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Running
on
L40S
File size: 3,342 Bytes
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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()
@classmethod
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)
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