Merge branch 'master' into dr-support-pip-cm

.github/workflows/windows_release_dependencies_manual.yml

@@ -0,0 +1,64 @@
+name: "Windows Release dependencies Manual"
+
+on:
+  workflow_dispatch:
+    inputs:
+      torch_dependencies:
+        description: 'torch dependencies'
+        required: false
+        type: string
+        default: "torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu128"
+      cache_tag:
+        description: 'Cached dependencies tag'
+        required: true
+        type: string
+        default: "cu128"
+
+      python_minor:
+        description: 'python minor version'
+        required: true
+        type: string
+        default: "12"
+
+      python_patch:
+        description: 'python patch version'
+        required: true
+        type: string
+        default: "10"
+
+jobs:
+  build_dependencies:
+    runs-on: windows-latest
+    steps:
+        - uses: actions/checkout@v4
+        - uses: actions/setup-python@v5
+          with:
+            python-version: 3.${{ inputs.python_minor }}.${{ inputs.python_patch }}
+
+        - shell: bash
+          run: |
+            echo "@echo off
+            call update_comfyui.bat nopause
+            echo -
+            echo This will try to update pytorch and all python dependencies.
+            echo -
+            echo If you just want to update normally, close this and run update_comfyui.bat instead.
+            echo -
+            pause
+            ..\python_embeded\python.exe -s -m pip install --upgrade ${{ inputs.torch_dependencies }} -r ../ComfyUI/requirements.txt pygit2
+            pause" > update_comfyui_and_python_dependencies.bat
+
+            grep -v comfyui requirements.txt > requirements_nocomfyui.txt
+            python -m pip wheel --no-cache-dir ${{ inputs.torch_dependencies }} -r requirements_nocomfyui.txt pygit2 -w ./temp_wheel_dir
+            python -m pip install --no-cache-dir ./temp_wheel_dir/*
+            echo installed basic
+            ls -lah temp_wheel_dir
+            mv temp_wheel_dir ${{ inputs.cache_tag }}_python_deps
+            tar cf ${{ inputs.cache_tag }}_python_deps.tar ${{ inputs.cache_tag }}_python_deps
+
+        - uses: actions/cache/save@v4
+          with:
+            path: |
+              ${{ inputs.cache_tag }}_python_deps.tar
+              update_comfyui_and_python_dependencies.bat
+            key: ${{ runner.os }}-build-${{ inputs.cache_tag }}-${{ inputs.python_minor }}

comfy_api_nodes/nodes_rodin.py

@@ -11,7 +11,6 @@ from comfy.comfy_types.node_typing import IO
 import folder_paths as comfy_paths
 import aiohttp
 import os
-import datetime
 import asyncio
 import io
 import logging
@@ -243,8 +242,8 @@ class Rodin3DAPI:
 
         return mesh_mode, quality_override
 
-    async def download_files(self, url_list):
+    async def download_files(self, url_list, task_uuid):
-        save_path = os.path.join(comfy_paths.get_output_directory(), "Rodin3D", datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S"))
+        save_path = os.path.join(comfy_paths.get_output_directory(), f"Rodin3D_{task_uuid}")
         os.makedirs(save_path, exist_ok=True)
         model_file_path = None
         async with aiohttp.ClientSession() as session:
@@ -320,7 +319,7 @@ class Rodin3D_Regular(Rodin3DAPI):
                                                                 **kwargs)
         await self.poll_for_task_status(subscription_key, **kwargs)
         download_list = await self.get_rodin_download_list(task_uuid, **kwargs)
-        model = await self.download_files(download_list)
+        model = await self.download_files(download_list, task_uuid)
 
         return (model,)
 
@@ -366,7 +365,7 @@ class Rodin3D_Detail(Rodin3DAPI):
                                                                 **kwargs)
         await self.poll_for_task_status(subscription_key, **kwargs)
         download_list = await self.get_rodin_download_list(task_uuid, **kwargs)
-        model = await self.download_files(download_list)
+        model = await self.download_files(download_list, task_uuid)
 
         return (model,)
 
@@ -412,7 +411,7 @@ class Rodin3D_Smooth(Rodin3DAPI):
                                                                 **kwargs)
         await self.poll_for_task_status(subscription_key, **kwargs)
         download_list = await self.get_rodin_download_list(task_uuid, **kwargs)
-        model = await self.download_files(download_list)
+        model = await self.download_files(download_list, task_uuid)
 
         return (model,)
 
@@ -467,7 +466,7 @@ class Rodin3D_Sketch(Rodin3DAPI):
         )
         await self.poll_for_task_status(subscription_key, **kwargs)
         download_list = await self.get_rodin_download_list(task_uuid, **kwargs)
-        model = await self.download_files(download_list)
+        model = await self.download_files(download_list, task_uuid)
 
         return (model,)
 

comfy_api_nodes/nodes_wan.py

@@ -28,6 +28,12 @@ class Text2ImageInputField(BaseModel):
     negative_prompt: Optional[str] = Field(None)
 
 
+class Image2ImageInputField(BaseModel):
+    prompt: str = Field(...)
+    negative_prompt: Optional[str] = Field(None)
+    images: list[str] = Field(..., min_length=1, max_length=2)
+
+
 class Text2VideoInputField(BaseModel):
     prompt: str = Field(...)
     negative_prompt: Optional[str] = Field(None)
@@ -49,6 +55,13 @@ class Txt2ImageParametersField(BaseModel):
     watermark: bool = Field(True)
 
 
+class Image2ImageParametersField(BaseModel):
+    size: Optional[str] = Field(None)
+    n: int = Field(1, description="Number of images to generate.")  # we support only value=1
+    seed: int = Field(..., ge=0, le=2147483647)
+    watermark: bool = Field(True)
+
+
 class Text2VideoParametersField(BaseModel):
     size: str = Field(...)
     seed: int = Field(..., ge=0, le=2147483647)
@@ -73,6 +86,12 @@ class Text2ImageTaskCreationRequest(BaseModel):
     parameters: Txt2ImageParametersField = Field(...)
 
 
+class Image2ImageTaskCreationRequest(BaseModel):
+    model: str = Field(...)
+    input: Image2ImageInputField = Field(...)
+    parameters: Image2ImageParametersField = Field(...)
+
+
 class Text2VideoTaskCreationRequest(BaseModel):
     model: str = Field(...)
     input: Text2VideoInputField = Field(...)
@@ -135,7 +154,12 @@ async def process_task(
     url: str,
     request_model: Type[T],
     response_model: Type[R],
-    payload: Union[Text2ImageTaskCreationRequest, Text2VideoTaskCreationRequest, Image2VideoTaskCreationRequest],
+    payload: Union[
+        Text2ImageTaskCreationRequest,
+        Image2ImageTaskCreationRequest,
+        Text2VideoTaskCreationRequest,
+        Image2VideoTaskCreationRequest,
+    ],
     node_id: str,
     estimated_duration: int,
     poll_interval: int,
@@ -288,6 +312,128 @@ class WanTextToImageApi(comfy_io.ComfyNode):
         return comfy_io.NodeOutput(await download_url_to_image_tensor(str(response.output.results[0].url)))
 
 
+class WanImageToImageApi(comfy_io.ComfyNode):
+    @classmethod
+    def define_schema(cls):
+        return comfy_io.Schema(
+            node_id="WanImageToImageApi",
+            display_name="Wan Image to Image",
+            category="api node/image/Wan",
+            description="Generates an image from one or two input images and a text prompt. "
+                        "The output image is currently fixed at 1.6 MP; its aspect ratio matches the input image(s).",
+            inputs=[
+                comfy_io.Combo.Input(
+                    "model",
+                    options=["wan2.5-i2i-preview"],
+                    default="wan2.5-i2i-preview",
+                    tooltip="Model to use.",
+                ),
+                comfy_io.Image.Input(
+                    "image",
+                    tooltip="Single-image editing or multi-image fusion, maximum 2 images.",
+                ),
+                comfy_io.String.Input(
+                    "prompt",
+                    multiline=True,
+                    default="",
+                    tooltip="Prompt used to describe the elements and visual features, supports English/Chinese.",
+                ),
+                comfy_io.String.Input(
+                    "negative_prompt",
+                    multiline=True,
+                    default="",
+                    tooltip="Negative text prompt to guide what to avoid.",
+                    optional=True,
+                ),
+                # redo this later as an optional combo of recommended resolutions
+                # comfy_io.Int.Input(
+                #     "width",
+                #     default=1280,
+                #     min=384,
+                #     max=1440,
+                #     step=16,
+                #     optional=True,
+                # ),
+                # comfy_io.Int.Input(
+                #     "height",
+                #     default=1280,
+                #     min=384,
+                #     max=1440,
+                #     step=16,
+                #     optional=True,
+                # ),
+                comfy_io.Int.Input(
+                    "seed",
+                    default=0,
+                    min=0,
+                    max=2147483647,
+                    step=1,
+                    display_mode=comfy_io.NumberDisplay.number,
+                    control_after_generate=True,
+                    tooltip="Seed to use for generation.",
+                    optional=True,
+                ),
+                comfy_io.Boolean.Input(
+                    "watermark",
+                    default=True,
+                    tooltip="Whether to add an \"AI generated\" watermark to the result.",
+                    optional=True,
+                ),
+            ],
+            outputs=[
+                comfy_io.Image.Output(),
+            ],
+            hidden=[
+                comfy_io.Hidden.auth_token_comfy_org,
+                comfy_io.Hidden.api_key_comfy_org,
+                comfy_io.Hidden.unique_id,
+            ],
+            is_api_node=True,
+        )
+
+    @classmethod
+    async def execute(
+        cls,
+        model: str,
+        image: torch.Tensor,
+        prompt: str,
+        negative_prompt: str = "",
+        # width: int = 1024,
+        # height: int = 1024,
+        seed: int = 0,
+        watermark: bool = True,
+    ):
+        n_images = get_number_of_images(image)
+        if n_images not in (1, 2):
+            raise ValueError(f"Expected 1 or 2 input images, got {n_images}.")
+        images = []
+        for i in image:
+            images.append("data:image/png;base64," + tensor_to_base64_string(i, total_pixels=4096*4096))
+        payload = Image2ImageTaskCreationRequest(
+            model=model,
+            input=Image2ImageInputField(prompt=prompt, negative_prompt=negative_prompt, images=images),
+            parameters=Image2ImageParametersField(
+                # size=f"{width}*{height}",
+                seed=seed,
+                watermark=watermark,
+            ),
+        )
+        response = await process_task(
+            {
+                "auth_token": cls.hidden.auth_token_comfy_org,
+                "comfy_api_key": cls.hidden.api_key_comfy_org,
+            },
+            "/proxy/wan/api/v1/services/aigc/image2image/image-synthesis",
+            request_model=Image2ImageTaskCreationRequest,
+            response_model=ImageTaskStatusResponse,
+            payload=payload,
+            node_id=cls.hidden.unique_id,
+            estimated_duration=42,
+            poll_interval=3,
+        )
+        return comfy_io.NodeOutput(await download_url_to_image_tensor(str(response.output.results[0].url)))
+
+
 class WanTextToVideoApi(comfy_io.ComfyNode):
     @classmethod
     def define_schema(cls):
@@ -593,6 +739,7 @@ class WanApiExtension(ComfyExtension):
     async def get_node_list(self) -> list[type[comfy_io.ComfyNode]]:
         return [
             WanTextToImageApi,
+            WanImageToImageApi,
             WanTextToVideoApi,
             WanImageToVideoApi,
         ]

comfy_extras/nodes_mahiro.py

@@ -1,17 +1,29 @@
+from typing_extensions import override
 import torch
 import torch.nn.functional as F
 
-class Mahiro:
+from comfy_api.latest import ComfyExtension, io
+
+
+class Mahiro(io.ComfyNode):
     @classmethod
-    def INPUT_TYPES(s):
+    def define_schema(cls):
-        return {"required": {"model": ("MODEL",),
+        return io.Schema(
-                            }}
+            node_id="Mahiro",
-    RETURN_TYPES = ("MODEL",)
+            display_name="Mahiro is so cute that she deserves a better guidance function!! (。・ω・。)",
-    RETURN_NAMES = ("patched_model",)
+            category="_for_testing",
-    FUNCTION = "patch"
+            description="Modify the guidance to scale more on the 'direction' of the positive prompt rather than the difference between the negative prompt.",
-    CATEGORY = "_for_testing"
+            inputs=[
-    DESCRIPTION = "Modify the guidance to scale more on the 'direction' of the positive prompt rather than the difference between the negative prompt."
+                io.Model.Input("model"),
-    def patch(self, model):
+            ],
+            outputs=[
+                io.Model.Output(display_name="patched_model"),
+            ],
+            is_experimental=True,
+        )
+
+    @classmethod
+    def execute(cls, model) -> io.NodeOutput:
         m = model.clone()
         def mahiro_normd(args):
             scale: float = args['cond_scale']
@@ -30,12 +42,16 @@ class Mahiro:
             wm = (simsc*cfg + (4-simsc)*leap) / 4
             return wm
         m.set_model_sampler_post_cfg_function(mahiro_normd)
-        return (m, )
+        return io.NodeOutput(m)
 
-NODE_CLASS_MAPPINGS = {
-    "Mahiro": Mahiro
-}
 
-NODE_DISPLAY_NAME_MAPPINGS = {
+class MahiroExtension(ComfyExtension):
-    "Mahiro": "Mahiro is so cute that she deserves a better guidance function!! (。・ω・。)",
+    @override
-}
+    async def get_node_list(self) -> list[type[io.ComfyNode]]:
+        return [
+            Mahiro,
+        ]
+
+
+async def comfy_entrypoint() -> MahiroExtension:
+    return MahiroExtension()

comfy_extras/nodes_mochi.py

@@ -1,23 +1,40 @@
-import nodes
+from typing_extensions import override
 import torch
 import comfy.model_management
+import nodes
+from comfy_api.latest import ComfyExtension, io
 
-class EmptyMochiLatentVideo:
+
+class EmptyMochiLatentVideo(io.ComfyNode):
     @classmethod
-    def INPUT_TYPES(s):
+    def define_schema(cls):
-        return {"required": { "width": ("INT", {"default": 848, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
+        return io.Schema(
-                              "height": ("INT", {"default": 480, "min": 16, "max": nodes.MAX_RESOLUTION, "step": 16}),
+            node_id="EmptyMochiLatentVideo",
-                              "length": ("INT", {"default": 25, "min": 7, "max": nodes.MAX_RESOLUTION, "step": 6}),
+            category="latent/video",
-                              "batch_size": ("INT", {"default": 1, "min": 1, "max": 4096})}}
+            inputs=[
-    RETURN_TYPES = ("LATENT",)
+                io.Int.Input("width", default=848, min=16, max=nodes.MAX_RESOLUTION, step=16),
-    FUNCTION = "generate"
+                io.Int.Input("height", default=480, min=16, max=nodes.MAX_RESOLUTION, step=16),
+                io.Int.Input("length", default=25, min=7, max=nodes.MAX_RESOLUTION, step=6),
+                io.Int.Input("batch_size", default=1, min=1, max=4096),
+            ],
+            outputs=[
+                io.Latent.Output(),
+            ],
+        )
 
-    CATEGORY = "latent/video"
+    @classmethod
-
+    def execute(cls, width, height, length, batch_size=1) -> io.NodeOutput:
-    def generate(self, width, height, length, batch_size=1):
         latent = torch.zeros([batch_size, 12, ((length - 1) // 6) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device())
-        return ({"samples":latent}, )
+        return io.NodeOutput({"samples": latent})
 
-NODE_CLASS_MAPPINGS = {
+
-    "EmptyMochiLatentVideo": EmptyMochiLatentVideo,
+class MochiExtension(ComfyExtension):
-}
+    @override
+    async def get_node_list(self) -> list[type[io.ComfyNode]]:
+        return [
+            EmptyMochiLatentVideo,
+        ]
+
+
+async def comfy_entrypoint() -> MochiExtension:
+    return MochiExtension()

comfy_extras/nodes_perpneg.py

@@ -5,6 +5,9 @@ import comfy.samplers
 import comfy.utils
 import node_helpers
 import math
+from typing_extensions import override
+from comfy_api.latest import ComfyExtension, io
+
 
 def perp_neg(x, noise_pred_pos, noise_pred_neg, noise_pred_nocond, neg_scale, cond_scale):
     pos = noise_pred_pos - noise_pred_nocond
@@ -16,20 +19,27 @@ def perp_neg(x, noise_pred_pos, noise_pred_neg, noise_pred_nocond, neg_scale, co
     return cfg_result
 
 #TODO: This node should be removed, it has been replaced with PerpNegGuider
-class PerpNeg:
+class PerpNeg(io.ComfyNode):
     @classmethod
-    def INPUT_TYPES(s):
+    def define_schema(cls):
-        return {"required": {"model": ("MODEL", ),
+        return io.Schema(
-                             "empty_conditioning": ("CONDITIONING", ),
+            node_id="PerpNeg",
-                             "neg_scale": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step": 0.01}),
+            display_name="Perp-Neg (DEPRECATED by PerpNegGuider)",
-                            }}
+            category="_for_testing",
-    RETURN_TYPES = ("MODEL",)
+            inputs=[
-    FUNCTION = "patch"
+                io.Model.Input("model"),
+                io.Conditioning.Input("empty_conditioning"),
+                io.Float.Input("neg_scale", default=1.0, min=0.0, max=100.0, step=0.01),
+            ],
+            outputs=[
+                io.Model.Output(),
+            ],
+            is_experimental=True,
+            is_deprecated=True,
+        )
 
-    CATEGORY = "_for_testing"
+    @classmethod
-    DEPRECATED = True
+    def execute(cls, model, empty_conditioning, neg_scale) -> io.NodeOutput:
-
-    def patch(self, model, empty_conditioning, neg_scale):
         m = model.clone()
         nocond = comfy.sampler_helpers.convert_cond(empty_conditioning)
 
@@ -50,7 +60,7 @@ class PerpNeg:
 
         m.set_model_sampler_cfg_function(cfg_function)
 
-        return (m, )
+        return io.NodeOutput(m)
 
 
 class Guider_PerpNeg(comfy.samplers.CFGGuider):
@@ -112,35 +122,42 @@ class Guider_PerpNeg(comfy.samplers.CFGGuider):
 
         return cfg_result
 
-class PerpNegGuider:
+class PerpNegGuider(io.ComfyNode):
     @classmethod
-    def INPUT_TYPES(s):
+    def define_schema(cls):
-        return {"required":
+        return io.Schema(
-                    {"model": ("MODEL",),
+            node_id="PerpNegGuider",
-                    "positive": ("CONDITIONING", ),
+            category="_for_testing",
-                    "negative": ("CONDITIONING", ),
+            inputs=[
-                    "empty_conditioning": ("CONDITIONING", ),
+                io.Model.Input("model"),
-                    "cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0, "step":0.1, "round": 0.01}),
+                io.Conditioning.Input("positive"),
-                    "neg_scale": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100.0, "step": 0.01}),
+                io.Conditioning.Input("negative"),
-                     }
+                io.Conditioning.Input("empty_conditioning"),
-                }
+                io.Float.Input("cfg", default=8.0, min=0.0, max=100.0, step=0.1, round=0.01),
+                io.Float.Input("neg_scale", default=1.0, min=0.0, max=100.0, step=0.01),
+            ],
+            outputs=[
+                io.Guider.Output(),
+            ],
+            is_experimental=True,
+        )
 
-    RETURN_TYPES = ("GUIDER",)
+    @classmethod
-
+    def execute(cls, model, positive, negative, empty_conditioning, cfg, neg_scale) -> io.NodeOutput:
-    FUNCTION = "get_guider"
-    CATEGORY = "_for_testing"
-
-    def get_guider(self, model, positive, negative, empty_conditioning, cfg, neg_scale):
         guider = Guider_PerpNeg(model)
         guider.set_conds(positive, negative, empty_conditioning)
         guider.set_cfg(cfg, neg_scale)
-        return (guider,)
+        return io.NodeOutput(guider)
 
-NODE_CLASS_MAPPINGS = {
-    "PerpNeg": PerpNeg,
-    "PerpNegGuider": PerpNegGuider,
-}
 
-NODE_DISPLAY_NAME_MAPPINGS = {
+class PerpNegExtension(ComfyExtension):
-    "PerpNeg": "Perp-Neg (DEPRECATED by PerpNegGuider)",
+    @override
-}
+    async def get_node_list(self) -> list[type[io.ComfyNode]]:
+        return [
+            PerpNeg,
+            PerpNegGuider,
+        ]
+
+
+async def comfy_entrypoint() -> PerpNegExtension:
+    return PerpNegExtension()

middleware/cache_middleware.py

@@ -26,11 +26,12 @@ async def cache_control(
     """Cache control middleware that sets appropriate cache headers based on file type and response status"""
     response: web.Response = await handler(request)
 
-    if (
+    path_filename = request.path.rsplit("/", 1)[-1]
-        request.path.endswith(".js")
+    is_entry_point = path_filename.startswith("index") and path_filename.endswith(
-        or request.path.endswith(".css")
+        ".json"
-        or request.path.endswith("index.json")
+    )
-    ):
+
+    if request.path.endswith(".js") or request.path.endswith(".css") or is_entry_point:
         response.headers.setdefault("Cache-Control", "no-cache")
         return response
 

requirements.txt

@@ -1,5 +1,5 @@
 comfyui-frontend-package==1.26.13
-comfyui-workflow-templates==0.1.88
+comfyui-workflow-templates==0.1.91
 comfyui-embedded-docs==0.2.6
 comfyui_manager==4.0.2
 torch

tests-unit/server_test/test_cache_control.py

@@ -48,6 +48,13 @@ CACHE_SCENARIOS = [
         "expected_cache": "no-cache",
         "should_have_header": True,
     },
+    {
+        "name": "localized_index_json_no_cache",
+        "path": "/templates/index.zh.json",
+        "status": 200,
+        "expected_cache": "no-cache",
+        "should_have_header": True,
+    },
     # Non-matching files
     {
         "name": "html_no_header",