Power Prompt - Simple (rgthree)¶
Documentation¶
- Class name:
Power Prompt - Simple (rgthree)
- Category:
rgthree
- Output node:
False
The Power Prompt - Simple node is designed to simplify the process of generating conditioning and text outputs based on a given prompt. It optionally incorporates CLIP embeddings and allows for the insertion of pre-saved prompts or embeddings, streamlining the creation of customized text inputs for further processing.
Input types¶
Required¶
prompt
- The primary text input for which conditioning and text outputs are generated. It serves as the base content for further modifications or enhancements.
- Comfy dtype:
STRING
- Python dtype:
str
Optional¶
opt_clip
- An optional CLIP model input that, if provided, is used to generate a conditioning output based on the prompt, enhancing the relevance or specificity of the generated text.
- Comfy dtype:
CLIP
- Python dtype:
Optional[str]
insert_embedding
- Allows for the insertion of a pre-saved embedding by name, enabling the customization of the prompt with specific, pre-defined characteristics.
- Comfy dtype:
COMBO[STRING]
- Python dtype:
Optional[str]
insert_saved
- Permits the inclusion of a pre-saved prompt by filename, facilitating the reuse of previously crafted prompts for new generations.
- Comfy dtype:
COMBO[STRING]
- Python dtype:
Optional[str]
Output types¶
CONDITIONING
- Comfy dtype:
CONDITIONING
- The conditioning output, generated based on the prompt and optionally enhanced by a CLIP model, which can be used for further processing or refinement.
- Python dtype:
Optional[torch.Tensor]
- Comfy dtype:
TEXT
- Comfy dtype:
STRING
- The original or modified prompt text, which can be used as input for subsequent operations or models.
- Python dtype:
str
- Comfy dtype:
Usage tips¶
- Infra type:
CPU
- Common nodes: unknown
Source code¶
class RgthreePowerPromptSimple(RgthreePowerPrompt):
NAME=get_name('Power Prompt - Simple')
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_clip": ("CLIP", ),
'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', 'STRING',)
RETURN_NAMES = ('CONDITIONING', 'TEXT',)
FUNCTION = 'main'
def main(self, prompt, opt_clip=None, insert_embedding=None, insert_saved=None, values_insert_saved=None):
conditioning=None
if opt_clip != None:
conditioning = CLIPTextEncode().encode(opt_clip, prompt)[0]
return (conditioning, prompt)