Refactoring: Started migration to ComfyUI API v3
This commit is contained in:
TenserTensor
+2
-4
@@ -1,17 +1,15 @@
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# (c) TenserTensor || Apache-2.0 (apache.org/licenses/LICENSE-2.0)
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from .node_mappings import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS, RESET, BRIGHT_GREEN, BRIGHT_CYAN, CYAN, YELLOW
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from .node_mappings import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS, NODES_COUNT, RESET, BRIGHT_GREEN, BRIGHT_CYAN, CYAN, YELLOW
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WEB_DIRECTORY = "./web"
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__all__ = ['NODE_CLASS_MAPPINGS', 'NODE_DISPLAY_NAME_MAPPINGS', 'WEB_DIRECTORY']
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nodes_count = len(NODE_CLASS_MAPPINGS)
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print()
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SEP = f"{CYAN}{'=' * 60}{RESET}"
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print(SEP)
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print(f"{YELLOW}TenserTensor ComfyUI Nodes Pack (v1.4.7): {BRIGHT_GREEN}{nodes_count} Nodes Loaded{RESET}")
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print(f"{YELLOW}TenserTensor ComfyUI Nodes Pack (v1.4.7): {BRIGHT_GREEN}{NODES_COUNT} Nodes Loaded{RESET}")
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print(SEP)
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print(f"{BRIGHT_CYAN}[V] Repository: https://github.com/tenser-tensor/ComfyUI-TenserTensor{RESET}")
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print(f"{BRIGHT_CYAN}[V] ComfyUI Registry: https://registry.comfy.org/publishers/tenser-tensor{RESET}")
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@@ -0,0 +1,141 @@
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# (c) TenserTensor || Apache-2.0 (apache.org/licenses/LICENSE-2.0)
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import dataclasses
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import re
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from typing import override
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import torch
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from comfy.clip_vision import Output
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from comfy_api.latest import IO, ComfyExtension, Input
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from .lib.common import Context, TTContext
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CATEGORY = "TenserTensor/Context"
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class ContextNode(IO.ComfyNode):
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"""
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Abstract base class for all context nodes.
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Handles context creation, delegation to handle(), and building return tuple.
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Subclasses should set INPUT_TYPES_DICT, RETURN_TYPES, RETURN_NAMES from a Schema,
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and override handle() to implement node-specific logic.
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"""
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REQUIRED = ()
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OPTIONAL = ()
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RETURNS = ()
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F_TYPES = {}
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@classmethod
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def fill_field_types(cls):
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cls.F_TYPES = {f.name: f.type.__args__[0] for f in dataclasses.fields(TTContext)}
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@classmethod
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def inputs(cls) -> list[Input]:
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def get_input(input_name, optional):
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return Context.Input("context", optional=optional) if input_name == "context" else cls.F_TYPES[input_name].Input(input_name,
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optional=optional)
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len(cls.F_TYPES) == 0 and cls.fill_field_types()
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input_schema = []
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for f_name in cls.REQUIRED:
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input_schema.append(get_input(f_name, optional=False))
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for f_name in cls.OPTIONAL:
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input_schema.append(get_input(f_name, optional=True))
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return input_schema
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@classmethod
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def outputs(cls) -> list[Output]:
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len(cls.F_TYPES) == 0 and cls.fill_field_types()
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output_schema = []
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for f_name in cls.RETURNS if len(cls.RETURNS) > 0 else cls.OPTIONAL:
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output_schema.append(
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Context.Output(display_name="CONTEXT") if f_name == "context" else cls.F_TYPES[f_name].Output(display_name=f_name.upper()))
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return output_schema
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@classmethod
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def node_output(cls, context, **kwargs) -> IO.NodeOutput:
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args = {}
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for f_name in cls.RETURNS if len(cls.RETURNS) > 0 else cls.OPTIONAL:
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if f_name != "context":
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args[f_name.upper()] = kwargs.get(f_name)
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return IO.NodeOutput(**{{"context": context}, args})
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@classmethod
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def display_name(cls):
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return re.sub(r'(?<=[a-z])(?=[A-Z])', ' ', cls.__name__.replace("TT_", "TT ").replace("Node", ""))
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@classmethod
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def define_schema(cls) -> IO.Schema:
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return IO.Schema(
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node_id=cls.__name__,
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display_name=cls.display_name(),
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category=CATEGORY,
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inputs=cls.inputs(),
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outputs=cls.outputs(),
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)
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@classmethod
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def handle(cls, context, **kwargs):
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return (context, kwargs,)
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@classmethod
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def execute(cls, context=None, **kwargs) -> IO.NodeOutput:
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context = TTContext.create(**kwargs) if not context else context
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context, kwargs = cls.handle(context, **kwargs)
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return cls.node_output(context, **kwargs)
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class TT_BaseContextNode(ContextNode):
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"""Base context node. Accepts model, clip, vae, latent and optional workflow_config."""
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REQUIRED = ("model", "clip", "vae", "latent")
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OPTIONAL = ("workflow_config",)
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RETURNS = ("context",)
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class TT_BaseContextFlux2Node(ContextNode):
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"""
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Base context node for FLUX2 workflows. Accepts model, clip, vae, latent, sampler, noise, and sigmas.
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Optionally accepts workflow_config. Returns context.
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"""
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REQUIRED = ("model", "clip", "vae", "latent", "sampler", "rnd_noise", "sigmas",)
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OPTIONAL = ("workflow_config",)
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RETURNS = ("context",)
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class TT_BaseContextPassthroughNode(ContextNode):
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"""Passes context through without modification."""
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REQUIRED = ("context",)
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OPTIONAL = ()
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RETURNS = ("context",)
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class ContextExtension(ComfyExtension):
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@override
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async def get_node_list(self) -> list[type[IO.ComfyNode]]:
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return [
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TT_BaseContextNode,
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TT_BaseContextFlux2Node,
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]
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async def comfy_entrypoint() -> ContextExtension:
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return ContextExtension()
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# ==============================================================================
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# Re-exports for backward compatibility
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# ==============================================================================
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__all__ = [
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"TT_BaseContextNode",
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"TT_BaseContextFlux2Node",
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"TT_BaseContextPassthroughNode",
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]
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+118
@@ -1,4 +1,12 @@
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# (c) TenserTensor || Apache-2.0 (apache.org/licenses/LICENSE-2.0)
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import dataclasses
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from dataclasses import dataclass
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import comfy.samplers as S
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from comfy_api.latest import IO
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from .workflow_classes import TTWorkflowSettings
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class BasicGuider(S.CFGGuider):
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@@ -11,3 +19,113 @@ class BasicGuider(S.CFGGuider):
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class CommonTypes():
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MEGAPIXELS = ["0.25 MP", "0.5 MP", "1 MP", "2 MP", "4 MP", "8 MP"]
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@IO.comfytype(io_type="TT_WORKFLOW_CONFIG")
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class WorkflowSettings:
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Type = TTWorkflowSettings
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class Input(IO.Input):
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def __init__(self, id: str, **kwargs):
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super().__init__(id, **kwargs)
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class Output(IO.Output):
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def __init__(self, **kwargs):
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super().__init__(**kwargs)
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@dataclass
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class TTContext():
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"""
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Shared context object passed between TenserTensor context nodes.
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Holds all pipeline state as optional fields.
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All fields default to None and are populated incrementally as the workflow progresses.
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Use create() to instantiate from kwargs, and set_attr/get_attr for safe field access.
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Workflow config fields are accessible via set_workflow_config_attr/get_workflow_config_attr.
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"""
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model: IO.Model | None = None
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clip: IO.Clip | None = None
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vae: IO.Vae | None = None
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guider: IO.Guider | None = None
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latent: IO.Latent | None = None
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positive: IO.Conditioning | None = None
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negative: IO.Conditioning | None = None
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conditioning: IO.Conditioning | None = None
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image: IO.Image | None = None
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mask: IO.Mask | None = None
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control_net: IO.ControlNet | None = None
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workflow_config: WorkflowSettings | None = None
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sampler_name: IO.String | None = None
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sampler: IO.Sampler | None = None
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scheduler: list[str] | None = None
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rnd_noise: IO.Noise | None = None
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sigmas: IO.Sigmas | None = None
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@classmethod
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def create(cls, **kwargs):
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ctx = cls()
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for field in dataclasses.fields(ctx):
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setattr(ctx, field.name, kwargs.get(field.name, None))
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return ctx
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@classmethod
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def get_attr_type(cls, key):
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return
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def set_attr(self, key, attr):
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if hasattr(self, key):
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setattr(self, key, attr)
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else:
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raise AttributeError(f"ERROR: Context has no attribute '{key}'")
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def get_attr(self, key, default=None):
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if hasattr(self, key):
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val = getattr(self, key)
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return val if val is not None else default
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else:
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raise AttributeError(f"ERROR: Context has no attribute '{key}'")
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def update_attrs(self, **kwargs):
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for key in kwargs.keys():
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if hasattr(self, key):
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val = kwargs.get(key)
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if val is not None:
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setattr(self, key, val)
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def set_workflow_config_attr(self, key, attr):
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if self.workflow_config:
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self.workflow_config.set_attr(key, attr)
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else:
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raise AttributeError(f"ERROR: Workflow Config is not set in context")
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def get_workflow_config_attr(self, key, default=None):
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if self.workflow_config:
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return self.workflow_config.get_attr(key, default)
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else:
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raise AttributeError(f"ERROR: Workflow Config is not set in context")
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def update_workflow_config_attrs(self, **kwargs):
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if self.workflow_config:
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for key in kwargs.keys():
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if hasattr(self.workflow_config, key):
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val = kwargs.get(key)
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if val is not None:
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self.workflow_config.set_attr(key, val)
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else:
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raise AttributeError(f"ERROR: Workflow Config is not set in context")
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@IO.comfytype(io_type="TT_CONTEXT")
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class Context:
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Type = TTContext
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class Input(IO.Input):
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def __init__(self, id: str, **kwargs):
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super().__init__(id, **kwargs)
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class Output(IO.Output):
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def __init__(self, **kwargs):
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super().__init__(**kwargs)
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@@ -0,0 +1,52 @@
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# (c) TenserTensor || Apache-2.0 (apache.org/licenses/LICENSE-2.0)
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import dataclasses
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from dataclasses import dataclass
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from comfy.samplers import KSampler
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@dataclass
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class TTWorkflowSettings():
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seed: int | None = None
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steps: int | None = None
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cfg: int | None = None
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sampler_name: list[str] | None = None
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scheduler_name: list[str] | None = None
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clip_l_positive: str | None = None
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clip_g_positive: str | None = None
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t5xxl_positive: str | None = None
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clip_l_negative: str | None = None
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clip_g_negative: str | None = None
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t5xxl_negative: str | None = None
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guidance: float | None = None
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ascore_positive: float | None = None
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ascore_negative: float | None = None
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width: int | None = None
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height: int | None = None
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target_width: int | None = None
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target_height: int | None = None
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@classmethod
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def create(cls, **kwargs):
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wf = cls()
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for field in dataclasses.fields(wf):
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setattr(wf, field.name, kwargs.get(field.name, None))
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setattr(wf, "sampler_name", KSampler.SAMPLERS)
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setattr(wf, "scheduler_name", KSampler.SCHEDULERS)
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return wf
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def set_attr(self, key, attr):
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if hasattr(self, key):
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setattr(self, key, attr)
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else:
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raise AttributeError(f"ERROR: Context has no attribute '{key}'")
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def get_attr(self, key, default=None):
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if hasattr(self, key):
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val = getattr(self, key)
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return val if val is not None else default
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else:
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raise AttributeError(f"ERROR: Context has no attribute '{key}'")
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+56
-20
@@ -11,90 +11,120 @@ WHITE = "\033[37m"
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BRIGHT_GREEN = "\033[92m"
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BRIGHT_CYAN = "\033[96m"
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NODES_COUNT = 0
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try:
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before = set(dir())
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from .context_nodes import *
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from .nodes.context.base_context import TT_BaseContext
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from .nodes.context.context import TT_Context
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from .nodes.context.context_passthrough import TT_ContextPassthrough
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from .nodes.context.context_set_guider import TT_ContextSetGuider
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from .nodes.context.context_set_image import TT_ContextSetImage
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from .nodes.context.context_set_latent import TT_ContextSetLatent
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from .nodes.context.context_set_guider import TT_ContextSetGuider
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from .nodes.context.even_larger_context import TT_EvenLargerContext
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from .nodes.context.large_context_flux import TT_LargeContextFlux
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from .nodes.context.large_context_sdxl import TT_LargeContextSdxl
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except ImportError:
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print(f"{YELLOW}TenserTensor: {RED}ERROR: Context nodes unavailable{RESET}")
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try:
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from .nodes.image.image_preview_save import TT_ImagePreviewSave
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from .nodes.image.image_preview_upscale_save import TT_ImagePreviewUpscaleSave
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from .nodes.image.guider_image_reference import TT_GuiderImageReference
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NODES_COUNT += len(set(dir()) - before)
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except ImportError:
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print(f"{YELLOW}TenserTensor: {RED}ERROR: Image nodes unavailable{RESET}")
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try:
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before = set(dir())
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from .nodes.image.image_preview_save import TT_ImagePreviewSave
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from .nodes.image.image_preview_upscale_save import TT_ImagePreviewUpscaleSave
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from .nodes.image.guider_image_reference import TT_GuiderImageReference
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NODES_COUNT += len(set(dir()) - before)
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except ImportError:
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print(f"{YELLOW}TenserTensor: {RED}ERROR: Image nodes unavailable{RESET}")
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try:
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before = set(dir())
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from .nodes.latent.latent_factory import TT_LatentFactory
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NODES_COUNT += len(set(dir()) - before)
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except ImportError:
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print(f"{YELLOW}TenserTensor: {RED}ERROR: Latent nodes unavailable{RESET}")
|
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|
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try:
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before = set(dir())
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from .nodes.loaders.flux_models_loader import TT_FluxModelsLoader
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from .nodes.loaders.flux_models_loader_advanced import TT_FluxModelsLoaderAdvanced
|
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from .nodes.loaders.gguf_models_loader import TT_Flux2GgufModelsLoader
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from .nodes.loaders.gguf_models_loader_advanced import TT_Flux2GgufModelsLoaderAdvanced
|
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from .nodes.loaders.sdxl_models_loader import TT_SdxlModelsLoader
|
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from .nodes.loaders.sdxl_models_loader_advanced import TT_SdxlModelsLoaderAdvanced
|
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|
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NODES_COUNT += len(set(dir()) - before)
|
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except ImportError:
|
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print(f"{YELLOW}TenserTensor: {RED}ERROR: Loader nodes unavailable{RESET}")
|
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|
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try:
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before = set(dir())
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from .nodes.postproduction.add_film_grain import TT_AddFilmGrain
|
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from .nodes.postproduction.apply_lut import TT_ApplyLut
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from .nodes.postproduction.image_enhancer import TT_ImageEnhancer
|
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from .nodes.postproduction.postproduction import TT_Postproduction
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from .nodes.postproduction.postproduction_advanced import TT_PostproductionAdvanced
|
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from .nodes.postproduction.quick_image_upscaler import TT_QuickImageUpscaler
|
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|
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NODES_COUNT += len(set(dir()) - before)
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except ImportError:
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print(f"{YELLOW}TenserTensor: {RED}ERROR: Postproduction nodes unavailable{RESET}")
|
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|
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try:
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before = set(dir())
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from .nodes.sampling.ksampler import TT_KSampler
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from .nodes.sampling.ksampler_advanced import TT_KSamplerAdvanced
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from .nodes.sampling.ksampler_context import TT_KSamplerContext
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from .nodes.sampling.ksampler_two_stage import TT_KSamplerTwoStage
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from .nodes.sampling.ksampler_guided import TT_KSamplerGuided
|
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|
||||
NODES_COUNT += len(set(dir()) - before)
|
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except ImportError:
|
||||
print("f{YELLOW}TenserTensor: {RED}ERROR: Sampler nodes unavailable{RESET}")
|
||||
|
||||
try:
|
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before = set(dir())
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from .nodes.text_encoders.clip_text_encode_flux import TT_ClipTextEncodeFlux
|
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from .nodes.text_encoders.clip_text_encode_flux_context import TT_ClipTextEncodeFluxContext
|
||||
from .nodes.text_encoders.clip_text_encode_sdxl import TT_ClipTextEncodeSdxl
|
||||
from .nodes.text_encoders.clip_text_encode_sdxl_context import TT_ClipTextEncodeSdxlContext
|
||||
from .nodes.text_encoders.clip_text_encode_flux2 import TT_ClipTextEncodeFlux2
|
||||
from .nodes.text_encoders.clip_text_encode_flux2_context import TT_ClipTextEncodeFlux2Context
|
||||
|
||||
NODES_COUNT += len(set(dir()) - before)
|
||||
except ImportError:
|
||||
print(f"{YELLOW}TenserTensor: {RED}ERROR: Text Encoder nodes unavailable{RESET}")
|
||||
|
||||
try:
|
||||
before = set(dir())
|
||||
from .nodes.vae.vae_decode_context import TT_VaeDecodeContext
|
||||
from .nodes.vae.vae_decode_tiled import TT_VaeDecodeTiled
|
||||
from .nodes.vae.vae_encode_context import TT_VaeEncodeContext
|
||||
from .nodes.vae.vae_encode_tiled import TT_VaeEncodeTiled
|
||||
|
||||
NODES_COUNT += len(set(dir()) - before)
|
||||
except ImportError:
|
||||
print(f"{YELLOW}TenserTensor: {RED}ERROR: VAE nodes unavailable{RESET}")
|
||||
|
||||
try:
|
||||
before = set(dir())
|
||||
from .nodes.workflow.flux_workflow_settings import TT_FluxWorkflowSettings
|
||||
from .nodes.workflow.flux_workflow_settings_advanced import TT_FluxWorkflowSettingsAdvanced
|
||||
from .nodes.workflow.sdxl_workflow_settings import TT_SdxlWorkflowSettings
|
||||
from .nodes.workflow.sdxl_workflow_settings_advanced import TT_SdxlWorkflowSettingsAdvanced
|
||||
from .nodes.workflow.flux2_workflow_settings import TT_Flux2WorkflowSettings
|
||||
from .nodes.workflow.flux2_workflow_settings_advanced import TT_Flux2WorkflowSettingsAdvanced
|
||||
|
||||
NODES_COUNT += len(set(dir()) - before)
|
||||
except ImportError:
|
||||
print(f"{YELLOW}TenserTensor: {RED}ERROR: Workflow nodes unavailable{RESET}")
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
# Context
|
||||
# Context Deprecated
|
||||
"TT_BaseContext": TT_BaseContext,
|
||||
"TT_Context": TT_Context,
|
||||
"TT_LargeContextFlux": TT_LargeContextFlux,
|
||||
@@ -103,8 +133,11 @@ NODE_CLASS_MAPPINGS = {
|
||||
"TT_ContextSetImage": TT_ContextSetImage,
|
||||
"TT_ContextSetLatent": TT_ContextSetLatent,
|
||||
"TT_ContextSetGuider": TT_ContextSetGuider,
|
||||
# Context Passthrough
|
||||
"TT_ContextPassthrough": TT_ContextPassthrough,
|
||||
# Context V3 Nodes
|
||||
"TT_BaseContextNode": TT_BaseContextNode,
|
||||
"TT_BaseContextFlux2Node": TT_BaseContextFlux2Node,
|
||||
"TT_BaseContextPassthroughNode": TT_BaseContextPassthroughNode,
|
||||
# Image
|
||||
"TT_ImagePreviewSave": TT_ImagePreviewSave,
|
||||
"TT_ImagePreviewUpscaleSave": TT_ImagePreviewUpscaleSave,
|
||||
@@ -153,17 +186,20 @@ NODE_CLASS_MAPPINGS = {
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
# Context
|
||||
"TT_BaseContext": "TT Base Context",
|
||||
"TT_Context": "TT Context",
|
||||
"TT_LargeContextFlux": "TT FLUX Large Context",
|
||||
"TT_LargeContextSdxl": "TT SDXL Large Context",
|
||||
"TT_EvenLargerContext": "TT Even Larger Context",
|
||||
"TT_ContextSetImage": "TT Context Set Image",
|
||||
"TT_ContextSetLatent": "TT Context Set Latent",
|
||||
"TT_ContextSetGuider": "TT Context Set Guider",
|
||||
# Context Passthrough
|
||||
"TT_ContextPassthrough": "TT Context Passthrough",
|
||||
# Context Deprecated
|
||||
"TT_BaseContext": "TT Base Context (Deprecated)",
|
||||
"TT_Context": "TT Context (Deprecated)",
|
||||
"TT_LargeContextFlux": "TT FLUX Large Context (Deprecated)",
|
||||
"TT_LargeContextSdxl": "TT SDXL Large Context (Deprecated)",
|
||||
"TT_EvenLargerContext": "TT Even Larger Context (Deprecated)",
|
||||
"TT_ContextSetImage": "TT Context Set Image (Deprecated)",
|
||||
"TT_ContextSetLatent": "TT Context Set Latent (Deprecated)",
|
||||
"TT_ContextSetGuider": "TT Context Set Guider (Deprecated)",
|
||||
"TT_ContextPassthrough": "TT Context Passthrough (Deprecated)",
|
||||
# Context V3 Nodes
|
||||
"TT_BaseContextNode": "TT Base Context",
|
||||
"TT_BaseContextFlux2Node": "TT FLUX2 Base Context",
|
||||
"TT_BaseContextPassthroughNode": "TT Context Passthrough",
|
||||
# Image
|
||||
"TT_ImagePreviewSave": "TT Image Preview / Save",
|
||||
"TT_ImagePreviewUpscaleSave": "TT Image Preview / Upscale / Save",
|
||||
|
||||
@@ -6,7 +6,7 @@ from .context_helpers import create_context_schema
|
||||
class TT_BaseContext:
|
||||
INPUT_TYPES_DICT, RETURN_TYPES, RETURN_NAMES = create_context_schema("base")
|
||||
FUNCTION = "process_context"
|
||||
CATEGORY = "TenserTensor/Context"
|
||||
CATEGORY = "TenserTensor/Deprecated/Context"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
|
||||
@@ -6,7 +6,7 @@ from .context_helpers import (build_return_tuple, create_context_schema, init_co
|
||||
class TT_Context:
|
||||
INPUT_TYPES_DICT, RETURN_TYPES, RETURN_NAMES = create_context_schema("standard")
|
||||
FUNCTION = "process_context"
|
||||
CATEGORY = "TenserTensor/Context"
|
||||
CATEGORY = "TenserTensor/Deprecated/Context"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
|
||||
@@ -6,7 +6,7 @@ from .context_helpers import (build_return_tuple, create_context_schema, init_co
|
||||
class TT_ContextPassthrough:
|
||||
INPUT_TYPES_DICT, RETURN_TYPES, RETURN_NAMES = create_context_schema("passthrough")
|
||||
FUNCTION = "process_context"
|
||||
CATEGORY = "TenserTensor/Context"
|
||||
CATEGORY = "TenserTensor/Deprecated/Context"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
|
||||
@@ -6,7 +6,7 @@ from .context_helpers import create_context_schema
|
||||
class TT_ContextSetGuider:
|
||||
INPUT_TYPES_DICT, RETURN_TYPES, RETURN_NAMES = create_context_schema("set_guider")
|
||||
FUNCTION = "process_context"
|
||||
CATEGORY = "TenserTensor/Context"
|
||||
CATEGORY = "TenserTensor/Deprecated/Context"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
|
||||
@@ -6,7 +6,7 @@ from .context_helpers import create_context_schema
|
||||
class TT_ContextSetImage:
|
||||
INPUT_TYPES_DICT, RETURN_TYPES, RETURN_NAMES = create_context_schema("set_image")
|
||||
FUNCTION = "process_context"
|
||||
CATEGORY = "TenserTensor/Context"
|
||||
CATEGORY = "TenserTensor/Deprecated/Context"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
|
||||
@@ -6,7 +6,7 @@ from .context_helpers import create_context_schema
|
||||
class TT_ContextSetLatent:
|
||||
INPUT_TYPES_DICT, RETURN_TYPES, RETURN_NAMES = create_context_schema("set_latent")
|
||||
FUNCTION = "process_context"
|
||||
CATEGORY = "TenserTensor/Context"
|
||||
CATEGORY = "TenserTensor/Deprecated/Context"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
|
||||
@@ -6,7 +6,7 @@ from .context_helpers import (build_return_tuple, create_context_schema, init_co
|
||||
class TT_EvenLargerContext:
|
||||
INPUT_TYPES_DICT, RETURN_TYPES, RETURN_NAMES = create_context_schema("huge")
|
||||
FUNCTION = "process_context"
|
||||
CATEGORY = "TenserTensor/Context"
|
||||
CATEGORY = "TenserTensor/Deprecated/Context"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
|
||||
@@ -6,7 +6,7 @@ from .context_helpers import (build_return_tuple, create_context_schema, init_co
|
||||
class TT_LargeContextFlux:
|
||||
INPUT_TYPES_DICT, RETURN_TYPES, RETURN_NAMES = create_context_schema("big_flux")
|
||||
FUNCTION = "process_context"
|
||||
CATEGORY = "TenserTensor/Context"
|
||||
CATEGORY = "TenserTensor/Deprecated/Context"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
|
||||
@@ -6,7 +6,7 @@ from .context_helpers import (build_return_tuple, create_context_schema, init_co
|
||||
class TT_LargeContextSdxl:
|
||||
INPUT_TYPES_DICT, RETURN_TYPES, RETURN_NAMES = create_context_schema("big_sdxl")
|
||||
FUNCTION = "process_context"
|
||||
CATEGORY = "TenserTensor/Context"
|
||||
CATEGORY = "TenserTensor/Deprecated/Context"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
|
||||
Reference in New Issue
Block a user