ComfyUI v0.26.1

Signed-off-by: bigcat88 <bigcat88@icloud.com>

comfy_api/latest/_io.py

@@ -891,14 +891,6 @@ class Tracks(ComfyTypeIO):
         track_visibility: torch.Tensor
     Type = TrackDict
 
-@comfytype(io_type="DICT")
-class Dict(ComfyTypeIO):
-    Type = dict
-
-@comfytype(io_type="ARRAY")
-class Array(ComfyTypeIO):
-    Type = list
-
 @comfytype(io_type="COMFY_MULTITYPED_V3")
 class MultiType:
     Type = Any
@@ -1287,19 +1279,6 @@ class Color(ComfyTypeIO):
       def as_dict(self):
           return super().as_dict()
 
-
-@comfytype(io_type="COLORS")
-class Colors(ComfyTypeIO):
-    Type = list[Color.Type]
-
-    class Input(WidgetInput):
-        def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None,
-                     socketless: bool=True, default: list[str]=None, advanced: bool=None):
-            super().__init__(id, display_name, optional, tooltip, None, default, socketless, None, None, None, None, advanced)
-            if default is None:
-                self.default = []
-
-
 @comfytype(io_type="BOUNDING_BOX")
 class BoundingBox(ComfyTypeIO):
     class BoundingBoxDict(TypedDict):
@@ -1347,20 +1326,6 @@ class Curve(ComfyTypeIO):
             return d
 
 
-@comfytype(io_type="BOUNDING_BOXES")
-class BoundingBoxes(ComfyTypeIO):
-    class BoundingBoxWithMetadata(BoundingBox.BoundingBoxDict):
-        metadata: dict
-    Type = list[BoundingBoxWithMetadata]
-
-    class Input(WidgetInput):
-        def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None,
-                     socketless: bool=True, default: list[dict]=None, advanced: bool=None):
-            super().__init__(id, display_name, optional, tooltip, None, default, socketless, None, None, None, None, advanced)
-            if default is None:
-                self.default = []
-
-
 @comfytype(io_type="HISTOGRAM")
 class Histogram(ComfyTypeIO):
     """A histogram represented as a list of bin counts."""
@@ -2411,8 +2376,6 @@ __all__ = [
     "AnyType",
     "MultiType",
     "Tracks",
-    "Dict",
-    "Array",
     "Color",
     # Dynamic Types
     "MatchType",
@@ -2431,8 +2394,6 @@ __all__ = [
     "PriceBadgeDepends",
     "PriceBadge",
     "BoundingBox",
-    "BoundingBoxes",
-    "Colors",
     "Curve",
     "Histogram",
     "Range",

comfy_api_nodes/apis/bytedance.py

@@ -177,10 +177,6 @@ SEEDANCE2_PRICE_PER_1K_TOKENS = {
     ("dreamina-seedance-2-0-fast-260128", True, "480p"): 0.0033,
     ("dreamina-seedance-2-0-fast-260128", False, "720p"): 0.0056,
     ("dreamina-seedance-2-0-fast-260128", True, "720p"): 0.0033,
-    ("dreamina-seedance-2-0-mini", False, "480p"): 0.0035,
-    ("dreamina-seedance-2-0-mini", True, "480p"): 0.0021,
-    ("dreamina-seedance-2-0-mini", False, "720p"): 0.0035,
-    ("dreamina-seedance-2-0-mini", True, "720p"): 0.0021,
 }
 
 
@@ -282,10 +278,6 @@ SEEDANCE2_REF_VIDEO_PIXEL_LIMITS = {
         "480p": {"min": 409_600, "max": 927_408},
         "720p": {"min": 409_600, "max": 927_408},
     },
-    "dreamina-seedance-2-0-mini": {
-        "480p": {"min": 409_600, "max": 927_408},
-        "720p": {"min": 409_600, "max": 927_408},
-    },
 }
 
 # The time in this dictionary are given for 10 seconds duration.

comfy_api_nodes/nodes_bytedance.py

@@ -89,7 +89,6 @@ BYTEPLUS_SEEDANCE2_TASK_STATUS_ENDPOINT = "/proxy/byteplus-seedance2/api/v3/cont
 SEEDANCE_MODELS = {
     "Seedance 2.0": "dreamina-seedance-2-0-260128",
     "Seedance 2.0 Fast": "dreamina-seedance-2-0-fast-260128",
-    "Seedance 2.0 Mini": "dreamina-seedance-2-0-mini",
 }
 
 DEPRECATED_MODELS = {"seedance-1-0-lite-t2v-250428", "seedance-1-0-lite-i2v-250428"}
@@ -1624,10 +1623,8 @@ class ByteDance2TextToVideoNode(IO.ComfyNode):
                     options=[
                         IO.DynamicCombo.Option("Seedance 2.0", _seedance2_text_inputs(["480p", "720p", "1080p", "4k"])),
                         IO.DynamicCombo.Option("Seedance 2.0 Fast", _seedance2_text_inputs(["480p", "720p"])),
-                        IO.DynamicCombo.Option("Seedance 2.0 Mini", _seedance2_text_inputs(["480p", "720p"])),
                     ],
-                    tooltip="Seedance 2.0 for maximum quality; Fast for speed optimization; "
-                    "Mini for the fastest, lowest-cost generation.",
+                    tooltip="Seedance 2.0 for maximum quality; Seedance 2.0 Fast for speed optimization.",
                 ),
                 IO.Int.Input(
                     "seed",
@@ -1669,7 +1666,6 @@ class ByteDance2TextToVideoNode(IO.ComfyNode):
                   $dur := $lookup(widgets, "model.duration");
                   $pricePer1K := $res = "4k"    ? 0.00572 :
                                  $res = "1080p" ? 0.011011 :
-                                 $contains($m, "mini") ? 0.005005 :
                                  $contains($m, "fast") ? 0.008008 : 0.01001;
                   $rate := $res = "4k"    ? $rate4k :
                            $res = "1080p" ? $rate1080 :
@@ -1738,13 +1734,8 @@ class ByteDance2FirstLastFrameNode(IO.ComfyNode):
                             "Seedance 2.0 Fast",
                             _seedance2_text_inputs(["480p", "720p"], default_ratio="adaptive"),
                         ),
-                        IO.DynamicCombo.Option(
-                            "Seedance 2.0 Mini",
-                            _seedance2_text_inputs(["480p", "720p"], default_ratio="adaptive"),
-                        ),
                     ],
-                    tooltip="Seedance 2.0 for maximum quality; Fast for speed optimization; "
-                    "Mini for the fastest, lowest-cost generation.",
+                    tooltip="Seedance 2.0 for maximum quality; Seedance 2.0 Fast for speed optimization.",
                 ),
                 IO.Image.Input(
                     "first_frame",
@@ -1810,7 +1801,6 @@ class ByteDance2FirstLastFrameNode(IO.ComfyNode):
                   $dur := $lookup(widgets, "model.duration");
                   $pricePer1K := $res = "4k"    ? 0.00572 :
                                  $res = "1080p" ? 0.011011 :
-                                 $contains($m, "mini") ? 0.005005 :
                                  $contains($m, "fast") ? 0.008008 : 0.01001;
                   $rate := $res = "4k"    ? $rate4k :
                            $res = "1080p" ? $rate1080 :
@@ -2034,13 +2024,8 @@ class ByteDance2ReferenceNode(IO.ComfyNode):
                             "Seedance 2.0 Fast",
                             _seedance2_reference_inputs(["480p", "720p"], default_ratio="adaptive"),
                         ),
-                        IO.DynamicCombo.Option(
-                            "Seedance 2.0 Mini",
-                            _seedance2_reference_inputs(["480p", "720p"], default_ratio="adaptive"),
-                        ),
                     ],
-                    tooltip="Seedance 2.0 for maximum quality; Fast for speed optimization; "
-                    "Mini for the fastest, lowest-cost generation.",
+                    tooltip="Seedance 2.0 for maximum quality; Seedance 2.0 Fast for speed optimization.",
                 ),
                 IO.Int.Input(
                     "seed",
@@ -2086,11 +2071,9 @@ class ByteDance2ReferenceNode(IO.ComfyNode):
                   $dur := $lookup(widgets, "model.duration");
                   $noVideoPricePer1K := $res = "4k"    ? 0.00572 :
                                         $res = "1080p" ? 0.011011 :
-                                        $contains($m, "mini") ? 0.005005 :
                                         $contains($m, "fast") ? 0.008008 : 0.01001;
                   $videoPricePer1K := $res = "4k"    ? 0.003432 :
                                       $res = "1080p" ? 0.006721 :
-                                      $contains($m, "mini") ? 0.003003 :
                                       $contains($m, "fast") ? 0.004719 : 0.006149;
                   $rate := $res = "4k"    ? $rate4k :
                            $res = "1080p" ? $rate1080 :

comfy_extras/color_util.py

@@ -1,23 +0,0 @@
-def hex_to_rgb(value: str) -> tuple[int, int, int]:
-    h = value.lstrip("#")
-    if len(h) != 6:
-        return (255, 255, 255)
-    try:
-        return (int(h[0:2], 16), int(h[2:4], 16), int(h[4:6], 16))
-    except ValueError:
-        return (255, 255, 255)
-
-
-def readable_color(rgb: tuple[int, int, int]) -> tuple[int, int, int]:
-    r, g, b = rgb
-    lum = 0.299 * r + 0.587 * g + 0.114 * b
-    if lum >= 130:
-        return (r, g, b)
-    t = (130 - lum) / (255 - lum)
-    return (round(r + (255 - r) * t), round(g + (255 - g) * t), round(b + (255 - b) * t))
-
-
-def normalize_palette(colors) -> list[str]:
-    if isinstance(colors, dict):
-        colors = colors.values()
-    return [c.upper() for c in colors if isinstance(c, str) and c]

comfy_extras/nodes_bounding_boxes.py

@@ -1,253 +0,0 @@
-import numpy as np
-import torch
-from PIL import Image, ImageDraw, ImageEnhance, ImageFont
-from typing_extensions import override
-
-from comfy_api.latest import ComfyExtension, io
-from comfy_extras.color_util import hex_to_rgb, normalize_palette, readable_color
-
-_PREVIEW_LONG_EDGE = 1024
-_PREVIEW_DIM = 0.25
-
-
-def pixels_to_fractions(box: dict, width: int, height: int) -> dict:
-    w = width or 1
-    h = height or 1
-    return {
-        "x": box.get("x", 0) / w,
-        "y": box.get("y", 0) / h,
-        "w": box.get("width", 0) / w,
-        "h": box.get("height", 0) / h,
-    }
-
-
-def fractions_to_pixels(box: dict, width: int, height: int) -> dict:
-    x, y = box.get("x", 0.0), box.get("y", 0.0)
-    w, h = box.get("w", 0.0), box.get("h", 0.0)
-    if w < 0:
-        x, w = x + w, -w
-    if h < 0:
-        y, h = y + h, -h
-    return {
-        "x": round(x * width),
-        "y": round(y * height),
-        "width": round(w * width),
-        "height": round(h * height),
-    }
-
-
-def fractions_to_bbox_frame(boxes: list, width: int, height: int) -> list:
-    pixels = [
-        fractions_to_pixels(box, width, height)
-        for box in boxes
-        if isinstance(box, dict)
-    ]
-    return [pixels] if pixels else []
-
-
-def _font(size: int):
-    try:
-        return ImageFont.load_default(size)
-    except Exception:
-        return ImageFont.load_default()
-
-
-def _wrap(draw, text: str, font, max_w: float) -> list[str]:
-    lines = []
-    for para in text.split("\n"):
-        line = ""
-        for word in para.split():
-            test = word if not line else line + " " + word
-            if line and draw.textlength(test, font=font) > max_w:
-                lines.append(line)
-                line = word
-            else:
-                line = test
-        lines.append(line)
-    return lines
-
-
-def _bg_from_image(image) -> Image.Image | None:
-    if image is None:
-        return None
-    try:
-        arr = (image[0].detach().cpu().numpy() * 255).clip(0, 255).astype(np.uint8)
-        return Image.fromarray(arr)
-    except Exception:
-        return None
-
-
-def render_preview(regions, width, height, bg=None):
-    if bg is not None:
-        iw, ih = bg.size
-        long_edge = max(iw, ih) or 1
-        scale = min(1.0, _PREVIEW_LONG_EDGE / long_edge)
-        rw, rh = max(1, round(iw * scale)), max(1, round(ih * scale))
-        base = bg.convert("RGB").resize((rw, rh), Image.LANCZOS)
-        base = ImageEnhance.Brightness(base).enhance(_PREVIEW_DIM)
-        img = base.convert("RGBA")
-    else:
-        long_edge = max(width, height) or 1
-        scale = min(1.0, _PREVIEW_LONG_EDGE / long_edge)
-        rw, rh = max(1, round(width * scale)), max(1, round(height * scale))
-        grey = round(_PREVIEW_DIM * 128)
-        img = Image.new("RGBA", (rw, rh), (grey, grey, grey, 255))
-
-    overlay = Image.new("RGBA", (rw, rh), (0, 0, 0, 0))
-    draw = ImageDraw.Draw(overlay)
-    fs = max(10, round(rh / 64))
-    font = _font(fs)
-    tag_font = _font(max(9, fs - 2))
-    line_h = fs + 2
-
-    for i, region in enumerate(regions):
-        if not isinstance(region, dict):
-            continue
-        palette = [c for c in (region.get("palette") or []) if c]
-        r, g, b = hex_to_rgb(palette[0]) if palette else (140, 140, 140)
-        x1 = max(0, min(rw, round(region.get("x", 0) * rw)))
-        y1 = max(0, min(rh, round(region.get("y", 0) * rh)))
-        x2 = max(0, min(rw, round((region.get("x", 0) + region.get("w", 0)) * rw)))
-        y2 = max(0, min(rh, round((region.get("y", 0) + region.get("h", 0)) * rh)))
-        if x2 < x1:
-            x1, x2 = x2, x1
-        if y2 < y1:
-            y1, y2 = y2, y1
-
-        draw.rectangle([x1, y1, x2, y2], outline=(r, g, b, 255), width=2)
-
-        swatches = palette[:5]
-        if swatches and (x2 - x1) > 2:
-            sh = max(5, fs // 2)
-            seg = (x2 - x1) / len(swatches)
-            for p, hexc in enumerate(swatches):
-                sx = x1 + round(p * seg)
-                draw.rectangle([sx, y1, x1 + round((p + 1) * seg), y1 + sh], fill=hex_to_rgb(hexc))
-
-        etype = "text" if region.get("type") == "text" else "obj"
-        tag = str(i + 1).zfill(2)
-        tw = draw.textlength(tag, font=tag_font)
-        draw.rectangle([x1, y1, x1 + tw + 6, y1 + fs + 2], fill=(r, g, b, 255))
-        tag_fill = (0, 0, 0, 255) if (0.299 * r + 0.587 * g + 0.114 * b) > 140 else (255, 255, 255, 255)
-        draw.text((x1 + 3, y1 + 1), tag, fill=tag_fill, font=tag_font)
-
-        body = region.get("desc", "") or ""
-        if etype == "text" and region.get("text"):
-            body = '"%s"%s' % (region["text"], " — " + body if body else "")
-        if body and (x2 - x1) > 8:
-            ty = y1 + fs + 5
-            for line in _wrap(draw, body, font, x2 - x1 - 8):
-                if ty > y2:
-                    break
-                draw.text((x1 + 4, ty), line, fill=readable_color((r, g, b)) + (255,), font=font)
-                ty += line_h
-
-    composed = Image.alpha_composite(img, overlay).convert("RGB")
-    arr = np.asarray(composed, dtype=np.float32) / 255.0
-    return torch.from_numpy(arr).unsqueeze(0)
-
-
-def boxes_to_regions(boxes, width: int, height: int) -> list:
-    regions: list = []
-    if not isinstance(boxes, list):
-        return regions
-    for box in boxes:
-        if not isinstance(box, dict):
-            continue
-        meta = box.get("metadata")
-        meta = meta if isinstance(meta, dict) else {}
-        regions.append({
-            **pixels_to_fractions(box, width, height),
-            "type": meta.get("type", "obj"),
-            "text": meta.get("text", ""),
-            "desc": meta.get("desc", ""),
-            "palette": meta.get("palette", []),
-        })
-    return regions
-
-
-def _norm_bbox(region: dict) -> list[int]:
-    def grid(value: float) -> int:
-        return max(0, min(1000, round(value * 1000)))
-
-    x, y = region.get("x", 0.0), region.get("y", 0.0)
-    w, h = region.get("w", 0.0), region.get("h", 0.0)
-    ymin, xmin, ymax, xmax = grid(y), grid(x), grid(y + h), grid(x + w)
-    if ymin > ymax:
-        ymin, ymax = ymax, ymin
-    if xmin > xmax:
-        xmin, xmax = xmax, xmin
-    return [ymin, xmin, ymax, xmax]
-
-
-def build_elements(regions: list) -> list:
-    elements = []
-    for region in regions:
-        if not isinstance(region, dict):
-            continue
-        etype = "text" if region.get("type") == "text" else "obj"
-        element = {"type": etype}
-        element["bbox"] = _norm_bbox(region)
-        if etype == "text":
-            element["text"] = region.get("text", "")
-        element["desc"] = region.get("desc", "")
-        palette = normalize_palette(region.get("palette", []))
-        if palette:
-            element["color_palette"] = palette[:5]
-        elements.append(element)
-    return elements
-
-
-class CreateBoundingBoxes(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        editor_state = io.BoundingBoxes.Input(
-            "editor_state",
-            socketless=False,
-            tooltip="Draw bounding boxes and set each box type, text, description, color palette. Start with background element first and foreground last.",
-        )
-        return io.Schema(
-            node_id="CreateBoundingBoxes",
-            display_name="Create Bounding Boxes",
-            category="utilities",
-            description="Draw bounding boxes in a canvas. Outputs Ideogram prompt elements, pixel-space bounding boxes, and a preview image.",
-            inputs=[
-                io.Image.Input(
-                    "background",
-                    optional=True,
-                    tooltip="Optional image used as background in the canvas and preview.",
-                ),
-                io.Int.Input("width", default=1024, min=64, max=16384, step=16,
-                             tooltip="Width of the canvas and the pixel grid for the bounding boxes."),
-                io.Int.Input("height", default=1024, min=64, max=16384, step=16,
-                             tooltip="Height of the canvas and the pixel grid for the bounding boxes."),
-                editor_state,
-            ],
-            outputs=[
-                io.Image.Output(display_name="preview"),
-                io.BoundingBox.Output(display_name="bboxes"),
-                io.Array.Output(display_name="elements"),
-            ],
-            is_experimental=True,
-        )
-
-    @classmethod
-    def execute(cls, width, height, editor_state=None, background=None) -> io.NodeOutput:
-        regions = boxes_to_regions(editor_state, width, height)
-        preview = render_preview(regions, width, height, _bg_from_image(background))
-        return io.NodeOutput(
-            preview,
-            fractions_to_bbox_frame(regions, width, height),
-            build_elements(regions),
-            ui={"dims": [width, height]},
-        )
-
-
-class BoundingBoxesExtension(ComfyExtension):
-    @override
-    async def get_node_list(self) -> list[type[io.ComfyNode]]:
-        return [CreateBoundingBoxes]
-
-
-async def comfy_entrypoint() -> BoundingBoxesExtension:
-    return BoundingBoxesExtension()

comfy_extras/nodes_color.py

@@ -1,6 +1,5 @@
 from typing_extensions import override
 from comfy_api.latest import ComfyExtension, io
-from comfy_extras.color_util import hex_to_rgb
 
 
 class ColorToRGBInt(io.ComfyNode):
@@ -25,11 +24,9 @@ class ColorToRGBInt(io.ComfyNode):
         # expect format #RRGGBB
         if len(color) != 7 or color[0] != "#":
             raise ValueError("Color must be in format #RRGGBB")
-        try:
-            int(color[1:], 16)
-        except ValueError:
-            raise ValueError("Color must be in format #RRGGBB") from None
-        r, g, b = hex_to_rgb(color)
+        r = int(color[1:3], 16)
+        g = int(color[3:5], 16)
+        b = int(color[5:7], 16)
 
         rgb_int = r * 256 * 256 + g * 256 + b
         return io.NodeOutput(rgb_int, color)

comfy_extras/nodes_json_prompt.py

@@ -1,77 +0,0 @@
-from typing_extensions import override
-
-from comfy_api.latest import ComfyExtension, io
-from comfy_extras.color_util import normalize_palette
-
-
-class BuildJsonPromptIdeogram(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        color_palette = io.Colors.Input(
-            "color_palette",
-            socketless=False,
-            tooltip="Hex color codes that steer the image's dominant colors. Up to 16 entries.",
-        )
-        return io.Schema(
-            node_id="BuildJsonPromptIdeogram",
-            display_name="Build JSON Prompt (Ideogram)",
-            category="text",
-            description="Build a JSON prompt for the Ideogram 4 model.",
-            inputs=[
-                io.Array.Input("element", tooltip="Prompt elements from the node Create Bounding Boxes."),
-                io.String.Input("high_level_description", multiline=True, default="",
-                                tooltip="Optional description of the image in one or two sentences. Strongly recommended."),
-                io.String.Input("background", multiline=True, default="",
-                                tooltip="Mandatory description of the image background or environment."),
-                io.DynamicCombo.Input("style", options=[
-                    io.DynamicCombo.Option("none", []),
-                    io.DynamicCombo.Option("photo", [io.String.Input("photo", default="", tooltip="Camera or lens details for photographic outputs (e.g. 35mm, f/1.4, bokeh).")]),
-                    io.DynamicCombo.Option("art_style", [io.String.Input("art_style", default="", tooltip="Art style description (e.g. flat vector illustration, bold outlines).")]),
-                ]),
-                io.String.Input("aesthetics", default="", tooltip="Mandatory aesthetic keywords (e.g. moody, cinematic, desaturated)."),
-                io.String.Input("lighting", default="", tooltip="Mandatory lighting description (e.g. golden hour, rim light, dramatic shadows)."),
-                io.String.Input("medium", default="", tooltip="Mandatory medium type (e.g. photograph, illustration, 3d_render, painting, graphic_design). When style = photo, set to photograph."),
-                color_palette,
-            ],
-            outputs=[io.Dict.Output(display_name="prompt")],
-            is_experimental=True,
-        )
-
-    @classmethod
-    def execute(cls, element, style, high_level_description="", background="",
-                aesthetics="", lighting="", medium="", color_palette=None) -> io.NodeOutput:
-        elements = element if isinstance(element, list) else []
-        kind = style.get("style", "none") if isinstance(style, dict) else "none"
-        photo = style.get("photo", "") if isinstance(style, dict) else ""
-        art_style = style.get("art_style", "") if isinstance(style, dict) else ""
-        palette = normalize_palette(color_palette or [])
-
-        caption: dict = {}
-        if high_level_description.strip():
-            caption["high_level_description"] = high_level_description
-        if kind != "none":
-            style_desc: dict = {"aesthetics": aesthetics, "lighting": lighting}
-            if kind == "photo":
-                style_desc["photo"] = photo
-                style_desc["medium"] = medium
-            else:
-                style_desc["medium"] = medium
-                style_desc["art_style"] = art_style
-            if palette:
-                style_desc["color_palette"] = palette
-            caption["style_description"] = style_desc
-        caption["compositional_deconstruction"] = {
-            "background": background,
-            "elements": elements,
-        }
-        return io.NodeOutput(caption)
-
-
-class JsonPromptExtension(ComfyExtension):
-    @override
-    async def get_node_list(self) -> list[type[io.ComfyNode]]:
-        return [BuildJsonPromptIdeogram]
-
-
-async def comfy_entrypoint() -> JsonPromptExtension:
-    return JsonPromptExtension()

comfy_extras/nodes_model_merging_model_specific.py

@@ -337,36 +337,6 @@ class ModelMergeQwenImage(comfy_extras.nodes_model_merging.ModelMergeBlocks):
 
         return {"required": arg_dict}
 
-class ModelMergeKrea2(comfy_extras.nodes_model_merging.ModelMergeBlocks):
-    CATEGORY = "model/merging/model specific"
-
-    @classmethod
-    def INPUT_TYPES(s):
-        arg_dict = { "model1": ("MODEL",),
-                              "model2": ("MODEL",)}
-
-        argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
-
-        arg_dict["first."] = argument
-        arg_dict["tmlp."] = argument
-        arg_dict["txtmlp."] = argument
-        arg_dict["tproj."] = argument
-
-        for i in range(2):
-            arg_dict["txtfusion.layerwise_blocks.{}.".format(i)] = argument
-
-        arg_dict["txtfusion.projector."] = argument
-
-        for i in range(2):
-            arg_dict["txtfusion.refiner_blocks.{}.".format(i)] = argument
-
-        for i in range(28):
-            arg_dict["blocks.{}.".format(i)] = argument
-
-        arg_dict["last."] = argument
-
-        return {"required": arg_dict}
-
 NODE_CLASS_MAPPINGS = {
     "ModelMergeSD1": ModelMergeSD1,
     "ModelMergeSD2": ModelMergeSD1, #SD1 and SD2 have the same blocks
@@ -383,5 +353,4 @@ NODE_CLASS_MAPPINGS = {
     "ModelMergeCosmosPredict2_2B": ModelMergeCosmosPredict2_2B,
     "ModelMergeCosmosPredict2_14B": ModelMergeCosmosPredict2_14B,
     "ModelMergeQwenImage": ModelMergeQwenImage,
-    "ModelMergeKrea2": ModelMergeKrea2,
 }

comfy_extras/nodes_seed.py

@@ -1,33 +0,0 @@
-import sys
-from typing_extensions import override
-
-from comfy_api.latest import ComfyExtension, io
-
-
-class SeedNode(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return io.Schema(
-            node_id="SeedNode",
-            display_name="Seed",
-            search_aliases=["seed", "random"],
-            category="utilities",
-            inputs=[
-                io.Int.Input("seed", min=0, max=sys.maxsize, control_after_generate=io.ControlAfterGenerate.fixed),
-            ],
-            outputs=[io.Int.Output(display_name="seed")],
-        )
-
-    @classmethod
-    def execute(cls, seed: int) -> io.NodeOutput:
-        return io.NodeOutput(seed)
-
-
-class SeedExtension(ComfyExtension):
-    @override
-    async def get_node_list(self) -> list[type[io.ComfyNode]]:
-        return [SeedNode]
-
-
-async def comfy_entrypoint() -> SeedExtension:
-    return SeedExtension()

comfy_extras/nodes_string.py

@@ -440,57 +440,6 @@ class JsonExtractString(io.ComfyNode):
         except (json.JSONDecodeError, TypeError):
             return io.NodeOutput("")
 
-
-def _dump_json(value, indent):
-    return json.dumps(value, ensure_ascii=False, indent=indent or None)
-
-
-class ConvertDictionaryToString(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return io.Schema(
-            node_id="ConvertDictionaryToString",
-            display_name="Convert Dictionary to String",
-            category="text",
-            search_aliases=["json", "dict to json", "stringify", "serialize", "dict to string"],
-            inputs=[
-                io.Dict.Input("dictionary"),
-                io.Int.Input("indent", default=2, min=0, max=8,
-                             tooltip="Spaces per indent level. 0 produces compact single-line string."),
-            ],
-            outputs=[
-                io.String.Output(),
-            ],
-        )
-
-    @classmethod
-    def execute(cls, dictionary, indent=2):
-        return io.NodeOutput(_dump_json(dictionary, indent))
-
-
-class ConvertArrayToString(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return io.Schema(
-            node_id="ConvertArrayToString",
-            display_name="Convert Array to String",
-            category="text",
-            search_aliases=["json", "list to json", "stringify", "serialize", "list to string", "array to json"],
-            inputs=[
-                io.Array.Input("array"),
-                io.Int.Input("indent", default=2, min=0, max=8,
-                             tooltip="Spaces per indent level. 0 produces compact single-line string."),
-            ],
-            outputs=[
-                io.String.Output(),
-            ],
-        )
-
-    @classmethod
-    def execute(cls, array, indent=2):
-        return io.NodeOutput(_dump_json(array, indent))
-
-
 class StringExtension(ComfyExtension):
     @override
     async def get_node_list(self) -> list[type[io.ComfyNode]]:
@@ -508,8 +457,6 @@ class StringExtension(ComfyExtension):
             RegexExtract,
             RegexReplace,
             JsonExtractString,
-            ConvertDictionaryToString,
-            ConvertArrayToString,
         ]
 
 async def comfy_entrypoint() -> StringExtension:

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.26.0"
+__version__ = "0.26.1"

nodes.py

@@ -2374,8 +2374,6 @@ async def init_builtin_extra_nodes():
         "nodes_images.py",
         "nodes_video_model.py",
         "nodes_ideogram4.py",
-        "nodes_bounding_boxes.py",
-        "nodes_json_prompt.py",
         "nodes_train.py",
         "nodes_dataset.py",
         "nodes_sag.py",
@@ -2475,7 +2473,6 @@ async def init_builtin_extra_nodes():
         "nodes_gaussian_splat.py",
         "nodes_triposplat.py",
         "nodes_depth_anything_3.py",
-        "nodes_seed.py",
     ]
 
     import_failed = []

openapi.yaml

@@ -1692,12 +1692,6 @@ paths:
                             schema:
                                 $ref: '#/components/schemas/ErrorResponse'
                     description: Unsupported media type
-                "422":
-                    content:
-                        application/json:
-                            schema:
-                                $ref: '#/components/schemas/ErrorResponse'
-                    description: Validation error (e.g., disallowed model_type tag)
                 "500":
                     content:
                         application/json:
@@ -2143,12 +2137,6 @@ paths:
                             schema:
                                 $ref: '#/components/schemas/ErrorResponse'
                     description: Source asset with given hash not found
-                "422":
-                    content:
-                        application/json:
-                            schema:
-                                $ref: '#/components/schemas/ErrorResponse'
-                    description: Validation error (e.g., disallowed model_type tag)
                 "500":
                     content:
                         application/json:
@@ -2369,10 +2357,6 @@ paths:
             description: |
                 Returns a list of model folders available in the system.
                 This is an experimental endpoint that replaces the legacy /models endpoint.
-                Each folder's name is the identifier to pass to /api/experiment/models/{folder}.
-                Once the model_type migration is active the names are model_type folder_names
-                (e.g. `ultralytics_bbox`); a folder with no folder_name mapping is returned by
-                its directory path.
             operationId: getModelFolders
             responses:
                 "200":
@@ -3004,7 +2988,7 @@ paths:
                     format: uuid
                     type: string
                 - description: |
-                    When present, each output item in the response receives a `short_url` field containing a short link for that asset. Omit this parameter (the default) to receive a response identical to the no-param baseline. The value selects the link's lifetime and auth model: use `ephemeral_tool_chain` for short-lived (≤5 minute) machine-to-machine handoffs — these are public bearer links where the link ID itself is the credential, so anyone holding the link can resolve it (intended for pasting into an agent/MCP tool chain); use `default` for durable (30 day) human-revisitable links, which are owner-gated and resolvable only by the authenticated owner. Links are always minted under the authenticated request owner's identity; the auth model is selected by the server and is never settable by the caller.
+                    When present, each output item in the response receives a `short_url` field containing an owner-gated durable link for that asset. Omit this parameter (the default) to receive a response identical to the no-param baseline. The value selects the link's lifetime: use `ephemeral_tool_chain` for short-lived machine-to-machine handoffs (~15 minutes); use `default` for durable human-revisitable links (30 days). Links are minted only for the authenticated request owner and are not resolvable by other users.
                   in: query
                   name: short_link
                   schema:

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.26.0"
+version = "0.26.1"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.10"

requirements.txt

@@ -1,5 +1,5 @@
 comfyui-frontend-package==1.45.19
-comfyui-workflow-templates==0.10.7
+comfyui-workflow-templates==0.10.2
 comfyui-embedded-docs==0.5.5
 torch
 torchsde