Merge remote-tracking branch 'origin' into feat/linux-amd-setup

README.md

@@ -6,6 +6,7 @@
 
 [![Website][website-shield]][website-url]
 [![Dynamic JSON Badge][discord-shield]][discord-url]
+[![Twitter][twitter-shield]][twitter-url]
 [![Matrix][matrix-shield]][matrix-url]
 <br>
 [![][github-release-shield]][github-release-link]
@@ -20,6 +21,8 @@
 <!-- Workaround to display total user from https://github.com/badges/shields/issues/4500#issuecomment-2060079995 -->
 [discord-shield]: https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscord.com%2Fapi%2Finvites%2Fcomfyorg%3Fwith_counts%3Dtrue&query=%24.approximate_member_count&logo=discord&logoColor=white&label=Discord&color=green&suffix=%20total
 [discord-url]: https://www.comfy.org/discord
+[twitter-shield]: https://img.shields.io/twitter/follow/ComfyUI
+[twitter-url]: https://x.com/ComfyUI
 
 [github-release-shield]: https://img.shields.io/github/v/release/comfyanonymous/ComfyUI?style=flat&sort=semver
 [github-release-link]: https://github.com/comfyanonymous/ComfyUI/releases
@@ -95,7 +98,8 @@ See what ComfyUI can do with the [example workflows](https://comfyanonymous.gith
 - [LCM models and Loras](https://comfyanonymous.github.io/ComfyUI_examples/lcm/)
 - Latent previews with [TAESD](#how-to-show-high-quality-previews)
 - Starts up very fast.
-- Works fully offline: will never download anything.
+- Works fully offline: core will never download anything unless you want to.
+- Optional API nodes to use paid models from external providers through the online [Comfy API](https://docs.comfy.org/tutorials/api-nodes/overview).
 - [Config file](extra_model_paths.yaml.example) to set the search paths for models.
 
 Workflow examples can be found on the [Examples page](https://comfyanonymous.github.io/ComfyUI_examples/)

comfy/controlnet.py

@@ -390,8 +390,9 @@ class ControlLora(ControlNet):
                 pass
 
         for k in self.control_weights:
-            if k not in {"lora_controlnet"}:
-                comfy.utils.set_attr_param(self.control_model, k, self.control_weights[k].to(dtype).to(comfy.model_management.get_torch_device()))
+            if (k not in {"lora_controlnet"}):
+                if (k.endswith(".up") or k.endswith(".down") or k.endswith(".weight") or k.endswith(".bias")) and ("__" not in k):
+                    comfy.utils.set_attr_param(self.control_model, k, self.control_weights[k].to(dtype).to(comfy.model_management.get_torch_device()))
 
     def copy(self):
         c = ControlLora(self.control_weights, global_average_pooling=self.global_average_pooling)

comfy/ldm/flux/controlnet.py

@@ -121,6 +121,9 @@ class ControlNetFlux(Flux):
         if img.ndim != 3 or txt.ndim != 3:
             raise ValueError("Input img and txt tensors must have 3 dimensions.")
 
+        if y is None:
+            y = torch.zeros((img.shape[0], self.params.vec_in_dim), device=img.device, dtype=img.dtype)
+
         # running on sequences img
         img = self.img_in(img)
 
@@ -174,7 +177,7 @@ class ControlNetFlux(Flux):
             out["output"] = out_output[:self.main_model_single]
         return out
 
-    def forward(self, x, timesteps, context, y, guidance=None, hint=None, **kwargs):
+    def forward(self, x, timesteps, context, y=None, guidance=None, hint=None, **kwargs):
         patch_size = 2
         if self.latent_input:
             hint = comfy.ldm.common_dit.pad_to_patch_size(hint, (patch_size, patch_size))

comfy/ldm/flux/model.py

@@ -101,6 +101,10 @@ class Flux(nn.Module):
         transformer_options={},
         attn_mask: Tensor = None,
     ) -> Tensor:
+
+        if y is None:
+            y = torch.zeros((img.shape[0], self.params.vec_in_dim), device=img.device, dtype=img.dtype)
+
         patches_replace = transformer_options.get("patches_replace", {})
         if img.ndim != 3 or txt.ndim != 3:
             raise ValueError("Input img and txt tensors must have 3 dimensions.")
@@ -188,7 +192,7 @@ class Flux(nn.Module):
         img = self.final_layer(img, vec)  # (N, T, patch_size ** 2 * out_channels)
         return img
 
-    def forward(self, x, timestep, context, y, guidance=None, control=None, transformer_options={}, **kwargs):
+    def forward(self, x, timestep, context, y=None, guidance=None, control=None, transformer_options={}, **kwargs):
         bs, c, h, w = x.shape
         patch_size = self.patch_size
         x = comfy.ldm.common_dit.pad_to_patch_size(x, (patch_size, patch_size))

comfy/model_management.py

@@ -295,6 +295,7 @@ except:
     pass
 
 
+SUPPORT_FP8_OPS = args.supports_fp8_compute
 try:
     if is_amd():
         try:
@@ -305,9 +306,13 @@ try:
         logging.info("AMD arch: {}".format(arch))
         logging.info("ROCm version: {}".format(rocm_version))
         if args.use_split_cross_attention == False and args.use_quad_cross_attention == False:
-            if torch_version_numeric[0] >= 2 and torch_version_numeric[1] >= 7:  # works on 2.6 but doesn't actually seem to improve much
-                if any((a in arch) for a in ["gfx1100", "gfx1101", "gfx1151"]):  # TODO: more arches
+            if torch_version_numeric >= (2, 7):  # works on 2.6 but doesn't actually seem to improve much
+                if any((a in arch) for a in ["gfx90a", "gfx942", "gfx1100", "gfx1101", "gfx1151"]):  # TODO: more arches, TODO: gfx1201 and gfx950
                     ENABLE_PYTORCH_ATTENTION = True
+        if torch_version_numeric >= (2, 7) and rocm_version >= (6, 4):
+            if any((a in arch) for a in ["gfx1201", "gfx942", "gfx950"]):  # TODO: more arches
+                SUPPORT_FP8_OPS = True
+
 except:
     pass
 
@@ -328,7 +333,7 @@ except:
     pass
 
 try:
-    if torch_version_numeric[0] == 2 and torch_version_numeric[1] >= 5:
+    if torch_version_numeric >= (2, 5):
         torch.backends.cuda.allow_fp16_bf16_reduction_math_sdp(True)
 except:
     logging.warning("Warning, could not set allow_fp16_bf16_reduction_math_sdp")
@@ -1047,7 +1052,7 @@ def pytorch_attention_flash_attention():
     global ENABLE_PYTORCH_ATTENTION
     if ENABLE_PYTORCH_ATTENTION:
         #TODO: more reliable way of checking for flash attention?
-        if is_nvidia(): #pytorch flash attention only works on Nvidia
+        if is_nvidia():
             return True
         if is_intel_xpu():
             return True
@@ -1063,7 +1068,7 @@ def force_upcast_attention_dtype():
     upcast = args.force_upcast_attention
 
     macos_version = mac_version()
-    if macos_version is not None and ((14, 5) <= macos_version < (16,)):  # black image bug on recent versions of macOS
+    if macos_version is not None and ((14, 5) <= macos_version):  # black image bug on recent versions of macOS, I don't think it's ever getting fixed
         upcast = True
 
     if upcast:
@@ -1262,7 +1267,7 @@ def should_use_bf16(device=None, model_params=0, prioritize_performance=True, ma
     return False
 
 def supports_fp8_compute(device=None):
-    if args.supports_fp8_compute:
+    if SUPPORT_FP8_OPS:
         return True
 
     if not is_nvidia():
@@ -1276,11 +1281,11 @@ def supports_fp8_compute(device=None):
     if props.minor < 9:
         return False
 
-    if torch_version_numeric[0] < 2 or (torch_version_numeric[0] == 2 and torch_version_numeric[1] < 3):
+    if torch_version_numeric < (2, 3):
         return False
 
     if WINDOWS:
-        if (torch_version_numeric[0] == 2 and torch_version_numeric[1] < 4):
+        if torch_version_numeric < (2, 4):
             return False
 
     return True

comfy_api_nodes/nodes_ideogram.py

@@ -324,7 +324,7 @@ class IdeogramV1(ComfyNodeABC):
 
     RETURN_TYPES = (IO.IMAGE,)
     FUNCTION = "api_call"
-    CATEGORY = "api node/image/Ideogram/v1"
+    CATEGORY = "api node/image/Ideogram"
     DESCRIPTION = cleandoc(__doc__ or "")
     API_NODE = True
 
@@ -483,7 +483,7 @@ class IdeogramV2(ComfyNodeABC):
 
     RETURN_TYPES = (IO.IMAGE,)
     FUNCTION = "api_call"
-    CATEGORY = "api node/image/Ideogram/v2"
+    CATEGORY = "api node/image/Ideogram"
     DESCRIPTION = cleandoc(__doc__ or "")
     API_NODE = True
 
@@ -649,7 +649,7 @@ class IdeogramV3(ComfyNodeABC):
 
     RETURN_TYPES = (IO.IMAGE,)
     FUNCTION = "api_call"
-    CATEGORY = "api node/image/Ideogram/v3"
+    CATEGORY = "api node/image/Ideogram"
     DESCRIPTION = cleandoc(__doc__ or "")
     API_NODE = True
 

comfy_config/config_parser.py

@@ -0,0 +1,97 @@
+import os
+from pathlib import Path
+from typing import Optional
+
+from pydantic_settings import PydanticBaseSettingsSource, TomlConfigSettingsSource
+
+from comfy_config.types import (
+    ComfyConfig,
+    ProjectConfig,
+    PyProjectConfig,
+    PyProjectSettings
+)
+
+"""
+Extract configuration from a custom node directory's pyproject.toml file or a Python file.
+
+This function reads and parses the pyproject.toml file in the specified directory
+to extract project and ComfyUI-specific configuration information. If no
+pyproject.toml file is found, it creates a minimal configuration using the
+folder name as the project name. If a Python file is provided, it uses the
+file name (without extension) as the project name.
+
+Args:
+    path (str): Path to the directory containing the pyproject.toml file, or
+               path to a .py file. If pyproject.toml doesn't exist in a directory,
+               the folder name will be used as the default project name. If a .py
+               file is provided, the filename (without .py extension) will be used
+               as the project name.
+
+Returns:
+    Optional[PyProjectConfig]: A PyProjectConfig object containing:
+        - project: Basic project information (name, version, dependencies, etc.)
+        - tool_comfy: ComfyUI-specific configuration (publisher_id, models, etc.)
+        Returns None if configuration extraction fails or if the provided file
+        is not a Python file.
+
+Notes:
+    - If pyproject.toml is missing in a directory, creates a default config with folder name
+    - If a .py file is provided, creates a default config with filename (without extension)
+    - Returns None for non-Python files
+
+Example:
+    >>> from comfy_config import config_parser
+    >>> # For directory
+    >>> custom_node_dir = os.path.dirname(os.path.realpath(__file__))
+    >>> project_config = config_parser.extract_node_configuration(custom_node_dir)
+    >>> print(project_config.project.name)  # "my_custom_node" or name from pyproject.toml
+    >>>
+    >>> # For single-file Python node file
+    >>> py_file_path = os.path.realpath(__file__) # "/path/to/my_node.py"
+    >>> project_config = config_parser.extract_node_configuration(py_file_path)
+    >>> print(project_config.project.name)  # "my_node"
+"""
+def extract_node_configuration(path) -> Optional[PyProjectConfig]:
+    if os.path.isfile(path):
+        file_path = Path(path)
+
+        if file_path.suffix.lower() != '.py':
+            return None
+
+        project_name = file_path.stem
+        project = ProjectConfig(name=project_name)
+        comfy = ComfyConfig()
+        return PyProjectConfig(project=project, tool_comfy=comfy)
+
+    folder_name = os.path.basename(path)
+    toml_path = Path(path) / "pyproject.toml"
+
+    if not toml_path.exists():
+        project = ProjectConfig(name=folder_name)
+        comfy = ComfyConfig()
+        return PyProjectConfig(project=project, tool_comfy=comfy)
+
+    raw_settings = load_pyproject_settings(toml_path)
+
+    project_data = raw_settings.project
+
+    tool_data = raw_settings.tool
+    comfy_data = tool_data.get("comfy", {}) if tool_data else {}
+
+    return PyProjectConfig(project=project_data, tool_comfy=comfy_data)
+
+
+def load_pyproject_settings(toml_path: Path) -> PyProjectSettings:
+    class PyProjectLoader(PyProjectSettings):
+        @classmethod
+        def settings_customise_sources(
+            cls,
+            settings_cls,
+            init_settings: PydanticBaseSettingsSource,
+            env_settings: PydanticBaseSettingsSource,
+            dotenv_settings: PydanticBaseSettingsSource,
+            file_secret_settings: PydanticBaseSettingsSource,
+        ):
+            return (TomlConfigSettingsSource(settings_cls, toml_path),)
+
+    return PyProjectLoader()

comfy_config/types.py

@@ -0,0 +1,80 @@
+from pydantic import BaseModel, Field
+from pydantic_settings import BaseSettings, SettingsConfigDict
+from typing import List, Optional
+
+# IMPORTANT: The type definitions specified in pyproject.toml for custom nodes
+# must remain synchronized with the corresponding files in the https://github.com/Comfy-Org/comfy-cli/blob/main/comfy_cli/registry/types.py.
+# Any changes to one must be reflected in the other to maintain consistency.
+
+class NodeVersion(BaseModel):
+    changelog: str
+    dependencies: List[str]
+    deprecated: bool
+    id: str
+    version: str
+    download_url: str
+
+
+class Node(BaseModel):
+    id: str
+    name: str
+    description: str
+    author: Optional[str] = None
+    license: Optional[str] = None
+    icon: Optional[str] = None
+    repository: Optional[str] = None
+    tags: List[str] = Field(default_factory=list)
+    latest_version: Optional[NodeVersion] = None
+
+
+class PublishNodeVersionResponse(BaseModel):
+    node_version: NodeVersion
+    signedUrl: str
+
+
+class URLs(BaseModel):
+    homepage: str = Field(default="", alias="Homepage")
+    documentation: str = Field(default="", alias="Documentation")
+    repository: str = Field(default="", alias="Repository")
+    issues: str = Field(default="", alias="Issues")
+
+
+class Model(BaseModel):
+    location: str
+    model_url: str
+
+
+class ComfyConfig(BaseModel):
+    publisher_id: str = Field(default="", alias="PublisherId")
+    display_name: str = Field(default="", alias="DisplayName")
+    icon: str = Field(default="", alias="Icon")
+    models: List[Model] = Field(default_factory=list, alias="Models")
+    includes: List[str] = Field(default_factory=list)
+
+
+class License(BaseModel):
+    file: str = ""
+    text: str = ""
+
+
+class ProjectConfig(BaseModel):
+    name: str = ""
+    description: str = ""
+    version: str = "1.0.0"
+    requires_python: str = Field(default=">= 3.9", alias="requires-python")
+    dependencies: List[str] = Field(default_factory=list)
+    license: License = Field(default_factory=License)
+    urls: URLs = Field(default_factory=URLs)
+
+
+class PyProjectConfig(BaseModel):
+    project: ProjectConfig = Field(default_factory=ProjectConfig)
+    tool_comfy: ComfyConfig = Field(default_factory=ComfyConfig)
+
+
+class PyProjectSettings(BaseSettings):
+    project: dict = Field(default_factory=dict)
+
+    tool: dict = Field(default_factory=dict)
+
+    model_config = SettingsConfigDict()

comfy_extras/nodes_images.py

@@ -16,7 +16,8 @@ from inspect import cleandoc
 import torch
 import comfy.utils
 
-from comfy.comfy_types import FileLocator
+from comfy.comfy_types import FileLocator, IO
+from server import PromptServer
 
 MAX_RESOLUTION = nodes.MAX_RESOLUTION
 
@@ -491,6 +492,37 @@ class SaveSVGNode:
             counter += 1
         return { "ui": { "images": results } }
 
+class GetImageSize:
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image": (IO.IMAGE,),
+            },
+            "hidden": {
+                "unique_id": "UNIQUE_ID",
+            }
+        }
+
+    RETURN_TYPES = (IO.INT, IO.INT, IO.INT)
+    RETURN_NAMES = ("width", "height", "batch_size")
+    FUNCTION = "get_size"
+
+    CATEGORY = "image"
+    DESCRIPTION = """Returns width and height of the image, and passes it through unchanged."""
+
+    def get_size(self, image, unique_id=None) -> tuple[int, int]:
+        height = image.shape[1]
+        width = image.shape[2]
+        batch_size = image.shape[0]
+
+        # Send progress text to display size on the node
+        if unique_id:
+            PromptServer.instance.send_progress_text(f"width: {width}, height: {height}\n batch size: {batch_size}", unique_id)
+
+        return width, height, batch_size
+
 NODE_CLASS_MAPPINGS = {
     "ImageCrop": ImageCrop,
     "RepeatImageBatch": RepeatImageBatch,
@@ -500,4 +532,5 @@ NODE_CLASS_MAPPINGS = {
     "SaveAnimatedPNG": SaveAnimatedPNG,
     "SaveSVGNode": SaveSVGNode,
     "ImageStitch": ImageStitch,
+    "GetImageSize": GetImageSize,
 }

comfy_extras/nodes_webcam.py

@@ -23,6 +23,10 @@ class WebcamCapture(nodes.LoadImage):
     def load_capture(self, image, **kwargs):
         return super().load_image(folder_paths.get_annotated_filepath(image))
 
+    @classmethod
+    def IS_CHANGED(cls, image, width, height, capture_on_queue):
+        return super().IS_CHANGED(image)
+
 
 NODE_CLASS_MAPPINGS = {
     "WebcamCapture": WebcamCapture,

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.3.39"
+__version__ = "0.3.40"

nodes.py

@@ -2067,6 +2067,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ImageQuantize": "Image Quantize",
     "ImageSharpen": "Image Sharpen",
     "ImageScaleToTotalPixels": "Scale Image to Total Pixels",
+    "GetImageSize": "Get Image Size",
     # _for_testing
     "VAEDecodeTiled": "VAE Decode (Tiled)",
     "VAEEncodeTiled": "VAE Encode (Tiled)",

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.3.39"
+version = "0.3.40"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.9"

requirements.txt

@@ -1,4 +1,4 @@
-comfyui-frontend-package==1.21.6
+comfyui-frontend-package==1.21.7
 comfyui-workflow-templates==0.1.25
 comfyui-embedded-docs==0.2.0
 torch

server.py

@@ -390,7 +390,7 @@ class PromptServer():
         async def view_image(request):
             if "filename" in request.rel_url.query:
                 filename = request.rel_url.query["filename"]
-                filename,output_dir = folder_paths.annotated_filepath(filename)
+                filename, output_dir = folder_paths.annotated_filepath(filename)
 
                 if not filename:
                     return web.Response(status=400)
@@ -476,9 +476,8 @@ class PromptServer():
                         # Get content type from mimetype, defaulting to 'application/octet-stream'
                         content_type = mimetypes.guess_type(filename)[0] or 'application/octet-stream'
 
-                        # For security, force certain extensions to download instead of display
-                        file_extension = os.path.splitext(filename)[1].lower()
-                        if file_extension in {'.html', '.htm', '.js', '.css'}:
+                        # For security, force certain mimetypes to download instead of display
+                        if content_type in {'text/html', 'text/html-sandboxed', 'application/xhtml+xml', 'text/javascript', 'text/css'}:
                             content_type = 'application/octet-stream'  # Forces download
 
                         return web.FileResponse(
@@ -789,7 +788,7 @@ class PromptServer():
             if hasattr(Image, 'Resampling'):
                 resampling = Image.Resampling.BILINEAR
             else:
-                resampling = Image.ANTIALIAS
+                resampling = Image.Resampling.LANCZOS
 
             image = ImageOps.contain(image, (max_size, max_size), resampling)
         type_num = 1

tests-unit/comfy_extras_test/image_stitch_test.py

@@ -5,7 +5,10 @@ from unittest.mock import patch, MagicMock
 mock_nodes = MagicMock()
 mock_nodes.MAX_RESOLUTION = 16384
 
-with patch.dict('sys.modules', {'nodes': mock_nodes}):
+# Mock server module for PromptServer
+mock_server = MagicMock()
+
+with patch.dict('sys.modules', {'nodes': mock_nodes, 'server': mock_server}):
     from comfy_extras.nodes_images import ImageStitch