from toolbox import update_ui from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down, get_conf import re, requests, unicodedata, os from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive def download_arxiv_(url_pdf): if 'arxiv.org' not in url_pdf: if ('.' in url_pdf) and ('/' not in url_pdf): new_url = 'https://arxiv.org/abs/'+url_pdf print('下载编号：', url_pdf, '自动定位：', new_url) # download_arxiv_(new_url) return download_arxiv_(new_url) else: print('不能识别的URL！') return None if 'abs' in url_pdf: url_pdf = url_pdf.replace('abs', 'pdf') url_pdf = url_pdf + '.pdf' url_abs = url_pdf.replace('.pdf', '').replace('pdf', 'abs') title, other_info = get_name(_url_=url_abs) paper_id = title.split()[0] # '[1712.00559]' if '2' in other_info['year']: title = other_info['year'] + ' ' + title known_conf = ['NeurIPS', 'NIPS', 'Nature', 'Science', 'ICLR', 'AAAI'] for k in known_conf: if k in other_info['comment']: title = k + ' ' + title download_dir = './gpt_log/arxiv/' os.makedirs(download_dir, exist_ok=True) title_str = title.replace('?', '？')\ .replace(':', '：')\ .replace('\"', '“')\ .replace('\n', '')\ .replace(' ', ' ')\ .replace(' ', ' ') requests_pdf_url = url_pdf file_path = download_dir+title_str # if os.path.exists(file_path): # print('返回缓存文件') # return './gpt_log/arxiv/'+title_str print('下载中') proxies, = get_conf('proxies') r = requests.get(requests_pdf_url, proxies=proxies) with open(file_path, 'wb+') as f: f.write(r.content) print('下载完成') # print('输出下载命令：','aria2c -o \"%s\" %s'%(title_str,url_pdf)) # subprocess.call('aria2c --all-proxy=\"172.18.116.150:11084\" -o \"%s\" %s'%(download_dir+title_str,url_pdf), shell=True) x = "%s %s %s.bib" % (paper_id, other_info['year'], other_info['authors']) x = x.replace('?', '？')\ .replace(':', '：')\ .replace('\"', '“')\ .replace('\n', '')\ .replace(' ', ' ')\ .replace(' ', ' ') return './gpt_log/arxiv/'+title_str, other_info def get_name(_url_): import os from bs4 import BeautifulSoup print('正在获取文献名！') print(_url_) # arxiv_recall = {} # if os.path.exists('./arxiv_recall.pkl'): # with open('./arxiv_recall.pkl', 'rb') as f: # arxiv_recall = pickle.load(f) # if _url_ in arxiv_recall: # print('在缓存中') # return arxiv_recall[_url_] proxies, = get_conf('proxies') res = requests.get(_url_, proxies=proxies) bs = BeautifulSoup(res.text, 'html.parser') other_details = {} # get year try: year = bs.find_all(class_='dateline')[0].text year = re.search(r'(\d{4})', year, re.M | re.I).group(1) other_details['year'] = year abstract = bs.find_all(class_='abstract mathjax')[0].text other_details['abstract'] = abstract except: other_details['year'] = '' print('年份获取失败') # get author try: authors = bs.find_all(class_='authors')[0].text authors = authors.split('Authors:')[1] other_details['authors'] = authors except: other_details['authors'] = '' print('authors获取失败') # get comment try: comment = bs.find_all(class_='metatable')[0].text real_comment = None for item in comment.replace('\n', ' ').split(' '): if 'Comments' in item: real_comment = item if real_comment is not None: other_details['comment'] = real_comment else: other_details['comment'] = '' except: other_details['comment'] = '' print('年份获取失败') title_str = BeautifulSoup( res.text, 'html.parser').find('title').contents[0] print('获取成功：', title_str) # arxiv_recall[_url_] = (title_str+'.pdf', other_details) # with open('./arxiv_recall.pkl', 'wb') as f: # pickle.dump(arxiv_recall, f) return title_str+'.pdf', other_details @CatchException def 下载arxiv论文并翻译摘要(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port): CRAZY_FUNCTION_INFO = "下载arxiv论文并翻译摘要，函数插件作者[binary-husky]。正在提取摘要并下载PDF文档……" import glob import os # 基本信息：功能、贡献者 chatbot.append(["函数插件功能？", CRAZY_FUNCTION_INFO]) 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: import pdfminer, bs4 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 pdfminer beautifulsoup4```。") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return # 清空历史，以免输入溢出 history = [] # 提取摘要，下载PDF文档 try: pdf_path, info = download_arxiv_(txt) except: report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"下载pdf文件未成功") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return # 翻译摘要等 i_say = f"请你阅读以下学术论文相关的材料，提取摘要，翻译为中文。材料如下：{str(info)}" i_say_show_user = f'请你阅读以下学术论文相关的材料，提取摘要，翻译为中文。论文：{pdf_path}' chatbot.append((i_say_show_user, "[Local Message] waiting gpt response.")) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 msg = '正常' # ** gpt request ** # 单线，获取文章meta信息 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="Your job is to collect information from materials and translate to Chinese。", ) # gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, llm_kwargs, history=[]) # 带超时倒计时 chatbot[-1] = (i_say_show_user, gpt_say) history.append(i_say_show_user); history.append(gpt_say) yield from update_ui(chatbot=chatbot, history=chatbot, msg=msg) # 刷新界面 # 写入文件 import shutil # 重置文件的创建时间 shutil.copyfile(pdf_path, f'./gpt_log/{os.path.basename(pdf_path)}'); os.remove(pdf_path) res = write_results_to_file(history) chatbot.append(("完成了吗？", res + "\n\nPDF文件也已经下载")) yield from update_ui(chatbot=chatbot, history=chatbot, msg=msg) # 刷新界面