Prompt With Style V2 (Mikey)

Documentation

• Class name: Prompt With Style V2
• Category: Mikey
• Output node: False

This node processes textual prompts by applying a specified style, removing any style syntax, and handling positive and negative prompts differently based on the style. It also incorporates seed-based modifications to ensure variability in the output.

Input types

Required

• positive_prompt
  • The positive prompt to be styled and modified. It undergoes transformations based on the specified style and seed, contributing to the generation of the styled output.
  • Comfy dtype: STRING
  • Python dtype: str
• negative_prompt
  • The negative prompt to be styled and modified similarly to the positive prompt, but with potentially different style applications based on the specified style.
  • Comfy dtype: STRING
  • Python dtype: str
• style
  • The style to be applied to the prompts. It determines how the prompts are modified and styled, playing a crucial role in the output generation process.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• ratio_selected
  • The selected ratio for image generation, affecting the dimensions of the output images.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: str
• batch_size
  • The number of prompts to process in a single batch, affecting performance and output volume.
  • Comfy dtype: INT
  • Python dtype: int
• seed
  • A seed value used to introduce variability and randomness in the processing of prompts, affecting how wildcards and random syntax are handled.
  • Comfy dtype: INT
  • Python dtype: int
• clip_base
  • The base CLIP model used for encoding the prompts.
  • Comfy dtype: CLIP
  • Python dtype: object
• clip_refiner
  • The CLIP refiner model used for refining the encoded prompts.
  • Comfy dtype: CLIP
  • Python dtype: object

Output types

• samples
  • Comfy dtype: LATENT
  • The generated samples based on the processed prompts and applied styles.
  • Python dtype: list
• base_pos_cond
  • Comfy dtype: CONDITIONING
  • The positive condition base encoding result from the CLIP model.
  • Python dtype: object
• base_neg_cond
  • Comfy dtype: CONDITIONING
  • The negative condition base encoding result from the CLIP model.
  • Python dtype: object
• refiner_pos_cond
  • Comfy dtype: CONDITIONING
  • The positive condition refiner encoding result from the CLIP refiner model.
  • Python dtype: object
• refiner_neg_cond
  • Comfy dtype: CONDITIONING
  • The negative condition refiner encoding result from the CLIP refiner model.
  • Python dtype: object
• positive_prompt
  • Comfy dtype: STRING
  • The processed positive prompt with the applied style, stripped of any style syntax.
  • Python dtype: str
• negative_prompt
  • Comfy dtype: STRING
  • The processed negative prompt with the applied style, stripped of any style syntax.
  • Python dtype: str

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class PromptWithStyleV2:
    @classmethod
    def INPUT_TYPES(s):
        s.ratio_sizes, s.ratio_dict = read_ratios()
        s.styles, s.pos_style, s.neg_style = read_styles()
        return {"required": {"positive_prompt": ("STRING", {"multiline": True, 'default': 'Positive Prompt'}),
                             "negative_prompt": ("STRING", {"multiline": True, 'default': 'Negative Prompt'}),
                             "style": (s.styles,),
                             "ratio_selected": (s.ratio_sizes,),
                             "batch_size": ("INT", {"default": 1, "min": 1, "max": 64}),
                             "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
                             "clip_base": ("CLIP",), "clip_refiner": ("CLIP",),
                             }
        }

    RETURN_TYPES = ('LATENT',
                    'CONDITIONING','CONDITIONING','CONDITIONING','CONDITIONING',
                    'STRING','STRING')
    RETURN_NAMES = ('samples',
                    'base_pos_cond','base_neg_cond','refiner_pos_cond','refiner_neg_cond',
                    'positive_prompt','negative_prompt')

    FUNCTION = 'start'
    CATEGORY = 'Mikey'

    def start(self, clip_base, clip_refiner, positive_prompt, negative_prompt, style, ratio_selected, batch_size, seed):
        """ get output from PromptWithStyle.start """
        (latent,
         pos_prompt, neg_prompt,
         pos_style, neg_style,
         width, height,
         refiner_width, refiner_height) = PromptWithStyle.start(self, positive_prompt,
                                                                negative_prompt,
                                                                style, ratio_selected,
                                                                batch_size, seed)
        # calculate dimensions for target_width, target height (base) and refiner_width, refiner_height (refiner)
        ratio = min([width, height]) / max([width, height])
        target_width, target_height = (4096, 4096 * ratio // 8 * 8) if width > height else (4096 * ratio // 8 * 8, 4096)
        refiner_width = target_width
        refiner_height = target_height
        #print('Width:', width, 'Height:', height,
        #     'Target Width:', target_width, 'Target Height:', target_height,
        #     'Refiner Width:', refiner_width, 'Refiner Height:', refiner_height)
        # encode text
        sdxl_pos_cond = CLIPTextEncodeSDXL.encode(self, clip_base, width, height, 0, 0, target_width, target_height, pos_prompt, pos_style)[0]
        sdxl_neg_cond = CLIPTextEncodeSDXL.encode(self, clip_base, width, height, 0, 0, target_width, target_height, neg_prompt, neg_style)[0]
        refiner_pos_cond = CLIPTextEncodeSDXLRefiner.encode(self, clip_refiner, 6, refiner_width, refiner_height, pos_prompt)[0]
        refiner_neg_cond = CLIPTextEncodeSDXLRefiner.encode(self, clip_refiner, 2.5, refiner_width, refiner_height, neg_prompt)[0]
        # return
        return (latent,
                sdxl_pos_cond, sdxl_neg_cond,
                refiner_pos_cond, refiner_neg_cond,
                pos_prompt, neg_prompt)