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98
crazy_functions/Langchain知识库.py
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98
crazy_functions/Langchain知识库.py
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@ -0,0 +1,98 @@
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from toolbox import CatchException, update_ui, ProxyNetworkActivate
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from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_files_from_everything
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@CatchException
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def 知识库问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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"""
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txt 输入栏用户输入的文本,例如需要翻译的一段话,再例如一个包含了待处理文件的路径
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llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行
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plugin_kwargs 插件模型的参数,暂时没有用武之地
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chatbot 聊天显示框的句柄,用于显示给用户
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history 聊天历史,前情提要
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system_prompt 给gpt的静默提醒
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web_port 当前软件运行的端口号
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"""
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history = [] # 清空历史,以免输入溢出
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chatbot.append(("这是什么功能?", "[Local Message] 从一批文件(txt, md, tex)中读取数据构建知识库, 然后进行问答。"))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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# resolve deps
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try:
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from zh_langchain import construct_vector_store
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from langchain.embeddings.huggingface import HuggingFaceEmbeddings
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from .crazy_utils import knowledge_archive_interface
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except Exception as e:
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chatbot.append(
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["依赖不足",
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"导入依赖失败。正在尝试自动安装,请查看终端的输出或耐心等待..."]
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)
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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from .crazy_utils import try_install_deps
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try_install_deps(['zh_langchain==0.2.0'])
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# < --------------------读取参数--------------- >
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if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
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kai_id = plugin_kwargs.get("advanced_arg", 'default')
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# < --------------------读取文件--------------- >
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file_manifest = []
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spl = ["txt", "doc", "docx", "email", "epub", "html", "json", "md", "msg", "pdf", "ppt", "pptx", "rtf"]
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for sp in spl:
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_, file_manifest_tmp, _ = get_files_from_everything(txt, type=f'.{sp}')
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file_manifest += file_manifest_tmp
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if len(file_manifest) == 0:
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chatbot.append(["没有找到任何可读取文件", "当前支持的格式包括: txt, md, docx, pptx, pdf, json等"])
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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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# < -------------------预热文本向量化模组--------------- >
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chatbot.append(['<br/>'.join(file_manifest), "正在预热文本向量化模组, 如果是第一次运行, 将消耗较长时间下载中文向量化模型..."])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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print('Checking Text2vec ...')
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from langchain.embeddings.huggingface import HuggingFaceEmbeddings
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with ProxyNetworkActivate(): # 临时地激活代理网络
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HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese")
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# < -------------------构建知识库--------------- >
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chatbot.append(['<br/>'.join(file_manifest), "正在构建知识库..."])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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print('Establishing knowledge archive ...')
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with ProxyNetworkActivate(): # 临时地激活代理网络
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kai = knowledge_archive_interface()
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kai.feed_archive(file_manifest=file_manifest, id=kai_id)
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kai_files = kai.get_loaded_file()
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kai_files = '<br/>'.join(kai_files)
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# chatbot.append(['知识库构建成功', "正在将知识库存储至cookie中"])
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# yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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# chatbot._cookies['langchain_plugin_embedding'] = kai.get_current_archive_id()
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# chatbot._cookies['lock_plugin'] = 'crazy_functions.Langchain知识库->读取知识库作答'
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# chatbot.append(['完成', "“根据知识库作答”函数插件已经接管问答系统, 提问吧! 但注意, 您接下来不能再使用其他插件了,刷新页面即可以退出知识库问答模式。"])
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chatbot.append(['构建完成', f"当前知识库内的有效文件:\n\n---\n\n{kai_files}\n\n---\n\n请切换至“知识库问答”插件进行知识库访问, 或者使用此插件继续上传更多文件。"])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间,我们先及时地做一次界面更新
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@CatchException
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def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port=-1):
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# < ------------------- --------------- >
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from .crazy_utils import knowledge_archive_interface
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kai = knowledge_archive_interface()
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if 'langchain_plugin_embedding' in chatbot._cookies:
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resp, prompt = kai.answer_with_archive_by_id(txt, chatbot._cookies['langchain_plugin_embedding'])
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else:
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if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
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kai_id = plugin_kwargs.get("advanced_arg", 'default')
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resp, prompt = kai.answer_with_archive_by_id(txt, kai_id)
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chatbot.append((txt, '[Local Message] ' + prompt))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间,我们先及时地做一次界面更新
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gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=prompt, inputs_show_user=txt,
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llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
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sys_prompt=system_prompt
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)
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history.extend((prompt, gpt_say))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间,我们先及时地做一次界面更新
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@ -238,3 +238,6 @@ def Latex英文纠错(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
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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 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en', mode='proofread')
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263
crazy_functions/Latex输出PDF结果.py
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263
crazy_functions/Latex输出PDF结果.py
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@ -0,0 +1,263 @@
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from toolbox import update_ui, trimmed_format_exc, get_conf, objdump, objload, promote_file_to_downloadzone
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from toolbox import CatchException, report_execption, update_ui_lastest_msg, zip_result, gen_time_str
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import glob, os, requests, time
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pj = os.path.join
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ARXIV_CACHE_DIR = os.path.expanduser(f"~/arxiv_cache/")
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# =================================== 工具函数 ===============================================
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沙雕GPT啊别犯这些低级翻译错误 = 'You must to translate "agent" to "智能体". '
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def switch_prompt(pfg, mode):
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"""
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Generate prompts and system prompts based on the mode for proofreading or translating.
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Args:
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- pfg: Proofreader or Translator instance.
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- mode: A string specifying the mode, either 'proofread' or 'translate_zh'.
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Returns:
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- inputs_array: A list of strings containing prompts for users to respond to.
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- sys_prompt_array: A list of strings containing prompts for system prompts.
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"""
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n_split = len(pfg.sp_file_contents)
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if mode == 'proofread':
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inputs_array = [r"Below is a section from an academic paper, proofread this section." +
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r"Do not modify any latex command such as \section, \cite, \begin, \item and equations. " +
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r"Answer me only with the revised text:" +
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f"\n\n{frag}" for frag in pfg.sp_file_contents]
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sys_prompt_array = ["You are a professional academic paper writer." for _ in range(n_split)]
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elif mode == 'translate_zh':
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inputs_array = [r"Below is a section from an English academic paper, translate it into Chinese." + 沙雕GPT啊别犯这些低级翻译错误 +
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r"Do not modify any latex command such as \section, \cite, \begin, \item and equations. " +
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r"Answer me only with the translated text:" +
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f"\n\n{frag}" for frag in pfg.sp_file_contents]
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sys_prompt_array = ["You are a professional translator." for _ in range(n_split)]
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else:
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assert False, "未知指令"
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return inputs_array, sys_prompt_array
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def desend_to_extracted_folder_if_exist(project_folder):
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"""
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Descend into the extracted folder if it exists, otherwise return the original folder.
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Args:
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- project_folder: A string specifying the folder path.
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Returns:
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- A string specifying the path to the extracted folder, or the original folder if there is no extracted folder.
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"""
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maybe_dir = [f for f in glob.glob(f'{project_folder}/*') if os.path.isdir(f)]
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if len(maybe_dir) == 0: return project_folder
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if maybe_dir[0].endswith('.extract'): return maybe_dir[0]
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return project_folder
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def move_project(project_folder, arxiv_id=None):
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"""
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Create a new work folder and copy the project folder to it.
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Args:
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- project_folder: A string specifying the folder path of the project.
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Returns:
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- A string specifying the path to the new work folder.
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"""
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import shutil, time
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time.sleep(2) # avoid time string conflict
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if arxiv_id is not None:
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new_workfolder = pj(ARXIV_CACHE_DIR, arxiv_id, 'workfolder')
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else:
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new_workfolder = f'gpt_log/{gen_time_str()}'
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try: shutil.rmtree(new_workfolder)
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except: pass
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shutil.copytree(src=project_folder, dst=new_workfolder)
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return new_workfolder
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def arxiv_download(chatbot, history, txt):
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def check_cached_translation_pdf(arxiv_id):
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translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'translation')
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if not os.path.exists(translation_dir):
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os.makedirs(translation_dir)
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target_file = pj(translation_dir, 'translate_zh.pdf')
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if os.path.exists(target_file):
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promote_file_to_downloadzone(target_file)
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return target_file
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return False
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if not txt.startswith('https://arxiv.org'):
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return txt, None
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# <-------------- inspect format ------------->
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chatbot.append([f"检测到arxiv文档连接", '尝试下载 ...'])
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yield from update_ui(chatbot=chatbot, history=history)
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time.sleep(1) # 刷新界面
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url_ = txt # https://arxiv.org/abs/1707.06690
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if not txt.startswith('https://arxiv.org/abs/'):
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msg = f"解析arxiv网址失败, 期望格式例如: https://arxiv.org/abs/1707.06690。实际得到格式: {url_}"
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yield from update_ui_lastest_msg(msg, chatbot=chatbot, history=history) # 刷新界面
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return msg, None
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# <-------------- set format ------------->
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arxiv_id = url_.split('/abs/')[-1]
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cached_translation_pdf = check_cached_translation_pdf(arxiv_id)
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if cached_translation_pdf: return cached_translation_pdf, arxiv_id
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url_tar = url_.replace('/abs/', '/e-print/')
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translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'e-print')
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extract_dst = pj(ARXIV_CACHE_DIR, arxiv_id, 'extract')
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os.makedirs(translation_dir, exist_ok=True)
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# <-------------- download arxiv source file ------------->
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dst = pj(translation_dir, arxiv_id+'.tar')
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if os.path.exists(dst):
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yield from update_ui_lastest_msg("调用缓存", chatbot=chatbot, history=history) # 刷新界面
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else:
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yield from update_ui_lastest_msg("开始下载", chatbot=chatbot, history=history) # 刷新界面
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proxies, = get_conf('proxies')
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r = requests.get(url_tar, proxies=proxies)
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with open(dst, 'wb+') as f:
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f.write(r.content)
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# <-------------- extract file ------------->
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yield from update_ui_lastest_msg("下载完成", chatbot=chatbot, history=history) # 刷新界面
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from toolbox import extract_archive
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extract_archive(file_path=dst, dest_dir=extract_dst)
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return extract_dst, arxiv_id
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# ========================================= 插件主程序1 =====================================================
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@CatchException
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def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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# <-------------- information about this plugin ------------->
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chatbot.append([ "函数插件功能?",
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"对整个Latex项目进行纠错, 用latex编译为PDF对修正处做高亮。函数插件贡献者: Binary-Husky。注意事项: 目前仅支持GPT3.5/GPT4,其他模型转化效果未知。目前对机器学习类文献转化效果最好,其他类型文献转化效果未知。仅在Windows系统进行了测试,其他操作系统表现未知。"])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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||||
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# <-------------- check deps ------------->
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try:
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import glob, os, time
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os.system(f'pdflatex -version')
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from .latex_utils import Latex精细分解与转化, 编译Latex差别
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||||
except Exception as e:
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chatbot.append([ f"解析项目: {txt}",
|
||||
f"尝试执行Latex指令失败。Latex没有安装, 或者不在环境变量PATH中。报错信息\n\n```\n\n{trimmed_format_exc()}\n\n```\n\n"])
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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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||||
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||||
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||||
# <-------------- clear history and read input ------------->
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history = []
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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}/**/*.tex', 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.tex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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||||
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||||
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||||
# <-------------- if is a zip/tar file ------------->
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project_folder = desend_to_extracted_folder_if_exist(project_folder)
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# <-------------- move latex project away from temp folder ------------->
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project_folder = move_project(project_folder, arxiv_id=None)
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||||
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||||
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||||
# <-------------- if merge_translate_zh is already generated, skip gpt req ------------->
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||||
if not os.path.exists(project_folder + '/merge_proofread.tex'):
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yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='proofread_latex', switch_prompt=switch_prompt)
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||||
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||||
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||||
# <-------------- compile PDF ------------->
|
||||
success = yield from 编译Latex差别(chatbot, history, main_file_original='merge', main_file_modified='merge_proofread',
|
||||
work_folder_original=project_folder, work_folder_modified=project_folder, work_folder=project_folder)
|
||||
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||||
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||||
# <-------------- zip PDF ------------->
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||||
zip_result(project_folder)
|
||||
if success:
|
||||
chatbot.append((f"成功啦", '请查收结果(压缩包)...'))
|
||||
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
|
||||
else:
|
||||
chatbot.append((f"失败了", '虽然PDF生成失败了, 但请查收结果(压缩包), 内含已经翻译的Tex文档, 也是可读的, 您可以到Github Issue区, 用该压缩包+对话历史存档进行反馈 ...'))
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||||
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
|
||||
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||||
# <-------------- we are done ------------->
|
||||
return success
|
||||
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||||
|
||||
# ========================================= 插件主程序2 =====================================================
|
||||
|
||||
@CatchException
|
||||
def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
# <-------------- information about this plugin ------------->
|
||||
chatbot.append([
|
||||
"函数插件功能?",
|
||||
"对整个Latex项目进行翻译, 生成中文PDF。函数插件贡献者: Binary-Husky。注意事项: 目前仅支持GPT3.5/GPT4,其他模型转化效果未知。目前对机器学习类文献转化效果最好,其他类型文献转化效果未知。仅在Windows系统进行了测试,其他操作系统表现未知。"])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
|
||||
# <-------------- check deps ------------->
|
||||
try:
|
||||
import glob, os, time
|
||||
os.system(f'pdflatex -version')
|
||||
from .latex_utils import Latex精细分解与转化, 编译Latex差别
|
||||
except Exception as e:
|
||||
chatbot.append([ f"解析项目: {txt}",
|
||||
f"尝试执行Latex指令失败。Latex没有安装, 或者不在环境变量PATH中。报错信息\n\n```\n\n{trimmed_format_exc()}\n\n```\n\n"])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
|
||||
|
||||
# <-------------- clear history and read input ------------->
|
||||
history = []
|
||||
txt, arxiv_id = yield from arxiv_download(chatbot, history, txt)
|
||||
if txt.endswith('.pdf'):
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"发现已经存在翻译好的PDF文档")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
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
|
||||
|
||||
|
||||
# <-------------- if is a zip/tar file ------------->
|
||||
project_folder = desend_to_extracted_folder_if_exist(project_folder)
|
||||
|
||||
|
||||
# <-------------- move latex project away from temp folder ------------->
|
||||
project_folder = move_project(project_folder, arxiv_id)
|
||||
|
||||
|
||||
# <-------------- if merge_translate_zh is already generated, skip gpt req ------------->
|
||||
if not os.path.exists(project_folder + '/merge_translate_zh.tex'):
|
||||
yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='translate_zh', switch_prompt=switch_prompt)
|
||||
|
||||
|
||||
# <-------------- compile PDF ------------->
|
||||
success = yield from 编译Latex差别(chatbot, history, main_file_original='merge', main_file_modified='merge_translate_zh',
|
||||
work_folder_original=project_folder, work_folder_modified=project_folder, work_folder=project_folder)
|
||||
|
||||
# <-------------- zip PDF ------------->
|
||||
zip_result(project_folder)
|
||||
if success:
|
||||
chatbot.append((f"成功啦", '请查收结果(压缩包)...'))
|
||||
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
|
||||
else:
|
||||
chatbot.append((f"失败了", '虽然PDF生成失败了, 但请查收结果(压缩包), 内含已经翻译的Tex文档, 也是可读的, 您可以到Github Issue区, 用该压缩包+对话历史存档进行反馈 ...'))
|
||||
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
|
||||
|
||||
# <-------------- we are done ------------->
|
||||
return success
|
||||
@ -3,6 +3,8 @@
|
||||
这个文件用于函数插件的单元测试
|
||||
运行方法 python crazy_functions/crazy_functions_test.py
|
||||
"""
|
||||
|
||||
# ==============================================================================================================================
|
||||
|
||||
def validate_path():
|
||||
import os, sys
|
||||
@ -10,10 +12,16 @@ def validate_path():
|
||||
root_dir_assume = os.path.abspath(os.path.dirname(__file__) + '/..')
|
||||
os.chdir(root_dir_assume)
|
||||
sys.path.append(root_dir_assume)
|
||||
|
||||
validate_path() # validate path so you can run from base directory
|
||||
|
||||
# ==============================================================================================================================
|
||||
|
||||
from colorful import *
|
||||
from toolbox import get_conf, ChatBotWithCookies
|
||||
import contextlib
|
||||
import os
|
||||
import sys
|
||||
from functools import wraps
|
||||
proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, API_KEY = \
|
||||
get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY')
|
||||
|
||||
@ -30,7 +38,43 @@ history = []
|
||||
system_prompt = "Serve me as a writing and programming assistant."
|
||||
web_port = 1024
|
||||
|
||||
# ==============================================================================================================================
|
||||
|
||||
def silence_stdout(func):
|
||||
@wraps(func)
|
||||
def wrapper(*args, **kwargs):
|
||||
_original_stdout = sys.stdout
|
||||
sys.stdout = open(os.devnull, 'w')
|
||||
for q in func(*args, **kwargs):
|
||||
sys.stdout = _original_stdout
|
||||
yield q
|
||||
sys.stdout = open(os.devnull, 'w')
|
||||
sys.stdout.close()
|
||||
sys.stdout = _original_stdout
|
||||
return wrapper
|
||||
|
||||
class CLI_Printer():
|
||||
def __init__(self) -> None:
|
||||
self.pre_buf = ""
|
||||
|
||||
def print(self, buf):
|
||||
bufp = ""
|
||||
for index, chat in enumerate(buf):
|
||||
a, b = chat
|
||||
bufp += sprint亮靛('[Me]:' + a) + '\n'
|
||||
bufp += '[GPT]:' + b
|
||||
if index < len(buf)-1:
|
||||
bufp += '\n'
|
||||
|
||||
if self.pre_buf!="" and bufp.startswith(self.pre_buf):
|
||||
print(bufp[len(self.pre_buf):], end='')
|
||||
else:
|
||||
print('\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n'+bufp, end='')
|
||||
self.pre_buf = bufp
|
||||
return
|
||||
|
||||
cli_printer = CLI_Printer()
|
||||
# ==============================================================================================================================
|
||||
def test_解析一个Python项目():
|
||||
from crazy_functions.解析项目源代码 import 解析一个Python项目
|
||||
txt = "crazy_functions/test_project/python/dqn"
|
||||
@ -116,6 +160,52 @@ def test_Markdown多语言():
|
||||
for cookies, cb, hist, msg in Markdown翻译指定语言(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
print(cb)
|
||||
|
||||
def test_Langchain知识库():
|
||||
from crazy_functions.Langchain知识库 import 知识库问答
|
||||
txt = "./"
|
||||
chatbot = ChatBotWithCookies(llm_kwargs)
|
||||
for cookies, cb, hist, msg in silence_stdout(知识库问答)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
cli_printer.print(cb) # print(cb)
|
||||
|
||||
chatbot = ChatBotWithCookies(cookies)
|
||||
from crazy_functions.Langchain知识库 import 读取知识库作答
|
||||
txt = "What is the installation method?"
|
||||
for cookies, cb, hist, msg in silence_stdout(读取知识库作答)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
cli_printer.print(cb) # print(cb)
|
||||
|
||||
def test_Langchain知识库读取():
|
||||
from crazy_functions.Langchain知识库 import 读取知识库作答
|
||||
txt = "远程云服务器部署?"
|
||||
for cookies, cb, hist, msg in silence_stdout(读取知识库作答)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
cli_printer.print(cb) # print(cb)
|
||||
|
||||
def test_Latex():
|
||||
from crazy_functions.Latex输出PDF结果 import Latex英文纠错加PDF对比, Latex翻译中文并重新编译PDF
|
||||
txt = "C:/Users/fuqingxu/Desktop/proofread"
|
||||
txt = "C:/Users/fuqingxu/Desktop/旧文件/gpt/paperx"
|
||||
txt = "C:/Users/fuqingxu/Desktop/旧文件/gpt/papery"
|
||||
txt = r"C:\Users\fuqingxu\Desktop\旧文件\gpt\latex2pdf\2023-06-03-14-57-06"
|
||||
txt = r"C:\Users\fuqingxu\Desktop\旧文件\gpt\latex2pdf\2023-06-03-15-40-20"
|
||||
txt = r"https://arxiv.org/abs/1902.03185"
|
||||
txt = r"C:\Users\fuqingxu\Desktop\旧文件\gpt\latex2pdf\2023-06-03-17-14-40"
|
||||
txt = r"https://arxiv.org/abs/2305.18290"
|
||||
txt = r"https://arxiv.org/abs/2305.17608"
|
||||
# txt = r"https://arxiv.org/abs/2306.00324"
|
||||
txt = r"https://arxiv.org/abs/2211.16068"
|
||||
|
||||
for cookies, cb, hist, msg in (Latex翻译中文并重新编译PDF)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
cli_printer.print(cb) # print(cb)
|
||||
|
||||
|
||||
|
||||
# txt = "2302.02948.tar"
|
||||
# print(txt)
|
||||
# main_tex, work_folder = Latex预处理(txt)
|
||||
# print('main tex:', main_tex)
|
||||
# res = 编译Latex(main_tex, work_folder)
|
||||
# # for cookies, cb, hist, msg in silence_stdout(编译Latex)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
# cli_printer.print(cb) # print(cb)
|
||||
|
||||
|
||||
|
||||
# test_解析一个Python项目()
|
||||
@ -129,7 +219,8 @@ def test_Markdown多语言():
|
||||
# test_联网回答问题()
|
||||
# test_解析ipynb文件()
|
||||
# test_数学动画生成manim()
|
||||
test_Markdown多语言()
|
||||
|
||||
# test_Langchain知识库()
|
||||
# test_Langchain知识库读取()
|
||||
test_Latex()
|
||||
input("程序完成,回车退出。")
|
||||
print("退出。")
|
||||
@ -1,4 +1,5 @@
|
||||
from toolbox import update_ui, get_conf, trimmed_format_exc
|
||||
import threading
|
||||
|
||||
def input_clipping(inputs, history, max_token_limit):
|
||||
import numpy as np
|
||||
@ -606,3 +607,94 @@ def get_files_from_everything(txt, type): # type='.md'
|
||||
success = False
|
||||
|
||||
return success, file_manifest, project_folder
|
||||
|
||||
|
||||
|
||||
|
||||
def Singleton(cls):
|
||||
_instance = {}
|
||||
|
||||
def _singleton(*args, **kargs):
|
||||
if cls not in _instance:
|
||||
_instance[cls] = cls(*args, **kargs)
|
||||
return _instance[cls]
|
||||
|
||||
return _singleton
|
||||
|
||||
|
||||
@Singleton
|
||||
class knowledge_archive_interface():
|
||||
def __init__(self) -> None:
|
||||
self.threadLock = threading.Lock()
|
||||
self.current_id = ""
|
||||
self.kai_path = None
|
||||
self.qa_handle = None
|
||||
self.text2vec_large_chinese = None
|
||||
|
||||
def get_chinese_text2vec(self):
|
||||
if self.text2vec_large_chinese is None:
|
||||
# < -------------------预热文本向量化模组--------------- >
|
||||
from toolbox import ProxyNetworkActivate
|
||||
print('Checking Text2vec ...')
|
||||
from langchain.embeddings.huggingface import HuggingFaceEmbeddings
|
||||
with ProxyNetworkActivate(): # 临时地激活代理网络
|
||||
self.text2vec_large_chinese = HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese")
|
||||
|
||||
return self.text2vec_large_chinese
|
||||
|
||||
|
||||
def feed_archive(self, file_manifest, id="default"):
|
||||
self.threadLock.acquire()
|
||||
# import uuid
|
||||
self.current_id = id
|
||||
from zh_langchain import construct_vector_store
|
||||
self.qa_handle, self.kai_path = construct_vector_store(
|
||||
vs_id=self.current_id,
|
||||
files=file_manifest,
|
||||
sentence_size=100,
|
||||
history=[],
|
||||
one_conent="",
|
||||
one_content_segmentation="",
|
||||
text2vec = self.get_chinese_text2vec(),
|
||||
)
|
||||
self.threadLock.release()
|
||||
|
||||
def get_current_archive_id(self):
|
||||
return self.current_id
|
||||
|
||||
def get_loaded_file(self):
|
||||
return self.qa_handle.get_loaded_file()
|
||||
|
||||
def answer_with_archive_by_id(self, txt, id):
|
||||
self.threadLock.acquire()
|
||||
if not self.current_id == id:
|
||||
self.current_id = id
|
||||
from zh_langchain import construct_vector_store
|
||||
self.qa_handle, self.kai_path = construct_vector_store(
|
||||
vs_id=self.current_id,
|
||||
files=[],
|
||||
sentence_size=100,
|
||||
history=[],
|
||||
one_conent="",
|
||||
one_content_segmentation="",
|
||||
text2vec = self.get_chinese_text2vec(),
|
||||
)
|
||||
VECTOR_SEARCH_SCORE_THRESHOLD = 0
|
||||
VECTOR_SEARCH_TOP_K = 4
|
||||
CHUNK_SIZE = 512
|
||||
resp, prompt = self.qa_handle.get_knowledge_based_conent_test(
|
||||
query = txt,
|
||||
vs_path = self.kai_path,
|
||||
score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
|
||||
vector_search_top_k=VECTOR_SEARCH_TOP_K,
|
||||
chunk_conent=True,
|
||||
chunk_size=CHUNK_SIZE,
|
||||
text2vec = self.get_chinese_text2vec(),
|
||||
)
|
||||
self.threadLock.release()
|
||||
return resp, prompt
|
||||
|
||||
def try_install_deps(deps):
|
||||
for dep in deps:
|
||||
import subprocess, sys
|
||||
subprocess.check_call([sys.executable, '-m', 'pip', 'install', '--user', dep])
|
||||
|
||||
606
crazy_functions/latex_utils.py
Normal file
606
crazy_functions/latex_utils.py
Normal file
@ -0,0 +1,606 @@
|
||||
from toolbox import update_ui, update_ui_lastest_msg # 刷新Gradio前端界面
|
||||
from toolbox import zip_folder, objdump, objload, promote_file_to_downloadzone
|
||||
import os, shutil
|
||||
import re
|
||||
pj = os.path.join
|
||||
|
||||
def 寻找Latex主文件(file_manifest, mode):
|
||||
"""
|
||||
在多Tex文档中,寻找主文件,必须包含documentclass,返回找到的第一个。
|
||||
P.S. 但愿没人把latex模板放在里面传进来
|
||||
"""
|
||||
for texf in file_manifest:
|
||||
if os.path.basename(texf).startswith('merge'):
|
||||
continue
|
||||
with open(texf, 'r', encoding='utf8') as f:
|
||||
file_content = f.read()
|
||||
if r'\documentclass' in file_content:
|
||||
return texf
|
||||
else:
|
||||
continue
|
||||
raise RuntimeError('无法找到一个主Tex文件(包含documentclass关键字)')
|
||||
|
||||
def merge_tex_files_(project_foler, main_file, mode):
|
||||
"""
|
||||
递归地把多Tex工程整合为一个Tex文档
|
||||
"""
|
||||
for s in reversed([q for q in re.finditer(r"\\input\{(.*?)\}", main_file, re.M)]):
|
||||
f = s.group(1)
|
||||
fp = os.path.join(project_foler, f)
|
||||
if os.path.exists(fp):
|
||||
# e.g., \input{srcs/07_appendix.tex}
|
||||
with open(fp, 'r', encoding='utf-8', errors='replace') as fx:
|
||||
c = fx.read()
|
||||
else:
|
||||
# e.g., \input{srcs/07_appendix}
|
||||
with open(fp+'.tex', 'r', encoding='utf-8', errors='replace') as fx:
|
||||
c = fx.read()
|
||||
c = merge_tex_files_(project_foler, c, mode)
|
||||
main_file = main_file[:s.span()[0]] + c + main_file[s.span()[1]:]
|
||||
return main_file
|
||||
|
||||
def merge_tex_files(project_foler, main_file, mode):
|
||||
"""
|
||||
递归地把多Tex工程整合为一个Tex文档(递归外层)
|
||||
P.S. 顺便把CTEX塞进去以支持中文
|
||||
P.S. 顺便把Latex的注释去除
|
||||
"""
|
||||
main_file = merge_tex_files_(project_foler, main_file, mode)
|
||||
if mode == 'translate_zh':
|
||||
pattern = re.compile(r'\\documentclass.*\n')
|
||||
match = pattern.search(main_file)
|
||||
position = match.end()
|
||||
main_file = main_file[:position] + '\\usepackage{CTEX}\n\\usepackage{url}\n' + main_file[position:]
|
||||
|
||||
new_file_remove_comment_lines = []
|
||||
for l in main_file.splitlines():
|
||||
# 删除整行的空注释
|
||||
if l.startswith("%") or (l.startswith(" ") and l.lstrip().startswith("%")):
|
||||
pass
|
||||
else:
|
||||
new_file_remove_comment_lines.append(l)
|
||||
main_file = '\n'.join(new_file_remove_comment_lines)
|
||||
main_file = re.sub(r'(?<!\\)%.*', '', main_file) # 使用正则表达式查找半行注释, 并替换为空字符串
|
||||
return main_file
|
||||
|
||||
|
||||
class LinkedListNode():
|
||||
"""
|
||||
链表单元
|
||||
"""
|
||||
def __init__(self, string, preserve=True) -> None:
|
||||
self.string = string
|
||||
self.preserve = preserve
|
||||
self.next = None
|
||||
|
||||
|
||||
def mod_inbraket(match):
|
||||
"""
|
||||
为啥chatgpt会把cite里面的逗号换成中文逗号呀 艹
|
||||
"""
|
||||
# get the matched string
|
||||
cmd = match.group(1)
|
||||
str_to_modify = match.group(2)
|
||||
# modify the matched string
|
||||
str_to_modify = str_to_modify.replace(':', ':') # 前面是中文冒号,后面是英文冒号
|
||||
str_to_modify = str_to_modify.replace(',', ',') # 前面是中文逗号,后面是英文逗号
|
||||
# str_to_modify = 'BOOM'
|
||||
return "\\" + cmd + "{" + str_to_modify + "}"
|
||||
|
||||
def fix_content(final_tex, node_string):
|
||||
"""
|
||||
Fix common GPT errors to increase success rate
|
||||
"""
|
||||
final_tex = final_tex.replace('%', r'\%')
|
||||
final_tex = final_tex.replace(r'\%', r'\\%')
|
||||
final_tex = re.sub(r"\\([a-z]{2,10})\ \{", r"\\\1{", string=final_tex)
|
||||
final_tex = re.sub(r"\\\ ([a-z]{2,10})\{", r"\\\1{", string=final_tex)
|
||||
final_tex = re.sub(r"\\([a-z]{2,10})\{([^\}]*?)\}", mod_inbraket, string=final_tex)
|
||||
if node_string.count('{') != node_string.count('}'):
|
||||
if final_tex.count('{') != node_string.count('{'):
|
||||
final_tex = node_string # 出问题了,还原原文
|
||||
if final_tex.count('}') != node_string.count('}'):
|
||||
final_tex = node_string # 出问题了,还原原文
|
||||
|
||||
return final_tex
|
||||
|
||||
class LatexPaperSplit():
|
||||
"""
|
||||
将Latex文档分解到一个链表中,每个链表节点用preserve的标志位提示它是否应当被GPT处理
|
||||
"""
|
||||
def __init__(self) -> None:
|
||||
"""
|
||||
root是链表的根节点
|
||||
"""
|
||||
self.root = None
|
||||
|
||||
def merge_result(self, arr, mode, msg):
|
||||
"""
|
||||
将GPT处理后的结果融合
|
||||
"""
|
||||
result_string = ""
|
||||
node = self.root
|
||||
p = 0
|
||||
while True:
|
||||
if node.preserve:
|
||||
result_string += node.string
|
||||
else:
|
||||
result_string += fix_content(arr[p], node.string)
|
||||
p += 1
|
||||
node = node.next
|
||||
if node is None: break
|
||||
if mode == 'translate_zh':
|
||||
try:
|
||||
pattern = re.compile(r'\\begin\{abstract\}.*\n')
|
||||
match = pattern.search(result_string)
|
||||
position = match.end()
|
||||
result_string = result_string[:position] + \
|
||||
"{\\scriptsize\\textbf{警告:该PDF由GPT-Academic开源项目调用大语言模型+Latex翻译插件一键生成,其内容可靠性没有任何保障,请仔细鉴别并以原文为准。" + \
|
||||
"项目Github地址 \\url{https://github.com/binary-husky/gpt_academic/}。" + \
|
||||
msg + \
|
||||
"为了防止大语言模型的意外谬误产生扩散影响,禁止移除或修改此警告。}}\\\\" + \
|
||||
result_string[position:]
|
||||
except:
|
||||
pass
|
||||
return result_string
|
||||
|
||||
def split(self, txt, project_folder):
|
||||
"""
|
||||
将Latex文档分解到一个链表中,每个链表节点用preserve的标志位提示它是否应当被GPT处理
|
||||
"""
|
||||
root = LinkedListNode(txt, False)
|
||||
def split_worker(root, pattern, flags=0):
|
||||
lt = root
|
||||
cnt = 0
|
||||
pattern_compile = re.compile(pattern, flags)
|
||||
while True:
|
||||
if not lt.preserve:
|
||||
while True:
|
||||
res = pattern_compile.search(lt.string)
|
||||
if not res: break
|
||||
before = res.string[:res.span()[0]]
|
||||
this = res.group(0)
|
||||
after = res.string[res.span()[1]:]
|
||||
# ======
|
||||
lt.string = before
|
||||
tmp = lt.next
|
||||
# ======
|
||||
mid = LinkedListNode(this, True)
|
||||
lt.next = mid
|
||||
# ======
|
||||
aft = LinkedListNode(after, False)
|
||||
mid.next = aft
|
||||
aft.next = tmp
|
||||
# ======
|
||||
lt = aft
|
||||
lt = lt.next
|
||||
cnt += 1
|
||||
# print(cnt)
|
||||
if lt is None: break
|
||||
|
||||
def split_worker_begin_end(root, pattern, flags=0, limit_n_lines=25):
|
||||
lt = root
|
||||
cnt = 0
|
||||
pattern_compile = re.compile(pattern, flags)
|
||||
while True:
|
||||
if not lt.preserve:
|
||||
while True:
|
||||
target_string = lt.string
|
||||
|
||||
def search_with_line_limit(target_string):
|
||||
for res in pattern_compile.finditer(target_string):
|
||||
cmd = res.group(1) # begin{what}
|
||||
this = res.group(2) # content between begin and end
|
||||
white_list = ['document', 'abstract', 'lemma', 'definition', 'sproof', 'em', 'emph', 'textit', 'textbf']
|
||||
if cmd in white_list or this.count('\n') > 25:
|
||||
sub_res = search_with_line_limit(this)
|
||||
if not sub_res: continue
|
||||
else: return sub_res
|
||||
else:
|
||||
return res.group(0)
|
||||
return False
|
||||
# ======
|
||||
# search for first encounter of \begin \end pair with less than 25 lines in the middle
|
||||
ps = search_with_line_limit(target_string)
|
||||
if not ps: break
|
||||
res = re.search(re.escape(ps), target_string, flags)
|
||||
if not res: assert False
|
||||
before = res.string[:res.span()[0]]
|
||||
this = res.group(0)
|
||||
after = res.string[res.span()[1]:]
|
||||
# ======
|
||||
lt.string = before
|
||||
tmp = lt.next
|
||||
# ======
|
||||
mid = LinkedListNode(this, True)
|
||||
lt.next = mid
|
||||
# ======
|
||||
aft = LinkedListNode(after, False)
|
||||
mid.next = aft
|
||||
aft.next = tmp
|
||||
# ======
|
||||
lt = aft
|
||||
lt = lt.next
|
||||
cnt += 1
|
||||
# print(cnt)
|
||||
if lt is None: break
|
||||
|
||||
|
||||
# root 是链表的头
|
||||
print('正在分解Latex源文件,构建链表结构')
|
||||
# 删除iffalse注释
|
||||
split_worker(root, r"\\iffalse(.*?)\\fi", re.DOTALL)
|
||||
# 吸收在25行以内的begin-end组合
|
||||
split_worker_begin_end(root, r"\\begin\{([a-z\*]*)\}(.*?)\\end\{\1\}", re.DOTALL, limit_n_lines=25)
|
||||
# 吸收匿名公式
|
||||
split_worker(root, r"\$\$(.*?)\$\$", re.DOTALL)
|
||||
# 吸收其他杂项
|
||||
split_worker(root, r"(.*?)\\maketitle", re.DOTALL)
|
||||
split_worker(root, r"\\section\{(.*?)\}")
|
||||
split_worker(root, r"\\section\*\{(.*?)\}")
|
||||
split_worker(root, r"\\subsection\{(.*?)\}")
|
||||
split_worker(root, r"\\subsubsection\{(.*?)\}")
|
||||
split_worker(root, r"\\bibliography\{(.*?)\}")
|
||||
split_worker(root, r"\\bibliographystyle\{(.*?)\}")
|
||||
split_worker(root, r"\\begin\{lstlisting\}(.*?)\\end\{lstlisting\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{wraptable\}(.*?)\\end\{wraptable\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{algorithm\}(.*?)\\end\{algorithm\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{wrapfigure\}(.*?)\\end\{wrapfigure\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{wrapfigure\*\}(.*?)\\end\{wrapfigure\*\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{figure\}(.*?)\\end\{figure\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{figure\*\}(.*?)\\end\{figure\*\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{multline\}(.*?)\\end\{multline\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{multline\*\}(.*?)\\end\{multline\*\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{table\}(.*?)\\end\{table\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{table\*\}(.*?)\\end\{table\*\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{minipage\}(.*?)\\end\{minipage\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{minipage\*\}(.*?)\\end\{minipage\*\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{align\*\}(.*?)\\end\{align\*\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{align\}(.*?)\\end\{align\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{equation\}(.*?)\\end\{equation\}", re.DOTALL)
|
||||
split_worker(root, r"\\begin\{equation\*\}(.*?)\\end\{equation\*\}", re.DOTALL)
|
||||
split_worker(root, r"\\item ")
|
||||
split_worker(root, r"\\label\{(.*?)\}")
|
||||
split_worker(root, r"\\begin\{(.*?)\}")
|
||||
split_worker(root, r"\\vspace\{(.*?)\}")
|
||||
split_worker(root, r"\\hspace\{(.*?)\}")
|
||||
split_worker(root, r"\\end\{(.*?)\}")
|
||||
|
||||
node = root
|
||||
while True:
|
||||
if len(node.string.strip('\n').strip(''))==0: node.preserve = True
|
||||
if len(node.string.strip('\n').strip(''))<50: node.preserve = True
|
||||
node = node.next
|
||||
if node is None: break
|
||||
|
||||
# 修复括号
|
||||
node = root
|
||||
while True:
|
||||
string = node.string
|
||||
if node.preserve:
|
||||
node = node.next
|
||||
if node is None: break
|
||||
continue
|
||||
def break_check(string):
|
||||
str_stack = [""] # (lv, index)
|
||||
for i, c in enumerate(string):
|
||||
if c == '{':
|
||||
str_stack.append('{')
|
||||
elif c == '}':
|
||||
if len(str_stack) == 1:
|
||||
print('stack kill')
|
||||
return i
|
||||
str_stack.pop(-1)
|
||||
else:
|
||||
str_stack[-1] += c
|
||||
return -1
|
||||
bp = break_check(string)
|
||||
|
||||
if bp == -1:
|
||||
pass
|
||||
elif bp == 0:
|
||||
node.string = string[:1]
|
||||
q = LinkedListNode(string[1:], False)
|
||||
q.next = node.next
|
||||
node.next = q
|
||||
else:
|
||||
node.string = string[:bp]
|
||||
q = LinkedListNode(string[bp:], False)
|
||||
q.next = node.next
|
||||
node.next = q
|
||||
|
||||
node = node.next
|
||||
if node is None: break
|
||||
|
||||
node = root
|
||||
while True:
|
||||
if len(node.string.strip('\n').strip(''))==0: node.preserve = True
|
||||
if len(node.string.strip('\n').strip(''))<50: node.preserve = True
|
||||
node = node.next
|
||||
if node is None: break
|
||||
|
||||
# 将前后断行符脱离
|
||||
node = root
|
||||
prev_node = None
|
||||
while True:
|
||||
if not node.preserve:
|
||||
lstriped_ = node.string.lstrip().lstrip('\n')
|
||||
if (prev_node is not None) and (prev_node.preserve) and (len(lstriped_)!=len(node.string)):
|
||||
prev_node.string += node.string[:-len(lstriped_)]
|
||||
node.string = lstriped_
|
||||
rstriped_ = node.string.rstrip().rstrip('\n')
|
||||
if (node.next is not None) and (node.next.preserve) and (len(rstriped_)!=len(node.string)):
|
||||
node.next.string = node.string[len(rstriped_):] + node.next.string
|
||||
node.string = rstriped_
|
||||
# =====
|
||||
prev_node = node
|
||||
node = node.next
|
||||
if node is None: break
|
||||
|
||||
# 将分解结果返回 res_to_t
|
||||
with open(pj(project_folder, 'debug_log.html'), 'w', encoding='utf8') as f:
|
||||
res_to_t = []
|
||||
node = root
|
||||
while True:
|
||||
show_html = node.string.replace('\n','<br/>')
|
||||
if not node.preserve:
|
||||
res_to_t.append(node.string)
|
||||
f.write(f'<p style="color:black;">#{show_html}#</p>')
|
||||
else:
|
||||
f.write(f'<p style="color:red;">{show_html}</p>')
|
||||
node = node.next
|
||||
if node is None: break
|
||||
|
||||
self.root = root
|
||||
self.sp = res_to_t
|
||||
return self.sp
|
||||
|
||||
class LatexPaperFileGroup():
|
||||
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_llm.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=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 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):
|
||||
manifest = []
|
||||
for path, res in zip(self.file_paths, self.file_result):
|
||||
with open(path + '.polish.tex', 'w', encoding='utf8') as f:
|
||||
manifest.append(path + '.polish.tex')
|
||||
f.write(res)
|
||||
return manifest
|
||||
|
||||
|
||||
|
||||
def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='proofread', switch_prompt=None):
|
||||
import time, os, re
|
||||
from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
|
||||
from .latex_utils import LatexPaperFileGroup, merge_tex_files, LatexPaperSplit, 寻找Latex主文件
|
||||
|
||||
# <-------- 寻找主tex文件 ---------->
|
||||
maintex = 寻找Latex主文件(file_manifest, mode)
|
||||
chatbot.append((f"定位主Latex文件", f'[Local Message] 分析结果:该项目的Latex主文件是{maintex}, 如果分析错误, 请立即终止程序, 删除或修改歧义文件, 然后重试。主程序即将开始, 请稍候。'))
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
time.sleep(5)
|
||||
|
||||
# <-------- 读取Latex文件, 将多文件tex工程融合为一个巨型tex ---------->
|
||||
main_tex_basename = os.path.basename(maintex)
|
||||
assert main_tex_basename.endswith('.tex')
|
||||
main_tex_basename_bare = main_tex_basename[:-4]
|
||||
may_exist_bbl = pj(project_folder, f'{main_tex_basename_bare}.bbl')
|
||||
if os.path.exists(may_exist_bbl):
|
||||
shutil.copyfile(may_exist_bbl, pj(project_folder, f'merge.bbl'))
|
||||
shutil.copyfile(may_exist_bbl, pj(project_folder, f'merge_{mode}.bbl'))
|
||||
shutil.copyfile(may_exist_bbl, pj(project_folder, f'merge_diff.bbl'))
|
||||
|
||||
with open(maintex, 'r', encoding='utf-8', errors='replace') as f:
|
||||
content = f.read()
|
||||
merged_content = merge_tex_files(project_folder, content, mode)
|
||||
|
||||
with open(project_folder + '/merge.tex', 'w', encoding='utf-8', errors='replace') as f:
|
||||
f.write(merged_content)
|
||||
|
||||
# <-------- 精细切分latex文件 ---------->
|
||||
lps = LatexPaperSplit()
|
||||
res = lps.split(merged_content, project_folder)
|
||||
|
||||
# <-------- 拆分过长的latex片段 ---------->
|
||||
pfg = LatexPaperFileGroup()
|
||||
for index, r in enumerate(res):
|
||||
pfg.file_paths.append('segment-' + str(index))
|
||||
pfg.file_contents.append(r)
|
||||
|
||||
pfg.run_file_split(max_token_limit=1024)
|
||||
n_split = len(pfg.sp_file_contents)
|
||||
|
||||
# <-------- 根据需要切换prompt ---------->
|
||||
inputs_array, sys_prompt_array = switch_prompt(pfg, mode)
|
||||
inputs_show_user_array = [f"{mode} {f}" for f in pfg.sp_file_tag]
|
||||
|
||||
if os.path.exists(pj(project_folder,'temp.pkl')):
|
||||
|
||||
# <-------- 【仅调试】如果存在调试缓存文件,则跳过GPT请求环节 ---------->
|
||||
pfg = objload(file=pj(project_folder,'temp.pkl'))
|
||||
|
||||
else:
|
||||
# <-------- gpt 多线程请求 ---------->
|
||||
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, # 并行任务数量限制, 最多同时执行5个, 其他的排队等待
|
||||
scroller_max_len = 40
|
||||
)
|
||||
|
||||
# <-------- 文本碎片重组为完整的tex片段 ---------->
|
||||
pfg.sp_file_result = []
|
||||
for i_say, gpt_say, orig_content in zip(gpt_response_collection[0::2], gpt_response_collection[1::2], pfg.sp_file_contents):
|
||||
pfg.sp_file_result.append(gpt_say)
|
||||
pfg.merge_result()
|
||||
|
||||
# <-------- 临时存储用于调试 ---------->
|
||||
pfg.get_token_num = None
|
||||
objdump(pfg, file=pj(project_folder,'temp.pkl'))
|
||||
|
||||
|
||||
# <-------- 写出文件 ---------->
|
||||
msg = f"当前大语言模型: {llm_kwargs['llm_model']},当前语言模型温度设定: {llm_kwargs['temperature']}。"
|
||||
final_tex = lps.merge_result(pfg.file_result, mode, msg)
|
||||
with open(project_folder + f'/merge_{mode}.tex', 'w', encoding='utf-8', errors='replace') as f:
|
||||
f.write(final_tex)
|
||||
|
||||
# <-------- 整理结果, 退出 ---------->
|
||||
chatbot.append((f"完成了吗?", 'GPT结果已输出, 正在编译PDF'))
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
# <-------- 返回 ---------->
|
||||
return project_folder + f'/merge_{mode}.tex'
|
||||
|
||||
|
||||
|
||||
def remove_buggy_lines(file_path, log_path, tex_name, tex_name_pure, n_fix, work_folder_modified):
|
||||
try:
|
||||
with open(log_path, 'r', encoding='utf-8', errors='replace') as f:
|
||||
log = f.read()
|
||||
with open(file_path, 'r', encoding='utf-8', errors='replace') as f:
|
||||
file_lines = f.readlines()
|
||||
import re
|
||||
buggy_lines = re.findall(tex_name+':([0-9]{1,5}):', log)
|
||||
buggy_lines = [int(l) for l in buggy_lines]
|
||||
buggy_lines = sorted(buggy_lines)
|
||||
print("removing lines that has errors", buggy_lines)
|
||||
file_lines.pop(buggy_lines[0]-1)
|
||||
with open(pj(work_folder_modified, f"{tex_name_pure}_fix_{n_fix}.tex"), 'w', encoding='utf-8', errors='replace') as f:
|
||||
f.writelines(file_lines)
|
||||
return True, f"{tex_name_pure}_fix_{n_fix}", buggy_lines
|
||||
except:
|
||||
return False, 0, [0]
|
||||
|
||||
|
||||
def compile_latex_with_timeout(command, timeout=60):
|
||||
import subprocess
|
||||
process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
|
||||
try:
|
||||
stdout, stderr = process.communicate(timeout=timeout)
|
||||
except subprocess.TimeoutExpired:
|
||||
process.kill()
|
||||
stdout, stderr = process.communicate()
|
||||
print("Process timed out!")
|
||||
return False
|
||||
return True
|
||||
|
||||
def 编译Latex差别(chatbot, history, main_file_original, main_file_modified, work_folder_original, work_folder_modified, work_folder):
|
||||
import os, time
|
||||
current_dir = os.getcwd()
|
||||
n_fix = 1
|
||||
max_try = 32
|
||||
chatbot.append([f"正在编译PDF文档", f'编译已经开始。当前工作路径为{work_folder},如果程序停顿5分钟以上,则大概率是卡死在Latex里面了。不幸卡死时请直接去该路径下取回翻译结果,或者重启之后再度尝试 ...']); yield from update_ui(chatbot=chatbot, history=history)
|
||||
chatbot.append([f"正在编译PDF文档", '...']); yield from update_ui(chatbot=chatbot, history=history); time.sleep(1); chatbot[-1] = list(chatbot[-1]) # 刷新界面
|
||||
yield from update_ui_lastest_msg('编译已经开始...', chatbot, history) # 刷新Gradio前端界面
|
||||
|
||||
while True:
|
||||
import os
|
||||
# https://stackoverflow.com/questions/738755/dont-make-me-manually-abort-a-latex-compile-when-theres-an-error
|
||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history) # 刷新Gradio前端界面
|
||||
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex'); os.chdir(current_dir)
|
||||
|
||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history) # 刷新Gradio前端界面
|
||||
os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex'); os.chdir(current_dir)
|
||||
|
||||
if ok and os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf')):
|
||||
# 只有第二步成功,才能继续下面的步骤
|
||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译BibTex ...', chatbot, history) # 刷新Gradio前端界面
|
||||
if not os.path.exists(pj(work_folder_original, f'{main_file_original}.bbl')):
|
||||
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'bibtex {main_file_original}.aux'); os.chdir(current_dir)
|
||||
if not os.path.exists(pj(work_folder_modified, f'{main_file_modified}.bbl')):
|
||||
os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'bibtex {main_file_modified}.aux'); os.chdir(current_dir)
|
||||
|
||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译文献交叉引用 ...', chatbot, history) # 刷新Gradio前端界面
|
||||
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex'); os.chdir(current_dir)
|
||||
os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex'); os.chdir(current_dir)
|
||||
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex'); os.chdir(current_dir)
|
||||
os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex'); os.chdir(current_dir)
|
||||
|
||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
|
||||
print( f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex')
|
||||
ok = compile_latex_with_timeout(f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex')
|
||||
|
||||
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history) # 刷新Gradio前端界面
|
||||
os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
|
||||
os.chdir(work_folder); ok = compile_latex_with_timeout(f'bibtex merge_diff.aux'); os.chdir(current_dir)
|
||||
os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
|
||||
os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
|
||||
|
||||
# <--------------------->
|
||||
os.chdir(current_dir)
|
||||
|
||||
# <---------- 检查结果 ----------->
|
||||
results_ = ""
|
||||
original_pdf_success = os.path.exists(pj(work_folder_original, f'{main_file_original}.pdf'))
|
||||
modified_pdf_success = os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf'))
|
||||
diff_pdf_success = os.path.exists(pj(work_folder, f'merge_diff.pdf'))
|
||||
results_ += f"原始PDF编译是否成功: {original_pdf_success};"
|
||||
results_ += f"转化PDF编译是否成功: {modified_pdf_success};"
|
||||
results_ += f"对比PDF编译是否成功: {diff_pdf_success};"
|
||||
yield from update_ui_lastest_msg(f'第{n_fix}编译结束:<br/>{results_}...', chatbot, history) # 刷新Gradio前端界面
|
||||
|
||||
if modified_pdf_success:
|
||||
yield from update_ui_lastest_msg(f'转化PDF编译已经成功, 即将退出 ...', chatbot, history) # 刷新Gradio前端界面
|
||||
os.chdir(current_dir)
|
||||
result_pdf = pj(work_folder_modified, f'{main_file_modified}.pdf')
|
||||
if os.path.exists(pj(work_folder, '..', 'translation')):
|
||||
shutil.copyfile(result_pdf, pj(work_folder, '..', 'translation', 'translate_zh.pdf'))
|
||||
promote_file_to_downloadzone(result_pdf)
|
||||
return True # 成功啦
|
||||
else:
|
||||
if n_fix>=max_try: break
|
||||
n_fix += 1
|
||||
can_retry, main_file_modified, buggy_lines = remove_buggy_lines(
|
||||
file_path=pj(work_folder_modified, f'{main_file_modified}.tex'),
|
||||
log_path=pj(work_folder_modified, f'{main_file_modified}.log'),
|
||||
tex_name=f'{main_file_modified}.tex',
|
||||
tex_name_pure=f'{main_file_modified}',
|
||||
n_fix=n_fix,
|
||||
work_folder_modified=work_folder_modified,
|
||||
)
|
||||
yield from update_ui_lastest_msg(f'由于最为关键的转化PDF编译失败, 将根据报错信息修正tex源文件并重试, 当前报错的latex代码处于第{buggy_lines}行 ...', chatbot, history) # 刷新Gradio前端界面
|
||||
if not can_retry: break
|
||||
|
||||
os.chdir(current_dir)
|
||||
return False # 失败啦
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user