163 lines
7.1 KiB
Python
163 lines
7.1 KiB
Python
from toolbox import update_ui
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from toolbox import CatchException, report_exception
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from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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from toolbox import write_history_to_file, promote_file_to_downloadzone
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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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# Create a PDF parser object associated with the file object
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parser = PDFParser(fp)
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# Create a PDF document object that stores the document structure.
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# Password for initialization as 2nd parameter
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document = PDFDocument(parser)
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# Check if the document allows text extraction. If not, abort.
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if not document.is_extractable:
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raise PDFTextExtractionNotAllowed
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# Create a PDF resource manager object that stores shared resources.
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rsrcmgr = PDFResourceManager()
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# Create a PDF device object.
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# device = PDFDevice(rsrcmgr)
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# BEGIN LAYOUT ANALYSIS.
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# Set parameters for analysis.
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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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# Create a PDF page aggregator object.
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device = PDFPageAggregator(rsrcmgr, laparams=laparams)
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# Create a PDF interpreter object.
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interpreter = PDFPageInterpreter(rsrcmgr, device)
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# loop over all pages in the document
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outTextList = []
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for page in PDFPage.create_pages(document):
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# read the page into a layout object
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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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# print(obj.get_text())
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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, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
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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', errors='replace') 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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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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if not fast_debug:
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msg = '正常'
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# ** gpt request **
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gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=i_say,
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inputs_show_user=i_say_show_user,
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llm_kwargs=llm_kwargs,
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chatbot=chatbot,
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history=[],
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sys_prompt="总结文章。"
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) # 带超时倒计时
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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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yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
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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 from update_ui(chatbot=chatbot, history=history) # 刷新界面
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if not fast_debug:
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msg = '正常'
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# ** gpt request **
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gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=i_say,
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inputs_show_user=i_say,
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llm_kwargs=llm_kwargs,
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chatbot=chatbot,
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history=history,
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sys_prompt="总结文章。"
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) # 带超时倒计时
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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 from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
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res = write_history_to_file(history)
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promote_file_to_downloadzone(res, chatbot=chatbot)
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chatbot.append(("完成了吗？", res))
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yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
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@CatchException
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def 批量总结PDF文档pdfminer(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
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history = [] # 清空历史，以免输入溢出
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import glob, os
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# 基本信息：功能、贡献者
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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 from update_ui(chatbot=chatbot, history=history) # 刷新界面
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# 尝试导入依赖，如果缺少依赖，则给出安装建议
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try:
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import pdfminer, bs4
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except:
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report_exception(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 from update_ui(chatbot=chatbot, history=history) # 刷新界面
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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_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}")
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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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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# [f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)] + \
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# [f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)]
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if len(file_manifest) == 0:
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report_exception(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 from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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yield from 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
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