block unstable

back
feat: 为predict函数添加文件和URL读取功能
2025-12-06 14:36:48 +00:00 · 2025-08-23 15:59:05 +08:00 · 2025-07-21 02:18:46 +08:00 · 2025-07-19 19:06:38 +08:00 · 2025-07-16 00:57:45 +08:00 · 2025-07-14 02:20:20 +08:00
--- a/.github/workflows/stale.yml
+++ b/.github/workflows/stale.yml
@@ -7,7 +7,7 @@
 name: 'Close stale issues and PRs'
 on:
  schedule:
-    - cron: '*/5 * * * *'
+    - cron: '*/30 * * * *'

 jobs:
  stale:
@@ -19,7 +19,6 @@ jobs:
    steps:
      - uses: actions/stale@v8
        with:
-          stale-issue-message: 'This issue is stale because it has been open 100 days with no activity. Remove stale label or comment or this will be closed in 1 days.'
+          stale-issue-message: 'This issue is stale because it has been open 100 days with no activity. Remove stale label or comment or this will be closed in 7 days.'
          days-before-stale: 100
-          days-before-close: 1
-          debug-only: true
+          days-before-close: 7
--- a/.gitignore
+++ b/.gitignore
@@ -163,3 +163,5 @@ objdump*
 TODO
 experimental_mods
 search_results
+gg.docx
+unstructured_reader.py
--- a/27
+++ b/27
@@ -3,37 +3,38 @@
 # - 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
+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()'

-# 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()'
-
+ENV CGO_ENABLED=0

 # 启动（必要）
-CMD ["python3", "-u", "main.py"]
+CMD ["bash", "-c", "python main.py"]
--- a/README.md
+++ b/README.md
@@ -1,12 +1,14 @@
 > [!IMPORTANT]
+> `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  
 >
-> 2024.10.10: 突发停电，紧急恢复了提供[whl包](https://drive.google.com/file/d/19U_hsLoMrjOlQSzYS3pzWX9fTzyusArP/view?usp=sharing)的文件服务器  
-> 2024.10.8: 版本3.90加入对llama-index的初步支持，版本3.80加入插件二级菜单功能（详见wiki）  
+> 2025.2.2: 三分钟快速接入最强qwen2.5-max[视频](https://www.bilibili.com/video/BV1LeFuerEG4)  
+> 2025.2.1: 支持自定义字体  
+> 2024.10.10: 突发停电，紧急恢复了提供[whl包](https://drive.google.com/drive/folders/14kR-3V-lIbvGxri4AHc8TpiA1fqsw7SK?usp=sharing)的文件服务器  
 > 2024.5.1: 加入Doc2x翻译PDF论文的功能，[查看详情](https://github.com/binary-husky/gpt_academic/wiki/Doc2x)  
 > 2024.3.11: 全力支持Qwen、GLM、DeepseekCoder等中文大语言模型！ SoVits语音克隆模块，[查看详情](https://www.bilibili.com/video/BV1Rp421S7tF/) 
-> 2024.1.17: 安装依赖时，请选择`requirements.txt`中**指定的版本**。 安装命令：`pip install -r requirements.txt`。本项目完全开源免费，您可通过订阅[在线服务](https://github.com/binary-husky/gpt_academic/wiki/online)的方式鼓励本项目的发展。
+> 2024.1.17: 安装依赖时，请选择`requirements.txt`中**指定的版本**。 安装命令：`pip install -r requirements.txt`。

 <br>

@@ -127,20 +129,20 @@ Latex论文一键校对 | [插件] 仿Grammarly对Latex文章进行语法、拼

 ```mermaid
 flowchart TD
-    A{"安装方法"} --> W1("I. 🔑直接运行 (Windows, Linux or MacOS)")
-    W1 --> W11["1. Python pip包管理依赖"]
-    W1 --> W12["2. Anaconda包管理依赖（推荐⭐）"]
+    A{"安装方法"} --> W1("I 🔑直接运行 (Windows, Linux or MacOS)")
+    W1 --> W11["1 Python pip包管理依赖"]
+    W1 --> W12["2 Anaconda包管理依赖（推荐⭐）"]

-    A --> W2["II. 🐳使用Docker (Windows, Linux or MacOS)"]
+    A --> W2["II 🐳使用Docker (Windows, Linux or MacOS)"]

-    W2 --> k1["1. 部署项目全部能力的大镜像（推荐⭐）"]
-    W2 --> k2["2. 仅在线模型（GPT, GLM4等）镜像"]
-    W2 --> k3["3. 在线模型 + Latex的大镜像"]
+    W2 --> k1["1 部署项目全部能力的大镜像（推荐⭐）"]
+    W2 --> k2["2 仅在线模型（GPT, GLM4等）镜像"]
+    W2 --> k3["3 在线模型 + Latex的大镜像"]

-    A --> W4["IV. 🚀其他部署方法"]
-    W4 --> C1["1. Windows/MacOS 一键安装运行脚本（推荐⭐）"]
-    W4 --> C2["2. Huggingface, Sealos远程部署"]
-    W4 --> C4["3. ... 其他 ..."]
+    A --> W4["IV 🚀其他部署方法"]
+    W4 --> C1["1 Windows/MacOS 一键安装运行脚本（推荐⭐）"]
+    W4 --> C2["2 Huggingface, Sealos远程部署"]
+    W4 --> C4["3 其他 ..."]
 ```

 ### 安装方法I：直接运行 (Windows, Linux or MacOS)
@@ -426,7 +428,6 @@ timeline LR
 1. `master` 分支: 主分支，稳定版
 2. `frontier` 分支: 开发分支，测试版
 3. 如何[接入其他大模型](request_llms/README.md)
-4. 访问GPT-Academic的[在线服务并支持我们](https://github.com/binary-husky/gpt_academic/wiki/online)

 ### V：参考与学习

--- a/check_proxy.py
+++ b/check_proxy.py
@@ -230,6 +230,48 @@ def warm_up_modules():
        enc.encode("模块预热", disallowed_special=())
        enc = model_info["gpt-4"]['tokenizer']
        enc.encode("模块预热", disallowed_special=())
+        try_warm_up_vectordb()
+
+
+# def try_warm_up_vectordb():
+#     try:
+#         import os
+#         import nltk
+#         target = os.path.expanduser('~/nltk_data')
+#         logger.info(f'模块预热: nltk punkt (从Github下载部分文件到 {target})')
+#         nltk.data.path.append(target)
+#         nltk.download('punkt', download_dir=target)
+#         logger.info('模块预热完成: nltk punkt')
+#     except:
+#         logger.exception('模块预热: nltk punkt 失败，可能需要手动安装 nltk punkt')
+#         logger.error('模块预热: nltk punkt 失败，可能需要手动安装 nltk punkt')
+
+
+def try_warm_up_vectordb():
+    import os
+    import nltk
+    target = os.path.expanduser('~/nltk_data')
+    nltk.data.path.append(target)
+    try:
+        # 尝试加载 punkt
+        logger.info(f'nltk模块预热')
+        nltk.data.find('tokenizers/punkt')
+        nltk.data.find('tokenizers/punkt_tab')
+        nltk.data.find('taggers/averaged_perceptron_tagger_eng')
+        logger.info('nltk模块预热完成（读取本地缓存）')
+    except:
+        # 如果找不到，则尝试下载
+        try:
+            logger.info(f'模块预热: nltk punkt (从 Github 下载部分文件到 {target})')
+            from shared_utils.nltk_downloader import Downloader
+            _downloader = Downloader()
+            _downloader.download('punkt', download_dir=target)
+            _downloader.download('punkt_tab', download_dir=target)
+            _downloader.download('averaged_perceptron_tagger_eng', download_dir=target)
+            logger.info('nltk模块预热完成')
+        except Exception:
+            logger.exception('模块预热: nltk punkt 失败，可能需要手动安装 nltk punkt')
+

 def warm_up_vectordb():
    """
--- a/config.py
+++ b/config.py
@@ -7,11 +7,16 @@
    Configuration reading priority: environment variable > config_private.py > config.py
 """

-# [step 1]>> 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 = "此处填API密钥"    # 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 1-1]>> ( 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]>> ( 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 2]>> 改为True应用代理，如果直接在海外服务器部署，此处不修改；如果使用本地或无地域限制的大模型时，此处也不需要修改
+# [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 = ""
+
+# [step 2]>> 改为True应用代理。如果使用本地或无地域限制的大模型时，此处不修改；如果直接在海外服务器部署，此处不修改
 USE_PROXY = False
 if USE_PROXY:
    """
@@ -32,11 +37,16 @@ else:

 # [step 3]>> 模型选择是 (注意: LLM_MODEL是默认选中的模型, 它*必须*被包含在AVAIL_LLM_MODELS列表中 )
 LLM_MODEL = "gpt-3.5-turbo-16k" # 可选 ↓↓↓
-AVAIL_LLM_MODELS = ["gpt-4-1106-preview", "gpt-4-turbo-preview", "gpt-4-vision-preview",
+AVAIL_LLM_MODELS = ["qwen-max", "o1-mini", "o1-mini-2024-09-12", "o1", "o1-2024-12-17", "o1-preview", "o1-preview-2024-09-12",
+                    "gpt-4-1106-preview", "gpt-4-turbo-preview", "gpt-4-vision-preview",
                    "gpt-4o", "gpt-4o-mini", "gpt-4-turbo", "gpt-4-turbo-2024-04-09",
                    "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"
+                    "gemini-1.5-pro", "chatglm3", "chatglm4",
+                    "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"
@@ -47,7 +57,7 @@ EMBEDDING_MODEL = "text-embedding-3-small"
 #   "glm-4-0520", "glm-4-air", "glm-4-airx", "glm-4-flash",
 #   "qianfan", "deepseekcoder",
 #   "spark", "sparkv2", "sparkv3", "sparkv3.5", "sparkv4",
-#   "qwen-turbo", "qwen-plus", "qwen-max", "qwen-local",
+#   "qwen-turbo", "qwen-plus", "qwen-local",
 #   "moonshot-v1-128k", "moonshot-v1-32k", "moonshot-v1-8k",
 #   "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", "gpt-3.5-turbo-0125", "gpt-4o-2024-05-13"
 #   "claude-3-haiku-20240307","claude-3-sonnet-20240229","claude-3-opus-20240229", "claude-2.1", "claude-instant-1.2",
@@ -74,7 +84,7 @@ API_URL_REDIRECT = {}

 # 多线程函数插件中，默认允许多少路线程同时访问OpenAI。Free trial users的限制是每分钟3次，Pay-as-you-go users的限制是每分钟3500次
 # 一言以蔽之：免费（5刀）用户填3，OpenAI绑了信用卡的用户可以填 16 或者更高。提高限制请查询：https://platform.openai.com/docs/guides/rate-limits/overview
-DEFAULT_WORKER_NUM = 3
+DEFAULT_WORKER_NUM = 8


 # 色彩主题, 可选 ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast"]
@@ -82,6 +92,31 @@ DEFAULT_WORKER_NUM = 3
 THEME = "Default"
 AVAIL_THEMES = ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast", "Gstaff/Xkcd", "NoCrypt/Miku"]

+FONT = "Theme-Default-Font"
+AVAIL_FONTS = [
+    "默认值(Theme-Default-Font)",
+    "宋体(SimSun)",
+    "黑体(SimHei)",
+    "楷体(KaiTi)",
+    "仿宋(FangSong)",
+    "华文细黑(STHeiti Light)",
+    "华文楷体(STKaiti)",
+    "华文仿宋(STFangsong)",
+    "华文宋体(STSong)",
+    "华文中宋(STZhongsong)",
+    "华文新魏(STXinwei)",
+    "华文隶书(STLiti)",
+    # 备注：以下字体需要网络支持，您可以自定义任意您喜欢的字体，如下所示，需要满足的格式为 "字体昵称(字体英文真名@字体css下载链接)"
+    "思源宋体(Source Han Serif CN VF@https://chinese-fonts-cdn.deno.dev/packages/syst/dist/SourceHanSerifCN/result.css)",
+    "月星楷(Moon Stars Kai HW@https://chinese-fonts-cdn.deno.dev/packages/moon-stars-kai/dist/MoonStarsKaiHW-Regular/result.css)",
+    "珠圆体(MaokenZhuyuanTi@https://chinese-fonts-cdn.deno.dev/packages/mkzyt/dist/猫啃珠圆体/result.css)",
+    "平方萌萌哒(PING FANG MENG MNEG DA@https://chinese-fonts-cdn.deno.dev/packages/pfmmd/dist/平方萌萌哒/result.css)",
+    "Helvetica",
+    "ui-sans-serif",
+    "sans-serif",
+    "system-ui"
+]
+

 # 默认的系统提示词（system prompt）
 INIT_SYS_PROMPT = "Serve me as a writing and programming assistant."
@@ -133,10 +168,6 @@ MULTI_QUERY_LLM_MODELS = "gpt-3.5-turbo&chatglm3"
 QWEN_LOCAL_MODEL_SELECTION = "Qwen/Qwen-1_8B-Chat-Int8"


-# 接入通义千问在线大模型 https://dashscope.console.aliyun.com/
-DASHSCOPE_API_KEY = "" # 阿里灵积云API_KEY
-
-
 # 百度千帆（LLM_MODEL="qianfan"）
 BAIDU_CLOUD_API_KEY = ''
 BAIDU_CLOUD_SECRET_KEY = ''
@@ -238,8 +269,9 @@ MOONSHOT_API_KEY = ""
 # 零一万物(Yi Model) API KEY
 YIMODEL_API_KEY = ""

-# 深度求索(DeepSeek) API KEY，默认请求地址为"https://api.deepseek.com/v1/chat/completions"
-DEEPSEEK_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
@@ -303,7 +335,7 @@ ARXIV_CACHE_DIR = "gpt_log/arxiv_cache"


 # 除了连接OpenAI之外，还有哪些场合允许使用代理，请尽量不要修改
-WHEN_TO_USE_PROXY = ["Download_LLM", "Download_Gradio_Theme", "Connect_Grobid",
+WHEN_TO_USE_PROXY = ["Connect_OpenAI", "Download_LLM", "Download_Gradio_Theme", "Connect_Grobid",
                     "Warmup_Modules", "Nougat_Download", "AutoGen", "Connect_OpenAI_Embedding"]


@@ -319,6 +351,23 @@ NUM_CUSTOM_BASIC_BTN = 4
 DAAS_SERVER_URLS = [ f"https://niuziniu-biligpt{i}.hf.space/stream" for i in range(1,5) ]


+# 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 = ""
+
+
+# SEMANTIC SCHOLAR API KEY
+SEMANTIC_SCHOLAR_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 ---------------
--- a/crazy_functional.py
+++ b/crazy_functional.py
@@ -50,6 +50,9 @@ def get_crazy_functions():
    from crazy_functions.SourceCode_Comment import 注释Python项目
    from crazy_functions.SourceCode_Comment_Wrap import SourceCodeComment_Wrap
    from crazy_functions.VideoResource_GPT import 多媒体任务
+    from crazy_functions.Document_Conversation import 批量文件询问
+    from crazy_functions.Document_Conversation_Wrap import Document_Conversation_Wrap
+

    function_plugins = {
        "多媒体智能体": {
@@ -113,7 +116,7 @@ def get_crazy_functions():
            "Group": "学术",
            "Color": "stop",
            "AsButton": True,
-            "Info": "Arixv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
+            "Info": "ArXiv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
            "Function": HotReload(Latex翻译中文并重新编译PDF),  # 当注册Class后，Function旧接口仅会在“虚空终端”中起作用
            "Class": Arxiv_Localize,    # 新一代插件需要注册Class
        },
@@ -352,7 +355,7 @@ def get_crazy_functions():
            "ArgsReminder": r"如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 "
                            r"例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: "
                            r'If the term "agent" is used in this section, it should be translated to "智能体". ',
-            "Info": "Arixv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
+            "Info": "ArXiv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
            "Function": HotReload(Latex翻译中文并重新编译PDF),  # 当注册Class后，Function旧接口仅会在“虚空终端”中起作用
            "Class": Arxiv_Localize,    # 新一代插件需要注册Class
        },
@@ -378,7 +381,16 @@ def get_crazy_functions():
            "Info": "PDF翻译中文，并重新编译PDF | 输入参数为路径",
            "Function": HotReload(PDF翻译中文并重新编译PDF),   # 当注册Class后，Function旧接口仅会在“虚空终端”中起作用
            "Class": PDF_Localize   # 新一代插件需要注册Class
-        }
+        },
+        "批量文件询问 (支持自定义总结各种文件)": {
+            "Group": "学术",
+            "Color": "stop",
+            "AsButton": False,
+            "AdvancedArgs": False,
+            "Info": "先上传文件，点击此按钮，进行提问",
+            "Function": HotReload(批量文件询问),
+            "Class": Document_Conversation_Wrap,
+        },
    }

    function_plugins.update(
@@ -414,8 +426,6 @@ def get_crazy_functions():



-
-    # -=--=- 尚未充分测试的实验性插件 & 需要额外依赖的插件 -=--=-
    try:
        from crazy_functions.下载arxiv论文翻译摘要 import 下载arxiv论文并翻译摘要

@@ -434,36 +444,6 @@ def get_crazy_functions():
        logger.error(trimmed_format_exc())
        logger.error("Load function plugin failed")

-    # try:
-    #     from crazy_functions.联网的ChatGPT import 连接网络回答问题
-
-    #     function_plugins.update(
-    #         {
-    #             "连接网络回答问题（输入问题后点击该插件，需要访问谷歌）": {
-    #                 "Group": "对话",
-    #                 "Color": "stop",
-    #                 "AsButton": False,  # 加入下拉菜单中
-    #                 # "Info": "连接网络回答问题（需要访问谷歌）| 输入参数是一个问题",
-    #                 "Function": HotReload(连接网络回答问题),
-    #             }
-    #         }
-    #     )
-    #     from crazy_functions.联网的ChatGPT_bing版 import 连接bing搜索回答问题
-
-    #     function_plugins.update(
-    #         {
-    #             "连接网络回答问题（中文Bing版，输入问题后点击该插件）": {
-    #                 "Group": "对话",
-    #                 "Color": "stop",
-    #                 "AsButton": False,  # 加入下拉菜单中
-    #                 "Info": "连接网络回答问题（需要访问中文Bing）| 输入参数是一个问题",
-    #                 "Function": HotReload(连接bing搜索回答问题),
-    #             }
-    #         }
-    #     )
-    # except:
-    #     logger.error(trimmed_format_exc())
-    #     logger.error("Load function plugin failed")

    try:
        from crazy_functions.SourceCode_Analyse import 解析任意code项目
@@ -674,22 +654,21 @@ def get_crazy_functions():
        logger.error(trimmed_format_exc())
        logger.error("Load function plugin failed")

-    try:
-        from crazy_functions.多智能体 import 多智能体终端
-
-        function_plugins.update(
-            {
-                "AutoGen多智能体终端（仅供测试）": {
-                    "Group": "智能体",
-                    "Color": "stop",
-                    "AsButton": False,
-                    "Function": HotReload(多智能体终端),
-                }
-            }
-        )
-    except:
-        logger.error(trimmed_format_exc())
-        logger.error("Load function plugin failed")
+    # try:
+    #     from crazy_functions.多智能体 import 多智能体终端
+    #     function_plugins.update(
+    #         {
+    #             "AutoGen多智能体终端（仅供测试）": {
+    #                 "Group": "智能体",
+    #                 "Color": "stop",
+    #                 "AsButton": False,
+    #                 "Function": HotReload(多智能体终端),
+    #             }
+    #         }
+    #     )
+    # except:
+    #     logger.error(trimmed_format_exc())
+    #     logger.error("Load function plugin failed")

    try:
        from crazy_functions.互动小游戏 import 随机小游戏
@@ -726,6 +705,44 @@ def get_crazy_functions():
        logger.error(trimmed_format_exc())
        logger.error("Load function plugin failed")

+    # try:
+    #     from crazy_functions.Document_Optimize import 自定义智能文档处理
+    #     function_plugins.update(
+    #         {
+    #             "一键处理文档（支持自定义全文润色、降重等）": {
+    #                 "Group": "学术",
+    #                 "Color": "stop",
+    #                 "AsButton": False,
+    #                 "AdvancedArgs": True,
+    #                 "ArgsReminder": "请输入处理指令和要求（可以详细描述），如：请帮我润色文本，要求幽默点。默认调用润色指令。",
+    #                 "Info": "保留文档结构，智能处理文档内容 | 输入参数为文件路径",
+    #                 "Function": HotReload(自定义智能文档处理)
+    #             },
+    #         }
+    #     )
+    # except:
+    #     logger.error(trimmed_format_exc())
+    #     logger.error("Load function plugin failed")
+
+
+
+    # try:
+    #     from crazy_functions.Paper_Reading import 快速论文解读
+    #     function_plugins.update(
+    #         {
+    #             "速读论文": {
+    #                 "Group": "学术",
+    #                 "Color": "stop",
+    #                 "AsButton": False,
+    #                 "Info": "上传一篇论文进行快速分析和解读 |  输入参数为论文路径或DOI/arXiv ID",
+    #                 "Function": HotReload(快速论文解读),
+    #             },
+    #         }
+    #     )
+    # except:
+    #     logger.error(trimmed_format_exc())
+    #     logger.error("Load function plugin failed")
+

    # try:
    #     from crazy_functions.高级功能函数模板 import 测试图表渲染
@@ -771,12 +788,15 @@ def get_multiplex_button_functions():
        "常规对话":
            "",

-        "多模型对话": 
+        "查互联网后回答":
+            "查互联网后回答",
+
+        "多模型对话":
            "询问多个GPT模型", # 映射到上面的 `询问多个GPT模型` 插件

-        "智能召回 RAG": 
+        "智能召回 RAG":
            "Rag智能召回", # 映射到上面的 `Rag智能召回` 插件

-        "多媒体查询": 
+        "多媒体查询":
            "多媒体智能体", # 映射到上面的 `多媒体智能体` 插件
    }
--- a/crazy_functions/Academic_Conversation.py
+++ b/crazy_functions/Academic_Conversation.py
@@ -0,0 +1,290 @@
+import re
+import os
+import asyncio
+from typing import List, Dict, Tuple
+from dataclasses import dataclass
+from textwrap import dedent
+from toolbox import CatchException, get_conf, update_ui, promote_file_to_downloadzone, get_log_folder, get_user
+from toolbox import update_ui, CatchException, report_exception, write_history_to_file
+from crazy_functions.review_fns.data_sources.semantic_source import SemanticScholarSource
+from crazy_functions.review_fns.data_sources.arxiv_source import ArxivSource
+from crazy_functions.review_fns.query_analyzer import QueryAnalyzer
+from crazy_functions.review_fns.handlers.review_handler import 文献综述功能
+from crazy_functions.review_fns.handlers.recommend_handler import 论文推荐功能
+from crazy_functions.review_fns.handlers.qa_handler import 学术问答功能
+from crazy_functions.review_fns.handlers.paper_handler import 单篇论文分析功能
+from crazy_functions.Conversation_To_File import write_chat_to_file
+from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+from crazy_functions.review_fns.handlers.latest_handler import Arxiv最新论文推荐功能
+from datetime import datetime
+
+@CatchException
+def 学术对话(txt: str, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List,
+           history: List, system_prompt: str, user_request: str):
+    """主函数"""
+
+    # 初始化数据源
+    arxiv_source = ArxivSource()
+    semantic_source = SemanticScholarSource(
+        api_key=get_conf("SEMANTIC_SCHOLAR_KEY")
+    )
+
+    # 初始化处理器
+    handlers = {
+        "review": 文献综述功能(arxiv_source, semantic_source, llm_kwargs),
+        "recommend": 论文推荐功能(arxiv_source, semantic_source, llm_kwargs),
+        "qa": 学术问答功能(arxiv_source, semantic_source, llm_kwargs),
+        "paper": 单篇论文分析功能(arxiv_source, semantic_source, llm_kwargs),
+        "latest": Arxiv最新论文推荐功能(arxiv_source, semantic_source, llm_kwargs),
+    }
+
+    # 分析查询意图
+    chatbot.append([None, "正在分析研究主题和查询要求..."])
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    query_analyzer = QueryAnalyzer()
+    search_criteria = yield from query_analyzer.analyze_query(txt, chatbot, llm_kwargs)
+    handler = handlers.get(search_criteria.query_type)
+    if not handler:
+        handler = handlers["qa"]  # 默认使用QA处理器
+
+    # 处理查询
+    chatbot.append([None, f"使用{handler.__class__.__name__}处理...，可能需要您耐心等待3～5分钟..."])
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    final_prompt = asyncio.run(handler.handle(
+        criteria=search_criteria,
+        chatbot=chatbot,
+        history=history,
+        system_prompt=system_prompt,
+        llm_kwargs=llm_kwargs,
+        plugin_kwargs=plugin_kwargs
+    ))
+
+    if final_prompt:
+        # 检查是否是道歉提示
+        if "很抱歉，我们未能找到" in final_prompt:
+            chatbot.append([txt, final_prompt])
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+        # 在 final_prompt 末尾添加用户原始查询要求
+        final_prompt += dedent(f"""
+        Original user query: "{txt}"
+
+        IMPORTANT NOTE :
+        - Your response must directly address the user's original user query above
+        - While following the previous guidelines, prioritize answering what the user specifically asked
+        - Make sure your response format and content align with the user's expectations
+        - Do not translate paper titles, keep them in their original language
+        - Do not generate a reference list in your response - references will be handled separately
+        """)
+
+        # 使用最终的prompt生成回答
+        response = yield from request_gpt_model_in_new_thread_with_ui_alive(
+            inputs=final_prompt,
+            inputs_show_user=txt,
+            llm_kwargs=llm_kwargs,
+            chatbot=chatbot,
+            history=[],
+            sys_prompt=f"You are a helpful academic assistant. Response in Chinese by default unless specified language is required in the user's query."
+        )
+
+        # 1. 获取文献列表
+        papers_list = handler.ranked_papers  # 直接使用原始论文数据
+
+        # 在新的对话中添加格式化的参考文献列表
+        if papers_list:
+            references = ""
+            for idx, paper in enumerate(papers_list, 1):
+                # 构建作者列表
+                authors = paper.authors[:3]
+                if len(paper.authors) > 3:
+                    authors.append("et al.")
+                authors_str = ", ".join(authors)
+
+                # 构建期刊指标信息
+                metrics = []
+                if hasattr(paper, 'if_factor') and paper.if_factor:
+                    metrics.append(f"IF: {paper.if_factor}")
+                if hasattr(paper, 'jcr_division') and paper.jcr_division:
+                    metrics.append(f"JCR: {paper.jcr_division}")
+                if hasattr(paper, 'cas_division') and paper.cas_division:
+                    metrics.append(f"中科院分区: {paper.cas_division}")
+                metrics_str = f" [{', '.join(metrics)}]" if metrics else ""
+
+                # 构建DOI链接
+                doi_link = ""
+                if paper.doi:
+                    if "arxiv.org" in str(paper.doi):
+                        doi_url = paper.doi
+                    else:
+                        doi_url = f"https://doi.org/{paper.doi}"
+                    doi_link = f" <a href='{doi_url}' target='_blank'>DOI: {paper.doi}</a>"
+
+                # 构建完整的引用
+                reference = f"[{idx}] {authors_str}. *{paper.title}*"
+                if paper.venue_name:
+                    reference += f". {paper.venue_name}"
+                if paper.year:
+                    reference += f", {paper.year}"
+                reference += metrics_str
+                if doi_link:
+                    reference += f".{doi_link}"
+                reference += "  \n"
+
+                references += reference
+
+            # 添加新的对话显示参考文献
+            chatbot.append(["参考文献如下：", references])
+            yield from update_ui(chatbot=chatbot, history=history)
+
+
+        # 2. 保存为不同格式
+        from .review_fns.conversation_doc.word_doc import WordFormatter
+        from .review_fns.conversation_doc.word2pdf import WordToPdfConverter
+        from .review_fns.conversation_doc.markdown_doc import MarkdownFormatter
+        from .review_fns.conversation_doc.html_doc import HtmlFormatter
+
+        # 创建保存目录
+        save_dir =  get_log_folder(get_user(chatbot),  plugin_name='chatscholar')
+
+        if not os.path.exists(save_dir):
+            os.makedirs(save_dir)
+
+        # 生成文件名
+        def get_safe_filename(txt, max_length=10):
+            # 获取文本前max_length个字符作为文件名
+            filename = txt[:max_length].strip()
+            # 移除不安全的文件名字符
+            filename = re.sub(r'[\\/:*?"<>|]', '', filename)
+            # 如果文件名为空，使用时间戳
+            if not filename:
+                filename = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
+            return filename
+
+        base_filename = get_safe_filename(txt)
+
+        result_files = []  # 收集所有生成的文件
+        pdf_path = None  # 用于跟踪PDF是否成功生成
+
+        # 保存为Markdown
+        try:
+            md_formatter = MarkdownFormatter()
+            md_content = md_formatter.create_document(txt, response, papers_list)
+            result_file_md = write_history_to_file(
+                history=[md_content],
+                file_basename=f"markdown_{base_filename}.md"
+            )
+            result_files.append(result_file_md)
+        except Exception as e:
+            print(f"Markdown保存失败: {str(e)}")
+
+        # 保存为HTML
+        try:
+            html_formatter = HtmlFormatter()
+            html_content = html_formatter.create_document(txt, response, papers_list)
+            result_file_html = write_history_to_file(
+                history=[html_content],
+                file_basename=f"html_{base_filename}.html"
+            )
+            result_files.append(result_file_html)
+        except Exception as e:
+            print(f"HTML保存失败: {str(e)}")
+
+        # 保存为Word
+        try:
+            word_formatter = WordFormatter()
+            try:
+                doc = word_formatter.create_document(txt, response, papers_list)
+            except Exception as e:
+                print(f"Word文档内容生成失败: {str(e)}")
+                raise e
+
+            try:
+                result_file_docx = os.path.join(
+                    os.path.dirname(result_file_md) if result_file_md else save_dir,
+                    f"docx_{base_filename}.docx"
+                )
+                doc.save(result_file_docx)
+                result_files.append(result_file_docx)
+                print(f"Word文档已保存到: {result_file_docx}")
+
+                # 转换为PDF
+                try:
+                    pdf_path = WordToPdfConverter.convert_to_pdf(result_file_docx)
+                    if pdf_path:
+                        result_files.append(pdf_path)
+                        print(f"PDF文档已生成: {pdf_path}")
+                except Exception as e:
+                    print(f"PDF转换失败: {str(e)}")
+
+            except Exception as e:
+                print(f"Word文档保存失败: {str(e)}")
+                raise e
+
+        except Exception as e:
+            print(f"Word格式化失败: {str(e)}")
+            import traceback
+            print(f"详细错误信息: {traceback.format_exc()}")
+
+        # 保存为BibTeX格式
+        try:
+            from .review_fns.conversation_doc.reference_formatter import ReferenceFormatter
+            ref_formatter = ReferenceFormatter()
+            bibtex_content = ref_formatter.create_document(papers_list)
+
+            # 在与其他文件相同目录下创建BibTeX文件
+            result_file_bib = os.path.join(
+                os.path.dirname(result_file_md) if result_file_md else save_dir,
+                f"references_{base_filename}.bib"
+            )
+
+            # 直接写入文件
+            with open(result_file_bib, 'w', encoding='utf-8') as f:
+                f.write(bibtex_content)
+
+            result_files.append(result_file_bib)
+            print(f"BibTeX文件已保存到: {result_file_bib}")
+        except Exception as e:
+            print(f"BibTeX格式保存失败: {str(e)}")
+
+        # 保存为EndNote格式
+        try:
+            from .review_fns.conversation_doc.endnote_doc import EndNoteFormatter
+            endnote_formatter = EndNoteFormatter()
+            endnote_content = endnote_formatter.create_document(papers_list)
+
+            # 在与其他文件相同目录下创建EndNote文件
+            result_file_enw = os.path.join(
+                os.path.dirname(result_file_md) if result_file_md else save_dir,
+                f"references_{base_filename}.enw"
+            )
+
+            # 直接写入文件
+            with open(result_file_enw, 'w', encoding='utf-8') as f:
+                f.write(endnote_content)
+
+            result_files.append(result_file_enw)
+            print(f"EndNote文件已保存到: {result_file_enw}")
+        except Exception as e:
+            print(f"EndNote格式保存失败: {str(e)}")
+
+        # 添加所有文件到下载区
+        success_files = []
+        for file in result_files:
+            try:
+                promote_file_to_downloadzone(file, chatbot=chatbot)
+                success_files.append(os.path.basename(file))
+            except Exception as e:
+                print(f"文件添加到下载区失败: {str(e)}")
+
+        # 更新成功提示消息
+        if success_files:
+            chatbot.append(["保存对话记录成功，bib和enw文件支持导入到EndNote、Zotero、JabRef、Mendeley等文献管理软件，HTML文件支持在浏览器中打开，里面包含详细论文源信息", "对话已保存并添加到下载区，可以在下载区找到相关文件"])
+        else:
+            chatbot.append(["保存对话记录", "所有格式的保存都失败了，请检查错误日志。"])
+
+        yield from update_ui(chatbot=chatbot, history=history)
+    else:
+        report_exception(chatbot, history, a=f"处理失败", b=f"请尝试其他查询")
+        yield from update_ui(chatbot=chatbot, history=history)
--- a/crazy_functions/Conversation_To_File.py
+++ b/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):
--- a/crazy_functions/Document_Conversation.py
+++ b/crazy_functions/Document_Conversation.py
@@ -0,0 +1,537 @@
+import os
+import threading
+import time
+from dataclasses import dataclass
+from typing import List, Tuple, Dict, Generator
+from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
+from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
+from crazy_functions.rag_fns.rag_file_support import extract_text
+from request_llms.bridge_all import model_info
+from toolbox import update_ui, CatchException, report_exception
+from shared_utils.fastapi_server import validate_path_safety
+
+
+@dataclass
+class FileFragment:
+    """文件片段数据类，用于组织处理单元"""
+    file_path: str
+    content: str
+    rel_path: str
+    fragment_index: int
+    total_fragments: int
+
+
+class BatchDocumentSummarizer:
+    """优化的文档总结器 - 批处理版本"""
+
+    def __init__(self, llm_kwargs: Dict, query: str, chatbot: List, history: List, system_prompt: str):
+        """初始化总结器"""
+        self.llm_kwargs = llm_kwargs
+        self.query = query
+        self.chatbot = chatbot
+        self.history = history
+        self.system_prompt = system_prompt
+        self.failed_files = []
+        self.file_summaries_map = {}
+
+    def _get_token_limit(self) -> int:
+        """获取模型token限制"""
+        max_token = model_info[self.llm_kwargs['llm_model']]['max_token']
+        return max_token * 3 // 4
+
+    def _create_batch_inputs(self, fragments: List[FileFragment]) -> Tuple[List, List, List]:
+        """创建批处理输入"""
+        inputs_array = []
+        inputs_show_user_array = []
+        history_array = []
+
+        for frag in fragments:
+            if self.query:
+                i_say = (f'请按照用户要求对文件内容进行处理，文件名为{os.path.basename(frag.file_path)}，'
+                         f'用户要求为：{self.query}：'
+                         f'文件内容是 ```{frag.content}```')
+                i_say_show_user = (f'正在处理 {frag.rel_path} (片段 {frag.fragment_index + 1}/{frag.total_fragments})')
+            else:
+                i_say = (f'请对下面的内容用中文做总结，不超过500字，文件名是{os.path.basename(frag.file_path)}，'
+                         f'内容是 ```{frag.content}```')
+                i_say_show_user = f'正在处理 {frag.rel_path} (片段 {frag.fragment_index + 1}/{frag.total_fragments})'
+
+            inputs_array.append(i_say)
+            inputs_show_user_array.append(i_say_show_user)
+            history_array.append([])
+
+        return inputs_array, inputs_show_user_array, history_array
+
+    def _process_single_file_with_timeout(self, file_info: Tuple[str, str], mutable_status: List) -> List[FileFragment]:
+        """包装了超时控制的文件处理函数"""
+
+        def timeout_handler():
+            thread = threading.current_thread()
+            if hasattr(thread, '_timeout_occurred'):
+                thread._timeout_occurred = True
+
+        # 设置超时标记
+        thread = threading.current_thread()
+        thread._timeout_occurred = False
+
+        # 设置超时时间为30秒，给予更多处理时间
+        TIMEOUT_SECONDS = 30
+        timer = threading.Timer(TIMEOUT_SECONDS, timeout_handler)
+        timer.start()
+
+        try:
+            fp, project_folder = file_info
+            fragments = []
+
+            # 定期检查是否超时
+            def check_timeout():
+                if hasattr(thread, '_timeout_occurred') and thread._timeout_occurred:
+                    raise TimeoutError(f"处理文件 {os.path.basename(fp)} 超时（{TIMEOUT_SECONDS}秒）")
+
+            # 更新状态
+            mutable_status[0] = "检查文件大小"
+            mutable_status[1] = time.time()
+            check_timeout()
+
+            # 文件大小检查
+            if os.path.getsize(fp) > self.max_file_size:
+                self.failed_files.append((fp, f"文件过大：超过{self.max_file_size / 1024 / 1024}MB"))
+                mutable_status[2] = "文件过大"
+                return fragments
+
+            # 更新状态
+            mutable_status[0] = "提取文件内容"
+            mutable_status[1] = time.time()
+
+            # 提取内容 - 使用单独的超时控制
+            content = None
+            extract_start_time = time.time()
+            try:
+                while True:
+                    check_timeout()  # 检查全局超时
+
+                    # 检查提取过程是否超时（10秒）
+                    if time.time() - extract_start_time > 10:
+                        raise TimeoutError("文件内容提取超时（10秒）")
+
+                    try:
+                        content = extract_text(fp)
+                        break
+                    except Exception as e:
+                        if "timeout" in str(e).lower():
+                            continue  # 如果是临时超时，重试
+                        raise  # 其他错误直接抛出
+
+            except Exception as e:
+                self.failed_files.append((fp, f"文件读取失败：{str(e)}"))
+                mutable_status[2] = "读取失败"
+                return fragments
+
+            if content is None:
+                self.failed_files.append((fp, "文件解析失败：不支持的格式或文件损坏"))
+                mutable_status[2] = "格式不支持"
+                return fragments
+            elif not content.strip():
+                self.failed_files.append((fp, "文件内容为空"))
+                mutable_status[2] = "内容为空"
+                return fragments
+
+            check_timeout()
+
+            # 更新状态
+            mutable_status[0] = "分割文本"
+            mutable_status[1] = time.time()
+
+            # 分割文本 - 添加超时检查
+            split_start_time = time.time()
+            try:
+                while True:
+                    check_timeout()  # 检查全局超时
+
+                    # 检查分割过程是否超时（5秒）
+                    if time.time() - split_start_time > 5:
+                        raise TimeoutError("文本分割超时（5秒）")
+
+                    paper_fragments = breakdown_text_to_satisfy_token_limit(
+                        txt=content,
+                        limit=self._get_token_limit(),
+                        llm_model=self.llm_kwargs['llm_model']
+                    )
+                    break
+
+            except Exception as e:
+                self.failed_files.append((fp, f"文本分割失败：{str(e)}"))
+                mutable_status[2] = "分割失败"
+                return fragments
+
+            # 处理片段
+            rel_path = os.path.relpath(fp, project_folder)
+            for i, frag in enumerate(paper_fragments):
+                check_timeout()  # 每处理一个片段检查一次超时
+                if frag.strip():
+                    fragments.append(FileFragment(
+                        file_path=fp,
+                        content=frag,
+                        rel_path=rel_path,
+                        fragment_index=i,
+                        total_fragments=len(paper_fragments)
+                    ))
+
+            mutable_status[2] = "处理完成"
+            return fragments
+
+        except TimeoutError as e:
+            self.failed_files.append((fp, str(e)))
+            mutable_status[2] = "处理超时"
+            return []
+        except Exception as e:
+            self.failed_files.append((fp, f"处理失败：{str(e)}"))
+            mutable_status[2] = "处理异常"
+            return []
+        finally:
+            timer.cancel()
+
+    def prepare_fragments(self, project_folder: str, file_paths: List[str]) -> Generator:
+        import concurrent.futures
+
+        from concurrent.futures import ThreadPoolExecutor
+        from typing import Generator, List
+        """并行准备所有文件的处理片段"""
+        all_fragments = []
+        total_files = len(file_paths)
+
+        # 配置参数
+        self.refresh_interval = 0.2  # UI刷新间隔
+        self.watch_dog_patience = 5  # 看门狗超时时间
+        self.max_file_size = 10 * 1024 * 1024  # 10MB限制
+        self.max_workers = min(32, len(file_paths))  # 最多32个线程
+
+        # 创建有超时控制的线程池
+        executor = ThreadPoolExecutor(max_workers=self.max_workers)
+
+        # 用于跨线程状态传递的可变列表 - 增加文件名信息
+        mutable_status_array = [["等待中", time.time(), "pending", file_path] for file_path in file_paths]
+
+        # 创建文件处理任务
+        file_infos = [(fp, project_folder) for fp in file_paths]
+
+        # 提交所有任务，使用带超时控制的处理函数
+        futures = [
+            executor.submit(
+                self._process_single_file_with_timeout,
+                file_info,
+                mutable_status_array[i]
+            ) for i, file_info in enumerate(file_infos)
+        ]
+
+        # 更新UI的计数器
+        cnt = 0
+
+        try:
+            # 监控任务执行
+            while True:
+                time.sleep(self.refresh_interval)
+                cnt += 1
+
+                # 检查任务完成状态
+                worker_done = [f.done() for f in futures]
+
+                # 更新状态显示
+                status_str = ""
+                for i, (status, timestamp, desc, file_path) in enumerate(mutable_status_array):
+                    # 获取文件名（去掉路径）
+                    file_name = os.path.basename(file_path)
+                    if worker_done[i]:
+                        status_str += f"文件 {file_name}: {desc}\n\n"
+                    else:
+                        status_str += f"文件 {file_name}: {status} {desc}\n\n"
+
+                # 更新UI
+                self.chatbot[-1] = [
+                    "处理进度",
+                    f"正在处理文件...\n\n{status_str}" + "." * (cnt % 10 + 1)
+                ]
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+                # 检查是否所有任务完成
+                if all(worker_done):
+                    break
+
+        finally:
+            # 确保线程池正确关闭
+            executor.shutdown(wait=False)
+
+        # 收集结果
+        processed_files = 0
+        for future in futures:
+            try:
+                fragments = future.result(timeout=0.1)  # 给予一个短暂的超时时间来获取结果
+                all_fragments.extend(fragments)
+                processed_files += 1
+            except concurrent.futures.TimeoutError:
+                # 处理获取结果超时
+                file_index = futures.index(future)
+                self.failed_files.append((file_paths[file_index], "结果获取超时"))
+                continue
+            except Exception as e:
+                # 处理其他异常
+                file_index = futures.index(future)
+                self.failed_files.append((file_paths[file_index], f"未知错误：{str(e)}"))
+                continue
+
+        # 最终进度更新
+        self.chatbot.append([
+            "文件处理完成",
+            f"成功处理 {len(all_fragments)} 个片段，失败 {len(self.failed_files)} 个文件"
+        ])
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        return all_fragments
+
+    def _process_fragments_batch(self, fragments: List[FileFragment]) -> Generator:
+        """批量处理文件片段"""
+        from collections import defaultdict
+        batch_size = 64  # 每批处理的片段数
+        max_retries = 3  # 最大重试次数
+        retry_delay = 5  # 重试延迟（秒）
+        results = defaultdict(list)
+
+        # 按批次处理
+        for i in range(0, len(fragments), batch_size):
+            batch = fragments[i:i + batch_size]
+
+            inputs_array, inputs_show_user_array, history_array = self._create_batch_inputs(batch)
+            sys_prompt_array = ["请总结以下内容："] * len(batch)
+
+            # 添加重试机制
+            for retry in range(max_retries):
+                try:
+                    response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
+                        inputs_array=inputs_array,
+                        inputs_show_user_array=inputs_show_user_array,
+                        llm_kwargs=self.llm_kwargs,
+                        chatbot=self.chatbot,
+                        history_array=history_array,
+                        sys_prompt_array=sys_prompt_array,
+                    )
+
+                    # 处理响应
+                    for j, frag in enumerate(batch):
+                        summary = response_collection[j * 2 + 1]
+                        if summary and summary.strip():
+                            results[frag.rel_path].append({
+                                'index': frag.fragment_index,
+                                'summary': summary,
+                                'total': frag.total_fragments
+                            })
+                    break  # 成功处理，跳出重试循环
+
+                except Exception as e:
+                    if retry == max_retries - 1:  # 最后一次重试失败
+                        for frag in batch:
+                            self.failed_files.append((frag.file_path, f"处理失败：{str(e)}"))
+                    else:
+                        yield from update_ui(self.chatbot.append([f"批次处理失败，{retry_delay}秒后重试...", str(e)]))
+                        time.sleep(retry_delay)
+
+        return results
+
+    def _generate_final_summary_request(self) -> Tuple[List, List, List]:
+        """准备最终总结请求"""
+        if not self.file_summaries_map:
+            return (["无可用的文件总结"], ["生成最终总结"], [[]])
+
+        summaries = list(self.file_summaries_map.values())
+        if all(not summary for summary in summaries):
+            return (["所有文件处理均失败"], ["生成最终总结"], [[]])
+
+        if self.plugin_kwargs.get("advanced_arg"):
+            i_say = "根据以上所有文件的处理结果，按要求进行综合处理：" + self.plugin_kwargs['advanced_arg']
+        else:
+            i_say = "请根据以上所有文件的处理结果，生成最终的总结，不超过1000字。"
+
+        return ([i_say], [i_say], [summaries])
+
+    def process_files(self, project_folder: str, file_paths: List[str]) -> Generator:
+        """处理所有文件"""
+        total_files = len(file_paths)
+        self.chatbot.append([f"开始处理", f"总计 {total_files} 个文件"])
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        # 1. 准备所有文件片段
+        # 在 process_files 函数中：
+        fragments = yield from self.prepare_fragments(project_folder, file_paths)
+        if not fragments:
+            self.chatbot.append(["处理失败", "没有可处理的文件内容"])
+            return "没有可处理的文件内容"
+
+        # 2. 批量处理所有文件片段
+        self.chatbot.append([f"文件分析", f"共计 {len(fragments)} 个处理单元"])
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        try:
+            file_summaries = yield from self._process_fragments_batch(fragments)
+        except Exception as e:
+            self.chatbot.append(["处理错误", f"批处理过程失败：{str(e)}"])
+            return "处理过程发生错误"
+
+        # 3. 为每个文件生成整体总结
+        self.chatbot.append(["生成总结", "正在汇总文件内容..."])
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        # 处理每个文件的总结
+        for rel_path, summaries in file_summaries.items():
+            if len(summaries) > 1:  # 多片段文件需要生成整体总结
+                sorted_summaries = sorted(summaries, key=lambda x: x['index'])
+                if self.plugin_kwargs.get("advanced_arg"):
+
+                    i_say = f'请按照用户要求对文件内容进行处理，用户要求为：{self.plugin_kwargs["advanced_arg"]}：'
+                else:
+                    i_say = f"请总结文件 {os.path.basename(rel_path)} 的主要内容，不超过500字。"
+
+                try:
+                    summary_texts = [s['summary'] for s in sorted_summaries]
+                    response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
+                        inputs_array=[i_say],
+                        inputs_show_user_array=[f"生成 {rel_path} 的处理结果"],
+                        llm_kwargs=self.llm_kwargs,
+                        chatbot=self.chatbot,
+                        history_array=[summary_texts],
+                        sys_prompt_array=["你是一个优秀的助手，"],
+                    )
+                    self.file_summaries_map[rel_path] = response_collection[1]
+                except Exception as e:
+                    self.chatbot.append(["警告", f"文件 {rel_path} 总结生成失败：{str(e)}"])
+                    self.file_summaries_map[rel_path] = "总结生成失败"
+            else:  # 单片段文件直接使用其唯一的总结
+                self.file_summaries_map[rel_path] = summaries[0]['summary']
+
+        # 4. 生成最终总结
+        if total_files == 1:
+            return "文件数为1，此时不调用总结模块"
+        else:
+            try:
+                # 收集所有文件的总结用于生成最终总结
+                file_summaries_for_final = []
+                for rel_path, summary in self.file_summaries_map.items():
+                    file_summaries_for_final.append(f"文件 {rel_path} 的总结：\n{summary}")
+
+                if self.plugin_kwargs.get("advanced_arg"):
+                    final_summary_prompt = ("根据以下所有文件的总结内容，按要求进行综合处理：" +
+                                            self.plugin_kwargs['advanced_arg'])
+                else:
+                    final_summary_prompt = "请根据以下所有文件的总结内容，生成最终的总结报告。"
+
+                response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
+                    inputs_array=[final_summary_prompt],
+                    inputs_show_user_array=["生成最终总结报告"],
+                    llm_kwargs=self.llm_kwargs,
+                    chatbot=self.chatbot,
+                    history_array=[file_summaries_for_final],
+                    sys_prompt_array=["总结所有文件内容。"],
+                    max_workers=1
+                )
+
+                return response_collection[1] if len(response_collection) > 1 else "生成总结失败"
+            except Exception as e:
+                self.chatbot.append(["错误", f"最终总结生成失败：{str(e)}"])
+                return "生成总结失败"
+
+    def save_results(self, final_summary: str):
+        """保存结果到文件"""
+        from toolbox import promote_file_to_downloadzone, write_history_to_file
+        from crazy_functions.doc_fns.batch_file_query_doc import MarkdownFormatter, HtmlFormatter, WordFormatter
+        import os
+        timestamp = time.strftime("%Y%m%d_%H%M%S")
+
+        # 创建各种格式化器
+        md_formatter = MarkdownFormatter(final_summary, self.file_summaries_map, self.failed_files)
+        html_formatter = HtmlFormatter(final_summary, self.file_summaries_map, self.failed_files)
+        word_formatter = WordFormatter(final_summary, self.file_summaries_map, self.failed_files)
+
+        result_files = []
+
+        # 保存 Markdown
+        try:
+            md_content = md_formatter.create_document()
+            result_file_md = write_history_to_file(
+                history=[md_content],  # 直接传入内容列表
+                file_basename=f"文档总结_{timestamp}.md"
+            )
+            result_files.append(result_file_md)
+        except:
+            pass
+
+        # 保存 HTML
+        try:
+            html_content = html_formatter.create_document()
+            result_file_html = write_history_to_file(
+                history=[html_content],
+                file_basename=f"文档总结_{timestamp}.html"
+            )
+            result_files.append(result_file_html)
+        except:
+            pass
+
+        # 保存 Word
+        try:
+            doc = word_formatter.create_document()
+            # 由于 Word 文档需要用 doc.save()，我们使用与 md 文件相同的目录
+            result_file_docx = os.path.join(
+                os.path.dirname(result_file_md),
+                f"文档总结_{timestamp}.docx"
+            )
+            doc.save(result_file_docx)
+            result_files.append(result_file_docx)
+        except:
+            pass
+
+        # 添加到下载区
+        for file in result_files:
+            promote_file_to_downloadzone(file, chatbot=self.chatbot)
+
+        self.chatbot.append(["处理完成", f"结果已保存至: {', '.join(result_files)}"])
+
+
+@CatchException
+def 批量文件询问(txt: str, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List,
+                 history: List, system_prompt: str, user_request: str):
+    """主函数 - 优化版本"""
+    # 初始化
+    import glob
+    import re
+    from crazy_functions.rag_fns.rag_file_support import supports_format
+    from toolbox import report_exception
+    query = plugin_kwargs.get("advanced_arg")
+    summarizer = BatchDocumentSummarizer(llm_kwargs, query, chatbot, history, system_prompt)
+    chatbot.append(["函数插件功能", f"作者：lbykkkk，批量总结文件。支持格式: {', '.join(supports_format)}等其他文本格式文件，如果长时间卡在文件处理过程，请查看处理进度，然后删除所有处于“pending”状态的文件，然后重新上传处理。"])
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    # 验证输入路径
+    if not os.path.exists(txt):
+        report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到项目或无权访问: {txt}")
+        yield from update_ui(chatbot=chatbot, history=history)
+        return
+
+    # 获取文件列表
+    project_folder = txt
+    user_name = chatbot.get_user()
+    validate_path_safety(project_folder, user_name)
+    extract_folder = next((d for d in glob.glob(f'{project_folder}/*')
+                           if os.path.isdir(d) and d.endswith('.extract')), project_folder)
+    exclude_patterns = r'/[^/]+\.(zip|rar|7z|tar|gz)$'
+    file_manifest = [f for f in glob.glob(f'{extract_folder}/**', recursive=True)
+                     if os.path.isfile(f) and not re.search(exclude_patterns, f)]
+
+    if not file_manifest:
+        report_exception(chatbot, history, a=f"解析项目: {txt}", b="未找到支持的文件类型")
+        yield from update_ui(chatbot=chatbot, history=history)
+        return
+
+    # 处理所有文件并生成总结
+    final_summary = yield from summarizer.process_files(project_folder, file_manifest)
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    # 保存结果
+    summarizer.save_results(final_summary)
+    yield from update_ui(chatbot=chatbot, history=history)
--- a/crazy_functions/Document_Conversation_Wrap.py
+++ b/crazy_functions/Document_Conversation_Wrap.py
@@ -0,0 +1,36 @@
+import random
+from toolbox import get_conf
+from crazy_functions.Document_Conversation import 批量文件询问
+from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
+
+
+class Document_Conversation_Wrap(GptAcademicPluginTemplate):
+    def __init__(self):
+        """
+        请注意`execute`会执行在不同的线程中，因此您在定义和使用类变量时，应当慎之又慎！
+        """
+        pass
+
+    def define_arg_selection_menu(self):
+        """
+        定义插件的二级选项菜单
+
+        第一个参数，名称`main_input`，参数`type`声明这是一个文本框，文本框上方显示`title`，文本框内部显示`description`，`default_value`为默认值；
+        第二个参数，名称`advanced_arg`，参数`type`声明这是一个文本框，文本框上方显示`title`，文本框内部显示`description`，`default_value`为默认值；
+        第三个参数，名称`allow_cache`，参数`type`声明这是一个下拉菜单，下拉菜单上方显示`title`+`description`，下拉菜单的选项为`options`，`default_value`为下拉菜单默认值；
+
+        """
+        gui_definition = {
+            "main_input":
+                ArgProperty(title="已上传的文件", description="上传文件后自动填充", default_value="", type="string").model_dump_json(),
+            "searxng_url":
+                ArgProperty(title="对材料提问", description="提问", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步
+        }
+        return gui_definition
+
+    def execute(txt, llm_kwargs, plugin_kwargs:dict, chatbot, history, system_prompt, user_request):
+        """
+        执行插件
+        """
+        yield from 批量文件询问(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
+
--- a/crazy_functions/Document_Optimize.py
+++ b/crazy_functions/Document_Optimize.py
@@ -0,0 +1,673 @@
+import os
+import time
+import glob
+import re
+import threading
+from typing import Dict, List, Generator, Tuple
+from dataclasses import dataclass
+
+from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
+from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
+from crazy_functions.rag_fns.rag_file_support import extract_text, supports_format, convert_to_markdown
+from request_llms.bridge_all import model_info
+from toolbox import update_ui, CatchException, report_exception, promote_file_to_downloadzone, write_history_to_file
+from shared_utils.fastapi_server import validate_path_safety
+
+# 新增：导入结构化论文提取器
+from crazy_functions.doc_fns.read_fns.unstructured_all.paper_structure_extractor import PaperStructureExtractor, ExtractorConfig, StructuredPaper
+
+# 导入格式化器
+from crazy_functions.paper_fns.file2file_doc import (
+    TxtFormatter,
+    MarkdownFormatter,
+    HtmlFormatter,
+    WordFormatter
+)
+
+@dataclass
+class TextFragment:
+    """文本片段数据类，用于组织处理单元"""
+    content: str
+    fragment_index: int
+    total_fragments: int
+
+
+class DocumentProcessor:
+    """文档处理器 - 处理单个文档并输出结果"""
+
+    def __init__(self, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List, history: List, system_prompt: str):
+        """初始化处理器"""
+        self.llm_kwargs = llm_kwargs
+        self.plugin_kwargs = plugin_kwargs
+        self.chatbot = chatbot
+        self.history = history
+        self.system_prompt = system_prompt
+        self.processed_results = []
+        self.failed_fragments = []
+        # 新增：初始化论文结构提取器
+        self.paper_extractor = PaperStructureExtractor()
+
+    def _get_token_limit(self) -> int:
+        """获取模型token限制，返回更小的值以确保更细粒度的分割"""
+        max_token = model_info[self.llm_kwargs['llm_model']]['max_token']
+        # 降低token限制，使每个片段更小
+        return max_token // 4  # 从3/4降低到1/4
+
+    def _create_batch_inputs(self, fragments: List[TextFragment]) -> Tuple[List, List, List]:
+        """创建批处理输入"""
+        inputs_array = []
+        inputs_show_user_array = []
+        history_array = []
+
+        user_instruction = self.plugin_kwargs.get("advanced_arg", "请润色以下学术文本，提高其语言表达的准确性、专业性和流畅度，保持学术风格，确保逻辑连贯，但不改变原文的科学内容和核心观点")
+
+        for frag in fragments:
+            i_say = (f'请按照以下要求处理文本内容：{user_instruction}\n\n'
+                     f'请将对文本的处理结果放在<decision>和</decision>标签之间。\n\n'
+                     f'文本内容：\n```\n{frag.content}\n```')
+
+            i_say_show_user = f'正在处理文本片段 {frag.fragment_index + 1}/{frag.total_fragments}'
+
+            inputs_array.append(i_say)
+            inputs_show_user_array.append(i_say_show_user)
+            history_array.append([])
+
+        return inputs_array, inputs_show_user_array, history_array
+
+    def _extract_decision(self, text: str) -> str:
+        """从LLM响应中提取<decision>标签内的内容"""
+        import re
+        pattern = r'<decision>(.*?)</decision>'
+        matches = re.findall(pattern, text, re.DOTALL)
+
+        if matches:
+            return matches[0].strip()
+        else:
+            # 如果没有找到标签，返回原始文本
+            return text.strip()
+
+    def process_file(self, file_path: str) -> Generator:
+        """处理单个文件"""
+        self.chatbot.append(["开始处理文件", f"文件路径: {file_path}"])
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        try:
+            # 首先尝试转换为Markdown
+            from crazy_functions.rag_fns.rag_file_support import convert_to_markdown
+            file_path = convert_to_markdown(file_path)
+
+            # 1. 检查文件是否为支持的论文格式
+            is_paper_format = any(file_path.lower().endswith(ext) for ext in self.paper_extractor.SUPPORTED_EXTENSIONS)
+
+            if is_paper_format:
+                # 使用结构化提取器处理论文
+                return (yield from self._process_structured_paper(file_path))
+            else:
+                # 使用原有方式处理普通文档
+                return (yield from self._process_regular_file(file_path))
+
+        except Exception as e:
+            self.chatbot.append(["处理错误", f"文件处理失败: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return None
+
+    def _process_structured_paper(self, file_path: str) -> Generator:
+        """处理结构化论文文件"""
+        # 1. 提取论文结构
+        self.chatbot[-1] = ["正在分析论文结构", f"文件路径: {file_path}"]
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        try:
+            paper = self.paper_extractor.extract_paper_structure(file_path)
+
+            if not paper or not paper.sections:
+                self.chatbot.append(["无法提取论文结构", "将使用全文内容进行处理"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+                # 使用全文内容进行段落切分
+                if paper and paper.full_text:
+                    # 使用增强的分割函数进行更细致的分割
+                    fragments = self._breakdown_section_content(paper.full_text)
+
+                    # 创建文本片段对象
+                    text_fragments = []
+                    for i, frag in enumerate(fragments):
+                        if frag.strip():
+                            text_fragments.append(TextFragment(
+                                content=frag,
+                                fragment_index=i,
+                                total_fragments=len(fragments)
+                            ))
+
+                    # 批量处理片段
+                    if text_fragments:
+                        self.chatbot[-1] = ["开始处理文本", f"共 {len(text_fragments)} 个片段"]
+                        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+                        # 一次性准备所有输入
+                        inputs_array, inputs_show_user_array, history_array = self._create_batch_inputs(text_fragments)
+
+                        # 使用系统提示
+                        instruction = self.plugin_kwargs.get("advanced_arg", "请润色以下学术文本，提高其语言表达的准确性、专业性和流畅度，保持学术风格，确保逻辑连贯，但不改变原文的科学内容和核心观点")
+                        sys_prompt_array = [f"你是一个专业的学术文献编辑助手。请按照用户的要求：'{instruction}'处理文本。保持学术风格，增强表达的准确性和专业性。"] * len(text_fragments)
+
+                        # 调用LLM一次性处理所有片段
+                        response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
+                            inputs_array=inputs_array,
+                            inputs_show_user_array=inputs_show_user_array,
+                            llm_kwargs=self.llm_kwargs,
+                            chatbot=self.chatbot,
+                            history_array=history_array,
+                            sys_prompt_array=sys_prompt_array,
+                        )
+
+                        # 处理响应
+                        for j, frag in enumerate(text_fragments):
+                            try:
+                                llm_response = response_collection[j * 2 + 1]
+                                processed_text = self._extract_decision(llm_response)
+
+                                if processed_text and processed_text.strip():
+                                    self.processed_results.append({
+                                        'index': frag.fragment_index,
+                                        'content': processed_text
+                                    })
+                                else:
+                                    self.failed_fragments.append(frag)
+                                    self.processed_results.append({
+                                        'index': frag.fragment_index,
+                                        'content': frag.content
+                                    })
+                            except Exception as e:
+                                self.failed_fragments.append(frag)
+                                self.processed_results.append({
+                                    'index': frag.fragment_index,
+                                    'content': frag.content
+                                })
+
+                        # 按原始顺序合并结果
+                        self.processed_results.sort(key=lambda x: x['index'])
+                        final_content = "\n".join([item['content'] for item in self.processed_results])
+
+                        # 更新UI
+                        success_count = len(text_fragments) - len(self.failed_fragments)
+                        self.chatbot[-1] = ["处理完成", f"成功处理 {success_count}/{len(text_fragments)} 个片段"]
+                        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+                        return final_content
+                    else:
+                        self.chatbot.append(["处理失败", "未能提取到有效的文本内容"])
+                        yield from update_ui(chatbot=self.chatbot, history=self.history)
+                        return None
+                else:
+                    self.chatbot.append(["处理失败", "未能提取到论文内容"])
+                    yield from update_ui(chatbot=self.chatbot, history=self.history)
+                    return None
+
+            # 2. 准备处理章节内容（不处理标题）
+            self.chatbot[-1] = ["已提取论文结构", f"共 {len(paper.sections)} 个主要章节"]
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            # 3. 收集所有需要处理的章节内容并分割为合适大小
+            sections_to_process = []
+            section_map = {}  # 用于映射处理前后的内容
+
+            def collect_section_contents(sections, parent_path=""):
+                """递归收集章节内容，跳过参考文献部分"""
+                for i, section in enumerate(sections):
+                    current_path = f"{parent_path}/{i}" if parent_path else f"{i}"
+
+                    # 检查是否为参考文献部分，如果是则跳过
+                    if section.section_type == 'references' or section.title.lower() in ['references', '参考文献', 'bibliography', '文献']:
+                        continue  # 跳过参考文献部分
+
+                    # 只处理内容非空的章节
+                    if section.content and section.content.strip():
+                        # 使用增强的分割函数进行更细致的分割
+                        fragments = self._breakdown_section_content(section.content)
+
+                        for fragment_idx, fragment_content in enumerate(fragments):
+                            if fragment_content.strip():
+                                fragment_index = len(sections_to_process)
+                                sections_to_process.append(TextFragment(
+                                    content=fragment_content,
+                                    fragment_index=fragment_index,
+                                    total_fragments=0  # 临时值，稍后更新
+                                ))
+
+                                # 保存映射关系，用于稍后更新章节内容
+                                # 为每个片段存储原始章节和片段索引信息
+                                section_map[fragment_index] = (current_path, section, fragment_idx, len(fragments))
+
+                    # 递归处理子章节
+                    if section.subsections:
+                        collect_section_contents(section.subsections, current_path)
+
+            # 收集所有章节内容
+            collect_section_contents(paper.sections)
+
+            # 更新总片段数
+            total_fragments = len(sections_to_process)
+            for frag in sections_to_process:
+                frag.total_fragments = total_fragments
+
+            # 4. 如果没有内容需要处理，直接返回
+            if not sections_to_process:
+                self.chatbot.append(["处理完成", "未找到需要处理的内容"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+                return None
+
+            # 5. 批量处理章节内容
+            self.chatbot[-1] = ["开始处理论文内容", f"共 {len(sections_to_process)} 个内容片段"]
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            # 一次性准备所有输入
+            inputs_array, inputs_show_user_array, history_array = self._create_batch_inputs(sections_to_process)
+
+            # 使用系统提示
+            instruction = self.plugin_kwargs.get("advanced_arg", "请润色以下学术文本，提高其语言表达的准确性、专业性和流畅度，保持学术风格，确保逻辑连贯，但不改变原文的科学内容和核心观点")
+            sys_prompt_array = [f"你是一个专业的学术文献编辑助手。请按照用户的要求：'{instruction}'处理文本。保持学术风格，增强表达的准确性和专业性。"] * len(sections_to_process)
+
+            # 调用LLM一次性处理所有片段
+            response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
+                inputs_array=inputs_array,
+                inputs_show_user_array=inputs_show_user_array,
+                llm_kwargs=self.llm_kwargs,
+                chatbot=self.chatbot,
+                history_array=history_array,
+                sys_prompt_array=sys_prompt_array,
+            )
+
+            # 处理响应，重组章节内容
+            section_contents = {}  # 用于重组各章节的处理后内容
+
+            for j, frag in enumerate(sections_to_process):
+                try:
+                    llm_response = response_collection[j * 2 + 1]
+                    processed_text = self._extract_decision(llm_response)
+
+                    if processed_text and processed_text.strip():
+                        # 保存处理结果
+                        self.processed_results.append({
+                            'index': frag.fragment_index,
+                            'content': processed_text
+                        })
+
+                        # 存储处理后的文本片段，用于后续重组
+                        fragment_index = frag.fragment_index
+                        if fragment_index in section_map:
+                            path, section, fragment_idx, total_fragments = section_map[fragment_index]
+
+                            # 初始化此章节的内容容器（如果尚未创建）
+                            if path not in section_contents:
+                                section_contents[path] = [""] * total_fragments
+
+                            # 将处理后的片段放入正确位置
+                            section_contents[path][fragment_idx] = processed_text
+                    else:
+                        self.failed_fragments.append(frag)
+                except Exception as e:
+                    self.failed_fragments.append(frag)
+
+            # 重组每个章节的内容
+            for path, fragments in section_contents.items():
+                section = None
+                for idx in section_map:
+                    if section_map[idx][0] == path:
+                        section = section_map[idx][1]
+                        break
+
+                if section:
+                    # 合并该章节的所有处理后片段
+                    section.content = "\n".join(fragments)
+
+            # 6. 更新UI
+            success_count = total_fragments - len(self.failed_fragments)
+            self.chatbot[-1] = ["处理完成", f"成功处理 {success_count}/{total_fragments} 个内容片段"]
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            # 收集参考文献部分（不进行处理）
+            references_sections = []
+            def collect_references(sections, parent_path=""):
+                """递归收集参考文献部分"""
+                for i, section in enumerate(sections):
+                    current_path = f"{parent_path}/{i}" if parent_path else f"{i}"
+
+                    # 检查是否为参考文献部分
+                    if section.section_type == 'references' or section.title.lower() in ['references', '参考文献', 'bibliography', '文献']:
+                        references_sections.append((current_path, section))
+
+                    # 递归检查子章节
+                    if section.subsections:
+                        collect_references(section.subsections, current_path)
+
+            # 收集参考文献
+            collect_references(paper.sections)
+
+            # 7. 将处理后的结构化论文转换为Markdown
+            markdown_content = self.paper_extractor.generate_markdown(paper)
+
+            # 8. 返回处理后的内容
+            self.chatbot[-1] = ["处理完成", f"成功处理 {success_count}/{total_fragments} 个内容片段，参考文献部分未处理"]
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            return markdown_content
+
+        except Exception as e:
+            self.chatbot.append(["结构化处理失败", f"错误: {str(e)}，将尝试作为普通文件处理"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return (yield from self._process_regular_file(file_path))
+
+    def _process_regular_file(self, file_path: str) -> Generator:
+        """使用原有方式处理普通文件"""
+        # 原有的文件处理逻辑
+        self.chatbot[-1] = ["正在读取文件", f"文件路径: {file_path}"]
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        content = extract_text(file_path)
+        if not content or not content.strip():
+            self.chatbot.append(["处理失败", "文件内容为空或无法提取内容"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return None
+
+        # 2. 分割文本
+        self.chatbot[-1] = ["正在分析文件", "将文件内容分割为适当大小的片段"]
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        # 使用增强的分割函数
+        fragments = self._breakdown_section_content(content)
+
+        # 3. 创建文本片段对象
+        text_fragments = []
+        for i, frag in enumerate(fragments):
+            if frag.strip():
+                text_fragments.append(TextFragment(
+                    content=frag,
+                    fragment_index=i,
+                    total_fragments=len(fragments)
+                ))
+
+        # 4. 处理所有片段
+        self.chatbot[-1] = ["开始处理文本", f"共 {len(text_fragments)} 个片段"]
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        # 批量处理片段
+        batch_size = 8  # 每批处理的片段数
+        for i in range(0, len(text_fragments), batch_size):
+            batch = text_fragments[i:i + batch_size]
+
+            inputs_array, inputs_show_user_array, history_array = self._create_batch_inputs(batch)
+
+            # 使用系统提示
+            instruction = self.plugin_kwargs.get("advanced_arg", "请润色以下文本")
+            sys_prompt_array = [f"你是一个专业的文本处理助手。请按照用户的要求：'{instruction}'处理文本。"] * len(batch)
+
+            # 调用LLM处理
+            response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
+                inputs_array=inputs_array,
+                inputs_show_user_array=inputs_show_user_array,
+                llm_kwargs=self.llm_kwargs,
+                chatbot=self.chatbot,
+                history_array=history_array,
+                sys_prompt_array=sys_prompt_array,
+            )
+
+            # 处理响应
+            for j, frag in enumerate(batch):
+                try:
+                    llm_response = response_collection[j * 2 + 1]
+                    processed_text = self._extract_decision(llm_response)
+
+                    if processed_text and processed_text.strip():
+                        self.processed_results.append({
+                            'index': frag.fragment_index,
+                            'content': processed_text
+                        })
+                    else:
+                        self.failed_fragments.append(frag)
+                        self.processed_results.append({
+                            'index': frag.fragment_index,
+                            'content': frag.content  # 如果处理失败，使用原始内容
+                        })
+                except Exception as e:
+                    self.failed_fragments.append(frag)
+                    self.processed_results.append({
+                        'index': frag.fragment_index,
+                        'content': frag.content  # 如果处理失败，使用原始内容
+                    })
+
+        # 5. 按原始顺序合并结果
+        self.processed_results.sort(key=lambda x: x['index'])
+        final_content = "\n".join([item['content'] for item in self.processed_results])
+
+        # 6. 更新UI
+        success_count = len(text_fragments) - len(self.failed_fragments)
+        self.chatbot[-1] = ["处理完成", f"成功处理 {success_count}/{len(text_fragments)} 个片段"]
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        return final_content
+
+    def save_results(self, content: str, original_file_path: str) -> List[str]:
+        """保存处理结果为多种格式"""
+        if not content:
+            return []
+
+        timestamp = time.strftime("%Y%m%d_%H%M%S")
+        original_filename = os.path.basename(original_file_path)
+        filename_without_ext = os.path.splitext(original_filename)[0]
+        base_filename = f"{filename_without_ext}_processed_{timestamp}"
+
+        result_files = []
+
+        # 获取用户指定的处理类型
+        processing_type = self.plugin_kwargs.get("advanced_arg", "文本处理")
+
+        # 1. 保存为TXT
+        try:
+            txt_formatter = TxtFormatter()
+            txt_content = txt_formatter.create_document(content)
+            txt_file = write_history_to_file(
+                history=[txt_content],
+                file_basename=f"{base_filename}.txt"
+            )
+            result_files.append(txt_file)
+        except Exception as e:
+            self.chatbot.append(["警告", f"TXT格式保存失败: {str(e)}"])
+
+        # 2. 保存为Markdown
+        try:
+            md_formatter = MarkdownFormatter()
+            md_content = md_formatter.create_document(content, processing_type)
+            md_file = write_history_to_file(
+                history=[md_content],
+                file_basename=f"{base_filename}.md"
+            )
+            result_files.append(md_file)
+        except Exception as e:
+            self.chatbot.append(["警告", f"Markdown格式保存失败: {str(e)}"])
+
+        # 3. 保存为HTML
+        try:
+            html_formatter = HtmlFormatter(processing_type=processing_type)
+            html_content = html_formatter.create_document(content)
+            html_file = write_history_to_file(
+                history=[html_content],
+                file_basename=f"{base_filename}.html"
+            )
+            result_files.append(html_file)
+        except Exception as e:
+            self.chatbot.append(["警告", f"HTML格式保存失败: {str(e)}"])
+
+        # 4. 保存为Word
+        try:
+            word_formatter = WordFormatter()
+            doc = word_formatter.create_document(content, processing_type)
+
+            # 获取保存路径
+            from toolbox import get_log_folder
+            word_path = os.path.join(get_log_folder(), f"{base_filename}.docx")
+            doc.save(word_path)
+
+            # 5. 保存为PDF（通过Word转换）
+            try:
+                from crazy_functions.paper_fns.file2file_doc.word2pdf import WordToPdfConverter
+                pdf_path = WordToPdfConverter.convert_to_pdf(word_path)
+                result_files.append(pdf_path)
+            except Exception as e:
+                self.chatbot.append(["警告", f"PDF格式保存失败: {str(e)}"])
+
+        except Exception as e:
+            self.chatbot.append(["警告", f"Word格式保存失败: {str(e)}"])
+
+        # 添加到下载区
+        for file in result_files:
+            promote_file_to_downloadzone(file, chatbot=self.chatbot)
+
+        return result_files
+
+    def _breakdown_section_content(self, content: str) -> List[str]:
+        """对文本内容进行分割与合并
+
+        主要按段落进行组织，只合并较小的段落以减少片段数量
+        保留原始段落结构，不对长段落进行强制分割
+        针对中英文设置不同的阈值，因为字符密度不同
+        """
+        # 先按段落分割文本
+        paragraphs = content.split('\n\n')
+
+        # 检测语言类型
+        chinese_char_count = sum(1 for char in content if '\u4e00' <= char <= '\u9fff')
+        is_chinese_text = chinese_char_count / max(1, len(content)) > 0.3
+
+        # 根据语言类型设置不同的阈值（只用于合并小段落）
+        if is_chinese_text:
+            # 中文文本：一个汉字就是一个字符，信息密度高
+            min_chunk_size = 300  # 段落合并的最小阈值
+            target_size = 800  # 理想的段落大小
+        else:
+            # 英文文本：一个单词由多个字符组成，信息密度低
+            min_chunk_size = 600  # 段落合并的最小阈值
+            target_size = 1600  # 理想的段落大小
+
+        # 1. 只合并小段落，不对长段落进行分割
+        result_fragments = []
+        current_chunk = []
+        current_length = 0
+
+        for para in paragraphs:
+            # 如果段落太小且不会超过目标大小，则合并
+            if len(para) < min_chunk_size and current_length + len(para) <= target_size:
+                current_chunk.append(para)
+                current_length += len(para)
+            # 否则，创建新段落
+            else:
+                # 如果当前块非空且与当前段落无关，先保存它
+                if current_chunk and current_length > 0:
+                    result_fragments.append('\n\n'.join(current_chunk))
+
+                # 当前段落作为新块
+                current_chunk = [para]
+                current_length = len(para)
+
+            # 如果当前块大小已接近目标大小，保存并开始新块
+            if current_length >= target_size:
+                result_fragments.append('\n\n'.join(current_chunk))
+                current_chunk = []
+                current_length = 0
+
+        # 保存最后一个块
+        if current_chunk:
+            result_fragments.append('\n\n'.join(current_chunk))
+
+        # 2. 处理可能过大的片段（确保不超过token限制）
+        final_fragments = []
+        max_token = self._get_token_limit()
+
+        for fragment in result_fragments:
+            # 检查fragment是否可能超出token限制
+            # 根据语言类型调整token估算
+            if is_chinese_text:
+                estimated_tokens = len(fragment) / 1.5  # 中文每个token约1-2个字符
+            else:
+                estimated_tokens = len(fragment) / 4  # 英文每个token约4个字符
+
+            if estimated_tokens > max_token:
+                # 即使可能超出限制，也尽量保持段落的完整性
+                # 使用breakdown_text但设置更大的限制来减少分割
+                larger_limit = max_token * 0.95  # 使用95%的限制
+                sub_fragments = breakdown_text_to_satisfy_token_limit(
+                    txt=fragment,
+                    limit=larger_limit,
+                    llm_model=self.llm_kwargs['llm_model']
+                )
+                final_fragments.extend(sub_fragments)
+            else:
+                final_fragments.append(fragment)
+
+        return final_fragments
+
+
+@CatchException
+def 自定义智能文档处理(txt: str, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List,
+              history: List, system_prompt: str, user_request: str):
+    """主函数 - 文件到文件处理"""
+    # 初始化
+    processor = DocumentProcessor(llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
+    chatbot.append(["函数插件功能", "文件内容处理：将文档内容按照指定要求处理后输出为多种格式"])
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    # 验证输入路径
+    if not os.path.exists(txt):
+        report_exception(chatbot, history, a=f"解析路径: {txt}", b=f"找不到路径或无权访问: {txt}")
+        yield from update_ui(chatbot=chatbot, history=history)
+        return
+
+    # 验证路径安全性
+    user_name = chatbot.get_user()
+    validate_path_safety(txt, user_name)
+
+    # 获取文件列表
+    if os.path.isfile(txt):
+        # 单个文件处理
+        file_paths = [txt]
+    else:
+        # 目录处理 - 类似批量文件询问插件
+        project_folder = txt
+        extract_folder = next((d for d in glob.glob(f'{project_folder}/*')
+                           if os.path.isdir(d) and d.endswith('.extract')), project_folder)
+
+        # 排除压缩文件
+        exclude_patterns = r'/[^/]+\.(zip|rar|7z|tar|gz)$'
+        file_paths = [f for f in glob.glob(f'{extract_folder}/**', recursive=True)
+                     if os.path.isfile(f) and not re.search(exclude_patterns, f)]
+
+        # 过滤支持的文件格式
+        file_paths = [f for f in file_paths if any(f.lower().endswith(ext) for ext in
+                    list(processor.paper_extractor.SUPPORTED_EXTENSIONS) + ['.json', '.csv', '.xlsx', '.xls'])]
+
+    if not file_paths:
+        report_exception(chatbot, history, a=f"解析路径: {txt}", b="未找到支持的文件类型")
+        yield from update_ui(chatbot=chatbot, history=history)
+        return
+
+    # 处理文件
+    if len(file_paths) > 1:
+        chatbot.append(["发现多个文件", f"共找到 {len(file_paths)} 个文件，将处理第一个文件"])
+        yield from update_ui(chatbot=chatbot, history=history)
+
+    # 只处理第一个文件
+    file_to_process = file_paths[0]
+    processed_content = yield from processor.process_file(file_to_process)
+
+    if processed_content:
+        # 保存结果
+        result_files = processor.save_results(processed_content, file_to_process)
+
+        if result_files:
+            chatbot.append(["处理完成", f"已生成 {len(result_files)} 个结果文件"])
+        else:
+            chatbot.append(["处理完成", "但未能保存任何结果文件"])
+    else:
+        chatbot.append(["处理失败", "未能生成有效的处理结果"])
+
+    yield from update_ui(chatbot=chatbot, history=history)
--- a/crazy_functions/Internet_GPT.py
+++ b/crazy_functions/Internet_GPT.py
@@ -7,7 +7,7 @@ from bs4 import BeautifulSoup
 from functools import lru_cache
 from itertools import zip_longest
 from check_proxy import check_proxy
-from toolbox import CatchException, update_ui, get_conf, update_ui_lastest_msg
+from toolbox import CatchException, update_ui, get_conf, update_ui_latest_msg
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
 from request_llms.bridge_all import model_info
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -49,7 +49,7 @@ def search_optimizer(
    mutable = ["", time.time(), ""]
    llm_kwargs["temperature"] = 0.8
    try:
-        querys_json = predict_no_ui_long_connection(
+        query_json = predict_no_ui_long_connection(
            inputs=query,
            llm_kwargs=llm_kwargs,
            history=[],
@@ -57,31 +57,31 @@ def search_optimizer(
            observe_window=mutable,
        )
    except Exception:
-        querys_json = "1234"
+        query_json = "null"
    #* 尝试解码优化后的搜索结果
-    querys_json = re.sub(r"```json|```", "", querys_json)
+    query_json = re.sub(r"```json|```", "", query_json)
    try:
-        querys = json.loads(querys_json)
+        queries = json.loads(query_json)
    except Exception:
        #* 如果解码失败,降低温度再试一次
        try:
            llm_kwargs["temperature"] = 0.4
-            querys_json = predict_no_ui_long_connection(
+            query_json = predict_no_ui_long_connection(
                inputs=query,
                llm_kwargs=llm_kwargs,
                history=[],
                sys_prompt=sys_prompt,
                observe_window=mutable,
            )
-            querys_json = re.sub(r"```json|```", "", querys_json)
-            querys = json.loads(querys_json)
+            query_json = re.sub(r"```json|```", "", query_json)
+            queries = json.loads(query_json)
        except Exception:
            #* 如果再次失败，直接返回原始问题
-            querys = [query]
+            queries = [query]
    links = []
    success = 0
    Exceptions = ""
-    for q in querys:
+    for q in queries:
        try:
            link = searxng_request(q, proxies, categories, searxng_url, engines=engines)
            if len(link) > 0:
@@ -175,10 +175,17 @@ def scrape_text(url, proxies) -> str:
    Returns:
        str: The scraped text
    """
+    from loguru import logger
    headers = {
        'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36',
        'Content-Type': 'text/plain',
    }
+
+    # 首先采用Jina进行文本提取
+    if get_conf("JINA_API_KEY"):
+        try: return jina_scrape_text(url)
+        except: logger.debug("Jina API 请求失败，回到旧方法")
+
    try:
        response = requests.get(url, headers=headers, proxies=proxies, timeout=8)
        if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding
@@ -193,21 +200,39 @@ def scrape_text(url, proxies) -> str:
    text = "\n".join(chunk for chunk in chunks if chunk)
    return text

+
+def jina_scrape_text(url) -> str:
+    "jina_39727421c8fa4e4fa9bd698e5211feaaDyGeVFESNrRaepWiLT0wmHYJSh-d"
+    headers = {
+        'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36',
+        'Content-Type': 'text/plain',
+        "X-Retain-Images": "none",
+        "Authorization": f'Bearer {get_conf("JINA_API_KEY")}'
+    }
+    response = requests.get("https://r.jina.ai/" + url, headers=headers, proxies=None, timeout=8)
+    if response.status_code != 200:
+        raise ValueError("Jina API 请求失败，开始尝试旧方法！" + response.text)
+    if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding
+    result = response.text
+    result = result.replace("\\[", "[").replace("\\]", "]").replace("\\(", "(").replace("\\)", ")")
+    return response.text
+
+
 def internet_search_with_analysis_prompt(prompt, analysis_prompt, llm_kwargs, chatbot):
    from toolbox import get_conf
    proxies = get_conf('proxies')
    categories = 'general'
    searxng_url = None  # 使用默认的searxng_url
    engines = None  # 使用默认的搜索引擎
-    yield from update_ui_lastest_msg(lastmsg=f"检索中: {prompt} ...", chatbot=chatbot, history=[], delay=1)
+    yield from update_ui_latest_msg(lastmsg=f"检索中: {prompt} ...", chatbot=chatbot, history=[], delay=1)
    urls = searxng_request(prompt, proxies, categories, searxng_url, engines=engines)
-    yield from update_ui_lastest_msg(lastmsg=f"依次访问搜索到的网站 ...", chatbot=chatbot, history=[], delay=1)
+    yield from update_ui_latest_msg(lastmsg=f"依次访问搜索到的网站 ...", chatbot=chatbot, history=[], delay=1)
    if len(urls) == 0:
        return None
    max_search_result = 5   # 最多收纳多少个网页的结果
    history = []
    for index, url in enumerate(urls[:max_search_result]):
-        yield from update_ui_lastest_msg(lastmsg=f"依次访问搜索到的网站: {url['link']} ...", chatbot=chatbot, history=[], delay=1)
+        yield from update_ui_latest_msg(lastmsg=f"依次访问搜索到的网站: {url['link']} ...", chatbot=chatbot, history=[], delay=1)
        res = scrape_text(url['link'], proxies)
        prefix = f"第{index}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
        history.extend([prefix, res])
@@ -222,7 +247,7 @@ def internet_search_with_analysis_prompt(prompt, analysis_prompt, llm_kwargs, ch
        llm_kwargs=llm_kwargs,
        history=history,
        sys_prompt="请从搜索结果中抽取信息，对最相关的两个搜索结果进行总结，然后回答问题。",
-        console_slience=False,
+        console_silence=False,
    )
    return gpt_say

@@ -246,23 +271,52 @@ def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
        urls = search_optimizer(txt, proxies, optimizer_history, llm_kwargs, optimizer, categories, searxng_url, engines)
    history = []
    if len(urls) == 0:
-        chatbot.append((f"结论：{txt}",
-                        "[Local Message] 受到限制，无法从searxng获取信息！请尝试更换搜索引擎。"))
+        chatbot.append((f"结论：{txt}", "[Local Message] 受到限制，无法从searxng获取信息！请尝试更换搜索引擎。"))
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        return

    # ------------- < 第2步：依次访问网页 > -------------
+    from concurrent.futures import ThreadPoolExecutor
+    from textwrap import dedent
    max_search_result = 5   # 最多收纳多少个网页的结果
    if optimizer == "开启(增强)":
        max_search_result = 8
-    chatbot.append(["联网检索中 ...", None])
-    for index, url in enumerate(urls[:max_search_result]):
-        res = scrape_text(url['link'], proxies)
-        prefix = f"第{index}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
-        history.extend([prefix, res])
-        res_squeeze = res.replace('\n', '...')
-        chatbot[-1] = [prefix + "\n\n" + res_squeeze[:500] + "......", None]
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+    template = dedent("""
+        <details>
+        <summary>{TITLE}</summary>
+        <div class="search_result">{URL}</div>
+        <div class="search_result">{CONTENT}</div>
+        </details>
+    """)
+
+    buffer = ""
+
+    # 创建线程池
+    with ThreadPoolExecutor(max_workers=5) as executor:
+        # 提交任务到线程池
+        futures = []
+        for index, url in enumerate(urls[:max_search_result]):
+            future = executor.submit(scrape_text, url['link'], proxies)
+            futures.append((index, future, url))
+
+        # 处理完成的任务
+        for index, future, url in futures:
+            # 开始
+            prefix = f"正在加载 第{index+1}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
+            string_structure = template.format(TITLE=prefix, URL=url['link'], CONTENT="正在加载，请稍后 ......")
+            yield from update_ui_latest_msg(lastmsg=(buffer + string_structure), chatbot=chatbot, history=history, delay=0.1)  # 刷新界面
+
+            # 获取结果
+            res = future.result()
+
+            # 显示结果
+            prefix = f"第{index+1}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
+            string_structure = template.format(TITLE=prefix, URL=url['link'], CONTENT=res[:1000] + "......")
+            buffer += string_structure
+
+            # 更新历史
+            history.extend([prefix, res])
+            yield from update_ui_latest_msg(lastmsg=buffer, chatbot=chatbot, history=history, delay=0.1)  # 刷新界面

    # ------------- < 第3步：ChatGPT综合 > -------------
    if (optimizer != "开启(增强)"):
--- a/crazy_functions/Internet_GPT_Wrap.py
+++ b/crazy_functions/Internet_GPT_Wrap.py
@@ -38,11 +38,12 @@ class NetworkGPT_Wrap(GptAcademicPluginTemplate):
        }
        return gui_definition

-    def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
+    def execute(txt, llm_kwargs, plugin_kwargs:dict, chatbot, history, system_prompt, user_request):
        """
        执行插件
        """
-        if plugin_kwargs["categories"] == "网页": plugin_kwargs["categories"] = "general"
-        if plugin_kwargs["categories"] == "学术论文": plugin_kwargs["categories"] = "science"
+        if plugin_kwargs.get("categories", None) == "网页": plugin_kwargs["categories"] = "general"
+        elif plugin_kwargs.get("categories", None) == "学术论文": plugin_kwargs["categories"] = "science"
+        else: plugin_kwargs["categories"] = "general"
        yield from 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)

--- a/crazy_functions/Latex_Function.py
+++ b/crazy_functions/Latex_Function.py
@@ -1,5 +1,5 @@
 from toolbox import update_ui, trimmed_format_exc, get_conf, get_log_folder, promote_file_to_downloadzone, check_repeat_upload, map_file_to_sha256
-from toolbox import CatchException, report_exception, update_ui_lastest_msg, zip_result, gen_time_str
+from toolbox import CatchException, report_exception, update_ui_latest_msg, zip_result, gen_time_str
 from functools import partial
 from loguru import logger

@@ -41,7 +41,7 @@ def switch_prompt(pfg, mode, more_requirement):
    return inputs_array, sys_prompt_array


-def desend_to_extracted_folder_if_exist(project_folder):
+def descend_to_extracted_folder_if_exist(project_folder):
    """
    Descend into the extracted folder if it exists, otherwise return the original folder.

@@ -130,7 +130,7 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):

    if not txt.startswith('https://arxiv.org/abs/'):
        msg = f"解析arxiv网址失败, 期望格式例如: https://arxiv.org/abs/1707.06690。实际得到格式: {url_}。"
-        yield from update_ui_lastest_msg(msg, chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui_latest_msg(msg, chatbot=chatbot, history=history)  # 刷新界面
        return msg, None
    # <-------------- set format ------------->
    arxiv_id = url_.split('/abs/')[-1]
@@ -156,16 +156,16 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):
        return False

    if os.path.exists(dst) and allow_cache:
-        yield from update_ui_lastest_msg(f"调用缓存 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui_latest_msg(f"调用缓存 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
        success = True
    else:
-        yield from update_ui_lastest_msg(f"开始下载 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui_latest_msg(f"开始下载 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
        success = fix_url_and_download()
-        yield from update_ui_lastest_msg(f"下载完成 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui_latest_msg(f"下载完成 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面


    if not success:
-        yield from update_ui_lastest_msg(f"下载失败 {arxiv_id}", chatbot=chatbot, history=history)
+        yield from update_ui_latest_msg(f"下载失败 {arxiv_id}", chatbot=chatbot, history=history)
        raise tarfile.ReadError(f"论文下载失败 {arxiv_id}")

    # <-------------- extract file ------------->
@@ -288,7 +288,7 @@ def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, histo
        return

    # <-------------- if is a zip/tar file ------------->
-    project_folder = desend_to_extracted_folder_if_exist(project_folder)
+    project_folder = descend_to_extracted_folder_if_exist(project_folder)

    # <-------------- move latex project away from temp folder ------------->
    from shared_utils.fastapi_server import validate_path_safety
@@ -365,7 +365,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
    try:
        txt, arxiv_id = yield from arxiv_download(chatbot, history, txt, allow_cache)
    except tarfile.ReadError as e:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
            "无法自动下载该论文的Latex源码，请前往arxiv打开此论文下载页面，点other Formats，然后download source手动下载latex源码包。接下来调用本地Latex翻译插件即可。",
            chatbot=chatbot, history=history)
        return
@@ -404,7 +404,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
        return

    # <-------------- if is a zip/tar file ------------->
-    project_folder = desend_to_extracted_folder_if_exist(project_folder)
+    project_folder = descend_to_extracted_folder_if_exist(project_folder)

    # <-------------- move latex project away from temp folder ------------->
    from shared_utils.fastapi_server import validate_path_safety
@@ -518,7 +518,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
    # repeat, project_folder = check_repeat_upload(file_manifest[0], hash_tag)

    # if repeat:
-    #     yield from update_ui_lastest_msg(f"发现重复上传，请查收结果（压缩包）...", chatbot=chatbot, history=history)
+    #     yield from update_ui_latest_msg(f"发现重复上传，请查收结果（压缩包）...", chatbot=chatbot, history=history)
    #     try:
    #         translate_pdf = [f for f in glob.glob(f'{project_folder}/**/merge_translate_zh.pdf', recursive=True)][0]
    #         promote_file_to_downloadzone(translate_pdf, rename_file=None, chatbot=chatbot)
@@ -531,7 +531,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
    #         report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"发现重复上传，但是无法找到相关文件")
    #         yield from update_ui(chatbot=chatbot, history=history)
    # else:
-    #     yield from update_ui_lastest_msg(f"未发现重复上传", chatbot=chatbot, history=history)
+    #     yield from update_ui_latest_msg(f"未发现重复上传", chatbot=chatbot, history=history)

    # <-------------- convert pdf into tex ------------->
    chatbot.append([f"解析项目: {txt}", "正在将PDF转换为tex项目，请耐心等待..."])
@@ -543,7 +543,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
        return False

    # <-------------- translate latex file into Chinese ------------->
-    yield from update_ui_lastest_msg("正在tex项目将翻译为中文...", chatbot=chatbot, history=history)
+    yield from update_ui_latest_msg("正在tex项目将翻译为中文...", chatbot=chatbot, history=history)
    file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]
    if len(file_manifest) == 0:
        report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何.tex文件: {txt}")
@@ -551,7 +551,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
        return

    # <-------------- if is a zip/tar file ------------->
-    project_folder = desend_to_extracted_folder_if_exist(project_folder)
+    project_folder = descend_to_extracted_folder_if_exist(project_folder)

    # <-------------- move latex project away from temp folder ------------->
    from shared_utils.fastapi_server import validate_path_safety
@@ -571,7 +571,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
                                    switch_prompt=_switch_prompt_)

    # <-------------- compile PDF ------------->
-    yield from update_ui_lastest_msg("正在将翻译好的项目tex项目编译为PDF...", chatbot=chatbot, history=history)
+    yield from update_ui_latest_msg("正在将翻译好的项目tex项目编译为PDF...", chatbot=chatbot, history=history)
    success = yield from 编译Latex(chatbot, history, main_file_original='merge',
                                main_file_modified='merge_translate_zh', mode='translate_zh',
                                work_folder_original=project_folder, work_folder_modified=project_folder,
--- a/crazy_functions/PDF_Translate.py
+++ b/crazy_functions/PDF_Translate.py
@@ -1,5 +1,5 @@
 from toolbox import CatchException, check_packages, get_conf
-from toolbox import update_ui, update_ui_lastest_msg, disable_auto_promotion
+from toolbox import update_ui, update_ui_latest_msg, disable_auto_promotion
 from toolbox import trimmed_format_exc_markdown
 from crazy_functions.crazy_utils import get_files_from_everything
 from crazy_functions.pdf_fns.parse_pdf import get_avail_grobid_url
@@ -57,9 +57,9 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
            yield from 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url)
            return

-    if method == "ClASSIC":
+    if method == "Classic":
        # ------- 第三种方法，早期代码，效果不理想 -------
-        yield from update_ui_lastest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
+        yield from update_ui_latest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
        yield from 解析PDF_简单拆解(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
        return

@@ -77,7 +77,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
        if grobid_url is not None:
            yield from 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url)
            return
-        yield from update_ui_lastest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
+        yield from update_ui_latest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
        yield from 解析PDF_简单拆解(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
        return

--- a/crazy_functions/PDF_Translate_Wrap.py
+++ b/crazy_functions/PDF_Translate_Wrap.py
@@ -19,7 +19,7 @@ class PDF_Tran(GptAcademicPluginTemplate):
            "additional_prompt":
                ArgProperty(title="额外提示词", description="例如：对专有名词、翻译语气等方面的要求", default_value="", type="string").model_dump_json(), # 高级参数输入区，自动同步
            "pdf_parse_method":
-                ArgProperty(title="PDF解析方法", options=["DOC2X", "GROBID", "ClASSIC"], description="无", default_value="GROBID", type="dropdown").model_dump_json(),
+                ArgProperty(title="PDF解析方法", options=["DOC2X", "GROBID", "Classic"], description="无", default_value="GROBID", type="dropdown").model_dump_json(),
        }
        return gui_definition

--- a/crazy_functions/Paper_Reading.py
+++ b/crazy_functions/Paper_Reading.py
@@ -0,0 +1,360 @@
+import os
+import time
+import glob
+from pathlib import Path
+from datetime import datetime
+from dataclasses import dataclass
+from typing import Dict, List, Generator, Tuple
+from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+from toolbox import update_ui, promote_file_to_downloadzone, write_history_to_file, CatchException, report_exception
+from shared_utils.fastapi_server import validate_path_safety
+from crazy_functions.paper_fns.paper_download import extract_paper_id, extract_paper_ids, get_arxiv_paper, format_arxiv_id
+
+
+
+@dataclass
+class PaperQuestion:
+    """论文分析问题类"""
+    id: str  # 问题ID
+    question: str  # 问题内容
+    importance: int  # 重要性 (1-5，5最高)
+    description: str  # 问题描述
+
+
+class PaperAnalyzer:
+    """论文快速分析器"""
+
+    def __init__(self, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List, history: List, system_prompt: str):
+        """初始化分析器"""
+        self.llm_kwargs = llm_kwargs
+        self.plugin_kwargs = plugin_kwargs
+        self.chatbot = chatbot
+        self.history = history
+        self.system_prompt = system_prompt
+        self.paper_content = ""
+        self.results = {}
+
+        # 定义论文分析问题库（已合并为4个核心问题）
+        self.questions = [
+            PaperQuestion(
+                id="research_and_methods",
+                question="这篇论文的主要研究问题、目标和方法是什么？请分析：1)论文的核心研究问题和研究动机；2)论文提出的关键方法、模型或理论框架；3)这些方法如何解决研究问题。",
+                importance=5,
+                description="研究问题与方法"
+            ),
+            PaperQuestion(
+                id="findings_and_innovation",
+                question="论文的主要发现、结论及创新点是什么？请分析：1)论文的核心结果与主要发现；2)作者得出的关键结论；3)研究的创新点与对领域的贡献；4)与已有工作的区别。",
+                importance=4,
+                description="研究发现与创新"
+            ),
+            PaperQuestion(
+                id="methodology_and_data",
+                question="论文使用了什么研究方法和数据？请详细分析：1)研究设计与实验设置；2)数据收集方法与数据集特点；3)分析技术与评估方法；4)方法学上的合理性。",
+                importance=3,
+                description="研究方法与数据"
+            ),
+            PaperQuestion(
+                id="limitations_and_impact",
+                question="论文的局限性、未来方向及潜在影响是什么？请分析：1)研究的不足与限制因素；2)作者提出的未来研究方向；3)该研究对学术界和行业可能产生的影响；4)研究结果的适用范围与推广价值。",
+                importance=2,
+                description="局限性与影响"
+            ),
+        ]
+
+        # 按重要性排序
+        self.questions.sort(key=lambda q: q.importance, reverse=True)
+
+    def _load_paper(self, paper_path: str) -> Generator:
+        from crazy_functions.doc_fns.text_content_loader import TextContentLoader
+        """加载论文内容"""
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        # 使用TextContentLoader读取文件
+        loader = TextContentLoader(self.chatbot, self.history)
+
+        yield from loader.execute_single_file(paper_path)
+
+        # 获取加载的内容
+        if len(self.history) >= 2 and self.history[-2]:
+            self.paper_content = self.history[-2]
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return True
+        else:
+            self.chatbot.append(["错误", "无法读取论文内容，请检查文件是否有效"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return False
+
+    def _analyze_question(self, question: PaperQuestion) -> Generator:
+        """分析单个问题 - 直接显示问题和答案"""
+        try:
+            # 创建分析提示
+            prompt = f"请基于以下论文内容回答问题：\n\n{self.paper_content}\n\n问题：{question.question}"
+
+            # 使用单线程版本的请求函数
+            response = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs=prompt,
+                inputs_show_user=question.question,  # 显示问题本身
+                llm_kwargs=self.llm_kwargs,
+                chatbot=self.chatbot,
+                history=[],  # 空历史，确保每个问题独立分析
+                sys_prompt="你是一个专业的科研论文分析助手，需要仔细阅读论文内容并回答问题。请保持客观、准确，并基于论文内容提供深入分析。"
+            )
+
+            if response:
+                self.results[question.id] = response
+                return True
+            return False
+
+        except Exception as e:
+            self.chatbot.append(["错误", f"分析问题时出错: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return False
+
+    def _generate_summary(self) -> Generator:
+        """生成最终总结报告"""
+        self.chatbot.append(["生成报告", "正在整合分析结果，生成最终报告..."])
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        summary_prompt = "请基于以下对论文的各个方面的分析，生成一份全面的论文解读报告。报告应该简明扼要地呈现论文的关键内容，并保持逻辑连贯性。"
+
+        for q in self.questions:
+            if q.id in self.results:
+                summary_prompt += f"\n\n关于{q.description}的分析:\n{self.results[q.id]}"
+
+        try:
+            # 使用单线程版本的请求函数，可以在前端实时显示生成结果
+            response = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs=summary_prompt,
+                inputs_show_user="生成论文解读报告",
+                llm_kwargs=self.llm_kwargs,
+                chatbot=self.chatbot,
+                history=[],
+                sys_prompt="你是一个科研论文解读专家，请将多个方面的分析整合为一份完整、连贯、有条理的报告。报告应当重点突出，层次分明，并且保持学术性和客观性。"
+            )
+
+            if response:
+                return response
+            return "报告生成失败"
+
+        except Exception as e:
+            self.chatbot.append(["错误", f"生成报告时出错: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return "报告生成失败: " + str(e)
+
+    def save_report(self, report: str) -> Generator:
+        """保存分析报告"""
+        timestamp = time.strftime("%Y%m%d_%H%M%S")
+
+        # 保存为Markdown文件
+        try:
+            md_content = f"# 论文快速解读报告\n\n{report}"
+            for q in self.questions:
+                if q.id in self.results:
+                    md_content += f"\n\n## {q.description}\n\n{self.results[q.id]}"
+
+            result_file = write_history_to_file(
+                history=[md_content],
+                file_basename=f"论文解读_{timestamp}.md"
+            )
+
+            if result_file and os.path.exists(result_file):
+                promote_file_to_downloadzone(result_file, chatbot=self.chatbot)
+                self.chatbot.append(["保存成功", f"解读报告已保存至: {os.path.basename(result_file)}"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+            else:
+                self.chatbot.append(["警告", "保存报告成功但找不到文件"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+        except Exception as e:
+            self.chatbot.append(["警告", f"保存报告失败: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+    def analyze_paper(self, paper_path: str) -> Generator:
+        """分析论文主流程"""
+        # 加载论文
+        success = yield from self._load_paper(paper_path)
+        if not success:
+            return
+
+        # 分析关键问题 - 直接询问每个问题，不显示进度信息
+        for question in self.questions:
+            yield from self._analyze_question(question)
+
+        # 生成总结报告
+        final_report = yield from self._generate_summary()
+
+        # 显示最终报告
+        # self.chatbot.append(["论文解读报告", final_report])
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        # 保存报告
+        yield from self.save_report(final_report)
+
+
+def _find_paper_file(path: str) -> str:
+    """查找路径中的论文文件（简化版）"""
+    if os.path.isfile(path):
+        return path
+
+    # 支持的文件扩展名（按优先级排序）
+    extensions = ["pdf", "docx", "doc", "txt", "md", "tex"]
+
+    # 简单地遍历目录
+    if os.path.isdir(path):
+        try:
+            for ext in extensions:
+                # 手动检查每个可能的文件，而不使用glob
+                potential_file = os.path.join(path, f"paper.{ext}")
+                if os.path.exists(potential_file) and os.path.isfile(potential_file):
+                    return potential_file
+
+            # 如果没找到特定命名的文件，检查目录中的所有文件
+            for file in os.listdir(path):
+                file_path = os.path.join(path, file)
+                if os.path.isfile(file_path):
+                    file_ext = file.split('.')[-1].lower() if '.' in file else ""
+                    if file_ext in extensions:
+                        return file_path
+        except Exception:
+            pass  # 忽略任何错误
+
+    return None
+
+
+def download_paper_by_id(paper_info, chatbot, history) -> str:
+    """下载论文并返回保存路径
+
+    Args:
+        paper_info: 元组，包含论文ID类型（arxiv或doi）和ID值
+        chatbot: 聊天机器人对象
+        history: 历史记录
+
+    Returns:
+        str: 下载的论文路径或None
+    """
+    from crazy_functions.review_fns.data_sources.scihub_source import SciHub
+    id_type, paper_id = paper_info
+
+    # 创建保存目录 - 使用时间戳创建唯一文件夹
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    user_name = chatbot.get_user() if hasattr(chatbot, 'get_user') else "default"
+    from toolbox import get_log_folder, get_user
+    base_save_dir = get_log_folder(get_user(chatbot), plugin_name='paper_download')
+    save_dir = os.path.join(base_save_dir, f"papers_{timestamp}")
+    if not os.path.exists(save_dir):
+        os.makedirs(save_dir)
+    save_path = Path(save_dir)
+
+    chatbot.append([f"下载论文", f"正在下载{'arXiv' if id_type == 'arxiv' else 'DOI'} {paper_id} 的论文..."])
+    update_ui(chatbot=chatbot, history=history)
+
+    pdf_path = None
+
+    try:
+        if id_type == 'arxiv':
+            # 使用改进的arxiv查询方法
+            formatted_id = format_arxiv_id(paper_id)
+            paper_result = get_arxiv_paper(formatted_id)
+
+            if not paper_result:
+                chatbot.append([f"下载失败", f"未找到arXiv论文: {paper_id}"])
+                update_ui(chatbot=chatbot, history=history)
+                return None
+
+            # 下载PDF
+            filename = f"arxiv_{paper_id.replace('/', '_')}.pdf"
+            pdf_path = str(save_path / filename)
+            paper_result.download_pdf(filename=pdf_path)
+
+        else:  # doi
+            # 下载DOI
+            sci_hub = SciHub(
+                doi=paper_id,
+                path=save_path
+            )
+            pdf_path = sci_hub.fetch()
+
+        # 检查下载结果
+        if pdf_path and os.path.exists(pdf_path):
+            promote_file_to_downloadzone(pdf_path, chatbot=chatbot)
+            chatbot.append([f"下载成功", f"已成功下载论文: {os.path.basename(pdf_path)}"])
+            update_ui(chatbot=chatbot, history=history)
+            return pdf_path
+        else:
+            chatbot.append([f"下载失败", f"论文下载失败: {paper_id}"])
+            update_ui(chatbot=chatbot, history=history)
+            return None
+
+    except Exception as e:
+        chatbot.append([f"下载错误", f"下载论文时出错: {str(e)}"])
+        update_ui(chatbot=chatbot, history=history)
+        return None
+
+
+@CatchException
+def 快速论文解读(txt: str, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List,
+             history: List, system_prompt: str, user_request: str):
+    """主函数 - 论文快速解读"""
+    # 初始化分析器
+    chatbot.append(["函数插件功能及使用方式", "论文快速解读：通过分析论文的关键要素，帮助您迅速理解论文内容，适用于各学科领域的科研论文。 <br><br>📋 使用方式：<br>1、直接上传PDF文件或者输入DOI号（仅针对SCI hub存在的论文）或arXiv ID（如2501.03916）<br>2、点击插件开始分析"])
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    paper_file = None
+
+    # 检查输入是否为论文ID（arxiv或DOI）
+    paper_info = extract_paper_id(txt)
+
+    if paper_info:
+        # 如果是论文ID，下载论文
+        chatbot.append(["检测到论文ID", f"检测到{'arXiv' if paper_info[0] == 'arxiv' else 'DOI'} ID: {paper_info[1]}，准备下载论文..."])
+        yield from update_ui(chatbot=chatbot, history=history)
+
+        # 下载论文 - 完全重新实现
+        paper_file = download_paper_by_id(paper_info, chatbot, history)
+
+        if not paper_file:
+            report_exception(chatbot, history, a=f"下载论文失败", b=f"无法下载{'arXiv' if paper_info[0] == 'arxiv' else 'DOI'}论文: {paper_info[1]}")
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+    else:
+        # 检查输入路径
+        if not os.path.exists(txt):
+            report_exception(chatbot, history, a=f"解析论文: {txt}", b=f"找不到文件或无权访问: {txt}")
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+
+        # 验证路径安全性
+        user_name = chatbot.get_user()
+        validate_path_safety(txt, user_name)
+
+        # 查找论文文件
+        paper_file = _find_paper_file(txt)
+
+        if not paper_file:
+            report_exception(chatbot, history, a=f"解析论文", b=f"在路径 {txt} 中未找到支持的论文文件")
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    # 增加调试信息，检查paper_file的类型和值
+    chatbot.append(["文件类型检查", f"paper_file类型: {type(paper_file)}, 值: {paper_file}"])
+    yield from update_ui(chatbot=chatbot, history=history)
+    chatbot.pop()  # 移除调试信息
+
+    # 确保paper_file是字符串
+    if paper_file is not None and not isinstance(paper_file, str):
+        # 尝试转换为字符串
+        try:
+            paper_file = str(paper_file)
+        except:
+            report_exception(chatbot, history, a=f"类型错误", b=f"论文路径不是有效的字符串: {type(paper_file)}")
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+
+    # 分析论文
+    chatbot.append(["开始分析", f"正在分析论文: {os.path.basename(paper_file)}"])
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    analyzer = PaperAnalyzer(llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
+    yield from analyzer.analyze_paper(paper_file)
--- a/crazy_functions/Rag_Interface.py
+++ b/crazy_functions/Rag_Interface.py
@@ -4,7 +4,7 @@ from typing import List
 from shared_utils.fastapi_server import validate_path_safety

 from toolbox import report_exception
-from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_lastest_msg
+from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_latest_msg
 from shared_utils.fastapi_server import validate_path_safety
 from crazy_functions.crazy_utils import input_clipping
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
@@ -92,7 +92,7 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
        chatbot.append([txt, f'正在清空 ({current_context}) ...'])
        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
        rag_worker.purge_vector_store()
-        yield from update_ui_lastest_msg('已清空', chatbot, history, delay=0)  # 刷新界面
+        yield from update_ui_latest_msg('已清空', chatbot, history, delay=0)  # 刷新界面
        return

    # 3. Normal Q&A processing
@@ -109,10 +109,10 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u

    # 5. If input is clipped, add input to vector store before retrieve
    if input_is_clipped_flag:
-        yield from update_ui_lastest_msg('检测到长输入, 正在向量化 ...', chatbot, history, delay=0)  # 刷新界面
+        yield from update_ui_latest_msg('检测到长输入, 正在向量化 ...', chatbot, history, delay=0)  # 刷新界面
        # Save input to vector store
        rag_worker.add_text_to_vector_store(txt_origin)
-        yield from update_ui_lastest_msg('向量化完成 ...', chatbot, history, delay=0)  # 刷新界面
+        yield from update_ui_latest_msg('向量化完成 ...', chatbot, history, delay=0)  # 刷新界面

        if len(txt_origin) > REMEMBER_PREVIEW:
            HALF = REMEMBER_PREVIEW // 2
@@ -142,7 +142,7 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
    )

    # 8. Remember Q&A
-    yield from update_ui_lastest_msg(
+    yield from update_ui_latest_msg(
        model_say + '</br></br>' + f'对话记忆中, 请稍等 ({current_context}) ...',
        chatbot, history, delay=0.5
    )
@@ -150,4 +150,4 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
    history.extend([i_say, model_say])

    # 9. Final UI Update
-    yield from update_ui_lastest_msg(model_say, chatbot, history, delay=0, msg=tip)
+    yield from update_ui_latest_msg(model_say, chatbot, history, delay=0, msg=tip)
--- a/crazy_functions/Social_Helper.py
+++ b/crazy_functions/Social_Helper.py
@@ -1,5 +1,5 @@
 import pickle, os, random
-from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_lastest_msg
+from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_latest_msg
 from crazy_functions.crazy_utils import input_clipping
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -9,7 +9,7 @@ from loguru import logger
 from typing import List


-SOCIAL_NETWOK_WORKER_REGISTER = {}
+SOCIAL_NETWORK_WORKER_REGISTER = {}

 class SocialNetwork():
    def __init__(self):
@@ -78,7 +78,7 @@ class SocialNetworkWorker(SaveAndLoad):
            for f in friend.friends_list: 
                self.add_friend(f)
            msg = f"成功添加{len(friend.friends_list)}个联系人: {str(friend.friends_list)}"
-            yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=0)
+            yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=0)


    def run(self, txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
@@ -104,12 +104,12 @@ class SocialNetworkWorker(SaveAndLoad):
        }

        try:
-            Explaination = '\n'.join([f'{k}: {v["explain_to_llm"]}' for k, v in self.tools_to_select.items()])
+            Explanation = '\n'.join([f'{k}: {v["explain_to_llm"]}' for k, v in self.tools_to_select.items()])
            class UserSociaIntention(BaseModel):
                intention_type: str = Field(
                    description=
                        f"The type of user intention. You must choose from {self.tools_to_select.keys()}.\n\n" 
-                        f"Explaination:\n{Explaination}", 
+                        f"Explanation:\n{Explanation}", 
                    default="SocialAdvice"
                )
            pydantic_cls_instance, err_msg = select_tool(
@@ -118,7 +118,7 @@ class SocialNetworkWorker(SaveAndLoad):
                pydantic_cls=UserSociaIntention
            )
        except Exception as e:
-            yield from update_ui_lastest_msg(
+            yield from update_ui_latest_msg(
                lastmsg=f"无法理解用户意图 {err_msg}", 
                chatbot=chatbot, 
                history=history, 
@@ -150,10 +150,10 @@ def I人助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt,
    # 1. we retrieve worker from global context
    user_name = chatbot.get_user()
    checkpoint_dir=get_log_folder(user_name, plugin_name='experimental_rag')
-    if user_name in SOCIAL_NETWOK_WORKER_REGISTER:
-        social_network_worker = SOCIAL_NETWOK_WORKER_REGISTER[user_name]
+    if user_name in SOCIAL_NETWORK_WORKER_REGISTER:
+        social_network_worker = SOCIAL_NETWORK_WORKER_REGISTER[user_name]
    else:
-        social_network_worker = SOCIAL_NETWOK_WORKER_REGISTER[user_name] = SocialNetworkWorker(
+        social_network_worker = SOCIAL_NETWORK_WORKER_REGISTER[user_name] = SocialNetworkWorker(
            user_name, 
            llm_kwargs, 
            checkpoint_dir=checkpoint_dir, 
--- a/crazy_functions/SourceCode_Comment.py
+++ b/crazy_functions/SourceCode_Comment.py
@@ -1,5 +1,5 @@
 import os, copy, time
-from toolbox import CatchException, report_exception, update_ui, zip_result, promote_file_to_downloadzone, update_ui_lastest_msg, get_conf, generate_file_link
+from toolbox import CatchException, report_exception, update_ui, zip_result, promote_file_to_downloadzone, update_ui_latest_msg, get_conf, generate_file_link
 from shared_utils.fastapi_server import validate_path_safety
 from crazy_functions.crazy_utils import input_clipping
 from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
@@ -117,7 +117,7 @@ def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
                logger.error(f"文件: {fp} 的注释结果未能成功")
        file_links = generate_file_link(preview_html_list)

-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
            f"当前任务: <br/>{'<br/>'.join(tasks)}.<br/>" + 
            f"剩余源文件数量: {remain}.<br/>" + 
            f"已完成的文件: {sum(worker_done)}.<br/>" + 
--- a/crazy_functions/VideoResource_GPT.py
+++ b/crazy_functions/VideoResource_GPT.py
@@ -7,7 +7,7 @@ from bs4 import BeautifulSoup
 from functools import lru_cache
 from itertools import zip_longest
 from check_proxy import check_proxy
-from toolbox import CatchException, update_ui, get_conf, promote_file_to_downloadzone, update_ui_lastest_msg, generate_file_link
+from toolbox import CatchException, update_ui, get_conf, promote_file_to_downloadzone, update_ui_latest_msg, generate_file_link
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
 from request_llms.bridge_all import model_info
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -46,7 +46,7 @@ def download_video(bvid, user_name, chatbot, history):
    # pause a while
    tic_time = 8
    for i in range(tic_time):
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
            lastmsg=f"即将下载音频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。", 
            chatbot=chatbot, history=[], delay=1)

@@ -61,13 +61,13 @@ def download_video(bvid, user_name, chatbot, history):
    # preview
    preview_list = [promote_file_to_downloadzone(fp) for fp in downloaded_files]
    file_links = generate_file_link(preview_list)
-    yield from update_ui_lastest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_latest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
    chatbot.append((None, f"即将下载视频。"))

    # pause a while
    tic_time = 16
    for i in range(tic_time):
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
            lastmsg=f"即将下载视频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。", 
            chatbot=chatbot, history=[], delay=1)

@@ -78,7 +78,7 @@ def download_video(bvid, user_name, chatbot, history):
    # preview
    preview_list = [promote_file_to_downloadzone(fp) for fp in downloaded_files_part2]
    file_links = generate_file_link(preview_list)
-    yield from update_ui_lastest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_latest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)

    # return
    return downloaded_files + downloaded_files_part2
@@ -110,7 +110,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
        # 结构化生成
        internet_search_keyword = user_wish

-        yield from update_ui_lastest_msg(lastmsg=f"发起互联网检索: {internet_search_keyword} ...", chatbot=chatbot, history=[], delay=1)
+        yield from update_ui_latest_msg(lastmsg=f"发起互联网检索: {internet_search_keyword} ...", chatbot=chatbot, history=[], delay=1)
        from crazy_functions.Internet_GPT import internet_search_with_analysis_prompt
        result = yield from internet_search_with_analysis_prompt(
            prompt=internet_search_keyword,
@@ -119,7 +119,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
            chatbot=chatbot
        )

-        yield from update_ui_lastest_msg(lastmsg=f"互联网检索结论: {result} \n\n 正在生成进一步检索方案 ...", chatbot=chatbot, history=[], delay=1)
+        yield from update_ui_latest_msg(lastmsg=f"互联网检索结论: {result} \n\n 正在生成进一步检索方案 ...", chatbot=chatbot, history=[], delay=1)
        rf_req = dedent(f"""
        The user wish to get the following resource:
            {user_wish}
@@ -132,7 +132,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
        rf_req = dedent(f"""
        The user wish to get the following resource:
            {user_wish}
-        Generate reseach keywords (less than 5 keywords) accordingly.
+        Generate research keywords (less than 5 keywords) accordingly.
        """)
    gpt_json_io = GptJsonIO(Query)
    inputs = rf_req + gpt_json_io.format_instructions
@@ -146,12 +146,12 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

    # 获取候选资源
-    candadate_dictionary: dict =  get_video_resource(video_engine_keywords)
-    candadate_dictionary_as_str = json.dumps(candadate_dictionary, ensure_ascii=False, indent=4)
+    candidate_dictionary: dict =  get_video_resource(video_engine_keywords)
+    candidate_dictionary_as_str = json.dumps(candidate_dictionary, ensure_ascii=False, indent=4)

    # 展示候选资源
-    candadate_display = "\n".join([f"{i+1}. {it['title']}" for i, it in enumerate(candadate_dictionary)])
-    chatbot.append((None, f"候选:\n\n{candadate_display}"))
+    candidate_display = "\n".join([f"{i+1}. {it['title']}" for i, it in enumerate(candidate_dictionary)])
+    chatbot.append((None, f"候选:\n\n{candidate_display}"))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

    # 结构化生成
@@ -160,7 +160,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
        {user_wish}

    Select the most relevant and suitable video resource from the following search results:
-        {candadate_dictionary_as_str}
+        {candidate_dictionary_as_str}

    Note:
        1. The first several search video results are more likely to satisfy the user's wish.
--- a/crazy_functions/agent_fns/auto_agent.py
+++ b/crazy_functions/agent_fns/auto_agent.py
@@ -1,5 +1,5 @@
 from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
-from toolbox import report_exception, get_log_folder, update_ui_lastest_msg, Singleton
+from toolbox import report_exception, get_log_folder, update_ui_latest_msg, Singleton
 from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom
 from crazy_functions.agent_fns.general import AutoGenGeneral

--- a/crazy_functions/agent_fns/echo_agent.py
+++ b/crazy_functions/agent_fns/echo_agent.py
@@ -8,7 +8,7 @@ class EchoDemo(PluginMultiprocessManager):
        while True:
            msg = self.child_conn.recv() # PipeCom
            if msg.cmd == "user_input":
-                # wait futher user input
+                # wait father user input
                self.child_conn.send(PipeCom("show", msg.content))
                wait_success = self.subprocess_worker_wait_user_feedback(wait_msg="我准备好处理下一个问题了.")
                if not wait_success:
--- a/crazy_functions/agent_fns/general.py
+++ b/crazy_functions/agent_fns/general.py
@@ -27,7 +27,7 @@ def gpt_academic_generate_oai_reply(
        llm_kwargs=llm_config,
        history=history,
        sys_prompt=self._oai_system_message[0]['content'],
-        console_slience=True
+        console_silence=True
    )
    assumed_done = reply.endswith('\nTERMINATE')
    return True, reply
--- a/crazy_functions/agent_fns/python_comment_agent.py
+++ b/crazy_functions/agent_fns/python_comment_agent.py
@@ -10,7 +10,7 @@ from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_
 # TODO: 解决缩进问题

 find_function_end_prompt = '''
-Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to sperate functions, class functions etc.
+Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to separate functions, class functions etc.
 - Provide the line number where the first visible function ends.
 - Provide the line number where the next visible function begins.
 - If there are no other functions in this page, you should simply return the line number of the last line.
@@ -59,7 +59,7 @@ OUTPUT:



-revise_funtion_prompt = '''
+revise_function_prompt = '''
 You need to read the following code, and revise the source code ({FILE_BASENAME}) according to following instructions:
 1. You should analyze the purpose of the functions (if there are any).
 2. You need to add docstring for the provided functions (if there are any).
@@ -117,7 +117,7 @@ def zip_result(folder):
 '''


-revise_funtion_prompt_chinese = '''
+revise_function_prompt_chinese = '''
 您需要阅读以下代码，并根据以下说明修订源代码({FILE_BASENAME}):
 1. 如果源代码中包含函数的话, 你应该分析给定函数实现了什么功能
 2. 如果源代码中包含函数的话, 你需要为函数添加docstring, docstring必须使用中文
@@ -188,9 +188,9 @@ class PythonCodeComment():
        self.language = language
        self.observe_window_update = observe_window_update
        if self.language == "chinese":
-            self.core_prompt = revise_funtion_prompt_chinese
+            self.core_prompt = revise_function_prompt_chinese
        else:
-            self.core_prompt = revise_funtion_prompt
+            self.core_prompt = revise_function_prompt
        self.path = None
        self.file_basename = None
        self.file_brief = ""
@@ -222,7 +222,7 @@ class PythonCodeComment():
            history=[],
            sys_prompt="",
            observe_window=[],
-            console_slience=True
+            console_silence=True
        )

        def extract_number(text):
@@ -316,7 +316,7 @@ class PythonCodeComment():
    def tag_code(self, fn, hint):
        code = fn
        _, n_indent = self.dedent(code)
-        indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preseve them in the OUTPUT.)"
+        indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preserve them in the OUTPUT.)"
        brief_reminder = "" if self.file_brief == "" else f"({self.file_basename} abstract: {self.file_brief})"
        hint_reminder = "" if hint is None else f"(Reminder: do not ignore or modify code such as `{hint}`, provide complete code in the OUTPUT.)"
        self.llm_kwargs['temperature'] = 0
@@ -333,7 +333,7 @@ class PythonCodeComment():
            history=[],
            sys_prompt="",
            observe_window=[],
-            console_slience=True
+            console_silence=True
        )

        def get_code_block(reply):
@@ -400,7 +400,7 @@ class PythonCodeComment():
        return revised

    def begin_comment_source_code(self, chatbot=None, history=None):
-        # from toolbox import update_ui_lastest_msg
+        # from toolbox import update_ui_latest_msg
        assert self.path is not None
        assert '.py' in self.path   # must be python source code
        # write_target = self.path + '.revised.py'
@@ -409,10 +409,10 @@ class PythonCodeComment():
        # with open(self.path + '.revised.py', 'w+', encoding='utf8') as f:
        while True:
            try:
-                # yield from update_ui_lastest_msg(f"({self.file_basename}) 正在读取下一段代码片段:\n", chatbot=chatbot, history=history, delay=0)
+                # yield from update_ui_latest_msg(f"({self.file_basename}) 正在读取下一段代码片段:\n", chatbot=chatbot, history=history, delay=0)
                next_batch, line_no_start, line_no_end = self.get_next_batch()
                self.observe_window_update(f"正在处理{self.file_basename} - {line_no_start}/{len(self.full_context)}\n")
-                # yield from update_ui_lastest_msg(f"({self.file_basename}) 处理代码片段:\n\n{next_batch}", chatbot=chatbot, history=history, delay=0)
+                # yield from update_ui_latest_msg(f"({self.file_basename}) 处理代码片段:\n\n{next_batch}", chatbot=chatbot, history=history, delay=0)
                
                hint = None
                MAX_ATTEMPT = 2
--- a/crazy_functions/crazy_utils.py
+++ b/crazy_functions/crazy_utils.py
@@ -1,7 +1,7 @@
 import os
 import threading
 from loguru import logger
-from shared_utils.char_visual_effect import scolling_visual_effect
+from shared_utils.char_visual_effect import scrolling_visual_effect
 from toolbox import update_ui, get_conf, trimmed_format_exc, get_max_token, Singleton

 def input_clipping(inputs, history, max_token_limit, return_clip_flags=False):
@@ -256,7 +256,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
                # 【第一种情况】：顺利完成
                gpt_say = predict_no_ui_long_connection(
                    inputs=inputs, llm_kwargs=llm_kwargs, history=history,
-                    sys_prompt=sys_prompt, observe_window=mutable[index], console_slience=True
+                    sys_prompt=sys_prompt, observe_window=mutable[index], console_silence=True
                )
                mutable[index][2] = "已成功"
                return gpt_say
@@ -326,7 +326,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
            mutable[thread_index][1] = time.time()
        # 在前端打印些好玩的东西
        for thread_index, _ in enumerate(worker_done):
-            print_something_really_funny = f"[ ...`{scolling_visual_effect(mutable[thread_index][0], scroller_max_len)}`... ]"
+            print_something_really_funny = f"[ ...`{scrolling_visual_effect(mutable[thread_index][0], scroller_max_len)}`... ]"
            observe_win.append(print_something_really_funny)
        # 在前端打印些好玩的东西
        stat_str = ''.join([f'`{mutable[thread_index][2]}`: {obs}\n\n'
@@ -389,11 +389,11 @@ def read_and_clean_pdf_text(fp):
        """
        提取文本块主字体
        """
-        fsize_statiscs = {}
+        fsize_statistics = {}
        for wtf in l['spans']:
-            if wtf['size'] not in fsize_statiscs: fsize_statiscs[wtf['size']] = 0
-            fsize_statiscs[wtf['size']] += len(wtf['text'])
-        return max(fsize_statiscs, key=fsize_statiscs.get)
+            if wtf['size'] not in fsize_statistics: fsize_statistics[wtf['size']] = 0
+            fsize_statistics[wtf['size']] += len(wtf['text'])
+        return max(fsize_statistics, key=fsize_statistics.get)

    def ffsize_same(a,b):
        """
@@ -433,11 +433,11 @@ def read_and_clean_pdf_text(fp):

        ############################## <第 2 步，获取正文主字体> ##################################
        try:
-            fsize_statiscs = {}
+            fsize_statistics = {}
            for span in meta_span:
-                if span[1] not in fsize_statiscs: fsize_statiscs[span[1]] = 0
-                fsize_statiscs[span[1]] += span[2]
-            main_fsize = max(fsize_statiscs, key=fsize_statiscs.get)
+                if span[1] not in fsize_statistics: fsize_statistics[span[1]] = 0
+                fsize_statistics[span[1]] += span[2]
+            main_fsize = max(fsize_statistics, key=fsize_statistics.get)
            if REMOVE_FOOT_NOTE:
                give_up_fize_threshold = main_fsize * REMOVE_FOOT_FFSIZE_PERCENT
        except:
@@ -610,9 +610,9 @@ class nougat_interface():


    def NOUGAT_parse_pdf(self, fp, chatbot, history):
-        from toolbox import update_ui_lastest_msg
+        from toolbox import update_ui_latest_msg

-        yield from update_ui_lastest_msg("正在解析论文, 请稍候。进度：正在排队, 等待线程锁...",
+        yield from update_ui_latest_msg("正在解析论文, 请稍候。进度：正在排队, 等待线程锁...",
                                         chatbot=chatbot, history=history, delay=0)
        self.threadLock.acquire()
        import glob, threading, os
@@ -620,7 +620,7 @@ class nougat_interface():
        dst = os.path.join(get_log_folder(plugin_name='nougat'), gen_time_str())
        os.makedirs(dst)

-        yield from update_ui_lastest_msg("正在解析论文, 请稍候。进度：正在加载NOUGAT... （提示：首次运行需要花费较长时间下载NOUGAT参数）",
+        yield from update_ui_latest_msg("正在解析论文, 请稍候。进度：正在加载NOUGAT... （提示：首次运行需要花费较长时间下载NOUGAT参数）",
                                         chatbot=chatbot, history=history, delay=0)
        command = ['nougat', '--out', os.path.abspath(dst), os.path.abspath(fp)]
        self.nougat_with_timeout(command, cwd=os.getcwd(), timeout=3600)
--- a/crazy_functions/doc_fns/AI_review_doc.py
+++ b/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>
+        """
--- a/crazy_functions/doc_fns/init.py
+++ b/crazy_functions/doc_fns/init.py
--- a/crazy_functions/doc_fns/batch_file_query_doc.py
+++ b/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>
+        """
--- a/crazy_functions/doc_fns/content_folder.py
+++ b/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)
+
--- a/crazy_functions/doc_fns/conversation_doc/excel_doc.py
+++ b/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)
--- a/crazy_functions/doc_fns/conversation_doc/html_doc.py
+++ b/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>
+        """
--- a/crazy_functions/doc_fns/conversation_doc/markdown_doc.py
+++ b/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)
--- a/crazy_functions/doc_fns/conversation_doc/pdf_doc.py
+++ b/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
--- a/crazy_functions/doc_fns/conversation_doc/txt_doc.py
+++ b/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)
--- a/crazy_functions/doc_fns/conversation_doc/word2pdf.py
+++ b/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)}") 
--- a/crazy_functions/doc_fns/conversation_doc/word_doc.py
+++ b/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
+
--- a/crazy_functions/doc_fns/read_fns/init.py
+++ b/crazy_functions/doc_fns/read_fns/init.py
--- a/crazy_functions/doc_fns/read_fns/docx_reader.py
+++ b/crazy_functions/doc_fns/read_fns/docx_reader.py
@@ -0,0 +1,4 @@
+import nltk
+nltk.data.path.append('~/nltk_data')
+nltk.download('averaged_perceptron_tagger', download_dir='~/nltk_data')
+nltk.download('punkt', download_dir='~/nltk_data')
--- a/crazy_functions/doc_fns/read_fns/excel_reader.py
+++ b/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()
--- a/crazy_functions/doc_fns/read_fns/markitdown/markdown_reader.py
+++ b/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() 
--- a/crazy_functions/doc_fns/read_fns/unstructured_all/init.py
+++ b/crazy_functions/doc_fns/read_fns/unstructured_all/init.py
--- a/crazy_functions/doc_fns/read_fns/unstructured_all/paper_metadata_extractor.py
+++ b/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() 
--- a/crazy_functions/doc_fns/read_fns/unstructured_all/paper_structure_extractor.py
+++ b/crazy_functions/doc_fns/read_fns/unstructured_all/paper_structure_extractor.py
--- a/crazy_functions/doc_fns/read_fns/unstructured_all/unstructured_md.py
+++ b/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)
--- a/crazy_functions/doc_fns/read_fns/unstructured_all/unstructured_reader.py
+++ b/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()
--- a/crazy_functions/doc_fns/read_fns/web_reader.py
+++ b/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()
--- a/crazy_functions/doc_fns/text_content_loader.py
+++ b/crazy_functions/doc_fns/text_content_loader.py
@@ -0,0 +1,451 @@
+import os
+import re
+import glob
+import time
+import queue
+import threading
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from typing import List, Generator, Tuple, Set, Optional, Dict
+from dataclasses import dataclass
+from loguru import logger
+from toolbox import update_ui
+from crazy_functions.rag_fns.rag_file_support import extract_text
+from crazy_functions.doc_fns.content_folder import ContentFoldingManager, FileMetadata, FoldingOptions, FoldingStyle, FoldingError
+from shared_utils.fastapi_server import validate_path_safety
+from datetime import datetime
+import mimetypes
+
+@dataclass
+class FileInfo:
+    """文件信息数据类"""
+    path: str  # 完整路径
+    rel_path: str  # 相对路径
+    size: float  # 文件大小(MB)
+    extension: str  # 文件扩展名
+    last_modified: str  # 最后修改时间
+
+
+class TextContentLoader:
+    """优化版本的文本内容加载器 - 保持原有接口"""
+
+    # 压缩文件扩展名
+    COMPRESSED_EXTENSIONS: Set[str] = {'.zip', '.rar', '.7z', '.tar', '.gz', '.bz2', '.xz'}
+
+    # 系统配置
+    MAX_FILE_SIZE: int = 100 * 1024 * 1024  # 最大文件大小（100MB）
+    MAX_TOTAL_SIZE: int = 100 * 1024 * 1024  # 最大总大小（100MB）
+    MAX_FILES: int = 100  # 最大文件数量
+    CHUNK_SIZE: int = 1024 * 1024  # 文件读取块大小（1MB）
+    MAX_WORKERS: int = min(32, (os.cpu_count() or 1) * 4)  # 最大工作线程数
+    BATCH_SIZE: int = 5  # 批处理大小
+
+    def __init__(self, chatbot: List, history: List):
+        """初始化加载器"""
+        self.chatbot = chatbot
+        self.history = history
+        self.failed_files: List[Tuple[str, str]] = []
+        self.processed_size: int = 0
+        self.start_time: float = 0
+        self.file_cache: Dict[str, str] = {}
+        self._lock = threading.Lock()
+        self.executor = ThreadPoolExecutor(max_workers=self.MAX_WORKERS)
+        self.results_queue = queue.Queue()
+        self.folding_manager = ContentFoldingManager()
+
+    def _create_file_info(self, entry: os.DirEntry, root_path: str) -> FileInfo:
+        """优化的文件信息创建
+
+        Args:
+            entry: 目录入口对象
+            root_path: 根路径
+
+        Returns:
+            FileInfo: 文件信息对象
+        """
+        try:
+            stats = entry.stat()  # 使用缓存的文件状态
+            return FileInfo(
+                path=entry.path,
+                rel_path=os.path.relpath(entry.path, root_path),
+                size=stats.st_size / (1024 * 1024),
+                extension=os.path.splitext(entry.path)[1].lower(),
+                last_modified=time.strftime('%Y-%m-%d %H:%M:%S',
+                                          time.localtime(stats.st_mtime))
+            )
+        except (OSError, ValueError) as e:
+            return None
+
+    def _process_file_batch(self, file_batch: List[FileInfo]) -> List[Tuple[FileInfo, Optional[str]]]:
+        """批量处理文件
+
+        Args:
+            file_batch: 要处理的文件信息列表
+
+        Returns:
+            List[Tuple[FileInfo, Optional[str]]]: 处理结果列表
+        """
+        results = []
+        futures = {}
+
+        for file_info in file_batch:
+            if file_info.path in self.file_cache:
+                results.append((file_info, self.file_cache[file_info.path]))
+                continue
+
+            if file_info.size * 1024 * 1024 > self.MAX_FILE_SIZE:
+                with self._lock:
+                    self.failed_files.append(
+                        (file_info.rel_path,
+                         f"文件过大（{file_info.size:.2f}MB > {self.MAX_FILE_SIZE / (1024 * 1024)}MB）")
+                    )
+                continue
+
+            future = self.executor.submit(self._read_file_content, file_info)
+            futures[future] = file_info
+
+        for future in as_completed(futures):
+            file_info = futures[future]
+            try:
+                content = future.result()
+                if content:
+                    with self._lock:
+                        self.file_cache[file_info.path] = content
+                        self.processed_size += file_info.size * 1024 * 1024
+                    results.append((file_info, content))
+            except Exception as e:
+                with self._lock:
+                    self.failed_files.append((file_info.rel_path, f"读取失败: {str(e)}"))
+
+        return results
+
+    def _read_file_content(self, file_info: FileInfo) -> Optional[str]:
+        """读取单个文件内容
+
+        Args:
+            file_info: 文件信息对象
+
+        Returns:
+            Optional[str]: 文件内容
+        """
+        try:
+            content = extract_text(file_info.path)
+            if not content or not content.strip():
+                return None
+            return content
+        except Exception as e:
+            logger.exception(f"读取文件失败: {str(e)}")
+            raise Exception(f"读取文件失败: {str(e)}")
+
+    def _is_valid_file(self, file_path: str) -> bool:
+        """检查文件是否有效
+
+        Args:
+            file_path: 文件路径
+
+        Returns:
+            bool: 是否为有效文件
+        """
+        if not os.path.isfile(file_path):
+            return False
+
+        extension = os.path.splitext(file_path)[1].lower()
+        if (extension in self.COMPRESSED_EXTENSIONS or
+            os.path.basename(file_path).startswith('.') or
+            not os.access(file_path, os.R_OK)):
+            return False
+
+        # 只要文件可以访问且不在排除列表中就认为是有效的
+        return True
+
+    def _collect_files(self, path: str) -> List[FileInfo]:
+        """收集文件信息
+
+        Args:
+            path: 目标路径
+
+        Returns:
+            List[FileInfo]: 有效文件信息列表
+        """
+        files = []
+        total_size = 0
+
+        # 处理单个文件的情况
+        if os.path.isfile(path):
+            if self._is_valid_file(path):
+                file_info = self._create_file_info(os.DirEntry(os.path.dirname(path)), os.path.dirname(path))
+                if file_info:
+                    return [file_info]
+            return []
+
+        # 处理目录的情况
+        try:
+            # 使用os.walk来递归遍历目录
+            for root, _, filenames in os.walk(path):
+                for filename in filenames:
+                    if len(files) >= self.MAX_FILES:
+                        self.failed_files.append((filename, f"超出最大文件数限制({self.MAX_FILES})"))
+                        continue
+
+                    file_path = os.path.join(root, filename)
+
+                    if not self._is_valid_file(file_path):
+                        continue
+
+                    try:
+                        stats = os.stat(file_path)
+                        file_size = stats.st_size / (1024 * 1024)  # 转换为MB
+
+                        if file_size * 1024 * 1024 > self.MAX_FILE_SIZE:
+                            self.failed_files.append((file_path,
+                                f"文件过大（{file_size:.2f}MB > {self.MAX_FILE_SIZE / (1024 * 1024)}MB）"))
+                            continue
+
+                        if total_size + file_size * 1024 * 1024 > self.MAX_TOTAL_SIZE:
+                            self.failed_files.append((file_path, "超出总大小限制"))
+                            continue
+
+                        file_info = FileInfo(
+                            path=file_path,
+                            rel_path=os.path.relpath(file_path, path),
+                            size=file_size,
+                            extension=os.path.splitext(file_path)[1].lower(),
+                            last_modified=time.strftime('%Y-%m-%d %H:%M:%S',
+                                                      time.localtime(stats.st_mtime))
+                        )
+
+                        total_size += file_size * 1024 * 1024
+                        files.append(file_info)
+
+                    except Exception as e:
+                        self.failed_files.append((file_path, f"处理文件失败: {str(e)}"))
+                        continue
+
+        except Exception as e:
+            self.failed_files.append(("目录扫描", f"扫描失败: {str(e)}"))
+            return []
+
+        return sorted(files, key=lambda x: x.rel_path)
+
+    def _format_content_with_fold(self, file_info, content: str) -> str:
+        """使用折叠管理器格式化文件内容"""
+        try:
+            metadata = FileMetadata(
+                rel_path=file_info.rel_path,
+                size=file_info.size,
+                last_modified=datetime.fromtimestamp(
+                    os.path.getmtime(file_info.path)
+                ),
+                mime_type=mimetypes.guess_type(file_info.path)[0]
+            )
+
+            options = FoldingOptions(
+                style=FoldingStyle.DETAILED,
+                code_language=self.folding_manager._guess_language(
+                    os.path.splitext(file_info.path)[1]
+                ),
+                show_timestamp=True
+            )
+
+            return self.folding_manager.format_content(
+                content=content,
+                formatter_type='file',
+                metadata=metadata,
+                options=options
+            )
+
+        except Exception as e:
+            return f"Error formatting content: {str(e)}"
+
+    def _format_content_for_llm(self, file_infos: List[FileInfo], contents: List[str]) -> str:
+        """格式化用于LLM的内容
+
+        Args:
+            file_infos: 文件信息列表
+            contents: 内容列表
+
+        Returns:
+            str: 格式化后的内容
+        """
+        if len(file_infos) != len(contents):
+            raise ValueError("文件信息和内容数量不匹配")
+
+        result = [
+            "以下是多个文件的内容集合。每个文件的内容都以 '===== 文件 {序号}: {文件名} =====' 开始，",
+            "以 '===== 文件 {序号} 结束 =====' 结束。你可以根据这些分隔符来识别不同文件的内容。\n\n"
+        ]
+
+        for idx, (file_info, content) in enumerate(zip(file_infos, contents), 1):
+            result.extend([
+                f"===== 文件 {idx}: {file_info.rel_path} =====",
+                "文件内容:",
+                content.strip(),
+                f"===== 文件 {idx} 结束 =====\n"
+            ])
+
+        return "\n".join(result)
+
+    def execute(self, txt: str) -> Generator:
+        """执行文本加载和显示 - 保持原有接口
+
+        Args:
+            txt: 目标路径
+
+        Yields:
+            Generator: UI更新生成器
+        """
+        try:
+            # 首先显示正在处理的提示信息
+            self.chatbot.append(["提示", "正在提取文本内容，请稍作等待..."])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            user_name = self.chatbot.get_user()
+            validate_path_safety(txt, user_name)
+            self.start_time = time.time()
+            self.processed_size = 0
+            self.failed_files.clear()
+            successful_files = []
+            successful_contents = []
+
+            # 收集文件
+            files = self._collect_files(txt)
+            if not files:
+                # 移除之前的提示信息
+                self.chatbot.pop()
+                self.chatbot.append(["提示", "未找到任何有效文件"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+                return
+
+            # 批量处理文件
+            content_blocks = []
+            for i in range(0, len(files), self.BATCH_SIZE):
+                batch = files[i:i + self.BATCH_SIZE]
+                results = self._process_file_batch(batch)
+
+                for file_info, content in results:
+                    if content:
+                        content_blocks.append(self._format_content_with_fold(file_info, content))
+                        successful_files.append(file_info)
+                        successful_contents.append(content)
+
+            # 显示文件内容，替换之前的提示信息
+            if content_blocks:
+                # 移除之前的提示信息
+                self.chatbot.pop()
+                self.chatbot.append(["文件内容", "\n".join(content_blocks)])
+                self.history.extend([
+                    self._format_content_for_llm(successful_files, successful_contents),
+                    "我已经接收到你上传的文件的内容，请提问"
+                ])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        except Exception as e:
+            # 发生错误时，移除之前的提示信息
+            if len(self.chatbot) > 0 and self.chatbot[-1][0] == "提示":
+                self.chatbot.pop()
+            self.chatbot.append(["错误", f"处理过程中出现错误: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        finally:
+            self.executor.shutdown(wait=False)
+            self.file_cache.clear()
+
+    def execute_single_file(self, file_path: str) -> Generator:
+        """执行单个文件的加载和显示
+
+        Args:
+            file_path: 文件路径
+
+        Yields:
+            Generator: UI更新生成器
+        """
+        try:
+            # 首先显示正在处理的提示信息
+            self.chatbot.append(["提示", "正在提取文本内容，请稍作等待..."])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            user_name = self.chatbot.get_user()
+            validate_path_safety(file_path, user_name)
+            self.start_time = time.time()
+            self.processed_size = 0
+            self.failed_files.clear()
+
+            # 验证文件是否存在且可读
+            if not os.path.isfile(file_path):
+                self.chatbot.pop()
+                self.chatbot.append(["错误", f"指定路径不是文件: {file_path}"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+                return
+
+            if not self._is_valid_file(file_path):
+                self.chatbot.pop()
+                self.chatbot.append(["错误", f"无效的文件类型或无法读取: {file_path}"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+                return
+
+            # 创建文件信息
+            try:
+                stats = os.stat(file_path)
+                file_size = stats.st_size / (1024 * 1024)  # 转换为MB
+
+                if file_size * 1024 * 1024 > self.MAX_FILE_SIZE:
+                    self.chatbot.pop()
+                    self.chatbot.append(["错误", f"文件过大（{file_size:.2f}MB > {self.MAX_FILE_SIZE / (1024 * 1024)}MB）"])
+                    yield from update_ui(chatbot=self.chatbot, history=self.history)
+                    return
+
+                file_info = FileInfo(
+                    path=file_path,
+                    rel_path=os.path.basename(file_path),
+                    size=file_size,
+                    extension=os.path.splitext(file_path)[1].lower(),
+                    last_modified=time.strftime('%Y-%m-%d %H:%M:%S',
+                                              time.localtime(stats.st_mtime))
+                )
+            except Exception as e:
+                self.chatbot.pop()
+                self.chatbot.append(["错误", f"处理文件失败: {str(e)}"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+                return
+
+            # 读取文件内容
+            try:
+                content = self._read_file_content(file_info)
+                if not content:
+                    self.chatbot.pop()
+                    self.chatbot.append(["提示", f"文件内容为空或无法提取: {file_path}"])
+                    yield from update_ui(chatbot=self.chatbot, history=self.history)
+                    return
+            except Exception as e:
+                self.chatbot.pop()
+                self.chatbot.append(["错误", f"读取文件失败: {str(e)}"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+                return
+
+            # 格式化内容并更新UI
+            formatted_content = self._format_content_with_fold(file_info, content)
+
+            # 移除之前的提示信息
+            self.chatbot.pop()
+            self.chatbot.append(["文件内容", formatted_content])
+
+            # 更新历史记录，便于LLM处理
+            llm_content = self._format_content_for_llm([file_info], [content])
+            self.history.extend([llm_content, "我已经接收到你上传的文件的内容，请提问"])
+
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        except Exception as e:
+            # 发生错误时，移除之前的提示信息
+            if len(self.chatbot) > 0 and self.chatbot[-1][0] == "提示":
+                self.chatbot.pop()
+            self.chatbot.append(["错误", f"处理过程中出现错误: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+    def __del__(self):
+        """析构函数 - 确保资源被正确释放"""
+        if hasattr(self, 'executor'):
+            self.executor.shutdown(wait=False)
+        if hasattr(self, 'file_cache'):
+            self.file_cache.clear()
--- a/crazy_functions/game_fns/game_ascii_art.py
+++ b/crazy_functions/game_fns/game_ascii_art.py
@@ -1,4 +1,4 @@
-from toolbox import CatchException, update_ui, update_ui_lastest_msg
+from toolbox import CatchException, update_ui, update_ui_latest_msg
 from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -13,7 +13,7 @@ class MiniGame_ASCII_Art(GptAcademicGameBaseState):
        else:
            if prompt.strip() == 'exit':
                self.delete_game = True
-                yield from update_ui_lastest_msg(lastmsg=f"谜底是{self.obj}，游戏结束。", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_latest_msg(lastmsg=f"谜底是{self.obj}，游戏结束。", chatbot=chatbot, history=history, delay=0.)
                return
            chatbot.append([prompt, ""])
        yield from update_ui(chatbot=chatbot, history=history)
@@ -31,12 +31,12 @@ class MiniGame_ASCII_Art(GptAcademicGameBaseState):
            self.cur_task = 'identify user guess'
            res = get_code_block(raw_res)
            history += ['', f'the answer is {self.obj}', inputs, res]
-            yield from update_ui_lastest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.)

        elif self.cur_task == 'identify user guess':
            if is_same_thing(self.obj, prompt, self.llm_kwargs):
                self.delete_game = True
-                yield from update_ui_lastest_msg(lastmsg="你猜对了！", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_latest_msg(lastmsg="你猜对了！", chatbot=chatbot, history=history, delay=0.)
            else:
                self.cur_task = 'identify user guess'
-                yield from update_ui_lastest_msg(lastmsg="猜错了，再试试，输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_latest_msg(lastmsg="猜错了，再试试，输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.)
--- a/crazy_functions/game_fns/game_interactive_story.py
+++ b/crazy_functions/game_fns/game_interactive_story.py
@@ -63,7 +63,7 @@ prompts_terminate = """小说的前文回顾：
 """


-from toolbox import CatchException, update_ui, update_ui_lastest_msg
+from toolbox import CatchException, update_ui, update_ui_latest_msg
 from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -112,7 +112,7 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
            if prompt.strip() == 'exit' or prompt.strip() == '结束剧情':
                # should we terminate game here?
                self.delete_game = True
-                yield from update_ui_lastest_msg(lastmsg=f"游戏结束。", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_latest_msg(lastmsg=f"游戏结束。", chatbot=chatbot, history=history, delay=0.)
                return
            if '剧情收尾' in prompt:
                self.cur_task = 'story_terminate'
@@ -137,8 +137,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
            )
            self.story.append(story_paragraph)
            # # 配图
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)

            # # 构建后续剧情引导
            previously_on_story = ""
@@ -171,8 +171,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
            )
            self.story.append(story_paragraph)
            # # 配图
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)

            # # 构建后续剧情引导
            previously_on_story = ""
@@ -204,8 +204,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
                chatbot, history_, self.sys_prompt_
            )
            # # 配图
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)

            # terminate game
            self.delete_game = True
--- a/crazy_functions/gen_fns/gen_fns_shared.py
+++ b/crazy_functions/gen_fns/gen_fns_shared.py
@@ -2,7 +2,7 @@ import time
 import importlib
 from toolbox import trimmed_format_exc, gen_time_str, get_log_folder
 from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
-from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_lastest_msg
+from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_latest_msg
 import multiprocessing

 def get_class_name(class_string):
--- a/crazy_functions/json_fns/pydantic_io.py
+++ b/crazy_functions/json_fns/pydantic_io.py
@@ -102,10 +102,10 @@ class GptJsonIO():
                logging.info(f'Repairing json：{response}')
                repair_prompt = self.generate_repair_prompt(broken_json = response, error=repr(e))
                result = self.generate_output(gpt_gen_fn(repair_prompt, self.format_instructions))
-                logging.info('Repaire json success.')
+                logging.info('Repair json success.')
            except Exception as e:
                # 没辙了，放弃治疗
-                logging.info('Repaire json fail.')
+                logging.info('Repair json fail.')
                raise JsonStringError('Cannot repair json.', str(e))
        return result

--- a/crazy_functions/latex_fns/latex_actions.py
+++ b/crazy_functions/latex_fns/latex_actions.py
@@ -3,7 +3,7 @@ import re
 import shutil
 import numpy as np
 from loguru import logger
-from toolbox import update_ui, update_ui_lastest_msg, get_log_folder, gen_time_str
+from toolbox import update_ui, update_ui_latest_msg, get_log_folder, gen_time_str
 from toolbox import get_conf, promote_file_to_downloadzone
 from crazy_functions.latex_fns.latex_toolbox import PRESERVE, TRANSFORM
 from crazy_functions.latex_fns.latex_toolbox import set_forbidden_text, set_forbidden_text_begin_end, set_forbidden_text_careful_brace
@@ -20,7 +20,7 @@ def split_subprocess(txt, project_folder, return_dict, opts):
    """
    break down latex file to a linked list,
    each node use a preserve flag to indicate whether it should
-    be proccessed by GPT.
+    be processed by GPT.
    """
    text = txt
    mask = np.zeros(len(txt), dtype=np.uint8) + TRANSFORM
@@ -85,14 +85,14 @@ class LatexPaperSplit():
    """
    break down latex file to a linked list,
    each node use a preserve flag to indicate whether it should
-    be proccessed by GPT.
+    be processed by GPT.
    """
    def __init__(self) -> None:
        self.nodes = None
        self.msg = "*{\\scriptsize\\textbf{警告：该PDF由GPT-Academic开源项目调用大语言模型+Latex翻译插件一键生成，" + \
            "版权归原文作者所有。翻译内容可靠性无保障，请仔细鉴别并以原文为准。" + \
            "项目Github地址 \\url{https://github.com/binary-husky/gpt_academic/}。"
-        # 请您不要删除或修改这行警告，除非您是论文的原作者（如果您是论文原作者，欢迎加REAME中的QQ联系开发者）
+        # 请您不要删除或修改这行警告，除非您是论文的原作者（如果您是论文原作者，欢迎加README中的QQ联系开发者）
        self.msg_declare = "为了防止大语言模型的意外谬误产生扩散影响，禁止移除或修改此警告。}}\\\\"
        self.title = "unknown"
        self.abstract = "unknown"
@@ -151,7 +151,7 @@ class LatexPaperSplit():
        """
        break down latex file to a linked list,
        each node use a preserve flag to indicate whether it should
-        be proccessed by GPT.
+        be processed by GPT.
        P.S. use multiprocessing to avoid timeout error
        """
        import multiprocessing
@@ -351,7 +351,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
    max_try = 32
    chatbot.append([f"正在编译PDF文档", f'编译已经开始。当前工作路径为{work_folder}，如果程序停顿5分钟以上，请直接去该路径下取回翻译结果，或者重启之后再度尝试 ...']); yield from update_ui(chatbot=chatbot, history=history)
    chatbot.append([f"正在编译PDF文档", '...']); yield from update_ui(chatbot=chatbot, history=history); time.sleep(1); chatbot[-1] = list(chatbot[-1]) # 刷新界面
-    yield from update_ui_lastest_msg('编译已经开始...', chatbot, history)   # 刷新Gradio前端界面
+    yield from update_ui_latest_msg('编译已经开始...', chatbot, history)   # 刷新Gradio前端界面
    # 检查是否需要使用xelatex
    def check_if_need_xelatex(tex_path):
        try:
@@ -373,7 +373,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
    # 根据编译器类型返回编译命令
    def get_compile_command(compiler, filename):
        compile_command = f'{compiler} -interaction=batchmode -file-line-error {filename}.tex'
-        logger.info('Latex 编译指令: ', compile_command)
+        logger.info('Latex 编译指令: ' + compile_command)
        return compile_command

    # 确定使用的编译器
@@ -396,32 +396,32 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
            shutil.copyfile(may_exist_bbl, target_bbl)

        # https://stackoverflow.com/questions/738755/dont-make-me-manually-abort-a-latex-compile-when-theres-an-error
-        yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history)   # 刷新Gradio前端界面
+        yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history)   # 刷新Gradio前端界面
        ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)

-        yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history)   # 刷新Gradio前端界面
+        yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history)   # 刷新Gradio前端界面
        ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)

        if ok and os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf')):
            # 只有第二步成功，才能继续下面的步骤
-            yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译BibTex ...', chatbot, history)    # 刷新Gradio前端界面
+            yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译BibTex ...', chatbot, history)    # 刷新Gradio前端界面
            if not os.path.exists(pj(work_folder_original, f'{main_file_original}.bbl')):
                ok = compile_latex_with_timeout(f'bibtex  {main_file_original}.aux', work_folder_original)
            if not os.path.exists(pj(work_folder_modified, f'{main_file_modified}.bbl')):
                ok = compile_latex_with_timeout(f'bibtex  {main_file_modified}.aux', work_folder_modified)

-            yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译文献交叉引用 ...', chatbot, history)  # 刷新Gradio前端界面
+            yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译文献交叉引用 ...', chatbot, history)  # 刷新Gradio前端界面
            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
            ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)

            if mode!='translate_zh':
-                yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
+                yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
                logger.info(    f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex  {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex')
                ok = compile_latex_with_timeout(f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex  {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex', os.getcwd())

-                yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history)   # 刷新Gradio前端界面
+                yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history)   # 刷新Gradio前端界面
                ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
                ok = compile_latex_with_timeout(f'bibtex    merge_diff.aux', work_folder)
                ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
@@ -435,13 +435,13 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
        results_ += f"原始PDF编译是否成功: {original_pdf_success};"
        results_ += f"转化PDF编译是否成功: {modified_pdf_success};"
        results_ += f"对比PDF编译是否成功: {diff_pdf_success};"
-        yield from update_ui_lastest_msg(f'第{n_fix}编译结束:<br/>{results_}...', chatbot, history) # 刷新Gradio前端界面
+        yield from update_ui_latest_msg(f'第{n_fix}编译结束:<br/>{results_}...', chatbot, history) # 刷新Gradio前端界面

        if diff_pdf_success:
            result_pdf = pj(work_folder_modified, f'merge_diff.pdf')    # get pdf path
            promote_file_to_downloadzone(result_pdf, rename_file=None, chatbot=chatbot)  # promote file to web UI
        if modified_pdf_success:
-            yield from update_ui_lastest_msg(f'转化PDF编译已经成功, 正在尝试生成对比PDF, 请稍候 ...', chatbot, history)    # 刷新Gradio前端界面
+            yield from update_ui_latest_msg(f'转化PDF编译已经成功, 正在尝试生成对比PDF, 请稍候 ...', chatbot, history)    # 刷新Gradio前端界面
            result_pdf = pj(work_folder_modified, f'{main_file_modified}.pdf') # get pdf path
            origin_pdf = pj(work_folder_original, f'{main_file_original}.pdf') # get pdf path
            if os.path.exists(pj(work_folder, '..', 'translation')):
@@ -472,7 +472,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
                work_folder_modified=work_folder_modified,
                fixed_line=fixed_line
            )
-            yield from update_ui_lastest_msg(f'由于最为关键的转化PDF编译失败, 将根据报错信息修正tex源文件并重试, 当前报错的latex代码处于第{buggy_lines}行 ...', chatbot, history)   # 刷新Gradio前端界面
+            yield from update_ui_latest_msg(f'由于最为关键的转化PDF编译失败, 将根据报错信息修正tex源文件并重试, 当前报错的latex代码处于第{buggy_lines}行 ...', chatbot, history)   # 刷新Gradio前端界面
            if not can_retry: break

    return False # 失败啦
--- a/crazy_functions/latex_fns/latex_toolbox.py
+++ b/crazy_functions/latex_fns/latex_toolbox.py
@@ -168,7 +168,7 @@ def set_forbidden_text(text, mask, pattern, flags=0):
 def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
    """
    Move area out of preserve area (make text editable for GPT)
-    count the number of the braces so as to catch compelete text area.
+    count the number of the braces so as to catch complete text area.
    e.g.
    \begin{abstract} blablablablablabla. \end{abstract}
    """
@@ -188,7 +188,7 @@ def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
 def set_forbidden_text_careful_brace(text, mask, pattern, flags=0):
    """
    Add a preserve text area in this paper (text become untouchable for GPT).
-    count the number of the braces so as to catch compelete text area.
+    count the number of the braces so as to catch complete text area.
    e.g.
    \caption{blablablablabla\texbf{blablabla}blablabla.}
    """
@@ -214,7 +214,7 @@ def reverse_forbidden_text_careful_brace(
 ):
    """
    Move area out of preserve area (make text editable for GPT)
-    count the number of the braces so as to catch compelete text area.
+    count the number of the braces so as to catch complete text area.
    e.g.
    \caption{blablablablabla\texbf{blablabla}blablabla.}
    """
@@ -287,23 +287,23 @@ def find_main_tex_file(file_manifest, mode):
    在多Tex文档中，寻找主文件，必须包含documentclass，返回找到的第一个。
    P.S. 但愿没人把latex模板放在里面传进来 (6.25 加入判定latex模板的代码)
    """
-    canidates = []
+    candidates = []
    for texf in file_manifest:
        if os.path.basename(texf).startswith("merge"):
            continue
        with open(texf, "r", encoding="utf8", errors="ignore") as f:
            file_content = f.read()
        if r"\documentclass" in file_content:
-            canidates.append(texf)
+            candidates.append(texf)
        else:
            continue

-    if len(canidates) == 0:
+    if len(candidates) == 0:
        raise RuntimeError("无法找到一个主Tex文件（包含documentclass关键字）")
-    elif len(canidates) == 1:
-        return canidates[0]
-    else:  # if len(canidates) >= 2 通过一些Latex模板中常见（但通常不会出现在正文）的单词，对不同latex源文件扣分，取评分最高者返回
-        canidates_score = []
+    elif len(candidates) == 1:
+        return candidates[0]
+    else:  # if len(candidates) >= 2 通过一些Latex模板中常见（但通常不会出现在正文）的单词，对不同latex源文件扣分，取评分最高者返回
+        candidates_score = []
        # 给出一些判定模板文档的词作为扣分项
        unexpected_words = [
            "\\LaTeX",
@@ -316,19 +316,19 @@ def find_main_tex_file(file_manifest, mode):
            "reviewers",
        ]
        expected_words = ["\\input", "\\ref", "\\cite"]
-        for texf in canidates:
-            canidates_score.append(0)
+        for texf in candidates:
+            candidates_score.append(0)
            with open(texf, "r", encoding="utf8", errors="ignore") as f:
                file_content = f.read()
                file_content = rm_comments(file_content)
            for uw in unexpected_words:
                if uw in file_content:
-                    canidates_score[-1] -= 1
+                    candidates_score[-1] -= 1
            for uw in expected_words:
                if uw in file_content:
-                    canidates_score[-1] += 1
-        select = np.argmax(canidates_score)  # 取评分最高者返回
-        return canidates[select]
+                    candidates_score[-1] += 1
+        select = np.argmax(candidates_score)  # 取评分最高者返回
+        return candidates[select]


 def rm_comments(main_file):
@@ -374,7 +374,7 @@ def find_tex_file_ignore_case(fp):

 def merge_tex_files_(project_foler, main_file, mode):
    """
-    Merge Tex project recrusively
+    Merge Tex project recursively
    """
    main_file = rm_comments(main_file)
    for s in reversed([q for q in re.finditer(r"\\input\{(.*?)\}", main_file, re.M)]):
@@ -429,7 +429,7 @@ def find_title_and_abs(main_file):

 def merge_tex_files(project_foler, main_file, mode):
    """
-    Merge Tex project recrusively
+    Merge Tex project recursively
    P.S. 顺便把CTEX塞进去以支持中文
    P.S. 顺便把Latex的注释去除
    """
--- a/crazy_functions/media_fns/get_media.py
+++ b/crazy_functions/media_fns/get_media.py
@@ -1,4 +1,4 @@
-from toolbox import update_ui, get_conf, promote_file_to_downloadzone, update_ui_lastest_msg, generate_file_link
+from toolbox import update_ui, get_conf, promote_file_to_downloadzone, update_ui_latest_msg, generate_file_link
 from shared_utils.docker_as_service_api import stream_daas
 from shared_utils.docker_as_service_api import DockerServiceApiComModel
 import random
@@ -25,7 +25,7 @@ def download_video(video_id, only_audio, user_name, chatbot, history):
        status_buf += "\n\n"
        status_buf += "DaaS file attach: \n\n"
        status_buf += str(output_manifest['server_file_attach'])
-        yield from update_ui_lastest_msg(status_buf, chatbot, history)
+        yield from update_ui_latest_msg(status_buf, chatbot, history)

    return output_manifest['server_file_attach']

--- a/crazy_functions/multi_stage/multi_stage_utils.py
+++ b/crazy_functions/multi_stage/multi_stage_utils.py
@@ -1,6 +1,6 @@
 from pydantic import BaseModel, Field
 from typing import List
-from toolbox import update_ui_lastest_msg, disable_auto_promotion
+from toolbox import update_ui_latest_msg, disable_auto_promotion
 from toolbox import CatchException, update_ui, get_conf, select_api_key, get_log_folder
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
--- a/crazy_functions/paper_fns/init.py
+++ b/crazy_functions/paper_fns/init.py
--- a/crazy_functions/paper_fns/auto_git/handlers/base_handler.py
+++ b/crazy_functions/paper_fns/auto_git/handlers/base_handler.py
@@ -0,0 +1,386 @@
+from abc import ABC, abstractmethod
+from typing import List, Dict, Any
+from ..query_analyzer import SearchCriteria
+from ..sources.github_source import GitHubSource
+import asyncio
+import re
+from datetime import datetime
+
+class BaseHandler(ABC):
+    """处理器基类"""
+
+    def __init__(self, github: GitHubSource, llm_kwargs: Dict = None):
+        self.github = github
+        self.llm_kwargs = llm_kwargs or {}
+        self.ranked_repos = []  # 存储排序后的仓库列表
+
+    def _get_search_params(self, plugin_kwargs: Dict) -> Dict:
+        """获取搜索参数"""
+        return {
+            'max_repos': plugin_kwargs.get('max_repos', 150),  # 最大仓库数量，从30改为150
+            'max_details': plugin_kwargs.get('max_details', 80),  # 最多展示详情的仓库数量，新增参数
+            'search_multiplier': plugin_kwargs.get('search_multiplier', 3),  # 检索倍数
+            'min_stars': plugin_kwargs.get('min_stars', 0),  # 最少星标数
+        }
+
+    @abstractmethod
+    async def handle(
+            self,
+            criteria: SearchCriteria,
+            chatbot: List[List[str]],
+            history: List[List[str]],
+            system_prompt: str,
+            llm_kwargs: Dict[str, Any],
+            plugin_kwargs: Dict[str, Any],
+    ) -> str:
+        """处理查询"""
+        pass
+
+    async def _search_repositories(self, query: str, language: str = None, min_stars: int = 0,
+                                sort: str = "stars", per_page: int = 30) -> List[Dict]:
+        """搜索仓库"""
+        try:
+            # 构建查询字符串
+            if min_stars > 0 and "stars:>" not in query:
+                query += f" stars:>{min_stars}"
+                
+            if language and "language:" not in query:
+                query += f" language:{language}"
+                
+            # 执行搜索
+            result = await self.github.search_repositories(
+                query=query,
+                sort=sort,
+                per_page=per_page
+            )
+            
+            if result and "items" in result:
+                return result["items"]
+            return []
+        except Exception as e:
+            print(f"仓库搜索出错: {str(e)}")
+            return []
+
+    async def _search_bilingual_repositories(self, english_query: str, chinese_query: str, language: str = None, min_stars: int = 0,
+                                sort: str = "stars", per_page: int = 30) -> List[Dict]:
+        """同时搜索中英文仓库并合并结果"""
+        try:
+            # 搜索英文仓库
+            english_results = await self._search_repositories(
+                query=english_query,
+                language=language,
+                min_stars=min_stars,
+                sort=sort,
+                per_page=per_page
+            )
+            
+            # 搜索中文仓库
+            chinese_results = await self._search_repositories(
+                query=chinese_query,
+                language=language,
+                min_stars=min_stars,
+                sort=sort,
+                per_page=per_page
+            )
+            
+            # 合并结果，去除重复项
+            merged_results = []
+            seen_repos = set()
+            
+            # 优先添加英文结果
+            for repo in english_results:
+                repo_id = repo.get('id')
+                if repo_id and repo_id not in seen_repos:
+                    seen_repos.add(repo_id)
+                    merged_results.append(repo)
+            
+            # 添加中文结果（排除重复）
+            for repo in chinese_results:
+                repo_id = repo.get('id')
+                if repo_id and repo_id not in seen_repos:
+                    seen_repos.add(repo_id)
+                    merged_results.append(repo)
+            
+            # 按星标数重新排序
+            merged_results.sort(key=lambda x: x.get('stargazers_count', 0), reverse=True)
+            
+            return merged_results[:per_page]  # 返回合并后的前per_page个结果
+        except Exception as e:
+            print(f"双语仓库搜索出错: {str(e)}")
+            return []
+
+    async def _search_code(self, query: str, language: str = None, per_page: int = 30) -> List[Dict]:
+        """搜索代码"""
+        try:
+            # 构建查询字符串
+            if language and "language:" not in query:
+                query += f" language:{language}"
+                
+            # 执行搜索
+            result = await self.github.search_code(
+                query=query,
+                per_page=per_page
+            )
+            
+            if result and "items" in result:
+                return result["items"]
+            return []
+        except Exception as e:
+            print(f"代码搜索出错: {str(e)}")
+            return []
+
+    async def _search_bilingual_code(self, english_query: str, chinese_query: str, language: str = None, per_page: int = 30) -> List[Dict]:
+        """同时搜索中英文代码并合并结果"""
+        try:
+            # 搜索英文代码
+            english_results = await self._search_code(
+                query=english_query,
+                language=language,
+                per_page=per_page
+            )
+            
+            # 搜索中文代码
+            chinese_results = await self._search_code(
+                query=chinese_query,
+                language=language,
+                per_page=per_page
+            )
+            
+            # 合并结果，去除重复项
+            merged_results = []
+            seen_files = set()
+            
+            # 优先添加英文结果
+            for item in english_results:
+                # 使用文件URL作为唯一标识
+                file_url = item.get('html_url', '')
+                if file_url and file_url not in seen_files:
+                    seen_files.add(file_url)
+                    merged_results.append(item)
+            
+            # 添加中文结果（排除重复）
+            for item in chinese_results:
+                file_url = item.get('html_url', '')
+                if file_url and file_url not in seen_files:
+                    seen_files.add(file_url)
+                    merged_results.append(item)
+            
+            # 对结果进行排序，优先显示匹配度高的结果
+            # 由于无法直接获取匹配度，这里使用仓库的星标数作为替代指标
+            merged_results.sort(key=lambda x: x.get('repository', {}).get('stargazers_count', 0), reverse=True)
+            
+            return merged_results[:per_page]  # 返回合并后的前per_page个结果
+        except Exception as e:
+            print(f"双语代码搜索出错: {str(e)}")
+            return []
+
+    async def _search_users(self, query: str, per_page: int = 30) -> List[Dict]:
+        """搜索用户"""
+        try:
+            result = await self.github.search_users(
+                query=query,
+                per_page=per_page
+            )
+            
+            if result and "items" in result:
+                return result["items"]
+            return []
+        except Exception as e:
+            print(f"用户搜索出错: {str(e)}")
+            return []
+
+    async def _search_bilingual_users(self, english_query: str, chinese_query: str, per_page: int = 30) -> List[Dict]:
+        """同时搜索中英文用户并合并结果"""
+        try:
+            # 搜索英文用户
+            english_results = await self._search_users(
+                query=english_query,
+                per_page=per_page
+            )
+            
+            # 搜索中文用户
+            chinese_results = await self._search_users(
+                query=chinese_query,
+                per_page=per_page
+            )
+            
+            # 合并结果，去除重复项
+            merged_results = []
+            seen_users = set()
+            
+            # 优先添加英文结果
+            for user in english_results:
+                user_id = user.get('id')
+                if user_id and user_id not in seen_users:
+                    seen_users.add(user_id)
+                    merged_results.append(user)
+            
+            # 添加中文结果（排除重复）
+            for user in chinese_results:
+                user_id = user.get('id')
+                if user_id and user_id not in seen_users:
+                    seen_users.add(user_id)
+                    merged_results.append(user)
+            
+            # 按关注者数量进行排序
+            merged_results.sort(key=lambda x: x.get('followers', 0), reverse=True)
+            
+            return merged_results[:per_page]  # 返回合并后的前per_page个结果
+        except Exception as e:
+            print(f"双语用户搜索出错: {str(e)}")
+            return []
+
+    async def _search_topics(self, query: str, per_page: int = 30) -> List[Dict]:
+        """搜索主题"""
+        try:
+            result = await self.github.search_topics(
+                query=query,
+                per_page=per_page
+            )
+            
+            if result and "items" in result:
+                return result["items"]
+            return []
+        except Exception as e:
+            print(f"主题搜索出错: {str(e)}")
+            return []
+
+    async def _search_bilingual_topics(self, english_query: str, chinese_query: str, per_page: int = 30) -> List[Dict]:
+        """同时搜索中英文主题并合并结果"""
+        try:
+            # 搜索英文主题
+            english_results = await self._search_topics(
+                query=english_query,
+                per_page=per_page
+            )
+            
+            # 搜索中文主题
+            chinese_results = await self._search_topics(
+                query=chinese_query,
+                per_page=per_page
+            )
+            
+            # 合并结果，去除重复项
+            merged_results = []
+            seen_topics = set()
+            
+            # 优先添加英文结果
+            for topic in english_results:
+                topic_name = topic.get('name')
+                if topic_name and topic_name not in seen_topics:
+                    seen_topics.add(topic_name)
+                    merged_results.append(topic)
+            
+            # 添加中文结果（排除重复）
+            for topic in chinese_results:
+                topic_name = topic.get('name')
+                if topic_name and topic_name not in seen_topics:
+                    seen_topics.add(topic_name)
+                    merged_results.append(topic)
+            
+            # 可以按流行度进行排序（如果有）
+            if merged_results and 'featured' in merged_results[0]:
+                merged_results.sort(key=lambda x: x.get('featured', False), reverse=True)
+            
+            return merged_results[:per_page]  # 返回合并后的前per_page个结果
+        except Exception as e:
+            print(f"双语主题搜索出错: {str(e)}")
+            return []
+
+    async def _get_repo_details(self, repos: List[Dict]) -> List[Dict]:
+        """获取仓库详细信息"""
+        enhanced_repos = []
+        
+        for repo in repos:
+            try:
+                # 获取README信息
+                owner = repo.get('owner', {}).get('login') if repo.get('owner') is not None else None
+                repo_name = repo.get('name')
+                
+                if owner and repo_name:
+                    readme = await self.github.get_repo_readme(owner, repo_name)
+                    if readme and "decoded_content" in readme:
+                        # 提取README的前1000个字符作为摘要
+                        repo['readme_excerpt'] = readme["decoded_content"][:1000] + "..."
+                    
+                    # 获取语言使用情况
+                    languages = await self.github.get_repository_languages(owner, repo_name)
+                    if languages:
+                        repo['languages_detail'] = languages
+                    
+                    # 获取最新发布版本
+                    releases = await self.github.get_repo_releases(owner, repo_name, per_page=1)
+                    if releases and len(releases) > 0:
+                        repo['latest_release'] = releases[0]
+                    
+                    # 获取主题标签
+                    topics = await self.github.get_repo_topics(owner, repo_name)
+                    if topics and "names" in topics:
+                        repo['topics'] = topics["names"]
+                
+                enhanced_repos.append(repo)
+            except Exception as e:
+                print(f"获取仓库 {repo.get('full_name')} 详情时出错: {str(e)}")
+                enhanced_repos.append(repo)  # 添加原始仓库信息
+                
+        return enhanced_repos
+
+    def _format_repos(self, repos: List[Dict]) -> str:
+        """格式化仓库列表"""
+        formatted = []
+        
+        for i, repo in enumerate(repos, 1):
+            # 构建仓库URL
+            repo_url = repo.get('html_url', '')
+            
+            # 构建完整的引用
+            reference = (
+                f"{i}. **{repo.get('full_name', '')}**\n"
+                f"   - 描述: {repo.get('description', 'N/A')}\n"
+                f"   - 语言: {repo.get('language', 'N/A')}\n"
+                f"   - 星标: {repo.get('stargazers_count', 0)}\n"
+                f"   - Fork数: {repo.get('forks_count', 0)}\n"
+                f"   - 更新时间: {repo.get('updated_at', 'N/A')[:10]}\n"
+                f"   - 创建时间: {repo.get('created_at', 'N/A')[:10]}\n"
+                f"   - URL: <a href='{repo_url}' target='_blank'>{repo_url}</a>\n"
+            )
+            
+            # 添加主题标签(如果有)
+            if repo.get('topics'):
+                topics_str = ", ".join(repo.get('topics'))
+                reference += f"   - 主题标签: {topics_str}\n"
+                
+            # 添加最新发布版本(如果有)
+            if repo.get('latest_release'):
+                release = repo.get('latest_release')
+                reference += f"   - 最新版本: {release.get('tag_name', 'N/A')} ({release.get('published_at', 'N/A')[:10]})\n"
+                
+            # 添加README摘要(如果有)
+            if repo.get('readme_excerpt'):
+                # 截断README，只取前300个字符
+                readme_short = repo.get('readme_excerpt')[:300].replace('\n', ' ')
+                reference += f"   - README摘要: {readme_short}...\n"
+                
+            formatted.append(reference)
+            
+        return "\n".join(formatted)
+
+    def _generate_apology_prompt(self, criteria: SearchCriteria) -> str:
+        """生成道歉提示"""
+        return f"""很抱歉，我们未能找到与"{criteria.main_topic}"相关的GitHub项目。
+
+可能的原因：
+1. 搜索词过于具体或冷门
+2. 星标数要求过高
+3. 编程语言限制过于严格
+
+建议解决方案：
+   1. 尝试使用更通用的关键词
+   2. 降低最低星标数要求
+   3. 移除或更改编程语言限制
+请根据以上建议调整后重试。"""
+
+    def _get_current_time(self) -> str:
+        """获取当前时间信息"""
+        now = datetime.now()
+        return now.strftime("%Y年%m月%d日") 
--- a/crazy_functions/paper_fns/auto_git/handlers/code_handler.py
+++ b/crazy_functions/paper_fns/auto_git/handlers/code_handler.py
@@ -0,0 +1,156 @@
+from typing import List, Dict, Any
+from .base_handler import BaseHandler
+from ..query_analyzer import SearchCriteria
+import asyncio
+
+class CodeSearchHandler(BaseHandler):
+    """代码搜索处理器"""
+    
+    def __init__(self, github, llm_kwargs=None):
+        super().__init__(github, llm_kwargs)
+    
+    async def handle(
+        self,
+        criteria: SearchCriteria,
+        chatbot: List[List[str]],
+        history: List[List[str]],
+        system_prompt: str,
+        llm_kwargs: Dict[str, Any],
+        plugin_kwargs: Dict[str, Any],
+    ) -> str:
+        """处理代码搜索请求，返回最终的prompt"""
+        
+        search_params = self._get_search_params(plugin_kwargs)
+        
+        # 搜索代码
+        code_results = await self._search_bilingual_code(
+            english_query=criteria.github_params["query"],
+            chinese_query=criteria.github_params["chinese_query"],
+            language=criteria.language,
+            per_page=search_params['max_repos']
+        )
+        
+        if not code_results:
+            return self._generate_apology_prompt(criteria)
+            
+        # 获取代码文件内容
+        enhanced_code_results = await self._get_code_details(code_results[:search_params['max_details']])
+        self.ranked_repos = [item["repository"] for item in enhanced_code_results if "repository" in item]
+        
+        if not enhanced_code_results:
+            return self._generate_apology_prompt(criteria)
+        
+        # 构建最终的prompt
+        current_time = self._get_current_time()
+        final_prompt = f"""当前时间: {current_time}
+
+基于用户对{criteria.main_topic}的查询，我找到了以下代码示例。
+
+代码搜索结果:
+{self._format_code_results(enhanced_code_results)}
+
+请提供:
+
+1. 对于搜索的"{criteria.main_topic}"主题的综合解释:
+   - 概念和原理介绍
+   - 常见实现方法和技术
+   - 最佳实践和注意事项
+
+2. 对每个代码示例:
+   - 解释代码的主要功能和实现方式
+   - 分析代码质量、可读性和效率
+   - 指出代码中的亮点和潜在改进空间
+   - 说明代码的适用场景
+
+3. 代码实现比较:
+   - 不同实现方法的优缺点
+   - 性能和可维护性分析
+   - 适用不同场景的实现建议
+
+4. 学习建议:
+   - 理解和使用这些代码需要的背景知识
+   - 如何扩展或改进所展示的代码
+   - 进一步学习相关技术的资源
+
+重要提示:
+- 深入解释代码的核心逻辑和实现思路
+- 提供专业、技术性的分析
+- 优先关注代码的实现质量和技术价值
+- 当代码实现有问题时，指出并提供改进建议
+- 对于复杂代码，分解解释其组成部分
+- 根据用户查询的具体问题提供针对性答案
+- 所有链接请使用<a href='链接地址' target='_blank'>链接文本</a>格式，确保链接在新窗口打开
+
+使用markdown格式提供清晰的分节回复。
+"""
+        
+        return final_prompt
+
+    async def _get_code_details(self, code_results: List[Dict]) -> List[Dict]:
+        """获取代码详情"""
+        enhanced_results = []
+        
+        for item in code_results:
+            try:
+                repo = item.get('repository', {})
+                file_path = item.get('path', '')
+                repo_name = repo.get('full_name', '')
+                
+                if repo_name and file_path:
+                    owner, repo_name = repo_name.split('/')
+                    
+                    # 获取文件内容
+                    file_content = await self.github.get_file_content(owner, repo_name, file_path)
+                    if file_content and "decoded_content" in file_content:
+                        item['code_content'] = file_content["decoded_content"]
+                        
+                        # 获取仓库基本信息
+                        repo_details = await self.github.get_repo(owner, repo_name)
+                        if repo_details:
+                            item['repository'] = repo_details
+                
+                enhanced_results.append(item)
+            except Exception as e:
+                print(f"获取代码详情时出错: {str(e)}")
+                enhanced_results.append(item)  # 添加原始信息
+                
+        return enhanced_results
+
+    def _format_code_results(self, code_results: List[Dict]) -> str:
+        """格式化代码搜索结果"""
+        formatted = []
+        
+        for i, item in enumerate(code_results, 1):
+            # 构建仓库信息
+            repo = item.get('repository', {})
+            repo_name = repo.get('full_name', 'N/A')
+            repo_url = repo.get('html_url', '')
+            stars = repo.get('stargazers_count', 0)
+            language = repo.get('language', 'N/A')
+            
+            # 构建文件信息
+            file_path = item.get('path', 'N/A')
+            file_url = item.get('html_url', '')
+            
+            # 构建代码内容
+            code_content = item.get('code_content', '')
+            if code_content:
+                # 只显示前30行代码
+                code_lines = code_content.split("\n")
+                if len(code_lines) > 30:
+                    displayed_code = "\n".join(code_lines[:30]) + "\n... (代码太长已截断) ..."
+                else:
+                    displayed_code = code_content
+            else:
+                displayed_code = "(代码内容获取失败)"
+            
+            reference = (
+                f"### {i}. {file_path} (在 {repo_name} 中)\n\n"
+                f"- **仓库**: <a href='{repo_url}' target='_blank'>{repo_name}</a> (⭐ {stars}, 语言: {language})\n"
+                f"- **文件路径**: <a href='{file_url}' target='_blank'>{file_path}</a>\n\n"
+                f"```{language.lower()}\n{displayed_code}\n```\n\n"
+            )
+            
+            formatted.append(reference)
+            
+        return "\n".join(formatted) 
--- a/crazy_functions/paper_fns/auto_git/handlers/repo_handler.py
+++ b/crazy_functions/paper_fns/auto_git/handlers/repo_handler.py
@@ -0,0 +1,192 @@
+from typing import List, Dict, Any
+from .base_handler import BaseHandler
+from ..query_analyzer import SearchCriteria
+import asyncio
+
+class RepositoryHandler(BaseHandler):
+    """仓库搜索处理器"""
+    
+    def __init__(self, github, llm_kwargs=None):
+        super().__init__(github, llm_kwargs)
+    
+    async def handle(
+        self,
+        criteria: SearchCriteria,
+        chatbot: List[List[str]],
+        history: List[List[str]],
+        system_prompt: str,
+        llm_kwargs: Dict[str, Any],
+        plugin_kwargs: Dict[str, Any],
+    ) -> str:
+        """处理仓库搜索请求，返回最终的prompt"""
+        
+        search_params = self._get_search_params(plugin_kwargs)
+        
+        # 如果是特定仓库查询
+        if criteria.repo_id:
+            try:
+                owner, repo = criteria.repo_id.split('/')
+                repo_details = await self.github.get_repo(owner, repo)
+                if repo_details:
+                    # 获取推荐的相似仓库
+                    similar_repos = await self.github.get_repo_recommendations(criteria.repo_id, limit=5)
+                    
+                    # 添加详细信息
+                    all_repos = [repo_details] + similar_repos
+                    enhanced_repos = await self._get_repo_details(all_repos)
+                    
+                    self.ranked_repos = enhanced_repos
+                    
+                    # 构建最终的prompt
+                    current_time = self._get_current_time()
+                    final_prompt = self._build_repo_detail_prompt(enhanced_repos[0], enhanced_repos[1:], current_time)
+                    return final_prompt
+                else:
+                    return self._generate_apology_prompt(criteria)
+            except Exception as e:
+                print(f"处理特定仓库时出错: {str(e)}")
+                return self._generate_apology_prompt(criteria)
+        
+        # 一般仓库搜索
+        repos = await self._search_bilingual_repositories(
+            english_query=criteria.github_params["query"],
+            chinese_query=criteria.github_params["chinese_query"],
+            language=criteria.language,
+            min_stars=criteria.min_stars,
+            per_page=search_params['max_repos']
+        )
+        
+        if not repos:
+            return self._generate_apology_prompt(criteria)
+        
+        # 获取仓库详情
+        enhanced_repos = await self._get_repo_details(repos[:search_params['max_details']])  # 使用max_details参数
+        self.ranked_repos = enhanced_repos
+        
+        if not enhanced_repos:
+            return self._generate_apology_prompt(criteria)
+        
+        # 构建最终的prompt
+        current_time = self._get_current_time()
+        final_prompt = f"""当前时间: {current_time}
+
+基于用户对{criteria.main_topic}的兴趣，以下是相关的GitHub仓库。
+
+可供推荐的GitHub仓库:
+{self._format_repos(enhanced_repos)}
+
+请提供:
+1. 按功能、用途或成熟度对仓库进行分组
+
+2. 对每个仓库：
+   - 简要描述其主要功能和用途
+   - 分析其技术特点和优势
+   - 说明其适用场景和使用难度
+   - 指出其与同类产品相比的独特优势
+   - 解释其星标数量和活跃度代表的意义
+
+3. 使用建议：
+   - 新手最适合入门的仓库
+   - 生产环境中最稳定可靠的选择
+   - 最新技术栈或创新方案的代表
+   - 学习特定技术的最佳资源
+
+4. 相关资源：
+   - 学习这些项目需要的前置知识
+   - 项目间的关联和技术栈兼容性
+   - 可能的使用组合方案
+
+重要提示:
+- 重点解释为什么每个仓库值得关注
+- 突出项目间的关联性和差异性
+- 考虑用户不同水平的需求(初学者vs专业人士)
+- 在介绍项目时，使用<a href='链接' target='_blank'>文本</a>格式，确保链接在新窗口打开
+- 根据仓库的活跃度、更新频率、维护状态提供使用建议
+- 仅基于提供的信息，不要做无根据的猜测
+- 在信息缺失或不明确时，坦诚说明
+
+使用markdown格式提供清晰的分节回复。
+"""
+        
+        return final_prompt
+
+    def _build_repo_detail_prompt(self, main_repo: Dict, similar_repos: List[Dict], current_time: str) -> str:
+        """构建仓库详情prompt"""
+        
+        # 提取README摘要
+        readme_content = "未提供"
+        if main_repo.get('readme_excerpt'):
+            readme_content = main_repo.get('readme_excerpt')
+            
+        # 构建语言分布
+        languages = main_repo.get('languages_detail', {})
+        lang_distribution = []
+        if languages:
+            total = sum(languages.values())
+            for lang, bytes_val in languages.items():
+                percentage = (bytes_val / total) * 100
+                lang_distribution.append(f"{lang}: {percentage:.1f}%")
+        
+        lang_str = "未知"
+        if lang_distribution:
+            lang_str = ", ".join(lang_distribution)
+            
+        # 构建最终prompt
+        prompt = f"""当前时间: {current_time}
+
+## 主要仓库信息
+
+### {main_repo.get('full_name')}
+
+- **描述**: {main_repo.get('description', '未提供')}
+- **星标数**: {main_repo.get('stargazers_count', 0)}
+- **Fork数**: {main_repo.get('forks_count', 0)}
+- **Watch数**: {main_repo.get('watchers_count', 0)}
+- **Issues数**: {main_repo.get('open_issues_count', 0)}
+- **语言分布**: {lang_str}
+- **许可证**: {main_repo.get('license', {}).get('name', '未指定') if main_repo.get('license') is not None else '未指定'}
+- **创建时间**: {main_repo.get('created_at', '')[:10]}
+- **最近更新**: {main_repo.get('updated_at', '')[:10]}
+- **主题标签**: {', '.join(main_repo.get('topics', ['无']))}
+- **GitHub链接**: <a href='{main_repo.get('html_url')}' target='_blank'>链接</a>
+
+### README摘要:
+{readme_content}
+
+## 类似仓库:
+{self._format_repos(similar_repos)}
+
+请提供以下内容:
+
+1. **项目概述**
+   - 详细解释{main_repo.get('name', '')}项目的主要功能和用途
+   - 分析其技术特点、架构和实现原理
+   - 讨论其在所属领域的地位和影响力
+   - 评估项目成熟度和稳定性
+
+2. **优势与特点**
+   - 与同类项目相比的独特优势
+   - 显著的技术创新或设计模式
+   - 值得学习或借鉴的代码实践
+
+3. **使用场景**
+   - 最适合的应用场景
+   - 潜在的使用限制和注意事项
+   - 入门门槛和学习曲线评估
+   - 产品级应用的可行性分析
+
+4. **资源与生态**
+   - 相关学习资源推荐
+   - 配套工具和库的建议
+   - 社区支持和活跃度评估
+
+5. **类似项目对比**
+   - 与列出的类似项目的详细对比
+   - 不同场景下的最佳选择建议
+   - 潜在的互补使用方案
+
+提示：所有链接请使用<a href='链接地址' target='_blank'>链接文本</a>格式，确保链接在新窗口打开。
+
+请以专业、客观的技术分析角度回答，使用markdown格式提供结构化信息。
+"""
+        return prompt 
--- a/crazy_functions/paper_fns/auto_git/handlers/topic_handler.py
+++ b/crazy_functions/paper_fns/auto_git/handlers/topic_handler.py
@@ -0,0 +1,217 @@
+from typing import List, Dict, Any
+from .base_handler import BaseHandler
+from ..query_analyzer import SearchCriteria
+import asyncio
+
+class TopicHandler(BaseHandler):
+    """主题搜索处理器"""
+    
+    def __init__(self, github, llm_kwargs=None):
+        super().__init__(github, llm_kwargs)
+    
+    async def handle(
+        self,
+        criteria: SearchCriteria,
+        chatbot: List[List[str]],
+        history: List[List[str]],
+        system_prompt: str,
+        llm_kwargs: Dict[str, Any],
+        plugin_kwargs: Dict[str, Any],
+    ) -> str:
+        """处理主题搜索请求，返回最终的prompt"""
+        
+        search_params = self._get_search_params(plugin_kwargs)
+        
+        # 搜索主题
+        topics = await self._search_bilingual_topics(
+            english_query=criteria.github_params["query"],
+            chinese_query=criteria.github_params["chinese_query"],
+            per_page=search_params['max_repos']
+        )
+        
+        if not topics:
+            # 尝试用主题搜索仓库
+            search_query = criteria.github_params["query"]
+            chinese_search_query = criteria.github_params["chinese_query"]
+            if "topic:" not in search_query:
+                search_query += " topic:" + criteria.main_topic.replace(" ", "-")
+            if "topic:" not in chinese_search_query:
+                chinese_search_query += " topic:" + criteria.main_topic.replace(" ", "-")
+            
+            repos = await self._search_bilingual_repositories(
+                english_query=search_query,
+                chinese_query=chinese_search_query,
+                language=criteria.language,
+                min_stars=criteria.min_stars,
+                per_page=search_params['max_repos']
+            )
+            
+            if not repos:
+                return self._generate_apology_prompt(criteria)
+                
+            # 获取仓库详情
+            enhanced_repos = await self._get_repo_details(repos[:10])
+            self.ranked_repos = enhanced_repos
+            
+            if not enhanced_repos:
+                return self._generate_apology_prompt(criteria)
+                
+            # 构建基于主题的仓库列表prompt
+            current_time = self._get_current_time()
+            final_prompt = f"""当前时间: {current_time}
+
+基于用户对主题"{criteria.main_topic}"的查询，我找到了以下相关GitHub仓库。
+
+主题相关仓库:
+{self._format_repos(enhanced_repos)}
+
+请提供:
+
+1. 主题综述:
+   - "{criteria.main_topic}"主题的概述和重要性
+   - 该主题在技术领域中的应用和发展趋势
+   - 主题相关的主要技术栈和知识体系
+
+2. 仓库分析:
+   - 按功能、技术栈或应用场景对仓库进行分类
+   - 每个仓库在该主题领域的定位和贡献
+   - 不同仓库间的技术路线对比
+
+3. 学习路径建议:
+   - 初学者入门该主题的推荐仓库和学习顺序
+   - 进阶学习的关键仓库和技术要点
+   - 实际应用中的最佳实践选择
+
+4. 技术生态分析:
+   - 该主题下的主流工具和库
+   - 社区活跃度和维护状况
+   - 与其他相关技术的集成方案
+
+重要提示:
+- 主题"{criteria.main_topic}"是用户查询的核心，请围绕此主题展开分析
+- 注重仓库质量评估和使用建议
+- 提供基于事实的客观技术分析
+- 在介绍仓库时使用<a href='链接地址' target='_blank'>链接文本</a>格式，确保链接在新窗口打开
+- 考虑不同技术水平用户的需求
+
+使用markdown格式提供清晰的分节回复。
+"""
+            return final_prompt
+            
+        # 如果找到了主题，则获取主题下的热门仓库
+        topic_repos = []
+        for topic in topics[:5]:  # 增加到5个主题
+            topic_name = topic.get('name', '')
+            if topic_name:
+                # 搜索该主题下的仓库
+                repos = await self._search_repositories(
+                    query=f"topic:{topic_name}",
+                    language=criteria.language,
+                    min_stars=criteria.min_stars,
+                    per_page=20  # 每个主题最多20个仓库
+                )
+                
+                if repos:
+                    for repo in repos:
+                        repo['topic_source'] = topic_name
+                        topic_repos.append(repo)
+        
+        if not topic_repos:
+            return self._generate_apology_prompt(criteria)
+            
+        # 获取前N个仓库的详情
+        enhanced_repos = await self._get_repo_details(topic_repos[:search_params['max_details']])
+        self.ranked_repos = enhanced_repos
+        
+        if not enhanced_repos:
+            return self._generate_apology_prompt(criteria)
+            
+        # 构建最终的prompt
+        current_time = self._get_current_time()
+        final_prompt = f"""当前时间: {current_time}
+
+基于用户对"{criteria.main_topic}"主题的查询，我找到了以下相关GitHub主题和仓库。
+
+主题相关仓库:
+{self._format_topic_repos(enhanced_repos)}
+
+请提供:
+
+1. 主题概述:
+   - 对"{criteria.main_topic}"相关主题的介绍和技术背景
+   - 这些主题在软件开发中的重要性和应用范围
+   - 主题间的关联性和技术演进路径
+
+2. 精选仓库分析:
+   - 每个主题下最具代表性的仓库详解
+   - 仓库的技术亮点和创新点
+   - 使用场景和技术成熟度评估
+
+3. 技术趋势分析:
+   - 基于主题和仓库活跃度的技术发展趋势
+   - 新兴解决方案和传统方案的对比
+   - 未来可能的技术方向预测
+
+4. 实践建议:
+   - 不同应用场景下的最佳仓库选择
+   - 学习路径和资源推荐
+   - 实际项目中的应用策略
+
+重要提示:
+- 将分析重点放在主题的技术内涵和价值上
+- 突出主题间的关联性和技术演进脉络
+- 提供基于数据(星标数、更新频率等)的客观分析
+- 考虑不同技术背景用户的需求
+- 所有链接请使用<a href='链接地址' target='_blank'>链接文本</a>格式，确保链接在新窗口打开
+
+使用markdown格式提供清晰的分节回复。
+"""
+        
+        return final_prompt
+        
+    def _format_topic_repos(self, repos: List[Dict]) -> str:
+        """按主题格式化仓库列表"""
+        # 按主题分组
+        topics_dict = {}
+        for repo in repos:
+            topic = repo.get('topic_source', '其他')
+            if topic not in topics_dict:
+                topics_dict[topic] = []
+            topics_dict[topic].append(repo)
+        
+        # 格式化输出
+        formatted = []
+        for topic, topic_repos in topics_dict.items():
+            formatted.append(f"## 主题: {topic}\n")
+            
+            for i, repo in enumerate(topic_repos, 1):
+                # 构建仓库URL
+                repo_url = repo.get('html_url', '')
+                
+                # 构建引用
+                reference = (
+                    f"{i}. **{repo.get('full_name', '')}**\n"
+                    f"   - 描述: {repo.get('description', 'N/A')}\n"
+                    f"   - 语言: {repo.get('language', 'N/A')}\n"
+                    f"   - 星标: {repo.get('stargazers_count', 0)}\n"
+                    f"   - Fork数: {repo.get('forks_count', 0)}\n"
+                    f"   - 更新时间: {repo.get('updated_at', 'N/A')[:10]}\n"
+                    f"   - URL: <a href='{repo_url}' target='_blank'>{repo_url}</a>\n"
+                )
+                
+                # 添加主题标签(如果有)
+                if repo.get('topics'):
+                    topics_str = ", ".join(repo.get('topics'))
+                    reference += f"   - 主题标签: {topics_str}\n"
+                
+                # 添加README摘要(如果有)
+                if repo.get('readme_excerpt'):
+                    # 截断README，只取前200个字符
+                    readme_short = repo.get('readme_excerpt')[:200].replace('\n', ' ')
+                    reference += f"   - README摘要: {readme_short}...\n"
+                
+                formatted.append(reference)
+            
+            formatted.append("\n")  # 主题之间添加空行
+            
+        return "\n".join(formatted) 
--- a/crazy_functions/paper_fns/auto_git/handlers/user_handler.py
+++ b/crazy_functions/paper_fns/auto_git/handlers/user_handler.py
@@ -0,0 +1,164 @@
+from typing import List, Dict, Any
+from .base_handler import BaseHandler
+from ..query_analyzer import SearchCriteria
+import asyncio
+
+class UserSearchHandler(BaseHandler):
+    """用户搜索处理器"""
+    
+    def __init__(self, github, llm_kwargs=None):
+        super().__init__(github, llm_kwargs)
+    
+    async def handle(
+        self,
+        criteria: SearchCriteria,
+        chatbot: List[List[str]],
+        history: List[List[str]],
+        system_prompt: str,
+        llm_kwargs: Dict[str, Any],
+        plugin_kwargs: Dict[str, Any],
+    ) -> str:
+        """处理用户搜索请求，返回最终的prompt"""
+        
+        search_params = self._get_search_params(plugin_kwargs)
+        
+        # 搜索用户
+        users = await self._search_bilingual_users(
+            english_query=criteria.github_params["query"],
+            chinese_query=criteria.github_params["chinese_query"],
+            per_page=search_params['max_repos']
+        )
+        
+        if not users:
+            return self._generate_apology_prompt(criteria)
+            
+        # 获取用户详情和仓库
+        enhanced_users = await self._get_user_details(users[:search_params['max_details']])
+        self.ranked_repos = []  # 添加用户top仓库进行展示
+        
+        for user in enhanced_users:
+            if user.get('top_repos'):
+                self.ranked_repos.extend(user.get('top_repos'))
+        
+        if not enhanced_users:
+            return self._generate_apology_prompt(criteria)
+        
+        # 构建最终的prompt
+        current_time = self._get_current_time()
+        final_prompt = f"""当前时间: {current_time}
+
+基于用户对{criteria.main_topic}的查询，我找到了以下GitHub用户。
+
+GitHub用户搜索结果:
+{self._format_users(enhanced_users)}
+
+请提供:
+
+1. 用户综合分析:
+   - 各开发者的专业领域和技术专长
+   - 他们在GitHub开源社区的影响力
+   - 技术实力和项目质量评估
+
+2. 对每位开发者:
+   - 其主要贡献领域和技术栈
+   - 代表性项目及其价值
+   - 编程风格和技术特点
+   - 在相关领域的影响力
+
+3. 项目推荐:
+   - 针对用户查询的最有价值项目
+   - 值得学习和借鉴的代码实践
+   - 不同用户项目的相互补充关系
+
+4. 如何学习和使用:
+   - 如何从这些开发者项目中学习
+   - 最适合入门学习的项目
+   - 进阶学习的路径建议
+
+重要提示:
+- 关注开发者的技术专长和核心贡献
+- 分析其开源项目的技术价值
+- 根据用户的原始查询提供相关建议
+- 避免过度赞美或主观评价
+- 基于事实数据(项目数、星标数等)进行客观分析
+- 所有链接请使用<a href='链接地址' target='_blank'>链接文本</a>格式，确保链接在新窗口打开
+
+使用markdown格式提供清晰的分节回复。
+"""
+        
+        return final_prompt
+
+    async def _get_user_details(self, users: List[Dict]) -> List[Dict]:
+        """获取用户详情和仓库"""
+        enhanced_users = []
+        
+        for user in users:
+            try:
+                username = user.get('login')
+                
+                if username:
+                    # 获取用户详情
+                    user_details = await self.github.get_user(username)
+                    if user_details:
+                        user.update(user_details)
+                    
+                    # 获取用户仓库
+                    repos = await self.github.get_user_repos(
+                        username,
+                        sort="stars",
+                        per_page=10  # 增加到10个仓库
+                    )
+                    if repos:
+                        user['top_repos'] = repos
+                
+                enhanced_users.append(user)
+            except Exception as e:
+                print(f"获取用户 {user.get('login')} 详情时出错: {str(e)}")
+                enhanced_users.append(user)  # 添加原始信息
+                
+        return enhanced_users
+
+    def _format_users(self, users: List[Dict]) -> str:
+        """格式化用户列表"""
+        formatted = []
+        
+        for i, user in enumerate(users, 1):
+            # 构建用户信息
+            username = user.get('login', 'N/A')
+            name = user.get('name', username)
+            profile_url = user.get('html_url', '')
+            bio = user.get('bio', '无简介')
+            followers = user.get('followers', 0)
+            public_repos = user.get('public_repos', 0)
+            company = user.get('company', '未指定')
+            location = user.get('location', '未指定')
+            blog = user.get('blog', '')
+            
+            user_info = (
+                f"### {i}. {name} (@{username})\n\n"
+                f"- **简介**: {bio}\n"
+                f"- **关注者**: {followers} | **公开仓库**: {public_repos}\n"
+                f"- **公司**: {company} | **地点**: {location}\n"
+                f"- **个人网站**: {blog}\n"
+                f"- **GitHub**: <a href='{profile_url}' target='_blank'>{username}</a>\n\n"
+            )
+            
+            # 添加用户的热门仓库
+            top_repos = user.get('top_repos', [])
+            if top_repos:
+                user_info += "**热门仓库**:\n\n"
+                for repo in top_repos:
+                    repo_name = repo.get('name', '')
+                    repo_url = repo.get('html_url', '')
+                    repo_desc = repo.get('description', '无描述')
+                    repo_stars = repo.get('stargazers_count', 0)
+                    repo_language = repo.get('language', '未指定')
+                    
+                    user_info += (
+                        f"- <a href='{repo_url}' target='_blank'>{repo_name}</a> - ⭐ {repo_stars}, {repo_language}\n"
+                        f"  {repo_desc}\n\n"
+                    )
+            
+            formatted.append(user_info)
+            
+        return "\n".join(formatted) 
--- a/crazy_functions/paper_fns/auto_git/query_analyzer.py
+++ b/crazy_functions/paper_fns/auto_git/query_analyzer.py
@@ -0,0 +1,356 @@
+from typing import Dict, List
+from dataclasses import dataclass
+import re
+
+@dataclass
+class SearchCriteria:
+    """搜索条件"""
+    query_type: str  # 查询类型: repo/code/user/topic
+    main_topic: str  # 主题
+    sub_topics: List[str]  # 子主题列表
+    language: str  # 编程语言
+    min_stars: int  # 最少星标数
+    github_params: Dict  # GitHub搜索参数
+    original_query: str = ""  # 原始查询字符串
+    repo_id: str = ""  # 特定仓库ID或名称
+
+class QueryAnalyzer:
+    """查询分析器"""
+
+    # 响应索引常量
+    BASIC_QUERY_INDEX = 0
+    GITHUB_QUERY_INDEX = 1
+    
+    def __init__(self):
+        self.valid_types = {
+            "repo": ["repository", "project", "library", "framework", "tool"],
+            "code": ["code", "snippet", "implementation", "function", "class", "algorithm"],
+            "user": ["user", "developer", "organization", "contributor", "maintainer"],
+            "topic": ["topic", "category", "tag", "field", "area", "domain"]
+        }
+
+    def analyze_query(self, query: str, chatbot: List, llm_kwargs: Dict):
+        """分析查询意图"""
+        from crazy_functions.crazy_utils import \
+            request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency as request_gpt
+        
+        # 1. 基本查询分析
+        type_prompt = f"""请分析这个与GitHub相关的查询，并严格按照以下XML格式回答：
+
+查询: {query}
+
+说明:
+1. 你的回答必须使用下面显示的XML标签，不要有任何标签外的文本
+2. 从以下选项中选择查询类型: repo/code/user/topic
+   - repo: 用于查找仓库、项目、框架或库
+   - code: 用于查找代码片段、函数实现或算法
+   - user: 用于查找用户、开发者或组织
+   - topic: 用于查找主题、类别或领域相关项目
+3. 识别主题和子主题
+4. 识别首选编程语言(如果有)
+5. 确定最低星标数(如果适用)
+
+必需格式:
+<query_type>此处回答</query_type>
+<main_topic>此处回答</main_topic>
+<sub_topics>子主题1, 子主题2, ...</sub_topics>
+<language>此处回答</language>
+<min_stars>此处回答</min_stars>
+
+示例回答:
+
+1. 仓库查询:
+查询: "查找有至少1000颗星的Python web框架"
+<query_type>repo</query_type>
+<main_topic>web框架</main_topic>
+<sub_topics>后端开发, HTTP服务器, ORM</sub_topics>
+<language>Python</language>
+<min_stars>1000</min_stars>
+
+2. 代码查询:
+查询: "如何用JavaScript实现防抖函数"
+<query_type>code</query_type>
+<main_topic>防抖函数</main_topic>
+<sub_topics>事件处理, 性能优化, 函数节流</sub_topics>
+<language>JavaScript</language>
+<min_stars>0</min_stars>"""
+
+        # 2. 生成英文搜索条件
+        github_prompt = f"""Optimize the following GitHub search query:
+
+Query: {query}
+
+Task: Convert the natural language query into an optimized GitHub search query.
+Please use English, regardless of the language of the input query.
+
+Available search fields and filters:
+1. Basic fields:
+   - in:name - Search in repository names
+   - in:description - Search in repository descriptions
+   - in:readme - Search in README files
+   - in:topic - Search in topics
+   - language:X - Filter by programming language
+   - user:X - Repositories from a specific user
+   - org:X - Repositories from a specific organization
+
+2. Code search fields:
+   - extension:X - Filter by file extension
+   - path:X - Filter by path
+   - filename:X - Filter by filename
+
+3. Metric filters:
+   - stars:>X - Has more than X stars
+   - forks:>X - Has more than X forks
+   - size:>X - Size greater than X KB
+   - created:>YYYY-MM-DD - Created after a specific date
+   - pushed:>YYYY-MM-DD - Updated after a specific date
+
+4. Other filters:
+   - is:public/private - Public or private repositories
+   - archived:true/false - Archived or not archived
+   - license:X - Specific license
+   - topic:X - Contains specific topic tag
+
+Examples:
+
+1. Query: "Find Python machine learning libraries with at least 1000 stars"
+<query>machine learning in:description language:python stars:>1000</query>
+
+2. Query: "Recently updated React UI component libraries"
+<query>UI components library in:readme in:description language:javascript topic:react pushed:>2023-01-01</query>
+
+3. Query: "Open source projects developed by Facebook"
+<query>org:facebook is:public</query>
+
+4. Query: "Depth-first search implementation in JavaScript"
+<query>depth first search in:file language:javascript</query>
+
+Please analyze the query and answer using only the XML tag:
+<query>Provide the optimized GitHub search query, using appropriate fields and operators</query>"""
+
+        # 3. 生成中文搜索条件
+        chinese_github_prompt = f"""优化以下GitHub搜索查询:
+
+查询: {query}
+
+任务: 将自然语言查询转换为优化的GitHub搜索查询语句。
+为了搜索中文内容，请提取原始查询的关键词并使用中文形式，同时保留GitHub特定的搜索语法为英文。
+
+可用的搜索字段和过滤器:
+1. 基本字段:
+   - in:name - 在仓库名称中搜索
+   - in:description - 在仓库描述中搜索
+   - in:readme - 在README文件中搜索
+   - in:topic - 在主题中搜索
+   - language:X - 按编程语言筛选
+   - user:X - 特定用户的仓库
+   - org:X - 特定组织的仓库
+
+2. 代码搜索字段:
+   - extension:X - 按文件扩展名筛选
+   - path:X - 按路径筛选
+   - filename:X - 按文件名筛选
+
+3. 指标过滤器:
+   - stars:>X - 有超过X颗星
+   - forks:>X - 有超过X个分支
+   - size:>X - 大小超过X KB
+   - created:>YYYY-MM-DD - 在特定日期后创建
+   - pushed:>YYYY-MM-DD - 在特定日期后更新
+
+4. 其他过滤器:
+   - is:public/private - 公开或私有仓库
+   - archived:true/false - 已归档或未归档
+   - license:X - 特定许可证
+   - topic:X - 含特定主题标签
+
+示例:
+
+1. 查询: "找有关机器学习的Python库，至少1000颗星"
+<query>机器学习 in:description language:python stars:>1000</query>
+
+2. 查询: "最近更新的React UI组件库"
+<query>UI 组件库 in:readme in:description language:javascript topic:react pushed:>2023-01-01</query>
+
+3. 查询: "微信小程序开发框架"
+<query>微信小程序 开发框架 in:name in:description in:readme</query>
+
+请分析查询并仅使用XML标签回答:
+<query>提供优化的GitHub搜索查询，使用适当的字段和运算符，保留中文关键词</query>"""
+
+        try:
+            # 构建提示数组
+            prompts = [
+                type_prompt,
+                github_prompt,
+                chinese_github_prompt,
+            ]
+
+            show_messages = [
+                "分析查询类型...",
+                "优化英文GitHub搜索参数...",
+                "优化中文GitHub搜索参数...",
+            ]
+
+            sys_prompts = [
+                "你是一个精通GitHub生态系统的专家，擅长分析与GitHub相关的查询。",
+                "You are a GitHub search expert, specialized in converting natural language queries into optimized GitHub search queries in English.",
+                "你是一个GitHub搜索专家，擅长处理查询并保留中文关键词进行搜索。",
+            ]
+            
+            # 使用同步方式调用LLM
+            responses = yield from request_gpt(
+                inputs_array=prompts,
+                inputs_show_user_array=show_messages,
+                llm_kwargs=llm_kwargs,
+                chatbot=chatbot,
+                history_array=[[] for _ in prompts],
+                sys_prompt_array=sys_prompts,
+                max_workers=3
+            )
+
+            # 从收集的响应中提取我们需要的内容
+            extracted_responses = []
+            for i in range(len(prompts)):
+                if (i * 2 + 1) < len(responses):
+                    response = responses[i * 2 + 1]
+                    if response is None:
+                        raise Exception(f"Response {i} is None")
+                    if not isinstance(response, str):
+                        try:
+                            response = str(response)
+                        except:
+                            raise Exception(f"Cannot convert response {i} to string")
+                    extracted_responses.append(response)
+                else:
+                    raise Exception(f"未收到第 {i + 1} 个响应")
+
+            # 解析基本信息
+            query_type = self._extract_tag(extracted_responses[self.BASIC_QUERY_INDEX], "query_type")
+            if not query_type:
+                print(
+                    f"Debug - Failed to extract query_type. Response was: {extracted_responses[self.BASIC_QUERY_INDEX]}")
+                raise Exception("无法提取query_type标签内容")
+            query_type = query_type.lower()
+
+            main_topic = self._extract_tag(extracted_responses[self.BASIC_QUERY_INDEX], "main_topic")
+            if not main_topic:
+                print(f"Debug - Failed to extract main_topic. Using query as fallback.")
+                main_topic = query
+
+            query_type = self._normalize_query_type(query_type, query)
+
+            # 提取子主题
+            sub_topics = []
+            sub_topics_text = self._extract_tag(extracted_responses[self.BASIC_QUERY_INDEX], "sub_topics")
+            if sub_topics_text:
+                sub_topics = [topic.strip() for topic in sub_topics_text.split(",")]
+
+            # 提取语言
+            language = self._extract_tag(extracted_responses[self.BASIC_QUERY_INDEX], "language")
+            
+            # 提取最低星标数
+            min_stars = 0
+            min_stars_text = self._extract_tag(extracted_responses[self.BASIC_QUERY_INDEX], "min_stars")
+            if min_stars_text and min_stars_text.isdigit():
+                min_stars = int(min_stars_text)
+
+            # 解析GitHub搜索参数 - 英文
+            english_github_query = self._extract_tag(extracted_responses[self.GITHUB_QUERY_INDEX], "query")
+            
+            # 解析GitHub搜索参数 - 中文
+            chinese_github_query = self._extract_tag(extracted_responses[2], "query")
+            
+            # 构建GitHub参数
+            github_params = {
+                "query": english_github_query,
+                "chinese_query": chinese_github_query,
+                "sort": "stars",  # 默认按星标排序
+                "order": "desc",  # 默认降序
+                "per_page": 30,   # 默认每页30条
+                "page": 1         # 默认第1页
+            }
+            
+            # 检查是否为特定仓库查询
+            repo_id = ""
+            if "repo:" in english_github_query or "repository:" in english_github_query:
+                repo_match = re.search(r'(repo|repository):([a-zA-Z0-9_.-]+/[a-zA-Z0-9_.-]+)', english_github_query)
+                if repo_match:
+                    repo_id = repo_match.group(2)
+            
+            print(f"Debug - 提取的信息:")
+            print(f"查询类型: {query_type}")
+            print(f"主题: {main_topic}")
+            print(f"子主题: {sub_topics}")
+            print(f"语言: {language}")
+            print(f"最低星标数: {min_stars}")
+            print(f"英文GitHub参数: {english_github_query}")
+            print(f"中文GitHub参数: {chinese_github_query}")
+            print(f"特定仓库: {repo_id}")
+
+            # 更新返回的 SearchCriteria，包含中英文查询
+            return SearchCriteria(
+                query_type=query_type,
+                main_topic=main_topic,
+                sub_topics=sub_topics,
+                language=language,
+                min_stars=min_stars,
+                github_params=github_params,
+                original_query=query,
+                repo_id=repo_id
+            )
+
+        except Exception as e:
+            raise Exception(f"分析查询失败: {str(e)}")
+
+    def _normalize_query_type(self, query_type: str, query: str) -> str:
+        """规范化查询类型"""
+        if query_type in ["repo", "code", "user", "topic"]:
+            return query_type
+
+        query_lower = query.lower()
+        for type_name, keywords in self.valid_types.items():
+            for keyword in keywords:
+                if keyword in query_lower:
+                    return type_name
+
+        query_type_lower = query_type.lower()
+        for type_name, keywords in self.valid_types.items():
+            for keyword in keywords:
+                if keyword in query_type_lower:
+                    return type_name
+
+        return "repo"  # 默认返回repo类型
+
+    def _extract_tag(self, text: str, tag: str) -> str:
+        """提取标记内容"""
+        if not text:
+            return ""
+
+        # 标准XML格式（处理多行和特殊字符）
+        pattern = f"<{tag}>(.*?)</{tag}>"
+        match = re.search(pattern, text, re.DOTALL | re.IGNORECASE)
+        if match:
+            content = match.group(1).strip()
+            if content:
+                return content
+
+        # 备用模式
+        patterns = [
+            rf"<{tag}>\s*([\s\S]*?)\s*</{tag}>",  # 标准XML格式
+            rf"<{tag}>([\s\S]*?)(?:</{tag}>|$)",  # 未闭合的标签
+            rf"[{tag}]([\s\S]*?)[/{tag}]",  # 方括号格式
+            rf"{tag}:\s*(.*?)(?=\n\w|$)",  # 冒号格式
+            rf"<{tag}>\s*(.*?)(?=<|$)"  # 部分闭合
+        ]
+
+        # 尝试所有模式
+        for pattern in patterns:
+            match = re.search(pattern, text, re.IGNORECASE | re.DOTALL)
+            if match:
+                content = match.group(1).strip()
+                if content:  # 确保提取的内容不为空
+                    return content
+
+        # 如果所有模式都失败，返回空字符串
+        return "" 
--- a/crazy_functions/paper_fns/auto_git/sources/github_source.py
+++ b/crazy_functions/paper_fns/auto_git/sources/github_source.py
@@ -0,0 +1,701 @@
+import aiohttp
+import asyncio
+import base64
+import json
+import random
+from datetime import datetime
+from typing import List, Dict, Optional, Union, Any
+
+class GitHubSource:
+    """GitHub API实现"""
+
+    # 默认API密钥列表 - 可以放置多个GitHub令牌
+    API_KEYS = [
+        "github_pat_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
+        "github_pat_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
+        # "your_github_token_1",
+        # "your_github_token_2",
+        # "your_github_token_3"
+    ]
+
+    def __init__(self, api_key: Optional[Union[str, List[str]]] = None):
+        """初始化GitHub API客户端
+
+        Args:
+            api_key: GitHub个人访问令牌或令牌列表
+        """
+        if api_key is None:
+            self.api_keys = self.API_KEYS
+        elif isinstance(api_key, str):
+            self.api_keys = [api_key]
+        else:
+            self.api_keys = api_key
+
+        self._initialize()
+
+    def _initialize(self) -> None:
+        """初始化客户端，设置默认参数"""
+        self.base_url = "https://api.github.com"
+        self.headers = {
+            "Accept": "application/vnd.github+json",
+            "X-GitHub-Api-Version": "2022-11-28",
+            "User-Agent": "GitHub-API-Python-Client"
+        }
+
+        # 如果有可用的API密钥，随机选择一个
+        if self.api_keys:
+            selected_key = random.choice(self.api_keys)
+            self.headers["Authorization"] = f"Bearer {selected_key}"
+            print(f"已随机选择API密钥进行认证")
+        else:
+            print("警告: 未提供API密钥，将受到GitHub API请求限制")
+
+    async def _request(self, method: str, endpoint: str, params: Dict = None, data: Dict = None) -> Any:
+        """发送API请求
+
+        Args:
+            method: HTTP方法 (GET, POST, PUT, DELETE等)
+            endpoint: API端点
+            params: URL参数
+            data: 请求体数据
+
+        Returns:
+            解析后的响应JSON
+        """
+        async with aiohttp.ClientSession(headers=self.headers) as session:
+            url = f"{self.base_url}{endpoint}"
+
+            # 为调试目的打印请求信息
+            print(f"请求: {method} {url}")
+            if params:
+                print(f"参数: {params}")
+
+            # 发送请求
+            request_kwargs = {}
+            if params:
+                request_kwargs["params"] = params
+            if data:
+                request_kwargs["json"] = data
+
+            async with session.request(method, url, **request_kwargs) as response:
+                response_text = await response.text()
+
+                # 检查HTTP状态码
+                if response.status >= 400:
+                    print(f"API请求失败: HTTP {response.status}")
+                    print(f"响应内容: {response_text}")
+                    return None
+
+                # 解析JSON响应
+                try:
+                    return json.loads(response_text)
+                except json.JSONDecodeError:
+                    print(f"JSON解析错误: {response_text}")
+                    return None
+
+    # ===== 用户相关方法 =====
+
+    async def get_user(self, username: Optional[str] = None) -> Dict:
+        """获取用户信息
+
+        Args:
+            username: 指定用户名，不指定则获取当前授权用户
+
+        Returns:
+            用户信息字典
+        """
+        endpoint = "/user" if username is None else f"/users/{username}"
+        return await self._request("GET", endpoint)
+
+    async def get_user_repos(self, username: Optional[str] = None, sort: str = "updated",
+                            direction: str = "desc", per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取用户的仓库列表
+
+        Args:
+            username: 指定用户名，不指定则获取当前授权用户
+            sort: 排序方式 (created, updated, pushed, full_name)
+            direction: 排序方向 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            仓库列表
+        """
+        endpoint = "/user/repos" if username is None else f"/users/{username}/repos"
+        params = {
+            "sort": sort,
+            "direction": direction,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_user_starred(self, username: Optional[str] = None,
+                              per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取用户星标的仓库
+
+        Args:
+            username: 指定用户名，不指定则获取当前授权用户
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            星标仓库列表
+        """
+        endpoint = "/user/starred" if username is None else f"/users/{username}/starred"
+        params = {
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    # ===== 仓库相关方法 =====
+
+    async def get_repo(self, owner: str, repo: str) -> Dict:
+        """获取仓库信息
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+
+        Returns:
+            仓库信息
+        """
+        endpoint = f"/repos/{owner}/{repo}"
+        return await self._request("GET", endpoint)
+
+    async def get_repo_branches(self, owner: str, repo: str, per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取仓库的分支列表
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            分支列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/branches"
+        params = {
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_repo_commits(self, owner: str, repo: str, sha: Optional[str] = None,
+                              path: Optional[str] = None, per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取仓库的提交历史
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            sha: 特定提交SHA或分支名
+            path: 文件路径筛选
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            提交列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/commits"
+        params = {
+            "per_page": per_page,
+            "page": page
+        }
+        if sha:
+            params["sha"] = sha
+        if path:
+            params["path"] = path
+
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_commit_details(self, owner: str, repo: str, commit_sha: str) -> Dict:
+        """获取特定提交的详情
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            commit_sha: 提交SHA
+
+        Returns:
+            提交详情
+        """
+        endpoint = f"/repos/{owner}/{repo}/commits/{commit_sha}"
+        return await self._request("GET", endpoint)
+
+    # ===== 内容相关方法 =====
+
+    async def get_file_content(self, owner: str, repo: str, path: str, ref: Optional[str] = None) -> Dict:
+        """获取文件内容
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            path: 文件路径
+            ref: 分支名、标签名或提交SHA
+
+        Returns:
+            文件内容信息
+        """
+        endpoint = f"/repos/{owner}/{repo}/contents/{path}"
+        params = {}
+        if ref:
+            params["ref"] = ref
+
+        response = await self._request("GET", endpoint, params=params)
+        if response and isinstance(response, dict) and "content" in response:
+            try:
+                # 解码Base64编码的文件内容
+                content = base64.b64decode(response["content"].encode()).decode()
+                response["decoded_content"] = content
+            except Exception as e:
+                print(f"解码文件内容时出错: {str(e)}")
+
+        return response
+
+    async def get_directory_content(self, owner: str, repo: str, path: str, ref: Optional[str] = None) -> List[Dict]:
+        """获取目录内容
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            path: 目录路径
+            ref: 分支名、标签名或提交SHA
+
+        Returns:
+            目录内容列表
+        """
+        # 注意：此方法与get_file_content使用相同的端点，但对于目录会返回列表
+        endpoint = f"/repos/{owner}/{repo}/contents/{path}"
+        params = {}
+        if ref:
+            params["ref"] = ref
+
+        return await self._request("GET", endpoint, params=params)
+
+    # ===== Issues相关方法 =====
+
+    async def get_issues(self, owner: str, repo: str, state: str = "open",
+                        sort: str = "created", direction: str = "desc",
+                        per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取仓库的Issues列表
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            state: Issue状态 (open, closed, all)
+            sort: 排序方式 (created, updated, comments)
+            direction: 排序方向 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            Issues列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/issues"
+        params = {
+            "state": state,
+            "sort": sort,
+            "direction": direction,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_issue(self, owner: str, repo: str, issue_number: int) -> Dict:
+        """获取特定Issue的详情
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            issue_number: Issue编号
+
+        Returns:
+            Issue详情
+        """
+        endpoint = f"/repos/{owner}/{repo}/issues/{issue_number}"
+        return await self._request("GET", endpoint)
+
+    async def get_issue_comments(self, owner: str, repo: str, issue_number: int) -> List[Dict]:
+        """获取Issue的评论
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            issue_number: Issue编号
+
+        Returns:
+            评论列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/issues/{issue_number}/comments"
+        return await self._request("GET", endpoint)
+
+    # ===== Pull Requests相关方法 =====
+
+    async def get_pull_requests(self, owner: str, repo: str, state: str = "open",
+                               sort: str = "created", direction: str = "desc",
+                               per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取仓库的Pull Request列表
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            state: PR状态 (open, closed, all)
+            sort: 排序方式 (created, updated, popularity, long-running)
+            direction: 排序方向 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            Pull Request列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/pulls"
+        params = {
+            "state": state,
+            "sort": sort,
+            "direction": direction,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_pull_request(self, owner: str, repo: str, pr_number: int) -> Dict:
+        """获取特定Pull Request的详情
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            pr_number: Pull Request编号
+
+        Returns:
+            Pull Request详情
+        """
+        endpoint = f"/repos/{owner}/{repo}/pulls/{pr_number}"
+        return await self._request("GET", endpoint)
+
+    async def get_pull_request_files(self, owner: str, repo: str, pr_number: int) -> List[Dict]:
+        """获取Pull Request中修改的文件
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            pr_number: Pull Request编号
+
+        Returns:
+            修改文件列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/pulls/{pr_number}/files"
+        return await self._request("GET", endpoint)
+
+    # ===== 搜索相关方法 =====
+
+    async def search_repositories(self, query: str, sort: str = "stars",
+                                 order: str = "desc", per_page: int = 30, page: int = 1) -> Dict:
+        """搜索仓库
+
+        Args:
+            query: 搜索关键词
+            sort: 排序方式 (stars, forks, updated)
+            order: 排序顺序 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            搜索结果
+        """
+        endpoint = "/search/repositories"
+        params = {
+            "q": query,
+            "sort": sort,
+            "order": order,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def search_code(self, query: str, sort: str = "indexed",
+                         order: str = "desc", per_page: int = 30, page: int = 1) -> Dict:
+        """搜索代码
+
+        Args:
+            query: 搜索关键词
+            sort: 排序方式 (indexed)
+            order: 排序顺序 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            搜索结果
+        """
+        endpoint = "/search/code"
+        params = {
+            "q": query,
+            "sort": sort,
+            "order": order,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def search_issues(self, query: str, sort: str = "created",
+                           order: str = "desc", per_page: int = 30, page: int = 1) -> Dict:
+        """搜索Issues和Pull Requests
+
+        Args:
+            query: 搜索关键词
+            sort: 排序方式 (created, updated, comments)
+            order: 排序顺序 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            搜索结果
+        """
+        endpoint = "/search/issues"
+        params = {
+            "q": query,
+            "sort": sort,
+            "order": order,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def search_users(self, query: str, sort: str = "followers",
+                          order: str = "desc", per_page: int = 30, page: int = 1) -> Dict:
+        """搜索用户
+
+        Args:
+            query: 搜索关键词
+            sort: 排序方式 (followers, repositories, joined)
+            order: 排序顺序 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            搜索结果
+        """
+        endpoint = "/search/users"
+        params = {
+            "q": query,
+            "sort": sort,
+            "order": order,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    # ===== 组织相关方法 =====
+
+    async def get_organization(self, org: str) -> Dict:
+        """获取组织信息
+
+        Args:
+            org: 组织名称
+
+        Returns:
+            组织信息
+        """
+        endpoint = f"/orgs/{org}"
+        return await self._request("GET", endpoint)
+
+    async def get_organization_repos(self, org: str, type: str = "all",
+                                    sort: str = "created", direction: str = "desc",
+                                    per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取组织的仓库列表
+
+        Args:
+            org: 组织名称
+            type: 仓库类型 (all, public, private, forks, sources, member, internal)
+            sort: 排序方式 (created, updated, pushed, full_name)
+            direction: 排序方向 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            仓库列表
+        """
+        endpoint = f"/orgs/{org}/repos"
+        params = {
+            "type": type,
+            "sort": sort,
+            "direction": direction,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_organization_members(self, org: str, per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取组织成员列表
+
+        Args:
+            org: 组织名称
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            成员列表
+        """
+        endpoint = f"/orgs/{org}/members"
+        params = {
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    # ===== 更复杂的操作 =====
+
+    async def get_repository_languages(self, owner: str, repo: str) -> Dict:
+        """获取仓库使用的编程语言及其比例
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+
+        Returns:
+            语言使用情况
+        """
+        endpoint = f"/repos/{owner}/{repo}/languages"
+        return await self._request("GET", endpoint)
+
+    async def get_repository_stats_contributors(self, owner: str, repo: str) -> List[Dict]:
+        """获取仓库的贡献者统计
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+
+        Returns:
+            贡献者统计信息
+        """
+        endpoint = f"/repos/{owner}/{repo}/stats/contributors"
+        return await self._request("GET", endpoint)
+
+    async def get_repository_stats_commit_activity(self, owner: str, repo: str) -> List[Dict]:
+        """获取仓库的提交活动
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+
+        Returns:
+            提交活动统计
+        """
+        endpoint = f"/repos/{owner}/{repo}/stats/commit_activity"
+        return await self._request("GET", endpoint)
+
+async def example_usage():
+    """GitHubSource使用示例"""
+    # 创建客户端实例（可选传入API令牌）
+    # github = GitHubSource(api_key="your_github_token")
+    github = GitHubSource()
+
+    try:
+        # 示例1：搜索热门Python仓库
+        print("\n=== 示例1：搜索热门Python仓库 ===")
+        repos = await github.search_repositories(
+            query="language:python stars:>1000",
+            sort="stars",
+            order="desc",
+            per_page=5
+        )
+
+        if repos and "items" in repos:
+            for i, repo in enumerate(repos["items"], 1):
+                print(f"\n--- 仓库 {i} ---")
+                print(f"名称: {repo['full_name']}")
+                print(f"描述: {repo['description']}")
+                print(f"星标数: {repo['stargazers_count']}")
+                print(f"Fork数: {repo['forks_count']}")
+                print(f"最近更新: {repo['updated_at']}")
+                print(f"URL: {repo['html_url']}")
+
+        # 示例2：获取特定仓库的详情
+        print("\n=== 示例2：获取特定仓库的详情 ===")
+        repo_details = await github.get_repo("microsoft", "vscode")
+        if repo_details:
+            print(f"名称: {repo_details['full_name']}")
+            print(f"描述: {repo_details['description']}")
+            print(f"星标数: {repo_details['stargazers_count']}")
+            print(f"Fork数: {repo_details['forks_count']}")
+            print(f"默认分支: {repo_details['default_branch']}")
+            print(f"开源许可: {repo_details.get('license', {}).get('name', '无')}")
+            print(f"语言: {repo_details['language']}")
+            print(f"Open Issues数: {repo_details['open_issues_count']}")
+
+        # 示例3：获取仓库的提交历史
+        print("\n=== 示例3：获取仓库的最近提交 ===")
+        commits = await github.get_repo_commits("tensorflow", "tensorflow", per_page=5)
+        if commits:
+            for i, commit in enumerate(commits, 1):
+                print(f"\n--- 提交 {i} ---")
+                print(f"SHA: {commit['sha'][:7]}")
+                print(f"作者: {commit['commit']['author']['name']}")
+                print(f"日期: {commit['commit']['author']['date']}")
+                print(f"消息: {commit['commit']['message'].splitlines()[0]}")
+
+        # 示例4：搜索代码
+        print("\n=== 示例4：搜索代码 ===")
+        code_results = await github.search_code(
+            query="filename:README.md language:markdown pytorch in:file",
+            per_page=3
+        )
+        if code_results and "items" in code_results:
+            print(f"共找到: {code_results['total_count']} 个结果")
+            for i, item in enumerate(code_results["items"], 1):
+                print(f"\n--- 代码 {i} ---")
+                print(f"仓库: {item['repository']['full_name']}")
+                print(f"文件: {item['path']}")
+                print(f"URL: {item['html_url']}")
+
+        # 示例5：获取文件内容
+        print("\n=== 示例5：获取文件内容 ===")
+        file_content = await github.get_file_content("python", "cpython", "README.rst")
+        if file_content and "decoded_content" in file_content:
+            content = file_content["decoded_content"]
+            print(f"文件名: {file_content['name']}")
+            print(f"大小: {file_content['size']} 字节")
+            print(f"内容预览: {content[:200]}...")
+
+        # 示例6：获取仓库使用的编程语言
+        print("\n=== 示例6：获取仓库使用的编程语言 ===")
+        languages = await github.get_repository_languages("facebook", "react")
+        if languages:
+            print(f"React仓库使用的编程语言:")
+            for lang, bytes_of_code in languages.items():
+                print(f"- {lang}: {bytes_of_code} 字节")
+
+        # 示例7：获取组织信息
+        print("\n=== 示例7：获取组织信息 ===")
+        org_info = await github.get_organization("google")
+        if org_info:
+            print(f"名称: {org_info['name']}")
+            print(f"描述: {org_info.get('description', '无')}")
+            print(f"位置: {org_info.get('location', '未指定')}")
+            print(f"公共仓库数: {org_info['public_repos']}")
+            print(f"成员数: {org_info.get('public_members', 0)}")
+            print(f"URL: {org_info['html_url']}")
+
+        # 示例8：获取用户信息
+        print("\n=== 示例8：获取用户信息 ===")
+        user_info = await github.get_user("torvalds")
+        if user_info:
+            print(f"名称: {user_info['name']}")
+            print(f"公司: {user_info.get('company', '无')}")
+            print(f"博客: {user_info.get('blog', '无')}")
+            print(f"位置: {user_info.get('location', '未指定')}")
+            print(f"公共仓库数: {user_info['public_repos']}")
+            print(f"关注者数: {user_info['followers']}")
+            print(f"URL: {user_info['html_url']}")
+
+    except Exception as e:
+        print(f"发生错误: {str(e)}")
+        import traceback
+        print(traceback.format_exc())
+
+if __name__ == "__main__":
+    import asyncio
+
+    # 运行示例
+    asyncio.run(example_usage())
--- a/crazy_functions/paper_fns/document_structure_extractor.py
+++ b/crazy_functions/paper_fns/document_structure_extractor.py
@@ -0,0 +1,593 @@
+from typing import List, Dict, Optional, Tuple, Union, Any
+from dataclasses import dataclass, field
+import os
+import re
+import logging
+
+from crazy_functions.doc_fns.read_fns.unstructured_all.paper_structure_extractor import (
+    PaperStructureExtractor, PaperSection, StructuredPaper
+)
+from unstructured.partition.auto import partition
+from unstructured.documents.elements import (
+    Text, Title, NarrativeText, ListItem, Table,
+    Footer, Header, PageBreak, Image, Address
+)
+
+@dataclass
+class DocumentSection:
+    """通用文档章节数据类"""
+    title: str  # 章节标题，如果没有标题则为空字符串
+    content: str  # 章节内容
+    level: int = 0  # 标题级别，0为主标题，1为一级标题，以此类推
+    section_type: str = "content"  # 章节类型
+    is_heading_only: bool = False  # 是否仅包含标题
+    subsections: List['DocumentSection'] = field(default_factory=list)  # 子章节列表
+
+
+@dataclass
+class StructuredDocument:
+    """结构化文档数据类"""
+    title: str = ""  # 文档标题
+    metadata: Dict[str, Any] = field(default_factory=dict)  # 元数据
+    sections: List[DocumentSection] = field(default_factory=list)  # 章节列表
+    full_text: str = ""  # 完整文本
+    is_paper: bool = False  # 是否为学术论文
+
+
+class GenericDocumentStructureExtractor:
+    """通用文档结构提取器
+    
+    可以从各种文档格式中提取结构信息，包括标题和内容。
+    支持论文、报告、文章和一般文本文档。
+    """
+    
+    # 支持的文件扩展名
+    SUPPORTED_EXTENSIONS = [
+        '.pdf', '.docx', '.doc', '.pptx', '.ppt', 
+        '.txt', '.md', '.html', '.htm', '.xml',
+        '.rtf', '.odt', '.epub', '.msg', '.eml'
+    ]
+    
+    # 常见的标题前缀模式
+    HEADING_PATTERNS = [
+        # 数字标题 (1., 1.1., etc.)
+        r'^\s*(\d+\.)+\s+',
+        # 中文数字标题 (一、, 二、, etc.)
+        r'^\s*[一二三四五六七八九十]+[、：:]\s+',
+        # 带括号的数字标题 ((1), (2), etc.)
+        r'^\s*\(\s*\d+\s*\)\s+',
+        # 特定标记的标题 (Chapter 1, Section 1, etc.)
+        r'^\s*(chapter|section|part|附录|章|节)\s+\d+[\.:：]\s+',
+    ]
+    
+    # 常见的文档分段标记词
+    SECTION_MARKERS = {
+        'introduction': ['简介', '导言', '引言', 'introduction', '概述', 'overview'],
+        'background': ['背景', '现状', 'background', '理论基础', '相关工作'],
+        'main_content': ['主要内容', '正文', 'main content', '分析', '讨论'],
+        'conclusion': ['结论', '总结', 'conclusion', '结语', '小结', 'summary'],
+        'reference': ['参考', '参考文献', 'references', '文献', 'bibliography'],
+        'appendix': ['附录', 'appendix', '补充资料', 'supplementary']
+    }
+    
+    def __init__(self):
+        """初始化提取器"""
+        self.paper_extractor = PaperStructureExtractor()  # 论文专用提取器
+        self._setup_logging()
+        
+    def _setup_logging(self):
+        """配置日志"""
+        logging.basicConfig(
+            level=logging.INFO,
+            format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+        )
+        self.logger = logging.getLogger(__name__)
+        
+    def extract_document_structure(self, file_path: str, strategy: str = "fast") -> StructuredDocument:
+        """提取文档结构
+        
+        Args:
+            file_path: 文件路径
+            strategy: 提取策略 ("fast" 或 "accurate")
+            
+        Returns:
+            StructuredDocument: 结构化文档对象
+        """
+        try:
+            self.logger.info(f"正在处理文档结构: {file_path}")
+            
+            # 1. 首先尝试使用论文提取器
+            try:
+                paper_result = self.paper_extractor.extract_paper_structure(file_path)
+                if paper_result and len(paper_result.sections) > 2:  # 如果成功识别为论文结构
+                    self.logger.info(f"成功识别为学术论文: {file_path}")
+                    # 将论文结构转换为通用文档结构
+                    return self._convert_paper_to_document(paper_result)
+            except Exception as e:
+                self.logger.debug(f"论文结构提取失败，将尝试通用提取: {str(e)}")
+            
+            # 2. 使用通用方法提取文档结构
+            elements = partition(
+                str(file_path),
+                strategy=strategy,
+                include_metadata=True,
+                nlp=False
+            )
+            
+            # 3. 使用通用提取器处理
+            doc = self._extract_generic_structure(elements)
+            return doc
+            
+        except Exception as e:
+            self.logger.error(f"文档结构提取失败: {str(e)}")
+            # 返回一个空的结构化文档
+            return StructuredDocument(
+                title="未能提取文档标题",
+                sections=[DocumentSection(
+                    title="", 
+                    content="", 
+                    level=0, 
+                    section_type="content"
+                )]
+            )
+    
+    def _convert_paper_to_document(self, paper: StructuredPaper) -> StructuredDocument:
+        """将论文结构转换为通用文档结构
+        
+        Args:
+            paper: 结构化论文对象
+            
+        Returns:
+            StructuredDocument: 转换后的通用文档结构
+        """
+        doc = StructuredDocument(
+            title=paper.metadata.title,
+            is_paper=True,
+            full_text=paper.full_text
+        )
+        
+        # 转换元数据
+        doc.metadata = {
+            'title': paper.metadata.title,
+            'authors': paper.metadata.authors,
+            'keywords': paper.keywords,
+            'abstract': paper.metadata.abstract if hasattr(paper.metadata, 'abstract') else "",
+            'is_paper': True
+        }
+        
+        # 转换章节结构
+        doc.sections = self._convert_paper_sections(paper.sections)
+        
+        return doc
+    
+    def _convert_paper_sections(self, paper_sections: List[PaperSection], level: int = 0) -> List[DocumentSection]:
+        """递归转换论文章节为通用文档章节
+        
+        Args:
+            paper_sections: 论文章节列表
+            level: 当前章节级别
+            
+        Returns:
+            List[DocumentSection]: 通用文档章节列表
+        """
+        doc_sections = []
+        
+        for section in paper_sections:
+            doc_section = DocumentSection(
+                title=section.title,
+                content=section.content,
+                level=section.level,
+                section_type=section.section_type,
+                is_heading_only=False if section.content else True
+            )
+            
+            # 递归处理子章节
+            if section.subsections:
+                doc_section.subsections = self._convert_paper_sections(
+                    section.subsections, level + 1
+                )
+                
+            doc_sections.append(doc_section)
+            
+        return doc_sections
+    
+    def _extract_generic_structure(self, elements) -> StructuredDocument:
+        """从元素列表中提取通用文档结构
+        
+        Args:
+            elements: 文档元素列表
+            
+        Returns:
+            StructuredDocument: 结构化文档对象
+        """
+        # 创建结构化文档对象
+        doc = StructuredDocument(full_text="")
+        
+        # 1. 提取文档标题
+        title_candidates = []
+        for i, element in enumerate(elements[:5]):  # 只检查前5个元素
+            if isinstance(element, Title):
+                title_text = str(element).strip()
+                title_candidates.append((i, title_text))
+                
+        if title_candidates:
+            # 使用第一个标题作为文档标题
+            doc.title = title_candidates[0][1]
+        
+        # 2. 识别所有标题元素和内容
+        title_elements = []
+        
+        # 2.1 首先识别所有标题
+        for i, element in enumerate(elements):
+            is_heading = False
+            title_text = ""
+            level = 0
+            
+            # 检查元素类型
+            if isinstance(element, Title):
+                is_heading = True
+                title_text = str(element).strip()
+                
+                # 进一步检查是否为真正的标题
+                if self._is_likely_heading(title_text, element, i, elements):
+                    level = self._estimate_heading_level(title_text, element)
+                else:
+                    is_heading = False
+            
+            # 也检查格式像标题的普通文本
+            elif isinstance(element, (Text, NarrativeText)) and i > 0:
+                text = str(element).strip()
+                # 检查是否匹配标题模式
+                if any(re.match(pattern, text) for pattern in self.HEADING_PATTERNS):
+                    # 检查长度和后续内容以确认是否为标题
+                    if len(text) < 100 and self._has_sufficient_following_content(i, elements):
+                        is_heading = True
+                        title_text = text
+                        level = self._estimate_heading_level(title_text, element)
+            
+            if is_heading:
+                section_type = self._identify_section_type(title_text)
+                title_elements.append((i, title_text, level, section_type))
+        
+        # 2.2 为每个标题提取内容
+        sections = []
+        
+        for i, (index, title_text, level, section_type) in enumerate(title_elements):
+            # 确定内容范围
+            content_start = index + 1
+            content_end = elements[-1]  # 默认到文档结束
+            
+            # 如果有下一个标题，内容到下一个标题开始
+            if i < len(title_elements) - 1:
+                content_end = title_elements[i+1][0]
+            else:
+                content_end = len(elements)
+            
+            # 提取内容
+            content = self._extract_content_between(elements, content_start, content_end)
+            
+            # 创建章节
+            section = DocumentSection(
+                title=title_text,
+                content=content,
+                level=level,
+                section_type=section_type,
+                is_heading_only=False if content.strip() else True
+            )
+            
+            sections.append(section)
+        
+        # 3. 如果没有识别到任何章节，创建一个默认章节
+        if not sections:
+            all_content = self._extract_content_between(elements, 0, len(elements))
+            
+            # 尝试从内容中提取标题
+            first_line = all_content.split('\n')[0] if all_content else ""
+            if first_line and len(first_line) < 100:
+                doc.title = first_line
+                all_content = '\n'.join(all_content.split('\n')[1:])
+            
+            default_section = DocumentSection(
+                title="",
+                content=all_content,
+                level=0,
+                section_type="content"
+            )
+            sections.append(default_section)
+        
+        # 4. 构建层次结构
+        doc.sections = self._build_section_hierarchy(sections)
+        
+        # 5. 提取完整文本
+        doc.full_text = "\n\n".join([str(element) for element in elements if isinstance(element, (Text, NarrativeText, Title, ListItem))])
+        
+        return doc
+    
+    def _build_section_hierarchy(self, sections: List[DocumentSection]) -> List[DocumentSection]:
+        """构建章节层次结构
+        
+        Args:
+            sections: 章节列表
+            
+        Returns:
+            List[DocumentSection]: 具有层次结构的章节列表
+        """
+        if not sections:
+            return []
+        
+        # 按层级排序
+        top_level_sections = []
+        current_parents = {0: None}  # 每个层级的当前父节点
+        
+        for section in sections:
+            # 找到当前节点的父节点
+            parent_level = None
+            for level in sorted([k for k in current_parents.keys() if k < section.level], reverse=True):
+                parent_level = level
+                break
+            
+            if parent_level is None:
+                # 顶级章节
+                top_level_sections.append(section)
+            else:
+                # 子章节
+                parent = current_parents[parent_level]
+                if parent:
+                    parent.subsections.append(section)
+                else:
+                    top_level_sections.append(section)
+            
+            # 更新当前层级的父节点
+            current_parents[section.level] = section
+            
+            # 清除所有更深层级的父节点缓存
+            deeper_levels = [k for k in current_parents.keys() if k > section.level]
+            for level in deeper_levels:
+                current_parents.pop(level, None)
+        
+        return top_level_sections
+    
+    def _is_likely_heading(self, text: str, element, index: int, elements) -> bool:
+        """判断文本是否可能是标题
+        
+        Args:
+            text: 文本内容
+            element: 元素对象
+            index: 元素索引
+            elements: 所有元素列表
+            
+        Returns:
+            bool: 是否可能是标题
+        """
+        # 1. 检查文本长度 - 标题通常不会太长
+        if len(text) > 150:  # 标题通常不超过150个字符
+            return False
+            
+        # 2. 检查是否匹配标题的数字编号模式
+        if any(re.match(pattern, text) for pattern in self.HEADING_PATTERNS):
+            return True
+            
+        # 3. 检查是否包含常见章节标记词
+        lower_text = text.lower()
+        for markers in self.SECTION_MARKERS.values():
+            if any(marker.lower() in lower_text for marker in markers):
+                return True
+        
+        # 4. 检查后续内容数量 - 标题后通常有足够多的内容
+        if not self._has_sufficient_following_content(index, elements, min_chars=100):
+            # 但如果文本很短且以特定格式开头，仍可能是标题
+            if len(text) < 50 and (text.endswith(':') or text.endswith('：')):
+                return True
+            return False
+                
+        # 5. 检查格式特征
+        # 标题通常是元素的开头，不在段落中间
+        if len(text.split('\n')) > 1:
+            # 多行文本不太可能是标题
+            return False
+            
+        # 如果有元数据，检查字体特征（字体大小等）
+        if hasattr(element, 'metadata') and element.metadata:
+            try:
+                font_size = getattr(element.metadata, 'font_size', None)
+                is_bold = getattr(element.metadata, 'is_bold', False)
+                
+                # 字体较大或加粗的文本更可能是标题
+                if font_size and font_size > 12:
+                    return True
+                if is_bold:
+                    return True
+            except (AttributeError, TypeError):
+                pass
+        
+        # 默认返回True，因为元素已被识别为Title类型
+        return True
+    
+    def _estimate_heading_level(self, text: str, element) -> int:
+        """估计标题的层级
+        
+        Args:
+            text: 标题文本
+            element: 元素对象
+            
+        Returns:
+            int: 标题层级 (0为主标题，1为一级标题, 等等)
+        """
+        # 1. 通过编号模式判断层级
+        for pattern, level in [
+            (r'^\s*\d+\.\s+', 1),  # 1. 开头 (一级标题)
+            (r'^\s*\d+\.\d+\.\s+', 2),  # 1.1. 开头 (二级标题)
+            (r'^\s*\d+\.\d+\.\d+\.\s+', 3),  # 1.1.1. 开头 (三级标题)
+            (r'^\s*\d+\.\d+\.\d+\.\d+\.\s+', 4),  # 1.1.1.1. 开头 (四级标题)
+        ]:
+            if re.match(pattern, text):
+                return level
+                
+        # 2. 检查是否是常见的主要章节标题
+        lower_text = text.lower()
+        main_sections = [
+            'abstract', 'introduction', 'background', 'methodology', 
+            'results', 'discussion', 'conclusion', 'references'
+        ]
+        for section in main_sections:
+            if section in lower_text:
+                return 1  # 主要章节为一级标题
+        
+        # 3. 根据文本特征判断
+        if text.isupper():  # 全大写文本可能是章标题
+            return 1
+        
+        # 4. 通过元数据判断层级
+        if hasattr(element, 'metadata') and element.metadata:
+            try:
+                # 根据字体大小判断层级
+                font_size = getattr(element.metadata, 'font_size', None)
+                if font_size is not None:
+                    if font_size > 18:  # 假设主标题字体最大
+                        return 0
+                    elif font_size > 16:
+                        return 1
+                    elif font_size > 14:
+                        return 2
+                    else:
+                        return 3
+            except (AttributeError, TypeError):
+                pass
+        
+        # 默认为二级标题
+        return 2
+    
+    def _identify_section_type(self, title_text: str) -> str:
+        """识别章节类型，包括参考文献部分"""
+        lower_text = title_text.lower()
+        
+        # 特别检查是否为参考文献部分
+        references_patterns = [
+            r'references', r'参考文献', r'bibliography', r'引用文献', 
+            r'literature cited', r'^cited\s+literature', r'^文献$', r'^引用$'
+        ]
+        
+        for pattern in references_patterns:
+            if re.search(pattern, lower_text, re.IGNORECASE):
+                return "references"
+        
+        # 检查是否匹配其他常见章节类型
+        for section_type, markers in self.SECTION_MARKERS.items():
+            if any(marker.lower() in lower_text for marker in markers):
+                return section_type
+        
+        # 检查带编号的章节
+        if re.match(r'^\d+\.', lower_text):
+            return "content"
+            
+        # 默认为内容章节
+        return "content"
+    
+    def _has_sufficient_following_content(self, index: int, elements, min_chars: int = 150) -> bool:
+        """检查元素后是否有足够的内容
+        
+        Args:
+            index: 当前元素索引
+            elements: 所有元素列表
+            min_chars: 最小字符数要求
+            
+        Returns:
+            bool: 是否有足够的内容
+        """
+        total_chars = 0
+        for i in range(index + 1, min(index + 5, len(elements))):
+            if isinstance(elements[i], Title):
+                # 如果紧接着是标题，就停止检查
+                break
+            if isinstance(elements[i], (Text, NarrativeText, ListItem, Table)):
+                total_chars += len(str(elements[i]))
+                if total_chars >= min_chars:
+                    return True
+        
+        return total_chars >= min_chars
+    
+    def _extract_content_between(self, elements, start_index: int, end_index: int) -> str:
+        """提取指定范围内的内容文本
+        
+        Args:
+            elements: 元素列表
+            start_index: 开始索引
+            end_index: 结束索引
+            
+        Returns:
+            str: 提取的内容文本
+        """
+        content_parts = []
+        
+        for i in range(start_index, end_index):
+            if isinstance(elements[i], (Text, NarrativeText, ListItem, Table)):
+                content_parts.append(str(elements[i]).strip())
+        
+        return "\n\n".join([part for part in content_parts if part])
+    
+    def generate_markdown(self, doc: StructuredDocument) -> str:
+        """将结构化文档转换为Markdown格式
+        
+        Args:
+            doc: 结构化文档对象
+            
+        Returns:
+            str: Markdown格式文本
+        """
+        md_parts = []
+        
+        # 添加标题
+        if doc.title:
+            md_parts.append(f"# {doc.title}\n")
+        
+        # 添加元数据
+        if doc.is_paper:
+            # 作者信息
+            if 'authors' in doc.metadata and doc.metadata['authors']:
+                authors_str = ", ".join(doc.metadata['authors'])
+                md_parts.append(f"**作者:** {authors_str}\n")
+            
+            # 关键词
+            if 'keywords' in doc.metadata and doc.metadata['keywords']:
+                keywords_str = ", ".join(doc.metadata['keywords'])
+                md_parts.append(f"**关键词:** {keywords_str}\n")
+            
+            # 摘要
+            if 'abstract' in doc.metadata and doc.metadata['abstract']:
+                md_parts.append(f"## 摘要\n\n{doc.metadata['abstract']}\n")
+        
+        # 添加章节内容
+        md_parts.append(self._format_sections_markdown(doc.sections))
+        
+        return "\n".join(md_parts)
+    
+    def _format_sections_markdown(self, sections: List[DocumentSection], base_level: int = 0) -> str:
+        """递归格式化章节为Markdown
+        
+        Args:
+            sections: 章节列表
+            base_level: 基础层级
+            
+        Returns:
+            str: Markdown格式文本
+        """
+        md_parts = []
+        
+        for section in sections:
+            # 计算标题级别 (确保不超过6级)
+            header_level = min(section.level + base_level + 1, 6)
+            
+            # 添加标题和内容
+            if section.title:
+                md_parts.append(f"{'#' * header_level} {section.title}\n")
+            
+            if section.content:
+                md_parts.append(f"{section.content}\n")
+            
+            # 递归处理子章节
+            if section.subsections:
+                md_parts.append(self._format_sections_markdown(
+                    section.subsections, base_level
+                ))
+        
+        return "\n".join(md_parts) 
--- a/crazy_functions/paper_fns/file2file_doc/init.py
+++ b/crazy_functions/paper_fns/file2file_doc/init.py
@@ -0,0 +1,4 @@
+from .txt_doc import TxtFormatter
+from .markdown_doc import MarkdownFormatter
+from .html_doc import HtmlFormatter
+from .word_doc import WordFormatter
--- a/crazy_functions/paper_fns/file2file_doc/html_doc.py
+++ b/crazy_functions/paper_fns/file2file_doc/html_doc.py
@@ -0,0 +1,300 @@
+class HtmlFormatter:
+    """HTML格式文档生成器 - 保留原始文档结构"""
+    
+    def __init__(self, processing_type="文本处理"):
+        self.processing_type = processing_type
+        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); }
+        }
+        
+        .container {
+            animation: fadeIn 0.6s ease-out;
+        }
+        
+        .document-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);
+        }
+
+        .document-body {
+            display: flex;
+            flex-direction: column;
+            gap: 1.5rem;
+            margin: 2rem 0;
+        }
+        
+        .document-header {
+            display: flex;
+            flex-direction: column;
+            align-items: center;
+            margin-bottom: 2rem;
+        }
+        
+        .processing-type {
+            color: var(--secondary-color);
+            font-size: 1.2em;
+            margin: 0.5rem 0;
+        }
+        
+        .processing-date {
+            color: var(--text-color);
+            font-size: 0.9em;
+            opacity: 0.8;
+        }
+        
+        .document-content {
+            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);
+        }
+
+        /* 保留文档结构的样式 */
+        h1, h2, h3, h4, h5, h6 {
+            color: var(--secondary-color);
+            margin-top: 1.5em;
+            margin-bottom: 0.5em;
+        }
+        
+        h1 { font-size: 1.8em; }
+        h2 { font-size: 1.5em; }
+        h3 { font-size: 1.3em; }
+        h4 { font-size: 1.1em; }
+        
+        p {
+            margin: 0.8em 0;
+        }
+        
+        ul, ol {
+            margin: 1em 0;
+            padding-left: 2em;
+        }
+        
+        li {
+            margin: 0.5em 0;
+        }
+        
+        blockquote {
+            margin: 1em 0;
+            padding: 0.5em 1em;
+            border-left: 4px solid var(--primary-light);
+            background: rgba(0,0,0,0.02);
+        }
+        
+        code {
+            font-family: monospace;
+            background: rgba(0,0,0,0.05);
+            padding: 0.2em 0.4em;
+            border-radius: 3px;
+        }
+        
+        pre {
+            background: rgba(0,0,0,0.05);
+            padding: 1em;
+            border-radius: 5px;
+            overflow-x: auto;
+        }
+        
+        pre code {
+            background: transparent;
+            padding: 0;
+        }
+
+        @media (prefers-color-scheme: dark) {
+            :root {
+                --background-color: #0f172a;
+                --text-color: #e2e8f0;
+                --border-color: #1e293b;
+            }
+            
+            .container, .document-content {
+                background: #1e293b;
+            }
+            
+            blockquote {
+                background: rgba(255,255,255,0.05);
+            }
+            
+            code, pre {
+                background: rgba(255,255,255,0.05);
+            }
+        }
+        """
+
+    def _escape_html(self, text):
+        """转义HTML特殊字符"""
+        import html
+        return html.escape(text)
+    
+    def _markdown_to_html(self, text):
+        """将Markdown格式转换为HTML格式，保留文档结构"""
+        try:
+            import markdown
+            # 使用Python-Markdown库将markdown转换为HTML，启用更多扩展以支持嵌套列表
+            return markdown.markdown(text, extensions=['tables', 'fenced_code', 'codehilite', 'nl2br', 'sane_lists', 'smarty', 'extra'])
+        except ImportError:
+            # 如果没有markdown库，使用更复杂的替换来处理嵌套列表
+            import re
+            
+            # 替换标题
+            text = re.sub(r'^# (.+)$', r'<h1>\1</h1>', text, flags=re.MULTILINE)
+            text = re.sub(r'^## (.+)$', r'<h2>\1</h2>', text, flags=re.MULTILINE)
+            text = re.sub(r'^### (.+)$', r'<h3>\1</h3>', text, flags=re.MULTILINE)
+            
+            # 预处理列表 - 在列表项之间添加空行以正确分隔
+            # 处理编号列表
+            text = re.sub(r'(\n\d+\.\s.+)(\n\d+\.\s)', r'\1\n\2', text)
+            # 处理项目符号列表
+            text = re.sub(r'(\n•\s.+)(\n•\s)', r'\1\n\2', text)
+            text = re.sub(r'(\n\*\s.+)(\n\*\s)', r'\1\n\2', text)
+            text = re.sub(r'(\n-\s.+)(\n-\s)', r'\1\n\2', text)
+            
+            # 处理嵌套列表 - 确保正确的缩进和结构
+            lines = text.split('\n')
+            in_list = False
+            list_type = None  # 'ol' 或 'ul'
+            list_html = []
+            normal_lines = []
+            
+            i = 0
+            while i < len(lines):
+                line = lines[i]
+                
+                # 匹配编号列表项
+                numbered_match = re.match(r'^(\d+)\.\s+(.+)$', line)
+                # 匹配项目符号列表项
+                bullet_match = re.match(r'^[•\*-]\s+(.+)$', line)
+                
+                if numbered_match:
+                    if not in_list or list_type != 'ol':
+                        # 开始新的编号列表
+                        if in_list:
+                            # 关闭前一个列表
+                            list_html.append(f'</{list_type}>')
+                        list_html.append('<ol>')
+                        in_list = True
+                        list_type = 'ol'
+                    
+                    num, content = numbered_match.groups()
+                    list_html.append(f'<li>{content}</li>')
+                    
+                elif bullet_match:
+                    if not in_list or list_type != 'ul':
+                        # 开始新的项目符号列表
+                        if in_list:
+                            # 关闭前一个列表
+                            list_html.append(f'</{list_type}>')
+                        list_html.append('<ul>')
+                        in_list = True
+                        list_type = 'ul'
+                    
+                    content = bullet_match.group(1)
+                    list_html.append(f'<li>{content}</li>')
+                    
+                else:
+                    if in_list:
+                        # 结束当前列表
+                        list_html.append(f'</{list_type}>')
+                        in_list = False
+                        # 将完成的列表添加到正常行中
+                        normal_lines.append(''.join(list_html))
+                        list_html = []
+                    
+                    normal_lines.append(line)
+                
+                i += 1
+            
+            # 如果最后还在列表中，确保关闭列表
+            if in_list:
+                list_html.append(f'</{list_type}>')
+                normal_lines.append(''.join(list_html))
+            
+            # 重建文本
+            text = '\n'.join(normal_lines)
+            
+            # 替换段落，但避免处理已经是HTML标签的部分
+            paragraphs = text.split('\n\n')
+            for i, p in enumerate(paragraphs):
+                # 如果不是以HTML标签开始且不为空
+                if not (p.strip().startswith('<') and p.strip().endswith('>')) and p.strip() != '':
+                    paragraphs[i] = f'<p>{p}</p>'
+            
+            return '\n'.join(paragraphs)
+
+    def create_document(self, content: str) -> str:
+        """生成完整的HTML文档，保留原始文档结构
+        
+        Args:
+            content: 处理后的文档内容
+            
+        Returns:
+            str: 完整的HTML文档字符串
+        """
+        from datetime import datetime
+        
+        # 将markdown内容转换为HTML
+        html_content = self._markdown_to_html(content)
+        
+        return f"""
+        <!DOCTYPE html>
+        <html lang="zh-CN">
+        <head>
+            <meta charset="utf-8">
+            <meta name="viewport" content="width=device-width, initial-scale=1">
+            <title>文档处理结果</title>
+            <style>{self.css_styles}</style>
+        </head>
+        <body>
+            <div class="container">
+                <h1 class="document-title">文档处理结果</h1>
+                
+                <div class="document-header">
+                    <div class="processing-type">处理方式: {self._escape_html(self.processing_type)}</div>
+                    <div class="processing-date">处理时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}</div>
+                </div>
+                
+                <div class="document-content">
+                    {html_content}
+                </div>
+            </div>
+        </body>
+        </html>
+        """
--- a/crazy_functions/paper_fns/file2file_doc/markdown_doc.py
+++ b/crazy_functions/paper_fns/file2file_doc/markdown_doc.py
@@ -0,0 +1,40 @@
+class MarkdownFormatter:
+    """Markdown格式文档生成器 - 保留原始文档结构"""
+
+    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, content: str, processing_type: str = "文本处理") -> str:
+        """
+        创建完整的Markdown文档，保留原始文档结构
+        Args:
+            content: 处理后的文档内容
+            processing_type: 处理类型（润色、翻译等）
+        Returns:
+            str: 生成的Markdown文本
+        """
+        self.content = []
+        
+        # 添加标题和说明
+        self.content.append(f"# 文档处理结果\n")
+        self.content.append(f"## 处理方式: {processing_type}\n")
+        
+        # 添加处理时间
+        from datetime import datetime
+        self.content.append(f"*处理时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}*\n")
+        
+        # 添加分隔线
+        self.content.append("---\n")
+        
+        # 添加原始内容，保留结构
+        self.content.append(content)
+            
+        # 添加结尾分隔线
+        self.content.append("\n---\n")
+
+        return "\n".join(self.content)
--- a/crazy_functions/paper_fns/file2file_doc/txt_doc.py
+++ b/crazy_functions/paper_fns/file2file_doc/txt_doc.py
@@ -0,0 +1,69 @@
+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:
+    """文本格式化器 - 保留原始文档结构"""
+
+    def __init__(self):
+        self.content = []
+        self._setup_document()
+
+    def _setup_document(self):
+        """初始化文档标题"""
+        self.content.append("=" * 50)
+        self.content.append("处理后文档".center(48))
+        self.content.append("=" * 50)
+
+    def _format_header(self):
+        """创建文档头部信息"""
+        from datetime import datetime
+        date_str = datetime.now().strftime('%Y年%m月%d日')
+        return [
+            date_str.center(48),
+            "\n"  # 添加空行
+        ]
+
+    def create_document(self, content):
+        """生成保留原始结构的文档"""
+        # 添加头部信息
+        self.content.extend(self._format_header())
+        
+        # 处理内容，保留原始结构
+        processed_content = convert_markdown_to_txt(content)
+        
+        # 添加处理后的内容
+        self.content.append(processed_content)
+        
+        # 合并所有内容
+        return "\n".join(self.content)
--- a/crazy_functions/paper_fns/file2file_doc/word2pdf.py
+++ b/crazy_functions/paper_fns/file2file_doc/word2pdf.py
@@ -0,0 +1,125 @@
+from docx2pdf import convert
+import os
+import platform
+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
+                if not os.system('which libreoffice') == 0:
+                    raise RuntimeError("请先安装LibreOffice: sudo apt-get install libreoffice")
+                
+                # 使用libreoffice进行转换
+                os.system(f'libreoffice --headless --convert-to pdf "{word_path}" --outdir "{pdf_path.parent}"')
+                
+                # 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:
+                    os.rename(default_pdf, pdf_path)
+            else:
+                # Windows和MacOS使用docx2pdf
+                convert(word_path, pdf_path)
+            
+            return str(pdf_path)
+            
+        except Exception as 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)}") 
--- a/crazy_functions/paper_fns/file2file_doc/word_doc.py
+++ b/crazy_functions/paper_fns/file2file_doc/word_doc.py
@@ -0,0 +1,236 @@
+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:
+    """文档Word格式化器 - 保留原始文档结构"""
+
+    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("文档处理结果")
+            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)
+
+        # 创建标题样式
+        title_style = self.doc.styles.add_style('Title_Custom', WD_STYLE_TYPE.PARAGRAPH)
+        title_style.font.name = '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
+
+        # 创建标题1样式
+        h1_style = self.doc.styles.add_style('Heading1_Custom', WD_STYLE_TYPE.PARAGRAPH)
+        h1_style.font.name = '黑体'
+        h1_style._element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
+        h1_style.font.size = Pt(18)
+        h1_style.font.bold = True
+        h1_style.paragraph_format.space_before = Pt(12)
+        h1_style.paragraph_format.space_after = Pt(6)
+
+        # 创建标题2样式
+        h2_style = self.doc.styles.add_style('Heading2_Custom', WD_STYLE_TYPE.PARAGRAPH)
+        h2_style.font.name = '黑体'
+        h2_style._element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
+        h2_style.font.size = Pt(16)
+        h2_style.font.bold = True
+        h2_style.paragraph_format.space_before = Pt(10)
+        h2_style.paragraph_format.space_after = Pt(6)
+
+        # 创建标题3样式
+        h3_style = self.doc.styles.add_style('Heading3_Custom', WD_STYLE_TYPE.PARAGRAPH)
+        h3_style.font.name = '黑体'
+        h3_style._element.rPr.rFonts.set(qn('w:eastAsia'), '黑体')
+        h3_style.font.size = Pt(14)
+        h3_style.font.bold = True
+        h3_style.paragraph_format.space_before = Pt(8)
+        h3_style.paragraph_format.space_after = Pt(4)
+
+        # 创建代码块样式
+        code_style = self.doc.styles.add_style('Code_Custom', WD_STYLE_TYPE.PARAGRAPH)
+        code_style.font.name = 'Courier New'
+        code_style.font.size = Pt(11)
+        code_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.SINGLE
+        code_style.paragraph_format.space_before = Pt(6)
+        code_style.paragraph_format.space_after = Pt(6)
+        code_style.paragraph_format.left_indent = Pt(36)
+        code_style.paragraph_format.right_indent = Pt(36)
+
+        # 创建列表样式
+        list_style = self.doc.styles.add_style('List_Custom', WD_STYLE_TYPE.PARAGRAPH)
+        list_style.font.name = '仿宋'
+        list_style._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
+        list_style.font.size = Pt(12)
+        list_style.paragraph_format.line_spacing_rule = WD_LINE_SPACING.ONE_POINT_FIVE
+        list_style.paragraph_format.left_indent = Pt(21)
+        list_style.paragraph_format.first_line_indent = Pt(-21)
+
+    def create_document(self, content: str, processing_type: str = "文本处理"):
+        """创建文档，保留原始结构"""
+        # 添加标题
+        title_para = self.doc.add_paragraph(style='Title_Custom')
+        title_run = title_para.add_run('文档处理结果')
+
+        # 添加处理类型
+        processing_para = self.doc.add_paragraph()
+        processing_para.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
+        processing_run = processing_para.add_run(f"处理方式: {processing_type}")
+        processing_run.font.name = '仿宋'
+        processing_run._element.rPr.rFonts.set(qn('w:eastAsia'), '仿宋')
+        processing_run.font.size = Pt(14)
+
+        # 添加日期
+        date_para = self.doc.add_paragraph()
+        date_para.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
+        date_run = date_para.add_run(f"处理时间: {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(14)
+
+        self.doc.add_paragraph()  # 添加空行
+
+        # 预处理内容，将Markdown格式转换为适合Word的格式
+        processed_content = convert_markdown_to_word(content)
+        
+        # 按行处理文本，保留结构
+        lines = processed_content.split('\n')
+        in_code_block = False
+        current_paragraph = None
+        
+        for line in lines:
+            # 检查是否为标题
+            header_match = re.match(r'^(#{1,6})\s+(.+)$', line)
+            
+            if header_match:
+                # 根据#的数量确定标题级别
+                level = len(header_match.group(1))
+                title_text = header_match.group(2)
+                
+                if level == 1:
+                    style = 'Heading1_Custom'
+                elif level == 2:
+                    style = 'Heading2_Custom'
+                else:
+                    style = 'Heading3_Custom'
+                
+                self.doc.add_paragraph(title_text, style=style)
+                current_paragraph = None
+            
+            # 检查代码块标记
+            elif '[代码块]' in line:
+                in_code_block = True
+                current_paragraph = self.doc.add_paragraph(style='Code_Custom')
+                code_line = line.replace('[代码块]', '').strip()
+                if code_line:
+                    current_paragraph.add_run(code_line)
+            
+            elif '[/代码块]' in line:
+                in_code_block = False
+                code_line = line.replace('[/代码块]', '').strip()
+                if code_line and current_paragraph:
+                    current_paragraph.add_run(code_line)
+                current_paragraph = None
+            
+            # 检查列表项
+            elif line.strip().startswith('•'):
+                p = self.doc.add_paragraph(style='List_Custom')
+                p.add_run(line.strip())
+                current_paragraph = None
+            
+            # 处理普通文本行
+            elif line.strip():
+                if in_code_block:
+                    if current_paragraph:
+                        current_paragraph.add_run('\n' + line)
+                    else:
+                        current_paragraph = self.doc.add_paragraph(line, style='Code_Custom')
+                else:
+                    if current_paragraph is None or not current_paragraph.text:
+                        current_paragraph = self.doc.add_paragraph(line, style='Normal_Custom')
+                    else:
+                        current_paragraph.add_run('\n' + line)
+            
+            # 处理空行，创建新段落
+            elif not in_code_block:
+                current_paragraph = None
+
+        return self.doc
+
--- a/crazy_functions/paper_fns/github_search.py
+++ b/crazy_functions/paper_fns/github_search.py
@@ -0,0 +1,278 @@
+from typing import List, Dict, Tuple
+import asyncio
+from dataclasses import dataclass
+from toolbox import CatchException, update_ui, promote_file_to_downloadzone, get_log_folder, get_user
+from toolbox import update_ui, CatchException, report_exception, write_history_to_file
+from crazy_functions.paper_fns.auto_git.query_analyzer import QueryAnalyzer, SearchCriteria
+from crazy_functions.paper_fns.auto_git.handlers.repo_handler import RepositoryHandler
+from crazy_functions.paper_fns.auto_git.handlers.code_handler import CodeSearchHandler
+from crazy_functions.paper_fns.auto_git.handlers.user_handler import UserSearchHandler
+from crazy_functions.paper_fns.auto_git.handlers.topic_handler import TopicHandler
+from crazy_functions.paper_fns.auto_git.sources.github_source import GitHubSource
+from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+import re
+from datetime import datetime
+import os
+import json
+from pathlib import Path
+import time
+
+# 导入格式化器
+from crazy_functions.paper_fns.file2file_doc import (
+    TxtFormatter,
+    MarkdownFormatter,
+    HtmlFormatter,
+    WordFormatter
+)
+from crazy_functions.paper_fns.file2file_doc.word2pdf import WordToPdfConverter
+
+@CatchException
+def GitHub项目智能检索(txt: str, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List,
+           history: List, system_prompt: str, user_request: str):
+    """GitHub项目智能检索主函数"""
+
+    # 初始化GitHub API调用源
+    github_source = GitHubSource(api_key=plugin_kwargs.get("github_api_key"))
+
+    # 初始化处理器
+    handlers = {
+        "repo": RepositoryHandler(github_source, llm_kwargs),
+        "code": CodeSearchHandler(github_source, llm_kwargs),
+        "user": UserSearchHandler(github_source, llm_kwargs),
+        "topic": TopicHandler(github_source, llm_kwargs),
+    }
+
+    # 分析查询意图
+    chatbot.append(["分析查询意图", "正在分析您的查询需求..."])
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    query_analyzer = QueryAnalyzer()
+    search_criteria = yield from query_analyzer.analyze_query(
+        txt, chatbot, llm_kwargs
+    )
+
+    # 根据查询类型选择处理器
+    handler = handlers.get(search_criteria.query_type)
+    if not handler:
+        handler = handlers["repo"]  # 默认使用仓库处理器
+
+    # 处理查询
+    chatbot.append(["开始搜索", f"使用{handler.__class__.__name__}处理您的请求，正在搜索GitHub..."])
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    final_prompt = asyncio.run(handler.handle(
+        criteria=search_criteria,
+        chatbot=chatbot,
+        history=history,
+        system_prompt=system_prompt,
+        llm_kwargs=llm_kwargs,
+        plugin_kwargs=plugin_kwargs
+    ))
+
+    if final_prompt:
+        # 检查是否是道歉提示
+        if "很抱歉，我们未能找到" in final_prompt:
+            chatbot.append([txt, final_prompt])
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+
+        # 在 final_prompt 末尾添加用户原始查询要求
+        final_prompt += f"""
+
+原始用户查询: "{txt}"
+
+重要提示:
+- 你的回答必须直接满足用户的原始查询要求
+- 在遵循之前指南的同时，优先回答用户明确提出的问题
+- 确保回答格式和内容与用户期望一致
+- 对于GitHub仓库需要提供链接地址, 回复中请采用以下格式的HTML链接:
+  * 对于GitHub仓库: <a href='Github_URL' target='_blank'>仓库名</a>
+- 不要生成参考列表，引用信息将另行处理
+"""
+
+        # 使用最终的prompt生成回答
+        response = yield from request_gpt_model_in_new_thread_with_ui_alive(
+            inputs=final_prompt,
+            inputs_show_user=txt,
+            llm_kwargs=llm_kwargs,
+            chatbot=chatbot,
+            history=[],
+            sys_prompt=f"你是一个熟悉GitHub生态系统的专业助手，能帮助用户找到合适的项目、代码和开发者。除非用户指定，否则请使用中文回复。"
+        )
+
+        # 1. 获取项目列表
+        repos_list = handler.ranked_repos  # 直接使用原始仓库数据
+
+        # 在新的对话中添加格式化的仓库参考列表
+        if repos_list:
+            references = ""
+            for idx, repo in enumerate(repos_list, 1):
+                # 构建仓库引用
+                stars_str = f"⭐ {repo.get('stargazers_count', 'N/A')}" if repo.get('stargazers_count') else ""
+                forks_str = f"🍴 {repo.get('forks_count', 'N/A')}" if repo.get('forks_count') else ""
+                stats = f"{stars_str} {forks_str}".strip()
+                stats = f" ({stats})" if stats else ""
+
+                language = f" [{repo.get('language', '')}]" if repo.get('language') else ""
+
+                reference = f"[{idx}] **{repo.get('name', '')}**{language}{stats}  \n"
+                reference += f"👤 {repo.get('owner', {}).get('login', 'N/A') if repo.get('owner') is not None else 'N/A'} | "
+                reference += f"📅 {repo.get('updated_at', 'N/A')[:10]} | "
+                reference += f"<a href='{repo.get('html_url', '')}' target='_blank'>GitHub</a>  \n"
+
+                if repo.get('description'):
+                    reference += f"{repo.get('description')}  \n"
+                reference += "  \n"
+
+                references += reference
+
+            # 添加新的对话显示参考仓库
+            chatbot.append(["推荐项目如下：", references])
+            yield from update_ui(chatbot=chatbot, history=history)
+
+        # 2. 保存结果到文件
+        # 创建保存目录
+        save_dir = get_log_folder(get_user(chatbot), plugin_name='github_search')
+        if not os.path.exists(save_dir):
+            os.makedirs(save_dir)
+
+        # 生成文件名
+        def get_safe_filename(txt, max_length=10):
+            # 获取文本前max_length个字符作为文件名
+            filename = txt[:max_length].strip()
+            # 移除不安全的文件名字符
+            filename = re.sub(r'[\\/:*?"<>|]', '', filename)
+            # 如果文件名为空，使用时间戳
+            if not filename:
+                filename = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
+            return filename
+
+        base_filename = get_safe_filename(txt)
+
+        # 准备保存的内容 - 优化文档结构
+        md_content = f"# GitHub搜索结果: {txt}\n\n"
+        md_content += f"搜索时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n"
+
+        # 添加模型回复
+        md_content += "## 搜索分析与总结\n\n"
+        md_content += response + "\n\n"
+
+        # 添加所有搜索到的仓库详细信息
+        md_content += "## 推荐项目详情\n\n"
+
+        if not repos_list:
+            md_content += "未找到匹配的项目\n\n"
+        else:
+            md_content += f"共找到 {len(repos_list)} 个相关项目\n\n"
+
+            # 添加项目简表
+            md_content += "### 项目一览表\n\n"
+            md_content += "| 序号 | 项目名称 | 作者 | 语言 | 星标数 | 更新时间 |\n"
+            md_content += "| ---- | -------- | ---- | ---- | ------ | -------- |\n"
+
+            for idx, repo in enumerate(repos_list, 1):
+                md_content += f"| {idx} | [{repo.get('name', '')}]({repo.get('html_url', '')}) | {repo.get('owner', {}).get('login', 'N/A') if repo.get('owner') is not None else 'N/A'} | {repo.get('language', 'N/A')} | {repo.get('stargazers_count', 'N/A')} | {repo.get('updated_at', 'N/A')[:10]} |\n"
+
+            md_content += "\n"
+
+            # 添加详细项目信息
+            md_content += "### 项目详细信息\n\n"
+            for idx, repo in enumerate(repos_list, 1):
+                md_content += f"#### {idx}. {repo.get('name', '')}\n\n"
+                md_content += f"- **仓库**: [{repo.get('full_name', '')}]({repo.get('html_url', '')})\n"
+                md_content += f"- **作者**: [{repo.get('owner', {}).get('login', '') if repo.get('owner') is not None else 'N/A'}]({repo.get('owner', {}).get('html_url', '') if repo.get('owner') is not None else '#'})\n"
+                md_content += f"- **描述**: {repo.get('description', 'N/A')}\n"
+                md_content += f"- **语言**: {repo.get('language', 'N/A')}\n"
+                md_content += f"- **星标**: {repo.get('stargazers_count', 'N/A')}\n"
+                md_content += f"- **Fork数**: {repo.get('forks_count', 'N/A')}\n"
+                md_content += f"- **最近更新**: {repo.get('updated_at', 'N/A')[:10]}\n"
+                md_content += f"- **创建时间**: {repo.get('created_at', 'N/A')[:10]}\n"
+                md_content += f"- **开源许可**: {repo.get('license', {}).get('name', 'N/A') if repo.get('license') is not None else 'N/A'}\n"
+                if repo.get('topics'):
+                    md_content += f"- **主题标签**: {', '.join(repo.get('topics', []))}\n"
+                if repo.get('homepage'):
+                    md_content += f"- **项目主页**: [{repo.get('homepage')}]({repo.get('homepage')})\n"
+                md_content += "\n"
+
+        # 添加查询信息和元数据
+        md_content += "## 查询元数据\n\n"
+        md_content += f"- **原始查询**: {txt}\n"
+        md_content += f"- **查询类型**: {search_criteria.query_type}\n"
+        md_content += f"- **关键词**: {', '.join(search_criteria.keywords) if hasattr(search_criteria, 'keywords') and search_criteria.keywords else 'N/A'}\n"
+        md_content += f"- **搜索日期**: {datetime.now().strftime('%Y-%m-%d')}\n\n"
+
+        # 保存为多种格式
+        saved_files = []
+        failed_files = []
+
+        # 1. 保存为TXT
+        try:
+            txt_formatter = TxtFormatter()
+            txt_content = txt_formatter.create_document(md_content)
+            txt_file = os.path.join(save_dir, f"github_results_{base_filename}.txt")
+            with open(txt_file, 'w', encoding='utf-8') as f:
+                f.write(txt_content)
+            promote_file_to_downloadzone(txt_file, chatbot=chatbot)
+            saved_files.append("TXT")
+        except Exception as e:
+            failed_files.append(f"TXT (错误: {str(e)})")
+
+        # 2. 保存为Markdown
+        try:
+            md_formatter = MarkdownFormatter()
+            formatted_md_content = md_formatter.create_document(md_content, "GitHub项目搜索")
+            md_file = os.path.join(save_dir, f"github_results_{base_filename}.md")
+            with open(md_file, 'w', encoding='utf-8') as f:
+                f.write(formatted_md_content)
+            promote_file_to_downloadzone(md_file, chatbot=chatbot)
+            saved_files.append("Markdown")
+        except Exception as e:
+            failed_files.append(f"Markdown (错误: {str(e)})")
+
+        # 3. 保存为HTML
+        try:
+            html_formatter = HtmlFormatter(processing_type="GitHub项目搜索")
+            html_content = html_formatter.create_document(md_content)
+            html_file = os.path.join(save_dir, f"github_results_{base_filename}.html")
+            with open(html_file, 'w', encoding='utf-8') as f:
+                f.write(html_content)
+            promote_file_to_downloadzone(html_file, chatbot=chatbot)
+            saved_files.append("HTML")
+        except Exception as e:
+            failed_files.append(f"HTML (错误: {str(e)})")
+
+        # 4. 保存为Word
+        word_file = None
+        try:
+            word_formatter = WordFormatter()
+            doc = word_formatter.create_document(md_content, "GitHub项目搜索")
+            word_file = os.path.join(save_dir, f"github_results_{base_filename}.docx")
+            doc.save(word_file)
+            promote_file_to_downloadzone(word_file, chatbot=chatbot)
+            saved_files.append("Word")
+        except Exception as e:
+            failed_files.append(f"Word (错误: {str(e)})")
+            word_file = None
+
+        # 5. 保存为PDF (仅当Word保存成功时)
+        if word_file and os.path.exists(word_file):
+            try:
+                pdf_file = WordToPdfConverter.convert_to_pdf(word_file)
+                promote_file_to_downloadzone(pdf_file, chatbot=chatbot)
+                saved_files.append("PDF")
+            except Exception as e:
+                failed_files.append(f"PDF (错误: {str(e)})")
+
+        # 报告保存结果
+        if saved_files:
+            success_message = f"成功保存以下格式: {', '.join(saved_files)}"
+            if failed_files:
+                failure_message = f"以下格式保存失败: {', '.join(failed_files)}"
+                chatbot.append(["部分格式保存成功", f"{success_message}。{failure_message}"])
+            else:
+                chatbot.append(["所有格式保存成功", success_message])
+        else:
+            chatbot.append(["保存失败", f"所有格式均保存失败: {', '.join(failed_files)}"])
+    else:
+        report_exception(chatbot, history, a=f"处理失败", b=f"请尝试其他查询")
+        yield from update_ui(chatbot=chatbot, history=history)
--- a/crazy_functions/paper_fns/journal_paper_recom.py
+++ b/crazy_functions/paper_fns/journal_paper_recom.py
@@ -0,0 +1,635 @@
+import os
+import time
+import glob
+from typing import Dict, List, Generator, Tuple
+from dataclasses import dataclass
+
+from crazy_functions.pdf_fns.text_content_loader import TextContentLoader
+from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+from toolbox import update_ui, promote_file_to_downloadzone, write_history_to_file, CatchException, report_exception
+from shared_utils.fastapi_server import validate_path_safety
+# 导入论文下载相关函数
+from crazy_functions.论文下载 import extract_paper_id, extract_paper_ids, get_arxiv_paper, format_arxiv_id, SciHub
+from pathlib import Path
+from datetime import datetime, timedelta
+import calendar
+
+
+@dataclass
+class RecommendationQuestion:
+    """期刊会议推荐分析问题类"""
+    id: str  # 问题ID
+    question: str  # 问题内容
+    importance: int  # 重要性 (1-5，5最高)
+    description: str  # 问题描述
+
+
+class JournalConferenceRecommender:
+    """论文期刊会议推荐器"""
+    
+    def __init__(self, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List, history: List, system_prompt: str):
+        """初始化推荐器"""
+        self.llm_kwargs = llm_kwargs
+        self.plugin_kwargs = plugin_kwargs
+        self.chatbot = chatbot
+        self.history = history
+        self.system_prompt = system_prompt
+        self.paper_content = ""
+        self.analysis_results = {}
+        
+        # 定义论文分析问题库（针对期刊会议推荐）
+        self.questions = [
+            RecommendationQuestion(
+                id="research_field_and_topic",
+                question="请分析这篇论文的研究领域、主题和关键词。具体包括：1)论文属于哪个主要学科领域（如自然科学、工程技术、医学、社会科学、人文学科等）；2)具体的研究子领域或方向；3)论文的核心主题和关键概念；4)重要的学术关键词和专业术语；5)研究的跨学科特征（如果有）；6)研究的地域性特征（国际性研究还是特定地区研究）。",
+                importance=5,
+                description="研究领域与主题分析"
+            ),
+            RecommendationQuestion(
+                id="methodology_and_approach",
+                question="请分析论文的研究方法和技术路线。包括：1)采用的主要研究方法（定量研究、定性研究、理论分析、实验研究、田野调查、文献综述、案例研究等）；2)使用的技术手段、工具或分析方法；3)研究设计的严谨性和创新性；4)数据收集和分析方法的适当性；5)研究方法在该学科中的先进性或传统性；6)方法学上的贡献或局限性。",
+                importance=4,
+                description="研究方法与技术路线"
+            ),
+            RecommendationQuestion(
+                id="novelty_and_contribution",
+                question="请评估论文的创新性和学术贡献。包括：1)研究的新颖性程度（理论创新、方法创新、应用创新等）；2)对现有知识体系的贡献或突破；3)解决问题的重要性和学术价值；4)研究成果的理论意义和实践价值；5)在该学科领域的地位和影响潜力；6)与国际前沿研究的关系；7)对后续研究的启发意义。",
+                importance=4,
+                description="创新性与学术贡献"
+            ),
+            RecommendationQuestion(
+                id="target_audience_and_scope",
+                question="请分析论文的目标受众和应用范围。包括：1)主要面向的学术群体（研究者、从业者、政策制定者等）；2)研究成果的潜在应用领域和受益群体；3)对学术界和实践界的价值；4)研究的国际化程度和跨文化适用性；5)是否适合国际期刊还是区域性期刊；6)语言发表偏好（英文、中文或其他语言）；7)开放获取的必要性和可行性。",
+                importance=3,
+                description="目标受众与应用范围"
+            ),
+        ]
+        
+        # 按重要性排序
+        self.questions.sort(key=lambda q: q.importance, reverse=True)
+        
+    def _load_paper(self, paper_path: str) -> Generator:
+        """加载论文内容"""
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+        
+        # 使用TextContentLoader读取文件
+        loader = TextContentLoader(self.chatbot, self.history)
+
+        yield from loader.execute_single_file(paper_path)
+        
+        # 获取加载的内容
+        if len(self.history) >= 2 and self.history[-2]:
+            self.paper_content = self.history[-2]
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return True
+        else:
+            self.chatbot.append(["错误", "无法读取论文内容，请检查文件是否有效"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return False
+            
+    def _analyze_question(self, question: RecommendationQuestion) -> Generator:
+        """分析单个问题"""
+        try:
+            # 创建分析提示
+            prompt = f"请基于以下论文内容回答问题：\n\n{self.paper_content}\n\n问题：{question.question}"
+            
+            # 使用单线程版本的请求函数
+            response = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs=prompt,
+                inputs_show_user=question.question,  # 显示问题本身
+                llm_kwargs=self.llm_kwargs,
+                chatbot=self.chatbot,
+                history=[],  # 空历史，确保每个问题独立分析
+                sys_prompt="你是一个专业的学术期刊会议推荐专家，需要仔细分析论文内容并提供准确的分析。请保持客观、专业，并基于论文内容提供深入分析。"
+            )
+            
+            if response:
+                self.analysis_results[question.id] = response
+                return True
+            return False
+            
+        except Exception as e:
+            self.chatbot.append(["错误", f"分析问题时出错: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return False
+
+    def _generate_journal_recommendations(self) -> Generator:
+        """生成期刊推荐"""
+        self.chatbot.append(["生成期刊推荐", "正在基于论文分析结果生成期刊推荐..."])
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+        
+        # 构建期刊推荐提示
+        journal_prompt = """请基于以下论文分析结果，为这篇论文推荐合适的学术期刊。
+
+推荐要求：
+1. 根据论文的创新性和工作质量，分别推荐不同级别的期刊：
+   - 顶级期刊（影响因子>8或该领域顶级期刊）：2-3个
+   - 高质量期刊（影响因子4-8或该领域知名期刊）：3-4个  
+   - 中等期刊（影响因子1.5-4或该领域认可期刊）：3-4个
+   - 入门期刊（影响因子<1.5但声誉良好的期刊）：2-3个
+
+注意：不同学科的影响因子标准差异很大，请根据论文所属学科的实际情况调整标准。
+特别是医学领域，需要考虑：
+- 临床医学期刊通常影响因子较高（顶级期刊IF>20，高质量期刊IF>10）
+- 基础医学期刊影响因子相对较低但学术价值很高
+- 专科医学期刊在各自领域内具有权威性
+- 医学期刊的临床实用性和循证医学价值
+
+2. 对每个期刊提供详细信息：
+   - 期刊全名和缩写
+   - 最新影响因子（如果知道）
+   - 期刊级别分类（Q1/Q2/Q3/Q4或该学科的分类标准）
+   - 主要研究领域和范围
+   - 与论文内容的匹配度评分（1-10分）
+   - 发表难度评估（容易/中等/困难/极难）
+   - 平均审稿周期
+   - 开放获取政策
+   - 期刊的学科分类（如SCI、SSCI、A&HCI等）
+   - 医学期刊特殊信息（如适用）：
+     * PubMed收录情况
+     * 是否为核心临床期刊
+     * 专科领域权威性
+     * 循证医学等级要求
+     * 临床试验注册要求
+     * 伦理委员会批准要求
+
+3. 按推荐优先级排序，并说明推荐理由
+4. 提供针对性的投稿建议，考虑该学科的特点
+
+论文分析结果："""
+        
+        for q in self.questions:
+            if q.id in self.analysis_results:
+                journal_prompt += f"\n\n{q.description}:\n{self.analysis_results[q.id]}"
+        
+        journal_prompt += "\n\n请提供详细的期刊推荐报告，重点关注期刊的层次性和适配性。请根据论文的具体学科领域，采用该领域通用的期刊评价标准和分类体系。"
+        
+        try:
+            response = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs=journal_prompt,
+                inputs_show_user="生成期刊推荐报告",
+                llm_kwargs=self.llm_kwargs,
+                chatbot=self.chatbot,
+                history=[],
+                sys_prompt="你是一个资深的跨学科学术期刊推荐专家，熟悉各个学科领域不同层次的期刊。请根据论文的具体学科和创新性，推荐从顶级到入门级的各层次期刊。不同学科有不同的期刊评价标准：理工科重视影响因子和SCI收录，社会科学重视SSCI和学科声誉，人文学科重视A&HCI和同行评议，医学领域重视PubMed收录、临床实用性、循证医学价值和伦理规范。请根据论文所属学科采用相应的评价标准。"
+            )
+            
+            if response:
+                return response
+            return "期刊推荐生成失败"
+            
+        except Exception as e:
+            self.chatbot.append(["错误", f"生成期刊推荐时出错: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return "期刊推荐生成失败: " + str(e)
+
+    def _generate_conference_recommendations(self) -> Generator:
+        """生成会议推荐"""
+        self.chatbot.append(["生成会议推荐", "正在基于论文分析结果生成会议推荐..."])
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+        
+        # 获取当前时间信息
+        current_time = datetime.now()
+        current_date_str = current_time.strftime("%Y年%m月%d日")
+        current_year = current_time.year
+        current_month = current_time.month
+        
+        # 构建会议推荐提示
+        conference_prompt = f"""请基于以下论文分析结果，为这篇论文推荐合适的学术会议。
+
+**重要提示：当前时间是{current_date_str}（{current_year}年{current_month}月），请基于这个时间点推断会议的举办时间和投稿截止时间。**
+
+推荐要求：
+1. 根据论文的创新性和工作质量，分别推荐不同级别的会议：
+   - 顶级会议（该领域最权威的国际会议）：2-3个
+   - 高质量会议（该领域知名的国际或区域会议）：3-4个
+   - 中等会议（该领域认可的专业会议）：3-4个
+   - 专业会议（该领域细分方向的专门会议）：2-3个
+
+注意：不同学科的会议评价标准不同：
+- 计算机科学：可参考CCF分类（A/B/C类）
+- 工程学：可参考EI收录和影响力
+- 医学：可参考会议的临床影响和同行认可度
+- 社会科学：可参考会议的学术声誉和参与度
+- 人文学科：可参考会议的历史和学术传统
+- 自然科学：可参考会议的国际影响力和发表质量
+
+特别是医学会议，需要考虑：
+- 临床医学会议重视实用性和临床指导价值
+- 基础医学会议重视科学创新和机制研究
+- 专科医学会议在各自领域内具有权威性
+- 国际医学会议的CME学分认证情况
+
+2. 对每个会议提供详细信息：
+   - 会议全名和缩写
+   - 会议级别分类（根据该学科的评价标准）
+   - 主要研究领域和主题
+   - 与论文内容的匹配度评分（1-10分）
+   - 录用难度评估（容易/中等/困难/极难）
+   - 会议举办周期（年会/双年会/不定期等）
+   - **基于当前时间{current_date_str}，推断{current_year}年和{current_year+1}年的举办时间和地点**（请根据往年的举办时间规律进行推断）
+   - **基于推断的会议时间，估算论文提交截止时间**（通常在会议前3-6个月）
+   - 会议的国际化程度和影响范围
+   - 医学会议特殊信息（如适用）：
+     * 是否提供CME学分
+     * 临床实践指导价值
+     * 专科认证机构认可情况
+     * 会议论文集的PubMed收录情况
+     * 伦理和临床试验相关要求
+
+3. 按推荐优先级排序，并说明推荐理由
+4. **基于当前时间{current_date_str}，提供会议投稿的时间规划建议**
+   - 哪些会议可以赶上{current_year}年的投稿截止时间
+   - 哪些会议需要准备{current_year+1}年的投稿
+   - 具体的时间安排建议
+
+论文分析结果："""
+        
+        for q in self.questions:
+            if q.id in self.analysis_results:
+                conference_prompt += f"\n\n{q.description}:\n{self.analysis_results[q.id]}"
+        
+        conference_prompt += f"\n\n请提供详细的会议推荐报告，重点关注会议的层次性和时效性。请根据论文的具体学科领域，采用该领域通用的会议评价标准。\n\n**特别注意：请根据当前时间{current_date_str}和各会议的历史举办时间规律，准确推断{current_year}年和{current_year+1}年的会议时间安排，不要使用虚构的时间。**"
+        
+        try:
+            response = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs=conference_prompt,
+                inputs_show_user="生成会议推荐报告",
+                llm_kwargs=self.llm_kwargs,
+                chatbot=self.chatbot,
+                history=[],
+                sys_prompt="你是一个资深的跨学科学术会议推荐专家，熟悉各个学科领域不同层次的学术会议。请根据论文的具体学科和创新性，推荐从顶级到专业级的各层次会议。不同学科有不同的会议评价标准和文化：理工科重视技术创新和国际影响力，社会科学重视理论贡献和社会意义，人文学科重视学术深度和文化价值，医学领域重视临床实用性、CME学分认证、专科权威性和伦理规范。请根据论文所属学科采用相应的评价标准和推荐策略。"
+            )
+            
+            if response:
+                return response
+            return "会议推荐生成失败"
+            
+        except Exception as e:
+            self.chatbot.append(["错误", f"生成会议推荐时出错: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return "会议推荐生成失败: " + str(e)
+
+    def _generate_priority_summary(self, journal_recommendations: str, conference_recommendations: str) -> Generator:
+        """生成优先级总结"""
+        self.chatbot.append(["生成优先级总结", "正在生成投稿优先级总结..."])
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+        
+        # 获取当前时间信息
+        current_time = datetime.now()
+        current_date_str = current_time.strftime("%Y年%m月%d日")
+        current_month = current_time.strftime("%Y年%m月")
+        
+        # 计算未来时间点
+        def add_months(date, months):
+            """安全地添加月份"""
+            month = date.month - 1 + months
+            year = date.year + month // 12
+            month = month % 12 + 1
+            day = min(date.day, calendar.monthrange(year, month)[1])
+            return date.replace(year=year, month=month, day=day)
+        
+        future_6_months = add_months(current_time, 6).strftime('%Y年%m月')
+        future_12_months = add_months(current_time, 12).strftime('%Y年%m月')
+        future_year = (current_time.year + 1)
+        
+        priority_prompt = f"""请基于以下期刊和会议推荐结果，生成一个综合的投稿优先级总结。
+
+**重要提示：当前时间是{current_date_str}（{current_month}），请基于这个时间点制定投稿计划。**
+
+期刊推荐结果：
+{journal_recommendations}
+
+会议推荐结果：
+{conference_recommendations}
+
+请提供：
+1. 综合投稿策略建议（考虑该学科的发表文化和惯例）
+   - 期刊优先还是会议优先（不同学科有不同偏好）
+   - 国际期刊/会议 vs 国内期刊/会议的选择策略
+   - 英文发表 vs 中文发表的考虑
+
+2. 按时间线排列的投稿计划（**基于当前时间{current_date_str}，考虑截止时间和审稿周期**）
+   - 短期目标（{current_month}起3-6个月内，即到{future_6_months}）
+   - 中期目标（6-12个月内，即到{future_12_months}）
+   - 长期目标（1年以上，即{future_year}年以后）
+
+3. 风险分散策略
+   - 同时投稿多个不同级别的目标
+   - 考虑该学科的一稿多投政策
+   - 备选方案和应急策略
+
+4. 针对论文可能需要的改进建议
+   - 根据目标期刊/会议的要求调整内容
+   - 语言和格式的优化建议
+   - 补充实验或分析的建议
+
+5. 预期的发表时间线和成功概率评估（基于当前时间{current_date_str}）
+
+6. 该学科特有的发表注意事项
+   - 伦理审查要求（如医学、心理学等）
+   - 数据开放要求（如某些自然科学领域）
+   - 利益冲突声明（如医学、工程等）
+   - 医学领域特殊要求：
+     * 临床试验注册要求（ClinicalTrials.gov、中国临床试验注册中心等）
+     * 患者知情同意和隐私保护
+     * 医学伦理委员会批准证明
+     * CONSORT、STROBE、PRISMA等报告规范遵循
+     * 药物/器械安全性数据要求
+     * CME学分认证相关要求
+     * 临床指南和循证医学等级要求
+   - 其他学科特殊要求
+
+请以表格形式总结前10个最推荐的投稿目标（期刊+会议），包括优先级排序、预期时间线和成功概率。
+
+**注意：所有时间规划都应基于当前时间{current_date_str}进行计算，不要使用虚构的时间。**"""
+        
+        try:
+            response = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs=priority_prompt,
+                inputs_show_user="生成投稿优先级总结",
+                llm_kwargs=self.llm_kwargs,
+                chatbot=self.chatbot,
+                history=[],
+                sys_prompt="你是一个资深的跨学科学术发表策略专家，熟悉各个学科的发表文化、惯例和要求。请综合考虑不同学科的特点：理工科通常重视期刊发表和影响因子，社会科学平衡期刊和专著，人文学科重视同行评议和学术声誉，医学重视临床意义和伦理规范。请为作者制定最适合其学科背景的投稿策略和时间规划。"
+            )
+            
+            if response:
+                return response
+            return "优先级总结生成失败"
+            
+        except Exception as e:
+            self.chatbot.append(["错误", f"生成优先级总结时出错: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return "优先级总结生成失败: " + str(e)
+    
+    def save_recommendations(self, journal_recommendations: str, conference_recommendations: str, priority_summary: str) -> Generator:
+        """保存推荐报告"""
+        timestamp = time.strftime("%Y%m%d_%H%M%S")
+        
+        # 保存为Markdown文件
+        try:
+            md_content = f"""# 论文期刊会议推荐报告
+
+## 投稿优先级总结
+
+{priority_summary}
+
+## 期刊推荐
+
+{journal_recommendations}
+
+## 会议推荐
+
+{conference_recommendations}
+
+---
+
+# 详细分析结果
+"""
+            
+            # 添加详细分析结果
+            for q in self.questions:
+                if q.id in self.analysis_results:
+                    md_content += f"\n\n## {q.description}\n\n{self.analysis_results[q.id]}"
+                    
+            result_file = write_history_to_file(
+                history=[md_content],
+                file_basename=f"期刊会议推荐_{timestamp}.md"
+            )
+            
+            if result_file and os.path.exists(result_file):
+                promote_file_to_downloadzone(result_file, chatbot=self.chatbot)
+                self.chatbot.append(["保存成功", f"推荐报告已保存至: {os.path.basename(result_file)}"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+            else:
+                self.chatbot.append(["警告", "保存报告成功但找不到文件"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+        except Exception as e:
+            self.chatbot.append(["警告", f"保存报告失败: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+    
+    def recommend_venues(self, paper_path: str) -> Generator:
+        """推荐期刊会议主流程"""
+        # 加载论文
+        success = yield from self._load_paper(paper_path)
+        if not success:
+            return
+        
+        # 分析关键问题
+        for question in self.questions:
+            yield from self._analyze_question(question)
+        
+        # 分别生成期刊和会议推荐
+        journal_recommendations = yield from self._generate_journal_recommendations()
+        conference_recommendations = yield from self._generate_conference_recommendations()
+        
+        # 生成优先级总结
+        priority_summary = yield from self._generate_priority_summary(journal_recommendations, conference_recommendations)
+        
+        # 显示结果
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+        
+        # 保存报告
+        yield from self.save_recommendations(journal_recommendations, conference_recommendations, priority_summary)
+        
+        # 将完整的分析结果和推荐内容添加到历史记录中，方便用户继续提问
+        self._add_to_history(journal_recommendations, conference_recommendations, priority_summary)
+        
+    def _add_to_history(self, journal_recommendations: str, conference_recommendations: str, priority_summary: str):
+        """将分析结果和推荐内容添加到历史记录中"""
+        try:
+            # 构建完整的内容摘要
+            history_content = f"""# 论文期刊会议推荐分析完成
+
+## 📊 投稿优先级总结
+{priority_summary}
+
+## 📚 期刊推荐
+{journal_recommendations}
+
+## 🏛️ 会议推荐
+{conference_recommendations}
+
+## 📋 详细分析结果
+"""
+            
+            # 添加详细分析结果
+            for q in self.questions:
+                if q.id in self.analysis_results:
+                    history_content += f"\n### {q.description}\n{self.analysis_results[q.id]}\n"
+            
+            history_content += "\n---\n💡 您现在可以基于以上分析结果继续提问，比如询问特定期刊的详细信息、投稿策略建议、或者对推荐结果的进一步解释。"
+            
+            # 添加到历史记录中
+            self.history.append("论文期刊会议推荐分析")
+            self.history.append(history_content)
+            
+            self.chatbot.append(["✅ 分析完成", "所有分析结果和推荐内容已添加到对话历史中，您可以继续基于这些内容提问。"])
+            
+        except Exception as e:
+            self.chatbot.append(["警告", f"添加到历史记录时出错: {str(e)}，但推荐报告已正常生成"])
+            # 即使添加历史失败，也不影响主要功能
+
+
+def _find_paper_file(path: str) -> str:
+    """查找路径中的论文文件（简化版）"""
+    if os.path.isfile(path):
+        return path
+        
+    # 支持的文件扩展名（按优先级排序）
+    extensions = ["pdf", "docx", "doc", "txt", "md", "tex"]
+    
+    # 简单地遍历目录
+    if os.path.isdir(path):
+        try:
+            for ext in extensions:
+                # 手动检查每个可能的文件，而不使用glob
+                potential_file = os.path.join(path, f"paper.{ext}")
+                if os.path.exists(potential_file) and os.path.isfile(potential_file):
+                    return potential_file
+                    
+            # 如果没找到特定命名的文件，检查目录中的所有文件
+            for file in os.listdir(path):
+                file_path = os.path.join(path, file)
+                if os.path.isfile(file_path):
+                    file_ext = file.split('.')[-1].lower() if '.' in file else ""
+                    if file_ext in extensions:
+                        return file_path
+        except Exception:
+            pass  # 忽略任何错误
+    
+    return None
+
+
+def download_paper_by_id(paper_info, chatbot, history) -> str:
+    """下载论文并返回保存路径
+    
+    Args:
+        paper_info: 元组，包含论文ID类型（arxiv或doi）和ID值
+        chatbot: 聊天机器人对象
+        history: 历史记录
+        
+    Returns:
+        str: 下载的论文路径或None
+    """
+    id_type, paper_id = paper_info
+    
+    # 创建保存目录 - 使用时间戳创建唯一文件夹
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    user_name = chatbot.get_user() if hasattr(chatbot, 'get_user') else "default"
+    from toolbox import get_log_folder, get_user
+    base_save_dir = get_log_folder(get_user(chatbot), plugin_name='paper_download')
+    save_dir = os.path.join(base_save_dir, f"papers_{timestamp}")
+    if not os.path.exists(save_dir):
+        os.makedirs(save_dir)
+    save_path = Path(save_dir)
+    
+    chatbot.append([f"下载论文", f"正在下载{'arXiv' if id_type == 'arxiv' else 'DOI'} {paper_id} 的论文..."])
+    update_ui(chatbot=chatbot, history=history)
+    
+    pdf_path = None
+    
+    try:
+        if id_type == 'arxiv':
+            # 使用改进的arxiv查询方法
+            formatted_id = format_arxiv_id(paper_id)
+            paper_result = get_arxiv_paper(formatted_id)
+            
+            if not paper_result:
+                chatbot.append([f"下载失败", f"未找到arXiv论文: {paper_id}"])
+                update_ui(chatbot=chatbot, history=history)
+                return None
+            
+            # 下载PDF
+            filename = f"arxiv_{paper_id.replace('/', '_')}.pdf"
+            pdf_path = str(save_path / filename)
+            paper_result.download_pdf(filename=pdf_path)
+            
+        else:  # doi
+            # 下载DOI
+            sci_hub = SciHub(
+                doi=paper_id,
+                path=save_path
+            )
+            pdf_path = sci_hub.fetch()
+        
+        # 检查下载结果
+        if pdf_path and os.path.exists(pdf_path):
+            promote_file_to_downloadzone(pdf_path, chatbot=chatbot)
+            chatbot.append([f"下载成功", f"已成功下载论文: {os.path.basename(pdf_path)}"])
+            update_ui(chatbot=chatbot, history=history)
+            return pdf_path
+        else:
+            chatbot.append([f"下载失败", f"论文下载失败: {paper_id}"])
+            update_ui(chatbot=chatbot, history=history)
+            return None
+            
+    except Exception as e:
+        chatbot.append([f"下载错误", f"下载论文时出错: {str(e)}"])
+        update_ui(chatbot=chatbot, history=history)
+        return None
+
+
+@CatchException
+def 论文期刊会议推荐(txt: str, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List,
+                history: List, system_prompt: str, user_request: str):
+    """主函数 - 论文期刊会议推荐"""
+    # 初始化推荐器
+    chatbot.append(["函数插件功能及使用方式", "论文期刊会议推荐：基于论文内容分析，为您推荐合适的学术期刊和会议投稿目标。适用于各个学科专业（自然科学、工程技术、医学、社会科学、人文学科等），根据不同学科的评价标准和发表文化，提供分层次的期刊会议推荐、影响因子分析、发表难度评估、投稿策略建议等。<br><br>📋 使用方式：<br>1、直接上传PDF文件<br>2、输入DOI号或arXiv ID<br>3、点击插件开始分析"])
+    yield from update_ui(chatbot=chatbot, history=history)
+    
+    paper_file = None
+    
+    # 检查输入是否为论文ID（arxiv或DOI）
+    paper_info = extract_paper_id(txt)
+    
+    if paper_info:
+        # 如果是论文ID，下载论文
+        chatbot.append(["检测到论文ID", f"检测到{'arXiv' if paper_info[0] == 'arxiv' else 'DOI'} ID: {paper_info[1]}，准备下载论文..."])
+        yield from update_ui(chatbot=chatbot, history=history)
+        
+        # 下载论文
+        paper_file = download_paper_by_id(paper_info, chatbot, history)
+        
+        if not paper_file:
+            report_exception(chatbot, history, a=f"下载论文失败", b=f"无法下载{'arXiv' if paper_info[0] == 'arxiv' else 'DOI'}论文: {paper_info[1]}")
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+    else:
+        # 检查输入路径
+        if not os.path.exists(txt):
+            report_exception(chatbot, history, a=f"解析论文: {txt}", b=f"找不到文件或无权访问: {txt}")
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+            
+        # 验证路径安全性
+        user_name = chatbot.get_user()
+        validate_path_safety(txt, user_name)
+        
+        # 查找论文文件
+        paper_file = _find_paper_file(txt)
+        
+        if not paper_file:
+            report_exception(chatbot, history, a=f"解析论文", b=f"在路径 {txt} 中未找到支持的论文文件")
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+    
+    yield from update_ui(chatbot=chatbot, history=history)
+    
+    # 确保paper_file是字符串
+    if paper_file is not None and not isinstance(paper_file, str):
+        # 尝试转换为字符串
+        try:
+            paper_file = str(paper_file)
+        except:
+            report_exception(chatbot, history, a=f"类型错误", b=f"论文路径不是有效的字符串: {type(paper_file)}")
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+    
+    # 开始推荐
+    chatbot.append(["开始分析", f"正在分析论文并生成期刊会议推荐: {os.path.basename(paper_file)}"])
+    yield from update_ui(chatbot=chatbot, history=history)
+    
+    recommender = JournalConferenceRecommender(llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
+    yield from recommender.recommend_venues(paper_file) 
--- a/crazy_functions/paper_fns/paper_download.py
+++ b/crazy_functions/paper_fns/paper_download.py
@@ -0,0 +1,295 @@
+import re
+import os
+import zipfile
+from toolbox import CatchException, update_ui, promote_file_to_downloadzone, get_log_folder, get_user
+
+from pathlib import Path
+from datetime import datetime
+
+def extract_paper_id(txt):
+    """从输入文本中提取论文ID"""
+    # 尝试匹配DOI（将DOI匹配提前，因为其格式更加明确）
+    doi_patterns = [
+        r'doi.org/([\w\./-]+)',        # doi.org/10.1234/xxx
+        r'doi:\s*([\w\./-]+)',         # doi: 10.1234/xxx
+        r'(10\.\d{4,}/[\w\.-]+)',      # 直接输入DOI: 10.1234/xxx
+    ]
+
+    for pattern in doi_patterns:
+        match = re.search(pattern, txt, re.IGNORECASE)
+        if match:
+            return ('doi', match.group(1))
+
+    # 尝试匹配arXiv ID
+    arxiv_patterns = [
+        r'arxiv.org/abs/(\d+\.\d+)',           # arxiv.org/abs/2103.14030
+        r'arxiv.org/pdf/(\d+\.\d+)',           # arxiv.org/pdf/2103.14030
+        r'arxiv/(\d+\.\d+)',                   # arxiv/2103.14030
+        r'^(\d{4}\.\d{4,5})$',                 # 直接输入ID: 2103.14030
+        # 添加对早期arXiv ID的支持
+        r'arxiv.org/abs/([\w-]+/\d{7})',       # arxiv.org/abs/math/0211159
+        r'arxiv.org/pdf/([\w-]+/\d{7})',       # arxiv.org/pdf/hep-th/9901001
+        r'^([\w-]+/\d{7})$',                   # 直接输入: math/0211159
+    ]
+
+    for pattern in arxiv_patterns:
+        match = re.search(pattern, txt, re.IGNORECASE)
+        if match:
+            paper_id = match.group(1)
+            # 如果是新格式（YYMM.NNNNN）或旧格式（category/NNNNNNN），都直接返回
+            if re.match(r'^\d{4}\.\d{4,5}$', paper_id) or re.match(r'^[\w-]+/\d{7}$', paper_id):
+                return ('arxiv', paper_id)
+
+    return None
+
+def extract_paper_ids(txt):
+    """从输入文本中提取多个论文ID"""
+    paper_ids = []
+
+    # 首先按换行符分割
+    for line in txt.strip().split('\n'):
+        line = line.strip()
+        if not line:  # 跳过空行
+            continue
+
+        # 对每一行再按空格分割
+        for item in line.split():
+            item = item.strip()
+            if not item:  # 跳过空项
+                continue
+            paper_info = extract_paper_id(item)
+            if paper_info:
+                paper_ids.append(paper_info)
+
+    # 去除重复项，保持顺序
+    unique_paper_ids = []
+    seen = set()
+    for paper_info in paper_ids:
+        if paper_info not in seen:
+            seen.add(paper_info)
+            unique_paper_ids.append(paper_info)
+
+    return unique_paper_ids
+
+def format_arxiv_id(paper_id):
+    """格式化arXiv ID，处理新旧两种格式"""
+    # 如果是旧格式 (e.g. astro-ph/0404140)，需要去掉arxiv:前缀
+    if '/' in paper_id:
+        return paper_id.replace('arxiv:', '')  # 确保移除可能存在的arxiv:前缀
+    return paper_id
+
+def get_arxiv_paper(paper_id):
+    """获取arXiv论文，处理新旧两种格式"""
+    import arxiv
+
+    # 尝试不同的查询方式
+    query_formats = [
+        paper_id,                    # 原始ID
+        paper_id.replace('/', ''),   # 移除斜杠
+        f"id:{paper_id}",           # 添加id:前缀
+    ]
+
+    for query in query_formats:
+        try:
+            # 使用Search查询
+            search = arxiv.Search(
+                query=query,
+                max_results=1
+            )
+            result = next(arxiv.Client().results(search))
+            if result:
+                return result
+        except:
+            continue
+
+        try:
+            # 使用id_list查询
+            search = arxiv.Search(id_list=[query])
+            result = next(arxiv.Client().results(search))
+            if result:
+                return result
+        except:
+            continue
+
+    return None
+
+def create_zip_archive(files, save_path):
+    """将多个PDF文件打包成zip"""
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    zip_filename = f"papers_{timestamp}.zip"
+    zip_path = str(save_path / zip_filename)
+
+    with zipfile.ZipFile(zip_path, 'w') as zipf:
+        for file in files:
+            if os.path.exists(file):
+                # 只添加文件名，不包含路径
+                zipf.write(file, os.path.basename(file))
+
+    return zip_path
+
+@CatchException
+def 论文下载(txt: str, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
+    """
+    txt: 用户输入，可以是DOI、arxiv ID或相关链接，支持多行输入进行批量下载
+    """
+    from crazy_functions.doc_fns.text_content_loader import TextContentLoader
+    from crazy_functions.review_fns.data_sources.arxiv_source import ArxivSource
+    from crazy_functions.review_fns.data_sources.scihub_source import SciHub
+    # 解析输入
+    paper_infos = extract_paper_ids(txt)
+    if not paper_infos:
+        chatbot.append(["输入解析", "未能识别任何论文ID或DOI，请检查输入格式。支持以下格式：\n- arXiv ID (例如：2103.14030)\n- arXiv链接\n- DOI (例如：10.1234/xxx)\n- DOI链接\n\n多个论文ID请用换行分隔。"])
+        yield from update_ui(chatbot=chatbot, history=history)
+        return
+
+    # 创建保存目录 - 使用时间戳创建唯一文件夹
+    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+    base_save_dir = get_log_folder(get_user(chatbot), plugin_name='paper_download')
+    save_dir = os.path.join(base_save_dir, f"papers_{timestamp}")
+    if not os.path.exists(save_dir):
+        os.makedirs(save_dir)
+    save_path = Path(save_dir)
+
+    # 记录下载结果
+    success_count = 0
+    failed_papers = []
+    downloaded_files = []  # 记录成功下载的文件路径
+
+    chatbot.append([f"开始下载", f"支持多行输入下载多篇论文，共检测到 {len(paper_infos)} 篇论文，开始下载..."])
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    for id_type, paper_id in paper_infos:
+        try:
+            if id_type == 'arxiv':
+                chatbot.append([f"正在下载", f"从arXiv下载论文 {paper_id}..."])
+                yield from update_ui(chatbot=chatbot, history=history)
+
+                # 使用改进的arxiv查询方法
+                formatted_id = format_arxiv_id(paper_id)
+                paper_result = get_arxiv_paper(formatted_id)
+
+                if not paper_result:
+                    failed_papers.append((paper_id, "未找到论文"))
+                    continue
+
+                # 下载PDF
+                try:
+                    filename = f"arxiv_{paper_id.replace('/', '_')}.pdf"
+                    pdf_path = str(save_path / filename)
+                    paper_result.download_pdf(filename=pdf_path)
+                    if os.path.exists(pdf_path):
+                        downloaded_files.append(pdf_path)
+                except Exception as e:
+                    failed_papers.append((paper_id, f"PDF下载失败: {str(e)}"))
+                    continue
+
+            else:  # doi
+                chatbot.append([f"正在下载", f"从Sci-Hub下载论文 {paper_id}..."])
+                yield from update_ui(chatbot=chatbot, history=history)
+
+                sci_hub = SciHub(
+                    doi=paper_id,
+                    path=save_path
+                )
+                pdf_path = sci_hub.fetch()
+                if pdf_path and os.path.exists(pdf_path):
+                    downloaded_files.append(pdf_path)
+
+            # 检查下载结果
+            if pdf_path and os.path.exists(pdf_path):
+                promote_file_to_downloadzone(pdf_path, chatbot=chatbot)
+                success_count += 1
+            else:
+                failed_papers.append((paper_id, "下载失败"))
+
+        except Exception as e:
+            failed_papers.append((paper_id, str(e)))
+
+        yield from update_ui(chatbot=chatbot, history=history)
+
+    # 创建ZIP压缩包
+    if downloaded_files:
+        try:
+            zip_path = create_zip_archive(downloaded_files, Path(base_save_dir))
+            promote_file_to_downloadzone(zip_path, chatbot=chatbot)
+            chatbot.append([
+                f"创建压缩包",
+                f"已将所有下载的论文打包为: {os.path.basename(zip_path)}"
+            ])
+            yield from update_ui(chatbot=chatbot, history=history)
+        except Exception as e:
+            chatbot.append([
+                f"创建压缩包失败",
+                f"打包文件时出现错误: {str(e)}"
+            ])
+            yield from update_ui(chatbot=chatbot, history=history)
+
+    # 生成最终报告
+    summary = f"下载完成！成功下载 {success_count} 篇论文。\n"
+    if failed_papers:
+        summary += "\n以下论文下载失败：\n"
+        for paper_id, reason in failed_papers:
+            summary += f"- {paper_id}: {reason}\n"
+
+    if downloaded_files:
+        summary += f"\n所有论文已存放在文件夹 '{save_dir}' 中，并打包到压缩文件中。您可以在下载区找到单个PDF文件和压缩包。"
+
+    chatbot.append([
+        f"下载完成",
+        summary
+    ])
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    # 如果下载成功且用户想要直接阅读内容
+    if downloaded_files:
+        chatbot.append([
+            "提示",
+            "正在读取论文内容进行分析，请稍候..."
+        ])
+        yield from update_ui(chatbot=chatbot, history=history)
+
+        # 使用TextContentLoader加载整个文件夹的PDF文件内容
+        loader = TextContentLoader(chatbot, history)
+
+        # 删除提示信息
+        chatbot.pop()
+
+        # 加载PDF内容 - 传入文件夹路径而不是单个文件路径
+        yield from loader.execute(save_dir)
+
+        # 添加提示信息
+        chatbot.append([
+            "提示",
+            "论文内容已加载完毕，您可以直接向AI提问有关该论文的问题。"
+        ])
+        yield from update_ui(chatbot=chatbot, history=history)
+
+if __name__ == "__main__":
+    # 测试代码
+    import asyncio
+    async def test():
+        # 测试批量输入
+        batch_inputs = [
+            # 换行分隔的测试
+            """https://arxiv.org/abs/2103.14030
+            math/0211159
+            10.1038/s41586-021-03819-2""",
+
+            # 空格分隔的测试
+            "https://arxiv.org/abs/2103.14030 math/0211159 10.1038/s41586-021-03819-2",
+
+            # 混合分隔的测试
+            """https://arxiv.org/abs/2103.14030 math/0211159
+            10.1038/s41586-021-03819-2 https://doi.org/10.1038/s41586-021-03819-2
+            2103.14030""",
+        ]
+
+        for i, test_input in enumerate(batch_inputs, 1):
+            print(f"\n测试用例 {i}:")
+            print(f"输入: {test_input}")
+            results = extract_paper_ids(test_input)
+            print(f"解析结果:")
+            for result in results:
+                print(f"  {result}")
+
+    asyncio.run(test())
--- a/crazy_functions/paper_fns/reduce_aigc.py
+++ b/crazy_functions/paper_fns/reduce_aigc.py
@@ -0,0 +1,867 @@
+import os
+import time
+import glob
+import re
+import threading
+from typing import Dict, List, Generator, Tuple
+from dataclasses import dataclass
+
+from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
+from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
+from crazy_functions.rag_fns.rag_file_support import extract_text,  convert_to_markdown
+from request_llms.bridge_all import model_info
+from toolbox import update_ui, CatchException, report_exception, promote_file_to_downloadzone, write_history_to_file
+from shared_utils.fastapi_server import validate_path_safety
+
+# 新增：导入结构化论文提取器
+from crazy_functions.doc_fns.read_fns.unstructured_all.paper_structure_extractor import PaperStructureExtractor, ExtractorConfig, StructuredPaper
+
+# 导入格式化器
+from crazy_functions.paper_fns.file2file_doc import (
+    TxtFormatter,
+    MarkdownFormatter,
+    HtmlFormatter,
+    WordFormatter
+)
+
+@dataclass
+class TextFragment:
+    """文本片段数据类，用于组织处理单元"""
+    content: str
+    fragment_index: int
+    total_fragments: int
+
+
+class DocumentProcessor:
+    """文档处理器 - 处理单个文档并输出结果"""
+
+    def __init__(self, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List, history: List, system_prompt: str):
+        """初始化处理器"""
+        self.llm_kwargs = llm_kwargs.copy()  # 创建原始llm_kwargs的副本
+        # 固定使用deepseek-reasoner模型
+        self.llm_kwargs['llm_model'] = "deepseek-reasoner"
+        self.plugin_kwargs = plugin_kwargs
+        self.chatbot = chatbot
+        self.history = history
+        self.system_prompt = system_prompt
+        self.processed_results = []
+        self.failed_fragments = []
+        # 新增：初始化论文结构提取器
+        self.paper_extractor = PaperStructureExtractor()
+        # 修改：设置降重次数，默认为1次（原为3次）
+        self.reduction_times = int(self.plugin_kwargs.get("reduction_times", 1))
+
+    def _get_token_limit(self) -> int:
+        """获取模型token限制，返回更小的值以确保更细粒度的分割"""
+        max_token = model_info[self.llm_kwargs['llm_model']]['max_token']
+        # 降低token限制，使每个片段更小
+        return max_token // 4  # 从3/4降低到1/4
+
+    def _create_batch_inputs(self, fragments: List[TextFragment], current_iteration: int = 1) -> Tuple[List, List, List]:
+        """创建批处理输入"""
+        inputs_array = []
+        inputs_show_user_array = []
+        history_array = []
+
+        # 基础指令 - 增强单次调用的效果
+        user_instruction = self.plugin_kwargs.get("advanced_arg", """你是一个人类科研工作者，请对以下学术文本进行深度改写，以彻底消除AI生成特征。具体要求如下：
+
+1. 保持学术写作的严谨性和专业性，但加入一些人类写作的不完美元素
+2. 维持原文的核心论述和逻辑框架，但打破过于完美的结构
+3. 彻底改变句式结构：
+   - 灵活运用主动句与被动句，偏好使用主动语态
+   - 适当使用不同长度的句子，包括一些较长的复杂句
+   - 引入变化多样的句式，打破规律性
+   - 完全避免AI常用的模板化句式和套路表达
+   - 增加一些学术写作中常见的转折和连接方式
+4. 全面改善用词：
+   - 使用更多学术语境下的专业词汇和同义词替换
+   - 避免过于机械和规律性的连接词，使用更自然的过渡
+   - 重构专业术语的表达方式，但保持准确性
+   - 增加词汇多样性，减少重复用词
+   - 偶尔使用一些不太常见但恰当的词汇
+5. 模拟真实学者的写作风格：
+   - 注重论证的严密性，但允许存在一些微小的不对称性
+   - 保持表达的客观性，同时适度体现个人学术见解
+   - 在适当位置表达观点时更加自信和坚定
+   - 避免过于完美和机械均衡的论述结构
+   - 允许段落长度有所变化，不要过于均匀
+6. 引入人类学者常见的写作特点：
+   - 段落之间的过渡更加自然流畅
+   - 适当使用一些学术界常见的修辞手法，但不过度使用
+   - 偶尔使用一些强调和限定性表达
+   - 适当使用一些学术界认可的个人化表达
+7. 彻底消除AI痕迹：
+   - 避免过于规整和均衡的段落结构
+   - 避免机械性的句式变化和词汇替换模式
+   - 避免过于完美的逻辑推导，适当增加一些转折
+   - 减少公式化的表达方式""")
+
+        # 对于单次调用的场景，不需要迭代前缀，直接使用更强力的改写指令
+        for frag in fragments:
+            # 在单次调用时使用更强力的指令
+            if self.reduction_times == 1:
+                i_say = (f'请对以下学术文本进行彻底改写，完全消除AI特征，使其像真实人类学者撰写的内容。\n\n{user_instruction}\n\n'
+                         f'请记住以下几点：\n'
+                         f'1. 避免过于规整和均衡的结构\n'
+                         f'2. 引入一些人类写作的微小不完美之处\n'
+                         f'3. 使用多样化的句式和词汇\n'
+                         f'4. 打破可能的AI规律性表达模式\n'
+                         f'5. 适当使用一些专业领域内的表达习惯\n\n'
+                         f'请将对文本的处理结果放在<decision>和</decision>标签之间。\n\n'
+                         f'文本内容：\n```\n{frag.content}\n```')
+            else:
+                # 原有的迭代前缀逻辑
+                iteration_prefix = ""
+                if current_iteration > 1:
+                    iteration_prefix = f"这是第{current_iteration}次改写，请在保持学术性的基础上，采用更加人性化、不同的表达方式。"
+                    if current_iteration == 2:
+                        iteration_prefix += "在保持专业性的同时，进一步优化句式结构和用词，显著降低AI痕迹。"
+                    elif current_iteration >= 3:
+                        iteration_prefix += "请在确保不损失任何学术内容的前提下，彻底重构表达方式，并适当引入少量人类学者常用的表达技巧，避免过度使用比喻和类比。"
+
+                i_say = (f'请按照以下要求处理文本内容：{iteration_prefix}{user_instruction}\n\n'
+                         f'请将对文本的处理结果放在<decision>和</decision>标签之间。\n\n'
+                         f'文本内容：\n```\n{frag.content}\n```')
+
+            i_say_show_user = f'正在处理文本片段 {frag.fragment_index + 1}/{frag.total_fragments}'
+
+            inputs_array.append(i_say)
+            inputs_show_user_array.append(i_say_show_user)
+            history_array.append([])
+
+        return inputs_array, inputs_show_user_array, history_array
+
+    def _extract_decision(self, text: str) -> str:
+        """从LLM响应中提取<decision>标签内的内容"""
+        import re
+        pattern = r'<decision>(.*?)</decision>'
+        matches = re.findall(pattern, text, re.DOTALL)
+
+        if matches:
+            return matches[0].strip()
+        else:
+            # 如果没有找到标签，返回原始文本
+            return text.strip()
+
+    def process_file(self, file_path: str) -> Generator:
+        """处理单个文件"""
+        self.chatbot.append(["开始处理文件", f"文件路径: {file_path}"])
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        try:
+            # 首先尝试转换为Markdown
+            file_path = convert_to_markdown(file_path)
+
+            # 1. 检查文件是否为支持的论文格式
+            is_paper_format = any(file_path.lower().endswith(ext) for ext in self.paper_extractor.SUPPORTED_EXTENSIONS)
+
+            if is_paper_format:
+                # 使用结构化提取器处理论文
+                return (yield from self._process_structured_paper(file_path))
+            else:
+                # 使用原有方式处理普通文档
+                return (yield from self._process_regular_file(file_path))
+
+        except Exception as e:
+            self.chatbot.append(["处理错误", f"文件处理失败: {str(e)}"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return None
+
+    def _process_structured_paper(self, file_path: str) -> Generator:
+        """处理结构化论文文件"""
+        # 1. 提取论文结构
+        self.chatbot[-1] = ["正在分析论文结构", f"文件路径: {file_path}"]
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        try:
+            paper = self.paper_extractor.extract_paper_structure(file_path)
+
+            if not paper or not paper.sections:
+                self.chatbot.append(["无法提取论文结构", "将使用全文内容进行处理"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+                # 使用全文内容进行段落切分
+                if paper and paper.full_text:
+                    # 使用增强的分割函数进行更细致的分割
+                    fragments = self._breakdown_section_content(paper.full_text)
+
+                    # 创建文本片段对象
+                    text_fragments = []
+                    for i, frag in enumerate(fragments):
+                        if frag.strip():
+                            text_fragments.append(TextFragment(
+                                content=frag,
+                                fragment_index=i,
+                                total_fragments=len(fragments)
+                            ))
+
+                    # 多次降重处理
+                    if text_fragments:
+                        current_fragments = text_fragments
+
+                        # 进行多轮降重处理
+                        for iteration in range(1, self.reduction_times + 1):
+                            # 处理当前片段
+                            processed_content = yield from self._process_text_fragments(current_fragments, iteration)
+
+                            # 如果这是最后一次迭代，保存结果
+                            if iteration == self.reduction_times:
+                                final_content = processed_content
+                                break
+
+                            # 否则，准备下一轮迭代的片段
+                            # 从处理结果中提取处理后的内容
+                            next_fragments = []
+                            for idx, item in enumerate(self.processed_results):
+                                next_fragments.append(TextFragment(
+                                    content=item['content'],
+                                    fragment_index=idx,
+                                    total_fragments=len(self.processed_results)
+                                ))
+
+                            current_fragments = next_fragments
+
+                        # 更新UI显示最终结果
+                        self.chatbot[-1] = ["处理完成", f"共完成 {self.reduction_times} 轮降重"]
+                        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+                        return final_content
+                    else:
+                        self.chatbot.append(["处理失败", "未能提取到有效的文本内容"])
+                        yield from update_ui(chatbot=self.chatbot, history=self.history)
+                        return None
+                else:
+                    self.chatbot.append(["处理失败", "未能提取到论文内容"])
+                    yield from update_ui(chatbot=self.chatbot, history=self.history)
+                    return None
+
+            # 2. 准备处理章节内容（不处理标题）
+            self.chatbot[-1] = ["已提取论文结构", f"共 {len(paper.sections)} 个主要章节"]
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            # 3. 收集所有需要处理的章节内容并分割为合适大小
+            sections_to_process = []
+            section_map = {}  # 用于映射处理前后的内容
+
+            def collect_section_contents(sections, parent_path=""):
+                """递归收集章节内容，跳过参考文献部分"""
+                for i, section in enumerate(sections):
+                    current_path = f"{parent_path}/{i}" if parent_path else f"{i}"
+
+                    # 检查是否为参考文献部分，如果是则跳过
+                    if section.section_type == 'references' or section.title.lower() in ['references', '参考文献', 'bibliography', '文献']:
+                        continue  # 跳过参考文献部分
+
+                    # 只处理内容非空的章节
+                    if section.content and section.content.strip():
+                        # 使用增强的分割函数进行更细致的分割
+                        fragments = self._breakdown_section_content(section.content)
+
+                        for fragment_idx, fragment_content in enumerate(fragments):
+                            if fragment_content.strip():
+                                fragment_index = len(sections_to_process)
+                                sections_to_process.append(TextFragment(
+                                    content=fragment_content,
+                                    fragment_index=fragment_index,
+                                    total_fragments=0  # 临时值，稍后更新
+                                ))
+
+                                # 保存映射关系，用于稍后更新章节内容
+                                # 为每个片段存储原始章节和片段索引信息
+                                section_map[fragment_index] = (current_path, section, fragment_idx, len(fragments))
+
+                    # 递归处理子章节
+                    if section.subsections:
+                        collect_section_contents(section.subsections, current_path)
+
+            # 收集所有章节内容
+            collect_section_contents(paper.sections)
+
+            # 更新总片段数
+            total_fragments = len(sections_to_process)
+            for frag in sections_to_process:
+                frag.total_fragments = total_fragments
+
+            # 4. 如果没有内容需要处理，直接返回
+            if not sections_to_process:
+                self.chatbot.append(["处理完成", "未找到需要处理的内容"])
+                yield from update_ui(chatbot=self.chatbot, history=self.history)
+                return None
+
+            # 5. 批量处理章节内容
+            self.chatbot[-1] = ["开始处理论文内容", f"共 {len(sections_to_process)} 个内容片段"]
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            # 一次性准备所有输入
+            inputs_array, inputs_show_user_array, history_array = self._create_batch_inputs(sections_to_process)
+
+            # 使用系统提示
+            instruction = self.plugin_kwargs.get("advanced_arg", """请对以下学术文本进行彻底改写，以显著降低AI生成特征。具体要求如下：
+
+1. 保持学术写作的严谨性和专业性
+2. 维持原文的核心论述和逻辑框架
+3. 优化句式结构：
+   - 灵活运用主动句与被动句
+   - 适当拆分复杂句式，提高可读性
+   - 注意句式的多样性，避免重复模式
+   - 打破AI常用的句式模板
+4. 改善用词：
+   - 使用更多学术语境下的同义词替换
+   - 避免过于机械和规律性的连接词
+   - 适当调整专业术语的表达方式
+   - 增加词汇多样性，减少重复用词
+5. 增强文本的学术特征：
+   - 注重论证的严密性
+   - 保持表达的客观性
+   - 适度体现作者的学术见解
+   - 避免过于完美和均衡的论述结构
+6. 确保语言风格的一致性
+7. 减少AI生成文本常见的套路和模式""")
+            sys_prompt_array = [f"""作为一位专业的学术写作顾问，请按照以下要求改写文本：
+
+1. 严格保持学术写作规范
+2. 维持原文的核心论述和逻辑框架
+3. 通过优化句式结构和用词降低AI生成特征
+4. 确保语言风格的一致性和专业性
+5. 保持内容的客观性和准确性
+6. 避免AI常见的套路化表达和过于完美的结构"""] * len(sections_to_process)
+
+            # 调用LLM一次性处理所有片段
+            response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
+                inputs_array=inputs_array,
+                inputs_show_user_array=inputs_show_user_array,
+                llm_kwargs=self.llm_kwargs,
+                chatbot=self.chatbot,
+                history_array=history_array,
+                sys_prompt_array=sys_prompt_array,
+            )
+
+            # 处理响应，重组章节内容
+            section_contents = {}  # 用于重组各章节的处理后内容
+
+            for j, frag in enumerate(sections_to_process):
+                try:
+                    llm_response = response_collection[j * 2 + 1]
+                    processed_text = self._extract_decision(llm_response)
+
+                    if processed_text and processed_text.strip():
+                        # 保存处理结果
+                        self.processed_results.append({
+                            'index': frag.fragment_index,
+                            'content': processed_text
+                        })
+
+                        # 存储处理后的文本片段，用于后续重组
+                        fragment_index = frag.fragment_index
+                        if fragment_index in section_map:
+                            path, section, fragment_idx, total_fragments = section_map[fragment_index]
+
+                            # 初始化此章节的内容容器（如果尚未创建）
+                            if path not in section_contents:
+                                section_contents[path] = [""] * total_fragments
+
+                            # 将处理后的片段放入正确位置
+                            section_contents[path][fragment_idx] = processed_text
+                    else:
+                        self.failed_fragments.append(frag)
+                except Exception as e:
+                    self.failed_fragments.append(frag)
+
+            # 重组每个章节的内容
+            for path, fragments in section_contents.items():
+                section = None
+                for idx in section_map:
+                    if section_map[idx][0] == path:
+                        section = section_map[idx][1]
+                        break
+
+                if section:
+                    # 合并该章节的所有处理后片段
+                    section.content = "\n".join(fragments)
+
+            # 6. 更新UI
+            success_count = total_fragments - len(self.failed_fragments)
+            self.chatbot[-1] = ["处理完成", f"成功处理 {success_count}/{total_fragments} 个内容片段"]
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            # 收集参考文献部分（不进行处理）
+            references_sections = []
+            def collect_references(sections, parent_path=""):
+                """递归收集参考文献部分"""
+                for i, section in enumerate(sections):
+                    current_path = f"{parent_path}/{i}" if parent_path else f"{i}"
+
+                    # 检查是否为参考文献部分
+                    if section.section_type == 'references' or section.title.lower() in ['references', '参考文献', 'bibliography', '文献']:
+                        references_sections.append((current_path, section))
+
+                    # 递归检查子章节
+                    if section.subsections:
+                        collect_references(section.subsections, current_path)
+
+            # 收集参考文献
+            collect_references(paper.sections)
+
+            # 7. 将处理后的结构化论文转换为Markdown
+            markdown_content = self.paper_extractor.generate_markdown(paper)
+
+            # 8. 返回处理后的内容
+            self.chatbot[-1] = ["处理完成", f"成功处理 {success_count}/{total_fragments} 个内容片段，参考文献部分未处理"]
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            return markdown_content
+
+        except Exception as e:
+            self.chatbot.append(["结构化处理失败", f"错误: {str(e)}，将尝试作为普通文件处理"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return (yield from self._process_regular_file(file_path))
+
+    def _process_regular_file(self, file_path: str) -> Generator:
+        """使用原有方式处理普通文件"""
+        # 原有的文件处理逻辑
+        self.chatbot[-1] = ["正在读取文件", f"文件路径: {file_path}"]
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        content = extract_text(file_path)
+        if not content or not content.strip():
+            self.chatbot.append(["处理失败", "文件内容为空或无法提取内容"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return None
+
+        # 2. 分割文本
+        self.chatbot[-1] = ["正在分析文件", "将文件内容分割为适当大小的片段"]
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        # 使用增强的分割函数
+        fragments = self._breakdown_section_content(content)
+
+        # 3. 创建文本片段对象
+        text_fragments = []
+        for i, frag in enumerate(fragments):
+            if frag.strip():
+                text_fragments.append(TextFragment(
+                    content=frag,
+                    fragment_index=i,
+                    total_fragments=len(fragments)
+                ))
+
+        # 4. 多轮降重处理
+        if not text_fragments:
+            self.chatbot.append(["处理失败", "未能提取到有效的文本内容"])
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+            return None
+
+        # 批处理大小
+        batch_size = 8  # 每批处理的片段数
+
+        # 第一次迭代
+        current_batches = []
+        for i in range(0, len(text_fragments), batch_size):
+            current_batches.append(text_fragments[i:i + batch_size])
+
+        all_processed_fragments = []
+
+        # 进行多轮降重处理
+        for iteration in range(1, self.reduction_times + 1):
+            self.chatbot[-1] = ["开始处理文本", f"第 {iteration}/{self.reduction_times} 次降重"]
+            yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+            next_batches = []
+            all_processed_fragments = []
+
+            # 分批处理当前迭代的片段
+            for batch in current_batches:
+                # 处理当前批次
+                _ = yield from self._process_text_fragments(batch, iteration)
+
+                # 收集处理结果
+                processed_batch = []
+                for item in self.processed_results:
+                    processed_batch.append(TextFragment(
+                        content=item['content'],
+                        fragment_index=len(all_processed_fragments) + len(processed_batch),
+                        total_fragments=0  # 临时值，稍后更新
+                    ))
+
+                all_processed_fragments.extend(processed_batch)
+
+                # 如果不是最后一轮迭代，准备下一批次
+                if iteration < self.reduction_times:
+                    for i in range(0, len(processed_batch), batch_size):
+                        next_batches.append(processed_batch[i:i + batch_size])
+
+            # 更新总片段数
+            for frag in all_processed_fragments:
+                frag.total_fragments = len(all_processed_fragments)
+
+            # 为下一轮迭代准备批次
+            current_batches = next_batches
+
+        # 合并最终结果
+        final_content = "\n\n".join([frag.content for frag in all_processed_fragments])
+
+        # 5. 更新UI显示最终结果
+        self.chatbot[-1] = ["处理完成", f"共完成 {self.reduction_times} 轮降重"]
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        return final_content
+
+    def save_results(self, content: str, original_file_path: str) -> List[str]:
+        """保存处理结果为TXT格式"""
+        if not content:
+            return []
+
+        timestamp = time.strftime("%Y%m%d_%H%M%S")
+        original_filename = os.path.basename(original_file_path)
+        filename_without_ext = os.path.splitext(original_filename)[0]
+        base_filename = f"{filename_without_ext}_processed_{timestamp}"
+
+        result_files = []
+
+        # 只保存为TXT
+        try:
+            txt_formatter = TxtFormatter()
+            txt_content = txt_formatter.create_document(content)
+            txt_file = write_history_to_file(
+                history=[txt_content],
+                file_basename=f"{base_filename}.txt"
+            )
+            result_files.append(txt_file)
+        except Exception as e:
+            self.chatbot.append(["警告", f"TXT格式保存失败: {str(e)}"])
+
+        # 添加到下载区
+        for file in result_files:
+            promote_file_to_downloadzone(file, chatbot=self.chatbot)
+
+        return result_files
+
+    def _breakdown_section_content(self, content: str) -> List[str]:
+        """对文本内容进行分割与合并
+
+        主要按段落进行组织，只合并较小的段落以减少片段数量
+        保留原始段落结构，不对长段落进行强制分割
+        针对中英文设置不同的阈值，因为字符密度不同
+        """
+        # 先按段落分割文本
+        paragraphs = content.split('\n\n')
+
+        # 检测语言类型
+        chinese_char_count = sum(1 for char in content if '\u4e00' <= char <= '\u9fff')
+        is_chinese_text = chinese_char_count / max(1, len(content)) > 0.3
+
+        # 根据语言类型设置不同的阈值（只用于合并小段落）
+        if is_chinese_text:
+            # 中文文本：一个汉字就是一个字符，信息密度高
+            min_chunk_size = 300  # 段落合并的最小阈值
+            target_size = 800  # 理想的段落大小
+        else:
+            # 英文文本：一个单词由多个字符组成，信息密度低
+            min_chunk_size = 600  # 段落合并的最小阈值
+            target_size = 1600  # 理想的段落大小
+
+        # 1. 只合并小段落，不对长段落进行分割
+        result_fragments = []
+        current_chunk = []
+        current_length = 0
+
+        for para in paragraphs:
+            # 如果段落太小且不会超过目标大小，则合并
+            if len(para) < min_chunk_size and current_length + len(para) <= target_size:
+                current_chunk.append(para)
+                current_length += len(para)
+            # 否则，创建新段落
+            else:
+                # 如果当前块非空且与当前段落无关，先保存它
+                if current_chunk and current_length > 0:
+                    result_fragments.append('\n\n'.join(current_chunk))
+
+                # 当前段落作为新块
+                current_chunk = [para]
+                current_length = len(para)
+
+            # 如果当前块大小已接近目标大小，保存并开始新块
+            if current_length >= target_size:
+                result_fragments.append('\n\n'.join(current_chunk))
+                current_chunk = []
+                current_length = 0
+
+        # 保存最后一个块
+        if current_chunk:
+            result_fragments.append('\n\n'.join(current_chunk))
+
+        # 2. 处理可能过大的片段（确保不超过token限制）
+        final_fragments = []
+        max_token = self._get_token_limit()
+
+        for fragment in result_fragments:
+            # 检查fragment是否可能超出token限制
+            # 根据语言类型调整token估算
+            if is_chinese_text:
+                estimated_tokens = len(fragment) / 1.5  # 中文每个token约1-2个字符
+            else:
+                estimated_tokens = len(fragment) / 4  # 英文每个token约4个字符
+
+            if estimated_tokens > max_token:
+                # 即使可能超出限制，也尽量保持段落的完整性
+                # 使用breakdown_text但设置更大的限制来减少分割
+                larger_limit = max_token * 0.95  # 使用95%的限制
+                sub_fragments = breakdown_text_to_satisfy_token_limit(
+                    txt=fragment,
+                    limit=larger_limit,
+                    llm_model=self.llm_kwargs['llm_model']
+                )
+                final_fragments.extend(sub_fragments)
+            else:
+                final_fragments.append(fragment)
+
+        return final_fragments
+
+    def _process_text_fragments(self, text_fragments: List[TextFragment], current_iteration: int = 1) -> str:
+        """处理文本片段，支持多次降重
+
+        Args:
+            text_fragments: 要处理的文本片段列表
+            current_iteration: 当前是第几次降重迭代
+
+        Returns:
+            处理后的文本内容
+        """
+        self.chatbot[-1] = ["开始处理文本", f"第 {current_iteration}/{self.reduction_times} 次降重，共 {len(text_fragments)} 个片段"]
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        # 重置处理结果，为当前迭代做准备
+        self.processed_results = []
+        self.failed_fragments = []
+
+        # 一次性准备所有输入
+        inputs_array, inputs_show_user_array, history_array = self._create_batch_inputs(text_fragments, current_iteration)
+
+        # 对于单次调用的特殊处理 - 使用更强力的系统提示词
+        if self.reduction_times == 1:
+            sys_prompt = f"""你是一个伪装成人类科研学者的AI，能够将各种AI生成内容改写成人类学者常用的表达方式，让人类学者无法分辨。
+
+你的任务是对学术文本进行深度改写，以彻底消除AI特征，使其具有真实人类学者的写作特点：
+
+1. 打破AI常见的规整句式结构和词汇选择模式
+2. 引入学术写作中的自然变化和不规则性
+3. 使用多样化的句式和段落结构，避免明显的平衡性和规律性
+4. 加入人类写作中常见的微小不完美之处，如段落长度变化、论述强调点不均等
+5. 在维持核心论点的同时，完全重构表达方式
+6. 适当使用学科领域内专家常用的表达习惯和术语
+7. 确保文本读起来自然流畅，避免机械感
+8. 打破AI生成内容常见的逻辑结构和表达套路
+9. 根据文本内容，在保持专业性的基础上增加写作的特色和个性
+
+对于每个文本片段，尽可能彻底地重构，使其无法被识别为AI生成。"""
+
+            sys_prompt_array = [sys_prompt] * len(text_fragments)
+
+        else:
+            # 原有的多次迭代处理逻辑
+            # 根据迭代次数调整系统提示词强度
+            base_instruction = self.plugin_kwargs.get("advanced_arg", """你是一个人类科研工作者，请对以下学术文本进行彻底改写，以显著降低AI生成特征。具体要求如下：
+
+1. 保持学术写作的严谨性和专业性
+2. 维持原文的核心论述和逻辑框架
+3. 优化句式结构：
+   - 灵活运用主动句与被动句
+   - 适当拆分复杂句式，提高可读性
+   - 注意句式的多样性，避免重复模式
+   - 打破AI常用的句式模板
+4. 改善用词：
+   - 使用更多学术语境下的同义词替换
+   - 避免过于机械和规律性的连接词
+   - 适当调整专业术语的表达方式
+   - 增加词汇多样性，减少重复用词
+5. 增强文本的学术特征：
+   - 注重论证的严密性
+   - 保持表达的客观性
+   - 适度体现作者的学术见解
+   - 避免过于完美和均衡的论述结构
+6. 确保语言风格的一致性
+7. 减少AI生成文本常见的套路和模式""")
+
+            # 根据迭代次数增强强度
+            if current_iteration == 1:
+                # 第一次迭代使用基础强度
+                instruction = base_instruction
+                sys_prompt = f"""你是一个伪装成人类科研学者的AI，能够将各种AI生成内容改写成人类学者常用的表达方式，让人类学者无法分辨。请进行第{current_iteration}轮深度改写：
+
+1. 严格保持学术写作规范
+2. 维持原文的核心论述和逻辑框架
+3. 通过优化句式结构和用词降低AI生成特征
+4. 确保语言风格的一致性和专业性
+5. 保持内容的客观性和准确性
+6. 避免AI常见的套路化表达和过于完美的结构"""
+            elif current_iteration == 2:
+                # 第二次迭代使用中等强度
+                instruction = base_instruction + """这是第二次改写，请进一步优化：
+
+1. 更深入地调整句式结构，增加表达多样性
+2. 在保持准确性的前提下，替换更多专业术语的表达方式
+3. 优化段落结构，增强逻辑连贯性
+4. 适当调整学术论证的表达方式
+5. 打破AI生成内容的常见模式，如过于均衡的结构和规律性的表达方式"""
+                sys_prompt = f"""你是一个伪装成人类科研学者的AI，能够将各种AI生成内容改写成人类学者常用的表达方式，让人类学者无法分辨。请进行第二轮改写：
+
+1. 在保持严谨性的基础上，优化表达方式
+2. 改善文本结构，提升学术论述的清晰度
+3. 增强专业术语使用的灵活性
+4. 确保论证过程的完整性和逻辑性
+5. 进一步减少AI生成内容的特征和模式
+6. 使文本表现出更自然、更人性化的写作风格"""
+            else:
+                # 第三次或更多次迭代使用高强度
+                instruction = base_instruction + f"""这是第{current_iteration}次改写，需要在保持学术性的前提下彻底重构文本：
+
+1. 全面重构句式，采用不同的表达策略
+2. 系统性替换学术用语，保持专业准确性
+3. 重组段落结构，优化论证层次
+4. 深化学术观点的表达方式
+5. 增强文本的逻辑严密性
+6. 提升论述的专业深度
+7. 确保不遗漏任何学术观点和论证要素
+8. 适当使用学术表达技巧（如精准举例、恰当转折等），但不过分依赖比喻和类比
+9. 彻底消除AI生成内容的特征，使文本具有真实学者的写作风格"""
+                sys_prompt = f"""你是一个伪装成人类科研学者的AI，能够将各种AI生成内容改写成人类学者常用的表达方式，让人类学者无法分辨。请进行第{current_iteration}轮深度改写：
+
+1. 在保持专业水准的前提下，彻底重构表达方式，引入长难句
+2. 确保学术论证的严密性和完整性
+3. 优化专业术语的运用
+4. 提升文本的学术价值
+5. 保持论述的逻辑性和连贯性
+6. 适当使用少量学术表达技巧，提高文本说服力，但避免过度使用比喻和类比
+7. 消除所有明显的AI生成痕迹，使文本更接近真实学者的写作风格"""
+
+            sys_prompt_array = [sys_prompt] * len(text_fragments)
+
+        # 调用LLM一次性处理所有片段
+        response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
+            inputs_array=inputs_array,
+            inputs_show_user_array=inputs_show_user_array,
+            llm_kwargs=self.llm_kwargs,
+            chatbot=self.chatbot,
+            history_array=history_array,
+            sys_prompt_array=sys_prompt_array,
+        )
+
+        # 处理响应
+        for j, frag in enumerate(text_fragments):
+            try:
+                llm_response = response_collection[j * 2 + 1]
+                processed_text = self._extract_decision(llm_response)
+
+                if processed_text and processed_text.strip():
+                    self.processed_results.append({
+                        'index': frag.fragment_index,
+                        'content': processed_text
+                    })
+                else:
+                    self.failed_fragments.append(frag)
+                    self.processed_results.append({
+                        'index': frag.fragment_index,
+                        'content': frag.content
+                    })
+            except Exception as e:
+                self.failed_fragments.append(frag)
+                self.processed_results.append({
+                    'index': frag.fragment_index,
+                    'content': frag.content
+                })
+
+        # 按原始顺序合并结果
+        self.processed_results.sort(key=lambda x: x['index'])
+        final_content = "\n".join([item['content'] for item in self.processed_results])
+
+        # 更新UI
+        success_count = len(text_fragments) - len(self.failed_fragments)
+        self.chatbot[-1] = ["当前阶段处理完成", f"第 {current_iteration}/{self.reduction_times} 次降重，成功处理 {success_count}/{len(text_fragments)} 个片段"]
+        yield from update_ui(chatbot=self.chatbot, history=self.history)
+
+        return final_content
+
+
+@CatchException
+def 学术降重(txt: str, llm_kwargs: Dict, plugin_kwargs: Dict, chatbot: List,
+              history: List, system_prompt: str, user_request: str):
+    """主函数 - 文件到文件处理"""
+    # 初始化
+    # 从高级参数中提取降重次数
+    if "advanced_arg" in plugin_kwargs and plugin_kwargs["advanced_arg"]:
+        # 检查是否包含降重次数的设置
+        match = re.search(r'reduction_times\s*=\s*(\d+)', plugin_kwargs["advanced_arg"])
+        if match:
+            reduction_times = int(match.group(1))
+            # 替换掉高级参数中的reduction_times设置，但保留其他内容
+            plugin_kwargs["advanced_arg"] = re.sub(r'reduction_times\s*=\s*\d+', '', plugin_kwargs["advanced_arg"]).strip()
+            # 添加到plugin_kwargs中作为单独的参数
+            plugin_kwargs["reduction_times"] = reduction_times
+
+    processor = DocumentProcessor(llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
+    chatbot.append(["函数插件功能", f"文件内容处理：将文档内容进行{processor.reduction_times}次降重处理"])
+
+    # 更新用户提示，提供关于降重策略的详细说明
+    if processor.reduction_times == 1:
+        chatbot.append(["降重策略", "将使用单次深度降重，这种方式能更有效地降低AI特征，减少查重率。我们采用特殊优化的提示词，通过一次性强力改写来实现降重效果。"])
+    elif processor.reduction_times > 1:
+        chatbot.append(["降重策略", f"将进行{processor.reduction_times}轮迭代降重，每轮降重都会基于上一轮的结果，并逐渐增加降重强度。请注意，多轮迭代可能会引入新的AI特征，单次强力降重通常效果更好。"])
+
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    # 验证输入路径
+    if not os.path.exists(txt):
+        report_exception(chatbot, history, a=f"解析路径: {txt}", b=f"找不到路径或无权访问: {txt}")
+        yield from update_ui(chatbot=chatbot, history=history)
+        return
+
+    # 验证路径安全性
+    user_name = chatbot.get_user()
+    validate_path_safety(txt, user_name)
+
+    # 获取文件列表
+    if os.path.isfile(txt):
+        # 单个文件处理
+        file_paths = [txt]
+    else:
+        # 目录处理 - 类似批量文件询问插件
+        project_folder = txt
+        extract_folder = next((d for d in glob.glob(f'{project_folder}/*')
+                           if os.path.isdir(d) and d.endswith('.extract')), project_folder)
+
+        # 排除压缩文件
+        exclude_patterns = r'/[^/]+\.(zip|rar|7z|tar|gz)$'
+        file_paths = [f for f in glob.glob(f'{extract_folder}/**', recursive=True)
+                     if os.path.isfile(f) and not re.search(exclude_patterns, f)]
+
+        # 过滤支持的文件格式
+        file_paths = [f for f in file_paths if any(f.lower().endswith(ext) for ext in
+                    list(processor.paper_extractor.SUPPORTED_EXTENSIONS) + ['.json', '.csv', '.xlsx', '.xls'])]
+
+    if not file_paths:
+        report_exception(chatbot, history, a=f"解析路径: {txt}", b="未找到支持的文件类型")
+        yield from update_ui(chatbot=chatbot, history=history)
+        return
+
+    # 处理文件
+    if len(file_paths) > 1:
+        chatbot.append(["发现多个文件", f"共找到 {len(file_paths)} 个文件，将处理第一个文件"])
+        yield from update_ui(chatbot=chatbot, history=history)
+
+    # 只处理第一个文件
+    file_to_process = file_paths[0]
+    processed_content = yield from processor.process_file(file_to_process)
+
+    if processed_content:
+        # 保存结果
+        result_files = processor.save_results(processed_content, file_to_process)
+
+        if result_files:
+            chatbot.append(["处理完成", f"已生成 {len(result_files)} 个结果文件"])
+        else:
+            chatbot.append(["处理完成", "但未能保存任何结果文件"])
+    else:
+        chatbot.append(["处理失败", "未能生成有效的处理结果"])
+
+    yield from update_ui(chatbot=chatbot, history=history)
--- a/crazy_functions/paper_fns/wiki/wikipedia_api.py
+++ b/crazy_functions/paper_fns/wiki/wikipedia_api.py
@@ -0,0 +1,387 @@
+import aiohttp
+import asyncio
+from typing import List, Dict, Optional
+import re
+import random
+import time
+
+class WikipediaAPI:
+    """维基百科API调用实现"""
+    
+    def __init__(self, language: str = "zh", user_agent: str = None, 
+                 max_concurrent: int = 5, request_delay: float = 0.5):
+        """
+        初始化维基百科API客户端
+        
+        Args:
+            language: 语言代码 (zh: 中文, en: 英文, ja: 日文等)
+            user_agent: 用户代理信息，如果为None将使用默认值
+            max_concurrent: 最大并发请求数
+            request_delay: 请求间隔时间(秒)
+        """
+        self.language = language
+        self.base_url = f"https://{language}.wikipedia.org/w/api.php"
+        self.user_agent = user_agent or "WikipediaAPIClient/1.0 (chatscholar@163.com)"
+        self.headers = {
+            "User-Agent": self.user_agent,
+            "Accept": "application/json"
+        }
+        # 添加并发控制
+        self.semaphore = asyncio.Semaphore(max_concurrent)
+        self.request_delay = request_delay
+        self.last_request_time = 0
+    
+    async def _make_request(self, url, params=None):
+        """
+        发起API请求，包含并发控制和请求延迟
+        
+        Args:
+            url: 请求URL
+            params: 请求参数
+            
+        Returns:
+            API响应数据
+        """
+        # 使用信号量控制并发
+        async with self.semaphore:
+            # 添加请求间隔
+            current_time = time.time()
+            time_since_last_request = current_time - self.last_request_time
+            if time_since_last_request < self.request_delay:
+                await asyncio.sleep(self.request_delay - time_since_last_request)
+            
+            # 设置随机延迟，避免规律性请求
+            jitter = random.uniform(0, 0.2)
+            await asyncio.sleep(jitter)
+            
+            # 记录本次请求时间
+            self.last_request_time = time.time()
+            
+            # 发起请求
+            try:
+                async with aiohttp.ClientSession(headers=self.headers) as session:
+                    async with session.get(url, params=params) as response:
+                        if response.status == 429:  # Too Many Requests
+                            retry_after = int(response.headers.get('Retry-After', 5))
+                            print(f"达到请求限制，等待 {retry_after} 秒后重试...")
+                            await asyncio.sleep(retry_after)
+                            return await self._make_request(url, params)
+                        
+                        if response.status != 200:
+                            print(f"API请求失败: HTTP {response.status}")
+                            print(f"响应内容: {await response.text()}")
+                            return None
+                        
+                        return await response.json()
+            except aiohttp.ClientError as e:
+                print(f"请求错误: {str(e)}")
+                return None
+    
+    async def search(self, query: str, limit: int = 10, namespace: int = 0) -> List[Dict]:
+        """
+        搜索维基百科文章
+        
+        Args:
+            query: 搜索关键词
+            limit: 返回结果数量
+            namespace: 命名空间 (0表示文章, 14表示分类等)
+            
+        Returns:
+            搜索结果列表
+        """
+        params = {
+            "action": "query",
+            "list": "search",
+            "srsearch": query,
+            "format": "json",
+            "srlimit": limit,
+            "srnamespace": namespace,
+            "srprop": "snippet|titlesnippet|sectiontitle|categorysnippet|size|wordcount|timestamp|redirecttitle"
+        }
+        
+        data = await self._make_request(self.base_url, params)
+        if not data:
+            return []
+        
+        search_results = data.get("query", {}).get("search", [])
+        return search_results
+    
+    async def get_page_content(self, title: str, section: Optional[int] = None) -> Dict:
+        """
+        获取维基百科页面内容
+        
+        Args:
+            title: 页面标题
+            section: 特定章节编号(可选)
+            
+        Returns:
+            页面内容字典
+        """
+        async with aiohttp.ClientSession(headers=self.headers) as session:
+            params = {
+                "action": "parse",
+                "page": title,
+                "format": "json",
+                "prop": "text|langlinks|categories|links|templates|images|externallinks|sections|revid|displaytitle|iwlinks|properties"
+            }
+            
+            # 如果指定了章节，只获取该章节内容
+            if section is not None:
+                params["section"] = section
+            
+            async with session.get(self.base_url, params=params) as response:
+                if response.status != 200:
+                    print(f"API请求失败: HTTP {response.status}")
+                    return {}
+                
+                data = await response.json()
+                if "error" in data:
+                    print(f"API错误: {data['error'].get('info', '未知错误')}")
+                    return {}
+                
+                return data.get("parse", {})
+    
+    async def get_summary(self, title: str, sentences: int = 3) -> str:
+        """
+        获取页面摘要
+        
+        Args:
+            title: 页面标题
+            sentences: 返回的句子数量
+            
+        Returns:
+            页面摘要文本
+        """
+        async with aiohttp.ClientSession(headers=self.headers) as session:
+            params = {
+                "action": "query",
+                "prop": "extracts",
+                "exintro": "1",
+                "exsentences": sentences,
+                "explaintext": "1",
+                "titles": title,
+                "format": "json"
+            }
+            
+            async with session.get(self.base_url, params=params) as response:
+                if response.status != 200:
+                    print(f"API请求失败: HTTP {response.status}")
+                    return ""
+                
+                data = await response.json()
+                pages = data.get("query", {}).get("pages", {})
+                # 获取第一个页面ID的内容
+                for page_id in pages:
+                    return pages[page_id].get("extract", "")
+                return ""
+    
+    async def get_random_articles(self, count: int = 1, namespace: int = 0) -> List[Dict]:
+        """
+        获取随机文章
+        
+        Args:
+            count: 需要的随机文章数量
+            namespace: 命名空间
+            
+        Returns:
+            随机文章列表
+        """
+        async with aiohttp.ClientSession(headers=self.headers) as session:
+            params = {
+                "action": "query",
+                "list": "random",
+                "rnlimit": count,
+                "rnnamespace": namespace,
+                "format": "json"
+            }
+            
+            async with session.get(self.base_url, params=params) as response:
+                if response.status != 200:
+                    print(f"API请求失败: HTTP {response.status}")
+                    return []
+                
+                data = await response.json()
+                return data.get("query", {}).get("random", [])
+
+    async def login(self, username: str, password: str) -> bool:
+        """
+        使用维基百科账户登录
+        
+        Args:
+            username: 维基百科用户名
+            password: 维基百科密码
+            
+        Returns:
+            登录是否成功
+        """
+        async with aiohttp.ClientSession(headers=self.headers) as session:
+            # 获取登录令牌
+            params = {
+                "action": "query",
+                "meta": "tokens",
+                "type": "login",
+                "format": "json"
+            }
+            
+            async with session.get(self.base_url, params=params) as response:
+                if response.status != 200:
+                    print(f"获取登录令牌失败: HTTP {response.status}")
+                    return False
+                
+                data = await response.json()
+                login_token = data.get("query", {}).get("tokens", {}).get("logintoken")
+                
+                if not login_token:
+                    print("获取登录令牌失败")
+                    return False
+                
+                # 使用令牌登录
+                login_params = {
+                    "action": "login",
+                    "lgname": username,
+                    "lgpassword": password,
+                    "lgtoken": login_token,
+                    "format": "json"
+                }
+                
+                async with session.post(self.base_url, data=login_params) as login_response:
+                    login_data = await login_response.json()
+                    
+                    if login_data.get("login", {}).get("result") == "Success":
+                        print(f"登录成功: {username}")
+                        return True
+                    else:
+                        print(f"登录失败: {login_data.get('login', {}).get('reason', '未知原因')}")
+                        return False
+
+    async def setup_oauth(self, consumer_token: str, consumer_secret: str, 
+                       access_token: str = None, access_secret: str = None) -> bool:
+        """
+        设置OAuth认证
+        
+        Args:
+            consumer_token: 消费者令牌
+            consumer_secret: 消费者密钥
+            access_token: 访问令牌（可选）
+            access_secret: 访问密钥（可选）
+            
+        Returns:
+            设置是否成功
+        """
+        try:
+            # 需要安装 mwoauth 库: pip install mwoauth
+            import mwoauth
+            import requests_oauthlib
+            
+            # 设置OAuth
+            self.consumer_token = consumer_token
+            self.consumer_secret = consumer_secret
+            
+            if access_token and access_secret:
+                # 如果已有访问令牌
+                self.auth = requests_oauthlib.OAuth1(
+                    consumer_token,
+                    consumer_secret,
+                    access_token,
+                    access_secret
+                )
+                print("OAuth设置成功")
+                return True
+            else:
+                # 需要获取访问令牌（这通常需要用户在网页上授权）
+                print("请在开发环境中完成以下OAuth授权流程:")
+                
+                # 创建消费者
+                consumer = mwoauth.Consumer(
+                    consumer_token, consumer_secret
+                )
+                
+                # 初始化握手
+                redirect, request_token = mwoauth.initiate(
+                    f"https://{self.language}.wikipedia.org/w/index.php",
+                    consumer
+                )
+                
+                print(f"请访问此URL授权应用: {redirect}")
+                # 这里通常会提示用户访问URL并输入授权码
+                # 实际应用中需要实现适当的授权流程
+                return False
+        except ImportError:
+            print("请安装 mwoauth 库: pip install mwoauth")
+            return False
+        except Exception as e:
+            print(f"设置OAuth时发生错误: {str(e)}")
+            return False
+
+async def example_usage():
+    """演示WikipediaAPI的使用方法"""
+    # 创建默认中文维基百科API客户端
+    wiki_zh = WikipediaAPI(language="zh")
+    
+    try:
+        # 示例1: 基本搜索
+        print("\n=== 示例1: 搜索维基百科 ===")
+        results = await wiki_zh.search("人工智能", limit=3)
+        
+        for i, result in enumerate(results, 1):
+            print(f"\n--- 结果 {i} ---")
+            print(f"标题: {result.get('title')}")
+            snippet = result.get('snippet', '')
+            # 清理HTML标签
+            snippet = re.sub(r'<.*?>', '', snippet)
+            print(f"摘要: {snippet}")
+            print(f"字数: {result.get('wordcount')}")
+            print(f"大小: {result.get('size')} 字节")
+
+        # 示例2: 获取页面摘要
+        print("\n=== 示例2: 获取页面摘要 ===")
+        summary = await wiki_zh.get_summary("深度学习", sentences=2)
+        print(f"深度学习摘要: {summary}")
+
+        # 示例3: 获取页面内容
+        print("\n=== 示例3: 获取页面内容 ===")
+        content = await wiki_zh.get_page_content("机器学习")
+        if content and "text" in content:
+            text = content["text"].get("*", "")
+            # 移除HTML标签以便控制台显示
+            clean_text = re.sub(r'<.*?>', '', text)
+            print(f"机器学习页面内容片段: {clean_text[:200]}...")
+            
+            # 显示页面包含的分类数量
+            categories = content.get("categories", [])
+            print(f"分类数量: {len(categories)}")
+            
+            # 显示页面包含的链接数量
+            links = content.get("links", [])
+            print(f"链接数量: {len(links)}")
+
+        # 示例4: 获取特定章节内容
+        print("\n=== 示例4: 获取特定章节内容 ===")
+        # 获取引言部分(通常是0号章节)
+        intro_content = await wiki_zh.get_page_content("人工智能", section=0)
+        if intro_content and "text" in intro_content:
+            intro_text = intro_content["text"].get("*", "")
+            clean_intro = re.sub(r'<.*?>', '', intro_text)
+            print(f"人工智能引言内容片段: {clean_intro[:200]}...")
+
+        # 示例5: 获取随机文章
+        print("\n=== 示例5: 获取随机文章 ===")
+        random_articles = await wiki_zh.get_random_articles(count=2)
+        print("随机文章:")
+        for i, article in enumerate(random_articles, 1):
+            print(f"{i}. {article.get('title')}")
+            
+            # 显示随机文章的简短摘要
+            article_summary = await wiki_zh.get_summary(article.get('title'), sentences=1)
+            print(f"   摘要: {article_summary[:100]}...")
+
+    except Exception as e:
+        print(f"发生错误: {str(e)}")
+        import traceback
+        print(traceback.format_exc())
+
+if __name__ == "__main__":
+    import asyncio
+    
+    # 运行示例
+    asyncio.run(example_usage()) 
--- a/crazy_functions/pdf_fns/breakdown_pdf_txt.py
+++ b/crazy_functions/pdf_fns/breakdown_pdf_txt.py
@@ -0,0 +1,275 @@
+from crazy_functions.ipc_fns.mp import run_in_subprocess_with_timeout
+from loguru import logger
+import time
+import re
+
+def force_breakdown(txt, limit, get_token_fn):
+    """ 当无法用标点、空行分割时，我们用最暴力的方法切割
+    """
+    for i in reversed(range(len(txt))):
+        if get_token_fn(txt[:i]) < limit:
+            return txt[:i], txt[i:]
+    return "Tiktoken未知错误", "Tiktoken未知错误"
+
+
+def maintain_storage(remain_txt_to_cut, remain_txt_to_cut_storage):
+    """ 为了加速计算，我们采样一个特殊的手段。当 remain_txt_to_cut > `_max` 时， 我们把 _max 后的文字转存至 remain_txt_to_cut_storage
+    当 remain_txt_to_cut < `_min` 时，我们再把 remain_txt_to_cut_storage 中的部分文字取出
+    """
+    _min = int(5e4)
+    _max = int(1e5)
+    # print(len(remain_txt_to_cut), len(remain_txt_to_cut_storage))
+    if len(remain_txt_to_cut) < _min and len(remain_txt_to_cut_storage) > 0:
+        remain_txt_to_cut = remain_txt_to_cut + remain_txt_to_cut_storage
+        remain_txt_to_cut_storage = ""
+    if len(remain_txt_to_cut) > _max:
+        remain_txt_to_cut_storage = remain_txt_to_cut[_max:] + remain_txt_to_cut_storage
+        remain_txt_to_cut = remain_txt_to_cut[:_max]
+    return remain_txt_to_cut, remain_txt_to_cut_storage
+
+
+def cut(limit, get_token_fn, txt_tocut, must_break_at_empty_line, break_anyway=False):
+    """ 文本切分
+    """
+    res = []
+    total_len = len(txt_tocut)
+    fin_len = 0
+    remain_txt_to_cut = txt_tocut
+    remain_txt_to_cut_storage = ""
+    # 为了加速计算，我们采样一个特殊的手段。当 remain_txt_to_cut > `_max` 时， 我们把 _max 后的文字转存至 remain_txt_to_cut_storage
+    remain_txt_to_cut, remain_txt_to_cut_storage = maintain_storage(remain_txt_to_cut, remain_txt_to_cut_storage)
+
+    while True:
+        if get_token_fn(remain_txt_to_cut) <= limit:
+            # 如果剩余文本的token数小于限制，那么就不用切了
+            res.append(remain_txt_to_cut); fin_len+=len(remain_txt_to_cut)
+            break
+        else:
+            # 如果剩余文本的token数大于限制，那么就切
+            lines = remain_txt_to_cut.split('\n')
+
+            # 估计一个切分点
+            estimated_line_cut = limit / get_token_fn(remain_txt_to_cut) * len(lines)
+            estimated_line_cut = int(estimated_line_cut)
+
+            # 开始查找合适切分点的偏移（cnt）
+            cnt = 0
+            for cnt in reversed(range(estimated_line_cut)):
+                if must_break_at_empty_line:
+                    # 首先尝试用双空行（\n\n）作为切分点
+                    if lines[cnt] != "":
+                        continue
+                prev = "\n".join(lines[:cnt])
+                post = "\n".join(lines[cnt:])
+                if get_token_fn(prev) < limit:
+                    break
+
+            if cnt == 0:
+                # 如果没有找到合适的切分点
+                if break_anyway:
+                    # 是否允许暴力切分
+                    prev, post = force_breakdown(remain_txt_to_cut, limit, get_token_fn)
+                else:
+                    # 不允许直接报错
+                    raise RuntimeError(f"存在一行极长的文本！{remain_txt_to_cut}")
+
+            # 追加列表
+            res.append(prev); fin_len+=len(prev)
+            # 准备下一次迭代
+            remain_txt_to_cut = post
+            remain_txt_to_cut, remain_txt_to_cut_storage = maintain_storage(remain_txt_to_cut, remain_txt_to_cut_storage)
+            process = fin_len/total_len
+            logger.info(f'正在文本切分 {int(process*100)}%')
+            if len(remain_txt_to_cut.strip()) == 0:
+                break
+    return res
+
+
+def breakdown_text_to_satisfy_token_limit_(txt, limit, llm_model="gpt-3.5-turbo"):
+    """ 使用多种方式尝试切分文本，以满足 token 限制
+    """
+    from request_llms.bridge_all import model_info
+    enc = model_info[llm_model]['tokenizer']
+    def get_token_fn(txt): return len(enc.encode(txt, disallowed_special=()))
+    try:
+        # 第1次尝试，将双空行（\n\n）作为切分点
+        return cut(limit, get_token_fn, txt, must_break_at_empty_line=True)
+    except RuntimeError:
+        try:
+            # 第2次尝试，将单空行（\n）作为切分点
+            return cut(limit, get_token_fn, txt, must_break_at_empty_line=False)
+        except RuntimeError:
+            try:
+                # 第3次尝试，将英文句号（.）作为切分点
+                res = cut(limit, get_token_fn, txt.replace('.', '。\n'), must_break_at_empty_line=False) # 这个中文的句号是故意的，作为一个标识而存在
+                return [r.replace('。\n', '.') for r in res]
+            except RuntimeError as e:
+                try:
+                    # 第4次尝试，将中文句号（。）作为切分点
+                    res = cut(limit, get_token_fn, txt.replace('。', '。。\n'), must_break_at_empty_line=False)
+                    return [r.replace('。。\n', '。') for r in res]
+                except RuntimeError as e:
+                    # 第5次尝试，没办法了，随便切一下吧
+                    return cut(limit, get_token_fn, txt, must_break_at_empty_line=False, break_anyway=True)
+
+breakdown_text_to_satisfy_token_limit = run_in_subprocess_with_timeout(breakdown_text_to_satisfy_token_limit_, timeout=60)
+
+def cut_new(limit, get_token_fn, txt_tocut, must_break_at_empty_line, must_break_at_one_empty_line=False, break_anyway=False):
+    """ 文本切分
+    """
+    res = []
+    res_empty_line = []
+    total_len = len(txt_tocut)
+    fin_len = 0
+    remain_txt_to_cut = txt_tocut
+    remain_txt_to_cut_storage = ""
+    # 为了加速计算，我们采样一个特殊的手段。当 remain_txt_to_cut > `_max` 时， 我们把 _max 后的文字转存至 remain_txt_to_cut_storage
+    remain_txt_to_cut, remain_txt_to_cut_storage = maintain_storage(remain_txt_to_cut, remain_txt_to_cut_storage)
+    empty=0
+
+    while True:
+        if get_token_fn(remain_txt_to_cut) <= limit:
+            # 如果剩余文本的token数小于限制，那么就不用切了
+            res.append(remain_txt_to_cut); fin_len+=len(remain_txt_to_cut)
+            res_empty_line.append(empty)
+            break
+        else:
+            # 如果剩余文本的token数大于限制，那么就切
+            lines = remain_txt_to_cut.split('\n')
+
+            # 估计一个切分点
+            estimated_line_cut = limit / get_token_fn(remain_txt_to_cut) * len(lines)
+            estimated_line_cut = int(estimated_line_cut)
+
+            # 开始查找合适切分点的偏移（cnt）
+            cnt = 0
+            for cnt in reversed(range(estimated_line_cut)):
+                if must_break_at_empty_line:
+                    # 首先尝试用双空行（\n\n）作为切分点
+                    if lines[cnt] != "":
+                        continue
+                if must_break_at_empty_line or must_break_at_one_empty_line:
+                    empty=1
+                prev = "\n".join(lines[:cnt])
+                post = "\n".join(lines[cnt:])
+                if get_token_fn(prev) < limit :
+                    break
+                    # empty=0
+                if get_token_fn(prev)>limit:
+                    if '.' not in prev or '。' not in prev:
+                        # empty = 0
+                        break
+
+            # if cnt
+            if cnt == 0:
+                # 如果没有找到合适的切分点
+                if break_anyway:
+                    # 是否允许暴力切分
+                    prev, post = force_breakdown(remain_txt_to_cut, limit, get_token_fn)
+                    empty =0
+                else:
+                    # 不允许直接报错
+                    raise RuntimeError(f"存在一行极长的文本！{remain_txt_to_cut}")
+
+            # 追加列表
+            res.append(prev); fin_len+=len(prev)
+            res_empty_line.append(empty)
+            # 准备下一次迭代
+            remain_txt_to_cut = post
+            remain_txt_to_cut, remain_txt_to_cut_storage = maintain_storage(remain_txt_to_cut, remain_txt_to_cut_storage)
+            process = fin_len/total_len
+            logger.info(f'正在文本切分 {int(process*100)}%')
+            if len(remain_txt_to_cut.strip()) == 0:
+                break
+    return res,res_empty_line
+
+
+def breakdown_text_to_satisfy_token_limit_new_(txt, limit, llm_model="gpt-3.5-turbo"):
+    """ 使用多种方式尝试切分文本，以满足 token 限制
+    """
+    from request_llms.bridge_all import model_info
+    enc = model_info[llm_model]['tokenizer']
+    def get_token_fn(txt): return len(enc.encode(txt, disallowed_special=()))
+    try:
+        # 第1次尝试，将双空行（\n\n）作为切分点
+        res, empty_line =cut_new(limit, get_token_fn, txt, must_break_at_empty_line=True)
+        return res,empty_line
+    except RuntimeError:
+        try:
+            # 第2次尝试，将单空行（\n）作为切分点
+            res, _ = cut_new(limit, get_token_fn, txt, must_break_at_empty_line=False,must_break_at_one_empty_line=True)
+            return res, _
+        except RuntimeError:
+            try:
+                # 第3次尝试，将英文句号（.）作为切分点
+                res, _ = cut_new(limit, get_token_fn, txt.replace('.', '。\n'), must_break_at_empty_line=False) # 这个中文的句号是故意的，作为一个标识而存在
+                return [r.replace('。\n', '.') for r in res],_
+
+            except RuntimeError as e:
+                try:
+                    # 第4次尝试，将中文句号（。）作为切分点
+                    res,_ = cut_new(limit, get_token_fn, txt.replace('。', '。。\n'), must_break_at_empty_line=False)
+                    return [r.replace('。。\n', '。') for r in res], _
+                except RuntimeError as e:
+                    # 第5次尝试，没办法了，随便切一下吧
+                    res, _ = cut_new(limit, get_token_fn, txt, must_break_at_empty_line=False, break_anyway=True)
+                    return res,_
+breakdown_text_to_satisfy_token_limit_new = run_in_subprocess_with_timeout(breakdown_text_to_satisfy_token_limit_new_, timeout=60)
+
+def cut_from_end_to_satisfy_token_limit_(txt, limit, reserve_token=500, llm_model="gpt-3.5-turbo"):
+    """从后往前裁剪文本，以论文为单位进行裁剪
+
+    参数：
+        txt: 要处理的文本（格式化后的论文列表字符串）
+        limit: token数量上限
+        reserve_token: 需要预留的token数量，默认500
+        llm_model: 使用的模型名称
+    返回：
+        裁剪后的文本
+    """
+    from request_llms.bridge_all import model_info
+    enc = model_info[llm_model]['tokenizer']
+    def get_token_fn(txt): return len(enc.encode(txt, disallowed_special=()))
+
+    # 计算当前文本的token数
+    current_tokens = get_token_fn(txt)
+    target_limit = limit - reserve_token
+
+    # 如果当前token数已经在限制范围内，直接返回
+    if current_tokens <= target_limit:
+        return txt
+
+    # 按论文编号分割文本
+    papers = re.split(r'\n(?=\d+\. \*\*)', txt)
+    if not papers:
+        return txt
+
+    # 从前往后累加论文，直到达到token限制
+    result = papers[0]  # 保留第一篇
+    current_tokens = get_token_fn(result)
+
+    for paper in papers[1:]:
+        paper_tokens = get_token_fn(paper)
+        if current_tokens + paper_tokens <= target_limit:
+            result += "\n" + paper
+            current_tokens += paper_tokens
+        else:
+            break
+
+    return result
+
+# 添加超时保护
+cut_from_end_to_satisfy_token_limit = run_in_subprocess_with_timeout(cut_from_end_to_satisfy_token_limit_, timeout=20)
+
+if __name__ == '__main__':
+    from crazy_functions.crazy_utils import read_and_clean_pdf_text
+    file_content, page_one = read_and_clean_pdf_text("build/assets/at.pdf")
+
+    from request_llms.bridge_all import model_info
+    for i in range(5):
+        file_content += file_content
+
+    logger.info(len(file_content))
+    TOKEN_LIMIT_PER_FRAGMENT = 2500
+    res = breakdown_text_to_satisfy_token_limit(file_content, TOKEN_LIMIT_PER_FRAGMENT)
+
--- a/crazy_functions/pdf_fns/parse_pdf.py
+++ b/crazy_functions/pdf_fns/parse_pdf.py
@@ -113,7 +113,7 @@ def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_fi
            return [txt]
        else:
            # raw_token_num > TOKEN_LIMIT_PER_FRAGMENT
-            # find a smooth token limit to achieve even seperation
+            # find a smooth token limit to achieve even separation
            count = int(math.ceil(raw_token_num / TOKEN_LIMIT_PER_FRAGMENT))
            token_limit_smooth = raw_token_num // count + count
            return breakdown_text_to_satisfy_token_limit(txt, limit=token_limit_smooth, llm_model=llm_kwargs['llm_model'])
--- a/crazy_functions/pdf_fns/parse_pdf_grobid.py
+++ b/crazy_functions/pdf_fns/parse_pdf_grobid.py
@@ -1,6 +1,6 @@
 import os
 from toolbox import CatchException, report_exception, get_log_folder, gen_time_str, check_packages
-from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
+from toolbox import update_ui, promote_file_to_downloadzone, update_ui_latest_msg, disable_auto_promotion
 from toolbox import write_history_to_file, promote_file_to_downloadzone, get_conf, extract_archive
 from crazy_functions.pdf_fns.parse_pdf import parse_pdf, translate_pdf

--- a/crazy_functions/pdf_fns/parse_word.py
+++ b/crazy_functions/pdf_fns/parse_word.py
@@ -14,17 +14,17 @@ def extract_text_from_files(txt, chatbot, history):
        final_result(list):文本内容
        page_one(list):第一页内容/摘要
        file_manifest(list):文件路径
-        excption(string):需要用户手动处理的信息,如没出错则保持为空
+        exception(string):需要用户手动处理的信息,如没出错则保持为空
    """

    final_result = []
    page_one = []
    file_manifest = []
-    excption = ""
+    exception = ""

    if txt == "":
        final_result.append(txt)
-        return False, final_result, page_one, file_manifest, excption   #如输入区内容不是文件则直接返回输入区内容
+        return False, final_result, page_one, file_manifest, exception   #如输入区内容不是文件则直接返回输入区内容

    #查找输入区内容中的文件
    file_pdf,pdf_manifest,folder_pdf = get_files_from_everything(txt, '.pdf')
@@ -33,20 +33,20 @@ def extract_text_from_files(txt, chatbot, history):
    file_doc,doc_manifest,folder_doc = get_files_from_everything(txt, '.doc')

    if file_doc:
-        excption = "word"
-        return False, final_result, page_one, file_manifest, excption
+        exception = "word"
+        return False, final_result, page_one, file_manifest, exception

    file_num = len(pdf_manifest) + len(md_manifest) + len(word_manifest)
    if file_num == 0:
        final_result.append(txt)
-        return False, final_result, page_one, file_manifest, excption   #如输入区内容不是文件则直接返回输入区内容
+        return False, final_result, page_one, file_manifest, exception   #如输入区内容不是文件则直接返回输入区内容

    if file_pdf:
        try:    # 尝试导入依赖，如果缺少依赖，则给出安装建议
            import fitz
        except:
-            excption = "pdf"
-            return False, final_result, page_one, file_manifest, excption
+            exception = "pdf"
+            return False, final_result, page_one, file_manifest, exception
        for index, fp in enumerate(pdf_manifest):
            file_content, pdf_one = read_and_clean_pdf_text(fp) # （尝试）按照章节切割PDF
            file_content = file_content.encode('utf-8', 'ignore').decode()   # avoid reading non-utf8 chars
@@ -72,8 +72,8 @@ def extract_text_from_files(txt, chatbot, history):
        try:    # 尝试导入依赖，如果缺少依赖，则给出安装建议
            from docx import Document
        except:
-            excption = "word_pip"
-            return False, final_result, page_one, file_manifest, excption
+            exception = "word_pip"
+            return False, final_result, page_one, file_manifest, exception
        for index, fp in enumerate(word_manifest):
            doc = Document(fp)
            file_content = '\n'.join([p.text for p in doc.paragraphs])
@@ -82,4 +82,4 @@ def extract_text_from_files(txt, chatbot, history):
            final_result.append(file_content)
            file_manifest.append(os.path.relpath(fp, folder_word))

-    return True, final_result, page_one, file_manifest, excption
+    return True, final_result, page_one, file_manifest, exception
--- a/crazy_functions/rag_fns/rag_file_support.py
+++ b/crazy_functions/rag_fns/rag_file_support.py
@@ -1,22 +1,48 @@
+import subprocess
 import os
-from llama_index.core import SimpleDirectoryReader

-supports_format = ['.csv', '.docx', '.epub', '.ipynb',  '.mbox', '.md', '.pdf',  '.txt', '.ppt',
-                   '.pptm', '.pptx']
+supports_format = ['.csv', '.docx', '.epub', '.ipynb',  '.mbox', '.md', '.pdf',  '.txt', '.ppt', '.pptm', '.pptx', '.bat']

+def convert_to_markdown(file_path: str) -> str:
+    """
+    将支持的文件格式转换为Markdown格式
+    Args:
+        file_path: 输入文件路径
+    Returns:
+        str: 转换后的Markdown文件路径，如果转换失败则返回原始文件路径
+    """
+    _, ext = os.path.splitext(file_path.lower())
+
+    if ext in ['.docx', '.doc', '.pptx', '.ppt', '.pptm', '.xls', '.xlsx', '.csv', 'pdf']:
+        try:
+            # 创建输出Markdown文件路径
+            md_path = os.path.splitext(file_path)[0] + '.md'
+            # 使用markitdown工具将文件转换为Markdown
+            command = f"markitdown {file_path} > {md_path}"
+            subprocess.run(command, shell=True, check=True)
+            print(f"已将{ext}文件转换为Markdown: {md_path}")
+            return md_path
+        except Exception as e:
+            print(f"{ext}转Markdown失败: {str(e)}，将继续处理原文件")
+            return file_path
+
+    return file_path

 # 修改后的 extract_text 函数，结合 SimpleDirectoryReader 和自定义解析逻辑
 def extract_text(file_path):
+    from llama_index.core import SimpleDirectoryReader
    _, ext = os.path.splitext(file_path.lower())

    # 使用 SimpleDirectoryReader 处理它支持的文件格式
    if ext in supports_format:
        try:
            reader = SimpleDirectoryReader(input_files=[file_path])
+            print(f"Extracting text from {file_path} using SimpleDirectoryReader")
            documents = reader.load_data()
-            if len(documents) > 0:
-                return documents[0].text
+            print(f"Complete: Extracting text from {file_path} using SimpleDirectoryReader")
+            buffer = [ doc.text for doc in documents ]
+            return '\n'.join(buffer)
        except Exception as e:
            pass
-
-    return None
+    else:
+        return '格式不支持'
--- a/crazy_functions/review_fns/init.py
+++ b/crazy_functions/review_fns/init.py
--- a/crazy_functions/review_fns/conversation_doc/endnote_doc.py
+++ b/crazy_functions/review_fns/conversation_doc/endnote_doc.py
@@ -0,0 +1,68 @@
+from typing import List
+from crazy_functions.review_fns.data_sources.base_source import PaperMetadata
+
+class EndNoteFormatter:
+    """EndNote参考文献格式生成器"""
+
+    def __init__(self):
+        pass
+
+    def create_document(self, papers: List[PaperMetadata]) -> str:
+        """生成EndNote格式的参考文献文本
+
+        Args:
+            papers: 论文列表
+
+        Returns:
+            str: EndNote格式的参考文献文本
+        """
+        endnote_text = ""
+
+        for paper in papers:
+            # 开始一个新条目
+            endnote_text += "%0 Journal Article\n"  # 默认类型为期刊文章
+
+            # 根据venue_type调整条目类型
+            if hasattr(paper, 'venue_type') and paper.venue_type:
+                if paper.venue_type.lower() == 'conference':
+                    endnote_text = endnote_text.replace("Journal Article", "Conference Paper")
+                elif paper.venue_type.lower() == 'preprint':
+                    endnote_text = endnote_text.replace("Journal Article", "Electronic Article")
+
+            # 添加标题
+            endnote_text += f"%T {paper.title}\n"
+
+            # 添加作者
+            for author in paper.authors:
+                endnote_text += f"%A {author}\n"
+
+            # 添加年份
+            if paper.year:
+                endnote_text += f"%D {paper.year}\n"
+
+            # 添加期刊/会议名称
+            if hasattr(paper, 'venue_name') and paper.venue_name:
+                endnote_text += f"%J {paper.venue_name}\n"
+            elif paper.venue:
+                endnote_text += f"%J {paper.venue}\n"
+
+            # 添加DOI
+            if paper.doi:
+                endnote_text += f"%R {paper.doi}\n"
+                endnote_text += f"%U https://doi.org/{paper.doi}\n"
+            elif paper.url:
+                endnote_text += f"%U {paper.url}\n"
+
+            # 添加摘要
+            if paper.abstract:
+                endnote_text += f"%X {paper.abstract}\n"
+
+            # 添加机构
+            if hasattr(paper, 'institutions'):
+                for institution in paper.institutions:
+                    endnote_text += f"%I {institution}\n"
+
+            # 条目之间添加空行
+            endnote_text += "\n"
+
+        return endnote_text
--- a/crazy_functions/review_fns/conversation_doc/excel_doc.py
+++ b/crazy_functions/review_fns/conversation_doc/excel_doc.py
@@ -0,0 +1,211 @@
+import re
+import os
+import pandas as pd
+from datetime import datetime
+
+
+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"""
+        from openpyxl import Workbook
+        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)
--- a/crazy_functions/review_fns/conversation_doc/html_doc.py
+++ b/crazy_functions/review_fns/conversation_doc/html_doc.py
@@ -0,0 +1,472 @@
+class HtmlFormatter:
+    """聊天记录HTML格式生成器"""
+    
+    def __init__(self):
+        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 create_document(self, question: str, answer: str, ranked_papers: list = None) -> str:
+        """生成完整的HTML文档
+        Args:
+            question: str, 用户问题
+            answer: str, AI回答
+            ranked_papers: list, 排序后的论文列表
+        Returns:
+            str: 完整的HTML文档字符串
+        """
+        chat_content = f'''
+        <div class="QaBox">
+            <div class="Question">{question}</div>
+            <div class="Answer markdown-body" id="answer-content">{answer}</div>
+        </div>
+        '''
+
+        references_content = ""
+        if ranked_papers:
+            references_content = '<div class="history-section"><h2 class="history-title">参考文献</h2>'
+            for idx, paper in enumerate(ranked_papers, 1):
+                authors = ', '.join(paper.authors)
+                
+                # 构建引用信息
+                citations_info = f"被引用次数：{paper.citations}" if paper.citations is not None else "引用信息未知"
+                
+                # 构建下载链接
+                download_links = []
+                if paper.doi:
+                    # 检查是否是arXiv链接
+                    if 'arxiv.org' in paper.doi:
+                        # 如果DOI中包含完整的arXiv URL，直接使用
+                        arxiv_url = paper.doi if paper.doi.startswith('http') else f'http://{paper.doi}'
+                        download_links.append(f'<a href="{arxiv_url}">arXiv链接</a>')
+                        # 提取arXiv ID并添加PDF链接
+                        arxiv_id = arxiv_url.split('abs/')[-1].split('v')[0]
+                        download_links.append(f'<a href="https://arxiv.org/pdf/{arxiv_id}.pdf">PDF下载</a>')
+                    else:
+                        # 非arXiv的DOI使用标准格式
+                        download_links.append(f'<a href="https://doi.org/{paper.doi}">DOI: {paper.doi}</a>')
+
+                if hasattr(paper, 'url') and paper.url and 'arxiv.org' not in str(paper.url):
+                    # 只有当URL不是arXiv链接时才添加
+                    download_links.append(f'<a href="{paper.url}">原文链接</a>')
+                download_section = ' | '.join(download_links) if download_links else "无直接下载链接"
+                
+                # 构建来源信息
+                source_info = []
+                if paper.venue_type:
+                    source_info.append(f"类型：{paper.venue_type}")
+                if paper.venue_name:
+                    source_info.append(f"来源：{paper.venue_name}")
+                    
+                # 添加期刊指标信息
+                if hasattr(paper, 'if_factor') and paper.if_factor:
+                    source_info.append(f"<span class='journal-metric'>IF: {paper.if_factor}</span>")
+                if hasattr(paper, 'jcr_division') and paper.jcr_division:
+                    source_info.append(f"<span class='journal-metric'>JCR分区: {paper.jcr_division}</span>")
+                if hasattr(paper, 'cas_division') and paper.cas_division:
+                    source_info.append(f"<span class='journal-metric'>中科院分区: {paper.cas_division}</span>")
+                    
+                if hasattr(paper, 'venue_info') and paper.venue_info:
+                    if paper.venue_info.get('journal_ref'):
+                        source_info.append(f"期刊参考：{paper.venue_info['journal_ref']}")
+                    if paper.venue_info.get('publisher'):
+                        source_info.append(f"出版商：{paper.venue_info['publisher']}")
+                source_section = ' | '.join(source_info) if source_info else ""
+
+                # 构建标准引用格式
+                standard_citation = f"[{idx}] "
+                # 添加作者（最多3个，超过则添加et al.）
+                author_list = paper.authors[:3]
+                if len(paper.authors) > 3:
+                    author_list.append("et al.")
+                standard_citation += ", ".join(author_list) + ". "
+                # 添加标题
+                standard_citation += f"<i>{paper.title}</i>"
+                # 添加期刊/会议名称
+                if paper.venue_name:
+                    standard_citation += f". {paper.venue_name}"
+                # 添加年份
+                if paper.year:
+                    standard_citation += f", {paper.year}"
+                # 添加DOI
+                if paper.doi:
+                    if 'arxiv.org' in paper.doi:
+                        # 如果是arXiv链接，直接使用arXiv URL
+                        arxiv_url = paper.doi if paper.doi.startswith('http') else f'http://{paper.doi}'
+                        standard_citation += f". {arxiv_url}"
+                    else:
+                        # 非arXiv的DOI使用标准格式
+                        standard_citation += f". DOI: {paper.doi}"
+                standard_citation += "."
+                
+                references_content += f'''
+                <div class="historyBox">
+                    <div class="entry">
+                        <p class="paper-title"><b>[{idx}]</b> <i>{paper.title}</i></p>
+                        <p class="paper-authors">作者：{authors}</p>
+                        <p class="paper-year">发表年份：{paper.year if paper.year else "未知"}</p>
+                        <p class="paper-citations">{citations_info}</p>
+                        {f'<p class="paper-source">{source_section}</p>' if source_section else ""}
+                        <p class="paper-abstract">摘要：{paper.abstract if paper.abstract else "无摘要"}</p>
+                        <p class="paper-links">链接：{download_section}</p>
+                        <div class="standard-citation">
+                            <p class="citation-title">标准引用格式：</p>
+                            <p class="citation-text">{standard_citation}</p>
+                            <button class="copy-btn" onclick="copyToClipboard(this.previousElementSibling)">复制引用格式</button>
+                        </div>
+                    </div>
+                </div>
+                '''
+            references_content += '</div>'
+
+        # 添加新的CSS样式
+        css_additions = """
+            .paper-title {
+                font-size: 1.1em;
+                margin-bottom: 0.5em;
+            }
+            .paper-authors {
+                color: var(--secondary-color);
+                margin: 0.3em 0;
+            }
+            .paper-year, .paper-citations {
+                color: var(--text-color);
+                margin: 0.3em 0;
+            }
+            .paper-source {
+                color: var(--text-color);
+                font-style: italic;
+                margin: 0.3em 0;
+            }
+            .paper-abstract {
+                margin: 0.8em 0;
+                padding: 0.8em;
+                background: var(--primary-light);
+                border-radius: 4px;
+            }
+            .paper-links {
+                margin-top: 0.5em;
+            }
+            .paper-links a {
+                color: var(--primary-color);
+                text-decoration: none;
+                margin-right: 1em;
+            }
+            .paper-links a:hover {
+                text-decoration: underline;
+            }
+            .standard-citation {
+                margin-top: 1em;
+                padding: 1em;
+                background: #f8fafc;
+                border-radius: 4px;
+                border: 1px solid var(--border-color);
+            }
+            
+            .citation-title {
+                font-weight: bold;
+                margin-bottom: 0.5em;
+                color: var(--secondary-color);
+            }
+            
+            .citation-text {
+                font-family: 'Times New Roman', Times, serif;
+                line-height: 1.6;
+                margin-bottom: 0.5em;
+                padding: 0.5em;
+                background: white;
+                border-radius: 4px;
+                border: 1px solid var(--border-color);
+            }
+            
+            .copy-btn {
+                background: var(--primary-color);
+                color: white;
+                border: none;
+                padding: 0.5em 1em;
+                border-radius: 4px;
+                cursor: pointer;
+                font-size: 0.9em;
+                transition: background-color 0.2s;
+            }
+            
+            .copy-btn:hover {
+                background: #1e40af;
+            }
+            
+            @media (prefers-color-scheme: dark) {
+                .standard-citation {
+                    background: #1e293b;
+                }
+                .citation-text {
+                    background: #0f172a;
+                }
+            }
+            
+            /* 添加期刊指标样式 */
+            .journal-metric {
+                display: inline-block;
+                padding: 0.2em 0.6em;
+                margin: 0 0.3em;
+                background: var(--primary-light);
+                border-radius: 4px;
+                font-weight: 500;
+                color: var(--primary-color);
+            }
+            
+            @media (prefers-color-scheme: dark) {
+                .journal-metric {
+                    background: #1e293b;
+                    color: #60a5fa;
+                }
+            }
+        """
+        
+        # 修改 js_code 部分，添加 markdown 解析功能
+        js_code = """
+        <script>
+        // 复制功能
+        function copyToClipboard(element) {
+            const text = element.innerText;
+            navigator.clipboard.writeText(text).then(function() {
+                const btn = element.nextElementSibling;
+                const originalText = btn.innerText;
+                btn.innerText = '已复制！';
+                setTimeout(() => {
+                    btn.innerText = originalText;
+                }, 2000);
+            }).catch(function(err) {
+                console.error('复制失败:', err);
+            });
+        }
+
+        // Markdown解析
+        document.addEventListener('DOMContentLoaded', function() {
+            const answerContent = document.getElementById('answer-content');
+            if (answerContent) {
+                const markdown = answerContent.textContent;
+                answerContent.innerHTML = marked.parse(markdown);
+            }
+        });
+        </script>
+        """
+
+        # 将新的CSS样式添加到现有样式中
+        self.css_styles += css_additions
+
+        return f"""
+        <!DOCTYPE html>
+        <html lang="zh-CN">
+        <head>
+            <meta charset="utf-8">
+            <meta name="viewport" content="width=device-width, initial-scale=1">
+            <title>学术对话存档</title>
+            <!-- 添加 marked.js -->
+            <script src="https://cdn.jsdelivr.net/npm/marked/marked.min.js"></script>
+            <!-- 添加 GitHub Markdown CSS -->
+            <link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/sindresorhus/github-markdown-css@4.0.0/github-markdown.min.css">
+            <style>
+                {self.css_styles}
+                /* 添加 Markdown 相关样式 */
+                .markdown-body {{
+                    font-family: system-ui, -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
+                    padding: 1rem;
+                    background: var(--primary-light);
+                    border-radius: 6px;
+                }}
+                .markdown-body pre {{
+                    background-color: #f6f8fa;
+                    border-radius: 6px;
+                    padding: 16px;
+                    overflow: auto;
+                }}
+                .markdown-body code {{
+                    background-color: rgba(175,184,193,0.2);
+                    border-radius: 6px;
+                    padding: 0.2em 0.4em;
+                    font-size: 85%;
+                }}
+                .markdown-body pre code {{
+                    background-color: transparent;
+                    padding: 0;
+                }}
+                .markdown-body blockquote {{
+                    border-left: 0.25em solid #d0d7de;
+                    padding: 0 1em;
+                    color: #656d76;
+                }}
+                .markdown-body table {{
+                    border-collapse: collapse;
+                    width: 100%;
+                    margin: 1em 0;
+                }}
+                .markdown-body table th,
+                .markdown-body table td {{
+                    border: 1px solid #d0d7de;
+                    padding: 6px 13px;
+                }}
+                .markdown-body table tr:nth-child(2n) {{
+                    background-color: #f6f8fa;
+                }}
+                @media (prefers-color-scheme: dark) {{
+                    .markdown-body {{
+                        background: #1e293b;
+                        color: #e2e8f0;
+                    }}
+                    .markdown-body pre {{
+                        background-color: #0f172a;
+                    }}
+                    .markdown-body code {{
+                        background-color: rgba(99,110,123,0.4);
+                    }}
+                    .markdown-body blockquote {{
+                        border-left-color: #30363d;
+                        color: #8b949e;
+                    }}
+                    .markdown-body table th,
+                    .markdown-body table td {{
+                        border-color: #30363d;
+                    }}
+                    .markdown-body table tr:nth-child(2n) {{
+                        background-color: #0f172a;
+                    }}
+                }}
+            </style>
+        </head>
+        <body>
+            <div class="container">
+                <h1 class="chat-title">学术对话存档</h1>
+                <div class="chat-body">
+                    {chat_content}
+                    {references_content}
+                </div>
+            </div>
+            {js_code}
+        </body>
+        </html>
+        """
--- a/crazy_functions/review_fns/conversation_doc/markdown_doc.py
+++ b/crazy_functions/review_fns/conversation_doc/markdown_doc.py
@@ -0,0 +1,47 @@
+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, question: str, answer: str, ranked_papers: list = None) -> str:
+        """创建完整的Markdown文档
+        Args:
+            question: str, 用户问题
+            answer: str, AI回答
+            ranked_papers: list, 排序后的论文列表
+        Returns:
+            str: 生成的Markdown文本
+        """
+        content = []
+
+        # 添加问答部分
+        content.append("## 问题")
+        content.append(question)
+        content.append("\n## 回答")
+        content.append(answer)
+
+        # 添加参考文献
+        if ranked_papers:
+            content.append("\n## 参考文献")
+            for idx, paper in enumerate(ranked_papers, 1):
+                authors = ', '.join(paper.authors[:3])
+                if len(paper.authors) > 3:
+                    authors += ' et al.'
+
+                ref = f"[{idx}] {authors}. *{paper.title}*"
+                if paper.venue_name:
+                    ref += f". {paper.venue_name}"
+                if paper.year:
+                    ref += f", {paper.year}"
+                if paper.doi:
+                    ref += f". [DOI: {paper.doi}](https://doi.org/{paper.doi})"
+
+                content.append(ref)
+
+        return "\n\n".join(content)
--- a/crazy_functions/review_fns/conversation_doc/reference_formatter.py
+++ b/crazy_functions/review_fns/conversation_doc/reference_formatter.py
@@ -0,0 +1,174 @@
+from typing import List
+from crazy_functions.review_fns.data_sources.base_source import PaperMetadata
+import re
+
+class ReferenceFormatter:
+    """通用参考文献格式生成器"""
+
+    def __init__(self):
+        pass
+
+    def _sanitize_bibtex(self, text: str) -> str:
+        """清理BibTeX字符串，处理特殊字符"""
+        if not text:
+            return ""
+
+        # 替换特殊字符
+        replacements = {
+            '&': '\\&',
+            '%': '\\%',
+            '$': '\\$',
+            '#': '\\#',
+            '_': '\\_',
+            '{': '\\{',
+            '}': '\\}',
+            '~': '\\textasciitilde{}',
+            '^': '\\textasciicircum{}',
+            '\\': '\\textbackslash{}',
+            '<': '\\textless{}',
+            '>': '\\textgreater{}',
+            '"': '``',
+            "'": "'",
+            '-': '--',
+            '—': '---',
+        }
+
+        for char, replacement in replacements.items():
+            text = text.replace(char, replacement)
+
+        return text
+
+    def _generate_cite_key(self, paper: PaperMetadata) -> str:
+        """生成引用键
+        格式: 第一作者姓氏_年份_第一个实词
+        """
+        # 获取第一作者姓氏
+        first_author = ""
+        if paper.authors and len(paper.authors) > 0:
+            first_author = paper.authors[0].split()[-1].lower()
+
+        # 获取年份
+        year = str(paper.year) if paper.year else "0000"
+
+        # 从标题中获取第一个实词
+        title_word = ""
+        if paper.title:
+            # 移除特殊字符，分割成单词
+            words = re.findall(r'\w+', paper.title.lower())
+            # 过滤掉常见的停用词
+            stop_words = {'a', 'an', 'the', 'in', 'on', 'at', 'to', 'for', 'of', 'with', 'by'}
+            for word in words:
+                if word not in stop_words and len(word) > 2:
+                    title_word = word
+                    break
+
+        # 组合cite key
+        cite_key = f"{first_author}{year}{title_word}"
+
+        # 确保cite key只包含合法字符
+        cite_key = re.sub(r'[^a-z0-9]', '', cite_key.lower())
+
+        return cite_key
+
+    def _get_entry_type(self, paper: PaperMetadata) -> str:
+        """确定BibTeX条目类型"""
+        if hasattr(paper, 'venue_type') and paper.venue_type:
+            venue_type = paper.venue_type.lower()
+            if venue_type == 'conference':
+                return 'inproceedings'
+            elif venue_type == 'preprint':
+                return 'unpublished'
+            elif venue_type == 'journal':
+                return 'article'
+            elif venue_type == 'book':
+                return 'book'
+            elif venue_type == 'thesis':
+                return 'phdthesis'
+        return 'article'  # 默认为期刊文章
+
+
+    def create_document(self, papers: List[PaperMetadata]) -> str:
+        """生成BibTeX格式的参考文献文本"""
+        bibtex_text = "% This file was automatically generated by GPT-Academic\n"
+        bibtex_text += "% Compatible with: EndNote, Zotero, JabRef, and LaTeX\n\n"
+
+        for paper in papers:
+            entry_type = self._get_entry_type(paper)
+            cite_key = self._generate_cite_key(paper)
+
+            bibtex_text += f"@{entry_type}{{{cite_key},\n"
+
+            # 添加标题
+            if paper.title:
+                bibtex_text += f"  title = {{{self._sanitize_bibtex(paper.title)}}},\n"
+
+            # 添加作者
+            if paper.authors:
+                # 确保每个作者的姓和名正确分隔
+                processed_authors = []
+                for author in paper.authors:
+                    names = author.split()
+                    if len(names) > 1:
+                        # 假设最后一个词是姓，其他的是名
+                        surname = names[-1]
+                        given_names = ' '.join(names[:-1])
+                        processed_authors.append(f"{surname}, {given_names}")
+                    else:
+                        processed_authors.append(author)
+
+                authors = " and ".join([self._sanitize_bibtex(author) for author in processed_authors])
+                bibtex_text += f"  author = {{{authors}}},\n"
+
+            # 添加年份
+            if paper.year:
+                bibtex_text += f"  year = {{{paper.year}}},\n"
+
+            # 添加期刊/会议名称
+            if hasattr(paper, 'venue_name') and paper.venue_name:
+                if entry_type == 'inproceedings':
+                    bibtex_text += f"  booktitle = {{{self._sanitize_bibtex(paper.venue_name)}}},\n"
+                elif entry_type == 'article':
+                    bibtex_text += f"  journal = {{{self._sanitize_bibtex(paper.venue_name)}}},\n"
+                    # 添加期刊相关信息
+                    if hasattr(paper, 'venue_info'):
+                        if 'volume' in paper.venue_info:
+                            bibtex_text += f"  volume = {{{paper.venue_info['volume']}}},\n"
+                        if 'number' in paper.venue_info:
+                            bibtex_text += f"  number = {{{paper.venue_info['number']}}},\n"
+                        if 'pages' in paper.venue_info:
+                            bibtex_text += f"  pages = {{{paper.venue_info['pages']}}},\n"
+            elif paper.venue:
+                venue_field = "booktitle" if entry_type == "inproceedings" else "journal"
+                bibtex_text += f"  {venue_field} = {{{self._sanitize_bibtex(paper.venue)}}},\n"
+
+            # 添加DOI
+            if paper.doi:
+                bibtex_text += f"  doi = {{{paper.doi}}},\n"
+
+            # 添加URL
+            if paper.url:
+                bibtex_text += f"  url = {{{paper.url}}},\n"
+            elif paper.doi:
+                bibtex_text += f"  url = {{https://doi.org/{paper.doi}}},\n"
+
+            # 添加摘要
+            if paper.abstract:
+                bibtex_text += f"  abstract = {{{self._sanitize_bibtex(paper.abstract)}}},\n"
+
+            # 添加机构
+            if hasattr(paper, 'institutions') and paper.institutions:
+                institutions = " and ".join([self._sanitize_bibtex(inst) for inst in paper.institutions])
+                bibtex_text += f"  institution = {{{institutions}}},\n"
+
+            # 添加月份
+            if hasattr(paper, 'month'):
+                bibtex_text += f"  month = {{{paper.month}}},\n"
+
+            # 添加注释字段
+            if hasattr(paper, 'note'):
+                bibtex_text += f"  note = {{{self._sanitize_bibtex(paper.note)}}},\n"
+
+            # 移除最后一个逗号并关闭条目
+            bibtex_text = bibtex_text.rstrip(',\n') + "\n}\n\n"
+
+        return bibtex_text
--- a/crazy_functions/review_fns/conversation_doc/word2pdf.py
+++ b/crazy_functions/review_fns/conversation_doc/word2pdf.py
@@ -0,0 +1,138 @@
+from docx2pdf import convert
+import os
+import platform
+from typing import Union
+from pathlib import Path
+from datetime import datetime
+
+class WordToPdfConverter:
+    """Word文档转PDF转换器"""
+
+    @staticmethod
+    def _replace_docx_in_filename(filename: Union[str, Path]) -> Path:
+        """
+        将文件名中的'docx'替换为'pdf'
+        例如: 'docx_test.pdf' -> 'pdf_test.pdf'
+        """
+        path = Path(filename)
+        new_name = path.stem.replace('docx', 'pdf')
+        return path.parent / f"{new_name}{path.suffix}"
+
+    @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:
+            word_path = Path(word_path)
+
+            if pdf_path is None:
+                # 创建新的pdf路径，同时替换文件名中的docx
+                pdf_path = WordToPdfConverter._replace_docx_in_filename(word_path).with_suffix('.pdf')
+            else:
+                pdf_path = WordToPdfConverter._replace_docx_in_filename(Path(pdf_path))
+
+            # 检查操作系统
+            if platform.system() == 'Linux':
+                # Linux系统需要安装libreoffice
+                if not os.system('which libreoffice') == 0:
+                    raise RuntimeError("请先安装LibreOffice: sudo apt-get install libreoffice")
+
+                # 使用libreoffice进行转换
+                os.system(f'libreoffice --headless --convert-to pdf "{word_path}" --outdir "{pdf_path.parent}"')
+
+                # 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:
+                    os.rename(default_pdf, pdf_path)
+            else:
+                # Windows和MacOS使用 docx2pdf
+                convert(word_path, pdf_path)
+
+            return str(pdf_path)
+
+        except Exception as 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 / WordToPdfConverter._replace_docx_in_filename(
+                        word_file.with_suffix('.pdf')
+                    ).name
+                else:
+                    pdf_path = WordToPdfConverter._replace_docx_in_filename(
+                        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)}")
--- a/crazy_functions/review_fns/conversation_doc/word_doc.py
+++ b/crazy_functions/review_fns/conversation_doc/word_doc.py
@@ -0,0 +1,246 @@
+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
+import docx
+from docx.oxml import shared
+from crazy_functions.doc_fns.conversation_doc.word_doc import convert_markdown_to_word
+
+
+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)
+
+            # 修改页眉
+            header = section.header
+            header_para = header.paragraphs[0]
+            header_para.alignment = WD_PARAGRAPH_ALIGNMENT.CENTER
+            header_run = header_para.add_run("GPT-Academic学术对话 (体验地址：https://auth.gpt-academic.top/)")
+            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)
+        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)  # 参考文献标题与问题同样大小
+        ref_title_style.font.bold = True
+        ref_title_style.paragraph_format.space_before = Pt(24)  # 增加段前距
+        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, question: str, answer: str, ranked_papers: list = None):
+        """写入聊天历史
+        Args:
+            question: str, 用户问题
+            answer: str, AI回答
+            ranked_papers: list, 排序后的论文列表
+        """
+        try:
+            # 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
+            try:
+                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)
+            except Exception as e:
+                print(f"添加日期失败: {str(e)}")
+                raise
+
+            self.doc.add_paragraph()  # 添加空行
+
+            # 添加问答对话
+            try:
+                q_para = self.doc.add_paragraph(style='Question_Style')
+                q_para.add_run('问题：').bold = True
+                q_para.add_run(str(question))
+
+                a_para = self.doc.add_paragraph(style='Answer_Style')
+                a_para.add_run('回答：').bold = True
+                a_para.add_run(convert_markdown_to_word(str(answer)))
+            except Exception as e:
+                print(f"添加问答对话失败: {str(e)}")
+                raise
+
+            # 添加参考文献部分
+            if ranked_papers:
+                try:
+                    ref_title = self.doc.add_paragraph(style='Reference_Title_Style')
+                    ref_title.add_run("参考文献")
+                    
+                    for idx, paper in enumerate(ranked_papers, 1):
+                        try:
+                            ref_para = self.doc.add_paragraph(style='Reference_Style')
+                            ref_para.add_run(f'[{idx}] ').bold = True
+                            
+                            # 添加作者
+                            authors = ', '.join(paper.authors[:3])
+                            if len(paper.authors) > 3:
+                                authors += ' et al.'
+                            ref_para.add_run(f'{authors}. ')
+                            
+                            # 添加标题
+                            title_run = ref_para.add_run(paper.title)
+                            title_run.italic = True
+                            if hasattr(paper, 'url') and paper.url:
+                                try:
+                                    title_run._element.rPr.rStyle = self._create_hyperlink_style()
+                                    self._add_hyperlink(ref_para, paper.title, paper.url)
+                                except Exception as e:
+                                    print(f"添加超链接失败: {str(e)}")
+                            
+                            # 添加期刊/会议信息
+                            if paper.venue_name:
+                                ref_para.add_run(f'. {paper.venue_name}')
+                            
+                            # 添加年份
+                            if paper.year:
+                                ref_para.add_run(f', {paper.year}')
+                            
+                            # 添加DOI
+                            if paper.doi:
+                                ref_para.add_run('. ')
+                                if "arxiv" in paper.url:
+                                    doi_url = paper.doi
+                                else:   
+                                    doi_url = f'https://doi.org/{paper.doi}'
+                                self._add_hyperlink(ref_para, f'DOI: {paper.doi}', doi_url)
+                            
+                            ref_para.add_run('.')
+                        except Exception as e:
+                            print(f"添加第 {idx} 篇参考文献失败: {str(e)}")
+                            continue
+                except Exception as e:
+                    print(f"添加参考文献部分失败: {str(e)}")
+                    raise
+
+            return self.doc
+        
+        except Exception as e:
+            print(f"Word文档创建失败: {str(e)}")
+            import traceback
+            print(f"详细错误信息: {traceback.format_exc()}")
+            raise
+
+    def _create_hyperlink_style(self):
+        """创建超链接样式"""
+        styles = self.doc.styles
+        if 'Hyperlink' not in styles:
+            hyperlink_style = styles.add_style('Hyperlink', WD_STYLE_TYPE.CHARACTER)
+            # 使用科技蓝 (#0066CC)
+            hyperlink_style.font.color.rgb = 0x0066CC  # 科技蓝
+            hyperlink_style.font.underline = True
+        return styles['Hyperlink']
+
+    def _add_hyperlink(self, paragraph, text, url):
+        """添加超链接到段落"""
+        # 这个是在XML级别添加超链接
+        part = paragraph.part
+        r_id = part.relate_to(url, docx.opc.constants.RELATIONSHIP_TYPE.HYPERLINK, is_external=True)
+        
+        # 创建超链接XML元素
+        hyperlink = docx.oxml.shared.OxmlElement('w:hyperlink')
+        hyperlink.set(docx.oxml.shared.qn('r:id'), r_id)
+        
+        # 创建文本运行
+        new_run = docx.oxml.shared.OxmlElement('w:r')
+        rPr = docx.oxml.shared.OxmlElement('w:rPr')
+        
+        # 应用超链接样式
+        rStyle = docx.oxml.shared.OxmlElement('w:rStyle')
+        rStyle.set(docx.oxml.shared.qn('w:val'), 'Hyperlink')
+        rPr.append(rStyle)
+        
+        # 添加文本
+        t = docx.oxml.shared.OxmlElement('w:t')
+        t.text = text
+        new_run.append(rPr)
+        new_run.append(t)
+        hyperlink.append(new_run)
+        
+        # 将超链接添加到段落
+        paragraph._p.append(hyperlink)
+
--- a/crazy_functions/review_fns/data_sources/init.py
+++ b/crazy_functions/review_fns/data_sources/init.py
--- a/crazy_functions/review_fns/data_sources/adsabs_source.py
+++ b/crazy_functions/review_fns/data_sources/adsabs_source.py
@@ -0,0 +1,279 @@
+from typing import List, Optional, Dict, Union
+from datetime import datetime
+import aiohttp
+import asyncio
+from crazy_functions.review_fns.data_sources.base_source import DataSource, PaperMetadata
+import json
+from tqdm import tqdm
+import random
+
+class AdsabsSource(DataSource):
+    """ADS (Astrophysics Data System) API实现"""
+
+    # 定义API密钥列表
+    API_KEYS = [
+        "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
+        "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
+        "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
+    ]
+
+    def __init__(self, api_key: str = None):
+        """初始化
+
+        Args:
+            api_key: ADS API密钥，如果不提供则从预定义列表中随机选择
+        """
+        self.api_key = api_key or random.choice(self.API_KEYS)  # 随机选择一个API密钥
+        self._initialize()
+
+    def _initialize(self) -> None:
+        """初始化基础URL和请求头"""
+        self.base_url = "https://api.adsabs.harvard.edu/v1"
+        self.headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json"
+        }
+
+    async def _make_request(self, url: str, method: str = "GET", data: dict = None) -> Optional[dict]:
+        """发送HTTP请求
+
+        Args:
+            url: 请求URL
+            method: HTTP方法
+            data: POST请求数据
+
+        Returns:
+            响应内容
+        """
+        try:
+            async with aiohttp.ClientSession(headers=self.headers) as session:
+                if method == "GET":
+                    async with session.get(url) as response:
+                        if response.status == 200:
+                            return await response.json()
+                elif method == "POST":
+                    async with session.post(url, json=data) as response:
+                        if response.status == 200:
+                            return await response.json()
+                return None
+        except Exception as e:
+            print(f"请求发生错误: {str(e)}")
+            return None
+
+    def _parse_paper(self, doc: dict) -> PaperMetadata:
+        """解析ADS文献数据
+
+        Args:
+            doc: ADS文献数据
+
+        Returns:
+            解析后的论文数据
+        """
+        try:
+            return PaperMetadata(
+                title=doc.get('title', [''])[0] if doc.get('title') else '',
+                authors=doc.get('author', []),
+                abstract=doc.get('abstract', ''),
+                year=doc.get('year'),
+                doi=doc.get('doi', [''])[0] if doc.get('doi') else None,
+                url=f"https://ui.adsabs.harvard.edu/abs/{doc.get('bibcode')}/abstract" if doc.get('bibcode') else None,
+                citations=doc.get('citation_count'),
+                venue=doc.get('pub', ''),
+                institutions=doc.get('aff', []),
+                venue_type="journal",
+                venue_name=doc.get('pub', ''),
+                venue_info={
+                    'volume': doc.get('volume'),
+                    'issue': doc.get('issue'),
+                    'pub_date': doc.get('pubdate', '')
+                },
+                source='adsabs'
+            )
+        except Exception as e:
+            print(f"解析文章时发生错误: {str(e)}")
+            return None
+
+    async def search(
+        self,
+        query: str,
+        limit: int = 100,
+        sort_by: str = "relevance",
+        start_year: int = None
+    ) -> List[PaperMetadata]:
+        """搜索论文
+
+        Args:
+            query: 搜索关键词
+            limit: 返回结果数量限制
+            sort_by: 排序方式 ('relevance', 'date', 'citations')
+            start_year: 起始年份
+
+        Returns:
+            论文列表
+        """
+        try:
+            # 构建查询
+            if start_year:
+                query = f"{query} year:{start_year}-"
+
+            # 设置排序
+            sort_mapping = {
+                'relevance': 'score desc',
+                'date': 'date desc',
+                'citations': 'citation_count desc'
+            }
+            sort = sort_mapping.get(sort_by, 'score desc')
+
+            # 构建搜索请求
+            search_url = f"{self.base_url}/search/query"
+            params = {
+                "q": query,
+                "rows": limit,
+                "sort": sort,
+                "fl": "title,author,abstract,year,doi,bibcode,citation_count,pub,aff,volume,issue,pubdate"
+            }
+
+            response = await self._make_request(f"{search_url}?{self._build_query_string(params)}")
+            if not response or 'response' not in response:
+                return []
+
+            # 解析结果
+            papers = []
+            for doc in response['response']['docs']:
+                paper = self._parse_paper(doc)
+                if paper:
+                    papers.append(paper)
+
+            return papers
+
+        except Exception as e:
+            print(f"搜索论文时发生错误: {str(e)}")
+            return []
+
+    def _build_query_string(self, params: dict) -> str:
+        """构建查询字符串"""
+        return "&".join([f"{k}={v}" for k, v in params.items()])
+
+    async def get_paper_details(self, bibcode: str) -> Optional[PaperMetadata]:
+        """获取指定bibcode的论文详情"""
+        search_url = f"{self.base_url}/search/query"
+        params = {
+            "q": f"identifier:{bibcode}",
+            "fl": "title,author,abstract,year,doi,bibcode,citation_count,pub,aff,volume,issue,pubdate"
+        }
+
+        response = await self._make_request(f"{search_url}?{self._build_query_string(params)}")
+        if response and 'response' in response and response['response']['docs']:
+            return self._parse_paper(response['response']['docs'][0])
+        return None
+
+    async def get_related_papers(self, bibcode: str, limit: int = 100) -> List[PaperMetadata]:
+        """获取相关论文"""
+        url = f"{self.base_url}/search/query"
+        params = {
+            "q": f"citations(identifier:{bibcode}) OR references(identifier:{bibcode})",
+            "rows": limit,
+            "fl": "title,author,abstract,year,doi,bibcode,citation_count,pub,aff,volume,issue,pubdate"
+        }
+
+        response = await self._make_request(f"{url}?{self._build_query_string(params)}")
+        if not response or 'response' not in response:
+            return []
+
+        papers = []
+        for doc in response['response']['docs']:
+            paper = self._parse_paper(doc)
+            if paper:
+                papers.append(paper)
+        return papers
+
+    async def search_by_author(
+        self,
+        author: str,
+        limit: int = 100,
+        start_year: int = None
+    ) -> List[PaperMetadata]:
+        """按作者搜索论文"""
+        query = f"author:\"{author}\""
+        return await self.search(query, limit=limit, start_year=start_year)
+
+    async def search_by_journal(
+        self,
+        journal: str,
+        limit: int = 100,
+        start_year: int = None
+    ) -> List[PaperMetadata]:
+        """按期刊搜索论文"""
+        query = f"pub:\"{journal}\""
+        return await self.search(query, limit=limit, start_year=start_year)
+
+    async def get_latest_papers(
+        self,
+        days: int = 7,
+        limit: int = 100
+    ) -> List[PaperMetadata]:
+        """获取最新论文"""
+        query = f"entdate:[NOW-{days}DAYS TO NOW]"
+        return await self.search(query, limit=limit, sort_by="date")
+
+    async def get_citations(self, bibcode: str) -> List[PaperMetadata]:
+        """获取引用该论文的文献"""
+        url = f"{self.base_url}/search/query"
+        params = {
+            "q": f"citations(identifier:{bibcode})",
+            "fl": "title,author,abstract,year,doi,bibcode,citation_count,pub,aff,volume,issue,pubdate"
+        }
+
+        response = await self._make_request(f"{url}?{self._build_query_string(params)}")
+        if not response or 'response' not in response:
+            return []
+
+        papers = []
+        for doc in response['response']['docs']:
+            paper = self._parse_paper(doc)
+            if paper:
+                papers.append(paper)
+        return papers
+
+    async def get_references(self, bibcode: str) -> List[PaperMetadata]:
+        """获取该论文引用的文献"""
+        url = f"{self.base_url}/search/query"
+        params = {
+            "q": f"references(identifier:{bibcode})",
+            "fl": "title,author,abstract,year,doi,bibcode,citation_count,pub,aff,volume,issue,pubdate"
+        }
+
+        response = await self._make_request(f"{url}?{self._build_query_string(params)}")
+        if not response or 'response' not in response:
+            return []
+
+        papers = []
+        for doc in response['response']['docs']:
+            paper = self._parse_paper(doc)
+            if paper:
+                papers.append(paper)
+        return papers
+
+async def example_usage():
+    """AdsabsSource使用示例"""
+    ads = AdsabsSource()
+
+    try:
+        # 示例1：基本搜索
+        print("\n=== 示例1：搜索黑洞相关论文 ===")
+        papers = await ads.search("black hole", limit=3)
+        for i, paper in enumerate(papers, 1):
+            print(f"\n--- 论文 {i} ---")
+            print(f"标题: {paper.title}")
+            print(f"作者: {', '.join(paper.authors)}")
+            print(f"发表年份: {paper.year}")
+            print(f"DOI: {paper.doi}")
+
+        # 其他示例...
+
+    except Exception as e:
+        print(f"发生错误: {str(e)}")
+
+if __name__ == "__main__":
+    # python -m crazy_functions.review_fns.data_sources.adsabs_source
+    asyncio.run(example_usage())
--- a/crazy_functions/review_fns/data_sources/arxiv_source.py
+++ b/crazy_functions/review_fns/data_sources/arxiv_source.py
@@ -0,0 +1,636 @@
+import arxiv
+from typing import List, Optional, Union, Literal, Dict
+from datetime import datetime
+from .base_source import DataSource, PaperMetadata
+import os
+from urllib.request import urlretrieve
+import feedparser
+from tqdm import tqdm
+
+class ArxivSource(DataSource):
+    """arXiv API实现"""
+    
+    CATEGORIES = {
+        # 物理学
+        "Physics": {
+            "astro-ph": "天体物理学",
+            "cond-mat": "凝聚态物理",
+            "gr-qc": "广义相对论与量子宇宙学",
+            "hep-ex": "高能物理实验",
+            "hep-lat": "格点场论",
+            "hep-ph": "高能物理理论",
+            "hep-th": "高能物理理论",
+            "math-ph": "数学物理",
+            "nlin": "非线性科学",
+            "nucl-ex": "核实验",
+            "nucl-th": "核理论",
+            "physics": "物理学",
+            "quant-ph": "量子物理",
+        },
+        
+        # 数学
+        "Mathematics": {
+            "math.AG": "代数几何",
+            "math.AT": "代数拓扑",
+            "math.AP": "分析与偏微分方程",
+            "math.CT": "范畴论",
+            "math.CA": "复分析",
+            "math.CO": "组合数学",
+            "math.AC": "交换代数",
+            "math.CV": "复变函数",
+            "math.DG": "微分几何",
+            "math.DS": "动力系统",
+            "math.FA": "泛函分析",
+            "math.GM": "一般数学",
+            "math.GN": "一般拓扑",
+            "math.GT": "几何拓扑",
+            "math.GR": "群论",
+            "math.HO": "数学史与数学概述",
+            "math.IT": "信息论",
+            "math.KT": "K理论与同调",
+            "math.LO": "逻辑",
+            "math.MP": "数学物理",
+            "math.MG": "度量几何",
+            "math.NT": "数论",
+            "math.NA": "数值分析",
+            "math.OA": "算子代数",
+            "math.OC": "最优化与控制",
+            "math.PR": "概率论",
+            "math.QA": "量子代数",
+            "math.RT": "表示论",
+            "math.RA": "环与代数",
+            "math.SP": "谱理论",
+            "math.ST": "统计理论",
+            "math.SG": "辛几何",
+        },
+        
+        # 计算机科学
+        "Computer Science": {
+            "cs.AI": "人工智能",
+            "cs.CL": "计算语言学",
+            "cs.CC": "计算复杂性",
+            "cs.CE": "计算工程",
+            "cs.CG": "计算几何",
+            "cs.GT": "计算机博弈论",
+            "cs.CV": "计算机视觉",
+            "cs.CY": "计算机与社会",
+            "cs.CR": "密码学与安全",
+            "cs.DS": "数据结构与算法",
+            "cs.DB": "数据库",
+            "cs.DL": "数字图书馆",
+            "cs.DM": "离散数学",
+            "cs.DC": "分布式计算",
+            "cs.ET": "新兴技术",
+            "cs.FL": "形式语言与自动机理论",
+            "cs.GL": "一般文献",
+            "cs.GR": "图形学",
+            "cs.AR": "硬件架构",
+            "cs.HC": "人机交互",
+            "cs.IR": "信息检索",
+            "cs.IT": "信息论",
+            "cs.LG": "机器学习",
+            "cs.LO": "逻辑与计算机",
+            "cs.MS": "数学软件",
+            "cs.MA": "多智能体系统",
+            "cs.MM": "多媒体",
+            "cs.NI": "网络与互联网架构",
+            "cs.NE": "神经与进化计算",
+            "cs.NA": "数值分析",
+            "cs.OS": "操作系统",
+            "cs.OH": "其他计算机科学",
+            "cs.PF": "性能评估",
+            "cs.PL": "编程语言",
+            "cs.RO": "机器人学",
+            "cs.SI": "社会与信息网络",
+            "cs.SE": "软件工程",
+            "cs.SD": "声音",
+            "cs.SC": "符号计算",
+            "cs.SY": "系统与控制",
+        },
+        
+        # 定量生物学
+        "Quantitative Biology": {
+            "q-bio.BM": "生物分子",
+            "q-bio.CB": "细胞行为",
+            "q-bio.GN": "基因组学",
+            "q-bio.MN": "分子网络",
+            "q-bio.NC": "神经计算",
+            "q-bio.OT": "其他",
+            "q-bio.PE": "群体与进化",
+            "q-bio.QM": "定量方法",
+            "q-bio.SC": "亚细胞过程",
+            "q-bio.TO": "组织与器官",
+        },
+        
+        # 定量金融
+        "Quantitative Finance": {
+            "q-fin.CP": "计算金融",
+            "q-fin.EC": "经济学",
+            "q-fin.GN": "一般金融",
+            "q-fin.MF": "数学金融",
+            "q-fin.PM": "投资组合管理",
+            "q-fin.PR": "定价理论",
+            "q-fin.RM": "风险管理",
+            "q-fin.ST": "统计金融",
+            "q-fin.TR": "交易与市场微观结构",
+        },
+        
+        # 统计学
+        "Statistics": {
+            "stat.AP": "应用统计",
+            "stat.CO": "计算统计",
+            "stat.ML": "机器学习",
+            "stat.ME": "方法论",
+            "stat.OT": "其他统计",
+            "stat.TH": "统计理论",
+        },
+        
+        # 电气工程与系统科学
+        "Electrical Engineering and Systems Science": {
+            "eess.AS": "音频与语音处理",
+            "eess.IV": "图像与视频处理",
+            "eess.SP": "信号处理",
+            "eess.SY": "系统与控制",
+        },
+        
+        # 经济学
+        "Economics": {
+            "econ.EM": "计量经济学",
+            "econ.GN": "一般经济学",
+            "econ.TH": "理论经济学",
+        }
+    }
+
+    def __init__(self):
+        """初始化"""
+        self._initialize()  # 调用初始化方法
+        # 修改排序选项映射
+        self.sort_options = {
+            'relevance': arxiv.SortCriterion.Relevance,  # arXiv的相关性排序
+            'lastUpdatedDate': arxiv.SortCriterion.LastUpdatedDate,  # 最后更新日期
+            'submittedDate': arxiv.SortCriterion.SubmittedDate,  # 提交日期
+        }
+        
+        self.sort_order_options = {
+            'ascending': arxiv.SortOrder.Ascending,
+            'descending': arxiv.SortOrder.Descending
+        }
+        
+        self.default_sort = 'lastUpdatedDate'
+        self.default_order = 'descending'
+        
+    def _initialize(self) -> None:
+        """初始化客户端，设置默认参数"""
+        self.client = arxiv.Client()
+
+    async def search(
+        self,
+        query: str,
+        limit: int = 10,
+        sort_by: str = None,
+        sort_order: str = None,
+        start_year: int = None
+    ) -> List[Dict]:
+        """搜索论文"""
+        try:
+            # 使用默认排序如果提供的排序选项无效
+            if not sort_by or sort_by not in self.sort_options:
+                sort_by = self.default_sort
+                
+            # 使用默认排序顺序如果提供的顺序无效    
+            if not sort_order or sort_order not in self.sort_order_options:
+                sort_order = self.default_order
+                
+            # 如果指定了起始年份，添加到查询中
+            if start_year:
+                query = f"{query} AND submittedDate:[{start_year}0101 TO 99991231]"
+            
+            search = arxiv.Search(
+                query=query,
+                max_results=limit,
+                sort_by=self.sort_options[sort_by],
+                sort_order=self.sort_order_options[sort_order]
+            )
+            
+            results = list(self.client.results(search))
+            return [self._parse_paper_data(result) for result in results]
+        except Exception as e:
+            print(f"搜索论文时发生错误: {str(e)}")
+            return []
+
+    async def search_by_id(self, paper_id: Union[str, List[str]]) -> List[PaperMetadata]:
+        """按ID搜索论文
+        
+        Args:
+            paper_id: 单个arXiv ID或ID列表，例如：'2005.14165' 或 ['2005.14165', '2103.14030']
+        """
+        if isinstance(paper_id, str):
+            paper_id = [paper_id]
+            
+        search = arxiv.Search(
+            id_list=paper_id,
+            max_results=len(paper_id)
+        )
+        results = list(self.client.results(search))
+        return [self._parse_paper_data(result) for result in results]
+
+    async def search_by_category(
+        self, 
+        category: str, 
+        limit: int = 100,
+        sort_by: str = 'relevance',
+        sort_order: str = 'descending',
+        start_year: int = None
+    ) -> List[PaperMetadata]:
+        """按类别搜索论文"""
+        query = f"cat:{category}"
+        
+        # 如果指定了起始年份，添加到查询中
+        if start_year:
+            query = f"{query} AND submittedDate:[{start_year}0101 TO 99991231]"
+        
+        return await self.search(
+            query=query,
+            limit=limit,
+            sort_by=sort_by,
+            sort_order=sort_order
+        )
+
+    async def search_by_authors(
+        self, 
+        authors: List[str], 
+        limit: int = 100,
+        sort_by: str = 'relevance',
+        start_year: int = None
+    ) -> List[PaperMetadata]:
+        """按作者搜索论文"""
+        query = " AND ".join([f"au:\"{author}\"" for author in authors])
+        
+        # 如果指定了起始年份，添加到查询中
+        if start_year:
+            query = f"{query} AND submittedDate:[{start_year}0101 TO 99991231]"
+        
+        return await self.search(
+            query=query,
+            limit=limit,
+            sort_by=sort_by
+        )
+
+    async def search_by_date_range(
+        self, 
+        start_date: datetime, 
+        end_date: datetime, 
+        limit: int = 100,
+        sort_by: Literal['relevance', 'updated', 'submitted'] = 'submitted',
+        sort_order: Literal['ascending', 'descending'] = 'descending'
+    ) -> List[PaperMetadata]:
+        """按日期范围搜索论文"""
+        query = f"submittedDate:[{start_date.strftime('%Y%m%d')} TO {end_date.strftime('%Y%m%d')}]"
+        return await self.search(
+            query, 
+            limit=limit, 
+            sort_by=sort_by, 
+            sort_order=sort_order
+        )
+
+    async def download_pdf(self, paper_id: str, dirpath: str = "./", filename: str = "") -> str:
+        """下载论文PDF
+        
+        Args:
+            paper_id: arXiv ID
+            dirpath: 保存目录
+            filename: 文件名，如果为空则使用默认格式：{paper_id}_{标题}.pdf
+            
+        Returns:
+            保存的文件路径
+        """
+        papers = await self.search_by_id(paper_id)
+        if not papers:
+            raise ValueError(f"未找到ID为 {paper_id} 的论文")
+        paper = papers[0]
+        
+        if not filename:
+            # 清理标题中的非法字符
+            safe_title = "".join(c if c.isalnum() else "_" for c in paper.title)
+            filename = f"{paper_id}_{safe_title}.pdf"
+            
+        filepath = os.path.join(dirpath, filename)
+        urlretrieve(paper.url, filepath)
+        return filepath
+
+    async def download_source(self, paper_id: str, dirpath: str = "./", filename: str = "") -> str:
+        """下载论文源文件（通常是LaTeX源码）
+        
+        Args:
+            paper_id: arXiv ID
+            dirpath: 保存目录
+            filename: 文件名，如果为空则使用默认格式：{paper_id}_{标题}.tar.gz
+            
+        Returns:
+            保存的文件路径
+        """
+        papers = await self.search_by_id(paper_id)
+        if not papers:
+            raise ValueError(f"未找到ID为 {paper_id} 的论文")
+        paper = papers[0]
+        
+        if not filename:
+            safe_title = "".join(c if c.isalnum() else "_" for c in paper.title)
+            filename = f"{paper_id}_{safe_title}.tar.gz"
+            
+        filepath = os.path.join(dirpath, filename)
+        source_url = paper.url.replace("/pdf/", "/src/")
+        urlretrieve(source_url, filepath)
+        return filepath
+
+    async def get_citations(self, paper_id: str) -> List[PaperMetadata]:
+        # arXiv API不直接提供引用信息
+        return []
+
+    async def get_references(self, paper_id: str) -> List[PaperMetadata]:
+        # arXiv API不直接提供引用信息
+        return []
+
+    async def get_paper_details(self, paper_id: str) -> Optional[PaperMetadata]:
+        """获取论文详情
+        
+        Args:
+            paper_id: arXiv ID 或 DOI
+            
+        Returns:
+            论文详细信息，如果未找到返回 None
+        """
+        try:
+            # 如果是完整的 arXiv URL，提取 ID
+            if "arxiv.org" in paper_id:
+                paper_id = paper_id.split("/")[-1]
+            # 如果是 DOI 格式且是 arXiv 论文，提取 ID
+            elif paper_id.startswith("10.48550/arXiv."):
+                paper_id = paper_id.split(".")[-1]
+                
+            papers = await self.search_by_id(paper_id)
+            return papers[0] if papers else None
+        except Exception as e:
+            print(f"获取论文详情时发生错误: {str(e)}")
+            return None
+
+    def _parse_paper_data(self, result: arxiv.Result) -> PaperMetadata:
+        """解析arXiv API返回的数据"""
+        # 解析主要类别和次要类别
+        primary_category = result.primary_category
+        categories = result.categories
+        
+        # 构建venue信息
+        venue_info = {
+            'primary_category': primary_category,
+            'categories': categories,
+            'comments': getattr(result, 'comment', None),
+            'journal_ref': getattr(result, 'journal_ref', None)
+        }
+        
+        return PaperMetadata(
+            title=result.title,
+            authors=[author.name for author in result.authors],
+            abstract=result.summary,
+            year=result.published.year,
+            doi=result.entry_id,
+            url=result.pdf_url,
+            citations=None,
+            venue=f"arXiv:{primary_category}",
+            institutions=[],
+            venue_type='preprint',  # arXiv论文都是预印本
+            venue_name='arXiv',
+            venue_info=venue_info,
+            source='arxiv'  # 添加来源标记
+        )
+
+    async def get_latest_papers(
+        self, 
+        category: str, 
+        debug: bool = False,
+        batch_size: int = 50
+    ) -> List[PaperMetadata]:
+        """获取指定类别的最新论文
+        
+        通过 RSS feed 获取最新发布的论文，然后批量获取详细信息
+        
+        Args:
+            category: arXiv类别，例如：
+                     - 整个领域: 'cs'
+                     - 具体方向: 'cs.AI'
+                     - 多个类别: 'cs.AI+q-bio.NC'
+            debug: 是否为调试模式，如果为True则只返回5篇最新论文
+            batch_size: 批量获取论文的数量，默认50
+            
+        Returns:
+            论文列表
+            
+        Raises:
+            ValueError: 如果类别无效
+        """
+        try:
+            # 处理类别格式
+            # 1. 转换为小写
+            # 2. 确保多个类别之间使用+连接
+            category = category.lower().replace(' ', '+')
+            
+            # 构建RSS feed URL
+            feed_url = f"https://rss.arxiv.org/rss/{category}"
+            print(f"正在获取RSS feed: {feed_url}")  # 添加调试信息
+            
+            feed = feedparser.parse(feed_url)
+            
+            # 检查feed是否有效
+            if hasattr(feed, 'status') and feed.status != 200:
+                raise ValueError(f"获取RSS feed失败，状态码: {feed.status}")
+                
+            if not feed.entries:
+                print(f"警告：未在feed中找到任何条目")  # 添加调试信息
+                print(f"Feed标题: {feed.feed.title if hasattr(feed, 'feed') else '无标题'}")
+                raise ValueError(f"无效的arXiv类别或未找到论文: {category}")
+                
+            if debug:
+                # 调试模式：只获取5篇最新论文
+                search = arxiv.Search(
+                    query=f'cat:{category}',
+                    sort_by=arxiv.SortCriterion.SubmittedDate,
+                    sort_order=arxiv.SortOrder.Descending,
+                    max_results=5
+                )
+                results = list(self.client.results(search))
+                return [self._parse_paper_data(result) for result in results]
+            
+            # 正常模式：获取所有新论文
+            # 从RSS条目中提取arXiv ID
+            paper_ids = []
+            for entry in feed.entries:
+                try:
+                    # RSS链接格式可能是以下几种：
+                    # - http://arxiv.org/abs/2403.xxxxx
+                    # - http://arxiv.org/pdf/2403.xxxxx
+                    # - https://arxiv.org/abs/2403.xxxxx
+                    link = entry.link or entry.id
+                    arxiv_id = link.split('/')[-1].replace('.pdf', '')
+                    if arxiv_id:
+                        paper_ids.append(arxiv_id)
+                except Exception as e:
+                    print(f"警告：处理条目时出错: {str(e)}")  # 添加调试信息
+                    continue
+                
+            if not paper_ids:
+                print("未能从feed中提取到任何论文ID")  # 添加调试信息
+                return []
+                
+            print(f"成功提取到 {len(paper_ids)} 个论文ID")  # 添加调试信息
+                
+            # 批量获取论文详情
+            papers = []
+            with tqdm(total=len(paper_ids), desc="获取arXiv论文") as pbar:
+                for i in range(0, len(paper_ids), batch_size):
+                    batch_ids = paper_ids[i:i + batch_size]
+                    search = arxiv.Search(
+                        id_list=batch_ids,
+                        max_results=len(batch_ids)
+                    )
+                    batch_results = list(self.client.results(search))
+                    papers.extend([self._parse_paper_data(result) for result in batch_results])
+                    pbar.update(len(batch_results))
+                    
+            return papers
+            
+        except Exception as e:
+            print(f"获取最新论文时发生错误: {str(e)}")
+            import traceback
+            print(traceback.format_exc())  # 添加完整的错误追踪
+            return []
+
+async def example_usage():
+    """ArxivSource使用示例"""
+    arxiv_source = ArxivSource()
+    
+    try:
+        # 示例1：基本搜索，使用不同的排序方式
+        # print("\n=== 示例1：搜索最新的机器学习论文（按提交时间排序）===")
+        # papers = await arxiv_source.search(
+        #     "ti:\"machine learning\"", 
+        #     limit=3,
+        #     sort_by='submitted',
+        #     sort_order='descending'
+        # )
+        # print(f"找到 {len(papers)} 篇论文")
+        
+        # for i, paper in enumerate(papers, 1):
+        #     print(f"\n--- 论文 {i} ---")
+        #     print(f"标题: {paper.title}")
+        #     print(f"作者: {', '.join(paper.authors)}")
+        #     print(f"发表年份: {paper.year}")
+        #     print(f"arXiv ID: {paper.doi}")
+        #     print(f"PDF URL: {paper.url}")
+        #     if paper.abstract:
+        #         print(f"\n摘要:")
+        #         print(paper.abstract)
+        #     print(f"发表venue: {paper.venue}")
+
+        # # 示例2：按ID搜索
+        # print("\n=== 示例2：按ID搜索论文 ===")
+        # paper_id = "2005.14165"  # GPT-3论文
+        # papers = await arxiv_source.search_by_id(paper_id)
+        # if papers:
+        #     paper = papers[0]
+        #     print(f"标题: {paper.title}")
+        #     print(f"作者: {', '.join(paper.authors)}")
+        #     print(f"发表年份: {paper.year}")
+
+        # # 示例3：按类别搜索
+        # print("\n=== 示例3：搜索人工智能领域最新论文 ===")
+        # ai_papers = await arxiv_source.search_by_category(
+        #     "cs.AI", 
+        #     limit=2,
+        #     sort_by='updated',
+        #     sort_order='descending'
+        # )
+        # for i, paper in enumerate(ai_papers, 1):
+        #     print(f"\n--- AI论文 {i} ---")
+        #     print(f"标题: {paper.title}")
+        #     print(f"作者: {', '.join(paper.authors)}")
+        #     print(f"发表venue: {paper.venue}")
+
+        # # 示例4：按作者搜索
+        # print("\n=== 示例4：搜索特定作者的论文 ===")
+        # author_papers = await arxiv_source.search_by_authors(
+        #     ["Bengio"], 
+        #     limit=2,
+        #     sort_by='relevance'
+        # )
+        # for i, paper in enumerate(author_papers, 1):
+        #     print(f"\n--- Bengio的论文 {i} ---")
+        #     print(f"标题: {paper.title}")
+        #     print(f"作者: {', '.join(paper.authors)}")
+        #     print(f"发表venue: {paper.venue}")
+
+        # # 示例5：按日期范围搜索
+        # print("\n=== 示例5：搜索特定日期范围的论文 ===")
+        # from datetime import datetime, timedelta
+        # end_date = datetime.now()
+        # start_date = end_date - timedelta(days=7)  # 最近一周
+        # recent_papers = await arxiv_source.search_by_date_range(
+        #     start_date,
+        #     end_date,
+        #     limit=2
+        # )
+        # for i, paper in enumerate(recent_papers, 1):
+        #     print(f"\n--- 最近论文 {i} ---")
+        #     print(f"标题: {paper.title}")
+        #     print(f"作者: {', '.join(paper.authors)}")
+        #     print(f"发表年份: {paper.year}")
+
+        # # 示例6：下载PDF
+        # print("\n=== 示例6：下载论文PDF ===")
+        # if papers:  # 使用之前搜索到的GPT-3论文
+        #     pdf_path = await arxiv_source.download_pdf(paper_id)
+        #     print(f"PDF已下载到: {pdf_path}")
+
+        # # 示例7：下载源文件
+        # print("\n=== 示例7：下载论文源文件 ===")
+        # if papers:
+        #     source_path = await arxiv_source.download_source(paper_id)
+        #     print(f"源文件已下载到: {source_path}")
+
+        # 示例6：获取最新论文
+        print("\n=== 示例8：获取最新论文 ===")
+        
+        # 获取CS.AI领域的最新论文
+        print("\n--- 获取AI领域最新论文 ---")
+        ai_latest = await arxiv_source.get_latest_papers("cs.AI", debug=True)
+        for i, paper in enumerate(ai_latest, 1):
+            print(f"\n论文 {i}:")
+            print(f"标题: {paper.title}")
+            print(f"作者: {', '.join(paper.authors)}")
+            print(f"发表年份: {paper.year}")
+            
+        # 获取整个计算机科学领域的最新论文
+        print("\n--- 获取整个CS领域最新论文 ---")
+        cs_latest = await arxiv_source.get_latest_papers("cs", debug=True)
+        for i, paper in enumerate(cs_latest, 1):
+            print(f"\n论文 {i}:")
+            print(f"标题: {paper.title}")
+            print(f"作者: {', '.join(paper.authors)}")
+            print(f"发表年份: {paper.year}")
+            
+        # 获取多个类别的最新论文
+        print("\n--- 获取AI和机器学习领域最新论文 ---")
+        multi_latest = await arxiv_source.get_latest_papers("cs.AI+cs.LG", debug=True)
+        for i, paper in enumerate(multi_latest, 1):
+            print(f"\n论文 {i}:")
+            print(f"标题: {paper.title}")
+            print(f"作者: {', '.join(paper.authors)}")
+            print(f"发表年份: {paper.year}")
+
+    except Exception as e:
+        print(f"发生错误: {str(e)}")
+        import traceback
+        print(traceback.format_exc())
+
+if __name__ == "__main__":
+    import asyncio
+    asyncio.run(example_usage()) 
--- a/crazy_functions/review_fns/data_sources/base_source.py
+++ b/crazy_functions/review_fns/data_sources/base_source.py
@@ -0,0 +1,102 @@
+from abc import ABC, abstractmethod
+from typing import List, Dict, Optional
+from dataclasses import dataclass
+
+class PaperMetadata:
+    """论文元数据"""
+    def __init__(
+        self,
+        title: str,
+        authors: List[str],
+        abstract: str,
+        year: int,
+        doi: str = None,
+        url: str = None,
+        citations: int = None,
+        venue: str = None,
+        institutions: List[str] = None,
+        venue_type: str = None,  # 来源类型(journal/conference/preprint等)
+        venue_name: str = None,  # 具体的期刊/会议名称
+        venue_info: Dict = None,  # 更多来源详细信息(如影响因子、分区等)
+        source: str = None  # 新增: 论文来源标记
+    ):
+        self.title = title
+        self.authors = authors
+        self.abstract = abstract
+        self.year = year
+        self.doi = doi
+        self.url = url
+        self.citations = citations
+        self.venue = venue
+        self.institutions = institutions or []
+        self.venue_type = venue_type  # 新增
+        self.venue_name = venue_name  # 新增
+        self.venue_info = venue_info or {}  # 新增
+        self.source = source  # 新增: 存储论文来源
+        
+        # 新增：影响因子和分区信息，初始化为None
+        self._if_factor = None
+        self._cas_division = None
+        self._jcr_division = None
+    
+    @property
+    def if_factor(self) -> Optional[float]:
+        """获取影响因子"""
+        return self._if_factor
+    
+    @if_factor.setter
+    def if_factor(self, value: float):
+        """设置影响因子"""
+        self._if_factor = value
+    
+    @property
+    def cas_division(self) -> Optional[str]:
+        """获取中科院分区"""
+        return self._cas_division
+    
+    @cas_division.setter
+    def cas_division(self, value: str):
+        """设置中科院分区"""
+        self._cas_division = value
+    
+    @property
+    def jcr_division(self) -> Optional[str]:
+        """获取JCR分区"""
+        return self._jcr_division
+    
+    @jcr_division.setter
+    def jcr_division(self, value: str):
+        """设置JCR分区"""
+        self._jcr_division = value
+
+class DataSource(ABC):
+    """数据源基类"""
+    
+    def __init__(self, api_key: Optional[str] = None):
+        self.api_key = api_key
+        self._initialize()
+    
+    @abstractmethod
+    def _initialize(self) -> None:
+        """初始化数据源"""
+        pass
+    
+    @abstractmethod
+    async def search(self, query: str, limit: int = 100) -> List[PaperMetadata]:
+        """搜索论文"""
+        pass
+    
+    @abstractmethod
+    async def get_paper_details(self, paper_id: str) -> PaperMetadata:
+        """获取论文详细信息"""
+        pass
+    
+    @abstractmethod
+    async def get_citations(self, paper_id: str) -> List[PaperMetadata]:
+        """获取引用该论文的文献"""
+        pass
+    
+    @abstractmethod
+    async def get_references(self, paper_id: str) -> List[PaperMetadata]:
+        """获取该论文引用的文献"""
+        pass 
--- a/crazy_functions/review_fns/data_sources/cas_if.json
+++ b/crazy_functions/review_fns/data_sources/cas_if.json
--- a/crazy_functions/review_fns/data_sources/crossref_source.py
+++ b/crazy_functions/review_fns/data_sources/crossref_source.py
@@ -0,0 +1,400 @@
+import aiohttp
+from typing import List, Dict, Optional
+from datetime import datetime
+from crazy_functions.review_fns.data_sources.base_source import DataSource, PaperMetadata
+import random
+
+class CrossrefSource(DataSource):
+    """Crossref API实现"""
+
+    CONTACT_EMAILS = [
+        "gpt_abc_academic@163.com",
+        "gpt_abc_newapi@163.com",
+        "gpt_abc_academic_pwd@163.com"
+    ]
+
+    def _initialize(self) -> None:
+        """初始化客户端，设置默认参数"""
+        self.base_url = "https://api.crossref.org"
+        # 随机选择一个邮箱
+        contact_email = random.choice(self.CONTACT_EMAILS)
+        self.headers = {
+            "Accept": "application/json",
+            "User-Agent": f"Mozilla/5.0 (compatible; PythonScript/1.0; mailto:{contact_email})",
+        }
+        if self.api_key:
+            self.headers["Crossref-Plus-API-Token"] = f"Bearer {self.api_key}"
+
+    async def search(
+        self,
+        query: str,
+        limit: int = 100,
+        sort_by: str = None,
+        sort_order: str = None,
+        start_year: int = None
+    ) -> List[PaperMetadata]:
+        """搜索论文
+
+        Args:
+            query: 搜索关键词
+            limit: 返回结果数量限制
+            sort_by: 排序字段
+            sort_order: 排序顺序
+            start_year: 起始年份
+        """
+        async with aiohttp.ClientSession(headers=self.headers) as session:
+            # 请求更多的结果以补偿可能被过滤掉的文章
+            adjusted_limit = min(limit * 3, 1000)  # 设置上限以避免请求过多
+            params = {
+                "query": query,
+                "rows": adjusted_limit,
+                "select": (
+                    "DOI,title,author,published-print,abstract,reference,"
+                    "container-title,is-referenced-by-count,type,"
+                    "publisher,ISSN,ISBN,issue,volume,page"
+                )
+            }
+
+            # 添加年份过滤
+            if start_year:
+                params["filter"] = f"from-pub-date:{start_year}"
+
+            # 添加排序
+            if sort_by:
+                params["sort"] = sort_by
+                if sort_order:
+                    params["order"] = sort_order
+
+            async with session.get(
+                f"{self.base_url}/works",
+                params=params
+            ) as response:
+                if response.status != 200:
+                    print(f"API请求失败: HTTP {response.status}")
+                    print(f"响应内容: {await response.text()}")
+                    return []
+
+                data = await response.json()
+                items = data.get("message", {}).get("items", [])
+                if not items:
+                    print(f"未找到相关论文")
+                    return []
+
+                # 过滤掉没有摘要的文章
+                papers = []
+                filtered_count = 0
+                for work in items:
+                    paper = self._parse_work(work)
+                    if paper.abstract and paper.abstract.strip():
+                        papers.append(paper)
+                        if len(papers) >= limit:  # 达到原始请求的限制后停止
+                            break
+                    else:
+                        filtered_count += 1
+
+                print(f"找到 {len(items)} 篇相关论文，其中 {filtered_count} 篇因缺少摘要被过滤")
+                print(f"返回 {len(papers)} 篇包含摘要的论文")
+                return papers
+
+    async def get_paper_details(self, doi: str) -> PaperMetadata:
+        """获取指定DOI的论文详情"""
+        async with aiohttp.ClientSession(headers=self.headers) as session:
+            async with session.get(
+                f"{self.base_url}/works/{doi}",
+                params={
+                    "select": (
+                        "DOI,title,author,published-print,abstract,reference,"
+                        "container-title,is-referenced-by-count,type,"
+                        "publisher,ISSN,ISBN,issue,volume,page"
+                    )
+                }
+            ) as response:
+                if response.status != 200:
+                    print(f"获取论文详情失败: HTTP {response.status}")
+                    print(f"响应内容: {await response.text()}")
+                    return None
+
+                try:
+                    data = await response.json()
+                    return self._parse_work(data.get("message", {}))
+                except Exception as e:
+                    print(f"解析论文详情时发生错误: {str(e)}")
+                    return None
+
+    async def get_references(self, doi: str) -> List[PaperMetadata]:
+        """获取指定DOI论文的参考文献列表"""
+        async with aiohttp.ClientSession(headers=self.headers) as session:
+            async with session.get(
+                f"{self.base_url}/works/{doi}",
+                params={"select": "reference"}
+            ) as response:
+                if response.status != 200:
+                    print(f"获取参考文献失败: HTTP {response.status}")
+                    return []
+
+                try:
+                    data = await response.json()
+                    # 确保我们正确处理返回的数据结构
+                    if not isinstance(data, dict):
+                        print(f"API返回了意外的数据格式: {type(data)}")
+                        return []
+
+                    references = data.get("message", {}).get("reference", [])
+                    if not references:
+                        print(f"未找到参考文献")
+                        return []
+
+                    return [
+                        PaperMetadata(
+                            title=ref.get("article-title", ""),
+                            authors=[ref.get("author", "")],
+                            year=ref.get("year"),
+                            doi=ref.get("DOI"),
+                            url=f"https://doi.org/{ref.get('DOI')}" if ref.get("DOI") else None,
+                            abstract="",
+                            citations=None,
+                            venue=ref.get("journal-title", ""),
+                            institutions=[]
+                        )
+                        for ref in references
+                    ]
+                except Exception as e:
+                    print(f"解析参考文献数据时发生错误: {str(e)}")
+                    return []
+
+    async def get_citations(self, doi: str) -> List[PaperMetadata]:
+        """获取引用指定DOI论文的文献列表"""
+        async with aiohttp.ClientSession(headers=self.headers) as session:
+            async with session.get(
+                f"{self.base_url}/works",
+                params={
+                    "filter": f"reference.DOI:{doi}",
+                    "select": "DOI,title,author,published-print,abstract"
+                }
+            ) as response:
+                if response.status != 200:
+                    print(f"获取引用信息失败: HTTP {response.status}")
+                    print(f"响应内容: {await response.text()}")
+                    return []
+
+                try:
+                    data = await response.json()
+                    # 检查返回的数据结构
+                    if isinstance(data, dict):
+                        items = data.get("message", {}).get("items", [])
+                        return [self._parse_work(work) for work in items]
+                    else:
+                        print(f"API返回了意外的数据格式: {type(data)}")
+                        return []
+                except Exception as e:
+                    print(f"解析引用数据时发生错误: {str(e)}")
+                    return []
+
+    def _parse_work(self, work: Dict) -> PaperMetadata:
+        """解析Crossref返回的数据"""
+        # 获取摘要 - 处理可能的不同格式
+        abstract = ""
+        if isinstance(work.get("abstract"), str):
+            abstract = work.get("abstract", "")
+        elif isinstance(work.get("abstract"), dict):
+            abstract = work.get("abstract", {}).get("value", "")
+
+        if not abstract:
+            print(f"警告: 论文 '{work.get('title', [''])[0]}' 没有可用的摘要")
+
+        # 获取机构信息
+        institutions = []
+        for author in work.get("author", []):
+            if "affiliation" in author:
+                for affiliation in author["affiliation"]:
+                    if "name" in affiliation and affiliation["name"] not in institutions:
+                        institutions.append(affiliation["name"])
+
+        # 获取venue信息
+        venue_name = work.get("container-title", [None])[0]
+        venue_type = work.get("type", "unknown")  # 文献类型
+        venue_info = {
+            "publisher": work.get("publisher"),
+            "issn": work.get("ISSN", []),
+            "isbn": work.get("ISBN", []),
+            "issue": work.get("issue"),
+            "volume": work.get("volume"),
+            "page": work.get("page")
+        }
+
+        return PaperMetadata(
+            title=work.get("title", [None])[0] or "",
+            authors=[
+                author.get("given", "") + " " + author.get("family", "")
+                for author in work.get("author", [])
+            ],
+            institutions=institutions,  # 添加机构信息
+            abstract=abstract,
+            year=work.get("published-print", {}).get("date-parts", [[None]])[0][0],
+            doi=work.get("DOI"),
+            url=f"https://doi.org/{work.get('DOI')}" if work.get("DOI") else None,
+            citations=work.get("is-referenced-by-count"),
+            venue=venue_name,
+            venue_type=venue_type,  # 添加venue类型
+            venue_name=venue_name,  # 添加venue名称
+            venue_info=venue_info,  # 添加venue详细信息
+            source='crossref'  # 添加来源标记
+        )
+
+    async def search_by_authors(
+        self,
+        authors: List[str],
+        limit: int = 100,
+        sort_by: str = None,
+        start_year: int = None
+    ) -> List[PaperMetadata]:
+        """按作者搜索论文"""
+        query = " ".join([f"author:\"{author}\"" for author in authors])
+        return await self.search(
+            query=query,
+            limit=limit,
+            sort_by=sort_by,
+            start_year=start_year
+        )
+
+    async def search_by_date_range(
+        self,
+        start_date: datetime,
+        end_date: datetime,
+        limit: int = 100,
+        sort_by: str = None,
+        sort_order: str = None
+    ) -> List[PaperMetadata]:
+        """按日期范围搜索论文"""
+        query = f"from-pub-date:{start_date.strftime('%Y-%m-%d')} until-pub-date:{end_date.strftime('%Y-%m-%d')}"
+        return await self.search(
+            query=query,
+            limit=limit,
+            sort_by=sort_by,
+            sort_order=sort_order
+        )
+
+async def example_usage():
+    """CrossrefSource使用示例"""
+    crossref = CrossrefSource(api_key=None)
+
+    try:
+        # 示例1：基本搜索，使用不同的排序方式
+        print("\n=== 示例1：搜索最新的机器学习论文 ===")
+        papers = await crossref.search(
+            query="machine learning",
+            limit=3,
+            sort_by="published",
+            sort_order="desc",
+            start_year=2023
+        )
+
+        for i, paper in enumerate(papers, 1):
+            print(f"\n--- 论文 {i} ---")
+            print(f"标题: {paper.title}")
+            print(f"作者: {', '.join(paper.authors)}")
+            print(f"发表年份: {paper.year}")
+            print(f"DOI: {paper.doi}")
+            print(f"URL: {paper.url}")
+            if paper.abstract:
+                print(f"摘要: {paper.abstract[:200]}...")
+            if paper.institutions:
+                print(f"机构: {', '.join(paper.institutions)}")
+            print(f"引用次数: {paper.citations}")
+            print(f"发表venue: {paper.venue}")
+            print(f"venue类型: {paper.venue_type}")
+            if paper.venue_info:
+                print("Venue详细信息:")
+                for key, value in paper.venue_info.items():
+                    if value:
+                        print(f"  - {key}: {value}")
+
+        # 示例2：按DOI获取论文详情
+        print("\n=== 示例2：获取特定论文详情 ===")
+        # 使用BERT论文的DOI
+        doi = "10.18653/v1/N19-1423"
+        paper = await crossref.get_paper_details(doi)
+        if paper:
+            print(f"标题: {paper.title}")
+            print(f"作者: {', '.join(paper.authors)}")
+            print(f"发表年份: {paper.year}")
+            print(f"DOI: {paper.doi}")
+            if paper.abstract:
+                print(f"摘要: {paper.abstract[:200]}...")
+            print(f"引用次数: {paper.citations}")
+
+        # 示例3：按作者搜索
+        print("\n=== 示例3：搜索特定作者的论文 ===")
+        author_papers = await crossref.search_by_authors(
+            authors=["Yoshua Bengio"],
+            limit=3,
+            sort_by="published",
+            start_year=2020
+        )
+        for i, paper in enumerate(author_papers, 1):
+            print(f"\n--- {i}. {paper.title} ---")
+            print(f"作者: {', '.join(paper.authors)}")
+            print(f"发表年份: {paper.year}")
+            print(f"DOI: {paper.doi}")
+            print(f"引用次数: {paper.citations}")
+
+        # 示例4：按日期范围搜索
+        print("\n=== 示例4：搜索特定日期范围的论文 ===")
+        from datetime import datetime, timedelta
+        end_date = datetime.now()
+        start_date = end_date - timedelta(days=30)  # 最近一个月
+        recent_papers = await crossref.search_by_date_range(
+            start_date=start_date,
+            end_date=end_date,
+            limit=3,
+            sort_by="published",
+            sort_order="desc"
+        )
+        for i, paper in enumerate(recent_papers, 1):
+            print(f"\n--- 最近发表的论文 {i} ---")
+            print(f"标题: {paper.title}")
+            print(f"作者: {', '.join(paper.authors)}")
+            print(f"发表年份: {paper.year}")
+            print(f"DOI: {paper.doi}")
+
+        # 示例5：获取论文引用信息
+        print("\n=== 示例5：获取论文引用信息 ===")
+        if paper:  # 使用之前获取的BERT论文
+            print("\n获取引用该论文的文献:")
+            citations = await crossref.get_citations(paper.doi)
+            for i, citing_paper in enumerate(citations[:3], 1):
+                print(f"\n--- 引用论文 {i} ---")
+                print(f"标题: {citing_paper.title}")
+                print(f"作者: {', '.join(citing_paper.authors)}")
+                print(f"发表年份: {citing_paper.year}")
+
+            print("\n获取该论文引用的参考文献:")
+            references = await crossref.get_references(paper.doi)
+            for i, ref_paper in enumerate(references[:3], 1):
+                print(f"\n--- 参考文献 {i} ---")
+                print(f"标题: {ref_paper.title}")
+                print(f"作者: {', '.join(ref_paper.authors)}")
+                print(f"发表年份: {ref_paper.year if ref_paper.year else '未知'}")
+
+        # 示例6：展示venue信息的使用
+        print("\n=== 示例6：展示期刊/会议详细信息 ===")
+        if papers:
+            paper = papers[0]
+            print(f"文献类型: {paper.venue_type}")
+            print(f"发表venue: {paper.venue_name}")
+            if paper.venue_info:
+                print("Venue详细信息:")
+                for key, value in paper.venue_info.items():
+                    if value:
+                        print(f"  - {key}: {value}")
+
+    except Exception as e:
+        print(f"发生错误: {str(e)}")
+        import traceback
+        print(traceback.format_exc())
+
+if __name__ == "__main__":
+    import asyncio
+
+    # 运行示例
+    asyncio.run(example_usage())
--- a/crazy_functions/review_fns/data_sources/elsevier_source.py
+++ b/crazy_functions/review_fns/data_sources/elsevier_source.py
@@ -0,0 +1,449 @@
+from typing import List, Optional, Dict, Union
+from datetime import datetime
+import aiohttp
+import asyncio
+from crazy_functions.review_fns.data_sources.base_source import DataSource, PaperMetadata
+import json
+from tqdm import tqdm
+import random
+
+class ElsevierSource(DataSource):
+    """Elsevier (Scopus) API实现"""
+
+    # 定义API密钥列表
+    API_KEYS = [
+        "xxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
+        "xxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
+    ]
+
+    def __init__(self, api_key: str = None):
+        """初始化
+
+        Args:
+            api_key: Elsevier API密钥，如果不提供则从预定义列表中随机选择
+        """
+        self.api_key = api_key or random.choice(self.API_KEYS)
+        self._initialize()
+
+    def _initialize(self) -> None:
+        """初始化基础URL和请求头"""
+        self.base_url = "https://api.elsevier.com/content"
+        self.headers = {
+            "X-ELS-APIKey": self.api_key,
+            "Accept": "application/json",
+            "Content-Type": "application/json",
+            # 添加更多必要的头部信息
+            "X-ELS-Insttoken": "",  # 如果有机构令牌
+        }
+
+    async def _make_request(self, url: str, params: Dict = None) -> Optional[Dict]:
+        """发送HTTP请求
+
+        Args:
+            url: 请求URL
+            params: 查询参数
+
+        Returns:
+            JSON响应
+        """
+        try:
+            async with aiohttp.ClientSession(headers=self.headers) as session:
+                async with session.get(url, params=params) as response:
+                    if response.status == 200:
+                        return await response.json()
+                    else:
+                        # 添加更详细的错误信息
+                        error_text = await response.text()
+                        print(f"请求失败: {response.status}")
+                        print(f"错误详情: {error_text}")
+                        if response.status == 401:
+                            print(f"使用的API密钥: {self.api_key}")
+                            # 尝试切换到另一个API密钥
+                            new_key = random.choice([k for k in self.API_KEYS if k != self.api_key])
+                            print(f"尝试切换到新的API密钥: {new_key}")
+                            self.api_key = new_key
+                            self.headers["X-ELS-APIKey"] = new_key
+                            # 重试请求
+                            return await self._make_request(url, params)
+                        return None
+        except Exception as e:
+            print(f"请求发生错误: {str(e)}")
+            return None
+
+    async def search(
+        self,
+        query: str,
+        limit: int = 100,
+        sort_by: str = "relevance",
+        start_year: int = None
+    ) -> List[PaperMetadata]:
+        """搜索论文"""
+        try:
+            params = {
+                "query": query,
+                "count": min(limit, 100),
+                "view": "STANDARD",
+                # 移除dc:description字段，因为它在STANDARD视图中不可用
+                "field": "dc:title,dc:creator,prism:doi,prism:coverDate,citedby-count,prism:publicationName"
+            }
+
+            # 添加年份过滤
+            if start_year:
+                params["date"] = f"{start_year}-present"
+
+            # 添加排序
+            if sort_by == "date":
+                params["sort"] = "-coverDate"
+            elif sort_by == "cited":
+                params["sort"] = "-citedby-count"
+
+            # 发送搜索请求
+            response = await self._make_request(
+                f"{self.base_url}/search/scopus",
+                params=params
+            )
+
+            if not response or "search-results" not in response:
+                return []
+
+            # 解析搜索结果
+            entries = response["search-results"].get("entry", [])
+            papers = [paper for paper in (self._parse_entry(entry) for entry in entries) if paper is not None]
+
+            # 尝试为每篇论文获取摘要
+            for paper in papers:
+                if paper.doi:
+                    paper.abstract = await self.fetch_abstract(paper.doi) or ""
+
+            return papers
+
+        except Exception as e:
+            print(f"搜索论文时发生错误: {str(e)}")
+            return []
+
+    def _parse_entry(self, entry: Dict) -> Optional[PaperMetadata]:
+        """解析Scopus API返回的条目"""
+        try:
+            # 获取作者列表
+            authors = []
+            creator = entry.get("dc:creator")
+            if creator:
+                authors = [creator]
+
+            # 获取发表年份
+            year = None
+            if "prism:coverDate" in entry:
+                try:
+                    year = int(entry["prism:coverDate"][:4])
+                except:
+                    pass
+
+            # 简化venue信息
+            venue_info = {
+                'source_id': entry.get("source-id"),
+                'issn': entry.get("prism:issn")
+            }
+
+            return PaperMetadata(
+                title=entry.get("dc:title", ""),
+                authors=authors,
+                abstract=entry.get("dc:description", ""),  # 从响应中获取摘要
+                year=year,
+                doi=entry.get("prism:doi"),
+                url=entry.get("prism:url"),
+                citations=int(entry.get("citedby-count", 0)),
+                venue=entry.get("prism:publicationName"),
+                institutions=[],  # 移除机构信息
+                venue_type="",
+                venue_name=entry.get("prism:publicationName"),
+                venue_info=venue_info
+            )
+
+        except Exception as e:
+            print(f"解析条目时发生错误: {str(e)}")
+            return None
+
+    async def get_citations(self, doi: str, limit: int = 100) -> List[PaperMetadata]:
+        """获取引用该论文的文献"""
+        try:
+            params = {
+                "query": f"REF({doi})",
+                "count": min(limit, 100),
+                "view": "STANDARD"
+            }
+
+            response = await self._make_request(
+                f"{self.base_url}/search/scopus",
+                params=params
+            )
+
+            if not response or "search-results" not in response:
+                return []
+
+            entries = response["search-results"].get("entry", [])
+            return [self._parse_entry(entry) for entry in entries]
+
+        except Exception as e:
+            print(f"获取引用文献时发生错误: {str(e)}")
+            return []
+
+    async def get_references(self, doi: str) -> List[PaperMetadata]:
+        """获取该论文引用的文献"""
+        try:
+            response = await self._make_request(
+                f"{self.base_url}/abstract/doi/{doi}/references",
+                params={"view": "STANDARD"}
+            )
+
+            if not response or "references" not in response:
+                return []
+
+            references = response["references"].get("reference", [])
+            papers = [paper for paper in (self._parse_reference(ref) for ref in references) if paper is not None]
+            return papers
+
+        except Exception as e:
+            print(f"获取参考文献时发生错误: {str(e)}")
+            return []
+
+    def _parse_reference(self, ref: Dict) -> Optional[PaperMetadata]:
+        """解析参考文献数据"""
+        try:
+            authors = []
+            if "author-list" in ref:
+                author_list = ref["author-list"].get("author", [])
+                if isinstance(author_list, list):
+                    authors = [f"{author.get('ce:given-name', '')} {author.get('ce:surname', '')}"
+                             for author in author_list]
+                else:
+                    authors = [f"{author_list.get('ce:given-name', '')} {author_list.get('ce:surname', '')}"]
+
+            year = None
+            if "prism:coverDate" in ref:
+                try:
+                    year = int(ref["prism:coverDate"][:4])
+                except:
+                    pass
+
+            return PaperMetadata(
+                title=ref.get("ce:title", ""),
+                authors=authors,
+                abstract="",  # 参考文献通常不包含摘要
+                year=year,
+                doi=ref.get("prism:doi"),
+                url=None,
+                citations=None,
+                venue=ref.get("prism:publicationName"),
+                institutions=[],
+                venue_type="unknown",
+                venue_name=ref.get("prism:publicationName"),
+                venue_info={}
+            )
+
+        except Exception as e:
+            print(f"解析参考文献时发生错误: {str(e)}")
+            return None
+
+    async def search_by_author(
+        self,
+        author: str,
+        limit: int = 100,
+        start_year: int = None
+    ) -> List[PaperMetadata]:
+        """按作者搜索论文"""
+        query = f"AUTHOR-NAME({author})"
+        return await self.search(query, limit=limit, start_year=start_year)
+
+    async def search_by_affiliation(
+        self,
+        affiliation: str,
+        limit: int = 100,
+        start_year: int = None
+    ) -> List[PaperMetadata]:
+        """按机构搜索论文"""
+        query = f"AF-ID({affiliation})"
+        return await self.search(query, limit=limit, start_year=start_year)
+
+    async def search_by_venue(
+        self,
+        venue: str,
+        limit: int = 100,
+        start_year: int = None
+    ) -> List[PaperMetadata]:
+        """按期刊/会议搜索论文"""
+        query = f"SRCTITLE({venue})"
+        return await self.search(query, limit=limit, start_year=start_year)
+
+    async def test_api_access(self):
+        """测试API访问权限"""
+        print(f"\n测试API密钥: {self.api_key}")
+
+        # 测试1: 基础搜索
+        basic_params = {
+            "query": "test",
+            "count": 1,
+            "view": "STANDARD"
+        }
+        print("\n1. 测试基础搜索...")
+        response = await self._make_request(
+            f"{self.base_url}/search/scopus",
+            params=basic_params
+        )
+        if response:
+            print("基础搜索成功")
+            print("可用字段:", list(response.get("search-results", {}).get("entry", [{}])[0].keys()))
+
+        # 测试2: 测试单篇文章访问
+        print("\n2. 测试文章详情访问...")
+        test_doi = "10.1016/j.artint.2021.103535"  # 一个示例DOI
+        response = await self._make_request(
+            f"{self.base_url}/abstract/doi/{test_doi}",
+            params={"view": "STANDARD"}  # 改为STANDARD视图
+        )
+        if response:
+            print("文章详情访问成功")
+        else:
+            print("文章详情访问失败")
+
+    async def get_paper_details(self, paper_id: str) -> Optional[PaperMetadata]:
+        """获取论文详细信息
+
+        注意：当前API权限不支持获取详细信息，返回None
+
+        Args:
+            paper_id: 论文ID
+
+        Returns:
+            None，因为当前API权限不支持此功能
+        """
+        return None
+
+    async def fetch_abstract(self, doi: str) -> Optional[str]:
+        """获取论文摘要
+
+        使用Scopus Abstract API获取论文摘要
+
+        Args:
+            doi: 论文的DOI
+
+        Returns:
+            摘要文本，如果获取失败则返回None
+        """
+        try:
+            # 使用Abstract API而不是Search API
+            response = await self._make_request(
+                f"{self.base_url}/abstract/doi/{doi}",
+                params={
+                    "view": "FULL"  # 使用FULL视图
+                }
+            )
+
+            if response and "abstracts-retrieval-response" in response:
+                # 从coredata中获取摘要
+                coredata = response["abstracts-retrieval-response"].get("coredata", {})
+                return coredata.get("dc:description", "")
+
+            return None
+
+        except Exception as e:
+            print(f"获取摘要时发生错误: {str(e)}")
+            return None
+
+async def example_usage():
+    """ElsevierSource使用示例"""
+    elsevier = ElsevierSource()
+
+    try:
+        # 首先测试API访问权限
+        print("\n=== 测试API访问权限 ===")
+        await elsevier.test_api_access()
+
+        # 示例1：基本搜索
+        print("\n=== 示例1：搜索机器学习相关论文 ===")
+        papers = await elsevier.search("machine learning", limit=3)
+        for i, paper in enumerate(papers, 1):
+            print(f"\n--- 论文 {i} ---")
+            print(f"标题: {paper.title}")
+            print(f"作者: {', '.join(paper.authors)}")
+            print(f"发表年份: {paper.year}")
+            print(f"DOI: {paper.doi}")
+            print(f"URL: {paper.url}")
+            print(f"引用次数: {paper.citations}")
+            print(f"期刊/会议: {paper.venue}")
+            print("期刊信息:")
+            for key, value in paper.venue_info.items():
+                if value:  # 只打印非空值
+                    print(f"  - {key}: {value}")
+
+        # 示例2：获取引用信息
+        if papers and papers[0].doi:
+            print("\n=== 示例2：获取引用该论文的文献 ===")
+            citations = await elsevier.get_citations(papers[0].doi, limit=3)
+            for i, paper in enumerate(citations, 1):
+                print(f"\n--- 引用论文 {i} ---")
+                print(f"标题: {paper.title}")
+                print(f"作者: {', '.join(paper.authors)}")
+                print(f"发表年份: {paper.year}")
+                print(f"DOI: {paper.doi}")
+                print(f"引用次数: {paper.citations}")
+                print(f"期刊/会议: {paper.venue}")
+
+        # 示例3：获取参考文献
+        if papers and papers[0].doi:
+            print("\n=== 示例3：获取论文的参考文献 ===")
+            references = await elsevier.get_references(papers[0].doi)
+            for i, paper in enumerate(references[:3], 1):
+                print(f"\n--- 参考文献 {i} ---")
+                print(f"标题: {paper.title}")
+                print(f"作者: {', '.join(paper.authors)}")
+                print(f"发表年份: {paper.year}")
+                print(f"DOI: {paper.doi}")
+                print(f"期刊/会议: {paper.venue}")
+
+        # 示例4：按作者搜索
+        print("\n=== 示例4：按作者搜索 ===")
+        author_papers = await elsevier.search_by_author("Hinton G", limit=3)
+        for i, paper in enumerate(author_papers, 1):
+            print(f"\n--- 论文 {i} ---")
+            print(f"标题: {paper.title}")
+            print(f"作者: {', '.join(paper.authors)}")
+            print(f"发表年份: {paper.year}")
+            print(f"DOI: {paper.doi}")
+            print(f"引用次数: {paper.citations}")
+            print(f"期刊/会议: {paper.venue}")
+
+        # 示例5：按机构搜索
+        print("\n=== 示例5：按机构搜索 ===")
+        affiliation_papers = await elsevier.search_by_affiliation("60027950", limit=3)  # MIT的机构ID
+        for i, paper in enumerate(affiliation_papers, 1):
+            print(f"\n--- 论文 {i} ---")
+            print(f"标题: {paper.title}")
+            print(f"作者: {', '.join(paper.authors)}")
+            print(f"发表年份: {paper.year}")
+            print(f"DOI: {paper.doi}")
+            print(f"引用次数: {paper.citations}")
+            print(f"期刊/会议: {paper.venue}")
+
+        # 示例6：获取论文摘要
+        print("\n=== 示例6：获取论文摘要 ===")
+        test_doi = "10.1016/j.artint.2021.103535"
+        abstract = await elsevier.fetch_abstract(test_doi)
+        if abstract:
+            print(f"摘要: {abstract[:200]}...")  # 只显示前200个字符
+        else:
+            print("无法获取摘要")
+
+        # 在搜索结果中显示摘要
+        print("\n=== 示例7：搜索结果中的摘要 ===")
+        papers = await elsevier.search("machine learning", limit=1)
+        for paper in papers:
+            print(f"标题: {paper.title}")
+            print(f"摘要: {paper.abstract[:200]}..." if paper.abstract else "摘要: 无")
+
+    except Exception as e:
+        print(f"发生错误: {str(e)}")
+        import traceback
+        print(traceback.format_exc())
+
+if __name__ == "__main__":
+    asyncio.run(example_usage())
--- a/crazy_functions/review_fns/data_sources/github_source.py
+++ b/crazy_functions/review_fns/data_sources/github_source.py
@@ -0,0 +1,698 @@
+import aiohttp
+import asyncio
+import base64
+import json
+import random
+from datetime import datetime
+from typing import List, Dict, Optional, Union, Any
+
+class GitHubSource:
+    """GitHub API实现"""
+
+    # 默认API密钥列表 - 可以放置多个GitHub令牌
+    API_KEYS = [
+        "github_pat_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
+        "github_pat_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
+    ]
+
+    def __init__(self, api_key: Optional[Union[str, List[str]]] = None):
+        """初始化GitHub API客户端
+
+        Args:
+            api_key: GitHub个人访问令牌或令牌列表
+        """
+        if api_key is None:
+            self.api_keys = self.API_KEYS
+        elif isinstance(api_key, str):
+            self.api_keys = [api_key]
+        else:
+            self.api_keys = api_key
+
+        self._initialize()
+
+    def _initialize(self) -> None:
+        """初始化客户端，设置默认参数"""
+        self.base_url = "https://api.github.com"
+        self.headers = {
+            "Accept": "application/vnd.github+json",
+            "X-GitHub-Api-Version": "2022-11-28",
+            "User-Agent": "GitHub-API-Python-Client"
+        }
+
+        # 如果有可用的API密钥，随机选择一个
+        if self.api_keys:
+            selected_key = random.choice(self.api_keys)
+            self.headers["Authorization"] = f"Bearer {selected_key}"
+            print(f"已随机选择API密钥进行认证")
+        else:
+            print("警告: 未提供API密钥，将受到GitHub API请求限制")
+
+    async def _request(self, method: str, endpoint: str, params: Dict = None, data: Dict = None) -> Any:
+        """发送API请求
+
+        Args:
+            method: HTTP方法 (GET, POST, PUT, DELETE等)
+            endpoint: API端点
+            params: URL参数
+            data: 请求体数据
+
+        Returns:
+            解析后的响应JSON
+        """
+        async with aiohttp.ClientSession(headers=self.headers) as session:
+            url = f"{self.base_url}{endpoint}"
+
+            # 为调试目的打印请求信息
+            print(f"请求: {method} {url}")
+            if params:
+                print(f"参数: {params}")
+
+            # 发送请求
+            request_kwargs = {}
+            if params:
+                request_kwargs["params"] = params
+            if data:
+                request_kwargs["json"] = data
+
+            async with session.request(method, url, **request_kwargs) as response:
+                response_text = await response.text()
+
+                # 检查HTTP状态码
+                if response.status >= 400:
+                    print(f"API请求失败: HTTP {response.status}")
+                    print(f"响应内容: {response_text}")
+                    return None
+
+                # 解析JSON响应
+                try:
+                    return json.loads(response_text)
+                except json.JSONDecodeError:
+                    print(f"JSON解析错误: {response_text}")
+                    return None
+
+    # ===== 用户相关方法 =====
+
+    async def get_user(self, username: Optional[str] = None) -> Dict:
+        """获取用户信息
+
+        Args:
+            username: 指定用户名，不指定则获取当前授权用户
+
+        Returns:
+            用户信息字典
+        """
+        endpoint = "/user" if username is None else f"/users/{username}"
+        return await self._request("GET", endpoint)
+
+    async def get_user_repos(self, username: Optional[str] = None, sort: str = "updated",
+                            direction: str = "desc", per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取用户的仓库列表
+
+        Args:
+            username: 指定用户名，不指定则获取当前授权用户
+            sort: 排序方式 (created, updated, pushed, full_name)
+            direction: 排序方向 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            仓库列表
+        """
+        endpoint = "/user/repos" if username is None else f"/users/{username}/repos"
+        params = {
+            "sort": sort,
+            "direction": direction,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_user_starred(self, username: Optional[str] = None,
+                              per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取用户星标的仓库
+
+        Args:
+            username: 指定用户名，不指定则获取当前授权用户
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            星标仓库列表
+        """
+        endpoint = "/user/starred" if username is None else f"/users/{username}/starred"
+        params = {
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    # ===== 仓库相关方法 =====
+
+    async def get_repo(self, owner: str, repo: str) -> Dict:
+        """获取仓库信息
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+
+        Returns:
+            仓库信息
+        """
+        endpoint = f"/repos/{owner}/{repo}"
+        return await self._request("GET", endpoint)
+
+    async def get_repo_branches(self, owner: str, repo: str, per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取仓库的分支列表
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            分支列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/branches"
+        params = {
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_repo_commits(self, owner: str, repo: str, sha: Optional[str] = None,
+                              path: Optional[str] = None, per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取仓库的提交历史
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            sha: 特定提交SHA或分支名
+            path: 文件路径筛选
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            提交列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/commits"
+        params = {
+            "per_page": per_page,
+            "page": page
+        }
+        if sha:
+            params["sha"] = sha
+        if path:
+            params["path"] = path
+
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_commit_details(self, owner: str, repo: str, commit_sha: str) -> Dict:
+        """获取特定提交的详情
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            commit_sha: 提交SHA
+
+        Returns:
+            提交详情
+        """
+        endpoint = f"/repos/{owner}/{repo}/commits/{commit_sha}"
+        return await self._request("GET", endpoint)
+
+    # ===== 内容相关方法 =====
+
+    async def get_file_content(self, owner: str, repo: str, path: str, ref: Optional[str] = None) -> Dict:
+        """获取文件内容
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            path: 文件路径
+            ref: 分支名、标签名或提交SHA
+
+        Returns:
+            文件内容信息
+        """
+        endpoint = f"/repos/{owner}/{repo}/contents/{path}"
+        params = {}
+        if ref:
+            params["ref"] = ref
+
+        response = await self._request("GET", endpoint, params=params)
+        if response and isinstance(response, dict) and "content" in response:
+            try:
+                # 解码Base64编码的文件内容
+                content = base64.b64decode(response["content"].encode()).decode()
+                response["decoded_content"] = content
+            except Exception as e:
+                print(f"解码文件内容时出错: {str(e)}")
+
+        return response
+
+    async def get_directory_content(self, owner: str, repo: str, path: str, ref: Optional[str] = None) -> List[Dict]:
+        """获取目录内容
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            path: 目录路径
+            ref: 分支名、标签名或提交SHA
+
+        Returns:
+            目录内容列表
+        """
+        # 注意：此方法与get_file_content使用相同的端点，但对于目录会返回列表
+        endpoint = f"/repos/{owner}/{repo}/contents/{path}"
+        params = {}
+        if ref:
+            params["ref"] = ref
+
+        return await self._request("GET", endpoint, params=params)
+
+    # ===== Issues相关方法 =====
+
+    async def get_issues(self, owner: str, repo: str, state: str = "open",
+                        sort: str = "created", direction: str = "desc",
+                        per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取仓库的Issues列表
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            state: Issue状态 (open, closed, all)
+            sort: 排序方式 (created, updated, comments)
+            direction: 排序方向 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            Issues列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/issues"
+        params = {
+            "state": state,
+            "sort": sort,
+            "direction": direction,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_issue(self, owner: str, repo: str, issue_number: int) -> Dict:
+        """获取特定Issue的详情
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            issue_number: Issue编号
+
+        Returns:
+            Issue详情
+        """
+        endpoint = f"/repos/{owner}/{repo}/issues/{issue_number}"
+        return await self._request("GET", endpoint)
+
+    async def get_issue_comments(self, owner: str, repo: str, issue_number: int) -> List[Dict]:
+        """获取Issue的评论
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            issue_number: Issue编号
+
+        Returns:
+            评论列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/issues/{issue_number}/comments"
+        return await self._request("GET", endpoint)
+
+    # ===== Pull Requests相关方法 =====
+
+    async def get_pull_requests(self, owner: str, repo: str, state: str = "open",
+                               sort: str = "created", direction: str = "desc",
+                               per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取仓库的Pull Request列表
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            state: PR状态 (open, closed, all)
+            sort: 排序方式 (created, updated, popularity, long-running)
+            direction: 排序方向 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            Pull Request列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/pulls"
+        params = {
+            "state": state,
+            "sort": sort,
+            "direction": direction,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_pull_request(self, owner: str, repo: str, pr_number: int) -> Dict:
+        """获取特定Pull Request的详情
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            pr_number: Pull Request编号
+
+        Returns:
+            Pull Request详情
+        """
+        endpoint = f"/repos/{owner}/{repo}/pulls/{pr_number}"
+        return await self._request("GET", endpoint)
+
+    async def get_pull_request_files(self, owner: str, repo: str, pr_number: int) -> List[Dict]:
+        """获取Pull Request中修改的文件
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+            pr_number: Pull Request编号
+
+        Returns:
+            修改文件列表
+        """
+        endpoint = f"/repos/{owner}/{repo}/pulls/{pr_number}/files"
+        return await self._request("GET", endpoint)
+
+    # ===== 搜索相关方法 =====
+
+    async def search_repositories(self, query: str, sort: str = "stars",
+                                 order: str = "desc", per_page: int = 30, page: int = 1) -> Dict:
+        """搜索仓库
+
+        Args:
+            query: 搜索关键词
+            sort: 排序方式 (stars, forks, updated)
+            order: 排序顺序 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            搜索结果
+        """
+        endpoint = "/search/repositories"
+        params = {
+            "q": query,
+            "sort": sort,
+            "order": order,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def search_code(self, query: str, sort: str = "indexed",
+                         order: str = "desc", per_page: int = 30, page: int = 1) -> Dict:
+        """搜索代码
+
+        Args:
+            query: 搜索关键词
+            sort: 排序方式 (indexed)
+            order: 排序顺序 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            搜索结果
+        """
+        endpoint = "/search/code"
+        params = {
+            "q": query,
+            "sort": sort,
+            "order": order,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def search_issues(self, query: str, sort: str = "created",
+                           order: str = "desc", per_page: int = 30, page: int = 1) -> Dict:
+        """搜索Issues和Pull Requests
+
+        Args:
+            query: 搜索关键词
+            sort: 排序方式 (created, updated, comments)
+            order: 排序顺序 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            搜索结果
+        """
+        endpoint = "/search/issues"
+        params = {
+            "q": query,
+            "sort": sort,
+            "order": order,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def search_users(self, query: str, sort: str = "followers",
+                          order: str = "desc", per_page: int = 30, page: int = 1) -> Dict:
+        """搜索用户
+
+        Args:
+            query: 搜索关键词
+            sort: 排序方式 (followers, repositories, joined)
+            order: 排序顺序 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            搜索结果
+        """
+        endpoint = "/search/users"
+        params = {
+            "q": query,
+            "sort": sort,
+            "order": order,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    # ===== 组织相关方法 =====
+
+    async def get_organization(self, org: str) -> Dict:
+        """获取组织信息
+
+        Args:
+            org: 组织名称
+
+        Returns:
+            组织信息
+        """
+        endpoint = f"/orgs/{org}"
+        return await self._request("GET", endpoint)
+
+    async def get_organization_repos(self, org: str, type: str = "all",
+                                    sort: str = "created", direction: str = "desc",
+                                    per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取组织的仓库列表
+
+        Args:
+            org: 组织名称
+            type: 仓库类型 (all, public, private, forks, sources, member, internal)
+            sort: 排序方式 (created, updated, pushed, full_name)
+            direction: 排序方向 (asc, desc)
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            仓库列表
+        """
+        endpoint = f"/orgs/{org}/repos"
+        params = {
+            "type": type,
+            "sort": sort,
+            "direction": direction,
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    async def get_organization_members(self, org: str, per_page: int = 30, page: int = 1) -> List[Dict]:
+        """获取组织成员列表
+
+        Args:
+            org: 组织名称
+            per_page: 每页结果数量
+            page: 页码
+
+        Returns:
+            成员列表
+        """
+        endpoint = f"/orgs/{org}/members"
+        params = {
+            "per_page": per_page,
+            "page": page
+        }
+        return await self._request("GET", endpoint, params=params)
+
+    # ===== 更复杂的操作 =====
+
+    async def get_repository_languages(self, owner: str, repo: str) -> Dict:
+        """获取仓库使用的编程语言及其比例
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+
+        Returns:
+            语言使用情况
+        """
+        endpoint = f"/repos/{owner}/{repo}/languages"
+        return await self._request("GET", endpoint)
+
+    async def get_repository_stats_contributors(self, owner: str, repo: str) -> List[Dict]:
+        """获取仓库的贡献者统计
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+
+        Returns:
+            贡献者统计信息
+        """
+        endpoint = f"/repos/{owner}/{repo}/stats/contributors"
+        return await self._request("GET", endpoint)
+
+    async def get_repository_stats_commit_activity(self, owner: str, repo: str) -> List[Dict]:
+        """获取仓库的提交活动
+
+        Args:
+            owner: 仓库所有者
+            repo: 仓库名
+
+        Returns:
+            提交活动统计
+        """
+        endpoint = f"/repos/{owner}/{repo}/stats/commit_activity"
+        return await self._request("GET", endpoint)
+
+async def example_usage():
+    """GitHubSource使用示例"""
+    # 创建客户端实例（可选传入API令牌）
+    # github = GitHubSource(api_key="your_github_token")
+    github = GitHubSource()
+
+    try:
+        # 示例1：搜索热门Python仓库
+        print("\n=== 示例1：搜索热门Python仓库 ===")
+        repos = await github.search_repositories(
+            query="language:python stars:>1000",
+            sort="stars",
+            order="desc",
+            per_page=5
+        )
+
+        if repos and "items" in repos:
+            for i, repo in enumerate(repos["items"], 1):
+                print(f"\n--- 仓库 {i} ---")
+                print(f"名称: {repo['full_name']}")
+                print(f"描述: {repo['description']}")
+                print(f"星标数: {repo['stargazers_count']}")
+                print(f"Fork数: {repo['forks_count']}")
+                print(f"最近更新: {repo['updated_at']}")
+                print(f"URL: {repo['html_url']}")
+
+        # 示例2：获取特定仓库的详情
+        print("\n=== 示例2：获取特定仓库的详情 ===")
+        repo_details = await github.get_repo("microsoft", "vscode")
+        if repo_details:
+            print(f"名称: {repo_details['full_name']}")
+            print(f"描述: {repo_details['description']}")
+            print(f"星标数: {repo_details['stargazers_count']}")
+            print(f"Fork数: {repo_details['forks_count']}")
+            print(f"默认分支: {repo_details['default_branch']}")
+            print(f"开源许可: {repo_details.get('license', {}).get('name', '无')}")
+            print(f"语言: {repo_details['language']}")
+            print(f"Open Issues数: {repo_details['open_issues_count']}")
+
+        # 示例3：获取仓库的提交历史
+        print("\n=== 示例3：获取仓库的最近提交 ===")
+        commits = await github.get_repo_commits("tensorflow", "tensorflow", per_page=5)
+        if commits:
+            for i, commit in enumerate(commits, 1):
+                print(f"\n--- 提交 {i} ---")
+                print(f"SHA: {commit['sha'][:7]}")
+                print(f"作者: {commit['commit']['author']['name']}")
+                print(f"日期: {commit['commit']['author']['date']}")
+                print(f"消息: {commit['commit']['message'].splitlines()[0]}")
+
+        # 示例4：搜索代码
+        print("\n=== 示例4：搜索代码 ===")
+        code_results = await github.search_code(
+            query="filename:README.md language:markdown pytorch in:file",
+            per_page=3
+        )
+        if code_results and "items" in code_results:
+            print(f"共找到: {code_results['total_count']} 个结果")
+            for i, item in enumerate(code_results["items"], 1):
+                print(f"\n--- 代码 {i} ---")
+                print(f"仓库: {item['repository']['full_name']}")
+                print(f"文件: {item['path']}")
+                print(f"URL: {item['html_url']}")
+
+        # 示例5：获取文件内容
+        print("\n=== 示例5：获取文件内容 ===")
+        file_content = await github.get_file_content("python", "cpython", "README.rst")
+        if file_content and "decoded_content" in file_content:
+            content = file_content["decoded_content"]
+            print(f"文件名: {file_content['name']}")
+            print(f"大小: {file_content['size']} 字节")
+            print(f"内容预览: {content[:200]}...")
+
+        # 示例6：获取仓库使用的编程语言
+        print("\n=== 示例6：获取仓库使用的编程语言 ===")
+        languages = await github.get_repository_languages("facebook", "react")
+        if languages:
+            print(f"React仓库使用的编程语言:")
+            for lang, bytes_of_code in languages.items():
+                print(f"- {lang}: {bytes_of_code} 字节")
+
+        # 示例7：获取组织信息
+        print("\n=== 示例7：获取组织信息 ===")
+        org_info = await github.get_organization("google")
+        if org_info:
+            print(f"名称: {org_info['name']}")
+            print(f"描述: {org_info.get('description', '无')}")
+            print(f"位置: {org_info.get('location', '未指定')}")
+            print(f"公共仓库数: {org_info['public_repos']}")
+            print(f"成员数: {org_info.get('public_members', 0)}")
+            print(f"URL: {org_info['html_url']}")
+
+        # 示例8：获取用户信息
+        print("\n=== 示例8：获取用户信息 ===")
+        user_info = await github.get_user("torvalds")
+        if user_info:
+            print(f"名称: {user_info['name']}")
+            print(f"公司: {user_info.get('company', '无')}")
+            print(f"博客: {user_info.get('blog', '无')}")
+            print(f"位置: {user_info.get('location', '未指定')}")
+            print(f"公共仓库数: {user_info['public_repos']}")
+            print(f"关注者数: {user_info['followers']}")
+            print(f"URL: {user_info['html_url']}")
+
+    except Exception as e:
+        print(f"发生错误: {str(e)}")
+        import traceback
+        print(traceback.format_exc())
+
+if __name__ == "__main__":
+    import asyncio
+
+    # 运行示例
+    asyncio.run(example_usage())
--- a/crazy_functions/review_fns/data_sources/journal_metrics.py
+++ b/crazy_functions/review_fns/data_sources/journal_metrics.py
@@ -0,0 +1,142 @@
+import json
+import os
+from typing import Dict, Optional
+
+class JournalMetrics:
+    """期刊指标管理类"""
+    
+    def __init__(self):
+        self.journal_data: Dict = {}  # 期刊名称到指标的映射
+        self.issn_map: Dict = {}      # ISSN到指标的映射
+        self.name_map: Dict = {}      # 标准化名称到指标的映射
+        self._load_journal_data()
+    
+    def _normalize_journal_name(self, name: str) -> str:
+        """标准化期刊名称
+        
+        Args:
+            name: 原始期刊名称
+            
+        Returns:
+            标准化后的期刊名称
+        """
+        if not name:
+            return ""
+            
+        # 转换为小写
+        name = name.lower()
+        
+        # 移除常见的前缀和后缀
+        prefixes = ['the ', 'proceedings of ', 'journal of ']
+        suffixes = [' journal', ' proceedings', ' magazine', ' review', ' letters']
+        
+        for prefix in prefixes:
+            if name.startswith(prefix):
+                name = name[len(prefix):]
+                
+        for suffix in suffixes:
+            if name.endswith(suffix):
+                name = name[:-len(suffix)]
+        
+        # 移除特殊字符，保留字母、数字和空格
+        name = ''.join(c for c in name if c.isalnum() or c.isspace())
+        
+        # 移除多余的空格
+        name = ' '.join(name.split())
+        
+        return name
+    
+    def _convert_if_value(self, if_str: str) -> Optional[float]:
+        """转换IF值为float，处理特殊情况"""
+        try:
+            if if_str.startswith('<'):
+                # 对于<0.1这样的值，返回0.1
+                return float(if_str.strip('<'))
+            return float(if_str)
+        except (ValueError, AttributeError):
+            return None
+    
+    def _load_journal_data(self):
+        """加载期刊数据"""
+        try:
+            file_path = os.path.join(os.path.dirname(__file__), 'cas_if.json')
+            with open(file_path, 'r', encoding='utf-8') as f:
+                data = json.load(f)
+                
+            # 建立期刊名称到指标的映射
+            for journal in data:
+                # 准备指标数据
+                metrics = {
+                    'if_factor': self._convert_if_value(journal.get('IF')),
+                    'jcr_division': journal.get('Q'),
+                    'cas_division': journal.get('B')
+                }
+                
+                # 存储期刊名称映射（使用标准化名称）
+                if journal.get('journal'):
+                    normalized_name = self._normalize_journal_name(journal['journal'])
+                    self.journal_data[normalized_name] = metrics
+                    self.name_map[normalized_name] = metrics
+                
+                # 存储期刊缩写映射
+                if journal.get('jabb'):
+                    normalized_abbr = self._normalize_journal_name(journal['jabb'])
+                    self.journal_data[normalized_abbr] = metrics
+                    self.name_map[normalized_abbr] = metrics
+                
+                # 存储ISSN映射
+                if journal.get('issn'):
+                    self.issn_map[journal['issn']] = metrics
+                if journal.get('eissn'):
+                    self.issn_map[journal['eissn']] = metrics
+                    
+        except Exception as e:
+            print(f"加载期刊数据时出错: {str(e)}")
+            self.journal_data = {}
+            self.issn_map = {}
+            self.name_map = {}
+    
+    def get_journal_metrics(self, venue_name: str, venue_info: dict) -> dict:
+        """获取期刊指标
+        
+        Args:
+            venue_name: 期刊名称
+            venue_info: 期刊详细信息
+            
+        Returns:
+            包含期刊指标的字典
+        """
+        try:
+            metrics = {}
+            
+            # 1. 首先尝试通过ISSN匹配
+            if venue_info and 'issn' in venue_info:
+                issn_value = venue_info['issn']
+                # 处理ISSN可能是列表的情况
+                if isinstance(issn_value, list):
+                    # 尝试每个ISSN
+                    for issn in issn_value:
+                        metrics = self.issn_map.get(issn, {})
+                        if metrics:  # 如果找到匹配的指标，就停止搜索
+                            break
+                else:  # ISSN是字符串的情况
+                    metrics = self.issn_map.get(issn_value, {})
+            
+            # 2. 如果ISSN匹配失败，尝试通过期刊名称匹配
+            if not metrics and venue_name:
+                # 标准化期刊名称
+                normalized_name = self._normalize_journal_name(venue_name)
+                metrics = self.name_map.get(normalized_name, {})
+                
+                # 如果完全匹配失败，尝试部分匹配
+                # if not metrics:
+                #     for db_name, db_metrics in self.name_map.items():
+                #         if normalized_name in db_name:
+                #             metrics = db_metrics
+                #             break
+            
+            return metrics
+            
+        except Exception as e:
+            print(f"获取期刊指标时出错: {str(e)}")
+            return {} 
--- a/crazy_functions/review_fns/data_sources/openalex_source.py
+++ b/crazy_functions/review_fns/data_sources/openalex_source.py
@@ -0,0 +1,163 @@
+import aiohttp
+from typing import List, Dict, Optional
+from datetime import datetime
+from .base_source import DataSource, PaperMetadata
+import os
+from urllib.parse import quote
+
+class OpenAlexSource(DataSource):
+    """OpenAlex API实现"""
+
+    def _initialize(self) -> None:
+        self.base_url = "https://api.openalex.org"
+        self.mailto = "xxxxxxxxxxxxxxxxxxxxxxxx@163.com"  # 直接写入邮件地址
+
+    async def search(self, query: str, limit: int = 100) -> List[PaperMetadata]:
+        params = {"mailto": self.mailto} if self.mailto else {}
+        params.update({
+            "filter": f"title.search:{query}",
+            "per-page": limit
+        })
+
+        async with aiohttp.ClientSession() as session:
+            async with session.get(
+                f"{self.base_url}/works",
+                params=params
+            ) as response:
+                try:
+                    response.raise_for_status()
+                    data = await response.json()
+                    results = data.get("results", [])
+                    return [self._parse_work(work) for work in results]
+                except Exception as e:
+                    print(f"搜索出错: {str(e)}")
+                    return []
+
+    def _parse_work(self, work: Dict) -> PaperMetadata:
+        """解析OpenAlex返回的数据"""
+        # 获取作者信息
+        raw_author_names = [
+            authorship.get("raw_author_name", "")
+            for authorship in work.get("authorships", [])
+            if authorship
+        ]
+        # 处理作者名字格式
+        authors = [
+            self._reformat_name(author)
+            for author in raw_author_names
+        ]
+
+        # 获取机构信息
+        institutions = [
+            inst.get("display_name", "")
+            for authorship in work.get("authorships", [])
+            for inst in authorship.get("institutions", [])
+            if inst
+        ]
+
+        # 获取主要发表位置信息
+        primary_location = work.get("primary_location") or {}
+        source = primary_location.get("source") or {}
+        venue = source.get("display_name")
+
+        # 获取发表日期
+        year = work.get("publication_year")
+
+        return PaperMetadata(
+            title=work.get("title", ""),
+            authors=authors,
+            institutions=institutions,
+            abstract=work.get("abstract", ""),
+            year=year,
+            doi=work.get("doi"),
+            url=work.get("doi"),  # OpenAlex 使用 DOI 作为 URL
+            citations=work.get("cited_by_count"),
+            venue=venue
+        )
+
+    def _reformat_name(self, name: str) -> str:
+        """重新格式化作者名字"""
+        if "," not in name:
+            return name
+        family, given_names = (x.strip() for x in name.split(",", maxsplit=1))
+        return f"{given_names} {family}"
+
+    async def get_paper_details(self, doi: str) -> PaperMetadata:
+        """获取指定DOI的论文详情"""
+        params = {"mailto": self.mailto} if self.mailto else {}
+        async with aiohttp.ClientSession() as session:
+            async with session.get(
+                f"{self.base_url}/works/https://doi.org/{quote(doi, safe='')}",
+                params=params
+            ) as response:
+                data = await response.json()
+                return self._parse_work(data)
+
+    async def get_references(self, doi: str) -> List[PaperMetadata]:
+        """获取指定DOI论文的参考文献列表"""
+        params = {"mailto": self.mailto} if self.mailto else {}
+        async with aiohttp.ClientSession() as session:
+            async with session.get(
+                f"{self.base_url}/works/https://doi.org/{quote(doi, safe='')}/references",
+                params=params
+            ) as response:
+                data = await response.json()
+                return [self._parse_work(work) for work in data.get("results", [])]
+
+    async def get_citations(self, doi: str) -> List[PaperMetadata]:
+        """获取引用指定DOI论文的文献列表"""
+        params = {"mailto": self.mailto} if self.mailto else {}
+        params.update({
+            "filter": f"cites:doi:{doi}",
+            "per-page": 100
+        })
+
+        async with aiohttp.ClientSession() as session:
+            async with session.get(
+                f"{self.base_url}/works",
+                params=params
+            ) as response:
+                data = await response.json()
+                return [self._parse_work(work) for work in data.get("results", [])]
+
+async def example_usage():
+    """OpenAlexSource使用示例"""
+    # 初始化OpenAlexSource
+    openalex = OpenAlexSource()
+
+    try:
+        print("正在搜索论文...")
+        # 搜索与"artificial intelligence"相关的论文，限制返回5篇
+        papers = await openalex.search(query="artificial intelligence", limit=5)
+
+        if not papers:
+            print("未获取到任何论文信息")
+            return
+
+        print(f"找到 {len(papers)} 篇论文")
+
+        # 打印搜索结果
+        for i, paper in enumerate(papers, 1):
+            print(f"\n--- 论文 {i} ---")
+            print(f"标题: {paper.title}")
+            print(f"作者: {', '.join(paper.authors) if paper.authors else '未知'}")
+            if paper.institutions:
+                print(f"机构: {', '.join(paper.institutions)}")
+            print(f"发表年份: {paper.year if paper.year else '未知'}")
+            print(f"DOI: {paper.doi if paper.doi else '未知'}")
+            print(f"URL: {paper.url if paper.url else '未知'}")
+            if paper.abstract:
+                print(f"摘要: {paper.abstract[:200]}...")
+            print(f"引用次数: {paper.citations if paper.citations is not None else '未知'}")
+            print(f"发表venue: {paper.venue if paper.venue else '未知'}")
+    except Exception as e:
+        print(f"发生错误: {str(e)}")
+        import traceback
+        print(traceback.format_exc())
+
+# 如果直接运行此文件，执行示例代码
+if __name__ == "__main__":
+    import asyncio
+
+    # 运行示例
+    asyncio.run(example_usage())
--- a/显示更多
+++ b/显示更多
作者	SHA1	备注	提交日期
binary-husky	d94a571eb5	block unstable	2025-08-23 15:59:05 +08:00
XiaoBoAI	91f28c2721	back	2025-07-21 02:18:46 +08:00
XiaoBoAI	6813ba88bb	feat: 为predict函数添加文件和URL读取功能 - 添加URL检测和网页内容提取功能，支持自动提取网页文本 - 添加文件路径识别和文件内容读取功能，支持private_upload路径格式 - 集成WebTextExtractor处理网页内容提取 - 集成TextContentLoader处理本地文件读取 - 支持文件路径与问题组合的智能处理	2025-07-19 19:06:38 +08:00
binary-husky	fb5189fd96	accelerate nltk	2025-07-16 00:57:45 +08:00
binary-husky	9945340277	merge more academic plugins	2025-07-14 02:20:20 +08:00
binary-husky	55607cbe8b	file dynamic load	2025-07-13 02:51:14 +08:00
binary-husky	a49085088c	Merge branch 'master' into master-4.0	2025-07-13 01:30:16 +08:00
binary-husky	a7a56b5058	fix buggy gradio version	2025-06-25 01:34:33 +08:00
binary-husky	8e0332c71b	fix buggy gradio version	2025-06-25 01:34:07 +08:00
binary-husky	90d1b34f5e	stage document conversation	2025-06-23 01:12:04 +08:00
binary-husky	73f573092b	stage academic conversation	2025-06-22 18:31:41 +08:00
binary-husky	8c21432291	use uv to build dockerfile	2025-06-04 02:24:09 +08:00
binary-husky	87b3f79ae9	setup nv	2025-06-04 01:53:29 +08:00
binary-husky	f42aad5093	implement doc_fns	2025-06-04 00:20:09 +08:00
binary-husky	725f60fba3	add context clip policy	2025-06-03 01:05:37 +08:00
binary-husky	be83907394	Merge branch 'master' of github.com:binary-husky/chatgpt_academic	2025-05-06 22:17:34 +08:00
binary-husky	eba48a0f1a	improve reset conversation ui	2025-05-06 22:10:21 +08:00
binary-husky	ee1a9e7cce	support qwen3 models - edit config hint	2025-04-29 11:10:49 +08:00
binary-husky	fc06be6f7a	support qwen3 models	2025-04-29 11:09:53 +08:00
binary-husky	883b513b91	add can_multi_thread	2025-04-21 00:50:24 +08:00
binary-husky	24cebaf4ec	add o3 and o4 models	2025-04-21 00:48:59 +08:00
binary-husky	858b5f69b0	add in-text stop btn	2025-04-15 01:08:54 +08:00
davidfir3	63c61e6204	添加gemini-2.0-flash (#2180 ) Co-authored-by: 柯仕锋 <12029064@zju.edu.cn>	2025-03-25 00:13:18 +08:00
BZfei	82aac97980	阿里云百炼(原灵积)增加对deepseek-r1、deepseek-v3模型支持 (#2182 ) * 阿里云百炼(原灵积)增加对deepseek-r1、deepseek-v3模型支持 * update reasoning display --------- Co-authored-by: binary-husky <qingxu.fu@outlook.com>	2025-03-25 00:11:55 +08:00
binary-husky	045cdb15d8	ensure display none even if css load fails	2025-03-10 23:44:47 +08:00
binary-husky	e78e8b0909	allow copy original text instead of renderend text	2025-03-09 00:04:27 +08:00
binary-husky	07974a26d0	Merge branch 'master' of github.com:binary-husky/chatgpt_academic	2025-03-08 23:10:42 +08:00
binary-husky	3e56c074cc	fix gui_toolbar	2025-03-08 23:09:22 +08:00
littleolaf	72dbe856d2	添加接入火山引擎在线大模型内容的支持 (#2165 ) * use oai adaptive bridge function to handle vol engine * add vol engine deepseek v3 --------- Co-authored-by: binary-husky <qingxu.fu@outlook.com>	2025-03-04 23:58:03 +08:00
Steven Moder	4a79aa6a93	typo: Fix typos and rename functions across multiple files (#2130 ) * typo: Fix typos and rename functions across multiple files This commit addresses several minor issues: - Corrected spelling of function names (e.g., `update_ui_lastest_msg` to `update_ui_latest_msg`) - Fixed typos in comments and variable names - Corrected capitalization in some strings (e.g., "ArXiv" instead of "Arixv") - Renamed some variables for consistency - Corrected some console-related parameter names (e.g., `console_slience` to `console_silence`) The changes span multiple files across the project, including request LLM bridges, crazy functions, and utility modules. * fix: f-string expression part cannot include a backslash (#2139) * raise error when the uploaded tar contain hard/soft link (#2136) * minor bug fix * fine tune reasoning css * upgrade internet gpt plugin * Update README.md * fix GHSA-gqp5-wm97-qxcv * typo fix * update readme --------- Co-authored-by: binary-husky <96192199+binary-husky@users.noreply.github.com> Co-authored-by: binary-husky <qingxu.fu@outlook.com>	2025-03-02 02:16:10 +08:00
binary-husky	5dffe8627f	fix GHSA-gqp5-wm97-qxcv	2025-03-02 01:58:45 +08:00
binary-husky	2aefef26db	Update README.md	2025-02-21 19:51:09 +08:00
binary-husky	957da731db	upgrade internet gpt plugin	2025-02-13 00:19:43 +08:00
binary-husky	add29eba08	fine tune reasoning css	2025-02-09 20:26:52 +08:00
binary-husky	163e59c0f3	minor bug fix	2025-02-09 19:33:02 +08:00
binary-husky	07ece29c7c	raise error when the uploaded tar contain hard/soft link (#2136 )	2025-02-08 20:54:01 +08:00
Steven Moder	991a903fa9	fix: f-string expression part cannot include a backslash (#2139 )	2025-02-08 20:50:54 +08:00
Steven Moder	cf7c81170c	fix: return 参数数量及返回类型考虑 (#2129 )	2025-02-07 21:33:06 +08:00
barry	6dda2061dd	Update bridge_openrouter.py (#2132 ) fix openrouter api 400 post bug Co-authored-by: lan <56376794+lostatnight@users.noreply.github.com>	2025-02-07 21:28:05 +08:00
binary-husky	8a0d96afd3	consider element missing cases in js	2025-02-07 01:21:21 +08:00
binary-husky	37f9b94dee	add options to hide ui components	2025-02-07 00:17:36 +08:00
binary-husky	936e2f5206	update readme	2025-02-04 16:15:56 +08:00
binary-husky	7f4b87a633	update readme	2025-02-04 16:08:18 +08:00
binary-husky	2ddd1bb634	Merge branch 'memset0-master'	2025-02-04 16:03:53 +08:00
binary-husky	c68285aeac	update config and version	2025-02-04 16:03:01 +08:00
Memento mori.	caaebe4296	add support for Deepseek R1 model and display CoT (#2118 ) * feat: add support for R1 model and display CoT * fix unpacking * feat: customized font & font size * auto hide tooltip when scoll down * tooltip glass transparent css * fix: Enhance API key validation in is_any_api_key function (#2113) * support qwen2.5-max! * update minior adjustment --------- Co-authored-by: binary-husky <qingxu.fu@outlook.com> Co-authored-by: Steven Moder <java20131114@gmail.com>	2025-02-04 16:02:02 +08:00
binary-husky	39d50c1c95	update minior adjustment	2025-02-04 15:57:35 +08:00
binary-husky	25dc7bf912	Merge branch 'master' of https://github.com/memset0/gpt_academic into memset0-master	2025-01-30 22:03:31 +08:00
binary-husky	0458590a77	support qwen2.5-max!	2025-01-29 23:29:38 +08:00
Steven Moder	44fe78fff5	fix: Enhance API key validation in is_any_api_key function (#2113 )	2025-01-29 21:40:30 +08:00
binary-husky	5ddd657ebc	tooltip glass transparent css	2025-01-28 23:50:21 +08:00
binary-husky	9b0b2cf260	auto hide tooltip when scoll down	2025-01-28 23:32:40 +08:00
binary-husky	9f39a6571a	feat: customized font & font size	2025-01-28 02:52:56 +08:00
memset0	d07e736214	fix unpacking	2025-01-25 00:00:13 +08:00
memset0	a1f7ae5b55	feat: add support for R1 model and display CoT	2025-01-24 14:43:49 +08:00
binary-husky	1213ef19e5	Merge branch 'master' of github.com:binary-husky/chatgpt_academic	2025-01-22 01:50:08 +08:00
binary-husky	aaafe2a797	fix xelatex font problem in all-cap image	2025-01-22 01:49:53 +08:00
binary-husky	2716606f0c	Update README.md	2025-01-16 23:40:24 +08:00
binary-husky	286f7303be	fix image display bug	2025-01-12 21:54:43 +08:00
binary-husky	7eeab9e376	fix code block display bug	2025-01-09 22:31:59 +08:00
binary-husky	4ca331fb28	prevent html rendering for input	2025-01-05 21:20:12 +08:00
binary-husky	9487829930	change max_chat_preserve = 10	2025-01-03 00:34:36 +08:00
binary-husky	a73074b89e	upgrade chat checkpoint	2025-01-03 00:31:03 +08:00
Southlandi	fd93622840	修复Gemini对话错误问题（停用词数量为0的情况） (#2092 )	2024-12-28 23:22:10 +08:00
whyXVI	09a82a572d	Fix RuntimeError in predict_no_ui_long_connection() (#2095 ) Bug fix: Fix RuntimeError in predict_no_ui_long_connection() In the original code, calling predict_no_ui_long_connection() would trigger a RuntimeError("OpenAI拒绝了请求：" + error_msg) even when the server responded normally. The issue occurred due to incorrect handling of SSE protocol comment lines (lines starting with ":"). Modified the parsing logic in both `predict` and `predict_no_ui_long_connection` to handle these lines correctly, making the logic more intuitive and robust.	2024-12-28 23:21:14 +08:00
G.RQ	c53ddf65aa	修复 bug“重置”按钮报错 (#2102 ) * fix 重置按钮bug * fix version control bug --------- Co-authored-by: binary-husky <qingxu.fu@outlook.com>	2024-12-28 23:19:25 +08:00
binary-husky	ac64a77c2d	allow disable openai proxy in `WHEN_TO_USE_PROXY`	2024-12-28 07:14:54 +08:00
binary-husky	dae8a0affc	compat bug fix	2024-12-25 01:21:58 +08:00
binary-husky	97a81e9388	fix temp issue of o1	2024-12-25 00:54:03 +08:00
binary-husky	1dd1d0ed6c	fix cookie overflow bug	2024-12-25 00:33:20 +08:00
binary-husky	060af0d2e6	Merge branch 'master' of github.com:binary-husky/chatgpt_academic	2024-12-22 23:33:44 +08:00
binary-husky	a848f714b6	fix welcome card bugs	2024-12-22 23:33:22 +08:00
binary-husky	924f8e30c7	Update issue stale.yml	2024-12-22 14:16:18 +08:00
binary-husky	f40347665b	github action change	2024-12-22 14:15:16 +08:00
binary-husky	734c40bbde	fix non-localhost javascript error	2024-12-22 14:01:22 +08:00
binary-husky	4ec87fbb54	history ng patch 1	2024-12-21 11:27:53 +08:00
binary-husky	17b5c22e61	Merge branch 'master' of github.com:binary-husky/chatgpt_academic	2024-12-19 22:46:14 +08:00
binary-husky	c6cd04a407	promote the rank of DASHSCOPE_API_KEY	2024-12-19 22:39:14 +08:00
YIQI JIANG	f60a12f8b4	Add o1 and o1-2024-12-17 model support (#2090 ) * Add o1 and o1-2024-12-17 model support * patch api key selection --------- Co-authored-by: 蒋翌琪 <jiangyiqi99@jiangyiqideMacBook-Pro.local> Co-authored-by: binary-husky <qingxu.fu@outlook.com>	2024-12-19 22:32:57 +08:00