import torch from comfy_api.v3.io import ( ComfyNodeV3, SchemaV3, CustomType, CustomInput, CustomOutput, InputBehavior, NumberDisplay, IntegerInput, MaskInput, ImageInput, ComboDynamicInput, ) class V3TestNode(ComfyNodeV3): @classmethod def DEFINE_SCHEMA(cls): schema = SchemaV3( node_id="V3TestNode1", display_name="V3 Test Node (1djekjd)", description="This is a funky V3 node test.", category="v3 nodes", inputs=[ IntegerInput("some_int", display_name="new_name", min=0, tooltip="My tooltip 😎"), MaskInput("mask", behavior=InputBehavior.optional), ImageInput("image", display_name="new_image"), # IntegerInput("some_int", display_name="new_name", min=0, tooltip="My tooltip 😎", display=NumberDisplay.slider, ), # ComboDynamicInput("mask", behavior=InputBehavior.optional), # IntegerInput("some_int", display_name="new_name", min=0, tooltip="My tooltip 😎", display=NumberDisplay.slider, # dependent_inputs=[ComboDynamicInput("mask", behavior=InputBehavior.optional)], # dependent_values=[lambda my_value: IO.STRING if my_value < 5 else IO.NUMBER], # ), # ["option1", "option2". "option3"] # ComboDynamicInput["sdfgjhl", [ComboDynamicOptions("option1", [IntegerInput("some_int", display_name="new_name", min=0, tooltip="My tooltip 😎", display=NumberDisplay.slider, ImageInput(), MaskInput(), String()]), # CombyDynamicOptons("option2", []) # ]] ], is_output_node=True, ) return schema def execute(self, some_int: int, image: torch.Tensor, mask: torch.Tensor=None, **kwargs): return (None,) NODES: list[ComfyNodeV3] = [ V3TestNode, ] NODE_CLASS_MAPPINGS = {} NODE_DISPLAY_NAME_MAPPINGS = {} for node in NODES: schema = node.GET_SCHEMA() NODE_CLASS_MAPPINGS[schema.node_id] = node if schema.display_name: NODE_DISPLAY_NAME_MAPPINGS[schema.node_id] = schema.display_name