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- from toolbox import CatchException, report_exception, get_log_folder, gen_time_str
- from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
- from toolbox import write_history_to_file, promote_file_to_downloadzone
- from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
- from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
- from .crazy_utils import read_and_clean_pdf_text
- from .pdf_fns.parse_pdf import parse_pdf, get_avail_grobid_url, translate_pdf
- from colorful import *
- import copy
- import os
- import math
- import logging
- def markdown_to_dict(article_content):
- import markdown
- from bs4 import BeautifulSoup
- cur_t = ""
- cur_c = ""
- results = {}
- for line in article_content:
- if line.startswith('#'):
- if cur_t!="":
- if cur_t not in results:
- results.update({cur_t:cur_c.lstrip('\n')})
- else:
- # 处理重名的章节
- results.update({cur_t + " " + gen_time_str():cur_c.lstrip('\n')})
- cur_t = line.rstrip('\n')
- cur_c = ""
- else:
- cur_c += line
- results_final = {}
- for k in list(results.keys()):
- if k.startswith('# '):
- results_final['title'] = k.split('# ')[-1]
- results_final['authors'] = results.pop(k).lstrip('\n')
- if k.startswith('###### Abstract'):
- results_final['abstract'] = results.pop(k).lstrip('\n')
- results_final_sections = []
- for k,v in results.items():
- results_final_sections.append({
- 'heading':k.lstrip("# "),
- 'text':v if len(v) > 0 else f"The beginning of {k.lstrip('# ')} section."
- })
- results_final['sections'] = results_final_sections
- return results_final
- @CatchException
- def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
- disable_auto_promotion(chatbot)
- # 基本信息:功能、贡献者
- chatbot.append([
- "函数插件功能?",
- "批量翻译PDF文档。函数插件贡献者: Binary-Husky"])
- yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
- # 清空历史,以免输入溢出
- history = []
- from .crazy_utils import get_files_from_everything
- success, file_manifest, project_folder = get_files_from_everything(txt, type='.pdf')
- if len(file_manifest) > 0:
- # 尝试导入依赖,如果缺少依赖,则给出安装建议
- try:
- import nougat
- import tiktoken
- except:
- report_exception(chatbot, history,
- a=f"解析项目: {txt}",
- b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade nougat-ocr tiktoken```。")
- yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
- return
- success_mmd, file_manifest_mmd, _ = get_files_from_everything(txt, type='.mmd')
- success = success or success_mmd
- file_manifest += file_manifest_mmd
- chatbot.append(["文件列表:", ", ".join([e.split('/')[-1] for e in file_manifest])]);
- yield from update_ui( chatbot=chatbot, history=history)
- # 检测输入参数,如没有给定输入参数,直接退出
- if not success:
- if txt == "": txt = '空空如也的输入栏'
- # 如果没找到任何文件
- if len(file_manifest) == 0:
- report_exception(chatbot, history,
- a=f"解析项目: {txt}", b=f"找不到任何.pdf拓展名的文件: {txt}")
- yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
- return
- # 开始正式执行任务
- yield from 解析PDF_基于NOUGAT(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
- def 解析PDF_基于NOUGAT(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
- import copy
- import tiktoken
- TOKEN_LIMIT_PER_FRAGMENT = 1024
- generated_conclusion_files = []
- generated_html_files = []
- DST_LANG = "中文"
- from crazy_functions.crazy_utils import nougat_interface
- from crazy_functions.pdf_fns.report_gen_html import construct_html
- nougat_handle = nougat_interface()
- for index, fp in enumerate(file_manifest):
- if fp.endswith('pdf'):
- chatbot.append(["当前进度:", f"正在解析论文,请稍候。(第一次运行时,需要花费较长时间下载NOUGAT参数)"]); yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
- fpp = yield from nougat_handle.NOUGAT_parse_pdf(fp, chatbot, history)
- promote_file_to_downloadzone(fpp, rename_file=os.path.basename(fpp)+'.nougat.mmd', chatbot=chatbot)
- else:
- chatbot.append(["当前论文无需解析:", fp]); yield from update_ui( chatbot=chatbot, history=history)
- fpp = fp
- with open(fpp, 'r', encoding='utf8') as f:
- article_content = f.readlines()
- article_dict = markdown_to_dict(article_content)
- logging.info(article_dict)
- yield from translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_files, TOKEN_LIMIT_PER_FRAGMENT, DST_LANG)
- chatbot.append(("给出输出文件清单", str(generated_conclusion_files + generated_html_files)))
- yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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