nit

README.md

@@ -69,8 +69,6 @@ See what ComfyUI can do with the [example workflows](https://comfyanonymous.gith
    - [Hunyuan Video](https://comfyanonymous.github.io/ComfyUI_examples/hunyuan_video/)
    - [Nvidia Cosmos](https://comfyanonymous.github.io/ComfyUI_examples/cosmos/)
    - [Wan 2.1](https://comfyanonymous.github.io/ComfyUI_examples/wan/)
-- 3D Models
-   - [Hunyuan3D 2.0](https://docs.comfy.org/tutorials/3d/hunyuan3D-2)
 - [Stable Audio](https://comfyanonymous.github.io/ComfyUI_examples/audio/)
 - Asynchronous Queue system
 - Many optimizations: Only re-executes the parts of the workflow that changes between executions.

app/frontend_management.py

@@ -22,46 +22,28 @@ import app.logger
 # The path to the requirements.txt file
 req_path = Path(__file__).parents[1] / "requirements.txt"
 
-
 def frontend_install_warning_message():
     """The warning message to display when the frontend version is not up to date."""
 
     extra = ""
     if sys.flags.no_user_site:
         extra = "-s "
-    return f"""
+    return f"Please install the updated requirements.txt file by running:\n{sys.executable} {extra}-m pip install -r {req_path}\n\nThis error is happening because the ComfyUI frontend is no longer shipped as part of the main repo but as a pip package instead.\n\nIf you are on the portable package you can run: update\\update_comfyui.bat to solve this problem"
-Please install the updated requirements.txt file by running:
-{sys.executable} {extra}-m pip install -r {req_path}
 
-This error is happening because the ComfyUI frontend is no longer shipped as part of the main repo but as a pip package instead.
 
-If you are on the portable package you can run: update\\update_comfyui.bat to solve this problem
+def parse_version(version: str) -> tuple[int, int, int]:
-""".strip()
+    return tuple(map(int, version.split(".")))
 
 
 def check_frontend_version():
     """Check if the frontend version is up to date."""
-
-    def parse_version(version: str) -> tuple[int, int, int]:
-        return tuple(map(int, version.split(".")))
-
     try:
         frontend_version_str = version("comfyui-frontend-package")
         frontend_version = parse_version(frontend_version_str)
         with open(req_path, "r", encoding="utf-8") as f:
             required_frontend = parse_version(f.readline().split("=")[-1])
         if frontend_version < required_frontend:
-            app.logger.log_startup_warning(
+            app.logger.log_startup_warning("________________________________________________________________________\nWARNING WARNING WARNING WARNING WARNING\n\nInstalled frontend version {} is lower than the recommended version {}.\n\n{}\n________________________________________________________________________".format('.'.join(map(str, frontend_version)), '.'.join(map(str, required_frontend)), frontend_install_warning_message()))
-                f"""
-________________________________________________________________________
-WARNING WARNING WARNING WARNING WARNING
-
-Installed frontend version {".".join(map(str, frontend_version))} is lower than the recommended version {".".join(map(str, required_frontend))}.
-
-{frontend_install_warning_message()}
-________________________________________________________________________
-""".strip()
-            )
         else:
             logging.info("ComfyUI frontend version: {}".format(frontend_version_str))
     except Exception as e:
@@ -91,6 +73,11 @@ class FrontEndProvider:
     owner: str
     repo: str
 
+    @property
+    def is_official(self) -> bool:
+        """Check if the provider is the default official one."""
+        return self.owner == "Comfy-Org" and self.repo == "ComfyUI_frontend"
+
     @property
     def folder_name(self) -> str:
         return f"{self.owner}_{self.repo}"
@@ -161,27 +148,26 @@ def download_release_asset_zip(release: Release, destination_path: str) -> None:
             zip_ref.extractall(destination_path)
 
 
+class FrontendInit(TypedDict):
+    web_root: str
+    """ The path to the initialized frontend. """
+    version: tuple[int, int, int] | None
+    """ The version of the initialized frontend. None for unrecognized version."""
+
 class FrontendManager:
     CUSTOM_FRONTENDS_ROOT = str(Path(__file__).parents[1] / "web_custom_versions")
 
     @classmethod
-    def default_frontend_path(cls) -> str:
+    def init_default_frontend(cls) -> FrontendInit:
+        check_frontend_version()
         try:
             import comfyui_frontend_package
-
+            return FrontendInit(
-            return str(importlib.resources.files(comfyui_frontend_package) / "static")
+                web_root=str(importlib.resources.files(comfyui_frontend_package) / "static"),
-        except ImportError:
+                version=parse_version(version("comfyui-frontend-package")),
-            logging.error(
-                f"""
-********** ERROR ***********
-
-comfyui-frontend-package is not installed.
-
-{frontend_install_warning_message()}
-
-********** ERROR ***********
-""".strip()
             )
+        except ImportError:
+            logging.error(f"\n\n********** ERROR ***********\n\ncomfyui-frontend-package is not installed. {frontend_install_warning_message()}\n********** ERROR **********\n")
             sys.exit(-1)
 
     @classmethod
@@ -204,9 +190,7 @@ comfyui-frontend-package is not installed.
         return match_result.group(1), match_result.group(2), match_result.group(3)
 
     @classmethod
-    def init_frontend_unsafe(
+    def init_frontend_unsafe(cls, version_string: str, provider: Optional[FrontEndProvider] = None) -> FrontendInit:
-        cls, version_string: str, provider: Optional[FrontEndProvider] = None
-    ) -> str:
         """
         Initializes the frontend for the specified version.
 
@@ -222,26 +206,17 @@ comfyui-frontend-package is not installed.
             main error source might be request timeout or invalid URL.
         """
         if version_string == DEFAULT_VERSION_STRING:
-            check_frontend_version()
+            return cls.init_default_frontend()
-            return cls.default_frontend_path()
 
         repo_owner, repo_name, version = cls.parse_version_string(version_string)
 
         if version.startswith("v"):
-            expected_path = str(
+            expected_path = str(Path(cls.CUSTOM_FRONTENDS_ROOT) / f"{repo_owner}_{repo_name}" / version.lstrip("v"))
-                Path(cls.CUSTOM_FRONTENDS_ROOT)
-                / f"{repo_owner}_{repo_name}"
-                / version.lstrip("v")
-            )
             if os.path.exists(expected_path):
-                logging.info(
+                logging.info(f"Using existing copy of specific frontend version tag: {repo_owner}/{repo_name}@{version}")
-                    f"Using existing copy of specific frontend version tag: {repo_owner}/{repo_name}@{version}"
-                )
                 return expected_path
 
-        logging.info(
+        logging.info(f"Initializing frontend: {repo_owner}/{repo_name}@{version}, requesting version details from GitHub...")
-            f"Initializing frontend: {repo_owner}/{repo_name}@{version}, requesting version details from GitHub..."
-        )
 
         provider = provider or FrontEndProvider(repo_owner, repo_name)
         release = provider.get_release(version)
@@ -266,10 +241,13 @@ comfyui-frontend-package is not installed.
                 if not os.listdir(web_root):
                     os.rmdir(web_root)
 
-        return web_root
+        return FrontendInit(
+            web_root=web_root,
+            version=parse_version(semantic_version) if provider.is_official else None,
+        )
 
     @classmethod
-    def init_frontend(cls, version_string: str) -> str:
+    def init_frontend(cls, version_string: str) -> FrontendInit:
         """
         Initializes the frontend with the specified version string.
 
@@ -284,5 +262,4 @@ comfyui-frontend-package is not installed.
         except Exception as e:
             logging.error("Failed to initialize frontend: %s", e)
             logging.info("Falling back to the default frontend.")
-            check_frontend_version()
+            return cls.init_default_frontend()
-            return cls.default_frontend_path()

comfy/comfy_types/node_typing.py

@@ -220,6 +220,13 @@ class ComfyNodeABC(ABC):
     """Flags a node as experimental, informing users that it may change or not work as expected."""
     DEPRECATED: bool
     """Flags a node as deprecated, indicating to users that they should find alternatives to this node."""
+    REQUIRED_FRONTEND_VERSION: str | None
+    """The minimum version of the ComfyUI frontend required to load this node.
+
+    Usage::
+
+        REQUIRED_FRONTEND_VERSION = "1.9.7"
+    """
 
     @classmethod
     @abstractmethod

comfy/ldm/modules/attention.py

@@ -471,7 +471,7 @@ def attention_pytorch(q, k, v, heads, mask=None, attn_precision=None, skip_resha
 def attention_sage(q, k, v, heads, mask=None, attn_precision=None, skip_reshape=False, skip_output_reshape=False):
     if skip_reshape:
         b, _, _, dim_head = q.shape
-        tensor_layout = "HND"
+        tensor_layout="HND"
     else:
         b, _, dim_head = q.shape
         dim_head //= heads
@@ -479,7 +479,7 @@ def attention_sage(q, k, v, heads, mask=None, attn_precision=None, skip_reshape=
             lambda t: t.view(b, -1, heads, dim_head),
             (q, k, v),
         )
-        tensor_layout = "NHD"
+        tensor_layout="NHD"
 
     if mask is not None:
         # add a batch dimension if there isn't already one
@@ -489,17 +489,7 @@ def attention_sage(q, k, v, heads, mask=None, attn_precision=None, skip_reshape=
         if mask.ndim == 3:
             mask = mask.unsqueeze(1)
 
-    try:
+    out = sageattn(q, k, v, attn_mask=mask, is_causal=False, tensor_layout=tensor_layout)
-        out = sageattn(q, k, v, attn_mask=mask, is_causal=False, tensor_layout=tensor_layout)
-    except Exception as e:
-        logging.error("Error running sage attention: {}, using pytorch attention instead.".format(e))
-        if tensor_layout == "NHD":
-            q, k, v = map(
-                lambda t: t.transpose(1, 2),
-                (q, k, v),
-            )
-        return attention_pytorch(q, k, v, heads, mask=mask, skip_reshape=True, skip_output_reshape=skip_output_reshape)
-
     if tensor_layout == "HND":
         if not skip_output_reshape:
             out = (

comfy/model_base.py

@@ -992,8 +992,7 @@ class WAN21(BaseModel):
 
     def concat_cond(self, **kwargs):
         noise = kwargs.get("noise", None)
-        extra_channels = self.diffusion_model.patch_embedding.weight.shape[1] - noise.shape[1]
+        if self.diffusion_model.patch_embedding.weight.shape[1] == noise.shape[1]:
-        if extra_channels == 0:
             return None
 
         image = kwargs.get("concat_latent_image", None)
@@ -1001,30 +1000,23 @@ class WAN21(BaseModel):
 
         if image is None:
             image = torch.zeros_like(noise)
-            shape_image = list(noise.shape)
-            shape_image[1] = extra_channels
-            image = torch.zeros(shape_image, dtype=noise.dtype, layout=noise.layout, device=noise.device)
-        else:
-            image = utils.common_upscale(image.to(device), noise.shape[-1], noise.shape[-2], "bilinear", "center")
-            for i in range(0, image.shape[1], 16):
-                image[:, i: i + 16] = self.process_latent_in(image[:, i: i + 16])
-            image = utils.resize_to_batch_size(image, noise.shape[0])
 
-        if not self.image_to_video or extra_channels == image.shape[1]:
+        image = utils.common_upscale(image.to(device), noise.shape[-1], noise.shape[-2], "bilinear", "center")
+        image = self.process_latent_in(image)
+        image = utils.resize_to_batch_size(image, noise.shape[0])
+
+        if not self.image_to_video:
             return image
 
         mask = kwargs.get("concat_mask", kwargs.get("denoise_mask", None))
         if mask is None:
             mask = torch.zeros_like(noise)[:, :4]
         else:
-            if mask.shape[1] != 4:
+            mask = 1.0 - torch.mean(mask, dim=1, keepdim=True)
-                mask = torch.mean(mask, dim=1, keepdim=True)
-            mask = 1.0 - mask
             mask = utils.common_upscale(mask.to(device), noise.shape[-1], noise.shape[-2], "bilinear", "center")
             if mask.shape[-3] < noise.shape[-3]:
                 mask = torch.nn.functional.pad(mask, (0, 0, 0, 0, 0, noise.shape[-3] - mask.shape[-3]), mode='constant', value=0)
-            if mask.shape[1] == 1:
+            mask = mask.repeat(1, 4, 1, 1, 1)
-                mask = mask.repeat(1, 4, 1, 1, 1)
             mask = utils.resize_to_batch_size(mask, noise.shape[0])
 
         return torch.cat((mask, image), dim=1)

comfy/model_management.py

@@ -46,32 +46,6 @@ cpu_state = CPUState.GPU
 
 total_vram = 0
 
-def get_supported_float8_types():
-    float8_types = []
-    try:
-        float8_types.append(torch.float8_e4m3fn)
-    except:
-        pass
-    try:
-        float8_types.append(torch.float8_e4m3fnuz)
-    except:
-        pass
-    try:
-        float8_types.append(torch.float8_e5m2)
-    except:
-        pass
-    try:
-        float8_types.append(torch.float8_e5m2fnuz)
-    except:
-        pass
-    try:
-        float8_types.append(torch.float8_e8m0fnu)
-    except:
-        pass
-    return float8_types
-
-FLOAT8_TYPES = get_supported_float8_types()
-
 xpu_available = False
 torch_version = ""
 try:
@@ -727,8 +701,11 @@ def unet_dtype(device=None, model_params=0, supported_dtypes=[torch.float16, tor
         return torch.float8_e5m2
 
     fp8_dtype = None
-    if weight_dtype in FLOAT8_TYPES:
+    try:
-        fp8_dtype = weight_dtype
+        if weight_dtype in [torch.float8_e4m3fn, torch.float8_e5m2]:
+            fp8_dtype = weight_dtype
+    except:
+        pass
 
     if fp8_dtype is not None:
         if supports_fp8_compute(device): #if fp8 compute is supported the casting is most likely not expensive

comfy/supported_models.py

@@ -969,24 +969,12 @@ class WAN21_I2V(WAN21_T2V):
     unet_config = {
         "image_model": "wan2.1",
         "model_type": "i2v",
-        "in_dim": 36,
     }
 
     def get_model(self, state_dict, prefix="", device=None):
         out = model_base.WAN21(self, image_to_video=True, device=device)
         return out
 
-class WAN21_FunControl2V(WAN21_T2V):
-    unet_config = {
-        "image_model": "wan2.1",
-        "model_type": "i2v",
-        "in_dim": 48,
-    }
-
-    def get_model(self, state_dict, prefix="", device=None):
-        out = model_base.WAN21(self, image_to_video=False, device=device)
-        return out
-
 class Hunyuan3Dv2(supported_models_base.BASE):
     unet_config = {
         "image_model": "hunyuan3d2",
@@ -1025,6 +1013,6 @@ class Hunyuan3Dv2mini(Hunyuan3Dv2):
 
     latent_format = latent_formats.Hunyuan3Dv2mini
 
-models = [LotusD, Stable_Zero123, SD15_instructpix2pix, SD15, SD20, SD21UnclipL, SD21UnclipH, SDXL_instructpix2pix, SDXLRefiner, SDXL, SSD1B, KOALA_700M, KOALA_1B, Segmind_Vega, SD_X4Upscaler, Stable_Cascade_C, Stable_Cascade_B, SV3D_u, SV3D_p, SD3, StableAudio, AuraFlow, PixArtAlpha, PixArtSigma, HunyuanDiT, HunyuanDiT1, FluxInpaint, Flux, FluxSchnell, GenmoMochi, LTXV, HunyuanVideoSkyreelsI2V, HunyuanVideoI2V, HunyuanVideo, CosmosT2V, CosmosI2V, Lumina2, WAN21_T2V, WAN21_I2V, WAN21_FunControl2V, Hunyuan3Dv2mini, Hunyuan3Dv2]
+models = [LotusD, Stable_Zero123, SD15_instructpix2pix, SD15, SD20, SD21UnclipL, SD21UnclipH, SDXL_instructpix2pix, SDXLRefiner, SDXL, SSD1B, KOALA_700M, KOALA_1B, Segmind_Vega, SD_X4Upscaler, Stable_Cascade_C, Stable_Cascade_B, SV3D_u, SV3D_p, SD3, StableAudio, AuraFlow, PixArtAlpha, PixArtSigma, HunyuanDiT, HunyuanDiT1, FluxInpaint, Flux, FluxSchnell, GenmoMochi, LTXV, HunyuanVideoSkyreelsI2V, HunyuanVideoI2V, HunyuanVideo, CosmosT2V, CosmosI2V, Lumina2, WAN21_T2V, WAN21_I2V, Hunyuan3Dv2mini, Hunyuan3Dv2]
 
 models += [SVD_img2vid]

comfy_extras/nodes_cfg.py

@@ -1,45 +0,0 @@
-import torch
-
-# https://github.com/WeichenFan/CFG-Zero-star
-def optimized_scale(positive, negative):
-    positive_flat = positive.reshape(positive.shape[0], -1)
-    negative_flat = negative.reshape(negative.shape[0], -1)
-
-    # Calculate dot production
-    dot_product = torch.sum(positive_flat * negative_flat, dim=1, keepdim=True)
-
-    # Squared norm of uncondition
-    squared_norm = torch.sum(negative_flat ** 2, dim=1, keepdim=True) + 1e-8
-
-    # st_star = v_cond^T * v_uncond / ||v_uncond||^2
-    st_star = dot_product / squared_norm
-
-    return st_star.reshape([positive.shape[0]] + [1] * (positive.ndim - 1))
-
-class CFGZeroStar:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {"required": {"model": ("MODEL",),
-                            }}
-    RETURN_TYPES = ("MODEL",)
-    RETURN_NAMES = ("patched_model",)
-    FUNCTION = "patch"
-    CATEGORY = "advanced/guidance"
-
-    def patch(self, model):
-        m = model.clone()
-        def cfg_zero_star(args):
-            guidance_scale = args['cond_scale']
-            x = args['input']
-            cond_p = args['cond_denoised']
-            uncond_p = args['uncond_denoised']
-            out = args["denoised"]
-            alpha = optimized_scale(x - cond_p, x - uncond_p)
-
-            return out + uncond_p * (alpha - 1.0)  + guidance_scale * uncond_p * (1.0 - alpha)
-        m.set_model_sampler_post_cfg_function(cfg_zero_star)
-        return (m, )
-
-NODE_CLASS_MAPPINGS = {
-    "CFGZeroStar": CFGZeroStar
-}

comfy_extras/nodes_load_3d.py

@@ -21,8 +21,8 @@ class Load3D():
             "height": ("INT", {"default": 1024, "min": 1, "max": 4096, "step": 1}),
         }}
 
-    RETURN_TYPES = ("IMAGE", "MASK", "STRING", "IMAGE", "IMAGE")
+    RETURN_TYPES = ("IMAGE", "MASK", "STRING")
-    RETURN_NAMES = ("image", "mask", "mesh_path", "normal", "lineart")
+    RETURN_NAMES = ("image", "mask", "mesh_path")
 
     FUNCTION = "process"
     EXPERIMENTAL = True
@@ -32,16 +32,12 @@ class Load3D():
     def process(self, model_file, image, **kwargs):
         image_path = folder_paths.get_annotated_filepath(image['image'])
         mask_path = folder_paths.get_annotated_filepath(image['mask'])
-        normal_path = folder_paths.get_annotated_filepath(image['normal'])
-        lineart_path = folder_paths.get_annotated_filepath(image['lineart'])
 
         load_image_node = nodes.LoadImage()
         output_image, ignore_mask = load_image_node.load_image(image=image_path)
         ignore_image, output_mask = load_image_node.load_image(image=mask_path)
-        normal_image, ignore_mask2 = load_image_node.load_image(image=normal_path)
-        lineart_image, ignore_mask3 = load_image_node.load_image(image=lineart_path)
 
-        return output_image, output_mask, model_file, normal_image, lineart_image
+        return output_image, output_mask, model_file,
 
 class Load3DAnimation():
     @classmethod
@@ -59,8 +55,8 @@ class Load3DAnimation():
             "height": ("INT", {"default": 1024, "min": 1, "max": 4096, "step": 1}),
         }}
 
-    RETURN_TYPES = ("IMAGE", "MASK", "STRING", "IMAGE")
+    RETURN_TYPES = ("IMAGE", "MASK", "STRING")
-    RETURN_NAMES = ("image", "mask", "mesh_path", "normal")
+    RETURN_NAMES = ("image", "mask", "mesh_path")
 
     FUNCTION = "process"
     EXPERIMENTAL = True
@@ -70,14 +66,12 @@ class Load3DAnimation():
     def process(self, model_file, image, **kwargs):
         image_path = folder_paths.get_annotated_filepath(image['image'])
         mask_path = folder_paths.get_annotated_filepath(image['mask'])
-        normal_path = folder_paths.get_annotated_filepath(image['normal'])
 
         load_image_node = nodes.LoadImage()
         output_image, ignore_mask = load_image_node.load_image(image=image_path)
         ignore_image, output_mask = load_image_node.load_image(image=mask_path)
-        normal_image, ignore_mask2 = load_image_node.load_image(image=normal_path)
 
-        return output_image, output_mask, model_file, normal_image
+        return output_image, output_mask, model_file,
 
 class Preview3D():
     @classmethod

comfy_extras/nodes_model_merging_model_specific.py

@@ -244,30 +244,6 @@ class ModelMergeCosmos14B(comfy_extras.nodes_model_merging.ModelMergeBlocks):
 
         return {"required": arg_dict}
 
-class ModelMergeWAN2_1(comfy_extras.nodes_model_merging.ModelMergeBlocks):
-    CATEGORY = "advanced/model_merging/model_specific"
-    DESCRIPTION = "1.3B model has 30 blocks, 14B model has 40 blocks. Image to video model has the extra img_emb."
-
-    @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["patch_embedding."] = argument
-        arg_dict["time_embedding."] = argument
-        arg_dict["time_projection."] = argument
-        arg_dict["text_embedding."] = argument
-        arg_dict["img_emb."] = argument
-
-        for i in range(40):
-            arg_dict["blocks.{}.".format(i)] = argument
-
-        arg_dict["head."] = argument
-
-        return {"required": arg_dict}
-
 NODE_CLASS_MAPPINGS = {
     "ModelMergeSD1": ModelMergeSD1,
     "ModelMergeSD2": ModelMergeSD1, #SD1 and SD2 have the same blocks
@@ -280,5 +256,4 @@ NODE_CLASS_MAPPINGS = {
     "ModelMergeLTXV": ModelMergeLTXV,
     "ModelMergeCosmos7B": ModelMergeCosmos7B,
     "ModelMergeCosmos14B": ModelMergeCosmos14B,
-    "ModelMergeWAN2_1": ModelMergeWAN2_1,
 }

comfy_extras/nodes_wan.py

@@ -3,7 +3,6 @@ import node_helpers
 import torch
 import comfy.model_management
 import comfy.utils
-import comfy.latent_formats
 
 
 class WanImageToVideo:
@@ -50,110 +49,6 @@ class WanImageToVideo:
         return (positive, negative, out_latent)
 
 
-class WanFunControlToVideo:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {"required": {"positive": ("CONDITIONING", ),
-                             "negative": ("CONDITIONING", ),
-                             "vae": ("VAE", ),
-                             "width": ("INT", {"default": 832, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
-                             "height": ("INT", {"default": 480, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
-                             "length": ("INT", {"default": 81, "min": 1, "max": nodes.MAX_RESOLUTION, "step": 4}),
-                             "batch_size": ("INT", {"default": 1, "min": 1, "max": 4096}),
-                },
-                "optional": {"clip_vision_output": ("CLIP_VISION_OUTPUT", ),
-                             "start_image": ("IMAGE", ),
-                             "control_video": ("IMAGE", ),
-                }}
-
-    RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "LATENT")
-    RETURN_NAMES = ("positive", "negative", "latent")
-    FUNCTION = "encode"
-
-    CATEGORY = "conditioning/video_models"
-
-    def encode(self, positive, negative, vae, width, height, length, batch_size, start_image=None, clip_vision_output=None, control_video=None):
-        latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device())
-        concat_latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device())
-        concat_latent = comfy.latent_formats.Wan21().process_out(concat_latent)
-        concat_latent = concat_latent.repeat(1, 2, 1, 1, 1)
-
-        if start_image is not None:
-            start_image = comfy.utils.common_upscale(start_image[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
-            concat_latent_image = vae.encode(start_image[:, :, :, :3])
-            concat_latent[:,16:,:concat_latent_image.shape[2]] = concat_latent_image[:,:,:concat_latent.shape[2]]
-
-        if control_video is not None:
-            control_video = comfy.utils.common_upscale(control_video[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
-            concat_latent_image = vae.encode(control_video[:, :, :, :3])
-            concat_latent[:,:16,:concat_latent_image.shape[2]] = concat_latent_image[:,:,:concat_latent.shape[2]]
-
-        positive = node_helpers.conditioning_set_values(positive, {"concat_latent_image": concat_latent})
-        negative = node_helpers.conditioning_set_values(negative, {"concat_latent_image": concat_latent})
-
-        if clip_vision_output is not None:
-            positive = node_helpers.conditioning_set_values(positive, {"clip_vision_output": clip_vision_output})
-            negative = node_helpers.conditioning_set_values(negative, {"clip_vision_output": clip_vision_output})
-
-        out_latent = {}
-        out_latent["samples"] = latent
-        return (positive, negative, out_latent)
-
-class WanFunInpaintToVideo:
-    @classmethod
-    def INPUT_TYPES(s):
-        return {"required": {"positive": ("CONDITIONING", ),
-                             "negative": ("CONDITIONING", ),
-                             "vae": ("VAE", ),
-                             "width": ("INT", {"default": 832, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
-                             "height": ("INT", {"default": 480, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
-                             "length": ("INT", {"default": 81, "min": 1, "max": nodes.MAX_RESOLUTION, "step": 4}),
-                             "batch_size": ("INT", {"default": 1, "min": 1, "max": 4096}),
-                },
-                "optional": {"clip_vision_output": ("CLIP_VISION_OUTPUT", ),
-                             "start_image": ("IMAGE", ),
-                             "end_image": ("IMAGE", ),
-                }}
-
-    RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "LATENT")
-    RETURN_NAMES = ("positive", "negative", "latent")
-    FUNCTION = "encode"
-
-    CATEGORY = "conditioning/video_models"
-
-    def encode(self, positive, negative, vae, width, height, length, batch_size, start_image=None, end_image=None, clip_vision_output=None):
-        latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device())
-        if start_image is not None:
-            start_image = comfy.utils.common_upscale(start_image[:length].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
-        if end_image is not None:
-            end_image = comfy.utils.common_upscale(end_image[-length:].movedim(-1, 1), width, height, "bilinear", "center").movedim(1, -1)
-
-        image = torch.ones((length, height, width, 3)) * 0.5
-        mask = torch.ones((1, 1, latent.shape[2] * 4, latent.shape[-2], latent.shape[-1]))
-
-        if start_image is not None:
-            image[:start_image.shape[0]] = start_image
-            mask[:, :, :start_image.shape[0] + 3] = 0.0
-
-        if end_image is not None:
-            image[-end_image.shape[0]:] = end_image
-            mask[:, :, -end_image.shape[0]:] = 0.0
-
-        concat_latent_image = vae.encode(image[:, :, :, :3])
-        mask = mask.view(1, mask.shape[2] // 4, 4, mask.shape[3], mask.shape[4]).transpose(1, 2)
-        positive = node_helpers.conditioning_set_values(positive, {"concat_latent_image": concat_latent_image, "concat_mask": mask})
-        negative = node_helpers.conditioning_set_values(negative, {"concat_latent_image": concat_latent_image, "concat_mask": mask})
-
-        if clip_vision_output is not None:
-            positive = node_helpers.conditioning_set_values(positive, {"clip_vision_output": clip_vision_output})
-            negative = node_helpers.conditioning_set_values(negative, {"clip_vision_output": clip_vision_output})
-
-        out_latent = {}
-        out_latent["samples"] = latent
-        return (positive, negative, out_latent)
-
 NODE_CLASS_MAPPINGS = {
     "WanImageToVideo": WanImageToVideo,
-    "WanFunControlToVideo": WanFunControlToVideo,
-    "WanFunInpaintToVideo": WanFunInpaintToVideo,
 }

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.3.27"
+__version__ = "0.3.26"

nodes.py

@@ -2267,7 +2267,6 @@ def init_builtin_extra_nodes():
         "nodes_lotus.py",
         "nodes_hunyuan3d.py",
         "nodes_primitive.py",
-        "nodes_cfg.py",
     ]
 
     import_failed = []

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.3.27"
+version = "0.3.26"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.9"

requirements.txt

@@ -1,4 +1,4 @@
-comfyui-frontend-package==1.14.6
+comfyui-frontend-package==1.14.5
 torch
 torchsde
 torchvision

server.py

@@ -1,3 +1,4 @@
+from __future__ import annotations
 import os
 import sys
 import asyncio
@@ -24,11 +25,12 @@ import logging
 
 import mimetypes
 from comfy.cli_args import args
+from comfy.comfy_types.node_typing import ComfyNodeABC
 import comfy.utils
 import comfy.model_management
 import node_helpers
 from comfyui_version import __version__
-from app.frontend_management import FrontendManager
+from app.frontend_management import FrontendInit, FrontendManager, parse_version
 from app.user_manager import UserManager
 from app.model_manager import ModelFileManager
 from app.custom_node_manager import CustomNodeManager
@@ -146,6 +148,11 @@ def create_origin_only_middleware():
     return origin_only_middleware
 
 class PromptServer():
+    web_root: str
+    """The path to the initialized frontend assets."""
+    frontend_version: tuple[int, int, int] | None = None
+    """The version of the initialized frontend. None for unrecognized version."""
+
     def __init__(self, loop):
         PromptServer.instance = self
 
@@ -176,12 +183,19 @@ class PromptServer():
         max_upload_size = round(args.max_upload_size * 1024 * 1024)
         self.app = web.Application(client_max_size=max_upload_size, middlewares=middlewares)
         self.sockets = dict()
-        self.web_root = (
+
-            FrontendManager.init_frontend(args.front_end_version)
+        if args.front_end_root:
-            if args.front_end_root is None
+            frontend_init = FrontendInit(
-            else args.front_end_root
+                web_root=args.front_end_root,
-        )
+                version=None,
+            )
+        else:
+            frontend_init = FrontendManager.init_frontend(args.front_end_version)
+
+        self.frontend_version = frontend_init["version"]
+        self.web_root = frontend_init["web_root"]
         logging.info(f"[Prompt Server] web root: {self.web_root}")
+
         routes = web.RouteTableDef()
         self.routes = routes
         self.last_node_id = None
@@ -587,6 +601,9 @@ class PromptServer():
             with folder_paths.cache_helper:
                 out = {}
                 for x in nodes.NODE_CLASS_MAPPINGS:
+                    if not self.node_is_supported(x):
+                        continue
+
                     try:
                         out[x] = node_info(x)
                     except Exception:
@@ -598,7 +615,11 @@ class PromptServer():
         async def get_object_info_node(request):
             node_class = request.match_info.get("node_class", None)
             out = {}
-            if (node_class is not None) and (node_class in nodes.NODE_CLASS_MAPPINGS):
+            if (
+                node_class is not None
+                and node_class in nodes.NODE_CLASS_MAPPINGS
+                and self.node_is_supported(node_class)
+            ):
                 out[node_class] = node_info(node_class)
             return web.json_response(out)
 
@@ -863,3 +884,15 @@ class PromptServer():
                 logging.warning(traceback.format_exc())
 
         return json_data
+
+    def node_is_supported(self, node_class: ComfyNodeABC) -> bool:
+        """Check if the node is supported by the frontend."""
+        # For unrecognized frontend version, we assume the node is supported.
+        if self.frontend_version is None:
+            return True
+
+        # Check if the node is supported by the frontend.
+        if node_class.REQUIRED_FRONTEND_VERSION is None:
+            return True
+
+        return parse_version(node_class.REQUIRED_FRONTEND_VERSION) <= self.frontend_version

tests-unit/app_test/frontend_manager_test.py

@@ -69,8 +69,10 @@ def test_get_release_invalid_version(mock_provider):
 
 def test_init_frontend_default():
     version_string = DEFAULT_VERSION_STRING
-    frontend_path = FrontendManager.init_frontend(version_string)
+    frontend_init = FrontendManager.init_frontend(version_string)
-    assert frontend_path == FrontendManager.default_frontend_path()
+    assert isinstance(frontend_init, dict)
+    assert "web_root" in frontend_init
+    assert "version" in frontend_init
 
 
 def test_init_frontend_invalid_version():
@@ -138,37 +140,47 @@ def test_parse_version_string_invalid():
 def test_init_frontend_default_with_mocks():
     # Arrange
     version_string = DEFAULT_VERSION_STRING
+    mock_path = "/mocked/path"
+    mock_version = (1, 0, 0)
 
     # Act
     with (
         patch("app.frontend_management.check_frontend_version") as mock_check,
         patch.object(
-            FrontendManager, "default_frontend_path", return_value="/mocked/path"
+            FrontendManager,
+            "init_default_frontend",
+            return_value={"web_root": mock_path, "version": mock_version},
         ),
     ):
-        frontend_path = FrontendManager.init_frontend(version_string)
+        frontend_init = FrontendManager.init_frontend(version_string)
 
     # Assert
-    assert frontend_path == "/mocked/path"
+    assert frontend_init["web_root"] == mock_path
-    mock_check.assert_called_once()
+    assert frontend_init["version"] == mock_version
+    mock_check.assert_not_called()  # check_frontend_version is now called inside init_default_frontend
 
 
 def test_init_frontend_fallback_on_error():
     # Arrange
     version_string = "test-owner/test-repo@1.0.0"
+    mock_path = "/default/path"
+    mock_version = (1, 0, 0)
 
     # Act
     with (
         patch.object(
-            FrontendManager, "init_frontend_unsafe", side_effect=Exception("Test error")
+            FrontendManager,
+            "init_frontend_unsafe",
+            side_effect=Exception("Test error")
         ),
-        patch("app.frontend_management.check_frontend_version") as mock_check,
         patch.object(
-            FrontendManager, "default_frontend_path", return_value="/default/path"
+            FrontendManager,
+            "init_default_frontend",
+            return_value={"web_root": mock_path, "version": mock_version},
         ),
     ):
-        frontend_path = FrontendManager.init_frontend(version_string)
+        frontend_init = FrontendManager.init_frontend(version_string)
 
     # Assert
-    assert frontend_path == "/default/path"
+    assert frontend_init["web_root"] == mock_path
-    mock_check.assert_called_once()
+    assert frontend_init["version"] == mock_version