mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-21 21:22:11 -03:00
41101ad5c6
Rename all node classes to use consistent 'LM' suffix pattern: - LoraCyclerNode → LoraCyclerLM - LoraManagerLoader → LoraLoaderLM - LoraManagerTextLoader → LoraTextLoaderLM - LoraStacker → LoraStackerLM - LoraRandomizerNode → LoraRandomizerLM - LoraPoolNode → LoraPoolLM - WanVideoLoraSelectFromText → WanVideoLoraTextSelectLM - DebugMetadata → DebugMetadataLM - TriggerWordToggle → TriggerWordToggleLM - PromptLoraManager → PromptLM Updated: - Core node class definitions (9 files) - NODE_CLASS_MAPPINGS in __init__.py - Node type mappings in node_extractors.py - All related test imports and references - Logger prefixes for consistency Frontend extension names remain unchanged (LoraManager.LoraStacker, etc.)
57 lines
1.9 KiB
Python
57 lines
1.9 KiB
Python
from typing import Any, Optional
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class PromptLM:
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"""Encodes text (and optional trigger words) into CLIP conditioning."""
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NAME = "Prompt (LoraManager)"
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CATEGORY = "Lora Manager/conditioning"
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DESCRIPTION = (
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"Encodes a text prompt using a CLIP model into an embedding that can be used "
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"to guide the diffusion model towards generating specific images."
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)
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"text": (
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"AUTOCOMPLETE_TEXT_EMBEDDINGS",
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{
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"placeholder": "Enter prompt...",
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"tooltip": "The text to be encoded.",
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},
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),
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"clip": (
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'CLIP',
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{"tooltip": "The CLIP model used for encoding the text."},
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),
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},
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"optional": {
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"trigger_words": (
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'STRING',
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{
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"forceInput": True,
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"tooltip": (
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"Optional trigger words to prepend to the text before "
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"encoding."
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)
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},
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)
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},
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}
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RETURN_TYPES = ('CONDITIONING', 'STRING',)
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RETURN_NAMES = ('CONDITIONING', 'PROMPT',)
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OUTPUT_TOOLTIPS = (
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"A conditioning containing the embedded text used to guide the diffusion model.",
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)
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FUNCTION = "encode"
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def encode(self, text: str, clip: Any, trigger_words: Optional[str] = None):
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prompt = text
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if trigger_words:
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prompt = ", ".join([trigger_words, text])
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from nodes import CLIPTextEncode # type: ignore
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conditioning = CLIPTextEncode().encode(clip, prompt)[0]
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return (conditioning, prompt,) |