from toolbox import update_ui from toolbox import CatchException, report_execption, write_results_to_file fast_debug = False class PaperFileGroup(): def __init__(self): self.file_paths = [] self.file_contents = [] self.sp_file_contents = [] self.sp_file_index = [] self.sp_file_tag = [] # count_token import tiktoken from toolbox import get_conf enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL')) def get_token_num(txt): return len(enc.encode(txt, disallowed_special=())) self.get_token_num = get_token_num def run_file_split(self, max_token_limit=1900): """ 将长文本分离开来 """ for index, file_content in enumerate(self.file_contents): if self.get_token_num(file_content) < max_token_limit: self.sp_file_contents.append(file_content) self.sp_file_index.append(index) self.sp_file_tag.append(self.file_paths[index]) else: from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit) for j, segment in enumerate(segments): self.sp_file_contents.append(segment) self.sp_file_index.append(index) self.sp_file_tag.append(self.file_paths[index] + f".part-{j}.tex") print('Segmentation: done') def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en'): import time, os, re from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency # <-------- 读取Latex文件，删除其中的所有注释 ----------> pfg = PaperFileGroup() for index, fp in enumerate(file_manifest): with open(fp, 'r', encoding='utf-8', errors='replace') as f: file_content = f.read() # 定义注释的正则表达式 comment_pattern = r'%.*' # 使用正则表达式查找注释，并替换为空字符串 clean_tex_content = re.sub(comment_pattern, '', file_content) # 记录删除注释后的文本 pfg.file_paths.append(fp) pfg.file_contents.append(clean_tex_content) # <-------- 拆分过长的latex文件 ----------> pfg.run_file_split(max_token_limit=1024) n_split = len(pfg.sp_file_contents) # <-------- 抽取摘要 ----------> # if language == 'en': # abs_extract_inputs = f"Please write an abstract for this paper" # # 单线，获取文章meta信息 # paper_meta_info = yield from request_gpt_model_in_new_thread_with_ui_alive( # inputs=abs_extract_inputs, # inputs_show_user=f"正在抽取摘要信息。", # llm_kwargs=llm_kwargs, # chatbot=chatbot, history=[], # sys_prompt="Your job is to collect information from materials。", # ) # <-------- 多线程润色开始 ----------> if language == 'en->zh': inputs_array = ["Below is a section from an English academic paper, translate it into Chinese, do not modify any latex command such as \section, \cite and equations:" + f"\n\n{frag}" for frag in pfg.sp_file_contents] inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag] sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)] elif language == 'zh->en': inputs_array = [f"Below is a section from a Chinese academic paper, translate it into English, do not modify any latex command such as \section, \cite and equations:" + f"\n\n{frag}" for frag in pfg.sp_file_contents] inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag] sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)] gpt_response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency( inputs_array=inputs_array, inputs_show_user_array=inputs_show_user_array, llm_kwargs=llm_kwargs, chatbot=chatbot, history_array=[[""] for _ in range(n_split)], sys_prompt_array=sys_prompt_array, max_workers=5, # OpenAI所允许的最大并行过载 scroller_max_len = 80 ) # <-------- 整理结果，退出 ----------> create_report_file_name = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + f"-chatgpt.polish.md" res = write_results_to_file(gpt_response_collection, file_name=create_report_file_name) history = gpt_response_collection chatbot.append((f"{fp}完成了吗？", res)) yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 @CatchException def Latex英译中(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port): # 基本信息：功能、贡献者 chatbot.append([ "函数插件功能？", "对整个Latex项目进行翻译。函数插件贡献者: Binary-Husky"]) 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 tiktoken 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 tiktoken```。") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return history = [] # 清空历史，以免输入溢出 import glob, os 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 file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)] if len(file_manifest) == 0: report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return yield from 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en->zh') @CatchException def Latex中译英(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port): # 基本信息：功能、贡献者 chatbot.append([ "函数插件功能？", "对整个Latex项目进行翻译。函数插件贡献者: Binary-Husky"]) 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 tiktoken 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 tiktoken```。") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return history = [] # 清空历史，以免输入溢出 import glob, os 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 file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)] if len(file_manifest) == 0: report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return yield from 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='zh->en')