readme update

Merge branch 'master' of github.com:binary-husky/chatgpt_academic
remove debug btn
2025-12-06 14:36:48 +00:00 · 2024-01-18 23:21:11 +08:00 · 2024-01-18 23:07:05 +08:00 · 2024-01-18 23:05:47 +08:00 · 2024-01-18 22:33:49 +08:00 · 2024-01-18 22:23:26 +08:00
--- a/.github/ISSUE_TEMPLATE/bug_report.yml
+++ b/.github/ISSUE_TEMPLATE/bug_report.yml
@@ -69,9 +69,3 @@ body:
    attributes:
      label: Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
      description: Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有）
-
-
-
-
-
-
--- a/.github/ISSUE_TEMPLATE/feature_request.yml
+++ b/.github/ISSUE_TEMPLATE/feature_request.yml
@@ -21,8 +21,3 @@ body:
    attributes:
      label: Feature Request | 功能请求
      description: Feature Request | 功能请求
-
-
-
-
-
--- a/.github/workflows/build-with-all-capacity-beta.yml
+++ b/.github/workflows/build-with-all-capacity-beta.yml
@@ -0,0 +1,44 @@
+# https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
+name: build-with-all-capacity-beta
+
+on:
+  push:
+    branches:
+      - 'master'
+
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME: ${{ github.repository }}_with_all_capacity_beta
+
+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+AllCapacityBeta
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
--- a/.gitignore
+++ b/.gitignore
@@ -152,3 +152,4 @@ request_llms/moss
 media
 flagged
 request_llms/ChatGLM-6b-onnx-u8s8
+.pre-commit-config.yaml
--- a/1
+++ b/1
@@ -18,7 +18,6 @@ WORKDIR /gpt

 # 安装大部分依赖，利用Docker缓存加速以后的构建 （以下三行，可以删除）
 COPY requirements.txt ./
-COPY ./docs/gradio-3.32.6-py3-none-any.whl ./docs/gradio-3.32.6-py3-none-any.whl
 RUN pip3 install -r requirements.txt


--- a/README.md
+++ b/README.md
@@ -1,8 +1,8 @@
-> **Caution**
-> 
-> 2023.11.12: 某些依赖包尚不兼容python 3.12，推荐python 3.11。
-> 
-> 2023.11.7: 安装依赖时，请选择`requirements.txt`中**指定的版本**。 安装命令：`pip install -r requirements.txt`。本项目开源免费，近期发现有人蔑视开源协议并利用本项目违规圈钱，请提高警惕，谨防上当受骗。
+> [!IMPORTANT]  
+> 2024.1.18: 更新3.70版本，支持Mermaid绘图库（让大模型绘制脑图）  
+> 2024.1.17: 恭迎GLM4，全力支持Qwen、GLM、DeepseekCoder等国内中文大语言基座模型！  
+> 2024.1.17: 某些依赖包尚不兼容python 3.12，推荐python 3.11。  
+> 2024.1.17: 安装依赖时，请选择`requirements.txt`中**指定的版本**。 安装命令：`pip install -r requirements.txt`。本项目完全开源免费，您可通过订阅[在线服务](https://github.com/binary-husky/gpt_academic/wiki/online)的方式鼓励本项目的发展。

 <br>

@@ -42,13 +42,11 @@ If you like this project, please give it a Star.
 Read this in [English](docs/README.English.md) | [日本語](docs/README.Japanese.md) | [한국어](docs/README.Korean.md) | [Русский](docs/README.Russian.md) | [Français](docs/README.French.md). All translations have been provided by the project itself. To translate this project to arbitrary language with GPT, read and run [`multi_language.py`](multi_language.py) (experimental).
 <br>

-
-> 1.请注意只有 **高亮** 标识的插件（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[自译解报告](https://github.com/binary-husky/gpt_academic/wiki/GPT‐Academic项目自译解报告)`self_analysis.md`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。常见问题请查阅wiki。
+> [!NOTE]
+> 1.本项目中每个文件的功能都在[自译解报告](https://github.com/binary-husky/gpt_academic/wiki/GPT‐Academic项目自译解报告)`self_analysis.md`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。常见问题请查阅wiki。
 >    [![常规安装方法](https://img.shields.io/static/v1?label=&message=常规安装方法&color=gray)](#installation)  [![一键安装脚本](https://img.shields.io/static/v1?label=&message=一键安装脚本&color=gray)](https://github.com/binary-husky/gpt_academic/releases)  [![配置说明](https://img.shields.io/static/v1?label=&message=配置说明&color=gray)](https://github.com/binary-husky/gpt_academic/wiki/项目配置说明) [![wiki](https://img.shields.io/static/v1?label=&message=wiki&color=gray)]([https://github.com/binary-husky/gpt_academic/wiki/项目配置说明](https://github.com/binary-husky/gpt_academic/wiki))
 >
-> 3.本项目兼容并鼓励尝试国产大语言模型ChatGLM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,azure-key3,api2d-key4"`。需要临时更换`API_KEY`时，在输入区输入临时的`API_KEY`然后回车键提交即可生效。
+> 2.本项目兼容并鼓励尝试国内中文大语言基座模型如通义千问，智谱GLM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,azure-key3,api2d-key4"`。需要临时更换`API_KEY`时，在输入区输入临时的`API_KEY`然后回车键提交即可生效。

 <br><br>

@@ -56,7 +54,7 @@ Read this in [English](docs/README.English.md) | [日本語](docs/README.Japanes

 功能（⭐= 近期新增功能） | 描述
 --- | ---
-⭐[接入新模型](https://github.com/binary-husky/gpt_academic/wiki/%E5%A6%82%E4%BD%95%E5%88%87%E6%8D%A2%E6%A8%A1%E5%9E%8B) | 百度[千帆](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu)与文心一言, 通义千问[Qwen](https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary)，上海AI-Lab[书生](https://github.com/InternLM/InternLM)，讯飞[星火](https://xinghuo.xfyun.cn/)，[LLaMa2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)，[智谱API](https://open.bigmodel.cn/)，DALLE3, [DeepseekCoder](https://coder.deepseek.com/)
+⭐[接入新模型](https://github.com/binary-husky/gpt_academic/wiki/%E5%A6%82%E4%BD%95%E5%88%87%E6%8D%A2%E6%A8%A1%E5%9E%8B) | 百度[千帆](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu)与文心一言, 通义千问[Qwen](https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary)，上海AI-Lab[书生](https://github.com/InternLM/InternLM)，讯飞[星火](https://xinghuo.xfyun.cn/)，[LLaMa2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)，[智谱GLM4](https://open.bigmodel.cn/)，DALLE3, [DeepseekCoder](https://coder.deepseek.com/)
 润色、翻译、代码解释 | 一键润色、翻译、查找论文语法错误、解释代码
 [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[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)
@@ -65,7 +63,7 @@ Read this in [English](docs/README.English.md) | [日本語](docs/README.Japanes
 Latex全文[翻译](https://www.bilibili.com/video/BV1nk4y1Y7Js/)、[润色](https://www.bilibili.com/video/BV1FT411H7c5/) | [插件] 一键翻译或润色latex论文
 批量注释生成 | [插件] 一键批量生成函数注释
 Markdown[中英互译](https://www.bilibili.com/video/BV1yo4y157jV/) | [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？就是出自他的手笔
-chat分析报告生成 | [插件] 运行后自动生成总结汇报
+⭐支持mermaid图像渲染 | 支持让GPT生成[流程图](https://www.bilibili.com/video/BV18c41147H9/)、状态转移图、甘特图、饼状图、GitGraph等等（3.7版本）
 [PDF论文全文翻译功能](https://www.bilibili.com/video/BV1KT411x7Wn) | [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) | [插件] 输入arxiv文章url即可一键翻译摘要+下载PDF
 Latex论文一键校对 | [插件] 仿Grammarly对Latex文章进行语法、拼写纠错+输出对照PDF
@@ -77,7 +75,6 @@ Latex论文一键校对 | [插件] 仿Grammarly对Latex文章进行语法、拼
 ⭐AutoGen多智能体插件 | [插件] 借助微软AutoGen，探索多Agent的智能涌现可能！
 启动暗色[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ChatGLM2](https://github.com/THUDM/ChatGLM2-6B)、[复旦MOSS](https://github.com/OpenLMLab/MOSS)伺候的感觉一定会很不错吧？
-⭐ChatGLM2微调模型 | 支持加载ChatGLM2微调模型，提供ChatGLM2微调辅助插件
 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)和[盘古α](https://openi.org.cn/pangu/)
 ⭐[void-terminal](https://github.com/binary-husky/void-terminal) pip包 | 脱离GUI，在Python中直接调用本项目的所有函数插件（开发中）
 ⭐虚空终端插件 | [插件] 能够使用自然语言直接调度本项目其他插件
@@ -111,7 +108,7 @@ Latex论文一键校对 | [插件] 仿Grammarly对Latex文章进行语法、拼
 <img src="https://user-images.githubusercontent.com/96192199/226935232-6b6a73ce-8900-4aee-93f9-733c7e6fef53.png" width="700" >
 </div>

- 多种大语言模型混合调用（ChatGLM + OpenAI-GPT3.5 + [API2D](https://api2d.com/)-GPT4）
+- 多种大语言模型混合调用（ChatGLM + OpenAI-GPT3.5 + GPT4）
 <div align="center">
 <img src="https://user-images.githubusercontent.com/96192199/232537274-deca0563-7aa6-4b5d-94a2-b7c453c47794.png" width="700" >
 </div>
@@ -152,10 +149,10 @@ Latex论文一键校对 | [插件] 仿Grammarly对Latex文章进行语法、拼
 <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>
 <p>

-【可选步骤】如果需要支持清华ChatGLM2/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）：

 ```sh
-# 【可选步骤I】支持清华ChatGLM2。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)
+# 【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
@@ -197,7 +194,7 @@ pip install peft
    docker-compose up
    ```

-1. 仅ChatGPT+文心一言+spark等在线模型（推荐大多数人选择）
+1. 仅ChatGPT + GLM4 + 文心一言+spark等在线模型（推荐大多数人选择）
 [![basic](https://github.com/binary-husky/gpt_academic/actions/workflows/build-without-local-llms.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-without-local-llms.yml)
 [![basiclatex](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml)
 [![basicaudio](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml)
@@ -209,7 +206,7 @@ pip install peft

 P.S. 如果需要依赖Latex的插件功能，请见Wiki。另外，您也可以直接使用方案4或者方案0获取Latex功能。

-2. ChatGPT + ChatGLM2 + MOSS + LLAMA2 + 通义千问（需要熟悉[Nvidia Docker](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#installing-on-ubuntu-and-debian)运行时）
+2. ChatGPT + GLM3 + MOSS + LLAMA2 + 通义千问（需要熟悉[Nvidia Docker](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#installing-on-ubuntu-and-debian)运行时）
 [![chatglm](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-chatglm.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-chatglm.yml)

    ``` sh
@@ -308,9 +305,9 @@ 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://github.com/binary-husky/gpt_academic/assets/96192199/bc7ab234-ad90-48a0-8d62-f703d9e74665" width="500" >
 </div>

-8. OpenAI音频解析与总结
+8. 基于mermaid的流图、脑图绘制
 <div align="center">
-<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/709ccf95-3aee-498a-934a-e1c22d3d5d5b" width="500" >
+<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/c518b82f-bd53-46e2-baf5-ad1b081c1da4" width="500" >
 </div>

 9. Latex全文校对纠错
@@ -327,8 +324,8 @@ 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


 ### II：版本:
-
- version 3.70（todo）: 优化AutoGen插件主题并设计一系列衍生插件
+- version 3.80(TODO): 优化AutoGen插件主题并设计一系列衍生插件
+- version 3.70: 引入Mermaid绘图，实现GPT画脑图等功能   
 - version 3.60: 引入AutoGen作为新一代插件的基石
 - version 3.57: 支持GLM3，星火v3，文心一言v4，修复本地模型的并发BUG
 - version 3.56: 支持动态追加基础功能按钮，新汇报PDF汇总页面
@@ -370,8 +367,8 @@ GPT Academic开发者QQ群：`610599535`

 1. `master` 分支: 主分支，稳定版
 2. `frontier` 分支: 开发分支，测试版
-3. 如何接入其他大模型：[接入其他大模型](request_llms/README.md)
-
+3. 如何[接入其他大模型](request_llms/README.md)
+4. 访问GPT-Academic的[在线服务并支持我们](https://github.com/binary-husky/gpt_academic/wiki/online)

 ### V：参考与学习

--- a/config.py
+++ b/config.py
@@ -89,11 +89,14 @@ DEFAULT_FN_GROUPS = ['对话', '编程', '学术', '智能体']
 LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
 AVAIL_LLM_MODELS = ["gpt-3.5-turbo-1106","gpt-4-1106-preview","gpt-4-vision-preview",
                    "gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5",
-                    "api2d-gpt-3.5-turbo", 'api2d-gpt-3.5-turbo-16k',
                    "gpt-4", "gpt-4-32k", "azure-gpt-4", "api2d-gpt-4",
-                    "chatglm3", "moss", "claude-2"]
-# P.S. 其他可用的模型还包括 ["zhipuai", "qianfan", "deepseekcoder", "llama2", "qwen", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613",  "gpt-3.5-random"
-# "spark", "sparkv2", "sparkv3", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"]
+                    "gemini-pro", "chatglm3", "claude-2", "zhipuai"]
+# P.S. 其他可用的模型还包括 [
+# "moss", "qwen-turbo", "qwen-plus", "qwen-max"
+# "zhipuai", "qianfan", "deepseekcoder", "llama2", "qwen-local", "gpt-3.5-turbo-0613", 
+# "gpt-3.5-turbo-16k-0613",  "gpt-3.5-random", "api2d-gpt-3.5-turbo", 'api2d-gpt-3.5-turbo-16k',
+# "spark", "sparkv2", "sparkv3", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"
+# ]


 # 定义界面上“询问多个GPT模型”插件应该使用哪些模型，请从AVAIL_LLM_MODELS中选择，并在不同模型之间用`&`间隔，例如"gpt-3.5-turbo&chatglm3&azure-gpt-4"
@@ -103,7 +106,11 @@ MULTI_QUERY_LLM_MODELS = "gpt-3.5-turbo&chatglm3"
 # 选择本地模型变体（只有当AVAIL_LLM_MODELS包含了对应本地模型时，才会起作用）
 # 如果你选择Qwen系列的模型，那么请在下面的QWEN_MODEL_SELECTION中指定具体的模型
 # 也可以是具体的模型路径
-QWEN_MODEL_SELECTION = "Qwen/Qwen-1_8B-Chat-Int8"
+QWEN_LOCAL_MODEL_SELECTION = "Qwen/Qwen-1_8B-Chat-Int8"
+
+
+# 接入通义千问在线大模型 https://dashscope.console.aliyun.com/
+DASHSCOPE_API_KEY = "" # 阿里灵积云API_KEY


 # 百度千帆（LLM_MODEL="qianfan"）
@@ -188,7 +195,13 @@ XFYUN_API_KEY = "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa"

 # 接入智谱大模型
 ZHIPUAI_API_KEY = ""
-ZHIPUAI_MODEL = "chatglm_turbo"
+ZHIPUAI_MODEL = "glm-4" # 可选 "glm-3-turbo" "glm-4"
+
+
+# # 火山引擎YUNQUE大模型
+# YUNQUE_SECRET_KEY = ""
+# YUNQUE_ACCESS_KEY = ""
+# YUNQUE_MODEL = ""


 # Claude API KEY
@@ -199,6 +212,10 @@ ANTHROPIC_API_KEY = ""
 CUSTOM_API_KEY_PATTERN = ""


+# Google Gemini API-Key
+GEMINI_API_KEY = ''
+
+
 # HUGGINGFACE的TOKEN，下载LLAMA时起作用 https://huggingface.co/docs/hub/security-tokens
 HUGGINGFACE_ACCESS_TOKEN = "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"

@@ -284,6 +301,12 @@ NUM_CUSTOM_BASIC_BTN = 4
 │   ├── ZHIPUAI_API_KEY
 │   └── ZHIPUAI_MODEL
 │
+├── "qwen-turbo" 等通义千问大模型
+│   └──  DASHSCOPE_API_KEY
+│
+├── "Gemini"
+│   └──  GEMINI_API_KEY
+│
 └── "newbing" Newbing接口不再稳定，不推荐使用
    ├── NEWBING_STYLE
    └── NEWBING_COOKIES
@@ -300,7 +323,7 @@ NUM_CUSTOM_BASIC_BTN = 4
 ├── "jittorllms_pangualpha"
 ├── "jittorllms_llama"
 ├── "deepseekcoder"
-├── "qwen"
+├── "qwen-local"
 ├──  RWKV的支持见Wiki
 └── "llama2"

--- a/core_functional.py
+++ b/core_functional.py
@@ -3,30 +3,58 @@
 # 'stop' 颜色对应 theme.py 中的 color_er
 import importlib
 from toolbox import clear_line_break
-
+from textwrap import dedent

 def get_core_functions():
    return {
+
        "英语学术润色": {
-            # 前缀，会被加在你的输入之前。例如，用来描述你的要求，例如翻译、解释代码、润色等等
-            "Prefix":   r"Below is a paragraph from an academic paper. Polish the writing to meet the academic style, " +
-                        r"improve the spelling, grammar, clarity, concision and overall readability. When necessary, rewrite the whole sentence. " +
+            # [1*] 前缀，会被加在你的输入之前。例如，用来描述你的要求，例如翻译、解释代码、润色等等
+            "Prefix":   r"Below is a paragraph from an academic paper. Polish the writing to meet the academic style, "
+                        r"improve the spelling, grammar, clarity, concision and overall readability. When necessary, rewrite the whole sentence. "
                        r"Firstly, you should provide the polished paragraph. "
                        r"Secondly, you should list all your modification and explain the reasons to do so in markdown table." + "\n\n",
-            # 后缀，会被加在你的输入之后。例如，配合前缀可以把你的输入内容用引号圈起来
+            # [2*] 后缀，会被加在你的输入之后。例如，配合前缀可以把你的输入内容用引号圈起来
            "Suffix":   r"",
-            # 按钮颜色 (默认 secondary)
+            # [3] 按钮颜色 (可选参数，默认 secondary)
            "Color":    r"secondary",
-            # 按钮是否可见 (默认 True，即可见)
+            # [4] 按钮是否可见 (可选参数，默认 True，即可见)
            "Visible": True,
-            # 是否在触发时清除历史 (默认 False，即不处理之前的对话历史)
-            "AutoClearHistory": False
+            # [5] 是否在触发时清除历史 (可选参数，默认 False，即不处理之前的对话历史)
+            "AutoClearHistory": False,
+            # [6] 文本预处理 （可选参数，默认 None，举例：写个函数移除所有的换行符）
+            "PreProcess": None,
        },
-        "中文学术润色": {
-            "Prefix":   r"作为一名中文学术论文写作改进助理，你的任务是改进所提供文本的拼写、语法、清晰、简洁和整体可读性，" +
-                        r"同时分解长句，减少重复，并提供改进建议。请只提供文本的更正版本，避免包括解释。请编辑以下文本" + "\n\n",
-            "Suffix":   r"",
+        
+        
+        "总结绘制脑图": {
+            # 前缀，会被加在你的输入之前。例如，用来描述你的要求，例如翻译、解释代码、润色等等
+            "Prefix":   r"",
+            # 后缀，会被加在你的输入之后。例如，配合前缀可以把你的输入内容用引号圈起来
+            "Suffix":
+                dedent("\n"+r'''
+                    ==============================
+                    使用mermaid flowchart对以上文本进行总结，概括上述段落的内容以及内在逻辑关系，例如：
+
+                    以下是对以上文本的总结，以mermaid flowchart的形式展示：
+                    ```mermaid
+                    flowchart LR
+                        A["节点名1"] --> B("节点名2")
+                        B --> C{"节点名3"}
+                        C --> D["节点名4"]
+                        C --> |"箭头名1"| E["节点名5"]
+                        C --> |"箭头名2"| F["节点名6"]
+                    ```
+
+                    警告：
+                    （1）使用中文
+                    （2）节点名字使用引号包裹，如["Laptop"]
+                    （3）`|` 和 `"`之间不要存在空格
+                    （4）根据情况选择flowchart LR（从左到右）或者flowchart TD（从上到下）
+                '''),
        },
+        
+        
        "查找语法错误": {
            "Prefix":   r"Help me ensure that the grammar and the spelling is correct. "
                        r"Do not try to polish the text, if no mistake is found, tell me that this paragraph is good. "
@@ -46,11 +74,15 @@ def get_core_functions():
            "Suffix":   r"",
            "PreProcess": clear_line_break,    # 预处理：清除换行符
        },
+        
+        
        "中译英": {
            "Prefix":   r"Please translate following sentence to English:" + "\n\n",
            "Suffix":   r"",
        },
-        "学术中英互译": {
+        
+        
+        "学术英中互译": {
            "Prefix":   r"I want you to act as a scientific English-Chinese translator, " +
                        r"I will provide you with some paragraphs in one language " +
                        r"and your task is to accurately and academically translate the paragraphs only into the other language. " +
@@ -59,28 +91,35 @@ def get_core_functions():
                        r"such as natural language processing, and rhetorical knowledge " +
                        r"and experience about effective writing techniques to reply. " +
                        r"I'll give you my paragraphs as follows, tell me what language it is written in, and then translate:" + "\n\n",
-            "Suffix": "",
-            "Color": "secondary",
+            "Suffix":   r"",
        },
+        
+        
        "英译中": {
            "Prefix":   r"翻译成地道的中文：" + "\n\n",
            "Suffix":   r"",
            "Visible":  False,
        },
+        
+        
        "找图片": {
-            "Prefix":   r"我需要你找一张网络图片。使用Unsplash API(https://source.unsplash.com/960x640/?<英语关键词>)获取图片URL，" +
+            "Prefix":   r"我需要你找一张网络图片。使用Unsplash API(https://source.unsplash.com/960x640/?<英语关键词>)获取图片URL，"
                        r"然后请使用Markdown格式封装，并且不要有反斜线，不要用代码块。现在，请按以下描述给我发送图片：" + "\n\n",
            "Suffix":   r"",
            "Visible":  False,
        },
+        
+        
        "解释代码": {
            "Prefix":   r"请解释以下代码：" + "\n```\n",
            "Suffix":   "\n```\n",
        },
+        
+        
        "参考文献转Bib": {
-            "Prefix":   r"Here are some bibliography items, please transform them into bibtex style." +
-                        r"Note that, reference styles maybe more than one kind, you should transform each item correctly." +
-                        r"Items need to be transformed:",
+            "Prefix":   r"Here are some bibliography items, please transform them into bibtex style."
+                        r"Note that, reference styles maybe more than one kind, you should transform each item correctly."
+                        r"Items need to be transformed:" + "\n\n",
            "Visible":  False,
            "Suffix":   r"",
        }
@@ -98,8 +137,14 @@ def handle_core_functionality(additional_fn, inputs, history, chatbot):
        return inputs, history
    else:
        # 预制功能
-        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）
+        if "PreProcess" in core_functional[additional_fn]:
+            if core_functional[additional_fn]["PreProcess"] is not None:
+                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"]
        if core_functional[additional_fn].get("AutoClearHistory", False):
            history = []
        return inputs, history
+
+if __name__ == "__main__":
+    t = get_core_functions()["总结绘制脑图"]
+    print(t["Prefix"] + t["Suffix"])
--- a/crazy_functional.py
+++ b/crazy_functional.py
@@ -37,110 +37,109 @@ def get_crazy_functions():
    from crazy_functions.批量Markdown翻译 import Markdown中译英
    from crazy_functions.虚空终端 import 虚空终端

-
    function_plugins = {
        "虚空终端": {
            "Group": "对话|编程|学术|智能体",
            "Color": "stop",
            "AsButton": True,
-            "Function": HotReload(虚空终端)
+            "Function": HotReload(虚空终端),
        },
        "解析整个Python项目": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": True,
            "Info": "解析一个Python项目的所有源文件(.py) | 输入参数为路径",
-            "Function": HotReload(解析一个Python项目)
+            "Function": HotReload(解析一个Python项目),
        },
        "载入对话历史存档（先上传存档或输入路径）": {
            "Group": "对话",
            "Color": "stop",
            "AsButton": False,
            "Info": "载入对话历史存档 | 输入参数为路径",
-            "Function": HotReload(载入对话历史存档)
+            "Function": HotReload(载入对话历史存档),
        },
        "删除所有本地对话历史记录（谨慎操作）": {
            "Group": "对话",
            "AsButton": False,
            "Info": "删除所有本地对话历史记录，谨慎操作 | 不需要输入参数",
-            "Function": HotReload(删除所有本地对话历史记录)
+            "Function": HotReload(删除所有本地对话历史记录),
        },
        "清除所有缓存文件（谨慎操作）": {
            "Group": "对话",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "清除所有缓存文件，谨慎操作 | 不需要输入参数",
-            "Function": HotReload(清除缓存)
+            "Function": HotReload(清除缓存),
        },
        "批量总结Word文档": {
            "Group": "学术",
            "Color": "stop",
            "AsButton": True,
            "Info": "批量总结word文档 | 输入参数为路径",
-            "Function": HotReload(总结word文档)
+            "Function": HotReload(总结word文档),
        },
        "解析整个Matlab项目": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,
            "Info": "解析一个Matlab项目的所有源文件(.m) | 输入参数为路径",
-            "Function": HotReload(解析一个Matlab项目)
+            "Function": HotReload(解析一个Matlab项目),
        },
        "解析整个C++项目头文件": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "解析一个C++项目的所有头文件(.h/.hpp) | 输入参数为路径",
-            "Function": HotReload(解析一个C项目的头文件)
+            "Function": HotReload(解析一个C项目的头文件),
        },
        "解析整个C++项目（.cpp/.hpp/.c/.h）": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "解析一个C++项目的所有源文件（.cpp/.hpp/.c/.h）| 输入参数为路径",
-            "Function": HotReload(解析一个C项目)
+            "Function": HotReload(解析一个C项目),
        },
        "解析整个Go项目": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "解析一个Go项目的所有源文件 | 输入参数为路径",
-            "Function": HotReload(解析一个Golang项目)
+            "Function": HotReload(解析一个Golang项目),
        },
        "解析整个Rust项目": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "解析一个Rust项目的所有源文件 | 输入参数为路径",
-            "Function": HotReload(解析一个Rust项目)
+            "Function": HotReload(解析一个Rust项目),
        },
        "解析整个Java项目": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "解析一个Java项目的所有源文件 | 输入参数为路径",
-            "Function": HotReload(解析一个Java项目)
+            "Function": HotReload(解析一个Java项目),
        },
        "解析整个前端项目（js,ts,css等）": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "解析一个前端项目的所有源文件（js,ts,css等） | 输入参数为路径",
-            "Function": HotReload(解析一个前端项目)
+            "Function": HotReload(解析一个前端项目),
        },
        "解析整个Lua项目": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "解析一个Lua项目的所有源文件 | 输入参数为路径",
-            "Function": HotReload(解析一个Lua项目)
+            "Function": HotReload(解析一个Lua项目),
        },
        "解析整个CSharp项目": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "解析一个CSharp项目的所有源文件 | 输入参数为路径",
-            "Function": HotReload(解析一个CSharp项目)
+            "Function": HotReload(解析一个CSharp项目),
        },
        "解析Jupyter Notebook文件": {
            "Group": "编程",
@@ -156,103 +155,102 @@ def get_crazy_functions():
            "Color": "stop",
            "AsButton": False,
            "Info": "读取Tex论文并写摘要 | 输入参数为路径",
-            "Function": HotReload(读文章写摘要)
+            "Function": HotReload(读文章写摘要),
        },
        "翻译README或MD": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": True,
            "Info": "将Markdown翻译为中文 | 输入参数为路径或URL",
-            "Function": HotReload(Markdown英译中)
+            "Function": HotReload(Markdown英译中),
        },
        "翻译Markdown或README（支持Github链接）": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,
            "Info": "将Markdown或README翻译为中文 | 输入参数为路径或URL",
-            "Function": HotReload(Markdown英译中)
+            "Function": HotReload(Markdown英译中),
        },
        "批量生成函数注释": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "批量生成函数的注释 | 输入参数为路径",
-            "Function": HotReload(批量生成函数注释)
+            "Function": HotReload(批量生成函数注释),
        },
        "保存当前的对话": {
            "Group": "对话",
            "AsButton": True,
            "Info": "保存当前的对话 | 不需要输入参数",
-            "Function": HotReload(对话历史存档)
+            "Function": HotReload(对话历史存档),
        },
        "[多线程Demo]解析此项目本身（源码自译解）": {
            "Group": "对话|编程",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "多线程解析并翻译此项目的源码 | 不需要输入参数",
-            "Function": HotReload(解析项目本身)
+            "Function": HotReload(解析项目本身),
        },
        "历史上的今天": {
            "Group": "对话",
            "AsButton": True,
            "Info": "查看历史上的今天事件 (这是一个面向开发者的插件Demo) | 不需要输入参数",
-            "Function": HotReload(高阶功能模板函数)
+            "Function": HotReload(高阶功能模板函数),
        },
        "精准翻译PDF论文": {
            "Group": "学术",
            "Color": "stop",
            "AsButton": True,
            "Info": "精准翻译PDF论文为中文 | 输入参数为路径",
-            "Function": HotReload(批量翻译PDF文档)
+            "Function": HotReload(批量翻译PDF文档),
        },
        "询问多个GPT模型": {
            "Group": "对话",
            "Color": "stop",
            "AsButton": True,
-            "Function": HotReload(同时问询)
+            "Function": HotReload(同时问询),
        },
        "批量总结PDF文档": {
            "Group": "学术",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "批量总结PDF文档的内容 | 输入参数为路径",
-            "Function": HotReload(批量总结PDF文档)
+            "Function": HotReload(批量总结PDF文档),
        },
        "谷歌学术检索助手（输入谷歌学术搜索页url）": {
            "Group": "学术",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "使用谷歌学术检索助手搜索指定URL的结果 | 输入参数为谷歌学术搜索页的URL",
-            "Function": HotReload(谷歌检索小助手)
+            "Function": HotReload(谷歌检索小助手),
        },
        "理解PDF文档内容 （模仿ChatPDF）": {
            "Group": "学术",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "理解PDF文档的内容并进行回答 | 输入参数为路径",
-            "Function": HotReload(理解PDF文档内容标准文件输入)
+            "Function": HotReload(理解PDF文档内容标准文件输入),
        },
        "英文Latex项目全文润色（输入路径或上传压缩包）": {
            "Group": "学术",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "对英文Latex项目全文进行润色处理 | 输入参数为路径或上传压缩包",
-            "Function": HotReload(Latex英文润色)
+            "Function": HotReload(Latex英文润色),
        },
        "英文Latex项目全文纠错（输入路径或上传压缩包）": {
            "Group": "学术",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "对英文Latex项目全文进行纠错处理 | 输入参数为路径或上传压缩包",
-            "Function": HotReload(Latex英文纠错)
+            "Function": HotReload(Latex英文纠错),
        },
        "中文Latex项目全文润色（输入路径或上传压缩包）": {
            "Group": "学术",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "对中文Latex项目全文进行润色处理 | 输入参数为路径或上传压缩包",
-            "Function": HotReload(Latex中文润色)
+            "Function": HotReload(Latex中文润色),
        },
-
        # 已经被新插件取代
        # "Latex项目全文中译英（输入路径或上传压缩包）": {
        #     "Group": "学术",
@@ -261,7 +259,6 @@ def get_crazy_functions():
        #     "Info": "对Latex项目全文进行中译英处理 | 输入参数为路径或上传压缩包",
        #     "Function": HotReload(Latex中译英)
        # },
-
        # 已经被新插件取代
        # "Latex项目全文英译中（输入路径或上传压缩包）": {
        #     "Group": "学术",
@@ -270,130 +267,153 @@ def get_crazy_functions():
        #     "Info": "对Latex项目全文进行英译中处理 | 输入参数为路径或上传压缩包",
        #     "Function": HotReload(Latex英译中)
        # },
-        
        "批量Markdown中译英（输入路径或上传压缩包）": {
            "Group": "编程",
            "Color": "stop",
            "AsButton": False,  # 加入下拉菜单中
            "Info": "批量将Markdown文件中文翻译为英文 | 输入参数为路径或上传压缩包",
-            "Function": HotReload(Markdown中译英)
+            "Function": HotReload(Markdown中译英),
        },
    }

    # -=--=- 尚未充分测试的实验性插件 & 需要额外依赖的插件 -=--=-
    try:
        from crazy_functions.下载arxiv论文翻译摘要 import 下载arxiv论文并翻译摘要
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "一键下载arxiv论文并翻译摘要（先在input输入编号，如1812.10695）": {
                    "Group": "学术",
                    "Color": "stop",
                    "AsButton": False,  # 加入下拉菜单中
                    # "Info": "下载arxiv论文并翻译摘要 | 输入参数为arxiv编号如1812.10695",
-                "Function": HotReload(下载arxiv论文并翻译摘要)
+                    "Function": HotReload(下载arxiv论文并翻译摘要),
                }
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

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

    try:
        from crazy_functions.解析项目源代码 import 解析任意code项目
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "解析项目源代码（手动指定和筛选源代码文件类型）": {
                    "Group": "编程",
                    "Color": "stop",
                    "AsButton": False,
                    "AdvancedArgs": True,  # 调用时，唤起高级参数输入区（默认False）
-                "ArgsReminder": "输入时用逗号隔开, *代表通配符, 加了^代表不匹配; 不输入代表全部匹配。例如: \"*.c, ^*.cpp, config.toml, ^*.toml\"",  # 高级参数输入区的显示提示
-                "Function": HotReload(解析任意code项目)
+                    "ArgsReminder": '输入时用逗号隔开, *代表通配符, 加了^代表不匹配; 不输入代表全部匹配。例如: "*.c, ^*.cpp, config.toml, ^*.toml"',  # 高级参数输入区的显示提示
+                    "Function": HotReload(解析任意code项目),
                },
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.询问多个大语言模型 import 同时问询_指定模型
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "询问多个GPT模型（手动指定询问哪些模型）": {
                    "Group": "对话",
                    "Color": "stop",
                    "AsButton": False,
                    "AdvancedArgs": True,  # 调用时，唤起高级参数输入区（默认False）
-                "ArgsReminder": "支持任意数量的llm接口，用&符号分隔。例如chatglm&gpt-3.5-turbo&api2d-gpt-4",  # 高级参数输入区的显示提示
-                "Function": HotReload(同时问询_指定模型)
+                    "ArgsReminder": "支持任意数量的llm接口，用&符号分隔。例如chatglm&gpt-3.5-turbo&gpt-4",  # 高级参数输入区的显示提示
+                    "Function": HotReload(同时问询_指定模型),
                },
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.图片生成 import 图片生成_DALLE2, 图片生成_DALLE3, 图片修改_DALLE2
-        function_plugins.update({
-            "图片生成_DALLE2 （先切换模型到openai或api2d）": {
+
+        function_plugins.update(
+            {
+                "图片生成_DALLE2 （先切换模型到gpt-*）": {
                    "Group": "对话",
                    "Color": "stop",
                    "AsButton": False,
                    "AdvancedArgs": True,  # 调用时，唤起高级参数输入区（默认False）
                    "ArgsReminder": "在这里输入分辨率, 如1024x1024（默认），支持 256x256, 512x512, 1024x1024",  # 高级参数输入区的显示提示
                    "Info": "使用DALLE2生成图片 | 输入参数字符串，提供图像的内容",
-                "Function": HotReload(图片生成_DALLE2)
+                    "Function": HotReload(图片生成_DALLE2),
                },
-        })
-        function_plugins.update({
-            "图片生成_DALLE3 （先切换模型到openai或api2d）": {
+            }
+        )
+        function_plugins.update(
+            {
+                "图片生成_DALLE3 （先切换模型到gpt-*）": {
                    "Group": "对话",
                    "Color": "stop",
                    "AsButton": False,
                    "AdvancedArgs": True,  # 调用时，唤起高级参数输入区（默认False）
                    "ArgsReminder": "在这里输入自定义参数「分辨率-质量(可选)-风格(可选)」, 参数示例「1024x1024-hd-vivid」 || 分辨率支持 「1024x1024」(默认) /「1792x1024」/「1024x1792」 || 质量支持 「-standard」(默认) /「-hd」 || 风格支持 「-vivid」(默认) /「-natural」",  # 高级参数输入区的显示提示
                    "Info": "使用DALLE3生成图片 | 输入参数字符串，提供图像的内容",
-                "Function": HotReload(图片生成_DALLE3)
+                    "Function": HotReload(图片生成_DALLE3),
                },
-        })
-        function_plugins.update({
-            "图片修改_DALLE2 （先切换模型到openai或api2d）": {
+            }
+        )
+        function_plugins.update(
+            {
+                "图片修改_DALLE2 （先切换模型到gpt-*）": {
                    "Group": "对话",
                    "Color": "stop",
                    "AsButton": False,
                    "AdvancedArgs": False,  # 调用时，唤起高级参数输入区（默认False）
                    # "Info": "使用DALLE2修改图片 | 输入参数字符串，提供图像的内容",
-                "Function": HotReload(图片修改_DALLE2)
+                    "Function": HotReload(图片修改_DALLE2),
                },
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.总结音视频 import 总结音视频
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "批量总结音视频（输入路径或上传压缩包）": {
                    "Group": "对话",
                    "Color": "stop",
@@ -401,203 +421,255 @@ def get_crazy_functions():
                    "AdvancedArgs": True,
                    "ArgsReminder": "调用openai api 使用whisper-1模型, 目前支持的格式:mp4, m4a, wav, mpga, mpeg, mp3。此处可以输入解析提示，例如：解析为简体中文（默认）。",
                    "Info": "批量总结音频或视频 | 输入参数为路径",
-                "Function": HotReload(总结音视频)
+                    "Function": HotReload(总结音视频),
                }
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.数学动画生成manim import 动画生成
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "数学动画生成（Manim）": {
                    "Group": "对话",
                    "Color": "stop",
                    "AsButton": False,
                    "Info": "按照自然语言描述生成一个动画 | 输入参数是一段话",
-                "Function": HotReload(动画生成)
+                    "Function": HotReload(动画生成),
                }
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.批量Markdown翻译 import Markdown翻译指定语言
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "Markdown翻译（指定翻译成何种语言）": {
                    "Group": "编程",
                    "Color": "stop",
                    "AsButton": False,
                    "AdvancedArgs": True,
                    "ArgsReminder": "请输入要翻译成哪种语言，默认为Chinese。",
-                "Function": HotReload(Markdown翻译指定语言)
+                    "Function": HotReload(Markdown翻译指定语言),
                }
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.知识库问答 import 知识库文件注入
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "构建知识库（先上传文件素材,再运行此插件）": {
                    "Group": "对话",
                    "Color": "stop",
                    "AsButton": False,
                    "AdvancedArgs": True,
                    "ArgsReminder": "此处待注入的知识库名称id, 默认为default。文件进入知识库后可长期保存。可以通过再次调用本插件的方式，向知识库追加更多文档。",
-                "Function": HotReload(知识库文件注入)
+                    "Function": HotReload(知识库文件注入),
                }
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.知识库问答 import 读取知识库作答
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "知识库文件注入（构建知识库后,再运行此插件）": {
                    "Group": "对话",
                    "Color": "stop",
                    "AsButton": False,
                    "AdvancedArgs": True,
                    "ArgsReminder": "待提取的知识库名称id, 默认为default, 您需要构建知识库后再运行此插件。",
-                "Function": HotReload(读取知识库作答)
+                    "Function": HotReload(读取知识库作答),
                }
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.交互功能函数模板 import 交互功能模板函数
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "交互功能模板Demo函数（查找wallhaven.cc的壁纸）": {
                    "Group": "对话",
                    "Color": "stop",
                    "AsButton": False,
-                "Function": HotReload(交互功能模板函数)
+                    "Function": HotReload(交互功能模板函数),
                }
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.Latex输出PDF结果 import Latex英文纠错加PDF对比
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "Latex英文纠错+高亮修正位置 [需Latex]": {
                    "Group": "学术",
                    "Color": "stop",
                    "AsButton": False,
                    "AdvancedArgs": True,
                    "ArgsReminder": "如果有必要, 请在此处追加更细致的矫错指令（使用英文）。",
-                "Function": HotReload(Latex英文纠错加PDF对比)
+                    "Function": HotReload(Latex英文纠错加PDF对比),
                }
-        })
+            }
+        )
        from crazy_functions.Latex输出PDF结果 import Latex翻译中文并重新编译PDF
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "Arxiv论文精细翻译（输入arxivID）[需Latex]": {
                    "Group": "学术",
                    "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". ',
+                    "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". ',
                    "Info": "Arixv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
-                "Function": HotReload(Latex翻译中文并重新编译PDF)
+                    "Function": HotReload(Latex翻译中文并重新编译PDF),
                }
-        })
-        function_plugins.update({
+            }
+        )
+        function_plugins.update(
+            {
                "本地Latex论文精细翻译（上传Latex项目）[需Latex]": {
                    "Group": "学术",
                    "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". ',
+                    "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". ',
                    "Info": "本地Latex论文精细翻译 | 输入参数是路径",
-                "Function": HotReload(Latex翻译中文并重新编译PDF)
+                    "Function": HotReload(Latex翻译中文并重新编译PDF),
                }
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from toolbox import get_conf
-        ENABLE_AUDIO = get_conf('ENABLE_AUDIO')
+
+        ENABLE_AUDIO = get_conf("ENABLE_AUDIO")
        if ENABLE_AUDIO:
            from crazy_functions.语音助手 import 语音助手
-            function_plugins.update({
+
+            function_plugins.update(
+                {
                    "实时语音对话": {
                        "Group": "对话",
                        "Color": "stop",
                        "AsButton": True,
                        "Info": "这是一个时刻聆听着的语音对话助手 | 没有输入参数",
-                    "Function": HotReload(语音助手)
+                        "Function": HotReload(语音助手),
                    }
-            })
+                }
+            )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.批量翻译PDF文档_NOUGAT import 批量翻译PDF文档
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "精准翻译PDF文档（NOUGAT）": {
                    "Group": "学术",
                    "Color": "stop",
                    "AsButton": False,
-                "Function": HotReload(批量翻译PDF文档)
+                    "Function": HotReload(批量翻译PDF文档),
                }
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.函数动态生成 import 函数动态生成
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "动态代码解释器（CodeInterpreter）": {
                    "Group": "智能体",
                    "Color": "stop",
                    "AsButton": False,
-                "Function": HotReload(函数动态生成)
+                    "Function": HotReload(函数动态生成),
                }
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")

    try:
        from crazy_functions.多智能体 import 多智能体终端
-        function_plugins.update({
+
+        function_plugins.update(
+            {
                "AutoGen多智能体终端（仅供测试）": {
                    "Group": "智能体",
                    "Color": "stop",
                    "AsButton": False,
-                "Function": HotReload(多智能体终端)
+                    "Function": HotReload(多智能体终端),
                }
-        })
+            }
+        )
    except:
        print(trimmed_format_exc())
-        print('Load function plugin failed')
+        print("Load function plugin failed")
+
+    try:
+        from crazy_functions.互动小游戏 import 随机小游戏
+
+        function_plugins.update(
+            {
+                "随机互动小游戏（仅供测试）": {
+                    "Group": "智能体",
+                    "Color": "stop",
+                    "AsButton": False,
+                    "Function": HotReload(随机小游戏),
+                }
+            }
+        )
+    except:
+        print(trimmed_format_exc())
+        print("Load function plugin failed")

    # try:
-    #     from crazy_functions.互动小游戏 import 随机小游戏
+    #     from crazy_functions.高级功能函数模板 import 测试图表渲染
    #     function_plugins.update({
-    #         "随机小游戏": {
+    #         "绘制逻辑关系（测试图表渲染）": {
    #             "Group": "智能体",
    #             "Color": "stop",
    #             "AsButton": True,
-    #             "Function": HotReload(随机小游戏)
+    #             "Function": HotReload(测试图表渲染)
    #         }
    #     })
    # except:
@@ -618,8 +690,6 @@ def get_crazy_functions():
    # except:
    #     print('Load function plugin failed')

-
-
    """
    设置默认值:
    - 默认 Group = 对话
@@ -629,12 +699,12 @@ def get_crazy_functions():
    """
    for name, function_meta in function_plugins.items():
        if "Group" not in function_meta:
-            function_plugins[name]["Group"] = '对话'
+            function_plugins[name]["Group"] = "对话"
        if "AsButton" not in function_meta:
            function_plugins[name]["AsButton"] = True
        if "AdvancedArgs" not in function_meta:
            function_plugins[name]["AdvancedArgs"] = False
        if "Color" not in function_meta:
-            function_plugins[name]["Color"] = 'secondary'
+            function_plugins[name]["Color"] = "secondary"

    return function_plugins
--- a/crazy_functions/Latex全文润色.py
+++ b/crazy_functions/Latex全文润色.py
@@ -26,8 +26,8 @@ class PaperFileGroup():
                self.sp_file_index.append(index)
                self.sp_file_tag.append(self.file_paths[index])
            else:
-                from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
-                segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit)
+                from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
+                segments = breakdown_text_to_satisfy_token_limit(file_content, max_token_limit)
                for j, segment in enumerate(segments):
                    self.sp_file_contents.append(segment)
                    self.sp_file_index.append(index)
--- a/crazy_functions/Latex全文翻译.py
+++ b/crazy_functions/Latex全文翻译.py
@@ -26,8 +26,8 @@ class PaperFileGroup():
                self.sp_file_index.append(index)
                self.sp_file_tag.append(self.file_paths[index])
            else:
-                from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
-                segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit)
+                from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
+                segments = breakdown_text_to_satisfy_token_limit(file_content, max_token_limit)
                for j, segment in enumerate(segments):
                    self.sp_file_contents.append(segment)
                    self.sp_file_index.append(index)
--- a/crazy_functions/Latex输出PDF结果.py
+++ b/crazy_functions/Latex输出PDF结果.py
@@ -5,7 +5,7 @@ import glob, os, requests, time
 pj = os.path.join
 ARXIV_CACHE_DIR = os.path.expanduser(f"~/arxiv_cache/")

-# =================================== 工具函数 ===============================================
+# =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- 工具函数 =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 # 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):
    """
@@ -142,7 +142,7 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):
    from toolbox import extract_archive
    extract_archive(file_path=dst, dest_dir=extract_dst)
    return extract_dst, arxiv_id
-# ========================================= 插件主程序1 =====================================================    
+# =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= 插件主程序1 =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=    


@CatchException
@@ -218,7 +218,7 @@ def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, histo
    # <-------------- we are done ------------->
    return success

-# ========================================= 插件主程序2 =====================================================    
+# =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= 插件主程序2 =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=    

@CatchException
 def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
--- a/crazy_functions/crazy_utils.py
+++ b/crazy_functions/crazy_utils.py
@@ -139,6 +139,8 @@ def can_multi_process(llm):
    if llm.startswith('gpt-'): return True
    if llm.startswith('api2d-'): return True
    if llm.startswith('azure-'): return True
+    if llm.startswith('spark'): return True
+    if llm.startswith('zhipuai'): return True
    return False

 def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
@@ -312,95 +314,6 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
    return gpt_response_collection


-def breakdown_txt_to_satisfy_token_limit(txt, get_token_fn, limit):
-    def cut(txt_tocut, must_break_at_empty_line):  # 递归
-        if get_token_fn(txt_tocut) <= limit:
-            return [txt_tocut]
-        else:
-            lines = txt_tocut.split('\n')
-            estimated_line_cut = limit / get_token_fn(txt_tocut) * len(lines)
-            estimated_line_cut = int(estimated_line_cut)
-            for cnt in reversed(range(estimated_line_cut)):
-                if must_break_at_empty_line:
-                    if lines[cnt] != "":
-                        continue
-                print(cnt)
-                prev = "\n".join(lines[:cnt])
-                post = "\n".join(lines[cnt:])
-                if get_token_fn(prev) < limit:
-                    break
-            if cnt == 0:
-                raise RuntimeError("存在一行极长的文本！")
-            # print(len(post))
-            # 列表递归接龙
-            result = [prev]
-            result.extend(cut(post, must_break_at_empty_line))
-            return result
-    try:
-        return cut(txt, must_break_at_empty_line=True)
-    except RuntimeError:
-        return cut(txt, must_break_at_empty_line=False)
-
-
-def force_breakdown(txt, limit, get_token_fn):
-    """
-    当无法用标点、空行分割时，我们用最暴力的方法切割
-    """
-    for i in reversed(range(len(txt))):
-        if get_token_fn(txt[:i]) < limit:
-            return txt[:i], txt[i:]
-    return "Tiktoken未知错误", "Tiktoken未知错误"
-
-def breakdown_txt_to_satisfy_token_limit_for_pdf(txt, get_token_fn, limit):
-    # 递归
-    def cut(txt_tocut, must_break_at_empty_line, break_anyway=False):  
-        if get_token_fn(txt_tocut) <= limit:
-            return [txt_tocut]
-        else:
-            lines = txt_tocut.split('\n')
-            estimated_line_cut = limit / get_token_fn(txt_tocut) * len(lines)
-            estimated_line_cut = int(estimated_line_cut)
-            cnt = 0
-            for cnt in reversed(range(estimated_line_cut)):
-                if must_break_at_empty_line:
-                    if lines[cnt] != "":
-                        continue
-                prev = "\n".join(lines[:cnt])
-                post = "\n".join(lines[cnt:])
-                if get_token_fn(prev) < limit:
-                    break
-            if cnt == 0:
-                if break_anyway:
-                    prev, post = force_breakdown(txt_tocut, limit, get_token_fn)
-                else:
-                    raise RuntimeError(f"存在一行极长的文本！{txt_tocut}")
-            # print(len(post))
-            # 列表递归接龙
-            result = [prev]
-            result.extend(cut(post, must_break_at_empty_line, break_anyway=break_anyway))
-            return result
-    try:
-        # 第1次尝试，将双空行（\n\n）作为切分点
-        return cut(txt, must_break_at_empty_line=True)
-    except RuntimeError:
-        try:
-            # 第2次尝试，将单空行（\n）作为切分点
-            return cut(txt, must_break_at_empty_line=False)
-        except RuntimeError:
-            try:
-                # 第3次尝试，将英文句号（.）作为切分点
-                res = cut(txt.replace('.', '。\n'), must_break_at_empty_line=False) # 这个中文的句号是故意的，作为一个标识而存在
-                return [r.replace('。\n', '.') for r in res]
-            except RuntimeError as e:
-                try:
-                    # 第4次尝试，将中文句号（。）作为切分点
-                    res = cut(txt.replace('。', '。。\n'), must_break_at_empty_line=False)
-                    return [r.replace('。。\n', '。') for r in res]
-                except RuntimeError as e:
-                    # 第5次尝试，没办法了，随便切一下敷衍吧
-                    return cut(txt, must_break_at_empty_line=False, break_anyway=True)
-
-

 def read_and_clean_pdf_text(fp):
    """
@@ -553,6 +466,9 @@ def read_and_clean_pdf_text(fp):
                    return True
                else:
                    return False
+            # 对于某些PDF会有第一个段落就以小写字母开头,为了避免索引错误将其更改为大写
+            if starts_with_lowercase_word(meta_txt[0]):
+                meta_txt[0] = meta_txt[0].capitalize()
            for _ in range(100):
                for index, block_txt in enumerate(meta_txt):
                    if starts_with_lowercase_word(block_txt):
@@ -631,7 +547,6 @@ def get_files_from_everything(txt, type): # type='.md'



-    
@Singleton
 class nougat_interface():
    def __init__(self):
--- a/crazy_functions/game_fns/game_ascii_art.py
+++ b/crazy_functions/game_fns/game_ascii_art.py
@@ -0,0 +1,42 @@
+from toolbox import CatchException, update_ui, update_ui_lastest_msg
+from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
+from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+from request_llms.bridge_all import predict_no_ui_long_connection
+from crazy_functions.game_fns.game_utils import get_code_block, is_same_thing
+import random
+
+
+class MiniGame_ASCII_Art(GptAcademicGameBaseState):
+    def step(self, prompt, chatbot, history):
+        if self.step_cnt == 0:  
+            chatbot.append(["我画你猜（动物）", "请稍等..."])
+        else:
+            if prompt.strip() == 'exit':
+                self.delete_game = True
+                yield from update_ui_lastest_msg(lastmsg=f"谜底是{self.obj}，游戏结束。", chatbot=chatbot, history=history, delay=0.)
+                return
+            chatbot.append([prompt, ""])
+        yield from update_ui(chatbot=chatbot, history=history)
+
+        if self.step_cnt == 0:
+            self.lock_plugin(chatbot)
+            self.cur_task = 'draw'
+
+        if self.cur_task == 'draw':
+            avail_obj = ["狗","猫","鸟","鱼","老鼠","蛇"]
+            self.obj = random.choice(avail_obj)
+            inputs = "I want to play a game called Guess the ASCII art. You can draw the ASCII art and I will try to guess it. " + \
+                f"This time you draw a {self.obj}. Note that you must not indicate what you have draw in the text, and you should only produce the ASCII art wrapped by ```. "
+            raw_res = predict_no_ui_long_connection(inputs=inputs, llm_kwargs=self.llm_kwargs, history=[], sys_prompt="")
+            self.cur_task = 'identify user guess'
+            res = get_code_block(raw_res)
+            history += ['', f'the answer is {self.obj}', inputs, res]
+            yield from update_ui_lastest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.)
+
+        elif self.cur_task == 'identify user guess':
+            if is_same_thing(self.obj, prompt, self.llm_kwargs):
+                self.delete_game = True
+                yield from update_ui_lastest_msg(lastmsg="你猜对了！", chatbot=chatbot, history=history, delay=0.)
+            else:
+                self.cur_task = 'identify user guess'
+                yield from update_ui_lastest_msg(lastmsg="猜错了，再试试，输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.)
--- a/crazy_functions/game_fns/game_interactive_story.py
+++ b/crazy_functions/game_fns/game_interactive_story.py
@@ -0,0 +1,212 @@
+prompts_hs = """ 请以“{headstart}”为开头，编写一个小说的第一幕。
+
+- 尽量短，不要包含太多情节，因为你接下来将会与用户互动续写下面的情节，要留出足够的互动空间。
+- 出现人物时，给出人物的名字。
+- 积极地运用环境描写、人物描写等手法，让读者能够感受到你的故事世界。
+- 积极地运用修辞手法，比如比喻、拟人、排比、对偶、夸张等等。
+- 字数要求：第一幕的字数少于300字，且少于2个段落。
+"""
+
+prompts_interact = """ 小说的前文回顾：
+「
+{previously_on_story}
+」
+
+你是一个作家，根据以上的情节，给出4种不同的后续剧情发展方向，每个发展方向都精明扼要地用一句话说明。稍后，我将在这4个选择中，挑选一种剧情发展。
+
+输出格式例如：
+1. 后续剧情发展1
+2. 后续剧情发展2
+3. 后续剧情发展3
+4. 后续剧情发展4
+"""
+
+
+prompts_resume = """小说的前文回顾：
+「
+{previously_on_story}
+」
+
+你是一个作家，我们正在互相讨论，确定后续剧情的发展。
+在以下的剧情发展中，
+「
+{choice}
+」
+我认为更合理的是：{user_choice}。
+请在前文的基础上（不要重复前文），围绕我选定的剧情情节，编写小说的下一幕。
+
+- 禁止杜撰不符合我选择的剧情。
+- 尽量短，不要包含太多情节，因为你接下来将会与用户互动续写下面的情节，要留出足够的互动空间。
+- 不要重复前文。
+- 出现人物时，给出人物的名字。
+- 积极地运用环境描写、人物描写等手法，让读者能够感受到你的故事世界。
+- 积极地运用修辞手法，比如比喻、拟人、排比、对偶、夸张等等。
+- 小说的下一幕字数少于300字，且少于2个段落。
+"""
+
+
+prompts_terminate = """小说的前文回顾：
+「
+{previously_on_story}
+」
+
+你是一个作家，我们正在互相讨论，确定后续剧情的发展。
+现在，故事该结束了，我认为最合理的故事结局是：{user_choice}。
+
+请在前文的基础上（不要重复前文），编写小说的最后一幕。
+
+- 不要重复前文。
+- 出现人物时，给出人物的名字。
+- 积极地运用环境描写、人物描写等手法，让读者能够感受到你的故事世界。
+- 积极地运用修辞手法，比如比喻、拟人、排比、对偶、夸张等等。
+- 字数要求：最后一幕的字数少于1000字。
+"""
+
+
+from toolbox import CatchException, update_ui, update_ui_lastest_msg
+from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
+from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+from request_llms.bridge_all import predict_no_ui_long_connection
+from crazy_functions.game_fns.game_utils import get_code_block, is_same_thing
+import random
+
+
+class MiniGame_ResumeStory(GptAcademicGameBaseState):
+    story_headstart = [
+        '先行者知道，他现在是全宇宙中唯一的一个人了。',
+        '深夜，一个年轻人穿过天安门广场向纪念堂走去。在二十二世纪编年史中，计算机把他的代号定为M102。',
+        '他知道，这最后一课要提前讲了。又一阵剧痛从肝部袭来，几乎使他晕厥过去。',
+        '在距地球五万光年的远方，在银河系的中心，一场延续了两万年的星际战争已接近尾声。那里的太空中渐渐隐现出一个方形区域，仿佛灿烂的群星的背景被剪出一个方口。',
+        '伊依一行三人乘坐一艘游艇在南太平洋上做吟诗航行，他们的目的地是南极，如果几天后能顺利到达那里，他们将钻出地壳去看诗云。',
+        '很多人生来就会莫名其妙地迷上一样东西，仿佛他的出生就是要和这东西约会似的，正是这样，圆圆迷上了肥皂泡。'
+    ]
+
+
+    def begin_game_step_0(self, prompt, chatbot, history):
+        # init game at step 0
+        self.headstart = random.choice(self.story_headstart)
+        self.story = []
+        chatbot.append(["互动写故事", f"这次的故事开头是：{self.headstart}"])
+        self.sys_prompt_ = '你是一个想象力丰富的杰出作家。正在与你的朋友互动，一起写故事，因此你每次写的故事段落应少于300字（结局除外）。'
+        
+        
+    def generate_story_image(self, story_paragraph):
+        try:
+            from crazy_functions.图片生成 import gen_image
+            prompt_ = predict_no_ui_long_connection(inputs=story_paragraph, llm_kwargs=self.llm_kwargs, history=[], sys_prompt='你需要根据用户给出的小说段落，进行简短的环境描写。要求：80字以内。')
+            image_url, image_path = gen_image(self.llm_kwargs, prompt_, '512x512', model="dall-e-2", quality='standard', style='natural')
+            return f'<br/><div align="center"><img src="file={image_path}"></div>'
+        except:
+            return ''
+        
+    def step(self, prompt, chatbot, history):
+        
+        """
+        首先，处理游戏初始化等特殊情况
+        """
+        if self.step_cnt == 0:  
+            self.begin_game_step_0(prompt, chatbot, history)
+            self.lock_plugin(chatbot)
+            self.cur_task = 'head_start'
+        else:
+            if prompt.strip() == 'exit' or prompt.strip() == '结束剧情':
+                # should we terminate game here?
+                self.delete_game = True
+                yield from update_ui_lastest_msg(lastmsg=f"游戏结束。", chatbot=chatbot, history=history, delay=0.)
+                return
+            if '剧情收尾' in prompt:
+                self.cur_task = 'story_terminate'
+            # # well, game resumes
+            # chatbot.append([prompt, ""])
+        # update ui, don't keep the user waiting
+        yield from update_ui(chatbot=chatbot, history=history)
+
+
+        """
+        处理游戏的主体逻辑
+        """
+        if self.cur_task == 'head_start':
+            """
+            这是游戏的第一步
+            """
+            inputs_ = prompts_hs.format(headstart=self.headstart)
+            history_ = []
+            story_paragraph = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs_, '故事开头', self.llm_kwargs, 
+                chatbot, history_, self.sys_prompt_
+            )
+            self.story.append(story_paragraph)
+            # # 配图
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+
+            # # 构建后续剧情引导
+            previously_on_story = ""
+            for s in self.story:
+                previously_on_story += s + '\n'
+            inputs_ = prompts_interact.format(previously_on_story=previously_on_story)
+            history_ = []
+            self.next_choices = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs_, '请在以下几种故事走向中，选择一种（当然，您也可以选择给出其他故事走向）：', self.llm_kwargs, 
+                chatbot,
+                history_,
+                self.sys_prompt_
+            )
+            self.cur_task = 'user_choice'
+
+
+        elif self.cur_task == 'user_choice':
+            """
+            根据用户的提示，确定故事的下一步
+            """
+            if '请在以下几种故事走向中，选择一种' in chatbot[-1][0]: chatbot.pop(-1)
+            previously_on_story = ""
+            for s in self.story:
+                previously_on_story += s + '\n'
+            inputs_ = prompts_resume.format(previously_on_story=previously_on_story, choice=self.next_choices, user_choice=prompt)
+            history_ = []
+            story_paragraph = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs_, f'下一段故事（您的选择是：{prompt}）。', self.llm_kwargs, 
+                chatbot, history_, self.sys_prompt_
+            )
+            self.story.append(story_paragraph)
+            # # 配图
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+
+            # # 构建后续剧情引导
+            previously_on_story = ""
+            for s in self.story:
+                previously_on_story += s + '\n'
+            inputs_ = prompts_interact.format(previously_on_story=previously_on_story)
+            history_ = []
+            self.next_choices = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs_, 
+                '请在以下几种故事走向中，选择一种。当然，您也可以给出您心中的其他故事走向。另外，如果您希望剧情立即收尾，请输入剧情走向，并以“剧情收尾”四个字提示程序。', self.llm_kwargs, 
+                chatbot, 
+                history_, 
+                self.sys_prompt_
+            )
+            self.cur_task = 'user_choice'
+
+
+        elif self.cur_task == 'story_terminate':
+            """
+            根据用户的提示，确定故事的结局
+            """
+            previously_on_story = ""
+            for s in self.story:
+                previously_on_story += s + '\n'
+            inputs_ = prompts_terminate.format(previously_on_story=previously_on_story, user_choice=prompt)
+            history_ = []
+            story_paragraph = yield from request_gpt_model_in_new_thread_with_ui_alive(
+                inputs_, f'故事收尾（您的选择是：{prompt}）。', self.llm_kwargs, 
+                chatbot, history_, self.sys_prompt_
+            )
+            # # 配图
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+
+            # terminate game
+            self.delete_game = True
+            return
--- a/crazy_functions/ipc_fns/mp.py
+++ b/crazy_functions/ipc_fns/mp.py
@@ -0,0 +1,37 @@
+import platform 
+import pickle
+import multiprocessing
+
+def run_in_subprocess_wrapper_func(v_args):
+    func, args, kwargs, return_dict, exception_dict = pickle.loads(v_args)
+    import sys
+    try:
+        result = func(*args, **kwargs)
+        return_dict['result'] = result
+    except Exception as e:
+        exc_info = sys.exc_info()
+        exception_dict['exception'] = exc_info
+
+def run_in_subprocess_with_timeout(func, timeout=60):
+    if platform.system() == 'Linux':
+        def wrapper(*args, **kwargs):
+            return_dict = multiprocessing.Manager().dict()
+            exception_dict = multiprocessing.Manager().dict()
+            v_args = pickle.dumps((func, args, kwargs, return_dict, exception_dict))
+            process = multiprocessing.Process(target=run_in_subprocess_wrapper_func, args=(v_args,))
+            process.start()
+            process.join(timeout)
+            if process.is_alive():
+                process.terminate()
+                raise TimeoutError(f'功能单元{str(func)}未能在规定时间内完成任务')
+            process.close()
+            if 'exception' in exception_dict:
+                # ooops, the subprocess ran into an exception
+                exc_info = exception_dict['exception']
+                raise exc_info[1].with_traceback(exc_info[2])
+            if 'result' in return_dict.keys():
+                # If the subprocess ran successfully, return the result
+                return return_dict['result']
+        return wrapper
+    else:
+        return func
--- a/crazy_functions/latex_fns/latex_actions.py
+++ b/crazy_functions/latex_fns/latex_actions.py
@@ -175,7 +175,6 @@ class LatexPaperFileGroup():
        self.sp_file_contents = []
        self.sp_file_index = []
        self.sp_file_tag = []
-
        # count_token
        from request_llms.bridge_all import model_info
        enc = model_info["gpt-3.5-turbo"]['tokenizer']
@@ -192,13 +191,12 @@ class LatexPaperFileGroup():
                self.sp_file_index.append(index)
                self.sp_file_tag.append(self.file_paths[index])
            else:
-                from ..crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
-                segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit)
+                from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
+                segments = breakdown_text_to_satisfy_token_limit(file_content, max_token_limit)
                for j, segment in enumerate(segments):
                    self.sp_file_contents.append(segment)
                    self.sp_file_index.append(index)
                    self.sp_file_tag.append(self.file_paths[index] + f".part-{j}.tex")
-        print('Segmentation: done')

    def merge_result(self):
        self.file_result = ["" for _ in range(len(self.file_paths))]
@@ -404,7 +402,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
            result_pdf = pj(work_folder_modified, f'merge_diff.pdf')    # get pdf path
            promote_file_to_downloadzone(result_pdf, rename_file=None, chatbot=chatbot)  # promote file to web UI
        if modified_pdf_success:
-            yield from update_ui_lastest_msg(f'转化PDF编译已经成功, 即将退出 ...', chatbot, history)    # 刷新Gradio前端界面
+            yield from update_ui_lastest_msg(f'转化PDF编译已经成功, 正在尝试生成对比PDF, 请稍候 ...', chatbot, history)    # 刷新Gradio前端界面
            result_pdf = pj(work_folder_modified, f'{main_file_modified}.pdf') # get pdf path
            origin_pdf = pj(work_folder_original, f'{main_file_original}.pdf') # get pdf path
            if os.path.exists(pj(work_folder, '..', 'translation')):
--- a/crazy_functions/latex_fns/latex_toolbox.py
+++ b/crazy_functions/latex_fns/latex_toolbox.py
@@ -1,15 +1,18 @@
 import os, shutil
 import re
 import numpy as np
+
 PRESERVE = 0
 TRANSFORM = 1

 pj = os.path.join

-class LinkedListNode():
+
+class LinkedListNode:
    """
    Linked List Node
    """
+
    def __init__(self, string, preserve=True) -> None:
        self.string = string
        self.preserve = preserve
@@ -18,12 +21,14 @@ class LinkedListNode():
        # self.begin_line = 0
        # self.begin_char = 0

+
 def convert_to_linklist(text, mask):
    root = LinkedListNode("", preserve=True)
    current_node = root
    for c, m, i in zip(text, mask, range(len(text))):
-        if (m==PRESERVE and current_node.preserve) \
-            or (m==TRANSFORM and not current_node.preserve):
+        if (m == PRESERVE and current_node.preserve) or (
+            m == TRANSFORM and not current_node.preserve
+        ):
            # add
            current_node.string += c
        else:
@@ -31,6 +36,7 @@ def convert_to_linklist(text, mask):
            current_node = current_node.next
    return root

+
 def post_process(root):
    # 修复括号
    node = root
@@ -38,21 +44,24 @@ def post_process(root):
        string = node.string
        if node.preserve:
            node = node.next
-            if node is None: break
+            if node is None:
+                break
            continue
+
        def break_check(string):
            str_stack = [""]  # (lv, index)
            for i, c in enumerate(string):
-                if c == '{':
-                    str_stack.append('{')
-                elif c == '}':
+                if c == "{":
+                    str_stack.append("{")
+                elif c == "}":
                    if len(str_stack) == 1:
-                        print('stack fix')
+                        print("stack fix")
                        return i
                    str_stack.pop(-1)
                else:
                    str_stack[-1] += c
            return -1
+
        bp = break_check(string)

        if bp == -1:
@@ -69,51 +78,66 @@ def post_process(root):
            node.next = q

        node = node.next
-        if node is None: break
+        if node is None:
+            break

    # 屏蔽空行和太短的句子
    node = root
    while True:
-        if len(node.string.strip('\n').strip(''))==0: node.preserve = True
-        if len(node.string.strip('\n').strip(''))<42: node.preserve = True
+        if len(node.string.strip("\n").strip("")) == 0:
+            node.preserve = True
+        if len(node.string.strip("\n").strip("")) < 42:
+            node.preserve = True
        node = node.next
-        if node is None: break
+        if node is None:
+            break
    node = root
    while True:
        if node.next and node.preserve and node.next.preserve:
            node.string += node.next.string
            node.next = node.next.next
        node = node.next
-        if node is None: break
+        if node is None:
+            break

    # 将前后断行符脱离
    node = root
    prev_node = None
    while True:
        if not node.preserve:
-            lstriped_ = node.string.lstrip().lstrip('\n')
-            if (prev_node is not None) and (prev_node.preserve) and (len(lstriped_)!=len(node.string)):
+            lstriped_ = node.string.lstrip().lstrip("\n")
+            if (
+                (prev_node is not None)
+                and (prev_node.preserve)
+                and (len(lstriped_) != len(node.string))
+            ):
                prev_node.string += node.string[: -len(lstriped_)]
                node.string = lstriped_
-            rstriped_ = node.string.rstrip().rstrip('\n')
-            if (node.next is not None) and (node.next.preserve) and (len(rstriped_)!=len(node.string)):
+            rstriped_ = node.string.rstrip().rstrip("\n")
+            if (
+                (node.next is not None)
+                and (node.next.preserve)
+                and (len(rstriped_) != len(node.string))
+            ):
                node.next.string = node.string[len(rstriped_) :] + node.next.string
                node.string = rstriped_
-        # =====
+        # =-=-=
        prev_node = node
        node = node.next
-        if node is None: break
+        if node is None:
+            break

    # 标注节点的行数范围
    node = root
    n_line = 0
    expansion = 2
    while True:
-        n_l = node.string.count('\n')
+        n_l = node.string.count("\n")
        node.range = [n_line - expansion, n_line + n_l + expansion]  # 失败时，扭转的范围
        n_line = n_line + n_l
        node = node.next
-        if node is None: break
+        if node is None:
+            break
    return root


@@ -131,12 +155,14 @@ def set_forbidden_text(text, mask, pattern, flags=0):
    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)
+    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 reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
    """
    Move area out of preserve area (make text editable for GPT)
@@ -144,7 +170,8 @@ def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
    e.g.
    \begin{abstract} blablablablablabla. \end{abstract}
    """
-    if isinstance(pattern, list): pattern = '|'.join(pattern)
+    if isinstance(pattern, list):
+        pattern = "|".join(pattern)
    pattern_compile = re.compile(pattern, flags)
    for res in pattern_compile.finditer(text):
        if not forbid_wrapper:
@@ -155,6 +182,7 @@ def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
            mask[res.regs[1][1] : res.regs[0][1]] = PRESERVE  # abstract
    return text, mask

+
 def set_forbidden_text_careful_brace(text, mask, pattern, flags=0):
    """
    Add a preserve text area in this paper (text become untouchable for GPT).
@@ -167,15 +195,21 @@ def set_forbidden_text_careful_brace(text, mask, pattern, flags=0):
        brace_level = -1
        p = begin = end = res.regs[0][0]
        for _ in range(1024 * 16):
-            if text[p] == '}' and brace_level == 0: break
-            elif text[p] == '}':  brace_level -= 1
-            elif text[p] == '{':  brace_level += 1
+            if text[p] == "}" and brace_level == 0:
+                break
+            elif text[p] == "}":
+                brace_level -= 1
+            elif text[p] == "{":
+                brace_level += 1
            p += 1
        end = p + 1
        mask[begin:end] = PRESERVE
    return text, mask

-def reverse_forbidden_text_careful_brace(text, mask, pattern, flags=0, forbid_wrapper=True):
+
+def reverse_forbidden_text_careful_brace(
+    text, mask, pattern, flags=0, forbid_wrapper=True
+):
    """
    Move area out of preserve area (make text editable for GPT)
    count the number of the braces so as to catch compelete text area.
@@ -187,9 +221,12 @@ def reverse_forbidden_text_careful_brace(text, mask, pattern, flags=0, forbid_wr
        brace_level = 0
        p = begin = end = res.regs[1][0]
        for _ in range(1024 * 16):
-            if text[p] == '}' and brace_level == 0: break
-            elif text[p] == '}':  brace_level -= 1
-            elif text[p] == '{':  brace_level += 1
+            if text[p] == "}" and brace_level == 0:
+                break
+            elif text[p] == "}":
+                brace_level -= 1
+            elif text[p] == "{":
+                brace_level += 1
            p += 1
        end = p
        mask[begin:end] = TRANSFORM
@@ -198,27 +235,42 @@ def reverse_forbidden_text_careful_brace(text, mask, pattern, flags=0, forbid_wr
            mask[end : res.regs[0][1]] = PRESERVE
    return text, mask

+
 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
    """
    pattern_compile = re.compile(pattern, flags)
+
    def search_with_line_limit(text, mask):
        for res in pattern_compile.finditer(text):
            cmd = res.group(1)  # begin{what}
            this = res.group(2)  # content between begin and end
            this_mask = mask[res.regs[2][0] : res.regs[2][1]]
-            white_list = ['document', 'abstract', 'lemma', 'definition', 'sproof', 
-                          'em', 'emph', 'textit', 'textbf', 'itemize', 'enumerate']
-            if (cmd in white_list) or this.count('\n') >= limit_n_lines: # use a magical number 42
+            white_list = [
+                "document",
+                "abstract",
+                "lemma",
+                "definition",
+                "sproof",
+                "em",
+                "emph",
+                "textit",
+                "textbf",
+                "itemize",
+                "enumerate",
+            ]
+            if (cmd in white_list) or this.count(
+                "\n"
+            ) >= limit_n_lines:  # use a magical number 42
                this, this_mask = search_with_line_limit(this, this_mask)
                mask[res.regs[2][0] : res.regs[2][1]] = this_mask
            else:
                mask[res.regs[0][0] : res.regs[0][1]] = PRESERVE
        return text, mask
-    return search_with_line_limit(text, mask) 

+    return search_with_line_limit(text, mask)


 """
@@ -227,6 +279,7 @@ Latex Merge File
 =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
 """

+
 def find_main_tex_file(file_manifest, mode):
    """
    在多Tex文档中，寻找主文件，必须包含documentclass，返回找到的第一个。
@@ -234,27 +287,36 @@ def find_main_tex_file(file_manifest, mode):
    """
    canidates = []
    for texf in file_manifest:
-        if os.path.basename(texf).startswith('merge'):
+        if os.path.basename(texf).startswith("merge"):
            continue
-        with open(texf, 'r', encoding='utf8', errors='ignore') as f:
+        with open(texf, "r", encoding="utf8", errors="ignore") as f:
            file_content = f.read()
-        if r'\documentclass' in file_content:
+        if r"\documentclass" in file_content:
            canidates.append(texf)
        else:
            continue

    if len(canidates) == 0:
-        raise RuntimeError('无法找到一个主Tex文件（包含documentclass关键字）')
+        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']
+        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', errors='ignore') as f:
+            with open(texf, "r", encoding="utf8", errors="ignore") as f:
                file_content = f.read()
                file_content = rm_comments(file_content)
            for uw in unexpected_words:
@@ -266,6 +328,7 @@ def find_main_tex_file(file_manifest, mode):
        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():
@@ -274,30 +337,39 @@ def rm_comments(main_file):
            pass
        else:
            new_file_remove_comment_lines.append(l)
-    main_file = '\n'.join(new_file_remove_comment_lines)
+    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
+    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

+
 def find_tex_file_ignore_case(fp):
    dir_name = os.path.dirname(fp)
    base_name = os.path.basename(fp)
    # 如果输入的文件路径是正确的
-    if os.path.isfile(pj(dir_name, base_name)): return pj(dir_name, base_name)
+    if os.path.isfile(pj(dir_name, base_name)):
+        return pj(dir_name, base_name)
    # 如果不正确，试着加上.tex后缀试试
-    if not base_name.endswith('.tex'): base_name+='.tex'
-    if os.path.isfile(pj(dir_name, base_name)): return pj(dir_name, base_name)
+    if not base_name.endswith(".tex"):
+        base_name += ".tex"
+    if os.path.isfile(pj(dir_name, base_name)):
+        return pj(dir_name, base_name)
    # 如果还找不到，解除大小写限制，再试一次
    import glob
-    for f in glob.glob(dir_name+'/*.tex'):
+
+    for f in glob.glob(dir_name + "/*.tex"):
        base_name_s = os.path.basename(fp)
        base_name_f = os.path.basename(f)
-        if base_name_s.lower() == base_name_f.lower(): return f
+        if base_name_s.lower() == base_name_f.lower():
+            return f
        # 试着加上.tex后缀试试
-        if not base_name_s.endswith('.tex'): base_name_s+='.tex'
-        if base_name_s.lower() == base_name_f.lower(): return f
+        if not base_name_s.endswith(".tex"):
+            base_name_s += ".tex"
+        if base_name_s.lower() == base_name_f.lower():
+            return f
    return None

+
 def merge_tex_files_(project_foler, main_file, mode):
    """
    Merge Tex project recrusively
@@ -309,18 +381,18 @@ def merge_tex_files_(project_foler, main_file, mode):
        fp_ = find_tex_file_ignore_case(fp)
        if fp_:
            try:
-                with open(fp_, 'r', encoding='utf-8', errors='replace') as fx: c = fx.read()
+                with open(fp_, "r", encoding="utf-8", errors="replace") as fx:
+                    c = fx.read()
            except:
                c = f"\n\nWarning from GPT-Academic: LaTex source file is missing!\n\n"
        else:
-            raise RuntimeError(f'找不到{fp}，Tex源文件缺失！')
+            raise RuntimeError(f"找不到{fp}，Tex源文件缺失！")
        c = merge_tex_files_(project_foler, c, mode)
        main_file = main_file[: s.span()[0]] + c + main_file[s.span()[1] :]
    return main_file


 def find_title_and_abs(main_file):
-
    def extract_abstract_1(text):
        pattern = r"\\abstract\{(.*?)\}"
        match = re.search(pattern, text, re.DOTALL)
@@ -362,21 +434,30 @@ def merge_tex_files(project_foler, main_file, mode):
    main_file = merge_tex_files_(project_foler, main_file, mode)
    main_file = rm_comments(main_file)

-    if mode == 'translate_zh':
+    if mode == "translate_zh":
        # find paper documentclass
-        pattern = re.compile(r'\\documentclass.*\n')
+        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 ''
+        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:]
        # fontset=windows
        import platform
-        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)
+
+        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_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)
@@ -385,7 +466,9 @@ def merge_tex_files(project_foler, main_file, mode):
            main_file = insert_abstract(main_file)
        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!"
+        assert (match_opt1 is not None) or (
+            match_opt2 is not None
+        ), "Cannot find paper abstract section!"
    return main_file


@@ -395,6 +478,7 @@ The GPT-Academic program cannot find abstract section in this paper.
 \end{abstract}
 """

+
 def insert_abstract(tex_content):
    if "\\maketitle" in tex_content:
        # find the position of "\maketitle"
@@ -402,7 +486,13 @@ def insert_abstract(tex_content):
        # find the nearest ending line
        end_line_index = tex_content.find("\n", find_index)
        # insert "abs_str" on the next line
-        modified_tex = tex_content[:end_line_index+1] + '\n\n' + insert_missing_abs_str + '\n\n' + tex_content[end_line_index+1:]
+        modified_tex = (
+            tex_content[: end_line_index + 1]
+            + "\n\n"
+            + insert_missing_abs_str
+            + "\n\n"
+            + tex_content[end_line_index + 1 :]
+        )
        return modified_tex
    elif r"\begin{document}" in tex_content:
        # find the position of "\maketitle"
@@ -410,16 +500,25 @@ def insert_abstract(tex_content):
        # find the nearest ending line
        end_line_index = tex_content.find("\n", find_index)
        # insert "abs_str" on the next line
-        modified_tex = tex_content[:end_line_index+1] + '\n\n' + insert_missing_abs_str + '\n\n' + tex_content[end_line_index+1:]
+        modified_tex = (
+            tex_content[: end_line_index + 1]
+            + "\n\n"
+            + insert_missing_abs_str
+            + "\n\n"
+            + tex_content[end_line_index + 1 :]
+        )
        return modified_tex
    else:
        return tex_content

+
 """
 =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
 Post process
 =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
 """
+
+
 def mod_inbraket(match):
    """
    为啥chatgpt会把cite里面的逗号换成中文逗号呀
@@ -428,11 +527,12 @@ def mod_inbraket(match):
    cmd = match.group(1)
    str_to_modify = match.group(2)
    # modify the matched string
-    str_to_modify = str_to_modify.replace('：', ':')    # 前面是中文冒号，后面是英文冒号
-    str_to_modify = str_to_modify.replace('，', ',')    # 前面是中文逗号，后面是英文逗号
+    str_to_modify = str_to_modify.replace("：", ":")  # 前面是中文冒号，后面是英文冒号
+    str_to_modify = str_to_modify.replace("，", ",")  # 前面是中文逗号，后面是英文逗号
    # str_to_modify = 'BOOM'
    return "\\" + cmd + "{" + str_to_modify + "}"

+
 def fix_content(final_tex, node_string):
    """
    Fix common GPT errors to increase success rate
@@ -444,9 +544,9 @@ def fix_content(final_tex, node_string):

    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'):
+    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('\_'):
+    if node_string.count("\_") > 0 and node_string.count("\_") > final_tex.count("\_"):
        # walk and replace any _ without \
        final_tex = re.sub(r"(?<!\\)_", "\\_", final_tex)

@@ -454,24 +554,32 @@ def fix_content(final_tex, node_string):
        # this function count the number of { and }
        brace_level = 0
        for c in string:
-            if c == "{": brace_level += 1
-            elif c == "}": brace_level -= 1
+            if c == "{":
+                brace_level += 1
+            elif c == "}":
+                brace_level -= 1
        return brace_level
+
    def join_most(tex_t, tex_o):
        # this function join translated string and original string when something goes wrong
        p_t = 0
        p_o = 0
+
        def find_next(string, chars, begin):
            p = begin
            while p < len(string):
-                if string[p] in chars: return p, string[p]
+                if string[p] in chars:
+                    return p, string[p]
                p += 1
            return None, None
+
        while True:
-            res1, char = find_next(tex_o, ['{','}'], p_o)
-            if res1 is None: break
+            res1, char = find_next(tex_o, ["{", "}"], p_o)
+            if res1 is None:
+                break
            res2, char = find_next(tex_t, [char], p_t)
-            if res2 is None: break
+            if res2 is None:
+                break
            p_o = res1 + 1
            p_t = res2 + 1
        return tex_t[:p_t] + tex_o[p_o:]
@@ -481,9 +589,13 @@ def fix_content(final_tex, node_string):
        final_tex = join_most(final_tex, node_string)
    return final_tex

+
 def compile_latex_with_timeout(command, cwd, timeout=60):
    import subprocess
-    process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=cwd)
+
+    process = subprocess.Popen(
+        command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, cwd=cwd
+    )
    try:
        stdout, stderr = process.communicate(timeout=timeout)
    except subprocess.TimeoutExpired:
@@ -493,43 +605,52 @@ def compile_latex_with_timeout(command, cwd, timeout=60):
        return False
    return True

+
 def run_in_subprocess_wrapper_func(func, args, kwargs, return_dict, exception_dict):
    import sys
+
    try:
        result = func(*args, **kwargs)
-        return_dict['result'] = result
+        return_dict["result"] = result
    except Exception as e:
        exc_info = sys.exc_info()
-        exception_dict['exception'] = exc_info
+        exception_dict["exception"] = exc_info
+

 def run_in_subprocess(func):
    import multiprocessing
+
    def wrapper(*args, **kwargs):
        return_dict = multiprocessing.Manager().dict()
        exception_dict = multiprocessing.Manager().dict()
-        process = multiprocessing.Process(target=run_in_subprocess_wrapper_func, 
-                                            args=(func, args, kwargs, return_dict, exception_dict))
+        process = multiprocessing.Process(
+            target=run_in_subprocess_wrapper_func,
+            args=(func, args, kwargs, return_dict, exception_dict),
+        )
        process.start()
        process.join()
        process.close()
-        if 'exception' in exception_dict:
+        if "exception" in exception_dict:
            # ooops, the subprocess ran into an exception
-            exc_info = exception_dict['exception']
+            exc_info = exception_dict["exception"]
            raise exc_info[1].with_traceback(exc_info[2])
-        if 'result' in return_dict.keys():
+        if "result" in return_dict.keys():
            # If the subprocess ran successfully, return the result
-            return return_dict['result']
+            return return_dict["result"]
+
    return wrapper

+
 def _merge_pdfs(pdf1_path, pdf2_path, output_path):
    import PyPDF2  # PyPDF2这个库有严重的内存泄露问题，把它放到子进程中运行，从而方便内存的释放
+
    Percent = 0.95
    # raise RuntimeError('PyPDF2 has a serious memory leak problem, please use other tools to merge PDF files.')
    # Open the first PDF file
-    with open(pdf1_path, 'rb') as pdf1_file:
+    with open(pdf1_path, "rb") as pdf1_file:
        pdf1_reader = PyPDF2.PdfFileReader(pdf1_file)
        # Open the second PDF file
-        with open(pdf2_path, 'rb') as pdf2_file:
+        with open(pdf2_path, "rb") as pdf2_file:
            pdf2_reader = PyPDF2.PdfFileReader(pdf2_file)
            # Create a new PDF file to store the merged pages
            output_writer = PyPDF2.PdfFileWriter()
@@ -549,14 +670,25 @@ def _merge_pdfs(pdf1_path, pdf2_path, output_path):
                    page2 = PyPDF2.PageObject.createBlankPage(pdf1_reader)
                # Create a new empty page with double width
                new_page = PyPDF2.PageObject.createBlankPage(
-                    width = int(int(page1.mediaBox.getWidth()) + int(page2.mediaBox.getWidth()) * Percent),
-                    height = max(page1.mediaBox.getHeight(), page2.mediaBox.getHeight())
+                    width=int(
+                        int(page1.mediaBox.getWidth())
+                        + int(page2.mediaBox.getWidth()) * Percent
+                    ),
+                    height=max(page1.mediaBox.getHeight(), page2.mediaBox.getHeight()),
                )
                new_page.mergeTranslatedPage(page1, 0, 0)
-                new_page.mergeTranslatedPage(page2, int(int(page1.mediaBox.getWidth())-int(page2.mediaBox.getWidth())* (1-Percent)), 0)
+                new_page.mergeTranslatedPage(
+                    page2,
+                    int(
+                        int(page1.mediaBox.getWidth())
+                        - int(page2.mediaBox.getWidth()) * (1 - Percent)
+                    ),
+                    0,
+                )
                output_writer.addPage(new_page)
            # Save the merged PDF file
-            with open(output_path, 'wb') as output_file:
+            with open(output_path, "wb") as output_file:
                output_writer.write(output_file)

+
 merge_pdfs = run_in_subprocess(_merge_pdfs)  # PyPDF2这个库有严重的内存泄露问题，把它放到子进程中运行，从而方便内存的释放
--- a/crazy_functions/pdf_fns/breakdown_txt.py
+++ b/crazy_functions/pdf_fns/breakdown_txt.py
@@ -0,0 +1,125 @@
+from crazy_functions.ipc_fns.mp import run_in_subprocess_with_timeout
+
+def force_breakdown(txt, limit, get_token_fn):
+    """ 当无法用标点、空行分割时，我们用最暴力的方法切割
+    """
+    for i in reversed(range(len(txt))):
+        if get_token_fn(txt[:i]) < limit:
+            return txt[:i], txt[i:]
+    return "Tiktoken未知错误", "Tiktoken未知错误"
+
+
+def maintain_storage(remain_txt_to_cut, remain_txt_to_cut_storage):
+    """ 为了加速计算，我们采样一个特殊的手段。当 remain_txt_to_cut > `_max` 时， 我们把 _max 后的文字转存至 remain_txt_to_cut_storage
+    当 remain_txt_to_cut < `_min` 时，我们再把 remain_txt_to_cut_storage 中的部分文字取出
+    """
+    _min = int(5e4)
+    _max = int(1e5)
+    # print(len(remain_txt_to_cut), len(remain_txt_to_cut_storage))
+    if len(remain_txt_to_cut) < _min and len(remain_txt_to_cut_storage) > 0:
+        remain_txt_to_cut = remain_txt_to_cut + remain_txt_to_cut_storage
+        remain_txt_to_cut_storage = ""
+    if len(remain_txt_to_cut) > _max:
+        remain_txt_to_cut_storage = remain_txt_to_cut[_max:] + remain_txt_to_cut_storage
+        remain_txt_to_cut = remain_txt_to_cut[:_max]
+    return remain_txt_to_cut, remain_txt_to_cut_storage
+
+
+def cut(limit, get_token_fn, txt_tocut, must_break_at_empty_line, break_anyway=False):
+    """ 文本切分
+    """
+    res = []
+    total_len = len(txt_tocut)
+    fin_len = 0
+    remain_txt_to_cut = txt_tocut
+    remain_txt_to_cut_storage = ""
+    # 为了加速计算，我们采样一个特殊的手段。当 remain_txt_to_cut > `_max` 时， 我们把 _max 后的文字转存至 remain_txt_to_cut_storage
+    remain_txt_to_cut, remain_txt_to_cut_storage = maintain_storage(remain_txt_to_cut, remain_txt_to_cut_storage)
+    
+    while True:
+        if get_token_fn(remain_txt_to_cut) <= limit:
+            # 如果剩余文本的token数小于限制，那么就不用切了
+            res.append(remain_txt_to_cut); fin_len+=len(remain_txt_to_cut)
+            break
+        else:
+            # 如果剩余文本的token数大于限制，那么就切
+            lines = remain_txt_to_cut.split('\n')
+
+            # 估计一个切分点
+            estimated_line_cut = limit / get_token_fn(remain_txt_to_cut) * len(lines)
+            estimated_line_cut = int(estimated_line_cut)
+
+            # 开始查找合适切分点的偏移（cnt）
+            cnt = 0
+            for cnt in reversed(range(estimated_line_cut)):
+                if must_break_at_empty_line:
+                    # 首先尝试用双空行（\n\n）作为切分点
+                    if lines[cnt] != "":
+                        continue
+                prev = "\n".join(lines[:cnt])
+                post = "\n".join(lines[cnt:])
+                if get_token_fn(prev) < limit:
+                    break
+
+            if cnt == 0:
+                # 如果没有找到合适的切分点
+                if break_anyway:
+                    # 是否允许暴力切分
+                    prev, post = force_breakdown(remain_txt_to_cut, limit, get_token_fn)
+                else:
+                    # 不允许直接报错
+                    raise RuntimeError(f"存在一行极长的文本！{remain_txt_to_cut}")
+
+            # 追加列表
+            res.append(prev); fin_len+=len(prev)
+            # 准备下一次迭代
+            remain_txt_to_cut = post
+            remain_txt_to_cut, remain_txt_to_cut_storage = maintain_storage(remain_txt_to_cut, remain_txt_to_cut_storage)
+            process = fin_len/total_len
+            print(f'正在文本切分 {int(process*100)}%')
+            if len(remain_txt_to_cut.strip()) == 0:
+                break
+    return res
+
+
+def breakdown_text_to_satisfy_token_limit_(txt, limit, llm_model="gpt-3.5-turbo"):
+    """ 使用多种方式尝试切分文本，以满足 token 限制
+    """
+    from request_llms.bridge_all import model_info
+    enc = model_info[llm_model]['tokenizer']
+    def get_token_fn(txt): return len(enc.encode(txt, disallowed_special=()))
+    try:
+        # 第1次尝试，将双空行（\n\n）作为切分点
+        return cut(limit, get_token_fn, txt, must_break_at_empty_line=True)
+    except RuntimeError:
+        try:
+            # 第2次尝试，将单空行（\n）作为切分点
+            return cut(limit, get_token_fn, txt, must_break_at_empty_line=False)
+        except RuntimeError:
+            try:
+                # 第3次尝试，将英文句号（.）作为切分点
+                res = cut(limit, get_token_fn, txt.replace('.', '。\n'), must_break_at_empty_line=False) # 这个中文的句号是故意的，作为一个标识而存在
+                return [r.replace('。\n', '.') for r in res]
+            except RuntimeError as e:
+                try:
+                    # 第4次尝试，将中文句号（。）作为切分点
+                    res = cut(limit, get_token_fn, txt.replace('。', '。。\n'), must_break_at_empty_line=False)
+                    return [r.replace('。。\n', '。') for r in res]
+                except RuntimeError as e:
+                    # 第5次尝试，没办法了，随便切一下吧
+                    return cut(limit, get_token_fn, txt, must_break_at_empty_line=False, break_anyway=True)
+
+breakdown_text_to_satisfy_token_limit = run_in_subprocess_with_timeout(breakdown_text_to_satisfy_token_limit_, timeout=60)
+
+if __name__ == '__main__':
+    from crazy_functions.crazy_utils import read_and_clean_pdf_text
+    file_content, page_one = read_and_clean_pdf_text("build/assets/at.pdf")
+
+    from request_llms.bridge_all import model_info
+    for i in range(5):
+        file_content += file_content
+
+    print(len(file_content))
+    TOKEN_LIMIT_PER_FRAGMENT = 2500
+    res = breakdown_text_to_satisfy_token_limit(file_content, TOKEN_LIMIT_PER_FRAGMENT)
+
--- a/crazy_functions/pdf_fns/parse_pdf.py
+++ b/crazy_functions/pdf_fns/parse_pdf.py
@@ -74,7 +74,7 @@ def produce_report_markdown(gpt_response_collection, meta, paper_meta_info, chat

 def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_files, TOKEN_LIMIT_PER_FRAGMENT, DST_LANG):
    from crazy_functions.pdf_fns.report_gen_html import construct_html
-    from crazy_functions.crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
+    from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
    from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
    from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency

@@ -116,7 +116,7 @@ def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_fi
            # find a smooth token limit to achieve even seperation
            count = int(math.ceil(raw_token_num / TOKEN_LIMIT_PER_FRAGMENT))
            token_limit_smooth = raw_token_num // count + count
-            return breakdown_txt_to_satisfy_token_limit_for_pdf(txt, get_token_fn=get_token_num, limit=token_limit_smooth)
+            return breakdown_text_to_satisfy_token_limit(txt, limit=token_limit_smooth, llm_model=llm_kwargs['llm_model'])

    for section in article_dict.get('sections'):
        if len(section['text']) == 0: continue
--- a/crazy_functions/互动小游戏.py
+++ b/crazy_functions/互动小游戏.py
@@ -3,47 +3,28 @@ from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseSta
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.game_fns.game_utils import get_code_block, is_same_thing
-import random
-
-
-class MiniGame_ASCII_Art(GptAcademicGameBaseState):
-    
-    def step(self, prompt, chatbot, history):
-        if self.step_cnt == 0:  
-            chatbot.append(["我画你猜（动物）", "请稍等..."])
-        else:
-            if prompt.strip() == 'exit':
-                self.delete_game = True
-                yield from update_ui_lastest_msg(lastmsg=f"谜底是{self.obj}，游戏结束。", chatbot=chatbot, history=history, delay=0.)
-                return
-            chatbot.append([prompt, ""])
-        yield from update_ui(chatbot=chatbot, history=history)
-
-        if self.step_cnt == 0:
-            self.lock_plugin(chatbot)
-            self.cur_task = 'draw'
-
-        if self.cur_task == 'draw':
-            avail_obj = ["狗","猫","鸟","鱼","老鼠","蛇"]
-            self.obj = random.choice(avail_obj)
-            inputs = "I want to play a game called Guess the ASCII art. You can draw the ASCII art and I will try to guess it. " + f"This time you draw a {self.obj}. Note that you must not indicate what you have draw in the text, and you should only produce the ASCII art wrapped by ```. "
-            raw_res = predict_no_ui_long_connection(inputs=inputs, llm_kwargs=self.llm_kwargs, history=[], sys_prompt="")
-            self.cur_task = 'identify user guess'
-            res = get_code_block(raw_res)
-            history += ['', f'the answer is {self.obj}', inputs, res]
-            yield from update_ui_lastest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.)
-
-        elif self.cur_task == 'identify user guess':
-            if is_same_thing(self.obj, prompt, self.llm_kwargs):
-                self.delete_game = True
-                yield from update_ui_lastest_msg(lastmsg="你猜对了！", chatbot=chatbot, history=history, delay=0.)
-            else:
-                self.cur_task = 'identify user guess'
-                yield from update_ui_lastest_msg(lastmsg="猜错了，再试试，输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.)
-            

@CatchException
 def 随机小游戏(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
+    from crazy_functions.game_fns.game_interactive_story import MiniGame_ResumeStory
+    # 清空历史
+    history = []
+    # 选择游戏
+    cls = MiniGame_ResumeStory
+    # 如果之前已经初始化了游戏实例，则继续该实例；否则重新初始化
+    state = cls.sync_state(chatbot, 
+                           llm_kwargs, 
+                           cls, 
+                           plugin_name='MiniGame_ResumeStory',
+                           callback_fn='crazy_functions.互动小游戏->随机小游戏',
+                           lock_plugin=True
+                           )
+    yield from state.continue_game(prompt, chatbot, history)
+
+
+@CatchException
+def 随机小游戏1(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
+    from crazy_functions.game_fns.game_ascii_art import MiniGame_ASCII_Art
    # 清空历史
    history = []
    # 选择游戏
@@ -53,7 +34,7 @@ def 随机小游戏(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_
                           llm_kwargs, 
                           cls, 
                           plugin_name='MiniGame_ASCII_Art',
-                           callback_fn='crazy_functions.互动小游戏->随机小游戏',
+                           callback_fn='crazy_functions.互动小游戏->随机小游戏1',
                           lock_plugin=True
                           )
    yield from state.continue_game(prompt, chatbot, history)
--- a/crazy_functions/图片生成.py
+++ b/crazy_functions/图片生成.py
@@ -104,7 +104,11 @@ def 图片生成_DALLE2(prompt, llm_kwargs, plugin_kwargs, chatbot, history, sys
    web_port        当前软件运行的端口号
    """
    history = []    # 清空历史,以免输入溢出
-    chatbot.append(("您正在调用“图像生成”插件。", "[Local Message] 生成图像, 请先把模型切换至gpt-*或者api2d-*。如果中文Prompt效果不理想, 请尝试英文Prompt。正在处理中 ....."))
+    if prompt.strip() == "":
+        chatbot.append((prompt, "[Local Message] 图像生成提示为空白，请在“输入区”输入图像生成提示。"))
+        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新
+        return
+    chatbot.append(("您正在调用“图像生成”插件。", "[Local Message] 生成图像, 请先把模型切换至gpt-*。如果中文Prompt效果不理想, 请尝试英文Prompt。正在处理中 ....."))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 由于请求gpt需要一段时间,我们先及时地做一次界面更新
    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
    resolution = plugin_kwargs.get("advanced_arg", '1024x1024')
@@ -121,7 +125,11 @@ def 图片生成_DALLE2(prompt, llm_kwargs, plugin_kwargs, chatbot, history, sys
@CatchException
 def 图片生成_DALLE3(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
    history = []    # 清空历史,以免输入溢出
-    chatbot.append(("您正在调用“图像生成”插件。", "[Local Message] 生成图像, 请先把模型切换至gpt-*或者api2d-*。如果中文Prompt效果不理想, 请尝试英文Prompt。正在处理中 ....."))
+    if prompt.strip() == "":
+        chatbot.append((prompt, "[Local Message] 图像生成提示为空白，请在“输入区”输入图像生成提示。"))
+        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新
+        return
+    chatbot.append(("您正在调用“图像生成”插件。", "[Local Message] 生成图像, 请先把模型切换至gpt-*。如果中文Prompt效果不理想, 请尝试英文Prompt。正在处理中 ....."))
    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 由于请求gpt需要一段时间,我们先及时地做一次界面更新
    if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
    resolution_arg = plugin_kwargs.get("advanced_arg", '1024x1024-standard-vivid').lower()
--- a/crazy_functions/总结word文档.py
+++ b/crazy_functions/总结word文档.py
@@ -29,17 +29,12 @@ def 解析docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot
            except:
                raise RuntimeError('请先将.doc文档转换为.docx文档。')

-        print(file_content)
        # private_upload里面的文件名在解压zip后容易出现乱码（rar和7z格式正常），故可以只分析文章内容，不输入文件名
-        from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
+        from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
        from request_llms.bridge_all import model_info
        max_token = model_info[llm_kwargs['llm_model']]['max_token']
        TOKEN_LIMIT_PER_FRAGMENT = max_token * 3 // 4
-        paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
-            txt=file_content,  
-            get_token_fn=model_info[llm_kwargs['llm_model']]['token_cnt'], 
-            limit=TOKEN_LIMIT_PER_FRAGMENT
-        )
+        paper_fragments = breakdown_text_to_satisfy_token_limit(txt=file_content, limit=TOKEN_LIMIT_PER_FRAGMENT, llm_model=llm_kwargs['llm_model'])
        this_paper_history = []
        for i, paper_frag in enumerate(paper_fragments):
            i_say = f'请对下面的文章片段用中文做概述，文件名是{os.path.relpath(fp, project_folder)}，文章内容是 ```{paper_frag}```'
--- a/crazy_functions/批量Markdown翻译.py
+++ b/crazy_functions/批量Markdown翻译.py
@@ -28,8 +28,8 @@ class PaperFileGroup():
                self.sp_file_index.append(index)
                self.sp_file_tag.append(self.file_paths[index])
            else:
-                from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
-                segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit)
+                from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
+                segments = breakdown_text_to_satisfy_token_limit(file_content, max_token_limit)
                for j, segment in enumerate(segments):
                    self.sp_file_contents.append(segment)
                    self.sp_file_index.append(index)
--- a/crazy_functions/批量总结PDF文档.py
+++ b/crazy_functions/批量总结PDF文档.py
@@ -20,14 +20,9 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
        
        TOKEN_LIMIT_PER_FRAGMENT = 2500

-        from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
-        from request_llms.bridge_all import model_info
-        enc = model_info["gpt-3.5-turbo"]['tokenizer']
-        def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
-        paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
-            txt=file_content,  get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT)
-        page_one_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
-            txt=str(page_one), get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT//4)
+        from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
+        paper_fragments = breakdown_text_to_satisfy_token_limit(txt=file_content,  limit=TOKEN_LIMIT_PER_FRAGMENT, llm_model=llm_kwargs['llm_model'])
+        page_one_fragments = breakdown_text_to_satisfy_token_limit(txt=str(page_one), limit=TOKEN_LIMIT_PER_FRAGMENT//4, llm_model=llm_kwargs['llm_model'])
        # 为了更好的效果，我们剥离Introduction之后的部分（如果有）
        paper_meta = page_one_fragments[0].split('introduction')[0].split('Introduction')[0].split('INTRODUCTION')[0]
        
--- a/crazy_functions/批量翻译PDF文档_多线程.py
+++ b/crazy_functions/批量翻译PDF文档_多线程.py
@@ -91,14 +91,9 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
        page_one = str(page_one).encode('utf-8', 'ignore').decode()      # avoid reading non-utf8 chars

        # 递归地切割PDF文件
-        from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
-        from request_llms.bridge_all import model_info
-        enc = model_info["gpt-3.5-turbo"]['tokenizer']
-        def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
-        paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
-            txt=file_content,  get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT)
-        page_one_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
-            txt=page_one, get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT//4)
+        from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
+        paper_fragments = breakdown_text_to_satisfy_token_limit(txt=file_content, limit=TOKEN_LIMIT_PER_FRAGMENT, llm_model=llm_kwargs['llm_model'])
+        page_one_fragments = breakdown_text_to_satisfy_token_limit(txt=page_one, limit=TOKEN_LIMIT_PER_FRAGMENT//4, llm_model=llm_kwargs['llm_model'])

        # 为了更好的效果，我们剥离Introduction之后的部分（如果有）
        paper_meta = page_one_fragments[0].split('introduction')[0].split('Introduction')[0].split('INTRODUCTION')[0]
--- a/crazy_functions/理解PDF文档内容.py
+++ b/crazy_functions/理解PDF文档内容.py
@@ -18,14 +18,9 @@ def 解析PDF(file_name, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
    
    TOKEN_LIMIT_PER_FRAGMENT = 2500

-    from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
-    from request_llms.bridge_all import model_info
-    enc = model_info["gpt-3.5-turbo"]['tokenizer']
-    def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
-    paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
-        txt=file_content,  get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT)
-    page_one_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
-        txt=str(page_one), get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT//4)
+    from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
+    paper_fragments = breakdown_text_to_satisfy_token_limit(txt=file_content, limit=TOKEN_LIMIT_PER_FRAGMENT, llm_model=llm_kwargs['llm_model'])
+    page_one_fragments = breakdown_text_to_satisfy_token_limit(txt=str(page_one), limit=TOKEN_LIMIT_PER_FRAGMENT//4, llm_model=llm_kwargs['llm_model'])
    # 为了更好的效果，我们剥离Introduction之后的部分（如果有）
    paper_meta = page_one_fragments[0].split('introduction')[0].split('Introduction')[0].split('INTRODUCTION')[0]
    
@@ -45,7 +40,7 @@ def 解析PDF(file_name, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
    for i in range(n_fragment):
        NUM_OF_WORD = MAX_WORD_TOTAL // n_fragment
        i_say = f"Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {paper_fragments[i]}"
-        i_say_show_user = f"[{i+1}/{n_fragment}] Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {paper_fragments[i][:200]}"
+        i_say_show_user = f"[{i+1}/{n_fragment}] Read this section, recapitulate the content of this section with less than {NUM_OF_WORD} words: {paper_fragments[i][:200]} ...."
        gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user,  # i_say=真正给chatgpt的提问， i_say_show_user=给用户看的提问
                                                                           llm_kwargs, chatbot, 
                                                                           history=["The main idea of the previous section is?", last_iteration_result], # 迭代上一次的结果
--- a/crazy_functions/解析JupyterNotebook.py
+++ b/crazy_functions/解析JupyterNotebook.py
@@ -12,13 +12,6 @@ class PaperFileGroup():
        self.sp_file_index = []
        self.sp_file_tag = []

-        # count_token
-        from request_llms.bridge_all import model_info
-        enc = model_info["gpt-3.5-turbo"]['tokenizer']
-        def get_token_num(txt): return len(
-            enc.encode(txt, disallowed_special=()))
-        self.get_token_num = get_token_num
-
    def run_file_split(self, max_token_limit=1900):
        """
        将长文本分离开来
@@ -29,9 +22,8 @@ class PaperFileGroup():
                self.sp_file_index.append(index)
                self.sp_file_tag.append(self.file_paths[index])
            else:
-                from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
-                segments = breakdown_txt_to_satisfy_token_limit_for_pdf(
-                    file_content, self.get_token_num, max_token_limit)
+                from crazy_functions.pdf_fns.breakdown_txt import breakdown_text_to_satisfy_token_limit
+                segments = breakdown_text_to_satisfy_token_limit(file_content, max_token_limit)
                for j, segment in enumerate(segments):
                    self.sp_file_contents.append(segment)
                    self.sp_file_index.append(index)
--- a/crazy_functions/高级功能函数模板.py
+++ b/crazy_functions/高级功能函数模板.py
@@ -27,3 +27,45 @@ def 高阶功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
        chatbot[-1] = (i_say, gpt_say)
        history.append(i_say);history.append(gpt_say)
        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
+
+
+
+
+PROMPT = """
+请你给出围绕“{subject}”的逻辑关系图，使用mermaid语法，mermaid语法举例：
+```mermaid
+graph TD
+    P(编程) --> L1(Python)
+    P(编程) --> L2(C)
+    P(编程) --> L3(C++)
+    P(编程) --> L4(Javascipt)
+    P(编程) --> L5(PHP)
+```
+"""
+@CatchException
+def 测试图表渲染(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，用于灵活调整复杂功能的各种参数
+    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
+    web_port        当前软件运行的端口号
+    """
+    history = []    # 清空历史，以免输入溢出
+    chatbot.append(("这是什么功能？", "一个测试mermaid绘制图表的功能，您可以在输入框中输入一些关键词，然后使用mermaid+llm绘制图表。"))
+    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
+    
+    if txt == "": txt = "空白的输入栏" # 调皮一下
+    
+    i_say_show_user = f'请绘制有关“{txt}”的逻辑关系图。'
+    i_say = PROMPT.format(subject=txt)
+    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
+        inputs=i_say,
+        inputs_show_user=i_say_show_user,
+        llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 
+        sys_prompt=""
+    )
+    history.append(i_say); history.append(gpt_say)
+    yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -229,4 +229,3 @@ services:
    # 不使用代理网络拉取最新代码
    command: >
      bash -c "python3 -u main.py"
-
--- a/docs/Dockerfile+ChatGLM
+++ b/docs/Dockerfile+ChatGLM
@@ -1,2 +1 @@
 # 此Dockerfile不再维护，请前往docs/GithubAction+ChatGLM+Moss
-
--- a/docs/GithubAction+AllCapacityBeta
+++ b/docs/GithubAction+AllCapacityBeta
@@ -0,0 +1,53 @@
+# docker build -t gpt-academic-all-capacity -f docs/GithubAction+AllCapacity  --network=host --build-arg http_proxy=http://localhost:10881 --build-arg https_proxy=http://localhost:10881 .
+# docker build -t gpt-academic-all-capacity -f docs/GithubAction+AllCapacityBeta  --network=host .
+# docker run -it --net=host gpt-academic-all-capacity  bash
+
+# 从NVIDIA源，从而支持显卡（检查宿主的nvidia-smi中的cuda版本必须>=11.3）
+FROM fuqingxu/11.3.1-runtime-ubuntu20.04-with-texlive:latest
+
+# use python3 as the system default python
+WORKDIR /gpt
+RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
+
+# # 非必要步骤，更换pip源 （以下三行，可以删除）
+# RUN echo '[global]' > /etc/pip.conf && \
+#     echo 'index-url = https://mirrors.aliyun.com/pypi/simple/' >> /etc/pip.conf && \
+#     echo 'trusted-host = mirrors.aliyun.com' >> /etc/pip.conf
+
+# 下载pytorch
+RUN python3 -m pip install torch torchvision --extra-index-url https://download.pytorch.org/whl/cu113
+# 准备pip依赖
+RUN python3 -m pip install openai numpy arxiv rich
+RUN python3 -m pip install colorama Markdown pygments pymupdf
+RUN python3 -m pip install python-docx moviepy pdfminer
+RUN python3 -m pip install zh_langchain==0.2.1 pypinyin
+RUN python3 -m pip install rarfile py7zr
+RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
+# 下载分支
+WORKDIR /gpt
+RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
+WORKDIR /gpt/gpt_academic
+RUN git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss
+
+RUN python3 -m pip install -r requirements.txt
+RUN python3 -m pip install -r request_llms/requirements_moss.txt
+RUN python3 -m pip install -r request_llms/requirements_qwen.txt
+RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
+RUN python3 -m pip install -r request_llms/requirements_newbing.txt
+RUN python3 -m pip install nougat-ocr
+
+# 预热Tiktoken模块
+RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
+
+# 安装知识库插件的额外依赖
+RUN apt-get update && apt-get install libgl1 -y
+RUN pip3 install transformers protobuf langchain sentence-transformers  faiss-cpu nltk beautifulsoup4 bitsandbytes tabulate icetk --upgrade
+RUN pip3 install unstructured[all-docs] --upgrade
+RUN python3  -c 'from check_proxy import warm_up_vectordb; warm_up_vectordb()'
+RUN rm -rf /usr/local/lib/python3.8/dist-packages/tests
+
+
+# COPY .cache /root/.cache
+# COPY config_private.py config_private.py
+# 启动
+CMD ["python3", "-u", "main.py"]
--- a/docs/GithubAction+NoLocal+Vectordb
+++ b/docs/GithubAction+NoLocal+Vectordb
@@ -17,10 +17,10 @@ RUN apt-get update && apt-get install libgl1 -y
 RUN pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cpu
 RUN pip3 install transformers protobuf langchain sentence-transformers  faiss-cpu nltk beautifulsoup4 bitsandbytes tabulate icetk --upgrade
 RUN pip3 install unstructured[all-docs] --upgrade
+RUN python3  -c 'from check_proxy import warm_up_vectordb; warm_up_vectordb()'

 # 可选步骤，用于预热模块
 RUN python3  -c 'from check_proxy import warm_up_modules; warm_up_modules()'
-RUN python3  -c 'from check_proxy import warm_up_vectordb; warm_up_vectordb()'

 # 启动
 CMD ["python3", "-u", "main.py"]
--- a/docs/README.Arabic.md
+++ b/docs/README.Arabic.md
@@ -341,4 +341,3 @@ https://github.com/oobabooga/one-click-installers
 # المزيد:
 https://github.com/gradio-app/gradio
 https://github.com/fghrsh/live2d_demo
-
--- a/docs/README.English.md
+++ b/docs/README.English.md
@@ -355,4 +355,3 @@ https://github.com/oobabooga/one-click-installers
 # More:
 https://github.com/gradio-app/gradio
 https://github.com/fghrsh/live2d_demo
-
--- a/docs/README.French.md
+++ b/docs/README.French.md
@@ -354,4 +354,3 @@ https://github.com/oobabooga/one-click-installers
 # Plus：
 https://github.com/gradio-app/gradio
 https://github.com/fghrsh/live2d_demo
-
--- a/docs/README.German.md
+++ b/docs/README.German.md
@@ -361,4 +361,3 @@ https://github.com/oobabooga/one-click-installers
 # Weitere:
 https://github.com/gradio-app/gradio
 https://github.com/fghrsh/live2d_demo
-
--- a/docs/README.Italian.md
+++ b/docs/README.Italian.md
@@ -358,4 +358,3 @@ https://github.com/oobabooga/one-click-installers
 # Altre risorse:
 https://github.com/gradio-app/gradio
 https://github.com/fghrsh/live2d_demo
-
--- a/docs/README.Japanese.md
+++ b/docs/README.Japanese.md
@@ -342,4 +342,3 @@ https://github.com/oobabooga/one-click-installers
 # その他：
 https://github.com/gradio-app/gradio
 https://github.com/fghrsh/live2d_demo
-
--- a/docs/README.Korean.md
+++ b/docs/README.Korean.md
@@ -361,4 +361,3 @@ https://github.com/oobabooga/one-click-installers
 # 더보기：
 https://github.com/gradio-app/gradio
 https://github.com/fghrsh/live2d_demo
-
--- a/docs/README.Portuguese.md
+++ b/docs/README.Portuguese.md
@@ -355,4 +355,3 @@ https://github.com/oobabooga/instaladores-de-um-clique
 # Mais:
 https://github.com/gradio-app/gradio
 https://github.com/fghrsh/live2d_demo
-
--- a/docs/README.Russian.md
+++ b/docs/README.Russian.md
@@ -358,4 +358,3 @@ https://github.com/oobabooga/one-click-installers
 # Больше:
 https://github.com/gradio-app/gradio
 https://github.com/fghrsh/live2d_demo
-
--- a/docs/gradio-3.32.6-py3-none-any.whl
+++ b/docs/gradio-3.32.6-py3-none-any.whl
--- a/docs/test_markdown_format.py
+++ b/docs/test_markdown_format.py
@@ -7,13 +7,27 @@ sample = """
 """
 import re

+
 def preprocess_newbing_out(s):
-    pattern = r'\^(\d+)\^' # 匹配^数字^
-    pattern2 = r'\[(\d+)\]' # 匹配^数字^
-    sub = lambda m: '\['+m.group(1)+'\]' # 将匹配到的数字作为替换值
+    pattern = r"\^(\d+)\^"  # 匹配^数字^
+    pattern2 = r"\[(\d+)\]"  # 匹配^数字^
+
+    def sub(m):
+        return "\\[" + m.group(1) + "\\]"  # 将匹配到的数字作为替换值
+
    result = re.sub(pattern, sub, s)  # 替换操作
-    if '[1]' in result:
-        result += '<br/><hr style="border-top: dotted 1px #44ac5c;"><br/><small>' + "<br/>".join([re.sub(pattern2, sub, r) for r in result.split('\n') if r.startswith('[')]) + '</small>'
+    if "[1]" in result:
+        result += (
+            '<br/><hr style="border-top: dotted 1px #44ac5c;"><br/><small>'
+            + "<br/>".join(
+                [
+                    re.sub(pattern2, sub, r)
+                    for r in result.split("\n")
+                    if r.startswith("[")
+                ]
+            )
+            + "</small>"
+        )
    return result


@@ -28,37 +42,39 @@ def close_up_code_segment_during_stream(gpt_reply):
        str: 返回一个新的字符串，将输出代码片段的“后面的```”补上。

    """
-    if '```' not in gpt_reply:
+    if "```" not in gpt_reply:
        return gpt_reply
-    if gpt_reply.endswith('```'):
+    if gpt_reply.endswith("```"):
        return gpt_reply

    # 排除了以上两个情况，我们
-    segments = gpt_reply.split('```')
+    segments = gpt_reply.split("```")
    n_mark = len(segments) - 1
    if n_mark % 2 == 1:
        # print('输出代码片段中！')
-        return gpt_reply+'\n```'
+        return gpt_reply + "\n```"
    else:
        return gpt_reply

+
 import markdown
 from latex2mathml.converter import convert as tex2mathml
-from functools import wraps, lru_cache
+
+
 def markdown_convertion(txt):
    """
    将Markdown格式的文本转换为HTML格式。如果包含数学公式，则先将公式转换为HTML格式。
    """
    pre = '<div class="markdown-body">'
-    suf = '</div>'
+    suf = "</div>"
    if txt.startswith(pre) and txt.endswith(suf):
        # print('警告，输入了已经经过转化的字符串，二次转化可能出问题')
        return txt  # 已经被转化过，不需要再次转化

    markdown_extension_configs = {
-        'mdx_math': {
-            'enable_dollar_delimiter': True,
-            'use_gitlab_delimiters': False,
+        "mdx_math": {
+            "enable_dollar_delimiter": True,
+            "use_gitlab_delimiters": False,
        },
    }
    find_equation_pattern = r'<script type="math/tex(?:.*?)>(.*?)</script>'
@@ -72,19 +88,19 @@ def markdown_convertion(txt):

    def replace_math_no_render(match):
        content = match.group(1)
-        if 'mode=display' in match.group(0):
-            content = content.replace('\n', '</br>')
-            return f"<font color=\"#00FF00\">$$</font><font color=\"#FF00FF\">{content}</font><font color=\"#00FF00\">$$</font>"
+        if "mode=display" in match.group(0):
+            content = content.replace("\n", "</br>")
+            return f'<font color="#00FF00">$$</font><font color="#FF00FF">{content}</font><font color="#00FF00">$$</font>'
        else:
-            return f"<font color=\"#00FF00\">$</font><font color=\"#FF00FF\">{content}</font><font color=\"#00FF00\">$</font>"
+            return f'<font color="#00FF00">$</font><font color="#FF00FF">{content}</font><font color="#00FF00">$</font>'

    def replace_math_render(match):
        content = match.group(1)
-        if 'mode=display' in match.group(0):
-            if '\\begin{aligned}' in content:
-                content = content.replace('\\begin{aligned}', '\\begin{array}')
-                content = content.replace('\\end{aligned}', '\\end{array}')
-                content = content.replace('&', ' ')
+        if "mode=display" in match.group(0):
+            if "\\begin{aligned}" in content:
+                content = content.replace("\\begin{aligned}", "\\begin{array}")
+                content = content.replace("\\end{aligned}", "\\end{array}")
+                content = content.replace("&", " ")
            content = tex2mathml_catch_exception(content, display="block")
            return content
        else:
@@ -94,37 +110,58 @@ def markdown_convertion(txt):
        """
        解决一个mdx_math的bug（单$包裹begin命令时多余<script>）
        """
-        content = content.replace('<script type="math/tex">\n<script type="math/tex; mode=display">', '<script type="math/tex; mode=display">')
-        content = content.replace('</script>\n</script>', '</script>')
+        content = content.replace(
+            '<script type="math/tex">\n<script type="math/tex; mode=display">',
+            '<script type="math/tex; mode=display">',
+        )
+        content = content.replace("</script>\n</script>", "</script>")
        return content

-
-    if ('$' in txt) and ('```' not in txt):  # 有$标识的公式符号，且没有代码段```的标识
+    if ("$" in txt) and ("```" not in txt):  # 有$标识的公式符号，且没有代码段```的标识
        # convert everything to html format
-        split = markdown.markdown(text='---')
-        convert_stage_1 = markdown.markdown(text=txt, extensions=['mdx_math', 'fenced_code', 'tables', 'sane_lists'], extension_configs=markdown_extension_configs)
+        split = markdown.markdown(text="---")
+        convert_stage_1 = markdown.markdown(
+            text=txt,
+            extensions=["mdx_math", "fenced_code", "tables", "sane_lists"],
+            extension_configs=markdown_extension_configs,
+        )
        convert_stage_1 = markdown_bug_hunt(convert_stage_1)
        # re.DOTALL: Make the '.' special character match any character at all, including a newline; without this flag, '.' will match anything except a newline. Corresponds to the inline flag (?s).
        # 1. convert to easy-to-copy tex (do not render math)
-        convert_stage_2_1, n = re.subn(find_equation_pattern, replace_math_no_render, convert_stage_1, flags=re.DOTALL)
+        convert_stage_2_1, n = re.subn(
+            find_equation_pattern,
+            replace_math_no_render,
+            convert_stage_1,
+            flags=re.DOTALL,
+        )
        # 2. convert to rendered equation
-        convert_stage_2_2, n = re.subn(find_equation_pattern, replace_math_render, convert_stage_1, flags=re.DOTALL)
+        convert_stage_2_2, n = re.subn(
+            find_equation_pattern, replace_math_render, convert_stage_1, flags=re.DOTALL
+        )
        # cat them together
-        return pre + convert_stage_2_1 + f'{split}' + convert_stage_2_2 + suf
+        return pre + convert_stage_2_1 + f"{split}" + convert_stage_2_2 + suf
    else:
-        return pre + markdown.markdown(txt, extensions=['fenced_code', 'codehilite', 'tables', 'sane_lists']) + suf
+        return (
+            pre
+            + markdown.markdown(
+                txt, extensions=["fenced_code", "codehilite", "tables", "sane_lists"]
+            )
+            + suf
+        )


 sample = preprocess_newbing_out(sample)
 sample = close_up_code_segment_during_stream(sample)
 sample = markdown_convertion(sample)
-with open('tmp.html', 'w', encoding='utf8') as f:
-    f.write("""
+with open("tmp.html", "w", encoding="utf8") as f:
+    f.write(
+        """

 <head>
    <title>My Website</title>
    <link rel="stylesheet" type="text/css" href="style.css">
 </head>

-    """)
+    """
+    )
    f.write(sample)
--- a/docs/translate_english.json
+++ b/docs/translate_english.json
@@ -2863,7 +2863,7 @@
    "加载API_KEY": "Loading API_KEY",
    "协助您编写代码": "Assist you in writing code",
    "我可以为您提供以下服务": "I can provide you with the following services",
-    "排队中请稍后 ...": "Please wait in line ...",
+    "排队中请稍候 ...": "Please wait in line ...",
    "建议您使用英文提示词": "It is recommended to use English prompts",
    "不能支撑AutoGen运行": "Cannot support AutoGen operation",
    "帮助您解决编程问题": "Help you solve programming problems",
--- a/docs/use_audio.md
+++ b/docs/use_audio.md
@@ -61,4 +61,3 @@ VI 两种音频监听模式切换时，需要刷新页面才有效。
 VII 非localhost运行+非https情况下无法打开录音功能的坑：https://blog.csdn.net/weixin_39461487/article/details/109594434

 ## 5.点击函数插件区“实时音频采集” 或者其他音频交互功能
-
--- a/main.py
+++ b/main.py
@@ -1,14 +1,25 @@
 import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
-import pickle
-import base64
+
+help_menu_description = \
+"""Github源代码开源和更新[地址🚀](https://github.com/binary-husky/gpt_academic), 
+感谢热情的[开发者们❤️](https://github.com/binary-husky/gpt_academic/graphs/contributors).
+</br></br>常见问题请查阅[项目Wiki](https://github.com/binary-husky/gpt_academic/wiki), 
+如遇到Bug请前往[Bug反馈](https://github.com/binary-husky/gpt_academic/issues).
+</br></br>普通对话使用说明: 1. 输入问题; 2. 点击提交
+</br></br>基础功能区使用说明: 1. 输入文本; 2. 点击任意基础功能区按钮
+</br></br>函数插件区使用说明: 1. 输入路径/问题, 或者上传文件; 2. 点击任意函数插件区按钮
+</br></br>虚空终端使用说明: 点击虚空终端, 然后根据提示输入指令, 再次点击虚空终端
+</br></br>如何保存对话: 点击保存当前的对话按钮
+</br></br>如何语音对话: 请阅读Wiki
+</br></br>如何临时更换API_KEY: 在输入区输入临时API_KEY后提交（网页刷新后失效）"""

 def main():
    import gradio as gr
-    if gr.__version__ not in ['3.32.6']: 
+    if gr.__version__ not in ['3.32.6', '3.32.7']: 
        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.")
    from request_llms.bridge_all import predict
    from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, load_chat_cookies, DummyWith
-    # 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到
+    # 建议您复制一个config_private.py放自己的秘密, 如API和代理网址
    proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION = get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION')
    CHATBOT_HEIGHT, LAYOUT, AVAIL_LLM_MODELS, AUTO_CLEAR_TXT = get_conf('CHATBOT_HEIGHT', 'LAYOUT', 'AVAIL_LLM_MODELS', 'AUTO_CLEAR_TXT')
    ENABLE_AUDIO, AUTO_CLEAR_TXT, PATH_LOGGING, AVAIL_THEMES, THEME = get_conf('ENABLE_AUDIO', 'AUTO_CLEAR_TXT', 'PATH_LOGGING', 'AVAIL_THEMES', 'THEME')
@@ -18,20 +29,10 @@ 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, load_dynamic_theme
-
+    from themes.theme import adjust_theme, advanced_css, theme_declaration
+    from themes.theme import js_code_for_css_changing, js_code_for_darkmode_init, js_code_for_toggle_darkmode, js_code_for_persistent_cookie_init
+    from themes.theme import load_dynamic_theme, to_cookie_str, from_cookie_str, init_cookie
    title_html = f"<h1 align=\"center\">GPT 学术优化 {get_current_version()}</h1>{theme_declaration}"
-    description =  "Github源代码开源和更新[地址🚀](https://github.com/binary-husky/gpt_academic), "
-    description += "感谢热情的[开发者们❤️](https://github.com/binary-husky/gpt_academic/graphs/contributors)."
-    description += "</br></br>常见问题请查阅[项目Wiki](https://github.com/binary-husky/gpt_academic/wiki), "
-    description += "如遇到Bug请前往[Bug反馈](https://github.com/binary-husky/gpt_academic/issues)."
-    description += "</br></br>普通对话使用说明: 1. 输入问题; 2. 点击提交"
-    description += "</br></br>基础功能区使用说明: 1. 输入文本; 2. 点击任意基础功能区按钮"
-    description += "</br></br>函数插件区使用说明: 1. 输入路径/问题, 或者上传文件; 2. 点击任意函数插件区按钮"
-    description += "</br></br>虚空终端使用说明: 点击虚空终端, 然后根据提示输入指令, 再次点击虚空终端"
-    description += "</br></br>如何保存对话: 点击保存当前的对话按钮"
-    description += "</br></br>如何语音对话: 请阅读Wiki"
-    description += "</br></br>如何临时更换API_KEY: 在输入区输入临时API_KEY后提交（网页刷新后失效）"
    
    # 问询记录, python 版本建议3.9+（越新越好）
    import logging, uuid
@@ -138,17 +139,17 @@ def main():
                            with gr.Row():
                                switchy_bt = gr.Button(r"请先从插件列表中选择", variant="secondary").style(size="sm")
                    with gr.Row():
-                        with gr.Accordion("点击展开“文件上传区”。上传本地文件/压缩包供函数插件调用。", open=False) as area_file_up:
+                        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")


-        with gr.Floating(init_x="0%", init_y="0%", visible=True, width=None, drag="forbidden"):
+        with gr.Floating(init_x="0%", init_y="0%", visible=True, width=None, drag="forbidden", elem_id="tooltip"):
            with gr.Row():
                with gr.Tab("上传文件", elem_id="interact-panel"):
                    gr.Markdown("请上传本地文件/压缩包供“函数插件区”功能调用。请注意: 上传文件后会自动把输入区修改为相应路径。")
                    file_upload_2 = gr.Files(label="任何文件, 推荐上传压缩文件(zip, tar)", file_count="multiple", elem_id="elem_upload_float")
    
-                with gr.Tab("更换模型 & Prompt", elem_id="interact-panel"):
+                with gr.Tab("更换模型", elem_id="interact-panel"):
                    md_dropdown = gr.Dropdown(AVAIL_LLM_MODELS, value=LLM_MODEL, label="更换LLM模型/请求源").style(container=False)
                    top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",)
                    temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",)
@@ -160,18 +161,11 @@ def main():
                    checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区", "浮动输入区", "输入清除键", "插件参数区"], 
                                                  value=["基础功能区", "函数插件区"], label="显示/隐藏功能区", elem_id='cbs').style(container=False)
                    checkboxes_2 = gr.CheckboxGroup(["自定义菜单"], 
-                                                  value=[], label="显示/隐藏自定义菜单", elem_id='cbs').style(container=False)
+                                                  value=[], label="显示/隐藏自定义菜单", elem_id='cbsc').style(container=False)
                    dark_mode_btn = gr.Button("切换界面明暗 ☀", variant="secondary").style(size="sm")
-                    dark_mode_btn.click(None, None, None, _js="""() => {
-                            if (document.querySelectorAll('.dark').length) {
-                                document.querySelectorAll('.dark').forEach(el => el.classList.remove('dark'));
-                            } else {
-                                document.querySelector('body').classList.add('dark');
-                            }
-                        }""",
-                    )
+                    dark_mode_btn.click(None, None, None, _js=js_code_for_toggle_darkmode)
                with gr.Tab("帮助", elem_id="interact-panel"):
-                    gr.Markdown(description)
+                    gr.Markdown(help_menu_description)

        with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top") as area_input_secondary:
            with gr.Accordion("浮动输入区", open=True, elem_id="input-panel2"):
@@ -186,16 +180,6 @@ def main():
                        stopBtn2 = gr.Button("停止", variant="secondary"); stopBtn2.style(size="sm")
                        clearBtn2 = gr.Button("清除", variant="secondary", visible=False); clearBtn2.style(size="sm")

-        def to_cookie_str(d):
-            # Pickle the dictionary and encode it as a string
-            pickled_dict = pickle.dumps(d)
-            cookie_value = base64.b64encode(pickled_dict).decode('utf-8')
-            return cookie_value
-        
-        def from_cookie_str(c):
-            # Decode the base64-encoded string and unpickle it into a dictionary
-            pickled_dict = base64.b64decode(c.encode('utf-8'))
-            return pickle.loads(pickled_dict)

        with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top") as area_customize:
            with gr.Accordion("自定义菜单", open=True, elem_id="edit-panel"):
@@ -255,7 +239,8 @@ def main():
                        basic_fn_load.click(reflesh_btn, [persistent_cookie, cookies], [cookies, *customize_btns.values(), *predefined_btns.values()])
                        h = basic_fn_confirm.click(assign_btn, [persistent_cookie, cookies, basic_btn_dropdown, basic_fn_title, basic_fn_prefix, basic_fn_suffix], 
                                                   [persistent_cookie, cookies, *customize_btns.values(), *predefined_btns.values()])
-                        h.then(None, [persistent_cookie], None, _js="""(persistent_cookie)=>{setCookie("persistent_cookie", persistent_cookie, 5);}""") # save persistent cookie
+                        # save persistent cookie
+                        h.then(None, [persistent_cookie], None, _js="""(persistent_cookie)=>{setCookie("persistent_cookie", persistent_cookie, 5);}""")

        # 功能区显示开关与功能区的互动
        def fn_area_visibility(a):
@@ -305,8 +290,8 @@ def main():
            click_handle = btn.click(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True), gr.State(btn.value)], outputs=output_combo)
            cancel_handles.append(click_handle)
        # 文件上传区，接收文件后与chatbot的互动
-        file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt, txt2, checkboxes, cookies], [chatbot, txt, txt2, cookies])
-        file_upload_2.upload(on_file_uploaded, [file_upload_2, chatbot, txt, txt2, checkboxes, cookies], [chatbot, txt, txt2, cookies])
+        file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt, txt2, checkboxes, cookies], [chatbot, txt, txt2, cookies]).then(None, None, None,   _js=r"()=>{toast_push('上传完毕 ...'); cancel_loading_status();}")
+        file_upload_2.upload(on_file_uploaded, [file_upload_2, chatbot, txt, txt2, checkboxes, cookies], [chatbot, txt, txt2, cookies]).then(None, None, None, _js=r"()=>{toast_push('上传完毕 ...'); cancel_loading_status();}")
        # 函数插件-固定按钮区
        for k in plugins:
            if not plugins[k].get("AsButton", True): continue
@@ -342,18 +327,7 @@ def main():
            None,
            [secret_css],
            None,
-            _js="""(css) => {
-                var existingStyles = document.querySelectorAll("style[data-loaded-css]");
-                for (var i = 0; i < existingStyles.length; i++) {
-                    var style = existingStyles[i];
-                    style.parentNode.removeChild(style);
-                }
-                var styleElement = document.createElement('style');
-                styleElement.setAttribute('data-loaded-css', css);
-                styleElement.innerHTML = css;
-                document.head.appendChild(styleElement);
-            }
-            """
+            _js=js_code_for_css_changing
        )
        # 随变按钮的回调函数注册
        def route(request: gr.Request, k, *args, **kwargs):
@@ -385,27 +359,10 @@ def main():
                rad.feed(cookies['uuid'].hex, audio)
            audio_mic.stream(deal_audio, inputs=[audio_mic, cookies])

-        def init_cookie(cookies, chatbot):
-            # 为每一位访问的用户赋予一个独一无二的uuid编码
-            cookies.update({'uuid': uuid.uuid4()})
-            return cookies
+
        demo.load(init_cookie, inputs=[cookies, chatbot], outputs=[cookies])
-        darkmode_js = """(dark) => {
-            dark = dark == "True";
-            if (document.querySelectorAll('.dark').length) {
-                if (!dark){
-                    document.querySelectorAll('.dark').forEach(el => el.classList.remove('dark'));
-                }
-            } else {
-                if (dark){
-                    document.querySelector('body').classList.add('dark');
-                }
-            }
-        }"""
-        load_cookie_js = """(persistent_cookie) => {
-            return getCookie("persistent_cookie");
-        }"""
-        demo.load(None, inputs=None, outputs=[persistent_cookie], _js=load_cookie_js)
+        darkmode_js = js_code_for_darkmode_init
+        demo.load(None, inputs=None, outputs=[persistent_cookie], _js=js_code_for_persistent_cookie_init)
        demo.load(None, inputs=[dark_mode], outputs=None, _js=darkmode_js)    # 配置暗色主题或亮色主题
        demo.load(None, inputs=[gr.Textbox(LAYOUT, visible=False)], outputs=None, _js='(LAYOUT)=>{GptAcademicJavaScriptInit(LAYOUT);}')
        
@@ -418,7 +375,7 @@ def main():

        def auto_updates(): time.sleep(0); auto_update()
        def open_browser(): time.sleep(2); webbrowser.open_new_tab(f"http://localhost:{PORT}")
-        def warm_up_mods(): time.sleep(4); warm_up_modules()
+        def warm_up_mods(): time.sleep(6); warm_up_modules()
        
        threading.Thread(target=auto_updates, name="self-upgrade", daemon=True).start() # 查看自动更新
        threading.Thread(target=open_browser, name="open-browser", daemon=True).start() # 打开浏览器页面
--- a/multi_language.py
+++ b/multi_language.py
@@ -352,9 +352,9 @@ def step_1_core_key_translate():
        chinese_core_keys_norepeat_mapping.update({k:cached_translation[k]})
    chinese_core_keys_norepeat_mapping = dict(sorted(chinese_core_keys_norepeat_mapping.items(), key=lambda x: -len(x[0])))

-    # ===============================================
+    # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
    # copy
-    # ===============================================
+    # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
    def copy_source_code():

        from toolbox import get_conf
@@ -367,9 +367,9 @@ def step_1_core_key_translate():
        shutil.copytree('./', backup_dir, ignore=lambda x, y: blacklist)
    copy_source_code()

-    # ===============================================
+    # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
    # primary key replace
-    # ===============================================
+    # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
    directory_path = f'./multi-language/{LANG}/'
    for root, dirs, files in os.walk(directory_path):
        for file in files:
@@ -389,9 +389,9 @@ def step_1_core_key_translate():

 def step_2_core_key_translate():

-    # =================================================================================================
+    # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
    # step2 
-    # =================================================================================================
+    # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=

    def load_string(strings, string_input):
        string_ = string_input.strip().strip(',').strip().strip('.').strip()
@@ -492,9 +492,9 @@ def step_2_core_key_translate():
    cached_translation.update(read_map_from_json(language=LANG_STD))
    cached_translation = dict(sorted(cached_translation.items(), key=lambda x: -len(x[0])))

-    # ===============================================
+    # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
    # literal key replace
-    # ===============================================
+    # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
    directory_path = f'./multi-language/{LANG}/'
    for root, dirs, files in os.walk(directory_path):
        for file in files:
--- a/request_llms/bridge_all.py
+++ b/request_llms/bridge_all.py
@@ -28,6 +28,9 @@ from .bridge_chatglm3 import predict as chatglm3_ui
 from .bridge_qianfan import predict_no_ui_long_connection as qianfan_noui
 from .bridge_qianfan import predict as qianfan_ui

+from .bridge_google_gemini import predict as genai_ui
+from .bridge_google_gemini import predict_no_ui_long_connection  as genai_noui
+
 colors = ['#FF00FF', '#00FFFF', '#FF0000', '#990099', '#009999', '#990044']

 class LazyloadTiktoken(object):
@@ -246,6 +249,22 @@ model_info = {
        "tokenizer": tokenizer_gpt35,
        "token_cnt": get_token_num_gpt35,
    },
+    "gemini-pro": {
+        "fn_with_ui": genai_ui,
+        "fn_without_ui": genai_noui,
+        "endpoint": None,
+        "max_token": 1024 * 32,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
+    "gemini-pro-vision": {
+        "fn_with_ui": genai_ui,
+        "fn_without_ui": genai_noui,
+        "endpoint": None,
+        "max_token": 1024 * 32,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
 }

 # -=-=-=-=-=-=- api2d 对齐支持 -=-=-=-=-=-=-
@@ -431,14 +450,14 @@ if "chatglm_onnx" in AVAIL_LLM_MODELS:
        })
    except:
        print(trimmed_format_exc())
-if "qwen" in AVAIL_LLM_MODELS:
+if "qwen-local" in AVAIL_LLM_MODELS:
    try:
-        from .bridge_qwen import predict_no_ui_long_connection as qwen_noui
-        from .bridge_qwen import predict as qwen_ui
+        from .bridge_qwen_local import predict_no_ui_long_connection as qwen_local_noui
+        from .bridge_qwen_local import predict as qwen_local_ui
        model_info.update({
-            "qwen": {
-                "fn_with_ui": qwen_ui,
-                "fn_without_ui": qwen_noui,
+            "qwen-local": {
+                "fn_with_ui": qwen_local_ui,
+                "fn_without_ui": qwen_local_noui,
                "endpoint": None,
                "max_token": 4096,
                "tokenizer": tokenizer_gpt35,
@@ -447,16 +466,32 @@ if "qwen" in AVAIL_LLM_MODELS:
        })
    except:
        print(trimmed_format_exc())
-if "chatgpt_website" in AVAIL_LLM_MODELS:   # 接入一些逆向工程https://github.com/acheong08/ChatGPT-to-API/
+if "qwen-turbo" in AVAIL_LLM_MODELS or "qwen-plus" in AVAIL_LLM_MODELS or "qwen-max" in AVAIL_LLM_MODELS:   # zhipuai
    try:
-        from .bridge_chatgpt_website import predict_no_ui_long_connection as chatgpt_website_noui
-        from .bridge_chatgpt_website import predict as chatgpt_website_ui
+        from .bridge_qwen import predict_no_ui_long_connection as qwen_noui
+        from .bridge_qwen import predict as qwen_ui
        model_info.update({
-            "chatgpt_website": {
-                "fn_with_ui": chatgpt_website_ui,
-                "fn_without_ui": chatgpt_website_noui,
-                "endpoint": openai_endpoint,
-                "max_token": 4096,
+            "qwen-turbo": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "endpoint": None,
+                "max_token": 6144,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "qwen-plus": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "endpoint": None,
+                "max_token": 30720,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "qwen-max": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "endpoint": None,
+                "max_token": 28672,
                "tokenizer": tokenizer_gpt35,
                "token_cnt": get_token_num_gpt35,
            }
@@ -559,6 +594,23 @@ if "deepseekcoder" in AVAIL_LLM_MODELS:   # deepseekcoder
        })
    except:
        print(trimmed_format_exc())
+# if "skylark" in AVAIL_LLM_MODELS:
+#     try:
+#         from .bridge_skylark2 import predict_no_ui_long_connection as skylark_noui
+#         from .bridge_skylark2 import predict as skylark_ui
+#         model_info.update({
+#             "skylark": {
+#                 "fn_with_ui": skylark_ui,
+#                 "fn_without_ui": skylark_noui,
+#                 "endpoint": None,
+#                 "max_token": 4096,
+#                 "tokenizer": tokenizer_gpt35,
+#                 "token_cnt": get_token_num_gpt35,
+#             }
+#         })
+#     except:
+#         print(trimmed_format_exc())
+

 # <-- 用于定义和切换多个azure模型 -->
 AZURE_CFG_ARRAY = get_conf("AZURE_CFG_ARRAY")
--- a/request_llms/bridge_chatgpt.py
+++ b/request_llms/bridge_chatgpt.py
@@ -51,7 +51,8 @@ def decode_chunk(chunk):
        chunkjson = json.loads(chunk_decoded[6:])
        has_choices = 'choices' in chunkjson
        if has_choices: choice_valid = (len(chunkjson['choices']) > 0)
-        if has_choices and choice_valid: has_content = "content" in chunkjson['choices'][0]["delta"]
+        if has_choices and choice_valid: has_content = ("content" in chunkjson['choices'][0]["delta"])
+        if has_content: has_content = (chunkjson['choices'][0]["delta"]["content"] is not None)
        if has_choices and choice_valid: has_role = "role" in chunkjson['choices'][0]["delta"]
    except: 
        pass
@@ -101,20 +102,25 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
    result = ''
    json_data = None
    while True:
-        try: chunk = next(stream_response).decode()
+        try: chunk = next(stream_response)
        except StopIteration: 
            break
        except requests.exceptions.ConnectionError:
-            chunk = next(stream_response).decode() # 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.encode('utf8'), stream_response).decode()
+            chunk = next(stream_response) # 失败了，重试一次？再失败就没办法了。
+        chunk_decoded, chunkjson, has_choices, choice_valid, has_content, has_role = decode_chunk(chunk)
+        if len(chunk_decoded)==0: continue
+        if not chunk_decoded.startswith('data:'): 
+            error_msg = get_full_error(chunk, stream_response).decode()
            if "reduce the length" in error_msg:
                raise ConnectionAbortedError("OpenAI拒绝了请求:" + error_msg)
            else:
                raise RuntimeError("OpenAI拒绝了请求：" + error_msg)
-        if ('data: [DONE]' in chunk): break # api2d 正常完成
-        json_data = json.loads(chunk.lstrip('data:'))['choices'][0]
+        if ('data: [DONE]' in chunk_decoded): break # api2d 正常完成
+        # 提前读取一些信息 （用于判断异常）
+        if has_choices and not choice_valid:
+            # 一些垃圾第三方接口的出现这样的错误
+            continue
+        json_data = chunkjson['choices'][0]
        delta = json_data["delta"]
        if len(delta) == 0: break
        if "role" in delta: continue
@@ -238,6 +244,9 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
                    if has_choices and not choice_valid:
                        # 一些垃圾第三方接口的出现这样的错误
                        continue
+                    if ('data: [DONE]' not in chunk_decoded) and len(chunk_decoded) > 0 and (chunkjson is None):
+                        # 传递进来一些奇怪的东西
+                        raise ValueError(f'无法读取以下数据，请检查配置。\n\n{chunk_decoded}')
                    # 前者是API2D的结束条件，后者是OPENAI的结束条件
                    if ('data: [DONE]' in chunk_decoded) or (len(chunkjson['choices'][0]["delta"]) == 0):
                        # 判定为数据流的结束，gpt_replying_buffer也写完了
--- a/request_llms/bridge_google_gemini.py
+++ b/request_llms/bridge_google_gemini.py
@@ -0,0 +1,114 @@
+# encoding: utf-8
+# @Time   : 2023/12/21
+# @Author : Spike
+# @Descr   :
+import json
+import re
+import os
+import time
+from request_llms.com_google import GoogleChatInit
+from toolbox import get_conf, update_ui, update_ui_lastest_msg, have_any_recent_upload_image_files, trimmed_format_exc
+
+proxies, TIMEOUT_SECONDS, MAX_RETRY = get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY')
+timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
+                  '网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。'
+
+
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None,
+                                  console_slience=False):
+    # 检查API_KEY
+    if get_conf("GEMINI_API_KEY") == "":
+        raise ValueError(f"请配置 GEMINI_API_KEY。")
+
+    genai = GoogleChatInit()
+    watch_dog_patience = 5  # 看门狗的耐心, 设置5秒即可
+    gpt_replying_buffer = ''
+    stream_response = genai.generate_chat(inputs, llm_kwargs, history, sys_prompt)
+    for response in stream_response:
+        results = response.decode()
+        match = re.search(r'"text":\s*"((?:[^"\\]|\\.)*)"', results, flags=re.DOTALL)
+        error_match = re.search(r'\"message\":\s*\"(.*?)\"', results, flags=re.DOTALL)
+        if match:
+            try:
+                paraphrase = json.loads('{"text": "%s"}' % match.group(1))
+            except:
+                raise ValueError(f"解析GEMINI消息出错。")
+            buffer = paraphrase['text']
+            gpt_replying_buffer += buffer
+            if len(observe_window) >= 1:
+                observe_window[0] = gpt_replying_buffer
+            if len(observe_window) >= 2:
+                if (time.time() - observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。")
+        if error_match:
+            raise RuntimeError(f'{gpt_replying_buffer} 对话错误')
+    return gpt_replying_buffer
+
+
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream=True, additional_fn=None):
+    # 检查API_KEY
+    if get_conf("GEMINI_API_KEY") == "":
+        yield from update_ui_lastest_msg(f"请配置 GEMINI_API_KEY。", chatbot=chatbot, history=history, delay=0)
+        return
+
+    # 适配润色区域
+    if additional_fn is not None:
+        from core_functional import handle_core_functionality
+        inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
+
+    if "vision" in llm_kwargs["llm_model"]:
+        have_recent_file, image_paths = have_any_recent_upload_image_files(chatbot)
+        def make_media_input(inputs, image_paths): 
+            for image_path in image_paths:
+                inputs = inputs + f'<br/><br/><div align="center"><img src="file={os.path.abspath(image_path)}"></div>'
+            return inputs
+        if have_recent_file:
+            inputs = make_media_input(inputs, image_paths)
+
+    chatbot.append((inputs, ""))
+    yield from update_ui(chatbot=chatbot, history=history)
+    genai = GoogleChatInit()
+    retry = 0
+    while True:
+        try:
+            stream_response = genai.generate_chat(inputs, llm_kwargs, history, system_prompt)
+            break
+        except Exception as e:
+            retry += 1
+            chatbot[-1] = ((chatbot[-1][0], trimmed_format_exc()))
+            yield from update_ui(chatbot=chatbot, history=history, msg="请求失败")  # 刷新界面
+            return
+    gpt_replying_buffer = ""
+    gpt_security_policy = ""
+    history.extend([inputs, ''])
+    for response in stream_response:
+        results = response.decode("utf-8")    # 被这个解码给耍了。。
+        gpt_security_policy += results
+        match = re.search(r'"text":\s*"((?:[^"\\]|\\.)*)"', results, flags=re.DOTALL)
+        error_match = re.search(r'\"message\":\s*\"(.*)\"', results, flags=re.DOTALL)
+        if match:
+            try:
+                paraphrase = json.loads('{"text": "%s"}' % match.group(1))
+            except:
+                raise ValueError(f"解析GEMINI消息出错。")
+            gpt_replying_buffer += paraphrase['text']    # 使用 json 解析库进行处理
+            chatbot[-1] = (inputs, gpt_replying_buffer)
+            history[-1] = gpt_replying_buffer
+            yield from update_ui(chatbot=chatbot, history=history)
+        if error_match:
+            history = history[-2]  # 错误的不纳入对话
+            chatbot[-1] = (inputs, gpt_replying_buffer + f"对话错误，请查看message\n\n```\n{error_match.group(1)}\n```")
+            yield from update_ui(chatbot=chatbot, history=history)
+            raise RuntimeError('对话错误')
+    if not gpt_replying_buffer:
+        history = history[-2]  # 错误的不纳入对话
+        chatbot[-1] = (inputs, gpt_replying_buffer + f"触发了Google的安全访问策略，没有回答\n\n```\n{gpt_security_policy}\n```")
+        yield from update_ui(chatbot=chatbot, history=history)
+
+
+
+if __name__ == '__main__':
+    import sys
+    llm_kwargs = {'llm_model': 'gemini-pro'}
+    result = predict('Write long a story about a magic backpack.', llm_kwargs, llm_kwargs, [])
+    for i in result:
+        print(i)
--- a/request_llms/bridge_newbingfree.py
+++ b/request_llms/bridge_newbingfree.py
@@ -1,16 +1,17 @@
 """
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 第一部分：来自EdgeGPT.py
 https://github.com/acheong08/EdgeGPT
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 """
 from .edge_gpt_free import Chatbot as NewbingChatbot
+
 load_message = "等待NewBing响应。"

 """
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 第二部分：子进程Worker（调用主体）
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 """
 import time
 import json
@@ -22,19 +23,30 @@ import threading
 from toolbox import update_ui, get_conf, trimmed_format_exc
 from multiprocessing import Process, Pipe

+
 def preprocess_newbing_out(s):
-    pattern = r'\^(\d+)\^' # 匹配^数字^
-    sub = lambda m: '('+m.group(1)+')' # 将匹配到的数字作为替换值
+    pattern = r"\^(\d+)\^"  # 匹配^数字^
+    sub = lambda m: "(" + m.group(1) + ")"  # 将匹配到的数字作为替换值
    result = re.sub(pattern, sub, s)  # 替换操作
-    if '[1]' in result:
-        result += '\n\n```reference\n' + "\n".join([r for r in result.split('\n') if r.startswith('[')]) + '\n```\n'
+    if "[1]" in result:
+        result += (
+            "\n\n```reference\n"
+            + "\n".join([r for r in result.split("\n") if r.startswith("[")])
+            + "\n```\n"
+        )
    return result

+
 def preprocess_newbing_out_simple(result):
-    if '[1]' in result:
-        result += '\n\n```reference\n' + "\n".join([r for r in result.split('\n') if r.startswith('[')]) + '\n```\n'
+    if "[1]" in result:
+        result += (
+            "\n\n```reference\n"
+            + "\n".join([r for r in result.split("\n") if r.startswith("[")])
+            + "\n```\n"
+        )
    return result

+
 class NewBingHandle(Process):
    def __init__(self):
        super().__init__(daemon=True)
@@ -51,6 +63,7 @@ class NewBingHandle(Process):
        try:
            self.success = False
            import certifi, httpx, rich
+
            self.info = "依赖检测通过，等待NewBing响应。注意目前不能多人同时调用NewBing接口（有线程锁），否则将导致每个人的NewBing问询历史互相渗透。调用NewBing时，会自动使用已配置的代理。"
            self.success = True
        except:
@@ -62,15 +75,16 @@ class NewBingHandle(Process):

    async def async_run(self):
        # 读取配置
-        NEWBING_STYLE = get_conf('NEWBING_STYLE')
+        NEWBING_STYLE = get_conf("NEWBING_STYLE")
        from request_llms.bridge_all import model_info
-        endpoint = model_info['newbing']['endpoint']
+
+        endpoint = model_info["newbing"]["endpoint"]
        while True:
            # 等待
            kwargs = self.child.recv()
-            question=kwargs['query']
-            history=kwargs['history']
-            system_prompt=kwargs['system_prompt']
+            question = kwargs["query"]
+            history = kwargs["history"]
+            system_prompt = kwargs["system_prompt"]

            # 是否重置
            if len(self.local_history) > 0 and len(history) == 0:
@@ -81,19 +95,19 @@ class NewBingHandle(Process):
            prompt = ""
            if system_prompt not in self.local_history:
                self.local_history.append(system_prompt)
-                prompt += system_prompt + '\n'
+                prompt += system_prompt + "\n"

            # 追加历史
            for ab in history:
                a, b = ab
                if a not in self.local_history:
                    self.local_history.append(a)
-                    prompt += a + '\n'
+                    prompt += a + "\n"

            # 问题
            prompt += question
            self.local_history.append(question)
-            print('question:', prompt)
+            print("question:", prompt)
            # 提交
            async for final, response in self.newbing_model.ask_stream(
                prompt=question,
@@ -104,11 +118,10 @@ class NewBingHandle(Process):
                    print(response)
                    self.child.send(str(response))
                else:
-                    print('-------- receive final ---------')
-                    self.child.send('[Finish]')
+                    print("-------- receive final ---------")
+                    self.child.send("[Finish]")
                    # self.local_history.append(response)

-    
    def run(self):
        """
        这个函数运行在子进程
@@ -118,32 +131,37 @@ class NewBingHandle(Process):
        self.local_history = []
        if (self.newbing_model is None) or (not self.success):
            # 代理设置
-            proxies, NEWBING_COOKIES = get_conf('proxies', 'NEWBING_COOKIES')
+            proxies, NEWBING_COOKIES = get_conf("proxies", "NEWBING_COOKIES")
            if proxies is None:
                self.proxies_https = None
            else:
-                self.proxies_https = proxies['https']
+                self.proxies_https = proxies["https"]

            if (NEWBING_COOKIES is not None) and len(NEWBING_COOKIES) > 100:
                try:
                    cookies = json.loads(NEWBING_COOKIES)
                except:
                    self.success = False
-                    tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
-                    self.child.send(f'[Local Message] NEWBING_COOKIES未填写或有格式错误。')
-                    self.child.send('[Fail]'); self.child.send('[Finish]')
+                    tb_str = "\n```\n" + trimmed_format_exc() + "\n```\n"
+                    self.child.send(f"[Local Message] NEWBING_COOKIES未填写或有格式错误。")
+                    self.child.send("[Fail]")
+                    self.child.send("[Finish]")
                    raise RuntimeError(f"NEWBING_COOKIES未填写或有格式错误。")
            else:
                cookies = None

            try:
-                self.newbing_model = NewbingChatbot(proxy=self.proxies_https, cookies=cookies)
+                self.newbing_model = NewbingChatbot(
+                    proxy=self.proxies_https, cookies=cookies
+                )
            except:
                self.success = False
-                tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
-                self.child.send(f'[Local Message] 不能加载Newbing组件，请注意Newbing组件已不再维护。{tb_str}')
-                self.child.send('[Fail]')
-                self.child.send('[Finish]')
+                tb_str = "\n```\n" + trimmed_format_exc() + "\n```\n"
+                self.child.send(
+                    f"[Local Message] 不能加载Newbing组件，请注意Newbing组件已不再维护。{tb_str}"
+                )
+                self.child.send("[Fail]")
+                self.child.send("[Finish]")
                raise RuntimeError(f"不能加载Newbing组件，请注意Newbing组件已不再维护。")

        self.success = True
@@ -151,10 +169,12 @@ class NewBingHandle(Process):
            # 进入任务等待状态
            asyncio.run(self.async_run())
        except Exception:
-            tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
-            self.child.send(f'[Local Message] Newbing 请求失败，报错信息如下. 如果是与网络相关的问题，建议更换代理协议（推荐http）或代理节点 {tb_str}.')
-            self.child.send('[Fail]')
-            self.child.send('[Finish]')
+            tb_str = "\n```\n" + trimmed_format_exc() + "\n```\n"
+            self.child.send(
+                f"[Local Message] Newbing 请求失败，报错信息如下. 如果是与网络相关的问题，建议更换代理协议（推荐http）或代理节点 {tb_str}."
+            )
+            self.child.send("[Fail]")
+            self.child.send("[Finish]")

    def stream_chat(self, **kwargs):
        """
@@ -164,21 +184,33 @@ class NewBingHandle(Process):
        self.parent.send(kwargs)  # 请求子进程
        while True:
            res = self.parent.recv()  # 等待newbing回复的片段
-            if res == '[Finish]': break                         # 结束
-            elif res == '[Fail]': self.success = False; break   # 失败
-            else: yield res                                     # newbing回复的片段
+            if res == "[Finish]":
+                break  # 结束
+            elif res == "[Fail]":
+                self.success = False
+                break  # 失败
+            else:
+                yield res  # newbing回复的片段
        self.threadLock.release()  # 释放线程锁


 """
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 第三部分：主进程统一调用函数接口
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 """
 global newbingfree_handle
 newbingfree_handle = None

-def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=[], console_slience=False):
+
+def predict_no_ui_long_connection(
+    inputs,
+    llm_kwargs,
+    history=[],
+    sys_prompt="",
+    observe_window=[],
+    console_slience=False,
+):
    """
    多线程方法
    函数的说明请见 request_llms/bridge_all.py
@@ -186,7 +218,8 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
    global newbingfree_handle
    if (newbingfree_handle is None) or (not newbingfree_handle.success):
        newbingfree_handle = NewBingHandle()
-        if len(observe_window) >= 1: observe_window[0] = load_message + "\n\n" + newbingfree_handle.info
+        if len(observe_window) >= 1:
+            observe_window[0] = load_message + "\n\n" + newbingfree_handle.info
        if not newbingfree_handle.success:
            error = newbingfree_handle.info
            newbingfree_handle = None
@@ -199,15 +232,34 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",

    watch_dog_patience = 5  # 看门狗 (watchdog) 的耐心, 设置5秒即可
    response = ""
-    if len(observe_window) >= 1: observe_window[0] = "[Local Message] 等待NewBing响应中 ..."
-    for response in newbingfree_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=sys_prompt, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
-        if len(observe_window) >= 1:  observe_window[0] = preprocess_newbing_out_simple(response)
+    if len(observe_window) >= 1:
+        observe_window[0] = "[Local Message] 等待NewBing响应中 ..."
+    for response in newbingfree_handle.stream_chat(
+        query=inputs,
+        history=history_feedin,
+        system_prompt=sys_prompt,
+        max_length=llm_kwargs["max_length"],
+        top_p=llm_kwargs["top_p"],
+        temperature=llm_kwargs["temperature"],
+    ):
+        if len(observe_window) >= 1:
+            observe_window[0] = preprocess_newbing_out_simple(response)
        if len(observe_window) >= 2:
            if (time.time() - observe_window[1]) > watch_dog_patience:
                raise RuntimeError("程序终止。")
    return preprocess_newbing_out_simple(response)

-def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
+
+def predict(
+    inputs,
+    llm_kwargs,
+    plugin_kwargs,
+    chatbot,
+    history=[],
+    system_prompt="",
+    stream=True,
+    additional_fn=None,
+):
    """
    单线程方法
    函数的说明请见 request_llms/bridge_all.py
@@ -225,7 +277,10 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp

    if additional_fn is not None:
        from core_functional import handle_core_functionality
-        inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
+
+        inputs, history = handle_core_functionality(
+            additional_fn, inputs, history, chatbot
+        )

    history_feedin = []
    for i in range(len(history) // 2):
@@ -233,13 +288,24 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp

    chatbot[-1] = (inputs, "[Local Message] 等待NewBing响应中 ...")
    response = "[Local Message] 等待NewBing响应中 ..."
-    yield from update_ui(chatbot=chatbot, history=history, msg="NewBing响应缓慢，尚未完成全部响应，请耐心完成后再提交新问题。")
-    for response in newbingfree_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=system_prompt, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
+    yield from update_ui(
+        chatbot=chatbot, history=history, msg="NewBing响应缓慢，尚未完成全部响应，请耐心完成后再提交新问题。"
+    )
+    for response in newbingfree_handle.stream_chat(
+        query=inputs,
+        history=history_feedin,
+        system_prompt=system_prompt,
+        max_length=llm_kwargs["max_length"],
+        top_p=llm_kwargs["top_p"],
+        temperature=llm_kwargs["temperature"],
+    ):
        chatbot[-1] = (inputs, preprocess_newbing_out(response))
-        yield from update_ui(chatbot=chatbot, history=history, msg="NewBing响应缓慢，尚未完成全部响应，请耐心完成后再提交新问题。")
-    if response == "[Local Message] 等待NewBing响应中 ...": response = "[Local Message] NewBing响应异常，请刷新界面重试 ..."
+        yield from update_ui(
+            chatbot=chatbot, history=history, msg="NewBing响应缓慢，尚未完成全部响应，请耐心完成后再提交新问题。"
+        )
+    if response == "[Local Message] 等待NewBing响应中 ...":
+        response = "[Local Message] NewBing响应异常，请刷新界面重试 ..."
    history.extend([inputs, response])
-    logging.info(f'[raw_input] {inputs}')
-    logging.info(f'[response] {response}')
+    logging.info(f"[raw_input] {inputs}")
+    logging.info(f"[response] {response}")
    yield from update_ui(chatbot=chatbot, history=history, msg="完成全部响应，请提交新问题。")
-
--- a/request_llms/bridge_qwen.py
+++ b/request_llms/bridge_qwen.py
@@ -1,59 +1,62 @@
-model_name = "Qwen"
-cmd_to_install = "`pip install -r request_llms/requirements_qwen.txt`"
+import time
+import os
+from toolbox import update_ui, get_conf, update_ui_lastest_msg
+from toolbox import check_packages, report_exception

-from toolbox import ProxyNetworkActivate, get_conf
-from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
+model_name = 'Qwen'

+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=[], console_slience=False):
+    """
+        ⭐多线程方法
+        函数的说明请见 request_llms/bridge_all.py
+    """
+    watch_dog_patience = 5
+    response = ""

+    from .com_qwenapi import QwenRequestInstance
+    sri = QwenRequestInstance()
+    for response in sri.generate(inputs, llm_kwargs, history, sys_prompt):
+        if len(observe_window) >= 1:
+            observe_window[0] = response
+        if len(observe_window) >= 2:
+            if (time.time()-observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。")
+    return response

-# ------------------------------------------------------------------------------------------------------------------------
-# 🔌💻 Local Model
-# ------------------------------------------------------------------------------------------------------------------------
-class GetQwenLMHandle(LocalLLMHandle):
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
+    """
+        ⭐单线程方法
+        函数的说明请见 request_llms/bridge_all.py
+    """
+    chatbot.append((inputs, ""))
+    yield from update_ui(chatbot=chatbot, history=history)

-    def load_model_info(self):
-        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
-        self.model_name = model_name
-        self.cmd_to_install = cmd_to_install
+    # 尝试导入依赖，如果缺少依赖，则给出安装建议
+    try:
+        check_packages(["dashscope"])
+    except:
+        yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade dashscope```。",
+                                         chatbot=chatbot, history=history, delay=0)
+        return

-    def load_model_and_tokenizer(self):
-        # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
-        # from modelscope import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
-        from transformers import AutoModelForCausalLM, AutoTokenizer
-        from transformers.generation import GenerationConfig
-        with ProxyNetworkActivate('Download_LLM'):
-            model_id = get_conf('QWEN_MODEL_SELECTION')
-            self._tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True, resume_download=True)
-            # use fp16
-            model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", trust_remote_code=True).eval()
-            model.generation_config = GenerationConfig.from_pretrained(model_id, trust_remote_code=True)  # 可指定不同的生成长度、top_p等相关超参
-            self._model = model
+    # 检查DASHSCOPE_API_KEY
+    if get_conf("DASHSCOPE_API_KEY") == "":
+        yield from update_ui_lastest_msg(f"请配置 DASHSCOPE_API_KEY。",
+                                         chatbot=chatbot, history=history, delay=0)
+        return

-        return self._model, self._tokenizer
+    if additional_fn is not None:
+        from core_functional import handle_core_functionality
+        inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)

-    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
+    # 开始接收回复
+    from .com_qwenapi import QwenRequestInstance
+    sri = QwenRequestInstance()
+    for response in sri.generate(inputs, llm_kwargs, history, system_prompt):
+        chatbot[-1] = (inputs, response)
+        yield from update_ui(chatbot=chatbot, history=history)

-        query, max_length, top_p, temperature, history = adaptor(kwargs)
-
-        for response in self._model.chat_stream(self._tokenizer, query, history=history):
-            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(GetQwenLMHandle, model_name)
+    # 总结输出
+    if response == f"[Local Message] 等待{model_name}响应中 ...":
+        response = f"[Local Message] {model_name}响应异常 ..."
+    history.extend([inputs, response])
+    yield from update_ui(chatbot=chatbot, history=history)
--- a/request_llms/bridge_qwen_local.py
+++ b/request_llms/bridge_qwen_local.py
@@ -0,0 +1,59 @@
+model_name = "Qwen_Local"
+cmd_to_install = "`pip install -r request_llms/requirements_qwen_local.txt`"
+
+from toolbox import ProxyNetworkActivate, get_conf
+from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
+
+
+
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 Local Model
+# ------------------------------------------------------------------------------------------------------------------------
+class GetQwenLMHandle(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
+        # from modelscope import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
+        from transformers import AutoModelForCausalLM, AutoTokenizer
+        from transformers.generation import GenerationConfig
+        with ProxyNetworkActivate('Download_LLM'):
+            model_id = get_conf('QWEN_LOCAL_MODEL_SELECTION')
+            self._tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True, resume_download=True)
+            # use fp16
+            model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", trust_remote_code=True).eval()
+            model.generation_config = GenerationConfig.from_pretrained(model_id, trust_remote_code=True)  # 可指定不同的生成长度、top_p等相关超参
+            self._model = model
+
+        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)
+
+        for response in self._model.chat_stream(self._tokenizer, query, history=history):
+            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(GetQwenLMHandle, model_name)
--- a/request_llms/bridge_skylark2.py
+++ b/request_llms/bridge_skylark2.py
@@ -0,0 +1,67 @@
+import time
+from toolbox import update_ui, get_conf, update_ui_lastest_msg
+from toolbox import check_packages, report_exception
+
+model_name = '云雀大模型'
+
+def validate_key():
+    YUNQUE_SECRET_KEY = get_conf("YUNQUE_SECRET_KEY")
+    if YUNQUE_SECRET_KEY == '': return False
+    return True
+
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=[], console_slience=False):
+    """
+        ⭐ 多线程方法
+        函数的说明请见 request_llms/bridge_all.py
+    """
+    watch_dog_patience = 5
+    response = ""
+
+    if validate_key() is False:
+        raise RuntimeError('请配置YUNQUE_SECRET_KEY')
+
+    from .com_skylark2api import YUNQUERequestInstance
+    sri = YUNQUERequestInstance()
+    for response in sri.generate(inputs, llm_kwargs, history, sys_prompt):
+        if len(observe_window) >= 1:
+            observe_window[0] = response
+        if len(observe_window) >= 2:
+            if (time.time()-observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。")
+    return response
+
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
+    """
+        ⭐ 单线程方法
+        函数的说明请见 request_llms/bridge_all.py
+    """
+    chatbot.append((inputs, ""))
+    yield from update_ui(chatbot=chatbot, history=history)
+
+    # 尝试导入依赖，如果缺少依赖，则给出安装建议
+    try:
+        check_packages(["zhipuai"])
+    except:
+        yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade zhipuai```。",
+                                         chatbot=chatbot, history=history, delay=0)
+        return
+
+    if validate_key() is False:
+        yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置HUOSHAN_API_KEY", chatbot=chatbot, history=history, delay=0)
+        return
+
+    if additional_fn is not None:
+        from core_functional import handle_core_functionality
+        inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
+
+    # 开始接收回复
+    from .com_skylark2api import YUNQUERequestInstance
+    sri = YUNQUERequestInstance()
+    for response in sri.generate(inputs, llm_kwargs, history, system_prompt):
+        chatbot[-1] = (inputs, response)
+        yield from update_ui(chatbot=chatbot, history=history)
+
+    # 总结输出
+    if response == f"[Local Message] 等待{model_name}响应中 ...":
+        response = f"[Local Message] {model_name}响应异常 ..."
+    history.extend([inputs, response])
+    yield from update_ui(chatbot=chatbot, history=history)
--- a/request_llms/bridge_spark.py
+++ b/request_llms/bridge_spark.py
@@ -26,7 +26,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",

    from .com_sparkapi import SparkRequestInstance
    sri = SparkRequestInstance()
-    for response in sri.generate(inputs, llm_kwargs, history, sys_prompt):
+    for response in sri.generate(inputs, llm_kwargs, history, sys_prompt, use_image_api=False):
        if len(observe_window) >= 1:
            observe_window[0] = response
        if len(observe_window) >= 2:
@@ -52,7 +52,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
    # 开始接收回复    
    from .com_sparkapi import SparkRequestInstance
    sri = SparkRequestInstance()
-    for response in sri.generate(inputs, llm_kwargs, history, system_prompt):
+    for response in sri.generate(inputs, llm_kwargs, history, system_prompt, use_image_api=True):
        chatbot[-1] = (inputs, response)
        yield from update_ui(chatbot=chatbot, history=history)

--- a/request_llms/bridge_stackclaude.py
+++ b/request_llms/bridge_stackclaude.py
@@ -7,14 +7,15 @@ import logging
 import time
 from toolbox import get_conf
 import asyncio
+
 load_message = "正在加载Claude组件，请稍候..."

 try:
    """
-    ========================================================================
+    =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
    第一部分：Slack API Client
    https://github.com/yokonsan/claude-in-slack-api
-    ========================================================================
+    =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
    """

    from slack_sdk.errors import SlackApiError
@@ -33,10 +34,13 @@ try:
        - get_reply()：异步方法。循环监听已打开频道的消息，如果收到"Typing…_"结尾的消息说明Claude还在继续输出，否则结束循环。

        """
+
        CHANNEL_ID = None

        async def open_channel(self):
-            response = await self.conversations_open(users=get_conf('SLACK_CLAUDE_BOT_ID'))
+            response = await self.conversations_open(
+                users=get_conf("SLACK_CLAUDE_BOT_ID")
+            )
            self.CHANNEL_ID = response["channel"]["id"]

        async def chat(self, text):
@@ -49,9 +53,14 @@ try:
        async def get_slack_messages(self):
            try:
                # TODO：暂时不支持历史消息，因为在同一个频道里存在多人使用时历史消息渗透问题
-                resp = await self.conversations_history(channel=self.CHANNEL_ID, oldest=self.LAST_TS, limit=1)
-                msg = [msg for msg in resp["messages"]
-                    if msg.get("user") == get_conf('SLACK_CLAUDE_BOT_ID')]
+                resp = await self.conversations_history(
+                    channel=self.CHANNEL_ID, oldest=self.LAST_TS, limit=1
+                )
+                msg = [
+                    msg
+                    for msg in resp["messages"]
+                    if msg.get("user") == get_conf("SLACK_CLAUDE_BOT_ID")
+                ]
                return msg
            except (SlackApiError, KeyError) as e:
                raise RuntimeError(f"获取Slack消息失败。")
@@ -69,13 +78,14 @@ try:
                else:
                    yield True, msg["text"]
                    break
+
 except:
    pass

 """
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 第二部分：子进程Worker（调用主体）
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 """


@@ -96,6 +106,7 @@ class ClaudeHandle(Process):
        try:
            self.success = False
            import slack_sdk
+
            self.info = "依赖检测通过，等待Claude响应。注意目前不能多人同时调用Claude接口（有线程锁），否则将导致每个人的Claude问询历史互相渗透。调用Claude时，会自动使用已配置的代理。"
            self.success = True
        except:
@@ -110,15 +121,15 @@ class ClaudeHandle(Process):
        while True:
            # 等待
            kwargs = self.child.recv()
-            question = kwargs['query']
-            history = kwargs['history']
+            question = kwargs["query"]
+            history = kwargs["history"]

            # 开始问问题
            prompt = ""

            # 问题
            prompt += question
-            print('question:', prompt)
+            print("question:", prompt)

            # 提交
            await self.claude_model.chat(prompt)
@@ -131,11 +142,15 @@ class ClaudeHandle(Process):
                else:
                    # 防止丢失最后一条消息
                    slack_msgs = await self.claude_model.get_slack_messages()
-                    last_msg = slack_msgs[-1]["text"] if slack_msgs and len(slack_msgs) > 0 else ""
+                    last_msg = (
+                        slack_msgs[-1]["text"]
+                        if slack_msgs and len(slack_msgs) > 0
+                        else ""
+                    )
                    if last_msg:
                        self.child.send(last_msg)
-                    print('-------- receive final ---------')
-                    self.child.send('[Finish]')
+                    print("-------- receive final ---------")
+                    self.child.send("[Finish]")

    def run(self):
        """
@@ -146,22 +161,24 @@ class ClaudeHandle(Process):
        self.local_history = []
        if (self.claude_model is None) or (not self.success):
            # 代理设置
-            proxies = get_conf('proxies')
+            proxies = get_conf("proxies")
            if proxies is None:
                self.proxies_https = None
            else:
-                self.proxies_https = proxies['https']
+                self.proxies_https = proxies["https"]

            try:
-                SLACK_CLAUDE_USER_TOKEN = get_conf('SLACK_CLAUDE_USER_TOKEN')
-                self.claude_model = SlackClient(token=SLACK_CLAUDE_USER_TOKEN, proxy=self.proxies_https)
-                print('Claude组件初始化成功。')
+                SLACK_CLAUDE_USER_TOKEN = get_conf("SLACK_CLAUDE_USER_TOKEN")
+                self.claude_model = SlackClient(
+                    token=SLACK_CLAUDE_USER_TOKEN, proxy=self.proxies_https
+                )
+                print("Claude组件初始化成功。")
            except:
                self.success = False
-                tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
-                self.child.send(f'[Local Message] 不能加载Claude组件。{tb_str}')
-                self.child.send('[Fail]')
-                self.child.send('[Finish]')
+                tb_str = "\n```\n" + trimmed_format_exc() + "\n```\n"
+                self.child.send(f"[Local Message] 不能加载Claude组件。{tb_str}")
+                self.child.send("[Fail]")
+                self.child.send("[Finish]")
                raise RuntimeError(f"不能加载Claude组件。")

        self.success = True
@@ -169,10 +186,10 @@ class ClaudeHandle(Process):
            # 进入任务等待状态
            asyncio.run(self.async_run())
        except Exception:
-            tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
-            self.child.send(f'[Local Message] Claude失败 {tb_str}.')
-            self.child.send('[Fail]')
-            self.child.send('[Finish]')
+            tb_str = "\n```\n" + trimmed_format_exc() + "\n```\n"
+            self.child.send(f"[Local Message] Claude失败 {tb_str}.")
+            self.child.send("[Fail]")
+            self.child.send("[Finish]")

    def stream_chat(self, **kwargs):
        """
@@ -182,9 +199,9 @@ class ClaudeHandle(Process):
        self.parent.send(kwargs)  # 发送请求到子进程
        while True:
            res = self.parent.recv()  # 等待Claude回复的片段
-            if res == '[Finish]':
+            if res == "[Finish]":
                break  # 结束
-            elif res == '[Fail]':
+            elif res == "[Fail]":
                self.success = False
                break
            else:
@@ -193,15 +210,22 @@ class ClaudeHandle(Process):


 """
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 第三部分：主进程统一调用函数接口
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 """
 global claude_handle
 claude_handle = None


-def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
+def predict_no_ui_long_connection(
+    inputs,
+    llm_kwargs,
+    history=[],
+    sys_prompt="",
+    observe_window=None,
+    console_slience=False,
+):
    """
    多线程方法
    函数的说明请见 request_llms/bridge_all.py
@@ -223,7 +247,14 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
    watch_dog_patience = 5  # 看门狗 (watchdog) 的耐心, 设置5秒即可
    response = ""
    observe_window[0] = "[Local Message] 等待Claude响应中 ..."
-    for response in claude_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=sys_prompt, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
+    for response in claude_handle.stream_chat(
+        query=inputs,
+        history=history_feedin,
+        system_prompt=sys_prompt,
+        max_length=llm_kwargs["max_length"],
+        top_p=llm_kwargs["top_p"],
+        temperature=llm_kwargs["temperature"],
+    ):
        observe_window[0] = preprocess_newbing_out_simple(response)
        if len(observe_window) >= 2:
            if (time.time() - observe_window[1]) > watch_dog_patience:
@@ -231,7 +262,16 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
    return preprocess_newbing_out_simple(response)


-def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream=True, additional_fn=None):
+def predict(
+    inputs,
+    llm_kwargs,
+    plugin_kwargs,
+    chatbot,
+    history=[],
+    system_prompt="",
+    stream=True,
+    additional_fn=None,
+):
    """
    单线程方法
    函数的说明请见 request_llms/bridge_all.py
@@ -249,7 +289,10 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp

    if additional_fn is not None:
        from core_functional import handle_core_functionality
-        inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
+
+        inputs, history = handle_core_functionality(
+            additional_fn, inputs, history, chatbot
+        )

    history_feedin = []
    for i in range(len(history) // 2):
@@ -257,13 +300,19 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp

    chatbot[-1] = (inputs, "[Local Message] 等待Claude响应中 ...")
    response = "[Local Message] 等待Claude响应中 ..."
-    yield from update_ui(chatbot=chatbot, history=history, msg="Claude响应缓慢，尚未完成全部响应，请耐心完成后再提交新问题。")
-    for response in claude_handle.stream_chat(query=inputs, history=history_feedin, system_prompt=system_prompt):
+    yield from update_ui(
+        chatbot=chatbot, history=history, msg="Claude响应缓慢，尚未完成全部响应，请耐心完成后再提交新问题。"
+    )
+    for response in claude_handle.stream_chat(
+        query=inputs, history=history_feedin, system_prompt=system_prompt
+    ):
        chatbot[-1] = (inputs, preprocess_newbing_out(response))
-        yield from update_ui(chatbot=chatbot, history=history, msg="Claude响应缓慢，尚未完成全部响应，请耐心完成后再提交新问题。")
+        yield from update_ui(
+            chatbot=chatbot, history=history, msg="Claude响应缓慢，尚未完成全部响应，请耐心完成后再提交新问题。"
+        )
    if response == "[Local Message] 等待Claude响应中 ...":
        response = "[Local Message] Claude响应异常，请刷新界面重试 ..."
    history.extend([inputs, response])
-    logging.info(f'[raw_input] {inputs}')
-    logging.info(f'[response] {response}')
+    logging.info(f"[raw_input] {inputs}")
+    logging.info(f"[response] {response}")
    yield from update_ui(chatbot=chatbot, history=history, msg="完成全部响应，请提交新问题。")
--- a/request_llms/bridge_zhipu.py
+++ b/request_llms/bridge_zhipu.py
@@ -42,7 +42,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
    try:
        check_packages(["zhipuai"])
    except:
-        yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade zhipuai```。",
+        yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install zhipuai==1.0.7```。",
                                         chatbot=chatbot, history=history, delay=0)
        return
    
--- a/request_llms/com_google.py
+++ b/request_llms/com_google.py
@@ -0,0 +1,229 @@
+# encoding: utf-8
+# @Time   : 2023/12/25
+# @Author : Spike
+# @Descr   :
+import json
+import os
+import re
+import requests
+from typing import List, Dict, Tuple
+from toolbox import get_conf, encode_image, get_pictures_list
+
+proxies, TIMEOUT_SECONDS = get_conf("proxies", "TIMEOUT_SECONDS")
+
+"""
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
+第五部分 一些文件处理方法
+files_filter_handler 根据type过滤文件
+input_encode_handler 提取input中的文件，并解析
+file_manifest_filter_html 根据type过滤文件, 并解析为html or md 文本
+link_mtime_to_md 文件增加本地时间参数，避免下载到缓存文件
+html_view_blank 超链接
+html_local_file 本地文件取相对路径
+to_markdown_tabs 文件list 转换为 md tab
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
+"""
+
+
+def files_filter_handler(file_list):
+    new_list = []
+    filter_ = [
+        "png",
+        "jpg",
+        "jpeg",
+        "bmp",
+        "svg",
+        "webp",
+        "ico",
+        "tif",
+        "tiff",
+        "raw",
+        "eps",
+    ]
+    for file in file_list:
+        file = str(file).replace("file=", "")
+        if os.path.exists(file):
+            if str(os.path.basename(file)).split(".")[-1] in filter_:
+                new_list.append(file)
+    return new_list
+
+
+def input_encode_handler(inputs, llm_kwargs):
+    if llm_kwargs["most_recent_uploaded"].get("path"):
+        image_paths = get_pictures_list(llm_kwargs["most_recent_uploaded"]["path"])
+    md_encode = []
+    for md_path in image_paths:
+        type_ = os.path.splitext(md_path)[1].replace(".", "")
+        type_ = "jpeg" if type_ == "jpg" else type_
+        md_encode.append({"data": encode_image(md_path), "type": type_})
+    return inputs, md_encode
+
+
+def file_manifest_filter_html(file_list, filter_: list = None, md_type=False):
+    new_list = []
+    if not filter_:
+        filter_ = [
+            "png",
+            "jpg",
+            "jpeg",
+            "bmp",
+            "svg",
+            "webp",
+            "ico",
+            "tif",
+            "tiff",
+            "raw",
+            "eps",
+        ]
+    for file in file_list:
+        if str(os.path.basename(file)).split(".")[-1] in filter_:
+            new_list.append(html_local_img(file, md=md_type))
+        elif os.path.exists(file):
+            new_list.append(link_mtime_to_md(file))
+        else:
+            new_list.append(file)
+    return new_list
+
+
+def link_mtime_to_md(file):
+    link_local = html_local_file(file)
+    link_name = os.path.basename(file)
+    a = f"[{link_name}]({link_local}?{os.path.getmtime(file)})"
+    return a
+
+
+def html_local_file(file):
+    base_path = os.path.dirname(__file__)  # 项目目录
+    if os.path.exists(str(file)):
+        file = f'file={file.replace(base_path, ".")}'
+    return file
+
+
+def html_local_img(__file, layout="left", max_width=None, max_height=None, md=True):
+    style = ""
+    if max_width is not None:
+        style += f"max-width: {max_width};"
+    if max_height is not None:
+        style += f"max-height: {max_height};"
+    __file = html_local_file(__file)
+    a = f'<div align="{layout}"><img src="{__file}" style="{style}"></div>'
+    if md:
+        a = f"![{__file}]({__file})"
+    return a
+
+
+def to_markdown_tabs(head: list, tabs: list, alignment=":---:", column=False):
+    """
+    Args:
+        head: 表头：[]
+        tabs: 表值：[[列1], [列2], [列3], [列4]]
+        alignment: :--- 左对齐， :---: 居中对齐， ---: 右对齐
+        column: True to keep data in columns, False to keep data in rows (default).
+    Returns:
+        A string representation of the markdown table.
+    """
+    if column:
+        transposed_tabs = list(map(list, zip(*tabs)))
+    else:
+        transposed_tabs = tabs
+    # Find the maximum length among the columns
+    max_len = max(len(column) for column in transposed_tabs)
+
+    tab_format = "| %s "
+    tabs_list = "".join([tab_format % i for i in head]) + "|\n"
+    tabs_list += "".join([tab_format % alignment for i in head]) + "|\n"
+
+    for i in range(max_len):
+        row_data = [tab[i] if i < len(tab) else "" for tab in transposed_tabs]
+        row_data = file_manifest_filter_html(row_data, filter_=None)
+        tabs_list += "".join([tab_format % i for i in row_data]) + "|\n"
+
+    return tabs_list
+
+
+class GoogleChatInit:
+    def __init__(self):
+        self.url_gemini = "https://generativelanguage.googleapis.com/v1beta/models/%m:streamGenerateContent?key=%k"
+
+    def generate_chat(self, inputs, llm_kwargs, history, system_prompt):
+        headers, payload = self.generate_message_payload(
+            inputs, llm_kwargs, history, system_prompt
+        )
+        response = requests.post(
+            url=self.url_gemini,
+            headers=headers,
+            data=json.dumps(payload),
+            stream=True,
+            proxies=proxies,
+            timeout=TIMEOUT_SECONDS,
+        )
+        return response.iter_lines()
+
+    def __conversation_user(self, user_input, llm_kwargs):
+        what_i_have_asked = {"role": "user", "parts": []}
+        if "vision" not in self.url_gemini:
+            input_ = user_input
+            encode_img = []
+        else:
+            input_, encode_img = input_encode_handler(user_input, llm_kwargs=llm_kwargs)
+        what_i_have_asked["parts"].append({"text": input_})
+        if encode_img:
+            for data in encode_img:
+                what_i_have_asked["parts"].append(
+                    {
+                        "inline_data": {
+                            "mime_type": f"image/{data['type']}",
+                            "data": data["data"],
+                        }
+                    }
+                )
+        return what_i_have_asked
+
+    def __conversation_history(self, history, llm_kwargs):
+        messages = []
+        conversation_cnt = len(history) // 2
+        if conversation_cnt:
+            for index in range(0, 2 * conversation_cnt, 2):
+                what_i_have_asked = self.__conversation_user(history[index], llm_kwargs)
+                what_gpt_answer = {
+                    "role": "model",
+                    "parts": [{"text": history[index + 1]}],
+                }
+                messages.append(what_i_have_asked)
+                messages.append(what_gpt_answer)
+        return messages
+
+    def generate_message_payload(
+        self, inputs, llm_kwargs, history, system_prompt
+    ) -> Tuple[Dict, Dict]:
+        messages = [
+            # {"role": "system", "parts": [{"text": system_prompt}]},  # gemini 不允许对话轮次为偶数，所以这个没有用，看后续支持吧。。。
+            # {"role": "user", "parts": [{"text": ""}]},
+            # {"role": "model", "parts": [{"text": ""}]}
+        ]
+        self.url_gemini = self.url_gemini.replace(
+            "%m", llm_kwargs["llm_model"]
+        ).replace("%k", get_conf("GEMINI_API_KEY"))
+        header = {"Content-Type": "application/json"}
+        if "vision" not in self.url_gemini:  # 不是vision 才处理history
+            messages.extend(
+                self.__conversation_history(history, llm_kwargs)
+            )  # 处理 history
+        messages.append(self.__conversation_user(inputs, llm_kwargs))  # 处理用户对话
+        payload = {
+            "contents": messages,
+            "generationConfig": {
+                # "maxOutputTokens": 800,
+                "stopSequences": str(llm_kwargs.get("stop", "")).split(" "),
+                "temperature": llm_kwargs.get("temperature", 1),
+                "topP": llm_kwargs.get("top_p", 0.8),
+                "topK": 10,
+            },
+        }
+        return header, payload
+
+
+if __name__ == "__main__":
+    google = GoogleChatInit()
+    # print(gootle.generate_message_payload('你好呀', {},  ['123123', '3123123'], ''))
+    # gootle.input_encode_handle('123123[123123](./123123), ![53425](./asfafa/fff.jpg)')
--- a/request_llms/com_qwenapi.py
+++ b/request_llms/com_qwenapi.py
@@ -0,0 +1,94 @@
+from http import HTTPStatus
+from toolbox import get_conf
+import threading
+import logging
+
+timeout_bot_msg = '[Local Message] Request timeout. Network error.'
+
+class QwenRequestInstance():
+    def __init__(self):
+        import dashscope
+        self.time_to_yield_event = threading.Event()
+        self.time_to_exit_event = threading.Event()
+        self.result_buf = ""
+
+        def validate_key():
+            DASHSCOPE_API_KEY = get_conf("DASHSCOPE_API_KEY")
+            if DASHSCOPE_API_KEY == '': return False
+            return True
+
+        if not validate_key():
+            raise RuntimeError('请配置 DASHSCOPE_API_KEY')
+        dashscope.api_key = get_conf("DASHSCOPE_API_KEY")
+
+
+    def generate(self, inputs, llm_kwargs, history, system_prompt):
+        # import _thread as thread
+        from dashscope import Generation
+        QWEN_MODEL = {
+            'qwen-turbo': Generation.Models.qwen_turbo,
+            'qwen-plus': Generation.Models.qwen_plus,
+            'qwen-max': Generation.Models.qwen_max,
+        }[llm_kwargs['llm_model']]
+        top_p = llm_kwargs.get('top_p', 0.8)
+        if top_p == 0: top_p += 1e-5
+        if top_p == 1: top_p -= 1e-5
+
+        self.result_buf = ""
+        responses = Generation.call(
+            model=QWEN_MODEL,
+            messages=generate_message_payload(inputs, llm_kwargs, history, system_prompt),
+            top_p=top_p,
+            temperature=llm_kwargs.get('temperature', 1.0),
+            result_format='message',
+            stream=True,
+            incremental_output=True
+        )
+
+        for response in responses:
+            if response.status_code == HTTPStatus.OK:
+                if response.output.choices[0].finish_reason == 'stop':
+                    yield self.result_buf
+                    break
+                elif response.output.choices[0].finish_reason == 'length':
+                    self.result_buf += "[Local Message] 生成长度过长，后续输出被截断"
+                    yield self.result_buf
+                    break
+                else:
+                    self.result_buf += response.output.choices[0].message.content
+                    yield self.result_buf
+            else:
+                self.result_buf += f"[Local Message] 请求错误：状态码：{response.status_code}，错误码:{response.code}，消息：{response.message}"
+                yield self.result_buf
+                break
+        logging.info(f'[raw_input] {inputs}')
+        logging.info(f'[response] {self.result_buf}')
+        return self.result_buf
+
+
+def generate_message_payload(inputs, llm_kwargs, history, system_prompt):
+    conversation_cnt = len(history) // 2
+    if system_prompt == '': system_prompt = 'Hello!'
+    messages = [{"role": "user", "content": system_prompt}, {"role": "assistant", "content": "Certainly!"}]
+    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
+                if what_gpt_answer["content"] == timeout_bot_msg:
+                    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)
+    return messages
--- a/request_llms/com_skylark2api.py
+++ b/request_llms/com_skylark2api.py
@@ -0,0 +1,95 @@
+from toolbox import get_conf
+import threading
+import logging
+import os
+
+timeout_bot_msg = '[Local Message] Request timeout. Network error.'
+#os.environ['VOLC_ACCESSKEY'] = ''
+#os.environ['VOLC_SECRETKEY'] = ''
+
+class YUNQUERequestInstance():
+    def __init__(self):
+
+        self.time_to_yield_event = threading.Event()
+        self.time_to_exit_event = threading.Event()
+
+        self.result_buf = ""
+
+    def generate(self, inputs, llm_kwargs, history, system_prompt):
+        # import _thread as thread
+        from volcengine.maas import MaasService, MaasException
+
+        maas = MaasService('maas-api.ml-platform-cn-beijing.volces.com', 'cn-beijing')
+
+        YUNQUE_SECRET_KEY, YUNQUE_ACCESS_KEY,YUNQUE_MODEL = get_conf("YUNQUE_SECRET_KEY", "YUNQUE_ACCESS_KEY","YUNQUE_MODEL")
+        maas.set_ak(YUNQUE_ACCESS_KEY) #填写 VOLC_ACCESSKEY
+        maas.set_sk(YUNQUE_SECRET_KEY) #填写 'VOLC_SECRETKEY'
+
+        self.result_buf = ""
+
+        req = {
+        "model": {
+            "name": YUNQUE_MODEL,
+            "version": "1.0", # use default version if not specified.
+        },
+        "parameters": {
+            "max_new_tokens": 4000,  # 输出文本的最大tokens限制
+            "min_new_tokens": 1,  # 输出文本的最小tokens限制
+            "temperature": llm_kwargs['temperature'],  # 用于控制生成文本的随机性和创造性，Temperature值越大随机性越大，取值范围0~1
+            "top_p": llm_kwargs['top_p'],  # 用于控制输出tokens的多样性，TopP值越大输出的tokens类型越丰富，取值范围0~1
+            "top_k": 0,  # 选择预测值最大的k个token进行采样，取值范围0-1000，0表示不生效
+            "max_prompt_tokens": 4000,  # 最大输入 token 数，如果给出的 prompt 的 token 长度超过此限制，取最后 max_prompt_tokens 个 token 输入模型。
+        },
+            "messages": self.generate_message_payload(inputs, llm_kwargs, history, system_prompt)
+        }
+
+        response = maas.stream_chat(req)
+
+        for resp in response:
+            self.result_buf += resp.choice.message.content
+            yield self.result_buf
+        '''
+        for event in response.events():
+            if event.event == "add":
+                self.result_buf += event.data
+                yield self.result_buf
+            elif event.event == "error" or event.event == "interrupted":
+                raise RuntimeError("Unknown error:" + event.data)
+            elif event.event == "finish":
+                yield self.result_buf
+                break
+            else:
+                raise RuntimeError("Unknown error:" + str(event))
+
+        logging.info(f'[raw_input] {inputs}')
+        logging.info(f'[response] {self.result_buf}')
+        '''
+        return self.result_buf
+
+    def generate_message_payload(inputs, llm_kwargs, history, system_prompt):
+        from volcengine.maas import ChatRole
+        conversation_cnt = len(history) // 2
+        messages = [{"role": ChatRole.USER, "content": system_prompt},
+                    {"role": ChatRole.ASSISTANT, "content": "Certainly!"}]
+        if conversation_cnt:
+            for index in range(0, 2 * conversation_cnt, 2):
+                what_i_have_asked = {}
+                what_i_have_asked["role"] = ChatRole.USER
+                what_i_have_asked["content"] = history[index]
+                what_gpt_answer = {}
+                what_gpt_answer["role"] = ChatRole.ASSISTANT
+                what_gpt_answer["content"] = history[index + 1]
+                if what_i_have_asked["content"] != "":
+                    if what_gpt_answer["content"] == "":
+                        continue
+                    if what_gpt_answer["content"] == timeout_bot_msg:
+                        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"] = ChatRole.USER
+        what_i_ask_now["content"] = inputs
+        messages.append(what_i_ask_now)
+        return messages
--- a/request_llms/com_sparkapi.py
+++ b/request_llms/com_sparkapi.py
@@ -72,12 +72,12 @@ class SparkRequestInstance():

        self.result_buf = ""

-    def generate(self, inputs, llm_kwargs, history, system_prompt):
+    def generate(self, inputs, llm_kwargs, history, system_prompt, use_image_api=False):
        llm_kwargs = llm_kwargs
        history = history
        system_prompt = system_prompt
        import _thread as thread
-        thread.start_new_thread(self.create_blocking_request, (inputs, llm_kwargs, history, system_prompt))
+        thread.start_new_thread(self.create_blocking_request, (inputs, llm_kwargs, history, system_prompt, use_image_api))
        while True:
            self.time_to_yield_event.wait(timeout=1)
            if self.time_to_yield_event.is_set():
@@ -86,7 +86,7 @@ class SparkRequestInstance():
                return self.result_buf


-    def create_blocking_request(self, inputs, llm_kwargs, history, system_prompt):
+    def create_blocking_request(self, inputs, llm_kwargs, history, system_prompt, use_image_api):
        if llm_kwargs['llm_model'] == 'sparkv2':
            gpt_url = self.gpt_url_v2
        elif llm_kwargs['llm_model'] == 'sparkv3':
@@ -94,9 +94,11 @@ class SparkRequestInstance():
        else:
            gpt_url = self.gpt_url
        file_manifest = []
-        if llm_kwargs.get('most_recent_uploaded'):
+        if use_image_api and llm_kwargs.get('most_recent_uploaded'):
            if llm_kwargs['most_recent_uploaded'].get('path'):
                file_manifest = get_pictures_list(llm_kwargs['most_recent_uploaded']['path'])
+                if len(file_manifest) > 0:
+                    print('正在使用讯飞图片理解API')
                    gpt_url = self.gpt_url_img
        wsParam = Ws_Param(self.appid, self.api_key, self.api_secret, gpt_url)
        websocket.enableTrace(False)
--- a/request_llms/com_zhipuapi.py
+++ b/request_llms/com_zhipuapi.py
@@ -26,6 +26,8 @@ class ZhipuRequestInstance():
        )
        for event in response.events():
            if event.event == "add":
+                # if self.result_buf == "" and event.data.startswith(" "):
+                #     event.data = event.data.lstrip(" ") # 每次智谱为啥都要带个空格开头呢？
                self.result_buf += event.data
                yield self.result_buf
            elif event.event == "error" or event.event == "interrupted":
@@ -35,7 +37,8 @@ class ZhipuRequestInstance():
                break
            else:
                raise RuntimeError("Unknown error:" + str(event))
-            
+        if self.result_buf == "":
+            yield "智谱没有返回任何数据, 请检查ZHIPUAI_API_KEY和ZHIPUAI_MODEL是否填写正确."
        logging.info(f'[raw_input] {inputs}')
        logging.info(f'[response] {self.result_buf}')
        return self.result_buf
--- a/request_llms/edge_gpt_free.py
+++ b/request_llms/edge_gpt_free.py
@@ -1,8 +1,8 @@
 """
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 第一部分：来自EdgeGPT.py
 https://github.com/acheong08/EdgeGPT
-========================================================================
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
 """
 """
 Main.py
@@ -452,9 +452,11 @@ class _ChatHub:
            ws_cookies = []
            for cookie in self.cookies:
                ws_cookies.append(f"{cookie['name']}={cookie['value']}")
-            req_header.update({
-                'Cookie': ';'.join(ws_cookies),
-            })
+            req_header.update(
+                {
+                    "Cookie": ";".join(ws_cookies),
+                }
+            )

        timeout = aiohttp.ClientTimeout(total=30)
        self.session = aiohttp.ClientSession(timeout=timeout)
--- a/request_llms/local_llm_class.py
+++ b/request_llms/local_llm_class.py
@@ -183,11 +183,11 @@ class LocalLLMHandle(Process):
    def stream_chat(self, **kwargs):
        # ⭐run in main process
        if self.get_state() == "`准备就绪`":
-            yield "`正在等待线程锁，排队中请稍后 ...`"
+            yield "`正在等待线程锁，排队中请稍候 ...`"

        with self.threadLock:
            if self.parent.poll():
-                yield "`排队中请稍后 ...`"
+                yield "`排队中请稍候 ...`"
                self.clear_pending_messages()
            self.parent.send(kwargs)
            std_out = ""
--- a/request_llms/requirements_chatglm_onnx.txt
+++ b/request_llms/requirements_chatglm_onnx.txt
@@ -6,5 +6,3 @@ sentencepiece
 numpy
 onnxruntime
 sentencepiece
-streamlit
-streamlit-chat
--- a/request_llms/requirements_moss.txt
+++ b/request_llms/requirements_moss.txt
@@ -5,5 +5,3 @@ accelerate
 matplotlib
 huggingface_hub
 triton
-streamlit
-
--- a/request_llms/requirements_qwen.txt
+++ b/request_llms/requirements_qwen.txt
@@ -1,4 +1 @@
-modelscope
-transformers_stream_generator
-auto-gptq
-optimum
+dashscope
--- a/request_llms/requirements_qwen_local.txt
+++ b/request_llms/requirements_qwen_local.txt
@@ -0,0 +1,5 @@
+modelscope
+transformers_stream_generator
+auto-gptq
+optimum
+urllib3<2
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,11 +1,14 @@
-./docs/gradio-3.32.6-py3-none-any.whl
+https://fastly.jsdelivr.net/gh/binary-husky/gradio-fix@gpt-academic/release/gradio-3.32.7-py3-none-any.whl
 pypdf2==2.12.1
+zhipuai<2
 tiktoken>=0.3.3
 requests[socks]
 pydantic==1.10.11
+protobuf==3.18
 transformers>=4.27.1
 scipdf_parser>=0.52
 python-markdown-math
+pymdown-extensions
 websocket-client
 beautifulsoup4
 prompt_toolkit
--- a/shared_utils/advanced_markdown_format.py
+++ b/shared_utils/advanced_markdown_format.py
@@ -0,0 +1,287 @@
+import markdown
+import re
+import os
+import math
+from textwrap import dedent
+from functools import lru_cache
+from pymdownx.superfences import fence_div_format, fence_code_format
+from latex2mathml.converter import convert as tex2mathml
+from shared_utils.config_loader import get_conf as get_conf
+
+pj = os.path.join
+default_user_name = 'default_user'
+
+markdown_extension_configs = {
+    'mdx_math': {
+        'enable_dollar_delimiter': True,
+        'use_gitlab_delimiters': False,
+    },
+}
+
+code_highlight_configs = {
+    "pymdownx.superfences": {
+        'css_class': 'codehilite',
+        "custom_fences": [
+            {
+                'name': 'mermaid',
+                'class': 'mermaid',
+                'format': fence_code_format
+            }
+        ]
+    },
+    "pymdownx.highlight": {
+        'css_class': 'codehilite',
+        'guess_lang': True,
+        # 'auto_title': True,
+        # 'linenums': True
+    }
+}
+
+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
+    elif '</div>' in text:
+        # careful input
+        return text
+    else:
+        # whatever input
+        lines = text.split("\n")
+        for i, line in enumerate(lines):
+            lines[i] = lines[i].replace(" ", "&nbsp;")
+        text = "</br>".join(lines)
+        return pre + text + suf
+
+
+def tex2mathml_catch_exception(content, *args, **kwargs):
+    try:
+        content = tex2mathml(content, *args, **kwargs)
+    except:
+        content = content
+    return content
+
+
+def replace_math_no_render(match):
+    content = match.group(1)
+    if 'mode=display' in match.group(0):
+        content = content.replace('\n', '</br>')
+        return f"<font color=\"#00FF00\">$$</font><font color=\"#FF00FF\">{content}</font><font color=\"#00FF00\">$$</font>"
+    else:
+        return f"<font color=\"#00FF00\">$</font><font color=\"#FF00FF\">{content}</font><font color=\"#00FF00\">$</font>"
+
+
+def replace_math_render(match):
+    content = match.group(1)
+    if 'mode=display' in match.group(0):
+        if '\\begin{aligned}' in content:
+            content = content.replace('\\begin{aligned}', '\\begin{array}')
+            content = content.replace('\\end{aligned}', '\\end{array}')
+            content = content.replace('&', ' ')
+        content = tex2mathml_catch_exception(content, display="block")
+        return content
+    else:
+        return tex2mathml_catch_exception(content)
+
+
+def markdown_bug_hunt(content):
+    """
+    解决一个mdx_math的bug（单$包裹begin命令时多余<script>）
+    """
+    content = content.replace('<script type="math/tex">\n<script type="math/tex; mode=display">',
+                                '<script type="math/tex; mode=display">')
+    content = content.replace('</script>\n</script>', '</script>')
+    return content
+
+
+def is_equation(txt):
+    """
+    判定是否为公式 | 测试1 写出洛伦兹定律，使用tex格式公式 测试2 给出柯西不等式，使用latex格式 测试3 写出麦克斯韦方程组
+    """
+    if '```' in txt and '```reference' not in txt: return False
+    if '$' not in txt and '\\[' not in txt: return False
+    mathpatterns = {
+        r'(?<!\\|\$)(\$)([^\$]+)(\$)': {'allow_multi_lines': False},                       #  $...$
+        r'(?<!\\)(\$\$)([^\$]+)(\$\$)': {'allow_multi_lines': True},                       # $$...$$
+        r'(?<!\\)(\\\[)(.+?)(\\\])': {'allow_multi_lines': False},                         # \[...\]
+        # r'(?<!\\)(\\\()(.+?)(\\\))': {'allow_multi_lines': False},                       # \(...\)
+        # r'(?<!\\)(\\begin{([a-z]+?\*?)})(.+?)(\\end{\2})': {'allow_multi_lines': True},  # \begin...\end
+        # r'(?<!\\)(\$`)([^`]+)(`\$)': {'allow_multi_lines': False},                       # $`...`$
+    }
+    matches = []
+    for pattern, property in mathpatterns.items():
+        flags = re.ASCII | re.DOTALL if property['allow_multi_lines'] else re.ASCII
+        matches.extend(re.findall(pattern, txt, flags))
+    if len(matches) == 0: return False
+    contain_any_eq = False
+    illegal_pattern = re.compile(r'[^\x00-\x7F]|echo')
+    for match in matches:
+        if len(match) != 3: return False
+        eq_canidate = match[1]
+        if illegal_pattern.search(eq_canidate):
+            return False
+        else:
+            contain_any_eq = True
+    return contain_any_eq
+
+
+def fix_markdown_indent(txt):
+    # fix markdown indent
+    if (' - ' not in txt) or ('. ' not in txt):
+        # do not need to fix, fast escape
+        return txt
+    # walk through the lines and fix non-standard indentation
+    lines = txt.split("\n")
+    pattern = re.compile(r'^\s+-')
+    activated = False
+    for i, line in enumerate(lines):
+        if line.startswith('- ') or line.startswith('1. '):
+            activated = True
+        if activated and pattern.match(line):
+            stripped_string = line.lstrip()
+            num_spaces = len(line) - len(stripped_string)
+            if (num_spaces % 4) == 3:
+                num_spaces_should_be = math.ceil(num_spaces / 4) * 4
+                lines[i] = ' ' * num_spaces_should_be + stripped_string
+    return '\n'.join(lines)
+
+
+FENCED_BLOCK_RE = re.compile(
+    dedent(r'''
+        (?P<fence>^[ \t]*(?:~{3,}|`{3,}))[ ]*                      # opening fence
+        ((\{(?P<attrs>[^\}\n]*)\})|                              # (optional {attrs} or
+        (\.?(?P<lang>[\w#.+-]*)[ ]*)?                            # optional (.)lang
+        (hl_lines=(?P<quot>"|')(?P<hl_lines>.*?)(?P=quot)[ ]*)?) # optional hl_lines)
+        \n                                                       # newline (end of opening fence)
+        (?P<code>.*?)(?<=\n)                                     # the code block
+        (?P=fence)[ ]*$                                          # closing fence
+    '''),
+    re.MULTILINE | re.DOTALL | re.VERBOSE
+)
+
+
+def get_line_range(re_match_obj, txt):
+    start_pos, end_pos = re_match_obj.regs[0]
+    num_newlines_before = txt[:start_pos+1].count('\n')
+    line_start = num_newlines_before
+    line_end = num_newlines_before + txt[start_pos:end_pos].count('\n')+1
+    return line_start, line_end
+
+
+def fix_code_segment_indent(txt):
+    lines = []
+    change_any = False
+    txt_tmp = txt
+    while True:
+        re_match_obj = FENCED_BLOCK_RE.search(txt_tmp)
+        if not re_match_obj: break
+        if len(lines) == 0: lines = txt.split("\n")
+        
+        # 清空 txt_tmp 对应的位置方便下次搜索
+        start_pos, end_pos = re_match_obj.regs[0]
+        txt_tmp = txt_tmp[:start_pos] + ' '*(end_pos-start_pos) + txt_tmp[end_pos:]
+        line_start, line_end = get_line_range(re_match_obj, txt)
+        
+        # 获取公共缩进
+        shared_indent_cnt = 1e5
+        for i in range(line_start, line_end):
+            stripped_string = lines[i].lstrip()
+            num_spaces = len(lines[i]) - len(stripped_string)
+            if num_spaces < shared_indent_cnt:
+                shared_indent_cnt = num_spaces
+
+        # 修复缩进
+        if (shared_indent_cnt < 1e5) and (shared_indent_cnt % 4) == 3:
+            num_spaces_should_be = math.ceil(shared_indent_cnt / 4) * 4
+            for i in range(line_start, line_end):
+                add_n = num_spaces_should_be - shared_indent_cnt
+                lines[i] = ' ' * add_n + lines[i]
+            if not change_any: # 遇到第一个
+                change_any = True
+
+    if change_any:
+        return '\n'.join(lines)
+    else:
+        return txt
+    
+    
+@lru_cache(maxsize=128) # 使用 lru缓存 加快转换速度
+def markdown_convertion(txt):
+    """
+    将Markdown格式的文本转换为HTML格式。如果包含数学公式，则先将公式转换为HTML格式。
+    """
+    pre = '<div class="markdown-body">'
+    suf = '</div>'
+    if txt.startswith(pre) and txt.endswith(suf):
+        # print('警告，输入了已经经过转化的字符串，二次转化可能出问题')
+        return txt # 已经被转化过，不需要再次转化
+
+    find_equation_pattern = r'<script type="math/tex(?:.*?)>(.*?)</script>'
+
+    txt = fix_markdown_indent(txt)
+    # txt = fix_code_segment_indent(txt)
+    if is_equation(txt):  # 有$标识的公式符号，且没有代码段```的标识
+        # convert everything to html format
+        split = markdown.markdown(text='---')
+        convert_stage_1 = markdown.markdown(text=txt, extensions=['sane_lists', 'tables', 'mdx_math', 'pymdownx.superfences', 'pymdownx.highlight'],
+                                            extension_configs={**markdown_extension_configs, **code_highlight_configs})
+        convert_stage_1 = markdown_bug_hunt(convert_stage_1)
+        # 1. convert to easy-to-copy tex (do not render math)
+        convert_stage_2_1, n = re.subn(find_equation_pattern, replace_math_no_render, convert_stage_1, flags=re.DOTALL)
+        # 2. convert to rendered equation
+        convert_stage_2_2, n = re.subn(find_equation_pattern, replace_math_render, convert_stage_1, flags=re.DOTALL)
+        # cat them together
+        return pre + convert_stage_2_1 + f'{split}' + convert_stage_2_2 + suf
+    else:
+        return pre + markdown.markdown(txt, extensions=['sane_lists', 'tables', 'pymdownx.superfences', 'pymdownx.highlight'], extension_configs=code_highlight_configs) + suf
+
+
+def close_up_code_segment_during_stream(gpt_reply):
+    """
+    在gpt输出代码的中途（输出了前面的```，但还没输出完后面的```），补上后面的```
+
+    Args:
+        gpt_reply (str): GPT模型返回的回复字符串。
+
+    Returns:
+        str: 返回一个新的字符串，将输出代码片段的“后面的```”补上。
+
+    """
+    if '```' not in gpt_reply:
+        return gpt_reply
+    if gpt_reply.endswith('```'):
+        return gpt_reply
+
+    # 排除了以上两个情况，我们
+    segments = gpt_reply.split('```')
+    n_mark = len(segments) - 1
+    if n_mark % 2 == 1:
+        return gpt_reply + '\n```' # 输出代码片段中！
+    else:
+        return gpt_reply
+
+
+def format_io(self, y):
+    """
+    将输入和输出解析为HTML格式。将y中最后一项的输入部分段落化，并将输出部分的Markdown和数学公式转换为HTML格式。
+    """
+    if y is None or y == []:
+        return []
+    i_ask, gpt_reply = y[-1]
+    # 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=['pymdownx.superfences', 'tables', 'pymdownx.highlight'], extension_configs=code_highlight_configs),
+        None if gpt_reply is None else markdown_convertion(gpt_reply)
+    )
+    return y
--- a/shared_utils/config_loader.py
+++ b/shared_utils/config_loader.py
@@ -0,0 +1,131 @@
+import importlib
+import time
+import os
+from functools import lru_cache
+from colorful import print亮红, print亮绿, print亮蓝
+
+pj = os.path.join
+default_user_name = 'default_user'
+
+def read_env_variable(arg, default_value):
+    """
+    环境变量可以是 `GPT_ACADEMIC_CONFIG`(优先)，也可以直接是`CONFIG`
+    例如在windows cmd中，既可以写：
+        set USE_PROXY=True
+        set API_KEY=sk-j7caBpkRoxxxxxxxxxxxxxxxxxxxxxxxxxxxx
+        set proxies={"http":"http://127.0.0.1:10085", "https":"http://127.0.0.1:10085",}
+        set AVAIL_LLM_MODELS=["gpt-3.5-turbo", "chatglm"]
+        set AUTHENTICATION=[("username", "password"), ("username2", "password2")]
+    也可以写：
+        set GPT_ACADEMIC_USE_PROXY=True
+        set GPT_ACADEMIC_API_KEY=sk-j7caBpkRoxxxxxxxxxxxxxxxxxxxxxxxxxxxx
+        set GPT_ACADEMIC_proxies={"http":"http://127.0.0.1:10085", "https":"http://127.0.0.1:10085",}
+        set GPT_ACADEMIC_AVAIL_LLM_MODELS=["gpt-3.5-turbo", "chatglm"]
+        set GPT_ACADEMIC_AUTHENTICATION=[("username", "password"), ("username2", "password2")]
+    """
+    arg_with_prefix = "GPT_ACADEMIC_" + arg
+    if arg_with_prefix in os.environ:
+        env_arg = os.environ[arg_with_prefix]
+    elif arg in os.environ:
+        env_arg = os.environ[arg]
+    else:
+        raise KeyError
+    print(f"[ENV_VAR] 尝试加载{arg}，默认值：{default_value} --> 修正值：{env_arg}")
+    try:
+        if isinstance(default_value, bool):
+            env_arg = env_arg.strip()
+            if env_arg == 'True': r = True
+            elif env_arg == 'False': r = False
+            else: print('Enter True or False, but have:', env_arg); r = default_value
+        elif isinstance(default_value, int):
+            r = int(env_arg)
+        elif isinstance(default_value, float):
+            r = float(env_arg)
+        elif isinstance(default_value, str):
+            r = env_arg.strip()
+        elif isinstance(default_value, dict):
+            r = eval(env_arg)
+        elif isinstance(default_value, list):
+            r = eval(env_arg)
+        elif default_value is None:
+            assert arg == "proxies"
+            r = eval(env_arg)
+        else:
+            print亮红(f"[ENV_VAR] 环境变量{arg}不支持通过环境变量设置! ")
+            raise KeyError
+    except:
+        print亮红(f"[ENV_VAR] 环境变量{arg}加载失败! ")
+        raise KeyError(f"[ENV_VAR] 环境变量{arg}加载失败! ")
+
+    print亮绿(f"[ENV_VAR] 成功读取环境变量{arg}")
+    return r
+
+
+@lru_cache(maxsize=128)
+def read_single_conf_with_lru_cache(arg):
+    from shared_utils.key_pattern_manager import is_any_api_key
+    try:
+        # 优先级1. 获取环境变量作为配置
+        default_ref = getattr(importlib.import_module('config'), arg) # 读取默认值作为数据类型转换的参考
+        r = read_env_variable(arg, default_ref)
+    except:
+        try:
+            # 优先级2. 获取config_private中的配置
+            r = getattr(importlib.import_module('config_private'), arg)
+        except:
+            # 优先级3. 获取config中的配置
+            r = getattr(importlib.import_module('config'), arg)
+
+    # 在读取API_KEY时，检查一下是不是忘了改config
+    if arg == 'API_URL_REDIRECT':
+        oai_rd = r.get("https://api.openai.com/v1/chat/completions", None) # API_URL_REDIRECT填写格式是错误的，请阅读`https://github.com/binary-husky/gpt_academic/wiki/项目配置说明`
+        if oai_rd and not oai_rd.endswith('/completions'):
+            print亮红("\n\n[API_URL_REDIRECT] API_URL_REDIRECT填错了。请阅读`https://github.com/binary-husky/gpt_academic/wiki/项目配置说明`。如果您确信自己没填错，无视此消息即可。")
+            time.sleep(5)
+    if arg == 'API_KEY':
+        print亮蓝(f"[API_KEY] 本项目现已支持OpenAI和Azure的api-key。也支持同时填写多个api-key，如API_KEY=\"openai-key1,openai-key2,azure-key3\"")
+        print亮蓝(f"[API_KEY] 您既可以在config.py中修改api-key(s)，也可以在问题输入区输入临时的api-key(s)，然后回车键提交后即可生效。")
+        if is_any_api_key(r):
+            print亮绿(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功")
+        else:
+            print亮红("[API_KEY] 您的 API_KEY 不满足任何一种已知的密钥格式，请在config文件中修改API密钥之后再运行。")
+    if arg == 'proxies':
+        if not read_single_conf_with_lru_cache('USE_PROXY'): r = None # 检查USE_PROXY，防止proxies单独起作用
+        if r is None:
+            print亮红('[PROXY] 网络代理状态：未配置。无代理状态下很可能无法访问OpenAI家族的模型。建议：检查USE_PROXY选项是否修改。')
+        else:
+            print亮绿('[PROXY] 网络代理状态：已配置。配置信息如下：', r)
+            assert isinstance(r, dict), 'proxies格式错误，请注意proxies选项的格式，不要遗漏括号。'
+    return r
+
+
+@lru_cache(maxsize=128)
+def get_conf(*args):
+    """
+    本项目的所有配置都集中在config.py中。 修改配置有三种方法，您只需要选择其中一种即可：
+        - 直接修改config.py
+        - 创建并修改config_private.py
+        - 修改环境变量（修改docker-compose.yml等价于修改容器内部的环境变量）
+
+    注意：如果您使用docker-compose部署，请修改docker-compose（等价于修改容器内部的环境变量）
+    """
+    res = []
+    for arg in args:
+        r = read_single_conf_with_lru_cache(arg)
+        res.append(r)
+    if len(res) == 1: return res[0]
+    return res
+
+
+def set_conf(key, value):
+    from toolbox import read_single_conf_with_lru_cache
+    read_single_conf_with_lru_cache.cache_clear()
+    get_conf.cache_clear()
+    os.environ[key] = str(value)
+    altered = get_conf(key)
+    return altered
+
+
+def set_multi_conf(dic):
+    for k, v in dic.items(): set_conf(k, v)
+    return
--- a/shared_utils/connect_void_terminal.py
+++ b/shared_utils/connect_void_terminal.py
@@ -0,0 +1,91 @@
+import os
+
+"""
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
+接驳void-terminal:
+    - set_conf:                     在运行过程中动态地修改配置
+    - set_multi_conf:               在运行过程中动态地修改多个配置
+    - get_plugin_handle:            获取插件的句柄
+    - get_plugin_default_kwargs:    获取插件的默认参数
+    - get_chat_handle:              获取简单聊天的句柄
+    - get_chat_default_kwargs:      获取简单聊天的默认参数
+=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
+"""
+
+
+def get_plugin_handle(plugin_name):
+    """
+    e.g. plugin_name = 'crazy_functions.批量Markdown翻译->Markdown翻译指定语言'
+    """
+    import importlib
+
+    assert (
+        "->" in plugin_name
+    ), "Example of plugin_name: crazy_functions.批量Markdown翻译->Markdown翻译指定语言"
+    module, fn_name = plugin_name.split("->")
+    f_hot_reload = getattr(importlib.import_module(module, fn_name), fn_name)
+    return f_hot_reload
+
+
+def get_chat_handle():
+    """
+    Get chat function
+    """
+    from request_llms.bridge_all import predict_no_ui_long_connection
+
+    return predict_no_ui_long_connection
+
+
+def get_plugin_default_kwargs():
+    """
+    Get Plugin Default Arguments
+    """
+    from toolbox import ChatBotWithCookies, load_chat_cookies
+
+    cookies = load_chat_cookies()
+    llm_kwargs = {
+        "api_key": cookies["api_key"],
+        "llm_model": cookies["llm_model"],
+        "top_p": 1.0,
+        "max_length": None,
+        "temperature": 1.0,
+    }
+    chatbot = ChatBotWithCookies(llm_kwargs)
+
+    # txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port
+    DEFAULT_FN_GROUPS_kwargs = {
+        "main_input": "./README.md",
+        "llm_kwargs": llm_kwargs,
+        "plugin_kwargs": {},
+        "chatbot_with_cookie": chatbot,
+        "history": [],
+        "system_prompt": "You are a good AI.",
+        "web_port": None,
+    }
+    return DEFAULT_FN_GROUPS_kwargs
+
+
+def get_chat_default_kwargs():
+    """
+    Get Chat Default Arguments
+    """
+    from toolbox import load_chat_cookies
+
+    cookies = load_chat_cookies()
+    llm_kwargs = {
+        "api_key": cookies["api_key"],
+        "llm_model": cookies["llm_model"],
+        "top_p": 1.0,
+        "max_length": None,
+        "temperature": 1.0,
+    }
+    default_chat_kwargs = {
+        "inputs": "Hello there, are you ready?",
+        "llm_kwargs": llm_kwargs,
+        "history": [],
+        "sys_prompt": "You are AI assistant",
+        "observe_window": None,
+        "console_slience": False,
+    }
+
+    return default_chat_kwargs
--- a/shared_utils/key_pattern_manager.py
+++ b/shared_utils/key_pattern_manager.py
@@ -0,0 +1,81 @@
+import re
+import os
+from functools import wraps, lru_cache
+from shared_utils.advanced_markdown_format import format_io
+from shared_utils.config_loader import get_conf as get_conf
+
+
+pj = os.path.join
+default_user_name = 'default_user'
+
+
+def is_openai_api_key(key):
+    CUSTOM_API_KEY_PATTERN = get_conf('CUSTOM_API_KEY_PATTERN')
+    if len(CUSTOM_API_KEY_PATTERN) != 0:
+        API_MATCH_ORIGINAL = re.match(CUSTOM_API_KEY_PATTERN, key)
+    else:
+        API_MATCH_ORIGINAL = re.match(r"sk-[a-zA-Z0-9]{48}$", key)
+    return bool(API_MATCH_ORIGINAL)
+
+
+def is_azure_api_key(key):
+    API_MATCH_AZURE = re.match(r"[a-zA-Z0-9]{32}$", key)
+    return bool(API_MATCH_AZURE)
+
+
+def is_api2d_key(key):
+    API_MATCH_API2D = re.match(r"fk[a-zA-Z0-9]{6}-[a-zA-Z0-9]{32}$", key)
+    return bool(API_MATCH_API2D)
+
+
+def is_any_api_key(key):
+    if ',' in key:
+        keys = key.split(',')
+        for k in keys:
+            if is_any_api_key(k): return True
+        return False
+    else:
+        return is_openai_api_key(key) or is_api2d_key(key) or is_azure_api_key(key)
+
+
+def what_keys(keys):
+    avail_key_list = {'OpenAI Key': 0, "Azure Key": 0, "API2D Key": 0}
+    key_list = keys.split(',')
+
+    for k in key_list:
+        if is_openai_api_key(k):
+            avail_key_list['OpenAI Key'] += 1
+
+    for k in key_list:
+        if is_api2d_key(k):
+            avail_key_list['API2D Key'] += 1
+
+    for k in key_list:
+        if is_azure_api_key(k):
+            avail_key_list['Azure Key'] += 1
+
+    return f"检测到： OpenAI Key {avail_key_list['OpenAI Key']} 个, Azure Key {avail_key_list['Azure Key']} 个, API2D Key {avail_key_list['API2D Key']} 个"
+
+
+def select_api_key(keys, llm_model):
+    import random
+    avail_key_list = []
+    key_list = keys.split(',')
+
+    if llm_model.startswith('gpt-'):
+        for k in key_list:
+            if is_openai_api_key(k): avail_key_list.append(k)
+
+    if llm_model.startswith('api2d-'):
+        for k in key_list:
+            if is_api2d_key(k): avail_key_list.append(k)
+
+    if llm_model.startswith('azure-'):
+        for k in key_list:
+            if is_azure_api_key(k): avail_key_list.append(k)
+
+    if len(avail_key_list) == 0:
+        raise RuntimeError(f"您提供的api-key不满足要求，不包含任何可用于{llm_model}的api-key。您可能选择了错误的模型或请求源（右下角更换模型菜单中可切换openai,azure,claude,api2d等请求源）。")
+
+    api_key = random.choice(avail_key_list) # 随机负载均衡
+    return api_key
--- a/tests/test_llms.py
+++ b/tests/test_llms.py
@@ -3,11 +3,13 @@
 # """
 def validate_path():
    import os, sys
-    dir_name = os.path.dirname(__file__)
-    root_dir_assume = os.path.abspath(os.path.dirname(__file__) +  '/..')
+
+    os.path.dirname(__file__)
+    root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..")
    os.chdir(root_dir_assume)
    sys.path.append(root_dir_assume)

+
 validate_path()  # validate path so you can run from base directory
 if __name__ == "__main__":
    # from request_llms.bridge_newbingfree import predict_no_ui_long_connection
@@ -18,19 +20,19 @@ if __name__ == "__main__":
    # from request_llms.bridge_internlm import predict_no_ui_long_connection
    # from request_llms.bridge_deepseekcoder import predict_no_ui_long_connection
    # from request_llms.bridge_qwen_7B import predict_no_ui_long_connection
-    from request_llms.bridge_qwen import predict_no_ui_long_connection
+    from request_llms.bridge_qwen_local import predict_no_ui_long_connection
+
    # from request_llms.bridge_spark import predict_no_ui_long_connection
    # from request_llms.bridge_zhipu import predict_no_ui_long_connection
    # from request_llms.bridge_chatglm3 import predict_no_ui_long_connection

    llm_kwargs = {
-        'max_length': 4096,
-        'top_p': 1,
-        'temperature': 1,
+        "max_length": 4096,
+        "top_p": 1,
+        "temperature": 1,
    }

-    result = predict_no_ui_long_connection( inputs="请问什么是质子？", 
-                                            llm_kwargs=llm_kwargs,
-                                            history=["你好", "我好！"],
-                                            sys_prompt="")
-    print('final result:', result)
+    result = predict_no_ui_long_connection(
+        inputs="请问什么是质子？", llm_kwargs=llm_kwargs, history=["你好", "我好！"], sys_prompt=""
+    )
+    print("final result:", result)
--- a/tests/test_markdown.py
+++ b/tests/test_markdown.py
@@ -1,44 +1,53 @@
 md = """
-作为您的写作和编程助手，我可以为您提供以下服务：
+You can use the following Python script to rename files matching the pattern '* - 副本.tex' to '* - wushiguang.tex' in a directory:

-1. 写作：
-    - 帮助您撰写文章、报告、散文、故事等。
-    - 提供写作建议和技巧。
-    - 协助您进行文案策划和内容创作。
+```python
+import os

-2. 编程：
-    - 帮助您解决编程问题，提供编程思路和建议。
-    - 协助您编写代码，包括但不限于 Python、Java、C++ 等。
-    - 为您解释复杂的技术概念，让您更容易理解。
+# Directory containing the files
+directory = 'Tex/'

-3. 项目支持：
-    - 协助您规划项目进度和任务分配。
-    - 提供项目管理和协作建议。
-    - 在项目实施过程中提供支持，确保项目顺利进行。
+for filename in os.listdir(directory):
+    if filename.endswith(' - 副本.tex'):
+        new_filename = filename.replace(' - 副本.tex', ' - wushiguang.tex')
+        os.rename(os.path.join(directory, filename), os.path.join(directory, new_filename))
+```

-4. 学习辅导：
-    - 帮助您巩固编程基础，提高编程能力。
-    - 提供计算机科学、数据科学、人工智能等相关领域的学习资源和建议。
-    - 解答您在学习过程中遇到的问题，让您更好地掌握知识。
-
-5. 行业动态和趋势分析：
-    - 为您提供业界最新的新闻和技术趋势。
-    - 分析行业动态，帮助您了解市场发展和竞争态势。
-    - 为您制定技术战略提供参考和建议。
-
-请随时告诉我您的需求，我会尽力提供帮助。如果您有任何问题或需要解答的议题，请随时提问。
+Replace 'Tex/' with the actual directory path where your files are located before running the script.
 """

+
+md = """
+Following code including wrapper
+
+```mermaid
+graph TD
+    A[Enter Chart Definition] --> B(Preview)
+    B --> C{decide}
+    C --> D[Keep]
+    C --> E[Edit Definition]
+    E --> B
+    D --> F[Save Image and Code]
+    F --> B
+```
+
+"""
 def validate_path():
    import os, sys
-    dir_name = os.path.dirname(__file__)
-    root_dir_assume = os.path.abspath(os.path.dirname(__file__) +  '/..')
+
+    os.path.dirname(__file__)
+    root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..")
    os.chdir(root_dir_assume)
    sys.path.append(root_dir_assume)
+
+
 validate_path()  # validate path so you can run from base directory
 from toolbox import markdown_convertion

 html = markdown_convertion(md)
-print(html)
-with open('test.html', 'w', encoding='utf-8') as f:
+# print(html)
+with open("test.html", "w", encoding="utf-8") as f:
    f.write(html)
+
+
+# TODO: 列出10个经典名著
--- a/tests/test_plugins.py
+++ b/tests/test_plugins.py
@@ -4,16 +4,28 @@


 import os, sys
-def validate_path(): dir_name = os.path.dirname(__file__); root_dir_assume = os.path.abspath(dir_name +  '/..'); os.chdir(root_dir_assume); sys.path.append(root_dir_assume)
+
+
+def validate_path():
+    dir_name = os.path.dirname(__file__)
+    root_dir_assume = os.path.abspath(dir_name + "/..")
+    os.chdir(root_dir_assume)
+    sys.path.append(root_dir_assume)
+
+
 validate_path()  # 返回项目根路径

 if __name__ == "__main__":
    from tests.test_utils import plugin_test
+
    # 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输出PDF结果->Latex翻译中文并重新编译PDF', main_input="2307.07522")

-    plugin_test(plugin='crazy_functions.Latex输出PDF结果->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.Latex输出PDF结果->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')

@@ -61,4 +73,3 @@ if __name__ == "__main__":

    # 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)
-
--- a/tests/test_utils.py
+++ b/tests/test_utils.py
@@ -9,45 +9,52 @@ from functools import wraps
 import sys
 import os

+
 def chat_to_markdown_str(chat):
    result = ""
    for i, cc in enumerate(chat):
-        result += f'\n\n{cc[0]}\n\n{cc[1]}'
+        result += f"\n\n{cc[0]}\n\n{cc[1]}"
        if i != len(chat) - 1:
-            result += '\n\n---'
+            result += "\n\n---"
    return result

+
 def silence_stdout(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        _original_stdout = sys.stdout
-        sys.stdout = open(os.devnull, 'w')
-        sys.stdout.reconfigure(encoding='utf-8')
+        sys.stdout = open(os.devnull, "w")
+        sys.stdout.reconfigure(encoding="utf-8")
        for q in func(*args, **kwargs):
            sys.stdout = _original_stdout
            yield q
-            sys.stdout = open(os.devnull, 'w')
-            sys.stdout.reconfigure(encoding='utf-8')
+            sys.stdout = open(os.devnull, "w")
+            sys.stdout.reconfigure(encoding="utf-8")
        sys.stdout.close()
        sys.stdout = _original_stdout
+
    return wrapper

+
 def silence_stdout_fn(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        _original_stdout = sys.stdout
-        sys.stdout = open(os.devnull, 'w')
-        sys.stdout.reconfigure(encoding='utf-8')
+        sys.stdout = open(os.devnull, "w")
+        sys.stdout.reconfigure(encoding="utf-8")
        result = func(*args, **kwargs)
        sys.stdout.close()
        sys.stdout = _original_stdout
        return result
+
    return wrapper

-class VoidTerminal():
+
+class VoidTerminal:
    def __init__(self) -> None:
        pass

+
 vt = VoidTerminal()
 vt.get_conf = silence_stdout_fn(get_conf)
 vt.set_conf = silence_stdout_fn(set_conf)
@@ -56,9 +63,27 @@ vt.get_plugin_handle = silence_stdout_fn(get_plugin_handle)
 vt.get_plugin_default_kwargs = silence_stdout_fn(get_plugin_default_kwargs)
 vt.get_chat_handle = silence_stdout_fn(get_chat_handle)
 vt.get_chat_default_kwargs = silence_stdout_fn(get_chat_default_kwargs)
-vt.chat_to_markdown_str = (chat_to_markdown_str)
-proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, API_KEY = \
-    vt.get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY')
+vt.chat_to_markdown_str = chat_to_markdown_str
+(
+    proxies,
+    WEB_PORT,
+    LLM_MODEL,
+    CONCURRENT_COUNT,
+    AUTHENTICATION,
+    CHATBOT_HEIGHT,
+    LAYOUT,
+    API_KEY,
+) = vt.get_conf(
+    "proxies",
+    "WEB_PORT",
+    "LLM_MODEL",
+    "CONCURRENT_COUNT",
+    "AUTHENTICATION",
+    "CHATBOT_HEIGHT",
+    "LAYOUT",
+    "API_KEY",
+)
+

 def plugin_test(main_input, plugin, advanced_arg=None, debug=True):
    from rich.live import Live
@@ -69,9 +94,9 @@ def plugin_test(main_input, plugin, advanced_arg=None, debug=True):

    plugin = vt.get_plugin_handle(plugin)
    plugin_kwargs = vt.get_plugin_default_kwargs()
-    plugin_kwargs['main_input'] = main_input
+    plugin_kwargs["main_input"] = main_input
    if advanced_arg is not None:
-        plugin_kwargs['plugin_kwargs'] = advanced_arg
+        plugin_kwargs["plugin_kwargs"] = advanced_arg
    if debug:
        my_working_plugin = (plugin)(**plugin_kwargs)
    else:
--- a/tests/test_vector_plugins.py
+++ b/tests/test_vector_plugins.py
@@ -4,14 +4,25 @@


 import os, sys
-def validate_path(): dir_name = os.path.dirname(__file__); root_dir_assume = os.path.abspath(dir_name +  '/..'); os.chdir(root_dir_assume); sys.path.append(root_dir_assume)
+
+
+def validate_path():
+    dir_name = os.path.dirname(__file__)
+    root_dir_assume = os.path.abspath(dir_name + "/..")
+    os.chdir(root_dir_assume)
+    sys.path.append(root_dir_assume)
+
+
 validate_path()  # 返回项目根路径

 if __name__ == "__main__":
    from tests.test_utils import plugin_test

-    plugin_test(plugin='crazy_functions.知识库问答->知识库文件注入', main_input="./README.md")
+    plugin_test(plugin="crazy_functions.知识库问答->知识库文件注入", main_input="./README.md")

-    plugin_test(plugin='crazy_functions.知识库问答->读取知识库作答', main_input="What is the installation method？")
+    plugin_test(
+        plugin="crazy_functions.知识库问答->读取知识库作答",
+        main_input="What is the installation method？",
+    )

-    plugin_test(plugin='crazy_functions.知识库问答->读取知识库作答', main_input="远程云服务器部署？")
+    plugin_test(plugin="crazy_functions.知识库问答->读取知识库作答", main_input="远程云服务器部署？")
--- a/themes/common.css
+++ b/themes/common.css
@@ -94,6 +94,10 @@
    background-color: var(--block-background-fill) !important;
 }

+#cbsc {
+    background-color: var(--block-background-fill) !important;
+}
+
 #interact-panel .form {
    border: hidden
 }
--- a/themes/common.js
+++ b/themes/common.js
@@ -1,3 +1,7 @@
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+//  第 1 部分: 工具函数
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+
 function gradioApp() {
    // https://github.com/GaiZhenbiao/ChuanhuChatGPT/tree/main/web_assets/javascript
    const elems = document.getElementsByTagName('gradio-app');
@@ -37,6 +41,143 @@ function getCookie(name) {
    return null;
 }

+let toastCount = 0;
+function toast_push(msg, duration) {
+    duration = isNaN(duration) ? 3000 : duration;
+    const existingToasts = document.querySelectorAll('.toast');
+    existingToasts.forEach(toast => {
+        toast.style.top = `${parseInt(toast.style.top, 10) - 70}px`;
+    });
+    const m = document.createElement('div');
+    m.innerHTML = msg;
+    m.classList.add('toast');
+    m.style.cssText = `font-size: var(--text-md) !important; color: rgb(255, 255, 255); background-color: rgba(0, 0, 0, 0.6); padding: 10px 15px; border-radius: 4px; position: fixed; top: ${50 + toastCount * 70}%; left: 50%; transform: translateX(-50%); width: auto; text-align: center; transition: top 0.3s;`;
+    document.body.appendChild(m);
+    setTimeout(function () {
+        m.style.opacity = '0';
+        setTimeout(function () {
+            document.body.removeChild(m);
+            toastCount--;
+        }, 500);
+    }, duration);
+    toastCount++;
+}
+
+function toast_up(msg) {
+    var m = document.getElementById('toast_up');
+    if (m) {
+        document.body.removeChild(m); // remove the loader from the body
+    }
+    m = document.createElement('div');
+    m.id = 'toast_up';
+    m.innerHTML = msg;
+    m.style.cssText = "font-size: var(--text-md) !important; color: rgb(255, 255, 255); background-color: rgba(0, 0, 100, 0.6); padding: 10px 15px; margin: 0 0 0 -60px; border-radius: 4px; position: fixed; top: 50%; left: 50%; width: auto; text-align: center;";
+    document.body.appendChild(m);
+}
+
+function toast_down() {
+    var m = document.getElementById('toast_up');
+    if (m) {
+        document.body.removeChild(m); // remove the loader from the body
+    }
+}
+
+function begin_loading_status() {
+    // Create the loader div and add styling
+    var loader = document.createElement('div');
+    loader.id = 'Js_File_Loading';
+    var C1 = document.createElement('div');
+    var C2 = document.createElement('div');
+    // var C3 = document.createElement('span');
+    // C3.textContent = '上传中...'
+    // C3.style.position = "fixed";
+    // C3.style.top = "50%";
+    // C3.style.left = "50%";
+    // C3.style.width = "80px";
+    // C3.style.height = "80px";
+    // C3.style.margin = "-40px 0 0 -40px";
+
+    C1.style.position = "fixed";
+    C1.style.top = "50%";
+    C1.style.left = "50%";
+    C1.style.width = "80px";
+    C1.style.height = "80px";
+    C1.style.borderLeft = "12px solid #00f3f300";
+    C1.style.borderRight = "12px solid #00f3f300";
+    C1.style.borderTop = "12px solid #82aaff";
+    C1.style.borderBottom = "12px solid #82aaff"; // Added for effect
+    C1.style.borderRadius = "50%";
+    C1.style.margin = "-40px 0 0 -40px";
+    C1.style.animation = "spinAndPulse 2s linear infinite";
+
+    C2.style.position = "fixed";
+    C2.style.top = "50%";
+    C2.style.left = "50%";
+    C2.style.width = "40px";
+    C2.style.height = "40px";
+    C2.style.borderLeft = "12px solid #00f3f300";
+    C2.style.borderRight = "12px solid #00f3f300";
+    C2.style.borderTop = "12px solid #33c9db";
+    C2.style.borderBottom = "12px solid #33c9db"; // Added for effect
+    C2.style.borderRadius = "50%";
+    C2.style.margin = "-20px 0 0 -20px";
+    C2.style.animation = "spinAndPulse2 2s linear infinite";
+
+    loader.appendChild(C1);
+    loader.appendChild(C2);
+    // loader.appendChild(C3);
+    document.body.appendChild(loader); // Add the loader to the body
+
+    // Set the CSS animation keyframes for spin and pulse to be synchronized
+    var styleSheet = document.createElement('style');
+    styleSheet.id = 'Js_File_Loading_Style';
+    styleSheet.textContent = `
+    @keyframes spinAndPulse {
+        0% { transform: rotate(0deg) scale(1); }
+        25% { transform: rotate(90deg) scale(1.1); }
+        50% { transform: rotate(180deg) scale(1); }
+        75% { transform: rotate(270deg) scale(0.9); }
+        100% { transform: rotate(360deg) scale(1); }
+    }
+
+    @keyframes spinAndPulse2 {
+        0% { transform: rotate(-90deg);}
+        25% { transform: rotate(-180deg);}
+        50% { transform: rotate(-270deg);}
+        75% { transform: rotate(-360deg);}
+        100% { transform: rotate(-450deg);}
+    }
+    `;
+    document.head.appendChild(styleSheet);
+}
+
+
+function cancel_loading_status() {
+    // remove the loader from the body
+    var loadingElement = document.getElementById('Js_File_Loading');
+    if (loadingElement) {
+        document.body.removeChild(loadingElement);
+    }
+    var loadingStyle = document.getElementById('Js_File_Loading_Style');
+    if (loadingStyle) {
+        document.head.removeChild(loadingStyle);
+    }
+    // create new listen event
+    let clearButton = document.querySelectorAll('div[id*="elem_upload"] button[aria-label="Clear"]');
+    for (let button of clearButton) {
+        button.addEventListener('click', function () {
+            setTimeout(function () {
+                register_upload_event();
+            }, 50);
+        });
+    }
+}
+
+
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+//  第 2 部分: 复制按钮
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+
 function addCopyButton(botElement) {
    // https://github.com/GaiZhenbiao/ChuanhuChatGPT/tree/main/web_assets/javascript
    // Copy bot button
@@ -45,8 +186,7 @@ function addCopyButton(botElement) {

    const messageBtnColumnElement = botElement.querySelector('.message-btn-row');
    if (messageBtnColumnElement) {
-        // Do something if .message-btn-column exists, for example, remove it
-        // messageBtnColumnElement.remove();
+        // if .message-btn-column exists
        return;
    }

@@ -89,6 +229,33 @@ function addCopyButton(botElement) {
    botElement.appendChild(messageBtnColumn);
 }

+
+let timeoutID = null;
+let lastInvocationTime = 0;
+let lastArgs = null;
+function do_something_but_not_too_frequently(min_interval, func) {
+    return function(...args) {
+        lastArgs = args;
+        const now = Date.now();
+        if (!lastInvocationTime || (now - lastInvocationTime) >= min_interval) {
+            lastInvocationTime = now;
+            // 现在就执行
+            setTimeout(() => {
+                func.apply(this, lastArgs);
+            }, 0);   
+        } else if (!timeoutID) {
+            // 等一会执行
+            timeoutID = setTimeout(() => {
+                timeoutID = null;
+                lastInvocationTime = Date.now();
+                func.apply(this, lastArgs);
+            }, min_interval - (now - lastInvocationTime));      
+        } else {
+            // 压根不执行
+        }
+    }
+}
+
 function chatbotContentChanged(attempt = 1, force = false) {
    // https://github.com/GaiZhenbiao/ChuanhuChatGPT/tree/main/web_assets/javascript
    for (var i = 0; i < attempt; i++) {
@@ -96,46 +263,69 @@ function chatbotContentChanged(attempt = 1, force = false) {
            gradioApp().querySelectorAll('#gpt-chatbot .message-wrap .message.bot').forEach(addCopyButton);
        }, i === 0 ? 0 : 200);
    }
+
+    const run_mermaid_render = do_something_but_not_too_frequently(1000, function () {
+        const blocks = document.querySelectorAll(`pre.mermaid, diagram-div`);
+        if (blocks.length == 0) { return; }
+        uml("mermaid");
+    });
+    run_mermaid_render();
 }

+
+
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+//  第 3 部分: chatbot动态高度调整
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+
 function chatbotAutoHeight() {
-    // 自动调整高度
+    // 自动调整高度：立即
    function update_height() {
-        var { panel_height_target, chatbot_height, chatbot } = get_elements(true);
-        if (panel_height_target!=chatbot_height)
-        {
-            var pixelString = panel_height_target.toString() + 'px';
+        var { height_target, chatbot_height, chatbot } = get_elements(true);
+        if (height_target != chatbot_height) {
+            var pixelString = height_target.toString() + 'px';
            chatbot.style.maxHeight = pixelString; chatbot.style.height = pixelString;
        }
    }

+    // 自动调整高度：缓慢
    function update_height_slow() {
-        var { panel_height_target, chatbot_height, chatbot } = get_elements();
-        if (panel_height_target!=chatbot_height)
-        {
-            new_panel_height = (panel_height_target - chatbot_height)*0.5 + chatbot_height;
-            if (Math.abs(new_panel_height - panel_height_target) < 10){
-                new_panel_height = panel_height_target;
+        var { height_target, chatbot_height, chatbot } = get_elements();
+        if (height_target != chatbot_height) {
+            // sign = (height_target - chatbot_height)/Math.abs(height_target - chatbot_height);
+            // speed = Math.max(Math.abs(height_target - chatbot_height), 1);
+            new_panel_height = (height_target - chatbot_height) * 0.5 + chatbot_height;
+            if (Math.abs(new_panel_height - height_target) < 10) {
+                new_panel_height = height_target;
            }
-            // console.log(chatbot_height, panel_height_target, new_panel_height);
            var pixelString = new_panel_height.toString() + 'px';
            chatbot.style.maxHeight = pixelString; chatbot.style.height = pixelString;
        }
    }
    monitoring_input_box()
    update_height();
-    setInterval(function() {
-        update_height_slow()
-    }, 50); // 每100毫秒执行一次
+    window.addEventListener('resize', function () { update_height(); });
+    window.addEventListener('scroll', function () { update_height_slow(); });
+    setInterval(function () { update_height_slow() }, 50); // 每50毫秒执行一次
 }

-function GptAcademicJavaScriptInit(LAYOUT = "LEFT-RIGHT") {
-    chatbotIndicator = gradioApp().querySelector('#gpt-chatbot > div.wrap');
-    var chatbotObserver = new MutationObserver(() => {
-        chatbotContentChanged(1);
-    });
-    chatbotObserver.observe(chatbotIndicator, { attributes: true, childList: true, subtree: true });
-    if (LAYOUT === "LEFT-RIGHT") {chatbotAutoHeight();}
+swapped = false;
+function swap_input_area() {
+    // Get the elements to be swapped
+    var element1 = document.querySelector("#input-panel");
+    var element2 = document.querySelector("#basic-panel");
+
+    // Get the parent of the elements
+    var parent = element1.parentNode;
+
+    // Get the next sibling of element2
+    var nextSibling = element2.nextSibling;
+
+    // Swap the elements
+    parent.insertBefore(element2, element1);
+    parent.insertBefore(element1, nextSibling);
+    if (swapped) { swapped = false; }
+    else { swapped = true; }
 }

 function get_elements(consider_state_panel = false) {
@@ -147,23 +337,95 @@ function get_elements(consider_state_panel=false) {
    const panel2 = document.querySelector('#basic-panel').getBoundingClientRect()
    const panel3 = document.querySelector('#plugin-panel').getBoundingClientRect();
    // const panel4 = document.querySelector('#interact-panel').getBoundingClientRect();
-    const panel5 = document.querySelector('#input-panel2').getBoundingClientRect();
    const panel_active = document.querySelector('#state-panel').getBoundingClientRect();
    if (consider_state_panel || panel_active.height < 25) {
        document.state_panel_height = panel_active.height;
    }
    // 25 是chatbot的label高度, 16 是右侧的gap
-    var panel_height_target = panel1.height + panel2.height + panel3.height + 0 + 0 - 25 + 16*2;
+    var height_target = panel1.height + panel2.height + panel3.height + 0 + 0 - 25 + 16 * 2;
    // 禁止动态的state-panel高度影响
-    panel_height_target = panel_height_target + (document.state_panel_height-panel_active.height)
-    var panel_height_target = parseInt(panel_height_target);
+    height_target = height_target + (document.state_panel_height - panel_active.height)
+    var height_target = parseInt(height_target);
    var chatbot_height = chatbot.style.height;
+    // 交换输入区位置，使得输入区始终可用
+    if (!swapped) {
+        if (panel1.top != 0 && (panel1.bottom + panel1.top) / 2 < 0) { swap_input_area(); }
+    }
+    else if (swapped) {
+        if (panel2.top != 0 && panel2.top > 0) { swap_input_area(); }
+    }
+    // 调整高度
+    const err_tor = 5;
+    if (Math.abs(panel1.left - chatbot.getBoundingClientRect().left) < err_tor) {
+        // 是否处于窄屏模式
+        height_target = window.innerHeight * 0.6;
+    } else {
+        // 调整高度
+        const chatbot_height_exceed = 15;
+        const chatbot_height_exceed_m = 10;
+        b_panel = Math.max(panel1.bottom, panel2.bottom, panel3.bottom)
+        if (b_panel >= window.innerHeight - chatbot_height_exceed) {
+            height_target = window.innerHeight - chatbot.getBoundingClientRect().top - chatbot_height_exceed_m;
+        }
+        else if (b_panel < window.innerHeight * 0.75) {
+            height_target = window.innerHeight * 0.8;
+        }
+    }
    var chatbot_height = parseInt(chatbot_height);
-    return { panel_height_target, chatbot_height, chatbot };
+    return { height_target, chatbot_height, chatbot };
 }


-function add_func_paste(input) {
+
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+//  第 4 部分: 粘贴、拖拽文件上传
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+
+var elem_upload = null;
+var elem_upload_float = null;
+var elem_input_main = null;
+var elem_input_float = null;
+var elem_chatbot = null;
+var elem_upload_component_float = null;
+var elem_upload_component = null;
+var exist_file_msg = '⚠️请先删除上传区（左上方）中的历史文件，再尝试上传。'
+
+function locate_upload_elems() {
+    elem_upload = document.getElementById('elem_upload')
+    elem_upload_float = document.getElementById('elem_upload_float')
+    elem_input_main = document.getElementById('user_input_main')
+    elem_input_float = document.getElementById('user_input_float')
+    elem_chatbot = document.getElementById('gpt-chatbot')
+    elem_upload_component_float = elem_upload_float.querySelector("input[type=file]");
+    elem_upload_component = elem_upload.querySelector("input[type=file]");
+}
+
+async function upload_files(files) {
+    let totalSizeMb = 0
+    elem_upload_component_float = elem_upload_float.querySelector("input[type=file]");
+    if (files && files.length > 0) {
+        // 执行具体的上传逻辑
+        if (elem_upload_component_float) {
+            for (let i = 0; i < files.length; i++) {
+                // 将从文件数组中获取的文件大小(单位为字节)转换为MB，
+                totalSizeMb += files[i].size / 1024 / 1024;
+            }
+            // 检查文件总大小是否超过20MB
+            if (totalSizeMb > 20) {
+                toast_push('⚠️文件夹大于 20MB 🚀上传文件中', 3000);
+            }
+            let event = new Event("change");
+            Object.defineProperty(event, "target", { value: elem_upload_component_float, enumerable: true });
+            Object.defineProperty(event, "currentTarget", { value: elem_upload_component_float, enumerable: true });
+            Object.defineProperty(elem_upload_component_float, "files", { value: files, enumerable: true });
+            elem_upload_component_float.dispatchEvent(event);
+        } else {
+            toast_push(exist_file_msg, 3000);
+        }
+    }
+}
+
+function register_func_paste(input) {
    let paste_files = [];
    if (input) {
        input.addEventListener("paste", async function (e) {
@@ -180,7 +442,7 @@ function add_func_paste(input) {
                }
                if (paste_files.length > 0) {
                    // 按照文件列表执行批量上传逻辑
-                    await paste_upload_files(paste_files);
+                    await upload_files(paste_files);
                    paste_files = []

                }
@@ -189,72 +451,110 @@ function add_func_paste(input) {
    }
 }

+function register_func_drag(elem) {
+    if (elem) {
+        const dragEvents = ["dragover"];
+        const leaveEvents = ["dragleave", "dragend", "drop"];

-async function paste_upload_files(files) {
-    const uploadInputElement = elem_upload_float.querySelector("input[type=file]");
-    let totalSizeMb = 0
-    if (files && files.length > 0) {
-        // 执行具体的上传逻辑
-        if (uploadInputElement) {
-            for (let i = 0; i < files.length; i++) {
-                // 将从文件数组中获取的文件大小(单位为字节)转换为MB，
-                totalSizeMb += files[i].size / 1024 / 1024;
-            }
-            // 检查文件总大小是否超过20MB
-            if (totalSizeMb > 20) {
-                toast_push('⚠️文件夹大于20MB 🚀上传文件中', 2000)
-                // return;  // 如果超过了指定大小, 可以不进行后续上传操作
-            }
-             // 监听change事件， 原生Gradio可以实现
-            // uploadInputElement.addEventListener('change', function(){replace_input_string()});
-            let event = new Event("change");
-            Object.defineProperty(event, "target", {value: uploadInputElement, enumerable: true});
-            Object.defineProperty(event, "currentTarget", {value: uploadInputElement, enumerable: true});
-            Object.defineProperty(uploadInputElement, "files", {value: files, enumerable: true});
-            uploadInputElement.dispatchEvent(event);
-            // toast_push('🎉上传文件成功', 2000)
+        const onDrag = function (e) {
+            e.preventDefault();
+            e.stopPropagation();
+            if (elem_upload_float.querySelector("input[type=file]")) {
+                toast_up('⚠️释放以上传文件')
            } else {
-            toast_push('⚠️请先删除上传区中的历史文件，再尝试粘贴。', 2000)
+                toast_up(exist_file_msg)
            }
+        };
+
+        const onLeave = function (e) {
+            toast_down();
+            e.preventDefault();
+            e.stopPropagation();
+        };
+
+        dragEvents.forEach(event => {
+            elem.addEventListener(event, onDrag);
+        });
+
+        leaveEvents.forEach(event => {
+            elem.addEventListener(event, onLeave);
+        });
+
+        elem.addEventListener("drop", async function (e) {
+            const files = e.dataTransfer.files;
+            await upload_files(files);
+        });
    }
 }
-//提示信息 封装
-function toast_push(msg, duration) {
-    duration = isNaN(duration) ? 3000 : duration;
-    const m = document.createElement('div');
-    m.innerHTML = msg;
-    m.style.cssText = "font-size:  var(--text-md) !important; color: rgb(255, 255, 255);background-color: rgba(0, 0, 0, 0.6);padding: 10px 15px;margin: 0 0 0 -60px;border-radius: 4px;position: fixed;    top: 50%;left: 50%;width: auto; text-align: center;";
-    document.body.appendChild(m);
-    setTimeout(function () {
-        var d = 0.5;
-        m.style.opacity = '0';
-        setTimeout(function () {
-            document.body.removeChild(m)
-        }, d * 1000);
-    }, duration);
-}

-var elem_upload = null;
-var elem_upload_float = null;
-var elem_input_main = null;
-var elem_input_float = null;
+function elem_upload_component_pop_message(elem) {
+    if (elem) {
+        const dragEvents = ["dragover"];
+        const leaveEvents = ["dragleave", "dragend", "drop"];
+        dragEvents.forEach(event => {
+            elem.addEventListener(event, function (e) {
+                e.preventDefault();
+                e.stopPropagation();
+                if (elem_upload_float.querySelector("input[type=file]")) {
+                    toast_up('⚠️释放以上传文件')
+                } else {
+                    toast_up(exist_file_msg)
+                }
+            });
+        });
+        leaveEvents.forEach(event => {
+            elem.addEventListener(event, function (e) {
+                toast_down();
+                e.preventDefault();
+                e.stopPropagation();
+            });
+        });
+        elem.addEventListener("drop", async function (e) {
+            toast_push('正在上传中，请稍等。', 2000);
+            begin_loading_status();
+        });
+    }
+}

+function register_upload_event() {
+    locate_upload_elems();
+    if (elem_upload_float) {
+        _upload = document.querySelector("#elem_upload_float div.center.boundedheight.flex")
+        elem_upload_component_pop_message(_upload);
+    }
+    if (elem_upload_component_float) {
+        elem_upload_component_float.addEventListener('change', function (event) {
+            toast_push('正在上传中，请稍等。', 2000);
+            begin_loading_status();
+        });
+    }
+    if (elem_upload_component) {
+        elem_upload_component.addEventListener('change', function (event) {
+            toast_push('正在上传中，请稍等。', 2000);
+            begin_loading_status();
+        });
+    } else {
+        toast_push("oppps", 3000);
+    }
+}

 function monitoring_input_box() {
-    elem_upload = document.getElementById('elem_upload')
-    elem_upload_float = document.getElementById('elem_upload_float')
-    elem_input_main = document.getElementById('user_input_main')
-    elem_input_float = document.getElementById('user_input_float')
+    register_upload_event();
+
    if (elem_input_main) {
        if (elem_input_main.querySelector("textarea")) {
-            add_func_paste(elem_input_main.querySelector("textarea"))
+            register_func_paste(elem_input_main.querySelector("textarea"))
        }
    }
    if (elem_input_float) {
        if (elem_input_float.querySelector("textarea")) {
-            add_func_paste(elem_input_float.querySelector("textarea"))
+            register_func_paste(elem_input_float.querySelector("textarea"))
        }
    }
+    if (elem_chatbot) {
+        register_func_drag(elem_chatbot)
+    }
+
 }


@@ -263,3 +563,153 @@ window.addEventListener("DOMContentLoaded", function () {
    // const ga = document.getElementsByTagName("gradio-app");
    gradioApp().addEventListener("render", monitoring_input_box);
 });
+
+
+
+
+
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+//  第 5 部分: 音频按钮样式变化
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+
+function audio_fn_init() {
+    let audio_component = document.getElementById('elem_audio');
+    if (audio_component) {
+        let buttonElement = audio_component.querySelector('button');
+        let specificElement = audio_component.querySelector('.hide.sr-only');
+        specificElement.remove();
+
+        buttonElement.childNodes[1].nodeValue = '启动麦克风';
+        buttonElement.addEventListener('click', function (event) {
+            event.stopPropagation();
+            toast_push('您启动了麦克风!下一步请点击“实时语音对话”启动语音对话。');
+        });
+
+        // 查找语音插件按钮
+        let buttons = document.querySelectorAll('button');
+        let audio_button = null;
+        for (let button of buttons) {
+            if (button.textContent.includes('语音')) {
+                audio_button = button;
+                break;
+            }
+        }
+        if (audio_button) {
+            audio_button.addEventListener('click', function () {
+                toast_push('您点击了“实时语音对话”启动语音对话。');
+            });
+            let parent_element = audio_component.parentElement; // 将buttonElement移动到audio_button的内部
+            audio_button.appendChild(audio_component);
+            buttonElement.style.cssText = 'border-color: #00ffe0;border-width: 2px; height: 25px;'
+            parent_element.remove();
+            audio_component.style.cssText = 'width: 250px;right: 0px;display: inline-flex;flex-flow: row-reverse wrap;place-content: stretch space-between;align-items: center;background-color: #ffffff00;';
+        }
+
+    }
+}
+
+function minor_ui_adjustment() {
+    let cbsc_area = document.getElementById('cbsc');
+    cbsc_area.style.paddingTop = '15px';
+    var bar_btn_width = [];
+    // 自动隐藏超出范围的toolbar按钮
+    function auto_hide_toolbar() {
+        var qq = document.getElementById('tooltip');
+        var tab_nav = qq.getElementsByClassName('tab-nav');
+        if (tab_nav.length == 0) { return; }
+        var btn_list = tab_nav[0].getElementsByTagName('button')
+        if (btn_list.length == 0) { return; }
+        // 获取页面宽度
+        var page_width = document.documentElement.clientWidth;
+        // 总是保留的按钮数量
+        const always_preserve = 2;
+        // 获取最后一个按钮的右侧位置
+        var cur_right = btn_list[always_preserve - 1].getBoundingClientRect().right;
+        if (bar_btn_width.length == 0) {
+            // 首次运行，记录每个按钮的宽度
+            for (var i = 0; i < btn_list.length; i++) {
+                bar_btn_width.push(btn_list[i].getBoundingClientRect().width);
+            }
+        }
+        // 处理每一个按钮
+        for (var i = always_preserve; i < btn_list.length; i++) {
+            var element = btn_list[i];
+            var element_right = element.getBoundingClientRect().right;
+            if (element_right != 0) { cur_right = element_right; }
+            if (element.style.display === 'none') {
+                if ((cur_right + bar_btn_width[i]) < (page_width * 0.37)) {
+                    // 恢复显示当前按钮
+                    element.style.display = 'block';
+                    return;
+                } else {
+                    return;
+                }
+            } else {
+                if (cur_right > (page_width * 0.38)) {
+                    // 隐藏当前按钮以及右侧所有按钮
+                    for (var j = i; j < btn_list.length; j++) {
+                        if (btn_list[j].style.display !== 'none') {
+                            btn_list[j].style.display = 'none';
+                        }
+                    }
+                    return;
+                }
+            }
+        }
+    }
+
+    setInterval(function () {
+        auto_hide_toolbar()
+    }, 200); // 每50毫秒执行一次
+}
+
+
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+//  第 6 部分: 避免滑动
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+let prevented_offset = 0;
+function limit_scroll_position() {
+    let scrollableDiv = document.querySelector('#gpt-chatbot > div.wrap');
+    scrollableDiv.addEventListener('wheel', function (e) {
+        let preventScroll = false;
+        if (e.deltaX != 0) { prevented_offset = 0; return;}
+        if (this.scrollHeight == this.clientHeight) { prevented_offset = 0; return;}
+        if (e.deltaY < 0) { prevented_offset = 0; return;}
+        if (e.deltaY > 0 && this.scrollHeight - this.clientHeight - this.scrollTop <= 1) { preventScroll = true; }
+
+        if (preventScroll) {
+            prevented_offset += e.deltaY;
+            if (Math.abs(prevented_offset) > 499) {
+                if (prevented_offset > 500) { prevented_offset = 500; }
+                if (prevented_offset < -500) { prevented_offset = -500; }
+                preventScroll = false;
+            }
+        } else {
+            prevented_offset = 0;
+        }
+        if (preventScroll) {
+            e.preventDefault();
+            return;
+        }
+    }, { passive: false }); // Passive event listener option should be false
+}
+
+
+
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+//  第 7 部分: JS初始化函数
+// -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+
+function GptAcademicJavaScriptInit(LAYOUT = "LEFT-RIGHT") {
+    audio_fn_init();
+    minor_ui_adjustment();
+    chatbotIndicator = gradioApp().querySelector('#gpt-chatbot > div.wrap');
+    var chatbotObserver = new MutationObserver(() => {
+        chatbotContentChanged(1);
+    });
+    chatbotObserver.observe(chatbotIndicator, { attributes: true, childList: true, subtree: true });
+    if (LAYOUT === "LEFT-RIGHT") { chatbotAutoHeight(); }
+    if (LAYOUT === "LEFT-RIGHT") { limit_scroll_position(); }
+    // setInterval(function () { uml("mermaid") }, 5000); // 每50毫秒执行一次
+
+}
--- a/themes/contrast.css
+++ b/themes/contrast.css
@@ -479,4 +479,3 @@
 .dark .codehilite .vi { color: #89DDFF } /* Name.Variable.Instance */
 .dark .codehilite .vm { color: #82AAFF } /* Name.Variable.Magic */
 .dark .codehilite .il { color: #F78C6C } /* Literal.Number.Integer.Long */
-
--- a/themes/contrast.py
+++ b/themes/contrast.py
@@ -1,18 +1,26 @@
 import os
 import gradio as gr
 from toolbox import get_conf
-CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU', 'LAYOUT')
+
+CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf("CODE_HIGHLIGHT", "ADD_WAIFU", "LAYOUT")
 theme_dir = os.path.dirname(__file__)

-def adjust_theme():

+def adjust_theme():
    try:
        color_er = gr.themes.utils.colors.fuchsia
        set_theme = gr.themes.Default(
            primary_hue=gr.themes.utils.colors.orange,
            neutral_hue=gr.themes.utils.colors.gray,
-            font=["Helvetica", "Microsoft YaHei", "ui-sans-serif", "sans-serif", "system-ui"],
-            font_mono=["ui-monospace", "Consolas", "monospace"])
+            font=[
+                "Helvetica",
+                "Microsoft YaHei",
+                "ui-sans-serif",
+                "sans-serif",
+                "system-ui",
+            ],
+            font_mono=["ui-monospace", "Consolas", "monospace"],
+        )
        set_theme.set(
            # Colors
            input_background_fill_dark="*neutral_800",
@@ -59,8 +67,14 @@ def adjust_theme():
            button_cancel_text_color_dark="white",
        )

-        with open(os.path.join(theme_dir, 'common.js'), 'r', encoding='utf8') as f: 
-            js = f"<script>{f.read()}</script>"
+        js = ""
+        for jsf in [
+            os.path.join(theme_dir, "common.js"),
+            os.path.join(theme_dir, "mermaid.min.js"),
+            os.path.join(theme_dir, "mermaid_loader.js"),
+        ]:
+            with open(jsf, "r", encoding="utf8") as f:
+                js += f"<script>{f.read()}</script>"

        # 添加一个萌萌的看板娘
        if ADD_WAIFU:
@@ -69,21 +83,26 @@ def adjust_theme():
                <script src="file=docs/waifu_plugin/jquery-ui.min.js"></script>
                <script src="file=docs/waifu_plugin/autoload.js"></script>
            """
-        if not hasattr(gr, 'RawTemplateResponse'):
+        if not hasattr(gr, "RawTemplateResponse"):
            gr.RawTemplateResponse = gr.routes.templates.TemplateResponse
        gradio_original_template_fn = gr.RawTemplateResponse
+
        def gradio_new_template_fn(*args, **kwargs):
            res = gradio_original_template_fn(*args, **kwargs)
-            res.body = res.body.replace(b'</html>', f'{js}</html>'.encode("utf8"))
+            res.body = res.body.replace(b"</html>", f"{js}</html>".encode("utf8"))
            res.init_headers()
            return res
-        gr.routes.templates.TemplateResponse = gradio_new_template_fn   # override gradio template
+
+        gr.routes.templates.TemplateResponse = (
+            gradio_new_template_fn  # override gradio template
+        )
    except:
        set_theme = None
-        print('gradio版本较旧, 不能自定义字体和颜色')
+        print("gradio版本较旧, 不能自定义字体和颜色")
    return set_theme

-with open(os.path.join(theme_dir, 'contrast.css'), "r", encoding="utf-8") as f:
+
+with open(os.path.join(theme_dir, "contrast.css"), "r", encoding="utf-8") as f:
    advanced_css = f.read()
-with open(os.path.join(theme_dir, 'common.css'), "r", encoding="utf-8") as f:
+with open(os.path.join(theme_dir, "common.css"), "r", encoding="utf-8") as f:
    advanced_css += f.read()
--- a/themes/cookies.py
+++ b/themes/cookies.py
--- a/themes/default.css
+++ b/themes/default.css
@@ -303,4 +303,3 @@
 .dark .codehilite .vi { color: #89DDFF } /* Name.Variable.Instance */
 .dark .codehilite .vm { color: #82AAFF } /* Name.Variable.Magic */
 .dark .codehilite .il { color: #F78C6C } /* Literal.Number.Integer.Long */
-
--- a/themes/default.py
+++ b/themes/default.py
@@ -1,17 +1,26 @@
 import os
 import gradio as gr
 from toolbox import get_conf
-CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU', 'LAYOUT')
-theme_dir = os.path.dirname(__file__)
-def adjust_theme():

+CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf("CODE_HIGHLIGHT", "ADD_WAIFU", "LAYOUT")
+theme_dir = os.path.dirname(__file__)
+
+
+def adjust_theme():
    try:
        color_er = gr.themes.utils.colors.fuchsia
        set_theme = gr.themes.Default(
            primary_hue=gr.themes.utils.colors.orange,
            neutral_hue=gr.themes.utils.colors.gray,
-            font=["Helvetica", "Microsoft YaHei", "ui-sans-serif", "sans-serif", "system-ui"],
-            font_mono=["ui-monospace", "Consolas", "monospace"])
+            font=[
+                "Helvetica",
+                "Microsoft YaHei",
+                "ui-sans-serif",
+                "sans-serif",
+                "system-ui",
+            ],
+            font_mono=["ui-monospace", "Consolas", "monospace"],
+        )
        set_theme.set(
            # Colors
            input_background_fill_dark="*neutral_800",
@@ -58,8 +67,14 @@ def adjust_theme():
            button_cancel_text_color_dark="white",
        )

-        with open(os.path.join(theme_dir, 'common.js'), 'r', encoding='utf8') as f: 
-            js = f"<script>{f.read()}</script>"
+        js = ""
+        for jsf in [
+            os.path.join(theme_dir, "common.js"),
+            os.path.join(theme_dir, "mermaid.min.js"),
+            os.path.join(theme_dir, "mermaid_loader.js"),
+        ]:
+            with open(jsf, "r", encoding="utf8") as f:
+                js += f"<script>{f.read()}</script>"

        # 添加一个萌萌的看板娘
        if ADD_WAIFU:
@@ -68,21 +83,26 @@ def adjust_theme():
                <script src="file=docs/waifu_plugin/jquery-ui.min.js"></script>
                <script src="file=docs/waifu_plugin/autoload.js"></script>
            """
-        if not hasattr(gr, 'RawTemplateResponse'):
+        if not hasattr(gr, "RawTemplateResponse"):
            gr.RawTemplateResponse = gr.routes.templates.TemplateResponse
        gradio_original_template_fn = gr.RawTemplateResponse
+
        def gradio_new_template_fn(*args, **kwargs):
            res = gradio_original_template_fn(*args, **kwargs)
-            res.body = res.body.replace(b'</html>', f'{js}</html>'.encode("utf8"))
+            res.body = res.body.replace(b"</html>", f"{js}</html>".encode("utf8"))
            res.init_headers()
            return res
-        gr.routes.templates.TemplateResponse = gradio_new_template_fn   # override gradio template
+
+        gr.routes.templates.TemplateResponse = (
+            gradio_new_template_fn  # override gradio template
+        )
    except:
        set_theme = None
-        print('gradio版本较旧, 不能自定义字体和颜色')
+        print("gradio版本较旧, 不能自定义字体和颜色")
    return set_theme

-with open(os.path.join(theme_dir, 'default.css'), "r", encoding="utf-8") as f:
+
+with open(os.path.join(theme_dir, "default.css"), "r", encoding="utf-8") as f:
    advanced_css = f.read()
-with open(os.path.join(theme_dir, 'common.css'), "r", encoding="utf-8") as f:
+with open(os.path.join(theme_dir, "common.css"), "r", encoding="utf-8") as f:
    advanced_css += f.read()
--- a/themes/gradios.py
+++ b/themes/gradios.py
@@ -2,30 +2,44 @@ import logging
 import os
 import gradio as gr
 from toolbox import get_conf, ProxyNetworkActivate
-CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU', 'LAYOUT')
+
+CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf("CODE_HIGHLIGHT", "ADD_WAIFU", "LAYOUT")
 theme_dir = os.path.dirname(__file__)

+
 def dynamic_set_theme(THEME):
    set_theme = gr.themes.ThemeClass()
-    with ProxyNetworkActivate('Download_Gradio_Theme'):
-        logging.info('正在下载Gradio主题，请稍等。')
-        if THEME.startswith('Huggingface-'): THEME = THEME.lstrip('Huggingface-')
-        if THEME.startswith('huggingface-'): THEME = THEME.lstrip('huggingface-')
+    with ProxyNetworkActivate("Download_Gradio_Theme"):
+        logging.info("正在下载Gradio主题，请稍等。")
+        if THEME.startswith("Huggingface-"):
+            THEME = THEME.lstrip("Huggingface-")
+        if THEME.startswith("huggingface-"):
+            THEME = THEME.lstrip("huggingface-")
        set_theme = set_theme.from_hub(THEME.lower())
    return set_theme

+
 def adjust_theme():
    try:
        set_theme = gr.themes.ThemeClass()
-        with ProxyNetworkActivate('Download_Gradio_Theme'):
-            logging.info('正在下载Gradio主题，请稍等。')
-            THEME = get_conf('THEME')
-            if THEME.startswith('Huggingface-'): THEME = THEME.lstrip('Huggingface-')
-            if THEME.startswith('huggingface-'): THEME = THEME.lstrip('huggingface-')
+        with ProxyNetworkActivate("Download_Gradio_Theme"):
+            logging.info("正在下载Gradio主题，请稍等。")
+            THEME = get_conf("THEME")
+            if THEME.startswith("Huggingface-"):
+                THEME = THEME.lstrip("Huggingface-")
+            if THEME.startswith("huggingface-"):
+                THEME = THEME.lstrip("huggingface-")
            set_theme = set_theme.from_hub(THEME.lower())

-        with open(os.path.join(theme_dir, 'common.js'), 'r', encoding='utf8') as f: 
-            js = f"<script>{f.read()}</script>"
+        js = ""
+        for jsf in [
+            os.path.join(theme_dir, "common.js"),
+            os.path.join(theme_dir, "mermaid.min.js"),
+            os.path.join(theme_dir, "mermaid_loader.js"),
+        ]:
+            with open(jsf, "r", encoding="utf8") as f:
+                js += f"<script>{f.read()}</script>"
+

        # 添加一个萌萌的看板娘
        if ADD_WAIFU:
@@ -34,20 +48,26 @@ def adjust_theme():
                <script src="file=docs/waifu_plugin/jquery-ui.min.js"></script>
                <script src="file=docs/waifu_plugin/autoload.js"></script>
            """
-        if not hasattr(gr, 'RawTemplateResponse'):
+        if not hasattr(gr, "RawTemplateResponse"):
            gr.RawTemplateResponse = gr.routes.templates.TemplateResponse
        gradio_original_template_fn = gr.RawTemplateResponse
+
        def gradio_new_template_fn(*args, **kwargs):
            res = gradio_original_template_fn(*args, **kwargs)
-            res.body = res.body.replace(b'</html>', f'{js}</html>'.encode("utf8"))
+            res.body = res.body.replace(b"</html>", f"{js}</html>".encode("utf8"))
            res.init_headers()
            return res
-        gr.routes.templates.TemplateResponse = gradio_new_template_fn   # override gradio template
-    except Exception as e:
+
+        gr.routes.templates.TemplateResponse = (
+            gradio_new_template_fn  # override gradio template
+        )
+    except Exception:
        set_theme = None
        from toolbox import trimmed_format_exc
-        logging.error('gradio版本较旧, 不能自定义字体和颜色:', trimmed_format_exc())
+
+        logging.error("gradio版本较旧, 不能自定义字体和颜色:", trimmed_format_exc())
    return set_theme

-with open(os.path.join(theme_dir, 'common.css'), "r", encoding="utf-8") as f:
+
+with open(os.path.join(theme_dir, "common.css"), "r", encoding="utf-8") as f:
    advanced_css = f.read()
--- a/themes/green.css
+++ b/themes/green.css
@@ -197,12 +197,12 @@ footer {
 }
 textarea.svelte-1pie7s6 {
    background: #e7e6e6 !important;
-    width: 96% !important;
+    width: 100% !important;
 }

 .dark textarea.svelte-1pie7s6 {
    background: var(--input-background-fill) !important;
-    width: 96% !important;
+    width: 100% !important;
 }

 .dark input[type=number].svelte-1cl284s {
@@ -256,13 +256,13 @@ textarea.svelte-1pie7s6 {
    max-height: 95% !important;
    overflow-y: auto !important;
 }*/
-.app.svelte-1mya07g.svelte-1mya07g {
+/* .app.svelte-1mya07g.svelte-1mya07g {
    max-width: 100%;
    position: relative;
    padding: var(--size-4);
    width: 100%;
    height: 100%;
-}
+} */

 .gradio-container-3-32-2 h1 {
    font-weight: 700 !important;
@@ -508,12 +508,14 @@ ol:not(.options), ul:not(.options) {
 [data-testid = "bot"] {
    max-width: 85%;
    border-bottom-left-radius: 0 !important;
+    box-shadow: 2px 2px 0px 1px rgba(0, 0, 0, 0.06);
    background-color: var(--message-bot-background-color-light) !important;
 }
 [data-testid = "user"] {
    max-width: 85%;
    width: auto !important;
    border-bottom-right-radius: 0 !important;
+    box-shadow: 2px 2px 0px 1px rgba(0, 0, 0, 0.06);
    background-color: var(--message-user-background-color-light) !important;
 }
 .dark [data-testid = "bot"] {
--- a/themes/green.py
+++ b/themes/green.py
@@ -1,9 +1,11 @@
 import os
 import gradio as gr
 from toolbox import get_conf
-CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU', 'LAYOUT')
+
+CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf("CODE_HIGHLIGHT", "ADD_WAIFU", "LAYOUT")
 theme_dir = os.path.dirname(__file__)

+
 def adjust_theme():
    try:
        set_theme = gr.themes.Soft(
@@ -50,7 +52,6 @@ def adjust_theme():
                c900="#2B2B2B",
                c950="#171717",
            ),
-
            radius_size=gr.themes.sizes.radius_sm,
        ).set(
            button_primary_background_fill="*primary_500",
@@ -75,8 +76,14 @@ def adjust_theme():
            chatbot_code_background_color_dark="*neutral_950",
        )

-        with open(os.path.join(theme_dir, 'common.js'), 'r', encoding='utf8') as f: 
-            js = f"<script>{f.read()}</script>"
+        js = ""
+        for jsf in [
+            os.path.join(theme_dir, "common.js"),
+            os.path.join(theme_dir, "mermaid.min.js"),
+            os.path.join(theme_dir, "mermaid_loader.js"),
+        ]:
+            with open(jsf, "r", encoding="utf8") as f:
+                js += f"<script>{f.read()}</script>"

        # 添加一个萌萌的看板娘
        if ADD_WAIFU:
@@ -86,24 +93,29 @@ def adjust_theme():
                <script src="file=docs/waifu_plugin/autoload.js"></script>
            """

-        with open(os.path.join(theme_dir, 'green.js'), 'r', encoding='utf8') as f: 
+        with open(os.path.join(theme_dir, "green.js"), "r", encoding="utf8") as f:
            js += f"<script>{f.read()}</script>"

-        if not hasattr(gr, 'RawTemplateResponse'):
+        if not hasattr(gr, "RawTemplateResponse"):
            gr.RawTemplateResponse = gr.routes.templates.TemplateResponse
        gradio_original_template_fn = gr.RawTemplateResponse
+
        def gradio_new_template_fn(*args, **kwargs):
            res = gradio_original_template_fn(*args, **kwargs)
-            res.body = res.body.replace(b'</html>', f'{js}</html>'.encode("utf8"))
+            res.body = res.body.replace(b"</html>", f"{js}</html>".encode("utf8"))
            res.init_headers()
            return res
-        gr.routes.templates.TemplateResponse = gradio_new_template_fn   # override gradio template
+
+        gr.routes.templates.TemplateResponse = (
+            gradio_new_template_fn  # override gradio template
+        )
    except:
        set_theme = None
-        print('gradio版本较旧, 不能自定义字体和颜色')
+        print("gradio版本较旧, 不能自定义字体和颜色")
    return set_theme

-with open(os.path.join(theme_dir, 'green.css'), "r", encoding="utf-8") as f:
+
+with open(os.path.join(theme_dir, "green.css"), "r", encoding="utf-8") as f:
    advanced_css = f.read()
-with open(os.path.join(theme_dir, 'common.css'), "r", encoding="utf-8") as f:
+with open(os.path.join(theme_dir, "common.css"), "r", encoding="utf-8") as f:
    advanced_css += f.read()
--- a/themes/mermaid.min.js
+++ b/themes/mermaid.min.js
--- a/themes/mermaid_editor.js
+++ b/themes/mermaid_editor.js
@@ -0,0 +1,55 @@
+import { deflate, inflate } from 'https://fastly.jsdelivr.net/gh/nodeca/pako@master/dist/pako.esm.mjs';
+import { toUint8Array, fromUint8Array, toBase64, fromBase64 } from 'https://cdn.jsdelivr.net/npm/js-base64@3.7.2/base64.mjs';
+
+const base64Serde = {
+    serialize: (state) => {
+        return toBase64(state, true);
+    },
+    deserialize: (state) => {
+        return fromBase64(state);
+    }
+};
+
+const pakoSerde = {
+    serialize: (state) => {
+        const data = new TextEncoder().encode(state);
+        const compressed = deflate(data, { level: 9 });
+        return fromUint8Array(compressed, true);
+    },
+    deserialize: (state) => {
+        const data = toUint8Array(state);
+        return inflate(data, { to: 'string' });
+    }
+};
+
+const serdes = {
+    base64: base64Serde,
+    pako: pakoSerde
+};
+
+export const serializeState = (state, serde = 'pako') => {
+    if (!(serde in serdes)) {
+        throw new Error(`Unknown serde type: ${serde}`);
+    }
+    const json = JSON.stringify(state);
+    const serialized = serdes[serde].serialize(json);
+    return `${serde}:${serialized}`;
+};
+
+const deserializeState = (state) => {
+    let type, serialized;
+    if (state.includes(':')) {
+        let tempType;
+        [tempType, serialized] = state.split(':');
+        if (tempType in serdes) {
+            type = tempType;
+        } else {
+            throw new Error(`Unknown serde type: ${tempType}`);
+        }
+    } else {
+        type = 'base64';
+        serialized = state;
+    }
+    const json = serdes[type].deserialize(serialized);
+    return JSON.parse(json);
+};
--- a/themes/mermaid_loader.js
+++ b/themes/mermaid_loader.js
@@ -0,0 +1,189 @@
+const uml = async className => {
+
+    // Custom element to encapsulate Mermaid content.
+    class MermaidDiv extends HTMLElement {
+
+        /**
+        * Creates a special Mermaid div shadow DOM.
+        * Works around issues of shared IDs.
+        * @return {void}
+        */
+        constructor() {
+            super()
+
+            // Create the Shadow DOM and attach style
+            const shadow = this.attachShadow({ mode: "open" })
+            const style = document.createElement("style")
+            style.textContent = `
+        :host {
+          display: block;
+          line-height: initial;
+          font-size: 16px;
+        }
+        div.diagram {
+          margin: 0;
+          overflow: visible;
+        }`
+            shadow.appendChild(style)
+        }
+    }
+
+    if (typeof customElements.get("diagram-div") === "undefined") {
+        customElements.define("diagram-div", MermaidDiv)
+    }
+
+    const getFromCode = parent => {
+        // Handles <pre><code> text extraction.
+        let text = ""
+        for (let j = 0; j < parent.childNodes.length; j++) {
+            const subEl = parent.childNodes[j]
+            if (subEl.tagName.toLowerCase() === "code") {
+                for (let k = 0; k < subEl.childNodes.length; k++) {
+                    const child = subEl.childNodes[k]
+                    const whitespace = /^\s*$/
+                    if (child.nodeName === "#text" && !(whitespace.test(child.nodeValue))) {
+                        text = child.nodeValue
+                        break
+                    }
+                }
+            }
+        }
+        return text
+    }
+
+    function createOrUpdateHyperlink(parentElement, linkText, linkHref) {
+        // Search for an existing anchor element within the parentElement
+        let existingAnchor = parentElement.querySelector("a");
+
+        // Check if an anchor element already exists
+        if (existingAnchor) {
+            // Update the hyperlink reference if it's different from the current one
+            if (existingAnchor.href !== linkHref) {
+                existingAnchor.href = linkHref;
+            }
+            // Update the target attribute to ensure it opens in a new tab
+            existingAnchor.target = '_blank';
+
+            // If the text must be dynamic, uncomment and use the following line:
+            // existingAnchor.textContent = linkText;
+        } else {
+            // If no anchor exists, create one and append it to the parentElement
+            let anchorElement = document.createElement("a");
+            anchorElement.href = linkHref; // Set hyperlink reference
+            anchorElement.textContent = linkText; // Set text displayed
+            anchorElement.target = '_blank'; // Ensure it opens in a new tab
+            parentElement.appendChild(anchorElement); // Append the new anchor element to the parent
+        }
+    }
+
+    function removeLastLine(str) {
+        // 将字符串按换行符分割成数组
+        var lines = str.split('\n');
+        lines.pop();
+        // 将数组重新连接成字符串，并按换行符连接
+        var result = lines.join('\n');
+        return result;
+    }
+
+    // 给出配置 Provide a default config in case one is not specified
+    const defaultConfig = {
+        startOnLoad: false,
+        theme: "default",
+        flowchart: {
+            htmlLabels: false
+        },
+        er: {
+            useMaxWidth: false
+        },
+        sequence: {
+            useMaxWidth: false,
+            noteFontWeight: "14px",
+            actorFontSize: "14px",
+            messageFontSize: "16px"
+        }
+    }
+    if (document.body.classList.contains("dark")) {
+        defaultConfig.theme = "dark"
+    }
+    
+    const Module = await import('./file=themes/mermaid_editor.js');
+
+    function do_render(block, code, codeContent, cnt) {
+        var rendered_content = mermaid.render(`_diagram_${cnt}`, code);
+        ////////////////////////////// 记录有哪些代码已经被渲染了 ///////////////////////////////////
+        let codeFinishRenderElement = block.querySelector("code_finish_render"); // 如果block下已存在code_already_rendered元素，则获取它
+        if (codeFinishRenderElement) {                                             // 如果block下已存在code_already_rendered元素
+            codeFinishRenderElement.style.display = "none";
+        } else {
+            // 如果不存在code_finish_render元素，则将code元素中的内容添加到新创建的code_finish_render元素中
+            let codeFinishRenderElementNew = document.createElement("code_finish_render"); // 创建一个新的code_already_rendered元素
+            codeFinishRenderElementNew.style.display = "none";
+            codeFinishRenderElementNew.textContent = "";
+            block.appendChild(codeFinishRenderElementNew); // 将新创建的code_already_rendered元素添加到block中
+            codeFinishRenderElement = codeFinishRenderElementNew;
+        }
+
+        ////////////////////////////// 创建一个用于渲染的容器 ///////////////////////////////////
+        let mermaidRender = block.querySelector(".mermaid_render"); // 尝试获取已存在的<div class='mermaid_render'>
+        if (!mermaidRender) {
+            mermaidRender = document.createElement("div");  // 不存在，创建新的<div class='mermaid_render'>
+            mermaidRender.classList.add("mermaid_render");
+            block.appendChild(mermaidRender);               // 将新创建的元素附加到block
+        }
+        mermaidRender.innerHTML = rendered_content
+        codeFinishRenderElement.textContent = code  // 标记已经渲染的部分
+
+        ////////////////////////////// 创建一个“点击这里编辑脑图” ///////////////////////////////
+        let pako_encode = Module.serializeState({
+            "code": codeContent,
+            "mermaid": "{\n  \"theme\": \"default\"\n}",
+            "autoSync": true,
+            "updateDiagram": false
+        });
+        createOrUpdateHyperlink(block, "点击这里编辑脑图", "https://mermaid.live/edit#" + pako_encode)
+    }
+
+    // 加载配置 Load up the config
+    mermaid.mermaidAPI.globalReset() // 全局复位
+    const config = (typeof mermaidConfig === "undefined") ? defaultConfig : mermaidConfig
+    mermaid.initialize(config)
+    // 查找需要渲染的元素 Find all of our Mermaid sources and render them.
+    const blocks = document.querySelectorAll(`pre.mermaid`);
+
+    for (let i = 0; i < blocks.length; i++) {
+        var block = blocks[i]
+        ////////////////////////////// 如果代码没有发生变化，就不渲染了 ///////////////////////////////////
+        var code = getFromCode(block);
+        let codeContent = block.querySelector("code").textContent; // 获取code元素中的文本内容
+        let codePendingRenderElement = block.querySelector("code_pending_render"); // 如果block下已存在code_already_rendered元素，则获取它
+        if (codePendingRenderElement) {                               // 如果block下已存在code_pending_render元素
+            codePendingRenderElement.style.display = "none";
+            if (codePendingRenderElement.textContent !== codeContent) {
+                codePendingRenderElement.textContent = codeContent; // 如果现有的code_pending_render元素中的内容与code元素中的内容不同，更新code_pending_render元素中的内容
+            }
+            else {
+                continue; // 如果相同，就不处理了
+            }
+        } else { // 如果不存在code_pending_render元素，则将code元素中的内容添加到新创建的code_pending_render元素中
+            let codePendingRenderElementNew = document.createElement("code_pending_render"); // 创建一个新的code_already_rendered元素
+            codePendingRenderElementNew.style.display = "none";
+            codePendingRenderElementNew.textContent = codeContent;
+            block.appendChild(codePendingRenderElementNew); // 将新创建的code_pending_render元素添加到block中
+            codePendingRenderElement = codePendingRenderElementNew;
+        }
+
+        ////////////////////////////// 在这里才真正开始渲染 ///////////////////////////////////
+        try {
+            do_render(block, code, codeContent, i);
+            // console.log("渲染", codeContent);
+        } catch (err) {
+            try {
+                var lines = code.split('\n'); if (lines.length < 2) { continue; }
+                do_render(block, removeLastLine(code), codeContent, i);
+                // console.log("渲染", codeContent);
+            } catch (err) {
+                console.log("以下代码不能渲染", code, removeLastLine(code), err);
+            }
+        }
+    }
+}
--- a/themes/theme.py
+++ b/themes/theme.py
@@ -1,23 +1,121 @@
-import gradio as gr
+import pickle
+import base64
+import uuid
 from toolbox import get_conf
-THEME = get_conf('THEME')
+
+"""
+-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
+第 1 部分
+加载主题相关的工具函数
+-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
+"""
+

 def load_dynamic_theme(THEME):
    adjust_dynamic_theme = None
-    if THEME == 'Chuanhu-Small-and-Beautiful':
+    if THEME == "Chuanhu-Small-and-Beautiful":
        from .green import adjust_theme, advanced_css
-        theme_declaration = "<h2 align=\"center\"  class=\"small\">[Chuanhu-Small-and-Beautiful主题]</h2>"
-    elif THEME == 'High-Contrast':
+
+        theme_declaration = (
+            '<h2 align="center"  class="small">[Chuanhu-Small-and-Beautiful主题]</h2>'
+        )
+    elif THEME == "High-Contrast":
        from .contrast import adjust_theme, advanced_css
+
        theme_declaration = ""
-    elif '/' in THEME:
+    elif "/" in THEME:
        from .gradios import adjust_theme, advanced_css
        from .gradios import dynamic_set_theme
+
        adjust_dynamic_theme = dynamic_set_theme(THEME)
        theme_declaration = ""
    else:
        from .default import adjust_theme, advanced_css
+
        theme_declaration = ""
    return adjust_theme, advanced_css, theme_declaration, adjust_dynamic_theme

-adjust_theme, advanced_css, theme_declaration, _ = load_dynamic_theme(THEME)
+
+adjust_theme, advanced_css, theme_declaration, _ = load_dynamic_theme(get_conf("THEME"))
+
+
+"""
+-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
+第 2 部分
+cookie相关工具函数
+-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
+"""
+
+
+def init_cookie(cookies, chatbot):
+    # 为每一位访问的用户赋予一个独一无二的uuid编码
+    cookies.update({"uuid": uuid.uuid4()})
+    return cookies
+
+
+def to_cookie_str(d):
+    # Pickle the dictionary and encode it as a string
+    pickled_dict = pickle.dumps(d)
+    cookie_value = base64.b64encode(pickled_dict).decode("utf-8")
+    return cookie_value
+
+
+def from_cookie_str(c):
+    # Decode the base64-encoded string and unpickle it into a dictionary
+    pickled_dict = base64.b64decode(c.encode("utf-8"))
+    return pickle.loads(pickled_dict)
+
+
+"""
+-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
+第 3 部分
+内嵌的javascript代码
+-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-
+"""
+
+js_code_for_css_changing = """(css) => {
+    var existingStyles = document.querySelectorAll("body > gradio-app > div > style")
+    for (var i = 0; i < existingStyles.length; i++) {
+        var style = existingStyles[i];
+        style.parentNode.removeChild(style);
+    }
+    var existingStyles = document.querySelectorAll("style[data-loaded-css]");
+    for (var i = 0; i < existingStyles.length; i++) {
+        var style = existingStyles[i];
+        style.parentNode.removeChild(style);
+    }
+    var styleElement = document.createElement('style');
+    styleElement.setAttribute('data-loaded-css', 'placeholder');
+    styleElement.innerHTML = css;
+    document.body.appendChild(styleElement);
+}
+"""
+
+js_code_for_darkmode_init = """(dark) => {
+    dark = dark == "True";
+    if (document.querySelectorAll('.dark').length) {
+        if (!dark){
+            document.querySelectorAll('.dark').forEach(el => el.classList.remove('dark'));
+        }
+    } else {
+        if (dark){
+            document.querySelector('body').classList.add('dark');
+        }
+    }
+}
+"""
+
+js_code_for_toggle_darkmode = """() => {
+    if (document.querySelectorAll('.dark').length) {
+        document.querySelectorAll('.dark').forEach(el => el.classList.remove('dark'));
+    } else {
+        document.querySelector('body').classList.add('dark');
+    }
+    document.querySelectorAll('code_pending_render').forEach(code => {code.remove();})
+}"""
+
+
+js_code_for_persistent_cookie_init = """(persistent_cookie) => {
+    return getCookie("persistent_cookie");
+}
+"""
--- a/toolbox.py
+++ b/toolbox.py
--- a/4
+++ b/4
@@ -1,5 +1,5 @@
 {
-  "version": 3.62,
+  "version": 3.70,
  "show_feature": true,
-  "new_feature": "修复若干隐蔽的内存BUG <-> 修复多用户冲突问题 <-> 接入Deepseek Coder <-> AutoGen多智能体插件测试版 <-> 修复本地模型在Windows下的加载BUG <-> 支持文心一言v4和星火v3 <-> 支持GLM3和智谱的API <-> 解决本地模型并发BUG <-> 支持动态追加基础功能按钮"
+  "new_feature": "支持Mermaid绘图库（让大模型绘制脑图） <-> 支持Gemini-pro <-> 支持直接拖拽文件到上传区 <-> 支持将图片粘贴到输入区 <-> 修复若干隐蔽的内存BUG <-> 修复多用户冲突问题 <-> 接入Deepseek Coder <-> AutoGen多智能体插件测试版"
 }
作者	SHA1	备注	提交日期
binary-husky	8565a35cf7	readme update	2024-01-18 23:21:11 +08:00
binary-husky	72d78eb150	Merge branch 'master' of github.com:binary-husky/chatgpt_academic	2024-01-18 23:07:05 +08:00
binary-husky	7aeda537ac	remove debug btn	2024-01-18 23:05:47 +08:00
binary-husky	6cea17d4b7	remove debug btn	2024-01-18 22:33:49 +08:00
binary-husky	20bc51d747	Merge branch 'master' into frontier	2024-01-18 22:23:26 +08:00
XIao	b8ebefa427	Google gemini fix (#1473 ) * 适配 google gemini 优化为从用户input中提取文件 * Update README.md (#1477) * Update README.md * Update README.md * Update requirements.txt (#1480) * welcome glm4 from 智谱! * Update README.md (#1484) * Update README.md (#1485) * update zhipu * Fix translation task name in core_functional.py * zhipuai version problem --------- Co-authored-by: binary-husky <96192199+binary-husky@users.noreply.github.com> Co-authored-by: binary-husky <qingxu.fu@outlook.com>	2024-01-18 18:06:07 +08:00
binary-husky	dcc9326f0b	zhipuai version problem	2024-01-18 17:51:20 +08:00
binary-husky	94fc396eb9	Fix translation task name in core_functional.py	2024-01-18 15:32:17 +08:00
binary-husky	e594e1b928	update zhipu	2024-01-18 00:32:51 +08:00
binary-husky	8fe545d97b	update zhipu	2024-01-18 00:31:53 +08:00
binary-husky	6f978fa72e	Merge branch 'master' into frontier	2024-01-17 12:37:07 +08:00
binary-husky	19be471aa8	Refactor core_functional.py	2024-01-17 12:34:42 +08:00
binary-husky	38956934fd	Update README.md (#1485 )	2024-01-17 11:45:49 +08:00
binary-husky	32439e14b5	Update README.md (#1484 )	2024-01-17 11:30:09 +08:00
binary-husky	317389bf4b	Merge branch 'master' into frontier	2024-01-16 21:53:53 +08:00
binary-husky	2c740fc641	welcome glm4 from 智谱!	2024-01-16 21:51:14 +08:00
binary-husky	96832a8228	Update requirements.txt (#1480 )	2024-01-16 20:08:32 +08:00
binary-husky	361557da3c	roll version	2024-01-16 02:15:35 +08:00
binary-husky	5f18d4a1af	Update README.md (#1477 ) * Update README.md * Update README.md	2024-01-16 02:14:08 +08:00
binary-husky	0d10bc570f	bug fix	2024-01-16 01:22:50 +08:00
binary-husky	3ce7d9347d	dark support	2024-01-16 00:33:11 +08:00
Keldos	8a78d7b89f	adapt mermaid to dark mode (#1476 ) Co-authored-by: binary-husky <96192199+binary-husky@users.noreply.github.com>	2024-01-16 00:32:12 +08:00
binary-husky	0e43b08837	同步	2024-01-16 00:29:46 +08:00
binary-husky	74bced2d35	添加脑图编辑按钮	2024-01-15 13:41:21 +08:00
binary-husky	961a24846f	remove console log	2024-01-15 11:50:37 +08:00
binary-husky	b7e4744f28	apply to other themes	2024-01-15 11:49:04 +08:00
binary-husky	71adc40901	support diagram plotting via mermaid !	2024-01-15 02:49:21 +08:00
binary-husky	a2099f1622	fix code highlight problem	2024-01-15 00:07:07 +08:00
binary-husky	c0a697f6c8	publish gradio via jsdelivr	2024-01-14 16:46:10 +08:00
binary-husky	bdde1d2fd7	format code	2024-01-14 04:18:38 +08:00
binary-husky	63373ab3b6	Merge branch 'frontier' of github.com:binary-husky/chatgpt_academic into frontier	2024-01-14 03:41:47 +08:00
binary-husky	fb6566adde	add todo	2024-01-14 03:41:23 +08:00
binary-husky	9f2ef9ec49	limit scroll	2024-01-14 02:11:07 +08:00
binary-husky	35c1aa21e4	limit scroll	2024-01-14 01:55:59 +08:00
binary-husky	627d739720	注入火山引擎大模型的接口代码	2024-01-13 22:33:08 +08:00
binary-husky	37f15185b6	Merge branch 'master' into frontier	2024-01-13 18:23:55 +08:00
binary-husky	9643e1c25f	code dem fix	2024-01-13 18:23:06 +08:00
binary-husky	28eae2f80e	Merge branch 'frontier' of github.com:binary-husky/chatgpt_academic into frontier	2024-01-13 18:04:21 +08:00
binary-husky	7ab379688e	format source code	2024-01-13 18:04:09 +08:00
binary-husky	3d4c6f54f1	format source code	2024-01-13 18:00:52 +08:00
binary-husky	1714116a89	break down toolbox.py to multiple files	2024-01-13 16:10:46 +08:00
hongyi-zhao	2bc65a99ca	Update bridge_all.py (#1472 ) 删除 "chatgpt_website" 函数，从而不再支持域基于逆向工程的方法的接口，该方法对应的实现项目为：https://github.com/acheong08/ChatGPT-to-API/。目前，该项目已被开发者 archived，且该方法由于其实现的原理，而不可能是稳健和完美的，因此不是可持续维护的。	2024-01-13 14:35:04 +08:00
binary-husky	0a2805513e	better gui interaction (#1459 )	2024-01-07 19:13:12 +08:00
binary-husky	d698b96209	Merge branch 'master' into frontier	2024-01-07 18:49:56 +08:00
binary-husky	6b1c6f0bf7	better gui interaction	2024-01-07 18:49:08 +08:00
binary-husky	c22867b74c	Merge pull request #1458 from binary-husky/frontier introduce Gemini & Format code	2024-01-07 16:24:33 +08:00
binary-husky	2abe665521	Merge branch 'master' into frontier	2024-01-05 16:12:41 +08:00
binary-husky	b0e6c4d365	change ui prompt	2024-01-05 16:11:30 +08:00
fzcqc	d883c7f34b	fix: expected_words添加反斜杆 (#1442 )	2024-01-03 19:57:10 +08:00
Menghuan1918	aba871342f	修复分割函数中使用的变量错误 (#1443 ) * Fix force_breakdown function parameter name * Add handling for PDFs with lowercase starting paragraphs * Change first lowercase word in meta_txt to uppercase	2024-01-03 19:49:17 +08:00
qingxu fu	37744a9cb1	jpeg type align for gemini	2023-12-31 20:28:39 +08:00
qingxu fu	480516380d	re-format code to with pre-commit	2023-12-31 19:30:32 +08:00
qingxu fu	60ba712131	use legacy image io for gemini	2023-12-31 19:02:40 +08:00
XIao	a7c960dcb0	适配 google gemini 优化为从用户input中提取文件 (#1419 ) 适配 google gemini 优化为从用户input中提取文件	2023-12-31 18:05:55 +08:00
binary-husky	a96f842b3a	minor ui change	2023-12-30 02:57:42 +08:00
binary-husky	417ca91e23	minor css change	2023-12-30 00:55:52 +08:00
binary-husky	ef8fadfa18	fix ui element padding	2023-12-29 15:16:33 +08:00
binary-husky	865c4ca993	Update README.md	2023-12-26 22:51:56 +08:00
binary-husky	31304f481a	remove console log	2023-12-25 22:57:09 +08:00
binary-husky	1bd3637d32	modify image gen plugin user interaction	2023-12-25 22:24:12 +08:00
binary-husky	160a683667	smart input panel swap	2023-12-25 22:05:14 +08:00
binary-husky	49ca03ca06	Merge branch 'master' into frontier	2023-12-25 21:43:33 +08:00
binary-husky	c625348ce1	smarter chatbot height adjustment	2023-12-25 21:26:24 +08:00
binary-husky	6d4a74893a	Merge pull request #1415 from binary-husky/frontier Merge Frontier Branch	2023-12-25 20:18:56 +08:00
qingxu fu	5c7499cada	compat with some third party api	2023-12-25 17:21:35 +08:00
binary-husky	f522691529	Merge pull request #1398 from leike0813/frontier 添加通义千问在线模型系列支持&增加插件	2023-12-24 18:21:45 +08:00
binary-husky	ca85573ec1	Update README.md	2023-12-24 18:14:57 +08:00
binary-husky	2c7bba5c63	change dash scope api key check behavior	2023-12-23 21:35:42 +08:00
binary-husky	e22f0226d5	Merge branch 'master' into leike0813-frontier	2023-12-23 21:00:38 +08:00
binary-husky	0f250305b4	add urllib3 version limit	2023-12-23 20:59:32 +08:00
binary-husky	7606f5c130	name fix	2023-12-23 20:55:58 +08:00
binary-husky	4f0dcc431c	Merge branch 'frontier' of https://github.com/leike0813/gpt_academic into leike0813-frontier	2023-12-23 20:42:43 +08:00
binary-husky	6ca0dd2f9e	Merge pull request #1410 from binary-husky/frontier fix spark image understanding api	2023-12-23 17:49:35 +08:00
binary-husky	e3e9921f6b	correct the misuse of spark image understanding	2023-12-23 17:46:25 +08:00
binary-husky	867ddd355e	adjust green theme layout	2023-12-22 21:59:18 +08:00
binary-husky	bb431db7d3	upgrade to version 3.64	2023-12-21 14:44:35 +08:00
binary-husky	43568b83e1	improve file upload notification	2023-12-21 14:39:58 +08:00
Keldos	2b90302851	feat: drag file to chatbot to upload 拖动以上传文件 (#1396 ) * feat: 拖动以上传文件 * 上传文件过程中转圈圈 * fix: 解决仅在第一次上传时才有上传动画的问题 --------- Co-authored-by: 505030475 <qingxu.fu@outlook.com>	2023-12-21 10:24:11 +08:00
binary-husky	f7588d4776	avoid adding the same file multiple times to the chatbot's files_to_promote list	2023-12-20 11:50:54 +08:00
binary-husky	a0bfa7ba1c	improve long text breakdown perfomance	2023-12-20 11:50:54 +08:00
leike0813	c60a7452bf	Improve NOUGAT pdf plugin Add an API version of NOUGAT plugin Add advanced argument support to NOUGAT plugin Adapt new text breakdown function bugfix	2023-12-20 08:57:27 +08:00
leike0813	68a49d3758	Add 2 plugins 相当于将“批量总结PDF文档”插件拆成了两部分，目的在于使用廉价的模型干粗活，再将关键的最终总结交给GPT-4，降低使用成本批量总结PDF文档_初步：初步总结PDF，每个PDF输出一个md文档批量总结Markdown文档_进阶：将所有md文档高度凝练并汇总至一个md文档，可直接使用“批量总结PDF文档_初步”的输出结果作为输入	2023-12-20 07:44:53 +08:00
leike0813	ac3d4cf073	Add support to aliyun qwen online models. Rename model tag "qwen" to "qwen-local" Add model tag "qwen-turbo", "qwen-plus", "qwen-max" Add corresponding model interfaces in request_llms/bridge_all.py Add configuration variable “DASHSCOPE_API_KEY" Rename request_llms/bridge_qwen.py to bridge_qwen_local.py to distinguish it from the online model interface	2023-12-20 07:37:26 +08:00
binary-husky	9479dd984c	avoid adding the same file multiple times to the chatbot's files_to_promote list	2023-12-19 19:43:03 +08:00
binary-husky	3c271302cc	improve long text breakdown perfomance	2023-12-19 19:30:44 +08:00
binary-husky	6e9936531d	fix theme shifting bug	2023-12-17 19:45:37 +08:00
binary-husky	439147e4b7	re-arrange main.py	2023-12-17 15:55:15 +08:00
binary-husky	8d13821099	a lm-based story writing game	2023-12-15 23:27:12 +08:00
binary-husky	49fe06ed69	add light edge for audio btn	2023-12-15 21:12:39 +08:00
binary-husky	7882ce7304	Merge branch 'master' into frontier	2023-12-15 16:34:06 +08:00
binary-husky	dc68e601a5	optimize audio plugin	2023-12-15 16:28:42 +08:00
binary-husky	d169fb4b16	fix typo	2023-12-15 13:32:39 +08:00
binary-husky	36e19d5202	compat further with one api	2023-12-15 13:16:06 +08:00
binary-husky	c5f1e4e392	version 3.63	2023-12-15 13:03:52 +08:00
binary-husky	d3f7267a63	Merge branch 'master' into frontier	2023-12-15 12:58:05 +08:00
qingxu fu	f4127a9c9c	change clip history policy	2023-12-15 12:52:21 +08:00
binary-husky	c181ad38b4	Update build-with-all-capacity-beta.yml	2023-12-14 12:23:49 +08:00
binary-husky	107944f5b7	Merge branch 'master' of github.com:binary-husky/chatgpt_academic	2023-12-14 11:01:02 +08:00
binary-husky	8c7569b689	修复protobuf版本错误	2023-12-14 11:00:55 +08:00
binary-husky	fa374bf1fc	try full dockerfile with vector store	2023-12-11 22:50:19 +08:00
				`@@ -1,2 +1 @@`
				`# 此Dockerfile不再维护，请前往docs/GithubAction+ChatGLM+Moss`