添加中转渠道支持功能

- 更新config.py配置文件，添加中转渠道相关配置项
- 修改bridge_all.py和bridge_chatgpt.py以支持中转渠道
- 更新key_pattern_manager.py处理中转渠道密钥模式

.github/workflows/conda-pack-windows.yml

@@ -0,0 +1,56 @@
+name: Create Conda Environment Package
+
+on:
+  workflow_dispatch:
+
+jobs:
+  build:
+    runs-on: windows-latest
+    
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@v4
+      
+    - name: Setup Miniconda
+      uses: conda-incubator/setup-miniconda@v3
+      with:
+        auto-activate-base: true
+        activate-environment: ""
+        
+    - name: Create new Conda environment
+      shell: bash -l {0}
+      run: |
+        conda create -n gpt python=3.11 -y
+        conda activate gpt
+        
+    - name: Install requirements
+      shell: bash -l {0}
+      run: |
+        conda activate gpt
+        pip install -r requirements.txt
+        
+    - name: Install conda-pack
+      shell: bash -l {0}
+      run: |
+        conda activate gpt
+        conda install conda-pack -y
+        
+    - name: Pack conda environment
+      shell: bash -l {0}
+      run: |
+        conda activate gpt
+        conda pack -n gpt -o gpt.tar.gz
+      
+    - name: Create workspace zip
+      shell: pwsh
+      run: |
+        mkdir workspace
+        Get-ChildItem -Exclude "workspace" | Copy-Item -Destination workspace -Recurse
+        Remove-Item -Path workspace/.git* -Recurse -Force -ErrorAction SilentlyContinue
+        Copy-Item gpt.tar.gz workspace/ -Force
+    
+    - name: Upload packed files
+      uses: actions/upload-artifact@v4
+      with:
+        name: gpt-academic-package
+        path: workspace

.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

.gitignore

@@ -160,4 +160,6 @@ test.*
 temp.*
 objdump*
 *.min.*.js
-TODO
+TODO
+experimental_mods
+search_results

Dockerfile

@@ -3,37 +3,36 @@
 # - 如何构建: 先修改 `config.py`， 然后 `docker build -t gpt-academic . `
 # - 如何运行(Linux下): `docker run --rm -it --net=host gpt-academic `
 # - 如何运行(其他操作系统，选择任意一个固定端口50923): `docker run --rm -it -e WEB_PORT=50923 -p 50923:50923 gpt-academic `
-FROM python:3.11
 
+FROM ghcr.io/astral-sh/uv:python3.12-bookworm
 
 # 非必要步骤，更换pip源 （以下三行，可以删除）
 RUN echo '[global]' > /etc/pip.conf && \
     echo 'index-url = https://mirrors.aliyun.com/pypi/simple/' >> /etc/pip.conf && \
     echo 'trusted-host = mirrors.aliyun.com' >> /etc/pip.conf
 
-
-# 语音输出功能（以下两行，第一行更换阿里源，第二行安装ffmpeg，都可以删除）
-RUN UBUNTU_VERSION=$(awk -F= '/^VERSION_CODENAME=/{print $2}' /etc/os-release); echo "deb https://mirrors.aliyun.com/debian/ $UBUNTU_VERSION main non-free contrib" > /etc/apt/sources.list; apt-get update
+# 语音输出功能（以下1,2行更换阿里源，第3,4行安装ffmpeg，都可以删除） 
+RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
+    sed -i 's/security.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \
+    apt-get update
 RUN apt-get install ffmpeg -y
-
+RUN apt-get clean
 
 # 进入工作路径（必要）
 WORKDIR /gpt
 
-
 # 安装大部分依赖，利用Docker缓存加速以后的构建 （以下两行，可以删除）
 COPY requirements.txt ./
-RUN pip3 install -r requirements.txt
-
+RUN uv venv --python=3.12 && uv pip install --verbose -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
+ENV PATH="/gpt/.venv/bin:$PATH"
+RUN python -c 'import loguru'
 
 # 装载项目文件，安装剩余依赖（必要）
 COPY . .
-RUN pip3 install -r requirements.txt
-
-
-# 非必要步骤，用于预热模块（可以删除）
-RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
+RUN uv venv --python=3.12 && uv pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
 
+# # 非必要步骤，用于预热模块（可以删除）
+RUN python -c 'from check_proxy import warm_up_modules; warm_up_modules()'
 
 # 启动（必要）
-CMD ["python3", "-u", "main.py"]
+CMD ["bash", "-c", "python main.py"]

README.md

@@ -1,9 +1,14 @@
 > [!IMPORTANT]
-> 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）  
+> `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  
+>
+> 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>
 
@@ -124,20 +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)
@@ -170,26 +175,32 @@ flowchart TD
     ```
 
 
-<details><summary>如果需要支持清华ChatGLM2/复旦MOSS/RWKV作为后端，请点击展开此处</summary>
+<details><summary>如果需要支持清华ChatGLM系列/复旦MOSS/RWKV作为后端，请点击展开此处</summary>
 <p>
 
-【可选步骤】如果需要支持清华ChatGLM3/复旦MOSS作为后端，需要额外安装更多依赖（前提条件：熟悉Python + 用过Pytorch + 电脑配置够强）：
+【可选步骤】如果需要支持清华ChatGLM系列/复旦MOSS作为后端，需要额外安装更多依赖（前提条件：熟悉Python + 用过Pytorch + 电脑配置够强）：
 
 ```sh
 # 【可选步骤I】支持清华ChatGLM3。清华ChatGLM备注：如果遇到"Call ChatGLM fail 不能正常加载ChatGLM的参数" 错误，参考如下： 1：以上默认安装的为torch+cpu版，使用cuda需要卸载torch重新安装torch+cuda； 2：如因本机配置不够无法加载模型，可以修改request_llm/bridge_chatglm.py中的模型精度, 将 AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) 都修改为 AutoTokenizer.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True)
 python -m pip install -r request_llms/requirements_chatglm.txt
 
-# 【可选步骤II】支持复旦MOSS
+# 【可选步骤II】支持清华ChatGLM4 注意：此模型至少需要24G显存
+python -m pip install -r request_llms/requirements_chatglm4.txt
+# 可使用modelscope下载ChatGLM4模型
+# pip install modelscope
+# modelscope download --model ZhipuAI/glm-4-9b-chat --local_dir ./THUDM/glm-4-9b-chat
+
+# 【可选步骤III】支持复旦MOSS
 python -m pip install -r request_llms/requirements_moss.txt
 git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss  # 注意执行此行代码时，必须处于项目根路径
 
-# 【可选步骤III】支持RWKV Runner
+# 【可选步骤IV】支持RWKV Runner
 参考wiki：https://github.com/binary-husky/gpt_academic/wiki/%E9%80%82%E9%85%8DRWKV-Runner
 
-# 【可选步骤IV】确保config.py配置文件的AVAIL_LLM_MODELS包含了期望的模型，目前支持的全部模型如下(jittorllms系列目前仅支持docker方案)：
+# 【可选步骤V】确保config.py配置文件的AVAIL_LLM_MODELS包含了期望的模型，目前支持的全部模型如下(jittorllms系列目前仅支持docker方案)：
 AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss"] # + ["jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
 
-# 【可选步骤V】支持本地模型INT8,INT4量化（这里所指的模型本身不是量化版本，目前deepseek-coder支持，后面测试后会加入更多模型量化选择）
+# 【可选步骤VI】支持本地模型INT8,INT4量化（这里所指的模型本身不是量化版本，目前deepseek-coder支持，后面测试后会加入更多模型量化选择）
 pip install bitsandbyte
 # windows用户安装bitsandbytes需要使用下面bitsandbytes-windows-webui
 python -m pip install bitsandbytes --prefer-binary --extra-index-url=https://jllllll.github.io/bitsandbytes-windows-webui
@@ -417,7 +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
 

check_proxy.py

@@ -1,24 +1,36 @@
 from loguru import logger
 
 def check_proxy(proxies, return_ip=False):
+    """
+    检查代理配置并返回结果。
+
+    Args:
+        proxies (dict): 包含http和https代理配置的字典。
+        return_ip (bool, optional): 是否返回代理的IP地址。默认为False。
+
+    Returns:
+        str or None: 检查的结果信息或代理的IP地址（如果`return_ip`为True）。
+    """
     import requests
     proxies_https = proxies['https'] if proxies is not None else '无'
     ip = None
     try:
-        response = requests.get("https://ipapi.co/json/", proxies=proxies, timeout=4)
+        response = requests.get("https://ipapi.co/json/", proxies=proxies, timeout=4)  # ⭐ 执行GET请求以获取代理信息
         data = response.json()
         if 'country_name' in data:
             country = data['country_name']
             result = f"代理配置 {proxies_https}, 代理所在地：{country}"
-            if 'ip' in data: ip = data['ip']
+            if 'ip' in data:
+                ip = data['ip']
         elif 'error' in data:
-            alternative, ip = _check_with_backup_source(proxies)
+            alternative, ip = _check_with_backup_source(proxies)  # ⭐ 调用备用方法检查代理配置
             if alternative is None:
                 result = f"代理配置 {proxies_https}, 代理所在地：未知，IP查询频率受限"
             else:
                 result = f"代理配置 {proxies_https}, 代理所在地：{alternative}"
         else:
             result = f"代理配置 {proxies_https}, 代理数据解析失败：{data}"
+
         if not return_ip:
             logger.warning(result)
             return result
@@ -33,17 +45,33 @@ def check_proxy(proxies, return_ip=False):
             return ip
 
 def _check_with_backup_source(proxies):
+    """
+    通过备份源检查代理，并获取相应信息。
+
+    Args:
+        proxies (dict): 包含代理信息的字典。
+
+    Returns:
+        tuple: 代理信息(geo)和IP地址(ip)的元组。
+    """
     import random, string, requests
     random_string = ''.join(random.choices(string.ascii_letters + string.digits, k=32))
     try:
-        res_json = requests.get(f"http://{random_string}.edns.ip-api.com/json", proxies=proxies, timeout=4).json()
+        res_json = requests.get(f"http://{random_string}.edns.ip-api.com/json", proxies=proxies, timeout=4).json()  # ⭐ 执行代理检查和备份源请求
         return res_json['dns']['geo'], res_json['dns']['ip']
     except:
         return None, None
 
 def backup_and_download(current_version, remote_version):
     """
-    一键更新协议：备份和下载
+    一键更新协议：备份当前版本，下载远程版本并解压缩。
+
+    Args:
+        current_version (str): 当前版本号。
+        remote_version (str): 远程版本号。
+
+    Returns:
+        str: 新版本目录的路径。
     """
     from toolbox import get_conf
     import shutil
@@ -60,7 +88,7 @@ def backup_and_download(current_version, remote_version):
     proxies = get_conf('proxies')
     try:    r = requests.get('https://github.com/binary-husky/chatgpt_academic/archive/refs/heads/master.zip', proxies=proxies, stream=True)
     except: r = requests.get('https://public.agent-matrix.com/publish/master.zip', proxies=proxies, stream=True)
-    zip_file_path = backup_dir+'/master.zip'
+    zip_file_path = backup_dir+'/master.zip'  # ⭐ 保存备份文件的路径
     with open(zip_file_path, 'wb+') as f:
         f.write(r.content)
     dst_path = new_version_dir
@@ -76,6 +104,17 @@ def backup_and_download(current_version, remote_version):
 def patch_and_restart(path):
     """
     一键更新协议：覆盖和重启
+
+    Args:
+        path (str): 新版本代码所在的路径
+
+    注意事项:
+        如果您的程序没有使用config_private.py私密配置文件，则会将config.py重命名为config_private.py以避免配置丢失。
+
+    更新流程:
+        - 复制最新版本代码到当前目录
+        - 更新pip包依赖
+        - 如果更新失败，则提示手动安装依赖库并重启
     """
     from distutils import dir_util
     import shutil
@@ -84,32 +123,43 @@ def patch_and_restart(path):
     import time
     import glob
     from shared_utils.colorful import log亮黄, log亮绿, log亮红
-    # if not using config_private, move origin config.py as config_private.py
+
     if not os.path.exists('config_private.py'):
         log亮黄('由于您没有设置config_private.py私密配置，现将您的现有配置移动至config_private.py以防止配置丢失，',
               '另外您可以随时在history子文件夹下找回旧版的程序。')
         shutil.copyfile('config.py', 'config_private.py')
+
     path_new_version = glob.glob(path + '/*-master')[0]
-    dir_util.copy_tree(path_new_version, './')
+    dir_util.copy_tree(path_new_version, './')  # ⭐ 将最新版本代码复制到当前目录
+
     log亮绿('代码已经更新，即将更新pip包依赖……')
     for i in reversed(range(5)): time.sleep(1); log亮绿(i)
+
     try:
         import subprocess
         subprocess.check_call([sys.executable, '-m', 'pip', 'install', '-r', 'requirements.txt'])
     except:
         log亮红('pip包依赖安装出现问题，需要手动安装新增的依赖库 `python -m pip install -r requirements.txt`，然后在用常规的`python main.py`的方式启动。')
+
     log亮绿('更新完成，您可以随时在history子文件夹下找回旧版的程序，5s之后重启')
     log亮红('假如重启失败，您可能需要手动安装新增的依赖库 `python -m pip install -r requirements.txt`，然后在用常规的`python main.py`的方式启动。')
     log亮绿(' ------------------------------ -----------------------------------')
+
     for i in reversed(range(8)): time.sleep(1); log亮绿(i)
-    os.execl(sys.executable, sys.executable, *sys.argv)
+    os.execl(sys.executable, sys.executable, *sys.argv)  # 重启程序
 
 
 def get_current_version():
+    """
+    获取当前的版本号。
+
+    Returns:
+        str: 当前的版本号。如果无法获取版本号，则返回空字符串。
+    """
     import json
     try:
         with open('./version', 'r', encoding='utf8') as f:
-            current_version = json.loads(f.read())['version']
+            current_version = json.loads(f.read())['version']  # ⭐ 从读取的json数据中提取版本号
     except:
         current_version = ""
     return current_version
@@ -118,6 +168,12 @@ def get_current_version():
 def auto_update(raise_error=False):
     """
     一键更新协议：查询版本和用户意见
+
+    Args:
+        raise_error (bool, optional): 是否在出错时抛出错误。默认为 False。
+
+    Returns:
+        None
     """
     try:
         from toolbox import get_conf
@@ -137,13 +193,13 @@ def auto_update(raise_error=False):
             current_version = json.loads(current_version)['version']
         if (remote_version - current_version) >= 0.01-1e-5:
             from shared_utils.colorful import log亮黄
-            log亮黄(f'\n新版本可用。新版本:{remote_version}，当前版本:{current_version}。{new_feature}')
+            log亮黄(f'\n新版本可用。新版本:{remote_version}，当前版本:{current_version}。{new_feature}')  # ⭐ 在控制台打印新版本信息
             logger.info('（1）Github更新地址:\nhttps://github.com/binary-husky/chatgpt_academic\n')
             user_instruction = input('（2）是否一键更新代码（Y+回车=确认，输入其他/无输入+回车=不更新）？')
             if user_instruction in ['Y', 'y']:
-                path = backup_and_download(current_version, remote_version)
+                path = backup_and_download(current_version, remote_version)  # ⭐ 备份并下载文件
                 try:
-                    patch_and_restart(path)
+                    patch_and_restart(path)  # ⭐ 执行覆盖并重启操作
                 except:
                     msg = '更新失败。'
                     if raise_error:
@@ -163,6 +219,9 @@ def auto_update(raise_error=False):
         logger.info(msg)
 
 def warm_up_modules():
+    """
+    预热模块，加载特定模块并执行预热操作。
+    """
     logger.info('正在执行一些模块的预热 ...')
     from toolbox import ProxyNetworkActivate
     from request_llms.bridge_all import model_info
@@ -173,6 +232,16 @@ def warm_up_modules():
         enc.encode("模块预热", disallowed_special=())
 
 def warm_up_vectordb():
+    """
+    执行一些模块的预热操作。
+
+    本函数主要用于执行一些模块的预热操作，确保在后续的流程中能够顺利运行。
+
+    ⭐ 关键作用：预热模块
+
+    Returns:
+        None
+    """
     logger.info('正在执行一些模块的预热 ...')
     from toolbox import ProxyNetworkActivate
     with ProxyNetworkActivate("Warmup_Modules"):
@@ -185,4 +254,4 @@ if __name__ == '__main__':
     os.environ['no_proxy'] = '*'  # 避免代理网络产生意外污染
     from toolbox import get_conf
     proxies = get_conf('proxies')
-    check_proxy(proxies)
+    check_proxy(proxies)

config.py

@@ -7,11 +7,49 @@
     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
+from pickle import TRUE
 
 
-# [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
+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 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 1-4]>> ( 接入中转渠道 ) 中转渠道配置，支持采用OpenAI接口模式的中转渠道商
+ZHONGZHUAN_ENABLE =  TRUE  # 是否启用中转渠道，默认关闭
+ZHONGZHUAN_ENDPOINT = "https://test.com/v1/chat/completions"  # 中转渠道的完整API端点
+ZHONGZHUAN_API_KEY = "sk-xxxxxxxxxxxxxxx"  # 中转渠道的API KEY，如果为空则使用API_KEY
+ZHONGZHUAN_MODELS = [
+    # 中转渠道支持的模型列表，使用原始模型名称
+    "o3-mini-all",
+    "gpt-4.1",
+    "gpt-4o",
+    "gpt-4o-mini", 
+    "claude-sonnet-4-20250514-thinking",
+    "claude-sonnet-4-20250514",
+    "gemini-2.5-pro-preview-03-25",
+    # 可以添加更多模型...
+]
+# 配置说明：
+# 1. 将ZHONGZHUAN_ENABLE设置为True启用中转渠道
+# 2. 将ZHONGZHUAN_ENDPOINT设置为你的中转渠道商提供的完整API端点（包含/chat/completions）
+# 3. 将ZHONGZHUAN_API_KEY设置为你的中转渠道商提供的API KEY（可选）
+# 4. 在ZHONGZHUAN_MODELS中配置你想要使用的模型，使用原始模型名称
+# 5. 系统将自动把ZHONGZHUAN_MODELS中的模型添加到AVAIL_LLM_MODELS中，无需重复配置
+# 6. 对于同时在两个列表中的模型，将自动使用中转渠道访问
+# 
+# 示例配置：
+# ZHONGZHUAN_ENABLE = True
+# ZHONGZHUAN_ENDPOINT = "https://api.your-provider.com/v1/chat/completions"
+# ZHONGZHUAN_API_KEY = "your-api-key-here"
+# ZHONGZHUAN_MODELS = ["o3-mini-all", "gpt-4.1", "claude-sonnet-4-20250514"]
+# 然后可以直接设置LLM_MODEL = "o3-mini-all"（将通过中转渠道访问）
+
+# [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:
     """
@@ -32,13 +70,26 @@ 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"
+                    "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",
                     ]
 
+# 自动将中转渠道模型添加到可用模型列表中，避免用户重复配置
+# 对于同时在AVAIL_LLM_MODELS和ZHONGZHUAN_MODELS中的模型，将自动使用中转渠道
+if ZHONGZHUAN_ENABLE and ZHONGZHUAN_MODELS:
+    for model in ZHONGZHUAN_MODELS:
+        if model not in AVAIL_LLM_MODELS:
+            AVAIL_LLM_MODELS.append(model)
+    print(f"[中转渠道] 已启用，共{len(ZHONGZHUAN_MODELS)}个模型将通过中转渠道访问: {', '.join(ZHONGZHUAN_MODELS)}")
+
 EMBEDDING_MODEL = "text-embedding-3-small"
 
 # --- --- --- ---
@@ -47,7 +98,7 @@ 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",
@@ -55,6 +106,7 @@ EMBEDDING_MODEL = "text-embedding-3-small"
 #   "deepseek-chat" ,"deepseek-coder",
 #   "gemini-1.5-flash",
 #   "yi-34b-chat-0205","yi-34b-chat-200k","yi-large","yi-medium","yi-spark","yi-large-turbo","yi-large-preview",
+#   "grok-beta",
 # ]
 # --- --- --- ---
 # 此外，您还可以在接入one-api/vllm/ollama/Openroute时，
@@ -73,7 +125,7 @@ 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"]
@@ -81,6 +133,31 @@ 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."
@@ -122,7 +199,7 @@ MAX_RETRY = 2
 DEFAULT_FN_GROUPS = ['对话', '编程', '学术', '智能体']
 
 
-# 定义界面上“询问多个GPT模型”插件应该使用哪些模型，请从AVAIL_LLM_MODELS中选择，并在不同模型之间用`&`间隔，例如"gpt-3.5-turbo&chatglm3&azure-gpt-4"
+# 定义界面上"询问多个GPT模型"插件应该使用哪些模型，请从AVAIL_LLM_MODELS中选择，并在不同模型之间用`&`间隔，例如"gpt-3.5-turbo&chatglm3&azure-gpt-4"
 MULTI_QUERY_LLM_MODELS = "gpt-3.5-turbo&chatglm3"
 
 
@@ -132,16 +209,15 @@ 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 = ''
 BAIDU_CLOUD_QIANFAN_MODEL = 'ERNIE-Bot'    # 可选 "ERNIE-Bot-4"(文心大模型4.0), "ERNIE-Bot"(文心一言), "ERNIE-Bot-turbo", "BLOOMZ-7B", "Llama-2-70B-Chat", "Llama-2-13B-Chat", "Llama-2-7B-Chat", "ERNIE-Speed-128K", "ERNIE-Speed-8K", "ERNIE-Lite-8K"
 
 
+# 如果使用ChatGLM3或ChatGLM4本地模型，请把 LLM_MODEL="chatglm3" 或LLM_MODEL="chatglm4"，并在此处指定模型路径
+CHATGLM_LOCAL_MODEL_PATH = "THUDM/glm-4-9b-chat" # 例如"/home/hmp/ChatGLM3-6B/"
+
 # 如果使用ChatGLM2微调模型，请把 LLM_MODEL="chatglmft"，并在此处指定模型路径
 CHATGLM_PTUNING_CHECKPOINT = "" # 例如"/home/hmp/ChatGLM2-6B/ptuning/output/6b-pt-128-1e-2/checkpoint-100"
 
@@ -235,13 +311,15 @@ MOONSHOT_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
 TAICHU_API_KEY = ""
 
+# Grok API KEY
+GROK_API_KEY = ""
 
 # Mathpix 拥有执行PDF的OCR功能，但是需要注册账号
 MATHPIX_APPID = ""
@@ -273,8 +351,8 @@ GROBID_URLS = [
 ]
 
 
-# Searxng互联网检索服务
-SEARXNG_URL = "https://cloud-1.agent-matrix.com/"
+# Searxng互联网检索服务（这是一个huggingface空间，请前往huggingface复制该空间，然后把自己新的空间地址填在这里）
+SEARXNG_URLS = [ f"https://kaletianlre-beardvs{i}dd.hf.space/" for i in range(1,5) ]
 
 
 # 是否允许通过自然语言描述修改本页的配置，该功能具有一定的危险性，默认关闭
@@ -298,7 +376,7 @@ 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"]
 
 
@@ -310,6 +388,23 @@ PLUGIN_HOT_RELOAD = False
 NUM_CUSTOM_BASIC_BTN = 4
 
 
+# 媒体智能体的服务地址（这是一个huggingface空间，请前往huggingface复制该空间，然后把自己新的空间地址填在这里）
+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 = ""
+
+
+# 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 ---------------
@@ -369,6 +464,7 @@ NUM_CUSTOM_BASIC_BTN = 4
 
 本地大模型示意图
 │
+├── "chatglm4"
 ├── "chatglm3"
 ├── "chatglm"
 ├── "chatglm_onnx"
@@ -399,7 +495,7 @@ NUM_CUSTOM_BASIC_BTN = 4
 插件在线服务配置依赖关系示意图
 │
 ├── 互联网检索
-│   └── SEARXNG_URL
+│   └── SEARXNG_URLS
 │
 ├── 语音功能
 │   ├── ENABLE_AUDIO
@@ -414,4 +510,11 @@ NUM_CUSTOM_BASIC_BTN = 4
     └── MATHPIX_APPKEY
 
 
+"zhongzhuan-..." 中转渠道模型配置
+    ├── ZHONGZHUAN_ENABLE
+    ├── ZHONGZHUAN_ENDPOINT
+    ├── ZHONGZHUAN_API_KEY
+    └── ZHONGZHUAN_MODELS
+
+
 """

crazy_functional.py

@@ -2,7 +2,6 @@ from toolbox import HotReload  # HotReload 的意思是热更新，修改函数
 from toolbox import trimmed_format_exc
 from loguru import logger
 
-
 def get_crazy_functions():
     from crazy_functions.读文章写摘要 import 读文章写摘要
     from crazy_functions.生成函数注释 import 批量生成函数注释
@@ -17,7 +16,7 @@ def get_crazy_functions():
     from crazy_functions.SourceCode_Analyse import 解析一个前端项目
     from crazy_functions.高级功能函数模板 import 高阶功能模板函数
     from crazy_functions.高级功能函数模板 import Demo_Wrap
-    from crazy_functions.Latex全文润色 import Latex英文润色
+    from crazy_functions.Latex_Project_Polish import Latex英文润色
     from crazy_functions.询问多个大语言模型 import 同时问询
     from crazy_functions.SourceCode_Analyse import 解析一个Lua项目
     from crazy_functions.SourceCode_Analyse import 解析一个CSharp项目
@@ -33,8 +32,8 @@ def get_crazy_functions():
     from crazy_functions.PDF_Translate import 批量翻译PDF文档
     from crazy_functions.谷歌检索小助手 import 谷歌检索小助手
     from crazy_functions.理解PDF文档内容 import 理解PDF文档内容标准文件输入
-    from crazy_functions.Latex全文润色 import Latex中文润色
-    from crazy_functions.Latex全文润色 import Latex英文纠错
+    from crazy_functions.Latex_Project_Polish import Latex中文润色
+    from crazy_functions.Latex_Project_Polish import Latex英文纠错
     from crazy_functions.Markdown_Translate import Markdown中译英
     from crazy_functions.虚空终端 import 虚空终端
     from crazy_functions.生成多种Mermaid图表 import Mermaid_Gen
@@ -49,8 +48,17 @@ def get_crazy_functions():
     from crazy_functions.Image_Generate import 图片生成_DALLE2, 图片生成_DALLE3, 图片修改_DALLE2
     from crazy_functions.Image_Generate_Wrap import ImageGen_Wrap
     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
 
     function_plugins = {
+        "多媒体智能体": {
+            "Group": "智能体",
+            "Color": "stop",
+            "AsButton": False,
+            "Info": "【仅测试】多媒体任务",
+            "Function": HotReload(多媒体任务),
+        },
         "虚空终端": {
             "Group": "对话|编程|学术|智能体",
             "Color": "stop",
@@ -71,6 +79,7 @@ def get_crazy_functions():
             "AsButton": False,
             "Info": "上传一系列python源文件(或者压缩包), 为这些代码添加docstring | 输入参数为路径",
             "Function": HotReload(注释Python项目),
+            "Class": SourceCodeComment_Wrap,
         },
         "载入对话历史存档（先上传存档或输入路径）": {
             "Group": "对话",
@@ -104,7 +113,7 @@ 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
         },
@@ -343,7 +352,7 @@ 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
         },
@@ -425,36 +434,6 @@ 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
@@ -718,12 +697,6 @@ def get_crazy_functions():
         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
     #     function_plugins.update({
@@ -738,19 +711,6 @@ def get_crazy_functions():
     #     logger.error(trimmed_format_exc())
     #     print('Load function plugin failed')
 
-    # try:
-    #     from crazy_functions.chatglm微调工具 import 微调数据集生成
-    #     function_plugins.update({
-    #         "黑盒模型学习: 微调数据集生成 (先上传数据集)": {
-    #             "Color": "stop",
-    #             "AsButton": False,
-    #             "AdvancedArgs": True,
-    #             "ArgsReminder": "针对数据集输入（如 绿帽子*深蓝色衬衫*黑色运动裤）给出指令，例如您可以将以下命令复制到下方: --llm_to_learn=azure-gpt-3.5 --prompt_prefix='根据下面的服装类型提示，想象一个穿着者，对这个人外貌、身处的环境、内心世界、过去经历进行描写。要求：100字以内，用第二人称。' --system_prompt=''",
-    #             "Function": HotReload(微调数据集生成)
-    #         }
-    #     })
-    # except:
-    #     print('Load function plugin failed')
 
     """
     设置默认值:
@@ -770,3 +730,26 @@ def get_crazy_functions():
             function_plugins[name]["Color"] = "secondary"
 
     return function_plugins
+
+
+
+
+def get_multiplex_button_functions():
+    """多路复用主提交按钮的功能映射
+    """
+    return {
+        "常规对话":
+            "",
+
+        "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": 
+            "Rag智能召回", # 映射到上面的 `Rag智能召回` 插件
+
+        "多媒体查询": 
+            "多媒体智能体", # 映射到上面的 `多媒体智能体` 插件
+    }

crazy_functions/Conversation_To_File.py

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

crazy_functions/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
+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:
@@ -115,7 +115,8 @@ def get_auth_ip():
 
 def searxng_request(query, proxies, categories='general', searxng_url=None, engines=None):
     if searxng_url is None:
-        url = get_conf("SEARXNG_URL")
+        urls = get_conf("SEARXNG_URLS")
+        url = random.choice(urls)
     else:
         url = searxng_url
 
@@ -174,10 +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
@@ -193,6 +201,56 @@ def scrape_text(url, proxies) -> str:
     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_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_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_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])
+    i_say = f"从以上搜索结果中抽取信息，然后回答问题：{prompt} {analysis_prompt}"
+    i_say, history = input_clipping( # 裁剪输入，从最长的条目开始裁剪，防止爆token
+        inputs=i_say,
+        history=history,
+        max_token_limit=8192
+    )
+    gpt_say = predict_no_ui_long_connection(
+        inputs=i_say,
+        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_silence=False,
+    )
+    return gpt_say
+
 @CatchException
 def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
     optimizer_history = history[:-8]
@@ -213,23 +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)"):

crazy_functions/Internet_GPT_Wrap.py

@@ -1,4 +1,4 @@
-
+import random
 from toolbox import get_conf
 from crazy_functions.Internet_GPT import 连接网络回答问题
 from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
@@ -20,6 +20,9 @@ class NetworkGPT_Wrap(GptAcademicPluginTemplate):
         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；
 
         """
+        urls = get_conf("SEARXNG_URLS")
+        url = random.choice(urls)
+
         gui_definition = {
             "main_input":
                 ArgProperty(title="输入问题", description="待通过互联网检索的问题，会自动读取输入框内容", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步
@@ -30,16 +33,17 @@ class NetworkGPT_Wrap(GptAcademicPluginTemplate):
             "optimizer":
                 ArgProperty(title="搜索优化", options=["关闭", "开启", "开启(增强)"], default_value="关闭", description="是否使用搜索增强。注意这可能会消耗较多token", type="dropdown").model_dump_json(),
             "searxng_url":
-                ArgProperty(title="Searxng服务地址", description="输入Searxng的地址", default_value=get_conf("SEARXNG_URL"), type="string").model_dump_json(), # 主输入，自动从输入框同步
+                ArgProperty(title="Searxng服务地址", description="输入Searxng的地址", default_value=url, 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, 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)
 

crazy_functions/Latex_Function.py

@@ -1,9 +1,9 @@
 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
 
-import glob, os, requests, time, json, tarfile
+import glob, os, requests, time, json, tarfile, threading
 
 pj = os.path.join
 ARXIV_CACHE_DIR = get_conf("ARXIV_CACHE_DIR")
@@ -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]
@@ -138,25 +138,43 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):
     cached_translation_pdf = check_cached_translation_pdf(arxiv_id)
     if cached_translation_pdf and allow_cache: return cached_translation_pdf, arxiv_id
 
-    url_tar = url_.replace('/abs/', '/e-print/')
-    translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'e-print')
     extract_dst = pj(ARXIV_CACHE_DIR, arxiv_id, 'extract')
-    os.makedirs(translation_dir, exist_ok=True)
-
-    # <-------------- download arxiv source file ------------->
+    translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'e-print')
     dst = pj(translation_dir, arxiv_id + '.tar')
-    if os.path.exists(dst):
-        yield from update_ui_lastest_msg("调用缓存", chatbot=chatbot, history=history)  # 刷新界面
+    os.makedirs(translation_dir, exist_ok=True)
+    # <-------------- download arxiv source file ------------->
+
+    def fix_url_and_download():
+        # for url_tar in [url_.replace('/abs/', '/e-print/'), url_.replace('/abs/', '/src/')]:
+        for url_tar in [url_.replace('/abs/', '/src/'), url_.replace('/abs/', '/e-print/')]:
+            proxies = get_conf('proxies')
+            r = requests.get(url_tar, proxies=proxies)
+            if r.status_code == 200:
+                with open(dst, 'wb+') as f:
+                    f.write(r.content)
+                return True
+        return False
+
+    if os.path.exists(dst) and allow_cache:
+        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("开始下载", chatbot=chatbot, history=history)  # 刷新界面
-        proxies = get_conf('proxies')
-        r = requests.get(url_tar, proxies=proxies)
-        with open(dst, 'wb+') as f:
-            f.write(r.content)
+        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_latest_msg(f"下载完成 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+
+
+    if not success:
+        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 ------------->
-    yield from update_ui_lastest_msg("下载完成", chatbot=chatbot, history=history)  # 刷新界面
     from toolbox import extract_archive
-    extract_archive(file_path=dst, dest_dir=extract_dst)
+    try:
+        extract_archive(file_path=dst, dest_dir=extract_dst)
+    except tarfile.ReadError:
+        os.remove(dst)
+        raise tarfile.ReadError(f"论文下载失败")
     return extract_dst, arxiv_id
 
 
@@ -270,7 +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
@@ -320,11 +338,17 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
     # <-------------- more requirements ------------->
     if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
     more_req = plugin_kwargs.get("advanced_arg", "")
-    no_cache = more_req.startswith("--no-cache")
-    if no_cache: more_req.lstrip("--no-cache")
+
+    no_cache = ("--no-cache" in more_req)
+    if no_cache: more_req = more_req.replace("--no-cache", "").strip()
+
+    allow_gptac_cloud_io = ("--allow-cloudio" in more_req)  # 从云端下载翻译结果，以及上传翻译结果到云端
+    if allow_gptac_cloud_io: more_req = more_req.replace("--allow-cloudio", "").strip()
+
     allow_cache = not no_cache
     _switch_prompt_ = partial(switch_prompt, more_requirement=more_req)
 
+
     # <-------------- check deps ------------->
     try:
         import glob, os, time, subprocess
@@ -341,7 +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
@@ -351,6 +375,20 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
         yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
         return
 
+    # #################################################################
+    if allow_gptac_cloud_io and arxiv_id:
+        # 访问 GPTAC学术云，查询云端是否存在该论文的翻译版本
+        from crazy_functions.latex_fns.latex_actions import check_gptac_cloud
+        success, downloaded = check_gptac_cloud(arxiv_id, chatbot)
+        if success:
+            chatbot.append([
+                f"检测到GPTAC云端存在翻译版本, 如果不满意翻译结果, 请禁用云端分享, 然后重新执行。", 
+                None
+            ])
+            yield from update_ui(chatbot=chatbot, history=history)
+            return
+    #################################################################
+
     if os.path.exists(txt):
         project_folder = txt
     else:
@@ -366,7 +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
@@ -388,14 +426,21 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
     # <-------------- zip PDF ------------->
     zip_res = zip_result(project_folder)
     if success:
+        if allow_gptac_cloud_io and arxiv_id:
+            # 如果用户允许，我们将翻译好的arxiv论文PDF上传到GPTAC学术云
+            from crazy_functions.latex_fns.latex_actions import upload_to_gptac_cloud_if_user_allow
+            threading.Thread(target=upload_to_gptac_cloud_if_user_allow, 
+                args=(chatbot, arxiv_id), daemon=True).start()
+
         chatbot.append((f"成功啦", '请查收结果（压缩包）...'))
-        yield from update_ui(chatbot=chatbot, history=history);
+        yield from update_ui(chatbot=chatbot, history=history)
         time.sleep(1)  # 刷新界面
         promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
+
     else:
         chatbot.append((f"失败了",
                         '虽然PDF生成失败了, 但请查收结果（压缩包）, 内含已经翻译的Tex文档, 您可以到Github Issue区, 用该压缩包进行反馈。如系统是Linux，请检查系统字体（见Github wiki） ...'))
-        yield from update_ui(chatbot=chatbot, history=history);
+        yield from update_ui(chatbot=chatbot, history=history)
         time.sleep(1)  # 刷新界面
         promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
 
@@ -473,7 +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)
@@ -486,7 +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..."])
@@ -498,7 +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}")
@@ -506,7 +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
@@ -514,7 +559,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
     project_folder = move_project(project_folder)
 
     # <-------------- set a hash tag for repeat-checking ------------->
-    with open(pj(project_folder, hash_tag + '.tag'), 'w') as f:
+    with open(pj(project_folder, hash_tag + '.tag'), 'w', encoding='utf8') as f:
         f.write(hash_tag)
         f.close()
 
@@ -526,7 +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,

crazy_functions/Latex_Function_Wrap.py

@@ -30,6 +30,8 @@ class Arxiv_Localize(GptAcademicPluginTemplate):
                             default_value="", type="string").model_dump_json(), # 高级参数输入区，自动同步
             "allow_cache":
                 ArgProperty(title="是否允许从缓存中调取结果", options=["允许缓存", "从头执行"], default_value="允许缓存", description="无", type="dropdown").model_dump_json(),
+            "allow_cloudio":
+                ArgProperty(title="是否允许从GPTAC学术云下载(或者上传)翻译结果(仅针对Arxiv论文)", options=["允许", "禁止"], default_value="禁止", description="共享文献，互助互利", type="dropdown").model_dump_json(),
         }
         return gui_definition
 
@@ -38,9 +40,14 @@ class Arxiv_Localize(GptAcademicPluginTemplate):
         执行插件
         """
         allow_cache = plugin_kwargs["allow_cache"]
+        allow_cloudio = plugin_kwargs["allow_cloudio"]
         advanced_arg = plugin_kwargs["advanced_arg"]
 
         if allow_cache == "从头执行": plugin_kwargs["advanced_arg"] = "--no-cache " + plugin_kwargs["advanced_arg"]
+
+        # 从云端下载翻译结果，以及上传翻译结果到云端；人人为我，我为人人。
+        if allow_cloudio == "允许": plugin_kwargs["advanced_arg"] = "--allow-cloudio " + plugin_kwargs["advanced_arg"]
+
         yield from Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
 
 

crazy_functions/Markdown_Translate.py

@@ -65,7 +65,7 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
             pfg.file_contents.append(file_content)
 
     #  <-------- 拆分过长的Markdown文件 ---------->
-    pfg.run_file_split(max_token_limit=2048)
+    pfg.run_file_split(max_token_limit=1024)
     n_split = len(pfg.sp_file_contents)
 
     #  <-------- 多线程翻译开始 ---------->

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
@@ -47,7 +47,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
                 yield from 解析PDF_基于DOC2X(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, DOC2X_API_KEY, user_request)
                 return
             except:
-                chatbot.append([None, f"DOC2X服务不可用，现在将执行效果稍差的旧版代码。{trimmed_format_exc_markdown()}"])
+                chatbot.append([None, f"DOC2X服务不可用，请检查报错详细。{trimmed_format_exc_markdown()}"])
                 yield from update_ui(chatbot=chatbot, history=history)
 
     if method == "GROBID":
@@ -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
 

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
 

crazy_functions/Rag_Interface.py

@@ -1,4 +1,11 @@
-from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_lastest_msg
+import os,glob
+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_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
 
@@ -7,6 +14,37 @@ MAX_HISTORY_ROUND = 5
 MAX_CONTEXT_TOKEN_LIMIT = 4096
 REMEMBER_PREVIEW = 1000
 
+@CatchException
+def handle_document_upload(files: List[str], llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request, rag_worker):
+    """
+    Handles document uploads by extracting text and adding it to the vector store.
+    """
+    from llama_index.core import Document
+    from crazy_functions.rag_fns.rag_file_support import extract_text, supports_format
+    user_name = chatbot.get_user()
+    checkpoint_dir = get_log_folder(user_name, plugin_name='experimental_rag')
+
+    for file_path in files:
+        try:
+            validate_path_safety(file_path, user_name)
+            text = extract_text(file_path)
+            if text is None:
+                chatbot.append(
+                    [f"上传文件: {os.path.basename(file_path)}", f"文件解析失败，无法提取文本内容，请更换文件。失败原因可能为：1.文档格式过于复杂；2. 不支持的文件格式，支持的文件格式后缀有:" + ", ".join(supports_format)])
+            else:
+                chatbot.append(
+                    [f"上传文件: {os.path.basename(file_path)}", f"上传文件前50个字符为:{text[:50]}。"])
+                document = Document(text=text, metadata={"source": file_path})
+                rag_worker.add_documents_to_vector_store([document])
+                chatbot.append([f"上传文件: {os.path.basename(file_path)}", "文件已成功添加到知识库。"])
+        except Exception as e:
+            report_exception(chatbot, history, a=f"处理文件: {file_path}", b=str(e))
+
+    yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
+
+
+# Main Q&A function with document upload support
 @CatchException
 def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
 
@@ -23,28 +61,45 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
     # 1. we retrieve rag worker from global context
     user_name = chatbot.get_user()
     checkpoint_dir = get_log_folder(user_name, plugin_name='experimental_rag')
+
     if user_name in RAG_WORKER_REGISTER:
         rag_worker = RAG_WORKER_REGISTER[user_name]
     else:
         rag_worker = RAG_WORKER_REGISTER[user_name] = LlamaIndexRagWorker(
-            user_name, 
-            llm_kwargs, 
-            checkpoint_dir=checkpoint_dir, 
-            auto_load_checkpoint=True)
+            user_name,
+            llm_kwargs,
+            checkpoint_dir=checkpoint_dir,
+            auto_load_checkpoint=True
+        )
+
     current_context = f"{VECTOR_STORE_TYPE} @ {checkpoint_dir}"
     tip = "提示：输入“清空向量数据库”可以清空RAG向量数据库"
-    if txt == "清空向量数据库":
-        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()
-        yield from update_ui_lastest_msg('已清空', chatbot, history, delay=0) # 刷新界面
+
+    # 2. Handle special commands
+    if os.path.exists(txt) and os.path.isdir(txt):
+        project_folder = txt
+        validate_path_safety(project_folder, chatbot.get_user())
+        # Extract file paths from the user input
+        # Assuming the user inputs file paths separated by commas after the command
+        file_paths =  [f for f in glob.glob(f'{project_folder}/**/*', recursive=True)]
+        chatbot.append([txt, f'正在处理上传的文档 ({current_context}) ...'])
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
+        yield from handle_document_upload(file_paths, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request, rag_worker)
         return
 
-    chatbot.append([txt, f'正在召回知识 ({current_context}) ...'])
-    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+    elif txt == "清空向量数据库":
+        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_latest_msg('已清空', chatbot, history, delay=0)  # 刷新界面
+        return
 
-    # 2. clip history to reduce token consumption
-    #   2-1. reduce chat round
+    # 3. Normal Q&A processing
+    chatbot.append([txt, f'正在召回知识 ({current_context}) ...'])
+    yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
+    # 4. Clip history to reduce token consumption
     txt_origin = txt
 
     if len(history) > MAX_HISTORY_ROUND * 2:
@@ -52,41 +107,47 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
     txt_clip, history, flags = input_clipping(txt, history, max_token_limit=MAX_CONTEXT_TOKEN_LIMIT, return_clip_flags=True)
     input_is_clipped_flag = (flags["original_input_len"] != flags["clipped_input_len"])
 
-    #   2-2. if input is clipped, add input to vector store before retrieve
+    # 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
-        # save input to vector store
+        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
+            HALF = REMEMBER_PREVIEW // 2
             i_say_to_remember = txt[:HALF] + f" ...\n...(省略{len(txt_origin)-REMEMBER_PREVIEW}字)...\n... " + txt[-HALF:]
             if (flags["original_input_len"] - flags["clipped_input_len"]) > HALF:
-                txt_clip = txt_clip  + f" ...\n...(省略{len(txt_origin)-len(txt_clip)-HALF}字)...\n... " + txt[-HALF:]
-            else:
-                pass
-            i_say = txt_clip
+                txt_clip = txt_clip + f" ...\n...(省略{len(txt_origin)-len(txt_clip)-HALF}字)...\n... " + txt[-HALF:]
         else:
             i_say_to_remember = i_say = txt_clip
     else:
         i_say_to_remember = i_say = txt_clip
 
-    # 3. we search vector store and build prompts
+    # 6. Search vector store and build prompts
     nodes = rag_worker.retrieve_from_store_with_query(i_say)
     prompt = rag_worker.build_prompt(query=i_say, nodes=nodes)
+    # 7. Query language model
+    if len(chatbot) != 0:
+        chatbot.pop(-1)  # Pop temp chat, because we are going to add them again inside `request_gpt_model_in_new_thread_with_ui_alive`
 
-    # 4. it is time to query llms
-    if len(chatbot) != 0: chatbot.pop(-1) # pop temp chat, because we are going to add them again inside `request_gpt_model_in_new_thread_with_ui_alive`
     model_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
-        inputs=prompt, inputs_show_user=i_say,
-        llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
+        inputs=prompt,
+        inputs_show_user=i_say,
+        llm_kwargs=llm_kwargs,
+        chatbot=chatbot,
+        history=history,
         sys_prompt=system_prompt,
         retry_times_at_unknown_error=0
     )
 
-    # 5. remember what has been asked / answered
-    yield from update_ui_lastest_msg(model_say + '</br></br>' + f'对话记忆中, 请稍等 ({current_context}) ...', chatbot, history, delay=0.5) # 刷新界面
+    # 8. Remember Q&A
+    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
+    )
     rag_worker.remember_qa(i_say_to_remember, model_say)
     history.extend([i_say, model_say])
 
-    yield from update_ui_lastest_msg(model_say, chatbot, history, delay=0, msg=tip) # 刷新界面
+    # 9. Final UI Update
+    yield from update_ui_latest_msg(model_say, chatbot, history, delay=0, msg=tip)

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, 

crazy_functions/SourceCode_Comment.py

@@ -1,12 +1,15 @@
 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
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from crazy_functions.agent_fns.python_comment_agent import PythonCodeComment
 from crazy_functions.diagram_fns.file_tree import FileNode
+from crazy_functions.agent_fns.watchdog import WatchDog
 from shared_utils.advanced_markdown_format import markdown_convertion_for_file
+from loguru import logger
+
 
 def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
 
@@ -24,12 +27,13 @@ def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
         file_tree_struct.add_file(file_path, file_path)
 
     # <第一步，逐个文件分析，多线程>
+    lang = "" if not plugin_kwargs["use_chinese"] else " (you must use Chinese)"
     for index, fp in enumerate(file_manifest):
         # 读取文件
         with open(fp, 'r', encoding='utf-8', errors='replace') as f:
             file_content = f.read()
         prefix = ""
-        i_say = prefix + f'Please conclude the following source code at {os.path.relpath(fp, project_folder)} with only one sentence, the code is:\n```{file_content}```'
+        i_say = prefix + f'Please conclude the following source code at {os.path.relpath(fp, project_folder)} with only one sentence{lang}, the code is:\n```{file_content}```'
         i_say_show_user = prefix + f'[{index+1}/{len(file_manifest)}] 请用一句话对下面的程序文件做一个整体概述: {fp}'
         # 装载请求内容
         MAX_TOKEN_SINGLE_FILE = 2560
@@ -37,7 +41,7 @@ def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
         inputs_array.append(i_say)
         inputs_show_user_array.append(i_say_show_user)
         history_array.append([])
-        sys_prompt_array.append("You are a software architecture analyst analyzing a source code project. Do not dig into details, tell me what the code is doing in general. Your answer must be short, simple and clear.")
+        sys_prompt_array.append(f"You are a software architecture analyst analyzing a source code project. Do not dig into details, tell me what the code is doing in general. Your answer must be short, simple and clear{lang}.")
     # 文件读取完成，对每一个源代码文件，生成一个请求线程，发送到大模型进行分析
     gpt_response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
         inputs_array = inputs_array,
@@ -50,10 +54,20 @@ def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
     )
 
     # <第二步，逐个文件分析，生成带注释文件>
+    tasks = ["" for _ in range(len(file_manifest))]
+    def bark_fn(tasks):
+        for i in range(len(tasks)): tasks[i] = "watchdog is dead"
+    wd = WatchDog(timeout=10, bark_fn=lambda: bark_fn(tasks), interval=3, msg="ThreadWatcher timeout")
+    wd.begin_watch()
     from concurrent.futures import ThreadPoolExecutor
     executor = ThreadPoolExecutor(max_workers=get_conf('DEFAULT_WORKER_NUM'))
-    def _task_multi_threading(i_say, gpt_say, fp, file_tree_struct):
-        pcc = PythonCodeComment(llm_kwargs, language='English')
+    def _task_multi_threading(i_say, gpt_say, fp, file_tree_struct, index):
+        language = 'Chinese' if plugin_kwargs["use_chinese"] else 'English'
+        def observe_window_update(x):
+            if tasks[index] == "watchdog is dead":
+                raise TimeoutError("ThreadWatcher: watchdog is dead")
+            tasks[index] = x
+        pcc = PythonCodeComment(llm_kwargs, plugin_kwargs, language=language, observe_window_update=observe_window_update)
         pcc.read_file(path=fp, brief=gpt_say)
         revised_path, revised_content = pcc.begin_comment_source_code(None, None)
         file_tree_struct.manifest[fp].revised_path = revised_path
@@ -65,7 +79,8 @@ def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
         with open("crazy_functions/agent_fns/python_comment_compare.html", 'r', encoding='utf-8') as f:
             html_template = f.read()
         warp = lambda x: "```python\n\n" + x + "\n\n```"
-        from themes.theme import advanced_css
+        from themes.theme import load_dynamic_theme
+        _, advanced_css, _, _ = load_dynamic_theme("Default")
         html_template = html_template.replace("ADVANCED_CSS", advanced_css)
         html_template = html_template.replace("REPLACE_CODE_FILE_LEFT", pcc.get_markdown_block_in_html(markdown_convertion_for_file(warp(pcc.original_content))))
         html_template = html_template.replace("REPLACE_CODE_FILE_RIGHT", pcc.get_markdown_block_in_html(markdown_convertion_for_file(warp(revised_content))))
@@ -73,17 +88,21 @@ def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
         file_tree_struct.manifest[fp].compare_html = compare_html_path
         with open(compare_html_path, 'w', encoding='utf-8') as f:
             f.write(html_template)
-        # print('done 1')
+        tasks[index] = ""
 
     chatbot.append([None, f"正在处理:"])
     futures = []
+    index = 0
     for i_say, gpt_say, fp in zip(gpt_response_collection[0::2], gpt_response_collection[1::2], file_manifest):
-        future = executor.submit(_task_multi_threading, i_say, gpt_say, fp, file_tree_struct)
+        future = executor.submit(_task_multi_threading, i_say, gpt_say, fp, file_tree_struct, index)
+        index += 1
         futures.append(future)
 
+    # <第三步，等待任务完成>
     cnt = 0
     while True:
         cnt += 1
+        wd.feed()
         time.sleep(3)
         worker_done = [h.done() for h in futures]
         remain = len(worker_done) - sum(worker_done)
@@ -92,14 +111,18 @@ def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
         preview_html_list = []
         for done, fp in zip(worker_done, file_manifest):
             if not done: continue
-            preview_html_list.append(file_tree_struct.manifest[fp].compare_html)
+            if hasattr(file_tree_struct.manifest[fp], 'compare_html'):
+                preview_html_list.append(file_tree_struct.manifest[fp].compare_html)
+            else:
+                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(
-            f"剩余源文件数量: {remain}.\n\n" + 
-            f"已完成的文件: {sum(worker_done)}.\n\n" + 
+        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/>" + 
             file_links +
-            "\n\n" +
+            "<br/>" +
             ''.join(['.']*(cnt % 10 + 1)
         ), chatbot=chatbot, history=history, delay=0)
         yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
@@ -120,6 +143,7 @@ def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
 @CatchException
 def 注释Python项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
     history = []    # 清空历史，以免输入溢出
+    plugin_kwargs["use_chinese"] = plugin_kwargs.get("use_chinese", False)
     import glob, os
     if os.path.exists(txt):
         project_folder = txt

crazy_functions/SourceCode_Comment_Wrap.py

@@ -0,0 +1,36 @@
+
+from toolbox import get_conf, update_ui
+from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty
+from crazy_functions.SourceCode_Comment import 注释Python项目
+
+class SourceCodeComment_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
+        """
+        gui_definition = {
+            "main_input":
+                ArgProperty(title="路径", description="程序路径（上传文件后自动填写）", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步
+            "use_chinese":
+                ArgProperty(title="注释语言", options=["英文", "中文"], default_value="英文", description="无", type="dropdown").model_dump_json(),
+            # "use_emoji":
+                # ArgProperty(title="在注释中使用emoji", options=["禁止", "允许"], default_value="禁止", description="无", type="dropdown").model_dump_json(),
+        }
+        return gui_definition
+
+    def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
+        """
+        执行插件
+        """
+        if plugin_kwargs["use_chinese"] == "中文": 
+            plugin_kwargs["use_chinese"] = True
+        else: 
+            plugin_kwargs["use_chinese"] = False
+
+        yield from 注释Python项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)

crazy_functions/VideoResource_GPT.py

@@ -0,0 +1,204 @@
+import requests
+import random
+import time
+import re
+import json
+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_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
+from crazy_functions.prompts.internet import SearchOptimizerPrompt, SearchAcademicOptimizerPrompt
+from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
+from textwrap import dedent
+from loguru import logger
+from pydantic import BaseModel, Field
+
+class Query(BaseModel):
+    search_keyword: str = Field(description="search query for video resource")
+
+
+class VideoResource(BaseModel):
+    thought: str = Field(description="analysis of the search results based on the user's query")
+    title: str = Field(description="title of the video")
+    author: str = Field(description="author/uploader of the video") 
+    bvid: str = Field(description="unique ID of the video")
+    another_failsafe_bvid: str = Field(description="provide another bvid, the other one is not working")
+
+
+def get_video_resource(search_keyword):
+    from crazy_functions.media_fns.get_media import search_videos
+
+    # Search for videos and return the first result
+    videos = search_videos(
+        search_keyword
+    )
+
+    # Return the first video if results exist, otherwise return None
+    return videos
+
+def download_video(bvid, user_name, chatbot, history):
+    # from experimental_mods.get_bilibili_resource import download_bilibili
+    from crazy_functions.media_fns.get_media import download_video
+    # pause a while
+    tic_time = 8
+    for i in range(tic_time):
+        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)
+
+    # download audio
+    chatbot.append((None, "下载音频, 请稍等...")); yield from update_ui(chatbot=chatbot, history=history)
+    downloaded_files = yield from download_video(bvid, only_audio=True, user_name=user_name, chatbot=chatbot, history=history)
+
+    if len(downloaded_files) == 0:
+        # failed to download audio
+        return []
+
+    # preview
+    preview_list = [promote_file_to_downloadzone(fp) for fp in downloaded_files]
+    file_links = generate_file_link(preview_list)
+    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_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)
+
+    # download video
+    chatbot.append((None, "下载视频, 请稍等...")); yield from update_ui(chatbot=chatbot, history=history)
+    downloaded_files_part2 = yield from download_video(bvid, only_audio=False, user_name=user_name, chatbot=chatbot, history=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_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
+
+
+class Strategy(BaseModel):
+    thought: str = Field(description="analysis of the user's wish, for example, can you recall the name of the resource?")
+    which_methods: str = Field(description="Which method to use to find the necessary information? choose from 'method_1' and 'method_2'.")
+    method_1_search_keywords: str = Field(description="Generate keywords to search the internet if you choose method 1, otherwise empty.")
+    method_2_generate_keywords: str = Field(description="Generate keywords for video download engine if you choose method 2, otherwise empty.")
+
+
+@CatchException
+def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
+    user_wish: str = txt
+    # query demos: 
+    #   - "我想找一首歌，里面有句歌词是“turn your face towards the sun”"
+    #   - "一首歌，第一句是红豆生南国"
+    #   - "一首音乐，中国航天任务专用的那首"
+    #   - "戴森球计划在熔岩星球的音乐"
+    #   - "hanser的百变什么精"
+    #   - "打大圣残躯时的bgm"
+    #   - "渊下宫战斗音乐"
+
+    # 搜索
+    chatbot.append((txt, "检索中, 请稍等..."))
+    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+    if "跳过联网搜索" not in user_wish:
+        # 结构化生成
+        internet_search_keyword = user_wish
+
+        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,
+            analysis_prompt="请根据搜索结果分析，获取用户需要找的资源的名称、作者、出处等信息。",
+            llm_kwargs=llm_kwargs,
+            chatbot=chatbot
+        )
+
+        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}
+        Meanwhile, you can access another expert's opinion on the user's wish:
+            {result}
+        Generate search keywords (less than 5 keywords) for video download engine accordingly.
+        """)
+    else:
+        user_wish = user_wish.replace("跳过联网搜索", "").strip()
+        rf_req = dedent(f"""
+        The user wish to get the following resource:
+            {user_wish}
+        Generate research keywords (less than 5 keywords) accordingly.
+        """)
+    gpt_json_io = GptJsonIO(Query)
+    inputs = rf_req + gpt_json_io.format_instructions
+    run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
+    analyze_res = run_gpt_fn(inputs, "")
+    logger.info(analyze_res)
+    query: Query = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
+    video_engine_keywords = query.search_keyword
+    # 关键词展示
+    chatbot.append((None, f"检索关键词已确认: {video_engine_keywords}。筛选中, 请稍等..."))
+    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+
+    # 获取候选资源
+    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
+    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
+    rf_req_2 = dedent(f"""
+    The user wish to get the following resource:
+        {user_wish}
+
+    Select the most relevant and suitable video resource from the following search results:
+        {candidate_dictionary_as_str}
+
+    Note:
+        1. The first several search video results are more likely to satisfy the user's wish.
+        2. The time duration of the video should be less than 10 minutes.
+        3. You should analyze the search results first, before giving your answer.
+        4. Use Chinese if possible.
+        5. Beside the primary video selection, give a backup video resource `bvid`.
+    """)
+    gpt_json_io = GptJsonIO(VideoResource)
+    inputs = rf_req_2 + gpt_json_io.format_instructions
+    run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
+    analyze_res = run_gpt_fn(inputs, "")
+    logger.info(analyze_res)
+    video_resource: VideoResource = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
+
+    # Display
+    chatbot.append(
+        (None, 
+            f"分析：{video_resource.thought}" "<br/>"
+            f"选择: `{video_resource.title}`。" "<br/>" 
+            f"作者：{video_resource.author}"
+        )
+    )
+    chatbot.append((None, f"下载中, 请稍等..."))
+    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+
+    if video_resource and video_resource.bvid:
+        logger.info(video_resource)
+        downloaded = yield from download_video(video_resource.bvid, chatbot.get_user(), chatbot, history)
+        if not downloaded:
+            chatbot.append((None, f"下载失败, 尝试备选 ..."))
+            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+            downloaded = yield from download_video(video_resource.another_failsafe_bvid, chatbot.get_user(), chatbot, history)
+
+
+
+
+        
+@CatchException
+def debug(bvid, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
+    yield from download_video(bvid, chatbot.get_user(), chatbot, history)

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
 

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:

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

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).
@@ -68,6 +68,7 @@ Be aware:
 1. You must NOT modify the indent of code.
 2. You are NOT authorized to change or translate non-comment code, and you are NOT authorized to add empty lines either, toggle qu.
 3. Use {LANG} to add comments and docstrings. Do NOT translate Chinese that is already in the code.
+4. Besides adding a docstring, use the ⭐ symbol to annotate the most core and important line of code within the function, explaining its role.
 
 ------------------ Example ------------------
 INPUT:
@@ -116,10 +117,66 @@ def zip_result(folder):
 '''
 
 
+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
+
+请注意：
+1. 你不得修改代码的缩进
+2. 你无权更改或翻译代码中的非注释部分，也不允许添加空行
+3. 使用 {LANG} 添加注释和文档字符串。不要翻译代码中已有的中文
+4. 除了添加docstring之外, 使用⭐符号给该函数中最核心、最重要的一行代码添加注释，并说明其作用
+
+------------------ 示例 ------------------
+INPUT:
+```
+L0000 |
+L0001 |def zip_result(folder):
+L0002 |    t = gen_time_str()
+L0003 |    zip_folder(folder, get_log_folder(), f"result.zip")
+L0004 |    return os.path.join(get_log_folder(), f"result.zip")
+L0005 |
+L0006 |
+```
+
+OUTPUT:
+
+<instruction_1_purpose>
+该函数用于压缩指定文件夹，并返回生成的`zip`文件的路径。
+</instruction_1_purpose>
+<instruction_2_revised_code>
+```
+def zip_result(folder):
+    """
+    该函数将指定的文件夹压缩成ZIP文件, 并将其存储在日志文件夹中。
+
+    输入参数:
+        folder (str): 需要压缩的文件夹的路径。
+    返回值:
+        str: 日志文件夹中创建的ZIP文件的路径。
+    """
+    t = gen_time_str()
+    zip_folder(folder, get_log_folder(), f"result.zip")  # ⭐ 执行文件夹的压缩
+    return os.path.join(get_log_folder(), f"result.zip")
+```
+</instruction_2_revised_code>
+------------------ End of Example ------------------
+
+
+------------------ the real INPUT you need to process NOW ({FILE_BASENAME}) ------------------
+```
+{THE_CODE}
+```
+{INDENT_REMINDER}
+{BRIEF_REMINDER}
+{HINT_REMINDER}
+'''
+
 
 class PythonCodeComment():
 
-    def __init__(self, llm_kwargs, language) -> None:
+    def __init__(self, llm_kwargs, plugin_kwargs, language, observe_window_update) -> None:
         self.original_content = ""
         self.full_context = []
         self.full_context_with_line_no = []
@@ -127,7 +184,13 @@ class PythonCodeComment():
         self.page_limit = 100 # 100 lines of code each page
         self.ignore_limit = 20
         self.llm_kwargs = llm_kwargs
+        self.plugin_kwargs = plugin_kwargs
         self.language = language
+        self.observe_window_update = observe_window_update
+        if self.language == "chinese":
+            self.core_prompt = revise_function_prompt_chinese
+        else:
+            self.core_prompt = revise_function_prompt
         self.path = None
         self.file_basename = None
         self.file_brief = ""
@@ -159,7 +222,7 @@ class PythonCodeComment():
             history=[],
             sys_prompt="",
             observe_window=[],
-            console_slience=True
+            console_silence=True
         )
 
         def extract_number(text):
@@ -253,12 +316,12 @@ 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
         result = predict_no_ui_long_connection(
-            inputs=revise_funtion_prompt.format(
+            inputs=self.core_prompt.format(
                 LANG=self.language, 
                 FILE_BASENAME=self.file_basename, 
                 THE_CODE=code, 
@@ -270,7 +333,7 @@ class PythonCodeComment():
             history=[],
             sys_prompt="",
             observe_window=[],
-            console_slience=True
+            console_silence=True
         )
 
         def get_code_block(reply):
@@ -337,7 +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'
@@ -346,9 +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()
-                # 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)
+                self.observe_window_update(f"正在处理{self.file_basename} - {line_no_start}/{len(self.full_context)}\n")
+                # 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

crazy_functions/ast_fns/comment_remove.py

@@ -1,39 +1,47 @@
-import ast
+import token
+import tokenize
+import copy
+import io
 
-class CommentRemover(ast.NodeTransformer):
-    def visit_FunctionDef(self, node):
-        # 移除函数的文档字符串
-        if (node.body and isinstance(node.body[0], ast.Expr) and
-                isinstance(node.body[0].value, ast.Str)):
-            node.body = node.body[1:]
-        self.generic_visit(node)
-        return node
 
-    def visit_ClassDef(self, node):
-        # 移除类的文档字符串
-        if (node.body and isinstance(node.body[0], ast.Expr) and
-                isinstance(node.body[0].value, ast.Str)):
-            node.body = node.body[1:]
-        self.generic_visit(node)
-        return node
+def remove_python_comments(input_source: str) -> str:
+    source_flag = copy.copy(input_source)
+    source = io.StringIO(input_source)
+    ls = input_source.split('\n')
+    prev_toktype = token.INDENT
+    readline = source.readline
 
-    def visit_Module(self, node):
-        # 移除模块的文档字符串
-        if (node.body and isinstance(node.body[0], ast.Expr) and
-                isinstance(node.body[0].value, ast.Str)):
-            node.body = node.body[1:]
-        self.generic_visit(node)
-        return node
-    
+    def get_char_index(lineno, col):
+        # find the index of the char in the source code
+        if lineno == 1:
+            return len('\n'.join(ls[:(lineno-1)])) + col
+        else:
+            return len('\n'.join(ls[:(lineno-1)])) + col + 1
+
+    def replace_char_between(start_lineno, start_col, end_lineno, end_col, source, replace_char, ls):
+        # replace char between start_lineno, start_col and end_lineno, end_col with replace_char, but keep '\n' and ' '
+        b = get_char_index(start_lineno, start_col)
+        e = get_char_index(end_lineno, end_col)
+        for i in range(b, e):
+            if source[i] == '\n':
+                source = source[:i] + '\n' + source[i+1:]
+            elif source[i] == ' ':
+                source = source[:i] + ' ' + source[i+1:]
+            else:
+                source = source[:i] + replace_char + source[i+1:]
+        return source
+
+    tokgen = tokenize.generate_tokens(readline)
+    for toktype, ttext, (slineno, scol), (elineno, ecol), ltext in tokgen:
+        if toktype == token.STRING and (prev_toktype == token.INDENT):
+            source_flag = replace_char_between(slineno, scol, elineno, ecol, source_flag, ' ', ls)
+        elif toktype == token.STRING and (prev_toktype == token.NEWLINE):
+            source_flag = replace_char_between(slineno, scol, elineno, ecol, source_flag, ' ', ls)
+        elif toktype == tokenize.COMMENT:
+            source_flag = replace_char_between(slineno, scol, elineno, ecol, source_flag, ' ', ls)
+        prev_toktype = toktype
+    return source_flag
 
-def remove_python_comments(source_code):
-    # 解析源代码为 AST
-    tree = ast.parse(source_code)
-    # 移除注释
-    transformer = CommentRemover()
-    tree = transformer.visit(tree)
-    # 将处理后的 AST 转换回源代码
-    return ast.unparse(tree)
 
 # 示例使用
 if __name__ == "__main__":

crazy_functions/chatglm微调工具.py

@@ -1,141 +0,0 @@
-from toolbox import CatchException, update_ui, promote_file_to_downloadzone
-from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
-import datetime, json
-
-def fetch_items(list_of_items, batch_size):
-    for i in range(0, len(list_of_items), batch_size):
-        yield list_of_items[i:i + batch_size]
-
-def string_to_options(arguments):
-    import argparse
-    import shlex
-
-    # Create an argparse.ArgumentParser instance
-    parser = argparse.ArgumentParser()
-
-    # Add command-line arguments
-    parser.add_argument("--llm_to_learn", type=str, help="LLM model to learn", default="gpt-3.5-turbo")
-    parser.add_argument("--prompt_prefix", type=str, help="Prompt prefix", default='')
-    parser.add_argument("--system_prompt", type=str, help="System prompt", default='')
-    parser.add_argument("--batch", type=int, help="System prompt", default=50)
-    parser.add_argument("--pre_seq_len", type=int, help="pre_seq_len", default=50)
-    parser.add_argument("--learning_rate", type=float, help="learning_rate", default=2e-2)
-    parser.add_argument("--num_gpus", type=int, help="num_gpus", default=1)
-    parser.add_argument("--json_dataset", type=str, help="json_dataset", default="")
-    parser.add_argument("--ptuning_directory", type=str, help="ptuning_directory", default="")
-
-
-
-    # Parse the arguments
-    args = parser.parse_args(shlex.split(arguments))
-
-    return args
-
-@CatchException
-def 微调数据集生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
-    """
-    txt             输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径
-    llm_kwargs      gpt模型参数，如温度和top_p等，一般原样传递下去就行
-    plugin_kwargs   插件模型的参数
-    chatbot         聊天显示框的句柄，用于显示给用户
-    history         聊天历史，前情提要
-    system_prompt   给gpt的静默提醒
-    user_request    当前用户的请求信息（IP地址等）
-    """
-    history = []    # 清空历史，以免输入溢出
-    chatbot.append(("这是什么功能？", "[Local Message] 微调数据集生成"))
-    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
-    args = plugin_kwargs.get("advanced_arg", None)
-    if args is None:
-        chatbot.append(("没给定指令", "退出"))
-        yield from update_ui(chatbot=chatbot, history=history); return
-    else:
-        arguments = string_to_options(arguments=args)
-
-    dat = []
-    with open(txt, 'r', encoding='utf8') as f:
-        for line in f.readlines():
-            json_dat = json.loads(line)
-            dat.append(json_dat["content"])
-
-    llm_kwargs['llm_model'] = arguments.llm_to_learn
-    for batch in fetch_items(dat, arguments.batch):
-        res = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
-            inputs_array=[f"{arguments.prompt_prefix}\n\n{b}" for b in (batch)],
-            inputs_show_user_array=[f"Show Nothing" for _ in (batch)],
-            llm_kwargs=llm_kwargs,
-            chatbot=chatbot,
-            history_array=[[] for _ in (batch)],
-            sys_prompt_array=[arguments.system_prompt for _ in (batch)],
-            max_workers=10  # OpenAI所允许的最大并行过载
-        )
-
-        with open(txt+'.generated.json', 'a+', encoding='utf8') as f:
-            for b, r in zip(batch, res[1::2]):
-                f.write(json.dumps({"content":b, "summary":r}, ensure_ascii=False)+'\n')
-
-    promote_file_to_downloadzone(txt+'.generated.json', rename_file='generated.json', chatbot=chatbot)
-    return
-
-
-
-@CatchException
-def 启动微调(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
-    """
-    txt             输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径
-    llm_kwargs      gpt模型参数，如温度和top_p等，一般原样传递下去就行
-    plugin_kwargs   插件模型的参数
-    chatbot         聊天显示框的句柄，用于显示给用户
-    history         聊天历史，前情提要
-    system_prompt   给gpt的静默提醒
-    user_request    当前用户的请求信息（IP地址等）
-    """
-    import subprocess
-    history = []    # 清空历史，以免输入溢出
-    chatbot.append(("这是什么功能？", "[Local Message] 微调数据集生成"))
-    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
-    args = plugin_kwargs.get("advanced_arg", None)
-    if args is None:
-        chatbot.append(("没给定指令", "退出"))
-        yield from update_ui(chatbot=chatbot, history=history); return
-    else:
-        arguments = string_to_options(arguments=args)
-
-
-
-    pre_seq_len = arguments.pre_seq_len             # 128
-    learning_rate = arguments.learning_rate                               # 2e-2
-    num_gpus = arguments.num_gpus                   # 1
-    json_dataset = arguments.json_dataset                 # 't_code.json'
-    ptuning_directory = arguments.ptuning_directory       # '/home/hmp/ChatGLM2-6B/ptuning'
-
-    command = f"torchrun --standalone --nnodes=1 --nproc-per-node={num_gpus} main.py \
-        --do_train \
-        --train_file AdvertiseGen/{json_dataset} \
-        --validation_file AdvertiseGen/{json_dataset} \
-        --preprocessing_num_workers 20 \
-        --prompt_column content \
-        --response_column summary \
-        --overwrite_cache \
-        --model_name_or_path THUDM/chatglm2-6b \
-        --output_dir output/clothgen-chatglm2-6b-pt-{pre_seq_len}-{learning_rate} \
-        --overwrite_output_dir \
-        --max_source_length 256 \
-        --max_target_length 256 \
-        --per_device_train_batch_size 1 \
-        --per_device_eval_batch_size 1 \
-        --gradient_accumulation_steps 16 \
-        --predict_with_generate \
-        --max_steps 100 \
-        --logging_steps 10 \
-        --save_steps 20 \
-        --learning_rate {learning_rate} \
-        --pre_seq_len {pre_seq_len} \
-        --quantization_bit 4"
-
-    process = subprocess.Popen(command, shell=True, cwd=ptuning_directory)
-    try:
-        process.communicate(timeout=3600*24)
-    except subprocess.TimeoutExpired:
-        process.kill()
-    return

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):
@@ -169,6 +169,7 @@ def can_multi_process(llm) -> bool:
     def default_condition(llm) -> bool:
         # legacy condition
         if llm.startswith('gpt-'): return True
+        if llm.startswith('chatgpt-'): return True
         if llm.startswith('api2d-'): return True
         if llm.startswith('azure-'): return True
         if llm.startswith('spark'): return True
@@ -255,7 +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
@@ -325,7 +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'
@@ -388,11 +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):
         """
@@ -432,11 +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:
@@ -609,9 +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
@@ -619,7 +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)

crazy_functions/doc_fns/AI_review_doc.py

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

crazy_functions/doc_fns/batch_file_query_doc.py

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

crazy_functions/doc_fns/content_folder.py

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

crazy_functions/doc_fns/conversation_doc/excel_doc.py

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

crazy_functions/doc_fns/conversation_doc/html_doc.py

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

crazy_functions/doc_fns/conversation_doc/markdown_doc.py

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

crazy_functions/doc_fns/conversation_doc/pdf_doc.py

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

crazy_functions/doc_fns/conversation_doc/txt_doc.py

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

crazy_functions/doc_fns/conversation_doc/word2pdf.py

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

crazy_functions/doc_fns/conversation_doc/word_doc.py

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

crazy_functions/doc_fns/read_fns/docx_reader.py

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

crazy_functions/doc_fns/read_fns/excel_reader.py

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

crazy_functions/doc_fns/read_fns/markitdown/markdown_reader.py

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

crazy_functions/doc_fns/read_fns/unstructured_all/paper_metadata_extractor.py

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

crazy_functions/doc_fns/read_fns/unstructured_all/unstructured_md.py

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

crazy_functions/doc_fns/read_fns/unstructured_all/unstructured_reader.py

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

crazy_functions/doc_fns/read_fns/web_reader.py

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

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.)

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

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):

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
 

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
+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
@@ -300,7 +300,8 @@ def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin
     write_html(pfg.sp_file_contents, pfg.sp_file_result, chatbot=chatbot, project_folder=project_folder)
 
     #  <-------- 写出文件 ---------->
-    msg = f"当前大语言模型: {llm_kwargs['llm_model']}，当前语言模型温度设定: {llm_kwargs['temperature']}。"
+    model_name = llm_kwargs['llm_model'].replace('_', '\\_')  # 替换LLM模型名称中的下划线为转义字符
+    msg = f"当前大语言模型: {model_name}，当前语言模型温度设定: {llm_kwargs['temperature']}。"
     final_tex = lps.merge_result(pfg.file_result, mode, msg)
     objdump((lps, pfg.file_result, mode, msg), file=pj(project_folder,'merge_result.pkl'))
 
@@ -350,7 +351,42 @@ 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:
+            with open(tex_path, 'r', encoding='utf-8', errors='replace') as f:
+                content = f.read(5000)
+                # 检查是否有使用xelatex的宏包
+                need_xelatex = any(
+                    pkg in content 
+                    for pkg in ['fontspec', 'xeCJK', 'xetex', 'unicode-math', 'xltxtra', 'xunicode']
+                )
+                if need_xelatex:
+                    logger.info(f"检测到宏包需要xelatex编译, 切换至xelatex编译")
+                else:
+                    logger.info(f"未检测到宏包需要xelatex编译, 使用pdflatex编译")
+                return need_xelatex
+        except Exception:
+            return False
+
+    # 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)
+        return compile_command
+
+    # 确定使用的编译器
+    compiler = 'pdflatex'
+    if check_if_need_xelatex(pj(work_folder_modified, f'{main_file_modified}.tex')):
+        logger.info("检测到宏包需要xelatex编译，切换至xelatex编译")
+        # Check if xelatex is installed
+        try:
+            import subprocess
+            subprocess.run(['xelatex', '--version'], capture_output=True, check=True)
+            compiler = 'xelatex'
+        except (subprocess.CalledProcessError, FileNotFoundError):
+            raise RuntimeError("检测到需要使用xelatex编译，但系统中未安装xelatex。请先安装texlive或其他提供xelatex的LaTeX发行版。")
 
     while True:
         import os
@@ -360,36 +396,36 @@ 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
-        ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', work_folder_original)
+        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
-        ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
+        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
-            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', work_folder_original)
-            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
-            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex', work_folder_original)
-            ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex', work_folder_modified)
+            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
-                ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
+                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(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
-                ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
+                ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
+                ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
 
         # <---------- 检查结果 ----------->
         results_ = ""
@@ -399,13 +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')):
@@ -436,7 +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
@@ -468,3 +504,70 @@ def write_html(sp_file_contents, sp_file_result, chatbot, project_folder):
     except:
         from toolbox import trimmed_format_exc
         logger.error('writing html result failed:', trimmed_format_exc())
+
+
+def upload_to_gptac_cloud_if_user_allow(chatbot, arxiv_id):
+    try:
+        # 如果用户允许，我们将arxiv论文PDF上传到GPTAC学术云
+        from toolbox import map_file_to_sha256
+        # 检查是否顺利，如果没有生成预期的文件，则跳过
+        is_result_good = False
+        for file_path in chatbot._cookies.get("files_to_promote", []):
+            if file_path.endswith('translate_zh.pdf'):
+                is_result_good = True
+        if not is_result_good:
+            return
+        # 上传文件
+        for file_path in chatbot._cookies.get("files_to_promote", []):
+            align_name = None
+            # normalized name
+            for name in ['translate_zh.pdf', 'comparison.pdf']:
+                if file_path.endswith(name): align_name = name
+            # if match any align name
+            if align_name:
+                logger.info(f'Uploading to GPTAC cloud as the user has set `allow_cloud_io`: {file_path}')
+                with open(file_path, 'rb') as f:
+                    import requests
+                    url = 'https://cloud-2.agent-matrix.com/arxiv_tf_paper_normal_upload'
+                    files = {'file': (align_name, f, 'application/octet-stream')}
+                    data = {
+                        'arxiv_id': arxiv_id,
+                        'file_hash': map_file_to_sha256(file_path),
+                        'language': 'zh',
+                        'trans_prompt': 'to_be_implemented',
+                        'llm_model': 'to_be_implemented',
+                        'llm_model_param': 'to_be_implemented',
+                    }
+                    resp = requests.post(url=url, files=files, data=data, timeout=30)
+                logger.info(f'Uploading terminate ({resp.status_code})`: {file_path}')
+    except:
+        # 如果上传失败，不会中断程序，因为这是次要功能
+        pass
+
+def check_gptac_cloud(arxiv_id, chatbot):
+    import requests
+    success = False
+    downloaded = []
+    try:
+        for pdf_target in ['translate_zh.pdf', 'comparison.pdf']:
+            url = 'https://cloud-2.agent-matrix.com/arxiv_tf_paper_normal_exist'
+            data = {
+                'arxiv_id': arxiv_id,
+                'name': pdf_target,
+            }
+            resp = requests.post(url=url, data=data)
+            cache_hit_result = resp.text.strip('"')
+            if cache_hit_result.startswith("http"):
+                url = cache_hit_result
+                logger.info(f'Downloading from GPTAC cloud: {url}')
+                resp = requests.get(url=url, timeout=30)
+                target = os.path.join(get_log_folder(plugin_name='gptac_cloud'), gen_time_str(), pdf_target)
+                os.makedirs(os.path.dirname(target), exist_ok=True)
+                with open(target, 'wb') as f:
+                    f.write(resp.content)
+                new_path = promote_file_to_downloadzone(target, chatbot=chatbot)
+                success = True
+                downloaded.append(new_path)
+    except:
+        pass
+    return success, downloaded

crazy_functions/latex_fns/latex_pickle_io.py

@@ -6,12 +6,16 @@ class SafeUnpickler(pickle.Unpickler):
     def get_safe_classes(self):
         from crazy_functions.latex_fns.latex_actions import LatexPaperFileGroup, LatexPaperSplit
         from crazy_functions.latex_fns.latex_toolbox import LinkedListNode
+        from numpy.core.multiarray import scalar
+        from numpy import dtype
         # 定义允许的安全类
         safe_classes = {
             # 在这里添加其他安全的类
             'LatexPaperFileGroup': LatexPaperFileGroup,
             'LatexPaperSplit': LatexPaperSplit,
             'LinkedListNode': LinkedListNode,
+            'scalar': scalar,
+            'dtype': dtype,
         }
         return safe_classes
 
@@ -22,8 +26,6 @@ class SafeUnpickler(pickle.Unpickler):
         for class_name in self.safe_classes.keys():
             if (class_name in f'{module}.{name}'):
                 match_class_name = class_name
-        if module == 'numpy' or module.startswith('numpy.'):
-            return super().find_class(module, name)
         if match_class_name is not None:
             return self.safe_classes[match_class_name]
         # 如果尝试加载未授权的类，则抛出异常

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
     """
@@ -697,15 +697,6 @@ def _merge_pdfs_ng(pdf1_path, pdf2_path, output_path):
                     ),
                     0,
                 )
-                if "/Annots" in page1:
-                    page1_annot_id = [annot.idnum for annot in page1["/Annots"]]
-                else:
-                    page1_annot_id = []
-
-                if "/Annots" in page2:
-                    page2_annot_id = [annot.idnum for annot in page2["/Annots"]]
-                else:
-                    page2_annot_id = []
                 if "/Annots" in new_page:
                     annotations = new_page["/Annots"]
                     for i, annot in enumerate(annotations):
@@ -720,114 +711,148 @@ def _merge_pdfs_ng(pdf1_path, pdf2_path, output_path):
                                 if "/S" in action and action["/S"] == "/GoTo":
                                     # 内部链接：跳转到文档中的某个页面
                                     dest = action.get("/D")  # 目标页或目标位置
-                                    if dest and annot.idnum in page2_annot_id:
-                                        # 获取原始文件中跳转信息，包括跳转页面
-                                        destination = pdf2_reader.named_destinations[
-                                            dest
-                                        ]
-                                        page_number = (
-                                            pdf2_reader.get_destination_page_number(
-                                                destination
-                                            )
-                                        )
-                                        # 更新跳转信息，跳转到对应的页面和，指定坐标 (100, 150)，缩放比例为 100%
-                                        # “/D”:[10,'/XYZ',100,100,0]
-                                        annot_obj["/A"].update(
-                                            {
-                                                NameObject("/D"): ArrayObject(
-                                                    [
-                                                        NumberObject(page_number),
-                                                        destination.dest_array[1],
-                                                        FloatObject(
-                                                            destination.dest_array[2]
-                                                            + int(
-                                                                page1.mediaBox.getWidth()
-                                                            )
-                                                        ),
-                                                        destination.dest_array[3],
-                                                        destination.dest_array[4],
-                                                    ]
-                                                )  # 确保键和值是 PdfObject
-                                            }
-                                        )
-                                        rect = annot_obj.get("/Rect")
-                                        # 更新点击坐标
-                                        rect = ArrayObject(
-                                            [
-                                                FloatObject(
-                                                    rect[0]
-                                                    + int(page1.mediaBox.getWidth())
-                                                ),
-                                                rect[1],
-                                                FloatObject(
-                                                    rect[2]
-                                                    + int(page1.mediaBox.getWidth())
-                                                ),
-                                                rect[3],
+                                    # if dest and annot.idnum in page2_annot_id:
+                                    # if dest in pdf2_reader.named_destinations:
+                                    if dest and page2.annotations:
+                                        if annot in page2.annotations:
+                                            # 获取原始文件中跳转信息，包括跳转页面
+                                            destination = pdf2_reader.named_destinations[
+                                                dest
                                             ]
-                                        )
-                                        annot_obj.update(
-                                            {
-                                                NameObject(
-                                                    "/Rect"
-                                                ): rect  # 确保键和值是 PdfObject
-                                            }
-                                        )
-                                    if dest and annot.idnum in page1_annot_id:
-                                        # 获取原始文件中跳转信息，包括跳转页面
-                                        destination = pdf1_reader.named_destinations[
-                                            dest
-                                        ]
-                                        page_number = (
-                                            pdf1_reader.get_destination_page_number(
-                                                destination
+                                            page_number = (
+                                                pdf2_reader.get_destination_page_number(
+                                                    destination
+                                                )
                                             )
-                                        )
-                                        # 更新跳转信息，跳转到对应的页面和，指定坐标 (100, 150)，缩放比例为 100%
-                                        # “/D”:[10,'/XYZ',100,100,0]
-                                        annot_obj["/A"].update(
-                                            {
-                                                NameObject("/D"): ArrayObject(
-                                                    [
-                                                        NumberObject(page_number),
-                                                        destination.dest_array[1],
-                                                        FloatObject(
-                                                            destination.dest_array[2]
-                                                        ),
-                                                        destination.dest_array[3],
-                                                        destination.dest_array[4],
-                                                    ]
-                                                )  # 确保键和值是 PdfObject
-                                            }
-                                        )
-                                        rect = annot_obj.get("/Rect")
-                                        rect = ArrayObject(
-                                            [
-                                                FloatObject(rect[0]),
-                                                rect[1],
-                                                FloatObject(rect[2]),
-                                                rect[3],
+                                            # 更新跳转信息，跳转到对应的页面和，指定坐标 (100, 150)，缩放比例为 100%
+                                            # “/D”:[10,'/XYZ',100,100,0]
+                                            if destination.dest_array[1] == "/XYZ":
+                                                annot_obj["/A"].update(
+                                                    {
+                                                        NameObject("/D"): ArrayObject(
+                                                            [
+                                                                NumberObject(page_number),
+                                                                destination.dest_array[1],
+                                                                FloatObject(
+                                                                    destination.dest_array[
+                                                                        2
+                                                                    ]
+                                                                    + int(
+                                                                        page1.mediaBox.getWidth()
+                                                                    )
+                                                                ),
+                                                                destination.dest_array[3],
+                                                                destination.dest_array[4],
+                                                            ]
+                                                        )  # 确保键和值是 PdfObject
+                                                    }
+                                                )
+                                            else:
+                                                annot_obj["/A"].update(
+                                                    {
+                                                        NameObject("/D"): ArrayObject(
+                                                            [
+                                                                NumberObject(page_number),
+                                                                destination.dest_array[1],
+                                                            ]
+                                                        )  # 确保键和值是 PdfObject
+                                                    }
+                                                )
+
+                                            rect = annot_obj.get("/Rect")
+                                            # 更新点击坐标
+                                            rect = ArrayObject(
+                                                [
+                                                    FloatObject(
+                                                        rect[0]
+                                                        + int(page1.mediaBox.getWidth())
+                                                    ),
+                                                    rect[1],
+                                                    FloatObject(
+                                                        rect[2]
+                                                        + int(page1.mediaBox.getWidth())
+                                                    ),
+                                                    rect[3],
+                                                ]
+                                            )
+                                            annot_obj.update(
+                                                {
+                                                    NameObject(
+                                                        "/Rect"
+                                                    ): rect  # 确保键和值是 PdfObject
+                                                }
+                                            )
+                                    # if dest and annot.idnum in page1_annot_id:
+                                    # if dest in pdf1_reader.named_destinations:
+                                    if dest and page1.annotations:
+                                        if annot in page1.annotations:
+                                            # 获取原始文件中跳转信息，包括跳转页面
+                                            destination = pdf1_reader.named_destinations[
+                                                dest
                                             ]
-                                        )
-                                        annot_obj.update(
-                                            {
-                                                NameObject(
-                                                    "/Rect"
-                                                ): rect  # 确保键和值是 PdfObject
-                                            }
-                                        )
+                                            page_number = (
+                                                pdf1_reader.get_destination_page_number(
+                                                    destination
+                                                )
+                                            )
+                                            # 更新跳转信息，跳转到对应的页面和，指定坐标 (100, 150)，缩放比例为 100%
+                                            # “/D”:[10,'/XYZ',100,100,0]
+                                            if destination.dest_array[1] == "/XYZ":
+                                                annot_obj["/A"].update(
+                                                    {
+                                                        NameObject("/D"): ArrayObject(
+                                                            [
+                                                                NumberObject(page_number),
+                                                                destination.dest_array[1],
+                                                                FloatObject(
+                                                                    destination.dest_array[
+                                                                        2
+                                                                    ]
+                                                                ),
+                                                                destination.dest_array[3],
+                                                                destination.dest_array[4],
+                                                            ]
+                                                        )  # 确保键和值是 PdfObject
+                                                    }
+                                                )
+                                            else:
+                                                annot_obj["/A"].update(
+                                                    {
+                                                        NameObject("/D"): ArrayObject(
+                                                            [
+                                                                NumberObject(page_number),
+                                                                destination.dest_array[1],
+                                                            ]
+                                                        )  # 确保键和值是 PdfObject
+                                                    }
+                                                )
+
+                                            rect = annot_obj.get("/Rect")
+                                            rect = ArrayObject(
+                                                [
+                                                    FloatObject(rect[0]),
+                                                    rect[1],
+                                                    FloatObject(rect[2]),
+                                                    rect[3],
+                                                ]
+                                            )
+                                            annot_obj.update(
+                                                {
+                                                    NameObject(
+                                                        "/Rect"
+                                                    ): rect  # 确保键和值是 PdfObject
+                                                }
+                                            )
 
                                 elif "/S" in action and action["/S"] == "/URI":
                                     # 外部链接：跳转到某个URI
                                     uri = action.get("/URI")
-
                 output_writer.addPage(new_page)
             # Save the merged PDF file
             with open(output_path, "wb") as output_file:
                 output_writer.write(output_file)
 
 
-
 def _merge_pdfs_legacy(pdf1_path, pdf2_path, output_path):
     import PyPDF2  # PyPDF2这个库有严重的内存泄露问题，把它放到子进程中运行，从而方便内存的释放
 

crazy_functions/media_fns/get_media.py

@@ -0,0 +1,43 @@
+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
+
+def download_video(video_id, only_audio, user_name, chatbot, history):
+    from toolbox import get_log_folder
+    chatbot.append([None, "Processing..."])
+    yield from update_ui(chatbot, history)
+    client_command = f'{video_id} --audio-only' if only_audio else video_id
+    server_urls = get_conf('DAAS_SERVER_URLS')
+    server_url = random.choice(server_urls)
+    docker_service_api_com_model = DockerServiceApiComModel(client_command=client_command)
+    save_file_dir = get_log_folder(user_name, plugin_name='media_downloader')
+    for output_manifest in stream_daas(docker_service_api_com_model, server_url, save_file_dir):
+        status_buf = ""
+        status_buf += "DaaS message: \n\n"
+        status_buf += output_manifest['server_message'].replace('\n', '<br/>')
+        status_buf += "\n\n"
+        status_buf += "DaaS standard error: \n\n"
+        status_buf += output_manifest['server_std_err'].replace('\n', '<br/>')
+        status_buf += "\n\n"
+        status_buf += "DaaS standard output: \n\n"
+        status_buf += output_manifest['server_std_out'].replace('\n', '<br/>')
+        status_buf += "\n\n"
+        status_buf += "DaaS file attach: \n\n"
+        status_buf += str(output_manifest['server_file_attach'])
+        yield from update_ui_latest_msg(status_buf, chatbot, history)
+
+    return output_manifest['server_file_attach']
+
+
+def search_videos(keywords):
+    from toolbox import get_log_folder
+    client_command = keywords
+    server_urls = get_conf('DAAS_SERVER_URLS')
+    server_url = random.choice(server_urls)
+    server_url = server_url.replace('stream', 'search')
+    docker_service_api_com_model = DockerServiceApiComModel(client_command=client_command)
+    save_file_dir = get_log_folder("default_user", plugin_name='media_downloader')
+    for output_manifest in stream_daas(docker_service_api_com_model, server_url, save_file_dir):
+        return output_manifest['server_message']
+

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

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'])

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
 

crazy_functions/pdf_fns/parse_pdf_via_doc2x.py

@@ -4,126 +4,228 @@ from toolbox import promote_file_to_downloadzone, extract_archive
 from toolbox import generate_file_link, zip_folder
 from crazy_functions.crazy_utils import get_files_from_everything
 from shared_utils.colorful import *
+from loguru import logger
 import os
+import requests
+import time
+
+
+def retry_request(max_retries=3, delay=3):
+    """
+    Decorator for retrying HTTP requests
+    Args:
+        max_retries: Maximum number of retry attempts
+        delay: Delay between retries in seconds
+    """
+
+    def decorator(func):
+        def wrapper(*args, **kwargs):
+            for attempt in range(max_retries):
+                try:
+                    return func(*args, **kwargs)
+                except Exception as e:
+                    if attempt < max_retries - 1:
+                        logger.error(
+                            f"Request failed, retrying... ({attempt + 1}/{max_retries}) Error: {e}"
+                        )
+                        time.sleep(delay)
+                        continue
+                    raise e
+            return None
+
+        return wrapper
+
+    return decorator
+
+
+@retry_request()
+def make_request(method, url, **kwargs):
+    """
+    Make HTTP request with retry mechanism
+    """
+    return requests.request(method, url, **kwargs)
+
+
+def doc2x_api_response_status(response, uid=""):
+    """
+    Check the status of Doc2x API response
+    Args:
+        response_data: Response object from Doc2x API
+    """
+    response_json = response.json()
+    response_data = response_json.get("data", {})
+    code = response_json.get("code", "Unknown")
+    meg = response_data.get("message", response_json)
+    trace_id = response.headers.get("trace-id", "Failed to get trace-id")
+    if response.status_code != 200:
+        raise RuntimeError(
+            f"Doc2x return an error:\nTrace ID: {trace_id} {uid}\n{response.status_code} - {response_json}"
+        )
+    if code in ["parse_page_limit_exceeded", "parse_concurrency_limit"]:
+        raise RuntimeError(
+            f"Reached the limit of Doc2x:\nTrace ID: {trace_id} {uid}\n{code} - {meg}"
+        )
+    if code not in ["ok", "success"]:
+        raise RuntimeError(
+            f"Doc2x return an error:\nTrace ID: {trace_id} {uid}\n{code} - {meg}"
+        )
+    return response_data
 
-def refresh_key(doc2x_api_key):
-    import requests, json
-    url = "https://api.doc2x.noedgeai.com/api/token/refresh"
-    res = requests.post(
-        url,
-        headers={"Authorization": "Bearer " + doc2x_api_key}
-    )
-    res_json = []
-    if res.status_code == 200:
-        decoded = res.content.decode("utf-8")
-        res_json = json.loads(decoded)
-        doc2x_api_key = res_json['data']['token']
-    else:
-        raise RuntimeError(format("[ERROR] status code: %d, body: %s" % (res.status_code, res.text)))
-    return doc2x_api_key
 
 def 解析PDF_DOC2X_转Latex(pdf_file_path):
-    import requests, json, os
-    DOC2X_API_KEY = get_conf('DOC2X_API_KEY')
+    zip_file_path, unzipped_folder = 解析PDF_DOC2X(pdf_file_path, format="tex")
+    return unzipped_folder
+
+
+def 解析PDF_DOC2X(pdf_file_path, format="tex"):
+    """
+    format: 'tex', 'md', 'docx'
+    """
+
+    DOC2X_API_KEY = get_conf("DOC2X_API_KEY")
     latex_dir = get_log_folder(plugin_name="pdf_ocr_latex")
+    markdown_dir = get_log_folder(plugin_name="pdf_ocr")
     doc2x_api_key = DOC2X_API_KEY
-    if doc2x_api_key.startswith('sk-'):
-        url = "https://api.doc2x.noedgeai.com/api/v1/pdf"
-    else:
-        doc2x_api_key = refresh_key(doc2x_api_key)
-        url = "https://api.doc2x.noedgeai.com/api/platform/pdf"
 
-    res = requests.post(
-        url,
-        files={"file": open(pdf_file_path, "rb")},
-        data={"ocr": "1"},
-        headers={"Authorization": "Bearer " + doc2x_api_key}
+    # < ------ 第1步：预上传获取URL，然后上传文件 ------ >
+    logger.info("Doc2x 上传文件：预上传获取URL")
+    res = make_request(
+        "POST",
+        "https://v2.doc2x.noedgeai.com/api/v2/parse/preupload",
+        headers={"Authorization": "Bearer " + doc2x_api_key},
+        timeout=15,
     )
-    res_json = []
-    if res.status_code == 200:
-        decoded = res.content.decode("utf-8")
-        for z_decoded in decoded.split('\n'):
-            if len(z_decoded) == 0: continue
-            assert z_decoded.startswith("data: ")
-            z_decoded = z_decoded[len("data: "):]
-            decoded_json = json.loads(z_decoded)
-            res_json.append(decoded_json)
-    else:
-        raise RuntimeError(format("[ERROR] status code: %d, body: %s" % (res.status_code, res.text)))
+    res_data = doc2x_api_response_status(res)
+    upload_url = res_data["url"]
+    uuid = res_data["uid"]
 
-    uuid = res_json[0]['uuid']
-    to = "latex" # latex, md, docx
-    url = "https://api.doc2x.noedgeai.com/api/export"+"?request_id="+uuid+"&to="+to
+    logger.info("Doc2x 上传文件：上传文件")
+    with open(pdf_file_path, "rb") as file:
+        res = make_request("PUT", upload_url, data=file, timeout=60)
+    res.raise_for_status()
 
-    res = requests.get(url, headers={"Authorization": "Bearer " + doc2x_api_key})
-    latex_zip_path = os.path.join(latex_dir, gen_time_str() + '.zip')
-    latex_unzip_path = os.path.join(latex_dir, gen_time_str())
-    if res.status_code == 200:
-        with open(latex_zip_path, "wb") as f: f.write(res.content)
-    else:
-        raise RuntimeError(format("[ERROR] status code: %d, body: %s" % (res.status_code, res.text)))
-
-    import zipfile
-    with zipfile.ZipFile(latex_zip_path, 'r') as zip_ref:
-        zip_ref.extractall(latex_unzip_path)
-
-
-    return latex_unzip_path
-
-
-
-
-def 解析PDF_DOC2X_单文件(fp, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, DOC2X_API_KEY, user_request):
-
-
-    def pdf2markdown(filepath):
-        import requests, json, os
-        markdown_dir = get_log_folder(plugin_name="pdf_ocr")
-        doc2x_api_key = DOC2X_API_KEY
-        if doc2x_api_key.startswith('sk-'):
-            url = "https://api.doc2x.noedgeai.com/api/v1/pdf"
-        else:
-            doc2x_api_key = refresh_key(doc2x_api_key)
-            url = "https://api.doc2x.noedgeai.com/api/platform/pdf"
-
-        chatbot.append((None, "加载PDF文件，发送至DOC2X解析..."))
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-
-        res = requests.post(
-            url,
-            files={"file": open(filepath, "rb")},
-            data={"ocr": "1"},
-            headers={"Authorization": "Bearer " + doc2x_api_key}
+    # < ------ 第2步：轮询等待 ------ >
+    logger.info("Doc2x 处理文件中：轮询等待")
+    params = {"uid": uuid}
+    max_attempts = 60
+    attempt = 0
+    while attempt < max_attempts:
+        res = make_request(
+            "GET",
+            "https://v2.doc2x.noedgeai.com/api/v2/parse/status",
+            headers={"Authorization": "Bearer " + doc2x_api_key},
+            params=params,
+            timeout=15,
         )
-        res_json = []
-        if res.status_code == 200:
-            decoded = res.content.decode("utf-8")
-            for z_decoded in decoded.split('\n'):
-                if len(z_decoded) == 0: continue
-                assert z_decoded.startswith("data: ")
-                z_decoded = z_decoded[len("data: "):]
-                decoded_json = json.loads(z_decoded)
-                res_json.append(decoded_json)
-            if 'limit exceeded' in decoded_json.get('status', ''):
-                raise RuntimeError("Doc2x API 页数受限，请联系 Doc2x 方面，并更换新的 API 秘钥。")
+        res_data = doc2x_api_response_status(res)
+        if res_data["status"] == "success":
+            break
+        elif res_data["status"] == "processing":
+            time.sleep(5)
+            logger.info(f"Doc2x is processing at {res_data['progress']}%")
+            attempt += 1
         else:
-            raise RuntimeError(format("[ERROR] status code: %d, body: %s" % (res.status_code, res.text)))
-        uuid = res_json[0]['uuid']
-        to = "md" # latex, md, docx
-        url = "https://api.doc2x.noedgeai.com/api/export"+"?request_id="+uuid+"&to="+to
+            raise RuntimeError(f"Doc2x return an error: {res_data}")
+    if attempt >= max_attempts:
+        raise RuntimeError("Doc2x processing timeout after maximum attempts")
 
-        chatbot.append((None, f"读取解析: {url} ..."))
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+    # < ------ 第3步：提交转化 ------ >
+    logger.info("Doc2x 第3步：提交转化")
+    data = {
+        "uid": uuid,
+        "to": format,
+        "formula_mode": "dollar",
+        "filename": "output"
+    }
+    res = make_request(
+        "POST",
+        "https://v2.doc2x.noedgeai.com/api/v2/convert/parse",
+        headers={"Authorization": "Bearer " + doc2x_api_key},
+        json=data,
+        timeout=15,
+    )
+    doc2x_api_response_status(res, uid=f"uid: {uuid}")
+
+    # < ------ 第4步：等待结果 ------ >
+    logger.info("Doc2x 第4步：等待结果")
+    params = {"uid": uuid}
+    max_attempts = 36
+    attempt = 0
+    while attempt < max_attempts:
+        res = make_request(
+            "GET",
+            "https://v2.doc2x.noedgeai.com/api/v2/convert/parse/result",
+            headers={"Authorization": "Bearer " + doc2x_api_key},
+            params=params,
+            timeout=15,
+        )
+        res_data = doc2x_api_response_status(res, uid=f"uid: {uuid}")
+        if res_data["status"] == "success":
+            break
+        elif res_data["status"] == "processing":
+            time.sleep(3)
+            logger.info("Doc2x still processing to convert file")
+            attempt += 1
+    if attempt >= max_attempts:
+        raise RuntimeError("Doc2x conversion timeout after maximum attempts")
+
+    # < ------ 第5步：最后的处理 ------ >
+    logger.info("Doc2x 第5步：下载转换后的文件")
+
+    if format == "tex":
+        target_path = latex_dir
+    if format == "md":
+        target_path = markdown_dir
+    os.makedirs(target_path, exist_ok=True)
+
+    max_attempt = 3
+    # < ------ 下载 ------ >
+    for attempt in range(max_attempt):
+        try:
+            result_url = res_data["url"]
+            res = make_request("GET", result_url, timeout=60)
+            zip_path = os.path.join(target_path, gen_time_str() + ".zip")
+            unzip_path = os.path.join(target_path, gen_time_str())
+            if res.status_code == 200:
+                with open(zip_path, "wb") as f:
+                    f.write(res.content)
+            else:
+                raise RuntimeError(f"Doc2x return an error: {res.json()}")
+        except Exception as e:
+            if attempt < max_attempt - 1:
+                logger.error(f"Failed to download uid = {uuid} file, retrying... {e}")
+                time.sleep(3)
+                continue
+            else:
+                raise e
+
+    # < ------ 解压 ------ >
+    import zipfile
+    with zipfile.ZipFile(zip_path, "r") as zip_ref:
+        zip_ref.extractall(unzip_path)
+    return zip_path, unzip_path
+
+
+def 解析PDF_DOC2X_单文件(
+    fp,
+    project_folder,
+    llm_kwargs,
+    plugin_kwargs,
+    chatbot,
+    history,
+    system_prompt,
+    DOC2X_API_KEY,
+    user_request,
+):
+    def pdf2markdown(filepath):
+        chatbot.append((None, f"Doc2x 解析中"))
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
+        md_zip_path, unzipped_folder = 解析PDF_DOC2X(filepath, format="md")
 
-        res = requests.get(url, headers={"Authorization": "Bearer " + doc2x_api_key})
-        md_zip_path = os.path.join(markdown_dir, gen_time_str() + '.zip')
-        if res.status_code == 200:
-            with open(md_zip_path, "wb") as f: f.write(res.content)
-        else:
-            raise RuntimeError(format("[ERROR] status code: %d, body: %s" % (res.status_code, res.text)))
         promote_file_to_downloadzone(md_zip_path, chatbot=chatbot)
         chatbot.append((None, f"完成解析 {md_zip_path} ..."))
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
         return md_zip_path
 
     def deliver_to_markdown_plugin(md_zip_path, user_request):
@@ -137,77 +239,97 @@ def 解析PDF_DOC2X_单文件(fp, project_folder, llm_kwargs, plugin_kwargs, cha
         os.makedirs(target_path_base, exist_ok=True)
         shutil.copyfile(md_zip_path, this_file_path)
         ex_folder = this_file_path + ".extract"
-        extract_archive(
-            file_path=this_file_path, dest_dir=ex_folder
-        )
+        extract_archive(file_path=this_file_path, dest_dir=ex_folder)
 
         # edit markdown files
-        success, file_manifest, project_folder = get_files_from_everything(ex_folder, type='.md')
+        success, file_manifest, project_folder = get_files_from_everything(
+            ex_folder, type=".md"
+        )
         for generated_fp in file_manifest:
             # 修正一些公式问题
-            with open(generated_fp, 'r', encoding='utf8') as f:
+            with open(generated_fp, "r", encoding="utf8") as f:
                 content = f.read()
             # 将公式中的\[ \]替换成$$
-            content = content.replace(r'\[', r'$$').replace(r'\]', r'$$')
+            content = content.replace(r"\[", r"$$").replace(r"\]", r"$$")
             # 将公式中的\( \)替换成$
-            content = content.replace(r'\(', r'$').replace(r'\)', r'$')
-            content = content.replace('```markdown', '\n').replace('```', '\n')
-            with open(generated_fp, 'w', encoding='utf8') as f:
+            content = content.replace(r"\(", r"$").replace(r"\)", r"$")
+            content = content.replace("```markdown", "\n").replace("```", "\n")
+            with open(generated_fp, "w", encoding="utf8") as f:
                 f.write(content)
             promote_file_to_downloadzone(generated_fp, chatbot=chatbot)
-            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+            yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
 
             # 生成在线预览html
-            file_name = '在线预览翻译（原文）' + gen_time_str() + '.html'
+            file_name = "在线预览翻译（原文）" + gen_time_str() + ".html"
             preview_fp = os.path.join(ex_folder, file_name)
-            from shared_utils.advanced_markdown_format import markdown_convertion_for_file
+            from shared_utils.advanced_markdown_format import (
+                markdown_convertion_for_file,
+            )
+
             with open(generated_fp, "r", encoding="utf-8") as f:
                 md = f.read()
             #     # Markdown中使用不标准的表格，需要在表格前加上一个emoji，以便公式渲染
             #     md = re.sub(r'^<table>', r'.<table>', md, flags=re.MULTILINE)
             html = markdown_convertion_for_file(md)
-            with open(preview_fp, "w", encoding="utf-8") as f: f.write(html)
+            with open(preview_fp, "w", encoding="utf-8") as f:
+                f.write(html)
             chatbot.append([None, f"生成在线预览：{generate_file_link([preview_fp])}"])
             promote_file_to_downloadzone(preview_fp, chatbot=chatbot)
 
-
-
         chatbot.append((None, f"调用Markdown插件 {ex_folder} ..."))
-        plugin_kwargs['markdown_expected_output_dir'] = ex_folder
+        plugin_kwargs["markdown_expected_output_dir"] = ex_folder
 
-        translated_f_name = 'translated_markdown.md'
-        generated_fp = plugin_kwargs['markdown_expected_output_path'] = os.path.join(ex_folder, translated_f_name)
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
-        yield from Markdown英译中(ex_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
+        translated_f_name = "translated_markdown.md"
+        generated_fp = plugin_kwargs["markdown_expected_output_path"] = os.path.join(
+            ex_folder, translated_f_name
+        )
+        yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+        yield from Markdown英译中(
+            ex_folder,
+            llm_kwargs,
+            plugin_kwargs,
+            chatbot,
+            history,
+            system_prompt,
+            user_request,
+        )
         if os.path.exists(generated_fp):
             # 修正一些公式问题
-            with open(generated_fp, 'r', encoding='utf8') as f: content = f.read()
-            content = content.replace('```markdown', '\n').replace('```', '\n')
+            with open(generated_fp, "r", encoding="utf8") as f:
+                content = f.read()
+            content = content.replace("```markdown", "\n").replace("```", "\n")
             # Markdown中使用不标准的表格，需要在表格前加上一个emoji，以便公式渲染
             # content = re.sub(r'^<table>', r'.<table>', content, flags=re.MULTILINE)
-            with open(generated_fp, 'w', encoding='utf8') as f: f.write(content)
+            with open(generated_fp, "w", encoding="utf8") as f:
+                f.write(content)
             # 生成在线预览html
-            file_name = '在线预览翻译' + gen_time_str() + '.html'
+            file_name = "在线预览翻译" + gen_time_str() + ".html"
             preview_fp = os.path.join(ex_folder, file_name)
-            from shared_utils.advanced_markdown_format import markdown_convertion_for_file
+            from shared_utils.advanced_markdown_format import (
+                markdown_convertion_for_file,
+            )
+
             with open(generated_fp, "r", encoding="utf-8") as f:
                 md = f.read()
             html = markdown_convertion_for_file(md)
-            with open(preview_fp, "w", encoding="utf-8") as f: f.write(html)
+            with open(preview_fp, "w", encoding="utf-8") as f:
+                f.write(html)
             promote_file_to_downloadzone(preview_fp, chatbot=chatbot)
             # 生成包含图片的压缩包
             dest_folder = get_log_folder(chatbot.get_user())
-            zip_name = '翻译后的带图文档.zip'
-            zip_folder(source_folder=ex_folder, dest_folder=dest_folder, zip_name=zip_name)
+            zip_name = "翻译后的带图文档.zip"
+            zip_folder(
+                source_folder=ex_folder, dest_folder=dest_folder, zip_name=zip_name
+            )
             zip_fp = os.path.join(dest_folder, zip_name)
             promote_file_to_downloadzone(zip_fp, chatbot=chatbot)
-            yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+            yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
+
     md_zip_path = yield from pdf2markdown(fp)
     yield from deliver_to_markdown_plugin(md_zip_path, user_request)
 
+
 def 解析PDF_基于DOC2X(file_manifest, *args):
     for index, fp in enumerate(file_manifest):
         yield from 解析PDF_DOC2X_单文件(fp, *args)
     return
-
-

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

crazy_functions/rag_fns/llama_index_worker.py

@@ -1,17 +1,13 @@
-import llama_index
-import os
 import atexit
 from loguru import logger
 from typing import List
+
 from llama_index.core import Document
-from llama_index.core.schema import TextNode
-from request_llms.embed_models.openai_embed import OpenAiEmbeddingModel
-from shared_utils.connect_void_terminal import get_chat_default_kwargs
-from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
-from crazy_functions.rag_fns.vector_store_index import GptacVectorStoreIndex
 from llama_index.core.ingestion import run_transformations
-from llama_index.core import PromptTemplate
-from llama_index.core.response_synthesizers import TreeSummarize
+from llama_index.core.schema import TextNode
+
+from crazy_functions.rag_fns.vector_store_index import GptacVectorStoreIndex
+from request_llms.embed_models.openai_embed import OpenAiEmbeddingModel
 
 DEFAULT_QUERY_GENERATION_PROMPT = """\
 Now, you have context information as below:
@@ -63,7 +59,7 @@ class SaveLoad():
     def purge(self):
         import shutil
         shutil.rmtree(self.checkpoint_dir, ignore_errors=True)
-        self.vs_index = self.create_new_vs()
+        self.vs_index = self.create_new_vs(self.checkpoint_dir)
 
 
 class LlamaIndexRagWorker(SaveLoad):
@@ -75,7 +71,7 @@ class LlamaIndexRagWorker(SaveLoad):
         if auto_load_checkpoint:
             self.vs_index = self.load_from_checkpoint(checkpoint_dir)
         else:
-            self.vs_index = self.create_new_vs(checkpoint_dir)
+            self.vs_index = self.create_new_vs()
         atexit.register(lambda: self.save_to_checkpoint(checkpoint_dir))
 
     def assign_embedding_model(self):
@@ -91,40 +87,52 @@ class LlamaIndexRagWorker(SaveLoad):
         logger.info('oo --------inspect_vector_store end--------')
         return vector_store_preview
 
-    def add_documents_to_vector_store(self, document_list):
-        documents = [Document(text=t) for t in document_list]
+    def add_documents_to_vector_store(self, document_list: List[Document]):
+        """
+        Adds a list of Document objects to the vector store after processing.
+        """
+        documents = document_list
         documents_nodes = run_transformations(
-                        documents,  # type: ignore
-                        self.vs_index._transformations,
-                        show_progress=True
-                    )
+            documents,  # type: ignore
+            self.vs_index._transformations,
+            show_progress=True
+        )
         self.vs_index.insert_nodes(documents_nodes)
-        if self.debug_mode: self.inspect_vector_store()
+        if self.debug_mode:
+            self.inspect_vector_store()
 
-    def add_text_to_vector_store(self, text):
+    def add_text_to_vector_store(self, text: str):
         node = TextNode(text=text)
         documents_nodes = run_transformations(
-                        [node],
-                        self.vs_index._transformations,
-                        show_progress=True
-                    )
+            [node],
+            self.vs_index._transformations,
+            show_progress=True
+        )
         self.vs_index.insert_nodes(documents_nodes)
-        if self.debug_mode: self.inspect_vector_store()
+        if self.debug_mode:
+            self.inspect_vector_store()
 
     def remember_qa(self, question, answer):
         formatted_str = QUESTION_ANSWER_RECORD.format(question=question, answer=answer)
         self.add_text_to_vector_store(formatted_str)
 
     def retrieve_from_store_with_query(self, query):
-        if self.debug_mode: self.inspect_vector_store()
+        if self.debug_mode:
+            self.inspect_vector_store()
         retriever = self.vs_index.as_retriever()
         return retriever.retrieve(query)
 
     def build_prompt(self, query, nodes):
         context_str = self.generate_node_array_preview(nodes)
         return DEFAULT_QUERY_GENERATION_PROMPT.format(context_str=context_str, query_str=query)
-        
+
     def generate_node_array_preview(self, nodes):
         buf = "\n".join(([f"(No.{i+1} | score {n.score:.3f}): {n.text}" for i, n in enumerate(nodes)]))
         if self.debug_mode: logger.info(buf)
         return buf
+
+    def purge_vector_store(self):
+        """
+        Purges the current vector store and creates a new one.
+        """
+        self.purge()

crazy_functions/rag_fns/rag_file_support.py

@@ -0,0 +1,22 @@
+import os
+from llama_index.core import SimpleDirectoryReader
+
+supports_format = ['.csv', '.docx', '.epub', '.ipynb',  '.mbox', '.md', '.pdf',  '.txt', '.ppt',
+                   '.pptm', '.pptx']
+
+
+# 修改后的 extract_text 函数，结合 SimpleDirectoryReader 和自定义解析逻辑
+def extract_text(file_path):
+    _, 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])
+            documents = reader.load_data()
+            if len(documents) > 0:
+                return documents[0].text
+        except Exception as e:
+            pass
+
+    return None

crazy_functions/vector_fns/vector_database.py

@@ -60,7 +60,7 @@ def similarity_search_with_score_by_vector(
         self, embedding: List[float], k: int = 4
 ) -> List[Tuple[Document, float]]:
 
-    def seperate_list(ls: List[int]) -> List[List[int]]:
+    def separate_list(ls: List[int]) -> List[List[int]]:
         lists = []
         ls1 = [ls[0]]
         for i in range(1, len(ls)):
@@ -82,7 +82,7 @@ def similarity_search_with_score_by_vector(
             continue
         _id = self.index_to_docstore_id[i]
         doc = self.docstore.search(_id)
-        if not self.chunk_conent:
+        if not self.chunk_content:
             if not isinstance(doc, Document):
                 raise ValueError(f"Could not find document for id {_id}, got {doc}")
             doc.metadata["score"] = int(scores[0][j])
@@ -104,12 +104,12 @@ def similarity_search_with_score_by_vector(
                         id_set.add(l)
             if break_flag:
                 break
-    if not self.chunk_conent:
+    if not self.chunk_content:
         return docs
     if len(id_set) == 0 and self.score_threshold > 0:
         return []
     id_list = sorted(list(id_set))
-    id_lists = seperate_list(id_list)
+    id_lists = separate_list(id_list)
     for id_seq in id_lists:
         for id in id_seq:
             if id == id_seq[0]:
@@ -132,7 +132,7 @@ class LocalDocQA:
     embeddings: object = None
     top_k: int = VECTOR_SEARCH_TOP_K
     chunk_size: int = CHUNK_SIZE
-    chunk_conent: bool = True
+    chunk_content: bool = True
     score_threshold: int = VECTOR_SEARCH_SCORE_THRESHOLD
 
     def init_cfg(self,
@@ -209,16 +209,16 @@ class LocalDocQA:
 
     # query      查询内容
     # vs_path    知识库路径
-    # chunk_conent   是否启用上下文关联
+    # chunk_content   是否启用上下文关联
     # score_threshold    搜索匹配score阈值
     # vector_search_top_k   搜索知识库内容条数，默认搜索5条结果
     # chunk_sizes    匹配单段内容的连接上下文长度
-    def get_knowledge_based_conent_test(self, query, vs_path, chunk_conent,
+    def get_knowledge_based_content_test(self, query, vs_path, chunk_content,
                                         score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
                                         vector_search_top_k=VECTOR_SEARCH_TOP_K, chunk_size=CHUNK_SIZE,
                                         text2vec=None):
         self.vector_store = FAISS.load_local(vs_path, text2vec)
-        self.vector_store.chunk_conent = chunk_conent
+        self.vector_store.chunk_content = chunk_content
         self.vector_store.score_threshold = score_threshold
         self.vector_store.chunk_size = chunk_size
 
@@ -241,7 +241,7 @@ class LocalDocQA:
 
 
 
-def construct_vector_store(vs_id, vs_path, files, sentence_size, history, one_conent, one_content_segmentation, text2vec):
+def construct_vector_store(vs_id, vs_path, files, sentence_size, history, one_content, one_content_segmentation, text2vec):
     for file in files:
         assert os.path.exists(file), "输入文件不存在：" + file
     import nltk
@@ -297,7 +297,7 @@ class knowledge_archive_interface():
             files=file_manifest,
             sentence_size=100,
             history=[],
-            one_conent="",
+            one_content="",
             one_content_segmentation="",
             text2vec = self.get_chinese_text2vec(),
         )
@@ -319,19 +319,19 @@ class knowledge_archive_interface():
                 files=[],
                 sentence_size=100,
                 history=[],
-                one_conent="",
+                one_content="",
                 one_content_segmentation="",
                 text2vec = self.get_chinese_text2vec(),
             )
         VECTOR_SEARCH_SCORE_THRESHOLD = 0
         VECTOR_SEARCH_TOP_K = 4
         CHUNK_SIZE = 512
-        resp, prompt = self.qa_handle.get_knowledge_based_conent_test(
+        resp, prompt = self.qa_handle.get_knowledge_based_content_test(
             query = txt,
             vs_path = self.kai_path,
             score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
             vector_search_top_k=VECTOR_SEARCH_TOP_K,
-            chunk_conent=True,
+            chunk_content=True,
             chunk_size=CHUNK_SIZE,
             text2vec = self.get_chinese_text2vec(),
         )

crazy_functions/vt_fns/vt_call_plugin.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 request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
 import copy, json, pickle, os, sys, time
@@ -9,14 +9,14 @@ import copy, json, pickle, os, sys, time
 def read_avail_plugin_enum():
     from crazy_functional import get_crazy_functions
     plugin_arr = get_crazy_functions()
-    # remove plugins with out explaination
+    # remove plugins with out explanation
     plugin_arr = {k:v for k, v in plugin_arr.items() if ('Info' in v) and ('Function' in v)}
     plugin_arr_info = {"F_{:04d}".format(i):v["Info"] for i, v in enumerate(plugin_arr.values(), start=1)}
     plugin_arr_dict = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
     plugin_arr_dict_parse = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
     plugin_arr_dict_parse.update({f"F_{i}":v for i, v in enumerate(plugin_arr.values(), start=1)})
     prompt = json.dumps(plugin_arr_info, ensure_ascii=False, indent=2)
-    prompt = "\n\nThe defination of PluginEnum:\nPluginEnum=" + prompt
+    prompt = "\n\nThe definition of PluginEnum:\nPluginEnum=" + prompt
     return prompt, plugin_arr_dict, plugin_arr_dict_parse
 
 def wrap_code(txt):
@@ -55,7 +55,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
         plugin_selection: str = Field(description="The most related plugin from one of the PluginEnum.", default="F_0000")
         reason_of_selection: str = Field(description="The reason why you should select this plugin.", default="This plugin satisfy user requirement most")
     # ⭐ ⭐ ⭐ 选择插件
-    yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n查找可用插件中...", chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n查找可用插件中...", chatbot=chatbot, history=history, delay=0)
     gpt_json_io = GptJsonIO(Plugin)
     gpt_json_io.format_instructions = "The format of your output should be a json that can be parsed by json.loads.\n"
     gpt_json_io.format_instructions += """Output example: {"plugin_selection":"F_1234", "reason_of_selection":"F_1234 plugin satisfy user requirement most"}\n"""
@@ -74,13 +74,13 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
         msg += "请求的Prompt为：\n" + wrap_code(get_inputs_show_user(inputs, plugin_arr_enum_prompt))
         msg += "语言模型回复为：\n" + wrap_code(gpt_reply)
         msg += "\n但您可以尝试再试一次\n"
-        yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
+        yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
         return
     if plugin_sel.plugin_selection not in plugin_arr_dict_parse:
         msg = f"抱歉, 找不到合适插件执行该任务, 或者{llm_kwargs['llm_model']}无法理解您的需求。"
         msg += f"语言模型{llm_kwargs['llm_model']}选择了不存在的插件：\n" + wrap_code(gpt_reply)
         msg += "\n但您可以尝试再试一次\n"
-        yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
+        yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
         return
 
     # ⭐ ⭐ ⭐ 确认插件参数
@@ -90,7 +90,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
         appendix_info = get_recent_file_prompt_support(chatbot)
 
     plugin = plugin_arr_dict_parse[plugin_sel.plugin_selection]
-    yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n提取插件参数...", chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n提取插件参数...", chatbot=chatbot, history=history, delay=0)
     class PluginExplicit(BaseModel):
         plugin_selection: str = plugin_sel.plugin_selection
         plugin_arg: str = Field(description="The argument of the plugin.", default="")
@@ -109,6 +109,6 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
     fn = plugin['Function']
     fn_name = fn.__name__
     msg = f'{llm_kwargs["llm_model"]}为您选择了插件: `{fn_name}`\n\n插件说明：{plugin["Info"]}\n\n插件参数：{plugin_sel.plugin_arg}\n\n假如偏离了您的要求，按停止键终止。'
-    yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
+    yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
     yield from fn(plugin_sel.plugin_arg, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, -1)
     return

crazy_functions/vt_fns/vt_modify_config.py

@@ -1,6 +1,6 @@
 from pydantic import BaseModel, Field
 from typing import List
-from toolbox import update_ui_lastest_msg, get_conf
+from toolbox import update_ui_latest_msg, get_conf
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.json_fns.pydantic_io import GptJsonIO
 import copy, json, pickle, os, sys
@@ -9,7 +9,7 @@ import copy, json, pickle, os, sys
 def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
     ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
     if not ALLOW_RESET_CONFIG:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
             chatbot=chatbot, history=history, delay=2
         )
@@ -30,7 +30,7 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
         new_option_value: str = Field(description="the new value of the option", default=None)
 
     # ⭐ ⭐ ⭐ 分析用户意图
-    yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n读取新配置中", chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n读取新配置中", chatbot=chatbot, history=history, delay=0)
     gpt_json_io = GptJsonIO(ModifyConfigurationIntention)
     inputs = "Analyze how to change configuration according to following user input, answer me with json: \n\n" + \
              ">> " + txt.rstrip('\n').replace('\n','\n>> ') + '\n\n' + \
@@ -44,11 +44,11 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
 
     ok = (explicit_conf in txt)
     if ok:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}",
             chatbot=chatbot, history=history, delay=1
         )
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}\n\n正在修改配置中",
             chatbot=chatbot, history=history, delay=2
         )
@@ -57,25 +57,25 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
         from toolbox import set_conf
         set_conf(explicit_conf, user_intention.new_option_value)
 
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n配置修改完成，重新页面即可生效。", chatbot=chatbot, history=history, delay=1
         )
     else:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"失败，如果需要配置{explicit_conf}，您需要明确说明并在指令中提到它。", chatbot=chatbot, history=history, delay=5
         )
 
 def modify_configuration_reboot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
     ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
     if not ALLOW_RESET_CONFIG:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
             chatbot=chatbot, history=history, delay=2
         )
         return
 
     yield from modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention)
-    yield from update_ui_lastest_msg(
+    yield from update_ui_latest_msg(
         lastmsg=f"正在执行任务: {txt}\n\n配置修改完成，五秒后即将重启！若出现报错请无视即可。", chatbot=chatbot, history=history, delay=5
     )
     os.execl(sys.executable, sys.executable, *sys.argv)

crazy_functions/vt_fns/vt_state.py

@@ -5,7 +5,7 @@ class VoidTerminalState():
         self.reset_state()
 
     def reset_state(self):
-        self.has_provided_explaination = False
+        self.has_provided_explanation = False
 
     def lock_plugin(self, chatbot):
         chatbot._cookies['lock_plugin'] = 'crazy_functions.虚空终端->虚空终端'

crazy_functions/互动小游戏.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

crazy_functions/函数动态生成.py

@@ -15,7 +15,7 @@ Testing:
 
 
 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
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
 from crazy_functions.crazy_utils import input_clipping, try_install_deps
 from crazy_functions.gen_fns.gen_fns_shared import is_function_successfully_generated
@@ -27,7 +27,7 @@ import time
 import glob
 import multiprocessing
 
-templete = """
+template = """
 ```python
 import ...  # Put dependencies here, e.g. import numpy as np.
 
@@ -77,10 +77,10 @@ def gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history):
 
     # 第二步
     prompt_compose = [
-        "If previous stage is successful, rewrite the function you have just written to satisfy following templete: \n",
-        templete
+        "If previous stage is successful, rewrite the function you have just written to satisfy following template: \n",
+        template
     ]
-    i_say = "".join(prompt_compose); inputs_show_user = "If previous stage is successful, rewrite the function you have just written to satisfy executable templete. "
+    i_say = "".join(prompt_compose); inputs_show_user = "If previous stage is successful, rewrite the function you have just written to satisfy executable template. "
     gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
         inputs=i_say, inputs_show_user=inputs_show_user,
         llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
@@ -164,18 +164,18 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
     if get_plugin_arg(plugin_kwargs, key="file_path_arg", default=False):
         file_path = get_plugin_arg(plugin_kwargs, key="file_path_arg", default=None)
         file_list.append(file_path)
-        yield from update_ui_lastest_msg(f"当前文件: {file_path}", chatbot, history, 1)
+        yield from update_ui_latest_msg(f"当前文件: {file_path}", chatbot, history, 1)
     elif have_any_recent_upload_files(chatbot):
         file_dir = get_recent_file_prompt_support(chatbot)
         file_list = glob.glob(os.path.join(file_dir, '**/*'), recursive=True)
-        yield from update_ui_lastest_msg(f"当前文件处理列表: {file_list}", chatbot, history, 1)
+        yield from update_ui_latest_msg(f"当前文件处理列表: {file_list}", chatbot, history, 1)
     else:
         chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
-        yield from update_ui_lastest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
+        yield from update_ui_latest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
         return  # 2. 如果没有文件
     if len(file_list) == 0:
         chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
-        yield from update_ui_lastest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
+        yield from update_ui_latest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
         return  # 2. 如果没有文件
 
     # 读取文件
@@ -183,7 +183,7 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
 
     # 粗心检查
     if is_the_upload_folder(txt):
-        yield from update_ui_lastest_msg(f"请在输入框内填写需求, 然后再次点击该插件! 至于您的文件，不用担心, 文件路径 {txt} 已经被记忆. ", chatbot, history, 1)
+        yield from update_ui_latest_msg(f"请在输入框内填写需求, 然后再次点击该插件! 至于您的文件，不用担心, 文件路径 {txt} 已经被记忆. ", chatbot, history, 1)
         return
 
     # 开始干正事
@@ -195,7 +195,7 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
             code, installation_advance, txt, file_type, llm_kwargs, chatbot, history = \
                 yield from gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history)
             chatbot.append(["代码生成阶段结束", ""])
-            yield from update_ui_lastest_msg(f"正在验证上述代码的有效性 ...", chatbot, history, 1)
+            yield from update_ui_latest_msg(f"正在验证上述代码的有效性 ...", chatbot, history, 1)
             # ⭐ 分离代码块
             code = get_code_block(code)
             # ⭐ 检查模块
@@ -206,11 +206,11 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
             if not traceback: traceback = trimmed_format_exc()
         # 处理异常
         if not traceback: traceback = trimmed_format_exc()
-        yield from update_ui_lastest_msg(f"第 {j+1}/{MAX_TRY} 次代码生成尝试, 失败了~ 别担心, 我们5秒后再试一次... \n\n此次我们的错误追踪是\n```\n{traceback}\n```\n", chatbot, history, 5)
+        yield from update_ui_latest_msg(f"第 {j+1}/{MAX_TRY} 次代码生成尝试, 失败了~ 别担心, 我们5秒后再试一次... \n\n此次我们的错误追踪是\n```\n{traceback}\n```\n", chatbot, history, 5)
 
     # 代码生成结束, 开始执行
     TIME_LIMIT = 15
-    yield from update_ui_lastest_msg(f"开始创建新进程并执行代码! 时间限制 {TIME_LIMIT} 秒. 请等待任务完成... ", chatbot, history, 1)
+    yield from update_ui_latest_msg(f"开始创建新进程并执行代码! 时间限制 {TIME_LIMIT} 秒. 请等待任务完成... ", chatbot, history, 1)
     manager = multiprocessing.Manager()
     return_dict = manager.dict()
 

crazy_functions/多智能体.py

@@ -8,7 +8,7 @@
 
 import time
 from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
-from toolbox import get_conf, select_api_key, update_ui_lastest_msg, Singleton
+from toolbox import get_conf, select_api_key, update_ui_latest_msg, Singleton
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
 from crazy_functions.crazy_utils import input_clipping, try_install_deps
 from crazy_functions.agent_fns.persistent import GradioMultiuserManagerForPersistentClasses

crazy_functions/批量翻译PDF文档_NOUGAT.py

@@ -1,5 +1,5 @@
 from toolbox import CatchException, report_exception, get_log_folder, gen_time_str
-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
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency

crazy_functions/数学动画生成manim.py

@@ -166,7 +166,7 @@ class PointWithTrace(Scene):
 
 ```
 
-# do not use get_graph, this funciton is deprecated
+# do not use get_graph, this function is deprecated
 
 class ExampleFunctionGraph(Scene):
     def construct(self):

crazy_functions/生成多种Mermaid图表.py

@@ -324,16 +324,16 @@ def 生成多种Mermaid图表(
     if os.path.exists(txt):  # 如输入区无内容则直接解析历史记录
         from crazy_functions.pdf_fns.parse_word import extract_text_from_files
 
-        file_exist, final_result, page_one, file_manifest, excption = (
+        file_exist, final_result, page_one, file_manifest, exception = (
             extract_text_from_files(txt, chatbot, history)
         )
     else:
         file_exist = False
-        excption = ""
+        exception = ""
         file_manifest = []
 
-    if excption != "":
-        if excption == "word":
+    if exception != "":
+        if exception == "word":
             report_exception(
                 chatbot,
                 history,
@@ -341,7 +341,7 @@ def 生成多种Mermaid图表(
                 b=f"找到了.doc文件，但是该文件格式不被支持，请先转化为.docx格式。",
             )
 
-        elif excption == "pdf":
+        elif exception == "pdf":
             report_exception(
                 chatbot,
                 history,
@@ -349,7 +349,7 @@ def 生成多种Mermaid图表(
                 b=f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pymupdf```。",
             )
 
-        elif excption == "word_pip":
+        elif exception == "word_pip":
             report_exception(
                 chatbot,
                 history,

crazy_functions/知识库问答.py

@@ -1,4 +1,4 @@
-from toolbox import CatchException, update_ui, ProxyNetworkActivate, update_ui_lastest_msg, get_log_folder, get_user
+from toolbox import CatchException, update_ui, ProxyNetworkActivate, update_ui_latest_msg, get_log_folder, get_user
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_files_from_everything
 from loguru import logger
 install_msg ="""
@@ -42,7 +42,7 @@ def 知识库文件注入(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
         yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
         # from crazy_functions.crazy_utils import try_install_deps
         # try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
-        # yield from update_ui_lastest_msg("安装完成，您可以再次重试。", chatbot, history)
+        # yield from update_ui_latest_msg("安装完成，您可以再次重试。", chatbot, history)
         return
 
     # < --------------------读取文件--------------- >
@@ -95,7 +95,7 @@ def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
         yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
         # from crazy_functions.crazy_utils import try_install_deps
         # try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
-        # yield from update_ui_lastest_msg("安装完成，您可以再次重试。", chatbot, history)
+        # yield from update_ui_latest_msg("安装完成，您可以再次重试。", chatbot, history)
         return
 
     # < -------------------  --------------- >

crazy_functions/虚空终端.py

@@ -47,7 +47,7 @@ explain_msg = """
 from pydantic import BaseModel, Field
 from typing import List
 from toolbox import CatchException, update_ui, is_the_upload_folder
-from toolbox import update_ui_lastest_msg, disable_auto_promotion
+from toolbox import update_ui_latest_msg, disable_auto_promotion
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from crazy_functions.crazy_utils import input_clipping
@@ -113,19 +113,19 @@ def 虚空终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
     # 用简单的关键词检测用户意图
     is_certain, _ = analyze_intention_with_simple_rules(txt)
     if is_the_upload_folder(txt):
-        state.set_state(chatbot=chatbot, key='has_provided_explaination', value=False)
+        state.set_state(chatbot=chatbot, key='has_provided_explanation', value=False)
         appendix_msg = "\n\n**很好，您已经上传了文件**，现在请您描述您的需求。"
 
-    if is_certain or (state.has_provided_explaination):
+    if is_certain or (state.has_provided_explanation):
         # 如果意图明确，跳过提示环节
-        state.set_state(chatbot=chatbot, key='has_provided_explaination', value=True)
+        state.set_state(chatbot=chatbot, key='has_provided_explanation', value=True)
         state.unlock_plugin(chatbot=chatbot)
         yield from update_ui(chatbot=chatbot, history=history)
         yield from 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
         return
     else:
         # 如果意图模糊，提示
-        state.set_state(chatbot=chatbot, key='has_provided_explaination', value=True)
+        state.set_state(chatbot=chatbot, key='has_provided_explanation', value=True)
         state.lock_plugin(chatbot=chatbot)
         chatbot.append(("虚空终端状态:", explain_msg+appendix_msg))
         yield from update_ui(chatbot=chatbot, history=history)
@@ -141,7 +141,7 @@ def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
     # ⭐ ⭐ ⭐ 分析用户意图
     is_certain, user_intention = analyze_intention_with_simple_rules(txt)
     if not is_certain:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n分析用户意图中", chatbot=chatbot, history=history, delay=0)
         gpt_json_io = GptJsonIO(UserIntention)
         rf_req = "\nchoose from ['ModifyConfiguration', 'ExecutePlugin', 'Chat']"
@@ -154,13 +154,13 @@ def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
             user_intention = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
             lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
         except JsonStringError as e:
-            yield from update_ui_lastest_msg(
+            yield from update_ui_latest_msg(
                 lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 失败 当前语言模型（{llm_kwargs['llm_model']}）不能理解您的意图", chatbot=chatbot, history=history, delay=0)
             return
     else:
         pass
 
-    yield from update_ui_lastest_msg(
+    yield from update_ui_latest_msg(
         lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
         chatbot=chatbot, history=history, delay=0)
 

crazy_functions/语音助手.py

@@ -42,7 +42,7 @@ class AsyncGptTask():
             MAX_TOKEN_ALLO = 2560
             i_say, history = input_clipping(i_say, history, max_token_limit=MAX_TOKEN_ALLO)
             gpt_say_partial = predict_no_ui_long_connection(inputs=i_say, llm_kwargs=llm_kwargs, history=history, sys_prompt=sys_prompt,
-                                                            observe_window=observe_window[index], console_slience=True)
+                                                            observe_window=observe_window[index], console_silence=True)
         except ConnectionAbortedError as token_exceed_err:
             logger.error('至少一个线程任务Token溢出而失败', e)
         except Exception as e:

crazy_functions/谷歌检索小助手.py

@@ -1,6 +1,6 @@
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from toolbox import CatchException, report_exception, promote_file_to_downloadzone
-from toolbox import update_ui, update_ui_lastest_msg, disable_auto_promotion, write_history_to_file
+from toolbox import update_ui, update_ui_latest_msg, disable_auto_promotion, write_history_to_file
 import logging
 import requests
 import time
@@ -156,7 +156,7 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
     history = []
     meta_paper_info_list = yield from get_meta_information(txt, chatbot, history)
     if len(meta_paper_info_list) == 0:
-        yield from update_ui_lastest_msg(lastmsg='获取文献失败，可能触发了google反爬虫机制。',chatbot=chatbot, history=history, delay=0)
+        yield from update_ui_latest_msg(lastmsg='获取文献失败，可能触发了google反爬虫机制。',chatbot=chatbot, history=history, delay=0)
         return
     batchsize = 5
     for batch in range(math.ceil(len(meta_paper_info_list)/batchsize)):

docker-compose.yml

@@ -180,6 +180,7 @@ version: '3'
 services:
   gpt_academic_with_latex:
     image: ghcr.io/binary-husky/gpt_academic_with_latex:master  # (Auto Built by Dockerfile: docs/GithubAction+NoLocal+Latex)
+    # 对于ARM64设备，请将以上镜像名称替换为 ghcr.io/binary-husky/gpt_academic_with_latex_arm:master
     environment:
       # 请查阅 `config.py` 以查看所有的配置信息
       API_KEY:                  '    sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx                              '

docs/GithubAction+AllCapacity

@@ -5,6 +5,10 @@ FROM fuqingxu/11.3.1-runtime-ubuntu20.04-with-texlive:latest
 
 # edge-tts需要的依赖，某些pip包所需的依赖
 RUN apt update && apt install ffmpeg build-essential -y
+RUN apt-get install -y fontconfig
+RUN ln -s /usr/local/texlive/2023/texmf-dist/fonts/truetype /usr/share/fonts/truetype/texlive
+RUN fc-cache -fv
+RUN apt-get clean
 
 # use python3 as the system default python
 WORKDIR /gpt
@@ -30,7 +34,7 @@ RUN python3 -m pip install -r request_llms/requirements_qwen.txt
 RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
 RUN python3 -m pip install -r request_llms/requirements_newbing.txt
 RUN python3 -m pip install nougat-ocr
-
+RUN python3 -m pip cache purge
 
 # 预热Tiktoken模块
 RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'

docs/GithubAction+ChatGLM+Moss

@@ -7,6 +7,7 @@ RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
 
 # edge-tts需要的依赖，某些pip包所需的依赖
 RUN apt update && apt install ffmpeg build-essential -y
+RUN apt-get clean
 
 # use python3 as the system default python
 RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
@@ -22,6 +23,7 @@ RUN python3 -m pip install -r request_llms/requirements_moss.txt
 RUN python3 -m pip install -r request_llms/requirements_qwen.txt
 RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
 RUN python3 -m pip install -r request_llms/requirements_newbing.txt
+RUN python3 -m pip cache purge
 
 
 # 预热Tiktoken模块

docs/GithubAction+NoLocal

@@ -18,5 +18,7 @@ RUN apt update && apt install ffmpeg -y
 # 可选步骤，用于预热模块
 RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
 
+RUN python3 -m pip cache purge && apt-get clean
+
 # 启动
 CMD ["python3", "-u", "main.py"]

docs/GithubAction+NoLocal+Latex

@@ -1,4 +1,4 @@
-# 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
+# 此Dockerfile适用于"无本地模型"的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
 # - 1 修改 `config.py`
 # - 2 构建 docker build -t gpt-academic-nolocal-latex -f docs/GithubAction+NoLocal+Latex .
 # - 3 运行 docker run -v /home/fuqingxu/arxiv_cache:/root/arxiv_cache --rm -it --net=host gpt-academic-nolocal-latex
@@ -7,15 +7,30 @@ FROM menghuan1918/ubuntu_uv_ctex:latest
 ENV DEBIAN_FRONTEND=noninteractive
 SHELL ["/bin/bash", "-c"]
 WORKDIR /gpt
-COPY . .
-RUN /root/.cargo/bin/uv venv --seed \
-    && source .venv/bin/activate \
-    && /root/.cargo/bin/uv pip install openai numpy arxiv rich colorama Markdown pygments pymupdf python-docx pdfminer \
-    && /root/.cargo/bin/uv pip install -r requirements.txt \
-    && /root/.cargo/bin/uv clean
+
+# 先复制依赖文件
+COPY requirements.txt .
+
+# 安装依赖
+RUN pip install --break-system-packages openai numpy arxiv rich colorama Markdown pygments pymupdf python-docx pdfminer \
+    && pip install --break-system-packages -r requirements.txt \
+    && if [ "$(uname -m)" = "x86_64" ]; then \
+    pip install --break-system-packages nougat-ocr; \
+    fi \
+    && pip cache purge \
+    && rm -rf /root/.cache/pip/*
+
+# 创建非root用户
+RUN useradd -m gptuser && chown -R gptuser /gpt
+USER gptuser
+
+# 最后才复制代码文件,这样代码更新时只需重建最后几层，可以大幅减少docker pull所需的大小
+COPY --chown=gptuser:gptuser . .
 
 # 可选步骤，用于预热模块
-RUN .venv/bin/python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
+RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
+
+RUN python3 -m pip cache purge
 
 # 启动
-CMD [".venv/bin/python3", "-u", "main.py"]
+CMD ["python3", "-u", "main.py"]

docs/GithubAction+NoLocal+Vectordb

@@ -24,6 +24,8 @@ RUN apt update && apt install ffmpeg -y
 
 # 可选步骤，用于预热模块
 RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
+RUN python3 -m pip cache purge && apt-get clean
+
 
 # 启动
 CMD ["python3", "-u", "main.py"]

docs/WindowsRun.bat

@@ -0,0 +1,26 @@
+@echo off
+setlocal
+
+:: 设置环境变量
+set ENV_NAME=gpt
+set ENV_PATH=%~dp0%ENV_NAME%
+set SCRIPT_PATH=%~dp0main.py
+
+:: 判断环境是否已解压
+if not exist "%ENV_PATH%" (
+    echo Extracting environment...
+    mkdir "%ENV_PATH%"
+    tar -xzf gpt.tar.gz -C "%ENV_PATH%"
+    
+    :: 运行conda环境激活脚本
+    call "%ENV_PATH%\Scripts\activate.bat"
+) else (
+    :: 如果环境已存在,直接激活
+    call "%ENV_PATH%\Scripts\activate.bat"
+)
+echo Start to run program:
+:: 运行Python脚本
+python "%SCRIPT_PATH%"
+
+endlocal
+pause

docs/translate_english.json

@@ -1141,7 +1141,7 @@
     "内容太长了都会触发token数量溢出的错误": "An error of token overflow will be triggered if the content is too long",
     "chatbot 为WebUI中显示的对话列表": "chatbot is the conversation list displayed in WebUI",
     "修改它": "Modify it",
-    "然后yeild出去": "Then yield it out",
+    "然后yield出去": "Then yield it out",
     "可以直接修改对话界面内容": "You can directly modify the conversation interface content",
     "additional_fn代表点击的哪个按钮": "additional_fn represents which button is clicked",
     "按钮见functional.py": "See functional.py for buttons",
@@ -1732,7 +1732,7 @@
     "或者重启之后再度尝试": "Or try again after restarting",
     "免费": "Free",
     "仅在Windows系统进行了测试": "Tested only on Windows system",
-    "欢迎加REAME中的QQ联系开发者": "Feel free to contact the developer via QQ in REAME",
+    "欢迎加README中的QQ联系开发者": "Feel free to contact the developer via QQ in README",
     "当前知识库内的有效文件": "Valid files in the current knowledge base",
     "您可以到Github Issue区": "You can go to the Github Issue area",
     "刷新Gradio前端界面": "Refresh the Gradio frontend interface",
@@ -1759,7 +1759,7 @@
     "报错信息如下. 如果是与网络相关的问题": "Error message as follows. If it is related to network issues",
     "功能描述": "Function description",
     "禁止移除或修改此警告": "Removal or modification of this warning is prohibited",
-    "Arixv翻译": "Arixv translation",
+    "ArXiv翻译": "ArXiv translation",
     "读取优先级": "Read priority",
     "包含documentclass关键字": "Contains the documentclass keyword",
     "根据文本使用GPT模型生成相应的图像": "Generate corresponding images using GPT model based on the text",
@@ -1998,7 +1998,7 @@
     "开始最终总结": "Start final summary",
     "openai的官方KEY需要伴随组织编码": "Openai's official KEY needs to be accompanied by organizational code",
     "将子线程的gpt结果写入chatbot": "Write the GPT result of the sub-thread into the chatbot",
-    "Arixv论文精细翻译": "Fine translation of Arixv paper",
+    "ArXiv论文精细翻译": "Fine translation of ArXiv paper",
     "开始接收chatglmft的回复": "Start receiving replies from chatglmft",
     "请先将.doc文档转换为.docx文档": "Please convert .doc documents to .docx documents first",
     "避免多用户干扰": "Avoid multiple user interference",
@@ -2360,7 +2360,7 @@
     "请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件": "Please set ALLOW_RESET_CONFIG=True in config.py and restart the software",
     "按照自然语言描述生成一个动画 | 输入参数是一段话": "Generate an animation based on natural language description | Input parameter is a sentence",
     "你的hf用户名如qingxu98": "Your hf username is qingxu98",
-    "Arixv论文精细翻译 | 输入参数arxiv论文的ID": "Fine translation of Arixv paper | Input parameter is the ID of arxiv paper",
+    "ArXiv论文精细翻译 | 输入参数arxiv论文的ID": "Fine translation of ArXiv paper | Input parameter is the ID of arxiv paper",
     "无法获取 abstract": "Unable to retrieve abstract",
     "尽可能地仅用一行命令解决我的要求": "Try to solve my request using only one command",
     "提取插件参数": "Extract plugin parameters",

docs/translate_japanese.json

@@ -753,7 +753,7 @@
     "手动指定和筛选源代码文件类型": "ソースコードファイルタイプを手動で指定およびフィルタリングする",
     "更多函数插件": "その他の関数プラグイン",
     "看门狗的耐心": "監視犬の忍耐力",
-    "然后yeild出去": "そして出力する",
+    "然后yield出去": "そして出力する",
     "拆分过长的IPynb文件": "長すぎるIPynbファイルを分割する",
     "1. 把input的余量留出来": "1. 入力の余裕を残す",
     "请求超时": "リクエストがタイムアウトしました",
@@ -1803,7 +1803,7 @@
     "默认值为1000": "デフォルト値は1000です",
     "写出文件": "ファイルに書き出す",
     "生成的视频文件路径": "生成されたビデオファイルのパス",
-    "Arixv论文精细翻译": "Arixv論文の詳細な翻訳",
+    "ArXiv论文精细翻译": "ArXiv論文の詳細な翻訳",
     "用latex编译为PDF对修正处做高亮": "LaTeXでコンパイルしてPDFに修正をハイライトする",
     "点击“停止”键可终止程序": "「停止」ボタンをクリックしてプログラムを終了できます",
     "否则将导致每个人的Claude问询历史互相渗透": "さもないと、各人のClaudeの問い合わせ履歴が相互に侵入します",
@@ -1987,7 +1987,7 @@
     "前面是中文逗号": "前面是中文逗号",
     "的依赖": "的依赖",
     "材料如下": "材料如下",
-    "欢迎加REAME中的QQ联系开发者": "欢迎加REAME中的QQ联系开发者",
+    "欢迎加README中的QQ联系开发者": "欢迎加README中的QQ联系开发者",
     "开始下载": "開始ダウンロード",
     "100字以内": "100文字以内",
     "创建request": "リクエストの作成",

docs/translate_traditionalchinese.json

@@ -771,7 +771,7 @@
     "查询代理的地理位置": "查詢代理的地理位置",
     "是否在输入过长时": "是否在輸入過長時",
     "chatGPT分析报告": "chatGPT分析報告",
-    "然后yeild出去": "然後yield出去",
+    "然后yield出去": "然後yield出去",
     "用户取消了程序": "使用者取消了程式",
     "琥珀色": "琥珀色",
     "这里是特殊函数插件的高级参数输入区": "這裡是特殊函數插件的高級參數輸入區",
@@ -1587,7 +1587,7 @@
     "否则将导致每个人的Claude问询历史互相渗透": "否則將導致每個人的Claude問詢歷史互相滲透",
     "提问吧! 但注意": "提問吧！但注意",
     "待处理的word文档路径": "待處理的word文檔路徑",
-    "欢迎加REAME中的QQ联系开发者": "歡迎加REAME中的QQ聯繫開發者",
+    "欢迎加README中的QQ联系开发者": "歡迎加README中的QQ聯繫開發者",
     "建议暂时不要使用": "建議暫時不要使用",
     "Latex没有安装": "Latex沒有安裝",
     "在这里放一些网上搜集的demo": "在這裡放一些網上搜集的demo",
@@ -1989,7 +1989,7 @@
     "请耐心等待": "請耐心等待",
     "在执行完成之后": "在執行完成之後",
     "参数简单": "參數簡單",
-    "Arixv论文精细翻译": "Arixv論文精細翻譯",
+    "ArXiv论文精细翻译": "ArXiv論文精細翻譯",
     "备份和下载": "備份和下載",
     "当前报错的latex代码处于第": "當前報錯的latex代碼處於第",
     "Markdown翻译": "Markdown翻譯",

main.py

@@ -1,4 +1,4 @@
-import os, json; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
+import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
 
 help_menu_description = \
 """Github源代码开源和更新[地址🚀](https://github.com/binary-husky/gpt_academic),
@@ -34,9 +34,9 @@ def encode_plugin_info(k, plugin)->str:
 
 def main():
     import gradio as gr
-    if gr.__version__ not in ['3.32.9', '3.32.10', '3.32.11']:
+    if gr.__version__ not in ['3.32.15']:
         raise ModuleNotFoundError("使用项目内置Gradio获取最优体验! 请运行 `pip install -r requirements.txt` 指令安装内置Gradio及其他依赖, 详情信息见requirements.txt.")
-    
+
     # 一些基础工具
     from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith
 
@@ -49,7 +49,7 @@ def main():
     # 读取配置
     proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION = get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION')
     CHATBOT_HEIGHT, LAYOUT, AVAIL_LLM_MODELS, AUTO_CLEAR_TXT = get_conf('CHATBOT_HEIGHT', 'LAYOUT', 'AVAIL_LLM_MODELS', 'AUTO_CLEAR_TXT')
-    ENABLE_AUDIO, AUTO_CLEAR_TXT, PATH_LOGGING, AVAIL_THEMES, THEME, ADD_WAIFU = get_conf('ENABLE_AUDIO', 'AUTO_CLEAR_TXT', 'PATH_LOGGING', 'AVAIL_THEMES', 'THEME', 'ADD_WAIFU')
+    ENABLE_AUDIO, AUTO_CLEAR_TXT, AVAIL_FONTS, AVAIL_THEMES, THEME, ADD_WAIFU = get_conf('ENABLE_AUDIO', 'AUTO_CLEAR_TXT', 'AVAIL_FONTS', 'AVAIL_THEMES', 'THEME', 'ADD_WAIFU')
     NUM_CUSTOM_BASIC_BTN, SSL_KEYFILE, SSL_CERTFILE = get_conf('NUM_CUSTOM_BASIC_BTN', 'SSL_KEYFILE', 'SSL_CERTFILE')
     DARK_MODE, INIT_SYS_PROMPT, ADD_WAIFU, TTS_TYPE = get_conf('DARK_MODE', 'INIT_SYS_PROMPT', 'ADD_WAIFU', 'TTS_TYPE')
     if LLM_MODEL not in AVAIL_LLM_MODELS: AVAIL_LLM_MODELS += [LLM_MODEL]
@@ -57,8 +57,8 @@ def main():
     # 如果WEB_PORT是-1, 则随机选取WEB端口
     PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
     from check_proxy import get_current_version
-    from themes.theme import adjust_theme, advanced_css, theme_declaration, js_code_clear, js_code_reset, js_code_show_or_hide, js_code_show_or_hide_group2
-    from themes.theme import js_code_for_toggle_darkmode, js_code_for_persistent_cookie_init
+    from themes.theme import adjust_theme, advanced_css, theme_declaration, js_code_clear, js_code_show_or_hide
+    from themes.theme import js_code_for_toggle_darkmode
     from themes.theme import load_dynamic_theme, to_cookie_str, from_cookie_str, assign_user_uuid
     title_html = f"<h1 align=\"center\">GPT 学术优化 {get_current_version()}</h1>{theme_declaration}"
 
@@ -68,7 +68,7 @@ def main():
     functional = get_core_functions()
 
     # 高级函数插件
-    from crazy_functional import get_crazy_functions
+    from crazy_functional import get_crazy_functions, get_multiplex_button_functions
     DEFAULT_FN_GROUPS = get_conf('DEFAULT_FN_GROUPS')
     plugins = get_crazy_functions()
     all_plugin_groups = list(set([g for _, plugin in plugins.items() for g in plugin['Group'].split('|')]))
@@ -106,7 +106,7 @@ def main():
             with gr_L2(scale=2, elem_id="gpt-chat"):
                 chatbot = gr.Chatbot(label=f"当前模型：{LLM_MODEL}", elem_id="gpt-chatbot")
                 if LAYOUT == "TOP-DOWN":  chatbot.style(height=CHATBOT_HEIGHT)
-                history, history_cache, history_cache_update = make_history_cache() # 定义 后端state（history）、前端（history_cache）、后端setter（history_cache_update）三兄弟
+                history, _, _ = make_history_cache() # 定义 后端state（history）、前端（history_cache）、后端setter（history_cache_update）三兄弟
             with gr_L2(scale=1, elem_id="gpt-panel"):
                 with gr.Accordion("输入区", open=True, elem_id="input-panel") as area_input_primary:
                     with gr.Row():
@@ -114,12 +114,7 @@ def main():
                     with gr.Row(elem_id="gpt-submit-row"):
                         multiplex_submit_btn = gr.Button("提交", elem_id="elem_submit_visible", variant="primary")
                         multiplex_sel = gr.Dropdown(
-                            choices=[
-                                "常规对话", 
-                                "多模型对话", 
-                                "智能召回 RAG",
-                                # "智能上下文", 
-                            ], value="常规对话",
+                            choices=get_multiplex_button_functions().keys(), value="常规对话",
                             interactive=True, label='', show_label=False,
                             elem_classes='normal_mut_select', elem_id="gpt-submit-dropdown").style(container=False)
                         submit_btn = gr.Button("提交", elem_id="elem_submit", variant="primary", visible=False)
@@ -179,16 +174,20 @@ def main():
                         with gr.Accordion("点击展开“文件下载区”。", open=False) as area_file_up:
                             file_upload = gr.Files(label="任何文件, 推荐上传压缩文件(zip, tar)", file_count="multiple", elem_id="elem_upload")
 
+
         # 左上角工具栏定义
         from themes.gui_toolbar import define_gui_toolbar
         checkboxes, checkboxes_2, max_length_sl, theme_dropdown, system_prompt, file_upload_2, md_dropdown, top_p, temperature = \
-            define_gui_toolbar(AVAIL_LLM_MODELS, LLM_MODEL, INIT_SYS_PROMPT, THEME, AVAIL_THEMES, ADD_WAIFU, help_menu_description, js_code_for_toggle_darkmode)
+            define_gui_toolbar(AVAIL_LLM_MODELS, LLM_MODEL, INIT_SYS_PROMPT, THEME, AVAIL_THEMES, AVAIL_FONTS, ADD_WAIFU, help_menu_description, js_code_for_toggle_darkmode)
 
         # 浮动菜单定义
         from themes.gui_floating_menu import define_gui_floating_menu
         area_input_secondary, txt2, area_customize, _, resetBtn2, clearBtn2, stopBtn2 = \
             define_gui_floating_menu(customize_btns, functional, predefined_btns, cookies, web_cookie_cache)
 
+        # 浮动时间线定义
+        gr.Spark()
+
         # 插件二级菜单的实现
         from themes.gui_advanced_plugin_class import define_gui_advanced_plugin_class
         new_plugin_callback, route_switchy_bt_with_arg, usr_confirmed_arg = \
@@ -211,14 +210,14 @@ def main():
             ret.update({area_customize: gr.update(visible=("自定义菜单" in a))})
             return ret
         checkboxes_2.select(fn_area_visibility_2, [checkboxes_2], [area_customize] )
-        checkboxes_2.select(None, [checkboxes_2], None, _js=js_code_show_or_hide_group2)
+        checkboxes_2.select(None, [checkboxes_2], None, _js="""apply_checkbox_change_for_group2""")
 
         # 整理反复出现的控件句柄组合
         input_combo = [cookies, max_length_sl, md_dropdown, txt, txt2, top_p, temperature, chatbot, history, system_prompt, plugin_advanced_arg]
         input_combo_order = ["cookies", "max_length_sl", "md_dropdown", "txt", "txt2", "top_p", "temperature", "chatbot", "history", "system_prompt", "plugin_advanced_arg"]
         output_combo = [cookies, chatbot, history, status]
         predict_args = dict(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True)], outputs=output_combo)
-        
+
         # 提交按钮、重置按钮
         multiplex_submit_btn.click(
             None, [multiplex_sel], None, _js="""(multiplex_sel)=>multiplex_function_begin(multiplex_sel)""")
@@ -227,11 +226,8 @@ def main():
         multiplex_sel.select(
             None, [multiplex_sel], None, _js=f"""(multiplex_sel)=>run_multiplex_shift(multiplex_sel)""")
         cancel_handles.append(submit_btn.click(**predict_args))
-        resetBtn.click(None, None, [chatbot, history, status], _js=js_code_reset)   # 先在前端快速清除chatbot&status
-        resetBtn2.click(None, None, [chatbot, history, status], _js=js_code_reset)  # 先在前端快速清除chatbot&status
-        reset_server_side_args = (lambda history: ([], [], "已重置", json.dumps(history)), [history], [chatbot, history, status, history_cache])
-        resetBtn.click(*reset_server_side_args)    # 再在后端清除history，把history转存history_cache备用
-        resetBtn2.click(*reset_server_side_args)   # 再在后端清除history，把history转存history_cache备用
+        resetBtn.click(None, None, [chatbot, history, status], _js= """clear_conversation""")   # 先在前端快速清除chatbot&status
+        resetBtn2.click(None, None, [chatbot, history, status], _js="""clear_conversation""")  # 先在前端快速清除chatbot&status
         clearBtn.click(None, None, [txt, txt2], _js=js_code_clear)
         clearBtn2.click(None, None, [txt, txt2], _js=js_code_clear)
         if AUTO_CLEAR_TXT:
@@ -331,7 +327,7 @@ def main():
         from shared_utils.cookie_manager import load_web_cookie_cache__fn_builder
         load_web_cookie_cache = load_web_cookie_cache__fn_builder(customize_btns, cookies, predefined_btns)
         app_block.load(load_web_cookie_cache, inputs = [web_cookie_cache, cookies],
-            outputs = [web_cookie_cache, cookies, *customize_btns.values(), *predefined_btns.values()], _js=js_code_for_persistent_cookie_init)
+            outputs = [web_cookie_cache, cookies, *customize_btns.values(), *predefined_btns.values()], _js="""persistent_cookie_init""")
         app_block.load(None, inputs=[], outputs=None, _js=f"""()=>GptAcademicJavaScriptInit("{DARK_MODE}","{INIT_SYS_PROMPT}","{ADD_WAIFU}","{LAYOUT}","{TTS_TYPE}")""")    # 配置暗色主题或亮色主题
         app_block.load(None, inputs=[], outputs=None, _js="""()=>{REP}""".replace("REP", register_advanced_plugin_init_arr))
 

request_llms/bridge_all.py

@@ -1,4 +1,3 @@
-
 """
     该文件中主要包含2个函数，是所有LLM的通用接口，它们会继续向下调用更底层的LLM模型，处理多模型并行等细节
 
@@ -26,6 +25,9 @@ from .bridge_chatglm import predict as chatglm_ui
 from .bridge_chatglm3 import predict_no_ui_long_connection as chatglm3_noui
 from .bridge_chatglm3 import predict as chatglm3_ui
 
+from .bridge_chatglm4 import predict_no_ui_long_connection as chatglm4_noui
+from .bridge_chatglm4 import predict as chatglm4_ui
+
 from .bridge_qianfan import predict_no_ui_long_connection as qianfan_noui
 from .bridge_qianfan import predict as qianfan_ui
 
@@ -76,6 +78,8 @@ cohere_endpoint = "https://api.cohere.ai/v1/chat"
 ollama_endpoint = "http://localhost:11434/api/chat"
 yimodel_endpoint = "https://api.lingyiwanwu.com/v1/chat/completions"
 deepseekapi_endpoint = "https://api.deepseek.com/v1/chat/completions"
+grok_model_endpoint = "https://api.x.ai/v1/chat/completions"
+volcengine_endpoint = "https://ark.cn-beijing.volces.com/api/v3/chat/completions"
 
 if not AZURE_ENDPOINT.endswith('/'): AZURE_ENDPOINT += '/'
 azure_endpoint = AZURE_ENDPOINT + f'openai/deployments/{AZURE_ENGINE}/chat/completions?api-version=2023-05-15'
@@ -97,6 +101,8 @@ if cohere_endpoint in API_URL_REDIRECT: cohere_endpoint = API_URL_REDIRECT[coher
 if ollama_endpoint in API_URL_REDIRECT: ollama_endpoint = API_URL_REDIRECT[ollama_endpoint]
 if yimodel_endpoint in API_URL_REDIRECT: yimodel_endpoint = API_URL_REDIRECT[yimodel_endpoint]
 if deepseekapi_endpoint in API_URL_REDIRECT: deepseekapi_endpoint = API_URL_REDIRECT[deepseekapi_endpoint]
+if grok_model_endpoint in API_URL_REDIRECT: grok_model_endpoint = API_URL_REDIRECT[grok_model_endpoint]
+if volcengine_endpoint in API_URL_REDIRECT: volcengine_endpoint = API_URL_REDIRECT[volcengine_endpoint]
 
 # 获取tokenizer
 tokenizer_gpt35 = LazyloadTiktoken("gpt-3.5-turbo")
@@ -108,6 +114,12 @@ get_token_num_gpt4 = lambda txt: len(tokenizer_gpt4.encode(txt, disallowed_speci
 # 开始初始化模型
 AVAIL_LLM_MODELS, LLM_MODEL = get_conf("AVAIL_LLM_MODELS", "LLM_MODEL")
 AVAIL_LLM_MODELS = AVAIL_LLM_MODELS + [LLM_MODEL]
+
+# 获取中转渠道配置
+ZHONGZHUAN_ENABLE, ZHONGZHUAN_ENDPOINT, ZHONGZHUAN_API_KEY, ZHONGZHUAN_MODELS = get_conf(
+    "ZHONGZHUAN_ENABLE", "ZHONGZHUAN_ENDPOINT", "ZHONGZHUAN_API_KEY", "ZHONGZHUAN_MODELS"
+)
+
 # -=-=-=-=-=-=- 以下这部分是最早加入的最稳定的模型 -=-=-=-=-=-=-
 model_info = {
     # openai
@@ -212,6 +224,16 @@ model_info = {
         "token_cnt": get_token_num_gpt4,
     },
 
+    "chatgpt-4o-latest": {
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "endpoint": openai_endpoint,
+        "has_multimodal_capacity": True,
+        "max_token": 128000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+    },
+
     "gpt-4o-2024-05-13": {
         "fn_with_ui": chatgpt_ui,
         "fn_without_ui": chatgpt_noui,
@@ -258,16 +280,88 @@ model_info = {
         "token_cnt": get_token_num_gpt4,
         "openai_disable_system_prompt": True,
         "openai_disable_stream": True,
+        "openai_force_temperature_one": True,
     },
+
     "o1-mini": {
         "fn_with_ui": chatgpt_ui,
         "fn_without_ui": chatgpt_noui,
         "endpoint": openai_endpoint,
+        "can_multi_thread": True,
         "max_token": 128000,
         "tokenizer": tokenizer_gpt4,
         "token_cnt": get_token_num_gpt4,
         "openai_disable_system_prompt": True,
         "openai_disable_stream": True,
+        "openai_force_temperature_one": True,
+    },
+
+    "o1-2024-12-17": {
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "endpoint": openai_endpoint,
+        "max_token": 200000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+        "openai_disable_system_prompt": True,
+        "openai_disable_stream": True,
+        "openai_force_temperature_one": True,
+    },
+
+    "o1": {
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "endpoint": openai_endpoint,
+        "max_token": 200000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+        "openai_disable_system_prompt": True,
+        "openai_disable_stream": True,
+        "openai_force_temperature_one": True,
+    },
+
+    "gpt-4.1":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+    },
+
+    "gpt-4.1-mini":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+    },
+
+    "o3":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+        "openai_disable_system_prompt": True,
+        "openai_disable_stream": True,
+        "openai_force_temperature_one": True,
+    },
+
+    "o4-mini":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "can_multi_thread": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
     },
 
     "gpt-4-turbo": {
@@ -385,6 +479,14 @@ model_info = {
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
+    "glm-4-plus":{
+        "fn_with_ui": zhipu_ui,
+        "fn_without_ui": zhipu_noui,
+        "endpoint": None,
+        "max_token": 10124 * 8,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
 
     # api_2d (此后不需要在此处添加api2d的接口了，因为下面的代码会自动添加)
     "api2d-gpt-4": {
@@ -396,6 +498,7 @@ model_info = {
         "token_cnt": get_token_num_gpt4,
     },
 
+    # ChatGLM本地模型
     # 将 chatglm 直接对齐到 chatglm2
     "chatglm": {
         "fn_with_ui": chatglm_ui,
@@ -421,6 +524,14 @@ model_info = {
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
+    "chatglm4": {
+        "fn_with_ui": chatglm4_ui,
+        "fn_without_ui": chatglm4_noui,
+        "endpoint": None,
+        "max_token": 8192,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
     "qianfan": {
         "fn_with_ui": qianfan_ui,
         "fn_without_ui": qianfan_noui,
@@ -469,6 +580,15 @@ model_info = {
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
+    "gemini-2.0-flash": {
+        "fn_with_ui": genai_ui,
+        "fn_without_ui": genai_noui,
+        "endpoint": gemini_endpoint,
+        "has_multimodal_capacity": True,
+        "max_token": 1024 * 204800,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
 
     # cohere
     "cohere-command-r-plus": {
@@ -752,8 +872,13 @@ if "qwen-local" in AVAIL_LLM_MODELS:
         })
     except:
         logger.error(trimmed_format_exc())
-# -=-=-=-=-=-=- 通义-在线模型 -=-=-=-=-=-=-
-if "qwen-turbo" in AVAIL_LLM_MODELS or "qwen-plus" in AVAIL_LLM_MODELS or "qwen-max" in AVAIL_LLM_MODELS:   # zhipuai
+
+# -=-=-=-=-=-=- 阿里云百炼（通义）-在线模型 -=-=-=-=-=-=-
+qwen_models = ["qwen-max-latest", "qwen-max-2025-01-25","qwen-max","qwen-turbo","qwen-plus",
+               "dashscope-deepseek-r1","dashscope-deepseek-v3",
+               "dashscope-qwen3-14b", "dashscope-qwen3-235b-a22b", "dashscope-qwen3-qwen3-32b",
+               ]
+if any(item in qwen_models for item in AVAIL_LLM_MODELS):
     try:
         from .bridge_qwen import predict_no_ui_long_connection as qwen_noui
         from .bridge_qwen import predict as qwen_ui
@@ -763,7 +888,7 @@ if "qwen-turbo" in AVAIL_LLM_MODELS or "qwen-plus" in AVAIL_LLM_MODELS or "qwen-
                 "fn_without_ui": qwen_noui,
                 "can_multi_thread": True,
                 "endpoint": None,
-                "max_token": 6144,
+                "max_token": 100000,
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
             },
@@ -772,7 +897,7 @@ if "qwen-turbo" in AVAIL_LLM_MODELS or "qwen-plus" in AVAIL_LLM_MODELS or "qwen-
                 "fn_without_ui": qwen_noui,
                 "can_multi_thread": True,
                 "endpoint": None,
-                "max_token": 30720,
+                "max_token": 129024,
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
             },
@@ -781,13 +906,79 @@ if "qwen-turbo" in AVAIL_LLM_MODELS or "qwen-plus" in AVAIL_LLM_MODELS or "qwen-
                 "fn_without_ui": qwen_noui,
                 "can_multi_thread": True,
                 "endpoint": None,
-                "max_token": 28672,
+                "max_token": 30720,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "qwen-max-latest": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 30720,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "qwen-max-2025-01-25": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 30720,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-deepseek-r1": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "enable_reasoning": True,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 57344,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-deepseek-v3": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 57344,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-qwen3-14b": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "enable_reasoning": True,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 129024,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-qwen3-235b-a22b": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 129024,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-qwen3-32b": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 129024,
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
             }
         })
     except:
         logger.error(trimmed_format_exc())
+
 # -=-=-=-=-=-=- 零一万物模型 -=-=-=-=-=-=-
 yi_models = ["yi-34b-chat-0205","yi-34b-chat-200k","yi-large","yi-medium","yi-spark","yi-large-turbo","yi-large-preview"]
 if any(item in yi_models for item in AVAIL_LLM_MODELS):
@@ -868,6 +1059,31 @@ if any(item in yi_models for item in AVAIL_LLM_MODELS):
         })
     except:
         logger.error(trimmed_format_exc())
+
+
+# -=-=-=-=-=-=- Grok model from x.ai -=-=-=-=-=-=-
+grok_models = ["grok-beta"]
+if any(item in grok_models for item in AVAIL_LLM_MODELS):
+    try:
+        grok_beta_128k_noui, grok_beta_128k_ui = get_predict_function(
+            api_key_conf_name="GROK_API_KEY", max_output_token=8192, disable_proxy=False
+        )
+        
+        model_info.update({
+            "grok-beta": {
+                "fn_with_ui": grok_beta_128k_ui,
+                "fn_without_ui": grok_beta_128k_noui,
+                "can_multi_thread": True,  
+                "endpoint": grok_model_endpoint,
+                "max_token": 128000,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            
+        })
+    except:
+        logger.error(trimmed_format_exc())
+
 # -=-=-=-=-=-=- 讯飞星火认知大模型 -=-=-=-=-=-=-
 if "spark" in AVAIL_LLM_MODELS:
     try:
@@ -969,7 +1185,7 @@ if "zhipuai" in AVAIL_LLM_MODELS:   # zhipuai 是glm-4的别名，向后兼容
         })
     except:
         logger.error(trimmed_format_exc())
-# -=-=-=-=-=-=- 幻方-深度求索大模型 -=-=-=-=-=-=-
+# -=-=-=-=-=-=- 幻方-深度求索本地大模型 -=-=-=-=-=-=-
 if "deepseekcoder" in AVAIL_LLM_MODELS:   # deepseekcoder
     try:
         from .bridge_deepseekcoder import predict_no_ui_long_connection as deepseekcoder_noui
@@ -986,19 +1202,21 @@ if "deepseekcoder" in AVAIL_LLM_MODELS:   # deepseekcoder
         })
     except:
         logger.error(trimmed_format_exc())
+
 # -=-=-=-=-=-=- 幻方-深度求索大模型在线API -=-=-=-=-=-=-
-if "deepseek-chat" in AVAIL_LLM_MODELS or "deepseek-coder" in AVAIL_LLM_MODELS:
+claude_models = ["deepseek-chat", "deepseek-coder", "deepseek-reasoner"]
+if any(item in claude_models for item in AVAIL_LLM_MODELS):
     try:
         deepseekapi_noui, deepseekapi_ui = get_predict_function(
             api_key_conf_name="DEEPSEEK_API_KEY", max_output_token=4096, disable_proxy=False
-            )
+        )
         model_info.update({
             "deepseek-chat":{
                 "fn_with_ui": deepseekapi_ui,
                 "fn_without_ui": deepseekapi_noui,
                 "endpoint": deepseekapi_endpoint,
                 "can_multi_thread": True,
-                "max_token": 32000,
+                "max_token": 64000,
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
             },
@@ -1011,9 +1229,73 @@ if "deepseek-chat" in AVAIL_LLM_MODELS or "deepseek-coder" in AVAIL_LLM_MODELS:
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
             },
+            "deepseek-reasoner":{
+                "fn_with_ui": deepseekapi_ui,
+                "fn_without_ui": deepseekapi_noui,
+                "endpoint": deepseekapi_endpoint,
+                "can_multi_thread": True,
+                "max_token": 64000,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+                "enable_reasoning": True
+            },
         })
     except:
         logger.error(trimmed_format_exc())
+
+# -=-=-=-=-=-=- 火山引擎 对齐支持 -=-=-=-=-=-=-
+for model in [m for m in AVAIL_LLM_MODELS if m.startswith("volcengine-")]:
+    # 为了更灵活地接入volcengine多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["volcengine-deepseek-r1-250120(max_token=6666)"]
+    # 其中
+    #   "volcengine-"          是前缀（必要）
+    #   "deepseek-r1-250120"   是模型名（必要）
+    #   "(max_token=6666)"     是配置（非必要）
+    model_info_extend = model_info
+    model_info_extend.update({
+        "deepseek-r1-250120": {
+            "max_token": 16384,
+            "enable_reasoning": True,
+            "can_multi_thread": True,
+            "endpoint": volcengine_endpoint,
+            "tokenizer": tokenizer_gpt35,
+            "token_cnt": get_token_num_gpt35,
+        },
+        "deepseek-v3-241226": {
+            "max_token": 16384,
+            "enable_reasoning": False,
+            "can_multi_thread": True,
+            "endpoint": volcengine_endpoint,
+            "tokenizer": tokenizer_gpt35,
+            "token_cnt": get_token_num_gpt35,
+        },
+    })
+    try:
+        origin_model_name, max_token_tmp = read_one_api_model_name(model)
+        # 如果是已知模型，则尝试获取其信息
+        original_model_info = model_info_extend.get(origin_model_name.replace("volcengine-", "", 1), None)
+    except:
+        logger.error(f"volcengine模型 {model} 的 max_token 配置不是整数，请检查配置文件。")
+        continue
+
+    volcengine_noui, volcengine_ui = get_predict_function(api_key_conf_name="ARK_API_KEY", max_output_token=8192, disable_proxy=True, model_remove_prefix = ["volcengine-"])
+
+    this_model_info = {
+        "fn_with_ui": volcengine_ui,
+        "fn_without_ui": volcengine_noui,
+        "endpoint": volcengine_endpoint,
+        "can_multi_thread": True,
+        "max_token": 64000,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    }
+
+    # 同步已知模型的其他信息
+    attribute = "has_multimodal_capacity"
+    if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
+    attribute = "enable_reasoning"
+    if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
+    model_info.update({model: this_model_info})
+
 # -=-=-=-=-=-=- one-api 对齐支持 -=-=-=-=-=-=-
 for model in [m for m in AVAIL_LLM_MODELS if m.startswith("one-api-")]:
     # 为了更灵活地接入one-api多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["one-api-mixtral-8x7b(max_token=6666)"]
@@ -1138,6 +1420,23 @@ for model in [m for m in AVAIL_LLM_MODELS if m.startswith("openrouter-")]:
         },
     })
 
+# -=-=-=-=-=-=- 中转渠道模型对齐支持 -=-=-=-=-=-=-
+# 为中转渠道模型创建统一的model_info配置
+if ZHONGZHUAN_ENABLE and ZHONGZHUAN_MODELS:
+    # 为每个中转渠道模型创建统一的model_info配置
+    # 注意：模型列表的合并已在config.py中处理
+    for model in ZHONGZHUAN_MODELS:
+        model_info.update({
+            model: {
+                "fn_with_ui": chatgpt_ui,
+                "fn_without_ui": chatgpt_noui,
+                "endpoint": ZHONGZHUAN_ENDPOINT,
+                "has_multimodal_capacity": True,
+                "max_token": 12800000,
+                "tokenizer": tokenizer_gpt4,
+                "token_cnt": get_token_num_gpt4,
+            }
+        })
 
 # -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
 # -=-=-=-=-=-=-=-=-=- ☝️ 以上是模型路由 -=-=-=-=-=-=-=-=-=
@@ -1152,9 +1451,9 @@ def LLM_CATCH_EXCEPTION(f):
     """
     装饰器函数，将错误显示出来
     """
-    def decorated(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list, console_slience:bool):
+    def decorated(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list, console_silence:bool):
         try:
-            return f(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
+            return f(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence)
         except Exception as e:
             tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
             observe_window[0] = tb_str
@@ -1162,7 +1461,7 @@ def LLM_CATCH_EXCEPTION(f):
     return decorated
 
 
-def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list=[], console_slience:bool=False):
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list=[], console_silence:bool=False):
     """
     发送至LLM，等待回复，一次性完成，不显示中间过程。但内部（尽可能地）用stream的方法避免中途网线被掐。
     inputs：
@@ -1182,11 +1481,11 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys
     model = llm_kwargs['llm_model']
     n_model = 1
     if '&' not in model:
-        # 如果只询问“一个”大语言模型（多数情况）：
+        # 如果只询问"一个"大语言模型（多数情况）：
         method = model_info[model]["fn_without_ui"]
-        return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
+        return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence)
     else:
-        # 如果同时询问“多个”大语言模型，这个稍微啰嗦一点，但思路相同，您不必读这个else分支
+        # 如果同时询问"多个"大语言模型，这个稍微啰嗦一点，但思路相同，您不必读这个else分支
         executor = ThreadPoolExecutor(max_workers=4)
         models = model.split('&')
         n_model = len(models)
@@ -1201,7 +1500,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys
             method = model_info[model]["fn_without_ui"]
             llm_kwargs_feedin = copy.deepcopy(llm_kwargs)
             llm_kwargs_feedin['llm_model'] = model
-            future = executor.submit(LLM_CATCH_EXCEPTION(method), inputs, llm_kwargs_feedin, history, sys_prompt, window_mutex[i], console_slience)
+            future = executor.submit(LLM_CATCH_EXCEPTION(method), inputs, llm_kwargs_feedin, history, sys_prompt, window_mutex[i], console_silence)
             futures.append(future)
 
         def mutex_manager(window_mutex, observe_window):
@@ -1278,6 +1577,11 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot,
 
     inputs = apply_gpt_academic_string_mask(inputs, mode="show_llm")
 
+    if llm_kwargs['llm_model'] not in model_info:
+        from toolbox import update_ui
+        chatbot.append([inputs, f"很抱歉，模型 '{llm_kwargs['llm_model']}' 暂不支持<br/>(1) 检查config中的AVAIL_LLM_MODELS选项<br/>(2) 检查request_llms/bridge_all.py中的模型路由"])
+        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+
     method = model_info[llm_kwargs['llm_model']]["fn_with_ui"]  # 如果这里报错，检查config中的AVAIL_LLM_MODELS选项
 
     if additional_fn: # 根据基础功能区 ModelOverride 参数调整模型类型
@@ -1285,4 +1589,3 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot,
 
     # 更新一下llm_kwargs的参数，否则会出现参数不匹配的问题
     yield from method(inputs, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, stream, additional_fn)
-

request_llms/bridge_chatglm3.py

@@ -23,39 +23,33 @@ class GetGLM3Handle(LocalLLMHandle):
         import os
         import platform
 
-        LOCAL_MODEL_QUANT, device = get_conf("LOCAL_MODEL_QUANT", "LOCAL_MODEL_DEVICE")
-        _model_name_ = "THUDM/chatglm3-6b"
-        # if LOCAL_MODEL_QUANT == "INT4":  # INT4
-        #     _model_name_ = "THUDM/chatglm3-6b-int4"
-        # elif LOCAL_MODEL_QUANT == "INT8":  # INT8
-        #     _model_name_ = "THUDM/chatglm3-6b-int8"
-        # else:
-        #     _model_name_ = "THUDM/chatglm3-6b"  # FP16
+        LOCAL_MODEL_PATH, LOCAL_MODEL_QUANT, device = get_conf("CHATGLM_LOCAL_MODEL_PATH", "LOCAL_MODEL_QUANT", "LOCAL_MODEL_DEVICE")
+        model_path = LOCAL_MODEL_PATH
         with ProxyNetworkActivate("Download_LLM"):
             chatglm_tokenizer = AutoTokenizer.from_pretrained(
-                _model_name_, trust_remote_code=True
+                model_path, trust_remote_code=True
             )
             if device == "cpu":
                 chatglm_model = AutoModel.from_pretrained(
-                    _model_name_,
+                    model_path,
                     trust_remote_code=True,
                     device="cpu",
                 ).float()
             elif LOCAL_MODEL_QUANT == "INT4":  # INT4
                 chatglm_model = AutoModel.from_pretrained(
-                    pretrained_model_name_or_path=_model_name_,
+                    pretrained_model_name_or_path=model_path,
                     trust_remote_code=True,
                     quantization_config=BitsAndBytesConfig(load_in_4bit=True),
                 )
             elif LOCAL_MODEL_QUANT == "INT8":  # INT8
                 chatglm_model = AutoModel.from_pretrained(
-                    pretrained_model_name_or_path=_model_name_,
+                    pretrained_model_name_or_path=model_path,
                     trust_remote_code=True,
                     quantization_config=BitsAndBytesConfig(load_in_8bit=True),
                 )
             else:
                 chatglm_model = AutoModel.from_pretrained(
-                    pretrained_model_name_or_path=_model_name_,
+                    pretrained_model_name_or_path=model_path,
                     trust_remote_code=True,
                     device="cuda",
                 )

request_llms/bridge_chatglm4.py

@@ -0,0 +1,81 @@
+model_name = "ChatGLM4"
+cmd_to_install = """
+`pip install -r request_llms/requirements_chatglm4.txt`
+`pip install modelscope`
+`modelscope download --model ZhipuAI/glm-4-9b-chat --local_dir ./THUDM/glm-4-9b-chat`
+"""
+
+
+from toolbox import get_conf, ProxyNetworkActivate
+from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
+
+
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 Local Model
+# ------------------------------------------------------------------------------------------------------------------------
+class GetGLM4Handle(LocalLLMHandle):
+
+    def load_model_info(self):
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
+        self.model_name = model_name
+        self.cmd_to_install = cmd_to_install
+
+    def load_model_and_tokenizer(self):
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
+        import torch
+        from transformers import AutoModel, AutoModelForCausalLM, AutoTokenizer
+        import os
+
+        LOCAL_MODEL_PATH, device = get_conf("CHATGLM_LOCAL_MODEL_PATH", "LOCAL_MODEL_DEVICE")
+        model_path = LOCAL_MODEL_PATH
+        chatglm_tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
+        chatglm_model = AutoModelForCausalLM.from_pretrained(
+            model_path,
+            torch_dtype=torch.bfloat16,
+            low_cpu_mem_usage=True,
+            trust_remote_code=True,
+            device=device
+        ).eval().to(device)
+        self._model = chatglm_model
+        self._tokenizer = chatglm_tokenizer
+        return self._model, self._tokenizer
+
+
+    def llm_stream_generator(self, **kwargs):
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
+        def adaptor(kwargs):
+            query = kwargs["query"]
+            max_length = kwargs["max_length"]
+            top_p = kwargs["top_p"]
+            temperature = kwargs["temperature"]
+            history = kwargs["history"]
+            return query, max_length, top_p, temperature, history
+
+        query, max_length, top_p, temperature, history = adaptor(kwargs)
+        inputs = self._tokenizer.apply_chat_template([{"role": "user", "content": query}],
+                                       add_generation_prompt=True,
+                                       tokenize=True,
+                                       return_tensors="pt",
+                                       return_dict=True
+                                       ).to(self._model.device)
+        gen_kwargs = {"max_length": max_length, "do_sample": True, "top_k": top_p}
+
+        outputs = self._model.generate(**inputs, **gen_kwargs)
+        outputs = outputs[:, inputs['input_ids'].shape[1]:]
+        response = self._tokenizer.decode(outputs[0], skip_special_tokens=True)
+        yield response
+
+    def try_to_import_special_deps(self, **kwargs):
+        # import something that will raise error if the user does not install requirement_*.txt
+        # 🏃‍♂️🏃‍♂️🏃‍♂️ 主进程执行
+        import importlib
+
+        # importlib.import_module('modelscope')
+
+
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 GPT-Academic Interface
+# ------------------------------------------------------------------------------------------------------------------------
+predict_no_ui_long_connection, predict = get_local_llm_predict_fns(
+    GetGLM4Handle, model_name, history_format="chatglm3"
+)

request_llms/bridge_chatglmft.py

@@ -139,7 +139,7 @@ global glmft_handle
 glmft_handle = None
 #################################################################################
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         多线程方法
         函数的说明请见 request_llms/bridge_all.py

request_llms/bridge_chatgpt.py

@@ -23,8 +23,13 @@ from loguru import logger
 from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history
 from toolbox import trimmed_format_exc, is_the_upload_folder, read_one_api_model_name, log_chat
 from toolbox import ChatBotWithCookies, have_any_recent_upload_image_files, encode_image
-proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG, AZURE_CFG_ARRAY = \
-    get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'API_ORG', 'AZURE_CFG_ARRAY')
+proxies, WHEN_TO_USE_PROXY, TIMEOUT_SECONDS, MAX_RETRY, API_ORG, AZURE_CFG_ARRAY = \
+    get_conf('proxies', 'WHEN_TO_USE_PROXY', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'API_ORG', 'AZURE_CFG_ARRAY')
+
+if "Connect_OpenAI" not in WHEN_TO_USE_PROXY:
+    if proxies is not None:
+        logger.error("虽然您配置了代理设置，但不会在连接OpenAI的过程中起作用，请检查WHEN_TO_USE_PROXY配置。")
+        proxies = None
 
 timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
                   '网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。'
@@ -120,7 +125,7 @@ def verify_endpoint(endpoint):
         raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
     return endpoint
 
-def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_slience:bool=False):
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_silence:bool=False):
     """
     发送至chatGPT，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免中途网线被掐。
     inputs：
@@ -180,19 +185,25 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
                 raise ConnectionAbortedError("正常结束，但显示Token不足，导致输出不完整，请削减单次输入的文本量。")
             else:
                 raise RuntimeError("OpenAI拒绝了请求：" + error_msg)
-        if ('data: [DONE]' in chunk_decoded): break # api2d 正常完成
+        if ('data: [DONE]' in chunk_decoded): break # api2d & one-api 正常完成
         # 提前读取一些信息 （用于判断异常）
         if has_choices and not choice_valid:
             # 一些垃圾第三方接口的出现这样的错误
             continue
         json_data = chunkjson['choices'][0]
         delta = json_data["delta"]
-        if len(delta) == 0: break
+
+        if len(delta) == 0:
+            is_termination_certain = False
+            if (has_choices) and (chunkjson['choices'][0].get('finish_reason', 'null') == 'stop'): is_termination_certain = True
+            if is_termination_certain: break
+            else: continue # 对于不符合规范的狗屎接口，这里需要继续
+
         if (not has_content) and has_role: continue
         if (not has_content) and (not has_role): continue # raise RuntimeError("发现不标准的第三方接口："+delta)
         if has_content: # has_role = True/False
             result += delta["content"]
-            if not console_slience: print(delta["content"], end='')
+            if not console_silence: print(delta["content"], end='')
             if observe_window is not None:
                 # 观测窗，把已经获取的数据显示出去
                 if len(observe_window) >= 1:
@@ -202,10 +213,13 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
                     if (time.time()-observe_window[1]) > watch_dog_patience:
                         raise RuntimeError("用户取消了程序。")
         else: raise RuntimeError("意外Json结构："+delta)
-    if json_data and json_data['finish_reason'] == 'content_filter':
-        raise RuntimeError("由于提问含不合规内容被Azure过滤。")
-    if json_data and json_data['finish_reason'] == 'length':
+
+    finish_reason = json_data.get('finish_reason', None) if json_data else None
+    if finish_reason == 'content_filter':
+        raise RuntimeError("由于提问含不合规内容被过滤。")
+    if finish_reason == 'length':
         raise ConnectionAbortedError("正常结束，但显示Token不足，导致输出不完整，请削减单次输入的文本量。")
+
     return result
 
 
@@ -217,7 +231,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
     inputs 是本次问询的输入
     top_p, temperature是chatGPT的内部调优参数
     history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+    chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
     additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     from request_llms.bridge_all import model_info
@@ -227,9 +241,19 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
         yield from update_ui(chatbot=chatbot, history=history, msg="api_key已导入") # 刷新界面
         return
     elif not is_any_api_key(chatbot._cookies['api_key']):
-        chatbot.append((inputs, "缺少api_key。\n\n1. 临时解决方案：直接在输入区键入api_key，然后回车提交。\n\n2. 长效解决方案：在config.py中配置。"))
-        yield from update_ui(chatbot=chatbot, history=history, msg="缺少api_key") # 刷新界面
-        return
+        # 对于中转渠道模型，额外检查中转渠道API key
+        is_zhongzhuan_valid = False
+        try:
+            ZHONGZHUAN_ENABLE, ZHONGZHUAN_MODELS, ZHONGZHUAN_API_KEY = get_conf("ZHONGZHUAN_ENABLE", "ZHONGZHUAN_MODELS", "ZHONGZHUAN_API_KEY")
+            if ZHONGZHUAN_ENABLE and llm_kwargs['llm_model'] in ZHONGZHUAN_MODELS and ZHONGZHUAN_API_KEY:
+                is_zhongzhuan_valid = is_any_api_key(ZHONGZHUAN_API_KEY)
+        except Exception:
+            pass
+        
+        if not is_zhongzhuan_valid:
+            chatbot.append((inputs, "缺少api_key。\n\n1. 临时解决方案：直接在输入区键入api_key，然后回车提交。\n\n2. 长效解决方案：在config.py中配置。"))
+            yield from update_ui(chatbot=chatbot, history=history, msg="缺少api_key") # 刷新界面
+            return
 
     user_input = inputs
     if additional_fn is not None:
@@ -255,12 +279,22 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
 
     # check mis-behavior
     if is_the_upload_folder(user_input):
-        chatbot[-1] = (inputs, f"[Local Message] 检测到操作错误！当您上传文档之后，需点击“**函数插件区**”按钮进行处理，请勿点击“提交”按钮或者“基础功能区”按钮。")
+        chatbot[-1] = (inputs, f"[Local Message] 检测到操作错误！当您上传文档之后，需点击\"**函数插件区**\"按钮进行处理，请勿点击\"提交\"按钮或者\"基础功能区\"按钮。")
         yield from update_ui(chatbot=chatbot, history=history, msg="正常") # 刷新界面
         time.sleep(2)
 
     try:
-        headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt, image_base64_array, has_multimodal_capacity, stream)
+        # 对于中转渠道模型，需要确保使用正确的API key
+        llm_kwargs_modified = llm_kwargs.copy()
+        try:
+            ZHONGZHUAN_ENABLE, ZHONGZHUAN_MODELS, ZHONGZHUAN_API_KEY = get_conf("ZHONGZHUAN_ENABLE", "ZHONGZHUAN_MODELS", "ZHONGZHUAN_API_KEY")
+            if ZHONGZHUAN_ENABLE and llm_kwargs['llm_model'] in ZHONGZHUAN_MODELS and ZHONGZHUAN_API_KEY:
+                # 确保中转渠道模型使用正确的API key
+                llm_kwargs_modified['api_key'] = ZHONGZHUAN_API_KEY
+        except Exception:
+            pass
+        
+        headers, payload = generate_payload(inputs, llm_kwargs_modified, history, system_prompt, image_base64_array, has_multimodal_capacity, stream)
     except RuntimeError as e:
         chatbot[-1] = (inputs, f"您提供的api-key不满足要求，不包含任何可用于{llm_kwargs['llm_model']}的api-key。您可能选择了错误的模型或请求源。")
         yield from update_ui(chatbot=chatbot, history=history, msg="api-key不满足要求") # 刷新界面
@@ -282,6 +316,8 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
         history.extend([inputs, ""])
 
     retry = 0
+    previous_ui_reflesh_time = 0
+    ui_reflesh_min_interval = 0.0
     while True:
         try:
             # make a POST request to the API endpoint, stream=True
@@ -294,13 +330,13 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
             yield from update_ui(chatbot=chatbot, history=history, msg="请求超时"+retry_msg) # 刷新界面
             if retry > MAX_RETRY: raise TimeoutError
 
-
     if not stream:
         # 该分支仅适用于不支持stream的o1模型，其他情形一律不适用
         yield from handle_o1_model_special(response, inputs, llm_kwargs, chatbot, history)
         return
 
     if stream:
+        reach_termination = False   # 处理一些 new-api 的奇葩异常
         gpt_replying_buffer = ""
         is_head_of_the_stream = True
         stream_response =  response.iter_lines()
@@ -313,11 +349,14 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                 error_msg = chunk_decoded
                 # 首先排除一个one-api没有done数据包的第三方Bug情形
                 if len(gpt_replying_buffer.strip()) > 0 and len(error_msg) == 0:
-                    yield from update_ui(chatbot=chatbot, history=history, msg="检测到有缺陷的非OpenAI官方接口，建议选择更稳定的接口。")
+                    yield from update_ui(chatbot=chatbot, history=history, msg="检测到有缺陷的接口，建议选择更稳定的接口。")
+                    if not reach_termination:
+                        reach_termination = True
+                        log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
                     break
                 # 其他情况，直接返回报错
                 chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg)
-                yield from update_ui(chatbot=chatbot, history=history, msg="非OpenAI官方接口返回了错误:" + chunk.decode()) # 刷新界面
+                yield from update_ui(chatbot=chatbot, history=history, msg="接口返回了错误:" + chunk.decode()) # 刷新界面
                 return
 
             # 提前读取一些信息 （用于判断异常）
@@ -327,6 +366,8 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                 # 数据流的第一帧不携带content
                 is_head_of_the_stream = False; continue
 
+            if "error" in chunk_decoded: logger.error(f"接口返回了未知错误: {chunk_decoded}")
+
             if chunk:
                 try:
                     if has_choices and not choice_valid:
@@ -335,14 +376,25 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                     if ('data: [DONE]' not in chunk_decoded) and len(chunk_decoded) > 0 and (chunkjson is None):
                         # 传递进来一些奇怪的东西
                         raise ValueError(f'无法读取以下数据，请检查配置。\n\n{chunk_decoded}')
-                    # 前者是API2D的结束条件，后者是OPENAI的结束条件
-                    if ('data: [DONE]' in chunk_decoded) or (len(chunkjson['choices'][0]["delta"]) == 0):
-                        # 判定为数据流的结束，gpt_replying_buffer也写完了
-                        log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
-                        break
+                    # 前者是API2D & One-API的结束条件，后者是OPENAI的结束条件
+                    one_api_terminate = ('data: [DONE]' in chunk_decoded)
+                    openai_terminate = (has_choices) and (len(chunkjson['choices'][0]["delta"]) == 0)
+                    if one_api_terminate or openai_terminate:
+                        is_termination_certain = False
+                        if one_api_terminate: is_termination_certain = True # 抓取符合规范的结束条件
+                        elif (has_choices) and (chunkjson['choices'][0].get('finish_reason', 'null') == 'stop'): is_termination_certain = True # 抓取符合规范的结束条件
+                        if is_termination_certain:
+                            reach_termination = True
+                            log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
+                            break # 对于符合规范的接口，这里可以break
+                        else:
+                            continue # 对于不符合规范的接口，这里需要继续
+                    # 到这里，我们已经可以假定必须包含choice了
+                    try:
+                        status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
+                    except:
+                        logger.error(f"一些第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
                     # 处理数据流的主体
-                    status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
-                    # 如果这里抛出异常，一般是文本过长，详情见get_full_error的输出
                     if has_content:
                         # 正常情况
                         gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
@@ -350,22 +402,27 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                         # 一些第三方接口的出现这样的错误，兼容一下吧
                         continue
                     else:
-                        # 至此已经超出了正常接口应该进入的范围，一些垃圾第三方接口会出现这样的错误
-                        if chunkjson['choices'][0]["delta"]["content"] is None: continue # 一些垃圾第三方接口出现这样的错误，兼容一下吧
+                        # 至此已经超出了正常接口应该进入的范围，一些第三方接口会出现这样的错误
+                        if chunkjson['choices'][0]["delta"].get("content", None) is None:
+                            logger.error(f"一些第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
+                            continue
                         gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
 
                     history[-1] = gpt_replying_buffer
                     chatbot[-1] = (history[-2], history[-1])
-                    yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
+                    if time.time() - previous_ui_reflesh_time > ui_reflesh_min_interval:
+                        yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
+                        previous_ui_reflesh_time = time.time()
                 except Exception as e:
                     yield from update_ui(chatbot=chatbot, history=history, msg="Json解析不合常规") # 刷新界面
                     chunk = get_full_error(chunk, stream_response)
                     chunk_decoded = chunk.decode()
                     error_msg = chunk_decoded
                     chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg)
-                    yield from update_ui(chatbot=chatbot, history=history, msg="Json解析异常" + error_msg) # 刷新界面
                     logger.error(error_msg)
+                    yield from update_ui(chatbot=chatbot, history=history, msg="Json解析异常" + error_msg) # 刷新界面
                     return
+        yield from update_ui(chatbot=chatbot, history=history, msg="完成") # 刷新界面
         return  # return from stream-branch
 
 def handle_o1_model_special(response, inputs, llm_kwargs, chatbot, history):
@@ -533,7 +590,8 @@ def generate_payload(inputs:str, llm_kwargs:dict, history:list, system_prompt:st
         "n": 1,
         "stream": stream,
     }
-
+    openai_force_temperature_one = model_info[llm_kwargs['llm_model']].get('openai_force_temperature_one', False)
+    if openai_force_temperature_one:
+        payload.pop('temperature')
     return headers,payload
 
-

request_llms/bridge_chatgpt_vision.py

@@ -16,7 +16,7 @@ import base64
 import glob
 from loguru import logger
 from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc, is_the_upload_folder, \
-    update_ui_lastest_msg, get_max_token, encode_image, have_any_recent_upload_image_files, log_chat
+    update_ui_latest_msg, get_max_token, encode_image, have_any_recent_upload_image_files, log_chat
 
 
 proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG, AZURE_CFG_ARRAY = \
@@ -67,7 +67,7 @@ def verify_endpoint(endpoint):
     """
     return endpoint
 
-def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_silence=False):
     raise NotImplementedError
 
 
@@ -183,7 +183,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
                     if ('data: [DONE]' in chunk_decoded) or (len(chunkjson['choices'][0]["delta"]) == 0):
                         # 判定为数据流的结束，gpt_replying_buffer也写完了
                         lastmsg = chatbot[-1][-1] + f"\n\n\n\n「{llm_kwargs['llm_model']}调用结束，该模型不具备上下文对话能力，如需追问，请及时切换模型。」"
-                        yield from update_ui_lastest_msg(lastmsg, chatbot, history, delay=1)
+                        yield from update_ui_latest_msg(lastmsg, chatbot, history, delay=1)
                         log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
                         break
                     # 处理数据流的主体

request_llms/bridge_claude.py

@@ -69,7 +69,7 @@ def decode_chunk(chunk):
     return need_to_pass, chunkjson, is_last_chunk
 
 
-def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_silence=False):
     """
     发送至chatGPT，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免中途网线被掐。
     inputs：
@@ -151,7 +151,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     inputs 是本次问询的输入
     top_p, temperature是chatGPT的内部调优参数
     history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+    chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
     additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     if inputs == "":     inputs = "空空如也的输入栏"

request_llms/bridge_cohere.py

@@ -68,7 +68,7 @@ def verify_endpoint(endpoint):
         raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
     return endpoint
 
-def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_slience:bool=False):
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_silence:bool=False):
     """
     发送，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免中途网线被掐。
     inputs：
@@ -111,7 +111,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
         if chunkjson['event_type'] == 'stream-start': continue
         if chunkjson['event_type'] == 'text-generation':
             result += chunkjson["text"]
-            if not console_slience: print(chunkjson["text"], end='')
+            if not console_silence: print(chunkjson["text"], end='')
             if observe_window is not None:
                 # 观测窗，把已经获取的数据显示出去
                 if len(observe_window) >= 1:
@@ -132,7 +132,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
     inputs 是本次问询的输入
     top_p, temperature是chatGPT的内部调优参数
     history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+    chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
     additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     # if is_any_api_key(inputs):