mirror of
https://github.com/comfyanonymous/ComfyUI.git
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[Developer Experience] Add node typing (#5676)
* [Developer Experience] Add node typing * Shim StrEnum * nit * nit * nit
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.github/workflows/test-launch.yml
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.github/workflows/test-launch.yml
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@ -28,7 +28,7 @@ jobs:
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- name: Start ComfyUI server
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run: |
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python main.py --cpu 2>&1 | tee console_output.log &
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wait-for-it --service 127.0.0.1:8188 -t 600
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wait-for-it --service 127.0.0.1:8188 -t 30
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working-directory: ComfyUI
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- name: Check for unhandled exceptions in server log
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run: |
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43
comfy/comfy_types/README.md
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43
comfy/comfy_types/README.md
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@ -0,0 +1,43 @@
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# Comfy Typing
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## Type hinting for ComfyUI Node development
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This module provides type hinting and concrete convenience types for node developers.
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If cloned to the custom_nodes directory of ComfyUI, types can be imported using:
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```python
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from comfy_types import IO, ComfyNodeABC, CheckLazyMixin
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class ExampleNode(ComfyNodeABC):
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@classmethod
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def INPUT_TYPES(s) -> InputTypeDict:
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return {"required": {}}
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```
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Full example is in [examples/example_nodes.py](examples/example_nodes.py).
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# Types
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A few primary types are documented below. More complete information is available via the docstrings on each type.
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## `IO`
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A string enum of built-in and a few custom data types. Includes the following special types and their requisite plumbing:
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- `ANY`: `"*"`
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- `NUMBER`: `"FLOAT,INT"`
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- `PRIMITIVE`: `"STRING,FLOAT,INT,BOOLEAN"`
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## `ComfyNodeABC`
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An abstract base class for nodes, offering type-hinting / autocomplete, and somewhat-alright docstrings.
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### Type hinting for `INPUT_TYPES`
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![INPUT_TYPES auto-completion in Visual Studio Code](examples/input_types.png)
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### `INPUT_TYPES` return dict
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![INPUT_TYPES return value type hinting in Visual Studio Code](examples/required_hint.png)
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### Options for individual inputs
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![INPUT_TYPES return value option auto-completion in Visual Studio Code](examples/input_options.png)
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@ -1,5 +1,6 @@
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import torch
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from typing import Callable, Protocol, TypedDict, Optional, List
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from .node_typing import IO, InputTypeDict, ComfyNodeABC, CheckLazyMixin
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class UnetApplyFunction(Protocol):
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@ -30,3 +31,15 @@ class UnetParams(TypedDict):
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UnetWrapperFunction = Callable[[UnetApplyFunction, UnetParams], torch.Tensor]
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__all__ = [
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"UnetWrapperFunction",
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UnetApplyConds.__name__,
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UnetParams.__name__,
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UnetApplyFunction.__name__,
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IO.__name__,
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InputTypeDict.__name__,
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ComfyNodeABC.__name__,
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CheckLazyMixin.__name__,
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]
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28
comfy/comfy_types/examples/example_nodes.py
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comfy/comfy_types/examples/example_nodes.py
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from comfy_types import IO, ComfyNodeABC, InputTypeDict
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from inspect import cleandoc
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class ExampleNode(ComfyNodeABC):
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"""An example node that just adds 1 to an input integer.
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* Requires an IDE configured with analysis paths etc to be worth looking at.
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* Not intended for use in ComfyUI.
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"""
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DESCRIPTION = cleandoc(__doc__)
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CATEGORY = "examples"
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@classmethod
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def INPUT_TYPES(s) -> InputTypeDict:
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return {
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"required": {
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"input_int": (IO.INT, {"defaultInput": True}),
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}
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}
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RETURN_TYPES = (IO.INT,)
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RETURN_NAMES = ("input_plus_one",)
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FUNCTION = "execute"
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def execute(self, input_int: int):
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return (input_int + 1,)
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comfy/comfy_types/examples/input_options.png
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comfy/comfy_types/examples/input_options.png
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comfy/comfy_types/examples/input_types.png
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comfy/comfy_types/examples/input_types.png
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comfy/comfy_types/examples/required_hint.png
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comfy/comfy_types/examples/required_hint.png
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274
comfy/comfy_types/node_typing.py
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comfy/comfy_types/node_typing.py
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"""Comfy-specific type hinting"""
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from __future__ import annotations
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from typing import Literal, TypedDict
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from abc import ABC, abstractmethod
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from enum import Enum
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class StrEnum(str, Enum):
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"""Base class for string enums. Python's StrEnum is not available until 3.11."""
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def __str__(self) -> str:
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return self.value
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class IO(StrEnum):
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"""Node input/output data types.
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Includes functionality for ``"*"`` (`ANY`) and ``"MULTI,TYPES"``.
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"""
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STRING = "STRING"
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IMAGE = "IMAGE"
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MASK = "MASK"
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LATENT = "LATENT"
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BOOLEAN = "BOOLEAN"
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INT = "INT"
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FLOAT = "FLOAT"
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CONDITIONING = "CONDITIONING"
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SAMPLER = "SAMPLER"
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SIGMAS = "SIGMAS"
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GUIDER = "GUIDER"
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NOISE = "NOISE"
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CLIP = "CLIP"
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CONTROL_NET = "CONTROL_NET"
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VAE = "VAE"
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MODEL = "MODEL"
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CLIP_VISION = "CLIP_VISION"
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CLIP_VISION_OUTPUT = "CLIP_VISION_OUTPUT"
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STYLE_MODEL = "STYLE_MODEL"
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GLIGEN = "GLIGEN"
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UPSCALE_MODEL = "UPSCALE_MODEL"
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AUDIO = "AUDIO"
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WEBCAM = "WEBCAM"
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POINT = "POINT"
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FACE_ANALYSIS = "FACE_ANALYSIS"
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BBOX = "BBOX"
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SEGS = "SEGS"
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ANY = "*"
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"""Always matches any type, but at a price.
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Causes some functionality issues (e.g. reroutes, link types), and should be avoided whenever possible.
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"""
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NUMBER = "FLOAT,INT"
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"""A float or an int - could be either"""
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PRIMITIVE = "STRING,FLOAT,INT,BOOLEAN"
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"""Could be any of: string, float, int, or bool"""
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def __ne__(self, value: object) -> bool:
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if self == "*" or value == "*":
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return False
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if not isinstance(value, str):
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return True
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a = frozenset(self.split(","))
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b = frozenset(value.split(","))
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return not (b.issubset(a) or a.issubset(b))
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class InputTypeOptions(TypedDict):
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"""Provides type hinting for the return type of the INPUT_TYPES node function.
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Due to IDE limitations with unions, for now all options are available for all types (e.g. `label_on` is hinted even when the type is not `IO.BOOLEAN`).
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Comfy Docs: https://docs.comfy.org/essentials/custom_node_datatypes
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"""
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default: bool | str | float | int | list | tuple
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"""The default value of the widget"""
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defaultInput: bool
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"""Defaults to an input slot rather than a widget"""
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forceInput: bool
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"""`defaultInput` and also don't allow converting to a widget"""
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lazy: bool
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"""Declares that this input uses lazy evaluation"""
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rawLink: bool
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"""When a link exists, rather than receiving the evaluated value, you will receive the link (i.e. `["nodeId", <outputIndex>]`). Designed for node expansion."""
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tooltip: str
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"""Tooltip for the input (or widget), shown on pointer hover"""
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# class InputTypeNumber(InputTypeOptions):
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# default: float | int
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min: float
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"""The minimum value of a number (``FLOAT`` | ``INT``)"""
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max: float
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"""The maximum value of a number (``FLOAT`` | ``INT``)"""
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step: float
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"""The amount to increment or decrement a widget by when stepping up/down (``FLOAT`` | ``INT``)"""
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round: float
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"""Floats are rounded by this value (``FLOAT``)"""
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# class InputTypeBoolean(InputTypeOptions):
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# default: bool
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label_on: str
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"""The label to use in the UI when the bool is True (``BOOLEAN``)"""
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label_on: str
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"""The label to use in the UI when the bool is False (``BOOLEAN``)"""
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# class InputTypeString(InputTypeOptions):
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# default: str
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multiline: bool
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"""Use a multiline text box (``STRING``)"""
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placeholder: str
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"""Placeholder text to display in the UI when empty (``STRING``)"""
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# Deprecated:
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# defaultVal: str
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dynamicPrompts: bool
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"""Causes the front-end to evaluate dynamic prompts (``STRING``)"""
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class HiddenInputTypeDict(TypedDict):
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"""Provides type hinting for the hidden entry of node INPUT_TYPES."""
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node_id: Literal["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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unique_id: Literal["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: Literal["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: Literal["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: Literal["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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class InputTypeDict(TypedDict):
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"""Provides type hinting for node INPUT_TYPES.
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Comfy Docs: https://docs.comfy.org/essentials/custom_node_more_on_inputs
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"""
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required: dict[str, tuple[IO, InputTypeOptions]]
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"""Describes all inputs that must be connected for the node to execute."""
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optional: dict[str, tuple[IO, InputTypeOptions]]
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"""Describes inputs which do not need to be connected."""
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hidden: HiddenInputTypeDict
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"""Offers advanced functionality and server-client communication.
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Comfy Docs: https://docs.comfy.org/essentials/custom_node_more_on_inputs#hidden-inputs
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"""
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class ComfyNodeABC(ABC):
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"""Abstract base class for Comfy nodes. Includes the names and expected types of attributes.
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Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview
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"""
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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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Usage::
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# Explicitly define the description
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DESCRIPTION = "Example description here."
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# Use the docstring of the node class.
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DESCRIPTION = cleandoc(__doc__)
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"""
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CATEGORY: str
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"""The category of the node, as per the "Add Node" menu.
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Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview#category
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"""
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EXPERIMENTAL: bool
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"""Flags a node as experimental, informing users that it may change or not work as expected."""
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DEPRECATED: bool
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"""Flags a node as deprecated, indicating to users that they should find alternatives to this node."""
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@classmethod
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@abstractmethod
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def INPUT_TYPES(s) -> InputTypeDict:
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"""Defines node inputs.
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* Must include the ``required`` key, which describes all inputs that must be connected for the node to execute.
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* The ``optional`` key can be added to describe inputs which do not need to be connected.
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* The ``hidden`` key offers some advanced functionality. More info at: https://docs.comfy.org/essentials/custom_node_more_on_inputs#hidden-inputs
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Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview#input-types
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"""
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return {"required": {}}
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OUTPUT_NODE: bool
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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/essentials/custom_node_server_overview#output-node
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"""
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INPUT_IS_LIST: bool
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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/essentials/custom_node_lists#list-processing
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"""
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OUTPUT_IS_LIST: tuple[bool]
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"""A tuple indicating which node outputs are lists, but will be connected to nodes that expect individual items.
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Connected nodes that do not implement `INPUT_IS_LIST` will be executed once for every item in the list.
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A ``tuple[bool]``, where the items match those in `RETURN_TYPES`::
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RETURN_TYPES = (IO.INT, IO.INT, IO.STRING)
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OUTPUT_IS_LIST = (True, True, False) # The string output will be handled normally
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From the docs:
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In order to tell Comfy that the list being returned should not be wrapped, but treated as a series of data for sequential processing,
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the node should provide a class attribute `OUTPUT_IS_LIST`, which is a ``tuple[bool]``, of the same length as `RETURN_TYPES`,
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specifying which outputs which should be so treated.
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Comfy Docs: https://docs.comfy.org/essentials/custom_node_lists#list-processing
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"""
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RETURN_TYPES: tuple[IO]
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"""A tuple representing the outputs of this node.
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Usage::
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RETURN_TYPES = (IO.INT, "INT", "CUSTOM_TYPE")
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Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview#return-types
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"""
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RETURN_NAMES: tuple[str]
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"""The output slot names for each item in `RETURN_TYPES`, e.g. ``RETURN_NAMES = ("count", "filter_string")``
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Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview#return-names
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"""
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OUTPUT_TOOLTIPS: tuple[str]
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"""A tuple of strings to use as tooltips for node outputs, one for each item in `RETURN_TYPES`."""
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FUNCTION: str
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"""The name of the function to execute as a literal string, e.g. `FUNCTION = "execute"`
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Comfy Docs: https://docs.comfy.org/essentials/custom_node_server_overview#function
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"""
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class CheckLazyMixin:
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"""Provides a basic check_lazy_status implementation and type hinting for nodes that use lazy inputs."""
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def check_lazy_status(self, **kwargs) -> list[str]:
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"""Returns a list of input names that should be evaluated.
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This basic mixin impl. requires all inputs.
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:kwargs: All node inputs will be included here. If the input is ``None``, it should be assumed that it has not yet been evaluated. \
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When using ``INPUT_IS_LIST = True``, unevaluated will instead be ``(None,)``.
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Params should match the nodes execution ``FUNCTION`` (self, and all inputs by name).
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Will be executed repeatedly until it returns an empty list, or all requested items were already evaluated (and sent as params).
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Comfy Docs: https://docs.comfy.org/essentials/custom_node_lazy_evaluation#defining-check-lazy-status
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"""
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need = [name for name in kwargs if kwargs[name] is None]
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return need
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12
nodes.py
12
nodes.py
@ -1,3 +1,4 @@
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from __future__ import annotations
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import torch
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import os
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@ -24,6 +25,7 @@ import comfy.sample
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import comfy.sd
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import comfy.utils
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import comfy.controlnet
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from comfy.comfy_types import IO, ComfyNodeABC, InputTypeDict
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import comfy.clip_vision
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@ -44,16 +46,16 @@ def interrupt_processing(value=True):
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MAX_RESOLUTION=16384
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class CLIPTextEncode:
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class CLIPTextEncode(ComfyNodeABC):
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@classmethod
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def INPUT_TYPES(s):
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def INPUT_TYPES(s) -> InputTypeDict:
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return {
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"required": {
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"text": ("STRING", {"multiline": True, "dynamicPrompts": True, "tooltip": "The text to be encoded."}),
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"clip": ("CLIP", {"tooltip": "The CLIP model used for encoding the text."})
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"text": (IO.STRING, {"multiline": True, "dynamicPrompts": True, "tooltip": "The text to be encoded."}),
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"clip": (IO.CLIP, {"tooltip": "The CLIP model used for encoding the text."})
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}
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}
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RETURN_TYPES = ("CONDITIONING",)
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RETURN_TYPES = (IO.CONDITIONING,)
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OUTPUT_TOOLTIPS = ("A conditioning containing the embedded text used to guide the diffusion model.",)
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FUNCTION = "encode"
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