from toolbox import update_ui from toolbox import CatchException, report_exception from toolbox import write_history_to_file, promote_file_to_downloadzone from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive fast_debug = False def 解析docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt): import time, os # pip install python-docx 用于docx格式,跨平台 # pip install pywin32 用于doc格式,仅支持Win平台 for index, fp in enumerate(file_manifest): if fp.split(".")[-1] == "docx": from docx import Document doc = Document(fp) file_content = "\n".join([para.text for para in doc.paragraphs]) else: try: import win32com.client word = win32com.client.Dispatch("Word.Application") word.visible = False # 打开文件 doc = word.Documents.Open(os.getcwd() + '/' + fp) # file_content = doc.Content.Text doc = word.ActiveDocument file_content = doc.Range().Text doc.Close() word.Quit() except: raise RuntimeError('请先将.doc文档转换为.docx文档。') # private_upload里面的文件名在解压zip后容易出现乱码(rar和7z格式正常),故可以只分析文章内容,不输入文件名 from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit from request_llms.bridge_all import model_info max_token = model_info[llm_kwargs['llm_model']]['max_token'] TOKEN_LIMIT_PER_FRAGMENT = max_token * 3 // 4 paper_fragments = breakdown_text_to_satisfy_token_limit(txt=file_content, limit=TOKEN_LIMIT_PER_FRAGMENT, llm_model=llm_kwargs['llm_model']) this_paper_history = [] for i, paper_frag in enumerate(paper_fragments): i_say = f'请对下面的文章片段用中文做概述,文件名是{os.path.relpath(fp, project_folder)},文章内容是 ```{paper_frag}```' i_say_show_user = f'请对下面的文章片段做概述: {os.path.abspath(fp)}的第{i+1}/{len(paper_fragments)}个片段。' gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( inputs=i_say, inputs_show_user=i_say_show_user, llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], sys_prompt="总结文章。" ) chatbot[-1] = (i_say_show_user, gpt_say) history.extend([i_say_show_user,gpt_say]) this_paper_history.extend([i_say_show_user,gpt_say]) # 已经对该文章的所有片段总结完毕,如果文章被切分了, if len(paper_fragments) > 1: i_say = f"根据以上的对话,总结文章{os.path.abspath(fp)}的主要内容。" gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( inputs=i_say, inputs_show_user=i_say, llm_kwargs=llm_kwargs, chatbot=chatbot, history=this_paper_history, sys_prompt="总结文章。" ) history.extend([i_say,gpt_say]) this_paper_history.extend([i_say,gpt_say]) res = write_history_to_file(history) promote_file_to_downloadzone(res, chatbot=chatbot) chatbot.append(("完成了吗?", res)) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 res = write_history_to_file(history) promote_file_to_downloadzone(res, chatbot=chatbot) chatbot.append(("所有文件都总结完成了吗?", res)) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 @CatchException def 总结word文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): import glob, os # 基本信息:功能、贡献者 chatbot.append([ "函数插件功能?", "批量总结Word文档。函数插件贡献者: JasonGuo1。注意, 如果是.doc文件, 请先转化为.docx格式。"]) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 尝试导入依赖,如果缺少依赖,则给出安装建议 try: from docx import Document 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 python-docx pywin32```。") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return # 清空历史,以免输入溢出 history = [] # 检测输入参数,如没有给定输入参数,直接退出 if os.path.exists(txt): project_folder = txt else: if txt == "": txt = '空空如也的输入栏' report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return # 搜索需要处理的文件清单 if txt.endswith('.docx') or txt.endswith('.doc'): file_manifest = [txt] else: file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.docx', recursive=True)] + \ [f for f in glob.glob(f'{project_folder}/**/*.doc', recursive=True)] # 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.docx或doc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docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)