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v0.12.0 ChinesePrompt && PromptGenerate
> ChinesePrompt && PromptGenerate，中文prompt节点，直接用中文书写你的prompt  > Web App增加图片编辑器
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,215 @@ | ||
| from transformers import pipeline, set_seed,AutoTokenizer, AutoModelForSeq2SeqLM | ||
| import random | ||
| import re | ||
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| import os,sys | ||
| import folder_paths | ||
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| # from PIL import Image | ||
| # import importlib.util | ||
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| import comfy.utils | ||
| # import numpy as np | ||
| import torch | ||
| import random | ||
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| global _available | ||
| _available=True | ||
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| text_generator_model_path=os.path.join(folder_paths.models_dir, "prompt_generator/text2image-prompt-generator") | ||
| if not os.path.exists(text_generator_model_path): | ||
| print(f"## text_generator_model not found: {text_generator_model_path}, pls download from https://huggingface.co/succinctly/text2image-prompt-generator/tree/main") | ||
| text_generator_model_path='succinctly/text2image-prompt-generator' | ||
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| zh_en_model_path=os.path.join(folder_paths.models_dir, "prompt_generator/opus-mt-zh-en") | ||
| if not os.path.exists(zh_en_model_path): | ||
| print(f"## zh_en_model not found: {zh_en_model_path}, pls download from https://huggingface.co/Helsinki-NLP/opus-mt-zh-en/tree/main") | ||
| zh_en_model_path='Helsinki-NLP/opus-mt-zh-en' | ||
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| def translate(zh_en_tokenizer,zh_en_model,texts): | ||
| with torch.no_grad(): | ||
| encoded = zh_en_tokenizer(texts, return_tensors="pt") | ||
| encoded.to(zh_en_model.device) | ||
| sequences = zh_en_model.generate(**encoded) | ||
| return zh_en_tokenizer.batch_decode(sequences, skip_special_tokens=True) | ||
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| # input = "青春不能回头，所以青春没有终点。 ——《火影忍者》" | ||
| # print(input, translate(input)) | ||
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| def text_generate(text_pipe,input,seed=None): | ||
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| if seed==None: | ||
| seed = random.randint(100, 1000000) | ||
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| set_seed(seed) | ||
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| for count in range(6): | ||
| sequences = text_pipe(input, max_length=random.randint(60, 90), num_return_sequences=8) | ||
| list = [] | ||
| for sequence in sequences: | ||
| line = sequence['generated_text'].strip() | ||
| if line != input and len(line) > (len(input) + 4) and line.endswith((":", "-", "—")) is False: | ||
| list.append(line) | ||
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| result = "\n".join(list) | ||
| result = re.sub('[^ ]+\.[^ ]+','', result) | ||
| result = result.replace("<", "").replace(">", "") | ||
| if result != "": | ||
| return result | ||
| if count == 5: | ||
| return result | ||
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| # input = "Youth can't turn back, so there's no end to youth." | ||
| # print(input, text_generate(input)) | ||
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| class ChinesePrompt: | ||
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| global _available | ||
| available=_available | ||
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| @classmethod | ||
| def INPUT_TYPES(s): | ||
| return {"required": { | ||
| "text": ("STRING",{"multiline": True,"default": "", "dynamicPrompts": False}), | ||
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| }, | ||
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| "optional":{ | ||
| "seed":("INT", {"default": 100, "min": 100, "max": 1000000}), | ||
| }, | ||
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| } | ||
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| RETURN_TYPES = ("STRING",) | ||
| RETURN_NAMES = ("prompt",) | ||
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| FUNCTION = "run" | ||
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| CATEGORY = "♾️Mixlab/Prompt" | ||
| OUTPUT_NODE = True | ||
| INPUT_IS_LIST = True | ||
| OUTPUT_IS_LIST = (True,) | ||
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| global text_pipe,zh_en_model,zh_en_tokenizer | ||
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| text_pipe= None | ||
| zh_en_model=None | ||
| zh_en_tokenizer=None | ||
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| def run(self,text,seed): | ||
| global text_pipe,zh_en_model,zh_en_tokenizer | ||
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| seed=seed[0] | ||
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| # 进度条 | ||
| pbar = comfy.utils.ProgressBar(len(text)+1) | ||
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| if zh_en_model==None: | ||
| zh_en_model = AutoModelForSeq2SeqLM.from_pretrained(zh_en_model_path).eval() | ||
| zh_en_tokenizer = AutoTokenizer.from_pretrained(zh_en_model_path) | ||
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| zh_en_model.to("cuda" if torch.cuda.is_available() else "cpu") | ||
| # zh_en_tokenizer.to("cuda" if torch.cuda.is_available() else "cpu") | ||
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| text_pipe=pipeline('text-generation', model=text_generator_model_path,device="cuda" if torch.cuda.is_available() else "cpu") | ||
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| # text_pipe.model.to("cuda" if torch.cuda.is_available() else "cpu") | ||
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| prompt_result=[] | ||
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| # print('zh_en_model device',zh_en_model.device,text_pipe.model.device,torch.cuda.current_device() ) | ||
| en_text=translate(zh_en_tokenizer,zh_en_model,text) | ||
| zh_en_model.to('cpu') | ||
| # en_text.to("cuda" if torch.cuda.is_available() else "cpu") | ||
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| pbar.update(1) | ||
| for t in en_text: | ||
| prompt =text_generate(text_pipe,t,seed) | ||
| # 多条，还是单条 | ||
| lines = prompt.split("\n") | ||
| longest_line = max(lines, key=len) | ||
| # print(longest_line) | ||
| prompt_result.append(longest_line) | ||
| pbar.update(1) | ||
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| text_pipe.model.to('cpu') | ||
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| return { | ||
| "ui":{ | ||
| "prompt": prompt_result | ||
| }, | ||
| "result": (prompt_result,)} | ||
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| class PromptGenerate: | ||
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| global _available | ||
| available=_available | ||
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| @classmethod | ||
| def INPUT_TYPES(s): | ||
| return {"required": { | ||
| "text": ("STRING",{"multiline": True,"default": "", "dynamicPrompts": False}), | ||
| }, | ||
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| "optional":{ | ||
| "multiple": (["off","on"],), | ||
| "seed":("INT", {"default": 100, "min": 100, "max": 1000000}), | ||
| }, | ||
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| } | ||
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| RETURN_TYPES = ("STRING",) | ||
| RETURN_NAMES = ("prompt",) | ||
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| FUNCTION = "run" | ||
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| CATEGORY = "♾️Mixlab/Prompt" | ||
| OUTPUT_NODE = True | ||
| INPUT_IS_LIST = True | ||
| OUTPUT_IS_LIST = (True,) | ||
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| global text_pipe | ||
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| text_pipe= None | ||
| # | ||
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| def run(self,text,multiple,seed): | ||
| global text_pipe | ||
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| seed=seed[0] | ||
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| multiple=multiple[0] | ||
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| # 进度条 | ||
| pbar = comfy.utils.ProgressBar(len(text)) | ||
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| text_pipe=pipeline('text-generation', model=text_generator_model_path,device="cuda" if torch.cuda.is_available() else "cpu") | ||
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| prompt_result=[] | ||
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| for t in text: | ||
| prompt =text_generate(text_pipe,t,seed) | ||
| prompt = prompt.split("\n") | ||
| if multiple=='off': | ||
| prompt = [max(prompt, key=len)] | ||
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| for p in prompt: | ||
| prompt_result.append(p) | ||
| pbar.update(1) | ||
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| text_pipe.model.to('cpu') | ||
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| return { | ||
| "ui":{ | ||
| "prompt": prompt_result | ||
| }, | ||
| "result": (prompt_result,)} |
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