镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-07 15:06:48 +00:00
添加Markdown全文翻译插件,并用此插件翻译了本项目的README
这个提交包含在:
@@ -80,7 +80,7 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
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elif language == 'zh->en':
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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:" +
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f"\n\n{frag}" for frag in pfg.sp_file_contents]
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inputs_show_user_array = [f"润色 {f}" for f in pfg.sp_file_tag]
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inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag]
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sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)]
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gpt_response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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162
crazy_functions/批量Markdown翻译.py
普通文件
162
crazy_functions/批量Markdown翻译.py
普通文件
@@ -0,0 +1,162 @@
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from toolbox import update_ui
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from toolbox import CatchException, report_execption, write_results_to_file
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fast_debug = False
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class PaperFileGroup():
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def __init__(self):
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self.file_paths = []
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self.file_contents = []
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self.sp_file_contents = []
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self.sp_file_index = []
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self.sp_file_tag = []
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# count_token
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import tiktoken
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from toolbox import get_conf
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enc = tiktoken.encoding_for_model(*get_conf('LLM_MODEL'))
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def get_token_num(txt): return len(enc.encode(txt))
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self.get_token_num = get_token_num
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def run_file_split(self, max_token_limit=1900):
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"""
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将长文本分离开来
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"""
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for index, file_content in enumerate(self.file_contents):
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if self.get_token_num(file_content) < max_token_limit:
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self.sp_file_contents.append(file_content)
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self.sp_file_index.append(index)
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self.sp_file_tag.append(self.file_paths[index])
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else:
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit)
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for j, segment in enumerate(segments):
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self.sp_file_contents.append(segment)
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self.sp_file_index.append(index)
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self.sp_file_tag.append(self.file_paths[index] + f".part-{j}.md")
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print('Segmentation: done')
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def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en'):
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import time, os, re
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from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
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# <-------- 读取Markdown文件,删除其中的所有注释 ---------->
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pfg = PaperFileGroup()
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for index, fp in enumerate(file_manifest):
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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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# 记录删除注释后的文本
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pfg.file_paths.append(fp)
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pfg.file_contents.append(file_content)
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# <-------- 拆分过长的Markdown文件 ---------->
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pfg.run_file_split(max_token_limit=2048)
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n_split = len(pfg.sp_file_contents)
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# <-------- 多线程润色开始 ---------->
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if language == 'en->zh':
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inputs_array = ["This is a Markdown file, translate it into Chinese, do not modify any existing Markdown commands:" +
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f"\n\n{frag}" for frag in pfg.sp_file_contents]
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inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag]
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sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)]
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elif language == 'zh->en':
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inputs_array = [f"This is a Markdown file, translate it into English, do not modify any existing Markdown commands:" +
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f"\n\n{frag}" for frag in pfg.sp_file_contents]
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inputs_show_user_array = [f"翻译 {f}" for f in pfg.sp_file_tag]
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sys_prompt_array = ["You are a professional academic paper translator." for _ in range(n_split)]
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gpt_response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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inputs_array=inputs_array,
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inputs_show_user_array=inputs_show_user_array,
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llm_kwargs=llm_kwargs,
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chatbot=chatbot,
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history_array=[[""] for _ in range(n_split)],
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sys_prompt_array=sys_prompt_array,
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max_workers=10, # OpenAI所允许的最大并行过载
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scroller_max_len = 80
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)
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# <-------- 整理结果,退出 ---------->
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create_report_file_name = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + f"-chatgpt.polish.md"
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res = write_results_to_file(gpt_response_collection, file_name=create_report_file_name)
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history = gpt_response_collection
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chatbot.append((f"{fp}完成了吗?", res))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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@CatchException
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def Markdown英译中(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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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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"对整个Markdown项目进行翻译。函数插件贡献者: Binary-Husky"])
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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 tiktoken
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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 tiktoken```。")
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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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history = [] # 清空历史,以免输入溢出
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import glob, os
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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 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}/**/*.md', 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.md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 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en->zh')
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@CatchException
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def Markdown中译英(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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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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"对整个Markdown项目进行翻译。函数插件贡献者: Binary-Husky"])
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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 tiktoken
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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 tiktoken```。")
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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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history = [] # 清空历史,以免输入溢出
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import glob, os
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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 from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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if txt.endswith('.md'):
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file_manifest = [txt]
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else:
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file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.md', 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.md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 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='zh->en')
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