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from request_llm.bridge_chatgpt import predict_no_ui |
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from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down |
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fast_debug = False |
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def readPdf(pdfPath): |
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""" |
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读取pdf文件,返回文本内容 |
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""" |
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import pdfminer |
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from pdfminer.pdfparser import PDFParser |
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from pdfminer.pdfdocument import PDFDocument |
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from pdfminer.pdfpage import PDFPage, PDFTextExtractionNotAllowed |
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from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter |
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from pdfminer.pdfdevice import PDFDevice |
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from pdfminer.layout import LAParams |
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from pdfminer.converter import PDFPageAggregator |
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fp = open(pdfPath, 'rb') |
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parser = PDFParser(fp) |
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document = PDFDocument(parser) |
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if not document.is_extractable: |
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raise PDFTextExtractionNotAllowed |
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rsrcmgr = PDFResourceManager() |
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laparams = LAParams( |
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char_margin=10.0, |
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line_margin=0.2, |
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boxes_flow=0.2, |
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all_texts=False, |
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) |
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device = PDFPageAggregator(rsrcmgr, laparams=laparams) |
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interpreter = PDFPageInterpreter(rsrcmgr, device) |
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outTextList = [] |
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for page in PDFPage.create_pages(document): |
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interpreter.process_page(page) |
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layout = device.get_result() |
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for obj in layout._objs: |
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if isinstance(obj, pdfminer.layout.LTTextBoxHorizontal): |
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outTextList.append(obj.get_text()) |
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return outTextList |
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def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt): |
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import time, glob, os |
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from bs4 import BeautifulSoup |
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print('begin analysis on:', file_manifest) |
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for index, fp in enumerate(file_manifest): |
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if ".tex" in fp: |
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with open(fp, 'r', encoding='utf-8') as f: |
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file_content = f.read() |
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if ".pdf" in fp.lower(): |
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file_content = readPdf(fp) |
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file_content = BeautifulSoup(''.join(file_content), features="lxml").body.text.encode('gbk', 'ignore').decode('gbk') |
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prefix = "接下来请你逐文件分析下面的论文文件,概括其内容" if index==0 else "" |
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i_say = prefix + f'请对下面的文章片段用中文做一个概述,文件名是{os.path.relpath(fp, project_folder)},文章内容是 ```{file_content}```' |
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i_say_show_user = prefix + f'[{index}/{len(file_manifest)}] 请对下面的文章片段做一个概述: {os.path.abspath(fp)}' |
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chatbot.append((i_say_show_user, "[Local Message] waiting gpt response.")) |
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print('[1] yield chatbot, history') |
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yield chatbot, history, '正常' |
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if not fast_debug: |
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msg = '正常' |
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) |
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print('[2] end gpt req') |
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chatbot[-1] = (i_say_show_user, gpt_say) |
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history.append(i_say_show_user); history.append(gpt_say) |
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print('[3] yield chatbot, history') |
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yield chatbot, history, msg |
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print('[4] next') |
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if not fast_debug: time.sleep(2) |
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all_file = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(file_manifest)]) |
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i_say = f'根据以上你自己的分析,对全文进行概括,用学术性语言写一段中文摘要,然后再写一段英文摘要(包括{all_file})。' |
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chatbot.append((i_say, "[Local Message] waiting gpt response.")) |
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yield chatbot, history, '正常' |
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if not fast_debug: |
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msg = '正常' |
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) |
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chatbot[-1] = (i_say, gpt_say) |
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history.append(i_say); history.append(gpt_say) |
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yield chatbot, history, msg |
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res = write_results_to_file(history) |
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chatbot.append(("完成了吗?", res)) |
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yield chatbot, history, msg |
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@CatchException |
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def 批量总结PDF文档pdfminer(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT): |
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history = [] |
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import glob, os |
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chatbot.append([ |
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"函数插件功能?", |
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"批量总结PDF文档,此版本使用pdfminer插件,带token约简功能。函数插件贡献者: Euclid-Jie。"]) |
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yield chatbot, history, '正常' |
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try: |
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import pdfminer, bs4 |
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except: |
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report_execption(chatbot, history, |
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a = f"解析项目: {txt}", |
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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 pdfminer beautifulsoup4```。") |
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yield chatbot, history, '正常' |
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return |
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if os.path.exists(txt): |
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project_folder = txt |
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else: |
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if txt == "": txt = '空空如也的输入栏' |
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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}") |
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yield chatbot, history, '正常' |
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return |
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file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)] + \ |
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[f for f in glob.glob(f'{project_folder}/**/*.pdf', recursive=True)] |
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if len(file_manifest) == 0: |
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report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex或pdf文件: {txt}") |
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yield chatbot, history, '正常' |
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return |
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yield from 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt) |
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