111 lines
6.2 KiB
Python
111 lines
6.2 KiB
Python
from toolbox import get_log_folder
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from toolbox import update_ui, promote_file_to_downloadzone
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from toolbox import write_history_to_file, promote_file_to_downloadzone
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from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
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from crazy_functions.crazy_utils import read_and_clean_pdf_text
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from shared_utils.colorful import *
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import os
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def 解析PDF_简单拆解(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
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"""
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注意：此函数已经弃用！！新函数位于：crazy_functions/pdf_fns/parse_pdf.py
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"""
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import copy
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TOKEN_LIMIT_PER_FRAGMENT = 1024
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generated_conclusion_files = []
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generated_html_files = []
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from crazy_functions.pdf_fns.report_gen_html import construct_html
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for index, fp in enumerate(file_manifest):
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# 读取PDF文件
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file_content, page_one = read_and_clean_pdf_text(fp)
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file_content = file_content.encode('utf-8', 'ignore').decode() # avoid reading non-utf8 chars
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page_one = str(page_one).encode('utf-8', 'ignore').decode() # avoid reading non-utf8 chars
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# 递归地切割PDF文件
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from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
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paper_fragments = breakdown_text_to_satisfy_token_limit(txt=file_content, limit=TOKEN_LIMIT_PER_FRAGMENT, llm_model=llm_kwargs['llm_model'])
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page_one_fragments = breakdown_text_to_satisfy_token_limit(txt=page_one, limit=TOKEN_LIMIT_PER_FRAGMENT//4, llm_model=llm_kwargs['llm_model'])
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# 为了更好的效果，我们剥离Introduction之后的部分（如果有）
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paper_meta = page_one_fragments[0].split('introduction')[0].split('Introduction')[0].split('INTRODUCTION')[0]
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# 单线，获取文章meta信息
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paper_meta_info = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=f"以下是一篇学术论文的基础信息，请从中提取出“标题”、“收录会议或期刊”、“作者”、“摘要”、“编号”、“作者邮箱”这六个部分。请用markdown格式输出，最后用中文翻译摘要部分。请提取：{paper_meta}",
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inputs_show_user=f"请从{fp}中提取出“标题”、“收录会议或期刊”等基本信息。",
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llm_kwargs=llm_kwargs,
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chatbot=chatbot, history=[],
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sys_prompt="Your job is to collect information from materials。",
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)
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# 多线，翻译
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gpt_response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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inputs_array=[
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f"你需要翻译以下内容：\n{frag}" for frag in paper_fragments],
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inputs_show_user_array=[f"\n---\n 原文： \n\n {frag.replace('#', '')} \n---\n 翻译：\n " for frag in paper_fragments],
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llm_kwargs=llm_kwargs,
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chatbot=chatbot,
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history_array=[[paper_meta] for _ in paper_fragments],
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sys_prompt_array=[
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"请你作为一个学术翻译，负责把学术论文准确翻译成中文。注意文章中的每一句话都要翻译。" + plugin_kwargs.get("additional_prompt", "")
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for _ in paper_fragments],
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# max_workers=5 # OpenAI所允许的最大并行过载
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)
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gpt_response_collection_md = copy.deepcopy(gpt_response_collection)
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# 整理报告的格式
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for i,k in enumerate(gpt_response_collection_md):
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if i%2==0:
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gpt_response_collection_md[i] = f"\n\n---\n\n ## 原文[{i//2}/{len(gpt_response_collection_md)//2}]： \n\n {paper_fragments[i//2].replace('#', '')} \n\n---\n\n ## 翻译[{i//2}/{len(gpt_response_collection_md)//2}]：\n "
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else:
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gpt_response_collection_md[i] = gpt_response_collection_md[i]
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final = ["一、论文概况\n\n---\n\n", paper_meta_info.replace('# ', '### ') + '\n\n---\n\n', "二、论文翻译", ""]
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final.extend(gpt_response_collection_md)
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create_report_file_name = f"{os.path.basename(fp)}.trans.md"
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res = write_history_to_file(final, create_report_file_name)
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promote_file_to_downloadzone(res, chatbot=chatbot)
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# 更新UI
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generated_conclusion_files.append(f'{get_log_folder()}/{create_report_file_name}')
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chatbot.append((f"{fp}完成了吗？", res))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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# write html
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try:
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ch = construct_html()
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orig = ""
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trans = ""
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gpt_response_collection_html = copy.deepcopy(gpt_response_collection)
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for i,k in enumerate(gpt_response_collection_html):
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if i%2==0:
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gpt_response_collection_html[i] = paper_fragments[i//2].replace('#', '')
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else:
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gpt_response_collection_html[i] = gpt_response_collection_html[i]
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final = ["论文概况", paper_meta_info.replace('# ', '### '), "二、论文翻译", ""]
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final.extend(gpt_response_collection_html)
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for i, k in enumerate(final):
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if i%2==0:
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orig = k
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if i%2==1:
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trans = k
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ch.add_row(a=orig, b=trans)
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create_report_file_name = f"{os.path.basename(fp)}.trans.html"
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generated_html_files.append(ch.save_file(create_report_file_name))
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except:
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from toolbox import trimmed_format_exc
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print('writing html result failed:', trimmed_format_exc())
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# 准备文件的下载
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for pdf_path in generated_conclusion_files:
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# 重命名文件
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rename_file = f'翻译-{os.path.basename(pdf_path)}'
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promote_file_to_downloadzone(pdf_path, rename_file=rename_file, chatbot=chatbot)
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for html_path in generated_html_files:
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# 重命名文件
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rename_file = f'翻译-{os.path.basename(html_path)}'
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promote_file_to_downloadzone(html_path, rename_file=rename_file, chatbot=chatbot)
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chatbot.append(("给出输出文件清单", str(generated_conclusion_files + generated_html_files)))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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