fix line endings

using moderngl package

.github/workflows/test-build.yml

@@ -25,6 +25,10 @@ jobs:
         uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
+      - name: Install system dependencies
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y libx11-dev
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip

comfy/latent_formats.py

@@ -81,7 +81,6 @@ class SD_X4(LatentFormat):
 
 class SC_Prior(LatentFormat):
     latent_channels = 16
-    spacial_downscale_ratio = 42
     def __init__(self):
         self.scale_factor = 1.0
         self.latent_rgb_factors = [
@@ -104,7 +103,6 @@ class SC_Prior(LatentFormat):
         ]
 
 class SC_B(LatentFormat):
-    spacial_downscale_ratio = 4
     def __init__(self):
         self.scale_factor = 1.0 / 0.43
         self.latent_rgb_factors = [
@@ -276,7 +274,6 @@ class Mochi(LatentFormat):
 class LTXV(LatentFormat):
     latent_channels = 128
     latent_dimensions = 3
-    spacial_downscale_ratio = 32
 
     def __init__(self):
         self.latent_rgb_factors = [
@@ -520,7 +517,6 @@ class Wan21(LatentFormat):
 class Wan22(Wan21):
     latent_channels = 48
     latent_dimensions = 3
-    spacial_downscale_ratio = 16
 
     latent_rgb_factors = [
             [ 0.0119,  0.0103,  0.0046],

comfy_api/latest/_io.py

@@ -1146,20 +1146,6 @@ class ImageCompare(ComfyTypeI):
       def as_dict(self):
           return super().as_dict()
 
-
-@comfytype(io_type="COLOR")
-class Color(ComfyTypeIO):
-  Type = str
-
-  class Input(WidgetInput):
-      def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None,
-                   socketless: bool=True, advanced: bool=None, default: str="#ffffff"):
-          super().__init__(id, display_name, optional, tooltip, None, default, socketless, None, None, None, None, advanced)
-          self.default: str
-
-      def as_dict(self):
-          return super().as_dict()
-
 DYNAMIC_INPUT_LOOKUP: dict[str, Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]] = {}
 def register_dynamic_input_func(io_type: str, func: Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]):
     DYNAMIC_INPUT_LOOKUP[io_type] = func
@@ -1266,6 +1252,23 @@ class NodeInfoV1:
     price_badge: dict | None = None
     search_aliases: list[str]=None
 
+@dataclass
+class NodeInfoV3:
+    input: dict=None
+    output: dict=None
+    hidden: list[str]=None
+    name: str=None
+    display_name: str=None
+    description: str=None
+    python_module: Any = None
+    category: str=None
+    output_node: bool=None
+    deprecated: bool=None
+    experimental: bool=None
+    dev_only: bool=None
+    api_node: bool=None
+    price_badge: dict | None = None
+
 
 @dataclass
 class PriceBadgeDepends:
@@ -1494,6 +1497,40 @@ class Schema:
         )
         return info
 
+
+    def get_v3_info(self, cls) -> NodeInfoV3:
+        input_dict = {}
+        output_dict = {}
+        hidden_list = []
+        # TODO: make sure dynamic types will be handled correctly
+        if self.inputs:
+            for input in self.inputs:
+                add_to_dict_v3(input, input_dict)
+        if self.outputs:
+            for output in self.outputs:
+                add_to_dict_v3(output, output_dict)
+        if self.hidden:
+            for hidden in self.hidden:
+                hidden_list.append(hidden.value)
+
+        info = NodeInfoV3(
+            input=input_dict,
+            output=output_dict,
+            hidden=hidden_list,
+            name=self.node_id,
+            display_name=self.display_name,
+            description=self.description,
+            category=self.category,
+            output_node=self.is_output_node,
+            deprecated=self.is_deprecated,
+            experimental=self.is_experimental,
+            dev_only=self.is_dev_only,
+            api_node=self.is_api_node,
+            python_module=getattr(cls, "RELATIVE_PYTHON_MODULE", "nodes"),
+            price_badge=self.price_badge.as_dict(self.inputs) if self.price_badge is not None else None,
+        )
+        return info
+
 def get_finalized_class_inputs(d: dict[str, Any], live_inputs: dict[str, Any], include_hidden=False) -> tuple[dict[str, Any], V3Data]:
     out_dict = {
         "required": {},
@@ -1548,6 +1585,9 @@ def add_to_dict_v1(i: Input, d: dict):
     as_dict.pop("optional", None)
     d.setdefault(key, {})[i.id] = (i.get_io_type(), as_dict)
 
+def add_to_dict_v3(io: Input | Output, d: dict):
+    d[io.id] = (io.get_io_type(), io.as_dict())
+
 class DynamicPathsDefaultValue:
     EMPTY_DICT = "empty_dict"
 
@@ -1708,6 +1748,13 @@ class _ComfyNodeBaseInternal(_ComfyNodeInternal):
         # set hidden
         type_clone.hidden = HiddenHolder.from_v3_data(v3_data)
         return type_clone
+
+    @final
+    @classmethod
+    def GET_NODE_INFO_V3(cls) -> dict[str, Any]:
+        schema = cls.GET_SCHEMA()
+        info = schema.get_v3_info(cls)
+        return asdict(info)
     #############################################
     # V1 Backwards Compatibility code
     #--------------------------------------------
@@ -2052,7 +2099,6 @@ __all__ = [
     "AnyType",
     "MultiType",
     "Tracks",
-    "Color",
     # Dynamic Types
     "MatchType",
     "DynamicCombo",
@@ -2061,10 +2107,12 @@ __all__ = [
     "HiddenHolder",
     "Hidden",
     "NodeInfoV1",
+    "NodeInfoV3",
     "Schema",
     "ComfyNode",
     "NodeOutput",
     "add_to_dict_v1",
+    "add_to_dict_v3",
     "V3Data",
     "ImageCompare",
     "PriceBadgeDepends",

comfy_api_nodes/apis/recraft.py

@@ -1,8 +1,11 @@
 from __future__ import annotations
 
-from enum import Enum
 
-from pydantic import BaseModel, Field
+
+from enum import Enum
+from typing import Optional
+
+from pydantic import BaseModel, Field, conint, confloat
 
 
 class RecraftColor:
@@ -226,24 +229,24 @@ class RecraftColorObject(BaseModel):
 
 
 class RecraftControlsObject(BaseModel):
-    colors: list[RecraftColorObject] | None = Field(None, description='An array of preferable colors')
-    background_color: RecraftColorObject | None = Field(None, description='Use given color as a desired background color')
-    no_text: bool | None = Field(None, description='Do not embed text layouts')
-    artistic_level: int | None = Field(None, description='Defines artistic tone of your image. At a simple level, the person looks straight at the camera in a static and clean style. Dynamic and eccentric levels introduce movement and creativity. The value should be in range [0..5].')
+    colors: Optional[list[RecraftColorObject]] = Field(None, description='An array of preferable colors')
+    background_color: Optional[RecraftColorObject] = Field(None, description='Use given color as a desired background color')
+    no_text: Optional[bool] = Field(None, description='Do not embed text layouts')
+    artistic_level: Optional[conint(ge=0, le=5)] = Field(None, description='Defines artistic tone of your image. At a simple level, the person looks straight at the camera in a static and clean style. Dynamic and eccentric levels introduce movement and creativity. The value should be in range [0..5].')
 
 
 class RecraftImageGenerationRequest(BaseModel):
     prompt: str = Field(..., description='The text prompt describing the image to generate')
-    size: RecraftImageSize | None = Field(None, description='The size of the generated image (e.g., "1024x1024")')
-    n: int = Field(..., description='The number of images to generate')
-    negative_prompt: str | None = Field(None, description='A text description of undesired elements on an image')
-    model: RecraftModel | None = Field(RecraftModel.recraftv3, description='The model to use for generation (e.g., "recraftv3")')
-    style: str | None = Field(None, description='The style to apply to the generated image (e.g., "digital_illustration")')
-    substyle: str | None = Field(None, description='The substyle to apply to the generated image, depending on the style input')
-    controls: RecraftControlsObject | None = Field(None, description='A set of custom parameters to tweak generation process')
-    style_id: str | None = Field(None, description='Use a previously uploaded style as a reference; UUID')
-    strength: float | None = Field(None, description='Defines the difference with the original image, should lie in [0, 1], where 0 means almost identical, and 1 means miserable similarity')
-    random_seed: int | None = Field(None, description="Seed for video generation")
+    size: Optional[RecraftImageSize] = Field(None, description='The size of the generated image (e.g., "1024x1024")')
+    n: conint(ge=1, le=6) = Field(..., description='The number of images to generate')
+    negative_prompt: Optional[str] = Field(None, description='A text description of undesired elements on an image')
+    model: Optional[RecraftModel] = Field(RecraftModel.recraftv3, description='The model to use for generation (e.g., "recraftv3")')
+    style: Optional[str] = Field(None, description='The style to apply to the generated image (e.g., "digital_illustration")')
+    substyle: Optional[str] = Field(None, description='The substyle to apply to the generated image, depending on the style input')
+    controls: Optional[RecraftControlsObject] = Field(None, description='A set of custom parameters to tweak generation process')
+    style_id: Optional[str] = Field(None, description='Use a previously uploaded style as a reference; UUID')
+    strength: Optional[confloat(ge=0.0, le=1.0)] = Field(None, description='Defines the difference with the original image, should lie in [0, 1], where 0 means almost identical, and 1 means miserable similarity')
+    random_seed: Optional[int] = Field(None, description="Seed for video generation")
     # text_layout
 
 
@@ -255,13 +258,5 @@ class RecraftReturnedObject(BaseModel):
 class RecraftImageGenerationResponse(BaseModel):
     created: int = Field(..., description='Unix timestamp when the generation was created')
     credits: int = Field(..., description='Number of credits used for the generation')
-    data: list[RecraftReturnedObject] | None = Field(None, description='Array of generated image information')
-    image: RecraftReturnedObject | None = Field(None, description='Single generated image')
-
-
-class RecraftCreateStyleRequest(BaseModel):
-    style: str = Field(..., description="realistic_image, digital_illustration, vector_illustration, or icon")
-
-
-class RecraftCreateStyleResponse(BaseModel):
-    id: str = Field(..., description="UUID of the created style")
+    data: Optional[list[RecraftReturnedObject]] = Field(None, description='Array of generated image information')
+    image: Optional[RecraftReturnedObject] = Field(None, description='Single generated image')

comfy_api_nodes/nodes_recraft.py

@@ -12,8 +12,6 @@ from comfy_api_nodes.apis.recraft import (
     RecraftColor,
     RecraftColorChain,
     RecraftControls,
-    RecraftCreateStyleRequest,
-    RecraftCreateStyleResponse,
     RecraftImageGenerationRequest,
     RecraftImageGenerationResponse,
     RecraftImageSize,
@@ -325,75 +323,6 @@ class RecraftStyleInfiniteStyleLibrary(IO.ComfyNode):
         return IO.NodeOutput(RecraftStyle(style_id=style_id))
 
 
-class RecraftCreateStyleNode(IO.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return IO.Schema(
-            node_id="RecraftCreateStyleNode",
-            display_name="Recraft Create Style",
-            category="api node/image/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.",
-            inputs=[
-                IO.Combo.Input(
-                    "style",
-                    options=["realistic_image", "digital_illustration"],
-                    tooltip="The base style of the generated images.",
-                ),
-                IO.Autogrow.Input(
-                    "images",
-                    template=IO.Autogrow.TemplatePrefix(
-                        IO.Image.Input("image"),
-                        prefix="image",
-                        min=1,
-                        max=5,
-                    ),
-                ),
-            ],
-            outputs=[
-                IO.String.Output(display_name="style_id"),
-            ],
-            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(
-                expr="""{"type":"usd","usd": 0.04}""",
-            ),
-        )
-
-    @classmethod
-    async def execute(
-        cls,
-        style: str,
-        images: IO.Autogrow.Type,
-    ) -> IO.NodeOutput:
-        files = []
-        total_size = 0
-        max_total_size = 5 * 1024 * 1024  # 5 MB limit
-        for i, img in enumerate(list(images.values())):
-            file_bytes = tensor_to_bytesio(img, total_pixels=2048 * 2048, mime_type="image/webp").read()
-            total_size += len(file_bytes)
-            if total_size > max_total_size:
-                raise Exception("Total size of all images exceeds 5 MB limit.")
-            files.append((f"file{i + 1}", file_bytes))
-
-        response = await sync_op(
-            cls,
-            endpoint=ApiEndpoint(path="/proxy/recraft/styles", method="POST"),
-            response_model=RecraftCreateStyleResponse,
-            files=files,
-            data=RecraftCreateStyleRequest(style=style),
-            content_type="multipart/form-data",
-            max_retries=1,
-        )
-
-        return IO.NodeOutput(response.id)
-
-
 class RecraftTextToImageNode(IO.ComfyNode):
     @classmethod
     def define_schema(cls):
@@ -466,7 +395,7 @@ class RecraftTextToImageNode(IO.ComfyNode):
         negative_prompt: str = None,
         recraft_controls: RecraftControls = None,
     ) -> IO.NodeOutput:
-        validate_string(prompt, strip_whitespace=False, min_length=1, max_length=1000)
+        validate_string(prompt, strip_whitespace=False, max_length=1000)
         default_style = RecraftStyle(RecraftStyleV3.realistic_image)
         if recraft_style is None:
             recraft_style = default_style
@@ -1095,7 +1024,6 @@ class RecraftExtension(ComfyExtension):
             RecraftStyleV3DigitalIllustrationNode,
             RecraftStyleV3LogoRasterNode,
             RecraftStyleInfiniteStyleLibrary,
-            RecraftCreateStyleNode,
             RecraftColorRGBNode,
             RecraftControlsNode,
         ]

comfy_execution/jobs.py

@@ -171,10 +171,9 @@ def get_outputs_summary(outputs: dict) -> tuple[int, Optional[dict]]:
                 continue
 
             for item in items:
-                count += 1
-
                 if not isinstance(item, dict):
                     continue
+                count += 1
 
                 if preview_output is None and is_previewable(media_type, item):
                     enriched = {

comfy_extras/nodes_color.py

@@ -1,42 +0,0 @@
-from typing_extensions import override
-from comfy_api.latest import ComfyExtension, io
-
-
-class ColorToRGBInt(io.ComfyNode):
-    @classmethod
-    def define_schema(cls) -> io.Schema:
-        return io.Schema(
-            node_id="ColorToRGBInt",
-            display_name="Color to RGB Int",
-            category="utils",
-            description="Convert a color to a RGB integer value.",
-            inputs=[
-                io.Color.Input("color"),
-            ],
-            outputs=[
-                io.Int.Output(display_name="rgb_int"),
-            ],
-        )
-
-    @classmethod
-    def execute(
-        cls,
-        color: str,
-    ) -> io.NodeOutput:
-        # expect format #RRGGBB
-        if len(color) != 7 or color[0] != "#":
-            raise ValueError("Color must be in format #RRGGBB")
-        r = int(color[1:3], 16)
-        g = int(color[3:5], 16)
-        b = int(color[5:7], 16)
-        return io.NodeOutput(r * 256 * 256 + g * 256 + b)
-
-
-class ColorExtension(ComfyExtension):
-    @override
-    async def get_node_list(self) -> list[type[io.ComfyNode]]:
-        return [ColorToRGBInt]
-
-
-async def comfy_entrypoint() -> ColorExtension:
-    return ColorExtension()

comfy_extras/nodes_glsl.py

@@ -0,0 +1,439 @@
+import os
+import re
+import logging
+from contextlib import contextmanager
+from typing import TypedDict, Generator
+
+import numpy as np
+import torch
+
+import nodes
+from comfy_api.latest import ComfyExtension, io, ui
+from comfy.cli_args import args
+from typing_extensions import override
+from utils.install_util import get_missing_requirements_message
+
+
+class SizeModeInput(TypedDict):
+    size_mode: str
+    width: int
+    height: int
+
+
+MAX_IMAGES = 5      # u_image0-4
+MAX_UNIFORMS = 5    # u_float0-4, u_int0-4
+MAX_OUTPUTS = 4     # fragColor0-3 (MRT)
+
+logger = logging.getLogger(__name__)
+
+try:
+    import moderngl
+except ImportError as e:
+    raise RuntimeError(f"ModernGL is not available.\n{get_missing_requirements_message()}") from e
+
+# Default NOOP fragment shader that passes through the input image unchanged
+# For multiple outputs, use: layout(location = 0) out vec4 fragColor0; etc.
+DEFAULT_FRAGMENT_SHADER = """#version 300 es
+precision highp float;
+
+uniform sampler2D u_image0;
+uniform vec2 u_resolution;
+
+in vec2 v_texCoord;
+layout(location = 0) out vec4 fragColor0;
+
+void main() {
+    fragColor0 = texture(u_image0, v_texCoord);
+}
+"""
+
+
+# Simple vertex shader for full-screen quad
+VERTEX_SHADER = """#version 330
+
+in vec2 in_position;
+in vec2 in_texcoord;
+
+out vec2 v_texCoord;
+
+void main() {
+    gl_Position = vec4(in_position, 0.0, 1.0);
+    v_texCoord = in_texcoord;
+}
+"""
+
+
+def _convert_es_to_desktop_glsl(source: str) -> str:
+    """Convert GLSL ES 3.00 shader to desktop GLSL 3.30 for ModernGL compatibility."""
+    return re.sub(r'#version\s+300\s+es', '#version 330', source)
+
+
+def _create_software_gl_context() -> moderngl.Context:
+    original_env = os.environ.get("LIBGL_ALWAYS_SOFTWARE")
+    os.environ["LIBGL_ALWAYS_SOFTWARE"] = "1"
+    try:
+        ctx = moderngl.create_standalone_context(require=330)
+        logger.info(f"Created software-rendered OpenGL context: {ctx.info['GL_RENDERER']}")
+        return ctx
+    finally:
+        if original_env is None:
+            os.environ.pop("LIBGL_ALWAYS_SOFTWARE", None)
+        else:
+            os.environ["LIBGL_ALWAYS_SOFTWARE"] = original_env
+
+
+def _create_gl_context(force_software: bool = False) -> moderngl.Context:
+    if force_software:
+        try:
+            return _create_software_gl_context()
+        except Exception as e:
+            raise RuntimeError(
+                "Failed to create software-rendered OpenGL context.\n"
+                "Ensure Mesa/llvmpipe is installed for software rendering support."
+            ) from e
+
+    # Try hardware rendering first, fall back to software
+    try:
+        ctx = moderngl.create_standalone_context(require=330)
+        logger.info(f"Created OpenGL context: {ctx.info['GL_RENDERER']}")
+        return ctx
+    except Exception as hw_error:
+        logger.warning(f"Hardware OpenGL context creation failed: {hw_error}")
+        logger.info("Attempting software rendering fallback...")
+        try:
+            return _create_software_gl_context()
+        except Exception as sw_error:
+            raise RuntimeError(
+                f"Failed to create OpenGL context.\n"
+                f"Hardware error: {hw_error}\n\n"
+                f"Possible solutions:\n"
+                f"1. Install GPU drivers with OpenGL 3.3+ support\n"
+                f"2. Install Mesa for software rendering (Linux: apt install libgl1-mesa-dri)\n"
+                f"3. On headless servers, ensure virtual framebuffer (Xvfb) or EGL is available"
+            ) from sw_error
+
+
+def _image_to_texture(ctx: moderngl.Context, image: np.ndarray) -> moderngl.Texture:
+    height, width = image.shape[:2]
+    channels = image.shape[2] if len(image.shape) > 2 else 1
+
+    components = min(channels, 4)
+
+    image_uint8 = (np.clip(image, 0, 1) * 255).astype(np.uint8)
+
+    # Flip vertically for OpenGL coordinate system (origin at bottom-left)
+    image_uint8 = np.ascontiguousarray(np.flipud(image_uint8))
+
+    texture = ctx.texture((width, height), components, image_uint8.tobytes())
+    texture.filter = (moderngl.LINEAR, moderngl.LINEAR)
+    texture.repeat_x = False
+    texture.repeat_y = False
+
+    return texture
+
+
+def _texture_to_image(fbo: moderngl.Framebuffer, attachment: int = 0, channels: int = 4) -> np.ndarray:
+    width, height = fbo.size
+
+    data = fbo.read(components=channels, attachment=attachment)
+    image = np.frombuffer(data, dtype=np.uint8).reshape((height, width, channels))
+
+    image = np.ascontiguousarray(np.flipud(image))
+
+    return image.astype(np.float32) / 255.0
+
+
+def _compile_shader(ctx: moderngl.Context, fragment_source: str) -> moderngl.Program:
+    # Convert user's GLSL ES 3.00 fragment shader to desktop GLSL 3.30 for ModernGL
+    fragment_source = _convert_es_to_desktop_glsl(fragment_source)
+
+    try:
+        program = ctx.program(
+            vertex_shader=VERTEX_SHADER,
+            fragment_shader=fragment_source,
+        )
+        return program
+    except Exception as e:
+        raise RuntimeError(
+            "Fragment shader compilation failed.\n\n"
+            "Make sure your shader:\n"
+            "1. Uses #version 300 es (WebGL 2.0 compatible)\n"
+            "2. Has valid GLSL ES 3.00 syntax\n"
+            "3. Includes 'precision highp float;' after version\n"
+            "4. Uses 'out vec4 fragColor' instead of gl_FragColor\n"
+            "5. Declares uniforms correctly (e.g., uniform sampler2D u_image0;)"
+        ) from e
+
+
+def _render_shader(
+    ctx: moderngl.Context,
+    program: moderngl.Program,
+    width: int,
+    height: int,
+    textures: list[moderngl.Texture],
+    uniforms: dict[str, int | float],
+) -> list[np.ndarray]:
+    # Create output textures
+    output_textures = []
+    for _ in range(MAX_OUTPUTS):
+        tex = ctx.texture((width, height), 4)
+        tex.filter = (moderngl.LINEAR, moderngl.LINEAR)
+        output_textures.append(tex)
+
+    fbo = ctx.framebuffer(color_attachments=output_textures)
+
+    # Full-screen quad vertices (position + texcoord)
+    vertices = np.array([
+        # Position (x, y), Texcoord (u, v)
+        -1.0, -1.0, 0.0, 0.0,
+        1.0, -1.0, 1.0, 0.0,
+        -1.0, 1.0, 0.0, 1.0,
+        1.0, 1.0, 1.0, 1.0,
+    ], dtype='f4')
+
+    vbo = ctx.buffer(vertices.tobytes())
+    vao = ctx.vertex_array(
+        program,
+        [(vbo, '2f 2f', 'in_position', 'in_texcoord')],
+    )
+
+    try:
+        # Bind textures
+        for i, texture in enumerate(textures):
+            texture.use(i)
+            uniform_name = f'u_image{i}'
+            if uniform_name in program:
+                program[uniform_name].value = i
+
+        # Set uniforms
+        if 'u_resolution' in program:
+            program['u_resolution'].value = (float(width), float(height))
+
+        for name, value in uniforms.items():
+            if name in program:
+                program[name].value = value
+
+        # Render
+        fbo.use()
+        fbo.clear(0.0, 0.0, 0.0, 1.0)
+        vao.render(moderngl.TRIANGLE_STRIP)
+
+        # Read results from all attachments
+        results = []
+        for i in range(MAX_OUTPUTS):
+            results.append(_texture_to_image(fbo, attachment=i, channels=4))
+        return results
+    finally:
+        vao.release()
+        vbo.release()
+        for tex in output_textures:
+            tex.release()
+        fbo.release()
+
+
+def _prepare_textures(
+    ctx: moderngl.Context,
+    image_list: list[torch.Tensor],
+    batch_idx: int,
+) -> list[moderngl.Texture]:
+    textures = []
+    for img_tensor in image_list[:MAX_IMAGES]:
+        img_idx = min(batch_idx, img_tensor.shape[0] - 1)
+        img_np = img_tensor[img_idx].cpu().numpy()
+        textures.append(_image_to_texture(ctx, img_np))
+    return textures
+
+
+def _prepare_uniforms(int_list: list[int], float_list: list[float]) -> dict[str, int | float]:
+    uniforms: dict[str, int | float] = {}
+    for i, val in enumerate(int_list[:MAX_UNIFORMS]):
+        uniforms[f'u_int{i}'] = int(val)
+    for i, val in enumerate(float_list[:MAX_UNIFORMS]):
+        uniforms[f'u_float{i}'] = float(val)
+    return uniforms
+
+
+def _release_textures(textures: list[moderngl.Texture]) -> None:
+    for texture in textures:
+        texture.release()
+
+
+@contextmanager
+def _gl_context(force_software: bool = False) -> Generator[moderngl.Context, None, None]:
+    ctx = _create_gl_context(force_software)
+    try:
+        yield ctx
+    finally:
+        ctx.release()
+
+
+@contextmanager
+def _shader_program(ctx: moderngl.Context, fragment_source: str) -> Generator[moderngl.Program, None, None]:
+    program = _compile_shader(ctx, fragment_source)
+    try:
+        yield program
+    finally:
+        program.release()
+
+
+@contextmanager
+def _textures_context(
+    ctx: moderngl.Context,
+    image_list: list[torch.Tensor],
+    batch_idx: int,
+) -> Generator[list[moderngl.Texture], None, None]:
+    textures = _prepare_textures(ctx, image_list, batch_idx)
+    try:
+        yield textures
+    finally:
+        _release_textures(textures)
+
+
+class GLSLShader(io.ComfyNode):
+
+    @classmethod
+    def define_schema(cls) -> io.Schema:
+        # Create autogrow templates
+        image_template = io.Autogrow.TemplatePrefix(
+            io.Image.Input("image"),
+            prefix="image",
+            min=1,
+            max=MAX_IMAGES,
+        )
+
+        float_template = io.Autogrow.TemplatePrefix(
+            io.Float.Input("float", default=0.0),
+            prefix="u_float",
+            min=0,
+            max=MAX_UNIFORMS,
+        )
+
+        int_template = io.Autogrow.TemplatePrefix(
+            io.Int.Input("int", default=0),
+            prefix="u_int",
+            min=0,
+            max=MAX_UNIFORMS,
+        )
+
+        return io.Schema(
+            node_id="GLSLShader",
+            display_name="GLSL Shader",
+            category="image/shader",
+            description=(
+                f"Apply GLSL fragment shaders to images. "
+                f"Inputs: u_image0-{MAX_IMAGES-1} (sampler2D), u_resolution (vec2), "
+                f"u_float0-{MAX_UNIFORMS-1}, u_int0-{MAX_UNIFORMS-1}. "
+                f"Outputs: layout(location = 0-{MAX_OUTPUTS-1}) out vec4 fragColor0-{MAX_OUTPUTS-1}."
+            ),
+            inputs=[
+                io.String.Input(
+                    "fragment_shader",
+                    default=DEFAULT_FRAGMENT_SHADER,
+                    multiline=True,
+                    tooltip="GLSL fragment shader source code (GLSL ES 3.00 / WebGL 2.0 compatible)",
+                ),
+                io.DynamicCombo.Input(
+                    "size_mode",
+                    options=[
+                        io.DynamicCombo.Option(
+                            "from_input",
+                            [],  # No extra inputs - uses first input image dimensions
+                        ),
+                        io.DynamicCombo.Option(
+                            "custom",
+                            [
+                                io.Int.Input("width", default=512, min=1, max=nodes.MAX_RESOLUTION),
+                                io.Int.Input("height", default=512, min=1, max=nodes.MAX_RESOLUTION),
+                            ],
+                        ),
+                    ],
+                    tooltip="Output size: 'from_input' uses first input image dimensions, 'custom' allows manual size",
+                ),
+                io.Autogrow.Input("images", template=image_template),
+                io.Autogrow.Input("floats", template=float_template),
+                io.Autogrow.Input("ints", template=int_template),
+            ],
+            outputs=[
+                io.Image.Output(display_name="IMAGE0"),
+                io.Image.Output(display_name="IMAGE1"),
+                io.Image.Output(display_name="IMAGE2"),
+                io.Image.Output(display_name="IMAGE3"),
+            ],
+        )
+
+    @classmethod
+    def execute(
+        cls,
+        fragment_shader: str,
+        size_mode: SizeModeInput,
+        images: io.Autogrow.Type,
+        floats: io.Autogrow.Type = None,
+        ints: io.Autogrow.Type = None,
+        **kwargs,
+    ) -> io.NodeOutput:
+        image_list = [v for v in images.values() if v is not None]
+        float_list = [v if v is not None else 0.0 for v in floats.values()] if floats else []
+        int_list = [v if v is not None else 0 for v in ints.values()] if ints else []
+
+        if not image_list:
+            raise ValueError("At least one input image is required")
+
+        # Determine output dimensions
+        if size_mode["size_mode"] == "custom":
+            out_width, out_height = size_mode["width"], size_mode["height"]
+        else:
+            out_height, out_width = image_list[0].shape[1], image_list[0].shape[2]
+
+        batch_size = image_list[0].shape[0]
+        uniforms = _prepare_uniforms(int_list, float_list)
+
+        with _gl_context(force_software=args.cpu) as ctx:
+            with _shader_program(ctx, fragment_shader) as program:
+                # Collect outputs for each render target across all batches
+                all_outputs: list[list[torch.Tensor]] = [[] for _ in range(MAX_OUTPUTS)]
+
+                for b in range(batch_size):
+                    with _textures_context(ctx, image_list, b) as textures:
+                        results = _render_shader(ctx, program, out_width, out_height, textures, uniforms)
+                        for i, result in enumerate(results):
+                            all_outputs[i].append(torch.from_numpy(result))
+
+                # Stack batches for each output
+                output_values = []
+                for i in range(MAX_OUTPUTS):
+                    output_batch = torch.stack(all_outputs[i], dim=0)
+                    output_values.append(output_batch)
+
+                return io.NodeOutput(*output_values, ui=cls._build_ui_output(image_list, output_values[0]))
+
+    @classmethod
+    def _build_ui_output(cls, image_list: list[torch.Tensor], output_batch: torch.Tensor) -> dict[str, list]:
+        """Build UI output with input and output images for client-side shader execution."""
+        combined_inputs = torch.cat(image_list, dim=0)
+        input_images_ui = ui.ImageSaveHelper.save_images(
+            combined_inputs,
+            filename_prefix="GLSLShader_input",
+            folder_type=io.FolderType.temp,
+            cls=None,
+            compress_level=1,
+        )
+
+        output_images_ui = ui.ImageSaveHelper.save_images(
+            output_batch,
+            filename_prefix="GLSLShader_output",
+            folder_type=io.FolderType.temp,
+            cls=None,
+            compress_level=1,
+        )
+
+        return {"input_images": input_images_ui, "images": output_images_ui}
+
+
+class GLSLExtension(ComfyExtension):
+    @override
+    async def get_node_list(self) -> list[type[io.ComfyNode]]:
+        return [GLSLShader]
+
+
+async def comfy_entrypoint() -> GLSLExtension:
+    return GLSLExtension()

comfy_extras/nodes_hunyuan.py

@@ -56,7 +56,7 @@ class EmptyHunyuanLatentVideo(io.ComfyNode):
     @classmethod
     def execute(cls, width, height, length, batch_size=1) -> io.NodeOutput:
         latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device())
-        return io.NodeOutput({"samples": latent, "downscale_ratio_spacial": 8})
+        return io.NodeOutput({"samples":latent})
 
     generate = execute  # TODO: remove
 
@@ -73,7 +73,7 @@ class EmptyHunyuanVideo15Latent(EmptyHunyuanLatentVideo):
     def execute(cls, width, height, length, batch_size=1) -> io.NodeOutput:
         # Using scale factor of 16 instead of 8
         latent = torch.zeros([batch_size, 32, ((length - 1) // 4) + 1, height // 16, width // 16], device=comfy.model_management.intermediate_device())
-        return io.NodeOutput({"samples": latent, "downscale_ratio_spacial": 16})
+        return io.NodeOutput({"samples": latent})
 
 
 class HunyuanVideo15ImageToVideo(io.ComfyNode):

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.11.1"
+__version__ = "0.11.0"

nodes.py

@@ -2432,8 +2432,8 @@ async def init_builtin_extra_nodes():
         "nodes_wanmove.py",
         "nodes_image_compare.py",
         "nodes_zimage.py",
-        "nodes_lora_debug.py",
-        "nodes_color.py"
+        "nodes_glsl.py",
+        "nodes_lora_debug.py"
     ]
 
     import_failed = []

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.11.1"
+version = "0.11.0"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.10"

requirements.txt

@@ -29,3 +29,4 @@ kornia>=0.7.1
 spandrel
 pydantic~=2.0
 pydantic-settings~=2.0
+moderngl