Merge pull request #881 from OverKit/master

update latex_utils.py
add item breaker
2025-12-06 14:36:48 +00:00 · 2023-06-27 19:20:17 +08:00 · 2023-06-27 19:16:05 +08:00 · 2023-06-27 18:59:56 +08:00 · 2023-06-27 16:14:12 +08:00 · 2023-06-27 15:03:15 +08:00
--- a/.github/workflows/build-with-latex.yml
+++ b/.github/workflows/build-with-latex.yml
@@ -0,0 +1,44 @@
+# https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
+name: Create and publish a Docker image for Latex support
+
+on:
+  push:
+    branches:
+      - 'master'
+
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME: ${{ github.repository }}_with_latex
+
+jobs:
+  build-and-push-image:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Log in to the Container registry
+        uses: docker/login-action@v2
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@v4
+        with:
+          images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          push: true
+          file: docs/GithubAction+NoLocal+Latex
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
--- a/README.md
+++ b/README.md
@@ -16,7 +16,7 @@ To translate this project to arbitary language with GPT, read and run [`multi_la
 >
 > 1.请注意只有**红颜色**标识的函数插件（按钮）才支持读取文件，部分插件位于插件区的**下拉菜单**中。另外我们以**最高优先级**欢迎和处理任何新插件的PR！
 >
-> 2.本项目中每个文件的功能都在自译解[`self_analysis.md`](https://github.com/binary-husky/chatgpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A)详细说明。随着版本的迭代，您也可以随时自行点击相关函数插件，调用GPT重新生成项目的自我解析报告。常见问题汇总在[`wiki`](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98)当中。[安装方法](#installation)。
+> 2.本项目中每个文件的功能都在自译解[`self_analysis.md`](https://github.com/binary-husky/gpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A)详细说明。随着版本的迭代，您也可以随时自行点击相关函数插件，调用GPT重新生成项目的自我解析报告。常见问题汇总在[`wiki`](https://github.com/binary-husky/gpt_academic/wiki/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98)当中。[安装方法](#installation)。
 > 
 > 3.本项目兼容并鼓励尝试国产大语言模型chatglm和RWKV, 盘古等等。支持多个api-key共存，可在配置文件中填写如`API_KEY="openai-key1,openai-key2,api2d-key3"`。需要临时更换`API_KEY`时，在输入区输入临时的`API_KEY`然后回车键提交后即可生效。

@@ -31,13 +31,13 @@ To translate this project to arbitary language with GPT, read and run [`multi_la
 一键中英互译 | 一键中英互译
 一键代码解释 | 显示代码、解释代码、生成代码、给代码加注释
 [自定义快捷键](https://www.bilibili.com/video/BV14s4y1E7jN) | 支持自定义快捷键
-模块化设计 | 支持自定义强大的[函数插件](https://github.com/binary-husky/chatgpt_academic/tree/master/crazy_functions)，插件支持[热更新](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
-[自我程序剖析](https://www.bilibili.com/video/BV1cj411A7VW) | [函数插件] [一键读懂](https://github.com/binary-husky/chatgpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A)本项目的源代码
+模块化设计 | 支持自定义强大的[函数插件](https://github.com/binary-husky/gpt_academic/tree/master/crazy_functions)，插件支持[热更新](https://github.com/binary-husky/gpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
+[自我程序剖析](https://www.bilibili.com/video/BV1cj411A7VW) | [函数插件] [一键读懂](https://github.com/binary-husky/gpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A)本项目的源代码
 [程序剖析](https://www.bilibili.com/video/BV1cj411A7VW) | [函数插件] 一键可以剖析其他Python/C/C++/Java/Lua/...项目树
 读论文、[翻译](https://www.bilibili.com/video/BV1KT411x7Wn)论文 | [函数插件] 一键解读latex/pdf论文全文并生成摘要
 Latex全文[翻译](https://www.bilibili.com/video/BV1nk4y1Y7Js/)、[润色](https://www.bilibili.com/video/BV1FT411H7c5/) | [函数插件] 一键翻译或润色latex论文
 批量注释生成 | [函数插件] 一键批量生成函数注释
-Markdown[中英互译](https://www.bilibili.com/video/BV1yo4y157jV/) | [函数插件] 看到上面5种语言的[README](https://github.com/binary-husky/chatgpt_academic/blob/master/docs/README_EN.md)了吗？
+Markdown[中英互译](https://www.bilibili.com/video/BV1yo4y157jV/) | [函数插件] 看到上面5种语言的[README](https://github.com/binary-husky/gpt_academic/blob/master/docs/README_EN.md)了吗？
 chat分析报告生成 | [函数插件] 运行后自动生成总结汇报
 [PDF论文全文翻译功能](https://www.bilibili.com/video/BV1KT411x7Wn) | [函数插件] PDF论文提取题目&摘要+翻译全文（多线程）
 [Arxiv小助手](https://www.bilibili.com/video/BV1LM4y1279X) | [函数插件] 输入arxiv文章url即可一键翻译摘要+下载PDF
@@ -46,8 +46,8 @@ chat分析报告生成 | [函数插件] 运行后自动生成总结汇报
 ⭐Arxiv论文精细翻译 | [函数插件] 一键[以超高质量翻译arxiv论文](https://www.bilibili.com/video/BV1dz4y1v77A/)，迄今为止最好的论文翻译工具⭐
 公式/图片/表格显示 | 可以同时显示公式的[tex形式和渲染形式](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png)，支持公式、代码高亮
 多线程函数插件支持 | 支持多线调用chatgpt，一键处理[海量文本](https://www.bilibili.com/video/BV1FT411H7c5/)或程序
-启动暗色gradio[主题](https://github.com/binary-husky/chatgpt_academic/issues/173) | 在浏览器url后面添加```/?__theme=dark```可以切换dark主题
-[多LLM模型](https://www.bilibili.com/video/BV1wT411p7yf)支持，[API2D](https://api2d.com/)接口支持 | 同时被GPT3.5、GPT4、[清华ChatGLM](https://github.com/THUDM/ChatGLM-6B)、[复旦MOSS](https://github.com/OpenLMLab/MOSS)同时伺候的感觉一定会很不错吧？
+启动暗色gradio[主题](https://github.com/binary-husky/gpt_academic/issues/173) | 在浏览器url后面添加```/?__theme=dark```可以切换dark主题
+[多LLM模型](https://www.bilibili.com/video/BV1wT411p7yf)支持 | 同时被GPT3.5、GPT4、[清华ChatGLM](https://github.com/THUDM/ChatGLM-6B)、[复旦MOSS](https://github.com/OpenLMLab/MOSS)同时伺候的感觉一定会很不错吧？
 更多LLM模型接入，支持[huggingface部署](https://huggingface.co/spaces/qingxu98/gpt-academic) | 加入Newbing接口(新必应)，引入清华[Jittorllms](https://github.com/Jittor/JittorLLMs)支持[LLaMA](https://github.com/facebookresearch/llama)，[RWKV](https://github.com/BlinkDL/ChatRWKV)和[盘古α](https://openi.org.cn/pangu/)
 更多新功能展示(图像生成等) …… | 见本文档结尾处 ……

@@ -91,13 +91,13 @@ chat分析报告生成 | [函数插件] 运行后自动生成总结汇报

 1. 下载项目
 ```sh
-git clone https://github.com/binary-husky/chatgpt_academic.git
-cd chatgpt_academic
+git clone https://github.com/binary-husky/gpt_academic.git
+cd gpt_academic
 ```

 2. 配置API_KEY

-在`config.py`中，配置API KEY等设置，[特殊网络环境设置](https://github.com/binary-husky/gpt_academic/issues/1) 。
+在`config.py`中，配置API KEY等设置，[点击查看特殊网络环境设置方法](https://github.com/binary-husky/gpt_academic/issues/1) 。

 (P.S. 程序运行时会优先检查是否存在名为`config_private.py`的私密配置文件，并用其中的配置覆盖`config.py`的同名配置。因此，如果您能理解我们的配置读取逻辑，我们强烈建议您在`config.py`旁边创建一个名为`config_private.py`的新配置文件，并把`config.py`中的配置转移（复制）到`config_private.py`中。`config_private.py`不受git管控，可以让您的隐私信息更加安全。P.S.项目同样支持通过`环境变量`配置大多数选项，环境变量的书写格式参考`docker-compose`文件。读取优先级: `环境变量` > `config_private.py` > `config.py`)

@@ -113,6 +113,7 @@ conda activate gptac_venv                 # 激活anaconda环境
 python -m pip install -r requirements.txt # 这个步骤和pip安装一样的步骤
 ```

+
 <details><summary>如果需要支持清华ChatGLM/复旦MOSS作为后端，请点击展开此处</summary>
 <p>

@@ -139,19 +140,13 @@ AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-
 python main.py
 ```

-5. 测试函数插件
-```
- 测试函数插件模板函数（要求gpt回答历史上的今天发生了什么），您可以根据此函数为模板，实现更复杂的功能
-    点击 "[函数插件模板Demo] 历史上的今天"
-```
-
 ## 安装-方法2：使用Docker

-1. 仅ChatGPT（推荐大多数人选择）
+1. 仅ChatGPT（推荐大多数人选择，等价于docker-compose方案1）

 ``` sh
-git clone https://github.com/binary-husky/chatgpt_academic.git  # 下载项目
-cd chatgpt_academic                                 # 进入路径
+git clone https://github.com/binary-husky/gpt_academic.git  # 下载项目
+cd gpt_academic                                 # 进入路径
 nano config.py                                      # 用任意文本编辑器编辑config.py, 配置 “Proxy”， “API_KEY” 以及 “WEB_PORT” (例如50923) 等
 docker build -t gpt-academic .                      # 安装

@@ -160,40 +155,43 @@ docker run --rm -it --net=host gpt-academic
 #（最后一步-选择2）在macOS/windows环境下，只能用-p选项将容器上的端口(例如50923)暴露给主机上的端口
 docker run --rm -it -e WEB_PORT=50923 -p 50923:50923 gpt-academic
 ```
+P.S. 如果需要依赖Latex的插件功能，请见Wiki。另外，您也可以直接使用docker-compose获取Latex功能（修改docker-compose.yml，保留方案4并删除其他方案）。

 2. ChatGPT + ChatGLM + MOSS（需要熟悉Docker）

 ``` sh
-# 修改docker-compose.yml，删除方案1和方案3，保留方案2。修改docker-compose.yml中方案2的配置，参考其中注释即可
+# 修改docker-compose.yml，保留方案2并删除其他方案。修改docker-compose.yml中方案2的配置，参考其中注释即可
 docker-compose up
 ```

 3. ChatGPT + LLAMA + 盘古 + RWKV（需要熟悉Docker）
 ``` sh
-# 修改docker-compose.yml，删除方案1和方案2，保留方案3。修改docker-compose.yml中方案3的配置，参考其中注释即可
+# 修改docker-compose.yml，保留方案3并删除其他方案。修改docker-compose.yml中方案3的配置，参考其中注释即可
 docker-compose up
 ```


 ## 安装-方法3：其他部署姿势
 1. 一键运行脚本。
-完全不熟悉python环境的Windows用户可以下载[Release](https://github.com/binary-husky/gpt_academic/releases)中发布的一键运行脚本安装无本地模型的版本，
-不建议电脑上已有python的用户采用此方法（在此基础上安装插件的依赖很麻烦）。
+完全不熟悉python环境的Windows用户可以下载[Release](https://github.com/binary-husky/gpt_academic/releases)中发布的一键运行脚本安装无本地模型的版本。
 脚本的贡献来源是[oobabooga](https://github.com/oobabooga/one-click-installers)。

 2. 使用docker-compose运行。
 请阅读docker-compose.yml后，按照其中的提示操作即可

-3. 如何使用反代URL/微软云AzureAPI。
+3. 如何使用反代URL
 按照`config.py`中的说明配置API_URL_REDIRECT即可。

-4. 远程云服务器部署（需要云服务器知识与经验）。
-请访问[部署wiki-1](https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BA%91%E6%9C%8D%E5%8A%A1%E5%99%A8%E8%BF%9C%E7%A8%8B%E9%83%A8%E7%BD%B2%E6%8C%87%E5%8D%97)
+4. 微软云AzureAPI
+按照`config.py`中的说明配置即可（AZURE_ENDPOINT等四个配置）

-5. 使用WSL2（Windows Subsystem for Linux 子系统）。
-请访问[部署wiki-2](https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BD%BF%E7%94%A8WSL2%EF%BC%88Windows-Subsystem-for-Linux-%E5%AD%90%E7%B3%BB%E7%BB%9F%EF%BC%89%E9%83%A8%E7%BD%B2)
+5. 远程云服务器部署（需要云服务器知识与经验）。
+请访问[部署wiki-1](https://github.com/binary-husky/gpt_academic/wiki/%E4%BA%91%E6%9C%8D%E5%8A%A1%E5%99%A8%E8%BF%9C%E7%A8%8B%E9%83%A8%E7%BD%B2%E6%8C%87%E5%8D%97)

-6. 如何在二级网址（如`http://localhost/subpath`）下运行。
+6. 使用WSL2（Windows Subsystem for Linux 子系统）。
+请访问[部署wiki-2](https://github.com/binary-husky/gpt_academic/wiki/%E4%BD%BF%E7%94%A8WSL2%EF%BC%88Windows-Subsystem-for-Linux-%E5%AD%90%E7%B3%BB%E7%BB%9F%EF%BC%89%E9%83%A8%E7%BD%B2)
+
+7. 如何在二级网址（如`http://localhost/subpath`）下运行。
 请访问[FastAPI运行说明](docs/WithFastapi.md)

 ---
@@ -220,7 +218,7 @@ docker-compose up

 编写强大的函数插件来执行任何你想得到的和想不到的任务。
 本项目的插件编写、调试难度很低，只要您具备一定的python基础知识，就可以仿照我们提供的模板实现自己的插件功能。
-详情请参考[函数插件指南](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)。
+详情请参考[函数插件指南](https://github.com/binary-husky/gpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)。

 ---
 # Latest Update
@@ -228,7 +226,7 @@ docker-compose up

 1. 对话保存功能。在函数插件区调用 `保存当前的对话` 即可将当前对话保存为可读+可复原的html文件，
 另外在函数插件区（下拉菜单）调用 `载入对话历史存档` ，即可还原之前的会话。
-Tip：不指定文件直接点击 `载入对话历史存档` 可以查看历史html存档缓存，点击 `删除所有本地对话历史记录` 可以删除所有html存档缓存。
+Tip：不指定文件直接点击 `载入对话历史存档` 可以查看历史html存档缓存。
 <div align="center">
 <img src="https://user-images.githubusercontent.com/96192199/235222390-24a9acc0-680f-49f5-bc81-2f3161f1e049.png" width="500" >
 </div>
@@ -251,38 +249,33 @@ Tip：不指定文件直接点击 `载入对话历史存档` 可以查看历史h
 <img src="https://user-images.githubusercontent.com/96192199/227504931-19955f78-45cd-4d1c-adac-e71e50957915.png" height="400" >
 </div>

-5. 这是一个能够“自我译解”的开源项目
-<div align="center">
-<img src="https://user-images.githubusercontent.com/96192199/226936850-c77d7183-0749-4c1c-9875-fd4891842d0c.png" width="500" >
-</div>
-
-6. 译解其他开源项目，不在话下
+5. 译解其他开源项目
 <div align="center">
 <img src="https://user-images.githubusercontent.com/96192199/226935232-6b6a73ce-8900-4aee-93f9-733c7e6fef53.png" height="250" >
 <img src="https://user-images.githubusercontent.com/96192199/226969067-968a27c1-1b9c-486b-8b81-ab2de8d3f88a.png" height="250" >
 </div>

-7. 装饰[live2d](https://github.com/fghrsh/live2d_demo)的小功能（默认关闭，需要修改`config.py`）
+6. 装饰[live2d](https://github.com/fghrsh/live2d_demo)的小功能（默认关闭，需要修改`config.py`）
 <div align="center">
 <img src="https://user-images.githubusercontent.com/96192199/236432361-67739153-73e8-43fe-8111-b61296edabd9.png" width="500" >
 </div>

-8. 新增MOSS大语言模型支持
+7. 新增MOSS大语言模型支持
 <div align="center">
 <img src="https://user-images.githubusercontent.com/96192199/236639178-92836f37-13af-4fdd-984d-b4450fe30336.png" width="500" >
 </div>

-9. OpenAI图像生成
+8. OpenAI图像生成
 <div align="center">
 <img src="https://github.com/binary-husky/gpt_academic/assets/96192199/bc7ab234-ad90-48a0-8d62-f703d9e74665" width="500" >
 </div>

-10. OpenAI音频解析与总结
+9. OpenAI音频解析与总结
 <div align="center">
 <img src="https://github.com/binary-husky/gpt_academic/assets/96192199/709ccf95-3aee-498a-934a-e1c22d3d5d5b" width="500" >
 </div>

-11. Latex全文校对纠错
+10. Latex全文校对纠错
 <div align="center">
 <img src="https://github.com/binary-husky/gpt_academic/assets/96192199/651ccd98-02c9-4464-91e1-77a6b7d1b033" height="200" > ===>
 <img src="https://github.com/binary-husky/gpt_academic/assets/96192199/476f66d9-7716-4537-b5c1-735372c25adb" height="200">
@@ -310,30 +303,32 @@ gpt_academic开发者QQ群-2：610599535

 - 已知问题
    - 某些浏览器翻译插件干扰此软件前端的运行
-    - 官方Gradio目前有很多兼容性Bug，请务必使用requirement.txt安装Gradio
+    - 官方Gradio目前有很多兼容性Bug，请务必使用`requirement.txt`安装Gradio

 ## 参考与学习

 ```
-代码中参考了很多其他优秀项目中的设计，主要包括：
+代码中参考了很多其他优秀项目中的设计，顺序不分先后：

-# 项目1：清华ChatGLM-6B:
+# 清华ChatGLM-6B:
 https://github.com/THUDM/ChatGLM-6B

-# 项目2：清华JittorLLMs:
+# 清华JittorLLMs:
 https://github.com/Jittor/JittorLLMs

-# 项目3：Edge-GPT:
-https://github.com/acheong08/EdgeGPT
-
-# 项目4：ChuanhuChatGPT:
-https://github.com/GaiZhenbiao/ChuanhuChatGPT
-
-# 项目5：ChatPaper:
+# ChatPaper:
 https://github.com/kaixindelele/ChatPaper

-# 更多：
+# Edge-GPT:
+https://github.com/acheong08/EdgeGPT
+
+# ChuanhuChatGPT:
+https://github.com/GaiZhenbiao/ChuanhuChatGPT
+
+# Oobabooga one-click installer:
+https://github.com/oobabooga/one-click-installers
+
+# More：
 https://github.com/gradio-app/gradio
 https://github.com/fghrsh/live2d_demo
-https://github.com/oobabooga/one-click-installers
 ```
--- a/config.py
+++ b/config.py
@@ -1,6 +1,7 @@
 # [step 1]>> 例如： API_KEY = "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" （此key无效）
 API_KEY = "sk-此处填API密钥"    # 可同时填写多个API-KEY，用英文逗号分割，例如API_KEY = "sk-openaikey1,sk-openaikey2,fkxxxx-api2dkey1,fkxxxx-api2dkey2"

+
 # [step 2]>> 改为True应用代理，如果直接在海外服务器部署，此处不修改
 USE_PROXY = False
 if USE_PROXY:
@@ -46,8 +47,8 @@ MAX_RETRY = 2

 # 模型选择是 (注意: LLM_MODEL是默认选中的模型, 同时它必须被包含在AVAIL_LLM_MODELS切换列表中 )
 LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
-AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "newbing-free", "stack-claude"]
-# P.S. 其他可用的模型还包括 ["newbing-free", "jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
+AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt35", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "newbing-free", "stack-claude"]
+# P.S. 其他可用的模型还包括 ["gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", "newbing-free", "jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]

 # 本地LLM模型如ChatGLM的执行方式 CPU/GPU
 LOCAL_MODEL_DEVICE = "cpu" # 可选 "cuda"
@@ -81,3 +82,10 @@ your bing cookies here
 # 如果需要使用Slack Claude，使用教程详情见 request_llm/README.md
 SLACK_CLAUDE_BOT_ID = ''   
 SLACK_CLAUDE_USER_TOKEN = ''
+
+
+# 如果需要使用AZURE 详情请见额外文档 docs\use_azure.md
+AZURE_ENDPOINT = "https://你的api名称.openai.azure.com/"
+AZURE_API_KEY = "填入azure openai api的密钥"
+AZURE_API_VERSION = "填入api版本"
+AZURE_ENGINE = "填入ENGINE"
--- a/crazy_functional.py
+++ b/crazy_functional.py
@@ -112,11 +112,11 @@ def get_crazy_functions():
            "AsButton": False,  # 加入下拉菜单中
            "Function": HotReload(解析项目本身)
        },
-        "[老旧的Demo] 把本项目源代码切换成全英文": {
-            # HotReload 的意思是热更新，修改函数插件代码后，不需要重启程序，代码直接生效
-            "AsButton": False,  # 加入下拉菜单中
-            "Function": HotReload(全项目切换英文)
-        },
+        # "[老旧的Demo] 把本项目源代码切换成全英文": {
+        #     # HotReload 的意思是热更新，修改函数插件代码后，不需要重启程序，代码直接生效
+        #     "AsButton": False,  # 加入下拉菜单中
+        #     "Function": HotReload(全项目切换英文)
+        # },
        "[插件demo] 历史上的今天": {
            # HotReload 的意思是热更新，修改函数插件代码后，不需要重启程序，代码直接生效
            "Function": HotReload(高阶功能模板函数)
@@ -358,15 +358,42 @@ def get_crazy_functions():
        })
        from crazy_functions.Latex输出PDF结果 import Latex翻译中文并重新编译PDF
        function_plugins.update({
-            "[功能尚不稳定] Latex翻译/Arixv翻译+重构PDF": {
+            "Arixv翻译（输入arxivID） [需Latex]": {
                "Color": "stop",
                "AsButton": False,
-                # "AdvancedArgs": True,
-                # "ArgsReminder": "",
+                "AdvancedArgs": True,
+                "ArgsReminder": 
+                    "如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 "+ 
+                    "例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: " + 'If the term "agent" is used in this section, it should be translated to "智能体". ',
                "Function": HotReload(Latex翻译中文并重新编译PDF)
            }
        })
+        # function_plugins.update({
+        #     "本地论文翻译（上传Latex压缩包） [需Latex]": {
+        #         "Color": "stop",
+        #         "AsButton": False,
+        #         "AdvancedArgs": True,
+        #         "ArgsReminder": 
+        #             "如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 "+ 
+        #             "例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: " + 'If the term "agent" is used in this section, it should be translated to "智能体". ',
+        #         "Function": HotReload(Latex翻译中文并重新编译PDF)
+        #     }
+        # })
    except:
        print('Load function plugin failed')
-    ###################### 第n组插件 ###########################
+
+    # try:
+    #     from crazy_functions.虚空终端 import 终端
+    #     function_plugins.update({
+    #         "超级终端": {
+    #             "Color": "stop",
+    #             "AsButton": False,
+    #             # "AdvancedArgs": True,
+    #             # "ArgsReminder": "",
+    #             "Function": HotReload(终端)
+    #         }
+    #     })
+    # except:
+    #     print('Load function plugin failed')
+
    return function_plugins
--- a/crazy_functions/Langchain知识库.py
+++ b/crazy_functions/Langchain知识库.py
@@ -30,7 +30,7 @@ def 知识库问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
        )
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        from .crazy_utils import try_install_deps
-        try_install_deps(['zh_langchain==0.2.0'])
+        try_install_deps(['zh_langchain==0.2.1'])
    
    # < --------------------读取参数--------------- >
    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
@@ -84,7 +84,7 @@ def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
        chatbot.append(["依赖不足", "导入依赖失败。正在尝试自动安装，请查看终端的输出或耐心等待..."])
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
        from .crazy_utils import try_install_deps
-        try_install_deps(['zh_langchain==0.2.0'])
+        try_install_deps(['zh_langchain==0.2.1'])

    # < -------------------  --------------- >
    kai = knowledge_archive_interface()
--- a/crazy_functions/Latex输出PDF结果.py
+++ b/crazy_functions/Latex输出PDF结果.py
@@ -1,12 +1,13 @@
 from toolbox import update_ui, trimmed_format_exc, get_conf, objdump, objload, promote_file_to_downloadzone
 from toolbox import CatchException, report_execption, update_ui_lastest_msg, zip_result, gen_time_str
+from functools import partial
 import glob, os, requests, time
 pj = os.path.join
 ARXIV_CACHE_DIR = os.path.expanduser(f"~/arxiv_cache/")

 # =================================== 工具函数 ===============================================
-沙雕GPT啊别犯这些低级翻译错误  = 'You must to translate "agent" to "智能体". '
-def switch_prompt(pfg, mode):
+专业词汇声明  = 'If the term "agent" is used in this section, it should be translated to "智能体". '
+def switch_prompt(pfg, mode, more_requirement):
    """
    Generate prompts and system prompts based on the mode for proofreading or translating.
    Args:
@@ -25,7 +26,7 @@ def switch_prompt(pfg, mode):
                        f"\n\n{frag}" for frag in pfg.sp_file_contents]
        sys_prompt_array = ["You are a professional academic paper writer." for _ in range(n_split)]
    elif mode == 'translate_zh':
-        inputs_array = [r"Below is a section from an English academic paper, translate it into Chinese." + 沙雕GPT啊别犯这些低级翻译错误 + 
+        inputs_array = [r"Below is a section from an English academic paper, translate it into Chinese. " + more_requirement + 
                        r"Do not modify any latex command such as \section, \cite, \begin, \item and equations. " + 
                        r"Answer me only with the translated text:" + 
                        f"\n\n{frag}" for frag in pfg.sp_file_contents]
@@ -79,7 +80,7 @@ def arxiv_download(chatbot, history, txt):
            os.makedirs(translation_dir)
        target_file = pj(translation_dir, 'translate_zh.pdf')
        if os.path.exists(target_file):
-            promote_file_to_downloadzone(target_file)
+            promote_file_to_downloadzone(target_file, rename_file=None, chatbot=chatbot)
            return target_file
        return False
    def is_float(s):
@@ -88,8 +89,10 @@ def arxiv_download(chatbot, history, txt):
            return True
        except ValueError:
            return False
-    if ('.' in txt) and ('/' not in txt) and is_float(txt):
-        txt = 'https://arxiv.org/abs/' + txt
+    if ('.' in txt) and ('/' not in txt) and is_float(txt): # is arxiv ID
+        txt = 'https://arxiv.org/abs/' + txt.strip()
+    if ('.' in txt) and ('/' not in txt) and is_float(txt[:10]): # is arxiv ID
+        txt = 'https://arxiv.org/abs/' + txt[:10]
    if not txt.startswith('https://arxiv.org'): 
        return txt, None
    
@@ -105,6 +108,7 @@ def arxiv_download(chatbot, history, txt):
        return msg, None
    # <-------------- set format ------------->
    arxiv_id = url_.split('/abs/')[-1]
+    if 'v' in arxiv_id: arxiv_id = arxiv_id[:10]
    cached_translation_pdf = check_cached_translation_pdf(arxiv_id)
    if cached_translation_pdf: return cached_translation_pdf, arxiv_id

@@ -177,7 +181,8 @@ def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, histo

    # <-------------- if merge_translate_zh is already generated, skip gpt req ------------->
    if not os.path.exists(project_folder + '/merge_proofread.tex'):
-        yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='proofread_latex', switch_prompt=switch_prompt)
+        yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, 
+                                chatbot, history, system_prompt, mode='proofread_latex', switch_prompt=switch_prompt)


    # <-------------- compile PDF ------------->
@@ -186,13 +191,14 @@ def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, histo
    

    # <-------------- zip PDF ------------->
-    zip_result(project_folder)
+    zip_res = zip_result(project_folder)
    if success:
        chatbot.append((f"成功啦", '请查收结果（压缩包）...'))
        yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
    else:
        chatbot.append((f"失败了", '虽然PDF生成失败了, 但请查收结果（压缩包）, 内含已经翻译的Tex文档, 也是可读的, 您可以到Github Issue区, 用该压缩包+对话历史存档进行反馈 ...'))
        yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
+        promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)

    # <-------------- we are done ------------->
    return success
@@ -205,9 +211,13 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
    # <-------------- information about this plugin ------------->
    chatbot.append([
        "函数插件功能？",
-        "对整个Latex项目进行翻译, 生成中文PDF。函数插件贡献者: Binary-Husky。注意事项: 目前仅支持GPT3.5/GPT4，其他模型转化效果未知。目前对机器学习类文献转化效果最好，其他类型文献转化效果未知。"])
+        "对整个Latex项目进行翻译, 生成中文PDF。函数插件贡献者: Binary-Husky。注意事项: 此插件Windows支持最佳，Linux下必须使用Docker安装，详见项目主README.md。目前仅支持GPT3.5/GPT4，其他模型转化效果未知。目前对机器学习类文献转化效果最好，其他类型文献转化效果未知。"])
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

+    # <-------------- 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", "")
+    _switch_prompt_ = partial(switch_prompt, more_requirement=more_req)

    # <-------------- check deps ------------->
    try:
@@ -255,21 +265,23 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,

    # <-------------- if merge_translate_zh is already generated, skip gpt req ------------->
    if not os.path.exists(project_folder + '/merge_translate_zh.tex'):
-        yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='translate_zh', switch_prompt=switch_prompt)
+        yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, 
+                                chatbot, history, system_prompt, mode='translate_zh', switch_prompt=_switch_prompt_)


    # <-------------- compile PDF ------------->
-    success = yield from 编译Latex(chatbot, history, main_file_original='merge', main_file_modified='merge_translate_zh', 
+    success = yield from 编译Latex(chatbot, history, main_file_original='merge', main_file_modified='merge_translate_zh', mode='translate_zh', 
                             work_folder_original=project_folder, work_folder_modified=project_folder, work_folder=project_folder)

    # <-------------- zip PDF ------------->
-    zip_result(project_folder)
+    zip_res = zip_result(project_folder)
    if success:
        chatbot.append((f"成功啦", '请查收结果（压缩包）...'))
        yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
    else:
        chatbot.append((f"失败了", '虽然PDF生成失败了, 但请查收结果（压缩包）, 内含已经翻译的Tex文档, 也是可读的, 您可以到Github Issue区, 用该压缩包+对话历史存档进行反馈 ...'))
        yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
+        promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)


    # <-------------- we are done ------------->
--- a/crazy_functions/crazy_functions_test.py
+++ b/crazy_functions/crazy_functions_test.py
@@ -188,7 +188,15 @@ def test_Latex():
    # txt = r"https://arxiv.org/abs/2305.17608"
    # txt = r"https://arxiv.org/abs/2211.16068"                     #  ACE
    # txt = r"C:\Users\x\arxiv_cache\2211.16068\workfolder"  #  ACE
-    txt = r"https://arxiv.org/abs/2002.09253"
+    # txt = r"https://arxiv.org/abs/2002.09253"
+    # txt = r"https://arxiv.org/abs/2306.07831"
+    txt = r"https://arxiv.org/abs/2212.10156"
+    # txt = r"https://arxiv.org/abs/2211.11559"
+    # txt = r"https://arxiv.org/abs/2303.08774"
+    # txt = r"https://arxiv.org/abs/2303.12712"
+    # txt = r"C:\Users\fuqingxu\arxiv_cache\2303.12712\workfolder"
+    
+
    for cookies, cb, hist, msg in (Latex翻译中文并重新编译PDF)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
        cli_printer.print(cb)   #  print(cb)

@@ -217,6 +225,7 @@ def test_Latex():
 # test_数学动画生成manim()
 # test_Langchain知识库()
 # test_Langchain知识库读取()
-test_Latex()
-input("程序完成，回车退出。")
-print("退出。")
+if __name__ == "__main__":
+    test_Latex()
+    input("程序完成，回车退出。")
+    print("退出。")
--- a/crazy_functions/crazy_utils.py
+++ b/crazy_functions/crazy_utils.py
@@ -698,3 +698,51 @@ def try_install_deps(deps):
    for dep in deps:
        import subprocess, sys
        subprocess.check_call([sys.executable, '-m', 'pip', 'install', '--user', dep])
+
+
+class construct_html():
+    def __init__(self) -> None:
+        self.css = """
+.row {
+  display: flex;
+  flex-wrap: wrap;
+}
+
+.column {
+  flex: 1;
+  padding: 10px;
+}
+
+.table-header {
+  font-weight: bold;
+  border-bottom: 1px solid black;
+}
+
+.table-row {
+  border-bottom: 1px solid lightgray;
+}
+
+.table-cell {
+  padding: 5px;
+}
+        """
+        self.html_string = f'<!DOCTYPE html><head><meta charset="utf-8"><title>翻译结果</title><style>{self.css}</style></head>'
+
+
+    def add_row(self, a, b):
+        tmp = """
+<div class="row table-row">
+    <div class="column table-cell">REPLACE_A</div>
+    <div class="column table-cell">REPLACE_B</div>
+</div>
+        """
+        from toolbox import markdown_convertion
+        tmp = tmp.replace('REPLACE_A', markdown_convertion(a))
+        tmp = tmp.replace('REPLACE_B', markdown_convertion(b))
+        self.html_string += tmp
+
+
+    def save_file(self, file_name):
+        with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
+            f.write(self.html_string.encode('utf-8', 'ignore').decode())
+
--- a/crazy_functions/latex_utils.py
+++ b/crazy_functions/latex_utils.py
@@ -8,24 +8,31 @@ pj = os.path.join
 """
 ========================================================================
 Part One
-Latex segmentation to a linklist
+Latex segmentation with a binary mask (PRESERVE=0, TRANSFORM=1)
 ========================================================================
 """
 PRESERVE = 0
 TRANSFORM = 1

-def split_worker(text, mask, pattern, flags=0):
+def set_forbidden_text(text, mask, pattern, flags=0):
    """
    Add a preserve text area in this paper
+    e.g. with pattern = r"\\begin\{algorithm\}(.*?)\\end\{algorithm\}"
+    you can mask out (mask = PRESERVE so that text become untouchable for GPT) 
+    everything between "\begin{equation}" and "\end{equation}"
    """
+    if isinstance(pattern, list): pattern = '|'.join(pattern)
    pattern_compile = re.compile(pattern, flags)
    for res in pattern_compile.finditer(text):
        mask[res.span()[0]:res.span()[1]] = PRESERVE
    return text, mask

-def split_worker_careful_brace(text, mask, pattern, flags=0):
+def set_forbidden_text_careful_brace(text, mask, pattern, flags=0):
    """
-    Move area into preserve area 
+    Add a preserve text area in this paper (text become untouchable for GPT).
+    count the number of the braces so as to catch compelete text area. 
+    e.g.
+    \caption{blablablablabla\texbf{blablabla}blablabla.} 
    """
    pattern_compile = re.compile(pattern, flags)
    for res in pattern_compile.finditer(text):
@@ -40,9 +47,12 @@ def split_worker_careful_brace(text, mask, pattern, flags=0):
        mask[begin:end] = PRESERVE
    return text, mask

-def split_worker_reverse_careful_brace(text, mask, pattern, flags=0):
+def reverse_forbidden_text_careful_brace(text, mask, pattern, flags=0, forbid_wrapper=True):
    """
-    Move area out of preserve area 
+    Move area out of preserve area (make text editable for GPT)
+    count the number of the braces so as to catch compelete text area. 
+    e.g.
+    \caption{blablablablabla\texbf{blablabla}blablabla.} 
    """
    pattern_compile = re.compile(pattern, flags)
    for res in pattern_compile.finditer(text):
@@ -55,9 +65,12 @@ def split_worker_reverse_careful_brace(text, mask, pattern, flags=0):
            p += 1
        end = p
        mask[begin:end] = TRANSFORM
+        if forbid_wrapper:
+            mask[res.regs[0][0]:begin] = PRESERVE
+            mask[end:res.regs[0][1]] = PRESERVE
    return text, mask

-def split_worker_begin_end(text, mask, pattern, flags=0, limit_n_lines=42):
+def set_forbidden_text_begin_end(text, mask, pattern, flags=0, limit_n_lines=42):
    """
    Find all \begin{} ... \end{} text block that with less than limit_n_lines lines.
    Add it to preserve area
@@ -110,28 +123,51 @@ Latex Merge File
 def 寻找Latex主文件(file_manifest, mode):
    """
    在多Tex文档中，寻找主文件，必须包含documentclass，返回找到的第一个。
-    P.S. 但愿没人把latex模板放在里面传进来
+    P.S. 但愿没人把latex模板放在里面传进来 (6.25 加入判定latex模板的代码)
    """
+    canidates = []
    for texf in file_manifest:
        if os.path.basename(texf).startswith('merge'):
            continue
        with open(texf, 'r', encoding='utf8') as f:
            file_content = f.read()
        if r'\documentclass' in file_content:
-            return texf
+            canidates.append(texf)
        else:
            continue
-    raise RuntimeError('无法找到一个主Tex文件（包含documentclass关键字）')

+    if len(canidates) == 0:
+        raise RuntimeError('无法找到一个主Tex文件（包含documentclass关键字）')
+    elif len(canidates) == 1:
+        return canidates[0]
+    else: # if len(canidates) >= 2 通过一些Latex模板中常见（但通常不会出现在正文）的单词，对不同latex源文件扣分，取评分最高者返回
+        canidates_score = []
+        # 给出一些判定模板文档的词作为扣分项
+        unexpected_words = ['\LaTeX', 'manuscript', 'Guidelines', 'font', 'citations', 'rejected', 'blind review', 'reviewers']
+        expected_words = ['\input', '\ref', '\cite']
+        for texf in canidates:
+            canidates_score.append(0)
+            with open(texf, 'r', encoding='utf8') as f:
+                file_content = f.read()
+            for uw in unexpected_words:
+                if uw in file_content:
+                    canidates_score[-1] -= 1
+            for uw in expected_words:
+                if uw in file_content:
+                    canidates_score[-1] += 1
+        select = np.argmax(canidates_score) # 取评分最高者返回
+        return canidates[select]
+    
 def rm_comments(main_file):
    new_file_remove_comment_lines = []
    for l in main_file.splitlines():
        # 删除整行的空注释
-        if l.startswith("%") or (l.startswith(" ") and l.lstrip().startswith("%")):
+        if l.lstrip().startswith("%"):
            pass
        else:
            new_file_remove_comment_lines.append(l)
    main_file = '\n'.join(new_file_remove_comment_lines)
+    # main_file = re.sub(r"\\include{(.*?)}", r"\\input{\1}", main_file)  # 将 \include 命令转换为 \input 命令
    main_file = re.sub(r'(?<!\\)%.*', '', main_file)  # 使用正则表达式查找半行注释, 并替换为空字符串
    return main_file

@@ -165,17 +201,24 @@ def merge_tex_files(project_foler, main_file, mode):
    main_file = rm_comments(main_file)

    if mode == 'translate_zh':
+        # find paper documentclass
        pattern = re.compile(r'\\documentclass.*\n')
        match = pattern.search(main_file)
+        assert match is not None, "Cannot find documentclass statement!"
        position = match.end()
        add_ctex = '\\usepackage{ctex}\n'
        add_url = '\\usepackage{url}\n' if '{url}' not in main_file else ''
        main_file = main_file[:position] + add_ctex + add_url + main_file[position:]
-        # 2 fontset=windows
+        # fontset=windows
        import platform
-        if platform.system() != 'Windows':
-            main_file = re.sub(r"\\documentclass\[(.*?)\]{(.*?)}", r"\\documentclass[\1,fontset=windows]{\2}",main_file)
-            main_file = re.sub(r"\\documentclass{(.*?)}", r"\\documentclass[fontset=windows]{\1}",main_file)
+        main_file = re.sub(r"\\documentclass\[(.*?)\]{(.*?)}", r"\\documentclass[\1,fontset=windows,UTF8]{\2}",main_file)
+        main_file = re.sub(r"\\documentclass{(.*?)}", r"\\documentclass[fontset=windows,UTF8]{\1}",main_file)
+        # find paper abstract
+        pattern_opt1 = re.compile(r'\\begin\{abstract\}.*\n')
+        pattern_opt2 = re.compile(r"\\abstract\{(.*?)\}", flags=re.DOTALL)
+        match_opt1 = pattern_opt1.search(main_file)
+        match_opt2 = pattern_opt2.search(main_file)
+        assert (match_opt1 is not None) or (match_opt2 is not None), "Cannot find paper abstract section!"
    return main_file


@@ -207,6 +250,8 @@ def fix_content(final_tex, node_string):
    final_tex = re.sub(r"\\\ ([a-z]{2,10})\{", r"\\\1{", string=final_tex)
    final_tex = re.sub(r"\\([a-z]{2,10})\{([^\}]*?)\}", mod_inbraket, string=final_tex)

+    if "Traceback" in final_tex and "[Local Message]" in final_tex:
+        final_tex = node_string # 出问题了，还原原文
    if node_string.count('\\begin') != final_tex.count('\\begin'):
        final_tex = node_string # 出问题了，还原原文
    if node_string.count('\_') > 0 and node_string.count('\_') > final_tex.count('\_'):
@@ -254,45 +299,33 @@ def split_subprocess(txt, project_folder, return_dict, opts):
    mask = np.zeros(len(txt), dtype=np.uint8) + TRANSFORM

    # 吸收title与作者以上的部分
-    text, mask = split_worker(text, mask, r"(.*?)\\maketitle", re.DOTALL)
-    # 删除iffalse注释
-    text, mask = split_worker(text, mask, r"\\iffalse(.*?)\\fi", re.DOTALL)
-    # 吸收在25行以内的begin-end组合
-    text, mask = split_worker_begin_end(text, mask, r"\\begin\{([a-z\*]*)\}(.*?)\\end\{\1\}", re.DOTALL, limit_n_lines=25)
+    text, mask = set_forbidden_text(text, mask, r"(.*?)\\maketitle", re.DOTALL)
+    # 吸收iffalse注释
+    text, mask = set_forbidden_text(text, mask, r"\\iffalse(.*?)\\fi", re.DOTALL)
+    # 吸收在42行以内的begin-end组合
+    text, mask = set_forbidden_text_begin_end(text, mask, r"\\begin\{([a-z\*]*)\}(.*?)\\end\{\1\}", re.DOTALL, limit_n_lines=42)
    # 吸收匿名公式
-    text, mask = split_worker(text, mask, r"\$\$(.*?)\$\$", re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, [ r"\$\$(.*?)\$\$",  r"\\\[.*?\\\]" ], re.DOTALL)
    # 吸收其他杂项
-    text, mask = split_worker(text, mask, r"\\section\{(.*?)\}")
-    text, mask = split_worker(text, mask, r"\\section\*\{(.*?)\}")
-    text, mask = split_worker(text, mask, r"\\subsection\{(.*?)\}")
-    text, mask = split_worker(text, mask, r"\\subsubsection\{(.*?)\}")
-    text, mask = split_worker(text, mask, r"\\bibliography\{(.*?)\}")
-    text, mask = split_worker(text, mask, r"\\bibliographystyle\{(.*?)\}")
-    text, mask = split_worker(text, mask, r"\\begin\{lstlisting\}(.*?)\\end\{lstlisting\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{wraptable\}(.*?)\\end\{wraptable\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{algorithm\}(.*?)\\end\{algorithm\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{wrapfigure\}(.*?)\\end\{wrapfigure\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{wrapfigure\*\}(.*?)\\end\{wrapfigure\*\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{figure\}(.*?)\\end\{figure\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{figure\*\}(.*?)\\end\{figure\*\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{multline\}(.*?)\\end\{multline\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{multline\*\}(.*?)\\end\{multline\*\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{table\}(.*?)\\end\{table\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{table\*\}(.*?)\\end\{table\*\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{minipage\}(.*?)\\end\{minipage\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{minipage\*\}(.*?)\\end\{minipage\*\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{align\*\}(.*?)\\end\{align\*\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{align\}(.*?)\\end\{align\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{equation\}(.*?)\\end\{equation\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\begin\{equation\*\}(.*?)\\end\{equation\*\}", re.DOTALL)
-    text, mask = split_worker(text, mask, r"\\item ")
-    text, mask = split_worker(text, mask, r"\\label\{(.*?)\}")
-    text, mask = split_worker(text, mask, r"\\begin\{(.*?)\}")
-    text, mask = split_worker(text, mask, r"\\vspace\{(.*?)\}")
-    text, mask = split_worker(text, mask, r"\\hspace\{(.*?)\}")
-    text, mask = split_worker(text, mask, r"\\end\{(.*?)\}")
-    text, mask = split_worker_careful_brace(text, mask, r"\\hl\{(.*?)\}", re.DOTALL)
-    text, mask = split_worker_reverse_careful_brace(text, mask, r"\\caption\{(.*?)\}", re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, [ r"\\section\{(.*?)\}", r"\\section\*\{(.*?)\}", r"\\subsection\{(.*?)\}", r"\\subsubsection\{(.*?)\}" ])
+    text, mask = set_forbidden_text(text, mask, [ r"\\bibliography\{(.*?)\}", r"\\bibliographystyle\{(.*?)\}" ])
+    text, mask = set_forbidden_text(text, mask, r"\\begin\{thebibliography\}.*?\\end\{thebibliography\}", re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, r"\\begin\{lstlisting\}(.*?)\\end\{lstlisting\}", re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, r"\\begin\{wraptable\}(.*?)\\end\{wraptable\}", re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, r"\\begin\{algorithm\}(.*?)\\end\{algorithm\}", re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, [r"\\begin\{wrapfigure\}(.*?)\\end\{wrapfigure\}", r"\\begin\{wrapfigure\*\}(.*?)\\end\{wrapfigure\*\}"], re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, [r"\\begin\{figure\}(.*?)\\end\{figure\}", r"\\begin\{figure\*\}(.*?)\\end\{figure\*\}"], re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, [r"\\begin\{multline\}(.*?)\\end\{multline\}", r"\\begin\{multline\*\}(.*?)\\end\{multline\*\}"], re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, [r"\\begin\{table\}(.*?)\\end\{table\}", r"\\begin\{table\*\}(.*?)\\end\{table\*\}"], re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, [r"\\begin\{minipage\}(.*?)\\end\{minipage\}", r"\\begin\{minipage\*\}(.*?)\\end\{minipage\*\}"], re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, [r"\\begin\{align\*\}(.*?)\\end\{align\*\}", r"\\begin\{align\}(.*?)\\end\{align\}"], re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, [r"\\begin\{equation\}(.*?)\\end\{equation\}", r"\\begin\{equation\*\}(.*?)\\end\{equation\*\}"], re.DOTALL)
+    text, mask = set_forbidden_text(text, mask, [r"\\includepdf\[(.*?)\]\{(.*?)\}", r"\\clearpage", r"\\newpage", r"\\appendix", r"\\tableofcontents", r"\\include\{(.*?)\}"])
+    text, mask = set_forbidden_text(text, mask, [r"\\vspace\{(.*?)\}", r"\\hspace\{(.*?)\}", r"\\label\{(.*?)\}", r"\\begin\{(.*?)\}", r"\\end\{(.*?)\}", r"\\item "])
+    text, mask = set_forbidden_text_careful_brace(text, mask, r"\\hl\{(.*?)\}", re.DOTALL)
+    # reverse 操作必须放在最后
+    text, mask = reverse_forbidden_text_careful_brace(text, mask, r"\\caption\{(.*?)\}", re.DOTALL, forbid_wrapper=True)
+    text, mask = reverse_forbidden_text_careful_brace(text, mask, r"\\abstract\{(.*?)\}", re.DOTALL, forbid_wrapper=True)
    root = convert_to_linklist(text, mask)

    # 修复括号
@@ -366,7 +399,7 @@ def split_subprocess(txt, project_folder, return_dict, opts):
        prev_node = node
        node = node.next
        if node is None: break
-
+    # 输出html调试文件，用红色标注处保留区（PRESERVE），用黑色标注转换区（TRANSFORM）
    with open(pj(project_folder, 'debug_log.html'), 'w', encoding='utf8') as f:
        segment_parts_for_gpt = []
        nodes = []
@@ -398,7 +431,7 @@ class LatexPaperSplit():
    def __init__(self) -> None:
        self.nodes = None
        self.msg = "{\\scriptsize\\textbf{警告：该PDF由GPT-Academic开源项目调用大语言模型+Latex翻译插件一键生成，" + \
-            "版权归原文作者所有。翻译内容可靠性无任何保障，请仔细鉴别并以原文为准。" + \
+            "版权归原文作者所有。翻译内容可靠性无保障，请仔细鉴别并以原文为准。" + \
            "项目Github地址 \\url{https://github.com/binary-husky/gpt_academic/}。"
        # 请您不要删除或修改这行警告，除非您是论文的原作者（如果您是论文原作者，欢迎加REAME中的QQ联系开发者）
        self.msg_declare = "为了防止大语言模型的意外谬误产生扩散影响，禁止移除或修改此警告。}}\\\\" 
@@ -418,7 +451,14 @@ class LatexPaperSplit():
        if mode == 'translate_zh':
            pattern = re.compile(r'\\begin\{abstract\}.*\n')
            match = pattern.search(result_string)
-            position = match.end()
+            if not match:
+                # match \abstract{xxxx}
+                pattern_compile = re.compile(r"\\abstract\{(.*?)\}", flags=re.DOTALL)
+                match = pattern_compile.search(result_string)
+                position = match.regs[1][0]
+            else:
+                # match \begin{abstract}xxxx\end{abstract}
+                position = match.end()
            result_string = result_string[:position] + self.msg + msg + self.msg_declare + result_string[position:]
        return result_string

@@ -437,6 +477,7 @@ class LatexPaperSplit():
            args=(txt, project_folder, return_dict, opts))
        p.start()
        p.join()
+        p.close()
        self.nodes = return_dict['nodes']
        self.sp = return_dict['segment_parts_for_gpt']
        return self.sp
@@ -491,7 +532,32 @@ class LatexPaperFileGroup():
                f.write(res)
        return manifest

+def write_html(sp_file_contents, sp_file_result, chatbot):

+    # write html
+    try:
+        import copy
+        from .crazy_utils import construct_html
+        from toolbox import gen_time_str
+        ch = construct_html() 
+        orig = ""
+        trans = ""
+        final = []
+        for c,r in zip(sp_file_contents, sp_file_result): 
+            final.append(c)
+            final.append(r)
+        for i, k in enumerate(final): 
+            if i%2==0:
+                orig = k
+            if i%2==1:
+                trans = k
+                ch.add_row(a=orig, b=trans)
+        create_report_file_name = f"{gen_time_str()}.trans.html"
+        ch.save_file(create_report_file_name)
+        promote_file_to_downloadzone(file=f'./gpt_log/{create_report_file_name}', chatbot=chatbot)
+    except:
+        from toolbox import trimmed_format_exc
+        print('writing html result failed:', trimmed_format_exc())

 def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='proofread', switch_prompt=None, opts=[]):
    import time, os, re
@@ -568,6 +634,7 @@ def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin
        pfg.get_token_num = None
        objdump(pfg, file=pj(project_folder,'temp.pkl'))

+    write_html(pfg.sp_file_contents, pfg.sp_file_result, chatbot=chatbot)

    #  <-------- 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']}。"
@@ -617,7 +684,7 @@ def compile_latex_with_timeout(command, timeout=60):
        return False
    return True

-def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_folder_original, work_folder_modified, work_folder):
+def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_folder_original, work_folder_modified, work_folder, mode='default'):
    import os, time
    current_dir = os.getcwd()
    n_fix = 1
@@ -628,6 +695,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f

    while True:
        import os
+
        # https://stackoverflow.com/questions/738755/dont-make-me-manually-abort-a-latex-compile-when-theres-an-error
        yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history)   # 刷新Gradio前端界面
        os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex'); os.chdir(current_dir)
@@ -649,15 +717,16 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
            os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex'); os.chdir(current_dir)
            os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex'); os.chdir(current_dir)

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

-            yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history)   # 刷新Gradio前端界面
-            os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
-            os.chdir(work_folder); ok = compile_latex_with_timeout(f'bibtex    merge_diff.aux'); os.chdir(current_dir)
-            os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
-            os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
+                yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history)   # 刷新Gradio前端界面
+                os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
+                os.chdir(work_folder); ok = compile_latex_with_timeout(f'bibtex    merge_diff.aux'); os.chdir(current_dir)
+                os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
+                os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex  -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)

        # <--------------------->
        os.chdir(current_dir)
@@ -678,7 +747,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
            result_pdf = pj(work_folder_modified, f'{main_file_modified}.pdf')
            if os.path.exists(pj(work_folder, '..', 'translation')):
                shutil.copyfile(result_pdf, pj(work_folder, '..', 'translation', 'translate_zh.pdf'))
-            promote_file_to_downloadzone(result_pdf)
+            promote_file_to_downloadzone(result_pdf, rename_file=None, chatbot=chatbot)
            return True # 成功啦
        else:
            if n_fix>=max_try: break
--- a/crazy_functions/对话历史存档.py
+++ b/crazy_functions/对话历史存档.py
@@ -1,4 +1,4 @@
-from toolbox import CatchException, update_ui
+from toolbox import CatchException, update_ui, promote_file_to_downloadzone
 from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 import re

@@ -29,9 +29,8 @@ def write_chat_to_file(chatbot, history=None, file_name=None):
        for h in history:
            f.write("\n>>>" + h)
        f.write('</code>')
-    res = '对话历史写入：' + os.path.abspath(f'./gpt_log/{file_name}')
-    print(res)
-    return res
+    promote_file_to_downloadzone(f'./gpt_log/{file_name}', rename_file=file_name, chatbot=chatbot)
+    return '对话历史写入：' + os.path.abspath(f'./gpt_log/{file_name}')

 def gen_file_preview(file_name):
    try:
--- a/crazy_functions/虚空终端.py
+++ b/crazy_functions/虚空终端.py
@@ -0,0 +1,131 @@
+from toolbox import CatchException, update_ui, gen_time_str
+from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+from .crazy_utils import input_clipping
+
+
+prompt = """
+I have to achieve some functionalities by calling one of the functions below.
+Your job is to find the correct funtion to use to satisfy my requirement,
+and then write python code to call this function with correct parameters.
+
+These are functions you are allowed to choose from:
+1. 
+    功能描述: 总结音视频内容
+    调用函数: ConcludeAudioContent(txt, llm_kwargs)
+    参数说明: 
+            txt: 音频文件的路径
+            llm_kwargs: 模型参数, 永远给定None
+2. 
+    功能描述: 将每次对话记录写入Markdown格式的文件中
+    调用函数: WriteMarkdown()
+3.
+    功能描述: 将指定目录下的PDF文件从英文翻译成中文
+    调用函数: BatchTranslatePDFDocuments_MultiThreaded(txt, llm_kwargs)
+    参数说明: 
+            txt: PDF文件所在的路径
+            llm_kwargs: 模型参数, 永远给定None
+4.
+    功能描述: 根据文本使用GPT模型生成相应的图像
+    调用函数: ImageGeneration(txt, llm_kwargs)
+    参数说明: 
+            txt: 图像生成所用到的提示文本
+            llm_kwargs: 模型参数, 永远给定None
+5.
+    功能描述: 对输入的word文档进行摘要生成 
+    调用函数: SummarizingWordDocuments(input_path, output_path)
+    参数说明: 
+            input_path: 待处理的word文档路径
+            output_path: 摘要生成后的文档路径
+
+
+You should always anwser with following format:
+----------------
+Code:
+```
+class AutoAcademic(object):
+    def __init__(self):
+        self.selected_function = "FILL_CORRECT_FUNCTION_HERE"      # e.g., "GenerateImage"
+        self.txt = "FILL_MAIN_PARAMETER_HERE"      # e.g., "荷叶上的蜻蜓"
+        self.llm_kwargs = None
+```
+Explanation:
+只有GenerateImage和生成图像相关, 因此选择GenerateImage函数。
+----------------
+
+Now, this is my requirement: 
+
+"""
+def get_fn_lib():
+    return {
+        "BatchTranslatePDFDocuments_MultiThreaded": ("crazy_functions.批量翻译PDF文档_多线程",  "批量翻译PDF文档"),
+        "SummarizingWordDocuments": ("crazy_functions.总结word文档",  "总结word文档"),
+        "ImageGeneration": ("crazy_functions.图片生成",  "图片生成"),
+        "TranslateMarkdownFromEnglishToChinese": ("crazy_functions.批量Markdown翻译",  "Markdown中译英"),
+        "SummaryAudioVideo": ("crazy_functions.总结音视频",  "总结音视频"),
+    }
+
+def inspect_dependency(chatbot, history):
+    return True
+
+def eval_code(code, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
+    import subprocess, sys, os, shutil, importlib
+
+    with open('gpt_log/void_terminal_runtime.py', 'w', encoding='utf8') as f:
+        f.write(code)
+
+    try:
+        AutoAcademic = getattr(importlib.import_module('gpt_log.void_terminal_runtime', 'AutoAcademic'), 'AutoAcademic')
+        # importlib.reload(AutoAcademic)
+        auto_dict = AutoAcademic()
+        selected_function = auto_dict.selected_function
+        txt = auto_dict.txt
+        fp, fn = get_fn_lib()[selected_function]
+        fn_plugin = getattr(importlib.import_module(fp, fn), fn)
+        yield from fn_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port)
+    except:
+        from toolbox import trimmed_format_exc
+        chatbot.append(["执行错误", f"\n```\n{trimmed_format_exc()}\n```\n"])
+        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+
+def get_code_block(reply):
+    import re
+    pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks
+    matches = re.findall(pattern, reply) # find all code blocks in text
+    if len(matches) != 1: 
+        raise RuntimeError("GPT is not generating proper code.")
+    return matches[0].strip('python') #  code block
+
+@CatchException
+def 终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
+    """
+    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, 暂时没有用武之地
+    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
+    web_port        当前软件运行的端口号
+    """
+    # 清空历史, 以免输入溢出
+    history = []    
+
+    # 基本信息：功能、贡献者
+    chatbot.append(["函数插件功能？", "根据自然语言执行插件命令, 作者: binary-husky, 插件初始化中 ..."])
+    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+
+    # # 尝试导入依赖, 如果缺少依赖, 则给出安装建议
+    # dep_ok = yield from inspect_dependency(chatbot=chatbot, history=history) # 刷新界面
+    # if not dep_ok: return
+    
+    # 输入
+    i_say = prompt + txt
+    # 开始
+    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
+        inputs=i_say, inputs_show_user=txt, 
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 
+        sys_prompt=""
+    )
+
+    # 将代码转为动画
+    code = get_code_block(gpt_say)
+    yield from eval_code(code, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port)
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -103,3 +103,30 @@ services:
                      echo '[jittorllms] 正在从github拉取最新代码...' &&
                      git --git-dir=request_llm/jittorllms/.git --work-tree=request_llm/jittorllms pull --force &&
                      python3 -u main.py"
+
+
+## ===================================================
+## 【方案四】 chatgpt + Latex
+## ===================================================
+version: '3'
+services:
+  gpt_academic_with_latex:
+    image: ghcr.io/binary-husky/gpt_academic_with_latex:master
+    environment:
+      # 请查阅 `config.py` 以查看所有的配置信息
+      API_KEY:                  '    sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx                              '
+      USE_PROXY:                '    True                                                                             '
+      proxies:                  '    { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", }   '
+      LLM_MODEL:                '    gpt-3.5-turbo                                                                    '
+      AVAIL_LLM_MODELS:         '    ["gpt-3.5-turbo", "gpt-4"]                                                       '
+      LOCAL_MODEL_DEVICE:       '    cuda                                                                             '
+      DEFAULT_WORKER_NUM:       '    10                                                                               '
+      WEB_PORT:                 '    12303                                                                            '
+
+    # 与宿主的网络融合
+    network_mode: "host"
+
+    # 不使用代理网络拉取最新代码
+    command: >
+      bash -c "python3 -u main.py"
+
--- a/docs/GithubAction+NoLocal+Latex
+++ b/docs/GithubAction+NoLocal+Latex
@@ -0,0 +1,25 @@
+# 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/Dockerfile+NoLocal+Latex .
+# - 3 运行 docker run -v /home/fuqingxu/arxiv_cache:/root/arxiv_cache --rm -it --net=host gpt-academic-nolocal-latex
+
+FROM fuqingxu/python311_texlive_ctex:latest
+
+# 指定路径
+WORKDIR /gpt
+
+RUN pip3 install gradio openai numpy arxiv rich
+RUN pip3 install colorama Markdown pygments pymupdf
+
+# 装载项目文件
+COPY . .
+
+
+# 安装依赖
+RUN pip3 install -r requirements.txt
+
+# 可选步骤，用于预热模块
+RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
+
+# 启动
+CMD ["python3", "-u", "main.py"]
--- a/docs/use_azure.md
+++ b/docs/use_azure.md
@@ -0,0 +1,152 @@
+# 通过微软Azure云服务申请 Openai API
+
+由于Openai和微软的关系，现在是可以通过微软的Azure云计算服务直接访问openai的api，免去了注册和网络的问题。
+
+快速入门的官方文档的链接是：[快速入门 - 开始通过 Azure OpenAI 服务使用 ChatGPT 和 GPT-4 - Azure OpenAI Service | Microsoft Learn](https://learn.microsoft.com/zh-cn/azure/cognitive-services/openai/chatgpt-quickstart?pivots=programming-language-python)
+
+# 申请API
+
+按文档中的“先决条件”的介绍，出了编程的环境以外，还需要以下三个条件：
+
+1.  Azure账号并创建订阅
+
+2.  为订阅添加Azure OpenAI 服务
+
+3.  部署模型
+
+## Azure账号并创建订阅
+
+### Azure账号
+
+创建Azure的账号时最好是有微软的账号，这样似乎更容易获得免费额度（第一个月的200美元，实测了一下，如果用一个刚注册的微软账号登录Azure的话，并没有这一个月的免费额度）。
+
+创建Azure账号的网址是：[立即创建 Azure 免费帐户 | Microsoft Azure](https://azure.microsoft.com/zh-cn/free/)
+
+![](https://wdcdn.qpic.cn/MTY4ODg1Mjk4NzI5NTU1NQ_944786_iH6AECuZ_tY0EaBd_1685327219?w=1327\&h=695\&type=image/png)
+
+打开网页后，点击 “免费开始使用” 会跳转到登录或注册页面，如果有微软的账户，直接登录即可，如果没有微软账户，那就需要到微软的网页再另行注册一个。
+
+注意，Azure的页面和政策时不时会变化，已实际最新显示的为准就好。
+
+### 创建订阅
+
+注册好Azure后便可进入主页：
+
+![](https://wdcdn.qpic.cn/MTY4ODg1Mjk4NzI5NTU1NQ_444847_tk-9S-pxOYuaLs_K_1685327675?w=1865\&h=969\&type=image/png)
+
+首先需要在订阅里进行添加操作，点开后即可进入订阅的页面：
+
+![](https://wdcdn.qpic.cn/MTY4ODg1Mjk4NzI5NTU1NQ_612820_z_1AlaEgnJR-rUl0_1685327892?w=1865\&h=969\&type=image/png)
+
+第一次进来应该是空的，点添加即可创建新的订阅（可以是“免费”或者“即付即用”的订阅），其中订阅ID是后面申请Azure OpenAI需要使用的。
+
+## 为订阅添加Azure OpenAI服务
+
+之后回到首页，点Azure OpenAI即可进入OpenAI服务的页面（如果不显示的话，则在首页上方的搜索栏里搜索“openai”即可）。
+
+![](https://wdcdn.qpic.cn/MTY4ODg1Mjk4NzI5NTU1NQ_269759_nExkGcPC0EuAR5cp_1685328130?w=1865\&h=969\&type=image/png)
+
+不过现在这个服务还不能用。在使用前，还需要在这个网址申请一下：
+
+[Request Access to Azure OpenAI Service (microsoft.com)](https://customervoice.microsoft.com/Pages/ResponsePage.aspx?id=v4j5cvGGr0GRqy180BHbR7en2Ais5pxKtso_Pz4b1_xUOFA5Qk1UWDRBMjg0WFhPMkIzTzhKQ1dWNyQlQCN0PWcu)
+
+这里有二十来个问题，按照要求和自己的实际情况填写即可。
+
+其中需要注意的是
+
+1.  千万记得填对"订阅ID"
+
+2.  需要填一个公司邮箱（可以不是注册用的邮箱）和公司网址
+
+之后，在回到上面那个页面，点创建，就会进入创建页面了：
+
+![](https://wdcdn.qpic.cn/MTY4ODg1Mjk4NzI5NTU1NQ_72708_9d9JYhylPVz3dFWL_1685328372?w=824\&h=590\&type=image/png)
+
+需要填入“资源组”和“名称”，按照自己的需要填入即可。
+
+完成后，在主页的“资源”里就可以看到刚才创建的“资源”了，点击进入后，就可以进行最后的部署了。
+
+![](https://wdcdn.qpic.cn/MTY4ODg1Mjk4NzI5NTU1NQ_871541_CGCnbgtV9Uk1Jccy_1685329861?w=1217\&h=628\&type=image/png)
+
+## 部署模型
+
+进入资源页面后，在部署模型前，可以先点击“开发”，把密钥和终结点记下来。
+
+![](https://wdcdn.qpic.cn/MTY4ODg1Mjk4NzI5NTU1NQ_852567_dxCZOrkMlWDSLH0d_1685330736?w=856\&h=568\&type=image/png)
+
+之后，就可以去部署模型了，点击“部署”即可，会跳转到 Azure OpenAI Stuido 进行下面的操作：
+
+![](https://wdcdn.qpic.cn/MTY4ODg1Mjk4NzI5NTU1NQ_169225_uWs1gMhpNbnwW4h2_1685329901?w=1865\&h=969\&type=image/png)
+
+进入 Azure OpenAi Studio 后，点击新建部署，会弹出如下对话框：
+
+![](https://wdcdn.qpic.cn/MTY4ODg1Mjk4NzI5NTU1NQ_391255_iXUSZAzoud5qlxjJ_1685330224?w=656\&h=641\&type=image/png)
+
+在这里选 gpt-35-turbo 或需要的模型并按需要填入“部署名”即可完成模型的部署。
+
+![](https://wdcdn.qpic.cn/MTY4ODg1Mjk4NzI5NTU1NQ_724099_vBaHcUilsm1EtPgK_1685330396?w=1869\&h=482\&type=image/png)
+
+这个部署名需要记下来。
+
+到现在为止，申请操作就完成了，需要记下来的有下面几个东西：
+
+● 密钥（1或2都可以）
+
+● 终结点
+
+● 部署名（不是模型名）
+
+# 修改 config.py
+
+```
+AZURE_ENDPOINT = "填入终结点"
+AZURE_API_KEY = "填入azure openai api的密钥"
+AZURE_API_VERSION = "2023-05-15"  # 默认使用 2023-05-15 版本，无需修改
+AZURE_ENGINE = "填入部署名"
+
+```
+# API的使用
+
+接下来就是具体怎么使用API了，还是可以参考官方文档：[快速入门 - 开始通过 Azure OpenAI 服务使用 ChatGPT 和 GPT-4 - Azure OpenAI Service | Microsoft Learn](https://learn.microsoft.com/zh-cn/azure/cognitive-services/openai/chatgpt-quickstart?pivots=programming-language-python)
+
+和openai自己的api调用有点类似，都需要安装openai库，不同的是调用方式
+
+```
+import openai
+openai.api_type = "azure" #固定格式，无需修改
+openai.api_base = os.getenv("AZURE_OPENAI_ENDPOINT") #这里填入“终结点”
+openai.api_version = "2023-05-15" #固定格式，无需修改
+openai.api_key = os.getenv("AZURE_OPENAI_KEY") #这里填入“密钥1”或“密钥2”
+
+response = openai.ChatCompletion.create(
+    engine="gpt-35-turbo", #这里填入的不是模型名，是部署名
+    messages=[
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Does Azure OpenAI support customer managed keys?"},
+        {"role": "assistant", "content": "Yes, customer managed keys are supported by Azure OpenAI."},
+        {"role": "user", "content": "Do other Azure Cognitive Services support this too?"}
+    ]
+)
+
+print(response)
+print(response['choices'][0]['message']['content'])
+
+```
+
+需要注意的是：
+
+1.  engine那里填入的是部署名，不是模型名
+
+2.  通过openai库获得的这个 response 和通过 request 库访问 url 获得的 response 不同，不需要 decode，已经是解析好的 json 了，直接根据键值读取即可。
+
+更细节的使用方法，详见官方API文档。
+
+# 关于费用
+
+Azure OpenAI API 还是需要一些费用的（免费订阅只有1个月有效期），费用如下：
+
+![image.png](https://note.youdao.com/yws/res/18095/WEBRESOURCEeba0ab6d3127b79e143ef2d5627c0e44)
+
+具体可以可以看这个网址 ：[Azure OpenAI 服务 - 定价| Microsoft Azure](https://azure.microsoft.com/zh-cn/pricing/details/cognitive-services/openai-service/?cdn=disable)
+
+并非网上说的什么“一年白嫖”，但注册方法以及网络问题都比直接使用openai的api要简单一些。
--- a/main.py
+++ b/main.py
@@ -155,7 +155,7 @@ def main():
        for k in crazy_fns:
            if not crazy_fns[k].get("AsButton", True): continue
            click_handle = crazy_fns[k]["Button"].click(ArgsGeneralWrapper(crazy_fns[k]["Function"]), [*input_combo, gr.State(PORT)], output_combo)
-            click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
+            click_handle.then(on_report_generated, [cookies, file_upload, chatbot], [cookies, file_upload, chatbot])
            cancel_handles.append(click_handle)
        # 函数插件-下拉菜单与随变按钮的互动
        def on_dropdown_changed(k):
@@ -175,7 +175,7 @@ def main():
            if k in [r"打开插件列表", r"请先从插件列表中选择"]: return
            yield from ArgsGeneralWrapper(crazy_fns[k]["Function"])(*args, **kwargs)
        click_handle = switchy_bt.click(route,[switchy_bt, *input_combo, gr.State(PORT)], output_combo)
-        click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
+        click_handle.then(on_report_generated, [cookies, file_upload, chatbot], [cookies, file_upload, chatbot])
        cancel_handles.append(click_handle)
        # 终止按钮的回调函数注册
        stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
--- a/request_llm/bridge_all.py
+++ b/request_llm/bridge_all.py
@@ -16,6 +16,9 @@ from toolbox import get_conf, trimmed_format_exc
 from .bridge_chatgpt import predict_no_ui_long_connection as chatgpt_noui
 from .bridge_chatgpt import predict as chatgpt_ui

+from .bridge_azure_test import predict_no_ui_long_connection as azure_noui
+from .bridge_azure_test import predict as azure_ui
+
 from .bridge_chatglm import predict_no_ui_long_connection as chatglm_noui
 from .bridge_chatglm import predict as chatglm_ui

@@ -83,6 +86,33 @@ model_info = {
        "tokenizer": tokenizer_gpt35,
        "token_cnt": get_token_num_gpt35,
    },
+    
+    "gpt-3.5-turbo-16k": {
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "endpoint": openai_endpoint,
+        "max_token": 1024*16,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
+
+    "gpt-3.5-turbo-0613": {
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "endpoint": openai_endpoint,
+        "max_token": 4096,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
+
+    "gpt-3.5-turbo-16k-0613": {
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "endpoint": openai_endpoint,
+        "max_token": 1024 * 16,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },

    "gpt-4": {
        "fn_with_ui": chatgpt_ui,
@@ -93,6 +123,16 @@ model_info = {
        "token_cnt": get_token_num_gpt4,
    },

+    # azure openai
+    "azure-gpt35":{
+        "fn_with_ui": azure_ui,
+        "fn_without_ui": azure_noui,
+        "endpoint": get_conf("AZURE_ENDPOINT"),
+        "max_token": 4096,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
+
    # api_2d
    "api2d-gpt-3.5-turbo": {
        "fn_with_ui": chatgpt_ui,
--- a/request_llm/bridge_azure_test.py
+++ b/request_llm/bridge_azure_test.py
@@ -0,0 +1,241 @@
+"""
+    该文件中主要包含三个函数
+
+    不具备多线程能力的函数：
+    1. predict: 正常对话时使用，具备完备的交互功能，不可多线程
+
+    具备多线程调用能力的函数
+    2. predict_no_ui：高级实验性功能模块调用，不会实时显示在界面上，参数简单，可以多线程并行，方便实现复杂的功能逻辑
+    3. predict_no_ui_long_connection：在实验过程中发现调用predict_no_ui处理长文档时，和openai的连接容易断掉，这个函数用stream的方式解决这个问题，同样支持多线程
+"""
+
+import logging
+import traceback
+import importlib
+import openai
+import time
+
+
+# 读取config.py文件中关于AZURE OPENAI API的信息
+from toolbox import get_conf, update_ui, clip_history, trimmed_format_exc
+TIMEOUT_SECONDS, MAX_RETRY, AZURE_ENGINE, AZURE_ENDPOINT, AZURE_API_VERSION, AZURE_API_KEY = \
+    get_conf('TIMEOUT_SECONDS', 'MAX_RETRY',"AZURE_ENGINE","AZURE_ENDPOINT", "AZURE_API_VERSION", "AZURE_API_KEY")
+
+
+def get_full_error(chunk, stream_response):
+    """
+        获取完整的从Openai返回的报错
+    """
+    while True:
+        try:
+            chunk += next(stream_response)
+        except:
+            break
+    return chunk
+
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
+    """
+    发送至azure openai api，流式获取输出。
+    用于基础的对话功能。
+    inputs 是本次问询的输入
+    top_p, temperature是chatGPT的内部调优参数
+    history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
+    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+    additional_fn代表点击的哪个按钮，按钮见functional.py
+    """
+    print(llm_kwargs["llm_model"])    
+
+    if additional_fn is not None:
+        import core_functional
+        importlib.reload(core_functional)    # 热更新prompt
+        core_functional = core_functional.get_core_functions()
+        if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs)  # 获取预处理函数（如果有的话）
+        inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
+
+    raw_input = inputs
+    logging.info(f'[raw_input] {raw_input}')
+    chatbot.append((inputs, ""))
+    yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面
+
+    
+    payload = generate_azure_payload(inputs, llm_kwargs, history, system_prompt, stream)    
+        
+    history.append(inputs); history.append("")
+
+    retry = 0
+    while True:
+        try:            
+                
+            openai.api_type = "azure"            
+            openai.api_version = AZURE_API_VERSION
+            openai.api_base = AZURE_ENDPOINT
+            openai.api_key = AZURE_API_KEY
+            response = openai.ChatCompletion.create(timeout=TIMEOUT_SECONDS, **payload);break
+        
+        except:
+            retry += 1
+            chatbot[-1] = ((chatbot[-1][0], "获取response失败，重试中。。。"))
+            retry_msg = f"，正在重试 ({retry}/{MAX_RETRY}) ……" if MAX_RETRY > 0 else ""
+            yield from update_ui(chatbot=chatbot, history=history, msg="请求超时"+retry_msg) # 刷新界面
+            if retry > MAX_RETRY: raise TimeoutError
+            
+    gpt_replying_buffer = ""    
+    is_head_of_the_stream = True
+    if stream:
+
+        stream_response = response
+
+        while True:
+            try:
+                chunk = next(stream_response)
+                    
+            except StopIteration:                
+                from toolbox import regular_txt_to_markdown; tb_str = '```\n' + trimmed_format_exc() + '```'
+                chatbot[-1] = (chatbot[-1][0], f"[Local Message] 远程返回错误: \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk)}")
+                yield from update_ui(chatbot=chatbot, history=history, msg="远程返回错误:" + chunk) # 刷新界面
+                return            
+            
+            if is_head_of_the_stream and (r'"object":"error"' not in chunk):
+                # 数据流的第一帧不携带content
+                is_head_of_the_stream = False; continue
+            
+            if chunk:
+                #print(chunk)
+                try:                     
+                    if "delta" in chunk["choices"][0]:
+                        if chunk["choices"][0]["finish_reason"] == "stop":
+                            logging.info(f'[response] {gpt_replying_buffer}')
+                            break
+                    status_text = f"finish_reason: {chunk['choices'][0]['finish_reason']}"    
+                    gpt_replying_buffer = gpt_replying_buffer + chunk["choices"][0]["delta"]["content"]                               
+                       
+                    history[-1] = gpt_replying_buffer
+                    chatbot[-1] = (history[-2], history[-1])
+                    yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
+
+                except Exception as e:
+                    traceback.print_exc()
+                    yield from update_ui(chatbot=chatbot, history=history, msg="Json解析不合常规") # 刷新界面
+                    chunk = get_full_error(chunk, stream_response)
+                    
+                    error_msg = chunk                    
+                    yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面
+                    return
+
+
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
+    """
+    发送至AZURE OPENAI API，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免中途网线被掐。
+    inputs：
+        是本次问询的输入
+    sys_prompt:
+        系统静默prompt
+    llm_kwargs：
+        chatGPT的内部调优参数
+    history：
+        是之前的对话列表
+    observe_window = None：
+        用于负责跨越线程传递已经输出的部分，大部分时候仅仅为了fancy的视觉效果，留空即可。observe_window[0]：观测窗。observe_window[1]：看门狗
+    """
+    watch_dog_patience = 5 # 看门狗的耐心, 设置5秒即可
+    payload = generate_azure_payload(inputs, llm_kwargs, history, system_prompt=sys_prompt, stream=True)
+    retry = 0
+    while True:
+
+        try:
+            openai.api_type = "azure"            
+            openai.api_version = AZURE_API_VERSION
+            openai.api_base = AZURE_ENDPOINT
+            openai.api_key = AZURE_API_KEY
+            response = openai.ChatCompletion.create(timeout=TIMEOUT_SECONDS, **payload);break
+        
+        except:  
+            retry += 1
+            traceback.print_exc()
+            if retry > MAX_RETRY: raise TimeoutError
+            if MAX_RETRY!=0: print(f'请求超时，正在重试 ({retry}/{MAX_RETRY}) ……')     
+        
+
+    stream_response =  response
+    result = ''
+    while True:
+        try: chunk = next(stream_response)
+        except StopIteration: 
+            break
+        except:
+            chunk = next(stream_response) # 失败了，重试一次？再失败就没办法了。
+
+        if len(chunk)==0: continue
+        if not chunk.startswith('data:'): 
+            error_msg = get_full_error(chunk, stream_response)
+            if "reduce the length" in error_msg:
+                raise ConnectionAbortedError("AZURE OPENAI API拒绝了请求:" + error_msg)
+            else:
+                raise RuntimeError("AZURE OPENAI API拒绝了请求：" + error_msg)
+        if ('data: [DONE]' in chunk): break 
+        
+        delta = chunk["delta"]
+        if len(delta) == 0: break
+        if "role" in delta: continue
+        if "content" in delta: 
+            result += delta["content"]
+            if not console_slience: print(delta["content"], end='')
+            if observe_window is not None: 
+                # 观测窗，把已经获取的数据显示出去
+                if len(observe_window) >= 1: observe_window[0] += delta["content"]
+                # 看门狗，如果超过期限没有喂狗，则终止
+                if len(observe_window) >= 2:  
+                    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 chunk['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
+
+
+def generate_azure_payload(inputs, llm_kwargs, history, system_prompt, stream):
+    """
+    整合所有信息，选择LLM模型，生成 azure openai api请求，为发送请求做准备
+    """    
+
+    conversation_cnt = len(history) // 2
+
+    messages = [{"role": "system", "content": system_prompt}]
+    if conversation_cnt:
+        for index in range(0, 2*conversation_cnt, 2):
+            what_i_have_asked = {}
+            what_i_have_asked["role"] = "user"
+            what_i_have_asked["content"] = history[index]
+            what_gpt_answer = {}
+            what_gpt_answer["role"] = "assistant"
+            what_gpt_answer["content"] = history[index+1]
+            if what_i_have_asked["content"] != "":
+                if what_gpt_answer["content"] == "": continue                
+                messages.append(what_i_have_asked)
+                messages.append(what_gpt_answer)
+            else:
+                messages[-1]['content'] = what_gpt_answer['content']
+
+    what_i_ask_now = {}
+    what_i_ask_now["role"] = "user"
+    what_i_ask_now["content"] = inputs
+    messages.append(what_i_ask_now)
+
+    payload = {
+        "model": llm_kwargs['llm_model'],
+        "messages": messages, 
+        "temperature": llm_kwargs['temperature'],  # 1.0,
+        "top_p": llm_kwargs['top_p'],  # 1.0,
+        "n": 1,
+        "stream": stream,
+        "presence_penalty": 0,
+        "frequency_penalty": 0,
+        "engine": AZURE_ENGINE
+    }
+    try:
+        print(f" {llm_kwargs['llm_model']} : {conversation_cnt} : {inputs[:100]} ..........")
+    except:
+        print('输入中可能存在乱码。')
+    return payload
+
+
--- a/toolbox.py
+++ b/toolbox.py
@@ -6,6 +6,7 @@ import re
 import os
 from latex2mathml.converter import convert as tex2mathml
 from functools import wraps, lru_cache
+pj = os.path.join

 """
 ========================================================================
@@ -221,16 +222,21 @@ def text_divide_paragraph(text):
    """
    将文本按照段落分隔符分割开，生成带有段落标签的HTML代码。
    """
+    pre = '<div class="markdown-body">'
+    suf = '</div>'
+    if text.startswith(pre) and text.endswith(suf):
+        return text
+    
    if '```' in text:
        # careful input
-        return text
+        return pre + text + suf
    else:
        # wtf input
        lines = text.split("\n")
        for i, line in enumerate(lines):
            lines[i] = lines[i].replace(" ", "&nbsp;")
        text = "</br>".join(lines)
-        return text
+        return pre + text + suf

@lru_cache(maxsize=128) # 使用 lru缓存 加快转换速度
 def markdown_convertion(txt):
@@ -342,8 +348,11 @@ def format_io(self, y):
    if y is None or y == []:
        return []
    i_ask, gpt_reply = y[-1]
-    i_ask = text_divide_paragraph(i_ask)  # 输入部分太自由，预处理一波
-    gpt_reply = close_up_code_segment_during_stream(gpt_reply)  # 当代码输出半截的时候，试着补上后个```
+    # 输入部分太自由，预处理一波
+    if i_ask is not None: i_ask = text_divide_paragraph(i_ask)
+    # 当代码输出半截的时候，试着补上后个```
+    if gpt_reply is not None: gpt_reply = close_up_code_segment_during_stream(gpt_reply)
+    # process
    y[-1] = (
        None if i_ask is None else markdown.markdown(i_ask, extensions=['fenced_code', 'tables']),
        None if gpt_reply is None else markdown_convertion(gpt_reply)
@@ -391,7 +400,7 @@ def extract_archive(file_path, dest_dir):
                print("Successfully extracted rar archive to {}".format(dest_dir))
        except:
            print("Rar format requires additional dependencies to install")
-            return '\n\n需要安装pip install rarfile来解压rar文件'
+            return '\n\n解压失败! 需要安装pip install rarfile来解压rar文件'

    # 第三方库，需要预先pip install py7zr
    elif file_extension == '.7z':
@@ -402,7 +411,7 @@ def extract_archive(file_path, dest_dir):
                print("Successfully extracted 7z archive to {}".format(dest_dir))
        except:
            print("7z format requires additional dependencies to install")
-            return '\n\n需要安装pip install py7zr来解压7z文件'
+            return '\n\n解压失败! 需要安装pip install py7zr来解压7z文件'
    else:
        return ''
    return ''
@@ -431,13 +440,17 @@ def find_recent_files(directory):

    return recent_files

-def promote_file_to_downloadzone(file, rename_file=None):
+def promote_file_to_downloadzone(file, rename_file=None, chatbot=None):
    # 将文件复制一份到下载区
    import shutil
    if rename_file is None: rename_file = f'{gen_time_str()}-{os.path.basename(file)}'
    new_path = os.path.join(f'./gpt_log/', rename_file)
-    if os.path.exists(new_path): os.remove(new_path)
-    shutil.copyfile(file, new_path)
+    if os.path.exists(new_path) and not os.path.samefile(new_path, file): os.remove(new_path)
+    if not os.path.exists(new_path): shutil.copyfile(file, new_path)
+    if chatbot:
+        if 'file_to_promote' in chatbot._cookies: current = chatbot._cookies['file_to_promote']
+        else: current = []
+        chatbot._cookies.update({'file_to_promote': [new_path] + current})

 def on_file_uploaded(files, chatbot, txt, txt2, checkboxes):
    """
@@ -477,16 +490,20 @@ def on_file_uploaded(files, chatbot, txt, txt2, checkboxes):
    return chatbot, txt, txt2


-def on_report_generated(files, chatbot):
+def on_report_generated(cookies, files, chatbot):
    from toolbox import find_recent_files
-    report_files = find_recent_files('gpt_log')
+    if 'file_to_promote' in cookies:
+        report_files = cookies['file_to_promote']
+        cookies.pop('file_to_promote')
+    else:
+        report_files = find_recent_files('gpt_log')
    if len(report_files) == 0:
        return None, chatbot
    # files.extend(report_files)
    file_links = ''
    for f in report_files: file_links += f'<br/><a href="file={os.path.abspath(f)}" target="_blank">{f}</a>'
    chatbot.append(['报告如何远程获取？', f'报告已经添加到右侧“文件上传区”（可能处于折叠状态），请查收。{file_links}'])
-    return report_files, chatbot
+    return cookies, report_files, chatbot

 def is_openai_api_key(key):
    API_MATCH_ORIGINAL = re.match(r"sk-[a-zA-Z0-9]{48}$", key)
@@ -788,7 +805,8 @@ def zip_result(folder):
    import time
    t = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
    zip_folder(folder, './gpt_log/', f'{t}-result.zip')
-    
+    return pj('./gpt_log/', f'{t}-result.zip')
+
 def gen_time_str():
    import time
    return time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
--- a/4
+++ b/4
@@ -1,5 +1,5 @@
 {
-  "version": 3.4,
+  "version": 3.41,
  "show_feature": true,
-  "new_feature": "新增最强Arxiv论文翻译插件 <-> 修复gradio复制按钮BUG <-> 修复PDF翻译的BUG, 新增HTML中英双栏对照 <-> 添加了OpenAI图片生成插件 <-> 添加了OpenAI音频转文本总结插件 <-> 通过Slack添加对Claude的支持"
+  "new_feature": "增加gpt-3.5-16k的支持 <-> 新增最强Arxiv论文翻译插件 <-> 修复gradio复制按钮BUG <-> 修复PDF翻译的BUG, 新增HTML中英双栏对照 <-> 添加了OpenAI图片生成插件 <-> 添加了OpenAI音频转文本总结插件 <-> 通过Slack添加对Claude的支持"
 }
作者	SHA1	备注	提交日期
binary-husky	601a95c948	Merge pull request #881 from OverKit/master update latex_utils.py	2023-06-27 19:20:17 +08:00
qingxu fu	e18bef2e9c	add `item` breaker	2023-06-27 19:16:05 +08:00
qingxu fu	f654c1af31	merge regex expressions	2023-06-27 18:59:56 +08:00
qingxu fu	e90048a671	Merge branch 'master' of https://github.com/OverKit/gpt_academic into OverKit-master	2023-06-27 16:14:12 +08:00
binary-husky	ea624b1510	Merge pull request #889 from dackdawn/master 添加0613模型的声明	2023-06-27 15:03:15 +08:00
qingxu fu	057e3dda3c	Merge branch 'master' of https://github.com/dackdawn/gpt_academic into dackdawn-master	2023-06-27 15:02:22 +08:00
binary-husky	280e14d7b7	更新Latex模块的docker-compose	2023-06-26 09:59:14 +08:00
505030475	9f0cf9fb2b	arxiv PDF 引用	2023-06-25 23:30:31 +08:00
505030475	b8560b7510	修正误判latex模板文件的bug	2023-06-25 22:46:16 +08:00
505030475	d841d13b04	add arxiv translation test samples	2023-06-25 22:12:44 +08:00
binary-husky	efda9e5193	Merge pull request #897 from Ranhuiryan/master 添加azure-gpt35选项	2023-06-24 17:59:51 +10:00
Ranhuiryan	33d2e75aac	add azure-gpt35 to model list	2023-06-21 16:19:49 +08:00
Ranhuiryan	74941170aa	update azure use instruction	2023-06-21 16:19:26 +08:00
505030475	cd38949903	当遇到错误时，回滚到原文	2023-06-21 11:53:57 +10:00
505030475	d87f1eb171	更新接入azure的说明	2023-06-21 11:38:59 +10:00
binary-husky	cd1e4e1ba7	Merge pull request #797 from XiaojianTang/master 增加azure openai api的支持	2023-06-21 11:23:41 +10:00
505030475	cf5f348d70	update test samples	2023-06-21 11:20:31 +10:00
binary-husky	0ee25f475e	Merge branch 'master' of github.com:binary-husky/chatgpt_academic	2023-06-20 23:07:51 +08:00
binary-husky	1fede6df7f	temp	2023-06-20 23:05:17 +08:00
binary-husky	22a65cd163	Create build-with-latex.yml	2023-06-21 00:55:24 +10:00
binary-husky	538b041ea3	Merge pull request #890 from Mcskiller/master Update README.md	2023-06-21 00:53:26 +10:00
505030475	d7b056576d	add latex docker-compose	2023-06-21 00:52:58 +10:00
505030475	cb0bb6ab4a	fix minor bugs	2023-06-21 00:41:33 +10:00
505030475	bf955aaf12	fix bugs	2023-06-20 23:12:30 +10:00
505030475	61eb0da861	fix encoding bug	2023-06-20 22:08:09 +10:00
Lebenito（生糸）	5da633d94d	Update README.md Fix the error URL for the git clone.	2023-06-20 19:10:11 +08:00
dackdawn	f3e4e26e2f	添加0613模型的声明 openai对gpt-3.5-turbo的RPM限制是3，而gpt-3.5-turbo-0613的RPM是60，虽然两个模型的内容是一致的，但是选定特定模型可以获得更高的RPM和TPM	2023-06-19 21:40:26 +08:00
505030475	af7734dd35	avoid file fusion	2023-06-19 16:57:11 +10:00
505030475	d5bab093f9	rename function names	2023-06-19 15:17:33 +10:00
505030475	f94b167dc2	Merge branch 'master' into overkit-master	2023-06-19 14:53:51 +10:00
505030475	951d5ec758	Merge branch 'master' of github.com:binary-husky/chatgpt_academic	2023-06-19 14:52:25 +10:00
505030475	016d8ee156	Merge remote-tracking branch 'origin/master' into OverKit-master	2023-06-19 14:51:59 +10:00
505030475	dca9ec4bae	Merge branch 'master' of https://github.com/OverKit/gpt_academic into OverKit-master	2023-06-19 14:49:50 +10:00
binary-husky	a06e43c96b	Update README.md	2023-06-18 16:15:37 +08:00
binary-husky	29c6bfb6cb	Update README.md	2023-06-18 16:12:06 +08:00
binary-husky	8d7ee975a0	Update README.md	2023-06-18 16:10:45 +08:00
binary-husky	4bafbb3562	Update Latex输出PDF结果.py	2023-06-18 15:54:23 +08:00
OverKit	7fdf0a8e51	调整区分内容的代码	2023-06-18 15:51:29 +08:00
binary-husky	2bb13b4677	Update README.md	2023-06-18 15:44:42 +08:00
OverKit	9a5a509dd9	修复关于abstract的搜索	2023-06-17 19:27:21 +08:00
binary-husky	cbcb98ef6a	Merge pull request #872 from Skyzayre/master Update README.md	2023-06-16 17:54:39 +08:00
qingxu fu	bb864c6313	增加一些提示文字	2023-06-16 17:33:19 +08:00
qingxu fu	6d849eeb12	修复Langchain插件的bug	2023-06-16 17:33:03 +08:00
Skyzayre	ef752838b0	Update README.md	2023-06-15 02:07:43 +08:00
binary-husky	73d4a1ff4b	Update README.md	2023-06-14 10:15:47 +08:00
qingxu fu	8c62f21aa6	3.41增加gpt-3.5-16k的支持	2023-06-14 09:57:09 +08:00
qingxu fu	c40ebfc21f	将gpt-3.5-16k作为加入支持列表	2023-06-14 09:50:15 +08:00
binary-husky	c365ea9f57	Update README.md	2023-06-13 16:13:19 +08:00
binary-husky	12d66777cc	Merge pull request #864 from OverKit/master check letter % after removing spaces or tabs in the left	2023-06-12 15:21:35 +08:00
OverKit	9ac3d0d65d	check letter % after removing spaces or tabs in the left	2023-06-12 10:09:52 +08:00
binary-husky	9fd212652e	专业词汇声明	2023-06-12 09:45:59 +08:00
505030475	ce0d8b9dab	虚空终端插件雏形	2023-06-11 01:36:23 +08:00
XiaojianTang	f3205994ea	增加azure openai api的支持	2023-05-26 23:22:12 +08:00