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