mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2025-06-08 23:27:14 +00:00
771 lines
26 KiB
Python
771 lines
26 KiB
Python
from __future__ import annotations
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from typing import Union, Any
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from enum import Enum
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from abc import ABC, abstractmethod
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from dataclasses import dataclass, asdict
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class InputBehavior(str, Enum):
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required = "required"
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optional = "optional"
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# TODO: handle hidden inputs
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def is_class(obj):
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'''
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Returns True if is a class type.
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Returns False if is a class instance.
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'''
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return isinstance(obj, type)
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class NumberDisplay(str, Enum):
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number = "number"
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slider = "slider"
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class IO_V3:
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'''
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Base class for V3 Inputs and Outputs.
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'''
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def __init__(self):
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pass
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def __init_subclass__(cls, io_type, **kwargs):
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cls.io_type = io_type
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super().__init_subclass__(**kwargs)
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class InputV3(IO_V3, io_type=None):
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'''
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Base class for a V3 Input.
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'''
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def __init__(self, id: str, display_name: str=None, behavior=InputBehavior.required, tooltip: str=None, lazy: bool=None):
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super().__init__()
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self.id = id
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self.display_name = display_name
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self.behavior = behavior
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self.tooltip = tooltip
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self.lazy = lazy
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def as_dict_V1(self):
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return prune_dict({
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"display_name": self.display_name,
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"tooltip": self.tooltip,
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"lazy": self.lazy
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})
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def get_io_type_V1(self):
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return self.io_type
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class WidgetInputV3(InputV3, io_type=None):
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'''
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Base class for a V3 Input with widget.
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'''
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def __init__(self, id: str, display_name: str=None, behavior=InputBehavior.required, tooltip: str=None, lazy: bool=None,
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default: Any=None,
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socketless: bool=None, widgetType: str=None):
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super().__init__(id, display_name, behavior, tooltip, lazy)
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self.default = default
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self.socketless = socketless
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self.widgetType = widgetType
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def as_dict_V1(self):
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return super().as_dict_V1() | prune_dict({
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"default": self.default,
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"socketless": self.socketless,
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"widgetType": self.widgetType,
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})
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def CustomType(io_type: str) -> type[IO_V3]:
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name = f"{io_type}_IO_V3"
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return type(name, (IO_V3,), {}, io_type=io_type)
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def CustomInput(id: str, io_type: str, display_name: str=None, behavior=InputBehavior.required, tooltip: str=None, lazy: bool=None) -> InputV3:
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'''
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Defines input for 'io_type'. Can be used to stand in for non-core types.
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'''
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input_kwargs = {
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"id": id,
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"display_name": display_name,
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"behavior": behavior,
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"tooltip": tooltip,
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"lazy": lazy,
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}
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return type(f"{io_type}Input", (InputV3,), {}, io_type=io_type)(**input_kwargs)
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def CustomOutput(id: str, io_type: str, display_name: str=None, tooltip: str=None) -> OutputV3:
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'''
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Defines output for 'io_type'. Can be used to stand in for non-core types.
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'''
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input_kwargs = {
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"id": id,
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"display_name": display_name,
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"tooltip": tooltip,
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}
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return type(f"{io_type}Output", (OutputV3,), {}, io_type=io_type)(**input_kwargs)
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class BooleanInput(WidgetInputV3, io_type="BOOLEAN"):
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'''
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Boolean input.
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'''
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def __init__(self, id: str, display_name: str=None, behavior=InputBehavior.required, tooltip: str=None, lazy: bool=None,
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default: bool=None, label_on: str=None, label_off: str=None,
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socketless: bool=None, widgetType: str=None):
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super().__init__(id, display_name, behavior, tooltip, lazy, default, socketless, widgetType)
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self.label_on = label_on
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self.label_off = label_off
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self.default: bool
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def as_dict_V1(self):
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return super().as_dict_V1() | prune_dict({
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"label_on": self.label_on,
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"label_off": self.label_off,
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})
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class IntegerInput(WidgetInputV3, io_type="INT"):
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'''
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Integer input.
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'''
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def __init__(self, id: str, display_name: str=None, behavior=InputBehavior.required, tooltip: str=None, lazy: bool=None,
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default: int=None, min: int=None, max: int=None, step: int=None, control_after_generate: bool=None,
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display_mode: NumberDisplay=None, socketless: bool=None, widgetType: str=None):
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super().__init__(id, display_name, behavior, tooltip, lazy, default, socketless, widgetType)
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self.min = min
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self.max = max
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self.step = step
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self.control_after_generate = control_after_generate
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self.display_mode = display_mode
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self.default: int
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def as_dict_V1(self):
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return super().as_dict_V1() | prune_dict({
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"min": self.min,
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"max": self.max,
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"step": self.step,
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"control_after_generate": self.control_after_generate,
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"display": self.display_mode, # NOTE: in frontend, the parameter is called "display"
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})
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class FloatInput(WidgetInputV3, io_type="FLOAT"):
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'''
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Float input.
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'''
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def __init__(self, id: str, display_name: str=None, behavior=InputBehavior.required, tooltip: str=None, lazy: bool=None,
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default: float=None, min: float=None, max: float=None, step: float=None, round: float=None,
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display_mode: NumberDisplay=None, socketless: bool=None, widgetType: str=None):
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super().__init__(id, display_name, behavior, tooltip, lazy, default, socketless, widgetType)
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self.default = default
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self.min = min
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self.max = max
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self.step = step
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self.round = round
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self.display_mode = display_mode
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self.default: float
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def as_dict_V1(self):
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return super().as_dict_V1() | prune_dict({
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"min": self.min,
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"max": self.max,
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"step": self.step,
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"round": self.round,
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"display": self.display_mode, # NOTE: in frontend, the parameter is called "display"
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})
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class StringInput(WidgetInputV3, io_type="STRING"):
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'''
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String input.
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'''
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def __init__(self, id: str, display_name: str=None, behavior=InputBehavior.required, tooltip: str=None, lazy: bool=None,
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multiline=False, placeholder: str=None, default: int=None,
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socketless: bool=None, widgetType: str=None):
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super().__init__(id, display_name, behavior, tooltip, lazy, default, socketless, widgetType)
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self.multiline = multiline
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self.placeholder = placeholder
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self.default: str
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def as_dict_V1(self):
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return super().as_dict_V1() | prune_dict({
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"multiline": self.multiline,
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"placeholder": self.placeholder,
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})
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class ComboInput(WidgetInputV3, io_type="COMBO"):
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'''Combo input (dropdown).'''
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def __init__(self, id: str, options: list[str], display_name: str=None, behavior=InputBehavior.required, tooltip: str=None, lazy: bool=None,
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default: str=None, control_after_generate: bool=None,
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socketless: bool=None, widgetType: str=None):
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super().__init__(id, display_name, behavior, tooltip, lazy, default, socketless, widgetType)
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self.multiselect = False
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self.options = options
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self.control_after_generate = control_after_generate
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self.default: str
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def as_dict_V1(self):
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return super().as_dict_V1() | prune_dict({
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"multiselect": self.multiselect,
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"options": self.options,
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"control_after_generate": self.control_after_generate,
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})
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class MultiselectComboWidget(ComboInput, io_type="COMBO"):
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'''Multiselect Combo input (dropdown for selecting potentially more than one value).'''
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def __init__(self, id: str, options: list[str], display_name: str=None, behavior=InputBehavior.required, tooltip: str=None, lazy: bool=None,
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default: list[str]=None, placeholder: str=None, chip: bool=None, control_after_generate: bool=None,
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socketless: bool=None, widgetType: str=None):
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super().__init__(id, options, display_name, behavior, tooltip, lazy, default, control_after_generate, socketless, widgetType)
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self.multiselect = True
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self.placeholder = placeholder
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self.chip = chip
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self.default: list[str]
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def as_dict_V1(self):
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return super().as_dict_V1() | prune_dict({
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"multiselect": self.multiselect,
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"placeholder": self.placeholder,
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"chip": self.chip,
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})
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class ImageInput(InputV3, io_type="IMAGE"):
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'''
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Image input.
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'''
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def __init__(self, id: str, display_name: str=None, behavior=InputBehavior.required, tooltip: str=None):
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super().__init__(id, display_name, behavior, tooltip)
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class MaskInput(InputV3, io_type="MASK"):
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'''
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Mask input.
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'''
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def __init__(self, id: str, display_name: str=None, behavior=InputBehavior.required, tooltip: str=None):
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super().__init__(id, display_name, behavior, tooltip)
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class LatentInput(InputV3, io_type="LATENT"):
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'''
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Latent input.
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'''
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def __init__(self, id: str, display_name: str=None, behavior=InputBehavior.required, tooltip: str=None):
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super().__init__(id, display_name, behavior, tooltip)
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class MultitypedInput(InputV3, io_type="COMFY_MULTITYPED_V3"):
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'''
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Input that permits more than one input type.
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'''
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def __init__(self, id: str, io_types: list[Union[type[IO_V3], InputV3, str]], display_name: str=None, behavior=InputBehavior.required, tooltip: str=None,):
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super().__init__(id, display_name, behavior, tooltip)
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self._io_types = io_types
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@property
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def io_types(self) -> list[type[InputV3]]:
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'''
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Returns list of InputV3 class types permitted.
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'''
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io_types = []
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for x in self._io_types:
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if not is_class(x):
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io_types.append(type(x))
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else:
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io_types.append(x)
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return io_types
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def get_io_type_V1(self):
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return ",".join(x.io_type for x in self.io_types)
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class OutputV3:
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def __init__(self, id: str, display_name: str=None, tooltip: str=None,
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is_output_list=False):
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self.id = id
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self.display_name = display_name
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self.tooltip = tooltip
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self.is_output_list = is_output_list
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def __init_subclass__(cls, io_type, **kwargs):
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cls.io_type = io_type
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super().__init_subclass__(**kwargs)
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class IntegerOutput(OutputV3, io_type="INT"):
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pass
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class FloatOutput(OutputV3, io_type="FLOAT"):
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pass
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class StringOutput(OutputV3, io_type="STRING"):
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pass
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# def __init__(self, id: str, display_name: str=None, tooltip: str=None):
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# super().__init__(id, display_name, tooltip)
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class ImageOutput(OutputV3, io_type="IMAGE"):
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pass
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class MaskOutput(OutputV3, io_type="MASK"):
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pass
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class LatentOutput(OutputV3, io_type="LATENT"):
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pass
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class DynamicInput(InputV3, io_type=None):
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'''
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Abstract class for dynamic input registration.
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'''
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def __init__(self, io_type: str, id: str, display_name: str=None):
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super().__init__(io_type, id, display_name)
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class DynamicOutput(OutputV3, io_type=None):
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'''
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Abstract class for dynamic output registration.
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'''
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def __init__(self, io_type: str, id: str, display_name: str=None):
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super().__init__(io_type, id, display_name)
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class AutoGrowDynamicInput(DynamicInput, io_type="COMFY_MULTIGROW_V3"):
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'''
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Dynamic Input that adds another template_input each time one is provided.
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Additional inputs are forced to have 'InputBehavior.optional'.
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'''
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def __init__(self, id: str, template_input: InputV3, min: int=1, max: int=None):
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super().__init__("AutoGrowDynamicInput", id)
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self.template_input = template_input
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if min is not None:
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assert(min >= 1)
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if max is not None:
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assert(max >= 1)
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self.min = min
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self.max = max
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class ComboDynamicInput(DynamicInput, io_type="COMFY_COMBODYNAMIC_V3"):
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def __init__(self, id: str):
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pass
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AutoGrowDynamicInput(id="dynamic", template_input=ImageInput(id="image"))
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class Hidden(str, Enum):
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'''
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Enumerator for requesting hidden variables in nodes.
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'''
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unique_id = "UNIQUE_ID"
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"""UNIQUE_ID is the unique identifier of the node, and matches the id property of the node on the client side. It is commonly used in client-server communications (see messages)."""
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prompt = "PROMPT"
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"""PROMPT is the complete prompt sent by the client to the server. See the prompt object for a full description."""
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extra_pnginfo = "EXTRA_PNGINFO"
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"""EXTRA_PNGINFO is a dictionary that will be copied into the metadata of any .png files saved. Custom nodes can store additional information in this dictionary for saving (or as a way to communicate with a downstream node)."""
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dynprompt = "DYNPROMPT"
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"""DYNPROMPT is an instance of comfy_execution.graph.DynamicPrompt. It differs from PROMPT in that it may mutate during the course of execution in response to Node Expansion."""
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auth_token_comfy_org = "AUTH_TOKEN_COMFY_ORG"
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"""AUTH_TOKEN_COMFY_ORG is a token acquired from signing into a ComfyOrg account on frontend."""
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api_key_comfy_org = "API_KEY_COMFY_ORG"
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"""API_KEY_COMFY_ORG is an API Key generated by ComfyOrg that allows skipping signing into a ComfyOrg account on frontend."""
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@dataclass
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class NodeInfoV1:
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input: dict=None
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input_order: dict[str, list[str]]=None
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output: list[str]=None
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output_is_list: list[bool]=None
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output_name: list[str]=None
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output_tooltips: list[str]=None
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name: str=None
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display_name: str=None
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description: str=None
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python_module: Any=None
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category: str=None
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output_node: bool=None
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deprecated: bool=None
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experimental: bool=None
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api_node: bool=None
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def as_pruned_dict(dataclass_obj):
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'''Return dict of dataclass object with pruned None values.'''
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return prune_dict(asdict(dataclass_obj))
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def prune_dict(d: dict):
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return {k: v for k,v in d.items() if v is not None}
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@dataclass
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class SchemaV3:
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"""Definition of V3 node properties."""
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node_id: str
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"""ID of node - should be globally unique. If this is a custom node, add a prefix or postfix to avoid name clashes."""
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display_name: str = None
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"""Display name of node."""
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category: str = "sd"
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"""The category of the node, as per the "Add Node" menu."""
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inputs: list[InputV3]=None
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outputs: list[OutputV3]=None
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hidden: list[Hidden]=None
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description: str=""
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"""Node description, shown as a tooltip when hovering over the node."""
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is_input_list: bool = False
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"""A flag indicating if this node implements the additional code necessary to deal with OUTPUT_IS_LIST nodes.
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All inputs of ``type`` will become ``list[type]``, regardless of how many items are passed in. This also affects ``check_lazy_status``.
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From the docs:
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A node can also override the default input behaviour and receive the whole list in a single call. This is done by setting a class attribute `INPUT_IS_LIST` to ``True``.
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Comfy Docs: https://docs.comfy.org/custom-nodes/backend/lists#list-processing
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"""
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is_output_node: bool=False
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"""Flags this node as an output node, causing any inputs it requires to be executed.
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If a node is not connected to any output nodes, that node will not be executed. Usage::
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OUTPUT_NODE = True
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From the docs:
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By default, a node is not considered an output. Set ``OUTPUT_NODE = True`` to specify that it is.
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Comfy Docs: https://docs.comfy.org/custom-nodes/backend/server_overview#output-node
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"""
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is_deprecated: bool=False
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"""Flags a node as deprecated, indicating to users that they should find alternatives to this node."""
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is_experimental: bool=False
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"""Flags a node as experimental, informing users that it may change or not work as expected."""
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is_api_node: bool=False
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"""Flags a node as an API node. See: https://docs.comfy.org/tutorials/api-nodes/overview."""
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# class SchemaV3Class:
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# def __init__(self,
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# node_id: str,
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# node_name: str,
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# category: str,
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# inputs: list[InputV3],
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# outputs: list[OutputV3]=None,
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# hidden: list[Hidden]=None,
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# description: str="",
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# is_input_list: bool = False,
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# is_output_node: bool=False,
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# is_deprecated: bool=False,
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# is_experimental: bool=False,
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# is_api_node: bool=False,
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# ):
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# self.node_id = node_id
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# """ID of node - should be globally unique. If this is a custom node, add a prefix or postfix to avoid name clashes."""
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# self.node_name = node_name
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# """Display name of node."""
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# self.category = category
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# """The category of the node, as per the "Add Node" menu."""
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# self.inputs = inputs
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# self.outputs = outputs
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# self.hidden = hidden
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# self.description = description
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# """Node description, shown as a tooltip when hovering over the node."""
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# self.is_input_list = is_input_list
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# """A flag indicating if this node implements the additional code necessary to deal with OUTPUT_IS_LIST nodes.
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# All inputs of ``type`` will become ``list[type]``, regardless of how many items are passed in. This also affects ``check_lazy_status``.
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# From the docs:
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# A node can also override the default input behaviour and receive the whole list in a single call. This is done by setting a class attribute `INPUT_IS_LIST` to ``True``.
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# Comfy Docs: https://docs.comfy.org/custom-nodes/backend/lists#list-processing
|
|
# """
|
|
# self.is_output_node = is_output_node
|
|
# """Flags this node as an output node, causing any inputs it requires to be executed.
|
|
|
|
# If a node is not connected to any output nodes, that node will not be executed. Usage::
|
|
|
|
# OUTPUT_NODE = True
|
|
|
|
# From the docs:
|
|
|
|
# By default, a node is not considered an output. Set ``OUTPUT_NODE = True`` to specify that it is.
|
|
|
|
# Comfy Docs: https://docs.comfy.org/custom-nodes/backend/server_overview#output-node
|
|
# """
|
|
# self.is_deprecated = is_deprecated
|
|
# """Flags a node as deprecated, indicating to users that they should find alternatives to this node."""
|
|
# self.is_experimental = is_experimental
|
|
# """Flags a node as experimental, informing users that it may change or not work as expected."""
|
|
# self.is_api_node = is_api_node
|
|
# """Flags a node as an API node. See: https://docs.comfy.org/tutorials/api-nodes/overview."""
|
|
|
|
|
|
class classproperty(object):
|
|
def __init__(self, f):
|
|
self.f = f
|
|
def __get__(self, obj, owner):
|
|
return self.f(owner)
|
|
|
|
|
|
class ComfyNodeV3(ABC):
|
|
"""Common base class for all V3 nodes."""
|
|
|
|
#############################################
|
|
# V1 Backwards Compatibility code
|
|
#--------------------------------------------
|
|
_DESCRIPTION = None
|
|
@classproperty
|
|
def DESCRIPTION(cls):
|
|
if cls._DESCRIPTION is None:
|
|
cls.GET_SCHEMA()
|
|
return cls._DESCRIPTION
|
|
|
|
_CATEGORY = None
|
|
@classproperty
|
|
def CATEGORY(cls):
|
|
if cls._CATEGORY is None:
|
|
cls.GET_SCHEMA()
|
|
return cls._CATEGORY
|
|
|
|
_EXPERIMENTAL = None
|
|
@classproperty
|
|
def EXPERIMENTAL(cls):
|
|
if cls._EXPERIMENTAL is None:
|
|
cls.GET_SCHEMA()
|
|
return cls._EXPERIMENTAL
|
|
|
|
_DEPRECATED = None
|
|
@classproperty
|
|
def DEPRECATED(cls):
|
|
if cls._DEPRECATED is None:
|
|
cls.GET_SCHEMA()
|
|
return cls._DEPRECATED
|
|
|
|
_API_NODE = None
|
|
@classproperty
|
|
def API_NODE(cls):
|
|
if cls._API_NODE is None:
|
|
cls.GET_SCHEMA()
|
|
return cls._API_NODE
|
|
|
|
_OUTPUT_NODE = None
|
|
@classproperty
|
|
def OUTPUT_NODE(cls):
|
|
if cls._OUTPUT_NODE is None:
|
|
cls.GET_SCHEMA()
|
|
return cls._OUTPUT_NODE
|
|
|
|
_INPUT_IS_LIST = None
|
|
@classproperty
|
|
def INPUT_IS_LIST(cls):
|
|
if cls._INPUT_IS_LIST is None:
|
|
cls.GET_SCHEMA()
|
|
return cls._INPUT_IS_LIST
|
|
_OUTPUT_IS_LIST = None
|
|
|
|
@classproperty
|
|
def OUTPUT_IS_LIST(cls):
|
|
if cls._OUTPUT_IS_LIST is None:
|
|
cls.GET_SCHEMA()
|
|
return cls._OUTPUT_IS_LIST
|
|
|
|
_RETURN_TYPES = None
|
|
@classproperty
|
|
def RETURN_TYPES(cls):
|
|
if cls._RETURN_TYPES is None:
|
|
cls.GET_SCHEMA()
|
|
return cls._RETURN_TYPES
|
|
|
|
_RETURN_NAMES = None
|
|
@classproperty
|
|
def RETURN_NAMES(cls):
|
|
if cls._RETURN_NAMES is None:
|
|
cls.GET_SCHEMA()
|
|
return cls._RETURN_NAMES
|
|
|
|
_OUTPUT_TOOLTIPS = None
|
|
@classproperty
|
|
def OUTPUT_TOOLTIPS(cls):
|
|
if cls._OUTPUT_TOOLTIPS is None:
|
|
cls.GET_SCHEMA()
|
|
return cls._OUTPUT_TOOLTIPS
|
|
|
|
FUNCTION = "execute"
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(cls) -> dict[str, dict]:
|
|
schema = cls.DEFINE_SCHEMA()
|
|
# for V1, make inputs be a dict with potential keys {required, optional, hidden}
|
|
input = {
|
|
"required": {}
|
|
}
|
|
if schema.inputs:
|
|
for i in schema.inputs:
|
|
input.setdefault(i.behavior.value, {})[i.id] = (i.get_io_type_V1(), i.as_dict_V1())
|
|
if schema.hidden:
|
|
for hidden in schema.hidden:
|
|
input.setdefault("hidden", {})[hidden.name] = (hidden.value,)
|
|
return input
|
|
|
|
@classmethod
|
|
def GET_SCHEMA(cls) -> SchemaV3:
|
|
schema = cls.DEFINE_SCHEMA()
|
|
if cls._DESCRIPTION is None:
|
|
cls._DESCRIPTION = schema.description
|
|
if cls._CATEGORY is None:
|
|
cls._CATEGORY = schema.category
|
|
if cls._EXPERIMENTAL is None:
|
|
cls._EXPERIMENTAL = schema.is_experimental
|
|
if cls._DEPRECATED is None:
|
|
cls._DEPRECATED = schema.is_deprecated
|
|
if cls._API_NODE is None:
|
|
cls._API_NODE = schema.is_api_node
|
|
if cls._OUTPUT_NODE is None:
|
|
cls._OUTPUT_NODE = schema.is_output_node
|
|
if cls._INPUT_IS_LIST is None:
|
|
cls._INPUT_IS_LIST = schema.is_input_list
|
|
|
|
if cls._RETURN_TYPES is None:
|
|
output = []
|
|
output_name = []
|
|
output_is_list = []
|
|
output_tooltips = []
|
|
if schema.outputs:
|
|
for o in schema.outputs:
|
|
output.append(o.io_type)
|
|
output_name.append(o.display_name if o.display_name else o.io_type)
|
|
output_is_list.append(o.is_output_list)
|
|
output_tooltips.append(o.tooltip if o.tooltip else None)
|
|
|
|
cls._RETURN_TYPES = output
|
|
cls._RETURN_NAMES = output_name
|
|
cls._OUTPUT_IS_LIST = output_is_list
|
|
cls._OUTPUT_TOOLTIPS = output_tooltips
|
|
|
|
return schema
|
|
|
|
@classmethod
|
|
def GET_NODE_INFO_V1(cls) -> dict[str, Any]:
|
|
schema = cls.GET_SCHEMA()
|
|
# get V1 inputs
|
|
input = cls.INPUT_TYPES()
|
|
|
|
# create separate lists from output fields
|
|
output = []
|
|
output_is_list = []
|
|
output_name = []
|
|
output_tooltips = []
|
|
if schema.outputs:
|
|
for o in schema.outputs:
|
|
output.append(o.io_type)
|
|
output_is_list.append(o.is_output_list)
|
|
output_name.append(o.display_name if o.display_name else o.io_type)
|
|
output_tooltips.append(o.tooltip if o.tooltip else None)
|
|
|
|
info = NodeInfoV1(
|
|
input=input,
|
|
input_order={key: list(value.keys()) for (key, value) in input.items()},
|
|
output=output,
|
|
output_is_list=output_is_list,
|
|
output_name=output_name,
|
|
output_tooltips=output_tooltips,
|
|
name=schema.node_id,
|
|
display_name=schema.display_name,
|
|
category=schema.category,
|
|
description=schema.description,
|
|
output_node=schema.is_output_node,
|
|
deprecated=schema.is_deprecated,
|
|
experimental=schema.is_experimental,
|
|
api_node=schema.is_api_node,
|
|
python_module=getattr(cls, "RELATIVE_PYTHON_MODULE", "nodes")
|
|
)
|
|
return asdict(info)
|
|
#--------------------------------------------
|
|
#############################################
|
|
|
|
|
|
@classmethod
|
|
@abstractmethod
|
|
def DEFINE_SCHEMA(cls) -> SchemaV3:
|
|
"""
|
|
Override this function with one that returns a SchemaV3 instance.
|
|
"""
|
|
return None
|
|
DEFINE_SCHEMA = None
|
|
|
|
def __init__(self):
|
|
if self.DEFINE_SCHEMA is None:
|
|
raise Exception("No DEFINE_SCHEMA function was defined for this node.")
|
|
|
|
@abstractmethod
|
|
def execute(self, inputs, outputs, hidden, **kwargs):
|
|
pass
|
|
|
|
|
|
class ReturnedInputs:
|
|
def __init__(self):
|
|
pass
|
|
|
|
class ReturnedOutputs:
|
|
def __init__(self):
|
|
pass
|
|
|
|
|
|
class NodeOutputV3:
|
|
def __init__(self):
|
|
pass
|
|
|
|
class UINodeOutput:
|
|
def __init__(self):
|
|
pass
|
|
|
|
|
|
class TestNode(ComfyNodeV3):
|
|
SCHEMA = SchemaV3(
|
|
node_id="TestNode_v3",
|
|
display_name="Test Node (V3)",
|
|
category="v3_test",
|
|
inputs=[IntegerInput("my_int"),
|
|
#AutoGrowDynamicInput("growing", ImageInput),
|
|
MaskInput("thing"),
|
|
],
|
|
outputs=[ImageOutput("image_output")],
|
|
hidden=[Hidden.api_key_comfy_org, Hidden.auth_token_comfy_org, Hidden.unique_id]
|
|
)
|
|
|
|
# @classmethod
|
|
# def GET_SCHEMA(cls):
|
|
# return cls.SCHEMA
|
|
|
|
@classmethod
|
|
def DEFINE_SCHEMA(cls):
|
|
return cls.SCHEMA
|
|
|
|
def execute(**kwargs):
|
|
pass
|
|
|
|
|
|
if __name__ == "__main__":
|
|
print("hello there")
|
|
inputs: list[InputV3] = [
|
|
IntegerInput("my_int"),
|
|
CustomInput("xyz", "XYZ"),
|
|
CustomInput("model1", "MODEL_M"),
|
|
ImageInput("my_image"),
|
|
FloatInput("my_float"),
|
|
MultitypedInput("my_inputs", [CustomType("MODEL_M"), CustomType("XYZ")]),
|
|
]
|
|
|
|
outputs: list[OutputV3] = [
|
|
ImageOutput("image"),
|
|
CustomOutput("xyz", "XYZ")
|
|
]
|
|
|
|
for c in inputs:
|
|
if isinstance(c, MultitypedInput):
|
|
print(f"{c}, {type(c)}, {type(c).io_type}, {c.id}, {[x.io_type for x in c.io_types]}")
|
|
print(c.get_io_type_V1())
|
|
else:
|
|
print(f"{c}, {type(c)}, {type(c).io_type}, {c.id}")
|
|
|
|
for c in outputs:
|
|
print(f"{c}, {type(c)}, {type(c).io_type}, {c.id}")
|
|
|
|
zz = TestNode()
|
|
print(zz.GET_NODE_INFO_V1())
|
|
|
|
# aa = NodeInfoV1()
|
|
# print(asdict(aa))
|
|
# print(as_pruned_dict(aa))
|