| |
|
|
| import torch, os, json, random, hashlib |
| from urllib.request import urlopen |
| import json |
|
|
| class WAS_NSP_CLIPTextEncoder: |
| def __init__(self): |
| pass |
|
|
| @classmethod |
| def INPUT_TYPES(s): |
| return { |
| "required": { |
| "noodle_key": ("STRING", {"default": '__', "multiline": False}), |
| "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}), |
| "text": ("STRING", {"multiline": True}), |
| "clip": ("CLIP",), |
| } |
| } |
| |
| RETURN_TYPES = ("CONDITIONING",) |
| FUNCTION = "nsp_encode" |
|
|
| CATEGORY = "conditioning" |
|
|
| def nsp_encode(self, clip, text, noodle_key = '__', seed = 0): |
| |
| |
| local_pantry = 'ComfyUI/custom_nodes/nsp_pantry.json' |
| if not os.path.exists(local_pantry): |
| response = urlopen('https://raw.githubusercontent.com/WASasquatch/noodle-soup-prompts/main/nsp_pantry.json') |
| tmp_pantry = json.loads(response.read()) |
| |
| pantry_serialized = json.dumps(tmp_pantry, indent=4) |
| with open(local_pantry, "w") as f: |
| f.write(pantry_serialized) |
| del response, tmp_pantry |
| |
| |
| with open(local_pantry, 'r') as f: |
| nspterminology = json.load(f) |
| |
| if seed > 0 or seed < 1: |
| random.seed(seed) |
| |
| |
| new_text = text |
| for term in nspterminology: |
| |
| tkey = f'{noodle_key}{term}{noodle_key}' |
| |
| tcount = new_text.count(tkey) |
| |
| for _ in range(tcount): |
| new_text = new_text.replace(tkey, random.choice(nspterminology[term]), 1) |
| seed = seed+1 |
| random.seed(seed) |
| |
| print('Parsed Prompt:', new_text) |
| |
| return ([[clip.encode(new_text), {}]], ) |
|
|
| NODE_CLASS_MAPPINGS = { |
| "CLIPTextEncode (NSP)": WAS_NSP_CLIPTextEncoder |
| } |
|
|
