Merge branch 'master' into worksplit-multigpu

README.md

@@ -31,10 +31,24 @@
 ![ComfyUI Screenshot](https://github.com/user-attachments/assets/7ccaf2c1-9b72-41ae-9a89-5688c94b7abe)
 </div>
 
-This ui will let you design and execute advanced stable diffusion pipelines using a graph/nodes/flowchart based interface. For some workflow examples and see what ComfyUI can do you can check out:
+ComfyUI lets you design and execute advanced stable diffusion pipelines using a graph/nodes/flowchart based interface. Available on Windows, Linux, and macOS.
-### [ComfyUI Examples](https://comfyanonymous.github.io/ComfyUI_examples/)
+
+## Get Started
+
+#### [Desktop Application](https://www.comfy.org/download)
+- The easiest way to get started. 
+- Available on Windows & macOS.
+
+#### [Windows Portable Package](#installing)
+- Get the latest commits and completely portable.
+- Available on Windows.
+
+#### [Manual Install](#manual-install-windows-linux)
+Supports all operating systems and GPU types (NVIDIA, AMD, Intel, Apple Silicon, Ascend).
+
+## Examples
+See what ComfyUI can do with the [example workflows](https://comfyanonymous.github.io/ComfyUI_examples/).
 
-### [Installing ComfyUI](#installing)
 
 ## Features
 - Nodes/graph/flowchart interface to experiment and create complex Stable Diffusion workflows without needing to code anything.
@@ -121,7 +135,7 @@ Workflow examples can be found on the [Examples page](https://comfyanonymous.git
 
 # Installing
 
-## Windows
+## Windows Portable
 
 There is a portable standalone build for Windows that should work for running on Nvidia GPUs or for running on your CPU only on the [releases page](https://github.com/comfyanonymous/ComfyUI/releases).
 
@@ -141,6 +155,15 @@ See the [Config file](extra_model_paths.yaml.example) to set the search paths fo
 
 To run it on services like paperspace, kaggle or colab you can use my [Jupyter Notebook](notebooks/comfyui_colab.ipynb)
 
+
+## [comfy-cli](https://docs.comfy.org/comfy-cli/getting-started)
+
+You can install and start ComfyUI using comfy-cli:
+```bash
+pip install comfy-cli
+comfy install
+```
+
 ## Manual Install (Windows, Linux)
 
 python 3.13 is supported but using 3.12 is recommended because some custom nodes and their dependencies might not support it yet.
@@ -293,6 +316,8 @@ Use `--tls-keyfile key.pem --tls-certfile cert.pem` to enable TLS/SSL, the app w
 
 ## Support and dev channel
 
+[Discord](https://comfy.org/discord): Try the #help or #feedback channels.
+
 [Matrix space: #comfyui_space:matrix.org](https://app.element.io/#/room/%23comfyui_space%3Amatrix.org) (it's like discord but open source).
 
 See also: [https://www.comfy.org/](https://www.comfy.org/)
@@ -309,7 +334,7 @@ For any bugs, issues, or feature requests related to the frontend, please use th
 
 The new frontend is now the default for ComfyUI. However, please note:
 
-1. The frontend in the main ComfyUI repository is updated weekly.
+1. The frontend in the main ComfyUI repository is updated fortnightly.
 2. Daily releases are available in the separate frontend repository.
 
 To use the most up-to-date frontend version:
@@ -326,7 +351,7 @@ To use the most up-to-date frontend version:
    --front-end-version Comfy-Org/ComfyUI_frontend@1.2.2
    ```
 
-This approach allows you to easily switch between the stable weekly release and the cutting-edge daily updates, or even specific versions for testing purposes.
+This approach allows you to easily switch between the stable fortnightly release and the cutting-edge daily updates, or even specific versions for testing purposes.
 
 ### Accessing the Legacy Frontend
 

api_server/routes/internal/internal_routes.py

@@ -1,8 +1,9 @@
 from aiohttp import web
 from typing import Optional
-from folder_paths import folder_names_and_paths
+from folder_paths import folder_names_and_paths, get_directory_by_type
 from api_server.services.terminal_service import TerminalService
 import app.logger
+import os
 
 class InternalRoutes:
     '''
@@ -50,6 +51,20 @@ class InternalRoutes:
                 response[key] = folder_names_and_paths[key][0]
             return web.json_response(response)
 
+        @self.routes.get('/files/{directory_type}')
+        async def get_files(request: web.Request) -> web.Response:
+            directory_type = request.match_info['directory_type']
+            if directory_type not in ("output", "input", "temp"):
+                return web.json_response({"error": "Invalid directory type"}, status=400)
+
+            directory = get_directory_by_type(directory_type)
+            sorted_files = sorted(
+                (entry for entry in os.scandir(directory) if entry.is_file()),
+                key=lambda entry: -entry.stat().st_mtime
+            )
+            return web.json_response([entry.name for entry in sorted_files], status=200)
+
+
     def get_app(self):
         if self._app is None:
             self._app = web.Application()

comfy/comfy_types/node_typing.py

@@ -66,13 +66,26 @@ class IO(StrEnum):
         b = frozenset(value.split(","))
         return not (b.issubset(a) or a.issubset(b))
 
+class RemoteInputOptions(TypedDict):
+    route: str
+    """The route to the remote source."""
+    refresh_button: bool
+    """Specifies whether to show a refresh button in the UI below the widget."""
+    control_after_refresh: Literal["first", "last"]
+    """Specifies the control after the refresh button is clicked. If "first", the first item will be automatically selected, and so on."""
+    timeout: int
+    """The maximum amount of time to wait for a response from the remote source in milliseconds."""
+    max_retries: int
+    """The maximum number of retries before aborting the request."""
+    refresh: int
+    """The TTL of the remote input's value in milliseconds. Specifies the interval at which the remote input's value is refreshed."""
 
 class InputTypeOptions(TypedDict):
     """Provides type hinting for the return type of the INPUT_TYPES node function.
 
     Due to IDE limitations with unions, for now all options are available for all types (e.g. `label_on` is hinted even when the type is not `IO.BOOLEAN`).
 
-    Comfy Docs: https://docs.comfy.org/essentials/custom_node_datatypes
+    Comfy Docs: https://docs.comfy.org/custom-nodes/backend/datatypes
     """
 
     default: bool | str | float | int | list | tuple
@@ -113,6 +126,14 @@ class InputTypeOptions(TypedDict):
     # defaultVal: str
     dynamicPrompts: bool
     """Causes the front-end to evaluate dynamic prompts (``STRING``)"""
+    # class InputTypeCombo(InputTypeOptions):
+    image_upload: bool
+    """Specifies whether the input should have an image upload button and image preview attached to it. Requires that the input's name is `image`."""
+    image_folder: Literal["input", "output", "temp"]
+    """Specifies which folder to get preview images from if the input has the ``image_upload`` flag.
+    """
+    remote: RemoteInputOptions
+    """Specifies the configuration for a remote input."""
 
 
 class HiddenInputTypeDict(TypedDict):
@@ -133,7 +154,7 @@ class HiddenInputTypeDict(TypedDict):
 class InputTypeDict(TypedDict):
     """Provides type hinting for node INPUT_TYPES.
 
-    Comfy Docs: https://docs.comfy.org/essentials/custom_node_more_on_inputs
+    Comfy Docs: https://docs.comfy.org/custom-nodes/backend/more_on_inputs
     """
 
     required: dict[str, tuple[IO, InputTypeOptions]]
@@ -143,14 +164,14 @@ class InputTypeDict(TypedDict):
     hidden: HiddenInputTypeDict
     """Offers advanced functionality and server-client communication.
 
-    Comfy Docs: https://docs.comfy.org/essentials/custom_node_more_on_inputs#hidden-inputs
+    Comfy Docs: https://docs.comfy.org/custom-nodes/backend/more_on_inputs#hidden-inputs
     """
 
 
 class ComfyNodeABC(ABC):
     """Abstract base class for Comfy nodes.  Includes the names and expected types of attributes.
 
-    Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview
+    Comfy Docs: https://docs.comfy.org/custom-nodes/backend/server_overview
     """
 
     DESCRIPTION: str
@@ -167,7 +188,7 @@ class ComfyNodeABC(ABC):
     CATEGORY: str
     """The category of the node, as per the "Add Node" menu.
 
-    Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview#category
+    Comfy Docs: https://docs.comfy.org/custom-nodes/backend/server_overview#category
     """
     EXPERIMENTAL: bool
     """Flags a node as experimental, informing users that it may change or not work as expected."""
@@ -181,9 +202,9 @@ class ComfyNodeABC(ABC):
 
         * Must include the ``required`` key, which describes all inputs that must be connected for the node to execute.
         * The ``optional`` key can be added to describe inputs which do not need to be connected.
-        * The ``hidden`` key offers some advanced functionality.  More info at: https://docs.comfy.org/essentials/custom_node_more_on_inputs#hidden-inputs
+        * The ``hidden`` key offers some advanced functionality.  More info at: https://docs.comfy.org/custom-nodes/backend/more_on_inputs#hidden-inputs
 
-        Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview#input-types
+        Comfy Docs: https://docs.comfy.org/custom-nodes/backend/server_overview#input-types
         """
         return {"required": {}}
 
@@ -198,7 +219,7 @@ class ComfyNodeABC(ABC):
 
     By default, a node is not considered an output. Set ``OUTPUT_NODE = True`` to specify that it is.
 
-    Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview#output-node
+    Comfy Docs: https://docs.comfy.org/custom-nodes/backend/server_overview#output-node
     """
     INPUT_IS_LIST: bool
     """A flag indicating if this node implements the additional code necessary to deal with OUTPUT_IS_LIST nodes.
@@ -209,7 +230,7 @@ class ComfyNodeABC(ABC):
 
     A node can also override the default input behaviour and receive the whole list in a single call. This is done by setting a class attribute `INPUT_IS_LIST` to ``True``.
 
-    Comfy Docs: https://docs.comfy.org/essentials/custom_node_lists#list-processing
+    Comfy Docs: https://docs.comfy.org/custom-nodes/backend/lists#list-processing
     """
     OUTPUT_IS_LIST: tuple[bool]
     """A tuple indicating which node outputs are lists, but will be connected to nodes that expect individual items.
@@ -227,7 +248,7 @@ class ComfyNodeABC(ABC):
     the node should provide a class attribute `OUTPUT_IS_LIST`, which is a ``tuple[bool]``, of the same length as `RETURN_TYPES`,
     specifying which outputs which should be so treated.
 
-    Comfy Docs: https://docs.comfy.org/essentials/custom_node_lists#list-processing
+    Comfy Docs: https://docs.comfy.org/custom-nodes/backend/lists#list-processing
     """
 
     RETURN_TYPES: tuple[IO]
@@ -237,19 +258,19 @@ class ComfyNodeABC(ABC):
 
         RETURN_TYPES = (IO.INT, "INT", "CUSTOM_TYPE")
 
-    Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview#return-types
+    Comfy Docs: https://docs.comfy.org/custom-nodes/backend/server_overview#return-types
     """
     RETURN_NAMES: tuple[str]
     """The output slot names for each item in `RETURN_TYPES`, e.g. ``RETURN_NAMES = ("count", "filter_string")``
 
-    Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview#return-names
+    Comfy Docs: https://docs.comfy.org/custom-nodes/backend/server_overview#return-names
     """
     OUTPUT_TOOLTIPS: tuple[str]
     """A tuple of strings to use as tooltips for node outputs, one for each item in `RETURN_TYPES`."""
     FUNCTION: str
     """The name of the function to execute as a literal string, e.g. `FUNCTION = "execute"`
 
-    Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview#function
+    Comfy Docs: https://docs.comfy.org/custom-nodes/backend/server_overview#function
     """
 
 
@@ -267,7 +288,7 @@ class CheckLazyMixin:
         Params should match the nodes execution ``FUNCTION`` (self, and all inputs by name).
         Will be executed repeatedly until it returns an empty list, or all requested items were already evaluated (and sent as params).
 
-        Comfy Docs: https://docs.comfy.org/essentials/custom_node_lazy_evaluation#defining-check-lazy-status
+        Comfy Docs: https://docs.comfy.org/custom-nodes/backend/lazy_evaluation#defining-check-lazy-status
         """
 
         need = [name for name in kwargs if kwargs[name] is None]

comfy/ldm/hunyuan_video/model.py

@@ -310,7 +310,7 @@ class HunyuanVideo(nn.Module):
             shape[i] = shape[i] // self.patch_size[i]
         img = img.reshape([img.shape[0]] + shape + [self.out_channels] + self.patch_size)
         img = img.permute(0, 4, 1, 5, 2, 6, 3, 7)
-        img = img.reshape(initial_shape)
+        img = img.reshape(initial_shape[0], self.out_channels, initial_shape[2], initial_shape[3], initial_shape[4])
         return img
 
     def forward(self, x, timestep, context, y, guidance=None, attention_mask=None, control=None, transformer_options={}, **kwargs):

comfy/ldm/modules/attention.py

@@ -30,38 +30,24 @@ ops = comfy.ops.disable_weight_init
 
 FORCE_UPCAST_ATTENTION_DTYPE = model_management.force_upcast_attention_dtype()
 
-def get_attn_precision(attn_precision):
+def get_attn_precision(attn_precision, current_dtype):
     if args.dont_upcast_attention:
         return None
-    if FORCE_UPCAST_ATTENTION_DTYPE is not None:
+
-        return FORCE_UPCAST_ATTENTION_DTYPE
+    if FORCE_UPCAST_ATTENTION_DTYPE is not None and current_dtype in FORCE_UPCAST_ATTENTION_DTYPE:
+        return FORCE_UPCAST_ATTENTION_DTYPE[current_dtype]
     return attn_precision
 
 def exists(val):
     return val is not None
 
 
-def uniq(arr):
-    return{el: True for el in arr}.keys()
-
-
 def default(val, d):
     if exists(val):
         return val
     return d
 
 
-def max_neg_value(t):
-    return -torch.finfo(t.dtype).max
-
-
-def init_(tensor):
-    dim = tensor.shape[-1]
-    std = 1 / math.sqrt(dim)
-    tensor.uniform_(-std, std)
-    return tensor
-
-
 # feedforward
 class GEGLU(nn.Module):
     def __init__(self, dim_in, dim_out, dtype=None, device=None, operations=ops):
@@ -96,7 +82,7 @@ def Normalize(in_channels, dtype=None, device=None):
     return torch.nn.GroupNorm(num_groups=32, num_channels=in_channels, eps=1e-6, affine=True, dtype=dtype, device=device)
 
 def attention_basic(q, k, v, heads, mask=None, attn_precision=None, skip_reshape=False, skip_output_reshape=False):
-    attn_precision = get_attn_precision(attn_precision)
+    attn_precision = get_attn_precision(attn_precision, q.dtype)
 
     if skip_reshape:
         b, _, _, dim_head = q.shape
@@ -165,7 +151,7 @@ def attention_basic(q, k, v, heads, mask=None, attn_precision=None, skip_reshape
 
 
 def attention_sub_quad(query, key, value, heads, mask=None, attn_precision=None, skip_reshape=False, skip_output_reshape=False):
-    attn_precision = get_attn_precision(attn_precision)
+    attn_precision = get_attn_precision(attn_precision, query.dtype)
 
     if skip_reshape:
         b, _, _, dim_head = query.shape
@@ -235,7 +221,7 @@ def attention_sub_quad(query, key, value, heads, mask=None, attn_precision=None,
     return hidden_states
 
 def attention_split(q, k, v, heads, mask=None, attn_precision=None, skip_reshape=False, skip_output_reshape=False):
-    attn_precision = get_attn_precision(attn_precision)
+    attn_precision = get_attn_precision(attn_precision, q.dtype)
 
     if skip_reshape:
         b, _, _, dim_head = q.shape

comfy/model_base.py

@@ -871,6 +871,15 @@ class HunyuanVideo(BaseModel):
         if cross_attn is not None:
             out['c_crossattn'] = comfy.conds.CONDRegular(cross_attn)
 
+        image = kwargs.get("concat_latent_image", None)
+        noise = kwargs.get("noise", None)
+
+        if image is not None:
+            padding_shape = (noise.shape[0], 16, noise.shape[2] - 1, noise.shape[3], noise.shape[4])
+            latent_padding = torch.zeros(padding_shape, device=noise.device, dtype=noise.dtype)
+            image_latents = torch.cat([image.to(noise), latent_padding], dim=2)
+            out['c_concat'] = comfy.conds.CONDNoiseShape(self.process_latent_in(image_latents))
+
         guidance = kwargs.get("guidance", 6.0)
         if guidance is not None:
             out['guidance'] = comfy.conds.CONDRegular(torch.FloatTensor([guidance]))

comfy/model_detection.py

@@ -136,7 +136,7 @@ def detect_unet_config(state_dict, key_prefix):
     if '{}txt_in.individual_token_refiner.blocks.0.norm1.weight'.format(key_prefix) in state_dict_keys: #Hunyuan Video
         dit_config = {}
         dit_config["image_model"] = "hunyuan_video"
-        dit_config["in_channels"] = 16
+        dit_config["in_channels"] = state_dict['{}img_in.proj.weight'.format(key_prefix)].shape[1] #SkyReels img2video has 32 input channels
         dit_config["patch_size"] = [1, 2, 2]
         dit_config["out_channels"] = 16
         dit_config["vec_in_dim"] = 768

comfy/model_management.py

@@ -245,7 +245,7 @@ def is_amd():
 
 MIN_WEIGHT_MEMORY_RATIO = 0.4
 if is_nvidia():
-    MIN_WEIGHT_MEMORY_RATIO = 0.1
+    MIN_WEIGHT_MEMORY_RATIO = 0.0
 
 ENABLE_PYTORCH_ATTENTION = False
 if args.use_pytorch_cross_attention:
@@ -281,9 +281,12 @@ if ENABLE_PYTORCH_ATTENTION:
     torch.backends.cuda.enable_flash_sdp(True)
     torch.backends.cuda.enable_mem_efficient_sdp(True)
 
+
+PRIORITIZE_FP16 = False  # TODO: remove and replace with something that shows exactly which dtype is faster than the other
 try:
     if is_nvidia() and args.fast:
         torch.backends.cuda.matmul.allow_fp16_accumulation = True
+        PRIORITIZE_FP16 = True  # TODO: limit to cards where it actually boosts performance
 except:
     pass
 
@@ -710,6 +713,10 @@ def unet_dtype(device=None, model_params=0, supported_dtypes=[torch.float16, tor
         if model_params * 2 > free_model_memory:
             return fp8_dtype
 
+    if PRIORITIZE_FP16:
+        if torch.float16 in supported_dtypes and should_use_fp16(device=device, model_params=model_params):
+            return torch.float16
+
     for dt in supported_dtypes:
         if dt == torch.float16 and should_use_fp16(device=device, model_params=model_params):
             if torch.float16 in supported_dtypes:
@@ -972,11 +979,11 @@ 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 <= (15, 2)):  # black image bug on recent versions of macOS
+    if macos_version is not None and ((14, 5) <= macos_version < (16,)):  # black image bug on recent versions of macOS
         upcast = True
 
     if upcast:
-        return torch.float32
+        return {torch.float16: torch.float32}
     else:
         return None
 
@@ -1050,8 +1057,6 @@ def is_directml_enabled():
     return False
 
 def should_use_fp16(device=None, model_params=0, prioritize_performance=True, manual_cast=False):
-    global directml_enabled
-
     if device is not None:
         if is_device_cpu(device):
             return False
@@ -1062,8 +1067,8 @@ def should_use_fp16(device=None, model_params=0, prioritize_performance=True, ma
     if FORCE_FP32:
         return False
 
-    if directml_enabled:
+    if is_directml_enabled():
-        return False
+        return True
 
     if (device is not None and is_device_mps(device)) or mps_mode():
         return True
@@ -1150,7 +1155,7 @@ def should_use_bf16(device=None, model_params=0, prioritize_performance=True, ma
 
     bf16_works = torch.cuda.is_bf16_supported()
 
-    if bf16_works or manual_cast:
+    if bf16_works and manual_cast:
         free_model_memory = maximum_vram_for_weights(device)
         if (not prioritize_performance) or model_params * 4 > free_model_memory:
             return True

comfy_extras/nodes_video.py

@@ -0,0 +1,75 @@
+import os
+import av
+import torch
+import folder_paths
+import json
+from fractions import Fraction
+
+
+class SaveWEBM:
+    def __init__(self):
+        self.output_dir = folder_paths.get_output_directory()
+        self.type = "output"
+        self.prefix_append = ""
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required":
+                    {"images": ("IMAGE", ),
+                     "filename_prefix": ("STRING", {"default": "ComfyUI"}),
+                     "codec": (["vp9", "av1"],),
+                     "fps": ("FLOAT", {"default": 24.0, "min": 0.01, "max": 1000.0, "step": 0.01}),
+                     "crf": ("FLOAT", {"default": 32.0, "min": 0, "max": 63.0, "step": 1, "tooltip": "Higher crf means lower quality with a smaller file size, lower crf means higher quality higher filesize."}),
+                     },
+                "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
+                }
+
+    RETURN_TYPES = ()
+    FUNCTION = "save_images"
+
+    OUTPUT_NODE = True
+
+    CATEGORY = "image/video"
+
+    EXPERIMENTAL = True
+
+    def save_images(self, images, codec, fps, filename_prefix, crf, prompt=None, extra_pnginfo=None):
+        filename_prefix += self.prefix_append
+        full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0])
+
+        file = f"{filename}_{counter:05}_.webm"
+        container = av.open(os.path.join(full_output_folder, file), mode="w")
+
+        if prompt is not None:
+            container.metadata["prompt"] = json.dumps(prompt)
+
+        if extra_pnginfo is not None:
+            for x in extra_pnginfo:
+                container.metadata[x] = json.dumps(extra_pnginfo[x])
+
+        codec_map = {"vp9": "libvpx-vp9", "av1": "libaom-av1"}
+        stream = container.add_stream(codec_map[codec], rate=Fraction(round(fps * 1000), 1000))
+        stream.width = images.shape[-2]
+        stream.height = images.shape[-3]
+        stream.pix_fmt = "yuv420p"
+        stream.bit_rate = 0
+        stream.options = {'crf': str(crf)}
+
+        for frame in images:
+            frame = av.VideoFrame.from_ndarray(torch.clamp(frame[..., :3] * 255, min=0, max=255).to(device=torch.device("cpu"), dtype=torch.uint8).numpy(), format="rgb24")
+            for packet in stream.encode(frame):
+                container.mux(packet)
+        container.close()
+
+        results = [{
+            "filename": file,
+            "subfolder": subfolder,
+            "type": self.type
+        }]
+
+        return {"ui": {"images": results, "animated": (True,)}}  # TODO: frontend side
+
+
+NODE_CLASS_MAPPINGS = {
+    "SaveWEBM": SaveWEBM,
+}

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.3.14"
+__version__ = "0.3.15"

nodes.py

@@ -1763,6 +1763,36 @@ class LoadImageMask:
 
         return True
 
+
+class LoadImageOutput(LoadImage):
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image": ("COMBO", {
+                    "image_upload": True,
+                    "image_folder": "output",
+                    "remote": {
+                        "route": "/internal/files/output",
+                        "refresh_button": True,
+                        "control_after_refresh": "first",
+                    },
+                }),
+            }
+        }
+
+    DESCRIPTION = "Load an image from the output folder. When the refresh button is clicked, the node will update the image list and automatically select the first image, allowing for easy iteration."
+    EXPERIMENTAL = True
+    FUNCTION = "load_image_output"
+
+    def load_image_output(self, image):
+        return self.load_image(f"{image} [output]")
+
+    @classmethod
+    def VALIDATE_INPUTS(s, image):
+        return True
+
+
 class ImageScale:
     upscale_methods = ["nearest-exact", "bilinear", "area", "bicubic", "lanczos"]
     crop_methods = ["disabled", "center"]
@@ -1949,6 +1979,7 @@ NODE_CLASS_MAPPINGS = {
     "PreviewImage": PreviewImage,
     "LoadImage": LoadImage,
     "LoadImageMask": LoadImageMask,
+    "LoadImageOutput": LoadImageOutput,
     "ImageScale": ImageScale,
     "ImageScaleBy": ImageScaleBy,
     "ImageInvert": ImageInvert,
@@ -2049,6 +2080,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "PreviewImage": "Preview Image",
     "LoadImage": "Load Image",
     "LoadImageMask": "Load Image (as Mask)",
+    "LoadImageOutput": "Load Image (from Outputs)",
     "ImageScale": "Upscale Image",
     "ImageScaleBy": "Upscale Image By",
     "ImageUpscaleWithModel": "Upscale Image (using Model)",
@@ -2234,6 +2266,7 @@ def init_builtin_extra_nodes():
         "nodes_multigpu.py",
         "nodes_load_3d.py",
         "nodes_cosmos.py",
+        "nodes_video.py",
         "nodes_lumina2.py",
     ]
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.3.14"
+version = "0.3.15"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.9"

requirements.txt

@@ -8,7 +8,8 @@ transformers>=4.28.1
 tokenizers>=0.13.3
 sentencepiece
 safetensors>=0.4.2
-aiohttp
+aiohttp>=3.11.8
+yarl>=1.18.0
 pyyaml
 Pillow
 scipy
@@ -19,3 +20,4 @@ psutil
 kornia>=0.7.1
 spandrel
 soundfile
+av

tests-unit/utils/extra_config_test.py

@@ -145,7 +145,7 @@ def test_load_extra_model_paths_expands_appdata(
     else:
         expected_base_path = '/Users/TestUser/AppData/Roaming/ComfyUI'
     expected_calls = [
-        ('checkpoints', os.path.join(expected_base_path, 'models/checkpoints'), False),
+        ('checkpoints', os.path.normpath(os.path.join(expected_base_path, 'models/checkpoints')), False),
     ]
 
     assert mock_add_model_folder_path.call_count == len(expected_calls)
@@ -197,8 +197,8 @@ def test_load_extra_path_config_relative_base_path(
 
     load_extra_path_config(dummy_yaml_name)
 
-    expected_checkpoints = os.path.abspath(os.path.join(str(tmp_path), sub_folder, "checkpoints"))
+    expected_checkpoints = os.path.abspath(os.path.join(str(tmp_path), "my_rel_base", "checkpoints"))
-    expected_some_value = os.path.abspath(os.path.join(str(tmp_path), sub_folder, "some_value"))
+    expected_some_value = os.path.abspath(os.path.join(str(tmp_path), "my_rel_base", "some_value"))
 
     actual_paths = folder_paths.folder_names_and_paths["checkpoints"][0]
     assert len(actual_paths) == 1, "Should have one path added for 'checkpoints'."

utils/extra_config.py

@@ -29,5 +29,6 @@ def load_extra_path_config(yaml_path):
                     full_path = os.path.join(base_path, full_path)
                 elif not os.path.isabs(full_path):
                     full_path = os.path.abspath(os.path.join(yaml_dir, y))
-                logging.info("Adding extra search path {} {}".format(x, full_path))
+                normalized_path = os.path.normpath(full_path)
-                folder_paths.add_model_folder_path(x, full_path, is_default)
+                logging.info("Adding extra search path {} {}".format(x, normalized_path))
+                folder_paths.add_model_folder_path(x, normalized_path, is_default)