optimize welcome page

* ✨ feat(request_llms and config.py): ChatGLM4 Deployment

Add support for local deployment of ChatGLM4 model

* 🦄 refactor(bridge_chatglm3.py): ChatGLM3 model path

Added ChatGLM3 path customization (in config.py).
Removed useless quantization model options that have been annotated

---------

Co-authored-by: MarkDeia <17290550+MarkDeia@users.noreply.github.com>

.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

.gitignore

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

README.md

@@ -1,4 +1,7 @@
 > [!IMPORTANT]
+> `frontier开发分支`最新动态(2024.12.9): 更新对话时间线功能，优化xelatex论文翻译  
+> `wiki文档`最新动态(2024.12.5): 更新ollama接入指南  
+>
 > 2024.10.10: 突发停电，紧急恢复了提供[whl包](https://drive.google.com/file/d/19U_hsLoMrjOlQSzYS3pzWX9fTzyusArP/view?usp=sharing)的文件服务器  
 > 2024.10.8: 版本3.90加入对llama-index的初步支持，版本3.80加入插件二级菜单功能（详见wiki）  
 > 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)  
@@ -170,26 +173,32 @@ 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

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

@@ -36,7 +36,7 @@ AVAIL_LLM_MODELS = ["gpt-4-1106-preview", "gpt-4-turbo-preview", "gpt-4-vision-p
                     "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"
                     ]
 
 EMBEDDING_MODEL = "text-embedding-3-small"
@@ -55,6 +55,7 @@ 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，
@@ -142,6 +143,9 @@ 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"
 
@@ -234,7 +238,6 @@ MOONSHOT_API_KEY = ""
 # 零一万物(Yi Model) API KEY
 YIMODEL_API_KEY = ""
 
-
 # 深度求索(DeepSeek) API KEY，默认请求地址为"https://api.deepseek.com/v1/chat/completions"
 DEEPSEEK_API_KEY = ""
 
@@ -242,6 +245,8 @@ DEEPSEEK_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 +278,8 @@ 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
@@ -310,6 +315,10 @@ 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) ]
+
+
 
 """
 --------------- 配置关联关系说明 ---------------
@@ -369,6 +378,7 @@ NUM_CUSTOM_BASIC_BTN = 4
 
 本地大模型示意图
 │
+├── "chatglm4"
 ├── "chatglm3"
 ├── "chatglm"
 ├── "chatglm_onnx"
@@ -399,7 +409,7 @@ 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

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",
@@ -718,12 +727,6 @@ 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 +741,6 @@ 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 +760,23 @@ 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":
+            "",
+
+        "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/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_lastest_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
@@ -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
 
@@ -192,6 +193,38 @@ def scrape_text(url, proxies) -> str:
     text = "\n".join(chunk for chunk in chunks if chunk)
     return text
 
+def internet_search_with_analysis_prompt(prompt, analysis_prompt, llm_kwargs, chatbot):
+    from toolbox import get_conf
+    proxies = get_conf('proxies')
+    categories = 'general'
+    searxng_url = None  # 使用默认的searxng_url
+    engines = None  # 使用默认的搜索引擎
+    yield from update_ui_lastest_msg(lastmsg=f"检索中: {prompt} ...", chatbot=chatbot, history=[], delay=1)
+    urls = searxng_request(prompt, proxies, categories, searxng_url, engines=engines)
+    yield from update_ui_lastest_msg(lastmsg=f"依次访问搜索到的网站 ...", chatbot=chatbot, history=[], delay=1)
+    if len(urls) == 0:
+        return None
+    max_search_result = 5   # 最多收纳多少个网页的结果
+    history = []
+    for index, url in enumerate(urls[:max_search_result]):
+        yield from update_ui_lastest_msg(lastmsg=f"依次访问搜索到的网站: {url['link']} ...", chatbot=chatbot, history=[], delay=1)
+        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_slience=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):

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
@@ -30,7 +33,7 @@ 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

crazy_functions/Latex_Function.py

@@ -3,7 +3,7 @@ from toolbox import CatchException, report_exception, update_ui_lastest_msg, zip
 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")
@@ -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_lastest_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_lastest_msg(f"开始下载 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        success = fix_url_and_download()
+        yield from update_ui_lastest_msg(f"下载完成 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+
+
+    if not success:
+        yield from update_ui_lastest_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
 
 
@@ -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
@@ -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:
@@ -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)
 
@@ -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()
 

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

@@ -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":

crazy_functions/Rag_Interface.py

@@ -1,4 +1,11 @@
+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_lastest_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_lastest_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_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
         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_lastest_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_lastest_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_lastest_msg(model_say, chatbot, history, delay=0, msg=tip)

crazy_functions/SourceCode_Comment.py

@@ -6,7 +6,10 @@ from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_ver
 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" + 
+            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_lastest_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_lastest_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_lastest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
+    chatbot.append((None, f"即将下载视频。"))
+
+    # pause a while
+    tic_time = 16
+    for i in range(tic_time):
+        yield from update_ui_lastest_msg(
+            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_lastest_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_lastest_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_lastest_msg(lastmsg=f"互联网检索结论: {result} \n\n 正在生成进一步检索方案 ...", chatbot=chatbot, history=[], delay=1)
+        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 reseach 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
+    candadate_dictionary: dict =  get_video_resource(video_engine_keywords)
+    candadate_dictionary_as_str = json.dumps(candadate_dictionary, ensure_ascii=False, indent=4)
+
+    # 展示候选资源
+    candadate_display = "\n".join([f"{i+1}. {it['title']}" for i, it in enumerate(candadate_dictionary)])
+    chatbot.append((None, f"候选:\n\n{candadate_display}"))
+    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:
+        {candadate_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/python_comment_agent.py

@@ -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_funtion_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_funtion_prompt_chinese
+        else:
+            self.core_prompt = revise_funtion_prompt
         self.path = None
         self.file_basename = None
         self.file_brief = ""
@@ -258,7 +321,7 @@ class PythonCodeComment():
         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, 
@@ -348,6 +411,7 @@ class PythonCodeComment():
             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)
                 next_batch, line_no_start, line_no_end = self.get_next_batch()
+                self.observe_window_update(f"正在处理{self.file_basename} - {line_no_start}/{len(self.full_context)}\n")
                 # yield from update_ui_lastest_msg(f"({self.file_basename}) 处理代码片段:\n\n{next_batch}", chatbot=chatbot, history=history, delay=0)
                 
                 hint = None

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

@@ -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

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_lastest_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
@@ -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'))
 
@@ -351,6 +352,41 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
     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
+    # 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
@@ -361,10 +397,10 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
 
         # 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)
+        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)
+        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
@@ -375,10 +411,10 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
                 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)
+            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
@@ -386,10 +422,10 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
                 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)
+                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_ = ""
@@ -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

@@ -712,134 +712,137 @@ def _merge_pdfs_ng(pdf1_path, pdf2_path, output_path):
                                     # 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:
-                                    if dest in pdf2_reader.named_destinations:
-                                        # 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]
-                                        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],
+                                    # 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
-                                            }
-                                        )
+                                            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]
+                                            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:
-
-                                        # 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
-                                            )
-                                        )
-                                        # 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],
+                                    # 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

crazy_functions/media_fns/get_media.py

@@ -0,0 +1,43 @@
+from toolbox import update_ui, get_conf, promote_file_to_downloadzone, update_ui_lastest_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_lastest_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/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/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

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+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 +7,28 @@ 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()'
 
 # 启动
-CMD [".venv/bin/python3", "-u", "main.py"]
+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

main.py

@@ -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 ['3.32.12']:
         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
 
@@ -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, js_code_show_or_hide_group2
+    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)
@@ -179,6 +174,7 @@ 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 = \
@@ -188,6 +184,9 @@ def main():
         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
@@ -227,11 +226,11 @@ 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="""(a,b,c)=>clear_conversation(a,b,c)""")   # 先在前端快速清除chatbot&status
+        resetBtn2.click(None, None, [chatbot, history, status], _js="""(a,b,c)=>clear_conversation(a,b,c)""")  # 先在前端快速清除chatbot&status
+        # reset_server_side_args = (lambda history: ([], [], "已重置"), [history], [chatbot, history, status])
+        # resetBtn.click(*reset_server_side_args)    # 再在后端清除history
+        # resetBtn2.click(*reset_server_side_args)   # 再在后端清除history
         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 +330,7 @@ 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

@@ -26,6 +26,9 @@ 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 +79,7 @@ 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"
 
 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 +101,7 @@ 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]
 
 # 获取tokenizer
 tokenizer_gpt35 = LazyloadTiktoken("gpt-3.5-turbo")
@@ -212,6 +217,16 @@ 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,
@@ -385,6 +400,14 @@ 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 +419,7 @@ 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 +445,14 @@ 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,
@@ -868,6 +900,31 @@ 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:
@@ -1285,4 +1342,3 @@ 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_chatgpt.py

@@ -202,10 +202,13 @@ 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
 
 
@@ -536,4 +539,3 @@ def generate_payload(inputs:str, llm_kwargs:dict, history:list, system_prompt:st
 
     return headers,payload
 
-

request_llms/bridge_llama2.py

@@ -26,7 +26,7 @@ class GetLlamaHandle(LocalLLMHandle):
         import platform
         huggingface_token, device = get_conf('HUGGINGFACE_ACCESS_TOKEN', 'LOCAL_MODEL_DEVICE')
         assert len(huggingface_token) != 0, "没有填写 HUGGINGFACE_ACCESS_TOKEN"
-        with open(os.path.expanduser('~/.cache/huggingface/token'), 'w') as f:
+        with open(os.path.expanduser('~/.cache/huggingface/token'), 'w', encoding='utf8') as f:
             f.write(huggingface_token)
         model_id = 'meta-llama/Llama-2-7b-chat-hf'
         with ProxyNetworkActivate('Download_LLM'):

request_llms/bridge_moonshot.py

@@ -31,7 +31,7 @@ class MoonShotInit:
                     files.append(f)
                 for file in files:
                     if file.split('.')[-1] in ['pdf']:
-                        with open(file, 'r') as fp:
+                        with open(file, 'r', encoding='utf8') as fp:
                             from crazy_functions.crazy_utils import read_and_clean_pdf_text
                             file_content, _ = read_and_clean_pdf_text(fp)
                         what_ask.append({"role": "system", "content": file_content})

request_llms/bridge_ollama.py

@@ -75,7 +75,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
             # make a POST request to the API endpoint, stream=False
             from .bridge_all import model_info
             endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
-            response = requests.post(endpoint, headers=headers, proxies=proxies,
+            response = requests.post(endpoint, headers=headers, proxies=None,
                                     json=payload, stream=True, timeout=TIMEOUT_SECONDS); break
         except requests.exceptions.ReadTimeout as e:
             retry += 1
@@ -152,10 +152,12 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     history.append(inputs); history.append("")
 
     retry = 0
+    if proxies is not None:
+        logger.error("Ollama不会使用代理服务器, 忽略了proxies的设置。")
     while True:
         try:
             # make a POST request to the API endpoint, stream=True
-            response = requests.post(endpoint, headers=headers, proxies=proxies,
+            response = requests.post(endpoint, headers=headers, proxies=None,
                                     json=payload, stream=True, timeout=TIMEOUT_SECONDS);break
         except:
             retry += 1

request_llms/requirements_chatglm4.txt

@@ -0,0 +1,7 @@
+protobuf
+cpm_kernels
+torch>=1.10
+transformers>=4.44
+mdtex2html
+sentencepiece
+accelerate

requirements.txt

@@ -1,4 +1,4 @@
-https://public.agent-matrix.com/publish/gradio-3.32.10-py3-none-any.whl
+https://public.agent-matrix.com/publish/gradio-3.32.12-py3-none-any.whl
 fastapi==0.110
 gradio-client==0.8
 pypdf2==2.12.1
@@ -25,7 +25,7 @@ pyautogen
 colorama
 Markdown
 pygments
-edge-tts
+edge-tts>=7.0.0
 pymupdf
 openai
 rjsmin

shared_utils/cookie_manager.py

@@ -77,16 +77,28 @@ def make_history_cache():
     # 定义 后端state（history）、前端（history_cache）、后端setter（history_cache_update）三兄弟
     import gradio as gr
     # 定义history的后端state
-    history = gr.State([])
-    # 定义history的一个孪生的前端存储区（隐藏）
-    history_cache = gr.Textbox(visible=False, elem_id="history_cache")
-    # 定义history_cache->history的更新方法（隐藏）。在触发这个按钮时，会先执行js代码更新history_cache，然后再执行python代码更新history
-    def process_history_cache(history_cache):
-        return json.loads(history_cache)
-    # 另一种更简单的setter方法
-    history_cache_update = gr.Button("", elem_id="elem_update_history", visible=False).click(
-        process_history_cache, inputs=[history_cache], outputs=[history])
-    return history, history_cache, history_cache_update
+    # history = gr.State([])
+    history = gr.Textbox(visible=False, elem_id="history-ng")
+    # # 定义history的一个孪生的前端存储区（隐藏）
+    # history_cache = gr.Textbox(visible=False, elem_id="history_cache")
+    # # 定义history_cache->history的更新方法（隐藏）。在触发这个按钮时，会先执行js代码更新history_cache，然后再执行python代码更新history
+    # def process_history_cache(history_cache):
+    #     return json.loads(history_cache)
+    # # 另一种更简单的setter方法
+    # history_cache_update = gr.Button("", elem_id="elem_update_history", visible=False).click(
+    #     process_history_cache, inputs=[history_cache], outputs=[history])
+    # # save history to history_cache
+    # def process_history_cache(history_cache):
+    #     return json.dumps(history_cache)
+    # # 定义history->history_cache的更新方法（隐藏）
+    # def sync_history_cache(history):
+    #     print("sync_history_cache", history)
+    #     return json.dumps(history)
+    # # history.change(sync_history_cache, inputs=[history], outputs=[history_cache])
+
+    # # history_cache_sync = gr.Button("", elem_id="elem_sync_history", visible=False).click(
+    # #     lambda history: (json.dumps(history)), inputs=[history_cache], outputs=[history])
+    return history, None, None
 
 
 

shared_utils/docker_as_service_api.py

@@ -0,0 +1,83 @@
+import requests
+import pickle
+import io
+import os
+from pydantic import BaseModel, Field
+from typing import Optional, Dict, Any
+from loguru import logger
+
+class DockerServiceApiComModel(BaseModel):
+    client_command: Optional[str] = Field(default=None, title="Client command", description="The command to be executed on the client side")
+    client_file_attach: Optional[dict] = Field(default=None, title="Client file attach", description="The file to be attached to the client side")
+    server_message: Optional[Any] = Field(default=None, title="Server standard error", description="The standard error from the server side")
+    server_std_err: Optional[str] = Field(default=None, title="Server standard error", description="The standard error from the server side")
+    server_std_out: Optional[str] = Field(default=None, title="Server standard output", description="The standard output from the server side")
+    server_file_attach: Optional[dict] = Field(default=None, title="Server file attach", description="The file to be attached to the server side")
+
+def process_received(received: DockerServiceApiComModel, save_file_dir="./daas_output", output_manifest=None):
+    # Process the received data
+    if received.server_message:
+        try:
+            output_manifest['server_message'] += received.server_message
+        except:
+            output_manifest['server_message'] = received.server_message
+    if received.server_std_err:
+        output_manifest['server_std_err'] += received.server_std_err
+    if received.server_std_out:
+        output_manifest['server_std_out'] += received.server_std_out
+    if received.server_file_attach:
+        # print(f"Recv file attach: {received.server_file_attach}")
+        for file_name, file_content in received.server_file_attach.items():
+            new_fp = os.path.join(save_file_dir, file_name)
+            new_fp_dir = os.path.dirname(new_fp)
+            if not os.path.exists(new_fp_dir):
+                os.makedirs(new_fp_dir, exist_ok=True)
+            with open(new_fp, 'wb') as f:
+                f.write(file_content)
+            output_manifest['server_file_attach'].append(new_fp)
+    return output_manifest
+
+def stream_daas(docker_service_api_com_model, server_url, save_file_dir):
+    # Prepare the file
+    # Pickle the object
+    pickled_data = pickle.dumps(docker_service_api_com_model)
+
+    # Create a file-like object from the pickled data
+    file_obj = io.BytesIO(pickled_data)
+
+    # Prepare the file for sending
+    files = {'file': ('docker_service_api_com_model.pkl', file_obj, 'application/octet-stream')}
+
+    # Send the POST request
+    response = requests.post(server_url, files=files, stream=True)
+
+    max_full_package_size = 1024 * 1024 * 1024 * 1  # 1 GB
+
+    received_output_manifest = {}
+    received_output_manifest['server_message'] = ""
+    received_output_manifest['server_std_err'] = ""
+    received_output_manifest['server_std_out'] = ""
+    received_output_manifest['server_file_attach'] = []
+
+    # Check if the request was successful
+    if response.status_code == 200:
+        # Process the streaming response
+        chunk_buf = None
+        for chunk in response.iter_content(max_full_package_size):
+            if chunk:
+                if chunk_buf is None: chunk_buf = chunk
+                else: chunk_buf += chunk
+
+                try:
+                    received = pickle.loads(chunk_buf)
+                    chunk_buf = None
+                    received_output_manifest = process_received(received, save_file_dir, output_manifest = received_output_manifest)
+                    yield received_output_manifest
+                except Exception as e:
+                    # logger.error(f"pickle data was truncated, but don't worry, we will continue to receive the rest of the data.")
+                    continue
+
+    else:
+        logger.error(f"Error: Received status code {response.status_code}, response.text: {response.text}")
+
+    return received_output_manifest

shared_utils/fastapi_server.py

@@ -138,7 +138,9 @@ def start_app(app_block, CONCURRENT_COUNT, AUTHENTICATION, PORT, SSL_KEYFILE, SS
     app_block.is_sagemaker = False
 
     gradio_app = App.create_app(app_block)
-
+    for route in list(gradio_app.router.routes):
+        if route.path == "/proxy={url_path:path}":
+            gradio_app.router.routes.remove(route)
     # --- --- replace gradio endpoint to forbid access to sensitive files --- ---
     if len(AUTHENTICATION) > 0:
         dependencies = []
@@ -154,9 +156,13 @@ def start_app(app_block, CONCURRENT_COUNT, AUTHENTICATION, PORT, SSL_KEYFILE, SS
         @gradio_app.head("/file={path_or_url:path}", dependencies=dependencies)
         @gradio_app.get("/file={path_or_url:path}", dependencies=dependencies)
         async def file(path_or_url: str, request: fastapi.Request):
-            if len(AUTHENTICATION) > 0:
-                if not _authorize_user(path_or_url, request, gradio_app):
-                    return "越权访问!"
+            if not _authorize_user(path_or_url, request, gradio_app):
+                return "越权访问!"
+            stripped = path_or_url.lstrip().lower()
+            if stripped.startswith("https://") or stripped.startswith("http://"):
+                return "账户密码授权模式下, 禁止链接!"
+            if '../' in stripped:
+                return "非法路径!"
             return await endpoint(path_or_url, request)
 
         from fastapi import Request, status
@@ -167,6 +173,26 @@ def start_app(app_block, CONCURRENT_COUNT, AUTHENTICATION, PORT, SSL_KEYFILE, SS
             response.delete_cookie('access-token')
             response.delete_cookie('access-token-unsecure')
             return response
+    else:
+        dependencies = []
+        endpoint = None
+        for route in list(gradio_app.router.routes):
+            if route.path == "/file/{path:path}":
+                gradio_app.router.routes.remove(route)
+            if route.path == "/file={path_or_url:path}":
+                dependencies = route.dependencies
+                endpoint = route.endpoint
+                gradio_app.router.routes.remove(route)
+        @gradio_app.get("/file/{path:path}", dependencies=dependencies)
+        @gradio_app.head("/file={path_or_url:path}", dependencies=dependencies)
+        @gradio_app.get("/file={path_or_url:path}", dependencies=dependencies)
+        async def file(path_or_url: str, request: fastapi.Request):
+            stripped = path_or_url.lstrip().lower()
+            if stripped.startswith("https://") or stripped.startswith("http://"):
+                return "账户密码授权模式下, 禁止链接!"
+            if '../' in stripped:
+                return "非法路径!"
+            return await endpoint(path_or_url, request)
 
     # --- --- enable TTS (text-to-speech) functionality --- ---
     TTS_TYPE = get_conf("TTS_TYPE")

shared_utils/handle_upload.py

@@ -104,17 +104,27 @@ def extract_archive(file_path, dest_dir):
             logger.info("Successfully extracted zip archive to {}".format(dest_dir))
 
     elif file_extension in [".tar", ".gz", ".bz2"]:
-        with tarfile.open(file_path, "r:*") as tarobj:
-            # 清理提取路径，移除任何不安全的元素
-            for member in tarobj.getmembers():
-                member_path = os.path.normpath(member.name)
-                full_path = os.path.join(dest_dir, member_path)
-                full_path = os.path.abspath(full_path)
-                if not full_path.startswith(os.path.abspath(dest_dir) + os.sep):
-                    raise Exception(f"Attempted Path Traversal in {member.name}")
+        try:
+            with tarfile.open(file_path, "r:*") as tarobj:
+                # 清理提取路径，移除任何不安全的元素
+                for member in tarobj.getmembers():
+                    member_path = os.path.normpath(member.name)
+                    full_path = os.path.join(dest_dir, member_path)
+                    full_path = os.path.abspath(full_path)
+                    if not full_path.startswith(os.path.abspath(dest_dir) + os.sep):
+                        raise Exception(f"Attempted Path Traversal in {member.name}")
 
-            tarobj.extractall(path=dest_dir)
-            logger.info("Successfully extracted tar archive to {}".format(dest_dir))
+                tarobj.extractall(path=dest_dir)
+                logger.info("Successfully extracted tar archive to {}".format(dest_dir))
+        except tarfile.ReadError as e:
+            if file_extension == ".gz":
+                # 一些特别奇葩的项目，是一个gz文件，里面不是tar，只有一个tex文件
+                import gzip
+                with gzip.open(file_path, 'rb') as f_in:
+                    with open(os.path.join(dest_dir, 'main.tex'), 'wb') as f_out:
+                        f_out.write(f_in.read())
+            else:
+                raise e
 
     # 第三方库，需要预先pip install rarfile
     # 此外，Windows上还需要安装winrar软件，配置其Path环境变量，如"C:\Program Files\WinRAR"才可以

shared_utils/key_pattern_manager.py

@@ -14,6 +14,7 @@ openai_regex = re.compile(
     r"sk-[a-zA-Z0-9_-]{92}$|" +
     r"sk-proj-[a-zA-Z0-9_-]{48}$|"+
     r"sk-proj-[a-zA-Z0-9_-]{124}$|"+
+    r"sk-proj-[a-zA-Z0-9_-]{156}$|"+ #新版apikey位数不匹配故修改此正则表达式
     r"sess-[a-zA-Z0-9]{40}$"
 )
 def is_openai_api_key(key):
@@ -77,7 +78,8 @@ def select_api_key(keys, llm_model):
     avail_key_list = []
     key_list = keys.split(',')
 
-    if llm_model.startswith('gpt-') or llm_model.startswith('one-api-') or llm_model.startswith('o1-'):
+    if llm_model.startswith('gpt-') or llm_model.startswith('chatgpt-') or \
+       llm_model.startswith('one-api-') or llm_model.startswith('o1-'):
         for k in key_list:
             if is_openai_api_key(k): avail_key_list.append(k)
 

tests/test_bilibili_down.py

@@ -0,0 +1,15 @@
+"""
+对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py
+"""
+
+import init_test
+import os, sys
+
+if __name__ == "__main__":
+    from experimental_mods.get_bilibili_resource import download_bilibili
+    download_bilibili("BV1LSSHYXEtv", only_audio=True, user_name="test")
+
+# if __name__ == "__main__":
+#     from test_utils import plugin_test
+
+#     plugin_test(plugin='crazy_functions.VideoResource_GPT->视频任务', main_input="帮我找到《天文馆的猫》，歌手泠鸢")

tests/test_doc2x.py

@@ -0,0 +1,7 @@
+import init_test
+
+from crazy_functions.pdf_fns.parse_pdf_via_doc2x import 解析PDF_DOC2X_转Latex
+
+# 解析PDF_DOC2X_转Latex("gpt_log/arxiv_cache_old/2410.10819/workfolder/merge.pdf")
+# 解析PDF_DOC2X_转Latex("gpt_log/arxiv_cache_ooo/2410.07095/workfolder/merge.pdf")
+解析PDF_DOC2X_转Latex("2410.11190v2.pdf")

tests/test_latex_auto_correct.py

@@ -19,4 +19,8 @@ if __name__ == "__main__":
     plugin_test = importlib.import_module('test_utils').plugin_test
 
 
-    plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2203.01927")
+    # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2203.01927")
+    # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="gpt_log/arxiv_cache/2203.01927/workfolder")
+    # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2410.05779")
+    plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="gpt_log/default_user/workfolder")
+

tests/test_markdown.py

@@ -29,8 +29,18 @@ graph TD
     E --> B
     D --> F[Save Image and Code]
     F --> B
+
+
+
 ```
 
+<details>
+<summary><b>My section header in bold</b></summary>
+
+Any folded content here. It requires an empty line just above it.
+
+</details>
+
 """
 def validate_path():
     import os, sys
@@ -44,8 +54,8 @@ def validate_path():
 validate_path()  # validate path so you can run from base directory
 from toolbox import markdown_convertion
 from shared_utils.advanced_markdown_format import markdown_convertion_for_file
-with open("gpt_log/default_user/shared/2024-04-22-01-27-43.zip.extract/translated_markdown.md", "r", encoding="utf-8") as f:
-    md = f.read()
+# with open("gpt_log/default_user/shared/2024-04-22-01-27-43.zip.extract/translated_markdown.md", "r", encoding="utf-8") as f:
+    # md = f.read()
 html = markdown_convertion_for_file(md)
 # print(html)
 with open("test.html", "w", encoding="utf-8") as f:

tests/test_media.py

@@ -0,0 +1,67 @@
+"""
+对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py
+"""
+
+import init_test
+import os, sys
+
+
+if __name__ == "__main__":
+    from test_utils import plugin_test
+
+    plugin_test(plugin='crazy_functions.VideoResource_GPT->多媒体任务', main_input="我想找一首歌，里面有句歌词是“turn your face towards the sun”")
+
+    # plugin_test(plugin='crazy_functions.Internet_GPT->连接网络回答问题', main_input="谁是应急食品？")
+
+    # plugin_test(plugin='crazy_functions.函数动态生成->函数动态生成', main_input='交换图像的蓝色通道和红色通道', advanced_arg={"file_path_arg": "./build/ants.jpg"})
+
+    # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2307.07522")
+
+    # plugin_test(plugin='crazy_functions.PDF_Translate->批量翻译PDF文档', main_input='build/pdf/t1.pdf')
+
+    # plugin_test(
+    #     plugin="crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF",
+    #     main_input="G:/SEAFILE_LOCAL/50503047/我的资料库/学位/paperlatex/aaai/Fu_8368_with_appendix",
+    # )
+
+    # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='修改api-key为sk-jhoejriotherjep')
+
+    # plugin_test(plugin='crazy_functions.批量翻译PDF文档_NOUGAT->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf')
+
+    # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='调用插件，对C:/Users/fuqingxu/Desktop/旧文件/gpt/chatgpt_academic/crazy_functions/latex_fns中的python文件进行解析')
+
+    # plugin_test(plugin='crazy_functions.命令行助手->命令行助手', main_input='查看当前的docker容器列表')
+
+    # plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个Python项目', main_input="crazy_functions/test_project/python/dqn")
+
+    # plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个C项目', main_input="crazy_functions/test_project/cpp/cppipc")
+
+    # plugin_test(plugin='crazy_functions.Latex_Project_Polish->Latex英文润色', main_input="crazy_functions/test_project/latex/attention")
+
+    # plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown中译英', main_input="README.md")
+
+    # plugin_test(plugin='crazy_functions.PDF_Translate->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf')
+
+    # plugin_test(plugin='crazy_functions.谷歌检索小助手->谷歌检索小助手', main_input="https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=auto+reinforcement+learning&btnG=")
+
+    # plugin_test(plugin='crazy_functions.总结word文档->总结word文档', main_input="crazy_functions/test_project/pdf_and_word")
+
+    # plugin_test(plugin='crazy_functions.下载arxiv论文翻译摘要->下载arxiv论文并翻译摘要', main_input="1812.10695")
+
+    # plugin_test(plugin='crazy_functions.联网的ChatGPT->连接网络回答问题', main_input="谁是应急食品？")
+
+    # plugin_test(plugin='crazy_functions.解析JupyterNotebook->解析ipynb文件', main_input="crazy_functions/test_samples")
+
+    # plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A ball split into 2, and then split into 4, and finally split into 8.")
+
+    # for lang in ["English", "French", "Japanese", "Korean", "Russian", "Italian", "German", "Portuguese", "Arabic"]:
+    #     plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown翻译指定语言', main_input="README.md", advanced_arg={"advanced_arg": lang})
+
+    # plugin_test(plugin='crazy_functions.知识库文件注入->知识库文件注入', main_input="./")
+
+    # plugin_test(plugin='crazy_functions.知识库文件注入->读取知识库作答', main_input="What is the installation method？")
+
+    # plugin_test(plugin='crazy_functions.知识库文件注入->读取知识库作答', main_input="远程云服务器部署？")
+
+    # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2210.03629")
+

tests/test_plugins.py

@@ -36,7 +36,7 @@ if __name__ == "__main__":
 
     # plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个C项目', main_input="crazy_functions/test_project/cpp/cppipc")
 
-    # plugin_test(plugin='crazy_functions.Latex全文润色->Latex英文润色', main_input="crazy_functions/test_project/latex/attention")
+    # plugin_test(plugin='crazy_functions.Latex_Project_Polish->Latex英文润色', main_input="crazy_functions/test_project/latex/attention")
 
     # plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown中译英', main_input="README.md")
 
@@ -65,8 +65,3 @@ if __name__ == "__main__":
 
     # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2210.03629")
 
-    # advanced_arg = {"advanced_arg":"--llm_to_learn=gpt-3.5-turbo --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、人设进行描写。要求：100字以内，用第二人称。' --system_prompt=''" }
-    # plugin_test(plugin='crazy_functions.chatglm微调工具->微调数据集生成', main_input='build/dev.json', advanced_arg=advanced_arg)
-
-    # advanced_arg = {"advanced_arg":"--pre_seq_len=128 --learning_rate=2e-2 --num_gpus=1 --json_dataset='t_code.json' --ptuning_directory='/home/hmp/ChatGLM2-6B/ptuning'     " }
-    # plugin_test(plugin='crazy_functions.chatglm微调工具->启动微调', main_input='build/dev.json', advanced_arg=advanced_arg)

tests/test_tts.py

@@ -0,0 +1,33 @@
+import edge_tts
+import os
+import httpx
+from toolbox import get_conf
+
+
+async def test_tts():    
+    async with httpx.AsyncClient() as client:
+        try:
+            # Forward the request to the target service
+            import tempfile
+            import edge_tts
+            import wave
+            import uuid
+            from pydub import AudioSegment
+            voice = get_conf("EDGE_TTS_VOICE")
+            tts = edge_tts.Communicate(text="测试", voice=voice)
+            temp_folder = tempfile.gettempdir()
+            temp_file_name = str(uuid.uuid4().hex)
+            temp_file = os.path.join(temp_folder, f'{temp_file_name}.mp3')
+            await tts.save(temp_file)
+            try:
+                mp3_audio = AudioSegment.from_file(temp_file, format="mp3")
+                mp3_audio.export(temp_file, format="wav")
+                with open(temp_file, 'rb') as wav_file: t = wav_file.read()
+            except:
+                raise RuntimeError("ffmpeg未安装，无法处理EdgeTTS音频。安装方法见`https://github.com/jiaaro/pydub#getting-ffmpeg-set-up`")
+        except httpx.RequestError as e:
+            raise RuntimeError(f"请求失败: {e}")
+        
+if __name__ == "__main__":
+    import asyncio
+    asyncio.run(test_tts())

themes/common.css

@@ -270,4 +270,9 @@
 }
 #gpt-submit-row #gpt-submit-dropdown > *:hover {
     cursor: context-menu;
+}
+
+.tooltip.svelte-p2nen8.svelte-p2nen8 {
+    box-shadow: 10px 10px 15px rgba(0, 0, 0, 0.5);
+    left: 10px;
 }

themes/common.js

@@ -318,7 +318,7 @@ function addCopyButton(botElement, index, is_last_in_arr) {
         }
     });
 
-    if (enable_tts){
+    if (enable_tts) {
         var audioButton = document.createElement('button');
         audioButton.classList.add('audio-toggle-btn');
         audioButton.innerHTML = audioIcon;
@@ -346,7 +346,7 @@ function addCopyButton(botElement, index, is_last_in_arr) {
     var messageBtnColumn = document.createElement('div');
     messageBtnColumn.classList.add('message-btn-row');
     messageBtnColumn.appendChild(copyButton);
-    if (enable_tts){
+    if (enable_tts) {
         messageBtnColumn.appendChild(audioButton);
     }
     botElement.appendChild(messageBtnColumn);
@@ -391,6 +391,8 @@ function chatbotContentChanged(attempt = 1, force = false) {
 
                 // Now pass both the message element and the is_last_in_arr boolean to addCopyButton
                 addCopyButton(message, index, is_last_in_arr);
+
+                save_conversation_history();
             });
             // gradioApp().querySelectorAll('#gpt-chatbot .message-wrap .message.bot').forEach(addCopyButton);
         }, i === 0 ? 0 : 200);
@@ -854,8 +856,7 @@ function limit_scroll_position() {
 // -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
 
 function loadLive2D() {
-    if (document.querySelector(".waifu") )
-    {
+    if (document.querySelector(".waifu")) {
         $('.waifu').show();
     } else {
         try {
@@ -922,12 +923,12 @@ function gpt_academic_gradio_saveload(
     if (save_or_load === "load") {
         let value = getCookie(cookie_key);
         if (value) {
-            console.log('加载cookie', elem_id, value)
+            // console.log('加载cookie', elem_id, value)
             push_data_to_gradio_component(value, elem_id, load_type);
         }
         else {
             if (load_default) {
-                console.log('加载cookie的默认值', elem_id, load_default_value)
+                // console.log('加载cookie的默认值', elem_id, load_default_value)
                 push_data_to_gradio_component(load_default_value, elem_id, load_type);
             }
         }
@@ -937,113 +938,149 @@ function gpt_academic_gradio_saveload(
     }
 }
 
+function update_conversation_metadata() {
+    // Create a conversation UUID and timestamp
+    const conversationId = crypto.randomUUID();
+    const timestamp = new Date().toISOString();
+    const conversationData = {
+        id: conversationId,
+        timestamp: timestamp
+    };
+    // Save to cookie
+    setCookie("conversation_metadata", JSON.stringify(conversationData), 2);
+    // read from cookie
+    let conversation_metadata = getCookie("conversation_metadata");
+    // console.log("conversation_metadata", conversation_metadata);
+}
+
+
+// Helper function to generate conversation preview
+function generatePreview(conversation, timestamp, maxLength = 100) {
+    if (!conversation || conversation.length === 0) return "";
+    // Join all messages with dash separator
+    let preview = conversation.join("\n");
+    const readableDate = new Date(timestamp).toLocaleString();
+    preview = readableDate + "\n" + preview;
+    if (preview.length <= maxLength) return preview;
+    return preview.substring(0, maxLength) + "...";
+}
+
+async function save_conversation_history() {
+    // 505030475
+    let chatbot = await get_data_from_gradio_component('gpt-chatbot');
+    let history = await get_data_from_gradio_component('history-ng');
+    let conversation_metadata = getCookie("conversation_metadata");
+    conversation_metadata = JSON.parse(conversation_metadata);
+    // console.log("conversation_metadata", conversation_metadata);
+    let conversation = {
+        timestamp: conversation_metadata.timestamp,
+        id: conversation_metadata.id,
+        metadata: conversation_metadata,
+        conversation: chatbot,
+        history: history,
+        preview: generatePreview(JSON.parse(history), conversation_metadata.timestamp)
+    };
+
+    // Get existing conversation history from local storage
+    let conversation_history = [];
+    try {
+        const stored = localStorage.getItem('conversation_history');
+        if (stored) {
+            conversation_history = JSON.parse(stored);
+        }
+    } catch (e) {
+        // console.error('Error reading conversation history from localStorage:', e);
+    }
+
+    // Find existing conversation with same ID
+    const existingIndex = conversation_history.findIndex(c => c.id === conversation.id);
+
+    if (existingIndex >= 0) {
+        // Update existing conversation
+        conversation_history[existingIndex] = conversation;
+    } else {
+        // Add new conversation
+        conversation_history.push(conversation);
+    }
+
+    // Sort conversations by timestamp, newest first
+    conversation_history.sort((a, b) => {
+        const timeA = new Date(a.timestamp).getTime();
+        const timeB = new Date(b.timestamp).getTime();
+        return timeB - timeA;
+    });
+
+    // Save back to local storage
+    try {
+        localStorage.setItem('conversation_history', JSON.stringify(conversation_history));
+        const LOCAL_STORAGE_UPDATED = "gptac_conversation_history_updated";
+        window.dispatchEvent(
+            new CustomEvent(LOCAL_STORAGE_UPDATED, {
+                detail: conversation_history
+            })
+        );
+    } catch (e) {
+        console.error('Error saving conversation history to localStorage:', e);
+    }
+}
+
+
+function restore_chat_from_local_storage(event) {
+    let conversation = event.detail;
+    push_data_to_gradio_component(conversation.conversation, "gpt-chatbot", "obj");
+    push_data_to_gradio_component(conversation.history, "history-ng", "obj");
+    // console.log("restore_chat_from_local_storage", conversation);
+
+    // Create a conversation UUID and timestamp
+    const conversationId = conversation.id;
+    const timestamp = conversation.timestamp;
+    const conversationData = {
+        id: conversationId,
+        timestamp: timestamp
+    };
+    // Save to cookie
+    setCookie("conversation_metadata", JSON.stringify(conversationData), 2);
+    // read from cookie
+    let conversation_metadata = getCookie("conversation_metadata");
+
+}
+
+
+function clear_conversation(a, b, c) {
+    update_conversation_metadata();
+    let stopButton = document.getElementById("elem_stop");
+    stopButton.click();
+    // console.log("clear_conversation");
+    return reset_conversation(a, b);
+}
+
 
 function reset_conversation(a, b) {
     // console.log("js_code_reset");
     a = btoa(unescape(encodeURIComponent(JSON.stringify(a))));
     setCookie("js_previous_chat_cookie", a, 1);
-    gen_restore_btn();
+    b = btoa(unescape(encodeURIComponent(JSON.stringify(b))));
+    setCookie("js_previous_history_cookie", b, 1);
+    // gen_restore_btn();
     return [[], [], "已重置"];
 }
 
+
 // clear -> 将 history 缓存至 history_cache -> 点击复原 -> restore_previous_chat() -> 触发elem_update_history -> 读取 history_cache
 function restore_previous_chat() {
-    console.log("restore_previous_chat");
+    // console.log("restore_previous_chat");
     let chat = getCookie("js_previous_chat_cookie");
     chat = JSON.parse(decodeURIComponent(escape(atob(chat))));
     push_data_to_gradio_component(chat, "gpt-chatbot", "obj");
-    document.querySelector("#elem_update_history").click(); // in order to call set_history_gr_state, and send history state to server
+    let history = getCookie("js_previous_history_cookie");
+    history = JSON.parse(decodeURIComponent(escape(atob(history))));
+    push_data_to_gradio_component(history, "history-ng", "obj");
+    // document.querySelector("#elem_update_history").click(); // in order to call set_history_gr_state, and send history state to server
 }
 
-function gen_restore_btn() {
-
-
-    // 创建按钮元素
-    const button = document.createElement('div');
-    // const recvIcon = '<span><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" height=".8em" width=".8em" xmlns="http://www.w3.org/2000/svg"><polyline points="20 6 9 17 4 12"></polyline></svg></span>';
-    const rec_svg = '<svg t="1714361184567" style="transform:translate(1px, 2.5px)" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="4389" width="35" height="35"><path d="M320 512h384v64H320zM320 384h384v64H320zM320 640h192v64H320z" p-id="4390" fill="#ffffff"></path><path d="M863.7 544c-1.9 44-11.4 86.8-28.5 127.2-18.5 43.8-45.1 83.2-78.9 117-33.8 33.8-73.2 60.4-117 78.9C593.9 886.3 545.7 896 496 896s-97.9-9.7-143.2-28.9c-43.8-18.5-83.2-45.1-117-78.9-33.8-33.8-60.4-73.2-78.9-117C137.7 625.9 128 577.7 128 528s9.7-97.9 28.9-143.2c18.5-43.8 45.1-83.2 78.9-117s73.2-60.4 117-78.9C398.1 169.7 446.3 160 496 160s97.9 9.7 143.2 28.9c23.5 9.9 45.8 22.2 66.5 36.7l-119.7 20 9.9 59.4 161.6-27 59.4-9.9-9.9-59.4-27-161.5-59.4 9.9 19 114.2C670.3 123.8 586.4 96 496 96 257.4 96 64 289.4 64 528s193.4 432 432 432c233.2 0 423.3-184.8 431.7-416h-64z" p-id="4391" fill="#ffffff"></path></svg>'
-    const recvIcon = '<span>' + rec_svg + '</span>';
-
-    // 设置按钮的样式和属性
-    button.id = 'floatingButton';
-    button.className = 'glow';
-    button.style.textAlign = 'center';
-    button.style.position = 'fixed';
-    button.style.bottom = '10px';
-    button.style.left = '10px';
-    button.style.width = '50px';
-    button.style.height = '50px';
-    button.style.borderRadius = '50%';
-    button.style.backgroundColor = '#007bff';
-    button.style.color = 'white';
-    button.style.display = 'flex';
-    button.style.alignItems = 'center';
-    button.style.justifyContent = 'center';
-    button.style.cursor = 'pointer';
-    button.style.transition = 'all 0.3s ease';
-    button.style.boxShadow = '0 0 10px rgba(0,0,0,0.2)';
-
-    button.innerHTML = recvIcon;
-
-    // 添加发光动画的关键帧
-    const styleSheet = document.createElement('style');
-    styleSheet.id = 'floatingButtonStyle';
-    styleSheet.innerText = `
-    @keyframes glow {
-        from {
-        box-shadow: 0 0 10px rgba(0,0,0,0.2);
-        }
-        to {
-        box-shadow: 0 0 13px rgba(0,0,0,0.5);
-        }
-    }
-    #floatingButton.glow {
-        animation: glow 1s infinite alternate;
-    }
-    #floatingButton:hover {
-        transform: scale(1.2);
-        box-shadow: 0 0 20px rgba(0,0,0,0.4);
-    }
-    #floatingButton.disappearing {
-        animation: shrinkAndDisappear 0.5s forwards;
-    }
-    `;
-
-    // only add when not exist
-    if (!document.getElementById('recvButtonStyle'))
-    {
-        document.head.appendChild(styleSheet);
-    }
-
-    // 鼠标悬停和移开的事件监听器
-    button.addEventListener('mouseover', function () {
-        this.textContent = "还原\n对话";
-    });
-
-    button.addEventListener('mouseout', function () {
-        this.innerHTML = recvIcon;
-    });
-
-    // 点击事件监听器
-    button.addEventListener('click', function () {
-        // 添加一个类来触发缩小和消失的动画
-        restore_previous_chat();
-        this.classList.add('disappearing');
-        // 在动画结束后移除按钮
-        document.body.removeChild(this);
-    });
-    // only add when not exist
-    if (!document.getElementById('recvButton'))
-    {
-        document.body.appendChild(button);
-    }
-
-    // 将按钮添加到页面中
-
-}
 
 async function on_plugin_exe_complete(fn_name) {
-    console.log(fn_name);
+    // console.log(fn_name);
     if (fn_name === "保存当前的对话") {
         // get chat profile path
         let chatbot = await get_data_from_gradio_component('gpt-chatbot');
@@ -1062,15 +1099,15 @@ async function on_plugin_exe_complete(fn_name) {
         }
         let href = get_href(may_have_chat_profile_info);
         if (href) {
-            const cleanedHref = href.replace('file=', ''); // /home/fuqingxu/chatgpt_academic/gpt_log/default_user/chat_history/GPT-Academic对话存档2024-04-12-00-35-06.html
-            console.log(cleanedHref);
+            const cleanedHref = href.replace('file=', ''); // gpt_log/default_user/chat_history/GPT-Academic对话存档2024-04-12-00-35-06.html
+            // console.log(cleanedHref);
         }
 
     }
 }
 
 
-async function generate_menu(guiBase64String, btnName){
+async function generate_menu(guiBase64String, btnName) {
     // assign the button and menu data
     push_data_to_gradio_component(guiBase64String, "invisible_current_pop_up_plugin_arg", "string");
     push_data_to_gradio_component(btnName, "invisible_callback_btn_for_plugin_exe", "string");
@@ -1104,22 +1141,22 @@ async function generate_menu(guiBase64String, btnName){
             ///////////////////////////////////////////////////////////////////////////////////////////
             ////////////////////////////////////    Textbox   ////////////////////////////////////
             ///////////////////////////////////////////////////////////////////////////////////////////
-            if (gui_args[key].type=='string'){ // PLUGIN_ARG_MENU
+            if (gui_args[key].type == 'string') { // PLUGIN_ARG_MENU
                 const component_name = "plugin_arg_txt_" + text_cnt;
                 push_data_to_gradio_component({
                     visible: true,
-                    label: gui_args[key].title + "(" + gui_args[key].description +  ")",
+                    label: gui_args[key].title + "(" + gui_args[key].description + ")",
                     // label: gui_args[key].title,
                     placeholder: gui_args[key].description,
                     __type__: 'update'
                 }, component_name, "obj");
-                if (key === "main_input"){
+                if (key === "main_input") {
                     // 为了与旧插件兼容，生成菜单时，自动加载输入栏的值
                     let current_main_input = await get_data_from_gradio_component('user_input_main');
                     let current_main_input_2 = await get_data_from_gradio_component('user_input_float');
                     push_data_to_gradio_component(current_main_input + current_main_input_2, component_name, "obj");
                 }
-                else if (key === "advanced_arg"){
+                else if (key === "advanced_arg") {
                     // 为了与旧插件兼容，生成菜单时，自动加载旧高级参数输入区的值
                     let advance_arg_input_legacy = await get_data_from_gradio_component('advance_arg_input_legacy');
                     push_data_to_gradio_component(advance_arg_input_legacy, component_name, "obj");
@@ -1134,12 +1171,12 @@ async function generate_menu(guiBase64String, btnName){
             ///////////////////////////////////////////////////////////////////////////////////////////
             ////////////////////////////////////    Dropdown   ////////////////////////////////////
             ///////////////////////////////////////////////////////////////////////////////////////////
-            if (gui_args[key].type=='dropdown'){ // PLUGIN_ARG_MENU
+            if (gui_args[key].type == 'dropdown') { // PLUGIN_ARG_MENU
                 const component_name = "plugin_arg_drop_" + dropdown_cnt;
                 push_data_to_gradio_component({
                     visible: true,
                     choices: gui_args[key].options,
-                    label: gui_args[key].title + "(" + gui_args[key].description +  ")",
+                    label: gui_args[key].title + "(" + gui_args[key].description + ")",
                     // label: gui_args[key].title,
                     placeholder: gui_args[key].description,
                     __type__: 'update'
@@ -1154,7 +1191,7 @@ async function generate_menu(guiBase64String, btnName){
     }
 }
 
-async function execute_current_pop_up_plugin(){
+async function execute_current_pop_up_plugin() {
     let guiBase64String = await get_data_from_gradio_component('invisible_current_pop_up_plugin_arg');
     const stringData = atob(guiBase64String);
     let guiJsonData = JSON.parse(stringData);
@@ -1170,8 +1207,8 @@ async function execute_current_pop_up_plugin(){
     let text_cnt = 0;
     for (const key in gui_args) {
         if (gui_args.hasOwnProperty(key)) {
-            if (gui_args[key].type=='string'){ // PLUGIN_ARG_MENU
-                corrisponding_elem_id = "plugin_arg_txt_"+text_cnt
+            if (gui_args[key].type == 'string') { // PLUGIN_ARG_MENU
+                corrisponding_elem_id = "plugin_arg_txt_" + text_cnt
                 gui_args[key].user_confirmed_value = await get_data_from_gradio_component(corrisponding_elem_id);
                 text_cnt += 1;
             }
@@ -1180,8 +1217,8 @@ async function execute_current_pop_up_plugin(){
     let dropdown_cnt = 0;
     for (const key in gui_args) {
         if (gui_args.hasOwnProperty(key)) {
-            if (gui_args[key].type=='dropdown'){ // PLUGIN_ARG_MENU
-                corrisponding_elem_id = "plugin_arg_drop_"+dropdown_cnt
+            if (gui_args[key].type == 'dropdown') { // PLUGIN_ARG_MENU
+                corrisponding_elem_id = "plugin_arg_drop_" + dropdown_cnt
                 gui_args[key].user_confirmed_value = await get_data_from_gradio_component(corrisponding_elem_id);
                 dropdown_cnt += 1;
             }
@@ -1200,29 +1237,29 @@ async function execute_current_pop_up_plugin(){
 
 }
 
-function hide_all_elem(){
-     // PLUGIN_ARG_MENU
-    for (text_cnt = 0; text_cnt < 8; text_cnt++){
+function hide_all_elem() {
+    // PLUGIN_ARG_MENU
+    for (text_cnt = 0; text_cnt < 8; text_cnt++) {
         push_data_to_gradio_component({
             visible: false,
             label: "",
             __type__: 'update'
-        }, "plugin_arg_txt_"+text_cnt, "obj");
-        document.getElementById("plugin_arg_txt_"+text_cnt).parentNode.parentNode.style.display = 'none';
+        }, "plugin_arg_txt_" + text_cnt, "obj");
+        document.getElementById("plugin_arg_txt_" + text_cnt).parentNode.parentNode.style.display = 'none';
     }
-    for (dropdown_cnt = 0; dropdown_cnt < 8; dropdown_cnt++){
+    for (dropdown_cnt = 0; dropdown_cnt < 8; dropdown_cnt++) {
         push_data_to_gradio_component({
             visible: false,
             choices: [],
             label: "",
             __type__: 'update'
-        }, "plugin_arg_drop_"+dropdown_cnt, "obj");
-        document.getElementById("plugin_arg_drop_"+dropdown_cnt).parentNode.style.display = 'none';
+        }, "plugin_arg_drop_" + dropdown_cnt, "obj");
+        document.getElementById("plugin_arg_drop_" + dropdown_cnt).parentNode.style.display = 'none';
     }
 }
 
-function close_current_pop_up_plugin(){
-     // PLUGIN_ARG_MENU
+function close_current_pop_up_plugin() {
+    // PLUGIN_ARG_MENU
     push_data_to_gradio_component({
         visible: false,
         __type__: 'update'
@@ -1233,15 +1270,13 @@ function close_current_pop_up_plugin(){
 
 // 生成高级插件的选择菜单
 plugin_init_info_lib = {}
-function register_plugin_init(key, base64String){
+function register_plugin_init(key, base64String) {
     // console.log('x')
     const stringData = atob(base64String);
     let guiJsonData = JSON.parse(stringData);
-    if (key in plugin_init_info_lib)
-    {
+    if (key in plugin_init_info_lib) {
     }
-    else
-    {
+    else {
         plugin_init_info_lib[key] = {};
     }
     plugin_init_info_lib[key].info = guiJsonData.Info;
@@ -1251,28 +1286,26 @@ function register_plugin_init(key, base64String){
     plugin_init_info_lib[key].enable_advanced_arg = guiJsonData.AdvancedArgs;
     plugin_init_info_lib[key].arg_reminder = guiJsonData.ArgsReminder;
 }
-function register_advanced_plugin_init_code(key, code){
-    if (key in plugin_init_info_lib)
-    {
+function register_advanced_plugin_init_code(key, code) {
+    if (key in plugin_init_info_lib) {
     }
-    else
-    {
+    else {
         plugin_init_info_lib[key] = {};
     }
     plugin_init_info_lib[key].secondary_menu_code = code;
 }
-function run_advanced_plugin_launch_code(key){
+function run_advanced_plugin_launch_code(key) {
     // convert js code string to function
     generate_menu(plugin_init_info_lib[key].secondary_menu_code, key);
 }
-function on_flex_button_click(key){
-    if (plugin_init_info_lib.hasOwnProperty(key) && plugin_init_info_lib[key].hasOwnProperty('secondary_menu_code')){
+function on_flex_button_click(key) {
+    if (plugin_init_info_lib.hasOwnProperty(key) && plugin_init_info_lib[key].hasOwnProperty('secondary_menu_code')) {
         run_advanced_plugin_launch_code(key);
-    }else{
+    } else {
         document.getElementById("old_callback_btn_for_plugin_exe").click();
     }
 }
-async function run_dropdown_shift(dropdown){
+async function run_dropdown_shift(dropdown) {
     let key = dropdown;
     push_data_to_gradio_component({
         value: key,
@@ -1281,7 +1314,7 @@ async function run_dropdown_shift(dropdown){
         __type__: 'update'
     }, "elem_switchy_bt", "obj");
 
-    if (plugin_init_info_lib[key].enable_advanced_arg){
+    if (plugin_init_info_lib[key].enable_advanced_arg) {
         push_data_to_gradio_component({
             visible: true,
             label: plugin_init_info_lib[key].label,
@@ -1303,9 +1336,9 @@ async function duplicate_in_new_window() {
     window.open(url, '_blank');
 }
 
-async function run_classic_plugin_via_id(plugin_elem_id){
-    for (key in plugin_init_info_lib){
-        if (plugin_init_info_lib[key].elem_id == plugin_elem_id){
+async function run_classic_plugin_via_id(plugin_elem_id) {
+    for (key in plugin_init_info_lib) {
+        if (plugin_init_info_lib[key].elem_id == plugin_elem_id) {
             // 获取按钮名称
             let current_btn_name = await get_data_from_gradio_component(plugin_elem_id);
             // 执行
@@ -1326,7 +1359,7 @@ async function call_plugin_via_name(current_btn_name) {
     hide_all_elem();
     // 为了与旧插件兼容，生成菜单时，自动加载旧高级参数输入区的值
     let advance_arg_input_legacy = await get_data_from_gradio_component('advance_arg_input_legacy');
-    if (advance_arg_input_legacy.length != 0){
+    if (advance_arg_input_legacy.length != 0) {
         gui_args["advanced_arg"] = {};
         gui_args["advanced_arg"].user_confirmed_value = advance_arg_input_legacy;
     }
@@ -1349,18 +1382,11 @@ async function multiplex_function_begin(multiplex_sel) {
         click_real_submit_btn();
         return;
     }
-    if (multiplex_sel === "多模型对话") {
-        let _align_name_in_crazy_function_py = "询问多个GPT模型";
-        call_plugin_via_name(_align_name_in_crazy_function_py);
-        return;
-    }
-    if (multiplex_sel === "智能召回 RAG") {
-        let _align_name_in_crazy_function_py = "Rag智能召回";
-        call_plugin_via_name(_align_name_in_crazy_function_py);
-        return;
-    }
+
+    // do not delete `REPLACE_EXTENDED_MULTIPLEX_FUNCTIONS_HERE`! It will be read and replaced by Python code.
+    // REPLACE_EXTENDED_MULTIPLEX_FUNCTIONS_HERE
 }
-async function run_multiplex_shift(multiplex_sel){
+async function run_multiplex_shift(multiplex_sel) {
     let key = multiplex_sel;
     if (multiplex_sel === "常规对话") {
         key = "提交";
@@ -1372,3 +1398,8 @@ async function run_multiplex_shift(multiplex_sel){
         __type__: 'update'
     }, "elem_submit_visible", "obj");
 }
+
+
+async function persistent_cookie_init(web_cookie_cache, cookie) {
+    return [localStorage.getItem('web_cookie_cache'), cookie];
+}

themes/common.py

@@ -2,6 +2,25 @@ from functools import lru_cache
 from toolbox import get_conf
 CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf("CODE_HIGHLIGHT", "ADD_WAIFU", "LAYOUT")
 
+def inject_mutex_button_code(js_content):
+    from crazy_functional import get_multiplex_button_functions
+    fns = get_multiplex_button_functions()
+
+    template = """
+    if (multiplex_sel === "{x}") {
+        let _align_name_in_crazy_function_py = "{y}";
+        call_plugin_via_name(_align_name_in_crazy_function_py);
+        return;
+    }
+    """
+
+    replacement = ""
+    for fn in fns.keys():
+        if fn == "常规对话": continue
+        replacement += template.replace("{x}", fn).replace("{y}", fns[fn])
+    js_content = js_content.replace("// REPLACE_EXTENDED_MULTIPLEX_FUNCTIONS_HERE", replacement)
+    return js_content
+
 def minimize_js(common_js_path):
     try:
         import rjsmin, hashlib, glob, os
@@ -10,14 +29,16 @@ def minimize_js(common_js_path):
             os.remove(old_min_js)
         # use rjsmin to minimize `common_js_path`
         c_jsmin = rjsmin.jsmin
-        with open(common_js_path, "r") as f:
+        with open(common_js_path, "r", encoding='utf-8') as f:
             js_content = f.read()
+        if common_js_path == "themes/common.js":
+            js_content = inject_mutex_button_code(js_content)
         minimized_js_content = c_jsmin(js_content)
         # compute sha256 hash of minimized js content
         sha_hash = hashlib.sha256(minimized_js_content.encode()).hexdigest()[:8]
         minimized_js_path = common_js_path + '.min.' + sha_hash + '.js'
         # save to minimized js file
-        with open(minimized_js_path, "w") as f:
+        with open(minimized_js_path, "w", encoding='utf-8') as f:
             f.write(minimized_js_content)
         # return minimized js file path
         return minimized_js_path

themes/gui_floating_menu.py

@@ -1,7 +1,7 @@
 import gradio as gr
 
 def define_gui_floating_menu(customize_btns, functional, predefined_btns, cookies, web_cookie_cache):
-    with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top") as area_input_secondary:
+    with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top", elem_id="f_area_input_secondary") as area_input_secondary:
         with gr.Accordion("浮动输入区", open=True, elem_id="input-panel2"):
             with gr.Row() as row:
                 row.style(equal_height=True)
@@ -17,7 +17,7 @@ def define_gui_floating_menu(customize_btns, functional, predefined_btns, cookie
                     clearBtn2 = gr.Button("清除", elem_id="elem_clear2", variant="secondary", visible=False); clearBtn2.style(size="sm")
 
 
-    with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top") as area_customize:
+    with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top", elem_id="f_area_customize") as area_customize:
         with gr.Accordion("自定义菜单", open=True, elem_id="edit-panel"):
             with gr.Row() as row:
                 with gr.Column(scale=10):
@@ -35,9 +35,9 @@ def define_gui_floating_menu(customize_btns, functional, predefined_btns, cookie
                     # update btn
                     h = basic_fn_confirm.click(assign_btn, [web_cookie_cache, cookies, basic_btn_dropdown, basic_fn_title, basic_fn_prefix, basic_fn_suffix],
                                             [web_cookie_cache, cookies, *customize_btns.values(), *predefined_btns.values()])
-                    h.then(None, [web_cookie_cache], None, _js="""(web_cookie_cache)=>{setCookie("web_cookie_cache", web_cookie_cache, 365);}""")
+                    h.then(None, [web_cookie_cache], None, _js="""(web_cookie_cache)=>{localStorage.setItem("web_cookie_cache", web_cookie_cache);}""")
                     # clean up btn
                     h2 = basic_fn_clean.click(assign_btn, [web_cookie_cache, cookies, basic_btn_dropdown, basic_fn_title, basic_fn_prefix, basic_fn_suffix, gr.State(True)],
                                             [web_cookie_cache, cookies, *customize_btns.values(), *predefined_btns.values()])
-                    h2.then(None, [web_cookie_cache], None, _js="""(web_cookie_cache)=>{setCookie("web_cookie_cache", web_cookie_cache, 365);}""")
+                    h2.then(None, [web_cookie_cache], None, _js="""(web_cookie_cache)=>{localStorage.setItem("web_cookie_cache", web_cookie_cache);}""")
     return area_input_secondary, txt2, area_customize, submitBtn2, resetBtn2, clearBtn2, stopBtn2

themes/init.js

@@ -3,6 +3,8 @@ async function GptAcademicJavaScriptInit(dark, prompt, live2d, layout, tts) {
     audio_fn_init();
     minor_ui_adjustment();
     ButtonWithDropdown_init();
+    update_conversation_metadata();
+    window.addEventListener("gptac_restore_chat_from_local_storage", restore_chat_from_local_storage);
     
     // 加载欢迎页面
     const welcomeMessage = new WelcomeMessage();

themes/theme.py

@@ -87,21 +87,6 @@ js_code_for_toggle_darkmode = """() => {
 }"""
 
 
-js_code_for_persistent_cookie_init = """(web_cookie_cache, cookie) => {
-    return [getCookie("web_cookie_cache"), cookie];
-}
-"""
-
-# 详见 themes/common.js
-js_code_reset = """
-(a,b,c)=>{
-    let stopButton = document.getElementById("elem_stop");
-    stopButton.click();
-    return reset_conversation(a,b);
-}
-"""
-
-
 js_code_clear = """
 (a,b)=>{
     return ["", ""];

themes/welcome.js

@@ -84,7 +84,7 @@ class WelcomeMessage {
         this.max_welcome_card_num = 6;
         this.card_array = [];
         this.static_welcome_message_previous = [];
-        this.reflesh_time_interval = 15*1000;
+        this.reflesh_time_interval = 15 * 1000;
 
 
         const reflesh_render_status = () => {
@@ -96,6 +96,9 @@ class WelcomeMessage {
         };
         const pageFocusHandler = new PageFocusHandler();
         pageFocusHandler.addFocusCallback(reflesh_render_status);
+
+        // call update when page size change, call this.update when page size change
+        window.addEventListener('resize', this.update.bind(this));
     }
 
     begin_render() {
@@ -105,7 +108,7 @@ class WelcomeMessage {
     async startRefleshCards() {
         await new Promise(r => setTimeout(r, this.reflesh_time_interval));
         await this.reflesh_cards();
-        if (this.visible){
+        if (this.visible) {
             setTimeout(() => {
                 this.startRefleshCards.call(this);
             }, 1);
@@ -113,7 +116,7 @@ class WelcomeMessage {
     }
 
     async reflesh_cards() {
-        if (!this.visible){
+        if (!this.visible) {
             return;
         }
 
@@ -173,18 +176,18 @@ class WelcomeMessage {
     }
 
     shuffle(array) {
-        var currentIndex = array.length,  randomIndex;
+        var currentIndex = array.length, randomIndex;
 
         // While there remain elements to shuffle...
         while (currentIndex != 0) {
 
-          // Pick a remaining element...
-          randomIndex = Math.floor(Math.random() * currentIndex);
-          currentIndex--;
+            // Pick a remaining element...
+            randomIndex = Math.floor(Math.random() * currentIndex);
+            currentIndex--;
 
-          // And swap it with the current element.
-          [array[currentIndex], array[randomIndex]] = [
-            array[randomIndex], array[currentIndex]];
+            // And swap it with the current element.
+            [array[currentIndex], array[randomIndex]] = [
+                array[randomIndex], array[currentIndex]];
         }
 
         return array;
@@ -192,23 +195,33 @@ class WelcomeMessage {
 
     async update() {
         // console.log('update')
+        const elem_chatbot = document.getElementById('gpt-chatbot');
+        const chatbot_top = elem_chatbot.getBoundingClientRect().top;
+        const welcome_card_container = document.getElementsByClassName('welcome-card-container')[0];
+        let welcome_card_overflow = false;
+        if (welcome_card_container) {
+            const welcome_card_top = welcome_card_container.getBoundingClientRect().top;
+            if (welcome_card_top < chatbot_top) {
+                welcome_card_overflow = true;
+                // console.log("welcome_card_overflow");
+            }
+        }
         var page_width = document.documentElement.clientWidth;
         const width_to_hide_welcome = 1200;
-        if (!await this.isChatbotEmpty() || page_width < width_to_hide_welcome) {
+        if (!await this.isChatbotEmpty() || page_width < width_to_hide_welcome || welcome_card_overflow) {
             if (this.visible) {
-                this.removeWelcome();
-                this.visible = false;
+                console.log("remove welcome");
+                this.removeWelcome(); this.visible = false; // this two lines must always be together
                 this.card_array = [];
                 this.static_welcome_message_previous = [];
             }
             return;
         }
-        if (this.visible){
+        if (this.visible) {
             return;
         }
-        // console.log("welcome");
-        this.showWelcome();
-        this.visible = true;
+        console.log("show welcome");
+        this.showWelcome(); this.visible = true; // this two lines must always be together
         this.startRefleshCards();
     }
 
@@ -220,28 +233,28 @@ class WelcomeMessage {
         const title = document.createElement('div');
         title.classList.add('welcome-card-title');
 
-            // 创建图标
-            const svg = document.createElement('img');
-            svg.classList.add('welcome-svg');
-            svg.src = message.svg;
-            svg.style.height = '30px';
-            title.appendChild(svg);
+        // 创建图标
+        const svg = document.createElement('img');
+        svg.classList.add('welcome-svg');
+        svg.src = message.svg;
+        svg.style.height = '30px';
+        title.appendChild(svg);
 
-            // 创建标题
-            const text = document.createElement('a');
-            text.textContent = message.title;
-            text.classList.add('welcome-title-text');
-            text.href = message.url;
-            text.target = "_blank";
-            title.appendChild(text)
+        // 创建标题
+        const text = document.createElement('a');
+        text.textContent = message.title;
+        text.classList.add('welcome-title-text');
+        text.href = message.url;
+        text.target = "_blank";
+        title.appendChild(text)
 
         // 创建内容
         const content = document.createElement('div');
         content.classList.add('welcome-content');
-            const content_c = document.createElement('div');
-            content_c.classList.add('welcome-content-c');
-            content_c.textContent = message.content;
-            content.appendChild(content_c);
+        const content_c = document.createElement('div');
+        content_c.classList.add('welcome-content-c');
+        content_c.textContent = message.content;
+        content.appendChild(content_c);
 
         // 将标题和内容添加到卡片 div 中
         card.appendChild(title);
@@ -307,28 +320,28 @@ class WelcomeMessage {
 
 class PageFocusHandler {
     constructor() {
-      this.hasReturned = false;
-      this.focusCallbacks = [];
+        this.hasReturned = false;
+        this.focusCallbacks = [];
 
-      // Bind the focus and blur event handlers
-      window.addEventListener('visibilitychange', this.handleFocus.bind(this));
+        // Bind the focus and blur event handlers
+        window.addEventListener('visibilitychange', this.handleFocus.bind(this));
     }
 
     // Method to handle the focus event
     handleFocus() {
-      if (this.hasReturned) {
-        this.focusCallbacks.forEach(callback => callback());
-      }
-      this.hasReturned = true;
+        if (this.hasReturned) {
+            this.focusCallbacks.forEach(callback => callback());
+        }
+        this.hasReturned = true;
     }
 
     // Method to add a custom callback function
     addFocusCallback(callback) {
-      if (typeof callback === 'function') {
-        this.focusCallbacks.push(callback);
-      } else {
-        throw new Error('Callback must be a function');
-      }
+        if (typeof callback === 'function') {
+            this.focusCallbacks.push(callback);
+        } else {
+            throw new Error('Callback must be a function');
+        }
     }
 }
 

toolbox.py

@@ -8,6 +8,7 @@ import base64
 import gradio
 import shutil
 import glob
+import json
 import uuid
 from loguru import logger
 from functools import wraps
@@ -92,8 +93,9 @@ def ArgsGeneralWrapper(f):
     """
     def decorated(request: gradio.Request, cookies:dict, max_length:int, llm_model:str,
                   txt:str, txt2:str, top_p:float, temperature:float, chatbot:list,
-                  history:list, system_prompt:str, plugin_advanced_arg:dict, *args):
+                  json_history:str, system_prompt:str, plugin_advanced_arg:dict, *args):
         txt_passon = txt
+        history = json.loads(json_history) if json_history else []
         if txt == "" and txt2 != "": txt_passon = txt2
         # 引入一个有cookie的chatbot
         if request.username is not None:
@@ -148,10 +150,11 @@ def ArgsGeneralWrapper(f):
     return decorated
 
 
-def update_ui(chatbot:ChatBotWithCookies, history, msg="正常", **kwargs):  # 刷新界面
+def update_ui(chatbot:ChatBotWithCookies, history:list, msg:str="正常", **kwargs):  # 刷新界面
     """
     刷新用户界面
     """
+    assert isinstance(history, list), "history必须是一个list"
     assert isinstance(
         chatbot, ChatBotWithCookies
     ), "在传递chatbot的过程中不要将其丢弃。必要时, 可用clear将其清空, 然后用for+append循环重新赋值。"
@@ -175,10 +178,11 @@ def update_ui(chatbot:ChatBotWithCookies, history, msg="正常", **kwargs):  #
     else:
         chatbot_gr = chatbot
 
-    yield cookies, chatbot_gr, history, msg
+    json_history = json.dumps(history, ensure_ascii=False)
+    yield cookies, chatbot_gr, json_history, msg
 
 
-def update_ui_lastest_msg(lastmsg:str, chatbot:ChatBotWithCookies, history:list, delay=1, msg="正常"):  # 刷新界面
+def update_ui_lastest_msg(lastmsg:str, chatbot:ChatBotWithCookies, history:list, delay:float=1, msg:str="正常"):  # 刷新界面
     """
     刷新用户界面
     """

version

@@ -1,5 +1,5 @@
 {
-  "version": 3.90,
+  "version": 3.91,
   "show_feature": true,
-  "new_feature": "增加RAG组件 <-> 升级多合一主提交键"
+  "new_feature": "优化前端并修复TTS的BUG <-> 添加时间线回溯功能 <-> 支持chatgpt-4o-latest <-> 增加RAG组件 <-> 升级多合一主提交键"
 }