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import os
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from .log import log_node_warn, log_node_info, log_node_success
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from .constants import get_category, get_name
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from .power_prompt_utils import get_and_strip_loras
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from nodes import LoraLoader, CLIPTextEncode
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import folder_paths
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NODE_NAME = get_name('Power Prompt')
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class RgthreePowerPrompt:
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NAME = NODE_NAME
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CATEGORY = get_category()
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@classmethod
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def INPUT_TYPES(cls):
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SAVED_PROMPTS_FILES = folder_paths.get_filename_list('saved_prompts')
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SAVED_PROMPTS_CONTENT = []
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for filename in SAVED_PROMPTS_FILES:
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with open(folder_paths.get_full_path('saved_prompts', filename), 'r') as f:
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SAVED_PROMPTS_CONTENT.append(f.read())
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return {
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'required': {
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'prompt': ('STRING', {
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'multiline': True
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}),
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},
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'optional': {
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"opt_model": ("MODEL",),
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"opt_clip": ("CLIP",),
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'insert_lora': (['CHOOSE', 'DISABLE LORAS'] +
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[os.path.splitext(x)[0] for x in folder_paths.get_filename_list('loras')],),
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'insert_embedding': ([
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'CHOOSE',
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] + [os.path.splitext(x)[0] for x in folder_paths.get_filename_list('embeddings')],),
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'insert_saved': ([
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'CHOOSE',
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] + SAVED_PROMPTS_FILES,),
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},
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'hidden': {
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'values_insert_saved': (['CHOOSE'] + SAVED_PROMPTS_CONTENT,),
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}
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}
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RETURN_TYPES = (
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'CONDITIONING',
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'MODEL',
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'CLIP',
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'STRING',
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)
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RETURN_NAMES = (
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'CONDITIONING',
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'MODEL',
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'CLIP',
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'TEXT',
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)
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FUNCTION = 'main'
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def main(self,
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prompt,
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opt_model=None,
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opt_clip=None,
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insert_lora=None,
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insert_embedding=None,
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insert_saved=None,
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values_insert_saved=None):
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if insert_lora == 'DISABLE LORAS':
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prompt, loras, skipped, unfound = get_and_strip_loras(prompt, log_node=NODE_NAME, silent=True)
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log_node_info(
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NODE_NAME,
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f'Disabling all found loras ({len(loras)}) and stripping lora tags for TEXT output.')
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elif opt_model is not None and opt_clip is not None:
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prompt, loras, skipped, unfound = get_and_strip_loras(prompt, log_node=NODE_NAME)
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if len(loras) > 0:
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for lora in loras:
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opt_model, opt_clip = LoraLoader().load_lora(opt_model, opt_clip, lora['lora'],
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lora['strength'], lora['strength'])
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log_node_success(NODE_NAME, f'Loaded "{lora["lora"]}" from prompt')
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log_node_info(NODE_NAME, f'{len(loras)} Loras processed; stripping tags for TEXT output.')
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elif '<lora:' in prompt:
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prompt, loras, skipped, unfound = get_and_strip_loras(prompt, log_node=NODE_NAME, silent=True)
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total_loras = len(loras) + len(skipped) + len(unfound)
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if total_loras:
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log_node_warn(
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NODE_NAME, f'Found {len(loras)} lora tags in prompt but model & clip were not supplied!')
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log_node_info(NODE_NAME, 'Loras not processed, keeping for TEXT output.')
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conditioning = None
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if opt_clip is not None:
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conditioning = CLIPTextEncode().encode(opt_clip, prompt)[0]
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return (conditioning, opt_model, opt_clip, prompt)
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