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| 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 | |
| CATEGORY = get_category() | |
| def INPUT_TYPES(cls): # pylint: disable = invalid-name, missing-function-docstring | |
| SAVED_PROMPTS_FILES = folder_paths.get_filename_list('saved_prompts') | |
| SAVED_PROMPTS_CONTENT = [] | |
| for filename in SAVED_PROMPTS_FILES: | |
| with open(folder_paths.get_full_path('saved_prompts', filename), 'r') as f: | |
| SAVED_PROMPTS_CONTENT.append(f.read()) | |
| return { | |
| 'required': { | |
| 'prompt': ('STRING', { | |
| 'multiline': True | |
| }), | |
| }, | |
| 'optional': { | |
| "opt_model": ("MODEL",), | |
| "opt_clip": ("CLIP",), | |
| 'insert_lora': (['CHOOSE', 'DISABLE LORAS'] + | |
| [os.path.splitext(x)[0] for x in folder_paths.get_filename_list('loras')],), | |
| 'insert_embedding': ([ | |
| 'CHOOSE', | |
| ] + [os.path.splitext(x)[0] for x in folder_paths.get_filename_list('embeddings')],), | |
| 'insert_saved': ([ | |
| 'CHOOSE', | |
| ] + SAVED_PROMPTS_FILES,), | |
| }, | |
| 'hidden': { | |
| 'values_insert_saved': (['CHOOSE'] + SAVED_PROMPTS_CONTENT,), | |
| } | |
| } | |
| RETURN_TYPES = ( | |
| 'CONDITIONING', | |
| 'MODEL', | |
| 'CLIP', | |
| 'STRING', | |
| ) | |
| RETURN_NAMES = ( | |
| 'CONDITIONING', | |
| 'MODEL', | |
| 'CLIP', | |
| 'TEXT', | |
| ) | |
| FUNCTION = 'main' | |
| def main(self, | |
| prompt, | |
| 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, skipped, unfound = 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 is not None and opt_clip is not None: | |
| prompt, loras, skipped, unfound = get_and_strip_loras(prompt, log_node=NODE_NAME) | |
| if len(loras) > 0: | |
| for lora in loras: | |
| 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: | |
| prompt, loras, skipped, unfound = get_and_strip_loras(prompt, log_node=NODE_NAME, silent=True) | |
| total_loras = len(loras) + len(skipped) + len(unfound) | |
| if total_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 is not None: | |
| conditioning = CLIPTextEncode().encode(opt_clip, prompt)[0] | |
| return (conditioning, opt_model, opt_clip, prompt) | |