Merge branch 'master' into HEAD

Co-authored-by: 柯仕锋 <12029064@zju.edu.cn>

Dockerfile

@@ -3,39 +3,36 @@
 # - 如何构建: 先修改 `config.py`， 然后 `docker build -t gpt-academic . `
 # - 如何运行(Linux下): `docker run --rm -it --net=host gpt-academic `
 # - 如何运行(其他操作系统，选择任意一个固定端口50923): `docker run --rm -it -e WEB_PORT=50923 -p 50923:50923 gpt-academic `
-FROM python:3.11
 
+FROM ghcr.io/astral-sh/uv:python3.12-bookworm
 
 # 非必要步骤，更换pip源 （以下三行，可以删除）
 RUN echo '[global]' > /etc/pip.conf && \
     echo 'index-url = https://mirrors.aliyun.com/pypi/simple/' >> /etc/pip.conf && \
     echo 'trusted-host = mirrors.aliyun.com' >> /etc/pip.conf
 
-
-# 语音输出功能（以下两行，第一行更换阿里源，第二行安装ffmpeg，都可以删除）
-RUN UBUNTU_VERSION=$(awk -F= '/^VERSION_CODENAME=/{print $2}' /etc/os-release); echo "deb https://mirrors.aliyun.com/debian/ $UBUNTU_VERSION main non-free contrib" > /etc/apt/sources.list; apt-get update
+# 语音输出功能（以下1,2行更换阿里源，第3,4行安装ffmpeg，都可以删除） 
+RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
+    sed -i 's/security.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
+    apt-get update
 RUN apt-get install ffmpeg -y
 RUN apt-get clean
 
-
 # 进入工作路径（必要）
 WORKDIR /gpt
 
-
 # 安装大部分依赖，利用Docker缓存加速以后的构建 （以下两行，可以删除）
 COPY requirements.txt ./
-RUN pip3 install -r requirements.txt
-
+RUN uv venv --python=3.12 && uv pip install --verbose -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
+ENV PATH="/gpt/.venv/bin:$PATH"
+RUN python -c 'import loguru'
 
 # 装载项目文件，安装剩余依赖（必要）
 COPY . .
-RUN pip3 install -r requirements.txt
-
-
-# 非必要步骤，用于预热模块（可以删除）
-RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
-RUN python3 -m pip cache purge
+RUN uv venv --python=3.12 && uv pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
 
+# # 非必要步骤，用于预热模块（可以删除）
+RUN python -c 'from check_proxy import warm_up_modules; warm_up_modules()'
 
 # 启动（必要）
-CMD ["python3", "-u", "main.py"]
+CMD ["bash", "-c", "python main.py"]

README.md

@@ -1,4 +1,5 @@
 > [!IMPORTANT]
+> `master主分支`最新动态(2025.7.31): 新GUI前端，Coming Soon
 > `master主分支`最新动态(2025.3.2): 修复大量代码typo / 联网组件支持Jina的api / 增加deepseek-r1支持  
 > `frontier开发分支`最新动态(2024.12.9): 更新对话时间线功能，优化xelatex论文翻译  
 > `wiki文档`最新动态(2024.12.5): 更新ollama接入指南  

config.py

@@ -7,11 +7,11 @@
     Configuration reading priority: environment variable > config_private.py > config.py
 """
 
-# [step 1-1]>> ( 接入GPT等模型 ) API_KEY = "sk-123456789xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx123456789"。极少数情况下，还需要填写组织（格式如org-123456789abcdefghijklmno的），请向下翻，找 API_ORG 设置项
+# [step 1-1]>> ( 接入OpenAI模型家族 ) API_KEY = "sk-123456789xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx123456789"。极少数情况下，还需要填写组织（格式如org-123456789abcdefghijklmno的），请向下翻，找 API_ORG 设置项
 API_KEY = "在此处填写APIKEY"    # 可同时填写多个API-KEY，用英文逗号分割，例如API_KEY = "sk-openaikey1,sk-openaikey2,fkxxxx-api2dkey3,azure-apikey4"
 
-# [step 1-2]>> ( 接入通义 qwen-max ) 接入通义千问在线大模型，api-key获取地址 https://dashscope.console.aliyun.com/
-DASHSCOPE_API_KEY = "" # 阿里灵积云API_KEY
+# [step 1-2]>> ( 强烈推荐！接入通义家族 & 大模型服务平台百炼 ) 接入通义千问在线大模型，api-key获取地址 https://dashscope.console.aliyun.com/
+DASHSCOPE_API_KEY = "" # 阿里灵积云API_KEY（用于接入qwen-max，dashscope-qwen3-14b，dashscope-deepseek-r1等）
 
 # [step 1-3]>> ( 接入 deepseek-reasoner, 即 deepseek-r1 ) 深度求索(DeepSeek) API KEY，默认请求地址为"https://api.deepseek.com/v1/chat/completions"
 DEEPSEEK_API_KEY = ""
@@ -43,7 +43,10 @@ AVAIL_LLM_MODELS = ["qwen-max", "o1-mini", "o1-mini-2024-09-12", "o1", "o1-2024-
                     "gpt-3.5-turbo-1106", "gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5",
                     "gpt-4", "gpt-4-32k", "azure-gpt-4", "glm-4", "glm-4v", "glm-3-turbo",
                     "gemini-1.5-pro", "chatglm3", "chatglm4",
-                    "deepseek-chat", "deepseek-coder", "deepseek-reasoner"
+                    "deepseek-chat", "deepseek-coder", "deepseek-reasoner", 
+                    "volcengine-deepseek-r1-250120", "volcengine-deepseek-v3-241226",
+                    "dashscope-deepseek-r1", "dashscope-deepseek-v3",
+                    "dashscope-qwen3-14b", "dashscope-qwen3-235b-a22b", "dashscope-qwen3-32b",
                     ]
 
 EMBEDDING_MODEL = "text-embedding-3-small"
@@ -267,6 +270,10 @@ MOONSHOT_API_KEY = ""
 YIMODEL_API_KEY = ""
 
 
+# 接入火山引擎的在线大模型)，api-key获取地址 https://console.volcengine.com/ark/region:ark+cn-beijing/endpoint
+ARK_API_KEY = "00000000-0000-0000-0000-000000000000" # 火山引擎 API KEY
+
+
 # 紫东太初大模型 https://ai-maas.wair.ac.cn
 TAICHU_API_KEY = ""
 
@@ -347,6 +354,17 @@ DAAS_SERVER_URLS = [ f"https://niuziniu-biligpt{i}.hf.space/stream" for i in ran
 # 在互联网搜索组件中，负责将搜索结果整理成干净的Markdown
 JINA_API_KEY = ""
 
+
+# 是否自动裁剪上下文长度（是否启动，默认不启动）
+AUTO_CONTEXT_CLIP_ENABLE = False
+# 目标裁剪上下文的token长度（如果超过这个长度，则会自动裁剪）
+AUTO_CONTEXT_CLIP_TRIGGER_TOKEN_LEN = 30*1000
+# 无条件丢弃x以上的轮数
+AUTO_CONTEXT_MAX_ROUND = 64
+# 在裁剪上下文时，倒数第x次对话能“最多”保留的上下文token的比例占 AUTO_CONTEXT_CLIP_TRIGGER_TOKEN_LEN 的多少
+AUTO_CONTEXT_MAX_CLIP_RATIO = [0.80, 0.60, 0.45, 0.25, 0.20, 0.18, 0.16, 0.14, 0.12, 0.10, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01]
+
+
 """
 --------------- 配置关联关系说明 ---------------
 

config_private.py

@@ -106,7 +106,7 @@ AVAIL_FONTS = [
 
 
 # 默认的系统提示词（system prompt）
-INIT_SYS_PROMPT = "Serve me as a writing and programming assistant."
+INIT_SYS_PROMPT = " "
 
 
 # 对话窗的高度 （仅在LAYOUT="TOP-DOWN"时生效）

crazy_functions/Conversation_To_File.py

@@ -1,10 +1,11 @@
-from toolbox import CatchException, update_ui, promote_file_to_downloadzone, get_log_folder, get_user
-from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
 import re
+from toolbox import CatchException, update_ui, promote_file_to_downloadzone, get_log_folder, get_user, update_ui_latest_msg
+from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
+from loguru import logger
 
 f_prefix = 'GPT-Academic对话存档'
 
-def write_chat_to_file(chatbot, history=None, file_name=None):
+def write_chat_to_file_legacy(chatbot, history=None, file_name=None):
     """
     将对话记录history以Markdown格式写入文件中。如果没有指定文件名，则使用当前时间生成文件名。
     """
@@ -12,6 +13,9 @@ def write_chat_to_file(chatbot, history=None, file_name=None):
     import time
     from themes.theme import advanced_css
 
+    if (file_name is not None) and (file_name != "") and (not file_name.endswith('.html')): file_name += '.html'
+    else: file_name = None
+
     if file_name is None:
         file_name = f_prefix + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.html'
     fp = os.path.join(get_log_folder(get_user(chatbot), plugin_name='chat_history'), file_name)
@@ -68,6 +72,147 @@ def write_chat_to_file(chatbot, history=None, file_name=None):
     promote_file_to_downloadzone(fp, rename_file=file_name, chatbot=chatbot)
     return '对话历史写入：' + fp
 
+def write_chat_to_file(chatbot, history=None, file_name=None):
+    """
+    将对话记录history以多种格式（HTML、Word、Markdown）写入文件中。如果没有指定文件名，则使用当前时间生成文件名。
+    
+    Args:
+        chatbot: 聊天机器人对象，包含对话内容
+        history: 对话历史记录
+        file_name: 指定的文件名，如果为None则使用时间戳
+        
+    Returns:
+        str: 提示信息，包含文件保存路径
+    """
+    import os
+    import time
+    import asyncio
+    import aiofiles
+    from toolbox import promote_file_to_downloadzone
+    from crazy_functions.doc_fns.conversation_doc.excel_doc import save_chat_tables
+    from crazy_functions.doc_fns.conversation_doc.html_doc import HtmlFormatter
+    from crazy_functions.doc_fns.conversation_doc.markdown_doc import MarkdownFormatter
+    from crazy_functions.doc_fns.conversation_doc.word_doc import WordFormatter
+    from crazy_functions.doc_fns.conversation_doc.txt_doc import TxtFormatter
+    from crazy_functions.doc_fns.conversation_doc.word2pdf import WordToPdfConverter
+
+    async def save_html():
+        try:
+            html_formatter = HtmlFormatter(chatbot, history)
+            html_content = html_formatter.create_document()
+            html_file = os.path.join(save_dir, base_name + '.html')
+            async with aiofiles.open(html_file, 'w', encoding='utf8') as f:
+                await f.write(html_content)
+            return html_file
+        except Exception as e:
+            print(f"保存HTML格式失败: {str(e)}")
+            return None
+
+    async def save_word():
+        try:
+            word_formatter = WordFormatter()
+            doc = word_formatter.create_document(history)
+            docx_file = os.path.join(save_dir, base_name + '.docx')
+            # 由于python-docx不支持异步，使用线程池执行
+            loop = asyncio.get_event_loop()
+            await loop.run_in_executor(None, doc.save, docx_file)
+            return docx_file
+        except Exception as e:
+            print(f"保存Word格式失败: {str(e)}")
+            return None
+    async def save_pdf(docx_file):
+        try:
+            if docx_file:
+                # 获取文件名和保存路径
+                pdf_file = os.path.join(save_dir, base_name + '.pdf')
+                
+                # 在线程池中执行转换
+                loop = asyncio.get_event_loop()
+                pdf_file = await loop.run_in_executor(
+                    None, 
+                    WordToPdfConverter.convert_to_pdf,
+                    docx_file
+                    # save_dir
+                )
+                
+                return pdf_file
+                
+        except Exception as e:
+            print(f"保存PDF格式失败: {str(e)}")
+            return None
+
+    async def save_markdown():
+        try:
+            md_formatter = MarkdownFormatter()
+            md_content = md_formatter.create_document(history)
+            md_file = os.path.join(save_dir, base_name + '.md')
+            async with aiofiles.open(md_file, 'w', encoding='utf8') as f:
+                await f.write(md_content)
+            return md_file
+        except Exception as e:
+            print(f"保存Markdown格式失败: {str(e)}")
+            return None
+
+    async def save_txt():
+        try:
+            txt_formatter = TxtFormatter()
+            txt_content = txt_formatter.create_document(history)
+            txt_file = os.path.join(save_dir, base_name + '.txt')
+            async with aiofiles.open(txt_file, 'w', encoding='utf8') as f:
+                await f.write(txt_content)
+            return txt_file
+        except Exception as e:
+            print(f"保存TXT格式失败: {str(e)}")
+            return None
+
+    async def main():
+        # 并发执行所有保存任务
+        html_task = asyncio.create_task(save_html())
+        word_task = asyncio.create_task(save_word())
+        md_task = asyncio.create_task(save_markdown())
+        txt_task = asyncio.create_task(save_txt())
+        
+        # 等待所有任务完成
+        html_file = await html_task
+        docx_file = await word_task
+        md_file = await md_task
+        txt_file = await txt_task
+        
+        # PDF转换需要等待word文件生成完成
+        pdf_file = await save_pdf(docx_file)
+        # 收集所有成功生成的文件
+        result_files = [f for f in [html_file, docx_file, md_file, txt_file, pdf_file] if f]
+        
+        # 保存Excel表格
+        excel_files = save_chat_tables(history, save_dir, base_name)
+        result_files.extend(excel_files)
+        
+        return result_files
+
+    # 生成时间戳
+    timestamp = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
+    
+    # 获取保存目录
+    save_dir = get_log_folder(get_user(chatbot), plugin_name='chat_history')
+    
+    # 处理文件名
+    base_name = file_name if file_name else f"聊天记录_{timestamp}"
+    
+    # 运行异步任务
+    result_files = asyncio.run(main())
+    
+    # 将生成的文件添加到下载区
+    for file in result_files:
+        promote_file_to_downloadzone(file, rename_file=os.path.basename(file), chatbot=chatbot)
+    
+    # 如果没有成功保存任何文件，返回错误信息
+    if not result_files:
+        return "保存对话记录失败，请检查错误日志"
+    
+    ext_list = [os.path.splitext(f)[1] for f in result_files]
+    # 返回成功信息和文件路径
+    return f"对话历史已保存至以下格式文件：" + "、".join(ext_list)
+
 def gen_file_preview(file_name):
     try:
         with open(file_name, 'r', encoding='utf8') as f:
@@ -119,12 +264,21 @@ def 对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
     user_request    当前用户的请求信息（IP地址等）
     """
     file_name = plugin_kwargs.get("file_name", None)
-    if (file_name is not None) and (file_name != "") and (not file_name.endswith('.html')): file_name += '.html'
-    else: file_name = None
-
-    chatbot.append((None, f"[Local Message] {write_chat_to_file(chatbot, history, file_name)}，您可以调用下拉菜单中的“载入对话历史存档”还原当下的对话。"))
-    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
 
+    chatbot.append((None, f"[Local Message] {write_chat_to_file_legacy(chatbot, history, file_name)}，您可以调用下拉菜单中的“载入对话历史存档”还原当下的对话。"))
+    try:
+        chatbot.append((None, f"[Local Message] 正在尝试生成pdf以及word格式的对话存档，请稍等..."))
+        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求需要一段时间，我们先及时地做一次界面更新
+        lastmsg = f"[Local Message] {write_chat_to_file(chatbot, history, file_name)}。" \
+              f"您可以调用下拉菜单中的“载入对话历史会话”还原当下的对话，请注意，目前只支持html格式载入历史。" \
+              f"当模型回答中存在表格，将提取表格内容存储为Excel的xlsx格式，如果你提供一些数据,然后输入指令要求模型帮你整理为表格" \
+              f"（如“请帮我将下面的数据整理为表格：”），再利用此插件就可以获取到Excel表格。"
+        yield from update_ui_latest_msg(lastmsg, chatbot, history) # 刷新界面 # 由于请求需要一段时间，我们先及时地做一次界面更新
+    except Exception as e:
+        logger.exception(f"已完成对话存档（pdf和word格式的对话存档生成未成功）。{str(e)}")
+        lastmsg = "已完成对话存档（pdf和word格式的对话存档生成未成功）。"
+        yield from update_ui_latest_msg(lastmsg, chatbot, history) # 刷新界面 # 由于请求需要一段时间，我们先及时地做一次界面更新
+    return
 
 class Conversation_To_File_Wrap(GptAcademicPluginTemplate):
     def __init__(self):

crazy_functions/doc_fns/AI_review_doc.py

@@ -0,0 +1,812 @@
+import os
+import time
+from abc import ABC, abstractmethod
+from datetime import datetime
+from docx import Document
+from docx.enum.style import WD_STYLE_TYPE
+from docx.enum.text import WD_PARAGRAPH_ALIGNMENT, WD_LINE_SPACING
+from docx.oxml.ns import qn
+from docx.shared import  Inches, Cm
+from docx.shared import Pt, RGBColor, Inches
+from typing import Dict, List, Tuple
+import markdown
+from crazy_functions.doc_fns.conversation_doc.word_doc import convert_markdown_to_word
+
+
+
+class DocumentFormatter(ABC):
+    """文档格式化基类，定义文档格式化的基本接口"""
+
+    def __init__(self, final_summary: str, file_summaries_map: Dict, failed_files: List[Tuple]):
+        self.final_summary = final_summary
+        self.file_summaries_map = file_summaries_map
+        self.failed_files = failed_files
+
+    @abstractmethod
+    def format_failed_files(self) -> str:
+        """格式化失败文件列表"""
+        pass
+
+    @abstractmethod
+    def format_file_summaries(self) -> str:
+        """格式化文件总结内容"""
+        pass
+
+    @abstractmethod
+    def create_document(self) -> str:
+        """创建完整文档"""
+        pass
+
+
+class WordFormatter(DocumentFormatter):
+    """Word格式文档生成器 - 符合中国政府公文格式规范(GB/T 9704-2012)，并进行了优化"""
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.doc = Document()
+        self._setup_document()
+        self._create_styles()
+        # 初始化三级标题编号系统
+        self.numbers = {
+            1: 0,  # 一级标题编号
+            2: 0,  # 二级标题编号
+            3: 0  # 三级标题编号
+        }
+
+    def _setup_document(self):
+        """设置文档基本格式，包括页面设置和页眉"""
+        sections = self.doc.sections
+        for section in sections:
+            # 设置页面大小为A4
+            section.page_width = Cm(21)
+            section.page_height = Cm(29.7)
+            # 设置页边距
+            section.top_margin = Cm(3.7)  # 上边距37mm
+            section.bottom_margin = Cm(3.5)  # 下边距35mm
+            section.left_margin = Cm(2.8)  # 左边距28mm
+            section.right_margin = Cm(2.6)  # 右边距26mm
+            # 设置页眉页脚距离
+            section.header_distance = Cm(2.0)
+            section.footer_distance = Cm(2.0)
+
+            # 添加页眉
+            header = section.header
+            header_para = header.paragraphs[0]
+            header_para.alignment = WD_PARAGRAPH_ALIGNMENT.RIGHT
+            header_run = header_para.add_run("该文档由GPT-academic生成")
+            header_run.font.name = '仿宋'
+            header_run._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
+            header_run.font.size = Pt(9)
+
+    def _create_styles(self):
+        """创建文档样式"""
+        # 创建正文样式
+        style = self.doc.styles.add_style('Normal_Custom', WD_STYLE_TYPE.PARAGRAPH)
+        style.font.name = '仿宋'
+        style._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
+        style.font.size = Pt(14)
+        style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
+        style.paragraph_format.space_after = Pt(0)
+        style.paragraph_format.first_line_indent = Pt(28)
+
+        # 创建各级标题样式
+        self._create_heading_style('Title_Custom', '方正小标宋简体', 32, WD_PARAGRAPH_ALIGNMENT.CENTER)
+        self._create_heading_style('Heading1_Custom', '黑体', 22, WD_PARAGRAPH_ALIGNMENT.LEFT)
+        self._create_heading_style('Heading2_Custom', '黑体', 18, WD_PARAGRAPH_ALIGNMENT.LEFT)
+        self._create_heading_style('Heading3_Custom', '黑体', 16, WD_PARAGRAPH_ALIGNMENT.LEFT)
+
+    def _create_heading_style(self, style_name: str, font_name: str, font_size: int, alignment):
+        """创建标题样式"""
+        style = self.doc.styles.add_style(style_name, WD_STYLE_TYPE.PARAGRAPH)
+        style.font.name = font_name
+        style._element.rPr.rFonts.set(qn('w:eastAsia'), font_name)
+        style.font.size = Pt(font_size)
+        style.font.bold = True
+        style.paragraph_format.alignment = alignment
+        style.paragraph_format.space_before = Pt(12)
+        style.paragraph_format.space_after = Pt(12)
+        style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
+        return style
+
+    def _get_heading_number(self, level: int) -> str:
+        """
+        生成标题编号
+
+        Args:
+            level: 标题级别 (0-3)
+
+        Returns:
+            str: 格式化的标题编号
+        """
+        if level == 0:  # 主标题不需要编号
+            return ""
+
+        self.numbers[level] += 1  # 增加当前级别的编号
+
+        # 重置下级标题编号
+        for i in range(level + 1, 4):
+            self.numbers[i] = 0
+
+        # 根据级别返回不同格式的编号
+        if level == 1:
+            return f"{self.numbers[1]}. "
+        elif level == 2:
+            return f"{self.numbers[1]}.{self.numbers[2]} "
+        elif level == 3:
+            return f"{self.numbers[1]}.{self.numbers[2]}.{self.numbers[3]} "
+        return ""
+
+    def _add_heading(self, text: str, level: int):
+        """
+        添加带编号的标题
+
+        Args:
+            text: 标题文本
+            level: 标题级别 (0-3)
+        """
+        style_map = {
+            0: 'Title_Custom',
+            1: 'Heading1_Custom',
+            2: 'Heading2_Custom',
+            3: 'Heading3_Custom'
+        }
+
+        number = self._get_heading_number(level)
+        paragraph = self.doc.add_paragraph(style=style_map[level])
+
+        if number:
+            number_run = paragraph.add_run(number)
+            font_size = 22 if level == 1 else (18 if level == 2 else 16)
+            self._get_run_style(number_run, '黑体', font_size, True)
+
+        text_run = paragraph.add_run(text)
+        font_size = 32 if level == 0 else (22 if level == 1 else (18 if level == 2 else 16))
+        self._get_run_style(text_run, '黑体', font_size, True)
+
+        # 主标题添加日期
+        if level == 0:
+            date_paragraph = self.doc.add_paragraph()
+            date_paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
+            date_run = date_paragraph.add_run(datetime.now().strftime('%Y年%m月%d日'))
+            self._get_run_style(date_run, '仿宋', 16, False)
+
+        return paragraph
+
+    def _get_run_style(self, run, font_name: str, font_size: int, bold: bool = False):
+        """设置文本运行对象的样式"""
+        run.font.name = font_name
+        run._element.rPr.rFonts.set(qn('w:eastAsia'), font_name)
+        run.font.size = Pt(font_size)
+        run.font.bold = bold
+
+    def format_failed_files(self) -> str:
+        """格式化失败文件列表"""
+        result = []
+        if not self.failed_files:
+            return "\n".join(result)
+
+        result.append("处理失败文件:")
+        for fp, reason in self.failed_files:
+            result.append(f"• {os.path.basename(fp)}: {reason}")
+
+        self._add_heading("处理失败文件", 1)
+        for fp, reason in self.failed_files:
+            self._add_content(f"• {os.path.basename(fp)}: {reason}", indent=False)
+        self.doc.add_paragraph()
+
+        return "\n".join(result)
+
+    def _add_content(self, text: str, indent: bool = True):
+        """添加正文内容，使用convert_markdown_to_word处理文本"""
+        # 使用convert_markdown_to_word处理markdown文本
+        processed_text = convert_markdown_to_word(text)
+        paragraph = self.doc.add_paragraph(processed_text, style='Normal_Custom')
+        if not indent:
+            paragraph.paragraph_format.first_line_indent = Pt(0)
+        return paragraph
+
+    def format_file_summaries(self) -> str:
+        """
+        格式化文件总结内容，确保正确的标题层级并处理markdown文本
+        """
+        result = []
+        # 首先对文件路径进行分组整理
+        file_groups = {}
+        for path in sorted(self.file_summaries_map.keys()):
+            dir_path = os.path.dirname(path)
+            if dir_path not in file_groups:
+                file_groups[dir_path] = []
+            file_groups[dir_path].append(path)
+
+        # 处理没有目录的文件
+        root_files = file_groups.get("", [])
+        if root_files:
+            for path in sorted(root_files):
+                file_name = os.path.basename(path)
+                result.append(f"\n📄 {file_name}")
+                result.append(self.file_summaries_map[path])
+                # 无目录的文件作为二级标题
+                self._add_heading(f"📄 {file_name}", 2)
+                # 使用convert_markdown_to_word处理文件内容
+                self._add_content(convert_markdown_to_word(self.file_summaries_map[path]))
+                self.doc.add_paragraph()
+
+        # 处理有目录的文件
+        for dir_path in sorted(file_groups.keys()):
+            if dir_path == "":  # 跳过已处理的根目录文件
+                continue
+
+            # 添加目录作为二级标题
+            result.append(f"\n📁 {dir_path}")
+            self._add_heading(f"📁 {dir_path}", 2)
+
+            # 该目录下的所有文件作为三级标题
+            for path in sorted(file_groups[dir_path]):
+                file_name = os.path.basename(path)
+                result.append(f"\n📄 {file_name}")
+                result.append(self.file_summaries_map[path])
+
+                # 添加文件名作为三级标题
+                self._add_heading(f"📄 {file_name}", 3)
+                # 使用convert_markdown_to_word处理文件内容
+                self._add_content(convert_markdown_to_word(self.file_summaries_map[path]))
+                self.doc.add_paragraph()
+
+        return "\n".join(result)
+
+
+    def create_document(self):
+        """创建完整Word文档并返回文档对象"""
+        # 重置所有编号
+        for level in self.numbers:
+            self.numbers[level] = 0
+
+        # 添加主标题
+        self._add_heading("文档总结报告", 0)
+        self.doc.add_paragraph()
+
+        # 添加总体摘要，使用convert_markdown_to_word处理
+        self._add_heading("总体摘要", 1)
+        self._add_content(convert_markdown_to_word(self.final_summary))
+        self.doc.add_paragraph()
+
+        # 添加失败文件列表（如果有）
+        if self.failed_files:
+            self.format_failed_files()
+
+        # 添加文件详细总结
+        self._add_heading("各文件详细总结", 1)
+        self.format_file_summaries()
+
+        return self.doc
+
+    def save_as_pdf(self, word_path, pdf_path=None):
+        """将生成的Word文档转换为PDF
+        
+        参数:
+            word_path: Word文档的路径
+            pdf_path: 可选，PDF文件的输出路径。如果未指定，将使用与Word文档相同的名称和位置
+            
+        返回:
+            生成的PDF文件路径，如果转换失败则返回None
+        """
+        from crazy_functions.doc_fns.conversation_doc.word2pdf import WordToPdfConverter
+        try:
+            pdf_path = WordToPdfConverter.convert_to_pdf(word_path, pdf_path)
+            return pdf_path
+        except Exception as e:
+            print(f"PDF转换失败: {str(e)}")
+            return None
+
+
+class MarkdownFormatter(DocumentFormatter):
+    """Markdown格式文档生成器"""
+
+    def format_failed_files(self) -> str:
+        if not self.failed_files:
+            return ""
+
+        formatted_text = ["\n## ⚠️ 处理失败的文件"]
+        for fp, reason in self.failed_files:
+            formatted_text.append(f"- {os.path.basename(fp)}: {reason}")
+        formatted_text.append("\n---")
+        return "\n".join(formatted_text)
+
+    def format_file_summaries(self) -> str:
+        formatted_text = []
+        sorted_paths = sorted(self.file_summaries_map.keys())
+        current_dir = ""
+
+        for path in sorted_paths:
+            dir_path = os.path.dirname(path)
+            if dir_path != current_dir:
+                if dir_path:
+                    formatted_text.append(f"\n## 📁 {dir_path}")
+                current_dir = dir_path
+
+            file_name = os.path.basename(path)
+            formatted_text.append(f"\n### 📄 {file_name}")
+            formatted_text.append(self.file_summaries_map[path])
+            formatted_text.append("\n---")
+
+        return "\n".join(formatted_text)
+
+    def create_document(self) -> str:
+        document = [
+            "# 📑 文档总结报告",
+            "\n## 总体摘要",
+            self.final_summary
+        ]
+
+        if self.failed_files:
+            document.append(self.format_failed_files())
+
+        document.extend([
+            "\n# 📚 各文件详细总结",
+            self.format_file_summaries()
+        ])
+
+        return "\n".join(document)
+
+
+
+class HtmlFormatter(DocumentFormatter):
+    """HTML格式文档生成器 - 优化版"""
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.md = markdown.Markdown(extensions=['extra','codehilite', 'tables','nl2br'])
+        self.css_styles = """
+        @keyframes fadeIn {
+            from { opacity: 0; transform: translateY(20px); }
+            to { opacity: 1; transform: translateY(0); }
+        }
+
+        @keyframes slideIn {
+            from { transform: translateX(-20px); opacity: 0; }
+            to { transform: translateX(0); opacity: 1; }
+        }
+
+        @keyframes pulse {
+            0% { transform: scale(1); }
+            50% { transform: scale(1.05); }
+            100% { transform: scale(1); }
+        }
+
+        :root {
+            /* Enhanced color palette */
+            --primary-color: #2563eb;
+            --primary-light: #eff6ff;
+            --secondary-color: #1e293b;
+            --background-color: #f8fafc;
+            --text-color: #334155;
+            --text-light: #64748b;
+            --border-color: #e2e8f0;
+            --error-color: #ef4444;
+            --error-light: #fef2f2;
+            --success-color: #22c55e;
+            --warning-color: #f59e0b;
+            --card-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1);
+            --hover-shadow: 0 20px 25px -5px rgb(0 0 0 / 0.1), 0 8px 10px -6px rgb(0 0 0 / 0.1);
+            
+            /* Typography */
+            --heading-font: "Plus Jakarta Sans", system-ui, sans-serif;
+            --body-font: "Inter", system-ui, sans-serif;
+        }
+
+        body {
+            font-family: var(--body-font);
+            line-height: 1.8;
+            max-width: 1200px;
+            margin: 0 auto;
+            padding: 2rem;
+            color: var(--text-color);
+            background-color: var(--background-color);
+            font-size: 16px;
+            -webkit-font-smoothing: antialiased;
+        }
+
+        .container {
+            background: white;
+            padding: 3rem;
+            border-radius: 24px;
+            box-shadow: var(--card-shadow);
+            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
+            animation: fadeIn 0.6s ease-out;
+            border: 1px solid var(--border-color);
+        }
+
+        .container:hover {
+            box-shadow: var(--hover-shadow);
+            transform: translateY(-2px);
+        }
+
+        h1, h2, h3 {
+            font-family: var(--heading-font);
+            font-weight: 600;
+        }
+
+        h1 {
+            color: var(--primary-color);
+            font-size: 2.8em;
+            text-align: center;
+            margin: 2rem 0 3rem;
+            padding-bottom: 1.5rem;
+            border-bottom: 3px solid var(--primary-color);
+            letter-spacing: -0.03em;
+            position: relative;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            gap: 1rem;
+        }
+
+        h1::after {
+            content: '';
+            position: absolute;
+            bottom: -3px;
+            left: 50%;
+            transform: translateX(-50%);
+            width: 120px;
+            height: 3px;
+            background: linear-gradient(90deg, var(--primary-color), var(--primary-light));
+            border-radius: 3px;
+            transition: width 0.3s ease;
+        }
+
+        h1:hover::after {
+            width: 180px;
+        }
+
+        h2 {
+            color: var(--secondary-color);
+            font-size: 1.9em;
+            margin: 2.5rem 0 1.5rem;
+            padding-left: 1.2rem;
+            border-left: 4px solid var(--primary-color);
+            letter-spacing: -0.02em;
+            display: flex;
+            align-items: center;
+            gap: 1rem;
+            transition: all 0.3s ease;
+        }
+
+        h2:hover {
+            color: var(--primary-color);
+            transform: translateX(5px);
+        }
+
+        h3 {
+            color: var(--text-color);
+            font-size: 1.5em;
+            margin: 2rem 0 1rem;
+            padding-bottom: 0.8rem;
+            border-bottom: 2px solid var(--border-color);
+            transition: all 0.3s ease;
+            display: flex;
+            align-items: center;
+            gap: 0.8rem;
+        }
+
+        h3:hover {
+            color: var(--primary-color);
+            border-bottom-color: var(--primary-color);
+        }
+
+        .summary {
+            background: var(--primary-light);
+            padding: 2.5rem;
+            border-radius: 16px;
+            margin: 2.5rem 0;
+            box-shadow: 0 4px 6px -1px rgba(37, 99, 235, 0.1);
+            position: relative;
+            overflow: hidden;
+            transition: transform 0.3s ease, box-shadow 0.3s ease;
+            animation: slideIn 0.5s ease-out;
+        }
+
+        .summary:hover {
+            transform: translateY(-3px);
+            box-shadow: 0 8px 12px -2px rgba(37, 99, 235, 0.15);
+        }
+
+        .summary::before {
+            content: '';
+            position: absolute;
+            top: 0;
+            left: 0;
+            width: 4px;
+            height: 100%;
+            background: linear-gradient(to bottom, var(--primary-color), rgba(37, 99, 235, 0.6));
+        }
+
+        .summary p {
+            margin: 1.2rem 0;
+            line-height: 1.9;
+            color: var(--text-color);
+            transition: color 0.3s ease;
+        }
+
+        .summary:hover p {
+            color: var(--secondary-color);
+        }
+
+        .details {
+            margin-top: 3.5rem;
+            padding-top: 2.5rem;
+            border-top: 2px dashed var(--border-color);
+            animation: fadeIn 0.8s ease-out;
+        }
+
+        .failed-files {
+            background: var(--error-light);
+            padding: 2rem;
+            border-radius: 16px;
+            margin: 3rem 0;
+            border-left: 4px solid var(--error-color);
+            position: relative;
+            transition: all 0.3s ease;
+            animation: slideIn 0.5s ease-out;
+        }
+
+        .failed-files:hover {
+            transform: translateX(5px);
+            box-shadow: 0 8px 15px -3px rgba(239, 68, 68, 0.1);
+        }
+
+        .failed-files h2 {
+            color: var(--error-color);
+            border-left: none;
+            padding-left: 0;
+        }
+
+        .failed-files ul {
+            margin: 1.8rem 0;
+            padding-left: 1.2rem;
+            list-style-type: none;
+        }
+
+        .failed-files li {
+            margin: 1.2rem 0;
+            padding: 1.2rem 1.8rem;
+            background: rgba(239, 68, 68, 0.08);
+            border-radius: 12px;
+            transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1);
+        }
+
+        .failed-files li:hover {
+            transform: translateX(8px);
+            background: rgba(239, 68, 68, 0.12);
+        }
+
+        .directory-section {
+            margin: 3.5rem 0;
+            padding: 2rem;
+            background: var(--background-color);
+            border-radius: 16px;
+            position: relative;
+            transition: all 0.3s ease;
+            animation: fadeIn 0.6s ease-out;
+        }
+
+        .directory-section:hover {
+            background: white;
+            box-shadow: var(--card-shadow);
+        }
+
+        .file-summary {
+            background: white;
+            padding: 2rem;
+            margin: 1.8rem 0;
+            border-radius: 16px;
+            box-shadow: var(--card-shadow);
+            border-left: 4px solid var(--border-color);
+            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
+            position: relative;
+            overflow: hidden;
+        }
+
+        .file-summary:hover {
+            border-left-color: var(--primary-color);
+            transform: translateX(8px) translateY(-2px);
+            box-shadow: var(--hover-shadow);
+        }
+
+        .file-summary {
+            background: white;
+            padding: 2rem;
+            margin: 1.8rem 0;
+            border-radius: 16px;
+            box-shadow: var(--card-shadow);
+            border-left: 4px solid var(--border-color);
+            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
+            position: relative;
+        }
+
+        .file-summary:hover {
+            border-left-color: var(--primary-color);
+            transform: translateX(8px) translateY(-2px);
+            box-shadow: var(--hover-shadow);
+        }
+
+        .icon {
+            display: inline-flex;
+            align-items: center;
+            justify-content: center;
+            width: 32px;
+            height: 32px;
+            border-radius: 8px;
+            background: var(--primary-light);
+            color: var(--primary-color);
+            font-size: 1.2em;
+            transition: all 0.3s ease;
+        }
+
+        .file-summary:hover .icon,
+        .directory-section:hover .icon {
+            transform: scale(1.1);
+            background: var(--primary-color);
+            color: white;
+        }
+
+        /* Smooth scrolling */
+        html {
+            scroll-behavior: smooth;
+        }
+
+        /* Selection style */
+        ::selection {
+            background: var(--primary-light);
+            color: var(--primary-color);
+        }
+
+        /* Print styles */
+        @media print {
+            body {
+                background: white;
+            }
+            .container {
+                box-shadow: none;
+                padding: 0;
+            }
+            .file-summary, .failed-files {
+                break-inside: avoid;
+                box-shadow: none;
+            }
+            .icon {
+                display: none;
+            }
+        }
+
+        /* Responsive design */
+        @media (max-width: 768px) {
+            body {
+                padding: 1rem;
+                font-size: 15px;
+            }
+            
+            .container {
+                padding: 1.5rem;
+            }
+
+            h1 {
+                font-size: 2.2em;
+                margin: 1.5rem 0 2rem;
+            }
+
+            h2 {
+                font-size: 1.7em;
+            }
+
+            h3 {
+                font-size: 1.4em;
+            }
+
+            .summary, .failed-files, .directory-section {
+                padding: 1.5rem;
+            }
+
+            .file-summary {
+                padding: 1.2rem;
+            }
+
+            .icon {
+                width: 28px;
+                height: 28px;
+            }
+        }
+
+        /* Dark mode support */
+        @media (prefers-color-scheme: dark) {
+            :root {
+                --primary-light: rgba(37, 99, 235, 0.15);
+                --background-color: #0f172a;
+                --text-color: #e2e8f0;
+                --text-light: #94a3b8;
+                --border-color: #1e293b;
+                --error-light: rgba(239, 68, 68, 0.15);
+            }
+
+            .container, .file-summary {
+                background: #1e293b;
+            }
+
+            .directory-section {
+                background: #0f172a;
+            }
+
+            .directory-section:hover {
+                background: #1e293b;
+            }
+        }
+        """
+
+    def format_failed_files(self) -> str:
+        if not self.failed_files:
+            return ""
+
+        failed_files_html = ['<div class="failed-files">']
+        failed_files_html.append('<h2><span class="icon">⚠️</span> 处理失败的文件</h2>')
+        failed_files_html.append("<ul>")
+        for fp, reason in self.failed_files:
+            failed_files_html.append(
+                f'<li><strong>📄 {os.path.basename(fp)}</strong><br><span style="color: var(--text-light)">{reason}</span></li>'
+            )
+        failed_files_html.append("</ul></div>")
+        return "\n".join(failed_files_html)
+
+    def format_file_summaries(self) -> str:
+        formatted_html = []
+        sorted_paths = sorted(self.file_summaries_map.keys())
+        current_dir = ""
+
+        for path in sorted_paths:
+            dir_path = os.path.dirname(path)
+            if dir_path != current_dir:
+                if dir_path:
+                    formatted_html.append('<div class="directory-section">')
+                    formatted_html.append(f'<h2><span class="icon">📁</span> {dir_path}</h2>')
+                    formatted_html.append('</div>')
+                current_dir = dir_path
+
+            file_name = os.path.basename(path)
+            formatted_html.append('<div class="file-summary">')
+            formatted_html.append(f'<h3><span class="icon">📄</span> {file_name}</h3>')
+            formatted_html.append(self.md.convert(self.file_summaries_map[path]))
+            formatted_html.append('</div>')
+
+        return "\n".join(formatted_html)
+
+    def create_document(self) -> str:
+        """生成HTML文档
+        Returns:
+            str: 完整的HTML文档字符串
+        """
+        return f"""
+        <!DOCTYPE html>
+        <html lang="zh-CN">
+        <head>
+            <meta charset="utf-8">
+            <meta name="viewport" content="width=device-width, initial-scale=1">
+            <title>文档总结报告</title>
+            <link href="https://cdnjs.cloudflare.com/ajax/libs/inter/3.19.3/inter.css" rel="stylesheet">
+            <link href="https://fonts.googleapis.com/css2?family=Plus+Jakarta+Sans:wght@400;600&display=swap" rel="stylesheet">
+            <style>{self.css_styles}</style>
+        </head>
+        <body>
+            <div class="container">
+                <h1><span class="icon">📑</span> 文档总结报告</h1>
+                <div class="summary">
+                    <h2><span class="icon">📋</span> 总体摘要</h2>
+                    <p>{self.md.convert(self.final_summary)}</p>
+                </div>
+                {self.format_failed_files()}
+                <div class="details">
+                    <h2><span class="icon">📚</span> 各文件详细总结</h2>
+                    {self.format_file_summaries()}
+                </div>
+            </div>
+
+        </body>
+        </html>
+        """

crazy_functions/doc_fns/batch_file_query_doc.py

@@ -0,0 +1,812 @@
+import os
+import time
+from abc import ABC, abstractmethod
+from datetime import datetime
+from docx import Document
+from docx.enum.style import WD_STYLE_TYPE
+from docx.enum.text import WD_PARAGRAPH_ALIGNMENT, WD_LINE_SPACING
+from docx.oxml.ns import qn
+from docx.shared import  Inches, Cm
+from docx.shared import Pt, RGBColor, Inches
+from typing import Dict, List, Tuple
+import markdown
+from crazy_functions.doc_fns.conversation_doc.word_doc import  convert_markdown_to_word
+
+
+
+class DocumentFormatter(ABC):
+    """文档格式化基类，定义文档格式化的基本接口"""
+
+    def __init__(self, final_summary: str, file_summaries_map: Dict, failed_files: List[Tuple]):
+        self.final_summary = final_summary
+        self.file_summaries_map = file_summaries_map
+        self.failed_files = failed_files
+
+    @abstractmethod
+    def format_failed_files(self) -> str:
+        """格式化失败文件列表"""
+        pass
+
+    @abstractmethod
+    def format_file_summaries(self) -> str:
+        """格式化文件总结内容"""
+        pass
+
+    @abstractmethod
+    def create_document(self) -> str:
+        """创建完整文档"""
+        pass
+
+
+class WordFormatter(DocumentFormatter):
+    """Word格式文档生成器 - 符合中国政府公文格式规范(GB/T 9704-2012)，并进行了优化"""
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.doc = Document()
+        self._setup_document()
+        self._create_styles()
+        # 初始化三级标题编号系统
+        self.numbers = {
+            1: 0,  # 一级标题编号
+            2: 0,  # 二级标题编号
+            3: 0  # 三级标题编号
+        }
+
+    def _setup_document(self):
+        """设置文档基本格式，包括页面设置和页眉"""
+        sections = self.doc.sections
+        for section in sections:
+            # 设置页面大小为A4
+            section.page_width = Cm(21)
+            section.page_height = Cm(29.7)
+            # 设置页边距
+            section.top_margin = Cm(3.7)  # 上边距37mm
+            section.bottom_margin = Cm(3.5)  # 下边距35mm
+            section.left_margin = Cm(2.8)  # 左边距28mm
+            section.right_margin = Cm(2.6)  # 右边距26mm
+            # 设置页眉页脚距离
+            section.header_distance = Cm(2.0)
+            section.footer_distance = Cm(2.0)
+
+            # 添加页眉
+            header = section.header
+            header_para = header.paragraphs[0]
+            header_para.alignment = WD_PARAGRAPH_ALIGNMENT.RIGHT
+            header_run = header_para.add_run("该文档由GPT-academic生成")
+            header_run.font.name = '仿宋'
+            header_run._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
+            header_run.font.size = Pt(9)
+
+    def _create_styles(self):
+        """创建文档样式"""
+        # 创建正文样式
+        style = self.doc.styles.add_style('Normal_Custom', WD_STYLE_TYPE.PARAGRAPH)
+        style.font.name = '仿宋'
+        style._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
+        style.font.size = Pt(14)
+        style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
+        style.paragraph_format.space_after = Pt(0)
+        style.paragraph_format.first_line_indent = Pt(28)
+
+        # 创建各级标题样式
+        self._create_heading_style('Title_Custom', '方正小标宋简体', 32, WD_PARAGRAPH_ALIGNMENT.CENTER)
+        self._create_heading_style('Heading1_Custom', '黑体', 22, WD_PARAGRAPH_ALIGNMENT.LEFT)
+        self._create_heading_style('Heading2_Custom', '黑体', 18, WD_PARAGRAPH_ALIGNMENT.LEFT)
+        self._create_heading_style('Heading3_Custom', '黑体', 16, WD_PARAGRAPH_ALIGNMENT.LEFT)
+
+    def _create_heading_style(self, style_name: str, font_name: str, font_size: int, alignment):
+        """创建标题样式"""
+        style = self.doc.styles.add_style(style_name, WD_STYLE_TYPE.PARAGRAPH)
+        style.font.name = font_name
+        style._element.rPr.rFonts.set(qn('w:eastAsia'), font_name)
+        style.font.size = Pt(font_size)
+        style.font.bold = True
+        style.paragraph_format.alignment = alignment
+        style.paragraph_format.space_before = Pt(12)
+        style.paragraph_format.space_after = Pt(12)
+        style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
+        return style
+
+    def _get_heading_number(self, level: int) -> str:
+        """
+        生成标题编号
+
+        Args:
+            level: 标题级别 (0-3)
+
+        Returns:
+            str: 格式化的标题编号
+        """
+        if level == 0:  # 主标题不需要编号
+            return ""
+
+        self.numbers[level] += 1  # 增加当前级别的编号
+
+        # 重置下级标题编号
+        for i in range(level + 1, 4):
+            self.numbers[i] = 0
+
+        # 根据级别返回不同格式的编号
+        if level == 1:
+            return f"{self.numbers[1]}. "
+        elif level == 2:
+            return f"{self.numbers[1]}.{self.numbers[2]} "
+        elif level == 3:
+            return f"{self.numbers[1]}.{self.numbers[2]}.{self.numbers[3]} "
+        return ""
+
+    def _add_heading(self, text: str, level: int):
+        """
+        添加带编号的标题
+
+        Args:
+            text: 标题文本
+            level: 标题级别 (0-3)
+        """
+        style_map = {
+            0: 'Title_Custom',
+            1: 'Heading1_Custom',
+            2: 'Heading2_Custom',
+            3: 'Heading3_Custom'
+        }
+
+        number = self._get_heading_number(level)
+        paragraph = self.doc.add_paragraph(style=style_map[level])
+
+        if number:
+            number_run = paragraph.add_run(number)
+            font_size = 22 if level == 1 else (18 if level == 2 else 16)
+            self._get_run_style(number_run, '黑体', font_size, True)
+
+        text_run = paragraph.add_run(text)
+        font_size = 32 if level == 0 else (22 if level == 1 else (18 if level == 2 else 16))
+        self._get_run_style(text_run, '黑体', font_size, True)
+
+        # 主标题添加日期
+        if level == 0:
+            date_paragraph = self.doc.add_paragraph()
+            date_paragraph.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
+            date_run = date_paragraph.add_run(datetime.now().strftime('%Y年%m月%d日'))
+            self._get_run_style(date_run, '仿宋', 16, False)
+
+        return paragraph
+
+    def _get_run_style(self, run, font_name: str, font_size: int, bold: bool = False):
+        """设置文本运行对象的样式"""
+        run.font.name = font_name
+        run._element.rPr.rFonts.set(qn('w:eastAsia'), font_name)
+        run.font.size = Pt(font_size)
+        run.font.bold = bold
+
+    def format_failed_files(self) -> str:
+        """格式化失败文件列表"""
+        result = []
+        if not self.failed_files:
+            return "\n".join(result)
+
+        result.append("处理失败文件:")
+        for fp, reason in self.failed_files:
+            result.append(f"• {os.path.basename(fp)}: {reason}")
+
+        self._add_heading("处理失败文件", 1)
+        for fp, reason in self.failed_files:
+            self._add_content(f"• {os.path.basename(fp)}: {reason}", indent=False)
+        self.doc.add_paragraph()
+
+        return "\n".join(result)
+
+    def _add_content(self, text: str, indent: bool = True):
+        """添加正文内容，使用convert_markdown_to_word处理文本"""
+        # 使用convert_markdown_to_word处理markdown文本
+        processed_text = convert_markdown_to_word(text)
+        paragraph = self.doc.add_paragraph(processed_text, style='Normal_Custom')
+        if not indent:
+            paragraph.paragraph_format.first_line_indent = Pt(0)
+        return paragraph
+
+    def format_file_summaries(self) -> str:
+        """
+        格式化文件总结内容，确保正确的标题层级并处理markdown文本
+        """
+        result = []
+        # 首先对文件路径进行分组整理
+        file_groups = {}
+        for path in sorted(self.file_summaries_map.keys()):
+            dir_path = os.path.dirname(path)
+            if dir_path not in file_groups:
+                file_groups[dir_path] = []
+            file_groups[dir_path].append(path)
+
+        # 处理没有目录的文件
+        root_files = file_groups.get("", [])
+        if root_files:
+            for path in sorted(root_files):
+                file_name = os.path.basename(path)
+                result.append(f"\n📄 {file_name}")
+                result.append(self.file_summaries_map[path])
+                # 无目录的文件作为二级标题
+                self._add_heading(f"📄 {file_name}", 2)
+                # 使用convert_markdown_to_word处理文件内容
+                self._add_content(convert_markdown_to_word(self.file_summaries_map[path]))
+                self.doc.add_paragraph()
+
+        # 处理有目录的文件
+        for dir_path in sorted(file_groups.keys()):
+            if dir_path == "":  # 跳过已处理的根目录文件
+                continue
+
+            # 添加目录作为二级标题
+            result.append(f"\n📁 {dir_path}")
+            self._add_heading(f"📁 {dir_path}", 2)
+
+            # 该目录下的所有文件作为三级标题
+            for path in sorted(file_groups[dir_path]):
+                file_name = os.path.basename(path)
+                result.append(f"\n📄 {file_name}")
+                result.append(self.file_summaries_map[path])
+
+                # 添加文件名作为三级标题
+                self._add_heading(f"📄 {file_name}", 3)
+                # 使用convert_markdown_to_word处理文件内容
+                self._add_content(convert_markdown_to_word(self.file_summaries_map[path]))
+                self.doc.add_paragraph()
+
+        return "\n".join(result)
+
+
+    def create_document(self):
+        """创建完整Word文档并返回文档对象"""
+        # 重置所有编号
+        for level in self.numbers:
+            self.numbers[level] = 0
+
+        # 添加主标题
+        self._add_heading("文档总结报告", 0)
+        self.doc.add_paragraph()
+
+        # 添加总体摘要，使用convert_markdown_to_word处理
+        self._add_heading("总体摘要", 1)
+        self._add_content(convert_markdown_to_word(self.final_summary))
+        self.doc.add_paragraph()
+
+        # 添加失败文件列表（如果有）
+        if self.failed_files:
+            self.format_failed_files()
+
+        # 添加文件详细总结
+        self._add_heading("各文件详细总结", 1)
+        self.format_file_summaries()
+
+        return self.doc
+
+    def save_as_pdf(self, word_path, pdf_path=None):
+        """将生成的Word文档转换为PDF
+        
+        参数:
+            word_path: Word文档的路径
+            pdf_path: 可选，PDF文件的输出路径。如果未指定，将使用与Word文档相同的名称和位置
+            
+        返回:
+            生成的PDF文件路径，如果转换失败则返回None
+        """
+        from crazy_functions.doc_fns.conversation_doc.word2pdf import WordToPdfConverter
+        try:
+            pdf_path = WordToPdfConverter.convert_to_pdf(word_path, pdf_path)
+            return pdf_path
+        except Exception as e:
+            print(f"PDF转换失败: {str(e)}")
+            return None
+
+
+class MarkdownFormatter(DocumentFormatter):
+    """Markdown格式文档生成器"""
+
+    def format_failed_files(self) -> str:
+        if not self.failed_files:
+            return ""
+
+        formatted_text = ["\n## ⚠️ 处理失败的文件"]
+        for fp, reason in self.failed_files:
+            formatted_text.append(f"- {os.path.basename(fp)}: {reason}")
+        formatted_text.append("\n---")
+        return "\n".join(formatted_text)
+
+    def format_file_summaries(self) -> str:
+        formatted_text = []
+        sorted_paths = sorted(self.file_summaries_map.keys())
+        current_dir = ""
+
+        for path in sorted_paths:
+            dir_path = os.path.dirname(path)
+            if dir_path != current_dir:
+                if dir_path:
+                    formatted_text.append(f"\n## 📁 {dir_path}")
+                current_dir = dir_path
+
+            file_name = os.path.basename(path)
+            formatted_text.append(f"\n### 📄 {file_name}")
+            formatted_text.append(self.file_summaries_map[path])
+            formatted_text.append("\n---")
+
+        return "\n".join(formatted_text)
+
+    def create_document(self) -> str:
+        document = [
+            "# 📑 文档总结报告",
+            "\n## 总体摘要",
+            self.final_summary
+        ]
+
+        if self.failed_files:
+            document.append(self.format_failed_files())
+
+        document.extend([
+            "\n# 📚 各文件详细总结",
+            self.format_file_summaries()
+        ])
+
+        return "\n".join(document)
+
+
+
+class HtmlFormatter(DocumentFormatter):
+    """HTML格式文档生成器 - 优化版"""
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.md = markdown.Markdown(extensions=['extra','codehilite', 'tables','nl2br'])
+        self.css_styles = """
+        @keyframes fadeIn {
+            from { opacity: 0; transform: translateY(20px); }
+            to { opacity: 1; transform: translateY(0); }
+        }
+
+        @keyframes slideIn {
+            from { transform: translateX(-20px); opacity: 0; }
+            to { transform: translateX(0); opacity: 1; }
+        }
+
+        @keyframes pulse {
+            0% { transform: scale(1); }
+            50% { transform: scale(1.05); }
+            100% { transform: scale(1); }
+        }
+
+        :root {
+            /* Enhanced color palette */
+            --primary-color: #2563eb;
+            --primary-light: #eff6ff;
+            --secondary-color: #1e293b;
+            --background-color: #f8fafc;
+            --text-color: #334155;
+            --text-light: #64748b;
+            --border-color: #e2e8f0;
+            --error-color: #ef4444;
+            --error-light: #fef2f2;
+            --success-color: #22c55e;
+            --warning-color: #f59e0b;
+            --card-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1);
+            --hover-shadow: 0 20px 25px -5px rgb(0 0 0 / 0.1), 0 8px 10px -6px rgb(0 0 0 / 0.1);
+            
+            /* Typography */
+            --heading-font: "Plus Jakarta Sans", system-ui, sans-serif;
+            --body-font: "Inter", system-ui, sans-serif;
+        }
+
+        body {
+            font-family: var(--body-font);
+            line-height: 1.8;
+            max-width: 1200px;
+            margin: 0 auto;
+            padding: 2rem;
+            color: var(--text-color);
+            background-color: var(--background-color);
+            font-size: 16px;
+            -webkit-font-smoothing: antialiased;
+        }
+
+        .container {
+            background: white;
+            padding: 3rem;
+            border-radius: 24px;
+            box-shadow: var(--card-shadow);
+            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
+            animation: fadeIn 0.6s ease-out;
+            border: 1px solid var(--border-color);
+        }
+
+        .container:hover {
+            box-shadow: var(--hover-shadow);
+            transform: translateY(-2px);
+        }
+
+        h1, h2, h3 {
+            font-family: var(--heading-font);
+            font-weight: 600;
+        }
+
+        h1 {
+            color: var(--primary-color);
+            font-size: 2.8em;
+            text-align: center;
+            margin: 2rem 0 3rem;
+            padding-bottom: 1.5rem;
+            border-bottom: 3px solid var(--primary-color);
+            letter-spacing: -0.03em;
+            position: relative;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            gap: 1rem;
+        }
+
+        h1::after {
+            content: '';
+            position: absolute;
+            bottom: -3px;
+            left: 50%;
+            transform: translateX(-50%);
+            width: 120px;
+            height: 3px;
+            background: linear-gradient(90deg, var(--primary-color), var(--primary-light));
+            border-radius: 3px;
+            transition: width 0.3s ease;
+        }
+
+        h1:hover::after {
+            width: 180px;
+        }
+
+        h2 {
+            color: var(--secondary-color);
+            font-size: 1.9em;
+            margin: 2.5rem 0 1.5rem;
+            padding-left: 1.2rem;
+            border-left: 4px solid var(--primary-color);
+            letter-spacing: -0.02em;
+            display: flex;
+            align-items: center;
+            gap: 1rem;
+            transition: all 0.3s ease;
+        }
+
+        h2:hover {
+            color: var(--primary-color);
+            transform: translateX(5px);
+        }
+
+        h3 {
+            color: var(--text-color);
+            font-size: 1.5em;
+            margin: 2rem 0 1rem;
+            padding-bottom: 0.8rem;
+            border-bottom: 2px solid var(--border-color);
+            transition: all 0.3s ease;
+            display: flex;
+            align-items: center;
+            gap: 0.8rem;
+        }
+
+        h3:hover {
+            color: var(--primary-color);
+            border-bottom-color: var(--primary-color);
+        }
+
+        .summary {
+            background: var(--primary-light);
+            padding: 2.5rem;
+            border-radius: 16px;
+            margin: 2.5rem 0;
+            box-shadow: 0 4px 6px -1px rgba(37, 99, 235, 0.1);
+            position: relative;
+            overflow: hidden;
+            transition: transform 0.3s ease, box-shadow 0.3s ease;
+            animation: slideIn 0.5s ease-out;
+        }
+
+        .summary:hover {
+            transform: translateY(-3px);
+            box-shadow: 0 8px 12px -2px rgba(37, 99, 235, 0.15);
+        }
+
+        .summary::before {
+            content: '';
+            position: absolute;
+            top: 0;
+            left: 0;
+            width: 4px;
+            height: 100%;
+            background: linear-gradient(to bottom, var(--primary-color), rgba(37, 99, 235, 0.6));
+        }
+
+        .summary p {
+            margin: 1.2rem 0;
+            line-height: 1.9;
+            color: var(--text-color);
+            transition: color 0.3s ease;
+        }
+
+        .summary:hover p {
+            color: var(--secondary-color);
+        }
+
+        .details {
+            margin-top: 3.5rem;
+            padding-top: 2.5rem;
+            border-top: 2px dashed var(--border-color);
+            animation: fadeIn 0.8s ease-out;
+        }
+
+        .failed-files {
+            background: var(--error-light);
+            padding: 2rem;
+            border-radius: 16px;
+            margin: 3rem 0;
+            border-left: 4px solid var(--error-color);
+            position: relative;
+            transition: all 0.3s ease;
+            animation: slideIn 0.5s ease-out;
+        }
+
+        .failed-files:hover {
+            transform: translateX(5px);
+            box-shadow: 0 8px 15px -3px rgba(239, 68, 68, 0.1);
+        }
+
+        .failed-files h2 {
+            color: var(--error-color);
+            border-left: none;
+            padding-left: 0;
+        }
+
+        .failed-files ul {
+            margin: 1.8rem 0;
+            padding-left: 1.2rem;
+            list-style-type: none;
+        }
+
+        .failed-files li {
+            margin: 1.2rem 0;
+            padding: 1.2rem 1.8rem;
+            background: rgba(239, 68, 68, 0.08);
+            border-radius: 12px;
+            transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1);
+        }
+
+        .failed-files li:hover {
+            transform: translateX(8px);
+            background: rgba(239, 68, 68, 0.12);
+        }
+
+        .directory-section {
+            margin: 3.5rem 0;
+            padding: 2rem;
+            background: var(--background-color);
+            border-radius: 16px;
+            position: relative;
+            transition: all 0.3s ease;
+            animation: fadeIn 0.6s ease-out;
+        }
+
+        .directory-section:hover {
+            background: white;
+            box-shadow: var(--card-shadow);
+        }
+
+        .file-summary {
+            background: white;
+            padding: 2rem;
+            margin: 1.8rem 0;
+            border-radius: 16px;
+            box-shadow: var(--card-shadow);
+            border-left: 4px solid var(--border-color);
+            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
+            position: relative;
+            overflow: hidden;
+        }
+
+        .file-summary:hover {
+            border-left-color: var(--primary-color);
+            transform: translateX(8px) translateY(-2px);
+            box-shadow: var(--hover-shadow);
+        }
+
+        .file-summary {
+            background: white;
+            padding: 2rem;
+            margin: 1.8rem 0;
+            border-radius: 16px;
+            box-shadow: var(--card-shadow);
+            border-left: 4px solid var(--border-color);
+            transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1);
+            position: relative;
+        }
+
+        .file-summary:hover {
+            border-left-color: var(--primary-color);
+            transform: translateX(8px) translateY(-2px);
+            box-shadow: var(--hover-shadow);
+        }
+
+        .icon {
+            display: inline-flex;
+            align-items: center;
+            justify-content: center;
+            width: 32px;
+            height: 32px;
+            border-radius: 8px;
+            background: var(--primary-light);
+            color: var(--primary-color);
+            font-size: 1.2em;
+            transition: all 0.3s ease;
+        }
+
+        .file-summary:hover .icon,
+        .directory-section:hover .icon {
+            transform: scale(1.1);
+            background: var(--primary-color);
+            color: white;
+        }
+
+        /* Smooth scrolling */
+        html {
+            scroll-behavior: smooth;
+        }
+
+        /* Selection style */
+        ::selection {
+            background: var(--primary-light);
+            color: var(--primary-color);
+        }
+
+        /* Print styles */
+        @media print {
+            body {
+                background: white;
+            }
+            .container {
+                box-shadow: none;
+                padding: 0;
+            }
+            .file-summary, .failed-files {
+                break-inside: avoid;
+                box-shadow: none;
+            }
+            .icon {
+                display: none;
+            }
+        }
+
+        /* Responsive design */
+        @media (max-width: 768px) {
+            body {
+                padding: 1rem;
+                font-size: 15px;
+            }
+            
+            .container {
+                padding: 1.5rem;
+            }
+
+            h1 {
+                font-size: 2.2em;
+                margin: 1.5rem 0 2rem;
+            }
+
+            h2 {
+                font-size: 1.7em;
+            }
+
+            h3 {
+                font-size: 1.4em;
+            }
+
+            .summary, .failed-files, .directory-section {
+                padding: 1.5rem;
+            }
+
+            .file-summary {
+                padding: 1.2rem;
+            }
+
+            .icon {
+                width: 28px;
+                height: 28px;
+            }
+        }
+
+        /* Dark mode support */
+        @media (prefers-color-scheme: dark) {
+            :root {
+                --primary-light: rgba(37, 99, 235, 0.15);
+                --background-color: #0f172a;
+                --text-color: #e2e8f0;
+                --text-light: #94a3b8;
+                --border-color: #1e293b;
+                --error-light: rgba(239, 68, 68, 0.15);
+            }
+
+            .container, .file-summary {
+                background: #1e293b;
+            }
+
+            .directory-section {
+                background: #0f172a;
+            }
+
+            .directory-section:hover {
+                background: #1e293b;
+            }
+        }
+        """
+
+    def format_failed_files(self) -> str:
+        if not self.failed_files:
+            return ""
+
+        failed_files_html = ['<div class="failed-files">']
+        failed_files_html.append('<h2><span class="icon">⚠️</span> 处理失败的文件</h2>')
+        failed_files_html.append("<ul>")
+        for fp, reason in self.failed_files:
+            failed_files_html.append(
+                f'<li><strong>📄 {os.path.basename(fp)}</strong><br><span style="color: var(--text-light)">{reason}</span></li>'
+            )
+        failed_files_html.append("</ul></div>")
+        return "\n".join(failed_files_html)
+
+    def format_file_summaries(self) -> str:
+        formatted_html = []
+        sorted_paths = sorted(self.file_summaries_map.keys())
+        current_dir = ""
+
+        for path in sorted_paths:
+            dir_path = os.path.dirname(path)
+            if dir_path != current_dir:
+                if dir_path:
+                    formatted_html.append('<div class="directory-section">')
+                    formatted_html.append(f'<h2><span class="icon">📁</span> {dir_path}</h2>')
+                    formatted_html.append('</div>')
+                current_dir = dir_path
+
+            file_name = os.path.basename(path)
+            formatted_html.append('<div class="file-summary">')
+            formatted_html.append(f'<h3><span class="icon">📄</span> {file_name}</h3>')
+            formatted_html.append(self.md.convert(self.file_summaries_map[path]))
+            formatted_html.append('</div>')
+
+        return "\n".join(formatted_html)
+
+    def create_document(self) -> str:
+        """生成HTML文档
+        Returns:
+            str: 完整的HTML文档字符串
+        """
+        return f"""
+        <!DOCTYPE html>
+        <html lang="zh-CN">
+        <head>
+            <meta charset="utf-8">
+            <meta name="viewport" content="width=device-width, initial-scale=1">
+            <title>文档总结报告</title>
+            <link href="https://cdnjs.cloudflare.com/ajax/libs/inter/3.19.3/inter.css" rel="stylesheet">
+            <link href="https://fonts.googleapis.com/css2?family=Plus+Jakarta+Sans:wght@400;600&display=swap" rel="stylesheet">
+            <style>{self.css_styles}</style>
+        </head>
+        <body>
+            <div class="container">
+                <h1><span class="icon">📑</span> 文档总结报告</h1>
+                <div class="summary">
+                    <h2><span class="icon">📋</span> 总体摘要</h2>
+                    <p>{self.md.convert(self.final_summary)}</p>
+                </div>
+                {self.format_failed_files()}
+                <div class="details">
+                    <h2><span class="icon">📚</span> 各文件详细总结</h2>
+                    {self.format_file_summaries()}
+                </div>
+            </div>
+
+        </body>
+        </html>
+        """

crazy_functions/doc_fns/content_folder.py

@@ -0,0 +1,237 @@
+from abc import ABC, abstractmethod
+from typing import Any, Dict, Optional, Type, TypeVar, Generic, Union
+
+from dataclasses import dataclass
+from enum import Enum, auto
+import logging
+from datetime import datetime
+
+# 设置日志
+logger = logging.getLogger(__name__)
+
+
+# 自定义异常类定义
+class FoldingError(Exception):
+    """折叠相关的自定义异常基类"""
+    pass
+
+
+class FormattingError(FoldingError):
+    """格式化过程中的错误"""
+    pass
+
+
+class MetadataError(FoldingError):
+    """元数据相关的错误"""
+    pass
+
+
+class ValidationError(FoldingError):
+    """验证错误"""
+    pass
+
+
+class FoldingStyle(Enum):
+    """折叠样式枚举"""
+    SIMPLE = auto()  # 简单折叠
+    DETAILED = auto()  # 详细折叠（带有额外信息）
+    NESTED = auto()  # 嵌套折叠
+
+
+@dataclass
+class FoldingOptions:
+    """折叠选项配置"""
+    style: FoldingStyle = FoldingStyle.DETAILED
+    code_language: Optional[str] = None  # 代码块的语言
+    show_timestamp: bool = False  # 是否显示时间戳
+    indent_level: int = 0  # 缩进级别
+    custom_css: Optional[str] = None  # 自定义CSS类
+
+
+T = TypeVar('T')  # 用于泛型类型
+
+
+class BaseMetadata(ABC):
+    """元数据基类"""
+
+    @abstractmethod
+    def validate(self) -> bool:
+        """验证元数据的有效性"""
+        pass
+
+    def _validate_non_empty_str(self, value: Optional[str]) -> bool:
+        """验证字符串非空"""
+        return bool(value and value.strip())
+
+
+@dataclass
+class FileMetadata(BaseMetadata):
+    """文件元数据"""
+    rel_path: str
+    size: float
+    last_modified: Optional[datetime] = None
+    mime_type: Optional[str] = None
+    encoding: str = 'utf-8'
+
+    def validate(self) -> bool:
+        """验证文件元数据的有效性"""
+        try:
+            if not self._validate_non_empty_str(self.rel_path):
+                return False
+            if self.size < 0:
+                return False
+            return True
+        except Exception as e:
+            logger.error(f"File metadata validation error: {str(e)}")
+            return False
+
+
+
+
+class ContentFormatter(ABC, Generic[T]):
+    """内容格式化抽象基类
+
+    支持泛型类型参数，可以指定具体的元数据类型。
+    """
+
+    @abstractmethod
+    def format(self,
+               content: str,
+               metadata: T,
+               options: Optional[FoldingOptions] = None) -> str:
+        """格式化内容
+
+        Args:
+            content: 需要格式化的内容
+            metadata: 类型化的元数据
+            options: 折叠选项
+
+        Returns:
+            str: 格式化后的内容
+
+        Raises:
+            FormattingError: 格式化过程中的错误
+        """
+        pass
+
+    def _create_summary(self, metadata: T) -> str:
+        """创建折叠摘要，可被子类重写"""
+        return str(metadata)
+
+    def _format_content_block(self,
+                              content: str,
+                              options: Optional[FoldingOptions]) -> str:
+        """格式化内容块，处理代码块等特殊格式"""
+        if not options:
+            return content
+
+        if options.code_language:
+            return f"```{options.code_language}\n{content}\n```"
+        return content
+
+    def _add_indent(self, text: str, level: int) -> str:
+        """添加缩进"""
+        if level <= 0:
+            return text
+        indent = "  " * level
+        return "\n".join(indent + line for line in text.splitlines())
+
+
+class FileContentFormatter(ContentFormatter[FileMetadata]):
+    """文件内容格式化器"""
+
+    def format(self,
+               content: str,
+               metadata: FileMetadata,
+               options: Optional[FoldingOptions] = None) -> str:
+        """格式化文件内容"""
+        if not metadata.validate():
+            raise MetadataError("Invalid file metadata")
+
+        try:
+            options = options or FoldingOptions()
+
+            # 构建摘要信息
+            summary_parts = [
+                f"{metadata.rel_path} ({metadata.size:.2f}MB)",
+                f"Type: {metadata.mime_type}" if metadata.mime_type else None,
+                (f"Modified: {metadata.last_modified.strftime('%Y-%m-%d %H:%M:%S')}"
+                 if metadata.last_modified and options.show_timestamp else None)
+            ]
+            summary = " | ".join(filter(None, summary_parts))
+
+            # 构建HTML类
+            css_class = f' class="{options.custom_css}"' if options.custom_css else ''
+
+            # 格式化内容
+            formatted_content = self._format_content_block(content, options)
+
+            # 组装最终结果
+            result = (
+                f'<details{css_class}><summary>{summary}</summary>\n\n'
+                f'{formatted_content}\n\n'
+                f'</details>\n\n'
+            )
+
+            return self._add_indent(result, options.indent_level)
+
+        except Exception as e:
+            logger.error(f"Error formatting file content: {str(e)}")
+            raise FormattingError(f"Failed to format file content: {str(e)}")
+
+
+class ContentFoldingManager:
+    """内容折叠管理器"""
+
+    def __init__(self):
+        """初始化折叠管理器"""
+        self._formatters: Dict[str, ContentFormatter] = {}
+        self._register_default_formatters()
+
+    def _register_default_formatters(self) -> None:
+        """注册默认的格式化器"""
+        self.register_formatter('file', FileContentFormatter())
+
+    def register_formatter(self, name: str, formatter: ContentFormatter) -> None:
+        """注册新的格式化器"""
+        if not isinstance(formatter, ContentFormatter):
+            raise TypeError("Formatter must implement ContentFormatter interface")
+        self._formatters[name] = formatter
+
+    def _guess_language(self, extension: str) -> Optional[str]:
+        """根据文件扩展名猜测编程语言"""
+        extension = extension.lower().lstrip('.')
+        language_map = {
+            'py': 'python',
+            'js': 'javascript',
+            'java': 'java',
+            'cpp': 'cpp',
+            'cs': 'csharp',
+            'html': 'html',
+            'css': 'css',
+            'md': 'markdown',
+            'json': 'json',
+            'xml': 'xml',
+            'sql': 'sql',
+            'sh': 'bash',
+            'yaml': 'yaml',
+            'yml': 'yaml',
+            'txt': None  # 纯文本不需要语言标识
+        }
+        return language_map.get(extension)
+
+    def format_content(self,
+                       content: str,
+                       formatter_type: str,
+                       metadata: Union[FileMetadata],
+                       options: Optional[FoldingOptions] = None) -> str:
+        """格式化内容"""
+        formatter = self._formatters.get(formatter_type)
+        if not formatter:
+            raise KeyError(f"No formatter registered for type: {formatter_type}")
+
+        if not isinstance(metadata, FileMetadata):
+            raise TypeError("Invalid metadata type")
+
+        return formatter.format(content, metadata, options)
+

crazy_functions/doc_fns/conversation_doc/excel_doc.py

@@ -0,0 +1,211 @@
+import re
+import os
+import pandas as pd
+from datetime import datetime
+from openpyxl import Workbook
+
+
+class ExcelTableFormatter:
+    """聊天记录中Markdown表格转Excel生成器"""
+
+    def __init__(self):
+        """初始化Excel文档对象"""
+        self.workbook = Workbook()
+        self._table_count = 0
+        self._current_sheet = None
+
+    def _normalize_table_row(self, row):
+        """标准化表格行，处理不同的分隔符情况"""
+        row = row.strip()
+        if row.startswith('|'):
+            row = row[1:]
+        if row.endswith('|'):
+            row = row[:-1]
+        return [cell.strip() for cell in row.split('|')]
+
+    def _is_separator_row(self, row):
+        """检查是否是分隔行（由 - 或 : 组成）"""
+        clean_row = re.sub(r'[\s|]', '', row)
+        return bool(re.match(r'^[-:]+$', clean_row))
+
+    def _extract_tables_from_text(self, text):
+        """从文本中提取所有表格内容"""
+        if not isinstance(text, str):
+            return []
+
+        tables = []
+        current_table = []
+        is_in_table = False
+
+        for line in text.split('\n'):
+            line = line.strip()
+            if not line:
+                if is_in_table and current_table:
+                    if len(current_table) >= 2:
+                        tables.append(current_table)
+                    current_table = []
+                    is_in_table = False
+                continue
+
+            if '|' in line:
+                if not is_in_table:
+                    is_in_table = True
+                current_table.append(line)
+            else:
+                if is_in_table and current_table:
+                    if len(current_table) >= 2:
+                        tables.append(current_table)
+                    current_table = []
+                    is_in_table = False
+
+        if is_in_table and current_table and len(current_table) >= 2:
+            tables.append(current_table)
+
+        return tables
+
+    def _parse_table(self, table_lines):
+        """解析表格内容为结构化数据"""
+        try:
+            headers = self._normalize_table_row(table_lines[0])
+
+            separator_index = next(
+                (i for i, line in enumerate(table_lines) if self._is_separator_row(line)),
+                1
+            )
+
+            data_rows = []
+            for line in table_lines[separator_index + 1:]:
+                cells = self._normalize_table_row(line)
+                # 确保单元格数量与表头一致
+                while len(cells) < len(headers):
+                    cells.append('')
+                cells = cells[:len(headers)]
+                data_rows.append(cells)
+
+            if headers and data_rows:
+                return {
+                    'headers': headers,
+                    'data': data_rows
+                }
+        except Exception as e:
+            print(f"解析表格时发生错误: {str(e)}")
+
+        return None
+
+    def _create_sheet(self, question_num, table_num):
+        """创建新的工作表"""
+        sheet_name = f'Q{question_num}_T{table_num}'
+        if len(sheet_name) > 31:
+            sheet_name = f'Table{self._table_count}'
+
+        if sheet_name in self.workbook.sheetnames:
+            sheet_name = f'{sheet_name}_{datetime.now().strftime("%H%M%S")}'
+
+        return self.workbook.create_sheet(title=sheet_name)
+
+    def create_document(self, history):
+        """
+        处理聊天历史中的所有表格并创建Excel文档
+
+        Args:
+            history: 聊天历史列表
+
+        Returns:
+            Workbook: 处理完成的Excel工作簿对象，如果没有表格则返回None
+        """
+        has_tables = False
+
+        # 删除默认创建的工作表
+        default_sheet = self.workbook['Sheet']
+        self.workbook.remove(default_sheet)
+
+        # 遍历所有回答
+        for i in range(1, len(history), 2):
+            answer = history[i]
+            tables = self._extract_tables_from_text(answer)
+
+            for table_lines in tables:
+                parsed_table = self._parse_table(table_lines)
+                if parsed_table:
+                    self._table_count += 1
+                    sheet = self._create_sheet(i // 2 + 1, self._table_count)
+
+                    # 写入表头
+                    for col, header in enumerate(parsed_table['headers'], 1):
+                        sheet.cell(row=1, column=col, value=header)
+
+                    # 写入数据
+                    for row_idx, row_data in enumerate(parsed_table['data'], 2):
+                        for col_idx, value in enumerate(row_data, 1):
+                            sheet.cell(row=row_idx, column=col_idx, value=value)
+
+                    has_tables = True
+
+        return self.workbook if has_tables else None
+
+
+def save_chat_tables(history, save_dir, base_name):
+    """
+    保存聊天历史中的表格到Excel文件
+
+    Args:
+        history: 聊天历史列表
+        save_dir: 保存目录
+        base_name: 基础文件名
+
+    Returns:
+        list: 保存的文件路径列表
+    """
+    result_files = []
+
+    try:
+        # 创建Excel格式
+        excel_formatter = ExcelTableFormatter()
+        workbook = excel_formatter.create_document(history)
+
+        if workbook is not None:
+            # 确保保存目录存在
+            os.makedirs(save_dir, exist_ok=True)
+
+            # 生成Excel文件路径
+            excel_file = os.path.join(save_dir, base_name + '.xlsx')
+
+            # 保存Excel文件
+            workbook.save(excel_file)
+            result_files.append(excel_file)
+            print(f"已保存表格到Excel文件: {excel_file}")
+    except Exception as e:
+        print(f"保存Excel格式失败: {str(e)}")
+
+    return result_files
+
+
+# 使用示例
+if __name__ == "__main__":
+    # 示例聊天历史
+    history = [
+        "问题1",
+        """这是第一个表格：
+        | A | B | C |
+        |---|---|---|
+        | 1 | 2 | 3 |""",
+
+        "问题2",
+        "这是没有表格的回答",
+
+        "问题3",
+        """回答包含多个表格：
+        | Name | Age |
+        |------|-----|
+        | Tom  | 20  |
+
+        第二个表格：
+        | X | Y |
+        |---|---|
+        | 1 | 2 |"""
+    ]
+
+    # 保存表格
+    save_dir = "output"
+    base_name = "chat_tables"
+    saved_files = save_chat_tables(history, save_dir, base_name)

crazy_functions/doc_fns/conversation_doc/html_doc.py

@@ -0,0 +1,190 @@
+
+
+class HtmlFormatter:
+    """聊天记录HTML格式生成器"""
+    
+    def __init__(self, chatbot, history):
+        self.chatbot = chatbot
+        self.history = history
+        self.css_styles = """
+        :root {
+            --primary-color: #2563eb;
+            --primary-light: #eff6ff;
+            --secondary-color: #1e293b;
+            --background-color: #f8fafc;
+            --text-color: #334155;
+            --border-color: #e2e8f0;
+            --card-shadow: 0 4px 6px -1px rgb(0 0 0 / 0.1), 0 2px 4px -2px rgb(0 0 0 / 0.1);
+        }
+
+        body {
+            font-family: system-ui, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
+            line-height: 1.8;
+            margin: 0;
+            padding: 2rem;
+            color: var(--text-color);
+            background-color: var(--background-color);
+        }
+
+        .container {
+            max-width: 1200px;
+            margin: 0 auto;
+            background: white;
+            padding: 2rem;
+            border-radius: 16px;
+            box-shadow: var(--card-shadow);
+        }
+        ::selection {
+            background: var(--primary-light);
+            color: var(--primary-color);
+        }
+        @keyframes fadeIn {
+            from { opacity: 0; transform: translateY(20px); }
+            to { opacity: 1; transform: translateY(0); }
+        }
+        
+        @keyframes slideIn {
+            from { transform: translateX(-20px); opacity: 0; }
+            to { transform: translateX(0); opacity: 1; }
+        }
+        
+        .container {
+            animation: fadeIn 0.6s ease-out;
+        }
+        
+        .QaBox {
+            animation: slideIn 0.5s ease-out;
+            transition: all 0.3s ease;
+        }
+        
+        .QaBox:hover {
+            transform: translateX(5px);
+        }
+        .Question, .Answer, .historyBox {
+            transition: all 0.3s ease;
+        }
+        .chat-title {
+            color: var(--primary-color);
+            font-size: 2em;
+            text-align: center;
+            margin: 1rem 0 2rem;
+            padding-bottom: 1rem;
+            border-bottom: 2px solid var(--primary-color);
+        }
+
+        .chat-body {
+            display: flex;
+            flex-direction: column;
+            gap: 1.5rem;
+            margin: 2rem 0;
+        }
+
+        .QaBox {
+            background: white;
+            padding: 1.5rem;
+            border-radius: 8px;
+            border-left: 4px solid var(--primary-color);
+            box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+            margin-bottom: 1.5rem;
+        }
+
+        .Question {
+            color: var(--secondary-color);
+            font-weight: 500;
+            margin-bottom: 1rem;
+        }
+
+        .Answer {
+            color: var(--text-color);
+            background: var(--primary-light);
+            padding: 1rem;
+            border-radius: 6px;
+        }
+
+        .history-section {
+            margin-top: 3rem;
+            padding-top: 2rem;
+            border-top: 2px solid var(--border-color);
+        }
+
+        .history-title {
+            color: var(--secondary-color);
+            font-size: 1.5em;
+            margin-bottom: 1.5rem;
+            text-align: center;
+        }
+
+        .historyBox {
+            background: white;
+            padding: 1rem;
+            margin: 0.5rem 0;
+            border-radius: 6px;
+            border: 1px solid var(--border-color);
+        }
+
+        @media (prefers-color-scheme: dark) {
+            :root {
+                --background-color: #0f172a;
+                --text-color: #e2e8f0;
+                --border-color: #1e293b;
+            }
+            
+            .container, .QaBox {
+                background: #1e293b;
+            }
+        }
+        """
+
+    def format_chat_content(self) -> str:
+        """格式化聊天内容"""
+        chat_content = []
+        for q, a in self.chatbot:
+            question = str(q) if q is not None else ""
+            answer = str(a) if a is not None else ""
+            chat_content.append(f'''
+            <div class="QaBox">
+                <div class="Question">{question}</div>
+                <div class="Answer">{answer}</div>
+            </div>
+            ''')
+        return "\n".join(chat_content)
+
+    def format_history_content(self) -> str:
+        """格式化历史记录内容"""
+        if not self.history:
+            return ""
+            
+        history_content = []
+        for entry in self.history:
+            history_content.append(f'''
+            <div class="historyBox">
+                <div class="entry">{entry}</div>
+            </div>
+            ''')
+        return "\n".join(history_content)
+
+    def create_document(self) -> str:
+        """生成完整的HTML文档
+        
+        Returns:
+            str: 完整的HTML文档字符串
+        """
+        return f"""
+        <!DOCTYPE html>
+        <html lang="zh-CN">
+        <head>
+            <meta charset="utf-8">
+            <meta name="viewport" content="width=device-width, initial-scale=1">
+            <title>对话存档</title>
+            <style>{self.css_styles}</style>
+        </head>
+        <body>
+            <div class="container">
+                <h1 class="chat-title">对话存档</h1>
+                <div class="chat-body">
+                    {self.format_chat_content()}
+                </div>
+            </div>
+        </body>
+        </html>
+        """

crazy_functions/doc_fns/conversation_doc/markdown_doc.py

@@ -0,0 +1,39 @@
+
+class MarkdownFormatter:
+    """Markdown格式文档生成器 - 用于生成对话记录的markdown文档"""
+
+    def __init__(self):
+        self.content = []
+
+    def _add_content(self, text: str):
+        """添加正文内容"""
+        if text:
+            self.content.append(f"\n{text}\n")
+
+    def create_document(self, history: list) -> str:
+        """
+        创建完整的Markdown文档
+        Args:
+            history: 历史记录列表，偶数位置为问题，奇数位置为答案
+        Returns:
+            str: 生成的Markdown文本
+        """
+        self.content = []
+        
+        # 处理问答对
+        for i in range(0, len(history), 2):
+            question = history[i]
+            answer = history[i + 1]
+            
+            # 添加问题
+            self.content.append(f"\n### 问题 {i//2 + 1}")
+            self._add_content(question)
+            
+            # 添加回答
+            self.content.append(f"\n### 回答 {i//2 + 1}")
+            self._add_content(answer)
+            
+            # 添加分隔线
+            self.content.append("\n---\n")
+
+        return "\n".join(self.content)

crazy_functions/doc_fns/conversation_doc/pdf_doc.py

@@ -0,0 +1,172 @@
+from datetime import datetime
+import os
+import re
+from reportlab.pdfbase import pdfmetrics
+from reportlab.pdfbase.ttfonts import TTFont
+
+def convert_markdown_to_pdf(markdown_text):
+    """将Markdown文本转换为PDF格式的纯文本"""
+    if not markdown_text:
+        return ""
+
+    # 标准化换行符
+    markdown_text = markdown_text.replace('\r\n', '\n').replace('\r', '\n')
+
+    # 处理标题、粗体、斜体
+    markdown_text = re.sub(r'^#\s+(.+)$', r'\1', markdown_text, flags=re.MULTILINE)
+    markdown_text = re.sub(r'\*\*(.+?)\*\*', r'\1', markdown_text)
+    markdown_text = re.sub(r'\*(.+?)\*', r'\1', markdown_text)
+
+    # 处理列表
+    markdown_text = re.sub(r'^\s*[-*+]\s+(.+?)(?=\n|$)', r'• \1', markdown_text, flags=re.MULTILINE)
+    markdown_text = re.sub(r'^\s*\d+\.\s+(.+?)(?=\n|$)', r'\1', markdown_text, flags=re.MULTILINE)
+
+    # 处理链接
+    markdown_text = re.sub(r'\[([^\]]+)\]\(([^)]+)\)', r'\1', markdown_text)
+
+    # 处理段落
+    markdown_text = re.sub(r'\n{2,}', '\n', markdown_text)
+    markdown_text = re.sub(r'(?<!\n)(?<!^)(?<!•\s)(?<!\d\.\s)\n(?![\s•\d])', '\n\n', markdown_text, flags=re.MULTILINE)
+
+    # 清理空白
+    markdown_text = re.sub(r' +', ' ', markdown_text)
+    markdown_text = re.sub(r'(?m)^\s+|\s+$', '', markdown_text)
+
+    return markdown_text.strip()
+
+class PDFFormatter:
+    """聊天记录PDF文档生成器 - 使用 Noto Sans CJK 字体"""
+
+    def __init__(self):
+        self._init_reportlab()
+        self._register_fonts()
+        self.styles = self._get_reportlab_lib()['getSampleStyleSheet']()
+        self._create_styles()
+
+    def _init_reportlab(self):
+        """初始化 ReportLab 相关组件"""
+        from reportlab.lib.pagesizes import A4
+        from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
+        from reportlab.lib.units import cm
+        from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
+        
+        self._lib = {
+            'A4': A4,
+            'getSampleStyleSheet': getSampleStyleSheet,
+            'ParagraphStyle': ParagraphStyle,
+            'cm': cm
+        }
+        
+        self._platypus = {
+            'SimpleDocTemplate': SimpleDocTemplate,
+            'Paragraph': Paragraph,
+            'Spacer': Spacer
+        }
+
+    def _get_reportlab_lib(self):
+        return self._lib
+
+    def _get_reportlab_platypus(self):
+        return self._platypus
+
+    def _register_fonts(self):
+        """注册 Noto Sans CJK 字体"""
+        possible_font_paths = [
+            '/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc',
+            '/usr/share/fonts/noto-cjk/NotoSansCJK-Regular.ttc',
+            '/usr/share/fonts/noto/NotoSansCJK-Regular.ttc'
+        ]
+
+        font_registered = False
+        for path in possible_font_paths:
+            if os.path.exists(path):
+                try:
+                    pdfmetrics.registerFont(TTFont('NotoSansCJK', path))
+                    font_registered = True
+                    break
+                except:
+                    continue
+
+        if not font_registered:
+            print("Warning: Could not find Noto Sans CJK font. Using fallback font.")
+            self.font_name = 'Helvetica'
+        else:
+            self.font_name = 'NotoSansCJK'
+
+    def _create_styles(self):
+        """创建文档样式"""
+        ParagraphStyle = self._lib['ParagraphStyle']
+
+        # 标题样式
+        self.styles.add(ParagraphStyle(
+            name='Title_Custom',
+            fontName=self.font_name,
+            fontSize=24,
+            leading=38,
+            alignment=1,
+            spaceAfter=32
+        ))
+
+        # 日期样式
+        self.styles.add(ParagraphStyle(
+            name='Date_Style',
+            fontName=self.font_name,
+            fontSize=16,
+            leading=20,
+            alignment=1,
+            spaceAfter=20
+        ))
+
+        # 问题样式
+        self.styles.add(ParagraphStyle(
+            name='Question_Style',
+            fontName=self.font_name,
+            fontSize=12,
+            leading=18,
+            leftIndent=28,
+            spaceAfter=6
+        ))
+
+        # 回答样式
+        self.styles.add(ParagraphStyle(
+            name='Answer_Style',
+            fontName=self.font_name,
+            fontSize=12,
+            leading=18,
+            leftIndent=28,
+            spaceAfter=12
+        ))
+
+    def create_document(self, history, output_path):
+        """生成PDF文档"""
+        # 创建PDF文档
+        doc = self._platypus['SimpleDocTemplate'](
+            output_path,
+            pagesize=self._lib['A4'],
+            rightMargin=2.6 * self._lib['cm'],
+            leftMargin=2.8 * self._lib['cm'],
+            topMargin=3.7 * self._lib['cm'],
+            bottomMargin=3.5 * self._lib['cm']
+        )
+
+        # 构建内容
+        story = []
+        Paragraph = self._platypus['Paragraph']
+
+        # 添加对话内容
+        for i in range(0, len(history), 2):
+            question = history[i]
+            answer = convert_markdown_to_pdf(history[i + 1]) if i + 1 < len(history) else ""
+
+            if question:
+                q_text = f'问题 {i // 2 + 1}：{str(question)}'
+                story.append(Paragraph(q_text, self.styles['Question_Style']))
+
+            if answer:
+                a_text = f'回答 {i // 2 + 1}：{str(answer)}'
+                story.append(Paragraph(a_text, self.styles['Answer_Style']))
+
+        # 构建PDF
+        doc.build(story)
+
+        return doc

crazy_functions/doc_fns/conversation_doc/txt_doc.py

@@ -0,0 +1,79 @@
+
+import re
+
+
+def convert_markdown_to_txt(markdown_text):
+    """Convert markdown text to plain text while preserving formatting"""
+    # Standardize line endings
+    markdown_text = markdown_text.replace('\r\n', '\n').replace('\r', '\n')
+
+    # 1. Handle headers but keep their formatting instead of removing them
+    markdown_text = re.sub(r'^#\s+(.+)$', r'# \1', markdown_text, flags=re.MULTILINE)
+    markdown_text = re.sub(r'^##\s+(.+)$', r'## \1', markdown_text, flags=re.MULTILINE)
+    markdown_text = re.sub(r'^###\s+(.+)$', r'### \1', markdown_text, flags=re.MULTILINE)
+
+    # 2. Handle bold and italic - simply remove markers
+    markdown_text = re.sub(r'\*\*(.+?)\*\*', r'\1', markdown_text)
+    markdown_text = re.sub(r'\*(.+?)\*', r'\1', markdown_text)
+
+    # 3. Handle lists but preserve formatting
+    markdown_text = re.sub(r'^\s*[-*+]\s+(.+?)(?=\n|$)', r'• \1', markdown_text, flags=re.MULTILINE)
+
+    # 4. Handle links - keep only the text
+    markdown_text = re.sub(r'\[([^\]]+)\]\(([^)]+)\)', r'\1 (\2)', markdown_text)
+
+    # 5. Handle HTML links - convert to user-friendly format
+    markdown_text = re.sub(r'<a href=[\'"]([^\'"]+)[\'"](?:\s+target=[\'"][^\'"]+[\'"])?>([^<]+)</a>', r'\2 (\1)',
+                           markdown_text)
+
+    # 6. Preserve paragraph breaks
+    markdown_text = re.sub(r'\n{3,}', '\n\n', markdown_text)  # normalize multiple newlines to double newlines
+
+    # 7. Clean up extra spaces but maintain indentation
+    markdown_text = re.sub(r' +', ' ', markdown_text)
+
+    return markdown_text.strip()
+
+
+class TxtFormatter:
+    """Chat history TXT document generator"""
+
+    def __init__(self):
+        self.content = []
+        self._setup_document()
+
+    def _setup_document(self):
+        """Initialize document with header"""
+        self.content.append("=" * 50)
+        self.content.append("GPT-Academic对话记录".center(48))
+        self.content.append("=" * 50)
+
+    def _format_header(self):
+        """Create document header with current date"""
+        from datetime import datetime
+        date_str = datetime.now().strftime('%Y年%m月%d日')
+        return [
+            date_str.center(48),
+            "\n"  # Add blank line after date
+        ]
+
+    def create_document(self, history):
+        """Generate document from chat history"""
+        # Add header with date
+        self.content.extend(self._format_header())
+
+        # Add conversation content
+        for i in range(0, len(history), 2):
+            question = history[i]
+            answer = convert_markdown_to_txt(history[i + 1]) if i + 1 < len(history) else ""
+
+            if question:
+                self.content.append(f"问题 {i // 2 + 1}：{str(question)}")
+                self.content.append("")  # Add blank line
+
+            if answer:
+                self.content.append(f"回答 {i // 2 + 1}：{str(answer)}")
+                self.content.append("")  # Add blank line
+
+        # Join all content with newlines
+        return "\n".join(self.content)

crazy_functions/doc_fns/conversation_doc/word2pdf.py

@@ -0,0 +1,155 @@
+from docx2pdf import convert
+import os
+import platform
+import subprocess
+from typing import Union
+from pathlib import Path
+from datetime import datetime
+
+class WordToPdfConverter:
+    """Word文档转PDF转换器"""
+    
+    @staticmethod
+    def convert_to_pdf(word_path: Union[str, Path], pdf_path: Union[str, Path] = None) -> str:
+        """
+        将Word文档转换为PDF
+        
+        参数:
+            word_path: Word文档的路径
+            pdf_path: 可选，PDF文件的输出路径。如果未指定，将使用与Word文档相同的名称和位置
+            
+        返回:
+            生成的PDF文件路径
+        
+        异常:
+            如果转换失败，将抛出相应异常
+        """
+        try:
+            # 确保输入路径是Path对象
+            word_path = Path(word_path)
+            
+            # 如果未指定pdf_path，则使用与word文档相同的名称
+            if pdf_path is None:
+                pdf_path = word_path.with_suffix('.pdf')
+            else:
+                pdf_path = Path(pdf_path)
+            
+            # 检查操作系统
+            if platform.system() == 'Linux':
+                # Linux系统需要安装libreoffice
+                which_result = subprocess.run(['which', 'libreoffice'], capture_output=True, text=True)
+                if which_result.returncode != 0:
+                    raise RuntimeError("请先安装LibreOffice: sudo apt-get install libreoffice")
+                
+                print(f"开始转换Word文档: {word_path} 到 PDF")
+                
+                # 使用subprocess代替os.system
+                result = subprocess.run(
+                    ['libreoffice', '--headless', '--convert-to', 'pdf:writer_pdf_Export', 
+                     str(word_path), '--outdir', str(pdf_path.parent)],
+                    capture_output=True, text=True
+                )
+                
+                if result.returncode != 0:
+                    error_msg = result.stderr or "未知错误"
+                    print(f"LibreOffice转换失败，错误信息: {error_msg}")
+                    raise RuntimeError(f"LibreOffice转换失败: {error_msg}")
+                
+                print(f"LibreOffice转换输出: {result.stdout}")
+                
+                # 如果输出路径与默认生成的不同，则重命名
+                default_pdf = word_path.with_suffix('.pdf')
+                if default_pdf != pdf_path and default_pdf.exists():
+                    os.rename(default_pdf, pdf_path)
+                    print(f"已将PDF从 {default_pdf} 重命名为 {pdf_path}")
+                
+                # 验证PDF是否成功生成
+                if not pdf_path.exists() or pdf_path.stat().st_size == 0:
+                    raise RuntimeError("PDF生成失败或文件为空")
+                
+                print(f"PDF转换成功，文件大小: {pdf_path.stat().st_size} 字节")
+            else:
+                # Windows和MacOS使用docx2pdf
+                print(f"使用docx2pdf转换 {word_path} 到 {pdf_path}")
+                convert(word_path, pdf_path)
+                
+                # 验证PDF是否成功生成
+                if not pdf_path.exists() or pdf_path.stat().st_size == 0:
+                    raise RuntimeError("PDF生成失败或文件为空")
+                    
+                print(f"PDF转换成功，文件大小: {pdf_path.stat().st_size} 字节")
+            
+            return str(pdf_path)
+            
+        except Exception as e:
+            print(f"PDF转换异常: {str(e)}")
+            raise Exception(f"转换PDF失败: {str(e)}")
+
+    @staticmethod
+    def batch_convert(word_dir: Union[str, Path], pdf_dir: Union[str, Path] = None) -> list:
+        """
+        批量转换目录下的所有Word文档
+        
+        参数:
+            word_dir: 包含Word文档的目录路径
+            pdf_dir: 可选，PDF文件的输出目录。如果未指定，将使用与Word文档相同的目录
+            
+        返回:
+            生成的PDF文件路径列表
+        """
+        word_dir = Path(word_dir)
+        if pdf_dir:
+            pdf_dir = Path(pdf_dir)
+            pdf_dir.mkdir(parents=True, exist_ok=True)
+            
+        converted_files = []
+        
+        for word_file in word_dir.glob("*.docx"):
+            try:
+                if pdf_dir:
+                    pdf_path = pdf_dir / word_file.with_suffix('.pdf').name
+                else:
+                    pdf_path = word_file.with_suffix('.pdf')
+                    
+                pdf_file = WordToPdfConverter.convert_to_pdf(word_file, pdf_path)
+                converted_files.append(pdf_file)
+                
+            except Exception as e:
+                print(f"转换 {word_file} 失败: {str(e)}")
+                
+        return converted_files
+
+    @staticmethod
+    def convert_doc_to_pdf(doc, output_dir: Union[str, Path] = None) -> str:
+        """
+        将docx对象直接转换为PDF
+        
+        参数:
+            doc: python-docx的Document对象
+            output_dir: 可选，输出目录。如果未指定，将使用当前目录
+            
+        返回:
+            生成的PDF文件路径
+        """
+        try:
+            # 设置临时文件路径和输出路径
+            output_dir = Path(output_dir) if output_dir else Path.cwd()
+            output_dir.mkdir(parents=True, exist_ok=True)
+            
+            # 生成临时word文件
+            temp_docx = output_dir / f"temp_{datetime.now().strftime('%Y%m%d_%H%M%S')}.docx"
+            doc.save(temp_docx)
+            
+            # 转换为PDF
+            pdf_path = temp_docx.with_suffix('.pdf')
+            WordToPdfConverter.convert_to_pdf(temp_docx, pdf_path)
+            
+            # 删除临时word文件
+            temp_docx.unlink()
+            
+            return str(pdf_path)
+            
+        except Exception as e:
+            if temp_docx.exists():
+                temp_docx.unlink()
+            raise Exception(f"转换PDF失败: {str(e)}") 

crazy_functions/doc_fns/conversation_doc/word_doc.py

@@ -0,0 +1,177 @@
+import re
+from docx import Document
+from docx.shared import Cm, Pt
+from docx.enum.text import WD_PARAGRAPH_ALIGNMENT, WD_LINE_SPACING
+from docx.enum.style import WD_STYLE_TYPE
+from docx.oxml.ns import qn
+from datetime import datetime
+
+
+def convert_markdown_to_word(markdown_text):
+    # 0. 首先标准化所有换行符为\n
+    markdown_text = markdown_text.replace('\r\n', '\n').replace('\r', '\n')
+
+    # 1. 处理标题 - 支持更多级别的标题，使用更精确的正则
+    # 保留标题标记，以便后续处理时还能识别出标题级别
+    markdown_text = re.sub(r'^(#{1,6})\s+(.+?)(?:\s+#+)?$', r'\1 \2', markdown_text, flags=re.MULTILINE)
+
+    # 2. 处理粗体、斜体和加粗斜体
+    markdown_text = re.sub(r'\*\*\*(.+?)\*\*\*', r'\1', markdown_text)  # 加粗斜体
+    markdown_text = re.sub(r'\*\*(.+?)\*\*', r'\1', markdown_text)  # 加粗
+    markdown_text = re.sub(r'\*(.+?)\*', r'\1', markdown_text)  # 斜体
+    markdown_text = re.sub(r'_(.+?)_', r'\1', markdown_text)  # 下划线斜体
+    markdown_text = re.sub(r'__(.+?)__', r'\1', markdown_text)  # 下划线加粗
+
+    # 3. 处理代码块 - 不移除，而是简化格式
+    # 多行代码块
+    markdown_text = re.sub(r'```(?:\w+)?\n([\s\S]*?)```', r'[代码块]\n\1[/代码块]', markdown_text)
+    # 单行代码
+    markdown_text = re.sub(r'`([^`]+)`', r'[代码]\1[/代码]', markdown_text)
+
+    # 4. 处理列表 - 保留列表结构
+    # 匹配无序列表
+    markdown_text = re.sub(r'^(\s*)[-*+]\s+(.+?)$', r'\1• \2', markdown_text, flags=re.MULTILINE)
+
+    # 5. 处理Markdown链接
+    markdown_text = re.sub(r'\[([^\]]+)\]\(([^)]+?)\s*(?:"[^"]*")?\)', r'\1 (\2)', markdown_text)
+
+    # 6. 处理HTML链接
+    markdown_text = re.sub(r'<a href=[\'"]([^\'"]+)[\'"](?:\s+target=[\'"][^\'"]+[\'"])?>([^<]+)</a>', r'\2 (\1)',
+                           markdown_text)
+
+    # 7. 处理图片
+    markdown_text = re.sub(r'!\[([^\]]*)\]\([^)]+\)', r'[图片：\1]', markdown_text)
+
+    return markdown_text
+
+
+class WordFormatter:
+    """聊天记录Word文档生成器 - 符合中国政府公文格式规范(GB/T 9704-2012)"""
+
+    def __init__(self):
+        self.doc = Document()
+        self._setup_document()
+        self._create_styles()
+
+    def _setup_document(self):
+        """设置文档基本格式，包括页面设置和页眉"""
+        sections = self.doc.sections
+        for section in sections:
+            # 设置页面大小为A4
+            section.page_width = Cm(21)
+            section.page_height = Cm(29.7)
+            # 设置页边距
+            section.top_margin = Cm(3.7)  # 上边距37mm
+            section.bottom_margin = Cm(3.5)  # 下边距35mm
+            section.left_margin = Cm(2.8)  # 左边距28mm
+            section.right_margin = Cm(2.6)  # 右边距26mm
+            # 设置页眉页脚距离
+            section.header_distance = Cm(2.0)
+            section.footer_distance = Cm(2.0)
+
+            # 添加页眉
+            header = section.header
+            header_para = header.paragraphs[0]
+            header_para.alignment = WD_PARAGRAPH_ALIGNMENT.RIGHT
+            header_run = header_para.add_run("GPT-Academic对话记录")
+            header_run.font.name = '仿宋'
+            header_run._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
+            header_run.font.size = Pt(9)
+
+    def _create_styles(self):
+        """创建文档样式"""
+        # 创建正文样式
+        style = self.doc.styles.add_style('Normal_Custom', WD_STYLE_TYPE.PARAGRAPH)
+        style.font.name = '仿宋'
+        style._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
+        style.font.size = Pt(12)  # 调整为12磅
+        style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
+        style.paragraph_format.space_after = Pt(0)
+
+        # 创建问题样式
+        question_style = self.doc.styles.add_style('Question_Style', WD_STYLE_TYPE.PARAGRAPH)
+        question_style.font.name = '黑体'
+        question_style._element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
+        question_style.font.size = Pt(14)  # 调整为14磅
+        question_style.font.bold = True
+        question_style.paragraph_format.space_before = Pt(12)  # 减小段前距
+        question_style.paragraph_format.space_after = Pt(6)
+        question_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
+        question_style.paragraph_format.left_indent = Pt(0)  # 移除左缩进
+
+        # 创建回答样式
+        answer_style = self.doc.styles.add_style('Answer_Style', WD_STYLE_TYPE.PARAGRAPH)
+        answer_style.font.name = '仿宋'
+        answer_style._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
+        answer_style.font.size = Pt(12)  # 调整为12磅
+        answer_style.paragraph_format.space_before = Pt(6)
+        answer_style.paragraph_format.space_after = Pt(12)
+        answer_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
+        answer_style.paragraph_format.left_indent = Pt(0)  # 移除左缩进
+
+        # 创建标题样式
+        title_style = self.doc.styles.add_style('Title_Custom', WD_STYLE_TYPE.PARAGRAPH)
+        title_style.font.name = '黑体'  # 改用黑体
+        title_style._element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
+        title_style.font.size = Pt(22)  # 调整为22磅
+        title_style.font.bold = True
+        title_style.paragraph_format.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
+        title_style.paragraph_format.space_before = Pt(0)
+        title_style.paragraph_format.space_after = Pt(24)
+        title_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
+
+        # 添加参考文献样式
+        ref_style = self.doc.styles.add_style('Reference_Style', WD_STYLE_TYPE.PARAGRAPH)
+        ref_style.font.name = '宋体'
+        ref_style._element.rPr.rFonts.set(qn('w:eastAsia'), '宋体')
+        ref_style.font.size = Pt(10.5)  # 参考文献使用小号字体
+        ref_style.paragraph_format.space_before = Pt(3)
+        ref_style.paragraph_format.space_after = Pt(3)
+        ref_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.SINGLE
+        ref_style.paragraph_format.left_indent = Pt(21)
+        ref_style.paragraph_format.first_line_indent = Pt(-21)
+
+        # 添加参考文献标题样式
+        ref_title_style = self.doc.styles.add_style('Reference_Title_Style', WD_STYLE_TYPE.PARAGRAPH)
+        ref_title_style.font.name = '黑体'
+        ref_title_style._element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
+        ref_title_style.font.size = Pt(16)
+        ref_title_style.font.bold = True
+        ref_title_style.paragraph_format.space_before = Pt(24)
+        ref_title_style.paragraph_format.space_after = Pt(12)
+        ref_title_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
+
+    def create_document(self,  history):
+        """写入聊天历史"""
+        # 添加标题
+        title_para = self.doc.add_paragraph(style='Title_Custom')
+        title_run = title_para.add_run('GPT-Academic 对话记录')
+
+        # 添加日期
+        date_para = self.doc.add_paragraph()
+        date_para.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
+        date_run = date_para.add_run(datetime.now().strftime('%Y年%m月%d日'))
+        date_run.font.name = '仿宋'
+        date_run._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
+        date_run.font.size = Pt(16)
+
+        self.doc.add_paragraph()  # 添加空行
+
+        # 添加对话内容
+        for i in range(0, len(history), 2):
+            question = history[i]
+            answer = convert_markdown_to_word(history[i + 1])
+
+            if question:
+                q_para = self.doc.add_paragraph(style='Question_Style')
+                q_para.add_run(f'问题 {i//2 + 1}：').bold = True
+                q_para.add_run(str(question))
+
+            if answer:
+                a_para = self.doc.add_paragraph(style='Answer_Style')
+                a_para.add_run(f'回答 {i//2 + 1}：').bold = True
+                a_para.add_run(str(answer))
+
+
+        return self.doc
+

crazy_functions/doc_fns/read_fns/docx_reader.py

@@ -0,0 +1,6 @@
+import nltk
+nltk.data.path.append('~/nltk_data')
+nltk.download('averaged_perceptron_tagger', download_dir='~/nltk_data',
+             )
+nltk.download('punkt', download_dir='~/nltk_data',
+               )

crazy_functions/doc_fns/read_fns/excel_reader.py

@@ -0,0 +1,286 @@
+from __future__ import annotations
+
+import pandas as pd
+import numpy as np
+from pathlib import Path
+from typing import Optional, List, Set, Dict, Union, Iterator, Tuple
+from dataclasses import dataclass, field
+import logging
+from concurrent.futures import ThreadPoolExecutor, as_completed
+import chardet
+from functools import lru_cache
+import os
+
+
+@dataclass
+class ExtractorConfig:
+    """提取器配置类"""
+    encoding: str = 'auto'
+    na_filter: bool = True
+    skip_blank_lines: bool = True
+    chunk_size: int = 10000
+    max_workers: int = 4
+    preserve_format: bool = True
+    read_all_sheets: bool = True  # 新增：是否读取所有工作表
+    text_cleanup: Dict[str, bool] = field(default_factory=lambda: {
+        'remove_extra_spaces': True,
+        'normalize_whitespace': False,
+        'remove_special_chars': False,
+        'lowercase': False
+    })
+
+
+class ExcelTextExtractor:
+    """增强的Excel格式文件文本内容提取器"""
+
+    SUPPORTED_EXTENSIONS: Set[str] = {
+        '.xlsx', '.xls', '.csv', '.tsv', '.xlsm', '.xltx', '.xltm', '.ods'
+    }
+
+    def __init__(self, config: Optional[ExtractorConfig] = None):
+        self.config = config or ExtractorConfig()
+        self._setup_logging()
+        self._detect_encoding = lru_cache(maxsize=128)(self._detect_encoding)
+
+    def _setup_logging(self) -> None:
+        """配置日志记录器"""
+        logging.basicConfig(
+            level=logging.INFO,
+            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+        )
+        self.logger = logging.getLogger(__name__)
+        fh = logging.FileHandler('excel_extractor.log')
+        fh.setLevel(logging.ERROR)
+        self.logger.addHandler(fh)
+
+    def _detect_encoding(self, file_path: Path) -> str:
+        if self.config.encoding != 'auto':
+            return self.config.encoding
+
+        try:
+            with open(file_path, 'rb') as f:
+                raw_data = f.read(10000)
+                result = chardet.detect(raw_data)
+                return result['encoding'] or 'utf-8'
+        except Exception as e:
+            self.logger.warning(f"Encoding detection failed: {e}. Using utf-8")
+            return 'utf-8'
+
+    def _validate_file(self, file_path: Union[str, Path]) -> Path:
+        path = Path(file_path).resolve()
+
+        if not path.exists():
+            raise ValueError(f"File not found: {path}")
+
+        if not path.is_file():
+            raise ValueError(f"Not a file: {path}")
+
+        if not os.access(path, os.R_OK):
+            raise PermissionError(f"No read permission: {path}")
+
+        if path.suffix.lower() not in self.SUPPORTED_EXTENSIONS:
+            raise ValueError(
+                f"Unsupported format: {path.suffix}. "
+                f"Supported: {', '.join(sorted(self.SUPPORTED_EXTENSIONS))}"
+            )
+
+        return path
+
+    def _format_value(self, value: Any) -> str:
+        if pd.isna(value) or value is None:
+            return ''
+        if isinstance(value, (int, float)):
+            return str(value)
+        return str(value).strip()
+
+    def _process_chunk(self, chunk: pd.DataFrame, columns: Optional[List[str]] = None, sheet_name: str = '') -> str:
+        """处理数据块，新增sheet_name参数"""
+        try:
+            if columns:
+                chunk = chunk[columns]
+
+            if self.config.preserve_format:
+                formatted_chunk = chunk.applymap(self._format_value)
+                rows = []
+
+                # 添加工作表名称作为标题
+                if sheet_name:
+                    rows.append(f"[Sheet: {sheet_name}]")
+
+                # 添加表头
+                headers = [str(col) for col in formatted_chunk.columns]
+                rows.append('\t'.join(headers))
+
+                # 添加数据行
+                for _, row in formatted_chunk.iterrows():
+                    rows.append('\t'.join(row.values))
+
+                return '\n'.join(rows)
+            else:
+                flat_values = (
+                    chunk.astype(str)
+                    .replace({'nan': '', 'None': '', 'NaN': ''})
+                    .values.flatten()
+                )
+                return ' '.join(v for v in flat_values if v)
+
+        except Exception as e:
+            self.logger.error(f"Error processing chunk: {e}")
+            raise
+
+    def _read_file(self, file_path: Path) -> Union[pd.DataFrame, Iterator[pd.DataFrame], Dict[str, pd.DataFrame]]:
+        """读取文件，支持多工作表"""
+        try:
+            encoding = self._detect_encoding(file_path)
+
+            if file_path.suffix.lower() in {'.csv', '.tsv'}:
+                sep = '\t' if file_path.suffix.lower() == '.tsv' else ','
+
+                # 对大文件使用分块读取
+                if file_path.stat().st_size > self.config.chunk_size * 1024:
+                    return pd.read_csv(
+                        file_path,
+                        encoding=encoding,
+                        na_filter=self.config.na_filter,
+                        skip_blank_lines=self.config.skip_blank_lines,
+                        sep=sep,
+                        chunksize=self.config.chunk_size,
+                        on_bad_lines='warn'
+                    )
+                else:
+                    return pd.read_csv(
+                        file_path,
+                        encoding=encoding,
+                        na_filter=self.config.na_filter,
+                        skip_blank_lines=self.config.skip_blank_lines,
+                        sep=sep
+                    )
+            else:
+                # Excel文件处理，支持多工作表
+                if self.config.read_all_sheets:
+                    # 读取所有工作表
+                    return pd.read_excel(
+                        file_path,
+                        na_filter=self.config.na_filter,
+                        keep_default_na=self.config.na_filter,
+                        engine='openpyxl',
+                        sheet_name=None  # None表示读取所有工作表
+                    )
+                else:
+                    # 只读取第一个工作表
+                    return pd.read_excel(
+                        file_path,
+                        na_filter=self.config.na_filter,
+                        keep_default_na=self.config.na_filter,
+                        engine='openpyxl',
+                        sheet_name=0  # 读取第一个工作表
+                    )
+
+        except Exception as e:
+            self.logger.error(f"Error reading file {file_path}: {e}")
+            raise
+
+    def extract_text(
+            self,
+            file_path: Union[str, Path],
+            columns: Optional[List[str]] = None,
+            separator: str = '\n'
+    ) -> str:
+        """提取文本，支持多工作表"""
+        try:
+            path = self._validate_file(file_path)
+            self.logger.info(f"Processing: {path}")
+
+            reader = self._read_file(path)
+            texts = []
+
+            # 处理Excel多工作表
+            if isinstance(reader, dict):
+                for sheet_name, df in reader.items():
+                    sheet_text = self._process_chunk(df, columns, sheet_name)
+                    if sheet_text:
+                        texts.append(sheet_text)
+                return separator.join(texts)
+
+            # 处理单个DataFrame
+            elif isinstance(reader, pd.DataFrame):
+                return self._process_chunk(reader, columns)
+
+            # 处理DataFrame迭代器
+            else:
+                with ThreadPoolExecutor(max_workers=self.config.max_workers) as executor:
+                    futures = {
+                        executor.submit(self._process_chunk, chunk, columns): i
+                        for i, chunk in enumerate(reader)
+                    }
+
+                    chunk_texts = []
+                    for future in as_completed(futures):
+                        try:
+                            text = future.result()
+                            if text:
+                                chunk_texts.append((futures[future], text))
+                        except Exception as e:
+                            self.logger.error(f"Error in chunk {futures[future]}: {e}")
+
+                    # 按块的顺序排序
+                    chunk_texts.sort(key=lambda x: x[0])
+                    texts = [text for _, text in chunk_texts]
+
+                # 合并文本，保留格式
+                if texts and self.config.preserve_format:
+                    result = texts[0]  # 第一块包含表头
+                    if len(texts) > 1:
+                        # 跳过后续块的表头行
+                        for text in texts[1:]:
+                            result += '\n' + '\n'.join(text.split('\n')[1:])
+                    return result
+                else:
+                    return separator.join(texts)
+
+        except Exception as e:
+            self.logger.error(f"Extraction failed: {e}")
+            raise
+
+    @staticmethod
+    def get_supported_formats() -> List[str]:
+        """获取支持的文件格式列表"""
+        return sorted(ExcelTextExtractor.SUPPORTED_EXTENSIONS)
+
+
+def main():
+    """主函数：演示用法"""
+    config = ExtractorConfig(
+        encoding='auto',
+        preserve_format=True,
+        read_all_sheets=True,  # 启用多工作表读取
+        text_cleanup={
+            'remove_extra_spaces': True,
+            'normalize_whitespace': False,
+            'remove_special_chars': False,
+            'lowercase': False
+        }
+    )
+
+    extractor = ExcelTextExtractor(config)
+
+    try:
+        sample_file = 'example.xlsx'
+        if Path(sample_file).exists():
+            text = extractor.extract_text(
+                sample_file,
+                columns=['title', 'content']
+            )
+            print("提取的文本:")
+            print(text)
+        else:
+            print(f"示例文件 {sample_file} 不存在")
+
+        print("\n支持的格式:", extractor.get_supported_formats())
+
+    except Exception as e:
+        print(f"错误: {e}")
+
+
+if __name__ == "__main__":
+    main()

crazy_functions/doc_fns/read_fns/markitdown/markdown_reader.py

@@ -0,0 +1,359 @@
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Optional, Set, Dict, Union, List
+from dataclasses import dataclass, field
+import logging
+import os
+import re
+import subprocess
+import tempfile
+import shutil
+
+@dataclass
+class MarkdownConverterConfig:
+    """PDF 到 Markdown 转换器配置类
+
+    Attributes:
+        extract_images: 是否提取图片
+        extract_tables: 是否尝试保留表格结构
+        extract_code_blocks: 是否识别代码块
+        extract_math: 是否转换数学公式
+        output_dir: 输出目录路径
+        image_dir: 图片保存目录路径
+        paragraph_separator: 段落之间的分隔符
+        text_cleanup: 文本清理选项字典
+        docintel_endpoint: Document Intelligence端点URL (可选)
+        enable_plugins: 是否启用插件
+        llm_client: LLM客户端对象 (例如OpenAI client)
+        llm_model: 要使用的LLM模型名称
+    """
+    extract_images: bool = True
+    extract_tables: bool = True
+    extract_code_blocks: bool = True
+    extract_math: bool = True
+    output_dir: str = ""
+    image_dir: str = "images"
+    paragraph_separator: str = '\n\n'
+    text_cleanup: Dict[str, bool] = field(default_factory=lambda: {
+        'remove_extra_spaces': True,
+        'normalize_whitespace': True,
+        'remove_special_chars': False,
+        'lowercase': False
+    })
+    docintel_endpoint: str = ""
+    enable_plugins: bool = False
+    llm_client: Optional[object] = None
+    llm_model: str = ""
+
+
+class MarkdownConverter:
+    """PDF 到 Markdown 转换器
+
+    使用 markitdown 库实现 PDF 到 Markdown 的转换，支持多种配置选项。
+    """
+
+    SUPPORTED_EXTENSIONS: Set[str] = {
+        '.pdf',
+    }
+
+    def __init__(self, config: Optional[MarkdownConverterConfig] = None):
+        """初始化转换器
+
+        Args:
+            config: 转换器配置对象，如果为None则使用默认配置
+        """
+        self.config = config or MarkdownConverterConfig()
+        self._setup_logging()
+        
+        # 检查是否安装了 markitdown
+        self._check_markitdown_installation()
+
+    def _setup_logging(self) -> None:
+        """配置日志记录器"""
+        logging.basicConfig(
+            level=logging.INFO,
+            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+        )
+        self.logger = logging.getLogger(__name__)
+
+        # 添加文件处理器
+        fh = logging.FileHandler('markdown_converter.log')
+        fh.setLevel(logging.ERROR)
+        self.logger.addHandler(fh)
+    
+    def _check_markitdown_installation(self) -> None:
+        """检查是否安装了 markitdown"""
+        try:
+            # 尝试导入 markitdown 库
+            from markitdown import MarkItDown
+            self.logger.info("markitdown 库已安装")
+        except ImportError:
+            self.logger.warning("markitdown 库未安装，尝试安装...")
+            try:
+                subprocess.check_call(["pip", "install", "markitdown"])
+                self.logger.info("markitdown 库安装成功")
+                from markitdown import MarkItDown
+            except (subprocess.SubprocessError, ImportError):
+                self.logger.error("无法安装 markitdown 库，请手动安装")
+                self.markitdown_available = False
+                return
+        
+        self.markitdown_available = True
+
+    def _validate_file(self, file_path: Union[str, Path], max_size_mb: int = 100) -> Path:
+        """验证文件
+
+        Args:
+            file_path: 文件路径
+            max_size_mb: 允许的最大文件大小(MB)
+
+        Returns:
+            Path: 验证后的Path对象
+
+        Raises:
+            ValueError: 文件不存在、格式不支持或大小超限
+            PermissionError: 没有读取权限
+        """
+        path = Path(file_path).resolve()
+
+        if not path.exists():
+            raise ValueError(f"文件不存在: {path}")
+
+        if not path.is_file():
+            raise ValueError(f"不是一个文件: {path}")
+
+        if not os.access(path, os.R_OK):
+            raise PermissionError(f"没有读取权限: {path}")
+
+        file_size_mb = path.stat().st_size / (1024 * 1024)
+        if file_size_mb > max_size_mb:
+            raise ValueError(
+                f"文件大小 ({file_size_mb:.1f}MB) 超过限制 {max_size_mb}MB"
+            )
+
+        if path.suffix.lower() not in self.SUPPORTED_EXTENSIONS:
+            raise ValueError(
+                f"不支持的格式: {path.suffix}. "
+                f"支持的格式: {', '.join(sorted(self.SUPPORTED_EXTENSIONS))}"
+            )
+
+        return path
+
+    def _cleanup_text(self, text: str) -> str:
+        """清理文本
+
+        Args:
+            text: 原始文本
+
+        Returns:
+            str: 清理后的文本
+        """
+        if self.config.text_cleanup['remove_extra_spaces']:
+            text = ' '.join(text.split())
+
+        if self.config.text_cleanup['normalize_whitespace']:
+            text = text.replace('\t', ' ').replace('\r', '\n')
+
+        if self.config.text_cleanup['lowercase']:
+            text = text.lower()
+
+        return text.strip()
+
+    @staticmethod
+    def get_supported_formats() -> List[str]:
+        """获取支持的文件格式列表"""
+        return sorted(MarkdownConverter.SUPPORTED_EXTENSIONS)
+
+    def convert_to_markdown(
+            self,
+            file_path: Union[str, Path],
+            output_path: Optional[Union[str, Path]] = None
+    ) -> str:
+        """将 PDF 转换为 Markdown
+
+        Args:
+            file_path: PDF 文件路径
+            output_path: 输出 Markdown 文件路径，如果为 None 则返回内容而不保存
+
+        Returns:
+            str: 转换后的 Markdown 内容
+
+        Raises:
+            Exception: 转换过程中的错误
+        """
+        try:
+            path = self._validate_file(file_path)
+            self.logger.info(f"处理: {path}")
+
+            if not self.markitdown_available:
+                raise ImportError("markitdown 库未安装，无法进行转换")
+
+            # 导入 markitdown 库
+            from markitdown import MarkItDown
+
+            # 准备输出目录
+            if output_path:
+                output_path = Path(output_path)
+                output_dir = output_path.parent
+                output_dir.mkdir(parents=True, exist_ok=True)
+            else:
+                # 创建临时目录作为输出目录
+                temp_dir = tempfile.mkdtemp()
+                output_dir = Path(temp_dir)
+                output_path = output_dir / f"{path.stem}.md"
+
+            # 图片目录
+            image_dir = output_dir / self.config.image_dir
+            image_dir.mkdir(parents=True, exist_ok=True)
+
+            # 创建 MarkItDown 实例并进行转换
+            if self.config.docintel_endpoint:
+                md = MarkItDown(docintel_endpoint=self.config.docintel_endpoint)
+            elif self.config.llm_client and self.config.llm_model:
+                md = MarkItDown(
+                    enable_plugins=self.config.enable_plugins,
+                    llm_client=self.config.llm_client,
+                    llm_model=self.config.llm_model
+                )
+            else:
+                md = MarkItDown(enable_plugins=self.config.enable_plugins)
+            
+            # 执行转换
+            result = md.convert(str(path))
+            markdown_content = result.text_content
+            
+            # 清理文本
+            markdown_content = self._cleanup_text(markdown_content)
+            
+            # 如果需要保存到文件
+            if output_path:
+                with open(output_path, 'w', encoding='utf-8') as f:
+                    f.write(markdown_content)
+                self.logger.info(f"转换成功，输出到: {output_path}")
+            
+            return markdown_content
+
+        except Exception as e:
+            self.logger.error(f"转换失败: {e}")
+            raise
+        finally:
+            # 如果使用了临时目录且没有指定输出路径，则清理临时目录
+            if 'temp_dir' in locals() and not output_path:
+                shutil.rmtree(temp_dir, ignore_errors=True)
+
+    def convert_to_markdown_and_save(
+            self,
+            file_path: Union[str, Path],
+            output_path: Union[str, Path]
+    ) -> Path:
+        """将 PDF 转换为 Markdown 并保存到指定路径
+
+        Args:
+            file_path: PDF 文件路径
+            output_path: 输出 Markdown 文件路径
+
+        Returns:
+            Path: 输出文件的 Path 对象
+
+        Raises:
+            Exception: 转换过程中的错误
+        """
+        self.convert_to_markdown(file_path, output_path)
+        return Path(output_path)
+    
+    def batch_convert(
+            self, 
+            file_paths: List[Union[str, Path]], 
+            output_dir: Union[str, Path]
+    ) -> List[Path]:
+        """批量转换多个 PDF 文件为 Markdown
+
+        Args:
+            file_paths: PDF 文件路径列表
+            output_dir: 输出目录路径
+
+        Returns:
+            List[Path]: 输出文件路径列表
+
+        Raises:
+            Exception: 转换过程中的错误
+        """
+        output_dir = Path(output_dir)
+        output_dir.mkdir(parents=True, exist_ok=True)
+        
+        output_paths = []
+        for file_path in file_paths:
+            path = Path(file_path)
+            output_path = output_dir / f"{path.stem}.md"
+            
+            try:
+                self.convert_to_markdown(file_path, output_path)
+                output_paths.append(output_path)
+                self.logger.info(f"成功转换: {path} -> {output_path}")
+            except Exception as e:
+                self.logger.error(f"转换失败 {path}: {e}")
+        
+        return output_paths
+
+
+def main():
+    """主函数：演示用法"""
+    # 配置
+    config = MarkdownConverterConfig(
+        extract_images=True,
+        extract_tables=True,
+        extract_code_blocks=True,
+        extract_math=True,
+        enable_plugins=False,
+        text_cleanup={
+            'remove_extra_spaces': True,
+            'normalize_whitespace': True,
+            'remove_special_chars': False,
+            'lowercase': False
+        }
+    )
+
+    # 创建转换器
+    converter = MarkdownConverter(config)
+
+    # 使用示例
+    try:
+        # 替换为实际的文件路径
+        sample_file = './crazy_functions/doc_fns/read_fns/paper/2501.12599v1.pdf'
+        if Path(sample_file).exists():
+            # 转换为 Markdown 并打印内容
+            markdown_content = converter.convert_to_markdown(sample_file)
+            print("转换后的 Markdown 内容:")
+            print(markdown_content[:500] + "...")  # 只打印前500个字符
+            
+            # 转换并保存到文件
+            output_file = f"./output_{Path(sample_file).stem}.md"
+            output_path = converter.convert_to_markdown_and_save(sample_file, output_file)
+            print(f"\n已保存到: {output_path}")
+            
+            # 使用LLM增强的示例 (需要添加相应的导入和配置)
+            # try:
+            #     from openai import OpenAI
+            #     client = OpenAI()
+            #     llm_config = MarkdownConverterConfig(
+            #         llm_client=client,
+            #         llm_model="gpt-4o"
+            #     )
+            #     llm_converter = MarkdownConverter(llm_config)
+            #     llm_result = llm_converter.convert_to_markdown("example.jpg")
+            #     print("LLM增强的结果:")
+            #     print(llm_result[:500] + "...")
+            # except ImportError:
+            #     print("未安装OpenAI库，跳过LLM示例")
+        else:
+            print(f"示例文件 {sample_file} 不存在")
+
+        print("\n支持的格式:", converter.get_supported_formats())
+
+    except Exception as e:
+        print(f"错误: {e}")
+
+
+if __name__ == "__main__":
+    main() 

crazy_functions/doc_fns/read_fns/unstructured_all/paper_metadata_extractor.py

@@ -0,0 +1,493 @@
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Optional, Set, Dict, Union, List
+from dataclasses import dataclass, field
+import logging
+import os
+import re
+
+from unstructured.partition.auto import partition
+from unstructured.documents.elements import (
+    Text, Title, NarrativeText, ListItem, Table,
+    Footer, Header, PageBreak, Image, Address
+)
+
+
+@dataclass
+class PaperMetadata:
+    """论文元数据类"""
+    title: str = ""
+    authors: List[str] = field(default_factory=list)
+    affiliations: List[str] = field(default_factory=list)
+    journal: str = ""
+    volume: str = ""
+    issue: str = ""
+    year: str = ""
+    doi: str = ""
+    date: str = ""
+    publisher: str = ""
+    conference: str = ""
+    abstract: str = ""
+    keywords: List[str] = field(default_factory=list)
+
+
+@dataclass
+class ExtractorConfig:
+    """元数据提取器配置类"""
+    paragraph_separator: str = '\n\n'
+    text_cleanup: Dict[str, bool] = field(default_factory=lambda: {
+        'remove_extra_spaces': True,
+        'normalize_whitespace': True,
+        'remove_special_chars': False,
+        'lowercase': False
+    })
+
+
+class PaperMetadataExtractor:
+    """论文元数据提取器
+    
+    使用unstructured库从多种文档格式中提取论文的标题、作者、摘要等元数据信息。
+    """
+
+    SUPPORTED_EXTENSIONS: Set[str] = {
+        '.pdf', '.docx', '.doc', '.txt', '.ppt', '.pptx',
+        '.xlsx', '.xls', '.md', '.org', '.odt', '.rst',
+        '.rtf', '.epub', '.html', '.xml', '.json'
+    }
+
+    # 定义论文各部分的关键词模式
+    SECTION_PATTERNS = {
+        'abstract': r'\b(摘要|abstract|summary|概要|résumé|zusammenfassung|аннотация)\b',
+        'keywords': r'\b(关键词|keywords|key\s+words|关键字|mots[- ]clés|schlüsselwörter|ключевые слова)\b',
+    }
+
+    def __init__(self, config: Optional[ExtractorConfig] = None):
+        """初始化提取器
+        
+        Args:
+            config: 提取器配置对象，如果为None则使用默认配置
+        """
+        self.config = config or ExtractorConfig()
+        self._setup_logging()
+
+    def _setup_logging(self) -> None:
+        """配置日志记录器"""
+        logging.basicConfig(
+            level=logging.INFO,
+            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+        )
+        self.logger = logging.getLogger(__name__)
+
+        # 添加文件处理器
+        fh = logging.FileHandler('paper_metadata_extractor.log')
+        fh.setLevel(logging.ERROR)
+        self.logger.addHandler(fh)
+
+    def _validate_file(self, file_path: Union[str, Path], max_size_mb: int = 100) -> Path:
+        """验证文件
+        
+        Args:
+            file_path: 文件路径
+            max_size_mb: 允许的最大文件大小(MB)
+            
+        Returns:
+            Path: 验证后的Path对象
+            
+        Raises:
+            ValueError: 文件不存在、格式不支持或大小超限
+            PermissionError: 没有读取权限
+        """
+        path = Path(file_path).resolve()
+
+        if not path.exists():
+            raise ValueError(f"文件不存在: {path}")
+
+        if not path.is_file():
+            raise ValueError(f"不是文件: {path}")
+
+        if not os.access(path, os.R_OK):
+            raise PermissionError(f"没有读取权限: {path}")
+
+        file_size_mb = path.stat().st_size / (1024 * 1024)
+        if file_size_mb > max_size_mb:
+            raise ValueError(
+                f"文件大小 ({file_size_mb:.1f}MB) 超过限制 {max_size_mb}MB"
+            )
+
+        if path.suffix.lower() not in self.SUPPORTED_EXTENSIONS:
+            raise ValueError(
+                f"不支持的文件格式: {path.suffix}. "
+                f"支持的格式: {', '.join(sorted(self.SUPPORTED_EXTENSIONS))}"
+            )
+
+        return path
+
+    def _cleanup_text(self, text: str) -> str:
+        """清理文本
+        
+        Args:
+            text: 原始文本
+            
+        Returns:
+            str: 清理后的文本
+        """
+        if self.config.text_cleanup['remove_extra_spaces']:
+            text = ' '.join(text.split())
+
+        if self.config.text_cleanup['normalize_whitespace']:
+            text = text.replace('\t', ' ').replace('\r', '\n')
+
+        if self.config.text_cleanup['lowercase']:
+            text = text.lower()
+
+        return text.strip()
+
+    @staticmethod
+    def get_supported_formats() -> List[str]:
+        """获取支持的文件格式列表"""
+        return sorted(PaperMetadataExtractor.SUPPORTED_EXTENSIONS)
+
+    def extract_metadata(self, file_path: Union[str, Path], strategy: str = "fast") -> PaperMetadata:
+        """提取论文元数据
+        
+        Args:
+            file_path: 文件路径
+            strategy: 提取策略 ("fast" 或 "accurate")
+            
+        Returns:
+            PaperMetadata: 提取的论文元数据
+            
+        Raises:
+            Exception: 提取过程中的错误
+        """
+        try:
+            path = self._validate_file(file_path)
+            self.logger.info(f"正在处理: {path}")
+
+            # 使用unstructured库分解文档
+            elements = partition(
+                str(path),
+                strategy=strategy,
+                include_metadata=True,
+                nlp=False,
+            )
+
+            # 提取元数据
+            metadata = PaperMetadata()
+            
+            # 提取标题和作者
+            self._extract_title_and_authors(elements, metadata)
+            
+            # 提取摘要和关键词
+            self._extract_abstract_and_keywords(elements, metadata)
+            
+            # 提取其他元数据
+            self._extract_additional_metadata(elements, metadata)
+            
+            return metadata
+
+        except Exception as e:
+            self.logger.error(f"元数据提取失败: {e}")
+            raise
+
+    def _extract_title_and_authors(self, elements, metadata: PaperMetadata) -> None:
+        """从文档中提取标题和作者信息 - 改进版"""
+        # 收集所有潜在的标题候选
+        title_candidates = []
+        all_text = []
+        raw_text = []
+        
+        # 首先收集文档前30个元素的文本，用于辅助判断
+        for i, element in enumerate(elements[:30]):
+            if isinstance(element, (Text, Title, NarrativeText)):
+                text = str(element).strip()
+                if text:
+                    all_text.append(text)
+                    raw_text.append(text)
+        
+        # 打印出原始文本，用于调试
+        print("原始文本前10行:")
+        for i, text in enumerate(raw_text[:10]):
+            print(f"{i}: {text}")
+        
+        # 1. 尝试查找连续的标题片段并合并它们
+        i = 0
+        while i < len(all_text) - 1:
+            current = all_text[i]
+            next_text = all_text[i + 1]
+            
+            # 检查是否存在标题分割情况：一行以冒号结尾，下一行像是标题的延续
+            if current.endswith(':') and len(current) < 50 and len(next_text) > 5 and next_text[0].isupper():
+                # 合并这两行文本
+                combined_title = f"{current} {next_text}"
+                # 查找合并前的文本并替换
+                all_text[i] = combined_title
+                all_text.pop(i + 1)
+                # 给合并后的标题很高的分数
+                title_candidates.append((combined_title, 15, i))
+            else:
+                i += 1
+        
+        # 2. 首先尝试从标题元素中查找
+        for i, element in enumerate(elements[:15]):  # 只检查前15个元素
+            if isinstance(element, Title):
+                title_text = str(element).strip()
+                # 排除常见的非标题内容
+                if title_text.lower() not in ['abstract', '摘要', 'introduction', '引言']:
+                    # 计算标题分数（越高越可能是真正的标题）
+                    score = self._evaluate_title_candidate(title_text, i, element)
+                    title_candidates.append((title_text, score, i))
+        
+        # 3. 特别处理常见的论文标题格式
+        for i, text in enumerate(all_text[:15]):
+            # 特别检查"KIMI K1.5:"类型的前缀标题
+            if re.match(r'^[A-Z][A-Z0-9\s\.]+(\s+K\d+(\.\d+)?)?:', text):
+                score = 12  # 给予很高的分数
+                title_candidates.append((text, score, i))
+                
+                # 如果下一行也是全大写，很可能是标题的延续
+                if i+1 < len(all_text) and all_text[i+1].isupper() and len(all_text[i+1]) > 10:
+                    combined_title = f"{text} {all_text[i+1]}"
+                    title_candidates.append((combined_title, 15, i))  # 给合并标题更高分数
+            
+            # 匹配全大写的标题行
+            elif text.isupper() and len(text) > 10 and len(text) < 100:
+                score = 10 - i * 0.5  # 越靠前越可能是标题
+                title_candidates.append((text, score, i))
+        
+        # 对标题候选按分数排序并选取最佳候选
+        if title_candidates:
+            title_candidates.sort(key=lambda x: x[1], reverse=True)
+            metadata.title = title_candidates[0][0]
+            title_position = title_candidates[0][2]
+            print(f"所有标题候选: {title_candidates[:3]}")
+        else:
+            # 如果没有找到合适的标题，使用一个备选策略
+            for text in all_text[:10]:
+                if text.isupper() and len(text) > 10 and len(text) < 200:  # 大写且适当长度的文本
+                    metadata.title = text
+                    break
+            title_position = 0
+        
+        # 提取作者信息 - 改进后的作者提取逻辑
+        author_candidates = []
+        
+        # 1. 特别处理"TECHNICAL REPORT OF"之后的行，通常是作者或团队
+        for i, text in enumerate(all_text):
+            if "TECHNICAL REPORT" in text.upper() and i+1 < len(all_text):
+                team_text = all_text[i+1].strip()
+                if re.search(r'\b(team|group|lab)\b', team_text, re.IGNORECASE):
+                    author_candidates.append((team_text, 15))
+        
+        # 2. 查找包含Team的文本
+        for text in all_text[:20]:
+            if "Team" in text and len(text) < 30:
+                # 这很可能是团队名
+                author_candidates.append((text, 12))
+        
+        # 添加作者到元数据
+        if author_candidates:
+            # 按分数排序
+            author_candidates.sort(key=lambda x: x[1], reverse=True)
+            
+            # 去重
+            seen_authors = set()
+            for author, _ in author_candidates:
+                if author.lower() not in seen_authors and not author.isdigit():
+                    seen_authors.add(author.lower())
+                    metadata.authors.append(author)
+        
+        # 如果没有找到作者，尝试查找隶属机构信息中的团队名称
+        if not metadata.authors:
+            for text in all_text[:20]:
+                if re.search(r'\b(team|group|lab|laboratory|研究组|团队)\b', text, re.IGNORECASE):
+                    if len(text) < 50:  # 避免太长的文本
+                        metadata.authors.append(text.strip())
+                        break
+        
+        # 提取隶属机构信息
+        for i, element in enumerate(elements[:30]):
+            element_text = str(element).strip()
+            if re.search(r'(university|institute|department|school|laboratory|college|center|centre|\d{5,}|^[a-zA-Z]+@|学院|大学|研究所|研究院)', element_text, re.IGNORECASE):
+                # 可能是隶属机构
+                if element_text not in metadata.affiliations and len(element_text) > 10:
+                    metadata.affiliations.append(element_text)
+
+    def _evaluate_title_candidate(self, text, position, element):
+        """评估标题候选项的可能性分数"""
+        score = 0
+        
+        # 位置因素：越靠前越可能是标题
+        score += max(0, 10 - position) * 0.5
+        
+        # 长度因素：标题通常不会太短也不会太长
+        if 10 <= len(text) <= 150:
+            score += 3
+        elif len(text) < 10:
+            score -= 2
+        elif len(text) > 150:
+            score -= 3
+        
+        # 格式因素
+        if text.isupper():  # 全大写可能是标题
+            score += 2
+        if re.match(r'^[A-Z]', text):  # 首字母大写
+            score += 1
+        if ':' in text:  # 标题常包含冒号
+            score += 1.5
+        
+        # 内容因素
+        if re.search(r'\b(scaling|learning|model|approach|method|system|framework|analysis)\b', text.lower()):
+            score += 2  # 包含常见的学术论文关键词
+            
+        # 避免误判
+        if re.match(r'^\d+$', text):  # 纯数字
+            score -= 10
+        if re.search(r'^(http|www|doi)', text.lower()):  # URL或DOI
+            score -= 5
+        if len(text.split()) <= 2 and len(text) < 15:  # 太短的短语
+            score -= 3
+            
+        # 元数据因素(如果有)
+        if hasattr(element, 'metadata') and element.metadata:
+            # 修复：正确处理ElementMetadata对象
+            try:
+                # 尝试通过getattr安全地获取属性
+                font_size = getattr(element.metadata, 'font_size', None)
+                if font_size is not None and font_size > 14:  # 假设标准字体大小是12
+                    score += 3
+                    
+                font_weight = getattr(element.metadata, 'font_weight', None)
+                if font_weight == 'bold':
+                    score += 2  # 粗体加分
+            except (AttributeError, TypeError):
+                # 如果metadata的访问方式不正确，尝试其他可能的访问方式
+                try:
+                    metadata_dict = element.metadata.__dict__ if hasattr(element.metadata, '__dict__') else {}
+                    if 'font_size' in metadata_dict and metadata_dict['font_size'] > 14:
+                        score += 3
+                    if 'font_weight' in metadata_dict and metadata_dict['font_weight'] == 'bold':
+                        score += 2
+                except Exception:
+                    # 如果所有尝试都失败，忽略元数据处理
+                    pass
+        
+        return score
+
+    def _extract_abstract_and_keywords(self, elements, metadata: PaperMetadata) -> None:
+        """从文档中提取摘要和关键词"""
+        abstract_found = False
+        keywords_found = False
+        abstract_text = []
+        
+        for i, element in enumerate(elements):
+            element_text = str(element).strip().lower()
+            
+            # 寻找摘要部分
+            if not abstract_found and (
+                isinstance(element, Title) and 
+                re.search(self.SECTION_PATTERNS['abstract'], element_text, re.IGNORECASE)
+            ):
+                abstract_found = True
+                continue
+            
+            # 如果找到摘要部分，收集内容直到遇到关键词部分或新章节
+            if abstract_found and not keywords_found:
+                # 检查是否遇到关键词部分或新章节
+                if (
+                    isinstance(element, Title) or 
+                    re.search(self.SECTION_PATTERNS['keywords'], element_text, re.IGNORECASE) or
+                    re.match(r'\b(introduction|引言|method|方法)\b', element_text, re.IGNORECASE)
+                ):
+                    keywords_found = re.search(self.SECTION_PATTERNS['keywords'], element_text, re.IGNORECASE)
+                    abstract_found = False  # 停止收集摘要
+                else:
+                    # 收集摘要文本
+                    if isinstance(element, (Text, NarrativeText)) and element_text:
+                        abstract_text.append(element_text)
+            
+            # 如果找到关键词部分，提取关键词
+            if keywords_found and not abstract_found and not metadata.keywords:
+                if isinstance(element, (Text, NarrativeText)):
+                    # 清除可能的"关键词:"/"Keywords:"前缀
+                    cleaned_text = re.sub(r'^\s*(关键词|keywords|key\s+words)\s*[：:]\s*', '', element_text, flags=re.IGNORECASE)
+                    
+                    # 尝试按不同分隔符分割
+                    for separator in [';', '；', ',', '，']:
+                        if separator in cleaned_text:
+                            metadata.keywords = [k.strip() for k in cleaned_text.split(separator) if k.strip()]
+                            break
+                    
+                    # 如果未能分割，将整个文本作为一个关键词
+                    if not metadata.keywords and cleaned_text:
+                        metadata.keywords = [cleaned_text]
+                    
+                    keywords_found = False  # 已提取关键词，停止处理
+        
+        # 设置摘要文本
+        if abstract_text:
+            metadata.abstract = self.config.paragraph_separator.join(abstract_text)
+
+    def _extract_additional_metadata(self, elements, metadata: PaperMetadata) -> None:
+        """提取其他元数据信息"""
+        for element in elements[:30]:  # 只检查文档前部分
+            element_text = str(element).strip()
+            
+            # 尝试匹配DOI
+            doi_match = re.search(r'(doi|DOI):\s*(10\.\d{4,}\/[a-zA-Z0-9.-]+)', element_text)
+            if doi_match and not metadata.doi:
+                metadata.doi = doi_match.group(2)
+            
+            # 尝试匹配日期
+            date_match = re.search(r'(published|received|accepted|submitted):\s*(\d{1,2}\s+[a-zA-Z]+\s+\d{4}|\d{4}[-/]\d{1,2}[-/]\d{1,2})', element_text, re.IGNORECASE)
+            if date_match and not metadata.date:
+                metadata.date = date_match.group(2)
+                
+            # 尝试匹配年份
+            year_match = re.search(r'\b(19|20)\d{2}\b', element_text)
+            if year_match and not metadata.year:
+                metadata.year = year_match.group(0)
+                
+            # 尝试匹配期刊/会议名称
+            journal_match = re.search(r'(journal|conference):\s*([^,;.]+)', element_text, re.IGNORECASE)
+            if journal_match:
+                if "journal" in journal_match.group(1).lower() and not metadata.journal:
+                    metadata.journal = journal_match.group(2).strip()
+                elif not metadata.conference:
+                    metadata.conference = journal_match.group(2).strip()
+
+
+def main():
+    """主函数：演示用法"""
+    # 创建提取器
+    extractor = PaperMetadataExtractor()
+
+    # 使用示例
+    try:
+        # 替换为实际的文件路径
+        sample_file = '/Users/boyin.liu/Documents/示例文档/论文/3.pdf'
+        if Path(sample_file).exists():
+            metadata = extractor.extract_metadata(sample_file)
+            print("提取的元数据:")
+            print(f"标题: {metadata.title}")
+            print(f"作者: {', '.join(metadata.authors)}")
+            print(f"机构: {', '.join(metadata.affiliations)}")
+            print(f"摘要: {metadata.abstract[:200]}...")
+            print(f"关键词: {', '.join(metadata.keywords)}")
+            print(f"DOI: {metadata.doi}")
+            print(f"日期: {metadata.date}")
+            print(f"年份: {metadata.year}")
+            print(f"期刊: {metadata.journal}")
+            print(f"会议: {metadata.conference}")
+        else:
+            print(f"示例文件 {sample_file} 不存在")
+
+        print("\n支持的格式:", extractor.get_supported_formats())
+
+    except Exception as e:
+        print(f"错误: {e}")
+
+
+if __name__ == "__main__":
+    main() 

crazy_functions/doc_fns/read_fns/unstructured_all/unstructured_md.py

@@ -0,0 +1,86 @@
+from pathlib import Path
+from crazy_functions.doc_fns.read_fns.unstructured_all.paper_structure_extractor import PaperStructureExtractor
+
+def extract_and_save_as_markdown(paper_path, output_path=None):
+    """
+    提取论文结构并保存为Markdown格式
+    
+    参数:
+        paper_path: 论文文件路径
+        output_path: 输出的Markdown文件路径，如果不指定，将使用与输入相同的文件名但扩展名为.md
+    
+    返回:
+        保存的Markdown文件路径
+    """
+    # 创建提取器
+    extractor = PaperStructureExtractor()
+    
+    # 解析文件路径
+    paper_path = Path(paper_path)
+    
+    # 如果未指定输出路径，使用相同文件名但扩展名为.md
+    if output_path is None:
+        output_path = paper_path.with_suffix('.md')
+    else:
+        output_path = Path(output_path)
+    
+    # 确保输出目录存在
+    output_path.parent.mkdir(parents=True, exist_ok=True)
+    
+    print(f"正在处理论文: {paper_path}")
+    
+    try:
+        # 提取论文结构
+        paper = extractor.extract_paper_structure(paper_path)
+        
+        # 生成Markdown内容
+        markdown_content = extractor.generate_markdown(paper)
+        
+        # 保存到文件
+        with open(output_path, 'w', encoding='utf-8') as f:
+            f.write(markdown_content)
+        
+        print(f"已成功保存Markdown文件: {output_path}")
+        
+        # 打印摘要信息
+        print("\n论文摘要信息:")
+        print(f"标题: {paper.metadata.title}")
+        print(f"作者: {', '.join(paper.metadata.authors)}")
+        print(f"关键词: {', '.join(paper.keywords)}")
+        print(f"章节数: {len(paper.sections)}")
+        print(f"图表数: {len(paper.figures)}")
+        print(f"表格数: {len(paper.tables)}")
+        print(f"公式数: {len(paper.formulas)}")
+        print(f"参考文献数: {len(paper.references)}")
+        
+        return output_path
+    
+    except Exception as e:
+        print(f"处理论文时出错: {e}")
+        import traceback
+        traceback.print_exc()
+        return None
+
+# 使用示例
+if __name__ == "__main__":
+    # 替换为实际的论文文件路径
+    sample_paper = "crazy_functions/doc_fns/read_fns/paper/2501.12599v1.pdf"
+    
+    # 可以指定输出路径，也可以使用默认路径
+    # output_file = "/path/to/output/paper_structure.md"
+    # extract_and_save_as_markdown(sample_paper, output_file)
+    
+    # 使用默认输出路径（与输入文件同名但扩展名为.md）
+    extract_and_save_as_markdown(sample_paper)
+    
+    # # 批量处理多个论文的示例
+    # paper_dir = Path("/path/to/papers/folder")
+    # output_dir = Path("/path/to/output/folder")
+    #
+    # # 确保输出目录存在
+    # output_dir.mkdir(parents=True, exist_ok=True)
+    #
+    # # 处理目录中的所有PDF文件
+    # for paper_file in paper_dir.glob("*.pdf"):
+    #     output_file = output_dir / f"{paper_file.stem}.md"
+    #     extract_and_save_as_markdown(paper_file, output_file)

crazy_functions/doc_fns/read_fns/unstructured_all/unstructured_reader.py

@@ -0,0 +1,275 @@
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Optional, Set, Dict, Union, List
+from dataclasses import dataclass, field
+import logging
+import os
+
+from unstructured.partition.auto import partition
+from unstructured.documents.elements import (
+    Text, Title, NarrativeText, ListItem, Table,
+    Footer, Header, PageBreak, Image, Address
+)
+
+
+@dataclass
+class TextExtractorConfig:
+    """通用文档提取器配置类
+
+    Attributes:
+        extract_headers_footers: 是否提取页眉页脚
+        extract_tables: 是否提取表格内容
+        extract_lists: 是否提取列表内容
+        extract_titles: 是否提取标题
+        paragraph_separator: 段落之间的分隔符
+        text_cleanup: 文本清理选项字典
+    """
+    extract_headers_footers: bool = False
+    extract_tables: bool = True
+    extract_lists: bool = True
+    extract_titles: bool = True
+    paragraph_separator: str = '\n\n'
+    text_cleanup: Dict[str, bool] = field(default_factory=lambda: {
+        'remove_extra_spaces': True,
+        'normalize_whitespace': True,
+        'remove_special_chars': False,
+        'lowercase': False
+    })
+
+
+class UnstructuredTextExtractor:
+    """通用文档文本内容提取器
+
+    使用 unstructured 库支持多种文档格式的文本提取，提供统一的接口和配置选项。
+    """
+
+    SUPPORTED_EXTENSIONS: Set[str] = {
+        # 文档格式
+        '.pdf', '.docx', '.doc', '.txt',
+        # 演示文稿
+        '.ppt', '.pptx',
+        # 电子表格
+        '.xlsx', '.xls', '.csv',
+        # 图片
+        '.png', '.jpg', '.jpeg', '.tiff',
+        # 邮件
+        '.eml', '.msg', '.p7s',
+        # Markdown
+        ".md",
+        # Org Mode
+        ".org",
+        # Open Office
+        ".odt",
+        # reStructured Text
+        ".rst",
+        # Rich Text
+        ".rtf",
+        # TSV
+        ".tsv",
+        # EPUB
+        '.epub',
+        # 其他格式
+        '.html', '.xml',  '.json',
+    }
+
+    def __init__(self, config: Optional[TextExtractorConfig] = None):
+        """初始化提取器
+
+        Args:
+            config: 提取器配置对象，如果为None则使用默认配置
+        """
+        self.config = config or TextExtractorConfig()
+        self._setup_logging()
+
+    def _setup_logging(self) -> None:
+        """配置日志记录器"""
+        logging.basicConfig(
+            level=logging.INFO,
+            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+        )
+        self.logger = logging.getLogger(__name__)
+
+        # 添加文件处理器
+        fh = logging.FileHandler('text_extractor.log')
+        fh.setLevel(logging.ERROR)
+        self.logger.addHandler(fh)
+
+    def _validate_file(self, file_path: Union[str, Path], max_size_mb: int = 100) -> Path:
+        """验证文件
+
+        Args:
+            file_path: 文件路径
+            max_size_mb: 允许的最大文件大小(MB)
+
+        Returns:
+            Path: 验证后的Path对象
+
+        Raises:
+            ValueError: 文件不存在、格式不支持或大小超限
+            PermissionError: 没有读取权限
+        """
+        path = Path(file_path).resolve()
+
+        if not path.exists():
+            raise ValueError(f"File not found: {path}")
+
+        if not path.is_file():
+            raise ValueError(f"Not a file: {path}")
+
+        if not os.access(path, os.R_OK):
+            raise PermissionError(f"No read permission: {path}")
+
+        file_size_mb = path.stat().st_size / (1024 * 1024)
+        if file_size_mb > max_size_mb:
+            raise ValueError(
+                f"File size ({file_size_mb:.1f}MB) exceeds limit of {max_size_mb}MB"
+            )
+
+        if path.suffix.lower() not in self.SUPPORTED_EXTENSIONS:
+            raise ValueError(
+                f"Unsupported format: {path.suffix}. "
+                f"Supported: {', '.join(sorted(self.SUPPORTED_EXTENSIONS))}"
+            )
+
+        return path
+
+    def _cleanup_text(self, text: str) -> str:
+        """清理文本
+
+        Args:
+            text: 原始文本
+
+        Returns:
+            str: 清理后的文本
+        """
+        if self.config.text_cleanup['remove_extra_spaces']:
+            text = ' '.join(text.split())
+
+        if self.config.text_cleanup['normalize_whitespace']:
+            text = text.replace('\t', ' ').replace('\r', '\n')
+
+        if self.config.text_cleanup['lowercase']:
+            text = text.lower()
+
+        return text.strip()
+
+    def _should_extract_element(self, element) -> bool:
+        """判断是否应该提取某个元素
+
+        Args:
+            element: 文档元素
+
+        Returns:
+            bool: 是否应该提取
+        """
+        if isinstance(element, (Text, NarrativeText)):
+            return True
+
+        if isinstance(element, Title) and self.config.extract_titles:
+            return True
+
+        if isinstance(element, ListItem) and self.config.extract_lists:
+            return True
+
+        if isinstance(element, Table) and self.config.extract_tables:
+            return True
+
+        if isinstance(element, (Header, Footer)) and self.config.extract_headers_footers:
+            return True
+
+        return False
+
+    @staticmethod
+    def get_supported_formats() -> List[str]:
+        """获取支持的文件格式列表"""
+        return sorted(UnstructuredTextExtractor.SUPPORTED_EXTENSIONS)
+
+    def extract_text(
+            self,
+            file_path: Union[str, Path],
+            strategy: str = "fast"
+    ) -> str:
+        """提取文本
+
+        Args:
+            file_path: 文件路径
+            strategy: 提取策略 ("fast" 或 "accurate")
+
+        Returns:
+            str: 提取的文本内容
+
+        Raises:
+            Exception: 提取过程中的错误
+        """
+        try:
+            path = self._validate_file(file_path)
+            self.logger.info(f"Processing: {path}")
+
+            # 修改这里：添加 nlp=False 参数来禁用 NLTK
+            elements = partition(
+                str(path),
+                strategy=strategy,
+                include_metadata=True,
+                nlp=True,
+            )
+
+            # 其余代码保持不变
+            text_parts = []
+            for element in elements:
+                if self._should_extract_element(element):
+                    text = str(element)
+                    cleaned_text = self._cleanup_text(text)
+                    if cleaned_text:
+                        if isinstance(element, (Header, Footer)):
+                            prefix = "[Header] " if isinstance(element, Header) else "[Footer] "
+                            text_parts.append(f"{prefix}{cleaned_text}")
+                        else:
+                            text_parts.append(cleaned_text)
+
+            return self.config.paragraph_separator.join(text_parts)
+
+        except Exception as e:
+            self.logger.error(f"Extraction failed: {e}")
+            raise
+
+
+
+def main():
+    """主函数：演示用法"""
+    # 配置
+    config = TextExtractorConfig(
+        extract_headers_footers=True,
+        extract_tables=True,
+        extract_lists=True,
+        extract_titles=True,
+        text_cleanup={
+            'remove_extra_spaces': True,
+            'normalize_whitespace': True,
+            'remove_special_chars': False,
+            'lowercase': False
+        }
+    )
+
+    # 创建提取器
+    extractor = UnstructuredTextExtractor(config)
+
+    # 使用示例
+    try:
+        # 替换为实际的文件路径
+        sample_file = './crazy_functions/doc_fns/read_fns/paper/2501.12599v1.pdf'
+        if Path(sample_file).exists() or True:
+            text = extractor.extract_text(sample_file)
+            print("提取的文本:")
+            print(text)
+        else:
+            print(f"示例文件 {sample_file} 不存在")
+
+        print("\n支持的格式:", extractor.get_supported_formats())
+
+    except Exception as e:
+        print(f"错误: {e}")
+
+
+if __name__ == "__main__":
+    main()

crazy_functions/doc_fns/read_fns/web_reader.py

@@ -0,0 +1,219 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Dict, Optional, Union
+from urllib.parse import urlparse
+import logging
+import trafilatura
+import requests
+from pathlib import Path
+
+
+@dataclass
+class WebExtractorConfig:
+    """网页内容提取器配置类
+
+    Attributes:
+        extract_comments: 是否提取评论
+        extract_tables: 是否提取表格
+        extract_links: 是否保留链接信息
+        paragraph_separator: 段落分隔符
+        timeout: 网络请求超时时间(秒)
+        max_retries: 最大重试次数
+        user_agent: 自定义User-Agent
+        text_cleanup: 文本清理选项
+    """
+    extract_comments: bool = False
+    extract_tables: bool = True
+    extract_links: bool = False
+    paragraph_separator: str = '\n\n'
+    timeout: int = 10
+    max_retries: int = 3
+    user_agent: str = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
+    text_cleanup: Dict[str, bool] = field(default_factory=lambda: {
+        'remove_extra_spaces': True,
+        'normalize_whitespace': True,
+        'remove_special_chars': False,
+        'lowercase': False
+    })
+
+
+class WebTextExtractor:
+    """网页文本内容提取器
+    
+    使用trafilatura库提取网页中的主要文本内容，去除广告、导航等无关内容。
+    """
+
+    def __init__(self, config: Optional[WebExtractorConfig] = None):
+        """初始化提取器
+
+        Args:
+            config: 提取器配置对象，如果为None则使用默认配置
+        """
+        self.config = config or WebExtractorConfig()
+        self._setup_logging()
+
+    def _setup_logging(self) -> None:
+        """配置日志记录器"""
+        logging.basicConfig(
+            level=logging.INFO,
+            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+        )
+        self.logger = logging.getLogger(__name__)
+
+        # 添加文件处理器
+        fh = logging.FileHandler('web_extractor.log')
+        fh.setLevel(logging.ERROR)
+        self.logger.addHandler(fh)
+
+    def _validate_url(self, url: str) -> bool:
+        """验证URL格式是否有效
+
+        Args:
+            url: 网页URL
+
+        Returns:
+            bool: URL是否有效
+        """
+        try:
+            result = urlparse(url)
+            return all([result.scheme, result.netloc])
+        except Exception:
+            return False
+
+    def _download_webpage(self, url: str) -> Optional[str]:
+        """下载网页内容
+
+        Args:
+            url: 网页URL
+
+        Returns:
+            Optional[str]: 网页HTML内容，失败返回None
+
+        Raises:
+            Exception: 下载失败时抛出异常
+        """
+        headers = {'User-Agent': self.config.user_agent}
+        
+        for attempt in range(self.config.max_retries):
+            try:
+                response = requests.get(
+                    url, 
+                    headers=headers,
+                    timeout=self.config.timeout
+                )
+                response.raise_for_status()
+                return response.text
+            except requests.RequestException as e:
+                self.logger.warning(f"Attempt {attempt + 1} failed: {e}")
+                if attempt == self.config.max_retries - 1:
+                    raise Exception(f"Failed to download webpage after {self.config.max_retries} attempts: {e}")
+        return None
+
+    def _cleanup_text(self, text: str) -> str:
+        """清理文本
+
+        Args:
+            text: 原始文本
+
+        Returns:
+            str: 清理后的文本
+        """
+        if not text:
+            return ""
+
+        if self.config.text_cleanup['remove_extra_spaces']:
+            text = ' '.join(text.split())
+
+        if self.config.text_cleanup['normalize_whitespace']:
+            text = text.replace('\t', ' ').replace('\r', '\n')
+
+        if self.config.text_cleanup['lowercase']:
+            text = text.lower()
+
+        return text.strip()
+
+    def extract_text(self, url: str) -> str:
+        """提取网页文本内容
+
+        Args:
+            url: 网页URL
+
+        Returns:
+            str: 提取的文本内容
+
+        Raises:
+            ValueError: URL无效时抛出
+            Exception: 提取失败时抛出
+        """
+        try:
+            if not self._validate_url(url):
+                raise ValueError(f"Invalid URL: {url}")
+
+            self.logger.info(f"Processing URL: {url}")
+            
+            # 下载网页
+            html_content = self._download_webpage(url)
+            if not html_content:
+                raise Exception("Failed to download webpage")
+
+            # 配置trafilatura提取选项
+            extract_config = {
+                'include_comments': self.config.extract_comments,
+                'include_tables': self.config.extract_tables,
+                'include_links': self.config.extract_links,
+                'no_fallback': False,  # 允许使用后备提取器
+            }
+
+            # 提取文本
+            extracted_text = trafilatura.extract(
+                html_content,
+                **extract_config
+            )
+
+            if not extracted_text:
+                raise Exception("No content could be extracted")
+
+            # 清理文本
+            cleaned_text = self._cleanup_text(extracted_text)
+            
+            return cleaned_text
+
+        except Exception as e:
+            self.logger.error(f"Extraction failed: {e}")
+            raise
+
+
+def main():
+    """主函数：演示用法"""
+    # 配置
+    config = WebExtractorConfig(
+        extract_comments=False,
+        extract_tables=True,
+        extract_links=False,
+        timeout=10,
+        text_cleanup={
+            'remove_extra_spaces': True,
+            'normalize_whitespace': True,
+            'remove_special_chars': False,
+            'lowercase': False
+        }
+    )
+
+    # 创建提取器
+    extractor = WebTextExtractor(config)
+
+    # 使用示例
+    try:
+        # 替换为实际的URL
+        sample_url = 'https://arxiv.org/abs/2412.00036'
+        text = extractor.extract_text(sample_url)
+        print("提取的文本:")
+        print(text)
+
+    except Exception as e:
+        print(f"错误: {e}")
+
+
+if __name__ == "__main__":
+    main()

main.py

@@ -31,7 +31,7 @@ def encode_plugin_info(k, plugin)->str:
 
 def main():
     import gradio as gr
-    if gr.__version__ not in ['3.32.12']:
+    if gr.__version__ not in ['3.32.15']:
         raise ModuleNotFoundError("使用项目内置Gradio获取最优体验! 请运行 `pip install -r requirements.txt` 指令安装内置Gradio及其他依赖, 详情信息见requirements.txt.")
 
     # 一些基础工具

request_llms/bridge_all.py

@@ -80,6 +80,7 @@ ollama_endpoint = "http://localhost:11434/api/chat"
 yimodel_endpoint = "https://api.lingyiwanwu.com/v1/chat/completions"
 deepseekapi_endpoint = "https://api.deepseek.com/v1/chat/completions"
 grok_model_endpoint = "https://api.x.ai/v1/chat/completions"
+volcengine_endpoint = "https://ark.cn-beijing.volces.com/api/v3/chat/completions"
 
 if not AZURE_ENDPOINT.endswith('/'): AZURE_ENDPOINT += '/'
 azure_endpoint = AZURE_ENDPOINT + f'openai/deployments/{AZURE_ENGINE}/chat/completions?api-version=2023-05-15'
@@ -102,6 +103,7 @@ if ollama_endpoint in API_URL_REDIRECT: ollama_endpoint = API_URL_REDIRECT[ollam
 if yimodel_endpoint in API_URL_REDIRECT: yimodel_endpoint = API_URL_REDIRECT[yimodel_endpoint]
 if deepseekapi_endpoint in API_URL_REDIRECT: deepseekapi_endpoint = API_URL_REDIRECT[deepseekapi_endpoint]
 if grok_model_endpoint in API_URL_REDIRECT: grok_model_endpoint = API_URL_REDIRECT[grok_model_endpoint]
+if volcengine_endpoint in API_URL_REDIRECT: volcengine_endpoint = API_URL_REDIRECT[volcengine_endpoint]
 
 # 获取tokenizer
 tokenizer_gpt35 = LazyloadTiktoken("gpt-3.5-turbo")
@@ -280,6 +282,7 @@ model_info = {
         "fn_with_ui": chatgpt_ui,
         "fn_without_ui": chatgpt_noui,
         "endpoint": openai_endpoint,
+        "can_multi_thread": True,
         "max_token": 128000,
         "tokenizer": tokenizer_gpt4,
         "token_cnt": get_token_num_gpt4,
@@ -312,6 +315,50 @@ model_info = {
         "openai_force_temperature_one": True,
     },
 
+    "gpt-4.1":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+    },
+
+    "gpt-4.1-mini":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+    },
+
+    "o3":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+        "openai_disable_system_prompt": True,
+        "openai_disable_stream": True,
+        "openai_force_temperature_one": True,
+    },
+
+    "o4-mini":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "can_multi_thread": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+    },
+
     "gpt-4-turbo": {
         "fn_with_ui": chatgpt_ui,
         "fn_without_ui": chatgpt_noui,
@@ -528,6 +575,15 @@ model_info = {
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
+    "gemini-2.0-flash": {
+        "fn_with_ui": genai_ui,
+        "fn_without_ui": genai_noui,
+        "endpoint": gemini_endpoint,
+        "has_multimodal_capacity": True,
+        "max_token": 1024 * 204800,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
 
     # cohere
     "cohere-command-r-plus": {
@@ -811,8 +867,12 @@ if "qwen-local" in AVAIL_LLM_MODELS:
         })
     except:
         logger.error(trimmed_format_exc())
-# -=-=-=-=-=-=- 通义-在线模型 -=-=-=-=-=-=-
-qwen_models = ["qwen-max-latest", "qwen-max-2025-01-25","qwen-max","qwen-turbo","qwen-plus"]
+
+# -=-=-=-=-=-=- 阿里云百炼（通义）-在线模型 -=-=-=-=-=-=-
+qwen_models = ["qwen-max-latest", "qwen-max-2025-01-25","qwen-max","qwen-turbo","qwen-plus",
+               "dashscope-deepseek-r1","dashscope-deepseek-v3",
+               "dashscope-qwen3-14b", "dashscope-qwen3-235b-a22b", "dashscope-qwen3-qwen3-32b",
+               ]
 if any(item in qwen_models for item in AVAIL_LLM_MODELS):
     try:
         from .bridge_qwen import predict_no_ui_long_connection as qwen_noui
@@ -862,10 +922,58 @@ if any(item in qwen_models for item in AVAIL_LLM_MODELS):
                 "max_token": 30720,
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-deepseek-r1": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "enable_reasoning": True,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 57344,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-deepseek-v3": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 57344,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-qwen3-14b": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "enable_reasoning": True,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 129024,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-qwen3-235b-a22b": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 129024,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-qwen3-32b": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 129024,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
             }
         })
     except:
         logger.error(trimmed_format_exc())
+
 # -=-=-=-=-=-=- 零一万物模型 -=-=-=-=-=-=-
 yi_models = ["yi-34b-chat-0205","yi-34b-chat-200k","yi-large","yi-medium","yi-spark","yi-large-turbo","yi-large-preview"]
 if any(item in yi_models for item in AVAIL_LLM_MODELS):
@@ -1089,8 +1197,10 @@ if "deepseekcoder" in AVAIL_LLM_MODELS:   # deepseekcoder
         })
     except:
         logger.error(trimmed_format_exc())
+
 # -=-=-=-=-=-=- 幻方-深度求索大模型在线API -=-=-=-=-=-=-
-if "deepseek-chat" in AVAIL_LLM_MODELS or "deepseek-coder" in AVAIL_LLM_MODELS or "deepseek-reasoner" in AVAIL_LLM_MODELS:
+claude_models = ["deepseek-chat", "deepseek-coder", "deepseek-reasoner"]
+if any(item in claude_models for item in AVAIL_LLM_MODELS):
     try:
         deepseekapi_noui, deepseekapi_ui = get_predict_function(
             api_key_conf_name="DEEPSEEK_API_KEY", max_output_token=4096, disable_proxy=False
@@ -1127,6 +1237,60 @@ if "deepseek-chat" in AVAIL_LLM_MODELS or "deepseek-coder" in AVAIL_LLM_MODELS o
         })
     except:
         logger.error(trimmed_format_exc())
+
+# -=-=-=-=-=-=- 火山引擎 对齐支持 -=-=-=-=-=-=-
+for model in [m for m in AVAIL_LLM_MODELS if m.startswith("volcengine-")]:
+    # 为了更灵活地接入volcengine多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["volcengine-deepseek-r1-250120(max_token=6666)"]
+    # 其中
+    #   "volcengine-"          是前缀（必要）
+    #   "deepseek-r1-250120"   是模型名（必要）
+    #   "(max_token=6666)"     是配置（非必要）
+    model_info_extend = model_info
+    model_info_extend.update({
+        "deepseek-r1-250120": {
+            "max_token": 16384,
+            "enable_reasoning": True,
+            "can_multi_thread": True,
+            "endpoint": volcengine_endpoint,
+            "tokenizer": tokenizer_gpt35,
+            "token_cnt": get_token_num_gpt35,
+        },
+        "deepseek-v3-241226": {
+            "max_token": 16384,
+            "enable_reasoning": False,
+            "can_multi_thread": True,
+            "endpoint": volcengine_endpoint,
+            "tokenizer": tokenizer_gpt35,
+            "token_cnt": get_token_num_gpt35,
+        },
+    })
+    try:
+        origin_model_name, max_token_tmp = read_one_api_model_name(model)
+        # 如果是已知模型，则尝试获取其信息
+        original_model_info = model_info_extend.get(origin_model_name.replace("volcengine-", "", 1), None)
+    except:
+        logger.error(f"volcengine模型 {model} 的 max_token 配置不是整数，请检查配置文件。")
+        continue
+
+    volcengine_noui, volcengine_ui = get_predict_function(api_key_conf_name="ARK_API_KEY", max_output_token=8192, disable_proxy=True, model_remove_prefix = ["volcengine-"])
+
+    this_model_info = {
+        "fn_with_ui": volcengine_ui,
+        "fn_without_ui": volcengine_noui,
+        "endpoint": volcengine_endpoint,
+        "can_multi_thread": True,
+        "max_token": 64000,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    }
+
+    # 同步已知模型的其他信息
+    attribute = "has_multimodal_capacity"
+    if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
+    attribute = "enable_reasoning"
+    if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
+    model_info.update({model: this_model_info})
+
 # -=-=-=-=-=-=- one-api 对齐支持 -=-=-=-=-=-=-
 for model in [m for m in AVAIL_LLM_MODELS if m.startswith("one-api-")]:
     # 为了更灵活地接入one-api多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["one-api-mixtral-8x7b(max_token=6666)"]

request_llms/bridge_chatgpt.py

@@ -368,12 +368,12 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                             log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
                             break # 对于符合规范的接口，这里可以break
                         else:
-                            continue # 对于不符合规范的狗屎接口，这里需要继续
+                            continue # 对于不符合规范的接口，这里需要继续
                     # 到这里，我们已经可以假定必须包含choice了
                     try:
                         status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
                     except:
-                        logger.error(f"一些垃圾第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
+                        logger.error(f"一些第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
                     # 处理数据流的主体
                     if has_content:
                         # 正常情况
@@ -382,9 +382,9 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                         # 一些第三方接口的出现这样的错误，兼容一下吧
                         continue
                     else:
-                        # 至此已经超出了正常接口应该进入的范围，一些垃圾第三方接口会出现这样的错误
+                        # 至此已经超出了正常接口应该进入的范围，一些第三方接口会出现这样的错误
                         if chunkjson['choices'][0]["delta"].get("content", None) is None:
-                            logger.error(f"一些垃圾第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
+                            logger.error(f"一些第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
                             continue
                         gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
 

request_llms/com_qwenapi.py

@@ -3,6 +3,7 @@ from toolbox import get_conf
 import threading
 
 timeout_bot_msg = '[Local Message] Request timeout. Network error.'
+model_prefix_to_remove = 'dashscope-'
 
 class QwenRequestInstance():
     def __init__(self):
@@ -20,6 +21,13 @@ class QwenRequestInstance():
             raise RuntimeError('请配置 DASHSCOPE_API_KEY')
         dashscope.api_key = get_conf("DASHSCOPE_API_KEY")
 
+    def format_reasoning(self, reasoning_content:str, main_content:str):
+        if reasoning_content:
+            reasoning_content_paragraphs = ''.join([f'<p style="margin: 1.25em 0;">{line}</p>' for line in reasoning_content.split('\n')])
+            formatted_reasoning_content = f'<div class="reasoning_process">{reasoning_content_paragraphs}</div>\n\n---\n\n'
+            return formatted_reasoning_content + main_content
+        else:
+            return main_content
 
     def generate(self, inputs, llm_kwargs, history, system_prompt):
         # import _thread as thread
@@ -28,9 +36,13 @@ class QwenRequestInstance():
         if top_p == 0: top_p += 1e-5
         if top_p == 1: top_p -= 1e-5
 
+        model_name = llm_kwargs['llm_model']
+        if model_name.startswith(model_prefix_to_remove): model_name = model_name[len(model_prefix_to_remove):]
+
+        self.reasoning_buf = ""
         self.result_buf = ""
         responses = Generation.call(
-            model=llm_kwargs['llm_model'],
+            model=model_name,
             messages=generate_message_payload(inputs, llm_kwargs, history, system_prompt),
             top_p=top_p,
             temperature=llm_kwargs.get('temperature', 1.0),
@@ -46,18 +58,24 @@ class QwenRequestInstance():
                         self.result_buf += response.output.choices[0].message.content
                     except:
                         pass
-                    yield self.result_buf
+                    yield self.format_reasoning(self.reasoning_buf, self.result_buf)
                     break
                 elif response.output.choices[0].finish_reason == 'length':
                     self.result_buf += "[Local Message] 生成长度过长，后续输出被截断"
-                    yield self.result_buf
+                    yield self.format_reasoning(self.reasoning_buf, self.result_buf)
                     break
                 else:
+                    try:
+                        contain_reasoning = hasattr(response.output.choices[0].message, 'reasoning_content')
+                    except:
+                        contain_reasoning = False
+                    if contain_reasoning:
+                        self.reasoning_buf += response.output.choices[0].message.reasoning_content
                     self.result_buf += response.output.choices[0].message.content
-                    yield self.result_buf
+                    yield self.format_reasoning(self.reasoning_buf, self.result_buf)
             else:
                 self.result_buf += f"[Local Message] 请求错误：状态码：{response.status_code}，错误码:{response.code}，消息：{response.message}"
-                yield self.result_buf
+                yield self.format_reasoning(self.reasoning_buf, self.result_buf)
                 break
 
         # 耗尽generator避免报错

request_llms/oai_std_model_template.py

@@ -57,7 +57,7 @@ def decode_chunk(chunk):
             finish_reason = chunk["error"]["code"]
         except:
             finish_reason = "API_ERROR"
-        return response, reasoning_content, finish_reason
+        return response, reasoning_content, finish_reason, str(chunk)
 
     try:
         if chunk["choices"][0]["delta"]["content"] is not None:
@@ -122,7 +122,8 @@ def generate_message(input, model, key, history, max_output_token, system_prompt
 def get_predict_function(
         api_key_conf_name,
         max_output_token,
-        disable_proxy = False
+        disable_proxy = False,
+        model_remove_prefix = [],
     ):
     """
     为openai格式的API生成响应函数，其中传入参数：
@@ -137,6 +138,16 @@ def get_predict_function(
 
     APIKEY = get_conf(api_key_conf_name)
 
+    def remove_prefix(model_name):
+        # 去除模型名字的前缀，输入 volcengine-deepseek-r1-250120 会返回 deepseek-r1-250120
+        if not model_remove_prefix:
+            return model_name
+        model_without_prefix = model_name
+        for prefix in model_remove_prefix:
+            if model_without_prefix.startswith(prefix):
+                model_without_prefix = model_without_prefix[len(prefix):]
+        return model_without_prefix
+
     def predict_no_ui_long_connection(
         inputs,
         llm_kwargs,
@@ -164,9 +175,11 @@ def get_predict_function(
             raise RuntimeError(f"APIKEY为空,请检查配置文件的{APIKEY}")
         if inputs == "":
             inputs = "你好👋"
+
+
         headers, payload = generate_message(
             input=inputs,
-            model=llm_kwargs["llm_model"],
+            model=remove_prefix(llm_kwargs["llm_model"]),
             key=APIKEY,
             history=history,
             max_output_token=max_output_token,
@@ -302,7 +315,7 @@ def get_predict_function(
 
         headers, payload = generate_message(
             input=inputs,
-            model=llm_kwargs["llm_model"],
+            model=remove_prefix(llm_kwargs["llm_model"]),
             key=APIKEY,
             history=history,
             max_output_token=max_output_token,

requirements.txt

@@ -1,4 +1,4 @@
-https://public.agent-matrix.com/publish/gradio-3.32.12-py3-none-any.whl
+https://public.agent-matrix.com/publish/gradio-3.32.15-py3-none-any.whl
 fastapi==0.110
 gradio-client==0.8
 pypdf2==2.12.1

shared_utils/advanced_markdown_format.py

@@ -3,7 +3,8 @@ import re
 import os
 import math
 import html
-
+import base64
+import gzip
 from loguru import logger
 from textwrap import dedent
 from functools import lru_cache
@@ -325,6 +326,14 @@ def markdown_convertion_for_file(txt):
     # cat them together
     return pre + convert_stage_5 + suf
 
+def compress_string(s):
+    compress_string = gzip.compress(s.encode('utf-8'))
+    return base64.b64encode(compress_string).decode()
+
+def decompress_string(s):
+    decoded_string = base64.b64decode(s)
+    return gzip.decompress(decoded_string).decode('utf-8')
+
 @lru_cache(maxsize=128)  # 使用 lru缓存 加快转换速度
 def markdown_convertion(txt):
     """
@@ -336,6 +345,12 @@ def markdown_convertion(txt):
         # print('警告，输入了已经经过转化的字符串，二次转化可能出问题')
         return txt  # 已经被转化过，不需要再次转化
 
+    # 在文本中插入一个base64编码的原始文本，以便在复制时能够获得原始文本
+    raw_text_encoded = compress_string(txt)
+    raw_text_node = f'<div class="raw_text" style="display:none">{raw_text_encoded}</div><div class="message_tail" style="display:none"/>'
+    suf = raw_text_node + "</div>"
+
+    # 用于查找数学公式的正则表达式
     find_equation_pattern = r'<script type="math/tex(?:.*?)>(.*?)</script>'
 
     txt = fix_markdown_indent(txt)
@@ -493,6 +508,7 @@ def simple_markdown_convertion(text):
     suf = "</div>"
     if text.startswith(pre) and text.endswith(suf):
         return text  # 已经被转化过，不需要再次转化
+
     text = compat_non_markdown_input(text)    # 兼容非markdown输入
     text = markdown.markdown(
         text,

shared_utils/context_clip_policy.py

@@ -0,0 +1,296 @@
+import copy
+from shared_utils.config_loader import get_conf
+
+def get_token_num(txt, tokenizer):
+    return len(tokenizer.encode(txt, disallowed_special=()))
+
+def get_model_info():
+    from request_llms.bridge_all import model_info
+    return model_info
+
+def clip_history(inputs, history, tokenizer, max_token_limit):
+    """
+    reduce the length of history by clipping.
+    this function search for the longest entries to clip, little by little,
+    until the number of token of history is reduced under threshold.
+
+    通过裁剪来缩短历史记录的长度。
+    此函数逐渐地搜索最长的条目进行剪辑，
+    直到历史记录的标记数量降低到阈值以下。
+
+    被动触发裁剪
+    """
+    import numpy as np
+
+    input_token_num = get_token_num(inputs)
+
+    if max_token_limit < 5000:
+        output_token_expect = 256  # 4k & 2k models
+    elif max_token_limit < 9000:
+        output_token_expect = 512  # 8k models
+    else:
+        output_token_expect = 1024  # 16k & 32k models
+
+    if input_token_num < max_token_limit * 3 / 4:
+        # 当输入部分的token占比小于限制的3/4时，裁剪时
+        # 1. 把input的余量留出来
+        max_token_limit = max_token_limit - input_token_num
+        # 2. 把输出用的余量留出来
+        max_token_limit = max_token_limit - output_token_expect
+        # 3. 如果余量太小了，直接清除历史
+        if max_token_limit < output_token_expect:
+            history = []
+            return history
+    else:
+        # 当输入部分的token占比 > 限制的3/4时，直接清除历史
+        history = []
+        return history
+
+    everything = [""]
+    everything.extend(history)
+    n_token = get_token_num("\n".join(everything))
+    everything_token = [get_token_num(e) for e in everything]
+
+    # 截断时的颗粒度
+    delta = max(everything_token) // 16
+
+    while n_token > max_token_limit:
+        where = np.argmax(everything_token)
+        encoded = tokenizer.encode(everything[where], disallowed_special=())
+        clipped_encoded = encoded[: len(encoded) - delta]
+        everything[where] = tokenizer.decode(clipped_encoded)[
+            :-1
+        ]  # -1 to remove the may-be illegal char
+        everything_token[where] = get_token_num(everything[where])
+        n_token = get_token_num("\n".join(everything))
+
+    history = everything[1:]
+    return history
+
+
+
+def auto_context_clip_each_message(current, history):
+    """
+    clip_history 是被动触发的
+
+    主动触发裁剪
+    """
+    context = history + [current]
+    trigger_clip_token_len = get_conf('AUTO_CONTEXT_CLIP_TRIGGER_TOKEN_LEN')
+    model_info = get_model_info()
+    tokenizer = model_info['gpt-4']['tokenizer']
+    # 只保留最近的128条记录，无论token长度，防止计算token时计算过长的时间
+    max_round = get_conf('AUTO_CONTEXT_MAX_ROUND')
+    char_len = sum([len(h) for h in context])
+    if char_len < trigger_clip_token_len*2:
+        # 不需要裁剪
+        history = context[:-1]
+        current = context[-1]
+        return current, history
+    if len(context) > max_round:
+        context = context[-max_round:]
+    # 计算各个历史记录的token长度
+    context_token_num = [get_token_num(h, tokenizer) for h in context]
+    context_token_num_old = copy.copy(context_token_num)
+    total_token_num = total_token_num_old = sum(context_token_num)
+    if total_token_num < trigger_clip_token_len:
+        # 不需要裁剪
+        history = context[:-1]
+        current = context[-1]
+        return current, history
+    clip_token_len = trigger_clip_token_len * 0.85
+    # 越长越先被裁，越靠后越先被裁
+    max_clip_ratio: list[float] = get_conf('AUTO_CONTEXT_MAX_CLIP_RATIO')
+    max_clip_ratio = list(reversed(max_clip_ratio))
+    if len(context) > len(max_clip_ratio):
+        # give up the oldest context
+        context = context[-len(max_clip_ratio):]
+        context_token_num = context_token_num[-len(max_clip_ratio):]
+    if len(context) < len(max_clip_ratio):
+        # match the length of two array
+        max_clip_ratio = max_clip_ratio[-len(context):]
+    
+    # compute rank
+    clip_prior_weight = [(token_num/clip_token_len + (len(context) - index)*0.1) for index, token_num in enumerate(context_token_num)]
+    # print('clip_prior_weight', clip_prior_weight)
+    # get sorted index of context_token_num, from largest to smallest
+    sorted_index = sorted(range(len(context_token_num)), key=lambda k: clip_prior_weight[k], reverse=True)
+
+    # pre compute space yield
+    for index in sorted_index:
+        print('index', index, f'current total {total_token_num}, target {clip_token_len}')
+        if total_token_num < clip_token_len:
+            # no need to clip
+            break
+        # clip room left
+        clip_room_left = total_token_num - clip_token_len
+        # get the clip ratio
+        allowed_token_num_this_entry = max_clip_ratio[index] * clip_token_len
+        if context_token_num[index] < allowed_token_num_this_entry:
+            print('index', index, '[allowed] before', context_token_num[index], 'allowed', allowed_token_num_this_entry)
+            continue
+
+        token_to_clip = context_token_num[index] - allowed_token_num_this_entry
+        if token_to_clip*0.85 > clip_room_left:
+            print('index', index, '[careful clip] token_to_clip', token_to_clip, 'clip_room_left', clip_room_left)
+            token_to_clip = clip_room_left
+
+        token_percent_to_clip = token_to_clip / context_token_num[index]
+        char_percent_to_clip = token_percent_to_clip
+        text_this_entry = context[index]
+        char_num_to_clip = int(len(text_this_entry) * char_percent_to_clip)
+        if char_num_to_clip < 500:
+            # 如果裁剪的字符数小于500，则不裁剪
+            print('index', index, 'before', context_token_num[index], 'allowed', allowed_token_num_this_entry)
+            continue
+        char_num_to_clip += 200 # 稍微多加一点
+        char_to_preseve = len(text_this_entry) - char_num_to_clip
+        _half = int(char_to_preseve / 2)
+        # 前半 + ... (content clipped because token overflows) ... + 后半
+        text_this_entry_clip = text_this_entry[:_half] + \
+                             " ... (content clipped because token overflows) ... " \
+                             + text_this_entry[-_half:]
+        context[index] = text_this_entry_clip
+        post_clip_token_cnt = get_token_num(text_this_entry_clip, tokenizer)
+        print('index', index, 'before', context_token_num[index], 'allowed', allowed_token_num_this_entry, 'after', post_clip_token_cnt)
+        context_token_num[index] = post_clip_token_cnt
+        total_token_num = sum(context_token_num)
+    context_token_num_final = [get_token_num(h, tokenizer) for h in context]
+    print('context_token_num_old', context_token_num_old)
+    print('context_token_num_final', context_token_num_final)
+    print('token change from', total_token_num_old, 'to', sum(context_token_num_final), 'target', clip_token_len)
+    history = context[:-1]
+    current = context[-1]
+    return current, history
+
+
+
+def auto_context_clip_search_optimal(current, history, promote_latest_long_message=False):
+    """
+    current: 当前消息
+    history: 历史消息列表
+    promote_latest_long_message: 是否特别提高最后一条长message的权重，避免过度裁剪
+
+    主动触发裁剪
+    """
+    context = history + [current]
+    trigger_clip_token_len = get_conf('AUTO_CONTEXT_CLIP_TRIGGER_TOKEN_LEN')
+    model_info = get_model_info()
+    tokenizer = model_info['gpt-4']['tokenizer']
+    # 只保留最近的128条记录，无论token长度，防止计算token时计算过长的时间
+    max_round = get_conf('AUTO_CONTEXT_MAX_ROUND')
+    char_len = sum([len(h) for h in context])
+    if char_len < trigger_clip_token_len:
+        # 不需要裁剪
+        history = context[:-1]
+        current = context[-1]
+        return current, history
+    if len(context) > max_round:
+        context = context[-max_round:]
+    # 计算各个历史记录的token长度
+    context_token_num = [get_token_num(h, tokenizer) for h in context]
+    context_token_num_old = copy.copy(context_token_num)
+    total_token_num = total_token_num_old = sum(context_token_num)
+    if total_token_num < trigger_clip_token_len:
+        # 不需要裁剪
+        history = context[:-1]
+        current = context[-1]
+        return current, history
+    clip_token_len = trigger_clip_token_len * 0.90
+    max_clip_ratio: list[float] = get_conf('AUTO_CONTEXT_MAX_CLIP_RATIO')
+    max_clip_ratio = list(reversed(max_clip_ratio))
+    if len(context) > len(max_clip_ratio):
+        # give up the oldest context
+        context = context[-len(max_clip_ratio):]
+        context_token_num = context_token_num[-len(max_clip_ratio):]
+    if len(context) < len(max_clip_ratio):
+        # match the length of two array
+        max_clip_ratio = max_clip_ratio[-len(context):]
+
+    _scale = _scale_init = 1.25
+    token_percent_arr = [(token_num/clip_token_len) for index, token_num in enumerate(context_token_num)]
+
+    # promote last long message, avoid clipping it too much
+    if promote_latest_long_message:
+        promote_weight_constant = 1.6
+        promote_index = -1
+        threshold = 0.50
+        for index, token_percent in enumerate(token_percent_arr):
+            if token_percent > threshold:
+                promote_index = index
+        if promote_index >= 0:
+            max_clip_ratio[promote_index] = promote_weight_constant
+
+    max_clip_ratio_arr = max_clip_ratio
+    step = 0.05
+    for i in range(int(_scale_init / step) - 1):
+        _take = 0
+        for max_clip, token_r in zip(max_clip_ratio_arr, token_percent_arr):
+            _take += min(max_clip * _scale, token_r)
+        if _take < 1.0:
+            break
+        _scale -= 0.05
+
+    # print('optimal scale', _scale)
+    # print([_scale * max_clip for max_clip in max_clip_ratio_arr])
+    # print([token_r for token_r in token_percent_arr])
+    # print([min(token_r, _scale * max_clip) for token_r, max_clip in zip(token_percent_arr, max_clip_ratio_arr)])
+    eps = 0.05
+    max_clip_ratio = [_scale * max_clip + eps for max_clip in max_clip_ratio_arr]
+
+    # compute rank
+    # clip_prior_weight_old = [(token_num/clip_token_len + (len(context) - index)*0.1) for index, token_num in enumerate(context_token_num)]
+    clip_prior_weight = [ token_r / max_clip  for max_clip, token_r in zip(max_clip_ratio_arr, token_percent_arr)]
+
+    # sorted_index_old = sorted(range(len(context_token_num)), key=lambda k: clip_prior_weight_old[k], reverse=True)
+    # print('sorted_index_old', sorted_index_old)
+    sorted_index = sorted(range(len(context_token_num)), key=lambda k: clip_prior_weight[k], reverse=True)
+    # print('sorted_index', sorted_index)
+
+    # pre compute space yield
+    for index in sorted_index:
+        # print('index', index, f'current total {total_token_num}, target {clip_token_len}')
+        if total_token_num < clip_token_len:
+            # no need to clip
+            break
+        # clip room left
+        clip_room_left = total_token_num - clip_token_len
+        # get the clip ratio
+        allowed_token_num_this_entry = max_clip_ratio[index] * clip_token_len
+        if context_token_num[index] < allowed_token_num_this_entry:
+            # print('index', index, '[allowed] before', context_token_num[index], 'allowed', allowed_token_num_this_entry)
+            continue
+
+        token_to_clip = context_token_num[index] - allowed_token_num_this_entry
+        if token_to_clip*0.85 > clip_room_left:
+            # print('index', index, '[careful clip] token_to_clip', token_to_clip, 'clip_room_left', clip_room_left)
+            token_to_clip = clip_room_left
+
+        token_percent_to_clip = token_to_clip / context_token_num[index]
+        char_percent_to_clip = token_percent_to_clip
+        text_this_entry = context[index]
+        char_num_to_clip = int(len(text_this_entry) * char_percent_to_clip)
+        if char_num_to_clip < 500:
+            # 如果裁剪的字符数小于500，则不裁剪
+            # print('index', index, 'before', context_token_num[index], 'allowed', allowed_token_num_this_entry)
+            continue
+        eps = 200
+        char_num_to_clip = char_num_to_clip + eps # 稍微多加一点
+        char_to_preseve = len(text_this_entry) - char_num_to_clip
+        _half = int(char_to_preseve / 2)
+        # 前半 + ... (content clipped because token overflows) ... + 后半
+        text_this_entry_clip = text_this_entry[:_half] + \
+                             " ... (content clipped because token overflows) ... " \
+                             + text_this_entry[-_half:]
+        context[index] = text_this_entry_clip
+        post_clip_token_cnt = get_token_num(text_this_entry_clip, tokenizer)
+        # print('index', index, 'before', context_token_num[index], 'allowed', allowed_token_num_this_entry, 'after', post_clip_token_cnt)
+        context_token_num[index] = post_clip_token_cnt
+        total_token_num = sum(context_token_num)
+    context_token_num_final = [get_token_num(h, tokenizer) for h in context]
+    # print('context_token_num_old', context_token_num_old)
+    # print('context_token_num_final', context_token_num_final)
+    # print('token change from', total_token_num_old, 'to', sum(context_token_num_final), 'target', clip_token_len)
+    history = context[:-1]
+    current = context[-1]
+    return current, history

shared_utils/fastapi_stream_server.py

@@ -0,0 +1,622 @@
+"""
+FastAPI WebSocket 流式服务器模块
+
+这个模块实现了一个基于FastAPI的WebSocket服务器，用于处理前端和后端之间的实时双向通信。
+主要功能包括：
+1. 维护WebSocket连接
+2. 处理消息队列
+3. 支持实时和阻塞式消息传输
+4. 提供事件管理机制
+
+主要组件：
+- FutureEvent: 用于事件管理的线程事件类
+- UserInterfaceMsg: 定义前后端通信的消息格式
+- PythonMethod_AsyncConnectionMaintainer_AgentcraftInterface: 连接维护器
+- MasterMindWebSocketServer: WebSocket服务器主类
+"""
+
+import uuid
+import time
+import json
+import platform
+import pickle
+import asyncio
+import threading
+import traceback
+from fastapi.websockets import WebSocketState
+from loguru import logger
+from queue import Queue
+from fastapi import FastAPI, WebSocket, File, UploadFile, Form
+from fastapi.responses import JSONResponse
+from datetime import datetime
+from typing import List, Optional, Any, Union
+from pydantic import BaseModel, Field
+import shutil
+import os
+from enum import auto, Enum
+from typing import List
+from toolbox import ChatBotWithCookies
+import starlette
+
+
+
+class UserInterfaceMsg(BaseModel):
+    """
+    用户界面消息模型，定义了前后端通信的数据结构
+
+    这个类使用Pydantic BaseModel定义了所有可能的消息字段，
+    包括插件功能、输入内容、LLM参数、聊天记录等。
+    """
+    function: str = Field(default="chat", description="使用哪个插件")
+    main_input: str = Field(default="", description="主要输入内容，通常是用户的问题")
+    llm_kwargs: dict = Field(default_factory=dict, description="围绕LLM的各种参数")
+    #     llm_kwargs = {
+    #         "api_key": cookies["api_key"],
+    #         "llm_model": cookies["llm_model"],
+    #         "top_p": 1.0,
+    #         "max_length": None,
+    #         "temperature": 1.0,
+    #         "user_name": "default_user",  # Default user name
+    #     }
+    plugin_kwargs: dict = Field(default_factory=dict, description="围绕该function的各种参数")
+    chatbot: list[list[Union[str|None]]] = Field(default=[], description="聊天记录（给人类看的）。格式为 [ [user_msg, bot_msg], [user_msg_2, bot_msg_2],...]，双层列表，第一层是每一轮对话，第二层是用户和机器人的消息。")
+    chatbot_cookies: dict = Field(default_factory=dict, description="其他新前端涉及的参数")
+    history: list[str] = Field(default=[], description="聊天记录（给模型看的）。单层列表")
+    system_prompt: str = Field(default="", description="系统提示词")
+    user_request: dict = Field(default="", description="用户相关的参数，如用户名")
+    special_kwargs: dict = Field(default_factory=dict, description="其他新前端涉及的参数")
+    special_state: dict = Field(default={}, description="特殊状态传递，例如对话结束。")
+
+TERMINATE_MSG = UserInterfaceMsg(function="TERMINATE", special_state={"stop": True})
+
+def setup_initial_com(initial_msg: UserInterfaceMsg):
+    """
+    设置插件参数
+
+    从初始消息中提取各种参数并构建插件执行所需的参数字典。
+
+    参数:
+        initial_msg: 初始的用户消息
+        chatbot_with_cookies: 带有cookie的聊天机器人实例
+
+    返回:
+        dict: 包含插件执行所需所有参数的字典
+    """
+    from toolbox import get_plugin_default_kwargs
+
+
+    com = get_plugin_default_kwargs()
+    com["main_input"] = initial_msg.main_input
+    # 设置LLM相关参数
+    if initial_msg.llm_kwargs.get('api_key', None):     com["llm_kwargs"]['api_key'] = initial_msg.llm_kwargs.get('api_key')
+    if initial_msg.llm_kwargs.get('llm_model', None):   com["llm_kwargs"]['llm_model'] = initial_msg.llm_kwargs.get('llm_model')
+    if initial_msg.llm_kwargs.get('top_p', None):       com["llm_kwargs"]['top_p'] = initial_msg.llm_kwargs.get('top_p')
+    if initial_msg.llm_kwargs.get('max_length', None):  com["llm_kwargs"]['max_length'] = initial_msg.llm_kwargs.get('max_length')
+    if initial_msg.llm_kwargs.get('temperature', None): com["llm_kwargs"]['temperature'] = initial_msg.llm_kwargs.get('temperature')
+    if initial_msg.llm_kwargs.get('user_name', None):   com["llm_kwargs"]['user_name'] = initial_msg.llm_kwargs.get('user_name')
+    if initial_msg.llm_kwargs.get('embed_model', None): com["llm_kwargs"]['embed_model'] = initial_msg.llm_kwargs.get('embed_model')
+
+    initial_msg.chatbot_cookies.update({
+        'api_key':      com["llm_kwargs"]['api_key'],
+        'top_p':        com["llm_kwargs"]['top_p'],
+        'llm_model':    com["llm_kwargs"]['llm_model'],
+        'embed_model':  com["llm_kwargs"]['embed_model'],
+        'temperature':  com["llm_kwargs"]['temperature'],
+        'user_name':    com["llm_kwargs"]['user_name'],
+        'customize_fn_overwrite': {},
+    })
+    chatbot_with_cookies = ChatBotWithCookies(initial_msg.chatbot_cookies)
+    chatbot_with_cookies.write_list(initial_msg.chatbot)
+    # 设置其他参数
+    com["plugin_kwargs"] = initial_msg.plugin_kwargs
+    com["chatbot_with_cookie"] = chatbot_with_cookies
+    com["history"] = initial_msg.history
+    com["system_prompt"] = initial_msg.system_prompt
+    com["user_request"] = initial_msg.user_request
+
+    return com
+
+
+class DummyRequest(object):
+    def __call__(self, username):
+        self.username = username
+
+
+def task_executor(initial_msg:UserInterfaceMsg, queue_blocking_from_client:asyncio.Queue, queue_back_to_client:asyncio.Queue):
+    """
+        initial_msg: 初始的用户消息 ( <---- begin_contact_websocket_server:initial_message )
+        queue_blocking_from_client: 从客户端接收阻塞消息的队列
+        queue_back_to_client: 发送消息回客户端的队列
+    """
+    from toolbox import get_plugin_handle
+    from toolbox import get_plugin_default_kwargs
+    from toolbox import on_file_uploaded
+
+    def update_ui_websocket(chatbot: List[List[str]], history: List[str], chatbot_cookies: dict, special_state: dict):
+        send_obj = UserInterfaceMsg(chatbot=chatbot, history=history, chatbot_cookies=chatbot_cookies, special_state=special_state)
+        queue_back_to_client.put_nowait(send_obj)
+
+
+    com = setup_initial_com(initial_msg)
+
+    main_input = com["main_input"]
+    plugin_kwargs = com["plugin_kwargs"]
+    chatbot_with_cookies = com["chatbot_with_cookie"]
+    history = com["history"]
+    system_prompt = com["system_prompt"]
+    user_request = com["user_request"]
+    llm_kwargs = com["llm_kwargs"]
+
+
+    # ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
+    # ''''''''''''''''''''''''''''''''   调用插件   '''''''''''''''''''''''''''''''''
+    # ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
+    # ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
+    if initial_msg.function == "chat":
+        plugin = get_plugin_handle("crazy_functions.Chat->Chat")
+        my_working_plugin = (plugin)(**com)
+        for cookies, chatbot, hist_json, msg in my_working_plugin:
+            history = json.loads(hist_json)
+            special_state = {'msg': msg}
+            update_ui_websocket(chatbot=chatbot, history=history, chatbot_cookies=cookies, special_state=special_state) # ----> receive_callback_fn
+
+    if initial_msg.function == "basic":
+        from request_llms.bridge_all import predict
+        additional_fn = initial_msg.special_kwargs.get("core_function")
+        for cookies, chatbot, hist_json, msg in \
+            predict(main_input, llm_kwargs, plugin_kwargs, chatbot_with_cookies, history=history, system_prompt=system_prompt, stream = True, additional_fn=additional_fn):
+            history = json.loads(hist_json)
+            special_state = {'msg': msg}
+            update_ui_websocket(chatbot=chatbot, history=history, chatbot_cookies=cookies, special_state=special_state) # ----> receive_callback_fn
+
+    # ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
+    # ''''''''''''''''''''''''''''''''   上传文件   '''''''''''''''''''''''''''''''''
+    # ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
+    # ''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
+    if initial_msg.function == "upload":
+        def wait_upload_done():
+            print('Waiting for file upload to complete...')
+            file_upload_done_msg = queue_blocking_from_client.get()
+            print('file upload complete...')
+            if file_upload_done_msg.function != "upload_done":
+                raise ValueError("Expected 'upload_done' function, got: {}".format(file_upload_done_msg.function))
+            if 'files' not in file_upload_done_msg.special_kwargs:
+                raise ValueError("Expected 'files' in special_kwargs, got: {}".format(file_upload_done_msg.special_kwargs))
+            return file_upload_done_msg.special_kwargs['files']
+
+        request = DummyRequest()
+        request.username = "default_user"
+        chatbot = initial_msg.chatbot
+        history = initial_msg.history
+        chatbot_cookies = initial_msg.chatbot_cookies
+        special_state = {'msg': '等待上传'}
+        chatbot += [[initial_msg.main_input, None]]
+        update_ui_websocket(chatbot=chatbot, history=history, chatbot_cookies=chatbot_cookies, special_state=special_state) # ----> receive_callback_fn
+
+        # 等待上传完成
+        files = wait_upload_done()
+
+        # 读取文件并预览
+        chatbot += [['正在处理', None]]
+        update_ui_websocket(chatbot=chatbot, history=history, chatbot_cookies=chatbot_cookies, special_state=special_state) # ----> receive_callback_fn
+        chatbot, _, _, chatbot_cookies = on_file_uploaded(
+            request=request, files=files, chatbot=chatbot,
+            txt="", txt2="", checkboxes="", cookies=chatbot_cookies
+        )
+        special_state = {'msg': '完成上传'}
+        # 更新前端
+        update_ui_websocket(chatbot=chatbot, history=history, chatbot_cookies=chatbot_cookies, special_state=special_state) # ----> receive_callback_fn
+
+
+
+class FutureEvent(threading.Event):
+    """
+    扩展的线程事件类，用于异步操作的结果获取
+
+    这个类扩展了threading.Event，添加了返回值存储功能，
+    使得可以在事件完成时同时传递结果数据。
+    """
+    def __init__(self) -> None:
+        super().__init__()
+        self.return_value = None
+
+    def terminate(self, return_value):
+        """
+        终止事件并设置返回值
+
+        参数:
+            return_value: 事件完成时要返回的值
+        """
+        self.return_value = return_value
+        self.set()
+
+    def wait_and_get_result(self):
+        """
+        等待事件完成并获取结果
+
+        返回:
+            任意类型: 事件完成时设置的返回值
+        """
+        self.wait()
+        return self.return_value
+
+
+class AtomicQueue:
+
+    def __init__(self):
+        self.queue = Queue()
+
+    def put(self, item):
+        self.queue.put(item)
+
+    def put_nowait(self, item):
+        self.queue.put(item)
+
+    def get(self, timeout=600):
+        while self.queue.empty() and timeout > 0:
+            time.sleep(1)
+            timeout -= 1
+        if timeout <= 0:
+            raise TimeoutError("Queue get operation timed out")
+        return self.queue.get()
+
+
+class PythonMethod_AsyncConnectionMaintainer_AgentcraftInterface():
+    """
+    异步连接维护器接口类
+
+    负责维护WebSocket连接的核心类，处理消息队列的创建和管理，
+    以及维护与客户端的长连接通信。
+    """
+
+    def make_queue(self):
+        """
+        创建消息队列
+
+        创建三个异步队列用于不同类型的消息传输：
+        1. queue_back_to_client: 发送给客户端的消息队列
+        2. queue_realtime_from_client: 实时接收的客户端消息队列
+        3. queue_blocking_from_client: 阻塞式接收的客户端消息队列
+
+        返回:
+            tuple: 包含三个异步队列的元组
+        """
+        queue_back_to_client = asyncio.Queue()
+        queue_realtime_from_client = asyncio.Queue()
+        queue_blocking_from_client = AtomicQueue()
+        terminate_event = asyncio.Event()
+        return queue_back_to_client, queue_realtime_from_client, queue_blocking_from_client, terminate_event
+
+    async def maintain_connection_forever(self, initial_msg: UserInterfaceMsg, websocket: WebSocket, client_id: str):
+        """
+        永久维护WebSocket连接
+
+        处理与客户端的持续连接，包括消息的发送和接收。
+        创建独立的任务处理消息发送和接收，并启动聊天处理线程。
+
+        参数:
+            initial_msg: 初始消息
+            websocket: WebSocket连接对象
+            client_id: 客户端标识符
+        """
+
+        async def wait_message_to_send(queue_back_to_client: asyncio.Queue, terminate_event: asyncio.Event):
+            """
+            等待并发送消息到客户端
+
+            持续监听消息队列，将消息序列化后发送给客户端。
+
+            参数:
+                queue_back_to_client: 发送给客户端的消息队列
+            """
+            # 🕜 wait message to send away -> front end
+            msg_cnt = 0
+            try:
+                while True:
+
+                    ################
+                    # get message and check terminate
+                    while True:
+                        try:
+                            if terminate_event.is_set():
+                                msg = TERMINATE_MSG
+                                break
+                            else:
+                                msg: UserInterfaceMsg = await asyncio.wait_for(queue_back_to_client.get(), timeout=0.25)
+                                break
+                        except asyncio.TimeoutError:
+                            continue  # 继续检查条件
+                    if msg.function == TERMINATE_MSG.function:
+                        logger.info("Received terminate message, skip this message and stopping wait_message_to_send.")
+                        break
+                    ################
+
+
+                    msg_cnt += 1
+                    if websocket.application_state != WebSocketState.CONNECTED:
+                        break
+                    msg.special_kwargs['uuid'] = uuid.uuid4().hex
+                    print(msg)
+                    await websocket.send_bytes(msg.model_dump_json())
+            except Exception as e:
+                logger.exception(f"Error in wait_message_to_send: {e}")
+                raise e
+
+        async def receive_forever(queue_realtime_from_client: asyncio.Queue, queue_blocking_from_client: asyncio.Queue, queue_back_to_client: asyncio.Queue, terminate_event: asyncio.Event):
+            """
+            永久接收客户端消息
+
+            持续监听WebSocket连接，接收客户端消息并根据消息类型分发到不同队列。
+
+            参数:
+                queue_realtime_from_client: 实时消息队列
+                queue_blocking_from_client: 阻塞消息队列
+                queue_back_to_client: 发送回客户端的消息队列
+            """
+            # 🕜 keep listening traffic <- front end
+            msg_cnt:int = 0
+            try:
+                while True:
+                    ################
+                    # get message and check terminate
+                    while True:
+                        try:
+                            if terminate_event.is_set():
+                                msg = TERMINATE_MSG
+                                break
+                            else:
+                                message = await asyncio.wait_for(websocket.receive_text(), timeout=0.25)
+                                msg: UserInterfaceMsg = UserInterfaceMsg.model_validate_json(message)
+                                break
+                        except asyncio.TimeoutError:
+                            continue  # 继续检查条件
+                    if msg.function == TERMINATE_MSG.function:
+                        logger.info("Received terminate message, stopping receive_forever")
+                        break
+                    ################
+                    msg_cnt += 1
+                    logger.info(f"Received message {msg_cnt}: {msg}")
+                    queue_blocking_from_client.put_nowait(msg)
+
+
+            except Exception as e:
+                logger.exception(f"Error in receive_forever: {e}")
+                raise e
+
+        queue_back_to_client, queue_realtime_from_client, queue_blocking_from_client, terminate_event = self.make_queue()
+
+        def terminate_callback():
+            terminate_event.set()
+
+        def ensure_last_message_sent(queue_back_to_client):
+            """
+            确保最后一条消息被发送到客户端
+            """
+            queue_back_to_client.put_nowait(TERMINATE_MSG)
+            tic = time.time()
+            termination_timeout = 5  # seconds
+            while not queue_back_to_client.empty():
+                time.sleep(0.25)
+                if queue_back_to_client.empty():
+                    break
+                if time.time() - tic > termination_timeout:
+                    break
+
+        def task_wrapper(func):
+            def wrapper(*args, **kwargs):
+                res = func(*args, **kwargs)
+                ensure_last_message_sent(queue_back_to_client)
+                terminate_callback()
+                return res
+            return wrapper
+
+        t_x = asyncio.create_task(wait_message_to_send(queue_back_to_client, terminate_event))
+        t_r = asyncio.create_task(receive_forever(queue_realtime_from_client, queue_blocking_from_client, queue_back_to_client, terminate_event))
+        task_thread = threading.Thread(target=task_wrapper(task_executor), args=(initial_msg, queue_blocking_from_client, queue_back_to_client), daemon=True)
+        task_thread.start()
+
+        await t_x
+        await t_r
+        await websocket.close()
+
+
+
+class MasterMindWebSocketServer(PythonMethod_AsyncConnectionMaintainer_AgentcraftInterface):
+    """
+    WebSocket服务器主类
+
+    继承自异步连接维护器接口，实现了完整的WebSocket服务器功能。
+    负责处理客户端连接、事件管理和消息路由。
+    """
+
+    def __init__(self, host, port) -> None:
+        """
+        初始化WebSocket服务器
+
+        参数:
+            host: 服务器主机地址
+            port: 服务器端口号
+        """
+        self.websocket_connections = {}
+        self.agentcraft_interface_websocket_connections = {}
+        self._event_hub = {}
+        self.host= host
+        self.port = port
+        pass
+
+    def create_event(self, event_name: str):
+        """
+        创建一个新的事件
+
+        参数:
+            event_name: 事件名称
+
+        返回:
+            FutureEvent: 新创建的事件对象
+        """
+        self._event_hub[event_name] = FutureEvent()
+        return self._event_hub[event_name]
+
+    def terminate_event(self, event_name: str, msg:UserInterfaceMsg):
+        """
+        终止指定的事件并设置返回消息
+
+        参数:
+            event_name: 要终止的事件名称
+            msg: 要返回的用户界面消息
+        """
+        self._event_hub[event_name].terminate(return_value = msg)
+        return
+
+    async def long_task_01_wait_incoming_connection(self):
+        """
+        等待传入连接的长期任务
+
+        启动FastAPI服务器并等待WebSocket连接。
+        处理新的连接请求，建立WebSocket通信。
+        """
+        # task 1 wait incoming agent connection
+        logger.info("task 1 wait incoming agent connection")
+
+        async def launch_websocket_server():
+            """
+            启动WebSocket服务器
+
+            创建FastAPI应用并配置WebSocket路由，
+            设置服务器参数并启动uvicorn服务器。
+            """
+            app = FastAPI()
+
+            class UserInput(BaseModel):
+                main_input: str
+            @app.post("/predict_user_input")
+            async def predict_user_input(main_input: UserInput):
+                def predict_future_input(main_input):
+                    from request_llms.bridge_all import predict_no_ui_long_connection
+                    from toolbox import get_plugin_default_kwargs
+                    from textwrap import dedent
+                    com = get_plugin_default_kwargs()
+                    llm_kwargs = com['llm_kwargs']
+                    llm_kwargs['llm_model'] = 'one-api-glm-4-flash'
+                    completion_system_prompt = dedent("""Predict the next input that the user might type.
+                    1. Do not repeat the <current_input>. The <future_input> should be a continuation of <current_input>.
+                    2. Use same language as the input.
+                    3. Do not predict too far ahead.
+                    4. Use punctuation when needed. Sometimes <future_input> has to begin with some punctuation.
+
+                    Example:
+                    <current_input>北京发布暴</current_input>
+                    <future_input>雨红色预警</future_input>
+
+                    <current_input>世界是你们的，也是我们</current_input>
+                    <future_input>的，但是归根结底是你们的</future_input>
+
+                    <current_input>多年以后，面对行刑队</current_input>
+                    <future_input>，奥雷里亚诺·布恩迪亚上校将会回想起父亲带他去见识冰块的那个遥远的下午。</future_input>
+
+                    Format:
+                    <future_input>... the predicted input ...</future_input>
+                    """)
+                    main_input = "<current_input>" + main_input + "</current_input>"
+                    result = predict_no_ui_long_connection(
+                        inputs=main_input, llm_kwargs=llm_kwargs, sys_prompt=completion_system_prompt, history=[], console_silence=True
+                    )
+                    print(result)
+                    if "<future_input>" not in result or "</future_input>" not in result:
+                        raise ValueError("The response does not contain the expected future input format.")
+                    result = result.split("<future_input>")[-1].split("</future_input>")[0].strip()
+                    return result
+
+                return JSONResponse(content={'future':predict_future_input(main_input.main_input)})
+
+            @app.post("/core_functional")
+            async def core_functional():
+                import core_functional, importlib
+                importlib.reload(core_functional)    # 热更新prompt
+                core_functionals = core_functional.get_core_functions()
+                for k in list(core_functionals.keys()):
+                    v = core_functionals[k]
+                    # remove PreProcess if any
+                    if "PreProcess" in v:
+                        v.pop("PreProcess")
+                    if "Visible" in v and not v["Visible"]:
+                        core_functionals.pop(k)
+                return JSONResponse(content=core_functionals)
+
+            @app.post("/upload")
+            async def upload_files(files: List[UploadFile] = File(...)):
+                """上传文件接口，支持多文件上传并显示进度"""
+                from toolbox import on_file_uploaded
+                results = []
+                upload_dir = "uploads"
+
+                # 确保上传目录存在
+                if not os.path.exists(upload_dir):
+                    os.makedirs(upload_dir)
+
+                for file in files:
+                    try:
+                        # 构建文件保存路径
+                        file_path = os.path.join(upload_dir, file.filename)
+                        total_size = 0
+                        processed_size = 0
+
+                        # 分块读取并保存文件，同时计算进度
+                        with open(file_path, "wb") as buffer:
+                            while chunk := await file.read(8192):  # 8KB chunks
+                                buffer.write(chunk)
+                                processed_size += len(chunk)
+                                if file.size:  # 如果文件大小可用
+                                    progress = (processed_size / file.size) * 100
+                                    logger.info(f"Uploading {file.filename}: {progress:.2f}%")
+
+                        results.append({
+                            "filename": file.filename,
+                            "size": processed_size,
+                            "status": "success",
+                            "path": file_path
+                        })
+                    except Exception as e:
+                        results.append({
+                            "filename": file.filename,
+                            "status": "error",
+                            "error": str(e)
+                        })
+                        logger.error(f"Error uploading {file.filename}: {str(e)}")
+
+                return JSONResponse(content={
+                    "message": "Files uploaded successfully",
+                    "files": results
+                })
+
+            @app.websocket("/main")
+            async def main(websocket: WebSocket):
+                """
+                WebSocket连接的主处理函数
+
+                处理新的WebSocket连接请求，接收初始消息并建立持久连接。
+
+                参数:
+                    websocket: WebSocket连接对象
+                """
+                try:
+                    await websocket.accept()
+                    logger.info(f"WebSocket connection established: {websocket.client.host}:{websocket.client.port}")
+                    msg: UserInterfaceMsg = UserInterfaceMsg.model_validate_json(await websocket.receive_text())
+                    logger.info(msg)
+                    await self.maintain_connection_forever(msg, websocket, "client_id")
+                except:
+                    logger.exception("Error in WebSocket connection handler")
+                    await websocket.close()
+            import uvicorn
+            config = uvicorn.Config(app, host=self.host, port=self.port, log_level="error", ws_ping_interval=300, ws_ping_timeout=600)
+            server = uvicorn.Server(config)
+            logger.info(f"uvicorn begin, serving at ws://{self.host}:{self.port}/main")
+            await server.serve()
+
+        await launch_websocket_server()
+        logger.info("uvicorn terminated")
+
+if __name__ == "__main__":
+    mmwss = MasterMindWebSocketServer(host="0.0.0.0", port=38000)
+    asyncio.run(mmwss.long_task_01_wait_incoming_connection())

shared_utils/key_pattern_manager.py

@@ -79,6 +79,14 @@ def what_keys(keys):
 
     return f"检测到： OpenAI Key {avail_key_list['OpenAI Key']} 个, Azure Key {avail_key_list['Azure Key']} 个, API2D Key {avail_key_list['API2D Key']} 个"
 
+def is_o_family_for_openai(llm_model):
+    if not llm_model.startswith('o'):
+        return False
+    if llm_model in ['o1', 'o2', 'o3', 'o4', 'o5', 'o6', 'o7', 'o8']:
+        return True
+    if llm_model[:3] in ['o1-', 'o2-', 'o3-', 'o4-', 'o5-', 'o6-', 'o7-', 'o8-']:
+        return True
+    return False
 
 def select_api_key(keys, llm_model):
     import random
@@ -86,7 +94,7 @@ def select_api_key(keys, llm_model):
     key_list = keys.split(',')
 
     if llm_model.startswith('gpt-') or llm_model.startswith('chatgpt-') or \
-       llm_model.startswith('one-api-') or llm_model == 'o1' or llm_model.startswith('o1-'):
+       llm_model.startswith('one-api-') or is_o_family_for_openai(llm_model):
         for k in key_list:
             if is_openai_api_key(k): avail_key_list.append(k)
 

themes/common.css

@@ -332,3 +332,77 @@
     text-wrap: wrap;
     opacity: 0.8;
 }
+
+.raw_text {
+    display: none;
+}
+
+.message_tail {
+    justify-content: center;
+    align-items: center;
+}
+.message_tail_stop {
+    border: dotted !important;
+    margin-top: 5px !important;
+    padding-left: 8px !important;
+    padding-top: 1px !important;
+    padding-bottom: 1px !important;
+    padding-right: 12px !important;
+}
+
+/* ant 开始 */
+
+/* 通用按钮样式 */
+.ant-btn {
+    display: inline-flex;
+    align-items: center;
+    justify-content: center;
+    padding: 8px 16px;
+    font-size: 14px;
+    font-weight: bold;
+    border-radius: 4px;
+    cursor: pointer;
+    transition: background-color 0.3s;
+}
+
+/* 按钮颜色和状态 */
+.ant-btn-primary {
+    background-color: #1890ff;
+    color: white;
+    border: none;
+}
+
+.ant-btn-primary:hover {
+    background-color: #40a9ff;
+}
+
+.ant-btn-loading {
+    pointer-events: none;
+    opacity: 0.7;
+}
+
+/* 图标样式 */
+.ant-btn-icon {
+    display: inline-flex;
+    margin-right: 8px;
+}
+
+.anticon {
+    width: 1em;
+    height: 1em;
+    fill: currentColor;
+}
+
+.anticon-spin {
+    animation: spin 1s linear infinite;
+}
+
+/* 动画效果 */
+@keyframes spin {
+    from {
+        transform: rotate(0deg);
+    }
+    to {
+        transform: rotate(360deg);
+    }
+}

themes/common.js

@@ -259,7 +259,24 @@ function cancel_loading_status() {
 // -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
 //  第 2 部分: 复制按钮
 // -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+// 解压缩函数
+function decompressString(compressedString) {
+    // 第1步：Base64解码
+    const binaryString = atob(compressedString);
 
+    // 第2步：将二进制字符串转换为Uint8Array
+    const bytes = new Uint8Array(binaryString.length);
+    for (let i = 0; i < binaryString.length; i++) {
+        bytes[i] = binaryString.charCodeAt(i);
+    }
+
+    // 第3步：使用DecompressionStream (基于Web Streams API)进行gzip解压缩
+    const ds = new DecompressionStream('gzip');
+    const decompressedStream = new Response(new Blob([bytes])).body.pipeThrough(ds);
+
+    // 第4步：获取解压后的数据并转换为字符串
+    return new Response(decompressedStream).text();
+}
 
 var allow_auto_read_continously = true;
 var allow_auto_read_tts_flag = false;
@@ -272,7 +289,7 @@ function addCopyButton(botElement, index, is_last_in_arr) {
     const audioIcon = '<span><svg t="1713628577799" fill="currentColor" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="4587" width=".9em" height=".9em"><path d="M113.7664 540.4672c0-219.9552 178.2784-398.2336 398.2336-398.2336S910.2336 320.512 910.2336 540.4672v284.4672c0 31.4368-25.4976 56.9344-56.9344 56.9344h-56.9344c-31.4368 0-56.9344-25.4976-56.9344-56.9344V597.2992c0-31.4368 25.4976-56.9344 56.9344-56.9344h56.9344c0-188.5184-152.7808-341.2992-341.2992-341.2992S170.7008 351.9488 170.7008 540.4672h56.9344c31.4368 0 56.9344 25.4976 56.9344 56.9344v227.5328c0 31.4368-25.4976 56.9344-56.9344 56.9344h-56.9344c-31.4368 0-56.9344-25.4976-56.9344-56.9344V540.4672z" p-id="4588"></path></svg></span>';
     // const cancelAudioIcon = '<span><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" height=".8em" width=".8em" xmlns="http://www.w3.org/2000/svg"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"></rect><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"></path></svg></span>';
 
-    // 此功能没准备好
+    // audio functionality
     if (allow_auto_read_continously && is_last_in_arr && allow_auto_read_tts_flag) {
         process_latest_text_output(botElement.innerText, index);
     }
@@ -283,19 +300,21 @@ function addCopyButton(botElement, index, is_last_in_arr) {
         return;
     }
 
-    var copyButton = document.createElement('button');
-    copyButton.classList.add('copy-bot-btn');
-    copyButton.setAttribute('aria-label', 'Copy');
-    copyButton.innerHTML = copyIcon;
-    copyButton.addEventListener('click', async () => {
-        const textToCopy = botElement.innerText;
+    // 原始文本拷贝
+    var copyButtonOrig = document.createElement('button');
+    copyButtonOrig.classList.add('copy-bot-btn');
+    copyButtonOrig.setAttribute('aria-label', 'Copy');
+    copyButtonOrig.innerHTML = copyIcon;
+    copyButtonOrig.addEventListener('click', async () => {
         try {
+            const base64gzipcode = botElement.getElementsByClassName('raw_text')[0].innerText;
+            const textToCopy = await decompressString(base64gzipcode);
             // push_text_to_audio(textToCopy).catch(console.error);
             if ("clipboard" in navigator) {
                 await navigator.clipboard.writeText(textToCopy);
-                copyButton.innerHTML = copiedIcon;
+                copyButtonOrig.innerHTML = copiedIcon;
                 setTimeout(() => {
-                    copyButton.innerHTML = copyIcon;
+                    copyButtonOrig.innerHTML = copyIcon;
                 }, 1500);
             } else {
                 const textArea = document.createElement("textarea");
@@ -304,9 +323,9 @@ function addCopyButton(botElement, index, is_last_in_arr) {
                 textArea.select();
                 try {
                     document.execCommand('copy');
-                    copyButton.innerHTML = copiedIcon;
+                    copyButtonOrig.innerHTML = copiedIcon;
                     setTimeout(() => {
-                        copyButton.innerHTML = copyIcon;
+                        copyButtonOrig.innerHTML = copyIcon;
                     }, 1500);
                 } catch (error) {
                     console.error("Copy failed: ", error);
@@ -345,7 +364,8 @@ function addCopyButton(botElement, index, is_last_in_arr) {
 
     var messageBtnColumn = document.createElement('div');
     messageBtnColumn.classList.add('message-btn-row');
-    messageBtnColumn.appendChild(copyButton);
+    // messageBtnColumn.appendChild(copyButton);
+    messageBtnColumn.appendChild(copyButtonOrig);
     if (enable_tts) {
         messageBtnColumn.appendChild(audioButton);
     }
@@ -381,7 +401,6 @@ function do_something_but_not_too_frequently(min_interval, func) {
 
 
 function chatbotContentChanged(attempt = 1, force = false) {
-    // https://github.com/GaiZhenbiao/ChuanhuChatGPT/tree/main/web_assets/javascript
     for (var i = 0; i < attempt; i++) {
         setTimeout(() => {
             const messages = gradioApp().querySelectorAll('#gpt-chatbot .message-wrap .message.bot');
@@ -392,6 +411,9 @@ function chatbotContentChanged(attempt = 1, force = false) {
                 // Now pass both the message element and the is_last_in_arr boolean to addCopyButton
                 addCopyButton(message, index, is_last_in_arr);
 
+                // if last message, add stop btn link
+                addStopButton(message, index, is_last_in_arr);
+
                 // save_conversation_history
                 save_conversation_history_slow_down();
             });
@@ -402,6 +424,79 @@ function chatbotContentChanged(attempt = 1, force = false) {
 
 }
 
+function addStopButton(botElement, index, is_last_in_arr) {
+    function is_generating() {
+        var statePanelElement = document.getElementById("state-panel");
+        var generatingElement = statePanelElement.querySelector(".generating");
+        if (generatingElement) {
+            return true;
+        } else {
+            return false;
+        }
+    }
+    function on_stop_btn_click() {
+        let stopButton = document.getElementById("elem_stop");
+        stopButton.click();
+    }
+    function remove_stop_generate_btn(messageTailElement) {
+        // remove all child elements of messageTailElement
+        while (messageTailElement.firstChild) {
+            messageTailElement.removeChild(messageTailElement.firstChild);
+        }
+        messageTailElement.style.display = 'none';
+        messageTailElement.classList.add('removed');
+    }
+    function add_stop_generate_btn() {
+        // write here: add a beautiful stop btn `bottomElement` as child, when clicked execute on_stop_btn_click
+        console.log("get_gradio_component")
+        const bottomElement = document.createElement('button');
+        bottomElement.className = 'ant-btn ant-btn-primary';
+        bottomElement.innerHTML = `
+            <span class="ant-btn-icon">
+                <svg viewBox="64 64 896 896" focusable="false" data-icon="sync" width="1em" height="1em" fill="currentColor" aria-hidden="true" class="anticon anticon-sync anticon-spin">
+                <path d="M168 504.2c1-43.7 10-86.1 26.9-126 17.3-41 42.1-77.7 73.7-109.4S337 212.3 378 195c42.4-17.9 87.4-27 133.9-27s91.5 9.1 133.8 27A341.5 341.5 0 01755 268.8c9.9 9.9 19.2 20.4 27.8 31.4l-60.2 47a8 8 0 003 14.1l175.7 43c5 1.2 9.9-2.6 9.9-7.7l.8-180.9c0-6.7-7.7-10.5-12.9-6.3l-56.4 44.1C765.8 155.1 646.2 92 511.8 92 282.7 92 96.3 275.6 92 503.8a8 8 0 008 8.2h60c4.4 0 7.9-3.5 8-7.8zm756 7.8h-60c-4.4 0-7.9 3.5-8 7.8-1 43.7-10 86.1-26.9 126-17.3 41-42.1 77.8-73.7 109.4A342.45 342.45 0 01512.1 856a342.24 342.24 0 01-243.2-100.8c-9.9-9.9-19.2-20.4-27.8-31.4l60.2-47a8 8 0 00-3-14.1l-175.7-43c-5-1.2-9.9 2.6-9.9 7.7l-.7 181c0 6.7 7.7 10.5 12.9 6.3l56.4-44.1C258.2 868.9 377.8 932 512.2 932c229.2 0 415.5-183.7 419.8-411.8a8 8 0 00-8-8.2z"></path>
+                </svg>
+            </span>
+            <span>终止</span>
+        `;
+        bottomElement.classList.add('message_tail_stop');
+        bottomElement.addEventListener('click', on_stop_btn_click);
+        messageTailElement.appendChild(bottomElement);
+    }
+
+    // find a sub element of class `message_tail`
+    const messageTailElement = botElement.querySelector('.message_tail');
+    // if not is_last_in_arr, hide this elem (display none)
+    if (!messageTailElement) {
+        return;
+    }
+    if (messageTailElement.classList.contains('removed')) {
+        return;
+    }
+    if (!is_last_in_arr) {
+        remove_stop_generate_btn(messageTailElement);
+        return;
+    }
+    messageTailElement.style.display = 'flex';
+    const messageTailStopElem = messageTailElement.querySelector('.message_tail_stop');
+    if(!is_generating()) {
+        setTimeout(() => {
+            if(!is_generating()) {
+                remove_stop_generate_btn(messageTailElement);
+                return;
+            } else {
+                if (!messageTailStopElem) {
+                    add_stop_generate_btn()
+                }
+            }
+        }, 500);
+    } else {
+        if (!messageTailStopElem) {
+            add_stop_generate_btn()
+        }
+    }
+
+}
 
 
 // -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
@@ -1089,6 +1184,15 @@ async function clear_conversation(a, b, c) {
     update_conversation_metadata();
     let stopButton = document.getElementById("elem_stop");
     stopButton.click();
+    // Save back to local storage
+    try {
+        const EVENT_NAME = "gptac_reset_btn_clicked";
+        window.dispatchEvent(
+            new CustomEvent(EVENT_NAME, {
+                detail: ""
+            })
+        );
+    } catch (e) {}
     return reset_conversation(a, b);
 }
 

toolbox.py

@@ -37,6 +37,9 @@ from shared_utils.handle_upload import html_local_file
 from shared_utils.handle_upload import html_local_img
 from shared_utils.handle_upload import file_manifest_filter_type
 from shared_utils.handle_upload import extract_archive
+from shared_utils.context_clip_policy import clip_history
+from shared_utils.context_clip_policy import auto_context_clip_each_message
+from shared_utils.context_clip_policy import auto_context_clip_search_optimal
 from typing import List
 pj = os.path.join
 default_user_name = "default_user"
@@ -133,6 +136,9 @@ def ArgsGeneralWrapper(f):
             if len(args) == 0:  # 插件通道
                 yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, request)
             else:               # 对话通道，或者基础功能通道
+                # 基础对话通道，或者基础功能通道
+                if get_conf('AUTO_CONTEXT_CLIP_ENABLE'):
+                    txt_passon, history = auto_context_clip(txt_passon, history)
                 yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
         else:
             # 处理少数情况下的特殊插件的锁定状态
@@ -588,7 +594,7 @@ def on_report_generated(cookies:dict, files:List[str], chatbot:ChatBotWithCookie
         file_links += (
             f'<br/><a href="file={os.path.abspath(f)}" target="_blank">{f}</a>'
         )
-    chatbot.append(["报告如何远程获取？", f"报告已经添加到右侧“文件下载区”（可能处于折叠状态），请查收。{file_links}"])
+    chatbot.append([None, f"已经添加到右侧“文件下载区”（可能处于折叠状态），请查收。您也可以点击以下链接直接下载：{file_links}"])
     return cookies, report_files, chatbot
 
 
@@ -712,66 +718,14 @@ def run_gradio_in_subpath(demo, auth, port, custom_path):
     app = gr.mount_gradio_app(app, demo, path=custom_path)
     uvicorn.run(app, host="0.0.0.0", port=port)  # , auth=auth
 
-
-def clip_history(inputs, history, tokenizer, max_token_limit):
-    """
-    reduce the length of history by clipping.
-    this function search for the longest entries to clip, little by little,
-    until the number of token of history is reduced under threshold.
-    通过裁剪来缩短历史记录的长度。
-    此函数逐渐地搜索最长的条目进行剪辑，
-    直到历史记录的标记数量降低到阈值以下。
-    """
-    import numpy as np
-    from request_llms.bridge_all import model_info
-
-    def get_token_num(txt):
-        return len(tokenizer.encode(txt, disallowed_special=()))
-
-    input_token_num = get_token_num(inputs)
-
-    if max_token_limit < 5000:
-        output_token_expect = 256  # 4k & 2k models
-    elif max_token_limit < 9000:
-        output_token_expect = 512  # 8k models
+def auto_context_clip(current, history, policy='search_optimal'):
+    if policy == 'each_message':
+        return auto_context_clip_each_message(current, history)
+    elif policy == 'search_optimal':
+        return auto_context_clip_search_optimal(current, history)
     else:
-        output_token_expect = 1024  # 16k & 32k models
+        raise RuntimeError(f"未知的自动上下文裁剪策略: {policy}。")
 
-    if input_token_num < max_token_limit * 3 / 4:
-        # 当输入部分的token占比小于限制的3/4时，裁剪时
-        # 1. 把input的余量留出来
-        max_token_limit = max_token_limit - input_token_num
-        # 2. 把输出用的余量留出来
-        max_token_limit = max_token_limit - output_token_expect
-        # 3. 如果余量太小了，直接清除历史
-        if max_token_limit < output_token_expect:
-            history = []
-            return history
-    else:
-        # 当输入部分的token占比 > 限制的3/4时，直接清除历史
-        history = []
-        return history
-
-    everything = [""]
-    everything.extend(history)
-    n_token = get_token_num("\n".join(everything))
-    everything_token = [get_token_num(e) for e in everything]
-
-    # 截断时的颗粒度
-    delta = max(everything_token) // 16
-
-    while n_token > max_token_limit:
-        where = np.argmax(everything_token)
-        encoded = tokenizer.encode(everything[where], disallowed_special=())
-        clipped_encoded = encoded[: len(encoded) - delta]
-        everything[where] = tokenizer.decode(clipped_encoded)[
-            :-1
-        ]  # -1 to remove the may-be illegal char
-        everything_token[where] = get_token_num(everything[where])
-        n_token = get_token_num("\n".join(everything))
-
-    history = everything[1:]
-    return history
 
 
 """