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			| ea031ab b841d58 ac4fce0 0666fec ac4fce0 03ba072 b841d58 03ba072 ac4fce0 03ba072 ac4fce0 03ba072 ac4fce0 03ba072 ac4fce0 0666fec ac4fce0 a87ce5b 0666fec ac4fce0 a098d08 0666fec ac4fce0 0666fec ac4fce0 03ba072 ac4fce0 0666fec ac4fce0 0666fec | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 | from toolbox import update_ui
from toolbox import CatchException, report_execption, write_results_to_file
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:
            import win32com.client
            word = win32com.client.Dispatch("Word.Application")
            word.visible = False
            # 打开文件
            print('fp', os.getcwd())
            doc = word.Documents.Open(os.getcwd() + '/' + fp)
            # file_content = doc.Content.Text
            doc = word.ActiveDocument
            file_content = doc.Range().Text
            doc.Close()
            word.Quit()
        print(file_content)
        # 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_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
        from request_llm.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_txt_to_satisfy_token_limit_for_pdf(
            txt=file_content,  
            get_token_fn=model_info[llm_kwargs['llm_model']]['token_cnt'], 
            limit=TOKEN_LIMIT_PER_FRAGMENT
        )
        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_results_to_file(history)
        chatbot.append(("完成了吗?", res))
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
    res = write_results_to_file(history)
    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, web_port):
    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"])
    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_execption(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_execption(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_execption(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)
 |