From 966c43ce268341de6e60762ef18e7628f7d311bf Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Tue, 22 Apr 2025 16:59:47 +0800
Subject: [PATCH 01/11] Add OFT/BOFT algorithm in weight adapter (#7725)

---
 comfy/weight_adapter/__init__.py |   4 ++
 comfy/weight_adapter/boft.py     | 115 +++++++++++++++++++++++++++++++
 comfy/weight_adapter/oft.py      |  94 +++++++++++++++++++++++++
 3 files changed, 213 insertions(+)
 create mode 100644 comfy/weight_adapter/boft.py
 create mode 100644 comfy/weight_adapter/oft.py

diff --git a/comfy/weight_adapter/__init__.py b/comfy/weight_adapter/__init__.py
index e6cd805b6..d2a1d0151 100644
--- a/comfy/weight_adapter/__init__.py
+++ b/comfy/weight_adapter/__init__.py
@@ -3,6 +3,8 @@ from .lora import LoRAAdapter
 from .loha import LoHaAdapter
 from .lokr import LoKrAdapter
 from .glora import GLoRAAdapter
+from .oft import OFTAdapter
+from .boft import BOFTAdapter
 
 
 adapters: list[type[WeightAdapterBase]] = [
@@ -10,4 +12,6 @@ adapters: list[type[WeightAdapterBase]] = [
     LoHaAdapter,
     LoKrAdapter,
     GLoRAAdapter,
+    OFTAdapter,
+    BOFTAdapter,
 ]
diff --git a/comfy/weight_adapter/boft.py b/comfy/weight_adapter/boft.py
new file mode 100644
index 000000000..c85adc7ab
--- /dev/null
+++ b/comfy/weight_adapter/boft.py
@@ -0,0 +1,115 @@
+import logging
+from typing import Optional
+
+import torch
+import comfy.model_management
+from .base import WeightAdapterBase, weight_decompose
+
+
+class BOFTAdapter(WeightAdapterBase):
+    name = "boft"
+
+    def __init__(self, loaded_keys, weights):
+        self.loaded_keys = loaded_keys
+        self.weights = weights
+
+    @classmethod
+    def load(
+        cls,
+        x: str,
+        lora: dict[str, torch.Tensor],
+        alpha: float,
+        dora_scale: torch.Tensor,
+        loaded_keys: set[str] = None,
+    ) -> Optional["BOFTAdapter"]:
+        if loaded_keys is None:
+            loaded_keys = set()
+        blocks_name = "{}.boft_blocks".format(x)
+        rescale_name = "{}.rescale".format(x)
+
+        blocks = None
+        if blocks_name in lora.keys():
+            blocks = lora[blocks_name]
+            if blocks.ndim == 4:
+                loaded_keys.add(blocks_name)
+
+        rescale = None
+        if rescale_name in lora.keys():
+            rescale = lora[rescale_name]
+            loaded_keys.add(rescale_name)
+
+        if blocks is not None:
+            weights = (blocks, rescale, alpha, dora_scale)
+            return cls(loaded_keys, weights)
+        else:
+            return None
+
+    def calculate_weight(
+        self,
+        weight,
+        key,
+        strength,
+        strength_model,
+        offset,
+        function,
+        intermediate_dtype=torch.float32,
+        original_weight=None,
+    ):
+        v = self.weights
+        blocks = v[0]
+        rescale = v[1]
+        alpha = v[2]
+        dora_scale = v[3]
+
+        blocks = comfy.model_management.cast_to_device(blocks, weight.device, intermediate_dtype)
+        if rescale is not None:
+            rescale = comfy.model_management.cast_to_device(rescale, weight.device, intermediate_dtype)
+
+        boft_m, block_num, boft_b, *_ = blocks.shape
+
+        try:
+            # Get r
+            I = torch.eye(boft_b, device=blocks.device, dtype=blocks.dtype)
+            # for Q = -Q^T
+            q = blocks - blocks.transpose(1, 2)
+            normed_q = q
+            if alpha > 0: # alpha in boft/bboft is for constraint
+                q_norm = torch.norm(q) + 1e-8
+                if q_norm > alpha:
+                    normed_q = q * alpha / q_norm
+            # use float() to prevent unsupported type in .inverse()
+            r = (I + normed_q) @ (I - normed_q).float().inverse()
+            r = r.to(original_weight)
+
+            inp = org = original_weight
+
+            r_b = boft_b//2
+            for i in range(boft_m):
+                bi = r[i]
+                g = 2
+                k = 2**i * r_b
+                if strength != 1:
+                    bi = bi * strength + (1-strength) * I
+                inp = (
+                    inp.unflatten(-1, (-1, g, k))
+                    .transpose(-2, -1)
+                    .flatten(-3)
+                    .unflatten(-1, (-1, boft_b))
+                )
+                inp = torch.einsum("b n m, b n ... -> b m ...", inp, bi)
+                inp = (
+                    inp.flatten(-2).unflatten(-1, (-1, k, g)).transpose(-2, -1).flatten(-3)
+                )
+
+            if rescale is not None:
+                inp = inp * rescale
+
+            lora_diff = inp - org
+            lora_diff = comfy.model_management.cast_to_device(lora_diff, weight.device, intermediate_dtype)
+            if dora_scale is not None:
+                weight = weight_decompose(dora_scale, weight, lora_diff, alpha, strength, intermediate_dtype, function)
+            else:
+                weight += function(((strength * alpha) * lora_diff).type(weight.dtype))
+        except Exception as e:
+            logging.error("ERROR {} {} {}".format(self.name, key, e))
+        return weight
diff --git a/comfy/weight_adapter/oft.py b/comfy/weight_adapter/oft.py
new file mode 100644
index 000000000..0ea229b79
--- /dev/null
+++ b/comfy/weight_adapter/oft.py
@@ -0,0 +1,94 @@
+import logging
+from typing import Optional
+
+import torch
+import comfy.model_management
+from .base import WeightAdapterBase, weight_decompose
+
+
+class OFTAdapter(WeightAdapterBase):
+    name = "oft"
+
+    def __init__(self, loaded_keys, weights):
+        self.loaded_keys = loaded_keys
+        self.weights = weights
+
+    @classmethod
+    def load(
+        cls,
+        x: str,
+        lora: dict[str, torch.Tensor],
+        alpha: float,
+        dora_scale: torch.Tensor,
+        loaded_keys: set[str] = None,
+    ) -> Optional["OFTAdapter"]:
+        if loaded_keys is None:
+            loaded_keys = set()
+        blocks_name = "{}.oft_blocks".format(x)
+        rescale_name = "{}.rescale".format(x)
+
+        blocks = None
+        if blocks_name in lora.keys():
+            blocks = lora[blocks_name]
+            if blocks.ndim == 3:
+                loaded_keys.add(blocks_name)
+
+        rescale = None
+        if rescale_name in lora.keys():
+            rescale = lora[rescale_name]
+            loaded_keys.add(rescale_name)
+
+        if blocks is not None:
+            weights = (blocks, rescale, alpha, dora_scale)
+            return cls(loaded_keys, weights)
+        else:
+            return None
+
+    def calculate_weight(
+        self,
+        weight,
+        key,
+        strength,
+        strength_model,
+        offset,
+        function,
+        intermediate_dtype=torch.float32,
+        original_weight=None,
+    ):
+        v = self.weights
+        blocks = v[0]
+        rescale = v[1]
+        alpha = v[2]
+        dora_scale = v[3]
+
+        blocks = comfy.model_management.cast_to_device(blocks, weight.device, intermediate_dtype)
+        if rescale is not None:
+            rescale = comfy.model_management.cast_to_device(rescale, weight.device, intermediate_dtype)
+
+        block_num, block_size, *_ = blocks.shape
+
+        try:
+            # Get r
+            I = torch.eye(block_size, device=blocks.device, dtype=blocks.dtype)
+            # for Q = -Q^T
+            q = blocks - blocks.transpose(1, 2)
+            normed_q = q
+            if alpha > 0: # alpha in oft/boft is for constraint
+                q_norm = torch.norm(q) + 1e-8
+                if q_norm > alpha:
+                    normed_q = q * alpha / q_norm
+            # use float() to prevent unsupported type in .inverse()
+            r = (I + normed_q) @ (I - normed_q).float().inverse()
+            r = r.to(original_weight)
+            lora_diff = torch.einsum(
+                "k n m, k n ... -> k m ...",
+                (r * strength) - strength * I,
+                original_weight,
+            )
+            if dora_scale is not None:
+                weight = weight_decompose(dora_scale, weight, lora_diff, alpha, strength, intermediate_dtype, function)
+            else:
+                weight += function(((strength * alpha) * lora_diff).type(weight.dtype))
+        except Exception as e:
+            logging.error("ERROR {} {} {}".format(self.name, key, e))
+        return weight

From 454a635c1b8aae9f635e7fb4f696bf7ac2e1fd1f Mon Sep 17 00:00:00 2001
From: Terry Jia <terryjia88@gmail.com>
Date: Tue, 22 Apr 2025 05:00:28 -0400
Subject: [PATCH 02/11] upstream MaskPreview from ComfyUI_essentials (#7719)

---
 comfy_extras/nodes_mask.py | 28 ++++++++++++++++++++++++++++
 1 file changed, 28 insertions(+)

diff --git a/comfy_extras/nodes_mask.py b/comfy_extras/nodes_mask.py
index 13d2b4bab..99b264a32 100644
--- a/comfy_extras/nodes_mask.py
+++ b/comfy_extras/nodes_mask.py
@@ -3,7 +3,10 @@ import scipy.ndimage
 import torch
 import comfy.utils
 import node_helpers
+import folder_paths
+import random
 
+import nodes
 from nodes import MAX_RESOLUTION
 
 def composite(destination, source, x, y, mask = None, multiplier = 8, resize_source = False):
@@ -362,6 +365,30 @@ class ThresholdMask:
         mask = (mask > value).float()
         return (mask,)
 
+# Mask Preview - original implement from
+# https://github.com/cubiq/ComfyUI_essentials/blob/9d9f4bedfc9f0321c19faf71855e228c93bd0dc9/mask.py#L81
+# upstream requested in https://github.com/Kosinkadink/rfcs/blob/main/rfcs/0000-corenodes.md#preview-nodes
+class MaskPreview(nodes.SaveImage):
+    def __init__(self):
+        self.output_dir = folder_paths.get_temp_directory()
+        self.type = "temp"
+        self.prefix_append = "_temp_" + ''.join(random.choice("abcdefghijklmnopqrstupvxyz") for x in range(5))
+        self.compress_level = 4
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {"mask": ("MASK",), },
+            "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
+        }
+
+    FUNCTION = "execute"
+    CATEGORY = "mask"
+
+    def execute(self, mask, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None):
+        preview = mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1])).movedim(1, -1).expand(-1, -1, -1, 3)
+        return self.save_images(preview, filename_prefix, prompt, extra_pnginfo)
+
 
 NODE_CLASS_MAPPINGS = {
     "LatentCompositeMasked": LatentCompositeMasked,
@@ -376,6 +403,7 @@ NODE_CLASS_MAPPINGS = {
     "FeatherMask": FeatherMask,
     "GrowMask": GrowMask,
     "ThresholdMask": ThresholdMask,
+    "MaskPreview": MaskPreview
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {

From a8f63c0d5b40b4ed12faa1376e973b0e790b1c0d Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Tue, 22 Apr 2025 17:01:27 +0800
Subject: [PATCH 03/11] Support dora_scale on both axis (#7727)

---
 comfy/weight_adapter/base.py | 24 +++++++++++++++++-------
 1 file changed, 17 insertions(+), 7 deletions(-)

diff --git a/comfy/weight_adapter/base.py b/comfy/weight_adapter/base.py
index 54af3babe..29873519d 100644
--- a/comfy/weight_adapter/base.py
+++ b/comfy/weight_adapter/base.py
@@ -43,13 +43,23 @@ def weight_decompose(dora_scale, weight, lora_diff, alpha, strength, intermediat
     dora_scale = comfy.model_management.cast_to_device(dora_scale, weight.device, intermediate_dtype)
     lora_diff *= alpha
     weight_calc = weight + function(lora_diff).type(weight.dtype)
-    weight_norm = (
-        weight_calc.transpose(0, 1)
-        .reshape(weight_calc.shape[1], -1)
-        .norm(dim=1, keepdim=True)
-        .reshape(weight_calc.shape[1], *[1] * (weight_calc.dim() - 1))
-        .transpose(0, 1)
-    )
+
+    wd_on_output_axis = dora_scale.shape[0] == weight_calc.shape[0]
+    if wd_on_output_axis:
+        weight_norm = (
+            weight.reshape(weight.shape[0], -1)
+            .norm(dim=1, keepdim=True)
+            .reshape(weight.shape[0], *[1] * (weight.dim() - 1))
+        )
+    else:
+        weight_norm = (
+            weight_calc.transpose(0, 1)
+            .reshape(weight_calc.shape[1], -1)
+            .norm(dim=1, keepdim=True)
+            .reshape(weight_calc.shape[1], *[1] * (weight_calc.dim() - 1))
+            .transpose(0, 1)
+        )
+    weight_norm = weight_norm + torch.finfo(weight.dtype).eps
 
     weight_calc *= (dora_scale / weight_norm).type(weight.dtype)
     if strength != 1.0:

From 2d6805ce57cede78acb6515112439c5092c7b257 Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Tue, 22 Apr 2025 03:17:38 -0700
Subject: [PATCH 04/11] Add option for using fp8_e8m0fnu for model weights.
 (#7733)

Seems to break every model I have tried but worth testing?
---
 comfy/cli_args.py         | 1 +
 comfy/model_management.py | 2 ++
 2 files changed, 3 insertions(+)

diff --git a/comfy/cli_args.py b/comfy/cli_args.py
index 81f29f098..1b971be3c 100644
--- a/comfy/cli_args.py
+++ b/comfy/cli_args.py
@@ -66,6 +66,7 @@ fpunet_group.add_argument("--bf16-unet", action="store_true", help="Run the diff
 fpunet_group.add_argument("--fp16-unet", action="store_true", help="Run the diffusion model in fp16")
 fpunet_group.add_argument("--fp8_e4m3fn-unet", action="store_true", help="Store unet weights in fp8_e4m3fn.")
 fpunet_group.add_argument("--fp8_e5m2-unet", action="store_true", help="Store unet weights in fp8_e5m2.")
+fpunet_group.add_argument("--fp8_e8m0fnu-unet", action="store_true", help="Store unet weights in fp8_e8m0fnu.")
 
 fpvae_group = parser.add_mutually_exclusive_group()
 fpvae_group.add_argument("--fp16-vae", action="store_true", help="Run the VAE in fp16, might cause black images.")
diff --git a/comfy/model_management.py b/comfy/model_management.py
index 19e6c8dff..43e402243 100644
--- a/comfy/model_management.py
+++ b/comfy/model_management.py
@@ -725,6 +725,8 @@ def unet_dtype(device=None, model_params=0, supported_dtypes=[torch.float16, tor
         return torch.float8_e4m3fn
     if args.fp8_e5m2_unet:
         return torch.float8_e5m2
+    if args.fp8_e8m0fnu_unet:
+        return torch.float8_e8m0fnu
 
     fp8_dtype = None
     if weight_dtype in FLOAT8_TYPES:

From 92cdc692f47188e6e4c48c5666ac802281240a37 Mon Sep 17 00:00:00 2001
From: Alex Butler <alexheretic@gmail.com>
Date: Tue, 22 Apr 2025 22:57:17 +0100
Subject: [PATCH 05/11] Replace aom-av1 with svt-av1 for saving webm videos,
 use preset 6 + yuv420p10le pixel format (#7736)

* Add support for saving svt-av1 webm videos & yuv420p10le pixel format

* Replace aom-av1 with svt-av1

Use yuv420p10le for av1
---
 comfy_extras/nodes_video.py | 6 ++++--
 requirements.txt            | 2 +-
 2 files changed, 5 insertions(+), 3 deletions(-)

diff --git a/comfy_extras/nodes_video.py b/comfy_extras/nodes_video.py
index 97ca513d8..a9e244ebe 100644
--- a/comfy_extras/nodes_video.py
+++ b/comfy_extras/nodes_video.py
@@ -50,13 +50,15 @@ class SaveWEBM:
             for x in extra_pnginfo:
                 container.metadata[x] = json.dumps(extra_pnginfo[x])
 
-        codec_map = {"vp9": "libvpx-vp9", "av1": "libaom-av1"}
+        codec_map = {"vp9": "libvpx-vp9", "av1": "libsvtav1"}
         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.pix_fmt = "yuv420p10le" if codec == "av1" else "yuv420p"
         stream.bit_rate = 0
         stream.options = {'crf': str(crf)}
+        if codec == "av1":
+            stream.options["preset"] = "6"
 
         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")
diff --git a/requirements.txt b/requirements.txt
index 5c3a854ce..90eb04612 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -22,4 +22,4 @@ psutil
 kornia>=0.7.1
 spandrel
 soundfile
-av
+av>=14.1.0

From 0738e4ea5dd5ecac34d8cf61bb381ea6d159394b Mon Sep 17 00:00:00 2001
From: Robin Huang <robin.j.huang@gmail.com>
Date: Tue, 22 Apr 2025 23:18:08 -0700
Subject: [PATCH 06/11] [API nodes] Add backbone for supporting api nodes in
 ComfyUI (#7745)

* Add Ideogram generate node.

* Add staging api.

* COMFY_API_NODE_NAME node property

* switch to boolean flag and use original node name for id

* add optional to type

* Add API_NODE and common error for missing auth token (#5)

* Add Minimax Video Generation + Async Task queue polling example (#6)

* [Minimax] Show video preview and embed workflow in ouput (#7)

* [API Nodes] Send empty request body instead of empty dictionary. (#8)

* Fixed: removed function from rebase.

* Add pydantic.

* Remove uv.lock

* Remove polling operations.

* Update stubs workflow.

* Remove polling comments.

* Update stubs.

* Use pydantic v2.

* Use pydantic v2.

* Add basic OpenAITextToImage node

* Add.

* convert image to tensor.

* Improve types.

* Ruff.

* Push tests.

* Handle multi-form data.

- Don't set content-type for multi-part/form
- Use data field instead of JSON

* Change to api.comfy.org

* Handle error code 409.

* Remove nodes.

---------

Co-authored-by: bymyself <cbyrne@comfy.org>
Co-authored-by: Yoland Y <4950057+yoland68@users.noreply.github.com>
---
 comfy/comfy_types/node_typing.py |   4 +-
 comfy_api_nodes/__init__.py      |   0
 comfy_api_nodes/apis/client.py   | 337 +++++++++++++++++++++++++++++++
 requirements.txt                 |   1 +
 server.py                        |   3 +
 5 files changed, 344 insertions(+), 1 deletion(-)
 create mode 100644 comfy_api_nodes/__init__.py
 create mode 100644 comfy_api_nodes/apis/client.py

diff --git a/comfy/comfy_types/node_typing.py b/comfy/comfy_types/node_typing.py
index a348791a9..0bdda032e 100644
--- a/comfy/comfy_types/node_typing.py
+++ b/comfy/comfy_types/node_typing.py
@@ -1,7 +1,7 @@
 """Comfy-specific type hinting"""
 
 from __future__ import annotations
-from typing import Literal, TypedDict
+from typing import Literal, TypedDict, Optional
 from typing_extensions import NotRequired
 from abc import ABC, abstractmethod
 from enum import Enum
@@ -229,6 +229,8 @@ 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."""
+    API_NODE: Optional[bool]
+    """Flags a node as an API node."""
 
     @classmethod
     @abstractmethod
diff --git a/comfy_api_nodes/__init__.py b/comfy_api_nodes/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/comfy_api_nodes/apis/client.py b/comfy_api_nodes/apis/client.py
new file mode 100644
index 000000000..cd81d5a1d
--- /dev/null
+++ b/comfy_api_nodes/apis/client.py
@@ -0,0 +1,337 @@
+import logging
+
+"""
+API Client Framework for api.comfy.org.
+
+This module provides a flexible framework for making API requests from ComfyUI nodes.
+It supports both synchronous and asynchronous API operations with proper type validation.
+
+Key Components:
+--------------
+1. ApiClient - Handles HTTP requests with authentication and error handling
+2. ApiEndpoint - Defines a single HTTP endpoint with its request/response models
+3. ApiOperation - Executes a single synchronous API operation
+
+Usage Examples:
+--------------
+
+# Example 1: Synchronous API Operation
+# ------------------------------------
+# For a simple API call that returns the result immediately:
+
+# 1. Create the API client
+api_client = ApiClient(
+    base_url="https://api.example.com",
+    api_key="your_api_key_here",
+    timeout=30.0,
+    verify_ssl=True
+)
+
+# 2. Define the endpoint
+user_info_endpoint = ApiEndpoint(
+    path="/v1/users/me",
+    method=HttpMethod.GET,
+    request_model=EmptyRequest,  # No request body needed
+    response_model=UserProfile,   # Pydantic model for the response
+    query_params=None
+)
+
+# 3. Create the request object
+request = EmptyRequest()
+
+# 4. Create and execute the operation
+operation = ApiOperation(
+    endpoint=user_info_endpoint,
+    request=request
+)
+user_profile = operation.execute(client=api_client)  # Returns immediately with the result
+
+"""
+
+from typing import (
+    Dict,
+    Type,
+    Optional,
+    Any,
+    TypeVar,
+    Generic,
+)
+from pydantic import BaseModel
+from enum import Enum
+import json
+import requests
+from urllib.parse import urljoin
+
+T = TypeVar("T", bound=BaseModel)
+R = TypeVar("R", bound=BaseModel)
+
+class EmptyRequest(BaseModel):
+    """Base class for empty request bodies.
+    For GET requests, fields will be sent as query parameters."""
+
+    pass
+
+
+class HttpMethod(str, Enum):
+    GET = "GET"
+    POST = "POST"
+    PUT = "PUT"
+    DELETE = "DELETE"
+    PATCH = "PATCH"
+
+
+class ApiClient:
+    """
+    Client for making HTTP requests to an API with authentication and error handling.
+    """
+
+    def __init__(
+        self,
+        base_url: str,
+        api_key: Optional[str] = None,
+        timeout: float = 30.0,
+        verify_ssl: bool = True,
+    ):
+        self.base_url = base_url
+        self.api_key = api_key
+        self.timeout = timeout
+        self.verify_ssl = verify_ssl
+
+    def get_headers(self) -> Dict[str, str]:
+        """Get headers for API requests, including authentication if available"""
+        headers = {"Content-Type": "application/json", "Accept": "application/json"}
+
+        if self.api_key:
+            headers["Authorization"] = f"Bearer {self.api_key}"
+
+        return headers
+
+    def request(
+        self,
+        method: str,
+        path: str,
+        params: Optional[Dict[str, Any]] = None,
+        json: Optional[Dict[str, Any]] = None,
+        files: Optional[Dict[str, Any]] = None,
+        headers: Optional[Dict[str, str]] = None,
+    ) -> Dict[str, Any]:
+        """
+        Make an HTTP request to the API
+
+        Args:
+            method: HTTP method (GET, POST, etc.)
+            path: API endpoint path (will be joined with base_url)
+            params: Query parameters
+            json: JSON body data
+            files: Files to upload
+            headers: Additional headers
+
+        Returns:
+            Parsed JSON response
+
+        Raises:
+            requests.RequestException: If the request fails
+        """
+        url = urljoin(self.base_url, path)
+        self.check_auth_token(self.api_key)
+        # Combine default headers with any provided headers
+        request_headers = self.get_headers()
+        if headers:
+            request_headers.update(headers)
+
+        # Let requests handle the content type when files are present.
+        if files:
+            del request_headers["Content-Type"]
+
+        logging.debug(f"[DEBUG] Request Headers: {request_headers}")
+        logging.debug(f"[DEBUG] Files: {files}")
+        logging.debug(f"[DEBUG] Params: {params}")
+        logging.debug(f"[DEBUG] Json: {json}")
+
+        try:
+            # If files are present, use data parameter instead of json
+            if files:
+                form_data = {}
+                if json:
+                    form_data.update(json)
+                response = requests.request(
+                    method=method,
+                    url=url,
+                    params=params,
+                    data=form_data,  # Use data instead of json
+                    files=files,
+                    headers=request_headers,
+                    timeout=self.timeout,
+                    verify=self.verify_ssl,
+                )
+            else:
+                response = requests.request(
+                    method=method,
+                    url=url,
+                    params=params,
+                    json=json,
+                    headers=request_headers,
+                    timeout=self.timeout,
+                    verify=self.verify_ssl,
+                )
+
+            # Raise exception for error status codes
+            response.raise_for_status()
+        except requests.ConnectionError:
+            raise Exception(
+                f"Unable to connect to the API server at {self.base_url}. Please check your internet connection or verify the service is available."
+            )
+
+        except requests.Timeout:
+            raise Exception(
+                f"Request timed out after {self.timeout} seconds. The server might be experiencing high load or the operation is taking longer than expected."
+            )
+
+        except requests.HTTPError as e:
+            status_code = e.response.status_code if hasattr(e, "response") else None
+            error_message = f"HTTP Error: {str(e)}"
+
+            # Try to extract detailed error message from JSON response
+            try:
+                if hasattr(e, "response") and e.response.content:
+                    error_json = e.response.json()
+                    if "error" in error_json and "message" in error_json["error"]:
+                        error_message = f"API Error: {error_json['error']['message']}"
+                        if "type" in error_json["error"]:
+                            error_message += f" (Type: {error_json['error']['type']})"
+                    else:
+                        error_message = f"API Error: {error_json}"
+            except Exception as json_error:
+                # If we can't parse the JSON, fall back to the original error message
+                logging.debug(f"[DEBUG] Failed to parse error response: {str(json_error)}")
+
+            logging.debug(f"[DEBUG] API Error: {error_message} (Status: {status_code})")
+            if hasattr(e, "response") and e.response.content:
+                logging.debug(f"[DEBUG] Response content: {e.response.content}")
+            if status_code == 401:
+                error_message = "Unauthorized: Please login first to use this node."
+            if status_code == 402:
+                error_message = "Payment Required: Please add credits to your account to use this node."
+            if status_code == 409:
+                error_message = "There is a problem with your account. Please contact support@comfy.org. "
+            if status_code == 429:
+                error_message = "Rate Limit Exceeded: Please try again later."
+            raise Exception(error_message)
+
+        # Parse and return JSON response
+        if response.content:
+            return response.json()
+        return {}
+
+    def check_auth_token(self, auth_token):
+        """Verify that an auth token is present."""
+        if auth_token is None:
+            raise Exception("Please login first to use this node.")
+        return auth_token
+
+
+class ApiEndpoint(Generic[T, R]):
+    """Defines an API endpoint with its request and response types"""
+
+    def __init__(
+        self,
+        path: str,
+        method: HttpMethod,
+        request_model: Type[T],
+        response_model: Type[R],
+        query_params: Optional[Dict[str, Any]] = None,
+    ):
+        """Initialize an API endpoint definition.
+
+        Args:
+            path: The URL path for this endpoint, can include placeholders like {id}
+            method: The HTTP method to use (GET, POST, etc.)
+            request_model: Pydantic model class that defines the structure and validation rules for API requests to this endpoint
+            response_model: Pydantic model class that defines the structure and validation rules for API responses from this endpoint
+            query_params: Optional dictionary of query parameters to include in the request
+        """
+        self.path = path
+        self.method = method
+        self.request_model = request_model
+        self.response_model = response_model
+        self.query_params = query_params or {}
+
+
+class SynchronousOperation(Generic[T, R]):
+    """
+    Represents a single synchronous API operation.
+    """
+
+    def __init__(
+        self,
+        endpoint: ApiEndpoint[T, R],
+        request: T,
+        files: Optional[Dict[str, Any]] = None,
+        api_base: str = "https://api.comfy.org",
+        auth_token: Optional[str] = None,
+        timeout: float = 60.0,
+        verify_ssl: bool = True,
+    ):
+        self.endpoint = endpoint
+        self.request = request
+        self.response = None
+        self.error = None
+        self.api_base = api_base
+        self.auth_token = auth_token
+        self.timeout = timeout
+        self.verify_ssl = verify_ssl
+        self.files = files
+    def execute(self, client: Optional[ApiClient] = None) -> R:
+        """Execute the API operation using the provided client or create one"""
+        try:
+            # Create client if not provided
+            if client is None:
+                if self.api_base is None:
+                    raise ValueError("Either client or api_base must be provided")
+                client = ApiClient(
+                    base_url=self.api_base,
+                    api_key=self.auth_token,
+                    timeout=self.timeout,
+                    verify_ssl=self.verify_ssl,
+                )
+
+            # Convert request model to dict, but use None for EmptyRequest
+            request_dict = None if isinstance(self.request, EmptyRequest) else self.request.model_dump(exclude_none=True)
+
+            # Debug log for request
+            logging.debug(f"[DEBUG] API Request: {self.endpoint.method.value} {self.endpoint.path}")
+            logging.debug(f"[DEBUG] Request Data: {json.dumps(request_dict, indent=2)}")
+            logging.debug(f"[DEBUG] Query Params: {self.endpoint.query_params}")
+
+            # Make the request
+            resp = client.request(
+                method=self.endpoint.method.value,
+                path=self.endpoint.path,
+                json=request_dict,
+                params=self.endpoint.query_params,
+                files=self.files,
+            )
+
+            # Debug log for response
+            logging.debug("=" * 50)
+            logging.debug("[DEBUG] RESPONSE DETAILS:")
+            logging.debug("[DEBUG] Status Code: 200 (Success)")
+            logging.debug(f"[DEBUG] Response Body: {json.dumps(resp, indent=2)}")
+            logging.debug("=" * 50)
+
+            # Parse and return the response
+            return self._parse_response(resp)
+
+        except Exception as e:
+            logging.debug(f"[DEBUG] API Exception: {str(e)}")
+            raise Exception(str(e))
+
+    def _parse_response(self, resp):
+        """Parse response data - can be overridden by subclasses"""
+        # The response is already the complete object, don't extract just the "data" field
+        # as that would lose the outer structure (created timestamp, etc.)
+
+        # Parse response using the provided model
+        self.response = self.endpoint.response_model.model_validate(resp)
+        logging.debug(f"[DEBUG] Parsed Response: {self.response}")
+        return self.response
diff --git a/requirements.txt b/requirements.txt
index 90eb04612..f8ad908ca 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -23,3 +23,4 @@ kornia>=0.7.1
 spandrel
 soundfile
 av>=14.1.0
+pydantic~=2.0
diff --git a/server.py b/server.py
index 0cc97b248..f64ec27d4 100644
--- a/server.py
+++ b/server.py
@@ -580,6 +580,9 @@ class PromptServer():
                 info['deprecated'] = True
             if getattr(obj_class, "EXPERIMENTAL", False):
                 info['experimental'] = True
+
+            if hasattr(obj_class, 'API_NODE'):
+                info['api_node'] = obj_class.API_NODE
             return info
 
         @routes.get("/object_info")

From 552615235dc043f0b07d11e1ff2e6571e6f90d4d Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Wed, 23 Apr 2025 01:12:52 -0700
Subject: [PATCH 07/11] Fix for dino lowvram. (#7748)

---
 comfy/image_encoders/dino2.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/comfy/image_encoders/dino2.py b/comfy/image_encoders/dino2.py
index 130ed6fd7..976f98c65 100644
--- a/comfy/image_encoders/dino2.py
+++ b/comfy/image_encoders/dino2.py
@@ -116,7 +116,7 @@ class Dino2Embeddings(torch.nn.Module):
     def forward(self, pixel_values):
         x = self.patch_embeddings(pixel_values)
         # TODO: mask_token?
-        x = torch.cat((self.cls_token.expand(x.shape[0], -1, -1), x), dim=1)
+        x = torch.cat((self.cls_token.to(device=x.device, dtype=x.dtype).expand(x.shape[0], -1, -1), x), dim=1)
         x = x + comfy.model_management.cast_to_device(self.position_embeddings, x.device, x.dtype)
         return x
 

From 21a11ef817e3749047c6b548231210ff84fe331d Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Wed, 23 Apr 2025 02:12:59 -0700
Subject: [PATCH 08/11] Pytorch stable 2.7 is out and support cu128 (#7749)

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index cf6df7e55..62800bb4f 100644
--- a/README.md
+++ b/README.md
@@ -216,9 +216,9 @@ Additional discussion and help can be found [here](https://github.com/comfyanony
 
 Nvidia users should install stable pytorch using this command:
 
-```pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu126```
+```pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu128```
 
-This is the command to install pytorch nightly instead which supports the new blackwell 50xx series GPUs and might have performance improvements.
+This is the command to install pytorch nightly instead which might have performance improvements.
 
 ```pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128```
 

From 7eaff81be106fa5e1479cfa69f5fd06265611f2e Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Wed, 23 Apr 2025 02:28:24 -0700
Subject: [PATCH 09/11] fp16 accumulation can now be enabled on the stable
 package. (#7750)

---
 .../run_nvidia_gpu_fast_fp16_accumulation.bat                     | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 rename .ci/{windows_nightly_base_files => windows_base_files}/run_nvidia_gpu_fast_fp16_accumulation.bat (100%)

diff --git a/.ci/windows_nightly_base_files/run_nvidia_gpu_fast_fp16_accumulation.bat b/.ci/windows_base_files/run_nvidia_gpu_fast_fp16_accumulation.bat
similarity index 100%
rename from .ci/windows_nightly_base_files/run_nvidia_gpu_fast_fp16_accumulation.bat
rename to .ci/windows_base_files/run_nvidia_gpu_fast_fp16_accumulation.bat

From 3eaad0590e51bc186b1d533fef906e3f296cdd42 Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Wed, 23 Apr 2025 02:47:09 -0700
Subject: [PATCH 10/11] Lower size of release package. (#7751)

---
 .github/workflows/windows_release_package.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/windows_release_package.yml b/.github/workflows/windows_release_package.yml
index 416544f71..8300c2faf 100644
--- a/.github/workflows/windows_release_package.yml
+++ b/.github/workflows/windows_release_package.yml
@@ -50,7 +50,7 @@ jobs:
 
         - uses: actions/checkout@v4
           with:
-            fetch-depth: 0
+            fetch-depth: 150
             persist-credentials: false
         - shell: bash
           run: |
@@ -82,7 +82,7 @@ jobs:
 
             cd ..
 
-            "C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma2 -mx=8 -mfb=64 -md=32m -ms=on -mf=BCJ2 ComfyUI_windows_portable.7z ComfyUI_windows_portable
+            "C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma2 -mx=9 -mfb=128 -md=256m -ms=on -mf=BCJ2 ComfyUI_windows_portable.7z ComfyUI_windows_portable
             mv ComfyUI_windows_portable.7z ComfyUI/new_ComfyUI_windows_portable_nvidia_cu${{ inputs.cu }}_or_cpu.7z
 
             cd ComfyUI_windows_portable

From 154f2911aaf0333db576a237c6098ed0a8160a7d Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Wed, 23 Apr 2025 03:33:09 -0700
Subject: [PATCH 11/11] Lower size of release package more. (#7754)

---
 .github/workflows/stable-release.yml                  | 6 +++---
 .github/workflows/windows_release_nightly_pytorch.yml | 2 +-
 .github/workflows/windows_release_package.yml         | 4 ++--
 3 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/.github/workflows/stable-release.yml b/.github/workflows/stable-release.yml
index f7d30a9a4..40df7ab88 100644
--- a/.github/workflows/stable-release.yml
+++ b/.github/workflows/stable-release.yml
@@ -36,7 +36,7 @@ jobs:
       - uses: actions/checkout@v4
         with:
           ref: ${{ inputs.git_tag }}
-          fetch-depth: 0
+          fetch-depth: 150
           persist-credentials: false
       - uses: actions/cache/restore@v4
         id: cache
@@ -70,7 +70,7 @@ jobs:
             cd ..
 
           git clone --depth 1 https://github.com/comfyanonymous/taesd
-          cp taesd/*.pth ./ComfyUI_copy/models/vae_approx/
+          cp taesd/*.safetensors ./ComfyUI_copy/models/vae_approx/
 
           mkdir ComfyUI_windows_portable
           mv python_embeded ComfyUI_windows_portable
@@ -85,7 +85,7 @@ jobs:
 
           cd ..
 
-          "C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma2 -mx=8 -mfb=64 -md=32m -ms=on -mf=BCJ2 ComfyUI_windows_portable.7z ComfyUI_windows_portable
+          "C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma2 -mx=9 -mfb=128 -md=512m -ms=on -mf=BCJ2 ComfyUI_windows_portable.7z ComfyUI_windows_portable
           mv ComfyUI_windows_portable.7z ComfyUI/ComfyUI_windows_portable_nvidia.7z
 
           cd ComfyUI_windows_portable
diff --git a/.github/workflows/windows_release_nightly_pytorch.yml b/.github/workflows/windows_release_nightly_pytorch.yml
index 24599249a..eb5ed9c91 100644
--- a/.github/workflows/windows_release_nightly_pytorch.yml
+++ b/.github/workflows/windows_release_nightly_pytorch.yml
@@ -56,7 +56,7 @@ jobs:
             cd ..
 
             git clone --depth 1 https://github.com/comfyanonymous/taesd
-            cp taesd/*.pth ./ComfyUI_copy/models/vae_approx/
+            cp taesd/*.safetensors ./ComfyUI_copy/models/vae_approx/
 
             mkdir ComfyUI_windows_portable_nightly_pytorch
             mv python_embeded ComfyUI_windows_portable_nightly_pytorch
diff --git a/.github/workflows/windows_release_package.yml b/.github/workflows/windows_release_package.yml
index 8300c2faf..dc79b1f4a 100644
--- a/.github/workflows/windows_release_package.yml
+++ b/.github/workflows/windows_release_package.yml
@@ -67,7 +67,7 @@ jobs:
             cd ..
 
             git clone --depth 1 https://github.com/comfyanonymous/taesd
-            cp taesd/*.pth ./ComfyUI_copy/models/vae_approx/
+            cp taesd/*.safetensors ./ComfyUI_copy/models/vae_approx/
 
             mkdir ComfyUI_windows_portable
             mv python_embeded ComfyUI_windows_portable
@@ -82,7 +82,7 @@ jobs:
 
             cd ..
 
-            "C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma2 -mx=9 -mfb=128 -md=256m -ms=on -mf=BCJ2 ComfyUI_windows_portable.7z ComfyUI_windows_portable
+            "C:\Program Files\7-Zip\7z.exe" a -t7z -m0=lzma2 -mx=9 -mfb=128 -md=512m -ms=on -mf=BCJ2 ComfyUI_windows_portable.7z ComfyUI_windows_portable
             mv ComfyUI_windows_portable.7z ComfyUI/new_ComfyUI_windows_portable_nvidia_cu${{ inputs.cu }}_or_cpu.7z
 
             cd ComfyUI_windows_portable