mirrors/ComfyUI
1
0
Fork 0
mirror of https://github.com/comfyanonymous/ComfyUI.git synced 2025-07-27 16:26:39 +00:00
Code Issues Packages Projects Releases Wiki Activity

Added simple Type defs to ComfyTypes in io.py

Browse Source
This commit is contained in:
Jedrzej Kosinski 2025-06-27 14:56:31 -07:00
parent cef73c75fb
commit ba857bd8a0
1 changed files with 30 additions and 20 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

50
comfy_api/v3/io.py
View File

@ -7,7 +7,16 @@ from collections import Counter
from comfy.comfy_types.node_typing import IO
# used for type hinting
import torch
from spandrel import ImageModelDescriptor
from comfy.model_patcher import ModelPatcher
from comfy.samplers import Sampler, CFGGuider
from comfy.sd import CLIP
from comfy.controlnet import ControlNet
from comfy.sd import VAE
from comfy.sd import StyleModel as StyleModel_
from comfy.clip_vision import ClipVisionModel
from comfy.clip_vision import Output as ClipVisionOutput_
from comfy_api.input import VideoInput
class FolderType(str, Enum):
@ -443,35 +452,35 @@ class Latent(ComfyTypeIO):
@comfytype(io_type=IO.CONDITIONING)
class Conditioning(ComfyTypeIO):
Type = Any
Type = Any # TODO: make Type a TypedDict
@comfytype(io_type=IO.SAMPLER)
class Sampler(ComfyTypeIO):
Type = Any
Type = Sampler
@comfytype(io_type=IO.SIGMAS)
class Sigmas(ComfyTypeIO):
Type = Any
Type = torch.Tensor
@comfytype(io_type=IO.NOISE)
class Noise(ComfyTypeIO):
Type = Any
Type = torch.Tensor
@comfytype(io_type=IO.GUIDER)
class Guider(ComfyTypeIO):
Type = Any
Type = CFGGuider
@comfytype(io_type=IO.CLIP)
class Clip(ComfyTypeIO):
Type = Any
Type = CLIP
@comfytype(io_type=IO.CONTROL_NET)
class ControlNet(ComfyTypeIO):
Type = Any
Type = ControlNet
@comfytype(io_type=IO.VAE)
class Vae(ComfyTypeIO):
Type = Any
Type = VAE
@comfytype(io_type=IO.MODEL)
class Model(ComfyTypeIO):
@ -479,47 +488,48 @@ class Model(ComfyTypeIO):
@comfytype(io_type=IO.CLIP_VISION)
class ClipVision(ComfyTypeIO):
Type = Any
Type = ClipVisionModel
@comfytype(io_type=IO.CLIP_VISION_OUTPUT)
class ClipVisionOutput(ComfyTypeIO):
Type = Any
Type = ClipVisionOutput_
@comfytype(io_type=IO.STYLE_MODEL)
class StyleModel(ComfyTypeIO):
Type = Any
Type = StyleModel_
@comfytype(io_type=IO.GLIGEN)
class Gligen(ComfyTypeIO):
Type = Any
'''ModelPatcher that wraps around a 'Gligen' model.'''
Type = ModelPatcher
@comfytype(io_type=IO.UPSCALE_MODEL)
class UpscaleModel(ComfyTypeIO):
Type = Any
Type = ImageModelDescriptor
@comfytype(io_type=IO.AUDIO)
class Audio(ComfyTypeIO):
Type = Any
Type = Any # TODO: make Type a TypedDict
@comfytype(io_type=IO.POINT)
class Point(ComfyTypeIO):
Type = Any
Type = Any # NOTE: I couldn't find any references in core code to POINT io_type. Does this exist?
@comfytype(io_type=IO.FACE_ANALYSIS)
class FaceAnalysis(ComfyTypeIO):
Type = Any
Type = Any # NOTE: I couldn't find any references in core code to POINT io_type. Does this exist?
@comfytype(io_type=IO.BBOX)
class BBOX(ComfyTypeIO):
Type = Any
Type = Any # NOTE: I couldn't find any references in core code to POINT io_type. Does this exist?
@comfytype(io_type=IO.SEGS)
class SEGS(ComfyTypeIO):
Type = Any
Type = Any # NOTE: I couldn't find any references in core code to POINT io_type. Does this exist?
@comfytype(io_type=IO.VIDEO)
class Video(ComfyTypeIO):
Type = Any
Type = VideoInput
@comfytype(io_type="COMFY_MULTITYPED_V3")
class MultiType:
@ -528,7 +538,7 @@ class MultiType:
'''
Input that permits more than one input type; if `id` is an instance of `ComfyType.Input`, then that input will be used to create a widget (if applicable) with overridden values.
'''
def __init__(self, id: str | ComfyType.Input, types: list[type[ComfyType] | ComfyType], display_name: str=None, optional=False, tooltip: str=None, lazy: bool=None, extra_dict=None):
def __init__(self, id: str | InputV3, types: list[type[ComfyType] | ComfyType], display_name: str=None, optional=False, tooltip: str=None, lazy: bool=None, extra_dict=None):
# if id is an Input, then use that Input with overridden values
self.input_override = None
if isinstance(id, InputV3):