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Includes 30 custom nodes committed directly, 7 Civitai-exclusive loras stored via Git LFS, and a setup script that installs all dependencies and downloads HuggingFace-hosted models on vast.ai. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
"""The original Context Switch."""
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from .constants import get_category, get_name
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from .context_utils import is_context_empty
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from .utils import ByPassTypeTuple, FlexibleOptionalInputType
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class RgthreeDynamicContextSwitch:
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"""The initial Context Switch node."""
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NAME = get_name("Dynamic Context Switch")
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CATEGORY = get_category()
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@classmethod
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def INPUT_TYPES(cls): # pylint: disable = invalid-name, missing-function-docstring
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return {
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"required": {},
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"optional": FlexibleOptionalInputType("RGTHREE_DYNAMIC_CONTEXT"),
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}
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RETURN_TYPES = ByPassTypeTuple(("RGTHREE_DYNAMIC_CONTEXT",))
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RETURN_NAMES = ByPassTypeTuple(("CONTEXT",))
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FUNCTION = "switch"
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def switch(self, **kwargs):
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"""Chooses the first non-empty Context to output."""
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output_keys = kwargs.get('output_keys', None)
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ctx = None
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for key, value in kwargs.items():
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if key.startswith('ctx_') and not is_context_empty(value):
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ctx = value
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break
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res = [ctx]
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output_keys = output_keys.split(',') if output_keys is not None else []
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for key in output_keys:
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res.append(ctx[key] if ctx is not None and key in ctx else None)
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return tuple(res)
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