import json
import re
import math
import numpy as np
from tqdm import tqdm


task_book_main_content_prompt = "请根据题目为《{}》，和研究内容为“{}”总结出至少6点本篇论文应完成的主要内容，使用阿拉伯数字排列"
pantten_title = "(.*?)》为题目的研究内容，包括整体简介和分最少三个方面总结"


path = "./data/paper_prompt_title_3/title_jianjie_prompt_data.txt"
with open(path, encoding="utf-8") as f:
    text = f.read()


text_list = text.split("请帮我生成《")

data_list = []
chinese_keyword_data_list = []

for text_dan in tqdm(text_list):
    # print(text_dan)
    try:
        title_prompt, jianjie = text_dan.split("**************")
    except:
        continue
    result_biaoti_list = re.findall(pantten_title, title_prompt)
    try:
        result_biaoti_list[0]
    except:
        print(title_prompt)
        continue

    title = str(result_biaoti_list[0]).strip("\n")
    jianjie = str(jianjie).strip("\n")

    data_list.append(task_book_main_content_prompt.format(title, jianjie))

import random

random.shuffle(data_list)

with open("./data/jianjie_to_/task_book_prompt.txt", mode="w", encoding="utf-8") as f:
    for i in data_list:
        f.write(json.dumps(i, ensure_ascii=False))
        f.write("\n")


#     for lable in table_of_contents:
#         text_len = len(paper_text)
#         dan_nerlable = [text_len, text_len + len(lable[0]), lable[1]]
#         nerlable_list.append(dan_nerlable)
#         paper_text += lable[0]
#         paper_text += "@"
#
#     paper_dan = {"text": paper_text, "label": nerlable_list}
#
#     ner_lable.append(str(table_of_contents))
#     text_zong.append(paper_dan)
#
# with open("../data/train.txt", mode="w", encoding="utf-8") as f:
#     for i in text_zong:
#         f.write(json.dumps(i, ensure_ascii=False))
#         f.write("\n")
#
#
# with open("../data/train_lable.txt", mode="w") as f:
#     for i in ner_lable:
#         f.write(json.dumps(i, ensure_ascii=False))
#         f.write("\n")