明日之后捏脸高颜值代码

明日之后捏脸高颜值代码：导入模块、全局变量、函数和主执行部分。

导入模块：

import bardapi.Bardimport generativeai.models.textfrom concurrent.futures import ThreadPoolExecutorfrom dotenv import load_dotenvimport os

全局变量：

generated_keywords_file_path = "generated_keywords.txt"model = None

函数：

def get_generated_keywords():with open(generated_keywords_file_path, "r") as f:return set(f.read().splitlines())def clear_generated_keywords_file():with open(generated_keywords_file_path, "w") as f:f.truncate()def generate_and_save(keyword):generated_text = model.generate(keyword, max_length=200)generated_text = generated_text.replace("[", "").replace("]", "").replace('"', "").replace(",", "")with open("generated_text.txt", "a") as f:f.write(generated_text + "\n")def main():load_dotenv()bardapi.configure(Bard(os.getenv("BARD_API_KEY")))model = generativeai.models.text.TextGenerator(os.getenv("GENERATIVE_AI_API_KEY"))generated_keywords = get_generated_keywords()clear_generated_keywords_file()executor = ThreadPoolExecutor(max_workers=10)for keyword in generated_keywords:executor.submit(generate_and_save, keyword)executor.shutdown()

主执行部分：

if __name__ == "__main__":main()

该代码通过导入模块、定义全局变量、封装函数和执行主逻辑，实现了基于关键词生成文本并保存到文件的功能。它利用了Google的Bard和Generative AI库，并以多线程的方式并发执行生成任务，提高了效率。