import glob, shutil, os, re, logging from toolbox import update_ui, trimmed_format_exc, gen_time_str from toolbox import CatchException, report_exception, get_log_folder from toolbox import write_history_to_file, promote_file_to_downloadzone 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 from request_llms.bridge_all import model_info enc = model_info["gpt-3.5-turbo"]['tokenizer'] 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=2048): """ 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_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit segments = breakdown_text_to_satisfy_token_limit(file_content, 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}.md") logging.info('Segmentation: done') def merge_result(self): self.file_result = ["" for _ in range(len(self.file_paths))] for r, k in zip(self.sp_file_result, self.sp_file_index): self.file_result[k] += r def write_result(self, language): manifest = [] for path, res in zip(self.file_paths, self.file_result): dst_file = os.path.join(get_log_folder(), f'{gen_time_str()}.md') with open(dst_file, 'w', encoding='utf8') as f: manifest.append(dst_file) f.write(res) return manifest def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en'): from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency # <-------- 读取Markdown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() # 记录删除注释后的文本 pfg.file_paths.append(fp) pfg.file_contents.append(file_content) # <-------- 拆分过长的Markdown文件 ----------> pfg.run_file_split(max_token_limit=2048) n_split = len(pfg.sp_file_contents) # <-------- 多线程翻译开始 ----------> if language == 'en->zh': inputs_array = ["This is a Markdown file, translate it into Chinese, do NOT modify any existing Markdown commands, do NOT use code wrapper (```), ONLY answer me with translated results:" + 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"This is a Markdown file, translate it into English, do NOT modify any existing Markdown commands, do NOT use code wrapper (```), ONLY answer me with translated results:" + 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)] else: inputs_array = [f"This is a Markdown file, translate it into {language}, do NOT modify any existing Markdown commands, do NOT use code wrapper (```), ONLY answer me with translated results:" + 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 ) try: pfg.sp_file_result = [] for i_say, gpt_say in zip(gpt_response_collection[0::2], gpt_response_collection[1::2]): pfg.sp_file_result.append(gpt_say) pfg.merge_result() output_file_arr = pfg.write_result(language) for output_file in output_file_arr: promote_file_to_downloadzone(output_file, chatbot=chatbot) if 'markdown_expected_output_path' in plugin_kwargs: expected_f_name = plugin_kwargs['markdown_expected_output_path'] shutil.copyfile(output_file, expected_f_name) except: logging.error(trimmed_format_exc()) # <-------- 整理结果，退出 ----------> create_report_file_name = gen_time_str() + f"-chatgpt.md" res = write_history_to_file(gpt_response_collection, file_basename=create_report_file_name) promote_file_to_downloadzone(res, chatbot=chatbot) 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 def get_files_from_everything(txt, preference=''): if txt == "": return False, None, None success = True if txt.startswith('http'): import requests from toolbox import get_conf proxies = get_conf('proxies') # 网络的远程文件 if preference == 'Github': logging.info('正在从github下载资源 ...') if not txt.endswith('.md'): # Make a request to the GitHub API to retrieve the repository information url = txt.replace("https://github.com/", "https://api.github.com/repos/") + '/readme' response = requests.get(url, proxies=proxies) txt = response.json()['download_url'] else: txt = txt.replace("https://github.com/", "https://raw.githubusercontent.com/") txt = txt.replace("/blob/", "/") r = requests.get(txt, proxies=proxies) download_local = f'{get_log_folder(plugin_name="批量Markdown翻译")}/raw-readme-{gen_time_str()}.md' project_folder = f'{get_log_folder(plugin_name="批量Markdown翻译")}' with open(download_local, 'wb+') as f: f.write(r.content) file_manifest = [download_local] elif txt.endswith('.md'): # 直接给定文件 file_manifest = [txt] project_folder = os.path.dirname(txt) elif os.path.exists(txt): # 本地路径，递归搜索 project_folder = txt file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.md', recursive=True)] else: project_folder = None file_manifest = [] success = False return success, file_manifest, project_folder @CatchException def Markdown英译中(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): # 基本信息：功能、贡献者 chatbot.append([ "函数插件功能？", "对整个Markdown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_exception(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 success, file_manifest, project_folder = get_files_from_everything(txt, preference="Github") if not success: # 什么都没有 if txt == "": txt = '空空如也的输入栏' 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}") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return if len(file_manifest) == 0: report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md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 Markdown中译英(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): # 基本信息：功能、贡献者 chatbot.append([ "函数插件功能？", "对整个Markdown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_exception(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 success, file_manifest, project_folder = get_files_from_everything(txt) if not success: # 什么都没有 if txt == "": txt = '空空如也的输入栏' 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}") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return if len(file_manifest) == 0: report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md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') @CatchException def Markdown翻译指定语言(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): # 基本信息：功能、贡献者 chatbot.append([ "函数插件功能？", "对整个Markdown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_exception(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 success, file_manifest, project_folder = get_files_from_everything(txt) if not success: # 什么都没有 if txt == "": txt = '空空如也的输入栏' 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}") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return if len(file_manifest) == 0: report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}") yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 return if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg") language = plugin_kwargs.get("advanced_arg", 'Chinese') yield from 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language=language)