镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-06 14:36:48 +00:00
比较提交
115 次代码提交
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1
.gitignore
vendored
1
.gitignore
vendored
@@ -146,3 +146,4 @@ debug*
|
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private*
|
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crazy_functions/test_project/pdf_and_word
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crazy_functions/test_samples
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request_llm/jittorllms
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160
README.md
160
README.md
@@ -1,10 +1,15 @@
|
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> **Note**
|
||||
>
|
||||
> 安装依赖时,请严格选择requirements.txt中**指定的版本**。
|
||||
>
|
||||
> `pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/`
|
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>
|
||||
|
||||
# <img src="docs/logo.png" width="40" > GPT 学术优化 (GPT Academic)
|
||||
|
||||
# <img src="docs/logo.png" width="40" > ChatGPT 学术优化
|
||||
**如果喜欢这个项目,请给它一个Star;如果你发明了更好用的快捷键或函数插件,欢迎发pull requests**
|
||||
|
||||
**如果喜欢这个项目,请给它一个Star;如果你发明了更好用的快捷键或函数插件,欢迎发issue或者pull requests**
|
||||
|
||||
If you like this project, please give it a Star. If you've come up with more useful academic shortcuts or functional plugins, feel free to open an issue or pull request. We also have a README in [English|](docs/README_EN.md)[日本語|](docs/README_JP.md)[Русский|](docs/README_RS.md)[Français](docs/README_FR.md) translated by this project itself.
|
||||
If you like this project, please give it a Star. If you've come up with more useful academic shortcuts or functional plugins, feel free to open an issue or pull request. We also have a README in [English|](docs/README_EN.md)[日本語|](docs/README_JP.md)[한국어|](https://github.com/mldljyh/ko_gpt_academic)[Русский|](docs/README_RS.md)[Français](docs/README_FR.md) translated by this project itself.
|
||||
|
||||
> **Note**
|
||||
>
|
||||
@@ -12,34 +17,33 @@ If you like this project, please give it a Star. If you've come up with more use
|
||||
>
|
||||
> 2.本项目中每个文件的功能都在自译解[`self_analysis.md`](https://github.com/binary-husky/chatgpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A)详细说明。随着版本的迭代,您也可以随时自行点击相关函数插件,调用GPT重新生成项目的自我解析报告。常见问题汇总在[`wiki`](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98)当中。
|
||||
>
|
||||
> 3.已支持OpenAI和API2D的api-key共存,可在配置文件中填写如`API_KEY="openai-key1,openai-key2,api2d-key3"`。需要临时更换`API_KEY`时,在输入区输入临时的`API_KEY`然后回车键提交后即可生效。
|
||||
> 3.本项目兼容并鼓励尝试国产大语言模型chatglm和RWKV, 盘古等等。已支持OpenAI和API2D的api-key共存,可在配置文件中填写如`API_KEY="openai-key1,openai-key2,api2d-key3"`。需要临时更换`API_KEY`时,在输入区输入临时的`API_KEY`然后回车键提交后即可生效。
|
||||
|
||||
<div align="center">
|
||||
|
||||
|
||||
功能 | 描述
|
||||
--- | ---
|
||||
一键润色 | 支持一键润色、一键查找论文语法错误
|
||||
一键中英互译 | 一键中英互译
|
||||
一键代码解释 | 显示代码、解释代码、生成代码、给代码加注释
|
||||
[自定义快捷键](https://www.bilibili.com/video/BV14s4y1E7jN) | 支持自定义快捷键
|
||||
[配置代理服务器](https://www.bilibili.com/video/BV1rc411W7Dr) | 支持配置代理服务器
|
||||
模块化设计 | 支持自定义高阶的函数插件与[函数插件],插件支持[热更新](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
|
||||
模块化设计 | 支持自定义强大的[函数插件](https://github.com/binary-husky/chatgpt_academic/tree/master/crazy_functions),插件支持[热更新](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
|
||||
[自我程序剖析](https://www.bilibili.com/video/BV1cj411A7VW) | [函数插件] [一键读懂](https://github.com/binary-husky/chatgpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A)本项目的源代码
|
||||
[程序剖析](https://www.bilibili.com/video/BV1cj411A7VW) | [函数插件] 一键可以剖析其他Python/C/C++/Java/Lua/...项目树
|
||||
读论文、翻译论文 | [函数插件] 一键解读latex/pdf论文全文并生成摘要
|
||||
Latex全文翻译、润色 | [函数插件] 一键翻译或润色latex论文
|
||||
生成GPT分析报告 | [函数插件] 运行后自动生成总结汇报,支持一键导出html格式对话记录
|
||||
Markdown中英互译 | [函数插件] 看到上面5种语言的[README](https://github.com/binary-husky/chatgpt_academic/blob/master/docs/README_EN.md)了吗?
|
||||
[arxiv小助手](https://www.bilibili.com/video/BV1LM4y1279X) | [函数插件] 输入arxiv文章url即可一键翻译摘要+下载PDF
|
||||
读论文、[翻译](https://www.bilibili.com/video/BV1KT411x7Wn)论文 | [函数插件] 一键解读latex/pdf论文全文并生成摘要
|
||||
Latex全文[翻译](https://www.bilibili.com/video/BV1nk4y1Y7Js/)、[润色](https://www.bilibili.com/video/BV1FT411H7c5/) | [函数插件] 一键翻译或润色latex论文
|
||||
批量注释生成 | [函数插件] 一键批量生成函数注释
|
||||
Markdown[中英互译](https://www.bilibili.com/video/BV1yo4y157jV/) | [函数插件] 看到上面5种语言的[README](https://github.com/binary-husky/chatgpt_academic/blob/master/docs/README_EN.md)了吗?
|
||||
chat分析报告生成 | [函数插件] 运行后自动生成总结汇报
|
||||
[PDF论文全文翻译功能](https://www.bilibili.com/video/BV1KT411x7Wn) | [函数插件] PDF论文提取题目&摘要+翻译全文(多线程)
|
||||
[谷歌学术统合小助手](https://www.bilibili.com/video/BV19L411U7ia) | [函数插件] 给定任意谷歌学术搜索页面的URL,让GPT帮你写Related Works
|
||||
互联网信息聚合+GPT | [函数插件] 一键让ChatGPT先Google搜索,再回答问题,信息流永不过时
|
||||
公式/图片/表格显示 | 可以同时显示公式的tex形式和渲染形式,支持公式、代码高亮
|
||||
多线程函数插件支持 | 支持多线调用chatgpt,一键处理海量文本或程序
|
||||
[Arxiv小助手](https://www.bilibili.com/video/BV1LM4y1279X) | [函数插件] 输入arxiv文章url即可一键翻译摘要+下载PDF
|
||||
[谷歌学术统合小助手](https://www.bilibili.com/video/BV19L411U7ia) | [函数插件] 给定任意谷歌学术搜索页面URL,让gpt帮你[写relatedworks](https://www.bilibili.com/video/BV1GP411U7Az/)
|
||||
互联网信息聚合+GPT | [函数插件] 一键[让GPT先从互联网获取信息](https://www.bilibili.com/video/BV1om4y127ck),再回答问题,让信息永不过时
|
||||
公式/图片/表格显示 | 可以同时显示公式的[tex形式和渲染形式](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png),支持公式、代码高亮
|
||||
多线程函数插件支持 | 支持多线调用chatgpt,一键处理[海量文本](https://www.bilibili.com/video/BV1FT411H7c5/)或程序
|
||||
启动暗色gradio[主题](https://github.com/binary-husky/chatgpt_academic/issues/173) | 在浏览器url后面添加```/?__dark-theme=true```可以切换dark主题
|
||||
[多LLM模型](https://www.bilibili.com/video/BV1wT411p7yf)支持,[API2D](https://api2d.com/)接口支持 | 同时被GPT3.5、GPT4和[清华ChatGLM](https://github.com/THUDM/ChatGLM-6B)伺候的感觉一定会很不错吧?
|
||||
更多LLM模型接入 | 新加入Newbing测试接口(新必应AI)
|
||||
huggingface免科学上网[在线体验](https://huggingface.co/spaces/qingxu98/gpt-academic) | 登陆huggingface后复制[此空间](https://huggingface.co/spaces/qingxu98/gpt-academic)
|
||||
更多LLM模型接入,支持[huggingface部署](https://huggingface.co/spaces/qingxu98/gpt-academic) | 新加入Newbing测试接口(新必应AI)
|
||||
…… | ……
|
||||
|
||||
</div>
|
||||
@@ -76,9 +80,6 @@ huggingface免科学上网[在线体验](https://huggingface.co/spaces/qingxu98/
|
||||
<img src="https://user-images.githubusercontent.com/96192199/232537274-deca0563-7aa6-4b5d-94a2-b7c453c47794.png" width="700" >
|
||||
</div>
|
||||
|
||||
多种大语言模型混合调用[huggingface测试版](https://huggingface.co/spaces/qingxu98/academic-chatgpt-beta)(huggingface版不支持chatglm)
|
||||
|
||||
|
||||
---
|
||||
|
||||
## 安装-方法1:直接运行 (Windows, Linux or MacOS)
|
||||
@@ -89,20 +90,16 @@ git clone https://github.com/binary-husky/chatgpt_academic.git
|
||||
cd chatgpt_academic
|
||||
```
|
||||
|
||||
2. 配置API_KEY和代理设置
|
||||
2. 配置API_KEY
|
||||
|
||||
在`config.py`中,配置API KEY等设置,[特殊网络环境设置](https://github.com/binary-husky/gpt_academic/issues/1) 。
|
||||
|
||||
在`config.py`中,配置 海外Proxy 和 OpenAI API KEY,说明如下
|
||||
```
|
||||
1. 如果你在国内,需要设置海外代理才能够顺利使用OpenAI API,设置方法请仔细阅读config.py(1.修改其中的USE_PROXY为True; 2.按照说明修改其中的proxies)。
|
||||
2. 配置 OpenAI API KEY。支持任意数量的OpenAI的密钥和API2D的密钥共存/负载均衡,多个KEY用英文逗号分隔即可,例如输入 API_KEY="OpenAI密钥1,API2D密钥2,OpenAI密钥3,OpenAI密钥4"
|
||||
3. 与代理网络有关的issue(网络超时、代理不起作用)汇总到 https://github.com/binary-husky/chatgpt_academic/issues/1
|
||||
```
|
||||
(P.S. 程序运行时会优先检查是否存在名为`config_private.py`的私密配置文件,并用其中的配置覆盖`config.py`的同名配置。因此,如果您能理解我们的配置读取逻辑,我们强烈建议您在`config.py`旁边创建一个名为`config_private.py`的新配置文件,并把`config.py`中的配置转移(复制)到`config_private.py`中。`config_private.py`不受git管控,可以让您的隐私信息更加安全。)
|
||||
|
||||
|
||||
3. 安装依赖
|
||||
```sh
|
||||
# (选择I: 如熟悉python)推荐
|
||||
# (选择I: 如熟悉python)(python版本3.9以上,越新越好)
|
||||
python -m pip install -r requirements.txt
|
||||
# 备注:使用官方pip源或者阿里pip源,其他pip源(如一些大学的pip)有可能出问题,临时换源方法:python -m pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
|
||||
|
||||
@@ -115,6 +112,10 @@ python -m pip install -r requirements.txt
|
||||
如果需要支持清华ChatGLM后端,需要额外安装更多依赖(前提条件:熟悉python + 电脑配置够强):
|
||||
```sh
|
||||
python -m pip install -r request_llm/requirements_chatglm.txt
|
||||
|
||||
# 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)
|
||||
```
|
||||
|
||||
4. 运行
|
||||
@@ -124,14 +125,8 @@ python main.py
|
||||
|
||||
5. 测试函数插件
|
||||
```
|
||||
- 测试Python项目分析
|
||||
(选择1)input区域 输入 `./crazy_functions/test_project/python/dqn` , 然后点击 "解析整个Python项目"
|
||||
(选择2)展开文件上传区,将python文件/包含python文件的压缩包拖拽进去,在出现反馈提示后, 然后点击 "解析整个Python项目"
|
||||
- 测试自我代码解读(本项目自译解)
|
||||
点击 "[多线程Demo] 解析此项目本身(源码自译解)"
|
||||
- 测试函数插件模板函数(要求gpt回答历史上的今天发生了什么),您可以根据此函数为模板,实现更复杂的功能
|
||||
点击 "[函数插件模板Demo] 历史上的今天"
|
||||
- 函数插件区下拉菜单中有更多功能可供选择
|
||||
```
|
||||
|
||||
## 安装-方法2:使用Docker
|
||||
@@ -142,7 +137,7 @@ python main.py
|
||||
# 下载项目
|
||||
git clone https://github.com/binary-husky/chatgpt_academic.git
|
||||
cd chatgpt_academic
|
||||
# 配置 “海外Proxy”, “API_KEY” 以及 “WEB_PORT” (例如50923) 等
|
||||
# 配置 “Proxy”, “API_KEY” 以及 “WEB_PORT” (例如50923) 等
|
||||
用任意文本编辑器编辑 config.py
|
||||
# 安装
|
||||
docker build -t gpt-academic .
|
||||
@@ -165,26 +160,30 @@ docker run --rm -it --net=host --gpus=all gpt-academic
|
||||
docker run --rm -it --net=host --gpus=all gpt-academic bash
|
||||
```
|
||||
|
||||
3. ChatGPT + LLAMA + 盘古 + RWKV(需要精通Docker)
|
||||
``` sh
|
||||
1. 修改docker-compose.yml,删除方案一和方案二,保留方案三(基于jittor)
|
||||
2. 修改docker-compose.yml中方案三的配置,参考其中注释即可
|
||||
3. 终端运行 docker-compose up
|
||||
```
|
||||
|
||||
## 安装-方法3:其他部署方式(需要云服务器知识与经验)
|
||||
|
||||
1. 远程云服务器部署
|
||||
## 安装-方法3:其他部署姿势
|
||||
|
||||
1. 如何使用反代URL/微软云AzureAPI
|
||||
按照`config.py`中的说明配置API_URL_REDIRECT即可。
|
||||
|
||||
2. 远程云服务器部署(需要云服务器知识与经验)
|
||||
请访问[部署wiki-1](https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BA%91%E6%9C%8D%E5%8A%A1%E5%99%A8%E8%BF%9C%E7%A8%8B%E9%83%A8%E7%BD%B2%E6%8C%87%E5%8D%97)
|
||||
|
||||
2. 使用WSL2(Windows Subsystem for Linux 子系统)
|
||||
3. 使用WSL2(Windows Subsystem for Linux 子系统)
|
||||
请访问[部署wiki-2](https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BD%BF%E7%94%A8WSL2%EF%BC%88Windows-Subsystem-for-Linux-%E5%AD%90%E7%B3%BB%E7%BB%9F%EF%BC%89%E9%83%A8%E7%BD%B2)
|
||||
|
||||
3. 如何在二级网址(如`http://localhost/subpath`)下运行
|
||||
4. 如何在二级网址(如`http://localhost/subpath`)下运行
|
||||
请访问[FastAPI运行说明](docs/WithFastapi.md)
|
||||
|
||||
## 安装-代理配置
|
||||
1. 常规方法
|
||||
[配置代理](https://github.com/binary-husky/chatgpt_academic/issues/1)
|
||||
|
||||
2. 纯新手教程
|
||||
[纯新手教程](https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BB%A3%E7%90%86%E8%BD%AF%E4%BB%B6%E9%97%AE%E9%A2%98%E7%9A%84%E6%96%B0%E6%89%8B%E8%A7%A3%E5%86%B3%E6%96%B9%E6%B3%95%EF%BC%88%E6%96%B9%E6%B3%95%E5%8F%AA%E9%80%82%E7%94%A8%E4%BA%8E%E6%96%B0%E6%89%8B%EF%BC%89)
|
||||
|
||||
|
||||
5. 使用docker-compose运行
|
||||
请阅读docker-compose.yml后,按照其中的提示操作即可
|
||||
---
|
||||
|
||||
## 自定义新的便捷按钮 / 自定义函数插件
|
||||
@@ -211,74 +210,48 @@ docker run --rm -it --net=host --gpus=all gpt-academic bash
|
||||
本项目的插件编写、调试难度很低,只要您具备一定的python基础知识,就可以仿照我们提供的模板实现自己的插件功能。
|
||||
详情请参考[函数插件指南](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)。
|
||||
|
||||
|
||||
---
|
||||
|
||||
## 其他功能说明
|
||||
|
||||
## 部分功能展示
|
||||
|
||||
1. 图片显示:
|
||||
|
||||
1. 对话保存功能。在函数插件区调用 `保存当前的对话` 即可将当前对话保存为可读+可复原的html文件,如图:
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/228737599-bf0a9d9c-1808-4f43-ae15-dfcc7af0f295.png" width="800" >
|
||||
<img src="https://user-images.githubusercontent.com/96192199/235222390-24a9acc0-680f-49f5-bc81-2f3161f1e049.png" width="500" >
|
||||
</div>
|
||||
|
||||
2. 本项目的代码自译解(如果一个程序能够读懂并剖析自己):
|
||||
在函数插件区(下拉菜单)调用 `载入对话历史存档` ,即可还原之前的会话。
|
||||
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/226936850-c77d7183-0749-4c1c-9875-fd4891842d0c.png" width="800" >
|
||||
</div>
|
||||
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/226936618-9b487e4b-ab5b-4b6e-84c6-16942102e917.png" width="800" >
|
||||
</div>
|
||||
|
||||
3. 其他任意Python/Cpp/Java/Go/Rect/...项目剖析:
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/226935232-6b6a73ce-8900-4aee-93f9-733c7e6fef53.png" width="800" >
|
||||
</div>
|
||||
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/226969067-968a27c1-1b9c-486b-8b81-ab2de8d3f88a.png" width="800" >
|
||||
</div>
|
||||
|
||||
4. Latex论文一键阅读理解与摘要生成
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/227504406-86ab97cd-f208-41c3-8e4a-7000e51cf980.png" width="800" >
|
||||
</div>
|
||||
|
||||
5. 自动报告生成
|
||||
2. 生成报告。大部分插件都会在执行结束后,生成工作报告
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/227503770-fe29ce2c-53fd-47b0-b0ff-93805f0c2ff4.png" height="300" >
|
||||
<img src="https://user-images.githubusercontent.com/96192199/227504617-7a497bb3-0a2a-4b50-9a8a-95ae60ea7afd.png" height="300" >
|
||||
<img src="https://user-images.githubusercontent.com/96192199/227504005-efeaefe0-b687-49d0-bf95-2d7b7e66c348.png" height="300" >
|
||||
</div>
|
||||
|
||||
6. 模块化功能设计
|
||||
3. 模块化功能设计,简单的接口却能支持强大的功能
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/229288270-093643c1-0018-487a-81e6-1d7809b6e90f.png" height="400" >
|
||||
<img src="https://user-images.githubusercontent.com/96192199/227504931-19955f78-45cd-4d1c-adac-e71e50957915.png" height="400" >
|
||||
</div>
|
||||
|
||||
|
||||
7. 源代码转译英文
|
||||
|
||||
4. 这是一个能够“自我译解”的开源项目
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/229720562-fe6c3508-6142-4635-a83d-21eb3669baee.png" height="400" >
|
||||
<img src="https://user-images.githubusercontent.com/96192199/226936850-c77d7183-0749-4c1c-9875-fd4891842d0c.png" width="500" >
|
||||
</div>
|
||||
|
||||
8. 互联网在线信息综合
|
||||
|
||||
5. 译解其他开源项目,不在话下
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/233575247-fb00819e-6d1b-4bb7-bd54-1d7528f03dd9.png" width="800" >
|
||||
<img src="https://user-images.githubusercontent.com/96192199/233779501-5ce826f0-6cca-4d59-9e5f-b4eacb8cc15f.png" width="800" >
|
||||
|
||||
<img src="https://user-images.githubusercontent.com/96192199/226935232-6b6a73ce-8900-4aee-93f9-733c7e6fef53.png" width="500" >
|
||||
</div>
|
||||
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/226969067-968a27c1-1b9c-486b-8b81-ab2de8d3f88a.png" width="500" >
|
||||
</div>
|
||||
|
||||
|
||||
## Todo 与 版本规划:
|
||||
- version 3.3+ (todo): NewBing支持
|
||||
## 版本:
|
||||
- version 3.5(Todo): 使用自然语言调用本项目的所有函数插件(高优先级)
|
||||
- version 3.4(Todo): 完善chatglm本地大模型的多线支持
|
||||
- version 3.3: +互联网信息综合功能
|
||||
- version 3.2: 函数插件支持更多参数接口 (保存对话功能, 解读任意语言代码+同时询问任意的LLM组合)
|
||||
- version 3.1: 支持同时问询多个gpt模型!支持api2d,支持多个apikey负载均衡
|
||||
- version 3.0: 对chatglm和其他小型llm的支持
|
||||
@@ -291,7 +264,8 @@ docker run --rm -it --net=host --gpus=all gpt-academic bash
|
||||
- version 2.0: 引入模块化函数插件
|
||||
- version 1.0: 基础功能
|
||||
|
||||
chatgpt_academic开发者QQ群:734063350
|
||||
gpt_academic开发者QQ群:734063350
|
||||
|
||||
|
||||
## 参考与学习
|
||||
|
||||
|
||||
@@ -56,22 +56,24 @@ def patch_and_restart(path):
|
||||
"""
|
||||
一键更新协议:覆盖和重启
|
||||
"""
|
||||
import distutils
|
||||
from distutils import dir_util
|
||||
import shutil
|
||||
import os
|
||||
import sys
|
||||
import time
|
||||
import glob
|
||||
from colorful import print亮黄, print亮绿, print亮红
|
||||
# if not using config_private, move origin config.py as config_private.py
|
||||
if not os.path.exists('config_private.py'):
|
||||
print亮黄('由于您没有设置config_private.py私密配置,现将您的现有配置移动至config_private.py以防止配置丢失,',
|
||||
'另外您可以随时在history子文件夹下找回旧版的程序。')
|
||||
shutil.copyfile('config.py', 'config_private.py')
|
||||
distutils.dir_util.copy_tree(path+'/chatgpt_academic-master', './')
|
||||
import subprocess
|
||||
path_new_version = glob.glob(path + '/*-master')[0]
|
||||
dir_util.copy_tree(path_new_version, './')
|
||||
print亮绿('代码已经更新,即将更新pip包依赖……')
|
||||
for i in reversed(range(5)): time.sleep(1); print(i)
|
||||
try:
|
||||
import subprocess
|
||||
subprocess.check_call([sys.executable, '-m', 'pip', 'install', '-r', 'requirements.txt'])
|
||||
except:
|
||||
print亮红('pip包依赖安装出现问题,需要手动安装新增的依赖库 `python -m pip install -r requirements.txt`,然后在用常规的`python main.py`的方式启动。')
|
||||
|
||||
16
config.py
16
config.py
@@ -10,11 +10,11 @@ if USE_PROXY:
|
||||
# [地址] 懂的都懂,不懂就填localhost或者127.0.0.1肯定错不了(localhost意思是代理软件安装在本机上)
|
||||
# [端口] 在代理软件的设置里找。虽然不同的代理软件界面不一样,但端口号都应该在最显眼的位置上
|
||||
|
||||
# 代理网络的地址,打开你的科学上网软件查看代理的协议(socks5/http)、地址(localhost)和端口(11284)
|
||||
# 代理网络的地址,打开你的*学*网软件查看代理的协议(socks5/http)、地址(localhost)和端口(11284)
|
||||
proxies = {
|
||||
# [协议]:// [地址] :[端口]
|
||||
"http": "socks5h://localhost:11284",
|
||||
"https": "socks5h://localhost:11284",
|
||||
"http": "socks5h://localhost:11284", # 再例如 "http": "http://127.0.0.1:7890",
|
||||
"https": "socks5h://localhost:11284", # 再例如 "https": "http://127.0.0.1:7890",
|
||||
}
|
||||
else:
|
||||
proxies = None
|
||||
@@ -33,6 +33,7 @@ CODE_HIGHLIGHT = True
|
||||
|
||||
# 窗口布局
|
||||
LAYOUT = "LEFT-RIGHT" # "LEFT-RIGHT"(左右布局) # "TOP-DOWN"(上下布局)
|
||||
DARK_MODE = True # "LEFT-RIGHT"(左右布局) # "TOP-DOWN"(上下布局)
|
||||
|
||||
# 发送请求到OpenAI后,等待多久判定为超时
|
||||
TIMEOUT_SECONDS = 30
|
||||
@@ -53,12 +54,17 @@ LOCAL_MODEL_DEVICE = "cpu" # 可选 "cuda"
|
||||
# 设置gradio的并行线程数(不需要修改)
|
||||
CONCURRENT_COUNT = 100
|
||||
|
||||
# 加一个看板娘装饰
|
||||
ADD_WAIFU = False
|
||||
|
||||
# 设置用户名和密码(不需要修改)(相关功能不稳定,与gradio版本和网络都相关,如果本地使用不建议加这个)
|
||||
# [("username", "password"), ("username2", "password2"), ...]
|
||||
AUTHENTICATION = []
|
||||
|
||||
# 重新URL重新定向,实现更换API_URL的作用(常规情况下,不要修改!!)
|
||||
# 格式 {"https://api.openai.com/v1/chat/completions": "在这里填写重定向的api.openai.com的URL"}
|
||||
# (高危设置!通过修改此设置,您将把您的API-KEY和对话隐私完全暴露给您设定的中间人!)
|
||||
# 格式 {"https://api.openai.com/v1/chat/completions": "在这里填写重定向的api.openai.com的URL"}
|
||||
# 例如 API_URL_REDIRECT = {"https://api.openai.com/v1/chat/completions": "https://ai.open.com/api/conversation"}
|
||||
API_URL_REDIRECT = {}
|
||||
|
||||
# 如果需要在二级路径下运行(常规情况下,不要修改!!)(需要配合修改main.py才能生效!)
|
||||
@@ -68,4 +74,4 @@ CUSTOM_PATH = "/"
|
||||
NEWBING_STYLE = "creative" # ["creative", "balanced", "precise"]
|
||||
NEWBING_COOKIES = """
|
||||
your bing cookies here
|
||||
"""
|
||||
"""
|
||||
|
||||
@@ -11,7 +11,7 @@ def get_crazy_functions():
|
||||
from crazy_functions.解析项目源代码 import 解析一个C项目
|
||||
from crazy_functions.解析项目源代码 import 解析一个Golang项目
|
||||
from crazy_functions.解析项目源代码 import 解析一个Java项目
|
||||
from crazy_functions.解析项目源代码 import 解析一个Rect项目
|
||||
from crazy_functions.解析项目源代码 import 解析一个前端项目
|
||||
from crazy_functions.高级功能函数模板 import 高阶功能模板函数
|
||||
from crazy_functions.代码重写为全英文_多线程 import 全项目切换英文
|
||||
from crazy_functions.Latex全文润色 import Latex英文润色
|
||||
@@ -21,15 +21,23 @@ def get_crazy_functions():
|
||||
from crazy_functions.总结word文档 import 总结word文档
|
||||
from crazy_functions.解析JupyterNotebook import 解析ipynb文件
|
||||
from crazy_functions.对话历史存档 import 对话历史存档
|
||||
from crazy_functions.对话历史存档 import 载入对话历史存档
|
||||
from crazy_functions.对话历史存档 import 删除所有本地对话历史记录
|
||||
|
||||
from crazy_functions.批量Markdown翻译 import Markdown英译中
|
||||
function_plugins = {
|
||||
|
||||
"解析整个Python项目": {
|
||||
"Color": "stop", # 按钮颜色
|
||||
"Function": HotReload(解析一个Python项目)
|
||||
},
|
||||
"保存当前的对话": {
|
||||
"载入对话历史存档(先上传存档或输入路径)": {
|
||||
"Color": "stop",
|
||||
"AsButton":False,
|
||||
"Function": HotReload(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(请谨慎操作)": {
|
||||
"AsButton":False,
|
||||
"Function": HotReload(删除所有本地对话历史记录)
|
||||
},
|
||||
"[测试功能] 解析Jupyter Notebook文件": {
|
||||
"Color": "stop",
|
||||
@@ -62,10 +70,10 @@ def get_crazy_functions():
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(解析一个Java项目)
|
||||
},
|
||||
"解析整个React项目": {
|
||||
"解析整个前端项目(js,ts,css等)": {
|
||||
"Color": "stop", # 按钮颜色
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(解析一个Rect项目)
|
||||
"Function": HotReload(解析一个前端项目)
|
||||
},
|
||||
"解析整个Lua项目": {
|
||||
"Color": "stop", # 按钮颜色
|
||||
@@ -81,19 +89,29 @@ def get_crazy_functions():
|
||||
"Color": "stop", # 按钮颜色
|
||||
"Function": HotReload(读文章写摘要)
|
||||
},
|
||||
"Markdown/Readme英译中": {
|
||||
# HotReload 的意思是热更新,修改函数插件代码后,不需要重启程序,代码直接生效
|
||||
"Color": "stop",
|
||||
"Function": HotReload(Markdown英译中)
|
||||
},
|
||||
"批量生成函数注释": {
|
||||
"Color": "stop", # 按钮颜色
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(批量生成函数注释)
|
||||
},
|
||||
"保存当前的对话": {
|
||||
"Function": HotReload(对话历史存档)
|
||||
},
|
||||
"[多线程Demo] 解析此项目本身(源码自译解)": {
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(解析项目本身)
|
||||
},
|
||||
"[多线程demo] 把本项目源代码切换成全英文": {
|
||||
"[老旧的Demo] 把本项目源代码切换成全英文": {
|
||||
# HotReload 的意思是热更新,修改函数插件代码后,不需要重启程序,代码直接生效
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(全项目切换英文)
|
||||
},
|
||||
"[函数插件模板Demo] 历史上的今天": {
|
||||
"[插件demo] 历史上的今天": {
|
||||
# HotReload 的意思是热更新,修改函数插件代码后,不需要重启程序,代码直接生效
|
||||
"Function": HotReload(高阶功能模板函数)
|
||||
},
|
||||
@@ -110,7 +128,6 @@ def get_crazy_functions():
|
||||
from crazy_functions.Latex全文翻译 import Latex中译英
|
||||
from crazy_functions.Latex全文翻译 import Latex英译中
|
||||
from crazy_functions.批量Markdown翻译 import Markdown中译英
|
||||
from crazy_functions.批量Markdown翻译 import Markdown英译中
|
||||
|
||||
function_plugins.update({
|
||||
"批量翻译PDF文档(多线程)": {
|
||||
@@ -157,30 +174,25 @@ def get_crazy_functions():
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(Latex中文润色)
|
||||
},
|
||||
"[测试功能] Latex项目全文中译英(输入路径或上传压缩包)": {
|
||||
"Latex项目全文中译英(输入路径或上传压缩包)": {
|
||||
# HotReload 的意思是热更新,修改函数插件代码后,不需要重启程序,代码直接生效
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(Latex中译英)
|
||||
},
|
||||
"[测试功能] Latex项目全文英译中(输入路径或上传压缩包)": {
|
||||
"Latex项目全文英译中(输入路径或上传压缩包)": {
|
||||
# HotReload 的意思是热更新,修改函数插件代码后,不需要重启程序,代码直接生效
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(Latex英译中)
|
||||
},
|
||||
"[测试功能] 批量Markdown中译英(输入路径或上传压缩包)": {
|
||||
"批量Markdown中译英(输入路径或上传压缩包)": {
|
||||
# HotReload 的意思是热更新,修改函数插件代码后,不需要重启程序,代码直接生效
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(Markdown中译英)
|
||||
},
|
||||
"[测试功能] 批量Markdown英译中(输入路径或上传压缩包)": {
|
||||
# HotReload 的意思是热更新,修改函数插件代码后,不需要重启程序,代码直接生效
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(Markdown英译中)
|
||||
},
|
||||
|
||||
|
||||
})
|
||||
|
||||
|
||||
@@ -172,7 +172,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
|
||||
if max_workers == -1: # 读取配置文件
|
||||
try: max_workers, = get_conf('DEFAULT_WORKER_NUM')
|
||||
except: max_workers = 8
|
||||
if max_workers <= 0 or max_workers >= 20: max_workers = 8
|
||||
if max_workers <= 0: max_workers = 3
|
||||
# 屏蔽掉 chatglm的多线程,可能会导致严重卡顿
|
||||
if not (llm_kwargs['llm_model'].startswith('gpt-') or llm_kwargs['llm_model'].startswith('api2d-')):
|
||||
max_workers = 1
|
||||
@@ -563,3 +563,46 @@ def read_and_clean_pdf_text(fp):
|
||||
# print亮绿('***************************')
|
||||
|
||||
return meta_txt, page_one_meta
|
||||
|
||||
|
||||
def get_files_from_everything(txt, type): # type='.md'
|
||||
"""
|
||||
这个函数是用来获取指定目录下所有指定类型(如.md)的文件,并且对于网络上的文件,也可以获取它。
|
||||
下面是对每个参数和返回值的说明:
|
||||
参数
|
||||
- txt: 路径或网址,表示要搜索的文件或者文件夹路径或网络上的文件。
|
||||
- type: 字符串,表示要搜索的文件类型。默认是.md。
|
||||
返回值
|
||||
- success: 布尔值,表示函数是否成功执行。
|
||||
- file_manifest: 文件路径列表,里面包含以指定类型为后缀名的所有文件的绝对路径。
|
||||
- project_folder: 字符串,表示文件所在的文件夹路径。如果是网络上的文件,就是临时文件夹的路径。
|
||||
该函数详细注释已添加,请确认是否满足您的需要。
|
||||
"""
|
||||
import glob, os
|
||||
|
||||
success = True
|
||||
if txt.startswith('http'):
|
||||
# 网络的远程文件
|
||||
import requests
|
||||
from toolbox import get_conf
|
||||
proxies, = get_conf('proxies')
|
||||
r = requests.get(txt, proxies=proxies)
|
||||
with open('./gpt_log/temp'+type, 'wb+') as f: f.write(r.content)
|
||||
project_folder = './gpt_log/'
|
||||
file_manifest = ['./gpt_log/temp'+type]
|
||||
elif txt.endswith(type):
|
||||
# 直接给定文件
|
||||
file_manifest = [txt]
|
||||
project_folder = os.path.dirname(txt)
|
||||
elif os.path.exists(txt):
|
||||
# 本地路径,递归搜索
|
||||
project_folder = txt
|
||||
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*'+type, recursive=True)]
|
||||
if len(file_manifest) == 0:
|
||||
success = False
|
||||
else:
|
||||
project_folder = None
|
||||
file_manifest = []
|
||||
success = False
|
||||
|
||||
return success, file_manifest, project_folder
|
||||
|
||||
@@ -1,7 +1,8 @@
|
||||
from toolbox import CatchException, update_ui
|
||||
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||
import re
|
||||
|
||||
def write_chat_to_file(chatbot, file_name=None):
|
||||
def write_chat_to_file(chatbot, history=None, file_name=None):
|
||||
"""
|
||||
将对话记录history以Markdown格式写入文件中。如果没有指定文件名,则使用当前时间生成文件名。
|
||||
"""
|
||||
@@ -11,20 +12,62 @@ def write_chat_to_file(chatbot, file_name=None):
|
||||
file_name = 'chatGPT对话历史' + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.html'
|
||||
os.makedirs('./gpt_log/', exist_ok=True)
|
||||
with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
|
||||
from theme import advanced_css
|
||||
f.write(f'<!DOCTYPE html><head><meta charset="utf-8"><title>对话历史</title><style>{advanced_css}</style></head>')
|
||||
for i, contents in enumerate(chatbot):
|
||||
for content in contents:
|
||||
for j, content in enumerate(contents):
|
||||
try: # 这个bug没找到触发条件,暂时先这样顶一下
|
||||
if type(content) != str: content = str(content)
|
||||
except:
|
||||
continue
|
||||
f.write(content)
|
||||
f.write('\n\n')
|
||||
if j == 0:
|
||||
f.write('<hr style="border-top: dotted 3px #ccc;">')
|
||||
f.write('<hr color="red"> \n\n')
|
||||
|
||||
f.write('<hr color="blue"> \n\n raw chat context:\n')
|
||||
f.write('<code>')
|
||||
for h in history:
|
||||
f.write("\n>>>" + h)
|
||||
f.write('</code>')
|
||||
res = '对话历史写入:' + os.path.abspath(f'./gpt_log/{file_name}')
|
||||
print(res)
|
||||
return res
|
||||
|
||||
def gen_file_preview(file_name):
|
||||
try:
|
||||
with open(file_name, 'r', encoding='utf8') as f:
|
||||
file_content = f.read()
|
||||
# pattern to match the text between <head> and </head>
|
||||
pattern = re.compile(r'<head>.*?</head>', flags=re.DOTALL)
|
||||
file_content = re.sub(pattern, '', file_content)
|
||||
html, history = file_content.split('<hr color="blue"> \n\n raw chat context:\n')
|
||||
history = history.strip('<code>')
|
||||
history = history.strip('</code>')
|
||||
history = history.split("\n>>>")
|
||||
return list(filter(lambda x:x!="", history))[0][:100]
|
||||
except:
|
||||
return ""
|
||||
|
||||
def read_file_to_chat(chatbot, history, file_name):
|
||||
with open(file_name, 'r', encoding='utf8') as f:
|
||||
file_content = f.read()
|
||||
# pattern to match the text between <head> and </head>
|
||||
pattern = re.compile(r'<head>.*?</head>', flags=re.DOTALL)
|
||||
file_content = re.sub(pattern, '', file_content)
|
||||
html, history = file_content.split('<hr color="blue"> \n\n raw chat context:\n')
|
||||
history = history.strip('<code>')
|
||||
history = history.strip('</code>')
|
||||
history = history.split("\n>>>")
|
||||
history = list(filter(lambda x:x!="", history))
|
||||
html = html.split('<hr color="red"> \n\n')
|
||||
html = list(filter(lambda x:x!="", html))
|
||||
chatbot.clear()
|
||||
for i, h in enumerate(html):
|
||||
i_say, gpt_say = h.split('<hr style="border-top: dotted 3px #ccc;">')
|
||||
chatbot.append([i_say, gpt_say])
|
||||
chatbot.append([f"存档文件详情?", f"[Local Message] 载入对话{len(html)}条,上下文{len(history)}条。"])
|
||||
return chatbot, history
|
||||
|
||||
@CatchException
|
||||
def 对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
"""
|
||||
@@ -37,6 +80,64 @@ def 对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
|
||||
web_port 当前软件运行的端口号
|
||||
"""
|
||||
|
||||
chatbot.append(("保存当前对话", f"[Local Message] {write_chat_to_file(chatbot)}"))
|
||||
chatbot.append(("保存当前对话",
|
||||
f"[Local Message] {write_chat_to_file(chatbot, history)},您可以调用“载入对话历史存档”还原当下的对话。\n警告!被保存的对话历史可以被使用该系统的任何人查阅。"))
|
||||
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
|
||||
|
||||
def hide_cwd(str):
|
||||
import os
|
||||
current_path = os.getcwd()
|
||||
replace_path = "."
|
||||
return str.replace(current_path, replace_path)
|
||||
|
||||
@CatchException
|
||||
def 载入对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
"""
|
||||
txt 输入栏用户输入的文本,例如需要翻译的一段话,再例如一个包含了待处理文件的路径
|
||||
llm_kwargs gpt模型参数,如温度和top_p等,一般原样传递下去就行
|
||||
plugin_kwargs 插件模型的参数,暂时没有用武之地
|
||||
chatbot 聊天显示框的句柄,用于显示给用户
|
||||
history 聊天历史,前情提要
|
||||
system_prompt 给gpt的静默提醒
|
||||
web_port 当前软件运行的端口号
|
||||
"""
|
||||
from .crazy_utils import get_files_from_everything
|
||||
success, file_manifest, _ = get_files_from_everything(txt, type='.html')
|
||||
|
||||
if not success:
|
||||
if txt == "": txt = '空空如也的输入栏'
|
||||
import glob
|
||||
local_history = "<br/>".join(["`"+hide_cwd(f)+f" ({gen_file_preview(f)})"+"`" for f in glob.glob(f'gpt_log/**/chatGPT对话历史*.html', recursive=True)])
|
||||
chatbot.append([f"正在查找对话历史文件(html格式): {txt}", f"找不到任何html文件: {txt}。但本地存储了以下历史文件,您可以将任意一个文件路径粘贴到输入区,然后重试:<br/>{local_history}"])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
|
||||
try:
|
||||
chatbot, history = read_file_to_chat(chatbot, history, file_manifest[0])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
except:
|
||||
chatbot.append([f"载入对话历史文件", f"对话历史文件损坏!"])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
|
||||
@CatchException
|
||||
def 删除所有本地对话历史记录(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
"""
|
||||
txt 输入栏用户输入的文本,例如需要翻译的一段话,再例如一个包含了待处理文件的路径
|
||||
llm_kwargs gpt模型参数,如温度和top_p等,一般原样传递下去就行
|
||||
plugin_kwargs 插件模型的参数,暂时没有用武之地
|
||||
chatbot 聊天显示框的句柄,用于显示给用户
|
||||
history 聊天历史,前情提要
|
||||
system_prompt 给gpt的静默提醒
|
||||
web_port 当前软件运行的端口号
|
||||
"""
|
||||
|
||||
import glob, os
|
||||
local_history = "<br/>".join(["`"+hide_cwd(f)+"`" for f in glob.glob(f'gpt_log/**/chatGPT对话历史*.html', recursive=True)])
|
||||
for f in glob.glob(f'gpt_log/**/chatGPT对话历史*.html', recursive=True):
|
||||
os.remove(f)
|
||||
chatbot.append([f"删除所有历史对话文件", f"已删除<br/>{local_history}"])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
|
||||
|
||||
|
||||
@@ -84,7 +84,33 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
|
||||
def get_files_from_everything(txt):
|
||||
import glob, os
|
||||
|
||||
success = True
|
||||
if txt.startswith('http'):
|
||||
# 网络的远程文件
|
||||
txt = txt.replace("https://github.com/", "https://raw.githubusercontent.com/")
|
||||
txt = txt.replace("/blob/", "/")
|
||||
import requests
|
||||
from toolbox import get_conf
|
||||
proxies, = get_conf('proxies')
|
||||
r = requests.get(txt, proxies=proxies)
|
||||
with open('./gpt_log/temp.md', 'wb+') as f: f.write(r.content)
|
||||
project_folder = './gpt_log/'
|
||||
file_manifest = ['./gpt_log/temp.md']
|
||||
elif txt.endswith('.md'):
|
||||
# 直接给定文件
|
||||
file_manifest = [txt]
|
||||
project_folder = os.path.dirname(txt)
|
||||
elif os.path.exists(txt):
|
||||
# 本地路径,递归搜索
|
||||
project_folder = txt
|
||||
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.md', recursive=True)]
|
||||
else:
|
||||
success = False
|
||||
|
||||
return success, file_manifest, project_folder
|
||||
|
||||
|
||||
@CatchException
|
||||
@@ -98,6 +124,7 @@ def Markdown英译中(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
|
||||
# 尝试导入依赖,如果缺少依赖,则给出安装建议
|
||||
try:
|
||||
import tiktoken
|
||||
import glob, os
|
||||
except:
|
||||
report_execption(chatbot, history,
|
||||
a=f"解析项目: {txt}",
|
||||
@@ -105,19 +132,21 @@ def Markdown英译中(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
project_folder = txt
|
||||
else:
|
||||
|
||||
success, file_manifest, project_folder = get_files_from_everything(txt)
|
||||
|
||||
if not success:
|
||||
# 什么都没有
|
||||
if txt == "": txt = '空空如也的输入栏'
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.md', recursive=True)]
|
||||
|
||||
if len(file_manifest) == 0:
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
|
||||
yield from 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en->zh')
|
||||
|
||||
|
||||
@@ -135,6 +164,7 @@ def Markdown中译英(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
|
||||
# 尝试导入依赖,如果缺少依赖,则给出安装建议
|
||||
try:
|
||||
import tiktoken
|
||||
import glob, os
|
||||
except:
|
||||
report_execption(chatbot, history,
|
||||
a=f"解析项目: {txt}",
|
||||
@@ -142,18 +172,13 @@ def Markdown中译英(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
project_folder = txt
|
||||
else:
|
||||
success, file_manifest, project_folder = get_files_from_everything(txt)
|
||||
if not success:
|
||||
# 什么都没有
|
||||
if txt == "": txt = '空空如也的输入栏'
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
if txt.endswith('.md'):
|
||||
file_manifest = [txt]
|
||||
else:
|
||||
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.md', recursive=True)]
|
||||
if len(file_manifest) == 0:
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
from toolbox import update_ui
|
||||
from toolbox import CatchException, report_execption, write_results_to_file
|
||||
from .crazy_utils import input_clipping
|
||||
|
||||
def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
|
||||
import os, copy
|
||||
@@ -61,13 +62,15 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
|
||||
previous_iteration_files.extend([os.path.relpath(fp, project_folder) for index, fp in enumerate(this_iteration_file_manifest)])
|
||||
previous_iteration_files_string = ', '.join(previous_iteration_files)
|
||||
current_iteration_focus = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(this_iteration_file_manifest)])
|
||||
i_say = f'根据以上分析,对程序的整体功能和构架重新做出概括。然后用一张markdown表格整理每个文件的功能(包括{previous_iteration_files_string})。'
|
||||
i_say = f'用一张Markdown表格简要描述以下文件的功能:{previous_iteration_files_string}。根据以上分析,用一句话概括程序的整体功能。'
|
||||
inputs_show_user = f'根据以上分析,对程序的整体功能和构架重新做出概括,由于输入长度限制,可能需要分组处理,本组文件为 {current_iteration_focus} + 已经汇总的文件组。'
|
||||
this_iteration_history = copy.deepcopy(this_iteration_gpt_response_collection)
|
||||
this_iteration_history.append(last_iteration_result)
|
||||
# 裁剪input
|
||||
inputs, this_iteration_history_feed = input_clipping(inputs=i_say, history=this_iteration_history, max_token_limit=2560)
|
||||
result = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=i_say, inputs_show_user=inputs_show_user, llm_kwargs=llm_kwargs, chatbot=chatbot,
|
||||
history=this_iteration_history, # 迭代之前的分析
|
||||
inputs=inputs, inputs_show_user=inputs_show_user, llm_kwargs=llm_kwargs, chatbot=chatbot,
|
||||
history=this_iteration_history_feed, # 迭代之前的分析
|
||||
sys_prompt="你是一个程序架构分析师,正在分析一个项目的源代码。")
|
||||
report_part_2.extend([i_say, result])
|
||||
last_iteration_result = result
|
||||
@@ -180,7 +183,7 @@ def 解析一个Java项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析一个Rect项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
def 解析一个前端项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@@ -194,9 +197,15 @@ def 解析一个Rect项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.tsx', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.json', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.js', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.vue', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.less', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.sass', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.wxml', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.wxss', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.css', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.jsx', recursive=True)]
|
||||
if len(file_manifest) == 0:
|
||||
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何Rect文件: {txt}")
|
||||
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何前端相关文件: {txt}")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
|
||||
|
||||
@@ -70,6 +70,7 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
||||
# 尝试导入依赖,如果缺少依赖,则给出安装建议
|
||||
try:
|
||||
import arxiv
|
||||
import math
|
||||
from bs4 import BeautifulSoup
|
||||
except:
|
||||
report_execption(chatbot, history,
|
||||
@@ -80,23 +81,23 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
||||
|
||||
# 清空历史,以免输入溢出
|
||||
history = []
|
||||
|
||||
meta_paper_info_list = yield from get_meta_information(txt, chatbot, history)
|
||||
batchsize = 5
|
||||
for batch in range(math.ceil(len(meta_paper_info_list)/batchsize)):
|
||||
if len(meta_paper_info_list[:batchsize]) > 0:
|
||||
i_say = "下面是一些学术文献的数据,提取出以下内容:" + \
|
||||
"1、英文题目;2、中文题目翻译;3、作者;4、arxiv公开(is_paper_in_arxiv);4、引用数量(cite);5、中文摘要翻译。" + \
|
||||
f"以下是信息源:{str(meta_paper_info_list[:batchsize])}"
|
||||
|
||||
if len(meta_paper_info_list[:10]) > 0:
|
||||
i_say = "下面是一些学术文献的数据,请从中提取出以下内容。" + \
|
||||
"1、英文题目;2、中文题目翻译;3、作者;4、arxiv公开(is_paper_in_arxiv);4、引用数量(cite);5、中文摘要翻译。" + \
|
||||
f"以下是信息源:{str(meta_paper_info_list[:10])}"
|
||||
inputs_show_user = f"请分析此页面中出现的所有文章:{txt},这是第{batch+1}批"
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=i_say, inputs_show_user=inputs_show_user,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
|
||||
sys_prompt="你是一个学术翻译,请从数据中提取信息。你必须使用Markdown表格。你必须逐个文献进行处理。"
|
||||
)
|
||||
|
||||
inputs_show_user = f"请分析此页面中出现的所有文章:{txt}"
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=i_say, inputs_show_user=inputs_show_user,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
|
||||
sys_prompt="你是一个学术翻译,请从数据中提取信息。你必须使用Markdown格式。你必须逐个文献进行处理。"
|
||||
)
|
||||
|
||||
history.extend([ "第一批", gpt_say ])
|
||||
meta_paper_info_list = meta_paper_info_list[10:]
|
||||
history.extend([ f"第{batch+1}批", gpt_say ])
|
||||
meta_paper_info_list = meta_paper_info_list[batchsize:]
|
||||
|
||||
chatbot.append(["状态?",
|
||||
"已经全部完成,您可以试试让AI写一个Related Works,例如您可以继续输入Write a \"Related Works\" section about \"你搜索的研究领域\" for me."])
|
||||
|
||||
122
docker-compose.yml
普通文件
122
docker-compose.yml
普通文件
@@ -0,0 +1,122 @@
|
||||
【请在修改完参数后,删除此行】请在以下方案中选择一种,然后删除其他的方案,最后docker-compose up运行
|
||||
|
||||
## ===================================================
|
||||
## 【方案一】 如果不需要运行本地模型(仅chatgpt类远程服务)
|
||||
## ===================================================
|
||||
version: '3'
|
||||
services:
|
||||
gpt_academic_nolocalllms:
|
||||
image: fuqingxu/gpt_academic:no-local-llms
|
||||
environment:
|
||||
# 请查阅 `config.py` 以查看所有的配置信息
|
||||
API_KEY: ' sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx '
|
||||
USE_PROXY: ' True '
|
||||
proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
|
||||
LLM_MODEL: ' gpt-3.5-turbo '
|
||||
AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "api2d-gpt-4"] '
|
||||
DEFAULT_WORKER_NUM: ' 10 '
|
||||
WEB_PORT: ' 22303 '
|
||||
ADD_WAIFU: ' True '
|
||||
AUTHENTICATION: ' [("username", "passwd"), ("username2", "passwd2")] '
|
||||
|
||||
# 与宿主的网络融合
|
||||
network_mode: "host"
|
||||
|
||||
# 不使用代理网络拉取最新代码
|
||||
command: >
|
||||
bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
|
||||
git checkout master --force &&
|
||||
git remote set-url origin https://github.com/binary-husky/chatgpt_academic.git &&
|
||||
git pull &&
|
||||
python3 -u main.py"
|
||||
|
||||
|
||||
### ===================================================
|
||||
### 【方案二】 如果需要运行ChatGLM本地模型
|
||||
### ===================================================
|
||||
version: '3'
|
||||
services:
|
||||
gpt_academic_with_chatglm:
|
||||
image: fuqingxu/gpt_academic:chatgpt-chatglm-newbing # [option 2] 如果需要运行ChatGLM本地模型
|
||||
environment:
|
||||
# 请查阅 `config.py` 以查看所有的配置信息
|
||||
API_KEY: ' sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx '
|
||||
USE_PROXY: ' True '
|
||||
proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
|
||||
LLM_MODEL: ' gpt-3.5-turbo '
|
||||
AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "api2d-gpt-4", "chatglm"] '
|
||||
LOCAL_MODEL_DEVICE: ' cuda '
|
||||
DEFAULT_WORKER_NUM: ' 10 '
|
||||
WEB_PORT: ' 12303 '
|
||||
ADD_WAIFU: ' True '
|
||||
AUTHENTICATION: ' [("username", "passwd"), ("username2", "passwd2")] '
|
||||
|
||||
# 显卡的使用,nvidia0指第0个GPU
|
||||
runtime: nvidia
|
||||
devices:
|
||||
- /dev/nvidia0:/dev/nvidia0
|
||||
|
||||
# 与宿主的网络融合
|
||||
network_mode: "host"
|
||||
|
||||
# 使用代理网络拉取最新代码
|
||||
# command: >
|
||||
# bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
|
||||
# truncate -s -1 /etc/proxychains.conf &&
|
||||
# echo \"socks5 127.0.0.1 10880\" >> /etc/proxychains.conf &&
|
||||
# proxychains git pull &&
|
||||
# python3 -u main.py "
|
||||
|
||||
# 不使用代理网络拉取最新代码
|
||||
command: >
|
||||
bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
|
||||
git pull &&
|
||||
python3 -u main.py"
|
||||
|
||||
|
||||
### ===================================================
|
||||
### 【方案三】 如果需要运行ChatGPT + LLAMA + 盘古 + RWKV本地模型
|
||||
### ===================================================
|
||||
version: '3'
|
||||
services:
|
||||
gpt_academic_with_rwkv:
|
||||
image: fuqingxu/gpt_academic:jittorllms # [option 2] 如果需要运行ChatGLM本地模型
|
||||
environment:
|
||||
# 请查阅 `config.py` 以查看所有的配置信息
|
||||
API_KEY: ' sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx '
|
||||
USE_PROXY: ' True '
|
||||
proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
|
||||
LLM_MODEL: ' gpt-3.5-turbo '
|
||||
AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "api2d-gpt-4", "jittorllms_rwkv"] '
|
||||
LOCAL_MODEL_DEVICE: ' cuda '
|
||||
DEFAULT_WORKER_NUM: ' 10 '
|
||||
WEB_PORT: ' 12305 '
|
||||
ADD_WAIFU: ' True '
|
||||
# AUTHENTICATION: ' [("username", "passwd"), ("username2", "passwd2")] '
|
||||
|
||||
# 显卡的使用,nvidia0指第0个GPU
|
||||
runtime: nvidia
|
||||
devices:
|
||||
- /dev/nvidia0:/dev/nvidia0
|
||||
|
||||
# 与宿主的网络融合
|
||||
network_mode: "host"
|
||||
|
||||
# 使用代理网络拉取最新代码
|
||||
# command: >
|
||||
# bash -c " truncate -s -1 /etc/proxychains.conf &&
|
||||
# echo \"socks5 127.0.0.1 10880\" >> /etc/proxychains.conf &&
|
||||
# echo '[gpt-academic] 正在从github拉取最新代码...' &&
|
||||
# proxychains git pull &&
|
||||
# echo '[jittorllms] 正在从github拉取最新代码...' &&
|
||||
# proxychains git --git-dir=request_llm/jittorllms/.git --work-tree=request_llm/jittorllms pull --force &&
|
||||
# python3 -u main.py"
|
||||
|
||||
# 不使用代理网络拉取最新代码
|
||||
|
||||
command: >
|
||||
bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
|
||||
git pull &&
|
||||
echo '[jittorllms] 正在从github拉取最新代码...' &&
|
||||
git --git-dir=request_llm/jittorllms/.git --work-tree=request_llm/jittorllms pull --force &&
|
||||
python3 -u main.py"
|
||||
@@ -1,6 +1,6 @@
|
||||
# How to build | 如何构建: docker build -t gpt-academic --network=host -f Dockerfile+ChatGLM .
|
||||
# How to run | 如何运行 (1) 直接运行(选择0号GPU): docker run --rm -it --net=host --gpus="0" gpt-academic
|
||||
# How to run | 如何运行 (2) 我想运行之前进容器做一些调整: docker run --rm -it --net=host --gpus="0" gpt-academic bash
|
||||
# How to run | (1) 我想直接一键运行(选择0号GPU): docker run --rm -it --net=host --gpus \"device=0\" gpt-academic
|
||||
# How to run | (2) 我想运行之前进容器做一些调整(选择1号GPU): docker run --rm -it --net=host --gpus \"device=1\" gpt-academic bash
|
||||
|
||||
# 从NVIDIA源,从而支持显卡运损(检查宿主的nvidia-smi中的cuda版本必须>=11.3)
|
||||
FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
|
||||
@@ -14,6 +14,7 @@ RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
|
||||
RUN $useProxyNetwork curl cip.cc
|
||||
RUN sed -i '$ d' /etc/proxychains.conf
|
||||
RUN sed -i '$ d' /etc/proxychains.conf
|
||||
# 在这里填写主机的代理协议(用于从github拉取代码)
|
||||
RUN echo "socks5 127.0.0.1 10880" >> /etc/proxychains.conf
|
||||
ARG useProxyNetwork=proxychains
|
||||
# # comment out above if you do not need proxy network | 如果不需要翻墙 - 从此行向上删除
|
||||
@@ -21,14 +22,15 @@ ARG useProxyNetwork=proxychains
|
||||
|
||||
# use python3 as the system default python
|
||||
RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
|
||||
|
||||
# 下载pytorch
|
||||
RUN $useProxyNetwork python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
|
||||
# 下载分支
|
||||
WORKDIR /gpt
|
||||
RUN $useProxyNetwork git clone https://github.com/binary-husky/chatgpt_academic.git
|
||||
WORKDIR /gpt/chatgpt_academic
|
||||
RUN $useProxyNetwork python3 -m pip install -r requirements.txt
|
||||
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_chatglm.txt
|
||||
RUN $useProxyNetwork python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
|
||||
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_newbing.txt
|
||||
|
||||
# 预热CHATGLM参数(非必要 可选步骤)
|
||||
RUN echo ' \n\
|
||||
@@ -48,6 +50,7 @@ RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
|
||||
# 可同时填写多个API-KEY,支持openai的key和api2d的key共存,用英文逗号分割,例如API_KEY = "sk-openaikey1,fkxxxx-api2dkey2,........"
|
||||
# LLM_MODEL 是选择初始的模型
|
||||
# LOCAL_MODEL_DEVICE 是选择chatglm等本地模型运行的设备,可选 cpu 和 cuda
|
||||
# [说明: 以下内容与`config.py`一一对应,请查阅config.py来完成一下配置的填写]
|
||||
RUN echo ' \n\
|
||||
API_KEY = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \n\
|
||||
USE_PROXY = True \n\
|
||||
|
||||
@@ -157,7 +157,7 @@
|
||||
|
||||
## [22/31] 请对下面的程序文件做一个概述: H:\chatgpt_academic_resolve\crazy_functions\解析项目源代码.py
|
||||
|
||||
这个程序文件实现了对一个源代码项目进行分析的功能。其中,函数`解析项目本身`、`解析一个Python项目`、`解析一个C项目的头文件`、`解析一个C项目`、`解析一个Java项目`和`解析一个Rect项目`分别用于解析不同类型的项目。函数`解析源代码新`实现了对每一个源代码文件的分析,并将分析结果汇总,同时还实现了分组和迭代处理,提高了效率。最后,函数`write_results_to_file`将所有分析结果写入文件。中间,还用到了`request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency`和`request_gpt_model_in_new_thread_with_ui_alive`来完成请求和响应,并用`update_ui`实时更新界面。
|
||||
这个程序文件实现了对一个源代码项目进行分析的功能。其中,函数`解析项目本身`、`解析一个Python项目`、`解析一个C项目的头文件`、`解析一个C项目`、`解析一个Java项目`和`解析前端项目`分别用于解析不同类型的项目。函数`解析源代码新`实现了对每一个源代码文件的分析,并将分析结果汇总,同时还实现了分组和迭代处理,提高了效率。最后,函数`write_results_to_file`将所有分析结果写入文件。中间,还用到了`request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency`和`request_gpt_model_in_new_thread_with_ui_alive`来完成请求和响应,并用`update_ui`实时更新界面。
|
||||
|
||||
## [23/31] 请对下面的程序文件做一个概述: H:\chatgpt_academic_resolve\crazy_functions\询问多个大语言模型.py
|
||||
|
||||
|
||||
130
docs/test_markdown_format.py
普通文件
130
docs/test_markdown_format.py
普通文件
@@ -0,0 +1,130 @@
|
||||
sample = """
|
||||
[1]: https://baike.baidu.com/item/%E8%B4%A8%E8%83%BD%E6%96%B9%E7%A8%8B/1884527 "质能方程(质能方程式)_百度百科"
|
||||
[2]: https://www.zhihu.com/question/348249281 "如何理解质能方程 E=mc²? - 知乎"
|
||||
[3]: https://zhuanlan.zhihu.com/p/32597385 "质能方程的推导与理解 - 知乎 - 知乎专栏"
|
||||
|
||||
你好,这是必应。质能方程是描述质量与能量之间的当量关系的方程[^1^][1]。用tex格式,质能方程可以写成$$E=mc^2$$,其中$E$是能量,$m$是质量,$c$是光速[^2^][2] [^3^][3]。
|
||||
"""
|
||||
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
|
||||
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>'
|
||||
return result
|
||||
|
||||
|
||||
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:
|
||||
# print('输出代码片段中!')
|
||||
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>'
|
||||
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,
|
||||
},
|
||||
}
|
||||
find_equation_pattern = r'<script type="math/tex(?:.*?)>(.*?)</script>'
|
||||
|
||||
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$包裹begin命令时多余<script>)
|
||||
"""
|
||||
content = content.replace('<script type="math/tex">\n<script type="math/tex; mode=display">', '<script type="math/tex; mode=display">')
|
||||
content = content.replace('</script>\n</script>', '</script>')
|
||||
return content
|
||||
|
||||
|
||||
if ('$' 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)
|
||||
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)
|
||||
# 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=['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("""
|
||||
|
||||
<head>
|
||||
<title>My Website</title>
|
||||
<link rel="stylesheet" type="text/css" href="style.css">
|
||||
</head>
|
||||
|
||||
""")
|
||||
f.write(sample)
|
||||
23
docs/waifu_plugin/autoload.js
普通文件
23
docs/waifu_plugin/autoload.js
普通文件
@@ -0,0 +1,23 @@
|
||||
try {
|
||||
$("<link>").attr({href: "file=docs/waifu_plugin/waifu.css", rel: "stylesheet", type: "text/css"}).appendTo('head');
|
||||
$('body').append('<div class="waifu"><div class="waifu-tips"></div><canvas id="live2d" class="live2d"></canvas><div class="waifu-tool"><span class="fui-home"></span> <span class="fui-chat"></span> <span class="fui-eye"></span> <span class="fui-user"></span> <span class="fui-photo"></span> <span class="fui-info-circle"></span> <span class="fui-cross"></span></div></div>');
|
||||
$.ajax({url: "file=docs/waifu_plugin/waifu-tips.js", dataType:"script", cache: true, success: function() {
|
||||
$.ajax({url: "file=docs/waifu_plugin/live2d.js", dataType:"script", cache: true, success: function() {
|
||||
/* 可直接修改部分参数 */
|
||||
live2d_settings['hitokotoAPI'] = "hitokoto.cn"; // 一言 API
|
||||
live2d_settings['modelId'] = 5; // 默认模型 ID
|
||||
live2d_settings['modelTexturesId'] = 1; // 默认材质 ID
|
||||
live2d_settings['modelStorage'] = false; // 不储存模型 ID
|
||||
live2d_settings['waifuSize'] = '210x187';
|
||||
live2d_settings['waifuTipsSize'] = '187x52';
|
||||
live2d_settings['canSwitchModel'] = true;
|
||||
live2d_settings['canSwitchTextures'] = true;
|
||||
live2d_settings['canSwitchHitokoto'] = false;
|
||||
live2d_settings['canTakeScreenshot'] = false;
|
||||
live2d_settings['canTurnToHomePage'] = false;
|
||||
live2d_settings['canTurnToAboutPage'] = false;
|
||||
/* 在 initModel 前添加 */
|
||||
initModel("file=docs/waifu_plugin/waifu-tips.json");
|
||||
}});
|
||||
}});
|
||||
} catch(err) { console.log("[Error] JQuery is not defined.") }
|
||||
二进制文件未显示。
@@ -0,0 +1,126 @@
|
||||
<?xml version="1.0" standalone="no"?>
|
||||
<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd" >
|
||||
<svg xmlns="http://www.w3.org/2000/svg">
|
||||
<metadata>
|
||||
<json>
|
||||
{
|
||||
"fontFamily": "flat-ui-icons",
|
||||
"majorVersion": 1,
|
||||
"minorVersion": 1,
|
||||
"fontURL": "http://designmodo.com/flat",
|
||||
"designer": "Sergey Shmidt",
|
||||
"designerURL": "http://designmodo.com",
|
||||
"license": "Attribution-NonCommercial-NoDerivs 3.0 Unported",
|
||||
"licenseURL": "http://creativecommons.org/licenses/by-nc-nd/3.0/",
|
||||
"version": "Version 1.1",
|
||||
"fontId": "flat-ui-icons",
|
||||
"psName": "flat-ui-icons",
|
||||
"subFamily": "Regular",
|
||||
"fullName": "flat-ui-icons",
|
||||
"description": "Generated by IcoMoon"
|
||||
}
|
||||
</json>
|
||||
</metadata>
|
||||
<defs>
|
||||
<font id="flat-ui-icons" horiz-adv-x="1024">
|
||||
<font-face units-per-em="1024" ascent="960" descent="-64" />
|
||||
<missing-glyph horiz-adv-x="1024" />
|
||||
<glyph unicode=" " d="" horiz-adv-x="512" />
|
||||
<glyph unicode="" d="M896 192l-384 512-384-512h768z" />
|
||||
<glyph unicode="" d="M128 704l384-512 384 512h-768z" />
|
||||
<glyph unicode="" d="M896 256h-768l384 384 384-384z" />
|
||||
<glyph unicode="" d="M512 256l-384 384h768l-384-384z" />
|
||||
<glyph unicode="" d="M896 0l-768 448 768 448v-896z" />
|
||||
<glyph unicode="" d="M128 896l768-448-768-448v896z" />
|
||||
<glyph unicode="" d="M224.96 448.768l447.168 447.232 128-131.008-321.152-318.016 321.152-320.896-128.256-128.256-446.912 450.944z" />
|
||||
<glyph unicode="" d="M353.152-2.112l-128.192 128.256 321.088 320.896-321.152 317.952 128 131.008 447.168-447.232-446.912-450.88z" />
|
||||
<glyph unicode="" d="M928 351.936h-320v-319.936c0-35.392-28.608-64-64-64h-64c-35.328 0-64 28.608-64 64v319.936h-320c-35.328 0-64 28.736-64 64.064v64.064c0 35.328 28.672 63.872 64 63.872h320v320.064c0 35.328 28.672 64 64 64h64c35.392 0 64-28.672 64-64v-320.064h320c35.392 0 64-28.544 64-63.872v-64.064c0-35.328-28.608-64.064-64-64.064z" />
|
||||
<glyph unicode="" d="M919.808 764.032c12.48-12.416 12.48-32.832 0-45.248l-248.896-249.024c-12.352-12.416-12.352-32.832 0-45.312l248.768-249.088c12.48-12.416 12.48-32.832 0-45.248l-90.624-90.432c-12.352-12.416-32.768-12.416-45.248 0l-248.64 249.088c-12.416 12.416-32.832 12.416-45.248 0l-248.896-248.896c-12.416-12.48-32.832-12.48-45.248 0l-90.496 90.624c-12.416 12.352-12.416 32.768 0 45.248l248.96 248.896c12.416 12.416 12.416 32.832 0 45.312l-248.768 249.024c-12.416 12.48-12.416 32.832 0 45.248l90.56 90.496c12.416 12.416 32.832 12.416 45.248 0l248.64-249.024c12.416-12.48 32.832-12.48 45.248-0.064l248.832 248.96c12.48 12.352 32.896 12.352 45.248 0l90.56-90.56z" />
|
||||
<glyph unicode="" d="M923.136 822.592c-12.352 12.544-32.768 12.544-45.12 0l-476.16-474.496c-12.48-12.544-32.832-12.544-45.248 0l-208.64 212.736c-6.144 6.208-14.272 9.408-22.336 9.472-8.256 0-16.576-3.008-22.848-9.472l-92.16-83.008c-6.144-6.272-9.472-14.144-9.472-22.336 0-8.32 3.328-17.024 9.472-23.232l210.368-220.992c12.416-12.48 32.832-33.024 45.248-45.632l90.432-91.264c12.416-12.48 32.768-12.48 45.248 0l611.712 611.328c12.48 12.48 12.48 33.088 0 45.632l-90.496 91.264z" />
|
||||
<glyph unicode="" d="M512 960c-281.6 0-512-230.4-512-512s230.4-512 512-512 512 230.4 512 512c0 281.6-230.4 512-512 512zM512 140.8c-168.96 0-307.2 138.24-307.2 307.2s138.24 307.2 307.2 307.2c168.96 0 307.2-138.24 307.2-307.2 0-168.96-138.24-307.2-307.2-307.2z" />
|
||||
<glyph unicode="" d="M512 960c-281.6 0-512-230.4-512-512s230.4-512 512-512 512 230.4 512 512c0 281.6-230.4 512-512 512zM512 140.8c-168.96 0-307.2 138.24-307.2 307.2s138.24 307.2 307.2 307.2c168.96 0 307.2-138.24 307.2-307.2 0-168.96-138.24-307.2-307.2-307.2zM512 601.6c-87.040 0-153.6-66.56-153.6-153.6s66.56-153.6 153.6-153.6 153.6 66.56 153.6 153.6c0 87.040-66.56 153.6-153.6 153.6z" />
|
||||
<glyph unicode="" d="M256 960h512c143.36 0 256-112.64 256-256v-512c0-143.36-112.64-256-256-256h-512c-143.36 0-256 112.64-256 256v512c0 143.36 112.64 256 256 256z" />
|
||||
<glyph unicode="" d="M768 960h-512c-143.36 0-256-112.64-256-256v-512c0-143.36 112.64-256 256-256h512c143.36 0 256 112.64 256 256v512c0 143.36-112.64 256-256 256zM844.8 550.4l-368.64-368.64c-5.12-5.12-20.48-5.12-25.6 0l-56.32 56.32c-5.12 5.12-20.48 20.48-25.6 25.6l-128 133.12c-5.12 5.12-5.12 10.24-5.12 15.36s0 10.24 5.12 15.36l56.32 51.2c5.12 0 10.24 5.12 10.24 5.12 5.12 0 10.24 0 15.36-5.12l122.88-128c5.12-5.12 20.48-5.12 25.6 0l286.72 286.72c5.12 5.12 20.48 5.12 25.6 0l56.32-56.32c10.24-10.24 10.24-20.48 5.12-30.72z" />
|
||||
<glyph unicode="" d="M512 960c-282.752 0-512-229.248-512-512 0-282.688 229.248-512 512-512 282.816 0 512 229.248 512 512 0 282.752-229.184 512-512 512zM576.768 195.136c0-37.056-28.992-67.072-64.768-67.072s-64.768 30.016-64.768 67.072v313.088c0 37.056 28.992 67.072 64.768 67.072s64.768-30.016 64.768-67.072v-313.088zM512 640.32c-35.776 0-64.768 28.608-64.768 63.872s28.992 63.744 64.768 63.744 64.768-28.544 64.768-63.808-28.992-63.808-64.768-63.808z" />
|
||||
<glyph unicode="" d="M512 960c-282.752 0-512-229.248-512-512s229.248-512 512-512c282.752 0 512 229.248 512 512 0 282.752-229.248 512-512 512zM512 128.064c-35.776 0-64.768 28.544-64.768 63.808 0 35.2 28.992 63.808 64.768 63.808 35.776 0 64.768-28.608 64.768-63.808 0-35.264-28.992-63.808-64.768-63.808zM576.768 387.776c0-37.056-28.992-67.072-64.768-67.072-35.776 0-64.768 30.080-64.768 67.072v313.088c0 37.056 28.992 67.072 64.768 67.072 35.776 0 64.768-30.080 64.768-67.072v-313.088z" />
|
||||
<glyph unicode="" d="M512-64c-282.752 0-512 229.248-512 512 0 282.688 229.248 512 512 512 282.752 0 512-229.248 512-512 0-282.752-229.248-512-512-512zM512 128.064c35.776 0 64.768 28.544 64.768 63.808 0 35.2-28.992 63.808-64.768 63.808-35.776 0-64.768-28.608-64.768-63.808 0-35.264 28.992-63.808 64.768-63.808zM650.752 724.288c-33.92 27.904-82.24 43.456-140.032 43.456-42.56 0-78.912-7.68-110.144-20.16-16.576-6.72-69.632-39.68-80.64-48.896l32.384-48.32c5.312-9.344 13.952-14.080 25.92-14.080 4.992 0 10.624 1.984 16.96 5.888 4.608 2.88 41.088 21.696 56.512 26.368 32.32 9.6 67.84 5.696 84.16 0.64 22.272-6.848 38.4-19.904 47.36-37.76 5.888-11.776 13.376-44.16-4.224-74.432-14.656-25.088-37.568-44.16-62.848-61.056-13.504-9.216-26.048-18.624-37.376-28.416-0.512 0-1.792-0.96-4.672-3.52 1.408 1.216 3.264 2.304 4.672 3.52 3.2 0.128-30.784-43.328-30.784-83.52 0-42.88 0-64 0-64h128v64c0 33.28 16.128 51.968 16.448 56.704 11.008 7.872 61.056 46.144 72.96 59.904 22.208 25.6 38.592 59.392 38.592 107.008 0 48.832-19.392 88.832-53.248 116.672z" />
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</font></defs></svg>
|
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|
之后 宽度: | 高度: | 大小: 56 KiB |
二进制文件未显示。
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docs/waifu_plugin/jquery-ui.min.js
vendored
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docs/waifu_plugin/jquery-ui.min.js
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4
docs/waifu_plugin/jquery.min.js
vendored
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4
docs/waifu_plugin/jquery.min.js
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文件差异因一行或多行过长而隐藏
4238
docs/waifu_plugin/live2d.js
普通文件
4238
docs/waifu_plugin/live2d.js
普通文件
文件差异内容过多而无法显示
加载差异
1
docs/waifu_plugin/source
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1
docs/waifu_plugin/source
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@@ -0,0 +1 @@
|
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https://github.com/fghrsh/live2d_demo
|
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405
docs/waifu_plugin/waifu-tips.js
普通文件
405
docs/waifu_plugin/waifu-tips.js
普通文件
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|
||||
window.live2d_settings = Array(); /*
|
||||
|
||||
く__,.ヘヽ. / ,ー、 〉
|
||||
\ ', !-─‐-i / /´
|
||||
/`ー' L//`ヽ、 Live2D 看板娘 参数设置
|
||||
/ /, /| , , ', Version 1.4.2
|
||||
イ / /-‐/ i L_ ハ ヽ! i Update 2018.11.12
|
||||
レ ヘ 7イ`ト レ'ァ-ト、!ハ| |
|
||||
!,/7 '0' ´0iソ| |
|
||||
|.从" _ ,,,, / |./ | 网页添加 Live2D 看板娘
|
||||
レ'| i>.、,,__ _,.イ / .i | https://www.fghrsh.net/post/123.html
|
||||
レ'| | / k_7_/レ'ヽ, ハ. |
|
||||
| |/i 〈|/ i ,.ヘ | i | Thanks
|
||||
.|/ / i: ヘ! \ | journey-ad / https://github.com/journey-ad/live2d_src
|
||||
kヽ>、ハ _,.ヘ、 /、! xiazeyu / https://github.com/xiazeyu/live2d-widget.js
|
||||
!'〈//`T´', \ `'7'ーr' Live2d Cubism SDK WebGL 2.1 Projrct & All model authors.
|
||||
レ'ヽL__|___i,___,ンレ|ノ
|
||||
ト-,/ |___./
|
||||
'ー' !_,.:*********************************************************************************/
|
||||
|
||||
|
||||
// 后端接口
|
||||
live2d_settings['modelAPI'] = '//live2d.fghrsh.net/api/'; // 自建 API 修改这里
|
||||
live2d_settings['tipsMessage'] = 'waifu-tips.json'; // 同目录下可省略路径
|
||||
live2d_settings['hitokotoAPI'] = 'lwl12.com'; // 一言 API,可选 'lwl12.com', 'hitokoto.cn', 'jinrishici.com'(古诗词)
|
||||
|
||||
// 默认模型
|
||||
live2d_settings['modelId'] = 1; // 默认模型 ID,可在 F12 控制台找到
|
||||
live2d_settings['modelTexturesId'] = 53; // 默认材质 ID,可在 F12 控制台找到
|
||||
|
||||
// 工具栏设置
|
||||
live2d_settings['showToolMenu'] = true; // 显示 工具栏 ,可选 true(真), false(假)
|
||||
live2d_settings['canCloseLive2d'] = true; // 显示 关闭看板娘 按钮,可选 true(真), false(假)
|
||||
live2d_settings['canSwitchModel'] = true; // 显示 模型切换 按钮,可选 true(真), false(假)
|
||||
live2d_settings['canSwitchTextures'] = true; // 显示 材质切换 按钮,可选 true(真), false(假)
|
||||
live2d_settings['canSwitchHitokoto'] = true; // 显示 一言切换 按钮,可选 true(真), false(假)
|
||||
live2d_settings['canTakeScreenshot'] = true; // 显示 看板娘截图 按钮,可选 true(真), false(假)
|
||||
live2d_settings['canTurnToHomePage'] = true; // 显示 返回首页 按钮,可选 true(真), false(假)
|
||||
live2d_settings['canTurnToAboutPage'] = true; // 显示 跳转关于页 按钮,可选 true(真), false(假)
|
||||
|
||||
// 模型切换模式
|
||||
live2d_settings['modelStorage'] = true; // 记录 ID (刷新后恢复),可选 true(真), false(假)
|
||||
live2d_settings['modelRandMode'] = 'switch'; // 模型切换,可选 'rand'(随机), 'switch'(顺序)
|
||||
live2d_settings['modelTexturesRandMode']= 'rand'; // 材质切换,可选 'rand'(随机), 'switch'(顺序)
|
||||
|
||||
// 提示消息选项
|
||||
live2d_settings['showHitokoto'] = true; // 显示一言
|
||||
live2d_settings['showF12Status'] = true; // 显示加载状态
|
||||
live2d_settings['showF12Message'] = false; // 显示看板娘消息
|
||||
live2d_settings['showF12OpenMsg'] = true; // 显示控制台打开提示
|
||||
live2d_settings['showCopyMessage'] = true; // 显示 复制内容 提示
|
||||
live2d_settings['showWelcomeMessage'] = true; // 显示进入面页欢迎词
|
||||
|
||||
//看板娘样式设置
|
||||
live2d_settings['waifuSize'] = '280x250'; // 看板娘大小,例如 '280x250', '600x535'
|
||||
live2d_settings['waifuTipsSize'] = '250x70'; // 提示框大小,例如 '250x70', '570x150'
|
||||
live2d_settings['waifuFontSize'] = '12px'; // 提示框字体,例如 '12px', '30px'
|
||||
live2d_settings['waifuToolFont'] = '14px'; // 工具栏字体,例如 '14px', '36px'
|
||||
live2d_settings['waifuToolLine'] = '20px'; // 工具栏行高,例如 '20px', '36px'
|
||||
live2d_settings['waifuToolTop'] = '0px' // 工具栏顶部边距,例如 '0px', '-60px'
|
||||
live2d_settings['waifuMinWidth'] = '768px'; // 面页小于 指定宽度 隐藏看板娘,例如 'disable'(禁用), '768px'
|
||||
live2d_settings['waifuEdgeSide'] = 'left:0'; // 看板娘贴边方向,例如 'left:0'(靠左 0px), 'right:30'(靠右 30px)
|
||||
live2d_settings['waifuDraggable'] = 'disable'; // 拖拽样式,例如 'disable'(禁用), 'axis-x'(只能水平拖拽), 'unlimited'(自由拖拽)
|
||||
live2d_settings['waifuDraggableRevert'] = true; // 松开鼠标还原拖拽位置,可选 true(真), false(假)
|
||||
|
||||
// 其他杂项设置
|
||||
live2d_settings['l2dVersion'] = '1.4.2'; // 当前版本
|
||||
live2d_settings['l2dVerDate'] = '2018.11.12'; // 版本更新日期
|
||||
live2d_settings['homePageUrl'] = 'auto'; // 主页地址,可选 'auto'(自动), '{URL 网址}'
|
||||
live2d_settings['aboutPageUrl'] = 'https://www.fghrsh.net/post/123.html'; // 关于页地址, '{URL 网址}'
|
||||
live2d_settings['screenshotCaptureName']= 'live2d.png'; // 看板娘截图文件名,例如 'live2d.png'
|
||||
|
||||
/****************************************************************************************************/
|
||||
|
||||
String.prototype.render = function(context) {
|
||||
var tokenReg = /(\\)?\{([^\{\}\\]+)(\\)?\}/g;
|
||||
|
||||
return this.replace(tokenReg, function (word, slash1, token, slash2) {
|
||||
if (slash1 || slash2) { return word.replace('\\', ''); }
|
||||
|
||||
var variables = token.replace(/\s/g, '').split('.');
|
||||
var currentObject = context;
|
||||
var i, length, variable;
|
||||
|
||||
for (i = 0, length = variables.length; i < length; ++i) {
|
||||
variable = variables[i];
|
||||
currentObject = currentObject[variable];
|
||||
if (currentObject === undefined || currentObject === null) return '';
|
||||
}
|
||||
return currentObject;
|
||||
});
|
||||
};
|
||||
|
||||
var re = /x/;
|
||||
console.log(re);
|
||||
|
||||
function empty(obj) {return typeof obj=="undefined"||obj==null||obj==""?true:false}
|
||||
function getRandText(text) {return Array.isArray(text) ? text[Math.floor(Math.random() * text.length + 1)-1] : text}
|
||||
|
||||
function showMessage(text, timeout, flag) {
|
||||
if(flag || sessionStorage.getItem('waifu-text') === '' || sessionStorage.getItem('waifu-text') === null){
|
||||
if(Array.isArray(text)) text = text[Math.floor(Math.random() * text.length + 1)-1];
|
||||
if (live2d_settings.showF12Message) console.log('[Message]', text.replace(/<[^<>]+>/g,''));
|
||||
|
||||
if(flag) sessionStorage.setItem('waifu-text', text);
|
||||
|
||||
$('.waifu-tips').stop();
|
||||
$('.waifu-tips').html(text).fadeTo(200, 1);
|
||||
if (timeout === undefined) timeout = 5000;
|
||||
hideMessage(timeout);
|
||||
}
|
||||
}
|
||||
|
||||
function hideMessage(timeout) {
|
||||
$('.waifu-tips').stop().css('opacity',1);
|
||||
if (timeout === undefined) timeout = 5000;
|
||||
window.setTimeout(function() {sessionStorage.removeItem('waifu-text')}, timeout);
|
||||
$('.waifu-tips').delay(timeout).fadeTo(200, 0);
|
||||
}
|
||||
|
||||
function initModel(waifuPath, type) {
|
||||
/* console welcome message */
|
||||
eval(function(p,a,c,k,e,r){e=function(c){return(c<a?'':e(parseInt(c/a)))+((c=c%a)>35?String.fromCharCode(c+29):c.toString(36))};if(!''.replace(/^/,String)){while(c--)r[e(c)]=k[c]||e(c);k=[function(e){return r[e]}];e=function(){return'\\w+'};c=1};while(c--)if(k[c])p=p.replace(new RegExp('\\b'+e(c)+'\\b','g'),k[c]);return p}('8.d(" ");8.d("\\U,.\\y\\5.\\1\\1\\1\\1/\\1,\\u\\2 \\H\\n\\1\\1\\1\\1\\1\\b \', !-\\r\\j-i\\1/\\1/\\g\\n\\1\\1\\1 \\1 \\a\\4\\f\'\\1\\1\\1 L/\\a\\4\\5\\2\\n\\1\\1 \\1 /\\1 \\a,\\1 /|\\1 ,\\1 ,\\1\\1\\1 \',\\n\\1\\1\\1\\q \\1/ /-\\j/\\1\\h\\E \\9 \\5!\\1 i\\n\\1\\1\\1 \\3 \\6 7\\q\\4\\c\\1 \\3\'\\s-\\c\\2!\\t|\\1 |\\n\\1\\1\\1\\1 !,/7 \'0\'\\1\\1 \\X\\w| \\1 |\\1\\1\\1\\n\\1\\1\\1\\1 |.\\x\\"\\1\\l\\1\\1 ,,,, / |./ \\1 |\\n\\1\\1\\1\\1 \\3\'| i\\z.\\2,,A\\l,.\\B / \\1.i \\1|\\n\\1\\1\\1\\1\\1 \\3\'| | / C\\D/\\3\'\\5,\\1\\9.\\1|\\n\\1\\1\\1\\1\\1\\1 | |/i \\m|/\\1 i\\1,.\\6 |\\F\\1|\\n\\1\\1\\1\\1\\1\\1.|/ /\\1\\h\\G \\1 \\6!\\1\\1\\b\\1|\\n\\1\\1\\1 \\1 \\1 k\\5>\\2\\9 \\1 o,.\\6\\2 \\1 /\\2!\\n\\1\\1\\1\\1\\1\\1 !\'\\m//\\4\\I\\g\', \\b \\4\'7\'\\J\'\\n\\1\\1\\1\\1\\1\\1 \\3\'\\K|M,p,\\O\\3|\\P\\n\\1\\1\\1\\1\\1 \\1\\1\\1\\c-,/\\1|p./\\n\\1\\1\\1\\1\\1 \\1\\1\\1\'\\f\'\\1\\1!o,.:\\Q \\R\\S\\T v"+e.V+" / W "+e.N);8.d(" ");',60,60,'|u3000|uff64|uff9a|uff40|u30fd|uff8d||console|uff8a|uff0f|uff3c|uff84|log|live2d_settings|uff70|u00b4|uff49||u2010||u3000_|u3008||_|___|uff72|u2500|uff67|u30cf|u30fc||u30bd|u4ece|u30d8|uff1e|__|u30a4|k_|uff17_|u3000L_|u3000i|uff1a|u3009|uff34|uff70r|u30fdL__||___i|l2dVerDate|u30f3|u30ce|nLive2D|u770b|u677f|u5a18|u304f__|l2dVersion|FGHRSH|u00b40i'.split('|'),0,{}));
|
||||
|
||||
/* 判断 JQuery */
|
||||
if (typeof($.ajax) != 'function') typeof(jQuery.ajax) == 'function' ? window.$ = jQuery : console.log('[Error] JQuery is not defined.');
|
||||
|
||||
/* 加载看板娘样式 */
|
||||
live2d_settings.waifuSize = live2d_settings.waifuSize.split('x');
|
||||
live2d_settings.waifuTipsSize = live2d_settings.waifuTipsSize.split('x');
|
||||
live2d_settings.waifuEdgeSide = live2d_settings.waifuEdgeSide.split(':');
|
||||
|
||||
$("#live2d").attr("width",live2d_settings.waifuSize[0]);
|
||||
$("#live2d").attr("height",live2d_settings.waifuSize[1]);
|
||||
$(".waifu-tips").width(live2d_settings.waifuTipsSize[0]);
|
||||
$(".waifu-tips").height(live2d_settings.waifuTipsSize[1]);
|
||||
$(".waifu-tips").css("top",live2d_settings.waifuToolTop);
|
||||
$(".waifu-tips").css("font-size",live2d_settings.waifuFontSize);
|
||||
$(".waifu-tool").css("font-size",live2d_settings.waifuToolFont);
|
||||
$(".waifu-tool span").css("line-height",live2d_settings.waifuToolLine);
|
||||
|
||||
if (live2d_settings.waifuEdgeSide[0] == 'left') $(".waifu").css("left",live2d_settings.waifuEdgeSide[1]+'px');
|
||||
else if (live2d_settings.waifuEdgeSide[0] == 'right') $(".waifu").css("right",live2d_settings.waifuEdgeSide[1]+'px');
|
||||
|
||||
window.waifuResize = function() { $(window).width() <= Number(live2d_settings.waifuMinWidth.replace('px','')) ? $(".waifu").hide() : $(".waifu").show(); };
|
||||
if (live2d_settings.waifuMinWidth != 'disable') { waifuResize(); $(window).resize(function() {waifuResize()}); }
|
||||
|
||||
try {
|
||||
if (live2d_settings.waifuDraggable == 'axis-x') $(".waifu").draggable({ axis: "x", revert: live2d_settings.waifuDraggableRevert });
|
||||
else if (live2d_settings.waifuDraggable == 'unlimited') $(".waifu").draggable({ revert: live2d_settings.waifuDraggableRevert });
|
||||
else $(".waifu").css("transition", 'all .3s ease-in-out');
|
||||
} catch(err) { console.log('[Error] JQuery UI is not defined.') }
|
||||
|
||||
live2d_settings.homePageUrl = live2d_settings.homePageUrl == 'auto' ? window.location.protocol+'//'+window.location.hostname+'/' : live2d_settings.homePageUrl;
|
||||
if (window.location.protocol == 'file:' && live2d_settings.modelAPI.substr(0,2) == '//') live2d_settings.modelAPI = 'http:'+live2d_settings.modelAPI;
|
||||
|
||||
$('.waifu-tool .fui-home').click(function (){
|
||||
//window.location = 'https://www.fghrsh.net/';
|
||||
window.location = live2d_settings.homePageUrl;
|
||||
});
|
||||
|
||||
$('.waifu-tool .fui-info-circle').click(function (){
|
||||
//window.open('https://imjad.cn/archives/lab/add-dynamic-poster-girl-with-live2d-to-your-blog-02');
|
||||
window.open(live2d_settings.aboutPageUrl);
|
||||
});
|
||||
|
||||
if (typeof(waifuPath) == "object") loadTipsMessage(waifuPath); else {
|
||||
$.ajax({
|
||||
cache: true,
|
||||
url: waifuPath == '' ? live2d_settings.tipsMessage : (waifuPath.substr(waifuPath.length-15)=='waifu-tips.json'?waifuPath:waifuPath+'waifu-tips.json'),
|
||||
dataType: "json",
|
||||
success: function (result){ loadTipsMessage(result); }
|
||||
});
|
||||
}
|
||||
|
||||
if (!live2d_settings.showToolMenu) $('.waifu-tool').hide();
|
||||
if (!live2d_settings.canCloseLive2d) $('.waifu-tool .fui-cross').hide();
|
||||
if (!live2d_settings.canSwitchModel) $('.waifu-tool .fui-eye').hide();
|
||||
if (!live2d_settings.canSwitchTextures) $('.waifu-tool .fui-user').hide();
|
||||
if (!live2d_settings.canSwitchHitokoto) $('.waifu-tool .fui-chat').hide();
|
||||
if (!live2d_settings.canTakeScreenshot) $('.waifu-tool .fui-photo').hide();
|
||||
if (!live2d_settings.canTurnToHomePage) $('.waifu-tool .fui-home').hide();
|
||||
if (!live2d_settings.canTurnToAboutPage) $('.waifu-tool .fui-info-circle').hide();
|
||||
|
||||
if (waifuPath === undefined) waifuPath = '';
|
||||
var modelId = localStorage.getItem('modelId');
|
||||
var modelTexturesId = localStorage.getItem('modelTexturesId');
|
||||
|
||||
if (!live2d_settings.modelStorage || modelId == null) {
|
||||
var modelId = live2d_settings.modelId;
|
||||
var modelTexturesId = live2d_settings.modelTexturesId;
|
||||
} loadModel(modelId, modelTexturesId);
|
||||
}
|
||||
|
||||
function loadModel(modelId, modelTexturesId=0) {
|
||||
if (live2d_settings.modelStorage) {
|
||||
localStorage.setItem('modelId', modelId);
|
||||
localStorage.setItem('modelTexturesId', modelTexturesId);
|
||||
} else {
|
||||
sessionStorage.setItem('modelId', modelId);
|
||||
sessionStorage.setItem('modelTexturesId', modelTexturesId);
|
||||
} loadlive2d('live2d', live2d_settings.modelAPI+'get/?id='+modelId+'-'+modelTexturesId, (live2d_settings.showF12Status ? console.log('[Status]','live2d','模型',modelId+'-'+modelTexturesId,'加载完成'):null));
|
||||
}
|
||||
|
||||
function loadTipsMessage(result) {
|
||||
window.waifu_tips = result;
|
||||
|
||||
$.each(result.mouseover, function (index, tips){
|
||||
$(document).on("mouseover", tips.selector, function (){
|
||||
var text = getRandText(tips.text);
|
||||
text = text.render({text: $(this).text()});
|
||||
showMessage(text, 3000);
|
||||
});
|
||||
});
|
||||
$.each(result.click, function (index, tips){
|
||||
$(document).on("click", tips.selector, function (){
|
||||
var text = getRandText(tips.text);
|
||||
text = text.render({text: $(this).text()});
|
||||
showMessage(text, 3000, true);
|
||||
});
|
||||
});
|
||||
$.each(result.seasons, function (index, tips){
|
||||
var now = new Date();
|
||||
var after = tips.date.split('-')[0];
|
||||
var before = tips.date.split('-')[1] || after;
|
||||
|
||||
if((after.split('/')[0] <= now.getMonth()+1 && now.getMonth()+1 <= before.split('/')[0]) &&
|
||||
(after.split('/')[1] <= now.getDate() && now.getDate() <= before.split('/')[1])){
|
||||
var text = getRandText(tips.text);
|
||||
text = text.render({year: now.getFullYear()});
|
||||
showMessage(text, 6000, true);
|
||||
}
|
||||
});
|
||||
|
||||
if (live2d_settings.showF12OpenMsg) {
|
||||
re.toString = function() {
|
||||
showMessage(getRandText(result.waifu.console_open_msg), 5000, true);
|
||||
return '';
|
||||
};
|
||||
}
|
||||
|
||||
if (live2d_settings.showCopyMessage) {
|
||||
$(document).on('copy', function() {
|
||||
showMessage(getRandText(result.waifu.copy_message), 5000, true);
|
||||
});
|
||||
}
|
||||
|
||||
$('.waifu-tool .fui-photo').click(function(){
|
||||
showMessage(getRandText(result.waifu.screenshot_message), 5000, true);
|
||||
window.Live2D.captureName = live2d_settings.screenshotCaptureName;
|
||||
window.Live2D.captureFrame = true;
|
||||
});
|
||||
|
||||
$('.waifu-tool .fui-cross').click(function(){
|
||||
sessionStorage.setItem('waifu-dsiplay', 'none');
|
||||
showMessage(getRandText(result.waifu.hidden_message), 1300, true);
|
||||
window.setTimeout(function() {$('.waifu').hide();}, 1300);
|
||||
});
|
||||
|
||||
window.showWelcomeMessage = function(result) {
|
||||
var text;
|
||||
if (window.location.href == live2d_settings.homePageUrl) {
|
||||
var now = (new Date()).getHours();
|
||||
if (now > 23 || now <= 5) text = getRandText(result.waifu.hour_tips['t23-5']);
|
||||
else if (now > 5 && now <= 7) text = getRandText(result.waifu.hour_tips['t5-7']);
|
||||
else if (now > 7 && now <= 11) text = getRandText(result.waifu.hour_tips['t7-11']);
|
||||
else if (now > 11 && now <= 14) text = getRandText(result.waifu.hour_tips['t11-14']);
|
||||
else if (now > 14 && now <= 17) text = getRandText(result.waifu.hour_tips['t14-17']);
|
||||
else if (now > 17 && now <= 19) text = getRandText(result.waifu.hour_tips['t17-19']);
|
||||
else if (now > 19 && now <= 21) text = getRandText(result.waifu.hour_tips['t19-21']);
|
||||
else if (now > 21 && now <= 23) text = getRandText(result.waifu.hour_tips['t21-23']);
|
||||
else text = getRandText(result.waifu.hour_tips.default);
|
||||
} else {
|
||||
var referrer_message = result.waifu.referrer_message;
|
||||
if (document.referrer !== '') {
|
||||
var referrer = document.createElement('a');
|
||||
referrer.href = document.referrer;
|
||||
var domain = referrer.hostname.split('.')[1];
|
||||
if (window.location.hostname == referrer.hostname)
|
||||
text = referrer_message.localhost[0] + document.title.split(referrer_message.localhost[2])[0] + referrer_message.localhost[1];
|
||||
else if (domain == 'baidu')
|
||||
text = referrer_message.baidu[0] + referrer.search.split('&wd=')[1].split('&')[0] + referrer_message.baidu[1];
|
||||
else if (domain == 'so')
|
||||
text = referrer_message.so[0] + referrer.search.split('&q=')[1].split('&')[0] + referrer_message.so[1];
|
||||
else if (domain == 'google')
|
||||
text = referrer_message.google[0] + document.title.split(referrer_message.google[2])[0] + referrer_message.google[1];
|
||||
else {
|
||||
$.each(result.waifu.referrer_hostname, function(i,val) {if (i==referrer.hostname) referrer.hostname = getRandText(val)});
|
||||
text = referrer_message.default[0] + referrer.hostname + referrer_message.default[1];
|
||||
}
|
||||
} else text = referrer_message.none[0] + document.title.split(referrer_message.none[2])[0] + referrer_message.none[1];
|
||||
}
|
||||
showMessage(text, 6000);
|
||||
}; if (live2d_settings.showWelcomeMessage) showWelcomeMessage(result);
|
||||
|
||||
var waifu_tips = result.waifu;
|
||||
|
||||
function loadOtherModel() {
|
||||
var modelId = modelStorageGetItem('modelId');
|
||||
var modelRandMode = live2d_settings.modelRandMode;
|
||||
|
||||
$.ajax({
|
||||
cache: modelRandMode == 'switch' ? true : false,
|
||||
url: live2d_settings.modelAPI+modelRandMode+'/?id='+modelId,
|
||||
dataType: "json",
|
||||
success: function(result) {
|
||||
loadModel(result.model['id']);
|
||||
var message = result.model['message'];
|
||||
$.each(waifu_tips.model_message, function(i,val) {if (i==result.model['id']) message = getRandText(val)});
|
||||
showMessage(message, 3000, true);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
function loadRandTextures() {
|
||||
var modelId = modelStorageGetItem('modelId');
|
||||
var modelTexturesId = modelStorageGetItem('modelTexturesId');
|
||||
var modelTexturesRandMode = live2d_settings.modelTexturesRandMode;
|
||||
|
||||
$.ajax({
|
||||
cache: modelTexturesRandMode == 'switch' ? true : false,
|
||||
url: live2d_settings.modelAPI+modelTexturesRandMode+'_textures/?id='+modelId+'-'+modelTexturesId,
|
||||
dataType: "json",
|
||||
success: function(result) {
|
||||
if (result.textures['id'] == 1 && (modelTexturesId == 1 || modelTexturesId == 0))
|
||||
showMessage(waifu_tips.load_rand_textures[0], 3000, true);
|
||||
else showMessage(waifu_tips.load_rand_textures[1], 3000, true);
|
||||
loadModel(modelId, result.textures['id']);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
function modelStorageGetItem(key) { return live2d_settings.modelStorage ? localStorage.getItem(key) : sessionStorage.getItem(key); }
|
||||
|
||||
/* 检测用户活动状态,并在空闲时显示一言 */
|
||||
if (live2d_settings.showHitokoto) {
|
||||
window.getActed = false; window.hitokotoTimer = 0; window.hitokotoInterval = false;
|
||||
$(document).mousemove(function(e){getActed = true;}).keydown(function(){getActed = true;});
|
||||
setInterval(function(){ if (!getActed) ifActed(); else elseActed(); }, 1000);
|
||||
}
|
||||
|
||||
function ifActed() {
|
||||
if (!hitokotoInterval) {
|
||||
hitokotoInterval = true;
|
||||
hitokotoTimer = window.setInterval(showHitokotoActed, 30000);
|
||||
}
|
||||
}
|
||||
|
||||
function elseActed() {
|
||||
getActed = hitokotoInterval = false;
|
||||
window.clearInterval(hitokotoTimer);
|
||||
}
|
||||
|
||||
function showHitokotoActed() {
|
||||
if ($(document)[0].visibilityState == 'visible') showHitokoto();
|
||||
}
|
||||
|
||||
function showHitokoto() {
|
||||
switch(live2d_settings.hitokotoAPI) {
|
||||
case 'lwl12.com':
|
||||
$.getJSON('https://api.lwl12.com/hitokoto/v1?encode=realjson',function(result){
|
||||
if (!empty(result.source)) {
|
||||
var text = waifu_tips.hitokoto_api_message['lwl12.com'][0];
|
||||
if (!empty(result.author)) text += waifu_tips.hitokoto_api_message['lwl12.com'][1];
|
||||
text = text.render({source: result.source, creator: result.author});
|
||||
window.setTimeout(function() {showMessage(text+waifu_tips.hitokoto_api_message['lwl12.com'][2], 3000, true);}, 5000);
|
||||
} showMessage(result.text, 5000, true);
|
||||
});break;
|
||||
case 'fghrsh.net':
|
||||
$.getJSON('https://api.fghrsh.net/hitokoto/rand/?encode=jsc&uid=3335',function(result){
|
||||
if (!empty(result.source)) {
|
||||
var text = waifu_tips.hitokoto_api_message['fghrsh.net'][0];
|
||||
text = text.render({source: result.source, date: result.date});
|
||||
window.setTimeout(function() {showMessage(text, 3000, true);}, 5000);
|
||||
showMessage(result.hitokoto, 5000, true);
|
||||
}
|
||||
});break;
|
||||
case 'jinrishici.com':
|
||||
$.ajax({
|
||||
url: 'https://v2.jinrishici.com/one.json',
|
||||
xhrFields: {withCredentials: true},
|
||||
success: function (result, status) {
|
||||
if (!empty(result.data.origin.title)) {
|
||||
var text = waifu_tips.hitokoto_api_message['jinrishici.com'][0];
|
||||
text = text.render({title: result.data.origin.title, dynasty: result.data.origin.dynasty, author:result.data.origin.author});
|
||||
window.setTimeout(function() {showMessage(text, 3000, true);}, 5000);
|
||||
} showMessage(result.data.content, 5000, true);
|
||||
}
|
||||
});break;
|
||||
default:
|
||||
$.getJSON('https://v1.hitokoto.cn',function(result){
|
||||
if (!empty(result.from)) {
|
||||
var text = waifu_tips.hitokoto_api_message['hitokoto.cn'][0];
|
||||
text = text.render({source: result.from, creator: result.creator});
|
||||
window.setTimeout(function() {showMessage(text, 3000, true);}, 5000);
|
||||
}
|
||||
showMessage(result.hitokoto, 5000, true);
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
$('.waifu-tool .fui-eye').click(function (){loadOtherModel()});
|
||||
$('.waifu-tool .fui-user').click(function (){loadRandTextures()});
|
||||
$('.waifu-tool .fui-chat').click(function (){showHitokoto()});
|
||||
}
|
||||
116
docs/waifu_plugin/waifu-tips.json
普通文件
116
docs/waifu_plugin/waifu-tips.json
普通文件
@@ -0,0 +1,116 @@
|
||||
{
|
||||
"waifu": {
|
||||
"console_open_msg": ["哈哈,你打开了控制台,是想要看看我的秘密吗?"],
|
||||
"copy_message": ["你都复制了些什么呀,转载要记得加上出处哦"],
|
||||
"screenshot_message": ["照好了嘛,是不是很可爱呢?"],
|
||||
"hidden_message": ["我们还能再见面的吧…"],
|
||||
"load_rand_textures": ["我还没有其他衣服呢", "我的新衣服好看嘛"],
|
||||
"hour_tips": {
|
||||
"t0-5": ["快睡觉去吧,年纪轻轻小心猝死哦"],
|
||||
"t5-7": ["早上好!一日之计在于晨,美好的一天就要开始了"],
|
||||
"t7-11": ["上午好!工作顺利嘛,不要久坐,多起来走动走动哦!"],
|
||||
"t11-14": ["中午了,工作了一个上午,现在是午餐时间!"],
|
||||
"t14-17": ["午后很容易犯困呢,今天的运动目标完成了吗?"],
|
||||
"t17-19": ["傍晚了!窗外夕阳的景色很美丽呢,最美不过夕阳红~"],
|
||||
"t19-21": ["晚上好,今天过得怎么样?"],
|
||||
"t21-23": ["已经这么晚了呀,早点休息吧,晚安~"],
|
||||
"t23-24": ["你是夜猫子呀?这么晚还不睡觉,明天起的来嘛"],
|
||||
"default": ["嗨~ 快来逗我玩吧!"]
|
||||
},
|
||||
"referrer_message": {
|
||||
"localhost": ["欢迎使用<span style=\"color:rgba(245, 20, 20, 0.62);\">『ChatGPT", "』</span>", " - "],
|
||||
"baidu": ["Hello! 来自 百度搜索 的朋友<br>你是搜索 <span style=\"color:rgba(245, 20, 20, 0.62);\">", "</span> 找到的我吗?"],
|
||||
"so": ["Hello! 来自 360搜索 的朋友<br>你是搜索 <span style=\"color:rgba(245, 20, 20, 0.62);\">", "</span> 找到的我吗?"],
|
||||
"google": ["Hello! 来自 谷歌搜索 的朋友<br>欢迎使用<span style=\"color:rgba(245, 20, 20, 0.62);\">『ChatGPT", "』</span>", " - "],
|
||||
"default": ["Hello! 来自 <span style=\"color:rgba(245, 20, 20, 0.62);\">", "</span> 的朋友"],
|
||||
"none": ["欢迎使用<span style=\"color:rgba(245, 20, 20, 0.62);\">『ChatGPT", "』</span>", " - "]
|
||||
},
|
||||
"referrer_hostname": {
|
||||
"example.com": ["示例网站"],
|
||||
"www.fghrsh.net": ["FGHRSH 的博客"]
|
||||
},
|
||||
"model_message": {
|
||||
"1": ["来自 Potion Maker 的 Pio 酱 ~"],
|
||||
"2": ["来自 Potion Maker 的 Tia 酱 ~"]
|
||||
},
|
||||
"hitokoto_api_message": {
|
||||
"lwl12.com": ["这句一言来自 <span style=\"color:#0099cc;\">『{source}』</span>", ",是 <span style=\"color:#0099cc;\">{creator}</span> 投稿的", "。"],
|
||||
"fghrsh.net": ["这句一言出处是 <span style=\"color:#0099cc;\">『{source}』</span>,是 <span style=\"color:#0099cc;\">FGHRSH</span> 在 {date} 收藏的!"],
|
||||
"jinrishici.com": ["这句诗词出自 <span style=\"color:#0099cc;\">《{title}》</span>,是 {dynasty}诗人 {author} 创作的!"],
|
||||
"hitokoto.cn": ["这句一言来自 <span style=\"color:#0099cc;\">『{source}』</span>,是 <span style=\"color:#0099cc;\">{creator}</span> 在 hitokoto.cn 投稿的。"]
|
||||
}
|
||||
},
|
||||
"mouseover": [
|
||||
{ "selector": ".container a[href^='http']", "text": ["要看看 <span style=\"color:#0099cc;\">{text}</span> 么?"] },
|
||||
{ "selector": ".fui-home", "text": ["点击前往首页,想回到上一页可以使用浏览器的后退功能哦"] },
|
||||
{ "selector": ".fui-chat", "text": ["一言一语,一颦一笑。一字一句,一颗赛艇。"] },
|
||||
{ "selector": ".fui-eye", "text": ["嗯··· 要切换 看板娘 吗?"] },
|
||||
{ "selector": ".fui-user", "text": ["喜欢换装 Play 吗?"] },
|
||||
{ "selector": ".fui-photo", "text": ["要拍张纪念照片吗?"] },
|
||||
{ "selector": ".fui-info-circle", "text": ["这里有关于我的信息呢"] },
|
||||
{ "selector": ".fui-cross", "text": ["你不喜欢我了吗..."] },
|
||||
{ "selector": "#tor_show", "text": ["翻页比较麻烦吗,点击可以显示这篇文章的目录呢"] },
|
||||
{ "selector": "#comment_go", "text": ["想要去评论些什么吗?"] },
|
||||
{ "selector": "#night_mode", "text": ["深夜时要爱护眼睛呀"] },
|
||||
{ "selector": "#qrcode", "text": ["手机扫一下就能继续看,很方便呢"] },
|
||||
{ "selector": ".comment_reply", "text": ["要吐槽些什么呢"] },
|
||||
{ "selector": "#back-to-top", "text": ["回到开始的地方吧"] },
|
||||
{ "selector": "#author", "text": ["该怎么称呼你呢"] },
|
||||
{ "selector": "#mail", "text": ["留下你的邮箱,不然就是无头像人士了"] },
|
||||
{ "selector": "#url", "text": ["你的家在哪里呢,好让我去参观参观"] },
|
||||
{ "selector": "#textarea", "text": ["认真填写哦,垃圾评论是禁止事项"] },
|
||||
{ "selector": ".OwO-logo", "text": ["要插入一个表情吗"] },
|
||||
{ "selector": "#csubmit", "text": ["要[提交]^(Commit)了吗,首次评论需要审核,请耐心等待~"] },
|
||||
{ "selector": ".ImageBox", "text": ["点击图片可以放大呢"] },
|
||||
{ "selector": "input[name=s]", "text": ["找不到想看的内容?搜索看看吧"] },
|
||||
{ "selector": ".previous", "text": ["去上一页看看吧"] },
|
||||
{ "selector": ".next", "text": ["去下一页看看吧"] },
|
||||
{ "selector": ".dropdown-toggle", "text": ["这里是菜单"] },
|
||||
{ "selector": "c-player a.play-icon", "text": ["想要听点音乐吗"] },
|
||||
{ "selector": "c-player div.time", "text": ["在这里可以调整<span style=\"color:#0099cc;\">播放进度</span>呢"] },
|
||||
{ "selector": "c-player div.volume", "text": ["在这里可以调整<span style=\"color:#0099cc;\">音量</span>呢"] },
|
||||
{ "selector": "c-player div.list-button", "text": ["<span style=\"color:#0099cc;\">播放列表</span>里都有什么呢"] },
|
||||
{ "selector": "c-player div.lyric-button", "text": ["有<span style=\"color:#0099cc;\">歌词</span>的话就能跟着一起唱呢"] },
|
||||
{ "selector": ".waifu #live2d", "text": [
|
||||
"别玩了,快去学习!",
|
||||
"偶尔放松下眼睛吧。",
|
||||
"看什么看(*^▽^*)",
|
||||
"焦虑时,吃顿大餐心情就好啦^_^",
|
||||
"你这个年纪,怎么睡得着觉的你^_^",
|
||||
"修改ADD_WAIFU=False,我就不再打扰你了~",
|
||||
"经常去github看看我们的更新吧,也许有好玩的新功能呢。",
|
||||
"试试本地大模型吧,有的也很强大的哦。",
|
||||
"很多强大的函数插件隐藏在下拉菜单中呢。",
|
||||
"红色的插件,使用之前需要把文件上传进去哦。",
|
||||
"想添加功能按钮吗?读读readme很容易就学会啦。",
|
||||
"敏感或机密的信息,不可以问chatGPT的哦!",
|
||||
"chatGPT究竟是划时代的创新,还是扼杀创造力的毒药呢?"
|
||||
] }
|
||||
],
|
||||
"click": [
|
||||
{
|
||||
"selector": ".waifu #live2d",
|
||||
"text": [
|
||||
"是…是不小心碰到了吧",
|
||||
"萝莉控是什么呀",
|
||||
"你看到我的小熊了吗",
|
||||
"再摸的话我可要报警了!⌇●﹏●⌇",
|
||||
"110吗,这里有个变态一直在摸我(ó﹏ò。)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"seasons": [
|
||||
{ "date": "01/01", "text": ["<span style=\"color:#0099cc;\">元旦</span>了呢,新的一年又开始了,今年是{year}年~"] },
|
||||
{ "date": "02/14", "text": ["又是一年<span style=\"color:#0099cc;\">情人节</span>,{year}年找到对象了嘛~"] },
|
||||
{ "date": "03/08", "text": ["今天是<span style=\"color:#0099cc;\">妇女节</span>!"] },
|
||||
{ "date": "03/12", "text": ["今天是<span style=\"color:#0099cc;\">植树节</span>,要保护环境呀"] },
|
||||
{ "date": "04/01", "text": ["悄悄告诉你一个秘密~<span style=\"background-color:#34495e;\">今天是愚人节,不要被骗了哦~</span>"] },
|
||||
{ "date": "05/01", "text": ["今天是<span style=\"color:#0099cc;\">五一劳动节</span>,计划好假期去哪里了吗~"] },
|
||||
{ "date": "06/01", "text": ["<span style=\"color:#0099cc;\">儿童节</span>了呢,快活的时光总是短暂,要是永远长不大该多好啊…"] },
|
||||
{ "date": "09/03", "text": ["<span style=\"color:#0099cc;\">中国人民抗日战争胜利纪念日</span>,铭记历史、缅怀先烈、珍爱和平、开创未来。"] },
|
||||
{ "date": "09/10", "text": ["<span style=\"color:#0099cc;\">教师节</span>,在学校要给老师问声好呀~"] },
|
||||
{ "date": "10/01", "text": ["<span style=\"color:#0099cc;\">国庆节</span>,新中国已经成立69年了呢"] },
|
||||
{ "date": "11/05-11/12", "text": ["今年的<span style=\"color:#0099cc;\">双十一</span>是和谁一起过的呢~"] },
|
||||
{ "date": "12/20-12/31", "text": ["这几天是<span style=\"color:#0099cc;\">圣诞节</span>,主人肯定又去剁手买买买了~"] }
|
||||
]
|
||||
}
|
||||
290
docs/waifu_plugin/waifu.css
普通文件
290
docs/waifu_plugin/waifu.css
普通文件
@@ -0,0 +1,290 @@
|
||||
.waifu {
|
||||
position: fixed;
|
||||
bottom: 0;
|
||||
z-index: 1;
|
||||
font-size: 0;
|
||||
-webkit-transform: translateY(3px);
|
||||
transform: translateY(3px);
|
||||
}
|
||||
.waifu:hover {
|
||||
-webkit-transform: translateY(0);
|
||||
transform: translateY(0);
|
||||
}
|
||||
.waifu-tips {
|
||||
opacity: 0;
|
||||
margin: -20px 20px;
|
||||
padding: 5px 10px;
|
||||
border: 1px solid rgba(224, 186, 140, 0.62);
|
||||
border-radius: 12px;
|
||||
background-color: rgba(236, 217, 188, 0.5);
|
||||
box-shadow: 0 3px 15px 2px rgba(191, 158, 118, 0.2);
|
||||
text-overflow: ellipsis;
|
||||
overflow: hidden;
|
||||
position: absolute;
|
||||
animation-delay: 5s;
|
||||
animation-duration: 50s;
|
||||
animation-iteration-count: infinite;
|
||||
animation-name: shake;
|
||||
animation-timing-function: ease-in-out;
|
||||
}
|
||||
.waifu-tool {
|
||||
display: none;
|
||||
color: #aaa;
|
||||
top: 50px;
|
||||
right: 10px;
|
||||
position: absolute;
|
||||
}
|
||||
.waifu:hover .waifu-tool {
|
||||
display: block;
|
||||
}
|
||||
.waifu-tool span {
|
||||
display: block;
|
||||
cursor: pointer;
|
||||
color: #5b6c7d;
|
||||
transition: 0.2s;
|
||||
}
|
||||
.waifu-tool span:hover {
|
||||
color: #34495e;
|
||||
}
|
||||
.waifu #live2d{
|
||||
position: relative;
|
||||
}
|
||||
|
||||
@keyframes shake {
|
||||
2% {
|
||||
transform: translate(0.5px, -1.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
4% {
|
||||
transform: translate(0.5px, 1.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
6% {
|
||||
transform: translate(1.5px, 1.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
8% {
|
||||
transform: translate(2.5px, 1.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
10% {
|
||||
transform: translate(0.5px, 2.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
12% {
|
||||
transform: translate(1.5px, 1.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
14% {
|
||||
transform: translate(0.5px, 0.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
16% {
|
||||
transform: translate(-1.5px, -0.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
18% {
|
||||
transform: translate(0.5px, 0.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
20% {
|
||||
transform: translate(2.5px, 2.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
22% {
|
||||
transform: translate(0.5px, -1.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
24% {
|
||||
transform: translate(-1.5px, 1.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
26% {
|
||||
transform: translate(1.5px, 0.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
28% {
|
||||
transform: translate(-0.5px, -0.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
30% {
|
||||
transform: translate(1.5px, -0.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
32% {
|
||||
transform: translate(2.5px, -1.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
34% {
|
||||
transform: translate(2.5px, 2.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
36% {
|
||||
transform: translate(0.5px, -1.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
38% {
|
||||
transform: translate(2.5px, -0.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
40% {
|
||||
transform: translate(-0.5px, 2.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
42% {
|
||||
transform: translate(-1.5px, 2.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
44% {
|
||||
transform: translate(-1.5px, 1.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
46% {
|
||||
transform: translate(1.5px, -0.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
48% {
|
||||
transform: translate(2.5px, -0.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
50% {
|
||||
transform: translate(-1.5px, 1.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
52% {
|
||||
transform: translate(-0.5px, 1.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
54% {
|
||||
transform: translate(-1.5px, 1.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
56% {
|
||||
transform: translate(0.5px, 2.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
58% {
|
||||
transform: translate(2.5px, 2.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
60% {
|
||||
transform: translate(2.5px, -1.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
62% {
|
||||
transform: translate(-1.5px, 0.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
64% {
|
||||
transform: translate(-1.5px, 1.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
66% {
|
||||
transform: translate(0.5px, 2.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
68% {
|
||||
transform: translate(2.5px, -1.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
70% {
|
||||
transform: translate(2.5px, 2.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
72% {
|
||||
transform: translate(-0.5px, -1.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
74% {
|
||||
transform: translate(-1.5px, 2.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
76% {
|
||||
transform: translate(-1.5px, 2.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
78% {
|
||||
transform: translate(-1.5px, 2.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
80% {
|
||||
transform: translate(-1.5px, 0.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
82% {
|
||||
transform: translate(-1.5px, 0.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
84% {
|
||||
transform: translate(-0.5px, 0.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
86% {
|
||||
transform: translate(2.5px, 1.5px) rotate(0.5deg);
|
||||
}
|
||||
|
||||
88% {
|
||||
transform: translate(-1.5px, 0.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
90% {
|
||||
transform: translate(-1.5px, -0.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
92% {
|
||||
transform: translate(-1.5px, -1.5px) rotate(1.5deg);
|
||||
}
|
||||
|
||||
94% {
|
||||
transform: translate(0.5px, 0.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
96% {
|
||||
transform: translate(2.5px, -0.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
98% {
|
||||
transform: translate(-1.5px, -1.5px) rotate(-0.5deg);
|
||||
}
|
||||
|
||||
0%, 100% {
|
||||
transform: translate(0, 0) rotate(0);
|
||||
}
|
||||
}
|
||||
@font-face {
|
||||
font-family: 'Flat-UI-Icons';
|
||||
src: url('flat-ui-icons-regular.eot');
|
||||
src: url('flat-ui-icons-regular.eot?#iefix') format('embedded-opentype'), url('flat-ui-icons-regular.woff') format('woff'), url('flat-ui-icons-regular.ttf') format('truetype'), url('flat-ui-icons-regular.svg#flat-ui-icons-regular') format('svg');
|
||||
}
|
||||
[class^="fui-"],
|
||||
[class*="fui-"] {
|
||||
font-family: 'Flat-UI-Icons';
|
||||
speak: none;
|
||||
font-style: normal;
|
||||
font-weight: normal;
|
||||
font-variant: normal;
|
||||
text-transform: none;
|
||||
-webkit-font-smoothing: antialiased;
|
||||
-moz-osx-font-smoothing: grayscale;
|
||||
}
|
||||
.fui-cross:before {
|
||||
content: "\e609";
|
||||
}
|
||||
.fui-info-circle:before {
|
||||
content: "\e60f";
|
||||
}
|
||||
.fui-photo:before {
|
||||
content: "\e62a";
|
||||
}
|
||||
.fui-eye:before {
|
||||
content: "\e62c";
|
||||
}
|
||||
.fui-chat:before {
|
||||
content: "\e62d";
|
||||
}
|
||||
.fui-home:before {
|
||||
content: "\e62e";
|
||||
}
|
||||
.fui-user:before {
|
||||
content: "\e631";
|
||||
}
|
||||
7
main.py
7
main.py
@@ -173,9 +173,6 @@ def main():
|
||||
yield from ArgsGeneralWrapper(crazy_fns[k]["Function"])(*args, **kwargs)
|
||||
click_handle = switchy_bt.click(route,[switchy_bt, *input_combo, gr.State(PORT)], output_combo)
|
||||
click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
|
||||
# def expand_file_area(file_upload, area_file_up):
|
||||
# if len(file_upload)>0: return {area_file_up: gr.update(open=True)}
|
||||
# click_handle.then(expand_file_area, [file_upload, area_file_up], [area_file_up])
|
||||
cancel_handles.append(click_handle)
|
||||
# 终止按钮的回调函数注册
|
||||
stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
|
||||
@@ -189,7 +186,9 @@ def main():
|
||||
print(f"\t(暗色主题): http://localhost:{PORT}/?__dark-theme=true")
|
||||
def open():
|
||||
time.sleep(2) # 打开浏览器
|
||||
webbrowser.open_new_tab(f"http://localhost:{PORT}/?__dark-theme=true")
|
||||
DARK_MODE, = get_conf('DARK_MODE')
|
||||
if DARK_MODE: webbrowser.open_new_tab(f"http://localhost:{PORT}/?__dark-theme=true")
|
||||
else: webbrowser.open_new_tab(f"http://localhost:{PORT}")
|
||||
threading.Thread(target=open, name="open-browser", daemon=True).start()
|
||||
threading.Thread(target=auto_update, name="self-upgrade", daemon=True).start()
|
||||
threading.Thread(target=warm_up_modules, name="warm-up", daemon=True).start()
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
|
||||
from transformers import AutoModel, AutoTokenizer
|
||||
import time
|
||||
import threading
|
||||
import importlib
|
||||
from toolbox import update_ui, get_conf
|
||||
from multiprocessing import Process, Pipe
|
||||
@@ -18,6 +19,7 @@ class GetGLMHandle(Process):
|
||||
self.success = True
|
||||
self.check_dependency()
|
||||
self.start()
|
||||
self.threadLock = threading.Lock()
|
||||
|
||||
def check_dependency(self):
|
||||
try:
|
||||
@@ -32,6 +34,7 @@ class GetGLMHandle(Process):
|
||||
return self.chatglm_model is not None
|
||||
|
||||
def run(self):
|
||||
# 子进程执行
|
||||
# 第一次运行,加载参数
|
||||
retry = 0
|
||||
while True:
|
||||
@@ -53,17 +56,25 @@ class GetGLMHandle(Process):
|
||||
self.child.send('[Local Message] Call ChatGLM fail 不能正常加载ChatGLM的参数。')
|
||||
raise RuntimeError("不能正常加载ChatGLM的参数!")
|
||||
|
||||
# 进入任务等待状态
|
||||
while True:
|
||||
# 进入任务等待状态
|
||||
kwargs = self.child.recv()
|
||||
# 收到消息,开始请求
|
||||
try:
|
||||
for response, history in self.chatglm_model.stream_chat(self.chatglm_tokenizer, **kwargs):
|
||||
self.child.send(response)
|
||||
# # 中途接收可能的终止指令(如果有的话)
|
||||
# if self.child.poll():
|
||||
# command = self.child.recv()
|
||||
# if command == '[Terminate]': break
|
||||
except:
|
||||
self.child.send('[Local Message] Call ChatGLM fail.')
|
||||
# 请求处理结束,开始下一个循环
|
||||
self.child.send('[Finish]')
|
||||
|
||||
def stream_chat(self, **kwargs):
|
||||
# 主进程执行
|
||||
self.threadLock.acquire()
|
||||
self.parent.send(kwargs)
|
||||
while True:
|
||||
res = self.parent.recv()
|
||||
@@ -71,7 +82,7 @@ class GetGLMHandle(Process):
|
||||
yield res
|
||||
else:
|
||||
break
|
||||
return
|
||||
self.threadLock.release()
|
||||
|
||||
global glm_handle
|
||||
glm_handle = None
|
||||
@@ -130,14 +141,20 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
||||
if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs) # 获取预处理函数(如果有的话)
|
||||
inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
|
||||
|
||||
# 处理历史信息
|
||||
history_feedin = []
|
||||
history_feedin.append(["What can I do?", system_prompt] )
|
||||
for i in range(len(history)//2):
|
||||
history_feedin.append([history[2*i], history[2*i+1]] )
|
||||
|
||||
# 开始接收chatglm的回复
|
||||
response = "[Local Message]: 等待ChatGLM响应中 ..."
|
||||
for response in glm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
|
||||
chatbot[-1] = (inputs, response)
|
||||
yield from update_ui(chatbot=chatbot, history=history)
|
||||
|
||||
# 总结输出
|
||||
if response == "[Local Message]: 等待ChatGLM响应中 ...":
|
||||
response = "[Local Message]: ChatGLM响应异常 ..."
|
||||
history.extend([inputs, response])
|
||||
yield from update_ui(chatbot=chatbot, history=history)
|
||||
yield from update_ui(chatbot=chatbot, history=history)
|
||||
|
||||
153
request_llm/bridge_jittorllms.py
普通文件
153
request_llm/bridge_jittorllms.py
普通文件
@@ -0,0 +1,153 @@
|
||||
|
||||
from transformers import AutoModel, AutoTokenizer
|
||||
import time
|
||||
import threading
|
||||
import importlib
|
||||
from toolbox import update_ui, get_conf
|
||||
from multiprocessing import Process, Pipe
|
||||
|
||||
load_message = "jittorllms尚未加载,加载需要一段时间。注意,取决于`config.py`的配置,jittorllms消耗大量的内存(CPU)或显存(GPU),也许会导致低配计算机卡死 ……"
|
||||
|
||||
#################################################################################
|
||||
class GetGLMHandle(Process):
|
||||
def __init__(self):
|
||||
super().__init__(daemon=True)
|
||||
self.parent, self.child = Pipe()
|
||||
self.jittorllms_model = None
|
||||
self.info = ""
|
||||
self.success = True
|
||||
self.check_dependency()
|
||||
self.start()
|
||||
self.threadLock = threading.Lock()
|
||||
|
||||
def check_dependency(self):
|
||||
try:
|
||||
import jittor
|
||||
from .jittorllms.models import get_model
|
||||
self.info = "依赖检测通过"
|
||||
self.success = True
|
||||
except:
|
||||
self.info = r"缺少jittorllms的依赖,如果要使用jittorllms,除了基础的pip依赖以外,您还需要运行`pip install -r request_llm/requirements_jittorllms.txt`"+\
|
||||
r"和`git clone https://gitlink.org.cn/jittor/JittorLLMs.git --depth 1 request_llm/jittorllms`两个指令来安装jittorllms的依赖(在项目根目录运行这两个指令)。"
|
||||
self.success = False
|
||||
|
||||
def ready(self):
|
||||
return self.jittorllms_model is not None
|
||||
|
||||
def run(self):
|
||||
# 子进程执行
|
||||
# 第一次运行,加载参数
|
||||
def load_model():
|
||||
import types
|
||||
try:
|
||||
if self.jittorllms_model is None:
|
||||
device, = get_conf('LOCAL_MODEL_DEVICE')
|
||||
from .jittorllms.models import get_model
|
||||
# availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
|
||||
args_dict = {'model': 'chatglm', 'RUN_DEVICE':'cpu'}
|
||||
self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
|
||||
except:
|
||||
self.child.send('[Local Message] Call jittorllms fail 不能正常加载jittorllms的参数。')
|
||||
raise RuntimeError("不能正常加载jittorllms的参数!")
|
||||
|
||||
load_model()
|
||||
|
||||
# 进入任务等待状态
|
||||
while True:
|
||||
# 进入任务等待状态
|
||||
kwargs = self.child.recv()
|
||||
# 收到消息,开始请求
|
||||
try:
|
||||
for response, history in self.jittorllms_model.run_web_demo(kwargs['query'], kwargs['history']):
|
||||
self.child.send(response)
|
||||
except:
|
||||
self.child.send('[Local Message] Call jittorllms fail.')
|
||||
# 请求处理结束,开始下一个循环
|
||||
self.child.send('[Finish]')
|
||||
|
||||
def stream_chat(self, **kwargs):
|
||||
# 主进程执行
|
||||
self.threadLock.acquire()
|
||||
self.parent.send(kwargs)
|
||||
while True:
|
||||
res = self.parent.recv()
|
||||
if res != '[Finish]':
|
||||
yield res
|
||||
else:
|
||||
break
|
||||
self.threadLock.release()
|
||||
|
||||
global glm_handle
|
||||
glm_handle = None
|
||||
#################################################################################
|
||||
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_llm/bridge_all.py
|
||||
"""
|
||||
global glm_handle
|
||||
if glm_handle is None:
|
||||
glm_handle = GetGLMHandle()
|
||||
if len(observe_window) >= 1: observe_window[0] = load_message + "\n\n" + glm_handle.info
|
||||
if not glm_handle.success:
|
||||
error = glm_handle.info
|
||||
glm_handle = None
|
||||
raise RuntimeError(error)
|
||||
|
||||
# jittorllms 没有 sys_prompt 接口,因此把prompt加入 history
|
||||
history_feedin = []
|
||||
history_feedin.append(["What can I do?", sys_prompt])
|
||||
for i in range(len(history)//2):
|
||||
history_feedin.append([history[2*i], history[2*i+1]] )
|
||||
|
||||
watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
|
||||
response = ""
|
||||
for response in glm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
|
||||
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_llm/bridge_all.py
|
||||
"""
|
||||
chatbot.append((inputs, ""))
|
||||
|
||||
global glm_handle
|
||||
if glm_handle is None:
|
||||
glm_handle = GetGLMHandle()
|
||||
chatbot[-1] = (inputs, load_message + "\n\n" + glm_handle.info)
|
||||
yield from update_ui(chatbot=chatbot, history=[])
|
||||
if not glm_handle.success:
|
||||
glm_handle = None
|
||||
return
|
||||
|
||||
if additional_fn is not None:
|
||||
import core_functional
|
||||
importlib.reload(core_functional) # 热更新prompt
|
||||
core_functional = core_functional.get_core_functions()
|
||||
if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs) # 获取预处理函数(如果有的话)
|
||||
inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
|
||||
|
||||
# 处理历史信息
|
||||
history_feedin = []
|
||||
history_feedin.append(["What can I do?", system_prompt] )
|
||||
for i in range(len(history)//2):
|
||||
history_feedin.append([history[2*i], history[2*i+1]] )
|
||||
|
||||
# 开始接收jittorllms的回复
|
||||
response = "[Local Message]: 等待jittorllms响应中 ..."
|
||||
for response in glm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
|
||||
chatbot[-1] = (inputs, response)
|
||||
yield from update_ui(chatbot=chatbot, history=history)
|
||||
|
||||
# 总结输出
|
||||
if response == "[Local Message]: 等待jittorllms响应中 ...":
|
||||
response = "[Local Message]: jittorllms响应异常 ..."
|
||||
history.extend([inputs, response])
|
||||
yield from update_ui(chatbot=chatbot, history=history)
|
||||
@@ -15,6 +15,7 @@ load_message = "等待NewBing响应。"
|
||||
import time
|
||||
import json
|
||||
import re
|
||||
import logging
|
||||
import asyncio
|
||||
import importlib
|
||||
import threading
|
||||
@@ -23,15 +24,15 @@ 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
|
||||
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```\n' + "\n".join([r for r in result.split('\n') if r.startswith('[')]) + '\n```\n'
|
||||
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```\n' + "\n".join([r for r in result.split('\n') if r.startswith('[')]) + '\n```\n'
|
||||
result += '\n\n```reference\n' + "\n".join([r for r in result.split('\n') if r.startswith('[')]) + '\n```\n'
|
||||
return result
|
||||
|
||||
class NewBingHandle(Process):
|
||||
@@ -88,14 +89,14 @@ class NewBingHandle(Process):
|
||||
if a not in self.local_history:
|
||||
self.local_history.append(a)
|
||||
prompt += a + '\n'
|
||||
if b not in self.local_history:
|
||||
self.local_history.append(b)
|
||||
prompt += b + '\n'
|
||||
# if b not in self.local_history:
|
||||
# self.local_history.append(b)
|
||||
# prompt += b + '\n'
|
||||
|
||||
# 问题
|
||||
prompt += question
|
||||
self.local_history.append(question)
|
||||
|
||||
print('question:', prompt)
|
||||
# 提交
|
||||
async for final, response in self.newbing_model.ask_stream(
|
||||
prompt=question,
|
||||
@@ -108,7 +109,8 @@ class NewBingHandle(Process):
|
||||
else:
|
||||
print('-------- receive final ---------')
|
||||
self.child.send('[Finish]')
|
||||
|
||||
# self.local_history.append(response)
|
||||
|
||||
|
||||
def run(self):
|
||||
"""
|
||||
@@ -239,11 +241,14 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
||||
history_feedin.append([history[2*i], history[2*i+1]] )
|
||||
|
||||
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 newbing_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。")
|
||||
|
||||
history.extend([inputs, preprocess_newbing_out(response)])
|
||||
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}')
|
||||
yield from update_ui(chatbot=chatbot, history=history, msg="完成全部响应,请提交新问题。")
|
||||
|
||||
|
||||
@@ -0,0 +1,4 @@
|
||||
jittor >= 1.3.7.9
|
||||
jtorch >= 0.1.3
|
||||
torch
|
||||
torchvision
|
||||
26
request_llm/test_llms.py
普通文件
26
request_llm/test_llms.py
普通文件
@@ -0,0 +1,26 @@
|
||||
"""
|
||||
对各个llm模型进行单元测试
|
||||
"""
|
||||
def validate_path():
|
||||
import os, sys
|
||||
dir_name = 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 request_llm.bridge_jittorllms import predict_no_ui_long_connection
|
||||
|
||||
llm_kwargs = {
|
||||
'max_length': 512,
|
||||
'top_p': 1,
|
||||
'temperature': 1,
|
||||
}
|
||||
|
||||
result = predict_no_ui_long_connection(inputs="你好",
|
||||
llm_kwargs=llm_kwargs,
|
||||
history=[],
|
||||
sys_prompt="")
|
||||
|
||||
print('result')
|
||||
265
theme.py
265
theme.py
@@ -1,6 +1,6 @@
|
||||
import gradio as gr
|
||||
from toolbox import get_conf
|
||||
CODE_HIGHLIGHT, = get_conf('CODE_HIGHLIGHT')
|
||||
CODE_HIGHLIGHT, ADD_WAIFU = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU')
|
||||
# gradio可用颜色列表
|
||||
# gr.themes.utils.colors.slate (石板色)
|
||||
# gr.themes.utils.colors.gray (灰色)
|
||||
@@ -27,6 +27,7 @@ CODE_HIGHLIGHT, = get_conf('CODE_HIGHLIGHT')
|
||||
|
||||
|
||||
def adjust_theme():
|
||||
|
||||
try:
|
||||
color_er = gr.themes.utils.colors.fuchsia
|
||||
set_theme = gr.themes.Default(
|
||||
@@ -80,6 +81,21 @@ def adjust_theme():
|
||||
button_cancel_text_color=color_er.c600,
|
||||
button_cancel_text_color_dark="white",
|
||||
)
|
||||
|
||||
# 添加一个萌萌的看板娘
|
||||
if ADD_WAIFU:
|
||||
js = """
|
||||
<script src="file=docs/waifu_plugin/jquery.min.js"></script>
|
||||
<script src="file=docs/waifu_plugin/jquery-ui.min.js"></script>
|
||||
<script src="file=docs/waifu_plugin/autoload.js"></script>
|
||||
"""
|
||||
gradio_original_template_fn = gr.routes.templates.TemplateResponse
|
||||
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.init_headers()
|
||||
return res
|
||||
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')
|
||||
@@ -137,6 +153,16 @@ advanced_css = """
|
||||
|
||||
/* 行内代码的背景设为淡灰色,设定圆角和间距. */
|
||||
.markdown-body code {
|
||||
display: inline;
|
||||
white-space: break-spaces;
|
||||
border-radius: 6px;
|
||||
margin: 0 2px 0 2px;
|
||||
padding: .2em .4em .1em .4em;
|
||||
background-color: rgba(13, 17, 23, 0.95);
|
||||
color: #c9d1d9;
|
||||
}
|
||||
|
||||
.dark .markdown-body code {
|
||||
display: inline;
|
||||
white-space: break-spaces;
|
||||
border-radius: 6px;
|
||||
@@ -144,8 +170,19 @@ advanced_css = """
|
||||
padding: .2em .4em .1em .4em;
|
||||
background-color: rgba(175,184,193,0.2);
|
||||
}
|
||||
|
||||
/* 设定代码块的样式,包括背景颜色、内、外边距、圆角。 */
|
||||
.markdown-body pre code {
|
||||
display: block;
|
||||
overflow: auto;
|
||||
white-space: pre;
|
||||
background-color: rgba(13, 17, 23, 0.95);
|
||||
border-radius: 10px;
|
||||
padding: 1em;
|
||||
margin: 1em 2em 1em 0.5em;
|
||||
}
|
||||
|
||||
.dark .markdown-body pre code {
|
||||
display: block;
|
||||
overflow: auto;
|
||||
white-space: pre;
|
||||
@@ -160,72 +197,162 @@ advanced_css = """
|
||||
if CODE_HIGHLIGHT:
|
||||
advanced_css += """
|
||||
|
||||
.hll { background-color: #ffffcc }
|
||||
.c { color: #3D7B7B; font-style: italic } /* Comment */
|
||||
.err { border: 1px solid #FF0000 } /* Error */
|
||||
.k { color: hsl(197, 94%, 51%); font-weight: bold } /* Keyword */
|
||||
.o { color: #666666 } /* Operator */
|
||||
.ch { color: #3D7B7B; font-style: italic } /* Comment.Hashbang */
|
||||
.cm { color: #3D7B7B; font-style: italic } /* Comment.Multiline */
|
||||
.cp { color: #9C6500 } /* Comment.Preproc */
|
||||
.cpf { color: #3D7B7B; font-style: italic } /* Comment.PreprocFile */
|
||||
.c1 { color: #3D7B7B; font-style: italic } /* Comment.Single */
|
||||
.cs { color: #3D7B7B; font-style: italic } /* Comment.Special */
|
||||
.gd { color: #A00000 } /* Generic.Deleted */
|
||||
.ge { font-style: italic } /* Generic.Emph */
|
||||
.gr { color: #E40000 } /* Generic.Error */
|
||||
.gh { color: #000080; font-weight: bold } /* Generic.Heading */
|
||||
.gi { color: #008400 } /* Generic.Inserted */
|
||||
.go { color: #717171 } /* Generic.Output */
|
||||
.gp { color: #000080; font-weight: bold } /* Generic.Prompt */
|
||||
.gs { font-weight: bold } /* Generic.Strong */
|
||||
.gu { color: #800080; font-weight: bold } /* Generic.Subheading */
|
||||
.gt { color: #a9dd00 } /* Generic.Traceback */
|
||||
.kc { color: #008000; font-weight: bold } /* Keyword.Constant */
|
||||
.kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
|
||||
.kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
|
||||
.kp { color: #008000 } /* Keyword.Pseudo */
|
||||
.kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
|
||||
.kt { color: #B00040 } /* Keyword.Type */
|
||||
.m { color: #666666 } /* Literal.Number */
|
||||
.s { color: #BA2121 } /* Literal.String */
|
||||
.na { color: #687822 } /* Name.Attribute */
|
||||
.nb { color: #e5f8c3 } /* Name.Builtin */
|
||||
.nc { color: #ffad65; font-weight: bold } /* Name.Class */
|
||||
.no { color: #880000 } /* Name.Constant */
|
||||
.nd { color: #AA22FF } /* Name.Decorator */
|
||||
.ni { color: #717171; font-weight: bold } /* Name.Entity */
|
||||
.ne { color: #CB3F38; font-weight: bold } /* Name.Exception */
|
||||
.nf { color: #f9f978 } /* Name.Function */
|
||||
.nl { color: #767600 } /* Name.Label */
|
||||
.nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
|
||||
.nt { color: #008000; font-weight: bold } /* Name.Tag */
|
||||
.nv { color: #19177C } /* Name.Variable */
|
||||
.ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
|
||||
.w { color: #bbbbbb } /* Text.Whitespace */
|
||||
.mb { color: #666666 } /* Literal.Number.Bin */
|
||||
.mf { color: #666666 } /* Literal.Number.Float */
|
||||
.mh { color: #666666 } /* Literal.Number.Hex */
|
||||
.mi { color: #666666 } /* Literal.Number.Integer */
|
||||
.mo { color: #666666 } /* Literal.Number.Oct */
|
||||
.sa { color: #BA2121 } /* Literal.String.Affix */
|
||||
.sb { color: #BA2121 } /* Literal.String.Backtick */
|
||||
.sc { color: #BA2121 } /* Literal.String.Char */
|
||||
.dl { color: #BA2121 } /* Literal.String.Delimiter */
|
||||
.sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
|
||||
.s2 { color: #2bf840 } /* Literal.String.Double */
|
||||
.se { color: #AA5D1F; font-weight: bold } /* Literal.String.Escape */
|
||||
.sh { color: #BA2121 } /* Literal.String.Heredoc */
|
||||
.si { color: #A45A77; font-weight: bold } /* Literal.String.Interpol */
|
||||
.sx { color: #008000 } /* Literal.String.Other */
|
||||
.sr { color: #A45A77 } /* Literal.String.Regex */
|
||||
.s1 { color: #BA2121 } /* Literal.String.Single */
|
||||
.ss { color: #19177C } /* Literal.String.Symbol */
|
||||
.bp { color: #008000 } /* Name.Builtin.Pseudo */
|
||||
.fm { color: #0000FF } /* Name.Function.Magic */
|
||||
.vc { color: #19177C } /* Name.Variable.Class */
|
||||
.vg { color: #19177C } /* Name.Variable.Global */
|
||||
.vi { color: #19177C } /* Name.Variable.Instance */
|
||||
.vm { color: #19177C } /* Name.Variable.Magic */
|
||||
.il { color: #666666 } /* Literal.Number.Integer.Long */
|
||||
.codehilite .hll { background-color: #6e7681 }
|
||||
.codehilite .c { color: #8b949e; font-style: italic } /* Comment */
|
||||
.codehilite .err { color: #f85149 } /* Error */
|
||||
.codehilite .esc { color: #c9d1d9 } /* Escape */
|
||||
.codehilite .g { color: #c9d1d9 } /* Generic */
|
||||
.codehilite .k { color: #ff7b72 } /* Keyword */
|
||||
.codehilite .l { color: #a5d6ff } /* Literal */
|
||||
.codehilite .n { color: #c9d1d9 } /* Name */
|
||||
.codehilite .o { color: #ff7b72; font-weight: bold } /* Operator */
|
||||
.codehilite .x { color: #c9d1d9 } /* Other */
|
||||
.codehilite .p { color: #c9d1d9 } /* Punctuation */
|
||||
.codehilite .ch { color: #8b949e; font-style: italic } /* Comment.Hashbang */
|
||||
.codehilite .cm { color: #8b949e; font-style: italic } /* Comment.Multiline */
|
||||
.codehilite .cp { color: #8b949e; font-weight: bold; font-style: italic } /* Comment.Preproc */
|
||||
.codehilite .cpf { color: #8b949e; font-style: italic } /* Comment.PreprocFile */
|
||||
.codehilite .c1 { color: #8b949e; font-style: italic } /* Comment.Single */
|
||||
.codehilite .cs { color: #8b949e; font-weight: bold; font-style: italic } /* Comment.Special */
|
||||
.codehilite .gd { color: #ffa198; background-color: #490202 } /* Generic.Deleted */
|
||||
.codehilite .ge { color: #c9d1d9; font-style: italic } /* Generic.Emph */
|
||||
.codehilite .gr { color: #ffa198 } /* Generic.Error */
|
||||
.codehilite .gh { color: #79c0ff; font-weight: bold } /* Generic.Heading */
|
||||
.codehilite .gi { color: #56d364; background-color: #0f5323 } /* Generic.Inserted */
|
||||
.codehilite .go { color: #8b949e } /* Generic.Output */
|
||||
.codehilite .gp { color: #8b949e } /* Generic.Prompt */
|
||||
.codehilite .gs { color: #c9d1d9; font-weight: bold } /* Generic.Strong */
|
||||
.codehilite .gu { color: #79c0ff } /* Generic.Subheading */
|
||||
.codehilite .gt { color: #ff7b72 } /* Generic.Traceback */
|
||||
.codehilite .g-Underline { color: #c9d1d9; text-decoration: underline } /* Generic.Underline */
|
||||
.codehilite .kc { color: #79c0ff } /* Keyword.Constant */
|
||||
.codehilite .kd { color: #ff7b72 } /* Keyword.Declaration */
|
||||
.codehilite .kn { color: #ff7b72 } /* Keyword.Namespace */
|
||||
.codehilite .kp { color: #79c0ff } /* Keyword.Pseudo */
|
||||
.codehilite .kr { color: #ff7b72 } /* Keyword.Reserved */
|
||||
.codehilite .kt { color: #ff7b72 } /* Keyword.Type */
|
||||
.codehilite .ld { color: #79c0ff } /* Literal.Date */
|
||||
.codehilite .m { color: #a5d6ff } /* Literal.Number */
|
||||
.codehilite .s { color: #a5d6ff } /* Literal.String */
|
||||
.codehilite .na { color: #c9d1d9 } /* Name.Attribute */
|
||||
.codehilite .nb { color: #c9d1d9 } /* Name.Builtin */
|
||||
.codehilite .nc { color: #f0883e; font-weight: bold } /* Name.Class */
|
||||
.codehilite .no { color: #79c0ff; font-weight: bold } /* Name.Constant */
|
||||
.codehilite .nd { color: #d2a8ff; font-weight: bold } /* Name.Decorator */
|
||||
.codehilite .ni { color: #ffa657 } /* Name.Entity */
|
||||
.codehilite .ne { color: #f0883e; font-weight: bold } /* Name.Exception */
|
||||
.codehilite .nf { color: #d2a8ff; font-weight: bold } /* Name.Function */
|
||||
.codehilite .nl { color: #79c0ff; font-weight: bold } /* Name.Label */
|
||||
.codehilite .nn { color: #ff7b72 } /* Name.Namespace */
|
||||
.codehilite .nx { color: #c9d1d9 } /* Name.Other */
|
||||
.codehilite .py { color: #79c0ff } /* Name.Property */
|
||||
.codehilite .nt { color: #7ee787 } /* Name.Tag */
|
||||
.codehilite .nv { color: #79c0ff } /* Name.Variable */
|
||||
.codehilite .ow { color: #ff7b72; font-weight: bold } /* Operator.Word */
|
||||
.codehilite .pm { color: #c9d1d9 } /* Punctuation.Marker */
|
||||
.codehilite .w { color: #6e7681 } /* Text.Whitespace */
|
||||
.codehilite .mb { color: #a5d6ff } /* Literal.Number.Bin */
|
||||
.codehilite .mf { color: #a5d6ff } /* Literal.Number.Float */
|
||||
.codehilite .mh { color: #a5d6ff } /* Literal.Number.Hex */
|
||||
.codehilite .mi { color: #a5d6ff } /* Literal.Number.Integer */
|
||||
.codehilite .mo { color: #a5d6ff } /* Literal.Number.Oct */
|
||||
.codehilite .sa { color: #79c0ff } /* Literal.String.Affix */
|
||||
.codehilite .sb { color: #a5d6ff } /* Literal.String.Backtick */
|
||||
.codehilite .sc { color: #a5d6ff } /* Literal.String.Char */
|
||||
.codehilite .dl { color: #79c0ff } /* Literal.String.Delimiter */
|
||||
.codehilite .sd { color: #a5d6ff } /* Literal.String.Doc */
|
||||
.codehilite .s2 { color: #a5d6ff } /* Literal.String.Double */
|
||||
.codehilite .se { color: #79c0ff } /* Literal.String.Escape */
|
||||
.codehilite .sh { color: #79c0ff } /* Literal.String.Heredoc */
|
||||
.codehilite .si { color: #a5d6ff } /* Literal.String.Interpol */
|
||||
.codehilite .sx { color: #a5d6ff } /* Literal.String.Other */
|
||||
.codehilite .sr { color: #79c0ff } /* Literal.String.Regex */
|
||||
.codehilite .s1 { color: #a5d6ff } /* Literal.String.Single */
|
||||
.codehilite .ss { color: #a5d6ff } /* Literal.String.Symbol */
|
||||
.codehilite .bp { color: #c9d1d9 } /* Name.Builtin.Pseudo */
|
||||
.codehilite .fm { color: #d2a8ff; font-weight: bold } /* Name.Function.Magic */
|
||||
.codehilite .vc { color: #79c0ff } /* Name.Variable.Class */
|
||||
.codehilite .vg { color: #79c0ff } /* Name.Variable.Global */
|
||||
.codehilite .vi { color: #79c0ff } /* Name.Variable.Instance */
|
||||
.codehilite .vm { color: #79c0ff } /* Name.Variable.Magic */
|
||||
.codehilite .il { color: #a5d6ff } /* Literal.Number.Integer.Long */
|
||||
|
||||
.dark .codehilite .hll { background-color: #2C3B41 }
|
||||
.dark .codehilite .c { color: #79d618; font-style: italic } /* Comment */
|
||||
.dark .codehilite .err { color: #FF5370 } /* Error */
|
||||
.dark .codehilite .esc { color: #89DDFF } /* Escape */
|
||||
.dark .codehilite .g { color: #EEFFFF } /* Generic */
|
||||
.dark .codehilite .k { color: #BB80B3 } /* Keyword */
|
||||
.dark .codehilite .l { color: #C3E88D } /* Literal */
|
||||
.dark .codehilite .n { color: #EEFFFF } /* Name */
|
||||
.dark .codehilite .o { color: #89DDFF } /* Operator */
|
||||
.dark .codehilite .p { color: #89DDFF } /* Punctuation */
|
||||
.dark .codehilite .ch { color: #79d618; font-style: italic } /* Comment.Hashbang */
|
||||
.dark .codehilite .cm { color: #79d618; font-style: italic } /* Comment.Multiline */
|
||||
.dark .codehilite .cp { color: #79d618; font-style: italic } /* Comment.Preproc */
|
||||
.dark .codehilite .cpf { color: #79d618; font-style: italic } /* Comment.PreprocFile */
|
||||
.dark .codehilite .c1 { color: #79d618; font-style: italic } /* Comment.Single */
|
||||
.dark .codehilite .cs { color: #79d618; font-style: italic } /* Comment.Special */
|
||||
.dark .codehilite .gd { color: #FF5370 } /* Generic.Deleted */
|
||||
.dark .codehilite .ge { color: #89DDFF } /* Generic.Emph */
|
||||
.dark .codehilite .gr { color: #FF5370 } /* Generic.Error */
|
||||
.dark .codehilite .gh { color: #C3E88D } /* Generic.Heading */
|
||||
.dark .codehilite .gi { color: #C3E88D } /* Generic.Inserted */
|
||||
.dark .codehilite .go { color: #79d618 } /* Generic.Output */
|
||||
.dark .codehilite .gp { color: #FFCB6B } /* Generic.Prompt */
|
||||
.dark .codehilite .gs { color: #FF5370 } /* Generic.Strong */
|
||||
.dark .codehilite .gu { color: #89DDFF } /* Generic.Subheading */
|
||||
.dark .codehilite .gt { color: #FF5370 } /* Generic.Traceback */
|
||||
.dark .codehilite .kc { color: #89DDFF } /* Keyword.Constant */
|
||||
.dark .codehilite .kd { color: #BB80B3 } /* Keyword.Declaration */
|
||||
.dark .codehilite .kn { color: #89DDFF; font-style: italic } /* Keyword.Namespace */
|
||||
.dark .codehilite .kp { color: #89DDFF } /* Keyword.Pseudo */
|
||||
.dark .codehilite .kr { color: #BB80B3 } /* Keyword.Reserved */
|
||||
.dark .codehilite .kt { color: #BB80B3 } /* Keyword.Type */
|
||||
.dark .codehilite .ld { color: #C3E88D } /* Literal.Date */
|
||||
.dark .codehilite .m { color: #F78C6C } /* Literal.Number */
|
||||
.dark .codehilite .s { color: #C3E88D } /* Literal.String */
|
||||
.dark .codehilite .na { color: #BB80B3 } /* Name.Attribute */
|
||||
.dark .codehilite .nb { color: #82AAFF } /* Name.Builtin */
|
||||
.dark .codehilite .nc { color: #FFCB6B } /* Name.Class */
|
||||
.dark .codehilite .no { color: #EEFFFF } /* Name.Constant */
|
||||
.dark .codehilite .nd { color: #82AAFF } /* Name.Decorator */
|
||||
.dark .codehilite .ni { color: #89DDFF } /* Name.Entity */
|
||||
.dark .codehilite .ne { color: #FFCB6B } /* Name.Exception */
|
||||
.dark .codehilite .nf { color: #82AAFF } /* Name.Function */
|
||||
.dark .codehilite .nl { color: #82AAFF } /* Name.Label */
|
||||
.dark .codehilite .nn { color: #FFCB6B } /* Name.Namespace */
|
||||
.dark .codehilite .nx { color: #EEFFFF } /* Name.Other */
|
||||
.dark .codehilite .py { color: #FFCB6B } /* Name.Property */
|
||||
.dark .codehilite .nt { color: #FF5370 } /* Name.Tag */
|
||||
.dark .codehilite .nv { color: #89DDFF } /* Name.Variable */
|
||||
.dark .codehilite .ow { color: #89DDFF; font-style: italic } /* Operator.Word */
|
||||
.dark .codehilite .pm { color: #89DDFF } /* Punctuation.Marker */
|
||||
.dark .codehilite .w { color: #EEFFFF } /* Text.Whitespace */
|
||||
.dark .codehilite .mb { color: #F78C6C } /* Literal.Number.Bin */
|
||||
.dark .codehilite .mf { color: #F78C6C } /* Literal.Number.Float */
|
||||
.dark .codehilite .mh { color: #F78C6C } /* Literal.Number.Hex */
|
||||
.dark .codehilite .mi { color: #F78C6C } /* Literal.Number.Integer */
|
||||
.dark .codehilite .mo { color: #F78C6C } /* Literal.Number.Oct */
|
||||
.dark .codehilite .sa { color: #BB80B3 } /* Literal.String.Affix */
|
||||
.dark .codehilite .sb { color: #C3E88D } /* Literal.String.Backtick */
|
||||
.dark .codehilite .sc { color: #C3E88D } /* Literal.String.Char */
|
||||
.dark .codehilite .dl { color: #EEFFFF } /* Literal.String.Delimiter */
|
||||
.dark .codehilite .sd { color: #79d618; font-style: italic } /* Literal.String.Doc */
|
||||
.dark .codehilite .s2 { color: #C3E88D } /* Literal.String.Double */
|
||||
.dark .codehilite .se { color: #EEFFFF } /* Literal.String.Escape */
|
||||
.dark .codehilite .sh { color: #C3E88D } /* Literal.String.Heredoc */
|
||||
.dark .codehilite .si { color: #89DDFF } /* Literal.String.Interpol */
|
||||
.dark .codehilite .sx { color: #C3E88D } /* Literal.String.Other */
|
||||
.dark .codehilite .sr { color: #89DDFF } /* Literal.String.Regex */
|
||||
.dark .codehilite .s1 { color: #C3E88D } /* Literal.String.Single */
|
||||
.dark .codehilite .ss { color: #89DDFF } /* Literal.String.Symbol */
|
||||
.dark .codehilite .bp { color: #89DDFF } /* Name.Builtin.Pseudo */
|
||||
.dark .codehilite .fm { color: #82AAFF } /* Name.Function.Magic */
|
||||
.dark .codehilite .vc { color: #89DDFF } /* Name.Variable.Class */
|
||||
.dark .codehilite .vg { color: #89DDFF } /* Name.Variable.Global */
|
||||
.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 */
|
||||
|
||||
"""
|
||||
|
||||
88
toolbox.py
88
toolbox.py
@@ -3,6 +3,7 @@ import importlib
|
||||
import traceback
|
||||
import inspect
|
||||
import re
|
||||
import os
|
||||
from latex2mathml.converter import convert as tex2mathml
|
||||
from functools import wraps, lru_cache
|
||||
|
||||
@@ -90,8 +91,9 @@ def CatchException(f):
|
||||
from toolbox import get_conf
|
||||
proxies, = get_conf('proxies')
|
||||
tb_str = '```\n' + trimmed_format_exc() + '```'
|
||||
if chatbot is None or len(chatbot) == 0:
|
||||
chatbot = [["插件调度异常", "异常原因"]]
|
||||
if len(chatbot) == 0:
|
||||
chatbot.clear()
|
||||
chatbot.append(["插件调度异常", "异常原因"])
|
||||
chatbot[-1] = (chatbot[-1][0],
|
||||
f"[Local Message] 实验性函数调用出错: \n\n{tb_str} \n\n当前代理可用性: \n\n{check_proxy(proxies)}")
|
||||
yield from update_ui(chatbot=chatbot, history=history, msg=f'异常 {e}') # 刷新界面
|
||||
@@ -216,13 +218,17 @@ def text_divide_paragraph(text):
|
||||
text = "</br>".join(lines)
|
||||
return text
|
||||
|
||||
|
||||
@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
|
||||
|
||||
markdown_extension_configs = {
|
||||
'mdx_math': {
|
||||
'enable_dollar_delimiter': True,
|
||||
@@ -266,8 +272,14 @@ def markdown_convertion(txt):
|
||||
content = content.replace('</script>\n</script>', '</script>')
|
||||
return content
|
||||
|
||||
def no_code(txt):
|
||||
if '```' not in txt:
|
||||
return True
|
||||
else:
|
||||
if '```reference' in txt: return True # newbing
|
||||
else: return False
|
||||
|
||||
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 ('$' in txt) and no_code(txt): # 有$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)
|
||||
@@ -454,8 +466,9 @@ def on_report_generated(files, chatbot):
|
||||
return report_files, chatbot
|
||||
|
||||
def is_openai_api_key(key):
|
||||
API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", key)
|
||||
return bool(API_MATCH)
|
||||
API_MATCH_ORIGINAL = re.match(r"sk-[a-zA-Z0-9]{48}$", key)
|
||||
API_MATCH_AZURE = re.match(r"[a-zA-Z0-9]{32}$", key)
|
||||
return bool(API_MATCH_ORIGINAL) or bool(API_MATCH_AZURE)
|
||||
|
||||
def is_api2d_key(key):
|
||||
if key.startswith('fk') and len(key) == 41:
|
||||
@@ -505,13 +518,72 @@ def select_api_key(keys, llm_model):
|
||||
api_key = random.choice(avail_key_list) # 随机负载均衡
|
||||
return api_key
|
||||
|
||||
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")]
|
||||
"""
|
||||
from colorful import print亮红, print亮绿
|
||||
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):
|
||||
r = bool(env_arg)
|
||||
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 colorful import print亮红, print亮绿, print亮蓝
|
||||
try:
|
||||
r = getattr(importlib.import_module('config_private'), arg)
|
||||
# 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:
|
||||
r = getattr(importlib.import_module('config'), arg)
|
||||
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_KEY':
|
||||
print亮蓝(f"[API_KEY] 本项目现已支持OpenAI和API2D的api-key。也支持同时填写多个api-key,如API_KEY=\"openai-key1,openai-key2,api2d-key3\"")
|
||||
|
||||
4
version
4
version
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"version": 3.3,
|
||||
"version": 3.32,
|
||||
"show_feature": true,
|
||||
"new_feature": "支持NewBing !! <-> 保存对话功能 <-> 解读任意语言代码+同时询问任意的LLM组合 <-> 添加联网(Google)回答问题插件 <-> 修复ChatGLM上下文BUG <-> 添加支持清华ChatGLM和GPT-4 <-> 改进架构,支持与多个LLM模型同时对话 <-> 添加支持API2D(国内,可支持gpt4)"
|
||||
"new_feature": "完善对话历史的保存/载入/删除 <-> 我们发现了自动更新模块的BUG,此次更新可能需要您手动到Github下载新版程序并覆盖 <-> ChatGLM加线程锁提高并发稳定性 <-> 支持NewBing <-> Markdown翻译功能支持直接输入Readme文件网址 <-> 保存对话功能 <-> 解读任意语言代码+同时询问任意的LLM组合 <-> 添加联网(Google)回答问题插件 <-> 修复ChatGLM上下文BUG <-> 添加支持清华ChatGLM"
|
||||
}
|
||||
|
||||
在新工单中引用
屏蔽一个用户