72 lines
2.9 KiB
Python
72 lines
2.9 KiB
Python
class loraSearch:
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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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"Lora Search": ("STRING", {
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"tooltip": "Searchg For Specific Lora By Name Or Civit AIR Code (eg: Cyberpunk).",
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}),
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"Model Architecture": ([
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"All",
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"FLUX.1-Schnell",
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"FLUX.1-Dev",
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"Pony",
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"SD 1.5",
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"SD 1.5 Hyper",
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"SD 1.5 LCM",
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"SD 3",
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"SDXL 1.0",
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"SDXL 1.0 LCM",
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"SDXL Distilled",
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"SDXL Hyper",
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"SDXL Lightning",
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"SDXL Turbo",
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], {
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"tooltip": "Choose Lora Model Architecture To Filter Results.",
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"default": "All",
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}),
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"LoraType": ([
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"Lora",
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], {
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"tooltip": "Choose Lora Type To Filter Results.",
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"default": "Lora",
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}),
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"LoraList": ([
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"civitai:58390@62833 (Detail Tweaker LoRA (细节调整LoRA))",
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"civitai:82098@87153 (Add More Details - Detail Enhancer / Tweaker (细节调整) LoRA)",
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"civitai:122359@135867 (Detail Tweaker XL)",
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"civitai:14171@16677 (Cute_girl_mix4)",
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"civitai:13941@16576 (epi_noiseoffset)",
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"civitai:25995@32988 (blindbox/大概是盲盒)",
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], {
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"tooltip": "Lora Results Will Show UP Here So You Could Choose From.",
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"default": "civitai:58390@62833 (Detail Tweaker LoRA (细节调整LoRA))",
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}),
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"weight": ("FLOAT", {
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"tooltip": "Defines the strength or influence of the LoRA model in the generation process.",
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"default": 1.0,
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"min": -4.0,
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"max": 4.0,
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"step": 0.1,
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}),
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},
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}
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DESCRIPTION = "Directly Search and Connect Lora's to Runware Inference Nodes In ComfyUI."
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FUNCTION = "loraSearch"
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RETURN_TYPES = ("RUNWARELORA",)
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RETURN_NAMES = ("Runware Lora",)
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CATEGORY = "Runware"
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@classmethod
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def VALIDATE_INPUTS(cls, LoraList):
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return True
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def loraSearch(self, **kwargs):
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currentModel = kwargs.get("LoraList")
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loraWeight = kwargs.get("weight")
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loraAIRCode = currentModel.split(" ")[0]
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return ({
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"model": loraAIRCode,
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"weight": round(loraWeight, 2),
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},) |