2 Text-to-Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate video from a text prompt",
             inputs=[
                 IO.Combo.Input("model", options=["viduq2"]),
@@ -584,7 +584,7 @@ class Vidu2ImageToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Vidu2ImageToVideoNode",
             display_name="Vidu2 Image-to-Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate a video from an image and an optional prompt.",
             inputs=[
                 IO.Combo.Input("model", options=["viduq2-pro-fast", "viduq2-pro", "viduq2-turbo"]),
@@ -714,7 +714,7 @@ class Vidu2ReferenceVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Vidu2ReferenceVideoNode",
             display_name="Vidu2 Reference-to-Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate a video from multiple reference images and a prompt.",
             inputs=[
                 IO.Combo.Input("model", options=["viduq2"]),
@@ -849,7 +849,7 @@ class Vidu2StartEndToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Vidu2StartEndToVideoNode",
             display_name="Vidu2 Start/End Frame-to-Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate a video from a start frame, an end frame, and a prompt.",
             inputs=[
                 IO.Combo.Input("model", options=["viduq2-pro-fast", "viduq2-pro", "viduq2-turbo"]),
@@ -969,7 +969,7 @@ class ViduExtendVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ViduExtendVideoNode",
             display_name="Vidu Video Extension",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Extend an existing video by generating additional frames.",
             inputs=[
                 IO.DynamicCombo.Input(
@@ -1138,7 +1138,7 @@ class ViduMultiFrameVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="ViduMultiFrameVideoNode",
             display_name="Vidu Multi-Frame Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate a video with multiple keyframe transitions.",
             inputs=[
                 IO.Combo.Input("model", options=["viduq2-pro", "viduq2-turbo"]),
@@ -1284,7 +1284,7 @@ class Vidu3TextToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Vidu3TextToVideoNode",
             display_name="Vidu Q3 Text-to-Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate video from a text prompt.",
             inputs=[
                 IO.DynamicCombo.Input(
@@ -1429,7 +1429,7 @@ class Vidu3ImageToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Vidu3ImageToVideoNode",
             display_name="Vidu Q3 Image-to-Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate a video from an image and an optional prompt.",
             inputs=[
                 IO.DynamicCombo.Input(
@@ -1571,7 +1571,7 @@ class Vidu3StartEndToVideoNode(IO.ComfyNode):
         return IO.Schema(
             node_id="Vidu3StartEndToVideoNode",
             display_name="Vidu Q3 Start/End Frame-to-Video Generation",
-            category="api node/video/Vidu",
+            category="video/partner/Vidu",
             description="Generate a video from a start frame, an end frame, and a prompt.",
             inputs=[
                 IO.DynamicCombo.Input(

comfy_api_nodes/nodes_wan.py

@@ -61,7 +61,7 @@ class WanTextToImageApi(IO.ComfyNode):
         return IO.Schema(
             node_id="WanTextToImageApi",
             display_name="Wan Text to Image",
-            category="api node/image/Wan",
+            category="image/partner/Wan",
             description="Generates an image based on a text prompt.",
             inputs=[
                 IO.Combo.Input(
@@ -184,7 +184,7 @@ class WanImageToImageApi(IO.ComfyNode):
         return IO.Schema(
             node_id="WanImageToImageApi",
             display_name="Wan Image to Image",
-            category="api node/image/Wan",
+            category="image/partner/Wan",
             description="Generates an image from one or two input images and a text prompt. "
             "The output image is currently fixed at 1.6 MP, and its aspect ratio matches the input image(s).",
             inputs=[
@@ -312,7 +312,7 @@ class WanTextToVideoApi(IO.ComfyNode):
         return IO.Schema(
             node_id="WanTextToVideoApi",
             display_name="Wan Text to Video",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Generates a video based on a text prompt.",
             inputs=[
                 IO.Combo.Input(
@@ -495,7 +495,7 @@ class WanImageToVideoApi(IO.ComfyNode):
         return IO.Schema(
             node_id="WanImageToVideoApi",
             display_name="Wan Image to Video",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Generates a video from the first frame and a text prompt.",
             inputs=[
                 IO.Combo.Input(
@@ -674,7 +674,7 @@ class WanReferenceVideoApi(IO.ComfyNode):
         return IO.Schema(
             node_id="WanReferenceVideoApi",
             display_name="Wan Reference to Video",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Use the character and voice from input videos, combined with a prompt, "
             "to generate a new video that maintains character consistency.",
             inputs=[
@@ -828,7 +828,7 @@ class Wan2TextToVideoApi(IO.ComfyNode):
         return IO.Schema(
             node_id="Wan2TextToVideoApi",
             display_name="Wan 2.7 Text to Video",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Generates a video based on a text prompt using the Wan 2.7 model.",
             inputs=[
                 IO.DynamicCombo.Input(
@@ -981,7 +981,7 @@ class Wan2ImageToVideoApi(IO.ComfyNode):
         return IO.Schema(
             node_id="Wan2ImageToVideoApi",
             display_name="Wan 2.7 Image to Video",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Generate a video from a first-frame image, with optional last-frame image and audio.",
             inputs=[
                 IO.DynamicCombo.Input(
@@ -1152,7 +1152,7 @@ class Wan2VideoContinuationApi(IO.ComfyNode):
         return IO.Schema(
             node_id="Wan2VideoContinuationApi",
             display_name="Wan 2.7 Video Continuation",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Continue a video from where it left off, with optional last-frame control.",
             inputs=[
                 IO.DynamicCombo.Input(
@@ -1319,7 +1319,7 @@ class Wan2VideoEditApi(IO.ComfyNode):
         return IO.Schema(
             node_id="Wan2VideoEditApi",
             display_name="Wan 2.7 Video Edit",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Edit a video using text instructions, reference images, or style transfer.",
             inputs=[
                 IO.DynamicCombo.Input(
@@ -1477,7 +1477,7 @@ class Wan2ReferenceVideoApi(IO.ComfyNode):
         return IO.Schema(
             node_id="Wan2ReferenceVideoApi",
             display_name="Wan 2.7 Reference to Video",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Generate a video featuring a person or object from reference materials. "
             "Supports single-character performances and multi-character interactions.",
             inputs=[
@@ -1651,7 +1651,7 @@ class HappyHorseTextToVideoApi(IO.ComfyNode):
         return IO.Schema(
             node_id="HappyHorseTextToVideoApi",
             display_name="HappyHorse Text to Video",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Generates a video based on a text prompt using the HappyHorse model.",
             inputs=[
                 IO.DynamicCombo.Input(
@@ -1775,7 +1775,7 @@ class HappyHorseImageToVideoApi(IO.ComfyNode):
         return IO.Schema(
             node_id="HappyHorseImageToVideoApi",
             display_name="HappyHorse Image to Video",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Generate a video from a first-frame image using the HappyHorse model.",
             inputs=[
                 IO.DynamicCombo.Input(
@@ -1905,7 +1905,7 @@ class HappyHorseVideoEditApi(IO.ComfyNode):
         return IO.Schema(
             node_id="HappyHorseVideoEditApi",
             display_name="HappyHorse Video Edit",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Edit a video using text instructions or reference images with the HappyHorse model. "
             "Output duration is 3-15s and matches the input video; inputs longer than 15s are truncated.",
             inputs=[
@@ -2046,7 +2046,7 @@ class HappyHorseReferenceVideoApi(IO.ComfyNode):
         return IO.Schema(
             node_id="HappyHorseReferenceVideoApi",
             display_name="HappyHorse Reference to Video",
-            category="api node/video/Wan",
+            category="video/partner/Wan",
             description="Generate a video featuring a person or object from reference materials with the HappyHorse "
             "model. Supports single-character performances and multi-character interactions.",
             inputs=[

comfy_api_nodes/nodes_wavespeed.py

@@ -27,7 +27,7 @@ class WavespeedFlashVSRNode(IO.ComfyNode):
         return IO.Schema(
             node_id="WavespeedFlashVSRNode",
             display_name="FlashVSR Video Upscale",
-            category="api node/video/WaveSpeed",
+            category="video/partner/WaveSpeed",
             description="Fast, high-quality video upscaler that "
             "boosts resolution and restores clarity for low-resolution or blurry footage.",
             inputs=[
@@ -98,7 +98,7 @@ class WavespeedImageUpscaleNode(IO.ComfyNode):
         return IO.Schema(
             node_id="WavespeedImageUpscaleNode",
             display_name="WaveSpeed Image Upscale",
-            category="api node/image/WaveSpeed",
+            category="image/partner/WaveSpeed",
             description="Boost image resolution and quality, upscaling photos to 4K or 8K for sharp, detailed results.",
             inputs=[
                 IO.Combo.Input("model", options=["SeedVR2", "Ultimate"]),

comfy_api_nodes/util/client.py

@@ -86,7 +86,7 @@ class _PollUIState:
 _RETRY_STATUS = {408, 500, 502, 503, 504}  # status 429 is handled separately
 COMPLETED_STATUSES = ["succeeded", "succeed", "success", "completed", "finished", "done", "complete"]
 FAILED_STATUSES = ["cancelled", "canceled", "canceling", "fail", "failed", "error"]
-QUEUED_STATUSES = ["created", "queued", "queueing", "submitted", "initializing", "wait"]
+QUEUED_STATUSES = ["created", "queued", "queueing", "submitted", "initializing", "wait", "in_queue"]
 
 
 async def sync_op(

comfy_extras/nodes_ace.py

@@ -11,7 +11,7 @@ class TextEncodeAceStepAudio(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="TextEncodeAceStepAudio",
-            category="conditioning",
+            category="model/conditioning",
             inputs=[
                 IO.Clip.Input("clip"),
                 IO.String.Input("tags", multiline=True, dynamic_prompts=True),
@@ -33,7 +33,7 @@ class TextEncodeAceStepAudio15(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="TextEncodeAceStepAudio1.5",
-            category="conditioning",
+            category="model/conditioning",
             inputs=[
                 IO.Clip.Input("clip"),
                 IO.String.Input("tags", multiline=True, dynamic_prompts=True),
@@ -67,7 +67,7 @@ class EmptyAceStepLatentAudio(IO.ComfyNode):
         return IO.Schema(
             node_id="EmptyAceStepLatentAudio",
             display_name="Empty Ace Step 1.0 Latent Audio",
-            category="latent/audio",
+            category="model/latent/audio",
             inputs=[
                 IO.Float.Input("seconds", default=120.0, min=1.0, max=1000.0, step=0.1),
                 IO.Int.Input(
@@ -90,7 +90,7 @@ class EmptyAceStep15LatentAudio(IO.ComfyNode):
         return IO.Schema(
             node_id="EmptyAceStep1.5LatentAudio",
             display_name="Empty Ace Step 1.5 Latent Audio",
-            category="latent/audio",
+            category="model/latent/audio",
             inputs=[
                 IO.Float.Input("seconds", default=120.0, min=1.0, max=1000.0, step=0.01),
                 IO.Int.Input(

comfy_extras/nodes_advanced_samplers.py

@@ -45,7 +45,7 @@ class SamplerLCMUpscale(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="SamplerLCMUpscale",
-            category="sampling/samplers",
+            category="model/sampling/samplers",
             inputs=[
                 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),
@@ -91,7 +91,7 @@ class SamplerLCM(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="SamplerLCM",
-            category="sampling/samplers",
+            category="model/sampling/samplers",
             description=("LCM sampler with tunable per-step noise. s_noise is a multiplier on the model's training noise scale"),
             inputs=[
                 io.Float.Input("s_noise", default=1.0, min=0.0, max=64.0, step=0.01,

comfy_extras/nodes_align_your_steps.py

@@ -29,7 +29,7 @@ class AlignYourStepsScheduler(io.ComfyNode):
         return io.Schema(
             node_id="AlignYourStepsScheduler",
             search_aliases=["AYS scheduler"],
-            category="sampling/schedulers",
+            category="model/sampling/schedulers",
             inputs=[
                 io.Combo.Input("model_type", options=["SD1", "SDXL", "SVD"]),
                 io.Int.Input("steps", default=10, min=1, max=10000),

comfy_extras/nodes_apg.py

@@ -16,7 +16,7 @@ class APG(io.ComfyNode):
         return io.Schema(
             node_id="APG",
             display_name="Adaptive Projected Guidance",
-            category="sampling/custom_sampling",
+            category="model/sampling/custom_sampling",
             inputs=[
                 io.Model.Input("model"),
                 io.Float.Input(

comfy_extras/nodes_ar_video.py

@@ -19,7 +19,7 @@ class EmptyARVideoLatent(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="EmptyARVideoLatent",
-            category="latent/video",
+            category="model/latent/video",
             inputs=[
                 io.Int.Input("width", default=832, min=16, max=8192, step=16),
                 io.Int.Input("height", default=480, min=16, max=8192, step=16),
@@ -53,7 +53,7 @@ class SamplerARVideo(io.ComfyNode):
         return io.Schema(
             node_id="SamplerARVideo",
             display_name="Sampler AR Video",
-            category="sampling/samplers",
+            category="model/sampling/samplers",
             inputs=[
                 io.Int.Input(
                     "num_frame_per_block",
@@ -85,7 +85,7 @@ class ARVideoI2V(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="ARVideoI2V",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Model.Input("model"),
                 io.Vae.Input("vae"),

comfy_extras/nodes_audio.py

@@ -16,7 +16,7 @@ class EmptyLatentAudio(IO.ComfyNode):
         return IO.Schema(
             node_id="EmptyLatentAudio",
             display_name="Empty Latent Audio",
-            category="latent/audio",
+            category="model/latent/audio",
             essentials_category="Audio",
             inputs=[
                 IO.Float.Input("seconds", default=47.6, min=1.0, max=1000.0, step=0.1),
@@ -41,7 +41,7 @@ class ConditioningStableAudio(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="ConditioningStableAudio",
-            category="conditioning",
+            category="model/conditioning",
             inputs=[
                 IO.Conditioning.Input("positive"),
                 IO.Conditioning.Input("negative"),
@@ -70,7 +70,7 @@ class VAEEncodeAudio(IO.ComfyNode):
             node_id="VAEEncodeAudio",
             search_aliases=["audio to latent"],
             display_name="VAE Encode Audio",
-            category="latent/audio",
+            category="model/latent/audio",
             inputs=[
                 IO.Audio.Input("audio"),
                 IO.Vae.Input("vae"),
@@ -115,7 +115,7 @@ class VAEDecodeAudio(IO.ComfyNode):
             node_id="VAEDecodeAudio",
             search_aliases=["latent to audio"],
             display_name="VAE Decode Audio",
-            category="latent/audio",
+            category="model/latent/audio",
             inputs=[
                 IO.Latent.Input("samples"),
                 IO.Vae.Input("vae"),
@@ -137,7 +137,7 @@ class VAEDecodeAudioTiled(IO.ComfyNode):
             node_id="VAEDecodeAudioTiled",
             search_aliases=["latent to audio"],
             display_name="VAE Decode Audio (Tiled)",
-            category="latent/audio",
+            category="model/latent/audio",
             inputs=[
                 IO.Latent.Input("samples"),
                 IO.Vae.Input("vae"),

comfy_extras/nodes_audio_encoder.py

@@ -11,7 +11,7 @@ class AudioEncoderLoader(io.ComfyNode):
         return io.Schema(
             node_id="AudioEncoderLoader",
             display_name="Load Audio Encoder",
-            category="loaders",
+            category="model/loaders",
             inputs=[
                 io.Combo.Input(
                     "audio_encoder_name",
@@ -36,7 +36,7 @@ class AudioEncoderEncode(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="AudioEncoderEncode",
-            category="conditioning",
+            category="model/conditioning",
             inputs=[
                 io.AudioEncoder.Input("audio_encoder"),
                 io.Audio.Input("audio"),

comfy_extras/nodes_bg_removal.py

@@ -11,7 +11,7 @@ class LoadBackgroundRemovalModel(IO.ComfyNode):
         return IO.Schema(
             node_id="LoadBackgroundRemovalModel",
             display_name="Load Background Removal Model",
-            category="loaders",
+            category="model/loaders",
             inputs=[
                 IO.Combo.Input("bg_removal_name", options=sorted(files), tooltip="The model used to remove backgrounds from images"),
             ],

comfy_extras/nodes_camera_trajectory.py

@@ -153,7 +153,7 @@ class WanCameraEmbedding(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="WanCameraEmbedding",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Combo.Input(
                     "camera_pose",

comfy_extras/nodes_chroma_radiance.py

@@ -13,7 +13,7 @@ class EmptyChromaRadianceLatentImage(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="EmptyChromaRadianceLatentImage",
-            category="latent/chroma_radiance",
+            category="model/latent/chroma_radiance",
             inputs=[
                 io.Int.Input(id="width", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),
                 io.Int.Input(id="height", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),
@@ -33,7 +33,7 @@ class ChromaRadianceOptions(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="ChromaRadianceOptions",
-            category="model_patches/chroma_radiance",
+            category="model/patch/chroma_radiance",
             description="Allows setting advanced options for the Chroma Radiance model.",
             inputs=[
                 io.Model.Input(id="model"),

comfy_extras/nodes_color.py

@@ -8,7 +8,7 @@ class ColorToRGBInt(io.ComfyNode):
         return io.Schema(
             node_id="ColorToRGBInt",
             display_name="Color to RGB Int",
-            category="utils",
+            category="utilities",
             description="Convert a color to a RGB integer value.",
             inputs=[
                 io.Color.Input("color"),

comfy_extras/nodes_context_windows.py

@@ -9,7 +9,7 @@ class ContextWindowsManualNode(io.ComfyNode):
         return io.Schema(
             node_id="ContextWindowsManual",
             display_name="Context Windows (Manual)",
-            category="model_patches",
+            category="model/patch",
             description="Manually set context windows.",
             inputs=[
                 io.Model.Input("model", tooltip="The model to apply context windows to during sampling."),

comfy_extras/nodes_controlnet.py

@@ -9,7 +9,7 @@ class SetUnionControlNetType(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SetUnionControlNetType",
-            category="conditioning/controlnet",
+            category="model/conditioning/controlnet",
             inputs=[
                 io.ControlNet.Input("control_net"),
                 io.Combo.Input("type", options=["auto"] + list(UNION_CONTROLNET_TYPES.keys())),
@@ -39,7 +39,7 @@ class ControlNetInpaintingAliMamaApply(io.ComfyNode):
         return io.Schema(
             node_id="ControlNetInpaintingAliMamaApply",
             search_aliases=["masked controlnet"],
-            category="conditioning/controlnet",
+            category="model/conditioning/controlnet",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Conditioning.Input("negative"),

comfy_extras/nodes_cosmos.py

@@ -13,7 +13,7 @@ class EmptyCosmosLatentVideo(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="EmptyCosmosLatentVideo",
-            category="latent/video",
+            category="model/latent/video",
             inputs=[
                 io.Int.Input("width", default=1280, min=16, max=nodes.MAX_RESOLUTION, step=16),
                 io.Int.Input("height", default=704, min=16, max=nodes.MAX_RESOLUTION, step=16),
@@ -45,7 +45,7 @@ class CosmosImageToVideoLatent(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="CosmosImageToVideoLatent",
-            category="conditioning/inpaint",
+            category="model/conditioning/inpaint",
             inputs=[
                 io.Vae.Input("vae"),
                 io.Int.Input("width", default=1280, min=16, max=nodes.MAX_RESOLUTION, step=16),
@@ -88,7 +88,7 @@ class CosmosPredict2ImageToVideoLatent(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="CosmosPredict2ImageToVideoLatent",
-            category="conditioning/inpaint",
+            category="model/conditioning/inpaint",
             inputs=[
                 io.Vae.Input("vae"),
                 io.Int.Input("width", default=848, min=16, max=nodes.MAX_RESOLUTION, step=16),

comfy_extras/nodes_curve.py

@@ -11,7 +11,7 @@ class CurveEditor(io.ComfyNode):
         return io.Schema(
             node_id="CurveEditor",
             display_name="Curve Editor",
-            category="utils",
+            category="utilities",
             inputs=[
                 io.Curve.Input("curve"),
                 io.Histogram.Input("histogram", optional=True),
@@ -38,7 +38,7 @@ class ImageHistogram(io.ComfyNode):
         return io.Schema(
             node_id="ImageHistogram",
             display_name="Image Histogram",
-            category="utils",
+            category="utilities",
             inputs=[
                 io.Image.Input("image"),
             ],

comfy_extras/nodes_custom_sampler.py

@@ -17,7 +17,7 @@ class BasicScheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="BasicScheduler",
-            category="sampling/schedulers",
+            category="model/sampling/schedulers",
             inputs=[
                 io.Model.Input("model"),
                 io.Combo.Input("scheduler", options=comfy.samplers.SCHEDULER_NAMES),
@@ -47,7 +47,7 @@ class KarrasScheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="KarrasScheduler",
-            category="sampling/schedulers",
+            category="model/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, advanced=True),
@@ -69,7 +69,7 @@ class ExponentialScheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="ExponentialScheduler",
-            category="sampling/schedulers",
+            category="model/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, advanced=True),
@@ -90,7 +90,7 @@ class PolyexponentialScheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="PolyexponentialScheduler",
-            category="sampling/schedulers",
+            category="model/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, advanced=True),
@@ -112,7 +112,7 @@ class LaplaceScheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LaplaceScheduler",
-            category="sampling/schedulers",
+            category="model/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, advanced=True),
@@ -136,7 +136,7 @@ class SDTurboScheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SDTurboScheduler",
-            category="sampling/schedulers",
+            category="model/sampling/schedulers",
             inputs=[
                 io.Model.Input("model"),
                 io.Int.Input("steps", default=1, min=1, max=10),
@@ -160,7 +160,7 @@ class BetaSamplingScheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="BetaSamplingScheduler",
-            category="sampling/schedulers",
+            category="model/sampling/schedulers",
             inputs=[
                 io.Model.Input("model"),
                 io.Int.Input("steps", default=20, min=1, max=10000),
@@ -182,7 +182,7 @@ class VPScheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="VPScheduler",
-            category="sampling/schedulers",
+            category="model/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, advanced=True), #TODO: fix default values
@@ -204,7 +204,7 @@ class SplitSigmas(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SplitSigmas",
-            category="sampling/sigmas",
+            category="model/sampling/sigmas",
             inputs=[
                 io.Sigmas.Input("sigmas"),
                 io.Int.Input("step", default=0, min=0, max=10000),
@@ -228,7 +228,7 @@ class SplitSigmasDenoise(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SplitSigmasDenoise",
-            category="sampling/sigmas",
+            category="model/sampling/sigmas",
             inputs=[
                 io.Sigmas.Input("sigmas"),
                 io.Float.Input("denoise", default=1.0, min=0.0, max=1.0, step=0.01),
@@ -254,7 +254,7 @@ class FlipSigmas(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="FlipSigmas",
-            category="sampling/sigmas",
+            category="model/sampling/sigmas",
             inputs=[io.Sigmas.Input("sigmas")],
             outputs=[io.Sigmas.Output()]
         )
@@ -276,7 +276,7 @@ class SetFirstSigma(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SetFirstSigma",
-            category="sampling/sigmas",
+            category="model/sampling/sigmas",
             inputs=[
                 io.Sigmas.Input("sigmas"),
                 io.Float.Input("sigma", default=136.0, min=0.0, max=20000.0, step=0.001, round=False),
@@ -298,7 +298,7 @@ class ExtendIntermediateSigmas(io.ComfyNode):
         return io.Schema(
             node_id="ExtendIntermediateSigmas",
             search_aliases=["interpolate sigmas"],
-            category="sampling/sigmas",
+            category="model/sampling/sigmas",
             inputs=[
                 io.Sigmas.Input("sigmas"),
                 io.Int.Input("steps", default=2, min=1, max=100),
@@ -351,7 +351,7 @@ class SamplingPercentToSigma(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SamplingPercentToSigma",
-            category="sampling/sigmas",
+            category="model/sampling/sigmas",
             inputs=[
                 io.Model.Input("model"),
                 io.Float.Input("sampling_percent", default=0.0, min=0.0, max=1.0, step=0.0001),
@@ -379,7 +379,7 @@ class KSamplerSelect(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="KSamplerSelect",
-            category="sampling/samplers",
+            category="model/sampling/samplers",
             inputs=[io.Combo.Input("sampler_name", options=comfy.samplers.SAMPLER_NAMES)],
             outputs=[io.Sampler.Output()]
         )
@@ -396,7 +396,7 @@ class SamplerDPMPP_3M_SDE(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SamplerDPMPP_3M_SDE",
-            category="sampling/samplers",
+            category="model/sampling/samplers",
             inputs=[
                 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),
@@ -421,7 +421,7 @@ class SamplerDPMPP_2M_SDE(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SamplerDPMPP_2M_SDE",
-            category="sampling/samplers",
+            category="model/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, advanced=True),
@@ -448,7 +448,7 @@ class SamplerDPMPP_SDE(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SamplerDPMPP_SDE",
-            category="sampling/samplers",
+            category="model/sampling/samplers",
             inputs=[
                 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),
@@ -474,7 +474,7 @@ class SamplerDPMPP_2S_Ancestral(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SamplerDPMPP_2S_Ancestral",
-            category="sampling/samplers",
+            category="model/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),
@@ -494,7 +494,7 @@ class SamplerEulerAncestral(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SamplerEulerAncestral",
-            category="sampling/samplers",
+            category="model/sampling/samplers",
             inputs=[
                 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),
@@ -515,7 +515,7 @@ class SamplerEulerAncestralCFGPP(io.ComfyNode):
         return io.Schema(
             node_id="SamplerEulerAncestralCFGPP",
             display_name="SamplerEulerAncestralCFG++",
-            category="sampling/samplers",
+            category="model/sampling/samplers",
             inputs=[
                 io.Float.Input("eta", default=1.0, min=0.0, max=1.0, step=0.01, round=False),
                 io.Float.Input("s_noise", default=1.0, min=0.0, max=10.0, step=0.01, round=False),
@@ -537,7 +537,7 @@ class SamplerLMS(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SamplerLMS",
-            category="sampling/samplers",
+            category="model/sampling/samplers",
             inputs=[io.Int.Input("order", default=4, min=1, max=100, advanced=True)],
             outputs=[io.Sampler.Output()]
         )
@@ -554,7 +554,7 @@ class SamplerDPMAdaptative(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SamplerDPMAdaptative",
-            category="sampling/samplers",
+            category="model/sampling/samplers",
             inputs=[
                 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),
@@ -585,7 +585,7 @@ class SamplerER_SDE(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SamplerER_SDE",
-            category="sampling/samplers",
+            category="model/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, advanced=True),
@@ -623,7 +623,7 @@ class SamplerSASolver(io.ComfyNode):
         return io.Schema(
             node_id="SamplerSASolver",
             search_aliases=["sde"],
-            category="sampling/samplers",
+            category="model/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, advanced=True),
@@ -668,7 +668,7 @@ class SamplerSEEDS2(io.ComfyNode):
         return io.Schema(
             node_id="SamplerSEEDS2",
             search_aliases=["sde", "exp heun"],
-            category="sampling/samplers",
+            category="model/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", advanced=True),
@@ -727,7 +727,7 @@ class SamplerCustom(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SamplerCustom",
-            category="sampling/custom_sampling",
+            category="model/sampling/custom_sampling",
             inputs=[
                 io.Model.Input("model"),
                 io.Boolean.Input("add_noise", default=True, advanced=True),
@@ -795,7 +795,7 @@ class BasicGuider(io.ComfyNode):
         return io.Schema(
             node_id="BasicGuider",
             display_name="Basic Guider",
-            category="sampling/guiders",
+            category="model/sampling/guiders",
             inputs=[
                 io.Model.Input("model"),
                 io.Conditioning.Input("conditioning"),
@@ -817,7 +817,7 @@ class CFGGuider(io.ComfyNode):
         return io.Schema(
             node_id="CFGGuider",
             display_name="CFG Guider",
-            category="sampling/guiders",
+            category="model/sampling/guiders",
             inputs=[
                 io.Model.Input("model"),
                 io.Conditioning.Input("positive"),
@@ -872,7 +872,7 @@ class DualCFGGuider(io.ComfyNode):
             node_id="DualCFGGuider",
             search_aliases=["dual prompt guidance"],
             display_name="Dual CFG Guider",
-            category="sampling/guiders",
+            category="model/sampling/guiders",
             inputs=[
                 io.Model.Input("model"),
                 io.Conditioning.Input("cond1"),
@@ -900,7 +900,7 @@ class DisableNoise(io.ComfyNode):
         return io.Schema(
             node_id="DisableNoise",
             search_aliases=["zero noise"],
-            category="sampling/noise",
+            category="model/sampling/noise",
             inputs=[],
             outputs=[io.Noise.Output()]
         )
@@ -917,7 +917,7 @@ class RandomNoise(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="RandomNoise",
-            category="sampling/noise",
+            category="model/sampling/noise",
             inputs=[io.Int.Input("noise_seed", default=0, min=0, max=0xffffffffffffffff, control_after_generate=True)],
             outputs=[io.Noise.Output()]
         )
@@ -934,7 +934,7 @@ class SamplerCustomAdvanced(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SamplerCustomAdvanced",
-            category="sampling/custom_sampling",
+            category="model/sampling/custom_sampling",
             inputs=[
                 io.Noise.Input("noise"),
                 io.Guider.Input("guider"),

comfy_extras/nodes_dataset.py

@@ -574,7 +574,7 @@ class TextProcessingNode(io.ComfyNode):
         return io.Schema(
             node_id=cls.node_id,
             display_name=cls.display_name or cls.node_id,
-            category="dataset/text",
+            category="text",
             is_experimental=True,
             is_input_list=is_group,  # True for group, False for individual
             inputs=inputs,
@@ -1208,7 +1208,7 @@ class ResolutionBucket(io.ComfyNode):
             node_id="ResolutionBucket",
             search_aliases=["bucket by resolution", "group by resolution", "batch by resolution"],
             display_name="Resolution Bucket",
-            category="training",
+            category="model/training",
             description="Group latents and conditionings into buckets",
             is_experimental=True,
             is_input_list=True,
@@ -1302,7 +1302,7 @@ class MakeTrainingDataset(io.ComfyNode):
             node_id="MakeTrainingDataset",
             search_aliases=["encode dataset"],
             display_name="Make Training Dataset",
-            category="training",
+            category="model/training",
             description="Encode images with VAE and texts with CLIP to create a training dataset of latents and conditionings.",
             is_experimental=True,
             is_input_list=True,  # images and texts as lists
@@ -1390,7 +1390,7 @@ class SaveTrainingDataset(io.ComfyNode):
             node_id="SaveTrainingDataset",
             search_aliases=["export dataset", "save dataset"],
             display_name="Save Training Dataset",
-            category="training",
+            category="model/training",
             description="Save encoded training dataset (latents + conditioning) to disk for efficient loading during training.",
             is_experimental=True,
             is_output_node=True,
@@ -1493,7 +1493,7 @@ class LoadTrainingDataset(io.ComfyNode):
             node_id="LoadTrainingDataset",
             search_aliases=["import dataset", "training data"],
             display_name="Load Training Dataset",
-            category="training",
+            category="model/training",
             description="Load encoded training dataset (latents + conditioning) from disk for use in training.",
             is_experimental=True,
             inputs=[

comfy_extras/nodes_eps.py

@@ -18,7 +18,7 @@ class EpsilonScaling(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="Epsilon Scaling",
-            category="model_patches/unet",
+            category="model/patch/unet",
             inputs=[
                 io.Model.Input("model"),
                 io.Float.Input(
@@ -84,7 +84,7 @@ class TemporalScoreRescaling(io.ComfyNode):
         return io.Schema(
             node_id="TemporalScoreRescaling",
             display_name="TSR - Temporal Score Rescaling",
-            category="model_patches/unet",
+            category="model/patch/unet",
             inputs=[
                 io.Model.Input("model"),
                 io.Float.Input(

comfy_extras/nodes_flux.py

@@ -40,7 +40,7 @@ class EmptyFlux2LatentImage(io.ComfyNode):
         return io.Schema(
             node_id="EmptyFlux2LatentImage",
             display_name="Empty Flux 2 Latent",
-            category="latent",
+            category="model/latent",
             inputs=[
                 io.Int.Input("width", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),
                 io.Int.Input("height", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),
@@ -215,7 +215,7 @@ class Flux2Scheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="Flux2Scheduler",
-            category="sampling/schedulers",
+            category="model/sampling/schedulers",
             inputs=[
                 io.Int.Input("steps", default=20, min=1, max=4096),
                 io.Int.Input("width", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=1),

comfy_extras/nodes_frame_interpolation.py

@@ -19,7 +19,7 @@ class FrameInterpolationModelLoader(io.ComfyNode):
         return io.Schema(
             node_id="FrameInterpolationModelLoader",
             display_name="Load Frame Interpolation Model",
-            category="loaders",
+            category="model/loaders",
             inputs=[
                 io.Combo.Input("model_name", options=folder_paths.get_filename_list("frame_interpolation"),
                                tooltip="Select a frame interpolation model to load. Models must be placed in the 'frame_interpolation' folder."),

comfy_extras/nodes_freelunch.py

@@ -29,7 +29,7 @@ class FreeU(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="FreeU",
-            category="model_patches/unet",
+            category="model/patch/unet",
             inputs=[
                 IO.Model.Input("model"),
                 IO.Float.Input("b1", default=1.1, min=0.0, max=10.0, step=0.01, advanced=True),
@@ -76,7 +76,7 @@ class FreeU_V2(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="FreeU_V2",
-            category="model_patches/unet",
+            category="model/patch/unet",
             inputs=[
                 IO.Model.Input("model"),
                 IO.Float.Input("b1", default=1.3, min=0.0, max=10.0, step=0.01, advanced=True),

comfy_extras/nodes_gits.py

@@ -340,7 +340,7 @@ class GITSScheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="GITSScheduler",
-            category="sampling/schedulers",
+            category="model/sampling/schedulers",
             inputs=[
                 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),

comfy_extras/nodes_hidream_o1.py

@@ -14,7 +14,7 @@ class EmptyHiDreamO1LatentImage(io.ComfyNode):
         return io.Schema(
             node_id="EmptyHiDreamO1LatentImage",
             display_name="Empty HiDream-O1 Latent Image",
-            category="latent/image",
+            category="model/latent/image",
             description=(
                 "Empty pixel-space latent for HiDream-O1-Image. The model was "
                 "trained at ~4 megapixels; lower resolutions go off-distribution "
@@ -47,7 +47,7 @@ class HiDreamO1ReferenceImages(io.ComfyNode):
         return io.Schema(
             node_id="HiDreamO1ReferenceImages",
             display_name="HiDream-O1 Reference Images",
-            category="conditioning/image",
+            category="model/conditioning/image",
             description=(
                 "Attach 1-10 reference images to conditioning, one for edit instruction"
                 "or multiple for subject-driven personalization."

comfy_extras/nodes_hunyuan.py

@@ -41,7 +41,7 @@ class EmptyHunyuanLatentVideo(io.ComfyNode):
         return io.Schema(
             node_id="EmptyHunyuanLatentVideo",
             display_name="Empty HunyuanVideo 1.0 Latent",
-            category="latent/video",
+            category="model/latent/video",
             inputs=[
                 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),
@@ -81,7 +81,7 @@ class HunyuanVideo15ImageToVideo(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="HunyuanVideo15ImageToVideo",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Conditioning.Input("negative"),
@@ -132,7 +132,7 @@ class HunyuanVideo15SuperResolution(io.ComfyNode):
         return io.Schema(
             node_id="HunyuanVideo15SuperResolution",
             display_name="Hunyuan Video 1.5 Super Resolution",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Conditioning.Input("negative"),
@@ -178,7 +178,7 @@ class LatentUpscaleModelLoader(io.ComfyNode):
         return io.Schema(
             node_id="LatentUpscaleModelLoader",
             display_name="Load Latent Upscale Model",
-            category="loaders",
+            category="model/loaders",
             inputs=[
                 io.Combo.Input("model_name", options=folder_paths.get_filename_list("latent_upscale_models")),
             ],
@@ -227,7 +227,7 @@ class HunyuanVideo15LatentUpscaleWithModel(io.ComfyNode):
         return io.Schema(
             node_id="HunyuanVideo15LatentUpscaleWithModel",
             display_name="Hunyuan Video 15 Latent Upscale With Model",
-            category="latent",
+            category="model/latent",
             inputs=[
                 io.LatentUpscaleModel.Input("model"),
                 io.Latent.Input("samples"),
@@ -308,7 +308,7 @@ class HunyuanImageToVideo(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="HunyuanImageToVideo",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Vae.Input("vae"),
@@ -359,7 +359,7 @@ class EmptyHunyuanImageLatent(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="EmptyHunyuanImageLatent",
-            category="latent",
+            category="model/latent",
             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),
@@ -384,7 +384,7 @@ class HunyuanRefinerLatent(io.ComfyNode):
         return io.Schema(
             node_id="HunyuanRefinerLatent",
             display_name="Hunyuan Latent Refiner",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Conditioning.Input("negative"),

comfy_extras/nodes_hunyuan3d.py

@@ -12,7 +12,7 @@ class EmptyLatentHunyuan3Dv2(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="EmptyLatentHunyuan3Dv2",
-            category="latent/3d",
+            category="model/latent/3d",
             inputs=[
                 IO.Int.Input("resolution", default=3072, min=1, max=8192),
                 IO.Int.Input("batch_size", default=1, min=1, max=4096, tooltip="The number of latent images in the batch."),
@@ -35,7 +35,7 @@ class Hunyuan3Dv2Conditioning(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="Hunyuan3Dv2Conditioning",
-            category="conditioning/3d_models",
+            category="model/conditioning/3d_models",
             inputs=[
                 IO.ClipVisionOutput.Input("clip_vision_output"),
             ],
@@ -60,7 +60,7 @@ class Hunyuan3Dv2ConditioningMultiView(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="Hunyuan3Dv2ConditioningMultiView",
-            category="conditioning/3d_models",
+            category="model/conditioning/3d_models",
             inputs=[
                 IO.ClipVisionOutput.Input("front", optional=True),
                 IO.ClipVisionOutput.Input("left", optional=True),
@@ -97,7 +97,7 @@ class VAEDecodeHunyuan3D(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="VAEDecodeHunyuan3D",
-            category="latent/3d",
+            category="model/latent/3d",
             inputs=[
                 IO.Latent.Input("samples"),
                 IO.Vae.Input("vae"),

comfy_extras/nodes_hypernetwork.py

@@ -103,7 +103,7 @@ class HypernetworkLoader(IO.ComfyNode):
         return IO.Schema(
             node_id="HypernetworkLoader",
             display_name="Load Hypernetwork",
-            category="loaders",
+            category="model/loaders",
             inputs=[
                 IO.Model.Input("model"),
                 IO.Combo.Input("hypernetwork_name", options=folder_paths.get_filename_list("hypernetworks")),

comfy_extras/nodes_hypertile.py

@@ -27,7 +27,7 @@ class HyperTile(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="HyperTile",
-            category="model_patches/unet",
+            category="model/patch/unet",
             inputs=[
                 io.Model.Input("model"),
                 io.Int.Input("tile_size", default=256, min=1, max=2048, advanced=True),

comfy_extras/nodes_images.py

@@ -95,7 +95,7 @@ class BoundingBox(IO.ComfyNode):
         return IO.Schema(
             node_id="PrimitiveBoundingBox",
             display_name="Bounding Box",
-            category="utils/primitive",
+            category="utilities/primitive",
             inputs=[
                 IO.Int.Input("x", default=0, min=0, max=MAX_RESOLUTION),
                 IO.Int.Input("y", default=0, min=0, max=MAX_RESOLUTION),

comfy_extras/nodes_ip2p.py

@@ -9,7 +9,7 @@ class InstructPixToPixConditioning(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="InstructPixToPixConditioning",
-            category="conditioning/instructpix2pix",
+            category="model/conditioning/instructpix2pix",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Conditioning.Input("negative"),

comfy_extras/nodes_kandinsky5.py

@@ -13,7 +13,7 @@ class Kandinsky5ImageToVideo(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="Kandinsky5ImageToVideo",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Conditioning.Input("negative"),
@@ -71,7 +71,7 @@ class NormalizeVideoLatentStart(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="NormalizeVideoLatentStart",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             description="Normalizes the initial frames of a video latent to match the mean and standard deviation of subsequent reference frames. Helps reduce differences between the starting frames and the rest of the video.",
             inputs=[
                 io.Latent.Input("latent"),

comfy_extras/nodes_latent.py

@@ -22,7 +22,7 @@ class LatentAdd(io.ComfyNode):
         return io.Schema(
             node_id="LatentAdd",
             search_aliases=["combine latents", "sum latents"],
-            category="latent/advanced",
+            category="model/latent/advanced",
             inputs=[
                 io.Latent.Input("samples1"),
                 io.Latent.Input("samples2"),
@@ -49,7 +49,7 @@ class LatentSubtract(io.ComfyNode):
         return io.Schema(
             node_id="LatentSubtract",
             search_aliases=["difference latent", "remove features"],
-            category="latent/advanced",
+            category="model/latent/advanced",
             inputs=[
                 io.Latent.Input("samples1"),
                 io.Latent.Input("samples2"),
@@ -76,7 +76,7 @@ class LatentMultiply(io.ComfyNode):
         return io.Schema(
             node_id="LatentMultiply",
             search_aliases=["scale latent", "amplify latent", "latent gain"],
-            category="latent/advanced",
+            category="model/latent/advanced",
             inputs=[
                 io.Latent.Input("samples"),
                 io.Float.Input("multiplier", default=1.0, min=-10.0, max=10.0, step=0.01),
@@ -100,7 +100,7 @@ class LatentInterpolate(io.ComfyNode):
         return io.Schema(
             node_id="LatentInterpolate",
             search_aliases=["blend latent", "mix latent", "lerp latent", "transition"],
-            category="latent/advanced",
+            category="model/latent/advanced",
             inputs=[
                 io.Latent.Input("samples1"),
                 io.Latent.Input("samples2"),
@@ -139,7 +139,7 @@ class LatentConcat(io.ComfyNode):
         return io.Schema(
             node_id="LatentConcat",
             search_aliases=["join latents", "stitch latents"],
-            category="latent/advanced",
+            category="model/latent/advanced",
             inputs=[
                 io.Latent.Input("samples1"),
                 io.Latent.Input("samples2"),
@@ -179,7 +179,7 @@ class LatentCut(io.ComfyNode):
         return io.Schema(
             node_id="LatentCut",
             search_aliases=["crop latent", "slice latent", "extract region"],
-            category="latent/advanced",
+            category="model/latent/advanced",
             inputs=[
                 io.Latent.Input("samples"),
                 io.Combo.Input("dim", options=["x", "y", "t"]),
@@ -220,7 +220,7 @@ class LatentCutToBatch(io.ComfyNode):
         return io.Schema(
             node_id="LatentCutToBatch",
             search_aliases=["slice to batch", "split latent", "tile latent"],
-            category="latent/advanced",
+            category="model/latent/advanced",
             inputs=[
                 io.Latent.Input("samples"),
                 io.Combo.Input("dim", options=["t", "x", "y"]),
@@ -262,7 +262,7 @@ class LatentBatch(io.ComfyNode):
         return io.Schema(
             node_id="LatentBatch",
             search_aliases=["combine latents", "merge latents", "join latents"],
-            category="latent/batch",
+            category="model/latent/batch",
             is_deprecated=True,
             inputs=[
                 io.Latent.Input("samples1"),
@@ -290,7 +290,7 @@ class LatentBatchSeedBehavior(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LatentBatchSeedBehavior",
-            category="latent/advanced",
+            category="model/latent/advanced",
             inputs=[
                 io.Latent.Input("samples"),
                 io.Combo.Input("seed_behavior", options=["random", "fixed"], default="fixed"),
@@ -319,7 +319,7 @@ class LatentApplyOperation(io.ComfyNode):
         return io.Schema(
             node_id="LatentApplyOperation",
             search_aliases=["transform latent"],
-            category="latent/advanced/operations",
+            category="model/latent/advanced/operations",
             is_experimental=True,
             inputs=[
                 io.Latent.Input("samples"),
@@ -343,7 +343,7 @@ class LatentApplyOperationCFG(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LatentApplyOperationCFG",
-            category="latent/advanced/operations",
+            category="model/latent/advanced/operations",
             is_experimental=True,
             inputs=[
                 io.Model.Input("model"),
@@ -375,7 +375,7 @@ class LatentOperationTonemapReinhard(io.ComfyNode):
         return io.Schema(
             node_id="LatentOperationTonemapReinhard",
             search_aliases=["hdr latent"],
-            category="latent/advanced/operations",
+            category="model/latent/advanced/operations",
             is_experimental=True,
             inputs=[
                 io.Float.Input("multiplier", default=1.0, min=0.0, max=100.0, step=0.01),
@@ -410,7 +410,7 @@ class LatentOperationSharpen(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LatentOperationSharpen",
-            category="latent/advanced/operations",
+            category="model/latent/advanced/operations",
             is_experimental=True,
             inputs=[
                 io.Int.Input("sharpen_radius", default=9, min=1, max=31, step=1, advanced=True),
@@ -447,7 +447,7 @@ class ReplaceVideoLatentFrames(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="ReplaceVideoLatentFrames",
-            category="latent/batch",
+            category="model/latent/batch",
             inputs=[
                 io.Latent.Input("destination", tooltip="The destination latent where frames will be replaced."),
                 io.Latent.Input("source", optional=True, tooltip="The source latent providing frames to insert into the destination latent. If not provided, the destination latent is returned unchanged."),

comfy_extras/nodes_logic.py

@@ -13,7 +13,7 @@ class NotNode(io.ComfyNode):
         return io.Schema(
             node_id="ComfyNotNode",
             display_name="Not",
-            category="utils/logic",
+            category="utilities/logic",
             description="Logical NOT operation. Returns true if the value is falsy. Uses Python's rules for truthiness.",
             search_aliases=["invert", "toggle", "negate", "flip boolean"],
             inputs=[
@@ -40,7 +40,7 @@ class AndNode(io.ComfyNode):
         return io.Schema(
             node_id="ComfyAndNode",
             display_name="And",
-            category="utils/logic",
+            category="utilities/logic",
             description="Logical AND operation. Returns true if all of the values are truthy. Uses Python's rules for truthiness.",
             search_aliases=["all", "every"],
             inputs=[
@@ -67,7 +67,7 @@ class OrNode(io.ComfyNode):
         return io.Schema(
             node_id="ComfyOrNode",
             display_name="Or",
-            category="utils/logic",
+            category="utilities/logic",
             description="Logical OR operation. Returns true if any of the values are truthy. Uses Python's rules for truthiness.",
             search_aliases=["any", "some"],
             inputs=[
@@ -90,7 +90,7 @@ class SwitchNode(io.ComfyNode):
         return io.Schema(
             node_id="ComfySwitchNode",
             display_name="Switch",
-            category="utils/logic",
+            category="utilities/logic",
             is_experimental=True,
             inputs=[
                 io.Boolean.Input("switch"),
@@ -121,7 +121,7 @@ class SoftSwitchNode(io.ComfyNode):
         return io.Schema(
             node_id="ComfySoftSwitchNode",
             display_name="Soft Switch",
-            category="utils/logic",
+            category="utilities/logic",
             is_experimental=True,
             inputs=[
                 io.Boolean.Input("switch"),
@@ -176,7 +176,7 @@ class CustomComboNode(io.ComfyNode):
         return io.Schema(
             node_id="CustomCombo",
             display_name="Custom Combo",
-            category="utils",
+            category="utilities",
             is_experimental=True,
             inputs=[io.Combo.Input("choice", options=[])],
             outputs=[
@@ -211,7 +211,7 @@ class DCTestNode(io.ComfyNode):
         return io.Schema(
             node_id="DCTestNode",
             display_name="DCTest",
-            category="utils/logic",
+            category="utilities/logic",
             is_output_node=True,
             inputs=[io.DynamicCombo.Input("combo", options=[
                 io.DynamicCombo.Option("option1", [io.String.Input("string")]),
@@ -249,7 +249,7 @@ class AutogrowNamesTestNode(io.ComfyNode):
         return io.Schema(
             node_id="AutogrowNamesTestNode",
             display_name="AutogrowNamesTest",
-            category="utils/logic",
+            category="utilities/logic",
             inputs=[
                 _io.Autogrow.Input("autogrow", template=template)
             ],
@@ -269,7 +269,7 @@ class AutogrowPrefixTestNode(io.ComfyNode):
         return io.Schema(
             node_id="AutogrowPrefixTestNode",
             display_name="AutogrowPrefixTest",
-            category="utils/logic",
+            category="utilities/logic",
             inputs=[
                 _io.Autogrow.Input("autogrow", template=template)
             ],
@@ -288,7 +288,7 @@ class ComboOutputTestNode(io.ComfyNode):
         return io.Schema(
             node_id="ComboOptionTestNode",
             display_name="ComboOptionTest",
-            category="utils/logic",
+            category="utilities/logic",
             inputs=[io.Combo.Input("combo", options=["option1", "option2", "option3"]),
                     io.Combo.Input("combo2", options=["option4", "option5", "option6"])],
             outputs=[io.Combo.Output(), io.Combo.Output()],
@@ -305,7 +305,7 @@ class ConvertStringToComboNode(io.ComfyNode):
             node_id="ConvertStringToComboNode",
             search_aliases=["string to dropdown", "text to combo"],
             display_name="Convert String to Combo",
-            category="utils/logic",
+            category="utilities/logic",
             inputs=[io.String.Input("string")],
             outputs=[io.Combo.Output()],
         )
@@ -321,7 +321,7 @@ class InvertBooleanNode(io.ComfyNode):
             node_id="InvertBooleanNode",
             search_aliases=["not", "toggle", "negate", "flip boolean"],
             display_name="Invert Boolean",
-            category="utils/logic",
+            category="utilities/logic",
             inputs=[io.Boolean.Input("boolean")],
             outputs=[io.Boolean.Output()],
         )

comfy_extras/nodes_lora_debug.py

@@ -30,7 +30,7 @@ class LoraLoaderBypass:
     OUTPUT_TOOLTIPS = ("The modified diffusion model.", "The modified CLIP model.")
     FUNCTION = "load_lora"
 
-    CATEGORY = "loaders"
+    CATEGORY = "model/loaders"
     DESCRIPTION = "Apply LoRA in bypass mode. Unlike regular LoRA, this doesn't modify model weights - instead it injects the LoRA computation during forward pass. Useful for training scenarios."
     EXPERIMENTAL = True
 

comfy_extras/nodes_lotus.py

@@ -10,7 +10,7 @@ class LotusConditioning(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LotusConditioning",
-            category="conditioning/lotus",
+            category="model/conditioning/lotus",
             inputs=[],
             outputs=[io.Conditioning.Output(display_name="conditioning")],
         )

comfy_extras/nodes_lt.py

@@ -25,7 +25,7 @@ class GetICLoRAParameters(io.ComfyNode):
             display_name="Get IC-LoRA Parameters",
             description="Extracts IC-LoRA parameters from the safetensors metadata of a LoRA-loaded "
                         "model and outputs them for LTXVAddGuide (eg. reference_downscale_factor).",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             search_aliases=["ic-lora", "ic lora", "iclora", "downscale factor", "reference downscale"],
             inputs=[
                 io.Model.Input(
@@ -62,7 +62,7 @@ class EmptyLTXVLatentVideo(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="EmptyLTXVLatentVideo",
-            category="latent/video/ltxv",
+            category="model/latent/video/ltxv",
             inputs=[
                 io.Int.Input("width", default=768, min=64, max=nodes.MAX_RESOLUTION, step=32),
                 io.Int.Input("height", default=512, min=64, max=nodes.MAX_RESOLUTION, step=32),
@@ -86,7 +86,7 @@ class LTXVImgToVideo(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LTXVImgToVideo",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Conditioning.Input("negative"),
@@ -131,7 +131,7 @@ class LTXVImgToVideoInplace(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LTXVImgToVideoInplace",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Vae.Input("vae"),
                 io.Image.Input("image"),
@@ -251,7 +251,7 @@ class LTXVAddGuide(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LTXVAddGuide",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Conditioning.Input("negative"),
@@ -498,7 +498,7 @@ class LTXVCropGuides(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LTXVCropGuides",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Conditioning.Input("negative"),
@@ -542,7 +542,7 @@ class LTXVConditioning(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LTXVConditioning",
-            category="conditioning/video_models",
+            category="model/conditioning/video_models",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Conditioning.Input("negative"),
@@ -611,7 +611,7 @@ class LTXVScheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LTXVScheduler",
-            category="sampling/schedulers",
+            category="model/sampling/schedulers",
             inputs=[
                 io.Int.Input("steps", default=20, min=1, max=10000),
                 io.Float.Input("max_shift", default=2.05, min=0.0, max=100.0, step=0.01),
@@ -746,7 +746,7 @@ class LTXVConcatAVLatent(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LTXVConcatAVLatent",
-            category="latent/video/ltxv",
+            category="model/latent/video/ltxv",
             inputs=[
                 io.Latent.Input("video_latent"),
                 io.Latent.Input("audio_latent"),
@@ -781,7 +781,7 @@ class LTXVSeparateAVLatent(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LTXVSeparateAVLatent",
-            category="latent/video/ltxv",
+            category="model/latent/video/ltxv",
             description="LTXV Separate AV Latent",
             inputs=[
                 io.Latent.Input("av_latent"),
@@ -814,7 +814,7 @@ class LTXVReferenceAudio(io.ComfyNode):
         return io.Schema(
             node_id="LTXVReferenceAudio",
             display_name="LTXV Reference Audio (ID-LoRA)",
-            category="conditioning/audio",
+            category="model/conditioning/audio",
             description="Set reference audio for ID-LoRA speaker identity transfer. Encodes a reference audio clip into the conditioning and optionally patches the model with identity guidance (extra forward pass without reference, amplifying the speaker identity effect).",
             inputs=[
                 io.Model.Input("model"),

comfy_extras/nodes_lt_audio.py

@@ -12,7 +12,7 @@ class LTXVAudioVAELoader(io.ComfyNode):
         return io.Schema(
             node_id="LTXVAudioVAELoader",
             display_name="Load LTXV Audio VAE",
-            category="loaders",
+            category="model/loaders",
             inputs=[
                 io.Combo.Input(
                     "ckpt_name",
@@ -40,7 +40,7 @@ class LTXVAudioVAEEncode(VAEEncodeAudio):
         return io.Schema(
             node_id="LTXVAudioVAEEncode",
             display_name="LTXV Audio VAE Encode",
-            category="latent/audio",
+            category="model/latent/audio",
             inputs=[
                 io.Audio.Input("audio", tooltip="The audio to be encoded."),
                 io.Vae.Input(
@@ -63,7 +63,7 @@ class LTXVAudioVAEDecode(io.ComfyNode):
         return io.Schema(
             node_id="LTXVAudioVAEDecode",
             display_name="LTXV Audio VAE Decode",
-            category="latent/audio",
+            category="model/latent/audio",
             inputs=[
                 io.Latent.Input("samples", tooltip="The latent to be decoded."),
                 io.Vae.Input(
@@ -96,7 +96,7 @@ class LTXVEmptyLatentAudio(io.ComfyNode):
         return io.Schema(
             node_id="LTXVEmptyLatentAudio",
             display_name="LTXV Empty Latent Audio",
-            category="latent/audio",
+            category="model/latent/audio",
             inputs=[
                 io.Int.Input(
                     "frames_number",

comfy_extras/nodes_lt_upsampler.py

@@ -13,7 +13,7 @@ class LTXVLatentUpsampler(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="LTXVLatentUpsampler",
-            category="latent/video",
+            category="model/latent/video",
             is_experimental=True,
             inputs=[
                 IO.Latent.Input("samples"),

comfy_extras/nodes_lumina2.py

@@ -81,7 +81,7 @@ class CLIPTextEncodeLumina2(io.ComfyNode):
             node_id="CLIPTextEncodeLumina2",
             search_aliases=["lumina prompt"],
             display_name="CLIP Text Encode for Lumina2",
-            category="conditioning",
+            category="model/conditioning",
             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.",
             inputs=[

comfy_extras/nodes_mask.py

@@ -53,7 +53,7 @@ class LatentCompositeMasked(IO.ComfyNode):
         return IO.Schema(
             node_id="LatentCompositeMasked",
             search_aliases=["overlay latent", "layer latent", "paste latent", "inpaint latent"],
-            category="latent",
+            category="model/latent",
             inputs=[
                 IO.Latent.Input("destination"),
                 IO.Latent.Input("source"),

comfy_extras/nodes_math.py

@@ -69,7 +69,7 @@ class MathExpressionNode(io.ComfyNode):
         return io.Schema(
             node_id="ComfyMathExpression",
             display_name="Math Expression",
-            category="utils",
+            category="utilities",
             search_aliases=[
                 "expression", "formula", "calculate", "calculator",
                 "eval", "math",

comfy_extras/nodes_mediapipe.py

@@ -205,7 +205,7 @@ class LoadMediaPipeFaceLandmarker(io.ComfyNode):
             node_id="LoadMediaPipeFaceLandmarker",
             search_aliases=["face", "facial", "mediapipe", "face landmark", "face mesh", "blazeface", "face detection"],
             display_name="Load Face Detection Model (MediaPipe)",
-            category="loaders",
+            category="model/loaders",
             inputs=[
                 io.Combo.Input("model_name", options=folder_paths.get_filename_list("detection"),
                                tooltip="Face detection model from models/detection/."),

comfy_extras/nodes_mochi.py

@@ -10,7 +10,7 @@ class EmptyMochiLatentVideo(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="EmptyMochiLatentVideo",
-            category="latent/video",
+            category="model/latent/video",
             inputs=[
                 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),

comfy_extras/nodes_model_downscale.py

@@ -10,7 +10,7 @@ class PatchModelAddDownscale(io.ComfyNode):
         return io.Schema(
             node_id="PatchModelAddDownscale",
             display_name="PatchModelAddDownscale (Kohya Deep Shrink)",
-            category="model_patches/unet",
+            category="model/patch/unet",
             inputs=[
                 io.Model.Input("model"),
                 io.Int.Input("block_number", default=3, min=1, max=32, step=1, advanced=True),

comfy_extras/nodes_model_patch.py

@@ -548,7 +548,7 @@ class USOStyleReference:
     FUNCTION = "apply_patch"
     EXPERIMENTAL = True
 
-    CATEGORY = "advanced/model_patches/flux"
+    CATEGORY = "model/patch/flux"
 
     def apply_patch(self, model, model_patch, clip_vision_output):
         encoded_image = torch.stack((clip_vision_output.all_hidden_states[:, -20], clip_vision_output.all_hidden_states[:, -11], clip_vision_output.penultimate_hidden_states))
@@ -594,7 +594,7 @@ class SUPIRApply(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="SUPIRApply",
-            category="model_patches/supir",
+            category="model/patch/supir",
             is_experimental=True,
             inputs=[
                 io.Model.Input("model"),

comfy_extras/nodes_moge.py

@@ -78,7 +78,7 @@ class LoadMoGeModel(io.ComfyNode):
         return io.Schema(
             node_id="LoadMoGeModel",
             display_name="Load MoGe Model",
-            category="loaders",
+            category="model/loaders",
             inputs=[
                 io.Combo.Input("model_name", options=folder_paths.get_filename_list("geometry_estimation")),
             ],
@@ -104,7 +104,7 @@ class MoGePanoramaInference(io.ComfyNode):
             node_id="MoGePanoramaInference",
             search_aliases=["moge", "panorama", "depth", "geometry", "depth estimation", "geometry estimation"],
             display_name="Run MoGe Panorama Inference",
-            category="image/geometry_estimation",
+            category="image/geometry estimation",
             description="Run MoGe on an equirectangular panorama by splitting it into 12 perspective views, running inference on each, and merging the results into a single depth map.",
             inputs=[
                 MoGeModelType.Input("moge_model"),
@@ -226,7 +226,7 @@ class MoGeInference(io.ComfyNode):
             search_aliases=["moge", "depth", "geometry", "depth estimation", "geometry estimation"],
             display_name="Run MoGe Inference",
             description="Run MoGe on a single image to estimate depth and geometry.",
-            category="image/geometry_estimation",
+            category="image/geometry estimation",
             inputs=[
                 MoGeModelType.Input("moge_model"),
                 io.Image.Input("image"),
@@ -283,7 +283,7 @@ class MoGeRender(io.ComfyNode):
             search_aliases=["moge", "render", "geometry", "depth", "normal"],
             display_name="Render MoGe Geometry",
             description="Render a depth map or normal map from geometry data",
-            category="image/geometry_estimation",
+            category="image/geometry estimation",
             inputs=[
                 MoGeGeometry.Input("moge_geometry"),
                 io.Combo.Input("output", options=["depth", "depth_colored", "normal_opengl", "normal_directx", "mask"], default="depth",
@@ -350,7 +350,7 @@ class MoGePointMapToMesh(io.ComfyNode):
             search_aliases=["moge", "mesh", "geometry", "point map"],
             display_name="Convert MoGe Point Map to Mesh",
             description="Convert a MoGe point map into a 3D mesh.",
-            category="image/geometry_estimation",
+            category="image/geometry estimation",
             inputs=[
                 MoGeGeometry.Input("moge_geometry"),
                 io.Int.Input("batch_index", default=0, min=0, max=4096,

comfy_extras/nodes_number_convert.py

@@ -20,7 +20,7 @@ class NumberConvertNode(io.ComfyNode):
         return io.Schema(
             node_id="ComfyNumberConvert",
             display_name="Convert Number",
-            category="utils",
+            category="utilities",
             search_aliases=[
                 "int to float", "float to int", "number convert",
                 "int2float", "float2int", "cast", "parse number",

comfy_extras/nodes_optimalsteps.py

@@ -31,7 +31,7 @@ class OptimalStepsScheduler(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="OptimalStepsScheduler",
-            category="sampling/schedulers",
+            category="model/sampling/schedulers",
             inputs=[
                 io.Combo.Input("model_type", options=["FLUX", "Wan", "Chroma"]),
                 io.Int.Input("steps", default=20, min=3, max=1000),

comfy_extras/nodes_pag.py

@@ -15,7 +15,7 @@ class PerturbedAttentionGuidance(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="PerturbedAttentionGuidance",
-            category="model_patches/unet",
+            category="model/patch/unet",
             inputs=[
                 io.Model.Input("model"),
                 io.Float.Input("scale", default=3.0, min=0.0, max=100.0, step=0.01, round=0.01),

comfy_extras/nodes_post_processing.py

@@ -616,7 +616,7 @@ class BatchLatentsNode(io.ComfyNode):
             node_id="BatchLatentsNode",
             search_aliases=["combine latents", "stack latents", "merge latents"],
             display_name="Batch Latents",
-            category="latent",
+            category="model/latent",
             inputs=[
                 io.Autogrow.Input("latents", template=autogrow_template)
             ],

comfy_extras/nodes_preview_any.py

@@ -16,7 +16,7 @@ class PreviewAny():
     FUNCTION = "main"
     OUTPUT_NODE = True
 
-    CATEGORY = "utils"
+    CATEGORY = "utilities"
     SEARCH_ALIASES = ["show output", "inspect", "debug", "print value", "show text"]
 
     def main(self, source=None):

comfy_extras/nodes_primitive.py

@@ -11,7 +11,7 @@ class String(io.ComfyNode):
             node_id="PrimitiveString",
             search_aliases=["text", "string", "text box", "prompt"],
             display_name="Text String",
-            category="utils/primitive",
+            category="utilities/primitive",
             inputs=[
                 io.String.Input("value"),
             ],
@@ -30,7 +30,7 @@ class StringMultiline(io.ComfyNode):
             node_id="PrimitiveStringMultiline",
             search_aliases=["text", "string", "text multiline", "string multiline", "text box", "prompt"],
             display_name="Text String (Multiline)",
-            category="utils/primitive",
+            category="utilities/primitive",
             essentials_category="Basics",
             inputs=[
                 io.String.Input("value", multiline=True),
@@ -49,7 +49,7 @@ class Int(io.ComfyNode):
         return io.Schema(
             node_id="PrimitiveInt",
             display_name="Int",
-            category="utils/primitive",
+            category="utilities/primitive",
             inputs=[
                 io.Int.Input("value", min=-sys.maxsize, max=sys.maxsize, control_after_generate=io.ControlAfterGenerate.fixed),
             ],
@@ -67,7 +67,7 @@ class Float(io.ComfyNode):
         return io.Schema(
             node_id="PrimitiveFloat",
             display_name="Float",
-            category="utils/primitive",
+            category="utilities/primitive",
             inputs=[
                 io.Float.Input("value", min=-sys.maxsize, max=sys.maxsize, step=0.1),
             ],
@@ -85,7 +85,7 @@ class Boolean(io.ComfyNode):
         return io.Schema(
             node_id="PrimitiveBoolean",
             display_name="Boolean",
-            category="utils/primitive",
+            category="utilities/primitive",
             inputs=[
                 io.Boolean.Input("value"),
             ],

comfy_extras/nodes_qwen.py

@@ -112,7 +112,7 @@ class EmptyQwenImageLayeredLatentImage(io.ComfyNode):
         return io.Schema(
             node_id="EmptyQwenImageLayeredLatentImage",
             display_name="Empty Qwen Image Layered Latent",
-            category="latent/qwen",
+            category="model/latent/qwen",
             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),

comfy_extras/nodes_rebatch.py

@@ -10,7 +10,7 @@ class LatentRebatch(io.ComfyNode):
         return io.Schema(
             node_id="RebatchLatents",
             display_name="Rebatch Latents",
-            category="latent/batch",
+            category="model/latent/batch",
             is_input_list=True,
             inputs=[
                 io.Latent.Input("latents"),

comfy_extras/nodes_resolution.py

@@ -35,7 +35,7 @@ class ResolutionSelector(io.ComfyNode):
         return io.Schema(
             node_id="ResolutionSelector",
             display_name="Resolution Selector",
-            category="utils",
+            category="utilities",
             description="Calculate width and height from aspect ratio and megapixel target. Useful for setting up Empty Latent Image dimensions.",
             inputs=[
                 io.Combo.Input(

comfy_extras/nodes_rope.py

@@ -7,7 +7,7 @@ class ScaleROPE(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="ScaleROPE",
-            category="advanced/model_patches",
+            category="model/patch",
             description="Scale and shift the ROPE of the model.",
             is_experimental=True,
             inputs=[

comfy_extras/nodes_sd3.py

@@ -41,7 +41,7 @@ class EmptySD3LatentImage(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="EmptySD3LatentImage",
-            category="latent/sd3",
+            category="model/latent/sd3",
             inputs=[
                 io.Int.Input("width", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),
                 io.Int.Input("height", default=1024, min=16, max=nodes.MAX_RESOLUTION, step=16),
@@ -113,7 +113,7 @@ class ControlNetApplySD3(io.ComfyNode):
         return io.Schema(
             node_id="ControlNetApplySD3",
             display_name="Apply Controlnet with VAE",
-            category="conditioning/controlnet",
+            category="model/conditioning/controlnet",
             inputs=[
                 io.Conditioning.Input("positive"),
                 io.Conditioning.Input("negative"),

comfy_extras/nodes_sdupscale.py

@@ -9,7 +9,7 @@ class SD_4XUpscale_Conditioning(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SD_4XUpscale_Conditioning",
-            category="conditioning/upscale_diffusion",
+            category="model/conditioning/upscale_diffusion",
             inputs=[
                 io.Image.Input("images"),
                 io.Conditioning.Input("positive"),

comfy_extras/nodes_stable3d.py

@@ -27,7 +27,7 @@ class StableZero123_Conditioning(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="StableZero123_Conditioning",
-            category="conditioning/3d_models",
+            category="model/conditioning/3d_models",
             inputs=[
                 io.ClipVision.Input("clip_vision"),
                 io.Image.Input("init_image"),
@@ -65,7 +65,7 @@ class StableZero123_Conditioning_Batched(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="StableZero123_Conditioning_Batched",
-            category="conditioning/3d_models",
+            category="model/conditioning/3d_models",
             inputs=[
                 io.ClipVision.Input("clip_vision"),
                 io.Image.Input("init_image"),
@@ -112,7 +112,7 @@ class SV3D_Conditioning(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SV3D_Conditioning",
-            category="conditioning/3d_models",
+            category="model/conditioning/3d_models",
             inputs=[
                 io.ClipVision.Input("clip_vision"),
                 io.Image.Input("init_image"),