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Author SHA1 Message Date
be7bf497d6 fix: improve error message when node type is missing
- Change error type from 'invalid_prompt' to 'missing_node_type' for frontend detection
- Add extra_info with node_id, class_type, and node_title (from _meta.title)
- Improve user-facing message: 'Node X not found. The custom node may not be installed.'

Fixes COM-12528

Amp-Thread-ID: https://ampcode.com/threads/T-019c0df1-aa57-72e0-8193-46aa24b5a327
Co-authored-by: Amp <amp@ampcode.com>
2026-01-30 13:40:04 -08:00
21 changed files with 175 additions and 1017 deletions

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@ -29,7 +29,7 @@ on:
description: 'python patch version'
required: true
type: string
default: "11"
default: "9"
# push:
# branches:
# - master

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@ -13,7 +13,6 @@ from torchvision import transforms
import comfy.patcher_extension
from comfy.ldm.modules.attention import optimized_attention
import comfy.ldm.common_dit
def apply_rotary_pos_emb(
t: torch.Tensor,
@ -836,8 +835,6 @@ class MiniTrainDIT(nn.Module):
padding_mask: Optional[torch.Tensor] = None,
**kwargs,
):
orig_shape = list(x.shape)
x = comfy.ldm.common_dit.pad_to_patch_size(x, (self.patch_temporal, self.patch_spatial, self.patch_spatial))
x_B_C_T_H_W = x
timesteps_B_T = timesteps
crossattn_emb = context
@ -885,5 +882,5 @@ class MiniTrainDIT(nn.Module):
)
x_B_T_H_W_O = self.final_layer(x_B_T_H_W_D, t_embedding_B_T_D, adaln_lora_B_T_3D=adaln_lora_B_T_3D)
x_B_C_Tt_Hp_Wp = self.unpatchify(x_B_T_H_W_O)[:, :, :orig_shape[-3], :orig_shape[-2], :orig_shape[-1]]
x_B_C_Tt_Hp_Wp = self.unpatchify(x_B_T_H_W_O)
return x_B_C_Tt_Hp_Wp

View File

@ -7,7 +7,7 @@ from comfy_api.internal.singleton import ProxiedSingleton
from comfy_api.internal.async_to_sync import create_sync_class
from ._input import ImageInput, AudioInput, MaskInput, LatentInput, VideoInput
from ._input_impl import VideoFromFile, VideoFromComponents
from ._util import VideoCodec, VideoContainer, VideoComponents, MESH, VOXEL, File3D
from ._util import VideoCodec, VideoContainer, VideoComponents, MESH, VOXEL
from . import _io_public as io
from . import _ui_public as ui
from comfy_execution.utils import get_executing_context
@ -105,7 +105,6 @@ class Types:
VideoComponents = VideoComponents
MESH = MESH
VOXEL = VOXEL
File3D = File3D
ComfyAPI = ComfyAPI_latest

View File

@ -27,7 +27,7 @@ if TYPE_CHECKING:
from comfy_api.internal import (_ComfyNodeInternal, _NodeOutputInternal, classproperty, copy_class, first_real_override, is_class,
prune_dict, shallow_clone_class)
from comfy_execution.graph_utils import ExecutionBlocker
from ._util import MESH, VOXEL, File3D, SVG as _SVG
from ._util import MESH, VOXEL, SVG as _SVG
class FolderType(str, Enum):
@ -667,49 +667,6 @@ class Voxel(ComfyTypeIO):
class Mesh(ComfyTypeIO):
Type = MESH
@comfytype(io_type="FILE_3D")
class File3DAny(ComfyTypeIO):
"""General 3D file type - accepts any supported 3D format."""
Type = File3D
@comfytype(io_type="FILE_3D_GLB")
class File3DGLB(ComfyTypeIO):
"""GLB format 3D file - binary glTF, best for web and cross-platform."""
Type = File3D
@comfytype(io_type="FILE_3D_GLTF")
class File3DGLTF(ComfyTypeIO):
"""GLTF format 3D file - JSON-based glTF with external resources."""
Type = File3D
@comfytype(io_type="FILE_3D_FBX")
class File3DFBX(ComfyTypeIO):
"""FBX format 3D file - best for game engines and animation."""
Type = File3D
@comfytype(io_type="FILE_3D_OBJ")
class File3DOBJ(ComfyTypeIO):
"""OBJ format 3D file - simple geometry format."""
Type = File3D
@comfytype(io_type="FILE_3D_STL")
class File3DSTL(ComfyTypeIO):
"""STL format 3D file - best for 3D printing."""
Type = File3D
@comfytype(io_type="FILE_3D_USDZ")
class File3DUSDZ(ComfyTypeIO):
"""USDZ format 3D file - Apple AR format."""
Type = File3D
@comfytype(io_type="HOOKS")
class Hooks(ComfyTypeIO):
if TYPE_CHECKING:
@ -1189,20 +1146,6 @@ class ImageCompare(ComfyTypeI):
def as_dict(self):
return super().as_dict()
@comfytype(io_type="COLOR")
class Color(ComfyTypeIO):
Type = str
class Input(WidgetInput):
def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None,
socketless: bool=True, advanced: bool=None, default: str="#ffffff"):
super().__init__(id, display_name, optional, tooltip, None, default, socketless, None, None, None, None, advanced)
self.default: str
def as_dict(self):
return super().as_dict()
DYNAMIC_INPUT_LOOKUP: dict[str, Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]] = {}
def register_dynamic_input_func(io_type: str, func: Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]):
DYNAMIC_INPUT_LOOKUP[io_type] = func
@ -1309,6 +1252,23 @@ class NodeInfoV1:
price_badge: dict | None = None
search_aliases: list[str]=None
@dataclass
class NodeInfoV3:
input: dict=None
output: dict=None
hidden: list[str]=None
name: str=None
display_name: str=None
description: str=None
python_module: Any = None
category: str=None
output_node: bool=None
deprecated: bool=None
experimental: bool=None
dev_only: bool=None
api_node: bool=None
price_badge: dict | None = None
@dataclass
class PriceBadgeDepends:
@ -1537,6 +1497,40 @@ class Schema:
)
return info
def get_v3_info(self, cls) -> NodeInfoV3:
input_dict = {}
output_dict = {}
hidden_list = []
# TODO: make sure dynamic types will be handled correctly
if self.inputs:
for input in self.inputs:
add_to_dict_v3(input, input_dict)
if self.outputs:
for output in self.outputs:
add_to_dict_v3(output, output_dict)
if self.hidden:
for hidden in self.hidden:
hidden_list.append(hidden.value)
info = NodeInfoV3(
input=input_dict,
output=output_dict,
hidden=hidden_list,
name=self.node_id,
display_name=self.display_name,
description=self.description,
category=self.category,
output_node=self.is_output_node,
deprecated=self.is_deprecated,
experimental=self.is_experimental,
dev_only=self.is_dev_only,
api_node=self.is_api_node,
python_module=getattr(cls, "RELATIVE_PYTHON_MODULE", "nodes"),
price_badge=self.price_badge.as_dict(self.inputs) if self.price_badge is not None else None,
)
return info
def get_finalized_class_inputs(d: dict[str, Any], live_inputs: dict[str, Any], include_hidden=False) -> tuple[dict[str, Any], V3Data]:
out_dict = {
"required": {},
@ -1591,6 +1585,9 @@ def add_to_dict_v1(i: Input, d: dict):
as_dict.pop("optional", None)
d.setdefault(key, {})[i.id] = (i.get_io_type(), as_dict)
def add_to_dict_v3(io: Input | Output, d: dict):
d[io.id] = (io.get_io_type(), io.as_dict())
class DynamicPathsDefaultValue:
EMPTY_DICT = "empty_dict"
@ -1751,6 +1748,13 @@ class _ComfyNodeBaseInternal(_ComfyNodeInternal):
# set hidden
type_clone.hidden = HiddenHolder.from_v3_data(v3_data)
return type_clone
@final
@classmethod
def GET_NODE_INFO_V3(cls) -> dict[str, Any]:
schema = cls.GET_SCHEMA()
info = schema.get_v3_info(cls)
return asdict(info)
#############################################
# V1 Backwards Compatibility code
#--------------------------------------------
@ -2078,13 +2082,6 @@ __all__ = [
"LossMap",
"Voxel",
"Mesh",
"File3DAny",
"File3DGLB",
"File3DGLTF",
"File3DFBX",
"File3DOBJ",
"File3DSTL",
"File3DUSDZ",
"Hooks",
"HookKeyframes",
"TimestepsRange",
@ -2102,7 +2099,6 @@ __all__ = [
"AnyType",
"MultiType",
"Tracks",
"Color",
# Dynamic Types
"MatchType",
"DynamicCombo",
@ -2111,10 +2107,12 @@ __all__ = [
"HiddenHolder",
"Hidden",
"NodeInfoV1",
"NodeInfoV3",
"Schema",
"ComfyNode",
"NodeOutput",
"add_to_dict_v1",
"add_to_dict_v3",
"V3Data",
"ImageCompare",
"PriceBadgeDepends",

View File

@ -1,5 +1,5 @@
from .video_types import VideoContainer, VideoCodec, VideoComponents
from .geometry_types import VOXEL, MESH, File3D
from .geometry_types import VOXEL, MESH
from .image_types import SVG
__all__ = [
@ -9,6 +9,5 @@ __all__ = [
"VideoComponents",
"VOXEL",
"MESH",
"File3D",
"SVG",
]

View File

@ -1,5 +1,3 @@
from io import BytesIO
import torch
@ -12,30 +10,3 @@ class MESH:
def __init__(self, vertices: torch.Tensor, faces: torch.Tensor):
self.vertices = vertices
self.faces = faces
class File3D:
"""3D file type storing binary data in memory.
This is the backing class for all FILE_3D_* ComfyTypes.
"""
def __init__(self, data: BytesIO, file_format: str):
self._data = data
self.format = file_format
@property
def data(self) -> BytesIO:
"""Get the BytesIO data, seeking to the beginning."""
self._data.seek(0)
return self._data
def save_to(self, path: str) -> str:
"""Save the 3D file data to disk."""
self._data.seek(0)
with open(path, "wb") as f:
f.write(self._data.read())
return path
def __repr__(self) -> str:
return f"File3D({self.format})"

View File

@ -109,9 +109,6 @@ class MeshyTextureRequest(BaseModel):
class MeshyModelsUrls(BaseModel):
glb: str = Field("")
fbx: str = Field("")
usdz: str = Field("")
obj: str = Field("")
class MeshyRiggedModelsUrls(BaseModel):

View File

@ -1,8 +1,11 @@
from __future__ import annotations
from enum import Enum
from pydantic import BaseModel, Field
from enum import Enum
from typing import Optional
from pydantic import BaseModel, Field, conint, confloat
class RecraftColor:
@ -226,24 +229,24 @@ class RecraftColorObject(BaseModel):
class RecraftControlsObject(BaseModel):
colors: list[RecraftColorObject] | None = Field(None, description='An array of preferable colors')
background_color: RecraftColorObject | None = Field(None, description='Use given color as a desired background color')
no_text: bool | None = Field(None, description='Do not embed text layouts')
artistic_level: int | None = Field(None, description='Defines artistic tone of your image. At a simple level, the person looks straight at the camera in a static and clean style. Dynamic and eccentric levels introduce movement and creativity. The value should be in range [0..5].')
colors: Optional[list[RecraftColorObject]] = Field(None, description='An array of preferable colors')
background_color: Optional[RecraftColorObject] = Field(None, description='Use given color as a desired background color')
no_text: Optional[bool] = Field(None, description='Do not embed text layouts')
artistic_level: Optional[conint(ge=0, le=5)] = Field(None, description='Defines artistic tone of your image. At a simple level, the person looks straight at the camera in a static and clean style. Dynamic and eccentric levels introduce movement and creativity. The value should be in range [0..5].')
class RecraftImageGenerationRequest(BaseModel):
prompt: str = Field(..., description='The text prompt describing the image to generate')
size: RecraftImageSize | None = Field(None, description='The size of the generated image (e.g., "1024x1024")')
n: int = Field(..., description='The number of images to generate')
negative_prompt: str | None = Field(None, description='A text description of undesired elements on an image')
model: RecraftModel | None = Field(RecraftModel.recraftv3, description='The model to use for generation (e.g., "recraftv3")')
style: str | None = Field(None, description='The style to apply to the generated image (e.g., "digital_illustration")')
substyle: str | None = Field(None, description='The substyle to apply to the generated image, depending on the style input')
controls: RecraftControlsObject | None = Field(None, description='A set of custom parameters to tweak generation process')
style_id: str | None = Field(None, description='Use a previously uploaded style as a reference; UUID')
strength: float | None = Field(None, description='Defines the difference with the original image, should lie in [0, 1], where 0 means almost identical, and 1 means miserable similarity')
random_seed: int | None = Field(None, description="Seed for video generation")
size: Optional[RecraftImageSize] = Field(None, description='The size of the generated image (e.g., "1024x1024")')
n: conint(ge=1, le=6) = Field(..., description='The number of images to generate')
negative_prompt: Optional[str] = Field(None, description='A text description of undesired elements on an image')
model: Optional[RecraftModel] = Field(RecraftModel.recraftv3, description='The model to use for generation (e.g., "recraftv3")')
style: Optional[str] = Field(None, description='The style to apply to the generated image (e.g., "digital_illustration")')
substyle: Optional[str] = Field(None, description='The substyle to apply to the generated image, depending on the style input')
controls: Optional[RecraftControlsObject] = Field(None, description='A set of custom parameters to tweak generation process')
style_id: Optional[str] = Field(None, description='Use a previously uploaded style as a reference; UUID')
strength: Optional[confloat(ge=0.0, le=1.0)] = Field(None, description='Defines the difference with the original image, should lie in [0, 1], where 0 means almost identical, and 1 means miserable similarity')
random_seed: Optional[int] = Field(None, description="Seed for video generation")
# text_layout
@ -255,13 +258,5 @@ class RecraftReturnedObject(BaseModel):
class RecraftImageGenerationResponse(BaseModel):
created: int = Field(..., description='Unix timestamp when the generation was created')
credits: int = Field(..., description='Number of credits used for the generation')
data: list[RecraftReturnedObject] | None = Field(None, description='Array of generated image information')
image: RecraftReturnedObject | None = Field(None, description='Single generated image')
class RecraftCreateStyleRequest(BaseModel):
style: str = Field(..., description="realistic_image, digital_illustration, vector_illustration, or icon")
class RecraftCreateStyleResponse(BaseModel):
id: str = Field(..., description="UUID of the created style")
data: Optional[list[RecraftReturnedObject]] = Field(None, description='Array of generated image information')
image: Optional[RecraftReturnedObject] = Field(None, description='Single generated image')

View File

@ -6,30 +6,6 @@ class SubjectReference(BaseModel):
images: list[str] = Field(...)
class FrameSetting(BaseModel):
prompt: str = Field(...)
key_image: str = Field(...)
duration: int = Field(...)
class TaskMultiFrameCreationRequest(BaseModel):
model: str = Field(...)
seed: int = Field(..., ge=0, le=2147483647)
resolution: str = Field(...)
start_image: str = Field(...)
image_settings: list[FrameSetting] = Field(...)
class TaskExtendCreationRequest(BaseModel):
model: str = Field(...)
prompt: str = Field(..., max_length=2000)
duration: int = Field(...)
seed: int = Field(..., ge=0, le=2147483647)
resolution: str = Field(...)
images: list[str] | None = Field(None, description="Base64 encoded string or image URL")
video_url: str = Field(..., description="URL of the video to extend")
class TaskCreationRequest(BaseModel):
model: str = Field(...)
prompt: str = Field(..., max_length=2000)

View File

@ -1,3 +1,5 @@
import os
from typing_extensions import override
from comfy_api.latest import IO, ComfyExtension, Input
@ -12,7 +14,7 @@ from comfy_api_nodes.apis.hunyuan3d import (
)
from comfy_api_nodes.util import (
ApiEndpoint,
download_url_to_file_3d,
download_url_to_bytesio,
downscale_image_tensor_by_max_side,
poll_op,
sync_op,
@ -20,13 +22,14 @@ from comfy_api_nodes.util import (
validate_image_dimensions,
validate_string,
)
from folder_paths import get_output_directory
def get_file_from_response(response_objs: list[ResultFile3D], file_type: str) -> ResultFile3D | None:
def get_glb_obj_from_response(response_objs: list[ResultFile3D]) -> ResultFile3D:
for i in response_objs:
if i.Type.lower() == file_type.lower():
if i.Type.lower() == "glb":
return i
return None
raise ValueError("No GLB file found in response. Please report this to the developers.")
class TencentTextToModelNode(IO.ComfyNode):
@ -71,9 +74,7 @@ class TencentTextToModelNode(IO.ComfyNode):
),
],
outputs=[
IO.String.Output(display_name="model_file"), # for backward compatibility only
IO.File3DGLB.Output(display_name="GLB"),
IO.File3DOBJ.Output(display_name="OBJ"),
IO.String.Output(display_name="model_file"),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
@ -123,20 +124,19 @@ class TencentTextToModelNode(IO.ComfyNode):
)
if response.Error:
raise ValueError(f"Task creation failed with code {response.Error.Code}: {response.Error.Message}")
task_id = response.JobId
result = await poll_op(
cls,
ApiEndpoint(path="/proxy/tencent/hunyuan/3d-pro/query", method="POST"),
data=To3DProTaskQueryRequest(JobId=task_id),
data=To3DProTaskQueryRequest(JobId=response.JobId),
response_model=To3DProTaskResultResponse,
status_extractor=lambda r: r.Status,
)
glb_result = get_file_from_response(result.ResultFile3Ds, "glb")
obj_result = get_file_from_response(result.ResultFile3Ds, "obj")
file_glb = await download_url_to_file_3d(glb_result.Url, "glb", task_id=task_id) if glb_result else None
return IO.NodeOutput(
file_glb, file_glb, await download_url_to_file_3d(obj_result.Url, "obj", task_id=task_id) if obj_result else None
model_file = f"hunyuan_model_{response.JobId}.glb"
await download_url_to_bytesio(
get_glb_obj_from_response(result.ResultFile3Ds).Url,
os.path.join(get_output_directory(), model_file),
)
return IO.NodeOutput(model_file)
class TencentImageToModelNode(IO.ComfyNode):
@ -184,9 +184,7 @@ class TencentImageToModelNode(IO.ComfyNode):
),
],
outputs=[
IO.String.Output(display_name="model_file"), # for backward compatibility only
IO.File3DGLB.Output(display_name="GLB"),
IO.File3DOBJ.Output(display_name="OBJ"),
IO.String.Output(display_name="model_file"),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
@ -271,20 +269,19 @@ class TencentImageToModelNode(IO.ComfyNode):
)
if response.Error:
raise ValueError(f"Task creation failed with code {response.Error.Code}: {response.Error.Message}")
task_id = response.JobId
result = await poll_op(
cls,
ApiEndpoint(path="/proxy/tencent/hunyuan/3d-pro/query", method="POST"),
data=To3DProTaskQueryRequest(JobId=task_id),
data=To3DProTaskQueryRequest(JobId=response.JobId),
response_model=To3DProTaskResultResponse,
status_extractor=lambda r: r.Status,
)
glb_result = get_file_from_response(result.ResultFile3Ds, "glb")
obj_result = get_file_from_response(result.ResultFile3Ds, "obj")
file_glb = await download_url_to_file_3d(glb_result.Url, "glb", task_id=task_id) if glb_result else None
return IO.NodeOutput(
file_glb, file_glb, await download_url_to_file_3d(obj_result.Url, "obj", task_id=task_id) if obj_result else None
model_file = f"hunyuan_model_{response.JobId}.glb"
await download_url_to_bytesio(
get_glb_obj_from_response(result.ResultFile3Ds).Url,
os.path.join(get_output_directory(), model_file),
)
return IO.NodeOutput(model_file)
class TencentHunyuan3DExtension(ComfyExtension):

View File

@ -1,3 +1,5 @@
import os
from typing_extensions import override
from comfy_api.latest import IO, ComfyExtension, Input
@ -18,12 +20,13 @@ from comfy_api_nodes.apis.meshy import (
)
from comfy_api_nodes.util import (
ApiEndpoint,
download_url_to_file_3d,
download_url_to_bytesio,
poll_op,
sync_op,
upload_images_to_comfyapi,
validate_string,
)
from folder_paths import get_output_directory
class MeshyTextToModelNode(IO.ComfyNode):
@ -76,10 +79,8 @@ class MeshyTextToModelNode(IO.ComfyNode):
),
],
outputs=[
IO.String.Output(display_name="model_file"), # for backward compatibility only
IO.String.Output(display_name="model_file"),
IO.Custom("MESHY_TASK_ID").Output(display_name="meshy_task_id"),
IO.File3DGLB.Output(display_name="GLB"),
IO.File3DFBX.Output(display_name="FBX"),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
@ -121,21 +122,16 @@ class MeshyTextToModelNode(IO.ComfyNode):
seed=seed,
),
)
task_id = response.result
result = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/meshy/openapi/v2/text-to-3d/{task_id}"),
ApiEndpoint(path=f"/proxy/meshy/openapi/v2/text-to-3d/{response.result}"),
response_model=MeshyModelResult,
status_extractor=lambda r: r.status,
progress_extractor=lambda r: r.progress,
)
file_glb = await download_url_to_file_3d(result.model_urls.glb, "glb", task_id=task_id)
return IO.NodeOutput(
file_glb,
task_id,
file_glb,
await download_url_to_file_3d(result.model_urls.fbx, "fbx", task_id=task_id),
)
model_file = f"meshy_model_{response.result}.glb"
await download_url_to_bytesio(result.model_urls.glb, os.path.join(get_output_directory(), model_file))
return IO.NodeOutput(model_file, response.result)
class MeshyRefineNode(IO.ComfyNode):
@ -171,10 +167,8 @@ class MeshyRefineNode(IO.ComfyNode):
),
],
outputs=[
IO.String.Output(display_name="model_file"), # for backward compatibility only
IO.String.Output(display_name="model_file"),
IO.Custom("MESHY_TASK_ID").Output(display_name="meshy_task_id"),
IO.File3DGLB.Output(display_name="GLB"),
IO.File3DFBX.Output(display_name="FBX"),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
@ -216,21 +210,16 @@ class MeshyRefineNode(IO.ComfyNode):
ai_model=model,
),
)
task_id = response.result
result = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/meshy/openapi/v2/text-to-3d/{task_id}"),
ApiEndpoint(path=f"/proxy/meshy/openapi/v2/text-to-3d/{response.result}"),
response_model=MeshyModelResult,
status_extractor=lambda r: r.status,
progress_extractor=lambda r: r.progress,
)
file_glb = await download_url_to_file_3d(result.model_urls.glb, "glb", task_id=task_id)
return IO.NodeOutput(
file_glb,
task_id,
file_glb,
await download_url_to_file_3d(result.model_urls.fbx, "fbx", task_id=task_id),
)
model_file = f"meshy_model_{response.result}.glb"
await download_url_to_bytesio(result.model_urls.glb, os.path.join(get_output_directory(), model_file))
return IO.NodeOutput(model_file, response.result)
class MeshyImageToModelNode(IO.ComfyNode):
@ -314,10 +303,8 @@ class MeshyImageToModelNode(IO.ComfyNode):
),
],
outputs=[
IO.String.Output(display_name="model_file"), # for backward compatibility only
IO.String.Output(display_name="model_file"),
IO.Custom("MESHY_TASK_ID").Output(display_name="meshy_task_id"),
IO.File3DGLB.Output(display_name="GLB"),
IO.File3DFBX.Output(display_name="FBX"),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
@ -381,21 +368,16 @@ class MeshyImageToModelNode(IO.ComfyNode):
seed=seed,
),
)
task_id = response.result
result = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/meshy/openapi/v1/image-to-3d/{task_id}"),
ApiEndpoint(path=f"/proxy/meshy/openapi/v1/image-to-3d/{response.result}"),
response_model=MeshyModelResult,
status_extractor=lambda r: r.status,
progress_extractor=lambda r: r.progress,
)
file_glb = await download_url_to_file_3d(result.model_urls.glb, "glb", task_id=task_id)
return IO.NodeOutput(
file_glb,
task_id,
file_glb,
await download_url_to_file_3d(result.model_urls.fbx, "fbx", task_id=task_id),
)
model_file = f"meshy_model_{response.result}.glb"
await download_url_to_bytesio(result.model_urls.glb, os.path.join(get_output_directory(), model_file))
return IO.NodeOutput(model_file, response.result)
class MeshyMultiImageToModelNode(IO.ComfyNode):
@ -482,10 +464,8 @@ class MeshyMultiImageToModelNode(IO.ComfyNode):
),
],
outputs=[
IO.String.Output(display_name="model_file"), # for backward compatibility only
IO.String.Output(display_name="model_file"),
IO.Custom("MESHY_TASK_ID").Output(display_name="meshy_task_id"),
IO.File3DGLB.Output(display_name="GLB"),
IO.File3DFBX.Output(display_name="FBX"),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
@ -551,21 +531,16 @@ class MeshyMultiImageToModelNode(IO.ComfyNode):
seed=seed,
),
)
task_id = response.result
result = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/meshy/openapi/v1/multi-image-to-3d/{task_id}"),
ApiEndpoint(path=f"/proxy/meshy/openapi/v1/multi-image-to-3d/{response.result}"),
response_model=MeshyModelResult,
status_extractor=lambda r: r.status,
progress_extractor=lambda r: r.progress,
)
file_glb = await download_url_to_file_3d(result.model_urls.glb, "glb", task_id=task_id)
return IO.NodeOutput(
file_glb,
task_id,
file_glb,
await download_url_to_file_3d(result.model_urls.fbx, "fbx", task_id=task_id),
)
model_file = f"meshy_model_{response.result}.glb"
await download_url_to_bytesio(result.model_urls.glb, os.path.join(get_output_directory(), model_file))
return IO.NodeOutput(model_file, response.result)
class MeshyRigModelNode(IO.ComfyNode):
@ -596,10 +571,8 @@ class MeshyRigModelNode(IO.ComfyNode):
),
],
outputs=[
IO.String.Output(display_name="model_file"), # for backward compatibility only
IO.String.Output(display_name="model_file"),
IO.Custom("MESHY_RIGGED_TASK_ID").Output(display_name="rig_task_id"),
IO.File3DGLB.Output(display_name="GLB"),
IO.File3DFBX.Output(display_name="FBX"),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
@ -633,21 +606,18 @@ class MeshyRigModelNode(IO.ComfyNode):
texture_image_url=texture_image_url,
),
)
task_id = response.result
result = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/meshy/openapi/v1/rigging/{task_id}"),
ApiEndpoint(path=f"/proxy/meshy/openapi/v1/rigging/{response.result}"),
response_model=MeshyRiggedResult,
status_extractor=lambda r: r.status,
progress_extractor=lambda r: r.progress,
)
file_glb = await download_url_to_file_3d(result.model_urls.glb, "glb", task_id=task_id)
return IO.NodeOutput(
file_glb,
task_id,
file_glb,
await download_url_to_file_3d(result.model_urls.fbx, "fbx", task_id=task_id),
model_file = f"meshy_model_{response.result}.glb"
await download_url_to_bytesio(
result.result.rigged_character_glb_url, os.path.join(get_output_directory(), model_file)
)
return IO.NodeOutput(model_file, response.result)
class MeshyAnimateModelNode(IO.ComfyNode):
@ -670,9 +640,7 @@ class MeshyAnimateModelNode(IO.ComfyNode):
),
],
outputs=[
IO.String.Output(display_name="model_file"), # for backward compatibility only
IO.File3DGLB.Output(display_name="GLB"),
IO.File3DFBX.Output(display_name="FBX"),
IO.String.Output(display_name="model_file"),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
@ -701,20 +669,16 @@ class MeshyAnimateModelNode(IO.ComfyNode):
action_id=action_id,
),
)
task_id = response.result
result = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/meshy/openapi/v1/animations/{task_id}"),
ApiEndpoint(path=f"/proxy/meshy/openapi/v1/animations/{response.result}"),
response_model=MeshyAnimationResult,
status_extractor=lambda r: r.status,
progress_extractor=lambda r: r.progress,
)
file_glb = await download_url_to_file_3d(result.model_urls.glb, "glb", task_id=task_id)
return IO.NodeOutput(
file_glb,
file_glb,
await download_url_to_file_3d(result.model_urls.fbx, "fbx", task_id=task_id),
)
model_file = f"meshy_model_{response.result}.glb"
await download_url_to_bytesio(result.result.animation_glb_url, os.path.join(get_output_directory(), model_file))
return IO.NodeOutput(model_file, response.result)
class MeshyTextureNode(IO.ComfyNode):
@ -751,10 +715,8 @@ class MeshyTextureNode(IO.ComfyNode):
),
],
outputs=[
IO.String.Output(display_name="model_file"), # for backward compatibility only
IO.String.Output(display_name="model_file"),
IO.Custom("MODEL_TASK_ID").Output(display_name="meshy_task_id"),
IO.File3DGLB.Output(display_name="GLB"),
IO.File3DFBX.Output(display_name="FBX"),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
@ -798,21 +760,16 @@ class MeshyTextureNode(IO.ComfyNode):
image_style_url=image_style_url,
),
)
task_id = response.result
result = await poll_op(
cls,
ApiEndpoint(path=f"/proxy/meshy/openapi/v1/retexture/{task_id}"),
ApiEndpoint(path=f"/proxy/meshy/openapi/v1/retexture/{response.result}"),
response_model=MeshyModelResult,
status_extractor=lambda r: r.status,
progress_extractor=lambda r: r.progress,
)
file_glb = await download_url_to_file_3d(result.model_urls.glb, "glb", task_id=task_id)
return IO.NodeOutput(
file_glb,
task_id,
file_glb,
await download_url_to_file_3d(result.model_urls.fbx, "fbx", task_id=task_id),
)
model_file = f"meshy_model_{response.result}.glb"
await download_url_to_bytesio(result.model_urls.glb, os.path.join(get_output_directory(), model_file))
return IO.NodeOutput(model_file, response.result)
class MeshyExtension(ComfyExtension):

View File

@ -12,8 +12,6 @@ from comfy_api_nodes.apis.recraft import (
RecraftColor,
RecraftColorChain,
RecraftControls,
RecraftCreateStyleRequest,
RecraftCreateStyleResponse,
RecraftImageGenerationRequest,
RecraftImageGenerationResponse,
RecraftImageSize,
@ -325,75 +323,6 @@ class RecraftStyleInfiniteStyleLibrary(IO.ComfyNode):
return IO.NodeOutput(RecraftStyle(style_id=style_id))
class RecraftCreateStyleNode(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="RecraftCreateStyleNode",
display_name="Recraft Create Style",
category="api node/image/Recraft",
description="Create a custom style from reference images. "
"Upload 1-5 images to use as style references. "
"Total size of all images is limited to 5 MB.",
inputs=[
IO.Combo.Input(
"style",
options=["realistic_image", "digital_illustration"],
tooltip="The base style of the generated images.",
),
IO.Autogrow.Input(
"images",
template=IO.Autogrow.TemplatePrefix(
IO.Image.Input("image"),
prefix="image",
min=1,
max=5,
),
),
],
outputs=[
IO.String.Output(display_name="style_id"),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
expr="""{"type":"usd","usd": 0.04}""",
),
)
@classmethod
async def execute(
cls,
style: str,
images: IO.Autogrow.Type,
) -> IO.NodeOutput:
files = []
total_size = 0
max_total_size = 5 * 1024 * 1024 # 5 MB limit
for i, img in enumerate(list(images.values())):
file_bytes = tensor_to_bytesio(img, total_pixels=2048 * 2048, mime_type="image/webp").read()
total_size += len(file_bytes)
if total_size > max_total_size:
raise Exception("Total size of all images exceeds 5 MB limit.")
files.append((f"file{i + 1}", file_bytes))
response = await sync_op(
cls,
endpoint=ApiEndpoint(path="/proxy/recraft/styles", method="POST"),
response_model=RecraftCreateStyleResponse,
files=files,
data=RecraftCreateStyleRequest(style=style),
content_type="multipart/form-data",
max_retries=1,
)
return IO.NodeOutput(response.id)
class RecraftTextToImageNode(IO.ComfyNode):
@classmethod
def define_schema(cls):
@ -466,7 +395,7 @@ class RecraftTextToImageNode(IO.ComfyNode):
negative_prompt: str = None,
recraft_controls: RecraftControls = None,
) -> IO.NodeOutput:
validate_string(prompt, strip_whitespace=False, min_length=1, max_length=1000)
validate_string(prompt, strip_whitespace=False, max_length=1000)
default_style = RecraftStyle(RecraftStyleV3.realistic_image)
if recraft_style is None:
recraft_style = default_style
@ -1095,7 +1024,6 @@ class RecraftExtension(ComfyExtension):
RecraftStyleV3DigitalIllustrationNode,
RecraftStyleV3LogoRasterNode,
RecraftStyleInfiniteStyleLibrary,
RecraftCreateStyleNode,
RecraftColorRGBNode,
RecraftControlsNode,
]

View File

@ -2,12 +2,9 @@ from typing_extensions import override
from comfy_api.latest import IO, ComfyExtension, Input
from comfy_api_nodes.apis.vidu import (
FrameSetting,
SubjectReference,
TaskCreationRequest,
TaskCreationResponse,
TaskExtendCreationRequest,
TaskMultiFrameCreationRequest,
TaskResult,
TaskStatusResponse,
)
@ -17,14 +14,11 @@ from comfy_api_nodes.util import (
get_number_of_images,
poll_op,
sync_op,
upload_image_to_comfyapi,
upload_images_to_comfyapi,
upload_video_to_comfyapi,
validate_image_aspect_ratio,
validate_image_dimensions,
validate_images_aspect_ratio_closeness,
validate_string,
validate_video_duration,
)
VIDU_TEXT_TO_VIDEO = "/proxy/vidu/text2video"
@ -37,8 +31,7 @@ VIDU_GET_GENERATION_STATUS = "/proxy/vidu/tasks/%s/creations"
async def execute_task(
cls: type[IO.ComfyNode],
vidu_endpoint: str,
payload: TaskCreationRequest | TaskExtendCreationRequest | TaskMultiFrameCreationRequest,
max_poll_attempts: int = 320,
payload: TaskCreationRequest,
) -> list[TaskResult]:
task_creation_response = await sync_op(
cls,
@ -54,7 +47,7 @@ async def execute_task(
response_model=TaskStatusResponse,
status_extractor=lambda r: r.state,
progress_extractor=lambda r: r.progress,
max_poll_attempts=max_poll_attempts,
max_poll_attempts=320,
)
if not response.creations:
raise RuntimeError(
@ -947,540 +940,6 @@ class Vidu2StartEndToVideoNode(IO.ComfyNode):
return IO.NodeOutput(await download_url_to_video_output(results[0].url))
class ViduExtendVideoNode(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="ViduExtendVideoNode",
display_name="Vidu Video Extension",
category="api node/video/Vidu",
description="Extend an existing video by generating additional frames.",
inputs=[
IO.DynamicCombo.Input(
"model",
options=[
IO.DynamicCombo.Option(
"viduq2-pro",
[
IO.Int.Input(
"duration",
default=4,
min=1,
max=7,
step=1,
display_mode=IO.NumberDisplay.slider,
tooltip="Duration of the extended video in seconds.",
),
IO.Combo.Input(
"resolution",
options=["720p", "1080p"],
tooltip="Resolution of the output video.",
),
],
),
IO.DynamicCombo.Option(
"viduq2-turbo",
[
IO.Int.Input(
"duration",
default=4,
min=1,
max=7,
step=1,
display_mode=IO.NumberDisplay.slider,
tooltip="Duration of the extended video in seconds.",
),
IO.Combo.Input(
"resolution",
options=["720p", "1080p"],
tooltip="Resolution of the output video.",
),
],
),
],
tooltip="Model to use for video extension.",
),
IO.Video.Input(
"video",
tooltip="The source video to extend.",
),
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="An optional text prompt for the extended video (max 2000 characters).",
),
IO.Int.Input(
"seed",
default=1,
min=0,
max=2147483647,
step=1,
display_mode=IO.NumberDisplay.number,
control_after_generate=True,
),
IO.Image.Input("end_frame", optional=True),
],
outputs=[
IO.Video.Output(),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["model", "model.duration", "model.resolution"]),
expr="""
(
$m := widgets.model;
$d := $lookup(widgets, "model.duration");
$res := $lookup(widgets, "model.resolution");
$contains($m, "pro")
? (
$base := $lookup({"720p": 0.15, "1080p": 0.3}, $res);
$perSec := $lookup({"720p": 0.05, "1080p": 0.075}, $res);
{"type":"usd","usd": $base + $perSec * ($d - 1)}
)
: (
$base := $lookup({"720p": 0.075, "1080p": 0.2}, $res);
$perSec := $lookup({"720p": 0.025, "1080p": 0.05}, $res);
{"type":"usd","usd": $base + $perSec * ($d - 1)}
)
)
""",
),
)
@classmethod
async def execute(
cls,
model: dict,
video: Input.Video,
prompt: str,
seed: int,
end_frame: Input.Image | None = None,
) -> IO.NodeOutput:
validate_string(prompt, max_length=2000)
validate_video_duration(video, min_duration=4, max_duration=55)
image_url = None
if end_frame is not None:
validate_image_aspect_ratio(end_frame, (1, 4), (4, 1))
validate_image_dimensions(end_frame, min_width=128, min_height=128)
image_url = await upload_image_to_comfyapi(cls, end_frame, wait_label="Uploading end frame")
results = await execute_task(
cls,
"/proxy/vidu/extend",
TaskExtendCreationRequest(
model=model["model"],
prompt=prompt,
duration=model["duration"],
seed=seed,
resolution=model["resolution"],
video_url=await upload_video_to_comfyapi(cls, video, wait_label="Uploading video"),
images=[image_url] if image_url else None,
),
max_poll_attempts=480,
)
return IO.NodeOutput(await download_url_to_video_output(results[0].url))
def _generate_frame_inputs(count: int) -> list:
"""Generate input widgets for a given number of frames."""
inputs = []
for i in range(1, count + 1):
inputs.extend(
[
IO.String.Input(
f"prompt{i}",
multiline=True,
default="",
tooltip=f"Text prompt for frame {i} transition.",
),
IO.Image.Input(
f"end_image{i}",
tooltip=f"End frame image for segment {i}. Aspect ratio must be between 1:4 and 4:1.",
),
IO.Int.Input(
f"duration{i}",
default=4,
min=2,
max=7,
step=1,
display_mode=IO.NumberDisplay.slider,
tooltip=f"Duration for segment {i} in seconds.",
),
]
)
return inputs
class ViduMultiFrameVideoNode(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="ViduMultiFrameVideoNode",
display_name="Vidu Multi-Frame Video Generation",
category="api node/video/Vidu",
description="Generate a video with multiple keyframe transitions.",
inputs=[
IO.Combo.Input("model", options=["viduq2-pro", "viduq2-turbo"]),
IO.Image.Input(
"start_image",
tooltip="The starting frame image. Aspect ratio must be between 1:4 and 4:1.",
),
IO.Int.Input(
"seed",
default=1,
min=0,
max=2147483647,
step=1,
display_mode=IO.NumberDisplay.number,
control_after_generate=True,
),
IO.Combo.Input("resolution", options=["720p", "1080p"]),
IO.DynamicCombo.Input(
"frames",
options=[
IO.DynamicCombo.Option("2", _generate_frame_inputs(2)),
IO.DynamicCombo.Option("3", _generate_frame_inputs(3)),
IO.DynamicCombo.Option("4", _generate_frame_inputs(4)),
IO.DynamicCombo.Option("5", _generate_frame_inputs(5)),
IO.DynamicCombo.Option("6", _generate_frame_inputs(6)),
IO.DynamicCombo.Option("7", _generate_frame_inputs(7)),
IO.DynamicCombo.Option("8", _generate_frame_inputs(8)),
IO.DynamicCombo.Option("9", _generate_frame_inputs(9)),
],
tooltip="Number of keyframe transitions (2-9).",
),
],
outputs=[
IO.Video.Output(),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(
widgets=[
"model",
"resolution",
"frames",
"frames.duration1",
"frames.duration2",
"frames.duration3",
"frames.duration4",
"frames.duration5",
"frames.duration6",
"frames.duration7",
"frames.duration8",
"frames.duration9",
]
),
expr="""
(
$m := widgets.model;
$n := $number(widgets.frames);
$is1080 := widgets.resolution = "1080p";
$d1 := $lookup(widgets, "frames.duration1");
$d2 := $lookup(widgets, "frames.duration2");
$d3 := $n >= 3 ? $lookup(widgets, "frames.duration3") : 0;
$d4 := $n >= 4 ? $lookup(widgets, "frames.duration4") : 0;
$d5 := $n >= 5 ? $lookup(widgets, "frames.duration5") : 0;
$d6 := $n >= 6 ? $lookup(widgets, "frames.duration6") : 0;
$d7 := $n >= 7 ? $lookup(widgets, "frames.duration7") : 0;
$d8 := $n >= 8 ? $lookup(widgets, "frames.duration8") : 0;
$d9 := $n >= 9 ? $lookup(widgets, "frames.duration9") : 0;
$totalDuration := $d1 + $d2 + $d3 + $d4 + $d5 + $d6 + $d7 + $d8 + $d9;
$contains($m, "pro")
? (
$base := $is1080 ? 0.3 : 0.15;
$perSec := $is1080 ? 0.075 : 0.05;
{"type":"usd","usd": $n * $base + $perSec * $totalDuration}
)
: (
$base := $is1080 ? 0.2 : 0.075;
$perSec := $is1080 ? 0.05 : 0.025;
{"type":"usd","usd": $n * $base + $perSec * $totalDuration}
)
)
""",
),
)
@classmethod
async def execute(
cls,
model: str,
start_image: Input.Image,
seed: int,
resolution: str,
frames: dict,
) -> IO.NodeOutput:
validate_image_aspect_ratio(start_image, (1, 4), (4, 1))
frame_count = int(frames["frames"])
image_settings: list[FrameSetting] = []
for i in range(1, frame_count + 1):
validate_image_aspect_ratio(frames[f"end_image{i}"], (1, 4), (4, 1))
validate_string(frames[f"prompt{i}"], max_length=2000)
start_image_url = await upload_image_to_comfyapi(
cls,
start_image,
mime_type="image/png",
wait_label="Uploading start image",
)
for i in range(1, frame_count + 1):
image_settings.append(
FrameSetting(
prompt=frames[f"prompt{i}"],
key_image=await upload_image_to_comfyapi(
cls,
frames[f"end_image{i}"],
mime_type="image/png",
wait_label=f"Uploading end image({i})",
),
duration=frames[f"duration{i}"],
)
)
results = await execute_task(
cls,
"/proxy/vidu/multiframe",
TaskMultiFrameCreationRequest(
model=model,
seed=seed,
resolution=resolution,
start_image=start_image_url,
image_settings=image_settings,
),
max_poll_attempts=480 * frame_count,
)
return IO.NodeOutput(await download_url_to_video_output(results[0].url))
class Vidu3TextToVideoNode(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="Vidu3TextToVideoNode",
display_name="Vidu Q3 Text-to-Video Generation",
category="api node/video/Vidu",
description="Generate video from a text prompt.",
inputs=[
IO.DynamicCombo.Input(
"model",
options=[
IO.DynamicCombo.Option(
"viduq3-pro",
[
IO.Combo.Input(
"aspect_ratio",
options=["16:9", "9:16", "3:4", "4:3", "1:1"],
tooltip="The aspect ratio of the output video.",
),
IO.Combo.Input(
"resolution",
options=["720p", "1080p"],
tooltip="Resolution of the output video.",
),
IO.Int.Input(
"duration",
default=5,
min=1,
max=16,
step=1,
display_mode=IO.NumberDisplay.slider,
tooltip="Duration of the output video in seconds.",
),
IO.Boolean.Input(
"audio",
default=False,
tooltip="When enabled, outputs video with sound "
"(including dialogue and sound effects).",
),
],
),
],
tooltip="Model to use for video generation.",
),
IO.String.Input(
"prompt",
multiline=True,
tooltip="A textual description for video generation, with a maximum length of 2000 characters.",
),
IO.Int.Input(
"seed",
default=1,
min=0,
max=2147483647,
step=1,
display_mode=IO.NumberDisplay.number,
control_after_generate=True,
),
],
outputs=[
IO.Video.Output(),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["model.duration", "model.resolution"]),
expr="""
(
$res := $lookup(widgets, "model.resolution");
$base := $lookup({"720p": 0.075, "1080p": 0.1}, $res);
$perSec := $lookup({"720p": 0.025, "1080p": 0.05}, $res);
{"type":"usd","usd": $base + $perSec * ($lookup(widgets, "model.duration") - 1)}
)
""",
),
)
@classmethod
async def execute(
cls,
model: dict,
prompt: str,
seed: int,
) -> IO.NodeOutput:
validate_string(prompt, min_length=1, max_length=2000)
results = await execute_task(
cls,
VIDU_TEXT_TO_VIDEO,
TaskCreationRequest(
model=model["model"],
prompt=prompt,
duration=model["duration"],
seed=seed,
aspect_ratio=model["aspect_ratio"],
resolution=model["resolution"],
audio=model["audio"],
),
max_poll_attempts=640,
)
return IO.NodeOutput(await download_url_to_video_output(results[0].url))
class Vidu3ImageToVideoNode(IO.ComfyNode):
@classmethod
def define_schema(cls):
return IO.Schema(
node_id="Vidu3ImageToVideoNode",
display_name="Vidu Q3 Image-to-Video Generation",
category="api node/video/Vidu",
description="Generate a video from an image and an optional prompt.",
inputs=[
IO.DynamicCombo.Input(
"model",
options=[
IO.DynamicCombo.Option(
"viduq3-pro",
[
IO.Combo.Input(
"resolution",
options=["720p", "1080p", "2K"],
tooltip="Resolution of the output video.",
),
IO.Int.Input(
"duration",
default=5,
min=1,
max=16,
step=1,
display_mode=IO.NumberDisplay.slider,
tooltip="Duration of the output video in seconds.",
),
IO.Boolean.Input(
"audio",
default=False,
tooltip="When enabled, outputs video with sound "
"(including dialogue and sound effects).",
),
],
),
],
tooltip="Model to use for video generation.",
),
IO.Image.Input(
"image",
tooltip="An image to be used as the start frame of the generated video.",
),
IO.String.Input(
"prompt",
multiline=True,
default="",
tooltip="An optional text prompt for video generation (max 2000 characters).",
),
IO.Int.Input(
"seed",
default=1,
min=0,
max=2147483647,
step=1,
display_mode=IO.NumberDisplay.number,
control_after_generate=True,
),
],
outputs=[
IO.Video.Output(),
],
hidden=[
IO.Hidden.auth_token_comfy_org,
IO.Hidden.api_key_comfy_org,
IO.Hidden.unique_id,
],
is_api_node=True,
price_badge=IO.PriceBadge(
depends_on=IO.PriceBadgeDepends(widgets=["model.duration", "model.resolution"]),
expr="""
(
$res := $lookup(widgets, "model.resolution");
$base := $lookup({"720p": 0.075, "1080p": 0.275, "2k": 0.35}, $res);
$perSec := $lookup({"720p": 0.05, "1080p": 0.075, "2k": 0.075}, $res);
{"type":"usd","usd": $base + $perSec * ($lookup(widgets, "model.duration") - 1)}
)
""",
),
)
@classmethod
async def execute(
cls,
model: dict,
image: Input.Image,
prompt: str,
seed: int,
) -> IO.NodeOutput:
validate_image_aspect_ratio(image, (1, 4), (4, 1))
validate_string(prompt, max_length=2000)
results = await execute_task(
cls,
VIDU_IMAGE_TO_VIDEO,
TaskCreationRequest(
model=model["model"],
prompt=prompt,
duration=model["duration"],
seed=seed,
resolution=model["resolution"],
audio=model["audio"],
images=[await upload_image_to_comfyapi(cls, image)],
),
max_poll_attempts=720,
)
return IO.NodeOutput(await download_url_to_video_output(results[0].url))
class ViduExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
@ -1493,10 +952,6 @@ class ViduExtension(ComfyExtension):
Vidu2ImageToVideoNode,
Vidu2ReferenceVideoNode,
Vidu2StartEndToVideoNode,
ViduExtendVideoNode,
ViduMultiFrameVideoNode,
Vidu3TextToVideoNode,
Vidu3ImageToVideoNode,
]

View File

@ -28,7 +28,6 @@ from .conversions import (
from .download_helpers import (
download_url_as_bytesio,
download_url_to_bytesio,
download_url_to_file_3d,
download_url_to_image_tensor,
download_url_to_video_output,
)
@ -70,7 +69,6 @@ __all__ = [
# Download helpers
"download_url_as_bytesio",
"download_url_to_bytesio",
"download_url_to_file_3d",
"download_url_to_image_tensor",
"download_url_to_video_output",
# Conversions

View File

@ -11,8 +11,7 @@ import torch
from aiohttp.client_exceptions import ClientError, ContentTypeError
from comfy_api.latest import IO as COMFY_IO
from comfy_api.latest import InputImpl, Types
from folder_paths import get_output_directory
from comfy_api.latest import InputImpl
from . import request_logger
from ._helpers import (
@ -262,38 +261,3 @@ def _generate_operation_id(method: str, url: str, attempt: int) -> str:
except Exception:
slug = "download"
return f"{method}_{slug}_try{attempt}_{uuid.uuid4().hex[:8]}"
async def download_url_to_file_3d(
url: str,
file_format: str,
*,
task_id: str | None = None,
timeout: float | None = None,
max_retries: int = 5,
cls: type[COMFY_IO.ComfyNode] = None,
) -> Types.File3D:
"""Downloads a 3D model file from a URL into memory as BytesIO.
If task_id is provided, also writes the file to disk in the output directory
for backward compatibility with the old save-to-disk behavior.
"""
file_format = file_format.lstrip(".").lower()
data = BytesIO()
await download_url_to_bytesio(
url,
data,
timeout=timeout,
max_retries=max_retries,
cls=cls,
)
if task_id is not None:
# This is only for backward compatability with current behavior when every 3D node is output node
# All new API nodes should not use "task_id" and instead users should use "SaveGLB" node to save results
output_dir = Path(get_output_directory())
output_path = output_dir / f"{task_id}.{file_format}"
output_path.write_bytes(data.getvalue())
data.seek(0)
return Types.File3D(data=data, file_format=file_format)

View File

@ -1,42 +0,0 @@
from typing_extensions import override
from comfy_api.latest import ComfyExtension, io
class ColorToRGBInt(io.ComfyNode):
@classmethod
def define_schema(cls) -> io.Schema:
return io.Schema(
node_id="ColorToRGBInt",
display_name="Color to RGB Int",
category="utils",
description="Convert a color to a RGB integer value.",
inputs=[
io.Color.Input("color"),
],
outputs=[
io.Int.Output(display_name="rgb_int"),
],
)
@classmethod
def execute(
cls,
color: str,
) -> io.NodeOutput:
# expect format #RRGGBB
if len(color) != 7 or color[0] != "#":
raise ValueError("Color must be in format #RRGGBB")
r = int(color[1:3], 16)
g = int(color[3:5], 16)
b = int(color[5:7], 16)
return io.NodeOutput(r * 256 * 256 + g * 256 + b)
class ColorExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [ColorToRGBInt]
async def comfy_entrypoint() -> ColorExtension:
return ColorExtension()

View File

@ -56,7 +56,7 @@ class EmptyHunyuanLatentVideo(io.ComfyNode):
@classmethod
def execute(cls, width, height, length, batch_size=1) -> io.NodeOutput:
latent = torch.zeros([batch_size, 16, ((length - 1) // 4) + 1, height // 8, width // 8], device=comfy.model_management.intermediate_device())
return io.NodeOutput({"samples": latent, "downscale_ratio_spacial": 8})
return io.NodeOutput({"samples":latent})
generate = execute # TODO: remove
@ -73,7 +73,7 @@ class EmptyHunyuanVideo15Latent(EmptyHunyuanLatentVideo):
def execute(cls, width, height, length, batch_size=1) -> io.NodeOutput:
# Using scale factor of 16 instead of 8
latent = torch.zeros([batch_size, 32, ((length - 1) // 4) + 1, height // 16, width // 16], device=comfy.model_management.intermediate_device())
return io.NodeOutput({"samples": latent, "downscale_ratio_spacial": 16})
return io.NodeOutput({"samples": latent})
class HunyuanVideo15ImageToVideo(io.ComfyNode):

View File

@ -622,21 +622,14 @@ class SaveGLB(IO.ComfyNode):
category="3d",
is_output_node=True,
inputs=[
IO.MultiType.Input(
IO.Mesh.Input("mesh"),
types=[
IO.File3DGLB,
IO.File3DAny,
],
tooltip="Mesh or 3D file to save as GLB",
),
IO.Mesh.Input("mesh"),
IO.String.Input("filename_prefix", default="mesh/ComfyUI"),
],
hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo]
)
@classmethod
def execute(cls, mesh: Types.MESH | Types.File3D, filename_prefix: str) -> IO.NodeOutput:
def execute(cls, mesh, filename_prefix) -> IO.NodeOutput:
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, folder_paths.get_output_directory())
results = []
@ -648,26 +641,15 @@ class SaveGLB(IO.ComfyNode):
for x in cls.hidden.extra_pnginfo:
metadata[x] = json.dumps(cls.hidden.extra_pnginfo[x])
if isinstance(mesh, Types.File3D):
# Handle File3D input - save BytesIO data to output folder
for i in range(mesh.vertices.shape[0]):
f = f"{filename}_{counter:05}_.glb"
mesh.save_to(os.path.join(full_output_folder, f))
save_glb(mesh.vertices[i], mesh.faces[i], os.path.join(full_output_folder, f), metadata)
results.append({
"filename": f,
"subfolder": subfolder,
"type": "output"
})
else:
# Handle Mesh input - save vertices and faces as GLB
for i in range(mesh.vertices.shape[0]):
f = f"{filename}_{counter:05}_.glb"
save_glb(mesh.vertices[i], mesh.faces[i], os.path.join(full_output_folder, f), metadata)
results.append({
"filename": f,
"subfolder": subfolder,
"type": "output"
})
counter += 1
counter += 1
return IO.NodeOutput(ui={"3d": results})

View File

@ -1,10 +1,9 @@
import nodes
import folder_paths
import os
import uuid
from typing_extensions import override
from comfy_api.latest import IO, UI, ComfyExtension, InputImpl, Types
from comfy_api.latest import IO, ComfyExtension, InputImpl, UI
from pathlib import Path
@ -82,19 +81,7 @@ class Preview3D(IO.ComfyNode):
is_experimental=True,
is_output_node=True,
inputs=[
IO.MultiType.Input(
IO.String.Input("model_file", default="", multiline=False),
types=[
IO.File3DGLB,
IO.File3DGLTF,
IO.File3DFBX,
IO.File3DOBJ,
IO.File3DSTL,
IO.File3DUSDZ,
IO.File3DAny,
],
tooltip="3D model file or path string",
),
IO.String.Input("model_file", default="", multiline=False),
IO.Load3DCamera.Input("camera_info", optional=True),
IO.Image.Input("bg_image", optional=True),
],
@ -102,15 +89,10 @@ class Preview3D(IO.ComfyNode):
)
@classmethod
def execute(cls, model_file: str | Types.File3D, **kwargs) -> IO.NodeOutput:
if isinstance(model_file, Types.File3D):
filename = f"preview3d_{uuid.uuid4().hex}.{model_file.format}"
model_file.save_to(os.path.join(folder_paths.get_output_directory(), filename))
else:
filename = model_file
def execute(cls, model_file, **kwargs) -> IO.NodeOutput:
camera_info = kwargs.get("camera_info", None)
bg_image = kwargs.get("bg_image", None)
return IO.NodeOutput(ui=UI.PreviewUI3D(filename, camera_info, bg_image=bg_image))
return IO.NodeOutput(ui=UI.PreviewUI3D(model_file, camera_info, bg_image=bg_image))
process = execute # TODO: remove

View File

@ -1011,11 +1011,17 @@ async def validate_prompt(prompt_id, prompt, partial_execution_list: Union[list[
class_type = prompt[x]['class_type']
class_ = nodes.NODE_CLASS_MAPPINGS.get(class_type, None)
if class_ is None:
node_data = prompt[x]
node_title = node_data.get('_meta', {}).get('title', class_type)
error = {
"type": "invalid_prompt",
"message": f"Cannot execute because node {class_type} does not exist.",
"type": "missing_node_type",
"message": f"Node '{node_title}' not found. The custom node may not be installed.",
"details": f"Node ID '#{x}'",
"extra_info": {}
"extra_info": {
"node_id": x,
"class_type": class_type,
"node_title": node_title
}
}
return (False, error, [], {})

View File

@ -2432,8 +2432,7 @@ async def init_builtin_extra_nodes():
"nodes_wanmove.py",
"nodes_image_compare.py",
"nodes_zimage.py",
"nodes_lora_debug.py",
"nodes_color.py"
"nodes_lora_debug.py"
]
import_failed = []